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2024 Alzheimer's disease facts and figures

PMID: 38689398
PMCID: PMC11095490
DOI: 10.1002/alz.13809

This article describes the public health impact of Alzheimer's disease (AD), including prevalence and incidence, mortality and morbidity, use and costs of care and the ramifications of AD for family caregivers, the dementia workforce and society. The Special Report discusses the larger health care system for older adults with cognitive issues, focusing on the role of caregivers and non-physician health care professionals. An estimated 6.9 million Americans age 65 and older are living with Alzheimer's dementia today. This number could grow to 13.8 million by 2060, barring the development of medical breakthroughs to prevent or cure AD. Official AD death certificates recorded 119,399 deaths from AD in 2021. In 2020 and 2021, when COVID-19 entered the ranks of the top ten causes of death, Alzheimer's was the seventh-leading cause of death in the United States. Official counts for more recent years are still being compiled. Alzheimer's remains the fifth-leading cause of death among Americans age 65 and older. Between 2000 and 2021, deaths from stroke, heart disease and HIV decreased, whereas reported deaths from AD increased more than 140%. More than 11 million family members and other unpaid caregivers provided an estimated 18.4 billion hours of care to people with Alzheimer's or other dementias in 2023. These figures reflect a decline in the number of caregivers compared with a decade earlier, as well as an increase in the amount of care provided by each remaining caregiver. Unpaid dementia caregiving was valued at $346.6 billion in 2023. Its costs, however, extend to unpaid caregivers' increased risk for emotional distress and negative mental and physical health outcomes. Members of the paid health care and broader community-based workforce are involved in diagnosing, treating and caring for people with dementia. However, the United States faces growing shortages across different segments of the dementia care workforce due to a combination of factors, including the absolute increase in the number of people living with dementia. Therefore, targeted programs and care delivery models will be needed to attract, better train and effectively deploy health care and community-based workers to provide dementia care. Average per-person Medicare payments for services to beneficiaries age 65 and older with AD or other dementias are almost three times as great as payments for beneficiaries without these conditions, and Medicaid payments are more than 22 times as great. Total payments in 2024 for health care, long-term care and hospice services for people age 65 and older with dementia are estimated to be $360 billion. The Special Report investigates how caregivers of older adults with cognitive issues interact with the health care system and examines the role non-physician health care professionals play in facilitating clinical care and access to community-based services and supports. It includes surveys of caregivers and health care workers, focusing on their experiences, challenges, awareness and perceptions of dementia care navigation.

Keywords: Alzheimer's dementia; Alzheimer's disease; Biomarkers; COVID‐19; Care navigation; Care navigator; Caregivers; Dementia; Dementia care navigation; Dementia workforce; Diagnostic criteria; Family caregiver; Health care costs; Health care expenditures; Health care professional; Health care utilization; Home and community‐based services; Incidence; Long‐term care costs; Long‐term care utilization; MCI due to Alzheimer's disease; Medicaid spending; Medicare spending; Mild cognitive impairment; Morbidity; Mortality; Navigator; Prevalence; Primary care physician; Risk factors.

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Alzheimer's disease (AD) continuum. Although…

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Seven recent papers amplify advances in Alzheimer’s research

Alzheimer's Disease Biomarkers Dementias Neuroscience

abstract graphic of a brain above a hand

AMP AD uses an open-science research model that makes all data and methods rapidly available to the research community at large through the data sharing infrastructure, the AD Knowledge Portal. Since the Portal’s launch in 2015, more than 3,000 researchers world wide from the academic, biotech, and pharmaceutical industry sectors have used the data resources for research on Alzheimer’s and related dementias.

Alzheimer’s is a complex disease, and as it slowly develops, many normal biological processes in the brain and the body go awry, from inflammation, to blood vessels damage and neuronal death. Seven recent AMP AD reports showcase research advances related to the discovery of new drug candidate targets, identification of molecular subtypes of the disease, and new potential biomarkers that can serve as the basis for a precision medicine approach to therapy development.

Identifying ATP6VA1 gene as a candidate target for treatment: Researchers at the Icahn School of Medicine at Mount Sinai in New York generated several types of molecular data from 364 brain donors at different stages of Alzheimer’s. Using network modeling, a way to show data and its relationships, the team identified large sets of genes associated with the disease. Among the thousands of molecular changes associated with Alzheimer’s, the expression of a set of neuronal genes (neuronal network) was the most disrupted. Their analyses identified ATP6VA1 as a master regulator gene of this neuronal network and demonstrated that increasing its expression genetically, or by using a pharmacologic agent, led to improving neuronal function in cultured cells and in flies. These findings were published in Neuron and pave the way for new drug discovery efforts targeting ATP6VA1 .

Finding and validating VGF gene as key regulator of Alzheimer’s: Another AMP AD study led by researchers at Icahn School of Medicine identified the VGF gene and protein as having a key role in protecting the brain against Alzheimer’s. This discovery was made possible by combining computational analyses that integrate large human Alzheimer’s molecular datasets, clinical features of Alzheimer’s, DNA variation, and data on gene- and protein expression with experimental studies in mouse models. The findings provide a new target for researchers seeking to develop drugs to treat or prevent Alzheimer’s. The report of the discovery of this gene as a key driver and its validation in mouse studies was published in Nature Communications .

Identifying different types of microglia associated with Alzheimer’s: An AMP AD research team at Columbia University conducted a study that measured the expression of genes in individual microglial cells purified from human brain samples obtained at autopsy and during neurosurgical procedures. This single cell profiling technology identified several molecular subtypes of microglia based on the pattern of gene expression. Follow-up validation studies in post mortem brain tissue showed that this microglia subtype was less abundant in Alzheimer's brains compared to control brains. These results, published in Nature Communications , will help design larger, more specific studies of the role of microglia subtypes in Alzheimer’s.

Using data to unfold and predict disease process: An AMP AD team led by researchers at Sage Bionetworks in Seattle used innovative computational approaches to make predictions about the sequence of molecular changes that lead to Alzheimer’s. The team used RNA sequencing data collected from a large collection of post-mortem tissue from Alzheimer’s and control brains. This modeling method, called the manifold learning method, predicted early-stage disease processes, such as RNA-splicing, mitochondrial function, and protein transport. Additionally, the method predicted several distinct molecular subtypes of late-onset Alzheimer’s. These predictions speak to the complex nature of the disease and the need to verify these observations in longitudinal studies where molecular signatures can be linked to different clinical features of the disease. These findings were published in Nature Communications .

Network modeling identifies molecular subtypes of Alzheimer’s: Using a large collection of human brain samples from different studies, a team led by researchers at Icahn School of Medicine also analyzed RNA sequencing data and identified three major molecular subtypes of Alzheimer’s. The subtypes, which are independent of age and disease stage, and are replicated across multiple brain regions, show how different combinations of biological pathways lead to brain degeneration. With further research and validation in larger groups, these molecular subtypes may help reveal how Alzheimer’s progresses and potential ways to slow or stop it. Their findings were published in Science Advances .

Identifying new biomarkers in spinal fluid: AMP AD researchers at Emory University identified groups of proteins (protein panels) associated with Alzheimer’s that could be identified in both brain and spinal fluid. These overlapping protein panels detected in the spinal fluid reflected changes in multiple biological process in the brain. The researchers found this by measuring 3,500 proteins in spinal fluid, and 12,000 proteins in a collection of postmortem brain samples, from patients with Alzheimer’s and cognitively normal study participants. The study also showed that these changes in the protein expression pattern were specific for Alzheimer’s. This work lays the foundation for the discovery of new fluid biomarkers for Alzheimer’s. These findings were published in Science Advances .

Investigating how being female may increase risk of Alzheimer’s: Duke University researchers and members of the Alzheimer’s Disease Metabolomic Consortium (ADMC) participating in the AMP AD program, analyzed the changes in the levels of 180 metabolites in the blood from more than 1,500 people who took part in the NIA-supported Alzheimer’s Disease Neuroimaging Initiative . The researchers reported that there are differences in a subset of blood metabolites associated with Alzheimer's based on sex and ApoE4 status. ApoE4 is the strongest Alzheimer's risk factor gene. Women with Alzheimer’s who carry the ApoE4 gene have a distinct metabolic pattern in blood. These metabolic changes suggest that females have a greater impairment of brain energy production than males. Dissecting metabolic differences in Alzheimer’s can identify specific pathways within specific patient subgroups and guide the way to personalized medicine.

The data and methods from the above studies are available and can be accessed by researchers across the world through the AD Knowledge Portal . The portal is the data repository for the AMP AD Target Discovery Program, and other NIA-supported team-science programs operating under open-science principles. Now in its sixth year, AMP AD is demonstrating the power of open science to enable the scientific community to investigate difficult scientific questions and jumpstart new drug discovery projects.

The AMP AD research teams are funded by NIA grants U01AG046152, U01AG046170, U01AG046139, U01AG046161, R01AG046171, R01AG046174, U19AG010483, U01AG042791, U01AG061357, U01AG061359, U01AG061835, and U24AG061340.

The studies outlined here were also supported by the following NIA grants (in order of appearance):

ATP6VA1: NIA grants U01AG046170, RF1AG054014, RF1AG057440, R01AG057907, U01AG052411, R01AG062355, U01AG058635, and R01AG068030
VGF: NIA grants U01AG046170, R01AG046170, RF1AG054014, RF1AG057440, R01AG057907, R01AG055501, U01AG046161, P50AG025688, 5R01AG053960, and 5R01AG062355
Microglia: NIA grants U01AG046152, R01AG036836, R01AG048015, and RF1AG057473
Disease process: NIA grants U54AG054345, RF1AG057443, P30AG10161, R01AG15819, R01AG17917, R01AG30146, R01AG36836, U01AG32984, U01AG46152, P50AG016574, R01AG032990, U01AG046139, R01AG018023, U01AG006576, U01AG006786, R01 AG025711, R01AG017216, and R01AG003949
Subtypes: U01AG046170, RF1AG054014, RF1AG057440, R01AG057907, U01AG052411, R01AG062355, U01AG058635, R01AG068030, P30AG10161, R01AG15819, R01AG17917, R01AG30146, R01AG36836, U01AG32984, U01AG46152, U01AG52411, K01AG062683, and U01AG058635
Spinal fluid biomarkers: NIA grants R01AG053960, R01AG057911, R01AG061800, RF1AG057471, RF1AG057470, R01AG061800, R01AG057911, R01AG057339, U01AG046161, and U01AG061357
Female risk: NIA grants U01AG024904, P30AG10161, R01AG15819, R01AG17917, U01AG46152, U01AG61356, R01AG059093, R01AG046171, RF1AG051550, and U01AG024904, RF1AG058942, R01AG057452, R03AG054936, and RF1AG061872

These AMP AD activities relate to NIH’s AD+ADRD Research Implementation Milestone 2.A , “Create new research programs that use data-driven, systems-based approaches to integrate the study of fundamental biology of aging with neurobiology of aging and research on neurodegeneration, AD and AD-related dementias to better understand the mechanism(s) of vulnerability and resilience in AD across all levels of biologic complexity (from cellular to population level) and to gain a deeper understanding of the complex biology and integrative physiology of healthy and pathologic brain aging;” Milestone 9.B , "Accelerate the development of the next generation CNS imaging ligands and biofluid molecular signatures targeting a variety of disease processes (neuroinflammation, bioenergetic/metabolic compromise, oxidative stress, synaptic pathology) that can be used as research tools or developed into diagnostic, prognostic, theragnostic or target engagement biomarkers;" and Milestone 9.F , “Initiate studies to develop minimally invasive biomarkers for detection of cerebral amyloidosis, AD and AD-related dementias pathophysiology.”

References:

Wang M, et al. Transformative network modeling of multi-omics data reveals detailed circuits, key regulators, and potential therapeutics for Alzheimer's disease . Neuron . 2021;109(2):257-272.e14. doi:10.1016/j.neuron.2020.11.002.

Beckmann ND, et al. Multiscale causal networks identify VGF as a key regulator of Alzheimer's disease . Nature Communications. 2020;11(1): 3942. doi:10.1038/s41467-020-17405-z.

Olah M, et al. Single cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer's disease . Nature Communications . 2020;11(1):6129. doi:10.1038/s41467-020-19737-2.

Mukherjee S, et al. Molecular estimation of neurodegeneration pseudotime in older brains . Nature Communications . 2020;11(1):5781. doi:10.1038/s41467-020-19622-y.

Neff RA, et al. Molecular subtyping of Alzheimer’s disease using RNA sequencing data reveals novel mechanisms and targets . Science Advances . 2021;7(2):eabb5398. doi: 10.1126/sciadv.abb5398.

Higginbotham L, et al. Integrated proteomics reveals brain-based cerebrospinal fluid biomarkers in asymptomatic and symptomatic Alzheimer's disease . Science Advances . 2020;6(43):eaaz9360. doi:10.1126/sciadv.aaz9360.

Arnold M, et al. Sex and APOE ε4 genotype modify the Alzheimer's disease serum metabolome . Nature Communications . 2020;11(1): 1148. doi:10.1038/s41467-020-14959-w.

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Published: 13 May 2021

Alzheimer disease

David S. Knopman ORCID: orcid.org/0000-0002-6544-066X 1 ,
Helene Amieva 2 ,
Ronald C. Petersen 1 ,
Gäel Chételat 3 ,
David M. Holtzman 4 ,
Bradley T. Hyman ORCID: orcid.org/0000-0002-7959-9401 5 ,
Ralph A. Nixon 6 , 7 &
David T. Jones ORCID: orcid.org/0000-0002-4807-9833 1

Nature Reviews Disease Primers volume 7 , Article number: 33 ( 2021 ) Cite this article

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Alzheimer's disease
Diagnostic markers
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Alzheimer disease (AD) is biologically defined by the presence of β-amyloid-containing plaques and tau-containing neurofibrillary tangles. AD is a genetic and sporadic neurodegenerative disease that causes an amnestic cognitive impairment in its prototypical presentation and non-amnestic cognitive impairment in its less common variants. AD is a common cause of cognitive impairment acquired in midlife and late-life but its clinical impact is modified by other neurodegenerative and cerebrovascular conditions. This Primer conceives of AD biology as the brain disorder that results from a complex interplay of loss of synaptic homeostasis and dysfunction in the highly interrelated endosomal/lysosomal clearance pathways in which the precursors, aggregated species and post-translationally modified products of Aβ and tau play important roles. Therapeutic endeavours are still struggling to find targets within this framework that substantially change the clinical course in persons with AD.

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Is Alzheimer disease a disease?

The Amyloid-β Pathway in Alzheimer’s Disease

Emerging diagnostics and therapeutics for Alzheimer disease

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Acknowledgements

The authors acknowledge research support from NIH (D.S.K. and R.C.P, P30 AG062677 and U01 AG006786; B.T.H., P30AG062421; R.A.N. P01 AG017617 and R01 AG062376).

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David S. Knopman, Ronald C. Petersen & David T. Jones

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Gäel Chételat

Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA

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Bradley T. Hyman

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Introduction (D.S.K.); Epidemiology (H.A.); Mechanisms/pathophysiology (D.T.J., R.A.N., B.T.H. and D.M.H.); Diagnosis, screening and prevention (G.C., R.C.P. and D.S.K.); Management (R.C.P. and D.S.K.); Quality of life (D.S.K.); Outlook (D.S.K.); Overview of Primer (D.S.K.).

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Correspondence to David S. Knopman .

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Competing interests.

D.S.K. served on a Data Safety Monitoring Board for the DIAN study. He serves on a Data Safety Monitoring Board for a tau therapeutic for Biogen but receives no personal compensation. He is a site investigator in a Biogen aducanumab trial. He is an investigator in a clinical trial sponsored by Lilly Pharmaceuticals and the University of Southern California. He serves as a consultant for Samus Therapeutics, Third Rock, Roche and Alzeca Biosciences but receives no personal compensation. He receives research support from the NIH. G.C. serves on the Scientific Advisory Board of the Fondation Vaincre Alzheimer but receives no personal compensation. She receives personal fees from Fondation d’entreprise MMA des Entrepreneurs du Futur and from Fondation Alzheimer as she serves in the Operational Committee. She receives research support from European Union Horizon 2020 research and innovation programme (grant agreement number 667696), Inserm, Fondation d’entreprise MMA des Entrepreneurs du Futur, Fondation Alzheimer, Programme Hospitalier de Recherche Clinique, Région Normandie, Association France Alzheimer et maladies apparentées and Fondation Vaincre Alzheimer. R.C.P. is a consultant for Biogen, Inc., Roche, Inc., Merck, Inc., Genentech Inc. and Eisai, Inc., has given educational lectures for GE Healthcare, receives publishing royalties from Mild Cognitive Impairment (Oxford University Press, 2003), UpToDate, and receives research support from the NIH. B.T.H. has a family member who works at Novartis and owns stock in Novartis; he serves on the SAB of Dewpoint and owns stock. He serves on a scientific advisory board or is a consultant for Biogen, Novartis, Cell Signalling, the US Dept of Justice, Takeda, Vigil, W20 group and Seer. His laboratory is supported by sponsored research agreements with Abbvie, F Prim, and research grants from the National Institutes of Health, Cure Alzheimer’s Fund, Tau Consortium, Brightfocus and the JPB Foundation. H.A. serves on the Scientific Advisory Board of the Observatoire des Mémoires but receives no personal compensation. She receives research support from Spoelberch Foundation, Association France Alzheimer et maladies apparentées, the Regional Health Agency of Aquitaine and National Research Agency. D.M.H. reports being a Co-founder for C2N Diagnostics LLC and participating in scientific advisory boards/consulting for Genentech, C2N Diagnostics, Denali, Merck and Idorsia. He is an inventor on patents licensed by Washington University to C2N Diagnostics on the therapeutic use of anti-tau antibodies (this anti-tau antibody programme is licensed to Abbvie) and to Eli Lilly on the therapeutic use of an anti-amyloid-β antibody. His laboratory receives research grants from the National Institutes of Health, Cure Alzheimer’s Fund, Tau Consortium, the JPB Foundation, Good Ventures, Centene, BrightFocus and C2N Diagnostics. All other authors declare no competing interests.

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Knopman, D.S., Amieva, H., Petersen, R.C. et al. Alzheimer disease. Nat Rev Dis Primers 7 , 33 (2021). https://doi.org/10.1038/s41572-021-00269-y

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Rabarison, K. M., Bouldin, E. D. , Bish, C. L., McGuire, L. C. , Taylor, C. A. , & Greenlund, K. J. (2018). The Economic Value of Informal Caregiving for Persons With Dementia: Results From 38 States, the District of Columbia, and Puerto Rico, 2015 and 2016 BRFSS. American Journal of Public Health , 108(10), 1370-1377. http://dx.doi.org/10.2105/ajph.2018.304573

Taylor, C. A. , Bouldin, E. D. , & McGuire, L. C. (2018). Subjective Cognitive Decline Among Adults Aged ≥45 Years — United States, 2015–2016. MMWR. Morbidity and Mortality Weekly Report , 67(27), 753-757. http://dx.doi.org/10.15585/mmwr.mm6727a1

Bouldin, E. , Trivedi, R., Reiber, G., Rosland, A., Silverman, J., Krieger, J., & Nelson, K. (2017). Associations between having an informal caregiver, social support, and self-care among low-income adults with poorly controlled diabetes. Chronic Illness , 13(4), 239-250. http://dx.doi.org/10.1177/1742395317690032

Bouldin, E. , Wong, E., Liu, C., Littman, A., Taylor, L., Rice, K., & Reiber, G. (2017). Chronic wound care utilization among Veterans using VHA and Medicare. Wound Medicine , 17, 1-6. http://dx.doi.org/10.1016/j.wndm.2017.01.003

Bouldin ED , Shaull L, Andresen EM, Edwards VJ , McGuire LC . Financial and Health Barriers and Caregiving-Related Difficulties Among Rural and Urban Caregivers. J Rural Health . 2017 Sep 23. http://dx.doi.org/10.1111/jrh.12273 .

Cancelliere C, Coronado VG, Taylor CA , Xu L (2017). Epidemiology of Isolated vs. Non-Isolated Mild Traumatic Brain Injury Treated in Emergency Departments in the United States, 2006–2012: Sociodemographic Characteristics. J Head Trauma Rehabil , 32(4):E37–E46 [ http://dx.doi.org/10.1097/HTR.0000000000000260 ].

Edwards VJ , Anderson LA , Thompson WW, Deokar AJ . Mental health differences between men and women caregivers, BRFSS 2009. J Women Aging . 2017;29(5):385-391. http://dx.doi.org/10.1080/08952841.2016.1223916 .

Eisenberg, Y., Bouldin, E . D., Gell, N., & Rosenberg, D. (2017). Planning Walking Environments for People with Disabilities and Older Adults. In Walking: Connecting Sustainable Transport with Health (pp. 187-209). Emerald Publishing Limited.

Haarbauer-Krupa J, Taylor CA , Yue JK, Winkler EA, Pirracchio R, Cooper SR, Burke JF, Stein MB, Manley GT, The TRACK-TBI Investigators (2017). Screening for Post-Traumatic Stress Disorder in a Civilian Emergency Department Population with Traumatic Brain Injury. J Neurotrauma , 34(1): 50–58 [ http://dx.doi.org/10.1089/neu.2015.4158 ].

Littman AJ, Bouldin ED , Haselkorn JK. This is your new normal: A qualitative study of barriers and facilitators to physical activity in Veterans with lower extremity loss. Disabil Health J . 2017 Oct;10(4):600-606. http://dx.doi.org/10.1016/j.dhjo.2017.03.004 .

Lock, S. L., Baumgart, M., Whiting, C. G., McGuire, L.C., Iskander, J. K., Thorpe, P., & Laird, S. (2017). Healthy aging: promoting well-being in older adults. CDC Grand Rounds.

Miyawaki CE, Bouldin ED , Kumar GS, McGuire LC . Associations between Physical Activity and Cognitive Functioning among Middle-Aged and Older Adults. J Nutr Health Aging . 2017;21(6):637-647. http://dx.doi.org/10.1007/s12603-016-0835-6 .

Snowden MB, Steinman LE, Bryant LL, Cherrier MM, Greenlund KJ, Leith KH, Levy C, Logsdon RG, Copeland C, Vogel M, Anderson LA , Atkins DC, Bell JF, Fitzpatrick AL. Dementia and co-occurring chronic conditions: a systematic literature review to identify what is known and where are the gaps in the evidence? Int J Geriatr Psychiatry . 2017 Apr;32(4):357-371. http://dx.doi.org/10.1002/gps.4652 .

Tang W, Kannaley K, Friedman DB, Edwards VJ , Wilcox S, Levkoff SE, Hunter RH, Irmiter C, Belza B. Concern about developing Alzheimer’s disease or dementia and intention to be screened: An analysis of national survey data. Arch Gerontol Geriatr . 2017 Jul;71:43-49. http://dx.doi.org/10.1016/j.archger.2017.02.013 .

Taylor CA , Greenlund SF, McGuire LC , Lu H, Croft JB. Deaths from Alzheimer’s Disease – United States, 1999-2014. MMWR Morb Mortal Wkly Rep . 2017 May 26;66(20):521-526. http://dx.doi.org/10.15585/mmwr.mm6620a1 .

Taylor CA , Bell JM, Breiding MB, Xu L (2017). Traumatic Brain Injury-related Emergency Department Visits, Hospitalizations, and Deaths — United States, 2007 and 2013. MMWR Surveill Summ , 66(No. SS-9): 1–16 [ http://dx.doi.org/10.15585/mmwr.ss6609a1 ].

Wiltz, J. L., Blanck, H. M., Lee, B., Kocot, S. L., Seeff, L., McGuire, L. C ., & Collins, J. (2017). Electronic Information Standards to Support Obesity Prevention and Bridge Services Across Systems, 2010–2015. Preventing Chronic Disease , 14, E103. http://doi.org/10.5888/pcd14.160299

Alzheimer’s Disease and Healthy Aging Program authors are in bold face .

Matthews, K. A., Holt, J., Gaglioti, A. H., Lochner, K. A., Shoff, C., McGuire, L. C. , & Greenlund, K. J. (2016). Peer Reviewed: County-Level Variation in Per Capita Spending for Multiple Chronic Conditions Among Fee-for-Service Medicare Beneficiaries, United States, 2014. Preventing Chronic Disease , 13 . DOI: 10.5888/pcd13.160240.

Eke, P. I., Wei, L., Borgnakke, W. S., Thornton-Evans, G., Zhang, X., Lu, H., McGuire, L. C. and Genco, R. J. (2016). Periodontitis prevalence in adults≥ 65 years of age, in the USA. Periodontology 2000 , 72 (1), 76-95. DOI: 10.1111/prd.12145.

VanFrank B.K., Park S., Foltz J.L., McGuire L.C. , Harris D.M. (2016). Physician Characteristics Associated With Sugar-Sweetened Beverage Counseling Practices. American Journal of Health Promotion , 0890117116680472. DOI: 10.1177/0890117116680472.

Park S., Akinbami L.J., McGuire L.C. , Blanck H.M. Association of sugar-sweetened beverage intake frequency and asthma among US adults, 2013. Preventive medicine , 91 , 58-61. DOI: 10.1016/j.ypmed.2016.08.004.

Park S., Thompson F.E., McGuire L.C. , Pan L., Galuska D.A., Blanck H.M. (2016). Sociodemographic and Behavioral Factors Associated with Added Sugars Intake among US Adults. Journal of the Academy of Nutrition and Dietetics, 116 (10), 1589-98. DOI: 10.1016/j.jand.2016.04.012.

Freedman D.S., Lawman H.G., Pan L., Skinner A.C., Allison D.B., McGuire L.C. , Blanck H.M. (2016). The prevalence and validity of high, biologically implausible values of weight, height, and BMI among 8.8 million children. Obesity , 24 (5), 1132-1139. DOI: 10.1002/oby.21446.

Lee-Kwan S.H., Pan L., Maynard L.M., McGuire L.C. , Park S. (2016). Factors Associated with Self-Reported Menu-Labeling Usage among US Adults. Journal of the Academy of Nutrition and Dietetics, 116 (7), 1127-35. DOI: 10.1016/j.jand.2015.12.015.

VanFrank, B. K., Park, S., Foltz, J., McGuire, L. C., & Harris, D. M. (2016). Physician Counseling on Sugar-Sweetened Beverages: Areas for Improvement. Pediatrics , 137 (Supplement 3), 121A-121A. DOI: 10.1542/peds.137.Supplement_3.121A.

Lee-Kwan, S. H., Park, S., Maynard, L. M., Blanck, H. M., McGuire, L. C. , & Collins, J. L. (2016). Parental Characteristics and Reasons Associated With Purchasing Kids’ Meals for Their Children. American Journal of Health Promotion , 0890117116683797. DOI: 10.1177/0890117116683797.

Jewett, A., Beck, L. F., Taylor, C ., & Baldwin, G. (2016). Bicycle helmet use among persons 5years and older in the United States, 2012. Journal of safety research , 59 , 1-7. DOI: 10.1016/j.jsr.2016.09.001.

Haarbauer-Krupa, J., Taylor, C. A ., Yue, J. K., Winkler, E. A., Pirracchio, R., Cooper, S. R., … & Manley, G. T. (2016). Screening for post-traumatic stress disorder in a civilian emergency department population with traumatic brain injury. Journal of neurotrauma , (ja). DOI: 10.1089/neu.2015.4158.

Edwards, V. J. , Anderson, L. A. , Thompson, W. W., & Deokar, A. J. (2016). Mental health differences between men and women caregivers, BRFSS 2009. Journal of Women & Aging , 1-7. DOI: 10.1080/08952841.2016.1223916.

Nicklett, E. J., Anderson, L. A., & Yen, I. H. (2016). Gardening Activities and Physical Health Among Older Adults A Review of the Evidence. Journal of Applied Gerontology , 35 (6), 678-690. DOI: 10.1177/0733464814563608.

Vandenberg, A. E., Hunter, R. H., Anderson, L. A., Bryant, L. L., Hooker, S. P., & Satariano, W. A. (2016). Walking and Walkability: Is Wayfinding a Missing Link? Implications for Public Health Practice. Journal of physical activity & health , 13 (2). DOI: 10.1123/jpah.2014-0577.

Anderson, L. A., & Slonim, A. (2016). Perspectives on the strategic uses of concept mapping to address public health challenges. Evaluation and Program Planning, 60, 194-201. DOI: 10.1016/j.evalprogplan.2016.08.011

Hunter, R. H., Anderson, L. A., & Belza, B. L. (Eds.). (2016). Community Wayfinding: Pathways to Understanding . Springer. ISBN 978-3-319-31072-5.

Greenlund, K. J., Liu, Y., Deokar, A. J., Wheaton, A. G., & Croft, J. B. (2016). Association of Chronic Obstructive Pulmonary Disease With Increased Confusion or Memory Loss and Functional Limitations Among Adults in 21 States, 2011 Behavioral Risk Factor Surveillance System. Preventing chronic disease , 13 . DOI: 10.5888/pcd13.150428.

Faul, M., Stevens, J. A., Sasser, S. M., Alee, L., Deokar, A. J., Kuhls, D. A., & Burke, P. A. (2016). Older adult falls seen by emergency medical service providers: a prevention opportunity. American journal of preventive medicine , 50 (6), 719-726. DOI: 10.1016/j.amepre.2015.12.011.

Bouldin, E. D., Thompson, M. L., Boyko, E. J., Morgenroth, D. C., & Littman, A. J. (2016). Weight change trajectories after incident lower-limb amputation. Archives of physical medicine and rehabilitation , 97 (1), 1-7. DOI: 10.1016/j.apmr.2015.09.017

Bouldin, E. D., Littman, A. J., Wong, E., Liu, C. F., Taylor, L., Rice, K., & Reiber, G. E. (2016). Medicare‐VHA dual use is associated with poorer chronic wound healing. Wound Repair and Regeneration , 24 (5), 913-922. DOI: 10.1111/wrr.12454

Cannell, M. B., Bouldin, E. D., Teigen, K., Akhtar, W. Z., & Andresen, E. M. (2016). The cross-sectional association between severity of non-cognitive disability and self-reported worsening memory. Disability and health journal , 9 (2), 289-297. DOI: 10.1016/j.dhjo.2015.09.001

CDC Healthy Aging Program authors are in bold face .

Anderson, L. (In Press). Population Aging. In Oxford Bibliographies in Public Health. Ed. David McQueen. New York: Oxford University Press.

Anderson, L.A. , Prohaska, T.R., & Satariano, W.A. (In Press). Prevention. Whitbourne, S.K. (ed.), The Encyclopedia of Adulthood and Aging. Hoboken, NJ: John Wiley & Sons, Inc.

Anderson, L.A., Deokar, A., Edwards, V.J. , Bouldin. E.D., & Greenlund, K.J. (2015). Demographic and Health Status Differences Among People Aged 45 or Older With and Without Functional Difficulties Related to Increased Confusion or Memory Loss, 2011 Behavioral Risk Factor Surveillance System. Preventing Chronic Disease , 12:140429. DOI: http://dx.doi.org/10.5888/pcd12.140429 .

Brady, T.J., Anderson, L.A. , & Kobau, R. (2015). Chronic Disease Self-Management Support: Public Health Perspectives. Frontiers in Public Health , http://dx.doi.org/10.3389/fpubh.2014.00234 .

Deokar, A.J. , Bouldin, E.D., Edwards, V.J., & Anderson, L.A. (2015). Increased Confusion and Memory Loss in Households, 2011 Behavioral Risk Factor Surveillance System. Preventing Chronic Disease , 12:140430. DOI: http://dx.doi.org/10.5888/pcd12.140430 .

Edwards, V.J., Anderson, L.A., & Deokar, A.J. (2015). Proxy Reports About Household Members With Increased Confusion or Memory Loss, 2011 Behavioral Risk Factor Surveillance System. Preventing Chronic Disease , 12:140427. DOI: http://dx.doi.org/10.5888/pcd12.140427 .

Friedman, D.B., Becofsky, K., Anderson, L.A. , et al. (2015). Public perceptions about risk and protective factors for cognitive health and impairment: A review of the literature. International Psychogeriatrics . Jan 16:1-13. doi:10.1017/S1041610214002877. (attached PDF for personal reading)

Phelan, E., Debman, K., Anderson, L.A. , & Owen, S. (2015). A Systematic Review of Intervention Studies to Prevent Hospitalizations of Community-dwelling Older Adults with Dementia. Medical Care . 53(2), 207–213. doi: 10.1097/MLR.0000000000000294

Petrescu-Prahova, M., Belza, B., Leith, K., Allen, P., Coe, N., & Anderson, L. (In Press). Using Social Network Analysis to Assess Mentorship and Collaboration in a Public Health Network. Preventing Chronic Disease .

Shenson, D., Moore, R.T., Benson, W., & Anderson, L.A. (2015). Polling Places, Pharmacies, and Public Health: Vote & Vax 2012. American Journal of Public Health . doi:10.2105/AJPH.2015.302628

Snowden, M., Steinman, L., Carlson, W.L., Mochan, K.N., Abraido-Lanza, A.F., Bryant , L. … & Anderson, L.A. (2015). Effect of Physical Activity, Social Support and Skills Training on Late-Life Emotional Health: A Systematic Literature Review and Implications for Public Health Research” Frontiers in Public Health .

Anderson, L.A. , & Egge, R. (2014). Expanding efforts to address Alzheimer’s disease: The Healthy Brain Initiative. Alzheimer’s & Dementia . 10:S453–S456. [doi:10.1016/j.jalz.2014.05.1748]

Anderson, L.A. , & Prohaska, T.R. (2014). Fostering Engagement and Independence: Opportunities and Challenges for an Aging Society, Health Education & Behavior , 41:5S-9S. [doi:10.1177/1090198114547818]

Anderson, L.A. , Slonim, A., Yen, I.H., Jones, D.L., Allen, P., Hunter, R.H., Goins, R.T., Leith, K.H., Rosenberg, D., Satariano, W.A., & McPhillips-Tangum, C. (2014). Developing a Framework and Priorities to Promote Mobility Among Older Adults. Health Education & Behavior . 41:10S-18S. [doi:10.1177/1090198114537492]

Barbour, K.E., Stevens, J.A., Helmick, C.G., Lou, Y-H, Murphy, L.B., Hootman, .J.M., Theis K., Anderson, L.A. , Baker, N.A., & Sugerman, D.E. (2014). Falls and Fall Injuries Among Adults with Arthritis — United States, 2012. MMWR . 63 (17):379–383.

Barile, J.P., Edwards, V.J. , Dhingra, S.S., & Thompson, W.W. (2014). Associations Among County-Level Social Determinants of Health, Child Maltreatment, and Emotional Support on Health-Related Quality of Life in Adulthood. Psychology of Violence . doi:10.1037/a0038202

Liu, Y., Croft, J.B., Anderson, L.A. , Wheaton, A.G., Presley-Cantrell, L.R., & Ford, E.S. (2014). The Association of Chronic Obstructive Pulmonary Disease, Disability, Engagement in Social Activities, and Mortality Among Older Adults: United States, 1994-2006. International Journal of Chronic Obstructive Pulmonary Disease . 9:75 – 83. [doi:dx.doi.org/10.2147/COPD.S53676]

Nicklett, E., Anderson, L.A. , & Yen, I. (2014). Gardening Activities and Physical Health among Older Adults: A Review of the Evidence. Journal of Applied Gerontology .DOI: 10.1177/0733464814563608

Ory, M.G., Anderson, L.A. , Friedman, D.B., Pulczinskia, J.C., Eugene, N., & Satariano, W.A., (2014). Setting the Stage: Cancer Prevention among Adults Aged 45 to 64. American Journal of Preventive Medicine . 46(3), Supplement 1: S1–S6.

Rao, J., Anderson, L.A. , Lin, F.C., & Laux, J.P. (2014). Completion of Advance Directives Among U.S. Consumers, American Journal of Preventive Medicine . 46(1):65–70.

Yen, I.H., Flood, J.F., Thompson, H., Anderson, L.A. , & Wong, G. (2014). How Design of Places Promotes or Inhibits Mobility of Older Adults: Realist Synthesis of 20 Years of Research. Journal of Aging and Health . Published online 30 April 2014 [doi:10.1177/0898264314527610]

Krist, A.H., Shenson, D., Woolf, S.H., Bradley, C., Liaw, W., Rothemich, S., Slonim, A., Benson, W. & Anderson, L.A. (2013). Clinical and Community Delivery Systems for Preventive Care: An Integration Framework. American Journal of Preventive Medicine . 45(4):508–516.

Liu Y, Croft JB, Chapman DP, Perry GS, Greenlund KJ, Zhao G, Edwards VJ . (2013). Relationship between adverse childhood experiences and unemployment among adults from five US states. Social Psychiatry and Psychiatric Epidemiology , 48, 357-369. doi:10.1007/s00127-012-0554-1.

Slonim, A., Benson, W., Anderson, L.A. , Jones, E. (2013). Strategic Priorities to Increase Use of Clinical Preventive Services Among Older US Adults. Preventing Chronic Disease . 10:120231. [doi:http://dx.doi.org/10.5888/pcd10.120231]

Spencer, L.M., Schooley, M.W., Anderson, L.A. , Kochtitzky, C.S., DeGroff, A..S, Devlin, H.M., & Mercer, S.L. (2013) Seeking Best Practices: A Conceptual Framework for Planning and Improving Evidence-Based Practices. Preventing Chronic Disease . 10:130186. [doi: http://dx.doi.org/10.5888/pcd10.130186]

Wilcox, S., Altpeter, M., Anderson, L.A. , Belza, B., Bryant, L., Jones, D.L., Leith, K.H., Phelan, E.A., & Satariano, W.A. (2013). The Healthy Aging Research Network: Resources for Building Capacity for Public Health and Aging Practice. American Journal of Health Promotion. 28(1):2-6. [doi: 10.4278/ajhp.121116-CIT-564]

Anderson, L.A. , Goodman, R., Holtzman R, Posner, S, & Northridge, M. (2012). Aging in the United States: Opportunities and Challenges for Public Health. American Journal of Public Health , 102(3):393–5.

Furner, S.E., & Anderson, L.A. (2012). Assessing the Health and Quality of Life of Older Populations: Concepts, Resources, and Systems. In Prohaska T, Anderson LA, Binstock R. editors. Public Health for an Aging Society. Baltimore, Maryland: Johns Hopkins University Press.

Holtzman, D., & Anderson, L.A. (2012). Aging and health in America: a tale from two boomers. American Journal of Public Health, 102(3):392.

Prohaska, T., Anderson, L.A. , Binstock. R., editors. (2012). Public Health for an Aging Society. Baltimore, Maryland: Johns Hopkins University Press.

Shenson, D., Adams, M., Bolen, J., Wooten K., Clough, J. Giles, W., & Anderson, L.A. (2012). Developing an Integrated Strategy to Reduce Ethnic and Racial Disparities in the Delivery of Clinical Preventive Services for Older Americans. American Journal of Public Health , On-line, Jun 14, 2012.

Yen, I.H., & Anderson, L.A. (2012). Built Environment and Mobility of Older Adults: Key Policy and Practice Efforts, Journal of the American Geriatrics Society. Article first published online: 9 MAY 2012. DOI: 10.1111/j.1532-5415.2012.03949

Anderson, L.A. Population Aging. Oxford Bibliographies Online, 2011. (Chapter for the Public Health section of Oxford Bibliographics Online. This chapter includes over 100 citations on aging related issues.

Anderson, L.A. , Day, K.L. , & Vandenberg A.E. (2011). Using a concept map as a tool for strategic planning: The Healthy Brain Initiative. Preventing Chronic Disease: Public Health Research, Practice, and Policy. 8(5):A117. http://www.cdc.gov/pcd/issues/2011/sep/10_0255.htm .

Day, K.L. , Friedman, D.B., Laditka, J.N., Anderson, L.A. , Hunter, R., Laditka, S.B., Wu, B., McGuire, L.C., & Coy, M.C. (2011). Prevention of Cognitive Impairment: Physician Perceptions and Practices. Journal of Applied Gerontology. DOI: 10.1177/0733464811401354

Kusano, C.T., Bouldin, E.D., Anderson, L.A. , McGuire, L.C. , Salvail, F.R., Wynkoop Simmons, K., Andresen, E.M. (2011). Adult informal caregivers reporting financial burden in Hawaii, Kansas, and Washington: Results from the 2007 Behavioral Risk Factor Surveillance System. Disability and Health Journal. 4(4):229–237.

Prohaska, T., Anderson, L.A. , Hooker, S.P., Hughes, S.L., & Belza, B. (2011). Editorial: Mobility and Aging: Transference to Transportation. Journal of Aging Research . Article ID 392751, doi:10.4061/2011/392751.

Shenson, D., Adams, M., Bolen, J., & Anderson, L.A. (2011). Routine checkups don’t ensure that seniors get preventive services. The Journal of Family Practice . 60(1): E1–10.

Snowden, M., Steinman, L., Mochan, K., Grodstein, F., Thurman, D., Brown, D., … & Anderson, L. A. (2011). Effect of exercise on cognitive performance in community-dwelling older adults: review of intervention trials and recommendations for public health practice and research. Journal of the American Geriatrics Society . 59:704–716.

Vandenberg, A.E., Price, A.E., Friedman, D.B., Marchman, G, & Anderson, L.A. , (2011). How Do Top Cable News Websites Portray Cognition as an Aging Issue? The Gerontologist . 52 (3): 367–382.

McGuire, L.C., Bouldin, E.L., Andresen, E.M., & Anderson, L.A. (2010). Examining modifiable health behaviors, body weight, and use of preventive health services among caregivers and non-caregivers aged 65 years and older using in Hawaii, Kansas, and Washington using BRFSS, 2007. Journal of Nutrition, Health and Aging . 14(5):373-9.

Rao, J.K. , Anderson, L.A. , Sukumar, B., Beauchesne, D.A., Stein, T., & Frankel, R.M. Engaging communication experts in a Delphi process to identify patient behaviors that could impact communication in medical encounters.BMC Health Services Research 2010, 10:97 (19 April 2010).

Snowden, M., Dhingra, S.S., Keyes, C.L.M., & Anderson, L.A. (2010). Changes in Mental Well-Being in the Transition to Late Life: Findings From MIDUS I and II. American Journal of Public Health . 100(12):2385-2388.

Anderson LA , Logsdon RG, Hochhalter AK, Sharkey JR. Introduction. The Gerontologist .2009; 49(S1):S1-S2.

Anderson LA , Day KL , Beard RL, Reed PS, Wu B. The public’s perceptions about cognitive health and Alzheimer’s disease among the U.S. population: A national review. The Gerontologist . 2009; 49(S1):S3-S11.

Day KL , McGuire LC , Anderson LA .The Centers for Disease Control and Prevention’s Healthy Brain Initiative: emerging implications of cognitive impairment. Generations . 2009; 33(1):11-17.

DeFries EL, McGuire LC , Andresen EM, Brumback BA, Anderson LA. Caregivers of older adults with cognitive impairment. Prev Chronic Dis . 2009 Apr;6(2):A46.

McGuire LC , Strine T, Vachirasudlekha S, Anderson LA ,Berry JT, Mokdad AH. Modifiable characteristics of a healthy lifestyle in US older adults with or without serious psychological distress, 2007 Behavioral Risk Factor Surveillance System. Int J Public Health . 2009;54:S84-S93.

McGuire LC, Strine T, Allen RS, Anderson LA , Mokdad AH. The Patient Health Questionnaire 8: current depressive symptoms among U.S. older adults, 2006 Behavioral Risk Factor Surveillance System. y . 2009 Apr;17(4):324-34.

Rao JK, Abraham L, Anderson LA . Novel approach, using end-of-life issues, for identifying items for public health surveillance. Preventing Chronic Disease . 2009;6(2):A57.

White-Cooper S, Dawkins NU, Kamin SL, Anderson LA. Community-Institutional Partnerships: Understanding Trust Among Partners. Health Educ Behav 2009 36: 334-347.

Ford ES, Mokdad AH, Li C, McGuire LC , Strine TW, Okoro CA, et al. Gender differences in coronary heart disease and health-related quality of life: Findings from 10 states from the 2004 Behavioral Risk Factor Surveillance System. Journal of Women’s Health 2008;17(5):757-768.

Frank E, Carrera JS, Rao JK , Anderson LA . Satisfaction with career choice among U.S. medical students. Archives of Internal Medicine 2008;168(15):1712-1716.

Garrett MD, Baldridge D, Benson WF , McGuire LC . Missing cohorts of caregivers among American Indian and Alaska Native communities. The IHS Primary Care Provider 2008;33:105-111.

Mark H, Irwin K, Sternberg M, Anderson LA , Magid DJ, Stiffman M. Providers’ perceived barriers to sexually transmitted disease care in 2 large health maintenance organizations. Sexually Transmitted Diseases 2008;35(2):184-189.

McGuire LC , Strine TW, Vachirasudlekha S , Mokdad AH, Anderson, LA . The prevalence of depression in older U.S. women, 2006 Behaviorial Risk Factor Surveillance System. Journal of Women’s Health 2008;17:501-507.

Rao JK . Applying the findings of public health research to communities: Balancing ideal conditions with real-world circumstances . Preventing Chronic Disease 2008;5(2):[4 pages].

Shenson D, Benson W , Harris AC . Expanding the delivery of clinical preventive services through community collaboration: The SPARC model . Preventing Chronic Disease 2008;5(1):[8 pages].

Thurman DJ, Stevens JA, Rao JK . Practice parameter: Assessing patients in a neurology practice for risk of falls (an evidence-based review): Report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology 2008;70(6):473-479.

Wright DS, Anderson LA , Brownson RC, Gwaltney MK, Scherer J, Cross AW, et al. Engaging partners to initiate evaluation efforts: Tactics used and lessons learned from the Prevention Research Centers Program . Preventing Chronic Disease 2008;5(1):[7 pages].

Anderson LA , McConnell SR. The healthy brain and our aging population: translating science to public health practice. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association 2007;3(S1):S1-S2.

Anderson LA , McConnell SR. Cognitive health: an emerging public health issue. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association 2007;3(S1):S70-S73.

Cunningham-Sabo L, Carpenter WR, Peterson JC, Anderson LA , Helfrich CD, Davis SM. Utilization of prevention research: searching for evidence. American Journal of Preventive Medicine 2007;33(1S):S9–S20.

Davis SM, Anderson LA (Guest Editors). The dissemination and utilization of prevention research: increasing our knowledge and understanding. American Journal of Preventive Medicine 2007;33(1S).

Ford ES, Ajani UA, McGuire LC , Liu S. Dietary magnesium and the metabolic syndrome among U.S. adults. Obesity 2007;15(5):1139-1146.

Li C, Ford ES, McGuire LC , Mokdad AH. Association of metabolic syndrome and insulin resistance with congestive heart failure: findings from National Health and Nutrition Examination Survey III”. Journal of Epidemiology and Community Health 2007;61(1):67-73.

Li C, Ford E, McGuire LC , Mokdad A. Increasing trends in waist circumference and abdominal obesity among US adults. Obesity 2007;15:217-223.

McGuire LC , Ajani UA, Ford ES. Cognitive functioning in late life: the impact of moderate alcohol consumption. Annals of Epidemiology 2007;17:93-99.

McGuire LC , Anderson LA , Talley RC, Crews JE. Supportive care needs of Americans: a major issue for women as both recipients and providers of such care. Journal of Women’s Health 2007:16(6):784-789.

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Current Alzheimer disease research highlights: evidence for novel risk factors

Editor(s): Ji, Yuan-Yuan

1 Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USA

2 Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA

3 Institute of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan 610072, China

4 Chinese Academy of Sciences Sichuan Translational Medicine Research Hospital, Chengdu, Sichuan, China

5 Centre for Public Health, Queen's University Belfast, Belfast, UK

6 Global Brain Health Institute, University of California, San Francisco, San Francisco, CA, USA

7 Department of Neurology, University of California, San Francisco, CA, USA.

Correspondence to: Dr. Wei-Dong Le, Institute of Neurology, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan 610072, ChinaE-Mail: [email protected] ; Dr. Yue Leng, Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA, USAE-Mail: [email protected]

How to cite this article: Brenowitz WD, Xiang Y, McEvoy CT, Yang C, Yaffe K, Le WD, Leng Y. Current Alzheimer disease research highlights: evidence for novel risk factors. Chin Med J 2021;134:2150–2159. doi: 10.1097/CM9.0000000000001706

Received 2 February, 2021

Willa D. Brenowitz and Yang Xiang contributed equally to the work.

This is an open access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal. http://creativecommons.org/licenses/by-nc-nd/4.0

Alzheimer disease (AD) is the most common type of dementia characterized by the progressive cognitive and social decline. Clinical drug targets have heavily focused on the amyloid hypothesis, with amyloid beta (Aβ), and tau proteins as key pathophysiologic markers of AD. However, no effective treatment has been developed so far, which prompts researchers to focus on other aspects of AD beyond Aβ, and tau proteins. Additionally, there is a mounting epidemiologic evidence that various environmental factors influence the development of dementia and that dementia etiology is likely heterogenous. In the past decades, new risk factors or potential etiologies have been widely studied. Here, we review several novel epidemiologic and clinical research developments that focus on sleep, hypoxia, diet, gut microbiota, and hearing impairment and their links to AD published in recent years. At the frontiers of AD research, these findings and updates could be worthy of further attention.

Introduction

As one of the most common neurodegenerative diseases and causes of dementia, Alzheimer disease (AD) is a critical topic for biomedical research. The main clinical manifestation of AD is the progressive decline of cognitive function and activities of daily living, and the pivotal pathological features of AD are amyloid beta (Aβ) deposition, neurofibrillary tangles, neuroinflammation, synaptic degeneration, and neuronal loss. [1] While research on AD has been ongoing for >100 years, our understanding of AD is also constantly enriched by the new research directions. However, there are still no effective treatments to delay, halt, or even reverse the process of AD.

In the past few decades, researchers have gradually shifted their attention from treatments to the early diagnosis and prevention of AD. [2] There is an interest in identifying the novel risk factors for AD as well as the novel biomarkers to help detect AD before the symptom onset. Several potential risk factors for AD have been studied extensively, including cardiovascular disease (CVD), diabetes, obesity, low education, social isolation, and depression. [3] However, recent epidemiologic and clinical studies are expanding our understanding of potential AD markers and risk factors to other health behaviors and conditions, such as sleep, diet, and hearing loss. For example, sleep disturbance has a complex association with AD and may be either a preclinical biomarker or potential modifiable risk factor for AD. In particular, hypoxia, often caused by severe obstructive sleep apnea syndrome (OSAS), significantly promotes the development of AD, inspiring the attempts to treat AD using the hyperbaric oxygen treatment (HBOT). [4] Dietary patterns are associated with cognition in older adults, and the Mediterranean-style diet (MD) is associated with reduced risk of AD. Gut microbiota may be an intriguing potential mediator between diet and AD. [5] Also, hearing impairment which is often ignored in clinical practice has strong associations with the risk of AD.

Here, we review the latest developments and especially the epidemiological evidence on sleep, hypoxia, diet, gut microbiota, and hearing impairment in the research field of AD published in recent years. These topics are receiving increasing research interest and may point to novel areas for intervention in the treatment and prevention of AD. As the frontiers of AD research, these findings and updates could be worthy of further attention.

Recent Progress in the Research of AD

In this section, we will review and summarize the recent progress in the research of AD focusing on five novel potential risk factors or early disease indicators such as sleep, hypoxia, diet, gut microbiota, and hearing impairment. As these factors are relatively novel, this review focuses on the epidemiologic evidence with some discussion of potential mechanisms as well as areas for future research.

Sleep and AD

One of the most exciting recent highlights in Alzheimer research is the bi-directional relationship between sleep disturbances and the risk of AD. Patients with AD frequently experience sleep disturbances, including insomnia, abnormal sleep duration, poor nighttime sleep quality, excessive daytime sleepiness, and disrupted circadian rhythms. [6] These sleep problems subsequently reduce patient quality of life and increase the risk for premature institutionalization.

Importantly, growing evidence from the epidemiological studies has suggested that 50% to 80% increased risk of dementia is associated with sleep disturbances, including insomnia, sleep-disordered breathing (SDB), disrupted circadian rhythms, and sleep-related movement disorders. [7–12] Excessive daytime napping has also been associated with an increased risk of cognitive impairment in older men, although the underlying mechanisms are less clear. [13] Several studies have found a U-shaped association between sleep duration and risk of dementia, [14,15] indicating the effects of both short and long sleep duration on cognitive aging. Furthermore, one recent study discovered 23 macro- and micro-physiological architecture metrics of sleep, including rapid eye movement sleep duration, features of the electroencephalography power spectra derived from multivariate analysis, and spindle and slow oscillation morphology and coupling, which were all strongly linked with cognitive performance in older adults. [16] Sleep disturbances are increasingly recognized as a preclinical marker or potential modifiable risk factor for AD.

Over the past decade, emerging evidence from animal and human studies has begun to uncover the nature of the association between sleep disturbances and AD. Since the earlier animal studies that identified a close link between sleep-wake cycle and the pathogenesis of AD, [17,18] a growing body of research has suggested sleep deprivation as both a result and trigger of Aβ, the hallmark pathological feature of AD. [19] Prospective analysis also showed that baseline measures of non-rapid eye movement (NREM) sleep slow-wave activity and sleep quality are sensitive in predicting longitudinal trajectory of Aβ deposition in healthy older adults, indicating the role of sleep as a useful biomarker for forecasting Aβ pathological progression before the clinical cognitive impairment. [20] Furthermore, sleep–wake cycle was found to regulate brain interstitial fluid (ISF) tau, and chronic sleep deprivation might increase ISF and cerebrospinal fluid (CSF) tau as well as tau pathology spreading. [21] It was also suggested that SDB might lead to increased tau levels over time in those with normal cognition or mild cognitive impairment (MCI). [22] Interestingly, one recent study found a coherent pattern of electrophysiological, hemodynamic, and CSF oscillations during human NREM sleep, suggesting a link in the neurophysiology of sleep and waste clearance in the brain. [23]

In addition to the use of neuroimaging and biomarkers, recent studies are also starting to use novel statistical approaches, such as Mendelian randomization (MR), to overcome the limitations of observational epidemiological studies and to reveal the causal relationship between sleep and AD. For instance, using the MR approach, it was found that higher genetic risk for AD might predict shorter sleep duration, suggesting that short sleep duration could be part of the AD disease process and thus serve as an early marker for AD. [24] Meanwhile, another MR study showed no causal effect of self-reported or accelerometer-measured sleep traits on AD risk. Given the growing evidence that indicates a bi-directional relationship between sleep disturbances and AD, emerging studies are underway to examine the use of sleep interventions in the prevention and treatment of AD. One recent review summarized the effects of several sleep interventions that have been studied in patients with MCI or mild dementia, including Cognitive Behavioral Therapy-Insomnia (CBT-I), a structured limbs exercise program, aromatherapy, phase locked loop acoustic stimulation, transcranial stimulation, suvorexant, melatonin, donepezil, galantamine, rivastigmine, tetrahydroaminoacridine, and Continuous Positive Airway Pressure (CPAP) and concluded that CBT-I, melatonin, suvorexant, and CPAP for OSA hold the most promises. [25] Since medications might further impair cognition, non-pharmacological interventions are of particular interest for older adults who are at high risk for dementia. Cordone et al [26] highlighted several promising techniques to enhance NREM sleep oscillations that have solid scientific basis for preventing or slowing down AD pathology but remain to be tested in clinical settings.

Overall, while it remains inconclusive whether sleep disturbances are early signs or risk factors for AD, recent research highlights the importance of sleep among older adults. Changes in sleep architecture and electroencephalogram might be considered as a valuable marker of AD before the onset of cognitive symptoms and help with the early detection of the disease. [27] Future research is needed to test whether sleep disturbances could be the risk factors for AD and to explore the use of sleep interventions in patients at high risk for AD. [25]

Hypoxia and AD

Hypoxia can be caused by CVD, hematological diseases, chronic kidney diseases (CKD), respiratory dysfunction, and environmental conditions, which could influence the central nervous system and induce neurodegeneration. [28–33] Acute hypoxia can be induced by stroke, while OSAS, capillary dysfunction, and CKD may lead to chronic hypoxia. Cognitive impairment may also occur in normal adults after hypoxia. [34,35]

Hypoxia is associated with AD. [28–33] Both acute and chronic hypoxia intervention in experimental animals can result in the aggravation of cognitive dysfunction and the AD-type pathological alterations including Aβ deposition, hyperphosphorylation of tau protein, synaptic degeneration, and neuronal loss. [36] Increasing evidence suggests that hypoxia facilitates the pathogenesis of AD through multiple pathways including increasing the production and accelerating the accumulation of Aβ, [36] decreasing the degradation of Aβ, [37] reducing the clearance of Aβ, [38] elevating the hyperphosphorylation of tau, [39] inhibiting the autophagic function, [40] aggravating neuroinflammation [41] and oxidation stress, [42] ruining the mitochondria function, [43] and causing the stress of endoplasmic reticulum. [44] As mentioned above, it is rational to propose that hypoxia is one of the essential factors contributing to the pathogenesis of AD.

Given that hypoxia contributes to the pathogenesis of AD, the development of prevention and treatment targeting hypoxia is promising. HBOT is a safe, effective, and routinely used medical procedure. Growing evidence suggests that HBOT can induce the neuroplasticity and improve the cognitive function in patients suffering from neurocognitive impairment due to stroke and brain injuries. [45,46] Moreover, HBOT cannot only improve cognitive functions and ameliorate the brain glucose metabolism in AD and amnestic MCI (aMCI) patients [4,47] but also induce significant senolytic effects including significantly increasing telomere length and clearance of senescent cells in the aging individuals. [48]

Besides, HBOT is capable of improving the cognitive behavioral performance, reducing Aβ burden and tau hyperphosphorylation, alleviating neuroinflammation by decreasing astrogliosis and microgliosis, reducing proinflammatory cytokines, and elevating phagocytic markers in mouse mole of AD. [49] More recently, HBOT was shown to be able to reduce Aβ accumulation and hippocampal neuritic atrophy, increase hippocampal neurogenesis, and profoundly improve the cognitive deficits through the upregulation of neurotrophic factors. [50] Moreover, HBOT has been proved to inhibit Aβ25–35-induced toxicity, oxidative stress, and neuronal apoptosis. [51,52] In addition, both the cognitive impairment and hippocampal damage can be attenuated by HBOT via NF-κB signaling pathway [53] or p38 mitogen-activated protein kinase (MAPK) in the animal model of AD. [54] However, there is still no research report on whether HBOT has the capacity of preventing or delaying the occurrence of AD in high-risk groups at an early stage. Besides, further experiments are still warranted because of the possibility of oxygen toxicity, even though HBOT itself seems to be beneficial to cognition.

Diet and AD

As poor diet contributes to several AD risk factors including obesity, hypertension, and diabetes, modifying the dietary behavior could be an effective public health strategy to protect against age-related neurodegeneration and AD in late life.

A growing body of evidence has linked several foods (eg, green vegetables, berries, fish, and olive oil), nutrients (eg, B-vitamins, vitamin E, and omega-3 fatty acids), and plant bioactives (eg, flavanoids) to reduce dementia risk. Consuming these nutrients and foods in combination as a dietary pattern is likely to exert greater synergistic effects on the physiological processes underlying neurodegeneration. The MD rich in antioxidants and flavonoids and characterized by high intake of fruits, vegetables, whole grains, olive oil, nuts, and legumes; moderate intake of fish, poultry, and alcohol, and low intake of red meat have proven cardiometabolic benefits [55] and remain the most frequently studied dietary pattern for neuroprotection during ageing. Evidence from prospective studies indicate beneficial associations among MD adherence, slower rate of cognitive decline, and reduced risk of cognitive impairment, in Western [56,57] and Asian [58] populations. However, findings have not been consistent likely because of the differences in populations studied, measures of MD and cognition, length of follow-up, and adjustment for important confounders such as cardiovascular morbidity and baseline cognitive function. To date, only a small number of studies have examined the relationship between diet and incident AD. [59] Among older cognitively healthy U.S. adults, those in the highest tertile of MD adherence had 40% to 54% reduced AD risk compared to those in the lowest MD tertile, but results have not been replicated in French or Swedish populations [59] making it difficult to draw firm conclusions.

The neuroprotective mechanisms of a healthy diet are not fully elucidated, but multiple antioxidants, anti-inflammatory, and vascular pathways are likely to be important. The MD improves vascular function and insulin resistance [55,60] that contribute to the cognitive decline and AD. Experimental and preclinical studies have shown that dietary antioxidants and flavonoids have a direct effect on the brain by inhibiting oxidative stress, cytokine production and pro-inflammatory cell signaling pathways, and suppressing neuroinflammatory processes implicated in AD. Emerging data suggest that diets rich in fruit, vegetables, whole grains, and fiber promote biodiversity of the gut microbiome and decreased pro-inflammatory gut-derived bacteria and toxins are shown to contribute to early neuroinflammatory changes, and AD pathology. [5,60] Evidence from observational studies report a link between greater MD adherence and favorable brain structures and functions that protect against neurodegeneration as well as less Aβ accumulation in AD-vulnerable regions of the brain. [61] Furthermore, dietary restriction [62] achieved by calorie restriction (30%–40%) or intermittent fasting may provide neuroprotection by attenuating neuroinflammation and insulin resistance and promoting synaptic plasticity and neurogenesis. [63] Beneficial effects of DR on AD pathology have been demonstrated in some [64,65] but not all [66] transgenic animal models, and it is not yet clear on how the findings translate to humans. [63]

The effect of diet on AD risk is not yet known; however, randomized controlled trial data evaluating the effect of diet on cognitive performance demonstrated less decline in global cognition, memory, and executive function in response to a MD >4 to 6 years [60] with no convincing benefit for shorter-term MD interventions (up to 12 months) [59] in cognitively healthy older adults, suggesting that several years of dietary exposure may be needed to detect changes in intermediate cognitive tests of AD risk in general populations.

Overall, accumulating data suggest a role for diet in AD prevention but larger adequately powered intervention and prospective studies in diverse populations with clinically relevant endpoints incorporating incident AD, MCI as well as sensitive neurocognitive tests and brain biomarkers associated with preclinical AD risk are required to understand the effect of diet on AD from the earliest to later stages of disease.

Gut microbiota and AD

Given the complex bidirectional communication system that exists between the gut and brain, there is a growing interest in the gut microbiome as a novel and potentially modifiable risk factor for cognitive impairment and AD. Gut dysbiosis has been implicated in the pathogenesis and progression of AD.

Compared with the normal controls, the Bacteroidetes , Actinomyces , Ruminococcus , and Selenomonas in AD patients are significantly different. [67] The cognitively normal elderly do not have an AD-type pattern of gut microbiota compared with patients at the early stage of AD, [68] and specific gut microbiota, especially enriched Enterobacteriaceae , are associated with AD patients compared with aMCI and cognitively healthy controls, [69] indicating the potential of gut microbiota in the differential diagnosis of AD. Besides, the alteration of gut microbiota tends to occur several years before the onset of dementia, even at the early stage of MCI. [68] A cross-sectional study showed that an increase in Bacteroidetes in non-dementia patients is independently associated with the presence of MCI. [70] The abundance increase of Enterobacteriaceae , Akkermansia , Slackia , Christensenellaceae , and Erysipelotriaceae in MCI patients suggests that this special gut microbiota composition may indicate the presence of MCI. [71]

To investigate the causal relationship between gut microbiota and AD, a clinical study found that gamma-aminobutyric acid (GABA) and serotonin may play an important role in the gut microbiota–host interaction in AD patients. [72] A pilot study revealed the characteristics of the MCI-specific gut fungi (mycobiome) signatures and elucidated that the diet-regulated mycobiome are associated with AD markers and fungal–bacterial co-regulation networks in MCI patients. [73] A clinical study showed that Proteobacteria is positively correlated with Aβ42:Aβ40 ratio, but the fecal propionic acid and butyric acid are negatively correlated with Aβ42 level in MCI patients with the MD. [71] Intriguingly, the gut microbiota composition is strongly correlated with apolipoprotein E (ApoE) genotype. The relative abundance of different bacterial groups is significantly different under the influence of ApoE genotype, [74] which is also related to the specific gut microbiota composition of human and ApoE-targeted replacement mice, especially the Prevotellaceae and Ruminococcaceae and several butyrate-producing genera. [75] Moreover, the relative abundance of Prevotella and Ruminococcus in female ApoE4-familial Alzheimers disease (FAD) mice is higher than that of female ApoE3-FAD mice, whereas the relative abundance of Sutterella in male ApoE4-FAD mice is significantly higher than that of female ApoE3-FAD mice, implying a synergistic effect of ApoE and sex on gut microbiota of AD. [76]

The metabolites of gut microbiota are particularly critical in the mechanism of the gut–brain axis. Trimethylamine-n-oxide (TMAO), a kind of gut microbiota metabolites, can be found in human CSF. [77] It was suggested that the gut microbiota metabolites, such as lipopolysaccharide (LPS) and short chain fatty acids, could mediate the systemic inflammation and intracerebral amyloidosis through endothelial dysfunction. [78] A multicenter clinical study found that the serum concentration of primary bile acid (BA) is significantly decreased, whereas the concentrations of secondary BA, deoxycholic acid, and its conjugated form of glycine and taurine are increased in AD patients compared with cognitively normal elderly. [79] Moreover, it was found that the certain blood BA-related indicators are associated with CSF-Aβ, CSF-p-tau 181, CSF-t-tau, glucose metabolism, and brain atrophy in patients with MCI and AD, respectively. [80]

Additionally, there are also many studies exploring the effect and mechanism of different types of intervention on AD using gut microbiota as a potential mediator. High dose of Jatrorrhizine, [81] an essential component of coptidis rhizome, a Chinese traditional herb, is capable of improving the learning and memory ability, reducing Aβ deposition, and altering the abundance of certain gut microbiota composition such as Firmicutes and Bacteroidetes in APP/PS1 mice. [82] Besides, 27-hydroxycholesterol can aggravate AD-type pathological alterations, gut microbiota dysbiosis, and intestinal barrier dysfunction. [83] The fructooligosaccharides derived from Morinda officinalis improves the learning and memory abilities of rats by regulating the interaction between intestinal ecosystem and brain. [84] Xanthoceraside can alleviate the symptoms of AD by affecting the composition and endogenous metabolites of gut microbiota in rats. [85] GV-971, an oligosaccharide sodium, has the capacity of inhibiting gut microbiota dysbiosis and related phenylalanine/isoleucine accumulation, alleviating neuroinflammation, and reversing cognitive dysfunction. [86]

Environmental factors may also influence the pathogenesis of AD through gut microbiota. Long-term exposure to noise alters gut microbiota composition and accelerates age-related neurochemical and inflammatory regulation disorders, resulting in the aggravated AD-type pathological changes in the brain of senescence-accelerated prone mice. [87] Treatment of mid infrared light of peak wavelength 7.7 to 10 mm can attenuate the decline of learning and memory, reduce Aβ deposition, and alter the gut microbiota composition. [88]

Due to the importance of gut microbiota in the pathogenesis of AD, many studies assessed its potential therapeutic value. Clinical studies have found that supplement of multiple probiotics alters the gut microbiota composition and serum tryptophan metabolism in AD patients, [89] and promotes the mental plasticity and stress relief in healthy elderly. [90] A multicenter study published recently has also shown that the MD can alter the composition of the gut microbiota and improve cognitive function in older adults. [5]

In animal study, it revealed that the transplantation of feces from normal wild type mice to AD transgenic mice significantly reduces Aβ burden and tau pathology, attenuates the glial activation, learning and memory impairment, and abnormal expression of genes related to intestinal macrophage activity, and restores the circulating inflammatory monocytes and synaptic plasticity in AD mice. [91,92] The gut microbiota alteration can promote Aβ deposition by activating the MAPK signaling pathway and C/enhancer binding protein β (EBP)/asparagine endopeptidase (AEP) signaling pathway in the brain of AD transgenic mice. [93,94] In addition, the probiotics have the capacity of improving the maze navigation, restoring the long-term potential, and balancing the antioxidant/oxidative biomarkers in mice. [95] In detail, Lactobacillus plantarum inhibits the synthesis of TMAO and reduces the clusterin level. [96] Clostridium butyricum and its metabolites inhibit microglia-mediated neuroinflammation. [97] Bifidobacterium longum regulates NF-κB activation via inhibiting LPS production. [98] Of note, however, clinical studies have found that probiotics supplement does not significantly improve the cognitive and biochemical indicators in patients with severe AD. [99]

Unlike the intestinal probiotics, the effects of antibiotics on AD are more complicated. Antibiotics, such as streptozotocin, can promote the growth of proinflammatory gut microbiota sub-types in animals, leading to learning and memory impairment, as has been used to establish sporadic AD models. [100] Rifampicin and minocycline could decrease the levels of Aβ, glial activation, and inflammatory cytokines in the brain of AD mice. [101,102] Rapamycin not only reduces the level of Aβ and the activation of microglia but also decreases the phosphorylation of tau protein. [103] Nevertheless, despite some encouraging results in the animal studies, the clinical efficacy of antibiotics in patients with AD remains controversial so far.

Hearing impairment and AD

There is an emerging interest in the role of age-related hearing impairment on development of AD and other dementias. Hearing impairments can be caused by changes in the inner ear (eg, peripheral hearing) and/or dysfunction in auditory processing (eg, central hearing). Hearing impairments are common among older adults: affecting up to 40% of adults aged 65 and up to 90% of adults aged >90. [104] Hearing difficulty is commonly reported by patients with AD. [105] Observational studies have found a consistent association between hearing loss and risk of dementia and cognitive decline. [106,107] This work raises the question whether hearing loss may cause AD and dementia; however, alternative mechanisms could also explain this association. [108]

Hearing impairments may directly affect dementia risk through brain atrophy by impairing cognitive processing abilities or by increasing cognitive load. [108] In animal studies, noise-induced (peripheral) hearing loss is associated with increased neurodegeneration in the hippocampus, decreased neurogenesis, and poor memory function. [109] Hearing impairments may also affect “psychosocial wellbeing” including social engagement, mental health, and physical activity, [109] which could lead to increased dementia risk. [110] In epidemiologic studies, peripheral hearing loss measured by pure tone audiometry may offer some of the stronger evidence that hearing loss may cause dementia, since pure tones are less affected by AD-neurodegeneration than central hearing. [110] Peripheral hearing impairment has also been associated with decreased whole brain volumes, reduced temporal lobe or auditory cortex volumes, [111,112] or reduced hippocampal volume. [113] But there are conflicting results. [114]

Hearing loss can often be corrected or mitigated, which could in turn also reduce dementia burden if hearing loss causes dementia. The Lancet commission on dementia prevention in 2020 suggested that treating hearing loss may reduce dementia burden by up to 8%. [110] However, this estimate is based on observational studies which may be biased. Evidence from several small clinical trials has been mixed; some studies are suggestive that treatment of hearing impairments may improve cognition in non-demented patients, [115] but this was not found in AD patients. [116] Although studies often include important confounders in statistical models, unmeasured or residual confounder may remain. Both hearing and cognitive impairments are strongly associated with age, tend to have a gradual onset, and may have shared etiologies, including neurodegeneration, vascular and metabolic diseases, and aging processes. [117] Some studies even question a biologic between hearing and cognition, as many cognitive tests rely on hearing and poor hearing may lead to more errors in hearing-based cognitive tests. [118]

Relatively few studies have examined associations between hearing and AD specifically; one study on dementia sub-types have found associations between hearing impairment and clinical AD but not vascular dementia. [119] One neuroimaging study found an association with pure tone and word recognition hearing loss and in vivo Aβ deposition, [120] while an autopsy study found an association between clinician rated hearing loss and tau neurofibrillary degeneration stage but not Aβ plaque frequency. [121] Higher genetic risk for AD also is associated with increased difficulty hearing in noise in older adults, suggesting a shared biologic pathway and that central hearing loss such as difficulty hearing in noise may be a preclinical marker for AD. [122] Neurodegeneration in AD affects anatomical structures including the auditory pathways: neuritic plaques and tangles have been found in auditory association cortex as well as subcortical auditory pathways, which includes the medial temporal lobe. Several studies find that central auditory processing dysfunction is strongly associated with AD and precedes dementia diagnosis. [123]

Older adults with hearing impairments are a higher risk for dementia and may be an important subgroup for referral for dementia evaluation. Treating hearing impairment may also help to prevent dementia; however, further research is needed to clarify the relationships between hearing impairments, AD, and dementia. Regardless, treatment for hearing impairments should be prioritized to improve quality of life of older adults with hearing loss.

Perspectives

There is no denying that the clinical treatment of AD is currently facing significant bottlenecks. The failure of many clinical trials suggests the importance of early diagnosis and prevention. Therefore, in recent years, researchers have been interested in thinking about AD from a broad perspective and in evaluating novel potential risk factors beyond those traditionally associated with AD such as CVD, diabetes, and education. These findings of the effects of oxygen metabolism, inflammation, and gut microbiota provide novel evidence that systemic effects may impact brain aging. Furthermore, our review highlights the potential importance of underappreciated health factors to healthy aging such as sleep, diet, and hearing. This new research adds further evidence to support a shift from amyloid focused drug targets to multi-domain interventions that may help prevent AD and slow cognitive decline.

However, there is still a lot of work to be done in these areas. In Table 1 , we present main evidence for each topic in our review as well as list key next steps for research. In particular, studies are needed to clarify the causal directions of the association between these potential novel risk factors and AD and to understand the underlying mechanisms and how they are related to AD neuropathogenesis. The clinical application of the study of oxygen metabolism and AD, such as the attempt to treat AD with HBOT; development of new intestinal probiotics; the prevention and treatment effect of specific diet components on AD. As the future direction of AD research, these works will require more multidisciplinary collaboration and the use of innovative research methods.

Items	Summary of main evidence	Priorities for future research
Sleep	There exists a bi-directional relationship between sleep disturbances and dementia, but it remains unclear whether sleep disturbances are early signs or risk factors for AD.	Future research to uncover potential mechanisms and to explore the use of sleep interventions for the prevention and treatment of AD among high-risk older adults.
Hypoxia	Chronic hypoxia is one of the important environmental factors contributing to the pathogenesis of AD.	Further research is needed to determine whether prospective prevention and treatment of hypoxia may be helpful to delay or ameliorate the progression of AD by any mechanism.
Diet	Certain nutrients (eg, antioxidants) and dietary patterns (eg, Mediterranean diet) might have neuroprotective effects, but results have been inconsistent.	Larger adequately powered intervention and prospective studies in diverse populations with clinically relevant endpoints as well as sensitive neurocognitive tests and brain biomarkers associated with preclinical AD risk are required to understand the effect of diet on AD from the earliest to later stages of disease.
Gut microbiome	Numerous evidences have been obtained on the relationship between gut microbiota and AD from clinical studies, animal experiments, and mechanism exploration.	Whether some specific bacteria or combinations of bacteria in the gut microbiota have a role in the prevention and treatment of AD remains to be further clarified.
Hearing loss	Peripheral and central hearing loss are associated with lower regional brain volumes and dementia risk	Studies to determine mechanisms and direction of associations.

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Comprehensive review on alzheimer’s disease: causes and treatment.

1. Introduction

2. alzheimer’s disease diagnostic criteria, 3. alzheimer’s disease’s neuropathology, 3.1. senile plaques (sp), 3.2. neurofibrillary tangles (nfts), 3.3. synaptic loss, 4. the stages of alzheimer’s disease, 5. causes and risk factors of alzheimer’s disease, 5.1. alzheimer’s disease hypotheses, 5.1.1. cholinergic hypothesis, 5.1.2. amyloid hypothesis, 5.2. alzheimer’s disease risk factors, 5.2.1. aging, 5.2.2. genetics.

Amyloid Precursor Protein (APP)
Presenilin-1 (PSEN-1) and Presenilin-2 (PSEN-2)
Apolipoprotein E (ApoE)
ATP Binding Cassette Transporter A1 (ABCA1)
Clusterin Gene (CLU) and Bridging Integrator 1 ( BIN1 )
Evolutionarily Conserved Signaling Intermediate in Toll pathway (ECSIT)
Estrogen Receptor Gene (ESR)
Other Genes

5.2.3. Environmental Factors

Air Pollution

5.2.4. Medical Factors

Cardiovascular Disease (CVDs)
Obesity and Diabetes

6. Treatment

6.1. symptomatic treatment of ad, 6.1.1. cholinesterase inhibitors.

Rivastigmine
Galantamine (GAL)

6.1.2. N -methyl d -aspartate (NMDA) Antagonists

6.2. promising future therapies, 6.2.1. disease-modifying therapeutics (dmt), 6.2.2. chaperones.

Heat Shock Proteins (Hsps)
Vacuolar sorting protein 35 (VPS35)

6.2.3. Natural Extract

7. conclusions, author contributions, conflicts of interest.

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Click here to enlarge figure

Disease Modifying Agents	Mechanism of Action
Phase 3 Clinical Trials
	Monoclonal antibody—targets β-amyloid and removes it.
	Monoclonal antibody—binds and removes β-amyloid.
	Amyloid vaccine—stimulates production of antibodies against β-amyloid.
	Monoclonal antibody—reduces protofibrillar β-amyloid.
	Tau protein aggregation inhibitor.
	Low-dose levetiracetam—improves synaptic function and reduces amyloid-induced neuronal hyperactivity
	Mast cell stabilizer and anti-inflammatory—promotes microglial clearance of amyloid
	RAGE (Receptor for Advanced Glycation End-products) antagonist—reduces inflammation and amyloid transport into the brain
	Glutamate modulator—reduces synaptic levels of glutamate and improves synaptic functioning
	Tyrosine kinase inhibitor—modulates inflammatory mast cell and reduces amyloid protein and tau phosphorylation

	Monoclonal antibody—targets soluble oligomers and removes β-amyloid
	Monoclonal antibody—prevents tau propagation
	Active immunotherapy—targets β-amyloid and removes it
	Monoclonal antibody—removes amyloid protofibrils and reduces amyloid plaques
	Monoclonal antibody—removes tau and reduces tau propagation
	Monoclonal antibody—removes amyloid by recognizing aggregated pyroglutamate form of Aβ
	Monoclonal antibody—neutralizes soluble tau aggregates
	Monoclonal antibody—removes extracellular tau
	Alpha-secretase modulator—reduces amyloid
	Monoclonal antibody—immunomodulatory that targets CD38 and regulates microglial activity
	Tyrosine kinase inhibitor (dasatinib) + flavonoid (quercetin)—reduces senescent cells and tau aggregation
	Epigenetic, Tau Antisense oligonucleotide—reduces tau production
	Neurotransmitter receptors ion channel modulator—improves neuropsychiatric symptoms
	Tyrosine kinase inhibitor—promotes clearance of amyloid and tau proteins
	Selective inhibitor of APP—reduces amyloid, tau, and α-synuclein production
	Filamin A protein inhibitor—reduces tau hyperphosphorylation, synaptic dysfunction, and stabilizes soluble amyloid and the α7 nicotinic acetylcholine receptor interaction
	Glutaminyl cyclase (QC) enzyme inhibitor—reduces amyloid plaques and pyroglutamates Aβ production
	Glutamate receptor antagonist—reduces glutamate-mediated excitotoxicity
	Activates ABCC1 (ATP binding cassette subfamily C member 1 transport protein)—removes amyloid

	Monoclonal antibody—removes tau and reduces tau propagation
	Monoclonal antibody—removes tau
	Aggregation inhibitor—reduces tau aggregation
	Monoclonal antibody—removes amyloid
	Stabilizes tubulin-binding, microtubule, and reduces cellular damage mediated by tau

Natural Compounds	Mechanism of Action
	Aβ formation inhibitors
	Reduction of Aβ accumulation
	Promotion of Aβ degradation
), Houttuyniacordata Thunb. (Saururaceae) water extracts, Huperzine A, and ethyl acetate extract from Diospyros kaki L.f	Inhibition of Aβ Neurotoxicity and reduce over-activation of microglial cells, neuroinflammation, oxidative stress, and disruption of calcium homeostasis, which lead to neuron loss
L., geniposide from the fruit of G. jasminoides J. Ellis, ginsenoside Rd from Panax ginseng C. A. Mey, crocin from Crocus sativus L., and quinones)	Inhibition of hyperphosphorylated tau protein and its aggregation

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Breijyeh, Z.; Karaman, R. Comprehensive Review on Alzheimer’s Disease: Causes and Treatment. Molecules 2020 , 25 , 5789. https://doi.org/10.3390/molecules25245789

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Dela J Public Health
v.7(4); 2021 Sep

Diagnosis and Treatment of Alzheimer’s Disease:

Introduction.

Alzheimer’s Disease (AD) exerts a significant worldwide impact. An estimated 44 million individuals currently live with this Major Neurocognitive Disorder. There are about 6.2 million Americans with AD dementia today and AD kills more people than breast cancer and prostate cancer combined. The National Institute on Aging estimates that the prevalence of AD doubles every five years beyond the age of 65 and as the population ages, a greater proportion of the population is affected. AD will cost the United States over $355 billion in 2021, rising to over $1.5 trillion by 2050 1 imposing a significant economic burden. Early diagnosis and treatment of neurocognitive disorders are critical in determining treatment approaches and shaping policy to prepare for the deluge of cases to come. This review describes current diagnostic approaches and treatment advances for AD.

Current Diagnostic Strategies

The evaluation of a person with suspected memory impairment includes a comprehensive set of assessments aimed at characterizing the etiology of cognitive decline and identifying treatable pathologies. These assessments include a detailed medical history, physical and mental status examinations, basic labs, and neuroimaging studies. Additional tools may also include neuropsychological testing and advanced brain imaging techniques. Once reversible causes have been ruled out, clues for specific causes of major neurocognitive disorder are sought. A history of multiple strokes, for example, may point towards a diagnosis of vascular dementia. A history of head trauma may suggest traumatic encephalopathy. A history of prolonged alcohol use disorder may support the diagnosis of an alcohol-related dementia. In adults over 60, the most frequent cause of progressive cognitive decline is AD. 2

Emerging Diagnostics

Finding earlier and more definitive ways to diagnose AD has been the subject of significant amounts of research, and testing advances have been seen in the last decade with expanded use of positron emission tomography (PET) and magnetic resonance imaging (MRI), as well as in the identification of biomarkers in cerebrospinal fluid (CSF) and more recently serum. While limited, some of these diagnostic advances are available to the public, though typically at a high price.

A high-level overview of emerging diagnostic strategies can be found below.

Volumetric Data

In simple terms, volume changes in specific brain regions can predict the likelihood of progression from mild cognitive impairment (MCI) to AD. These volume assessments can be done by radiologists or with the help of FDA-approved MRI volumetric data software packages such as Neuroquant and Neuoreader. Hippocampal volume changes in particular are regarded as an important AD biomarker. 3 Because of limited sensitivity of this measure in diagnosing AD, however, MRI studies are regarded as a contributor to the diagnostic process but not sufficient in themselves for determining a diagnosis. 4

Diffusion Tensor Imaging

Diffusion Tensor Imaging (DTI) is an advanced neuroimaging technique that uses the diffusion properties of water molecules to generate magnetic resonance images that correspond to changes in macroscopic axonal organization. This technique can be used to evaluate the structure of vertical cellular micro-circuits, termed “minicolumns.” Previous studies have demonstrated that minicolumns are known to be altered in a somewhat predictable and progressive manner during aging, MCI, and AD. 5 Additionally, pathologic changes of cortex columnar architecture are associated with increased plaque load and cognitive decline. 6 With the aid of proprietary software, DTI can be measured and used as a marker of neurodegeneration.

Pathologic species of two proteins, amyloid-β (Aβ) and hyperphosphorylated tau accumulate in the brains of persons with AD. PET scans are able to assess for both proteins and serve as a reliable biomarker. Amyloid accumulation precedes clinically significant cognitive changes and tau accumulation progresses in step with cognitive decline, suggesting the value of PET scans for diagnosis and measurement of disease progression. 7

CSF and Blood Tests

Cerebrospinal fluid (CSF), accessible through lumbar puncture, surrounds the brain. Changes in the levels of Aβ and tau proteins in the CSF develop decades before the onset of clinically significant AD. 8 Among the tests of CSF developed during recent decades, the most prominent are CSF Aβ42:Aβ40 ratio and the CSF tau phosphorylated at threonine 181 (P-tau181). CSF P-tau217, measurable in the peripheral circulation, is hoped to provide a biomarker with very high sensitivity and specificity. 9

Because blood is more easily accessed than CSF, C2N Diagnostics in St. Louis, Missouri has developed and released a blood test called PrecivityAD which is available in most of the U.S. and to the European Union. The test uses mass spectrometry to detect specific species of beta-amyloid in serum which are lower in AD. The test is not presently covered by insurance, representing a significant cost that may be defrayed for eligible individuals through a financial assistance program. The test is not a stand-alone diagnostic tool; rather the results are a probability score and are intended to be interpreted in concert with other testing means. 10 Additionally, research on plasma Aβ42:Aβ40 ratio and P-tau181 suggests potential value. 11 , 12

Implications of New Diagnostic Strategies: Risks vs. Benefits

Although some people express the wish not to know, almost 90% of people surveyed in a large US study expressed a wish to know their diagnosis. Sixty-five percent of respondents said that even if they were asymptomatic they would be likely or somewhat likely to accept a medical test to assess for AD. 13 Early detection offers the benefits of earlier access to medications, inclusion in clinical trials, the opportunity for lifestyle modification, and knowledge useful to families in preparing for the future while the affected individual remains able to participate actively in decision-making.

Early detection and disclosure, however, also carry risks. The mental health effects of receiving a diagnosis are known to be significant not only for patients but also for families. Multiple studies have documented a small increase in death by suicide in those with dementia, most prominently during the first three months after a diagnosis was made. 14 This suggests the need for increased mental health support and monitoring particularly in the early months after a diagnosis is given, as well as the importance of educating family about suicide risk. As treatment options for early stage dementia increase, the benefits and risks of early diagnostic assessment will become a matter of great significance.

Current Therapeutic Strategies and Options

Several mechanisms have been proposed to account for the pathology of AD, and current treatments are counteract these mechanisms. The most widely accepted disease models are the amyloid cascade hypothesis, the tau hypothesis, the cholinergic hypothesis, and the excitotoxicity hypothesis.

Our current AD medications were developed to address the cholinergic deficit that occurs early in AD. The selective loss of cholinergic neurons, an early pathologic finding in AD, results in a profound reduction in the neurotransmitter acetylcholine, which affects learning and memory neuronal circuitry. Facilitating cholinergic transmission was therefore an early approach to AD treatment which resulted in several palliative medications still in use. 15 – 17

Cholinesterase Inhibitors

The primary action of the cholinesterase inhibitors is the reversible inhibition of cholinesterase, the enzyme which breaks down acetylcholine in brain synapses, thereby prolonging the effect of the diminished level of brain acetylcholine. 18 , 19 Three cholinesterase inhibitors are currently used: donepezil, rivastigmine, and galantamine. Meta-analyses have shown that these agents delay decline in cognitive function, slow the decline in global clinical rating, and may delay the decline of activities of daily living (ADL) and emergence of adverse behaviors, as much as 6 to 12 months on average. 20 , 21 Significant side effects include gastrointestinal symptoms, dizziness, vertigo, fatigue, insomnia, hallucinations, bradycardia, syncope, and muscle cramps. 15

Donepezil is a reversible non-competitive acetylcholinesterase inhibitor shown to affect cognitive function, activities of daily living, and global clinical status. Benefits for the 10 mg dose appear marginally larger than for the 5 mg dose. A larger 23-mg dose form is available, with disputed clinical advantages. 20

Rivastigmine is a pseudo-irreversible inhibitor of acetylcholinesterase and butyrylcholinesterase and acts by binding to two active sites of acetylcholinesterase. It is called pseudo-irreversible because it dissociates slower than acetylcholinesterase. 20 Adverse effects of the oral preparation are significant, but the transdermal form is more tolerable for many patients, although it can cause dermatologic reactions. 22 , 23

Galantamine is a reversible competitive acetylcholinesterase inhibitor and modulator of nicotinic acetylcholine receptors. 15 Theoretically, this agent will have greater effect in areas of the brain with low levels of acetylcholine. 24 Its effects are similar to those of the other cholinesterase inhibitors. 24

NMDA Receptor Antagonist

Overstimulation of glutamatergic activity in the brain results in an excitotoxic overload of calcium flux into neurons through N-methyl-D-aspartate (NMDA) receptor ion channels. 25 , 26 Excitotoxicity leads to a gradual loss of synaptic function and eventual neurodegeneration, correlating with the progressive decline in cognition and the pathological anatomy seen in AD. 27 The NMDA receptor plays a critical role in glutamate synaptic transmission and in synaptic plasticity, thought to underlie learning and memory. 28 Memantine, a low-affinity NMDA receptor antagonist, modulates NMDA receptors to reduce glutamate-induced excitotoxicity and is thought to palliate cognitive decline associated with AD in this way. 27 , 28 Memantine is FDA-indicated for moderate to severe AD. 29 It has been shown to improve activities of daily living scores, global function assessment scores, and stage of dementia assessment scores. 30 , 31 It has also been suggested that it can be efficacious in reducing delusions, agitation/aggression, disinhibition, and diurnal rhythm disturbances. 32 Although benefit is clear, its magnitude is modest. 31 It is available as immediate and extended-release formulations, and as part of a combination pill with donepezil. 15 The combination of a cholinesterase inhibitor with memantine appears to have synergistic benefits so it is a standard practice in the treatment of moderate to severe AD. 33

Emerging Treatments

The search for disease-modifying AD therapies has led to the development of medications which target the pathologic forms of amyloid beta (Aβ) protein and tau protein associated with this disease. 34 The amyloid cascade hypothesis proposes that toxic forms of Aβ protein leads to neuronal death and synaptic dysfunction. Aβ pathology is an early finding in the disease. 34 , 35 The tau pathology has been shown to correlate more specifically with the progression of cognitive impairment. 36 , 37

Targeting Amyloid Pathology

The neurodegenerative effects of AD are attributed in part to the effects of beta amyloid and hyperphosphorylated tau, though newer theories raise additional possibilities. Amyloid plaques and tau-containing neurofibrillary tangles remain necessary for a pathological diagnosis of AD. 38 Several familial forms of AD have been linked to genetic mutations which alter the production of amyloid. CSF biomarker studies have also shown that Aβ42 peptides decline one to two decades prior to onset of symptoms in AD. 39 Although insoluble aggregates and soluble dimers of amyloid have been demonstrated to cause synaptic toxicity, the soluble aggregates are considered to correlate better with symptoms of AD and disease severity. 40

Therapeutic agents have been developed to reduce different forms of pathologic Aβ, interrupt Aβ aggregation, or increase Aβ clearance from the CNS. Many tested agents, however, have failed to demonstrate efficacy and some have even caused worsening of cognitive or physical symptoms, raising questions about the amyloid hypothesis. 41 Newer research techniques seek to improve drug evaluation by assuring that adequate measures are used and appropriate subjects enrolled in clinical trials. 42

Passive Immunotherapeutics

Following the early failure of a vaccine intended to develop a beneficial immune response in persons with AD, researchers developed passive immunotherapeutic agents: monoclonal antibody solutions created in biological systems for infusion into human subjects. 43 The objective is to reduce peripheral and central effects of Aβ42. 44 Several passive immunotherapeutic agents have failed clinical trials, but others remain in testing.

Aducanumab (BIIB037) is a human anti-Aβ monoclonal antibody that selectively targets aggregated forms of Aβ, including soluble oligomers and insoluble fibrils. Given as an infusion, aducanumab enters the central nervous system and decreases Aβ in prodromal or mild AD with Aβ PET-confirmed pathology, in a time and dose-dependent manner. Significant plaque reduction has been demonstrated. The main safety finding has been dose-related amyloid-related imaging abnormalities – edema/effusion (ARIA-E) which are more common among Apo-E4 carriers. In subjects who received the highest dose of 10 mg/kg, researchers reported a significant decline in the progression of cognitive impairment (on the CDR-Sum of Boxes). 45 In June of 2021, aducanumab was approved by the FDA for treatment of AD with the stipulation that a phase IV trial carefully assess its efficacy and safety. Subsequently, amidst some controversy about the accelerated approval process which occurred despite limited evidence of treatment benefit, the FDA revised the medication’s indication to target its use toward AD-related mild cognitive impairment or mild dementia.

Lecanemab (BAN2401) is a humanized IgG1 version of a mouse monoclonal antibody which selectively binds to large soluble Aβ protofibrils. Lecanemab has been shown to slow cognitive decline, increase CSF levels of Aβ (which drop in AD), and reduce total tau levels 46 but further validation of current findings is needed to address concerns about the methodology of the initial studies. Three clinical trials are currently in progress, looking at efficacy and safety among early AD subjects ( {"type":"clinical-trial","attrs":{"text":"NCT03887455","term_id":"NCT03887455"}} NCT03887455 ); efficacy and safety among early preclinical and preclinical AD subjects with early and intermediate amyloid ( {"type":"clinical-trial","attrs":{"text":"NCT04468659","term_id":"NCT04468659"}} NCT04468659 ); and safety, efficacy, and tolerability of different dose levels among early AD patients ( {"type":"clinical-trial","attrs":{"text":"NCT01767311","term_id":"NCT01767311"}} NCT01767311 ).

Donanemab (LY3002813) is an immunoglobulin directed towards a molecular target present only in brain amyloid plaques. In a phase II trial among early AD subjects, there was some improvement in composite cognition scores and ability to do activities of daily living (ADLs), but secondary outcomes did not show a significant difference. ARIA-E were observed but were noted to be asymptomatic. 47 A dose escalation study of single and multiple doses explored safety and tolerability and showed 40-50% amyloid reduction and 90% of subjects developed drug antibodies at three months after a single dose. 48

Gantenerumab, an additional monoclonal antibody in testing, has a 20-fold higher affinity for Aβ oligomers than monomers. 49 The earlier phase II trial was terminated for futility but there were dose-dependent effects observed indicating that higher doses may be necessary for efficacy. 50 An analysis of a PET sub-study suggests that at higher doses, there is a robust reduction of amyloid at two years. 51 There are currently ongoing trials evaluating pharmacodynamics of subcutaneous administration ( {"type":"clinical-trial","attrs":{"text":"NCT04592341","term_id":"NCT04592341"}} NCT04592341 ); safety and tolerability of long-term administration ( {"type":"clinical-trial","attrs":{"text":"NCT04339413","term_id":"NCT04339413"}} NCT04339413 ); safety and efficacy among early AD subjects ( {"type":"clinical-trial","attrs":{"text":"NCT03443973","term_id":"NCT03443973"}} NCT03443973 , {"type":"clinical-trial","attrs":{"text":"NCT03444870","term_id":"NCT03444870"}} NCT03444870 ); and safety, tolerability, biomarker, and cognitive efficacy among genetic early onset AD ( {"type":"clinical-trial","attrs":{"text":"NCT01760005","term_id":"NCT01760005"}} NCT01760005 ).

Crenezumab is a monoclonal antibody which binds to monomers and aggregated forms of Aβ with a 10-fold higher affinity for oligomers. 52 Earlier clinical trials did not meet clinical endpoints but there was note of a reduction in clinical decline in the higher dose group, as with gantenerumab. 53 Ongoing trials currently are evaluating crenezumab and its effect on tau burden among presenelin mutation carriers and noncarriers ( {"type":"clinical-trial","attrs":{"text":"NCT03977584","term_id":"NCT03977584"}} NCT03977584 ) and efficacy among preclinical AD ( {"type":"clinical-trial","attrs":{"text":"NCT01998841","term_id":"NCT01998841"}} NCT01998841 ).

BACE Inhibitors

β-site amyloid precursor protein cleaving enzyme (BACE) is an enzyme which performs the initial step in Aβ formation. 41 Several agents have been developed to block BACE activity in order to reduce Aβ accumulation.

Clinical failures of BACE inhibitors among persons with mild to moderate AD and prodromal AD have occurred with lanabecestat (AZD3293, LY3314814), atabecestat (JNJ-54861911), and verbecestat (MK8931). Elenbecestat (CNP520) was the last remaining BACE inhibitor evaluated to potentially slow down the onset and progression of clinical symptoms associated with AD ( {"type":"clinical-trial","attrs":{"text":"NCT02565511","term_id":"NCT02565511"}} NCT02565511 ). The trial was discontinued for safety concerns. 54

BACE inhibitors are successful in inhibiting Aβ formation but they have not been shown to produce cognitive, clinical, or functional benefit in large randomized controlled trials (RCT). Indeed, several BACE inhibitors were found to be poorly tolerated and some of them failed also in patients with prodromal AD. To some investigators, the failure of BACE inhibitors casts doubt on the value of blocking the formation of toxic Aβ in persons with AD. 55

Anti-Aggregation Agents

Another approach to interfering with the amyloid cascade is to block the aggregation of Aβ into oligomers and fibrils into amyloid plaques which may trigger the synaptic dysfunction and neuronal loss in AD. The soluble oligomers are considered the pathogenic form of Aβ associated with neurodegeneration. 56

Scyllo -Inositol (ELND005) has been shown to neutralize toxic effects of Aβ oligomers, including amelioration of oligomer-induced synaptic loss. 57 It is also thought to directly affect both Aβ clearance and myo-inositol regulation to improve cognitive function. 58 Its efficacy outcomes in mild to moderate AD, however, have not been found to be significant. 59 No ongoing trials are addressing its effect on earlier AD stages.

ALZ-801 is an improved prodrug of tramiprosate thought to inhibit the formation of amyloid oligomers without plaque interaction. 60 , 61 It selectively blocks the formation of Aβ oligomers with some clinical efficacy among high risk APOE carriers at a high dose and a dose dependent preservation of hippocampal volume. This is an oral agent which has been shown to have adequate CNS penetration. 60 , 62 Ongoing trials are looking into the effect of ALZ-801 on biomarkers ( {"type":"clinical-trial","attrs":{"text":"NCT04693520","term_id":"NCT04693520"}} NCT04693520 ) and efficacy and safety ( {"type":"clinical-trial","attrs":{"text":"NCT04770220","term_id":"NCT04770220"}} NCT04770220 ), both in APOE carriers.

Tau Directed Therapies

The lack of clear efficacy of amyloid-based therapeutics has led investigators to explore other upstream pathologic processes involving other targets. 46 Tau, a microtubule binding protein which forms neurofibrillary tangles (NFTs), is another histopathologic hallmark which characterizes AD. The accumulation of tau has been found to correlate more closely with severity of dementia than does amyloid load. There is evidence that Aβ accumulation can exacerbate tau pathology and vice versa. 63 Tau protein has also been found to at least partially mediate some of the toxic effects of Aβ leading to synapse loss, dendritic simplification, and eventual cell death in AD. 34 Initial approaches for tau-based therapies have focused on inhibition of kinases or tau aggregation or stabilization of microtubules. Most of these studies have been discontinued due to toxicity or lack of efficacy. 64 Current trials are focused on tau immunotherapies. Post-translational modifications and consequent loss of microtubule binding and tau misfolding lead to elevated levels of tau in the cytosol, making these processes viable targets. 34 , 64 Other significant targets include cytoskeletal disruption and impairments in protein degradation mechanisms. 64

Inhibition of Tau Aggregation

Methylene blue (MB) is a long established medication with broad utility in many conditions due to its role in promoting mitochondrial activity as well as mitigating neuroinflammation. 65 In animal models, MB has been shown to reduce Aβ levels and improved learning and memory thought to be mediated by an increase in Aβ clearance. 66 It has been found to reverse tau aggregation 67 and to promote clearance of tau filaments by inducing autophagy. 64 Although some efficacy was noted in improving cognition and reducing tau pathology in animal studies, it has not demonstrated significant benefits in human trials. This has been attributed to MB reducing the number of tau fibrils but increasing the number of granular tau oligomers, which are thought to be essential for neuronal death. 68

Curcumin is a natural plant product derived from turmeric root, with antioxidant and anti-inflammatory properties. It directly binds to β-pleated sheets of proteins and prevents aggregation. 69 Like MB, it has also been shown in animal studies to reduce tau and Aβ pathology and ameliorate cognitive deficits. 64 Previous trials have not shown any significant cognitive effects. 70 A recent trial involving a small population showed only modest results ( {"type":"clinical-trial","attrs":{"text":"NCT01383161","term_id":"NCT01383161"}} NCT01383161 ). The clinical development of curcumin as a therapeutic agent has been hindered by concern about bioavailability, poor water solubility at neutral or acidic pH, instability at basic pH, and rapid intestinal and first pass glucuronidation. 69

Post Translational Modifications

Protein phosphatase 2A (PP2A) is a protein that regulates signaling pathways. Sodium selenate is an antitumor agent which has been found to be a potent PP2A activator and reduces phosphoprylation of tau in animal studies in TBI 71 and AD. 72 In a phase IIa trial, 73 it was found to be safe and well-tolerated but there were no subsequent efficacy trials. A recent trial utilized sodium selenate as an oral supplement to potentially slow down neurodegeneration, based on the hypothesis that insufficient selenium supply to antioxidant enzymes may contribute to AD pathophysiology. 74

CDK5 inhibitors (flavopiridol and roscovitin) were developed primarily in oncology to prevent cell death. They compete with ATP for binding with CDK5, resulting in reduced activation of this kinase. 75 They have not been tested for neurodegenerative diseases although it has been thought that cell cycle progression and/or mitosis may be valid targets for AD. 76

Glycogen synthase kinase (GSK) 3β is highly expressed in the brain and has been implicated in tau phosphorylation. It is considered an important drug target due to its high specificity as a substrate. 77 Tideglusib is an irreversible GSK3β that does not compete with ATP. A phase II trial on mild AD subjects, however, showed tideglusib to have no clinical benefit. 78 An additional phase II trial showed no benefit to subjects with progressive supranuclear palsy (PSP). Lithium is another inhibitor of GSK3. Studies among patients with MCI and AD have been limited, but a reduction in phospho-tau levels were noted and one study showed stabilization of cognitive symptoms. In a meta-analysis of 5 RCTs on GSK 3 inhibitors, however (two trials on Tideglusib and three trials on lithium), GSK3 inhibitors were deemed ineffective in treating MCI and AD as the studies were found to be too small. 79

Microtubule Stabilization

Compounds that stabilize microtubules may have therapeutic potential as the disruption of microtubule-based transport mechanisms contributes to synaptic degeneration. 80

Epithilone D (BMS-241027) is a small molecule able to penetrate the blood brain barrier. It was found to increase microtubule numbers and reduce the number of axons in animal studies. 34 There was also note of improved cognition and reduced tau pathology in mouse models but the phase I clinical trial was discontinued in 2013 (NT 01492374).

TPI 287 (Abeotaxane) is another microtubule stabilizing compound which was initially found to reduce hyperphosphorylated tau in the brain and to improve performance in animal models. It was subsequently trialed in patients with AD, progressive supranuclear palsy, and corticobasal syndrome. Severe hypersensitivity reactions, however, were observed in AD patients and clinical worsening and biomarker changes were seen in PSP and corticobasal syndrome. 81

Davenutide (NAPVSIPQ) is an 8-amino acid peptide derived from activity-dependent neuroprotective protein (ADNP). ADNP deficiency is thought to lead to tauopathies. 34 In animal models, davenutide was found to play a positive role in attenuating Aβ1-42-induced impairments in spatial memory and synaptic plasticity. 82 It is thought to stabilize microtubules and reduce hyperphosphorylated tau levels. 83 In a phase I trial, it was found to be well tolerated given intranasally among patients with MCI. Although there was note of potential efficacy in two tests of memory and attention, the study failed to detect a statistically significant difference on composite cognitive memory scores. 84

Tau Immunization Approaches

Active and passive immunization against phospho-tau peptides have the potential to modulate tau pathology. Antibodies pass through the blood brain barrier and enter the brain. 34

One candidate active vaccine is AADvac1 which targets nonphsophorylated tau. In its phase I trial, patients were given 3 doses of the vaccine. Almost all developed an IgG immune response. The most common adverse effect was injection site reactions. There were no cases of meningoencephalitis or vasogenic edema after administration. 85 A follow-up study was done on the same population and given three more doses plus two boosters with the primary objective being the determination of long-term safety. The most common adverse event was again local injection site reaction. Again, no cases of meningoencephalitis or vasogenic edema were observed. New micro-hemorrhages were observed in one Apo E4 homozygote. IgG titers did regress over time indicating the need for more frequent boosters. A tendency towards slower atrophy on MRI was observed and there seems to be a slower decline on cognitive assessment in those with higher titers. 86

ACI-35 is another active vaccine that targets phosphorylated tau. 87 In animal studies, there was note of reduction in soluble and insoluble tau. The vaccine also did not induce marked CNS inflammation despite the multiple epitopes. 75 , 88 A phase Ib-IIa trial is currently ongoing to determine safety, tolerability, and immunogenicity. It is expected to complete by 2023 ( {"type":"clinical-trial","attrs":{"text":"NCT04445831","term_id":"NCT04445831"}} NCT04445831 ).

Passive Immunization

Passive immunization potentially provides a possible solution to concerns about immunologic side effects with active immunization. There is greater specificity for the target epitope and the effects of immunization are likely to be transient. 75 Anti-tau antibodies have been shown to enter neurons and bind to a cytosolic receptor which eventually leads to proteosomal degradation of the complex and inhibition of intracellular tau aggregation. 89 – 91

RG7345 (RO6926496) is an antibody that recognizes tau phosphorylated at Ser422. Tau phosphorylated at this site is considered pathological. 92 It has been shown to enter neurons and reduce tau pathology, but this trial was discontinued by Roche likely due to some pharmacokinetic issues ( {"type":"clinical-trial","attrs":{"text":"NCT02281786","term_id":"NCT02281786"}} NCT02281786 ). No apparent safety or efficacy concerns. 75

Gosuranemab (BIIB092) is an IgG4 monoclonal that recognizes a site in the N-terminal region. It was found safe and well-tolerated with no adverse effects in the low and moderate dosage arms. Unbound N-terminal tau in the CSF was reduced but AD biomarkers were not reduced. 93 , 94 There is currently a phase II trial for those with MCI and mild AD assessing safety and tolerability plus immunogenicity and efficacy of multiple doses in slowing cognitive and functional impairment (NTC 03352557). Expected completion of the study is in 2024.

Tilavonemab (ABBV-8E12, C2N-8E12) is an IgG4 antibody intended to work extracellularly. In vitro, this blocks uptake and inhibits seeded tau aggregation. 63 No adverse reactions were reported among PSP patients in phase I. Phase II trials included both PSP patients and AD patients. The trials for PSP were discontinued. The trials for AD patients, however, are still ongoing with the extension study expected to conclude July 2021 ( {"type":"clinical-trial","attrs":{"text":"NCT02880956","term_id":"NCT02880956"}} NCT02880956 , {"type":"clinical-trial","attrs":{"text":"NCT03712787","term_id":"NCT03712787"}} NCT03712787 ).

Zagotenemab (LY3303560) is a humanized version of the IgG1 antibody MC-1 with its primary epitope located in the N-terminal region. 63 The initial phase I trial evaluated safety, tolerability, and pharmacokinetics in healthy individuals ( {"type":"clinical-trial","attrs":{"text":"NCT02754830","term_id":"NCT02754830"}} NCT02754830 ) and among those with mild to moderate AD ( {"type":"clinical-trial","attrs":{"text":"NCT 03019536","term_id":"NCT03019536"}} NCT 03019536 ). A phase II trial is underway evaluating efficacy among early symptomatic AD patients ( {"type":"clinical-trial","attrs":{"text":"NCT03518073","term_id":"NCT03518073"}} NCT03518073 ). Study completion is estimated to be in October 2021.

Semorinemab (RO7105705, MTAU9937A) is an antibody designed to bind and intercept tau in the extracellular brain, blocking cell-to-cell spread. 63 Initial phase I results showed no dose-limiting toxicities and no serious adverse effects. The antibody was also detected in CSF. 95 , 96 The phase II trial on prodromal to mild AD was completed January 2021 and primary endpoints were safety measures and CDR-Sum of Boxes (NCT3289143). The phase II trial on moderate AD is still ongoing at this time ( {"type":"clinical-trial","attrs":{"text":"NCT03828747","term_id":"NCT03828747"}} NCT03828747 ).

BIIB076 (NI-105, 6C5 hulgG1/I) is a human IgG1 recombinant monoclonal antibody. Intravenous and subcutaneous forms were assessed up to 26 times highest predicted dose. Drug levels were measured in the serum and tau levels were measured in the CSF. No adverse effects noted. 92 The phase I trial on ascending doses given to healthy volunteers and AD patients monitored adverse events as well as pharmacokinetics ( {"type":"clinical-trial","attrs":{"text":"NCT03056729","term_id":"NCT03056729"}} NCT03056729 ). This study was completed in March 2020 but no results have been posted or published.

JNJ-63733657 is an IgG1 antibody with affinity for the paired helical filament. 63 It recognizes an epitope in the mid region of tau. The phase I trial of ascending doses in healthy participants found this antibody to be generally safe and well-tolerated ( {"type":"clinical-trial","attrs":{"text":"NCT03689153","term_id":"NCT03689153"}} NCT03689153 ). A second phase I ascending dose study was completed in December 2019 ( {"type":"clinical-trial","attrs":{"text":"NCT03375697","term_id":"NCT03375697"}} NCT03375697 ) with no results posted yet. A phase II trial on efficacy and safety in early AD is currently ongoing and expected to complete by March 2025 ( {"type":"clinical-trial","attrs":{"text":"NCT04619420","term_id":"NCT04619420"}} NCT04619420 ).

Bepranemab (UCB0107) is likely an IgG4 (Alzforum.org 2019b). It also binds to the mid-region of tau, like JNJ-63733657. 92 Two phase I clinical trials were completed in 2018 and 2019 ( {"type":"clinical-trial","attrs":{"text":"NCT03464227","term_id":"NCT03464227"}} NCT03464227 , {"type":"clinical-trial","attrs":{"text":"NCT 03605082","term_id":"NCT03605082"}} NCT 03605082 ). There are two other phase I trials involving safety and tolerability in PSP patients. The phase II study involving AD patients is not yet recruiting at this time ( {"type":"clinical-trial","attrs":{"text":"NCT04867616","term_id":"NCT04867616"}} NCT04867616 ).

Treatment of Noncognitive Symptoms of Dementia

Noncognitive symptoms of dementia (NCSD) are symptoms that contribute significantly to functional decline, caregiver burden, and eventually, the decision for institutionalization. 97 Early treatment, therefore, is essential. These symptoms present intermittently or persistently. The most prevalent and stable is apathy. Other symptoms include depression, anxiety, irritability, and psychosis. The four key symptoms of wandering, aggression/agitation, delusions, and irritability have been found to be associated with more severe illness. 98 Nonpharmacologic approaches are designated as the first line approach for treatment. Pharmacological interventions have been prescribed as well and are often seen as more expedient, though with variable benefit. Their use is complicated by adverse effects, dose-dependent increased mortality, and limited supporting evidence. 99 – 101 The concern for risks associated particularly with antipsychotic use has resulted in boxed warnings by the FDA for atypical and conventional antipsychotics. 99 Furthermore, none of these pharmacologic agents have been indicated for this use by the FDA so their use is off-label. The American Psychiatric Association’s (APA) guideline on antipsychotic use to treat agitation or psychosis in dementia recommends that antipsychotics be used when symptoms of agitation or psychosis are severe, dangerous, or cause significant distress to the patient, titrating doses only to the minimum effective dose, and to taper and withdraw once an adequate response is achieved. 102 Ultimately, among the antipsychotics, there is no single agent that is able to provide both efficacy and safety emphasizing the need to individualize treatment based on a careful balance of benefits and adverse effects. 103

Serotonergic antidepressants offer a more promising pharmacologic approach to the treatment of NCSD. Citalopram, a selective serotonin reuptake inhibitor (SSRI), has been shown to have some efficacy for agitation in dementia. 104 In a placebo controlled, double blind RCT, citalopram was found to meaningfully reduce agitation and caregiver distress. Some associated cognitive decline and cardiac side effects (QTc prolongation), however, hamper its long-term use. 105 , 106 Results suggest that citalopram needs to be given at least nine weeks to allow enough time for a full response. 107 The evidence for its use for this indication, nevertheless, remains compelling, and potentially could be a class effect for all SSRIs. 108 , 109

Some additional novel and/or repositioned agents are being studied as treatments for agitation in dementia. 99 Four will be discussed here.

Dextromethorphan is a sigma-1 receptor agonist which has some mood-modulating properties. 110 It is also a low affinity NMDA antagonist, a serotonin and norepinephrine reuptake inhibitor, a histamine H1 receptor agonist, and a neuronal nicotinic alpha-3 beta-4 receptor antagonist. 99 , 111 Quinidine and deuteration appear to prolong dextromethorphan's plasma half-life, reduce first pass metabolism, and facilitate brain penetration. 112 Deuterated (d6)-dextromethorphan/quinidine (AVP-786) is currently being evaluated as a treatment for agitation in people with AD. 113 Two phase III trials evaluating efficacy, safety, and tolerability have been completed, {"type":"clinical-trial","attrs":{"text":"NCT02442765","term_id":"NCT02442765"}} NCT02442765 (February 2020) and {"type":"clinical-trial","attrs":{"text":"NCT02442778","term_id":"NCT02442778"}} NCT02442778 (August 2020). The two trials reportedly showed mixed findings and failed to confirm the anti-agitation effect, probably due to differences in study design. 113 , 114 Four ongoing trials are currently recruiting subjects ( {"type":"clinical-trial","attrs":{"text":"NCT04464564","term_id":"NCT04464564"}} NCT04464564 , {"type":"clinical-trial","attrs":{"text":"NCT04408755","term_id":"NCT04408755"}} NCT04408755 , {"type":"clinical-trial","attrs":{"text":"NCT03393520","term_id":"NCT03393520"}} NCT03393520 , {"type":"clinical-trial","attrs":{"text":"NCT02446132","term_id":"NCT02446132"}} NCT02446132 ).

Cannabinoids like tetrahydrocannabinol (THC) are agonists at cannabinoid receptors 1 and 2. Cannabinoid receptor activity has behavioral effects and modulates of neuroinflammation and oxidative stress, so these receptors are a potential drug target. 115 Nabilone, a synthetic oral THC which is a partial agonist at CB1/2 receptors, is thought to potentially have some efficacy for agitation in moderate to severe AD. 116 In a recent RCT evaluating nabilone efficacy and safety, it was found to be effective for agitation, although with some dose-related sedation. Observational studies have also shown promising results, particularly in cases with refractory symptoms. 117 Two of three recent meta-analyses were unable to show conclusive results for cannabinoid efficacy in the treatment of agitation or aggression. 118 , 119 The most recent meta-analysis, however, was able to show significant improvement in different NPS instruments and efficacy was associated with baseline dementia severity and dose. 120

Brexpiprazole is a partial receptor agonist (D3, D2, 5-HT1A) and receptor antagonist (5HT2A, alpha1B/2C) which has been shown in phase II trials to be effective for agitation in patients with AD with improved safety profile compared with other second generation antipsychotics. 121 , 122 Of note, brexpiprazole on a slow titration schedule, had higher efficacy and tolerability. There are several ongoing phase III trials ( {"type":"clinical-trial","attrs":{"text":"NCT03594123","term_id":"NCT03594123"}} NCT03594123 , {"type":"clinical-trial","attrs":{"text":"NCT03724942","term_id":"NCT03724942"}} NCT03724942 , {"type":"clinical-trial","attrs":{"text":"NCT03548584","term_id":"NCT03548584"}} NCT03548584 , {"type":"clinical-trial","attrs":{"text":"NCT03620981","term_id":"NCT03620981"}} NCT03620981 ) to evaluate long term use, safety, efficacy.

Prazosin is a centrally acting alpha 1 receptor antagonist indicated for hypertension and symptoms of benign prostatic hypertrophy. It readily crosses the blood brain barrier and in a small double-blind trial, it has shown efficacy for agitation among patients with moderate AD using a flexible dosing titration up to a maximum of 6 mg TDD. It was also well tolerated. 123 A completed but unpublished second trial looked into the efficacy of a fixed dose of 4 mg twice daily given for a longer period of study ( {"type":"clinical-trial","attrs":{"text":"NCT01126099","term_id":"NCT01126099"}} NCT01126099 ). A phase III trial is ongoing to evaluate efficacy and dose titration ( {"type":"clinical-trial","attrs":{"text":"NCT03710642","term_id":"NCT03710642"}} NCT03710642 ).

Mirtazapine ( {"type":"clinical-trial","attrs":{"text":"NCT03031184","term_id":"NCT03031184"}} NCT03031184 , completed 06/2020) and lithium ( {"type":"clinical-trial","attrs":{"text":"NCT02129348","term_id":"NCT02129348"}} NCT02129348 , completed 01/2020) have also been evaluated for agitation in AD but results have yet to be published. Escitalopram is being reevaluated for agitation as well ( {"type":"clinical-trial","attrs":{"text":"NCT03108846","term_id":"NCT03108846"}} NCT03108846 , ongoing recruitment). 99

Public Health Implications

We may be standing at the brink of a new era of AD diagnosis and treatment, a development which will have significant public health implications. If early detection becomes a reality, the detected individuals will burden an already stressed system by new care needs. Resources may need to be directed at increasing public awareness of the health implications of dementia. Dissemination of information about the effectiveness of treatments will be needed as well as work to remove the stigma associated with mental health disorders and the stigma of being treated for them. Furthermore, overall access to mental health services needs to be improved. 124 , 125

The current advances should inspire hope, however, that many cases of dementia can be delayed or prevented as a result of earlier detection, lifestyle modifications, and new treatment approaches. We are on the verge of a paradigm shift in the way we approach AD.

Open access
Published: 03 July 2024

Plasma biomarkers of amyloid, tau, axonal, and neuroinflammation pathologies in dementia with Lewy bodies

Agathe Vrillon 1 , 2 , 3 ,
Olivier Bousiges 4 , 5 ,
Karl Götze 2 ,
Catherine Demuynck 6 ,
Candice Muller 6 ,
Alix Ravier 6 ,
Benoît Schorr 6 ,
Nathalie Philippi 5 , 6 , 7 ,
Claire Hourregue 1 ,
Emmanuel Cognat 1 , 2 ,
Julien Dumurgier 1 ,
Matthieu Lilamand 1 ,
Benjamin Cretin 5 , 6 , 7 ,
Frédéric Blanc 5 , 6 , 7 &
Claire Paquet 1 , 2

Alzheimer's Research & Therapy volume 16 , Article number: 146 ( 2024 ) Cite this article

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Increasing evidence supports the use of plasma biomarkers of amyloid, tau, neurodegeneration, and neuroinflammation for diagnosis of dementia. However, their performance for positive and differential diagnosis of dementia with Lewy bodies (DLB) in clinical settings is still uncertain.

We conducted a retrospective biomarker study in two tertiary memory centers, Paris Lariboisière and CM2RR Strasbourg, France, enrolling patients with DLB ( n = 104), Alzheimer’s disease (AD, n = 76), and neurological controls (NC, n = 27). Measured biomarkers included plasma Aβ40/Aβ42 ratio, p-tau181, NfL, and GFAP using SIMOA and plasma YKL-40 and sTREM2 using ELISA. DLB patients with available CSF analysis ( n = 90) were stratified according to their CSF Aβ profile.

DLB patients displayed modified plasma Aβ ratio, p-tau181, and GFAP levels compared with NC and modified plasma Aβ ratio, p-tau181, GFAP, NfL, and sTREM2 levels compared with AD patients. Plasma p-tau181 best differentiated DLB from AD patients (ROC analysis, area under the curve [AUC] = 0.80) and NC (AUC = 0.78), and combining biomarkers did not improve diagnosis performance. Plasma p-tau181 was the best standalone biomarker to differentiate amyloid-positive from amyloid-negative DLB cases (AUC = 0.75) and was associated with cognitive status in the DLB group. Combining plasma Aβ ratio, p-tau181 and NfL increased performance to identify amyloid copathology (AUC = 0.79). Principal component analysis identified different segregation patterns of biomarkers in the DLB and AD groups.

Conclusions

Amyloid, tau, neurodegeneration and neuroinflammation plasma biomarkers are modified in DLB, albeit with moderate diagnosis performance. Plasma p-tau181 can contribute to identify Aβ copathology in DLB.

Introduction

Dementia with Lewy bodies (DLB) is evaluated to be the third cause of dementia after Alzheimer’s disease (AD) and vascular dementia. DLB is characterized by a poorer prognosis, higher healthcare costs and caregiver burden, and a greater impact on quality of life compared with AD [ 1 , 2 ]. Yet, therapeutic research in DLB has long remained a poorly invested field, and there are no disease-specific treatments currently approved by the European Medicines Agency. However, this field has known some recent expansion, with more than 30 ongoing trials in 2022, including evaluations of disease modifier molecules [ 3 ]. In this context, achieving early and reliable diagnosis should be a priority.

Patients with DLB present with a wide range of cognitive, psychiatric, motor, and dysautonomic symptoms that can vary in-between patients and over time within individuals. The currently used diagnosis criteria, defined by McKeith et al., include imaging and electrophysiological supportive biomarkers in association with core clinical features [ 4 ]. However, no specific markers of pathology are included.

DLB is characterized by the presence of Lewy bodies formed primarily of alpha-synuclein. Amyloid-beta (Aβ) plaques, and to a lesser extent hyperphosphorylated tau (p-tau) tangles, may also be present [ 5 , 6 ]. Cerebral and peripheral inflammation has been demonstrated to be contributing mechanisms, especially at the early stages of the disease [ 7 ]. Specific blood-based assays would benefit diagnostic in clinical practice and facilitate clinical trials, as non-invasive and scalable. Real-time quaking-induced conversion (RT-QuIC) assays are showing high sensitivity and specificity to detect alpha-synuclein in cerebrospinal fluid (CSF) in DLB and Parkinson’s disease (PD [ 8 , 9 , 10 ]. However, they still require further validation, especially in plasma [ 11 ]. Interestingly, number of amyloid and tau plasma biomarkers, as well as axonal and neuroinflammatory markers have been studied in DLB and appear modified. Plasma p-tau has demonstrated good accuracy to identify an AD copathology commonly present in DLB [ 12 , 13 , 14 ]. Indeed, more than half of patients with DLB demonstrate coexisting amyloid lesions, that impact clinical presentation and disease progression [ 5 , 6 ]. Several plasma p-tau isoforms, including plasma p-tau181, p-tau231, and p-tau217, were reported to be higher in DLB patients with CSF or PET evidence of amyloid copathology [ 12 , 14 , 15 ]. Plasma NfL and glial fibrillary acidic protein (GFAP) levels were found to be higher in Lewy body dementia (DLB and Parkinson’s disease dementia) compared to controls but lower compared to AD [ 16 , 17 ]. Glial markers, including soluble triggering receptor expressed on myeloid cells 2 (sTREM2) and human chitinase-3 (YKL-40) have shown inconsistent modifications in DLB, both in CSF and in plasma, but nevertheless suggesting different glial activation patterns than in AD [ 18 , 19 ].

While being nonspecific and considering the presence of neuroinflammation and the possible co-existence of AD pathology, our question is could those existing plasma biomarkers be useful in DLB diagnosis? The aim of this study was to investigate 6 plasma biomarkers, as standalone markers or in combinations to evaluate their usefulness in DLB diagnosis, in comparison to AD patients and control individuals.

In a cross-sectional retrospective bicentric study, we analyzed samples from the Cognitive Neurology Center, Lariboisière Hospital, Université Paris Cité, Paris, France, and the Memory Clinic (CM2R) of Strasbourg, Alsace, France from 2012 to 2021. The cohort consecutively included 27 neurological control subjects (Paris: n = 19, Strasbourg: n = 8), 104 patients with DLB (Paris: n = 56, Strasbourg: n = 48), and 76 patients with AD (Paris: n = 71, Strasbourg: n = 5).

All included subjects underwent comprehensive neurological examination, neuropsychological evaluation, and brain imaging. All controls and AD subjects underwent lumbar puncture as well as 87% (90/104) of DLB patients. Consensus diagnoses were validated after a multidisciplinary review of cases, by neurologists, neuropsychologists, neuroradiologists, and biologists. All DLB patients fulfilled the most recent revised diagnosis criteria for probable DLB, established by McKeith et al. [ 4 ]. Diagnosis of AD, including MCI and dementia patients, was made according to Albert’s et al. criteria and Dubois et al. criteria [ 20 , 21 ]. All patients with AD displayed a CSF amyloid-positive profile. Neurological controls were individuals seen at the clinic but for whom, no evidence of neurocognitive disease was found; they presented with normative or sub-normative cognitive testing, normal morphological brain imaging, and normal CSF profile. Those subjects included some participants in observational research studies and individuals with subjective cognitive complaints in the context of minor depressive symptoms, sleep disorders, chronic pain or chronic fatigue, or systemic disorders. The cognitive status was assessed with the mini-mental state evaluation (MMSE).

Plasma biomarkers measurements

Plasma samples were obtained through venipuncture, in the morning in fasting conditions, on the same day as CSF uptake. After a 20-minute centrifugation at 1,900 x g within 4 h, plasma was aliquoted in polypropylene tubes and stored at − 80 °C until analysis.

All analyses were performed in Inserm U1144, Université Paris Cité, Paris, France.

Plasma Aβ40, Aβ42, NfL, and GFAP were measured with the Simoa Neurology 4-plex E kit from Quanterix®. Plasma p-tau181 was measured with the Simoa p-tau181 Advantage V2 assays also from Quanterix®. Samples were analyzed blinded in singlicate. All samples were above the threshold of quantification. All intra and inter coefficients of variations were below 10% (Aβ40: intraplate CV = 2.7%, interplate CV = 4.2%; Aβ42: intraplate CV = 1.2%, interplate CV;=3.4%; GFAP, intra plate CV = 9.9%, interplate CV = 6.0%; NfL, intraplate CV = 6.1%, interplate CV = 3.0%; p-tau181: intraplate CV = 9.5%, inter plate = 5.3% ).

Plasma sTREM2 and YKL-40 levels were measured using commercial ELISA kits from R&D System (respectively, #DY1828-05 and #DY2599), both validated for plasma measurements. Samples were run blinded in duplicates. Intra- and inter-coefficients of variations were respectively 7.1% and 10.7% for sTREM2 and 5.1% and 6.6% for plasma YKL-40.

Apolipoprotein E (APOE) genotype was determined through analysis of 2 single nucleotide variations (formerly single nucleotide polymorphisms, rs429358, and rs7412) using established standard polymerase chain reaction as described in Dumurgier et al. [ 22 ].

CSF AD biomarkers

CSF AD biomarkers analysis was available for all control subjects, AD patients, and 87% of DLB patients CSF was collected by standard lumbar puncture procedure. CSF samples were collected in polypropylene tubes for CSF AD biomarker measurements. In Paris cohort, CSF Aβ42, Aβ40, t-tau, and p-tau181 were measured by different assays across time, including Innotest Fujirebio® ( n = 30) and Elecsys Roche® for Aβ42, p-tau181 and t-tau and Innotest Fujirebio® for Aβ40 ( n = 101). In Strasbourg cohort, CSF Aβ42, Aβ40, t-Tau, and p-tau181 were measured with Innotest Fujirebio® for the largest part ( n = 58) and with Lumipulse Fujirebio® for n = 3 subjects. Assays and cut-offs are detailed in Supp. Table 1 .

Patients with available CSF AD biomarkers were classified according to the AT(N) classification [ 23 ].

Statistical analysis

Statistical analyses were conducted using SPSS® version 29.0 (IBM statistics) and Graphpad® Prism version 9.0 (GraphPad, San Diego, CA, USA). Continuous nonparametric data are presented as median (interquartile range) and parametric data as mean (standard deviation).

Age, MMSE, and levels of education were compared between diagnostic groups using Kruskall Wallis test and sex and APOE ɛ4 carriership using Chi-2 test. Plasma biomarker levels did not display a normal distribution and were log-transformed before analysis. Association of the biomarkers with age, sex, and APOE ɛ4 carriership was studied unadjusted (with Spearman’s correlation for age and chi-2 test for sex and APOE status) then adjusting for age, sex, and APOE status using linear regression.

One-way analysis of variance adjusted on age and sex with Tukey’s LSD post hoc analysis, adjusting for multiple comparisons, was used to assess biomarker level differences between the diagnostic groups. Effect sizes were estimated with Cohen’s d .

Receiver operating characteristic (ROC) analysis with area under the curve (AUC) calculation was obtained by performing logistic regression, including age and sex as covariates, to study the diagnosis performance of the plasma biomarkers. Combination of biomarkers were studied using logistic binary regression, in a stepwise backward elimination strategy based on Wald to identify the best combination for differentiation between diagnosis groups. Areas under the curve (AUCs) were compared with the Akaike information criterion (AIC).

The AD group was analyzed as two groups, AD-MCI and AD dementia, in secondary analyses.

To explore the association of our plasma biomarkers with amyloid copathology, we stratified DLB patients according to the AT scheme, dichotomizing on the A status defined by CSF Aβ42/Aβ40 ratio (A + versus A-), then by AT status (A + T + versus A-T-). The differences in plasma biomarker levels were studied using one-way analysis of variance adjusting on age and sex. Effect sizes were estimated using eta squared η 2 .

MMSE scores were transformed into the square root of the number of errors (√[30-MMSE]) to ensure normalcy of distribution [ 24 ]. The association of biomarkers with MMSE was studied using Spearman’s correlation and with linear regression adjusting on age, sex, and level of education.

Principal component analysis (PCA) was performed in the DLB and AD groups to explore the pattern of association between the different biomarkers. Outlier values, defined by a value > mean ± 3SD, were excluded for each biomarker before analysis. Kaiser–Meyer–Olkin Measure of Sampling Adequacy test and Bartlett’s Test of Sphericity were used to evaluate the suitability of the dataset. The number of components was determined by the number of eigenvalues greater than one. Variables with a loading factor > 0.4 or < − 0.4 were regarded as representative of the component.

The overall cohort’s demographic characteristics and plasma biomarker levels are presented in Table 1 , and by center in Supp. Table 2 . DLB and AD patients were significantly older than control individuals ( P < 0.001). We observed a higher percentage of males in the DLB group than in the AD and control groups ( P = 0.037). The AD group displayed more frequent APOE ɛ4 carriership than the DLB and NC groups ( P < 0.001). In the AD group, 97% ( n = 74) displayed a CSF A + T + profile and 3% ( n = 2) an A + T- profile. As a sensitivity analysis, the main analyses have been reproduced after the exclusion of the A + T- subjects and yielded similar results (Suppl. Figure 1 ). Additionally, the characteristics of AD-MCI and AD-dementia groups are presented in Supp. Table 3 .

Associations with age, sex, and APOE status are detailed in Supp. Table 4 . In the whole cohort, all plasma biomarkers were associated with age (β = 0.236–0.538, P ≤ 0.002) except for Aβ ratio (β=-0.042, P = 0.593) after adjustment on sex and APOE ɛ4 carriership. Plasma GFAP and YKL-40 levels were higher in females after adjustment on age and APOE status (GFAP: β = 0.258, P < 0.001; YKL-40, β = 0.198, P = 0.008). Plasma Aβ ratio, p-tau181, and sTREM2 levels were associated with APOE ɛ4 carriership in adjusted analysis (β = 0.165-0.228, P ≤ 0.028). Focusing on the DLB group, after adjustment for covariates, we found positive associations between age and plasma p-tau181, NfL, GFAP, and YKL-40 levels (β = 0.247–0.521, P ≤0.030) and between female sex and plasma GFAP levels (β = 0.259, P = 0.008). No association was found between any plasma marker and ApoE4 carriership, after adjustment for age and sex in the DLB group.

Correlations between biomarkers are displayed in Supp. Figure 2 . Focusing on DLB patients, plasma GFAP, p-tau181, and NfL showed significant associations ( r = 0.341–0.560, P < 0.0001 overall). Plasma YKL-40 and sTREM2 were significantly associated ( r = 0.284, P = 0.003), as well as with plasma NfL ( r = 0.406, P < 0.000 both). Plasma GFAP was the only marker significantly associated with the plasma Aβ ratio ( r =-0.325, P < 0.0001), though there was a tendency to association between the Aβ ratio and p-tau181 ( r =-0.185, P = 0.067).

Biomarkers levels across diagnosis groups

Plasma biomarker levels are displayed in Fig. 1 . Patients with DLB displayed lower levels of plasma Aβ ratio ( P = 0.037, d = 0.576) and higher p-tau181 ( P = 0.017, d = 0.644) and a tendency to higher GFAP levels ( P = 0.057, d = 0.057), compared to NC, after adjustment for age and sex. Additionally, patients with DLB displayed significantly lower levels of plasma p-tau181 ( P < 0.001, d = 1.11), NfL ( P = 0.037, d = 0.390), and GFAP ( P < 0.001, d = 0.685) compared with AD patients. DLB patients had higher levels of plasma sTREM2 compared with AD patients ( P = 0.022, d = 0.413). No difference was observed in plasma levels for YKL-40 between diagnostic groups, with or without adjustment. Plasma Aβ ratio levels were lower and p-tau181, GFAP, and NfL levels all higher in AD patients compared with controls, but not plasma sTREM2 and YKL-40.

Plasma biomarkers levels across diagnosis groups. Plasma biomarkers levels across diagnosis groups including a , Aβ ratio; b , p-tau181; c , NfL; d , GFAP; e , sTREM2; and f , YKL-40. P-values were obtained through one-way ANCOVA followed by post hoc Tukey’s test, adjusting for multiple comparisons. Significant differences ( P < 0.05) are reported. The effect size was determined using Cohen’s d . Boxplots display the median, IQR, and value for all participants

Looking at AD stages, plasma p-tau181 levels remained significantly higher in both AD-MCI and AD dementia groups compared with the DLB group (Supp. Figure 3 ). Plasma NfL and GFAP levels were higher and sTREM2 levels lower in the AD dementia group compared with the DLB groups, but did not differ between AD-MCI and DLB.

DLB diagnostic performance

To differentiate DLB from controls, our plasma biomarkers yielded moderate AUCs from 0.74 to 0.78, without significant differences between biomarkers (Fig. 2 a). Plasma p-tau181 yielded the highest AUC of 0.78 (95% CI 0.68–0.87). Combining biomarkers did not outperform p-tau-181 sole (Fig. 2 b).

Plasma biomarkers performance to identify DLB. ROC analysis: a , to compare single biomarkers performance to discriminate between DLB patients and NC; b , to compare biomarkers combination to discriminate between DLB and NC; c , to compare single biomarkers performance to discriminate between DLB and AD patients; d , to compare biomarkers combination to discriminate between DLB and AD patients. ROC analysis results are presented as AUC (95% CI). Combinations of biomarkers were selected through binary logistic regression with backward stepwise elimination, including age and sex as constant variables. a model including p-tau181 outperformed all other models (∂AIC > 4), b no significant difference in the model’s fit with the All markers model (∂AIC < 4).

To differentiate DLB from AD, plasma p-tau181 yielded the highest AUC (0.80) as a standalone biomarker and outperformed the other biomarkers (∂AIC > 4, Fig. 2 c). The optimal combination of markers was the association of plasma p-tau181 and YKL-40, that performed as well as the combination of all biomarkers (all biomarkers model, AUC = 0.84 versus plasma p-tau181 + plasma YKL-40, AUC = 0.83, ∂AIC < 4, Fig. 2 d).

To differentiate AD from controls, plasma p-tau181 had the best performance as a standalone biomarker (AUC = 0.92) and association with other biomarkers did not improve diagnosis performance (Supp. Table 5 ).

The diagnosis performance of the plasma biomarkers used individually was overall similar when analyzing separately AD-MCI and AD dementia cases (Supp. Figure 3 ). The combination of plasma p-tau181 and YKL-40 had the best performance to differentiate DLB patients from AD-MCI (AUC = 0.86, ∂AIC > 4 versus all biomarkers model [AUC = 0.88] and p-tau181 alone [AUC = 0.80]), with the best trade-off between the goodness of fit and parsimony. To distinguish DLB from AD dementia, the association of plasma Aβ ratio, p-tau181, and NfL (AUC = 0.85) was not inferior to the all biomarkers model (AUC = 0.87, ∂AIC < 4).

Identification of amyloid copathology in DLB

CSF analysis was available for 87% (90/104) of DLB patients (Table 1 ). According to the AT(N) classification, 24% of patients presented an AD CSF profile on the AD continuum, 12% being A + T- and 12% A + T+. A + DLB patients displayed higher concentrations of plasma p-tau 181 compared with A- DLB ( P = 0.011, η2 = 0.71) after adjustment on age and sex (Fig. 3 , a-f). A + T + patients displayed higher levels of plasma p-tau181 and NfL levels compared with A-T- DLB (respectively, P = 0.003, η2 = 0.131 and P = 0.036, η2 = 0.062, Fig. 3 , g-l).

Plasma biomarkers levels in relation to amyloid pathology in DLB patients. Plasma biomarkers levels across amyloid-negative (A-) DLB and amyloid-positive (A+) DLB patients including a , Aβ ratio; b , p-tau181; c , NfL; d , GFAP; e , sTREM2; f , YKL-40; and across A-T- DLB and A + T + DLB patients including: g , Aβ ratio; h , p-tau181; i , NfL; j , GFAP; k , sTREM2; l , YKL-40. For biomarker levels comparison, P-values were obtained through one-way ANCOVA adjusting for multiple comparisons. Significant differences ( P < 0.05) are reported in bold. The effect size was determined using η2. Boxplots display the median, IQR, and value for all participants

Plasma biomarkers identified A + DLB patients with overall moderate AUCs ranging from AUC = 0.64 to AUC = 0.75, as standalone biomarkers. Plasma p-tau181 displayed a higher AUC of 0.75, outperforming all other biomarkers (∂AIC > 4). The best combination of markers was the association of plasma p-tau181, GFAP, and NfL, yielding an AUC of 0.79, which was equivalent to the performance of the combination of all 6 plasma markers (AUC = 0.82, ∂AIC < 4 ). Plasma p-tau181 was outperformed by the combinations of all 6 biomarkers (AUC = 0.82 versus AUC = 0.75, ∂AIC = 5.5).

Diagnosis performance of our plasma biomarkers was overall better in discriminating A + T + from A-T- DLB patients (AUC = 0.71–0.85, Fig. 4 , c). Plasma p-tau181 displayed the highest AUC, of 0.85, outperforming all other biomarkers. Combining biomarkers (AUC = 0.87–0.91, Fig. 4 , d) did not statistically outperform plasma p-tau181 sole (AUC = 0.85, ∂AIC <4).

Plasma biomarkers performance for identification of amyloid copathology in DLB patients. ROC analysis: a , to compare single biomarkers performance to discriminate between A- and A + DLB patients; b , to compare biomarkers combination to discriminate between A- and A + DLB patients; c , to compare single biomarkers performance to discriminate between A-T- and A + T + DLB patients; d , to compare biomarkers combination to discriminate between A-T- and A + T + DLB patients. ROC analysis results are presented as AUC (95% CI). Combinations of biomarkers were selected through binary logistic regression with backward stepwise elimination, including age and sex as constant variables. a the model including p-tau181 outperformed all other models (∂AIC > 4). b the model associating plasma p-tau181, GFAP, and NfL was equivalent to the All markers models (∂AIC < 4). c the model including p-tau181 outperformed the All markers model (∂AIC > 4), with the best trade-off between parsimony and performance

Association with cognitive measurement

The associations of the plasma biomarkers with MMSE in diagnosis groups are presented in Supp. Table 6 . In the DLB patients, we found higher plasma levels of p-tau181 levels were correlated with lower MMSE in unadjusted analysis (Spearman’s r = 0.231, P = 0.024). After adjustment on age, sex, and level of education, there remained no significant association (β=-0.176, P = 0.072). In the whole cohort, higher plasma p-tau181 and plasma GFAP levels were significantly associated with lower MMSE, after adjustment on age, sex, and level of education (respectively: β=-0.378 and β=-0.373, P < 0.001). In the AD group, higher plasma GFAP levels were correlated with lower MMSE in unadjusted analysis ( r = -0.253, P = 0.032).

Principal component analysis

Lastly, we performed PCA to investigate the relationship between the different biomarkers in AD and DLB groups (Fig. 5 ). In DLB, we identified 2 principal components that explained 58% of the total variance in the dataset (Fig. 5 , a). Component 1 accounted for 19% of the variance and was associated with plasma Aβ ratio, p-tau181, and GFAP. Component 2 captured 39% of the variance and was associated with neuroinflammatory markers sTREM2 and YKL-40 and axonal damage markers NfL. In the AD group, PCA analysis yielded two principal components as well (Fig. 5 , b). First, a component 1 associated plasma Aβ ratio and neuroinflammatory markers sTREM2 and YKL-40, explaining 20% of the variance. A component 2 clustered plasma p-tau181, GFAP, and axonal damage markers NfL, capturing 36% of the variance.

Principal component analysis of biomarker data in DLB and AD patients. a , Principal component analysis in DLB patients ( n = 103). Component 1 associating plasma Aβ ratio, p-tau181, and GFAP explained 19% of the variance of the biomarkers data. Component 2 associating neuroinflammation sTREM2 and YKL-40 and axonal damage NfL makers explained 40% of variance. b , Principal component analysis in AD patients ( n = 76). Component 1 associating plasma Aβ ratio, p-tau181, and GFAP explained 20% of the variance of the biomarkers data. Component 2 associating neuroinflammation sTREM2 and YKL-40 and axonal damage NfL markers explained 36% of variance

In the present study, we report plasma biomarker modifications, including amyloid and tau, neurodegeneration, and neuroinflammation across a cohort of patients with probable DLB, compared with AD and controls. DLB patients displayed intermediate levels of plasma Aβ ratio, p-tau181and GFAP, falling in between control subjects and AD patients. Plasma p-tau181 was further altered in DLB patients with AD copathology. Subtle changes in plasma sTREM2 levels could be observed.

Plasma Aβ ratio, p-tau181, and GFAP levels were higher in DLB compared with NC but lower than those observed in the AD group. Those findings are in keeping with the previously published literature [ 25 ]. Plasma Aβ ratio was significantly lower in DLB patients compared with NC, even if the size of the effect was moderate compared with those of the decrease observed in the AD groups. Plasma Aβ42/40 has been reported to correlate with 18 F-florbetapir SUVR in DLB [ 17 ].

Regarding plasma p-tau, there is now significant evidence of its increase in DLB, already at the MCI stage [ 12 , 14 , 17 ]. The effect size difference was greater when comparing DLB and AD than between DLB and controls. Regarding diagnostic performance, p-tau181 had the highest performance in differentiating DLB from NC, and combining biomarkers did not improve diagnosis performance. To differentiate DLB from AD, p-tau181 also displayed the best performance, albeit moderate, in line with what has been reported in the literature [ 17 , 25 , 26 ]. Plasma GFAP displayed the largest effect size difference when comparing DLB to controls. It could reflect both copathology as GFAP has been demonstrated to be associated with Aβ mediated astrocytic reactivity, and general neurodegeneration [ 27 ]. In our study, it was not associated with CSF amyloid status, which could indicate Aβ-independent astrocytic activation or neurodegeneration. Indeed, there is emerging evidence that supports the existence of an astrocytic activation in DLB independently of amyloid pathology. Significant tracer uptake in 11 C-PK11195 microglial PET has been observed in DLB with no association with amyloid pathology [ 28 ]. Autopsy studies on DLB brains have demonstrated increased GFAP + astrocyte reactivity, in association with Lewy body pathology [ 29 , 30 ]. If it is established that AD copathology has an important impact on the inflammatory signals detected in DLB, there is emerging evidence for specific astroglial processes related to Lewy body pathology, that could be picked up by plasma biomarkers.

No difference in plasma NfL levels was observed between NC and DLB, whereas there was a significant difference between DLB and AD groups. Previous findings regarding plasma NfL in DLB have been ambiguous, which may partly be because of small sample studies, discrepancies in design, and variability of cohorts, combining sometimes DLB with Parkinson’s disease dementia [ 31 ]. In several studies, plasma NfL was shown to reflect disease progression in later DLB stages as a non-specific marker of worse cognitive and clinical outcomes, as well as a reflection of amyloid copathology [ 32 , 33 ].

In our cohort, no difference in levels of plasmaYKL-40 could be observed. Previous studies had reported no difference in CSF YKL-40 levels between DLB and controls [ 18 ]. In plasma, increased levels of YKL-40 have been described in a cohort of Lewy body dementia patients including DLB patients and Parkinson’s disease dementia patients [ 19 ]. Specific studies focusing on DLB cases will be needed to clearly state if CSF or plasma YKL-40 are consistently altered in DLB. In our work, the combination of plasma p-tau181 and YKL-40 levels increased performance to differentiate AD from DLB, which would still indicate an underlying glial process picked up by YKL-40. Plasma sTREM2 was higher in DLB compared with AD. High levels of CSF sTREM2 in DLB have already been reported [ 18 ]. Similar findings have been observed in PD brain, suggesting a reaction to alpha-synuclein deposition [ 34 ]. Plasma sTREM2 levels did not differ in A- and A + DLB subjects, suggesting that the observed increase in the DLB group is not related to AD pathology. However, it is still unclear if YKL-40 or sTREM2 plasma levels are the reflection of a central process, or of an associated peripherical immune dysregulation. In the brain, the expression and secretion of YKL-40 are attributed to astrocyte activation [ 35 ]. Brain-derived YKL-40 is hypothesized to then be released in the blood and contribute to plasma levels. Regarding sTREM2, while CSF levels are considered to reflect microglial inflammation, there is evidence that blood sTREM2 might reflect the activation of a wider range of myeloid cells [ 36 ]. In addition, there is growing evidence of altered peripherical immune response in DLB. High peripheral levels of cytokines and modified lymphocyte profile have been reported, at both MCI and dementia stages [ 37 , 38 ]. While both the central and peripherical inflammation processes are likely key features of DLB, CSF and plasma neuroinflammation markers might likely provide different information.

Complementary biomarkers reflecting the other pathological mechanisms of DLB, such as, first and foremost, αsynuclein aggregation but also synaptic alterations, and mitochondrial dysfunction, would most likely contribute to diagnosis.

Amyloid deposition is common in dementia with Lewy bodies (DLB), ranging from 40 to 70% in neuropathological studies [ 39 , 40 ]. Approximately half of patients with DLB demonstrate coexisting amyloid lesions, that impact clinical presentation and disease progression [ 41 ]. Plasma p-tau markers, including plasma p-tau181 and p-tau231, were shown to pick up amyloid pathology and correlate with cognitive decline, accordingly to CSF and PET markers [ 12 , 14 ]. In our study, only plasma p-tau181 was significantly higher comparing the A + DLB patients compared with the A-. Comparing A + T + to A-T-, both plasma p-tau181(with a higher effect size) and NfL were increased. This suggests that plasma biomarkers display more significant abnormalities in DLB patients with AD copathology when abnormalities in CSF Aβ and p-tau are both established (A + T + stage). We did not observe a difference in CSF A + and A- DLB groups for plasma GFAP or Aβ ratio, conversely as what has already been reported [ 17 ]. We cannot exclude that our small samples of CSF amyloid-positive patients could have prevented us from measuring existing effects. However, combining p-tau181 to Aβ ratio and NfL significantly increased performance to identify A + patients, compared with the use of p-tau181 sole.

Additionally, we only found an association of MMSE with plasma-tau181 in DLB patients in unadjusted analysis, keeping in line with the reported poorer cognitive status of patients with amyloid copathology [ 12 ]. Thus, we add evidence to existing studies that p-tau181 is a valuable marker of AD co-pathology and expand on the potential of combining biomarkers.

Interestingly, our PCA analysis demonstrated different segregations of our biomarkers in AD and DLB groups, pointing towards differential underlying physiopathology. In DLB, axonal NfL and glial markers sTREM2 and YKL-40 clustered in a 1st component, suggesting neuroinflammation and axonal loss as driving most of the variance in the data set. Plasma, Aβ ratio, p-tau181, and GFAP clustered in an “amyloid component”, that can be hypothesized as reflecting amyloid copathology. Indeed, plasma GFAP has been reported to be an early and independent marker of astrocytosis reactive to Aβ pathology, associating closely with amyloid markers [ 27 , 42 ]. In the AD group, plasma p-tau was associated with plasma GFAP and NfL in a first component explaining a higher part of the variance, in what could be identified as a tau and neurodegeneration component. In a 2nd component, plasma Aβ clustered with plasma glial markers. Studies on the longitudinal course of microglial activation along the AD continuum have reported an early peak at the MCI stage which could explain this segregation [ 43 ].

Our study included well-characterized DLB and AD patients and control subjects. It benefited from the use of biomarkers and reference diagnosis criteria. A strength is that our sample originated from clinical settings and thus brings ‘real-life’ evidence on the use of those novel biomarkers, compared to strictly selected research cohorts. Amyloid ratio, p-tau, NfL, and GFAP were measured with the established and highly accurate Simoa method.

This work does not go without limitations. CSF data about amyloid copathology was lacking for a small part of the cohort. We did not have available measurements of other p-tau isoforms than p-tau-181, notably of p-tau217 or p-tau231, which may be more sensitive and specific in early AD. There is still little evidence currently on possible differences in p-tau isoforms in diagnosis accuracy for DLB [ 12 , 14 , 15 ]. sTREM2 and YKL-40 levels were measured using Elisa, whereas all other biomarkers were measured using Simoa, which might have induced some variability. We had no available measurement of alpha-synuclein pathology, DLB patients being included on clinical diagnosis. However, the clinical criteria used have demonstrated high specificity [ 44 ]. Plasma biomarkers should also be investigated in comparison to other atypical parkinsonian syndromes and FTD syndromes, that constitute potential differential diagnoses for DLB. Finally, exploring the association of plasma biomarkers with the clinical features of the disease could further inform their use, and give some insight on the clinical heterogeneity observed within the DLB spectrum. Additionally, combining plasma biomarkers and other clinical and supportive biomarkers could provide a more accurate diagnosis and prognosis.

In conclusion, we found a specific pattern of impairment in plasma biomarkers of amyloid, tau axonal damage, and neuroinflammation in DLB patients. Plasma p-tau181 levels were elevated in DLB cases with AD comorbid pathology, which could have potential for selecting patients for Aβ targeting therapeutics. The diagnosis performance of our biomarkers for diagnosis remained moderate, underlying the need for further development of specific markers for synucleinopathies and DLB-specific biomarkers.

Data availability

Anonymized data will be shared upon reasonable request after approval by the local research ethics committee.

Abbreviations

Alzheimer’s disease

Akaike information criteria

area under the receiver operating characteristic curve

confidence interval

dementia with Lewy bodies

neurological controls

receiver operating characteristic curve

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This work was funded through a grant from l’Association des Aidants et Malades à Corps de Lewy (A2MCL).

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Contributions

AV, CP, FB, and OB created the concept and design. Data acquisition was performed by AV, CH, EC, KG, JD, OB, BC, CD, CM, AR, BC, BS, NP, and ML. AV performed data analysis. AV, CP, FB, and OB contributed to sample selection. All authors contributed to the interpretation of data. AV drafted the manuscript and all authors revised it. All authors have read and approved the final manuscript.

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Correspondence to Agathe Vrillon .

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All patients or their legal relatives gave written informed consent to their participation in the study. For Paris cohort, the collection and analysis of samples were approved by the local ethic committee of Bichat University, Paris, France (CEERB GHU Nord n°10–037). For Strasbourg cohort, this study was part of the larger cohort study AlphaLewyMA ( https://clinicaltrials.gov/ct2/show/NCT01876459 , registered June 11, 2013), approved by the ethics committee of East France (IV). All procedures were in accordance with the Declaration of Helsinki.

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Competing interests.

F.B. was the national coordinator for France for the Eisai Delphia (E2027), Axovant Headway-DLB and Roche Graduate therapeutic trials; he had received honoraria from Roche, Eisai and Biogen for oral presentations, and from Eisai for a board. C.P. is a member of the International Advisory Boards of Lilly; is a consultant for Fujiribio, Alzhois, Neuroimmune, Ads Neuroscience, Roche, AgenT and Gilead; and is involved as an investigator in several clinical trials for Roche, Esai, Lilly, Biogen, Astrazeneca, Lundbeck, and Neuroimmune. All other authors report no conflicts of interest.

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Vrillon, A., Bousiges, O., Götze, K. et al. Plasma biomarkers of amyloid, tau, axonal, and neuroinflammation pathologies in dementia with Lewy bodies. Alz Res Therapy 16 , 146 (2024). https://doi.org/10.1186/s13195-024-01502-y

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Alzheimer's Research & Therapy

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FDA approves new Alzheimer's treatment, donanemab from Eli Lilly

By Alexander Tin

Edited By Paula Cohen

Updated on: July 3, 2024 / 12:22 PM EDT / CBS News

The Food and Drug Administration approved a new Alzheimer's treatment called donanemab on Tuesday, clearing the way for the third addition to a new class of drugs aimed at slowing the brain's decline in patients facing the early stages of the disease.

Branded as Kisunla by drugmaker Eli Lilly, donanemab's approval follows years of setbacks and delays in getting the experimental Alzheimer's treatment to market, despite promising clinical trial results .

Eli Lilly says the drug will be available within weeks following the approval.

"Kisunla demonstrated very meaningful results for people with early symptomatic Alzheimer's disease, who urgently need effective treatment options. We know these medicines have the greatest potential benefit when people are treated earlier in their disease, and we are working hard in partnership with others to improve detection and diagnosis," Anne White, president of Eli Lilly's neuroscience arm, said in a news release .

CBS News chief medical correspondent Dr. Jon LaPook described it as "an incremental advance" that may slow the decline of cognitive function for people in the early stages of the disease.

"We're not reversing it — it's not a cure. But if you can slow the decline, I think that's important," LaPook said on "CBS Mornings."

The FDA previously rebuffed Eli Lilly's request for accelerated approval last year, citing concerns about its long-term safety data. After Eli Lilly submitted more data to the FDA, the company said it expected the agency would decide on approval by the end of March.

That decision was delayed after the FDA scheduled an advisory committee to wrestle with questions over the drug's safety issues and how effectiveness was measured in its trials. The panel ultimately voted unanimously last month in favor of the drug's benefits outweighing its risks, for patients in the early stages of Alzheimer's disease.

How does donanemab work?

Donanemab is part of a class of Alzheimer's treatments called anti-amyloid monoclonal antibodies, which work to combat the buildup of a protein in the brain called amyloid plaque that has been linked to Alzheimer's disease.

The antibody in donanemab targets amyloid plaques that have built up in patients by binding to and removing them from the brain.

Patients in Eli Lilly's trials were given intravenous donanemab infusions for around half an hour, every four weeks. Depending on brain scans measuring amyloid levels in the brain, patients were able to stop taking the drug after as early as six months.

In its trials , the company says almost half of patients were able to meaningfully clear out amyloid after around a year after taking the drug. Patients saw no "rebound of amyloid plaque" in the year after treatment wrapped up.

The only other Alzheimer's treatment that works in a similar way on the market is lecanemab, branded as Leqembi by drugmakers Eisai and Biogen. An earlier drug called aducanumab ( marketed as Aduhelm ) from Biogen was discontinued in January.

Beyond effectiveness, Eli Lilly has also touted a handful of other reasons that patients might choose their drug instead of lecanemab.

Donanemab infusions are shorter and less frequent. Trial participants were also able to stop using the drug after amyloid plaque was removed, "which can result in lower treatment costs and fewer infusions," a company spokesperson said.

How much will the treatment cost?

Eli Lilly says it will launch with a list price that adds up to $32,000 for 12 months of treatment, though the actual cost will depend on how long patients take the drug. Some patients in the clinical trials were able to stop the treatment after six months, based on results from brain scans, while others took it for 18 months.

Last year, Eisai defended its list price of $26,500 per year when it launched sales of Leqembi.

But most patients also do not pay the full list price for prescription drugs. For patients with Medicare Part B, the Centers for Medicare and Medicaid Services said donanemab will be covered in the same way it covers lecanemab (Leqembi), with patients paying a 20% coinsurance after they meet their deductible. These patients will need to get the drug from doctors enrolled in a study gathering data tracking its effectiveness.

"CMS is committed to helping people get timely access to treatments and improving care for people with Alzheimer's disease and their families," a CMS spokesperson said.

Eli Lilly noted in a statement: "The potential to complete treatment after a limited-duration course of therapy, along with 30-minute infusions once per month, could result in lower patient out-of-pocket treatment costs and fewer infusions compared to other amyloid-targeting therapies."

How effective was the treatment for Alzheimer's symptoms?

Eli Lilly measured donanemab's effectiveness primarily through rating scales designed to measure the cognitive and functional decline caused by dementia symptoms in patients with early stages of Alzhiemer's.

Compared with patients who received only a placebo, Eli Lilly said those who got the drug saw their decline slow. The gap widened over time, slowing by 22% overall at 76 weeks after first starting the donanemab infusions.

"Importantly, the magnitude of impact on these clinical endpoints meets, and in several respects exceeds prior approvals for demonstration of clinical benefit and effectiveness," the company said of the results in a briefing document given to the FDA panel.

The company says this translated to effectively prolonging how long it took until patients stepped down into the next stage of Alzheimer's disease.

What are the side effects of donanemab?

The labels for all of the anti-amyloid treatments greenlighted by the FDA to date for Alzheimer's already carry a boxed warning about "amyloid-related imaging abnormalities" that can show up on MRI scans.

While these abnormalities generally result in no symptoms, they have been linked to rare but serious issues in some patients like brain function issues and seizures.

These abnormalities were seen in around a quarter of participants in Eli Lilly's trials of donanemab. At least five deaths were reported in donanemab recipients in patients with these kinds of abnormalities, mostly from hemorrhages in the brain.

Eli Lilly says their trials of donanemab tested the drug in harder to treat patients than other treatments studied around the same time. That means the trial included older trial participants as well as those with a gene called APOE ε4 that can increase the risk of Alzheimer's as well as these abnormalities.

Close to 1 in 10 trial participants who took donanemab also experienced a reaction to the infusion, compared to 0.5% of placebo participants. The most common symptoms included chills, skin reddening, nausea, shortness of breath, headache and chest pain.

Approximately 3% of donanemab-treated participants developed hypersensitivity to the infusion, including 0.3% who had a severe allergic reaction.

Alzheimer's Disease

Alexander Tin is a digital reporter for CBS News based in the Washington, D.C. bureau. He covers the Biden administration's public health agencies, including the federal response to infectious disease outbreaks like COVID-19.

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New Breakthrough in Alzheimer’s Research: UTMB Researchers Develop Nasal Spray Treatment for Alzheimer’s Disease

July 3, 2024 • 2:00 p.m.

Researchers at the University of Texas Medical Branch recently discovered a significant advancement in the fight against neurodegenerative diseases such as Alzheimer’s disease and dementia. The study, published today in Science Translational Medicine, introduces an innovative nasal spray treatment that has shown promising results in clearing harmful tau protein build-up and improving cognitive functions in aged mice models with neurodegenerative diseases.

“This nasal spray approach opens new avenues for non-invasive delivery of tau therapeutic antibodies directly to the brain, and it holds promise for many neurodegenerative diseases.” said Dr. Rakez Kayed, lead author and professor at the Department of Neurology at UTMB.

Tau is a microtubule-associated protein found in human brains that helps stabilize microtubules, part of the framework that gives the cell its shape and helps it stay organized, in neurons. In healthy brains, tau proteins help keep things in order. But in neurodegenerative diseases, they can become abnormally twisted and form tangles that disrupt neuronal function and lead to cognitive decline. Current tau immunotherapies have struggled with efficacy due to their limited ability to penetrate intracellular compartments where these tau buildups reside.

Kayed and his team developed a specific type of antibody, TTCM2, which selectively recognizes and targets toxic tau buildup. The antibody was packaged in particles to enhance its delivery to the brain via the nasal route. This method bypasses the blood-brain barrier, a significant hurdle in neurodegenerative disease treatment, ensuring rapid and effective delivery of the therapy.

“Our research highlights the potential of nasal tau immunotherapy to effectively target intracellular tau aggregates– a primary driver of neurodegeneration and cognitive decline in diseases like Alzheimer’s and other tauopathies,” added Kayed. “This method not only improves the delivery of therapeutic antibodies but also enhances their efficacy in clearing tau aggregates and improving cognitive functions”.

An essential aspect of this approach is that it involves TRIM21, an intracellular receptor for antibodies and E3 ligase, known for mediating the clearance of antibody bound pathogens like viruses. In the study, TRIM21 facilitated the clearance of antibody bound intracellular tau aggregates, thereby enhancing the therapeutic effect and cognitive improvements in the mice model.

“This advancement could significantly impact the treatment strategies for Alzheimer’s and related tauopathies, offering new hope for millions of patients suffering from these debilitating conditions,” said Sagar Gaikwad, first author of the study and postdoctoral fellow at UTMB.

This study highlights the potential impact on future treatments for neurodegenerative diseases. Researchers at UTMB plan to advance this research by conducting further preclinical trials and exploring the potential of TTCM2-ms in human clinical trials. The goal is to translate these promising results into a viable treatment option for patients suffering from Alzheimer’s disease and other tau-related disorders.

The study was funded by grants from the NIH, Alzheimer’s Association and UTMB Claude D. Pepper OAIC Pilot grant. Authors and investigators also include Nicha Puangmalai, Minal Sonawane and Mauro Montalbano from UTMB.

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