{"id":52,"date":"2020-10-29T10:33:55","date_gmt":"2020-10-29T15:33:55","guid":{"rendered":"https:\/\/sites.bu.edu\/melodem\/?page_id=52"},"modified":"2025-11-20T15:22:07","modified_gmt":"2025-11-20T20:22:07","slug":"publication","status":"publish","type":"page","link":"https:\/\/sites.bu.edu\/melodem\/resources\/publication\/","title":{"rendered":"Publications by MELODEM Participants"},"content":{"rendered":"

Recent Publications<\/strong><\/p>\n

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(2025) Approaches to timescale choice in cognitive aging research and potential implications for estimated exposure effects: coordinated analyses in ten cohorts of older adults<\/strong><\/h4>
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Awarded the 2025 Lilienfeld Postdoctoral Prize Paper Award!<\/strong><\/p>\n

The aim of this study, initiated at the 2022 the Methods in Longitudinal Dementia Research (MELODEM) initiative data workshop,<\/span>\u00a0was to demonstrate approaches to timescale choice and highlight potential implications of the choice for estimated effects of an exposure on cognitive change. The paper involves coordinated analyses in ten major aging cohorts with distinct selection criteria, measurement protocols, participant characteristics, birth cohorts, and age ranges. We compared estimated effects of two exposures on cognitive change across different timescale specifications:\u00a0APOE<\/i>\u00a0genotype (a time-invariant exposure) and baseline diabetes status (a one-time measure of a potentially time-varying\/acquired exposure).\u00a0<\/span>We found that timescale was largely inconsequential for estimated effects of\u00a0APOE<\/i>\u00a0genotype, but yielded differences in estimated diabetes effects. Current age scale may be problematic because diabetes was measured heterogeneously in age across individuals<\/span>, a common issue in aging cohorts. The work\u00a0<\/span>demonstrates approaches to evaluate alternative timescales, including in multi-cohort analyses, and highlights potential implications for estimated exposure effects on cognitive change.<\/span><\/p>\n

Hayes-Larson, E., Andrews, R. M., Kezios, K. L., Bercu, A., Rouanet, A., Helmer, C., Crane, P. K., Gibbons, L. E., Klinedinst, B. S., McEvoy, L. K., Nichols, E., Weuve, J., Rajan, K. B., Hwang, P. H., Mez, J., Farina, M., Shaw, C., Sims, K. D., Therneau, T., Petersen, R. C., \u2026 Mayeda, E. R. (2025). Approaches to Timescale Choice in Cognitive Aging Research and Potential Implications for Estimated Exposure Effects: Coordinated Analyses in 10 Cohorts of Older Adults. Epidemiology (Cambridge, Mass.), 36(4), 560\u2013571. https:\/\/doi.org\/10.1097\/EDE.0000000000001859<\/p>\n

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(2024) <\/strong>Visual Impairment, Eye Conditions, and Diagnoses of Neurodegeneration and Dementia<\/strong><\/h4>
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Congratulations to Erin Ferguson and colleagues on their 2024 publication \u201cVisual Impairment, Eye Conditions, and Diagnoses of Neurodegeneration and Dementia\u201d. This paper aimed to determine whether visual acuity, cataracts, and myopia affect neurodegeneration and dementia risk. Evaluating causality here is difficult because dementia and vision in later life can share risk factors or in some cases influence each other. To disentangle these relationships, the authors used forward and reverse Mendelian Randomization (MR).<\/p>\n

Led by Erin Ferguson (PhD candidate at the University of California San Francisco with senior author Dr. Willa Brenowitz at Kaiser Permanente Center for Health Research in Portland, Oregon), the research team conducted observational and Mendelian Randomization (MR) analyses in UK Biobank participants. Observational studies examined the association between visual acuity, eye disorders with dementia diagnoses and brain volumes. 2 sample Mendelian Randomization (MR) analysis was conducted using genetic variants that predict risk for cataracts, myopia, and Alzheimer\u2019s Disease (AD). Variants were selected from prior GWAS of these conditions independent of UK Biobank (this entailed a limitation in that analyses were limited to individuals of European ancestry because the variants were identified in European ancestry populations and may differ for other genetic ancestries). The researchers conducted forward MR (vision conditions as affecting dementia) and reverse MR (AD as affecting vision outcomes) analyses.<\/p>\n

Researchers found that observed cataracts were linked to a 25% higher risk of developing Alzheimer&#39;s disease (AD) and a 25% higher risk of developing vascular dementia. Genetic risk of cataracts was associated with a reduction of 597.43 mm\u00b3 of overall brain volume. In MR studies, genetically predicted cataracts were linked to 92% higher odds of developing vascular dementia. This estimates the causal effect of having cataracts on vascular dementia, assuming valid MR assumptions. Genetically predicted AD was not associated with cataracts or poor vision. Although poor visual acuity (worse than 20\/40 vision) was associated with 35% higher dementia risk in observational studies, myopia and genetically predicted myopia was not associated with dementia. These results suggest a causal effect of cataracts\u2014or their underlying pathological processes\u2014on the risk of developing vascular dementia (VaD). This could plausibly occur through vascular pathways such as white matter damage.\u00a0 Additionally, the lack of association between genetic risk for Alzheimer\u2019s disease (AD) and eye conditions indicates that reverse causation is unlikely to explain the observed links between cataracts, poor vision, and AD. Despite uncertainty in clinical diagnoses of VaD versus AD, the potential role of vascular pathways is consistent with the finding that genetically predicted cataract was associated with VaD and but not AD.<\/p>\n

For more of Erin Ferguson\u2019s work, check out her MELODEM presentation<\/a> on multiverse analyses in March, 2024.<\/p>\n

For more on Mendelian Randomization based approaches to evaluating risk factors for dementia, check out Drs. Roopal Desai & Verena Zuber MELODEM presentation<\/a> in September, 2024.<\/p>\n

Ferguson, E. L., Thoma, M., Buto, P. T., Wang, J., Glymour, M. M., Hoffmann, T. J., Choquet, H., Andrews, S. J., Yaffe, K., Casaletto, K., & Brenowitz, W. D. (2024). Visual Impairment, Eye Conditions, and Diagnoses of Neurodegeneration and Dementia. JAMA network open, 7(7), e2424539. https:\/\/doi.org\/10.1001\/jamanetworkopen.2024.24539<\/p>\n

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(2024) <\/strong>Effect of a Cash Transfer Intervention on Memory Decline and Dementia Probability in Older Adults in Rural South Africa<\/strong><\/h4>
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The 2024 PNAS publication \u201cEffect of a Cash Transfer Intervention on Memory Decline and Dementia Probability in Older Adults in Rural South Africa<\/em><\/a>\u201d<\/a><\/span>\u00a0evaluated the impact of a randomized cash transfer on long-term cognitive outcomes in a low-income, aging population.<\/p>\n

The study was possible because a randomized study of cash transfers ($36 US per month at time of study, equivalent to about 67% of the average household monthly consumption) happened to include the households of 862 participants in the HAALSI study (Health and Aging in Africa: A Longitudinal Study of an INDEPTH Community, 2014\u20132022<\/a><\/span>). Because HAALSI was already tracking cognitive changes longitudinally, they could compare whether changes were slower for older adults in households randomized to receive a cash transfer. The cash transfer study was launched 2011-2012, and cash payouts continued for 1-5 years based on the age of the teenage girl in the household (who were the original intended beneficiaries of the intervention). HAALSI baseline was in 2014\/15 and follow-up continued for 7 years.<\/p>\n

Older adults (average age 61 years, SD=12 years) in households who received a short-term cash transfer experienced slower memory decline after 7 years of follow-up in the HAALSI cohort study, with stabilized or slower declines in memory scores compared to those who did not receive the transfer. At the end of follow-up, older adults in households that received the cash transfer had a 3-percentage point lower probability of dementia compared to households that did not receive the transfer. This study showed that modest cash transfers to older adults in low-income settings can slow memory decline and reduce dementia risk, emphasizing financial support as a tool for improving brain health in resource-limited areas.<\/p>\n

This manuscript was led by Dr. Molly Rosenberg at the Indiana University School of Public Health<\/a><\/span> and senior authored by long-term MELODEM participant Dr. Lindsay Kobayashi of University of Michigan<\/a><\/span>.\u00a0 Congratulations to the authors on such an impressive and creative study.<\/p>\n

M. Rosenberg,E.T. Beidelman,X. Chen,C. Whiteson Kabudula,A. Pettifor,D.T. Bassil,L. Berkman,K. Kahn,S. Tollman, & L.C. Kobayashi, Effect of a cash transfer intervention on memory decline and dementia probability in older adults in rural South Africa, Proc. Natl. Acad. Sci. U.S.A. 121 (40) e2321078121, https:\/\/doi.org\/10.1073\/pnas.2321078121 (2024).<\/p>\n

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(2024) <\/strong>Associations Between Blood-Based Biomarkers and Cognitive and Functional Trajectories Among Participants of the MEMENTO Cohort<\/strong><\/h4>
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The 2024 Neurology publication \u201cAssociations Between Blood-Based Biomarkers and Cognitive and Functional Trajectories Among Participants of the MEMENTO Cohort<\/a>,\u201d explores the relationship between blood-based Alzheimer’s Disease biomarkers and cognitive and functional trajectories over five years in older adults from the French MEMENTO cohort. With senior author Dr. Carole Dufouil and first-author Dr. Leslie Grasset, the team assessed the links between baseline biomarkers from blood samples and cognitive tests, including the Mini-Mental State Examination (MMSE), Free and Cued Selective Reminding Test (FCSRT), Semantic Fluency Test, and Trail Making Tests A and B (TMT-A and TMT-B).<\/p>\n

Elevated blood biomarkers p-tau181 (linked to Alzheimer’s) and neurofilament light chain (NfL, indicating nerve cell damage), were associated with faster decline in both multiple cognitive measures (e.g., assessing memory and language), as well as measures of physical functioning and autonomy (e.g., a battery of physical performance tasks such as gait speed, balance, and strength and a brief assessment of limitations in instrumental activities of daily living) physical tasks. Together, p-tau181 and NfL were associated with greater cognitive and functional decline than either alone. A lower A\u03b242\/40 ratio was only associated with a slightly faster cognitive decline in FCSRT and semantic fluency, as well as a slightly faster progression of disability. The clinical significance of this study lies in its potential to better understand the biomarkers that link with the biological progression of Alzheimer’s and pathologies that cause dementia.<\/p>\n

Grasset, L., Bouteloup, V., Cacciamani, F., Pellegrin, I., Planche, V., Ch\u00eane, G., Dufouil, C., & MEMENTO study group (2024). Associations Between Blood-Based Biomarkers and Cognitive and Functional Trajectories Among Participants of the MEMENTO Cohort. Neurology, 102(9), e209307. https:\/\/doi.org\/10.1212\/WNL.0000000000209307<\/p>\n

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Older Publications<\/strong><\/h3>
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Hayes-Larson E, Ackley SF, Zimmerman SC, et al. The competing risk of death and selective survival cannot fully explain the inverse cancer-dementia association.<\/a><\/span>Alzheimers Dement<\/span><\/i>. 2020;10.1002\/alz.12168.\u00a0<\/span><\/p>\n

Heterogeneous long-term trajectories of dependency in the elderly\u202f: The PAQUID cohort, a 22-year population-based study.<\/a> The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences. 2020; 75(12) 2396-2403.<\/span><\/p>\n

Wagner, M., Grodstein, F., Proust-Lima, C., & Samieri, C.. Long-Term Trajectories of Body Weight, Diet, and Physical Activity From Midlife Through Late Life and Subsequent Cognitive Decline in Women. <\/a><\/span>American Journal of Epidemiology<\/span><\/i>. 2020;189(4), 305\u2011313.<\/span><\/p>\n

Proust-Lima, C., Philipps, V., Dartigues, J.-F. et al. Are latent variable models preferable to composite score approaches when assessing risk factors of change? Evaluation of type-I error and statistical power in longitudinal cognitive studies.<\/a><\/span>Statistical Methods in Medical Research<\/span><\/i>. <\/span>2019;28(7):1942-1957.\u00a0<\/span><\/p>\n

Proust-Lima C, Philipps V, Dartigues J-F. A joint model for multiple dynamic processes and clinical endpoints: Application to Alzheimer\u2019s disease.<\/a><\/span> Stat Med<\/span><\/i>. 2019;38(23):4702-4717.<\/span><\/p>\n

Tadd\u00e9 BO, Jacqmin-Gadda H, Dartigues J-F, Commenges D, Proust-Lima C. Dynamic modeling of Multivariate Dimensions and Their Temporal Relationships using Latent Processes: Application to Alzheimer\u2019s Disease. <\/a><\/span>Biometrics<\/span><\/i>. 2019;<\/span>76<\/span>: <\/span>886<\/span>\u2013 <\/span>899<\/span>.<\/span><\/p>\n

Wagner M, Grodstein F, Proust-Lima C, Samieri C. Long-Term Trajectories of Body Weight, Diet, and Physical Activity From Midlife Through Late Life and Subsequent Cognitive Decline in Women. <\/a><\/span>Am J Epidemiol<\/span><\/i>. 2020;189(4):305-313.\u00a0<\/span><\/p>\n

Proust-Lima, C., Philipps, V., & Dartigues, J.-F. (2019). A joint model for multiple dynamic processes and clinical endpoints: Application to Alzheimer\u2019s disease.<\/a><\/span> Statistics in Medicine<\/span><\/i>. 2019;38(23), 4702\u20114717.\u00a0<\/span><\/p>\n

Dufouil C, Beiser A, Chene G, Seshadri S. Are Trends in Dementia Incidence Associated With Compression in Morbidity? Evidence From The Framingham Heart Study. <\/a><\/span>The journals of gerontology. Series B, Psychological sciences and social sciences. <\/span><\/i>2018;73(suppl_1):S65-s72.\u00a0<\/span><\/p>\n

Dufouil C, Glymour MM. Prediction to prevention in Alzheimer’s disease and dementia. <\/a><\/span>The Lancet. Neurology. <\/span><\/i>2018;17(5):388-389.<\/span><\/p>\n

Mayeda ER, Filshtein TJ, Tripodis Y, Glymour MM, Gross AL. Does selective survival before study enrollment attenuate estimated effects of education on the rate of cognitive decline in older adults? A simulation approach for quantifying survival bias in life course epidemiology. <\/a><\/span>Int J Epidemiol<\/span><\/i>. 2018;47(5):1507-1517.\u00a0<\/span><\/p>\n

Gross AL., Chu N., Anderson L., et al. <\/span>Coalition Against Major Diseases, Do people with Alzheimer\u2019s disease improve with repeated testing? Unpacking the role of content and context in retest effects. <\/span><\/a>Age and Ageing. <\/span><\/i>2018:47(6):866-871.<\/span><\/p>\n

Glymour MM, Brickman AM, Kivimaki M, et al. Will biomarker-based diagnosis of Alzheimer\u2019s disease maximize scientific progress? Evaluating proposed diagnostic criteria. <\/a><\/span>European Journal of Epidemiology. <\/span><\/i>2018;33:607-612.<\/span><\/p>\n

Mayeda ER, Banack HR, Bibbins-Domingo K, et al. <\/span>Can Survival Bias Explain the Age Attenuation of Racial Inequalities in Stroke Incidence? <\/span><\/a>Epidemiology. <\/span><\/i>2018;29(4):525-532.<\/span><\/p>\n

Gross AL, Payne BR, Casanova R, et al. The ACTIVE conceptual framework as a structural equation model. <\/a><\/span>Measurement in Physical Education and Exercise Science. <\/span><\/i>2018; 24(2):103-114.<\/span><\/p>\n

Wagner M, Dartigues J-F, Samieri C, Proust-Lima C. Modeling Risk-Factor Trajectories When Measurement Tools Change Sequentially During Follow-up in Cohort Studies: Application to Dietary Habits in Prodromal Dementia. <\/a><\/span>Am J Epidemiol<\/span><\/i>. 2018;187(4):845 54.<\/span><\/p>\n

Wagner M, Helmer C, Tzourio C, et al. Evaluation of the Concurrent Trajectories of Cardiometabolic Risk Factors in the 14 Years Before Dementia.<\/a><\/span> JAMA Psychiatry<\/span><\/i>. 2018;75(10):1033-1042.<\/span><\/p>\n

Gilsanz P, Karter AJ, Beeri MS, Quesenberry CP, Jr., Whitmer RA. The Bidirectional Association Between Depression and Severe Hypoglycemic and Hyperglycemic Events in Type 1 Diabetes. <\/a><\/span>Diabetes care. <\/span><\/i>2018;41(3):446-452.\u00a0<\/span><\/p>\n

Glymour MM, Brickman AM, Kivimaki M, et al. Will biomarker-based diagnosis of Alzheimer’s disease maximize scientific progress? Evaluating proposed diagnostic criteria. <\/a><\/span>European journal of epidemiology. <\/span><\/i>2018;33(7):607-612.\u00a0<\/span><\/p>\n

Gross AL, Chu N, Anderson L, Glymour MM, Jones RN. Do people with Alzheimer’s disease improve with repeated testing? Unpacking the role of content and context in retest effects. <\/a><\/span>Age and ageing. <\/span><\/i>2018;47(6):866-871.\u00a0<\/span><\/p>\n

Rooney JPK, Brayne C, Tobin K. et al. Benefits, pitfalls, and future design of population-based registers in neurodegenerative disease. <\/a><\/span>Neurology. <\/span><\/i>2017;88(24):2321-2329.<\/span><\/p>\n

Mayeda ER, Tchetgen Tchetgen EJ, Power MC, et al. A Simulation Platform for Quantifying Survival Bias: An Application to Research on Determinants of Cognitive Decline. <\/a><\/span>American journal of epidemiology<\/span><\/i>. 2016;184(5):378-387.\u00a0<\/span><\/p>\n

Vivot A, Power MC, Glymour MM, et al. Jump, Hop, or Skip: Modeling Practice Effects in Studies of Determinants of Cognitive Change in Older Adults. <\/a><\/span>American journal of epidemiology<\/span><\/i>. 2016;183(4):302-314.<\/span><\/p>\n

Weuve J, Proust-Lima C, Power MC, et al. Guidelines for reporting methodological challenges and evaluating potential bias in dementia research. <\/a><\/span>Alzheimer’s & dementia : the journal of the Alzheimer’s Association<\/span><\/i>. 2015;11(9):1098-1109.<\/span><\/p>\n

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Publications by Working Group Session Presenters<\/strong><\/h3>
<\/p>\n

Brian Downer:<\/strong> Gutierrez M, Wahrendorf M, Milani S, Mejia-Arango S, Wong R, Downer B. The Influence of Education and Occupation Type on Birth Cohort Differences in Cognitive Function of Mexican Older Adults.<\/a> The Journals of Gerontology: Series B. 2024 Jan 1;79(1):gbad155.<\/span><\/p>\n

Hyacinth I. Hyacinth: <\/strong>Sawyer, R. P., Worrall, B. B., Howard, V. J., Crowe, M. G., Howard, G., & Hyacinth, H. I. (2023). Methods of a Study to Assess the Contribution of Cerebral Small Vessel Disease and Dementia Risk Alleles to Racial Disparities in Vascular Cognitive Impairment and Dementia.<\/a>\u00a0Journal of the American Heart Association<\/i>,12<\/i>(17), e030925.<\/p>\n

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Recent Publications<\/p>\n","protected":false},"author":18606,"featured_media":0,"parent":464,"menu_order":3,"comment_status":"closed","ping_status":"closed","template":"page-templates\/no-sidebars.php","meta":[],"_links":{"self":[{"href":"https:\/\/sites.bu.edu\/melodem\/wp-json\/wp\/v2\/pages\/52"}],"collection":[{"href":"https:\/\/sites.bu.edu\/melodem\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.bu.edu\/melodem\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/melodem\/wp-json\/wp\/v2\/users\/18606"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/melodem\/wp-json\/wp\/v2\/comments?post=52"}],"version-history":[{"count":52,"href":"https:\/\/sites.bu.edu\/melodem\/wp-json\/wp\/v2\/pages\/52\/revisions"}],"predecessor-version":[{"id":1279,"href":"https:\/\/sites.bu.edu\/melodem\/wp-json\/wp\/v2\/pages\/52\/revisions\/1279"}],"up":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/melodem\/wp-json\/wp\/v2\/pages\/464"}],"wp:attachment":[{"href":"https:\/\/sites.bu.edu\/melodem\/wp-json\/wp\/v2\/media?parent=52"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}