Religious Orders Study and Rush Memory and Aging Project
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BACKGROUND: The Religious Orders Study and Rush Memory and Aging Project are both ongoing longitudinal clinical-pathologic cohort studies of aging and Alzheimer's disease (AD). OBJECTIVES: To summarize progress over the past five years and its implications for understanding neurodegenerative diseases. METHODS: Participants in both studies are older adults who enroll without dementia and agree to detailed longitudinal clinical evaluations and organ donation. The last review summarized findings through the end of 2011. Here we summarize progress and study findings over the past five years and discuss new directions for how these studies can inform on aging and AD in the future. RESULTS: We summarize 1) findings on the relation of neurobiology to clinical AD; 2) neurobiologic pathways linking risk factors to clinical AD; 3) non-cognitive AD phenotypes including motor function and decision making; 4) the development of a novel drug discovery platform. CONCLUSION: Complexity at multiple levels needs to be understood and overcome to develop effective treatments and preventions for cognitive decline and AD dementia.
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Genes associated with Alzheimer's disease progression are enriched in dopaminergic and inhibitory neuron subtypes, validated across two independent datasets.
“This key finding, validated across two independent datasets [41, 100], points specifically to the enrichment of these progression genes in dopaminergic and inhibitory neuron subtypes.”
From Genetic drivers of progression in Alzheimer’s disease are distinct from disease risk (2026) · cites this paper as [100]
The Introduction (page unavailable) identifies the Religious Orders Study and Rush Memory and Aging Project as cohort studies and describes their datasets, supporting this paper as a citation for a data resource. The paper does not report that Alzheimer’s progression genes are enriched in dopaminergic or inhibitory neuron subtypes, or that this finding was validated across two datasets. (LLM, conf=0.82)
Experimental — accuracy not yet measuredAll ROSMAP participants enrolled without known dementia and agreed to detailed clinical evaluation and brain donation at death.
“All ROSMAP partici- pants enrolled without known dementia and agreed to detailed clinical evaluation and brain donation at death.”
From PICALM Alzheimer’s risk allele causes aberrant lipid droplets in microglia (2025) · cites this paper as [62]
Aged individuals can harbor a high burden of AD brain lesions at autopsy while remaining cognitively intact, indicating resilience to AD pathology.
“several studies have revealed the existence of aged individuals harboring a high burden of brain lesions at autopsy while remaining cognitively intact, indicating resilience to AD pathology [3, 7, 21, 22, 56, 57, 68, 76, 78, 96].”
Some studies have identified selected overlaps in expression changes between AD mouse models and human brains.
“Although some studies have identified selected overlaps in expression changes between AD mouse models and human brains (Bennett et al., 2018; Castillo et al., 2017; Mostafavi et al., 2018; Neuner et al., 2019; Rojo et al., 2017), other studies have questioned the overall degree of conservation (Burns et al., 2015; Galatro et al., 2017; Hargis and Blalock, 2017).”
From Meta-Analysis of the Alzheimer’s Disease Human Brain Transcriptome and Functional Dissection in Mouse Models (2020) · cites this paper as Bennett et al., 2018
The Results section on the novel drug and biomarker discovery pipeline discusses human-brain omics and an ex vivo model, but does not compare expression changes in AD mouse models with human brains. Searches for mouse models, cross-species comparisons, and overlapping expression changes found no passage in our copy reporting the claimed overlap; pages were not provided. (LLM, conf=0.72)
Experimental — accuracy not yet measuredmiR-1908-5p is relevant to bipolar disorder despite its relatively low abundance.
“Notable among those, miR-1908–5p was previously observed to be differentially expressed in blood in the acute bipolar state compared to remission state62, which suggests that miR-1908–5p is relevant to bipolar disorder despite its relatively low abundance.”
From Mapping the microRNA landscape in the older adult brain and its genetic contribution to neuropsychiatric conditions (2024) · cites this paper as [62]
The Materials section discusses miRNA data from the Religious Orders Study and Rush Memory and Aging Project, but does not identify miR-1908-5p or address bipolar disorder. Searches for miR-1908-5p, acute bipolar state versus remission, and low abundance found no passage supporting the observation attributed to this source. (LLM, conf=0.77)
Experimental — accuracy not yet measured
The study performed single-nucleus RNA-sequencing of nuclei from 283 post-mortem brain samples across six brain regions from 48 ROSMAP participants.
“we performed single-nucleus RNA-sequencing (snRNA-seq) analysis of nuclei isolated from 283 post-mortem brain samples across six brain regions from 48 participants in the Religious Order Study (ROS) or the Rush Memory and Aging Project (MAP)28”
From Single-cell multiregion dissection of Alzheimer’s disease (2024) · cites this paper as [28]
miR-1908-5p was previously observed to be differentially expressed in blood in the acute bipolar state compared to remission state.
“Notable among those, miR-1908–5p was previously observed to be differentially expressed in blood in the acute bipolar state compared to remission state62, which suggests that miR-1908–5p is relevant to bipolar disorder despite its relatively low abundance.”
From Mapping the microRNA landscape in the older adult brain and its genetic contribution to neuropsychiatric conditions (2024) · cites this paper as [62]
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Single-cell transcriptomic analysis of Alzheimer’s disease
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Self-citationSingle cell RNA sequencing of human microglia uncovers a subset associated with Alzheimer’s disease
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MethodInfluentialSelf-citationSingle-cell multiregion dissection of Alzheimer’s disease
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MethodWan, Y.-W., Al-Ouran, R., Mangleburg, C. G., Perumal, T. M., Lee, T. V., Allison, K., Swarup, V., Funk, C. C., Gaiteri, C., Allen, M., et al. (2020) · Cell Reports · doi:10.1016/j.celrep.2020.107908 · Cited by 295 · see citing works
“Although some studies have identified selected overlaps in expression changes between AD mouse models and human brains (Bennett et al., 2018; Castillo et al., 2017; Mostafavi et al., 2018; Neuner et al., 2019; Rojo et al., 2017), other studies have questioned the overall degree of conservation (Burns et al.”
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Self-citationVarma, V. R., Wang, Y., An, Y., Varma, S., Bilgel, M., Doshi, J., Legido-Quigley, C., Delgado, J. C., Oommen, A. M., Roberts, J. A., et al. (2021) · PLOS Medicine · doi:10.1371/journal.pmed.1003615 · Cited by 97 · see citing works
Self-citationGenetic control of the human brain proteome
Robins, C., Wingo, A. P., Fan, W., Duong, D. M., Meigs, J., Gerasimov, E. S., Dammer, E. B., Cutler, D. J., Jager, P. L. D., Bennett, D. A., et al. (2019) · doi:10.1101/816652 · Cited by 104 · see citing works
Self-citationSex differences in brain protein expression and disease
Wingo, A. P., Liu, Y., Gerasimov, E. S., Vattathil, S. M., Liu, J., Cutler, D. J., Epstein, M. P., Blokland, G. A. M., Thambisetty, M., Troncoso, J. C., et al. (2023) · Nature Medicine · doi:10.1038/s41591-023-02509-y · Cited by 94 · see citing works
Self-citationEnhancing face validity of mouse models of Alzheimer’s disease with natural genetic variation
Onos, K. D., Uyar, A., Keezer, K. J., Jackson, H. M., Preuss, C., Acklin, C. J., O’Rourke, R., Buchanan, R., Cossette, T. L., Sukoff Rizzo, S. J., et al. (2019) · PLOS Genetics · doi:10.1371/journal.pgen.1008155 · Cited by 93 · see citing works
Tsai, A. P., Dong, C., Lin, P. B.-C., Messenger, E. J., Casali, B. T., Moutinho, M., Liu, Y., Oblak, A. L., Lamb, B. T., Landreth, G. E., et al. (2022) · Genome Medicine · doi:10.1186/s13073-022-01022-0 · Cited by 92 · see citing works
Welch, G. M., Boix, C. A., Schmauch, E., Davila-Velderrain, J., Victor, M. B., Dileep, V., Bozzelli, P. L., Su, Q., Cheng, J. D., Lee, A., et al. (2022) · Science Advances · doi:10.1126/sciadv.abo4662 · Cited by 84 · see citing works
Motoric cognitive risk syndrome and predictors of transition to dementia: a multicenter study
Verghese, J., Wang, C., Bennett, D. A., Lipton, R. B., Katz, M. J., & Ayers, E. (2019) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2019.03.011 · Cited by 79 · see citing works
Self-citationINPP5D regulates inflammasome activation in human microglia
Chou, V., Pearse, R. V., Aylward, A. J., Ashour, N., Taga, M., Terzioglu, G., Fujita, M., Fancher, S. B., Sigalov, A., Benoit, C. R., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-42819-w · Cited by 79 · see citing works
Self-citationDissecting the human leptomeninges at single-cell resolution
Kearns, N. A., Iatrou, A., Flood, D. J., De Tissera, S., Mullaney, Z. M., Xu, J., Gaiteri, C., Bennett, D. A., & Wang, Y. (2023) · Nature Communications · doi:10.1038/s41467-023-42825-y · Cited by 75 · see citing works
Self-citationCa2+ Dyshomeostasis Disrupts Neuronal and Synaptic Function in Alzheimer’s Disease
McDaid, J., Mustaly-Kalimi, S., & Stutzmann, G. E. (2020) · Cells · doi:10.3390/cells9122655 · Cited by 73 · see citing works
Shade, L. M. P., Katsumata, Y., Abner, E. L., Aung, K. Z., Claas, S. A., Qiao, Q., Heberle, B. A., Brandon, J. A., Page, M. L., Hohman, T. J., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01939-9 · Cited by 72 · see citing works
Self-citationTsai, A. P., Dong, C., Lin, P. B.-C., Oblak, A. L., Viana Di Prisco, G., Wang, N., Hajicek, N., Carr, A. J., Lendy, E. K., Hahn, O., et al. (2023) · Immunity · doi:10.1016/j.immuni.2023.08.008 · Cited by 71 · see citing works
Late‐life physical activity relates to brain tissue synaptic integrity markers in older adults
Casaletto, K., Ramos‐Miguel, A., VandeBunte, A., Memel, M., Buchman, A., Bennett, D., & Honer, W. (2022) · Alzheimer's & Dementia · doi:10.1002/alz.12530 · Cited by 53 · see citing works
Self-citationAssociation of small vessel disease with tau pathology
Kapasi, A., Yu, L., Petyuk, V., Arfanakis, K., Bennett, D. A., & Schneider, J. A. (2022) · Acta Neuropathologica · doi:10.1007/s00401-021-02397-x · Cited by 55 · see citing works
Self-citationPICALM Alzheimer’s risk allele causes aberrant lipid droplets in microglia
Kozlova, A., Zhang, S., Sudwarts, A., Zhang, H., Smirnou, S., Byeon, S. K., Thapa, C., Sun, X., Stephenson, K., Zhao, X., et al. (2025) · Nature · doi:10.1038/s41586-025-09486-x · Cited by 53 · see citing works
“The RADC brains came from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP) 62 .”
InfluentialSelf-citationEstrogen Receptor Genes, Cognitive Decline, and Alzheimer Disease
Oveisgharan, S., Yang, J., Yu, L., Burba, D., Bang, W., Tasaki, S., Grodstein, F., Wang, Y., Zhao, J., De Jager, P. L., et al. (2023) · Neurology · doi:10.1212/wnl.0000000000206833 · Cited by 53 · see citing works
Self-citationGreen, G. S., Yang, H., Fujita, M., Taga, M., Regev, A., Menon, V., Bennett, D. A. A., Habib, N., & De Jager, P. L. (2023) · Alzheimer's & Dementia · doi:10.1002/alz.083212 · Cited by 51 · see citing works
Self-citationGenetics of Gene Expression in the Aging Human Brain Reveal TDP-43 Proteinopathy Pathophysiology
Yang, H.-S., White, C. C., Klein, H.-U., Yu, L., Gaiteri, C., Ma, Y., Felsky, D., Mostafavi, S., Petyuk, V. A., Sperling, R. A., et al. (2020) · Neuron · doi:10.1016/j.neuron.2020.05.010 · Cited by 47 · see citing works
Self-citationXia, Y., Qadota, H., Wang, Z.-H., Liu, P., Liu, X., Ye, K. X., Matheny, C. J., Berglund, K., Yu, S. P., Drake, D., et al. (2022) · Science Advances · doi:10.1126/sciadv.abj8658 · Cited by 46 · see citing works
Self-citationTREM2 splice isoforms generate soluble TREM2 species that disrupt long-term potentiation
Moutinho, M., Coronel, I., Tsai, A. P., Di Prisco, G. V., Pennington, T., Atwood, B. K., Puntambekar, S. S., Smith, D. C., Martinez, P., Han, S., et al. (2023) · Genome Medicine · doi:10.1186/s13073-023-01160-z · Cited by 42 · see citing works
Evaluating the Alzheimer’s disease data landscape
Birkenbihl, C., Salimi, Y., Domingo‐Fernándéz, D., Lovestone, S., AddNeuroMed consortium, Fröhlich, H., Hofmann‐Apitius, M., Initiative, T. J. A. D. N., & Initiative, A. T. A. D. N. (2020) · Alzheimer's & Dementia: Translational Research & Clinical Interventions · doi:10.1002/trc2.12102 · Cited by 37 · see citing works
Ojelade, S. A., Lee, T. V., Giagtzoglou, N., Yu, L., Ugur, B., Li, Y., Duraine, L., Zuo, Z., Petyuk, V., De Jager, P. L., et al. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.07.041 · Cited by 42 · see citing works
Self-citationTrends in postmortem neurodegenerative and cerebrovascular neuropathologies over 25 years
Grodstein, F., Leurgans, S. E., Capuano, A. W., Schneider, J. A., & Bennett, D. A. (2023) · JAMA Neurology · doi:10.1001/jamaneurol.2022.5416 · Cited by 41 · see citing works
Self-citationMulti-cellular communities are perturbed in the aging human brain and Alzheimer’s disease
Cain, A., Taga, M., McCabe, C., Green, G., Hekselman, I., White, C. C., Lee, D. I., Gaur, P., Rozenblatt-Rosen, O., Zhang, F., et al. (2020) · doi:10.1101/2020.12.22.424084 · Cited by 143 · see citing works
Self-citationBiesbroek, J. M., Coenen, M., DeCarli, C., Fletcher, E. M., Maillard, P. M., Initiative, A. D. N., Barkhof, F., Barnes, J., Benke, T., Chen, C. P. L. H., et al. (2024) · Alzheimer's & Dementia · doi:10.1002/alz.13765 · Cited by 38 · see citing works
Wang, J., Dove, A., Song, R., Qi, X., Ma, J., Bennett, D. A., & Xu, W. (2022) · Alzheimer's & Dementia · doi:10.1002/alz.12625 · Cited by 34 · see citing works
Self-citationWu, Y., Liu, Q., Qiu, Y., & Xie, L. (2022) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1010367 · Cited by 34 · see citing works
Blood pressure variability, dementia, and role of antihypertensive medications in older adults
Mahinrad, S., Bennett, D. A., Sorond, F. A., & Gorelick, P. B. (2023) · Alzheimer's & Dementia · doi:10.1002/alz.12935 · Cited by 32 · see citing works
Self-citationKang, M., Ang, T. F. A., Devine, S. A., Sherva, R., Mukherjee, S., Trittschuh, E. H., Gibbons, L. E., Scollard, P., Lee, M., Choi, S.-E., et al. (2023) · Molecular Neurodegeneration · doi:10.1186/s13024-023-00633-4 · Cited by 29 · see citing works
Lomoio, S., Pandey, R. S., Rouleau, N., Menicacci, B., Kim, W., Cantley, W. L., Haydon, P. G., Bennett, D. A., Young-Pearse, T. L., Carter, G. W., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02147-3 · Cited by 25 · see citing works
Self-citationJury-Garfe, N., Redding-Ochoa, J., You, Y., Martínez, P., Karahan, H., Chimal-Juárez, E., Johnson, T. S., Zhang, J., Resnick, S., Kim, J., et al. (2024) · Acta Neuropathologica · doi:10.1007/s00401-024-02775-1 · Cited by 22 · see citing works
“However, several studies have revealed the existence of aged individuals harboring a high burden of brain lesions at autopsy while remaining cognitively intact, indicating resilience to AD pathology [3, 7, 21, 22, 56, 57, 68, 76, 78, 96].”
BackgroundBrand, Y. E., Kluge, F., Palmerini, L., Paraschiv-Ionescu, A., Becker, C., Cereatti, A., Maetzler, W., Sharrack, B., Vereijken, B., Yarnall, A. J., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-71491-3 · Cited by 19 · see citing works
Self-citationEngel, A., Wagner, V., Hahn, O., Foltz, A. G., Atkins, M., Beganovic, A., Guldner, I. H., Lu, N., Saksena, A., Fischer, U., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-59860-6 · Cited by 18 · see citing works
Vattathil, S. M., Gerasimov, E. S., Canon, S. M., Lori, A., Tan, S. S. M., Kim, P. J., Liu, Y., Lai, E. C., Bennett, D. A., Wingo, T. S., et al. (2024) · Nature Aging · doi:10.1038/s43587-024-00778-x · Cited by 14 · see citing works
Self-citationM3NetFlow: A multi-scale multi-hop graph AI model for integrative multi-omic data analysis
Zhang, H., Goedegebuure, S. P., Ding, L., DeNardo, D., Fields, R. C., Province, M., Chen, Y., Payne, P., & Li, F. (2025) · iScience · doi:10.1016/j.isci.2025.111920 · Cited by 12 · see citing works
Grodstein, F., James, B. D., Chen, Y., Capuano, A. W., Power, M. C., Bennett, D. A., Bynum, J. P. W., & Barnes, L. L. (2024) · The Journals of Gerontology: Series A · doi:10.1093/gerona/glad235 · Cited by 11 · see citing works
Self-citationAn interpretable deep learning framework identifies proteomic drivers of Alzheimer’s disease
Panizza, E., & Cerione, R. A. (2024) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2024.1379984 · Cited by 11 · see citing works
INPP5D/SHIP1 regulates inflammasome activation in human microglia
Chou, V., Fancher, S. B., Pearse, R. V., Lee, H., Lam, M., Seyfried, N. T., Bennett, D. A., De Jager, P. L., Menon, V., & Young-Pearse, T. L. (2023) · doi:10.1101/2023.02.25.530025 · Cited by 8 · see citing works
Self-citationPLCG2 as a Risk Factor for Alzheimer's Disease.
Tsai, A. P., Dong, C., Preuss, C., Moutinho, M., Lin, P. B.-C., Hajicek, N., Sondek, J., Bissel, S. J., Oblak, A. L., Carter, G. W., et al. (2020) · doi:10.21203/rs.3.rs-38216/v1 · Cited by 7 · see citing works
Establishing the relationship between brain cellular senescence and brain structure
Lund, A. N., Kopell, B. H., Golestani, N., Vornholt, E., Thompson, R. C., Liharska, L. E., Luo, Y., Cheng, E., Park, Y. J., Fennessy, B., et al. (2026) · Cell · doi:10.1016/j.cell.2025.10.014 · Cited by 6 · see citing works
INPP5D/SHIP1 regulates endo-lysosomal function and cargo-selective phagocytosis in human microglia
Terzioglu, G., Karp, E. S., Heuer, S. E., Chadarevian, J. P., Ahsan, F. M., Haage, V. C., Davtyan, H., Fogo, G. M., Curle, A. J., Ashour, N., et al. (2025) · doi:10.1101/2025.10.27.684632 · Cited by 3 · see citing works
Self-citationThe transcriptional and cellular landscape of cognitive resilience to Alzheimer’s disease
Khera, N., Raju, R. M., & Lipton, S. A. (2025) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2025.1665802 · Cited by 3 · see citing works
Genetic drivers of progression in Alzheimer’s disease are distinct from disease risk
Cohen, C. E., Fernandez, S., Yaman, U., Ehyaei, A. R., Kodosaki, E., Askarova, A., Porter, T., O’Brien, E., Study, A. I. B. A. L., Initiative, A. D. N., et al. (2026) · Alzheimer's Research & Therapy · doi:10.1186/s13195-026-02036-1 · Cited by 1 · see citing works
- Authors
- Bennett, D. A., Buchman, A. S., Boyle, P. A., Barnes, L. L., Wilson, R. S., & Schneider, J. A.
- Affiliations
- Rush University Medical Center (US)
- Corresponding author
- Bennett, David A.
- ORCID
- Venue
- Journal of Alzheimer's Disease
- Publisher
- SAGE Publications
- Published
- 2018-06-12
- Volume
- 64
- Issue
- s1
- Pages
- S161-S189
- ISSN
- 1387-2877 (ISSN-L)
- 1875-8908
- PMC
- PMC6380522
- OpenAlex
- W2809330972
- Cited by
- 1,260
- References
- 50
- Citations by year
- 2026: 160 · 2025: 249 · 2024: 194 · 2023: 181 · 2022: 169 · 2021: 127 · 2020: 88 · 2019: 75 · 2018: 12 · 2017: 1 · 2013: 1
- FWCI
- 11.67
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Journal of Alzheimer s Disease (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging (R01AG043379, R01AG017917, R01AG056352, R01AG042210, RF1AG022018, U01AG046152, R01AG036042, R01AG015819, P30AG010161, R01AG040039, R01AG047976, RF1AG054057, RF1AG015819, RF1AG036042, R01AG033678, R01AG034374, R01AG022018)
- National Institute of Neurological Disorders and Stroke (UH3NS100599, UH2NS100599, R01NS078009, UF1NS100599)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
- Keywords
- Alzheimer's disease, aging
- MeSH terms
- Aging, Alzheimer Disease, Humans, Memory, United States, Religious Personnel
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