Bridging the gap: Multi‐omics profiling of brain tissue in Alzheimer's disease and older controls in multi‐ethnic populations
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Abstract
INTRODUCTION: Multi‐omics studies in Alzheimer's disease (AD) revealed many potential disease pathways and therapeutic targets. Despite their promise of precision medicine, these studies lacked Black Americans (BA) and Latin Americans (LA), who are disproportionately affected by AD. METHODS: To bridge this gap, Accelerating Medicines Partnership in Alzheimer's Disease (AMP‐AD) expanded brain multi‐omics profiling to multi‐ethnic donors. RESULTS: We generated multi‐omics data and curated and harmonized phenotypic data from BA ( n = 306), LA ( n = 326), or BA and LA ( n = 4) brain donors plus non‐Hispanic White ( n = 252) and other ( n = 20) ethnic groups, to establish a foundational dataset enriched for BA and LA participants. This study describes the data available to the research community, including transcriptome from three brain regions, whole genome sequence, and proteome measures. DISCUSSION: The inclusion of traditionally underrepresented groups in multi‐omics studies is essential to discovering the full spectrum of precision medicine targets that will be pertinent to all populations affected with AD. Highlights: Accelerating Medicines Partnership in Alzheimer's Disease Diversity Initiative led brain tissue profiling in multi‐ethnic populations. Brain multi‐omics data is generated from Black American, Latin American, and non‐Hispanic White donors. RNA, whole genome sequencing and tandem mass tag proteomicsis completed and shared. Multiple brain regions including caudate, temporal and dorsolateral prefrontal cortex were profiled.
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Large-scale studies such as ROS/MAP have used multi-omic data from dorsolateral prefrontal cortex tissue to identify Alzheimer's disease subtypes that exhibit distinct cognitive trajectories.
“Large-scale studies such as ROS/MAP project have utilized multi-omic data from dorsolateral prefrontal cortex tissue to identify AD subtypes that exhibit distinct cognitive trajectories.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [397]
The Methods and Results sections identify ROS/MAP as a contributing cohort and describe multi-omics profiling of dorsolateral prefrontal cortex tissue. The paper does not report using those data to identify Alzheimer’s disease subtypes with distinct cognitive trajectories (searched: subtypes, cognitive trajectories). (LLM, conf=0.86)
Experimental — accuracy not yet measuredDeep learning frameworks have uncovered novel biological pathways, including those related to neuroinflammation and metabolic regulation, which account for diverse disease trajectories.
“Deep learning frameworks continue to uncover novel biological pathways, including those related to neuroinflammation and metabolic regulation, which account for diverse disease trajectories397,398.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [397]
The Discussion (page not provided) says multi-omics data revealed alterations in pathways including innate immunity and mitochondrial energetics, supporting heterogeneous molecular etiologies. It does not attribute those findings to deep learning frameworks or establish that the pathways account for diverse disease trajectories. (LLM, conf=0.84)
Experimental — accuracy not yet measuredAlzheimer's disease subtypes identified from ROS/MAP differ in lipid metabolism and synaptic function.
“These subtypes differ in lipid metabolism and synaptic function, highlighting the utility of combining molecular and clinical data to capture disease heterogeneity124,255,396,397.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [397]
The Study populations section identifies ROS and MAP as cohorts, and the Discussion mentions heterogeneous molecular changes, including synaptic biology. Neither passage reports ROS/MAP Alzheimer’s subtypes or differences between them in lipid metabolism and synaptic function. Searches for “subtypes,” “lipid metabolism,” and “synaptic function” found no passage addressing those differences; page numbers were unavailable in our copy. (LLM, conf=0.76)
Experimental — accuracy not yet measuredReviews of multi-omics analyses in brain tissue have emphasized the importance of time-series data in capturing the dynamic evolution of molecular and clinical features.
“Reviews of multi-omics analyses in brain tissue have emphasized the importance of time-series data in capturing the dynamic evolution of molecular and clinical features397.”
From Artificial intelligence-driven multi-omics approaches in Alzheimer's disease: Progress, challenges, and future directions (2025) · cites this paper as [397]
The Discussion (page unavailable) emphasizes sampling multiple brain regions because regions are affected at different disease stages. It does not discuss the importance of time-series data for capturing evolving molecular and clinical features; searches for time-series data and longitudinal dynamics found no such passage. (LLM, conf=0.76)
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Carrasquillo, M. M., Allen, M., Burgess, J. D., Wang, X., Strickland, S. L., Aryal, S., Siuda, J., Kachadoorian, M. L., Medway, C., Younkin, C. S., et al. (2017) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2016.10.005 · Cited by 58 · cited 1× · see citing works
“…specific biological pathways, including but not limitedtoinnateimmunity,synapticbiology,myelination,vascularbiol-ogy, and mitochondrial energetics, 28–30,32–34,37,39,45,54,86–89 thereby T. Seyfried, Anna K. Greenwood, and Nilüfer Ertekin-Taner obtained funding for and designed the AMP-AD…”
Self-citationAllen, M., Wang, X., Serie, D., Strickland, S. L., Burgess, J. D., Koga, S., Younkin, C. S., Nguyen, T., Malphrus, K. G., Lincoln, S., et al. (2018) · Acta Neuropathologica · doi:10.1007/s00401-018-1900-5 · Cited by 58 · see citing works
Self-citationMa, Y., Dammer, E. B., Felsky, D., Duong, D. M., Klein, H., White, C. C., Zhou, M., Logsdon, B. A., Aubin, C., Xu, J., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-27204-9 · Cited by 58 · see citing works
Self-citationSantos, O. A., Pedraza, O., Lucas, J. A., Duara, R., Greig‐Custo, M. T., Al‐Shaikh, F. S. H., Liesinger, A. M., Bieniek, K. F., Hinkle, K. M., Lesser, E. R., et al. (2019) · Alzheimer s & Dementia · doi:10.1016/j.jalz.2018.12.013 · Cited by 56 · see citing works
Self-citationChallenges and Considerations Related to Studying Dementia in Blacks/African Americans
Ighodaro, E. T., Nelson, P. T., Kukull, W. A., Schmitt, F. A., Abner, E. L., Caban‐Holt, A., Bardach, S. H., Hord, D. C., Glover, C. M., Jicha, G. A., et al. (2017) · Journal of Alzheimer s Disease · doi:10.3233/jad-170242 · Cited by 55 · see citing works
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Self-citationPlasma Biomarkers of Alzheimer’s Disease in African Americans
Deniz, K., Ho, C. C. G., Malphrus, K. G., Reddy, J. S., Nguyen, T., Carnwath, T., Crook, J. E., Lucas, J. A., Graff‐Radford, N. R., Carrasquillo, M. M., et al. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-200828 · Cited by 41 · see citing works
Self-citationEvidence of Recessive Alzheimer Disease Loci in a Caribbean Hispanic Data Set
Ghani, M., Sato, C., Lee, J. H., Reitz, C., Moreno, D., Mayeux, R. P., George‐Hyslop, P. S., & Rogaeva, E. A. (2013) · JAMA Neurology · doi:10.1001/jamaneurol.2013.3545 · Cited by 40 · see citing works
Self-citationAfrican American exome sequencing identifies potential risk variants at Alzheimer disease loci
N’Songo, A., Carrasquillo, M. M., Wang, X., Burgess, J. D., Nguyen, T., Asmann, Y. W., Serie, D., Younkin, S. G., Allen, M., Pedraza, O., et al. (2017) · Neurology Genetics · doi:10.1212/nxg.0000000000000141 · Cited by 36 · see citing works
Self-citationMAPT haplotype–stratified GWAS reveals differential association for AD risk variants
Strickland, S. L., Reddy, J. S., Allen, M., N’Songo, A., Burgess, J. D., Corda, M. M., Ballard, T., Wang, X., Carrasquillo, M. M., Biernacka, J. M., et al. (2020) · Alzheimer s & Dementia · doi:10.1002/alz.12099 · Cited by 35 · see citing works
Self-citationWang, X., Allen, M., İş, Ö., Reddy, J. S., Tutor‐New, F. Q., Casey, M. C., Carrasquillo, M. M., Oatman, S. R., Min, Y., Asmann, Y. W., et al. (2021) · Journal of Clinical Investigation · doi:10.1172/jci149904 · Cited by 30 · see citing works
Self-citationAge-at-onset linkage analysis in Caribbean Hispanics with familial late-onset Alzheimer’s disease
Lee, J. H., Barral, S., Cheng, R., Chacon, I. J., Santana, V., Williamson, J., Lantigua, R., Medrano, M., Velázquez, I. J., Stern, Y., et al. (2008) · Neurogenetics · doi:10.1007/s10048-007-0103-3 · Cited by 29 · see citing works
Self-citationPrecision oncology for gallbladder cancer: insights from genetic alterations and clinical practice
Lin, J., Dong, K., Bai, Y., Zhao, S., Dong, Y., Shi, J., Shi, W., Long, J., Yang, X., Wang, D., et al. (2019) · Annals of Translational Medicine · doi:10.21037/atm.2019.08.67 · Cited by 29 · see citing works
Genetics of Alzheimer’s Disease in the African American Population
Logue, M. W., Dasgupta, S., & Farrer, L. A. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12165189 · Cited by 28 · see citing works
Data-driven science and diversity in the All of Us Research Program
Ginsburg, G. S., Denny, J. C., & Schully, S. D. (2023) · Science Translational Medicine · doi:10.1126/scitranslmed.ade9214 · Cited by 27 · see citing works
Oatman, S. R., Reddy, J. S., Quicksall, Z., Carrasquillo, M. M., Wang, X., Liu, C., Yamazaki, Y., Nguyen, T., Malphrus, K. G., Heckman, M. G., et al. (2023) · Molecular Neurodegeneration · doi:10.1186/s13024-022-00592-2 · Cited by 25 · see citing works
Self-citationMin, Y., Wang, X., İş, Ö., Patel, T., Gao, J., Reddy, J. S., Quicksall, Z., Nguyen, T., Lin, S., Tutor‐New, F. Q., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-42626-3 · Cited by 20 · see citing works
Self-citationGlover, C. M., Shah, R. C., Bennett, D. A., Wilson, R. S., & Barnes, L. L. (2020) · Ethnicity & Disease · doi:10.18865/ed.30.s2.709 · Cited by 20 · see citing works
Self-citationEffects of Alzheimer and Lewy Body Disease Pathologies on Brain Metabolism
Lee, Y., Jeon, S., Park, M.-C., Kang, S. W., Yoon, S. H., Baik, K., Lee, P. H., Sohn, Y. H., Ye, B. S., & Initiative, T. A. D. N. (2022) · Annals of Neurology · doi:10.1002/ana.26355 · Cited by 19 · see citing works
Baloni, P., Arnold, M., Moreno, H., et al. (2021) · medRxiv · doi:10.1101/2021.07.16.21260601 · Cited by 19 · see citing works
Li, K., Rashid, T., Li, J.-Q., Honnorat, N., Nirmala, A. B., Fadaee, E., Wang, D., Charisis, S., Liu, H., Franklin, C. G., et al. (2023) · Journal of Alzheimer's Disease · doi:10.3233/jad-230389 · Cited by 18 · see citing works
Self-citationMulti-omic atlas of the parahippocampal gyrus in Alzheimer’s disease
Coleman, C., Wang, M., Wang, E., Micallef, C., Shao, Z., Vicari, J. M., Li, Y., Yu, K., Cai, D., Peng, J., et al. (2023) · Scientific Data · doi:10.1038/s41597-023-02507-2 · Cited by 16 · see citing works
Self-citationARTS: automated randomization of multiple traits for study design
Maienschein‐Cline, M., Lei, Z., Gardeux, V., Abbasi, T. A., Machado, R. F., Gordeuk, V. R., Desai, A. A., Saraf, S. L., Bahroos, N., & Lussier, Y. A. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu075 · Cited by 15 · see citing works
Association of Lewy Bodies With Age-Related Clinical Characteristics in Black and White Decedents
Nag, S., Barnes, L. L., Yu, L., Buchman, A. S., Bennett, D. A., Schneider, J. A., & Wilson, R. S. (2021) · Neurology · doi:10.1212/wnl.0000000000012324 · Cited by 15 · see citing works
Self-citationStrickland, S. L., Morel, H., Prusinski, C., Allen, M., Patel, T. A., Carrasquillo, M. M., Conway, O. J., Lincoln, S. J., Reddy, J. S., Nguyen, T., et al. (2020) · Acta Neuropathologica Communications · doi:10.1186/s40478-020-01050-0 · Cited by 15 · see citing works
Self-citationMa, Y., Yu, L., Olah, M., Smith, R. G., Oatman, S. R., Allen, M., Pishva, E., Zhang, B., Menon, V., Ertekin‐Taner, N., et al. (2021) · Alzheimer s & Dementia · doi:10.1002/alz.12425 · Cited by 14 · see citing works
Self-citationReddy, J. S., Jin, J., Lincoln, S., Ho, C. C. G., Crook, J. E., Wang, X., Malphrus, K. G., Nguyen, T., Tamvaka, N., Greig‐Custo, M. T., et al. (2022) · EBioMedicine · doi:10.1016/j.ebiom.2022.103929 · Cited by 9 · see citing works
Self-citationStites, S. D., & Coe, N. B. (2023) · Journal of Alzheimer s Disease · doi:10.3233/jad-220507 · Cited by 9 · see citing works
Ma, Y., Yu, L., Olah, M., Smith, R. G., Oatman, S. R., Allen, M., Pishva, E., Zhang, B., Menon, V., Ertekin-Taner, N., et al. (2020) · Alzheimer s & Dementia · doi:10.1002/alz.043533 · Cited by 7 · see citing works
Self-citationHendricks‐Sturrup, R., Edgar, L. M., Johnson-Glover, T., & Lu, C. Y. (2020) · SAGE Open Medicine · doi:10.1177/2050312120901740 · Cited by 4 · see citing works
Flagged first, then by citations
Cited by
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Ren, F., Wei, J., Chen, Q., Hu, M., Yu, L., Mi, J., Zhou, X., Qin, D., Wu, J., & Wu, A. (2025) · Acta Pharmaceutica Sinica B · doi:10.1016/j.apsb.2025.07.030 · Cited by 97 · see citing works
Levites, Y., Dammer, E. B., Ran, Y., Tsering, W., Duong, D. M., Abreha, M. H., Gadhavi, J. D., Lolo, K., Trejo‐Lopez, J. A., Phillips, J., et al. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101669 · Cited by 57 · see citing works
Self-citationLarge‐scale deep proteomic analysis in Alzheimer's disease brain regions across race and ethnicity
Seifar, F., Fox, E. J., Shantaraman, A., Liu, Y., Dammer, E. B., Modeste, E., Duong, D. M., Yin, L., Trautwig, A. N., Guo, Q., et al. (2024) · Alzheimer's & Dementia · doi:10.1002/alz.14360 · Cited by 52 · see citing works
Self-citationThe ROSMAP project: aging and neurodegenerative diseases through omic sciences
Pérez-González, A. P., García-Kroepfly, A. L., Pérez-Fuentes, K. A., García-Reyes, R. I., Solis-Roldan, F. F., Alba-González, J. A., Lemus, E. H., & de Anda‐Jáuregui, G. (2024) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2024.1443865 · Cited by 44 · see citing works
Wingo, A. P., Liu, Y., Vattathil, S. M., Gerasimov, E. S., Mei, Z., Ravindran, S. P., Liu, J., Shantaraman, A., Seifar, F., Wang, E., et al. (2025) · Nature Genetics · doi:10.1038/s41588-025-02291-2 · Cited by 21 · see citing works
Self-citationDong, J., & Zhong, H. (2025) · Neurology International · doi:10.3390/neurolint17120197 · Cited by 16 · see citing works
Population-scale cross-disorder atlas of the human prefrontal cortex at single-cell resolution
Fullard, J. F., Nm, P., Lee, D., Mathur, D. D., Therrien, K., Hong, A., Casey, C., Shao, Z., Alvia, M., Argyriou, S., et al. (2025) · Scientific Data · doi:10.1038/s41597-025-04687-5 · Cited by 17 · see citing works
Self-citationA primer on copper biology in the brain
Lane, A. R., Roberts, B. R., Fahrni, C. J., & Faúndez, V. (2025) · Neurobiology of Disease · doi:10.1016/j.nbd.2025.106974 · Cited by 15 · see citing works
An analysis of RNA quality metrics in human brain tissue
Tian, J., Lam, T. G., Ross, S. K., Ciener, B., Leskinen, S., Sivakumar, S., Bennett, D. A., Menon, V., McKhann, G. M., Runnels, A. M., et al. (2024) · Journal of Neuropathology & Experimental Neurology · doi:10.1093/jnen/nlae132 · Cited by 15 · see citing works
Self-citationNetwork-based analyses of multiomics data in biomedicine
Kumar, R., Romano, J. D., & Ritchie, M. D. (2025) · BioData Mining · doi:10.1186/s13040-025-00452-x · Cited by 15 · see citing works
Wojtas, A., Rathore, S., Dammer, E. B., Yu, L., Seifar, F., Gadhavi, J. D., Shantaraman, A., Duong, D. M., Wu, F., Liu, Y., et al. (2025) · medRxiv · doi:10.1101/2025.10.08.25337413 · Cited by 8 · see citing works
Self-citationOatman, S. R., Reddy, J. S., Atashgaran, A., Wang, X., Min, Y., Quicksall, Z., Vanelderen, F., Carrasquillo, M. M., Liu, C.-C., Yamazaki, Y., et al. (2026) · Nature Communications · doi:10.1038/s41467-026-68864-9 · Cited by 6 · see citing works
Self-citationKuchenbecker, L. A., Thompson, K. J., Hurst, C. D., Huang, Y.-N., Heckman, M. G., Reddy, J. S., Nguyen, T., Casellas, H. L., Sotelo, K. D., Reddy, D. J., et al. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.70505 · Cited by 4 · see citing works
Self-citationLish, A. M., & Young‐Pearse, T. L. (2026) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2026.103165 · Cited by 3 · see citing works
Logue, M. W., Labadorf, A. T., O’Neill, N. K., Dickson, D. W., Dugger, B. N., Flanagan, M. E., Frosch, M. P., Gearing, M., Jin, L., Kofler, J., et al. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.70629 · Cited by 2 · see citing works
Self-citationMulti‐omic expression of the VEGF family relates to Alzheimer's disease across diverse populations
Libby, J. B., Deters, K., Ertekin‐Taner, N., Carrasquillo, M. M., Allen, M., Jager, P. L. D., Menon, V., Zhang, B., Haroutunian, V. H., Levey, A. I., et al. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.71100 · Cited by 2 · see citing works
Self-citationMulti-ancestry studies in multi-omics of Alzheimer’s disease: Recent insights and future directions
Shir, D., Seifar, F., & Ertekin‐Taner, N. (2026) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2026.103205 · Cited by 2 · see citing works
Self-citationTechnological advances enabling an enhanced understanding of early Alzheimer's disease
Au, R., Bose, N., Imam, F. B., & Kolachalama, V. B. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.70883 · Cited by 2 · see citing works
Farfel, J. M., Capuano, A. W., Nag, S., Sampaio, M. C. M., Gibbons, J., Wilson, R. S., & Bennett, D. A. (2025) · Neuroepidemiology · doi:10.1159/000547564 · Cited by 1 · see citing works
Self-citationKuchenbecker, L. A., Thompson, K. J., Hurst, C. D., Opdenbosch, B. M., Heckman, M. G., Reddy, J. S., Nguyen, T., Casellas, H. L., Sotelo, K. D., Reddy, D. J., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.07.27.605373 · Cited by 1 · see citing works
Self-citationBenova, N., Kuklinkova, R., Haigh, J. L., Boyne, J. R., & Anene, C. A. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.31.667983 · Cited by 1 · see citing works
Genotyping TOMM40′523 poly-T polymorphisms using whole-genome sequencing
Vialle, R. A., Yu, L., Li, Y., Raittz, R. T., Farfel, J. M., Jager, P. L. D., Schneider, J. A., Barnes, L. L., Tasaki, S., & Bennett, D. A. (2025) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2025.100488
Self-citationSchweickart, A., Batra, R., Huynh, K., Blach, C., Kueider‐Paisley, A., Reddy, J. S., Klein, G., Bennett, D. A., Meikle, P. J., Zhang, B., et al. (2025) · medRxiv · doi:10.1101/2025.11.04.25339489
Self-citationZafarullah, M., Ponzini, M. D., Kim, K. M., Hagerman, P. J., Hagerman, R. J., & Tassone, F. (2026) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2026.1752903
Genetic and Proteomic Investigation of the Smoking-Parkinson’s Disease AssociationPreprint
Shi, M., Gunawan, T., Setzer, M. R., Okashah, N., Liu, Y., Wingo, T. S., Wingo, A. P., Weintraub, D., Schwarzschild, M. A., Rentsch, C. T., et al. (2026) · medRxiv · doi:10.64898/2026.04.17.26351138
Self-citationColocalization and discordance between plasma and brain protein quantitative trait lociPreprint
Cheng, Y., Zhang, W., & Lu, T. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.01.722237
Doddi, A., Dawes, P., Chan, Y., & Lim, E. T. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.06.08.727881
Schweickart, A., Batra, R., Huynh, K., Blach, C., Kueider‐Paisley, A., Reddy, J. S., Bennett, D. A., Meikle, P. J., Zhang, B., Jager, P. L. D., et al. (2026) · Alzheimer s & Dementia · doi:10.1002/alz.71690
Self-citation
- Authors
- Reddy, J. S., Heath, L., Linden, A. V., Allen, M., Lopes, K. D. P., Seifar, F., Wang, E., Ma, Y., Poehlman, W. L., Quicksall, Z. S., Runnels, A., Wang, Y., Duong, D. M., Yin, L., Xu, K., Modeste, E. S., Shantaraman, A., Dammer, E. B., Ping, L., Oatman, S. R., Scanlan, J., Ho, C., Carrasquillo, M. M., Atik, M., Yepez, G., Mitchell, A. O., Nguyen, T. T., Chen, X., Marquez, D. X., Reddy, H., Xiao, H., Seshadri, S., Mayeux, R., Prokop, S., Lee, E. B., Serrano, G. E., Beach, T. G., Teich, A. F., Haroutunian, V., Fox, E. J., Gearing, M., Wingo, A., Wingo, T., Lah, J. J., Levey, A. I., Dickson, D. W., Barnes, L. L., De Jager, P., Zhang, B., Bennett, D., Seyfried, N. T., Greenwood, A. K., & Ertekin‐Taner, N.
- Affiliations
- Mayo Clinic in Florida (US)
- Sage Bionetworks (US)
- Rush Alzheimer's Disease Center Rush University Medical Center Chicago Illinois USA
- Emory University (US)
- Icahn School of Medicine at Mount Sinai (US)
- Columbia University Irving Medical Center (US)
- New York Genome Center (US)
- Rush University Medical Center (US)
- Mayo Clinic Florida Jacksonville Florida USA
- The University of Texas at San Antonio (US)
- University of Florida (US)
- University of Pennsylvania (US)
- Banner Sun Health Research Institute (US)
- Columbia University Irving Medical Center New York New York USA
- Corresponding author
- Greenwood, Anna K.
- Ertekin‐Taner, Nilüfer
- ORCID
- Reddy, Joseph S.
- Heath, Laura
- Linden, Abby Vander
- Allen, Mariet
- Seifar, Fatemeh
- Wang, Erming
- Ma, Yiyi
- Poehlman, William L.
- Quicksall, Zachary S.
- Runnels, Alexi
- Wang, Yanling
- Duong, Duc M.
- Xu, Kaiming
- Modeste, Erica S.
- Shantaraman, Anantharaman
- Dammer, Eric B.
- Ping, Lingyan
- Ho, Charlotte
- Carrasquillo, Minerva M.
- Nguyen, Thuy T.
- Chen, Xianfeng
- Seshadri, Sudha
- Mayeux, Richard
- Prokop, Stefan
- Lee, Edward B.
- Serrano, Geidy E.
- Beach, Thomas G.
- Teich, Andrew F.
- Fox, Edward J.
- Gearing, Marla
- Wingo, Aliza
- Wingo, Thomas
- Lah, James J.
- Levey, Allan I.
- Dickson, Dennis W.
- Barnes, Lisa L.
- Zhang, Bin
- Bennett, David
- Seyfried, Nicholas T.
- Greenwood, Anna K.
- Ertekin‐Taner, Nilüfer
- Venue
- Alzheimer's & Dementia
- Publisher
- Wiley
- Published
- 2024-08-30
- Volume
- 20
- Issue
- 10
- Pages
- 7174-7192
- ISSN
- 1552-5260 (ISSN-L)
- 1552-5279
- PMC
- PMC11485084
- OpenAlex
- W4402094108
- Cited by
- 29
- References
- 101
- Citations by year
- 2026: 9 · 2025: 14 · 2024: 6
- FWCI
- 8.25
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Alzheimer s & Dementia (publishedVersion, cc-by-nc-nd)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by-nc-nd)
- PubMed Central (submittedVersion, cc-by-nc-nd)
- Funders
- National Institute on Aging (P50 AG016574, R01 AG032990, U01 AG046139, R01 AG018023, U01 AG006576, U01 AG006786, R01 AG025711, R01 AG017216, R01 AG003949, P30AG072979, P01AG066597, U19AG062418, U01AG061357, RF1AG062181, P30AG066511)
- Mayo Foundation for Medical Education and Research
- National Institute of Neurological Disorders and Stroke (R01‐NS080820)
- Arizona Department of Health Services
- Arizona Biomedical Research Commission
- Michael J. Fox Foundation for Parkinson's Research
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Keywords
- Alzheimer's disease, multi-omics profiling
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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