Human whole genome genotype and transcriptome data for Alzheimer’s and other neurodegenerative diseases
Open accessAbstract
Previous genome-wide association studies (GWAS), conducted by our group and others, have identified loci that harbor risk variants for neurodegenerative diseases, including Alzheimer's disease (AD). Human disease variants are enriched for polymorphisms that affect gene expression, including some that are known to associate with expression changes in the brain. Postulating that many variants confer risk to neurodegenerative disease via transcriptional regulatory mechanisms, we have analyzed gene expression levels in the brain tissue of subjects with AD and related diseases. Herein, we describe our collective datasets comprised of GWAS data from 2,099 subjects; microarray gene expression data from 773 brain samples, 186 of which also have RNAseq; and an independent cohort of 556 brain samples with RNAseq. We expect that these datasets, which are available to all qualified researchers, will enable investigators to explore and identify transcriptional mechanisms contributing to neurodegenerative diseases.
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The Mayo cohort includes 545 samples from temporal cortex (TCX) and cerebellum (CBE).
“while the Mayo cohort includes 545 samples from temporal cortex (TCX) and cerebellum (CBE) (Fig. 1, A and B, and table S1).”
From Comprehensive characterization of the transcriptional landscape in Alzheimer’s disease (AD) brains (2025) · cites this paper as [39]
The Background & Summary identifies a Mayo RNAseq cohort with samples from temporal cortex (TCX) and cerebellum (CER), but gives its size as 556, not 545. Methods > Study Populations specifies 278 samples from each region. Our copy therefore supports the brain regions but not the stated sample count; no page numbers are available in the indexed passages. (LLM, conf=0.88)
Experimental — accuracy not yet measuredDiscrepancies in RNA-seq library preparation methods, sequencing techniques, sequencing depth, and AD definition between the MSBB and Mayo cohorts could introduce biases in data interpretation.
“Discrepancies in RNA-seq library preparation methods, sequencing techniques, sequencing depth, and AD definition between the MSBB and Mayo cohorts could introduce biases in data interpretation (38, 39).”
From Comprehensive characterization of the transcriptional landscape in Alzheimer’s disease (AD) brains (2025) · cites this paper as [39]
Methods > Molecular Data (page unavailable) describes the Mayo RNA-seq library preparation and sequencing methods and cautions that samples prepared and sequenced at different times should be treated as separate datasets. Methods > Study Populations describes Mayo diagnostic categories. The copy does not compare Mayo with MSBB or establish differences in sequencing depth or AD definitions between those cohorts, so it does not support the full proposed source of bias. (LLM, conf=0.82)
Experimental — accuracy not yet measuredThe two bulk RNA-seq studies used AD samples and controls from the same patient cohorts but took unique approaches for co-expression network analysis.
“These studies both used AD samples and controls from the same patient cohorts (Religious Orders Study and Memory and Aging Project, Mayo Clinic, Mount Sinai School of Medicine),64,65,66 but they took unique approaches for co-expression network analysis.”
From hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data (2023) · cites this paper as [65]
AMP-AD resource includes post mortem RNA-seq datasets from ROSMAP, MSSM, and Mayo Clinic, encompassing >1200 individuals across seven brain regions.
“This resource includes post mortem RNA‐seq datasets from the Religious Orders Study and Memory and Aging Project (ROSMAP) 40 , Mount Sinai School of Medicine (MSSM), 39 and Mayo Clinic, 38 encompassing > 1200 individuals across seven brain regions (Figure 6A).”
From Unique transcriptomic alterations in 5XFAD;PS19 mouse model identify glial lipid dysregulation and coordinated microglial–oligodendrocyte responses (2026) · cites this paper as [38]
PLCG2 mRNA upregulation has been reported in cortical tissue of LOAD patients (FC 1.35; p = 0.0028).
“PLCG2 mRNA upregulation has been reported in cortical tissue of LOAD patients (FC, 1.35; p = 0.0028, [33])”
From Alzheimer’s disease phospholipase C-gamma-2 (PLCG2) protective variant is a functional hypermorph (2019) · cites this paper as [33]
The Methods (Study Populations and Molecular Data; page unavailable) describe transcriptome measurements from temporal cortex samples of AD and non-AD subjects. Searches for PLCG2, the reported fold change of 1.35, and p = 0.0028 found no passage reporting the claimed upregulation in our copy. (LLM, conf=0.74)
Experimental — accuracy not yet measured
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Panizza, E., & Cerione, R. A. (2024) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2024.1379984 · Cited by 11 · see citing works
PLCG2 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
Comprehensive characterization of the transcriptional landscape in Alzheimer’s disease (AD) brains
Chen, C., Zhang, Z., Liu, Y., Hong, W., Karahan, H., Wang, J., Li, W., Diao, L., Yu, M., Saykin, A. J., et al. (2025) · Science Advances · doi:10.1126/sciadv.adn1927 · Cited by 6 · see citing works
“AD subjects have “definite AD” diagnosis according to the National Institute of Neurological and Communicative Disorders and the Stroke-Alzheimer’s Disease and Related Disorders Association (NINCDS-ADRDA) criteria and a Braak NFT stage of 4 or greater (table S1) ( 39 ).”
InfluentialUzuner Odongo, D., İlgün, A., Bozkurt, F. B., & Çakır, T. (2025) · Communications Biology · doi:10.1038/s42003-025-07941-z · Cited by 4 · see citing works
Park, J. H., Kim, B., Al‐Amin, M. M., Tate, M. D., Sharify, A. D., John, S. K., Karahan, H., Lu, H., Dabin, L. C., & Kim, J. (2026) · Alzheimer's & Dementia · doi:10.1002/alz.71742
“This resource includes post mortem RNA-seq datasets from the Religious Orders Study and Memory and Aging Project (ROSMAP) 40 , Mount Sinai School of Medicine (MSSM), 39 and Mayo Clinic, 38 encompassing > 1200 individuals across seven brain regions (Figure 6A).”
- Authors
- Allen, M., Carrasquillo, M. M., Funk, C., Heavner, B. D., Zou, F., Younkin, C. S., Burgess, J. D., Chai, H.-S., Crook, J., Eddy, J. A., Li, H., Logsdon, B., Peters, M. A., Dang, K. K., Wang, X., Serie, D., Wang, C., Nguyen, T., Lincoln, S., Malphrus, K., Bisceglio, G., Li, M., Golde, T. E., Mangravite, L. M., Asmann, Y., Price, N. D., Petersen, R. C., Graff-Radford, N. R., Dickson, D. W., Younkin, S. G., & Ertekin-Taner, N.
- Affiliations
- Mayo Clinic in Florida (US)
- Institute for Systems Biology (US)
- Mayo Clinic (US)
- Sage Bionetworks (US)
- University of Florida (US)
- ORCID
- Venue
- Scientific Data
- Published
- 2016-10-11
- Volume
- 3
- Issue
- 1
- Pages
- 160089-160089
- ISSN
- 2052-4463 (ISSN-L)
- PMC
- PMC5058336
- OpenAlex
- W2531904292
- Cited by
- 439
- References
- 10
- Citations by year
- 2026: 32 · 2025: 46 · 2024: 58 · 2023: 51 · 2022: 60 · 2021: 72 · 2020: 62 · 2019: 29 · 2018: 20 · 2017: 7 · 2012: 1
- Type
- data paper
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Scientific Data (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Michael J. Fox Foundation for Parkinson's Research (U24 NS072026, 05-901, 211002, P30 AG19610)
- Mayo Clinic (05-901, U24 NS072026, U01 AG046139, P30 AG19610, P50 AG016574, R01 AG032990, U01 AG006786, R01 NS080820, 211002)
- Mayo Foundation for Medical Education and Research (U24 NS072026, AG016574)
- Arizona Department of Health Services (P30 AG19610, P50 AG016574, U24 NS072026, 05-901, 211002, Contract 211002, R01 AG032990)
- CurePSP
- GHR Foundation
- Arizona Biomedical Research Commission (P30 AG19610, 05–901, Contracts 4001, 0011, 05‐901 and 1001, U24 NS072026, 4001, 0011, 05-901, and 1001, 211002)
- National Institute on Aging (211002, U01-AG006576, P30-AG-19610, R01 AG003949, AG046139, R01AG018023, AG016574, AG-19610, U01AG006786, P01AG003949, R01AG023571, AG-006786, R01-AG025711, P50AG025711, AG025711, R01AG032990, P30AG019610, 05-901, P01AG017216, U01AG046139, AG017216, AG003949, R01-AG017216, P50AG016574)
- National Institute of Neurological Disorders and Stroke (R01NS080820, NS072026, 211002, NS080820, U24NS072026, 05-901, U24 NS072026 National Brain, P30 AG19610)
- 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 › Genetics › Genetic Associations and Epidemiology
- Keywords
- Alzheimer's disease, neurodegenerative diseases, genome-wide association study, brain gene expression, transcriptome, transcriptional regulation, genetic risk variants, brain tissue, RNA sequencing, microarray gene expression
- MeSH terms
- Alzheimer Disease, Humans, Genome, Human, Neurodegenerative Diseases, Genome-Wide Association Study, Transcriptome
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