TY - JOUR
T1 - Large eQTL meta-analysis reveals differing patterns between cerebral cortical and cerebellar brain regions
AU - The CommonMind Consortium (CMC)
AU - The AMP-AD Consortium
AU - Sieberts, Solveig K.
AU - Perumal, Thanneer M.
AU - Carrasquillo, Minerva M.
AU - Allen, Mariet
AU - Reddy, Joseph S.
AU - Hoffman, Gabriel E.
AU - Dang, Kristen K.
AU - Calley, John
AU - Ebert, Philip J.
AU - Eddy, James
AU - Wang, Xue
AU - Greenwood, Anna K.
AU - Mostafavi, Sara
AU - Akbarian, Schahram
AU - Bendl, Jaroslav
AU - Breen, Michael S.
AU - Brennand, Kristen
AU - Brown, Leanne
AU - Browne, Andrew
AU - Buxbaum, Joseph D.
AU - Charney, Alexander
AU - Chess, Andrew
AU - Couto, Lizette
AU - Crawford, Greg
AU - Devillers, Olivia
AU - Devlin, Bernie
AU - Dobbyn, Amanda
AU - Domenici, Enrico
AU - Filosi, Michele
AU - Flatow, Elie
AU - Francoeur, Nancy
AU - Fullard, John
AU - Gil, Sergio Espeso
AU - Girdhar, Kiran
AU - Gulyás-Kovács, Attila
AU - Gur, Raquel
AU - Hahn, Chang Gyu
AU - Haroutunian, Vahram
AU - Hauberg, Mads Engel
AU - Huckins, Laura
AU - Jacobov, Rivky
AU - Jiang, Yan
AU - Johnson, Jessica S.
AU - Kassim, Bibi
AU - Kim, Yungil
AU - Klei, Lambertus
AU - Kramer, Robin
AU - Lauria, Mario
AU - Lehner, Thomas
AU - Price, Nathan
N1 - Funding Information:
For the ROSMAP and Mayo RNAseq studies, the results published here are in whole or in part based on data obtained from the AMP-AD Knowledge Portal (doi:10.7303/syn2580853). ROSMAP study data were provided by the Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago. Data collection was supported through funding by NIA grants P30AG10161, R01AG15819, R01AG17917, R01AG30146, R01AG36836, U01AG32984, U01AG46152, the Illinois Department of Public Health, and the Translational Genomics Research Institute. Mayo RNA-seq study data were provided by the following sources: The Mayo Clinic Alzheimers Disease Genetic Studies, led by Dr. Nilufer Ertekin-Taner and Dr. Steven G. Younkin, Mayo Clinic, Jacksonville, FL using samples from the Mayo Clinic Study of Aging, the Mayo Clinic Alzheimer’s Disease Research Center, and the Mayo Clinic Brain Bank. Data collection was supported through funding by NIA grants P50 AG016574, R01 AG032990, U01 AG046139, R01 AG018023, U01 AG006576, U01 AG006786, R01 AG025711, R01 AG017216, R01 AG003949, NINDS grant R01 NS080820, CurePSP Foundation, and support from Mayo Foundation. Study data includes samples collected through the Sun Health Research Institute Brain and Body Donation Program of Sun City, Arizona. The Brain and Body Donation Program is supported by the National Institute of Neurological Disorders and Stroke (U24 NS072026 National Brain and Tissue Resource for Parkinsons Disease and Related Disorders), the National Institute on Aging (P30 AG19610 Arizona Alzheimers Disease Core Center), the Arizona Department of Health Services (contract 211002, Arizona Alzheimers Research Center), the Arizona Biomedical Research Commission (contracts 4001, 0011, 05-901 and 1001 to the Arizona Parkinson’s Disease Consortium) and the Michael J. Fox Foundation for Parkinsons Research. This study was in part supported by NIH RF1 AG051504 and R01 AG061796 (NET). For CommonMind, data were generated as part of the CommonMind Consortium supported by funding from Takeda Pharmaceuticals Company Limited, F. Hoffmann-La Roche Ltd and NIH grants R01MH085542, R01MH093725, P50MH066392, P50MH080405, R01MH097276, RO1-MH-075916, P50M096891, P50MH084053S1, R37MH057881, AG02219, AG05138, MH06692, R01MH110921, R01MH109677, R01MH109897, U01MH103392, and contract HHSN271201300031C through IRP NIMH. Brain tissue for the study was obtained from the following brain bank collections: the Mount Sinai NIH Brain and Tissue Repository, the University of Pennsylvania Alzheimer’s Disease Core Center, the University of Pittsburgh NeuroBioBank and Brain and Tissue Repositories, and the NIMH Human Brain Collection Core. CMC Leadership: Panos Roussos, Joseph Buxbaum, Andrew Chess, Schahram Akbarian, Vahram Haroutunian (Icahn School of Medicine at Mount Sinai), Bernie Devlin, David Lewis (University of Pittsburgh), Raquel Gur, Chang-Gyu Hahn (University of Pennsylvania), Enrico Domenici (University of Trento), Mette A. Peters, Solveig Sieberts (Sage Bionetworks), Thomas Lehner, Geetha Senthil, Stefano Marenco, Barbara K. Lipska (NIMH). SKS, TP, KKD, JE, AKG, LO, BAL, and LMM were additionally supported by NIA grants U24 AG61340, U01 AG46170, U01 AG 46161, R01 AG46171, R01 AG 46174. All data used in this manuscript have been previously released through their respective consortia and have been reviewed by IRBs at their institution of origin. Informed consent has been obtained from all individuals.
Publisher Copyright:
© 2020, The Author(s).
PY - 2020/12/1
Y1 - 2020/12/1
N2 - The availability of high-quality RNA-sequencing and genotyping data of post-mortem brain collections from consortia such as CommonMind Consortium (CMC) and the Accelerating Medicines Partnership for Alzheimer’s Disease (AMP-AD) Consortium enable the generation of a large-scale brain cis-eQTL meta-analysis. Here we generate cerebral cortical eQTL from 1433 samples available from four cohorts (identifying >4.1 million significant eQTL for >18,000 genes), as well as cerebellar eQTL from 261 samples (identifying 874,836 significant eQTL for >10,000 genes). We find substantially improved power in the meta-analysis over individual cohort analyses, particularly in comparison to the Genotype-Tissue Expression (GTEx) Project eQTL. Additionally, we observed differences in eQTL patterns between cerebral and cerebellar brain regions. We provide these brain eQTL as a resource for use by the research community. As a proof of principle for their utility, we apply a colocalization analysis to identify genes underlying the GWAS association peaks for schizophrenia and identify a potentially novel gene colocalization with lncRNA RP11-677M14.2 (posterior probability of colocalization 0.975).
AB - The availability of high-quality RNA-sequencing and genotyping data of post-mortem brain collections from consortia such as CommonMind Consortium (CMC) and the Accelerating Medicines Partnership for Alzheimer’s Disease (AMP-AD) Consortium enable the generation of a large-scale brain cis-eQTL meta-analysis. Here we generate cerebral cortical eQTL from 1433 samples available from four cohorts (identifying >4.1 million significant eQTL for >18,000 genes), as well as cerebellar eQTL from 261 samples (identifying 874,836 significant eQTL for >10,000 genes). We find substantially improved power in the meta-analysis over individual cohort analyses, particularly in comparison to the Genotype-Tissue Expression (GTEx) Project eQTL. Additionally, we observed differences in eQTL patterns between cerebral and cerebellar brain regions. We provide these brain eQTL as a resource for use by the research community. As a proof of principle for their utility, we apply a colocalization analysis to identify genes underlying the GWAS association peaks for schizophrenia and identify a potentially novel gene colocalization with lncRNA RP11-677M14.2 (posterior probability of colocalization 0.975).
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U2 - 10.1038/s41597-020-00642-8
DO - 10.1038/s41597-020-00642-8
M3 - Article
C2 - 33046718
AN - SCOPUS:85092511647
SN - 2052-4463
VL - 7
JO - Scientific Data
JF - Scientific Data
IS - 1
M1 - 340
ER -