@article{703dd447b6414fec85423a76fcf626a7,
title = "Mapping adipose and muscle tissue expression quantitative trait loci in African Americans to identify genes for type 2 diabetes and obesity",
abstract = "Relative to European Americans, type 2 diabetes (T2D) is more prevalent in African Americans (AAs). Genetic variation may modulate transcript abundance in insulin-responsive tissues and contribute to risk; yet, published studies identifying expression quantitative trait loci (eQTLs) in African ancestry populations are restricted to blood cells. This study aims to develop a map of genetically regulated transcripts expressed in tissues important for glucose homeostasis in AAs, critical for identifying the genetic etiology of T2D and related traits. Quantitative measures of adipose and muscle gene expression, and genotypic data were integrated in 260 non-diabetic AAs to identify expression regulatory variants. Their roles in genetic susceptibility to T2D, and related metabolic phenotypes, were evaluated by mining GWAS datasets. eQTL analysis identified 1971 and 2078 cis-eGenes in adipose and muscle, respectively. Cis-eQTLs for 885 transcripts including top cis-eGenes CHURC1, USMG5, and ERAP2 were identified in both tissues. 62.1 % of top cis-eSNPs were within ±50 kb of transcription start sites and cis-eGenes were enriched for mitochondrial transcripts. Mining GWAS databases revealed association of cis-eSNPs for more than 50 genes with T2D (e.g. PIK3C2A, RBMS1, UFSP1), gluco-metabolic phenotypes (e.g. INPP5E, SNX17, ERAP2, FN3KRP), and obesity (e.g. POMC, CPEB4). Integration of GWAS meta-analysis data from AA cohorts revealed the most significant association for cis-eSNPs of ATP5SL and MCCC1 genes, with T2D and BMI, respectively. This study developed the first comprehensive map of adipose and muscle tissue eQTLs in AAs (publically accessible at https://mdsetaa.phs.wakehealth.edu) and identified genetically regulated transcripts for delineating genetic causes of T2D, and related metabolic phenotypes.",
author = "Sajuthi, {Satria P.} and Sharma, {Neeraj K.} and Chou, {Jeff W.} and Palmer, {Nicholette D.} and McWilliams, {David R.} and John Beal and Comeau, {Mary E.} and Lijun Ma and Jorge Calles-Escandon and Jamehl Demons and Samantha Rogers and Kristina Cherry and Lata Menon and Ethel Kouba and Donna Davis and Marcie Burris and Byerly, {Sara J.} and Ng, {Maggie C.Y.} and Maruthur, {Nisa M.} and Patel, {Sanjay R.} and Bielak, {Lawrence F.} and Lange, {Leslie A.} and Xiuqing Guo and Sale, {Mich{\`e}le M.} and Chan, {Kei Hang K.} and Monda, {Keri L.} and Chen, {Gary K.} and Kira Taylor and Cameron Palmer and Edwards, {Todd L.} and North, {Kari E.} and Haiman, {Christopher A.} and Bowden, {Donald W.} and Freedman, {Barry I.} and Langefeld, {Carl D.} and Das, {Swapan K.}",
note = "Funding Information: We thank the dedicated staff of the Clinical Research Unit at WFSM and Kurt A. Langberg (WFSM-Endocrinology) for support of the clinical studies and assistance with data management. We thank Mrs. Joyce Byers for support in participant recruitment. We thank staff in the genomics core laboratory at Center for Genomics and Personalized Medicine Research, WFSM, especially Dr. Siqun Zheng, Shelly Smith, Tracey Young and Dr. Ge Li for their extensive support in genotyping, and gene expression analysis using the Illumina microarray platform. We acknowledge the support of the Center for Public Health Genomics, WFSM for computational resources. SKD and CDL are the guarantors of this work, and as such, had full access to all study data and take responsibility for integrity of the data and accuracy of data analysis. This work was supported by National Institutes of Health Grant R01 DK090111 (SKD). Funding Information: We thank the dedicated staff of the Clinical Research Unit at WFSM and Kurt A. Langberg (WFSM-Endocrinology) for support of the clinical studies and assistance with data management. We thank Mrs. Joyce Byers for support in participant recruitment. We thank staff in the genomics core laboratory at Center for Genomics and Personalized Medicine Research, WFSM, especially Dr. Siqun Zheng, Shelly Smith, Tracey Young and Dr. Ge Li for their extensive support in genotyping, and gene expression analysis using the Illumina microarray platform. We acknowledge the support of the Center for Public Health Genomics, WFSM for computational resources. SKD and CDL are the guarantors of this work, and as such, had full access to all study data and take responsibility for integrity of the data and accuracy of data analysis. This work was supported by National Institutes of Health Grant R01 DK090111 (SKD). Publisher Copyright: {\textcopyright} 2016, Springer-Verlag Berlin Heidelberg.",
year = "2016",
month = aug,
day = "1",
doi = "10.1007/s00439-016-1680-8",
language = "English (US)",
volume = "135",
pages = "869--880",
journal = "Human genetics",
issn = "0340-6717",
publisher = "Springer Verlag",
number = "8",
}