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Mapping adipose and muscle tissue expression quantitative trait loci in African Americans to identify genes for type 2 diabetes and obesity

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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.

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Acknowledgments

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).

Author contribution

S.P.S. performed quality control and statistical genetic analysis of data, and reviewed/edited the manuscript; N.K.S. performed biochemical and molecular genomic studies, analyzed data, and reviewed/edited the manuscript; J.W.C. performed quality control and analysis of genetics and genomic data, and reviewed/edited the manuscript; J. C-E., J.D., and S.R. performed studies including collection of tissue biopsy, and analyzed clinical data; L.Ma. and N.D.P. analyzed molecular genetic data, and reviewed/edited the manuscript; D.R.M. and J.B. contributed bioinformatic and computational tools; J.B. also developed the eQTL database; M.E.C. helped in experimental design and statistical analysis; L.M., E.K., and D.D. contributed to clinical studies and subject recruitment, and E.K. also reviewed/edited the manuscript; M.B. and S.J.B. performed physiological studies including OGTT and FSIVGT; the MEDIA consortium (M.N., N.M., S.P.,L.B., L.L., X.G., M.S., K.C.) and AAAG Consortium (K.M., G.C., K.T., C.P., T.E., K.N., C.H.) authors contributed meta-analysis data; D.W.B. contributed to study design, and reviewed/edited the manuscript; B.I.F supervised participant recruitment and clinical studies, analyzed clinical data, and reviewed/edited manuscript; C.D.L. contributed to study design, supervised all statistical analysis of genetic/genomic data, and reviewed/edited the manuscript; S.K.D. designed the project, supervised physiological and molecular genomic studies, researched and analyzed data, led the interpretation of data, and wrote/reviewed/edited the manuscript.

Author information

Author notes

  1. Jorge Calles-Escandon

    Present address: Division of Endocrinology, Metro Health System, and School of Medicine, Case Western Reserve University, Cleveland, OH, 44105, USA

Authors and Affiliations

  1. Division of Public Health Sciences, Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA

    Satria P. Sajuthi, Jeff W. Chou, David R. McWilliams, John Beal, Mary E. Comeau & Carl D. Langefeld

  2. Center for Public Health Genomics, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA

    Satria P. Sajuthi, Neeraj K. Sharma, Jeff W. Chou, Nicholette D. Palmer, David R. McWilliams, John Beal, Mary E. Comeau, Lijun Ma, Barry I. Freedman, Carl D. Langefeld & Swapan K. Das

  3. Department of Internal Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, 27157, USA

    Neeraj K. Sharma, Lijun Ma, Jorge Calles-Escandon, Jamehl Demons, Samantha Rogers, Kristina Cherry, Lata Menon, Ethel Kouba, Donna Davis, Barry I. Freedman & Swapan K. Das

  4. Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA

    Nicholette D. Palmer & Donald W. Bowden

  5. Clinical Research Unit, Biomedical Research Services and Administration, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA

    Marcie Burris & Sara J. Byerly

  6. Center for Diabetes Research and Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, 27157, USA

    Nicholette D. Palmer, Maggie C. Y. Ng, Donald W. Bowden & Barry I. Freedman

  7. Division of General Internal Medicine, Department of Medicine, The Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA

    Nisa M. Maruthur

  8. Department of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA

    Sanjay R. Patel

  9. Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA

    Lawrence F. Bielak

  10. Department of Genetics, University of North Carolina, Chapel Hill, NC, 27599, USA

    Leslie A. Lange

  11. Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA

    Xiuqing Guo

  12. Department of Public Health Sciences and Department of Biochemistry and Molecular Genetics, University of Virginia, Charlottesville, VA, 22908, USA

    Michèle M. Sale

  13. Laboratory of Molecular Epidemiology and Nutrition, Department of Epidemiology, Brown University, Providence, RI, 02912, USA

    Kei Hang K. Chan

  14. Center for Observational Research, Amgen, Inc, Thousand Oaks, CA, 91320, USA

    Keri L. Monda

  15. Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, 90033, USA

    Gary K. Chen & Christopher A. Haiman

  16. Department of Epidemiology and Population Health, University of Louisville, Louisville, KY, 40202, USA

    Kira Taylor

  17. Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, 02142, USA

    Cameron Palmer

  18. Vanderbilt Epidemiology Center, Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37203, USA

    Todd L. Edwards

  19. Department of Epidemiology, University of North Carolina, Chapel Hill, NC, 27514, USA

    Kari E. North

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  1. Satria P. Sajuthi
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  2. Neeraj K. Sharma
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  3. Jeff W. Chou
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Corresponding author

Correspondence to Swapan K. Das.

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Conflict of interest

No potential conflicts of interest relevant to this article were reported.

Additional information

S. P. Sajuthi and N. K. Sharma contributed equally.

M. C. Y. Ng, N. M. Maruthur, S. R. Patel, L. F. Bielak, L. A. Lange, X. Guo, M. M. Sale, and K. H. K. Chan for the MEta-analysis of type 2 DIabetes in African Americans (MEDIA) Consortium.

K. L. Monda, G. K. Chen, K. Taylor, C. Palmer, T. L. Edwards, K. E. North, and C. A. Haiman for The African Ancestry Anthropometry Genetics Consortium (AAAGC).

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Sajuthi, S.P., Sharma, N.K., Chou, J.W. et al. Mapping adipose and muscle tissue expression quantitative trait loci in African Americans to identify genes for type 2 diabetes and obesity. Hum Genet 135, 869–880 (2016). https://doi.org/10.1007/s00439-016-1680-8

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  • DOI: https://doi.org/10.1007/s00439-016-1680-8

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