Transcriptome-wide association study of blood cell traits in african ancestry and hispanic/latino populations

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  • Wen, J.
    • Affiliation: School of Medicine, Department of Genetics
  • Xie, M.
    • Affiliation: School of Medicine, Department of Genetics
  • Rowland, B.
    • Affiliation: Gillings School of Global Public Health, Department of Biostatistics
  • Rosen, J.D.
    • Affiliation: Gillings School of Global Public Health, Department of Biostatistics
  • Sun, Q.
    • Affiliation: Gillings School of Global Public Health, Department of Biostatistics
  • Chen, J.
    • Affiliation: Gillings School of Global Public Health, Department of Biostatistics
  • Tapia, A.L.
    • Affiliation: Gillings School of Global Public Health, Department of Biostatistics
  • Qian, H.
    • Affiliation: College of Arts and Sciences, Department of Statistics and Operations Research
  • Kowalski, M.H.
    • Affiliation: Gillings School of Global Public Health, Department of Biostatistics
  • Shan, Y.
    • Affiliation: Gillings School of Global Public Health, Department of Biostatistics
  • Young, K.L.
    • Affiliation: Gillings School of Global Public Health, Department of Epidemiology
  • Graff, M.
    • Affiliation: Gillings School of Global Public Health, Department of Epidemiology
  • Argos, M.
    • Other Affiliation: University of Illinois at Chicago
  • Avery, C.L.
    • Affiliation: Gillings School of Global Public Health, Department of Epidemiology
  • Bien, S.A.
    • Other Affiliation: Fred Hutchinson Cancer Research Center
  • Buyske, S.
    • Other Affiliation: Rutgers University
  • Yin, J.
    • Other Affiliation: Kaiser Permanente Northern California
  • Choquet, H.
    • Other Affiliation: Kaiser Permanente Northern California
  • Fornage, M.
    • Other Affiliation: The University of Texas Health Science Center
  • Hodonsky, C.J.
    • Other Affiliation: University of Virginia
  • Jorgenson, E.
    • Other Affiliation: Regeneron Genetics Center
  • Kooperberg, C.
    • Other Affiliation: Fred Hutchinson Cancer Research Center
  • Loos, R.J.F.
    • Other Affiliation: Icahn School of Medicine at Mount Sinai
  • Liu, Y.
    • Other Affiliation: Duke University
  • Moon, J.-Y.
    • Other Affiliation: Albert Einstein College of Medicine
  • North, K.E.
    • Affiliation: Gillings School of Global Public Health, Department of Epidemiology
  • Rich, S.S.
    • Other Affiliation: University of Virginia
  • Rotter, J.I.
    • Other Affiliation: Harbor-UCLA Medical Center
  • Smith, J.A.
    • Other Affiliation: University of Michigan
  • Zhao, W.
    • Other Affiliation: University of Michigan
  • Shang, L.
    • Other Affiliation: University of Michigan
  • Wang, T.
    • Other Affiliation: Albert Einstein College of Medicine
  • Zhou, X.
    • Other Affiliation: University of Michigan
  • Reiner, A.P.
    • Other Affiliation: University of Washington
  • Raffield, L.M.
    • Affiliation: School of Medicine, Department of Genetics
  • Li, Y.
    • Affiliation: School of Medicine, Department of Genetics
Abstract
  • Background: Thousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Moreover, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed. Methods: To derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including n = 229 African American and n = 381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, n = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (n = 27,955) and Hispanic/Latino (n = 28,324) ancestry participants. Results: Our results revealed 24 suggestive signals (p < 1 × 10−4 ) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN. Conclusions: These analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.
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  • Article
Rights statement
  • In Copyright
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  • Attribution 3.0 United States
Journal title
  • Genes
Journal volume
  • 12
Journal issue
  • 7
Language
  • English
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  • Publisher
ISSN
  • 2073-4425
Publisher
  • MDPI AG

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