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

Jia Wen, Munan Xie, Bryce Rowland, Jonathan D. Rosen, Quan Sun, Jiawen Chen, Amanda L. Tapia, Huijun Qian, Madeline H. Kowalski, Yue Shan, Kristin L. Young, Marielisa Graff, Maria Argos, Christy L. Avery, Stephanie A. Bien, Steve Buyske, Jie Yin, Hélène Choquet, Myriam Fornage, Chani J. HodonskyEric Jorgenson, Charles Kooperberg, Ruth J.F. Loos, Yongmei Liu, Jee Young Moon, Kari E. North, Stephen S. Rich, Jerome I. Rotter, Jennifer A. Smith, Wei Zhao, Lulu Shang, Tao Wang, Xiang Zhou, Alexander P. Reiner, Laura M. Raffield, Yun Li

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article number1049
JournalGenes
Volume12
Issue number7
DOIs
StatePublished - Jul 2021

Keywords

  • Ancestry
  • Expression analysis
  • Non-European populations
  • TWAS (transcriptome-wide association study)

ASJC Scopus subject areas

  • Genetics
  • Genetics(clinical)

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