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Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations.
Wen, Jia; Xie, Munan; Rowland, Bryce; Rosen, Jonathan D; Sun, Quan; Chen, Jiawen; Tapia, Amanda L; Qian, Huijun; Kowalski, Madeline H; Shan, Yue; Young, Kristin L; Graff, Marielisa; Argos, Maria; Avery, Christy L; Bien, Stephanie A; Buyske, Steve; Yin, Jie; Choquet, Hélène; Fornage, Myriam; Hodonsky, Chani J; Jorgenson, Eric; Kooperberg, Charles; Loos, Ruth J F; Liu, Yongmei; Moon, Jee-Young; North, Kari E; Rich, Stephen S; Rotter, Jerome I; Smith, Jennifer A; Zhao, Wei; Shang, Lulu; Wang, Tao; Zhou, Xiang; Reiner, Alexander P; Raffield, Laura M; Li, Yun.
Affiliation
  • Wen J; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA.
  • Xie M; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA.
  • Rowland B; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Rosen JD; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Sun Q; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Chen J; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Tapia AL; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Qian H; Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Kowalski MH; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Shan Y; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
  • Young KL; Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA.
  • Graff M; Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA.
  • Argos M; Division of Epidemiology and Biostatistics, University of Illinois at Chicago, Chicago, IL 60612, USA.
  • Avery CL; Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA.
  • Bien SA; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
  • Buyske S; Department of Statistics, Rutgers University, Piscataway, NJ 08854, USA.
  • Yin J; Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA.
  • Choquet H; Division of Research, Kaiser Permanente Northern California, Oakland, CA 94612, USA.
  • Fornage M; Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center, Houston, TX 77030, USA.
  • Hodonsky CJ; Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA.
  • Jorgenson E; Regeneron Genetics Center, Tarrytown, NY 10591, USA.
  • Kooperberg C; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA.
  • Loos RJF; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
  • Liu Y; Molecular Physiology Institute, Duke University, Durham, NC 27701, USA.
  • Moon JY; Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA.
  • North KE; Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA.
  • Rich SS; Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA.
  • Rotter JI; The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA 90502, USA.
  • Smith JA; Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.
  • Zhao W; Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.
  • Shang L; Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.
  • Wang T; Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA.
  • Zhou X; Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA.
  • Reiner AP; Department of Epidemiology, University of Washington, Seattle, WA 98195, USA.
  • Raffield LM; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA.
  • Li Y; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27514, USA.
Genes (Basel) ; 12(7)2021 07 08.
Article in En | MEDLINE | ID: mdl-34356065
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.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Black or African American / Blood Cells / Hispanic or Latino / Genetic Predisposition to Disease / Polymorphism, Single Nucleotide / Quantitative Trait Loci / Transcriptome Type of study: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Genes (Basel) Year: 2021 Document type: Article Affiliation country: Estados Unidos

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Black or African American / Blood Cells / Hispanic or Latino / Genetic Predisposition to Disease / Polymorphism, Single Nucleotide / Quantitative Trait Loci / Transcriptome Type of study: Etiology_studies / Incidence_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Genes (Basel) Year: 2021 Document type: Article Affiliation country: Estados Unidos
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