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Identification of proteins associated with type 2 diabetes risk in diverse racial and ethnic populations.
Liu, Shuai; Zhu, Jingjing; Zhong, Hua; Wu, Chong; Xue, Haoran; Darst, Burcu F; Guo, Xiuqing; Durda, Peter; Tracy, Russell P; Liu, Yongmei; Johnson, W Craig; Taylor, Kent D; Manichaikul, Ani W; Goodarzi, Mark O; Gerszten, Robert E; Clish, Clary B; Chen, Yii-Der Ida; Highland, Heather; Haiman, Christopher A; Gignoux, Christopher R; Lange, Leslie; Conti, David V; Raffield, Laura M; Wilkens, Lynne; Marchand, Loïc Le; North, Kari E; Young, Kristin L; Loos, Ruth J; Buyske, Steve; Matise, Tara; Peters, Ulrike; Kooperberg, Charles; Reiner, Alexander P; Yu, Bing; Boerwinkle, Eric; Sun, Quan; Rooney, Mary R; Echouffo-Tcheugui, Justin B; Daviglus, Martha L; Qi, Qibin; Mancuso, Nicholas; Li, Changwei; Deng, Youping; Manning, Alisa; Meigs, James B; Rich, Stephen S; Rotter, Jerome I; Wu, Lang.
Afiliación
  • Liu S; Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawai'i Cancer Center, University of Hawai'i at Manoa, Honolulu, HI, USA.
  • Zhu J; Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawai'i at Manoa, Honolulu, HI, USA.
  • Zhong H; Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawai'i Cancer Center, University of Hawai'i at Manoa, Honolulu, HI, USA.
  • Wu C; Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
  • Xue H; Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
  • Darst BF; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
  • Guo X; The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
  • Durda P; Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, VT, USA.
  • Tracy RP; Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, VT, USA.
  • Liu Y; Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
  • Johnson WC; Collaborative Health Studies Coordinating Center, University of Washington, Seattle, WA, USA.
  • Taylor KD; The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
  • Manichaikul AW; Department of Genome Sciences, University of Virginia, Charlottesville, VA, USA.
  • Goodarzi MO; Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
  • Gerszten RE; Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
  • Clish CB; Cardiovascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.
  • Chen YI; Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
  • Highland H; The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
  • Haiman CA; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Gignoux CR; Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Lange L; Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • Conti DV; Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • Raffield LM; Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Wilkens L; Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Marchand LL; Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawai'i Cancer Center, University of Hawai'i at Manoa, Honolulu, HI, USA.
  • North KE; Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawai'i Cancer Center, University of Hawai'i at Manoa, Honolulu, HI, USA.
  • Young KL; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Loos RJ; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Buyske S; The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
  • Matise T; Department of Statistics, Rutgers University, Piscataway, NJ, USA.
  • Peters U; Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.
  • Kooperberg C; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
  • Reiner AP; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
  • Yu B; Department of Epidemiology, University of Washington, Seattle, WA, USA.
  • Boerwinkle E; Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Sun Q; Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Rooney MR; Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
  • Echouffo-Tcheugui JB; Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
  • Daviglus ML; Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins Bayview Medical Center, Baltimore, MD, USA.
  • Qi Q; Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA.
  • Mancuso N; Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
  • Li C; Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Deng Y; Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA.
  • Manning A; Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawai'i at Manoa, Honolulu, HI, USA.
  • Meigs JB; Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, USA.
  • Rich SS; Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
  • Rotter JI; Department of Medicine, Harvard Medical School, Boston, MA, USA.
  • Wu L; Department of Medicine, Harvard Medical School, Boston, MA, USA.
Diabetologia ; 2024 Sep 30.
Article en En | MEDLINE | ID: mdl-39349773
ABSTRACT
AIMS/

HYPOTHESIS:

Several studies have reported associations between specific proteins and type 2 diabetes risk in European populations. To better understand the role played by proteins in type 2 diabetes aetiology across diverse populations, we conducted a large proteome-wide association study using genetic instruments across four racial and ethnic groups African; Asian; Hispanic/Latino; and European.

METHODS:

Genome and plasma proteome data from the Multi-Ethnic Study of Atherosclerosis (MESA) study involving 182 African, 69 Asian, 284 Hispanic/Latino and 409 European individuals residing in the USA were used to establish protein prediction models by using potentially associated cis- and trans-SNPs. The models were applied to genome-wide association study summary statistics of 250,127 type 2 diabetes cases and 1,222,941 controls from different racial and ethnic populations.

RESULTS:

We identified three, 44 and one protein associated with type 2 diabetes risk in Asian, European and Hispanic/Latino populations, respectively. Meta-analysis identified 40 proteins associated with type 2 diabetes risk across the populations, including well-established as well as novel proteins not yet implicated in type 2 diabetes development. CONCLUSIONS/

INTERPRETATION:

Our study improves our understanding of the aetiology of type 2 diabetes in diverse populations. DATA

AVAILABILITY:

The summary statistics of multi-ethnic type 2 diabetes GWAS of MVP, DIAMANTE, Biobank Japan and other studies are available from The database of Genotypes and Phenotypes (dbGaP) under accession number phs001672.v3.p1. MESA genetic, proteome and covariate data can be accessed through dbGaP under phs000209.v13.p3. All code is available on GitHub ( https//github.com/Arthur1021/MESA-1K-PWAS ).
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Diabetologia Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Diabetologia Año: 2024 Tipo del documento: Article País de afiliación: Estados Unidos