Identification of proteins associated with type 2 diabetes risk in diverse racial and ethnic populations

Shuai Liu¹, Jingjing Zhu², Hua Zhong¹, Chong Wu³, Haoran Xue⁴, Burcu F Darst⁵, Xiuqing Guo⁶, Peter Durda⁷, Russell P Tracy⁷, Yongmei Liu⁸, W Craig Johnson⁹, Kent D Taylor⁶, Ani W Manichaikul¹⁰, Mark O Goodarzi¹¹, Robert E Gerszten^{12

13}, Clary B Clish¹⁴, Yii-Der Ida Chen⁶, Heather Highland¹⁵, Christopher A Haiman¹⁶, Christopher R Gignoux¹⁷, Leslie Lange¹⁷, David V Conti¹⁶, Laura M Raffield¹⁸, Lynne Wilkens¹, Loïc Le Marchand¹, Kari E North¹⁵, Kristin L Young¹⁵, Ruth J Loos¹⁹, Steve Buyske²⁰, Tara Matise²¹, Ulrike Peters⁵, Charles Kooperberg⁵, Alexander P Reiner²², Bing Yu²³, Eric Boerwinkle²³, Quan Sun²⁴, Mary R Rooney²⁵, Justin B Echouffo-Tcheugui²⁶, Martha L Daviglus²⁷, Qibin Qi²⁸, Nicholas Mancuso¹⁶, Changwei Li²⁹, Youping Deng², Alisa Manning^{30

31

32}, James B Meigs^{32

33}, Stephen S Rich¹⁰, Jerome I Rotter⁶, Lang Wu³⁴

Affiliations

¹ Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI, USA.
² Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawai'i at Mānoa, Honolulu, HI, USA.
³ Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
⁴ Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
⁵ Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
⁶ 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.
⁷ Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, VT, USA.
⁸ Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
⁹ Collaborative Health Studies Coordinating Center, University of Washington, Seattle, WA, USA.
¹⁰ Department of Genome Sciences, University of Virginia, Charlottesville, VA, USA.
¹¹ Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
¹² Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
¹³ Cardiovascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.
¹⁴ Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
¹⁵ Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
¹⁶ Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
¹⁷ Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
¹⁸ Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
¹⁹ The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
²⁰ Department of Statistics, Rutgers University, Piscataway, NJ, USA.
²¹ Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.
²² Department of Epidemiology, University of Washington, Seattle, WA, USA.
²³ Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
²⁴ Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
²⁵ Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
²⁶ Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins Bayview Medical Center, Baltimore, MD, USA.
²⁷ Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA.
²⁸ Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
²⁹ Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA.
³⁰ Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, USA.
³¹ Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
³² Department of Medicine, Harvard Medical School, Boston, MA, USA.
³³ Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.
³⁴ Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI, USA. lwu@cc.hawaii.edu.

PMID: 39349773
PMCID: PMC11963907 (available on 2025-12-01)
DOI: 10.1007/s00125-024-06277-3

Identification of proteins associated with type 2 diabetes risk in diverse racial and ethnic populations

Shuai Liu et al. Diabetologia. 2024 Dec.

. 2024 Dec;67(12):2754-2770.

doi: 10.1007/s00125-024-06277-3. Epub 2024 Sep 30.

Authors

Affiliations

¹ Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI, USA.
² Department of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawai'i at Mānoa, Honolulu, HI, USA.
³ Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
⁴ Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
⁵ Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
⁶ 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.
⁷ Laboratory for Clinical Biochemistry Research, University of Vermont, Burlington, VT, USA.
⁸ Department of Medicine, Duke University School of Medicine, Durham, NC, USA.
⁹ Collaborative Health Studies Coordinating Center, University of Washington, Seattle, WA, USA.
¹⁰ Department of Genome Sciences, University of Virginia, Charlottesville, VA, USA.
¹¹ Division of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
¹² Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
¹³ Cardiovascular Institute, Beth Israel Deaconess Medical Center, Boston, MA, USA.
¹⁴ Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
¹⁵ Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
¹⁶ Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
¹⁷ Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
¹⁸ Department of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
¹⁹ The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
²⁰ Department of Statistics, Rutgers University, Piscataway, NJ, USA.
²¹ Department of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.
²² Department of Epidemiology, University of Washington, Seattle, WA, USA.
²³ Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
²⁴ Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
²⁵ Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
²⁶ Division of Endocrinology, Diabetes and Metabolism, Johns Hopkins Bayview Medical Center, Baltimore, MD, USA.
²⁷ Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA.
²⁸ Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
²⁹ Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA.
³⁰ Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, USA.
³¹ Programs in Metabolism and Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.
³² Department of Medicine, Harvard Medical School, Boston, MA, USA.
³³ Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA.
³⁴ Cancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI, USA. lwu@cc.hawaii.edu.

PMID: 39349773
PMCID: PMC11963907 (available on 2025-12-01)
DOI: 10.1007/s00125-024-06277-3

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 ).

Keywords: Aetiology; Diverse racial and ethnic populations; Proteome-wide association study; Type 2 diabetes.

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Conflict of interest statement

Acknowledgements: The authors would like to thank all of the individuals who participated in the parent studies and all the researchers, clinicians, technicians and administrative staff for their valuable contribution to the studies. A list of the PAGE senior investigators can be found at http://www.pagestudy.org . A list of participating MESA investigators and institutes can be found at http://www.mesa-nhlbi.org . Participants in the INTERVAL RCT were recruited with the active collaboration of NHS Blood and Transplant England ( www.nhsbt.nhs.uk ), which has supported field work and other elements of the trial. A complete list of the investigators and contributors to the INTERVAL trial is provided in reference [*]. The academic coordinating centre would also like to thank blood donor centre staff and blood donors for participating in the INTERVAL trial. WGS for the Trans-Omics in Precision Medicine (TOPMed) program was supported by the National Heart, Lung and Blood Institute (NHLBI). The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. *Di Angelantonio E, Thompson SG, Kaptoge SK, Moore C, Walker M, Armitage J, Ouwehand WH, Roberts DJ, Danesh J, INTERVAL Trial Group. Efficiency and safety of varying the frequency of whole blood donation (INTERVAL): a randomised trial of 45 000 donors. Lancet. 2017 Nov 25;390(10110):2360–2371 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 ). Funding: This research is supported by the University of Hawaiʻi Cancer Center and The Hawaiʻi Advanced Training in Artificial Intelligence for Precision Nutrition Science Research (AIPrN) (T32DK137523). LWu is also supported by V Foundation V Scholar Award, NCI R01CA263494 and NHGRI/NIMHD U54HG013243. The Population Architecture Using Genomics and Epidemiology (PAGE) program is funded by the National Human Genome Research Institute (NHGRI), supported by R01HG010297. WGS for ‘NHLBI TOPMed: Multi-Ethnic Study of Atherosclerosis (MESA)’ (phs001416.v1.p1) was performed at the Broad Institute of MIT and Harvard (3U54HG003067–13S1). SOMAscan proteomics for NHLBI TOPMed: Multi-Ethnic Study of Atherosclerosis (MESA) (phs001416.v1.p1) was performed at the Broad Institute and Beth Israel Proteomics Platform (HHSN268201600034I). Centralised read mapping and genotype calling, along with variant quality metrics and filtering were provided by the TOPMed Informatics Research Center (3R01HL-117626–02S1). Phenotype harmonisation, data management, sample-identity quality control and general study coordination were provided by the TOPMed Data Coordinating Center (3R01HL-120393–02S1) and TOPMed MESA Multi-Omics (HHSN2682015000031/HSN26800004). The MESA projects are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. The Multi-Ethnic Study of Atherosclerosis (MESA) projects are conducted and supported by the National Heart, Lung, and Blood Institute (NHLBI) in collaboration with MESA investigators. Support for MESA is provided by contracts 75N92020D00001, HHSN268201500003I, N01-HC-95159, 75N92020D00005, N01-HC-95160, 75N92020D00002, N01-HC-95161, 75N92020D00003, N01-HC-95162, 75N92020D00006, N01-HC-95163,75N92020D00004, N01-HC-95164, 75N92020D00007, N01-HC-95165, N01-HC-95166, N01-HC-95167, N01-HC-95168, N01-HC-95169, UL1-TR-000040, UL1-TR-001079, UL1-TR-001420, UL1TR001881, DK063491 and R01HL105756. Supported in part by the National Institutes of Health, National Heart, Lung, and Blood Institute (NHLBI) contract 1R01HL15185, R01DK081572 and the National Institute of Diabetes and Digestive and Kidney Diseases contract UM1DK078616. DNA extraction and genotyping were co-funded by the National Institute for Health Research (NIHR), the NIHR BioResource ( http://bioresource.nihr.ac.uk ) and the NIHR Cambridge Biomedical Research Centre (BRC-1215–20014). The academic coordinating centre for INTERVAL was supported by core funding from the NIHR Blood and Transplant Research Unit in Donor Health and Genomics (NIHR BTRU-2014–10024), UK Medical Research Council (MR/L003120/1), British Heart Foundation (SP/09/002; RG/13/13/30194; RG/18/13/33946) and NIHR Cambridge BRC (BRC-1215–20014). The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. Authors’ relationships and activities: LWu provided consulting service to Pupil Bio Inc., reviewed manuscripts for Gastroenterology Report not related to this study, and received honorarium. LMR is a consultant for the NHLBI Trans-Omics for Precision Medicine (TOPMed) consortium Administrative Coordinating Center (through Westat). QQ is a member of the editorial board of Diabetologia. PD and SB received grants from Regeneron Genetics Center LLC. The other authors declare that there are no relationships or activities that might bias, or be perceived to bias, their work. Contribution statement: LWu conceived and designed the study. SL developed the protein genetic prediction models. SL, JZ and HZ performed statistical analyses. JZ performed drug-repurposing analysis. CW and HX contributed to the fine-mapping analyses. HZ performed IPA analysis. SL wrote the initial draft manuscript with critical additions and inputs from JZ and LWu. BFD, XG, PD, RPT, YL, WCJ, KDT, AWM, MOG, REG, CBC, Y-DIC, HH, CAH, CRG, LL, DVC, LMR, LWi, LLM, KEN, KLY, RJL, SB, TM, UP, CK, APR, BY, EB, QS, MRR, JBE-T, MLD, QQ, NM, CL, YD, AM, JBM, SSR and JIR conducted the experiment, contributed materials and provided valuable feedback for revising and reviewing the manuscript. All authors contributed to the manuscript revision. All authors read and approved the final manuscript. LWu is the guarantor of this work.

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Identification of proteins associated with type 2 diabetes risk in diverse racial and ethnic populations

Affiliations

Identification of proteins associated with type 2 diabetes risk in diverse racial and ethnic populations

Authors

Affiliations

Abstract

Conflict of interest statement

References

MeSH terms

Grants and funding

LinkOut - more resources

Full Text Sources

Medical

Miscellaneous