Evidence map›Paper›PMID 39349773›Full record

ArticleDiabetologia2024

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

Shuai Liu, Jingjing Zhu, Hua Zhong, Chong Wu, Haoran Xue, Burcu F Darst, Xiuqing Guo, Peter Durda, Russell P Tracy, Yongmei Liu and 38 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Diabetologia, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

48 authors.

Shuai LiuCancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI, USA.ORCID http://orcid.org/0000-0003-2244-2216
Jingjing ZhuDepartment of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawai'i at Mānoa, Honolulu, HI, USA.
Hua ZhongCancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI, USA.ORCID http://orcid.org/0000-0002-9358-1582
Chong WuDepartment of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Haoran XueDivision of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
Burcu F DarstDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Xiuqing GuoThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
Peter DurdaLaboratory for Clinical Biochemistry Research, University of Vermont, Burlington, VT, USA.
Russell P TracyLaboratory for Clinical Biochemistry Research, University of Vermont, Burlington, VT, USA.
Yongmei LiuDepartment of Medicine, Duke University School of Medicine, Durham, NC, USA.
W Craig JohnsonCollaborative Health Studies Coordinating Center, University of Washington, Seattle, WA, USA.
Kent D TaylorThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
Ani W ManichaikulDepartment of Genome Sciences, University of Virginia, Charlottesville, VA, USA.
Mark O GoodarziDivision of Endocrinology, Diabetes and Metabolism, Department of Medicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Robert E GersztenDivision of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, MA, USA.
Clary B ClishMetabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Yii-Der Ida ChenThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
Heather HighlandDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Christopher A HaimanDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Christopher R GignouxDivision of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
Leslie LangeDivision of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
David V ContiDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Laura M RaffieldDepartment of Genetics, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Lynne WilkensCancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI, USA.
Loïc Le MarchandCancer Epidemiology Division, Population Sciences in the Pacific Program, University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, HI, USA.
Kari E NorthDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Kristin L YoungDepartment of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Ruth J LoosThe Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
Steve BuyskeDepartment of Statistics, Rutgers University, Piscataway, NJ, USA.
Tara MatiseDepartment of Genetics, Rutgers, The State University of New Jersey, Piscataway, NJ, USA.
Ulrike PetersDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Charles KooperbergDivision of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
Alexander P ReinerDepartment of Epidemiology, University of Washington, Seattle, WA, USA.
Bing YuDepartment of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Eric BoerwinkleDepartment of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
Quan SunDepartment of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Mary R RooneyDepartment of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
Justin B Echouffo-TcheuguiDivision of Endocrinology, Diabetes and Metabolism, Johns Hopkins Bayview Medical Center, Baltimore, MD, USA.
Martha L DaviglusInstitute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA.
Qibin QiDepartment of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.
Nicholas MancusoDepartment of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
Changwei LiDepartment of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA.
Youping DengDepartment of Quantitative Health Sciences, John A. Burns School of Medicine, University of Hawai'i at Mānoa, Honolulu, HI, USA.
Alisa ManningClinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA, USA.
James B MeigsDepartment of Medicine, Harvard Medical School, Boston, MA, USA.
Stephen S RichDepartment of Genome Sciences, University of Virginia, Charlottesville, VA, USA.
Jerome I RotterThe Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA.
Lang WuCancer 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.

Funding

Large Scale Sequencing and Analysis of GenomesU54HG003067 · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2004 to 2005
$111.5M
UCLA Clinical and Translational Science InstituteUL1TR001881 · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2025 to 2025
$9.9M
Pilot & Feasibility ProgramP30DK063491 · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2003 to 2025
$5.4M
Research Capacity CoreU54MD007601 · UNIVERSITY OF HAWAII AT MANOA · 2025 to 2025
$5.0M
TOPMed Omics of Type 2 Diabetes and Quantitative TraitsUM1DK078616 · NIDDK · MASSACHUSETTS GENERAL HOSPITAL · 2022 to 2025
$3.1M
Integrating genome, other layers of omics, and non-genetic data to improve understanding of the etiology of human diseases in multi-ethnic populationsU54HG013243 · UNIVERSITY OF HAWAII AT MANOA · 2025 to 2025
$2.0M
ChicAgo Center for Health and EnvironmenT (CACHET)P30ES027792 · UNIVERSITY OF CHICAGO · 2025 to 2025
$1.6M
MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA), COORDINATING CENTER - TASK AREA A - CORE STUDY OPERATIONS75N92020D00001 · UNIVERSITY OF WASHINGTON · 2025 to 2025
$972k
New York Regional Center for Diabetes Translation ResearchP30DK111022 · ALBERT EINSTEIN COLLEGE OF MEDICINE · 2025 to 2025
$810k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDYN01HC095166 · UNIVERSITY OF VERMONT &ST AGRIC COLLEGE · 1999 to 2001
$758k
SUBCLINICAL CARDIOVASCULAR DISEASE STUDY-FIELD CENTERN01HC095162 · JOHNS HOPKINS UNIVERSITY · 1999 to 2000
$694k
Uncovering causal protein markers to improve prostate cancer etiology understanding and risk prediction in Africans and EuropeansR01CA263494 · UNIVERSITY OF HAWAII AT MANOA · 2025 to 2025
$673k
British Heart Foundation RG/13/13/30194British Heart Foundation RG/18/13/33946NCATS NIH HHS UL1 TR000040NCATS NIH HHS UL1 TR001079NCATS NIH HHS UL1 TR001420NCATS NIH HHS UL1 TR001881NCI NIH HHS R01 CA263494NCI NIH HHS R01CA263494NHGRI NIH HHS R01 HG010297NHGRI NIH HHS U54 HG003067NHGRI NIH HHS U54 HG013243NHGRI/NIMHD U54HG013243NHLBI NIH HHS 75N92020D00001NHLBI NIH HHS 75N92020D00002NHLBI NIH HHS 75N92020D00003NHLBI NIH HHS 75N92020D00004NHLBI NIH HHS 75N92020D00005NHLBI NIH HHS 75N92020D00006NHLBI NIH HHS 75N92020D00007NHLBI NIH HHS HHSN268201500003CNHLBI NIH HHS HHSN268201500003INHLBI NIH HHS N01 HC095159NHLBI NIH HHS N01 HC095160NHLBI NIH HHS N01 HC095161NHLBI NIH HHS N01 HC095162NHLBI NIH HHS N01 HC095163NHLBI NIH HHS N01 HC095164NHLBI NIH HHS N01 HC095165NHLBI NIH HHS N01 HC095166NHLBI NIH HHS N01 HC095167NHLBI NIH HHS N01 HC095168NHLBI NIH HHS N01 HC095169NHLBI NIH HHS R01 HL105756NHLBI NIH HHS R01 HL117626NHLBI NIH HHS R01 HL120393NIDDK NIH HHS P30 DK063491NIDDK NIH HHS P30 DK111022NIDDK NIH HHS R01 DK081572NIDDK NIH HHS T32 DK137523NIDDK NIH HHS UM1 DK078616NIEHS NIH HHS P30 ES027792NIMHD NIH HHS U54 MD007601
6 · The paper itself

Abstract

aims/hypothesisSeveral 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.

methodsGenome 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.

resultsWe 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/

interpretationOur 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 ).

Indexed as

Diabetes Mellitus, Type 2Genome-Wide Association StudyPolymorphism, Single NucleotideAgedEthnicityFemaleGenetic Predisposition to DiseaseHumansMaleMiddle AgedRacial GroupsRisk FactorsAetiologyDiverse racial and ethnic populationsProteome-wide association studyType 2 diabetes

Identifiers

PMID39349773
PMCPMC11963907

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.