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Proteomic Analyses in Diverse Populations Improved Risk Prediction and Identified New Drug Targets for Type 2 Diabetes.
Yao, Pang; Iona, Andri; Pozarickij, Alfred; Said, Saredo; Wright, Neil; Lin, Kuang; Millwood, Iona; Fry, Hannah; Kartsonaki, Christiana; Mazidi, Mohsen; Chen, Yiping; Bragg, Fiona; Liu, Bowen; Yang, Ling; Liu, Junxi; Avery, Daniel; Schmidt, Dan; Sun, Dianjianyi; Pei, Pei; Lv, Jun; Yu, Canqing; Hill, Michael; Bennett, Derrick; Walters, Robin; Li, Liming; Clarke, Robert; Du, Huaidong; Chen, Zhengming.
Afiliação
  • Yao P; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Iona A; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Pozarickij A; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Said S; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Wright N; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Lin K; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Millwood I; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Fry H; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Kartsonaki C; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Mazidi M; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Chen Y; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Bragg F; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Liu B; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Yang L; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Liu J; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Avery D; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Schmidt D; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Sun D; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Pei P; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Lv J; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Yu C; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Hill M; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Bennett D; Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Walters R; Medical Research Council Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, U.K.
  • Li L; Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
  • Clarke R; Peking University Center for Public Health and Epidemic Preparedness & Response, Beijing, China.
  • Du H; Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China.
  • Chen Z; Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China.
Diabetes Care ; 47(6): 1012-1019, 2024 Jun 01.
Article em En | MEDLINE | ID: mdl-38623619
ABSTRACT

OBJECTIVE:

Integrated analyses of plasma proteomics and genetic data in prospective studies can help assess the causal relevance of proteins, improve risk prediction, and discover novel protein drug targets for type 2 diabetes (T2D). RESEARCH DESIGN AND

METHODS:

We measured plasma levels of 2,923 proteins using Olink Explore among ∼2,000 randomly selected participants from China Kadoorie Biobank (CKB) without prior diabetes at baseline. Cox regression assessed associations of individual protein with incident T2D (n = 92 cases). Proteomic-based risk models were developed with discrimination, calibration, reclassification assessed using area under the curve (AUC), calibration plots, and net reclassification index (NRI), respectively. Two-sample Mendelian randomization (MR) analyses using cis-protein quantitative trait loci identified in a genome-wide association study of CKB and UK Biobank for specific proteins were conducted to assess their causal relevance for T2D, along with colocalization analyses to examine shared causal variants between proteins and T2D.

RESULTS:

Overall, 33 proteins were significantly associated (false discovery rate <0.05) with risk of incident T2D, including IGFBP1, GHR, and amylase. The addition of these 33 proteins to a conventional risk prediction model improved AUC from 0.77 (0.73-0.82) to 0.88 (0.85-0.91) and NRI by 38%, with predicted risks well calibrated with observed risks. MR analyses provided support for the causal relevance for T2D of ENTR1, LPL, and PON3, with replication of ENTR1 and LPL in Europeans using different genetic instruments. Moreover, colocalization analyses showed strong evidence (pH4 > 0.6) of shared genetic variants of LPL and PON3 with T2D.

CONCLUSIONS:

Proteomic analyses in Chinese adults identified novel associations of multiple proteins with T2D with strong genetic evidence supporting their causal relevance and potential as novel drug targets for prevention and treatment of T2D.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteômica / Diabetes Mellitus Tipo 2 Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Diabetes Care Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Proteômica / Diabetes Mellitus Tipo 2 Limite: Adult / Aged / Female / Humans / Male / Middle aged Idioma: En Revista: Diabetes Care Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Reino Unido