Blood Plasma Proteome-Wide Association Study Implicates New Proteins in Type 2 Diabetes Mellitus Pathogenesis

The pathophysiological mechanisms underlying type 2 diabetes mellitus (T2DM) remain incompletely understood, and the disease continues to impose a substantial burden on global health. In this study, we integrated the data from the largest genome-wide association study (GWAS; N = 898 130) of T2DM with human plasma protein quantitative trait locus (pQTL; N = 53 022) data to conduct the first proteome-wide association study (PWAS) of T2DM. Following Mendelian randomization and colocalization analyses, we identified 9 independent putatively causal proteins. Among these, 3 were successfully replicated in other independent pQTL datasets, including 2 (HYOU1 and FLT3) that were novel and not identified in the original GWAS. Further integration with expression quantitative trait locus (eQTL) data from 3 diabetes-related tissues (blood, adipose tissue, and pancreas) revealed that 5 of the causal proteins also showed significant associations with T2DM at their cis-regulatory mRNA levels. Subsequent functional annotation supported potential pathogenic roles of the causal proteins. Notably, drug repurposing analysis identified 29 candidate drugs for T2DM treatment by targeting 4 causal proteins. In conclusion, our findings provide new insights into the pathogenesis of T2DM and highlight promising targets for future mechanistic and therapeutic investigations.

Authors

Institutions

Publication Details

Journal
The Journal of Clinical Endocrinology & Metabolism
Published
2025-08-12
DOI
https://doi.org/10.1210/clinem/dgaf462
Citations
1
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
1.82
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Blood Plasma Proteome-Wide Association Study Implicates New Proteins in Type 2 Diabetes Mellitus Pathogenesis

Jia-Hao Wang, Guanchen Liu, Tian-Pei Zhang, Shan‐Shan Dong et al.
1 citations
The Journal of Clinical Endocrinology & Metabolism
Genetic Associations and Epidemiology
1.82
article

Blood Plasma Proteome-Wide Association Study Implicates New Proteins in Type 2 Diabetes Mellitus Pathogenesis

Jia-Hao Wang, Guanchen Liu, Tian-Pei Zhang, Shan‐Shan Dong, Yan Guo, Tie‐Lin Yang, Yang Yang, Hairong Wang, Wei Chen, Ruo-Han Hao
article en
1 citations

Abstract

The pathophysiological mechanisms underlying type 2 diabetes mellitus (T2DM) remain incompletely understood, and the disease continues to impose a substantial burden on global health. In this study, we integrated the data from the largest genome-wide association study (GWAS; N = 898 130) of T2DM with human plasma protein quantitative trait locus (pQTL; N = 53 022) data to conduct the first proteome-wide association study (PWAS) of T2DM. Following Mendelian randomization and colocalization analyses, we identified 9 independent putatively causal proteins. Among these, 3 were successfully replicated in other independent pQTL datasets, including 2 (HYOU1 and FLT3) that were novel and not identified in the original GWAS. Further integration with expression quantitative trait locus (eQTL) data from 3 diabetes-related tissues (blood, adipose tissue, and pancreas) revealed that 5 of the causal proteins also showed significant associations with T2DM at their cis-regulatory mRNA levels. Subsequent functional annotation supported potential pathogenic roles of the causal proteins. Notably, drug repurposing analysis identified 29 candidate drugs for T2DM treatment by targeting 4 causal proteins. In conclusion, our findings provide new insights into the pathogenesis of T2DM and highlight promising targets for future mechanistic and therapeutic investigations.

The Journal of Clinical Endocrinology & MetabolismVol. 111(2)
Xian Center for Disease Control and Prevention (CN), First Affiliated Hospital of Xi'an Jiaotong University (CN), Xi'an Jiaotong University (CN)
Openalex Percentile: Top 13%
Genetic Associations and Epidemiology
1.82
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.