ArticleDiabetes care2024
Proteomic Analyses in Diverse Populations Improved Risk Prediction and Identified New Drug Targets for Type 2 Diabetes.
Article in Diabetes care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 28 citations in OpenAlex.
- Exploring Biomarkers in Type 2 Diabetes Mellitus versus Normoglycemia Identified through High-Throughput Proteomics: A Systematic Review and Meta-Analysis.Journal of proteome research · 2026Pooled it
- Large-Scale Proteomics Uncovers Pre-Disease Inflammation-Lipid Subtypes to Refine Risk Stratification and Prediction of Type 2 Diabetes.Diabetes, obesity & metabolism · 2026Article
- Proteomic Signatures of 3-Year Progression From Impaired Fasting Glucose to Diabetes: The Atherosclerosis Risk in Communities (ARIC) Study.Diabetes care · 2026Article
- Large-scale multi-omics enhance risk prediction for type 2 diabetes.Cardiovascular diabetology · 2026Article
- Identification of novel protein markers and therapeutic targets for common urological cancers by integrating large-scale human plasma proteome with the genome.Scientific reports · 2026Article
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- Elevated 1 h post-load plasma glucose associates with decreased serum lipoprotein lipase in youth and decreased leg fat mass in midlife.Scientific reports · 2025Article
- Circulating Proteomic Profiles Are Associated With Incident Type 2 Diabetes in Asian Populations.The Journal of clinical endocrinology and metabolism · 2025Article
- Blood plasma proteome-wide association study implicates novel proteins in the pathogenesis of multiple cardiovascular diseases.Cardiovascular diabetology · 2025Article
- Metabolic diseases in the East Asian populations.Nature reviews. Gastroenterology & hepatology · 2025Review
- Plasma proteomic signatures for type 2 diabetes and related traits in the UK Biobank cohort.Diabetes research and clinical practice · 2025Article
- Potential predictive value of CD8A and PGF protein expression in gastric cancer patients treated with neoadjuvant immunotherapy.BMC cancer · 2025Article
- Multi-fluid, multi-omics signatures of insulin resistance and incident type 2 diabetes among Puerto Rican adults.Frontiers in endocrinology · 2025Article
- Proteome Profiling Identifies CDH2 as a Potential Screening Marker for NAFLD and Liver Fibrosis in the Snoring Population.Nature and science of sleep · 2025Article
- Identification of potential novel targets for treating inflammatory bowel disease using Mendelian randomization analysis.International journal of colorectal disease · 2024Article
Corrections and comments
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Authors and funding
29 authors at 2 institutions in 2 countries.
Funding
Abstract
objectiveIntegrated 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
methodsWe 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.
resultsOverall, 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.
conclusionsProteomic 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.
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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.