Evidence map›Paper›PMID 42638160›Full record

ArticleDiabetes, obesity & metabolism2026

Proteomic Pathways Linking Type 2 Diabetes Genetic Clusters to Cardiovascular Diseases: A Network Mendelian Randomisation Study.

Shuang Liao, Gabriel Chun Yin Sung, Yiwen Liang, Chenxi Li, Shiu Lun Au Yeung

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Article in Diabetes, obesity & metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 · What the graph read from it

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Shuang LiaoSchool of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
Gabriel Chun Yin SungSchool of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.ORCID https://orcid.org/0000-0001-7284-3347
Yiwen LiangSchool of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
Chenxi LiSchool of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.
Shiu Lun Au YeungSchool of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China.ORCID https://orcid.org/0000-0001-6136-1836

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenetic clusters related to Type 2 diabetes (T2D) have differential impact on cardiovascular diseases (CVDs), although the underlying mechanisms, such as proteomic perturbation, remain unexplored. We conducted a network Mendelian randomisation (MR) study to identify proteomic mediators linking T2D genetic clusters and CVDs.

methodsWe assessed the associations between genetic liability to T2D and eight genetic clusters (N = 2 535 601) with 12 CVDs (N ≤ 1 946 349). For significant pairs, we performed a two-step MR (mediation) to identify proteins mediating these associations. Inverse-variance weighted method was the main analysis, with sensitivity analyses including genetic colocalisation. Robustness was evaluated in European-specific analyses as well as using Olink-measured proteomic data. False discovery rate (FDR) was used to correct for multiple comparisons.

resultsObesity cluster was linked to most CVDs (except haemorrhage strokes), with similar patterns for body fat, metabolic syndrome and lipodystrophy clusters. Majority of the protein signals (2739 out of 4907) were related to obesity cluster although glycemia-related clusters were only associated with a few proteomic signals (≤ 13). Amongst 16 proteins supported by genetic colocalisation (PP

conclusionThis proteogenomic MR study delineates protein-mediated pathways linking cluster-stratified T2D genetic predisposition to cardiovascular risk, which can inform preventive strategies by stratifying individuals based on distinct biological pathways represented by these genetic clusters.

Indexed as

Cardiovascular DiseasesDiabetes Mellitus, Type 2Genetic Predisposition to DiseaseGenome-Wide Association StudyHumansMendelian Randomization AnalysisMultigene FamilyObesityPolymorphism, Single NucleotideProteomicscardiovascular diseasegenetic clustersmendelian randomisationproteinstype 2 diabetes

Identifiers

PMID42638160
PMCPMC13646353

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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 OpenQuestion graph.