Aug 2026· Diabetes, obesity and metabolism· 0 citations· 48 references
Medicine
TL;DR
This network Mendelian randomisation 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.
Abstract
Background
Genetic 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.
Methods
We 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.
Results
Obesity 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 (PPH4 > 0.8), the proportion mediated ranged from 1.2% to 36.8%. APOC3, ADH1B, F11 and KLKB1 appeared to be shared across the different genetic clusters, implicating their shared role in CVDs risk. Sensitivity and replication analyses gave similar estimates.
Conclusion
This 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.
The authors' study identified putative actionable proteins that could reduce the elevated T2D risk attributable to childhood adiposity in Europeans, but their relevance in Asian populations requires further investigation.
Siyu Chen, Yiwen Liang, Shan Luo et al.· International Journal of Epi...· 0 citations
Insulin resistance (IR) is a hallmark feature of Type 2 Diabetes Mellitus and a well-established risk factor for coronary heart disease (CHD), yet the pathways through which IR contributes to CHD remain incompletely understood. To comprehensively describe the genetic architecture of IR, we collected three direct IR indicators--- fasting insulin (N = 151,013), the Modified Stumvoll insulin sensitivity index (N = 53,657), and pro-insulin (N = 45,861), and conducted joint analysis on them using Linkage Disequilibrium (LD) Score Regression and factor analysis. A single latent IR factor was generated which captures 60.5% of the shared genetic variance. Based on the IR factor, a multivariate GWAS was conducted within Genomic Structural Equation Modelling and then we built a polygenic risk score (PRS) of IR for the UK Biobank European cohort (N = 407,767; 55,729 CHD cases and 352,038 controls). Then we performed the association study to quantify the relationship between genetically predicted IR and CHD. Causal mediation analyses were also performed through 2,923 plasma proteins (Olink) and 168 metabolites (Nightingale NMR), followed by serial-mediation models (IR -> protein -> metabolite -> CHD) over all prescreened pairs. Single-mediator screening nominated 938 proteins and 159 metabolites; this yielded 3,669 significant "protein -> metabolite -> CHD" serial-mediation pathways, from which 33 broadly-acting core mediating proteins were prioritized. These acted predominantly through the large and very large high-density lipoprotein (HDL) particle subclasses: 30 of the 33 core proteins and all 14 HDL-subclass metabolites formed 306 pathways, of which 303 (99.0%) amplify the CHD risk. These results map a proteomic and metabolomic axis linking the genetic component of IR to CHD and highlight HDL lipoprotein-subclass biology as a candidate therapeutic and biomarker space.
R. Dong, J. Fu, B. Zhang et al.· medRxiv· 0 citations
BACKGROUND
Ischemic heart disease (IHD) is the leading cause of morbidity and mortality. Branched-chain amino acids (BCAAs) are associated with higher IHD risk, but the underlying biological pathways remain unclear.
OBJECTIVE
This study aims to explore these pathways using two-step proteome-wide Mendelian randomization.
METHODS
We examined the associations between genetic proxies for BCAAs and 2,922 proteins in the UK Biobank Pharma Proteomics Project (UKB-PPP), supplemented by a meta-analysis with data from deCODE to identify proteins associated with BCAAs. Then we tested their effects on IHD risk using CARDIoGRAMplusC4D (122,733 cases, 424,528 controls) and replicated in FinnGen (31,640 cases, 187,152 controls). We conducted sensitivity analyses using genetic instruments from deCODE. Proteins associated with IHD risk and, in a consistent direction, with genetically predicted BCAAs were considered potential mediators.
RESULTS
Genetic proxies for BCAAs were associated with 40 proteins. Among these, six proteins showed consistent evidence of mediation, including complement component 1s (C1S), coagulation factor II (F2), granulin (GRN), proprotein convertase subtilisin/kexin type 9 (PCSK9), sex hormone-binding globulin (SHBG) and V-set and transmembrane domain-containing Protein 2 Like (VSTM2L). These proteins are involved in inflammation, coagulation, lipid metabolism and cellular stress response. All associations were robust across different analytical methods and replicated in independent datasets. Mediation analysis showed that these proteins accounted for 6.5% to 32.1% of the association between BCAAs and IHD risk.
CONCLUSIONS
This study identified six proteins that potentially link BCAAs to IHD, implicating pathways related to inflammation, coagulation, lipid metabolism, and cellular stress responses. These findings provide novel mechanistic insights into the BCAA-IHD relationship and highlight potential protein targets for future prevention and intervention strategies.
Junmeng Zhang, R. V. van Dam, Jie V. Zhao· Journal of NutriLife· 0 citations
Blood proteins may play causal roles in cardiovascular diseases (CVDs) such as heart failure (HF) and peripheral artery disease (PAD). Proteome-wide Mendelian randomization (MR) has been widely used to prioritize drug targets for CVD in European populations, but its application to non-European populations remains limited. We conducted a proteome-wide MR analysis to evaluate the potential causal effects of 2,922 plasma proteins on five CVDs—atrial fibrillation (AF), coronary artery disease (CAD), HF, ischemic heart disease (IHD), and PAD. Analyses were performed across African (n = 931), East Asian (n = 262), and European (n = 10,840) populations using genetic instrument data from the UK Biobank cohort. Significant associations were further examined with genetic colocalization to strengthen causal inference. Using MR and colocalization analyses, we identified 53 significant protein–CVD associations across multi-populations, including 16 in African, six in East Asian, and 31 in European populations, respectively. Cross-population comparisons revealed four protein–CVD associations unique to African population and another four specific to East Asian population. Integration with clinical trial data prioritized 14 protein–disease pairs as promising candidates for therapeutic development or drug repurposing. Our findings highlight the value of proteome-wide MR in evaluating drug target applicability across populations. Several protein–disease associations were population-specific, emphasizing the need for inclusive genetic research to inform precision medicine in CVD prevention and treatment.
Hua Zhong, Jingjing Zhu, Shuai Liu et al.· Zeitschrift für Induktive Ab...· 0 citations
Background. Type 2 diabetes (T2D) and coronary artery disease (CAD) frequently co-occur, yet the biological pathways that jointly determine risk remain incompletely understood. Most genetic studies have examined shared risk from a single-disease perspective, limiting insight into the mechanisms that generate discordant risk between conditions. Methods. We applied PLACO to multi-ancestry GWAS data of T2D and CAD to identify shared loci, prioritising shared causal signals using colocalisation. Shared variants were clustered by their associations with 77 cardiometabolic traits, and cluster-specific genetic risk scores (GRS) were tested for association with 17 clinical biomarkers and 1,254 binary outcomes in 378,772 UK Biobank (UKB) participants. Two-sample Mendelian randomisation (MR) was used to test the causal role of liver fat. Results. We identified 149 loci shared between T2D and CAD; most novel loci had discordant effects (35 of 42), in contrast to the predominantly concordant signals reported previously. Clustering 187 independent shared variants revealed seven mechanistic clusters, three of them centred on liver fat and defined by discordant T2D?CAD effects. Enrichment analyses and cluster-GRS associations in UKB highlight associations between higher liver fat and T2D risk with a cardioprotective lipid profile and reduced CAD risk. Genetically higher liver fat increased T2D risk but lowered CAD risk in MR analyses; partitioning liver fat instruments by their effect on ApoB-containing lipoproteins indicates that the CAD effects are determined more by effects of circulating ApoB rather than liver fat itself. Conclusions. Liver fat largely sets the direction of T2D risk, whereas the fate of that lipid, retained in the liver with low circulating ApoB or exported as ApoB-containing lipoproteins, sets the direction of CAD risk. This liver-centric partitioning provides a mechanistic framework for the discordant cardiometabolic effects of hepatic lipid and lipid-lowering pathways, with implications for precision prevention.
X. Jiang, N. HirschmuÌller, H. Taylor et al.· medRxiv· 0 citations
It is revealed that the genetically predisposed higher risk of diabetic maculopathy was associated with increased salience network connectivity, shedding light on the neural drivers of diabetic pathologies.
Lin Chen, Hsin-Yu Hsieh, Nan Cheng et al.· Brain Research Bulletin· 0 citations
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