Biomedical subjects

Chen-Yang Su

Publications and source records attributed to Chen-Yang Su.

3 recordsLinked to original sources

PubMed2026

Disentangling adiposity-related and non-adiposity-related genetic pathways for type 2 diabetes.

OBJECTIVE: To identify circulating proteins associated with type 2 diabetes (T2D) risk through pathways not fully explained by body mass index (BMI), and to assess therapeutic actionability. RESEARCH DESIGN AND METHODS: We applied GWAS-by-subtraction within a genomic structural equation model to European ancestry summary statistics for T2D (74,124 cases, 824,006 controls) and BMI (n = 681,275), partitioning T2D liability into BMI-related and BMI-subtracted components. We then performed proteome-wide Mendelian randomization (MR) using cis-protein quantitative trait loci from four plasma proteomics cohorts: ARIC, deCODE, Fenland, and the UK Biobank Pharma Proteomics Project. Prioritized proteins passed sensitivity analyses with alternative MR methods and were supported by colocalization evidence. Tissue-resolution regulatory support was assessed using cis-eQTL colocalization across GTEx and pancreatic islet, subcutaneous adipose, and whole-blood resources. Actionability was evaluated using the druggable genome and Open Targets. RESULTS: GWAS-by-subtraction attenuated the genetic correlation between BMI and BMI-subtracted T2D from 0.54 (SE 0.02) to 0.35 (SE 0.02). Proteome-wide MR prioritized 29 proteins for BMI-subtracted T2D. Thirteen showed eQTL colocalization in at least one tissue, implicating liver and intermediary metabolism (GCDH, NOTCH2), pancreatic islet biology (CTRB2, MANBA), adipose and Wnt signaling (RSPO3, GALNT3), and whole blood regulatory signals (PAM, SNUPN). Sixteen proteins were classified within druggable-genome Tiers 1-3, and five had existing Open Targets compounds. CONCLUSIONS: Integrating GWAS-by-subtraction, proteome-wide MR, and colocalization nominated 29 proteins associated with T2D liability not fully explained by BMI. These findings highlight genetically supported targets for follow-up studies of T2D therapies that complement weight-centered approaches.

Journal Article↗

PubMed2026

Genetic evidence prioritizes circulating proteins for heart failure beyond shared BMI-related genetic liability.

BACKGROUND: Heart failure (HF) and body mass index (BMI) share substantial genetic architecture, which may lead genetically informed target discovery to preferentially identify adiposity-related pathways. We sought to identify circulating proteins associated with HF beyond this shared genetic component. METHODS: We applied GWAS-by-subtraction to overall HF, nonischemic HF, and nonischemic HF with reduced or preserved ejection fraction to derive BMI-related and BMI-subtracted HF components. We then performed proteome-wide cis-pQTL Mendelian randomization and colocalization using four independent proteomic cohorts, followed by tissue-specific eQTL colocalization, cardiac transcriptomic annotation, and druggability assessment. RESULTS: Compared with the original HF phenotypes, the BMI-subtracted components showed attenuated genetic correlations with BMI (0.045-0.147) while retaining 28 independent loci for overall HF and nine for nonischemic HF. Across 19,930 protein-HF tests, 11 associations involving nine proteins were prioritized by the Mendelian randomization and colocalization analyses. For example, a 1-SD increase in genetically predicted CELSR2 abundance was associated with lower overall HF risk (odds ratio, 0.96 [95% CI, 0.94-0.98]; P=8.6×10-7), whereas a 1-SD increase in genetically predicted CSF3 abundance was associated with higher nonischemic HF risk (odds ratio, 1.32 [95% CI, 1.18-1.48]; P=2.0×10-6). CELSR2 and TMEM106B colocalized with cis-eQTLs in failing left ventricular myocardium, and DAG1 showed cardiomyocyte enrichment with concordant downregulation in failing hearts. CONCLUSIONS: We identified nine circulating proteins associated with HF beyond the genetic component shared with BMI. These findings extend the range of genetically supported pathways implicated in HF and nominate candidate proteins for further mechanistic and therapeutic investigation.

Genetics↗

PubMed2025

Cardiovascular risk reduction with glucagon-like peptide-1 receptor agonists is proportional to HbA1c lowering in type 2 diabetes: An updated meta-regression analysis incorporating FLOW and SOUL trials.

AIMS: To evaluate relationships of cardiovascular and kidney outcomes with glycemic or bodyweight reductions in randomised placebo-controlled trials of glucagon-like peptide-1 receptor agonists (GLP-1RAs), incorporating data from FLOW and SOUL trials. MATERIALS AND METHODS: PubMed and EMBASE were searched up to 22 August 2025 for placebo-controlled randomized trials of oral or bolus-type, subcutaneous GLP-1RAs reporting major adverse cardiovascular events (MACE; a composite of cardiovascular death, myocardial infarction, and stroke) in adults with type 2 diabetes. The primary outcome was MACE; secondary outcomes included heart failure (HF) and kidney outcomes. Random-effects meta-analyses were followed by meta-regression evaluating associations with HbA1c and bodyweight reduction. RESULTS: A total of 73 263 individuals were included from 10 trials (ELIXA, LEADER, SUSTAIN-6, EXSCEL, Harmony Outcomes, PIONEER 6, REWIND, AMPLITUDE-O, FLOW, and SOUL). GLP-1RAs reduced MACE by 14% (hazard ratio: 0.86; 95% CI: 0.82 to 0.91; p <0.001), as well as hospitalisation for HF and the composite kidney outcome (both p <0.001). Meta-regression showed that every 1% extra reduction in HbA1c corresponded to a 27% lower HR for MACE (p = 0.015; R2 = 0.61). While HbA1c reduction was not significantly associated with secondary outcomes, the directionality was consistent with MACE. Bodyweight change was not associated with any of the analysed endpoints, including MACE (p = 0.13; R2 = 0.21). CONCLUSIONS: HbA1c reduction, not bodyweight change, was significantly and proportionally associated with MACE risk reduction. HbA1c lowering may serve as a useful surrogate for the cardiovascular improvements associated with GLP-1RAs in type 2 diabetes.

Humans↗