Daily Endocrinology Research Analysis
Cross-ancestry metabolomics GWAS reveals hundreds of variant–metabolite links and causal ties to coronary artery disease and heart failure. Paired chromatin and transcriptome profiling uncovers depot-specific regulatory architecture in human adipose tissue. Real-world comparative effectiveness shows adding a GLP-1 receptor agonist to basal insulin is associated with markedly fewer complications and lower mortality than insulin intensification.
Summary
Cross-ancestry metabolomics GWAS reveals hundreds of variant–metabolite links and causal ties to coronary artery disease and heart failure. Paired chromatin and transcriptome profiling uncovers depot-specific regulatory architecture in human adipose tissue. Real-world comparative effectiveness shows adding a GLP-1 receptor agonist to basal insulin is associated with markedly fewer complications and lower mortality than insulin intensification.
Research Themes
- Cross-ancestry metabolomics genetics and causal inference
- Depot-specific epigenomic regulation in adipose tissue
- Comparative effectiveness of GLP-1RA add-on versus insulin intensification
Selected Articles
1. Cross-ancestry analyses of Chinese and European populations reveal insights into the genetic architecture and disease implication of metabolites.
Large cross-ancestry metabolite GWAS identified 15 associations in Han Chinese (8 replicated) and 228 more via meta-analysis with UK Biobank Europeans, improving fine-mapping. Mendelian randomization linked higher HDL-triglyceride levels to increased coronary artery disease risk and higher glycine to reduced heart failure risk across ancestries.
Impact: Provides cross-ancestry genetic architecture of circulating metabolites with causal links to major cardiovascular diseases, enabling hypothesis-driven target discovery and risk stratification.
Clinical Implications: Findings support using metabolite-informed genetics for cardiovascular risk prediction and prioritizing pathways (e.g., HDL-triglycerides, glycine) for therapeutic development and precision prevention.
Key Findings
- GWAS of 171 metabolites in 10,792 Han Chinese identified 15 variant–metabolite associations; 8 replicated in an independent Chinese cohort (n=4,480).
- Cross-ancestry meta-analysis with 213,397 Europeans found 228 additional associations and improved fine-mapping resolution.
- Mendelian randomization implicated HDL-triglycerides in higher coronary artery disease risk and glycine in lower heart failure risk across ancestries.
Methodological Strengths
- Large cross-ancestry sample with discovery, replication, and meta-analysis components
- Use of Mendelian randomization to infer causality between metabolites and diseases
Limitations
- Metabolites measured by a single NMR platform may limit biochemical coverage and quantitation granularity
- Ancestry representation focused on Han Chinese and Europeans; limited generalizability to other populations
- MR assumptions (e.g., no horizontal pleiotropy) may not hold for all instruments
Future Directions: Extend to additional ancestries, integrate multi-omics and longitudinal phenotypes, and functionally validate prioritized loci and pathways to enable translation into biomarkers and therapeutics.
Differential susceptibilities to various diseases and corresponding metabolite variations have been documented across diverse ethnic populations, but the genetic determinants of these disparities remain unclear. Here, we performed large-scale genome-wide association studies of 171 directly quantifiable metabolites from a nuclear magnetic resonance-based metabolomics platform in 10,792 Han Chinese individuals. We identified 15 variant-metabolite associations, eight of which were successfully replicated in an independent Chinese population (n = 4,480). By cross-ancestry meta-analysis integrating 213,397 European individuals from the UK Biobank, we identified 228 additional variant-metabolite associations and improved fine-mapping precision. Moreover, two-sample Mendelian randomization analyses revealed evidence that genetically predicted levels of triglycerides in high-density lipoprotein were associated with a higher risk of coronary artery disease and that of glycine with a lower risk of heart failure in both ancestries. These findings enhance our understanding of the shared and specific genetic architecture of metabolites as well as their roles in complex diseases across populations.
2. Chromatin landscape in paired human visceral and subcutaneous adipose tissue and its impact on clinical variables in obesity.
Integrative ATAC-seq and RNA-seq in paired SAT and OVAT revealed twice as many depot-specific accessible regions in visceral fat, with SAT enriched for enhancer activity and OVAT for promoter and repressive/bivalent chromatin states. CTCF (SAT) and BACH1 (OVAT) motifs marked depot-specific regulation, and gene sets correlated with adiposity distribution and insulin–glucose–lipid metrics.
Impact: Reveals depot-specific epigenomic programs linking adipose regulation to clinical metabolic traits, providing a mechanistic basis for visceral fat’s higher cardiometabolic risk.
Clinical Implications: Identifies candidate regulatory factors and chromatin states that could be targeted to modulate visceral adipose dysfunction, informing precision strategies for obesity-related complications.
Key Findings
- Visceral adipose tissue (OVAT) harbored approximately twice as many depot-specific differentially accessible regions as subcutaneous adipose tissue (SAT).
- SAT-specific regions were enhancer-enriched for ECM and metabolic genes, whereas OVAT-specific regions were promoter-enriched and associated with cardiomyopathy-linked genes.
- OVAT showed enrichment of bivalent TSS and repressive chromatin states and was marked by BACH1 motifs; SAT DARs were enriched for CTCF motifs.
- Gene sets from depot-specific regions correlated with clinical measures of fat distribution and insulin, glucose, and lipid metabolism.
Methodological Strengths
- Intra-individual paired sampling minimizes inter-person variability
- Multi-omics integration (ATAC-seq and RNA-seq) with motif analysis and clinical trait correlations
Limitations
- Sample size and donor diversity not specified in the abstract; external generalizability may be limited
- Descriptive epigenomic correlations lack causal perturbation experiments
- Tissue heterogeneity (cell-type composition) may confound depot-specific signals
Future Directions: Single-cell multi-omics and perturbation studies to identify causal regulators, and validation across larger, diverse cohorts to inform therapeutic targeting of visceral adiposity.
BACKGROUND: Obesity is a global health challenge and adipose tissue exhibits distinct depot-specific characteristics impacting differentially on the risk of metabolic comorbidities. METHODS: Here, we integrate chromatin accessibility (ATAC-seq) and gene expression (RNA-seq) data from intra-individually paired human subcutaneous (SAT) and omental visceral adipose tissue (OVAT) samples to unveil depot-specific regulatory mechanisms. FINDINGS: We identified twice as many depot-specific differentially accessible regions (DARs) in OVAT compared to SAT. SAT-specific regions showed enrichment for adipose tissue enhancers involving genes controlling extracellular matrix organization and metabolic processes. In contrast, OVAT-specific regions showed enrichment in promoters linked to genes associated with cardiomyopathies. Moreover, OVAT-specific regions were enriched for bivalent transcription start site and repressive chromatin states, suggesting a "lingering" regulatory state. Motif analysis identified CTCF and BACH1 as most significantly enriched motifs in SAT and OVAT-specific DARs, respectively. Distinct gene sets correlated with important clinical variables of obesity, fat distribution measures, as well as insulin, glucose, and lipid metabolism. INTERPRETATION: We provide an integrated analysis of chromatin accessibility and transcriptional profiles in paired human SAT and OVAT samples, offering new insights into the regulatory landscape of adipose tissue and highlighting depot-specific mechanisms in obesity pathogenesis. FUNDING: SS received EU-Scientia postdoctoral Fellowship and project funding from the European Union's Horizon 2020 Research and Innovation program under the Marie Skłodowska-Curie Grant, (agreement No. 801133). LlCP and TR were supported by Helse Sør-Øst grants to Y.B (ID 2017079, ID 278908). MB received funding from grants from the DFG (German Research Foundation)-Projekt number 209933838-SFB 1052 (project B1) and by Deutsches Zentrum für Diabetesforschung (DZD, Grant: 82DZD00601).
3. Effectiveness of adding glucagon-like peptide-1 receptor agonist on diabetes complications and mortality among basal insulin-treated people with type 2 diabetes: A real-world Korean study.
In 38,634 basal insulin–treated adults with type 2 diabetes, adding a GLP-1RA—versus adding short-acting insulin or switching to premixed—was associated with substantially lower risks of cardiovascular and severe microvascular complications, diabetes-related hospitalization, and all-cause mortality.
Impact: Delivers large-scale real-world comparative effectiveness data supporting GLP-1RA add-on over insulin intensification for hard outcomes, aligning with cardiometabolic benefits seen in trials.
Clinical Implications: For basal insulin–treated T2D patients needing intensification, preferentially adding a GLP-1RA may improve outcomes beyond glycemic control and reduce hospitalizations and mortality.
Key Findings
- Among 38,634 adults, GLP-1RA add-on vs short-acting insulin add-on reduced cardiovascular complications (HR 0.56), severe microvascular complications (HR 0.30), hospitalizations (HR 0.62), and all-cause mortality (HR 0.27).
- Compared with switching to premixed insulin, GLP-1RA add-on lowered cardiovascular complications (HR 0.65), severe microvascular complications (HR 0.36), hospitalizations (HR 0.62), and mortality (HR 0.32).
- Real-world evidence supports GLP-1RA add-on as a superior intensification strategy to insulin-based approaches for multiple clinical endpoints.
Methodological Strengths
- Very large, national claims-based cohort enabling comparative effectiveness analyses across multiple outcomes
- Consistent benefits across cardiovascular, microvascular, hospitalization, and mortality endpoints
Limitations
- Observational design with potential residual confounding and confounding by indication
- Medication adherence, dosing, and lifestyle factors not fully captured in claims data
- Generalizability outside Korean healthcare context requires caution
Future Directions: Propensity-matched and instrumental-variable analyses, subgroup evaluation (e.g., CKD, CVD), and external validation in other health systems to strengthen causal inference.
AIMS: To compare the effectiveness of adding a glucagon-like peptide-1 receptor agonist (GLP-1RA) on composite of diabetes-related complications and mortality with that of adding short-acting insulin (SAI) or shifting to premixed insulin among basal insulin (BI)-treated individuals with type 2 diabetes mellitus (T2DM) in South Korea. METHODS: From the Health Insurance Review and Assessment Service database, individuals with T2DM who initiated BI treatment and had advanced their treatment regimen from July 1, 2012, to December 31, 2018. RESULTS: A total of 38,634 individuals with T2DM were included in this study. Compared to adding SAI to BI, adding GLP-1RA was associated with decreased risks of cardiovascular complications (hazard ratio 0.56; 95 % confidence interval 0.43-0.72), severe microvascular complications (0.30; 0.19-0.48), diabetes-related hospitalization (0.62; 0.53-0.73), and all-cause mortality (0.27; 0.13-0.57). Compared to switching to premixed insulin, adding GLP-1RA was also associated with lower risk of cardiovascular complications (0.65; 0.51-0.84), severe microvascular complications (0.36; 0.22-0.58), diabetes-related hospitalization (0.62; 0.53-0.73), and all-cause mortality (0.32; 0.15-0.67). CONCLUSIONS: In this real-world Korean study, adding GLP-1RA to BI reduced risks of diabetes complications and all-cause mortality than adding SAI or shifting to premixed insulin.