Daily Endocrinology Research Analysis
Gene–by–lifestyle interactions in human skeletal muscle were mapped after a 16-week weight-loss intervention, revealing lifestyle-responsive e/sQTLs and Asian-specific regulatory variants. Independent cohorts showed that metformin exposure consistently alters a defined panel of circulating proteins across platforms, underscoring the need to account for drug use in proteomic biomarker studies. Global analyses indicate a rising burden of type 1 diabetes in adolescents and young adults through 2045
Summary
Gene–by–lifestyle interactions in human skeletal muscle were mapped after a 16-week weight-loss intervention, revealing lifestyle-responsive e/sQTLs and Asian-specific regulatory variants. Independent cohorts showed that metformin exposure consistently alters a defined panel of circulating proteins across platforms, underscoring the need to account for drug use in proteomic biomarker studies. Global analyses indicate a rising burden of type 1 diabetes in adolescents and young adults through 2045, informing prevention and health system planning.
Research Themes
- Gene-by-lifestyle regulation in skeletal muscle
- Pharmacoproteomics of metformin and biomarker interpretation
- Global epidemiology and projections of type 1 diabetes in youth
Selected Articles
1. Impact of polymorphisms on gene expression and splicing in response to exercise and diet-induced weight loss in human skeletal muscle tissues.
In 54 overweight/obese Asian adults, a 16-week lifestyle intervention induced ~10% weight loss and ~30% higher insulin-stimulated glucose uptake, with improvements in 118/252 traits. Paired-muscle transcriptomics identified 505 DE genes and thousands of muscle e/sQTLs, including hundreds that were lifestyle-responsive; 4.2% of eQTLs and 7.3% of sQTLs were Asian-specific. Colocalization with GWAS highlighted 16 putative metabolic risk genes, revealing gene-by-lifestyle regulation in human muscle.
Impact: This study provides one of the first comprehensive maps of lifestyle-responsive regulatory variants in human skeletal muscle, including population-specific effects, bridging interventional physiology with functional genomics.
Clinical Implications: Findings inform precision lifestyle medicine by identifying regulatory variants that modulate transcriptional responses to weight loss, potentially guiding stratified interventions and targets for metabolic disease prevention.
Key Findings
- ~10% weight loss and ~30% increase in insulin-stimulated glucose uptake after 16 weeks
- 505 differentially expressed genes enriched for mitochondrial function and insulin sensitivity
- Thousands of muscle e/sQTLs identified, including hundreds lifestyle-responsive
- Asian-specific proportion: 4.2% of eQTLs and 7.3% of sQTLs
- Colocalization with GWAS highlighted 16 putative metabolic risk genes
Methodological Strengths
- Paired pre/post skeletal muscle biopsies with comprehensive transcriptomics
- Integration of e/sQTL mapping with GWAS for mechanistic inference
Limitations
- Sample size limited to 54 individuals from Asian populations
- Single-tissue (skeletal muscle) focus may miss systemic regulatory effects
Future Directions: Replicate lifestyle-responsive e/sQTLs across ancestries and tissues, test causality with CRISPR perturbations, and evaluate predictive utility for tailoring lifestyle interventions.
Weight loss through exercise and diet reduces the risk of type 2 diabetes, but the genetic regulation of gene expression and splicing in response to weight loss remains unclear in humans. We collected clinical data and skeletal muscle biopsies from 54 overweight/obese Asian individuals before and after a 16-week lifestyle intervention, which resulted in an average of ∼10% weight loss, accompanied by an ∼30% increase in insulin-stimulated glucose uptake. Improvements were observed in 118 of 252 clinical traits and six blood lipids. Transcriptomic analysis of paired skeletal muscle biopsies identified 505 differentially expressed genes enriched in mitochondrial function and insulin sensitivity. Thousands of muscle-specific expression/splicing quantitative trait loci (e/sQTLs) were detected pre- and post-intervention, including hundreds of lifestyle-responsive e/sQTLs. Notably, approximately 4.2% of eQTLs and 7.3% of sQTLs showed Asian specificity. Joint analysis with genome-wide association study (GWAS) identified 16 putative metabolic risk genes. Our study reveals gene-by-lifestyle interactions and how lifestyle modulates gene regulation in skeletal muscle.
2. The influence of metformin treatment on the circulating proteome.
Across discovery and two large replication cohorts using Olink and SomaLogic, 23 circulating proteins were robustly associated with metformin exposure, including 11 replicated across platforms (e.g., GDF15, REG4, t-PA, NOTCH3). Enrichment suggested intestinal-associated proteins. The study demonstrates that drug exposure can materially shape proteomic readouts, with implications for biomarker discovery and clinical interpretation.
Impact: By harmonizing longitudinal and cross-sectional cohorts with cross-platform validation, this work sets a benchmark for pharmacoproteomic confounding, directly informing trial design and clinical biomarker use in diabetes and beyond.
Clinical Implications: Proteomic studies and clinical assays should record and adjust for metformin and other medications; candidate biomarkers overlapping this metformin signature warrant re-evaluation for specificity.
Key Findings
- Identified 23 proteins consistently associated with metformin exposure across discovery and replication
- Eleven proteins (e.g., REG4, GDF15, REG1A, t-PA, TFF3, CDH5, CNTN1, OMD, NOTCH3, THBS4, CD93) replicated across both cohorts and platforms
- Gene-set enrichment implicated intestinal-associated proteins
- Cross-platform validation (Olink and SomaLogic) strengthens robustness
Methodological Strengths
- Discovery–replication framework with large independent cohorts
- Cross-platform proteomic validation (Olink and SomaLogic)
Limitations
- Longitudinal exposure duration and dosing details not specified in abstract
- Residual confounding from comorbidities or concomitant medications may persist
Future Directions: Quantify dose–response and time-course effects of metformin on proteome, extend to other widely used drugs, and develop adjustment algorithms for biomarker pipelines.
BACKGROUND: Metformin is one of the most used drugs worldwide. Given the increasing use of proteomics in trials, bioresources, and clinics, it is crucial to understand the influence of metformin on the levels of the circulating proteome. METHODS: We analysed a combined longitudinal proteomics dataset from the IMPOCT, RAMP and S3WP-T2D clinical trials in 98 participants before and after metformin exposure. This discovery analysis contained 372 proteins measured by proximity extension assays (Olink). We followed up experiment-wise statistically significant findings in two cross-sectional cohorts of people with type 2 diabetes comparing metformin treated and untreated individuals: IMI-DIRECT (784 participants, 372 proteins, Olink) and IMI-RHAPSODY (1175 participants, 1195 proteins, SomaLogic). FINDINGS: Overall, 23 protein analytes were robustly associated with exposure to metformin in the discovery and replication. This includes 11 protein-metformin associations that replicated in both replication sets and platforms (REG4, GDF15, REG1A, t-PA, TFF3, CDH5, CNTN1, OMD, NOTCH3, THBS4 and CD93), with the remaining 12 protein-metformin associations replicated using the Olink platform (EPCAM, SPINK1, SAA-4, COMP, ITGB2, ADGRG2, FAM3C, MERTK, COL1A1, HAOX1, VCAN, TIMD4) but not measured on the SomaLogic platform. Gene-set enrichment analysis revealed that the metformin exposure was associated with intestinal associated proteins. INTERPRETATION: These data highlight the need to account for exposure to metformin, and potentially other drugs, in proteomic studies and where protein biomarkers are used for clinical care. FUNDING: Innovative Medicines Initiative Joint Undertaking 2, under grant agreement no. 115881 (RHAPSODY) and the Innovative Medicines Initiative Joint Undertaking under grant agreement no. 115317 (DIRECT), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies in kind contribution as well as the Swiss State Secretariat for Education Research' and Innovation (SERI), under contract no. 16.0097 (RHAPSODY).
3. Global epidemiology of type 1 diabetes in youth: 1990-2021 and projections to 2045.
Using GBD 2021, the study reports 7.34 million prevalent cases and 196,104 incident cases of T1D among 15–39-year-olds in 2021, with rising prevalence and incidence since 1990 and declining mortality. The burden concentrates in middle SDI regions and South Asia, with projections indicating ~571,556 incident cases by 2045, predominantly in ages 15–19.
Impact: Comprehensive global quantification and projections provide actionable intelligence for resource allocation, screening strategies, and adolescent-focused prevention in T1D.
Clinical Implications: Health systems should prepare for increasing adolescent-onset T1D by expanding access to insulin, technologies, and education; region-specific strategies are needed, especially in South Asia and middle SDI regions.
Key Findings
- 2021 prevalence: 7.34 million cases among 15–39-year-olds; incidence: 196,104
- 1990–2021 increases in prevalence and incidence; mortality rates declined
- Middle SDI regions and South Asia bear the highest absolute burden
- Projected incidence by 2045: ~571,556 cases, heavily among ages 15–19
Methodological Strengths
- Utilization of standardized GBD 2021 methodology across regions and time
- Reporting of uncertainty intervals and annual percent change with SDI stratification
Limitations
- GBD estimates depend on data quality and modeling assumptions varying by region
- Clinical phenotyping heterogeneity and diagnostic practices may affect comparability
Future Directions: Link projections to cost-effectiveness analyses for insulin and diabetes technologies, and develop targeted adolescent screening/prevention programs in high-burden regions.
AIMS: This study examines the global burden of type 1 diabetes (T1D) among adolescents and young adults (15-39 years) from 1990-2021, with projections to 2045. METHODS: Using data from the Global Burden of Disease (GBD) 2021, we analyzed T1D prevalence, incidence, deaths, disability-adjusted life years (DALYs), and annual percent change (AAPC), with regional and gender differences. RESULTS: In 2021, global T1D prevalence among 15-39-year-olds was 7.34 million cases (95% UI: 5.94-9.00 million), with males accounting for 50.66%. Incidence was 196,104 cases (141,606-277,782), with 55.31% males. From 1990-2021, prevalence increased from 200.11-246.89 per 100,000 (AAPC 0.68), and incidence rose from 5.10-6.59 per 100,000 (AAPC 0.83). In 2021, there were 16,135 deaths and 1.40 million DALYs, with 54.94% attributed to males. Death rates decreased (AAPC -0.35). Middle SDI regions had the highest prevalence (1.86 million) and incidence (54,541), while high SDI areas had the highest rates. Low-middle SDI areas had the most deaths (5170) and DALYs (419,772). South Asia had the highest prevalence (1.73 million), incidence (46,310), deaths (5189), and DALYs (413,293). India, the USA, and China had the highest prevalence and incidence, while Finland, Canada, and Italy had the highest rates. By 2045, T1D incidence is projected to reach 571,556 cases, predominantly affecting those aged 15-19 years. CONCLUSION: The rising burden of T1D among adolescents and young adults underscores the need for targeted interventions and healthcare policies, particularly in high-risk regions.