Daily Endocrinology Research Analysis
Three impactful endocrinology studies stand out today: a nationwide cohort shows the triglyceride-glucose (TyG) index independently predicts cardiovascular events and mortality in diabetes; an international EBioMedicine cohort reveals oligogenic architectures in 46,XY DSD with NR5A1/SF-1 variants; and a large, multiethnic analysis defines ethnicity-specific normative cut-offs for hirsutism (mFG scale), refining PCOS diagnostics. Together, they advance precision risk stratification, genetic couns
Summary
Three impactful endocrinology studies stand out today: a nationwide cohort shows the triglyceride-glucose (TyG) index independently predicts cardiovascular events and mortality in diabetes; an international EBioMedicine cohort reveals oligogenic architectures in 46,XY DSD with NR5A1/SF-1 variants; and a large, multiethnic analysis defines ethnicity-specific normative cut-offs for hirsutism (mFG scale), refining PCOS diagnostics. Together, they advance precision risk stratification, genetic counseling, and culturally appropriate diagnostic thresholds.
Research Themes
- Precision cardiometabolic risk stratification using simple biomarkers
- Oligogenic genetics in disorders of sex development (DSD)
- Ethnicity-specific diagnostic thresholds for hirsutism and PCOS
Selected Articles
1. The PCOS Phenotype in Unselected Populations study: ethnic variation in population-based normative cut-offs for defining hirsutism.
In 9,829 community participants across eight countries, ethnicity-specific normative cut-offs for hirsutism (mFG scores) ranged from 4 to 8, confirming 2023 PCOS guideline recommendations while highlighting meaningful ethnic variation. These data justify ethnicity-tailored thresholds to reduce misclassification in PCOS evaluation.
Impact: Provides large-scale, population-based, multiethnic normative mFG cut-offs, enabling more equitable and precise PCOS diagnostics globally.
Clinical Implications: Adopt ethnicity-specific mFG cut-offs (range 4–8) when defining hirsutism to improve diagnostic accuracy for PCOS and tailor management. Aligns with, and refines, international guideline recommendations.
Key Findings
- Ethnicity-specific mFG normative cut-offs ranged from 4 to 8 across 9,829 participants.
- Highest cut-off: White Iranians (8); elevated cut-offs in White Italians and Black Africans (7).
- Cut-offs of 5 for Han Chinese, White Russians, Turkish, and Black Americans; 4 for White Americans, Asian Koreans, Asian/Mixed Russians.
- Findings confirm 2023 International PCOS Guidelines and emphasize the need to consider ethnicity.
Methodological Strengths
- Large, unselected, multi-country individual participant data analysis (n=9,829)
- Cluster analysis (k-means) on directly assessed mFG scores with cross-ethnic comparisons
Limitations
- Cross-sectional design limits causal inference for determinants of hirsutism
- Potential heterogeneity in mFG assessment and ethnic classification across studies
Future Directions: Prospective validation of ethnicity-specific thresholds against clinical outcomes and androgen levels; integration with AI-assisted image scoring to reduce inter-rater variability.
OBJECTIVE: Hirsutism, a diagnostic feature of polycystic ovary syndrome (PCOS), is often defined using arbitrary percentile cutoffs, rather than normative cutoffs from population-based data. We aimed to define normative cutoffs for hirsutism in diverse populations. DESIGN: Unselected population-based cluster analysis of individual participant data (IPD). METHODS: The PCOS Phenotype in Unselected Populations (P-PUP) study IPD asset of community-based studies, underwent k-means cluster analysis, of directly assessed hirsutism, using the modified Ferriman-Gallwey (mFG) visual scale. The primary outcome was ethnicity-specific normative cutoffs for the mFG score. Medians and cutoffs were compared across ethnic groups. RESULTS: We included 9829 unselected, medically unbiased participants, aged 18-45 years from 12 studies conducted across 8 countries including China, Iran, Italy, Nigeria, Russia, South Korea, Turkey, and the United States. The mFG cutoff scores for hirsutism on cluster analysis varied across ethnicities, ranging from 4 to 8. White Iranians had the highest cutoff score of 8, followed by White Italians and Black Africans of 7. Asian Han Chinese, White Russian, Turkish, and Black Americans shared a cutoff of 5; White Americans, Asian Koreans, Asian Russians, and Mixed Russians shared a cutoff of 4. Comparing medians and mFG cutoffs across ethnicities confirmed the same differences. CONCLUSION: This study confirms the 2023 International PCOS Guidelines recommendations defining hirsutism as an mFG score between 4 and 6 for the majority of populations studied, with few exceptions. However, we also highlight ethnic variation in mFG cutoff scores, suggesting that clinicians consider ethnicity in optimal diagnosis and personalized interventions.
2. Oligogenic analysis across broad phenotypes of 46,XY differences in sex development associated with NR5A1/SF-1 variants: findings from the international SF1next study.
Among 30 individuals with NR5A1/SF-1–related 46,XY DSD, 73% harbored one to seven additional rare variants (mostly in DSD genes), supporting oligogenic contributions to phenotype. Machine-learning–assisted filtering and ORVAL modeling highlighted combined pathogenicity, refining interpretation and counseling.
Impact: Introduces a robust framework to uncover oligogenic architectures in DSD, informing variant interpretation, penetrance, and individualized genetic counseling.
Clinical Implications: Genetic evaluation of NR5A1/SF-1–related DSD should consider additional DSD-gene variants and potential oligogenic interactions; counseling and management may be adjusted based on composite genetic risk.
Key Findings
- 73% (22/30) of 46,XY DSD cases with NR5A1/SF-1 variants had 1–7 additional rare variants, predominantly in known DSD genes.
- Identical variants were shared across eight unrelated individuals; additional frequent hits occurred in genes including FLNB, GLI2/3, KAT6B, SPRY4, ZFPM2.
- ORVAL modeling supported combined pathogenicity consistent with oligogenic mechanisms.
Methodological Strengths
- Whole-exome sequencing with trio analysis and tailored variant filtering in DSD genes
- Use of ORVAL machine learning to assess combined variant pathogenicity
Limitations
- Sample size is modest (n=30), limiting power to detect rare interactions
- Functional validation for many variant combinations is lacking
Future Directions: Expand to larger, multi-ancestry cohorts with functional assays to validate gene–gene interactions; integrate phenomics to quantify penetrance and expressivity.
BACKGROUND: Oligogenic inheritance has been suggested as a possible mechanism to explain the broad phenotype observed in individuals with differences of sex development (DSD) harbouring NR5A1/SF-1 variants. METHODS: We investigated genetic patterns of possible oligogenicity in a cohort of 30 individuals with NR5A1/SF-1 variants and 46,XY DSD recruited from the international SF1next study, using whole exome sequencing (WES) on family trios whenever available. WES data were analysed using a tailored filtering algorithm designed to identify rare variants in DSD and SF-1-related genes. Identified variants were subsequently tested using the Oligogenic Resource for Variant Analysis (ORVAL) bioinformatics platform for a possible combined pathogenicity with the individual NR5A1/SF-1 variant. FINDINGS: In 73% (22/30) of the individuals with NR5A1/SF-1 related 46,XY DSD, we identified one to seven additional variants, predominantly in known DSD-related genes, that might contribute to the phenotype. We found identical variants in eight unrelated individuals with DSD in DSD-related genes (e.g., TBCE, FLNB, GLI3 and PDGFRA) and different variants in eight genes frequently associated with DSD (e.g., CDH23, FLNB, GLI2, KAT6B, MYO7A, PKD1, SPRY4 and ZFPM2) in 15 index cases. Our study also identified combinations with NR5A1/SF-1 variants and variants in novel candidate genes. INTERPRETATION: These findings highlight the complex genetic landscape of DSD associated with NR5A1/SF-1, where in several cases, the use of advanced genetic testing and filtering with specific algorithms and machine learning tools revealed additional genetic hits that may contribute to the phenotype. FUNDING: Swiss National Science Foundation and Boveri Foundation Zurich.
3. Association between the Triglyceride-Glucose Index and Cardiovascular Risk and Mortality across Different Diabetes Durations: A Nationwide Cohort Study.
In over 1.09 million adults with diabetes, higher TyG index quartiles were independently associated with increased CVD (HR 1.18) and mortality (HR 1.16), with stronger effects in those with fasting glucose ≥126 mg/dL and diabetes duration ≥10 years. Associations were accentuated in younger, non-obese, and non-smokers.
Impact: Demonstrates a simple, widely available index (TyG) as a robust risk stratifier for CVD and mortality in diabetes across disease durations, supporting clinical adoption in cardio-metabolic care.
Clinical Implications: Incorporate TyG index into routine diabetes risk assessment to identify high-risk patients (especially with FPG ≥126 mg/dL or long disease duration) for intensified preventive cardiometabolic interventions.
Key Findings
- Highest TyG quartile (Q4) vs Q1: HR 1.18 for CVD and HR 1.16 for mortality after full adjustment.
- Stronger associations among patients with FPG ≥126 mg/dL and diabetes duration ≥10 years (CVD HR up to 1.44).
- Risk elevations were more pronounced in younger, non-obese, and non-smoker subgroups.
Methodological Strengths
- Very large nationwide cohort (n>1.09 million) with multivariable adjustment and subgroup analyses
- Stratification by diabetes duration and glycemic control enhances clinical interpretability
Limitations
- Observational retrospective design; residual confounding cannot be excluded
- Single-nation dataset may limit generalizability to other healthcare systems
Future Directions: Prospective validation and intervention trials testing TyG-guided prevention strategies; integration with genetic and imaging markers for multimodal risk models.
BACKGRUOUND: We aimed to assess the association between triglyceride-glucose (TyG) index and cardiovascular disease (CVD) risk and mortality in a large cohort of diabetes patients. METHODS: A retrospective cohort study of 1,090,485 participants from the Korean National Health Insurance Service database was conducted. Participants were stratified into TyG quartiles. RESULTS: Higher TyG index quartiles were significantly associated with an increased CVD risk and mortality risk. In fully adjusted models, participants in the highest TyG quartile (Q4) had an 18% higher risk of CVD (hazard ratio [HR], 1.18; 95% confidence interval [CI], 1.13 to 1.23) and a 16% higher risk of mortality (HR, 1.16; 95% CI, 1.11 to 1.23) compared to those in the lowest quartile (Q1). The association was particularly pronounced in patients with fasting glucose ≥126 mg/dL (CVD [HR, 1.33; 95% CI, 1.29 to 1.37], mortality [HR, 1.23; 95% CI, 1.20 to 1.26]; P for interaction <0.001). Patients with a diabetes duration of ≥10 years showed the strongest association between the TyG index and CVD risk (HR, 1.44; 95% CI, 1.38 to 1.50), while the mortality risk was particularly elevated in those with a diabetes duration of less than 5 years (HR, 1.23; 95% CI, 1.18 to 1.30). Subgroup analyses revealed stronger associations between TyG index and CVD risk in younger participants, non-obese individuals, and non-smokers. CONCLUSION: The TyG index is a significant predictor of CVD and mortality in diabetic patients, particularly in those with poor glycemic control or longer disease duration.