Daily Endocrinology Research Analysis
Three impactful endocrinology-related studies span genetics, metabolism, and clinical safety. A JBMR study identifies inactivating GNAS variants as a new genetic cause of multi-suture craniosynostosis, mechanistically linking impaired GPCR–cAMP signaling to dysregulated osteogenesis. A Gut multicenter cohort shows that admission gut microbiota predict postdischarge diabetes after acute pancreatitis with high accuracy. A large real-world pharmacovigilance screen finds TMP-SMX and metronidazole el
Summary
Three impactful endocrinology-related studies span genetics, metabolism, and clinical safety. A JBMR study identifies inactivating GNAS variants as a new genetic cause of multi-suture craniosynostosis, mechanistically linking impaired GPCR–cAMP signaling to dysregulated osteogenesis. A Gut multicenter cohort shows that admission gut microbiota predict postdischarge diabetes after acute pancreatitis with high accuracy. A large real-world pharmacovigilance screen finds TMP-SMX and metronidazole elevate severe hypoglycemia risk in older adults on sulfonylureas.
Research Themes
- GPCR signaling defects and skeletal/endocrine genetics
- Microbiome-based prediction of endocrine-metabolic outcomes
- Medication safety in diabetes management (drug–drug interactions)
Selected Articles
1. Inactivating GNAS variants impair GPCR signaling and cause multiple suture craniosynostosis in humans and zebrafish.
Germline inactivating GNAS variants were identified as a new cause of multi-suture craniosynostosis. Functional assays and zebrafish/MSC models show impaired G protein assembly and reduced cAMP signaling, relieving SMAD6 repression of RUNX2 and accelerating osteogenesis.
Impact: This study uncovers a novel genetic etiology and a coherent mechanistic pathway linking GPCR signaling defects to craniosynostosis, with implications for genetic diagnosis and pathway-targeted therapies.
Clinical Implications: Incorporate GNAS into craniosynostosis genetic testing panels and consider endocrine evaluation for possible hormone resistance. Mechanistic insights suggest potential for pathway-modulating therapies (e.g., cAMP/CREB or RUNX2/SMAD6 axis) in severe or refractory cases.
Key Findings
- Identified three de novo missense and one inherited splice-site GNAS variants in patients with multi-suture craniosynostosis.
- BRET assays showed impaired trimeric G protein assembly and reduced PTHR1 coupling; variants decreased basal and/or agonist-induced cAMP signaling.
- Zebrafish gnas inactivation and GNAS-deficient human mesenchymal stem cells recapitulated craniosynostosis and revealed CREB–SMAD6–RUNX2 pathway dysregulation driving osteogenesis.
Methodological Strengths
- Integrated human genetics with in vitro BRET functional assays and in vivo zebrafish models.
- Mechanistic dissection of downstream CREB–SMAD6–RUNX2 axis linking cAMP loss to osteogenic differentiation.
Limitations
- Number of affected individuals is limited; penetrance and phenotypic spectrum across populations remain to be defined.
- Translation of zebrafish and in vitro findings to human therapeutic interventions requires further validation.
Future Directions: Expand cohorts to define genotype–phenotype correlations and penetrance; assess therapeutic modulation of cAMP/CREB and RUNX2/SMAD6 signaling in preclinical craniosynostosis models.
G protein α-subunit (Gαs), encoded by GNAS, mediates GPCR signaling through cAMP second messenger pathways, and plays a pivotal role in craniofacial morphogenesis and osteoblast differentiation. Craniosynostosis, one of the most prevalent craniofacial developmental anomalies, is characterized by the premature fusion of cranial sutures. Here, we identify germline heterozygous variants in GNAS as a novel genetic cause of craniosynostosis. Affected individuals presented with multiple-suture synostosis, recognizable dysmorphic features, brachydactyly, short stature, with or without hormone resistance. We identified three de novo missense variants (c.286A>G;p.K96E, c.758A>G;p.Y253C, and c.691C>T;p.R231C) and one maternally inherited splicing variant (c.1039-2A>G). Functional analyses using bioluminescence resonance energy transfer (BRET) assays compared these variants to well-characterized activating variants p.R201H and p.Q227L. All tested variants impaired trimeric G protein assembly to varying degrees and exhibited reduced coupling with PTHR1. While the p.R201H and p.Q227L variants induced excessive cAMP production, the craniosynostosis-associated variants either displayed decreased basal cAMP levels or reduced agonist-induced cAMP production compared to wild-type, suggesting an inactivating nature. In zebrafish models, heterozygous gnas inactivation recapitulated human phenotypes, including multiple-suture synostosis, craniofacial abnormalities, and short stature. Mechanistically, GNAS haploinsufficiency in human mesenchymal stem cells promoted osteogenic differentiation through disrupted cAMP-CREB signaling, which relieved SMAD6-mediated repression of RUNX2 transcription. This study establishes inactivating GNAS variants as a genetic cause of craniosynostosis, uncovers a disease mechanism linking G protein inactivation to craniosynostosis through defective GPCR signal transduction. This study identifies inactivating variants in the GNAS gene as a novel genetic cause of craniosynostosis, a common craniofacial disorder characterized by premature fusion of skull sutures. The GNAS gene encodes the G protein α-subunit which is responsible for transducing GPCR signals through cAMP second messenger pathways. Affected individuals present with multi-suture synostosis, brachydactyly, short stature, with or without hormone resistance. Functional analyses using bioluminescence resonance energy transfer assays demonstrated that these variants impair G protein assembly and receptor coupling, leading to reduced cAMP signaling. Studies in a gnas knockout zebrafish model and GNAS-knockdown human mesenchymal stem cells demonstrated that GNAS deficiency recapitulates craniosynostosis phenotypes and accelerates osteogenic differentiation by disrupting the CREB-SMAD6-RUNX2 pathway. These findings establish GNAS loss-of-function as a mechanism driving craniosynostosis through defective G protein signal transduction.
2. Gut microbiota predict development of postdischarge diabetes mellitus in acute pancreatitis.
In a prospective multicenter cohort of acute pancreatitis, admission gut microbiome profiles predicted postdischarge diabetes with high accuracy (AUC up to 0.95) independent of traditional risk factors. Microbiome diversity also associated with mortality and recurrent pancreatitis.
Impact: Demonstrates a clinically actionable, early predictive tool for postdischarge diabetes using the admission microbiome in AP. This could enable precision surveillance and microbiome-targeted prevention strategies.
Clinical Implications: Consider microbiome-informed risk stratification after AP to target glucose monitoring, early endocrinology referral, and preventive interventions. Supports trials of microbiome modulation to prevent post-AP diabetes.
Key Findings
- Admission buccal and rectal microbiota profiles were associated with postdischarge outcomes including diabetes, mortality, and recurrent AP.
- An 11-species ridge regression classifier predicted postdischarge diabetes with AUC 0.948 (matched) and 0.862 (entire cohort), NPV 96%, and overall accuracy 95%.
- Predictive capacity was independent of AP severity, smoking, and alcohol, suggesting microbiome adds unique prognostic information.
Methodological Strengths
- Prospective multicenter design with long-term follow-up and combined 16S and metagenomic sequencing.
- Robust predictive modeling (ridge regression) with performance metrics and matched/entire cohort validation.
Limitations
- Moderate sample size; external validation in independent cohorts is needed.
- Causality cannot be inferred; interventional studies are required to test microbiome modulation effects.
Future Directions: External validation and randomized trials to test microbiome-targeted interventions for preventing post-AP diabetes; mechanistic studies linking taxa to beta-cell dysfunction.
BACKGROUND: Postdischarge morbidity and mortality is high in acute pancreatitis (AP) and pathophysiological mechanisms remain poorly understood. OBJECTIVES: We aim to investigate the composition of gut microbiota and clinical long-term outcomes of prospectively enrolled patients with AP to predict postdischarge complications. DESIGN: In this long-term follow-up study, we analysed clinical and microbiome data of 277 patients from the prospective multicentre Pancreatitis-Microbiome As Predictor of Severity trial. The primary endpoint was the association of the microbial composition with postdischarge mortality, recurrent AP (RAP), progression to chronic pancreatitis, pancreatic exocrine insufficiency, diabetes mellitus (DM) and pancreatic ductal adenocarcinoma. RESULTS: Buccal (n=238) and rectal (n=249) swabs were analysed by 16S rRNA and metagenomics sequencing using Oxford Nanopore Technologies. Median follow-up was 2.8 years. Distance-based redundancy analysis with canonical analysis of principal coordinates showed significant differences for β-diversity (Bray-Curtis) for postdischarge mortality (p=0.04), RAP (p=0.02) and DM (p=0.03). A ridge regression model including 11 differentially abundant species predicted postdischarge DM with an area under the receiving operating characteristic of 94.8% and 86.2% in the matched and entire cohort, respectively. Using this classifier, a positive predictive value of 66.6%, a negative predictive value of 96% and an accuracy of 95% was achieved. CONCLUSION: Our data indicate that the admission microbiome of patients with AP correlates with postdischarge complications independent from multiple risk factors such as AP severity, smoking or alcohol. Microbiota at admission show excellent capacity to predict postdischarge DM and may thus open new stratification tools for a tailored risk assessment in the future. TRIAL REGISTRATION NUMBER: NCT04777812.
3. Medications Associated with Increased Risk of Hypoglycemia in Older Adults on Sulfonylureas: A High-Throughput Case-Crossover-Based Screening Study.
Across three large US claims databases, a high-throughput case-crossover screen identified sulfamethoxazole/trimethoprim and metronidazole as associated with increased severe hypoglycemia among older adults on sulfonylureas after rigorous CCTC adjustment and FDR control.
Impact: Provides actionable medication safety signals for clinicians managing older adults on sulfonylureas, highlighting specific antibiotics that may precipitate severe hypoglycemia.
Clinical Implications: Avoid or closely monitor SU-treated older adults when prescribing TMP-SMX or metronidazole; consider alternative antibiotics and intensify glucose monitoring during and shortly after co-exposure.
Key Findings
- Among 1607 candidate drugs, TMP-SMX (CCTC OR 1.76; FDR q<0.01) and metronidazole (CCTC OR 2.17; FDR q=0.04) were linked to severe hypoglycemia with sulfonylureas.
- Insulin's apparent risk in CCO analysis attenuated after CCTC adjustment (CCTC OR 1.03), underscoring the importance of controlling for direct drug effects.
- Analytic approach controlled time-varying confounding and multiple testing (FDR 0.05) across three large databases (2003–2022).
Methodological Strengths
- Use of case-crossover with case-case time-control adjustment to mitigate time-varying confounding and direct drug effects.
- Replication across three national datasets and FDR control for multiple hypothesis testing.
Limitations
- Observational screening susceptible to residual confounding and exposure misclassification.
- Findings are hypothesis-generating and require pharmacoepidemiologic confirmation and mechanistic studies.
Future Directions: Confirmatory cohort/self-controlled studies quantifying absolute risk; drug–drug interaction mechanistic work (e.g., CYP2C9/transporters) and clinical decision support integration.
BACKGROUND: Sulfonylureas (SU) are widely used for diabetes management in older adults but can cause hypoglycemia, which may be worsened by drug interactions. We applied high-throughput data mining to identify medications that could increase hypoglycemia risk when taken with SU. METHODS: Using Medicare, MarketScan, and Optum Clinformatics (2003-2022), we identified patients aged ≥ 65 years who experienced a severe hypoglycemic event after at least 90 days on SU. We evaluated all medications dispensed in the 90 days before the event using a case-crossover (CCO) design. We adjusted for time-varying confounding and direct effect of the evaluated medications (precipitant) using a case-case time-control (CCTC) approach and metformin as control. We computed odds ratios (ORs) for its association with hypoglycemia. The false discovery rate (FDR) was controlled at 0.05 to adjust for multiple testing. To reduce confounding from other diabetes medications, we analyzed non-diabetes and diabetes medications separately. RESULTS: Among 1607 candidate drugs received before experiencing hypoglycemia, 86 non-diabetes medications showed a CCO OR ≥ 1.00. With metformin as control, sulfamethoxazole/trimethoprim (CCTC OR 1.76, p < 0.01, FDR q < 0.01) and metronidazole (CCTC OR 2.17, p < 0.01, FDR q = 0.04) were associated with severe hypoglycemia. Among 10 diabetes medications, insulin showed increased association (CCO OR 1.22, p < 0.01); however, once adjusted for the drug's direct effects, CCTC OR was 1.03 (p = 0.47, FDR q = 0.47). CONCLUSIONS: Using a high-throughput data mining approach, we identified two antibiotics (sulfamethoxazole/trimethoprim and metronidazole) that may increase hypoglycemia risk in older adults on sulfonylureas. Given the exploratory nature of this study, these findings warrant further investigation.