Daily Endocrinology Research Analysis
Analyzed 79 papers and selected 3 impactful papers.
Summary
Three impactful endocrinology papers stood out today: a large meta-analysis confirms elevated, site-specific fracture risks in type 2 diabetes; a multi-omics study reveals that postprandial responses outperform fasting metrics for obesity risk stratification and are modulated by diet and gut microbiota; and a neuroendocrine oncology cohort shows >90% NET-specific mortality in carcinoid syndrome with chromogranin A and lung primary as independent prognosticators.
Research Themes
- Diabetes and skeletal health risk
- Postprandial multi-omics and personalized nutrition
- Neuroendocrine tumor prognosis and biomarkers
Selected Articles
1. Association between type 2 diabetes and site-specific fracture risk: A systematic review and meta-analysis of cohort studies including over 13 million participants.
Across 22 cohort studies including 13,074,868 individuals, type 2 diabetes was associated with a 25% higher overall fracture risk, with the strongest increases in lower limb fractures (hip, ankle, foot). Risk was higher in women and with longer diabetes duration, supporting site-specific risk assessment and preventive strategies in T2D.
Impact: Defines precise, site-specific fracture risks in T2D at unprecedented scale, informing targeted screening and prevention. Registration and large sample strengthen causal inference from observational data.
Clinical Implications: Incorporate site-specific fracture risk into T2D care (e.g., prioritize lower limb fracture prevention), especially in women and those with longer disease duration; consider early bone health assessment and fall prevention.
Key Findings
- Pooled HR for any fracture in T2D vs non-diabetes: 1.25 (95% CI 1.20–1.31).
- Higher risks at specific sites: lower limb HR 1.43 (1.30–1.57), upper limb HR 1.29 (1.16–1.45), fragility fractures HR 1.14 (1.02–1.28).
- Risk elevation stronger in prospective cohorts, greater among women, and with longer T2D duration.
Methodological Strengths
- Registered protocol (PROSPERO) and comprehensive multi-database search.
- Large pooled sample (13,074,868) enabling precise site-specific estimates and meta-regression.
Limitations
- Heterogeneity across cohorts and potential residual confounding inherent to observational data.
- Variability in fracture ascertainment and adjustments across included studies.
Future Directions: Prospective, harmonized cohorts with standardized fracture ascertainment and stratification by glycemic control, medications, and diabetes duration to refine site-specific risk models.
OBJECTIVE: This review aimed to quantify the association between Type 2 Diabetes (T2D) and the risk of fracture at various anatomical sites by synthesising data from cohort studies. METHODS: A systematic search was conducted across Medline, Embase, CINAHL and Web of Science databases, from inception to 10 June 2025. We estimated pooled hazard ratios (HRs) with corresponding 95% confidence intervals using random-effects models. This study is registered with PROSPERO (CRD42024548795). RESULTS: This meta-analysis of 22 studies, selected from 6534 screened studies, assessed a total of 13,074,868 individuals (2,644,443 people with T2D and 10,430,425 without T2D). People with T2D have a 25% increased risk of fractures (all anatomical sites) compared to individuals without T2D (HR: 1.25; 95% CI: 1.20 to 1.31). T2D was significantly associated with an increased risk of appendicular lower limb fractures (HR: 1.43; 95% CI: 1.30 to 1.57), upper limb fractures (HR: 1.29; 95% CI: 1.16 to 1.45), osteoporotic/fragility fractures (HR: 1.14; 95% CI: 1.02 to 1.28) and appendicular unspecified fractures (HR: 1.25; 95% CI: 1.05 to 1.48). Subgroup analyses indicated stronger associations in prospective studies. Women with T2D had a significantly higher fracture risk than men. Meta-regression analyses showed that a higher percentage of women participants and a longer duration of T2D were associated with stronger associations between T2D and fracture risk, particularly for lower limb fractures. CONCLUSION: T2D is associated with an increased risk of fractures, especially in lower limbs (hip, ankle and foot). These findings highlight the importance of targeted fracture prevention strategies and site-specific risk assessment for individuals with T2D. However, due to the heterogeneity among studies, caution is required in the interpretation of these findings.
2. Multi-omics analysis of dynamic profiles in response to various nutrient loads provides novel insights into obesity.
In 147 participants undergoing mixed-meal testing and 24 in single macronutrient loads, postprandial multi-omic profiles correlated more strongly with obesity than fasting metrics. An acute obesity-risk signature (AORS) ranked glucose lowest among isocaloric macronutrients, and olive oil responses differed by gut enterotype, highlighting diet–microbiome–metabolism interactions.
Impact: Introduces a dynamic, multi-omic framework and a quantifiable AORS to refine obesity risk assessment, moving beyond static fasting measures and enabling microbiota-informed nutrition strategies.
Clinical Implications: Supports incorporating postprandial testing and considering gut enterotypes when tailoring macronutrient recommendations; suggests potential for real-time, personalized nutrition to mitigate obesity risk.
Key Findings
- Postprandial multi-omic analytes outperformed fasting measures in association with obesity indicators.
- Among isocaloric macronutrients, glucose showed the lowest acute obesity-risk signature (AORS 0.1082 ± 0.1917%).
- Olive oil AORS differed by gut enterotype (Bacteroides vs Prevotella; p=0.043), indicating microbiota-modulated nutrient responses.
Methodological Strengths
- Integrated untargeted metabolomics, lipidomics, proteomics, and hormones with metagenomic profiling.
- Two complementary protocols (MMTT and SMNTT) enabling pathway and nutrient-specific inference.
Limitations
- Observational design with limited sample size in SMNTT (n=24) may constrain generalizability.
- Short-term, acute responses; long-term clinical outcomes not assessed.
Future Directions: Genotype- and microbiota-stratified interventional trials testing macronutrient prescriptions guided by AORS and real-world, continuous phenotyping.
BACKGROUND& AIMS: Obesity is a global health issue driven by improper nutrient intake and metabolic dysregulation. The complexity of dietary components and the dynamic nature of postprandial metabolism limit our understanding of how different nutrient loads associated with obesity. This study aims to characterize the dynamic metabolic responses to nutrient intake using multi-omics approaches, assess the influence of dietary habits and gut microbiota, and evaluate the acute obesity-risk signature (AORS) associated with different macronutrients. METHODS: We conducted a mixed meal tolerance test (MMTT) in 147 non-diabetic individuals (54 controls, 38 overweight, 55 obese). Blood samples were collected at multiple time points for untargeted metabolomics, lipidomics, proteomics, and hormone assays. Gut microbiota was profiled via metagenomic sequencing. A separate single macronutrient tolerance test (SMNTT) involving glucose, whey protein, butter, and olive oil was performed in 24 healthy volunteers to compare acute metabolic responses and derive an AORS based on postprandial multi-omics data. RESULTS: Postprandial multi-omic analytes showed stronger associations with obesity indicators than fasting measures. Distinct temporal changes in metabolites, lipids, and proteins were observed across different BMI groups, with enrichment in pathways such as bile acid biosynthesis, triglyceride metabolism, and complement activation. Dietary habits and gut microbiota significantly influenced postprandial metabolic profiles, with specific metabolites and proteins mediating their effects on obesity. In SMNTT, glucose load exhibited the lowest AORS among isocaloric macronutrients (0.1082 ± 0.1917 %). Gut microbiota composition further modulated metabolic responses, with olive oil showing divergent AORS between Bacteroides- and Prevotella-dominated enterotypes (p = 0.043). CONCLUSION: Postprandial multi-omics provides superior insights into obesity pathophysiology compared to fasting measurements. Our findings reveal that dietary habits and gut microbiota significantly influence postprandial metabolism and obesity risk, and demonstrate that different macronutrients confer distinct AORS values, which are further modified by an individual's gut microbiota composition. This underscores the potential for personalized nutritional strategies based on dynamic metabolic responses and microbial ecology.
3. Determining Prognosis in Patients With Carcinoid Syndrome: A Retrospective Single-Center Cohort Study.
Among 427 patients with carcinoid syndrome, 90.6% of recorded deaths were NET-specific, median OS was 7.1 years, and 5- and 10-year survival were 65.1% and 34.1%. Age, WHO grade 2, elevated chromogranin A (CgA), and primary lung NET predicted worse survival, while carcinoid heart disease was not independently associated after accounting for CgA.
Impact: Clarifies that mortality in carcinoid syndrome is predominantly NET-specific and identifies accessible prognostic markers (CgA, grade, lung primary) to refine risk stratification and follow-up intensity.
Clinical Implications: Use CgA levels, tumor grade, and primary site to stratify risk and guide surveillance and therapeutic escalation in CS; emphasizes the need for more effective systemic options given high NET-specific mortality.
Key Findings
- NET-specific deaths accounted for 90.6% (231/255) of recorded deaths in CS.
- Median overall survival: 7.1 years; 5-year and 10-year survival: 65.1% and 34.1%.
- Independent predictors of worse survival: age (HR 1.06), WHO grade 2 (HR 2.11), CgA 200–940 µg/L (HR 1.64) and >940 µg/L (HR 3.18), and primary lung NET (HR 1.77).
Methodological Strengths
- Large single-center cohort with long observation window (1995–2021).
- Multivariable Cox modeling and cause-of-death categorization.
Limitations
- Retrospective, single-center design limits generalizability; treatment paradigms evolved over decades.
- Cause of death unavailable in a subset; potential residual confounding.
Future Directions: Prospective, multicenter validation incorporating modern therapies and dynamic biomarkers (e.g., serial CgA, imaging metrics) to refine prognostic models.
BACKGROUND: Carcinoid syndrome (CS), the most prevalent neuroendocrine tumor (NET)-related hormonal syndrome, is associated with impaired survival. However, the contribution of NET-specific death in patients with this syndrome is currently unknown. This study aimed to evaluate overall survival (OS), prognostic factors, and causes of death in patients with CS. PATIENTS AND METHODS: We retrospectively included patients with CS treated between 1995 and 2021 at our ENETS Center of Excellence. We used Kaplan-Meier curves and log-rank tests to perform survival analyses, and a Cox proportional hazards model to calculate mortality hazard ratios (HRs). RESULTS: A total of 295 of 427 included patients with CS died during follow-up, and cause of death was recorded in 255 patients. In 231 (90.6%) patients, the cause of death was NET-specific. Median OS was 7.1 years, and 65.1% and 34.1% of CS patients were alive at 5 and 10 years, respectively. Multivariate analysis identified age (HR, 1.06; P<.001), WHO tumor grade 2 (HR, 2.11; P=.01), plasma chromogranin A (CgA) level of 200 to 940 µg/L (HR, 1.64; P=.04), CgA level >940 µg/L (HR, 3.18; P<.001), and primary lung NET (HR, 1.77; P=.008) as negative predictors of survival. The presence of carcinoid heart disease (HR, 1.01; P=.97) was not associated with OS in a multivariate model due to interaction with CgA levels. CONCLUSIONS: Patients with CS are likely to succumb to their disease, with >90% of mortality being NET-specific. Age, tumor grade, primary lung origin, and CgA levels were independent predictors of mortality. These findings indicate that there is an urgent need for advances in therapeutic options for patients with CS.