Daily Endocrinology Research Analysis
Three impactful endocrinology-related studies advanced precision care and diagnostics: kinome profiling in MEN2 revealed RET variant–specific signaling targets for medullary thyroid cancer; copeptin measurement at ED admission improved diagnosis and risk stratification in hypotonic hyponatremia; and a new interpretable Steatotic Liver Index outperformed the Fatty Liver Index for steatotic liver disease detection and prediction.
Summary
Three impactful endocrinology-related studies advanced precision care and diagnostics: kinome profiling in MEN2 revealed RET variant–specific signaling targets for medullary thyroid cancer; copeptin measurement at ED admission improved diagnosis and risk stratification in hypotonic hyponatremia; and a new interpretable Steatotic Liver Index outperformed the Fatty Liver Index for steatotic liver disease detection and prediction.
Research Themes
- Precision oncology in endocrine neoplasia
- Biomarker-enabled triage in electrolyte disorders
- Interpretable machine learning for metabolic liver disease
Selected Articles
1. Kinome profiling reveals pathogenic variant specific protein signalling networks in MEN2 children with Medullary Thyroid Cancer.
Kinome profiling across 24 familial MEN2 cases uncovered RET variant– and subtype–specific signaling alterations (mTOR, PKA, NF-κB, focal adhesion) and validated these in patient thyroid tissues. These data provide mechanistic insight and nominate actionable pathways that could complement RET-directed strategies in medullary thyroid cancer.
Impact: Provides first-in-kind functional kinome maps in pediatric MEN2, revealing variant-specific drivers beyond RET and pointing to new therapeutic targets.
Clinical Implications: While not practice-changing yet, these findings support biomarker-driven stratification and exploration of combinatorial therapies (e.g., RET inhibitors plus mTOR or NF-κB pathway modulators) in medullary thyroid cancer.
Key Findings
- Kinome profiling of 24 familial MEN2 patients identified RET variant–specific signaling alterations involving mTOR, PKA, NF-κB, and focal adhesion pathways.
- Findings were validated in patient thyroid tissue, supporting biological relevance.
- Results reveal novel disease drivers and potential therapeutic targets differing by MEN2 subtype and RET pathogenic variant.
Methodological Strengths
- Use of functional kinome profiling with validation in patient-derived thyroid tissues
- Subtype- and variant-specific analyses enabling mechanistic granularity
Limitations
- Small cohort size (n=24) may limit generalizability
- Lack of in vivo functional validation or direct clinical outcome correlations
Future Directions: Test targeted inhibitors against the identified pathways in preclinical MEN2 models; integrate kinome signatures with clinical outcomes to guide personalized therapy and trial stratification.
Multiple Endocrine Neoplasia Type 2 (MEN2) is an autosomal dominant disease caused by pathogenic variants in the receptor tyrosine kinase RET, with strong genotype-phenotype correlations. The development and progression of these tumours are not always predictable even within families with the same RET pathogenic variant, demonstrating a need for better understanding of the underlying molecular mechanisms. Precision molecular medicine is not widely used and the standard of care remains prophylactic thyroidectomy. This absence of curative approaches is exacerbated by the lack of novel therapeutic markers/targets. In this study, we investigated the functional kinome of 24 familial MEN2 patients. We identified MEN2 subtype and RET pathogenic variant-specific alterations in signalling pathways including mTOR, PKA, NF-κB and focal adhesions, which were validated in patient thyroid tissue. Overall, our study of MEN2 functional kinomes uncovers novel specific drivers of MEN2 disease and its pathogenic variant subtypes, identifying new potential therapeutic targets for MEN2.
2. Reassessing the Role of Copeptin in Emergency Department Admissions for Hypotonic Hyponatremia.
In a prospective ED cohort with 6-month follow-up, the copeptin-to-urinary sodium ratio (≤29.5 pmol/mmol) markedly improved identification of preserved extracellular fluid status and outperformed standard urinary sodium thresholds. Copeptin levels also predicted in-hospital and 6-month mortality, providing actionable diagnostic and prognostic information at presentation.
Impact: Introduces an easily measurable biomarker and a combined index (copeptin/u-Na) that refines volume assessment in hypotonic hyponatremia and stratifies mortality risk.
Clinical Implications: Incorporating copeptin with urinary sodium at ED admission can improve differentiation of preserved vs depleted ECF states and guide initial therapy, while identifying high-risk patients for closer monitoring.
Key Findings
- Copeptin/u-Na ratio ≤29.5 pmol/mmol increased the odds of preserved ECF more than four-fold (OR 4.28; P=.026), outperforming standard urinary sodium (AUC difference 0.177; P=.013).
- Copeptin >60.1 pmol/L predicted in-hospital mortality (P=.0005).
- Copeptin >13.6 pmol/L indicated >4-fold risk of 6-month mortality (HR 4.507; P=.0001).
Methodological Strengths
- Prospective cohort with blinded expert adjudication of ECF status
- Use of both direct and indirect ion-selective electrode assays and predefined mortality endpoints
Limitations
- Single-center study with a modest sample size (n=84)
- No interventional validation of biomarker-guided management
Future Directions: Validate copeptin-based algorithms in multicenter cohorts and randomized trials to test whether biomarker-guided management improves clinical outcomes.
CONTEXT: The role of copeptin in assessing hyponatremic patients at emergency department (ED) admission remains debated. OBJECTIVE: This work aimed to assess copeptin's effectiveness in evaluating extracellular fluid (ECF) volume and its predictive value in hyponatremic adults admitted to the medical ED. METHODS: This work comprises a report from the IPSO-URG, a prospective cohort study with recruitment from June 2018 to August 2019 and 6-month follow-up. The setting is a medical ED of a single tertiary center. Patients included a consecutive sample of 123 adults with hyponatremia confirmed by direct and indirect ion-selective electrode assay after glucose correction. Excluding 33 individuals with missing consent or criteria and 6 without hypotonic hyponatremia, 84 patients were analyzed. Data included symptoms, vital signs, ultrasound, medical history, Charlson Comorbidity Index, and pretreatment blood and urine samples. ECF status was reassessed post discharge by 3 endocrinologists, blinded to copeptin results, who classified cases etiologically and resolved disagreements through discussion. In-hospital and 6-month mortality were recorded. RESULTS: A copeptin-to-urinary sodium (u-Na) ratio less than or equal to 29.5 pmol/mmol increased the likelihood of preserved ECF more than 4-fold (odds ratio 4.28; P = .026), outperforming standard u-Na (area under the curve difference 0.177; P = .013). Copeptin predicted in-hospital mortality (hazard ratio [HR] 1.005), with greater than 60.1 pmol/L as the optimal cutoff (P = .0005). Copeptin (HR 1.005; P = .02), N-terminal prohormone of brain natriuretic peptide (HR 1.004; P = .031), and comorbidity burden (HR 1.207; P = .009) predicted 6-month mortality, with copeptin greater than 13.6 pmol/L indicating a more than 4-fold risk (HR 4.507; P = .0001). CONCLUSION: Measuring copeptin on ED admission in hypotonic hyponatremia aids diagnosis and mortality prediction. The copeptin/u-Na index more accurately identifies preserved ECF than the standard u-Na cutoff.
3. Steatotic liver index: An interpretable predictor of steatotic liver disease using machine learning with an enhanced shrinkage method.
Using a large health-check cohort (n=92,968), the authors developed an interpretable four-variable Steatotic Liver Index via a modified LASSO. SLI achieved higher diagnostic discrimination than FLI (C-statistic 0.909 vs 0.892; p<0.001) and better predicted both incident SLD and remission among those with SLD.
Impact: Delivers a simple, transparent tool with superior performance to FLI for SLD detection and prognosis, supporting scalable screening and monitoring.
Clinical Implications: SLI can be implemented in routine health checks to better identify and follow individuals at risk for SLD, prioritizing lifestyle or pharmacologic interventions; external validation will be needed before global adoption.
Key Findings
- SLI uses four routinely available variables (BMI, waist circumference, ALT, triglycerides) selected via a modified LASSO emphasizing interpretability.
- For SLD diagnosis, SLI outperformed FLI (C-statistic 0.909 vs 0.892; p<0.001) on the test set.
- SLI better predicted incident SLD in those without SLD and remission among those with SLD compared with FLI.
Methodological Strengths
- Very large cohort with internal training/test split and prespecified performance metrics
- Interpretable, parsimonious model using routine clinical variables
Limitations
- Single-region dataset (Tokyo, Japan) with ultrasound-defined SLD; lacks external validation
- Observational design may include selection and measurement biases
Future Directions: External validation across diverse populations and imaging standards; evaluation of clinical impact and cost-effectiveness of SLI-guided care pathways.
AIM: While the Fatty Liver Index (FLI) has been the most prominent among interpretable predictors for steatotic liver disease (SLD), we aimed to prepare a novel diagnostic/prognostic index better than FLI for SLD using a non-black-box and modified parsimonious machine learning method. METHODS: We included individuals who participated in an annual health checkup in Tokyo, Japan, between January 2008 and December 2018. In the training set (randomly selected 80% of the sample), we developed a novel interpretable model, Steatotic Liver Index (SLI), using a modified method of least absolute shrinkage and selection operator regression focusing on parsimony and interpretability using as few variables as FLI, and confirming its superiority to FLI using the test set (the remaining 20%). The predictive performance of the constructed index was assessed for the diagnosis, development, and remission of SLD. RESULTS: Among ultrasound data of 92 968 participants at the first health checkup, 20 380 (21.9%) had SLD. Using a modified method of least absolute shrinkage and selection operator regression, SLI was constructed with four variables: body mass index, waist circumference, alanine aminotransferase, and triglycerides. The C-statistic of SLI for SLD diagnosis was superior to that of FLI (0.909 vs. 0.892, p < 0.001). In participants without SLD, SLI was more accurate than FLI in predicting SLD development, whereas among those with SLD, SLI showed better accuracy in predicting SLD remission compared with FLI. CONCLUSIONS: We developed SLI, a novel interpretable and parsimonious index for diagnosing SLD, which demonstrates superior predictive capability compared with FLI. Further studies are necessary to validate the diagnostic ability outside Japan.