Daily Endocrinology Research Analysis
Three impactful endocrinology papers advance precision care and risk stratification: a Diabetologia cohort study validates a model to target SGLT2 inhibitors for kidney protection beyond albuminuria thresholds; a JCEM inpatient experiment shows estradiol suppression and sleep fragmentation independently worsen cardiometabolic health, highlighting sleep as a modifiable target; a JACC Advances analysis demonstrates that mortality risks from both obesity and underweight are strongest in younger adu
Summary
Three impactful endocrinology papers advance precision care and risk stratification: a Diabetologia cohort study validates a model to target SGLT2 inhibitors for kidney protection beyond albuminuria thresholds; a JCEM inpatient experiment shows estradiol suppression and sleep fragmentation independently worsen cardiometabolic health, highlighting sleep as a modifiable target; a JACC Advances analysis demonstrates that mortality risks from both obesity and underweight are strongest in younger adults, underscoring age-tailored interventions.
Research Themes
- Precision therapeutics in type 2 diabetes and kidney protection
- Menopause biology: estradiol, sleep fragmentation, and cardiometabolic risk
- Age-modified associations between adiposity and mortality
Selected Articles
1. Precision medicine in type 2 diabetes: targeting SGLT2 inhibitor treatment for kidney protection.
Using UK primary care EHR data, the authors validated a CKD-PC–adapted model that predicts individual absolute kidney benefit from SGLT2 inhibitors, outperforming the conventional albuminuria (uACR ≥3 mg/mmol) threshold in targeting therapy. SGLT2 initiation was associated with a 42% lower relative risk of kidney disease progression, and model-guided targeting could prevent >10% more events over 3 years, including in a subgroup with uACR <3 mg/mmol.
Impact: Provides a clinically actionable precision tool to allocate SGLT2 inhibitors for kidney protection beyond albuminuria thresholds, potentially improving population-level outcomes.
Clinical Implications: Clinicians can use a validated risk-prediction approach to identify individuals— including some with uACR <3 mg/mmol— who derive greater absolute kidney benefit from SGLT2 inhibitors, enabling more efficient, equitable prescribing than current guideline thresholds.
Key Findings
- Initiation of SGLT2 inhibitors was associated with a 42% lower relative risk of kidney disease progression vs DPP4i/sulfonylurea (HR 0.58; 95% CI 0.48–0.69).
- The adapted CKD-PC model showed strong calibration (slope ~1.05–1.10) and predicted a median absolute risk reduction of 0.37% at 3 years.
- Model-guided targeting prevented >10% more kidney events over 3 years than the uACR ≥3 mg/mmol threshold, identifying a 6.7% subgroup with uACR <3 mg/mmol with higher absolute benefit (3.2% vs 1.2% over 5 years; p=0.05).
Methodological Strengths
- Large real-world comparative cohort with robust EHR data and externalized risk score (CKD-PC) calibration.
- Clear clinical utility demonstration via event prevention estimates under model-guided targeting.
Limitations
- Observational design with potential residual confounding and treatment selection bias.
- Generalizability beyond UK primary care and to diverse ethnicities requires further validation.
Future Directions: Prospective pragmatic trials to test model-guided SGLT2i allocation, integration into electronic prescribing systems, and external validation across healthcare systems and ancestries.
AIMS/HYPOTHESIS: Current guidelines recommend use of sodium-glucose cotransporter-2 inhibitors (SGLT2 inhibitors) for kidney protection in people with type 2 diabetes and early-stage chronic kidney disease (CKD) based on a urinary albumin/creatinine ratio (uACR) of ≥3 mg/mmol. However, individuals with a normal uACR or low-level albuminuria were not represented in kidney outcome trials, leaving uncertainty about absolute treatment benefit in this group. To address this gap and support treatment decisions in clinical practice, we developed and validated a model to predict individual-level kidney protection benefit through the use of SGLT2 inhibitors. METHODS: This observational cohort study used electronic health record data from UK primary care (Clinical Practice Research Datalink, 2013-2020) of adults with type 2 diabetes, eGFR ≥60 ml/min per 1.73 m RESULTS: In 53,096 initiations of SGLT2 inhibitor treatment compared with 88,404 initiations of DPP4 inhibitor/sulfonylurea treatment, there was a 42% lower relative risk of kidney disease progression with SGLT2 inhibitors (HR 0.58; 95% CI 0.48, 0.69), consistent with a previous trial meta-analysis. The CKD-PC risk score did not require recalibration (calibration slope 1.05; 95% CI 0.94, 1.17). The median overall model-predicted absolute risk reduction with SGLT2 inhibitors was 0.37% at 3 years (IQR 0.26-0.55), and showed good calibration (calibration slope 1.10; 95% CI 1.09, 1.12). As an illustration of clinical utility, using the model predictions to target the same proportion of the population (n=25,303, 17.9%) as the albuminuria threshold would prevent over 10% more events over 3 years (253 vs 228) by identifying a subgroup of 6.7% of individuals with uACR <3 mg/mmol who showed significantly greater absolute risk reduction in response to SGLT2 inhibitor treatment than the remainder with uACR <3 mg/mmol (3.2% vs 1.2% in extended 5 year observational analyses, p=0.05). CONCLUSIONS/INTERPRETATION: A model adapting the international CKD-PC risk score can accurately predict the individual-level kidney protection benefit from treatment with SGLT2 inhibitors in people with type 2 diabetes and no or early-stage CKD. This could guide treatment decisions in clinical practice worldwide and could target treatment more effectively than the ≥3 mg/mmol albuminuria threshold recommended by current international guidelines.
2. Adverse cardiometabolic impacts of sleep fragmentation and estradiol suppression: An experimental model of menopause.
In a controlled inpatient crossover experiment with 38 healthy women, estradiol suppression reduced leptin and worsened lipid profiles, while sleep fragmentation raised heart rate and tended to increase fasting glucose. Combined, these core menopausal components worsened cardiometabolic measures, with sleep fragmentation adding a 103% deterioration over estradiol suppression alone, highlighting sleep as a modifiable risk factor.
Impact: Provides mechanistic human evidence that sleep fragmentation independently contributes to cardiometabolic risk during menopausal transition beyond estradiol decline.
Clinical Implications: Menopausal care should address sleep fragmentation (eg, hot flash management, behavioral sleep interventions) alongside hormonal changes to mitigate cardiometabolic risk; monitoring of lipids, heart rate, and possibly leptin may be warranted.
Key Findings
- Estradiol suppression significantly decreased leptin and worsened lipid profiles (FDR-adjusted p≤0.05).
- Sleep fragmentation significantly increased heart rate (FDR-adjusted p=0.002) and trended toward higher fasting glucose (FDR-adjusted p=0.08).
- Sleep fragmentation worsened a composite cardiometabolic index by an additional 103% over estradiol suppression alone; combined exposures worsened individual outcomes by a median of 4.0% from baseline.
Methodological Strengths
- Within-subject, tightly controlled inpatient protocol under eucaloric conditions minimizing confounding.
- Objective multi-domain outcomes with FDR-adjusted analyses across lipid, autonomic, and glycemic measures.
Limitations
- Modest sample size and short-term exposures limit generalizability and long-term inference.
- Induced hypoestrogenism and laboratory sleep fragmentation may not fully recapitulate natural menopausal transition.
Future Directions: Randomized trials testing sleep interventions for cardiometabolic risk reduction in peri/postmenopausal women; mechanistic profiling (autonomic, inflammatory) to map causal pathways and identify biomarkers.
CONTEXT: Risk of cardiometabolic disease increases in women transitioning to postmenopause, during which estradiol declines universally. Most of these women experience fragmentation of sleep due to nocturnal hot flashes, without a reduction in total sleep time. OBJECTIVE: We examined the independent impact of estradiol suppression, sleep, and their combination on cardiometabolic outcomes categorized as satiety and hunger, lipid profile, cardiac vital signs, and glucoregulation. DESIGN: Participants completed 5-night inpatient studies under eucaloric conditions, once during mid-follicular phase/estrogenized and again under estrogen suppressed conditions, using the same experimental protocol both times. For all participants, sleep was unfragmented the first two nights and then experimentally fragmented without reducing total sleep time the next three nights. SETTING: Inpatient Intensive Physiological Monitoring research facility. PARTICIPANTS: 38 healthy premenopausal women. INTERVENTION(S): Clinical experimental induced menopause model including gonadotropin-releasing hormone agonist-induced hypoestrogenism and sleep fragmentation. MAIN OUTCOME MEASURE(S): Leptin and satiety. RESULTS: Estradiol suppression significantly decreased leptin and increased lipid profiles (FDR-adjusted p≤0.05). Sleep fragmentation significantly increased heart rate (FDR-adjusted p=0.002) and trended to increase fasting glucose (FDR-adjusted p=0.08). Estradiol suppression and sleep fragmentation worsened individual cardiometabolic outcomes by (median, IQR) 4.0% (1.5%, 6.3%) from normalized baseline values. Sleep fragmentation worsened a composite cardiometabolic index derived from individual clinical cardiometabolic measures by an additional 103% over estradiol suppression alone. CONCLUSIONS: Independent of aging, there are significant adverse changes in cardiometabolic health induced by core components of the transition to postmenopause, including novel effects of sleep fragmentation, a modifiable target.
3. Age-Specific Associations Between Adiposity and Mortality in U.S. Adults, 1999-2018.
In 44,041 U.S. adults with median 10.1-year follow-up, age significantly modified adiposity–mortality associations across BMI, waist circumference, weight, and waist-to-height ratio. Risks from both severe obesity and underweight were greatest in younger adults, emphasizing the importance of earlier, age-tailored prevention and treatment strategies.
Impact: Quantifies how age modifies the mortality risks of both high and low adiposity using nationally representative data, informing targeted public health and clinical strategies.
Clinical Implications: Prioritize aggressive obesity prevention and treatment in younger adults while also addressing risks of underweight; use multiple adiposity metrics for risk stratification and age-tailored counseling.
Key Findings
- Significant interactions between age and all four adiposity measures for all-cause and cardiovascular mortality (P < 0.05).
- Per 1-SD higher BMI, cardiovascular mortality HR was 1.49 (95% CI 1.27–1.77) in ages 18–49 vs 1.15 (95% CI 0.99–1.32) in ages 70–79.
- Class 3 obesity had HR 4.37 (95% CI 2.01–9.50) for cardiovascular mortality in younger adults; underweight was linked with higher all-cause mortality in younger individuals (HR 2.04; 95% CI 1.24–3.36).
Methodological Strengths
- Nationally representative sample with long follow-up and linkage to mortality outcomes.
- Assessment across multiple adiposity measures with multivariable adjustment and formal age-interaction testing.
Limitations
- Observational design with potential residual confounding and measurement error in anthropometrics.
- Attenuation in older adults may reflect survivor bias or competing risks not fully captured.
Future Directions: Investigate causal pathways and life-course interventions targeting early adulthood; evaluate whether intensive obesity treatment in younger adults reduces long-term mortality.
BACKGROUND: Obesity is a leading risk factor for increased mortality. However, it remains unclear how this relationship varies across different age groups. OBJECTIVES: The purpose of this study was to evaluate whether the associations between adiposity and mortality are modified by age in a nationally representative sample of U.S. adults. METHODS: We analyzed data from 44,041 U.S. adults aged 18 to 79 years from the National Health and Nutrition Examination Survey (1999-2018), linked to mortality data through 2019. Anthropometric measures included body mass index, waist circumference, weight, and waist-to-height ratio. Cox proportional hazards models were used to assess the interaction between age and adiposity on all-cause and cardiovascular mortality, adjusting for demographic, behavioral, and clinical covariates. RESULTS: Over a median follow-up of 10.1 years, there were 5,019 deaths (1,186 cardiovascular). Significant interactions between age and all 4 adiposity measures were observed (P < 0.05). Associations between adiposity and mortality were strongest among younger adults. For example, each 1-SD increase in body mass index was associated with a cardiovascular mortality HR of 1.49 (95% CI: 1.27-1.77) in adults aged 18 to 49 years, vs 1.15 (95% CI: 0.99-1.32) in those aged 70 to 79 years. Class 3 obesity was associated with a cardiovascular mortality HR of 4.37 (95% CI: 2.01-9.50) in younger adults. Underweight status was also associated with elevated all-cause mortality, particularly among younger individuals (HR: 2.04; 95% CI: 1.24-3.36). CONCLUSIONS: Age significantly modifies the relationship between adiposity and mortality. Younger adults experience greater mortality risks from both obesity and underweight, underscoring the need for early, age-tailored interventions.