The Journal of Clinical Endocrinology & Metabolism

Cushings disease is caused by the overproduction of cortisol. The effects of this disease are well known in a general population, including high blood pressure, diabetes, and weight gain. Cushings disease causes both obesity and metabolic related symptoms, and it can be difficult to discern the obesity-dependent from the obesity-independent mechanisms of Cushings disease. To identify patients with Cushings disease, we identified 476 Michigan Medicine patients between January 1st 2000-2025 along with propensity-matched control cases. We stratified our participants by obesity status and into a Cushings disease group and a control group. As expected, the Cushings group had an elevated BMI compared to the control group (34 kg/m2 vs 29 kg/m2). We found a higher proportion of females diagnosed with Cushings compared to males (287 vs 72). Cushings disease was associated with an increase in the fasting glucose levels in both non-obese and obese patients. In both the obese, and non-obese patients, there was an increase in ALT and AST levels regardless of Cushings disease status, but the increase due to Cushings disease was much greater in the patients with obesity (73.4 vs 35.1 mg/dL). Cushings disease also had a moderating effect on blood pressure, with participants a BMI under 30 kg/m2 increasing by 12.6 mmHg and participants with obesity increasing by only 7.9 mmHg. These findings highlight the need to consider obesity status when evaluating the effects of Cushings disease.

ContextPolycystic ovary syndrome (PCOS) is characterized by hyperandrogenism and frequent metabolic disturbances, including insulin resistance (IR), and is commonly accompanied by chronic low-grade inflammation. Complete blood count (CBC)-derived indices provide inexpensive markers reflecting systemic inflammatory and hematologic status; however, their relationships with androgen-related features in PCOS remain incompletely characterized. ObjectiveTo evaluate associations between androgen-related biomarkers and CBC-derived indices in young women with PCOS and to determine whether these associations persist after accounting for insulin resistance. DesignCross-sectional observational study. SettingSingle-center Gynecological Endocrinology Clinic in Katowice, Poland. ParticipantsWomen aged 16-25 years diagnosed with PCOS (Rotterdam criteria) between 2018 and 2025 (N = 1,300). Available-case and complete-case analyses were performed. Main Outcome MeasuresNeutrophil-to-lymphocyte ratio (NLR), red cell distribution width (RDW), and platelet-to-lymphocyte ratio (PLR). Associations with free androgen index (FAI), total testosterone, and dehydroepiandrosterone sulfate (DHEAS) were assessed using Spearman correlation and multivariable linear regression models adjusted for age and log-transformed HOMA-IR with heteroskedasticity-consistent (HC3) standard errors. False discovery rate (FDR) correction was applied. ResultsFAI was positively associated with NLR in both available-case and complete-case analyses (Spearman {rho} = 0.201; FDR-adjusted q < 0.001). DHEAS showed a positive association with NLR in complete-case analysis (q = 0.040). In multivariable models adjusted for age and log(HOMA-IR) (n = 885-888 depending on outcome), higher FAI was independently associated with lower RDW ({beta} = -0.075; 95% CI -0.141 to -0.009; q = 0.032) and lower PLR ({beta} = -2.37; 95% CI -4.60 to -0.14; q = 0.042). Higher DHEAS was independently associated with lower RDW ({beta} = -0.00056; 95% CI -0.00109 to -0.00004; q = 0.042). In complete-case analysis, total testosterone was inversely associated with PLR ({beta} = -3.91; 95% CI -7.58 to -0.24; q = 0.038). Associations between androgen markers and NLR were attenuated after adjustment. ConclusionsAmong young women with PCOS, androgen-related biomarkers are independently associated with selected CBC-derived indices, particularly RDW and PLR, whereas associations with NLR appear partly explained by shared metabolic correlates. These findings suggest that androgen excess may be linked to subtle hematologic alterations in early-stage PCOS beyond insulin resistance.

ContextPolycystic ovary syndrome (PCOS) is a heterogeneous endocrine disorder associated with reproductive dysfunction and long-term cardiometabolic risk. Traditional phenotype classifications based on diagnostic criteria may not fully capture the multidimensional biological variability underlying endocrine and metabolic risk profiles, particularly in young women. ObjectiveTo identify data-driven endocrine-metabolic phenotypes in young women with PCOS and evaluate their association with established cardiometabolic risk markers. Design and SettingCross-sectional study conducted at a tertiary Gynecological Endocrinology Clinic in Poland between January 2018 and May 2025. ParticipantsA total of 1300 young women diagnosed with PCOS according to Rotterdam criteria were included. The primary analytic cohort comprised 1032 participants aged 16-25 years with complete endocrine-metabolic biomarker data. Main Outcome MeasuresEndocrine-metabolic phenotypes were derived using principal component analysis followed by Gaussian mixture model clustering. Cardiometabolic risk endpoints included impaired glucose tolerance (2-hour plasma glucose during an oral glucose tolerance test [&ge;]140 mg/dL), an atherogenic lipid profile (triglycerides (TG)/high-density lipoproteins (HDL-C) ratio >3.50), elevated non-HDL cholesterol ([&ge;]130 mg/dL), and a composite outcome of any abnormality. ResultsPrincipal component analysis retained 10 components explaining 81.9% of total variance. Unsupervised clustering identified two stable phenotypes (silhouette = 0.392; ARI = 0.842). Cluster 0 (n=954; 92.4%) represented a mixed endocrine-metabolic profile, whereas cluster 1 (n=78; 7.6%) was enriched for thyroid/autoimmune features, with higher anti-thyroid peroxidase antibody levels and higher thyroid-stimulating hormone. Cluster 1 showed a higher prevalence of an atherogenic lipid profile compared with cluster 0, while differences in glucose intolerance and non-HDL cholesterol were modest. Logistic regression analyses suggested phenotype-specific variation in cardiometabolic risk markers. ConclusionsIn a large cohort of young women with PCOS, data-driven analysis identified two reproducible endocrine-metabolic phenotypes, including a distinct thyroid/autoimmune-enriched subgroup. These findings highlight clinically relevant heterogeneity beyond traditional diagnostic phenotypes and support the potential value of integrated endocrine-metabolic profiling for early risk stratification in PCOS.

ObjectivesThere is currently insufficient evidence linking COVID-19 infection with Graves disease (GD). Following the complete lifting of COVID-19 restrictions on December 13, 2022, widespread infection in Guangzhou provides a basis for this study. This research aims to investigate the correlation between COVID-19 infection and GD onset, explore the epidemiological characteristics of newly diagnosed GD post-infection, and offer a scientific basis for treatment. MethodsThe study population included 494 GD outpatients treated in the Department of Endocrinology at the Second Affiliated Hospital of Guangzhou Medical University from January 1 to June 30 each year between 2021 and 2023. They were divided into two groups: 2023 (N=219) and 2021-2022 (N=275), based on the time node of widespread COVID-19 infection in 2023. The new diagnosis rate, general clinical characteristics, and serological test results of GD patients were analyzed before and after the outbreak of COVID-19. ResultsCompared with the 2021-2022 group, the new diagnosis rate of GD patients in 2023 showed a significant increase (12.8% vs. 8.4%, P<0.001). Furthermore, there was a significant decrease in pre-treatment thyrotropin receptor antibody levels (P=0.01), white blood cell count (P=0.02), and neutrophil proportion (P=0.04), while there was a significant increase in the proportion of patients with a family history (P=0.047). Follow-up until June 30 of that year revealed that the proportion of newly diagnosed GD patients developing hypothyroidism during treatment in 2023 significantly increased compared to the 2021-2022 group (P<0.001). ConclusionsAfter widespread infection of COVID-19, the diagnosis rate of newly diagnosed GD increased, which may influence the epidemiological characteristics of related GD patients before initial treatment and during treatment.

ObjectiveSome evidence suggests that higher serum TSH may be a part of normal aging, but current studies are limited to 13-year follow-up. We examined TSH changes during 22 years of follow-up across the adult lifespan. DesignLongitudinal analyses of the population-based HUNT Study in Norway, with TSH measurements from 1995-97, 2006-08 and 2017-19. MethodsIn the overall population and in individuals without thyroid medication or disease, we estimated i) geometric mean serum TSH by age, integrating cross-sectional and longitudinal measurements using linear mixed models, ii) percentiles of the TSH distribution by age, and iii) within-individual TSH change during follow-up, expressed by geometric mean ratios (GMR) reflecting the fold change in geometric mean TSH. ResultsWe included 136,925 TSH measurements among 84,342 participants, of whom 40,615 had [&ge;]2 measurements and 13,613 had [~]22-year follow-up. Mean TSH was higher at older age in men, but weaker and less consistent in women. The TSH distribution widened at older age in men and women. Among individuals without thyroid medication or disease, mean TSH increased modestly by 0.13 mIU/L (GMR 1.09; 95%CI 1.08,1.11) during 22-year follow-up in men, but not in women (GMR 0.99; 95%CI 0.98,1.00). This increase was stronger at 0.5 mIU/L in men aged [&ge;]70 years at baseline (GMR 1.32; 95%CI 1.18,1.48). ConclusionsMean serum TSH increased with age in older men, but showed only modest or no age-related change in younger men and in women. The wider TSH distribution at older age supports the need for age-specific TSH reference ranges. Significance statementPrevious evidence of higher TSH concentrations at older age comes from cross-sectional studies and longitudinal studies with up to 13-year follow-up. We utilized a large population-based study to extend the evidence on within-individual TSH changes to [~]22-year follow-up across the adult lifespan. Mean TSH increased with age in men, modestly at 0.13 mIU/L overall, but stronger at 0.5 mIU/L in men followed from their 70s to their 90s. In women, mean serum TSH appeared stable during follow-up, but more frequent thyroid hormone supplementation may have skewed the TSH distribution away from higher, but still physiological levels. The TSH distribution widened at older age in both men and women, supporting the need for age-specific TSH reference ranges.

ImportanceDiagnosis of polycystic ovary syndrome (PCOS) in adolescence is challenging because menstrual irregularity and hyperandrogenism are common in adolescents. Recent international guidelines highlighted an at risk for PCOS category based on either menstrual regularity or hyperandrogenism; however, its population prevalence and genetic correlates remain unknown. ObjectiveTo estimate the prevalence of PCOS and at risk for PCOS in adolescence and evaluate associations with genetic risk for PCOS. Design, Settings, and ParticipantsPopulation-based analysis of 1,533 adolescents from the Avon Longitudinal Study of Parents and Children (ALSPAC) with sufficient reproductive data. ExposurePolygenic score (PGS) for PCOS derived from the largest genome-wide association study in European women. Main Outcomes and MeasuresGuideline-defined PCOS (presence of both irregular menses and hyperandrogenism) and at risk for PCOS (presence of one feature). ResultsPCOS prevalence was 3.2%, while 27.2% met criteria for being at risk for PCOS. A higher PCOS PGS was associated with hyperandrogenism (OR per SD increase in PGS: 1.22; 95% CI, 1.07-1.39; P=4x10-3) but not irregular menses. Conclusions and RelevanceOver one-fourth of adolescents met criteria for being at risk for PCOS. Genetic risk for PCOS was associated with hyperandrogenism but not isolated menstrual irregularity, suggesting that androgen excess is a more specific early manifestation of inherited PCOS liability.

BackgroundHypertensive disorders of pregnancy (HDP) affect up to 15% of pregnancies and are linked to adverse maternal and fetal outcomes. Primary aldosteronism (PA) affects up to 25% of hypertensive patients. We examined PA prevalence in women with prior HDP and its relationship to hypertension trajectory. MethodsAdults from across the U.S.A. meeting guideline-recommended screening criteria for PA were prospectively tested. Women with a self-reported history of HDP completed a questionnaire examining the relationship between PA and hypertension trajectory. ResultsOf 330 hypertensive parous women (62.4 {+/-} 9.8y; 32.1% non-white), 83 (25.2%) reported a history of HDP. Women with HDP were younger at hypertension diagnosis (38.8 vs. 47.9y; p <0.001). The prevalence of a positive PA test was similarly high in those with and without HDP (26.5% vs 32%; p = 0.35). Among women with HDP, 63 completed the follow-up questionnaire, of whom 15 (23.8%) tested positive for PA. Compared with PA-negative women, those with PA reported a higher proportion of pregnancies complicated by hypertension (76.5% vs. 60.9%, p = 0.11) and fetal complications (55.6% vs. 27.9%, p <0.01). Hypertension trajectories also differed: sustained hypertension, defined as persistently elevated blood pressure beyond the postpartum period, was nearly twice as frequent in women with a positive PA test (66.7 vs. 37.5%; p=0.047). ConclusionOver 25% of women with hypertension and a prior pregnancy screened positive for PA, highlighting its high prevalence, irrespective of history of HDP. Women with HDP remain at elevated cardiovascular risk, and PA may represent a targetable contributor.

There is an unmet need to identify biomarkers of active thyroid eye disease (TED). scRNAseq revealed that orbital fibroblasts from orbital decompressions in people with TED express high levels of thyroid hormone receptors, growth factor receptors, including insulin-like growth factor 1 receptor (IGF1R), and extracellular matrix proteins including SPARC (osteonectin), whereas orbital fat endothelial cells expressed thyroid peroxidase (TPO). SPARC was significantly raised in the serum of people with thyroid disease compared to healthy controls. Furthermore, those with moderate, severe and sight threatening TED had higher SPARC levels than those with thyroid disease but free of TED or mild TED. Free-triiodothyronine (FT3) levels were positively correlated with SPARC in moderate-sight threatening TED. SPARC and IGF1 were positively correlated across people with thyroid disease alone, as well as TED. Thyroid stimulating hormone (TSH) levels were negatively correlated with SPARC in moderate-sight threatening TED. When participants were followed longitudinally, SPARC decreased after the active phase of TED. At the protein level, immunohistochemistry indicated that SPARC was heterogeneously expressed by fibroblasts in both control and TED orbital fat. SPARC is a key mediator of fibrosis and deposition of extracellular matrix and the correlation of SPARC serum levels to TED status and FT3 make it a promising biomarker of active TED.

BackgroundThe role of adipokines in childhood glycemia is poorly understood. We investigate the longitudinal association between adipokines and glycemia in a cohort of children in Mexico City. MethodsChildren from the Programming Research in Obesity, Growth, Environment, and Social Stressors (PROGRESS) cohort (948 children, 52% male) were followed longitudinally from birth. Leptin, adiponectin, glucose, and HbA1c were measured at four, six, and eight years, and fasting insulin at eight years. Adiponectin to leptin ratio (ALR) and HOMA2 indices were computed. Longitudinal associations were examined by linear mixed models and cross-sectional associations were examined by multivariable linear regression. All models were adjusted for maternal and child covariates. FindingsBetween ages four and eight years, average levels of leptin increased from 3{middle dot}2 to 10{middle dot}8 ug/mL; adiponectin dropped from 15{middle dot}7 to 13{middle dot}7 ng/mL; and ALR dropped from 9{middle dot}1 to 3{middle dot}1 ug/ng. Longitudinally, across timepoints four, six, and eight years after birth, there was no association between adipokines and glycemia. However, the cross-sectional analysis at age 8 years found an association between leptin and insulin (1{middle dot}0, 95% CI: 1{middle dot}0; 1{middle dot}1), HOMA2-B (1{middle dot}0, 95% CI: 1{middle dot}0; 1{middle dot}0), HOMA2-IR (1{middle dot}0, 95% CI: 1{middle dot}0; 1{middle dot}1), and HOMA2-S (0{middle dot}9, 95% CI: 0{middle dot}9; 0{middle dot}9). InterpretationFurther investigation is needed to understand the role of adipokines in the development of T2DM in children and the factors that may alter adipokine metabolism.

Breastfeeding is associated with metabolic benefits for women with type 2 diabetes and their infants, yet breastfeeding rates in these women are poorly described. Obesity is associated with type 2 diabetes, and lower breastfeeding rates, making it difficult to disentangle type 2 diabetes vs. obesity effects on breastfeeding. AimsThe primary objective was to examine breastfeeding rates in women with type 2 diabetes, compared to normoglycaemic women with either (1) matched body mass index (BMI) or (2) normal BMI. The secondary objective was to examine variables associated with breastfeeding. MethodsPregnant women with type 2 diabetes (cases) or normoglycaemia (controls) were prospectively recruited. Each case was matched with two controls by age and parity and either (1) matched or (2) normal (18-25 kg/m{superscript 2}) BMI. Data were collected from in-person surveys antenatally, medical records, and a four-month postpartum telephone survey. Analysis included descriptive and inferential statistics. ResultsFour-month breastfeeding data were available for 29, 29 and 28 women in each group. Breastfeeding rates were similar in women with type 2 diabetes and BMI-matched controls, both significantly lower than normal-BMI controls. ConclusionsMaternal obesity, rather than type 2 diabetes, may be the major determinant of reduced breastfeeding rates four-months postpartum.

Stratifying progression from early-stage type 1 diabetes to clinical disease is essential for optimally timing disease-modifying therapies. We previously developed a progression likelihood score (PLS) that includes quantitative IA-2 autoantibody (IA-2A) measurements. This study aligned IA-2A thresholds used for PLS calculation between the radiobinding assay (RBA) and a commercially available RSR IA-2A ELISA to support broader clinical application. Serum samples from 349 children with stage 1 type 1 diabetes were analyzed using both assays. IA-2A positivity was similar by RBA (61.6%) and ELISA (59.0%). Centile-based alignment of ELISA-positive samples defined thresholds corresponding to RBA IA-2A categories. ELISA-derived PLS low (PLS < 0.5), moderate (PLS 0.5-4.0) and high (PLS > 4.0) risk groups stratified progression to stage 3 disease comparably to RBA-derived groups. The 3-year progression rate for children with an ELISA IA-2A PLS >4.0 was 52.4% (95% CI, 30.5- 66.1), similar to the RBA-derived PLS >4.0 group (58.7%; 95% CI, 37.1-72.8). These results demonstrate that the commercial ELISA can be used for PLS-based risk stratification.

The detection of monogenic diabetes illustrates the potential of precision medicine, with treatments tailored to specific genes and diagnosis involving targeted genetic testing. Current detection criteria are derived from White populations. We investigated detection of monogenic diabetes in an unselected multiethnic cohort comprising 1,706 participants diagnosed with diabetes before the age of 30-years. Using broad biomarker criteria (triple pancreatic antibody negative and detectable C-peptide) to select for next generation sequencing of monogenic diabetes genes, we found a non-significantly different minimum cohort prevalence of monogenic diabetes of 2.1% in White, 2.0% in South Asian, 2.5% in African-Caribbean, and 3.6% in Mixed participants. The detection rate, however, varied significantly (17.7% in White, 5.3%in South Asian, 8.0% in African-Caribbean, and 15.2% in Mixed participants, p<0.001). Those without monogenic diabetes showed significant variations in BMI. No difference in phenotype of monogenic diabetes across ancestry groups was observed. Non-white ethnicity participants were significantly more likely to have undiagnosed monogenic diabetes than White with on average a 10-year duration before receiving a correct diagnosis. By applying ancestry-specific BMI cut-offs (White <30, South Asian <27, African-Caribbean and Mixed <35 kg/m{superscript 2}), the overall detection rate increased from 8.8 to 16%, reducing the number needed to test to identify one case from 11 to 6 and boosting detection rates to 39, 11, 9 and 26% in White, South Asian, African-Caribbean and Mixed-ethnicity participants, respectively. These findings were validated in an external real-world dataset. Applying broad biomarker criteria for initial selection, mitigates clinical biases leading to misclassification of monogenic diabetes in non-White ethnicities. However, further tailoring criteria with ethnic-specific BMI cut-offs doubled detection rates, improving cost-effectiveness by minimising unnecessary testing. Our study highlights the need to develop precision medicine approaches accounting for phenotypic variation across diverse populations, to ensure accurate diagnoses and cost-efficient healthcare provision.

Prediabetes is a high-risk dysglycemic state. We used a real-world endocrine/diabetes clinic registry from Najaf, Iraq to characterize patients labeled as having pre-diabetes and to explore factors associated with follow-up engagement. We identified prediabetes visits using keyword-based case finding (English and Arabic terms including prediabetes/pre-diabetes, IFG, IGT, and impaired fasting glucose/tolerance) across semi-structured registry fields. Visit-level data were collapsed to patient-level records. Binary indicators of hypertension, dyslipidemia/statin use, obesity/weight management, smoking, and common glucose-lowering therapies were derived from registry text using keyword/brand-name matching. The primary outcome was follow-up engagement defined as [&ge;]2 recorded visits. The prediabetes subset comprised 242 unique patients and 302 visits. Median age was 45 years (IQR 35-55); 47 patients (19.4%) had [&ge;]2 visits. Median follow-up duration was 0 days (maximum 321). Obesity/weight-management indicators were frequent (71.1%), as were hypertension (43.4%) and dyslipidemia/statin indicators (46.3%). In multivariable logistic regression, no evaluated predictor reached conventional statistical significance for follow-up engagement. Registry enhancements to capture laboratory confirmation and standardized follow-up fields may improve the ability to evaluate diabetes prevention pathways.

Uric acid (UA) is traditionally regarded as a metabolic risk marker; however, its dynamic behavior during glucose-lowering therapy remains incompletely understood. We compared UA responses to a modified traditional Japanese diet (MJDD) and the DPP-4 inhibitor alogliptin in patients with early-stage type 2 diabetes mellitus (T2DM). In this prospective observational study, drug-naive patients received MJDD (n=58) or alogliptin (n=52) monotherapy for 3 months. Changes ({Delta}) in serum UA were analyzed in relation to glycemic control, insulin resistance, adipose tissue insulin resistance (adipo-IR), and beta-cell function. Both interventions significantly reduced fasting blood glucose and HbA1c while paradoxically increasing serum UA and HOMA-B. Baseline UA was the primary determinant of {Delta}UA in both cohorts. MJDD significantly reduced body mass index, insulin, free fatty acids, HOMA-R, and adipo-IR, with effects most pronounced in subjects with baseline BMI >25. In contrast, alogliptin selectively reduced adipo-IR in leaner subjects (BMI <25). Across both treatments, {Delta}UA correlated positively with {Delta}HOMA-B and inversely with {Delta}HbA1c. Notably, during MJDD, {Delta}UA showed a paradoxical negative correlation with {Delta}BMI and {Delta}FBG, and a positive correlation with {Delta}FFA. Patients exhibiting the greatest UA increases demonstrated the most marked improvements in beta-cell function and, with MJDD, the greatest weight loss. These findings indicate that MJDD and alogliptin exert distinct metabolic effects in early T2DM, yet both link rising UA to enhanced beta-cell function, suggesting that UA may serve as a dynamic pharmacometabolic biomarker reflecting therapy-specific metabolic adaptation rather than metabolic deterioration.

Obesity-driven type 2 diabetes (T2D) is characterized by pathological alterations in visceral white adipose tissue (vWAT). While microRNAs (miRNAs) are key post-transcriptional regulators, comprehensive human vWAT profiling across metabolic states remains limited. This study characterized vWAT miRNA expression in lean, obese, and obese+T2D individuals to identify regulatory networks associated with metabolic failure. Deep miRNA sequencing was performed on vWAT samples from a discovery cohort, followed by validation via qPCR in an independent replication cohort. Differentially expressed miRNAs across the three groups were bioinformatically integrated with matched mRNA transcriptomic data to construct functional regulatory modules and identify enriched pathways underlying metabolic impairment. Several miRNAs exhibited robust and reproducible differential expression between obesity and obesity with T2D. Integrated miRNA-mRNA analyses revealed coherent regulatory modules involving inflammation, lipid metabolism, insulin signaling, and iron homeostasis. Specifically, miR-141-3p, miR-200b-3p, miR-15b-3p, miR-12136, and miR-585-3p showed consistent differential expression. Notably, miR-141-3p and miR-200b-3p were markedly upregulated and inversely associated with metabolic stress-related genes, including TF and FBXO32. Several miRNAs correlated with clinical markers of metabolic dysfunction, supporting their biomarker potential. By comparing lean, obese, and diabetic populations, this study provides a comprehensive characterization of the vWAT miRNA landscape and identifies specific miRNA-mRNA regulatory circuits that orchestrate the transition from healthy adiposity to pathological adipose tissue dysfunction. These findings pinpoint novel molecular drivers of type 2 diabetes progression and offer potential targets for therapeutic intervention in metabolic endocrine disorders.

ObjectiveHbA1c thresholds used to define dysglycemia in autoantibody-positive individuals at risk for type 1 diabetes do not account for age-related increases in HbA1c and may overestimate progression risk in adults. We evaluated whether age-adjusted HbA1c or a higher HbA1c threshold improves risk stratification across age groups. Research Design and MethodsWe analyzed 5,024 autoantibody-positive relatives (3,720 children and 1,304 adults) participating in the TrialNet Pathway to Prevention study. Age-related HbA1c effects were modelled using 6,273 adults from the population-based Exeter 10,000 cohort. Progression risk was compared using the standard dysglycemia threshold (HbA1c [&ge;] 5.7% [39 mmol/mol]), age-adjusted HbA1c, and an alternative threshold of HbA1c [&ge;]6.0% (42 mmol/mol). ResultsUsing HbA1c [&ge;] 5.7%, children had higher 1-year progression risk than adults among single autoantibody-positive participants (38% [95% CI 28, 47] vs. 13% [7.2, 19]) and multiple autoantibody-positive participants (55% [49, 60] vs. 38% [27, 47]; both p<0.001). Age adjustment reduced these differences; progression risk was similar among single autoantibody-positive participants (38% [28, 47] vs. 27% [13, 39]; p=0.32), with attenuated differences among multiple autoantibody-positive participants. An HbA1c threshold [&ge;]6.0% yielded comparable progression risk between adults and children across autoantibody subgroups. In post hoc analyses, adults aged <30 years had progression risk similar to children (p=0.1). ConclusionsAge-related variation in HbA1c influences dysglycemia classification in adults at risk for type 1 diabetes. Age-adjusted HbA1c or a higher HbA1c threshold ([&ge;]6.0% [42 mmol/mol]) in adults [&ge;]30 years identifies individuals with progression risk comparable to children and may improve age-specific risk stratification in prevention seungs.

Identifying individuals at risk of early onset type 1 diabetes (diagnosed <2 years) would be highly beneficial in reducing risk of severe diabetic ketoacidosis (DKA) for those with extreme autoimmunity. We aimed to investigate whether genetic variation contributes to heterogeneity in age of type 1 diabetes onset, focusing on those diagnosed <2 years and ages previously defined by histological differences. We carried out association testing on 6773 individuals with type 1 diabetes and tested for heterogeneity in Human Leukocyte Antigen (HLA) variants across stratified age groups (594 diagnosed <2 years, 2241 diagnosed 2-7 years, 3094 diagnosed 7-13 years, 844 diagnosed 13+ years). We used a 67 SNP type 1 diabetes genetic risk score (T1D-GRS) to quantify aggregated genetic risk and assessed its utility in screening for type 1 diabetes <2 years. We observed higher T1D-GRSs as age of onset decreased in type 1 diabetes and found that DR3-DQ2 homozygosity was most strongly associated with <2 years onset (log-OR=4.27). The T1D-GRS showed high discriminative ability for <2 years onset type 1 diabetes onset (AUC=0.94) and correctly identified 88% of type 1 diabetes cases at the 85th population centile. We have shown higher genetic risk for very early onset T1D and suggest T1D-GRSs in newborn screening is likely to be particularly sensitive to those with younger type 1 diabetes onset.

Diabetes mellitus (DM) and obesity frequently coexist. Both are associated with adipose dysfunction, yet the contribution of DM remains uncertain. Using bulk transcriptomics of subcutaneous and visceral adipose tissue (SAT and VAT, respectively), we show that DM is associated with shared and distinct patterns of differential gene expression in these depots. Gene ontology analysis of hits across depots highlighted extracellular matrix, inflammatory pathways, metabolism, axon guidance and endoplasmic reticulum stress. Histology revealed larger SAT adipocytes in people with DM, but only in the overweight category. Body mass index (BMI)-stratified transcriptomic analyses of SAT identified DM-associated hits present only in the overweight group. These were validated in plasma protein form using UK Biobank, informing our development of an adipose risk score that predicted incident DM in overweight people beyond a clinical risk score. Hence, molecular signatures of diabetic SAT can define high-risk adiposity, which may aid the targeting of clinical interventions.

The melanocortin 4 receptor (MC4R) plays a critical role in the central control of energy homeostasis and its disruption causes severe early onset obesity. The MC4R agonist Imcivree has been approved for the treatment of certain genetic obesity syndromes. Here we demonstrate that the membrane-spanning protein Attractin-like protein 1 (ATRNL1) directly interacts with MC4R to amplify its signaling in cells and that expression of ATRNL1 potentiates the activation of MC4R neurons by MC4R agonists in mice. Disruption of ATRNL1 in the PVN of the hypothalamus causes increased food intake and obesity, which cannot be rescued by MC4R agonist treatment. In exomes from 927 children with severe early-onset obesity, we identified 21 rare ATRNL1 variants. Eleven of 17 variants studied in cells impaired ATRNL1-mediated regulation of MC4R signaling, including variants ultra-rare or absent from UK Biobank and other populations. Cumulatively, these findings establish ATRNL1 as an important regulator of mammalian energy homeostasis.

AimsThe distribution of abdominal adipose depots and their mechanistic links to type 2 diabetes remain incompletely understood. This study elucidated the relationship between type 2 diabetes presence and quantitative abdominal imaging traits, including hepatic steatosis, liver and spleen size, and adipose distribution, using unenhanced computed tomography (CT) scans from a large-scale, racially diverse, disease-focused medical biobank. Materials and MethodsDeep learning algorithms were applied to abdominal CT scans to automatically quantify image-derived phenotypes, including spleen-hepatic attenuation difference (SHAD) for hepatic steatosis, liver and spleen volumes (LV and SV, respectively), visceral and subcutaneous adipose tissue (VAT and SAT, respectively), and visceral-to-subcutaneous fat ratio (VSR). ResultsDiabetic individuals demonstrated a greater degree of hepatic steatosis and central adiposity than those without diabetes. Liver attenuation was lower (47.6 vs. 52.4 Hounsfield units (HU); lower values indicate greater steatosis), SHAD was higher (-5.41 vs. -8.41 HU; more positive values indicate greater steatosis), and steatosis prevalence increased (38.4% vs. 21.4%) (all p<2.2x10-{superscript 1}). VSR was also elevated (0.64 vs. 0.54, p=5.86x10-{superscript 1}3). These trends remained significant after stratification by sex. Multivariate analyses revealed independent associations of diabetes with SHAD (OR 1.04), LV (OR 1.59), SV (OR 3.95), VAT (OR 1.23), SAT (OR 1.05), and VSR (OR 2.27), after adjusting for age, sex, race, and BMI. ConclusionsHepatic steatosis, hepatomegaly, and visceral adiposity on CT imaging are predictive of type 2 diabetes presence. Notably, VSR showed a stronger association with diabetes than BMI, underscoring how body-fat distribution, rather than overall adiposity, more accurately reflects metabolic disease risk.