Citations

Abstract Background The associations between different types of diabetes, characterized by distinct pathophysiology and genetic architecture, and pancreatic ductal adenocarcinoma (PDAC) risk are not understood. Methods We investigated associations of genetic susceptibility to type 2 diabetes (T2D), 8 T2D mechanistic clusters, type 1 diabetes (T1D), and maturity-onset diabetes of the young (MODY) with PDAC risk. We used genome-wide association study (GWAS) summary-level statistics for T2D (242 283 cases, 1 569 734 controls), T1D (18 942 cases, 501 638 controls), and PDAC (10 244 cases and 360 535 controls) in individuals of European ancestry. Results Two-sample Mendelian randomization (MR) using the Robust Adjusted Profile Score (MR-RAPS) method indicated that genetically predicted T2D was associated with PDAC risk (OR = 1.10; 95% CI = 1.05 to 1.15), particularly the T2D obesity (OR = 1.28; 95% CI = 1.15 to 1.42) and lipodystrophy (OR = 1.25; 95% CI = 1.03 to 1.51) clusters. No association was observed for T1D with PDAC risk (OR = 1.01; 95% CI = 0.99 to 1.02). Pathway/gene-set analysis using the summary-based Adaptive Rank Truncated Product (sARTP) method revealed a significant association between the MODY gene-sets and PDAC risk (P = 1.5 × 10−8), which remained after excluding 20 known PDAC GWAS loci (P = 7.6 × 10−4). HNF1A, FOXA3, and HNF4A were the top contributing genes after excluding the previously identified GWAS loci regions. Conclusions Our results from this genetic association study support that T2D, particularly the obesity and lipodystrophy mechanistic clusters, and MODY genomic susceptibility regions play a role in the etiology of PDAC.

Abstract Repetitive head impacts are common in contact and collision sports and are linked to structural brain changes and an elevated risk of neurodegenerative diseases such as Chronic Traumatic Encephalopathy. Identifying early in vivo structural markers remains challenging. Although diagnosis currently requires post-mortem confirmation, clinical symptoms, including cognitive impairment and behavioural changes, are reflected in the diagnosis of Traumatic Encephalopathy Syndrome. These symptoms align with dysfunction in key brain regions—amygdala, hippocampus and thalamus—which support memory, emotion and behaviour and commonly show tau pathology in Chronic Traumatic Encephalopathy. This study uses shape analysis to examine structural differences in these regions between former American football players and unexposed asymptomatic controls and evaluates the influence of age, head impact exposure and clinical diagnosis on brain structure. We analyzed brain morphology in former American football players (n = 163) and unexposed, asymptomatic controls (n = 53). Structural segmentation was performed with FreeSurfer 7.1, and the shape analysis pipeline was used to generate subregional reconstructions. Vertex-level morphometry, based on the logarithm of the Jacobian determinant and radial distance, quantified local surface area dilation and thickness. Group differences were examined with covariate-adjusted linear regression models contrasting football players and controls, as well as participants with and without a Traumatic Encephalopathy Syndrome diagnosis. Partial correlations examined the influence of age, age of first football exposure and cumulative head impact index metrics, including frequency, linear acceleration and rotational force. Models were adjusted accordingly for age, body mass index, education, race, imaging site, apolipoprotein ϵ4 status and total intracranial volume. Former football players exhibited bilateral surface area contractions in the hippocampus and amygdala, along with reduced amygdala thickness, compared to controls. Older age was associated with widespread surface contractions and thinning across all regions, except for preserved thickness in the left hippocampus. An earlier age of first exposure to football correlated with surface contractions in the thalamus and left hippocampus. Greater cumulative linear acceleration was linked to bilateral hippocampal surface contractions and reduced thickness in the left thalamus, while greater rotational force exposure was associated with hippocampal thinning. No significant structural differences were found between players with and without a diagnosis of Traumatic Encephalopathy Syndrome. These findings extend volume-based research by revealing localized alterations in surface area dilation and thickness and emphasize the roles of age and repetitive head impact exposure in long-term brain changes.

Background: Breast cancer polygenic risk scores (PRS) and traditional risk models (e.g., the Gail model [Gail]) are known to contribute largely independent information, but it is unclear how the overlap varies by ancestry, age, disease type (invasive breast cancer, DCIS), and risk threshold. Methods: In a retrospective case–control study, we evaluated risk prediction performance in 180,398 women (161,849 of European ancestry; 18,549 of Asian ancestry). Odds ratios (ORs) from logistic regression models and the area under the receiver operating characteristic curve (AUC) were estimated. Results: PRS for invasive disease showed a stronger association in younger (<50 years) women (OR = 2.51, AUC = 0.622) than in women ≥ 50 years (OR = 2.06, AUC = 0.653) of European ancestry. PRS performance in Asians was lower (OR range = 1.62–1.64, AUC = 0.551–0.600). Gail performance was modest across groups and poor in younger Asian women (OR = 0.94–0.99, AUC = 0.523–0.533). Age interactions were observed for both PRS (p < 0.001) and Gail (p < 0.001) in Europeans, whereas in Asians, age interaction was observed only for Gail (invasive: p < 0.001; DCIS: p = 0.002). PRS identified more high-risk individuals than Gail in Asian populations, especially ≥50 years, while Gail identified more in Europeans. Overlap between PRS, Gail, and family history was limited at higher thresholds. Calibration analysis, comparing empirical and model-based ROC curves, showed divergence for both PRS and Gail (p < 0.001), which indicates miscalibration. In Europeans, family history and prior biopsies drove Gail discrimination. In younger Asians, age at first live birth was influential. Conclusions: PRS adds value to risk stratification beyond traditional tools, especially in younger women and Asian ancestry populations.

Abstract Purpose: AXL, a receptor tyrosine kinase related to oncogenic processes, is aberrantly expressed in various cancers and associated with treatment resistance. Enapotamab vedotin (EnaV), a novel anti-AXL human IgG1 and monomethyl auristatin E antibody–drug conjugate, demonstrated antitumor activity in preclinical models, including non–small cell lung cancer (NSCLC). This phase 1/2 study assessed the safety and preliminary efficacy of EnaV in solid tumors. Patients and Methods: This study comprised dose-escalation and dose-expansion phases; both phases investigated EnaV once every 3 weeks (Q3W) and EnaV on days 1, 8, and 15 of a 28-day cycle (3Q4W). Primary objectives determined the maximum tolerated dose (dose escalation) and safety (dose expansion). Pharmacokinetic profile, antitumor activity, and AXL expression were also assessed. Results: During dose escalation, 32 patients received EnaV Q3W; 15 received EnaV 3Q4W. The maximum tolerated dose and recommended phase 2 dose were 2.2 mg/kg in Q3W and 1.0 mg/kg in 3Q4W schedules. In dose expansion, 189 patients received EnaV Q3W; 70 received EnaV 3Q4W. Common adverse events in dose expansion included fatigue, constipation, nausea, decreased appetite, and diarrhea. Overall response rates ranged from 4.5% to 12.5% with Q3W dose schedule and from 9.1% to 11.5% with 3Q4W dose schedule. Disease control rates for NSCLC cohorts were 40.9% to 50.0%. NSCLC subset analysis demonstrated correlation between radiomics signature and disease control. The relationship between clinical activity and AXL expression was not apparent. Conclusions: EnaV had an acceptable safety profile; however, because the evaluation of antitumor activity did not show clinically meaningful responses, clinical development of EnaV was discontinued. Significance: EnaV, an anti-AXL human IgG1 and monomethyl auristatin E antibody–drug conjugate, showed single-agent antitumor activity in preclinical models. This phase 1/2 study of EnaV demonstrated a manageable safety profile and antitumor activity in selected tumor types. Further studies exploring alternative targeting modalities, patient selection, and/or combinations are needed.

INTRODUCTION: Indomethacin is often used experimentally to induce intestinal hyperpermeability, enabling evaluation of interventions targeting barrier function. METHODS: We conducted a randomized, double-blind, placebo-controlled study (NCT05538247) in healthy volunteers to assess whether a supplement could mitigate indomethacin-induced hyperpermeability. Participants received 150 mg/d of indomethacin for 6 days, either before or during placebo/supplement administration. Permeability was measured using 13 C-mannitol and lactulose urinary excretion. RESULTS: Contrary to expectations, indomethacin failed to increase 13 C-mannitol excretion in either group. No meaningful elevations in serum (zonulin, claudins) or fecal (calprotectin) biomarkers were observed. DISCUSSION: Our findings suggest that the expected increase in intestinal permeability after indomethacin administration may not be consistently observed in healthy volunteers. These results highlight the need to carefully consider the reproducibility and sensitivity of this model in future clinical studies aiming to investigate gut barrier function.

Treatment-induced ovarian function loss is a significant concern for many young patients with breast cancer. Accurately predicting this risk is crucial for counselling young patients and informing their fertility-related decision-making. However, current risk prediction models for treatment-related ovarian function loss have limitations. To provide a broader representation of patient cohorts and improve feature selection, we combined retrospective data from six datasets within the FoRECAsT (Infertility after Cancer Predictor) databank, including 2679 pre-menopausal women diagnosed with breast cancer. This combined dataset presented notable missingness, prompting us to employ cross imputation using the k-nearest neighbours (KNN) machine learning (ML) algorithm. Employing Lasso regression, we developed an ML model to forecast the risk of treatment-related amenorrhea as a surrogate marker of ovarian function loss at 12 months after starting chemotherapy. Our model identified 20 variables significantly associated with risk of developing amenorrhea. Internal validation resulted in an area under the receiver operating characteristic curve (AUC) of 0.820 (95% CI: 0.817–0.823), while external validation with another dataset demonstrated an AUC of 0.743 (95% CI: 0.666–0.818). A cutoff of 0.20 was chosen to achieve higher sensitivity in validation, as false negatives—patients incorrectly classified as likely to regain menses—could miss timely opportunities for fertility preservation if desired. At this threshold, internal validation yielded sensitivity and precision rates of 91.3% and 61.7%, respectively, while external validation showed 92.9% and 60.0%. Leveraging ML methodologies, we not only devised a model for personalised risk prediction of amenorrhea, demonstrating substantial enhancements over existing models but also showcased a robust framework for maximally harnessing available data sources.

Abstract Disclosure: A. Prete: HRA Pharmaceuticals, Lundbeck, Diurnal. L. Adbi: None. J.T. Bain: None. F. Shaheen: None. O. Suntornlohanakul: None. E. Deflorenne: None. A. Blanchard: None. M. Nestola: None. C. Pamporaki: None. I. Tizianel: None. E. Nowak: None. J. Bertherat: None. D.A. Vassiliadi: None. I. Bancos: None. C.M. Dennedy: None. D. Kastelan: None. M. Fassnacht: None. P. Mulatero: None. U. Ambroziak: None. A. Tabarin: None. M. Quinkler: None. S. Puglisi: None. J. Deinum: None. G.Å. Ueland: None. L. Lenzini: None. F. Beuschlein: None. M. Reincke: None. F. Ceccato: None. G. Eisenhofer: None. S.M. Corsello: None. L. Amar: None. M. Zennaro: None. N. Karavitaki: None. A.E. Taylor: None. W. Arlt: None. Introduction: Twenty-four-hour urinary free cortisol is used to diagnose Cushing’s syndrome (CS); amongst its limitations is failure to differentiate ACTH-dependent CS (AD-CS) from ACTH-independent CS (AI-CS). We tested the performance of urine steroid metabolomics (USM), the computational analysis of 24-hour urine steroid metabolome data by machine learning, for the diagnosis and differential diagnosis of CS. Given the physiological diurnal rhythm of cortisol secretion and its loss in CS, we also hypothesised that the difference in glucocorticoid excretion between CS and controls should be higher during nighttime, thereby facilitating more sensitive detection of CS. Methods: 264 subjects completed a 24-hour urine collection (40 AD-CS, 103 AI-CS due to adrenocortical adenoma or hyperplasia, 121 healthy subjects). A subset of 52 individuals (13 CS, 39 healthy) provided a nighttime urine collection and a daytime urine collection. Mass spectrometry-based multi-steroid profiling was used to quantify the urinary excretion of 27 steroid metabolites. Data were analysed by generalised matrix learning vector quantisation (a prototype-based supervised machine learning approach), multiple linear regression adjusted for age, sex, and BMI, and multiple logistic regression adjusted for age, sex, and BMI. Results: Twenty-four-hour USM demonstrated very high accuracy in differentiating CS from healthy individuals (AUC-ROC 0.99, 95%CI 0.99-0.99), reflected by higher urinary excretion of glucocorticoid and glucocorticoid precursor metabolites in CS. USM yielded high accuracy in differentiating AD-CS from AI-CS (AUC-ROC 0.91, 95%CI 0.89-0.94), with androgen metabolites being the most discriminatory. We observed significant sex differences in steroid excretion in both healthy individuals and those with CS. Women exhibited markedly lower excretion of both glucocorticoids and mineralocorticoids compared to men: average glucocorticoid excretion was reduced by 43% in healthy women and 30% in CS women, while average mineralocorticoid excretion was 29% lower in healthy women and 51% lower in CS women (results adjusted for age and BMI). Timed steroid excretion in healthy individuals reflected the diurnal pattern of adrenal steroid secretion, with lower nighttime than daytime excretion of glucocorticoid metabolites. Nighttime glucocorticoid metabolite excretion (AUC-ROC 1.00, 95%CI 0.99-1.00) performed better than daytime (AUC-ROC 0.91, 95%CI 0.77-1.00) and 24-hour excretion (AUC-ROC 0.94, 95%CI 0.86-1.00) in separating CS cases from healthy individuals. Conclusions: USM is a non-invasive, one-step candidate test for the accurate diagnosis and differential diagnosis of CS. Timed nighttime urine collection leverages cortisol circadian rhythmicity and improves the diagnostic accuracy of the current reference standard 24-hour collection. Presentation: Sunday, July 13, 2025

The COVID-19 pandemic caused unprecedented disruption of social networks and negatively impacted social determinants of health (SDoH, e.g., economic stability, mental health, health care access) among African Americans. The FAITH! (Fostering African-American Improvement in Total Health!) Program, an academic-community partnership with African American churches, pivoted to pandemic-related impacts on health behaviors of African Americans. This exploratory, cross-sectional study examined associations between multilevel factors influencing difficulty maintaining a healthy lifestyle during the early pandemic phase, including mental/emotional health and COVID-19 hardships (e.g., job/food/housing insecurity, paying utilities). An online survey was distributed via FAITH!-affiliated churches and social media. Logistic regression (odds ratios [ORs], adjusted for age/gender) and associated 95% confidence intervals [CIs]) examined associations between difficulty maintaining a healthy lifestyle and multilevel factors. Greater than half of respondents reported difficulty maintaining a healthy lifestyle (N = 169, 54% [91/169]). Adjusted odds of having difficulty maintaining a healthy lifestyle were greater for those reporting mental/emotional health issues (high-stress OR 4.0; 95% CI [1.9,8.9], p < .001); occasional symptoms of depression (OR 3.7; 95% CI [01.9,7.7]; p < .001); anger (OR 2.5; 95% CI [1.2,5.4]; p = .044), and anxiety (OR 2.8; 95% CI [1.4,6.0]; p = .008)). COVID-19 hardships of job insecurity (OR 1.4.; 95% CI [0.7, 2,8]; p = .015), difficulty paying rent (OR 4.4; 95% CI [2.1,9.9]; p < .001) or difficulty paying for food/utilities (OR 5.4; 95% CI [2.6,11.7]; p < .001) were associated with difficulty maintaining a healthy lifestyle. Our study revealed the negative impact of mental/emotional health and COVID-19 hardships on maintaining a healthy lifestyle among African Americans. This could inform SDoH-focused lifestyle interventions during future public health crises.

Abstract Women make up 51% of the world's population, and the global population of postmenopausal women is growing. About 25% of these women experience debilitating menopausal symptoms. Since it is important that all health care professionals have a fundamental knowledge of managing women presenting with symptoms related to the menopause, this European Society of Endocrinology Clinical Practice Guideline was developed. It provides guidance on evaluation and optimal clinical management of women who go through the menopause in middle age, those with Premature Ovarian Insufficiency (POI), Early Menopause and those for whom hormones are not appropriate, including women with, or at high risk of, breast cancer. This guideline discusses the benefits and risks of hormone therapy administration as well as summarizing other treatments for menopausal symptoms. Further, the contentious issue of the impact of menopausal hormone therapy in the prevention of chronic disease is considered.

Background: Cardiac fibrosis is a central pathological process that leads to worse outcomes in various cardiomyopathies. Recent evidence shows that CDCP1 (CUB domain-containing protein 1) modulates myocardial recovery by attenuating human cardiac fibroblast (HCF) proliferation. This study investigates the hypothesis that selective targeting of the CDCP1 cleavage domain can mitigate fibroblast proliferation, thereby offering a novel therapeutic approach to reducing cardiac fibrosis. Methods: A high-throughput in silico screening was performed using the Enamine compound library, focusing on structural regions that include the cleavage and adjacent sites of CDCP1 . A total of 147 candidate compounds were prioritized based on docking scores and binding stability profiles. Selected compounds were subsequently evaluated in vitro using HCF cultures seeded at 3,000 cells/well in 96-well plates. Each compound was administered at 10 μM concentration, and cell proliferation and viability were assessed by time-lapse imaging in the Incucyte® system at 24 and 96 hours. All experiments were done in triplicate with appropriate DMSO vehicle controls. Results: Compound C3 significantly reduced HCF proliferation (Fig B) to 27.3±2.4% relative to DMSO controls (99.9±0.5%, P <0.001) at 96 hours. Detailed structural modeling indicated that C3 binds to the CDCP1 cleavage site (Fig C) with a favorable Glide XP docking score of -7.66 kcal/mol. The interaction is stabilized by hydrogen bonds with Lys365 and Cys374 (Fig D), and supplementary hydrophobic interactions between aromatic rings and aliphatic groups, which contribute to a strong inhibitory effect. Conclusion: Targeting the CDCP1 cleavage domain with compound C3 effectively diminishes HCF proliferation in vitro. Therefore, these results substantiate the therapeutic potential of CDCP1 inhibition in cardiac fibrosis. Ongoing in vivo studies will explore the translational relevance of these findings.