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Hyperglycemia in prediabetes is accompanied by increased amino acid (AA) concentrations and impaired suppression of glucagon secretion by glucose. It is unknown whether an abnormal response to AA contributes or hepatic steatosis exacerbates α-cell dysfunction. Therefore, lean participants and participants with obesity (with and without hepatic steatosis) were studied on two occasions in random order using a graded glucose infusion. Saline or an AA mixture was infused. The glucagon secretion rate (GSR) was derived from peripheral glucagon concentrations, and the change in glucose required to reduce GSR by 50% (G50) was calculated for each participant. AAs were measured during the experiment. On both occasions, experimental conditions produced a progressive rise in insulin secretion and an inverse exponential suppression of glucagon. G50 did not differ between groups in response to glucose alone. AA infusion did not change G50 in lean participants. G50 increased during AA infusion in participants with obesity with and without hepatic steatosis, leading us to report these participants as a single group. The relative change in AA concentrations across study days was generally similar between groups. We conclude that despite a normal response to glucose, obesity increases α-cell responses to AA in humans. Article Highlights The aim of this study was to understand the pathogenesis of α-cell dysfunction in prediabetes. The primary hypothesis was that α-cell responsivity to glucose (reduction of the glucagon secretion rate by 50%) is impaired by amino acid (AA) infusion. A secondary hypothesis was that this abnormal response is exacerbated by hepatic steatosis. AA infusion impaired α-cell suppression in response to rising glucose in participants with obesity, but not in lean participants, despite a normal response to glucose alone. This abnormal response was unaffected by the presence or absence of hepatic steatosis. It seems likely that an abnormal α-cell response to AAs precedes an abnormal response to glucose alone.

The advent of high-throughput sequencing technologies has revolutionized cardiovascular genetics, generating vast amounts of data. A major challenge in the genomic era is the efficient and accurate identification of causative genetic variants associated with cardiovascular disease. Artificial intelligence (AI)-driven computational approaches offer a powerful solution by enabling the automation of variant classification, improving consistency and reproducibility, and enhancing predictive accuracy. These methods may guide not only variant classification, variant effect prediction, and clinical prioritization, but also open the door to data-driven precision medicine, enabling more accurate and individualized diagnoses and targeted therapeutic strategies tailored to each patient’s unique genetic and clinical profile. This state-of-the-art review provides a structured overview of AI methodologies applied to cardiovascular genomics, beginning with rule-based expert systems that encode standardized guidelines for consistent variant interpretation. Next, we examine machine learning approaches capable of identifying complex patterns in annotated multimodal clinical and multi-omic datasets. The role of deep learning algorithms is highlighted for their ability to extract features from high-dimensional, unstructured data relevant to cardiovascular disease. In addition, the potential of generative AI is explored, including applications in synthetic data generation, variant impact prediction, and automated summarization of biomedical literature. Despite advances, several challenges remain, including data heterogeneity, the need for explainable AI models to elucidate the decision mechanisms, and the complexity linked to the integration of AI-based tools into clinical workflows. Addressing these issues requires interdisciplinary collaboration among clinicians, geneticists, data scientists, and bioinformaticians to ensure the effective translation of AI-generated insights into clinical practice. This review aims to provide a comprehensive perspective on the evolving role of AI in cardiovascular genomics and its implications for advancing precision medicine.

ABSTRACT Many real‐world patients with advanced biliary tract cancer (BTC) are excluded by TOPAZ‐1 criteria; this study assessed cisplatin and gemcitabine plus durvalumab (CGD) efficacy and safety in these patients. Data from 1358 patients with advanced BTC treated with first‐line CGD across 55 international centers were retrospectively analyzed. Patients were classified as TOPAZ‐1‐in (meeting all inclusion criteria) or TOPAZ‐1‐out (meeting ≥ 1 exclusion criterion). Primary endpoints were overall survival (OS) and progression‐free survival (PFS); secondary endpoints included objective response rate (ORR), disease control rate (DCR), and safety. Furthermore, OS and PFS of the TOPAZ‐1‐out cohort were compared with reconstructed survival data from the phase III trial. 912 (67.1%) patients were classified as TOPAZ‐1‐in , and 446 (32.9%) as TOPAZ‐1‐out . After a median follow‐up of 14.5 months (95% CI: 13.7–36.5), OS was 16.1 months in TOPAZ‐1‐in and 12.5 months in TOPAZ‐1‐out (HR 0.69, 95% CI: 14.6–16.5, p = 0.0001); PFS was 8.2 versus 6.5 months (HR 0.73, 95% CI: 7.1–8.1, p < 0.0001). Median OS in the TOPAZ‐1‐out cohort (12.5 months) was nearly identical to the phase III trial experimental arm (12.9 months; HR 1.15, p = 0.13); for PFS the HR was 1.12 (95% CI 0.93–1.42; p = 0.09). Among TOPAZ‐1‐out patients, active infection, elevated bilirubin, and ECOG PS > 1 were linked to poorer OS, while no detrimental impact emerged for ALT/AST abnormalities, corticosteroid use, renal or hematologic parameters, or prior surgery within 6 months, suggesting treatment effectiveness was broadly maintained across clinical subgroups. Furthermore, TOPAZ‐1‐out patients experienced no significant increase in adverse events compared with the TOPAZ‐1‐in group. Real‐world data suggest CGD may be effective in TOPAZ‐1‐out patients, with no evident increase in toxicity, supporting the potential expanded use of the regimen in clinical practice.

OBJECTIVE Genetic variation in the glucagon-like peptide 1 receptor (GLP1R) has been implicated in type 2 diabetes (T2D) risk and treatment response. We investigated whether GLP1R R131Q, which was previously reported as a T2D-protective variant in genome-wide association studies, alters receptor signaling, β-cell function, and response to glucagon-like peptide 1 receptor agonists (GLP-1RAs). RESEARCH DESIGN AND METHODS Trajectory of β-cell function was evaluated in a 20-year community-based prospective cohort in Korea (n = 6,373), where participants underwent biennial 2-h 75-g oral glucose tolerance tests, and disposition index was used as surrogate marker. Pharmacogenetic response to GLP-1RAs was assessed in a hospital-based T2D cohort in Korea (n = 177). Hyperglycemic clamp studies (n = 17), human islet experiments (n = 21), and in vitro assays were conducted to characterize GLP1R R131Q effects on receptor signaling and islet function. RESULTS GLP1R R131Q was associated with slower decline in disposition index in individuals without T2D, with reductions from baseline of 30% in homozygous carriers, 35% in heterozygotes, and 37% in wild-type individuals. In people with T2D, each allele conferred an additional 0.53% or 5.8 mmol/mol reduction in HbA1c after 6 months of GLP-1RA treatment (P = 5.8 × 10−4). Hyperglycemic clamp and human islet experiments demonstrated allele-dependent enhancement of GLP-1RA–stimulated insulin secretion (P = 0.050 and P = 0.037, respectively). In vitro, GLP1R R131Q increased GLP-1RA–stimulated cAMP production with directional observations consistent with pathway bias. CONCLUSIONS GLP1R R131Q is a gain-of-function variant associated with preservation of β-cell function and enhanced glycemic response to GLP-1RA treatment, supporting further investigation as a candidate pharmacogenetic marker for precision diabetes care.

Importance Elevated low-density lipoprotein cholesterol (LDL-C) is a modifiable risk factor for cardiovascular disease, the leading cause of premature death worldwide. Assessing the LDL-C–related burden is critical for guiding prevention and treatment strategies. Objectives To estimate the global, regional, and national burden of ischemic heart disease and ischemic stroke attributable to elevated LDL-C (relative to 35-54 mg/dL) from 1990 to 2023 and to quantify the contributions of population growth, aging, risk-deleted burden, and exposure changes to burden trends. Design, Setting, and Population This comparative risk assessment, part of the Global Burden of Disease Study 2023, estimated population-level LDL-C exposure and associated health loss in 204 countries and territories. Mean LDL-C levels were estimated using spatiotemporal gaussian process regression based on 806 studies across 161 countries. Relative risks were derived from meta-analyses of 38 randomized clinical trials. Population-attributable fractions for deaths and disability-adjusted life-years (DALYs) were estimated by age and sex for adults aged 25 years or older from 1990 to 2023, with 95% uncertainty intervals. Exposure Population-level LDL-C concentrations. Main Outcomes and Measures Population-attributable fractions, counts, and rates (all ages and age standardized per 100 000) of LDL-C–attributable deaths and DALYs from ischemic heart disease and ischemic stroke, with uncertainty intervals. Results In 2023, elevated LDL-C accounted for 3.6 million deaths (95% uncertainty interval, 2.2-5.4 million; 6.0% of global mortality) and 90.7 million DALYs (95% uncertainty interval, 58.9-123.3 million; 3.2% of DALYs). Although global all-ages rates remained stable, age-standardized death and DALY rates decreased by 45.6% and 39.5%, respectively, since 1990. In 2023, age-standardized LDL-C–attributable DALY rates were highest in Eastern Europe and lowest in high-income Asia-Pacific. One-third of the global LDL-C burden occurred in India and China. Population growth and aging drove the increasing burden, with notable regional disparities in LDL-C exposure and risk-deleted DALY rates shifting toward middle-sociodemographic settings. Conclusions and Relevance Despite declining age-standardized rates, the absolute LDL-C burden has increased since 1990 due to demographic changes and has shifted toward middle-sociodemographic countries. Measurement and surveillance gaps persist. Strengthened prevention, diagnosis, and treatment access strategies are essential to mitigate the health burden of LDL-C.

Abstract Background There is limited data on immune checkpoint inhibitor (ICI) use in patients with non-small cell lung cancer (NSCLC) and known pericardial effusions. Methods This international multi-center observational retrospective study included patients with advanced NSCLC with or without pericardial effusions receiving ICIs. Immune-related adverse events (irAEs) were graded per CTCAE v5.0. Overall survival (OS) and progression-free survival (PFS) were estimated by the Kaplan-Meier method. Cox proportional hazards multivariable models assessed the association between survival outcomes and clinicopathologic variables, and an inverse probability of treatment weighting (IPTW) model compared outcomes between the two groups. Results A total of 1248 patients with advanced NSCLC treated with ICIs across 13 institutions were included. Of these, 85 patients (6.8%) had pre-existing pericardial effusions. Compared to controls, patients with pericardial effusions were younger (median age 63 vs 67 years, P = .007), diagnosed more frequently with PD-L1 positive tumors (96% vs 76%, P &lt; .001), and had a higher median number of baseline metastatic sites (3 vs 1, P &lt; .001). IrAEs were similar between both groups (42% vs 38%), and no cardiac irAEs occurred in patients with pericardial effusions. PFS (median 5.6 vs 4.6 months, P = .3) and OS (median 10.2 vs 14.7 months, P = .50) were not statistically different between patients with pericardial effusions and the controls, respectively. In both multivariable and IPTW models, pericardial effusions were not associated with PFS or OS. Conclusions Among patients with NSCLC and pre-existing pericardial effusions, ICIs demonstrate meaningful clinical benefit similar to those without effusions, with no new cardiac or severe toxicities.

Early-onset colorectal cancer is increasing, making reproductive health an increasingly relevant survivorship issue. While immune checkpoint inhibitors have altered the management of deficient mismatch repair/microsatellite instability-high (dMMR/MSI-H) colorectal cancer, their implications for reproductive-age women remain insufficiently defined. We performed a focused narrative review, structured in line with the SANRA framework, to clarify this specific clinical domain. Immunotherapy may reshape female oncofertility counseling through two distinct mechanisms: direct reproductive uncertainty, including established endocrine toxicities and hypothesized, but currently unproven, direct gonadal effects; and indirect pathway-modifying effects, such as the potential avoidance of pelvic radiotherapy or radical surgery in selected patients with locally advanced dMMR/MSI-H rectal cancer. Anatomical organ preservation should not be automatically equated with functional fertility preservation. The key clinical message is that reproductive counseling should not be restricted to historically gonadotoxic chemotherapy. Instead, early multidisciplinary guidance should explicitly distinguish CRC-specific evidence from extrapolated or theoretical concerns, integrate fertility preservation strategies when clinically feasible, and address pelvic and sexual health, contraception, washout, endocrine follow-up, and future pregnancy planning. Until prospective CRC-specific reproductive data become available, immunotherapy should not be presented as either reproductively neutral or fertility-preserving.

Abstract Background The Global Bipolar Cohort (GBC) was established to identify existing bipolar disorder (BD) cohorts worldwide and foster collaborations focused on descriptive and analytic outcomes relevant to BD. A distributed analytic framework has been implemented to engage multiple sites without the need for central data pooling. This report describes the GBC endeavor and global functional impairment patterns. Cross-cohort comparisons of functional correlates are limited by heterogeneous measures and data-sharing constraints. Large, culturally diverse comparisons are needed to distinguish broadly reproducible correlates from cohort-specific effects. Participating sites completed a 28-item descriptive survey covering diagnostic methods, cognition, genetics, treatment, functioning, and follow-up strategies. We implemented a harmonized local logistic regression model of dichotomized functional outcome and shared summary statistics only. Results We identified 69 cohorts across five continents. Thirty-seven cohorts contributed functional outcome analyses from 17,130 participants. Outcome measures included clinician-rated disability scales and social indicators such as employment and marital status. The proportion classified with poor functioning ranged from 16% to 77% (mean 50%). In 32 of 37 cohorts, the overall regression model significantly explained variance in functioning. Current depressive symptoms were the most robust and reproducible correlate of poor functional outcome: they were assessed in 29 cohorts, significant in 22 (75.8%), ranked among the top three correlates in 22, and were the top-ranked correlates in 19. Associations between depressive burden and poor functioning were observed across clinician-rated disability scales and work or social indicators, and across geographically diverse cohorts. Comorbid substance use disorder and medication-related variables were associated with poorer functioning in subsets of cohorts, whereas sex, ancestry, bipolar subtype, psychosis history, and premorbid IQ showed weak or inconsistent associations. Cognitive measures, available in a minority of regression models, showed modest and non-uniform effects. Conclusions Across heterogeneous international cohorts, current depressive symptom burden emerged as the most consistent correlate of poor functioning in bipolar disorder. These findings replicate earlier multisite work at a larger scale, show that protocol-based distributed analyses can identify reproducible clinical signals without sharing individual-level data, and support prioritizing detection and treatment of depressive symptoms when aiming to improve real-world functioning. Future work should expand longitudinal harmonization and representation of under-studied populations.

Abstract Aims SCN5A-E1784K (c.5350G&gt;A) is the most common variant associated with the long QT (LQTS) and Brugada syndromes (BrS). It can manifest variably as LQTS, BrS, and/or conduction disorders. This presents a challenge for risk stratification. We aimed to describe clinical and ECG characteristics and identify risk markers that associate with arrhythmic events. Methods and results We undertook a retrospective observational multicentre study of a large cohort of 231 subjects with SCN5A-E1784K from Europe, USA, and Japan. Comprehensive demographic and clinical data, including initial presentation ECG and follow-up, were collected. ‘Lethal events’ were defined as sudden death, non-fatal cardiac arrest, and documented sustained VT or VF. ‘Cardiac events’ were defined as arrhythmic syncope plus any lethal events. Clinical characteristics and ECG parameters corrected for age were investigated for association with lethal and/or cardiac events. Fourteen (6%) subjects experienced a lethal event and 45 (19%) a cardiac event. PR interval and QRS duration were associated with lethal and cardiac events. In multivariable models, both PR interval and QRS duration were associated with lethal events, but only QRS duration was associated with cardiac events. Only age-corrected QRS (rQRS) was associated with lethal and cardiac event-free survival from birth after correction for multiple testing. Conclusion Ventricular myocardial conduction appears likely to play a role in the risk of arrhythmic events in patients with SCN5A-E1784K. This provides an important opportunity for the personalization of management and has the potential to guide preventative therapies.