Christopher G. Kevil

Background: Contemporary cardiovascular disease (CVD) risk equations may not fully capture cumulative biological aging or long-term exposure burden. DNA methylation (DNAm) biomarkers may capture aging- and exposure-related biology, but their incremental prognostic value beyond clinical risk-factor models like PREVENT remains uncertain. To our knowledge, no prior study has benchmarked DNAm-based biomarkers with PREVENT. Methods: In a population-based cohort study, we analyzed NHANES 1999-2002 participants with DNAm biomarkers and mortality follow-up. We derived a DNAmScore from candidate DNAm biomarkers using elastic-net Cox regression with repeated nested cross-validation. A PREVENT-like clinical model was defined as a Cox model fit in NHANES using PREVENT predictors. Weighted Cox models estimated the association between DNAmScore and mortality after adjustment for PREVENT-like clinical predictors. We then compared the PREVENT-like clinical model, DNAmScore alone, and a combined model (PREVENT-like clinical predictors plus DNAmScore) using cross-fitted C-index, time-dependent AUC, calibration, and Brier score. Results: Our cohort included 2,282 participants; 597 and 937 deaths occurred by 10 and 15 years, respectively. After adjustment for PREVENT-like clinical predictors, the cross-fitted DNAmScore was strongly associated with all-cause mortality (HR per 1-SD increase, 2.43; 95% CI, 1.97–2.99). At 10 years, AUCs were 0.791 for the PREVENT-like model, 0.791 for DNAmScore, and 0.803 for the combined model. At 15 years, corresponding AUCs were 0.825, 0.822, and 0.835. Compared with the PREVENT-like model, the combined model improved AUC by 0.013 (95% CI, 0.006–0.020) at 10 years and 0.010 (95% CI, 0.004–0.015) at 15 years. The combined model had lower Brier scores at all three horizons with similar calibration. DNAmScore remained associated with CVD mortality after clinical adjustment. Conclusions: DNAmScore identified residual biological risk beyond PREVENT-like clinical predictors, with strong independent mortality associations and modest, consistent improvements in cross-fitted prediction performance. These findings support development and external validation of CVD-specific DNAm biomarkers. What Is Known: Contemporary cardiovascular risk models may not fully capture cumulative biological aging and exposure burden. DNA methylation biomarkers are associated with mortality, but their incremental predictive value beyond clinical risk predictors remains uncertain. What the Study Adds: In a nationally representative NHANES cohort, a cross-fitted composite DNAmScore remained strongly associated with mortality after adjustment for PREVENT predictors. Adding DNAmScore produced modest improvements in discrimination and prediction error at 5, 10, and 15 years, and DNAmScore was also associated with cardiovascular mortality in secondary analyses.

The role played by anionic channels in diabetic kidney disease (DKD) is not known. Chloride channel accessory 1 (CLCA1) facilitates the activity of TMEM16A (Anoctamin-1), a Ca ²⁺ -dependent Cl ^– channel. We examined if CLCA1/TMEM16A had a role in DKD. In mice with type 2 diabetes, renal cortical CLCA1 and TMEM16A content was increased. CLCA1 and TMEM16A content was associated with hydrogen sulfide (H ₂ S) deficiency, mTOR complex 1 (mTORC1) activation, albuminuria, and matrix increase. Administering sodium hydrosulfide (NaHS), a source of H ₂ S, mitigated these changes. In proximal tubular epithelial (MCT) cells, high glucose rapidly increased CLCA1 by recruiting the IL-6/STAT3 axis and augmented TMEM16A expression by stimulating its mRNA translation; these changes were abolished by NaHS. Patch clamp experiments showed that high glucose increased Cl ^– current in MCT cells that was ameliorated by NaHS and a TMEM16A chemical inhibitor. siRNA against CLCA1 or TMEM16A and TMEM16A inhibitor abolished high glucose–induced mTORC1 activation and matrix protein increase. Tubular expression of TMEM16A correlated with albuminuria in kidney biopsies from people with type 2 diabetes. We report a pathway for DKD in which H ₂ S deficiency results in kidney injury by the recruitment of the CLCA1/TMEM16A/Cl ^– current system.

The incidence of metabolic dysfunction-associated steatohepatitis (MASH) is on the rise, and with limited pharmacological therapy available, identification of new metabolic targets is urgently needed. Oxalate is a terminal metabolite produced from glyoxylate by hepatic lactate dehydrogenase (LDHA). The liver-specific alanine-glyoxylate aminotransferase (AGXT) detoxifies glyoxylate, preventing oxalate accumulation. Here we show that AGXT is suppressed and LDHA is activated in livers from patients and mice with MASH, leading to oxalate overproduction. In turn, oxalate promotes steatosis in hepatocytes by inhibiting peroxisome proliferator-activated receptor-α (PPARα) transcription and fatty acid β-oxidation and induces monocyte chemotaxis via C–C motif chemokine ligand 2. In male mice with diet-induced MASH, targeting oxalate overproduction through hepatocyte-specific AGXT overexpression or pharmacological inhibition of LDHA potently lowers steatohepatitis and fibrosis by inducing PPARα-driven fatty acid β-oxidation and suppressing monocyte chemotaxis, nuclear factor-κB and transforming growth factor-β targets. These findings highlight hepatic oxalate overproduction as a target for the treatment of MASH.

Heart disease is the leading cause of death worldwide, and cardiac function as measured by ejection fraction (EF) is an important determinant of outcomes, making accurate measurement a critical parameter in PT evaluation. Echocardiograms are commonly used for measuring EF, but human interpretation has limitations in terms of intra- and inter-observer (or reader) variance. Deep learning (DL) has driven a resurgence in machine learning, leading to advancements in medical applications. We introduce the ViViEchoformer DL approach, which uses a video vision transformer to directly regress the left ventricular function (LVEF) from echocardiogram videos. The study used a dataset of 10,030 apical-4-chamber echocardiography videos from patients at Stanford University Hospital. The model accurately captures spatial information and preserves inter-frame relationships by extracting spatiotemporal tokens from video input, allowing for accurate, fully automatic EF predictions that aid human assessment and analysis. The ViViEchoformer’s prediction of ejection fraction has a mean absolute error of 6.14%, a root mean squared error of 8.4%, a mean squared log error of 0.04, and an R ² of 0.55. ViViEchoformer predicted heart failure with reduced ejection fraction (HFrEF) with an area under the curve of 0.83 and a classification accuracy of 87 using a standard threshold of less than 50% ejection fraction. Our video-based method provides precise left ventricular function quantification, offering a reliable alternative to human evaluation and establishing a fundamental basis for echocardiogram interpretation.

Glucocorticoids acting via the glucocorticoid receptors (GR) are key regulators of metabolism and the stress response. However, uncontrolled or excessive GR signaling adversely affects adipose tissue, including endocrine, immune, and metabolic functions. Inflammation of the adipose tissue promotes systemic metabolic dysfunction; however, the molecular mechanisms underlying the role of adipocyte GR in regulating genes associated with adipose tissue inflammation are poorly understood. We performed in vivo studies using adipocyte specific GR knockout mice (Adipo GRKO) in conjunction with in vitro studies to understand the contribution of adipocyte GR in regulating adipose tissue immune homeostasis. Our findings show that adipocyte specific GR signaling regulates adipokines at both mRNA and plasma levels, and immune regulatory (Coch, Pdcd1, Cemip, and Cxcr2) mRNA gene expression, which affects myeloid immune cell presence in white adipose tissue. We found that in adipocytes, GR directly influences Cxcr2. This chemokine receptor promotes immune cell migration, indirectly affecting Pdcd1 and Cemip gene expression in non-adipocyte or stromal cells. Our findings suggest that GR adipocyte signaling suppresses inflammatory signals, maintaining immune homeostasis. We also found that GR signaling in adipose tissue in response to stress is sexually dimorphic. Understanding the molecular relationship between GR signaling and adipose tissue inflammation could help develop potential targets to improve local and systemic inflammation, insulin sensitivity, and metabolic health.

Mental stress is a risk factor for myocardial infarction in women. The central hypothesis of this study is that restraint stress induces sex-specific changes in gene expression in the heart, which leads to an intensified response to ischemia/reperfusion injury due to the development of a pro-oxidative environment in female hearts. We challenged male and female C57BL/6 mice in a restraint stress model to mimic the effects of mental stress. Exposure to restraint stress led to sex differences in the expression of genes involved in cardiac hypertrophy, inflammation, and iron-dependent cell death (ferroptosis). Among those genes, we identified tumor protein p53 and cyclin-dependent kinase inhibitor 1A (p21), which have established controversial roles in ferroptosis. The exacerbated response to I/R injury in restraint-stressed females correlated with downregulation of p53 and nuclear factor erythroid 2–related factor 2 (Nrf2, a master regulator of the antioxidant response system-ARE). S-female hearts also showed increased superoxide levels, lipid peroxidation, and prostaglandin-endoperoxide synthase 2 (Ptgs2) expression (a hallmark of ferroptosis) compared with those of their male counterparts. Our study is the first to test the sex-specific impact of restraint stress on the heart in the setting of I/R and its outcome.

Amyotrophic lateral sclerosis (ALS) is a complex systemic disease that primarily involves motor neuron dysfunction and skeletal muscle atrophy. One commonly used mouse model to study ALS was generated by transgenic expression of a mutant form of human superoxide dismutase 1 (SOD1) gene harboring a single amino acid substitution of glycine to alanine at codon 93 (G93A*SOD1). Although mutant-SOD1 is ubiquitously expressed in G93A*SOD1 mice, a detailed analysis of the skeletal muscle expression pattern of the mutant protein and the resultant muscle pathology were never performed. Using different skeletal muscles isolated from G93A*SOD1 mice, we extensively characterized the pathological sequelae of histological, molecular, ultrastructural, and biochemical alterations. Muscle atrophy in G93A*SOD1 mice was associated with increased and differential expression of mutant-SOD1 across myofibers and increased MuRF1 protein level. In addition, high collagen deposition and myopathic changes sections accompanied the reduced muscle strength in the G93A*SOD1 mice. Furthermore, all the muscles in G93A*SOD1 mice showed altered protein levels associated with different signaling pathways, including inflammation, mitochondrial membrane transport, mitochondrial lipid uptake, and antioxidant enzymes. In addition, the mutant-SOD1 protein was found in the mitochondrial fraction in the muscles from G93A*SOD1 mice, which was accompanied by vacuolized and abnormal mitochondria, altered OXPHOS and PDH complex protein levels, and defects in mitochondrial respiration. Overall, we reported the pathological sequelae observed in the skeletal muscles of G93A*SOD1 mice resulting from the whole-body mutant-SOD1 protein expression.