Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as non-alcoholic fatty liver disease, is closely associated with atherosclerotic cardiovascular risk. However, lipid metabolism-related mechanisms shared by fatty liver and carotid atherosclerosis remain incompletely defined. Bulk transcriptomic datasets were used to identify shared lipid metabolism-related differentially expressed genes between MASLD-spectrum liver samples and carotid plaques. Lipid metabolism-related genes were collected from GeneCards, GSEA and Harmonizome. LASSO and SVM-RFE were applied for candidate gene selection, followed by fixed-model assessment in additional liver cohorts. Carotid plaque scRNA-seq datasets were integrated for cell localization, subclustering and CellChat analysis. Liver-side snRNA-seq was used for hepatic cellular localization. An independent ultrasound cohort of 122 participants was analyzed separately to assess phenotype-level associations between fatty liver severity and carotid atherosclerotic burden. We identified 44 directionally consistent shared lipid metabolism-related genes, including 21 commonly upregulated and 23 commonly downregulated genes. Enrichment analysis indicated immune activation, inflammation, extracellular matrix organization and vascular remodeling. FILIP1L and TNFSF10 were selected as machine learning consensus candidate genes. Plaque signals localized to macrophages, smooth muscle, fibroblast and endothelial populations. FILIP1L was enriched in contractile smooth muscle cells and myofibroblast-like cells, whereas TNFSF10 was mainly enriched in endothelial states. Functional analyses indicated macrophage immune activation, smooth-muscle contraction and myofibroblast matrix remodeling. CellChat predicted CXCL8–ACKR1, SPP1/FN1–integrin, APP–CD74 and MIF-related interactions. Liver signals localized to hepatocytes, cholangiocytes and endothelial cells. ATI-mean and Hamaguchi grade were associated with carotid intima-media thickness and plaque total score. The original two-gene liver model had limited discrimination in GSE48452 (AUC 0.569). In the additional microarray cohort E-MEXP-3291, TNFSF10 upregulation was reproduced, but FILIP1L changed in the opposite direction. The primary combined-disease AUC was 0.579. These findings indicate cohort- and case-definition-dependent expression and performance rather than a validated liver diagnostic signature. This study reports shared lipid metabolism and immune remodeling signatures in MASLD and carotid atherosclerosis. FILIP1L and TNFSF10 emerged as exploratory cross-tissue candidate genes with distinct cellular localization patterns. The ultrasound findings provide phenotype-level support for an association between fatty liver severity and carotid atherosclerotic burden. Overall, the study is hypothesis-generating and requires confirmation in larger independent molecular and clinical cohorts.
Type B aortic dissection (TBAD) represents a life-threatening condition with an increasing incidence. Although elevated body mass index (BMI) is associated with both TBAD incidence and mortality, the underlying mechanisms remain unclear. Periaortic adipose tissue (PAAT) increases with BMI, and the PAAT of AD shows marked inflammatory infiltration, suggesting PAAT-driven inflammation may contribute to the development of AD. However, no direct evidence links BMI and PAAT to AD. To further elucidate the obesity-inflammation-AD relationship, we aim to quantify the contributions of BMI, PAAT, and their derived indices to the risk of TBAD. This retrospective multicenter study (June-November 2025) quantified PAAT from the descending thoracic aorta distal to the left subclavian artery to the aortic bifurcation with CT angiography (CTA). Missing data were handled using Multivariate Imputation by Chained Equations (MICE). Logistic regression analyses were performed to identify TBAD risk factors. Based on the Boruta algorithm and ROC curve analysis, the variable importance for TBAD risk was assessed. Bootstrap resampling was employed for internal validation. The dose–response relationship between BMI–Volume-derived metric (BMV) and TBAD risk was further characterized by quartile stratification and restricted cubic spline (RCS). This study enrolled 376 consecutive participants. After adjusting for potential confounders, male, smoking, diabetes mellitus (DM), TC/HDLC, ApoE, PAAT area(Area), PAAT volume/length of aortic centerline (V/L), PAAT fat attenuation index (FAI), and BMV were identified as independent predictors of AD. FAI was the strongest TBAD predictor with the highest Z-score. Compared to TC/HDLC (AUC 0.572, 95
The prognosis of a small left ventricle (LV) in patients with coronary artery disease (CAD), as well as its inherent correlation with the occurrence of cardiovascular events, remains not fully investigated. To evaluate the association between a small LV and the risk of cardiovascular events in patients with coronary artery disease. We conducted a retrospective analysis of data from the Prospective Registry of the Current Status of Care for Patients with Coronary Artery Disease database, all participants with full data of conventional transthoracic echocardiography between Jan 2022 and Sep 2024 were collected. According to the American Society of Echocardiography guidelines, participants were categorized by left ventricular end-diastolic diameter (LVEDD) as having a small, normal (42.0–58.4 mm in men and 37.8–52.2 mm in women), or large LV. Cox proportional hazards models were used to assess the association between LV size and the 1-year major adverse cardiovascular events (MACE), defined as all-cause death, myocardial infarction, stroke or heart failure. Among 38,881 participants, 2,550 (6.6
Cardiovascular disease (CVD) remains a major global health challenge. The cholesterol–high-density lipoprotein–glucose (CHG) index and glucose-lipid metabolic index (GLMI) have been associated with cardiovascular outcomes, but studies on their associations with incident heart disease in Chinese populations remain scarce. This study compared their associations with incident heart disease and assessed their standalone discriminative ability in middle-aged and older Chinese adults. This cohort study included 5,549 adults aged ≥ 45 years from the China Health and Retirement Longitudinal Study (CHARLS). Baseline data (2011) were used to calculate the CHG index and GLMI; incident heart disease was ascertained over 9 years. Cox proportional hazards models with sequential adjustment, restricted cubic splines (RCS), Kaplan–Meier (KM) curves, time-dependent receiver operating characteristic (ROC) analyses, and subgroup analyses were used to examine associations and describe standalone discrimination. During 9 years of follow-up, 1,404 (25.3
Severe heart failure (HF; Killip or NYHA class III–IV) carries high in-hospital mortality, but the Get With The Guidelines–Heart Failure (GWTG-HF) score omits inflammation, hypoxic injury, and nutritional status, factors linked to prognosis. We tested whether the neutrophil-to-lymphocyte ratio (NLR) and lactate dehydrogenase-to-albumin ratio (LAR) add incremental value beyond NT-proBNP and this score. In a dual-center retrospective cohort (derivation, n = 1596, 223 deaths; external validation, n = 378, 48 deaths), four nested logistic models, GWTG-HF alone or with NLR, LAR, or both, were assessed in derivation for discrimination, reclassification, and calibration; the combined model was bootstrap-validated for optimism and compared with GWTG-HF + NT-proBNP in both cohorts. Independent associations of NLR and LAR were assessed by multivariable logistic regression adjusting for GWTG-HF score, age, sex, log-transformed NT-proBNP, myocardial infarction history, diabetes, and moderate-to-severe chronic kidney disease. Without refitting (intercept recalibrated), discrimination, calibration, and decision-curve analysis, but not reclassification, were re-evaluated externally. LAR and NLR showed higher univariable discrimination than NT-proBNP in this severe-HF cohort (area under the curve [AUC] 0.732 and 0.704 vs. 0.673). Adding both raised derivation AUC from 0.750 to 0.777 (optimism-corrected 0.776; integrated discrimination improvement 0.032, p < 0.001; net reclassification improvement 0.059, p = 0.013), persisting externally (0.670 to 0.710, p = 0.039). The NT-proBNP model matched the gain (AUC 0.765) but lost significance externally (p = 0.914). LAR remained externally significant (p = 0.039); NLR did not (p = 0.085); only the combined model was significant on every metric assessed in both cohorts. NLR was independently associated with mortality (adjusted odds ratio 1.032, p = 0.001); LAR did not retain independent significance (p = 0.066); variance inflation factors were low (1.13–1.16), indicating partial informational overlap rather than collinearity. Adding NLR and LAR to GWTG-HF improved mortality discrimination and, unlike NT-proBNP, this improvement persisted externally, albeit with uncertainty from case-mix differences; the two augmented models were not directly compared with each other.This suggests that markers related to inflammation, tissue injury, and nutritional status may carry prognostic information beyond current tools. Because each marker dominated in a different cohort, combining both, not either alone, provided the most consistent incremental value, supporting their use as a low-cost candidate for risk-stratification.
