Objective: Intestinal remnant chylomicrons (CMs) are involved in cardiovascular residual risk and the atherogenic process. Microsomal triglyceride transfer protein (MTTP) catalyzes the assembly of lipids to apolipoprotein B48, generating CMs. Dysbiosis could alter this behavior. This study investigated the chemical composition of CMs and their associations with intestinal MTTP and gut fat depots in a diet-induced dysbiosis animal model. Methods: Male Wistar rats were fed either a standard diet (control, n=10) or a high-fat high-sucrose diet (HFSD, n=10) for 14 weeks. Measurements included serum glucose, lipid-lipoprotein profile, free fatty acids (FFAs), lipopolysaccharide (LPS) and the Firmicutes/ Bacteroidetes (F/B) ratio in stool samples, via real-time quantitative polymerase chain reaction.Lipid content in isolated CMs (ultracentrifugation d <0.95 g/mL) was assessed, and MTTP, cell intestinal fat content (CIF), histology, apoB mRNA and tight junction (TJ) proteins were analyzed, in intestinal tissue. Results: Compared to control, HFSD rats showed higher levels of LPS, triglycerides (TGs), non-high-density lipoprotein cholesterol (HDL-C) levels, TG/HDL-C ratio, FFAs, and the F/B ratio. HFSD CMs showed increased TG and phospholipids. TJ proteins levels were lower in the HFSD group, while histological scores showed no differences. CIF was increased in the HFSD group. No significant differences in apoB mRNA were found. MTTP expression was higher in the HFSD group, and directly correlated with CM-TG and inversely correlated with CIF. Conclusion Our findings imply that gut TG content may constitute an important determinant of the secretion of TG-rich CMs, promoted by MTTP, with increased atherogenic potential.

Dyslipidemia is a major risk factor for cardiovascular disease, and its impact may be exacerbated when accompanied by metabolic dysfunction-associated steatotic liver disease (MASLD). The simultaneous management of these conditions poses multiple challenges for healthcare providers. Insulin resistance has been implicated in the pathogenesis of both dyslipidemia and MASLD, necessitating a holistic approach to managing dyslipidemia, glucose levels, body weight, and MASLD. This review explores the intricate pathophysiological relationship between MASLD and dyslipidemia. It also examines current guidance regarding the use of lipid-lowering agents (including statins, ezetimibe, fibrates, omega-3 polyunsaturated fatty acids, and proprotein convertase subtilisin/kexin type 9 inhibitors) as well as glucose-lowering medications (such as pioglitazone, glucagon-like peptide-1 receptor agonists, and sodium-glucose cotransporter 2 inhibitors) in patients with MASLD, with or without metabolic dysfunction-associated steatohepatitis (MASH), and dyslipidemia. Additionally, the review addresses the potential of emerging drugs to concurrently target both MASLD/MASH and dyslipidemia. Our hope is that a deeper understanding of the mechanisms underlying MASLD and dyslipidemia may assist clinicians in the management of these complex cases.

Objective: Lipoprotein (a) (Lp[a]), which is a highly heritable trait, is associated with coronary artery disease (CAD). However, the insight into whether the association between Lp(a) and CAD differs according to the family history of CAD remains unclear. Methods: We investigated clinical data of 4,512 participants who underwent serum Lp(a) level measurement at Kanazawa University Hospital between 2008 and 2016. The association between Lp(a) and CAD according to CAD family history was investigated through logistic regression analyses. Results: CAD family history and Lp(a) levels were significantly associated with CAD development (odds ratio [OR], 1.32; 95% confidence interval [CI], 1.12–1.52; p<0.001 and OR, 1.13; 95% CI, 1.03–1.23; p<0.001 per 10 mg/dL, respectively). In patients without CAD family history, those with Lp(a) levels ≥30 mg/dL had higher CAD risk than those with Lp(a) levels <30 mg/dL (reference) (OR, 1.33; 95% CI, 1.05–1.61; p<0.001). In patients with CAD family history, those who had Lp(a) levels <30 and ≥30 mg/dL were both highly at risk for CAD (OR, 1.24; 95% CI, 1.04–1.44; p<0.001 and OR, 1.68; 95% CI, 1.34–2.02; p<0.001, respectively). Adding CAD family history and Lp(a) information to other conventional risk factors enhanced CAD risk discrimination (C-statistics: 0.744 [0.704–0.784] to 0.768 [0.730–0.806], and 0.791 [0.751–0.831], respectively; p<0.05 for both). Conclusion Lp(a) level was associated with CAD development regardless of CAD family history status.

Dyslipidemia dramatically increases the risk of cardiovascular diseases, necessitating appropriate treatment techniques. Generative AI (GenAI), an advanced AI technology that can generate diverse content by learning from vast datasets, provides promising new opportunities to address this challenge. GenAI-powered frequently asked questions systems and chatbots offer continuous, personalized support by addressing lifestyle modifications and medication adherence, which is crucial for patients with dyslipidemia. These tools also help to promote health literacy by making information more accessible and reliable.GenAI helps healthcare providers construct clinical case scenarios, training materials, and evaluation tools, which supports professional development and evidence-based practice.Multimodal GenAI technology analyzes food images and nutritional content to deliver personalized dietary recommendations tailored to each patient's condition, improving long-term nutritional management for those with dyslipidemia. Moreover, using GenAI for image generation enhances the visual quality of educational materials for both patients and professionals, allowing healthcare providers to create real-time, customized visual aids. To apply successfully, healthcare providers must develop GenAI-related abilities, such as prompt engineering and critical evaluation of GenAI-generated data.

Epidemiological evidence has shown that diabetes is associated with overt heart failure (HF) and worse clinical outcomes. However, the presence of a distinct primary diabetic cardiomyopathy (DCM) has not been easy to prove because the association between diabetes and HF is confounded by hypertension, obesity, microvascular dysfunction, and autonomic neuropathy. In addition, the molecular mechanisms underlying DCM are not yet fully understood, DCM usually remains asymptomatic in the early stage, and no specific biomarkers have been identified. Nonetheless, several mechanistic associations at the systemic, cardiac, and cellular/molecular levels explain different aspects of myocardial dysfunction, including impaired cardiac relaxation, compliance, and contractility. In this review, we focus on recent clinical and preclinical advances in our understanding of the molecular mechanisms of DCM and the role of anti-hyperglycemic agents in preventing DCM beyond their glucose lowering effect.