The incidence and prevalence of metabolic syndrome (MetS) and type 2 diabetes mellitus (T2DM) are rising globally. MetS and T2DM are associated with significant morbidity and mortality, which is partly related to liver and cardiovascular disease. Insulin resistance is central to MetS and T2DM pathophysiology, and drives ectopic fat deposition in the liver, also known as metabolic dysfunction-associated steatotic liver disease (MASLD). MetS and T2DM are not only risk factors for developing MASLD but are also independently associated with disease progression to steatohepatitis, cirrhosis, and hepatocellular carcinoma. In addition to the risk of liver disease, MetS and T2DM are independent risk factors for cardiovascular disease (CVD), including coronary artery disease (CAD) and heart failure (HF). Importantly, there is a bidirectional relationship between liver and CVD due to shared disease pathophysiology in patients with MetS and T2DM. In this review, we have described studies exploring the relationship of MetS and T2DM with MASLD and CVD, independently. Following this we discuss studies evaluating the interplay between liver and cardiovascular risk as well as pragmatic risk mitigation strategies in this patient population.
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http://dx.doi.org/10.1016/j.diabres.2024.111650 | DOI Listing |
Lipids Health Dis
December 2024
Internal Medicine and Pathology, UC Davis School of Medicine, 2616 Hepworth Drive, Davis, CA, 95618, US.
Background: The Triglyceride-glucose (TyG) index represents a simple, cost-effective, and valid proxy for insulin resistance. This surrogate marker has also been proposed as a predictor of metabolic and cardiovascular disease (CVD). In this descriptive review, we aimed to assess the utility of the TyG index as a predictive biomarker of cardiometabolic diseases.
View Article and Find Full Text PDFNaunyn Schmiedebergs Arch Pharmacol
December 2024
Pharmacological Research Center of Medicinal Plants, Mashhad University of Medical Sciences, Mashhad, Iran.
Front Clin Diabetes Healthc
November 2024
Department of Internal Medicine, Adama Hospital Medical College, Adama, Ethiopia.
Introduction: The prevalence of metabolic syndrome among type 2 diabetes mellitus patients was inconsistent in Ethiopia. Therefore, we aimed to pool the prevalence of metabolic syndrome among type 2 diabetes mellitus patients using a systematic review and meta-analysis.
Methods: PubMed, EMBASE, and Cochrane Library databases were systematically searched for relevant articles from January 2023 to January 2024.
J Diabetes Metab Disord
December 2024
Mathematical Applications & Data Analytics Group, School of Science, Edith Cowan University, Perth, Australia.
Objectives: The burgeoning prevalence of cardiometabolic disorders, including type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS) within Africa is concerning. Machine learning (ML) techniques offer a unique opportunity to leverage data-driven insights and construct predictive models for MetS risk, thereby enhancing the implementation of personalised prevention strategies. In this work, we employed ML techniques to develop predictive models for pre-MetS and MetS among diabetic patients.
View Article and Find Full Text PDFFront Physiol
November 2024
Departamento de Bioquímica y Biología Molecular y Fisiología, Universidad de Valladolid, Valladolid, Spain.
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