Circulating MicroRNAs Are Promising Biomarkers for Assessing the Risk of Antipsychotic-Induced Metabolic Syndrome (Review): Part 2

INTRODUCTION. The first part of this article discussed antipsychotic-induced metabolic syndrome (AIMetS) as a common adverse reaction to the pharmacotherapy of psychiatric and addiction disorders. The authors presented a review of basic and additional clinical and biochemical biomarkers of metabolic syndrome (MetS) in general and AIMetS in particular in patients with schizophrenia spectrum disorders and outlined approaches to measuring these biomarkers. Detecting changes in the expression of circulating microRNAs in the blood can be considered a promising method for predicting and diagnosing AIMetS. AIM . This study aimed to evaluate the role of circulating microRNAs as epigenetic biomarkers of the key components of AIMetS pathogenesis. DISCUSSION . The authors reviewed and collated the results of academic and clinical research (2012–2024) with a focus on the role of circulating microRNAs involved in the key AIMetS pathogenesis and progression pathways. The authors analysed the results of studies on the role of circulating microRNAs in the blood as regulators of the key components of MetS and AIMetS pathogenesis. The studied components of pathogenesis included oxidative stress, systemic inflammation, adipogenesis regulation (and abdominal adiposity development), lipid metabolism, high- and low-density lipoprotein cholesterol homeostasis, atherogenesis, and hepatic steatosis, as well as the regulation of insulin and leptin sensitivity, glucose metabolism and appetite, and insulin, neuropeptide Y, orexin, thyroid and parathyroid hormone expression. A personalised assessment of the safety of pharmacotherapy may depend on the pattern of circulating microRNAs that induce or inhibit the main components of AIMetS pathogenesis. The differences in the results of the reviewed microRNA studies may be due to the differences in the design of these academic (mainly) and clinical studies and their lack of consideration for modifiable and unmodifiable risk factors for developing AIMetS. The authors proposed a microRNA classification according to the risk level of developing AIMetS. CONCLUSIONS . The findings demonstrate that the sensitivity and specificity of epigenetic biomarkers of AIMetS can vary widely, depending on the nature of their influence (predictive or protective) on one or several pathogenetic components of this widespread adverse reaction to psychopharmacotherapy. The most studied microRNAs are predictive biomarkers of oxidative stress (miR-1, miR-21, miR-23b, miR-27a, etc.) and systemic inflammation (miR-21, miR-23a, miR-27a, etc.) in patients at high risk of developing MetS and AIMetS. Promising epigenetic AIMetS biomarkers include microRNAs that affect the expression of and sensitivity to neuropeptides, including neuropeptide Y (miR-let7b, miR-29b, miR-33, etc.), leptin (miR-let7a, miR-9, miR-30e, etc.), and orexin (miR-137, miR-637, miR-654, etc.).