Advances in familial hypercholesterolemia management: a systematic review of novel therapies and AI screening

Background. Familial hypercholesterolemia (FH) is a prevalent monogenic lipid disorder characterized by elevated low-density lipoprotein cholesterol (LDL-C) from birth, predisposing individuals to premature atherosclerotic cardiovascular disease. Despite advances in standard lipid-lowering therapy, many patients – particularly those with homozygous FH (HoFH) or LDLR-null mutations – fail to reach LDL-C targets, necessitating innovative strategies and precision diagnostics. Objectives. To evaluate recent pharmacologic advances, functional genetic findings, and the integration of machine learning models for improved diagnosis and management of FH. Methods. Following PRISMA 2020 guidelines, a comprehensive search of peer-reviewed literature from January 2017 to February 2025 was conducted in PubMed, Scopus, and Web of Science. Ten high-quality studies were included based on predefined PICO criteria. Study characteristics and outcomes were extracted and synthesized thematically. Results. PCSK9 inhibitors (evolocumab) reduced LDL-C by up to 60%, with additional anti-inflammatory effects in COVID-19 patients. Inclisiran, a small interfering RNA (siRNA), achieved a sustained 44.2% reduction over 4 years (ORION-3). ANGPTL3 inhibition with evinacumab lowered LDL-C by up to 49%, independent of LDL receptor function. Functional genomics enabled reclassification of APOB variants and confirmed ANGPTL3 loss-of-function as cardioprotective. Artificial intelligence models, including random forests and LASSO regression with polygenic scores, outperformed traditional diagnostic tools, achieving AUROC values up to 0.94 and reducing unnecessary genetic testing by 18%. Conclusions. Emerging lipid-lowering agents, functional genomic insights, and AI-driven diagnostics address key limitations of conventional FH care. Their integration offers a more precise and individualized approach to detection and treatment. Continued validation and clinical adoption are essential to maximize global impact.