Long noncoding RNAs in familial hypercholesterolemia: biomarkers, therapeutics, and AI in precision medicine

家族性高胆固醇血症中的长链非编码RNA:生物标志物、治疗方法和人工智能在精准医学中的应用

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Abstract

Long noncoding RNAs (lncRNAs) have emerged as critical regulators of lipid metabolism, playing pivotal roles in cholesterol biosynthesis, transport, and efflux. Familial Hypercholesterolemia (FH), a genetic disorder characterized by excessive low-density lipoprotein cholesterol (LDL-C) levels, remains a significant contributor to premature cardiovascular disease (CVD). Traditional diagnostic methods, including lipid profiling and genetic testing, have limitations in sensitivity and accessibility, highlighting the need for novel molecular biomarkers. This review delves into the mechanistic involvement of lncRNAs in FH pathogenesis, shedding light on their potential as non-invasive biomarkers and therapeutic targets. Key lncRNAs such as LeXis, CHROME, and H19 have been implicated in cholesterol regulation and atherosclerosis progression, making them attractive candidates for precision medicine applications. Additionally, advancements in AI-driven lncRNA discovery and single-cell transcriptomics are paving the way for innovative diagnostic and therapeutic strategies. Emerging RNA-based therapeutics, including antisense oligonucleotides, small interfering RNAs (siRNAs), and CRISPR-based gene-editing tools, hold promise for modulating lncRNA function to restore lipid homeostasis. However, challenges such as biomarker validation, efficient RNA delivery, and regulatory approval must be addressed for clinical translation. The integration of lncRNA-based approaches into FH management offers new possibilities for early detection, targeted therapy, and personalized cardiovascular risk assessment, underscoring the need for continued research in this rapidly evolving field.

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