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Genetics-based risk scores for prediction of premature coronary artery disease

Premature coronary artery disease (CAD) is endemic in India. Global Burden of Diseases study has reported that it led to 286,000 deaths in 2019 in India. Many of these patients have standard risk factors but a third have none. Clinical risk algorithms and imaging provide limited risk information in...

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Detalles Bibliográficos
Autor principal: Gupta, Rajeev
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10568063/
https://www.ncbi.nlm.nih.gov/pubmed/37633460
http://dx.doi.org/10.1016/j.ihj.2023.08.003
Descripción
Sumario:Premature coronary artery disease (CAD) is endemic in India. Global Burden of Diseases study has reported that it led to 286,000 deaths in 2019 in India. Many of these patients have standard risk factors but a third have none. Clinical risk algorithms and imaging provide limited risk information in premature CAD. CAD is multifactorial and studies have now focused on the predictive capability of clusters of genes and single nucleotide polymorphisms (SNPs) using gene risk score (GRS). Older studies combined data from 10 to 12 genes and 100–500 SNPs to calculate GRS, however, following the advent of genome-wide association studies (GWAS), millions of SNPs have been incorporated. Studies have reported that GWAS-based GRS may be more discriminative than conventional tools. Recent studies, especially among South Asians, have reported that GRS improves net reclassification by 15% (12–19%) for younger individuals. Aggressive lifestyle interventions and lipid-lowering therapies can ameliorate risk in high-GRS individuals and potentially prevent premature CAD.