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

Area of Science:

• Cardiovascular Medicine
• Genetics
• Public Health

Background:

• Premature coronary artery disease (CAD) is a major cause of death in India, affecting individuals with and without traditional risk factors.
• Current clinical risk algorithms and imaging techniques offer limited predictive information for premature CAD.
• CAD is a complex, multifactorial condition necessitating advanced risk assessment tools.

Purpose of the Study:

• To evaluate the predictive capability of gene risk scores (GRS) derived from genome-wide association studies (GWAS) for premature CAD.
• To assess the effectiveness of GWAS-based GRS in improving risk stratification for younger individuals.
• To explore the potential of GRS in guiding aggressive interventions for preventing premature CAD.

Main Methods:

• Utilizing genome-wide association studies (GWAS) to incorporate millions of single nucleotide polymorphisms (SNPs) for GRS calculation.
• Comparing the discriminative power of GWAS-based GRS against conventional risk assessment tools.
• Analyzing the impact of GRS on the net reclassification of risk, particularly in South Asian populations.

Main Results:

• GWAS-based GRS demonstrate enhanced discriminative ability compared to traditional methods for assessing CAD risk.
• GRS significantly improves risk reclassification by approximately 15% in younger individuals, especially among South Asians.
• High GRS identifies individuals who may benefit from intensified lifestyle interventions and lipid-lowering therapies.

Conclusions:

• GWAS-based GRS represent a powerful tool for predicting and stratifying risk in premature CAD.
• Integrating GRS into clinical practice can lead to more personalized and effective prevention strategies.
• Targeted interventions in high-GRS individuals hold the potential to significantly reduce the burden of premature CAD.