Machine Learning Reveals the Contribution of Rare Genetic Variants and Enhances Risk Prediction for Coronary Artery Disease in the Japanese Population.

doi:10.1161/CIRCGEN.125.005341

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Machine Learning Reveals the Contribution of Rare Genetic Variants and Enhances Risk Prediction for Coronary Artery Disease in the Japanese Population.

Circulation. Genomic and precision medicine - 1 Aug 2026

Ieki Hirotaka, Zhang Sai, Koyama Satoshi, Kjellberg Martin, Yoshida Hiroki, Kurosawa Ryo, Matsunaga Hiroshi, Miyazawa Kazuo, Enzan Nobuyuki, Kim Changhoon, Seo Jeong-Sun, Higasa Koichiro, Ozaki Kouichi, Onouchi Yoshihiro, Matsuda Koichi, Kamatani Yoichiro, Terao Chikashi, Matsuda Fumihiko, Snyder Michael P, Komuro Issei, Ito Kaoru

Abstract excerpt

BACKGROUND: GWASs (genome-wide association studies) have advanced our understanding of coronary artery disease (CAD) genetics and enabled the development of polygenic risk scores (PRSs) for estimating genetic risk based on common variant burden. However, GWASs have limitations in analyzing rare variants due to insufficient statistical power, thereby constraining PRS performance. METHODS: We conducted whole-genome...

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PMID: 42237915
DOI: 10.1161/CIRCGEN.125.005341
PMCID: PMC13310176

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CAD
LDLR

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