Abstract 4361108: Genome-wide analysis of heart failure yields insights into disease heterogeneity and enables prognostic prediction in the Japanese population

To understand the genetic basis of heart failure (HF) in the Japanese population, we performed genome-wide association studies (GWASs) comprising 16,251 all-cause HF cases, 4,254 HF with reduced ejection fraction cases, 7,154 HF with preserved ejection fraction cases, and 11,122 non-ischemic HF cases among 213,828 individuals (Figure 1) and identified five novel loci (Figure 2). A subsequent cross-ancestry meta-analysis and multi-trait analysis of the GWAS data identified 19 novel loci in total. Among these susceptibility loci, a common non-coding variant in TTN (rs1484116) was associated with reduced cardiac function and worse long-term mortality. We leveraged the HF meta-GWASs along with cardiac function-related GWASs to develop a polygenic risk score (PRS) for HF. The PRS successfully identified early-onset HF and those with an increased risk of long-term HF mortality (Figure 3). Our results shed light on the shared and distinct genetic basis of HF between Japanese and European populations and improve the clinical value of HF genetics.

Authors

Institutions

Publication Details

Journal
Circulation
Published
2025-11-03
DOI
https://doi.org/10.1161/circ.152.suppl_3.4361108
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract 4361108: Genome-wide analysis of heart failure yields insights into disease heterogeneity and enables prognostic prediction in the Japanese population

Hiroyuki Aburatani, Yukihide Momozawa, Chikashi C. Terao, Joseph Jacob et al.
Circulation
Genetic Associations and Epidemiology
article

Abstract 4361108: Genome-wide analysis of heart failure yields insights into disease heterogeneity and enables prognostic prediction in the Japanese population

Hiroyuki Aburatani, Yukihide Momozawa, Chikashi C. Terao, Joseph Jacob, Satoshi Koyama, Nobuyuki Enzan, Fumie Takechi, Kohei Tomizuka, Ryosuke Osako, Hiroshi Akazawa, Benjamin Franklin Voight, Yoichiro Kamatani, Yan V. Sun, Kazuo Miyazawa, Ryo Kurosawa, Hirotaka Ieki, Koichi Node, Kouichi Ozaki, Takanori Yamaguchi, Issei Komuro, Patrick T. Ellinor, Masashi Fukuyama, Koichi Matsuda, Michael G. Levin, Scott M. Damrauer, Toshiharu Ninomiya, Xiaoxi Liu, Kaoru Ito, Yoshihiro Onouchi
article en

Abstract

To understand the genetic basis of heart failure (HF) in the Japanese population, we performed genome-wide association studies (GWASs) comprising 16,251 all-cause HF cases, 4,254 HF with reduced ejection fraction cases, 7,154 HF with preserved ejection fraction cases, and 11,122 non-ischemic HF cases among 213,828 individuals (Figure 1) and identified five novel loci (Figure 2). A subsequent cross-ancestry meta-analysis and multi-trait analysis of the GWAS data identified 19 novel loci in total. Among these susceptibility loci, a common non-coding variant in TTN (rs1484116) was associated with reduced cardiac function and worse long-term mortality. We leveraged the HF meta-GWASs along with cardiac function-related GWASs to develop a polygenic risk score (PRS) for HF. The PRS successfully identified early-onset HF and those with an increased risk of long-term HF mortality (Figure 3). Our results shed light on the shared and distinct genetic basis of HF between Japanese and European populations and improve the clinical value of HF genetics.

CirculationVol. 152(Suppl_3)
Kyushu University (JP), Emory University (US), Saga University (JP), Brown University (US), Massachusetts General Hospital (US), RIKEN Center for Integrative Medical Sciences (JP), The University of Tokyo (JP), International University of Health and Welfare (JP), University of Pennsylvania (US)
Openalex Percentile: Top 66%
Genetic Associations and Epidemiology
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.