hum0495-v1Release info

Precision medicine for preventing stroke in patients with atrial fibrillation

Aims

Atrial fibrillation (AF) is common in older adults, and AF-associated ischemic stroke can lead to reduced quality of life or a bedridden state. This study will collect multi-layered data, including genetic, clinical, physiological, and electrocardiographic information, from AF patients and healthy controls, and will develop AI-based algorithms to stratify the risks of AF onset and stroke. Our goal is to establish a foundation applicable to primary screening through health checkups and IoT devices, personalized preemptive medicine, and drug discovery or new drug development.

Methods

[hum0495.v1.gwas.v1] We performed whole exome sequencing and processed the sequencing data according to the best practices described in the Genome Analysis Toolkit (GATK). We also performed gene-based association tests, specifically burden tests, sequence kernel association test (SKAT), and SKAT-O.
[JGAS000866] Genotyping was performed using SNP arrays, followed by imputation with the 1000 Genomes reference panel, and GWAS was performed using covariate-adjusted logistic regression.

Participants/materials

1,176 PAF patients and 1,172 non-PAF patients

URL

N/A

Principal investigator

Toshihiro Tanaka

Affiliation

Department of Human Genetics and Disease Diversity, Institute of Science Tokyo

No research projects.