rs115880984 - ROBO1

Magnitude 2.2 · 1 study on file

Reported associations

• Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes - Unknown journal (n.d.) · Unknown authors · PubMed 36587059

  ABSTRACT: Artificial intelligence (AI)-based approaches can now use electrocardiograms (ECGs) to provide expert-level performance in detecting heart abnormalities and diagnosing disease. Additionally, patient age predicted from ECGs by AI models has shown great potential as a biomarker for cardiovascular age, where recent work has found its deviation from chronological age ("delta age") to be associated with mortality and co-morbidities. However, despite being crucial for understanding underlying individual risk, the genetic underpinning of delta age is unknown. In this work we performed a genome-wide association study using UK Biobank data (n=34,432) and identified eight loci associated with delta age (), including genes linked to cardiovascular disease (CVD) (e.g. SCN5A) and (heart)

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