Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes.
Deep learning-derived cardiovascular age shares a genetic basis with other cardiac phenotypes.
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DOI：
10.1038/s41598-022-27254-z
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发表时间：
2022-12-31
影响因子：
4.6
通讯作者：
中科院分区：
文献类型：
--
作者：
基于人工智能(AI)的方法现在可以使用心电图(ECG)在检测心脏异常和诊断疾病方面提供专家级的性能。此外，人工智能模型根据心电图预测的患者年龄已显示出作为心血管年龄生物标记物的巨大潜力，最近的研究发现，它与时间年龄的偏差(增量年龄)与死亡率和并存疾病有关。然而，尽管对了解潜在的个体风险至关重要，三角洲年龄的遗传基础尚不清楚。在这项工作中，我们使用英国生物库数据(n=34,432)进行了全基因组关联研究，并确定了八个与Delta age()相关的基因，包括与心血管疾病(CVD)(例如SCN5A)和(心脏)肌肉发育(例如TTN)相关的基因。我们的结果表明，心血管衰老的遗传基础主要是由与心血管系统直接相关的基因决定的，而不是与更一般的衰老机制有关的基因。我们的洞察力为心血管疾病的流行病学提供了信息，并对预防和精确医学产生了影响。
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) muscle development (e.g. TTN). Our results indicate that the genetic basis of cardiovascular ageing is predominantly determined by genes directly involved with the cardiovascular system rather than those connected to more general mechanisms of ageing. Our insights inform the epidemiology of CVD, with implications for preventative and precision medicine.
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影响因子：
9.2
作者：
Chang CC;Chow CC;Tellier LC;Vattikuti S;Purcell SM;Lee JJ
通讯作者：
Lee JJ
影响因子：
14.9
作者：
Buniello, Annalisa;MacArthur, Jacqueline A. L.;Parkinson, Helen
通讯作者：
Parkinson, Helen
DOI：
10.1002/prca.201300105
发表时间：
2014-06
期刊：
Proteomics. Clinical applications
影响因子：
--
作者：
Aggarwal N;Sloane BF
通讯作者：
Sloane BF
DOI：
10.1042/cs20130326
发表时间：
2014-05
期刊：
Clinical science (London, England : 1979)
影响因子：
--
作者：
Glover M;Ware JS;Henry A;Wolley M;Walsh R;Wain LV;Xu S;Van't Hoff WG;Tobin MD;Hall IP;Cook S;Gordon RD;Stowasser M;O'Shaughnessy KM
通讯作者：
O'Shaughnessy KM
影响因子：
--
作者：
Ball, Robyn L.;Feiveson, Alan H.;Dabney, Alan R.
通讯作者：
Dabney, Alan R.