Large-scale exome-wide association analysis identifies new genes associated with sleep
Research News
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Jan 4, 2024
A joint team led by Jintai Yu, a researcher at Tianqiao and Chrissy Chen Institute, identified new genes associated with sleep phenotypes based on exome-wide sequencing data and association analysis algorithms of nearly 450,000 people, further analyzed the genetic contribution of rare mutations to sleep phenotypes, and explained the genetic mechanisms underlying the association of sleep with health outcomes such as cognition, neuropsychiatric disorders, and inflammation. The study has the largest sample size to date and includes a comprehensive exome-wide association analysis of sleep with a comprehensive range of phenotypes.
In addition, the study found that these genes are enriched in pathways associated with circadian rhythms and are predominantly expressed in neurons of the central nervous system. Finally, the team further explored the association of these genes with biochemical, brain structure, cardiovascular disease, cognition, cardiac function, inflammation, neuropsychiatric disorders, lung function, and other indicators and diseases. The findings were published in Nature Human Behaviour.
A joint team led by Jintai Yu, a researcher at Tianqiao and Chrissy Chen Institute, identified new genes associated with sleep phenotypes based on exome-wide sequencing data and association analysis algorithms of nearly 450,000 people, further analyzed the genetic contribution of rare mutations to sleep phenotypes, and explained the genetic mechanisms underlying the association of sleep with health outcomes such as cognition, neuropsychiatric disorders, and inflammation. The study has the largest sample size to date and includes a comprehensive exome-wide association analysis of sleep with a comprehensive range of phenotypes.
In addition, the study found that these genes are enriched in pathways associated with circadian rhythms and are predominantly expressed in neurons of the central nervous system. Finally, the team further explored the association of these genes with biochemical, brain structure, cardiovascular disease, cognition, cardiac function, inflammation, neuropsychiatric disorders, lung function, and other indicators and diseases. The findings were published in Nature Human Behaviour.
