2019
DOI: 10.1101/832162
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Leveraging pleiotropy to discover and interpret GWAS results for sleep-associated traits

Abstract: Genetic association studies of many heritable traits resulting from physiological testing often have modest sample sizes due to the cost and invasiveness of the required phenotyping. This reduces statistical power to discover multiple genetic associations. We present a strategy to leverage pleiotropy between traits to both discover new loci and to provide mechanistic hypotheses of the underlying pathophysiology, using obstructive sleep apnea (OSA) as an exemplar. OSA is a common disorder diagnosed via overnigh… Show more

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Cited by 4 publications
(1 citation statement)
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References 106 publications
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“…[58] Although we were unable to assess the genetic overlap between HbA1c, cholesterol, triglycerides in our study, methods appropriate in leveraging pleiotropy in larger studies have been developed. [59,60] These methods may enhance both discovery and genetic associations while creating potentially more powerful PRS for each of the traits. [13] Lastly, our study has several other limitations and strengths.…”
Section: Discussionmentioning
confidence: 99%
“…[58] Although we were unable to assess the genetic overlap between HbA1c, cholesterol, triglycerides in our study, methods appropriate in leveraging pleiotropy in larger studies have been developed. [59,60] These methods may enhance both discovery and genetic associations while creating potentially more powerful PRS for each of the traits. [13] Lastly, our study has several other limitations and strengths.…”
Section: Discussionmentioning
confidence: 99%