Using the Coriell Personalized Medicine Collaborative Data to conduct a genome‐wide association study of sleep duration

Abstract

Sleep is critical to health and functionality, and several studies have investigated the inherited component of insomnia and other sleep disorders using genome‐wide association studies (GWAS). However, genome‐wide studies focused on sleep duration are less common. Here, we used data from participants in the Coriell Personalized Medicine Collaborative (CPMC) (n = 4,401) to examine putative associations between self‐reported sleep duration, demographic and lifestyle variables, and genome‐wide single nucleotide polymorphism (SNP) data to better understand genetic contributions to variation in sleep duration. We employed stepwise ordered logistic regression to select our model and retained the following predictive variables: age, gender, weight, physical activity, physical activity at work, smoking status, alcohol consumption, ethnicity, and ancestry (as measured by principal components analysis) in our association testing. Several of our strongest candidate genes were previously identified in GWAS related to sleep duration (TSHZ2, ABCC9, FBXO15) and narcolepsy (NFATC2, SALL4). In addition, we have identified novel candidate genes for involvement in sleep duration including SORCS1 and ELOVL2. Our results demonstrate that the self‐reported data collected through the CPMC are robust, and our genome‐wide association analysis has identified novel candidate genes involved in sleep duration. More generally, this study contributes to a better understanding of the complexity of human sleep. © 2015 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Genetic Influences on Evening Preference Overlap with Those for Bipolar Disorder in a Sample of Mexican Americans and American Indians

“…The results of several Genome-Wide Association Studies (GWAS) on sleep duration, sleep latency, sleep depth, sleep quality, insomnia, daytime sleepiness, sleep apnea, and actigraphic measurements are available (Allebrandt et al, 2013; Amin et al, 2016; Byrne et al, 2013; Cade, Chen, et al, 2016; Cade, Gottlieb, et al, 2016; Gottlieb et al, 2015; Gottlieb et al, 2007; Lane et al, 2017; Marinelli et al, 2016; Ollila et al, 2014; Scheinfeldt et al, 2015; Spada et al, 2016), yet many of these phenotypes are independent of chronotype (Jones et al, 2016; Lane et al, 2017; Lehnkering & Siegmund, 2007). Two early GWAS identified several single nucleotide polymorphisms (SNPs) associated with the chronotype measure bedtime.…”

“…While these studies have shed light onto the molecular basis of diurnal preference in human populations, they have solely looked at populations of European ancestry. Several GWAS on sleep phenotypes have included subjects of diverse ethnic background (Cade, Gottlieb, et al, 2016; Scheinfeldt et al, 2015), including a solely Hispanic sample (Cade, Chen, et al, 2016), yet these studies did not assess chronotype.…”

Human genetics and sleep behavior

“…Although several other intriguing candidate genes have been identified, statistical and functional evidence is lacking for many implicated cases [16–19]. Interestingly, ion-channel genes have been shown to regulate duration of sleep or sleep-like behavior in model organisms [20–22], though it is still unclear whether such genes also regulate sleep duration in humans.…”

“…Interestingly, ion-channel genes have been shown to regulate duration of sleep or sleep-like behavior in model organisms [20–22], though it is still unclear whether such genes also regulate sleep duration in humans. A plausible case was the ATP-binding cassette sub-family C member 9 (ABCC9) gene which encodes a pore-forming subunit of an ATP-sensitive potassium channel, but the SNPs found by different studies were all intronic [16,17,23]. …”

Encouraging Physician Adoption of Genetic Testing for Precision Medicine

“…The cost-effectiveness of KRAS gene testing for colorectal cancer has been demonstrated [3]. Our own research with the Coriell Personalized Medicine Collaborative (CPMC) has shown genetic information to be a motivating factor for positive health behavior change in melanoma prevention [4] and coronary artery disease prevention [ Scheinfeldt LB, Schmidlen TJ, Gharani N et al Unpublished Data ], identified genes associated with sleep duration [5], and generated new models for genomic counseling and education [6,7]. Pharmacogenomics (PGx) to predict and optimize therapeutic response and reduce risk of adverse events is rarely utilized in the clinic despite that as of May 2015, 137 US FDA-approved drugs have PGx information in their labeling [8].…”