Genome-wide association analysis of excessive daytime sleepiness identifies 42 loci that suggest phenotypic subgroups

Wang, H; Lane, Jacqueline M.; Jones, Samuel E.; Dashti, Hassan S.; Ollila, Hanna; Wood, Andrew R.; Hees, Vincent T. van; Brumpton, Ben; Winsvold, Bendik S.; Kantojärvi, Katri; Cade, Brian E.; Sofer, Tamar; Song, Yanwei; Patel, Krunal; Anderson, Simon; Bowden, Jack; Emsley, Richard; Kyle, Simon D.; Little, Max A.; Loudon, A. S. I.; Scheer, Frank A.J.L.; Purcell, Shaun; Richmond, Rebecca C; Spiegelhalder, Kai; Tyrrell, Jessica; Zhu, Xiaofeng; Kristiansson, Kati; Sulkava, Sonja; Paunio, Tiina; Hveem, Kristian; Nielsen, Jonas B.; Willer, Cristen J.; Ja, Zwart; Strand, Linn Beate; Frayling, Timothy M.; Ray, David; Lawlor, Debbie A; Rutter, Martin K.; Weedon, Michael N.; Redline, Susan; Saxena, Richa

doi:10.1101/454561

Cited by 4 publications

(4 citation statements)

References 90 publications

(121 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The discovery data sets were GWAS summary statistics for insomnia, sleep duration, daytime sleepiness, and chronotype conducted in participants recruited to the UK Biobank . Sleep phenotypes were assessed using touchscreen questions.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Comparison of Genetic Liability for Sleep Traits Among Individuals With Bipolar Disorder I or II and Control Participants

et al. 2020

View full text Add to dashboard Cite

IMPORTANCE Insomnia, hypersomnia, and an evening chronotype are common in individuals with bipolar disorder (BD), but whether this reflects shared genetic liability is unclear. Stratifying by BD subtypes could elucidate this association and inform sleep and BD research.OBJECTIVE To assess whether polygenic risk scores (PRSs) for sleep traits are associated with BD subtypes I and II. DESIGN, SETTING, AND PARTICIPANTSThis case-control study was conducted in the United Kingdom and Sweden with participants with BD and control participants. Multinomial regression was used to assess whether PRSs for insomnia, daytime sleepiness, sleep duration, and chronotype are associated with BD subtypes compared with control participants. Affected individuals were recruited from the Bipolar Disorder Research Network. Control participants were recruited from the 1958 British Birth Cohort and the UK Blood Service. Analyses were repeated in an independent Swedish sample from August 2018 to July 2019. All participants were of European ancestry.EXPOSURES Standardized PRSs derived using alleles from genome-wide association studies of insomnia, sleep duration, daytime sleepiness, and chronotype. These were adjusted for the first 10 population principal components, genotyping platforms, and sex.MAIN OUTCOMES AND MEASURES Association of PRSs with BD subtypes, determined by semistructured psychiatric interview and case notes. RESULTS The main analysis included 4672 participants with BD (3132 female participants [67.0%]; 3404 with BD-I [72.9%]) and 5714 control participants (2812 female participants [49.2%]). Insomnia PRS was associated with increased risk of BD-II (relative risk [RR], 1.14 [95% CI, 1.07-1.21]; P = 8.26 × 10 −5 ) but not BD-I (RR, 0.98 [95% CI, 0.94-1.03]; P = .409) relative to control participants. Sleep-duration PRS was associated with BD-I (RR, 1.10 [95% CI, 1.06-1.15]; P = 1.13 × 10 −5 ) but not BD-II (RR, 0.99 [95% CI, 0.93-1.06]; P = .818). Associations between (1) insomnia PRS and BD-II and (2) sleep-duration PRS and BD-I were replicated in the Swedish sample of 4366 individuals with BD (2697 female participants [61.8%]; 2627 with BD-I [60.2%]) and 6091 control participants (3767 female participants [61.8%]). Chronotype and daytime-sleepiness PRS were not associated with BD subtypes.CONCLUSIONS AND RELEVANCE Per this analysis, BD subtypes differ in genetic liability to insomnia and hypersomnia, providing further evidence that the distinction between BD-I and BD-II has genetic validity. This distinction will be crucial in selecting participants for future research on the role of sleep disturbance in BD.

show abstract

Section: Methodsmentioning

confidence: 99%

“…Recent genome-wide association studies (GWAS) provide an opportunity to examine the association between sleep and BD at the genomic level. Using summary-level data, some studies have demonstrated a positive genetic correlation between BD and sleep duration .…”

Section: Introductionmentioning

confidence: 99%

Comparison of Genetic Liability for Sleep Traits Among Individuals With Bipolar Disorder I or II and Control Participants

et al. 2020

View full text Add to dashboard Cite

show abstract

“…These two screening steps were performed on the MESA subsample of the race/ethnic group in which the DNAm-ESS association was detected, and in all groups if the association was detected in the combined analysis. SNPs that were associated with ESS with p -value < 0.05 were carried forward to independent replication analysis (see below) of the SNP-sleepiness association in the UK Biobank [58]. We also report SNPs-ESS associations in MESA race/ethnic groups that did not identify the original DNAm-ESS association, while noting that such associations may not be detected due to lower sample size and power.…”

Section: Methodsmentioning

confidence: 99%

Epigenome-wide association analysis of daytime sleepiness in the Multi-Ethnic Study of Atherosclerosis reveals African-American-specific associations

Barfield

Wang

Liu

et al. 2019

Sleep

Self Cite

View full text Add to dashboard Cite

Study Objectives Daytime sleepiness is a consequence of inadequate sleep, sleep–wake control disorder, or other medical conditions. Population variability in prevalence of daytime sleepiness is likely due to genetic and biological factors as well as social and environmental influences. DNA methylation (DNAm) potentially influences multiple health outcomes. Here, we explored the association between DNAm and daytime sleepiness quantified by the Epworth Sleepiness Scale (ESS). Methods We performed multi-ethnic and ethnic-specific epigenome-wide association studies for DNAm and ESS in the Multi-Ethnic Study of Atherosclerosis (MESA; n = 619) and the Cardiovascular Health Study (n = 483), with cross-study replication and meta-analysis. Genetic variants near ESS-associated DNAm were analyzed for methylation quantitative trait loci and followed with replication of genotype-sleepiness associations in the UK Biobank. Results In MESA only, we detected four DNAm-ESS associations: one across all race/ethnic groups; three in African-Americans (AA) only. Two of the MESA AA associations, in genes KCTD5 and RXRA, nominally replicated in CHS (p-value < 0.05). In the AA meta-analysis, we detected 14 DNAm-ESS associations (FDR q-value < 0.05, top association p-value = 4.26 × 10−8). Three DNAm sites mapped to genes (CPLX3, GFAP, and C7orf50) with biological relevance. We also found evidence for associations with DNAm sites in RAI1, a gene associated with sleep and circadian phenotypes. UK Biobank follow-up analyses detected SNPs in RAI1, RXRA, and CPLX3 with nominal sleepiness associations. Conclusions We identified methylation sites in multiple genes possibly implicated in daytime sleepiness. Most significant DNAm-ESS associations were specific to AA. Future work is needed to identify mechanisms driving ancestry-specific methylation effects.

show abstract

“…Genetic data on sleep behaviors (sleep duration [29], di culty getting up [30], chronotype [31], nap during day [32], insomnia [33], snoring [34], daytime dozing [35]) were used in the largest relevant genome-wide association study (n = 446,118 for sleep duration; n = 386,533 for di culty getting up; n = 697,828 for chronotype; n = 452,633 for nap during day; n = 2,365,010 for insomnia; n = 408,317 for snoring; n = 452,071 for daytime dozing) to date. To mitigate the impact of linkage disequilibrium (LD) on MR analysis[36], we performed clumping for LD at r 2 < 0.01 in 500-kb regions and extracted single nucleotide polymorphisms (SNPs) with the lowest P value (P < 5×10 − 8 ) for the associated trait.…”

Section: Summary-level Data and Selection Of Instrumental Variablesmentioning

confidence: 99%

Poor sleep behaviors and high genetic susceptibility increase the risk of osteoarthritis

Yang,

Yu,

et al. 2023

Preprint

View full text Add to dashboard Cite

Background Emerging research evidence suggests an association between sleep behaviors and the risk of osteoarthritis. The various sleep behaviors are typically correlated; however, most previous studies have focused on a particular sleep behavior without considering the overall sleep pattern. Combining conventional evidence from UK Biobank longitudinal data and genetic evidence from Mendelian randomization methods to infer causality between sleep behaviors and osteoarthritis (OA) at different sites. Method First, we conducted an assessment of the association between various sleep behaviors and different OA sites based on the comprehensive prospective cohort study of the UK Biobank. Furthermore, we constructed individual sleep risk scores (ISRS) to evaluate their effect on OA when combined. Second, we utilized MR to provide genetic evidence for the causal linkage between sleep behavior and OA. Finally, we calculated a genetic risk score (GRS) for OA based on a large-scale genome-wide association study and assessed the joint effect of sleep and genetic factors on the risk of OA. Results We found a U-shaped relationship between sleep duration and the risk of OA (Pnonlinear < 0.001), with the lowest risk for sleep duration of 7–8 hours per day. Participants with often and sometimes insomnia had a 46.9% and 16.4% increased risk of OA (HR Sometimes = 1.164, 95% CI = 1.132∼1.197, PSometimes = 3.44×10− 26; HR Usually =1.469, 95% CI = 1.426∼1.514, PUsually =3.82×10− 142), respectively, while MR analysis also provided consistent evidence. Similar results were observed in participants who were daytime dozing, but no association between daytime dozing and risk of OA was shown in the MR analysis. In observational studies, snoring and difficulty getting up are associated with an increased risk of OA. We further constructed ISRS with potential risk sleep factors. We found that the risk of OA was positively associated with ISRS; furthermore, if all participants maintained healthy sleep behavior, 21.3% of OA cases could be removed. Conclusion Unhealthy sleep behaviors, individually or in combination, could increase the risk of OA, while poor sleep behaviors and genetic factors can collaboratively increase the risk of OA.

show abstract

Genome-wide association analysis of excessive daytime sleepiness identifies 42 loci that suggest phenotypic subgroups

Cited by 4 publications

References 90 publications

Comparison of Genetic Liability for Sleep Traits Among Individuals With Bipolar Disorder I or II and Control Participants

Comparison of Genetic Liability for Sleep Traits Among Individuals With Bipolar Disorder I or II and Control Participants

Epigenome-wide association analysis of daytime sleepiness in the Multi-Ethnic Study of Atherosclerosis reveals African-American-specific associations

Poor sleep behaviors and high genetic susceptibility increase the risk of osteoarthritis

Contact Info

Product

Resources

About