Quantitative traits analyzed in Genome‐Wide Association Studies (GWAS) are often nonnormally distributed. For such traits, association tests based on standard linear regression are subject to reduced ...power and inflated type I error in finite samples. Applying the rank‐based inverse normal transformation (INT) to nonnormally distributed traits has become common practice in GWAS. However, the different variations on INT‐based association testing have not been formally defined, and guidance is lacking on when to use which approach. In this paper, we formally define and systematically compare the direct (D‐INT) and indirect (I‐INT) INT‐based association tests. We discuss their assumptions, underlying generative models, and connections. We demonstrate that the relative powers of D‐INT and I‐INT depend on the underlying data generating process. Since neither approach is uniformly most powerful, we combine them into an adaptive omnibus test (O‐INT). O‐INT is robust to model misspecification, protects the type I error, and is well powered against a wide range of nonnormally distributed traits. Extensive simulations were conducted to examine the finite sample operating characteristics of these tests. Our results demonstrate that, for nonnormally distributed traits, INT‐based tests outperform the standard untransformed association test, both in terms of power and type I error rate control. We apply the proposed methods to GWAS of spirometry traits in the UK Biobank. O‐INT has been implemented in the R package RNOmni, which is available on CRAN.
Being a morning person is a behavioural indicator of a person's underlying circadian rhythm. Using genome-wide data from 697,828 UK Biobank and 23andMe participants we increase the number of genetic ...loci associated with being a morning person from 24 to 351. Using data from 85,760 individuals with activity-monitor derived measures of sleep timing we find that the chronotype loci associate with sleep timing: the mean sleep timing of the 5% of individuals carrying the most morningness alleles is 25 min earlier than the 5% carrying the fewest. The loci are enriched for genes involved in circadian regulation, cAMP, glutamate and insulin signalling pathways, and those expressed in the retina, hindbrain, hypothalamus, and pituitary. Using Mendelian Randomisation, we show that being a morning person is causally associated with better mental health but does not affect BMI or risk of Type 2 diabetes. This study offers insights into circadian biology and its links to disease in humans.
To examine the effects of past and current night shift work and genetic type 2 diabetes vulnerability on type 2 diabetes odds.
In the UK Biobank, we examined associations of current (
= 272,214) and ...lifetime (
= 70,480) night shift work exposure with type 2 diabetes risk (6,770 and 1,191 prevalent cases, respectively). For 180,704 and 44,141 unrelated participants of European ancestry (4,002 and 726 cases, respectively) with genetic data, we assessed whether shift work exposure modified the relationship between a genetic risk score (comprising 110 single-nucleotide polymorphisms) for type 2 diabetes and prevalent diabetes.
Compared with day workers, all current night shift workers were at higher multivariable-adjusted odds for type 2 diabetes (none or rare night shifts: odds ratio OR 1.15 95% CI 1.05-1.26; some nights: OR 1.18 95% CI 1.05-1.32; and usual nights: OR 1.44 95% CI 1.19-1.73), except current permanent night shift workers (OR 1.09 95% CI 0.93-1.27). Considering a person's lifetime work schedule and compared with never shift workers, working more night shifts per month was associated with higher type 2 diabetes odds (<3/month: OR 1.24 95% CI 0.90-1.68; 3-8/month: OR 1.11 95% CI 0.90-1.37; and >8/month: OR 1.36 95% CI 1.14-1.62;
= 0.001). The association between genetic type 2 diabetes predisposition and type 2 diabetes odds was not modified by shift work exposure.
Our findings show that night shift work, especially rotating shift work including night shifts, is associated with higher type 2 diabetes odds and that the number of night shifts worked per month appears most relevant for type 2 diabetes odds. Also, shift work exposure does not modify genetic risk for type 2 diabetes, a novel finding that warrants replication.
Sleep is an essential state of decreased activity and alertness but molecular factors regulating sleep duration remain unknown. Through genome-wide association analysis in 446,118 adults of European ...ancestry from the UK Biobank, we identify 78 loci for self-reported habitual sleep duration (p < 5 × 10
; 43 loci at p < 6 × 10
). Replication is observed for PAX8, VRK2, and FBXL12/UBL5/PIN1 loci in the CHARGE study (n = 47,180; p < 6.3 × 10
), and 55 signals show sign-concordant effects. The 78 loci further associate with accelerometer-derived sleep duration, daytime inactivity, sleep efficiency and number of sleep bouts in secondary analysis (n = 85,499). Loci are enriched for pathways including striatum and subpallium development, mechanosensory response, dopamine binding, synaptic neurotransmission and plasticity, among others. Genetic correlation indicates shared links with anthropometric, cognitive, metabolic, and psychiatric traits and two-sample Mendelian randomization highlights a bidirectional causal link with schizophrenia. This work provides insights into the genetic basis for inter-individual variation in sleep duration implicating multiple biological pathways.
Morning diurnal preference is associated with reduced risk of major depressive disorder (MDD); however, causality in this association is uncertain.
To examine the association of genetically proxied ...morning diurnal preference with depression risk using mendelian randomization.
This 2-sample mendelian randomization study used summary-level genetic associations with diurnal preference and MDD. Up to 340 genetic loci associated with diurnal preference in a meta-analysis of the UK Biobank and 23andMe cohorts were considered as genetic proxies for diurnal preference. The effect size of these variants was scaled using genetic associations with accelerometer-based measurement of sleep midpoint. Genetic associations with MDD were obtained from a meta-analysis of genome-wide association studies data from the Psychiatric Genomics Consortium and UK Biobank. The inverse-variance weighted method was used to estimate the association of genetically proxied morning diurnal preference, corresponding to a 1-hour earlier sleep midpoint, with MDD risk.
Morning diurnal preference scaled to a 1-hour earlier, objectively measured sleep midpoint.
Risk of MDD, including self-reported and clinically diagnosed cases, as ascertained in meta-analyses of genome-wide association studies.
A total of 697 828 individuals (all of European ancestry) were in the UK Biobank and 23andMe cohorts; 85 502 in the UK Biobank had measurements of the sleep midpoint. A further 170 756 individuals with MDD and 329 443 control participants (all of European ancestry) were in the Psychiatric Genomics Consortium and UK Biobank data. Genetically proxied earlier diurnal preference was associated with a 23% lower risk of depression (odds ratio OR per 1-hour earlier sleep midpoint, 0.77 95% CI, 0.63-0.94; P = .01). This association was similar when restricting analysis to individuals with MDD as stringently defined by the Psychiatric Genomics Consortium (OR, 0.73 95% CI, 0.54-1.00; P = .05) but not statistically significant when defined by hospital-based billing codes in the UK Biobank (OR, 0.64 95% CI, 0.39-1.06; P = .08). Sensitivity analyses examining potential bias due to pleiotropy or reverse causality showed similar findings (eg, intercept SE, 0.00 0.001; P = .66 by Egger intercept test).
The results of this mendelian randomization study support a protective association of earlier diurnal preference with risk of MDD and provide estimates contextualized to an objective sleep timing measure. Further investigation in the form of randomized clinical trials may be warranted.
Sleep is an essential human function but its regulation is poorly understood. Using accelerometer data from 85,670 UK Biobank participants, we perform a genome-wide association study of 8 derived ...sleep traits representing sleep quality, quantity and timing, and validate our findings in 5,819 individuals. We identify 47 genetic associations at P < 5 × 10
, of which 20 reach a stricter threshold of P < 8 × 10
. These include 26 novel associations with measures of sleep quality and 10 with nocturnal sleep duration. The majority of identified variants associate with a single sleep trait, except for variants previously associated with restless legs syndrome. For sleep duration we identify a missense variant (p.Tyr727Cys) in PDE11A as the likely causal variant. As a group, sleep quality loci are enriched for serotonin processing genes. Although accelerometer-derived measures of sleep are imperfect and may be affected by restless legs syndrome, these findings provide new biological insights into sleep compared to previous efforts based on self-report sleep measures.
Circadian rhythms and sleep are fundamental biological processes integral to human health. Their disruption is associated with detrimental physiological consequences, including cognitive, metabolic, ...cardiovascular and immunological dysfunctions. Yet many of the molecular underpinnings of sleep regulation in health and disease have remained elusive. Given the moderate heritability of circadian and sleep traits, genetics offers an opportunity that complements insights from model organism studies to advance our fundamental molecular understanding of human circadian and sleep physiology and linked chronic disease biology. Here, we review recent discoveries of the genetics of circadian and sleep physiology and disorders with a focus on those that reveal causal contributions to complex diseases.
Daytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remain unclear. Here, we perform a genome-wide association study of ...self-reported daytime napping in the UK Biobank (n = 452,633) and identify 123 loci of which 61 replicate in the 23andMe research cohort (n = 541,333). Findings include missense variants in established drug targets for sleep disorders (HCRTR1, HCRTR2), genes with roles in arousal (TRPC6, PNOC), and genes suggesting an obesity-hypersomnolence pathway (PNOC, PATJ). Association signals are concordant with accelerometer-measured daytime inactivity duration and 33 loci colocalize with loci for other sleep phenotypes. Cluster analysis identifies three distinct clusters of nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization shows potential causal links between more frequent daytime napping and higher blood pressure and waist circumference.
Our sleep timing preference, or chronotype, is a manifestation of our internal biological clock. Variation in chronotype has been linked to sleep disorders, cognitive and physical performance, and ...chronic disease. Here we perform a genome-wide association study of self-reported chronotype within the UK Biobank cohort (n=100,420). We identify 12 new genetic loci that implicate known components of the circadian clock machinery and point to previously unstudied genetic variants and candidate genes that might modulate core circadian rhythms or light-sensing pathways. Pathway analyses highlight central nervous and ocular systems and fear-response-related processes. Genetic correlation analysis suggests chronotype shares underlying genetic pathways with schizophrenia, educational attainment and possibly BMI. Further, Mendelian randomization suggests that evening chronotype relates to higher educational attainment. These results not only expand our knowledge of the circadian system in humans but also expose the influence of circadian characteristics over human health and life-history variables such as educational attainment.
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