The heritability of insomnia from childhood to adolescence: results from a longitudinal twin study

Study Objectives: To determine prevalence and heritability of insomnia during middle/late childhood and adolescence; examine longitudinal associations in insomnia over time; and assess the extent to which genetic and environmental factors on insomnia remain stable, or whether new factors come into play, across this developmental period. Design: Longitudinal twin study. Setting: Academic medical center. Patients or Participants: There were 739 complete monozygotic twin pairs (52%) and 672 complete dizygotic twin pairs (48%) initially enrolled and were followed up at three additional time points (waves). Mode ages at each wave were 8, 10, 14, and 15 y (ages ranged from 8-18 y). Interventions: None. Measurements and Results: Clinical ratings of insomnia symptoms were assessed using the Child and Adolescent Psychiatric Assessment (CAPA) by trained clinicians, and rated according to Diagnostic and Statistical Manual of Mental Disorders (DSM)-III-R criteria for presence of ‘clinically significant insomnia’, over four sequential waves. Insomnia symptoms were prevalent but significantly decreased across the four waves (ranging from 16.6% to 31.2%). ‘Clinically significant insomnia’ was moderately heritable at all waves (h2 range = 14% to 38%), and the remaining source of variance was the nonshared environment. Multivariate models indicated that genetic influences at wave 1 contributed to insomnia at all subsequent waves, and that new genetic influences came into play at wave 2, which further contributed to stability of symptoms. Nonshared environmental influences were time-specific. Conclusion: Insomnia is prevalent in childhood and adolescence, and is moderately heritable. The progression of insomnia across this developmental time period is influenced by stable as well as new genetic factors that come into play at wave 2. Molecular genetic studies should now identify genes related to insomnia progression during childhood and adolescence

Genetic correlation analysis suggests association between increased self reported sleep duration in adults and schizophrenia and type 2 diabetes

Study Objectives: We sought to examine how much of the heritability of self-report sleep duration is tagged by common genetic variation in populations of European ancestry and to test if the common variants contributing to sleep duration are also associated with other diseases and traits. Methods: We utilized linkage disequilibrium (LD)-score regression to estimate the heritability tagged by common single nucleotide polymorphisms (SNPs) in the CHARGE consortium genome-wide association study (GWAS) of self-report sleep duration. We also used bivariate LD-score regression to investigate the genetic correlation of sleep duration with other publicly available GWAS datasets. Results: We show that 6% (SE = 1%) of the variance in self-report sleep duration in the CHARGE study is tagged by common SNPs in European populations. Furthermore, we find evidence of a positive genetic correlation (rG) between sleep duration and type 2 diabetes (rG = 0.26, P = 0.02), and between sleep duration and schizophrenia (rG = 0.19, P = 0.01). Conclusions: Our results show that increased sample sizes will identify more common variants for self-report sleep duration; however, the heritability tagged is small when compared to other traits and diseases. These results also suggest that those who carry variants that increase risk to type 2 diabetes and schizophrenia are more likely to report longer sleep duration

Molecular genetic overlap between posttraumatic stress disorder and sleep phenotypes

Study Objectives Sleep problems are common, serving as both a predictor and symptom of posttraumatic stress disorder (PTSD), with these bidirectional relationships well established in the literature. While both sleep phenotypes and PTSD are moderately heritable, there has been a paucity of investigation into potential genetic overlap between sleep and PTSD. Here, we estimate genetic correlations between multiple sleep phenotypes (including insomnia symptoms, sleep duration, daytime sleepiness, and chronotype) and PTSD, using results from the largest genome-wide association study (GWAS) to date of PTSD, as well as publicly available GWAS results for sleep phenotypes within UK Biobank data (23 variations, encompassing four main phenotypes). Methods Genetic correlations were estimated utilizing linkage disequilibrium score regression (LDSC), an approach that uses GWAS summary statistics to compute genetic correlations across traits, and Mendelian randomization (MR) analyses were conducted to follow up on significant correlations. Results Significant, moderate genetic correlations were found between insomnia symptoms (rg range 0.36–0.49), oversleeping (rg range 0.32–0.44), undersleeping (rg range 0.48–0.49), and PTSD. In contrast, there were mixed results for continuous sleep duration and daytime sleepiness phenotypes, and chronotype was not correlated with PTSD. MR analyses did not provide evidence for casual effects of sleep phenotypes on PTSD. Conclusion Sleep phenotypes, particularly insomnia symptoms and extremes of sleep duration, have shared genetic etiology with PTSD, but causal relationships were not identified. This highlights the importance of further investigation into the overlapping influences on these phenotypes as sample sizes increase and new methods to investigate directionality and causality become available

Seasonality Shows Evidence for Polygenic Architecture and Genetic Correlation With Schizophrenia and Bipolar Disorder

OBJECTIVE: To test common genetic variants for association with seasonality (seasonal changes in mood and behavior) and to investigate whether there are shared genetic risk factors between psychiatric disorders and seasonality. METHOD: Genome-wide association studies (GWASs) were conducted in Australian (between 1988 and 1990 and between 2010 and 2013) and Amish (between May 2010 and December 2011) samples in whom the Seasonal Pattern Assessment Questionnaire (SPAQ) had been administered, and the results were meta-analyzed in a total sample of 4,156 individuals. Genetic risk scores based on results from prior large GWAS studies of bipolar disorder, major depressive disorder (MDD), and schizophrenia were calculated to test for overlap in risk between psychiatric disorders and seasonality. RESULTS: The most significant association was with rs11825064 (P = 1.7 × 10⁻⁶, β = 0.64, standard error = 0.13), an intergenic single nucleotide polymorphism (SNP) found on chromosome 11. The evidence for overlap in risk factors was strongest for schizophrenia and seasonality, with the schizophrenia genetic profile scores explaining 3% of the variance in log-transformed global seasonality scores. Bipolar disorder genetic profile scores were also associated with seasonality, although at much weaker levels (minimum P value = 3.4 × 10⁻³), and no evidence for overlap in risk was detected between MDD and seasonality. CONCLUSIONS: Common SNPs of large effect most likely do not exist for seasonality in the populations examined. As expected, there were overlapping genetic risk factors for bipolar disorder (but not MDD) with seasonality. Unexpectedly, the risk for schizophrenia and seasonality had the largest overlap, an unprecedented finding that requires replication in other populations and has potential clinical implications considering overlapping cognitive deficits in seasonal affective disorders and schizophrenia

Genome-Wide Association Analyses in 128,266 Individuals Identifies New Morningness and Sleep Duration Loci

Disrupted circadian rhythms and reduced sleep duration are associated with several human diseases, particularly obesity and type 2 diabetes, but until recently, little was known about the genetic factors influencing these heritable traits. We performed genome-wide association studies of self-reported chronotype (morning/evening person) and self-reported sleep duration in 128,266 white British individuals from the UK Biobank study. Sixteen variants were associated with chronotype (P<5x10-8), including variants near the known circadian rhythm genes RGS16 (1.21 odds of morningness, 95% CI [1.15, 1.27], P = 3x10-12) and PER2 (1.09 odds of morningness, 95% CI [1.06, 1.12], P = 4x10-10). The PER2 signal has previously been associated with iris function. We sought replication using self-reported data from 89,283 23andMe participants; thirteen of the chronotype signals remained associated at P<5x10-8 on meta-analysis and eleven of these reached P<0.05 in the same direction in the 23andMe study. We also replicated 9 additional variants identified when the 23andMe study was used as a discovery GWAS of chronotype (all P<0.05 and meta-analysis P<5x10-8). For sleep duration, we replicated one known signal in PAX8 (2.6 minutes per allele, 95% CI [1.9, 3.2], P = 5.7x10-16) and identified and replicated two novel associations at VRK2 (2.0 minutes per allele, 95% CI [1.3, 2.7], P = 1.2x10-9; and 1.6 minutes per allele, 95% CI [1.1, 2.2], P = 7.6x10-9). Although we found genetic correlation between chronotype and BMI (rG = 0.056, P = 0.05); undersleeping and BMI (rG = 0.147, P = 1x10-5) and oversleeping and BMI (rG = 0.097, P = 0.04), Mendelian Randomisation analyses, with limited power, provided no consistent evidence of causal associations between BMI or type 2 diabetes and chronotype or sleep duration. Our study brings the total number of loci associated with chronotype to 22 and with sleep duration to three, and provides new insights into the biology of sleep and circadian rhythms in humans. © 2016 Jones et al.</p

Genetic studies of accelerometer-based sleep measures yield new insights into human sleep behaviour

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 −8 , of which 20 reach a stricter threshold of P < 8 × 10 −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. © 2019, The Author(s).</p

Genome-wide association analyses of chronotype in 697,828 individuals provides insights into circadian rhythms

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. © 2019, The Author(s).</p

Genetic variants in RBFOX3 are associated with sleep latency

Item does not contain fulltextTime to fall asleep (sleep latency) is a major determinant of sleep quality. Chronic, long sleep latency is a major characteristic of sleep-onset insomnia and/or delayed sleep phase syndrome. In this study we aimed to discover common polymorphisms that contribute to the genetics of sleep latency. We performed a meta-analysis of genome-wide association studies (GWAS) including 2 572 737 single nucleotide polymorphisms (SNPs) established in seven European cohorts including 4242 individuals. We found a cluster of three highly correlated variants (rs9900428, rs9907432 and rs7211029) in the RNA-binding protein fox-1 homolog 3 gene (RBFOX3) associated with sleep latency (P-values=5.77 x 10-08, 6.59 x 10-08 and 9.17 x 10-08). These SNPs were replicated in up to 12 independent populations including 30 377 individuals (P-values=1.5 x 10-02, 7.0 x 10-03 and 2.5 x 10-03; combined meta-analysis P-values=5.5 x 10-07, 5.4 × 10-07 and 1.0 x 10-07). A functional prediction of RBFOX3 based on co-expression with other genes shows that this gene is predominantly expressed in brain (P-value=1.4 x 10-316) and the central nervous system (P-value=7.5 x 10-321). The predicted function of RBFOX3 based on co-expression analysis with other genes shows that this gene is significantly involved in the release cycle of neurotransmitters including gamma-aminobutyric acid and various monoamines (P-values<2.9 x 10-11) that are crucial in triggering the onset of sleep. To conclude, in this first large-scale GWAS of sleep latency we report a novel association of variants in RBFOX3 gene. Further, a functional prediction of RBFOX3 supports the involvement of RBFOX3 with sleep latency.8 p