The heritability of insomnia: Systematic review and meta-analysis of twin studies

Functional MRI-based biomarkers of insomnia with objective short sleep duration phenotype

BACKGROUND

Insomnia disorder with objective short sleep duration (ISS) phenotype is a more serious biological subtype than insomnia with objective normal sleep duration (INS) phenotype, and the neuroimaging data is helpful to understand the pathophysiology of the ISS phenotype. This study was to compare the amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), and functional connectivity (FC) between the ISS phenotype and the INS phenotype.

METHODS

In this cross-sectional study, 55 patients with insomnia disorder were recruited, and 22 of them were defined as the ISS phenotype by the objective cardiopulmonary coupling (CPC) technique. The blood oxygen level-dependent (BOLD) sequences of all participants were obtained using the 3.0 T magnetic resonance imaging system. We analyzed and compared the ALFF, ReHo, and FC between the ISS phenotype and the INS phenotype. We also conducted Pearson's correlation analysis between significant neuroimaging biomarkers and the CPC parameters.

RESULTS

The differences were not significant in ALFF (PFWE-corr＞0.05) or ReHo (PFWE-corr＞0.05) between the ISS phenotype and the INS phenotype. For the FC analysis, the ISS phenotype had a Hub-node of the left inferior occipital gyrus (IOG.L), with significantly decreased connections (p＜0.001) in the bilateral occipital, parietal, and temporal regions. The significant FCs were closely related to sleep parameters.

CONCLUSION

The left inferior occipital gyrus (IOG.L), as a Hub-node with decreased functional connections, may be a potential fMRI-based biomarker of the ISS phenotype.

Disadvantaged social status contributed to sleep disorders: An observational and genome-wide gene-environment interaction analysis

BACKGROUND

Sleep is a natural and essential physiological need for individuals. Our study aimed to research the associations between accumulated social risks and sleep disorders.

METHODS

In this study, we came up with a polysocial risk score (PsRS), which is a cumulative social risk index composed of 13 social determinants of health. This research includes 239,165 individuals with sleep disorders and social determinants of health data from the UK Biobank cohort. First, logistic regression models were performed to examine the associations of social determinants of health and sleep disorders, including chronotype, narcolepsy, insomnia, snoring, short and long sleep duration. Then, PsRS was calculated based on statistically significant social determinants of health for each sleep disorder. Third, a genome-wide gene-environment interaction study was conducted to explore the interactions between single-nucleotide polymorphisms and PsRS in relation to sleep disorders.

RESULTS

Higher PsRS scores were associated with worse sleep status, with the adjusted odds ratio (OR) ranging from 1.10 (95% Confidence interval [CI]: 1.09-1.11) to 1.29 (95% CI: 1.27-1.30) for sleep disorders. Emotional stress (OR = 1.36, 95% CI: 1.28-1.43) and not in paid employment (OR = 2.62, 95% CI: 2.51-2.74) were found to have significant contributions for sleep disorders. Moreover, multiple single-nucleotide polymorphisms were discovered to have interactions with PsRS, such as FRAS1 (P = 2.57 × 10-14) and CACNA1A (P = 8.62 × 10-14) for narcolepsy, and ACKR3 (P = 1.24 × 10-8) for long sleep.

CONCLUSIONS

Our findings suggested that cumulative social risks was associated with sleep disorders, while the interactions between genetic susceptibility and disadvantaged social status are risk factors for the development of sleep disorders.

The interaction between polygenic risk and environmental influences: A direct test of the 3P model of insomnia in adolescents

BACKGROUND

Stress is a universal phenomenon and one of the most common precipitants of insomnia. However, not everyone develops insomnia after experiencing a stressful life event. This study aims to test aspects of Spielman's '3P model of insomnia' (during adolescence) by exploring the extent to which: (a) insomnia symptoms are predicted by polygenic scores (PGS); (b) life events predict insomnia symptoms; (c) the interaction between PGS and life events contribute to the prediction of insomnia symptoms; (d) gene-environment interaction effects remain after controlling for sex.

METHODS

The sample comprised 4,629 twins aged 16 from the Twin Early Development Study who reported on their insomnia symptoms and life events. PGS for insomnia were calculated. In order to test the main hypothesis of this study (a significant interaction between PGS and negative life events), we fitted a series of mixed effect regressions.

RESULTS

The best fit was provided by the model including sex, PGS for insomnia, negative life events, and their interactions (AIC = 26,158.7). Our results show that the association between insomnia symptoms and negative life events is stronger for those with a higher genetic risk for insomnia.

CONCLUSIONS

This work sheds light on the complex relationship between genetic and environmental factors implicated for insomnia. This study has tested for the first time the interaction between genetic predisposition (PGS) for insomnia and environmental stressors (negative life events) in adolescents. This work represents a direct test of components of Spielman's 3P model for insomnia which is supported by our results.

Linking genetic foundations of sleep disturbances to personality traits: a study of mid-life twins

Risk of sleep disturbances depends on individuals' personality, and a large body of evidence indicates that individuals prone to neuroticism, impulsivity, and (low) extraversion are more likely to experience them. Origins of these associations are unclear, but common genetic background may play an important role. Participants included 405 twin pairs (mean age of 54 years; 59% female) from the National Survey of Midlife Development in the United States (MIDUS) who reported on their personality traits (broad and specific), as well as sleep disturbances (problems with falling asleep, staying asleep, waking early, and feeling unrested). Uni- and bivariate biometric decompositions evaluated contributions of genetic and environmental factors to associations between personality and poor sleep, as well as unique contributions from individual traits. Neuroticism, extraversion, conscientiousness, and aggressiveness were the strongest phenotypic predictors of poor sleep. Genetic sources of covariance were about twice as large as non-shared environmental sources, and only shared genetic background accounted for links between aggressiveness and poor sleep. Neuroticism and extraversion accounted for most of the genetic overlap between personality and sleep disturbances. The findings shed light on developmental antecedents of ties between personality and poor sleep, suggesting a larger role of common genetic background than idiosyncratic life experiences. The results also suggest that emotion-related traits play the most important role for poor sleep, compared to other personality traits, and may partially account for genetic associations with other traits.

Potential genetic and epigenetic mechanisms in insomnia: A systematic review

Insomnia is a stress-related sleep disorder conceptualised within a diathesis-stress framework, which it is thought to result from predisposing factors interacting with precipitating stressful events that trigger the development of insomnia. Among predisposing factors genetics and epigenetics may play a role. A systematic review of the current evidence for the genetic and epigenetic basis of insomnia was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) system. A total of 24 studies were collected for twins and family heritability, 55 for genome-wide association studies, 26 about candidate genes for insomnia, and eight for epigenetics. Data showed that insomnia is a complex polygenic stress-related disorder, and it is likely to be caused by a synergy of genetic and environmental factors, with stress-related sleep reactivity being the important trait. Even if few studies have been conducted to date on insomnia, epigenetics may be the framework to understand long-lasting consequences of the interaction between genetic and environmental factors and effects of stress on the brain in insomnia. Interestingly, polygenic risk for insomnia has been causally linked to different mental and medical disorders. Probably, by treating insomnia it would be possible to intervene on the effect of stress on the brain and prevent some medical and mental conditions.

Sub-types of insomnia in adolescents: Insights from a quantitative/molecular twin study

Background

Insomnia with short sleep duration has been postulated as more severe than that accompanied by normal/long sleep length. While the short duration subtype is considered to have greater genetic influence than the other subtype, no studies have addressed this question. This study aimed to compare these subtypes in terms of: (1) the heritability of insomnia symptoms; (2) polygenic scores (PGS) for insomnia symptoms and sleep duration; (3) the associations between insomnia symptoms and a wide variety of traits/disorders.

Methods

The sample comprised 4000 pairs of twins aged 16 from the Twins Early Development Study. Twin models were fitted to estimate the heritability of insomnia in both groups. PGS were calculated for self-reported insomnia and sleep duration and compared among participants with short and normal/long sleep duration.

Results

Heritability was not significantly different in the short sleep duration group (A = 0.13 [95%CI = 0.01, 0.32]) and the normal/long sleep duration group (A = 0.35 [95%CI = 0.29, 0.40]). Shared environmental factors accounted for a substantial proportion of the variance in the short sleep duration group (C = 0.19 [95%CI = 0.05, 0.32]) but not in the normal/long sleep duration group (C = 0.00 [95%CI = 0.00, 0.04]). PGS did not differ significantly between groups although results were in the direction expected by the theory. Our results also showed that insomnia with short (as compared to normal/long) sleep duration had a stronger association with anxiety and depression (p < .05)-although not once adjusting for multiple testing.

Conclusions

We found mixed results in relation to the expected differences between the insomnia subtypes in adolescents. Future research needs to further establish cut-offs for 'short' sleep at different developmental stages and employ objective measures of sleep.

Behaviour genetics and sleep: A narrative review of the last decade of quantitative and molecular genetic research in humans

During the last decade quantitative and molecular genetic research on sleep has increased considerably. New behavioural genetics techniques have marked a new era for sleep research. This paper provides a summary of the most important findings from the last ten years, on the genetic and environmental influences on sleep and sleep disorders and their associations with health-related variables (including anxiety and depression) in humans. In this review we present a brief summary of the main methods in behaviour genetic research (such as twin and genome-wide association studies). We then discuss key research findings on: genetic and environmental influences on normal sleep and sleep disorders, as well as on the association between sleep and health variables (highlighting a substantial role for genes in individual differences in sleep and their associations with other variables). We end by discussing future lines of enquiry and drawing conclusions, including those focused on problems and misconceptions associated with research of this type. In this last decade our knowledge about genetic and environmental influences on sleep and its disorders has expanded. Both, twin and genome-wide association studies show that sleep and sleep disorders are substantially influenced by genetic factors and for the very first time multiple specific genetic variants have been associated with sleep traits and disorders.

Assessing the effect of interaction between lifestyle and longitudinal changes in brain structure on sleep phenotypes

Longitudinal changes in brain structure and lifestyle can affect sleep phenotypes. However, the influence of the interaction between longitudinal changes in brain structure and lifestyle on sleep phenotypes remains unclear. Genome-wide association study dataset of longitudinal changes in brain structure was obtained from published study. Phenotypic data of lifestyles and sleep phenotypes were obtained from UK Biobank cohort. Using genotype data from UK Biobank, we calculated polygenetic risk scores of longitudinal changes in brain structure phenotypes. Linear/logistic regression analysis was conducted to evaluate interactions between longitudinal changes in brain structure and lifestyles on sleep duration, chronotype, insomnia, snoring and daytime dozing. Multiple lifestyle × longitudinal changes in brain structure interactions were detected for 5 sleep phenotypes, such as physical activity×caudate_age2 for daytime dozing (OR = 1.0389, P = 8.84 × 10-3) in total samples, coffee intake×cerebellar white matter volume_age2 for daytime dozing (OR = 0.9652, P = 1.13 × 10-4) in females. Besides, we found 4 overlapping interactions in different sleep phenotypes. We conducted sex stratification analysis and identified one overlapping interaction between female and male. Our results support the moderate effects of interaction between lifestyle and longitudinal changes in brain structure on sleep phenotypes, and deepen our understanding of the pathogenesis of sleep disorders.

Effect of Familial Longevity on Frailty and Sarcopenia: A Case-Control Study

Familial longevity confers advantages in terms of health, functionality, and longevity. We sought to assess potential differences in frailty and sarcopenia in older adults according to a parental history of extraordinary longevity. A total of 176 community-dwelling subjects aged 65-80 years were recruited in this observational case-control study, pair-matched 1:1 for gender, age, and place of birth and residence: 88 centenarians' offspring (case group) and 88 non-centenarians' offspring (control group). The main variables were frailty and sarcopenia based on Fried's phenotype and the European Working Group on Sarcopenia in Older People (EWGSOP) definitions, respectively. Sociodemographics, comorbidities, clinical and functional variables, the presence of geriatric syndromes, and laboratory parameters were also collected. Related sample tests were applied, and conditional logistic regression was performed. Cases had a higher percentage of robust patients (31.8% vs. 15.9%), lower percentages of frailty (9.1% vs. 21.6%) and pre-frailty (59.1% vs. 62.5%) (p = 0.001), and lower levels of IL-6 (p = 0.044) than controls. The robust adjusted OR for cases was 3.00 (95% CI = 1.06-8.47, p = 0.038). No significant differences in muscle mass were found. Familial longevity was also associated with less obesity, insomnia, pain, and polypharmacy and a higher education level and total and low-density lipoprotein cholesterol. The results suggest an inherited genetic component in the frailty phenotype, while the sarcopenia association with familial longevity remains challenging.

Portability of Polygenic Risk Scores for Sleep Duration, Insomnia and Chronotype in 33,493 Individuals

Polygenic risk scores (PRSs) estimate genetic liability for diseases and traits. However, the portability of PRSs in sleep traits has remained elusive. We generated PRSs for self-reported insomnia, chronotype and sleep duration using summary data from genome-wide association studies (GWASs) performed in 350,000 to 697,000 European-ancestry individuals. We then projected the scores in two independent Finnish population cohorts (N = 33,493) and tested whether the PRSs were associated with their respective sleep traits. We observed that all the generated PRSs were associated with their corresponding traits (p < 0.05 in all cases). Furthermore, we found that there was a 22.2 min difference in reported sleep between the 5% tails of the PRS for sleep duration (p < 0.001). Our findings indicate that sleep-related PRSs show portability across cohorts. The findings also demonstrate that sleep measures using PRSs for sleep behaviors may provide useful instruments for testing disease and trait associations in cohorts where direct sleep parameters have not yet been measured.

Genetic evidence for a potential causal relationship between insomnia symptoms and suicidal behavior: a Mendelian randomization study

Insomnia and restless leg syndrome (RLS) are associated with increased risk for suicidal behavior (SB), which is often comorbid with mood or thought disorders; however, it is unclear whether these relationships are causal. We performed a two-sample Mendelian randomization study using summary-level genetic associations with insomnia symptoms and RLS against the outcomes of risk of major depressive disorder (MDD), bipolar disorder (BP), schizophrenia (SCZ), and SB. The inverse-variance weighted method was used in the main analysis. We performed replication and sensitivity analyses to examine the robustness of the results. We identified outcome cohorts for MDD (n = 170,756 cases/329,443 controls), BP (n = 20,352/31,358), SCZ (n = 69,369/236,642), SB-Cohort-2019 (n = 6569/14,996 all with MDD, BP or SCZ; and SB within individual disease categories), and SB-Cohort-2020 (n = 29,782/519,961). Genetically proxied liability to insomnia symptoms significantly associated with increased risk of MDD (odds ratio (OR) = 1.23, 95% confidence interval (CI) = 1.2-1.26, P = 1.37 × 10-61), BP (OR = 1.15, 95% CI = 1.07-1.23, P = 5.11 × 10-5), SB-Cohort-2019 (OR = 1.17, 95% CI = 1.07-1.27, P = 2.30 × 10-4), SB-Cohort-2019 in depressed patients (OR = 1.34, 95% CI = 1.16-1.54, P = 5.97 × 10-5), and SB-Cohort-2020 (OR = 1.24, 95% CI = 1.18-1.3, P = 1.47 × 10-18). Genetically proxied liability to RLS did not significantly influence the risk of any of the outcomes (all corrected P > 0.05). Results were replicated for insomnia with MDD and SB in Mass General Brigham Biobank and were consistent in multiple lines of sensitivity analyses. In conclusion, human genetic evidence supports for the first time a potentially independent and causal effect of insomnia on SB and encourages further clinical investigation of treatment of insomnia for prevention or treatment of SB.

Comparison of the Differences in State-Trait Anxiety Inventory Scores and Insomnia Histories between Monozygotic and Dizygotic Twins: A Cross-Sectional Study Using KoGES HTS Data

The heritability of anxiety and its association with insomnia have been suggested. This study investigated the coincidence of anxiety and insomnia in monozygotic twins compared to dizygotic twins. The Korean Genome and Epidemiology Study 2005–2014 was used. The ≥20-year-old cohort population was composed of 1300 twin participants. A total of 980 monozygotic twins and 232 dizygotic twins were compared for the concordance for the history of insomnia in both twin pairs (coincidence of insomnia) and the difference in state of anxiety and trait of anxiety scores. The odds ratios (ORs) for the coincidence of insomnia in monozygotic twins compared to dizygotic twins were analyzed using multiple logistic regression analysis. The estimated values (EV) of the difference of state and trait of anxiety scores were analyzed using a linear regression model. The coincidence of insomnia was not high in monozygotic twins compared to dizygotic twins. The difference in the state of anxiety score was comparable between monozygotic twins and dizygotic twins. However, the difference in anxiety scores was higher in dizygotic twins than in monozygotic twins. The monozygotic twin group did not demonstrate higher coincidence of insomnia or the state of anxiety than the dizygotic twin group. However, the monozygotic twin group indicated higher coincidence of the trait of anxiety than the dizygotic twins. The current results implied the potential contribution of heritable factors for the trait of anxiety.

Characterisation of the genetic relationship between the domains of sleep and circadian-related behaviours with substance use phenotypes

Sleep problems and substance use frequently co-occur. While substance use can result in specific sleep deficits, genetic pleiotropy could explain part of the relationship between sleep and substance use and use disorders. Here we use the largest publicly available genome-wide summary statistics of substance use behaviours (N = 79,729-632,802) and sleep/activity phenotypes to date (N = 85,502-449,734) to (1) assess the genetic overlap between substance use behaviours and both sleep and circadian-related activity measures, (2) estimate clusters from genetic correlations and (3) test processes of causality versus genetic pleiotropy. We found 31 genetic correlations between substance use and sleep/activity after Bonferroni correction. These patterns of overlap were represented by two genetic clusters: (1) tobacco use severity (age of first regular tobacco use and smoking cessation) and sleep health (sleep duration, sleep efficiency and chronotype) and (2) substance consumption/problematic use (drinks per day and cigarettes per day, cannabis use disorder, opioid use disorder and problematic alcohol use) and sleep problems (insomnia, self-reported short sleep duration, increased number of sleep episodes, increased sleep duration variability and diurnal inactivity) and measures of circadian-related activity (L5, M10 and sleep midpoint). Latent causal variable analyses determined that horizontal pleiotropy (rather than genetic causality) underlies a majority of the associations between substance use and sleep/circadian related measures, except one plausible genetically causal relationship for opioid use disorder on self-reported long sleep duration. Results show that shared genetics are likely a mechanism that is at least partly responsible for the overlap between sleep and substance use traits.

Genome-Wide Association Study and Genetic Correlation Scan Provide Insights into Its Genetic Architecture of Sleep Health Score in the UK Biobank Cohort

PURPOSE

Most previous genetic studies of sleep behaviors were conducted individually, without comprehensive consideration of the complexity of various sleep behaviors. Our aim is to identify the genetic architecture and potential biomarker of the sleep health score, which more powerfully represents overall sleep traits.

PATIENTS AND METHODS

We conducted a genome-wide association study (GWAS) of sleep health score (overall assessment of sleep duration, snoring, insomnia, chronotype, and daytime dozing) using 336,463 participants from the UK Biobank. Proteome-wide association study (PWAS) and transcriptome-wide association study (TWAS) were then performed to identify candidate genes at the protein and mRNA level, respectively. We finally used linkage disequilibrium score regression (LDSC) to estimate the genetic correlations between sleep health score and other functionally relevance traits.

RESULTS

GWAS identified multiple variants near known candidate genes associated with sleep health score, such as MEIS1, FBXL13, MED20 and SMAD5. HDHD2 (PPWAS = 0.0146) and GFAP (PPWAS = 0.0236) were identified associated with sleep health score by PWAS. TWAS identified ORC4 (PTWAS = 0.0212) and ZNF732 (PTWAS = 0.0349) considering mRNA expression level. LDSC found significant genetic correlations of sleep health score with 3 sleep behaviors (including insomnia, snoring, dozing), 4 psychiatry disorders (major depressive disorder, attention deficit/hyperactivity disorder, schizophrenia, autism spectrum disorder), and 9 plasma protein (such as Stabilin-1, Stromelysin-2, Cytochrome c) (all LDSC PLDSC < 0.05).

CONCLUSION

Our results advance the comprehensive understanding of the aetiology and genetic architecture of the sleep health score, refine the understanding of the relationship of sleep health score with other traits and diseases, and may serve as potential targets for future mechanistic studies of sleep phenotype.

Heritability of Sleep and Its Disorders in Childhood and Adolescence

Purpose of Review

This review summarizes recent literature on the heritability of sleep and sleep disorders in childhood and adolescence. We also identify gaps in the literature and priorities for future research.

Recent Findings

Findings indicate that age, measurement method, reporter, and timing of sleep measurements can influence heritability estimates. Recent genome-wide association studies (GWAS) have identified differences in the heritability of sleep problems when ancestral differences are considered, but sample sizes are small compared to adult GWAS. Most studies focus on sleep variables in the full range rather than on disorder. Studies using objective measures of sleep typically comprised small samples.

Summary

Current evidence demonstrates a wide range of heritability estimates across sleep phenotypes in childhood and adolescence, but research in larger samples, particularly using objective sleep measures and GWAS, is needed. Further understanding of environmental mechanisms and the interaction between genes and environment is key for future research.