Concordance in parent-child and sibling actigraphy-measured sleep: Evidence among early adolescent twins and primary caregivers

STUDY OBJECTIVES

Growing evidence suggests concordance between parent and youth sleep. However, no known study has simultaneously examined concordance among siblings' sleep patterns. This study investigated daily and average concordance in (1) parent-youth and (2) sibling actigraphy-measured sleep, as well as the degree to which sibling concordance varied by sleeping arrangements.

METHODS

516 twin siblings (Mage = 10.74, 51% female; 30% monozygotic (MZ) twin pairs, 37% same-sex dizygotic pairs (DZ-ss), 33% opposite-sex DZ pairs (DZ-os)) and their primary caregivers (Mage = 40.59, 95% female) wore wrist-based accelerometers for 7 consecutive nights to measure sleep duration, efficiency, midpoint time, and latency. Primary caregivers also reported on demographics, youth pubertal status, and room-sharing. Two-level multilevel models were estimated to examine daily and average concordance in parent-youth and sibling sleep.

RESULTS

Daily concordance was observed between parent and youth sleep duration and midpoint; average concordance was found for sleep duration, midpoint, and latency. Within sibling dyads, daily and average concordance was evident across all sleep parameters (duration, efficiency, midpoint, latency), with generally stronger concordance patterns for MZ than DZ twin pairs, and for twins who shared a room with their co-twin.

CONCLUSIONS

This is the first known study to document concordance among parent-youth and siblings' actigraphy-measured sleep within the same study (i.e., triad). Our findings can help inform the development of family-level interventions targeting daily and overall sleep hygiene.

Sex differences in sleep quality and psychological distress: Insights from a middle-aged twin sample from Spain

There is a moderate association between poor sleep and psychological distress. There are marked sex differences in the prevalence of both variables, with females outnumbering males. However, the origin of these sex differences remains unclear. The objectives of this study were to: (1) study genetic and environmental influences on the relationship between poor sleep quality and psychological distress; and (2) test possible sex differences in this relationship. The sample comprised 3544 participants from the Murcia Twin Registry. Univariate and multivariate twin models were fitted to estimate the magnitude of genetic and environmental influences on both individual variance and covariance between poor sleep quality and psychological distress. Sleep quality and psychological distress were measured using the Pittsburgh Sleep Quality Index and the EuroQol five-dimensions questionnaire, respectively. The results reveal a strong genetic association between poor sleep quality and psychological distress, which accounts for 44% (95%CI: 27%-61%) of the association between these two variables. Substantial genetic (rA = 0.50; 95%CI: 0.32, 0.67) and non-shared environmental (rE = 0.41; 95%CI: 0.30, 0.52) correlations were also found, indicating a moderate overlap between genetic (and non-shared environmental) factors influencing both phenotypes. Equating sexes in sex-limitation models did not result in significant decreases in model fit. Despite the remarkable sex differences in the prevalence of both poor sleep quality and psychological distress, there were no sex differences in the genetic and environmental influences on these variables. This suggests that genetic factors play a similar role for men and women in explaining individual differences in both phenotypes and their relationship.

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.

Sleep quality among inpatients of Spanish public hospitals

Sleep is a complex process and is needed both in health and illness. Deprivation of sleep is known to have multiple negative physiological effects on people's bodies and minds. Despite the awareness of these harmful effects, previous studies have shown that sleep is poor among hospitalised patients. We utilized an observational design with 343 patients recruited from medical and surgical units in 12 hospitals located in nine Spanish regions. Sociodemographic and clinical characteristics of patients were collected. Sleep quality at admission and during hospitalisation was measured by the Pittsburgh Sleep Quality Index. Sleep quantity was self-reported by patients in hours and minutes. Mean PSQI score before and during hospitalisation were respectively 8.62 ± 4.49 and 11.31 ± 4.04. Also, inpatients slept about an hour less during their hospital stay. Lower educational level, sedative medication intake, and multi-morbidity was shown to be associated with poorer sleep quality during hospitalisation. A higher level of habitual physical activity has shown to correlate positively with sleep quality in hospital. Our study showed poor sleep quality and quantity of inpatients and a drastic deterioration of sleep in hospital versus at home. These results may be helpful in drawing attention to patients' sleep in hospitals and encouraging interventions to improve sleep.

Phenotypic, Genetic and Environmental Architecture of the Components of Sleep Quality

The genetic and environmental underpinnings of sleep quality have been widely investigated. However, less is known about the etiology of the different sleep quality components and their associations. Subjective sleep quality has been studied most commonly using the Pittsburgh Sleep Quality Index (PSQI). Therefore, this work aimed to study the structure of sleep quality dimensions in a population-based twin sample by examining the etiology of the associations among the PSQI components themselves and between them. The sample comprised 2129 participants from the Murcia Twin Registry. In order to study the phenotypic, genetic and environmental structure of the PSQI we used three alternative multivariate twin models including all seven sub-scales of the PSQI (subjective sleep quality, latency, duration, efficiency, disturbances, use of sleeping medication and daytime dysfunction): a multivariate model (with seven separate correlated factors), a common pathway model and an independent pathway model. The multivariate correlated factors model showed the best fit to the data. All twin models indicated significant genetic overlap among most of the PSQI components, except daytime dysfunction and use of sleep medication. Bivariate heritability explained between 25 and 50% of the covariance for most associations between dimensions. Furthermore, the common pathway model showed that around one third of the variance (0.32; CI 95% 0.18.0.43) of a latent factor common to all questionnaire dimensions is explained by genetic factors. Genetic influences on a latent factor common to all questionnaire dimensions produced the same heritability estimates as the PSQI global score. However, sleep quality dimensions showed considerable specificity regarding its genetic-environmental structure.

Nature and nurture. Genetic and environmental factors on the relationship between back pain and sleep quality

BACKGROUND

Chronic low back pain (LBP), neck pain (NP), and sleep quality (SQ) are genetically influenced. All three conditions frequently co-occur and shared genetic etiology on a pairwise base has been reported. However, to our knowledge no study has yet investigated if these three conditions are influenced by the same genetic and environmental factors and the extent and pattern of genetic overlap between them, hence the current research.

METHODS

The sample included 2134 participants. Lifetime prevalence of NP and LBP were assessed through a dichotomous self-reported question derived from the Spanish National Health Survey. SQ was measured using the Pittsburgh Sleep Quality Index Questionnaire. A common pathway model with sleep quality and back pain as latent factors was fitted.

RESULTS

Our results highlight that a latent back pain factor, including both NP and LBP, is explained by both genetic (41%) and environmental (59%) factors. There are also significant unique environmental factors for NP (33%) and LBP (37%) respectively. Yet, specific genetic factors were scant (9%) for NP and negligible for LBP (0%). Genetic and environmental factors affecting SQ only contribute with 3% and 5% of the variance, respectively, to the common latent back pain variable.

CONCLUSIONS

NP and LBP share most of their genetic variance, while environmental effects show greater specificity for each of the back pain locations. Associations with SQ were of a limited magnitude.

Assessing the joint effects of brain aging and gut microbiota on the risks of psychiatric disorders

We aim to explore the potential interaction effects of brain aging and gut microbiota on the risks of sleep, anxiety and depression disorders. The genome-wide association study (GWAS) datasets of brain aging (N = 21,407) and gut microbiota (N = 3,890) were obtained from published studies. Individual level genotype and phenotype data of psychiatric traits (including sleep, anxiety and depression) were all from the UK Biobank (N = 107,947-374,505). We first calculated the polygenic risk scores (PRS) of 62 brain aging modes and 114 gut microbiota taxa as the instrumental variables, and then constructed linear and logistic regression analyses to systematically explore the potential interaction effects of brain aging and gut microbiota on psychiatric disorders. We observed the interaction effects of brain aging and gut microbiota on sleep, anxiety and depression disorders, such as Putamen/caudate T2* vs. Rhodospirillales (β = -0.012, P = 8.4 × 10^-4) was negatively associated with chronotype, Fornix MD vs. Holdemanella (β = -0.007, P = 1.76 × 10^-2) was negatively related to general anxiety disorder (GAD) scores, and White matter lesions vs. Acidaminococcaceae (β = 0.019, P = 1.29 × 10^-3) was positively correlated with self-reported depression. Interestingly, Putamen volume vs. Intestinibacter was associated with all three psychiatric disorders, including chronotype (negative correlation), GAD scores (positive correlation) and self-reported depression (positive correlation). Our study results suggest the significant impacts of brain aging and gut microbiota on the development of sleep, anxiety and depression disorders, providing new clues for clarifying the pathogenesis of these disorders.

Genetic versus stress and mood determinants of sleep in the Amish

Sleep is essential to the human brain and is regulated by genetics with many features conserved across species. Sleep is also influenced by health and environmental factors; identifying replicable genetic variants contributing to sleep may require accounting for these factors. We examined how stress and mood disorder contribute to sleep and impact its heritability. Our sample included 326 Amish/Mennonite individuals with a lifestyle with limited technological interferences with sleep. Sleep measures included Pittsburgh Sleep Quality Index (PSQI), bedtime, wake time, and time to sleep onset. Current stress level, cumulative life stressors, and mood disorder were also evaluated. We estimated the heritability of sleep features and examined the impact of current stress, lifetime stress, mood diagnosis on sleep quality. The results showed current stress, lifetime stress, and mood disorder were independently associated with PSQI score (p < .05). Heritability of PSQI was low (0-0.23) before and after accounting for stress and mood. Bedtime, wake time, and minutes to sleep time did show significant heritability at 0.44, 0.42, and 0.29. However, after adjusting for shared environment, only heritability of wake time remained significant. Sleep is affected by environmental stress and mental health factors even in a society with limited technological interference with sleep. Wake time may be a more biological marker of sleep as compared to the evening measures which are more influenced by other household members. Accounting for nongenetic and partially genetic determinants of sleep particularly stress and mood disorder is likely important for improving the precision of genetic studies of sleep.

Heritability of sleep duration and quality: A systematic review and meta-analysis

Epidemiological and interventional research has highlighted sleep as a potentially modifiable risk factor associated with poor physical and mental health. Emerging evidence from (behavioral) genetic research also shows that sleep characteristics are under strong genetic control. With this study we aimed to meta-analyze the literature in this area to quantify the heritability of sleep duration and sleep quality in the general population. We conducted a systematic literature search in five online databases on January 24th 2020. Two authors independently screened 5644 abstracts, and 160 complete articles for the inclusion criteria of twin studies from the general population reporting heritability statistics on sleep duration and/or quality, and written in English. We ultimately included 23 papers (19 independent samples: 45,328 twins between 6 mo and 88 y) for sleep duration, and 13 papers (10 independent samples: 39,020 twins between 16 and 95 y) for sleep quality. Collectively, we showed that 46% of the variability in sleep duration and 44% of the variability in sleep quality is genetically determined. The remaining variation in the sleep characteristics can mostly be attributed to the unique environment the twins experience, although the shared environment seemed to play a role for the variability of childhood sleep duration. Meta-analyzed heritability estimates for sleep duration, however, varied substantially with age (17% infancy, 20-52% childhood, 69% adolescence and 42-45% adulthood) and reporter (8% parent-report, 38-52% self-report). Heritability estimates for actigraphic and Polysomnography (PSG)-estimated sleep were based on few small samples, warranting more research. Our findings highlight the importance of considering genetic influences when aiming to understand the underlying mechanisms contributing to the trajectories of sleep patterns across the lifespan.

Sleep quality and chronic neck pain: a cotwin study

STUDY OBJECTIVES

Sleep quality and chronic neck pain (NP) are associated. However, the genetic influences on this association have not been explored. This study investigated the genetic and environmental influences on the association between sleep quality and chronic NP.

METHODS

The sample comprised 2,328 individual twins from the Murcia Twin Registry (Spain). A bidirectional cotwin logistic regression analysis was performed (sleep quality assessed as the exposure and chronic NP as the outcome and vice versa). Analysis included 2 sequential stages: total sample analysis and within-pair twin case-control analysis.

RESULTS

Sleep quality was significantly associated with chronic NP in the total sample analysis (adjusted odds ratio [OR]: 1.09; 95% confidence interval [CI]: 1.06, 1.12; P < .001); in the cotwin case-control analysis, including both monozygotic and dizygotic twin pairs (adjusted OR: 1.10; 95% CI: 1.04, 1.17; P = .001); in dizygotic pairs (Adjusted OR: 1.11; 95% CI: 1.03, 1.19; P = .005); but not in monozygotic pairs (adjusted OR: 1.08; 95% CI: 0.98, 1.19; P = .118). Chronic NP was significantly associated with poor sleep quality in the total sample analysis (adjusted OR: 1.80; 95% CI: 1.43, 2.26; P < .001); in the cotwin case-control analysis, including both monozygotic and dizygotic twin pairs (Adjusted OR: 1.63; 95% CI: 1.07, 2.47; P = .023); in dizygotic pairs (Adjusted OR: 1.80; 95% CI: 1.05, 3.09; P = .031), but not in monozygotic pairs (adjusted OR: 1.67; 95% CI: 0.80, 3.48; P = .170).

CONCLUSIONS

The association between sleep quality and chronic NP is partially confounded by genetic factors.

The interrelation of sleep and mental and physical health is anchored in grey-matter neuroanatomy and under genetic control

Humans need about seven to nine hours of sleep per night. Sleep habits are heritable, associated with brain function and structure, and intrinsically related to well-being, mental, and physical health. However, the biological basis of the interplay of sleep and health is incompletely understood. Here we show, by combining neuroimaging and behavioral genetic approaches in two independent large-scale datasets (HCP (n = 1106), age range: 22-37, eNKI (n = 783), age range: 12-85), that sleep, mental, and physical health have a shared neurobiological basis in grey matter anatomy; and that these relationships are driven by shared genetic factors. Though local associations between sleep and cortical thickness were inconsistent across samples, we identified two robust latent components, highlighting the multivariate interdigitation of sleep, intelligence, BMI, depression, and macroscale cortical structure. Our observations provide a system-level perspective on the interrelation of sleep, mental, and physical conditions, anchored in grey-matter neuroanatomy.

Relationship between subjective well-being and healthy lifestyle behaviours in older adults: a longitudinal study

Objectives: People who report better subjective well-being tend to be healthier in their daily behaviours. The objective of this study is to assess whether different components of subjective well-being are prospectively associated with different healthy lifestyle behaviours and to assess whether these associations differ by age.Method: A total of 1,892 participants aged 50+ living in Spain were interviewed in 2011-12 and 2014-15. Life satisfaction was measured with the Cantril Self-Anchoring Striving Scale. Positive and negative affect were assessed using the Day Reconstruction Method. Physical activity was assessed with the Global Physical Activity Questionnaire version 2. The remaining healthy lifestyle behaviours were self-reported. Generalised Estimating Equations (GEE) models were run.Results: Not having a heavy episodic alcohol drinking was the healthy lifestyle behaviour most fulfilled (97.97%), whereas the intake of five or more fruits and vegetables was the least followed (33.12%). GEE models conducted over the 50-64 and the 65+ age groups showed that a higher life satisfaction was significantly related to a higher physical activity in both groups. Relationships between a higher negative affect and presenting a lower level of physical activity, and a higher positive affect and following the right consumption of fruits and vegetables and being a non-daily smoker, were only found in the older group.Conclusion: The relationship between subjective well-being and healthy lifestyle behaviours was found fundamentally in those aged 65+ years. Interventions focused on incrementing subjective well-being would have an impact on keeping a healthy lifestyle and, therefore, on reducing morbidity and mortality.

Sleep quality, insomnia, and internalizing difficulties in adolescents: insights from a twin study

Study Objectives

There is a well-established association between poor sleep quality and internalizing traits. This relationship has previously been studied using a twin design. However, when it comes to adolescence, there is a paucity of twin studies that have investigated this relationship, despite the importance of this developmental stage for both the development of poor sleep quality and internalizing symptoms. Additionally, anxiety sensitivity, which is commonly associated with poor sleep quality, has not been studied in this context. Our objective was to estimate genetic and environmental influences on the relationships between insomnia, poor sleep quality, and internalizing symptoms in adolescence.

Methods

Insomnia, poor sleep quality, depression, anxiety, and anxiety sensitivity traits were measured in a sample of 5111 twin pairs from the Twins Early Development Study, born between 1994 and 1996 (mean age 16.32 years [SD = 0.68]).

Results

A moderate proportion of the variance for the different variables (.29–.42) was explained by genetic factors. Associations between sleep and internalizing variables were moderate (r = .34–.46) and there was a large genetic overlap between these variables (rA= .51–.73).

Conclusion

This study adds novel information by showing that there are large genetic correlations between sleep disturbances and internalizing symptoms in adolescence.

An Update of Twin Research in Spain: The Murcia Twin Registry

The Murcia Twin Registry (MTR) is the only population-based registry in Spain. Created in 2006, the registry has been growing more than a decade to become one of the references for twin research in the Mediterranean region. The MTR database currently comprises 3545 adult participants born between 1940 and 1977. It also holds a recently launched satellite registry of university students (N = 204). Along five waves of data collection, the registry has gathered questionnaire and anthropometric data, as well as biological samples. The MTR keeps its main research focus on health and health-related behaviors from a public health perspective. This includes lifestyle, health promotion, quality of life or environmental conditions. Future short-term development points to the expansion of the biobank and the continuation of the collection of longitudinal data.