Person:

Tiemeier, Henning

Objectives. The study has three main objectives: 1) to obtain reliable reference charts for sleep duration; 2) estimate the prevalence of sleep complaints in the general population across the lifespan; and 3) to identify risk indicators of poor sleep. Design. Systematic review and meta-analysis of individual participant data (IPD). Data sources. Studies identified through systematic literature search in Embase, Medline and Web of Science (August 9th 2019), and through personal contacts with colleagues in the UK and US. Eligibility criteria. Studies eligible for IPD meta-analysis had to be published between 2000 and 2017 with data on sleep characteristics assessed with questionnaires that sampled ≥100 participants from the general population of the Netherlands. Large population-based studies/surveys from UK and US were included for comparisons. Data synthesis. For IPD analysis, data were obtained for 36 out of 47 eligible studies. Two researchers independently coded sleep variables: (time in bed (TIB), sleep duration (Total Sleep Time, TST), sleep efficiency (TST/TIB*100)), self/caregiver-reported sleep quality, insomnia symptoms and other sleep complaints, as well as socio-demographic characteristics (sex, age, education, ethnic origin, employment and partnership status) and health risk indicators (smoking and body mass index). All variables were coded following a standardized protocol. For comparison, complementary sleep data from the UK Biobank and the National Health Interview Survey in the USA were included. Where available, actigraphic sleep estimates were obtained using validated algorithms. Results. We assembled IPD from 200,358 persons (age range 1-100 years, 55% female) from the Netherlands, 471,759 persons (40 to 69 years old, 55.5% female) from the UK, and 409,617 persons (≥18 years, 55.8% female) from the US. Age-specific percentile curves for TST demonstrate that overall 24.5% of the studied population slept less than age-specific recommendations, but only 5.8% slept outside of the “acceptable range” for sleep duration. Short sleep duration was most prevalent in teenagers, as 51.5% reported TST less than the recommended 8-10 hours and 18% report daytime sleepiness. In adults (≥18yrs), poor sleep quality (13.3%) and insomnia symptoms (9.6-19.4%) were more prevalent than short sleep duration (6.5% with TST<6 hours). Insomnia symptoms were least frequent in 26-to-40-year-olds and most frequent in persons aged >65 years, and those spending 9 or more hours in bed. Poor sleep quality was most common in those spending <6 hours in bed. Women, persons of non-European origin, overweight persons and smokers were more prone to poor sleep. While habitual TST was similar in the different countries, insomnia symptoms were between 1.5 to 2.9 times higher in USA than in the Netherlands. Women (41+) reported sleeping shorter or slightly less efficient than men, which was opposite to actigraphy estimates where women were estimated to sleep longer and more efficiently than man, both in the UK and in the Netherlands. Conclusion. In the largest descriptive sleep study to date, we provide age- and sex-specific population reference charts for sleep duration and efficiency which can be used in research, clinical and preventive in industrialized countries. More people report poor sleep quality than short sleep duration. Thus, whereas most available guidelines address optimal sleep duration, our findings highlight the importance of also targeting sleep quality.

Characterising genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. Here we describe results of DNA methylation-quantitative trait loci (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTL of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We reveal that the genetic architecture of DNAm levels is highly polygenic and DNAm exhibits signatures of negative and positive natural selection. Using shared genetic control between distal DNAm sites we construct networks, identifying discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic factors are associated with both DNAm levels and complex diseases but only in a minority of cases these associations reflect direct causal relationships from DNAm to trait or vice versa indicating a more complex genotype-phenotype map than previously anticipated.

Minimal phenotyping refers to the reliance on the use of a small number of self-report items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined Major Depressive Disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases, and a higher proportion of the genome contributing to this shared genetic liability with other conditions than strictly-defined MDD. GWAS on minimal phenotyping definitions identify loci that are not specific to MDD, and though it can generate highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than specificity for MDD. Our results reveal reliance on results from minimal phenotyping may bias our views of the genetic architecture of MDD and impede our ability to identify pathways specific to MDD.