Genome-Wide and Abdominal MRI-Imaging Data Provides Evidence that a Genetically Determined Favourable Adiposity Phenotype is Characterized by Lower Ectopic Liver Fat and Lower Risk of Type 2 Diabetes, Heart Disease and Hypertension

Recent genetic studies have identified alleles associated with opposite effects on adiposity and risk of type 2 diabetes. We aimed to identify more of these variants and test the hypothesis that such “favourable adiposity” alleles are associated with higher subcutaneous fat and lower ectopic fat. We combined magnetic resonance imaging (MRI) data with genome-wide association studies (GWAS) of body fat % and metabolic traits. We report 14 alleles, including 7 newly characterized alleles, associated with higher adiposity, but a favourable metabolic profile. Consistent with previous studies, individuals carrying more “favourable adiposity” alleles had higher body fat % and higher BMI, but lower risk of type 2 diabetes, heart disease and hypertension. These individuals also had higher subcutaneous fat, but lower liver fat and lower visceral-to-subcutaneous adipose tissue ratio. Individual alleles associated with higher body fat % but lower liver fat and lower risk of type 2 diabetes included those in PPARG, GRB14 and IRS1, whilst the allele in ANKRD55 was paradoxically associated with higher visceral fat but lower risk of type 2 diabetes. Most identified “favourable adiposity” alleles are associated with higher subcutaneous and lower liver fat, a mechanism consistent with the beneficial effects of storing excess triglyceride in metabolically low risk depots.Diabetes UK RD Lawrence fellowship, European Research Council, Wellcome Trust and Royal Society grant, European Regional Development Fund, Medical Research Council, German Federal Ministry of Education and Research, German Research Foundation, Innovative Medicines Initiative Joint Undertaking, European Union's Seventh Framework Programme, Dutch Science Organisation, Scottish Government Health Directorates, Scottish Funding Council and Medical Research Council UK and the Wellcome Trust

The search for circadian clock components in humans: new perspectives for association studies

Individual circadian clocks entrain differently to environmental cycles (zeitgebers, e.g., light and darkness), earlier or later within the day, leading to different chronotypes. In human populations, the distribution of chronotypes forms a bell-shaped curve, with the extreme early and late types _ larks and owls, respectively _ at its ends. Human chronotype, which can be assessed by the timing of an individual's sleep-wake cycle, is partly influenced by genetic factors - known from animal experimentation. Here, we review population genetic studies which have used a questionnaire probing individual daily timing preference for associations with polymorphisms in clock genes. We discuss their inherent limitations and suggest an alternative approach combining a short questionnaire (Munich ChronoType Questionnaire, MCTQ), which assesses chronotype in a quantitative manner, with a genome-wide analysis (GWA). The advantages of these methods in comparison to assessing time-of-day preferences and single nucleotide polymorphism genotyping are discussed. In the future, global studies of chronotype using the MCTQ and GWA may also contribute to understanding the influence of seasons, latitude (e.g., different photoperiods), and climate on allele frequencies and chronotype distribution in different populations

Chronotype and sleep duration: The influence of season of assessment.

Little is known about human entrainment under natural conditions, partly due to the complexity of human behavior, torn between biological and social time and influenced by zeitgebers (light-dark cycles) that are progressively "polluted" (and thereby weakened) by artificial light. In addition, data about seasonal variations in sleep parameters are scarce. We, therefore, investigated seasonal variation in cross-sectional assessments of sleep/wake times of 9765 subjects from four European populations (EGCUT = Estonian Genome Centre, University of Tartu in Estonia; KORA = Cooperative Health Research in the Region of Augsburg in Germany; KORCULA = The Korcula study in Croatia; and ORCADES = The Orkney Complex Disease Study in Scotland). We identified time-of-year dependencies for the distribution of chronotype (phase of entrainment assessed as the mid-sleep time point on free days adjusted for sleep deficit of workdays) in cohorts from Estonia (EGCUT) and Germany (KORA). Our results indicate that season (defined as daylight saving time - DST and standard zonetime periods - SZT) specifications of photoperiod influence the distribution of chronotype (adjusted for age and sex). Second, in the largest investigated sample, from Estonia (EGCUT; N = 5878), we could detect that seasonal variation in weekly average sleep duration was dependent on individual chronotype. Later chronotypes in this cohort showed significant variation in their average sleep duration across the year, especially during DST (1 h advance in social time from the end of March to end of October), while earlier chronotypes did not. Later chronotypes not only slept less during the DST period but the average chronotype of the population assessed during this period was earlier than during the SZT (local time for a respective time zone) period. More in detail, hierarchical multiple regression analyses showed that, beyond season of assessment (DST or SZT), social jetlag (SJl; the discrepancy between the mid sleep on free and work days - which varied with age and sex) contributed to a greater extent to the variation in sleep duration than chronotype (after taking into account factors that are known to influence sleep duration, i.e. age, sex and body mass index). Variation in chronotype was also dependent on age, sex, season of assessment and SJl (which is highly correlated with chronotype - SJl was larger among later chronotypes). In summary, subjective assessments of sleep/wake times are very reliable to assess internal time and sleep duration (e.g. reproducing sleep duration and timing tendencies related to age and sex across the investigated populations), but season of assessment should be regarded as a potential confounder. We identified in this study photoperiod (seasonal adaptation) and SJl as two main factors influencing seasonal variation in chronotype and sleep duration. In conclusion, season of assessment, sex and age have an effect on epidemiological variation in sleep duration, chronotype and SJl, and should be included in studies investigating associations between these phenotypes and health parameters, and on the development of optimal prevention strategies

Investigating the lipodystrophy genetic score associations with insulin sensitivity, ectopic and visceral fat in people at risk or with diabetes: a DIRECT study

Molecular Epidemiolog

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

Genetic variants in RBFOX3 are associated with sleep latency

Time 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 × 10-08, 6.59 × 10- 08 and 9.17 × 10- 08). These SNPs were replicated in up to 12 independent populations including 30 377 individuals (P-values=1.5 × 10- 02, 7.0 × 10- 03 and 2.5 × 10- 03; combined meta-analysis P-values=5.5 × 10-07, 5.4 × 10-07 and 1.0 × 10-07). A functional prediction of RBFOX3 base