Biology subjects

Tiemeier, H.

Publications and source records attributed to Tiemeier, H..

18 recordsLinked to original sources

bioRxiv2026

Development of a microRNA clock for gestational age in the general population

IntroductionDNA methylation (DNAm) has shown promise as a biological marker of gestational age (GA). Here, we aimed to characterize how plasma circulating miRNAs - another epigenetic mechanism regulating gene expression - associate with GA at birth, and to construct a miRNA-based GA clock (miRClock-GA). MethodsWe leveraged 2083 umbilical cord plasma-derived circulating miRNAs from Generation R (N=1695). First, we performed linear regressions to identify miRNome-wide significant miRNAs associated with GA. Second, we applied elastic net regression to construct miRClock-GA. These steps were validated in Gen3G (N=213). Finally, we computed age acceleration (miRClock-AA) and evaluated association of miRClock-GA and miRClock-AA with child developmental outcomes up to 17 years of age, including comparisons with DNAmClocks. FindingsWe identified 123 miRNAs associated with GA, with miR-150-5p showing the strongest positive association ( B=0.244, SE=0.036, P=2.3e-11) and miR-373-3p the strongest negative association ( B=-0.255, SE=0.065, P=8.6e-5). MiRClock-GA correlated consistently with GA in Generation R train (rrange=0.62-0.72) and test sets (rrange=0.45-0.52) and in the independent validation cohort (rGen3G =0.33). Correlations between miRClock-GA and DNAmClocks were weak to moderate (rrange=0.28-0.42). MiRClock-AA explained significant variance in birthweight and childhood BMI beyond clinical GA. ConclusionsThis study reveals widespread associations between circulating miRNAs and GA, supports miRClock-GA as a consistent, well-performing biological marker of GA, with miRClock-AA predicting birthweight and childhood BMI beyond GA itself. Our findings provide a broader perspective on the potential utility of miRNAs as early markers of development. FundingE.U. Horizon Europe Research and Innovation Programme (FAMILY,No.101057529); European Research Council (TEMPO,No.101039672). Full funding in Acknowledgements. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSEpigenetic clocks have emerged as powerful tools for assessing individual differences in biological ageing. Existing epigenetic clocks are typically constructed using DNA methylation (DNAm) data and are developed to estimate whether an individuals epigenetic age deviates relative to their chronological age. In adults, higher predicted biological epigenetic age than chronological age (accelerated epigenetic ageing) is an established indicator of mortality risk and other age-related morbidities. MicroRNAs are another epigenetic mechanism associated with chronological age and age-related phenotypes across species such as C. elegans, mice, primates and humans. Recently, a plasma-derived, cell-free circulating miRNA clock was developed in a sample of older European adults, with accelerated miRNA age predicting biological age-related conditions such as frailty and multi-system blood biomarkers. However, miRNA-based estimations of biological gestational age at birth have not been previously done and their relationship to child health outcomes are unknown. Added value of this studyTo gain a broader perspective on the role of epigenetic markers in biological gestational age at birth and the potential utility of miRNAs as early markers of (altered) development, we leveraged cord blood plasma circulating miRNA data collected at birth in a large population-based cohort. First, we identified 123 miRNAs associated with gestational age. Second, we used this information to construct a miRNA-based epigenetic clock for gestational age (miRClock-GA) and validated this clock in an independent cohort. MiRClock-GA showed moderate correlations with both gestational age and existing DNAm-based gestational clocks. Third, we found that miRClock-GA correlated cross-sectionally with birthweight, as well as prospectively with several adaptive, behavioural, cognitive, and growth outcomes measured up to age 17y, after taking into account maternal influences such as maternal education level, smoking, pre-pregnancy BMI, and age. Accelerated ageing of miRClock-GA (miRClock-AA) explained variance in birthweight and childhood BMI beyond clinical GA, after accounting for maternal influences. Implications of all available evidenceOur study provides the first large-scale evidence that circulating miRNAs in cord blood plasma show widespread associations with gestational age at birth and can be used to derive a robust biological marker of GA (MiRClock-GA), which explains a substantial proportion of the variation in clinical GA. MiRClock-AA provides information beyond GA in some child outcomes, such as BMI. These findings extend adult research, supporting the potential of miRNAs as promising markers for early risk assessment and health monitoring in a developmental context.

genomics↗

bioRxiv2025

Epigenome-wide association study meta-analysis of wellbeing

Wellbeing is associated with both behavioral phenotypes as well as several key life outcomes, such as health, employment, and coping with stressful events. These phenotypes associated with wellbeing could be potential indicators of differential epigenetic patterns between individuals that differ in their levels of wellbeing. We performed the largest epigenome-wide (EWAS) meta-analysis of wellbeing to date by combining whole blood DNA methylation data (Illumina 450k array) from 13 cohorts from Europe, Australia, and the USA (N = 10,757 participants). After correcting for smoking and BMI, no epigenome-wide significant methylation sites were identified. We tested whether a weighted methylation score (MS) based on leave-one-cohort-out EWAS meta-analysis summary statistics predicted wellbeing in an independent cohort, and whether prediction was significant over and above the polygenic score (PGS) for wellbeing. The MS was associated with wellbeing (variance explained=0.22%, p=0.03) and was no longer significant after adding the polygenic score (PGS; variance explained=0.43%, p=0.0046, MS; variance explained=0.07%, p=0.2842). We further compared DNA methylation levels in 16 pairs of monozygotic twins discordant for wellbeing. These analyses revealed no significant within-pair DNA methylation differences at the top-sites from the meta-analysis or in MS. Our results suggest that larger EWAS meta-analyses with uniform phenotype assessment are required to identify methylation sites associated with wellbeing.

genomics↗

bioRxiv2025

The Binary Cellular Biology of Human Growth I Quantifying the Creation and Growth of the Body and its Parts

Assessing and understanding the Growth and Development of animals generally, and of human fetuses specifically, provides essential information for the management of the health of the newborn and its mother. Here we show that a consideration of the formation of the body, in units of numbers of cells, N, and the change in these numbers by the binary either/or decisions of cells to divide or not, an approach we call Binary Cellular Analysis, provides new insights and new equations for quantifying the growth and development of the body and its parts. These equations include: 1) The Binary Cellular Universal Growth Equation, which captures growth from conception to adulthood, and provides a method for biologically-based, data-driven, Growth Curves; 2) The Binary Cellular Universal Mitotic Fraction Equation, which lies within the Binary Cellular Universal Growth Equation, and captures the mechanism of growth to adult size, control of cell division; 3) The Binary Cellular Allometric Growth Equation, which captures the creation and growth of the Tissues, Organs, and Anatomical Structures of the body, and how the embryo creates each Body Part from a Single Founder Cell; and, 4) Binary Cellular Estimated Fetal Weight Equations, derived from the Binary Cellular Allometric Growth Equation, which captures the relationship between Ultrasound Measurement and the Size of the body as a whole. These equations capture the developmental process of Cellular Selection, resulting from Differential Cellular Proliferation, which molds the formation of the body from a single fertilized ovum into a multicellular animal. The parameters of these equations both capture the differences in Size and Growth between animals across the taxonomic spectrum, and between human fetuses, as well as identify the individual mechanisms of mitosis that drive Growth and Development. From the Binary Cellular Universal Growth Equation, the Growth of human fetuses can be measured, thus providing a much-needed tool for understanding the biological forces that cause a fetus to grow to Small, Average, or Large Size at birth, for providing the basis of biologically-based, data-driven, Growth Curves, and for assisting the management of the obstetric care of the fetus and its mother.

developmental biology↗

bioRxiv2025

The Binary Cellular Biology of Human Growth II Calculating the Size of the Human Fetus from the Size of its Parts

Assessing and understanding the Size of the human fetus provides essential information for the management of the health of the newborn and its mother, a quality that is commonly measured by Fetal Ultrasound. Many equations for making such calculations have been considered, none of which have been entirely satisfactory. As we have shown in the previous paper in this series, a consideration of the formation of the body, in units of numbers of cells, N, an approach we call Binary Cellular Analysis, provides new quantitative tools for estimating the Size and Age of the fetus. These tools include a new mathematical basis for creating useful expressions, Binary Cellular Estimated Fetal Weight Equations, for calculating human Fetal Weight from Ultrasound Measurements. As we show here, the most promising of these expressions, the Abdominal Circumference Binary Cellular Estimated Fetal Weight Equation, performs better than other currently used Fetal Weight Equations, while also yielding up new methods for improving ultrasound size assessment. Web-based calculators (https://kidzgrowth.com) make these mathematical manipulations available for obstetric care.

developmental biology↗

bioRxiv2022

The gut microbiome and child mental health: a population-based study

The link between the gut microbiome and the brain has gained increasing scientific and public interest for its potential to explain psychiatric risk. While differences in gut microbiome composition have been associated with several mental health problems, evidence to date has been largely based on animal models and human studies in small sample sizes. Here, we aimed to systematically characterize associations of the gut microbiome with overall psychiatric symptoms as well as with specific domains of emotional and behavioral problems, assessed via the maternally rated Child Behavior Checklist in 1,784 ten-year-old children from the multi-ethnic, population-based Generation R Study. While we observe lower gut microbiome diversity in case of more overall and specific mental health problems, associations were not significant. Likewise, we did not identify any taxonomic feature associated with mental health problems after multiple testing correction, although nominally significant findings indicated depletion of genera previously associated with psychiatric disorders, including Anaerotruncus, Anaeroplasma, and Hungatella. The identified compositional abundance differences were found to be similar across all mental health problems. Finally, we did not find any specific microbial functions that were enriched in relation to children with mental health problems. In conclusion, based on the largest sample examined to date, we found no clear evidence of associations between gut microbiome diversity, taxonomies or functions and mental health problems in the general pediatric population. In future, the use of longitudinal designs with repeated measurements microbiome and psychiatric outcomes will be critical to clarify any emerging associations between the gut microbiome and mental health from early life to adulthood.

microbiology↗

bioRxiv2022

Genomic contributions to infant and toddler vocabulary scores: Implications for association with health-, cognition- and behaviour-related outcomes

BackgroundThe number of words children produce (expressive vocabulary) and understand (receptive vocabulary) changes rapidly during early development, partially due to genetic factors, although mechanisms are not well understood. Here, we performed a meta-genome-wide association study within the EAGLE consortium and investigated polygenic overlap with later-life traits, including Attention-Deficit/Hyperactivity Disorder (ADHD) and cognition. MethodsWe studied 37,913 parent-reported vocabulary size measures (English, Dutch, Danish) for 17,298 children of European descent. Meta-analyses were performed for early-phase expressive (infancy, 15-18 months), late-phase expressive (toddlerhood, 24-38 months) and late-phase receptive (toddlerhood, 24-38 months) vocabulary. Subsequently, we estimated Single-Nucleotide Polymorphism heritability (SNP-h2), genetic correlations (rg) and modelled underlying genetic factor structures with multivariate models. ResultsContributions of common genetic variation to early-life vocabulary were modest (SNP-h2: 0.08(SE=0.01) to 0.24(SE=0.03)) and multi-factorial. Genetic overlap between infant expressive and toddler receptive vocabulary was near zero (rg=0.07(SE=0.10)), although both measures were genetically related to toddler expressive vocabulary (rg=0.69(SE=0.14) and rg=0.67(SE=0.16), respectively). Consistently, polygenic association patterns with later-life traits differed: Genetic links with cognition emerged only in toddlerhood (e.g. toddler receptive vocabulary and intelligence: rg=0.36(SE=0.12)), despite comparable study power for infant measures. Furthermore, increased polygenic ADHD risk was associated with larger infant expressive vocabulary (rg=0.23(SE=0.08)), as confirmed by ADHD-symptom-based follow-up analyses in the Avon Longitudinal Study of Parents and Children (ALSPAC-rg=0.54(SE=0.26)). Genetic relationships with toddler receptive vocabulary were, however, opposite (ALSPAC-rg=-0.74(SE=0.23)), highlighting developmental changes in genetic architectures. ConclusionsMultiple genetic components contribute to early-life vocabulary development, shaping polygenic association patterns with later-life ADHD symptoms and cognition.

genomics↗

bioRxiv2021

Long-term association of pregnancy and maternal brain structure: the Rotterdam Study

The peripartum period is the highest risk interval for the onset or exacerbation of psychiatric illness in womens lives. Notably, pregnancy and childbirth have been associated with short-term structural and functional changes in the maternal human brain. Yet the long-term effects of parity on maternal brain structure remain unknown. Therefore, we utilized a large population-based cohort to examine the association between parity and brain structure. In total, 2,835 women (mean age 65.2 years; all free from dementia, stroke, and cortical brain infarcts) from the Rotterdam Study underwent magnetic resonance imaging (1.5 T) between 2005 and 2015. Associations of parity with global and lobar brain tissue volumes, white matter microstructure, and markers of vascular brain disease were examined using regression models. We found that parity was associated with a larger global gray matter volume ({beta}= 0.14, 95% CI = 0.09-0.19), a finding that persisted following adjustment for sociodemographic factors. A non-significant dose-dependent relationship was observed between a higher number of childbirths and larger gray matter volume. The gray matter volume association with parity was globally proportional across lobes. No associations were found regarding white matter volume or integrity, nor with markers of cerebral small vessel disease. The current findings indicate that pregnancy and childbirth are associated with robust long-term changes in brain structure involving larger global gray matter volume that persists for decades. Taken together, these data provide novel insight into the impact of motherhood on the human brain.

neuroscience↗

bioRxiv2021

Genome-wide analysis of mitochondrial DNA copy number reveals multiple loci implicated in nucleotide metabolism, platelet activation, and megakaryocyte proliferation

Mitochondrial DNA copy number (mtDNA-CN) measured from blood specimens is a minimally invasive marker of mitochondrial function that exhibits both inter-individual and intercellular variation. To identify genes involved in regulating mitochondrial function, we performed a genome-wide association study (GWAS) in 465,809 White individuals from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (UKB). We identified 133 SNPs with statistically significant, independent effects associated with mtDNA-CN across 100 loci. A combination of fine-mapping, variant annotation, and co-localization analyses were used to prioritize genes within each of the 133 independent sites. Putative causal genes were enriched for known mitochondrial DNA depletion syndromes (p = 3.09 x 10-15) and the gene ontology (GO) terms for mtDNA metabolism (p = 1.43 x 10-8) and mtDNA replication (p = 1.2 x 10-7). A clustering approach leveraged pleiotropy between mtDNA-CN associated SNPs and 41 mtDNA-CN associated phenotypes to identify functional domains, revealing three distinct groups, including platelet activation, megakaryocyte proliferation, and mtDNA metabolism. Finally, using mitochondrial SNPs, we establish causal relationships between mitochondrial function and a variety of blood cell related traits, kidney function, liver function and overall (p = 0.044) and non-cancer mortality (p = 6.56 x 10-4).

genetics↗

bioRxiv2020

Meta-analysis of epigenome-wide associations between DNA methylation at birth and childhood cognitive skills.

Cognitive skills are a strong predictor of a wide range of later life outcomes. Genetic and epigenetic associations across the genome explain some of the variation in general cognitive abilities in the general population and it is plausible that epigenetic associations might arise from prenatal environmental exposures and/or genetic variation early in life. We investigated the association between cord blood DNA methylation at birth and cognitive skills assessed in children from eight pregnancy cohorts (N=2196-3798) within the Pregnancy And Childhood Epigenetics (PACE) Consortium across overall, verbal and non-verbal cognitive scores. The associations at single CpG sites were weak for all of the cognitive domains investigated. One region near DUSP22 on chromosome 6 was associated with non-verbal cognition in a model adjusted for maternal IQ. We conclude that there is little evidence to support the idea that cord blood DNA methylation at single CpGs can predict cognitive skills and further studies are needed to confirm regional differences.

developmental biology↗

bioRxiv2020

Epigenome-wide change and variation in DNA methylation from birth to late adolescence

DNA methylation (DNAm) is known to play a pivotal role in childhood health and development, but a comprehensive characterization of genome-wide DNAm trajectories across this age period is currently lacking. We have therefore performed a series of epigenome-wide association studies in 5,019 blood samples collected at multiple time-points from birth to late adolescence from 2,348 participants of two large independent cohorts. DNAm profiles of autosomal CpG sites (CpGs) were generated using the Illumina Infinium HumanMethylation450 BeadChip. Change over time was widespread, observed at over one-half (53%) of CpGs. In most cases DNAm was decreasing (36% of CpGs). Inter-individual variation in linear trajectories was similarly widespread (27% of CpGs). Evidence for nonlinear change and inter-individual variation in nonlinear trajectories was somewhat less common (11% and 8% of CpGs, respectively). Very little inter-individual variation in change was explained by sex differences (0.4% of CpGs) even though sex-specific DNAm was observed at 5% of CpGs. DNAm trajectories were distributed non-randomly across the genome. For example, CpGs with decreasing DNAm were enriched in gene bodies and enhancers and were annotated to genes enriched in immune-developmental functions. By contrast, CpGs with increasing DNAm were enriched in promoter regions and annotated to genes enriched in neurodevelopmental functions. These findings depict a methylome undergoing widespread and often nonlinear change throughout childhood. They support a developmental role for DNA methylation that extends beyond birth into late adolescence and has implications for understanding life-long health and disease. DNAm trajectories can be visualized at http://epidelta.mrcieu.ac.uk.

genomics↗

bioRxiv2019

Association between DNA methylation and ADHD symptoms from birth to school age: A prospective meta-analysis

Attention-deficit and hyperactivity disorder (ADHD) is a common childhood disorder with a substantial genetic component. However, the extent to which epigenetic mechanisms play a role in the etiology of the disorder is not known. We performed epigenome-wide association studies (EWAS) within the Pregnancy And Childhood Epigenetics (PACE) Consortium to identify DNA methylation sites associated with ADHD symptoms at two methylation assessment periods: birth and school-age. We examined associations of DNA methylation in cord blood with repeatedly assessed ADHD symptoms (age range 4-15 years) in 2477 children from five cohorts and DNA methylation at school-age with concurrent ADHD symptoms (age 7-11 years) in 2374 children from ten cohorts. CpGs identified with nominal significance (p<0.05) in either of the EWAS were correlated between timepoints ({rho}=0.30), suggesting overlap in associations, however, top signals were very different. At birth, we identified nine CpGs that were associated with later ADHD symptoms (P<1*10-7), including ERC2 and CREB5. Peripheral blood DNA methylation at one of these CpGs (cg01271805 located in the promotor region of ERC2, which regulates neurotransmitter release) was previously associated with brain methylation. Another (cg25520701) lies within the gene body of CREB5, which was associated with neurite outgrowth and an ADHD diagnosis in previous studies. In contrast, at school-age, no CpGs were associated with ADHD with P<1*10-7. In conclusion, we found evidence in this study that DNA methylation at birth is associated with ADHD. Future studies are needed to confirm the utility of methylation variation as biomarker and its involvement in causal pathways.

genetics↗

bioRxiv2018

Phenome-wide investigation of health outcomes associated with genetic predisposition to loneliness

AO_SCPLOWBSTRACTC_SCPLOWHumans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. While the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. While it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition towards loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we conducted a genome-wide association (GWAS) meta-analysis of loneliness (N=475,661), report 12 associated loci (two novel) and significant genetic correlations with 34 other complex traits. The polygenic basis for loneliness was significantly enriched for evolutionary constrained genes and genes expressed in specific brain tissues: (frontal) cortex, cerebellum, anterior cingulate cortex, and substantia nigra. We built polygenic scores based on this GWAS meta-analysis to explore the genetic association between loneliness and health outcomes in an independent sample of 18,498 individuals for whom electronic health records were available. A genetic predisposition towards loneliness predicted cardiovascular, psychiatric, and metabolic disorders, and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, effect of body fat on loneliness, and a similar weaker causal effect of BMI. Our results provide a framework for ongoing studies of the genetic basis of loneliness and its role in mental and physical health.

genetics↗

bioRxiv2018

Novel DNA methylation sites of glucose and insulin homeostasis: an integrative cross-omics analysis

Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of the functional relevance of the phenomenon remains limited. Because obesity is the main risk factor for T2D and a driver of methylation from previous study, we aimed to explore the effect of DNA methylation in the early phases of T2D pathology while accounting for body mass index (BMI). We performed a blood-based epigenome-wide association study (EWAS) of fasting glucose and insulin among 4,808 non-diabetic European individuals and replicated the findings in an independent sample consisting of 11,750 non-diabetic subjects. We integrated blood-based in silico cross-omics databases comprising genomics, epigenomics and transcriptomics collected by BIOS project of the Biobanking and BioMolecular resources Research Infrastructure of the Netherlands (BBMRI-NL), the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC), the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium, and the tissue-specific Genotype-Tissue Expression (GTEx) project. We identified and replicated nine novel differentially methylated sites in whole blood (P-value < 1.27 x 10-7): sites in LETM1, RBM20, IRS2, MAN2A2 genes and 1q25.3 region were associated with fasting insulin; sites in FCRL6, SLAMF1, APOBEC3H genes and 15q26.1 region were associated with fasting glucose. The association between SLAMF1, APOBEC3H and 15q26.1 methylation sites and glucose emerged only when accounted for BMI. Follow-up in silico cross-omics analyses indicate that the cis-acting meQTLs near SLAMF1 and SLAMF1 expression are involved in glucose level regulation. Moreover, our data suggest that differential methylation in FCRL6 may affect glucose level and the risk of T2D by regulating FCLR6 expression in the liver. In conclusion, the present study provided nine new DNA methylation sites associated with glycemia homeostasis and also provided new insights of glycemia related loci into the genetics, epigenetics and transcriptomics pathways based on the integration of cross-omics data in silico.

genomics↗

bioRxiv2018

GWAS in 446,118 European adults identifies 78 genetic loci for self-reported habitual sleep duration supported by accelerometer-derived estimates

Sleep is an essential homeostatically-regulated state of decreased activity and alertness conserved across animal species, and both short and long sleep duration associate with chronic disease and all-cause mortality1,2. Defining genetic contributions to sleep duration could point to regulatory mechanisms and clarify causal disease relationships. Through genome-wide association analyses in 446,118 participants of European ancestry from the UK Biobank, we discover 78 loci for self-reported sleep duration that further impact accelerometer-derived measures of sleep duration, daytime inactivity duration, sleep efficiency and number of sleep bouts in a subgroup (n=85,499) with up to 7-day accelerometry. Associations are enriched for genes expressed in several brain regions, and for pathways including striatum and subpallium development, mechanosensory response, dopamine binding, synaptic neurotransmission, catecholamine production, synaptic plasticity, and unsaturated fatty acid metabolism. Genetic correlation analysis indicates shared biological links between sleep duration and psychiatric, cognitive, anthropometric and metabolic traits and Mendelian randomization highlights a causal link of longer sleep with schizophrenia.

genetics↗

bioRxiv2018

Genetic studies of accelerometer-based sleep measures in 85,670 individuals yield new insights into human sleep behaviour

Sleep is an essential human function but its regulation is poorly understood. Identifying genetic variants associated with quality, quantity and timing of sleep will provide biological insights into the regulation of sleep and potential links with disease. Using accelerometer data from 85,670 individuals in the UK Biobank, we performed a genome-wide association study of 8 accelerometer-derived sleep traits, 5 of which are not accessible through self-report alone. We identified 47 genetic associations across the sleep traits (P<5x10-8) and replicated our findings in 5,819 individuals from 3 independent studies. These included 26 novel associations for sleep quality and 10 for nocturnal sleep duration. The majority of newly identified variants were associated with a single sleep trait, except for variants previously associated with restless legs syndrome that were associated with multiple sleep traits. Of the new associated and replicated sleep duration loci, we were able to fine-map a missense variant (p.Tyr727Cys) in PDE11A, a dual-specificity 3,5-cyclic nucleotide phosphodiesterase expressed in the hippocampus, as the likely causal variant. As a group, sleep quality loci were enriched for serotonin processing genes and all sleep traits were enriched for cerebellar-expressed genes. These findings provide new biological insights into sleep characteristics.

genetics↗

bioRxiv2018

Genome-wide association analyses of chronotype in 697,828 individuals provides new insights into circadian rhythms in humans and links to disease

Using genome-wide data from 697,828 research participants from 23andMe and UK Biobank, we increase the number of identified loci associated with being a morning person, a behavioural indicator of a persons underlying circadian rhythm, from 24 to 351. Using data from 85,760 individuals with activity-monitor derived measures of sleep timing we show that the chronotype loci influence sleep timing: the mean sleep timing of the 5% of individuals carrying the most "morningness" alleles was 25 minutes earlier than the 5% carrying the fewest. The loci were enriched for genes involved in circadian regulation, cAMP, glutamate and insulin signalling pathways, and those expressed in the retina, hindbrain, hypothalamus, and pituitary. We provide evidence that being a morning person is causally associated with better mental health but does not appear to affect BMI or Type 2 diabetes. This study offers new insights into the biology of circadian rhythms and links to disease in humans.

genetics↗

bioRxiv2018

Genome-wide Analysis of Insomnia (N=1,331,010) Identifies Novel Loci and Functional Pathways

Insomnia is the second-most prevalent mental disorder, with no sufficient treatment available. Despite a substantial role of genetic factors, only a handful of genes have been implicated and insight into the associated neurobiological pathways remains limited. Here, we use an unprecedented large genetic association sample (N=1,331,010) to allow detection of a substantial number of genetic variants and gain insight into biological functions, cell types and tissues involved in insomnia complaints. We identify 202 genome-wide significant loci implicating 956 genes through positional, eQTL and chromatin interaction mapping. We show involvement of the axonal part of neurons, of specific cortical and subcortical tissues, and of two specific cell-types in insomnia: striatal medium spiny neurons and hypothalamic neurons. These cell-types have been implicated previously in the regulation of reward processing, sleep and arousal in animal studies, but have never been genetically linked to insomnia in humans. We found weak genetic correlations with other sleep-related traits, but strong genetic correlations with psychiatric and metabolic traits. Mendelian randomization identified causal effects of insomnia on specific psychiatric and metabolic traits. Our findings reveal key brain areas and cells implicated in the neurobiology of insomnia and its related disorders, and provide novel targets for treatment.

genetics↗

bioRxiv2017

GWAS Meta-Analysis of Neuroticism (N=449,484) Identifies Novel Genetic Loci and Pathways

Neuroticism is an important risk factor for psychiatric traits including depression1, anxiety2,3, and schizophrenia4-6. Previous genome-wide association studies7-12 (GWAS) reported 16 genomic loci10-12. Here we report the largest neuroticism GWAS meta-analysis to date (N=449,484), and identify 136 independent genome-wide significant loci (124 novel), implicating 599 genes. Extensive functional follow-up analyses show enrichment in several brain regions and involvement of specific cell-types, including dopaminergic neuroblasts (P=3x10-8), medium spiny neurons (P=4x10-8) and serotonergic neurons (P=1x10-7). Gene-set analyses implicate three specific pathways: neurogenesis (P=4.4x10-9), behavioural response to cocaine processes (P=1.84x10-7), and axon part (P=5.26x10-8). We show that neuroticisms genetic signal partly originates in two genetically distinguishable subclusters13 (depressed affect and worry, the former being genetically strongly related to depression, rg=0.84), suggesting distinct causal mechanisms for subtypes of individuals. These results vastly enhance our neurobiological understanding of neuroticism, and provide specific leads for functional follow-up experiments.

genetics↗