Biology subjects

Lawlor, D. A.

Publications and source records attributed to Lawlor, D. A..

At least 19 recordsLinked to original sources

bioRxiv2026

Genetic, intrinsic, and environmental determinants of innate immune cytokine responses in healthy four-year-old children

Abstract/SummaryInnate immune responses are crucial for host defence but vary markedly between individuals. Although determinants of this variation are well characterised in adults, data from healthy children remain scarce. We therefore profiled whole-blood cytokine responses to innate immune stimulation in 286 children aged approximately four years and examined genetic, host-intrinsic, and environmental correlates of response. Cytokine responses showed marked inter-individual heterogeneity and stimulus-specific patterns. The top 50 genetic variants explained a substantial proportion ([~]20-45%) of this variance across many stimulus conditions, including a biologically coherent association of the STING locus with cGAMP-induced cytokine production. In contrast, sex, age, adiposity, and perinatal variables showed limited or modest associations. Systemic inflammatory biomarkers of systemic inflammation (hsCRP, glycoprotein acetyls, granulocyte-to-lymphocyte ratio) were strongly positively associated with cytokine responses. Finally, seasonal population-level viral infection burden was positively associated with antiviral and inflammatory cytokine responses. Collectively, these findings advance our understanding of variation in early-life whole-blood cytokine responses, underscoring this developmental period as a critical window for understanding immune development trajectories relevant to long-term health.

immunology↗

bioRxiv2022

DNA co-methylation has a stable structure and is related to specific aspects of genome regulation

DNA methylation (DNAm) is influenced by genetic and environmental factors, and can be used to understand interindividual variability in genomic regulation. Co-methylation between DNAm sites is a known phenomenon, but the architecture of relationships between the approximately 450,000 (450k) sites commonly measured in epidemiological studies has not been described. We investigate whether interindividual co-methylation structure amongst the 450k sites changes with age, whether it differs between UK-born White (n=849, 910, 921 and 424) and Pakistani ancestry (n=439) individuals, and how it relates to genome regulation. We find stability between birth and adolescence, across cohorts, and between two ethnic groups. Highly correlated DNAm sites in close proximity are heritable, but these relationships are weakly influenced by nearby genetic variants, and are enriched for transcription factor (TF) binding sites related to regulation of short RNAs transcribed by RNA polymerase III. Highly correlated sites that are distant, or on different chromosomes (in trans), are driven by common and unique environmental factors, with methylation at these sites less likely to be driven by genotype. Trans co-methylated DNAm sites are enriched for multiple TF binding sites and for inter-chromosomal chromatin contact sites, suggesting DNA co-methylation of distant sites may relate to long-range cooperative TF interactions. We conclude that DNA co-methylation has a stable structure from birth to adolescence, and between UK-born White and Pakistani individuals. This stable structure might have implications for future design and interpretation of epigenetic studies. We hypothesise that co-methylation may have roles in genome regulation in humans, including 3D chromatin architecture.

bioinformatics↗

bioRxiv2021

metaboprep: an R package for pre-analysis data description and processing.

MotivationMetabolomics is an increasingly common part of health research and there is need for pre-analytical data processing. Researchers typically need to characterize the data and to exclude errors within the context of the intended analysis. While some pre-processing steps are common, there is currently a lack of standardization and reporting transparency for these procedures. ResultsHere we introduce metaboprep, a standardized data processing workflow to extract and characterize high quality metabolomics data sets. The package extracts data from pre-formed worksheets, provides summary statistics and enables the user to select samples and metabolites for their analysis based on a set of quality metrics. A report summarizing quality metrics and the influence of available batch variables on the data is generated for the purpose of open disclosure. Where possible, we provide users flexibility in defining their own selection thresholds. Availability and implementationmetaboprep is an open-source R package available at https://github.com/MRCIEU/metaboprep Contactd.a.hughes@bristol.ac.uk or laura.corbin@bristol.ac.uk

bioinformatics↗

bioRxiv2020

Validation of lipid-related therapeutic targets for coronary heart disease prevention using human genetics

Drug target Mendelian randomization (MR) studies use DNA sequence variants in or near a gene encoding a drug target, that alter its expression or function, as a tool to anticipate the effect of drug action on the same target. Here, we applied MR to prioritize drug targets for their causal relevance for coronary heart disease (CHD). The targets were further prioritized using genetic co-localization, protein expression profiles from the Human Protein Atlas and, for targets with a licensed drug or an agent in clinical development, by sourcing data from the British National Formulary and clinicaltrials.gov. Out of the 341 drug targets identified through their association with circulating blood lipids (HDL-C, LDL-C and triglycerides), we were able to robustly prioritize 30 targets that might elicit beneficial treatment effects in the prevention or treatment of CHD. The prioritized list included NPC1L1 and PCSK9, the targets of licensed drugs whose efficacy has been already proven in clinical trials. To conclude, we discuss how this approach can be generalized to other targets, disease biomarkers and clinical end-points to help prioritize and validate targets during the drug development process. One Sentence SummaryWe provide genetic support for lipid-modifying drug targets for coronary heart disease prevention using drug target Mendelian randomization and further prioritization based on clinical and biological evidence.

genetics↗

bioRxiv2020

Fetal alleles predisposing to metabolically favourable adiposity are associated with higher birth weight

BackgroundHigher birth weight is associated with higher adult body mass index (BMI). If genetic variants can be identified with alleles that predispose to both greater fetal growth and to greater adult adiposity, such shared genetic effects might indicate biological processes important in the early patterning of adiposity. However, variants identified in genome-wide association studies of adult BMI have overall been only weakly associated with birth weight. Genetic variants have recently been identified where one allele is associated with higher adult body fat percentage, but lower risk of metabolic disease, likely due to a favourable body fat distribution. The effect of these adult metabolically favourable adiposity alleles on an individuals own birth weight is unknown. AimWe aimed to test the effect on birth weight of a fetal genetic predisposition to higher metabolically favourable adult adiposity and to compare this with the effects of a fetal genetic predisposition to higher adult BMI. We also aimed to examine the effects of a genetic predisposition to higher metabolically favourable adult adiposity or BMI on other birth anthropometric traits (length, ponderal index, head circumference and skinfold thickness) and on cord-blood insulin, leptin and adiponectin. MethodsWe used published GWAS data from up to 406,063 individuals to estimate the fetal effects on birth weight of alleles that are robustly associated with higher metabolically favourable adult adiposity or BMI. We additionally used 9,350 mother-child pairs from four cohorts to test the effects of the same alleles on other birth anthropometric traits and cord-blood markers. In all analyses, we adjusted for potential confounding due to the maternal genotype. We used inverse-variance weighted meta-analyses to combine summary data across SNPs. ResultsFetal genetic predisposition to higher metabolically favourable adult adiposity was associated with higher birth weight (10 grams (95% CI: 7 to 13) higher mean birth weight per 1 SD pooled "genetic score"). Fetal genetic predisposition to higher adult BMI was also associated with higher birth weight, but with a smaller magnitude of effect (4 grams (95% CI: 0 to 8) higher mean birth weight per 1 SD pooled "genetic score") and with higher heterogeneity across SNPs. Effects on other birth anthropometric outcomes were consistent with the effect on birth weight but with wider confidence intervals. There was no strong evidence for an effect on cord-blood markers. ConclusionsSome genetic variants previously linked to adult adiposity influence birth weight. Alleles that predispose to higher metabolically favourable adult adiposity collectively have a stronger effect on birth weight than those predisposing to higher BMI. This suggests that the early accumulation of a metabolically favourable fat distribution might underlie part of the observed association between higher birth weight and higher adult BMI. Larger samples are needed to clarify the effects on other birth anthropometric measures and cord-blood markers.

genetics↗

bioRxiv2020

Investigating the causal effect of maternal vitamin B12 and folate levels on offspring birthweight

Lower maternal serum vitamin B12 (B12) and folate levels have been associated with lower offspring birthweight in observational studies. The aim of this study was to investigate whether this relationship is causal. We performed two-sample Mendelian Randomization (MR) using summary data on associations between genotype-B12 (10 genetic variants) or genotype-folate (4 genetic variants) levels from a genome-wide association study of 45,576 individuals (sample 1) and maternal-specific genetic effects on offspring birthweight from the latest EGG consortium meta-analysis with 297,356 individuals reporting their own birthweight and 210,248 women reporting their offsprings birthweight (sample 2). To investigate the effect of offsprings own B12 or folate levels on their own birthweight, we performed two-sample MR using the fetal-specific genetic effects from the latest EGG consortium meta-analysis. We used the inverse variance weighted method, and sensitivity analyses to account for pleiotropy, in addition to sensitivity analyses excluding a potentially pleiotropic variant in the FUT2 gene for B12. We did not find evidence for a causal effect of maternal B12 on offspring birthweight, nor evidence for an effect of offspring B12 on their own birthweight using the fetal-specific genetic effect. The results were consistent across the different methods and in sensitivity analyses excluding the FUT2 variant. We found a positive effect of maternal folate on offspring birthweight (0.146 [0.065, 0.227], which corresponds to an increase in birthweight of 71g per 1SD higher folate). We found some evidence for a small inverse effect of fetal folate on their own birthweight (-0.051 [-0.100, -0.003]). In conclusion, our results are consistent with evidence from randomized controlled trials that increased maternal folate levels increase offspring birthweight. We did not find evidence for a causal effect of B12 on offspring birthweight, suggesting previous observational studies may have been due to confounding.

genetics↗

bioRxiv2019

Bias in two-sample Mendelian randomization by using covariable-adjusted summary associations

BackgroundTwo-sample Mendelian randomization (MR) allows the use of freely accessible summary association results from genome-wide association studies (GWAS) to estimate causal effects of modifiable exposures on outcomes. Some GWAS adjust for heritable covariables in an attempt to estimate direct effects of genetic variants on the trait of interest. One, both or neither of the exposure GWAS and outcome GWAS may have been adjusted for covariables. MethodsWe performed a simulation study comprising different scenarios that could motivate covariable adjustment in a GWAS and analysed real data to assess the influence of using covariable-adjusted summary association results in two-sample MR. ResultsIn the absence of residual confounding between exposure and covariable, between exposure and outcome, and between covariable and outcome, using covariable-adjusted summary associations for two-sample MR eliminated bias due to horizontal pleiotropy. However, covariable adjustment led to bias in the presence of residual confounding (especially between the covariable and the outcome), even in the absence of horizontal pleiotropy (when the genetic variants would be valid instruments without covariable adjustment). In an analysis using real data from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and UK Biobank, the causal effect estimate of waist circumference on blood pressure changed direction upon adjustment of waist circumference for body mass index. ConclusionsOur findings indicate that using covariable-adjusted summary associations in MR should generally be avoided. When that is not possible, careful consideration of the causal relationships underlying the data (including potentially unmeasured confounders) is required to direct sensitivity analyses and interpret results with appropriate caution. Key messagesO_LISummary genetic associations from large genome-wide associations studies (GWAS) have been increasingly used in two-sample Mendelian randomization (MR) analyses. C_LIO_LIMany GWAS adjust for heritable covariates in an attempt to estimate direct genetic effects on the trait of interest. C_LIO_LIIn an extensive simulation study, we demonstrate that using covariable-adjusted summary associations may bias MR analyses. C_LIO_LIThe bias largely depends on the underlying causal structure, specially the presence of unmeasured common causes between the covariable and the outcome. C_LIO_LIOur findings indicate that using covariable-adjusted summary associations in MR should generally be avoided. C_LI

genetics↗

bioRxiv2019

Haplotype genetic score analysis in 10,734 mother/infant pairs reveals complex maternal and fetal genetic effects underlying the associations between maternal phenotypes, birth outcomes and adult phenotypes

Many maternal traits are associated with a neonates gestational duration, birth weight and birth length. These birth outcomes are subsequently associated with late onset health conditions. Based on 10,734 mother/infant duos of European ancestry, we constructed haplotype genetic scores to dissect the maternal and fetal genetic effects underlying these observed associations. We showed that maternal height and fetal growth jointly affect the duration of gestation - maternal height positively influences the gestational duration, while faster fetal growth reduces gestational duration. Fetal growth is influenced by both maternal and fetal effects and can reciprocally influence maternal phenotypes: tall maternal stature and higher blood glucose causally increase birth size; in the fetus, the height and metabolic risk increasing alleles can lead to increased and decreased birth size respectively; birth weight-raising alleles in fetus may reduce gestational duration and increase maternal blood pressure. These maternal and fetal genetic effects can largely explain the observed associations between the studied maternal phenotypes and birth outcomes as well as the life-course associations between these birth outcomes and adult phenotypes.

genetics↗

bioRxiv2019

Age at period cessation and trajectories of cardiovascular risk factors across mid and later life: a prospective cohort study

What is already known about this topicAge at period cessation is associated with cardiovascular disease. Whether age at period cessation adversely affects change in conventional cardiovascular intermediates from mid to later life is not well understood.\n\nWhat this study addsWomen and clinicians concerned about the impact of type and timing of period cessation on conventional cardiovascular intermediates from midlife should be reassured that the impacts over the long term are small.\n\nAbstractO_ST_ABSObjectiveC_ST_ABSTo examine the association between age at period cessation (by type of period cessation) and trajectories of anthropometry, blood pressure, lipids and HBA1c from midlife.\n\nDesignProspective cohort study of women recruited to the Medical Research Council National Survey of Health and Development (NSHD).\n\nSettingPopulation based prospective cohort study.\n\nParticipantsWomen participating in NSHD with a known date of period cessation and at least one measure of each intermediate cardiovascular risk factor.\n\nExposuresAge at period cessation and type of period cessation (hysterectomy compared with natural menopause).\n\nOutcomesRepeated measures of systolic blood pressure, diastolic blood pressure, body mass index (BMI) and waist circumference (WC) from 36 to 69 years and repeated measures of triglyceride, low density lipoprotein cholesterol (LDL-c), high density lipoprotein cholesterol (HDL-c) and glycated haemoglobin (HBA1c) from 53 to 69 years.\n\nResultsWe found no evidence that age at period cessation was associated with trajectories of log triglyceride, LDL-c and HDL-c from 53 to 69 years and trajectories of blood pressure from 36 to 69 years, regardless of whether period cessation occurred naturally or due to hysterectomy. While we found some evidence of associations of age at period cessation with log BMI, log WC and log HBA1C, patterns were not consistent and differences were small at age 69 years, with confidence intervals that spanned the null. For instance, the difference in log WC at age 69 per year increase in age at natural menopause was 0.003 (95% confidence interval, -0.0002, 0.01) while the difference per year increase in age at hysterectomy was -0.002 (95% CI, -0.005, 0.001).\n\nConclusionHow and when women experience period cessation is unlikely to adversely affect conventional cardiovascular risk factors across mid and later life. Women and clinicians concerned about the impact of type and timing of period cessation on conventional cardiovascular intermediates from midlife should be reassured that the impacts over the long term are small.

epidemiology↗

bioRxiv2019

Is disrupted sleep a risk factor for Alzheimers disease? Evidence from a two-sample Mendelian randomization analysis

INTRODUCTIONIt is established that Alzheimers disease (AD) patients experience sleep disruption. However, it remains unknown whether disruption in the quantity, quality or timing of sleep is a risk factor for the onset of AD.\n\nMETHODSMendelian randomization (MR) was used to estimate the causal effect of self-reported and accelerometer-measured sleep parameters (chronotype, duration, fragmentation, insomnia, daytime napping and daytime sleepiness) on AD risk.\n\nRESULTSOverall, there was little evidence that sleep traits affect the risk of AD. There was some evidence to suggest that self-reported daytime napping was associated with lower AD risk (odds ratio [OR]: 0.70, 95% confidence interval [CI]: 0.50 to 0.99). Some other sleep traits (accelerometer-measured eveningness and sleep duration, and self-reported daytime sleepiness) had ORs for AD risk of a similar magnitude to daytime napping, but were less precisely estimated.\n\nDISCUSSONOur findings provide tentative evidence that daytime napping may reduce AD risk. However, findings should be replicated using independent samples.

epidemiology↗

bioRxiv2019

The Parkinsons Disease Mendelian Randomization Research Portal

BackgroundMendelian randomization (MR) is a method for exploring observational associations to find evidence of causality.\n\nObjectiveTo apply MR between multiple risk factors/phenotypic traits (exposures) and Parkinsons disease (PD) in a large, unbiased manner, and to create a public resource for research.\n\nMethodsWe used two-sample MR in which the summary statistics relating to SNPs from genome wide association studies (GWASes) of 5,839 exposures curated on MR Base were used to assess causal relationships with PD. We selected the highest quality exposure GWASes for this report (n=401). For the disease outcome, summary statistics from the largest published PD GWAS were used. For each exposure, the causal effect on PD was assessed using the inverse variance weighted (IVW) method, followed by a range of sensitivity analyses. We used a false discovery rate (FDR) corrected p-value of <0.05 from the IVW analysis to prioritize traits of interest.\n\nResultsWe observed evidence for causal associations between twelve exposures and risk of PD. Of these, nine were causal effects related to increasing adiposity and decreasing risk of PD. The remaining top exposures that affected PD risk were tea drinking, time spent watching television and forced vital capacity, but the latter two appeared to be biased by violations of underlying MR assumptions.\n\nDiscussionWe present a new platform which offers MR analyses for a total of 5,839 GWASes versus the largest PD GWASes available (https://pdgenetics.shinyapps.io/pdgenetics/). Alongside, we report further evidence to support a causal role for adiposity on lowering the risk of PD.

neuroscience↗

bioRxiv2019

Sex and area differences in the association between adiposity and lipid profile in Malawi

BackgroundEvidence from high-income countries shows that higher adiposity results in an adverse lipid profile, but it is unclear whether this association is similar in Sub-Saharan African (SSA) populations. This study aimed to assess the association between total and central adiposity measures and lipid profile in Malawi, exploring differences by sex and area of residence (rural/urban). MethodsData from 12,847 rural and 12,096 urban Malawian residents were used. The associations of body mass index (BMI) and waist-hip ratio (WHR) with fasting lipids (total cholesterol (TC), low density lipoprotein-cholesterol (LDL-C), high density lipoprote in-cholesterol (HDL-C) and triglycerides (TG)) were assessed by area and sex. ResultsA great proportion of adults have high BMI and WHR, and this was associated with adverse lipid profiles; higher BMI and WHR were linearly associated with increased TC, LDL-C and TG and reduced HDL-C. BMI was more strongly related to fasting lipids than was WHR. The associations of adiposity with adverse lipid profile were stronger in urban compared with rural residents. ConclusionsThe consistent associations observed of higher adiposity with adverse lipid profiles in females and males living in rural and urban areas of Malawi highlight the emerging adverse cardio-metabolic epidemic in this poor population. Our findings underline the potential utility of BMI in estimating cardiovascular risk and highlight the need for greater investment to understand the long-term health outcomes of obesity and adverse lipid profiles and the extent to which lifestyle changes and treatments effectively prevent and modify adverse cardio-metabolic outcomes. Key messagesO_LIHigher body mass index (BMI) and waist to hip ratio (WHR) are associated with increased total cholesterol (TC), low density lipoprotein-cholesterol (LDL-C) and triglycerides (TG) and reduced high density lipoprotein-cholesterol (HDL-C) in a large sub-Saharan African population. C_LIO_LITotal adiposity is more strongly associated with adverse lipid profile than central adiposity. C_LIO_LIDespite the higher BMI and the less favourable lipid profile in urban residents, stronger associations between BMI and TC, LDL-C and TG are observed in rural than urban residents. C_LI

epidemiology↗

bioRxiv2019

The effect of pre-analytical conditions on blood metabolomics in epidemiological studies

BackgroundSerum and plasma are commonly used biofluids for large-scale metabolomic-epidemiology studies. Their metabolomic profile is susceptible to changes due to variability in pre-analytical conditions and the impact of this is unclear.\n\nMethodsParticipant-matched EDTA-plasma and serum samples were collected from 37 non-fasting volunteers and profiled using a targeted nuclear magnetic resonance (NMR) metabolomics platform (N=151 traits). Metabolic concentrations were compared between reference (pre-storage: 4{degrees}C, 1.5h; post-storage: no sample preparation or NMR-analysis delays) and four, pre-storage, blood processing conditions, where samples were incubated at (i) 4{degrees}C, 24h; (ii) 4{degrees}C, 48h; (iii) 21{degrees}C, 24h; (iv) 21{degrees}C, 48h, before centrifugation; and two, post-storage, sample processing conditions in which samples (i) thawed overnight, then left for 24h before addition of sodium buffer followed by immediate NMR analysis; (ii) thawed overnight, addition of sodium buffer, then left for 24h before profiling. Linear regression models with random-intercepts were used to assess the impact of these six pre-analytical conditions on EDTA-plasma/serum metabolome.\n\nResultsFatty acids, beta-hydroxybutyrate, glycoprotein-acetyls and most lipid-related traits, in serum and plasma, were robust to the tested pre and post-storage conditions. Pre-storage conditions impacted concentrations of glycolysis metabolites, acetate, albumin and amino-acids by levels that could potentially bias research results (up to 1.4SD difference compared with reference). Post-storage conditions affected histidine, phenylalanine and LDL-particle-size, with differences up to 1.4SD.\n\nConclusionsMost metabolic traits are robust to the pre- and post-storage conditions tested here and that may commonly occur in large-scale cohorts. However, concentrations of glycolysis metabolites, and amino-acids may be compromised.\n\nKey messagesO_LIIn large scale epidemiological studies, blood processing delays, incubation at high temperature prior to long term storage, and NMR profiling delays after long term storage, may occur.\nC_LIO_LIConcentrations of fatty acids, beta-hydroxybutyrate, glycoprotein acetyls and most lipid-related traits are robust to variations in pre-storage temperature and duration of incubation (4{degrees}C or 21{degrees}C for up to 48h prior to centrifugation) and post-storage sample handling (24h delay in sample preparation or NMR profiling).\nC_LIO_LIGlycolytic metabolite concentrations are altered by pre-storage conditions and amino-acids, particularly histidine and phenylalanine, by both, pre and post-storage conditions.\nC_LI

epidemiology↗

bioRxiv2018

GLU: A tool for analysing continuously measured glucose in epidemiology

MotivationContinuous glucose monitors (CGM) record interstitial glucose continuously, producing a sequence of measurements for each participant (e.g. the average glucose every 5 minutes over several days, both day and night). To analyze these data, researchers tend to derive summary variables such as the Area Under the Curve (AUC), to then use in subsequent analyses. To date, a lack of consistency and transparency of precise definitions used for these summary variables has hindered interpretation, replication and comparison of results across studies. We present GLU, an open-source software package for deriving a consistent set of summary variables from CGM data.\n\nGeneral featuresGLU performs quality control of each CGM sample (e.g. addressing missing data), derives a diverse set of summary variables (e.g. AUC, and proportion of time spent in hypo-, normo- and hyper-glycaemic levels) covering six broad domains, and outputs these (with quality control information) to the user.\n\nImplementationGLU is implemented in R.\n\nAVAILABILITYGLU is available on GitHub at [https://github.com/MRCIEU/GLU]. Git tag v0.1 corresponds to the version presented here.

epidemiology↗

bioRxiv2018

Genome-wide association study of anti-Mullerian hormone levels in pre-menopausal women of late reproductive age and relationship with genetic determinants of reproductive lifespan

Anti-Mullerian hormone (AMH) is required for sexual differentiation in the fetus, and in adult females AMH is produced by growing ovarian follicles. Consequently, AMH levels are correlated with ovarian reserve, declining towards menopause when the oocyte pool is exhausted. A previous genome-wide association study identified three genetic variants in and around the AMH gene that explained 25% of variation in AMH levels in adolescent males but did not identify any genetic associations reaching genome-wide significance in adolescent females. To explore the role of genetic variation in determining AMH levels in women of late reproductive age, we carried out a genome-wide meta-analysis in 3,344 pre-menopausal women from five cohorts (median age 44-48 years at blood draw). A single genetic variant, rs16991615, previously associated with age at menopause, reached genome-wide significance at P=3.48x10-10, with a per allele difference in age-adjusted inverse normal AMH of 0.26 SD (95% CI [0.18,0.34]). We investigated whether genetic determinants of female reproductive lifespan were more generally associated with pre-menopausal AMH levels. Genetically-predicted age at menarche had no robust association but genetically-predicted age at menopause was associated with lower AMH levels by 0.18 SD (95% CI [0.14,0.21]) in age-adjusted inverse normal AMH per one-year earlier age at menopause. Our findings support the hypothesis that AMH is a valid measure of ovarian reserve in pre-menopausal women and suggest that the underlying biology of ovarian reserve results in a causal link between pre-menopausal AMH levels and menopause timing.

genomics↗

bioRxiv2018

Investigating causal relationships between sleep traits and risk of breast cancer: a Mendelian randomization study

ObjectiveTo examine whether sleep traits have a causal effect on risk of breast cancer.\n\nDesignMultivariable regression, one- and two-sample Mendelian randomization.\n\nSettingThe UK Biobank prospective cohort study and the Breast Cancer Association Consortium (BCAC) case-control genome-wide association study.\n\nParticipants156,848 women in the multivariable regression and one-sample Mendelian randomization analysis in UK Biobank (7,784 with a breast cancer diagnosis) and 122,977 breast cancer cases and 105,974 controls from BCAC in the two-sample Mendelian randomization analysis.\n\nExposuresSelf-reported chronotype (morning/evening preference), insomnia symptoms and sleep duration in multivariable regression, and genetic variants robustly associated with these sleep traits.\n\nMain outcome measuresBreast cancer (prevalent and incident cases in UK Biobank, prevalent cases only in BCAC).\n\nResultsIn multivariable regression analysis using data on breast cancer incidence in UK Biobank, morning preference was inversely associated with breast cancer (HR 0.95, 95% CI 0.93, 0.98 per category increase) while there was little evidence for an association with sleep duration and insomnia symptoms. Using 341 single nucleotide polymorphisms (SNPs) associated with chronotype, 91 SNPs associated sleep duration and 57 SNPs associated with insomnia symptoms, one-sample MR analysis in UK Biobank provided some supportive evidence for a protective effect of morning preference on breast cancer risk (HR 0.85, 95% 0.70, 1.03 per category increase) but imprecise estimates for sleep duration and insomnia symptoms. Two-sample MR using data from BCAC supported findings for a protective effect of morning preference (OR 0.88, 95% CI 0.82, 0.93 per category increase) and adverse effect of increased sleep duration (OR 1.19, 95% CI 1.02, 1.39 per hour increase) on breast cancer (both estrogen receptor positive and negative), while there was inconsistent evidence for insomnia symptoms. Results were largely robust to sensitivity analyses accounting for horizontal pleiotropy.\n\nConclusionsWe found consistent evidence for a protective effect of morning preference and suggestive evidence for an adverse effect of sleep duration on breast cancer risk.

epidemiology↗

bioRxiv2018

Genome-wide association analysis of excessive daytime sleepiness identifies 42 loci that suggest phenotypic subgroups

Excessive daytime sleepiness (EDS) affects 10-20% of the population and is associated with substantial functional deficits. We identified 42 loci for self-reported EDS in GWAS of 452,071 individuals from the UK Biobank, with enrichment for genes expressed in brain tissues and in neuronal transmission pathways. We confirmed the aggregate effect of a genetic risk score of 42 SNPs on EDS in independent Scandinavian cohorts and on other sleep disorders (restless leg syndrome, insomnia) and sleep traits (duration, chronotype, accelerometer-derived sleep efficiency and daytime naps or inactivity). Strong genetic correlations were also seen with obesity, coronary heart disease, psychiatric diseases, cognitive traits and reproductive ageing. EDS variants clustered into two predominant composite phenotypes - sleep propensity and sleep fragmentation - with the former showing stronger evidence for enriched expression in central nervous system tissues, suggesting two unique mechanistic pathways. Mendelian randomization analysis indicated that higher BMI is causally associated with EDS risk, but EDS does not appear to causally influence BMI.

genomics↗

bioRxiv2018

Variants in the fetal genome near pro-inflammatory cytokine genes on 2q13 are associated with gestational duration

The duration of pregnancy is influenced by fetal and maternal genetic and non-genetic factors. We conducted a fetal genome-wide association meta-analysis of gestational duration, and early preterm, preterm, and postterm birth in 84,689 infants. One locus on chromosome 2q13 was associated with gestational duration; the association was replicated in 9,291 additional infants (combined P = 3.96 x 10-14). Analysis of 15,536 mother-child pairs showed that the association was driven by fetal rather than maternal genotype. Functional experiments showed that the lead SNP, rs7594852, alters the binding of the HIC1 transcriptional repressor. Genes at the locus include several interleukin 1 family members with roles in pro-inflammatory pathways that are central to the process of parturition. Further understanding of the underlying mechanisms will be of great public health importance, since giving birth either before or after the window of term gestation is associated with increased morbidity and mortality.

genetics↗