A novel hypothesis-generating approach for detecting phenotypic associations using epigenetic data.

Aim: Hypotheses about what phenotypes to include in causal analyses, that in turn can have clinical and policy implications, can be guided by hypothesis-free approaches leveraging the epigenome, for example. Materials & methods: Minimally adjusted epigenome-wide association studies (EWAS) using ALSPAC data were performed for example conditions, dysmenorrhea and heavy menstrual bleeding (HMB). Differentially methylated CpGs were searched in the EWAS Catalog and associated traits identified. Traits were compared between those with and without the example conditions in ALSPAC. Results: Seven CpG sites were associated with dysmenorrhea and two with HMB. Smoking and adverse childhood experience score were associated with both conditions in the hypothesis-testing phase. Conclusion: Hypothesis-generating EWAS can help identify associations for future analyses.

To inform policy and improve clinical practice, it is important that researchers who study people's health find out which traits might increase the risk of illness. However, it can be difficult to know which traits should be looked at. In this study, we wanted to look for traits that might increase the risk of painful and heavy periods, using data about the switches that turn our genes on and off. There are some people in the Children of the 90s study that have data on gene switches. We compared all the switches between those with and without painful or heavy periods. For painful periods, we found links with seven switches and for heavy periods, we found two. We then used another data source, called the EWAS Catalog, to see which traits were associated with these switches. The traits we found included body size, smoking and child abuse. Finally, when using data on traits from the wider Children of the 90s group, we found that smoking and more difficult childhoods were some of the traits related to painful and heavy periods. A good thing about this approach is that we could find new traits that might increase the risk of painful or heavy periods; these should be looked at in future studies.

Cardiovascular disease risk factors and infertility: multivariable analyses and one-sample Mendelian randomization analyses in the Trøndelag Health Study.

STUDY QUESTION: Are cardiovascular disease (CVD) risk factors causally associated with higher risk of infertility among women and men? SUMMARY ANSWER: We found evidence to support a causal relationship between smoking initiation and history of infertility in women. WHAT IS KNOWN ALREADY: Several CVD risk factors are associated with history of infertility. Previous studies using Mendelian randomization (MR) further support a causal relationship between BMI and infertility in women. STUDY DESIGN SIZE DURATION: We used data from the Trøndelag Health Study (HUNT) in Norway, a prospective population-based cohort study, including 26 811 women and 15 598 men participating in three survey collections in 1995-1997 (HUNT2), 2006-2008 (HUNT3), and 2017-2019 (HUNT4). PARTICIPANTS/MATERIALS SETTING METHODS: Our outcome was women's self-reported history of infertility, defined as ever having tried to conceive for 12 months or more or having used ART. We assigned the history of infertility reported by women to their male partners; therefore, the measure of infertility was on the couple level. We used both conventional multivariable analyses and one-sample MR analyses to evaluate the association between female and male CVD risk factors (including BMI, blood pressure, lipid profile measurements, and smoking behaviours) and history of infertility in women and men, separately. MAIN RESULTS AND THE ROLE OF CHANCE: A total of 4702 women (18%) and 2508 men (16%) were classified with a history of infertility. We found a higher risk of infertility among female smokers compared to non-smokers in both multivariable and MR analyses (odds ratio (OR) in multivariable analysis, 1.20; 95% CI, 1.12-1.28; OR in MR analysis, 1.13; CI, 1.02-1.26), and potentially for higher BMI (OR in multivariable analysis, 1.13; CI, 1.09-1.18; OR in MR analysis, 1.11, CI, 0.92-1.34). In multivariable analysis in women, we also found evidence of associations between triglyceride levels, high-density lipoprotein cholesterol, lifetime smoking index, and smoking intensity with higher risk of infertility. However, these results were not consistent in MR analyses. We found no robust or consistent associations between male CVD risk factors and infertility. LIMITATIONS REASONS FOR CAUTION: Our main limitation was that the CVD risk factors measured might not adequately capture the relevant time periods for when couples were trying to conceive. Additionally, we did not have information on causes of infertility in either women or men. WIDER IMPLICATIONS OF THE FINDINGS: Women with infertility could have a worse CVD risk factor profile and thus public health interventions aimed at reducing the impact of some CVD risk factors, such as smoking and BMI, could reduce the burden of infertility. However, additional MR studies of the relationship between CVD risk factors and infertility with a larger sample size would be of value. STUDY FUNDING/COMPETING INTERESTS: The study was supported by a grant from the European Research Council under the European Union's Horizon 2020 research and innovation program (grant agreements no. 947684). This research was also supported by the Research Council of Norway through its Centres of Excellence funding scheme (project no. 262700) and partly funded by the Research Council of Norway, project: Women's fertility-an essential component of health and well-being (project no. 320656). D.A.L. and A.F. work in a unit that is supported by the University of Bristol and the UK Medical Research Council (MC_UU_00011/6). D.A.L.'s contribution to the article is supported by the European Research Council (101021566), the British Heart Foundation (CH/F/20/90003 and AA/18/7/34219). S.B.'s contribution to the article is supported by the Wellcome Trust (225790/Z/22/Z). B.M.B. is funded by The Liaison Committee for education, research and innovation in Central Norway; and the Joint Research Committee between St. Olavs Hospital and the Faculty of Medicine and Health Sciences, NTNU. The genotyping in HUNT was financed by the National Institute of Health (NIH); University of Michigan; The Research Council of Norway; The Liaison Committee for education, research and innovation in Central Norway; and the Joint Research Committee between St. Olavs Hospital and the Faculty of Medicine and Health Sciences, NTNU. None of the funding organizations influenced the study design, reporting, or interpretation of results. The views expressed in the present article are those of the authors and not necessarily any acknowledged funding organization. D.A.L. reports grants from Medtronic Ltd and Roche Diagnostics outside the submitted work. The other authors have no conflicts of interest. TRIAL REGISTRATION NUMBER: N/A.

The role of accelerometer-derived sleep traits on glycated haemoglobin and glucose levels: a Mendelian randomization study.

Self-reported shorter/longer sleep duration, insomnia, and evening preference are associated with hyperglycaemia in observational analyses, with similar observations in small studies using accelerometer-derived sleep traits. Mendelian randomization (MR) studies support an effect of self-reported insomnia, but not others, on glycated haemoglobin (HbA1c). To explore potential effects, we used MR methods to assess effects of accelerometer-derived sleep traits (duration, mid-point least active 5-h, mid-point most active 10-h, sleep fragmentation, and efficiency) on HbA1c/glucose in European adults from the UK Biobank (UKB) (n = 73,797) and the MAGIC consortium (n = 146,806). Cross-trait linkage disequilibrium score regression was applied to determine genetic correlations across accelerometer-derived, self-reported sleep traits, and HbA1c/glucose. We found no causal effect of any accelerometer-derived sleep trait on HbA1c or glucose. Similar MR results for self-reported sleep traits in the UKB sub-sample with accelerometer-derived measures suggested our results were not explained by selection bias. Phenotypic and genetic correlation analyses suggested complex relationships between self-reported and accelerometer-derived traits indicating that they may reflect different types of exposure. These findings suggested accelerometer-derived sleep traits do not affect HbA1c. Accelerometer-derived measures of sleep duration and quality might not simply be 'objective' measures of self-reported sleep duration and insomnia, but rather captured different sleep characteristics.

Prenatal Urban Environment and Blood Pressure Trajectories From Childhood to Early Adulthood.

Background: Prenatal urban environmental exposures have been associated with blood pressure in children. The dynamic of these associations across childhood and later ages is unknown. Objectives: The purpose of this study was to assess associations of prenatal urban environmental exposures with blood pressure trajectories from childhood to early adulthood. Methods: Repeated measures of systolic blood pressure (SBP) and diastolic blood pressure (DBP) were collected in up to 7,454 participants from a UK birth cohort. Prenatal urban exposures (n = 43) covered measures of noise, air pollution, built environment, natural spaces, traffic, meteorology, and food environment. An exposome-wide association study approach was used. Linear spline mixed-effects models were used to model associations of each exposure with trajectories of blood pressure. Replication was sought in 4 independent European cohorts (up to 9,261). Results: In discovery analyses, higher humidity was associated with a faster increase (mean yearly change in SBP for an interquartile range increase in humidity: 0.29 mm Hg/y, 95% CI: 0.20-0.39) and higher temperature with a slower increase (mean yearly change in SBP per interquartile range increase in temperature: -0.17 mm Hg/y, 95% CI: -0.28 to -0.07) in SBP in childhood. Higher levels of humidity and air pollution were associated with faster increase in DBP in childhood and slower increase in adolescence. There was little evidence of an association of other exposures with change in SBP or DBP. Results for humidity and temperature, but not for air pollution, were replicated in other cohorts. Conclusions: Replicated findings suggest that higher prenatal humidity and temperature could modulate blood pressure changes across childhood.

Green space exposure and blood DNA methylation at birth and in childhood - A multi-cohort study.

Green space exposure has been associated with improved mental, physical and general health. However, the underlying biological mechanisms remain largely unknown. The aim of this study was to investigate the association between green space exposure and cord and child blood DNA methylation. Data from eight European birth cohorts with a total of 2,988 newborns and 1,849 children were used. Two indicators of residential green space exposure were assessed: (i) surrounding greenness (satellite-based Normalized Difference Vegetation Index (NDVI) in buffers of 100 m and 300 m) and (ii) proximity to green space (having a green space ≥ 5,000 m2 within a distance of 300 m). For these indicators we assessed two exposure windows: (i) pregnancy, and (ii) the period from pregnancy to child blood DNA methylation assessment, named as cumulative exposure. DNA methylation was measured with the Illumina 450K or EPIC arrays. To identify differentially methylated positions (DMPs) we fitted robust linear regression models between pregnancy green space exposure and cord blood DNA methylation and between cumulative green space exposure and child blood DNA methylation. Two sensitivity analyses were conducted: (i) without adjusting for cellular composition, and (ii) adjusting for air pollution. Cohort results were combined through fixed-effect inverse variance weighted meta-analyses. Differentially methylated regions (DMRs) were identified from meta-analysed results using the Enmix-combp and DMRcate methods. There was no statistical evidence of pregnancy or cumulative exposures associating with any DMP (False Discovery Rate, FDR, p-value < 0.05). However, surrounding greenness exposure was inversely associated with four DMRs (three in cord blood and one in child blood) annotated to ADAMTS2, KCNQ1DN, SLC6A12 and SDK1 genes. Results did not change substantially in the sensitivity analyses. Overall, we found little evidence of the association between green space exposure and blood DNA methylation. Although we identified associations between surrounding greenness exposure with four DMRs, these findings require replication.

Epidural analgesia during labour and severe maternal morbidity: population based study.

OBJECTIVES: To determine the effect of labour epidural on severe maternal morbidity (SMM) and to explore whether this effect might be greater in women with a medical indication for epidural analgesia during labour, or with preterm labour. DESIGN: Population based study. SETTING: All NHS hospitals in Scotland. PARTICIPANTS: 567 216 women in labour at 24+0 to 42+6 weeks' gestation between 1 January 2007 and 31 December 2019, delivering vaginally or through unplanned caesarean section. MAIN OUTCOME MEASURES: The primary outcome was SMM, defined as the presence of ≥1 of 21 conditions used by the US Centers for Disease Control and Prevention (CDC) as criteria for SMM, or a critical care admission, with either occurring at any point from date of delivery to 42 days post partum (described as SMM). Secondary outcomes included a composite of ≥1 of the 21 CDC conditions and critical care admission (SMM plus critical care admission), and respiratory morbidity. RESULTS: Of the 567 216 women, 125 024 (22.0%) had epidural analgesia during labour. SMM occurred in 2412 women (4.3 per 1000 births, 95% confidence interval (CI) 4.1 to 4.4). Epidural analgesia was associated with a reduction in SMM (adjusted relative risk 0.65, 95% CI 0.50 to 0.85), SMM plus critical care admission (0.46, 0.29 to 0.73), and respiratory morbidity (0.42, 0.16 to 1.15), although the last of these was underpowered and had wide confidence intervals. Greater risk reductions in SMM were detected among women with a medical indication for epidural analgesia (0.50, 0.34 to 0.72) compared with those with no such indication (0.67, 0.43 to 1.03; P<0.001 for difference). More marked reductions in SMM were seen in women delivering preterm (0.53, 0.37 to 0.76) compared with those delivering at term or post term (1.09, 0.98 to 1.21; P<0.001 for difference). The observed reduced risk of SMM with epidural analgesia was increasingly noticeable as gestational age at birth decreased in the whole cohort, and in women with a medical indication for epidural analgesia. CONCLUSION: Epidural analgesia during labour was associated with a 35% reduction in SMM, and showed a more pronounced effect in women with medical indications for epidural analgesia and with preterm births. Expanding access to epidural analgesia for all women during labour, and particularly for those at greatest risk, could improve maternal health.

Born in Bradford's Age of Wonder cohort: protocol for adolescent data collection.

Background: Adolescence and transition into adulthood are periods shaping life-long mental health, cardiometabolic risk, and inequalities. However, they are poorly studied and understood. By extending and expanding the Born in Bradford (BiB) cohort study through this period using innovative, co-produced approaches to collect and analyse data, we aim to understand better the interplay of factors that influence health and wellbeing, and inform/evaluate interventions to improve them and reduce inequalities. Protocol: BiB Age of Wonder (AoW) is a large, whole city cohort that will capture the contemporary lived experience amongst multi-ethnic adolescents progressing into young adulthood. We will collect repeated data from existing BiB participants and their peers (N~30,000 adolescents). The protocol for the first phase of the quantitative methods, involving survey measurements and health assessments in mainstream secondary schools is described here. We describe the co-production behind these methods, and lessons learned from the first year of data collection.

Born in Bradford have been following the health and wellbeing of over 13,000 Bradford children since they were born. This group of children are now in their teenage years ­ a time that is crucial for their future mental and physical health. Age of Wonder aims to capture this journey through adolescence and early adulthood with up to 30,000 young people in Bradford over 7 years. In the first phase of this project, data collection is taking part in secondary schools in Bradford. This protocol describes how this data collection is currently being carried out in the schools. Young people aged 12-15 are being asked to complete questionnaires, covering topics such as mental and physical health. These topics have been designed with groups of young people, schools and other partners, to make sure we are capturing data on the things most important to young people. Those in Year 9 (13-14 years old), are also asked to take part in physical health measurements such as height, weight, blood pressure and a blood sample, as well as computer-based assessments of cognition (memory), movement and language. There have been a number of lessons learned from the first full year of data collection, such as how to make the research as easy as possible for schools to take part in when they have so many competing demands on their time.

Social inequalities in pregnancy metabolic profile: findings from the multi-ethnic Born in Bradford cohort study.

BACKGROUND: Lower socioeconomic position (SEP) associates with adverse pregnancy and perinatal outcomes and with less favourable metabolic profile in nonpregnant adults. Socioeconomic differences in pregnancy metabolic profile are unknown. We investigated association between a composite measure of SEP and pregnancy metabolic profile in White European (WE) and South Asian (SA) women. METHODS: We included 3,905 WE and 4,404 SA pregnant women from a population-based UK cohort. Latent class analysis was applied to nineteen individual, household, and area-based SEP indicators (collected by questionnaires or linkage to residential address) to derive a composite SEP latent variable. Targeted nuclear magnetic resonance spectroscopy was used to determine 148 metabolic traits from mid-pregnancy serum samples. Associations between SEP and metabolic traits were examined using linear regressions adjusted for gestational age and weighted by latent class probabilities. RESULTS: Five SEP sub-groups were identified and labelled 'Highest SEP' (48% WE and 52% SA), 'High-Medium SEP' (77% and 23%), 'Medium SEP' (56% and 44%) 'Low-Medium SEP' (21% and 79%), and 'Lowest SEP' (52% and 48%). Lower SEP was associated with more adverse levels of 113 metabolic traits, including lower high-density lipoprotein (HDL) and higher triglycerides and very low-density lipoprotein (VLDL) traits. For example, mean standardized difference (95%CI) in concentration of small VLDL particles (vs. Highest SEP) was 0.12 standard deviation (SD) units (0.05 to 0.20) for 'Medium SEP' and 0.25SD (0.18 to 0.32) for 'Lowest SEP'. There was statistical evidence of ethnic differences in associations of SEP with 31 traits, primarily characterised by stronger associations in WE women e.g., mean difference in HDL cholesterol in WE and SA women respectively (vs. Highest-SEP) was -0.30SD (-0.41 to -0.20) and -0.16SD (-0.27 to -0.05) for 'Medium SEP', and -0.62SD (-0.72 to -0.52) and -0.29SD (-0.40 to -0.20) for 'Lowest SEP'. CONCLUSIONS: We found widespread socioeconomic differences in metabolic traits in pregnant WE and SA women residing in the UK. Further research is needed to understand whether the socioeconomic differences we observe here reflect pre-conception differences or differences in the metabolic pregnancy response. If replicated, it would be important to explore if these differences contribute to socioeconomic differences in pregnancy outcomes.

Differences between brachial and aortic blood pressure in adolescence and their implications for diagnosis of hypertension.

OBJECTIVES: Blood pressure (BP) is the leading global cause of mortality, and its prevalence is increasing in children and adolescents. Aortic BP is lower than brachial BP in adults. We aimed to assess the extent of this difference and its impact on the diagnosis of hypertension among adolescents. METHODS: We used data from 3850 participants from a UK cohort of births in the early 1990s in the Southwest of England, who attended their ∼17-year follow-up and had valid measures of brachial and aortic BP at that clinic [mean (SD) age 17.8 (0.4) years, 66% female individuals]. Data are presented as mean differences [95% prediction intervals] for both sexes. RESULTS: Aortic systolic BP (SBP) was lower than brachial SBP [male, -22.3 (-31.2, -13.3) mmHg; female, -17.8 (-25.5, -10.0) mmHg]. Differences between aortic and brachial diastolic BP (DBP) were minimal. Based on brachial BP measurements, 101 male individuals (6%) and 22 female individuals (1%) were classified as hypertensive. In contrast, only nine male individuals (<1%) and 14 female individuals (<1%) met the criteria for hypertension based on aortic BP, and the predictive value of brachial BP for aortic hypertension was poor (positive-predictive value = 13.8%). Participants with aortic hypertension had a higher left ventricular mass index than those with brachial hypertension. CONCLUSION: Brachial BP substantially overestimates aortic BP in adolescents because of marked aortic-to-brachial pulse pressure amplification. The use of brachial BP measurement may result in an overdiagnosis of hypertension during screening in adolescence.

Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum.

Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (P≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (rg=0.585, P=8.98E-14), and between polycystic ovary syndrome and anovulatory infertility (rg=0.403, P=2.16E-03). The evolutionary persistence of female infertility-risk alleles in EBAG9 may be explained by recent directional selection. We additionally identified up to 269 genetic loci associated with follicle-stimulating hormone (FSH), luteinising hormone, oestradiol, and testosterone through sex-specific GWAS meta-analyses (N=6,095-246,862). While hormone-associated variants near FSHB and ARL14EP colocalised with signals for anovulatory infertility, we found no rg between female infertility and reproductive hormones (P>0.05). Exome sequencing analyses in the UK Biobank (N=197,340) revealed that women carrying testosterone-lowering rare variants in GPC2 were at higher risk of infertility (OR=2.63, P=1.25E-03). Taken together, our results suggest that while individual genes associated with hormone regulation may be relevant for fertility, there is limited genetic evidence for correlation between reproductive hormones and infertility at the population level. We provide the first comprehensive view of the genetic architecture of infertility across multiple diagnostic criteria in men and women, and characterise its relationship to other health conditions.

A framework for conducting time-varying genome-wide association studies: An application to body mass index across childhood in six multiethnic cohorts.

Genetic effects on changes in human traits over time are understudied and may have important pathophysiological impact. We propose a framework that enables data quality control, implements mixed models to evaluate trajectories of change in traits, and estimates phenotypes to identify age-varying genetic effects in genome-wide association studies (GWASs). Using childhood body mass index (BMI) as an example, we included 71,336 participants from six cohorts and estimated the slope and area under the BMI curve within four time periods (infancy, early childhood, late childhood and adolescence) for each participant, in addition to the age and BMI at the adiposity peak and the adiposity rebound. GWAS on each of the estimated phenotypes identified 28 genome-wide significant variants at 13 loci across the 12 estimated phenotypes, one of which was novel (in DAOA) and had not been previously associated with childhood or adult BMI. Genetic studies of changes in human traits over time could uncover novel biological mechanisms influencing quantitative traits.

Genome-wide association analysis of composite sleep health scores in 413,904 individuals.

Recent genome-wide association studies (GWASs) of several individual sleep traits have identified hundreds of genetic loci, suggesting diverse mechanisms. Moreover, sleep traits are moderately correlated, and together may provide a more complete picture of sleep health, while also illuminating distinct domains. Here we construct novel sleep health scores (SHSs) incorporating five core self-report measures: sleep duration, insomnia symptoms, chronotype, snoring, and daytime sleepiness, using additive (SHS-ADD) and five principal components-based (SHS-PCs) approaches. GWASs of these six SHSs identify 28 significant novel loci adjusting for multiple testing on six traits (p<8.3e-9), along with 341 previously reported loci (p<5e-08). The heritability of the first three SHS-PCs equals or exceeds that of SHS-ADD (SNP-h2=0.094), while revealing sleep-domain-specific genetic discoveries. Significant loci enrich in multiple brain tissues and in metabolic and neuronal pathways. Post GWAS analyses uncover novel genetic mechanisms underlying sleep health and reveal connections to behavioral, psychological, and cardiometabolic traits.

Urban environment in pregnancy and postpartum depression: An individual participant data meta-analysis of 12 European birth cohorts.

BACKGROUND: Urban environmental exposures associate with adult depression, but it is unclear whether they are associated to postpartum depression (PPD). OBJECTIVES: We investigated associations between urban environment exposures during pregnancy and PPD. METHODS: We included women with singleton deliveries to liveborn children from 12 European birth cohorts (N with minimum one exposure = 30,772, analysis N range 17,686-30,716 depending on exposure; representing 26-46 % of the 66,825 eligible women). We estimated maternal exposure during pregnancy to ambient air pollution with nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10), road traffic noise (Lden), natural spaces (Normalised Difference Vegetation Index; NDVI, proximity to major green or blue spaces) and built environment (population density, facility richness and walkability). Maternal PPD was assessed 3-18 months after birth using self-completed questionnaires. We used adjusted logistic regression models to estimate cohort-specific associations between each exposure and PPD and combined results via meta-analysis using DataSHIELD. RESULTS: Of the 30,772 women included, 3,078 (10 %) reported having PPD. Exposure to PM10 was associated with slightly increased odds of PPD (adjusted odd ratios (OR) of 1.08 [95 % Confidence Intervals (CI): 0.99, 1.17] per inter quartile range increment of PM10) whilst associations for exposure to NO2 and PM2.5 were close to null. Exposure to high levels of road traffic noise (≥65 dB vs. < 65 dB) was associated with an OR of 1.12 [CI: 0.95, 1.32]. Associations between green spaces and PPD were close to null; whilst proximity to major blue spaces was associated with increased risk of PPD (OR 1.12, 95 %CI: 1.00, 1.26). All associations between built environment and PPD were close to null. Multiple exposure models showed similar results. DISCUSSION: The study findings suggest that exposure to PM10, road traffic noise and blue spaces in pregnancy may increase PPD risk, however future studies should explore this causally.

The impact of reproductive factors on the metabolic profile of females from menarche to menopause.

We explore the relation between age at menarche, parity and age at natural menopause with 249 metabolic traits in over 65,000 UK Biobank women using multivariable regression, Mendelian randomization and negative control (parity only). Older age of menarche is related to a less atherogenic metabolic profile in multivariable regression and Mendelian randomization, which is largely attenuated when accounting for adult body mass index. In multivariable regression, higher parity relates to more particles and lipids in VLDL, which are not observed in male negative controls. In multivariable regression and Mendelian randomization, older age at natural menopause is related to lower concentrations of inflammation markers, but we observe inconsistent results for LDL-related traits due to chronological age-specific effects. For example, older age at menopause is related to lower LDL-cholesterol in younger women but slightly higher in older women. Our findings support a role of reproductive traits on later life metabolic profile and provide insights into identifying novel markers for the prevention of adverse cardiometabolic outcomes in women.

Parental infertility and offspring cardiometabolic trajectories: a pooled analysis of three European cohorts.

OBJECTIVE: To assess whether parental infertility is associated with differences in cardiometabolic trajectories in offspring. DESIGN: Pooled observational analysis in three prospective cohorts. SETTING: Three nationwide pregnancy cohorts. PATIENTS: A total of 14,609 singletons from the UK Avon Longitudinal Study of Parents and Children, the Portuguese Geraçao 21, and the Amsterdam Born Children and Their Development study. Each cohort contributed data up to ages 26, 12, and 13 years, respectively. INTERVENTION: Parental infertility is defined as time-to-pregnancy of ≥12 months (n = 1,392, 9.5%). MAIN OUTCOME MEASURES: Trajectories of body mass index (BMI), waist circumference, systolic blood pressure, diastolic blood pressure, low-density lipoprotein cholesterol (LDL-C) level, high-density lipoprotein cholesterol (HDL-C) level, triglycerides level, and glucose level were compared in the offspring of couples with and without infertility. Trajectories were modeled using mixed-effects models with natural cubic splines adjusting for cohort, sex of the offspring, and maternal factors (age, BMI, smoking, educational level, parity, and ethnicity). Predicted levels of cardiometabolic traits up to 25 years of age were compared with parental infertility. RESULTS: Offspring of couples with infertility had increasingly higher BMI (difference in mean predicted levels by age 25 years: 1.09 kg/m2, 95% confidence interval [0.68-1.50]) and suggestively higher diastolic blood pressure at age 25 years (1.21 mmHg [-0.003 to 2.43]). Their LDL-C tended to be higher, and their HDL-C values tended to be lower over time (age: 25 years, LDL-C: 4.07% [-0.79 to 8.93]; HDL-C: -2.78% [-6.99 to 1.43]). At age 17 years, offspring of couples with infertility had higher waist circumference (1.05 cm [0.11-1.99]) and systolic blood pressure (age: 17 years; 0.93 mmHg [0.044-1.81]), but these differences attenuated at later ages. No intergroup differences in triglyceride and glucose level trajectories were observed. Further adjustment for paternal age, BMI, smoking, and educational level, and both parents' histories of diabetes and hypertension in the cohort with this information available (Avon Longitudinal Study of Parents and Children) did not attenuate intergroup differences. CONCLUSION: Offspring of couples with infertility relative to those of fertile couples have increasingly higher BMI over the years, suggestively higher blood pressure levels, and tend to have greater values of LDL-C and lower values of HDL-C with age.

Meta-regression of genome-wide association studies to estimate age-varying genetic effects.

Fixed-effect meta-analysis has been used to summarize genetic effects on a phenotype across multiple Genome-Wide Association Studies (GWAS) assuming a common underlying genetic effect. Genetic effects may vary with age (or other characteristics), and not allowing for this in a GWAS might lead to bias. Meta-regression models between study heterogeneity and allows effect modification of the genetic effects to be explored. The aim of this study was to explore the use of meta-analysis and meta-regression for estimating age-varying genetic effects on phenotypes. With simulations we compared the performance of meta-regression to fixed-effect and random -effects meta-analyses in estimating (i) main genetic effects and (ii) age-varying genetic effects (SNP by age interactions) from multiple GWAS studies under a range of scenarios. We applied meta-regression on publicly available summary data to estimate the main and age-varying genetic effects of the FTO SNP rs9939609 on Body Mass Index (BMI). Fixed-effect and random-effects meta-analyses accurately estimated genetic effects when these did not change with age. Meta-regression accurately estimated both main genetic effects and age-varying genetic effects. When the number of studies or the age-diversity between studies was low, meta-regression had limited power. In the applied example, each additional minor allele (A) of rs9939609 was inversely associated with BMI at ages 0 to 3, and positively associated at ages 5.5 to 13. Our findings challenge the assumption that genetic effects are consistent across all ages and provide a method for exploring this. GWAS consortia should be encouraged to use meta-regression to explore age-varying genetic effects.

Prospective study design and data analysis in UK Biobank.

Population-based prospective studies, such as UK Biobank, are valuable for generating and testing hypotheses about the potential causes of human disease. We describe how UK Biobank's study design, data access policies, and approaches to statistical analysis can help to minimize error and improve the interpretability of research findings, with implications for other population-based prospective studies being established worldwide.