Do sex hormones confound or mediate the effect of chronotype on breast and prostate cancer? A Mendelian randomization study.

Morning-preference chronotype has been found to be protective against breast and prostate cancer. Sex hormones have been implicated in relation to chronotype and the development of both cancers. This study aimed to assess whether sex hormones confound or mediate the effect of chronotype on breast and prostate cancer using a Mendelian Randomization (MR) framework. Genetic variants associated with chronotype and sex hormones (total testosterone, bioavailable testosterone, sex hormone binding globulin, and oestradiol) (p<5×10-8) were obtained from published genome-wide association studies (n≤244,207 females and n≤205,527 males). These variants were used to investigate causal relationships with breast (nCases/nControls = 133,384/113,789) and prostate (nCases/nControls = 79,148/61,106) cancer using univariable, bidirectional and multivariable MR. In females, we found evidence for: I) Reduced risk of breast cancer per category increase in morning-preference (OR = 0.93, 95% CI:0. 88, 1.00); II) Increased risk of breast cancer per SD increase in bioavailable testosterone (OR = 1.10, 95% CI: 1.01, 1.19) and total testosterone (OR = 1.15, 95% CI:1.07, 1.23); III) Bidirectional effects between morning-preference and both bioavailable and total testosterone (e.g. mean SD difference in bioavailable testosterone = -0.08, 95% CI:-0.12, -0.05 per category increase in morning-preference vs difference in morning-preference category = -0.04, 95% CI: -0.08, 0.00 per SD increase in bioavailable testosterone). In males, we found evidence for: I) Reduced risk of prostate cancer per category increase in morning-preference (OR = 0.90, 95% CI: 0.83, 0.97) and II) Increased risk of prostate cancer per SD increase in bioavailable testosterone (OR = 1.22, 95% CI: 1.08, 1.37). No bidirectional effects were found between morning-preference and testosterone in males. While testosterone levels were causally implicated with both chronotype and cancer, there was inconsistent evidence for testosterone as a mediator of the relationship. The protective effect of morning-preference on both breast and prostate cancer is clinically interesting, although it may be difficult to effectively modify chronotype. Further studies are needed to investigate other potentially modifiable intermediates.

The impact of fatty acids biosynthesis on the risk of cardiovascular diseases in Europeans and East Asians: a Mendelian randomization study.

Despite early interest, the evidence linking fatty acids to cardiovascular diseases (CVDs) remains controversial. We used Mendelian randomization to explore the involvement of polyunsaturated (PUFA) and monounsaturated (MUFA) fatty acids biosynthesis in the etiology of several CVD endpoints in up to 1 153 768 European (maximum 123 668 cases) and 212 453 East Asian (maximum 29 319 cases) ancestry individuals. As instruments, we selected single nucleotide polymorphisms mapping to genes with well-known roles in PUFA (i.e. FADS1/2 and ELOVL2) and MUFA (i.e. SCD) biosynthesis. Our findings suggest that higher PUFA biosynthesis rate (proxied by rs174576 near FADS1/2) is related to higher odds of multiple CVDs, particularly ischemic stroke, peripheral artery disease and venous thromboembolism, whereas higher MUFA biosynthesis rate (proxied by rs603424 near SCD) is related to lower odds of coronary artery disease among Europeans. Results were unclear for East Asians as most effect estimates were imprecise. By triangulating multiple approaches (i.e. uni-/multi-variable Mendelian randomization, a phenome-wide scan, genetic colocalization and within-sibling analyses), our results are compatible with higher low-density lipoprotein (LDL) cholesterol (and possibly glucose) being a downstream effect of higher PUFA biosynthesis rate. Our findings indicate that PUFA and MUFA biosynthesis are involved in the etiology of CVDs and suggest LDL cholesterol as a potential mediating trait between PUFA biosynthesis and CVDs risk.

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

BACKGROUND: Higher birthweight is associated with higher adult body mass index (BMI). Alleles that predispose to greater adult adiposity might act in fetal life to increase fetal growth and birthweight. Whether there are fetal effects of recently identified adult metabolically favorable adiposity alleles on birthweight is unknown. AIM: We aimed to test the effect on birthweight of fetal genetic predisposition to higher metabolically favorable adult adiposity and compare that with the effect of fetal genetic predisposition to higher adult BMI. METHODS: We used published genome wide association study data (n = upto 406 063) to estimate fetal effects on birthweight (adjusting for maternal genotype) of alleles known to raise metabolically favorable adult adiposity or BMI. We combined summary data across single nucleotide polymorphisms (SNPs) with random effects meta-analyses. We performed weighted linear regression of SNP-birthweight effects against SNP-adult adiposity effects to test for a dose-dependent association. RESULTS: Fetal genetic predisposition to higher metabolically favorable adult adiposity and higher adult BMI were both associated with higher birthweight (3 g per effect allele (95% CI: 1-5) averaged over 14 SNPs; P = 0.002; 0.5 g per effect allele (95% CI: 0-1) averaged over 76 SNPs; P = 0.042, respectively). SNPs with greater effects on metabolically favorable adiposity tended to have greater effects on birthweight (R2 = 0.2912, P = 0.027). There was no dose-dependent association for BMI (R2 = -0.0019, P = 0.602). CONCLUSIONS: Fetal genetic predisposition to both higher adult metabolically favorable adiposity and BMI is associated with birthweight. Fetal effects of metabolically favorable adiposity-raising alleles on birthweight are modestly proportional to their effects on future adiposity, but those of BMI-raising alleles are not.

Parental genetically predicted liability for coronary heart disease and risk of adverse pregnancy outcomes: a cohort study.

BACKGROUND: Adverse pregnancy outcomes (APO) may unmask or exacerbate a woman's underlying risk for coronary heart disease (CHD). We estimated associations of maternal and paternal genetically predicted liability for CHD with lifelong risk of APOs. We hypothesized that associations would be found for women, but not their male partners (negative controls). METHODS: We studied up to 83,969‬ women (and up to 55,568‬ male partners) from the Norwegian Mother, Father and Child Cohort Study or the Trøndelag Health Study with genotyping data and lifetime history of any APO in their pregnancies (1967-2019) in the Medical Birth Registry of Norway (miscarriage, stillbirth, hypertensive disorders of pregnancy, gestational diabetes, small for gestational age, large for gestational age, and spontaneous preterm birth). Maternal and paternal genetic risk scores (GRS) for CHD were generated using 148 gene variants (p-value < 5 × 10-8, not in linkage disequilibrium). Associations between GRS for CHD and each APO were determined using logistic regression, adjusting for genomic principal components, in each cohort separately, and combined using fixed effects meta-analysis. RESULTS: One standard deviation higher GRS for CHD in women was related to increased risk of any hypertensive disorders of pregnancy (odds ratio [OR] 1.08, 95% confidence interval [CI] 1.05-1.10), pre-eclampsia (OR 1.08, 95% CI 1.05-1.11), and small for gestational age (OR 1.04, 95% CI 1.01-1.06). Imprecise associations with lower odds of large for gestational age (OR 0.98, 95% CI 0.96-1.00) and higher odds of stillbirth (OR 1.04, 95% CI 0.98-1.11) were suggested. These findings remained consistent after adjusting for number of total pregnancies and the male partners' GRS and restricting analyses to stable couples. Associations for other APOs were close to the null. There was weak evidence of an association of paternal genetically predicted liability for CHD with spontaneous preterm birth in female partners (OR 1.02, 95% CI 0.99-1.05), but not with other APOs. CONCLUSIONS: Hypertensive disorders of pregnancy, small for gestational age, and stillbirth may unmask women with a genetically predicted propensity for CHD. The association of paternal genetically predicted CHD risk with spontaneous preterm birth in female partners needs further exploration.

Integrating multiple lines of evidence to assess the effects of maternal BMI on pregnancy and perinatal outcomes.

BACKGROUND: Higher maternal pre-pregnancy body mass index (BMI) is associated with adverse pregnancy and perinatal outcomes. However, whether these associations are causal remains unclear. METHODS: We explored the relation of maternal pre-/early-pregnancy BMI with 20 pregnancy and perinatal outcomes by integrating evidence from three different approaches (i.e. multivariable regression, Mendelian randomisation, and paternal negative control analyses), including data from over 400,000 women. RESULTS: All three analytical approaches supported associations of higher maternal BMI with lower odds of maternal anaemia, delivering a small-for-gestational-age baby and initiating breastfeeding, but higher odds of hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, caesarean section, large-for-gestational age, high birthweight, low Apgar score at 1 min, and neonatal intensive care unit admission. For example, higher maternal BMI was associated with higher risk of gestational hypertension in multivariable regression (OR = 1.67; 95% CI = 1.63, 1.70 per standard unit in BMI) and Mendelian randomisation (OR = 1.59; 95% CI = 1.38, 1.83), which was not seen for paternal BMI (OR = 1.01; 95% CI = 0.98, 1.04). Findings did not support a relation between maternal BMI and perinatal depression. For other outcomes, evidence was inconclusive due to inconsistencies across the applied approaches or substantial imprecision in effect estimates from Mendelian randomisation. CONCLUSIONS: Our findings support a causal role for maternal pre-/early-pregnancy BMI on 14 out of 20 adverse pregnancy and perinatal outcomes. Pre-conception interventions to support women maintaining a healthy BMI may reduce the burden of obstetric and neonatal complications. FUNDING: Medical Research Council, British Heart Foundation, European Research Council, National Institutes of Health, National Institute for Health Research, Research Council of Norway, Wellcome Trust.

Impaired glucose tolerance and cardiovascular risk factors in relation to infertility: a Mendelian randomization analysis in the Norwegian Mother, Father, and Child Cohort Study.

STUDY QUESTION: Are impaired glucose tolerance (as measured by fasting glucose, glycated hemoglobin, and fasting insulin) and cardiovascular disease risk (as measured by low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, triglycerides, systolic blood pressure, and diastolic blood pressure) causally related to infertility? SUMMARY ANSWER: Genetic instruments suggest that higher fasting insulin may increase infertility in women. WHAT IS KNOWN ALREADY: Observational evidence suggests a shared etiology between impaired glucose tolerance, cardiovascular risk, and fertility problems. STUDY DESIGN, SIZE, DURATION: This study included two-sample Mendelian randomization (MR) analyses, in which we used genome-wide association summary data that were publicly available for the biomarkers of impaired glucose tolerance and cardiovascular disease, and sex-specific genome-wide association studies (GWASs) of infertility conducted in the Norwegian Mother, Father, and Child Cohort Study. PARTICIPANTS/MATERIALS, SETTING, METHODS: There were 68 882 women (average age 30, involved in 81 682 pregnancies) and 47 474 of their male partners (average age 33, 55 744 pregnancies) who had available genotype data and who provided self-reported information on time-to-pregnancy and use of ARTs. Of couples, 12% were infertile (having tried to conceive for ≥12 months or used ARTs to conceive). We applied the inverse variance weighted method with random effects to pool data across variants and a series of sensitivity analyses to explore genetic instrument validity. (We checked the robustness of genetic instruments and the lack of unbalanced horizontal pleiotropy, and we used methods that are robust to population stratification.) Findings were corrected for multiple comparisons by the Bonferroni method (eight exposures: P-value < 0.00625). MAIN RESULTS AND THE ROLE OF CHANCE: In women, increases in genetically determined fasting insulin levels were associated with greater odds of infertility (+1 log(pmol/l): odds ratio 1.60, 95% CI 1.17 to 2.18, P-value = 0.003). The results were robust in the sensitivity analyses exploring the validity of MR assumptions and the role of pleiotropy of other cardiometabolic risk factors. There was also evidence of higher glucose and glycated hemoglobin causing infertility in women, but the findings were imprecise and did not pass our P-value threshold for multiple testing. The results for lipids and blood pressure were close to the null, suggesting that these did not cause infertility. LIMITATIONS, REASONS FOR CAUTION: We did not know if underlying causes of infertility were in the woman, man, or both. Our analyses only involved couples who had conceived. We did not have data on circulating levels of cardiometabolic risk factors, and we opted to conduct an MR analysis using GWAS summary statistics. No sex-specific genetic instruments on cardiometabolic risk factors were available. Our results may be affected by selection and misclassification bias. Finally, the characteristics of our study sample limit the generalizability of our results to populations of non-European ancestry. WIDER IMPLICATIONS OF THE FINDINGS: Treatments for lower fasting insulin levels may reduce the risk of infertility in women. STUDY FUNDING/COMPETING INTEREST(S): The MoBa Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Norwegian Ministry of Education and Research. This work was supported by the European Research Council [grant numbers 947684, 101071773, 293574, 101021566], the Research Council of Norway [grant numbers 262700, 320656, 274611], the South-Eastern Norway Regional Health Authority [grant numbers 2020022, 2021045], and the British Heart Foundation [grant numbers CH/F/20/90003, AA/18/1/34219]. Open Access funding was provided by the Norwegian Institute of Public Health. The funders had no role in the study design; the collection, analysis, and interpretation of data; the writing of the report; or the decision to submit the article for publication. D.A.L. has received research support from National and International government and charitable bodies, Roche Diagnostics and Medtronic for research unrelated to the current work. O.A.A. has been a consultant to HealthLytix. The rest of the authors declare that no competing interests exist. TRIAL REGISTRATION NUMBER: N/A.

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.

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.

Exploiting collider bias to apply two-sample summary data Mendelian randomization methods to one-sample individual level data.

Over the last decade the availability of SNP-trait associations from genome-wide association studies has led to an array of methods for performing Mendelian randomization studies using only summary statistics. A common feature of these methods, besides their intuitive simplicity, is the ability to combine data from several sources, incorporate multiple variants and account for biases due to weak instruments and pleiotropy. With the advent of large and accessible fully-genotyped cohorts such as UK Biobank, there is now increasing interest in understanding how best to apply these well developed summary data methods to individual level data, and to explore the use of more sophisticated causal methods allowing for non-linearity and effect modification. In this paper we describe a general procedure for optimally applying any two sample summary data method using one sample data. Our procedure first performs a meta-analysis of summary data estimates that are intentionally contaminated by collider bias between the genetic instruments and unmeasured confounders, due to conditioning on the observed exposure. These estimates are then used to correct the standard observational association between an exposure and outcome. Simulations are conducted to demonstrate the method's performance against naive applications of two sample summary data MR. We apply the approach to the UK Biobank cohort to investigate the causal role of sleep disturbance on HbA1c levels, an important determinant of diabetes. Our approach can be viewed as a generalization of Dudbridge et al. (Nat. Comm. 10: 1561), who developed a technique to adjust for index event bias when uncovering genetic predictors of disease progression based on case-only data. Our work serves to clarify that in any one sample MR analysis, it can be advantageous to estimate causal relationships by artificially inducing and then correcting for collider bias.

Sleep duration in preschool age and later behavioral and cognitive outcomes: an individual participant data meta-analysis in five European cohorts.

Short sleep duration has been linked to adverse behavioral and cognitive outcomes in schoolchildren, but few studies examined this relation in preschoolers. We aimed to investigate the association between parent-reported sleep duration at 3.5 years and behavioral and cognitive outcomes at 5 years in European children. We used harmonized data from five cohorts of the European Union Child Cohort Network: ALSPAC, SWS (UK); EDEN, ELFE (France); INMA (Spain). Associations were estimated through DataSHIELD using adjusted generalized linear regression models fitted separately for each cohort and pooled with random-effects meta-analysis. Behavior was measured with the Strengths and Difficulties Questionnaire. Language and non-verbal intelligence were assessed by the Wechsler Preschool and Primary Scale of Intelligence or the McCarthy Scales of Children's Abilities. Behavioral and cognitive analyses included 11,920 and 2981 children, respectively (34.0%/13.4% of the original sample). In meta-analysis, longer mean sleep duration per day at 3.5 years was associated with lower mean internalizing and externalizing behavior percentile scores at 5 years (adjusted mean difference: - 1.27, 95% CI [- 2.22, - 0.32] / - 2.39, 95% CI [- 3.04, - 1.75]). Sleep duration and language or non-verbal intelligence showed trends of inverse associations, however, with imprecise estimates (adjusted mean difference: - 0.28, 95% CI [- 0.83, 0.27] / - 0.42, 95% CI [- 0.99, 0.15]). This individual participant data meta-analysis suggests that longer sleep duration in preschool age may be important for children's later behavior and highlight the need for larger samples for robust analyses of cognitive outcomes. Findings could be influenced by confounding or reverse causality and require replication.

Long-term cardiometabolic health in people born after assisted reproductive technology: a multi-cohort analysis.

AIMS: To examine associations of assisted reproductive technology (ART) conception (vs. natural conception: NC) with offspring cardiometabolic health outcomes and whether these differ with age. METHODS AND RESULTS: Differences in systolic (SBP) and diastolic blood pressure (DBP), heart rate (HR), lipids, and hyperglycaemic/insulin resistance markers were examined using multiple linear regression models in 14 population-based birth cohorts in Europe, Australia, and Singapore, and results were combined using meta-analysis. Change in cardiometabolic outcomes from 2 to 26 years was examined using trajectory modelling of four cohorts with repeated measures. 35 938 (654 ART) offspring were included in the meta-analysis. Mean age ranged from 13 months to 27.4 years but was <10 years in 11/14 cohorts. Meta-analysis found no statistical difference (ART minus NC) in SBP (-0.53 mmHg; 95% CI:-1.59 to 0.53), DBP (-0.24 mmHg; -0.83 to 0.35), or HR (0.02 beat/min; -0.91 to 0.94). Total cholesterol (2.59%; 0.10-5.07), HDL cholesterol (4.16%; 2.52-5.81), LDL cholesterol (4.95%; 0.47-9.43) were statistically significantly higher in ART-conceived vs. NC offspring. No statistical difference was seen for triglycerides (TG), glucose, insulin, and glycated haemoglobin. Long-term follow-up of 17 244 (244 ART) births identified statistically significant associations between ART and lower predicted SBP/DBP in childhood, and subtle trajectories to higher SBP and TG in young adulthood; however, most differences were not statistically significant. CONCLUSION: These findings of small and statistically non-significant differences in offspring cardiometabolic outcomes should reassure people receiving ART. Longer-term follow-up is warranted to investigate changes over adulthood in the risks of hypertension, dyslipidaemia, and preclinical and clinical cardiovascular disease.

Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies.

BACKGROUND: Preterm birth is the leading cause of perinatal morbidity and mortality and is associated with adverse developmental and long-term health outcomes, including several cardiometabolic risk factors and outcomes. However, evidence about the association of preterm birth with later body size derives mainly from studies using birth weight as a proxy of prematurity rather than an actual length of gestation. We investigated the association of gestational age (GA) at birth with body size from infancy through adolescence. METHODS AND FINDINGS: We conducted a two-stage individual participant data (IPD) meta-analysis using data from 253,810 mother-child dyads from 16 general population-based cohort studies in Europe (Denmark, Finland, France, Italy, Norway, Portugal, Spain, the Netherlands, United Kingdom), North America (Canada), and Australasia (Australia) to estimate the association of GA with body mass index (BMI) and overweight (including obesity) adjusted for the following maternal characteristics as potential confounders: education, height, prepregnancy BMI, ethnic background, parity, smoking during pregnancy, age at child's birth, gestational diabetes and hypertension, and preeclampsia. Pregnancy and birth cohort studies from the LifeCycle and the EUCAN-Connect projects were invited and were eligible for inclusion if they had information on GA and minimum one measurement of BMI between infancy and adolescence. Using a federated analytical tool (DataSHIELD), we fitted linear and logistic regression models in each cohort separately with a complete-case approach and combined the regression estimates and standard errors through random-effects study-level meta-analysis providing an overall effect estimate at early infancy (>0.0 to 0.5 years), late infancy (>0.5 to 2.0 years), early childhood (>2.0 to 5.0 years), mid-childhood (>5.0 to 9.0 years), late childhood (>9.0 to 14.0 years), and adolescence (>14.0 to 19.0 years). GA was positively associated with BMI in the first decade of life, with the greatest increase in mean BMI z-score during early infancy (0.02, 95% confidence interval (CI): 0.00; 0.05, p < 0.05) per week of increase in GA, while in adolescence, preterm individuals reached similar levels of BMI (0.00, 95% CI: -0.01; 0.01, p 0.9) as term counterparts. The association between GA and overweight revealed a similar pattern of association with an increase in odds ratio (OR) of overweight from late infancy through mid-childhood (OR 1.01 to 1.02) per week increase in GA. By adolescence, however, GA was slightly negatively associated with the risk of overweight (OR 0.98 [95% CI: 0.97; 1.00], p 0.1) per week of increase in GA. Although based on only four cohorts (n = 32,089) that reached the age of adolescence, data suggest that individuals born very preterm may be at increased odds of overweight (OR 1.46 [95% CI: 1.03; 2.08], p < 0.05) compared with term counterparts. Findings were consistent across cohorts and sensitivity analyses despite considerable heterogeneity in cohort characteristics. However, residual confounding may be a limitation in this study, while findings may be less generalisable to settings in low- and middle-income countries. CONCLUSIONS: This study based on data from infancy through adolescence from 16 cohort studies found that GA may be important for body size in infancy, but the strength of association attenuates consistently with age. By adolescence, preterm individuals have on average a similar mean BMI to peers born at term.

Correction: Gestational age at birth and body size from infancy through adolescence: An individual participant data meta-analysis on 253,810 singletons in 16 birth cohort studies.

[This corrects the article DOI: 10.1371/journal.pmed.1004036.].

Associations of Maternal Educational Level, Proximity to Greenspace During Pregnancy, and Gestational Diabetes With Body Mass Index From Infancy to Early Adulthood: A Proof-of-Concept Federated Analysis in 18 Birth Cohorts.

International sharing of cohort data for research is important and challenging. We explored the feasibility of multi-cohort federated analyses by examining associations between three pregnancy exposures (maternal education, exposure to green vegetation and gestational diabetes) with offspring BMI from infancy to 17 years. We used data from 18 cohorts (n=206,180 mother-child pairs) from the EU Child Cohort Network and derived BMI at ages 0-1, 2-3, 4-7, 8-13 and 14-17 years. Associations were estimated using linear regression via one-stage IPD meta-analysis using DataSHIELD. Associations between lower maternal education and higher child BMI emerged from age 4 and increased with age (difference in BMI z-score comparing low with high education age 2-3 years = 0.03 [95% CI 0.00, 0.05], 4-7 years = 0.16 [95% CI 0.14, 0.17], 8-13 years = 0.24 [95% CI 0.22, 0.26]). Gestational diabetes was positively associated with BMI from 8 years (BMI z-score difference = 0.18 [CI 0.12, 0.25]) but not at younger ages; however associations attenuated towards the null when restricted to cohorts which measured GDM via universal screening. Exposure to green vegetation was weakly associated with higher BMI up to age one but not at older ages. Opportunities of cross-cohort federated analyses are discussed.

Identifying the potential causal role of insomnia symptoms on 11,409 health-related outcomes: a phenome-wide Mendelian randomisation analysis in UK Biobank.

BACKGROUND: Insomnia symptoms are widespread in the population and might have effects on many chronic conditions and their risk factors but previous research has focused on select hypothesised associations/effects rather than taking a systematic hypothesis-free approach across many health outcomes. METHODS: We performed a Mendelian randomisation (MR) phenome-wide association study (PheWAS) in 336,975 unrelated white-British UK Biobank participants. Self-reported insomnia symptoms were instrumented by a genetic risk score (GRS) created from 129 single-nucleotide polymorphisms (SNPs). A total of 11,409 outcomes from UK Biobank were extracted and processed by an automated pipeline (PHESANT) for the MR-PheWAS. Potential causal effects (those passing a Bonferroni-corrected significance threshold) were followed up with two-sample MR in MR-Base, where possible. RESULTS: Four hundred thirty-seven potential causal effects of insomnia symptoms were observed for a diverse range of outcomes, including anxiety, depression, pain, body composition, respiratory, musculoskeletal and cardiovascular traits. We were able to undertake two-sample MR for 71 of these 437 and found evidence of causal effects (with directionally concordant effect estimates across main and sensitivity analyses) for 30 of these. These included novel findings (by which we mean not extensively explored in conventional observational studies and not previously explored using MR based on a systematic search) of an adverse effect on risk of spondylosis (OR [95%CI] = 1.55 [1.33, 1.81]) and bronchitis (OR [95%CI] = 1.12 [1.03, 1.22]), among others. CONCLUSIONS: Insomnia symptoms potentially cause a wide range of adverse health-related outcomes and behaviours. This has implications for developing interventions to prevent and treat a number of diseases in order to reduce multimorbidity and associated polypharmacy.

The effect of maternal BMI, smoking and alcohol on congenital heart diseases: a Mendelian randomisation study.

BACKGROUND: Congenital heart diseases (CHDs) remain a significant cause of infant morbidity and mortality. Epidemiological studies have explored maternal risk factors for offspring CHDs, but few have used genetic epidemiology methods to improve causal inference. METHODS: Three birth cohorts, including 65,510 mother/offspring pairs (N = 562 CHD cases) were included. We used Mendelian randomisation (MR) analyses to explore the effects of genetically predicted maternal body mass index (BMI), smoking and alcohol on offspring CHDs. We generated genetic risk scores (GRS) using summary data from large-scale genome-wide association studies (GWAS) and validated the strength and relevance of the genetic instrument for exposure levels during pregnancy. Logistic regression was used to estimate the odds ratio (OR) of CHD per 1 standard deviation (SD) higher GRS. Results for the three cohorts were combined using random-effects meta-analyses. We performed several sensitivity analyses including multivariable MR to check the robustness of our findings. RESULTS: The GRSs associated with the exposures during pregnancy in all three cohorts. The associations of the GRS for maternal BMI with offspring CHD (pooled OR (95% confidence interval) per 1SD higher GRS: 0.95 (0.88, 1.03)), lifetime smoking (pooled OR: 1.01 (0.93, 1.09)) and alcoholic drinks per week (pooled OR: 1.06 (0.98, 1.15)) were close to the null. Sensitivity analyses yielded similar results. CONCLUSIONS: Our results do not provide robust evidence of an effect of maternal BMI, smoking or alcohol on offspring CHDs. However, results were imprecise. Our findings need to be replicated, and highlight the need for more and larger studies with maternal and offspring genotype and offspring CHD data.

Effect of common pregnancy and perinatal complications on offspring metabolic traits across the life course: a multi-cohort study.

BACKGROUND: Common pregnancy and perinatal complications are associated with offspring cardiometabolic risk factors. These complications may influence multiple metabolic traits in the offspring and these associations might differ with offspring age. METHODS: We used data from eight population-based cohort studies to examine and compare associations of pre-eclampsia (PE), gestational hypertension (GH), gestational diabetes (GD), preterm birth (PTB), small (SGA) and large (LGA) for gestational age (vs. appropriate size for gestational age (AGA)) with up to 167 plasma/serum-based nuclear magnetic resonance-derived metabolic traits encompassing lipids, lipoproteins, fatty acids, amino acids, ketones, glycerides/phospholipids, glycolysis, fluid balance, and inflammation. Confounder-adjusted regression models were used to examine associations (adjusted for maternal education, parity age at pregnancy, ethnicity, pre/early pregnancy body mass index and smoking, and offspring sex and age at metabolic trait assessment), and results were combined using meta-analysis by five age categories representing different periods of the offspring life course: neonates (cord blood), infancy (mean ages: 1.1-1.6 years), childhood (4.2-7.5 years); adolescence (12.0-16.0 years), and adulthood (22.0-67.8 years). RESULTS: Offspring numbers for each age category/analysis varied from 8925 adults (441 PTB) to 1181 infants (135 GD); 48.4% to 60.0% were females. Pregnancy complications (PE, GH, GD) were each associated with up to three metabolic traits in neonates (P≤0.001) with some evidence of persistence to older ages. PTB and SGA were associated with 32 and 12 metabolic traits in neonates respectively, which included an adjusted standardised mean difference of -0.89 standard deviation (SD) units for albumin with PTB (95% CI: -1.10 to -0.69, P=1.3×10-17) and -0.41 SD for total lipids in medium HDL with SGA (95% CI: -0.56 to -0.25, P=2.6×10-7), with some evidence of persistence to older ages. LGA was inversely associated with 19 metabolic traits including lower levels of cholesterol, lipoproteins, fatty acids, and amino acids, with associations emerging in adolescence, (e.g. -0.11 SD total fatty acids, 95% CI: -0.18 to -0.05, P=0.0009), and attenuating with older age across adulthood. CONCLUSIONS: These reassuring findings suggest little evidence of wide-spread and long-term impact of common pregnancy and perinatal complications on offspring metabolic traits, with most associations only observed for newborns rather than older ages, and for perinatal rather than pregnancy complications.

Associations between health behaviours, fertility and reproductive outcomes: triangulation of evidence in the Norwegian Mother, Father and Child Cohort Study (MoBa).

BACKGROUND: Guidance to improve fertility includes reducing alcohol and caffeine consumption, achieving healthy weight-range and stopping smoking. Advice is informed by observational evidence, which is often biased by confounding. METHODS: This study primarily used data from a pregnancy cohort, the Norwegian Mother, Father and Child Cohort Study. First, we conducted multivariable regression of health behaviours (alcohol and caffeine consumption, body-mass index (BMI), and smoking) on fertility outcomes (e.g. time to conception) and reproductive outcomes (e.g. age at first birth) (n = 84,075 females, 68,002 males), adjusting for birth year, education and attention-deficit and hyperactive-impulsive (ADHD) traits. Second, we used individual-level Mendelian randomisation (MR) to explore possible causal effects of health behaviours on fertility/reproductive outcomes (n = 63,376 females, 45,460 males). Finally, we performed summary-level MR for available outcomes in UK Biobank (n = 91,462-1,232,091) and controlled for education and ADHD liability using multivariable MR. RESULTS: In multivariable regression analyses, higher BMI associated with fertility (longer time to conception, increased odds of infertility treatment and miscarriage), and smoking was associated with longer time to conception. In individual-level MR analyses, there was strong evidence for effects of smoking initiation and higher BMI on younger age at first birth, of higher BMI on increased time to conception, and weak evidence for effects of smoking initiation on increased time to conception. Age at first birth associations were replicated in summary-level MR analysis; however, effects attenuated using multivariable MR. CONCLUSIONS: Smoking behaviour and BMI showed the most consistent associations for increased time to conception and a younger age at first birth. Given that age at first birth and time to conception are positively correlated, this suggests that the mechanisms for reproductive outcomes are distinct to the mechanisms acting on fertility outcomes. Multivariable MR suggested that effects on age at first birth might be explained by underlying liability to ADHD and education.

metaboprep: an R package for preanalysis data description and processing.

MOTIVATION: Metabolomics is an increasingly common part of health research and there is need for preanalytical data processing. Researchers typically need to characterize the data and to exclude errors within the context of the intended analysis. Whilst some preprocessing steps are common, there is currently a lack of standardization and reporting transparency for these procedures. RESULTS: Here, we introduce metaboprep, a standardized data processing workflow to extract and characterize high quality metabolomics datasets. The package extracts data from preformed 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 are generated for the purpose of open disclosure. Where possible, we provide users flexibility in defining their own selection thresholds. AVAILABILITY AND IMPLEMENTATION: metaboprep is an open-source R package available at https://github.com/MRCIEU/metaboprep. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

General health in a cohort of children conceived after assisted reproductive technology in the United Kingdom: a population-based record-linkage study.

BACKGROUND: Assisted reproductive technology use is increasing annually; however, data on long-term child health outcomes including hospital admissions are limited. OBJECTIVE: This study aimed to examine the potential effects of assisted reproductive technology on any and cause-specific hospital admissions unrelated to perinatal diagnoses. STUDY DESIGN: This was a population-based record-linkage study that included a previously established cohort of children born after assisted reproductive technology in the United Kingdom between 1997 and 2009 (n=63,877), their naturally conceived siblings (n=11,343), and matched naturally conceived population controls (n=127,544) linked to their postnatal health outcomes up to March 31, 2016 to provide robust risk estimates of the potential effects of assisted reproductive technology on any and cause-specific hospital admissions unrelated to perinatal diagnoses. In addition, comparison of hospital admissions by type of treatment was made. Cox regression was used to estimate the risk of hospital admission, and negative binomial regression was used to compare the number of hospital admissions per year. RESULTS: This study had 1.6 million person-years of follow-up (mean, 12.9 years; range, 0-19 years), and the mean age at the time of first hospital admission was 6.5 years (range, 0-19 years). Singletons born after assisted reproductive technology had increased risk of any hospital admission compared with naturally conceived population controls (hazard ratio, 1.08; 95% confidence interval, 1.05-1.10) but not naturally conceived siblings (hazard ratio, 1.01; 95% confidence interval, 0.94-1.09). We observed increased risk of diagnoses related to neoplasms and diseases of the respiratory, musculoskeletal, digestive, and genitourinary systems, and lower risk of injury, poisoning, and consequences of external causes compared with naturally conceived population controls. Children born after intracytoplasmic sperm injection had a lower risk of hospital admission compared with those born after in vitro fertilization, although no such differences were observed between children born after fresh embryo transfers and those born after frozen embryo transfers. CONCLUSION: Children born after assisted reproductive technology had greater numbers of hospital admissions compared with naturally conceived population controls. Attenuation of these differences in relation to their naturally conceived siblings suggested that this could be partially attributed to the influence of parental subfertility on child health, increased parental concerns, and an actual increase in morbidity in children born after assisted conception.