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 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.

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.

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.

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.

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.

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.

Hypertensive disorders of pregnancy and midlife maternal cognition in a prospective cohort study.

Hypertensive disorders of pregnancy (HDP) are associated with an increased risk of cardiovascular disorders, with recent evidence linking pre-eclampsia with vascular dementia. We examined associations of HDP with cognitive performance measured in midlife, in a prospective cohort study, the Avon Longitudinal Study of Parents and Children. Six cognitive function domains were measured 20 years after pregnancy at a mean age of 51 years. The cognition tests were repeated at clinics in the following two years. Cognitive function domains measured were immediate and delayed verbal episodic memory, working memory, processing speed, verbal intelligence, and verbal fluency. Exposures were pre-eclampsia, gestational hypertension (GH), and a combined category of any HDP, all compared to normotensive pregnancy. Of 3393 pregnancies included in the analysis, GH was experienced by 417 (12.3%) and pre-eclampsia by 57 (1.7%). GH was associated with lower verbal episodic memory, in the delayed logic memory test (-0.16 SDs; 95% CI -0.30, -0.03; p = .015) and there was weak evidence of an association with the immediate logic memory test (-0.13 SDs; -0.27, 0.001; p = .058). However, we did not see steeper declines by age for women with GH and there was no evidence of associations with other cognitive domains or for pre-eclampsia with any domains. Results were not substantially changed after controlling for midlife blood pressure. Our findings suggest that a history of GH is associated with slightly reduced episodic memory 20 years after pregnancy, but we found no evidence of a quicker age-related decline compared to women with normotensive pregnancies.

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.

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.

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.

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.

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.

Body mass index in parents and their adult offspring: A systematic review and meta-analysis.

Obesity may track across generations, due to genetics and shared family environmental factors, or possibly intrauterine programming. However, many studies only assess associations between maternal body mass index (BMI) and offspring BMI in childhood. To determine whether maternal and paternal associations with offspring BMI differ and whether associations persist into adulthood, a systematic review and meta-analysis was done. PubMed, Embase, Web of Science, and Google Scholar (to October 2022) were searched. Observational studies reporting associations between maternal or paternal BMI and adult offspring BMI were included. Offspring BMIs were reported as continuous or categorical measures. Forty-six studies were included in the systematic review. Meta-analyses were conducted using random-effects models. Parental BMI was positively associated with offspring BMI in adulthood. The pooled mother-offspring standardized mean difference (SMD) was 0.23 (95% confidence interval [CI]: 0.20, 0.26), and father-offspring SMD was similar: 0.22 (95% CI: 0.19, 0.25) in adjusted models. Offspring of mothers with overweight or obesity had the same risk of higher BMI as offspring of fathers with overweight or obesity. If these associations are causal, they support interventions targeting all family members, rather than focusing solely on mothers, to obtain a healthy weight development among offspring.

Non-linear associations of maternal pre-pregnancy body mass index with risk of stillbirth, infant, and neonatal mortality in over 28 million births in the USA: a retrospective cohort study.

Background: Higher maternal pre-pregnancy body mass index (BMI) has been associated with higher risk of stillbirth, infant and neonatal mortality. Studies exploring underweight have varied in their conclusions. Our aim was to examine the risk of stillbirth, infant and neonatal mortality across the BMI distribution and establish a likely healthy BMI range. Methods: In this retrospective cohort study, we used publicly available datasets (covering 1st January 2014 to 31st December 2021) from the US National Center for Health Statistics National Vital Statistics System. All births were eligible; analyses included those with non-missing data. Fractional polynomial multivariable logistic regression was used to examine the associations of maternal pre-pregnant BMI with stillbirth (birth with no signs of life at ≥24 weeks), infant mortality (death of a live born baby aged <365 days) and neonatal mortality (death of a live born baby aged <28 days). Findings: There were 77,896/28,310,154 (2.8 per 1000 births) stillbirths, 143,620/28,231,807 (5.1 per 1000 live births) infant deaths and 94,246/28,231,807 (3.3 per 1000 live births) neonatal deaths among complete cases. Mean (SD) BMI was 27.1 kg/m2 (6.7 kg/m2). We found non-linear associations between BMI and all three outcomes; risk was elevated at both low and high BMIs although, for stillbirth, the increased risk at low BMI was less marked than for infant/neonatal mortality. The lowest risk was at a BMI of 21 kg/m2 for infant and neonatal mortality and 19 kg/m2 for stillbirth. Interpretation: Public health messaging for preconception and postnatal care should focus on healthy weight to maximise maternal and child health, and not focus solely on maternal overweight or obesity. Funding: European Research Council, US National Institute of Health, UK Medical Research Council and National Institute for Health and Care Research.

Menstrual cycle features in mothers and daughters in the Avon Longitudinal Study of Parents and Children (ALSPAC).

Problematic menstrual cycle features, including irregular periods, severe pain, heavy bleeding, absence of periods, frequent or infrequent cycles, and premenstrual symptoms, are experienced by high proportions of females and can have substantial impacts on their health and well-being. However, research aimed at identifying causes and risk factors associated with such menstrual cycle features is sparse and limited. This data note describes prospective, longitudinal data collected in a UK birth cohort, the Avon Longitudinal Study of Parents and Children (ALSPAC), on menstrual cycle features, which can be utilised to address the research gaps in this area. Data were collected across 21 timepoints (between the average age of 28.6 and 57.7 years) in mothers (G0) and 20 timepoints (between the average age of 8 and 24 years) in index daughters (G1) between 1991 and 2020. This data note details all available variables, proposes methods to derive comparable variables across data collection timepoints, and discusses important limitations specific to each menstrual cycle feature. Also, the data note identifies broader issues for researchers to consider when utilising the menstrual cycle feature data, such as hormonal contraception, pregnancy, breastfeeding, and menopause, as well as missing data and misclassification.

Correlations in sleeping patterns and circadian preference between spouses.

Spouses may affect each other's sleeping behaviour. In 47,420 spouse-pairs from the UK Biobank, we found a weak positive phenotypic correlation between spouses for self-reported sleep duration (r = 0.11; 95% CI = 0.10, 0.12) and a weak inverse correlation for chronotype (diurnal preference) (r = -0.11; -0.12, -0.10), which replicated in up to 127,035 23andMe spouse-pairs. Using accelerometer data on 3454 UK Biobank spouse-pairs, the correlation for derived sleep duration was similar to self-report (r = 0.12; 0.09, 0.15). Timing of diurnal activity was positively correlated (r = 0.24; 0.21, 0.27) in contrast to the inverse correlation for chronotype. In Mendelian randomization analysis, positive effects of sleep duration (mean difference=0.13; 0.04, 0.23 SD per SD) and diurnal activity (0.49; 0.03, 0.94) were observed, as were inverse effects of chronotype (-0.15; -0.26, -0.04) and snoring (-0.15; -0.27, -0.04). Findings support the notion that an individual's sleep may impact that of their partner, promoting opportunities for sleep interventions at the family-level.

Effects of the maternal and fetal proteome on birth weight: a Mendelian randomization analysis.

Fetal growth is an indicator of fetal survival, regulated by maternal and fetal factors, but little is known about the underlying molecular mechanisms. We used Mendelian randomization to explore the effects of maternal and fetal genetically-instrumented plasma proteins on birth weight using genome-wide association summary data (n=406,063 with maternal and/or fetal genotype), with independent replication (n=74,932 mothers and n=62,108 offspring), and colocalisation. Higher genetically-predicted maternal levels of PCSK1 increased birthweight (mean-difference: 9g (95% CI: 5g, 13g) per 1 standard deviation protein level). Higher maternal levels of LGALS4 decreased birthweight (-54g (-29g, -80g)), as did VCAM1, RAD51D and GP1BA. In the offspring, higher genetically-predicted fetal levels of LGALS4 (46g (23g, 70g)) increased birthweight, alongside FCGR2B. Higher offspring levels of PCSK1 decreased birth weight (-9g (-16g, 4g), alongside LEPR. Results support maternal and fetal protein effects on birth weight, implicating roles for glucose metabolism, energy homeostasis, endothelial function and adipocyte differentiation.