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Numerous observational studies have attempted to identify risk factors for infection with SARS-CoV-2 and COVID-19 disease outcomes. Studies have used datasets sampled from patients admitted to hospital, people tested for active infection, or people who volunteered to participate. Here, we highlight the challenge of interpreting observational evidence from such non-representative samples. Collider bias can induce associations between two or more variables which affect the likelihood of an individual being sampled, distorting associations between these variables in the sample. Analysing UK Biobank data, compared to the wider cohort the participants tested for COVID-19 were highly selected for a range of genetic, behavioural, cardiovascular, demographic, and anthropometric traits. We discuss the mechanisms inducing these problems, and approaches that could help mitigate them. While collider bias should be explored in existing studies, the optimal way to mitigate the problem is to use appropriate sampling strategies at the study design stage. Many published studies of the current SARS-CoV-2 pandemic have analysed data from non-representative samples from populations. Here, using UK BioBank samples, Gibran Hemani and colleagues discuss the potential for such studies to suffer from collider bias, and provide suggestions for optimising study design to account for this.

Background Women’s reproductive factors include their age at menarche and menopause, the age at which they start and stop having children and the number of children they have. Studies that have linked these factors with disease risk have largely investigated individual reproductive factors and have not considered the genetic correlation and total interplay that may occur between them. This study aimed to investigate the nature of the relationships between eight female reproductive factors. Methods We used data from the UK Biobank and genetic consortia with data available for the following reproductive factors: age at menarche, age at menopause, age at first birth, age at last birth, number of births, being parous, age first had sexual intercourse and lifetime number of sexual partners. Linkage disequilibrium score regression (LDSC) was performed to investigate the genetic correlation between reproductive factors. We then applied Mendelian randomisation (MR) methods to estimate the causal relationships between these factors. Sensitivity analyses were used to investigate directionality of the effects, test for evidence of pleiotropy and account for sample overlap. Results LDSC indicated that most reproductive factors are genetically correlated ( r g range: |0.06–0.94|), though there was little evidence for genetic correlations between lifetime number of sexual partners and age at last birth, number of births and ever being parous ( r g < 0.01). MR revealed potential causal relationships between many reproductive factors, including later age at menarche (1 SD increase) leading to a later age at first sexual intercourse (beta ( B ) = 0.09 SD, 95% confidence intervals ( CI ) = 0.06,0.11), age at first birth ( B = 0.07 SD, CI = 0.04,0.10), age at last birth ( B = 0.06 SD, CI = 0.04,0.09) and age at menopause ( B = 0.06 SD, CI = 0.03,0.10). Later age at first birth was found to lead to a later age at menopause ( B = 0.21 SD, CI = 0.13,0.29), age at last birth ( B = 0.72 SD, CI = 0.67, 0.77) and a lower number of births ( B = −0.38 SD, CI = −0.44, −0.32). Conclusion This study presents evidence that women’s reproductive factors are genetically correlated and causally related. Future studies examining the health sequelae of reproductive factors should consider a woman’s entire reproductive history, including the causal interplay between reproductive factors.

There is increasing evidence that genetic risk variants for non-syndromic cleft lip/palate (nsCL/P) are also associated with normal-range variation in facial morphology. However, previous analyses are mostly limited to candidate SNPs and findings have not been consistently replicated. Here, we used polygenic risk scores (PRS) to test for genetic overlap between nsCL/P and seven biologically relevant facial phenotypes. Where evidence was found of genetic overlap, we used bidirectional Mendelian randomization (MR) to test the hypothesis that genetic liability to nsCL/P is causally related to implicated facial phenotypes. Across 5,804 individuals of European ancestry from two studies, we found strong evidence, using PRS, of genetic overlap between nsCL/P and philtrum width; a 1 S.D. increase in nsCL/P PRS was associated with a 0.10 mm decrease in philtrum width (95% C.I. 0.054, 0.146; P = 2x10-5). Follow-up MR analyses supported a causal relationship; genetic variants for nsCL/P homogeneously cause decreased philtrum width. In addition to the primary analysis, we also identified two novel risk loci for philtrum width at 5q22.2 and 7p15.2 in our Genome-wide Association Study (GWAS) of 6,136 individuals. Our results support a liability threshold model of inheritance for nsCL/P, related to abnormalities in development of the philtrum.

Background There is some evidence that paternal health behaviours during and around pregnancy could be associated with offspring health outcomes. However, the impact that paternal health behaviours during pregnancy can have on offspring mental health is understudied and remains unclear. Methods We conducted a systematic review and meta-analysis of articles in PubMed describing studies of potentially modifiable paternal health behaviours (tobacco smoking, alcohol consumption, caffeine consumption and physical activity) in the prenatal period in relation to offspring mental health. GRADE was used to measure risk of bias. Results Eight studies were included and categorized by paternal health behaviour and offspring mental health outcome investigated. The narrative synthesis provided evidence of association between paternal health behaviours around pregnancy and offspring mental health problems, with the strongest evidence shown for tobacco use. Grouped by analysis type, two separate meta-analyses showed evidence of paternal smoking during pregnancy being associated with greater odds of ADHD in offspring (OR 1.42, 95% CI 1.02–1.99; HR 1.28, 95% CI 1.19–1.39). Conclusions The small number of studies that have investigated paternal prenatal effects on offspring mental health, and the limited sample sizes of those studies, makes it challenging to draw firm conclusions. Although existing studies suggest that paternal tobacco smoking and alcohol consumption in the prenatal period are associated with poorer offspring mental health, (particularly hyperactivity/ADHD), further investigation of potential paternal effects is required, using methods that allow stronger inference to determine whether associations are causal. Plain language summary More research has focused on the impact mothers’ behaviours (such as smoking or alcohol use) during and around pregnancy may have on their children’s health, with less research investigating the role paternal health behaviours may play. This review captured what research was currently available that investigated the impact of paternal alcohol, tobacco, caffeine use, and physical activity during pregnancy on children’s mental health. We showed that this area is currently under researched, finding only eight studies. However, of the research that was already published we found evidence of paternal health behaviours having an impact on children’s mental health. The strongest evidence was shown for paternal smoking during pregnancy having a negative impact on children’s hyperactivity/ADHD. No studies measured paternal caffeine use or physical activity around pregnancy. This review highlights the lack of research that has investigated the association between paternal modifiable health behaviours around pregnancy and offspring mental health. Despite including four different types of paternal health behaviours and a broad definition of offspring mental health across any age, only eight studies were shown. This review suggests further research within this area is needed which may influence health warnings to potential fathers to be both before conception and during pregnancy.

Background Few studies have investigated associations between adiposity and reproductive factors using causal methods, both of which have a number of consequences on women’s health. Here we assess whether adiposity at different points in the lifecourse affects reproductive factors differently and independently, and the plausibility of the impact of reproductive factors on adiposity. Methods We used genetic data from UK Biobank (273,238 women) and other consortia (EGG, GIANT, ReproGen and SSGAC) for eight reproductive factors: age at menarche, age at menopause, age at first birth, age at last birth, number of births, being parous, age first had sexual intercourse and lifetime number of sexual partners, and two adiposity traits: childhood and adulthood body size. We applied multivariable Mendelian randomization to account for genetic correlation and to estimate the causal effects of childhood and adulthood adiposity, independently of each other, on reproductive factors. Additionally, we estimated the effects of reproductive factors, independently of other relevant reproductive factors, on adulthood adiposity. Results We found a higher childhood body size leads to an earlier age at menarche, and an earlier age at menarche leads to a higher adulthood body size. Furthermore, we find contrasting and independent effects of childhood and adulthood body size on age at first birth (beta 0.22 SD (95% confidence interval: 0.14, 0.31) vs − 2.49 (− 2.93, − 2.06) per 1 SD increase), age at last birth (0.13 (0.06,0.21) vs − 1.86 (− 2.23, − 1.48) per 1 SD increase), age at menopause (0.17 (0.09, 0.25) vs − 0.99 (− 1.39, − 0.59) per 1 SD increase), and likelihood of having children (Odds ratio 0.97 (0.95, 1.00) vs 1.20 (1.06, 1.37) per 1 SD increase). Conclusions Our findings demonstrate the importance of considering a lifecourse approach when investigating the inter-relationships between adiposity measures and reproductive events, as well as the use of ‘age specific’ genetic instruments when evaluating lifecourse hypotheses in a Mendelian randomization framework.

Background Observational evidence proposes a protective effect of having children and an early first pregnancy on breast cancer development; however, the causality of this association remains uncertain. Here, we assess whether parity-related reproductive factors impact breast cancer risk independently of each other and other causally related or genetically correlated factors: adiposity, age at menarche, and age at menopause. Methods We used genetic data from UK Biobank for reproductive factors and adiposity, and the Breast Cancer Association Consortium for risk of overall, estrogen receptor (ER) positive and negative breast cancer, and breast cancer subtypes. We applied univariable and multivariable Mendelian randomization (MR) to estimate genetically predicted direct effects of ever parous status, ages at first birth and last birth, and number of births on breast cancer risk. Results We found limited evidence for a genetically predicted protective effect of an earlier age at first birth on breast cancer risk. While the univariable analysis revealed later age at first birth decreased ER-negative breast cancer risk (odds ratio (OR): 0.76; 95% confidence interval: 0.61, 0.95 per standard deviation (SD) increase in age at first birth), this effect attenuated with separate adjustment for age at menarche (potential confounder) (OR: 0.83; 0.62, 1.06) and age at menopause (genetically correlated factor) (OR: 0.80; 0.66, 1.01). Furthermore, we found evidence that a later age at first birth decreased HER2-enriched breast cancer risk but only after adjusting for number of births (potential mediator) (OR: 0.28; 0.11, 0.57 per SD increase in age at first birth). In the multivariable analysis, we found little evidence for genetically predicted effects of ever-parous status, age at last birth, or number of births on breast cancer risk; however, analyses of ever-parous status and age at last birth were limited by weak instruments. Conclusions This study found minimal evidence of a genetically predicted protective effect of earlier age at first birth on breast cancer risk, while identifying some evidence for a genetically predicted adverse effect on ER-negative breast cancer risk. However, weak instruments limited the multivariable analysis of ever parous status and age at last birth, which may be improved with larger sample sizes.

Menstrual and mental health form a close relationship that is under-appreciated in scientific research, clinical practice and social policy. This association is extremely complex, involving interactions between biology, psychology and social, political and structural influences on health and wellbeing. Research in these areas has traditionally been siloed: focusing on menstrual or mental health in isolation, or the interrelation from a limited one-dimensional perspective. We recognised the need for a more holistic and comprehensive approach that considers the complex interweaving nature of menstrual and mental health. In 2021, we established the Menarche, Menstruation, Menopause and Mental Health (4M) consortium as a tool to address this gap and to facilitate interdisciplinary research. This paper provides a comprehensive source of information about 4M for researchers and stakeholders who may be interested in joining or working with the consortium.

Background Epigenetic data could help identify risk factors for orofacial clefts, either by revealing a causal role for epigenetic mechanisms in causing clefts or by capturing information about causal genetic or environmental factors. Given the evidence that different subtypes of orofacial cleft have distinct aetiologies, we explored whether children with different cleft subtypes showed distinct epigenetic profiles. Methods In whole-blood samples from 150 children from the Cleft Collective cohort study, we measured DNA methylation at over 450,000 sites on the genome. We then carried out epigenome-wide association studies (EWAS) to test the association between methylation at each site and cleft subtype (cleft lip only (CLO) n  = 50; cleft palate only (CPO) n  = 50; cleft lip and palate (CLP) n  = 50). We also compared methylation in the blood to methylation in the lip or palate tissue using genome-wide data from the same 150 children and conducted an EWAS of CLO compared to CLP in lip tissue. Results We found four genomic regions in blood differentially methylated in CLO compared to CLP, 17 in CPO compared to CLP and 294 in CPO compared to CLO. Several regions mapped to genes that have previously been implicated in the development of orofacial clefts (for example, TBX1 , COL11A2 , HOXA2 , PDGFRA ), and over 250 associations were novel. Methylation in blood correlated with that in lip/palate at some regions. There were 14 regions differentially methylated in the lip tissue from children with CLO and CLP, with one region (near KIAA0415 ) showing up in both the blood and lip EWAS. Conclusions Our finding of distinct methylation profiles in different orofacial cleft (OFC) subtypes represents a promising first step in exploring the potential role of epigenetic modifications in the aetiology of OFCs and/or as clinically useful biomarkers of OFC subtypes.

Menstrual symptoms may negatively impact academic achievement, but rigorous population-based studies are lacking. 2,698 participants from the Avon Longitudinal Study of Parents and Children (ALSPAC) self-reported heavy or prolonged bleeding and menstrual pain during adolescence and multivariable regression were used to estimate associations with linked data on absences and attainment at age 15/16, adjusting for confounders. Heavy or prolonged bleeding and pain were associated with missing 1.7 (16.58% increase) and 1.2 (12.83% increase) additional days of school per year, respectively, and 48% and 42% higher odds of persistent (≥10%) absence. Heavy or prolonged bleeding was associated with lower examination scores (−5.7 points) and 27% lower odds of achieving five standard passes. The association between pain and attainment was weaker but still present (−3.14 points; 95% CI: −7.46, 1.17; 16% lower odds of five standard passes). Greater research and support are needed to prevent adolescents’ menstrual symptoms impacting their academic achievement.

An incomplete understanding of the molecular mechanisms that initiate normal human labour at term seriously hampers the development of effective ways to predict, prevent and treat disorders such as preterm labour. Appropriate analysis of large microarray experiments that compare gene expression in non-labouring and labouring gestational tissues is necessary to help bridge these gaps in our knowledge. In this work, gene expression in 48 (22 labouring, 26 non-labouring) lower-segment myometrial samples collected at Caesarean section were analysed using Illumina HT-12 v4.0 BeadChips. Normalised data were compared between labouring and non-labouring groups using traditional statistical methods and a novel network graph approach. We sought technical validation with quantitative real-time PCR, and biological replication through inverse variance-weighted meta-analysis with published microarray data. We have extended the list of genes suggested to be associated with labour: Compared to non-labouring samples, labouring samples showed apparent higher expression at 960 probes (949 genes) and apparent lower expression at 801 probes (789 genes) (absolute fold change ≥1.2, rank product percentage of false positive value (RP-PFP) <0.05). Although half of the women in the labouring group had received pharmaceutical treatment to induce or augment labour, sensitivity analysis suggested that this did not confound our results. In agreement with previous studies, functional analysis suggested that labour was characterised by an increase in the expression of inflammatory genes and network analysis suggested a strong neutrophil signature. Our analysis also suggested that labour is characterised by a decrease in the expression of muscle-specific processes, which has not been explicitly discussed previously. We validated these findings through the first formal meta-analysis of raw data from previous experiments and we hypothesise that this represents a change in the composition of myometrial tissue at labour. Further work will be necessary to reveal whether these results are solely due to leukocyte infiltration into the myometrium as a mechanism initiating labour, or in addition whether they also represent gene changes in the myocytes themselves. We have made all our data available at www.ebi.ac.uk/arrayexpress/ (accession number E-MTAB-3136) to facilitate progression of this work.