Advancing human health in the decade ahead: pregnancy as a key window for discovery: A Burroughs Wellcome Fund Pregnancy Think Tank

Recent revolutionary advances at the intersection of medicine, omics, data sciences, computing, epidemiology, and related technologies inspire us to ponder their impact on health. Their potential impact is particularly germane to the biology of pregnancy and perinatal medicine, where limited improvement in health outcomes for women and children has remained a global challenge. We assembled a group of experts to establish a Pregnancy Think Tank to discuss a broad spectrum of major gestational disorders and adverse pregnancy outcomes that affect maternal-infant lifelong health and should serve as targets for leveraging the many recent advances. This report reflects avenues for future effects that hold great potential in 3 major areas: developmental genomics, including the application of methodologies designed to bridge genotypes, physiology, and diseases, addressing vexing questions in early human development; gestational physiology, from immune tolerance to growth and the timing of parturition; and personalized and population medicine, focusing on amalgamating health record data and deep phenotypes to create broad knowledge that can be integrated into healthcare systems and drive discovery to address pregnancy-related disease and promote general health. We propose a series of questions reflecting development, systems biology, diseases, clinical approaches and tools, and population health, and a call for scientific action. Clearly, transdisciplinary science must advance and accelerate to address adverse pregnancy outcomes. Disciplines not traditionally involved in the reproductive sciences, such as computer science, engineering, mathematics, and pharmacology, should be engaged at the study design phase to optimize the information gathered and to identify and further evaluate potentially actionable therapeutic targets. Information sources should include noninvasive personalized sensors and monitors, alongside instructive "liquid biopsies" for noninvasive pregnancy assessment. Future research should also address the diversity of human cohorts in terms of geography, racial and ethnic distributions, and social and health disparities. Modern technologies, for both data-gathering and data-analyzing, make this possible at a scale that was previously unachievable. Finally, the psychosocial and economic environment in which pregnancy takes place must be considered to promote the health and wellness of communities worldwide.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.WT_/Wellcome Trust/United Kingdom R35 GM127087/GM/NIGMS NIH HHS/United Statespublished version, accepted version (12 month embargo

Using structural equation modelling to jointly estimate maternal and fetal effects on birthweight in the UK Biobank

This is the author accepted manuscript. The final version is available from OUP via the DOI in this recordBackground: To date, 60 genetic variants have been robustly associated with birthweight. It is unclear whether these associations represent the effect of an individual’s own genotype on their birthweight, their mother’s genotype, or both. Methods: We demonstrate how structural equation modelling (SEM) can be used to estimate both maternal and fetal effects when phenotype information is present for individuals in two generations and genotype information is available on the older individual. We conduct an extensive simulation study to assess the bias, power and type 1 error rates of the SEM and also apply the SEM to birthweight data in the UK Biobank study. Results: Unlike simple regression models, our approach is unbiased when there is both a maternal and fetal effect. The method can be used when either the individual’s own phenotype or the phenotype of their offspring is not available, and allows the inclusion of summary statistics from additional cohorts where raw data cannot be shared. We show that the type 1 error rate of the method is appropriate, there is substantial statistical power to detect a genetic variant that has a moderate effect on the phenotype, and reasonable power to detect whether it is a fetal and/or maternal effect. We also identify a subset of birthweight associated SNPs that have opposing maternal and fetal effects in the UK Biobank. Conclusions: Our results show that SEM can be used to estimate parameters that would be difficult to quantify using simple statistical methods alone.N.M.W. is supported by a National Health and Medical Research Council Early Career Fellowship (grant number APP1104818). D.M.E. is funded by an Australian Research Council Future Fellowship (grant number FT130101709) and an Medical Research Council programme grant (grant number MC_UU_12013/4). This research has been conducted using the UK Biobank Resource. Access to the UKBB study data was funded by University of Queensland Early Career Researcher Grant (2014002959)

A common genetic variant in the 15q24 nicotinic acetylcholine receptor gene cluster (CHRNA5–CHRNA3–CHRNB4) is associated with a reduced ability of women to quit smoking in pregnancy

Maternal smoking during pregnancy is associated with low birth weight and adverse pregnancy outcomes. Women are more likely to quit smoking during pregnancy than at any other time in their lives, but some pregnant women continue to smoke. A recent genome-wide association study demonstrated an association between a common polymorphism (rs1051730) in the nicotinic acetylcholine receptor gene cluster (CHRNA5–CHRNA3–CHRNB4) and both smoking quantity and nicotine dependence. We aimed to test whether the same polymorphism that predisposes to greater cigarette consumption would also reduce the likelihood of smoking cessation in pregnancy. We studied 7845 pregnant women of European descent from the South-West of England. Using 2474 women who smoked regularly immediately pre-pregnancy, we analysed the association between the rs1051730 risk allele and both smoking cessation during pregnancy and smoking quantity. Each additional copy of the risk allele was associated with a 1.27-fold higher odds (95% CI 1.11–1.45) of continued smoking during pregnancy (P = 0.0006). Adjustment for pre-pregnancy smoking quantity weakened, but did not remove this association [odds ratio (OR) 1.20 (95% CI 1.03–1.39); P = 0.018]. The same risk allele was also associated with heavier smoking before pregnancy and in the first, but not the last, trimester [OR for smoking 10+ cigarettes/day versus 1–9/day in first trimester = 1.30 (95% CI 1.13–1.50); P = 0.0003]. To conclude, we have found strong evidence of association between the rs1051730 variant and an increased likelihood of continued smoking in pregnancy and have confirmed the previously observed association with smoking quantity. Our data support the role of genetic factors in influencing smoking cessation during pregnancy

Using genetics to understand the causal influence of higher BMI on depression

Background: Depression is more common in obese than non-obese individuals, especially in women, but the causal relationship between obesity and depression is complex and uncertain. Previous studies have used genetic variants associated with BMI to provide evidence that higher body mass index (BMI) causes depression, but have not tested whether this relationship is driven by the metabolic consequences of BMI nor for differences between men and women. Methods: We performed a Mendelian randomization study using 48 791 individuals with depression and 291 995 controls in the UK Biobank, to test for causal effects of higher BMI on depression (defined using self-report and Hospital Episode data). We used two genetic instruments, both representing higher BMI, but one with and one without its adverse metabolic consequences, in an attempt to 'uncouple' the psychological component of obesity from the metabolic consequences. We further tested causal relationships in men and women separately, and using subsets of BMI variants from known physiological pathways. Results: Higher BMI was strongly associated with higher odds of depression, especially in women. Mendelian randomization provided evidence that higher BMI partly causes depression. Using a 73-variant BMI genetic risk score, a genetically determined one standard deviation (1 SD) higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals [odds ratio (OR): 1.18, 95% confidence interval (CI): 1.09, 1.28, P = 0.00007) and women only (OR: 1.24, 95% CI: 1.11, 1.39, P = 0.0001). Meta-analysis with 45 591 depression cases and 97 647 controls from the Psychiatric Genomics Consortium (PGC) strengthened the statistical confidence of the findings in all individuals. Similar effect size estimates were obtained using different Mendelian randomization methods, although not all reached P < 0.05. Using a metabolically favourable adiposity genetic risk score, and meta-analysing data from the UK biobank and PGC, a genetically determined 1 SD higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals (OR: 1.26, 95% CI: 1.06, 1.50], P = 0.010), but with weaker statistical confidence. Conclusions: Higher BMI, with and without its adverse metabolic consequences, is likely to have a causal role in determining the likelihood of an individual developing depression.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.DH_/Department of Health/United Kingdom MC_PC_17228/MRC_/Medical Research Council/United Kingdom MC_QA137853/MRC_/Medical Research Council/United Kingdom 104150/Z/14/Z/WT_/Wellcome Trust/United Kingdom MR/M005070/1/MRC_/Medical Research Council/United Kingdom WT097835MF/WT_/Wellcome Trust/United Kingdompublished version, accepted version (12 month embargo), submitted versio

The influence of transmitted and non-transmitted parental BMI-associated alleles on the risk of overweight in childhood

Overweight in children is strongly associated with parental body mass index (BMI) and overweight. We assessed parental transmitted and non-transmitted genetic contributions to overweight in children from the Danish National Birth Cohort by constructing genetic risk scores (GRSs) from 941 common genetic variants associated with adult BMI and estimating associations of transmitted maternal/paternal and non-transmitted maternal GRS with child overweight. Maternal and paternal BMI (standard deviation (SD) units) had a strong association with childhood overweight [Odds ratio (OR): 2.01 (95% confidence interval (CI) 1.74; 2.34) and 1.64 (95% CI 1.43; 1.89)]. Maternal and paternal transmitted GRSs (SD-units) increased odds for child overweight equally [OR: 1.30 (95% CI 1.16; 1.46) and 1.30 (95% CI 1.16; 1.47)]. However, both the parental phenotypic and the GRS associations may depend on maternal BMI, being weaker among mothers with overweight. Maternal non-transmitted GRS was not associated with child overweight [OR 0.98 (95% CI 0.88; 1.10)] suggesting no specific influence of maternal adiposity as such. In conclusion, parental transmitted GRSs, based on adult BMI, contribute to child overweight, but in overweight mothers other genetic and environmental factors may play a greater role.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.WT104150/Wellcome Trust (Wellcome)published version, accepted version, submitted versio

Smoking Is Associated with, but Does Not Cause, Depressed Mood in Pregnancy – A Mendelian Randomization Study

Smokers have a higher prevalence of major depressive episodes and depressive symptoms than the general population, but whether this association is causal, or is due to confounding or reverse causation is uncertain because of the problems inherent in some epidemiological studies. Mendelian randomization, in which a genetic variant is used as a surrogate for measuring exposure, is an approach which may be used to better understand this association. We investigated the rs1051730 single nucleotide polymorphism in the nicotine acetylcholine receptor gene cluster (CHRNA5-CHRNA3-CHRNB4), associated with smoking phenotypes, to determine whether women who continued to smoke were also more likely to report a low mood during pregnancy. We found among women who smoked pre-pregnancy, those with the 1051730 T allele smoked more and were less likely to quit smoking during pregnancy, but were also less likely to report high levels of depressed mood at 18 weeks of pregnancy (per allele OR = 0.84, 95%CI 0.72 to 0.99, p = 0.034). The association between genotype and depressed mood was limited to women who were smokers prior to pregnancy, with weak evidence of an interaction between smoking status and genotype (p = 0.07). Our results do not support a causal role of smoking on depressed mood, but are consistent with a self-medication hypothesis, whereby smoking is used to alleviate symptoms of depression. A replication study using multiple genetic variants which influence smoking via different pathways is required to confirm these findings and provide evidence that the genetic variant is reflecting the effect of quitting smoking on depressed mood, and is not directly affecting mood

Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study: common genetic variants in GCK and TCF7L2 are associated with fasting and postchallenge glucose levels in pregnancy and with the new consensus definition of gestational diabetes mellitus from the International Association of Diabetes and Pregnancy Study Groups.

OBJECTIVE: Common genetic variants in GCK and TCF7L2 are associated with higher fasting glucose and type 2 diabetes in nonpregnant populations. However, their associations with glucose levels from oral glucose tolerance tests (OGTTs) in pregnancy have not been assessed in a large sample. We hypothesized that these variants are associated with quantitative measures of glycemia in pregnancy. RESEARCH DESIGN AND METHODS: We analyzed the associations between variants rs1799884 (GCK) and rs7903146 (TCF7L2) and OGTT outcomes at 24-32 weeks' gestation in 3,811 mothers of European (U.K. and Australia) and 1,706 mothers of Asian (Thailand) ancestry from the HAPO cohort. We also tested associations with offspring birth anthropometrics. RESULTS: The maternal GCK variant was associated with higher fasting glucose in Europeans (P = 0.001) and Thais (P 0.05). In both populations, both variants were associated with higher odds of gestational diabetes mellitus according to the new International Association of Diabetes and Pregnancy Study Groups recommendations (P = 0.001-0.08). CONCLUSIONS: Maternal GCK and TCF7L2 variants are associated with glucose levels known to carry an increased risk of adverse pregnancy outcome in women without overt diabetes. Further studies will be important to determine the variance in maternal glucose explained by all known genetic variants

Dissecting maternal and fetal genetic effects underlying the associations between maternal phenotypes, birth outcomes, and adult phenotypes: A mendelian-randomization and haplotype-based genetic score analysis in 10,734 mother–infant pairs

Author summaryWhy was this study done? Maternal height, BMI, blood glucose, and blood pressure are associated with gestational duration, birth weight, and birth length. These birth outcomes are subsequently associated with late-onset health conditions. The causal mechanisms and the relative contributions of maternal and fetal genetic effects underlying these observed associations are not clear. What did the researchers do and find? We dissected the relative contributions of maternal and fetal genetic effects using haplotype genetic score analysis in 10,734 mother-infant pairs of European ancestry. Genetically elevated maternal height is associated with longer gestational duration and larger birth size. In the fetus, alleles associated with adult height are positively associated with birth size. Alleles elevating blood pressure are associated with shorter gestational duration through a maternal effect and are associated with reduced fetal growth through a fetal genetic effect. Alleles that increase blood glucose in the mother are associated with increased birth weight, whereas risk alleles for type 2 diabetes in the fetus are associated with reduced birth weight. Alleles raising birth weight in fetus are associated with shorter gestational duration and higher maternal blood pressure during pregnancy. What do these findings mean? Maternal size and fetal growth are important factors in shaping the duration of gestation. Fetal growth is influenced by both maternal and fetal effects. Higher maternal BMI and glucose levels positively associate with birth weight through maternal effects. In the fetus, alleles associated with higher metabolic risks are negatively associated with birth weight. More rapid fetal growth is associated with shorter gestational duration and higher maternal blood pressure. These maternal and fetal genetic effects can largely explain the observed associations between maternal phenotypes and birth outcomes, as well as the life-course associations between these birth outcomes and adult phenotypes. Background Many maternal traits are associated with a neonate's gestational duration, birth weight, and birth length. These birth outcomes are subsequently associated with late-onset health conditions. The causal mechanisms and the relative contributions of maternal and fetal genetic effects behind these observed associations are unresolved. Methods and findings Based on 10,734 mother-infant duos of European ancestry from the UK, Northern Europe, Australia, and North America, we constructed haplotype genetic scores using single-nucleotide polymorphisms (SNPs) known to be associated with adult height, body mass index (BMI), blood pressure (BP), fasting plasma glucose (FPG), and type 2 diabetes (T2D). Using these scores as genetic instruments, we estimated the maternal and fetal genetic effects underlying the observed associations between maternal phenotypes and pregnancy outcomes. We also used infant-specific birth weight genetic scores as instrument and examined the effects of fetal growth on pregnancy outcomes, maternal BP, and glucose levels during pregnancy. The maternal nontransmitted haplotype score for height was significantly associated with gestational duration (p= 2.2 x 10(-4)). Both maternal and paternal transmitted height haplotype scores were highly significantly associated with birth weight and length (p<1 x 10(-17)). The maternal transmitted BMI scores were associated with birth weight with a significant maternal effect (p= 1.6 x 10(-4)). Both maternal and paternal transmitted BP scores were negatively associated with birth weight with a significant fetal effect (p= 9.4 x 10(-3)), whereas BP alleles were significantly associated with gestational duration and preterm birth through maternal effects (p= 3.3 x 10(-2)andp= 4.5 x 10(-3), respectively). The nontransmitted haplotype score for FPG was strongly associated with birth weight (p= 4.7 x 10(-6)); however, the glucose-increasing alleles in the fetus were associated with reduced birth weight through a fetal effect (p= 2.2 x 10(-3)). The haplotype scores for T2D were associated with birth weight in a similar way but with a weaker maternal effect (p= 6.4 x 10(-3)) and a stronger fetal effect (p= 1.3 x 10(-5)). The paternal transmitted birth weight score was significantly associated with reduced gestational duration (p= 1.8 x 10(-4)) and increased maternal systolic BP during pregnancy (p= 2.2 x 10(-2)). The major limitations of the study include missing and heterogenous phenotype data in some data sets and different instrumental strength of genetic scores for different phenotypic traits. Conclusions We found that both maternal height and fetal growth are important factors in shaping the duration of gestation: genetically elevated maternal height is associated with longer gestational duration, whereas alleles that increase fetal growth are associated with shorter gestational duration. Fetal growth is influenced by both maternal and fetal effects and can reciprocally influence maternal phenotypes: taller maternal stature, higher maternal BMI, and higher maternal blood glucose are associated with larger birth size through maternal effects; in the fetus, the height- and metabolic-risk-increasing alleles are associated with increased and decreased birth size, respectively; alleles raising birth weight in the fetus are associated with shorter gestational duration and higher maternal BP. These maternal and fetal genetic effects may explain the observed associations between the studied maternal phenotypes and birth outcomes, as well as the life-course associations between these birth outcomes and adult phenotypes.Peer reviewe

Adult height variants affect birth length and growth rate in children

Previous studies identified 180 single nucleotide polymorphisms (SNPs) associated with adult height, explaining ∼10% of the variance. The age at which these begin to affect growth is unclear. We modelled the effect of these SNPs on birth length and childhood growth. A total of 7768 participants in the Avon Longitudinal Study of Parents and Children had data available. Individual growth trajectories from 0 to 10 years were estimated using mixed-effects linear spline models and differences in trajectories by individual SNPs and allelic score were determined. The allelic score was associated with birth length (0.026 cm increase per ‘tall’ allele, SE = 0.003, P = 1 × 10−15, equivalent to 0.017 SD). There was little evidence of association between the allelic score and early infancy growth (0–3 months), but there was evidence of association between the allelic score and later growth. This association became stronger with each consecutive growth period, per ‘tall’ allele per month effects were 0.015 SD (3 months–1 year, SE = 0.004), 0.023 SD (1–3 years, SE = 0.003) and 0.028 SD (3–10 years, SE = 0.003). By age 10, the mean height difference between individuals with ≤170 versus ≥191 ‘tall’ alleles (the top and bottom 10%) was 4.7 cm (0.8 SD), explaining ∼5% of the variance. There was evidence of associations with specific growth periods for some SNPs (rs3791675, EFEMP1 and rs6569648, L3MBTL3) and supportive evidence for previously reported age-dependent effects of HHIP and SOCS2 SNPs. SNPs associated with adult height influence birth length and have an increasing effect on growth from late infancy through to late childhood. By age 10, they explain half the height variance (∼5%) of that explained in adults (∼10%)

Quantifying the extent to which index event biases influence large genetic association studies

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.As genetic association studies increase in size to 100,000s of individuals, subtle biases may influence conclusions. One possible bias is "index event bias" (IEB) that appears due to the stratification by, or enrichment for, disease status when testing associations between genetic variants and a disease-associated trait. We aimed to test the extent to which IEB influences some known trait associations in a range of study designs and provide a statistical framework for assessing future associations. Analysing data from 113,203 non-diabetic UK Biobank participants, we observed three (near TCF7L2, CDKN2AB and CDKAL1) overestimated (BMI-decreasing) and one (near MTNR1B) underestimated (BMI-increasing) associations among 11 type 2 diabetes risk alleles (at P  500,000 if the prevalence of those diseases differs by > 10% from the background population. In conclusion, IEB may result in false positive or negative genetic associations in very large studies stratified or strongly enriched for/against disease cases.H.Y., A.R.W. and T.M.F. are supported by the European Research Council grant: 323195; SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC. S.E.J. is funded by the Medical Research Council (grant: MR/M005070/1). M.A.T., M.N.W. and A.M. are supported by the Wellcome Trust Institutional Strategic Support Award (WT097835MF). R.M.F. is a Sir Henry Dale Fellow (Wellcome Trust and Royal Society grant: 104150/Z/14/Z). R.B. is funded by the Wellcome Trust and Royal Society grant: 104150/Z/14/Z. J.T. is funded by a Diabetes Research and Wellness Foundation Fellowship. Z.K. received financial support from the Leenaards Foundation, the Swiss Institute of Bioinformatics and the Swiss National Science Foundation (31003A-143914) and SystemsX.ch (39). The work of M.P.B was supported by the National Heart, Lung, And Blood Institute of the National Institutes of Health under Award no. T32HL007779. Generation Scotland received core support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006]. E.R.P. holds a WT New investigator award 102820/Z/13/Z