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BackgroundHigher urate levels associate with higher systolic blood pressure (SBP) in adults, and in pregnancy, with lower offspring birthweight. Mendelian randomization (MR) analyses suggest a causal effect of higher urate on higher SBP and of higher maternal SBP on lower offspring birthweight. If urate causally reduces birthweight, it might confound the effect of SBP on birth weight. We therefore tested for a causal effect of maternal urate on offspring birthweight.MethodsWe tested the association between maternal urate levels and offspring birthweight using multivariable linear regression in UK Biobank (UKB; n=133,187) and Exeter Family Study of Childhood Health (EFSOCH; n=872). We conducted two-sample MR to test for a causal effect of maternal urate (114 single nucleotide polymorphisms [SNPs]; n=288,649 European-ancestry) on offspring birthweight (n=406,063 European-ancestry; maternal SNP effect estimates adjusted for fetal effects). Using one-sample MR (n=199,768 UKB women), we also tested for a causal relationship between urate and SBP.ResultsHigher maternal urate was associated with lower offspring birthweight in UKB (28g lower birthweight per 1-SD higher urate [95% CI: -31, -25]; P=1.8×10−75), with a similar effect estimate in EFSOCH (22g [95%CI: -50, 6]; P=0.13). The MR causal effect estimate was directionally consistent, but smaller (−11g [95% CI: -25, 3]; PIVW=0.13). In women, higher urate was causally associated with higher SBP (1.7 mmHg higher SBP per 1-SD higher urate [95% CI: 1.4, 2.1]; P=7.8×10−22) consistent with that previously published in women and men.ConclusionsThe marked attenuation of the MR result of maternal urate on offspring birthweight, compared to the multivariable regression result suggests previous observational associations may be confounded. The 95% CIs of the MR result included the null but suggest a possible weak effect on birthweight. Maternal urate levels are unlikely to be an important contributor to offspring birthweight.Key MessagesPrevious research suggests higher maternal serum urate in pregnancy is associated with lower offspring birthweight, and Mendelian randomization studies suggest a causal relationship between urate and systolic blood pressure (SBP), and SBP and birthweight; a causal effect of urate on birthweight has not yet been estimated, and thus it is also unknown whether it confounds maternal SBP-birthweight effects.The causal effect estimate of urate on offspring birthweight was directionally consistent, but weaker than, observational estimates; the estimate had 95% confidence intervals which included the null.This study confirmed a causal association between serum urate and higher SBP in women consistent with that published from a sample of both women and men.Maternal urate is unlikely to be a major determinant of birthweight or an important confounder of the causal relationship between SBP and lower birthweight.

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.

This research has been conducted using the UK Biobank resource under application number 9072. Copyright © The Author(s) 2021. Higher adiposity is an established risk factor for psychiatric diseases including depression and anxiety. The associations between adiposity and depression may be explained by the metabolic consequences and/or by the psychosocial impact of higher adiposity. We performed one-and two-sample Mendelian randomization (MR) in up to 145 668 European participants from the UK Biobank to test for a causal effect of higher adiposity on 10 well-validated mental health and well-being outcomes derived using the Mental Health Questionnaire (MHQ). We used three sets of adiposity genetic instruments: (a) a set of 72 BMI genetic variants, (b) a set of 36 favourable adiposity variants and (c) a set of 38 unfavourable adiposity variants. We additionally tested causal relationships (1) in men and women separately, (2) in a subset of individuals not taking antidepressants and (3) in non-linear MR models. Two-sample MR provided evidence that a genetically determined one standard deviation (1-SD) higher BMI (4.6 kg/m2) was associated with higher odds of current depression [OR: 1.50, 95%CI: 1.15, 1.95] and lower well-being [ß:-0.15, 95%CI:-0.26,-0.04]. Findings were similar when using the metabolically favourable and unfavourable adiposity variants, with higher adiposity associated with higher odds of depression and lower well-being scores. Our study provides further evidence that higher BMI causes higher odds of depression and lowers well-being. Using genetics to separate out metabolic and psychosocial effects, our study suggests that in the absence of adverse metabolic effects higher adiposity remains causal to depression and lowers well-being. Academy of Medical Sciences (AMS) Springboard award, which is supported by the AMS, the Wellcome Trust, GCRF, the Government Department of Business, Energy and Industrial strategy, the British Heart Foundation and Diabetes UK (SBF004\1079 to J.O., F.C. and J.T.); Wellcome Senior Research Fellowship (WT220390 to R.M.F.). Diabetes UK RD Lawrence fellowship (17/0005594 to H.Y.).

ImportanceHigher maternal pre-pregnancy body mass index (BMI) is associated with adverse pregnancy and perinatal outcomes. However, which of these associations are causal remains unclear.ObjectiveTo explore the relation of maternal pre-pregnancy BMI with pregnancy and perinatal outcomes by integrating evidence from three different methods (i.e. multivariable regression, Mendelian randomization, and paternal negative control analyses).DesignTriangulation of multivariable regression, Mendelian randomization and paternal negative control results from up to 14 studies in the MR-PREG collaboration.SettingEurope and North America.ParticipantsUp to 497,932 women of European ancestry.ExposureMaternal pre- or early-pregnancy BMI based on self-reported or measured weight and height.Main outcomes and MeasuresMiscarriage, stillbirth, hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, maternal anaemia, perinatal depression, pre-labour rupture of membranes, induction of labour, caesarean section, preterm birth, small- and large-for-gestational age, low and high birthweight, low Apgar score at 1 and 5 minutes, neonatal intensive care unit admission, and no initiation of breastfeeding.ResultsMultivariable regression, Mendelian randomization and paternal negative control analyses supported an association of higher maternal BMI with lower risk of small-for-gestational age and higher risk of hypertensive disorders of pregnancy, gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, large-for-gestational age, and high birthweight. As an example, higher maternal BMI was associated with higher risk of gestational hypertension in multivariable regression (OR: 1.67; 95% CI: 1.64, 1.71 per standard unit in BMI) and Mendelian randomization (OR: 1.58; 95% CI: 1.29, 1.93), which was not seen for paternal BMI (OR: 1.02; 95% CI: 0.99, 1.05). 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 randomization.Conclusions and RelevanceOur findings support a causal role for maternal pre-/early-pregnancy BMI on a range of adverse pregnancy and perinatal outcomes. Pre-conception interventions to support women maintaining a healthy BMI may reduce the burden of obstetric and neonatal complications.KEY POINTSQuestionWhat is the effect of higher maternal pre-/early-pregnancy body mass index (BMI) on adverse pregnancy and perinatal outcomes?FindingsWe found consistent evidence that higher maternal BMI was related to higher risk of gestational hypertension, preeclampsia, gestational diabetes, pre-labour membrane rupture, induction of labour, and having a large-for-gestational-age baby, lower risk of having a small-for-gestational-age baby, and not related to perinatal depression.MeaningThese findings highlight the importance of supporting women to achieve/maintain a healthy pre-conception BMI to reduce the burden of obstetric and neonatal complications.

Graphical abstract In 1998 the fetal insulin hypothesis proposed that lower birthweight and adult-onset type 2 diabetes are two phenotypes of the same genotype. Since then, advances in research investigating the role of genetics affecting insulin secretion and action have furthered knowledge of fetal insulin-mediated growth and the biology of type 2 diabetes. In this review, we discuss the historical research context from which the fetal insulin hypothesis originated and consider the position of the hypothesis in light of recent evidence. In summary, there is now ample evidence to support the idea that variants of certain genes which result in impaired pancreatic beta cell function and reduced insulin secretion contribute to both lower birthweight and higher type 2 diabetes risk in later life when inherited by the fetus. There is also evidence to support genetic links between type 2 diabetes secondary to reduced insulin action and lower birthweight but this applies only to loci implicated in body fat distribution and not those influencing insulin resistance via obesity or lipid metabolism by the liver. Finally, we also consider how advances in genetics are being used to explore alternative hypotheses, namely the role of the maternal intrauterine environment, in the relationship between lower birthweight and adult cardiometabolic disease. Supplementary Information The online version of this article (10.1007/s00125-021-05386-7) contains a slideset of the figures for download, which is available to authorised users.

Amino acids are key to protein synthesis, energy metabolism, cell signaling and gene expression; however, the contribution of specific maternal amino acids to fetal growth is unclear. We explored the effect of maternal circulating amino acids on fetal growth, proxied by birthweight, using two-sample Mendelian randomization and summary data from a genome-wide association study (GWAS) of serum amino acids levels (sample 1, n = 86,507) and a maternal GWAS of offspring birthweight, adjusting for fetal genotype effects (sample 2, n = 406,063 with maternal and/or fetal genotype effect estimates). A total of 106 independent single nucleotide polymorphisms (SNPs) robustly associated with 19 amino acids (p < 4.9 × 10−10) were used as genetic instrumental variables. Our results provide evidence that maternal circulating glutamine (59 g offspring birthweight increase per SD increase in maternal amino acid level, 95% CI: 7, 110) and serine (27 g, 95% CI: 9, 46) raise, while leucine (−59 g, 95% CI: -106, -11) and phenylalanine (−25 g, 95% CI: -47, -4) lower offspring birthweight. Our findings strengthen evidence for key roles of maternal circulating amino acids in healthy fetal growth.

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.

Background Human birthweight is a complex, multifactorial trait. Maternal characteristics contribute to birthweight variation by influencing the intrauterine environment. Variation explained by genetic effects is also important, but their contributions have not been assessed alongside other key determinants. We aimed to investigate variance in birthweight explained by genetic scores in addition to easily-measurable clinical and anthropometric variables. Methods We analysed 549 European-ancestry parent-offspring trios from a UK community-based birth cohort. We investigated variance explained in birthweight (adjusted for sex and gestational age) in multivariable linear regression models including genetic scores, routinely-measured maternal characteristics, and parental anthropometric variables. We used R-Squared (R2) to estimate variance explained, adjusted R-squared (Adj-R2) to assess improvement in model fit from added predictors, and F-tests to compare nested models. Results Maternal and fetal genetic scores together explained 6.0% variance in birthweight. A model containing maternal age, weight, smoking, parity and 28-week fasting glucose explained 21.7% variance. Maternal genetic score explained additional variance when added to maternal characteristics (Adj-R2 = 0.233 vs Adj-R2 = 0.210, p R2 = 0.264 vs 0.248, p Conclusions Genetic scores account for variance explained in birthweight in addition to easily measurable clinical variables. Parental heights partially capture fetal genotype and its contribution to birthweight, but genetic scores explain additional variance. While the genetic contribution is modest, it is comparable to that of individual clinical characteristics such as parity, which suggests that genetics could be included in tools aiming to predict risk of high or low birthweights.

BackgroundHuman birthweight is a complex, multifactorial trait. Maternal characteristics contribute to birthweight variation by influencing the intrauterine environment. Variation explained by genetic effects is also important, but their contributions have not been assessed alongside other key determinants. We aimed to investigate variance in birthweight explained by genetic scores in addition to easily-measurable clinical and anthropometric variables.MethodsWe analysed 549 European-ancestry parent-offspring trios. We investigated variance explained in birthweight (adjusted for sex and gestational age) in multivariable linear regression models including genetic scores, routinely-measured maternal characteristics and parental anthropometric variables. We used R-Squared (R2) to estimate variance explained, adjusted R-squared (Adj-R2) to assess improvement in model fit from added predictors, and F-tests to compare nested models.ResultsMaternal and fetal genetic scores together explained 6.0% variance in birthweight. A model containing maternal age, weight, smoking, parity and 28-week fasting glucose explained 21.7% variance. Maternal genetic score explained additional variance when added to maternal characteristics (Adj-R2 =0.233 vs Adj-R2=0.210, p2=0.264 vs 0.248, pConclusionsGenetic scores account for variance explained in birthweight in addition to easily measurable clinical variables. Parental heights partially capture fetal genotype and its contribution to birthweight, but genetic scores explain additional variance. While the genetic contribution is modest, it is comparable to that of individual clinical characteristics such as parity, which suggests that genetics could be included in tools aiming to predict risk of high or low birthweights.Key messagesKnown contributors to variation in birthweight include (i) factors associated with the maternal intrauterine environment (e.g. maternal glycaemia or smoking), and (ii) parental heights, which capture some of the genetic contribution to fetal growth. However, the added contribution of genetic scores composed of common birthweight-associated variants has not been assessed.We showed, using 549 parent-offspring trios, that maternal and fetal genetic scores explained additional variation in sex-and gestational age-adjusted birthweight, when added to maternal variables that are easily obtained in a clinical setting (age, weight, smoking, parity and 28-week fasting glucose).Parental heights explained variance in birthweight independently of routinely measured maternal clinical variables, but the maternal and fetal (or paternal) genetic scores made additional, independent contributions to birthweight variance.The genetic score contribution was modest, but it was comparable to that of individual clinical characteristics such as parity, which suggests that genetics could be included in tools aiming to predict risk of high or low birthweights.Since this work was limited to a UK sample of European ancestry, it will, however, be important to test the relative contributions of genetics and other factors to birthweight variation in diverse populations.

Size at birth is known to be influenced by various fetal and maternal factors including genetic effects. South Asians have a high burden of low birthweight and cardiometabolic diseases, yet studies of common genetic variations underpinning these phenotypes are lacking. We generated independent, weighted fetal genetic score (fGS) and maternal genetic score (mGS) from 196 birthweight-associated variants identified in Europeans and conducted association analysis with various fetal birth parameters and anthropometric and cardiometabolic traits measured at different follow-up stages (5-6 years’ intervals) from seven Indian and Bangladeshi cohorts of South Asian ancestry. The results from above cohorts were compared with South Asians in UK BioBank and The Exeter Family Study of Childhood Health, a European ancestry cohort. Birthweight increased by 50.7g and 33.6g per standard deviation of fGS (p = 9.1x10-11) and mGS (p = 0.003) respectively in South Asians. A relatively weaker maternal genetic score effect compared to Europeans indicates possible different intrauterine exposures between Europeans and South Asians. Birthweight was strongly associated with body size in both childhood and adolescence (p = 3x10-5 - 1.9x10-51), however, fetal genetic score was associated with body size in childhood only (p < 0.01) and with head circumference, fasting glucose and triglycerides in adults (p < 0.01). The substantially smaller newborn size in South Asians with comparable fetal genetic effect to Europeans on birthweight suggests a significant role of factors related to fetal growth that were not captured by the present genetic scores. These factors may include different environmental exposures, maternal body size, health and nutritional status etc. Persistent influence of genetic loci on size at birth and adult metabolic syndrome in our study supports a common genetic mechanism partly explaining associations between early development and later cardiometabolic health in various populations, despite marked differences in phenotypic and environmental factors in South Asians.

Data availability: Our study uses two-sample MR. We used both published summary results (i.e. taking results from published research papers and websites) and individual participant cohort data: journal-published and website summary data were used for sample one of the two-sample MR (published GWAS of BMI and body fat percentage). The references to the published data sources are provided in the main paper. The data for the GWAS of BMI are available at https://portals.broadinstitute.org/collaboration/giant/index.php/GIANT_consortium_data_files. The data for the GWAS of body fat percentage are available at https://walker05.u.hpc.mssm.edu. We used individual participant data for the second MR sample and for undertaking sensitivity analyses from the UKB, ALSPAC, BiB, EFSOCH and HAPO cohorts. The data in UKB, ALSPAC and BiB are fully available, via managed systems, to any researchers. The managed system for both studies is a requirement of the study funders but access is not restricted on the basis of overlap with other applications to use the data or on the basis of peer review of the proposed science. Researchers have to pay for a dataset to be prepared for them. Full information on how to access UKB data can be found at www.ukbiobank.ac.uk/using-the-resource/. The ALSPAC data management plan (www.bristol.ac.uk/alspac/researchers/data-access/documents/alspac-data-management-plan.pdf) describes, in detail, the policy regarding data sharing, which is through a system of managed open access. The following steps highlight how to apply for access to the data included in this paper and all other ALSPAC data: (1) please read the ALSPAC access policy (PDF, 627 kB), which describes the process of accessing the data and samples in detail, and outlines the costs associated with doing so; (2) you may also find it useful to browse the fully searchable ALSPAC research proposals database, which lists all research projects that have been approved since April 2011; (3) please submit your research proposal for consideration by the ALSPAC Executive Committee and you will receive a response within 10 working days to advise you whether your proposal has been approved. If you have any questions about accessing data, please e-mail alspac-data@bristol.ac.uk. Full information on how to access BiB data can be found at https://borninbradford.nhs.uk/research/how-to-access-data/. Requests for access to the original EFSOCH dataset should be made in writing in the first instance to the EFSOCH data team via the Exeter Clinical Research Facility (crf@exeter.ac.uk). Copyright © The Author(s) 2022. Aims/hypothesis: Higher maternal BMI during pregnancy is associated with higher offspring birthweight, but it is not known whether this is solely the result of adverse metabolic consequences of higher maternal adiposity, such as maternal insulin resistance and fetal exposure to higher glucose levels, or whether there is any effect of raised adiposity through non-metabolic (e.g. mechanical) factors. We aimed to use genetic variants known to predispose to higher adiposity, coupled with a favourable metabolic profile, in a Mendelian randomisation (MR) study comparing the effect of maternal ‘metabolically favourable adiposity’ on offspring birthweight with the effect of maternal general adiposity (as indexed by BMI). Methods: To test the causal effects of maternal metabolically favourable adiposity or general adiposity on offspring birthweight, we performed two-sample MR. We used variants identified in large, published genetic-association studies as being associated with either higher adiposity and a favourable metabolic profile, or higher BMI (n = 442,278 and n = 322,154 for metabolically favourable adiposity and BMI, respectively). We then extracted data on the metabolically favourable adiposity and BMI variants from a large, published genetic-association study of maternal genotype and offspring birthweight controlling for fetal genetic effects (n = 406,063 with maternal and/or fetal genotype effect estimates). We used several sensitivity analyses to test the reliability of the results. As secondary analyses, we used data from four cohorts (total n = 9323 mother–child pairs) to test the effects of maternal metabolically favourable adiposity or BMI on maternal gestational glucose, anthropometric components of birthweight and cord-blood biomarkers. Results: Higher maternal adiposity with a favourable metabolic profile was associated with lower offspring birthweight (−94 [95% CI −150, −38] g per 1 SD [6.5%] higher maternal metabolically favourable adiposity, p = 0.001). By contrast, higher maternal BMI was associated with higher offspring birthweight (35 [95% CI 16, 53] g per 1 SD [4 kg/m2] higher maternal BMI, p = 0.0002). Sensitivity analyses were broadly consistent with the main results. There was evidence of outlier SNPs for both exposures; their removal slightly strengthened the metabolically favourable adiposity estimate and made no difference to the BMI estimate. Our secondary analyses found evidence to suggest that a higher maternal metabolically favourable adiposity decreases pregnancy fasting glucose levels while a higher maternal BMI increases them. The effects on neonatal anthropometric traits were consistent with the overall effect on birthweight but the smaller sample sizes for these analyses meant that the effects were imprecisely estimated. We also found evidence to suggest that higher maternal metabolically favourable adiposity decreases cord-blood leptin while higher maternal BMI increases it. Conclusions/interpretation: Our results show that higher adiposity in mothers does not necessarily lead to higher offspring birthweight. Higher maternal adiposity can lead to lower offspring birthweight if accompanied by a favourable metabolic profile. US National Institute of Health (R01 DK10324); European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement no 669545; British Heart Foundation (CS/16/4/32482 and AA/18/7/34219); NIHR Biomedical Centre at the University Hospitals Bristol NHS Foundation Trust; University of Bristol.

Gestational diabetes mellitus (GDM) is associated with increased risk of pregnancy complications and adverse perinatal outcomes. GDM often reoccurs and is associated with increased risk of subsequent diagnosis of type 2 diabetes (T2D). To improve our understanding of the aetiological factors and molecular processes driving the occurrence of GDM, including the extent to which these overlap with T2D pathophysiology, the GENetics of Diabetes In Pregnancy (GenDIP) Consortium assembled genome-wide association studies (GWAS) of diverse ancestry in a total of 5,485 women with GDM and 347,856 without GDM. Through trans-ancestry meta-analysis, we identified five loci with genome-wide significant association (p−8) with GDM, mapping to/near MTNR1B (p=4.3×10−54), TCF7L2 (p=4.0×10−16), CDKAL1 (p=1.6×10−14), CDKN2A-CDKN2B (p=4.1×10−9) and HKDC1 (p=2.9×10−8). Multiple lines of evidence pointed to genetic contributions to the shared pathophysiology of GDM and T2D: (i) four of the five GDM loci (not HKDC1) have been previously reported at genome-wide significance for T2D; (ii) significant enrichment for associations with GDM at previously reported T2D loci; (iii) strong genetic correlation between GDM and T2D; and (iv) enrichment of GDM associations mapping to genomic annotations in diabetes-relevant tissues and transcription factor binding sites. Mendelian randomisation analyses demonstrated significant causal association (5% false discovery rate) of higher body mass index on increased GDM risk. Our results provide support for the hypothesis that GDM and T2D are part of the same underlying pathology but that, as exemplified by the HKDC1 locus, there are genetic determinants of GDM that are specific to glucose regulation in pregnancy.

The COVID-19 pandemic has put diabetes at the forefront of conversation. The prevalence of type 2 diabetes in the United Kingdom is high1 and has links to adverse COVID-19 outcomes.2 Research investigating the links between these two public health issues are moving at pace. However, the pandemic has seen early career researchers (ECRs) in diabetes face professional and personal challenges that have the potential to slow down or derail bourgeoning careers. These challenges are not unique to ECRs working in the diabetes field—and they compound a challenging decade that included the fallout from an economic crisis and uncertainties arising from a protracted Brexit. In May 2021, 15 ECRs gathered online as part of the Diabetes UK annual Innovators in Diabetes (IDia) training programme. A discussion on the career challenges faced and possible solutions to facilitate a healthy future for diabetes ECRs was initiated and facilitated by senior leaders in diabetes research. This letter summarises the themes from that discussion.

Background It is suggested amino acids are critical for fetal growth, but analyses assessing causality are lacking. Mendelian randomisation (MR) can be used to examine causal effects under instrumental variable (IV) assumptions. Methods We conducted a two-sample MR study utilizing summary data from genome-wide association studies (GWAS) of amino acids (sample 1, n = 86,507) and of offspring birthweight (sample 2, combined UK Biobank and Early Growth Genetics Consortium, n = 406,063). Seventy-five independent single nucleotide polymorphisms (SNPs) robustly associated with 18 amino acids (p Results There was evidence of positive causal effects of maternal alanine (51.9 g birthweight increase per SD increase in amino acid level, 95% CI: 24.2, 79.5), glutamine (51.3 g, 95% CI: 33.5, 69.0), glycine (10.4 g, 95% CI: 1.3, 19.6) and serine (27.1 g, 95% CI: 11.2, 43.0) on birthweight and inverse causal effects of maternal isoleucine (-109.7 g, 95% CI: -194.6, -24.9) and histidine (-41.1 g, 95% CI: -78.5, -3.7) on birthweight. Sensitivity analyses to explore reverse causality and bias due to horizontal pleiotropy supported our findings. Conclusions Some maternal circulating amino acids have causal effects on birthweight. Key messages MR can be extended to probe effects of maternal nutrition on offspring development.

The duration of pregnancy is influenced by fetal and maternal genetic and non-genetic factors. Here we report a fetal genome-wide association meta-analysis of gestational duration, and early preterm, preterm, and postterm birth in 84,689 infants. One locus on chromosome 2q13 is associated with gestational duration; the association is replicated in 9,291 additional infants (combined P = 3.96 × 10−14). Analysis of 15,588 mother-child pairs shows that the association is driven by fetal rather than maternal genotype. Functional experiments show that the lead SNP, rs7594852, alters the binding of the HIC1 transcriptional repressor. Genes at the locus include several interleukin 1 family members with roles in pro-inflammatory pathways that are central to the process of parturition. Further understanding of the underlying mechanisms will be of great public health importance, since giving birth either before or after the window of term gestation is associated with increased morbidity and mortality., Gestational duration depends on both maternal and fetal genetic influences. Here, the authors perform a fetal genome-wide association meta-analysis and find that a locus on 2q13 is associated with pregnancy duration and further show that the lead SNP rs7594852 changes the binding properties of transcriptional repressor HIC1.

Being a morning person is a behavioural indicator of a person’s underlying circadian rhythm. Using genome-wide data from 697,828 UK Biobank and 23andMe participants we increase the number of genetic loci associated with being a morning person from 24 to 351. Using data from 85,760 individuals with activity-monitor derived measures of sleep timing we find that the chronotype loci associate with sleep timing: the mean sleep timing of the 5% of individuals carrying the most morningness alleles is 25 min earlier than the 5% carrying the fewest. The loci are enriched for genes involved in circadian regulation, cAMP, glutamate and insulin signalling pathways, and those expressed in the retina, hindbrain, hypothalamus, and pituitary. Using Mendelian Randomisation, we show that being a morning person is causally associated with better mental health but does not affect BMI or risk of Type 2 diabetes. This study offers insights into circadian biology and its links to disease in humans., GWAS have previously found 24 genomic loci associated with chronotype, an individual’s preference for early or late sleep timing. Here, the authors identify 327 additional loci in a sample of 697,828 individuals and further explore the relationships of chronotype with metabolic and psychiatric diseases.

We recently reported genetic variants associated with birth weight and their effect on future cardiometabolic risk in Europeans. Despite a higher burden of low birth weight and cardiometabolic disorders, such studies are lacking in South Asians. We generated fetal and maternal genetic scores (fGS and mGS) from 196 birth weight-associated variants identified in Europeans and conducted association analysis with various birth measures and serially measured anthropometric and cardiometabolic traits from seven Indian and Bangladeshi cohorts. Although fGS and mGS were comparable to Europeans, birth weight was substantially smaller suggesting strong environmental constraints on fetal growth in South Asians. Birth weight increased by 50.7g and 33.6g per standard deviation fGS (P=9.1×10−11) and mGS (P=0.003) in South Asians. The fGS was further associated with childhood body size and head circumference, fasting glucose, and triglycerides in adults (P

We recently reported genetic variants associated with birth weight and their effect on future cardiometabolic risk in Europeans. Despite a higher burden of low birth weight and cardiometabolic disorders, such studies are lacking in South Asians. We generated fetal and maternal genetic scores (fGS and mGS) from 196 birth weight-associated variants identified in Europeans and conducted association analysis with various birth measures and serially measured anthropometric and cardiometabolic traits from seven Indian and Bangladeshi cohorts. Although fGS and mGS were comparable to Europeans, birth weight was substantially smaller suggesting strong environmental constraints on fetal growth in South Asians. Birth weight increased by 50.7g and 33.6g per standard deviation fGS (P=9.1x10-11) and mGS (P=0.003) in South Asians. The fGS was further associated with childhood body size and head circumference, fasting glucose, and triglycerides in adults (P

Background: Using genetic scores for fasting plasma glucose (FPG GS) and type 2 diabetes (T2D GS), we investigated whether the fasting, 1-hour and 2-hour glucose thresholds from the WHO 2013 criteria for gestational diabetes (GDM) have different implications for genetic susceptibility to raised fasting glucose and type 2 diabetes in women from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) and Atlantic Diabetes in Pregnancy (DIP) studies. Methods: Cases were divided into three subgroups: (i) FPG ≥5.1 mmol/L only, n=222; (ii) 1-hour glucose post 75 g oral glucose load ≥10 mmol/L only, n=154 (iii) 2-hour glucose ≥8.5 mmol/L only, n=73; and (iv) both FPG ≥5.1 mmol/L and either of a 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, n=172. We compared the FPG and T2D GS of these groups with controls (n=3,091) in HAPO and DIP separately. Results: In HAPO and DIP, the mean FPG GS in women with a FPG ≥5.1 mmol/L, either on its own or with 1-hour glucose ≥10 mmol/L or 2-hour glucose ≥8.5 mmol/L, was higher than controls (all P

Background Lower maternal serum vitamin B12 (B12) and folate levels have been associated with lower offspring birthweight, in observational studies. The aim of this study was to investigate whether this relationship is causal. Methods We performed two-sample Mendelian randomization (MR) using summary data on associations between genotype-B12 (10 genetic variants) or genotype-folate (four genetic variants) levels from: a genome-wide association study of 45 576 individuals (sample 1); and both maternal- and fetal-specific genetic effects on offspring birthweight from the latest Early Growth Genetics consortium meta-analysis with 297 356 individuals reporting their own birthweight and 210 248 women reporting their offspring's birthweight (sample 2). We used the inverse variance weighted method, and sensitivity analyses to account for pleiotropy, in addition to excluding a potentially pleiotropic variant in the FUT2 gene for B12 levels. Results We did not find evidence for a causal effect of maternal or fetal B12 levels on offspring birthweight. The results were consistent across the different methods. We found a positive causal effect of maternal folate levels on offspring birthweight [0.146 (0.065, 0.227), which corresponds to an increase in birthweight of 71 g per 1 standard deviation higher folate]. We found some evidence for a small inverse effect of fetal folate levels on their own birthweight [−0.051 (−0.100, −0.003)]. Conclusions Our results are consistent with evidence from randomized controlled trials that higher maternal folate levels increase offspring birthweight. We did not find evidence for a causal effect of B12 levels on offspring birthweight, suggesting previous observational studies may have been confounded.

Birth weight is an important factor in newborn and infant survival, and both low and high birth weights are associated with adverse later life health outcomes. Genome-wide association studies (GWAS) have identified 190 loci associated with either maternal or fetal effects on birth weight. Knowledge of the underlying causal genes and pathways is crucial to understand how these loci influence birth weight, and the links between infant and adult morbidity. Numerous monogenic developmental syndromes are associated with birth weights at the extreme upper or lower ends of the normal distribution, and genes implicated in those syndromes may provide valuable information to help prioritise candidate genes at GWAS loci. We examined the proximity of genes implicated in developmental disorders to birth weight GWAS loci at which a fetal effect is either likely or cannot be ruled out. We used simulations to test whether those genes fall disproportionately close to the GWAS loci. We found that birth weight GWAS single nucleotide polymorphisms (SNPs) fall closer to such genes than expected by chance. This is the case both when the developmental disorder gene is the nearest gene to the birth weight SNP and also when examining all genes within 258kb of the SNP. This enrichment was driven by genes that cause monogenic developmental disorders with dominant modes of inheritance. We found several examples of SNPs located in the intron of one gene that mark plausible effects via different nearby genes implicated in monogenic short stature, highlighting the closest gene to the SNP not necessarily being the functionally relevant gene. This is the first application of this approach to birth weight loci, which has helped identify GWAS loci likely to have direct fetal effects on birth weight which could not previously be classified as fetal or maternal due to insufficient statistical power.

Babies born clinically Small- or Large-for-Gestational-Age (SGA or LGA; sex- and gestational age-adjusted birth weight (BW) 90th percentile, respectively), are at higher risks of complications. SGA and LGA include babies who have experienced environment-related growth-restriction or overgrowth, respectively, and babies who are heritably small or large. However, the relative proportions within each group are unclear. We assessed the extent to which common genetic variants underlying variation in birth weight influence the probability of being SGA or LGA. We calculated independent fetal and maternal genetic scores (GS) for BW in 11,951 babies and 5,182 mothers. These scores capture the direct fetal and indirect maternal (via intrauterine environment) genetic contributions to BW, respectively. We also calculated maternal fasting glucose (FG) and systolic blood pressure (SBP) GS. We tested associations between each GS and probability of SGA or LGA. For the BW GS, we used simulations to assess evidence of deviation from an expected polygenic model. Higher BW GS were strongly associated with lower odds of SGA and higher odds of LGA (ORfetal = 0.75 (0.71,0.80) and 1.32 (1.26,1.39); ORmaternal = 0.81 (0.75,0.88) and 1.17 (1.09,1.25), respectively per 1 decile higher GS). We found evidence that the smallest 3% of babies had a higher BW GS, on average, than expected from their observed birth weight (assuming an additive polygenic model: Pfetal = 0.014, Pmaternal = 0.062). Higher maternal SBP GS was associated with higher odds of SGA P = 0.005. We conclude that common genetic variants contribute to risk of SGA and LGA, but that additional factors become more important for risk of SGA in the smallest 3% of babies., Author summary Babies in the lowest or highest 10% of the population distribution of birth weight (BW) for a given gestational age are referred to as Small- or Large-for-Gestational-Age (SGA or LGA) respectively. These babies have higher risks of complications compared with babies with BW closer to the average. SGA and LGA babies may have experienced growth restriction or overgrowth, respectively, but may alternatively just be at the tail ends of the normal growth distribution. The relative proportions of normal vs. sub-optimal growth within these groups is unclear. To examine the role of common genetic variation in SGA and LGA, we tested their associations with a fetal genetic score (GS) for BW in 11,951 European-ancestry individuals. We also tested associations with maternal GS (5,182 mothers) for offspring BW, fasting glucose and systolic blood pressure, each of which influences fetal growth via the in utero environment. We found fetal and maternal GS were associated with SGA and LGA, supporting strong maternal and fetal genetic contributions to birth weight in both tails of the distribution. However, within the smallest 3% of babies, the maternal and fetal GS for BW were higher than expected, suggesting factors additional to common genetic variation are more important in determining birth weight in these very small babies.

Late diurnal preference has been linked to poorer mental health outcomes, but the understanding of the causal role of diurnal preference on mental health and wellbeing is currently limited. Late diurnal preference is often associated with circadian misalignment (a mismatch between the timing of the endogenous circadian system and behavioural rhythms), so that evening people live more frequently against their internal clock. This study aims to quantify the causal contribution of diurnal preference on mental health outcomes, including anxiety, depression and general wellbeing and test the hypothesis that more misaligned individuals have poorer mental health and wellbeing using an actigraphy-based measure of circadian misalignment. Multiple Mendelian Randomisation (MR) approaches were used to test causal pathways between diurnal preference and seven well-validated mental health and wellbeing outcomes in up to 451,025 individuals. In addition, observational analyses tested the association between a novel, objective measure of behavioural misalignment (Composite Phase Deviation, CPD) and seven mental health and wellbeing outcomes. Using genetic instruments identified in the largest GWAS for diurnal preference, we provide robust evidence that early diurnal preference is protective for depression and improves wellbeing. For example, using one-sample MR, a twofold higher genetic liability of morningness was associated with lower odds of depressive symptoms (OR: 0.92, 95% CI: 0.88, 0.97). It is possible that behavioural factors including circadian misalignment may contribute in the chronotype depression relationship, but further work is needed to confirm these findings.

In recent years, genome-wide association studies have shed light on the genetics of early growth and its links with later-life health outcomes. Large-scale datasets and meta-analyses, combined with recently developed analytical methods, have enabled dissection of the maternal and fetal genetic contributions to variation in birth weight. Additionally, longitudinal approaches have shown differences between the genetic contributions to infant, childhood and adult adiposity. In contrast, studies of adult height loci have shown strong associations with early body length and childhood height. Early growth-associated loci provide useful tools for causal analyses: Mendelian randomization (MR) studies have provided evidence that early BMI and height are causally related to a number of adult health outcomes. We advise caution in the design and interpretation of MR studies of birth weight investigating effects of fetal growth on later-life cardiometabolic disease because birth weight is only a crude indicator of fetal growth, and the choice of genetic instrument (maternal or fetal) will greatly influence the interpretation of the results. Most genetic studies of early growth have to date centered on European-ancestry participants and outcomes measured at a single time-point, so key priorities for future studies of early growth genetics are aggregation of large samples of diverse ancestries and longitudinal studies of growth trajectories.

Aims/HypothesisHigher maternal BMI during pregnancy results in higher offspring birth weight, but it is not known whether this is solely the result of adverse metabolic consequences of higher maternal adiposity, such as maternal insulin resistance and fetal exposure to higher glucose levels, or whether there is any effect of raised adiposity through non-metabolic (e.g. mechanical) factors. We aimed to use genetic variants known to predispose to higher adiposity coupled with a favourable metabolic profile, in a Mendelian Randomisation (MR) study comparing the effect of maternal “metabolically favourable adiposity” on offspring birth weight with the effect of maternal general adiposity (as indexed by BMI).MethodsTo test the causal effects of maternal metabolically favourable adiposity or general adiposity on offspring birth weight, we performed two sample MR. We used variants identified in large genetic association studies as associated with either higher adiposity and a favourable metabolic profile, or higher BMI (N = 442,278 and N = 322,154 for metabolically favourable adiposity and BMI, respectively). We then used data from the same variants in a large genetic study of maternal genotype and offspring birth weight independent of fetal genetic effects (N = 406,063 with maternal and/or fetal genotype effect estimates). We used several sensitivity analyses to test the reliability of the results. As secondary analyses, we used data from four cohorts (total N = 9,323 mother-child pairs) to test the effects of maternal metabolically favourable adiposity or BMI on maternal gestational glucose, anthropometric components of birth weight and cord-blood biomarkers.ResultsHigher maternal adiposity with a favourable metabolic profile was associated with lower offspring birth weight (−94 (95% CI: −150 to −38) grams per 1 SD (6.5%) higher maternal metabolically favourable adiposity). By contrast, higher maternal BMI was associated with higher offspring birth weight (35 (95% CI: 16 to 53) grams per 1 SD (4 kg/m2) higher maternal BMI). Sensitivity analyses were broadly consistent with the main results. There was evidence of outlier SNPs for both exposures and their removal slightly strengthened the metabolically favourable adiposity estimate and made no difference to the BMI estimate. Our secondary analyses found evidence to suggest that maternal metabolically favourable adiposity decreases pregnancy fasting glucose levels whilst maternal BMI increases them.The effects on neonatal anthropometric traits were consistent with the overall effect on birth weight, but the smaller sample sizes for these analyses meant the effects were imprecisely estimated. We also found evidence to suggest that maternal metabolically favourable adiposity decreases cord-blood leptin whilst maternal BMI increases it.Conclusions/InterpretationOur results show that higher adiposity in mothers does not necessarily lead to higher offspring birth weight. Higher maternal adiposity can lead to lower offspring birth weight if accompanied by a favourable metabolic profile.Research in ContextWhat is already known about this subject?Studies in non-pregnant people with obesity suggest many people can have a “metabolically healthy” form of obesity, but effects in pregnancy and on offspring are not known.Multiple lines of evidence show that higher maternal BMI is causally associated with higher offspring birth weight, and that this may be mediated by the fetal insulin response to higher maternal gestational glucose.Recently, genetic variants have been identified, where one allele is associated with higher adiposity but lower risk of type II diabetes and favourable metabolic profile, including lower insulin and glucose levels, so called “metabolically favourable adiposity”; the mechanism is thought to be due to greater subcutaneous adipose storage capacity that leads to higher insulin sensitivity.What is the key question?What is the effect of maternal metabolically favourable adiposity on birth weight, and how does it compare with the effect of maternal BMI on birth weight?What are the new findings?Higher maternal adiposity can lead to lower, not higher birth weight, if it is also associated with a metabolically favourable profile; this contrasts with the effect of higher maternal general adiposity (BMI), on higher birth weight.Higher maternal metabolically favourable adiposity causes lower maternal fasting plasma glucose levels, most likely due to higher insulin sensitivity; in contrast higher maternal general adiposity leads to higher maternal fasting plasma glucose levels, most likely due to lower insulin sensitivity.How might this impact on clinical practice in the foreseeable future?Identifying ways of stratifying overweight and obese pregnant women into those with and without metabolically favourable adiposity could allow for targeted management to obtain healthy fetal growth and birth weight.

Babies born clinically Small- or Large-for-Gestational-Age (SGA or LGA; sex- and gestational age-adjusted birth weight (BW) th or >90th percentile, respectively), are at higher risks of complications. SGA and LGA include babies who have experienced growth-restriction or overgrowth, respectively, and babies who are naturally small or large. However, the relative proportions within each group are unclear. We aimed to assess the extent to which the genetics of normal variation in birth weight influence the probability of SGA/LGA. We calculated independent fetal and maternal genetic scores (GS) for BW in 12,125 babies and 5,187 mothers. These scores capture the direct fetal and indirect maternal (via intrauterine environment) genetic contributions to BW, respectively. We also calculated maternal fasting glucose (FG) and systolic blood pressure (SBP) GS. We tested associations between each GS and probability of SGA or LGA. For the BW GS, we used simulations to assess evidence of deviation from an expected polygenic model.Higher BW GS were strongly associated with lower odds of SGA and higher odds of LGA (ORfetal=0.65 (0.60,0.71) and 1.47 (1.36,1.59); ORmaternal=0.80 (0.76,0.87) and 1.23 (1.15,1.31), respectively per 1 decile higher GS). Associations were in accordance with a polygenic model except in the smallest 3% of babies (Pfetal=0.0034, Pmaternal=0.023). Higher maternal GS for FG and SBP were associated with higher odds of LGA and SGA respectively (both PWe conclude that common genetic variants contribute to risk of SGA and LGA, but that additional factors become more important for risk of SGA in the smallest 3% of babies. Naturally low maternal glucose and blood pressure levels may additionally contribute to risk of SGA and LGA, respectively.Author SummaryBabies in the lowest or highest 10% of the population distribution of birth weight (BW) for a given gestational age are referred to as Small- or Large-for-Gestational-Age (SGA or LGA) respectively. These babies have higher risks of complications compared to babies with BW closer to the mean. SGA and LGA babies may have experienced growth restriction or overgrowth, respectively, but may alternatively just be at the tail ends of the normal growth distribution. The relative proportions of normal vs. sub-optimal growth within these groups is unclear. To examine the role of common genetic variation in SGA and LGA, we tested their associations with a fetal genetic score (GS) for BW in 12,125 European-ancestry individuals. We also tested associations with maternal GS (5,187 mothers) for offspring BW, fasting glucose and systolic blood pressure, each of which influences fetal growth via the in utero environment. We found all fetal and maternal GS were associated with SGA and LGA, supporting strong maternal and fetal genetic contributions to birth weight in both tails of the distribution. However, within the smallest 3% of babies, the maternal and fetal GS for BW were higher than expected, suggesting factors additional to common genetic variation are more important in determining birth weight in these very small babies.

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 × 10−4). Both maternal and paternal transmitted height haplotype scores were highly significantly associated with birth weight and length (p < 1 × 10−17). The maternal transmitted BMI scores were associated with birth weight with a significant maternal effect (p = 1.6 × 10−4). Both maternal and paternal transmitted BP scores were negatively associated with birth weight with a significant fetal effect (p = 9.4 × 10−3), whereas BP alleles were significantly associated with gestational duration and preterm birth through maternal effects (p = 3.3 × 10−2 and p = 4.5 × 10−3, respectively). The nontransmitted haplotype score for FPG was strongly associated with birth weight (p = 4.7 × 10−6); however, the glucose-increasing alleles in the fetus were associated with reduced birth weight through a fetal effect (p = 2.2 × 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 × 10−3) and a stronger fetal effect (p = 1.3 × 10−5). The paternal transmitted birth weight score was significantly associated with reduced gestational duration (p = 1.8 × 10−4) and increased maternal systolic BP during pregnancy (p = 2.2 × 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., In a Mendelian randomization and haplotype genetic score analysis, Jing Chen and colleagues investigate contributions of maternal and fetal genetic effects to pregnancy outcomes, maternal phenotypes, and offspring adult health outcomes among mother-infant pairs., Author summary Why 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.

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.

There is a robust observational relationship between lower birthweight and higher risk of cardiometabolic disease in later life. The Developmental Origins of Health and Disease (DOHaD) hypothesis posits that adverse environmental factors in utero increase future risk of cardiometabolic disease. Here, we explore if a genetic risk score (GRS) of maternal SNPs associated with offspring birthweight is also associated with offspring cardiometabolic risk factors, after controlling for offspring GRS, in up to 26,057 mother–offspring pairs (and 19,792 father–offspring pairs) from the Nord-Trøndelag Health (HUNT) Study. We find little evidence for a maternal (or paternal) genetic effect of birthweight associated variants on offspring cardiometabolic risk factors after adjusting for offspring GRS. In contrast, offspring GRS is strongly related to many cardiometabolic risk factors, even after conditioning on maternal GRS. Our results suggest that the maternal intrauterine environment, as proxied by maternal SNPs that influence offspring birthweight, is unlikely to be a major determinant of adverse cardiometabolic outcomes in population based samples of individuals., Observationally, lower birthweight is a risk factor for cardiometabolic disease. Using Mendelian Randomization, the authors investigate whether maternal genetic factors that lower offspring birthweight also increase offspring cardiometabolic risk and show that the observational correlation is unlikely to be due to the intrauterine environment.

Purpose Many women with X chromosome aneuploidy undergo lifetime clinical monitoring for possible complications. However, ascertainment of cases in the clinic may mean that the penetrance has been overestimated. Methods We characterized the prevalence and phenotypic consequences of X chromosome aneuploidy in a population of 244,848 women over 40 years of age from UK Biobank, using single-nucleotide polymorphism (SNP) array data. Results We detected 30 women with 45,X; 186 with mosaic 45,X/46,XX; and 110 with 47,XXX. The prevalence of nonmosaic 45,X (12/100,000) and 47,XXX (45/100,000) was lower than expected, but was higher for mosaic 45,X/46,XX (76/100,000). The characteristics of women with 45,X were consistent with the characteristics of a clinically recognized Turner syndrome phenotype, including short stature and primary amenorrhea. In contrast, women with mosaic 45,X/46,XX were less short, had a normal reproductive lifespan and birth rate, and no reported cardiovascular complications. The phenotype of women with 47,XXX included taller stature (5.3 cm; SD = 5.52 cm; P = 5.8 × 10−20) and earlier menopause age (5.12 years; SD = 5.1 years; P = 1.2 × 10−14). Conclusion Our results suggest that the clinical management of women with 45,X/46,XX mosaicism should be minimal, particularly those identified incidentally.