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The Barker Hypothesis posits that adverse intrauterine environments result in fetal growth restriction and increased risk of cardiometabolic disease through developmental compensations. Here we introduce a new statistical model using the genomic SEM software that is capable of simultaneously partitioning the genetic covariation between birthweight and cardiometabolic traits into maternally mediated and offspring mediated contributions. We model the covariance between birthweight and later life outcomes, such as blood pressure, non-fasting glucose, blood lipids and body mass index in the Norwegian HUNT study, consisting of 15,261 mother-eldest offspring pairs with genetic and phenotypic data. Application of this model showed some evidence for maternally mediated effects of systolic blood pressure on offspring birthweight, and pleiotropy between birthweight and non-fasting glucose mediated through the offspring genome. This underscores the importance of genetic links between birthweight and cardiometabolic phenotypes and offer alternative explanations to environmentally based hypotheses for the phenotypic correlation between these variables.

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 Coffee consumption has been associated with several adverse pregnancy outcomes, although data from randomized–controlled trials are lacking. We investigate whether there is a causal relationship between coffee consumption and miscarriage, stillbirth, birthweight, gestational age and pre-term birth using Mendelian randomization (MR). Methods A two-sample MR study was performed using summary results data from a genome-wide association meta-analysis of coffee consumption (N = 91 462) from the Coffee and Caffeine Genetics Consortium. Outcomes included self-reported miscarriage (N = 49 996 cases and 174 109 controls from a large meta-analysis); the number of stillbirths [N = 60 453 from UK Biobank (UKBB)]; gestational age and pre-term birth (N = 43 568 from the 23andMe, Inc cohort) and birthweight (N = 297 356 reporting own birthweight and N = 210 248 reporting offspring’s birthweight from UKBB and the Early Growth Genetics Consortium). Additionally, a one-sample genetic risk score (GRS) analysis of coffee consumption in UKBB women (N up to 194 196) and the Avon Longitudinal Study of Parents and Children (N up to 6845 mothers and 4510 children) and its relationship with offspring outcomes was performed. Results Both the two-sample MR and one-sample GRS analyses showed no change in risk of sporadic miscarriages, stillbirths, pre-term birth or effect on gestational age connected to coffee consumption. Although both analyses showed an association between increased coffee consumption and higher birthweight, the magnitude of the effect was inconsistent. Conclusion Our results suggest that coffee consumption during pregnancy might not itself contribute to adverse outcomes such as stillbirth, sporadic miscarriages and pre-term birth or lower gestational age or birthweight of the offspring.

Trace elements are important for human health but may exert toxic or adverse effects. Mechanisms of uptake, distribution, metabolism, and excretion are partly under genetic control but have not yet been extensively mapped. Here we report a comprehensive multi-element genome-wide association study (GWAS) of 57 essential and non-essential trace elements. We performed GWA meta-analyses of 14 trace elements in up to 6580 Scandinavian whole-blood samples, and GWASs of 43 trace elements in up to 2819 samples measured only in the Trøndelag Health Study (HUNT). We identified 11 novel genetic loci associated with blood concentrations of arsenic, cadmium, manganese, selenium, and zinc in genome-wide meta-analyses. In HUNT, several genome-wide significant loci were also indicated for other trace elements. Using two-sample Mendelian randomization, we found several indications of weak to moderate effects on health outcomes, the most precise being a weak harmful effect of increased zinc on prostate cancer. However, independent validation is needed. Our new understanding of trace element-associated genetic variants may help establish consequences of trace elements on human health.

Purpose: As favorable outcomes from malignant brain tumors remain limited by poor survival and treatment-related toxicity, novel approaches to cure are essential. Previously, we identified the cyclic AMP phosphodiesterase-4 (PDE4) inhibitor Rolipram as a potent antitumor agent. Here, we investigate the role of PDE4 in brain tumors and examine the utility of PDE4 as a therapeutic target.Experimental Design: Immunohistochemistry was used to evaluate the expression pattern of a subfamily of PDE4, PDE4A, in multiple brain tumor types. To evaluate the effect of PDE4A on growth, a brain-specific isoform, PDE4A1 was overexpressed in xenografts of Daoy medulloblastoma and U87 glioblastoma cells. To determine therapeutic potential of PDE4 inhibition, Rolipram, temozolomide, and radiation were tested alone and in combination on mice bearing intracranial U87 xenografts.Results: We found that PDE4A is expressed in medulloblastoma, glioblastoma, oligodendroglioma, ependymoma, and meningioma. Moreover, when PDE4A1 was overexpressed in Daoy medulloblastoma and U87 glioblastoma cells, in vivo doubling times were significantly shorter for PDE4A1-overexpressing xenografts compared with controls. In long-term survival and bioluminescence studies, Rolipram in combination with first-line therapy for malignant gliomas (temozolomide and conformal radiation therapy) enhanced the survival of mice bearing intracranial xenografts of U87 glioblastoma cells. Bioluminescence imaging indicated that whereas temozolomide and radiation therapy arrested intracranial tumor growth, the addition of Rolipram to this regimen resulted in tumor regression.Conclusions: This study shows that PDE4 is widely expressed in brain tumors and promotes their growth and that inhibition with Rolipram overcomes tumor resistance and mediates tumor regression.

Supplementary Figures S1-S3 from Targeted Inhibition of Cyclic AMP Phosphodiesterase-4 Promotes Brain Tumor Regression

Supplementary Figure Legends 1-4 from Cyclic AMP Suppression Is Sufficient to Induce Gliomagenesis in a Mouse Model of Neurofibromatosis-1

Supplementary Figure 2 from Cyclic AMP Suppression Is Sufficient to Induce Gliomagenesis in a Mouse Model of Neurofibromatosis-1

Supplemental Table 2: List of SNPs analyzed.

Supplementary Figure 2 from Spatiotemporal Differences in CXCL12 Expression and Cyclic AMP Underlie the Unique Pattern of Optic Glioma Growth in Neurofibromatosis Type 1

Supplementary Figure 1 from Cyclic AMP Suppression Is Sufficient to Induce Gliomagenesis in a Mouse Model of Neurofibromatosis-1

The chemokine receptor CXCR4 is expressed in many cancers where it may regulate tumor cell growth and migration. The role of CXCR4 in cancer will depend on it being in an activated, signaling state. To better define the significance of CXCR4 expression in cancer, we developed an antibody that can distinguish CXCR4 phosphorylated on serine 339, a residue previously identified as a site for ligand-induced phosphorylation. With this antibody, we investigated the mechanisms of CXCR4 phosphorylation and evaluated the phosphorylation status of CXCR4 in human astrocytomas. In vitro, phosphorylation of serine 339 occurred in response to CXCL12 or epidermal growth factor (EGF) treatment and was increased by protein kinase C activation. In all grades of astrocytomas, CXCR4 was expressed in tumor cells and some endothelial cells, whereas CXCL12 was present in endothelial cells and infiltrating microglia. We found that CXCR4 phosphorylated on serine 339 was present in tumor cells and vascular endothelial cells in all grades of astrocytoma. These data indicate that CXCR4 is expressed and activated in astrocytomas and that phosphorylation of CXCR4 can occur through ligand activation or transactivation via the EGF receptor. These studies extend the potential roles of CXCR4 in cancer to include functions associated with benign (grade 1) tumors. The ability to distinguish phosphorylated CXCR4 will be invaluable for the continued analysis of the role of CXCR4 in cancer and the development of CXCR4 antagonist therapy for patients suffering with primary tumors of the brain and other sites. (Cancer Res 2005; 65(24): 11392-9)

Supplementary Figure 1 from Widespread CXCR4 Activation in Astrocytomas Revealed by Phospho-CXCR4-Specific Antibodies

Supplemental Table 3. Primer sequences.

Supplementary Figure 1 from Spatiotemporal Differences in CXCL12 Expression and Cyclic AMP Underlie the Unique Pattern of Optic Glioma Growth in Neurofibromatosis Type 1

Supplementary Figure 4 from Cyclic AMP Suppression Is Sufficient to Induce Gliomagenesis in a Mouse Model of Neurofibromatosis-1

Current models of oncogenesis incorporate the contributions of chronic inflammation and aging to the patterns of tumor formation. These oncogenic pathways, involving leukocytes and fibroblasts, are not readily applicable to brain tumors (glioma), and other mechanisms must account for microenvironmental influences on central nervous system tumorigenesis. Previous studies from our laboratories have used neurofibromatosis-1 (NF1) genetically engineered mouse (GEM) models to understand the spatial restriction of glioma formation to the optic pathway of young children. Based on our initial findings, we hypothesize that brain region–specific differences in cAMP levels account for the pattern of NF1 gliomagenesis. To provide evidence that low levels of cAMP promote glioma formation in NF1, we generated foci of decreased cAMP in brain regions where gliomas rarely form in children with NF1. Focal cAMP reduction was achieved by forced expression of phosphodiesterase 4A1 (PDE4A1) in the cortex of Nf1 GEM strains. Ectopic PDE4A1 expression produced hypercellular lesions with features of human NF1-associated glioma. Conversely, pharmacologic elevation of cAMP with the PDE4 inhibitor rolipram dramatically inhibited optic glioma growth and tumor size in Nf1 GEM in vivo. Together, these results indicate that low levels of cAMP in a susceptible Nf1 mouse strain are sufficient to promote gliomagenesis, and justify the implementation of cAMP-based stroma-targeted therapies for glioma. Cancer Res; 70(14); 5717–27. ©2010 AACR.

Supplemental Table 1: Specimen Characteristics.

Supplementary Legends 1-2 from Spatiotemporal Differences in CXCL12 Expression and Cyclic AMP Underlie the Unique Pattern of Optic Glioma Growth in Neurofibromatosis Type 1

BackgroundThe intergenerational transmission of obesity-related traits could propagate an accelerating cycle of obesity, if parental adiposity causally influences offspring adiposity via intrauterine or periconceptional mechanisms. We aimed to establish whether associations between parental peri-pregnancy body mass index (BMI) and offspring birth weight (BW), BMI until 8 years and 8-year eating behaviour are due to genetic confounding.MethodsWe used data from the Norwegian Mother, Father and Child Cohort Study and the Medical Birth Registry of Norway. We compared the strength of the associations of maternal versus paternal BMI with offspring outcomes, and used an extended children of twins structural equation model (SEM) to quantify the extent to which associations were due to genetic confounding (n = 17001 to 85866 children).FindingsMaternal BMI was more strongly associated than paternal BMI with offspring BW, but the maternal-paternal difference decreased for offspring BMI after birth. Greater parental BMI was associated with obesity-related offspring eating behaviours. SEM results indicated that genetic confounding did not explain the association between parental BMI and offspring BW, but explained the majority of the association with offspring BMI from 6 months onwards. For 8-year BMI, genetic confounding explained 79% (95% CI: 62%, 95%) of the covariance with maternal BMI and 94% (95% CI: 72%, 113%) of the covariance with paternal BMI.InterpretationWe found strong evidence that parent-child BMI associations are primarily due to genetic confounding, arguing against a strong causal effect of maternal or paternal adiposity on childhood adiposity via intrauterine or periconceptional mechanisms.

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.

BackgroundFixed-effect meta-analysis has been used to summarize genetic effects on a phenotype across multiple Genome-Wide Association Studies (GWAS) assuming a common underlying genetic effect. Genetic effects may vary with age, therefore meta-analysing GWAS of age-diverse samples could be misleading. Meta-regression allows adjustment for study specific characteristics and models heterogeneity between studies. The aim of this study was to explore the use of meta-analysis and meta-regression for estimating age-varying genetic effects on phenotypes.MethodsWith simulations we compared the performance of meta-regression to fixed-effect and random -effects meta-analyses in estimating (i) main genetic effects and (ii) age-varying genetic effects (SNP by age interactions) from multiple GWAS studies under a range of scenarios. We applied meta-regression on publicly available summary data to estimate the main and age-varying genetic effects of theFTOSNP rs9939609 on Body Mass Index (BMI).ResultsFixed-effect and random-effects meta-analyses accurately estimated genetic effects when these did not change with age. Meta-regression accurately estimated both the main genetic effects and the age-varying genetic effects. When the number of studies or the age-diversity between studies was low, meta-regression had limited power. In the applied example, each additional minor allele (A) of rs9939609 was inversely associated with BMI at ages 0 to 3, and positively associated at ages 5.5 to 13. This is similar to the association that has been previously reported by a study that used individual participant data.ConclusionsGWAS using summary statistics from age-diverse samples should consider using meta-regression to explore age-varying genetic effects.KEY MESSAGESMeta-analysis has been used to summarize genetic effects on a phenotype across multiple Genome-Wide Association Studies (GWAS) assuming a common underlying genetic effect for all studies. However, genetic effects may vary with age, therefore meta-analysing GWAS of age-diverse samples could produce misleading results.Meta-regression could be used to relate observed between-study heterogeneity to study characteristics such as age. Therefore, meta-regression could be used to combine summary level GWAS data to provide evidence for any age-varying genetic effects.This simulation study shows that when genetic effects vary with age, meta-regression provides unbiased estimates of main and age-varying genetic effects. The precision of the estimates depends on the number of studies included, and the diversity in age between them.The applied example using publicly available summary data, supported the simulation study.By applying meta-regression, we observed a previously reported age-varying association between each additional minor allele (A) of rs9939609 and BMI; an inverse at ages 0 to 3 and a positive association at ages 5.5 to 13.Similar association has been previously reported by a study that used individual participant data.

Birth weight (BW), as a proxy for intrauterine growth, is influenced by both fetal and maternal genetic factors. Single nucleotide polymorphisms in the human leukocyte antigen (HLA) region in both maternal and fetal genomes have been robustly associated with BW in previous genetic association studies suggesting the involvement of classical HLA alleles in BW etiology. However, no study to date has partitioned the association between BW and classical HLA alleles into maternal and fetal components. We used structural equation modelling (SEM) to estimate the indirect maternal (i.e. via the intrauterine environment) and direct fetal effects of classical HLA alleles on BW. Our SEM leverages the data structure of the UK Biobank (UKB), which includes participants’ own BW and/or the BW of their firstborn child (in the case of UKB females). We show via simulation that our model yields asymptotically unbiased estimates of the maternal and fetal allelic effects on BW and appropriate type I error rates, in contrast to simple regression models that estimate unconditioned maternal and fetal effects. Asymptotic power calculations show that we have sufficient power to detect moderate-sized maternal or fetal allelic effects (standardized effect size ≥ 0.01) of common HLA alleles on BW in the UKB. Applying our SEM to imputed classical HLA alleles and own and offspring BW of ∼270,000 participants from the UKB replicated the previously reported association at the HLA-C locus (C*04:01, P = 2.13×10−7, C*05:01, P= 6.91×10−5, C*03:03, P= 4.53×10−3, respectively) and revealed strong evidence for maternal (HLA-A*03:01, P = 7.90×10−8; B*35:01, P = 7.78×10−5; B*39:06, P = 8.49 ×10−5) and fetal allelic effects (HLA-B*39:06, P = 4.03×10−4) of non-HLA-C alleles on BW. These novel allelic associations between BW and classical HLA alleles provide insight into the immunogenetics of fetal growth in utero.

Males exhibit higher incidence and worse prognosis for the majority of cancers, including glioblastoma (GBM). Disparate survival may be related to sex-biased responses to treatment, including radiation. Using a mouse model of GBM, we show that female cells are more sensitive to radiation, and that senescence represents a major component of the radiation therapeutic response in both sexes. Correlation analyses revealed that the CDK inhibitor p21 and irradiation induced senescence were differentially regulated between male and female cells. Indeed, female cellular senescence was more sensitive to changes in p21 levels, a finding that was observed in wildtype and transformed murine astrocytes, as well as patient-derived GBM cell lines. Using a novel Four Core Genotypes model of GBM, we further show that sex differences in p21-induced senescence are patterned during early development by gonadal sex. These data provide a rationale for the further study of sex differences in radiation response and how senescence might be enhanced for radiation sensitization. The determination that p21 and gonadal sex are required for sex differences in radiation response will serve as a foundation for these future mechanistic studies.

Background Observational epidemiological studies suggest a link between several factors related to ovulation and reproductive function and endometrial cancer (EC) risk; however, it is not clear whether these relationships are causal, and whether the risk factors act independently of each other. The aim of this study was to investigate putative causal relationships between the number of live births, age at last live birth, and years ovulating and EC risk. Methods We conducted a series of observational analyses to investigate various risk factors and EC risk in the UK Biobank (UKBB). Additionally, multivariate analysis was performed to elucidate the relationship between the number of live births, age at last live birth, and years ovulating and other related factors such as age at natural menopause, age at menarche, and body mass index (BMI). Secondly, we used Mendelian randomization (MR) to assess if these observed relationships were causal. Genome-wide significant single nucleotide polymorphisms (SNPs) were extracted from previous studies of woman’s number of live births, age at menopause and menarche, and BMI. We conducted a genome-wide association analysis using the UKBB to identify SNPs associated with years ovulating, years using the contraceptive pill, and age at last live birth. Results We found evidence for a causal effect of the number of live births (inverse variance weighted (IVW) odds ratio (OR): 0.537, p = 0.006), the number of years ovulating (IVW OR: 1.051, p = 0.014), in addition to the known risk factors BMI, age at menarche, and age at menopause on EC risk in the univariate MR analyses. Due to the close relationships between these factors, we followed up with multivariable MR (MVMR) analysis. Results from the MVMR analysis showed that number of live births had a causal effect on EC risk (OR: 0.783, p = 0.036) independent of BMI, age at menarche and age at menopause. Conclusions MVMR analysis showed that the number of live births causally reduced the risk of EC.

Several epidemiological studies have reported a relationship between statin treatment and increased bone mineral density (BMD) and reduced fracture risk, but the mechanism underlying the purported relationship is unclear. We used Mendelian randomization (MR) to assess whether this relationship is explained by a specific effect in response to statin use or by a general effect of lipid lowering. We utilized 400 single-nucleotide polymorphisms (SNPs) robustly associated with plasma lipid levels as exposure. The outcome results were obtained from a heel estimated BMD (eBMD) genomewide association study (GWAS) from the UK Biobank and dual-energy X-ray absorptiometry (DXA) BMD at four body sites and fracture GWAS from the GEFOS consortium. We performed univariate and multivariable MR analyses of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglyceride levels on BMD and fracture. Univariate MR analyses suggested a causal effect of LDL-C on eBMD (β = −0.06; standard deviation change in eBMD per standard deviation change in LDL-C, 95% confidence interval [CI] = –0.08 to −0.04; p = 4 × 10), total body BMD (β = −0.05, 95% CI = –0.08 to −0.01, p = 6 × 10) and potentially on lumbar spine BMD. Multivariable MR suggested that the effects of LDL-C on eBMD and total body BMD were independent of HDL-C and triglycerides. Sensitivity MR analyses suggested that the LDL-C results were robust to pleiotropy. MR analyses of LDL-C restricted to SNPs in the HMGCR region showed similar effects on eBMD (β = −0.083; −0.132 to −0.034; p = 0.001) to those excluding these SNPs (β = −0.063; −0.090 to −0.036; p = 8 × 10). Bidirectional MR analyses provided some evidence for a causal effect of eBMD on plasma LDL-C levels. Our results suggest that effects of statins on eBMD and total body BMD are at least partly due to their LDL-C lowering effect. Further studies are required to examine the potential role of modifying plasma lipid levels in treating osteoporosis.

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.

In cancer, missense mutations in the DNA-binding domain of TP53 are common. They abrogate canonical p53 activity and frequently confer gain-of-oncogenic function (GOF) through localization of transcriptionally active mutant p53 to noncanonical genes. We found that several recurring p53 mutations exhibit a sex difference in frequency in patients with glioblastoma (GBM). In vitro and in vivo analysis of three mutations, p53R172H, p53Y202C, and p53Y217C, revealed unique interactions between cellular sex and p53 GOF mutations that determined each mutation's ability to transform male versus female primary mouse astrocytes. These phenotypic differences were correlated with sex- and p53 mutation–specific patterns of genomic localization to the transcriptional start sites of upregulated genes belonging to core cancer pathways. The promoter regions of these genes exhibited a sex difference in enrichment for different transcription factor DNA-binding motifs. Together, our data establish a novel mechanism for sex-specific mutant p53 GOF activity in GBM with implications for all cancer. Significance: Sex differences in cancer, including glioblastoma, have been observed in both incidence and outcome. We reveal that TP53, the most commonly mutated gene in cancer, contributes to sex differences through differential GOF activity. This discovery has critical implications for our understanding of p53 mutations and the importance of sex as a biological variable.

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.

Supplemental Digital Content is available in the text., Observational epidemiological studies have reported that higher maternal blood pressure (BP) during pregnancy is associated with increased future risk of offspring cardiometabolic disease. However, it is unclear whether this association represents a causal relationship through intrauterine mechanisms. We used a Mendelian randomization (MR) framework to examine the relationship between unweighted maternal genetic scores for systolic BP and diastolic BP and a range of cardiometabolic risk factors in the offspring of up to 29 708 genotyped mother-offspring pairs from the UKB study (UK Biobank) and the HUNT study (Trøndelag Health). We conducted similar analyses in up to 21 423 father-offspring pairs from the same cohorts. We confirmed that the BP-associated genetic variants from the general population sample also had similar effects on maternal BP during pregnancy in independent cohorts. We did not detect any association between maternal (or paternal) unweighted genetic scores and cardiometabolic offspring outcomes in the meta-analysis of UKB and HUNT after adjusting for offspring genotypes at the same loci. We find little evidence to support the notion that maternal BP is a major causal risk factor for adverse offspring cardiometabolic outcomes in later life.

Estimation of direct and indirect (i.e. parental and/or sibling) genetic effects on phenotypes is becoming increasingly important. We compare several multivariate methods that utilize summary results statistics from genome-wide association studies to determine how well they estimate direct and indirect genetic effects. Using data from the UK Biobank, we contrast point estimates and standard errors at individual loci compared to those obtained using individual level data. We show that Genomic structural equation modelling (SEM) outperforms the other methods in accurately estimating conditional genetic effects and their standard errors. We apply Genomic SEM to fertility data in the UK Biobank and partition the genetic effect into female and male fertility and a sibling specific effect. We identify a novel locus for fertility and genetic correlations between fertility and educational attainment, risk taking behaviour, autism and subjective well-being. We recommend Genomic SEM be used to partition genetic effects into direct and indirect components when using summary results from genome-wide association studies., Estimating direct and indirect effects of genotypes on phenotypes is important for genetic analyses such as Mendelian randomization. Here the authors compare five different methods to estimate direct and indirect genetic effects using summary results statistics that account for sample overlap.

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.

Significant interindividual variation exists among “normal” human humoral immune responses to viral infection. However, although the genetic etiology of immunologic extremes such as primary immunodeficiency has been well characterized, little is known about the genetics of normal interindividual variation in immune response. The classical twin design, which compares the phenotypic similarity between monozygotic (MZ) twin pairs and dizygotic (DZ) twin pairs, can be used to estimate the proportion of interindividual variation due to genetic factors. For example, the classical twin design has been used to demonstrate that antibody response to vaccination against certain pathogens is likely to be influenced by genetic factors.1 The present study used twin and sibling data to estimate the genetic and environmental determinants of antibody titers to 6 common human viruses: EBV, Coxsackie B virus (CVB), parvovirus B-19 (PV-B19), herpes simplex virus 1 (HSV-1), human herpes virus 6 (HHV-6), and cytomegalovirus (CMV). Although these viruses usually cause relatively mild symptoms or are asymptomatic, many are also observationally associated with the development of more severe diseases, including autoimmune diseases such as multiple sclerosis, rheumatoid arthritis, type 1 diabetes, and systemic lupus erythematosus.2

The tumor suppressor TP53 is the most frequently mutated gene in cancer. Most TP53 mutations are missense mutations in the DNA-binding domain, which in addition to loss of canonical p53 activity, frequently confer gain-of-function (GOF) aberrant transcriptional activity through mutant p53 localization to non-canonical genes. GOF phenotypes differ by mutation and cell identity and are reported to include increased proliferation, migration, metabolic reprogramming, and therapy resistance. We found that several recurring p53 mutations exhibit a sex-bias in patients with glioblastoma (GBM). In vitro and in vivo analysis of three mutations, p53R172H, p53Y202C, and p53Y217C revealed sex differences in each mutation’s ability to transform primary mouse astrocytes. p53R172H exhibited a far greater ability to transform female astrocytes than males, p53Y202C transformed both male and female astrocytes with a small male bias, and p53Y217C only exhibited GOF transformation effects in male astrocytes. These phenotypic differences reflect an interaction between sex and GOF mutation to drive unique gene expression patterns in cancer pathways. We found that mutant p53 exhibits sex and mutation specific aberrant genomic localization to the transcriptional start sites of upregulated genes, whose promoter regions were enriched for different sets of transcription factor DNA-binding motifs. Together, our data establish a novel paradigm for sex specific mutant p53 GOF activity in GBM with implications for all cancer.

Handedness, a consistent asymmetry in skill or use of the hands, has been studied extensively because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and 32 studies from the International Handedness Consortium, we conducted the world’s largest genome-wide association study of handedness (1,534,836 right-handed, 194,198 (11.0%) left-handed and 37,637 (2.1%) ambidextrous individuals). We found 41 genetic loci associated with left-handedness and seven associated with ambidexterity at genome-wide levels of significance (P < 5×10−8). Tissue enrichment analysis implicated the central nervous system and brain tissues including the hippocampus and cerebrum in the etiology of left-handedness. Pathways including regulation of microtubules, neurogenesis, axonogenesis and hippocampus morphology were also highlighted. We found suggestive positive genetic correlations between being left-handed and some neuropsychiatric traits including schizophrenia and bipolar disorder. SNP heritability analyses indicated that additive genetic effects of genotyped variants explained 5.9% (95% CI = 5.8% – 6.0%) of the underlying liability of being left-handed, while the narrow sense heritability was estimated at 12% (95% CI = 7.2% – 17.7%). Further, we show that genetic correlation between left-handedness and ambidexterity is low (rg = 0.26; 95% CI = 0.08 – 0.43) implying that these traits are largely influenced by different genetic mechanisms. In conclusion, our findings suggest that handedness, like many other complex traits is highly polygenic, and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders that has been observed in multiple observational studies.

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.

Recent studies have used Mendelian randomization (MR) to investigate the observational association between low birth weight (BW) and increased risk of cardiometabolic outcomes, specifically cardiovascular disease, glycemic traits, and type 2 diabetes (T2D), and inform on the validity of the Barker hypothesis. We used simulations to assess the validity of these previous MR studies, and to determine whether a better formulated model can be used in this context. Genetic and phenotypic data were simulated under a model of no direct causal effect of offspring BW on cardiometabolic outcomes and no effect of maternal genotype on offspring cardiometabolic risk through intrauterine mechanisms; where the observational relationship between BW and cardiometabolic risk was driven entirely by horizontal genetic pleiotropy in the offspring (i.e. offspring genetic variants affecting both BW and cardiometabolic disease simultaneously rather than a mechanism consistent with the Barker hypothesis). We investigated the performance of four commonly used MR analysis methods (weighted allele score MR (WAS-MR), inverse variance weighted MR (IVW-MR), weighted median MR (WM-MR), and MR-Egger) and a new approach, which tests the association between maternal genotypes related to offspring BW and offspring cardiometabolic risk after conditioning on offspring genotype at the same loci. We caution against using traditional MR analyses, which do not take into account the relationship between maternal and offspring genotypes, to assess the validity of the Barker hypothesis, as results are biased in favor of a causal relationship. In contrast, we recommend the aforementioned conditional analysis framework utilizing maternal and offspring genotypes as a valid test of not only the Barker hypothesis, but also to investigate hypotheses relating to the Developmental Origins of Health and Disease more broadly.