Biology subjects

Warrington, N. M.

Publications and source records attributed to Warrington, N. M..

9 recordsLinked to original sources

bioRxiv2025

EGR1 drives sex-differences in glioblastoma tumorigenicity

Although progress has been made in treating glioblastoma (GBM), with fewer than 5% of patients surviving more than 5 years after diagnosis. For reasons that are not well understood, females are roughly 60% as likely as males to develop GBM, and female patients consistently respond better to treatment than do males. Understanding the molecular etiology of these sex differences in tumor progression and resiliency to treatment could reveal potent new therapeutic targets, ultimately improving survival of both male and female GBM patients. Here we show that the transcription factor Egr1 is a primary mediator of sex differences in multiple GBM tumorigenic phenotypes. In multivariate analysis, high levels of EGR1 expression are correlated with shortened survival for male GBM patients only. To investigate the molecular mechanisms underlying this sex difference, we performed a genomic analysis in our established ex vivo murine model of sex differences, which showed that the transcription factors Egr1 and Klf5 preferentially recruit the transcriptional activator Brd4 to enhancers in male cells relative to female cells, explaining a previously made observation that Brd4 inhibitors reverse sex differences in GBM. Next, using murine and human primary GBM cells, we demonstrated that the small molecule compound SR18662, which downregulates Egr1 and its downstream target Klf5, abrogates GBM growth, migration, invasion, clonogenicity, and response to radiation in a sex-biased fashion. Finally, we knocked down Egr1 and Klf5 via CRISPRi in both untreated and SR18662-treated GBM cells to reveal the sex-biased anti-tumorigenic effects of SR18662 were largely due to Egr1 downregulation, independent of Klf5 downregulation. This result was replicated in vivo. Our results strongly indicate that an Egr1 regulon is a key determinant of sex differences in GBM. As EGR1 is implicated in the cancer biology of many cancers that also display sex differences in incidence and treatment response, our results are likely to be broadly applicable in oncology.

cancer biology↗

bioRxiv2022

Partitioning genetic effects on birth weight at classical human leukocyte antigen loci into indirect maternal and direct fetal components using structural equation modelling

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 = 2.13x10-7, C*05:01, P= 6.91x10-5, C*03:03, P= 4.53x10-3, respectively) and revealed strong evidence for maternal (HLA-A*03:01, P = 7.90x10-8; B*35:01, P = 7.78x10-5; B*39:06, P = 8.49 x10-5) and fetal allelic effects (HLA-B*39:06, P = 4.03x10-4) 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.

genetics↗

bioRxiv2020

Estimating direct and indirect genetic effects on offspring phenotypes using genome-wide summary results data: a comparison of multivariate methods

Estimation of the direct genetic effect of an individuals own genotype on their phenotype, independent of any contaminating indirect parental genetic effects is becoming increasingly important. These conditional estimates are of interest in their own right, but are also useful for downstream analyses such as intergenerational Mendelian randomization. We compare several available multivariate methods that utilize summary results statistics from genome-wide association studies to determine how well they estimate conditional direct and indirect genetic effects, while accounting for sample overlap. Using robustly associated birth weight variants and data from the UK Biobank, we contrasted the point estimates and their standard errors at each of the individual loci compared to those obtained using individual level genotype data, in addition to comparing the computational time, inflation of the test statistics and number of genome-wide significant SNPs identified by each of the methods. We show that Genomic SEM outperforms the other methods in accurately estimating conditional genetic effects and their standard errors. We subsequently applied Genomic SEM to fertility data in the UK Biobank and partitioned the genetic effect into female and male fertility in addition to a sibling specific effect. This analysis identified one novel locus for fertility and replicated seven previously identified loci. We also identified genetic correlations between fertility and educational attainment, risk taking behaviour, autism and subjective well-being. We therefore recommend Genomic SEM to be used to partition genetic effects across the genome into direct and indirect components.

genetics↗

bioRxiv2020

Fetal alleles predisposing to metabolically favourable adiposity are associated with higher birth weight

BackgroundHigher birth weight is associated with higher adult body mass index (BMI). If genetic variants can be identified with alleles that predispose to both greater fetal growth and to greater adult adiposity, such shared genetic effects might indicate biological processes important in the early patterning of adiposity. However, variants identified in genome-wide association studies of adult BMI have overall been only weakly associated with birth weight. Genetic variants have recently been identified where one allele is associated with higher adult body fat percentage, but lower risk of metabolic disease, likely due to a favourable body fat distribution. The effect of these adult metabolically favourable adiposity alleles on an individuals own birth weight is unknown. AimWe aimed to test the effect on birth weight of a fetal genetic predisposition to higher metabolically favourable adult adiposity and to compare this with the effects of a fetal genetic predisposition to higher adult BMI. We also aimed to examine the effects of a genetic predisposition to higher metabolically favourable adult adiposity or BMI on other birth anthropometric traits (length, ponderal index, head circumference and skinfold thickness) and on cord-blood insulin, leptin and adiponectin. MethodsWe used published GWAS data from up to 406,063 individuals to estimate the fetal effects on birth weight of alleles that are robustly associated with higher metabolically favourable adult adiposity or BMI. We additionally used 9,350 mother-child pairs from four cohorts to test the effects of the same alleles on other birth anthropometric traits and cord-blood markers. In all analyses, we adjusted for potential confounding due to the maternal genotype. We used inverse-variance weighted meta-analyses to combine summary data across SNPs. ResultsFetal genetic predisposition to higher metabolically favourable adult adiposity was associated with higher birth weight (10 grams (95% CI: 7 to 13) higher mean birth weight per 1 SD pooled "genetic score"). Fetal genetic predisposition to higher adult BMI was also associated with higher birth weight, but with a smaller magnitude of effect (4 grams (95% CI: 0 to 8) higher mean birth weight per 1 SD pooled "genetic score") and with higher heterogeneity across SNPs. Effects on other birth anthropometric outcomes were consistent with the effect on birth weight but with wider confidence intervals. There was no strong evidence for an effect on cord-blood markers. ConclusionsSome genetic variants previously linked to adult adiposity influence birth weight. Alleles that predispose to higher metabolically favourable adult adiposity collectively have a stronger effect on birth weight than those predisposing to higher BMI. This suggests that the early accumulation of a metabolically favourable fat distribution might underlie part of the observed association between higher birth weight and higher adult BMI. Larger samples are needed to clarify the effects on other birth anthropometric measures and cord-blood markers.

genetics↗

bioRxiv2020

Investigating the causal effect of maternal vitamin B12 and folate levels on offspring birthweight

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. We performed two-sample Mendelian Randomization (MR) using summary data on associations between genotype-B12 (10 genetic variants) or genotype-folate (4 genetic variants) levels from a genome-wide association study of 45,576 individuals (sample 1) and maternal-specific genetic effects on offspring birthweight from the latest EGG consortium meta-analysis with 297,356 individuals reporting their own birthweight and 210,248 women reporting their offsprings birthweight (sample 2). To investigate the effect of offsprings own B12 or folate levels on their own birthweight, we performed two-sample MR using the fetal-specific genetic effects from the latest EGG consortium meta-analysis. We used the inverse variance weighted method, and sensitivity analyses to account for pleiotropy, in addition to sensitivity analyses excluding a potentially pleiotropic variant in the FUT2 gene for B12. We did not find evidence for a causal effect of maternal B12 on offspring birthweight, nor evidence for an effect of offspring B12 on their own birthweight using the fetal-specific genetic effect. The results were consistent across the different methods and in sensitivity analyses excluding the FUT2 variant. We found a positive effect of maternal folate on offspring birthweight (0.146 [0.065, 0.227], which corresponds to an increase in birthweight of 71g per 1SD higher folate). We found some evidence for a small inverse effect of fetal folate on their own birthweight (-0.051 [-0.100, -0.003]). In conclusion, our results are consistent with evidence from randomized controlled trials that increased maternal folate levels increase offspring birthweight. We did not find evidence for a causal effect of B12 on offspring birthweight, suggesting previous observational studies may have been due to confounding.

genetics↗

bioRxiv2018

Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors

Birth weight (BW) variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. These associations have been proposed to reflect the lifelong consequences of an adverse intrauterine environment. In earlier work, we demonstrated that much of the negative correlation between BW and adult cardio-metabolic traits could instead be attributable to shared genetic effects. However, that work and other previous studies did not systematically distinguish the direct effects of an individuals own genotype on BW and subsequent disease risk from indirect effects of their mothers correlated genotype, mediated by the intrauterine environment. Here, we describe expanded genome-wide association analyses of own BW (n=321,223) and offspring BW (n=230,069 mothers), which identified 278 independent association signals influencing BW (214 novel). We used structural equation modelling to decompose the contributions of direct fetal and indirect maternal genetic influences on BW, implicating fetal- and maternal-specific mechanisms. We used Mendelian randomization to explore the causal relationships between factors influencing BW through fetal or maternal routes, for example, glycemic traits and blood pressure. Direct fetal genotype effects dominate the shared genetic contribution to the association between lower BW and higher type 2 diabetes risk, whereas the relationship between lower BW and higher later blood pressure (BP) is driven by a combination of indirect maternal and direct fetal genetic effects: indirect effects of maternal BP-raising genotypes act to reduce offspring BW, but only direct fetal genotype effects (once inherited) increase the offsprings later BP. Instrumental variable analysis using maternal BW-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring BP. In successfully separating fetal from maternal genetic effects, this work represents an important advance in genetic studies of perinatal outcomes, and shows that the association between lower BW and higher adult BP is attributable to genetic effects, and not to intrauterine programming.

genetics↗

bioRxiv2017

Clinically Important sex differences in GBM biology revealed by analysis of male and female imaging, transcriptome and survival data

Sex differences in the incidence and outcome of human disease are broadly recognized but in most cases not adequately understood to enable sex-specific approaches to treatment. Glioblastoma (GBM), the most common malignant brain tumor, provides a case in point. Despite well-established differences in incidence, and emerging indications of differences in outcome, there are few insights that distinguish male and female GBM at the molecular level, or allow specific targeting of these biological differences. Here, using a quantitative imaging-based measure of response, we found that temozolomide chemotherapy is more effective in female compared to male GBM patients. We then applied a novel computational algorithm to linked GBM transcriptome and outcome data, and identified novel sex-specific molecular subtypes of GBM in which cell cycle and integrin signaling were identified as the critical determinants of survival for male and female patients, respectively. The clinical utility of cell cycle and integrin signaling pathway signatures was further established through correlations between gene expression and in vitro chemotherapy sensitivity in a panel of male and female patient-derived GBM cell lines. Together these results suggest that greater precision in GBM molecular subtyping can be achieved through sex-specific analyses, and that improved outcome for all patients might be accomplished via tailoring treatment to sex differences in molecular mechanisms.\n\nOne Sentence SummaryMale and female glioblastoma are biologically distinct and maximal chances for cure may require sex-specific approaches to treatment.

cancer biology↗

bioRxiv2017

Effect modification of FADS2 polymorphisms on the association between breastfeeding and intelligence: results from a collaborative meta-analysis

BackgroundAccumulating evidence suggests that breastfeeding benefits the childrens intelligence. Long-chain polyunsaturated fatty acids (LC-PUFAs) present in breast milk may explain part of this association. Under a nutritional adequacy hypothesis, an interaction between breastfeeding and genetic variants associated with endogenous LC-PUFAs synthesis might be expected. However, the literature on this topic is controversial.\n\nMethods and FindingsWe investigated this GenexEnvironment interaction in a de novo meta-analysis involving >12,000 individuals in the primary analysis, and >45,000 individuals in a secondary analysis using relaxed inclusion criteria. Our primary analysis used ever breastfeeding, FADS2 polymorphisms rs174575 and rs1535 coded assuming a recessive effect of the G allele, and intelligence quotient (IQ) in Z scores. Using random effects meta-analysis, ever breastfeeding was associated with 0.17 (95% CI: 0.03; 0.32) higher Z scores in IQ, or about 2.1 points. There was no strong evidence of interaction, with pooled covariate-adjusted interaction coefficients (i.e., difference between genetic groups of the difference in IQZ scores comparing ever with never breastfed individuals) of 0.12 (95% CI: -0.19; 0.43) and 0.06 (95% CI: -0.16; 0.27) for the rs174575 and rs1535 variants, respectively. Secondary analyses corroborated these results. In studies with >5.85 and <5.85 months of breastfeeding duration, pooled estimates for the rs174575 variant were 0.50 (95% CI: -0.06; 1.06) and 0.14 (95% CI: -0.10; 0.38), respectively, and 0.27 (95% CI: -0.28; 0.82) and -0.01 (95% CI: -0.19; 0.16) for the rs1535 variant. However, between-group comparisons were underpowered.\n\nConclusionsOur findings do not support an interaction between ever breastfeeding and FADS2 polymorphisms. However, our subgroup analysis raises the possibility that breastfeeding supplies LC-PUFAs requirements for cognitive development (if such threshold exists) if it lasts for some (currently unknown) time. Future studies in large individual-level datasets would allow properly powered subgroup analyses and would improve our understanding on the role of breastfeeding duration in the breastfeedingxFADS2 interaction.

epidemiology↗

bioRxiv2017

Genetic architecture of early childhood growth phenotypes gives insights into their link with later obesity

Early childhood growth patterns are associated with adult metabolic health, but the underlying mechanisms are unclear. We performed genome-wide meta-analyses and follow-up in up to 22,769 European children for six early growth phenotypes derived from longitudinal data: peak height and weight velocities, age and body mass index (BMI) at adiposity peak (AP ~9 months) and rebound (AR ~5-6 years). We identified four associated loci (P< 5x10-8): LEPR/LEPROT with BMI at AP, FTO and TFAP2B with Age at AR and GNPDA2 with BMI at AR. The observed AR-associated SNPs at FTO, TFAP2B and GNPDA2 represent known adult BMI-associated variants. The common BMI at AP associated variant at LEPR/LEPROT was not associated with adult BMI but was associated with LEPROT gene expression levels, especially in subcutaneous fat (P<2x10-51). We identify strong positive genetic correlations between early growth and later adiposity traits, and analysis of the full discovery stage results for Age at AR revealed enrichment for insulin-like growth factor 1 (IGF-1) signaling and apolipoprotein pathways. This genome-wide association study suggests mechanistic links between early childhood growth and adiposity in later childhood and adulthood, highlighting these early growth phenotypes as potential targets for the prevention of obesity.

genomics↗