Targeting brain tumor cAMP: The case for sex-specific therapeutics

A relationship between cyclic adenosine 3’, 5’-monophosphate (cAMP) levels and brain tumor biology has been evident for nearly as long as cAMP and its synthetase, adenylate cyclase (ADCY) have been known. The importance of the pathway in brain tumorigenesis has been demonstrated in vitro and in multiple animal models. Recently, we provided human validation for a cooperating oncogenic role for cAMP in brain tumorigenesis when we found that SNPs in ADCY8 were correlated with glioma (brain tumor) risk in individuals with Neurofibromatosis type 1 (NF1). Together, these studies provide a strong rationale for targeting cAMP in brain tumor therapy. However, the cAMP pathway is well known to be sexually dimorphic, and SNPs in ADCY8 affected glioma risk in a sex-specific fashion, elevating the risk for females while protecting males. The cAMP pathway can be targeted at multiple levels in the regulation of its synthesis and degradation. Sex differences in response to drugs that target cAMP regulators indicate that successful targeting of the cAMP pathway for brain tumor patients is likely to require matching specific mechanisms of drug action with patient sex

Why does Jack, and not Jill, break his crown? Sex disparity in brain tumors

It is often reported that brain tumors occur more frequently in males, and that males suffer a worse outcome from brain tumors than females. If correct, these observations suggest that sex plays a fundamental role in brain tumor biology. The following review of the literature regarding primary and metastatic brain tumors, reveals that brain tumors do occur more frequently in males compared to females regardless of age, tumor histology, or region of the world. Sexually dimorphic mechanisms that might control tumor cell biology, as well as immune and brain microenvironmental responses to cancer, are explored as the basis for this sex disparity. Elucidating the mechanisms by which sex chromosomes and sex hormones impact on brain tumorigenesis and progression will advance our understanding of basic cancer biology and is likely to be essential for optimizing the care of brain tumor patients

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

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

Using Mendelian randomization to determine causal effects of maternal pregnancy (intrauterine) exposures on offspring outcomes:Sources of bias and methods for assessing them

Mendelian randomization (MR), the use of genetic variants as instrumental variables (IVs) to test causal effects, is increasingly used in aetiological epidemiology. Few of the methodological developments in MR have considered the specific situation of using genetic IVs to test the causal effect of exposures in pregnant women on postnatal offspring outcomes. In this paper, we describe specific ways in which the IV assumptions might be violated when MR is used to test such intrauterine effects. We highlight the importance of considering the extent to which there is overlap between genetic variants in offspring that influence their outcome with genetic variants used as IVs in their mothers. Where there is overlap, and particularly if it generates a strong association of maternal genetic IVs with offspring outcome via the offspring genotype, the exclusion restriction assumption of IV analyses will be violated. We recommend a set of analyses that ought to be considered when MR is used to address research questions concerned with intrauterine effects on post-natal offspring outcomes, and provide details of how these can be undertaken and interpreted. These additional analyses include the use of genetic data from offspring and fathers, examining associations using maternal non-transmitted alleles, and using simulated data in sensitivity analyses (for which we provide code). We explore the extent to which new methods that have been developed for exploring violation of the exclusion restriction assumption in the two-sample setting (MR-Egger and median based methods) might be used when exploring intrauterine effects in one-sample MR. We provide a list of recommendations that researchers should use when applying MR to test the effects of intrauterine exposures on postnatal offspring outcomes and use an illustrative example with real data to demonstrate how our recommendations can be applied and subsequent results appropriately interpreted

Calculating Power to Detect Maternal and Offspring Genetic Effects in Genetic Association Studies

Offspring outcomes are a function of maternal genetics operating on the intrauterine and postnatal environment, offspring genetics and environmental factors. Partitioning genetic effects into maternal and offspring components requires genotyped mother–offspring pairs or genotyped individuals with phenotypic information on themselves and their offspring. We performed asymptotic power calculations and data simulations to estimate power to detect maternal and offspring genetic effects under a range of different study designs and models. We also developed the “Maternal and offspring Genetic effects Power Calculator” (M-GPC), an online utility which allows users to estimate the power to detect maternal and offspring genetic effects in their own studies. We find that approximately 50,000 genotyped mother–offspring pairs will be required to detect realistically sized maternal or offspring genetic effects (> 0.1% variance explained) with appreciable power (power > 90%, α = 5 × 10, two degree of freedom test), whereas greater than 10,000 pairs will be required to determine whether known genetic loci have maternal and/or offspring genetic effects (power > 78%, α = 0.05). The structural equation modelling framework espoused in this manuscript provides a natural method of combining different data structures including those present in large scale biobanks in order to maximize power to detect maternal and offspring genetic effects. We conclude that the sample sizes required to detect maternal or offspring genetic effects that explain realistic proportions of the trait variance with appreciable power are achievable and within the range of current research consortia

Introducing M-GCTA a Software Package to Estimate Maternal (or Paternal) Genetic Effects on Offspring Phenotypes

There is increasing interest within the genetics community in estimating the relative contribution of parental genetic effects on offspring phenotypes. Here we describe the user-friendly M-GCTA software package used to estimate the proportion of phenotypic variance explained by maternal (or alternatively paternal) and offspring genotypes on offspring phenotypes. The tool requires large studies where genome-wide genotype data are available on mother- (or alternatively father-) offspring pairs. The software includes several options for data cleaning and quality control, including the ability to detect and automatically remove cryptically related pairs of individuals. It also allows users to construct genetic relationship matrices indexing genetic similarity across the genome between parents and offspring, enabling the estimation of variance explained by maternal (or alternatively paternal) and offspring genetic effects. We evaluated the performance of the software using a range of data simulations and estimated the computing time and memory requirements. We demonstrate the use of M-GCTA on previously analyzed birth weight data from two large population based birth cohorts, the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Norwegian Mother and Child Cohort Study (MoBa). We show how genetic variation in birth weight is predominantly explained by fetal genetic rather than maternal genetic sources of variation

Role of the TCF4 gene intronic variant in normal variation of corneal endothelium

PURPOSE: To identify early features of Fuchs endothelial dystrophy (FED) in carriers of the rs613872(G) transcription factor 4 gene (TCF4) aged 20 to 21 years. METHODS: Prospective cohort study of people aged 20 to 21 years previously enrolled in the Western Australia Pregnancy (Raine) Cohort. Specular microscopy was performed using a noncontact specular microscopy (EM-3000; Tomey, Nagoya, Japan). Individual genotype data were extracted from the genome-wide Illumina 660 Quad Array. Analysis of the association between the rs613872 risk allele in TCF4 and specular microscopic measurements was conducted. RESULTS: Association between the rs613872 risk allele and corneal endothelial cell density (CD) as well as the coefficient of variation in cell shape was the main outcome measure. Genotype and specular microscopic data were available for a total of 445 participants (46% women). The median CD was 2851 and 2850 cells per square millimeter in the right and left eyes, respectively. No significant differences between intereye variability in endothelial CD were seen (right eye to left eye correlation = 0.64); however, a significant difference in variability of endothelial CD between men and women was observed (male: OD, 2839 ± 124 cells/mm and OS, 2845 ± 124 cells/mm vs. female: OD, 2838 ± 134 cells/mm and OS, 2842 ± 132 cells/mm; OD, P = 0.0013 and OS, P = 0.0016). Eleven individuals were homozygous for the rs613872 risk allele. We found no association between rs613872 genotype and CD or coefficient of variation. One of 11 homozygous GG individuals was found to have a gutta in 1 sample field on specular microscopy, whereas 2 of 297 TT individuals also had a gutta each in 1 sample field. CONCLUSIONS: We were unable to detect an association between TCF4 rs613872 genotype and the variation in corneal endothelial CD or variation in cell morphology in a healthy young adult population. Copyrigh

Investigating a Potential Causal Relationship Between Maternal Blood Pressure During Pregnancy and Future Offspring Cardiometabolic Health

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

Novel chemical library screen identifies naturally occurring plant products that specifically disrupt glioblastoma-endothelial cell interactions

Tumor growth is not solely a consequence of autonomous tumor cell properties. Rather, tumor cells act upon and are acted upon by their microenvironment. It is tumor tissue biology that ultimately determines tumor growth. Thus, we developed a compound library screen for agents that could block essential tumor-promoting effects of the glioblastoma (GBM) perivascular stem cell niche (PVN). We modeled the PVN with three-dimensional primary cultures of human brain microvascular endothelial cells in Matrigel. We previously demonstrated stimulated growth of GBM cells in this PVN model and used this to assay PVN function. We screened the Microsource Spectrum Collection library for drugs that specifically blocked PVN function, without any direct effect on GBM cells themselves. Three candidate PVN-disrupting agents, Iridin, Tigogenin and Triacetylresveratrol (TAR), were identified and evaluated in secondary in vitro screens against a panel of primary GBM isolates as well as in two different in vivo intracranial models. Iridin and TAR significantly inhibited intracranial tumor growth and prolonged survival in these mouse models. Together these data identify Iridin and TAR as drugs with novel GBM tissue disrupting effects and validate the importance of preclinical screens designed to address tumor tissue function rather than the mechanisms of autonomous tumor cell growth

Sexually dimorphic RB inactivation underlies mesenchymal glioblastoma prevalence in males

The prevalence of brain tumors in males is common but unexplained. While sex differences in disease are typically mediated through acute sex hormone actions, sex-specific differences in brain tumor rates are comparable at all ages, suggesting that factors other than sex hormones underlie this discrepancy. We found that mesenchymal glioblastoma (Mes-GBM) affects more males as the result of cell-intrinsic sexual dimorphism in astrocyte transformation. We used astrocytes from neurofibromin-deficient (Nf1(–/–)) mice expressing a dominant-negative form of the tumor suppressor p53 (DNp53) and treated them with EGF as a Mes-GBM model. Male Mes-GBM astrocytes exhibited greater growth and colony formation compared with female Mes-GBM astrocytes. Moreover, male Mes-GBM astrocytes underwent greater tumorigenesis in vivo, regardless of recipient mouse sex. Male Mes-GBM astrocytes exhibited greater inactivation of the tumor suppressor RB, higher proliferation rates, and greater induction of a clonogenic, stem-like cell population compared with female Mes-GBM astrocytes. Furthermore, complete inactivation of RB and p53 in Mes-GBM astrocytes resulted in equivalent male and female tumorigenic transformation, indicating that intrinsic differences in RB activation are responsible for the predominance of tumorigenic transformation in male astrocytes. Together, these results indicate that cell-intrinsic sex differences in RB regulation and stem-like cell function may underlie the predominance of GBM in males