Biology subjects

Davey Smith, G.

Publications and source records attributed to Davey Smith, G..

At least 37 records · Page 2Linked to original sources

bioRxiv2019

A cross-disorder MR-pheWAS of 5 major psychiatric disorders in UK Biobank

Psychiatric disorders are highly heritable and associated with a wide variety of social adversity and physical health problems. Using genetic liability (rather than phenotypic measures of disease) as a proxy for psychiatric disease risk can be a useful alternative for research questions that would traditionally require large cohort studies with long-term follow up.\n\nHere we conducted a hypothesis-free phenome-wide association study in about 300,000 participants from the UK Biobank to examine associations of polygenic risk scores (PRS) for five psychiatric disorders (major depression (MDD), bipolar disorder (BP), schizophrenia (SCZ), attention-deficit/ hyperactivity disorder (ADHD) and autism spectrum disorder (ASD)) with 23,004 outcomes in UK Biobank, using the open-source PHESANT software package.\n\nThere was evidence after multiple testing (p<2.55x10-06) for associations of PRSs with 226 outcomes, most of them attributed to associations of PRSMDD (n=120) with mental health factors and PRSADHD (n=77) with socio-demographic factors. Among others, we found strong evidence of associations between a 1 standard deviation increase in PRSADHD with 1.1 months younger age at first sexual intercourse [95% confidence interval [CI]: -1.26,-0.94]; PRSASD with 0.01% reduced lower erythrocyte distribution width [95%CI: -0.013,-0.007]; PRSSCZ with 0.98 odds of playing computer games [95%CI:0.976,0.989]; PRSMDD with a 0.11 points higher neuroticism score [95%CI:0.094,0.118] and PRSBP with 1.04 higher odds of having a university degree [95%CI:1.033,1.048].\n\nWe were able to show that genetic liabilities for five major psychiatric disorders associate with long-term aspects of adult life, including socio-demographic factors, mental and physical health. This is evident even in individuals from the general population who do not necessarily present with a psychiatric disorder diagnosis.\n\nAUTHOR SUMMARYPsychiatric disorders are associated with a wide range of adverse health, social and economic problems. Our study investigates the association of genetic risk for five common psychiatric disorders with socio-demographics, lifestyle and health of about 330,000 participants in the UK Biobank using a systematic, hypothesis-free approach. We found that genetic risk for attention deficit/hyperactivity disorder (ADHD) and bipolar disorder were most strongly associated with lifestyle factors, such as time of first sexual intercourse and educational attainment. Genetic risks for autism spectrum disorder and schizophrenia were associated with altered blood cell counts and time playing computer games, respectively. Increased genetic risk for depression was associated with other mental health outcomes such as neuroticism and irritability. In general, our results suggest that genetic risk for psychiatric disorders associates with a range of health and lifestyle traits that were measured in adulthood, in individuals from the general population who do not necessarily present with a psychiatric disorder diagnosis. However, it is important to note that these associations arent necessary causal but can themselves be influenced by other factors, like socio-economic factors and selection into the cohort. The findings inform future hypotheses to be tested using causally informative designs.

epidemiology↗

bioRxiv2019

Why are education, socioeconomic position and intelligence genetically correlated?

Genetic associations and correlations are perceived as confirmation that genotype influences one or more phenotypes respectively. However, genetic correlations can arise from non-biological or indirect mechanisms including population stratification, dynastic effects, and assortative mating. In this paper, we outline these mechanisms and demonstrate available tools and analytic methods that can be used to assess their presence in estimates of genetic correlations and genetic associations. Using educational attainment and parental socioeconomic position data as an exemplar, we demonstrate that both heritability and genetic correlation estimates may be inflated by these indirect mechanisms. The results highlight the limitations of between-individual estimates obtained from samples of unrelated individuals and the potential value of family-based studies. Use of the highlighted tools in combination with within-sibling or mother-father-offspring trio data may offer researchers greater opportunity to explore the underlying mechanisms behind genetic associations and correlations and identify the underlying causes of estimate inflation.

genetics↗

bioRxiv2019

Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases

The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma protein levels. Here, we estimated the effects of 1002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium (LD) is widespread in naive phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes (www.epigraphdb.org/pqtl/). Evaluation of data from historic drug development programmes showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of our approach in identifying and prioritising potential therapeutic targets.

genetics↗

bioRxiv2019

Is disrupted sleep a risk factor for Alzheimers disease? Evidence from a two-sample Mendelian randomization analysis

INTRODUCTIONIt is established that Alzheimers disease (AD) patients experience sleep disruption. However, it remains unknown whether disruption in the quantity, quality or timing of sleep is a risk factor for the onset of AD.\n\nMETHODSMendelian randomization (MR) was used to estimate the causal effect of self-reported and accelerometer-measured sleep parameters (chronotype, duration, fragmentation, insomnia, daytime napping and daytime sleepiness) on AD risk.\n\nRESULTSOverall, there was little evidence that sleep traits affect the risk of AD. There was some evidence to suggest that self-reported daytime napping was associated with lower AD risk (odds ratio [OR]: 0.70, 95% confidence interval [CI]: 0.50 to 0.99). Some other sleep traits (accelerometer-measured eveningness and sleep duration, and self-reported daytime sleepiness) had ORs for AD risk of a similar magnitude to daytime napping, but were less precisely estimated.\n\nDISCUSSONOur findings provide tentative evidence that daytime napping may reduce AD risk. However, findings should be replicated using independent samples.

epidemiology↗

bioRxiv2019

Proxy gene-by-environment Mendelian randomization study confirms a causal effect of maternal smoking on offspring birthweight, but little evidence of long-term influences on offspring health

ObjectiveTo validate a novel proxy gene-by-environment (GxE) Mendelian randomization (MR) approach by replicating the previously established effect of maternal smoking heaviness in pregnancy on offspring birthweight, and then use GxE MR to investigate the effect of smoking heaviness in pregnancy on offspring health outcomes in later life and grandchilds birthweight.\n\nDesignA proxy GxE MR using participants genotype (i.e. rs16969968 in CHRNA5) as a proxy for their mothers genotype.\n\nSettingUK Biobank.\n\nParticipants289,684 white British men and women aged 40-69 in UK Biobank.\n\nMain outcome measuresParticipants birthweight and later life outcomes (height, body mass index, lung function, asthma, blood pressure, age at menarche, years of education, fluid intelligence score, depression/anxiety, happiness), and birthweight of female participants first child.\n\nResultsIn our proof of principle analysis, each additional smoking-increasing allele was associated with a 0.018 (95% confidence interval (CI): -0.026, -0.009) kg lower birthweight in the \"maternal smoking during pregnancy\" stratum, but no meaningful effect (-0.002kg; 95% CI: -0.008, 0.003) in the \"maternal non-smoking during pregnancy\" stratum (interaction P-value=0.004). We found little evidence of an effect of maternal smoking heaviness on participants later life outcomes. We found the differences in associations of rs16969968 with grandchilds birthweight between grandmothers who did versus did not smoke were heterogeneous (interaction P-value=0.042) among female participants who did (-0.020kg per allele; 95% CI: -0.044, 0.003) versus did not (0.007kg per allele; 95% CI: -0.005, 0.020) smoke in pregnancy.\n\nConclusionsOur study demonstrated how offspring genotype can be used to proxy for mothers genotype in GxE MR. We confirmed the previously established causal effect of maternal smoking on offspring birthweight but found little evidence of an effect on long-term health outcomes in the offspring. For grandchilds birthweight, the effect of grandmothers smoking heaviness in pregnancy may be modulated by maternal smoking status in pregnancy.\n\nWHAT IS ALREADY KNOWN TO THIS TOPICHeavier maternal smoking in pregnancy causes lower offspring birthweight Maternal smoking in pregnancy is also associated with offspring outcomes in later life and grandchilds birthweight, but it is not known whether these associations are causal Understanding the transgenerational causal effects of maternal smoking heaviness in pregnancy is important to inform public health policies\n\nWHAT THIS STUDY ADDSThe proxy gene-by-environment Mendelian randomization approach can be used to explore maternal effects on offspring phenotypes when maternal genetic information is unavailable The approach confirmed the causal effect of smoking on offspring birthweight.\n\nMaternal smoking status in pregnancy modulates the effect of grandmothers smoking heaviness in pregnancy on grandchilds birthweight, highlighting the importance of smoking cessation before pregnancy in each generation

epidemiology↗

bioRxiv2019

The Parkinsons Disease Mendelian Randomization Research Portal

BackgroundMendelian randomization (MR) is a method for exploring observational associations to find evidence of causality.\n\nObjectiveTo apply MR between multiple risk factors/phenotypic traits (exposures) and Parkinsons disease (PD) in a large, unbiased manner, and to create a public resource for research.\n\nMethodsWe used two-sample MR in which the summary statistics relating to SNPs from genome wide association studies (GWASes) of 5,839 exposures curated on MR Base were used to assess causal relationships with PD. We selected the highest quality exposure GWASes for this report (n=401). For the disease outcome, summary statistics from the largest published PD GWAS were used. For each exposure, the causal effect on PD was assessed using the inverse variance weighted (IVW) method, followed by a range of sensitivity analyses. We used a false discovery rate (FDR) corrected p-value of <0.05 from the IVW analysis to prioritize traits of interest.\n\nResultsWe observed evidence for causal associations between twelve exposures and risk of PD. Of these, nine were causal effects related to increasing adiposity and decreasing risk of PD. The remaining top exposures that affected PD risk were tea drinking, time spent watching television and forced vital capacity, but the latter two appeared to be biased by violations of underlying MR assumptions.\n\nDiscussionWe present a new platform which offers MR analyses for a total of 5,839 GWASes versus the largest PD GWASes available (https://pdgenetics.shinyapps.io/pdgenetics/). Alongside, we report further evidence to support a causal role for adiposity on lowering the risk of PD.

neuroscience↗

bioRxiv2019

Within-family studies for Mendelian randomization: avoiding dynastic, assortative mating, and population stratification biases

Mendelian randomization (MR) is a widely-used method for causal inference using genetic data. Mendelian randomization studies of unrelated individuals may be susceptible to bias from family structure, for example, through dynastic effects which occur when parental genotypes directly affect offspring phenotypes. Here we describe methods for within-family Mendelian randomization and through simulations show that family-based methods can overcome bias due to dynastic effects. We illustrate these issues empirically using data from 61,008 siblings from the UK Biobank and Nord-Trondelag Health Study. Both within-family and population-based Mendelian randomization analyses reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while MR estimates from population-based samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects largely disappeared in within-family MR analyses. We found differences between population-based and within-family based estimates, indicating the importance of controlling for family effects and population structure in Mendelian randomization studies.

genetics↗

bioRxiv2019

Polygenic risk score for Alzheimer’s disease and trajectories of cardiometabolic risk factors in children

INTRODUCTIONCardiometabolic factors are implicated in the aetiology of Alzheimers disease and may lie on the pathways linking genetic variants to Alzheimers disease across the life course. We examined whether polygenic risk scores (PRS) were associated with cardiometabolic health indicators through childhood and adolescence.\n\nMETHODSIn 7,977 participants from the Avon Longitudinal Study of Parents and Children, we tested whether a PRS for Alzheimers disease was associated with trajectories of cardiometabolic risk factors. We examined trajectories for height 1-18 years; lean and fat mass 9-18 years; systolic and diastolic blood pressure 7-18 years; glucose and C-reactive protein 9-18 years; insulin 10-18 years; high and low-density lipoproteins and triglycerides birth-18 years. We also examined birthweight, interleukin-6 (IL-6) at age 9 years and physical activity at ages 11, 12, and 15 years.\n\nRESULTSNo consistent associations were observed between the PRS excluding genetic variants in the apolipoprotein E (ApoE) gene region and cardiometabolic factors trajectories across childhood and adolescence.\n\nCONCLUSIONWe did not detect evidence to suggest that the PRS for Alzheimers disease acts through childhood and adolescent cardiometabolic risk factors. Further studies should examine whether these associations emerge later in adulthood when variation in cardiometabolic risk factors is likely to be greater.

epidemiology↗

bioRxiv2019

The causal effect of adiposity on hospital costs: Mendelian Randomization analysis of over 300,000 individuals from the UK Biobank

Estimates of the marginal effect of measures of adiposity such as body mass index (BMI) on healthcare costs are important for the formulation and evaluation of policies targeting adverse weight profiles. Many existing estimates of this association are affected by endogeneity bias caused by simultaneity, measurement error and omitted variables. The contribution of this study is to avoid this bias by using a novel identification strategy - random germline genetic variation in an instrumental variable analysis - to identify the presence and magnitude of the causal effect of BMI on inpatient hospital costs. We also use data on genetic variants to undertake much richer testing of the sensitivity of results to potential violations of the instrumental variable assumptions than is possible with existing approaches. Using data on over 300,000 individuals, we found effect sizes for the marginal unit of BMI more than 50% larger than multivariable effect sizes. These effects attenuated under sensitivity analyses, but remained larger than multivariable estimates for all but one estimator. There was little evidence for non-linear effects of BMI on hospital costs. Within-family estimates, intended to address dynastic biases, were null but suffered from low power. This paper is the first to use genetic variants in a Mendelian Randomization framework to estimate the causal effect of BMI (or any other disease/trait) on healthcare costs. This type of analysis can be used to inform the cost-effectiveness of interventions and policies targeting the prevention and treatment of overweight and obesity, and for setting research priorities.

epidemiology↗

bioRxiv2019

A transcriptome-wide Mendelian randomization study to uncover tissue-dependent regulatory mechanisms across the human phenome

BackgroundDeveloping insight into tissue-specific transcriptional mechanisms can help improve our understanding of how genetic variants exert their effects on complex traits and disease. By applying the principles of Mendelian randomization, we have undertaken a systematic analysis to evaluate transcriptome-wide associations between gene expression across 48 different tissue types and 395 complex traits. ResultsOverall, we identified 100,025 gene-trait associations based on conventional genome-wide corrections (P < 5 x 10-08) that also provided evidence of genetic colocalization. These results indicated that genetic variants which influence gene expression levels in multiple tissues are more likely to influence multiple complex traits. We identified many examples of tissue-specific effects, such as genetically-predicted TPO, NR3C2 and SPATA13 expression only associating with thyroid disease in thyroid tissue. Additionally, FBN2 expression was associated with both cardiovascular and lung function traits, but only when analysed in heart and lung tissue respectively. We also demonstrate that conducting phenome-wide evaluations of our results can help flag adverse on-target side effects for therapeutic intervention, as well as propose drug repositioning opportunities. Moreover, we find that exploring the tissue-dependency of associations identified by genome-wide association studies (GWAS) can help elucidate the causal genes and tissues responsible for effects, as well as uncover putative novel associations. ConclusionsThe atlas of tissue-dependent associations we have constructed should prove extremely valuable to future studies investigating the genetic determinants of complex disease. The follow-up analyses we have performed in this study are merely a guide for future research. Conducting similar evaluations can be undertaken systematically at http://mrcieu.mrsoftware.org/Tissue_MR_atlas/.

genetics↗

bioRxiv2019

A rare SMAD9 mutation identifies the BMP signalling pathway as a potential osteoanabolic target

To identify targets for novel anabolic medicines for osteoporosis, we recruited a large cohort with unexplained high bone mass (HBM). Exome sequencing identified a rare (minor allele frequency 0.0014) missense mutation in SMAD9 (c.65T>C, p.Leu22Pro) segregating with HBM in an autosomal dominant family. The same mutation was identified in another two unrelated individuals with HBM. In-silico protein modelling predicts the mutation severely disrupts the MH1 DNA-binding domain of SMAD9. Affected individuals have bone mineral density [BMD] Z-Scores +3 to +5, with increased volumetric cortical and trabecular BMD, increased cortical thickness, and low/normal bone turnover. Fractures and nerve compressions are not seen. Both genome-wide, and gene-based association testing of heel estimated-BMD in >362,924 UK-Biobank British subjects showed strong associations with SMAD9 (PGWAS=6x10-16; PGENE =8x10-17). Smad9 is highly expressed in murine osteocytes and zebrafish bone tissue. Our findings support SMAD9 as a novel HBM gene, and a potential novel osteoanabolic target.

genetics↗

bioRxiv2018

What explains the effect of education on cardiovascular disease? Applying Mendelian randomization to identify the consequences of education inequality

Key PointsO_ST_ABSQuestionC_ST_ABSWhat is the role of body mass index, systolic blood pressure and smoking in mediating the effect of education on cardiovascular disease risk?\n\nFindingWe find consistent evidence that body mass index, systolic blood pressure and smoking mediate the effect of education, explaining up to 18%, 27% and 33% respectively. Including all three risk factors in a model together explains around 40% of the effect of education.\n\nMeaningIntervening on body mass index, systolic blood pressure and smoking would lead to reductions in cases of CVD attributable to lower levels of education. Over half of the effect of education on risk of cardiovascular disease is not mediated through these risk factors.\n\nImportanceLower levels of education are causally related to higher cardiovascular risk, but the extent to which this is driven by modifiable risk factors also associated with education is unknown.\n\nObjectiveTo investigate the role of body mass index, systolic blood pressure and smoking in explaining the effect of education on risk of cardiovascular disease outcomes.\n\nDesignMultivariable regression analysis of observational data and Mendelian randomization (MR) analysis of genetic data.\n\nSettingUK Biobank and international genome-wide association study consortia.\n\nParticipantsPredominantly individuals of European ancestry.\n\nMain outcomes and measuresThe effects of education (per 1-standard deviation increase, equivalent to 3.6 years) on coronary heart disease, cardiovascular disease (all subtypes), myocardial infarction and stroke risk (all measured in odds ratio, OR), and the degree to which this is mediated through body mass index, systolic blood pressure and smoking.\n\nResultsEach additional standard deviation of education associated with 13% lower risk of coronary heart disease (OR 0.87, 95% confidence interval [CI] 0.84 to 0.89) in observational analysis and 37% lower risk (OR 0.63, 95% CI 0.60 to 0.67) in Mendelian randomization analysis. As a proportion of the total risk reduction, body mass index mediated 15% (95% CI 13% to 17%) and 18% (95% CI 14% to 23%) in the observational and Mendelian randomization estimates, respectively. Corresponding estimates for systolic blood pressure were 11% (95% CI 9% to 13%) and 21% (95% CI 15% to 27%), and for smoking, 19% (15% to 22%) and 33% (95% CI 17% to 49%). All three risk factors combined mediated 42% (95% CI 36% to 48%) and 36% (95 % CI 16% to 63%) of the effect of education on coronary heart disease in observational and Mendelian randomization respectively. Similar results were obtained when investigating risk of stroke, myocardial infarction and all-cause cardiovascular disease.\n\nConclusions and relevanceBMI, SBP and smoking mediate a substantial proportion of the protective effect of education on risk of cardiovascular outcomes and intervening on these would lead to reductions in cases of CVD attributable to lower levels of education. However, more than half of the protective effect of education remains unexplained and requires further investigation.

epidemiology↗

bioRxiv2018

The effect of plasma lipids and lipid lowering interventions on bone mineral density: a Mendelian randomization study

Statin treatment increases bone mineral density (BMD) and reduces fracture risk, but the underlying mechanism is unclear. We used Mendelian randomization (MR) to assess whether this relation 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 and results from a heel BMD GWAS (derived from quantitative ultrasound) in 426,824 individuals from the UK Biobank. 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. To test whether the effect of statins on BMD was mediated by lowering lipid levels, MR was repeated with and without SNPs in the HMGCR region, the gene targeted by statins. Univariate MR analyses provided evidence for a causal effect of LDL-C on BMD ({beta} = -0.060; -0.084 to -0.036; P = 4x10-6; standard deviation change in BMD per standard deviation change in LDL-C, with 95% CI), but not HDL or triglycerides. Multivariable MR analysis suggested that the effect of LDL-C on BMD was independent of HDL-C and triglycerides, and sensitivity analyses involving MR Egger and weighted median MR approaches 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 BMD({beta} = -0.083; -0.132 to -0.034; P = 0.001) to those excluding these SNPs ({beta} = -0.063; -0.090 to -0.036; P = 8x10-6). Bidirectional MR analyses provided some evidence for a causal effect of BMD on plasma LDL-C levels. Our results suggest that effects of statins on 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.

epidemiology↗

bioRxiv2018

MR-TRYX: Exploiting horizontal pleiotropy to infer novel causal pathways

In Mendelian randomization (MR) analysis, variants that exert horizontal pleiotropy are typically treated as a nuisance. However, they could be valuable in identifying novel pathways to the traits under investigation. Here, we developed the MR-TRYX framework, following the advice of William Bateson to \"TReasure Your eXceptions\". We begin by detecting outliers in a single exposure-outcome MR analysis, hypothesising they are due to horizontal pleiotropy. We search across thousands of complete GWAS summary datasets in the MR-Base database to systematically identify other (\"candidate\") traits that associate with the outliers. We developed a multi-trait pleiotropy model of the heterogeneity in the exposure-outcome analysis due to pathways through candidate traits. Through detailed investigation of several causal relationships, many pleiotropic pathways were uncovered with already established causal effects, validating the approach, but also novel putative causal pathways. Adjustment for pleiotropic pathways reduced the heterogeneity across the analyses.

bioinformatics↗

bioRxiv2018

Epigenetic regulation of PAR4-related platelet activation: mechanistic links between environmental exposure and cardiovascular disease

Protease-activated receptor 4 (PAR4) is a potent thrombin receptor. Epigenetic control of the F2RL3 locus (which encodes for PAR4) via DNA methylation is associated with both smoking and cardiovascular disease. We examined the association between DNA hypomethylation at F2RL3 and risk of cardiovascular disease, focusing on acute myocardial infarction (AMI) (n=853 cases / 2,352 controls). We used in vitro cell models to dissect the role of DNA methylation in regulating expression of F2RL3. We investigated the interplay between F2RL3 DNA methylation and platelet function in human (n=41). Lastly, we used Mendelian randomization to unify observational and functional work by assessing evidence for causal relationships using data from UK Biobank (n=407,141) and CARDIoGRAMplusC4D (n=184,305). Observationally, one standard deviation (SD) decrease in DNA methylation at F2RL3 was associated with a 25% increase in the odds of AMI. In vitro, short-term exposure of cells to cigarette smoke reduced F2RL3 DNA methylation and increased gene expression. Transcriptional assays flagged a role for a CEBP recognition sequence in modulating the enhancer activity of F2RL3 exon 2. Lower DNA methylation at F2RL3 was associated with increased platelet reactivity in human. The estimated casual odds ratio of ischaemic heart disease was 1.03 (95% CI: 1.00, 1.07) per 1 SD decrease in F2RL3 DNA. In conclusion, we show that DNA methylation-dependent platelet activation is part of a complex system of features contributing to cardiovascular health. Tailoring therapeutic intervention to new knowledge of F2RL3/PAR4 function should be explored to ameliorate the detrimental effects of this risk factor on cardiovascular health.\n\nOne sentence summaryDNA methylation-dependent platelet activation is a likely causal contributor to cardiovascular health.

epidemiology↗

bioRxiv2018

Evaluating causal associations between previously reported risk factors and epithelial ovarian cancer: a Mendelian randomization analysis

BackgroundPreviously reported observational associations between risk factors and epithelial ovarian cancer (EOC) could reflect residual confounding, reverse causation, or measurement error. Mendelian randomization (MR) uses genetic variants as proxies for modifiable risk factors to strengthen causal inference in observational studies.\n\nMethodsWe used MR to evaluate the causal role of 13 previously reported risk factors in overall and histotype-specific EOC in up to 25,509 case subjects and 40,941 controls in the Ovarian Cancer Association Consortium. Inverse-variance weighted models were employed to generate effect estimates and MR-Egger, weighted median, and weighted mode were performed to examine evidence of horizontal pleiotropy. A Bonferroni-corrected P-value threshold was used to establish \"strong evidence\" (P<0.0038) and \"suggestive evidence\" (0.0038<P<0.05) for associations.\n\nResultsThere was strong or suggestive evidence that 9 of 13 risk factors were causally associated with overall or histotype-specific EOC. Genetic liability to endometriosis was strongly associated with EOC (OR per log odds higher liability: 1.27,95%CI:1.16-1.40;P=6.94x10-7) and lifetime smoking exposure was suggestively associated with EOC (OR per unit increase in smoking score:1.36,95%CI:1.04-1.78;P=0.02). In histotype-stratified analyses, the strongest associations found were between: height and clear cell carcinoma (OR per SD increase:1.36,95%CI:1.15-1.61;P=0.0003); age at natural menopause and endometrioid carcinoma (OR per year later onset:1.09,95% CI:1.02-1.16;P=0.007); and genetic liability to polycystic ovary syndrome and endometrioid carcinoma (OR per log odds higher liability:0.74,95% CI:0.62-0.90;P=0.002). There was little evidence that genetic liability to type 2 diabetes, parity, or circulating levels of 25-hydroxyvitamin D and sex hormone-binding globulin were associated with ovarian cancer or its subtypes.\n\nConclusionsOur comprehensive examination of possible etiological drivers of ovarian carcinogenesis supports a causal role for few of these factors in epithelial ovarian cancer and suggests distinct etiologies across histotypes.

epidemiology↗

bioRxiv2018

Investigating the phenotypic consistency and genetic architecture of noncognitive skills.

Non-cognitive skills have previously been associated with a range of health and socioeconomic outcomes, though there has been considerable heterogeneity in published research. Many studies have used cross sectional data and therefore the longitudinal consistency of measures designed to capture non-cognitive skills is poorly understood. Using data from a UK cohort, we assess the consistency of non-cognitive skills over a 17-year period throughout childhood and adolescence, their genomic architecture, and their associations with socioeconomic outcomes. We find that longitudinal measurement consistency is high for behavioural and communication skills but low for other non-cognitive skills, implicating a high noise to signal ratio for many non-cognitive skills. Consistent non-zero heritability estimates and genetic correlations applied to cross-sectional measures are observed only for behavioural difficulties. When aggregating across multiple measurements, we find evidence of low heritability [Formula] for behaviour, communication, self-esteem and locus of control. We find weak correlations between aggregate measures of skills, further supporting cross-sectional measurement error in the non-cognitive measures. Associations between non-cognitive skills and educational outcomes are observed for skills measured in mid to late childhood and these are at most a third of the size of IQ-education associations. These results suggest that individual measures designed to capture non-cognitive skills may be subject to considerable measurement error and provide unreliable indicators of childrens skills. However, aggregate measures that leverage longitudinal data may more reliably identify underlying non-cognitive traits.

genetics↗

bioRxiv2018

An atlas of polygenic risk score associations to highlight putative causal relationships across the human phenome

The age of large-scale genome-wide association studies (GWAS) has provided us with an unprecedented opportunity to evaluate the genetic liability of complex disease using polygenic risk scores (PRS). In this study, we have analysed 162 PRS (P<5xl0 05) derived from GWAS and 551 heritable traits from the UK Biobank study (N=334,398). Findings can be investigated using a web application (http://mrcieu.mrsoftware.org/PRS_atlas/), which we envisage will help uncover both known and novel mechanisms which contribute towards disease susceptibility.\n\nTo demonstrate this, we have investigated the results from a phenome-wide evaluation of schizophrenia genetic liability. Amongst findings were inverse associations with measures of cognitive function which extensive follow-up analyses using Mendelian randomization (MR) provided evidence of a causal relationship. We have also investigated the effect of multiple risk factors on disease using mediation and multivariable MR frameworks. Our atlas provides a resource for future endeavours seeking to unravel the causal determinants of complex disease.

genetics↗