Biology subjects

Hemani, G.

Publications and source records attributed to Hemani, G..

At least 55 records · Page 3Linked to original sources

bioRxiv2018

Systematic evaluation of the causal relationship between DNA methylation and C-reactive protein

Elevated C-reactive protein (CRP) levels are an indicator of chronic low-grade inflammation. Epigenetic modifications, including DNA methylation, have been linked to CRP, but systematic investigations into potential underlying causal relationships have not yet been performed.\n\nWe systematically performed two-sample Mendelian randomization and colocalization analysis between CRP and DNA methylation levels, using GWAS and EWAS summary statistics as well as individual level data available through the ARIES subset of the Avon Longitudinal Study of Parents and Children (ALSPAC; 1,616 participants).\n\nWe found no convincing examples for a causal association from CRP to DNA methylation. Testing for the reverse (a putative causal effect of DNA methylation on CRP), we found three CpG sites that had shared genetic effects with CRP levels after correcting for multiple testing (cg26470501 (offspring: beta=0.07 [0.03, 0.11]; mothers: beta=0.08 [0.04, 0.13]), cg27023597 (offspring: beta=0.18 [0.10, 0.25]; mothers: beta=0.20 [0.12, 0.28]) and cg12054453 (offspring: beta=0.09 [0.05, 0.13])) influenced CRP levels. For all three CpG sites, linked to the genes TMEM49, BCL3 and MIR21, increased methylation related to an increase in CRP levels. Two CpGs (cg27023597 and cg12054453) were influenced by SNPs in genomic regions that had not previously been implicated in CRP GWASs, implicating them as novel genetic associations.\n\nOverall, our findings suggest that CRP associations with DNA methylation are more likely to be driven by either confounding or causal influences of DNA methylation on CRP levels, rather than the reverse.

genetics↗

bioRxiv2018

Schizophrenia risk and reproductive success: A Mendelian randomization study.

Schizophrenia is a debilitating and heritable mental disorder associated with lower reproductive success. However, the prevalence of schizophrenia is stable over populations and time, resulting in an evolutionary puzzle: how is schizophrenia maintained in the population given its apparent fitness costs? One possibility is that increased genetic liability for schizophrenia, in the absence of the disorder itself, may confer some reproductive advantage. We assessed the correlation and causal effect of genetic liability for schizophrenia with number of children and age at first birth using data from the Psychiatric Genomics Consortium and UK Biobank. Linkage disequilibrium score regression showed little evidence of genetic correlation between genetic liability for schizophrenia and number of children (rg=0.002, p=0.84) or age at first birth (rg=-0.007, p=0.45). Mendelian randomization indicated no robust evidence of a causal effect of genetic liability for schizophrenia on number of children (mean difference: 0.003 increase in number of children per doubling in the natural log odds ratio of schizophrenia risk, 95% CI: -0.003 to 0.009, p=0.39) or age at first birth (-0.004 years lower age at first birth, 95% CI: -0.043 to 0.034, p=0.82). These results suggest that increased genetic liability for schizophrenia does not confer a reproductive advantage.

evolutionary biology↗

bioRxiv2018

Prenatal alcohol exposure and facial morphology in a UK cohort

High levels of prenatal alcohol exposure are known to cause an array of adverse outcomes including foetal alcohol syndrome (FAS); however, the effects of low to moderate exposure are less-well characterised. Previous findings suggest that differences in normal-range facial morphology may be a marker for alcohol exposure and related adverse effects. Therefore, in the Avon Longitudinal Study of Parents and Children, we tested for an association between maternal alcohol consumption and six FAS-related facial phenotypes in their offspring, using both self-report questionnaires and the maternal genotype at rs1229984 in ADH1B as measures of maternal alcohol consumption. In both self-reported alcohol consumption (N=4,233) and rs1229984 genotype (N=3,139) analyses, we found no strong statistical evidence for an association between maternal alcohol consumption and facial phenotypes tested. The directions of effect estimates were compatible with the known effects of heavy alcohol exposure, but confidence intervals were largely centred around zero. We conclude that, in a sample representative of the general population, there is no strong evidence for an effect of prenatal alcohol exposure on normal-range variation in facial morphology.

epidemiology↗

bioRxiv2018

Common genetic variants and health outcomes appear geographically structured in the UK Biobank sample: Old concerns returning and their implications.

Introductory paragraphThe inclusion of genetic data in large studies has enabled the discovery of genetic contributions to complex traits and their application in applied analyses including those using genetic risk scores (GRS) for the prediction of phenotypic variance. If genotypes show structure by location and coincident structure exists for the trait of interest, analyses can be biased. Having illustrated structure in an apparently homogeneous collection, we aimed to a) test for geographical stratification of genotypes in UK Biobank and b) assess whether stratification might induce bias in genetic association analysis.\n\nWe found that single genetic variants are associated with birth location within UK Biobank and that geographic structure in genetic data could not be accounted for using routine adjustment for study centre and principal components (PCs) derived from genotype data. We found that GRS for complex traits do appear geographically structured and analysis using GRS can yield biased associations. We discuss the likely origins of these observations and potential implications for analysis within large-scale population based genetic studies.

genetics↗

bioRxiv2018

Appraising the causal relevance of DNA methylation for risk of lung cancer

DNA methylation changes in peripheral blood have been identified in relation to lung cancer risk. However, the causal nature of these associations remains to be fully elucidated. Meta-analysis of four epigenome-wide association studies (918 cases, 918 controls) revealed differential methylation at 16 CpG sites (FDR < 0.05) in relation to lung cancer risk. A two-sample Mendelian randomization analysis, using genetic instruments for methylation at 14 of the 16 CpG sites, and 29,863 cases and 55,586 controls from the TRICL-ILCCO lung cancer consortium, was performed to appraise the causal role of methylation at these sites on lung cancer. This approach provided little evidence that DNA methylation in peripheral blood at the 14 CpG sites play a causal role in lung cancer development, including for cg05575921 AHRR, where methylation is strongly associated with lung cancer risk. Further studies are needed to investigate the causal role played by DNA methylation in lung tissue.

epidemiology↗

bioRxiv2018

Tendency towards being a “Morning person” increases risk of Parkinson’s disease: evidence from Mendelian randomisation

BackgroundCircadian rhythm may play a role in neurodegenerative diseases such as Parkinsons disease (PD). Chronotype is the behavioural manifestation of circadian rhythm and Mendelian randomisation (MR) involves the use of genetic variants to explore causal effects of exposures on outcomes. This study aimed to explore a causal relationship between chronotype and coffee consumption on risk of PD.\n\nMethodsTwo-sample MR was undertaken using publicly available GWAS data. Associations between genetic instrumental variables (IV) and \"morning person\" (one extreme of chronotype) were obtained from the personal genetics company 23andMe, Inc., and UK Biobank, and consisted of the per-allele odds ratio of being a \"morning person\" for 15 independent variants. The per-allele difference in log-odds of PD for each variant was estimated from a recent meta-analysis. The inverse variance weight method was used to estimate an odds ratio (OR) for the effect of being a \"morning person\" on PD. Additional MR methods were used to check for bias in the IVW estimate, arising through violation of MR assumptions. The results were compared to analyses employing a genetic instrument of coffee consumption, because coffee consumption has been previously inversely linked to PD.\n\nFindingsBeing a \"morning person\" was causally linked with risk of PD (OR 1*27; 95% confidence interval 1*06-1*51; p=0*012). Sensitivity analyses did not suggest that invalid instruments were biasing the effect estimate and there was no evidence for a reverse causal relationship between liability for PD and chronotype. There was no robust evidence for a causal effect of high coffee consumption using IV analysis, but the effect was imprecisely estimated (OR 1*12; 95% CI 0*89-1*42; p=0*22).\n\nInterpretationWe observed causal evidence to support the notion that being a \"morning person\", a phenotype driven by the circadian clock, is associated with a higher risk of PD. Further work on the mechanisms is warranted and may lead to novel therapeutic targets.\n\nFundingNo specific funding source.

epidemiology↗

bioRxiv2018

DNA methylation mediates genetic liability to non-syndromic cleft lip/palate

BackgroundNon-syndromic cleft lip/palate (nsCL/P) is a complex trait with genetic and environmental risk factors. Around 40 distinct genetic risk loci have been identified for nsCL/P, but many reside in non-protein-coding regions with an unclear function. We hypothesised that one possibility is that the genetic risk variants influence susceptibility to nsCL/P through gene regulation pathways, such as those involving DNA methylation.\n\nMethodsUsing nsCL/P Genome-wide association study summary data and methylation data from four studies, we used Mendelian randomization and joint likelihood mapping to identify putative loci where genetic liability to nsCL/P may be mediated by variation in DNA methylation in blood.\n\nResultsThere was evidence at three independent loci, VAX1 (10q25.3), LOC146880 (17q23.3) and NTN1 (17p13.1), that liability to nsCL/P and variation in DNA methylation might be driven by the same genetic variant. Follow up analyses using DNA methylation data, derived from lip and palate tissue, and gene expression catalogues provided further insight into possible biological mechanisms.\n\nConclusionsGenetic variation may increase liability to nsCL/P by influencing DNA methylation and gene expression at VAX1, LOC146880 and NTN1.

genetics↗

bioRxiv2018

Investigating the shared genetics of non-syndromic cleft lip/palate and facial morphology

There is increasing evidence that genetic risk variants for non-syndromic cleft lip/palate (nsCL/P) are also associated with normal-range variation in facial morphology. However, previous analyses are mostly limited to candidate SNPs and findings have not been consistently replicated. Here, we used polygenic risk scores (PRS) to test for genetic overlap between nsCL/P and seven biologically relevant facial phenotypes. Where evidence was found of genetic overlap, we used bidirectional Mendelian randomization (MR) to test the hypothesis that genetic liability to nsCL/P is causally related to implicated facial phenotypes. Across 5,804 individuals of European ancestry from two studies, we found strong evidence, using PRS, of genetic overlap between nsCL/P and philtrum width; a 1 S.D. increase in nsCL/P PRS was associated with a 0.10 mm decrease in philtrum width (95% C.I. 0.054, 0.146; P = 0.00002). Follow-up MR analyses supported a causal relationship; genetic variants for nsCL/P homogeneously cause decreased philtrum width. In addition to the primary analysis, we also identified two novel risk loci for philtrum width at 5q22.2 and 7p15.2 in our Genome-wide Association Study (GWAS) of 6,136 individuals. Our results support a liability threshold model of inheritance for nsCL/P, related to abnormalities in development of the philtrum.

genetics↗

bioRxiv2018

Identification of loci where DNA methylation potentially mediate genetic risk of type 1 diabetes

The risk of Type 1 Diabetes (T1D) comprises both genetic and environmental components. We investigated whether genetic susceptibility to T1D could be mediated by changes in DNA methylation, an epigenetic mechanism that potentially plays a role in autoimmune diabetes. Using data from a non-diabetic population comprising blood samples taken at birth (n=844), childhood (n=911) and adolescence (n=907), we evaluated the associations between 65 top GWAS single nucleotide polymorphisms (SNPs) and genome-wide DNA methylation levels. We identified 159 proximal SNP-cytosine phosphate guanine (CpG) pairs (cis), and 7 distal SNP-CpG associations (trans) at birth, childhood, and adolescence. There was also a systematic enrichment for methylation related SNPs to be associated with T1D across the genome, after controlling for genomic characteristics of the SNPs, implying that methylation could either be on the causal pathway to T1D or a non-causal biomarker. Combining the principles of Mendelian Randomization and genetic colocalization analysis, we provided evidence that at 5 loci, ITGB3BP, AFF3, PTPN2, CTSH and CTLA4, DNA methylation is potentially on the causal pathway to T1D.

genomics↗

bioRxiv2017

Systematic Mendelian randomization framework elucidates hundreds of genetic loci which may influence disease through changes in DNA methylation levels

We have undertaken an extensive Mendelian randomization (MR) study using methylation quantitative trait loci (mQTL) as genetic instruments to assess the potential causal relationship between genetic variation, DNA methylation and 139 complex traits. Using two-sample MR, we observed 1,191 effects across 62 traits where genetic variants were associated with both proximal DNA methylation (i.e. cis-mQTL) and complex trait variation (P<1.39x10-08). Joint likelihood mapping provided evidence that the causal mQTL for 364 of these effects across 58 traits was also likely the causal variant for trait variation. These effects showed a high rate of replication in the UK Biobank dataset for 14 selected traits, as 121 of the attempted 129 effects replicated. Integrating expression quantitative trait loci (eQTL) data suggested that genetic variants responsible for 319 of the 364 mQTL effects also influence gene expression, which indicates a coordinated system of effects that are consistent with causality. CpG sites were enriched for histone mark peaks in tissue types relevant to their associated trait and implicated genes were enriched across relevant biological pathways. Though we are unable to distinguish mediation from horizontal pleiotropy in these analyses, our findings should prove valuable in identifying candidate loci for further evaluation and help develop mechanistic insight into the aetiology of complex disease.

genetics↗

bioRxiv2017

Automating Mendelian randomization through machine learning to construct a putative causal map of the human phenome

A major application for genome-wide association studies (GWAS) has been the emerging field of causal inference using Mendelian randomization (MR), where the causal effect between a pair of traits can be estimated using only summary level data. MR depends on SNPs exhibiting vertical pleiotropy, where the SNP influences an outcome phenotype only through an exposure phenotype. Issues arise when this assumption is violated due to SNPs exhibiting horizontal pleiotropy. We demonstrate that across a range of pleiotropy models, instrument selection will be increasingly liable to selecting invalid instruments as GWAS sample sizes continue to grow. Methods have been developed in an attempt to protect MR from different patterns of horizontal pleiotropy, and here we have designed a mixture-of-experts machine learning framework (MR-MoE 1.0) that predicts the most appropriate model to use for any specific causal analysis, improving on both power and false discovery rates. Using the approach, we systematically estimated the causal effects amongst 2407 phenotypes. Almost 90% of causal estimates indicated some level of horizontal pleiotropy. The causal estimates are organised into a publicly available graph database (http://eve.mrbase.org), and we use it here to highlight the numerous challenges that remain in automated causal inference.

epidemiology↗

bioRxiv2017

Investigating the role of insulin in increased adiposity: Bi-directional Mendelian randomization study

Insulin may serve as a key causal agent which regulates fat accumulation in the body. Here we assessed the causal relationship between fasting insulin and adiposity using publicly-available results from two large-scale genome-wide association studies for body mass index and fasting insulin levels in a two-sample, bidirectional Mendelian Randomized approach. This approach is only valid on the condition that the two instruments are independent of one another. In analysis excluding overlapping loci, there was an increase of 0.20 (0.17, 0.23) log pmol/L fasting insulin per SD increase in BMI (P= 2.80 x 10-36), while there was a null effect of fasting insulin on BMI, with a 0.01 (-0.39, 0.38) SD decrease in BMI per log pmol/L increase in fasting insulin (P= 0.98). Furthermore, a high degree of heterogeneity in the causal estimates was obtained from the insulin-related variants, which may be attributed to varying mechanisms of action of the insulin-associated variants. Results were largely consistent when an Egger regression technique and weighted median and mode estimators were applied. Findings suggest that the positive correlation between adiposity and fasting insulin levels are at least in part explained by the causal effect of adiposity on increasing insulin, rather than vice versa.

epidemiology↗

bioRxiv2017

PhenoSpD: an atlas of phenotypic correlations and a multiple testing correction for the human phenome

BackgroundIdentifying phenotypic correlations between complex traits and diseases can provide useful etiological insights. Restricted access to individual-level phenotype data makes it difficult to estimate large-scale phenotypic correlation across the human phenome. State-of-the-art methods, metaCCA and LD score regression, provide an alternative approach to estimate phenotypic correlation using genome-wide association study (GWAS) summary statistics.\n\nResultsHere, we present an integrated R toolkit, PhenoSpD, to 1) apply metaCCA (or LD score regression) to estimate phenotypic correlations using GWAS summary statistics; and 2) to utilize the estimated phenotypic correlations to inform correction of multiple testing for complex human traits using the spectral decomposition of matrices (SpD). The simulations suggest it is possible to estimate phenotypic correlation using samples with only a partial overlap, but as overlap decreases correlations will attenuate towards zero and multiple testing correction will be more stringent than in perfectly overlapping samples. In a case study, PhenoSpD using GWAS results suggested 324.4 independent tests among 452 metabolites, which is close to the 296 independent tests estimated using true phenotypic correlation. We further applied PhenoSpD to estimated 7,503 pair-wise phenotypic correlations among 123 metabolites using GWAS summary statistics from Kettunen et al. and PhenoSpD suggested 44.9 number of independent tests for theses metabolites.\n\nConclusionPhenoSpD integrates existing methods and provides a simple and conservative way to reduce dimensionality for complex human traits using GWAS summary statistics, which is particularly valuable for post-GWAS analysis of complex molecular traits.\n\nAvailabilityR code and documentation for PhenoSpD V1.0.0 is available online (https://github.com/MRCIEU/PhenoSpD).

bioinformatics↗

bioRxiv2017

Partitioning Phenotypic Variance Due To Parent-Of-Origin Effects Using Genomic Relatedness Matrices

Introduction Introduction Methods Statistical Methods Results Discussion References Parent-of-origin effects (POEs) describe the phenomenon in which the effects of alleles depend upon their parental origin. POEs imply that heterozygote individuals have phenotypes which are distributed differently depending upon which of their alleles were maternally and paternally transmitted (Guilmatre and Sharp 2012; Lawson et al. 2013). The extreme case of POEs is polar overdominance, where the two heterozygotes' phenotypes differ in distribution but the two homozygotes share the same distribution (Hoggart et al. 2014). Imprinting, a phenomenon in which one parent's allele is not expressed, is probably the most widely studied example of POE (Peters 2 ...

genetics↗

bioRxiv2017

Causal epigenome-wide association study identifies CpG sites that influence cardiovascular disease risk

The extent to which genetic influences on complex traits and disease are mediated by changes in DNA methylation levels has not been systematically explored. We developed an analytical framework that integrates genetic fine mapping and Mendelian randomization with epigenome-wide association studies to evaluate the causal relationships between methylation levels and 14 cardiovascular disease traits.\n\nWe identified 10 genetic loci known to influence proximal DNA methylation which were also associated with cardiovascular traits (P < 3.83x10-08). Bivariate fine mapping suggested that the individual variants responsible for the observed effects on cardiovascular traits at the ABO, ADCY3, ADIPOQ, APOA1 and IL6R loci were likely mediated through changes in DNA methylation. Causal effect estimates on cardiovascular traits ranged between 0.109-0.992 per standard deviation change in DNA methylation and were replicated using results from large-scale consortia.\n\nFunctional informatics suggests that the causal variants and CpG sites identified in this study were enriched for histone mark peaks in adipose tissue and gene promoter regions. Integrating our results with expression quantitative trait loci data we provide evidence that variation at these regulatory regions is likely to also influence gene expression at these loci.

epidemiology↗

bioRxiv2017

Meffil: efficient normalisation and analysis of very large DNA methylation samples

AbstractO_ST_ABSBackgroundC_ST_ABSTechnological advances in high throughput DNA methylation microarrays have allowed dramatic growth of a new branch of epigenetic epidemiology. DNA methylation datasets are growing ever larger in terms of the number of samples profiled, the extent of genome coverage, and the number of studies being meta-analysed. Novel computational solutions are required to efficiently handle these data.\n\nMethodsWe have developed meffil, an R package designed to quality control, normalize and perform epigenome-wide association studies (EWAS) efficiently on large samples of Illumina Infinium HumanMethylation450 and MethylationEPIC BeadChip microarrays. We tested meffil by applying it to 6000 450k microarrays generated from blood collected for two different datasets, Accessible Resource for Integrative Epigenomic Studies (ARIES) and The Genetics of Overweight Young Adults (GOYA) study.\n\nResultsA complete reimplementation of functional normalization minimizes computational memory requirements to 5% of that required by other R packages, without increasing running time. Incorporating fixed and random effects alongside functional normalization, and automated estimation of functional normalisation parameters reduces technical variation in DNA methylation levels, thus reducing false positive associations and improving power. We also demonstrate that the ability to normalize datasets distributed across physically different locations without sharing any biologically-based individual-level data may reduce heterogeneity in meta-analyses of epigenome-wide association studies. However, we show that when batch is perfectly confounded with cases and controls functional normalization is unable to prevent spurious associations.\n\nConclusionsmeffil is available online (https://github.com/perishky/meffil/) along with tutorials covering typical use cases.

bioinformatics↗

bioRxiv2017

The causal effect of educational attainment on Alzheimer’s disease: A two-sample Mendelian randomization study

BackgroundObservational evidence suggests that higher educational attainment is protective for Alzheimers disease (AD). It is unclear whether this association is causal or confounded by demographic and socioeconomic characteristics. We examined the causal effect of educational attainment on AD in a two-sample MR framework.\n\nMethodsWe extracted all available effect estimates of the 74 single nucleotide polymorphisms (SNPs) associated with years of schooling from the largest genome-wide association study (GWAS) of educational attainment (N=293,723) and the GWAS of AD conducted by the International Genomics of Alzheimers Project (n=17,008 AD cases and 37,154 controls). SNP-exposure and SNP-outcome coefficients were combined using an inverse variance weighted approach, providing an estimate of the causal effect of each SD increase in years of schooling on AD. We also performed appropriate sensitivity analyses examining the robustness of causal effect estimates to the various assumptions and conducted simulation analyses to examine potential survival bias of MR analyses.\n\nFindingsWith each SD increase in years of schooling (3.51 years), the odds of AD were, on average, reduced by approximately one third (odds ratio= 0.63, 95% confidence interval [CI]: 0.48 to 0.83, p<0.001). Causal effect estimates were consistent when using causal methods with varying MR assumptions or different sets of SNPs for educational attainment, lending confidence to the magnitude and direction of effect in our main findings. There was also no evidence of survival bias in our study.\n\nInterpretationOur findings support a causal role of educational attainment on AD, whereby an additional [~]3.5 years of schooling reduces the odds of AD by approximately one third.

epidemiology↗

bioRxiv2017

The role of glycaemic and lipid risk factors in mediating the effect of BMI on coronary heart disease: A two-step, two-sample Mendelian randomization study

BackgroundThe extent to which effects of BMI on coronary heart disease (CHD) are mediated by gylcaemic and lipid risk factors is unclear.\n\nMethodsWe used two-sample Mendelian randomization to determine the causal effect of: (i) BMI on CHD (60,801 cases; 123, 504 controls), type 2 diabetes (T2DM; 34,840 cases; 114,981 controls), fasting glucose (n=46,186), insulin (n=38,238), HbA1c (n=46,368), LDL-cholesterol (LDL-C), HDL-cholesterol (HDL-C) and triglycerides (n=188,577); (ii) glycaemic and lipids traits on CHD; and (iii) extent to which these traits mediated any effect of BMI on CHD.\n\nFindingsOne standard deviation (SD) increase in BMI (~ 4.5kg/m2) increased CHD (odds ratio=1.45 (95% confidence interval (CI): 1.27, 1.66)) and T2DM (1.96 (1.35, 2.83)), and levels of fasting glucose (0.07mmol/l (95%CI 0.03, 0.11)), HbA1c (0.05% (95%CI 0.01, 0.08)), fasting insulin (0.18log pmol/l (95%CI 0.14, 0.22)) and triglycerides (0.20 SD (95%CI 0.14, 0.26)), and lowered levels of HDL-C (-0.23 SD (95%CI -0.32, -0.15)). BMI was not causally related to LDL-C. After accounting for potential pleiotropy, triglycerides, HbA1c and T2DM were causally related to CHD. The BMI-CHD effect reduced from 1.45 to 1.16 (95%CI 0.99, 1.36) and to 1.36 (95%CI 1.19, 1.57) with genetic adjustment for triglycerides or HbA1c respectively, and to 1.09 (95%CI 0.94, 1.27) with adjustment for both.\n\nInterpretationIncreased triglyceride levels and poor glycaemic control appear to mediate much of the effect of BMI on CHD.\n\nFundingEuropean Research Council (669545), European Union (733206), China Medical Board (CMB_2015/16), Conselho Nacional de Desenvolvimento Cientifico e Tecnologico and UK Medical Research Council (MC_UU_12013/5).

epidemiology↗