Biology subjects

Gaunt, T. R.

Publications and source records attributed to Gaunt, T. R..

14 recordsLinked to original sources

bioRxiv2018

Identification of new therapeutic targets for osteoarthritis through genome-wide analyses of UK Biobank

Osteoarthritis is the most common musculoskeletal disease and the leading cause of disability globally. Here, we perform the largest genome-wide association study for osteoarthritis to date (77,052 cases and 378,169 controls), analysing 4 phenotypes: knee osteoarthritis, hip osteoarthritis, knee and/or hip osteoarthritis, and any osteoarthritis. We discover 64 signals, 52 of them novel, more than doubling the number of established disease loci. Six signals fine map to a single variant. We identify putative effector genes by integrating eQTL colocalization, fine-mapping, human rare disease, animal model, and osteoarthritis tissue expression data. We find enrichment for genes underlying monogenic forms of bone development diseases, and for the collagen formation and extracellular matrix organisation biological pathways. Ten of the likely effector genes, including TGFB1, FGF18, CTSK and IL11 have therapeutics approved or in clinical trials, with mechanisms of action supportive of evaluation for efficacy in osteoarthritis.

genetics↗

bioRxiv2018

Leveraging brain cortex-derived molecular data to elucidate epigenetic and transcriptomic drivers of neurological function and disease

Integrative approaches which harness large-scale molecular datasets can help develop mechanistic insight into findings from genome-wide association studies (GWAS). We have performed extensive analyses to uncover transcriptional and epigenetic processes which may play a role in neurological trait variation.\n\nThis was undertaken by applying Bayesian multiple-trait colocalization systematically across the genome to identify genetic variants responsible for influencing intermediate molecular phenotypes as well as neurological traits. In this analysis we leveraged high dimensional quantitative trait loci data derived from prefrontal cortex tissue (concerning gene expression, DNA methylation and histone acetylation) and GWAS findings for 5 neurological traits (Neuroticism, Schizophrenia, Educational Attainment, Insomnia and Alzheimers disease).\n\nThere was evidence of colocalization for 118 associations suggesting that the same underlying genetic variant influenced both nearby gene expression as well as neurological trait variation. Of these, 73 associations provided evidence that the genetic variant also influenced proximal DNA methylation and/or histone acetylation. These findings support previous evidence at loci where epigenetic mechanisms may putatively mediate effects of genetic variants on traits, such as KLC1 and schizophrenia. We also uncovered evidence implicating novel loci in neurological disease susceptibility, including genes expressed predominantly in brain tissue such as MDGA1, KIRREL3 and SLC12A5.\n\nAn inverse relationship between DNA methylation and gene expression was observed more than can be accounted for by chance, supporting previous findings implicating DNA methylation as a transcriptional repressor. Our study should prove valuable in helping future studies prioritise candidate genes and epigenetic mechanisms for in-depth functional follow-up analyses.

genetics↗

bioRxiv2018

Integrating Mendelian randomization and multiple-trait colocalization to uncover cell-specific inflammatory drivers of autoimmune and atopic disease

Immune mediated diseases (IMDs) arise from a lack of immune tolerance, causing chronic inflammation. Despite their growing prevalence, targeted therapies to treat IMDs are lacking. Cytokines and their receptors, which mediate inflammation, have been associated with IMD susceptibility. However, the complex signalling networks and multiple cell-types required to orchestrate inflammatory responses have made it difficult to pinpoint specific cytokines and immune cell-types which drive IMDs.\n\nIn this study, we developed an analytical framework which integrates Mendelian randomisation (MR) and multiple-trait colocalization (moloc) analyses to determine putative cell-specific drivers of IMDs. We used MR to determine the likelihood of causal associations between the levels of 10 circulating cytokines/cytokine receptors and 9 IMDs within human populations of European descent. Conservative (single SNP) and liberal (multiple SNP) MR analysis supported a causal role for IL-18 in inflammatory bowel disease (P = 1.17 x 10-4) and eczema/dermatitis (P = 2.81 x 10-3), as well as roles for IL-2r and IL-6R in several IMDs.\n\nWhere associations between cytokines/cytokine receptors and IMDs were discovered using MR, we undertook moloc analyses. This was to assess the likelihood that cytokine/cytokine receptor protein quantitative trait loci (pQTL) and IMD-associated loci share a causal genetic variant along with expression QTL (eQTL) using data from 3 immune cell-types: monocytes, neutrophils and T cells. We found a monocyte and neutrophil-driven role for IL-18 in IBD pathogenesis, amongst evidence supporting several other cell-specific inflammatory drivers of IMDs. Our study helps to elucidate causal pathways for the pathogeneses of IMDs which, together with other studies, highlights possible therapeutic targets for their treatment.

genetics↗

bioRxiv2018

A genome-wide association study of mitochondrial DNA copy number in two population-based cohorts

Mitochondrial DNA copy number (mtDNA CN) exhibits interindividual and intercellular variation, but few genome-wide association studies (GWAS) of directly assayed mtDNA CN exist.\n\nWe undertook a GWAS of qPCR-assayed mtDNA CN in the Avon Longitudinal Study of Parents and Children (ALSPAC), and the UK Blood Service (UKBS) cohort. After validating and harmonising data, 5461 ALSPAC mothers (16-43 years at mtDNA CN assay), and 1338 UKBS females (17-69 years) were included in a meta-analysis. Sensitivity analyses restricted to females with white cell-extracted DNA, and adjusted for estimated or assayed cell proportions. Associations were also explored in ALSPAC children, and UKBS males.\n\nA neutrophil-associated locus approached genome-wide significance (rs709591 [MED24], {beta}[SE] -0.084 [0.016], p=1.54e-07) in the main meta-analysis of adult females. This association was concordant in magnitude and direction in UKBS males and ALSPAC neonates. SNPs in and around ABHD8 were associated with mtDNA CN in ALSPAC neonates (rs10424198, {beta}[SE] 0.262 [0.034], p=1.40e-14), but not other study groups. In a meta-analysis of unrelated individuals (N=11253), we replicated a published association in TFAM {beta}[SE] 0.046 [0.017], p=0.006), with an effect size much smaller than that observed in the replication analysis of a previous in silico GWAS.\n\nIn a hypothesis-generating GWAS, we confirm an association between TFAM and mtDNA CN, and present putative loci requiring replication in much larger samples. We discuss the limitations of our work, in terms of measurement error and cellular heterogeneity, and highlight the need for larger studies to better understand nuclear genomic control of mtDNA copy number.

genomics↗

bioRxiv2018

Prioritizing putative influential genes in early life cardiovascular disease susceptibility by applying tissue-specific Mendelian randomization

BackgroundThe extent to which changes in gene expression can influence cardiovascular disease risk across different tissue types has not yet been systematically explored. We have developed an analytical framework that integrates tissue-specific gene expression, Mendelian randomization and multiple-trait colocalization to develop functional mechanistic insight into the causal pathway from genetic variant to complex trait.\n\nMethodsWe undertook a transcriptome-wide association study in a population of young individuals to uncover genetic variants associated with both nearby gene expression and cardiovascular traits. Two-sample Mendelian randomization was then applied using large-scale datasets to investigate whether changes in gene expression within certain tissue types may influence cardiovascular trait variation. We subsequently performed Bayesian multiple-trait colocalization to further interrogate findings and also gain insight into whether DNA methylation, as well as gene expression, may play a role in disease susceptibility.\n\nResultsEight genetic loci were associated with changes in gene expression and early life measures of cardiovascular function. Our Mendelian randomization analysis provided evidence of tissue-specific effects at multiple loci, of which the effects at the ADCY3 and FADS1 loci for body mass index and cholesterol respectively were particularly insightful. Multiple trait colocalization uncovered evidence which suggested that changes in DNA methylation at the promoter region upstream of FADS1/TMEM258 may also play a role in cardiovascular trait variation along with gene expression. Furthermore, colocalization analyses were able to uncover evidence of tissue-specificity, most prominantly between SORT1 expression in liver tissue and cholesterol levels.\n\nConclusionsDisease susceptibility can be influenced by differential changes in tissue-specific gene expression and DNA methylation. Our analytical framework should prove valuable in elucidating mechanisms in disease, as well as helping prioritize putative causal genes at associated loci where multiple nearby genes may be co-regulated. Future studies which continue to uncover quantitative trait loci for molecular traits across various tissue and cell typse will further improve our capability to understand and prevent disease.

genetics↗

bioRxiv2017

Searching for the causal effects of BMI in over 300 000 individuals, using Mendelian randomization

Mendelian randomization (MR) has been used to estimate the causal effect of body mass index (BMI) on particular traits thought to be affected by BMI. However, BMI may also be a modifiable, causal risk factor for outcomes where there is no prior reason to suggest that a causal effect exists. We perform a MR phenome-wide association study (MR-pheWAS) to search for the causal effects of BMI in UK Biobank (n=334 968), using the PHESANT open-source phenome scan tool. Of the 20 461 tests performed, our MR-pheWAS identified 519 associations below a stringent P value threshold corresponding to a 5% estimated false discovery rate, including many previously identified causal effects. We also identified several novel effects, including protective effects of higher BMI on a set of psychosocial traits, identified initially in our preliminary MR-pheWAS and replicated in an independent subset of UK Biobank. Such associations need replicating in an independent sample.

epidemiology↗

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

Imprinted loci may be more widespread in humans than previously appreciated and enable limited assignment of parental allelic transmissions in unrelated individuals

Genomic imprinting is an epigenetic mechanism leading to parent-of-origin dependent gene expression. So far, the precise number of imprinted genes in humans is uncertain. In this study, we leveraged genome-wide DNA methylation in whole blood measured longitudinally at 3 time points (birth, childhood and adolescence) and GWAS data in 740 Mother-Child duos from the Avon Longitudinal Study of Parents and Children (ALSPAC) to systematically identify imprinted loci. We reasoned that cis-meQTLs at genomic regions that were imprinted would show strong evidence of parent-of-origin associations with DNA methylation, enabling the detection of imprinted regions. Using this approach, we identified genome-wide significant cis-meQTLs that exhibited parent-of-origin effects (POEs) at 35 novel and 50 known imprinted regions (10-10< P <10-300). Among the novel loci, we observed signals near genes implicated in cardiovascular disease (PCSK9), and Alzheimers disease (CR1), amongst others. Most of the significant regions exhibited imprinting patterns consistent with uniparental expression, with the exception of twelve loci (including the IGF2, IGF1R, and IGF2R genes), where we observed a bipolar-dominance pattern. POEs were remarkably consistent across time points and were so strong at some loci that methylation levels enabled good discrimination of parental transmissions at these and surrounding genomic regions. The implication is that parental allelic transmissions could be modelled at many imprinted (and linked) loci and hence POEs detected in GWAS of unrelated individuals given a combination of genetic and methylation data. Our results indicate that modelling POEs on DNA methylation is effective to identify loci that may be affected by imprinting.

genomics↗

bioRxiv2017

Epigenome-Wide Association Study Of Asthma And Wheeze In Childhood And Adolescence

Asthma heritability has only been partially explained by genetic variants and is known to be sensitive to environmental factors, implicating epigenetic modifications such as DNA methylation in its pathogenesis.\n\nUsing data collected in the Avon Longitudinal Study of Parents and Children (ALSPAC), we assessed associations of asthma and wheeze with DNA methylation at 7.5 years and 16.5 years, at over 450,000 CpG sites in DNA from the peripheral blood of approx. 1000 participants. We used Mendelian randomization (MR), a method of causal inference that uses genetic variants as instrumental variables, to infer the direction of association between DNA methylation and asthma.\n\nWe identified 302 CpGs associated with current asthma status (FDR-adjusted P-value <0.05) and 445 with current wheeze status at 7.5 years, with substantial overlap between the two. Genes annotated to the 302 associated CpGs were enriched for pathways related to movement of cellular/subcellular components, locomotion, interleukin-4 production and eosinophil migration. All associations attenuated when adjusted for eosinophil and neutrophil cell count estimates. At 16.5 years, two sites were associated with current asthma after adjustment for cell counts. The CpGs mapped to the AP2A2 and IL5RA genes, with a -2.32 [95% CI -1.47,-3.18] and -2.49 [95% CI -1.56,-3.43] change in percentage methylation in asthma cases respectively. Two-sample bi-directional MR indicated a causal effect of asthma on DNA methylation at several CpG sites at 7.5 years. However, associations did not persist after adjustment for multiple testing. There was no evidence of a causal effect of asthma on DNA methylation at either of the two CpG sites at 16.5 years.\n\nThe majority of observed associations are driven by higher eosinophil cell counts in asthma cases, acting as an intermediate phenotype, with important implications for future studies of DNA methylation in atopic diseases.

epidemiology↗

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

Metabolic profiling of adiponectin levels in adults: Mendelian randomization analysis

BackgroundAdiponectin, a circulating adipocyte-derived protein has insulin-sensitizing, anti-inflammatory, anti-atherogenic, and cardiomyocyte-protective properties in animal models. However, the systemic effects of adiponectin in humans are unknown.\n\nObjectivesOur aims were to define the metabolic profile associated with higher blood adiponectin concentration and investigate whether variation in adiponectin concentration affects the systemic metabolic profile.\n\nMethodsWe applied multivariable regression in up to 5,906 adults and Mendelian randomization (using cis-acting genetic variants in the vicinity of the adiponectin gene as instrumental variables) for analysing the causal effect of adiponectin in the metabolic profile of up to 38,058 adults. Participants were largely European from six longitudinal studies and one genome-wide association consortium.\n\nResultsIn the multivariable regression analyses, higher circulating adiponectin was associated with higher HDL lipids and lower VLDL lipids, glucose levels, branched-chain amino acids, and inflammatory markers. However, these findings were not supported by Mendelian randomization analyses for most metabolites. Findings were consistent between sexes and after excluding high risk groups (defined by age and occurrence of previous cardiovascular event) and one study with admixed population.\n\nConclusionOur findings indicate that blood adiponectin concentration is more likely to be an epiphenomenon in the context of metabolic disease than a key determinant.

epidemiology↗

bioRxiv2017

Physical Activity Phenotyping With Activity Bigrams, And Their Association With BMI

BackgroundAnalysis of physical activity usually focuses on a small number of summary statistics derived from accelerometer recordings: average counts per minute, and the proportion of time spent in moderate-vigorous physical activity or in sedentary behaviour. We show how bigrams, a concept from the field of text mining, can be used to describe how a persons activity levels change across (brief) time points. These variables can, for instance, differentiate between two people with the same time in moderate activity, where one person often stays in moderate activity from one moment to the next and the other does not.\n\nMethodsWe use data on 4810 participants of the Avon Longitudinal Study of Parents and Children (ALSPAC). We generate a profile of bigram frequencies for each participant and test the association of each frequency with body mass index (BMI), as an exemplar.\n\nResultsWe found several associations between changes in bigram frequencies and BMI. For instance, a 1 standard deviation decrease in the number of adjacent minutes in sedentary then moderate activity (or vice versa), with a corresponding increase in the number of adjacent minutes in moderate then vigorous activity (or vice versa), was associated with a 2.36 kg/m2 lower BMI [95% CI: -3.47, -1.26], after accounting for the time spent at sedentary, low, moderate and vigorous activity.\n\nConclusionsActivity bigrams are novel variables that capture how a persons activity changes from one moment to the next. These variables can be used to investigate how sequential activity patterns associate with other traits.\n\nKey MessagesO_LIEpidemiologists typically use only a small number of variables to analyse the association of physical activity with other traits, such as the average counts per minute and the proportion of time spent in moderate-vigorous physical activity or being sedentary.\nC_LIO_LIWe demonstrate how activity bigrams can be used as a set of interpretable variables describing how a persons activity levels change from one moment to the next.\nC_LIO_LITesting the association of activity bigrams with exposures or outcomes can help us gain further understanding of how physical activity is associated with other traits; with further research they might provide evidence for more refined public health advice.\nC_LI

epidemiology↗

bioRxiv2016

MR-Base: a platform for systematic causal inference across the phenome using billions of genetic associations

Published genetic associations can be used to infer causal relationships between phenotypes, bypassing the need for individual-level genotype or phenotype data. We have curated complete summary data from 1094 genome-wide association studies (GWAS) on diseases and other complex traits into a centralised database, and developed an analytical platform that uses these data to perform Mendelian randomization (MR) tests and sensitivity analyses (MR-Base, http://www.mrbase.org). Combined with curated data of published GWAS hits for phenomic measures, the MR-Base platform enables millions of potential causal relationships to be evaluated. We use the platform to predict the impact of lipid lowering on human health. While our analysis provides evidence that reducing LDL-cholesterol, lipoprotein(a) or triglyceride levels reduce coronary disease risk, it also suggests causal effects on a number of other non-vascular outcomes, indicating potential for adverse-effects or drug repositioning of lipid-lowering therapies.

epidemiology↗