Biology subjects

Relton, C. L.

Publications and source records attributed to Relton, C. L..

At least 19 recordsLinked to original sources

bioRxiv2022

Epigenetic markers of adverse lifestyle identified among night shift workers

BackgroundEpigenetic changes in the form of DNA methylation (DNAm) may act as biological markers of risk factors or adverse health states. We investigated associations between night shift work and established DNAm predictors of lifestyle, and compared them with those observed between night shift work and self-reported or conventionally-measured phenotypes. MethodsIn two cohort studies, Generation Scotland (GS) (n=7,028) and Understanding Society (UKHLS) (n=1,175), we evaluated associations between night shift work and four lifestyle factors (body mass index, smoking, alcohol, education) using both conventionally-measured phenotypes and DNA methylation-based scores proxying the phenotypes. DNA methylation-based measures of biological ageing were also generated using six established "epigenetic clocks". Meta-analysis of GS and UKHLS results was conducted using inverse-variance weighted fixed effects. ResultsNight shift work was associated with higher BMI (0.79; 95%CI 0.02, 1.56; p=0.04) and lower education (-0.18; -0.30, -0.07; p=0.002). There was weak evidence of association between night shift work and DNAm scores for smoking (0.06, -0.03, 0.15; p=0.18) and education (-0.24; -0.49, 0.01; p=0.06) in fully adjusted models. Two of the epigenetic age measures demonstrated higher age acceleration among night shift workers (0.80; 0.42, 1.18; p<0.001 for GrimAge and 0.46; 0.00, 0.92; p=0.05 for PhenoAge). ConclusionsNight shift work is associated with phenotypic and DNAm-based measures of lower education. Night shift work was also related to DNAm predictors of smoking and ageing.

genetics↗

bioRxiv2020

Epigenome-wide change and variation in DNA methylation from birth to late adolescence

DNA methylation (DNAm) is known to play a pivotal role in childhood health and development, but a comprehensive characterization of genome-wide DNAm trajectories across this age period is currently lacking. We have therefore performed a series of epigenome-wide association studies in 5,019 blood samples collected at multiple time-points from birth to late adolescence from 2,348 participants of two large independent cohorts. DNAm profiles of autosomal CpG sites (CpGs) were generated using the Illumina Infinium HumanMethylation450 BeadChip. Change over time was widespread, observed at over one-half (53%) of CpGs. In most cases DNAm was decreasing (36% of CpGs). Inter-individual variation in linear trajectories was similarly widespread (27% of CpGs). Evidence for nonlinear change and inter-individual variation in nonlinear trajectories was somewhat less common (11% and 8% of CpGs, respectively). Very little inter-individual variation in change was explained by sex differences (0.4% of CpGs) even though sex-specific DNAm was observed at 5% of CpGs. DNAm trajectories were distributed non-randomly across the genome. For example, CpGs with decreasing DNAm were enriched in gene bodies and enhancers and were annotated to genes enriched in immune-developmental functions. By contrast, CpGs with increasing DNAm were enriched in promoter regions and annotated to genes enriched in neurodevelopmental functions. These findings depict a methylome undergoing widespread and often nonlinear change throughout childhood. They support a developmental role for DNA methylation that extends beyond birth into late adolescence and has implications for understanding life-long health and disease. DNAm trajectories can be visualized at http://epidelta.mrcieu.ac.uk.

genomics↗

bioRxiv2019

The association of DNA methylation with body mass index: distinguishing between predictors and biomarkers

BackgroundDNA methylation is associated with body mass index (BMI), but it is not clear if methylation scores are biomarkers for extant BMI, or predictive of future BMI. Here we explore the causal nature and predictive utility of DNA methylation measured in peripheral blood with BMI and cardiometabolic traits. MethodsAnalyses were conducted across the life course using the ARIES cohort of mothers (n=792) and children (n=906), for whom DNA methylation and genetic profiles and BMI at multiple time points (3 in children at birth, in childhood and in adolescence, 2 in mothers during pregnancy and in middle age) were available. Genetic and DNA methylation scores for BMI were derived using published associations between BMI and DNA methylation and genotype. Causal relationships between methylation and BMI were assessed using Mendelian randomisation and cross-lagged models. ResultsThe DNA methylation scores in adult women explained 10% of extant BMI variance. However, less extant variance was explained by scores generated in the same women during pregnancy (2% BMI variance) and in older children (15-17 years; 3% BMI variance). Similarly, little extant variance was explained in younger children (at birth and at 7 years; 1% and 2%, respectively). These associations remained following adjustment for smoking exposure and education levels. The DNA methylation score was found to be a poor predictor of future BMI using linear and cross-lagged models, suggesting that DNA methylation variation does not cause later variation in BMI. However, there was some evidence to suggest that BMI is predictive of later DNA methylation. Mendelian randomisation analyses also support this direction of effect, although evidence is weak. Finally, we find that DNA methylation scores for BMI are associated with extant cardiometabolic traits independently of BMI and genetic score. ConclusionThe age-specific nature of DNA methylation associations with BMI, lack of causal relationship, and limited predictive ability of future BMI, indicate that DNA methylation is likely influenced by BMI and might more accurately be considered a biomarker of BMI and related outcomes than a predictor. Future epigenome-wide association studies may benefit from further examining associations between early DNA methylation and later health outcomes.

genetics↗

bioRxiv2019

Association between DNA methylation and ADHD symptoms from birth to school age: A prospective meta-analysis

Attention-deficit and hyperactivity disorder (ADHD) is a common childhood disorder with a substantial genetic component. However, the extent to which epigenetic mechanisms play a role in the etiology of the disorder is not known. We performed epigenome-wide association studies (EWAS) within the Pregnancy And Childhood Epigenetics (PACE) Consortium to identify DNA methylation sites associated with ADHD symptoms at two methylation assessment periods: birth and school-age. We examined associations of DNA methylation in cord blood with repeatedly assessed ADHD symptoms (age range 4-15 years) in 2477 children from five cohorts and DNA methylation at school-age with concurrent ADHD symptoms (age 7-11 years) in 2374 children from ten cohorts. CpGs identified with nominal significance (p<0.05) in either of the EWAS were correlated between timepoints ({rho}=0.30), suggesting overlap in associations, however, top signals were very different. At birth, we identified nine CpGs that were associated with later ADHD symptoms (P<1*10-7), including ERC2 and CREB5. Peripheral blood DNA methylation at one of these CpGs (cg01271805 located in the promotor region of ERC2, which regulates neurotransmitter release) was previously associated with brain methylation. Another (cg25520701) lies within the gene body of CREB5, which was associated with neurite outgrowth and an ADHD diagnosis in previous studies. In contrast, at school-age, no CpGs were associated with ADHD with P<1*10-7. In conclusion, we found evidence in this study that DNA methylation at birth is associated with ADHD. Future studies are needed to confirm the utility of methylation variation as biomarker and its involvement in causal pathways.

genetics↗

bioRxiv2019

Association between breastfeeding and DNA methylation over the life course: findings from the Avon Longitudinal Study of Parents and Children (ALSPAC)

BackgroundBreastfeeding is associated with short and long-term health benefits. Long-term effects might be mediated by epigenetic mechanisms, yet a recent systematic review indicated that the literature on this topic is scarce. We performed the first epigenome-wide association study of infant feeding, comparing breastfed vs non-breastfed children. We measured DNA methylation in children from peripheral blood collected in childhood (age 7, N=640) and adolescence (age 15-17, N=709) within the Accessible Resource for Integrated Epigenomic Studies (ARIES) project, part of the larger Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Cord blood methylation (N=702) was used as a negative control for potential pre-natal residual confounding.\n\nResultsTwo differentially-methylated sites presented directionally-consistent associations with breastfeeding at ages 7 and 15-17, but not at birth. Twelve differentially-methylated regions in relation to breastfeeding were identified, and for three of them there was evidence of directional concordance between ages 7 and 15-17, but not between birth and age 7.\n\nConclusionsOur findings indicate that DNA methylation in childhood and adolescence may be predicted by breastfeeding, but further studies with sufficiently large samples for replication are required to identify robust associations.

genetics↗

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↗

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 causal relationships between sleep traits and risk of breast cancer: a Mendelian randomization study

ObjectiveTo examine whether sleep traits have a causal effect on risk of breast cancer.\n\nDesignMultivariable regression, one- and two-sample Mendelian randomization.\n\nSettingThe UK Biobank prospective cohort study and the Breast Cancer Association Consortium (BCAC) case-control genome-wide association study.\n\nParticipants156,848 women in the multivariable regression and one-sample Mendelian randomization analysis in UK Biobank (7,784 with a breast cancer diagnosis) and 122,977 breast cancer cases and 105,974 controls from BCAC in the two-sample Mendelian randomization analysis.\n\nExposuresSelf-reported chronotype (morning/evening preference), insomnia symptoms and sleep duration in multivariable regression, and genetic variants robustly associated with these sleep traits.\n\nMain outcome measuresBreast cancer (prevalent and incident cases in UK Biobank, prevalent cases only in BCAC).\n\nResultsIn multivariable regression analysis using data on breast cancer incidence in UK Biobank, morning preference was inversely associated with breast cancer (HR 0.95, 95% CI 0.93, 0.98 per category increase) while there was little evidence for an association with sleep duration and insomnia symptoms. Using 341 single nucleotide polymorphisms (SNPs) associated with chronotype, 91 SNPs associated sleep duration and 57 SNPs associated with insomnia symptoms, one-sample MR analysis in UK Biobank provided some supportive evidence for a protective effect of morning preference on breast cancer risk (HR 0.85, 95% 0.70, 1.03 per category increase) but imprecise estimates for sleep duration and insomnia symptoms. Two-sample MR using data from BCAC supported findings for a protective effect of morning preference (OR 0.88, 95% CI 0.82, 0.93 per category increase) and adverse effect of increased sleep duration (OR 1.19, 95% CI 1.02, 1.39 per hour increase) on breast cancer (both estrogen receptor positive and negative), while there was inconsistent evidence for insomnia symptoms. Results were largely robust to sensitivity analyses accounting for horizontal pleiotropy.\n\nConclusionsWe found consistent evidence for a protective effect of morning preference and suggestive evidence for an adverse effect of sleep duration on breast cancer risk.

epidemiology↗

bioRxiv2018

Cleft lip/palate and educational attainment: cause, consequence, or correlation? A Mendelian randomization study

ImportancePrevious studies have found that children born with a non-syndromic form of cleft lip and/or palate have lower-than-average educational attainment. These differences could be due to a genetic predisposition to low intelligence and academic performance, factors arising due to the cleft phenotype (such as school absence, social stigmatization and impaired speech and language development), or confounding by the prenatal environment. A clearer understanding of this mechanism will inform development of interventions to improve educational attainment in individuals born with a cleft, which could have wide-ranging knock-on effects on their quality of life.\n\nObjectiveTo assess evidence for the hypothesis that common variant genetic liability to non-syndromic cleft lip with or without cleft palate (nsCL/P) influences educational attainment.\n\nDesignUsing summary data from genome-wide association studies (GWAS), we performed Linkage Disequilibrium (LD)-score regression and two-sample Mendelian randomization to evaluate the relationship between genetic liability to nsCL/P (GWAS n=3,987) and educational attainment (GWAS n=766,345), and intelligence (GWAS n=257,828).\n\nResultsThere was little evidence for shared genetic aetiology between nsCL/P and educational attainment (rg -0.03, 95% CI -0.14 to 0.08, P 0.58; {beta}MR 0.002, 95% CI -0.001 to 0.005, P 0.417) or intelligence (rg -0.01, 95% CI -0.12 to 0.10, P 0.85; {beta}MR 0.002, 95% CI -0.010 to 0.014, P 0.669).\n\nConclusions and relevanceCommon genetic variants are unlikely to predispose individuals born with nsCL/P to low educational attainment or intelligence. This information will help tailor clinical-, school-, social- and family-level interventions to improve educational attainment in this group.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSDo children born with a non-syndromic cleft lip with or without palate (nsCL/P) have lower-than average academic achievement because of an underlying genetic predisposition to educational attainment and/or intelligence?\n\nFindingsThere was little evidence for shared common variant genetic correlation between nsCL/P, educational attainment and intelligence.\n\nMeaningCommon genetic variants are unlikely to predispose individuals born with nsCL/P to low educational attainment or intelligence. This information will help tailor clinical-, school-, social- and family-level interventions to improve educational attainment in this group.

genetics↗

bioRxiv2018

DNA methylation links prenatal smoking exposure to later life health outcomes in offspring.

Maternal smoking during pregnancy is associated with adverse offspring health outcomes across their life course. We hypothesize that DNA methylation is a potential mediator of this relationship. To test this, we examined the association of prenatal maternal smoking with DNA methylation in 2,821 individuals (age 16 to 48 years) from five prospective birth cohort studies and perform Mendelian randomization and mediation analyses to assess, whether methylation markers have causal effects on disease outcomes in the offspring. We identify 69 differentially methylated CpGs in 36 genomic regions (P < 1x10-7), and show that DNA methylation may represent a biological mechanism through which maternal smoking is associated with increased risk of psychiatric morbidity in the exposed offspring.

epidemiology↗

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

Predicting cellular aging following exposure to adversity: Does accumulation, recency, or developmental timing of exposure matter?

Exposure to adversity has been linked to accelerated biological aging, which in turn has been shown to predict numerous health problems, including neuropsychiatric disease. In recent years, measures of DNA methylation-based epigenetic age - known as \"epigenetic clocks\" - have been used to estimate accelerated epigenetic aging. Yet, few studies have been conducted in children. Using data from the Avon Longitudinal Study of Parents and Children (n=973), we explored the prospective association between repeated measures of childhood exposure to seven types of adversity on epigenetic age assessed at age 7 using the Horvath and Hannum epigenetic clocks. With a Least Angle Regression variable selection procedure, we evaluated the effects of the developmental timing, accumulation, and recency of adversity exposure. We found that exposure to sexual or physical abuse, financial stress, or neighborhood disadvantage during sensitive periods in early and middle childhood best explained variability in the deviation of the Hannum epigenetic age from the chronological age. Secondary sex-stratified analyses identified particularly strong sensitive period effects, such that by age 7, girls who were exposed to abuse at age 3.5 were biologically older than their unexposed peers by almost 2 months. These effects were undetected in analyses comparing children \"exposed\" versus \"unexposed\" to adversity. Our results suggest that exposure to adversity may alter methylation processes in ways that perturb normal cellular aging and that these effects may be heightened during sensitive periods in development. Research is needed to demonstrate the effect of accelerated epigenetic aging on negative health outcomes following childhood adversity exposure.

genetics↗

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↗

bioRxiv2018

Sensitive periods for the effect of childhood adversity on DNA methylation: Results from a prospective, longitudinal study

BackgroundExposure to \"early life\" adversity is known to predict DNA methylation (DNAm) patterns that may be related to prolonged psychiatric risk. However, few studies have investigated whether adversity has time-dependent effects based on the age at exposure.\n\nMethodsUsing a two-stage structured life course modeling approach (SLCMA), we tested the hypothesis that there are sensitive periods when adversity induced greater DNAm changes. We tested this hypothesis in relation to two alternative explanations: an accumulation hypothesis, in which the effect of adversity on DNAm increases with the number of occasions exposed, regardless of timing, and a recency model, in which the effect of adversity is stronger for more proximal events. Data came from the Accessible Resource for Integrated Epigenomics Studies (ARIES), a subsample of mother-child pairs from the Avon Longitudinal Study of Parents and Children (ALSPAC; n=670-776).\n\nResultsAfter covariate adjustment and multiple testing correction, we identified 40 CpG sites that were differentially methylated at age 7 following exposure to adversity. Most loci (n=32) were predicted by the timing of adversity, namely exposures during infancy. Neither the accumulation nor recency of the adversity explained considerable variability in DNAm. A standard EWAS of lifetime exposure (vs. no exposure) failed to detect these associations.\n\nConclusionsThe developmental timing of adversity explains more variability in DNAm than the accumulation or recency of exposure. Infancy appears to be a sensitive period when exposure to adversity predicts differential DNAm patterns. Classification of individuals as exposed vs. unexposed to \"early life\" adversity may dilute observed effects.

genetics↗

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↗

bioRxiv2017

Causal inference in cancer epidemiology: what is the role of Mendelian randomization?

Observational epidemiological studies are prone to confounding, measurement error, and reverse causation, undermining their ability to generate reliable causal estimates of the effect of risk factors to inform cancer prevention and treatment strategies. Mendelian randomization (MR) is an analytical approach that uses genetic variants to proxy potentially modifiable exposures (e.g. environmental factors, biological traits, and druggable pathways) to permit robust causal inference of the effects of these exposures on diseases and their outcomes. MR has seen widespread adoption within population health research in cardio-metabolic disease, but also holds much promise for identifying possible interventions (e.g., dietary, behavioural, or pharmacological) for cancer prevention and treatment. However, some methodological and conceptual challenges in the implementation of MR are particularly pertinent when applying this method to cancer aetiology and prognosis, including reverse causation arising from disease latency and selection bias in studies of cancer progression. These issues must be carefully considered to ensure appropriate design, analysis, and interpretation of such studies.\n\nIn this review, we provide an overview of the key principles and assumptions of MR focusing on applications of this method to the study of cancer aetiology and prognosis. We summarize recent studies in the cancer literature that have adopted a MR framework to highlight strengths of this approach compared to conventional epidemiological studies. Lastly, limitations of MR and recent methodological developments to address them are discussed, along with the translational opportunities they present to inform public health and clinical interventions in cancer.

epidemiology↗

bioRxiv2017

Circulating selenium and prostate cancer risk: a Mendelian randomization analysis

In the Selenium and Vitamin E Cancer Prevention Trial (SELECT), selenium supplementation (causing a median 114 g/L increase in circulating selenium) did not lower overall prostate cancer risk, but increased risk of high-grade prostate cancer and type 2 diabetes. Mendelian randomization analysis uses genetic variants to proxy modifiable risk factors and can strengthen causal inference in observational studies. We constructed a genetic risk score comprising eleven single-nucleotide polymorphisms robustly (P<5x10-8) associated with circulating selenium in genome-wide association studies. In a Mendelian randomization analysis of 72,729 men in the PRACTICAL Consortium (44,825 cases, 27,904 controls), 114 g/L higher genetically-elevated circulating selenium was not associated with prostate cancer (OR: 1.01; 95% CI: 0.89-1.13). Concordant with findings from SELECT, selenium was weakly associated with advanced (including high-grade) prostate cancer (OR: 1.21; 95% CI: 0.98-1.49) and type 2 diabetes (OR: 1.18; 95% CI: 0.97-1.43; in a type 2 diabetes GWAS meta-analysis with up to 49,266 cases, 249,906 controls). Mendelian randomization mirrored the outcome of selenium supplementation in SELECT and may offer an approach for the prioritization of interventions for follow-up in large-scale randomized controlled trials.

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↗