Publications by authors named "Tom G Richardson"

54 Publications

Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation.

Nat Genet 2021 Sep 6;53(9):1311-1321. Epub 2021 Sep 6.

Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia.

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15-17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype-phenotype map than previously anticipated.
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http://dx.doi.org/10.1038/s41588-021-00923-xDOI Listing
September 2021

Mendelian Randomization Analyses Suggest Childhood Body Size Indirectly Influences End Points From Across the Cardiovascular Disease Spectrum Through Adult Body Size.

J Am Heart Assoc 2021 Sep 1;10(17):e021503. Epub 2021 Sep 1.

MRC Integrative Epidemiology Unit Population Health Sciences Bristol Medical School University of Bristol United Kingdom.

Background Obesity is associated with long-term health consequences including cardiovascular disease. Separating the independent effects of childhood and adulthood obesity on cardiovascular disease risk is challenging as children with obesity typically remain overweight throughout the lifecourse. Methods and Results This study used 2-sample univariable and multivariable Mendelian randomization to estimate the effect of childhood body size both independently and after accounting for adult body size on 12 endpoints across the cardiovascular disease disease spectrum. Univariable analyses identified strong evidence of a total effect between genetically predicted childhood body size and increased risk of atherosclerosis, atrial fibrillation, coronary artery disease, heart failure, hypertension, myocardial infarction, peripheral artery disease, and varicose veins. However, evidence of a direct effect was weak after accounting for adult body size using multivariable Mendelian randomization, suggesting that childhood body size indirectly increases risk of these 8 disease outcomes via the pathway involving adult body size. Conclusions These findings suggest that the effect of genetically predicted childhood body size on the cardiovascular disease outcomes analyzed in this study are a result of larger body size persisting into adulthood. Further research is necessary to ascertain the critical timepoints where, if ever, the detrimental impact of obesity initiated in early life begins to become immutable.
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http://dx.doi.org/10.1161/JAHA.121.021503DOI Listing
September 2021

Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging.

Genome Biol 2021 06 29;22(1):194. Epub 2021 Jun 29.

Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA.

Background: Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field.

Results: Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels.

Conclusion: This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.
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http://dx.doi.org/10.1186/s13059-021-02398-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8243879PMC
June 2021

The causal effects of serum lipids and apolipoproteins on kidney function: multivariable and bidirectional Mendelian-randomization analyses.

Int J Epidemiol 2021 Jun 21. Epub 2021 Jun 21.

K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.

Background: The causal nature of the observed associations between serum lipids and apolipoproteins and kidney function are unclear.

Methods: Using two-sample and multivariable Mendelian randomization (MR), we examined the causal effects of serum lipids and apolipoproteins on kidney function, indicated by the glomerular-filtration rate estimated using creatinine (eGFRcrea) or cystatin C (eGFRcys) and the urinary albumin-to-creatinine ratio (UACR). We obtained lipid- and apolipoprotein-associated genetic variants from the Global Lipids Genetics Consortium (n = 331 368) and UK Biobank (n = 441 016), respectively, and kidney-function markers from the Trøndelag Health Study (HUNT; n = 69 736) and UK Biobank (n = 464 207). The reverse causal direction was examined using variants associated with kidney-function markers selected from recent genome-wide association studies.

Results: There were no strong associations between genetically predicted lipid and apolipoprotein levels with kidney-function markers. Some, but inconsistent, evidence suggested a weak association of higher genetically predicted atherogenic lipid levels [indicated by low-density lipoprotein cholesterol (LDL-C), triglycerides and apolipoprotein B] with increased eGFR and UACR. For high-density lipoprotein cholesterol (HDL-C), results differed between eGFRcrea and eGFRcys, but neither analysis suggested substantial effects. We found no clear evidence of a reverse causal effect of eGFR on lipid or apolipoprotein traits, but higher UACR was associated with higher LDL-C, triglyceride and apolipoprotein B levels.

Conclusion: Our MR estimates suggest that serum lipid and apolipoprotein levels do not cause substantial changes in kidney function. A possible weak effect of higher atherogenic lipids on increased eGFR and UACR warrants further investigation. Processes leading to higher UACR may lead to more atherogenic lipid levels.
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http://dx.doi.org/10.1093/ije/dyab014DOI Listing
June 2021

Triangulating molecular evidence to prioritize candidate causal genes at established atopic dermatitis loci.

J Invest Dermatol 2021 Apr 23. Epub 2021 Apr 23.

MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK. Electronic address:

Genome-wide association studies for atopic dermatitis (AD) have identified 25 reproducible loci. We attempt to prioritize candidate causal genes at these loci using extensive molecular resources compiled into a bioinformatics pipeline. We identified a list of 103 molecular resources for AD aetiology, including expression, protein and DNA methylation QTL datasets in skin or immune-relevant tissues which were tested for overlap with GWAS signals. This was combined with functional annotation using regulatory variant prediction, and features such as promoter-enhancer interactions, expression studies and variant fine-mapping. For each gene at each locus, we condensed the evidence into a prioritization score. Across the investigated loci, we detected significant enrichment of genes with adaptive immune regulatory function and epidermal barrier formation among the top prioritized genes. At 8 loci, we were able to prioritize a single candidate gene (IL6R, ADO, PRR5L, IL7R, ETS1, INPP5D, MDM1, TRAF3). In addition, at 6 of the 25 loci, our analysis prioritizes less familiar candidates (SLC22A5, IL2RA, MDM1, DEXI, ADO, STMN3). Our analysis provides support for previously implicated genes at several AD GWAS loci, as well as evidence for plausible additional candidates at others, which may represent potential targets for drug discovery.
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http://dx.doi.org/10.1016/j.jid.2021.03.027DOI Listing
April 2021

Evaluating the direct effects of childhood adiposity on adult systemic metabolism: a multivariable Mendelian randomization analysis.

Int J Epidemiol 2021 Mar 30. Epub 2021 Mar 30.

MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.

Background: Individuals who are obese in childhood have an elevated risk of disease in adulthood. However, whether childhood adiposity directly impacts intermediate markers of this risk, independently of adult adiposity, is unclear. In this study, we have simultaneously evaluated the effects of childhood and adulthood body size on 123 systemic molecular biomarkers representing multiple metabolic pathways.

Methods: Two-sample Mendelian randomization (MR) was conducted to estimate the causal effect of childhood body size on a total of 123 nuclear magnetic resonance-based metabolic markers using summary genome-wide association study (GWAS) data from up to 24 925 adults. Multivariable MR was then applied to evaluate the direct effects of childhood body size on these metabolic markers whilst accounting for adult body size. Further MR analyses were undertaken to estimate the potential mediating effects of these circulating metabolites on the risk of coronary artery disease (CAD) in adulthood using a sample of 60 801 cases and 123 504 controls.

Results: Univariable analyses provided evidence that childhood body size has an effect on 42 of the 123 metabolic markers assessed (based on P < 4.07 × 10-4). However, the majority of these effects (35/42) substantially attenuated when accounting for adult body size using multivariable MR. We found little evidence that the biomarkers that were potentially influenced directly by childhood body size (leucine, isoleucine and tyrosine) mediate this effect onto adult disease risk. Very-low-density lipoprotein markers provided the strongest evidence of mediating the long-term effect of adiposity on CAD risk.

Conclusions: Our findings suggest that childhood adiposity predominantly exerts its detrimental effect on adult systemic metabolism along a pathway that involves adulthood body size.
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http://dx.doi.org/10.1093/ije/dyab051DOI Listing
March 2021

Childhood obesity and multiple sclerosis: A Mendelian randomization study.

Mult Scler 2021 Mar 22:13524585211001781. Epub 2021 Mar 22.

Centre for Clinical Epidemiology, Department of Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada/Department of Human Genetics, McGill University, Montreal, QC, Canada/Department of Medicine, McGill University Montreal, QC, Canada/Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada/Department of Twin Research & Genetic Epidemiology, King's College London, London, UK.

Background: Higher childhood body mass index (BMI) has been associated with an increased risk of multiple sclerosis (MS).

Objective: To evaluate whether childhood BMI has a causal influence on MS, and whether this putative effect is independent from early adult obesity and pubertal timing.

Methods: We performed Mendelian randomization (MR) using summary genetic data on 14,802 MS cases and 26,703 controls. Large-scale genome-wide association studies provided estimates for BMI in childhood ( = 47,541) and adulthood ( = 322,154). In multivariable MR, we examined the direct effects of each timepoint and further adjusted for age at puberty. Findings were replicated using the UK Biobank ( = 453,169).

Results: Higher genetically predicted childhood BMI was associated with increased odds of MS (odds ratio (OR) = 1.26/SD BMI increase, 95% confidence interval (CI): 1.07-1.50). However, there was little evidence of a direct effect after adjusting for adult BMI (OR = 1.03, 95% CI: 0.70-1.53). Conversely, the effect of adult BMI persisted independent of childhood BMI (OR = 1.43; 95% CI: 1.01-2.03). The addition of age at puberty did not alter the findings. UK Biobank analyses showed consistent results. Sensitivity analyses provided no evidence of pleiotropy.

Conclusion: Genetic evidence supports an association between childhood obesity and MS susceptibility, mediated by persistence of obesity into early adulthood but independent of pubertal timing.
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http://dx.doi.org/10.1177/13524585211001781DOI Listing
March 2021

Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development.

Nat Rev Cardiol 2021 06 11;18(6):435-453. Epub 2021 Mar 11.

Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK.

Drug development in cardiovascular disease is stagnating, with lack of efficacy and adverse effects being barriers to innovation. Human genetics can provide compelling evidence of causation through approaches such as Mendelian randomization, with genetic support for causation increasing the probability of a clinical trial succeeding. Mendelian randomization applied to quantitative traits can identify risk factors for disease that are both causal and amenable to therapeutic modification. However, important differences exist between genetic investigations of a biomarker (such as HDL cholesterol) and a drug target aimed at modifying the same biomarker of interest (such as cholesteryl ester transfer protein), with implications for the methodology, interpretation and application of Mendelian randomization to drug development. Differences include the comparative nature of the genetic architecture - that is, biomarkers are typically polygenic, whereas protein drug targets are influenced by either cis-acting or trans-acting genetic variants - and the potential for drug targets to show disease associations that might differ from those of the biomarker that they are intended to modify (target-mediated pleiotropy). In this Review, we compare and contrast the use of Mendelian randomization to evaluate potential drug targets versus quantitative traits. We explain how genetic epidemiological studies can be used to assess the aetiological roles of biomarkers in disease and to prioritize drug targets, including designing their evaluation in clinical trials.
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http://dx.doi.org/10.1038/s41569-020-00493-1DOI Listing
June 2021

The use of negative control outcomes in Mendelian randomization to detect potential population stratification.

Int J Epidemiol 2021 Aug;50(4):1350-1361

MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.

A key assumption of Mendelian randomization (MR) analysis is that there is no association between the genetic variants used as instruments and the outcome other than through the exposure of interest. One way in which this assumption can be violated is through population stratification, which can introduce confounding of the relationship between the genetic variants and the outcome and so induce an association between them. Negative control outcomes are increasingly used to detect unobserved confounding in observational epidemiological studies. Here we consider the use of negative control outcomes in MR studies to detect confounding of the genetic variants and the exposure or outcome. As a negative control outcome in an MR study, we propose the use of phenotypes which are determined before the exposure and outcome but which are likely to be subject to the same confounding as the exposure or outcome of interest. We illustrate our method with a two-sample MR analysis of a preselected set of exposures on self-reported tanning ability and hair colour. Our results show that, of the 33 exposures considered, genome-wide association studies (GWAS) of adiposity and education-related traits are likely to be subject to population stratification that is not controlled for through adjustment, and so any MR study including these traits may be subject to bias that cannot be identified through standard pleiotropy robust methods. Negative control outcomes should therefore be used regularly in MR studies to detect potential population stratification in the data used.
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http://dx.doi.org/10.1093/ije/dyaa288DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8407870PMC
August 2021

Genetic predictors of participation in optional components of UK Biobank.

Nat Commun 2021 02 9;12(1):886. Epub 2021 Feb 9.

MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK.

Large studies such as UK Biobank are increasingly used for GWAS and Mendelian randomization (MR) studies. However, selection into and dropout from studies may bias genetic and phenotypic associations. We examine genetic factors affecting participation in four optional components in up to 451,306 UK Biobank participants. We used GWAS to identify genetic variants associated with participation, MR to estimate effects of phenotypes on participation, and genetic correlations to compare participation bias across different studies. 32 variants were associated with participation in one of the optional components (P < 6 × 10), including loci with links to intelligence and Alzheimer's disease. Genetic correlations demonstrated that participation bias was common across studies. MR showed that longer educational duration, older menarche and taller stature increased participation, whilst higher levels of adiposity, dyslipidaemia, neuroticism, Alzheimer's and schizophrenia reduced participation. Our effect estimates can be used for sensitivity analysis to account for selective participation biases in genetic or non-genetic analyses.
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http://dx.doi.org/10.1038/s41467-021-21073-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7873270PMC
February 2021

Evaluating the effects of cardiometabolic exposures on circulating proteins which may contribute to severe SARS-CoV-2.

EBioMedicine 2021 Feb 3;64:103228. Epub 2021 Feb 3.

Medical Research Council Integrative Epidemiology Unit (MRC IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom.

Background: Developing insight into the pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is of critical importance to overcome the global pandemic caused by coronavirus disease 2019 (covid-19). In this study, we have applied Mendelian randomization (MR) to systematically evaluate the effect of 10 cardiometabolic risk factors and genetic liability to lifetime smoking on 97 circulating host proteins postulated to either interact or contribute to the maladaptive host response of SARS-CoV-2.

Methods: We applied the inverse variance weighted (IVW) approach and several robust MR methods in a two-sample setting to systemically estimate the genetically predicted effect of each risk factor in turn on levels of each circulating protein. Multivariable MR was conducted to simultaneously evaluate the effects of multiple risk factors on the same protein. We also applied MR using cis-regulatory variants at the genomic location responsible for encoding these proteins to estimate whether their circulating levels may influence severe SARS-CoV-2.

Findings: In total, we identified evidence supporting 105 effects between risk factors and circulating proteins which were robust to multiple testing corrections and sensitivity analyzes. For example, body mass index provided evidence of an effect on 23 circulating proteins with a variety of functions, such as inflammatory markers c-reactive protein (IVW Beta=0.34 per standard deviation change, 95% CI=0.26 to 0.41, P = 2.19 × 10) and interleukin-1 receptor antagonist (IVW Beta=0.23, 95% CI=0.17 to 0.30, P = 9.04 × 10). Further analyzes using multivariable MR provided evidence that the effect of BMI on lowering immunoglobulin G, an antibody class involved in protection from infection, is substantially mediated by raised triglycerides levels (IVW Beta=-0.18, 95% CI=-0.25 to -0.12, P = 2.32 × 10, proportion mediated=44.1%). The strongest evidence that any of the circulating proteins highlighted by our initial analysis influence severe SARS-CoV-2 was identified for soluble glycoprotein 130 (odds ratio=1.81, 95% CI=1.25 to 2.62, P = 0.002), a signal transductor for interleukin-6 type cytokines which are involved in inflammatory response. However, based on current case samples for severe SARS-CoV-2 we were unable to replicate findings in independent samples.

Interpretation: Our findings highlight several key proteins which are influenced by established exposures for disease. Future research to determine whether these circulating proteins mediate environmental effects onto risk of SARS-CoV-2 infection or covid-19 progression are warranted to help elucidate therapeutic strategies for severe covid-19 disease.

Funding: The Medical Research Council, the Wellcome Trust, the British Heart Foundation and UK Research and Innovation.
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http://dx.doi.org/10.1016/j.ebiom.2021.103228DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7857697PMC
February 2021

Exploring the Effects of Cigarette Smoking on Inflammatory Bowel Disease Using Mendelian Randomization.

Crohns Colitis 360 2020 Jan 12;2(1):otaa018. Epub 2020 Mar 12.

MRC Integrative Epidemiology Unit, Bristol, UK.

Background: Previous observational evidence has suggested an association between smoking and inflammatory bowel disease (IBD).

Methods: We used observational techniques followed by Mendelian randomization to explore whether smoking is a causal factor in the development of IBD and its subtypes.

Results: In those who have ever smoked, we observed increased risk of IBD and, in current smokers, we observed increased risk of Crohn disease and decreased risk of ulcerative colitis. However, our Mendelian randomization analyses found little evidence that smoking affects the development of IBD.

Conclusion: Overall, our results suggest that smoking does not causally influence the risk of IBD.
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http://dx.doi.org/10.1093/crocol/otaa018DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7809707PMC
January 2020

Multi-omics analyses of cognitive traits and psychiatric disorders highlights brain-dependent mechanisms.

Hum Mol Genet 2021 Jan 22. Epub 2021 Jan 22.

MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.

Integrating findings from genome-wide association studies with molecular datasets can develop insight into the underlying functional mechanisms responsible for trait-associated genetic variants. We have applied the principles of Mendelian randomization (MR) to investigate whether brain-derived gene expression (n = 1194) may be responsible for mediating the effect of genetic variants on eight cognitive and psychological outcomes (attention deficit hyperactivity disorder (ADHD), Alzheimer's disease, bipolar disorder, depression, intelligence, insomnia, neuroticism and schizophrenia). Transcriptome-wide analyses identified 83 genes associated with at least one outcome (PBonferroni < 6.72 × 10-6), with multiple-trait colocalization also implicating changes to brain-derived DNA methylation at nine of these loci. Comparing effects between outcomes identified evidence of enrichment which may reflect putative causal relationships, such as an inverse relationship between genetic liability towards schizophrenia risk and cognitive ability in later life. Repeating these analyses in whole blood (n = 31 684), we replicated 58.2% of brain-derived effects (based on P < 0.05). Finally, we undertook phenome-wide evaluations at associated loci to investigate pleiotropic effects with 700 complex traits. This highlighted pleiotropic loci such as FURIN (initially implicated in schizophrenia risk (P = 1.05 × 10-7)) which had evidence of an effect on 28 other outcomes, as well as genes which may have a more specific role in disease pathogenesis (e.g. SLC12A5 which only provided evidence of an effect on depression (P = 7.13 × 10-10)). Our results support the utility of whole blood as a valuable proxy for informing initial target identification but also suggest that gene discovery in a tissue-specific manner may be more informative. Finally, non-pleiotropic loci highlighted by our study may be of use for therapeutic translational endeavours.
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http://dx.doi.org/10.1093/hmg/ddab016DOI Listing
January 2021

Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome.

PLoS Genet 2021 01 8;17(1):e1009224. Epub 2021 Jan 8.

MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, University of Bristol, Bristol, United Kingdom.

Discovering drugs that efficiently treat brain diseases has been challenging. Genetic variants that modulate the expression of potential drug targets can be utilized to assess the efficacy of therapeutic interventions. We therefore employed Mendelian Randomization (MR) on gene expression measured in brain tissue to identify drug targets involved in neurological and psychiatric diseases. We conducted a two-sample MR using cis-acting brain-derived expression quantitative trait loci (eQTLs) from the Accelerating Medicines Partnership for Alzheimer's Disease consortium (AMP-AD) and the CommonMind Consortium (CMC) meta-analysis study (n = 1,286) as genetic instruments to predict the effects of 7,137 genes on 12 neurological and psychiatric disorders. We conducted Bayesian colocalization analysis on the top MR findings (using P<6x10-7 as evidence threshold, Bonferroni-corrected for 80,557 MR tests) to confirm sharing of the same causal variants between gene expression and trait in each genomic region. We then intersected the colocalized genes with known monogenic disease genes recorded in Online Mendelian Inheritance in Man (OMIM) and with genes annotated as drug targets in the Open Targets platform to identify promising drug targets. 80 eQTLs showed MR evidence of a causal effect, from which we prioritised 47 genes based on colocalization with the trait. We causally linked the expression of 23 genes with schizophrenia and a single gene each with anorexia, bipolar disorder and major depressive disorder within the psychiatric diseases and 9 genes with Alzheimer's disease, 6 genes with Parkinson's disease, 4 genes with multiple sclerosis and two genes with amyotrophic lateral sclerosis within the neurological diseases we tested. From these we identified five genes (ACE, GPNMB, KCNQ5, RERE and SUOX) as attractive drug targets that may warrant follow-up in functional studies and clinical trials, demonstrating the value of this study design for discovering drug targets in neuropsychiatric diseases.
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http://dx.doi.org/10.1371/journal.pgen.1009224DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7819609PMC
January 2021

Computational Tools for Causal Inference in Genetics.

Cold Spring Harb Perspect Med 2021 Jun 1;11(6). Epub 2021 Jun 1.

MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, United Kingdom.

The advent of large-scale, phenotypically rich, and readily accessible data provides an unprecedented opportunity for epidemiologists, statistical geneticists, bioinformaticians, and also behavioral and social scientists to investigate the causes and consequences of disease. Computational tools and resources are an integral component of such endeavors, which will become increasingly important as these data continue to grow exponentially. In this review, we have provided an overview of computational software and databases that have been developed to assist with analyses in causal inference. This includes online tools that can be used to help generate hypotheses, publicly accessible resources that store summary-level information for millions of genetic markers, and computational approaches that can be used to leverage this wealth of data to study causal relationships.
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http://dx.doi.org/10.1101/cshperspect.a039248DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8168525PMC
June 2021

Separating the genetics of childhood and adult obesity: a validation study of genetic scores for body mass index in adolescence and adulthood in the HUNT Study.

Hum Mol Genet 2021 02;29(24):3966-3973

Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway.

From a life-course perspective, genetic and environmental factors driving childhood obesity may have a lasting influence on health later in life. However, how obesity trajectories vary throughout the life-course remains unknown. Recently, Richardson et al. created powerful early life and adult gene scores for body mass index (BMI) in a comprehensive attempt to separate childhood and adult obesity. The childhood score was derived using questionnaire-based data administered to adults aged 40-69 regarding their relative body size at age 10, making it prone to recall and misclassification bias. We therefore attempted to validate the childhood and adult scores using measured BMI data in adolescence and adulthood among 66 963 individuals from the HUNT Study in Norway from 1963 to 2019. The predictive performance of the childhood score was better in adolescence and early adulthood, whereas the predictive performance of the adult score was better in adulthood. In the age group 12-15.9 years, the variance explained by the childhood polygenic risk score (PRS) was 6.7% versus 2.4% for the adult PRS. In the age group 24-29.9 years, the variance explained by the adult PRS was 3.9% versus 3.6% for the childhood PRS. Our findings support that genetic factors driving BMI differ at young age and in adulthood. Within the framework of multivariable Mendelian randomization, the validated childhood gene score can now be used to determine the consequence of childhood obesity on later disease.
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http://dx.doi.org/10.1093/hmg/ddaa256DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7906755PMC
February 2021

Discovery of rare variants associated with blood pressure regulation through meta-analysis of 1.3 million individuals.

Nat Genet 2020 12 23;52(12):1314-1332. Epub 2020 Nov 23.

Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark.

Genetic studies of blood pressure (BP) to date have mainly analyzed common variants (minor allele frequency > 0.05). In a meta-analysis of up to ~1.3 million participants, we discovered 106 new BP-associated genomic regions and 87 rare (minor allele frequency ≤ 0.01) variant BP associations (P < 5 × 10), of which 32 were in new BP-associated loci and 55 were independent BP-associated single-nucleotide variants within known BP-associated regions. Average effects of rare variants (44% coding) were ~8 times larger than common variant effects and indicate potential candidate causal genes at new and known loci (for example, GATA5 and PLCB3). BP-associated variants (including rare and common) were enriched in regions of active chromatin in fetal tissues, potentially linking fetal development with BP regulation in later life. Multivariable Mendelian randomization suggested possible inverse effects of elevated systolic and diastolic BP on large artery stroke. Our study demonstrates the utility of rare-variant analyses for identifying candidate genes and the results highlight potential therapeutic targets.
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http://dx.doi.org/10.1038/s41588-020-00713-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610439PMC
December 2020

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

Nat Genet 2020 10 7;52(10):1122-1131. Epub 2020 Sep 7.

MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Bristol, UK.

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 1,002 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 is widespread in naïve 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 ( https://www.epigraphdb.org/pqtl/ ). Evaluation of data from historic drug development programs showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of this approach in identifying and prioritizing potential therapeutic targets.
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http://dx.doi.org/10.1038/s41588-020-0682-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7610464PMC
October 2020

Common mechanisms for type 2 diabetes and psychosis: Findings from a prospective birth cohort.

Schizophr Res 2020 09 19;223:227-235. Epub 2020 Aug 19.

Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, England, UK; Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, England, UK.

Background: Psychosis and type 2 diabetes mellitus (T2DM) are commonly comorbid and may share pathophysiologic mechanisms. To investigate shared genetic variation and inflammation as potential common mechanisms, we tested: (i) associations between genetic predisposition for T2DM and psychotic experiences and psychotic disorder in young adults; (ii) the association between genetic predisposition for schizophrenia and insulin resistance (IR), a precursor of T2DM; and (iii) whether these associations are mediated by childhood inflammation.

Methods: Psychotic experiences (PEs), psychotic disorder and IR were assessed at age 18. Polygenic risk scores (PRS) for T2DM and schizophrenia were derived based on large genome-wide association studies. Associations between PRS and psychotic/IR outcomes were assessed using regression analysis based on 3768 ALSPAC birth cohort participants with complete data. Inflammatory markers C-reactive protein (CRP) and interleukin 6 (IL-6) measured at age 9 were used in regression and mediation analyses.

Results: Genetic predisposition for T2DM was associated with PEs (adjusted OR = 1.21; 95% CI, 1.01-1.45) and psychotic disorder (adjusted OR = 1.51; 95% CI, 1.04-2.03) at age 18 in a linear dose-response fashion. Genetic predisposition for schizophrenia was weakly associated with IR (adjusted OR = 1.10; 95% C·I, 0.99-1.22) at age 18. The association between genetic risk for T2DM and PEs was partly mediated by childhood CRP (p = .040).

Conclusions: Comorbidity between psychosis and T2DM may be partly underpinned by shared genes and inflammation. A summation of minor genetic variation representing lifetime risk for T2DM at conception may predispose individuals to psychosis in adulthood by influencing physiologic changes, such as low-grade inflammation, detectable as early as childhood.
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http://dx.doi.org/10.1016/j.schres.2020.08.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7758839PMC
September 2020

Characterizing the Causal Pathway for Genetic Variants Associated with Neurological Phenotypes Using Human Brain-Derived Proteome Data.

Am J Hum Genet 2020 06 14;106(6):885-892. Epub 2020 May 14.

Medical Research Council (MRC) Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom. Electronic address:

Leveraging high-dimensional molecular datasets can help us develop mechanistic insight into associations between genetic variants and complex traits. In this study, we integrated human proteome data derived from brain tissue to evaluate whether targeted proteins putatively mediate the effects of genetic variants on seven neurological phenotypes (Alzheimer disease, amyotrophic lateral sclerosis, depression, insomnia, intelligence, neuroticism, and schizophrenia). Applying the principles of Mendelian randomization (MR) systematically across the genome highlighted 43 effects between genetically predicted proteins derived from the dorsolateral prefrontal cortex and these outcomes. Furthermore, genetic colocalization provided evidence that the same causal variant at 12 of these loci was responsible for variation in both protein and neurological phenotype. This included genes such as DCC, which encodes the netrin-1 receptor and has an important role in the development of the nervous system (p = 4.29 × 10 with neuroticism), as well as SARM1, which has been previously implicated in axonal degeneration (p = 1.76 × 10 with amyotrophic lateral sclerosis). We additionally conducted a phenome-wide MR study for each of these 12 genes to assess potential pleiotropic effects on 700 complex traits and diseases. Our findings suggest that genes such as SNX32, which was initially associated with increased risk of Alzheimer disease, may potentially influence other complex traits in the opposite direction. In contrast, genes such as CTSH (which was also associated with Alzheimer disease) and SARM1 may make worthwhile therapeutic targets because they did not have genetically predicted effects on any of the other phenotypes after correcting for multiple testing.
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http://dx.doi.org/10.1016/j.ajhg.2020.04.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273531PMC
June 2020

Use of genetic variation to separate the effects of early and later life adiposity on disease risk: mendelian randomisation study.

BMJ 2020 May 6;369:m1203. Epub 2020 May 6.

MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.

Objective: To evaluate whether body size in early life has an independent effect on risk of disease in later life or whether its influence is mediated by body size in adulthood.

Design: Two sample univariable and multivariable mendelian randomisation.

Setting: The UK Biobank prospective cohort study and four large scale genome-wide association studies (GWAS) consortiums.

Participants: 453 169 participants enrolled in UK Biobank and a combined total of more than 700 000 people from different GWAS consortiums.

Exposures: Measured body mass index during adulthood (mean age 56.5) and self-reported perceived body size at age 10.

Main Outcome Measures: Coronary artery disease, type 2 diabetes, breast cancer, and prostate cancer.

Results: Having a larger genetically predicted body size in early life was associated with an increased odds of coronary artery disease (odds ratio 1.49 for each change in body size category unless stated otherwise, 95% confidence interval 1.33 to 1.68) and type 2 diabetes (2.32, 1.76 to 3.05) based on univariable mendelian randomisation analyses. However, little evidence was found of a direct effect (ie, not through adult body size) based on multivariable mendelian randomisation estimates (coronary artery disease: 1.02, 0.86 to 1.22; type 2 diabetes:1.16, 0.74 to 1.82). In the multivariable mendelian randomisation analysis of breast cancer risk, strong evidence was found of a protective direct effect for larger body size in early life (0.59, 0.50 to 0.71), with less evidence of a direct effect of adult body size on this outcome (1.08, 0.93 to 1.27). Including age at menarche as an additional exposure provided weak evidence of a total causal effect (univariable mendelian randomisation odds ratio 0.98, 95% confidence interval 0.91 to 1.06) but strong evidence of a direct causal effect, independent of early life and adult body size (multivariable mendelian randomisation odds ratio 0.90, 0.85 to 0.95). No strong evidence was found of a causal effect of either early or later life measures on prostate cancer (early life body size odds ratio 1.06, 95% confidence interval 0.81 to 1.40; adult body size 0.87, 0.70 to 1.08).

Conclusions: The findings suggest that the positive association between body size in childhood and risk of coronary artery disease and type 2 diabetes in adulthood can be attributed to individuals remaining large into later life. However, having a smaller body size during childhood might increase the risk of breast cancer regardless of body size in adulthood, with timing of puberty also putatively playing a role.
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http://dx.doi.org/10.1136/bmj.m1203DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7201936PMC
May 2020

Pleiotropy of polygenic factors associated with focal and generalized epilepsy in the general population.

PLoS One 2020 28;15(4):e0232292. Epub 2020 Apr 28.

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, United States of America.

Epilepsy is clinically heterogeneous, and neurological or psychiatric comorbidities are frequently observed in patients. It has not been tested whether common risk variants for generalized or focal epilepsy are enriched in people with other disorders or traits related to brain or cognitive function. Here, we perform two brain-focused phenome association studies of polygenic risk scores (PRS) for generalized epilepsy (GE-PRS) or focal epilepsy (FE-PRS) with all binary brain or cognitive function-related traits available for 334,310 European-ancestry individuals of the UK Biobank. Higher GE-PRS were associated with not having a college or university degree (P = 3.00x10-4), five neuroticism-related personality traits (P<2.51x10-4), and having ever smoked (P = 1.27x10-6). Higher FE-PRS were associated with several measures of low educational attainment (P<4.87x10-5), one neuroticism-related personality trait (P = 2.33x10-4), having ever smoked (P = 1.71x10-4), and having experienced events of anxiety or depression (P = 2.83x10-4). GE- and FE-PRS had the same direction of effect for each of the associated traits. Genetic factors associated with GE or FE showed similar patterns of correlation with genetic factors associated with cortical morphology in a subset of the UKB with 16,612 individuals and T1 magnetic resonance imaging data. In summary, our results suggest that genetic factors associated with epilepsies may confer risk for other neurological and psychiatric disorders in a population sample not enriched for epilepsy.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0232292PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7188256PMC
July 2020

Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis.

PLoS Med 2020 03 23;17(3):e1003062. Epub 2020 Mar 23.

Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom.

Background: Circulating lipoprotein lipids cause coronary heart disease (CHD). However, the precise way in which one or more lipoprotein lipid-related entities account for this relationship remains unclear. Using genetic instruments for lipoprotein lipid traits implemented through multivariable Mendelian randomisation (MR), we sought to compare their causal roles in the aetiology of CHD.

Methods And Findings: We conducted a genome-wide association study (GWAS) of circulating non-fasted lipoprotein lipid traits in the UK Biobank (UKBB) for low-density lipoprotein (LDL) cholesterol, triglycerides, and apolipoprotein B to identify lipid-associated single nucleotide polymorphisms (SNPs). Using data from CARDIoGRAMplusC4D for CHD (consisting of 60,801 cases and 123,504 controls), we performed univariable and multivariable MR analyses. Similar GWAS and MR analyses were conducted for high-density lipoprotein (HDL) cholesterol and apolipoprotein A-I. The GWAS of lipids and apolipoproteins in the UKBB included between 393,193 and 441,016 individuals in whom the mean age was 56.9 y (range 39-73 y) and of whom 54.2% were women. The mean (standard deviation) lipid concentrations were LDL cholesterol 3.57 (0.87) mmol/L and HDL cholesterol 1.45 (0.38) mmol/L, and the median triglycerides was 1.50 (IQR = 1.11) mmol/L. The mean (standard deviation) values for apolipoproteins B and A-I were 1.03 (0.24) g/L and 1.54 (0.27) g/L, respectively. The GWAS identified multiple independent SNPs associated at P < 5 × 10-8 for LDL cholesterol (220), apolipoprotein B (n = 255), triglycerides (440), HDL cholesterol (534), and apolipoprotein A-I (440). Between 56%-93% of SNPs identified for each lipid trait had not been previously reported in large-scale GWASs. Almost half (46%) of these SNPs were associated at P < 5 × 10-8 with more than one lipid-related trait. Assessed individually using MR, LDL cholesterol (odds ratio [OR] 1.66 per 1-standard-deviation-higher trait; 95% CI: 1.49-1.86; P < 0.001), triglycerides (OR 1.34; 95% CI: 1.25-1.44; P < 0.001) and apolipoprotein B (OR 1.73; 95% CI: 1.56-1.91; P < 0.001) had effect estimates consistent with a higher risk of CHD. In multivariable MR, only apolipoprotein B (OR 1.92; 95% CI: 1.31-2.81; P < 0.001) retained a robust effect, with the estimate for LDL cholesterol (OR 0.85; 95% CI: 0.57-1.27; P = 0.44) reversing and that of triglycerides (OR 1.12; 95% CI: 1.02-1.23; P = 0.01) becoming weaker. Individual MR analyses showed a 1-standard-deviation-higher HDL cholesterol (OR 0.80; 95% CI: 0.75-0.86; P < 0.001) and apolipoprotein A-I (OR 0.83; 95% CI: 0.77-0.89; P < 0.001) to lower the risk of CHD, but these effect estimates attenuated substantially to the null on accounting for apolipoprotein B. A limitation is that, owing to the nature of lipoprotein metabolism, measures related to the composition of lipoprotein particles are highly correlated, creating a challenge in making exclusive interpretations on causation of individual components.

Conclusions: These findings suggest that apolipoprotein B is the predominant trait that accounts for the aetiological relationship of lipoprotein lipids with risk of CHD.
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http://dx.doi.org/10.1371/journal.pmed.1003062DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7089422PMC
March 2020

Combined Effect of PNPLA3, TM6SF2, and HSD17B13 Variants on Risk of Cirrhosis and Hepatocellular Carcinoma in the General Population.

Hepatology 2020 09;72(3):845-856

Department of Clinical Biochemistry, Rigshospitalet, Copenhagen, Denmark.

Background And Aims: We hypothesized that a genetic risk score (GRS) for fatty liver disease influences the risk of cirrhosis and hepatocellular carcinoma (HCC). Three genetic variants (patatin-like phospholipase domain-containing protein 3 [PNPLA3] p.I148M; transmembrane 6, superfamily member 2 [TM6SF2] p.E167K; and hydroxysteroid 17-beta dehydrogenase 13 [HSD17B13] rs72613567) were combined into a risk score, ranging from 0 to 6 for risk-increasing alleles.

Approach And Results: We examined the association of the risk score with plasma markers of liver disease and with cirrhosis and HCC in 110,761 individuals from Copenhagen, Denmark, and 334,691 individuals from the UK Biobank. The frequencies of risk scores of 0, 1, 2, 3, 4, and 5 or 6 were 5%, 25%, 41%, 23%, 5.5%, and 0.5%, respectively. A higher GRS was associated with an increase in plasma alanine aminotransferase (ALT) level of 26% in those with score 5 or 6 versus 0. In meta-analysis of the Copenhagen studies and the UK Biobank, individuals with scores 1, 2, 3, 4, and 5 or 6 had odds ratios (ORs) for cirrhosis of 1.6 (95% confidence interval [CI], 1.3, 1.9), 2.0 (95% CI, 1.8, 2.2), 3.1 (95% CI, 2.7, 3.5), 5.2 (95% CI, 4.2, 6.4), and 12 (95% CI, 7.7, 19), respectively, as compared with those with a score of 0. The corresponding ORs for HCC were 1.2 (95% CI, 0.9, 1.7), 1.0 (95% CI, 0.7, 1.3), 2.4 (95% CI, 1.9, 3.0), 3.3 (95% CI, 2.2, 5.0), and 29 (95% CI, 17, 51).

Conclusion: A GRS for fatty liver disease confers up to a 12-fold higher risk of cirrhosis and up to a 29-fold higher risk of HCC in individuals from the general population.
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http://dx.doi.org/10.1002/hep.31238DOI Listing
September 2020

The Effect of Plasma Lipids and Lipid-Lowering Interventions on Bone Mineral Density: A Mendelian Randomization Study.

J Bone Miner Res 2020 07 12;35(7):1224-1235. Epub 2020 Mar 12.

Medical Research Council (MRC) Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol, UK.

Several epidemiological studies have reported a relationship between statin treatment and increased bone mineral density (BMD) and reduced fracture risk, but the mechanism underlying the purported relationship is unclear. We used Mendelian randomization (MR) to assess whether this relationship 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 as exposure. The outcome results were obtained from a heel estimated BMD (eBMD) genomewide association study (GWAS) from the UK Biobank and dual-energy X-ray absorptiometry (DXA) BMD at four body sites and fracture GWAS from the GEFOS consortium. 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 and fracture. Univariate MR analyses suggested a causal effect of LDL-C on eBMD (β = -0.06; standard deviation change in eBMD per standard deviation change in LDL-C, 95% confidence interval [CI] = -0.08 to -0.04; p = 4 × 10 ), total body BMD (β = -0.05, 95% CI = -0.08 to -0.01, p = 6 × 10 ) and potentially on lumbar spine BMD. Multivariable MR suggested that the effects of LDL-C on eBMD and total body BMD were independent of HDL-C and triglycerides. Sensitivity MR analyses 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 eBMD (β = -0.083; -0.132 to -0.034; p = .001) to those excluding these SNPs (β = -0.063; -0.090 to -0.036; p = 8 × 10 ). Bidirectional MR analyses provided some evidence for a causal effect of eBMD on plasma LDL-C levels. Our results suggest that effects of statins on eBMD and total body 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. © 2020 American Society for Bone and Mineral Research.
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http://dx.doi.org/10.1002/jbmr.3989DOI Listing
July 2020

Smoking, DNA Methylation, and Lung Function: a Mendelian Randomization Analysis to Investigate Causal Pathways.

Am J Hum Genet 2020 03 20;106(3):315-326. Epub 2020 Feb 20.

Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK. Electronic address:

Whether smoking-associated DNA methylation has a causal effect on lung function has not been thoroughly evaluated. We first investigated the causal effects of 474 smoking-associated CpGs on forced expiratory volume in 1 s (FEV) in UK Biobank (n = 321,047) by using two-sample Mendelian randomization (MR) and then replicated this investigation in the SpiroMeta Consortium (n = 79,055). Second, we used two-step MR to investigate whether DNA methylation mediates the effect of smoking on FEV. Lastly, we evaluated the presence of horizontal pleiotropy and assessed whether there is any evidence for shared causal genetic variants between lung function, DNA methylation, and gene expression by using a multiple-trait colocalization ("moloc") framework. We found evidence of a possible causal effect for DNA methylation on FEV at 18 CpGs (p < 1.2 × 10). Replication analysis supported a causal effect at three CpGs (cg21201401 [LIME1 and ZGPAT], cg19758448 [PGAP3], and cg12616487 [EML3 and AHNAK] [p < 0.0028]). DNA methylation did not clearly mediate the effect of smoking on FEV, although DNA methylation at some sites might influence lung function via effects on smoking. By using "moloc", we found evidence of shared causal variants between lung function, gene expression, and DNA methylation. These findings highlight potential therapeutic targets for improving lung function and possibly smoking cessation, although larger, tissue-specific datasets are required to confirm these results.
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http://dx.doi.org/10.1016/j.ajhg.2020.01.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7058834PMC
March 2020

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

Nat Commun 2020 01 10;11(1):185. Epub 2020 Jan 10.

MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.

Developing insight into tissue-specific transcriptional mechanisms can help improve our understanding of how genetic variants exert their effects on complex traits and disease. In this study, we apply the principles of Mendelian randomization to systematically evaluate transcriptome-wide associations between gene expression (across 48 different tissue types) and 395 complex traits. Our findings indicate that variants which influence gene expression levels in multiple tissues are more likely to influence multiple complex traits. Moreover, detailed investigations of our results highlight tissue-specific associations, drug validation opportunities, insight into the likely causal pathways for trait-associated variants and also implicate putative associations at loci yet to be implicated in disease susceptibility. Similar evaluations can be conducted at http://mrcieu.mrsoftware.org/Tissue_MR_atlas/.
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http://dx.doi.org/10.1038/s41467-019-13921-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6954187PMC
January 2020

Investigating causality between liability to ADHD and substance use, and liability to substance use and ADHD risk, using Mendelian randomization.

Addict Biol 2021 01 16;26(1):e12849. Epub 2019 Nov 16.

School of Psychological Science, University of Bristol, Bristol, United Kingdom.

Attention-deficit hyperactivity disorder (ADHD) has consistently been associated with substance use, but the nature of this association is not fully understood. To inform intervention development and public health messages, a vital question is whether there are causal pathways from ADHD to substance use and/or vice versa. We applied bidirectional Mendelian randomization, using summary-level data from the largest available genome-wide association studies (GWAS) on ADHD, smoking (initiation, cigarettes per day, cessation, and a compound measure of lifetime smoking), alcohol use (drinks per week, alcohol problems, and alcohol dependence), cannabis use (initiation), and coffee consumption (cups per day). Genetic variants robustly associated with the "exposure" were selected as instruments and identified in the "outcome" GWAS. Effect estimates from individual genetic variants were combined with inverse-variance weighted regression and five sensitivity analyses (weighted median, weighted mode, MR-Egger, generalized summary data-based MR, and Steiger filtering). We found evidence that liability to ADHD increases likelihood of smoking initiation and heaviness of smoking among smokers, decreases likelihood of smoking cessation, and increases likelihood of cannabis initiation. There was weak evidence that liability to ADHD increases alcohol dependence risk but not drinks per week or alcohol problems. In the other direction, there was weak evidence that smoking initiation increases ADHD risk, but follow-up analyses suggested a high probability of horizontal pleiotropy. There was no clear evidence of causal pathways between ADHD and coffee consumption. Our findings corroborate epidemiological evidence, suggesting causal pathways from liability to ADHD to smoking, cannabis use, and, tentatively, alcohol dependence. Further work is needed to explore the exact mechanisms mediating these causal effects.
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http://dx.doi.org/10.1111/adb.12849DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7228854PMC
January 2021

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

Hum Mol Genet 2019 10;28(19):3293-3300

MRC Integrative Epidemiology Unit, Population Health Sciences Institute, University of Bristol, Bristol, BS8 2BN, UK.

Immune-mediated diseases (IMDs) arise when tolerance is lost and chronic inflammation is targeted towards healthy tissues. Despite their growing prevalence, therapies to treat IMDs are lacking. Cytokines and their receptors orchestrate inflammatory responses by regulating elaborate signalling networks across multiple cell types making it challenging to pinpoint therapeutically relevant drivers of IMDs. We developed an analytical framework that integrates Mendelian randomization (MR) and multiple-trait colocalization (moloc) analyses to highlight putative cell-specific drivers of IMDs. MR evaluated causal associations between the levels of 10 circulating cytokines and 9 IMDs within human populations. Subsequently, we undertook moloc analyses to assess whether IMD trait, cytokine protein and corresponding gene expression are driven by a shared causal variant. Moreover, we leveraged gene expression data from three separate cell types (monocytes, neutrophils and T cells) to discern whether associations may be attributed to cell type-specific drivers of disease. MR analyses supported a causal role for IL-18 in inflammatory bowel disease (IBD) (P = 1.17 × 10-4) and eczema/dermatitis (P = 2.81 × 10-3), as well as associations between IL-2rα and IL-6R with several other IMDs. Moloc strengthened evidence of a causal association for these results, as well as providing evidence of a monocyte and neutrophil-driven role for IL-18 in IBD pathogenesis. In contrast, IL-2rα and IL-6R associations were found to be T cell specific. Our analytical pipeline can help to elucidate putative molecular pathways in the pathogeneses of IMDs, which could be applied to other disease contexts.
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http://dx.doi.org/10.1093/hmg/ddz155DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6859431PMC
October 2019
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