scholarly journals The absence of association between anorexia nervosa and smoking: converging evidence across two studies

2021 ◽  
Author(s):  
E. Caitlin Lloyd ◽  
Zoe E. Reed ◽  
Robyn E. Wootton
Keyword(s):  
Anorexia Nervosa ◽  
Association Studies ◽  
Smoking Behaviour ◽  
Causal Effects ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Gwas Study ◽  
Logistic Regression Models ◽  
Parents And Children ◽  
Using Data

AbstractPrevious studies have found increased smoking prevalence amongst adults with anorexia nervosa (AN) compared to the general population. The current investigation explored bidirectional associations between AN and smoking behaviour (initiation and heaviness), to address questions surrounding causation. In Study One, logistic regression models with variance robust standard errors assessed longitudinal associations between AN and smoking, using data from adolescent participants of the Avon Longitudinal Study of Parents and Children (N = 5100). In Study Two, two-sample Mendelian randomisation (MR) tested possible causal effects using summary statistics from publicly available genome-wide association studies (GWAS). Study One provided no clear evidence for a predictive effect of AN on subsequent smoking behaviour, or for smoking heaviness/initiation predicting later AN. MR findings did not support causal effects between AN and smoking behaviour, in either direction. Findings do not support predictive or causal effects between AN and smoking behaviour. Previously reported associations may have been vulnerable to confounding, highlighting the possibility of smoking and AN sharing causal risk factors.

scholarly journals Evidence for causal effects of lifetime smoking on risk for depression and schizophrenia: a Mendelian randomisation study

2019 ◽  
Vol 50 (14) ◽  
pp. 2435-2443 ◽  
Author(s):  
Robyn E. Wootton ◽  
Rebecca C. Richmond ◽  
Bobby G. Stuijfzand ◽  
Rebecca B. Lawn ◽  
Hannah M. Sallis ◽  
...  
Keyword(s):  
Causal Effect ◽  
Association Studies ◽  
Smoking Initiation ◽  
Smoking Behaviour ◽  
Positive Control ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Weak Evidence ◽  
Smoking Duration ◽  
The Uk

AbstractBackgroundSmoking prevalence is higher amongst individuals with schizophrenia and depression compared with the general population. Mendelian randomisation (MR) can examine whether this association is causal using genetic variants identified in genome-wide association studies (GWAS).MethodsWe conducted two-sample MR to explore the bi-directional effects of smoking on schizophrenia and depression. For smoking behaviour, we used (1) smoking initiation GWAS from the GSCAN consortium and (2) we conducted our own GWAS of lifetime smoking behaviour (which captures smoking duration, heaviness and cessation) in a sample of 462690 individuals from the UK Biobank. We validated this instrument using positive control outcomes (e.g. lung cancer). For schizophrenia and depression we used GWAS from the PGC consortium.ResultsThere was strong evidence to suggest smoking is a risk factor for both schizophrenia (odds ratio (OR) 2.27, 95% confidence interval (CI) 1.67–3.08, p < 0.001) and depression (OR 1.99, 95% CI 1.71–2.32, p < 0.001). Results were consistent across both lifetime smoking and smoking initiation. We found some evidence that genetic liability to depression increases smoking (β = 0.091, 95% CI 0.027–0.155, p = 0.005) but evidence was mixed for schizophrenia (β = 0.022, 95% CI 0.005–0.038, p = 0.009) with very weak evidence for an effect on smoking initiation.ConclusionsThese findings suggest that the association between smoking, schizophrenia and depression is due, at least in part, to a causal effect of smoking, providing further evidence for the detrimental consequences of smoking on mental health.

scholarly journals 586Effects of maternal circulating amino acids on offspring birthweight: a Mendelian randomisation analysis

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Jian Zhao ◽  
Rachel Freathy ◽  
David Evans ◽  
Nicole Warrington ◽  
Claudia Langenberg ◽  
...  
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Association Studies ◽  
Amino Acid Level ◽  
Causal Effects ◽  
Sensitivity Analyses ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Reverse Causality

Abstract Background It is suggested amino acids are critical for fetal growth, but analyses assessing causality are lacking. Mendelian randomisation (MR) can be used to examine causal effects under instrumental variable (IV) assumptions. Methods We conducted a two-sample MR study utilizing summary data from genome-wide association studies (GWAS) of amino acids (sample 1, n = 86,507) and of offspring birthweight (sample 2, combined UK Biobank and Early Growth Genetics Consortium, n = 406,063). Seventy-five independent single nucleotide polymorphisms (SNPs) robustly associated with 18 amino acids (p &lt; 4.9 × 10-10) were used as genetic instruments. Wald ratio and inverse variance weighted methods were used in MR main analysis. Sensitivity analyses were performed to explore IV assumption violations. To explore whether there was consistency between SNP-amino acid associations in pregnancy and in the GWAS, the latter were compared to associations in the Born in Bradford cohort. Results There was evidence of positive causal effects of maternal alanine (51.9 g birthweight increase per SD increase in amino acid level, 95% CI: 24.2, 79.5), glutamine (51.3 g, 95% CI: 33.5, 69.0), glycine (10.4 g, 95% CI: 1.3, 19.6) and serine (27.1 g, 95% CI: 11.2, 43.0) on birthweight and inverse causal effects of maternal isoleucine (-109.7 g, 95% CI: -194.6, -24.9) and histidine (-41.1 g, 95% CI: -78.5, -3.7) on birthweight. Sensitivity analyses to explore reverse causality and bias due to horizontal pleiotropy supported our findings. Conclusions Some maternal circulating amino acids have causal effects on birthweight. Key messages MR can be extended to probe effects of maternal nutrition on offspring development.

scholarly journals Sex-specific genome-wide association study in glioma identifies new risk locus at 3p21.31 in females, and finds sex-differences in risk at 8q24.21

2017 ◽  
Author(s):  
Quinn T. Ostrom ◽  
Ben Kinnersley ◽  
Margaret R. Wrensch ◽  
Jeanette E. Eckel-Passow ◽  
Georgina Armstrong ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Sex Chromosome ◽  
Association Studies ◽  
Meta Analysis ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Autosomal Snps ◽  
Logistic Regression Models ◽  
Genome Wide ◽  
Using Data

AbstractIncidence of glioma is approximately 50% higher in males. Previous analyses have examined exposures related to sex hormones in women as potential protective factors for these tumors, with inconsistent results. Previous glioma genome-wide association studies (GWAS) have not stratified by sex. Potential sex-specific genetic effects were assessed in autosomal SNPs and sex chromosome variants for all glioma, GBM and non-GBM patients using data from four previous glioma GWAS. Datasets were analyzed using sex-stratified logistic regression models and combined using meta-analysis. There were 4,831 male cases, 5,216 male controls, 3,206 female cases and 5,470 female controls. A significant association was detected at rs11979158 (7p11.2) in males only. Association at rs55705857 (8q24.21) was stronger in females than in males. A large region on 3p21.31 was identified with significant association in females only. The identified differences in effect of risk variants do not fully explain the observed incidence difference in glioma by sex.

Mendelian randomisation study of the effects of known and putative risk factors on pancreatic cancer

2020 ◽  
Vol 57 (12) ◽  
pp. 820-828 ◽  
Author(s):  
Ye Lu ◽  
Manuel Gentiluomo ◽  
Justo Lorenzo-Bermejo ◽  
Luca Morelli ◽  
Ofure Obazee ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Pancreatic Cancer ◽  
Association Studies ◽  
Dietary Factors ◽  
Causal Effects ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Fasting Insulin

BackgroundObservational studies have reported multiple risk factors for pancreatic ductal adenocarcinoma (PDAC). Some are well established, like tobacco smoking, alcohol drinking, obesity and type 2 diabetes, whereas some others are putative, such as allergy and dietary factors. Identifying causal risk factors can help establishing those that can be targeted to contribute to prevent PDAC.ObjectiveWe sought to investigate the possible causal effects of established and putative factors on PDAC risk.MethodsWe conducted a two-sample Mendelian randomisation (MR) study using publicly available data for genetic variants associated with the factors of interest, and summary genetic data from genome-wide association studies of the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PanC4), including in total 8769 cases and 7055 controls. Causality was assessed using inverse-variance weighted, MR-Egger regression and weighted median methods, complemented with sensitivity and radial MR analyses.ResultsWe found evidence for a causal effect of body mass index (BMI) on PDAC risk (OR 1.43, 95% CI 1.20 to 1.71, p=8.43×10−5). Fasting insulin (OR 2.84, 95% CI 1.23 to 6.56, p=0.01), low-density lipoprotein cholesterol (OR 1.16, 95% CI 1.02 to 1.32, p=0.03) and type 2 diabetes (OR 1.09, 95% CI 1.01 to 1.17, p=0.02) were also causally associated with PDAC risk. BMI showed both direct and fasting insulin-mediated causal effects.ConclusionWe found strong evidence that BMI is causally associated with PDAC risk, providing support that obesity management may be a potential prevention strategy for reducing pancreatic cancer risk while fasting insulin and type 2 diabetes showed a suggestive association that should be further investigated.

scholarly journals Trans-ethnic genome-wide association study of kidney function provides novel insight into effector genes and causal effects on kidney-specific disease aetiologies

2018 ◽  
Author(s):  
Andrew P Morris ◽  
Thu H Le ◽  
Haojia Wu ◽  
Artur Akbarov ◽  
Peter J van der Most ◽  
...  
Keyword(s):  
Kidney Function ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Causal Effects ◽  
Genome Wide Association ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Effector Genes ◽  
Genome Wide ◽  
Insight Into

Chronic kidney disease (CKD) affects ∼10% of the global population, with considerable ethnic differences in prevalence and aetiology. We assembled genome-wide association studies (GWAS)1-3 of estimated glomerular filtration rate (eGFR), a measure of kidney function that defines CKD, in 312,468 individuals from four ancestry groups. We identified 93 loci (20 novel), which were delineated to 127 distinct association signals. These signals were homogenous across ancestries, and were enriched for protein-coding exons, kidney-specific histone modifications, and transcription factor binding sites for HDAC2 and EZH2. Fine-mapping revealed 40 high-confidence variants driving eGFR associations and highlighted potential causal genes with cell-type specific expression in glomerulus, and proximal and distal nephron. Mendelian randomisation (MR) supported causal effects of eGFR on overall and cause-specific CKD, kidney stone formation, diastolic blood pressure (DBP) and hypertension. These results define novel molecular mechanisms and effector genes for eGFR, offering insight into clinical outcomes and routes to CKD treatment development.

scholarly journals Identifying the potential role of insomnia on multimorbidity: A Mendelian randomization phenome-wide association study in UK Biobank

2022 ◽  
Author(s):  
Mark J Gibson ◽  
Deborah A Lawlor ◽  
Louise AC Millard
Keyword(s):  
Health Outcomes ◽  
Association Study ◽  
Genetic Risk ◽  
Association Studies ◽  
Causal Effects ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Wide Range

Objectives: To identify the breadth of potential causal effects of insomnia on health outcomes and hence its possible role in multimorbidity. Design: Mendelian randomisation (MR) Phenome-wide association study (MR-PheWAS) with two-sample Mendelian randomisation follow-up. Setting: Individual data from UK Biobank and summary data from a number of genome-wide association studies. Participants: 336,975 unrelated white-British UK Biobank participants. Exposures: Standardised genetic risk of insomnia for the MR-PheWAS and genetically predicted insomnia for the two-sample MR follow-up, with insomnia instrumented by a genetic risk score (GRS) created from 129 single-nucleotide polymorphisms (SNPs). Main outcomes measures: 11,409 outcomes from UK Biobank extracted and processed by an automated pipeline (PHESANT). Potential causal effects (i.e., those passing a Bonferroni-corrected significance threshold) were followed up with two-sample MR in MR-Base, where possible. Results: 437 potential causal effects of insomnia were observed for a number of traits, including anxiety, stress, depression, mania, addiction, pain, body composition, immune, respiratory, endocrine, dental, musculoskeletal, cardiovascular and reproductive traits, as well as socioeconomic and behavioural traits. We were able to undertake two-sample MR for 71 of these 437 and found evidence of causal effects (with directionally concordant effect estimates across all analyses) for 25 of these. These included, for example, risk of anxiety disorders (OR=1.55 [95% confidence interval (CI): 1.30, 1.86] per category increase in insomnia), diseases of the oesophagus/stomach/duodenum (OR=1.32 [95% CI: 1.14, 1.53]) and spondylosis (OR=1.57 [95% CI: 1.22, 2.01]). Conclusion: Insomnia potentially causes a wide range of adverse health outcomes and behaviours. This has implications for developing interventions to prevent and treat a number of diseases in order to reduce multimorbidity and associated polypharmacy.

scholarly journals Understanding the nature of association between anxiety phenotypes and anorexia nervosa: a triangulation approach

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
E. Caitlin Lloyd ◽  
Hannah M. Sallis ◽  
Bas Verplanken ◽  
Anne M. Haase ◽  
Marcus R. Munafò
Keyword(s):  
Anorexia Nervosa ◽  
Longitudinal Study ◽  
Anxiety Disorder ◽  
Anxiety Disorders ◽  
Causal Effect ◽  
Causal Effects ◽  
Observational Research ◽  
Genome Wide Association Studies ◽  
Genetic Liability ◽  
Depressed Affect

Abstract Background Evidence from observational studies suggests an association between anxiety disorders and anorexia nervosa (AN), but causal inference is complicated by the potential for confounding in these studies. We triangulate evidence across a longitudinal study and a Mendelian randomization (MR) study, to evaluate whether there is support for anxiety disorder phenotypes exerting a causal effect on AN risk. Methods Study One assessed longitudinal associations of childhood worry and anxiety disorders with lifetime AN in the Avon Longitudinal Study of Parents and Children cohort. Study Two used two-sample MR to evaluate: causal effects of worry, and genetic liability to anxiety disorders, on AN risk; causal effects of genetic liability to AN on anxiety outcomes; and the causal influence of worry on anxiety disorder development. The independence of effects of worry, relative to depressed affect, on AN and anxiety disorder outcomes, was explored using multivariable MR. Analyses were completed using summary statistics from recent genome-wide association studies. Results Study One did not support an association between worry and subsequent AN, but there was strong evidence for anxiety disorders predicting increased risk of AN. Study Two outcomes supported worry causally increasing AN risk, but did not support a causal effect of anxiety disorders on AN development, or of AN on anxiety disorders/worry. Findings also indicated that worry causally influences anxiety disorder development. Multivariable analysis estimates suggested the influence of worry on both AN and anxiety disorders was independent of depressed affect. Conclusions Overall our results provide mixed evidence regarding the causal role of anxiety exposures in AN aetiology. The inconsistency between outcomes of Studies One and Two may be explained by limitations surrounding worry assessment in Study One, confounding of the anxiety disorder and AN association in observational research, and low power in MR analyses probing causal effects of genetic liability to anxiety disorders. The evidence for worry acting as a causal risk factor for anxiety disorders and AN supports targeting worry for prevention of both outcomes. Further research should clarify how a tendency to worry translates into AN risk, and whether anxiety disorder pathology exerts any causal effect on AN.

scholarly journals A comprehensive evaluation of methods for Mendelian randomization using realistic simulations and an analysis of 38 biomarkers for risk of type 2 diabetes

2021 ◽  
Author(s):  
Guanghao Qi ◽  
Nilanjan Chatterjee
Keyword(s):  
Type 2 Diabetes ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Real Data ◽  
Causal Effects ◽  
Type I ◽  
Genome Wide Association Studies ◽  
Simulation Studies ◽  
Sample Sizes

Abstract Background Previous studies have often evaluated methods for Mendelian randomization (MR) analysis based on simulations that do not adequately reflect the data-generating mechanisms in genome-wide association studies (GWAS) and there are often discrepancies in the performance of MR methods in simulations and real data sets. Methods We use a simulation framework that generates data on full GWAS for two traits under a realistic model for effect-size distribution coherent with the heritability, co-heritability and polygenicity typically observed for complex traits. We further use recent data generated from GWAS of 38 biomarkers in the UK Biobank and performed down sampling to investigate trends in estimates of causal effects of these biomarkers on the risk of type 2 diabetes (T2D). Results Simulation studies show that weighted mode and MRMix are the only two methods that maintain the correct type I error rate in a diverse set of scenarios. Between the two methods, MRMix tends to be more powerful for larger GWAS whereas the opposite is true for smaller sample sizes. Among the other methods, random-effect IVW (inverse-variance weighted method), MR-Robust and MR-RAPS (robust adjust profile score) tend to perform best in maintaining a low mean-squared error when the InSIDE assumption is satisfied, but can produce large bias when InSIDE is violated. In real-data analysis, some biomarkers showed major heterogeneity in estimates of their causal effects on the risk of T2D across the different methods and estimates from many methods trended in one direction with increasing sample size with patterns similar to those observed in simulation studies. Conclusion The relative performance of different MR methods depends heavily on the sample sizes of the underlying GWAS, the proportion of valid instruments and the validity of the InSIDE assumption. Down-sampling analysis can be used in large GWAS for the possible detection of bias in the MR methods.

scholarly journals Transcriptome-wide Mendelian randomization study prioritising novel tissue-dependent genes for glioma susceptibility

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jamie W. Robinson ◽  
Richard M. Martin ◽  
Spiridon Tsavachidis ◽  
Amy E. Howell ◽  
Caroline L. Relton ◽  
...  
Keyword(s):  
Gene Expression ◽  
Association Studies ◽  
Tissue Expression ◽  
Tissue Type ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Causal Pathways ◽  
Genome Wide ◽  
Glioma Risk ◽  
Brain Tissues

AbstractGenome-wide association studies (GWAS) have discovered 27 loci associated with glioma risk. Whether these loci are causally implicated in glioma risk, and how risk differs across tissues, has yet to be systematically explored. We integrated multi-tissue expression quantitative trait loci (eQTLs) and glioma GWAS data using a combined Mendelian randomisation (MR) and colocalisation approach. We investigated how genetically predicted gene expression affects risk across tissue type (brain, estimated effective n = 1194 and whole blood, n = 31,684) and glioma subtype (all glioma (7400 cases, 8257 controls) glioblastoma (GBM, 3112 cases) and non-GBM gliomas (2411 cases)). We also leveraged tissue-specific eQTLs collected from 13 brain tissues (n = 114 to 209). The MR and colocalisation results suggested that genetically predicted increased gene expression of 12 genes were associated with glioma, GBM and/or non-GBM risk, three of which are novel glioma susceptibility genes (RETREG2/FAM134A, FAM178B and MVB12B/FAM125B). The effect of gene expression appears to be relatively consistent across glioma subtype diagnoses. Examining how risk differed across 13 brain tissues highlighted five candidate tissues (cerebellum, cortex, and the putamen, nucleus accumbens and caudate basal ganglia) and four previously implicated genes (JAK1, STMN3, PICK1 and EGFR). These analyses identified robust causal evidence for 12 genes and glioma risk, three of which are novel. The correlation of MR estimates in brain and blood are consistently low which suggested that tissue specificity needs to be carefully considered for glioma. Our results have implicated genes yet to be associated with glioma susceptibility and provided insight into putatively causal pathways for glioma risk.

scholarly journals Cigarette smoking and personality: interrogating causality using Mendelian randomisation

2018 ◽  
Vol 49 (13) ◽  
pp. 2197-2205 ◽  
Author(s):  
Hannah M. Sallis ◽  
George Davey Smith ◽  
Marcus R. Munafò
Keyword(s):  
Personality Traits ◽  
Association Studies ◽  
Smoking Initiation ◽  
Mendelian Randomisation ◽  
Genome Wide Association Studies ◽  
Individual Level ◽  
Causal Pathways ◽  
Genome Wide ◽  
Level Data ◽  
Causal Nature

AbstractBackgroundDespite the well-documented association between smoking and personality traits such as neuroticism and extraversion, little is known about the potential causal nature of these findings. If it were possible to unpick the association between personality and smoking, it may be possible to develop tailored smoking interventions that could lead to both improved uptake and efficacy.MethodsRecent genome-wide association studies (GWAS) have identified variants robustly associated with both smoking phenotypes and personality traits. Here we use publicly available GWAS summary statistics in addition to individual-level data from UK Biobank to investigate the link between smoking and personality. We first estimate genetic overlap between traits using LD score regression and then use bidirectional Mendelian randomisation methods to unpick the nature of this relationship.ResultsWe found clear evidence of a modest genetic correlation between smoking behaviours and both neuroticism and extraversion. We found some evidence that personality traits are causally linked to certain smoking phenotypes: among current smokers each additional neuroticism risk allele was associated with smoking an additional 0.07 cigarettes per day (95% CI 0.02–0.12, p = 0.009), and each additional extraversion effect allele was associated with an elevated odds of smoking initiation (OR 1.015, 95% CI 1.01–1.02, p = 9.6 × 10−7).ConclusionWe found some evidence for specific causal pathways from personality to smoking phenotypes, and weaker evidence of an association from smoking initiation to personality. These findings could be used to inform future smoking interventions or to tailor existing schemes.

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