scholarly journals Does Smoking Cause Lower Educational Attainment and General Cognitive Ability? Triangulation of causal evidence using multiple study designs

2019 ◽  
Author(s):  
Suzanne H. Gage ◽  
Hannah Sallis ◽  
Glenda Lassi ◽  
Robyn Wootton ◽  
Claire Mokrysz ◽  
...  
Keyword(s):  
Cohort Study ◽  
Educational Attainment ◽  
Cognitive Ability ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Smoking Initiation ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Lower Educational Attainment

AbstractObjectivesObservational epidemiological studies have found associations between smoking and both poorer cognitive ability and lower educational attainment; however, evaluating causality is more challenging. We used two complementary methods to attempt to ascertain whether smoking causes poorer cognitive ability and lower educational attainment.DesignA cohort study (Study One) and a two-sample Mendelian randomization study using publicly-available summary statistics (Study Two).SettingThe Avon Longitudinal Study of Parents and Children (ALSPAC), a birth-cohort study based in Bristol, United Kingdom, and general population samples from published genome-wide association studies (GWAS).ParticipantsUp to 12,004 young people in ALSPAC (complete case analysis N = 2,107) (Study One and Study Two), and summary statistics from three previously published GWAS (not individual-level data) (Study Two).Main outcome measuresCognitive ability at age 15 (assessed via the Wechsler Abbreviated Scale of Intelligence) and educational attainment at age 16 (assessed via school records) (Study One), and educational attainment (measured as years in education) and fluid intelligence from previously published GWAS (Study Two).ResultsIn Study One, heaviness of smoking at age 15 was associated with lower cognitive ability at age 15 and lower educational attainment at age 16. Adjustment for potential confounders and earlier cognitive ability or educational attainment attenuated findings although evidence of an association remained (e.g., fully adjusted cognitive ability beta - 0.736, 95% CI −1.238 to −0.233, P = 0.004; fully adjusted educational attainment beta −1.254, 95% CI −1.597 to −0.911, P < 0.001). Comparable results were found in sensitivity analyses of multiply imputed data. In Study Two, two-sample Mendelian randomization indicated that both smoking initiation and lifetime smoking lower educational attainment and cognitive ability (e.g., smoking initiation to educational attainment inverse-variance weighted MR beta −0.197, 95% CI −0.223, −0.171, P = 1.78 × 10−49). Educational attainment results were robust to various sensitivity analyses, while cognition analyses were less so.ConclusionsOur results provide evidence consistent with a causal effect of smoking on lower educational attainment, although were less consistent for cognitive ability. The triangulation of evidence from observational and Mendelian randomisation methods is an important strength for causal inference.Summary boxesWhat is already known on this topicAssociations are seen between smoking and both educational attainment and cognition. These is some evidence that educational attainment might causally influence smoking, but causality in the opposite direction has not been assessed.What this study addsUsing multiple methodologies, we found evidence consistent with a causal effect of smoking on lower educational attainment. An exploration of potential mechanisms could inform the development of interventions to mitigate this risk.

scholarly journals Does smoking cause lower educational attainment and general cognitive ability? Triangulation of causal evidence using multiple study designs

2020 ◽  
pp. 1-9
Author(s):  
Suzanne H. Gage ◽  
Hannah M. Sallis ◽  
Glenda Lassi ◽  
Robyn E. Wootton ◽  
Claire Mokrysz ◽  
...  
Keyword(s):  
Educational Attainment ◽  
Cognitive Ability ◽  
Fluid Intelligence ◽  
Causal Effect ◽  
Smoking Initiation ◽  
Sensitivity Analyses ◽  
Mendelian Randomisation ◽  
General Cognitive Ability ◽  
Inverse Variance ◽  
Lower Educational Attainment

Abstract Background Observational studies have found associations between smoking and both poorer cognitive ability and lower educational attainment; however, evaluating causality is challenging. We used two complementary methods to explore this. Methods We conducted observational analyses of up to 12 004 participants in a cohort study (Study One) and Mendelian randomisation (MR) analyses using summary and cohort data (Study Two). Outcome measures were cognitive ability at age 15 and educational attainment at age 16 (Study One), and educational attainment and fluid intelligence (Study Two). Results Study One: heaviness of smoking at age 15 was associated with lower cognitive ability at age 15 and lower educational attainment at age 16. Adjustment for potential confounders partially attenuated findings (e.g. fully adjusted cognitive ability β −0.736, 95% CI −1.238 to −0.233, p = 0.004; fully adjusted educational attainment β −1.254, 95% CI −1.597 to −0.911, p < 0.001). Study Two: MR indicated that both smoking initiation and lifetime smoking predict lower educational attainment (e.g. smoking initiation to educational attainment inverse-variance weighted MR β −0.197, 95% CI −0.223 to −0.171, p = 1.78 × 10−49). Educational attainment results were robust to sensitivity analyses, while analyses of general cognitive ability were less so. Conclusion We find some evidence of a causal effect of smoking on lower educational attainment, but not cognitive ability. Triangulation of evidence across observational and MR methods is a strength, but the genetic variants associated with smoking initiation may be pleiotropic, suggesting caution in interpreting these results. The nature of this pleiotropy warrants further study.

scholarly journals Investigating causality in associations between education and smoking: A two-sample Mendelian randomization study

2017 ◽  
Author(s):  
Suzanne H. Gage ◽  
Jack Bowden ◽  
George Davey Smith ◽  
Marcus R. Munafo
Keyword(s):  
Smoking Cessation ◽  
Educational Attainment ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Smoking Initiation ◽  
Self Report ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Increased Risk ◽  
Higher Educational Attainment

AbstractBackgroundLower educational attainment is associated with increased rates of smoking, but ascertaining causality is challenging. We used two-sample Mendelian randomization (MR) analyses of summary statistics to examine whether educational attainment is causally related to smoking.Methods and FindingsWe used summary statistics from genome-wide association studies of educational attainment and a range of smoking phenotypes (smoking initiation, cigarettes per day, cotinine levels and smoking cessation). Various complementary MR techniques (inverse-variance weighted regression, MR Egger, weighted-median regression) were used to test the robustness of our results. We found broadly consistent evidence across these techniques that higher educational attainment leads to reduced likelihood of smoking initiation, reduced heaviness of smoking among smokers (as measured via self-report and cotinine levels), and greater likelihood of smoking cessation among smokers.ConclusionsOur findings indicate a causal association between low educational attainment and increased risk of smoking, and may explain the observational associations between educational attainment and adverse health outcomes such as risk of coronary heart disease.

scholarly journals The Parkinson’s Disease Mendelian Randomization Research Portal

2019 ◽  
Author(s):  
Alastair J Noyce ◽  
Sara Bandres-Ciga ◽  
Jonggeol Kim ◽  
Karl Heilbron ◽  
Demis Kia ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
P Value ◽  
Phenotypic Traits ◽  
Genome Wide Association Studies ◽  
Summary Statistics

ABSTRACTBackgroundMendelian randomization (MR) is a method for exploring observational associations to find evidence of causality.ObjectiveTo apply MR between multiple risk factors/phenotypic traits (exposures) and Parkinson’s disease (PD) in a large, unbiased manner, and to create a public resource for research.MethodsWe used two-sample MR in which the summary statistics relating to SNPs from genome wide association studies (GWASes) of 5,839 exposures curated on MR Base were used to assess causal relationships with PD. We selected the highest quality exposure GWASes for this report (n=401). For the disease outcome, summary statistics from the largest published PD GWAS were used. For each exposure, the causal effect on PD was assessed using the inverse variance weighted (IVW) method, followed by a range of sensitivity analyses. We used a false discovery rate (FDR) corrected p-value of <0.05 from the IVW analysis to prioritize traits of interest.ResultsWe observed evidence for causal associations between twelve exposures and risk of PD. Of these, nine were causal effects related to increasing adiposity and decreasing risk of PD. The remaining top exposures that affected PD risk were tea drinking, time spent watching television and forced vital capacity, but the latter two appeared to be biased by violations of underlying MR assumptions.DiscussionWe present a new platform which offers MR analyses for a total of 5,839 GWASes versus the largest PD GWASes available (https://pdgenetics.shinyapps.io/pdgenetics/). Alongside, we report further evidence to support a causal role for adiposity on lowering the risk of PD.

scholarly journals Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations

2021 ◽  
Author(s):  
Fernando Pires Hartwig ◽  
Kate Tilling ◽  
George Davey Smith ◽  
Deborah A Lawlor ◽  
Maria Carolina Borges
Keyword(s):  
Waist Circumference ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Real Data ◽  
Sensitivity Analyses ◽  
Effect Estimate ◽  
Genome Wide Association Studies ◽  
Residual Confounding

Abstract Background Two-sample Mendelian randomization (MR) allows the use of freely accessible summary association results from genome-wide association studies (GWAS) to estimate causal effects of modifiable exposures on outcomes. Some GWAS adjust for heritable covariables in an attempt to estimate direct effects of genetic variants on the trait of interest. One, both or neither of the exposure GWAS and outcome GWAS may have been adjusted for covariables. Methods We performed a simulation study comprising different scenarios that could motivate covariable adjustment in a GWAS and analysed real data to assess the influence of using covariable-adjusted summary association results in two-sample MR. Results In the absence of residual confounding between exposure and covariable, between exposure and outcome, and between covariable and outcome, using covariable-adjusted summary associations for two-sample MR eliminated bias due to horizontal pleiotropy. However, covariable adjustment led to bias in the presence of residual confounding (especially between the covariable and the outcome), even in the absence of horizontal pleiotropy (when the genetic variants would be valid instruments without covariable adjustment). In an analysis using real data from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and UK Biobank, the causal effect estimate of waist circumference on blood pressure changed direction upon adjustment of waist circumference for body mass index. Conclusions Our findings indicate that using covariable-adjusted summary associations in MR should generally be avoided. When that is not possible, careful consideration of the causal relationships underlying the data (including potentially unmeasured confounders) is required to direct sensitivity analyses and interpret results with appropriate caution.

scholarly journals Univariable and Multivariable Two-Sample Mendelian Randomization Investigating the Effects of Leisure Sedentary Behaviors on the Risk of Lung Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Haoxin Peng ◽  
Xiangrong Wu ◽  
Yaokai Wen ◽  
Yiyuan Ao ◽  
Yutian Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Computer Use ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Sedentary Behaviors ◽  
Watching Tv

Background:Leisure sedentary behaviors (LSB) are widespread, and observational studies have provided emerging evidence that LSB play a role in the development of lung cancer (LC). However, the causal inference between LSB and LC remains unknown.Methods: We utilized univariable (UVMR) and multivariable two-sample Mendelian randomization (MVMR) analysis to disentangle the effects of LSB on the risk of LC. MR analysis was conducted with genetic variants from genome-wide association studies of LSB (408,815 persons from UK Biobank), containing 152 single-nucleotide polymorphisms (SNPs) for television (TV) watching, 37 SNPs for computer use, and four SNPs for driving, and LC from the International Lung Cancer Consortium (11,348 cases and 15,861 controls). Multiple sensitivity analyses were further performed to verify the causality.Results: UVMR demonstrated that genetically predisposed 1.5-h increase in LSB spent on watching TV increased the odds of LC by 90% [odds ratio (OR), 1.90; 95% confidence interval (CI), 1.44–2.50; p &lt; 0.001]. Similar trends were observed for squamous cell lung cancer (OR, 1.97; 95%CI, 1.31–2.94; p = 0.0010) and lung adenocarcinoma (OR, 1.64; 95%CI 1.12–2.39; p = 0.0110). The causal effects remained significant after adjusting for education (OR, 1.97; 95%CI, 1.44–2.68; p &lt; 0.001) and body mass index (OR, 1.86; 95%CI, 1.36–2.54; p &lt; 0.001) through MVMR approach. No association was found between prolonged LSB spent on computer use and driving and LC risk. Genetically predisposed prolonged LSB was additionally correlated with smoking (OR, 1.557; 95%CI, 1.287–1.884; p &lt; 0.001) and alcohol consumption (OR, 1.010; 95%CI, 1.004–1.016; p = 0.0016). Consistency of results across complementary sensitivity MR methods further strengthened the causality.Conclusion: Robust evidence was demonstrated for an independent, causal effect of LSB spent on watching TV in increasing the risk of LC. Further work is necessary to investigate the potential mechanisms.

scholarly journals The effect of smoking on multiple sclerosis: a mendelian randomization study

2020 ◽  
Author(s):  
Ruth E Mitchell ◽  
Kirsty Bates ◽  
Robyn E Wootton ◽  
Adil Harroud ◽  
J. Brent Richards ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Meta Analysis ◽  
Smoking Initiation ◽  
Smoking Behaviour ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Smoking Duration

AbstractThe causes of multiple sclerosis (MS) remain unknown. Smoking has been associated with MS in observational studies and is often thought of as an environmental risk factor. We used two-sample Mendelian Randomization (MR) to examined whether this association is causal using genetic variants identified in genome-wide association studies (GWAS) as associated with smoking. We assessed both smoking initiation and lifetime smoking behaviour (which captures smoking duration, heaviness and cessation). There was very limited evidence for a meaningful effect of smoking on MS susceptibility was measured using summary statistics from the International Multiple Sclerosis Genetics Consortium (IMSGC) meta-analysis, including 14,802 cases and 26,703 controls. There was no clear evidence for an effect of smoking on the risk of developing MS (smoking initiation: odds ratio [OR] 1.03, 95% confidence interval [CI] 0.92-1.61; lifetime smoking: OR 1.10, 95% CI 0.87-1.40). These findings suggest that smoking does not have a detrimental consequence on MS susceptibility. Further work is needed to determine the causal effect of smoking on MS progression.

scholarly journals An iterative approach to detect pleiotropy and perform Mendelian Randomization analysis using GWAS summary statistics

2020 ◽  
Author(s):  
Xiaofeng Zhu ◽  
Xiaoyin Li ◽  
Rong Xu ◽  
Tao Wang
Keyword(s):  
Complex Traits ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Real Data ◽  
Supplementary Information ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Causal Relationships ◽  
Multiple Traits

Abstract Motivation The overall association evidence of a genetic variant with multiple traits can be evaluated by cross-phenotype association analysis using summary statistics from genome-wide association studies. Further dissecting the association pathways from a variant to multiple traits is important to understand the biological causal relationships among complex traits. Results Here, we introduce a flexible and computationally efficient Iterative Mendelian Randomization and Pleiotropy (IMRP) approach to simultaneously search for horizontal pleiotropic variants and estimate causal effect. Extensive simulations and real data applications suggest that IMRP has similar or better performance than existing Mendelian Randomization methods for both causal effect estimation and pleiotropic variant detection. The developed pleiotropy test is further extended to detect colocalization for multiple variants at a locus. IMRP will greatly facilitate our understanding of causal relationships underlying complex traits, in particular, when a large number of genetic instrumental variables are used for evaluating multiple traits. Availability and implementation The software IMRP is available at https://github.com/XiaofengZhuCase/IMRP. The simulation codes can be downloaded at http://hal.case.edu/∼xxz10/zhu-web/ under the link: MR Simulations software. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Correction for sample overlap, winner's curse and weak instrument bias in two-sample Mendelian Randomization

2021 ◽  
Author(s):  
Ninon Mounier ◽  
Zoltan Kutalik
Keyword(s):  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Simulated Data ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Winner's Curse ◽  
Weak Instruments ◽  
Winner’S Curse ◽  
Wide Range

Inverse-variance weighted two-sample Mendelian Randomization (IVW-MR) is the most widely used approach that uses genome-wide association studies summary statistics to infer the existence and strength of the causal effect between an exposure and an outcome. Estimates from this approach can be subject to different biases due to: (i) the overlap between the exposure and outcome samples; (ii) the use of weak instruments and winner's curse. We developed a method that aims at tackling all these biases together. Assuming spike-and-slab genomic architecture and leveraging LD-score regression and other techniques, we could analytically derive and reliably estimate the bias of IVW-MR using association summary statistics only. This allowed us to apply a bias correction to IVW-MR estimates, which we tested using simulated data for a wide range of realistic scenarios. In all the explored scenarios, our correction reduced the bias, in some situations by as much as 30 folds. When applied to real data on obesity-related exposures, we observed significant differences between IVW-based and corrected effects, both for non-overlapping and fully overlapping samples. While most studies are extremely careful to avoid any sample overlap when performing two-sample MR analysis, we have demonstrated that the incurred bias is much less substantial than the one due to weak instruments or winner's curse, which are often ignored.

scholarly journals Educational Attainment Decreases the Risk of COVID-19 Severity in the European Population: A Two-Sample Mendelian Randomization Study

2021 ◽  
Vol 9 ◽  
Author(s):  
Masahiro Yoshikawa ◽  
Kensuke Asaba
Keyword(s):  
Educational Attainment ◽  
Lower Risk ◽  
Mendelian Randomization ◽  
European Population ◽  
Sensitivity Analyses ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Standard Deviation Increase ◽  
Summary Data ◽  
Years Of Schooling

Observational studies have reported that the severity of COVID-19 depends not only on physical conditions but also on socioeconomic status, including educational level. Because educational attainment (EA), which measures the number of years of schooling, is moderately heritable, we investigated the causal association of EA on the risk of COVID-19 severity using the Mendelian randomization (MR) approach. A two-sample MR analysis was performed using publicly available summary-level data sets of genome-wide association studies (GWASs). A total of 235 single-nucleotide polymorphisms (SNPs) were extracted as instrumental variables for the exposure of EA from the Social Science Genetic Association Consortium GWAS summary data of 766,345 participants of European ancestry. The effect of each SNP on the outcome of COVID-19 severity risk was obtained from the GWAS summary data of 1,059,456 participants of European ancestry gathered from the COVID-19 Host Genetics Initiative. Using inverse variance weighted method, our MR study shows that EA was significantly associated with a lower risk of COVID-19 severity (odds ratio per one standard deviation increase in years of schooling, 0.540; 95% confidence interval, 0.376–0.777, P = 0.0009). A series of sensitivity analyses showed little evidence of bias. In conclusion, we show for the first time using a two-sample MR approach the associations between higher EA and the lower risk of COVID-19 severity in the European population. However, the genetic or epidemiological mechanisms underlying the association between EA and the risk of COVID-19 severity remain unknown, and further studies are warranted to validate the MR findings and investigate underlying mechanisms.

scholarly journals Depression and Osteoporosis: A Mendelian Randomization Study

2021 ◽  
Author(s):  
Bin He ◽  
Qiong Lyu ◽  
Lifeng Yin ◽  
Muzi Zhang ◽  
Zhengxue Quan ◽  
...  
Keyword(s):  
Observational Studies ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Meta Analysis ◽  
Sensitivity Analyses ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Reverse Causality ◽  
Mineral Density

AbstractObservational studies suggest a link between depression and osteoporosis, but these may be subject to confounding and reverse causality. In this two-sample Mendelian randomization analysis, we included the large meta-analysis of genome-wide association studies for depression among 807,553 individuals (246,363 cases and 561,190 controls) of European descent, the large meta-analysis to identify genetic variants associated with femoral neck bone mineral density (FN-BMD), forearm BMD (FA-BMD) and lumbar spine BMD (LS-BMD) among 53,236 individuals of European ancestry, and the GWAS summary data of heel BMD (HE-BMD) and fracture among 426,824 individuals of European ancestry. The results revealed that genetic predisposition towards depression showed no causal effect on FA-BMD (beta-estimate: 0.091, 95% confidence interval [CI] − 0.088 to 0.269, SE:0.091, P value = 0.320), FN-BMD (beta-estimate: 0.066, 95% CI − 0.016 to 0.148, SE:0.042, P value = 0.113), LS-BMD (beta-estimate: 0.074, 95% CI − 0.029 to 0.177, SE:0.052, P value = 0.159), HE-BMD (beta-estimate: 0.009, 95% CI − 0.043 to 0.061, SE:0.027, P value = 0.727), or fracture (beta-estimate: 0.008, 95% CI − 0.071 to 0.087, SE:0.041, P value = 0.844). These results were also confirmed by multiple sensitivity analyses. Contrary to the findings of observational studies, our results do not reveal a causal role of depression in osteoporosis or fracture.

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