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

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.

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Mendelian randomization analysis revealed causal effects from gut microbiota to abdominal obesity

10.1101/2020.04.20.052407 ◽

2020 ◽

Author(s):

Qian Xu ◽

Shan-Shan Zhang ◽

Yu-Fang Pei ◽

Jing-Jing Ni ◽

Lei Zhang ◽

...

Keyword(s):

Gut Microbiota ◽

Causal Relationship ◽

Abdominal Obesity ◽

Mendelian Randomization ◽

Association Studies ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Replication Sample ◽

Discovery Sample ◽

Increased Risk

ABSTRACTAlthough recent studies have revealed the association between the gut microbiota and obesity, the causality remains elusive. We performed a Mendelian Randomization (MR) analysis to determine whether there is a causal relationship between gut microbiota and abdominal obesity. We used a two-sample MR approach to assess the causal effect from gut microbiota to obesity based on genome-wide association studies (GWAS) summary statistics. The GWAS summary statistics of gut microbiota obtained from UK-twins cohort (N=1,126) were used as discovery sample exposure, and the GWAS summary statistics from the Genetic Environmental Microbial (GEM) project (N=1,098) were used as replication sample exposure. Trunk fat mass (TFM) summary statistics from the UK Biobank (UKB) cohort (N=330,762) were used as outcome. Bacteria were grouped into taxa features at family level. A total of 16 families were analyzed in the discovery sample. Family Barnesiellaceae was associated with TFM at the nominal significance level (b=-3.81×10−4, P=1.96×10−3). The causal association was successfully replicated in the replication sample (b=-7.34×10−3, P =2.77×10−2). Our findings provided evidence of causal relationship from microbiota to fat development, and may be helpful in selecting potential causal bacteria for manipulating candidate gut microbiota to therapy obesity.IMPORTANCEObesity, as a global public health problem, is one of the most important risk factors contributing to the overall global burden of disease, and is associated with an increased risk of cardiovascular disease, type 2 diabetes, and certain cancers. Recent studies have shown that gut microbiota is closely related to the development of obesity, but the causal relationship is unclear. Therefore, it is necessary to identify the causality between gut microbiota and obesity. The significance of our research is in identifying the causal relationship from specific bacteria to fat development, which will provide the new insights into the microbiota mediated the fat development mechanism.

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Evidence for genetic correlations and bidirectional, causal effects between smoking and sleep behaviours

10.1101/258384 ◽

2018 ◽

Cited By ~ 3

Author(s):

Mark Gibson ◽

Marcus R Munafò ◽

Amy E Taylor ◽

Jorien L. Treur

Keyword(s):

Smoking Cessation ◽

Sleep Duration ◽

Association Studies ◽

Genetic Correlations ◽

Smoking Initiation ◽

Causal Effects ◽

Poor Sleep ◽

Genome Wide Association Studies ◽

Level Data ◽

Increased Risk

AbstractIntroductionCigarette smokers are at increased risk of poor sleep behaviours. However, it is largely unknown whether these associations are due to shared (genetic) risk factors and/or causal effects (which may be bi-directional).MethodsWe obtained summary-level data of genome-wide association studies of smoking (smoking initiation (n=74,035), cigarettes per day (n=38,181) and smoking cessation (n=41,278)) and sleep behaviours (sleep duration and chronotype, or ‘morningness’) (n=128,266) and insomnia (n=113,006)). Using LD score regression, we calculated genetic correlations between smoking and sleep behaviours. To investigate causal effects, we employed Mendelian randomization (MR), both with summary-level data and individual level data (n=333,581 UK Biobank participants). For MR with summary-level data, individual genetic variants were combined with inverse-variance weighted meta-analysis, weighted median regression and MR Egger regression methods.ResultsWe found positive genetic correlations between insomnia and smoking initiation (rg=0.27, 95% CI 0.06 to 0.49) and insomnia and cigarettes per day (rg=0.15, 0.01 to 0.28), and negative genetic correlations between sleep duration and smoking initiation (rg=-0.14, -0.26 to -0.01) and chronotype and smoking cessation (rg=-0.18, -0.31 to -0.06). MR analyses provided strong evidence that smoking more cigarettes per day causally decreases the odds of being a morning person, and weak evidence that insomnia causally increases smoking heaviness and decreases smoking cessation odds.ConclusionsSmoking and sleep behaviours show moderate genetic correlation. Heavier smoking seems to causally affect circadian rhythm and there is some indication that insomnia increases smoking heaviness and hampers cessation. Our findings point to sleep as a potentially interesting smoking treatment target.

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

10.1101/19009365 ◽

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.

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Causal Inference Between Chronic Periodontitis and Chronic Kidney Disease: A Bidirectional Mendelian Randomization Analysis in a European Population

Frontiers in Genetics ◽

10.3389/fgene.2021.676136 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jie Yang ◽

Tianyi Chen ◽

Yahong Zhu ◽

Mingxia Bai ◽

Xingang Li

Keyword(s):

Chronic Kidney Disease ◽

Kidney Disease ◽

Causal Inference ◽

Causal Relationship ◽

Instrumental Variables ◽

Chronic Periodontitis ◽

Mendelian Randomization ◽

Association Studies ◽

Genome Wide Association Studies ◽

Summary Statistics

BackgroundPrevious epidemiological studies have shown significant associations between chronic periodontitis (CP) and chronic kidney disease (CKD), but the causal relationship remains uncertain. Aiming to examine the causal relationship between these two diseases, we conducted a bidirectional two-sample Mendelian randomization (MR) analysis with multiple MR methods.MethodsFor the casual effect of CP on CKD, we selected seven single-nucleotide polymorphisms (SNPs) specific to CP as genetic instrumental variables from the genome-wide association studies (GWAS) in the GLIDE Consortium. The summary statistics of complementary kidney function measures, i.e., estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN), were derived from the GWAS in the CKDGen Consortium. For the reversed causal inference, six SNPs associated with eGFR and nine with BUN from the CKDGen Consortium were included and the summary statistics were extracted from the CLIDE Consortium.ResultsNo significant causal association between genetically determined CP and eGFR or BUN was found (all p > 0.05). Based on the conventional inverse variance-weighted method, one of seven instrumental variables supported genetically predicted CP being associated with a higher risk of eGFR (estimate = 0.019, 95% CI: 0.012–0.026, p < 0.001).ConclusionEvidence from our bidirectional causal inference does not support a causal relation between CP and CKD risk and therefore suggests that associations reported by previous observational studies may represent confounding.

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Evaluating the effects of alcohol and tobacco use on cardiovascular disease using multivariable Mendelian randomization

10.1101/757146 ◽

2019 ◽

Cited By ~ 1

Author(s):

Daniel B. Rosoff ◽

George Davey Smith ◽

Nehal Mehta ◽

Toni-Kim Clarke ◽

Falk W. Lohoff

Keyword(s):

Risk Factors ◽

Cardiovascular Disease ◽

Alcohol Use ◽

Tobacco Use ◽

Mendelian Randomization ◽

Association Studies ◽

Density Lipoprotein ◽

Genome Wide Association Studies ◽

Cvd Risk ◽

Increased Risk

ABSTRACTAlcohol and tobacco use, two major modifiable risk factors for cardiovascular disease (CVD), are often consumed together. Using large publicly available genome-wide association studies (results from > 940,000 participants), we conducted two-sample multivariable Mendelian randomization (MR) to simultaneously assess the independent effects of alcohol and tobacco use on CVD risk factors and events. We found genetic instruments associated with increased alcohol use, controlling for tobacco use, associated with increased high-density-lipoprotein-cholesterol (HDL-C), decreased triglycerides, but not with coronary heart disease (CHD), myocardial infarction (MI), nor stroke; and instruments for increased tobacco use, controlling for alcohol use, associated with decreased HDL-C, increased triglycerides, and increased risk of CHD and MI. Exploratory analysis found associations with HDL-C, LDL-C, and intermediate-density-lipoprotein metabolites. Consistency of results across complementary methods accommodating different MR assumptions strengthened causal inference, providing strong genetic evidence for the causal effects of modifiable lifestyle risk factors on CVD risk.

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Daytime sleepiness, night sleep changes and ALS: a Mendelian randomization study

10.21203/rs.3.rs-34260/v1 ◽

2020 ◽

Author(s):

Gan Zhang ◽

Linjing Zhang ◽

Tao Huang ◽

Dongsheng Fan

Keyword(s):

Sleep Duration ◽

Daytime Sleepiness ◽

Mendelian Randomization ◽

Association Studies ◽

Sleep Efficiency ◽

Genome Wide Association Studies ◽

Night Sleep ◽

Inverse Variance ◽

Point Increase ◽

Increased Risk

Abstract Background Observational studies have indicated that there is a high prevalence of daytime sleepiness and night sleep changes in amyotrophic lateral sclerosis (ALS). However, the actual relation between these symptoms and ALS remains unclear. We aimed to determine whether daytime sleepiness and night sleep changes have an effect on ALS. Methods We used 2-sample mendelian randomization to estimate the effects of daytime sleepiness, sleep efficiency, number of sleep episodes and sleep duration on ALS. Summary statistics we used was from resent and large genome-wide association studies on the traits we chosen (n = 85,670–452,071) and ALS (cases n = 20,806, controls n = 59,804). Inverse variance weighted method was used as the main method for assessing causality. Results A genetically predicted 1-point increase in the assessment of daytime sleepiness was significantly associated with an increased risk of ALS (inverse-variance-weighted (IVW) odds ratio = 2.70, 95% confidence interval (CI): 1.27–5.76; P = 0.010). ALS was not associated with a genetically predicted 1-SD increase in sleep efficiency (IVW 1.01, 0.64–1.58; P = 0.973), Number of sleep episodes (IVW 1.02, 0.80–1.30; P = 0.859) or sleep duration (IVW 1.00, 1.00–1.01; P = 0.250). Conclusions Our results provide novel evidence that daytime sleepiness causes an increase in the risk of ALS and indicate that daytime sleepiness may be inherent in preclinical and clinical ALS patients, rather than simply affected by potential influencing factors.

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Educational attainment impacts drinking behaviors and risk for alcohol dependence: results from a two-sample Mendelian randomization study with ~780,000 participants

Molecular Psychiatry ◽

10.1038/s41380-019-0535-9 ◽

2019 ◽

Cited By ~ 4

Author(s):

Daniel B. Rosoff ◽

Toni-Kim Clarke ◽

Mark J. Adams ◽

Andrew M. McIntosh ◽

George Davey Smith ◽

...

Keyword(s):

Alcohol Use ◽

Educational Attainment ◽

Alcohol Dependence ◽

Mendelian Randomization ◽

Association Studies ◽

Significant Snps ◽

Genome Wide Association Studies ◽

Reverse Causality ◽

Genome Wide ◽

Genetic Instruments

Abstract Observational studies suggest that lower educational attainment (EA) may be associated with risky alcohol use behaviors; however, these findings may be biased by confounding and reverse causality. We performed two-sample Mendelian randomization (MR) using summary statistics from recent genome-wide association studies (GWAS) with >780,000 participants to assess the causal effects of EA on alcohol use behaviors and alcohol dependence (AD). Fifty-three independent genome-wide significant SNPs previously associated with EA were tested for association with alcohol use behaviors. We show that while genetic instruments associated with increased EA are not associated with total amount of weekly drinks, they are associated with reduced frequency of binge drinking ≥6 drinks (ßIVW = −0.198, 95% CI, −0.297 to –0.099, PIVW = 9.14 × 10−5), reduced total drinks consumed per drinking day (ßIVW = −0.207, 95% CI, −0.293 to –0.120, PIVW = 2.87 × 10−6), as well as lower weekly distilled spirits intake (ßIVW = −0.148, 95% CI, −0.188 to –0.107, PIVW = 6.24 × 10−13). Conversely, genetic instruments for increased EA were associated with increased alcohol intake frequency (ßIVW = 0.331, 95% CI, 0.267–0.396, PIVW = 4.62 × 10−24), and increased weekly white wine (ßIVW = 0.199, 95% CI, 0.159–0.238, PIVW = 7.96 × 10−23) and red wine intake (ßIVW = 0.204, 95% CI, 0.161–0.248, PIVW = 6.67 × 10−20). Genetic instruments associated with increased EA reduced AD risk: an additional 3.61 years schooling reduced the risk by ~50% (ORIVW = 0.508, 95% CI, 0.315–0.819, PIVW = 5.52 × 10−3). Consistency of results across complementary MR methods accommodating different assumptions about genetic pleiotropy strengthened causal inference. Our findings suggest EA may have important effects on alcohol consumption patterns and may provide potential mechanisms explaining reported associations between EA and adverse health outcomes.

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MR-LDP: a two-sample Mendelian randomization for GWAS summary statistics accounting for linkage disequilibrium and horizontal pleiotropy

NAR Genomics and Bioinformatics ◽

10.1093/nargab/lqaa028 ◽

2020 ◽

Vol 2 (2) ◽

Cited By ~ 2

Author(s):

Qing Cheng ◽

Yi Yang ◽

Xingjie Shi ◽

Kar-Fu Yeung ◽

Can Yang ◽

...

Keyword(s):

Risk Factors ◽

Linkage Disequilibrium ◽

Genetic Variants ◽

Mendelian Randomization ◽

Association Studies ◽

Alternative Methods ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Causal Relationships ◽

Disease Outcomes

Abstract The proliferation of genome-wide association studies (GWAS) has prompted the use of two-sample Mendelian randomization (MR) with genetic variants as instrumental variables (IVs) for drawing reliable causal relationships between health risk factors and disease outcomes. However, the unique features of GWAS demand that MR methods account for both linkage disequilibrium (LD) and ubiquitously existing horizontal pleiotropy among complex traits, which is the phenomenon wherein a variant affects the outcome through mechanisms other than exclusively through the exposure. Therefore, statistical methods that fail to consider LD and horizontal pleiotropy can lead to biased estimates and false-positive causal relationships. To overcome these limitations, we proposed a probabilistic model for MR analysis in identifying the causal effects between risk factors and disease outcomes using GWAS summary statistics in the presence of LD and to properly account for horizontal pleiotropy among genetic variants (MR-LDP) and develop a computationally efficient algorithm to make the causal inference. We then conducted comprehensive simulation studies to demonstrate the advantages of MR-LDP over the existing methods. Moreover, we used two real exposure–outcome pairs to validate the results from MR-LDP compared with alternative methods, showing that our method is more efficient in using all-instrumental variants in LD. By further applying MR-LDP to lipid traits and body mass index (BMI) as risk factors for complex diseases, we identified multiple pairs of significant causal relationships, including a protective effect of high-density lipoprotein cholesterol on peripheral vascular disease and a positive causal effect of BMI on hemorrhoids.

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Association of 25 hydroxyvitamin D concentration with risk of COVID-19: a Mendelian randomization study

10.1101/2020.08.09.20171280 ◽

2020 ◽

Author(s):

Di Liu ◽

Qiuyue Tian ◽

Jie Zhang ◽

Haifeng Hou ◽

Wei Wang ◽

...

Keyword(s):

Causal Relationship ◽

Mendelian Randomization ◽

Association Studies ◽

Sensitivity Analyses ◽

Genome Wide Association Studies ◽

Causal Association ◽

Hydroxyvitamin D ◽

Increased Risk ◽

25Ohd Concentration ◽

25 Hydroxyvitamin D

Background In observational studies, 25 hydroxyvitamin D (25OHD) concentration has been associated with an increased risk of Coronavirus disease 2019 (COVID-19). However, it remains unclear whether this association is causal. Methods We performed a two-sample Mendelian randomization (MR) to explore the causal relationship between 25OHD concentration and COVID-19, using summary data from the genome-wide association studies (GWASs) and using 25OHD concentration-related SNPs as instrumental variables (IVs). Results MR analysis did not show any evidence of a causal association of 25OHD concentration with COVID-19 susceptibility and severity (odds ratio [OR]=1.136, 95% confidence interval [CI] 0.988-1.306, P=0.074; OR=0.889, 95% CI 0.549-1.439, P=0.632). Sensitivity analyses using different instruments and statistical models yielded similar findings, suggesting the robustness of the causal association. No obvious pleiotropy bias and heterogeneity were observed. Conclusion The MR analysis showed that there might be no linear causal relationship of 25OHD concentration with COVID-19 susceptibility and severity.

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

10.1101/2020.06.24.20138834 ◽

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.

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