scholarly journals Smoking and COVID-19 outcomes: an observational and Mendelian randomisation study using the UK Biobank cohort

Thorax ◽  
2021 ◽  
pp. thoraxjnl-2021-217080
Author(s):  
Ashley K Clift ◽  
Adam von Ende ◽  
Pui San Tan ◽  
Hannah M Sallis ◽  
Nicola Lindson ◽  
...  
Keyword(s):  
Large Scale ◽  
Hospital Admissions ◽  
Causal Effect ◽  
Smoking Status ◽  
Smoking Initiation ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
Never Smokers ◽  
The Uk ◽  
Analytical Approaches

BackgroundConflicting evidence has emerged regarding the relevance of smoking on risk of COVID-19 and its severity.MethodsWe undertook large-scale observational and Mendelian randomisation (MR) analyses using UK Biobank. Most recent smoking status was determined from primary care records (70.8%) and UK Biobank questionnaire data (29.2%). COVID-19 outcomes were derived from Public Health England SARS-CoV-2 testing data, hospital admissions data, and death certificates (until 18 August 2020). Logistic regression was used to estimate associations between smoking status and confirmed SARS-CoV-2 infection, COVID-19-related hospitalisation, and COVID-19-related death. Inverse variance-weighted MR analyses using established genetic instruments for smoking initiation and smoking heaviness were undertaken (reported per SD increase).ResultsThere were 421 469 eligible participants, 1649 confirmed infections, 968 COVID-19-related hospitalisations and 444 COVID-19-related deaths. Compared with never-smokers, current smokers had higher risks of hospitalisation (OR 1.80, 95% CI 1.26 to 2.29) and mortality (smoking 1–9/day: OR 2.14, 95% CI 0.87 to 5.24; 10–19/day: OR 5.91, 95% CI 3.66 to 9.54; 20+/day: OR 6.11, 95% CI 3.59 to 10.42). In MR analyses of 281 105 White British participants, genetically predicted propensity to initiate smoking was associated with higher risks of infection (OR 1.45, 95% CI 1.10 to 1.91) and hospitalisation (OR 1.60, 95% CI 1.13 to 2.27). Genetically predicted higher number of cigarettes smoked per day was associated with higher risks of all outcomes (infection OR 2.51, 95% CI 1.20 to 5.24; hospitalisation OR 5.08, 95% CI 2.04 to 12.66; and death OR 10.02, 95% CI 2.53 to 39.72).InterpretationCongruent results from two analytical approaches support a causal effect of smoking on risk of severe COVID-19.

scholarly journals Polynomial Mendelian Randomization reveals widespread non-linear causal effects in the UK Biobank

2021 ◽  
Author(s):  
Jonathan Sulc ◽  
Jenny Sjaarda ◽  
Zoltan Kutalik
Keyword(s):  
Causal Inference ◽  
Large Scale ◽  
Causal Effect ◽  
Causal Effects ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
Individual Level ◽  
Glucose Levels ◽  
Causal Function ◽  
The Uk

Causal inference is a critical step in improving our understanding of biological processes and Mendelian randomisation (MR) has emerged as one of the foremost methods to efficiently interrogate diverse hypotheses using large-scale, observational data from biobanks. Although many extensions have been developed to address the three core assumptions of MR-based causal inference (relevance, exclusion restriction, and exchangeability), most approaches implicitly assume that any putative causal effect is linear. Here we propose PolyMR, an MR-based method which provides a polynomial approximation of an (arbitrary) causal function between an exposure and an outcome. We show that this method provides accurate inference of the shape and magnitude of causal functions with greater accuracy than existing methods. We applied this method to data from the UK Biobank, testing for effects between anthropometric traits and continuous health-related phenotypes and found most of these (84%) to have causal effects which deviate significantly from linear. These deviations ranged from slight attenuation at the extremes of the exposure distribution, to large changes in the magnitude of the effect across the range of the exposure (e.g. a 1 kg/m2 change in BMI having stronger effects on glucose levels if the initial BMI was higher), to non-monotonic causal relationships (e.g. the effects of BMI on cholesterol forming an inverted U shape). Finally, we show that the linearity assumption of the causal effect may lead to the misinterpretation of health risks at the individual level or heterogeneous effect estimates when using cohorts with differing average exposure levels.

scholarly journals Polynomial Mendelian Radomization reveals widespread non-linear causal effects in the UK Biobank

2022 ◽  
Author(s):  
Jonathan Sulc ◽  
Jennifer Sjaarda ◽  
Zoltan Kutalik
Keyword(s):  
Causal Inference ◽  
Large Scale ◽  
Causal Effect ◽  
Causal Effects ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
Individual Level ◽  
Glucose Levels ◽  
Causal Function ◽  
The Uk

Abstract Causal inference is a critical step in improving our understanding of biological processes and Mendelian randomisation (MR) has emerged as one of the foremost methods to efficiently interrogate diverse hypotheses using large-scale, observational data from biobanks. Although many extensions have been developed to address the three core assumptions of MR-based causal inference (relevance, exclusion restriction, and exchangeability), most approaches implicitly assume that any putative causal effect is linear. Here we propose PolyMR, an MR-based method which provides a polynomial approximation of an (arbitrary) causal function between an exposure and an outcome. We show that this method provides accurate inference of the shape and magnitude of causal functions with greater accuracy than existing methods. We applied this method to data from the UK Biobank, testing for effects between anthropometric traits and continuous health-related phenotypes and found most of these (84%) to have causal effects which deviate significantly from linear. These deviations ranged from slight attenuation at the extremes of the exposure distribution, to large changes in the magnitude of the effect across the range of the exposure (e.g. a 1 kg/m2 change in BMI having stronger effects on glucose levels if the initial BMI was higher), to non-monotonic causal relationships (e.g. the effects of BMI on cholesterol forming an inverted U shape). Finally, we show that the linearity assumption of the causal effect may lead to the misinterpretation of health risks at the individual level or heterogeneous effect estimates when using cohorts with differing average exposure levels.

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 Alcohol causes an increased risk of head and neck but not breast cancer in individuals from the UK Biobank study: A Mendelian randomisation analysis

2019 ◽  
Author(s):  
Nathan Ingold ◽  
Hasnat A Amin ◽  
Fotios Drenos
Keyword(s):  
Breast Cancer ◽  
Alcohol Consumption ◽  
Head And Neck ◽  
Causal Effect ◽  
Head And Neck Cancers ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
Increased Risk ◽  
The Uk ◽  
Risk Of Cancer

ABSTACTAlcohol intake and the risk of various types of cancers have been previously correlated. Correlation though does not always mean that a causal relationship between the two is present. Excessive alcohol consumption is also correlated with other lifestyle factors and behaviours, such as smoking and increased adiposity, that also affect the risk of cancer and make the identification and estimation of the causal effect of alcohol on cancer difficult. Here, using individual level data for 322,193 individuals from the UK Biobank, we report the observational and causal effects of alcohol consumption on types of cancer previously suggested as correlated to alcohol. Alcohol was observationally associated with cancers of the lower digestive system, head and neck and breast cancer. No associations were observed when we considered those keeping alcohol consumption below the recommended threshold of 14 units/week. When Mendelian randomisation was used to assess the causal effect of alcohol on cancer, we found that increasing alcohol consumption, especially above the recommended level, was causal to head and neck cancers but not breast cancer. Our results where replicated using a two sample MR method and data from the much larger COGS genome wide analysis of breast cancer. We conclude that alcohol is causally related to head and neck cancers, especially cancer of larynx, but the observed association with breast cancer are likely due to confounding. The suggested threshold of 14 units/week appears suitable to manage the risk of cancer due to alcohol.

scholarly journals Examining the association between family status and depression in the UK Biobank

2020 ◽  
Author(s):  
Alexandors Giannelis ◽  
Alish Palmos ◽  
Saskia P Hagenaars ◽  
Gerome Breen ◽  
Cathryn M Lewis ◽  
...  
Keyword(s):  
Causal Effect ◽  
Age Groups ◽  
Risk Scores ◽  
Mendelian Randomisation ◽  
Family Status ◽  
Uk Biobank ◽  
Number Of Children ◽  
The Uk ◽  
Social Demographic ◽  
Mental Health Questionnaire

Background: We examined associations between family status (living with a spouse or partner, number of children) and lifetime depression. Methods: We used data from the UK Biobank, a large prospective study of middle-aged and older adults. Lifetime depression was assessed as part of a follow-up mental health questionnaire. Logistic regression was used to estimate associations between family status and depression. We included extensive adjustment for social, demographic and other potential confounders, including depression polygenic risk scores. Results: 52,078 participants (mean age = 63.6, SD = 7.6; 52% female) were included in our analyses. Living with a spouse or partner was associated with substantially lower odds of lifetime depression (OR = 0.67, 95% CI 0.62-0.74). Compared to individuals without children, we found higher odds of lifetime depression for parents of one child (OR = 1.17, 95% CI 1.07-1.27), and parents of three (OR = 1.11, 95% CI 1.03-1.20) or four or more children (OR = 1.27, 95% CI 1.14-1.42). Amongst those not cohabiting, having any number of children was associated with higher odds of lifetime depression. Our results were consistent across age groups, the sexes, neighbourhood deprivation and genetic risk for depression. Exploratory Mendelian randomisation analyses suggested a causal effect of number of children on lifetime depression. Limitations: Our data did not allow distinguishing between non-marital and marital cohabitation. Results may not generalise to all ages or populations. Conclusions: Living with a spouse or partner was strongly associated with reduced odds of depression. Having one or three or more children was associated with increased odds of depression, especially in individuals not living with a spouse or partner.

scholarly journals A Mendelian randomisation study of smoking causality in IPF compared with COPD

2020 ◽  
Author(s):  
Anna Duckworth ◽  
Michael A. Gibbons ◽  
Robin N Beaumont ◽  
Andrew R Wood ◽  
Howard Almond ◽  
...  
Keyword(s):  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Disease Status ◽  
Disease Prevalence ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
Genetic Technique ◽  
Never Smokers ◽  
The Uk

AbstractIn a normal year, the fatal lung disease Idiopathic Pulmonary Fibrosis (IPF) accounts for ∼1% of UK deaths. Smoking is a recognised risk factor for IPF but the question of causality remains unanswered. Here, we used data from the UK Biobank (UKBB) and the well-established genetic technique of Mendelian randomisation (MR) methods to investigate whether smoking is causal for IPF compared with COPD, where causality is established.We looked at observational associations in unrelated Europeans, with 871 IPF cases, 11,413 COPD cases and 366,942 controls. We performed analyses using one-sample MR to test for inferred smoking causality in ever smokers using genetic variants that have a previously demonstrated association with smoking heaviness.Strong associations between disease status and ever having smoked were found in both IPF (OR = 1.52; 95%CI:1.32-1.74; P=2.4×10−8) and COPD (OR= 5.77; 95%CI:5.48-6.07; P<1×10−15). Using MR, a one allele increase in smoking volume genetic risk score was associated with higher odds of COPD in ever smokers, (OR = 4.32; 95%CI:3.37-5.54; P<1×10−15), but no association was seen in IPF (OR=0.55; 95%CI: 0.17-1.81; P=0.33). No association was found between the genetic risk score and disease prevalence in never smokers with IPF (OR = 1.00; 95%CI:0.98-1.02; P=1.00) or COPD (OR = 1.00; 95%CI:0.99-1.01; P=0.53).Although both IPF and COPD are observationally associated with smoking, our analysis provides evidence inferring that the association is causal in COPD but there is no such evidence in IPF. This suggests that other environmental exposures also need consideration in IPF.

scholarly journals Examining the effect of smoking on suicidal ideation and attempts: A triangulation of epidemiological approaches

2019 ◽  
Author(s):  
Ruth Harrison ◽  
Marcus R Munafò ◽  
George Davey Smith ◽  
Robyn E Wootton
Keyword(s):  
Suicidal Behaviour ◽  
Causal Effect ◽  
Smoking Status ◽  
Strong Association ◽  
Smoking Initiation ◽  
Smoking Behaviour ◽  
Mendelian Randomisation ◽  
Snp Analysis ◽  
Suicidal Thoughts ◽  
Smoking Behaviours

AbstractBackgroundPrevious literature has demonstrated a strong association between cigarette smoking and suicide-related behaviours, characterised as ideation, plans, attempts and suicide related death. This association has not previously been examined in a causal inference framework and has important implications for suicide prevention strategies.AimsWe aimed to examine the evidence for an association between smoking behaviours (initiation, smoking status, heaviness, lifetime smoking) and suicidal thoughts or attempts by triangulating across observational and Mendelian randomisation (MR) analyses.MethodsFirst, in the UK Biobank, we calculate observed associations between smoking behaviours and suicidal thoughts or attempts. Second, we used Mendelian randomisation (MR) to explore the relationship between smoking and suicide using genetic variants as instruments to reduce bias from residual confounding and reverse causation.ResultsOur observational analysis showed a relationship between smoking behaviour and suicidal behaviour, particularly between smoking initiation and suicidal attempts (OR = 2.07, 95% CI = 1.91 to 2.26, p<0.001). The MR analysis and single SNP analysis, however, did not support this. Despite past literature showing a positive dose-response relationship our results showed no clear evidence for a causal effect of smoking on suicidal behaviours.ConclusionThis was the first MR study to explore the effect of smoking on suicidal behaviours. Our results suggest that, despite observed associations, there is no strong evidence for a causal effect of smoking behaviour on suicidal behaviour. Our evidence suggests that further research is needed into alternative risk factors for suicide which might make better intervention targets.

scholarly journals Lack of an association between gallstone disease and bilirubin levels with risk of colorectal cancer: a Mendelian randomisation analysis

2021 ◽  
Author(s):  
Richard Culliford ◽  
Alex J. Cornish ◽  
Philip J. Law ◽  
Susan M. Farrington ◽  
Kimmo Palin ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Large Scale ◽  
Causal Effect ◽  
Gallstone Disease ◽  
Epidemiological Studies ◽  
Mendelian Randomisation ◽  
Linear Relationships ◽  
Potential Risk Factors ◽  
The Relationship ◽  
Circulating Levels

Abstract Background Epidemiological studies of the relationship between gallstone disease and circulating levels of bilirubin with risk of developing colorectal cancer (CRC) have been inconsistent. To address possible confounding and reverse causation, we examine the relationship between these potential risk factors and CRC using Mendelian randomisation (MR). Methods We used two-sample MR to examine the relationship between genetic liability to gallstone disease and circulating levels of bilirubin with CRC in 26,397 patients and 41,481 controls. We calculated the odds ratio per genetically predicted SD unit increase in log bilirubin levels (ORSD) for CRC and tested for a non-zero causal effect of gallstones on CRC. Sensitivity analysis was applied to identify violations of estimator assumptions. Results No association between either gallstone disease (P value = 0.60) or circulating levels of bilirubin (ORSD = 1.00, 95% confidence interval (CI) = 0.96–1.03, P value = 0.90) with CRC was shown. Conclusions Despite the large scale of this study, we found no evidence for a causal relationship between either circulating levels of bilirubin or gallstone disease with risk of developing CRC. While the magnitude of effect suggested by some observational studies can confidently be excluded, we cannot exclude the possibility of smaller effect sizes and non-linear relationships.

scholarly journals Machine Learning Prediction of Biomarkers from SNPs and of Disease Risk from Biomarkers in the UK Biobank

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 991
Author(s):  
Erik Widen ◽  
Timothy G. Raben ◽  
Louis Lello ◽  
Stephen D. H. Hsu
Keyword(s):  
Disease Risk ◽  
Smoking Status ◽  
Glycated Haemoglobin ◽  
European Ancestry ◽  
Risk Scores ◽  
Common Disease ◽  
Atherosclerotic Cardiovascular Disease ◽  
Uk Biobank ◽  
Lipoprotein A ◽  
The Uk

We use UK Biobank data to train predictors for 65 blood and urine markers such as HDL, LDL, lipoprotein A, glycated haemoglobin, etc. from SNP genotype. For example, our Polygenic Score (PGS) predictor correlates ∼0.76 with lipoprotein A level, which is highly heritable and an independent risk factor for heart disease. This may be the most accurate genomic prediction of a quantitative trait that has yet been produced (specifically, for European ancestry groups). We also train predictors of common disease risk using blood and urine biomarkers alone (no DNA information); we call these predictors biomarker risk scores, BMRS. Individuals who are at high risk (e.g., odds ratio of >5× population average) can be identified for conditions such as coronary artery disease (AUC∼0.75), diabetes (AUC∼0.95), hypertension, liver and kidney problems, and cancer using biomarkers alone. Our atherosclerotic cardiovascular disease (ASCVD) predictor uses ∼10 biomarkers and performs in UKB evaluation as well as or better than the American College of Cardiology ASCVD Risk Estimator, which uses quite different inputs (age, diagnostic history, BMI, smoking status, statin usage, etc.). We compare polygenic risk scores (risk conditional on genotype: PRS) for common diseases to the risk predictors which result from the concatenation of learned functions BMRS and PGS, i.e., applying the BMRS predictors to the PGS output.

scholarly journals Collateral impact of COVID-19: why should children continue to suffer?

2021 ◽  
Author(s):  
Prasad Nagakumar ◽  
Ceri-Louise Chadwick ◽  
Andrew Bush ◽  
Atul Gupta
Keyword(s):  
Young People ◽  
Large Scale ◽  
Hospital Admissions ◽  
Severe Disease ◽  
Children And Young People ◽  
Collateral Effects ◽  
Rsv Infection ◽  
Syncytial Virus ◽  
Set Up ◽  
The Uk

AbstractThe COVID-19 pandemic caused by SARS-COV-2 virus fortunately resulted in few children suffering from severe disease. However, the collateral effects on the COVID-19 pandemic appear to have had significant detrimental effects on children affected and young people. There are also some positive impacts in the form of reduced prevalence of viral bronchiolitis. The new strain of SARS-COV-2 identified recently in the UK appears to have increased transmissibility to children. However, there are no large vaccine trials set up in children to evaluate safety and efficacy. In this short communication, we review the collateral effects of COVID-19 pandemic in children and young people. We highlight the need for urgent strategies to mitigate the risks to children due to the COVID-19 pandemic. What is Known:• Children and young people account for <2% of all COVID-19 hospital admissions• The collateral impact of COVID-19 pandemic on children and young people is devastating• Significant reduction in influenza and respiratory syncytial virus (RSV) infection in the southern hemisphere What is New:• The public health measures to reduce COVID-19 infection may have also resulted in near elimination of influenza and RSV infections across the globe• A COVID-19 vaccine has been licensed for adults. However, large scale vaccine studies are yet to be initiated although there is emerging evidence of the new SARS-COV-2 strain spreading more rapidly though young people.• Children and young people continue to bear the collateral effects of COVID-19 pandemic

Sign in / Sign up

Export Citation Format

Share Document