Elucidation of causal direction between asthma and obesity: a bi-directional Mendelian randomization study.

BACKGROUND Observational associations between asthma and obesity are well established, but inferring causality is challenging. We leveraged publicly available summary statistics to ascertain the causal direction between asthma and obesity via Mendelian randomization in European-ancestry adults. METHODS We performed two-sample bi-directional Mendelian randomization analysis using publicly available genome-wide association studies summary statistics. Single nucleotide polymorphisms associated with asthma and body mass index at genome-wide significance were combined using a fixed effect meta-analysis in each direction. An extensive sensitivity analysis was considered. RESULTS There was evidence in support of increasing causal effect of body mass index on risk of asthma (odds ratio 1.18 per unit increase, 95% confidence interval (CI) (1.11, 1.25), P = 2 × 10-8. No significant causal effect of asthma on adult body mass index was observed [estimate -0.004, 95% CI (-0.018, 0.009), P = 0.553]. CONCLUSIONS Our results confirmed that in European-ancestry populations, adult body mass index is likely to be causally linked to the risk of asthma; yet the effect of asthma on body mass index is small, if present at all.

[1]  M. Grayson,et al.  Heterogeneity and the origins of asthma. , 2018, Annals of allergy, asthma & immunology : official publication of the American College of Allergy, Asthma, & Immunology.

[2]  T. Liou,et al.  Causal relationships between adiposity and childhood asthma: bi-directional Mendelian Randomization analysis , 2018, International Journal of Obesity.

[3]  A. Price,et al.  Mixed-model association for biobank-scale datasets , 2018, Nature Genetics.

[4]  B. Neale,et al.  Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases , 2018, Nature Genetics.

[5]  Luke R. Lloyd-Jones,et al.  Transformation of Summary Statistics from Linear Mixed Model Association on All-or-None Traits to Odds Ratio , 2018, Genetics.

[6]  T. Hansen,et al.  Estimating the causal effect of body mass index on hay fever, asthma and lung function using Mendelian randomization , 2018, Allergy.

[7]  J. Revez,et al.  Lessons from ten years of genome-wide association studies of asthma , 2017, Clinical & translational immunology.

[8]  Manuel A. R. Ferreira,et al.  Multiancestry association study identifies new asthma risk loci that colocalize with immune cell enhancer marks , 2017, Nature Genetics.

[9]  A. Price,et al.  Distinguishing genetic correlation from causation across 52 diseases and complex traits , 2017, bioRxiv.

[10]  P. Donnelly,et al.  Genome-wide genetic data on ~500,000 UK Biobank participants , 2017, bioRxiv.

[11]  Christopher S. Poultney,et al.  Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia , 2017, Molecular Autism.

[12]  Igor Burstyn,et al.  Umbilical cord blood androgen levels and ASD-related phenotypes at 12 and 36 months in an enriched risk cohort study , 2017, Molecular Autism.

[13]  Danny J. Smith,et al.  Cannabis use and risk of schizophrenia: a Mendelian randomization study , 2016, Molecular Psychiatry.

[14]  Eugene Bleecker,et al.  Asthma heterogeneity and severity , 2016, The World Allergy Organization journal.

[15]  William J. Astle,et al.  Allelic Landscape of Human Blood Cell Trait Variation and Links , 2016 .

[16]  S. Thompson,et al.  Bias due to participant overlap in two‐sample Mendelian randomization , 2016, Genetic epidemiology.

[17]  N. Eriksson,et al.  Genome-wide association and HLA region fine-mapping studies identify susceptibility loci for multiple common infections , 2016, Nature Communications.

[18]  D. Lawlor Commentary: Two-sample Mendelian randomization: opportunities and challenges , 2016, International journal of epidemiology.

[19]  G. Davey Smith,et al.  Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator , 2016, Genetic epidemiology.

[20]  James T. Elder,et al.  Genome-wide Association Analysis of Psoriatic Arthritis and Cutaneous Psoriasis Reveals Differences in Their Genetic Architecture. , 2015, American journal of human genetics.

[21]  S. Weiss,et al.  CTNNA3 and SEMA3D: Promising loci for asthma exacerbation identified through multiple genome-wide association studies. , 2015, The Journal of allergy and clinical immunology.

[22]  Mitchell J. Machiela,et al.  LDlink: a web-based application for exploring population-specific haplotype structure and linking correlated alleles of possible functional variants , 2015, Bioinform..

[23]  B. Nordestgaard,et al.  Obese individuals experience wheezing without asthma but not asthma without wheezing: a Mendelian randomisation study of 85 437 adults from the Copenhagen General Population Study , 2015, Thorax.

[24]  P. Visscher,et al.  New data and an old puzzle: the negative association between schizophrenia and rheumatoid arthritis. , 2015, International journal of epidemiology.

[25]  Judy H. Cho,et al.  Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations , 2015, Nature Genetics.

[26]  Saskia le Cessie,et al.  Mendelian randomization studies: a review of the approaches used and the quality of reporting. , 2015, International journal of epidemiology.

[27]  G. Davey Smith,et al.  Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression , 2015, International journal of epidemiology.

[28]  N. Timpson,et al.  Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors , 2015, European Journal of Epidemiology.

[29]  P. Elliott,et al.  UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age , 2015, PLoS medicine.

[30]  Ross M. Fraser,et al.  Genetic studies of body mass index yield new insights for obesity biology , 2015, Nature.

[31]  C. Ulrik,et al.  Obesity and asthma: current knowledge and future needs , 2015, Current opinion in pulmonary medicine.

[32]  J. Sterne,et al.  Effects of BMI, Fat Mass, and Lean Mass on Asthma in Childhood: A Mendelian Randomization Study , 2014, PLoS medicine.

[33]  Michael F Dulin,et al.  Obesity and asthma: Pathophysiology and implications for diagnosis and management in primary care , 2014, Experimental biology and medicine.

[34]  E. R. Sutherland,et al.  Linking obesity and asthma , 2014, Annals of the New York Academy of Sciences.

[35]  A. Dixon,et al.  The Many Faces of Asthma in Obesity , 2014, Journal of cellular biochemistry.

[36]  C. Ulrik,et al.  Obesity and asthma: a coincidence or a causal relationship? A systematic review. , 2013, Respiratory medicine.

[37]  A. Dixon,et al.  Effects of obesity and weight loss on airway physiology and inflammation in asthma. , 2013, Pulmonary pharmacology & therapeutics.

[38]  C. Salome,et al.  Obesity, expiratory flow limitation and asthma symptoms. , 2013, Pulmonary pharmacology & therapeutics.

[39]  S. Farzan The Asthma Phenotype in the Obese: Distinct or Otherwise? , 2013, Journal of allergy.

[40]  R. Pratley,et al.  Obesity and asthma: an inflammatory disease of adipose tissue not the airway. , 2012, American journal of respiratory and critical care medicine.

[41]  C. Ulrik,et al.  Asthma and obesity: does weight loss improve asthma control? a systematic review , 2012, Journal of asthma and allergy.

[42]  L. Wood,et al.  Obesity and childhood asthma – mechanisms and manifestations , 2012, Current opinion in allergy and clinical immunology.

[43]  Christian Gieger,et al.  A genome-wide association study of plasma total IgE concentrations in the Framingham Heart Study. , 2012, The Journal of allergy and clinical immunology.

[44]  Y. Kamatani,et al.  Genome-wide association study of classical Hodgkin lymphoma and Epstein-Barr virus status-defined subgroups. , 2012, Journal of the National Cancer Institute.

[45]  E. Forno,et al.  Obesity and asthma , 2018, The Journal of allergy and clinical immunology.

[46]  W. Busse,et al.  Obesity and asthma: an association modified by age of asthma onset. , 2011, The Journal of allergy and clinical immunology.

[47]  Helen Schuilenburg,et al.  Genome-wide association study and meta-analysis finds over 40 loci affect risk of type 1 diabetes , 2009, Nature Genetics.

[48]  D. Postma,et al.  Sequence variants affecting eosinophil numbers associate with asthma and myocardial infarction , 2009, Nature Genetics.

[49]  Pui-Yan Kwok,et al.  Genomewide Scan Reveals Association of Psoriasis with IL-23 and NF-κB Pathways , 2008, Nature Genetics.

[50]  Vincent Plagnol,et al.  Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci , 2008, Nature Genetics.

[51]  George Davey Smith,et al.  Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology , 2008, Statistics in medicine.

[52]  Joseph T. Glessner,et al.  A genome-wide association study identifies KIAA0350 as a type 1 diabetes gene , 2007, Nature.

[53]  P. Nafstad,et al.  Body mass index in relation to adult asthma among 135,000 Norwegian men and women. , 2004, American journal of epidemiology.

[54]  S. Ebrahim,et al.  'Mendelian randomization': can genetic epidemiology contribute to understanding environmental determinants of disease? , 2003, International journal of epidemiology.

[55]  M. Katan APOUPOPROTEIN E ISOFORMS, SERUM CHOLESTEROL, AND CANCER , 1986, The Lancet.

[56]  Tm Brouwers,et al.  VIRUS-INFECTION OF URINARY-TRACT , 1974 .

[57]  A. Khera,et al.  Mendelian Randomization. , 2017, JAMA.

[58]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .