title: MR-PheWAS: hypothesis prioritization among potential causal effects of body mass index on many outcomes, using Mendelian randomization.
abstract: Observational cohort studies can provide rich datasets with a diverse range of phenotypic variables. However, hypothesis-driven epidemiological analyses by definition only test particular hypotheses chosen by researchers. Furthermore, observational analyses may not provide robust evidence of causality, as they are susceptible to confounding, reverse causation and measurement error. Using body mass index (BMI) as an exemplar, we demonstrate a novel extension to the phenome-wide association study (pheWAS) approach, using automated screening with genotypic instruments to screen for causal associations amongst any number of phenotypic outcomes. We used a sample of 8,121 children from the ALSPAC dataset, and tested the linear association of a BMI-associated allele score with 172 phenotypic outcomes (with variable sample sizes). We also performed an instrumental variable analysis to estimate the causal effect of BMI on each phenotype. We found 21 of the 172 outcomes were associated with the allele score at an unadjusted p < 0.05 threshold, and use Bonferroni corrections, permutation testing and estimates of the false discovery rate to consider the strength of results given the number of tests performed. The most strongly associated outcomes included leptin, lipid profile, and blood pressure. We also found novel evidence of effects of BMI on a global self-worth score.
authors.affiliation: MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, University of Bristol, Bristol.|Intelligent Systems Laboratory, Department of Computer Science, University of Bristol, UK.
authors.forename: Louise A C
authors.initials: LA
authors.lastname: Millard
authors.affiliation: MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, University of Bristol, Bristol.
authors.forename: Neil M
authors.initials: NM
authors.lastname: Davies
authors.affiliation: MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, University of Bristol, Bristol.
authors.forename: Nic J
authors.initials: NJ
authors.lastname: Timpson
authors.affiliation: MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, University of Bristol, Bristol.
authors.forename: Kate
authors.initials: K
authors.lastname: Tilling
authors.affiliation: MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, University of Bristol, Bristol.|Intelligent Systems Laboratory, Department of Computer Science, University of Bristol, UK.
authors.forename: Peter A
authors.initials: PA
authors.lastname: Flach
authors.affiliation: MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, University of Bristol, Bristol.
authors.forename: George
authors.initials: G
authors.lastname: Davey Smith
mesh_terms: D000483:Alleles; D000071516:Alpha-Ketoglutarate-Dependent Dioxygenase FTO; D001794:Blood Pressure / Q000235:genetics; D015992:Body Mass Index; D002648:Child; D015331:Cohort Studies; D005260:Female; D055106:Genome-Wide Association Study; D005838:Genotype; D006801:Humans; D020738:Leptin / Q000235:genetics; D008055:Lipids / Q000097:blood; D008137:Longitudinal Studies; D008297:Male; D057182:Mendelian Randomization Analysis; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide / Q000235:genetics; D011506:Proteins / Q000235:genetics
chemical_list: D020738:Leptin; D008055:Lipids; D011506:Proteins; D000071516:Alpha-Ketoglutarate-Dependent Dioxygenase FTO; C526492:FTO protein, human