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MR-PheWAS: hypothesis prioritization among potential causal effects of body mass index on many outcomes, using Mendelian randomization.

Millard LA, Davies NM, Timpson NJ, Tilling K, Flach PA, Davey Smith G - Sci Rep (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, University of Bristol, Bristol.

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.

No MeSH data available.


Distribution of the percentage of missing data, in our 8,121 sample, across the 172 outcomes.
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f6: Distribution of the percentage of missing data, in our 8,121 sample, across the 172 outcomes.

Mentions: As shown in Fig. 6, the outcomes had varying numbers of missing values, which means there were differences in statistical power across outcomes. However, the ranking of our main analysis is highly correlated with the ranking of the imputation dataset (Spearman’s rank correlation of 0.919 (P < 0.001)). Results using the imputed dataset are given in Supplementary Table 4.


MR-PheWAS: hypothesis prioritization among potential causal effects of body mass index on many outcomes, using Mendelian randomization.

Millard LA, Davies NM, Timpson NJ, Tilling K, Flach PA, Davey Smith G - Sci Rep (2015)

Distribution of the percentage of missing data, in our 8,121 sample, across the 172 outcomes.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4644974&req=5

f6: Distribution of the percentage of missing data, in our 8,121 sample, across the 172 outcomes.
Mentions: As shown in Fig. 6, the outcomes had varying numbers of missing values, which means there were differences in statistical power across outcomes. However, the ranking of our main analysis is highly correlated with the ranking of the imputation dataset (Spearman’s rank correlation of 0.919 (P < 0.001)). Results using the imputed dataset are given in Supplementary Table 4.

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: MRC Integrative Epidemiology Unit (IEU) at the University of Bristol, University of Bristol, Bristol.

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.

No MeSH data available.