Combining the strengths of inverse-variance weighting and Egger regression in Mendelian randomization using a mixture of regressions model.
PLoS Genet
; 17(11): e1009922, 2021 11.
Article
en En
| MEDLINE
| ID: mdl-34793444
ABSTRACT
With the increasing availability of large-scale GWAS summary data on various traits, Mendelian randomization (MR) has become commonly used to infer causality between a pair of traits, an exposure and an outcome. It depends on using genetic variants, typically SNPs, as instrumental variables (IVs). The inverse-variance weighted (IVW) method (with a fixed-effect meta-analysis model) is most powerful when all IVs are valid; however, when horizontal pleiotropy is present, it may lead to biased inference. On the other hand, Egger regression is one of the most widely used methods robust to (uncorrelated) pleiotropy, but it suffers from loss of power. We propose a two-component mixture of regressions to combine and thus take advantage of both IVW and Egger regression; it is often both more efficient (i.e. higher powered) and more robust to pleiotropy (i.e. controlling type I error) than either IVW or Egger regression alone by accounting for both valid and invalid IVs respectively. We propose a model averaging approach and a novel data perturbation scheme to account for uncertainties in model/IV selection, leading to more robust statistical inference for finite samples. Through extensive simulations and applications to the GWAS summary data of 48 risk factor-disease pairs and 63 genetically uncorrelated trait pairs, we showcase that our proposed methods could often control type I error better while achieving much higher power than IVW and Egger regression (and sometimes than several other new/popular MR methods). We expect that our proposed methods will be a useful addition to the toolbox of Mendelian randomization for causal inference.
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Predisposición Genética a la Enfermedad
/
Polimorfismo de Nucleótido Simple
/
Estudio de Asociación del Genoma Completo
/
Análisis de la Aleatorización Mendeliana
Tipo de estudio:
Clinical_trials
/
Diagnostic_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
PLoS Genet
Asunto de la revista:
GENETICA
Año:
2021
Tipo del documento:
Article
País de afiliación:
Estados Unidos