A randomization-based causal inference framework for uncovering environmental exposure effects on human gut microbiota.
PLoS Comput Biol
; 18(5): e1010044, 2022 05.
Article
en En
| MEDLINE
| ID: mdl-35533202
ABSTRACT
Statistical analysis of microbial genomic data within epidemiological cohort studies holds the promise to assess the influence of environmental exposures on both the host and the host-associated microbiome. However, the observational character of prospective cohort data and the intricate characteristics of microbiome data make it challenging to discover causal associations between environment and microbiome. Here, we introduce a causal inference framework based on the Rubin Causal Model that can help scientists to investigate such environment-host microbiome relationships, to capitalize on existing, possibly powerful, test statistics, and test plausible sharp null hypotheses. Using data from the German KORA cohort study, we illustrate our framework by designing two hypothetical randomized experiments with interventions of (i) air pollution reduction and (ii) smoking prevention. We study the effects of these interventions on the human gut microbiome by testing shifts in microbial diversity, changes in individual microbial abundances, and microbial network wiring between groups of matched subjects via randomization-based inference. In the smoking prevention scenario, we identify a small interconnected group of taxa worth further scrutiny, including Christensenellaceae and Ruminococcaceae genera, that have been previously associated with blood metabolite changes. These findings demonstrate that our framework may uncover potentially causal links between environmental exposure and the gut microbiome from observational data. We anticipate the present statistical framework to be a good starting point for further discoveries on the role of the gut microbiome in environmental health.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Contexto en salud:
2_ODS3
/
3_ND
Problema de salud:
2_quimicos_contaminacion
/
3_zoonosis
Asunto principal:
Microbioma Gastrointestinal
Tipo de estudio:
Clinical_trials
/
Etiology_studies
/
Incidence_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
PLoS Comput Biol
Asunto de la revista:
BIOLOGIA
/
INFORMATICA MEDICA
Año:
2022
Tipo del documento:
Article
País de afiliación:
Estados Unidos