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A microbial causal mediation analytic tool for health disparity and applications in body mass index.
Wang, Chan; Ahn, Jiyoung; Tarpey, Thaddeus; Yi, Stella S; Hayes, Richard B; Li, Huilin.
Afiliação
  • Wang C; Department of Population Health, Division of Biostatistics, New York University Grossman School of Medicine, New York, NY, 10016, USA.
  • Ahn J; Department of Population Health, Division of Epidemiology, New York University Grossman School of Medicine, New York, NY, 10016, USA.
  • Tarpey T; Department of Population Health, Division of Biostatistics, New York University Grossman School of Medicine, New York, NY, 10016, USA.
  • Yi SS; Department of Population Health Section for Health Equity, New York University Grossman School of Medicine, New York, 10016, USA.
  • Hayes RB; Department of Population Health, Division of Epidemiology, New York University Grossman School of Medicine, New York, NY, 10016, USA.
  • Li H; Department of Population Health, Division of Biostatistics, New York University Grossman School of Medicine, New York, NY, 10016, USA. Huilin.Li@nyulangone.org.
Microbiome ; 11(1): 164, 2023 07 27.
Article em En | MEDLINE | ID: mdl-37496080
BACKGROUND: Emerging evidence suggests the potential mediating role of microbiome in health disparities. However, no analytic framework can be directly used to analyze microbiome as a mediator between health disparity and clinical outcome, due to the non-manipulable nature of the exposure and the unique structure of microbiome data, including high dimensionality, sparsity, and compositionality. METHODS: Considering the modifiable and quantitative features of the microbiome, we propose a microbial causal mediation model framework, SparseMCMM_HD, to uncover the mediating role of microbiome in health disparities, by depicting a plausible path from a non-manipulable exposure (e.g., ethnicity or region) to the outcome through the microbiome. The proposed SparseMCMM_HD rigorously defines and quantifies the manipulable disparity measure that would be eliminated by equalizing microbiome profiles between comparison and reference groups and innovatively and successfully extends the existing microbial mediation methods, which are originally proposed under potential outcome or counterfactual outcome study design, to address health disparities. RESULTS: Through three body mass index (BMI) studies selected from the curatedMetagenomicData 3.4.2 package and the American gut project: China vs. USA, China vs. UK, and Asian or Pacific Islander (API) vs. Caucasian, we exhibit the utility of the proposed SparseMCMM_HD framework for investigating the microbiome's contributions in health disparities. Specifically, BMI exhibits disparities and microbial community diversities are significantly distinctive between reference and comparison groups in all three applications. By employing SparseMCMM_HD, we illustrate that microbiome plays a crucial role in explaining the disparities in BMI between ethnicities or regions. 20.63%, 33.09%, and 25.71% of the overall disparity in BMI in China-USA, China-UK, and API-Caucasian comparisons, respectively, would be eliminated if the between-group microbiome profiles were equalized; and 15, 18, and 16 species are identified to play the mediating role respectively. CONCLUSIONS: The proposed SparseMCMM_HD is an effective and validated tool to elucidate the mediating role of microbiome in health disparity. Three BMI applications shed light on the utility of microbiome in reducing BMI disparity by manipulating microbial profiles. Video Abstract.
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Assunto principal: Microbiota Aspecto: Equity_inequality Limite: Humans País/Região como assunto: Asia Idioma: En Revista: Microbiome Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 1_ASSA2030 Base de dados: MEDLINE Assunto principal: Microbiota Aspecto: Equity_inequality Limite: Humans País/Região como assunto: Asia Idioma: En Revista: Microbiome Ano de publicação: 2023 Tipo de documento: Article