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<p>This study investigated the role of food insecurity as an effect modifier between the gut microbiome, including groups of microbes (cliques), and risk of cognitive impairment (RCI). The analytical sample (<i>n</i> = 360) included adult participants of the Survey of the Health of Wisconsin with complete data on food insecurity, RCI, and 16S rRNA sequencing from stool samples. Microbial cliques associated with RCI were identified using an interpretable machine-learning-based algorithm. All analyses were stratified by food insecurity level, and adjusted for relevant confounders. We identified two cliques whose associations with RCI were modified by food insecurity status. The presence of the clique with either <i>Eisenbergiella</i> or <i>Eubacterium</i> was more strongly associated with RCI for the food-insecure group (β = 0.29, <i>p</i> &lt; 0.0001). A clique representing the presence of <i>Ruminococcus torques</i>, <i>Bacteroides</i>, CAG-352F, and/or <i>Eubacterium</i> had a stronger association with RCI for the food-secure group (β = 0.1, <i>p</i> &lt; 0.0001). Findings suggest food security be considered in RCI etiology.</p>

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Food insecurity modifies the association between the gut microbiome and the risk of cognitive impairment in adults

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月18日

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  • Shoshannah Eggers,
  • Zachary E. Hoggarth,
  • Kiran Nagdeo,
  • Maria J. Banas,
  • Jamil M. Lane,
  • Elza Rechtman,
  • Chris Gennings,
  • Elizabeth O’Neal,
  • Paul E. Peppard,
  • Ajay K. Sethi,
  • Nasia Safdar,
  • Kristen MC Malecki,
  • Amy A. Schultz,
  • Vishal Midya

摘要

This study investigated the role of food insecurity as an effect modifier between the gut microbiome, including groups of microbes (cliques), and risk of cognitive impairment (RCI). The analytical sample (n = 360) included adult participants of the Survey of the Health of Wisconsin with complete data on food insecurity, RCI, and 16S rRNA sequencing from stool samples. Microbial cliques associated with RCI were identified using an interpretable machine-learning-based algorithm. All analyses were stratified by food insecurity level, and adjusted for relevant confounders. We identified two cliques whose associations with RCI were modified by food insecurity status. The presence of the clique with either Eisenbergiella or Eubacterium was more strongly associated with RCI for the food-insecure group (β = 0.29, p < 0.0001). A clique representing the presence of Ruminococcus torques, Bacteroides, CAG-352F, and/or Eubacterium had a stronger association with RCI for the food-secure group (β = 0.1, p < 0.0001). Findings suggest food security be considered in RCI etiology.