This study aims to fill a gap in Attention Deficit Hyperactivity Disorder (ADHD) gut microbiome research by exploring the dynamics underlying macroscale metrics and venturing beyond taxa abundances and into taxa relationships.
Studies have analyzed the Attention Deficit Hyperactivity Disorder (ADHD) gut microbiome using macroscale metrics such as diversity and differential abundance and have proposed several taxa as elevated or reduced in ADHD compared to Control, but few have delved into the complex underlying dynamics ultimately responsible for the emergence of such metrics, leaving a largely incomplete, sometimes contradictory, and ultimately inconclusive picture. The authors of this study aim to help complete this picture by venturing beyond taxa abundances and into taxa relationships (i.e. cooperation and competition). Symptoms emerge from underlying deficiencies in neurocircuitry, and recent research has suggested a role played by the gut microbiome. The gut microbiome is an ecosystem of interdependent taxa involved in an exponentially complex web of interactions, plus host gene and reaction pathways, some of which involve neurotransmitters with roles in ADHD neurocircuitry. The authors use using a publicly available gut microbiome dataset (targeted 16S, v3-4 region, qPCR) from an observational, case-control study of 30 Control (15 female, 15 male) and 28 ADHD (15 female, 13 male) undergraduate students. The authors first perform the same macroscale analyses prevalent in ADHD gut microbiome literature (diversity, differential abundance, and composition) to observe the degree of correspondence, or any new trends. They then estimate two-way ecological relationships by producing Control and ADHD Microbial Co-occurrence Networks (MCNs), using SparCC correlations (p ≤ 0.01). The authors perform community detection to find clusters of taxa estimated to mutually cooperate along with their centroids, and centrality calculations to estimate taxa most vital to overall gut ecology. Finally, the authors summarize results, providing conjectures on how they can guide future experiments, some methods for improving our experiments, and general implications for the field. (Published Abstract Provided)
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