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Beyond samples: A metric revealing more connections of gut microbiota between individuals.

ABSTRACT: Studies of gut microbiota explore their complicated connections between individuals of different characteristics by applying different metrics to abundance data obtained from fecal samples. Although classic metrics are capable to quantify differences between samples, the microbiome of fecal sample is not a good surrogate for the gut microbiome of individuals because the microbial populations of the distal colon does not adequately represent that of the entire gastrointestinal tract. To overcome the deficiency of classic metrics in which the differences can be measured between the samples analyzed, but not the corresponding populations, we propose a metric for representing composition differences in the gut microbiota of individuals. Our investigation shows this metric outperforms traditional measures for multiple scenarios. For gut microbiota in diverse geographic populations, this metric presents more explainable data variance than others, not only in regular variance analysis but also in principle component analysis and partition analysis of biologic characteristics. With time-series data, the metric further presents a strong correlation with the time interval of serial sampling. Our findings suggest that the metric is robust and powerfully detects the intrinsic variations in gut microbiota. The metric holds promise for revealing more relations between gut microbiota and human health.

SUBMITTER: Yang Z

PROVIDER: S-EPMC8319210 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundSome observational studies have shown that immune thrombocytopenia (ITP) is highly associated with the alteration-composition of gut microbiota. However, the causality of gut microbiota on ITP has not yet been determined.MethodsBased on accessible summary statistics of the genome-wide union, the latent connection between ITP and gut microbiota was estimated using bi-directional Mendelian randomization (MR) and multivariable MR (MVMR) analyses. Inverse variance weighted (IVW), weighted median analyses, and MR-Egger regression methods were performed to examine the causal correlation between ITP and the gut microbiota. Several sensitivity analyses verified the MR results. The strength of causal relationships was evaluated using the MR-Steiger test. MVMR analysis was undertaken to test the independent causal effect. MR analyses of reverse direction were made to exclude the potential of reverse correlations. Finally, GO enrichment analyses were carried out to explore the biological functions.ResultsAfter FDR adjustment, two microbial taxa were identified to be causally associated with ITP (PFDR < 0.10), namely Alcaligenaceae (PFDR = 7.31 × 10-2) and Methanobacteriaceae (PFDR = 7.31 × 10-2). In addition, eight microbial taxa were considered as potentially causal features under the nominal significance (P < 0.05): Actinobacteria, Lachnospiraceae, Methanobacteria, Bacillales, Methanobacteriales, Coprococcus2, Gordonibacter, and Veillonella. According to the reverse-direction MR study findings, the gut microbiota was not significantly affected by ITP. There was no discernible horizontal pleiotropy or instrument heterogeneity. Finally, GO enrichment analyses showed how the identified microbial taxa participate in ITP through their underlying biological mechanisms.ConclusionSeveral microbial taxa were discovered to be causally linked to ITP in this MR investigation. The findings improve our understanding of the gut microbiome in the risk of ITP.

Project description:BackgroundThe transition from methamphetamine (MA) casual use (MCU) to compulsive use is enigmatic as some MA users can remain in casual use, but some cannot. There is a knowledge gap if gut microbiota (GM) play a role in differing MCU from MA use disorder (MUD). We aimed to investigate the clinical features and GM differences between individuals with MCU and MUD.MethodWe recruited two groups of MA users -MCU and MUD - and matched them according to age and body mass index (n=21 in each group). Participants were accessed using the Semi-Structured Assessment for Drug Dependence and Alcoholism, and their fecal samples were undergone 16S ribosomal DNA sequencing. We compared the hosts' clinical features and GM diversity, composition, and structure (represented by enterotypes) between the two groups. We have identified differential microbes between the two groups and performed network analyses connecting GM and the clinical traits.ResultCompared with the casual users, individuals with MUD had higher incidences of MA-induced neuropsychiatric symptoms (e.g., paranoia, depression) and withdrawal symptoms (e.g., fatigue, drowsiness, and increased appetite), as well as stronger cravings for and intentions to use MA, and increased MA tolerance. The GM diversity showed no significant differences between the two groups, but four genera (Halomonas, Clostridium, Devosia, and Dorea) were enriched in the individuals with MUD (p<0.05). Three distinct enterotypes were identified in all MA users, and Ruminococcus-driven enterotype 2 was dominant in individuals with MUD compared to the MCU (61.90% vs. 28.60%, p=0.03). Network analysis shows that Devosia is the hub genus (hub index = 0.75), which is not only related to the counts of the MUD diagnostic criteria (ρ=0.40; p=0.01) but also to the clinical features of MA users such as reduced social activities (ρ=0.54; p<0.01). Devosia is also associated with the increased intention to use MA (ρ=0.48; p<0.01), increased MA tolerance (ρ=0.38; p=0.01), craving for MA (ρ=0.37; p=0.01), and MA-induced withdrawal symptoms (p<0.05).ConclusionOur findings suggest that Ruminococcus-driven enterotype 2 and the genera Devosia might be two influential factors that differentiate MA casual use from MUD, but further studies are warranted.

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Beyond samples: A metric revealing more connections of gut microbiota between individuals.

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