Fig 1.
Data collection and processing flowchart.
Head impact data, on-field activity data, surveys of clinically relevant factors, and fecal samples were collected from 19 original participants. Thirteen participants were excluded due to missing head impact data or an insufficient number of fecal samples (fewer than 15 samples). Twenty fecal samples from the remaining six participants were excluded due to oral antibiotic prescription or duplicate samples collected on the same day. Fifteen clinical factors from available survey data were selected, and missing survey data were imputed. After exclusions, the bacterial DNA from 226 fecal samples was extracted, sequenced, and processed into relative abundance data and diversity metrics. Head impacts were monitored, and impact load was calculated based on the severity of impacts. On-field activity was monitored to measure physical strain (player load).
Fig 2.
Study participants exhibit variability in head impact frequency and intensity, as well as in fecal microbiome composition.
(a) Availability of fecal samples by participant. The days on which samples were collected and those on which they were not are marked in blue and orange, respectively. White boxes indicate that the sample collected on this date was excluded due to oral antibiotic use. The final two samples from participants 1, 4, and 9 were collected 10-21 days after the season’s final game. (b) Head impacts and head impact loads sustained by participants. Error bars represent the standard error of the mean. See Methods for data collection and Supplementary Table 2 (S2 Table) for exact values. (c) Beta diversity analysis of the gut microbiota from all samples used in the study. The scatter plot displays a principal coordinate analysis (PCoA) with data points color-coded by the participant. Each participant’s data is enclosed within its own ellipsoid.
Fig 3.
Bray Curtis Dissimilarity increases 48-72 and 72-96 hours following severe head impact exposure.
Cluster of fecal samples across four consecutive days isolated such that hour 0 represents a head impact load exposure in the top 75th percentile, followed by 96 consecutive hours in which there was no head impact load exposure in the top 75th percentile. Friedman’s Chi-Square test and Nemenyi’s post hoc pairwise test revealed a significant increase in Bray-Curtis Dissimilarity between 48-72 and 72-96 hours post-impact relative to 0-24 hour (day of impact). Gray lines connect samples from the same data slice. (* indicates p < 0.05).
Table 1.
Bray-Curtis dissimilarity changes in relation to head impacts sustained in the previous 48-72 hours, after adjusting for clinical factors. Significant p-values (< 0.05) are highlighted in dark blue, and marginally significant p-values (< 0.10) are highlighted in light blue. The 48-72 hour time-shifted model is bolded. Only time, player load, and consumption of pre-workout drinks remain significant after the Benjamini-Hochberg p-value correction. “Estimate” indicates the direction and magnitude of the effect on Bray-Curtis Dissimilarity.
Table 2.
Changes in relative abundances of Coriobacteriales, Prevotella, Prevotellaceae, Ruminococcus, and Verrucomicrobiales correlate with head impacts sustained in the prior 48-72 hours. Dark blue: p < 0.05; light blue: p < 0.10. “Estimate” indicates direction and magnitude of the correlation between the variable and the relative abundance of the taxa.
Fig 4.
(a) Bray-Curtis Dissimilarity increases across the sample collection period.
The first three, the middle three, and the last three fecal samples available for each participant (excluding postseason samples) were used for the early, middle, and late periods, respectively (see methods and S2 Fig). Bray-Curtis Dissimilarity increased from the early to late period (*indicates p < 0.05). (b) Faith’s Phylogenetic Diversity did not change significantly across the sample collection period. Analysis revealed no significant differences in Faith’s Phylogenetic Diversity across the sample collection period for the three time points analyzed. (c) The relative abundance of phyla varies across participants and across the sample collection period. Firmicutes and Bacteroidota were the most abundant phyla for all participants, but their relative abundances varied among participants and across the sample collection period.