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Collision sports athletes experience many head acceleration events (HAEs) perseason. The effects of these subconcussive events are largely understudiedsince HAEs may produce no overt symptoms, and are likely to diffusely manifestacross multiple scales of study (e.g., molecular, cellular network, andbehavior). This study integrated resting-state fMRI with metabolome,transcriptome and computational virtual reality (VR) behavior measures toassess the effects of exposure to HAEs on players in a collegiate Americanfootball team. Permutation-based mediation and moderation analysis was used toinvestigate relationships between network fingerprint, changes in omic measuresand VR metrics over the season. Change in an energy cycle fatty acid,tridecenedioate, moderated the relationship between 1) miR-505 and DMNfingerprint and 2) the relationship between DMN fingerprint and worsening VRBalance measures (all p less than or equal to 0.05). In addition, thesimilarity in DMN over the season was negatively related to cumulative numberof HAEs above 80G, and DMN fingerprint was less similar across the season inathletes relative to age-matched non-athletes. miR-505 was also positivelyrelated to average number of HAEs above 25G per session. It is important tonote that tridecenedioate has a double bond making it a candidate for ROSscavenging. These findings between a candidate ROS-related metabolite,inflammatory miRNA, altered brain imaging and diminished behavioral performancesuggests that impact athletes may experience chronic neuroinflammation. Therigorous permutation-based mediation/moderation may provide a methodology forinvestigating complex multi-scale biological data within humans alone and thusassist study of other functional brain problems.

A metabolomic measure of energy metabolism moderates how an inflammatory miRNA relates to rs-fMRI network and motor control in football athletes