Unique diagnostic signatures of concussion in the saliva of male athletes: the Study of Concussion in Rugby Union through MicroRNAs (SCRUM)

Abstract

ObjectiveTo investigate the role of salivary small non-coding RNAs (sncRNAs) in the diagnosis of sport-related concussion.MethodsSaliva was obtained from male professional players in the top two tiers of England’s elite rugby union competition across two seasons (2017–2019). Samples were collected preseason from 1028 players, and during standardised head injury assessments (HIAs) at three time points (in-game, post-game, and 36–48 hours post-game) from 156 of these. Samples were also collected from controls (102 uninjured players and 66 players sustaining a musculoskeletal injury). Diagnostic sncRNAs were identified with next generation sequencing and validated using quantitative PCR in 702 samples. A predictive logistic regression model was built on 2017–2018 data (training dataset) and prospectively validated the following season (test dataset).ResultsThe HIA process confirmed concussion in 106 players (HIA+) and excluded this in 50 (HIA−). 32 sncRNAs were significantly differentially expressed across these two groups, with let-7f-5p showing the highest area under the curve (AUC) at 36–48 hours. Additionally, a combined panel of 14 sncRNAs (let-7a-5p, miR-143-3p, miR-103a-3p, miR-34b-3p, RNU6-7, RNU6-45, Snora57, snoU13.120, tRNA18Arg-CCT, U6-168, U6-428, U6-1249, Uco22cjg1,YRNA_255) could differentiate concussed subjects from all other groups, including players who were HIA− and controls, immediately after the game (AUC 0.91, 95% CI 0.81 to 1) and 36–48 hours later (AUC 0.94, 95% CI 0.86 to 1). When prospectively tested, the panel confirmed high predictive accuracy (AUC 0.96, 95% CI 0.92 to 1 post-game and AUC 0.93, 95% CI 0.86 to 1 at 36–48 hours).ConclusionsSCRUM, a large prospective observational study of non-invasive concussion biomarkers, has identified unique signatures of concussion in saliva of male athletes diagnosed with concussion.

Peripheral microRNA alteration and pathway signaling after mild traumatic brain injur

“…However, the published pathways were derived from a single database, e.g., KEGG or Ingenuity Pathway analysis, respectively, leading to only partial results due to small overlap across pathway databases (Rahmati et al 2017). Despite this methodological limitation the mTOR, TGF-beta, IGF1R, neurotrophin and inflammatory signaling represent major overlap with findings of our meta-analysis and support their involvement in post mTBI conditions by multiple evidence (Qin et al 2018;Atif and Hicks 2019;Devoto et al 2020;Hicks et al 2020a;Di Pietro et al 2021).…”

Alterations to the Gut Microbiome after Sport-Related Concussion in a Collegiate Football Players Cohort

“…Interestingly, we did not identify any observable changes in salivary microbiota, dampening the potential utility of this sample type as a biomarker of concussions. Despite this, a recent large prospective observational study of non-invasive concussion biomarkers has shown changes in salivary small non-coding RNAs (sncRNAs) in saliva in rugby players diagnosed with concussion 56 . The idea of having sncRNAs identi ers that correlate with microbiome signatures could represent a complete panel of concussion pro les that should be studied.…”

The biological significance and clinical utility of emerging blood biomarkers for traumatic brain injury

“…miR-21 can reduce neuronal apoptosis after TBI through activation of the PTEN-Akt signaling pathway (Ji et al, 2018). ↑ Severe TBI [serum]: at 1d and 15d post-injury compared to healthy controls (Di Pietro et al, 2017) ↑ Concussion [saliva]: collected 48-72 h post-injury, compared to non-injured age-matched peers (Di Pietro et al, 2021) ↑ Stroke [whole blood]: at 6-18 months post-injury, compared to healthy controls (Tan et al, 2009) ↑ Relapsing remitting MS [peripheral mononuclear cells from whole blood]: compared to matched healthy controls (Fenoglio et al, 2011) ↓ Progressive MS [peripheral mononuclear cells from whole blood, enriched for CD4 + T cells]: compared to healthy controls (Sanders et al, 2016) miR-34a Participates in regulation of energy metabolism and inflammation by mediating the crosstalk between NF-κB pathway and SIRT1 enzyme: NF-κB upregulates miR-34a expression which in turn inhibits SIRT1 expression (Kauppinen et al, 2013). Inhibits expression of Bcl-2, a protein that inhibits caspase-3 and -9 activation and prevents apoptosis (Wang et al, 2009).…”

“…↓ History of multiple mild TBI [exosomal miRNA in plasma]: compared to control group (Devoto et al, 2020) ↓ AD [whole blood]: compared to healthy controls (Chang et al, 2017;Leidinger et al, 2013) miR-107 Modulates cellular glucose metabolic pathway by interacting with granulin. Decrease in neuronal miR-107 in the hippocampus was noted acutely after TBI in mouse, allowing transcription of granulin to trigger inflammation and healing (Wang ↓ AD [whole blood]: compared to healthy controls (Chang et al, 2017;Leidinger et al, 2013) ↑ Concussion [saliva]: collected 48-72 h post-injury, compared to non-injured age-matched peers (Di Pietro et al, 2021)…”