Clinical and Translational Medicine (Oct 2020)

Diagnosing mild traumatic brain injury using saliva RNA compared to cognitive and balance testing

  • Steven D. Hicks,
  • Cayce Onks,
  • Raymond Y. Kim,
  • Kevin J. Zhen,
  • Jayson Loeffert,
  • Andrea C. Loeffert,
  • Robert P. Olympia,
  • Gregory Fedorchak,
  • Samantha DeVita,
  • Aakanksha Rangnekar,
  • John Leddy,
  • Mohammad N. Haider,
  • Zofia Gagnon,
  • Callan D. McLoughlin,
  • Matthew Badia,
  • Jason Randall,
  • Miguel Madeira,
  • Aaron M. Yengo‐Kahn,
  • Justin Wenzel,
  • Matthew Heller,
  • Hallie Zwibel,
  • Aaron Roberts,
  • Samantha Johnson,
  • Chuck Monteith,
  • Michael N. Dretsch,
  • Thomas R. Campbell,
  • Rebekah Mannix,
  • Christopher Neville,
  • Frank Middleton

DOI
https://doi.org/10.1002/ctm2.197
Journal volume & issue
Vol. 10, no. 6
pp. n/a – n/a

Abstract

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Abstract Background Early, accurate diagnosis of mild traumatic brain injury (mTBI) can improve clinical outcomes for patients, but mTBI remains difficult to diagnose because of reliance on subjective symptom reports. An objective biomarker could increase diagnostic accuracy and improve clinical outcomes. The aim of this study was to assess the ability of salivary noncoding RNA (ncRNA) to serve as a diagnostic adjunct to current clinical tools. We hypothesized that saliva ncRNA levels would demonstrate comparable accuracy for identifying mTBI as measures of symptom burden, neurocognition, and balance. Methods This case‐control study involved 538 individuals. Participants included 251 individuals with mTBI, enrolled ≤14 days postinjury, from 11 clinical sites. Saliva samples (n = 679) were collected at five time points (≤3, 4‐7, 8‐14, 15‐30, and 31‐60 days post‐mTBI). Levels of ncRNAs (microRNAs, small nucleolar RNAs, and piwi‐interacting RNAs) were quantified within each sample using RNA sequencing. The first sample from each mTBI participant was compared to saliva samples from 287 controls. Samples were divided into testing (n = 430; mTBI = 201 and control = 239) and training sets (n = 108; mTBI = 50 and control = 58). The test set was used to identify ncRNA diagnostic candidates and create a diagnostic model. Model accuracy was assessed in the naïve test set. Results A model utilizing seven ncRNA ratios, along with participant age and chronic headache status, differentiated mTBI and control participants with a cross‐validated area under the curve (AUC) of .857 in the training set (95% CI, .816‐.903) and .823 in the naïve test set. In a subset of participants (n = 321; mTBI = 176 and control = 145) assessed for symptom burden (Post‐Concussion Symptom Scale), as well as neurocognition and balance (ClearEdge System), these clinical measures yielded cross‐validated AUC of .835 (95% CI, .782‐.880) and .853 (95% CI, .803‐.899), respectively. A model employing symptom burden and four neurocognitive measures identified mTBI participants with similar AUC (.888; CI, .845‐.925) as symptom burden and four ncRNAs (.932; 95% CI, .890‐.965). Conclusion Salivary ncRNA levels represent a noninvasive, biologic measure that can aid objective, accurate diagnosis of mTBI.

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