Diagnosing mild traumatic brain injury using saliva RNA compared to cognitive and balance testing
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. Th...
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Published in: | Clinical and translational medicine Vol. 10; no. 6; pp. e197 - n/a |
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Language: | English |
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John Wiley and Sons Inc
01-10-2020
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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.
Levels of nine salivary noncoding RNAs (ncRNAs) accurately differentiated 251 individuals with mild traumatic brain injury (mTBI) from 287 peers with mTBI‐like symptoms.
ncRNA performance (area under the curve [AUC] = .857) was similar to other diagnostic adjuncts: neurocognition (AUC = .835) and balance (AUC = .853).
Combining ncRNA levels with symptom severity (AUC = .932) demonstrated comparable accuracy to current clinical guidelines (symptom severity plus neurocognition; AUC = .888). |
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AbstractList | 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.
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.
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).
Salivary ncRNA levels represent a noninvasive, biologic measure that can aid objective, accurate diagnosis of mTBI. 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. BACKGROUNDEarly, 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.METHODSThis 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.RESULTSA 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).CONCLUSIONSalivary ncRNA levels represent a noninvasive, biologic measure that can aid objective, accurate diagnosis of mTBI. Levels of nine salivary noncoding RNAs (ncRNAs) accurately differentiated 251 individuals with mild traumatic brain injury (mTBI) from 287 peers with mTBI‐like symptoms. ncRNA performance (area under the curve [AUC] = .857) was similar to other diagnostic adjuncts: neurocognition (AUC = .835) and balance (AUC = .853). Combining ncRNA levels with symptom severity (AUC = .932) demonstrated comparable accuracy to current clinical guidelines (symptom severity plus neurocognition; AUC = .888). 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. Levels of nine salivary noncoding RNAs (ncRNAs) accurately differentiated 251 individuals with mild traumatic brain injury (mTBI) from 287 peers with mTBI‐like symptoms. ncRNA performance (area under the curve [AUC] = .857) was similar to other diagnostic adjuncts: neurocognition (AUC = .835) and balance (AUC = .853). Combining ncRNA levels with symptom severity (AUC = .932) demonstrated comparable accuracy to current clinical guidelines (symptom severity plus neurocognition; AUC = .888). |
Author | Leddy, John McLoughlin, Callan D. Zwibel, Hallie Campbell, Thomas R. Onks, Cayce Heller, Matthew Middleton, Frank Roberts, Aaron Randall, Jason Hicks, Steven D. Neville, Christopher Olympia, Robert P. Johnson, Samantha Madeira, Miguel Wenzel, Justin Kim, Raymond Y. Gagnon, Zofia Zhen, Kevin J. Loeffert, Andrea C. Badia, Matthew Fedorchak, Gregory Rangnekar, Aakanksha Yengo‐Kahn, Aaron M. Dretsch, Michael N. Loeffert, Jayson Haider, Mohammad N. DeVita, Samantha Monteith, Chuck Mannix, Rebekah |
AuthorAffiliation | 17 Department of PT Education, Orthopedics, and Neuroscience SUNY Upstate Medical University Syracuse New York 16 Division of Emergency Medicine, Boston Children's Hospital Harvard Medical School Boston Massachusetts 3 Department of Orthopedics and Rehabilitation Penn State College of Medicine Hershey Pennsylvania 14 US Army Medical Research Directorate‐West Walter Reed Army Institute of Research Joint Base Lewis–McChord Washington 8 Department of Environmental Science School of Science Marist College Poughkeepsie New York 2 Department of Family Medicine Penn State College of Medicine Hershey Pennsylvania 6 UBMD Orthopedics and Sports Medicine, Jacobs School of Medicine and Biomedical Sciences State University of New York Buffalo New York 18 Department of Neuroscience and Physiology SUNY Upstate Medical University Syracuse New York 5 Quadrant Biosciences Syracuse New York 4 Department of Emergency Medicine Penn State College of Medicine Hershey Pennsylvania 11 Department of Family Medicine New Y |
AuthorAffiliation_xml | – name: 8 Department of Environmental Science School of Science Marist College Poughkeepsie New York – name: 5 Quadrant Biosciences Syracuse New York – name: 18 Department of Neuroscience and Physiology SUNY Upstate Medical University Syracuse New York – name: 11 Department of Family Medicine New York Institute of Technology College of Osteopathic Medicine Old Westbury New York – name: 14 US Army Medical Research Directorate‐West Walter Reed Army Institute of Research Joint Base Lewis–McChord Washington – name: 9 Department of Biology, School of Science Marist College Poughkeepsie New York – name: 4 Department of Emergency Medicine Penn State College of Medicine Hershey Pennsylvania – name: 1 Department of Pediatrics Penn State College of Medicine Hershey Pennsylvania – name: 13 Athletic Training Department Colgate University Hamilton New York – name: 6 UBMD Orthopedics and Sports Medicine, Jacobs School of Medicine and Biomedical Sciences State University of New York Buffalo New York – name: 10 Vanderbilt Sports Concussion Center Vanderbilt University Medical Center Nashville Tennessee – name: 16 Division of Emergency Medicine, Boston Children's Hospital Harvard Medical School Boston Massachusetts – name: 12 Adena Bone and Joint Center Adena Regional Medical Center Chillicothe Ohio – name: 3 Department of Orthopedics and Rehabilitation Penn State College of Medicine Hershey Pennsylvania – name: 7 Department of Biomedical Science Marist College Poughkeepsie New York – name: 2 Department of Family Medicine Penn State College of Medicine Hershey Pennsylvania – name: 17 Department of PT Education, Orthopedics, and Neuroscience SUNY Upstate Medical University Syracuse New York – name: 15 Athletic Training Department Old Dominion University Norfolk Virginia |
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Copyright | 2020 The Authors. published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics 2020 The Authors. Clinical and Translational Medicine published by John Wiley & Sons Australia, Ltd on behalf of Shanghai Institute of Clinical Bioinformatics. |
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Snippet | Background
Early, accurate diagnosis of mild traumatic brain injury (mTBI) can improve clinical outcomes for patients, but mTBI remains difficult to diagnose... Early, accurate diagnosis of mild traumatic brain injury (mTBI) can improve clinical outcomes for patients, but mTBI remains difficult to diagnose because of... BACKGROUNDEarly, accurate diagnosis of mild traumatic brain injury (mTBI) can improve clinical outcomes for patients, but mTBI remains difficult to diagnose... Levels of nine salivary noncoding RNAs (ncRNAs) accurately differentiated 251 individuals with mild traumatic brain injury (mTBI) from 287 peers with mTBI‐like... Abstract Background Early, accurate diagnosis of mild traumatic brain injury (mTBI) can improve clinical outcomes for patients, but mTBI remains difficult to... |
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SubjectTerms | balance biomarker concussion diagnosis neurocognition RNA saliva traumatic brain injury |
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Title | Diagnosing mild traumatic brain injury using saliva RNA compared to cognitive and balance testing |
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