Poly-omic predictors of symptom duration and recovery for adolescent concussion
青少年脑震荡症状持续时间和恢复的多组学预测因子
基本信息
- 批准号:10552597
- 负责人:
- 金额:$ 67.2万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2020
- 资助国家:美国
- 起止时间:2020-01-01 至 2025-12-31
- 项目状态:未结题
- 来源:
- 关键词:21 year oldAcuteAdolescentAgeAlgorithmsAthleticBerlinBiologicalBiological TestingBrainBrain ConcussionCaringCenters for Disease Control and Prevention (U.S.)Cerebrospinal FluidChildChildhoodChildhood InjuryChronicClinicalClinical ManagementClinical assessmentsCohort StudiesCollaborationsConsensusEmergency MedicineEnrollmentEquipment and supply inventoriesFactor AnalysisFamilyFollow-Up StudiesGenetic TranscriptionGoalsGuidelinesHourInjuryLearningMeasuresMediatingMedicalMethodsMicroRNAsModelingMolecularMolecular BiologyMolecular ProfilingMulticenter StudiesNeurogliaNeurologyNeuronsOlfactory NerveOropharyngealOutcomeParticipantPatient Self-ReportPatientsPediatricsPerformancePeripheralPharmacological TreatmentPhenotypePhysiciansPilot ProjectsPlayPost-Concussion SyndromePrognosisPsychiatric Social WorkPsychological FactorsPsychologyPublishingRNAReaction TimeRecommendationRecoveryReportingResearchResearch PersonnelRiskSalivaSchoolsSensitivity and SpecificitySerumSeveritiesStandardizationSurveysSymptomsTBI treatmentTechniquesTechnologyTestingTimeTrainingUntranslated RNAValidationWorld Health Organizationbrain repairclinical applicationclinical predictorscohortconcussive symptomepitranscriptomicsexosomeexperiencefeature selectioninnovationmild traumatic brain injurymultidisciplinarymultiplex assayneurobehavioralpatient subsetspediatric patientspersonalized managementprediction algorithmpredictive modelingpredictive toolsprotein expressionpsychologicrepairedresponsereturn to sportsaliva samplesocialsocial factorssuccesstool
项目摘要
PROJECT SUMMARY
There are nearly three million mild traumatic brain injuries (mTBIs) in the U.S. each year, and most occur in
patients less than 21 years of age. Clinical assessment of mTBI relies on symptom surveys that cannot
accurately predict the duration of symptoms or objectively identify brain recovery. A biologic test would allow
physicians to provide individualized recommendations for school and athletics participation, prescribe timely
pharmacologic treatments, or initiate early psychosocial services in patients at risk for persistent post-
concussion symptoms (PPCS). Non-coding ribonucleic acids (ncRNAs), such as microRNAs, are epi-
transcriptional molecules that are altered in patients with mTBI. They can be measured in peripheral biofluids
such as serum, or even saliva. Our previous research demonstrates that ncRNA changes in cerebrospinal fluid
are reflected in saliva, and that saliva ncRNA levels can predict PPCS. Validation of these findings in a large,
independent cohort could yield a biologic measure of PPCS risk (Aim 1), and guide individualized clinical
management decisions (Aim 2). This scientific premise forms the basis for our proposed multi-center study. We
will enroll 750 adolescents (ages 13-18 years) with mTBI, defined by the World Health Organization and Berlin
Consensus Criteria. We will measure levels of saliva ncRNAs enriched in neuronal and glial exosomes at
acute (<48 hours), sub-acute (7 days), and chronic (30 days) post-injury time points. PPCS will be defined by
persistence of ≥ 3 symptoms on day 30 (compared with pre-injury state, determined by the Post-Concussion
Symptom Inventory; PCSI). In 250 participants (training set), we will use a LASSO technique to refine a
multivariate model, that employs acute and sub-acute ncRNA levels, along with clinical, social, and
psychologic factors, to predict PPCS (while controlling for biologic covariates). Accuracy of the model will be
externally validated in the remaining 500 participants (test set). Sensitivity and specificity will be compared to
the validated “5P” clinical prediction tool. We will also examine the relationships between concussive symptom
phenotypes and ncRNA levels with a factor analysis and hierarchical clustering. In Aim 2, we will use LASSO
in a training set (n=250) to refine a second multivariate model, that uses acute and chronic ncRNA levels,
along with clinical, social, and psychologic factors to identify concussion recovery. Recovery will be defined by
self-report of “no difference from pre-injury” on the PCSI. Accuracy of the model will be externally validated in
the test set, and compared to the accuracy of reaction time performance across acute and chronic time points.
Our multi-disciplinary team includes experts in pediatrics, neurology, molecular biology, psychology, and
emergency medicine with a published track record of collaboration and the expertise necessary for this
proposal’s success. The study will yield an objective measure of PPCS risk, concussion phenotype, and
clinical recovery. When paired with medical, social, and psychologic assessments, this technology will allow
researchers to study mTBI therapies in biologically-defined patient subsets and personalize concussion care.
项目总结
项目成果
期刊论文数量(0)
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科研奖励数量(0)
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Steven Daniel Hicks其他文献
Steven Daniel Hicks的其他文献
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{{ truncateString('Steven Daniel Hicks', 18)}}的其他基金
Severity Predictors Integrating salivary Transcriptomics and proteomics with Multi neural network Intelligence in SARS-CoV2 infection in Children (SPITS MISC)
将唾液转录组学和蛋白质组学与多神经网络智能相结合用于儿童 SARS-CoV2 感染的严重程度预测 (SPITS MISC)
- 批准号:
10273618 - 财政年份:2021
- 资助金额:
$ 67.2万 - 项目类别:
Severity Predictors Integrating salivary Transcriptomics and proteomics with Multi neural network Intelligence in SARS-CoV2 infection in Children (SPITS MISC)
将唾液转录组学和蛋白质组学与多神经网络智能相结合用于儿童 SARS-CoV2 感染的严重程度预测 (SPITS MISC)
- 批准号:
10733697 - 财政年份:2021
- 资助金额:
$ 67.2万 - 项目类别:
Severity Predictors Integrating salivary Transcriptomics and proteomics with Multi neural network Intelligence in SARS-CoV2 infection in Children (SPITS MISC)
将唾液转录组学和蛋白质组学与多神经网络智能相结合用于儿童 SARS-CoV2 感染的严重程度预测 (SPITS MISC)
- 批准号:
10320490 - 财政年份:2021
- 资助金额:
$ 67.2万 - 项目类别:
Severity Predictors Integrating salivary Transcriptomics and proteomics with Multi neural network Intelligence in SARS-CoV2 infection in Children (SPITS MISC)
将唾液转录组学和蛋白质组学与多神经网络智能相结合用于儿童 SARS-CoV2 感染的严重程度预测 (SPITS MISC)
- 批准号:
10847809 - 财政年份:2021
- 资助金额:
$ 67.2万 - 项目类别:
Poly-omic predictors of symptom duration and recovery for adolescent concussion
青少年脑震荡症状持续时间和恢复的多组学预测因子
- 批准号:
10323290 - 财政年份:2020
- 资助金额:
$ 67.2万 - 项目类别:
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