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

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.
项目摘要 美国每年有近300万例轻度创伤性脑损伤(mTBI),大多数发生在 年龄小于21岁的患者。mTBI的临床评估依赖于症状调查, 准确预测症状的持续时间或客观地识别大脑恢复。生物测试可以让 医生提供个性化的建议,为学校和体育参与,及时处方 药物治疗,或对有持续性产后抑郁症风险的患者进行早期心理社会服务。 脑震荡症状(PPCS)。非编码核糖核酸(ncRNA),如microRNA,是表位的。 在mTBI患者中改变的转录分子。它们可以在外周生物液中测量 例如血清或甚至唾液。我们以前的研究表明,脑脊液中ncRNA的变化 反映在唾液中,唾液ncRNA水平可以预测PPCS。在一个大的, 独立队列可以产生PPCS风险的生物学测量(目标1),并指导个体化临床 管理决策(目标2)。这一科学前提构成了我们提议的多中心研究的基础。我们 将招募750名患有mTBI的青少年(年龄13 - 18岁),由世界卫生组织和柏林定义 共识标准。我们将测量在神经元和神经胶质外泌体中富集的唾液ncRNA的水平, 急性(<48小时)、亚急性(7天)和慢性(30天)损伤后时间点。PPCS的定义如下: 第30天持续存在≥ 3种症状(与损伤前状态相比,由脑震荡后 症状量表; PCSI)。在250名参与者(训练集)中,我们将使用LASSO技术来改进 多变量模型,采用急性和亚急性ncRNA水平,沿着临床、社会和 心理因素,预测PPCS(同时控制生物学协变量)。模型的准确性将是 在其余500名参与者中进行外部验证(测试集)。灵敏度和特异性将与 “5P”临床预测工具。我们还将研究脑震荡症状之间的关系 表型和ncRNA水平的因子分析和层次聚类。在目标2中,我们将使用LASSO 在训练组(n = 250)中,使用急性和慢性ncRNA水平来改进第二多变量模型, 沿着临床、社会和心理因素来确定脑震荡的恢复情况。恢复将由以下定义: PCSI自我报告"与损伤前无差异"。该模型的准确性将在外部进行验证, 测试集,并与急性和慢性时间点的反应时间性能的准确性进行比较。 我们的多学科团队包括儿科、神经病学、分子生物学、心理学和 急诊医学,具有已公布的合作记录和为此所需的专业知识 提案的成功。这项研究将产生一个客观的衡量PPCS的风险,脑震荡表型, 临床康复当与医疗,社会和心理评估相结合时,这项技术将允许 研究人员在生物学定义的患者亚群中研究mTBI疗法,并个性化脑震荡护理。

项目成果

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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:
    $ 67.68万
  • 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:
    $ 67.68万
  • 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:
    $ 67.68万
  • 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:
    $ 67.68万
  • 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:
    10552597
  • 财政年份:
    2020
  • 资助金额:
    $ 67.68万
  • 项目类别:

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