Secondary Analysis and Integration of Existing Data Related to Chronic Orofacial Pain and Placebo Effects
与慢性口面部疼痛和安慰剂效应相关的现有数据的二次分析和整合
基本信息
- 批准号:10597861
- 负责人:
- 金额:$ 42.49万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2022
- 资助国家:美国
- 起止时间:2022-09-22 至 2024-09-21
- 项目状态:已结题
- 来源:
- 关键词:Absence of pain sensationAffectAgeAlgorithmsAreaBehavioralBehavioral GeneticsBiologicalBiological MarkersBloodBlood specimenCandidate Disease GeneCaringCellsChronicClassificationClinicalComplexConsensusDataData AnalysesDopamineEndocannabinoidsEngineeringEnsureExpectancyFosteringFundingFutureGenesGeneticGenomicsGoalsHealthIndividualInterdisciplinary StudyKnowledgeLaboratoriesMachine LearningMedicineModelingMolecularNeural PathwaysNeuronsOpioidOrofacial PainPainPain intensityPain managementParticipantPathway interactionsPatientsPhenotypePlacebo EffectPlacebosPopulationPredictive FactorPreparationProcessProspective StudiesProteomicsPsychological FactorsPublishingQuality of lifeRNARandomized Clinical TrialsRecommendationReportingResearchResearch PrioritySamplingSerotoninSeveritiesSeverity of illnessSingle Nucleotide PolymorphismSystemTemporomandibular Joint DisordersTestingTherapeuticTwin Multiple BirthUnited States National Academy of SciencesValidationVariantVisualWorkanalogbasechronic painchronic painful conditionclinical phenotypeclinically relevantcohortendophenotypegenetic variantgenome wide association studymachine learning modelmolecular markernon-opioid analgesicorofacialpain inhibitionpain reductionpain scorepain signalpillprecision medicinepsychologicpsychosocialresponsesecondary analysissexsociodemographicstraittranscriptometranscriptome sequencingtranscriptomics
项目摘要
This project in response to RFA-DE-22-011 aims to analyze existing data representing a subset of participants
with Temporomandibular disorders (TMD) who underwent in-depth clinical, behavioral, and psychological
phenotyping under R01 DE025946 (PI: Colloca, ending September 30, 2022). The proposed aims are
substantially different from the original R01-work exploring genetic variants associated with expectancy-induced
analgesia in chronic orofacial pain, psychological factors predicting placebo responders, and genes-related
neuronal changes in the prefrontal and limbic areas associated with expectancy-induced analgesia. Using
Dean’s Initiative Funds allocated to Dr. Colloca, we collected blood and extracted RNA-seq data from a subset
of 74 TMD participants. With the behavioral, psychological, clinical and now, transcriptomic data from this subset
of TMD participants, the central hypothesis is distinct Differently Expressed Genes (DEG) and pathways
associated with Endogenous Pain Modulation (EPM) characterize those TMD participants who show the highest
placebo effects. We will compare transcriptomic profiles associated with high versus low EPM via placebo
effects tested in TMD participants (AIM1) and we will predict high EPM integrating transcriptomic,
sociodemographic, clinical and psychological data (Exploratory Specific Aim 2) using machine learning
models. In order to identify transcriptomic profiles of high placebo responsiveness, TMD participants will be
divided into High Placebo Responders (HLR) and Low Placebo Responders (LPR) based on an average reported
pain score cut-off of 30 on a visual analogue scale (VAS) anchored from zero=no pain to 100=maximum
imaginable pain. Based on our prior published results, informative preliminary results, and DEG power
calculation, we expect enough power to identify key DEG associations in HPR compared to those TMD who do
not respond and/or have lower placebo responses while controlling for sex, age and pain severity. Importantly,
unbiased enrichment analyses will be conducted to identify transcriptomic processes associated with EPM.
Machine learning approaches (e.g., generalized boosted models) will allow us to integrate sociodemographic,
clinical and psychological with transcriptomic markers to further characterize HPR in TMD participants. Our team
is strong with complementary expertise, ensuring that this research will provide integrative models towards step-
by-step discoveries of molecular mechanisms characterizing those who show the largest activation of EPM via
placebo effects. This is the first project to use transcriptomic profiling and machine learning models to predict
EPM in an understudied TMD population. Findings will have high clinical relevance and will inform more
extensive studies generating knowledge that will be critical to guide future steps towards integrative and
translational precision medicine.
本项目响应RFA-DE-22-011,旨在分析代表参与者子集的现有数据
患有颞下颌关节紊乱病(TMD),他们接受了深入的临床、行为和心理研究
根据R01 DE025946(PI:Colloca,截至2022年9月30日)进行表型鉴定。建议的目标是
与最初的R01有很大不同-探索与预期诱导相关的遗传变异的工作
慢性口腔面部疼痛的止痛作用、心理因素对安慰剂反应的预测作用及相关基因
与预期镇痛相关的前额叶和边缘区域的神经元变化。vbl.使用
院长的倡议基金分配给科洛卡博士,我们采集了血液并从一个子集提取了RNA-SEQ数据
在74名TMD参与者中。有了这个子集的行为、心理、临床和现在的转录数据
在TMD参与者中,中心假设是不同的差异表达基因(DEG)和途径
与内源性疼痛调制(EPM)相关的特征是表现出最高TMD的参与者
安慰剂效应。我们将通过安慰剂比较与高EPM和低EPM相关的转录图谱
在TMD参与者中测试的效果(AIM1),我们将预测高EPM整合转录,
使用机器学习的社会人口学、临床和心理数据(探索性特定目标2)
模特们。为了确定高安慰剂反应性的转录图谱,TMD参与者将被
根据平均报告分为高安慰剂应答者(HLR)和低安慰剂应答者(LPR)
在视觉模拟评分(VAS)上,疼痛评分从0=无痛到100=最高,以30为界值
想象得到的痛苦。基于我们之前发布的结果、信息性的初步结果和DEG能力
计算,我们希望有足够的能力来识别HPR中的关键DEG关联,而不是那些TMD
无反应和/或安慰剂反应较低,同时控制性别、年龄和疼痛严重程度。重要的是
将进行无偏见的浓缩分析,以确定与EPM相关的转录过程。
机器学习方法(例如,广义增强模型)将允许我们整合社会人口统计学,
临床和心理的转录标记物,以进一步表征TMD参与者的HPR。我们队
具有强大的互补性专业知识,确保这项研究将提供综合模型,以实现步骤-
循序渐进地发现那些表现出EPM最大活性的分子机制
安慰剂效应。这是第一个使用转录特征分析和机器学习模型来预测
未被充分研究的TMD人群中的EPM。研究结果将具有很高的临床相关性,并将提供更多信息
广泛的研究产生知识,这些知识将对指导未来迈向一体化和
翻译精准医学。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Luana Colloca其他文献
Luana Colloca的其他文献
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{{ truncateString('Luana Colloca', 18)}}的其他基金
Secondary Analysis and Integration of Existing Data Related to Chronic Orofacial Pain and Placebo Effects - Administrative Supplement
与慢性口面部疼痛和安慰剂效应相关的现有数据的二次分析和整合 - 行政补充
- 批准号:
10741330 - 财政年份:2023
- 资助金额:
$ 42.49万 - 项目类别:
Neural Mechanisms of Immersive Virtual Reality in Chronic Pain
沉浸式虚拟现实治疗慢性疼痛的神经机制
- 批准号:
10617854 - 财政年份:2021
- 资助金额:
$ 42.49万 - 项目类别:
Neural Mechanisms of Immersive Virtual Reality in Chronic Pain
沉浸式虚拟现实治疗慢性疼痛的神经机制
- 批准号:
10314729 - 财政年份:2021
- 资助金额:
$ 42.49万 - 项目类别:
Neural Mechanisms of Immersive Virtual Reality in Chronic Pain
沉浸式虚拟现实治疗慢性疼痛的神经机制
- 批准号:
10455010 - 财政年份:2021
- 资助金额:
$ 42.49万 - 项目类别:
Neural correlates of hypoalgesia driven by observation
观察驱动的痛觉减退的神经相关性
- 批准号:
10452769 - 财政年份:2019
- 资助金额:
$ 42.49万 - 项目类别:
Neural correlates of hypoalgesia driven by observation
观察驱动的痛觉减退的神经相关性
- 批准号:
10212245 - 财政年份:2019
- 资助金额:
$ 42.49万 - 项目类别:
Neural correlates of hypoalgesia driven by observation
观察驱动的痛觉减退的神经相关性
- 批准号:
10673015 - 财政年份:2019
- 资助金额:
$ 42.49万 - 项目类别:
Chronic orofacial pain: genetics, cognitive-emotional factors, and endogenous modulatory systems
慢性口面部疼痛:遗传、认知情绪因素和内源性调节系统
- 批准号:
9265070 - 财政年份:2016
- 资助金额:
$ 42.49万 - 项目类别:
Chronic orofacial pain: genetics, cognitive-emotional factors, and endogenous modulatory systems
慢性口面部疼痛:遗传、认知情绪因素和内源性调节系统
- 批准号:
9098079 - 财政年份:2016
- 资助金额:
$ 42.49万 - 项目类别:
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