Psychosocial risk factors for chronic pain: Characterizing brain and genetic pathways and variation across understudied populations

慢性疼痛的心理社会危险因素：描述大脑和遗传途径以及未充分研究人群的差异

• 批准号: 10599396
• 负责人: TOR D. WAGER
• 金额: $ 45.88万
• 依托单位: DARTMOUTH COLLEGE
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-19 至 2024-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10599396
• 关键词: Acute; Address; Adopted; Adult; African ancestry; American; Amygdaloid structure; Anhedonia; Animals; Anterior; Anxiety; Area; Arthritis; Asian ancestry; Assessment tool; Back Pain; Behavior Therapy; Behavioral; Belief; Biological; Brain; Characteristics; Chronic; Clinic; Clinical; Cognitive; Combined Modality Therapy; Custom; Data; Data Analyses; Data Set; Development; Diabetes Mellitus; Diagnosis; Disease; Economics; Emotions; Epidemiology; Esthesia; European; Evaluation; Functional Imaging; Functional disorder; Future; Gender; Genetic; Genetic Risk; Health; Health Care Costs; Heart Diseases; Human; Individual; Injury; Insula of Reil; Light; Link; Literature; Magnetic Resonance Imaging; Malignant Neoplasms; Measures; Mental Depression; Modeling; Modernization; Neurobiology; Neurotic Disorders; Nociception; Operative Surgical Procedures; Output; Pain; Pathway interactions; Patients; Peripheral; Personality; Persons; Pharmacological Treatment; Pharmacology; Phenotype; Physiological; Policies; Population; Post-Traumatic Stress Disorders; Postoperative Pain; Prevention; Reaction; Resources; Risk; Risk Assessment; Risk Factors; Sampling; Screening procedure; Smell Perception; Societies; Spinal Stenosis; Structure; Symptoms; Techniques; Testing; Thoracic Surgical Procedures; Time; Variant; Work; alternative treatment; base; biobank; brain pathway; burden of illness; central sensitization; chronic pain; chronic painful condition; clinical care; cost; cost effective measures; drug misuse; economic cost; experience; genome wide association study; knee replacement arthroplasty; multiple omics; multisensory; negative affect; neuroimaging; opioid epidemic; opioid mortality; parabrachial nucleus; predictive modeling; prescription pain reliever; prospective; psychologic; psychosocial; racial and ethnic; screening; sex; social; socioeconomics; sound; statistical learning; tool; working group

Chronic pain is a highly prevalent health problem with tremendous cognitive, social, and economic costs to the individual and society. Negative affect and associated disorders–including depression, anxiety, PTSD, neuroticism, catastrophizing, and multisensory sensitivity–confer risk for the development of chronic pain after surgery or injury. These correlations have been shown at the epidemiological, genetic, and brain structural levels, which suggests that negative affect may be a consistent risk factor for multiple types of chronic pain, and therefore an effective target for prevention and treatment. Quantitative predictive models based on negative affect and related risk factors could help identify patients who are likely to develop pain after injury or surgery and those who would respond better to psychological, behavioral, pharmacological, or multimodal treatment. Such models could be readily adopted in clinical screening, but for this to happen in a useful and equitable way, several barriers must be overcome. First, negative affect is often seen as superfluous to the biological mechanisms that drive pain. Second, existing evidence linking them is restricted to statistical associations between aggregate measures, rather than precise predictive models, and effect sizes are moderate but below the level needed for clinical utility. Third, the relevant psychosocial risk factors and the extent of their effects is likely to vary across ancestry, sex, and culture. This study capitalizes on our group’s work over the past 2 years on large-sample genetic, phenotypic, and neuroimaging data analysis to make forward progress on these challenges. In Aim 1, we will use modern statistical learning techniques to develop quantitative predictive models linking negative affect and related psychosocial risk factors to multiple types of chronic pain in the 500,000- person UK Biobank sample, linking psychosocial risk profiles to (a) Genome Wide Association data in >400,000 individuals of European descent and >20,000 samples of African and Asian descent, and (b) MRI measures of brain structure and function on >60,000 individuals. In Aim 2, we investigate how these models apply to, and how they can be customized for, diverse U.S. populations in the 477,000-person All Of Us study, including customizations for racial/ethnic, sex, and socioeconomic characteristics. In Aim 3 (exploratory), we will assess whether these risk profiles predict post-surgical pain in All Of Us (in approximately 40,000 individuals who have undergone surgery) and in the U.S. Acute to Chronic Pain Signatures study, which tracks 2,800 patients longitudinally pre- and post-surgery (knee arthroplasty or thoracic surgery) with psychosocial, functional, imaging, and multi-omics measures. Together, this work will provide new, quantitative models of psychosocial risks for post-surgical pain and beyond that are both readily scalable for clinical use and grounded in a genetic and neurobiological framework.

慢性疼痛是一个非常普遍的健康问题，巨大的认知，社会和经济成本对 个人和社会。负面影响和相关疾病 - 包括抑郁症，动画，PTSD， 在 手术或受伤。这些相关性已在流行病学，遗传和大脑结构水平上显示 这表明负面影响可能是多种类型的慢性疼痛的一致风险因素，并且 因此，预防和治疗的有效目标。基于负面的定量预测模型 情感和相关风险因素可以帮助识别受伤或手术后可能患疼痛的患者 那些对心理，行为，药物或多模式治疗的反应者。 在临床筛查中可以很容易地采用此类模型，但是要以有用且公平的方式发生这种模型 必须克服几个障碍。首先，负面影响通常被视为生物学多余 引起疼痛的机制。其次，将它们联系起来的现有证据仅限于统计协会 在总措施之间而不是精确的预测模型之间，效果大小是现代的，但下面 临床实用程序所需的水平。第三，相关的社会心理危险因素及其影响程度是 可能在祖先，性别和文化中变化。这项研究利用了过去两年来我们小组的工作 关于大样本的遗传，表型和神经影像学数据分析，以在这些数据上进行进步 挑战。在AIM 1中，我们将使用现代统计学习技术来开发定量预测模型 在500,000- 英国人的生物库样本，将心理社会风险概况与（a）> 40万的基因组范围的关联数据联系起来 欧洲血统的个体和> 20,000个非洲和亚洲血统样本，（b）MRI测量 > 60,000个人的大脑结构和功能。在AIM 2中，我们研究了这些模型如何应用于和 如何为它们定制为美国所有人学习的美国人群的潜水员，包括 种族/种族，性别和社会经济特征的定制。在AIM 3（探索性）中，我们将评估 这些风险概况是否预测我们所有人的手术后疼痛（大约有40,000名患者 接受了手术）和美国急性对慢性疼痛签名研究，该研究追踪了2800名患者 纵向手术前后（膝关节置换术或胸外科手术），具有心理，功能，功能 成像和多词措施。这项工作将共同提供新的，定量的社会心理模型 外科后疼痛及以后的风险都可以易于扩展用于临床使用，并以遗传为基础 和神经生物学框架。