Behavioral and Neural Phenotypes of Primary Dysmenorrhea in Adolescents

项目总结/摘要 慢性疼痛是一个重要的和昂贵的公共卫生问题，导致国家经济负担， 每年3000亿美元识别那些有发展慢性疼痛风险的生物标志物在很大程度上是未知的。 原发性痛经（PD），定义为月经疼痛没有确定的有机原因，是一个独特的， 研究疼痛过程的人群，因为患有PD的女性有重复的，明确的疼痛发作， 其他方面都没有痛苦数据表明，患有PD的女性与患有PD的个体具有相似的疼痛生物标志物。 慢性疼痛，包括疼痛敏感性增强。因为PD开始于青春期-一个关键的 与建立神经通路和完善大脑网络连接相关的发展阶段- 前瞻性地识别内源性疼痛处理和大脑结构和连接的改变， 人群可以提供有关慢性疼痛机制的关键信息。这是 设计有针对性的个性化治疗以防止那些有风险的人发展的关键下一步 持续的疼痛和残疾。 拟议的研究将使用PD作为模型来检查与月经和非月经相关的生物标志物。 14-18岁青春期女孩的月经身体疼痛，她们将经历广泛的表型，包括疼痛 抑制测试和多模式神经成像，以获得灰质形态计量学、微结构 白色物质的完整性，以及解剖学（扩散张量成像）和功能（静息态磁共振成像） 在基线和12个月后的共振成像）连接。月经疼痛的严重程度和非月经 每月评估身体疼痛，为期24个月。我们的目标是1）确定PD的中枢机制， 疼痛抑制和大脑结构的测量，以及感觉运动、默认、情绪唤起的连接， 和显着性网络，2）确定疼痛抑制的缺陷和大脑结构和网络的改变 预测月经疼痛和非月经身体疼痛的一年发展轨迹的连接性 疼痛，和3）确定疼痛抑制和大脑结构之间的动态关系， 与月经疼痛和非月经身体疼痛的症状变化的连接。我们假设 内源性疼痛抑制的缺陷和脑结构、连接性和区域神经元功能的改变 网络将与基线时的月经疼痛严重程度评分呈正相关，并预测其轨迹 月经期和非月经期的身体疼痛超过2年。将使用图形理论分析成像数据 方法和综合数据分析一般线性和一般线性混合模型。结果 预计将确定预测从急性/周期性转变的具体机制和特征 疼痛持续或慢性疼痛，这将支持治疗的发展，如认知行为 治疗或经颅直流电刺激，以防止从复发性疼痛转变为慢性疼痛， 成年

Project Summary/Abstract Chronic pain is a significant and costly public health concern, resulting in a national economic burden of $300 billion annually. Biomarkers identifying those at risk for developing chronic pain are largely unknown. Primary dysmenorrhea (PD), defined as menstrual pain without an identified organic cause, is a unique population for studying pain processes, as women with PD have repeated, defined episodes of pain and are otherwise pain-free. Data suggest that women with PD share similar pain biomarkers with individuals with chronic pain, including enhanced pain sensitivity. Because PD begins in adolescence – a critical developmental phase associated with establishing neural pathways and refining brain network connectivity – prospectively identifying alterations in endogenous pain processing and brain structure and connectivity in this population can provide critical information about mechanisms involved in the chronification of pain. This is the crucial next step to designing targeted, individualized treatments to prevent those at risk from developing ongoing pain and disability. The proposed study will use PD as a model to examine biomarkers associated with menstrual and non- menstrual bodily pain in adolescent girls, ages 14-18, who will undergo extensive phenotyping including pain inhibition testing and multimodal neuroimaging to obtain indices of gray matter morphometry, microstructural integrity of white matter, and anatomical (diffusion tensor imaging) and functional (resting state magnetic resonance imaging) connectivity at baseline and 12 months later. Menstrual pain severity and non-menstrual bodily pain will be assessed monthly for 24 months. We aim to 1) identify the central mechanisms of PD using measures of pain inhibition and brain structure and connectivity of sensorimotor, default, emotional arousal, and salience networks, 2) determine deficits in pain inhibition and alterations in brain structure and network connectivity that predict the one-year developmental trajectories of menstrual pain and non-menstrual bodily pain, and 3) identify the dynamic relationship between alterations in pain inhibition and brain structure and connectivity with symptom change in menstrual pain and non-menstrual bodily pain. We hypothesize that deficits in endogenous pain inhibition and alterations in brain structure, connectivity, and function of regional networks will be positively associated with menstrual pain severity ratings at baseline and predict the trajectory of menstrual and non-menstrual bodily pain over 2 years. Imaging data will be analyzed using graph theoretical approaches, and comprehensive data analyses general linear and general linear mixed models. The results are expected to identify specific mechanisms and characteristics that predict the transition from acute/cyclical pain to persistent or chronic pain, which will support the development of therapies, such as cognitive-behavior therapy or transcranial direct current stimulation, to prevent the transition from recurrent to chronic pain in adulthood.