2/2 - Inflammation and Stress Response in Familial and Nonfamilial Youth Suicidal Behavior

自杀是美国年轻人死亡的第二大原因，17年来上升了33%。临床危险因素 单独具有令人失望的预测能力，生物预测因子显示出希望，但很少分为长期- 由于在自杀行为前不久检测生物特征的挑战， （SB）。我们提出了一种新的务实的方法，检查生物风险概况后，立即急性 自杀危机，然后将其分为家庭和非家庭风险概况。我们的合作表明 与更致命的家族性SB相关的应激反应生物表型，其中炎症 激活犬尿氨酸途径，通过将色氨酸从5-羟色胺转向 犬尿氨酸合成。炎症和神经炎症可能是由HPA轴引起的， 线粒体失调我们还发现，HPA轴失调和炎症反应， 我们假设家族因素主要是长期和非家族性的 主要是短期风险因素。我们建议检查短期或近端生物风险概况 在应激反应和炎症通路中，外周和大脑中的自杀行为（SB），以及 研究年轻人SB的家族和非家族生物学机制。我们将招募120名年轻人 精神科住院患者或门诊患者，年龄18-30岁，80岁，SB高风险定义为那些出现在 急诊科（艾德）或因自杀意念（SI）入院，并有计划和意图，或在最后两个月内有SB 40例风险较低，在过去3个月内没有SB或SI计划/意图。组将频率匹配 家庭风险。我们将收集：1）临床数据; 2）头发，以测量头发皮质醇浓度（HCC）; 3）进行 特里尔社会应激任务（TSST），以测量皮质醇、外周炎症（细胞因子、犬尿氨酸） 代谢物）和循环无细胞线粒体DNA（ccf-mtDNA）; 4）使用[11 C] ER 176配体的PET成像 测量神经炎症;和5）近红外光谱（NIRS）测量PFC氧化态， 细胞色素c氧化酶（oxCOX），线粒体功能的脑标志物。患者将在1、3、 还有12个月住院/艾德出院后一年是SB的高风险期，前3个月是SB的高风险期。 最高风险期。我们假设高风险患者将显示较高的[11 C] ER 176 PET结合和较低的oxCOX 在基线。他们也会表现出较低的HCC和较高的皮质醇反应的压力和较高的炎症， ccf-mtDNA之前和基线时对应激的反应。后代会表现出更严重的生物学 由于短期和长期风险因素的影响，我们还将研究 之间的外周和大脑的措施，并探讨他们是否预测SB。这项研究将提高我们的 了解SB的家族和非家族生物学机制，以更好地区分长期和短期 术语风险生物表型，这将有助于指导风险检测和新的及时方法。

Suicide is 2nd leading cause of death in the US youth, and rates have risen 33% in 17 years. Clinical risk factors alone have disappointing predictive power and biological predictors show promise but rarely separated into long- term and short-term predictors due to the challenge of detecting biological profiles shortly before suicide behavior (SB). We propose a novel pragmatic approach of examining biological risk profiles immediately after an acute suicidal crisis and then separating them into familial and nonfamilial risk profiles. Our collaborative work indicates a stress responsive biological phenotype associated with more lethal and familial SB where inflammation activates the kynurenine pathway depleting brain serotonin by shunting tryptophan away from serotonin toward kynurenine synthesis. Inflammation and neuroinflammation can potentially result from HPA axis and mitochondrial dysregulations. We also find HPA axis dysregulation and inflammation to be more pronounced in those with SB and family history of SB. We hypothesize familial factors to be mostly long-term and nonfamilial factors to be mostly short-term risk factors. We propose to examine short-term or proximal biological risk profiles for suicidal behavior (SB) in stress response and inflammatory pathways, peripherally and in the brain, and examine familial and nonfamilial biological mechanisms for SB in young adults. We will recruit 120 young adult psychiatric inpatients or outpatients, aged 18-30 years, 80 at high-risk for SB defined as those presenting to the emergency department (ED) or admitted for suicidal ideation (SI) with a plan and intent or SB in the last two weeks; and 40 at lower risk with no SB or SI with plan/intent in past 3 months. Groups will be frequency-matched on familial risk. We will collect: 1) clinical data; 2) hair to measure hair cortisol concentrations (HCC); 3) conduct the Trier Social Stress Task (TSST) to measure cortisol, peripheral inflammation (cytokines, kynurenine metabolites) and circulating cell free mitochondrial DNA (ccf-mtDNA); 4) PET imaging using [11C]ER176 ligand to measure neuroinflammation; and 5) near-infrared spectroscopy (NIRS) to measure in PFC oxidation state of cytochrome-c-oxidase (oxCOX), a brain marker of mitochondrial function. Patients will be followed up at 1, 3, and 12 months. The year post-hospital/ED discharge is a high-risk period for SB and the first 3 months is the highest risk period. We hypothesize high-risk patients will show higher [11C]ER176 PET binding and lower oxCOX at baseline. They will also show lower HCC and higher cortisol response to stress and higher inflammation and ccf-mtDNA prior and in response to stress at baseline. Offspring of attempters will show more severe biological profiles due to the contribution of short and longer-term risk factors. We will also examine the relationships between peripheral and brain measures and explore whether they predict SB. This study will improve our understanding of familial and nonfamilial biological mechanisms for SB to better separate long-term and short- term risk biological phenotypes, which will help guide risk detection and novel just-in-time approaches.