Inflammatory factors and kynurenine metabolites tracking suicidal behavior

项目总结/摘要 自杀是美国的主要死亡原因，而且自杀率还在继续上升。大多数死于 自杀与卫生保健有关，但临床风险评估具有挑战性。炎症生物标志物具有 暂时与自杀有关然而，纵向研究建立了他们在跟踪自杀的准确性， 缺乏行为和严重症状。因此，我们提出了一项纵向研究，包括1,280项评估， 测量自杀行为、相关临床症状和炎症的血液生物标志物。我们还将 分析自杀死亡者死后脑组织中的炎症介质。我们的首要目标是 确定一组生物标志物，区分有自杀行为的患者和没有自杀行为的抑郁患者。 自杀行为此外，我们打算定义在主动自杀行为期间升高的生物标志物（在- 在同一个病人中。我们的工作模型是炎症（通过促炎细胞因子） 诱导犬尿氨酸途径，导致神经毒性犬尿氨酸代谢物的产生增加（即， NMDA受体激动剂喹啉酸），从而引发自杀行为。我们预测， 自杀个体中的喹啉酸与表观遗传变化有关，调节 血液和脑细胞中的犬尿氨酸酶。我们假设炎性细胞因子和犬尿氨酸 血浆中的代谢物是自杀行为的生物标志物，类似的变化也将是明显的， 自杀死者的死后脑组织为了验证这一点，我们将追求三个具体目标：（1）建立 表明主动自杀行为风险的生物标志物;（2）量化 （3）确定自杀死亡者血液和脑组织中的表观遗传标记， 有自杀行为的患者。在目标1中，我们将入组重度抑郁症（MDD）患者， 自杀行为，以及没有当前或过去自杀行为的MDD患者。每名受试者将在 一年内的8个时间点，包括住院病房入院和出院时的两次评估。我们 将测量白细胞介素和急性期反应物，以及色氨酸，血清素和代谢物， 犬尿氨酸途径。在目标2中，我们将测量死后的炎症生物标志物， 来自相同诊断组和对照组的无药物自杀死亡者的脑组织。我们预计 自杀将与脑部炎症和关键犬尿氨酸代谢物水平增加有关， 反映了途径中酶的表观遗传调节改变。最后，我们将进行全基因组 使用Illumina EPIC阵列进行甲基化分析，然后进行基因途径分析，两者都在血液中进行。 招募的病人和死后的脑组织。我们的项目将有助于生物标志物在临床上的应用。 照顾有自杀风险的病人，以便在关键时刻加强干预。的 这里获得的生物学见解可以指导专门针对自杀倾向的治疗开发， 减少自杀人数的最终目标。

Project Summary/Abstract Suicide is a leading cause of death in the US, and its rate continues to increase. Most individuals who die by suicide are in contact with health care, but clinical risk assessment is challenging. Inflammatory biomarkers have tentatively been linked to suicide. However, longitudinal studies establishing their accuracy in tracking suicidal behavior and critical symptoms are lacking. Therefore, we propose a longitudinal study with 1,280 assessments, measuring suicidal behavior, associated clinical symptoms and blood biomarkers of inflammation. We will also analyze the inflammatory mediators in postmortem brain tissue from suicide decedents. Our overriding aim is to identify a set of biomarkers that distinguish patients with suicidal behavior from depressive patients without suicidal behavior. Further, we intend to define biomarkers that are elevated during active suicidal behavior (at- risk periods) within the same patients. Our working model is that inflammation (via pro-inflammatory cytokines) induces the kynurenine pathway, leading to an increased production of neurotoxic kynurenine metabolites (i.e., the NMDA-receptor agonist quinolinic acid), which triggers suicidal behavior. We predict that the elevated quinolinic acid in suicidal individuals is associated with epigenetic changes, regulating the expression of kynurenine enzymes in blood and brain cells. We hypothesize that inflammatory cytokines and kynurenine metabolites in plasma are biomarkers of suicidal behavior, and that similar changes will also be evident in postmortem brain tissue from suicide decedents. To test this, we will pursue three specific aims: (1) Establish biomarkers that indicate risk for active suicidal behavior; (2) Quantify levels of inflammatory mediators in postmortem brain tissue from suicide decedents; (3) Determine epigenetic marks in blood and brain tissue of patients with suicidal behavior. In Aim 1, we will enroll patients with Major Depressive Disorder (MDD) and active suicidal behavior, and MDD patients without current or past suicidal behavior. Each subject will be assessed at eight time-points over one year, including two assessments at admission and discharge at an inpatient ward. We will measure interleukins and acute phase reactants as well as tryptophan, serotonin and metabolites of the kynurenine pathway in peripheral blood. In Aim 2, we will measure the inflammatory biomarkers in post-mortem brain tissue from medication-free suicide decedents from the same diagnostic groups and controls. We expect that suicide will be associated with inflammation in brain and increased levels of key kynurenine metabolites, reflecting an altered epigenetic regulation of enzymes in the pathway. Last, we will perform whole-genome methylation analysis using Illumina EPIC arrays, followed by gene pathway analyses, both in blood of the enrolled patients and in postmortem brain tissue. Our project will aid the implementation of biomarkers in clinical care for patients with suicide risk, in order to enable intensified intervention during critical time-points. The biological insight obtained here can guide therapeutic development specifically targeting suicidality, with the ultimate goal of reducing suicide numbers.