Inflammatory factors and kynurenine metabolites tracking suicidal behavior

项目摘要/摘要 在美国，自杀是主要的死亡原因，而且其比率还在继续上升。大多数人死于 自杀与医疗保健联系在一起，但临床风险评估具有挑战性。炎性生物标志物 暂时被认为与自杀有关。然而，纵向研究证实了它们在追踪自杀行为方面的准确性 缺乏行为和严重症状。因此，我们建议进行一项有1280项评估的纵向研究， 测量自杀行为、相关的临床症状和炎症的血液生物标志物。我们还将 分析自杀死者死后脑组织中的炎症介质。我们最重要的目标是 确定一组生物标记物，区分有自杀行为的患者和无自杀行为的抑郁症患者 自杀行为。此外，我们打算定义在主动自杀行为期间(在- 风险期)。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)，触发自杀行为。我们预测，被抬高的 自杀个体中的喹啉酸与表观遗传学变化有关，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，类似的变化也将在 自杀死者的死后脑组织。为了测试这一点，我们将追求三个具体目标：(1)建立 指示主动自杀行为风险的生物标记物；(2)量化炎症介质水平 自杀死者的死后脑组织；(3)测定自杀死者血液和脑组织中的表观遗传标记 有自杀行为的病人。在目标1中，我们将招募患有严重抑郁障碍(MDD)和活动期的患者 自杀行为，以及目前或过去没有自杀行为的MDD患者。每门课的成绩将在 一年中的8个时间点，包括住院病房入院和出院时的两次评估。我们 将测量白细胞介素素和急性期反应物以及色氨酸、5-羟色胺和 外周血中犬尿氨酸途径。在目标2中，我们将测量身体中的炎性生物标志物 来自相同诊断组和对照组的非药物自杀死者的脑组织。我们预计 自杀将与脑部炎症和关键犬尿氨酸代谢物水平升高有关， 反映了该途径中酶的表观遗传调节的改变。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，这两种方法都是在 在登记的患者和死后脑组织中。我们的项目将帮助生物标记物在临床上的实施 护理有自杀风险的患者，以便能够在关键时间点加强干预。这个 在这里获得的生物学洞察力可以指导专门针对自杀的治疗开发， 最终目标是减少自杀人数。

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.