Abstract:
It appears that the THC dosage is the link between dysregulation of the hypothalamic pituitary adrenal (HPA) axis and suicidal thoughts and behaviors (STB). We proposed a new model to understand the underlying pathophysiological mechanism of STB based on the interaction of cortisol and THC dosage. From September 1, 2019, to January 1, 2024, we conducted a population-based, matched-pair, nested case-control study resulting from a three-wave complete longitudinal, multicenter cohort study on a sample of congress 60 clients. A total of 368 male continued cannabis users (CCu) were allocated to four categories, including low, moderate and high THC dosages and relapse, using optimal matching. Several HPA axis measures were analyzed in the saliva using liquid chromatography with tandem mass spectrometry (LC-MS-MS), and carboxylic acids levels in the urine were assessed via gas chromatography/mass spectrometry (GC-MS). We used structural equation modeling (SEM) to examine the relationship between the variables of interest and the model fit test, and used the Akaike information criterion (AIC) to compare the model fit and select the best-fitting model. Population attributable fractions (PAFs) and cumulative risk score were also calculated for the best-fitting pattern. The analysis showed that the likelihood of STB in individuals with a cortisol awakening response (CAR) and a blunted diurnal cortisol slope (DCS) and higher area under the curve (AUC) who reported heavy cannabis use was more than three times higher than the control group (OR 3.2, 95 % CI 2.4-4.1). These findings indicate the importance of the specific cortisol secretion pattern in the increased clinical expression of STB and may be an important factor for guiding preventive efforts in this area.
摘要:
似乎THC剂量是下丘脑垂体肾上腺(HPA)轴失调与自杀念头和行为(STB)之间的联系。我们提出了一种基于皮质醇和THC剂量相互作用的新模型来理解STB的潜在病理生理机制。从2019年9月1日到2024年1月1日,我们进行了以人口为基础的,配对,嵌套病例对照研究是由三波完整的纵向,对国会60名客户进行的多中心队列研究。共有368名男性持续大麻使用者(CCu)被分配到四个类别,包括低,中等和高THC剂量和复发,使用最优匹配。使用液相色谱-串联质谱(LC-MS-MS)分析唾液中的几种HPA轴测量值,通过气相色谱/质谱(GC-MS)评估尿液中的羧酸水平。我们使用结构方程模型(SEM)来检验感兴趣变量与模型拟合检验之间的关系,并采用Akaike信息准则(AIC)对模型拟合度进行比较,选择拟合度最佳的模型。还计算了最佳拟合模式的人群归因分数(PAF)和累积风险评分。分析显示,报告大量使用大麻的皮质醇觉醒反应(CAR)和昼夜皮质醇斜率(DCS)和曲线下面积(AUC)较高的个体发生STB的可能性比对照组高三倍以上(OR3.2,95%CI2.4-4.1)。这些发现表明特定的皮质醇分泌模式在STB临床表达增加中的重要性,并且可能是指导该领域预防工作的重要因素。