Department of Psychology, Carleton University, Ottawa, ON, Canada.
University of Ottawa Institute of Mental Health Research, Ottawa, ON, Canada.
Transl Psychiatry. 2022 Mar 31;12(1):133. doi: 10.1038/s41398-022-01900-6.
Considering the burden of depression and the lack of efficacy of available treatments, there is a need for biomarkers to predict tailored or personalized treatments. However, identifying reliable biomarkers for depression has been challenging, likely owing to the vast symptom heterogeneity and high rates of comorbidity that exists. Examining biomarkers that map onto dimensions of depression as well as shared symptoms/constructs that cut across disorders could be most effective for informing personalized treatment approaches. With a sample of 539 young adults, we conducted a principal component analysis (PCA) followed by hierarchical cluster analysis to develop transdiagnostic clusters of depression and anxiety symptoms. We collected blood to assess whether neuroendocrine (cortisol) and inflammatory profiles (C-reactive protein (CRP), Interleukin (IL)-6, and tumor necrosis factor (TNF) - α) could be used to differentiate symptom clusters. Six distinct clusters were identified that differed significantly on symptom dimensions including somatic anxiety, general anxiety, anhedonia, and neurovegetative depression. Moreover, the neurovegetative depression cluster displayed significantly elevated CRP levels compared to other clusters. In fact, inflammation was not strongly associated with overall depression scores or severity, but rather related to specific features of depression marked by eating, appetite, and tiredness. This study emphasizes the importance of characterizing the biological underpinnings of symptom dimensions and subtypes to better understand the etiology of complex mental health disorders such as depression.
考虑到抑郁的负担以及现有治疗方法效果不佳，我们需要生物标志物来预测针对性或个性化的治疗方法。然而，由于抑郁症状存在广泛的异质性和高共病率，因此识别可靠的抑郁生物标志物一直具有挑战性。研究与抑郁维度相关的生物标志物以及跨障碍共享的症状/结构，可能是为个性化治疗方法提供信息的最有效方法。本研究使用了 539 名年轻成年人的样本，我们进行了主成分分析（PCA），然后进行了层次聚类分析，以开发抑郁和焦虑症状的跨诊断聚类。我们采集了血液以评估神经内分泌（皮质醇）和炎症特征（C 反应蛋白（CRP）、白细胞介素（IL）-6 和肿瘤坏死因子（TNF）-α）是否可用于区分症状聚类。确定了六个不同的聚类，这些聚类在包括躯体焦虑、广泛性焦虑、快感缺失和神经vegetative 抑郁在内的症状维度上存在显著差异。此外，与其他聚类相比，神经vegetative 抑郁聚类的 CRP 水平明显升高。实际上，炎症与总体抑郁评分或严重程度没有很强的关联，而是与以饮食、食欲和疲倦为特征的特定抑郁特征有关。这项研究强调了描述症状维度和亚型的生物学基础的重要性，以更好地理解复杂精神疾病（如抑郁）的病因。
