Department of Psychiatry, Royal College of Surgeons in Ireland, Dublin, Ireland.
SFI FutureNeuro Research Centre, Royal College of Surgeons in Ireland, Dublin, Ireland.
Transl Psychiatry. 2022 Sep 9;12(1):377. doi: 10.1038/s41398-022-02142-2.
Individuals with psychotic disorders and depressive disorder exhibit altered concentrations of peripheral inflammatory markers. It has been suggested that clinical trials of anti-inflammatory therapies for psychiatric disorders should stratify patients by their inflammatory profile. Hence, we investigated whether different subgroups of individuals exist across psychiatric disorders, based on their inflammatory biomarker signatures. We measured the plasma concentrations of 17 inflammatory markers and receptors in 380 participants with psychotic disorder, depressive disorder or generalised anxiety disorder and 399 controls without psychiatric symptoms from the ALSPAC cohort at age 24. We employed a semi-supervised clustering algorithm, which discriminates multiple clusters of psychiatric disorder cases from controls. The best fit was for a two-cluster model of participants with psychiatric disorders (Adjusted Rand Index (ARI) = 0.52 ± 0.01) based on the inflammatory markers. Permutation analysis indicated the stability of the clustering solution performed better than chance (ARI = 0.43 ± 0.11; p < 0.001), and the clusters explained the inflammatory marker data better than a Gaussian distribution (p = 0.021). Cluster 2 exhibited marked increases in sTNFR1/2, suPAR, sCD93 and sIL-2RA, compared to cluster 1. Participants in the cluster exhibiting higher inflammation were less likely to be in employment, education or training, indicating poorer role functioning. This study found evidence for a novel pattern of inflammatory markers specific to psychiatric disorders and strongly associated with a transdiagnostic measure of illness severity. sTNFR1/2, suPAR, sCD93 and sIL-2RA could be used to stratify clinical trials of anti-inflammatory therapies for psychiatric disorders.
个体患有精神病性障碍和抑郁障碍会表现出外周炎症标志物浓度的改变。有人提出,对于精神疾病的抗炎治疗临床试验,应该根据患者的炎症状况对其进行分层。因此,我们研究了是否存在不同的亚组,这些亚组是基于他们的炎症生物标志物特征存在于精神障碍患者中。我们测量了来自 ALSPAC 队列的 380 名患有精神病性障碍、抑郁障碍或广泛性焦虑障碍的个体以及 399 名无精神病症状的对照者在 24 岁时的血浆中 17 种炎症标志物和受体的浓度。我们采用了一种半监督聚类算法,该算法可以区分精神病病例和对照者的多个聚类。根据炎症标志物,对精神病患者(调整兰德指数(ARI)=0.52±0.01)最好的拟合是两个聚类模型。置换分析表明聚类解决方案的稳定性优于随机(ARI=0.43±0.11;p<0.001),并且聚类比高斯分布更好地解释了炎症标志物数据(p=0.021)。与聚类 1 相比,聚类 2 中 sTNFR1/2、suPAR、sCD93 和 sIL-2RA 明显增加。在聚类中表现出更高炎症的个体更不可能就业、接受教育或培训,表明其角色功能更差。这项研究为特定于精神障碍的新型炎症标志物模式提供了证据,并且与疾病严重程度的跨诊断测量指标密切相关。sTNFR1/2、suPAR、sCD93 和 sIL-2RA 可以用于分层抗炎治疗精神疾病的临床试验。