Hässler Signe, Lorenzon Roberta, Binvignat Marie, Ribet Claire, Roux Alexandra, Johanet Catherine, Amouyal Chloé, Amselem Serge, Berenbaum Francis, Benveniste Olivier, Cacoub Patrice, Grateau Gilles, Hartemann Agnès, Saadoun David, Salem Joe-Elie, Sellam Jérémie, Seksik Philippe, Vicaut Eric, Mariotti-Ferrandiz Encarnita, Rosenzwajg Michelle, Klatzmann David
Immunology, Immunopathology, Immunotherapy (i3), Sorbonne Université, INSERM, Paris, 75013, France; Biotherapy (CIC-BTi) and Inflammation, Immunopathology, Biotherapy Department (i2B), Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, Paris, 75013, France.
Immunology, Immunopathology, Immunotherapy (i3), Sorbonne Université, INSERM, Paris, 75013, France; Biotherapy (CIC-BTi) and Inflammation, Immunopathology, Biotherapy Department (i2B), Pitié-Salpêtrière Hospital, Assistance Publique-Hôpitaux de Paris, Paris, 75013, France; INSERM UMRS 938, Centre de Recherche Saint-Antoine, FHU PaCeMM, Sorbonne Université, Paris, 75012, France; Rheumatology Department, Saint-Antoine Hospital, Assistance Publique-Hôpitaux de Paris, Paris, 75012, France.
J Autoimmun. 2024 Dec;149:103318. doi: 10.1016/j.jaut.2024.103318. Epub 2024 Oct 1.
Autoimmune and inflammatory diseases (AIDs) are a heterogeneous group of disorders with diverse etiopathogenic mechanisms. This study explores the potential utility of family history, together with present and past comorbidities, in identifying distinct etiopathogenic subgroups. This approach may facilitate more accurate diagnosis, prognosis and personalized therapy.
We performed a multiple correspondence analysis on patients' comorbidities, followed by hierarchical principal component clustering of clinical data from 48 healthy volunteers and 327 patients with at least one of 19 selected AIDs included in the TRANSIMMUNOM cross-sectional study.
We identified three distinct clusters characterized by: 1) the absence of comorbidities, 2) polyautoimmunity, and 3) polyinflammation. These clusters were further distinguished by specific comorbidities and biological parameters. Autoantibodies, allergies, and viral infections characterized the polyautoimmunity cluster, while older age, BMI, depression, cancer, hypertension, periodontal disease, and dyslipidemia characterized the polyinflammation cluster. Rheumatoid arthritis patients were distributed across all three clusters. They had higher DAS28 and prevalence of extra-articular manifestations when belonging to the polyinflammation and polyautoimmunity clusters, and also lower ACPA and RF seropositivity and higher pain scores within the polyinflammation cluster. We developed a model allowing to classify AID patients into comorbidity clusters.
In this study, we have uncovered three distinct comorbidity profiles among AID patients. These profiles suggest the presence of distinct etiopathogenic mechanisms underlying these subgroups. Validation, longitudinal stability assessment, and exploration of their impact on therapy efficacy are needed for a comprehensive understanding of their potential role in personalized medicine.
自身免疫性和炎性疾病(AIDs)是一组病因发病机制多样的异质性疾病。本研究探讨家族史以及当前和既往合并症在识别不同病因发病亚组方面的潜在效用。这种方法可能有助于更准确的诊断、预后评估和个性化治疗。
我们对患者的合并症进行了多重对应分析,随后对来自48名健康志愿者和327名患有TRANSIMMUNOM横断面研究中19种选定AIDs中至少一种疾病的患者的临床数据进行了分层主成分聚类。
我们识别出三个不同的聚类,其特征分别为:1)无合并症;2)多自身免疫性;3)多炎症性。这些聚类通过特定的合并症和生物学参数进一步区分。自身抗体、过敏和病毒感染是多自身免疫性聚类的特征,而高龄、体重指数、抑郁症、癌症、高血压、牙周病和血脂异常是多炎症性聚类的特征。类风湿关节炎患者分布在所有三个聚类中。当他们属于多炎症性和多自身免疫性聚类时,疾病活动评分28(DAS28)更高且关节外表现的患病率更高,而在多炎症性聚类中,抗环瓜氨酸肽抗体(ACPA)和类风湿因子(RF)血清阳性率更低且疼痛评分更高。我们开发了一个模型,可将AID患者分类到合并症聚类中。
在本研究中,我们在AID患者中发现了三种不同的合并症特征。这些特征表明这些亚组背后存在不同的病因发病机制。为了全面了解它们在个性化医疗中的潜在作用,需要进行验证、纵向稳定性评估以及探索它们对治疗效果的影响。