自身免疫性疾病和炎症性疾病 (AID) 是一组具有不同病因机制的异质性疾病。本研究探讨了家族史以及当前和过去的合并症在识别不同病因亚组方面的潜在效用。这种方法可能有助于更准确的诊断、预后和个性化治疗。我们对患者的合并症进行了多重对应分析，然后对来自 48 名健康志愿者和 327 名患有 19 种选定 AID 中至少一种的患者的临床数据进行分层主成分聚类。 TRANSIMMUNOM 横断面研究。我们确定了三个不同的集群，其特征是：1）不存在合并症，2）多自身免疫，3）多炎症。这些簇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发性自身免疫群的特征，而老年、BMI、抑郁症、癌症、高血压、牙周病和血脂异常是多发性炎症群的特征。类风湿性关节炎患者分布在所有三个集群中。当属于多炎症和多自身免疫簇时，他们的 DAS28 和关节外表现的患病率较高，并且在多炎症簇内 ACPA 和 RF 血清阳性率较低，疼痛评分较高。我们开发了一个模型，可以将 AID 患者分类为合并症群。在这项研究中，我们发现了 AID 患者中三种不同的合并症概况。这些概况表明这些亚组存在不同的致病机制。为了全面了解它们在个性化医疗中的潜在作用，需要验证、纵向稳定性评估以及探索它们对治疗效果的影响。版权所有 © 2024 作者。由爱思唯尔有限公司出版。保留所有权利。

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.Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.