GENYO. Centre for Genomics and Oncological Research: Pfizer, University of Granada, Andalusian Regional Government, PTS Granada, Avenida de la Ilustración 114, 18016, Granada, Spain.
Department of Statistics. University of Granada, 18071, Granada, Spain.
Brief Bioinform. 2022 Sep 20;23(5). doi: 10.1093/bib/bbac332.
Systemic Lupus Erythematosus is a complex autoimmune disease that leads to significant worsening of quality of life and mortality. Flares appear unpredictably during the disease course and therapies used are often only partially effective. These challenges are mainly due to the molecular heterogeneity of the disease, and in this context, personalized medicine-based approaches offer major promise. With this work we intended to advance in that direction by developing MyPROSLE, an omic-based analytical workflow for measuring the molecular portrait of individual patients to support clinicians in their therapeutic decisions.
Immunological gene-modules were used to represent the transcriptome of the patients. A dysregulation score for each gene-module was calculated at the patient level based on averaged z-scores. Almost 6100 Lupus and 750 healthy samples were used to analyze the association among dysregulation scores, clinical manifestations, prognosis, flare and remission events and response to Tabalumab. Machine learning-based classification models were built to predict around 100 different clinical parameters based on personalized dysregulation scores.
MyPROSLE allows to molecularly summarize patients in 206 gene-modules, clustered into nine main lupus signatures. The combination of these modules revealed highly differentiated pathological mechanisms. We found that the dysregulation of certain gene-modules is strongly associated with specific clinical manifestations, the occurrence of relapses or the presence of long-term remission and drug response. Therefore, MyPROSLE may be used to accurately predict these clinical outcomes.
MyPROSLE (https://myprosle.genyo.es) allows molecular characterization of individual Lupus patients and it extracts key molecular information to support more precise therapeutic decisions.
红斑狼疮是一种复杂的自身免疫性疾病，会导致生活质量显著恶化和死亡率升高。疾病过程中会出现不可预测的发作，而使用的疗法往往仅部分有效。这些挑战主要归因于疾病的分子异质性，在这种情况下，基于个性化医学的方法提供了重大的希望。我们旨在通过开发 MyPROSLE 来朝这个方向取得进展，这是一种基于组学的分析工作流程，用于测量个体患者的分子特征，以支持临床医生做出治疗决策。
免疫基因模块用于代表患者的转录组。基于平均 z 分数，在患者水平上计算每个基因模块的失调评分。使用近 6100 个狼疮和 750 个健康样本，分析失调评分与临床表现、预后、发作和缓解事件以及对 Tabalumab 的反应之间的关联。基于个性化失调评分，构建基于机器学习的分类模型来预测大约 100 种不同的临床参数。
MyPROSLE 允许将患者分子总结为 206 个基因模块，聚类为九个主要狼疮特征。这些模块的组合揭示了高度分化的病理机制。我们发现，某些基因模块的失调与特定的临床表现、复发的发生或长期缓解和药物反应的存在密切相关。因此，MyPROSLE 可用于准确预测这些临床结果。
MyPROSLE（https://myprosle.genyo.es）允许对个体狼疮患者进行分子特征分析，并提取关键分子信息，以支持更精确的治疗决策。
