Department of Cell Biology and Immunology, Institute of Parasitology and Biomedicine López-Neyra, CSIC.
Departamento de Genética e Instituto de Biotecnología, Centro de Investigación Biomédica, Universidad de Granada, Armilla.
Curr Opin Rheumatol. 2022 Nov 1;34(6):295-301. doi: 10.1097/BOR.0000000000000897. Epub 2022 Aug 16.
Systemic sclerosis (SSc) is a complex autoimmune disorder that affects the connective tissue and causes severe vascular damage and fibrosis of the skin and internal organs. There are recent advances in the field that apply novel methods to high throughput genotype information of thousands of patients with SSc and provide promising results towards the use of genomic data to help SSc diagnosis and clinical care.
This review addresses the development of the first SSc genomic risk score, which can contribute to differentiating SSc patients from healthy controls and other immune-mediated diseases. Moreover, we explore the implementation of data mining strategies on the results of genome-wide association studies to highlight subtype-specific HLA class II associations and a strong association of the HLA class I locus with SSc for the first time. Finally, the combination of genomic data with transcriptomics informed drug repurposing and genetic association studies in well characterized SSc patient cohorts identified markers of severe complications of the disease.
Early diagnosis and clinical management of SSc and SSc-related complications are still challenging for rheumatologists. The development of predictive models and tools using genotype data may help to finally deliver personalized clinical care and treatment for patients with SSc in the near future.
目的综述:系统性硬化症(SSc)是一种复杂的自身免疫性疾病,会影响结缔组织,并导致皮肤和内部器官的严重血管损伤和纤维化。该领域最近有了新的进展,将新型方法应用于数千例 SSc 患者的高通量基因型信息,为利用基因组数据帮助 SSc 诊断和临床护理提供了有希望的结果。
最新发现:这篇综述介绍了第一个 SSc 基因组风险评分的发展,它有助于区分 SSc 患者与健康对照者和其他免疫介导性疾病。此外,我们还探讨了在全基因组关联研究结果上实施数据挖掘策略,以突出特定亚型的 HLA Ⅱ类关联,并首次强烈关联 HLA Ⅰ类基因座与 SSc。最后,将基因组数据与转录组学结合起来,对具有明确特征的 SSc 患者队列进行药物再利用和遗传关联研究,确定了疾病严重并发症的标志物。
总结:早期诊断和 SSc 及 SSc 相关并发症的临床管理对风湿病学家来说仍然具有挑战性。使用基因型数据开发预测模型和工具,可能有助于在不久的将来为 SSc 患者提供个性化的临床护理和治疗。