Biomarkers to Personalize the Treatment of Rheumatoid Arthritis: Focus on Autoantibodies and Pharmacogenetics.
Biomarkers to Personalize the Treatment of Rheumatoid Arthritis: Focus on Autoantibodies and Pharmacogenetics.
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DOI：
10.3390/biom10121672
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发表时间：
2020-12-14
期刊：
影响因子：
5.5
通讯作者：
Filippelli A
中科院分区：
文献类型：
--
作者：
Conti V;Corbi G;Costantino M;De Bellis E;Manzo V;Sellitto C;Stefanelli B;Colucci F;Filippelli A
类风湿性关节炎（RA）是一种复杂的慢性炎症性疾病。如果治疗不充分，RA患者可能会表现出过度的发病率和残疾，对生活质量产生重要影响。药理学治疗是基于疾病缓解抗风湿药物（DMARD）的给药，分为常规合成（csDMARD），靶向合成（tsDMARD）和生物（bDMARD）。bDMARD现在经常用于患者，既可作为替代治疗，也可与csDMARD一起使用。不幸的是，对新旧药物都存在治疗反应的差异性。因此，确定治疗前和治疗中的反应预测因子是一个优先事项。本文综述了近年来在理解RA治疗反应变异性的原因方面取得的进展，特别关注自身抗体和DMARD药物遗传学的预测潜力。近年来，已经提出了几种生物标志物来个性化治疗。不幸的是，并不存在灵丹妙药，因为许多因素与疾病易感性和治疗结果一致，围绕患者的先天背景起作用。需要整合人口统计学、临床、生化和遗传数据的模型，以增强特定因素的预测能力，这些因素被单独考虑，以优化多学科患者管理中的RA治疗。
Rheumatoid arthritis (RA) is a chronic inflammatory disease that is very complex and heterogeneous. If not adequately treated, RA patients are likely to manifest excess of morbidity and disability with an important impact on the quality of life. Pharmacological treatment is based on the administration of the disease-modifying antirheumatic drugs (DMARDs), subdivided into conventional synthetic (csDMARDs), targeted synthetic (tsDMARDs), and biological (bDMARDs). bDMARDs are now frequently administered in patients, both as alternative treatment and together with csDMARDs. Unfortunately, there is a therapeutic response variability both to old and new drugs. Therefore, to identify pre-therapeutic and on-treatment predictors of response is a priority. This review aims to summarize recent advances in understanding the causes of the variability in treatment response in RA, with particular attention to predictive potential of autoantibodies and DMARD pharmacogenetics. In recent years, several biomarkers have been proposed to personalize the therapy. Unfortunately, a magic bullet does not exist, as many factors concur to disease susceptibility and treatment outcomes, acting around the patient’s congenital background. Models integrating demographic, clinical, biochemical, and genetic data are needed to enhance the predictive capacity of specific factors singularly considered to optimize RA treatment in light of multidisciplinary patient management.
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影响因子：
2.1
作者：
Cuchacovich, M.;Soto, L.;Valenzuela, O.
通讯作者：
Valenzuela, O.
影响因子：
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作者：
Conti V;De Bellis E;Manzo V;Sabbatino F;Iannello F;Dal Piaz F;Izzo V;Charlier B;Stefanelli B;Torsiello M;Iannaccone T;Coglianese A;Colucci F;Pepe S;Filippelli A
通讯作者：
Filippelli A
影响因子：
2.6
作者：
Canet, Luz M.;Filipescu, Ileana;Sainz, Juan
通讯作者：
Sainz, Juan
影响因子：
--
作者：
Bendtzen, Klaus;Geborek, Pierre;Saxne, Tore
通讯作者：
Saxne, Tore
影响因子：
4.9
作者：
de Moel EC;Derksen VFAM;Stoeken G;Trouw LA;Bang H;Goekoop RJ;Speyer I;Huizinga TWJ;Allaart CF;Toes REM;van der Woude D
通讯作者：
van der Woude D