MS-HRM

  • 文章类型: Journal Article
    背景:对锂(Li)的反应在双相情感障碍(BD)中是高度可变的。尽管经过几十年的研究,尚未一致确定对Li预防反应的临床预测因子。最近,我们开发了表观遗传甲基化特异性高分辨率熔解(MS-HRM)测定法,该测定法能够区分BD1型(BD-I)个体中的良好应答者(GR)与非应答者(NR)和Li。这项研究检查了临床和表观遗传标记的组合是否可以将NR与其他类型的Li反应者区分开。
    方法:我们记录了64名BD-I患者的临床变量,这些变量可能与Li反应相关。对从外周血分离的DNA进行MS-HRM测定。我们使用反向逐步逻辑回归分析,然后进行受试者工作特征(ROC)曲线分析,以估计临床变量的性能,单独与表观遗传生物标志物结合,确定GR和部分响应者(PaR)与NR。
    结果:开始时的极性,BD发病时的精神病症状和家族史根据Li反应正确分类了70%的个体(PaRGR=86%;NR=35%)。当与表观遗传生物标志物结合时,这三个临床变量加上酒精滥用(和一个DMR:差异甲基化区域)正确分类了86%的个体,提高PaR+GR(93%)和NR(70%)的预测。ROC分析显示曲线下面积从0.75(仅临床变量)改善至0.87(临床和表观遗传标记的组合)。
    结论:联合临床预测因子和Li反应的DNA甲基化标记在临床实践中可能比单独依靠临床特征具有更大的实用性。
    BACKGROUND: Response to lithium (Li) is highly variable in bipolar disorders (BD). Despite decades of research, no clinical predictor(s) of response to Li prophylaxis have been consistently identified. Recently, we developed epigenetic Methylation Specific High-Resolution Melting (MS-HRM) assays able to discriminate good responders (GR) from non-responders (NR) to Li in individuals with BD type 1 (BD-I). This study examined whether a combination of clinical and epigenetic markers can distinguish NR from other types of Li responders.
    METHODS: We recorded clinical variables that are potentially associated with Li response in 64 individuals with BD-I. MS-HRM assays were performed on DNA isolated from peripheral blood. We used backward stepwise logistic regression analyses, followed by receiver operating characteristic (ROC) curve analysis to estimate the performance of the clinical variables, alone then in combination with the epigenetic biomarkers, to identify GR and partial responders (PaR) vs NR.
    RESULTS: Polarity at onset, psychotic symptoms at onset and family history of BD classified correctly 70% of individuals according to their Li response (PaR + GR = 86%; NR = 35%). When combined with the epigenetic biomarkers, these three clinical variables plus alcohol misuse (and one DMR: Differentially Methylated Region) correctly classified 86% of individuals, improving the prediction of PaR + GR (93%) and of NR (70%). The ROC analysis demonstrated an improvement in the area under the curve from 0.75 (clinical variables alone) to 0.87 (combination of clinical and epigenetic markers).
    CONCLUSIONS: Combining clinical predictors and DNA methylation markers of Li response may have greater utility in clinical practice than relying on clinical characteristics alone.
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  • 文章类型: Journal Article
    对锂(Li)的反应在双相情感障碍(BD)中变化很大,迄今为止尚未验证长期反应的临床或生物学预测因子。使用全基因组甲基化方法(SeqCapEpi),我们以前确定了7个差异甲基化区域(DMRs),可区分良好和无反应者(使用"Alda"量表定义的预防性反应表型).这项研究证明了这种表观遗传特征从工作台到床边的可转移性。为此,我们使用甲基化特异性高分辨率熔融(MS-HRM),一种基于PCR的方法,可以在任何医学实验室中以低成本和最少的设备实施。在23名患有BD的人中,七个DMRs中有三个的MS-HRM措施在技术上是可行的,SeqCapEpi和MS-HRM措施之间的一致性中等到高。在BD患者的扩展样本中(n=70),三个MS-HRM测量的DMRs主要预测无反应,根据表型的不同定义(基于Alda或机器学习的定义),AUC在0.70-0.80之间。分类树分析进一步表明,MS-HRM测量的DMR将高达84%的个体正确分类为良好或非响应者。这项研究表明,表观遗传生物标志物,在回顾性样本中确定,准确区分非响应者和对Li的响应者,并且可以转移到常规实践。
    Response to lithium (Li) is highly variable in bipolar disorders (BD) and no clinical or biological predictors of long-term response have been validated to date. Using a genome-wide methylomic approach (SeqCapEpi), we previously identified seven differentially methylated regions (DMRs) that discriminated good from non-responders (prophylactic response phenotype defined using the \"Alda\" scale). This study is a proof of transferability from bench to bedside of this epigenetic signature. For this purpose, we used Methylation Specific High-Resolution Melting (MS-HRM), a PCR based method that can be implemented in any medical laboratory at low cost and with minimal equipment. In 23 individuals with BD, MS-HRM measures of three out of seven DMRs were technically feasible and consistencies between SeqCapEpi and MS-HRM-measures were moderate to high. In an extended sample of individuals with BD (n = 70), the three MS-HRM-measured DMRs mainly predicted nonresponse, with AUC between 0.70-0.80 according to different definitions of the phenotype (Alda- or machine-learning-based definitions). Classification tree analyses further suggested that the MS-HRM-measured DMRs correctly classified up to 84% of individuals as good or non-responders. This study suggested that epigenetic biomarkers, identified in a retrospective sample, accurately discriminate non-responders from responders to Li and may be transferrable to routine practice.
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