A blood-based prognostic biomarker in inflammatory bowel disease
A blood-based prognostic biomarker in inflammatory bowel disease
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炎症性肠病的血液预后生物标志物
DOI：
10.1101/535153
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发表时间：
2019
期刊：
影响因子：
--
通讯作者：
Biasci D
中科院分区：
文献类型：
--
作者：
Biasci D
目的我们之前描述了 CD8 T 细胞中的预后转录特征，该特征将炎症性肠病 (IBD) 患者分为 2 个表型不同的亚组，我们将其称为 IBD1 和 IBD2。在这里，我们试图开发一种基于血液的预后测试，无需细胞分离即可识别这些患者亚组，从而适合克罗恩病（CD）和溃疡性结肠炎（UC）的常规临床使用。设计在治疗前招募活动性IBD患者。对纯化的 CD8 T 细胞和/或全血进行转录组分析。前瞻性收集详细的表型信息。 IBD1/IBD2 患者亚组通过 CD8 T 细胞转录组的共识聚类来确定。在训练队列中，统计（机器）学习用于识别全血中差异表达的基因组（“分类器”），重新创建了 IBD1/IBD2 患者亚组。来自最佳分类器的基因经过 qPCR 优化，并将进一步的统计学习应用于 qPCR 数据集，以确定最佳分类器，并将其锁定以进行进一步测试。在不同的 CD (n=66) 和 UC 患者 (n=57) 队列中寻求独立验证。结果在两个独立验证队列中，基于 17 基因 qPCR 的分类器将患者分为两个不同的亚组。无论潜在的诊断如何，IBDhi 患者（类似于预后不良的 IBD1 亚组）比 IBDlo 患者（类似于 IBD2）经历了明显更具侵袭性的疾病，需要更早地升级治疗，并且随着时间的推移会升级更多。结论这是第一个经过验证的预后生物标志物，可以预测新诊断的 IBD 患者的预后，代表着向个性化治疗迈出了一步。关于该主题的已知信息CD 和 UC 的病程患者之间差异很大，但临床实践中尚无可靠的预后标志物。这阻碍了疾病管理，因为对于惰性疾病患者来说最佳的治疗方法（其特点是不频繁发作，可以通过一线治疗轻松控制）将不可避免地对患有进展性疾病的患者治疗不足。相反，适当控制经常复发、进行性疾病的策略将使处于静止期疾病的患者面临不必要治疗的风险和副作用。我们之前描述了与 T 细胞耗竭差异相对应的 CD8 T 细胞基因表达特征，在未治疗的活动性疾病期间（包括诊断时）可检测到，并预测 UC 和 CD 的病程。然而，对细胞分离和基于微阵列的基因表达分析的需求使得这种方法难以转化为临床实践。新发现是什么我们开发、优化并独立验证了一种基于全血 qPCR 的分类器，旨在识别 IBD1 和 IBD2 患者亚组，无需细胞分离即可可靠地预测 CD 或 UC 患者的预后。我们还提供了 IBD1/IBDhi 或 IBD2/IBDlo 亚组患者经历的病程的详细表型更新，包括扩大的患者队列和更长的随访时间。这为这些患者亚组不同需要的治疗方案提供了新的见解，并加强了它们与疾病预后的关联。在可预见的未来，它会对临床实践产生怎样的影响？基于 qPCR 的分类器具有优于预后的性能特征……
ObjectiveWe have previously described a prognostic transcriptional signature in CD8 T cells that separates inflammatory bowel disease (IBD) patients into 2 phenotypically-distinct subgroups, which we termed IBD1 and IBD2. Here we sought to develop a blood-based prognostic test that could identify these patient subgroups without the need for cell separation, and thus be suitable for routine clinical use in Crohn’s disease (CD) and ulcerative colitis (UC).DesignPatients with active IBD were recruited before treatment. Transcriptomic analyses were performed on purified CD8 T cells and/or whole blood. Detailed phenotype information was collected prospectively. IBD1/IBD2 patient subgroups were identified by consensus clustering of CD8 T cell transcriptomes. In a training cohort, statistical (machine) learning was used to identify groups of genes (“classifiers”) whose differential expression in whole blood re-created the IBD1/IBD2 patient subgroups. Genes from the best classifiers were qPCR-optimised, and further statistical learning was applied to the qPCR dataset to identify the optimal classifier, which was locked-down for further testing. Independent validation was sought in separate cohorts of CD (n=66) and UC patients (n=57).ResultsIn both independent validation cohorts, a 17-gene qPCR-based classifier stratified patients into two distinct subgroups. Irrespective of the underlying diagnosis, IBDhi patients (analogous to the poor prognosis IBD1 subgroup) experienced significantly more aggressive disease than IBDlo patients (analogous to IBD2), with earlier need for treatment escalation and more escalations over time.ConclusionThis is the first validated prognostic biomarker that can predict prognosis in newly-diagnosed IBD patients, and represents a step towards personalised therapy.What is already known about this subjectThe course of CD and UC varies considerably between patients, but reliable prognostic markers are not available in clinical practice. This hinders disease management because treatment approaches that would be optimal for patients with indolent disease – characterised by infrequent flare-ups that can be readily controlled by first-line therapy – will inevitably undertreat those with progressive disease. Conversely, strategies that would appropriately control frequently-relapsing, progressive disease will expose patients with more quiescent disease to the risks and side effects of unnecessary treatment. We have previously described a CD8 T cell gene expression signature that corresponds to differences in T cell exhaustion, is detectable during active untreated disease (including at diagnosis), and predicts disease course in both UC and CD. However, the need for cell separation and microarray-based gene expression analysis would make this difficult to translate to clinical practice.What are the new findingsWe have developed, optimised, and independently validated a whole blood qPCR-based classifier – designed to identify the IBD1 and IBD2 patient subgroups – that can reliably predict prognosis in patients with CD or UC from diagnosis without the need for cell separation. We also present a detailed phenotypic update on the disease course experienced by patients in either the IBD1/IBDhi or IBD2/IBDlo subgroups, incorporating both expanded patient cohorts and substantially longer follow-up. This affords new insights into the spectrum of therapies that are differentially required in these patient subgroups, and reinforces their association with disease prognosis.How might it impact on clinical practice in the foreseeable future?The qPCR-based classifier has performance characteristics that compare favourably to prognostic …
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影响因子：
14.9
作者：
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作者：
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DOI：
--
发表时间：
2018
期刊：
Nature reviews: Gastroenterology & hepatology
影响因子：
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作者：
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