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从机制角度定义肾小球疾病:在肾脏病学中实施整合生物学方法。

Defining Glomerular Disease in Mechanistic Terms: Implementing an Integrative Biology Approach in Nephrology.

作者信息

Mariani Laura H, Pendergraft William F, Kretzler Matthias

机构信息

Division of Nephrology, University of Michigan Medical Center, Ann Arbor, Michigan; and.

Division of Nephrology and Hypertension, Department of Medicine, University of North Carolina Kidney Center, Chapel Hill, North Carolina.

出版信息

Clin J Am Soc Nephrol. 2016 Nov 7;11(11):2054-2060. doi: 10.2215/CJN.13651215. Epub 2016 Sep 14.

Abstract

Advances in biomedical research allow for the capture of an unprecedented level of genetic, molecular, and clinical information from large patient cohorts, where the quest for precision medicine can be pursued. An overarching goal of precision medicine is to integrate the large-scale genetic and molecular data with deep phenotypic information to identify a new mechanistic disease classification. This classification can ideally be used to meet the clinical goal of the right medication for the right patient at the right time. Glomerular disease presents a formidable challenge for precision medicine. Patients present with similar signs and symptoms, which cross the current disease categories. The diseases are grouped by shared histopathologic features, but individual patients have dramatic variability in presentation, progression, and response to therapy, reflecting the underlying biologic heterogeneity within each glomerular disease category. Despite the clinical challenge, glomerular disease has several unique advantages to building multilayered datasets connecting genetic, molecular, and structural information needed to address the goals of precision medicine in this population. Kidney biopsy tissue, obtained during routine clinical care, provides a direct window into the molecular mechanisms active in the affected organ. In addition, urine is a biofluid ideally suited for repeated measurement from the diseased organ as a liquid biopsy with potential to reflect the dynamic state of renal tissue. In our review, current approaches for large-scale data generation and integration along the genotype-phenotype continuum in glomerular disease will be summarized. Several successful examples of this integrative biology approach within glomerular disease will be highlighted along with an outlook on how achieving a mechanistic disease classification could help to shape glomerular disease research and care in the future.

摘要

生物医学研究的进展使得从大型患者队列中获取前所未有的基因、分子和临床信息成为可能,从而推动了精准医学的发展。精准医学的一个总体目标是将大规模的基因和分子数据与深入的表型信息相结合,以确定一种新的疾病机制分类。理想情况下,这种分类可用于实现为合适的患者在合适的时间提供合适药物的临床目标。肾小球疾病对精准医学提出了巨大挑战。患者表现出相似的体征和症状,跨越了当前的疾病类别。这些疾病按共同的组织病理学特征分组,但个体患者在表现、进展和对治疗的反应方面存在显著差异,这反映了每个肾小球疾病类别中潜在的生物学异质性。尽管存在临床挑战,但肾小球疾病在构建多层数据集以连接实现该人群精准医学目标所需的基因、分子和结构信息方面具有几个独特优势。在常规临床护理过程中获取的肾活检组织为了解受影响器官中活跃的分子机制提供了直接窗口。此外,尿液是一种生物流体,非常适合作为液体活检从患病器官进行重复测量,有可能反映肾组织的动态状态。在我们的综述中,将总结目前在肾小球疾病中沿着基因型 - 表型连续体进行大规模数据生成和整合的方法。将重点介绍肾小球疾病中这种整合生物学方法的几个成功例子,并展望实现疾病机制分类如何有助于塑造未来的肾小球疾病研究和治疗。

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