Beyond the Granuloma: New Insights into Cardiac Sarcoidosis Using Spatial Proteomics

E. Peyster, David Smith, Therese Bittermann, Paco Bravo, Kenneth Margulies
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Abstract

Abstract Cardiac sarcoidosis is poorly understood, challenging to diagnose, and portends a poor prognosis. A lack of animal models necessitates the use of residual human samples to study sarcoidosis, which in turn necessitates the use of analytical tools compatible with archival, fixed tissue. We employed high-plex spatial protein analysis within a large cohort of archival human cardiac sarcoidosis and control tissue samples, studying the immunologic, fibrotic, and metabolic landscape of sarcoidosis at different stages of disease, in different cardiac tissue compartments, and in tissue regions with and without overt inflammation. Utilizing a small set of differentially expressed protein biomarkers, we also report the development of a predictive model capable of accurately discriminating between control cardiac tissue and sarcoidosis tissue, even when no histologic evidence of sarcoidosis is present. This finding has major translational implications, with the potential to markedly improve the diagnostic yield of clinical biopsies obtained from suspected sarcoidosis patients.
超越肉芽肿:利用空间蛋白质组学揭示心脏肉样瘤病的新奥秘
摘要 心脏肉样瘤病鲜为人知,诊断困难,预后不良。由于缺乏动物模型,因此必须使用残留的人体样本来研究肉样瘤病,这反过来又需要使用与档案固定组织兼容的分析工具。我们在一大批存档的人类心脏肉样瘤病和对照组织样本中采用了高倍空间蛋白质分析,研究了肉样瘤病在不同疾病阶段、不同心脏组织分区以及有明显炎症和无明显炎症组织区域的免疫、纤维化和代谢情况。我们还报告了利用少量差异表达的蛋白质生物标记物开发出的预测模型,该模型能够准确区分对照心脏组织和肉样瘤病组织,即使在没有肉样瘤病组织学证据的情况下也是如此。这一发现具有重大的转化意义,有可能显著提高疑似肉样瘤病患者临床活检的诊断率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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