Tensions in Taxonomies: Current Understanding and Future Directions in the Pathobiologic Basis and Treatment of Group 1 and Group 3 Pulmonary Hypertension.
Tensions in Taxonomies: Current Understanding and Future Directions in the Pathobiologic Basis and Treatment of Group 1 and Group 3 Pulmonary Hypertension.
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DOI：
10.1002/cphy.c220010
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发表时间：
2023-01-30
影响因子：
5.8
通讯作者：
Stenmark, Kurt R.
中科院分区：
文献类型：
--
作者：
Gu, Sue;Goel, Khushboo;Forbes, Lindsay M.;Kheyfets, Vitaly O.;Yu, Yen-rei A.;Tuder, Rubin M.;Stenmark, Kurt R.
自认识肺动脉高压（PH）以来的 100 多年来，对该疾病的病理生理学及其治疗的认识取得了巨大进展并取得了重大成就。这些进展主要集中在特发性肺动脉高压 (IPAH) 方面，在 1998 年第二届世界肺动脉高压研讨会上，其被归类为第 1 类肺动脉高压 (PH)。然而，由于慢性肺病引起的 PH（被归类为第 3 类 PH）的病理学仍然知之甚少，因此其治疗方法仍然有限。我们回顾了 PH 的五组分类的历史，旨在对 1 组 PH 和 3 组 PH 发病机制的理解提供最先进的综述，包括从新颖的高通量组学技术中获得的见解，这些技术揭示了这些类别内的异质性以及它们之间的相似性。需要利用在了解 PAH 的基因组学、表观基因组学、蛋白质组学和代谢组学方面取得的实质性成果来了解 PH 复杂、异质疾病的全谱。在仔细考虑这些技术的强大优势以及局限性和缺陷后，多模态组学数据以及有监督和公正的机器学习方法可以实现更早的诊断、更精确的风险分层、更好的疾病反应预测、肺动脉高压类型内的新亚表型分组，以及确定多环芳烃和其他类型肺动脉高压之间的共享途径，从而产生新的治疗目标。
In the over 100 years since the recognition of pulmonary hypertension (PH), immense progress and significant achievements have been made with regard to understanding the pathophysiology of the disease and its treatment. These advances have been mostly in idiopathic pulmonary arterial hypertension (IPAH), which was classified as Group 1 Pulmonary Hypertension (PH) at the Second World Symposia on PH in 1998. However, the pathobiology of PH due to chronic lung disease, classified as Group 3 PH, remains poorly understood and its treatments thus remain limited. We review the history of the classification of the five groups of PH and aim to provide a state-of-the-art review of the understanding of the pathogenesis of Group 1 PH and Group 3 PH including insights gained from novel high-throughput omics technologies that have revealed heterogeneities within these categories as well as similarities between them. Leveraging the substantial gains made in understanding the genomics, epigenomics, proteomics, and metabolomics of PAH to understand the full spectrum of the complex, heterogeneous disease of PH is needed. Multimodal omics data as well as supervised and unbiased machine learning approaches after careful consideration of the powerful advantages as well as of the limitations and pitfalls of these technologies could lead to earlier diagnosis, more precise risk stratification, better predictions of disease response, new sub-phenotype groupings within types of PH, and identification of shared pathways between PAH and other types of PH that could lead to new treatment targets.
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影响因子：
37.8
作者：
Abdul-Salam, Vahitha B.;Wharton, John;Wilkins, Martin R.
通讯作者：
Wilkins, Martin R.
DOI：
10.1164/rccm.201003-0491oc
发表时间：
2010-11-01
影响因子：
24.7
作者：
Aldred, Micheala A.;Comhair, Suzy A.;Coldren, Christopher D.
通讯作者：
Coldren, Christopher D.
影响因子：
9.6
作者：
Benza, Raymond L.;Gomberg-Maitland, Mardi;Frantz, Robert P.
通讯作者：
Frantz, Robert P.
影响因子：
20.1
作者：
Brittain, Evan L.;Hemnes, Anna R.
通讯作者：
Hemnes, Anna R.
影响因子：
5.5
作者：
Bailey, Damian M.;Dehnert, Christoph;Berger, Marc M.
通讯作者：
Berger, Marc M.