The task is clear: we need better treatments for pulmonary fibrosis (PF). The two antifibrotic therapies licensed for idiopathic pulmonary fibrosis (IPF) have shown efficacy in other forms of PF but do not meet the needs of people living with PF; drugs that can halt or even reverse progression and, importantly, improve quality of life. Although a number of new potential therapies are now reaching late-stage clinical trials, the recent failure of three of these has been disheartening1 and highlights the need to dig deeper, and smarter, for new potential drug targets. Over the last 9 years, several studies have shown that drug targets with support from genetic association studies were more likely to be successful in clinical development than those without.2–4 This has prompted considerable interest and investment in the generation of genetic data by academia and industry. The supposition underpinning the success of genetically supported targets is that they represent dysregulation of mechanisms that are causal of disease, rather than processes that are the consequence of disease. This is because the genetic perturbations that implicate genes in risk of development of a disease are fixed in an individual at conception and are not altered by subsequent lifestyle choices or environmental factors. Genome-wide Association Studies (GWAS) for almost all complex …

中文翻译：

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特发性肺纤维化的原因或后果：使用遗传数据来支持正确的马


任务很明确：我们需要更好的肺纤维化（PF）治疗方法。获得许可用于治疗特发性肺纤维化 (IPF) 的两种抗纤维化疗法已在其他形式的 PF 中显示出疗效，但不能满足 PF 患者的需求；可以阻止甚至逆转病情进展的药物，更重要的是，可以改善生活质量。尽管许多新的潜在疗法现已进入后期临床试验，但其中三种疗法最近的失败令人沮丧1，并凸显需要更深入、更明智地挖掘新的潜在药物靶点。过去 9 年中，多项研究表明，有遗传关联研究支持的药物靶点比没有遗传关联研究支持的药物靶点更有可能在临床开发中取得成功。2-4 这引起了学术界对生成遗传数据的极大兴趣和投资和工业。支持基因支持靶标成功的假设是，它们代表了导致疾病的机制的失调，而不是疾病结果的过程。这是因为涉及疾病发展风险的基因的遗传扰动在受孕时就固定在个体中，并且不会因随后的生活方式选择或环境因素而改变。几乎所有复杂的全基因组关联研究（GWAS）......