Genome-Wide Association Studies in Idiopathic Pulmonary Fibrosis: Bridging the Gap between Sequence and Consequence.
Genome-Wide Association Studies in Idiopathic Pulmonary Fibrosis: Bridging the Gap between Sequence and Consequence.
复制标题
特发性肺纤维化的全基因组关联研究:弥合序列和后果之间的差距。
DOI:
10.1164/rccm.201911-2286ed
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发表时间:
2020
影响因子:
24.7
通讯作者:
Kropski,JonathanA
中科院分区:
文献类型:
--
作者:
Spagnolo,Paolo;Kropski,JonathanA
Genome-wide association studies (GWASs) have been developed with the aim of improving our understanding of disease biology and discovering novel therapeutic targets through the identification of sequence variants associated with the disease or trait of interest across the genome of affected individuals (1). Since 2005, GWASs have identified several thousands of loci associated with hundreds of complex diseases (ie, those determined by variations across multiple genes, often interacting with environmental factors, and each contributing an effect of varying yet relatively modest magnitude). However, contrary to early expectations that GWASs would identify functional (ie, proteindisrupting) variants, z90% of GWAS loci linked to disease risk lie in noncoding regions of the genome. The functions of many such diseaseassociated risk variants have remained elusive, although it is generally presumed that these variants play cis-or trans-regulatory roles. Rapid, high-throughput approaches for defining the function of such regulatory variants are clearly needed to accelerate the translation of these genetic discoveries to disease-relevant biological understanding. Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and almost invariably fatal interstitial lung disease (ILD) of unknown origin that occurs primarily in older adults (2). Although the mechanisms of fibrosis in IPF remain incompletely understood, the disease is believed to result from aberrant repair of the alveolar epithelium after repetitive microinjuries, with smoking, viral infection, environmental pollutants, and chronic microaspiration of gastric content representing plausible putative triggers of the fibrotic response (3). Excessive unopposed extracellular matrix synthesis by myofibroblasts—cells that express features of both fibroblasts and smooth muscle cells—leads to progressive scarring of the lung, parenchymal distortion, and irreversible loss of function (4). The role of genetic factors in both familial and sporadic cases of IPF is increasingly appreciated (5). Specifically, familial studies have identified associations with genes related to telomere biology and surfactant production, whereas GWASs of sporadic cases, including high-resolution resequencing of implicated loci (6), have reported associations with loci containing genes related to lung defense, telomere maintenance, and cell–cell adhesion (7). However, these genetic abnormalities have been estimated to account for only z30% of the genetic risk of IPF, and the molecular mechanisms through which they promote disease development are largely unknown (8). In this issue of the Journal, Allen and colleagues (pp. 564–574) report findings from a collaborative effort to perform the largest GWAS of IPF susceptibility to date (9). The study population included all patients and control subjects of European ancestry who had been recruited to any previously reported IPF GWAS (10–12)(ie, 2,668 patients with IPF and 8,591 control subjects). The authors conducted a meta-analysis of the results of these GWASs (the discovery cohort). Two independent case/control datasets were included as a replication cohort (1,467 patients with IPF and 11,874 control subjects). The study confirmed associations at 11 previously reported loci, and conditional analyses confirmed that risk at the 11p15 locus is driven by the MUC5B promoter variant. Three novel association signals near KIF15 (in 3p21. 31), MAD1L1 (in 7p22. 3), and DEPTOR (DEP domain-containing mTOR-interacting protein)(in 8q24. 12) were also identified and remained significant after adjustment for multiplicity, and were replicated in all of the discovery and replication datasets. Using three …