A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases.
A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases.
复制标题
DOI：
10.1371/journal.pgen.1010825
复制
发表时间：
2023-07
期刊：
影响因子：
4.5
通讯作者：
中科院分区：
文献类型：
--
作者：
发现与疾病相关的组织和细胞类型可以促进功能基因和变异的识别和研究。特别是，细胞类型比例可以作为潜在的疾病预测生物标记物。在这篇手稿中，我们介绍了一个新的统计框架，细胞类型广泛关联研究(CWAS)，它整合了基因数据和转录数据，以确定其基因调控比例(GRP)与疾病/性状相关的细胞类型。在模拟和真实的GWA数据上，CWAs显示了良好的统计能力，与新发现的疾病相关组织中显著的GRP关联。更具体地说，肺组织内皮细胞和肌成纤维细胞的GRP分别与特发性肺纤维化和慢性阻塞性肺疾病相关。对于乳腺癌，血CD8+T细胞的GRP与乳腺癌的风险和生存呈负相关。总体而言，CWAS是一个强大的工具，可以揭示与GRPs介导的复杂疾病相关的细胞类型。细胞类型比例，如T细胞比例，已被发现是潜在的疾病进展指标，特别是对癌症患者。然而，细胞类型比例的变化可能是由于疾病状态，因此很难知道这些变化的比例是由于疾病进展还是由于疾病状态的原因。然而，细胞类型比例的遗传成分可能有助于识别导致不同疾病状态的细胞类型比例。在这里，我们介绍了一种新的统计框架，细胞类型广泛关联研究(CWAS)，它将遗传数据与转录数据相结合，以识别其基因调控比例(GRP)与疾病/性状相关的细胞类型。在模拟数据中，CWA在识别疾病相关细胞类型与良好控制的I型错误率方面显示出很高的统计能力。将CWAS应用于乳腺癌数据，我们发现血中CD8+T细胞可能是乳腺癌的保护因素，即CD8+T细胞比例高导致乳腺癌风险较低，预后较好。总体而言，CWAs是一个强大的工具，有助于识别与疾病相关的细胞类型比例，并可能有助于临床研究和实践。
Finding disease-relevant tissues and cell types can facilitate the identification and investigation of functional genes and variants. In particular, cell type proportions can serve as potential disease predictive biomarkers. In this manuscript, we introduce a novel statistical framework, cell-type Wide Association Study (cWAS), that integrates genetic data with transcriptomics data to identify cell types whose genetically regulated proportions (GRPs) are disease/trait-associated. On simulated and real GWAS data, cWAS showed good statistical power with newly identified significant GRP associations in disease-associated tissues. More specifically, GRPs of endothelial and myofibroblasts in lung tissue were associated with Idiopathic Pulmonary Fibrosis and Chronic Obstructive Pulmonary Disease, respectively. For breast cancer, the GRP of blood CD8+ T cells was negatively associated with breast cancer (BC) risk as well as survival. Overall, cWAS is a powerful tool to reveal cell types associated with complex diseases mediated by GRPs. Cell type proportions such as T cell proportions have been found to be potential disease progression indicator especially for cancer patients. However, cell type proportion changes can result from disease status, thus making it difficult to know whether those changed proportions are due to disease progression or the cause of disease status. Genetic components of cell type proportions, however, can potentially help to identify cell type proportions leading to different disease statuses. Here we introduce a novel statistical framework, cell-type Wide Association Study (cWAS), that integrates genetic data with transcriptomics data to identify cell types whose genetically regulated proportions (GRPs) are disease/trait-associated. In simulated data, cWAS showed a high statistical power in identifying disease-associated cell type associations with a well-controlled type-I error rate. Applying cWAS to breast cancer data, we found that blood CD8+ T cells may serve as the protective factor against breast cancer, i.e. high CD8+ T cell proportions lead to lower breast cancer risks and better prognostic condition. Overall, cWAS is a powerful tool to help identify disease-associated cell type proportions and potentially help in clinical research and practices.
登录
查看更多内容
影响因子：
3.7
作者：
Gustafsson J;Held F;Robinson JL;Björnson E;Jörnsten R;Nielsen J
通讯作者：
Nielsen J
DOI：
10.1007/978-3-319-68483-3_4
发表时间：
2018
期刊：
Advances in anatomy, embryology, and cell biology
影响因子：
--
作者：
Chambers E;Rounds S;Lu Q
通讯作者：
Lu Q
影响因子：
64.8
作者：
Bycroft C;Freeman C;Petkova D;Band G;Elliott LT;Sharp K;Motyer A;Vukcevic D;Delaneau O;O'Connell J;Cortes A;Welsh S;Young A;Effingham M;McVean G;Leslie S;Allen N;Donnelly P;Marchini J
通讯作者：
Marchini J
影响因子：
9.3
作者：
Baron M;Veres A;Wolock SL;Faust AL;Gaujoux R;Vetere A;Ryu JH;Wagner BK;Shen-Orr SS;Klein AM;Melton DA;Yanai I
通讯作者：
Yanai I
影响因子：
6.8
作者：
Tansey KE;Hill MJ
通讯作者：
Hill MJ