Distinct COPD subtypes in former smokers revealed by gene network perturbation analysis.
Distinct COPD subtypes in former smokers revealed by gene network perturbation analysis.
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DOI：
10.1186/s12931-023-02316-6
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发表时间：
2023-01-25
影响因子：
5.8
通讯作者：
中科院分区：
文献类型：
--
作者：
慢性阻塞性肺疾病（COPD）在症状和生理表现上差异显著。从容易获得的血液样本中收集的分子数据中识别疾病亚型，可以帮助对患者进行分层，并指导疾病管理和治疗。使用网络扰动分析方法分析COPD基因研究中通过RNA测序测量的血液基因表达。将每个COPD样本与学习的参考基因网络进行比较，以确定失调的部分。基因失调值用于聚类疾病样品。该发现集包括来自COPDGene的617名前吸烟者。四个不同的基因网络亚型被确定为在症状、运动能力和死亡率方面具有显著差异。这些聚类不一定与肺功能损害的水平相对应，并且在两个外部队列中独立验证：来自COPDGene的769名前吸烟者和多种族动脉粥样硬化研究（梅萨）中的431名前吸烟者。此外，我们确定了几个在这些亚型中显著失调的基因，包括DSP和GSTM 1，这些基因以前通过全基因组关联研究（GWAS）与COPD相关。所确定的亚型在死亡率及其临床和功能特征方面有所不同，这强调了可能通过选定的基因表达标志物进行补充的多维评估的必要性。各队列的亚型一致，可用于新患者分层和疾病预后。在线版本包含补充材料，可通过10.1186/s12931-023-02316-6获得。
Chronic obstructive pulmonary disease (COPD) varies significantly in symptomatic and physiologic presentation. Identifying disease subtypes from molecular data, collected from easily accessible blood samples, can help stratify patients and guide disease management and treatment. Blood gene expression measured by RNA-sequencing in the COPDGene Study was analyzed using a network perturbation analysis method. Each COPD sample was compared against a learned reference gene network to determine the part that is deregulated. Gene deregulation values were used to cluster the disease samples. The discovery set included 617 former smokers from COPDGene. Four distinct gene network subtypes are identified with significant differences in symptoms, exercise capacity and mortality. These clusters do not necessarily correspond with the levels of lung function impairment and are independently validated in two external cohorts: 769 former smokers from COPDGene and 431 former smokers in the Multi-Ethnic Study of Atherosclerosis (MESA). Additionally, we identify several genes that are significantly deregulated across these subtypes, including DSP and GSTM1, which have been previously associated with COPD through genome-wide association study (GWAS). The identified subtypes differ in mortality and in their clinical and functional characteristics, underlining the need for multi-dimensional assessment potentially supplemented by selected markers of gene expression. The subtypes were consistent across cohorts and could be used for new patient stratification and disease prognosis. The online version contains supplementary material available at 10.1186/s12931-023-02316-6.
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DOI：
10.2147/copd.s184424
发表时间：
2018-01-01
影响因子：
2.8
作者：
Johnson, Kate M.;Safari, Abdollah;Sadatsafavi, Mohsen
通讯作者：
Sadatsafavi, Mohsen
影响因子：
10
作者：
Castaldi, Peter J.;Benet, Marta;Garcia-Aymerich, Judith
通讯作者：
Garcia-Aymerich, Judith
DOI：
10.1164/rccm.201509-1863oc
发表时间：
2016-05-15
影响因子：
24.7
作者：
Mathai, Susan K.;Pedersen, Brent S.;Schwartz, David A.
通讯作者：
Schwartz, David A.
影响因子：
5.8
作者：
Kim, Woori;Cho, Michael H.;Beaty, Terri H.
通讯作者：
Beaty, Terri H.
影响因子：
30.8
作者：
Hobbs BD;de Jong K;Lamontagne M;Bossé Y;Shrine N;Artigas MS;Wain LV;Hall IP;Jackson VE;Wyss AB;London SJ;North KE;Franceschini N;Strachan DP;Beaty TH;Hokanson JE;Crapo JD;Castaldi PJ;Chase RP;Bartz TM;Heckbert SR;Psaty BM;Gharib SA;Zanen P;Lammers JW;Oudkerk M;Groen HJ;Locantore N;Tal-Singer R;Rennard SI;Vestbo J;Timens W;Paré PD;Latourelle JC;Dupuis J;O'Connor GT;Wilk JB;Kim WJ;Lee MK;Oh YM;Vonk JM;de Koning HJ;Leng S;Belinsky SA;Tesfaigzi Y;Manichaikul A;Wang XQ;Rich SS;Barr RG;Sparrow D;Litonjua AA;Bakke P;Gulsvik A;Lahousse L;Brusselle GG;Stricker BH;Uitterlinden AG;Ampleford EJ;Bleecker ER;Woodruff PG;Meyers DA;Qiao D;Lomas DA;Yim JJ;Kim DK;Hawrylkiewicz I;Sliwinski P;Hardin M;Fingerlin TE;Schwartz DA;Postma DS;MacNee W;Tobin MD;Silverman EK;Boezen HM;Cho MH;COPDGene Investigators;ECLIPSE Investigators;LifeLines Investigators;SPIROMICS Research Group;International COPD Genetics Network Investigators;UK BiLEVE Investigators;International COPD Genetics Consortium
通讯作者：
International COPD Genetics Consortium