Identification of new biomarkers for Acute Respiratory Distress Syndrome by expression-based genome-wide association study

BMC Pulmonary Medicine

Shui Q. Ye¹  Li Qin Zhang²  Daniel P. Heruth²  Suman Chaudhary²  Dilyara I. Cheranova²  Dmitry N. Grigoryev³ 

[1] Department of Biomedical and Health Informatics, University of Missouri Kansas City School of Medicine, Kansas City, MO, USA;Division of Experimental and Translational Genetics, Department of Pediatrics, Children’s Mercy Hospitals and Clinics, Kansas City, MO, USA;Laboratory of Translational Studies and Personalized Medicine, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow Region, Russian Federation

关键词: Genomics;    Microarray;    Biomarkers;    Gene expression;    Acute respiratory distress syndrome;    Expression-based genome-wide association studies;   

Others  :  1222538
DOI  :  10.1186/s12890-015-0088-x

 received in 2015-02-06, accepted in 2015-07-31,  发布年份 2015

【 摘 要 】

Background

Accumulated to-date gene microarray data on Acute Respiratory Distress Syndrome (ARDS) in the Gene Expression Omnibus (GEO) represent a rich source for identifying new unsuspected targets and mechanisms of ARDS. The recently developed expression-based genome-wide association study (eGWAS) for analysis of GEO data was successfully used for analysis of gene expression of comparatively noncomplex adipose tissue, 75 % of which is represented by adipocytes. Although lung tissue is more heterogenic and does not possess a prevalent cell type for driving gene expression patterns, we hypothesized that eGWAS of ARDS samples will generate biologically meaningful results.

Methods

The eGWAS was conducted according to (Proc Natl Acad Sci U S A 109:7049-7054, 2012) and genes were ranked according to p values of chi-square test.

Results

The search of GEO retrieved 487 ARDS related entries. These entries were filtered for multiple qualitative and quantitative conditions and 219 samples were selected: mouse n_sham/ARDS  = 67/92, rat n = 13/13, human cells n = 11/11, canine n = 6/6 with the following ARDS model distributions: mechanical ventilation (MV)/cyclic stretch n = 11; endotoxin (LPS) treatment n = 8; MV + LPS n = 3; distant organ injury induced ARDS n = 3; chemically induced ARDS n = 2; Staphylococcus aureus induced ARDS n = 2; and one experiment each for radiation and shock induced ARDS. The eGWAS of this dataset identified 42 significant (Bonferroni threshold P < 1.55 × 10 ⁻⁶ ) genes. 66.6 % of these genes, were associated previously with lung injury and include the well known ARDS genes such as IL1R2 (P = 4.42 × 10 ⁻¹⁹ ), IL1β (P = 3.38 × 10 ⁻¹⁷ ), PAI1 (P = 9.59 × 10 ⁻¹⁴ ), IL6 (P = 3.57 × 10 ⁻¹² ), SOCS3 (P = 1.05 × 10 ⁻¹⁰ ), and THBS1 (P = 2.01 × 10 ⁻⁹ ). The remaining genes were new ARDS candidates. Expression of the most prominently upregulated genes, CLEC4E (P = 4.46 × 10 ⁻¹⁴ ) and CD300LF (P = 2.31 × 10 ⁻¹⁶ ), was confirmed by real time PCR. The former was also validated by in silico pathway analysis and the latter by Western blot analysis.

Conclusions

Our first in the field application of eGWAS in ARDS and utilization of more than 120 publicly available microarray samples of ARDS not only justified applicability of eGWAS to complex lung tissue, but also discovered 14 new candidate genes which associated with ARDS. Detailed studies of these new candidates might lead to identification of unsuspected evolutionarily conserved mechanisms triggered by ARDS.

【 授权许可】

   
2015 Grigoryev et al.

【 图 表 】

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