Genomic and Genetic Approaches to Deciphering Acute Respiratory Distress Syndrome Risk and Mortality

Abstract

Significance: Acute respiratory distress syndrome (ARDS) is a severe, highly heterogeneous critical illness with staggering mortality that is influenced by environmental factors, such as mechanical ventilation, and genetic factors. Significant unmet needs in ARDS are addressing the paucity of validated predictive biomarkers for ARDS risk and susceptibility that hamper the conduct of successful clinical trials in ARDS and the complete absence of novel disease-modifying therapeutic strategies. Recent Advances: The current ARDS definition relies on clinical characteristics that fail to capture the diversity of disease pathology, severity, and mortality risk. We undertook a comprehensive survey of the available ARDS literature to identify genes and genetic variants (candidate gene and limited genome-wide association study approaches) implicated in susceptibility to developing ARDS in hopes of uncovering novel biomarkers for ARDS risk and mortality and potentially novel therapeutic targets in ARDS. We further attempted to address the well-known health disparities that exist in susceptibility to and mortality from ARDS. Critical Issues: Bioinformatic analyses identified 201 ARDS candidate genes with pathway analysis indicating a strong predominance in key evolutionarily conserved inflammatory pathways, including reactive oxygen species, innate immunity-related inflammation, and endothelial vascular signaling pathways. Future Directions: Future studies employing a system biology approach that combines clinical characteristics, genomics, transcriptomics, and proteomics may allow for a better definition of biologically relevant pathways and genotype-phenotype connections and result in improved strategies for the sub-phenotyping of diverse ARDS patients via molecular signatures. These efforts should facilitate the potential for successful clinical trials in ARDS and yield a better fundamental understanding of ARDS pathobiology.

Keywords: ARDS mortality; acute respiratory distress syndrome (ARDS); candidate gene studies; genome-wide association studies (GWAS); inflammation; pathway analysis; reactive oxygen species (ROS).

FIG. 1.

Schema of the overlapping syndromes and complications in the critically ill. Depicted are the major causes of critical care illnesses and associated complications that contribute to the staggering morbidity, mortality, and health care costs in the critically ill.

FIG. 2.

ARDS causes. An adaptation of the summary of Cochi et al. data from 15 years of ARDS comorbidity data (1999–2013) that identified four major comorbidities that occur with ARDS (49). ARDS, acute respiratory distress syndrome.

FIG. 3.

A timeline of ARDS clinical and genetic contributions. A selection of clinical contributions for ARDS (bottom) and genetic contributions to the ARDS literature (top). The relative recent history of genetic contributions to the ARDS literature should be noted compared with a much long history of clinical contributions to treatment. Clinical and genetic timelines adapted from Laffey et al. and Reilly et al. (107, 149).

FIG. 4.

ARDS gene table and top pathways. Two hundred one genes identified through differential gene expression (mRNA sequencing, mRNA CHIP array, RNA microarray, proteomics, candidate gene sequencing, or GWAS) that mapped onto either the Reactome or Wikipathways databases for pathway analysis (5359 human pathways covered). The second, third and fourth columns reflect the number of citations for each gene (14). Four broad categories of enriched pathways (immunological signaling, ROS-related signaling, vascular signaling, and transcription factor-related pathways) and the number or genes represented in each (p < 0.01, five members minimum per pathway). GWAS, genome-wide association study; ROS, reactive oxygen species.

FIG. 5.

Heatmap of PBMC gene expression predicting ARDS susceptibility and ARDS mortality. (A) The 33 top genes identified in a molecular survival signature from PBMC mRNA in ARDS patients (n = 23) versus controls (n = 80, PMID:19222302). Nineteen genes are downregulated, and 14 are upregulated (Fold change >2 ± 4.41, p < 7.26e-23). (B) 22 genes in the ROS pathway were predictive of ARDS survival in ARDS patients. Five of these genes are upregulated, and 17 are downregulated (24). PBMC, peripheral blood mononuclear cell.

FIG. 6.

Inflammation pathways. Using the entirety of 201 genes identified by our eGWAS approach, we identified the top five enriched inflammation pathways: neutrophils, cytokine signaling, immune system, innate immune system, leukocytes. Shown are the individual genes in each pathway with significant overlap. eGWAS, expression genome-wide association study.

FIG. 7.

Five interleukin-associated signaling-specific pathways. (IL-10 signaling, IL-4 and IL-13 signaling, development of the ILC family, IL-1 signaling, leukocytes) and the genes that overlap. IL, interleukin.

FIG. 8.

Genes represented in top enriched endothelial vascular pathways. Shown are the top six cardiovascular signaling pathways and the number of genes in each pathway: Hemostasis, VEGFA-VEGFR2, MAPK signaling, PI3K-Akt signaling, AGE-RAGE. RAGE, receptor of advanced glycation end products; MAPK, mitogen-activated protein kinase; VEGF, vascular endothelial growth factor.

FIG. 9.

Platelet and coagulation pathways. Fourteen genes are shared among the top four enriched platelet and coagulation pathways.

FIG. 10.

Risk genes in African descent and Hispanic ethnicity. Depicted are the seven top risk single nucleotide polymorphisms/genes that are unique to ARDS risk in African descent individuals and to ARDS survival. The genes were identified via interrogation of GWAS results (HEATR1, SELPLG) or via candidate gene approaches and sequencing (S1PR3, MYLK, DIO2, GADD45a). DIO2, iodothyronine deiodinase 2; GADD45a, growth arrest and DNA damage-inducible gene; MYLK, myosin light chain kinase; S1Ps, sphingosine 1-phosphate receptors.