Interrogating ARDS Risk and Severity Utilizing Genomic and Systems Biology Approaches

Abstract

Introduction: 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 include 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. The current ARDS definition relies on clinical characteristics that fail to capture the diversity of disease pathology, severity, and mortality risk. Methods: A systems biology approach utilizing a variety of cellular and molecular biology techniques, genetic and genomic data, and data analysis was performed to examine i) novel candidate genes in ARDS (an agnostic approach) and ii) known candidate genes associated with key areas of lung injury pathology. I undertook a comprehensive survey of the available ARDS literature to identify genes and genetic variants (candidate gene and limited GWAS 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. I further attempted to address the well-known health disparities that exist in susceptibility to and mortality from ARDS by utilizing a genetic risk score incorporating both genetic risk SNPs and plasma protein biomarkers in NAMPT (a known candidate gene previously associated with ARDS risk). I extended the exploration of genomics in ARDS by performing the first genome-wide methylation study focused on ARDS mortality. I validated the individual CpG sites, islands, and pathways from this study. Results: Bioinformatic analyses identified 201 ARDS candidate genes with pathway analysis indicating a strong predominance in key evolutionarily-conserved inflammatory pathways including reactive oxygen species (ROS), innate immunity-related inflammation, and endothelial vascular signaling pathways. The rs61330082 was significantly associated with risk of ARDS mortality (p=0.036). The rs61330082 GA genotype was associated with lower mortality risk in an adjusted logistic regression model (OR=0.46 [0.24, 0.88], p=0.019) and was linked to lower NAMPT promoter activity in response to either lipopolysaccharide (LPS) challenge (p<0.001) or to combined LPS/18% cyclic stretch exposure (p<0.001). An additive rs61330082 genetic model was associated with lower APACHE II scores (p=0.012), and rs61330082 AA was associated with APAHCE II score in an adjusted linear model [β=-26.85[-48.81, -4.90], p=0.017). Higher eNAMPT levels were also associated with higher APACHE II scores (p<0.001). The NAMPT haplotype rs61330082/rs59744560 A/C was also associated with lowered plasma eNAMPT levels (β=-9.25 ng/mL [-17.76, -0.73], p=0.033). A mortality risk score utilizing NAMPT haplotype risk, eNAMPT plasma levels, and covariates (AUC: 0.645 [0.567, 0.722]) significantly predicted ARDS mortality across the cohort after adjustment for age, gender, and race (p=0.002). We identified 15 CpG sites in a mortality-based ARDS outcome pilot study (p<0.05 after FDR multiple testing correction, n=22 survived, n=23 deceased) that were hyper-methylated in ARDS patients with more severe outcomes (28-day based mortality). Pathway-based expression analysis discovered the c-MET pathway as being significant in ARDS severity outcomes. Conclusion: A systems biology approach allowed for the synthesis of novel and candidate genes associated with ARDS to be incorporated into my studies of ARDS. I have established a novel genotype-phenotype relationship between NAMPT SNPs, eNAMPT levels, and mortality in ARDS. This mortality risk score may have utility in integrating genotype-phenotype data of high-risk subjects for clinical trial stratification.