Abstract
Abstract
Background
Acute respiratory distress syndrome (ARDS) is a complex, heterogeneous, and deadly condition often resulting from pulmonary lesions due to sepsis, among other causes. There is a lack of targeted therapies to specifically treat the patients. Common genetic factors in the population (frequency > 1%) have been associated with ARDS susceptibility, but systematic genetic screens of the role of rare genetic variants are lacking. We used the network of known molecular interactions to identify ARDS risks from clusters of biologically related genes containing qualifying variants (QVs) with frequency
Methods
We conducted whole-exome sequencing in sepsis patients from the GEN-SEP cohort (
n
= 822, of which 272 developed ARDS). A network-based heterogeneity clustering algorithm was used to discover significant gene clusters (
p
–5
). Gene-set enrichment analysis and logistic regression models aggregating QVs were used for cross-verification to confirm consistency and deepen understanding of the effect sizes of gene clusters.
Results
We identified 19 significant clusters (
p
lowest
= 3.29 × 10
–10
), each containing an average of 102 genes (11.6% mean similarity). QVs in nine gene clusters were associated with sepsis-associated ARDS (
p
lowest
= 1 × 10
–5
) but were not associated with 28-day survival. Clusters were enriched in several biological pathways, notably the
Toll-like receptor cascades
.
Conclusions
These results support a marked genetic heterogeneity underlying ARDS susceptibility and the presence of rare risk variants involving multiple biological processes that are associated with sepsis outcomes. Particularly, they underscore the importance of rare variants in genes of the
Toll-like receptor cascades
in the risk for sepsis-associated ARDS.