Abstract
Genome-wide association studies (GWASs) in acute respiratory distress syndrome (ARDS) have been hampered by the heterogeneity of the clinical phenotypes and the large sample size requirement. As the limitations of these studies to uncover the complex genetic architecture of ARDS are evident, new approaches intended to reduce data complexity need to be applied. Intermediate phenotypes are mechanism-related manifestations of the disease, located closer to the genetic substrate than to disease phenotype, and therefore able to reflect more directly and more strongly the effect of causal genes. The dissection of complex phenotypes into less complex intermediate phenotypes is a valuable strategy to facilitate the discovery of those genetic variants whose effect is not strong enough to be detected as markers of disease in traditional GWASs. Genetic causal inference methodologies can be then applied to estimate the implication of the intermediate trait in the causal circuit between genes and disease. By following this strategy, platelet count, a relevant intermediate quantitative trait in ARDS, has been recently identified as a novel mediator in the genetic contribution to ARDS risk and mortality. The use of intermediate phenotypes and causal inference are emerging methodological and statistical strategies that can help to overcome the limitations of traditional GWASs in ARDS. Moreover, these approaches can provide evidence for the mechanisms linking genes to ARDS and help to prioritize therapeutic targets for the treatment of this devastating syndrome.
Keywords
ARDS - genetic epidemiology - intermediate phenotypes - platelet count - causal inference - biomarkers
