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
