PLoS ONE (Jan 2024)

Phenome-wide association study identifies new clinical phenotypes associated with Staphylococcus aureus infections.

  • Patrick Allaire,
  • Noha S Elsayed,
  • Richard L Berg,
  • Warren Rose,
  • Sanjay K Shukla

DOI
https://doi.org/10.1371/journal.pone.0303395
Journal volume & issue
Vol. 19, no. 7
p. e0303395

Abstract

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BackgroundPhenome-Wide Association study (PheWAS) is a powerful tool designed to systematically screen clinical observations derived from medical records (phenotypes) for association with a variable of interest. Despite their usefulness, no systematic screening of phenotypes associated with Staphylococcus aureus infections (SAIs) has been done leaving potential novel risk factors or complications undiscovered.Method and cohortsWe tailored the PheWAS approach into a two-stage screening procedure to identify novel phenotypes correlating with SAIs. The first stage screened for co-occurrence of SAIs with other phenotypes within medical records. In the second stage, significant findings were examined for the correlations between their age of onset with that of SAIs. The PheWAS was implemented using the medical records of 754,401 patients from the Marshfield Clinic Health System. Any novel associations discovered were subsequently validated using datasets from TriNetX and All of Us, encompassing 109,884,571 and 118,538 patients respectively.ResultsForty-one phenotypes met the significance criteria of a p-value 5. Out of these, we classified 23 associations either as risk factors or as complications of SAIs. Three novel associations were discovered and classified either as a risk (long-term use of aspirin) or complications (iron deficiency anemia and anemia of chronic disease). All novel associations were replicated in the TriNetX cohort. In the All of Us cohort, anemia of chronic disease was replicated according to our significance criteria.ConclusionsThe PheWAS of SAIs expands our understanding of SAIs interacting phenotypes. Additionally, the novel two-stage PheWAS approach developed in this study can be applied to examine other disease-disease interactions of interest. Due to the possibility of bias inherent in observational data, the findings of this study require further investigation.