Profiling of serum factors associated with skin and soft tissue infections as a foundation for biomarker identification.

Background: People living in close quarters, such as military trainees, are at increased risk for skin and soft tissue infections (SSTI), especially those caused by methicillin-resistant (MRSA). The serum immune factors associated with the onset of SSTI are not well understood.

Methods: We conducted a longitudinal study of SSTIs, enrolling US Army trainees before starting military training and following up for 14 weeks. Samples were collected on Day 0, 56, and 90. Serum chemokines and cytokines among 16 SSTI cases and 51 healthy controls were evaluated using an electro-chemiluminescence based multiplex assay platform.

Results: Of 54 tested cytokines, 12 were significantly higher among SSTI cases as compared to controls. Among the cases, there were correlations between factors associated with vascular injury (i.e., VCAM-1, ICAM-1, and Flt1), the angiogenetic factor VEGF, and IL-10. Unsupervised machine learning (Principal Component Analysis) revealed that IL10, IL17A, C-reactive protein, ICAM1, VCAM1, SAA, Flt1, and VGEF were indicative of SSTI.

Conclusion: The study demonstrates the power of immunoprofiling for identifying factors predictive of pre-illness state of SSTI thereby identifying early stages of an infection and individuals susceptible to SSTI.