Host genetics of invasive Aspergillus and Candida infections.

Invasive candidiasis and aspergillosis are major complications in surgical and onco-hematological patients, and still associated with an important morbidity and mortality. A large number of studies highlighted the potential role of host genetic polymorphisms that may influence susceptibility to fungal pathogens, but many were limited by insufficient statistical power, problematic design, and/or lack of replication. However, some relevant polymorphisms are now emerging from well-conducted studies whose associations have been replicated and/or are supported by strong biological evidence. Such polymorphisms together with other biomarkers may play a role in the prediction, diagnosis, and management of severe fungal infections in high-risk patients in the coming years.

PTX3 Polymorphisms and Invasive Mold Infections After Solid Organ Transplant.

Donor PTX3 polymorphisms were shown to influence the risk of invasive aspergillosis among hematopoietic stem cell transplant recipients. Here, we show that PTX3 polymorphisms are independent risk factors for invasive mold infections among 1101 solid organ transplant recipients, thereby strengthening their role in mold infection pathogenesis and patients' risk stratification.

Prediction of multiple infections after severe burn trauma: a prospective cohort study.

OBJECTIVE: To develop predictive models for early triage of burn patients based on hypersusceptibility to repeated infections. BACKGROUND: Infection remains a major cause of mortality and morbidity after severe trauma, demanding new strategies to combat infections. Models for infection prediction are lacking. METHODS: Secondary analysis of 459 burn patients (≥16 years old) with 20% or more total body surface area burns recruited from 6 US burn centers. We compared blood transcriptomes with a 180-hour cutoff on the injury-to-transcriptome interval of 47 patients (≤1 infection episode) to those of 66 hypersusceptible patients [multiple (≥2) infection episodes (MIE)]. We used LASSO regression to select biomarkers and multivariate logistic regression to built models, accuracy of which were assessed by area under receiver operating characteristic curve (AUROC) and cross-validation. RESULTS: Three predictive models were developed using covariates of (1) clinical characteristics; (2) expression profiles of 14 genomic probes; (3) combining (1) and (2). The genomic and clinical models were highly predictive of MIE status [AUROCGenomic = 0.946 (95% CI: 0.906-0.986); AUROCClinical = 0.864 (CI: 0.794-0.933); AUROCGenomic/AUROCClinical P = 0.044]. Combined model has an increased AUROCCombined of 0.967 (CI: 0.940-0.993) compared with the individual models (AUROCCombined/AUROCClinical P = 0.0069). Hypersusceptible patients show early alterations in immune-related signaling pathways, epigenetic modulation, and chromatin remodeling. CONCLUSIONS: Early triage of burn patients more susceptible to infections can be made using clinical characteristics and/or genomic signatures. Genomic signature suggests new insights into the pathophysiology of hypersusceptibility to infection may lead to novel potential therapeutic or prophylactic targets.