Derivation of a metabolic signature associated with bacterial meningitis in infants

Abstract

Background:Diagnosis of bacterial meningitis (BM) is challenging in newborn infants. Presently, biomarkers of BM have limited diagnostic accuracy. Analysis of cerebrospinal fluid (CSF) metabolites may be a useful diagnostic tool in BM.Methods:In a nested case-control study, we examined over 400 metabolites in CSF of uninfected infants and infants with culture-confirmed BM using gas- and liquid-chromatography mass spectrometry. Preterm and full-term infants in a Level III or IV Neonatal Intensive Care Unit were prospectively enrolled when evaluated for serious bacterial infection.Results:Over 200 CSF metabolites significantly differed in uninfected infants and infants with BM. Using machine-learning, we found as few as 6 metabolites distinguished infants with BM from uninfected infants in this pilot cohort. Further analysis demonstrated 3 metabolites associated with Group B Streptococcal meningitis.Conclusions:We report the first comprehensive metabolic analysis of CSF in infants with BM. In our pilot cohort, we derived a metabolic signature that predicted the presence or absence of BM, irrespective of gestational age, postnatal age, sex, race and ethnicity, presence of neurosurgical hardware, white blood cell count in CSF, and red blood cell contamination in CSF. Metabolic analysis may aid diagnosis of BM and facilitate clinical decision-making in infants.