Novel biomarker combination improves the diagnosis of serious bacterial infections in Malawian children
1 Department of Women’s and Children’s Health, University of Liverpool, Liverpool, UK
2 Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi
3 Centre for Integrated Medical Genomic Research, University of Manchester, Manchester, UK
4 Department of Biostatistics, University of Liverpool, Liverpool, UK
5 Health Protection Agency North West, Manchester Medical Microbiology Partnership, Manchester, UK
6 Department of Paediatrics, University of Malawi College of Medicine, Blantyre, Malawi
7 Institute of Child Health, University of Liverpool, Alder Hey Children’s NHS Foundation Trust, Eaton Road, Liverpool, L12 2AP, UK
BMC Medical Genomics 2012, 5:13 doi:10.1186/1755-8794-5-13Published: 4 May 2012
High throughput technologies offer insight into disease processes and heightens opportunities for improved diagnostics. Using transcriptomic analyses, we aimed to discover and to evaluate the clinical validity of a combination of reliable and functionally important biomarkers of serious bacterial infection (SBI).
We identified three previously reported biomarkers of infection (neutrophil gelatinase-associated lipocalin (NGAL), granulysin and resistin) and measured gene expression using quantitative real-time PCR. Protein products related to the three transcripts were measured by immunoassays.
Relative gene expression values of NGAL and resistin were significantly increased, and expression of granulysin significantly decreased in cases compared to controls. Plasma concentrations of NGAL and resistin were significantly increased in children with confirmed SBI compared to children with no detectable bacterial infection (NBI), and to controls (287 versus 128 versus 62 ng/ml and 195 versus 90 versus 18 ng/ml, respectively, p < 0.05). Plasma protein concentrations of NGAL and resistin were significantly increased in non-survivors compared to survivors (306 versus 211 and 214 versus 150 ng/ml, p = 0.02). The respective areas under the curve (AUC) for NGAL, resistin and procalcitonin in predicting SBI were 0.79, 0.80 and 0.86, whilst a combination of NGAL, resistin and procalcitonin achieved an AUC of 0.90.
We have demonstrated a unique combination of diagnostic biomarkers of SBI using transcriptomics, and demonstrated translational concordance with the corresponding protein. The addition of NGAL and resistin protein measurement to procalcitonin significantly improved the diagnosis of SBI.