Identification of candidate serum biomarkers of childhood-onset growth hormone deficiency using SWATH-MS and feature selection.
Journal:
Journal of proteomics
Published Date:
Mar 20, 2018
Abstract
UNLABELLED: A typical clinical manifestation of growth hormone deficiency (GHD) is a short stature resulting from delayed growth, but GHD affects bone health, cardiovascular function and metabolic profile and therefore quality of life. Although early GH treatment during childhood has been shown to improve outcomes, no single biochemical parameter is currently available for the accurate diagnosis of GHD in children. There is hence a need for non-invasive biomarkers. In this study, the relative abundance of serum proteins from GHD children and healthy controls was measured by next-generation proteomics SWATH-MS technology. The data generated was analysed by machine-learning feature-selection algorithms in order to discover the minimum number of protein biomarkers that best discriminate between both groups. The analysis of serum proteins by a SWATH-MS approach yielded a useful method for discovering potential biomarkers of GHD in children. A total of 263 proteins were confidently detected and quantified in each sample. Pathway analysis indicated an effect on tissue/organ structure and morphogenesis. The top ten serum protein biomarker candidates were identified after applying feature-selection data analysis. The combination of three proteins - apolipoprotein A-IV, complement factor H-related protein 4 and platelet basic protein - demonstrated the best classification performance for our data. In addition, the apolipoprotein group resulted in strong over-representation, thus highlighting these proteins as an additional promising biomarker panel.