Screening newborns for candidate biomarkers of type 1 diabetes

Abstract

Combining samples from a national neonatal screening programme with the information from a national health registry allow for unique opportunities in analysing newborn blood for protein changes that could predict eventual disease development. A nested case-control cohort (n = 54 cases, 108 controls) was analysed by proteomics as a new way of looking for biomarkers that could bolster prediction of T1D risk in newborns. Protein extraction and haemoglobin depletion were automated and samples were processed and analysed by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). The data set was reduced to the highest quality peaks and analysed using conditional logistic regression. A total of 25 protein peaks were found to differ between the two groups. The automated haemoglobin depletion provides a platform for further proteomics studies of individual patient material. The method opens a door to a wealth of patient material stored as dried blood spots.