Screening newborns for candidate biomarkers of type 1 diabetes

Arch Physiol Biochem. 2010 Oct-Dec;116(4-5):227-32. doi: 10.3109/13813455.2010.501801. Epub 2010 Sep 24.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Automation
  • Biological Specimen Banks
  • Biomarkers / analysis*
  • Biomarkers / chemistry*
  • Blood Proteins* / analysis
  • Blood Proteins* / chemistry
  • Case-Control Studies
  • Diabetes Mellitus, Type 1* / blood
  • Diabetes Mellitus, Type 1* / diagnosis
  • Hemoglobins / chemistry
  • Humans
  • Infant, Newborn
  • Neonatal Screening* / methods
  • Predictive Value of Tests
  • Protein Array Analysis / methods
  • Protein Array Analysis / standards
  • Proteomics / instrumentation
  • Proteomics / methods*
  • Reproducibility of Results
  • Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / methods*

Substances

  • Biomarkers
  • Blood Proteins
  • Hemoglobins