Big data and stratified medicine: what does it mean for children?

Arch Dis Child. 2019 Apr;104(4):389-394. doi: 10.1136/archdischild-2018-315125. Epub 2018 Sep 28.

Abstract

Stratified medicine in paediatrics is increasingly becoming a reality, as our understanding of disease pathogenesis improves and novel treatment targets emerge. We have already seen some success in paediatrics in targeted therapies such as cystic fibrosis for specific cystic fibrosis transmembrane conductance regulator variants. With the increased speed and decreased cost of processing and analysing data from rare disease registries, we are increasingly able to use a systems biology approach (including '-omics') to screen across populations for molecules and genes of interest. Improving our understanding of the molecular mechanisms underlying disease, and how to classify patients according to these will lead the way for targeted therapies for individual patients. This review article will summarise how 'big data' and the 'omics' are being used and developed, and taking examples from paediatric renal medicine and rheumatology, demonstrate progress being made towards stratified medicine for children.

Keywords: nephrology; paediatric practice; rheumatology.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Big Data*
  • Child
  • Computational Biology
  • Forecasting
  • Genomics
  • Humans
  • Metabolomics
  • Pediatrics / statistics & numerical data*
  • Proteomics
  • Rare Diseases
  • Registries
  • Systems Biology
  • Transcriptome