Login / Signup

Different epigenetic clocks reflect distinct pathophysiological features of multiple sclerosis.

Eleftheria TheodoropoulouLars AlfredssonFredrik PiehlFrancesco MarabitaMaja Jagodic
Published in: Epigenomics (2019)
Aim: Accumulating evidence links epigenetic age to diseases and age-related conditions, but little is known about its association with multiple sclerosis (MS). Materials & methods: We estimated epigenetic age acceleration measures using DNA methylation from blood or sorted cells of MS patients and controls. Results: In blood, sex (p = 4.39E-05) and MS (p = 2.99E-03) explained the variation in age acceleration, and isolated blood cell types showed different epigenetic age. Intrinsic epigenetic age acceleration and extrinsic epigenetic age acceleration were only associated with sex (p = 2.52E-03 and p = 1.58E-04, respectively), while PhenoAge Acceleration displayed positive association with MS (p = 3.40E-02). Conclusion: Different age acceleration measures are distinctly influenced by phenotypic factors, and they might measure separate pathophysiological aspects of MS. Data deposition: DNA methylation data can be accessed at Gene Expression Omnibus database under accession number GSE35069, GSE43976, GSE106648, GSE130029, GSE130030.
Keyphrases
  • dna methylation
  • multiple sclerosis
  • gene expression
  • mass spectrometry
  • genome wide
  • ms ms
  • emergency department
  • mesenchymal stem cells
  • bone marrow
  • chronic kidney disease
  • artificial intelligence
  • big data
  • drug induced