Gene expression profiles of autophagy-related genes in multiple sclerosis

Mehri Igci*, Mehmet Baysan, Remzi Yigiter, Mustafa Ulasli, Sirma Geyik, Recep Bayraktar, İbrahim Bozgeyik, Esra Bozgeyik, Ali Bayram, Ecir Ali Cakmak

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

52 Citations (Scopus)


Multiple sclerosis (MS) is an imflammatory disease of central nervous system caused by genetic and environmental factors that remain largely unknown. Autophagy is the process of degradation and recycling of damaged cytoplasmic organelles, macromolecular aggregates, and long-lived proteins. Malfunction of autophagy contributes to the pathogenesis of neurological diseases, and autophagy genes may modulate the T cell survival. We aimed to examine the expression levels of autophagy-related genes. The blood samples of 95 unrelated patients (aged 17–65 years, 37 male, 58 female) diagnosed as MS and 95 healthy controls were used to extract the RNA samples. After conversion to single stranded cDNA using polyT priming: the targeted genes were pre-amplified, and 96 × 78 (samples × primers) qRT-PCR reactions were performed for each primer pair on each sample on a 96.96 array of Fluidigm BioMark™. Compared to age- and sex-matched controls, gene expression levels of ATG16L2, ATG9A, BCL2, FAS, GAA, HGS, PIK3R1, RAB24, RGS19, ULK1, FOXO1, HTT were significantly altered (false discovery rate < 0.05). Thus, altered expression levels of several autophagy related genes may affect protein levels, which in turn would influence the activity of autophagy, or most probably, those genes might be acting independent of autophagy and contributing to MS pathogenesis as risk factors. The indeterminate genetic causes leading to alterations in gene expressions require further analysis.

Original languageEnglish
Pages (from-to)38-46
Number of pages9
Issue number1
Publication statusPublished - 15 Aug 2016
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2016 Elsevier B.V.


  • Autophagy
  • Gene expression analysis
  • Multiple sclerosis


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