Developing a biomarker for restless leg syndrome using genome wide DNA methylation data

Research output: Contribution to journalArticlepeer-review

Abstract

This study reports on an epigenetic biomarker for restless leg syndrome (RLS) developed using whole genome DNA methylation data. Lymphocyte-derived DNA methylation was examined in 15 subjects with and without RLS (discovery cohort). T-tests and linear regressions were used followed by a principal component analysis (PCA). The principal component model from the discovery cohort was used to predict RLS status in a peripheral blood (N = 24; including 12 cases and 12 controls) and a post-mortem neural tissue (N = 71; including 36 cases and 35 controls) replication cohort as well as iron deficiency anemia status in a publicly available dataset (N = 71, 59 cases with iron deficiency anemia, 12 controls). Using receiver-operating characteristic analysis the optimum biomarker model - that included 49 probes - predicted RLS status in the blood-based replication cohort with an area under the curve (AUC) of 87.5% (confidence interval = 71.9%–100%). In the neural tissue samples, the model predicted RLS status with an AUC of 73.4% (confidence interval = 61.5%–85.3%). An AUC of 83% was found for predictions of iron deficiency anemia. Thus, the blood-based biomarker model reported here and built with epigenome-wide data showed reasonable replicability in lymphocytes and neural tissue samples. A limitation of this study is that we could not determine the metabolic or neurobiological pathways linking epigenetic changes with RLS. Further research is needed to fine-tune this model for prospective predictions of RLS and to enable translation for clinical use.

Original languageEnglish (US)
Pages (from-to)120-127
Number of pages8
JournalSleep Medicine
Volume78
DOIs
StatePublished - Feb 2021

Keywords

  • Epigenetics
  • Iron deficiency
  • Restless leg syndrome
  • Sleep disorders

ASJC Scopus subject areas

  • Medicine(all)

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