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    • The detection of ODC derived DeMeth

    2018-11-09

    The detection of ODC-derived DeMeth MOG-DNA in the cuprizone mouse model lead us to examine the methylation state of the MOG gene in human DNA. Analysis of an evolutionarily conserved region of MOG-DNA in human brains and liver showed an identical demethylation pattern in CpG dinucleotides also present in mouse MOG. The fact that sequencing analysis of methylergometrine DNA revealed only a partial conversion of C→T suggests that non-ODC cells contribute to the Meth form of MOG-DNA while ODCs are the sole source of DeMeth MOG-DNA as seen in the O4+ and O4− cell fractions in the mouse. Methylation-specific primers designed to distinguish between the Meth and DeMeth form of CpGs +2410 and +2430 showed a high degree of specificity and sensitivity similar to that of the mouse assay, and were able to detect DeMeth MOG in brain DNA at DMI levels nearly 10,000 folds higher than those observed in the liver. When tested, these primers showed a high DMI signal in OPCs when compared with liver, showing the ability of the assay to detect ODC-like DNA. The high degree of sensitivity and specificity of the human methylation-specific primers allowed us to analyze blood samples from 40 patients with RRMS, with active (n=20) or inactive (n=20) disease. Healthy controls (n=20) were also used to establish the baseline background DMI levels of normal subjects. Disease activity in RRMS patients was determined by clinical episodes and, in some cases, by the formation of new brain lesions in the CNS. While both RRMS patients with inactive and active disease were similar in age, gender, and duration of disease, patients with active RRMS had significant elevation in DMI values. ROC analysis of active and inactive RRMS revealed average AUC and preliminary cutoff values of specificity and sensitivity for assay performance. Additional studies consisting of larger patient cohorts would be needed to validate these values and allow for their use in the clinic. To our knowledge, this is the first report demonstrating the utility of differentially methylated ODC-derived cfDNA as a biomarker of cell loss in RRMS where DMI levels reflect disease activity. This report describes the differential methylation of the MOG gene in ODCs and brain tissues of both mouse and human origin. The unique DeMeth patterns in ODCs provide a new biomarker for the detection of ODC-cell loss in MS. Currently, diagnosis of MS is based on several criteria (Polman et al., 2011), including identification of lesions by MRI and positive identification of biomarkers in cerebral spinal fluid (CSF). MS is a financially burdening disease (Adelman et al., 2013; Kobelt et al., 2006), making MRIs cost-prohibitive for many underinsured patients. Despite the ongoing identification of useful biomarkers in CSF testing (Teunissen et al., 2015; Fitzner et al., 2015), lumbar punctures are an invasive procedure which prevents collecting samples from healthy individuals. The collection of cfDNA is a cost effective, minimally invasive procedure that can be implemented for diagnosis, prognosis, and monitoring of treatment efficacy. The ability to measure ODC loss may prove beneficial not only to MS but also to other disease afflicting ODC survival such as progressive multifocal leukoencephalopathy (PML). The following is the supplementary data related to this article.
    Funding This work was supported by the National Multiple Sclerosis Society (Grant No. PP2130), the Marilyn Hilton Award for Innovation in MS Research, and Winthrop University Hospital Pilot Award. Granting agencies did not play a role in the design, data collection, or analysis of data.
    The Duality of Interest
    Author Contributions
    Acknowledgments
    Introduction Accumulating evidence indicates that meditation facilitates affective regulation, enhances positive affect and reduces negative affect states (Jain et al., 2007; Robins et al., 2012; Chiesa et al., 2013). Such effects of meditation training are accompanied by neural functional connectivity changes (Brewer et al., 2011; Jang et al., 2011; Kilpatrick et al., 2011). Hence, further exploration on the associations between the affective and neural effects of meditation on brain connectivity patterns would enhance our theoretical understanding of the neural network mechanisms by which meditation training influences affective processing, as well as providing important clinical implications for improving the states of individuals with compromised affective regulation capacities, such as those with major depressive disorders (MDD) (Chiesa and Serretti, 2011; Simon and Engström, 2015).