Chromosome conformation capture to discover candidate epigenetic markers of Multiple Sclerosis disease severity
Author(s): ,
D Sangurdekar
Affiliations:
Biogen, Cambridge, MA, United States
,
T Plavina
Affiliations:
Biogen, Cambridge, MA, United States
,
C Singh
Affiliations:
Biogen, Cambridge, MA, United States
,
A Enayetallah
Affiliations:
Biogen, Cambridge, MA, United States
,
M Subramanyam
Affiliations:
Biogen, Cambridge, MA, United States
,
E Hunter
Affiliations:
Oxford BioDynamics, Oxford, United Kingdom
,
A Akoulitchev
Affiliations:
Oxford BioDynamics, Oxford, United Kingdom
J Goyal
Affiliations:
Biogen, Cambridge, MA, United States
ECTRIMS Online Library. Plavina T. Sep 16, 2016; 146797; P957
Tatiana Plavina
Tatiana Plavina
Contributions
Abstract

Abstract: P957

Type: Poster

Abstract Category: Pathology and pathogenesis of MS - Genetics /Epigenetics and Pharmacogenetics

Background: Multiple Sclerosis (MS) is a heterogeneous disease with diverse outcomes creating a need for better understanding of underlying pathophysiological mechanisms, and implementation of prognostic biomarkers to optimize treatment decisions. Growing evidence suggests an imperative role of epigenetic mechanisms in the development of autoimmune and neurodegenerative disorders, including MS.

Objectives: To identify an epigenetic signature associated with MS disease severity and progression.

Methods: Chromosomal Conformation Signature (CCS) profiling technology and platform (EpiSwitch™, Oxford BioDynamics) was used to profile whole blood from 16 MS subjects with varying disease severity (EDSS≥5 and EDSS≤2) and 7 healthy controls. Markers initially discovered on an MS custom-designed CCS array platform were validated using PCR assays. Univariate and contingency table analysis was performed to select candidate markers associated with clinical and radiological MS disease characteristics.

Results: To build a discovery array, 747 genes associated with MS pathogenesis were annotated with chromosome conformation interactions predicted using the EpiSwitchTM in silico prediction software, resulting in 42,458 high-confidence CCS candidates. The array profiling generated 156 candidate markers from 96 unique genes that were then translated into the PCR assay used for marker verification in additional samples. As a result, 27 chromatin conformation markers from several genetic loci, including BSCL2, MICB and STAT4, were found to be associated with clinical and radiological characteristics in the tested discovery cohort of patients. A follow up study that comprises 60 MS patients with longitudinal sampling and diverse clinical characteristics has been initiated to further refine the signature.

Conclusions: Pilot study of MS patients with extreme clinical phenotypes using EpiSwitch™ chromatin conformation platform identified candidate hypotheses and markers that are being verified in a larger longitudinal cohort.

Disclosure: Supported by: Biogen

Dipen Sangurdekar: employee of and holds stock/stock options in Biogen

Tatiana Plavina: employee of and holds stock/stock options in Biogen

Carol Singh: employee of and holds stock/stock options in Biogen

Bryan Innis: employee of and holds stock/stock options in Biogen

Ahmed Enayetallah: employee of and holds stock/stock options in Biogen

Meena Subramanyam: employee of and holds stock/stock options in Biogen

Ewan Hunter: employee of Oxford BioDynamics

Alexandre Akoulitchev: employee of Oxford BioDynamics

Jaya Goyal: employee of and holds stock/stock options in Biogen

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