From Genetics to Transcriptomics to Unravel the Mechanisms Behind a Poor Outcome in Multiple Sclerosis

Nantes University Hospital130 enrolled

Overview

MS is a heterogeneous disease either in its response to treatment or clinical manifestation. Indeed, the natural history of MS is varying from a benign condition to a devastating and rapidly incapacitating disease. Clinical heterogeneity could also be cellular and / or molecular. The aim is to identify from OMIC analyses, at the early stage of the disease, differentially expressed molecules and / or cell subpopulations derived from CD8 + T lymphocytes and / or CD4 + T lymphocytes and / or B lymphocytes and monocytes from patients with aggressive versus non-aggressive, compared to a cohort of healthy controls

Study Type

INTERVENTIONAL

Allocation

NON_RANDOMIZED

Purpose

BASIC_SCIENCE

Masking

NONE

Enrollment

130

Conditions

Multiple Sclerosis

Interventions

Venous blood sample will be collected from patients belonging to validation cohort and healthy volunteers at baseline resulting in 90 Ml EDTA tube and 10 ml serum tube. Approximately 100 ml will be collected. optional saliva and stool collection will be performed.

Eligibility

Sex: ALLMin age: 18 YearsHealthy volunteers:

Medical Language ↔ Plain English

Inclusion Criteria : Common criteria for retrospective MS patients: * Patients aged 18 years or older * Clinical isolated syndrome (CIS) with or without dissemination in space * Patients affiliated to an appropriate health insurance Criteria for Aggressive MS group • Start of a 2nd line therapy within the two years following the CIS Criteria for Non aggressive MS group * No conversion according to McDonald criteria from clinical isolated syndrome to multiple sclerosis within 2 years or * Conversion based to McDonald criteria treated or not with first line disease modifying therapy within 2 years. * Have a minimum of least 2 years of follow-up. Healthy volunteers * Aged 18 years or older * No history of clinically isolated syndrome or MS Pairing criteria : * Age +/- 5 years * Sex Prospective MS Patients * Patients aged 18 years or older * Clinical isolated syndrome (CIS) with or without dissemination in space * Patients affiliated to an appropriate health insurance Exclusion Criteria : * Ongoing participation to a another study * Refusal to genetic analyses * Immunosuppressive drug at the time of blood collection * Plasma exchange or corticosteroid treatment within the four weeks prior to blood sample * Adults under a legal protection regime (guardianship, trusteeship, judicial safeguard) * Pregnancy

Outcomes

Primary Outcomes

Bulk RNA-sequencing

Transcriptional profile of T and B cells in aggressive and non-aggressive MS and healthy volunteers. Measurement of gene expression of naïve and memory CD4+ and CD8+ T and B cell. Comparison of these expression level between MS patients with aggressive and non-aggressive form and healthy volunteers.

Time frame: Blood sample collection within 6 months after first inflammatory event for MS patients and at inclusion for healthy volunteers.

Secondary Outcomes

Single RNA sequencing

Single cell transcriptomics of T and B cells in order to identify by clustering, sub populations within these cells based on gene expression and associated to poor pronostic.

Time frame: Blood sample collection within 6 months after first inflammatory event.

Association of genetic sequence variation from whole genome sequencing with gene expression profile via Bulk RNA-seq

Add genetic variant analyzes to RNA seq analyses related to MS 1) Identify eQTL. 2 Impute SNPs result to calculate MS Genetic Burden (MSGB) a polygenic risk score of MS computed based on a weighted scoring algorithm using independent MS-SNPs.

Time frame: Blood sample collection within 6 months after first inflammatory event.

Association of transcriptomic variation with DNA methylation

Add Analyzes of gene expression regulation throughout DNA methylation of CpG sites to RNA seq analyses related to MS.

Time frame: Blood sample collection within 6 months after first inflammatory event.

OMIC integration

Developing machine learning method to combine genomic, epigenomic transcriptomic and clinical data to pinpoint genes of interest particularly involved in aggressive MS outcomes.

Time frame: Blood sample collection within 6 months after first inflammatory event.

From Genetics to Transcriptomics to Unravel the Mechanisms Behind a Poor Outcome in Multiple Sclerosis

Overview

Conditions

Interventions

Eligibility

Locations (1)

Outcomes

Primary Outcomes

Secondary Outcomes

Central Contacts