Non-parametric combination analysis of multiple data types enables detection of novel regulatory mechanisms in T cells of multiple sclerosis patients

Sunjay Jude Fernandes,Ingrid Kockum,Mohsen Khademi,Nestoras Karathanasis,Hiromasa Morikawa,Ewoud Ewing,Tomas Olsson,Maja Jagodic,Sabrina Ruhrmann,Angelika Schmidt,Rubin Narayan Joshi,David Gomez-Cabrero,Ioannis Tsamardinos,Nuria Planell,Fredrik Piehl,Vincenzo Lagani,Jesper Tegnér

doi:10.1038/s41598-019-48493-7

Abstract

Multiple Sclerosis (MS) is an autoimmune disease of the central nervous system with prominent neurodegenerative components. The triggering and progression of MS is associated with transcriptional and epigenetic alterations in several tissues, including peripheral blood. The combined influence of transcriptional and epigenetic changes associated with MS has not been assessed in the same individuals. Here we generated paired transcriptomic (RNA-seq) and DNA methylation (Illumina 450 K array) profiles of CD4+ and CD8+ T cells (CD4, CD8), using clinically accessible blood from healthy donors and MS patients in the initial relapsing-remitting and subsequent secondary-progressive stage. By integrating the output of a differential expression test with a permutation-based non-parametric combination methodology, we identified 149 differentially expressed (DE) genes in both CD4 and CD8 cells collected from MS patients. Moreover, by leveraging the methylation-dependent regulation of gene expression, we identified the gene SH3YL1, which displayed significant correlated expression and methylation changes in MS patients. Importantly, silencing of SH3YL1 in primary human CD4 cells demonstrated its influence on T cell activation. Collectively, our strategy based on paired sampling of several cell-types provides a novel approach to increase sensitivity for identifying shared mechanisms altered in CD4 and CD8 cells of relevance in MS in small sized clinical materials.

Highlights

Precise triggering mechanisms remain unknown, the causal role of the immune system in Multiple Sclerosis (MS) is supported by genome-wide association studies (GWAS), which have uncovered many MS risk alleles in immune related loci[3,4,5,6]
Performing a differential expression (DE) analysis (FDR < 0.1) in CD4, we identified 34 genes differentially expressed between healthy controls (HC) and Relapse Remitting MS (RR) (Fig. 1a)
Our analysis reveals 149 differentially expressed genes in both CD4 and CD8, where several genes and processes were of confirmatory nature, as well as discovering several novel genes and processes putatively involved in MS

Summary

Introduction

Precise triggering mechanisms remain unknown, the causal role of the immune system in MS is supported by genome-wide association studies (GWAS), which have uncovered many MS risk alleles in immune related loci[3,4,5,6]. HLA class II genes that are essential for the initiation of the antigen-specific immune response by CD4 cells are established to be the most important risk genes contributing to susceptibility for MS. They are essential for antigen presentation to the T cell receptor (TCR). Using sorted CD4 and CD8 cells from RR and SP patients and healthy controls (HC), we perform transcriptomic profiling (RNA-Seq). We integrate this data at the epigenetic level by incorporating methylation profiles from the same cell-types in the same individuals. Due to limited number of samples and limited statistical power, we adapted a non-parametric combination analysis framework[20,21] to integrate such data across cell-types, and across different data-types

Methods

Results

Conclusion