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

对多种数据类型进行非参数组合分析,能够检测多发性硬化症患者T细胞中的新型调控机制

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

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.

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