Summary: Here we investigated the earliest possible evidence of subclinical neuro-inflammation (SCNI) using a small cohort of monozygotic twins where one sibling had clinically definite MS and the other been clinically "healthy" but has a maximal genetic for developing MS. In contrast to subjects with radiologically isolated syndrome (RIS), our group of very early SCNI does not even fulfill the (arbitrary) MRI criteria for RIS but have more subtle MRI changes and/or evidence of neuro-inflammation in the CSF, e.g. oligoclonal bands (OCBs). For analyzing CSF samples from Twin pairs and controls in greater detail we applied single-cell whole transcriptome sequencing (scRNAseq). Our findings demonstrate that even the earliest experimentally approachable stage of MS is characterized by synergistic activation of CD8+ T cells, CD4+ T cells and B cells.
Overall Design: scRNA-seq. Library preparation: Smart-seq2; alignement: to UCSC hg38 using HISAT2; gene counts: featureCounts (Liao et al.); single-cell analysis: Seurat // PRJNA513835 - SRP180896
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Species: |
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Tissue: |
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Healthy Condition: |
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Cell Type: |
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Growth Protocol: | - |
Treatment Protocol: | - |
Extract Protocol: | Smart-seq2 |
Library Construction Protocol: | - |
Molecule Type: | poly(A)+ RNA |
Library Source: | |
Library Layout: | PAIRED |
Library Strand: | - |
Platform: | ILLUMINA |
Instrument Model: | Illumina HiSeq 1500 |
Strand-Specific: | Unspecific |
Data Resource | GEN Sample ID | GEN Dataset ID | Project ID | BioProject ID | Sample ID | Sample Name | BioSample ID | Sample Accession | Experiment Accession | Release Date | Submission Date | Update Date | Species | Race | Ethnicity | Age | Age Unit | Gender | Source Name | Tissue | Cell Type | Cell Subtype | Cell Line | Disease | Disease State | Development Stage | Mutation | Phenotype | Case Detail | Control Detail | Growth Protocol | Treatment Protocol | Extract Protocol | Library Construction Protocol | Molecule Type | Library Layout | Strand-Specific | Library Strand | Spike-In | Strategy | Platform | Instrument Model | Cell Number | Reads Number | Gbases | AvgSpotLen1 | AvgSpotLen2 | Uniq Mapping Rate | Multiple Mapping Rate | Coverage Rate |
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