Background Genetic risk variants for complex disorders such as multiple sclerosis (MS) rarely encode protein. Growing evidence suggests risk variants regulate gene expression in specific disease-relevant cells by altering regulatory genetic sequences. This can be explored by correlating genotype at risk loci with expression of nearby genes (cis-regulation), with greatest sensitivity demonstrated in the most relevant cell types. Identifying genes under regulation by the MS risk variants could be a crucial step in identifying novel therapeutic targets.

Aims 1) Interrogate MS risk loci for cis-regulatory effects using allele-specific expression (ASE) analysis. 2) Establish a publicly available resource of genome-wide RNA-seq expression data in CSF-derived CD4 +T lymphocytes. 3) Correlate gene expression data with longitudinal clinical data to seek biomarkers of prognosis.

Method and progress We have extracted RNA from FACS-sorted CSF-derived CD4 +T lymphocytes from over 100 individuals. cDNA library preparation and sequencing for each sample is underway.

Data analysis ASE analysis makes use of a pre-selected transcribed SNP to differentiate maternal and paternal transcripts of each gene of interest. When an individual is heterozygous at an additional functional regulatory locus the ratio of maternal: paternal expression will deviate from 1:1. Each MS risk locus will be interrogated for this effect.