Genome wide differences of gene expression associated with HLA-DRB1 genotype in multiple sclerosis: a pilot study

MMPred: a tool to predict peptide mimicry events in MHC class II recognition

We present MMPred, a software tool that integrates epitope prediction and sequence alignment algorithms to streamline the computational analysis of molecular mimicry events in autoimmune diseases. Starting with two protein or peptide sets (e.g., from human and SARS-CoV-2), MMPred facilitates the generation, investigation, and testing of mimicry hypotheses by providing epitope predictions specifically for MHC class II alleles, which are frequently implicated in autoimmunity. However, the tool is easily extendable to MHC class I predictions by incorporating pre-trained models from CNN-PepPred and NetMHCpan. To evaluate MMPred's ability to produce biologically meaningful insights, we conducted a comprehensive assessment involving i) predicting associations between known HLA class II human autoepitopes and microbial-peptide mimicry, ii) interpreting these predictions within a systems biology framework to identify potential functional links between the predicted autoantigens and pathophysiological pathways related to autoimmune diseases, and iii) analyzing illustrative cases in the context of SARS-CoV-2 infection and autoimmunity. MMPred code and user guide are made freely available at https://github.com/ComputBiol-IBB/MMPRED.

Could the Heat Shock Proteins 70 Family Members Exacerbate the Immune Response in Multiple Sclerosis? An in Silico Study

Multiple sclerosis (MS) is a chronic autoimmune demyelinating disease of the central nervous system. It represents one of the main causes of neurological disability in young people. In MS, the autoimmune response is directed against myelin antigens but other possible bio-molecular markers are investigated. The aim of this work was, through an in silico study, the evaluation of the transcriptional modifications between healthy subjects and MS patients in six brain areas (corpus callosum, hippocampus, internal capsule, optic chiasm, frontal and parietal cortex) in order to identify genes representative of the disease. Our results show the upregulation of the Heat Shock Proteins (HSPs) HSPA1A, HSPA1B, HSPA7, HSPA6, HSPH1 and HSPA4L of the HSP70 family, among which HSPA1A and HSPA1B are upregulated in all the brain areas. HSP70s are molecular chaperones indispensable for protein folding, recently associated with immune system maintenance. The little overexpression of the HSPs protects the cells from stress but extreme upregulation can contribute to the MS pathogenesis. We also investigated the genes involved in the immune system that result in overall upregulation in the corpus callosum, hippocampus, internal capsule, optic chiasm and are absent in the cortex. Interestingly, the genes of the immune system and the HSP70s have comparable levels of expression.

DNA methylation as a mediator of HLA-DRB1*15:01 and a protective variant in multiple sclerosis

The human leukocyte antigen (HLA) haplotype DRB1*15:01 is the major risk factor for multiple sclerosis (MS). Here, we find that DRB1*15:01 is hypomethylated and predominantly expressed in monocytes among carriers of DRB1*15:01. A differentially methylated region (DMR) encompassing HLA-DRB1 exon 2 is particularly affected and displays methylation-sensitive regulatory properties in vitro. Causal inference and Mendelian randomization provide evidence that HLA variants mediate risk for MS via changes in the HLA-DRB1 DMR that modify HLA-DRB1 expression. Meta-analysis of 14,259 cases and 171,347 controls confirms that these variants confer risk from DRB1*15:01 and also identifies a protective variant (rs9267649, p < 3.32 × 10^-8, odds ratio = 0.86) after conditioning for all MS-associated variants in the region. rs9267649 is associated with increased DNA methylation at the HLA-DRB1 DMR and reduced expression of HLA-DRB1, suggesting a modulation of the DRB1*15:01 effect. Our integrative approach provides insights into the molecular mechanisms of MS susceptibility and suggests putative therapeutic strategies targeting a methylation-mediated regulation of the major risk gene.

Late-onset Alzheimer disease risk variants mark brain regulatory loci

Objective:

To investigate the top late-onset Alzheimer disease (LOAD) risk loci detected or confirmed by the International Genomics of Alzheimer's Project for association with brain gene expression levels to identify variants that influence Alzheimer disease (AD) risk through gene expression regulation.

Methods:

Expression levels from the cerebellum (CER) and temporal cortex (TCX) were obtained using Illumina whole-genome cDNA-mediated annealing, selection, extension, and ligation assay (WG-DASL) for ∼400 autopsied patients (∼200 with AD and ∼200 with non-AD pathologies). We tested 12 significant LOAD genome-wide association study (GWAS) index single nucleotide polymorphisms (SNPs) for cis association with levels of 34 genes within ±100 kb. We also evaluated brain levels of 14 LOAD GWAS candidate genes for association with 1,899 cis-SNPs. Significant associations were validated in a subset of TCX samples using next-generation RNA sequencing (RNAseq).

Results:

We identified strong associations of brain CR1, HLA-DRB1, and PILRB levels with LOAD GWAS index SNPs. We also detected other strong cis-SNPs for LOAD candidate genes MEF2C, ZCWPW1, and SLC24A4. MEF2C and SLC24A4, but not ZCWPW1 cis-SNPs, also associate with LOAD risk, independent of the index SNPs. The TCX expression associations could be validated with RNAseq for CR1, HLA-DRB1, ZCWPW1, and SLC24A4.

Conclusions:

Our results suggest that some LOAD GWAS variants mark brain regulatory loci, nominate genes under regulation by LOAD risk variants, and annotate these variants for their brain regulatory effects.

Ten years of proteomics in multiple sclerosis

Multiple sclerosis, which is the most common cause of chronic neurological disability in young adults, is an inflammatory, demyelinating, and neurodegenerative disease of the CNS, which leads to the formation of multiple foci of demyelinated lesions in the white matter. The diagnosis is based currently on magnetic resonance image and evidence of dissemination in time and space. However, this could be facilitated if biomarkers were available to rule out other disorders with similar symptoms as well as to avoid cerebrospinal fluid analysis, which requires an invasive collection. Additionally, the molecular mechanisms of the disease are not completely elucidated, especially those related to the neurodegenerative aspects of the disease. The identification of biomarker candidates and molecular mechanisms of multiple sclerosis may be approached by proteomics. In the last 10 years, proteomic techniques have been applied in different biological samples (CNS tissue, cerebrospinal fluid, and blood) from multiple sclerosis patients and in its experimental model. In this review, we summarize these data, presenting their value to the current knowledge of the disease mechanisms, as well as their importance in identifying biomarkers or treatment targets.