HLA genotype as a marker of multiple sclerosis prognosis: A pilot study

Single-Cell Sequencing Combined with Transcriptome Sequencing Constructs a Predictive Model of Key Genes in Multiple Sclerosis and Explores Molecular Mechanisms Related to Cellular Communication

Background

Multiple sclerosis (MS) causes chronic inflammation and demyelination of the central nervous system and comprises a class of neurodegenerative diseases in which interactions between multiple immune cell types mediate the involvement of MS development. However, the early diagnosis and treatment of MS remain challenging.

Methods

Gene expression profiles of MS patients were obtained from the Gene Expression Omnibus (GEO) database. Single-cell and intercellular communication analyses were performed to identify candidate gene sets. Predictive models were constructed using LASSO regression. Relationships between genes and immune cells were analyzed by single sample gene set enrichment analysis (ssGSEA). The molecular mechanisms of key genes were explored using gene enrichment analysis. An miRNA network was constructed to search for target miRNAs related to key genes, and related transcription factors were searched by transcriptional regulation analysis. We utilized the GeneCard database to detect the correlations between disease-regulated genes and key genes. We verified the mRNA expression of 4 key genes by reverse transcription-quantitative PCR (RT‒qPCR).

Results

Monocyte marker genes were selected as candidate gene sets. CD3D, IL2RG, MS4A6A, and NCF2 were found to be the key genes by LASSO regression. We constructed a prediction model with AUC values of 0.7569 and 0.719. The key genes were closely related to immune factors and immune cells. We explored the signaling pathways and molecular mechanisms involving the key genes by gene enrichment analysis. We obtained and visualized the miRNAs associated with the key genes using the miRcode database. We also predicted the transcription factors involved. We used validated key genes in MS patients, several of which were confirmed by RT‒qPCR.

Conclusion

The prediction model constructed with the CD3D, IL2RG, MS4A6A, and NCF2 genes has good diagnostic efficacy and provides new ideas for the diagnosis and treatment of MS.

HLA-DQA1*04:01 is related to a higher multiple sclerosis lesion load on T2/Flair MRI sequences

BACKGROUND

The genetic predisposition to multiple sclerosis (MS) is associated with HLA alleles, especially HLA-DRB1*15:01.

OBJECTIVE

To identify associations between findings in magnetic resonance imaging (MRI) and genetic features in a Brazilian cohort of patients with MS.

METHODS

We retrospectively studied data from 95 consecutive patients with MS. Two independent observers who were blinded to the clinical data identified black holes and enhanced lesions on T1 MRI sequences, and counted and measured contrast-enhanced lesions on T2 and Flair (fluid attenuation inversion recovery) sequences. Cases were classified according to lesion size, number, and volume. The HLA-DRB1, HLA-DQB1, and HLA-DQA1 alleles, and the rs4774, rs3087456, rs6897932, rs731236, and rs1033182 single nucleotide polymorphisms were identified by polymerase chain reaction amplification with sequence-specific primers using the One Lambda Inc. Kit, Canoga Park, CA, USA.

RESULTS

Patients with the HLA-DQA1*04:01 allele had lesion load (adjusted for age, sex, and MS duration) above median compared with patients with other HLA-DQA1 alleles (p=0.02). There were no differences among all the other HLA alleles and single nucleotide polymorphisms and lesion load.

CONCLUSIONS

The correlation of the HLA-DQA1*04:01 allele with a higher lesion load on T2/Flair MRI sequences suggests that the presence of this allele is associated with the risk of greater MS severity.

Epstein-Barr Virus and Multiple Sclerosis

Multiple sclerosis (MS) is a neurologic disease affecting myelinated nerves in the central nervous system (CNS). The disease often debuts as a clinically isolated syndrome, e.g., optic neuritis (ON), which later develops into relapsing-remitting (RR) MS, with temporal attacks or primary progressive (PP) MS. Characteristic features of MS are inflammatory foci in the CNS and intrathecal synthesis of immunoglobulins (Igs), measured as an IgG index, oligoclonal bands (OCBs), or specific antibody indexes. Major predisposing factors for MS are certain tissue types (e.g., HLA DRB1*15:01), vitamin D deficiency, smoking, obesity, and infection with Epstein-Barr virus (EBV). Many of the clinical signs of MS described above can be explained by chronic/recurrent EBV infection and current models of EBV involvement suggest that RRMS may be caused by repeated entry of EBV-transformed B cells to the CNS in connection with attacks, while PPMS may be caused by more chronic activity of EBV-transformed B cells in the CNS. In line with the model of EBV's role in MS, new treatments based on monoclonal antibodies (MAbs) targeting B cells have shown good efficacy in clinical trials both for RRMS and PPMS, while MAbs inhibiting B cell mobilization and entry to the CNS have shown efficacy in RRMS. Thus, these agents, which are now first line therapy in many patients, may be hypothesized to function by counteracting a chronic EBV infection.

Relation Between the Novel Marker Monocyte to High-Density Lipoprotein Cholesterol Ratio and Severity in Multiple Sclerosis

INTRODUCTION

This study aimed to establish whether there is a relationship between the Monocyte to High-Density Lipoprotein Cholesterol (HDL-C) ratio (MHR) and severity of disease, and whether it can be used as a new marker for predicting disability in Multiple Sclerosis (MS), a chronic disease, which is usually contracted in early adolescence.

METHODS

184 patient subjects who had been definitively diagnosed with MS, based on the McDonald criteria, and 105 healthy subjects with a similar age and gender profile were included in the study. The patients' Expanded Disability Status Scale (EDSS) scores, MS subtypes, length of time with the disease and demographics were captured. Blood samples were collected for hematologic and biochemical testing. The MHR values were calculated and statistically compared with those of the control group.

RESULTS

The average age of the MS patients was 38.3 ± 8.6 years and their average EDSS score was 2.5 [0-7.5]. The patient arm consisted of 118 (64.1%) females and 66 (35.9%) males. In the patients with MS, the MHR was 15.01 ± 0.63 compared to 9.61 ± 0.25 in the controls. This difference was statistically significant (P < 0.001). In the MS patients, the MHR cut-off value was 12.95 compared to controls, which was statistically significant (P < 0.001). Also, a statistically-significant (r: 0.297, P < 0.001) positive correlation was found between the MHR and EDSS score.

CONCLUSION

The Monocyte to High-Density Lipoprotein Cholesterol ratio is associated with disease severity and disability in MS patients, and may be used as an independent marker for predicting disability. However, broader-scale studies are needed for more conclusive results.

Human Leukocyte Antigen Genotype as a Marker of Multiple Sclerosis Prognosis

OBJECTIVE

In a previous pilot monocentric study, we investigated the relation between human leukocyte antigen (HLA) genotype and multiple sclerosis (MS) disease progression over 2 years. HLA-A*02 allele was correlated with better outcomes, whereas HLA-B*07 and HLA-B*44 were correlated with worse outcomes. The objective of this extension study was to further investigate the possible association of HLA genotype with disease status and progression in MS as measured by sensitive and complex clinical and imaging parameters.

METHODS

Hundred and forty-six MS patients underwent HLA typing. Over a 4-year period of follow-up, we performed three clinical and magnetic resonance imaging (MRI) assessments per patient, which respectively included Expanded Disability Status Scale, Multiple Sclerosis Severity Scale, Timed-25-Foot-Walk, 9-Hole Peg Test, Symbol Digit Modalities Test, Brief Visual Memory Test, California Verbal Learning Test-II, and whole-brain atrophy, fluid-attenuated inversion recovery (FLAIR) lesion volume change and number of new FLAIR lesions using icobrain. We then compared the clinical and MRI outcomes between predefined HLA patient groups.

RESULTS

Results of this larger study with a longer follow-up are in line with what we have previously shown. HLA-A*02 allele is associated with potentially better MS outcomes, whereas HLA-B*07, HLA-B*44, HLA-B*08, and HLA-DQB1*06 with a potential negative effect. Results for HLA-DRB1*15 are inconclusive.

CONCLUSION

In the era of MS treatment abundance, HLA genotype might serve as an early biomarker for MS outcomes to inform individualized treatment decisions.

Spatial analyzes of HLA data in Rio Grande do Sul, south Brazil: genetic structure and possible correlation with autoimmune diseases

Background

HLA genes are the most polymorphic of the human genome and have distinct allelic frequencies in populations of different geographical regions of the world, serving as genetic markers in ancestry studies. In addition, specific HLA alleles may be associated with various autoimmune and infectious diseases. The bone marrow donor registry in Brazil is the third largest in the world, and it counts with genetic typing of HLA-A, -B, and -DRB1. Since 1991 Brazil has maintained the DATASUS database, a system fed with epidemiological and health data from compulsory registration throughout the country.

Methods

In this work, we perform spatial analysis and georeferencing of HLA genetic data from more than 86,000 bone marrow donors from Rio Grande do Sul (RS) and data of hospitalization for rheumatoid arthritis, multiple sclerosis and Crohn’s disease in RS, comprising the period from 1995 to 2016 obtained through the DATASUS system. The allele frequencies were georeferenced using Empirical Bayesian Kriging; the diseases prevalence were georeferenced using Inverse Distance Weighted and cluster analysis for both allele and disease were performed using Getis-Ord Gi* method. Spearman’s test was used to test the correlation between each allele and disease.

Results

The results indicate a HLA genetic structure compatible with the history of RS colonization, where it is possible to observe differentiation between regions that underwent different colonization processes. Spatial analyzes of autoimmune disease hospitalization data were performed revealing clusters for different regions of the state for each disease analyzed. The correlation test between allelic frequency and the occurrence of autoimmune diseases indicated a significant correlation between the HLA-B*08 allele and rheumatoid arthritis.

Conclusions

Genetic mapping of populations and the spatial analyzes such as those performed in this work have great economic relevance and can be very useful in the formulation of public health campaigns and policies, contributing to the planning and adjustment of clinical actions, as well as informing and educating professionals and the population.

Electronic supplementary material

The online version of this article (10.1186/s12942-018-0154-8) contains supplementary material, which is available to authorized users.

Genotype and Phenotype in Multiple Sclerosis-Potential for Disease Course Prediction?

PURPOSE OF REVIEW

This review will examine the current evidence that genetic and/or epigenetic variation may influence the multiple sclerosis (MS) clinical course, phenotype, and measures of MS severity including disability progression and relapse rate.

RECENT FINDINGS

There is little evidence that MS clinical phenotype is under significant genetic control. There is increasing evidence that there may be genetic determinants of the rate of disability progression. However, studies that can analyse disability progression and take into account all the confounding variables such as treatment, clinical characteristics, and environmental factors are by necessity longitudinal, relatively small, and generally of short duration, and thus do not lend themselves to the assessment of hundreds of thousands of genetic variables obtained from GWAS. Despite this, there is recent evidence to support the association of genetic loci with relapse rate. Recent progress suggests that genetic variations could be associated with disease severity, but not MS clinical phenotype, but these findings are not definitive and await replication. Pooling of study results, application of other genomic techniques including epigenomics, and analysis of biomarkers of progression could functionally validate putative severity markers.