Impact of multiple sclerosis risk loci in postinfectious neurological syndromes

Background: The genetic component of multiple sclerosis (MS) is now set to 200 autosomal common variants. However, it is unclear how genetic knowledge be clinically used in the differential diagnosis between MS and other inflammatory conditions like adult-onset postinfectious neurological syndromes (PINS). The aim of this study was to investigate whether PINS and MS have a shared genetic background using an updated polygenic risk scores. / Methods: Eighty-eight PINS patients have been consecutively recruited between 1996 and 2016 at Mondino Foundation of Pavia, diagnosed according to clinical, MRI and CSF findings and followed-up for several years. Patients were typed using Illumina array, and genotypes imputed using the 1000 Genomes Project reference panel. A weighted genetic risk score (wGRS) has been calculated based on autosomal MS risk loci derived from large-scale studies, and an HLA genetic burden (HLAGB) was also calculated on loci associated to MS. / Results: PINS occurred as an episode of myelitis in 44% of patients, encephalomyelitis in 44%, and encephalitis in remaining cases, with an involvement of peripheral nervous system in 41% of patients. Mean age of onset was 50.1 years, and female:male ratio was 1.4. Patients were followed-up for a mean of 7.2 years, and at last visit 55% had a low disability grade (mRS 0–1). Disease was monophasic in 67% of patients, relapsing in 18% and chronic-progressive in 15%. The wGRS of PINS cases was comparable to 370 healthy controls, while significantly lower compared to 907 bout-onset MS (BOMS) cases (wGRS= 20.9 vs 21.2; p<0.0001). The difference was even larger for PINS with peripheral nervous system involvement (wGRS=20.6) vs BOMS. / Conclusion: The distinction between MS and PINS is not easy to make in clinical practice. However, our study shows that the new set of MS risk alleles does not confer increased susceptibility to PINS. These data support the importance to discriminate these cases from MS with pathophysiological and therapeutic implications

NLRP3 polymorphisms and response to interferon-beta in multiple sclerosis patients

Evidence exists for a potential modulation of inflammasome activity by interferon beta. Here, we investigated the roles of inflammasomes [absent in melanoma 2 (AIM2); NLR family, CARD domain containing 4 (NLRC4); NLR family, pyrin domain containing 1 and 3 (NLRP1 and NLRP3)] and related cytokines (IL1B, IL10, IL18) in the response to interferon beta in patients with relapsing-remitting multiple sclerosis. Ninety-seven patients treated with interferon beta were classified into responders and non-responders according to clinical criteria after 24 months and clinical-radiological criteria after 12 months of treatment. Messenger RNA expression levels of inflammasomes and cytokines were determined by real-time polymerase chain reaction in peripheral blood mononuclear cells collected before treatment with interferon beta. In a subgroup of patients, NLRP3 and IL1B expression was also determined after 3 months (n = 32) and 12 months (n = 20) of interferon beta treatment. A polymorphism located in the NLRP3 gene, rs35829419, was genotyped in 789 multiple sclerosis patients treated with interferon beta. Baseline mRNA expression levels for NLRP3 and IL1B were increased in peripheral blood mononuclear cells from non-responders compared to responders classified according to clinical criteria after 24 months (P = 0.02 and P = 0.001, respectively). No significant differences were observed for other inflammasomes and related cytokines. Differences in NLRP3 and IL1B expression remained significant following a clinical-radiological classification after 12 months (P = 0.007 and P = 0.02, respectively). After treatment with interferon beta, NLRP3 and IL1B expression was increased in responders but unchanged in non-responders. A trend for association was observed between rs35829419 and interferon beta response (pM-H = 0.08). These results point to a role of the NLRP3 inflammasome and its related cytokine IL1B in the response to interferon beta in patients with relapsing-remitting multiple sclerosis

Contribution of Rare and Low-Frequency Variants to Multiple Sclerosis Susceptibility in the Italian Continental Population

Genome-wide association studies identified over 200 risk loci for multiple sclerosis (MS) focusing on common variants, which account for about 50% of disease heritability. The goal of this study was to investigate whether low-frequency and rare functional variants, located in MS-established associated loci, may contribute to disease risk in a relatively homogeneous population, testing their cumulative effect (burden) with gene-wise tests. We sequenced 98 genes in 588 Italian patients with MS and 408 matched healthy controls (HCs). Variants were selected using different filtering criteria based on allelic frequency and in silico functional impacts. Genes showing a significant burden (n = 17) were sequenced in an independent cohort of 504 MS and 504 HC. The highest signal in both cohorts was observed for the disruptive variants (stop-gain, stop-loss, or splicing variants) located in EFCAB13, a gene coding for a protein of an unknown function (p &lt; 10–4). Among these variants, the minor allele of a stop-gain variant showed a significantly higher frequency in MS versus HC in both sequenced cohorts (p = 0.0093 and p = 0.025), confirmed by a meta-analysis on a third independent cohort of 1298 MS and 1430 HC (p = 0.001) assayed with an SNP array. Real-time PCR on 14 heterozygous individuals for this variant did not evidence the presence of the stop-gain allele, suggesting a transcript degradation by non-sense mediated decay, supported by the evidence that the carriers of the stop-gain variant had a lower expression of this gene (p = 0.0184). In conclusion, we identified a novel low-frequency functional variant associated with MS susceptibility, suggesting the possible role of rare/low-frequency variants in MS as reported for other complex diseases

Next generation sequencing of pooled samples : guideline for variants&apos; filtering

Sequencing large number of individuals, which is often needed for population genetics studies, is still economically challenging despite falling costs of Next Generation Sequencing (NGS). Pool-seq is an alternative cost- and time-effective option in which DNA from several individuals is pooled for sequencing. However, pooling of DNA creates new problems and challenges for accurate variant call and allele frequency (AF) estimation. In particular, sequencing errors confound with the alleles present at low frequency in the pools possibly giving rise to false positive variants. We sequenced 996 individuals in 83 pools (12 individuals/pool) in a targeted re-sequencing experiment. We show that Pool-seq AFs are robust and reliable by comparing them with public variant databases and in-house SNP-genotyping data of individual subjects of pools. Furthermore, we propose a simple filtering guideline for the removal of spurious variants based on the Kolmogorov-Smirnov statistical test. We experimentally validated our filters by comparing Pool-seq to individual sequencing data showing that the filters remove most of the false variants while retaining majority of true variants. The proposed guideline is fairly generic in nature and could be easily applied in other Pool-seq experiments

Unraveling gene expression profiles in peripheral motor nerve from Amyotrophic Lateral Sclerosis patients : insights into pathogenesis

The aim of the present study is to investigate the molecular pathways underlying amyotrophic lateral sclerosis (ALS) pathogenesis within the peripheral nervous system. We analyzed gene expression changes in human motor nerve diagnostic biopsies obtained from eight ALS patients and seven patients affected by motor neuropathy as controls. An integrated transcriptomics and system biology approach was employed. We identified alterations in the expression of 815 genes, with 529 up-regulated and 286 down-regulated in ALS patients. Up-regulated genes clustered around biological process involving RNA processing and protein metabolisms. We observed a significant enrichment of up-regulated small nucleolar RNA transcripts (p = 2.68 1710-11) and genes related to endoplasmic reticulum unfolded protein response and chaperone activity. We found a significant down-regulation in ALS of genes related to the glutamate metabolism. Interestingly, a network analysis highlighted HDAC2, belonging to the histone deacetylase family, as the most interacting node. While so far gene expression studies in human ALS have been performed in postmortem tissues, here specimens were obtained from biopsy at an early phase of the disease, making these results new in the field of ALS research and therefore appealing for gene discovery studies

Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility

We analyzed genetic data of 47,429 multiple sclerosis (MS) and 68,374 control subjects and established a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 variants within the extended MHC. We used an ensemble of methods to prioritize 551 putative susceptibility genes that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we observed enrichment for MS genes in these brain-resident immune cells, suggesting that these may have a role in targeting an autoimmune process to the central nervous system, although MS is most likely initially triggered by perturbation of peripheral immune responses

Locus for severity implicates CNS resilience in progression of multiple sclerosis

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) that results in significant neurodegeneration in the majority of those affected and is a common cause of chronic neurological disability in young adults(1,2). Here, to provide insight into the potential mechanisms involved in progression, we conducted a genome-wide association study of the age-related MS severity score in 12,584 cases and replicated our findings in a further 9,805 cases. We identified a significant association with rs10191329 in the DYSF-ZNF638 locus, the risk allele of which is associated with a shortening in the median time to requiring a walking aid of a median of 3.7 years in homozygous carriers and with increased brainstem and cortical pathology in brain tissue. We also identified suggestive association with rs149097173 in the DNM3-PIGC locus and significant heritability enrichment in CNS tissues. Mendelian randomization analyses suggested a potential protective role for higher educational attainment. In contrast to immune-driven susceptibility(3), these findings suggest a key role for CNS resilience and potentially neurocognitive reserve in determining outcome in MS

Network topology of NaV1.7 mutations in sodium channel-related painful disorders

Background: Gain-of-function mutations in SCN9A gene that encodes the voltage-gated sodium channel NaV1.7 have been associated with a wide spectrum of painful syndromes in humans including inherited erythromelalgia, paroxysmal extreme pain disorder and small fibre neuropathy. These mutations change the biophysical properties of NaV1.7 channels leading to hyperexcitability of dorsal root ganglion nociceptors and pain symptoms. There is a need for better understanding of how gain-of-function mutations alter the atomic structure of Nav1.7. Results: We used homology modeling to build an atomic model of NaV1.7 and a network-based theoretical approach, which can predict interatomic interactions and connectivity arrangements, to investigate how pain-related NaV1.7 mutations may alter specific interatomic bonds and cause connectivity rearrangement, compared to benign variants and polymorphisms. For each amino acid substitution, we calculated the topological parameters betweenness centrality (Bct), degree (D), clustering coefficient (CCct), closeness (Cct), and eccentricity (Ect), and calculated their variation (value= mutantvalue-WTvalue). Pathogenic NaV1.7 mutations showed significantly higher variation of |Bct| compared to benign variants and polymorphisms. Using the cut-off value \uc2\ub10.26 calculated by receiver operating curve analysis, we found that Bctcorrectly differentiated pathogenic NaV1.7 mutations from variants not causing biophysical abnormalities (nABN) and homologous SNPs (hSNPs) with 76% sensitivity and 83% specificity. Conclusions: Our in-silico analyses predict that pain-related pathogenic NaV1.7 mutations may affect the network topological properties of the protein and suggest |Bct| value as a potential in-silico marker