Evidence for VAV2 and ZNF433 as susceptibility genes for multiple sclerosis

Changes in iron load in specific brain areas lead to neurodegenerative diseases of the central nervous system

The causes of neurodegenerative diseases remain largely elusive, increasing their personal and societal impacts. To reveal the causal effects of iron load on Parkinson's disease (PD), Alzheimer's disease (AD), amyotrophic lateral sclerosis and multiple sclerosis, we used Mendelian randomisation and brain imaging data from a UK Biobank genome-wide association study of 39,691 brain imaging samples (predominantly of European origin). Using susceptibility-weighted images, which reflect iron load, we analysed genetically significant brain regions. Inverse variance weighting was used as the main estimate, while MR Egger and weighted median were used to detect heterogeneity and pleiotropy. Nine clear associations were obtained. For AD and PD, an increased iron load was causative: the right pallidum for AD and the right caudate, left caudate and right accumbens for PD. However, a reduced iron load was identified in the right and left caudate for multiple sclerosis, the bilateral hippocampus for mixed vascular dementia and the left thalamus and bilateral accumbens for subcortical vascular dementia. Thus, changes in iron load in different brain regions have causal effects on neurodegenerative diseases. Our results are crucial for understanding the pathogenesis and investigating the treatment of these diseases.

CD4+ Cytotoxic T Cells Involved in the Development of EBV-Associated Diseases

Activated cytotoxic CD4 T cells (HLA-DR+) play an important role in the control of EBV infection, especially in cells with latency I (EBNA-1). One of the evasion mechanisms of these latency cells is generated by gp42, which, via peripherally binding to the β1 domain of the β chain of MHC class II (HLA-DQ, -DR, and -DP) of the infected B lymphocyte, can block/alter the HLA class II/T-cell receptor (TCR) interaction, and confer an increased level of susceptibility towards the development of EBV-associated autoimmune diseases or cancer in genetically predisposed individuals (HLA-DRB1* and DQB1* alleles). The main developments predisposing the factors of these diseases are: EBV infection; HLA class II risk alleles; sex; and tissue that is infiltrated with EBV-latent cells, forming ectopic lymphoid structures. Therefore, there is a need to identify treatments for eliminating cells with EBV latency, because the current treatments (e.g., antivirals and rituximab) are ineffective.

Multilocus evaluation of genetic predictors of multiple sclerosis

BACKGROUND

Genome-wide association studies identified numerous susceptibility loci for multiple sclerosis in populations of European ancestry, but the associations are not always reproducible in other populations due to admixture and different linkage disequilibrium patterns obscuring true association signals.

OBJECTIVE

Our aim was to identify genetic predictors of multiple sclerosis in three ethnically homogenous populations from the Volga-Ural region of Russian Federation.

METHODS

In the largest to date study of multiple sclerosis in Russian population, involving 2048 participants from the Republic of Bashkortostan, Russian Federation (641 patients with multiple sclerosis and 1407 unaffected individuals), we performed replication analysis of previously identified genome-wide signals for multiple sclerosis. Associations were tested using logistic regression analysis under additive genetic model adjusted for sex. Meta-analysis of the study results in three populations was performed under fixed effects and random effects models.

RESULTS

We demonstrate the association with multiple sclerosis of the five variants (INAVA rs7522462, EOMES rs11129295, C6orf10 rs3129934, CD86 rs9282641, and GPR65 rs2119704). The strongest association (OR = 2.16, CI:1.85-2.74, P = 2.53x10^-13) was detected for rs3129934 polymorphism in the major histocompatibility region. Multilocus analysis has revealed 322 and 27 allelic patterns associated with multiple sclerosis in women and men, respectively. In women, the highest risk of MS was conferred by C6orf10 rs3129934*T/T + STAT3 rs744166*T combination (OR = 11.87), in men - by C6orf10 rs3129934*T + EOMES rs11129295*C + RPS6KB1 rs180515*C combination (OR = 3.25).

CONCLUSION

We confirm five associations with multiple sclerosis previously reported in genome-wide scans in Europeans in three ethnic groups from the Volga-Ural region of Russia.

Genetics and functional genomics of multiple sclerosis

Multiple sclerosis (MS) is an inflammatory neurodegenerative disease with genetic predisposition. Over the last decade, genome-wide association studies with increasing sample size led to the discovery of robustly associated genetic variants at an exponential rate. More than 200 genetic loci have been associated with MS susceptibility and almost half of its heritability can be accounted for. However, many challenges and unknowns remain. Definitive studies of disease progression and endophenotypes are yet to be performed, whereas the majority of the identified MS variants are not yet functionally characterized. Despite these shortcomings, the unraveling of MS genetics has opened up a new chapter on our understanding MS causal mechanisms.

A new and spontaneous animal model for ankylosing spondylitis is found in cynomolgus monkeys

BACKGROUND

Ankylosing spondylitis is a progressive, disabling joint disease that affects millions worldwide. Given its unclear etiology, studies of ankylosing spondylitis relied heavily on drug-induced or transgenic rodent models which retain only partial clinical features. There is obviously a lack of a useful disease model to conduct comprehensive mechanistic studies.

METHODS

We followed a group of cynomolgus monkeys having joint lesions reported of spinal stiffness for 2 years by conducting hematological testing, radiographic examination, family aggregation analysis, pathological analysis, and genetic testing.

RESULTS

The results confirmed that these diseased animals suffered from spontaneous ankylosing spondylitis with clinical features recapitulating human ankylosing spondylitis disease progression, manifested by pathological changes and biochemical indicators similar to that of ankylosing spondylitis patients.

CONCLUSION

The study offers a promising non-human primate model for spontaneous ankylosing spondylitis which may serve as an excellent substitute for its pre-clinical research.

Contribution of common risk variants to multiple sclerosis in Orkney and Shetland

Orkney and Shetland, the population isolates that make up the Northern Isles of Scotland, are of particular interest to multiple sclerosis (MS) research. While MS prevalence is high in Scotland, Orkney has the highest global prevalence, higher than more northerly Shetland. Many hypotheses for the excess of MS cases in Orkney have been investigated, including vitamin D deficiency and homozygosity: neither was found to cause the high prevalence of MS. It is possible that this excess prevalence may be explained through unique genetics. We used polygenic risk scores (PRS) to look at the contribution of common risk variants to MS. Analyses were conducted using ORCADES (97/2118 cases/controls), VIKING (15/2000 cases/controls) and Generation Scotland (30/8708 cases/controls) data sets. However, no evidence of a difference in MS-associated common variant frequencies was found between the three control populations, aside from HLA-DRB1*15:01 tag SNP rs9271069. This SNP had a significantly higher risk allele frequency in Orkney (0.23, p value = 8 × 10-13) and Shetland (0.21, p value = 2.3 × 10-6) than mainland Scotland (0.17). This difference in frequency is estimated to account for 6 (95% CI 3, 8) out of 150 observed excess cases per 100,000 individuals in Shetland and 9 (95% CI 8, 11) of the observed 257 excess cases per 100,000 individuals in Orkney, compared with mainland Scotland. Common variants therefore appear to account for little of the excess burden of MS in the Northern Isles of Scotland.

Lung cancer risk in patients with multiple sclerosis: a Mendelian randomization analysis

BACKGROUND

The relationship of multiple sclerosis (MS) with lung cancer is under debate. Conventional observational studies have reported conflicting findings, but such studies are susceptible to confounding and reverse causation. With a Mendelian Randomization approach, we were able to evaluate the causality between MS and lung cancer.

METHODS

According to published genome-wide association studies (GWASs), we obtained 35 MS-related single-nucleotide polymorphisms, which were used as instrumental variables in our study. Summary data of individual-level genetic information were obtained from the International Lung Cancer Consortium (ILCCO), with a total of 15,861 controls and 11,348 cases; the latter is composed of patients with lung adenocarcinoma and squamous cell lung cancer. The inverse variance-weighted method was applied to estimate the causation between MS and lung cancer. To further evaluate the pleiotropy, the MR-Egger and Weighted median methods were implemented.

RESULTS

The results of MR analysis suggested a causal effect of MS on lung cancer incidence, with evidence of an increased risk for overall lung cancer [odds ratio (OR): 1.0648; 95% confidence interval (CI): 1.0163-1.1156; p = 0.0082]. However, subgroup analyses showed no significant causal relationships between MS and lung adenocarcinoma (OR = 1.0716; 95% CI 0.9840-1.1671, p = 0.1119) and squamous cell lung cancer (OR = 1.0284; 95% CI 0.9575-1.1045, p = 0.4424). In addition, no pleiotropy was found in our study.

CONCLUSION

Our study indicated that MS is a causal risk factor in the development of lung cancer. Further work is needed to elucidate the potential mechanisms.

Coding and non-coding RNA interactions reveal immune-related pathways in peripheral blood mononuclear cells derived from patients with proliferative vitreoretinopathy

BACKGROUND

Peripheral immune response has been revealed to play a critical role in proliferative vitreoretinopathy (PVR). However, the reliable immune-related factors that are acting as prognostic indicators or therapeutic targets for PVR remain to explore further.

METHODS

In the current study, we applied whole-transcriptome sequencing to profile peripheral blood mononuclear cells from PVR patients and also analyzed lncRNA-mRNA interactions in peripheral immune cells to explore the pathways that might mediate immunopathology and resultant retinal damage in PVR. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses and Ingenuity Pathway Analysis (IPA) were employed to classify the function of these differentially expressed genes.

RESULTS

Compared to the controls, there were 319 genes upregulated, and 191 genes downregulated in PVR patients. GO, and KEGG enrichment analyses as well as IPA showed that these upregulated genes were significantly enriched in immune-related and infection-relate terms. Immune-related gene NFKBIA, CXCL2, and CXCL8 were detected as hub-genes in the co-expression network, while lncRNAs such as AC007032.1, AC037198.2, AL929472.2, and SLED1 were highly co-expressed with them. lncRNA-mRNA interactions analysis also showed that putative targeted genes of these differentially expressed lncRNAs were also significantly enriched in immune-related or infection-relate pathways.

CONCLUSION

Our study highlights the transformation of immune-related genes/pathways in PVR by comparing controls, and validates several critical genes and lncRNAs, which are serving as potential diagnostic markers for PVR patients.

Mouse mammary tumor viral env sequences are not present in the human genome but are present in breast tumors and normal breast tissues

In 1936, John Joseph Bittner identified mouse mammary tumor virus (MMTV), a milk transmitted beta retrovirus, a form of single-stranded positive-sense RNA virus. A retrovirus inserts a copy of its genome into the DNA of a host cell, thus altering the cell's genome. In the current analysis, we searched for MMTV sequences within the human genome. To compare the MMTV genome to the human genome, we used BLAT, the Blast-Like Alignment Tool of the UCSC Genome Browser. BLAT can align a user sequence of 25 bases or more to the genome. 60 MMTV sequences were in the human genome. Of 56 sequences from the MMTV POL gene, 36 POL sequences were from the same part of the gene, beginning at viral nucleotide 4800 but of different lengths. 8 viral sequences began at nucleotide ∼3430 of the POL gene. Four viral sequences were from GAGdUTPase, encoded by the MMTV PRO gene. Deoxyuridine 5'-triphosphate nucleotidohydrolase (dUTPase) is an enzyme present in several major retroviral families. In MMTV dUTPase may be essential for viral replication. Since BLAT identified no MMTV envelope (env) sequence in the human genome, the env sequences from breast tumors and normal breast tissue found in other studies may have come from an MMTV infection. However, no one is certain how MMTV could enter human cells, since the cells do not have a cellular receptor for MMTV, as do mouse cells.

Genome-Wide Multiple Sclerosis Association Data and Coagulation

The emerging concept of a crosstalk between hemostasis, inflammation, and immune system prompt recent works on coagulation cascade in multiple sclerosis (MS). Studies on MS pathology identified several coagulation factors since the beginning of the disease pathophysiology: fibrin deposition with breakdown of blood brain barrier, and coagulation factors within active plaques may exert pathogenic role, especially through the innate immune system. Studies on circulating coagulation factors showed complex imbalance involving several components of hemostasis cascade (thrombin, factor X, factor XII). To analyze the role of the coagulation process in connection with other pathogenic pathways, we implemented a systematic matching of genome-wide association studies (GWAS) data with an informative and unbiased network of coagulation pathways. Using MetaCore (version 6.35 build 69300, 2018) we analyzed the connectivity (i.e., direct and indirect interactions among two networks) between the network of the coagulation process and the network resulting from feeding into MetaCore the MS GWAS data. The two networks presented a remarkable over-connectivity: 958 connections vs. 561 expected by chance; z-score = 17.39; p-value < 0.00001. Moreover, genes coding for cluster of differentiation 40 (CD40) and plasminogen activator, urokinase (PLAU) shared both networks, pointed to an integral interplay between coagulation cascade and main pathogenic immune effectors. In fact, CD40 pathways is especially operative in B cells, that are currently a major therapeutic target in MS field. The potential interaction of PLAU with a signal of paramount importance for B cell pathogenicity, such as CD40, suggest new lines of research and pave the way to implement new therapeutic targets.

ZNF433 positively regulates the beta-catenin/ TCF pathway in prostate cancer and enhances the tumorigenicity of cancer cells

Background

Prostate cancer often shows the over-activation of beta-catenin/t-cell factor (TCF) signaling. It remains largely unknown how the beta-catenin/TCF transcriptional machinery is tightly controlled.

Methods

The ZNF433 mRNA and protein levels in the clinical tissues were examined using q-PCR, Western blot and immunohistochemistry. The phenotypes of prostate cancer cells were examined using MTT assay, Boyden chamber assay and anchorage-independent assay. The interaction between ZNF433 and beta-catenin was evaluated by immunoprecipitation.

Results

In the present study, ZNF433 was upregulated in prostate cancer samples, and promoted the growth and migration of prostate cancer cells. Furthermore, ZNF433 was the binding partner of beta-catenin and activated beta-catenin/TCF signaling in prostate cancer. Moreover, ZNF433 enhanced the binding between beta-catenin and TCF4. In addition, NC043, small antagonist for beta-catenin/TCF complex, inhibited the malignant behaviors of prostate cancer cells driven by ZNF433.

Conclusion

In summary, these studies demonstrate the tumor-promoting roles of ZNF433 in prostate cancer, and suggesting that ZNF433 was a potential target for the treatment.

Interpreting Non-coding Genetic Variation in Multiple Sclerosis Genome-Wide Associated Regions

Multiple sclerosis (MS) is the most common neurological disorder in young adults. Despite extensive studies, only a fraction of MS heritability has been explained, with association studies focusing primarily on protein-coding genes, essentially for the difficulty of interpreting non-coding features. However, non-coding RNAs (ncRNAs) and functional elements, such as super-enhancers (SE), are crucial regulators of many pathways and cellular mechanisms, and they have been implicated in a growing number of diseases. In this work, we searched for possible enrichments in non-coding elements at MS genome-wide associated loci, with the aim to highlight their possible involvement in the susceptibility to the disease. We first reconstructed the linkage disequilibrium (LD) structure of the Italian population using data of 727,478 single-nucleotide polymorphisms (SNPs) from 1,668 healthy individuals. The genomic coordinates of the obtained LD blocks were intersected with those of the top hits identified in previously published MS genome-wide association studies (GWAS). By a bootstrapping approach, we hence demonstrated a striking enrichment of non-coding elements, especially of circular RNAs (circRNAs) mapping in the 73 LD blocks harboring MS-associated SNPs. In particular, we found a total of 482 circRNAs (annotated in publicly available databases) vs. a mean of 194 ± 65 in the random sets of LD blocks, using 1,000 iterations. As a proof of concept of a possible functional relevance of this observation, we experimentally verified that the expression levels of a circRNA derived from an MS-associated locus, i.e., hsa_circ_0043813 from the STAT3 gene, can be modulated by the three genotypes at the disease-associated SNP. Finally, by evaluating RNA-seq data of two cell lines, SH-SY5Y and Jurkat cells, representing tissues relevant for MS, we identified 18 (two novel) circRNAs derived from MS-associated genes. In conclusion, this work showed for the first time that MS-GWAS top hits map in LD blocks enriched in circRNAs, suggesting circRNAs as possible novel contributors to the disease pathogenesis.

Low-Frequency and Rare-Coding Variation Contributes to Multiple Sclerosis Risk

Multiple sclerosis is a complex neurological disease, with ∼20% of risk heritability attributable to common genetic variants, including >230 identified by genome-wide association studies. Multiple strands of evidence suggest that much of the remaining heritability is also due to additive effects of common variants rather than epistasis between these variants or mutations exclusive to individual families. Here, we show in 68,379 cases and controls that up to 5% of this heritability is explained by low-frequency variation in gene coding sequence. We identify four novel genes driving MS risk independently of common-variant signals, highlighting key pathogenic roles for regulatory T cell homeostasis and regulation, IFNγ biology, and NFκB signaling. As low-frequency variants do not show substantial linkage disequilibrium with other variants, and as coding variants are more interpretable and experimentally tractable than non-coding variation, our discoveries constitute a rich resource for dissecting the pathobiology of MS.

Genetics of Multiple Sclerosis: An Overview and New Directions

The contribution of genetic inheritance in multiple sclerosis was established early on. Although multiple sclerosis is not a Mendelian disease, its incidence and prevalence is higher in family members of affected individuals compared with the general population. Throughout the last decade, several small studies failed to identify any robust genetic associations besides the classic associations in the major histocompatibility complex region. During the past few years, genome-wide association studies (GWAS) have revolutionized the genetics of multiple sclerosis, uncovering more than 200 implicated genetic loci. Here, we describe these main findings and discuss the new avenues that these discoveries lay open.

Genome-wide association studies of multiple sclerosis

Large-scale genetic studies of multiple sclerosis have identified over 230 risk effects across the human genome, making it a prototypical common disease with complex genetic architecture. Here, after a brief historical background on the discovery and definition of the disease, we summarise the last fifteen years of genetic discoveries and map out the challenges that remain to translate these findings into an aetiological framework and actionable clinical understanding.

PheWAS and Beyond: The Landscape of Associations with Medical Diagnoses and Clinical Measures across 38,662 Individuals from Geisinger

Most phenome-wide association studies (PheWASs) to date have used a small to moderate number of SNPs for association with phenotypic data. We performed a large-scale single-cohort PheWAS, using electronic health record (EHR)-derived case-control status for 541 diagnoses using International Classification of Disease version 9 (ICD-9) codes and 25 median clinical laboratory measures. We calculated associations between these diagnoses and traits with ∼630,000 common frequency SNPs with minor allele frequency > 0.01 for 38,662 individuals. In this landscape PheWAS, we explored results within diseases and traits, comparing results to those previously reported in genome-wide association studies (GWASs), as well as previously published PheWASs. We further leveraged the context of functional impact from protein-coding to regulatory regions, providing a deeper interpretation of these associations. The comprehensive nature of this PheWAS allows for novel hypothesis generation, the identification of phenotypes for further study for future phenotypic algorithm development, and identification of cross-phenotype associations.

Multiple sclerosis: genetics, biomarkers, treatments

PURPOSE OF REVIEW

We discuss new paradigms for understanding the immunopathology of multiple sclerosis through the recent development of high throughput genetic analysis, emergence of numerous candidate biomarkers, and the broadening of the treatment arsenal.

RECENT FINDINGS

The recent use of genome wide association studies provide new tools for a better understanding of multiple sclerosis etiology. Genome-wide association studies have identified many genes implicated in immune regulation and the next step will be to elucidate how those genetic variations influence immune cell function to drive disease development and progression. Furthermore, patient care has seen the emergence of new biomarkers for monitoring disease progression and response to treatment. Finally, the introduction of numerous immunomodulatory treatments will likely improve clinical outcome of multiple sclerosis patients in the future.

SUMMARY

Breakthroughs in the field of multiple sclerosis have led to a better understanding of the physiopathology of the disease, follow up, and treatment of the patients that develop relapsing remitting multiple sclerosis. The next challenge for multiple sclerosis will be to press forward to model and decipher multiple sclerosis progression, which will help both to develop therapeutics and generate knowledge about mechanisms of neurodegeneration.

Is There a Genetic Correlation between Multiple Sclerosis and Cerebral Aneurysms?

BACKGROUND

Multiple sclerosis (MS) is a common autoimmune and neurodegenerative disease of the central nervous system characterized by inflammatory demyelination, axonal degeneration, and neuronal loss. The exact pathogenesis of MS remains uncertain; however, studies have shown that the development of MS is influenced by genetic and environmental factors. Cerebral aneurysms (CAs) are life-threatening lesions of cerebral vessels characterized by a bulge in the intracranial arterial wall that spontaneously ruptures. It has been hypothesized that patients with MS are at increased risk of developing cerebral aneurysms. This hypothesis can be supported by analyzing the pathogenesis and genetics of the development of MS and CA. To our knowledge, no previous studies have shown an association between MS and CA.

CASE DESCRIPTION

In this report, we performed middle cerebral artery aneurysm clipping for two patients with MS who were referred to our clinic for CA in the bifurcation of middle cerebral artery that was found incidentally on magnetic resonance imaging. We aim to identify any genetic correlation between MS and CA pathogenesis.

CONCLUSION

This report suggests a possible genetic association between MS and CAs. The strongest evidence of association was found for the TNFRSF1A gene, a proinflammatory gene that is involved in mitogen-activated protein kinase (MAPK) and NF-Kappa B signaling pathways, and has been identified as a candidate gene in the development of MS. MAPKs were also found to be elevated in CAs.

Advances in the immunopathogenesis of multiple sclerosis

PURPOSE OF REVIEW

Recent studies indicate a role for immune dysregulation in the pathogenesis of multiple sclerosis, an inflammatory demyelinating and degenerative disease of the central nervous system. This review addresses the current mechanisms of immune dysregulation in the development of multiple sclerosis, including the impact of environmental risk factors on immunity in both multiple sclerosis and its animal models.

RECENT FINDINGS

CD4 T-helper (Th) cells have long been implicated as the main drivers of pathogenesis of multiple sclerosis. However, current studies indicate that multiple sclerosis is largely a heterogeneous disease process, which involves both innate and adaptive immune-mediated inflammatory mechanisms that ultimately contribute to demyelination and neurodegeneration. Therefore, B cells, CD8 T cells, and microglia/macrophages can also play an important role in the immunopathogenesis of multiple sclerosis apart from proinflammatory CD4 Th1/Th17 cell subsets. Furthermore, increasing evidence indicates that environmental risk factors, such as Vitamin D deficiency, Epstein-Barr virus, smoking, Western diet, and the commensal microbiota, influence the development of multiple sclerosis through interactions with genetic variants of multiple sclerosis, thus leading to the dysregulation of immune responses.

SUMMARY

A better understanding of immune-mediated mechanisms in the pathogenesis of multiple sclerosis and the contribution of environmental risk factors toward the development of multiple sclerosis will help further improve therapeutic approaches to prevent disease progression.

Genetic determinants of risk and progression in multiple sclerosis

Multiple sclerosis (MS) is an autoimmune disease that represents a primary cause of neurological disability in the young adult population. Converging evidence supports the importance of genetic determinants for MS etiology. However, with the exception of the major histocompatibility complex, their nature has been elusive for more than 20 years. In the last decade, the advent of large genome-wide association studies has significantly improved our understanding of the disease, leading to the golden era of MS genetic research. To date more than 110 genetic variants have been firmly associated to an increased risk of developing MS. A large part of these variants tag genes involved in the regulation of immune response and several of them are shared with other autoimmune diseases, suggesting a common etiological root for this class of disorders. Despite the impressive body of data obtained in the last years, we are still far from fully decoding MS genetic complexity. For example, we ignore how these genetic factors interact with each other and with the environment. Thus, the biggest challenge for the next era of MS research will consist in identifying and characterizing the molecular mechanisms and the cellular pathways in which these risk variants play a role.

Genome-wide association studies in neurology

Genome-wide association studies (GWAS) are a powerful tool for understanding the genetic underpinnings of human disease. In this article, we briefly review the role and findings of GWAS in common neurological diseases, including Stroke, Alzheimer's disease, Parkinson's disease, epilepsy, multiple sclerosis, migraine, amyotrophic lateral sclerosis, frontotemporal lobar degeneration, restless legs syndrome, intracranial aneurysm, human prion diseases and moyamoya disease. We then discuss the present and future implications of these findings with regards to disease prediction, uncovering basic biology, and the development of potential therapeutic agents.

Nerve conduction velocity is regulated by the inositol polyphosphate-4-phosphatase II gene

Impairment of nerve conduction is common in neurodegenerative and neuroinflammatory diseases such as multiple sclerosis (MS), and measurement of evoked potentials (visual, motor, or sensory) has been widely used for diagnosis and recently also as a prognostic marker for MS. We used a classical genetic approach to identify novel genes controlling nerve conduction. First, we used quantitative trait mapping in F2 progeny of B10/SJL mice to identify EAE31, a locus controlling latency of motor evoked potentials (MEPs) and clinical onset of experimental autoimmune encephalomyelitis. Then, by combining congenic mapping, in silico haplotype analyses, and comparative genomics we identified inositol polyphosphate-4-phosphatase, type II (Inpp4b) as the quantitative trait gene for EAE31. Sequence variants of Inpp4b (C/A, exon 13; A/C, exon 14) were identified as differing among multiple mouse strains and correlated with individual cortical MEP latency differences. To evaluate the functional relevance of the amino acid exchanges at positions S474R and H548P, we generated transgenic mice carrying the longer-latency allele (Inpp4b(474R/548P)) in the C57BL/6J background. Inpp4b(474R/548P) mice exhibited significantly longer cortical MEP latencies (4.5 ± 0.22 ms versus 3.7 ± 0.13 ms; P = 1.04 × 10(-9)), indicating that INPP4B regulates nerve conduction velocity. An association of an INPP4B polymorphism (rs13102150) with MS was observed in German and Spanish MS cohorts (3676 controls and 911 cases) (P = 8.8 × 10(-3)).

Multiple sclerosis genetics

Genome-wide association studies have revolutionised the genetic analysis of multiple sclerosis. Through international collaborative efforts involving tens of thousands of cases and controls, more than 100 associated common variants have now been identified. These variants consistently implicate genes associated with immunological processes, overwhelmingly lie in regulatory rather than coding regions, and are frequently associated with other autoimmune diseases. The functional implications of these associated variants are mostly unknown; however, early work has shown that several variants have effects on splicing that result in meaningful changes in the balance between different isoforms in relevant tissues. Including the well established risk attributable to variants in genes encoding human leucocyte antigens, only about a quarter of reported heritability can now be accounted for, suggesting that a substantial potential for further discovery remains.

Multiple sclerosis genetics

Familial aggregation and the studies of twins indicate that heredity contributes to multiple sclerosis (MS) risk. Immunologic studies of leukocyte antigens subsequently followed by gene-mapping techniques identified the primary MS susceptibility locus to be within the major histocompatibility complex (MHC). The primary risk allele is HLA-DRB1*15, although other alleles of this gene also influence MS susceptibility. Other genes within the MHC also contribute to MS susceptibility. Genome-wide association studies have identified over 50 additional common variants of genes across the genome. Estimates suggest that there may be as many as 200 genes involved in MS susceptibility. In addition to these common polymorphisms, studies have identified several rare risk alleles in some families. Interestingly, the majority of the genes identified have known immunologic functions and many contribute to the risk of inheriting other autoimmune diseases. Genetic variants in the vitamin D metabolic pathway have also been identified. That vitamin D contributes to MS susceptibility as both an environmental as well as genetic risk factor underscores the importance of this metabolic pathway in disease pathogenesis. Current efforts are focused on understanding how the myriad of genetic risk alleles interact within networks to influence MS risk at family level as well as within populations.

Next-generation sequencing in understanding complex neurological disease

Next-generation sequencing techniques have made vast quantities of data on human genomes and transcriptomes available to researchers. Huge progress has been made towards understanding the basis of many Mendelian neurological conditions, but progress has been considerably slower in complex neurological diseases (multiple sclerosis, migraine, Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and so on). The authors review current next-generation sequencing methodologies and present selected studies illustrating how these have been used to cast light on the genetic etiology of complex neurological diseases with specific focus on multiple sclerosis. The authors highlight particular pitfalls in next-generation sequencing experiments and speculate on both clinical and research applications of these sequencing platforms for complex neurological disorders in the future.

Contribution of genome-wide association studies to scientific research: a pragmatic approach to evaluate their impact

The factual value of genome-wide association studies (GWAS) for the understanding of multifactorial diseases is a matter of intense debate. Practical consequences for the development of more effective therapies do not seem to be around the corner. Here we propose a pragmatic and objective evaluation of how much new biology is arising from these studies, with particular attention to the information that can help prioritize therapeutic targets. We chose multiple sclerosis (MS) as a paradigm disease and assumed that, in pre-GWAS candidate-gene studies, the knowledge behind the choice of each gene reflected the understanding of the disease prior to the advent of GWAS. Importantly, this knowledge was based mainly on non-genetic, phenotypic grounds. We performed single-gene and pathway-oriented comparisons of old and new knowledge in MS by confronting an unbiased list of candidate genes in pre-GWAS association studies with those genes exceeding the genome-wide significance threshold in GWAS published from 2007 on. At the single gene level, the majority (94 out of 125) of GWAS-discovered variants had never been contemplated as plausible candidates in pre-GWAS association studies. The 31 genes that were present in both pre- and post-GWAS lists may be of particular interest in that they represent disease-associated variants whose pathogenetic relevance is supported at the phenotypic level (i.e. the phenotypic information that steered their selection as candidate genes in pre-GWAS association studies). As such they represent attractive therapeutic targets. Interestingly, our analysis shows that some of these variants are targets of pharmacologically active compounds, including drugs that are already registered for human use. Compared with the above single-gene analysis, at the pathway level GWAS results appear more coherent with previous knowledge, reinforcing some of the current views on MS pathogenesis and related therapeutic research. This study presents a pragmatic approach that helps interpret and exploit GWAS knowledge.

Genetic burden in multiple sclerosis families

A previous study using cumulative genetic risk estimations in multiple sclerosis (MS) successfully tracked the aggregation of susceptibility variants in multi-case and single-case families. It used a limited description of susceptibility loci available at the time (17 loci). Even though the full roster of MS risk genes remains unavailable, we estimated the genetic burden in MS families and assess its disease predictive power using up to 64 single-nucleotide polymorphism (SNP) markers according to the most recent literature. A total of 708 controls, 3251 MS patients and their relatives, as well as 117 twin pairs were genotyped. We validated the increased aggregation of genetic burden in multi-case compared with single-case families (P=4.14e-03) and confirm that these data offer little opportunity to accurately predict MS, even within sibships (area under receiver operating characteristic (AUROC)=0.59 (0.55, 0.53)). Our results also suggest that the primary progressive and relapsing-type forms of MS share a common genetic architecture (P=0.368; difference being limited to that corresponding to ± 2 typical MS-associated SNPs). We have confirmed the properties of individual genetic risk score in MS. Comparing with previous reference point for MS genetics (17 SNPs), we underlined the corrective consequences of the integration of the new findings from GWAS and meta-analysis.

Network-based multiple sclerosis pathway analysis with GWAS data from 15,000 cases and 30,000 controls

Multiple sclerosis (MS) is an inflammatory CNS disease with a substantial genetic component, originally mapped to only the human leukocyte antigen (HLA) region. In the last 5 years, a total of seven genome-wide association studies and one meta-analysis successfully identified 57 non-HLA susceptibility loci. Here, we merged nominal statistical evidence of association and physical evidence of interaction to conduct a protein-interaction-network-based pathway analysis (PINBPA) on two large genetic MS studies comprising a total of 15,317 cases and 29,529 controls. The distribution of nominally significant loci at the gene level matched the patterns of extended linkage disequilibrium in regions of interest. We found that products of genome-wide significantly associated genes are more likely to interact physically and belong to the same or related pathways. We next searched for subnetworks (modules) of genes (and their encoded proteins) enriched with nominally associated loci within each study and identified those modules in common between the two studies. We demonstrate that these modules are more likely to contain genes with bona fide susceptibility variants and, in addition, identify several high-confidence candidates (including BCL10, CD48, REL, TRAF3, and TEC). PINBPA is a powerful approach to gaining further insights into the biology of associated genes and to prioritizing candidates for subsequent genetic studies of complex traits.

Association of SNPs of CD40 gene with multiple sclerosis in Russians

Multiple sclerosis (MS) is a serious, incurable neurological disease. In 2009, the ANZgene studies detected the suggestive association of located upstream of CD40 gene in chromosome 20q13 (p = 1.3×10(-7)). Identification of the causal variant(s) in the CD40 locus leads to a better understanding of the mechanism underlying the development of autoimmune pathologies. We determined the genotypes of rs6074022, rs1883832, rs1535045, and rs11086996 in patients with MS (n = 1684) and in the control group (n = 879). Two SNPs were significantly associated with MS: rs6074022 (additive model C allele OR = 1.27, 95% CI = [1.12-1.45], p = 3×10(-4)) and rs1883832 (additive model T allele OR = 1.20, 95% CI = [1.05-1.38], p = 7×10(-3)). In the meta-analysis of our results and the results of four previous studies, we obtain the association p-value of 2.34×10(-12), which confirmed the association between MS and rs6074022 at a genome-wide significant level. Next, we demonstrated that the model including rs6074022 only sufficiently described the association. From our analysis, we can speculate that the association between rs1883832 and MS was induced by LD, whereas rs6074022 was a marker in stronger LD with the functional variant or was the functional variant itself. Our results indicated that the functional variants were located in the upstream region of the gene CD40 and were in higher LD with rs6074022 than LD with rs1883832.

Identification of shared genes and pathways: a comparative study of multiple sclerosis susceptibility, severity and response to interferon beta treatment

Recent genome-wide association studies (GWAS) have successfully identified several gene loci associated with multiple sclerosis (MS) susceptibility, severity or interferon-beta (IFN-ß) response. However, due to the nature of these studies, the functional relevance of these loci is not yet fully understood. We have utilized a systems biology based approach to explore the genetic interactomes of these MS related traits. We hypothesised that genes and pathways associated with the 3 MS related phenotypes might interact collectively to influence the heterogeneity and unpredictable clinical outcomes observed. Individual genetic interactomes for each trait were constructed and compared, followed by prioritization of common interactors based on their frequencies. Pathway enrichment analyses were performed to highlight shared functional pathways. Biologically relevant genes ABL1, GRB2, INPP5D, KIF1B, PIK3R1, PLCG1, PRKCD, SRC, TUBA1A and TUBA4A were identified as common to all 3 MS phenotypes. We observed that the highest number of first degree interactors were shared between MS susceptibility and MS severity (p = 1.34×10⁻⁷⁹) with UBC as the most prominent first degree interactor for this phenotype pair from the prioritisation analysis. As expected, pairwise comparisons showed that MS susceptibility and severity interactomes shared the highest number of pathways. Pathways from signalling molecules and interaction, and signal transduction categories were found to be highest shared pathways between 3 phenotypes. Finally, FYN was the most common first degree interactor in the MS drugs-gene network. By applying the systems biology based approach, additional significant information can be extracted from GWAS. Results of our interactome analyses are complementary to what is already known in the literature and also highlight some novel interactions which await further experimental validation. Overall, this study illustrates the potential of using a systems biology based approach in an attempt to unravel the biological significance of gene loci identified in large GWAS.

From Identification to Characterization of the Multiple Sclerosis Susceptibility Gene CLEC16A

Multiple sclerosis (MS) is an inflammatory, demyelinating disorder of the central nervous system that develops in genetically susceptible individuals, probably triggered by common environmental factors. Human leukocyte antigen (HLA) loci were early shown to confer the strongest genetic associations in MS. Now, more than 50 non-HLA MS susceptibility loci are identified, of which the majority are located in immune-regulatory genes. Single nucleotide polymorphisms (SNPs) in the C-type lectin-like domain family 16A (CLEC16A) gene were among the first non-HLA genetic variants that were confirmed to be associated with MS. Fine-mapping has indicated a primary association in MS and also other autoimmune diseases to intronic CLEC16A SNPs. Here, we review the identification of MS susceptibility variants in the CLEC16A gene region, functional studies of the CLEC16A molecule and the recent progress in understanding the implications thereof for MS development. This may serve as an example of the importance for further molecular investigation of the loci identified in genetic studies, with the aim to translate this knowledge into the clinic.

A genome-wide integrative genomic study localizes genetic factors influencing antibodies against Epstein-Barr virus nuclear antigen 1 (EBNA-1)

Infection with Epstein-Barr virus (EBV) is highly prevalent worldwide, and it has been associated with infectious mononucleosis and severe diseases including Burkitt lymphoma, Hodgkin lymphoma, nasopharyngeal lymphoma, and lymphoproliferative disorders. Although EBV has been the focus of extensive research, much still remains unknown concerning what makes some individuals more sensitive to infection and to adverse outcomes as a result of infection. Here we use an integrative genomics approach in order to localize genetic factors influencing levels of Epstein Barr virus (EBV) nuclear antigen-1 (EBNA-1) IgG antibodies, as a measure of history of infection with this pathogen, in large Mexican American families. Genome-wide evidence of both significant linkage and association was obtained on chromosome 6 in the human leukocyte antigen (HLA) region and replicated in an independent Mexican American sample of large families (minimum p-value in combined analysis of both datasets is 1.4×10(-15) for SNPs rs477515 and rs2516049). Conditional association analyses indicate the presence of at least two separate loci within MHC class II, and along with lymphocyte expression data suggest genes HLA-DRB1 and HLA-DQB1 as the best candidates. The association signals are specific to EBV and are not found with IgG antibodies to 12 other pathogens examined, and therefore do not simply reveal a general HLA effect. We investigated whether SNPs significantly associated with diseases in which EBV is known or suspected to play a role (namely nasopharyngeal lymphoma, Hodgkin lymphoma, systemic lupus erythematosus, and multiple sclerosis) also show evidence of associated with EBNA-1 antibody levels, finding an overlap only for the HLA locus, but none elsewhere in the genome. The significance of this work is that a major locus related to EBV infection has been identified, which may ultimately reveal the underlying mechanisms by which the immune system regulates infection with this pathogen.

Epistasis and immunity: the role of genetic interactions in autoimmune diseases

Autoimmune disorders are a complex and varied group of diseases that are caused by breakdown of self-tolerance. The aetiology of autoimmunity is multi-factorial, with both environmental triggers and genetically determined risk factors. In recent years, it has been increasingly recognized that genetic risk factors do not act in isolation, but rather the combination of individual additive effects, gene-gene interactions and gene-environment interactions determine overall risk of autoimmunity. The importance of gene-gene interactions, or epistasis, has been recently brought into focus, with research demonstrating that many autoimmune diseases, including rheumatic arthritis, autoimmune glomerulonephritis, systemic lupus erythematosus and multiple sclerosis, are influenced by epistatic interactions. This review sets out to examine the basic mechanisms of epistasis, how epistasis influences the immune system and the role of epistasis in two major autoimmune conditions, systemic lupus erythematosus and multiple sclerosis.

The genetics of multiple sclerosis: an up-to-date review

Multiple sclerosis (MS) is a prevalent inflammatory disease of the central nervous system that often leads to disability in young adults. Treatment options are limited and often only partly effective. The disease is likely caused by a complex interaction between multiple genes and environmental factors, leading to inflammatory-mediated central nervous system deterioration. A series of genomic studies have confirmed a central role for the immune system in the development of MS, including genetic association studies that have now dramatically expanded the roster of MS susceptibility genes beyond the longstanding human leukocyte antigen (HLA) association in MS first identified nearly 40 years ago. Advances in technology together with novel models for collaboration across research groups have enabled the discovery of more than 50 non-HLA genetic risk factors associated with MS. However, with a large proportion of the disease heritability still unaccounted for, current studies are now geared towards identification of causal alleles, associated pathways, epigenetic mechanisms, and gene-environment interactions. This article reviews recent efforts in addressing the genetics of MS and the challenges posed by an ever increasing amount of analyzable data, which is spearheading development of novel statistical methods necessary to cope with such complexity.

GWAS signals across the HLA regions: revealing a clue for common etiology underlying infectious tumors and other immunity diseases

Increasing evidence suggests that multiple genes in the human leukocyte antigen (HLA) regions play an important role in development of cancers and immunity disorders. However, the biological mechanisms of the HLA associations are not well understood. We recently conducted a survey of all genome-wide association studies (GWAS) with significant findings in the HLA regions and concluded that diseases such as cancer and immune disorders are more likely to be associated with genetic variants located in the HLA regions than other diseases. This finding is suggestive for testing a hypothesis of a common etiology of infectious tumors and other immunity diseases.

The genetics of multiple sclerosis: an up-to-date review

Multiple sclerosis (MS) is a prevalent inflammatory disease of the central nervous system that often leads to disability in young adults. Treatment options are limited and often only partly effective. The disease is likely caused by a complex interaction between multiple genes and environmental factors, leading to inflammatory-mediated central nervous system deterioration. A series of genomic studies have confirmed a central role for the immune system in the development of MS, including genetic association studies that have now dramatically expanded the roster of MS susceptibility genes beyond the longstanding human leukocyte antigen (HLA) association in MS first identified nearly 40 years ago. Advances in technology together with novel models for collaboration across research groups have enabled the discovery of more than 50 non-HLA genetic risk factors associated with MS. However, with a large proportion of the disease heritability still unaccounted for, current studies are now geared towards identification of causal alleles, associated pathways, epigenetic mechanisms, and gene-environment interactions. This article reviews recent efforts in addressing the genetics of MS and the challenges posed by an ever increasing amount of analyzable data, which is spearheading development of novel statistical methods necessary to cope with such complexity.

Multiple sclerosis

Multiple sclerosis (MS) is a multifocal demyelinating disease with progressive neurodegeneration caused by an autoimmune response to self-antigens in a genetically susceptible individual. While the formation and persistence of meningeal lymphoid follicles suggest persistence of antigens to drive the continuing inflammatory and humoral response, the identity of an antigen or infectious agent leading to the oligoclonal expansion of B and T cells is unknown. In this review we examine new paradigms for understanding the immunopathology of MS, present recent data defining the common genetic variants underlying disease susceptibility, and explore how improved understanding of immune pathway disruption can inform MS prognosis and treatment decisions.

Evaluation of nanofluidics technology for high-throughput SNP genotyping in a clinical setting

The current need for high-throughput genotyping platforms for targeted validation of disease-associated single nucleotide polymorphisms (SNPs) motivated us to evaluate a novel nanofluidics platform for genotyping DNA extracted from peripheral blood and buccal wash samples. SNP genotyping was performed using a Fluidigm 48.48 Dynamic Array biochip on the BioMark polymerase chain reaction platform and results were compared against standard TaqMan assays and DNA sequencing. Pilot runs using these dynamic arrays on 90 samples against 20 SNP assays had an average call rate of 99.7%, with 100% call rates for 16 of the assays. Manual TaqMan genotyping of these samples against three SNPs demonstrated 100% correlation between the two platforms. To understand the influence of DNA template variability, three sources of blood samples (CH-1, n = 20; CH-2, n = 47; KK, n = 47) and buccal washes (n = 37) were genotyped for 24 SNPs. Although both CH-1 and CH-2 batches showed good base calling (≥98.8%), the KK batch and buccal wash samples exhibited lower call rates (82.1% and 94.0%). Importantly, repurification of the KK and buccal wash samples resulted in significant improvements in their call rates (to ≥97.9%). Scale-up for genotyping 1698 cases and controls for 24 SNPs had overall call rates of 97.6% for KK and 99.2% for CH samples. The Dynamic Array approach demonstrated accuracy similar to that of TaqMan genotyping, while offering significant savings in DNA, effort, time, and costs.

Entering a new phase of multiple sclerosis genetic epidemiology

Multiple sclerosis (MS) is a complex disease, where multiple genetic variants have been found to influence the risk of development. The evidence for environmental-attributable risk is also strong, indicating an interaction of risk factors leading to the development of disease in the individual. An importance of genetic variation within the human leukocyte antigen (HLA) region has been known for almost 40 years, but the search for additional variants connected to susceptibility has been long and largely fruitless. Joint efforts of the MS research community in collecting and sharing results from genetic case control cohorts, together with the technical development, eventually lead to the identification of multiple risk factors for MS as in other complex diseases. The list of identified genetic variants associated with disease is increasingly growing and some leads for functional mechanisms are emerging. Many of the identified regions also harbor associations with other immune-mediated diseases, suggesting common etiology across these various diseases. The great challenge in front of us now is to translate these point-wise indications of genetic effects to functional understanding of how disease develops.

Revealing the genetic basis of multiple sclerosis: are we there yet?

For more than 30 years the only genetic factor associated with susceptibility to multiple sclerosis (MS) was the human leukocyte antigen (HLA) region. Recent advancements in genotyping platforms and the development of more effective statistical methods resulted in the identification of 16 more genes by genome-wide association studies (GWAS) in the last three years alone. While the effect of each of these genes is modest compared to that of HLA, this list is expected to grow significantly in the near future, thus defining a complex landscape in which susceptibility may be determined by a combination of allelic variants in different pathways according to ethnic background, disease sub-type, and specific environmental triggers. A considerable overlap of susceptibility genes among multiple autoimmune diseases is becoming evident and integration of these genetic variants with our current knowledge of affected biological pathways will greatly improve our understanding of mechanisms of general autoimmunity and of tissue specificity.