Polygenic risk score association with multiple sclerosis susceptibility and phenotype in Europeans.

Polygenic inheritance plays a pivotal role in driving multiple sclerosis susceptibility, an inflammatory demyelinating disease of the CNS. We developed polygenic risk scores (PRS) of multiple sclerosis and assessed associations with both disease status and severity in cohorts of European descent. The largest genome-wide association dataset for multiple sclerosis to date (n = 41 505) was leveraged to generate PRS scores, serving as an informative susceptibility marker, tested in two independent datasets, UK Biobank [area under the curve (AUC) = 0.73, 95% confidence interval (CI): 0.72-0.74, P = 6.41 × 10-146] and Kaiser Permanente in Northern California (KPNC, AUC = 0.8, 95% CI: 0.76-0.82, P = 1.5 × 10-53). Individuals within the top 10% of PRS were at higher than 5-fold increased risk in UK Biobank (95% CI: 4.7-6, P = 2.8 × 10-45) and 15-fold higher risk in KPNC (95% CI: 10.4-24, P = 3.7 × 10-11), relative to the median decile. The cumulative absolute risk of developing multiple sclerosis from age 20 onwards was significantly higher in genetically predisposed individuals according to PRS. Furthermore, inclusion of PRS in clinical risk models increased the risk discrimination by 13% to 26% over models based only on conventional risk factors in UK Biobank and KPNC, respectively. Stratifying disease risk by gene sets representative of curated cellular signalling cascades, nominated promising genetic candidate programmes for functional characterization. These pathways include inflammatory signalling mediation, response to viral infection, oxidative damage, RNA polymerase transcription, and epigenetic regulation of gene expression to be among significant contributors to multiple sclerosis susceptibility. This study also indicates that PRS is a useful measure for estimating susceptibility within related individuals in multicase families. We show a significant association of genetic predisposition with thalamic atrophy within 10 years of disease progression in the UCSF-EPIC cohort (P < 0.001), consistent with a partial overlap between the genetics of susceptibility and end-organ tissue injury. Mendelian randomization analysis suggested an effect of multiple sclerosis susceptibility on thalamic volume, which was further indicated to be through horizontal pleiotropy rather than a causal effect. In summary, this study indicates important, replicable associations of PRS with enhanced risk assessment and radiographic outcomes of tissue injury, potentially informing targeted screening and prevention strategies.

Not all roads lead to the immune system: the genetic basis of multiple sclerosis severity.

Multiple sclerosis is a leading cause of neurological disability in adults. Heterogeneity in multiple sclerosis clinical presentation has posed a major challenge for identifying genetic variants associated with disease outcomes. To overcome this challenge, we used prospectively ascertained clinical outcomes data from the largest international multiple sclerosis registry, MSBase. We assembled a cohort of deeply phenotyped individuals of European ancestry with relapse-onset multiple sclerosis. We used unbiased genome-wide association study and machine learning approaches to assess the genetic contribution to longitudinally defined multiple sclerosis severity phenotypes in 1813 individuals. Our primary analyses did not identify any genetic variants of moderate to large effect sizes that met genome-wide significance thresholds. The strongest signal was associated with rs7289446 (ß = -0.4882, P = 2.73 × 10-7), intronic to SEZ6L on chromosome 22. However, we demonstrate that clinical outcomes in relapse-onset multiple sclerosis are associated with multiple genetic loci of small effect sizes. Using a machine learning approach incorporating over 62 000 variants together with clinical and demographic variables available at multiple sclerosis disease onset, we could predict severity with an area under the receiver operator curve of 0.84 (95% CI 0.79-0.88). Our machine learning algorithm achieved positive predictive value for outcome assignation of 80% and negative predictive value of 88%. This outperformed our machine learning algorithm that contained clinical and demographic variables alone (area under the receiver operator curve 0.54, 95% CI 0.48-0.60). Secondary, sex-stratified analyses identified two genetic loci that met genome-wide significance thresholds. One in females (rs10967273; ßfemale = 0.8289, P = 3.52 × 10-8), the other in males (rs698805; ßmale = -1.5395, P = 4.35 × 10-8), providing some evidence for sex dimorphism in multiple sclerosis severity. Tissue enrichment and pathway analyses identified an overrepresentation of genes expressed in CNS compartments generally, and specifically in the cerebellum (P = 0.023). These involved mitochondrial function, synaptic plasticity, oligodendroglial biology, cellular senescence, calcium and G-protein receptor signalling pathways. We further identified six variants with strong evidence for regulating clinical outcomes, the strongest signal again intronic to SEZ6L (adjusted hazard ratio 0.72, P = 4.85 × 10-4). Here we report a milestone in our progress towards understanding the clinical heterogeneity of multiple sclerosis outcomes, implicating functionally distinct mechanisms to multiple sclerosis risk. Importantly, we demonstrate that machine learning using common single nucleotide variant clusters, together with clinical variables readily available at diagnosis can improve prognostic capabilities at diagnosis, and with further validation has the potential to translate to meaningful clinical practice change.

Non-parametric Polygenic Risk Prediction via Partitioned GWAS Summary Statistics.

In complex trait genetics, the ability to predict phenotype from genotype is the ultimate measure of our understanding of genetic architecture underlying the heritability of a trait. A complete understanding of the genetic basis of a trait should allow for predictive methods with accuracies approaching the trait's heritability. The highly polygenic nature of quantitative traits and most common phenotypes has motivated the development of statistical strategies focused on combining myriad individually non-significant genetic effects. Now that predictive accuracies are improving, there is a growing interest in the practical utility of such methods for predicting risk of common diseases responsive to early therapeutic intervention. However, existing methods require individual-level genotypes or depend on accurately specifying the genetic architecture underlying each disease to be predicted. Here, we propose a polygenic risk prediction method that does not require explicitly modeling any underlying genetic architecture. We start with summary statistics in the form of SNP effect sizes from a large GWAS cohort. We then remove the correlation structure across summary statistics arising due to linkage disequilibrium and apply a piecewise linear interpolation on conditional mean effects. In both simulated and real datasets, this new non-parametric shrinkage (NPS) method can reliably allow for linkage disequilibrium in summary statistics of 5 million dense genome-wide markers and consistently improves prediction accuracy. We show that NPS improves the identification of groups at high risk for breast cancer, type 2 diabetes, inflammatory bowel disease, and coronary heart disease, all of which have available early intervention or prevention treatments.

The CYP24A1 gene variant rs2762943 is associated with low serum 1,25-dihydroxyvitamin D levels in multiple sclerosis patients.

BACKGROUND AND PURPOSE: Vitamin D is considered to play a role in multiple sclerosis (MS) etiopathogenesis. A polymorphism in the CYP24A1 gene, rs2762943, was recently identified that was associated with an increased MS risk. CYP24A1 encodes a protein involved in the catabolism of the active form of vitamin D. The immunological effects of carrying the rs2762943 risk allele were investigated, as well as its role as genetic modifier. METHODS: Serum levels of 25-hydroxyvitamin D and 1,25-dihydroxyvitamin D (1,25(OH)2 D) were measured in a cohort of 167 MS patients. In a subgroup of patients, expression levels of major histocompatibility complex class II and co-stimulatory molecules were determined by flow cytometry, and serum levels of pro-inflammatory (interferon gamma, granulocyte macrophage colony-stimulating factor, C-X-C motif chemokine ligand 13) and anti-inflammatory (interleukin 10) cytokines and neurofilament light chain were measured by single-molecule array assays. The effect of the rs2762943 polymorphism on disease activity and disability measures was evaluated in 340 MS patients. RESULTS: Compared to non-carriers, carriers of the rs2762943 risk allele were characterized by reduced levels of 1,25(OH)2 D (p = 0.0001) and elevated levels of interferon gamma (p = 0.03) and granulocyte macrophage colony-stimulating factor (p = 0.008), whereas no significant differences were observed for the other markers. The presence of the rs2762943 risk allele had no significant impact on disease activity and disability outcomes during follow-up. However, risk allele carriers were younger at disease onset (p = 0.04). CONCLUSIONS: These findings suggest that the CYP24A1 rs2762943 polymorphism plays a more important role in MS susceptibility than in disease prognosis and is associated with lower 1,25(OH)2 D levels and a heightened pro-inflammatory environment in MS patients.

Genetic and epigenetic fine mapping of causal autoimmune disease variants.

Genome-wide association studies have identified loci underlying human diseases, but the causal nucleotide changes and mechanisms remain largely unknown. Here we developed a fine-mapping algorithm to identify candidate causal variants for 21 autoimmune diseases from genotyping data. We integrated these predictions with transcription and cis-regulatory element annotations, derived by mapping RNA and chromatin in primary immune cells, including resting and stimulated CD4(+) T-cell subsets, regulatory T cells, CD8(+) T cells, B cells, and monocytes. We find that ∼90% of causal variants are non-coding, with ∼60% mapping to immune-cell enhancers, many of which gain histone acetylation and transcribe enhancer-associated RNA upon immune stimulation. Causal variants tend to occur near binding sites for master regulators of immune differentiation and stimulus-dependent gene activation, but only 10-20% directly alter recognizable transcription factor binding motifs. Rather, most non-coding risk variants, including those that alter gene expression, affect non-canonical sequence determinants not well-explained by current gene regulatory models.

Mother-child histocompatibility and risk of rheumatoid arthritis and systemic lupus erythematosus among mothers.

The study objective was to test the hypothesis that having histocompatible children increases the risk of rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), possibly by contributing to the persistence of fetal cells acquired during pregnancy. We conducted a case control study using data from the UC San Francisco Mother Child Immunogenetic Study and studies at the Inova Translational Medicine Institute. We imputed human leukocyte antigen (HLA) alleles and minor histocompatibility antigens (mHags). We created a variable of exposure to histocompatible children. We estimated an average sequence similarity matching (SSM) score for each mother based on discordant mother-child alleles as a measure of histocompatibility. We used logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals. A total of 138 RA, 117 SLE, and 913 control mothers were analyzed. Increased risk of RA was associated with having any child compatible at HLA-B (OR 1.9; 1.2-3.1), DPB1 (OR 1.8; 1.2-2.6) or DQB1 (OR 1.8; 1.2-2.7). Compatibility at mHag ZAPHIR was associated with reduced risk of SLE among mothers carrying the HLA-restriction allele B*07:02 (n = 262; OR 0.4; 0.2-0.8). Our findings support the hypothesis that mother-child histocompatibility is associated with risk of RA and SLE.

Targeted resequencing reveals rare variants enrichment in multiple sclerosis susceptibility genes.

Although genome-wide association studies have identified a number of common variants associated with multiple sclerosis (MS) susceptibility, little is known about the relevance of rare variants. Here, we aimed to explore the role of rare variants in 14 MS risk genes (FCRL1, RGS1, TIMMDC1, HHEX, CXCR5, LTBR, TSFM, GALC, TRAF3, STAT3, TNFSF14, IFI30, CD40, and CYP24A1) by targeted resequencing in an Iberian population of 524 MS cases and 546 healthy controls. Four rare variants-enriched regions within CYP24A1, FCRL1, RGS1, and TRAF3 were identified as significantly associated with MS. Functional studies revealed significantly decreased regulator of G protein signaling 1 (RGS1) gene expression levels in peripheral blood mononuclear cells from MS patients with RGS1 rare variants compared to noncarriers, whereas no significant differences in gene expression were observed for CYP24A1, FCRL1, and TRAF3 between rare variants carriers and noncarriers. Immunophenotyping showed significant decrease in RGS1 expression in peripheral blood B lymphocytes from MS patients with RGS1 rare variants relative to noncarriers. Lastly, peripheral blood mononuclear cell from MS patients carrying RGS1 rare variants showed significantly lower induction of RGS1 gene expression by interferon-ß compared to MS patients lacking RGS1 variants. The presence of rare variants in RGS1 reinforce the ideas of high genetic heterogeneity and a role of rare variants in MS pathogenesis.

Loss of LDAH associated with prostate cancer and hearing loss.

Great strides in gene discovery have been made using a multitude of methods to associate phenotypes with genetic variants, but there still remains a substantial gap between observed symptoms and identified genetic defects. Herein, we use the convergence of various genetic and genomic techniques to investigate the underpinnings of a constellation of phenotypes that include prostate cancer (PCa) and sensorineural hearing loss (SNHL) in a human subject. Through interrogation of the subject's de novo, germline, balanced chromosomal translocation, we first identify a correlation between his disorders and a poorly annotated gene known as lipid droplet associated hydrolase (LDAH). Using data repositories of both germline and somatic variants, we identify convergent genomic evidence that substantiates a correlation between loss of LDAH and PCa. This correlation is validated through both in vitro and in vivo models that show loss of LDAH results in increased risk of PCa and, to a lesser extent, SNHL. By leveraging convergent evidence in emerging genomic data, we hypothesize that loss of LDAH is involved in PCa and other phenotypes observed in support of a genotype-phenotype association in an n-of-one human subject.

Genetic and gene expression signatures in multiple sclerosis.

Multiple sclerosis (MS) exhibits a well-documented increased incidence in individuals with respective family history, that is, is a heritable disease. In the last decade, genome-wide association studies have enabled the agnostic interrogation of the whole genome at a large scale. To date, over 200 genetic associations have been described at the strict level of genome-wide significance. Our current understanding of MS genetics can explain up to half of the disease's heritability, raising the important question of whether this is enough information to leverage toward improving diagnosis in MS. Parallel advancements in technologies that allow the characterization of the full transcriptome down to the single-cell level have enabled the generation of an unprecedented wealth of information. Transcriptional changes of putative causal cells could be utilized to identify early signs of disease onset. These recent findings in genetics and genomics, coupled with new technologies and deeply phenotyped cohorts, have the potential to improve the diagnosis of MS.

Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores.

Polygenic risk scores have shown great promise in predicting complex disease risk and will become more accurate as training sample sizes increase. The standard approach for calculating risk scores involves linkage disequilibrium (LD)-based marker pruning and applying a p value threshold to association statistics, but this discards information and can reduce predictive accuracy. We introduce LDpred, a method that infers the posterior mean effect size of each marker by using a prior on effect sizes and LD information from an external reference panel. Theory and simulations show that LDpred outperforms the approach of pruning followed by thresholding, particularly at large sample sizes. Accordingly, predicted R(2) increased from 20.1% to 25.3% in a large schizophrenia dataset and from 9.8% to 12.0% in a large multiple sclerosis dataset. A similar relative improvement in accuracy was observed for three additional large disease datasets and for non-European schizophrenia samples. The advantage of LDpred over existing methods will grow as sample sizes increase.

A non-synonymous single-nucleotide polymorphism associated with multiple sclerosis risk affects the EVI5 interactome.

Despite recent progress in the characterization of genetic loci associated with multiple sclerosis (MS) risk, the ubiquitous linkage disequilibrium operating across the genome has stalled efforts to distinguish causative variants from proxy single-nucleotide polymorphisms (SNPs). Here, we have identified through fine mapping and meta-analysis EVI5 as the most plausible disease risk gene within the 1p22.1 locus. We further show that an exonic SNP associated with risk induces changes in superficial hydrophobicity patterns of the coiled-coil domain of EVI5, which, in turns, affects the EVI5 interactome. Immunoprecipitation of wild-type and mutated EVI5 followed by mass spectrometry generated a roster of disease-specific interactors functionally linked to lipid metabolism. Among the exclusive binding partners of the risk variant, we describe the novel interaction with sphingosine 1-phosphate lyase (SGPL1)-a key enzyme for the creation of the sphingosine-1 phosphate gradient, which is relevant to the pathogenic process and therapeutic management of MS.

Increased risk of rheumatoid arthritis among mothers with children who carry DRB1 risk-associated alleles.

OBJECTIVE: To investigate whether a child's genotype affects a mother's risk of rheumatoid arthritis (RA) beyond the risk associated with her genotype and to test whether exposure to fetal alleles inherited from the father increases risk of RA among mothers without risk alleles. METHODS: A case-control study was conducted among 1165 mothers (170 cases/995 controls) and their respective 1482 children. We tested the association between having any child with alleles encoding amino acids (AAs) associated with RA including the 'shared epitope' (SE) and DERAA AA sequences at positions 70-74; AA valine, lysine and alanine at positions 11, 71 and 74 of HLA-DRB1; aspartic acid at position 9 of HLA-B and phenylalanine at position 9 of DPB1. We used logistic regression models to estimate OR and 95% CI for each group of alleles, adjusting for maternal genotype and number of live births. RESULTS: We found increased risk of RA among mothers who had any child with SE (OR 3.0; 95% CI 2.0 to 4.6); DERAA (OR 1.7; 95% CI 1.1 to 2.6); or valine (OR 2.3; 95% CI 1.6 to 3.5), lysine (OR 2.3; 95% CI 1.5 to 3.4) and alanine (OR 2.8; 95% CI 1.2 to 6.4) at DRB1 positions 11, 71 and 74, respectively. Among non-carrier mothers, increased risk of RA was associated with having children who carried DERAA (OR 1.7; 95% CI 1.0 to 2.7) and alleles encoding lysine at DRB1 position 71 (OR 2.3; 95% CI 1.5 to 4.8). CONCLUSION: Findings support the hypothesis that a child's genotype can contribute independently to risk of RA among mothers.

Genetic risk and a primary role for cell-mediated immune mechanisms in multiple sclerosis.

Multiple sclerosis is a common disease of the central nervous system in which the interplay between inflammatory and neurodegenerative processes typically results in intermittent neurological disturbance followed by progressive accumulation of disability. Epidemiological studies have shown that genetic factors are primarily responsible for the substantially increased frequency of the disease seen in the relatives of affected individuals, and systematic attempts to identify linkage in multiplex families have confirmed that variation within the major histocompatibility complex (MHC) exerts the greatest individual effect on risk. Modestly powered genome-wide association studies (GWAS) have enabled more than 20 additional risk loci to be identified and have shown that multiple variants exerting modest individual effects have a key role in disease susceptibility. Most of the genetic architecture underlying susceptibility to the disease remains to be defined and is anticipated to require the analysis of sample sizes that are beyond the numbers currently available to individual research groups. In a collaborative GWAS involving 9,772 cases of European descent collected by 23 research groups working in 15 different countries, we have replicated almost all of the previously suggested associations and identified at least a further 29 novel susceptibility loci. Within the MHC we have refined the identity of the HLA-DRB1 risk alleles and confirmed that variation in the HLA-A gene underlies the independent protective effect attributable to the class I region. Immunologically relevant genes are significantly overrepresented among those mapping close to the identified loci and particularly implicate T-helper-cell differentiation in the pathogenesis of multiple sclerosis.

Functional variations modulating PRKCA expression and alternative splicing predispose to multiple sclerosis.

The protein kinase C alpha (PRKCA) gene, encoding a Th17-cell-selective kinase, was repeatedly associated with multiple sclerosis (MS), but the underlying pathogenic mechanism remains unknown. We replicated the association in Italians (409 cases, 723 controls), identifying a protective signal in the PRKCA promoter (P = 0.033), and a risk haplotype in intron 3 (P = 7.7 × 10(-4); meta-analysis with previously published data: P = 4.01 × 10(-8)). Expression experiments demonstrated that the protective signal is associated with alleles conferring higher PRKCA expression levels, well fitting our observation that MS patients have significantly lower PRKCA mRNA levels in blood. The risk haplotype was shown to be driven by a GGTG ins/del polymorphism influencing the heterogeneous nuclear ribonucleoprotein H-dependent inclusion/skipping of a PRKCA alternative exon 3*. Indeed, exon 3* can be present in two different versions in PRKCA mRNAs (out-of-frame 61 bp or in-frame 66 bp long), and is preferentially included in transcripts generated through a premature polyadenylation event. The GGTG insertion downregulates 3* inclusion and shifts splicing towards the 66 bp isoform. Both events reduce the nonsense-mediated mRNA-decay-induced degradation of exon 3*-containing mRNAs. Since we demonstrated that the protein isoform produced through premature polyadenylation aberrantly localizes to the plasma membrane and/or in cytoplasmic clusters, dysregulated PRKCA 3* inclusion may represent an additional mechanism relevant to MS susceptibility.

No evidence for shared genetic basis of common variants in multiple sclerosis and amyotrophic lateral sclerosis.

Genome-wide association studies have been successful in identifying common variants that influence the susceptibility to complex diseases. From these studies, it has emerged that there is substantial overlap in susceptibility loci between diseases. In line with those findings, we hypothesized that shared genetic pathways may exist between multiple sclerosis (MS) and amyotrophic lateral sclerosis (ALS). While both diseases may have inflammatory and neurodegenerative features, epidemiological studies have indicated an increased co-occurrence within individuals and families. To this purpose, we combined genome-wide data from 4088 MS patients, 3762 ALS patients and 12 030 healthy control individuals in whom 5 440 446 single-nucleotide polymorphisms (SNPs) were successfully genotyped or imputed. We tested these SNPs for the excess association shared between MS and ALS and also explored whether polygenic models of SNPs below genome-wide significance could explain some of the observed trait variance between diseases. Genome-wide association meta-analysis of SNPs as well as polygenic analyses fails to provide evidence in favor of an overlap in genetic susceptibility between MS and ALS. Hence, our findings do not support a shared genetic background of common risk variants in MS and ALS.

Association of Parkinson disease with structural and regulatory variants in the HLA region.

Historically, association of disease with the major histocompatibility complex (HLA) genes has been tested with HLA alleles that encode antigen-binding affinity. The association with Parkinson disease (PD), however, was discovered with noncoding SNPs in a genome-wide association study (GWAS). We show here that several HLA-region SNPs that have since been associated with PD form two blocks tagged by rs3129882 (p = 9 × 10(-11)) and by rs9268515 and/or rs2395163 (p = 3 × 10(-11)). We investigated whether these SNP-associations were driven by HLA-alleles at adjacent loci. We imputed class I and class II HLA-alleles for 2000 PD cases and 1986 controls from the NeuroGenetics Research Consortium GWAS and sequenced a subset of 194 cases and 204 controls. We were therefore able to assess accuracy of two imputation algorithms against next-generation-sequencing while taking advantage of the larger imputed data sets for disease study. Additionally, we imputed HLA alleles for 843 cases and 856 controls from another GWAS for replication. PD risk was positively associated with the B(∗)07:02_C(∗)07:02_DRB5(∗)01_DRB1(∗)15:01_DQA1(∗)01:02_DQB1(∗)06:02 haplotype and negatively associated with the C(∗)03:04, DRB1(∗)04:04 and DQA1(∗)03:01 alleles. The risk haplotype and DQA1(∗)03:01 lost significance when conditioned on the SNPs, but C(∗)03:04 (OR = 0.72, p = 8 × 10(-6)) and DRB1(∗)04:04 (OR = 0.65, p = 4 × 10(-5)) remained significant. Similarly, rs3129882 and the closely linked rs9268515 and rs2395163 remained significant irrespective of HLA alleles. rs3129882 and rs2395163 are expression quantitative trait loci (eQTLs) for HLA-DR and HLA-DQ (9 × 10(-5) ≥ PeQTL ≥ 2 × 10(-79)), suggesting that HLA gene expression might influence PD. Our data suggest that PD is associated with both structural and regulatory elements in HLA. Furthermore, our study demonstrates that noncoding SNPs in the HLA region can be associated with disease irrespective of HLA alleles, and that observed associations with HLA alleles can sometimes be secondary to a noncoding variant.

A Child's HLA-DRB1 genotype increases maternal risk of systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) disproportionately affects women of reproductive age. During pregnancy, women are exposed to various sources of fetal material possibly constituting a significant immunologic exposure relevant to the development of SLE. The objective of this study was to investigate whether having any children who carry DRB1 alleles associated with SLE increase the risk of maternal SLE. This case-control study is based on the University of California, San Francisco Mother-Child Immunogenetic Study and from studies at the Inova Translational Medicine Institute. Analyses were conducted using data for 1304 mothers (219 cases/1085 controls) and their respective 1664 children. We selected alleles based on their known association with risk of SLE (DRB1*03:01, *15:01, or *08:01) or Epstein-Barr virus (EBV) glycoproteins (*04:01) due to the established EBV association with SLE risk. We used logistic regression models to estimate odds ratios (OR) and 95% confidence intervals (CI) for each allele of interest, taking into account maternal genotype and number of live births. We found an increase in risk of maternal SLE associated with exposure to children who inherited DRB1*04:01 from their father (OR 1.9; 95% CI, 1.1-3.2), among *04:01 allele-negative mothers. Increased risk was only present among mothers who were positive for one or more SLE risk-associated alleles (*03:01, *15:01 and/or *08:01). We did not find increased risk of maternal SLE associated with any other tested allele. These findings support the hypothesis that a child's alleles inherited from the father influence a mother's subsequent risk of SLE.

A pharmacogenetic study implicates SLC9a9 in multiple sclerosis disease activity.

OBJECTIVE: A proportion of multiple sclerosis (MS) patients experience disease activity despite treatment. The early identification of the most effective drug is critical to impact long-term outcome and to move toward a personalized approach. The aim of the present study is to identify biomarkers for further clinical development and to yield insights into the pathophysiology of disease activity. METHODS: We performed a genome-wide association study in interferon-ß (IFNß)-treated MS patients followed by validation in 3 independent cohorts. The role of the validated variant was examined in several RNA data sets, and the function of the presumed target gene was explored using an RNA interference approach in primary T cells in vitro. RESULTS: We found an association between rs9828519(G) and nonresponse to IFNß (pdiscovery = 4.43 × 10(-8)) and confirmed it in a meta-analysis across 3 replication data sets (preplication = 7.78 × 10(-4)). Only 1 gene is found in the linkage disequilibrium block containing rs9828519: SLC9A9. Exploring the function of this gene, we see that SLC9A9 mRNA expression is diminished in MS subjects who are more likely to have relapses. Moreover, SLC9A9 knockdown in T cells in vitro leads an increase in expression of IFNγ, which is a proinflammatory molecule. INTERPRETATION: This study identifies and validates the role of rs9828519, an intronic variant in SLC9A9, in IFNß-treated subjects, demonstrating a successful pharmacogenetic screen in MS. Functional characterization suggests that SLC9A9, an Na(+) -H(+) exchanger found in endosomes, appears to influence the differentiation of T cells to a proinflammatory fate and may have a broader role in MS disease activity, outside of IFNß treatment.

Genetic loci for Epstein-Barr virus nuclear antigen-1 are associated with risk of multiple sclerosis.

BACKGROUND: Infection with the Epstein-Barr virus (EBV) is associated with an increased risk of multiple sclerosis (MS). OBJECTIVE: We sought genetic loci influencing EBV nuclear antigen-1 (EBNA-1) IgG titers and hypothesized that they may play a role in MS risk. METHODS: We performed a genome-wide association study (GWAS) of anti-EBNA-1 IgG titers in 3599 individuals from an unselected twin family cohort, followed by a meta-analysis with data from an independent EBNA-1 GWAS. We then examined the shared polygenic risk between the EBNA-1 GWAS (effective sample size (Neff) = 5555) and a large MS GWAS (Neff = 15,231). RESULTS: We identified one locus of strong association within the human leukocyte antigen (HLA) region, of which the most significantly associated genotyped single nucleotide polymorphism (SNP) was rs2516049 (p = 4.11 × 10-9). A meta-analysis including data from another EBNA-1 GWAS in a cohort of Mexican-American families confirmed that rs2516049 remained the most significantly associated SNP (p = 3.32 × 10-20). By examining the shared polygenic risk, we show that the genetic risk for elevated anti-EBNA-1 titers is positively correlated with the development of MS, and that elevated EBNA-1 titers are not an epiphenomena secondary to MS. In the joint meta-analysis of EBNA-1 titers and MS, loci at 1p22.1, 3p24.1, 3q13.33, and 10p15.1 reached genome-wide significance (p < 5 × 10-8). CONCLUSIONS: Our results suggest that apart from the confirmed HLA region, the association of anti-EBNA-1 IgG titer with MS risk is also mediated through non-HLA genes, and that studies aimed at identifying genetic loci influencing EBNA immune response provides a novel opportunity to identify new and characterize existing genetic risk factors for MS.