Ingrid Kockum

Variation in interleukin 7 receptor alpha chain (IL7R) influences risk of multiple sclerosis

Multiple sclerosis is a chronic, often disabling, disease of the central nervous system affecting more than 1 in 1,000 people in most western countries. The inflammatory lesions typical of multiple sclerosis show autoimmune features and depend partly on genetic factors. Of these genetic factors, only the HLA gene complex has been repeatedly confirmed to be associated with multiple sclerosis, despite considerable efforts. Polymorphisms in a number of non-HLA genes have been reported to be associated with multiple sclerosis, but so far confirmation has been difficult. Here, we report compelling evidence that polymorphisms in IL7R, which encodes the interleukin 7 receptor α chain (IL7Rα), indeed contribute to the non-HLA genetic risk in multiple sclerosis, demonstrating a role for this pathway in the pathophysiology of this disease. In addition, we report altered expression of the genes encoding IL7Rα and its ligand, IL7, in the cerebrospinal fluid compartment of individuals with multiple sclerosis.

Smoking and two human leukocyte antigen genes interact to increase the risk for multiple sclerosis

Both genetic and environmental factors display low or modest associations with multiple sclerosis. Hypothetically, gene-environment interactions may exert much stronger effects. In this study, we investigated potential interactions between genetic risk factors and smoking in relation to risk of developing multiple sclerosis. A population-based case-control study involving incident cases of multiple sclerosis (843 cases, 1209 controls) was performed in Sweden. Cases and controls were classified according to their smoking status and human leukocyte antigen DRB1 as well as human leukocyte antigen A genotypes. Subjects with different genotypes and smoking habits were compared with regard to incidence of multiple sclerosis, by calculating odds ratios with 95% confidence intervals employing logistic regression. The potential interaction between different genotypes, as well as between genotype and smoking, was evaluated by calculating attributable proportion due to interaction. A significant interaction between two genetic risk factors, carriage of human leukocyte antigen DRB1*15 and absence of human leukocyte antigen A*02, was observed among smokers whereas such an interaction was absent among non-smokers. There were considerable differences in odds ratios between the various groups. Compared with non-smokers with neither of the genetic risk factors, the odds ratio was 13.5 (8.1-22.6) for smokers with both genetic risk factors. The odds ratio for smokers without genetic risk was 1.4 (0.9-2.1) and the odds ratio for non-smokers with both genetic risk factors was 4.9 (3.6-6.6). Among those with both genetic risk factors, smoking increased the risk by a factor of 2.8 in comparison with a factor of 1.4 among those without the genetic risk factors. The risk of developing multiple sclerosis associated with human leukocyte antigen genotypes may be strongly influenced by smoking status. The findings are consistent with our hypothesis that priming of the immune response in the lungs may subsequently lead to multiple sclerosis in genetically susceptible people.

The expanding genetic overlap between multiple sclerosis and type I diabetes

Familial clustering of autoimmune disease is well recognized and raises the possibility that some susceptibility genes may predispose to autoimmunity in general. In light of this observation, it might be expected that some of the variants of established relevance in one autoimmune disease may also be relevant in other related conditions. On the basis of this hypothesis, we tested seven single nucleotide polymorphisms (SNPs) that are known to be associated with type I diabetes in a large multiple sclerosis data set consisting of 2369 trio families, 5737 cases and 10 296 unrelated controls. Two of these seven SNPs showed evidence of association with multiple sclerosis; that is rs12708716 from the CLEC16A gene (P=1.6 × 10−16) and rs763361 from the CD226 gene (P=5.4 × 10−8). These findings thereby identify two additional multiple sclerosis susceptibility genes and lend support to the notion of autoimmune susceptibility genes.

Cerebrospinal fluid CXCL13 in multiple sclerosis: a suggestive prognostic marker for the disease course

Background: Levels of CXCL13, a potent B-cell chemoattractant, are elevated in the cerebrospinal fluid (CSF) during multiple sclerosis (MS) and are associated with markers of MS activity. Levels decrease upon effective treatments. Objective: Here we validate the potential role of CSF CXCL13 as a biomarker for aspects of MS in a large amount of clinical material, the majority collected at early diagnostic work-up. Methods: CXCL13 was measured by ELISA in 837 subjects: relapsing–remitting MS (RRMS; n = 323), secondary progressive MS (SPMS; n = 40), primary progressive MS (PPMS; n = 24), clinically isolated syndrome (CIS; n = 79), other neurological diseases (ONDs; n = 181), ONDs with signs of inflammation or viral/bacterial infections (iONDs; n = 176) and healthy controls (n = 14). Results: Subjects with viral/bacterial infections had extremely high CXCL13 levels compared to all included groups (p < 0.0001). CXCL13 was otherwise significantly higher in MS compared to the remaining controls (p < 0.0001), and CIS (p < 0.01). A significant and positive correlation between CXCL13 and relapse rate, the results obtained for the Expanded Disability Status Scale (EDSS) and the number of lesions detected by MRI was demonstrated. CXCL13 was increased in CIS conversion to clinically definite MS (p < 0.001). Oligoclonal immunoglobulin band (OCB)-positive CIS or MS had significantly increased CXCL13 levels compared to OCB-negative CIS or MS (p < 0.001 and p < 0.0001, respectively). Conclusion: CXCL13 was associated with disease exacerbations and unfavourable prognosis in RRMS. Increased CXCL13 was not specific for MS since subjects with viral/bacterial infections exhibited even higher levels. High levels predicted CIS conversion to MS. We suggest that measurement of CSF CXCL13 can be part of the armamentarium in the diagnostic and prognostic work-up in MS and be of help in future treatment decisions.

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.

Interaction between adolescent obesity and HLA risk genes in the etiology of multiple sclerosis

Objective: We investigated potential interactions between human leukocyte antigen (HLA) genotype and body mass index (BMI) status in relation to the risk of developing multiple sclerosis (MS). Methods: We used 2 case-control studies, one with incident cases (1,510 cases, 2,017 controls) and one with prevalent cases (937 cases, 609 controls). Subjects with different genotypes and BMI were compared with regard to incidence of MS by calculating odds ratios (ORs) with 95% confidence intervals (CIs) employing logistic regression. Potential interactions between genotypes and BMI were evaluated by calculating the attributable proportion due to interaction. Results: In both cohorts, a significant interaction was observed between HLA-DRB1*15 and obesity, regardless of HLA-A*02 status. Similarly, there was a significant interaction between absence of A*02 and obesity, regardless of DRB1*15 status. In the incident cohort, obese subjects with the most susceptible genotype (carriage of DRB1*15 and absence of A*02) had an OR of 16.2 (95% CI 7.5–35.2) compared to nonobese subjects without the genetic risk factors. The corresponding OR in the prevalent study was 13.8 (95% CI 4.1–46.8). Conclusions: We observed striking interactions between BMI status and HLA genotype with regard to MS risk. Hypothetically, a low-grade inflammatory response inherent to obesity synergizes with the adaptive, HLA molecule–restricted arm of the immune system, causing MS. Prevention of adolescent obesity may thus lower the risk of developing MS, predominantly among people with a genetic susceptibility to the disease.

Epstein-Barr virus and multiple sclerosis: interaction with HLA.

Epstein-Barr virus (EBV) infection, history of infectious mononucleosis (IM) and HLA-A and DRB1 have all been proposed as risk factors for multiple sclerosis (MS). Our aim was to analyse possible interactions between antibodies against Epstein-Barr virus nuclear antigen 1 (EBNA1) or EBNA1 fragments, presence of DRB1*15 and absence of A*02. The study population includes newly diagnosed cases and matched controls. Interaction on the additive scale was calculated using attributable proportion due to interaction (AP), which is the proportion of the incidence among individuals exposed to two interacting factors that is attributable to the interaction per se. IM showed association with MS, odds ratio (OR)=1.89 (1.45–2.48% confidence interval (CI)), as did raised EBNA1 IgG OR=1.74 (1.38–2.18 95%CI). All EBNA1 fragment IgGs were associated with MS risk. However, EBNA1 fragment 385–420 IgG levels were more strongly associated to MS than total EBNA1 IgG, OR=3.60 (2.75–4.72 95%CI), and also interacted with both DRB1*15 and absence of A*02, AP 0.60 (0.45–0.76 95%CI) and AP 0.39 (0.18–0.61 95%CI), respectively. The observed interaction between HLA class I and II genotype and reactivity to EBV-related epitopes suggest that the mechanism through which HLA genes influence the risk of MS may, at least in part, involve the immune control of EBV infection.

Refining genetic associations in multiple sclerosis

Genome-wide association studies involve several hundred thousand markers and, even when quality control is scrupulous, are invariably confounded by residual uncorrected errors that can falsely inflate the apparent difference between cases and controls (so-called genomic inflation). As a consequence such studies inevitably generate false positives alongside genuine associations. By use of Bayesian logic and empirical data, the Wellcome Trust Case Control Consortium suggested that association studies in complex disease should involve at least 2000 cases and 2000 controls, at which level they predicted that p values of less than 5×10 −7 would more commonly signify true positives than false positives.

Class II HLA interactions modulate genetic risk for multiple sclerosis.

Association studies have greatly refined the understanding of how variation within the human leukocyte antigen (HLA) genes influences risk of multiple sclerosis. However, the extent to which major effects are modulated by interactions is poorly characterized. We analyzed high-density SNP data on 17,465 cases and 30,385 controls from 11 cohorts of European ancestry, in combination with imputation of classical HLA alleles, to build a high-resolution map of HLA genetic risk and assess the evidence for interactions involving classical HLA alleles. Among new and previously identified class II risk alleles (HLA-DRB1*15:01, HLA-DRB1*13:03, HLA-DRB1*03:01, HLA-DRB1*08:01 and HLA-DQB1*03:02) and class I protective alleles (HLA-A*02:01, HLA-B*44:02, HLA-B*38:01 and HLA-B*55:01), we find evidence for two interactions involving pairs of class II alleles: HLA-DQA1*01:01–HLA-DRB1*15:01 and HLA-DQB1*03:01–HLA-DQB1*03:02. We find no evidence for interactions between classical HLA alleles and non-HLA risk-associated variants and estimate a minimal effect of polygenic epistasis in modulating major risk alleles.

Hydrogeochemical changes before and after a major earthquake

Hydrogeochemical changes were detected by monitoring ice age meteoric waters before and after a magnitude (M) 5.8 earthquake on 16 September 2002 in the Tjornes Fracture Zone, northern Iceland. Significant Cu, Zn, Mn, and Cr anomalies reached our sampling station 1, 2, 5, and ≥10 weeks before the earthquake, respectively. By comparison with published experimental, geophysical, and geochemical studies, we suggest stress-induced source mixing and leakage of fluid from an external (hotter) basalt-hosted source reservoir, where fluid-rock interaction was more rapid. Rapid 12%–19% increases in the concentrations of B, Ca, K, Li, Mo, Na, Rb, S, Si, Sr, Cl, and SO 4 , and decreases in Na/Ca, δ 18 O, and δD, occurred 2–9 days after the earthquake. The rapidity of these changes is consistent with time scales of fault sealing due to coupled deformation and fluid flow. We interpret fluid-source switching in response to fault sealing and unsealing, with the newly tapped aquifer containing chemically and isotopically distinct ice age meteoric water. Variation in Na/Ca ratio appears to be sensitive to the changing stress state associated with M > 4 earthquakes. This study highlights the potential of hydrogeochemical change in earthquake-prediction studies.