Lisa F. Barcellos

Interleukin 7 receptor α chain ( IL7R ) shows allelic and functional association with multiple sclerosis

Multiple sclerosis is a demyelinating neurodegenerative disease with a strong genetic component. Previous genetic risk studies have failed to identify consistently linked regions or genes outside of the major histocompatibility complex on chromosome 6p. We describe allelic association of a polymorphism in the gene encoding the interleukin 7 receptor α chain ( IL7R ) as a significant risk factor for multiple sclerosis in four independent family-based or case-control data sets (overall P = 2.9 × 10−7). Further, the likely causal SNP, rs6897932, located within the alternatively spliced exon 6 of IL7R, has a functional effect on gene expression. The SNP influences the amount of soluble and membrane-bound isoforms of the protein by putatively disrupting an exonic splicing silencer.

Association mapping of disease loci, by use of a pooled DNA genomic screen.

Genomic screening to map disease loci by association requires automation, pooling of DNA samples, and 3,000-6,000 highly polymorphic, evenly spaced microsatellite markers. Case-control samples can be used in an initial screen, followed by family-based data to confirm marker associations. Association mapping is relevant to genetic studies of complex diseases in which linkage analysis may be less effective and to cases in which multigenerational data are difficult to obtain, including rare or late-onset conditions and infectious diseases. The method can also be used effectively to follow up and confirm regions identified in linkage studies or to investigate candidate disease loci. Study designs can incorporate disease heterogeneity and interaction effects by appropriate subdivision of samples before screening. Here we report use of pooled DNA amplifications-the accurate determination of marker-disease associations for both case-control and nuclear family-based data-including application of correction methods for stutter artifact and preferential amplification. These issues, combined with a discussion of both statistical power and experimental design to define the necessary requirements for detecting of disease loci while virtually eliminating false positives, suggest the feasibility and efficiency of association mapping using pooled DNA screening.

A second major histocompatibility complex susceptibility locus for multiple sclerosis

Variation in the major histocompatibility complex (MHC) on chromosome 6p21 is known to influence susceptibility to multiple sclerosis with the strongest effect originating from the HLA‐DRB1 gene in the class II region. The possibility that other genes in the MHC independently influence susceptibility to multiple sclerosis has been suggested but remains unconfirmed.

Clustering of autoimmune diseases in families with a high-risk for multiple sclerosis: a descriptive study

BACKGROUND Autoimmune mechanisms are thought to have a major role in the pathogenesis of multiple sclerosis. We aimed to identify coexisting autoimmune phenotypes in patients with multiple sclerosis from families with several members with the disease and in their first-degree relatives. METHODS A total of 176 families (386 individuals and 1107 first-degree relatives) were characterised for a history of other autoimmune disorders. Family-based or case-control analyses were done to assess the association of cytotoxic T-lymphocyte-antigen 4 (CTLA4) and protein tyrosine phosphatase (PTPN22) variants with susceptibility to multiple sclerosis. FINDINGS 46 (26%) index cases reported at least one coexisting autoimmune disorder. The most common were Hashimoto thyroiditis (10%), psoriasis (6%), inflammatory bowel disease (3%), and rheumatoid arthritis (2%). 112 (64%) families with a history of multiple sclerosis reported autoimmune disorders (excluding multiple sclerosis) in one or more first-degree relatives, whereas 64 (36%) families reported no history of autoimmunity. Similar to index cases, Hashimoto thyroiditis, psoriasis, and inflammatory bowel disease were also the most common disorders occurring in family members. A common variant within CTLA4 was strongly associated with multiple sclerosis in families who had other autoimmune diseases (p=0.009) but not in families without a history of other autoimmune disorders (p=0.90). INTERPRETATION The presence of various immune disorders in families with several members with multiple sclerosis suggests that the disease might arise on a background of a generalised susceptibility to autoimmunity. This distinct multiple-sclerosis phenotype, defined by its association with other autoimmune diseases, segregates with specific genotypes that could underlie the common susceptibility.

Genome-Wide Pharmacogenomic Analysis of the Response to Interferon Beta Therapy in Multiple Sclerosis

OBJECTIVE To identify promising candidate genes linked to interindividual differences in the efficacy of interferon beta therapy. Recombinant interferon beta therapy is widely used to reduce disease activity in multiple sclerosis (MS). However, up to 50% of patients continue to have relapses and worsening disability despite therapy. DESIGN We used a genome-wide pharmacogenomic approach to identify single-nucleotide polymorphism (SNP) allelic differences associated with interferon beta therapy response. SETTING Four collaborating centers in the Mediterranean Basin. Data Coordination Center at the University of California, San Francisco. PATIENTS A cohort of 206 patients with relapsing-remitting MS followed up prospectively for 2 years after initiation of treatment. INTERVENTION DNA was pooled and hybridized to Affymetrix 100K GeneChips. Pooling schemes were designed to minimize confounding batch effects and increase confidence by technical replication. MAIN OUTCOME MEASURES Single-nucleotide polymorphism detection. Comparison of allelic frequencies between good responders and nonresponders to interferon beta therapy. RESULTS A multianalytical approach detected significant associations between several SNPs and treatment response, which were validated by individual DNA genotyping on an independent platform. After the validation stage was complete, 81 additional individuals were added to the analysis to increase power. We found that responders and nonresponders had significantly different genotype frequencies for SNPs located in many genes, including glypican 5, collagen type XXV alpha1, hyaluronan proteoglycan link protein, calpastatin, and neuronal PAS domain protein 3. CONCLUSIONS The reported results address the question of genetic heterogeneity in MS and the response to immunotherapy by analysis of the correlation between different genotypes and clinical response to interferon beta therapy. Many of the detected differences between responders and nonresponders were genes associated with ion channels and signal transduction pathways. The study also suggests that genetic variants in heparan sulfate proteoglycan genes may be of clinical interest in MS as predictors of the response to therapy. In addition to new insights into the mechanistic biology of interferon beta, these results help define the molecular basis of interferon beta therapy response heterogeneity.

The role of the CD58 locus in multiple sclerosis

Multiple sclerosis (MS) is an inflammatory disease of the central nervous system associated with demyelination and axonal loss. A whole genome association scan suggested that allelic variants in the CD58 gene region, encoding the costimulatory molecule LFA-3, are associated with risk of developing MS. We now report additional genetic evidence, as well as resequencing and fine mapping of the CD58 locus in patients with MS and control subjects. These efforts identify a CD58 variant that provides further evidence of association with MS (P = 1.1 × 10−6, OR 0.82) and the single protective effect within the CD58 locus is captured by the rs2300747G allele. This protective rs2300747G allele is associated with a dose-dependent increase in CD58 mRNA expression in lymphoblastic cell lines (P = 1.1 × 10−10) and in peripheral blood mononuclear cells from MS subjects (P = 0.0037). This protective effect of enhanced CD58 expression on circulating mononuclear cells in patients with MS is supported by finding that CD58 mRNA expression is higher in MS subjects during clinical remission. Functional investigations suggest a potential mechanism whereby increases in CD58 expression, mediated by the protective allele, up-regulate the expression of transcription factor FoxP3 through engagement of the CD58 receptor, CD2, leading to the enhanced function of CD4+CD25high regulatory T cells that are defective in subjects with MS.

An application of Random Forests to a genome-wide association dataset: Methodological considerations & new findings

BackgroundAs computational power improves, the application of more advanced machine learning techniques to the analysis of large genome-wide association (GWA) datasets becomes possible. While most traditional statistical methods can only elucidate main effects of genetic variants on risk for disease, certain machine learning approaches are particularly suited to discover higher order and non-linear effects. One such approach is the Random Forests (RF) algorithm. The use of RF for SNP discovery related to human disease has grown in recent years; however, most work has focused on small datasets or simulation studies which are limited.ResultsUsing a multiple sclerosis (MS) case-control dataset comprised of 300 K SNP genotypes across the genome, we outline an approach and some considerations for optimally tuning the RF algorithm based on the empirical dataset. Importantly, results show that typical default parameter values are not appropriate for large GWA datasets. Furthermore, gains can be made by sub-sampling the data, pruning based on linkage disequilibrium (LD), and removing strong effects from RF analyses. The new RF results are compared to findings from the original MS GWA study and demonstrate overlap. In addition, four new interesting candidate MS genes are identified, MPHOSPH9, CTNNA3, PHACTR2 and IL7, by RF analysis and warrant further follow-up in independent studies.ConclusionsThis study presents one of the first illustrations of successfully analyzing GWA data with a machine learning algorithm. It is shown that RF is computationally feasible for GWA data and the results obtained make biologic sense based on previous studies. More importantly, new genes were identified as potentially being associated with MS, suggesting new avenues of investigation for this complex disease.

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.

Multiple sclerosis genetics: leaving no stone unturned.

Compelling epidemiologic and molecular data indicate that genes play a primary role in determining who is at risk for developing multiple sclerosis (MS), how the disease progresses, and how someone responds to therapy. The genetic component of MS etiology is believed to result from the action of allelic variants in several genes. Their incomplete penetrance and moderate individual effect probably reflects epistatic interactions, post-transcriptional regulatory mechanisms, and significant environmental influences. Equally significant, it is also likely that locus heterogeneity exists, whereby specific genes influence susceptibility and pathogenesis in some individuals but not in others. With the aid of novel analytical algorithms, the combined study of genomic, transcriptional, proteomic, and phenotypic information in well-controlled study groups will define a useful conceptual model of pathogenesis and a framework for understanding the mechanisms of action of existing therapies for this disorder, as well as the rationale for novel curative strategies.

118 SNPs of folate-related genes and risks of spina bifida and conotruncal heart defects

BackgroundFolic acid taken in early pregnancy reduces risks for delivering offspring with several congenital anomalies. The mechanism by which folic acid reduces risk is unknown. Investigations into genetic variation that influences transport and metabolism of folate will help fill this data gap. We focused on 118 SNPs involved in folate transport and metabolism.MethodsUsing data from a California population-based registry, we investigated whether risks of spina bifida or conotruncal heart defects were influenced by 118 single nucleotide polymorphisms (SNPs) associated with the complex folate pathway. This case-control study included 259 infants with spina bifida and a random sample of 359 nonmalformed control infants born during 1983–86 or 1994–95. It also included 214 infants with conotruncal heart defects born during 1983–86. Infant genotyping was performed blinded to case or control status using a designed SNPlex assay. We examined single SNP effects for each of the 118 SNPs, as well as haplotypes, for each of the two outcomes.ResultsFew odds ratios (ORs) revealed sizable departures from 1.0. With respect to spina bifida, we observed ORs with 95% confidence intervals that did not include 1.0 for the following SNPs (heterozygous or homozygous) relative to the reference genotype: BHMT (rs3733890) OR = 1.8 (1.1–3.1), CBS (rs2851391) OR = 2.0 (1.2–3.1); CBS (rs234713) OR = 2.9 (1.3–6.7); MTHFD1 (rs2236224) OR = 1.7 (1.1–2.7); MTHFD1 (hcv11462908) OR = 0.2 (0–0.9); MTHFD2 (rs702465) OR = 0.6 (0.4–0.9); MTHFD2 (rs7571842) OR = 0.6 (0.4–0.9); MTHFR (rs1801133) OR = 2.0 (1.2–3.1); MTRR (rs162036) OR = 3.0 (1.5–5.9); MTRR (rs10380) OR = 3.4 (1.6–7.1); MTRR (rs1801394) OR = 0.7 (0.5–0.9); MTRR (rs9332) OR = 2.7 (1.3–5.3); TYMS (rs2847149) OR = 2.2 (1.4–3.5); TYMS (rs1001761) OR = 2.4 (1.5–3.8); and TYMS (rs502396) OR = 2.1 (1.3–3.3). However, multiple SNPs observed for a given gene showed evidence of linkage disequilibrium indicating that the observed SNPs were not individually contributing to risk. We did not observe any ORs with confidence intervals that did not include 1.0 for any of the studied SNPs with conotruncal heart defects. Haplotype reconstruction showed statistical evidence of nonrandom associations with TYMS, MTHFR, BHMT and MTR for spina bifida.ConclusionOur observations do not implicate a particular folate transport or metabolism gene to be strongly associated with risks for spina bifida or conotruncal defects.