GWAS analysis implicates NF-κB-mediated induction of inflammatory T cells in multiple sclerosis

To identify genes and biologically relevant pathways associated with risk to develop multiple sclerosis (MS), the Genome-Wide Association Studies noise reduction method (GWAS-NR) was applied to MS genotyping data. Regions of association were defined based on the significance of linkage disequilibrium blocks. Candidate genes were cross-referenced based on a review of current literature, with attention to molecular function and directly interacting proteins. Supplementary annotations and pathway enrichment scores were generated using The Database for Annotation, Visualization and Integrated Discovery. The candidate set of 220 MS susceptibility genes prioritized by GWAS-NR was highly enriched with genes involved in biological pathways related to positive regulation of cell, lymphocyte and leukocyte activation (P=6.1E-15, 1.2E-14 and 5.0E-14, respectively). Novel gene candidates include key regulators of NF-κB signaling and CD4+ T helper type 1 (Th1) and T helper type 17 (Th17) lineages. A large subset of MS candidate genes prioritized by GWAS-NR were found to interact in a tractable pathway regulating the NF-κB-mediated induction and infiltration of pro-inflammatory Th1/Th17 T-cell lineages, and maintenance of immune tolerance by T-regulatory cells. This mechanism provides a biological context that potentially links clinical observations in MS to the underlying genetic landscape that may confer susceptibility.

An Analysis Paradigm for Investigating Multi-locus Effects in Complex Disease: Examination of Three GABAA Receptor Subunit Genes on 15q11-q13 as Risk Factors for Autistic Disorder

Gene-gene interactions are likely involved in many complex genetic disorders and new statistical approaches for detecting such interactions are needed. We propose a multi-analytic paradigm, relying on convergence of evidence across multiple analysis tools. Our paradigm tests for main and interactive effects, through allele, genotype and haplotype association. We applied our paradigm to genotype data from three GABAA receptor subunit genes (GABRB3, GABRA5, and GABRG3) on chromosome 15 in 470 Caucasian autism families. Previously implicated in autism, we hypothesized these genes interact to contribute to risk. We detected no evidence of main effects by allelic (PDT, FBAT) or genotypic (genotype-PDT) association at individual markers. However, three two-marker haplotypes in GABRG3 were significant (HBAT). We detected no significant multi-locus associations using genotype-PDT analysis or the EMDR data reduction program. However, consistent with the haplotype findings, the best single locus EMDR model selected a GABRG3 marker. Further, the best pairwise genotype-PDT result involved GABRB3 and GABRG3, and all multi-locus EMDR models also selected GABRB3 and GABRG3 markers. GABA receptor subunit genes do not significantly interact to contribute to autism risk in our overall data set. However, the consistency of results across analyses suggests that we have defined a useful framework for evaluating gene-gene interactions.

Identification of significant association and gene-gene interaction of GABA receptor subunit genes in autism

Autism is a common neurodevelopmental disorder with a significant genetic component. Existing research suggests that multiple genes contribute to autism and that epigenetic effects or gene-gene interactions are likely contributors to autism risk. However, these effects have not yet been identified. Gamma-aminobutyric acid (GABA), the primary inhibitory neurotransmitter in the adult brain, has been implicated in autism etiology. Fourteen known autosomal GABA receptor subunit genes were studied to look for the genes associated with autism and their possible interactions. Single-nucleotide polymorphisms (SNPs) were screened in the following genes: GABRG1, GABRA2, GABRA4, and GABRB1 on chromosome 4p12; GABRB2, GABRA6, GABRA1, GABRG2, and GABRP on 5q34-q35.1; GABRR1 and GABRR2 on 6q15; and GABRA5, GABRB3, and GABRG3 on 15q12. Intronic and/or silent mutation SNPs within each gene were analyzed in 470 white families with autism. Initially, SNPs were used in a family-based study for allelic association analysis--with the pedigree disequilibrium test and the family-based association test--and for genotypic and haplotypic association analysis--with the genotype-pedigree disequilibrium test (geno-PDT), the association in the presence of linkage (APL) test, and the haplotype family-based association test. Next, with the use of five refined independent marker sets, extended multifactor-dimensionality reduction (EMDR) analysis was employed to identify the models with locus joint effects, and interaction was further verified by conditional logistic regression. Significant allelic association was found for markers RS1912960 (in GABRA4; P = .01) and HCV9866022 (in GABRR2; P = .04). The geno-PDT found significant genotypic association for HCV8262334 (in GABRA2), RS1912960 and RS2280073 (in GABRA4), and RS2617503 and RS12187676 (in GABRB2). Consistent with the allelic and genotypic association results, EMDR confirmed the main effect at RS1912960 (in GABRA4). EMDR also identified a significant two-locus gene-gene effect model involving RS1912960 in GABRA4 and RS2351299 in GABRB1. Further support for this two-locus model came from both the multilocus geno-PDT and the APL test, which indicated a common genotype and haplotype combination positively associated with disease. Finally, these results were also consistent with the results from the conditional logistic regression, which confirmed the interaction between GABRA4 and GABRB1 (odds ratio = 2.9 for interaction term; P = .002). Through the convergence of all analyses, we conclude that GABRA4 is involved in the etiology of autism and potentially increases autism risk through interaction with GABRB1. These results support the hypothesis that GABA receptor subunit genes are involved in autism, most likely via complex gene-gene interactions.