Characterization of complex genetic component contributing to the susceptibility for multiple sclerosis and rheumatoid arthritis

Autoimmune diseases (ADs) are a major public health concern, as the third most common category of disease in the US, following cancer and heart disease. As a result, autoimmunity has become one of the most active genetic and epidemiologic research areas. However, unraveling the etiological mechanisms in ADs has proven difficult. There is strong evidence suggesting a complex genetic component contributes to all ADs. For most ADs, the prominent genetic risk locus is within the major histocompatibility complex (MHC) on chromosome 6p21.3. Unfortunately, identifying non-MHC susceptibility loci has proven difficult in studies of ADs, for which multigenic patterns of inheritance are observed. Recently, through concerted international efforts, several genome-wide association (GWA) studies and subsequent replication analyses have confirmed many new susceptibility loci for ADs with very modest effects. The remainder of genetic variants contributing to AD susceptibility are unknown. It is clear that current approaches will be limited to completely characterize the complex genetic component in ADs. This dissertation is focused on the use of strong epidemiological approaches and novel analytical strategies to identify additional non-MHC genetic risk factors for two complex ADs: multiple sclerosis (MS) and rheumatoid arthritis (RA).;In Chapter 1, the relationship between variation in DNA repair pathways genes and risk for MS was investigated. Univariate association testing, epistatic tests of interactions, logistic regression modeling and non-parametric Random Forests analyses were performed using genotypes from 1,343 MS cases and 1,379 healthy controls of European ancestry. A total of 485 single nucleotide polymorphisms (SNPs) within 72 genes related to DNA repair pathways, including base excision repair, nucleotide excision repair, and double strand breaks repair, were investigated. A SNP variant within GTF2H4 on 6p21.33 was significantly associated with MS (odds ratio=0.7, P=3.5 x 10-5) after accounting for multiple testing, and was not due to linkage disequilibrium with the well-established HLA-DRB1*1501 allele within the MHC. Despite clear evidence for an association between GTF2H4 and MS, collectively, these results, derived from a well-powered study, do not support a strong role for common variation within DNA repair pathway genes in MS.;In Chapter 2, the relationship between variation within 8 candidate hypothalamic-pituitary-adrenal (HPA) axis genes and susceptibility to MS was comprehensively investigated. A total of 326 SNPs were investigated in 1,343 MS cases and 1,379 healthy controls of European ancestry using a multi-analytical strategy. Random Forests, a supervised machine learning algorithm, identified 8 SNPs within the corticotropin releasing hormone receptor 1 or CRHR1 locus on 17q21.31 as important predictors of MS. Based on univariate analyses, five CRHR1 variants were associated with decreased risk for disease following a conservative correction for multiple tests. Independent replication was observed in a large meta-analysis comprised of 2,624 MS cases and 7,220 healthy controls of European ancestry. Collectively, results provide strong evidence for the involvement of CRHR1 in MS.;In Chapter 3, epistatic interactions with a well-established genetic risk factor (PTPN22 1858T) in RA were investigated. The analysis consisted of four stages: Stage I (data reduction) -- identifying candidate chromosomal regions in 292 affected RA sibling pairs, by predicting PTPN22 concordance using multipoint identity-by-descent probabilities and Random Forests; Stage II (extension analysis) -- testing detailed genetic data within candidate chromosomal regions for epistasis with PTPN22 1858T in 677 RA cases and 750 controls using logistic regression; Stage III (replication analysis) -- confirmation of epistatic interactions in 947 RA cases and 1,756 controls; Stage IV (combined analysis) -- a pooled analysis including all 1,624 RA cases and 2,506 control subjects for final estimates of effect size. A total of 7 epistatic interactions identified in Stage II were replicated in Stage III. A SNP variant (rs7200573) within CDH13 demonstrated the strongest evidence for interaction ( p=1.5 x 10-4) with PTPN22. There was also evidence for epistasis between PTPN22 and SNP variants within MYO3A, CEP72 and near WFDC1.;The research conducted in Chapters 1 through 3 describes the use of analytical approaches based on strong hypotheses, multi-stage analyses, and the use of robust non-parametric methods in tandem with conventional association testing. Results described in these chapters are scientifically important, as they contribute to our understanding of the underlying genetic architecture in two very debilitating ADs (MS and RA), and also provide methodological frameworks for investigating other chronic diseases with a complex genetic component.