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Characterization of Complex Genetic Component Contributing to the Susceptibility for Multiple Sclerosis and Rheumatoid Arthritis

Abstract

Autoimmune diseases (ADs) are a major public health concern, as the third most common category of disease in the US, after cancer and heart disease. As a result, ADs has become one of the most active genetic and epidemiologic research areas, however, unraveling the etiological mechanisms of ADs has proven difficult. There is strong evidence suggesting a complex genetic component contributing 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 these complex ADs with multigenic patterns of inheritance. Recently, through concerted international efforts, several genome-wide association (GWA) studies and subsequent replication analyses have confirmed several other AD susceptibility loci of modest effects; much of the remaining genetic variants contributing to AD susceptibility are unknown. It is clear that current approaches will be limited to identify all the complex genetic component ADs, therefore this dissertation focuses using strong epidemiological approaches and robust analytical frameworks to identify additional non-MHC genetic risk factors in 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 HLA-DRB1*1501. Despite clear evidence for an association between GTF2H4and MS, collectively, these results, derived from a well-powered study, do not support a strong role for 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 were 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 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. The results provide strong evidence for the involvement of CRHR1 (rs242936: p=9.7 x 10-5) in MS.

In Chapter 3, epistatic interactions with a well-established genetic factor (PTPN22 1858T) in a RA was investigated. The analysis consisted of four principal stages: Stage I (data reduction) - identifying candidate chromosomal regions in 292 affected 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 cases and 750 controls using logistic regression; Stage III (replication analysis) - confirmation of epistatic interactions in 947 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 replicating epistatic interactions were identified. A SNP variant (rs7200573) within CDH13 demonstrated significant 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 describe analytical approaches that were based on strong hypotheses, multi-stage analyses, and the use of robust non-parametric methods in tandem with conventional association testing. These chapters are scientifically important, as they contribute to our understanding of the underlying genetic architecture in two debilitating ADs (MS and RA) and provide strong methodological frameworks for investigating other chronic diseases with a complex genetic component.

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