765 resultados para P-Value


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Background Leucocyte telomere length (LTL), which is fashioned by multiple genes, has been linked to a host of human diseases, including sporadic melanoma. A number of genes associated with LTL have already been identified through genome-wide association studies. The main aim of this study was to establish whether DCAF4 (DDB1 and CUL4-associated factor 4) is associated with LTL. In addition, using ingenuity pathway analysis (IPA), we examined whether LTL-associated genes in the general population might partially explain the inherently longer LTL in patients with sporadic melanoma, the risk for which is increased with ultraviolet radiation (UVR). Results Genome-wide association (GWA) meta-analysis and de novo genotyping of 20 022 individuals revealed a novel association (p=6.4×10−10) between LTL and rs2535913, which lies within DCAF4. Notably, eQTL analysis showed that rs2535913 is associated with decline in DCAF4 expressions in both lymphoblastoid cells and sun-exposed skin (p=4.1×10−3 and 2×10−3, respectively). Moreover, IPA revealed that LTL-associated genes, derived from GWA meta-analysis (N=9190), are over-represented among genes engaged in melanoma pathways. Meeting increasingly stringent p value thresholds (p<0.05, <0.01, <0.005, <0.001) in the LTL-GWA meta-analysis, these genes were jointly over-represented for melanoma at p values ranging from 1.97×10−169 to 3.42×10−24. Conclusions We uncovered a new locus associated with LTL in the general population. We also provided preliminary findings that suggest a link of LTL through genetic mechanisms with UVR and melanoma in the general population.

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Uterine leiomyomata (UL), the most prevalent pelvic tumors in women of reproductive age, pose a major public health problem given their high frequency, associated morbidities, and most common indication for hysterectomies. A genetic component to UL predisposition is supported by analyses of ethnic predisposition, twin studies, and familial aggregation. A genome-wide SNP linkage panel was genotyped and analyzed in 261 white UL-affected sister-pair families from the Finding Genes for Fibroids study. Two significant linkage regions were detected in 10p11 (LOD = 4.15) and 3p21 (LOD = 3.73), and five additional linkage regions were identified with LOD scores > 2.00 in 2q37, 5p13, 11p15, 12q14, and 17q25. Genome-wide association studies were performed in two independent cohorts of white women, and a meta-analysis was conducted. One SNP (rs4247357) was identified with a p value (p = 3.05 x 10(-8)) that reached genome-wide significance (odds ratio = 1.299). The candidate SNP is under a linkage peak and in a block of linkage disequilibrium in 17q25.3, which spans fatty acid synthase (FASN), coiled-coil-domain-containing 57 (CCDC57), and solute-carrier family 16, member 3 (SLC16A3). By tissue microarray immunohistochemistry, we found elevated (3-fold) FAS levels in UL-affected tissue compared to matched myometrial tissue. FAS transcripts and/or protein levels are upregulated in various neoplasms and implicated in tumor cell survival. FASN represents the initial UL risk allele identified in white women by a genome-wide, unbiased approach and opens a path to management and potential therapeutic intervention.

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Telomere length (TL) has been associated with aging and mortality, but individual differences are also influenced by genetic factors, with previous studies reporting heritability estimates ranging from 34 to 82%. Here we investigate the heritability, mode of inheritance and the influence of parental age at birth on TL in six large, independent cohort studies with a total of 19 713 participants. The meta-analysis estimate of TL heritability was 0.70 (95% CI 0.64–0.76) and is based on a pattern of results that is highly similar for twins and other family members. We observed a stronger mother–offspring (r=0.42; P-value=3.60 × 10−61) than father–offspring correlation (r=0.33; P-value=7.01 × 10−5), and a significant positive association with paternal age at offspring birth (β=0.005; P-value=7.01 × 10−5). Interestingly, a significant and quite substantial correlation in TL between spouses (r=0.25; P-value=2.82 × 10−30) was seen, which appeared stronger in older spouse pairs (mean age ≥55 years; r=0.31; P-value=4.27 × 10−23) than in younger pairs (mean age<55 years; r=0.20; P-value=3.24 × 10−10). In summary, we find a high and very consistent heritability estimate for TL, evidence for a maternal inheritance component and a positive association with paternal age.

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Endometriosis is a common gynecological disease associated with pelvic pain and subfertility. We conducted a genome-wide association study (GWAS) in 3,194 individuals with surgically confirmed endometriosis (cases) and 7,060 controls from Australia and the UK. Polygenic predictive modeling showed significantly increased genetic loading among 1,364 cases with moderate to severe endometriosis. The strongest association signal was on 7p15.2 (rs12700667) for 'all' endometriosis (P = 2.6 x 10(-)(7), odds ratio (OR) = 1.22, 95% CI 1.13-1.32) and for moderate to severe disease (P = 1.5 x 10(-)(9), OR = 1.38, 95% CI 1.24-1.53). We replicated rs12700667 in an independent cohort from the United States of 2,392 self-reported, surgically confirmed endometriosis cases and 2,271 controls (P = 1.2 x 10(-)(3), OR = 1.17, 95% CI 1.06-1.28), resulting in a genome-wide significant P value of 1.4 x 10(-)(9) (OR = 1.20, 95% CI 1.13-1.27) for 'all' endometriosis in our combined datasets of 5,586 cases and 9,331 controls. rs12700667 is located in an intergenic region upstream of the plausible candidate genes NFE2L3 and HOXA10.

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BACKGROUND Correlations between Educational Attainment (EA) and measures of cognitive performance are as high as 0.8. This makes EA an attractive alternative phenotype for studies wishing to map genes affecting cognition due to the ease of collecting EA data compared to other cognitive phenotypes such as IQ. METHODOLOGY In an Australian family sample of 9538 individuals we performed a genome-wide association scan (GWAS) using the imputed genotypes of approximately 2.4 million single nucleotide polymorphisms (SNP) for a 6-point scale measure of EA. Top hits were checked for replication in an independent sample of 968 individuals. A gene-based test of association was then applied to the GWAS results. Additionally we performed prediction analyses using the GWAS results from our discovery sample to assess the percentage of EA and full scale IQ variance explained by the predicted scores. RESULTS The best SNP fell short of having a genome-wide significant p-value (p = 9.77x10(-7)). In our independent replication sample six SNPs among the top 50 hits pruned for linkage disequilibrium (r(2)<0.8) had a p-value<0.05 but only one of these SNPs survived correction for multiple testing--rs7106258 (p = 9.7*10(-4)) located in an intergenic region of chromosome 11q14.1. The gene based test results were non-significant and our prediction analyses show that the predicted scores explained little variance in EA in our replication sample. CONCLUSION While we have identified a polymorphism chromosome 11q14.1 associated with EA, further replication is warranted. Overall, the absence of genome-wide significant p-values in our large discovery sample confirmed the high polygenic architecture of EA. Only the assembly of large samples or meta-analytic efforts will be able to assess the implication of common DNA polymorphisms in the etiology of EA.

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Migraine is a common neurological disorder with a genetically complex background. This paper describes a meta-analysis of genome-wide association (GWA) studies on migraine, performed by the Dutch-Icelandic migraine genetics (DICE) consortium, which brings together six population-based European migraine cohorts with a total sample size of 10,980 individuals (2446 cases and 8534 controls). A total of 32 SNPs showed marginal evidence for association at a P-value<10(-5). The best result was obtained for SNP rs9908234, which had a P-value of 8.00 x 10(-8). This top SNP is located in the nerve growth factor receptor (NGFR) gene. However, this SNP did not replicate in three cohorts from the Netherlands and Australia. Of the other 31 SNPs, 18 SNPs were tested in two replication cohorts, but none replicated. In addition, we explored previously identified candidate genes in the meta-analysis data set. This revealed a modest gene-based significant association between migraine and the metadherin (MTDH) gene, previously identified in the first clinic-based GWA study (GWAS) for migraine (Bonferroni-corrected gene-based P-value=0.026). This finding is consistent with the involvement of the glutamate pathway in migraine. Additional research is necessary to further confirm the involvement of glutamate.

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BACKGROUND Given moderately strong genetic contributions to variation in alcoholism and heaviness of drinking (50% to 60% heritability) with high correlation of genetic influences, we have conducted a quantitative trait genome-wide association study (GWAS) for phenotypes related to alcohol use and dependence. METHODS Diagnostic interview and blood/buccal samples were obtained from sibships ascertained through the Australian Twin Registry. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed with 8754 individuals (2062 alcohol-dependent cases) selected for informativeness for alcohol use disorder and associated quantitative traits. Family-based association tests were performed for alcohol dependence, dependence factor score, and heaviness of drinking factor score, with confirmatory case-population control comparisons using an unassessed population control series of 3393 Australians with genome-wide SNP data. RESULTS No findings reached genome-wide significance (p = 8.4 x 10(-8) for this study), with lowest p value for primary phenotypes of 1.2 x 10(-7). Convergent findings for quantitative consumption and diagnostic and quantitative dependence measures suggest possible roles for a transmembrane protein gene (TMEM108) and for ANKS1A. The major finding, however, was small effect sizes estimated for individual SNPs, suggesting that hundreds of genetic variants make modest contributions (1/4% of variance or less) to alcohol dependence risk. CONCLUSIONS We conclude that: - 1) meta-analyses of consumption data may contribute usefully to gene discovery; - 2) translation of human alcoholism GWAS results to drug discovery or clinically useful prediction of risk will be challenging, and; - 3) through accumulation across studies, GWAS data may become valuable for improved genetic risk differentiation in research in biological psychiatry (e.g., prospective high-risk or resilience studies).

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Migraine is a common episodic neurological disorder, typically presenting with recurrent attacks of severe headache and autonomic dysfunction. Apart from rare monogenic subtypes, no genetic or molecular markers for migraine have been convincingly established. We identified the minor allele of rs1835740 on chromosome 8q22.1 to be associated with migraine (P = 5.38 x 10(-)(9), odds ratio = 1.23, 95% CI 1.150-1.324) in a genome-wide association study of 2,731 migraine cases ascertained from three European headache clinics and 10,747 population-matched controls. The association was replicated in 3,202 cases and 40,062 controls for an overall meta-analysis P value of 1.69 x 10(-)(1)(1) (odds ratio = 1.18, 95% CI 1.127-1.244). rs1835740 is located between MTDH (astrocyte elevated gene 1, also known as AEG-1) and PGCP (encoding plasma glutamate carboxypeptidase). In an expression quantitative trait study in lymphoblastoid cell lines, transcript levels of the MTDH were found to have a significant correlation to rs1835740 (P = 3.96 x 10(-)(5), permuted threshold for genome-wide significance 7.7 x 10(-)(5). To our knowledge, our data establish rs1835740 as the first genetic risk factor for migraine.

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Objective: To examine if streamlining a medical research funding application process saved time for applicants. Design: Cross-sectional surveys before and after the streamlining. Setting: The National Health and Medical Research Council (NHMRC) of Australia. Participants: Researchers who submitted one or more NHMRC Project Grant applications in 2012 or 2014. Main outcome measures: Average researcher time spent preparing an application and the total time for all applications in working days. Results: The average time per application increased from 34 working days before streamlining (95% CI 33 to 35) to 38 working days after streamlining (95% CI 37 to 39; mean difference 4 days, bootstrap p value <0.001). The estimated total time spent by all researchers on applications after streamlining was 614 working years, a 67-year increase from before streamlining. Conclusions: Streamlined applications were shorter but took longer to prepare on average. Researchers may be allocating a fixed amount of time to preparing funding applications based on their expected return, or may be increasing their time in response to increased competition. Many potentially productive years of researcher time are still being lost to preparing failed applications.

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This thesis which consists of an introduction and four peer-reviewed original publications studies the problems of haplotype inference (haplotyping) and local alignment significance. The problems studied here belong to the broad area of bioinformatics and computational biology. The presented solutions are computationally fast and accurate, which makes them practical in high-throughput sequence data analysis. Haplotype inference is a computational problem where the goal is to estimate haplotypes from a sample of genotypes as accurately as possible. This problem is important as the direct measurement of haplotypes is difficult, whereas the genotypes are easier to quantify. Haplotypes are the key-players when studying for example the genetic causes of diseases. In this thesis, three methods are presented for the haplotype inference problem referred to as HaploParser, HIT, and BACH. HaploParser is based on a combinatorial mosaic model and hierarchical parsing that together mimic recombinations and point-mutations in a biologically plausible way. In this mosaic model, the current population is assumed to be evolved from a small founder population. Thus, the haplotypes of the current population are recombinations of the (implicit) founder haplotypes with some point--mutations. HIT (Haplotype Inference Technique) uses a hidden Markov model for haplotypes and efficient algorithms are presented to learn this model from genotype data. The model structure of HIT is analogous to the mosaic model of HaploParser with founder haplotypes. Therefore, it can be seen as a probabilistic model of recombinations and point-mutations. BACH (Bayesian Context-based Haplotyping) utilizes a context tree weighting algorithm to efficiently sum over all variable-length Markov chains to evaluate the posterior probability of a haplotype configuration. Algorithms are presented that find haplotype configurations with high posterior probability. BACH is the most accurate method presented in this thesis and has comparable performance to the best available software for haplotype inference. Local alignment significance is a computational problem where one is interested in whether the local similarities in two sequences are due to the fact that the sequences are related or just by chance. Similarity of sequences is measured by their best local alignment score and from that, a p-value is computed. This p-value is the probability of picking two sequences from the null model that have as good or better best local alignment score. Local alignment significance is used routinely for example in homology searches. In this thesis, a general framework is sketched that allows one to compute a tight upper bound for the p-value of a local pairwise alignment score. Unlike the previous methods, the presented framework is not affeced by so-called edge-effects and can handle gaps (deletions and insertions) without troublesome sampling and curve fitting.

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Head motion (HM) is a well known confound in analyses of functional MRI (fMRI) data. Neuroimaging researchers therefore typically treat HM as a nuisance covariate in their analyses. Even so, it is possible that HM shares a common genetic influence with the trait of interest. Here we investigate the extent to which this relationship is due to shared genetic factors, using HM extracted from resting-state fMRI and maternal and self report measures of Inattention and Hyperactivity-Impulsivity from the Strengths and Weaknesses of ADHD Symptoms and Normal Behaviour (SWAN) scales. Our sample consisted of healthy young adult twins (N = 627 (63% females) including 95 MZ and 144 DZ twin pairs, mean age 22, who had mother-reported SWAN; N = 725 (58% females) including 101 MZ and 156 DZ pairs, mean age 25, with self reported SWAN). This design enabled us to distinguish genetic from environmental factors in the association between head movement and ADHD scales. HM was moderately correlated with maternal reports of Inattention (r = 0.17, p-value = 7.4E-5) and Hyperactivity-Impulsivity (r = 0.16, p-value = 2.9E-4), and these associations were mainly due to pleiotropic genetic factors with genetic correlations [95% CIs] of rg = 0.24 [0.02, 0.43] and rg = 0.23 [0.07, 0.39]. Correlations between self-reports and HM were not significant, due largely to increased measurement error. These results indicate that treating HM as a nuisance covariate in neuroimaging studies of ADHD will likely reduce power to detect between-group effects, as the implicit assumption of independence between HM and Inattention or Hyperactivity-Impulsivity is not warranted. The implications of this finding are problematic for fMRI studies of ADHD, as failing to apply HM correction is known to increase the likelihood of false positives. We discuss two ways to circumvent this problem: censoring the motion contaminated frames of the RS-fMRI scan or explicitly modeling the relationship between HM and Inattention or Hyperactivity-Impulsivity

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MicroRNAs (miRNAs) are critical post-transcriptional regulators. Based on a previous genome-wide association (GWA) scan, we conducted a polymorphism in microRNAs' Target Sites (poly-miRTS)-centric multistage meta-analysis for lumbar spine (LS)-, total hip (HIP)-, and femoral neck (FN)-bone mineral density (BMD). In stage I, 41,102 poly-miRTSs were meta-analyzed in 7 cohorts with a genome-wide significance (GWS) α=0.05/41,102=1.22×10-6. By applying α=5×10-5 (suggestive significance), 11 poly-miRTSs were selected, with FGFRL1 rs4647940 and PRR5 rs3213550 as top signals for FN-BMD (P-value=7.67×10-6 and 1.58×10-5) in gender-combined sample. In stage II in silico replication (two cohorts), FGFRL1 rs4647940 was the only signal marginally replicated for FN-BMD (P-value=5.08×10-3) at α=0.10/11=9.09×10-3. PRR5 rs3213550 was also selected based on biological significance. In stage III de novo genotyping replication (two cohorts), FGFRL1 rs4647940 was the only signal significantly replicated for FN-BMD (P-value=7.55×10-6) at α=0.05/2=0.025 in gender-combined sample. Aggregating three stages, FGFRL1 rs4647940 was the single stage I-discovered and stages II- and III-replicated signal attaining GWS for FN-BMD (P-value=8.87×10-12). Dual-luciferase reporter assays demonstrated that FGFRL1 3' untranslated region harboring rs4647940 appears to be hsa-miR-140-5p's target site. In a zebrafish microinjection experiment, dre-miR-140-5p is shown to exert a dramatic impact on craniofacial skeleton formation. Taken together, we provided functional evidence for a novel FGFRL1 poly-miRTS rs4647940 in a previously known 4p16.3 locus, and experimental and clinical genetics studies have shown both FGFRL1 and hsa-miR-140-5p are important for bone formation. © The Author 2015. Published by Oxford University Press. All rights reserved.

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Aiming to identify novel genetic variants and to confirm previously identified genetic variants associated with bone mineral density (BMD), we conducted a three-stage genome-wide association (GWA) meta-analysis in 27 061 study subjects. Stage 1 meta-analyzed seven GWA samples and 11 140 subjects for BMDs at the lumbar spine, hip and femoral neck, followed by a Stage 2 in silico replication of 33 SNPs in 9258 subjects, and by a Stage 3 de novo validation of three SNPs in 6663 subjects. Combining evidence from all the stages, we have identified two novel loci that have not been reported previously at the genome-wide significance (GWS; 5.0 × 10-8) level: 14q24.2 (rs227425, P-value 3.98 × 10-13, SMOC1) in the combined sample of males and females and 21q22.13 (rs170183, P-value 4.15 × 10-9, CLDN14) in the female-specific sample. The two newly identified SNPs were also significant in the GEnetic Factors for OSteoporosis consortium (GEFOS, n 5 32 960) summary results. We have also independently confirmed 13 previously reported loci at the GWS level: 1p36.12 (ZBTB40), 1p31.3 (GPR177), 4p16.3 (FGFRL1), 4q22.1 (MEPE), 5q14.3 (MEF2C), 6q25.1 (C6orf97, ESR1), 7q21.3 (FLJ42280, SHFM1), 7q31.31 (FAM3C, WNT16), 8q24.12 (TNFRSF11B), 11p15.3 (SOX6), 11q13.4 (LRP5), 13q14.11 (AKAP11) and 16q24 (FOXL1). Gene expression analysis in osteogenic cells implied potential functional association of the two candidate genes (SMOC1 and CLDN14) in bone metabolism. Our findings independently confirm previously identified biological pathways underlying bone metabolism and contribute to the discovery of novel pathways, thus providing valuable insights into the intervention and treatment of osteoporosis. © The Author 2013. Published by Oxford University Press.

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Autoimmune diseases are more common in dogs than in humans and are already threatening the future of some highly predisposed dog breeds. Susceptibility to autoimmune diseases is controlled by environmental and genetic factors, especially the major histocompatibility complex (MHC) gene region. Dogs show a similar physiology, disease presentation and clinical response as humans, making them an excellent disease model for autoimmune diseases common to both species. The genetic background of canine autoimmune disorders is largely unknown, but recent annotation of the dog genome and subsequent development of new genomic tools offer a unique opportunity to map novel autoimmune genes in various breeds. Many autoimmune disorders show breed-specific enrichment, supporting a strong genetic background. Furthermore, the presence of hundreds of breeds as genetic isolates facilitates gene mapping in complex autoimmune disorders. Identification of novel predisposing genes establishes breeds as models and may reveal novel candidate genes for the corresponding human disorders. Genetic studies will eventually shed light on common biological functions and interactions between genes and the environment. This study aimed to identify genetic risk factors in various autoimmune disorders, including systemic lupus erythematosus (SLE)-related diseases, comprising immune-mediated rheumatic disease (IMRD) and steroid-responsive meningitis arteritis (SMRA) as well as Addison s disease (AD) in Nova Scotia Duck Tolling Retrievers (NSDTRs) and chronic superficial keratitis (CSK) in German Shepherd dogs (GSDs). We used two different approaches to identify genetic risk factors. Firstly, a candidate gene approach was applied to test the potential association of MHC class II, also known as a dog leukocyte antigen (DLA) in canine species. Secondly, a genome-wide association study (GWAS) was performed to identify novel risk loci for SLE-related disease and AD in NSDTRs. We identified DLA risk haplotypes for an IMRD subphenotype of SLE-related disease, AD and CSK, but not in SMRA, and show that the MHC class II gene region is a major genetic risk factor in canine autoimmune diseases. An elevated risk was found for IMRD in dogs that carried the DLA-DRB1*00601/DQA1*005011/DQB1*02001 haplotype (OR = 2.0, 99% CI = 1.03-3.95, p = 0.01) and for ANA-positive IMRD dogs (OR = 2.3, 99% CI = 1.07-5.04, p-value 0.007). We also found that DLA-DRB1*01502/DQA*00601/DQB1*02301 haplotype was significantly associated with AD in NSDTRs (OR = 2.1, CI = 1.0-4.4, P = 0.044) and the DLA-DRB1*01501/DQA1*00601/DQB1*00301 haplotype with the CSK in GSDs (OR=2.67, CI=1.17-6.44, p= 0.02). In addition, we found that homozygosity for the risk haplotype increases the risk for each disease phenotype and that an overall homozygosity for the DLA region predisposes to CSK and AD. Our results have enabled the development of genetic tests to improve breeding practices by avoiding the production of puppies homozygous for risk haplotypes. We also performed the first successful GWAS for a complex disease in dogs. With less than 100 cases and 100 controls, we identified five risk loci for SLE-related disease and AD and found strong candidate genes involved in a novel T-cell activation pathway. We show that an inbred dog population has fewer risk factors, but each of them has a stronger genetic risk. Ongoing studies aim to identify the causative mutations and bring new knowledge to help diagnostics, treatment and understanding of the aetiology of SLE-related diseases.

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Multiple sclerosis (MS) is the most common cause of neurological disability in young adults, affecting more than two million people worldwide. It manifests as a chronic inflammation in the central nervous system (CNS) and causes demyelination and neurodegeneration. Depending on the location of the demyelinated plaques and axonal loss, a variety of symptoms can be observed including deficits in vision, coordination, balance and movement. With a typical age of onset at 20-40 years, the social and economic impacts of MS on lives of the patients and their families are considerable. Unfortunately the current treatments are relatively inefficient and the development of more effective treatments has been impeded by our limited understanding of the causes and pathogenesis of MS. Risk of MS is higher in biological relatives of MS patients than in the general population. Twin and adoption studies have shown that familial clustering of MS is explained by shared genetic factors rather than by shared familial environment. While the involvement of the human leukocyte antigen (HLA) genes was first discovered four decades ago, additional genetic risk factors have only recently been identified through genome-wide association studies (GWAS). Current evidence suggests that MS is a highly polygenic disease with perhaps hundreds of common variants with relatively modest effects contributing to susceptibility. Despite extensive research, the majority of these risk factors still remain to be identified. In this thesis the aim was to identify novel genes and pathways involved in MS. Using genome-wide microarray technology, gene expression levels in peripheral blood mononuclear cells (PBMC) from 12 MS patients and 15 controls were profiled and more than 600 genes with altered expression in MS were identified. Three of five selected findings, DEFA1A3, LILRA4 and TNFRSF25, were successfully replicated in an independent sample. Increased expression of DEFA1A3 in MS is a particularly interesting observation, because its elevated levels have previously been reported also in several other autoimmune diseases. A systematic review of seven microarray studies was then performed leading to identification of 229 genes, in which either decreased or increased expression in MS had been reported in at least two studies. In general there was relatively little overlap across the experiments: 11 of the 229 genes had been reported in three studies and only HSPA1A in four studies. Nevertheless, these 229 genes were associated with several immunological pathways including interleukin pathways related to type 2 and type 17 helper T cells and regulatory T cells. However, whether these pathways are involved in causing MS or related to secondary processes activated after disease onset remains to be investigated. The 229 genes were also compared with loci identified in published MS GWASs. Single nucleotide polymorphisms (SNP) in 17 of the 229 loci had been reported to be associated with MS with P-value less than 0.0001 including variants in CXCR4 and SAPS2, which were the only loci where evidence for correlation between the associated variant and gene expression was found. The CXCR4 variant was further tested for association with MS in a large case-control sample and the previously reported suggestive association was replicated (P-value is 0.0004). Finally, common genetic variants in candidate genes, which had been selected on the basis of showing association with other autoimmune diseases (MYO9B) or showing differential expression in MS in our study (DEFA1A3, LILRA4 and TNFRSF25), were tested for association with MS, but no evidence of association was found. In conclusion, through a systematic review of genome-wide expression studies in MS we have identified several promising candidate genes and pathways for future studies. In addition, we have replicated a previously suggested association of a SNP variant upstream of CXCR4 with MS. Keywords: autoimmune disease, common variant, CXCR4, DEFA1A3, HSPA1A,gene expression, genetic association, GWAS, MS, multiple sclerosis, systematic review