Rheumatoid Arthritis (RA) is one of the most prevalent autoimmune
diseases in the world and is characterized by the chronic in
ammation
of the synovial joints. The origin of the disease is unknown but it
is actually accepted that it is caused by the complex interaction of
a genetic susceptibility background and environmental factors. To
date, the characterization of the genetic architecture of RA is far
from complete. In the present work we will use the power of two
distinct genomic approaches to identify new candidate genes for the
susceptibility to RA.
In the rst genomic approach, we have used gene expression microarrays
to characterize the in vitro transcriptional response of the synovial
broblast (SF) to the stimulation with RA synovial
uid. Using
a reverse engineering approach, we have inferred the main transcriptional
regulatory network that governs the response to this complex
proin
ammatory stimulus. We have then studied the genes in this
regulatory network as risk factors for RA susceptibility using a casecontrol
approach. We have analyzed the association of each gene
with disease independently, but we have also analyzed the presence of
higher order interactions associated with disease risk (i.e. epistasis)
using the Multifactor Dimensionality Reduction method.
In the second genomic approach, we have used whole genome genotyping
microarrays targeting more than 300,000 SNPs (Single Nucleotide
Polymorphisms) markers to perform a Genome-wide Association
Study (GWAS) in RA. In order to increase the statistical power
of our study we have implemented a liability-based design. We have subsequently validated those loci showing highest evidence of association
using an independent replication cohort. Also, in order to
integrate our ndings with the evidence of previous GWAS in RA,
we have determined those genomic loci showing increased clustering
of signals between studies. Finally, we have performed an exhaustive
genome-wide analysis of the two-way epistatic interactions associated
with RA applying parallel computation.
Using the SF in vitro stimulation model we have identi ed n = 157
genes signi cantly associated with the response to RA proin
ammatory
stimulus. Within this set of di erentially expressed genes there
are genes that have been clearly associated to RA pathophisiology but
also new genes not previously linked to this disease. From the di erential
expression data we have been able to identify a 13 gene Nuclear
Factor kappa-Beta (NF-kB) transcriptional regulatory network, as the
key transcriptional regulatory force in this RA SF model. Whilst
several of the genes in the network showed nominal association to
disease, we have identi ed a signi cant epistatic interaction between
interleukin 6 (IL6 ) and interleukin 4 induced 1 (IL4I1 ) genes.
In the GWAS approach we have identi ed several candidate genes for
RA, advanced RA and chronic arthritis risk. Using an independent
replication dataset we have found an intronic SNP in Kruppel-Like
Factor 12 (KLF12) gene as the most strongly associated SNP with
RA. The meta-analysis with previous GWAS results has also identi-
ed several genomic regions -including KLF12 locus- that are likely
to harbour new risk variants for RA. In the genome-wide epistasis
analysis we have found a number of SNP pairs associated with RA
with a signi cance close to the conservative multiple test correction
threshold. Also, we have found that two-way interactions including
the HLA region, the strongest main e ect in RA, are ranked secondarily
to many other potentially interacting loci, thus suggesting a
minor role for this locus in the epistatic susceptibility to disease.
The two alternative genomic approaches we present in this work have
identi ed a group of new loci which are likely to be associated with
the risk to RA. This group of candidate loci should be now validated
in independent populations to con rm their implication in RA susceptibility.
| Identifer | oai:union.ndltd.org:TDX_UAB/oai:www.tdx.cat:10803/48650 |
| Date | 03 January 2010 |
| Creators | Julià Cano, Antonio |
| Contributors | Marsal Barril, Sara, Universitat Autònoma de Barcelona. Departament de Bioquímica i Biologia Molecular |
| Publisher | Universitat Autònoma de Barcelona |
| Source Sets | Universitat Autònoma de Barcelona |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis, info:eu-repo/semantics/publishedVersion |
| Format | 148 p., application/pdf |
| Source | TDX (Tesis Doctorals en Xarxa) |
| Rights | info:eu-repo/semantics/openAccess, ADVERTIMENT. L'accés als continguts d'aquesta tesi doctoral i la seva utilització ha de respectar els drets de la persona autora. Pot ser utilitzada per a consulta o estudi personal, així com en activitats o materials d'investigació i docència en els termes establerts a l'art. 32 del Text Refós de la Llei de Propietat Intel·lectual (RDL 1/1996). Per altres utilitzacions es requereix l'autorització prèvia i expressa de la persona autora. En qualsevol cas, en la utilització dels seus continguts caldrà indicar de forma clara el nom i cognoms de la persona autora i el títol de la tesi doctoral. No s'autoritza la seva reproducció o altres formes d'explotació efectuades amb finalitats de lucre ni la seva comunicació pública des d'un lloc aliè al servei TDX. Tampoc s'autoritza la presentació del seu contingut en una finestra o marc aliè a TDX (framing). Aquesta reserva de drets afecta tant als continguts de la tesi com als seus resums i índexs. |
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