Download Vincent Klapper Dr. Ely Genetics 303 Revised term paper 11/15/13

Vincent Klapper
Dr. Ely Genetics 303
Revised term paper 11/15/13
How Genome Wide Association Studies have Enhanced our Understanding of Autoimmune
Disorders
In recent years, genetics research has made use of genome wide association studies.
Genome wide association studies (GWAS) compare entire genomes of human beings to analyze
single nucleotide polymorphisms, or SNPs, at various loci in the genome. By comparing the
genomes of healthy controls to patients with various disorders, geneticists can determine genes
that contain significant SNPs in patients with that disorder. Using that information, further
research can be done to discover which SNPs are indicated in which disease. GWAS do not
confirm that these SNPs cause a disease, but do show that genetic mutations in specific genes are
consistent across several diseases. Knowing that diseases have similar genetic components can
help us understand if the diseases are connected. And by knowing which genes are affected,
further research can uncover the mechanism of the disease by understanding what the affected
genes regulate. One classification of diseases that, in recent years, has been better understood by
GWAS is autoimmune disorders. In autoimmune disorders, the immune system attacks tissue in
the body through the creation of autoantibodies. These diseases include diabetes type 1,
autoimmune thyroid disorder, inflammatory bowel disease, multiple sclerosis, lupus, and
myasthenia gravis, among others. GWAS have demonstrated that these diseases share similar
genetic components and have examined other SNPs that could be related to the mechanism of the
disease.
Recently, a GWAS was performed on patients with multiple sclerosis. The experiment
done by Cox et al. (2013) attempted to identify which genes are over or under expressed in
patients with MS who are and are not receiving treatment. The type of treatment received by the
patients in this study was interferon beta (INF-beta) treatment which affects the expression of
genes that regulate the immune system. They wanted to examine what genes are affected by MS.
Studies by Sawcer et al. and Kemppinen et al. (cited in Cox et al. 2013) have indicated a strong
genetic component to MS, particularly in the HLA-DR2 gene. The HLA gene had been
implicated in many autoimmune disorders, so analysis of other genes could help determine
which risk factors contribute to MS. Their results revealed 50 genes with increased expression in
MS patients not receiving treatment compared to healthy controls, most of which were related to
cell signaling and immunity (Cox et al. 2013). In addition, “Pathway analysis revealed four
pathways with a significantly higher number of genes showing altered expression than expected,
these included plasminogen activating cascade, blood coagulation, inflammation mediated
chemokine and cytokine signaling pathway, and Alzheimer disease-presenilin pathway” (Cox et
al. 2013). By examining the over expressed genes in MS patients, they identified that the
plasminogen activation pathway was overregulated compared to controls. They concluded that it
is possible that the plasminogen activation pathway may be responsible for some of the effects of
MS. They then examined its mechanism using the PANTHER 7.0 classification system, which is
used to find biochemical pathways associated with the over expressed genes (Cox et al. 2013).
The plasminogen activation cascade directly affects the expression of matrix
metallopeptidase 9 (MMP9). This is significant because MMP9 is indicated in the integrity of the
blood brain barrier (Cox et al. 2013). In MS, immune cells enter the central nervous system and
attack the myelin sheath of the nerve cells. It is still in question how the immune cells pass
through the blood brain barrier to enter the central nervous system, but if MMP9 affects the
integrity of the blood brain barrier, and over regulation of the plasminogen activation cascade
leads to an increase in MMP9 in MS patients, it is possible that this mechanism could be the key
to understanding the mechanism of MS. These conclusions are not definite, and further
experimentation needs to occur before MS can be fully understood, but the GWAS of this
disorder has given future research an area and direction to start from.
An example of the further research that can occur after GWAS preliminary findings was
a study done by Bouzid et al. (2013) on genes indicated in two types of inflammatory bowel
disease. They examined the association of SNPs in the genes ZAP70 and PTPN6 with Crohn’s
disease (CD) and ulcerative colitis (UC) in the Tunisian population. Bouzid et al. performed this
experiment because previous GWAS by Franke et al. and Anderson et al. (cited in Bouzid et al.
2013) implicated the ZAP70 and PTPN6 genes in patients with CD and UC. They genotyped
patients with CD, UC, and healthy controls and found, “The rs13420683 polymorphism in
ZAP70 showed a marked increase in the frequency of the C allele in the patients with CD
(67.6%) as compared to the controls (48%)” (Bouzid et al. 2013). In fact, the CC genotype at the
rs13420683 polymorphism was most frequent in patients with CD. Allelic association analysis
confirmed that this marked increase in frequency was significant in patients with CD (Bouzid et
al. 2013). They also found that the rs7310161 polymorphism for the T allele of PTPN6 was more
frequent in patients with UC, compared to healthy controls, although this increased frequency
lost its significance after the Bonferroni’s testing correction (Bouzid et al. 2013). These
associations are important because even though both of these genes are involved in immune
signaling, the specific polymorphism at each locus could determine the risk factor for the
development of CD or UC. These diseases are related by other polymorphisms, so by analyzing
their differences, it may be possible to determine why one develops and not the other. The next
step in this area of research would be to see if these polymorphisms are consistent in other
populations and to analyze the biological processes associated with these genes, to see if they
provide insight into the mechanism of the disease.
Studies have also been done recently to determine not only the association between
polymorphisms and the risk factors of a disease, but also the severity of a disease. Based on the
results of a GWAS, Inoue et al. (2012) examined the relationship between polymorphisms of the
CTLA4, PTPN22, CD40, FCRL3, and ZFAT genes and the prognosis of two types of
autoimmune thyroid disorders, Grave’s disease (GD) and Hashimoto’s disease (HD), in an Asian
population. These genes have been implicated in autoimmune thyroid disorders in studies by
Begovich et al., Kavvoura et al., Sakai et al., and Tomer et al. (cited in Inoue et al. 2012),
“However, any possible association between these genes and AITD prognosis remains unknown”
(Inoue et al. 2012). They genotyped the polymorphisms in patients with intractable GD, GD in
remission, mild HD, severe HD, and healthy controls. They found the G allele in CTLA4 was
more frequent in patients with severe HD than controls, the C allele in CD40 was more frequent
in patients with GD in remission, the T allele in FCRL3 was less frequent in patients with
intractable GD, and the T allele in ZFAT was more frequent in patients with severe HD (Inoue et
al. 2012). All of these results were found to be significant using chi-squared and Fisher’s exact
tests (Inoue et al. 2012). It is already known that polymorphisms could be related to the risk of
developing an autoimmune disorder, but from this study, it may be possible to determine the
severity of the autoimmune disorder from the polymorphisms as well. This information could be
extremely valuable in treating patients and determining the mechanism of the disease. Each
polymorphism affects gene expression in a specific way. So if one polymorphism causes a more
severe form of the disease, the alteration of expression caused by that polymorphism could be
integral to the mechanism of the disease.
Over expression of the HLA gene has been implicated in almost all autoimmune
disorders studied. However, over expression of HLA does not always indicate an autoimmune
disorder, just as patients with under expression of HLA can still develop autoimmune disorders.
This discrepancy is why GWAS are useful. They allow a more extensive understanding of all the
genes that could potentially contribute to an autoimmune disorder. One study by Ostensson et al.
(2013) examined such a discrepancy in patients with celiac disease. They performed a GWAS,
pathway analysis, and two-locus interaction analysis in Swedish and Norwegian families with
celiac disease, a gluten intolerance that causes inflammation of the intestines, to determine which
genes were significantly associated in patients with celiac disease compared with healthy
controls. They found that, “As expected, the region around the CD associated HLA genes on
chromosome 6 showed the strongest association with the most significant p-value reaching
4.9x10-21 at marker rs424232” (Ostensson et al. 2013). However, some patients with celiac
disease did not exhibit significant correlation of the HLA related genes. These patients were
labeled as HLA low-risk (Ostensson et al. 2013). This means that with their genotype, they
would be less likely to develop celiac disease. However, they still developed it implying that
there are other genes associated with the development of celiac disease. From their analysis,
Ostensson et al. found, “A region including the DUSP10 gene (also known as MKP5) reached
genome-wide significance (p-value = 3.8x10-8) in the low-risk group” (Ostensson et al. 2013).
The HLA complex plays an important role in the development of autoimmune disorders. But
because of their research, Ostensson et al. (2013) was able to identify another gene, DUSP10,
associated with celiac disease. Even though patients may be at a low risk for the disease at the
HLA locus, they could be at a high risk at the DUSP10 locus. In this case, GWAS helped
indicate another gene that could potentially play an important role in the development of celiac
disease.
Even though autoimmune disorders can develop without over expression of the HLA
complex, in most cases, over expression of the HLA complex can lead to a higher risk for the
development of autoimmune disorders. This could potentially affect how we classify
autoimmune disorders. From our current understanding, an autoimmune disorder is characterized
by the creation of autoantibodies, which in turn attack specific cells of the body. Recently, a
number of GWAS have examined that there is a very strong correlation between the over
expression of HLA DQB1 and narcolepsy (Singh et al. 2013). These studies suggest that certain
polymorphisms, especially at the t-cell receptor alpha locus, could play an important role in the
development of narcolepsy (Singh et al. 2013). However, “The occurrence of autoantibody is an
important feature of autoimmune diseases and one of important factor for Witebsky’s defining
criteria for an autoimmune disease” (Singh et al. 2013). And as of yet, no autoantibodies have
been identified in patients with narcolepsy. The mechanism of narcolepsy is thought to involve
the destruction of hypocretin neurons. “Hypocretin (orexin) neurons play a critical role in the
regulation of sleep and wakefulness, and disturbances of the hypocretin system have been
directly linked to narcolepsy in animals and humans” (Singh et al. 2013). The correlation
between over expression of HLA genes and the destruction of specific body cells would seem to
indicate an autoimmune disorder, but without the presence of autoantibodies, it is merely a
correlation.
The case for narcolepsy as an autoimmune disorder is circumstantial at best, but the
correlation between HLA over expression and the occurrence of the disease revealed by GWAS
is significant (Singh et al. 2013). Our classification of autoimmune disorders could soon include
a genetic component based on the extensive findings of genome wide association studies. GWAS
are not without their faults though. As with many genetic experiments, most GWAS suffer from
a very small sample size, and most of the experiments discussed in this paper were performed on
populations in very specific regions. GWAS are also merely association studies. As with the case
for narcolepsy, correlation does not imply causation. However, the merits of GWAS cannot be
denied. They offer focus and direction for future studies, and are only the first step on the path to
understanding and combating diseases.
Works Cited
Bouzid, Dorra, Fourati, Hajer, Amouri, Ali, Marques, Isabel, Abida, Olfa, Haddouk, Samy,
Ayed, Mourad Ben, Tahri, Nabil, Penha-Gonclaves, Carlos, Masmoudi, Hatem. 2013.
Association of ZAP70 and PTPN6, but Not BANK1 or CLEC2D, with Inflammatory
Bowel Disease in the Tunisian Population. Genetic Testing and Molecular Biomarkers
17:321-326. Available from
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Cox, Matthew B., Bowden, Nikola A., Scott, Rodney J., Lechner-Scott, Jeannette. 2013. Altered
expression of the plasminogen activation pathway in peripheral blood mononuclear cells
in multiple sclerosis: possible pathomechanism of matrix metalloproteinase activation.
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Yamakawa, Noriko, Akahane, Maiko, Shimizuishi, Yu, Hidaka, Yoh, Iwatani, Yoshinori.
2012. Associations Between Autoimmune Thyroid Disease Prognosis and Functional
Polymorphisms of Susceptibility Genes, CTLA4, PTPN22, CD40, FCRL3, and ZFAT,
Previously Revealed in Genome-wide Association Studies. Journal of Clinical
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Svetlana, Ek, Johan, Ascher, Henry, Pollak, Elisabet, Arnell, Henrik, Browaldh, Lara,
Agardh, Daniel, Wahlstrom, Jan, Nilsson, Staffan, Torinsson-Naluai, Asa. 2013. A
Possible Mechanism behind Autoimmune Disorders Discovered By Genome-Wide
Linkage and Association Analysis in Celiac Disease. PLoS One 8:1-22. Available from
http://www-ncbi-nlm-nihgov.pallas2.tcl.sc.edu/pmc/articles/PMC3732286/pdf/pone.0070174.pdf
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Available from
http://www.sciencedirect.com.pallas2.tcl.sc.edu/science/article/pii/S0896841113000358