Transcript The Genetics of Multiple Sclerosis: How do Genes affect Prognosis?

The Genetics of Multiple Sclerosis: How do Genes affect Prognosis?
Project Summary
Multiple Sclerosis is a disorder that
affects the central nervous system
and seems to have a genetic link.
This study proposes to take a look at
chromosomes 1, 3, 6, 7 and X and
see how they affect the prognosis of
the patient. The overall goal of this
study is to see if a different numbers
of mutations affect the prognosis of
the patient. This will be done by
determining how many mutations
each patient has and then tracking
their progress over the course of 10
years. This study hopes to yield a
new way to test for MS, or allow
recently diagnosed patients a way to
better prepare for what may be in
their future.
http://www.livenet.ch/Service/images-cards/dna-.jpg
Introduction
MS is a progressive disorder that
affects the central nervous system by
degenerating the myelin sheath
around nerves. (Multiple Sclerosis
1990).
Both symptoms and treatments of MS
vary due to which nerves are
affected, and how frequent the
attacks on the myelin sheath happen.
In most cases, the disease starts with
alternating episodes and recovery,
then progressing into a phase where
there is no recovery.
Many theories exist as to what
exactly causes MS, but no definite
correlation has been found. Genetics
is the strongest correlation thus far.
A number of chromosomes have
been linked to causing MS, but
exactly which loci have not yet been
determined.
Andrea Child
Department of Biological Sciences
Objective
To determine if more gene polymorphisms
indicate a worse prognosis for patients.
http://www.mspathways.ca/en/images/myelin.jpg
Review of Literature
Studies have shown that there
appears to be a genetic link to
this disease. There is a familial
recurrence rate of approximately
15% (Compston 1990). Studies
have also shown that fraternal
twins have a 3-5% chance of
developing MS after the first twin,
but identical twins have a 25%
chance of developing it (Aaseng
2000).
Genetics is not the only predictor
of prognosis of MS; however it is
the most prominent. Pregnancy,
virus infections and trauma have
all been linked to more frequent
attacks to the myelin sheath.
These all must be taken into
account when observing the
prognosis of MS. However an
estimation on the course of MS
can be made by genetic factors,
age, and year of onset in relatives
(Compston 1999).
There are many treatments for
MS, but they all fall under two
main categories. One strategy is
to attempt to reduce the attack
on the CNS. The other focuses on
relief of symptoms (Multiple
Sclerosis 1990). Both of these
treatments are heavy in different
types of drugs.
Research Design
My thesis proposal is an original idea with considerations
taken from Compston (1999) and Risch (1990). Gene loci
used in the study were decided upon by past studies,
including such done by Ebers et al (1996) and Chataway
et al (1998). They were decided on by relevancy found in
studies, maximum lod scores from a combination of
studies, and how many times the loci were mentioned in
separate studies. Actual DNA isolation and amplification
methods came from Ebers et al (1996) and He et al
(1998).
1) Patients are gathered with the cooperation of doctors.
All will be females ranging in age from 20-40 from the
same states in Canada who have all been recently
diagnosed.
2) A gene screen is performed to determine the number of
mutations in each patient. (PCR Assay) From this,
patients will be put into groups, as shown by the figure
below. Within the groups of MS patients, sub-groups will
be made based on the type of treatment the patient is
receiving.
Expected Results
If genes are correlated, more
mutations should lead to a worse
prognosis.
The group with 1-2 mutations
should progress the slowest
through the stages of MS, have
very few plaques, and score low on
the Incapacity Scale and high on
Self Rated and Quality of Life
scales.
The group with 5 mutations should
progress quickly and have more
plaques on the MRI’s and have
higher scores on the Incapacity
Scale and lower scores on the Self
Rated and Quality of Life scales.
The group with 3-4 mutations
should fall somewhere within the
middle of these two groups.
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Literature Cited
Aaseng, Nathan. 2000. Multiple Sclerosis. New York: Franklin Watts
Chataway, Jeremy, Feakes, Robert, Coraddu, Francesca, Gray, Julia, Deans,
Jackie, Fraser, Mary, Robertson, Neil, Broadley, Simon, Jones, Hywel,
Clayton, David, Goodfellow, Peter, Sawcer, Stephen, and Compston,
Alastair. 1998. The genetics of multiple sclerosis: principles, background
and updated results of the United Kingdom systematic genome screen.
Brain 121:1869-1887
Compston, Alastair. 1990. The Genetic Epidemiology of Multiple Sclerosis.
Philosophical Transactions: Biological Sciences 354:1623-1635
Ebers, Geroge C., Kukay, Kim, Bulman, Dennis E., Anderson, Carol,
Armstrong, Holly, Cousin, Kieth, Bell, Robert B., Hader, Walter, Paty, Donald
W., Hashimoto, Stanley, Oger, Joel, Duquette, Pierre, Warren, Sharon, Gray,
Trevor, O’Connor, Paul, Nath, Avindra, Auty, Anthony, Metz, Luanne,
Francis, Gordon, Paulseth, John E., Murray, T. John, Pryse-Phillips, William,
Nelson, Robert, Freedman, Mark, Brunet, Donald, Bouchard, Jean-Pierre,
Hinds, David, and Risch, Neil. 1996. A full genome search in multiple
sclerosis. Nature Genetics 13:472-476
3) Study: Runs for 10 years. Data collected every year via
MRI’s and questionnaires. Data analyses will be done at
the 2, 5 and 10 year marks. MRI’s are done to scan for
plaques. Questionnaires used include Self Rated Abilities
Scale, Incapacity Status Scale, and Quality of life index:
MS Version.
He, Bing, Xu, Chun, Yang, Bei, Lantiblom, Anne-Marie, Fredrikson, Sten,
and Hillert, Jan. 1998. Linkage and association analysis of genes encoding
cytokines and myelin proteins in multiple sclerosis. Journal of
Neuroimmunology. 86:13-19
Risch, Neil. 1990. Linkage Strategies for Genetically Complex Traits. I
Multilocus Models. American Journal of Human Genetics. 46:222-228
U.S. Department of Health and Human Services. 1990. Multiple Sclerosis.
Washington DC: U.S. Government Printing Office
Acknowledgements
Dr. Kaltreider for all of his time helping me bounce ideas
back and forth and Dr. Rehnberg for giving wonderful
feedback.