Abstract
Parkinson's disease is a very common neurodegenerative disorder. Patients usually undergo destruction of substantia nigra to develop typical symptoms such as resting tremor, hypokinesia, and rigidity. However, the exact mechanism of Parkinson's disease is still unknown, so it is called idiopathic Parkinsonism. According to my microarray analysis of peripheral blood leukocytes and substantia nigra brain tissue,
Introduction
Parkinson's disease is the second most common neurodegenerative disorder. Primary Parkisonism is also called idiopathic Parkinson's disease because its exact etiology is still unknown. After the destruction of substantia nigra of midbrain, patients will develop resting tremor, cogwheel rigidity, hypokinesia, and postural instability.
Introduction
Patients' life expectancy is much shorter than normal healthy population. Even it is a very common and detrimental illness, the etiology and pathogenesis is still a puzzle.
Introduction
By using microarray analysis of peripheral blood leukocytes and substantia nigra brain tissue, I find out that idiopathic Parkinsonism is actually a TH17 dominant autoimmune disease. Summary of all previous literatures also support that Parkinson's disease is a TH17 autoimmune illness.
Materials and methods

Microarray datasets of Parkinson's disease
In this paper, I incooperate two microarray datasets for analysis. The fist one is peripheral blood mononuclear cell gene expression profiles in Parkinson's disease patient. The dataset GSE6613 is available in GEO website. Dr. C.R. Scherzer published the research results of peripheral blood biomarkers for Parkinson's disease in PNAS.
The second dataset(GSE7621) is substantia nigra gene expression profiles in
Parkinson's disease. Substantia nigra is the major affected brain area of Parkinson's disease.
Statistical analysis
RMA express software(UC Berkeley, Board Institute) is used to do normalization and to rule out the outliners of the above dataset. I rule out the potential outliners of samples due to the following criteria:
Statistical analysis
1. Remove samples which have strong deviation in NUSE plot 2. Remove samples which have broad spectrum in RLE value plot 3. Remove samples which have strong deviation in RLE-NUSE mutiplot 4. Remove samples which exceed 99% line in RLE-NUSE T2 plot After the analysis of RMA express, we select 47 Parkinson's disease and 19 healthy controls. We remove GSE153479, GSE153497, and GSE153508 in healthy control due to RNA express analysis. We remove GSE153411, GSE153421, GSE153454 in Parkinsonism group. (Figure 1 and Figure 2 ) Then, we use Genespring to find out statistically significant expressed genes in substantia nigra and peripheral leukocytes of Parkinson's disease.
Validation by RT-PCR
Since this study is a secondary dataset analysis, I don't have samples in hand to do wet bench validation such as RT-PCR. However, in Dr. Scherzer's paper, he performed RT-PCR to confirm his result of microarray experiment by using RT-PCR. He found that the gene ST13, a HSP70 cofactor, is down-regulated in Parkinsonism compared to that in Healthy control due to microarray analysis. Then, he used quantitative real-time PCR assays based on precise fluorogenic 5' nuclease chemistry in a large set of 39 Parkinsonism patients and 12 age-, sex-, and blood count-matched healthy controls. He used the housekeeping gene glyceraldehydes-3-phosphate dehydrogenase to control for input RNA and the comparative threshold cycle method for analysis. The RT-PCR results confirmed that ST13 is lower in Parkinsonism patients.
Validation by RT-PCR
Thus, it states that the microarray platform of Dr. Scherzer's experiments is valid and reliable.
Results
Heat shock protein, Toll-like receptor, Caspases, and TH17 related gene up-regulation in substantia nigra of Parkinson's disease patients
Results
In the first dataset, we selected 816 genes of substantia nigra of Parkinson's disease compared to healthy control with fold change>1.5 and Benjamin adjusted false discovery rate<0.05. Then, we selected immune-related genes from this 816 genelist.(Table1) We find out that heat shock protein genes are almost all up-regulated in Parkinson's disease including HSP40, HSP70, HSP90, HSP27, and HSP105. In addition, TLR5 and TLR7 are up-regulated as well. Based on several references, TLR5 and TLR7 can recognize heat shock protein to trigger TH17 immunity. 

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