Parkinson’s disease (PD) is complex and most likely results from an unknown combination of genetic and environmental factors. Here, we defined discrete genes (DGs) in a microarray analysis and found that the percentage of DGs versus all analyzable genes correlated with PD progression. Furthermore, this new parameter was also easily used to evaluate the therapeutic effect of high- frequency electro-acupuncture (EA), thus improving symptoms of PD model rats.
In the past two decades, rapid advances in gene expression profiling using microarray technology have not only brightened the prospect of deciphering the complexity of the disease genesis and progression at the genomic level but have also revolutionized the diagnostic, therapeutic, and prognostic approaches [
With this objective, we used microarrays to explore the gene expression profiles in the 6-OHDA-unilateral lesion rat model of PD between two phases (28ds and 35ds). The experimental procedures were approved by the Committee on Animal Care and Usage, Capital Medical University, and all efforts were made to minimize animal suffering. An injection of 6-OHDA into the medial forebrain bundle (MFB lesion model) causes effects similar to end-stage PD [
Including the unknown genes, the cortex chips showed 1289 differential transcripts (690 up-regulated and 599 down-regulated, p < 0.05) after 4 weeks of 6-OHDA treatment in the model group and 912 differential transcripts (507 up-regulated and 405 down-regulated, p < 0.05) after 5 weeks (5W) compared to the control. To
overlay the Cortex results of 4 and 5 weeks, 345 mutual genes were detected for further analysis (data not shown). Then, 944 differential transcripts (456 up-regulated and 488 down-regulated, p < 0.05) were used in the 4W, but not in the 5W, model group, and 567 differential transcripts (273 up-regulated and 294 down-regulated, p < 0.05) were used in the 5W, but not in the 4W, model group. The chips of STR showed 1039 differential transcripts (557 up-regulated and 482 down-regulated, p < 0.05) after 4 weeks of 6-OHDA treatment (4W) and 913 differential transcripts (563 up-regulated and 350 down-regulated, p < 0.05) after 5 weeks (5W) compared to control. To compare the 4-week and 5-week STR results, 405 mutual genes were detected for further analysis (data not shown). Then, 634 differential transcripts (301 up-regulated and 333 down-regulated, p < 0.05) were selected in the 4W, but not in the 5W, model group, and 508 differential transcripts (307 up-regulated and 201 down-regulated, p < 0.05) were selected in the 5W, but not in 4W, model group.
Discrete genes were a group of sporadic genes that could not compose a functional cluster. As the disease progresses, DG levels change. The differentially expressed transcripts in the cortex and STR were analyzed at two time points using DAVID 6.7. The percentage of DGs [DG/(DG + CG)] is shown in
Using DAVID Bioinformatics Resources 6.7, as described in
Items | M-Cort-4w | M-Cort-5w | M-Cort | EA-M-Cort | M-STR-4w | M-STR-5w | M-STR | EA-M-STR | |
---|---|---|---|---|---|---|---|---|---|
① | ② | ③ | ④ | ⑤ | ⑥ | ⑦ | ⑧ | ||
Respectively compared to control | |||||||||
Up-regulated genes | 414 | 273 | 273 | 662 | 395 | 383 | 383 | 238 | |
DG in up-regulated genes | 173 | 147 | 147 | 265 | 187 | 188 | 188 | 61 | |
The percentage of DGs | 41.79% | 53.85% | 53.85% | 40.03% | 47.34% | 49.09% | 49.09% | 25.63% | |
Chi-square value | 9.6156 | 14.9637 | 0.2368 | 33.6225 | |||||
p-value | P = 0.001929 | P = 0.000110 | P = 0.626527 | P = 0.000000 | |||||
Down-regulated genes | 382 | 252 | 252 | 728 | 272 | 222 | 222 | 235 | |
DG in down-regulated genes | 127 | 119 | 119 | 212 | 180 | 153 | 153 | 110 | |
The percentage of DG | 33.25% | 47.22% | 47.22% | 29.12% | 66.18% | 68.92% | 68.92% | 46.81% | |
Chi-square value | 12.489 | 27.4299 | 0.4179 | 22.8428 | |||||
p-value | p = 0.000409 | p = 0.000000 | p = 0.517987 | p = 0.000002 | |||||
Comparison between the two groups (for further analysis) | |||||||||
Up-regulated genes | 297 | 156 | 122 | 511 | 209 | 197 | 301 | 156 | |
DG in up-regulated genes | 126 | 85 | 71 | 199 | 82 | 109 | 150 | 42 | |
The percentage of DG | 42.42% | 54.49% | 58.20% | 38.94% | 39.23% | 55.33% | 49.83% | 26.92% | |
Chi-square value | 5.9834 | 14.9222 | 10.5422 | 22.1373 | |||||
p-value | p = 0.014441 | p = 0.000112 | p = 0.001167 | p = 0.000003 | |||||
Down-regulated genes | 311 | 181 | 143 | 619 | 175 | 125 | 166 | 179 | |
DG in down-regulated genes | 116 | 111 | 79 | 189 | 106 | 95 | 119 | 95 | |
The percentage of DG | 37.30% | 61.33% | 55.24% | 30.53% | 60.57% | 76% | 71.69% | 53.07% | |
Chi-square value | 24.0081 | 31.1211 | 7.845 | 12.6671 | |||||
p-value | p = 0.000001 | p = 0.000000 | p = 0.005096 | p = 0.000372 | |||||
Compared serials: ① and ②; ③ and ④; ⑤ and ⑥; ⑦ and ⑧; M: Model group; Cort: cortex; STR: striatum; EA: electro-acupuncture; 4/5W: 4/5 weeks.
analytical system (Functional Annotation Chart, DAVID 6.7) but were not found to have a statistically significant (i.e., with a p-value ≤1) functional annotation. These genes were neglected during analysis but in fact proved very important for explaining the level of disease progression. Their products varied predictably over time, and DG expression reliably predicted the stage of disease progression. That is, DGs showed little to no clustering for some functions. Correspondingly, the genes in the output results were defined as cluster genes (CGs).
Based on our observation of gene expression in different phases, we considered higher discrete ratios (the percentage DGs versus the sum of DGs and CGs) to be directly correlated to increasingly disordered corresponding patho-tissues. When we compared the differentially expressed genes at the two time points (4 weeks and 5 weeks), the up-regulated and the down-regulated transcripts compared to control were separated first, and then after analysis using DAVID 6.7, we found that the discrete ratio from the 5-week model increased not only in the cortex but also in the STR and included both up-regulated and down-regulated gene. When we deleted the mutual genes and compared the differentially expressed genes in the 4W and 5W model groups (see
The Model group was analyzed 5 weeks after 6-OHDA injections into the unilateral MFB. The EA group was treated using 100-Hz EA for 4 weeks (EA treatment was applied during weeks 2 through 5 after the injection of 6-OHDA). The Cortex chips showed 912 differential transcripts (507 up-regulated and 405 down-regulated, p < 0.05) in the model group (Model) and 2369 differential transcripts (1280 up-regulated and 1089 down-regulated, p < 0.05) in the 100-Hz EA group (EA) compared to the control (a). To compare the Cortex results of the Model and EA groups, 483 mutual genes were detected for further analysis (data not shown). Then, 429 differential transcripts (212 up-regulated and 217 down-regulated, p < 0.05) were used in the Model group, but not in the EA group, and 1886 differential transcripts (985 up-regulated and 901 down-regulated, p < 0.05) were used in the EA group, but not in the Model group (b). The STR chips showed 913 differential transcripts (563 up-regu- lated and 350 down-regulated, p < 0.05) in the Model group and 740 differential transcripts (387 up-regulated and 353 down-regulated, p < 0.05) in the EA group compared to the control (c). To compare the Cortex results of the Model and EA groups, 204 mutual genes were detected for further analyses (data not shown). Then, 709 differential transcripts (445 up-regulated and 264 down-regulated, p < 0.05) were selected in the Model group, but not in the EA group, and 536 differential transcripts (269 up-regulated and 267 down-regulated, p < 0.05) were selected in the EA group, but not in the Model group (d).
At the same time, we analyzed effective therapeutic measures for PD, such as electro-acupuncture (EA). EA, especially high-frequency EA, has been frequently used as an alternative therapy for PD and has been reportedly effective for alleviating motor symptoms in patients [
Both in the comparison between the model and EA-treated group and in the comparison between those groups and the control group, our results showed that the discrete ratio of the cortex and STR were significantly decreased after EA treatment (see
・ In the impaired (damaged) samples, the higher the discrete ratio, the more serious was the damage in the region. In contrast, the higher cluster ratio, the more favorable was disease progression.
・ The percentage of discrete or cluster genes can be used to determine the severity of PD.
・ If possible, the discrete or cluster ratios calculated by analyzing differential gene expression can be used to assess therapeutic treatments.
・ The value of the discrete or cluster ratios can be used to compare microarray data across similar clinical samples.
In particular, when we analyzed clinical gene regulation data, we needed to know the state of disease progression among the PD patients in order to group them accordingly. The discrete ratio is more convenient for grouping patients. More importantly, the discrete ratio may be used to assess treatment efficacy: therapeutic treatments with lower ratios could be potential treatments for both multi-genic and sporadic PD.
Our results suggest that a new theoretical parameter of microarray analysis can be used to evaluate the extent disease progression in this complicated disorder. Additionally, the decrease in the discrete ratio after treatment with 100-Hz EA may contribute to the behavioral improvement in PD model rats. However, development and deployment of EA for clinical evaluation and trials requires a detailed and complete strategy, which is beyond the scope of this paper.
Using David 6.7, we analyzed the normalized microarray data, described here. Group 1 and 2 were two comparable series consisting of either the Model groups at 4 and 5 weeks or Model and EA groups (Cortex or STR). First, we compared each group with their corresponding control (A and B). Second, the data between A and B were compared even further. The mutual genes were deleted (E), and the differential genes between A and B are shown as C and D.
The differentially expressed transcripts in the cortex and STR were analyzed at two time points (Delete the mutual genes, A and B) or at Model and EA groups (Delete the mutual genes, C and D). The entire analyzed results are shown in Results and
This work was supported by the National Basic Research Program of China (2011CB504100), the National Natural Science Foundation of China (31200811), and the “215” Talents Projects in Health System of Beijing (2013-3-096). There is no conflict of interest involved in this study.
Lirong Huo,Xibin Liang,Yi He,Xiaomin Wang, (2015) A Microarray Analysis of Parkinson’s Disease: New Clues and Evaluation. Journal of Biosciences and Medicines,03,55-60. doi: 10.4236/jbm.2015.39009