Earticle

초록

영어

Parkinson’s Disease (PD) patients were reported to exceed approximately 10 million worldwide, and the number has been consistently increasing every year. Factors causing PD are genetic and environmental factors. We focus on the effects of environmental factors on epigenetic. Specifically, the α- synuclein (SNCA) gene is a risk factor causing PD, and we analyze it based on its regulation by the methylated 3’ Untranslated Region (UTR). The analysis data consists of Deoxyribonucleic Acid (DNA) methylation by NCBI GEO datasets, including 40 samples from PD cases and 38 from cognitively healthy subjects. The total number of CpG islands (CGI) is 863,159. To select the distinctive CGI from the DNA methylation data, we apply the Recursive Feature Elimination (RFE) method. Consequently, we have the results from selecting the 20 CGIs. Based on 20 CGI, we employ four models, Support Vector Machine (SVM), RandomForest (RF), Extreme Gradient Boosting (XGBoost), and Neural Network (NN), to divide the control and PD. Among the results, the RF model achieved the highest accuracy at 87.5%. Our findings indicate that changes in DNA methylation levels of the 20 selected CGIs are associated with PD occurrence. Based on these results, we suggest that PD occurrence is related to environmental factors such as chemical stress, eating habits, and general stress. Furthermore, our paper provides insights into the relationship between epigenetics and neurodegenerative disease.

목차

Abstract
I. INTRODUCTION
II. METHOD AND MATERIAL
A. Work Flow
B. Model Description
III. RESULT
A. Data
B. Selected the CGI Group
C. Test
IV. CONCLUSION
ACKNOWLEDGMENT
REFERENCES

저자

• Dongjin Oh [ dept. of Biomedical Science Chosun University Gwangju, Republic of Korea ]
• Yedam Park [ dept. of Biomedical Science Chosun University Gwangju, Republic of Korea ]
• Hamin Im [ dept. of Biomedical Science Chosun University Gwangju, Republic of Korea ]
• Chan-Uk Yeom [ Division of AI Convergence College Chosun University Gwangju, Republic of Korea ]
• Keun-Chang Kwak [ dept. of Electronics Engineering Chosun University Gwangju, Republic of Korea ] Corresponding Author

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