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Your search keyword '"Chao, Yin-Xia"' showing total 28 results
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28 results on '"Chao, Yin-Xia"'

12. Association analysis of PSAP variants in Parkinson’s disease patients

Author

Chao, Yin Xia, primary, Lee, Bernett, additional, Ng, Ebonne Yulin, additional, Lian, Michelle Mulan, additional, Chew, Elaine Guo Yan, additional, Tandiono, Moses, additional, Li, Zheng, additional, Khor, Chiea Chuen, additional, Kumar, Prakash, additional, Tan, Louis C S, additional, Foo, Jia Nee, additional, and Tan, Eng-King, additional

Published
2020
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13. Cohort profile: the Diet and Healthy Aging (DaHA) study in Singapore

Author

Yu, Rongjun, primary, Sun, Ye, additional, Ye, Kaisy Xinhong, additional, Feng, Qiushi, additional, Lim, Su Lin, additional, Mahendran, Rathi, additional, Cheah, Irwin Kee-Mun, additional, Foo, Roger Sik Yin, additional, Chua, Ru Yuan, additional, Gwee, Xinyi, additional, Loh, Marie, additional, Sarmugam, Rani, additional, Khine, Wei Wei Thwe, additional, Chao, Yin Xia, additional, Larbi, Anis, additional, Lee, Yuan Kun, additional, Kumar, Alan Prem, additional, Kennedy, Brian K., additional, Kua, Ee Heok, additional, and Feng, Lei, additional

Published
2020
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14. Multimodal analysis of gene expression from postmortem brains and blood identifies synaptic vesicle trafficking genes to be associated with Parkinson’s disease

Author

Gao, Xiaoya, primary, Huang, Zifeng, additional, Feng, Cailing, additional, Guan, Chaohao, additional, Li, Ruidong, additional, Xie, Haiting, additional, Chen, Jian, additional, Li, Mingchun, additional, Que, Rongfang, additional, Deng, Bin, additional, Cao, Peihua, additional, Li, Mengyan, additional, Lu, Jianjun, additional, Huang, Yihong, additional, Li, Minzi, additional, Yang, Weihong, additional, Yang, Xiaohua, additional, Wen, Chunyan, additional, Liang, Xiaomei, additional, Yang, Qin, additional, Chao, Yin-Xia, additional, Chan, Ling-Ling, additional, Yenari, Midori A, additional, Jin, Kunlin, additional, Chaudhuri, K Ray, additional, Zhang, Jing, additional, Tan, Eng-King, additional, and Wang, Qing, additional

Published
2020
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24. Association Analysis of COQ2 Variant in Dementia and Essential Tremor

Author

Chao, Yin Xia, primary, Ng, Ebonne Yu Lin, additional, Li, Huihua, additional, Nagaendran, Kandiah, additional, Yih, Yuen, additional, Chong, Mei Sian, additional, Prakash, Kumar M., additional, Tan, Louis, additional, Au, Wing Lok, additional, Zhao, Yi, additional, Zhou, Zhi Dong, additional, Tio, Murni, additional, Pavanni, Ratnagopal, additional, and Tan, Eng King, additional

Published
2015
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27. Prevalence, risk and protective factors for mild cognitive impairment in a population-based study of Singaporean elderly.

Author

Liu LY, Lu Y, Shen L, Li CB, Yu JT, Yuan CR, Ye KX, Chao YX, Shen QF, Mahendran R, Kua EH, Yu DH, and Feng L

Abstract

The prevalence of dementia has been widely reported, and its potential risk and protective factors are well-characterized. However, there is a scarcity of related information regarding mild cognitive impairment (MCI). Thus this population-based study aimed to determine the prevalences of MCI and its subtypes, as well as to identify the risk and protective factors for MCI in the Chinese elderly population of Singapore. Results showed that the overall prevalence of MCI was 12.5%, while the gender-adjusted prevalence of MCI was 12.3%. Gender was found to be significantly associated with the subtypes of MCI, with males more likely to have amnestic MCI and females more likely to have non-amnestic MCI. Older age, lower educational levels, lower social activity levels, depression, hypertension, hyperlipidemia, diabetes and stroke were found to be risk factors for MCI in univariate analysis. However, multivariable analysis showed that only hypertension and stroke were the significant risk factors for MCI. Higher educational levels and active social engagements were significant protective factors for MCI in multivariable analysis. Age and depression had boundary significant associations with the prevalence of MCI. After adjusting for gender, the influence of hypertension, stroke, social engagement, age and depression on MCI remained unchanged, except that education became a boundary significant lower risk factor of MCI development. In conclusion, this study presented the prevalence, risk and protective factors for MCI among Singaporean Chinese older adults, which facilitates the screening of vulnerable groups for MCI., (Copyright © 2021. Published by Elsevier Ltd.)

Published
2021
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28. Multimodal analysis of gene expression from postmortem brains and blood identifies synaptic vesicle trafficking genes to be associated with Parkinson's disease.

Author

Gao X, Huang Z, Feng C, Guan C, Li R, Xie H, Chen J, Li M, Que R, Deng B, Cao P, Li M, Lu J, Huang Y, Li M, Yang W, Yang X, Wen C, Liang X, Yang Q, Chao YX, Chan LL, Yenari MA, Jin K, Chaudhuri KR, Zhang J, Tan EK, and Wang Q

Subjects
Autopsy, Biomarkers metabolism, Female, Humans, Male, Gene Expression Profiling, Gene Expression Regulation, Gene Regulatory Networks, Nerve Tissue Proteins biosynthesis, Nerve Tissue Proteins genetics, Parkinson Disease genetics, Parkinson Disease metabolism, Protein Interaction Maps, Synaptic Vesicles genetics, Synaptic Vesicles metabolism
Abstract

Objective: We aimed to identify key susceptibility gene targets in multiple datasets generated from postmortem brains and blood of Parkinson's disease (PD) patients and healthy controls (HC)., Methods: We performed a multitiered analysis to integrate the gene expression data using multiple-gene chips from 244 human postmortem tissues. We identified hub node genes in the highly PD-related consensus module by constructing protein-protein interaction (PPI) networks. Next, we validated the top four interacting genes in 238 subjects (90 sporadic PD, 125 HC and 23 Parkinson's Plus Syndrome (PPS)). Utilizing multinomial logistic regression analysis (MLRA) and receiver operating characteristic (ROC), we analyzed the risk factors and diagnostic power for discriminating PD from HC and PPS., Results: We identified 1333 genes that were significantly different between PD and HCs based on seven microarray datasets. The identified MEturquoise module is related to synaptic vesicle trafficking (SVT) dysfunction in PD (P < 0.05), and PPI analysis revealed that SVT genes PPP2CA, SYNJ1, NSF and PPP3CB were the top four hub node genes in MEturquoise (P < 0.001). The levels of these four genes in PD postmortem brains were lower than those in HC brains. We found lower blood levels of PPP2CA, SYNJ1 and NSF in PD compared with HC, and lower SYNJ1 in PD compared with PPS (P < 0.05). SYNJ1, negatively correlated to PD severity, displayed an excellent power to discriminating PD from HC and PPS., Conclusions: This study highlights that SVT genes, especially SYNJ1, may be promising markers in discriminating PD from HCs and PPS., (© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Published
2021
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