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Comparison of machine learning tools for the prediction of AMD based on genetic, age, and diabetes-related variables in the Chinese population. Regen Ther 2021; 15:180-186. [PMID: 33426217 PMCID: PMC7770346 DOI: 10.1016/j.reth.2020.09.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Revised: 09/01/2020] [Accepted: 09/09/2020] [Indexed: 11/23/2022] Open
Abstract
Introduction Age-related macular degeneration (AMD) is the main cause of visual impairment and the most important cause of blindness in older people. However, there is currently no effective treatment for this disease, so it is necessary to establish a risk model to predict AMD development. Methods This study included a total of 202 subjects, comprising 82 AMD patients and 120 control subjects. Sixty-six single-nucleotide polymorphisms (SNPs) were identified using the MassArray assay. Considering 14 independent clinical variables as well as SNPs, four predictive models were established in the training set and evaluated by the confusion matrix, area under the receiver operating characteristic (ROC) curve (AUROC). The difference distributions of the 14 independent clinical features between the AMD and control groups were tested using the chi-squared test. Age and diabetes were adjusted using logistic regression analysis and the “genomic-control” method was used for multiple testing correction. Results Three SNPs (rs10490924, OR = 1.686, genomic-control corrected p-value (GC) = 0.030; rs2338104, OR = 1.794, GC = 0.025 and rs1864163, OR = 2.125, GC = 0.038) were significant risk factors for AMD development. In the training set, four models obtained AUROC values above 0.72. Conclusions We believe machine learning tools will be useful for the early prediction of AMD and for the development of relevant intervention strategies.
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Li M, Dong X, Chen S, Wang W, Yang C, Li B, Liang D, Yang W, Liu X, Yang X. Genetic polymorphisms and transcription profiles associated with intracranial aneurysm: a key role for NOTCH3. Aging (Albany NY) 2020; 11:5173-5191. [PMID: 31339861 PMCID: PMC6682524 DOI: 10.18632/aging.102111] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2019] [Accepted: 07/16/2019] [Indexed: 12/14/2022]
Abstract
Intracranial aneurysm (IA) incidence is about 1~2%. However, the specific mechanisms of IA onset and development need further study. Our objective was to discover novel IA-related genes to determine possible etiologies further. We performed next-generation sequencing on nineteen Chinese patients with familial IA and one patient with sporadic IA. We obtained mRNA expression data of 129 samples from Gene Expression Omnibus (GEO) and made statistical computing to discover differentially expressed genes (DEGs). The screened IA-related gene NOTCH3 was determined by bioinformatic data mining. We verified the IA-related indicators of NOTCH3. Association was found between IA and the NOTCH3 SNPs rs779314594, rs200504060 and rs2285981. Levels of NOTCH3 mRNA were lower in IA tissue than in control tissue, but higher in peripheral blood neutrophils from IA patients than in neutrophils from controls. Levels of NOTCH3 protein were lower in IA tissue than in cerebral artery tissue. NOTCH3 also decreased the expression of angiogenesis factors in human umbilical vein endothelial cells. Variation in NOTCH3 and alteration of its expression in cerebral artery or neutrophils may contribute to IA. Our findings also describe a bioinformatic-experimental approach that may prove useful for probing the pathophysiology of other complex diseases.
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Affiliation(s)
- Mengqi Li
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300052, China.,Tianjin Neurological Institute, Key Laboratory of Post-trauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education, Tianjin Key Laboratory of Injuries, Variations and Regeneration of Nervous System, Tianjin 300052, China.,Department of Cardiovascular Surgery, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Xinlong Dong
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300052, China.,Tianjin Neurological Institute, Key Laboratory of Post-trauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education, Tianjin Key Laboratory of Injuries, Variations and Regeneration of Nervous System, Tianjin 300052, China
| | - Shi Chen
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300052, China.,Tianjin Neurological Institute, Key Laboratory of Post-trauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education, Tianjin Key Laboratory of Injuries, Variations and Regeneration of Nervous System, Tianjin 300052, China.,Department of Neurosurgery, Fuzhou Second Hospital Affiliated to Xiamen University, Fuzhou 350007, China
| | - Weihan Wang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300052, China.,Tianjin Neurological Institute, Key Laboratory of Post-trauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education, Tianjin Key Laboratory of Injuries, Variations and Regeneration of Nervous System, Tianjin 300052, China
| | - Chao Yang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300052, China.,Tianjin Neurological Institute, Key Laboratory of Post-trauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education, Tianjin Key Laboratory of Injuries, Variations and Regeneration of Nervous System, Tianjin 300052, China
| | - Bochuan Li
- Collaborative Innovation Center of Tianjin for Medical Epigenetics and Department of Physiology and Pathophysiology, Tianjin Medical University, Tianjin 300052, China
| | - Degang Liang
- Department of Cardiovascular Surgery, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Weidong Yang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300052, China.,Tianjin Neurological Institute, Key Laboratory of Post-trauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education, Tianjin Key Laboratory of Injuries, Variations and Regeneration of Nervous System, Tianjin 300052, China
| | - Xiaozhi Liu
- Department of Neurosurgery, Tianjin Fifth Central Hospital, Tianjin 300450, China
| | - Xinyu Yang
- Department of Neurosurgery, Tianjin Medical University General Hospital, Tianjin 300052, China.,Tianjin Neurological Institute, Key Laboratory of Post-trauma Neuro-repair and Regeneration in Central Nervous System, Ministry of Education, Tianjin Key Laboratory of Injuries, Variations and Regeneration of Nervous System, Tianjin 300052, China
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