Cargando…

Genetic Mechanism Revealed of Age-Related Macular Degeneration Based on Fusion of Statistics and Machine Learning Method

Age-related macular degeneration (AMD) is the most common cause of irreversible vision loss in the developed world which affects the quality of life for millions of elderly individuals worldwide. Genome-wide association studies (GWAS) have identified genetic variants at 34 loci contributing to AMD....

Descripción completa

Detalles Bibliográficos
Autores principales: Du, Yongyi, Kong, Ning, Zhang, Jibin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8375266/
https://www.ncbi.nlm.nih.gov/pubmed/34422023
http://dx.doi.org/10.3389/fgene.2021.726599
_version_ 1783740287559925760
author Du, Yongyi
Kong, Ning
Zhang, Jibin
author_facet Du, Yongyi
Kong, Ning
Zhang, Jibin
author_sort Du, Yongyi
collection PubMed
description Age-related macular degeneration (AMD) is the most common cause of irreversible vision loss in the developed world which affects the quality of life for millions of elderly individuals worldwide. Genome-wide association studies (GWAS) have identified genetic variants at 34 loci contributing to AMD. To better understand the disease pathogenesis and identify causal genes for AMD, we applied random walk (RW) and support vector machine (SVM) to identify AMD-related genes based on gene interaction relationship and significance of genes. Our model achieved 0.927 of area under the curve (AUC), and 65 novel genes have been identified as AMD-related genes. To verify our results, a statistics method called summary data-based Mendelian randomization (SMR) has been implemented to integrate GWAS data and transcriptome data to verify AMD susceptibility-related genes. We found 45 genes are related to AMD by SMR. Among these genes, 37 genes overlap with those found by SVM-RW. Finally, we revealed the biological process of genetic mutations leading to changes in gene expression leading to AMD. Our results reveal the genetic pathogenic factors and related mechanisms of AMD.
format Online
Article
Text
id pubmed-8375266
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Frontiers Media S.A.
record_format MEDLINE/PubMed
spelling pubmed-83752662021-08-20 Genetic Mechanism Revealed of Age-Related Macular Degeneration Based on Fusion of Statistics and Machine Learning Method Du, Yongyi Kong, Ning Zhang, Jibin Front Genet Genetics Age-related macular degeneration (AMD) is the most common cause of irreversible vision loss in the developed world which affects the quality of life for millions of elderly individuals worldwide. Genome-wide association studies (GWAS) have identified genetic variants at 34 loci contributing to AMD. To better understand the disease pathogenesis and identify causal genes for AMD, we applied random walk (RW) and support vector machine (SVM) to identify AMD-related genes based on gene interaction relationship and significance of genes. Our model achieved 0.927 of area under the curve (AUC), and 65 novel genes have been identified as AMD-related genes. To verify our results, a statistics method called summary data-based Mendelian randomization (SMR) has been implemented to integrate GWAS data and transcriptome data to verify AMD susceptibility-related genes. We found 45 genes are related to AMD by SMR. Among these genes, 37 genes overlap with those found by SVM-RW. Finally, we revealed the biological process of genetic mutations leading to changes in gene expression leading to AMD. Our results reveal the genetic pathogenic factors and related mechanisms of AMD. Frontiers Media S.A. 2021-08-05 /pmc/articles/PMC8375266/ /pubmed/34422023 http://dx.doi.org/10.3389/fgene.2021.726599 Text en Copyright © 2021 Du, Kong and Zhang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Du, Yongyi
Kong, Ning
Zhang, Jibin
Genetic Mechanism Revealed of Age-Related Macular Degeneration Based on Fusion of Statistics and Machine Learning Method
title Genetic Mechanism Revealed of Age-Related Macular Degeneration Based on Fusion of Statistics and Machine Learning Method
title_full Genetic Mechanism Revealed of Age-Related Macular Degeneration Based on Fusion of Statistics and Machine Learning Method
title_fullStr Genetic Mechanism Revealed of Age-Related Macular Degeneration Based on Fusion of Statistics and Machine Learning Method
title_full_unstemmed Genetic Mechanism Revealed of Age-Related Macular Degeneration Based on Fusion of Statistics and Machine Learning Method
title_short Genetic Mechanism Revealed of Age-Related Macular Degeneration Based on Fusion of Statistics and Machine Learning Method
title_sort genetic mechanism revealed of age-related macular degeneration based on fusion of statistics and machine learning method
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8375266/
https://www.ncbi.nlm.nih.gov/pubmed/34422023
http://dx.doi.org/10.3389/fgene.2021.726599
work_keys_str_mv AT duyongyi geneticmechanismrevealedofagerelatedmaculardegenerationbasedonfusionofstatisticsandmachinelearningmethod
AT kongning geneticmechanismrevealedofagerelatedmaculardegenerationbasedonfusionofstatisticsandmachinelearningmethod
AT zhangjibin geneticmechanismrevealedofagerelatedmaculardegenerationbasedonfusionofstatisticsandmachinelearningmethod