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ANCO-GeneDB: annotations and comprehensive analysis of candidate genes for alcohol, nicotine, cocaine and opioid dependence
Studies have shown that genetic factors play an important role in the risk to substance addiction and abuse. So far, various genetic and genomic studies have reported the related evidence. These rich, but highly heterogeneous, data provide us an unprecedented opportunity to systematically collect, c...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6310508/ https://www.ncbi.nlm.nih.gov/pubmed/30403795 http://dx.doi.org/10.1093/database/bay121 |
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author | Hu, Ruifeng Dai, Yulin Jia, Peilin Zhao, Zhongming |
author_facet | Hu, Ruifeng Dai, Yulin Jia, Peilin Zhao, Zhongming |
author_sort | Hu, Ruifeng |
collection | PubMed |
description | Studies have shown that genetic factors play an important role in the risk to substance addiction and abuse. So far, various genetic and genomic studies have reported the related evidence. These rich, but highly heterogeneous, data provide us an unprecedented opportunity to systematically collect, curate and assess the genetic and genomic signals from published studies and to perform a comprehensive analysis of their features, functional roles and druggability. Such genetic data resources have been made available for other disease or phenotypes but not for major substance dependence yet. Here, we report comprehensive data collection and secondary analyses of four phenotypes of dependence: alcohol dependence, nicotine dependence, cocaine dependence and opioid dependence, collectively named as Alcohol, Nicotine, Cocaine and Opioid (ANCO) dependence. We built the ANCO-GeneDB, an ANCO-dependence-associated gene resource database. ANCO-GeneDB includes resources from genome-wide association studies and candidate gene-based studies, transcriptomic studies, methylation studies, literature mining and drug-target data, as well as the derived data such as spatial–temporal gene expression, promoters, enhancers and expression quantitative trait loci. All associated genes and genetic variants are well annotated by using the collected evidence. Based on the collected data, we performed integrative, secondary analyses to prioritize genes, pathways, eQTLs and tissues that are significantly enriched in ANCO-related phenotypes. |
format | Online Article Text |
id | pubmed-6310508 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-63105082019-01-07 ANCO-GeneDB: annotations and comprehensive analysis of candidate genes for alcohol, nicotine, cocaine and opioid dependence Hu, Ruifeng Dai, Yulin Jia, Peilin Zhao, Zhongming Database (Oxford) Original Article Studies have shown that genetic factors play an important role in the risk to substance addiction and abuse. So far, various genetic and genomic studies have reported the related evidence. These rich, but highly heterogeneous, data provide us an unprecedented opportunity to systematically collect, curate and assess the genetic and genomic signals from published studies and to perform a comprehensive analysis of their features, functional roles and druggability. Such genetic data resources have been made available for other disease or phenotypes but not for major substance dependence yet. Here, we report comprehensive data collection and secondary analyses of four phenotypes of dependence: alcohol dependence, nicotine dependence, cocaine dependence and opioid dependence, collectively named as Alcohol, Nicotine, Cocaine and Opioid (ANCO) dependence. We built the ANCO-GeneDB, an ANCO-dependence-associated gene resource database. ANCO-GeneDB includes resources from genome-wide association studies and candidate gene-based studies, transcriptomic studies, methylation studies, literature mining and drug-target data, as well as the derived data such as spatial–temporal gene expression, promoters, enhancers and expression quantitative trait loci. All associated genes and genetic variants are well annotated by using the collected evidence. Based on the collected data, we performed integrative, secondary analyses to prioritize genes, pathways, eQTLs and tissues that are significantly enriched in ANCO-related phenotypes. Oxford University Press 2018-11-06 /pmc/articles/PMC6310508/ /pubmed/30403795 http://dx.doi.org/10.1093/database/bay121 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Hu, Ruifeng Dai, Yulin Jia, Peilin Zhao, Zhongming ANCO-GeneDB: annotations and comprehensive analysis of candidate genes for alcohol, nicotine, cocaine and opioid dependence |
title | ANCO-GeneDB: annotations and comprehensive analysis of candidate genes for alcohol, nicotine, cocaine and opioid dependence |
title_full | ANCO-GeneDB: annotations and comprehensive analysis of candidate genes for alcohol, nicotine, cocaine and opioid dependence |
title_fullStr | ANCO-GeneDB: annotations and comprehensive analysis of candidate genes for alcohol, nicotine, cocaine and opioid dependence |
title_full_unstemmed | ANCO-GeneDB: annotations and comprehensive analysis of candidate genes for alcohol, nicotine, cocaine and opioid dependence |
title_short | ANCO-GeneDB: annotations and comprehensive analysis of candidate genes for alcohol, nicotine, cocaine and opioid dependence |
title_sort | anco-genedb: annotations and comprehensive analysis of candidate genes for alcohol, nicotine, cocaine and opioid dependence |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6310508/ https://www.ncbi.nlm.nih.gov/pubmed/30403795 http://dx.doi.org/10.1093/database/bay121 |
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