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Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure
Discovering genetic variants associated with human brain structures is an on-going effort. The ENIGMA consortium conducted genome-wide association studies (GWAS) with standard multi-study analytical methodology and identified several significant single nucleotide polymorphisms (SNPs). Here we employ...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5691156/ https://www.ncbi.nlm.nih.gov/pubmed/29147026 http://dx.doi.org/10.1038/s41598-017-15705-x |
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author | Chen, Chi-Hua Wang, Yunpeng Lo, Min-Tzu Schork, Andrew Fan, Chun-Chieh Holland, Dominic Kauppi, Karolina Smeland, Olav B. Djurovic, Srdjan Sanyal, Nilotpal Hibar, Derrek P. Thompson, Paul M. Thompson, Wesley K. Andreassen, Ole A. Dale, Anders M. |
author_facet | Chen, Chi-Hua Wang, Yunpeng Lo, Min-Tzu Schork, Andrew Fan, Chun-Chieh Holland, Dominic Kauppi, Karolina Smeland, Olav B. Djurovic, Srdjan Sanyal, Nilotpal Hibar, Derrek P. Thompson, Paul M. Thompson, Wesley K. Andreassen, Ole A. Dale, Anders M. |
author_sort | Chen, Chi-Hua |
collection | PubMed |
description | Discovering genetic variants associated with human brain structures is an on-going effort. The ENIGMA consortium conducted genome-wide association studies (GWAS) with standard multi-study analytical methodology and identified several significant single nucleotide polymorphisms (SNPs). Here we employ a novel analytical approach that incorporates functional genome annotations (e.g., exon or 5′UTR), total linkage disequilibrium (LD) scores and heterozygosity to construct enrichment scores for improved identification of relevant SNPs. The method provides increased power to detect associated SNPs by estimating stratum-specific false discovery rate (FDR), where strata are classified according to enrichment scores. Applying this approach to the GWAS summary statistics of putamen volume in the ENIGMA cohort, a total of 15 independent significant SNPs were identified (conditional FDR < 0.05). In contrast, 4 SNPs were found based on standard GWAS analysis (P < 5 × 10(−8)). These 11 novel loci include GATAD2B, ASCC3, DSCAML1, and HELZ, which are previously implicated in various neural related phenotypes. The current findings demonstrate the boost in power with the annotation-informed FDR method, and provide insight into the genetic architecture of the putamen. |
format | Online Article Text |
id | pubmed-5691156 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-56911562017-11-24 Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure Chen, Chi-Hua Wang, Yunpeng Lo, Min-Tzu Schork, Andrew Fan, Chun-Chieh Holland, Dominic Kauppi, Karolina Smeland, Olav B. Djurovic, Srdjan Sanyal, Nilotpal Hibar, Derrek P. Thompson, Paul M. Thompson, Wesley K. Andreassen, Ole A. Dale, Anders M. Sci Rep Article Discovering genetic variants associated with human brain structures is an on-going effort. The ENIGMA consortium conducted genome-wide association studies (GWAS) with standard multi-study analytical methodology and identified several significant single nucleotide polymorphisms (SNPs). Here we employ a novel analytical approach that incorporates functional genome annotations (e.g., exon or 5′UTR), total linkage disequilibrium (LD) scores and heterozygosity to construct enrichment scores for improved identification of relevant SNPs. The method provides increased power to detect associated SNPs by estimating stratum-specific false discovery rate (FDR), where strata are classified according to enrichment scores. Applying this approach to the GWAS summary statistics of putamen volume in the ENIGMA cohort, a total of 15 independent significant SNPs were identified (conditional FDR < 0.05). In contrast, 4 SNPs were found based on standard GWAS analysis (P < 5 × 10(−8)). These 11 novel loci include GATAD2B, ASCC3, DSCAML1, and HELZ, which are previously implicated in various neural related phenotypes. The current findings demonstrate the boost in power with the annotation-informed FDR method, and provide insight into the genetic architecture of the putamen. Nature Publishing Group UK 2017-11-16 /pmc/articles/PMC5691156/ /pubmed/29147026 http://dx.doi.org/10.1038/s41598-017-15705-x Text en © The Author(s) 2017 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Chen, Chi-Hua Wang, Yunpeng Lo, Min-Tzu Schork, Andrew Fan, Chun-Chieh Holland, Dominic Kauppi, Karolina Smeland, Olav B. Djurovic, Srdjan Sanyal, Nilotpal Hibar, Derrek P. Thompson, Paul M. Thompson, Wesley K. Andreassen, Ole A. Dale, Anders M. Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure |
title | Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure |
title_full | Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure |
title_fullStr | Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure |
title_full_unstemmed | Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure |
title_short | Leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure |
title_sort | leveraging genome characteristics to improve gene discovery for putamen subcortical brain structure |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5691156/ https://www.ncbi.nlm.nih.gov/pubmed/29147026 http://dx.doi.org/10.1038/s41598-017-15705-x |
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