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Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration
Genome-wide association studies and other discovery genetics methods provide a means to identify previously unknown biological mechanisms underlying behavioral disorders that may point to new therapeutic avenues, augment diagnostic tools, and yield a deeper understanding of the biology of psychiatri...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688940/ https://www.ncbi.nlm.nih.gov/pubmed/32791514 http://dx.doi.org/10.1038/s41386-020-00795-5 |
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author | Reynolds, Timothy Johnson, Emma C. Huggett, Spencer B. Bubier, Jason A. Palmer, Rohan H. C. Agrawal, Arpana Baker, Erich J. Chesler, Elissa J. |
author_facet | Reynolds, Timothy Johnson, Emma C. Huggett, Spencer B. Bubier, Jason A. Palmer, Rohan H. C. Agrawal, Arpana Baker, Erich J. Chesler, Elissa J. |
author_sort | Reynolds, Timothy |
collection | PubMed |
description | Genome-wide association studies and other discovery genetics methods provide a means to identify previously unknown biological mechanisms underlying behavioral disorders that may point to new therapeutic avenues, augment diagnostic tools, and yield a deeper understanding of the biology of psychiatric conditions. Recent advances in psychiatric genetics have been made possible through large-scale collaborative efforts. These studies have begun to unearth many novel genetic variants associated with psychiatric disorders and behavioral traits in human populations. Significant challenges remain in characterizing the resulting disease-associated genetic variants and prioritizing functional follow-up to make them useful for mechanistic understanding and development of therapeutics. Model organism research has generated extensive genomic data that can provide insight into the neurobiological mechanisms of variant action, but a cohesive effort must be made to establish which aspects of the biological modulation of behavioral traits are evolutionarily conserved across species. Scalable computing, new data integration strategies, and advanced analysis methods outlined in this review provide a framework to efficiently harness model organism data in support of clinically relevant psychiatric phenotypes. |
format | Online Article Text |
id | pubmed-7688940 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-76889402020-11-30 Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration Reynolds, Timothy Johnson, Emma C. Huggett, Spencer B. Bubier, Jason A. Palmer, Rohan H. C. Agrawal, Arpana Baker, Erich J. Chesler, Elissa J. Neuropsychopharmacology Neuropsychopharmacology Reviews Genome-wide association studies and other discovery genetics methods provide a means to identify previously unknown biological mechanisms underlying behavioral disorders that may point to new therapeutic avenues, augment diagnostic tools, and yield a deeper understanding of the biology of psychiatric conditions. Recent advances in psychiatric genetics have been made possible through large-scale collaborative efforts. These studies have begun to unearth many novel genetic variants associated with psychiatric disorders and behavioral traits in human populations. Significant challenges remain in characterizing the resulting disease-associated genetic variants and prioritizing functional follow-up to make them useful for mechanistic understanding and development of therapeutics. Model organism research has generated extensive genomic data that can provide insight into the neurobiological mechanisms of variant action, but a cohesive effort must be made to establish which aspects of the biological modulation of behavioral traits are evolutionarily conserved across species. Scalable computing, new data integration strategies, and advanced analysis methods outlined in this review provide a framework to efficiently harness model organism data in support of clinically relevant psychiatric phenotypes. Springer International Publishing 2020-08-13 2021-01 /pmc/articles/PMC7688940/ /pubmed/32791514 http://dx.doi.org/10.1038/s41386-020-00795-5 Text en © The Author(s) 2020 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 | Neuropsychopharmacology Reviews Reynolds, Timothy Johnson, Emma C. Huggett, Spencer B. Bubier, Jason A. Palmer, Rohan H. C. Agrawal, Arpana Baker, Erich J. Chesler, Elissa J. Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration |
title | Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration |
title_full | Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration |
title_fullStr | Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration |
title_full_unstemmed | Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration |
title_short | Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration |
title_sort | interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration |
topic | Neuropsychopharmacology Reviews |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688940/ https://www.ncbi.nlm.nih.gov/pubmed/32791514 http://dx.doi.org/10.1038/s41386-020-00795-5 |
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