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Low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder

Major depressive disorder (MDD) is a common but serious psychiatric disorder with significant levels of morbidity and mortality. Recent genome-wide association studies (GWAS) on common variants increase our understanding of MDD; however, the underlying genetic basis remains largely unknown. Many stu...

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Autores principales: Yu, Chenglong, Arcos-Burgos, Mauricio, Baune, Bernhard T., Arolt, Volker, Dannlowski, Udo, Wong, Ma-Li, Licinio, Julio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5913271/
https://www.ncbi.nlm.nih.gov/pubmed/29581422
http://dx.doi.org/10.1038/s41398-018-0117-7
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author Yu, Chenglong
Arcos-Burgos, Mauricio
Baune, Bernhard T.
Arolt, Volker
Dannlowski, Udo
Wong, Ma-Li
Licinio, Julio
author_facet Yu, Chenglong
Arcos-Burgos, Mauricio
Baune, Bernhard T.
Arolt, Volker
Dannlowski, Udo
Wong, Ma-Li
Licinio, Julio
author_sort Yu, Chenglong
collection PubMed
description Major depressive disorder (MDD) is a common but serious psychiatric disorder with significant levels of morbidity and mortality. Recent genome-wide association studies (GWAS) on common variants increase our understanding of MDD; however, the underlying genetic basis remains largely unknown. Many studies have been proposed to explore the genetics of complex diseases from a viewpoint of the “missing heritability” by considering low-frequency and rare variants, copy-number variations, and other types of genetic variants. Here we developed a novel computational and statistical strategy to investigate the “missing heritability” of MDD. We applied Hamming distance on common, low-frequency, and rare single-nucleotide polymorphism (SNP) sets to measure genetic distance between two individuals, and then built the multi-dimensional scaling (MDS) pictures. Whole-exome genotyping data from a Los Angeles Mexican-American cohort (203 MDD and 196 controls) and a European-ancestry cohort (473 MDD and 497 controls) were examined using our proposed methodology. MDS plots showed very significant separations between MDD cases and healthy controls for low-frequency SNP set (P value < 2.2e−16) and rare SNP set (P value = 7.681e−12). Our results suggested that low-frequency and rare variants may play more significant roles in the genetics of MDD.
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spelling pubmed-59132712018-04-24 Low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder Yu, Chenglong Arcos-Burgos, Mauricio Baune, Bernhard T. Arolt, Volker Dannlowski, Udo Wong, Ma-Li Licinio, Julio Transl Psychiatry Article Major depressive disorder (MDD) is a common but serious psychiatric disorder with significant levels of morbidity and mortality. Recent genome-wide association studies (GWAS) on common variants increase our understanding of MDD; however, the underlying genetic basis remains largely unknown. Many studies have been proposed to explore the genetics of complex diseases from a viewpoint of the “missing heritability” by considering low-frequency and rare variants, copy-number variations, and other types of genetic variants. Here we developed a novel computational and statistical strategy to investigate the “missing heritability” of MDD. We applied Hamming distance on common, low-frequency, and rare single-nucleotide polymorphism (SNP) sets to measure genetic distance between two individuals, and then built the multi-dimensional scaling (MDS) pictures. Whole-exome genotyping data from a Los Angeles Mexican-American cohort (203 MDD and 196 controls) and a European-ancestry cohort (473 MDD and 497 controls) were examined using our proposed methodology. MDS plots showed very significant separations between MDD cases and healthy controls for low-frequency SNP set (P value < 2.2e−16) and rare SNP set (P value = 7.681e−12). Our results suggested that low-frequency and rare variants may play more significant roles in the genetics of MDD. Nature Publishing Group UK 2018-03-27 /pmc/articles/PMC5913271/ /pubmed/29581422 http://dx.doi.org/10.1038/s41398-018-0117-7 Text en © The Author(s) 2018 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
Yu, Chenglong
Arcos-Burgos, Mauricio
Baune, Bernhard T.
Arolt, Volker
Dannlowski, Udo
Wong, Ma-Li
Licinio, Julio
Low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder
title Low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder
title_full Low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder
title_fullStr Low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder
title_full_unstemmed Low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder
title_short Low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder
title_sort low-frequency and rare variants may contribute to elucidate the genetics of major depressive disorder
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5913271/
https://www.ncbi.nlm.nih.gov/pubmed/29581422
http://dx.doi.org/10.1038/s41398-018-0117-7
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