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Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies
To identify genetic risk loci for major depressive disorder (MDD), two broad study design approaches have been applied: (1) to maximize sample size by combining data from different phenotype assessment modalities (e.g. clinical interview, self-report questionnaires) and (2) to reduce phenotypic hete...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6877467/ https://www.ncbi.nlm.nih.gov/pubmed/31559935 http://dx.doi.org/10.1017/S0033291719002502 |
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author | Schwabe, I. Milaneschi, Y. Gerring, Z. Sullivan, P. F. Schulte, E. Suppli, N. P. Thorp, J. G. Derks, E. M. Middeldorp, C. M. |
author_facet | Schwabe, I. Milaneschi, Y. Gerring, Z. Sullivan, P. F. Schulte, E. Suppli, N. P. Thorp, J. G. Derks, E. M. Middeldorp, C. M. |
author_sort | Schwabe, I. |
collection | PubMed |
description | To identify genetic risk loci for major depressive disorder (MDD), two broad study design approaches have been applied: (1) to maximize sample size by combining data from different phenotype assessment modalities (e.g. clinical interview, self-report questionnaires) and (2) to reduce phenotypic heterogeneity through selecting more homogenous MDD subtypes. The value of these strategies has been debated. In this review, we summarize the most recent findings of large genomic studies that applied these approaches, and we highlight the merits and pitfalls of both approaches with particular attention to methodological and psychometric issues. We also discuss the results of analyses that investigated the heterogeneity of MDD. We conclude that both study designs are essential for further research. So far, increasing sample size has led to the identification of a relatively high number of genomic loci linked to depression. However, part of the identified variants may be related to a phenotype common to internalizing disorders and related traits. As such, samples containing detailed clinical information are needed to dissect depression heterogeneity and enable the potential identification of variants specific to a more restricted MDD phenotype. A balanced portfolio reconciling both study design approaches is the optimal approach to progress further in unraveling the genetic architecture of depression. |
format | Online Article Text |
id | pubmed-6877467 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-68774672019-12-04 Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies Schwabe, I. Milaneschi, Y. Gerring, Z. Sullivan, P. F. Schulte, E. Suppli, N. P. Thorp, J. G. Derks, E. M. Middeldorp, C. M. Psychol Med Review Article To identify genetic risk loci for major depressive disorder (MDD), two broad study design approaches have been applied: (1) to maximize sample size by combining data from different phenotype assessment modalities (e.g. clinical interview, self-report questionnaires) and (2) to reduce phenotypic heterogeneity through selecting more homogenous MDD subtypes. The value of these strategies has been debated. In this review, we summarize the most recent findings of large genomic studies that applied these approaches, and we highlight the merits and pitfalls of both approaches with particular attention to methodological and psychometric issues. We also discuss the results of analyses that investigated the heterogeneity of MDD. We conclude that both study designs are essential for further research. So far, increasing sample size has led to the identification of a relatively high number of genomic loci linked to depression. However, part of the identified variants may be related to a phenotype common to internalizing disorders and related traits. As such, samples containing detailed clinical information are needed to dissect depression heterogeneity and enable the potential identification of variants specific to a more restricted MDD phenotype. A balanced portfolio reconciling both study design approaches is the optimal approach to progress further in unraveling the genetic architecture of depression. Cambridge University Press 2019-12 2019-09-27 /pmc/articles/PMC6877467/ /pubmed/31559935 http://dx.doi.org/10.1017/S0033291719002502 Text en © The Author(s) 2019 http://creativecommons.org/licenses/by/4.0/ This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Review Article Schwabe, I. Milaneschi, Y. Gerring, Z. Sullivan, P. F. Schulte, E. Suppli, N. P. Thorp, J. G. Derks, E. M. Middeldorp, C. M. Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies |
title | Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies |
title_full | Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies |
title_fullStr | Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies |
title_full_unstemmed | Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies |
title_short | Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies |
title_sort | unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies |
topic | Review Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6877467/ https://www.ncbi.nlm.nih.gov/pubmed/31559935 http://dx.doi.org/10.1017/S0033291719002502 |
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