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Structural neuroimaging measures and lifetime depression across levels of phenotyping in UK biobank
Depression is assessed in various ways in research, with large population studies often relying on minimal phenotyping. Genetic results suggest clinical diagnoses and self-report measures of depression show some core similarities, but also important differences. It is not yet clear how neuroimaging...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9007989/ https://www.ncbi.nlm.nih.gov/pubmed/35418197 http://dx.doi.org/10.1038/s41398-022-01926-w |
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author | Harris, Mathew A. Cox, Simon R. de Nooij, Laura Barbu, Miruna C. Adams, Mark J. Shen, Xueyi Deary, Ian J. Lawrie, Stephen M. McIntosh, Andrew M. Whalley, Heather C. |
author_facet | Harris, Mathew A. Cox, Simon R. de Nooij, Laura Barbu, Miruna C. Adams, Mark J. Shen, Xueyi Deary, Ian J. Lawrie, Stephen M. McIntosh, Andrew M. Whalley, Heather C. |
author_sort | Harris, Mathew A. |
collection | PubMed |
description | Depression is assessed in various ways in research, with large population studies often relying on minimal phenotyping. Genetic results suggest clinical diagnoses and self-report measures of depression show some core similarities, but also important differences. It is not yet clear how neuroimaging associations depend on levels of phenotyping. We studied 39,300 UK Biobank imaging participants (20,701 female; aged 44.6 to 82.3 years, M = 64.1, SD = 7.5) with structural neuroimaging and lifetime depression data. Past depression phenotypes included a single-item self-report measure, an intermediate measure of ‘probable’ lifetime depression, derived from multiple questionnaire items relevant to a history of depression, and a retrospective clinical diagnosis according to DSM-IV criteria. We tested (i) associations between brain structural measures and each depression phenotype, and (ii) effects of phenotype on these associations. Depression-brain structure associations were small (β < 0.1) for all phenotypes, but still significant after FDR correction for many regional metrics. Lifetime depression was consistently associated with reduced white matter integrity across phenotypes. Cortical thickness showed negative associations with Self-reported Depression in particular. Phenotype effects were small across most metrics, but significant for cortical thickness in most regions. We report consistent effects of lifetime depression in brain structural measures, including reduced integrity of thalamic radiations and association fibres. We also observed significant differences in associations with cortical thickness across depression phenotypes. Although these results did not relate to level of phenotyping as expected, effects of phenotype definition are still an important consideration for future depression research. |
format | Online Article Text |
id | pubmed-9007989 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-90079892022-04-27 Structural neuroimaging measures and lifetime depression across levels of phenotyping in UK biobank Harris, Mathew A. Cox, Simon R. de Nooij, Laura Barbu, Miruna C. Adams, Mark J. Shen, Xueyi Deary, Ian J. Lawrie, Stephen M. McIntosh, Andrew M. Whalley, Heather C. Transl Psychiatry Article Depression is assessed in various ways in research, with large population studies often relying on minimal phenotyping. Genetic results suggest clinical diagnoses and self-report measures of depression show some core similarities, but also important differences. It is not yet clear how neuroimaging associations depend on levels of phenotyping. We studied 39,300 UK Biobank imaging participants (20,701 female; aged 44.6 to 82.3 years, M = 64.1, SD = 7.5) with structural neuroimaging and lifetime depression data. Past depression phenotypes included a single-item self-report measure, an intermediate measure of ‘probable’ lifetime depression, derived from multiple questionnaire items relevant to a history of depression, and a retrospective clinical diagnosis according to DSM-IV criteria. We tested (i) associations between brain structural measures and each depression phenotype, and (ii) effects of phenotype on these associations. Depression-brain structure associations were small (β < 0.1) for all phenotypes, but still significant after FDR correction for many regional metrics. Lifetime depression was consistently associated with reduced white matter integrity across phenotypes. Cortical thickness showed negative associations with Self-reported Depression in particular. Phenotype effects were small across most metrics, but significant for cortical thickness in most regions. We report consistent effects of lifetime depression in brain structural measures, including reduced integrity of thalamic radiations and association fibres. We also observed significant differences in associations with cortical thickness across depression phenotypes. Although these results did not relate to level of phenotyping as expected, effects of phenotype definition are still an important consideration for future depression research. Nature Publishing Group UK 2022-04-13 /pmc/articles/PMC9007989/ /pubmed/35418197 http://dx.doi.org/10.1038/s41398-022-01926-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Harris, Mathew A. Cox, Simon R. de Nooij, Laura Barbu, Miruna C. Adams, Mark J. Shen, Xueyi Deary, Ian J. Lawrie, Stephen M. McIntosh, Andrew M. Whalley, Heather C. Structural neuroimaging measures and lifetime depression across levels of phenotyping in UK biobank |
title | Structural neuroimaging measures and lifetime depression across levels of phenotyping in UK biobank |
title_full | Structural neuroimaging measures and lifetime depression across levels of phenotyping in UK biobank |
title_fullStr | Structural neuroimaging measures and lifetime depression across levels of phenotyping in UK biobank |
title_full_unstemmed | Structural neuroimaging measures and lifetime depression across levels of phenotyping in UK biobank |
title_short | Structural neuroimaging measures and lifetime depression across levels of phenotyping in UK biobank |
title_sort | structural neuroimaging measures and lifetime depression across levels of phenotyping in uk biobank |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9007989/ https://www.ncbi.nlm.nih.gov/pubmed/35418197 http://dx.doi.org/10.1038/s41398-022-01926-w |
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