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Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents
BACKGROUND: Major depressive disorder (MDD) is a polygenic disorder associated with brain alterations but until recently, there have been no brain-based metrics to quantify individual-level variation in brain morphology. Here, we evaluated and compared the performance of a new brain-based ‘Regional...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cambridge University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9393914/ https://www.ncbi.nlm.nih.gov/pubmed/35899848 http://dx.doi.org/10.1192/j.eurpsy.2022.2301 |
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author | Thng, Gladi Shen, Xueyi Stolicyn, Aleks Harris, Mathew A. Adams, Mark J. Barbu, Miruna C. Kwong, Alex S. F. Frangou, Sophia Lawrie, Stephen M. McIntosh, Andrew M. Romaniuk, Liana Whalley, Heather C. |
author_facet | Thng, Gladi Shen, Xueyi Stolicyn, Aleks Harris, Mathew A. Adams, Mark J. Barbu, Miruna C. Kwong, Alex S. F. Frangou, Sophia Lawrie, Stephen M. McIntosh, Andrew M. Romaniuk, Liana Whalley, Heather C. |
author_sort | Thng, Gladi |
collection | PubMed |
description | BACKGROUND: Major depressive disorder (MDD) is a polygenic disorder associated with brain alterations but until recently, there have been no brain-based metrics to quantify individual-level variation in brain morphology. Here, we evaluated and compared the performance of a new brain-based ‘Regional Vulnerability Index’ (RVI) with polygenic risk scores (PRS), in the context of MDD. We assessed associations with syndromal MDD in an adult sample (N = 702, age = 59 ± 10) and with subclinical depressive symptoms in a longitudinal adolescent sample (baseline N = 3,825, age = 10 ± 1; 2-year follow-up N = 2,081, age = 12 ± 1). METHODS: MDD-RVIs quantify the correlation of the individual’s corresponding brain metric with the expected pattern for MDD derived in an independent sample. Using the same methodology across samples, subject-specific MDD-PRS and six MDD-RVIs based on different brain modalities (subcortical volume, cortical thickness, cortical surface area, mean diffusivity, fractional anisotropy, and multimodal) were computed. RESULTS: In adults, MDD-RVIs (based on white matter and multimodal measures) were more strongly associated with MDD (β = 0.099–0.281, P(FDR) = 0.001–0.043) than MDD-PRS (β = 0.056–0.152, P(FDR) = 0.140–0.140). In adolescents, depressive symptoms were associated with MDD-PRS at baseline and follow-up (β = 0.084–0.086, p = 1.38 × 10(−4)−4.77 × 10(−4)) but not with any MDD-RVIs (β < 0.05, p > 0.05). CONCLUSIONS: Our results potentially indicate the ability of brain-based risk scores to capture a broader range of risk exposures than genetic risk scores in adults and are also useful in helping us to understand the temporal origins of depression-related brain features. Longitudinal data, specific to the developmental period and on white matter measures, will be useful in informing risk for subsequent psychiatric illness. |
format | Online Article Text |
id | pubmed-9393914 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Cambridge University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-93939142022-08-23 Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents Thng, Gladi Shen, Xueyi Stolicyn, Aleks Harris, Mathew A. Adams, Mark J. Barbu, Miruna C. Kwong, Alex S. F. Frangou, Sophia Lawrie, Stephen M. McIntosh, Andrew M. Romaniuk, Liana Whalley, Heather C. Eur Psychiatry Research Article BACKGROUND: Major depressive disorder (MDD) is a polygenic disorder associated with brain alterations but until recently, there have been no brain-based metrics to quantify individual-level variation in brain morphology. Here, we evaluated and compared the performance of a new brain-based ‘Regional Vulnerability Index’ (RVI) with polygenic risk scores (PRS), in the context of MDD. We assessed associations with syndromal MDD in an adult sample (N = 702, age = 59 ± 10) and with subclinical depressive symptoms in a longitudinal adolescent sample (baseline N = 3,825, age = 10 ± 1; 2-year follow-up N = 2,081, age = 12 ± 1). METHODS: MDD-RVIs quantify the correlation of the individual’s corresponding brain metric with the expected pattern for MDD derived in an independent sample. Using the same methodology across samples, subject-specific MDD-PRS and six MDD-RVIs based on different brain modalities (subcortical volume, cortical thickness, cortical surface area, mean diffusivity, fractional anisotropy, and multimodal) were computed. RESULTS: In adults, MDD-RVIs (based on white matter and multimodal measures) were more strongly associated with MDD (β = 0.099–0.281, P(FDR) = 0.001–0.043) than MDD-PRS (β = 0.056–0.152, P(FDR) = 0.140–0.140). In adolescents, depressive symptoms were associated with MDD-PRS at baseline and follow-up (β = 0.084–0.086, p = 1.38 × 10(−4)−4.77 × 10(−4)) but not with any MDD-RVIs (β < 0.05, p > 0.05). CONCLUSIONS: Our results potentially indicate the ability of brain-based risk scores to capture a broader range of risk exposures than genetic risk scores in adults and are also useful in helping us to understand the temporal origins of depression-related brain features. Longitudinal data, specific to the developmental period and on white matter measures, will be useful in informing risk for subsequent psychiatric illness. Cambridge University Press 2022-07-28 /pmc/articles/PMC9393914/ /pubmed/35899848 http://dx.doi.org/10.1192/j.eurpsy.2022.2301 Text en © The Author(s) 2022 https://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, provided the original article is properly cited. |
spellingShingle | Research Article Thng, Gladi Shen, Xueyi Stolicyn, Aleks Harris, Mathew A. Adams, Mark J. Barbu, Miruna C. Kwong, Alex S. F. Frangou, Sophia Lawrie, Stephen M. McIntosh, Andrew M. Romaniuk, Liana Whalley, Heather C. Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents |
title | Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents |
title_full | Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents |
title_fullStr | Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents |
title_full_unstemmed | Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents |
title_short | Comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents |
title_sort | comparing personalized brain-based and genetic risk scores for major depressive disorder in large population samples of adults and adolescents |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9393914/ https://www.ncbi.nlm.nih.gov/pubmed/35899848 http://dx.doi.org/10.1192/j.eurpsy.2022.2301 |
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