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Allostatic load in early adolescence: gene / environment contributions and relevance for mental health
BACKGROUND. Allostatic load is the cumulative “wear and tear” on the body due to chronic adversity. We aimed to test poly-environmental (exposomic) and polygenic contributions to allostatic load and their combined contribution to early adolescent mental health. METHODS. We analyzed data on N = 5,035...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Cold Spring Harbor Laboratory
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635214/ https://www.ncbi.nlm.nih.gov/pubmed/37961462 http://dx.doi.org/10.1101/2023.10.27.23297674 |
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author | Hoffman, Kevin W. Tran, Kate T. Moore, Tyler M. Gataviņš, Mārtiņš M. Visoki, Elina DiDomenico, Grace E. Schultz, Laura M. Almasy, Laura Hayes, Matthew R. Daskalakis, Nikolaos P. Barzilay, Ran |
author_facet | Hoffman, Kevin W. Tran, Kate T. Moore, Tyler M. Gataviņš, Mārtiņš M. Visoki, Elina DiDomenico, Grace E. Schultz, Laura M. Almasy, Laura Hayes, Matthew R. Daskalakis, Nikolaos P. Barzilay, Ran |
author_sort | Hoffman, Kevin W. |
collection | PubMed |
description | BACKGROUND. Allostatic load is the cumulative “wear and tear” on the body due to chronic adversity. We aimed to test poly-environmental (exposomic) and polygenic contributions to allostatic load and their combined contribution to early adolescent mental health. METHODS. We analyzed data on N = 5,035 diverse youth (mean age 12) from the Adolescent Brain Cognitive Development Study (ABCD). Using dimensionality reduction method, we calculated and overall allostatic load score (AL) using body mass index [BMI], waist circumference, blood pressure, blood glycemia, blood cholesterol, and salivary DHEA. Childhood exposomic risk was quantified using multi-level environmental exposures before age 11. Genetic risk was quantified using polygenic risk scores (PRS) for metabolic system susceptibility (type 2 diabetes [T2D]) and stress-related psychiatric disease (major depressive disorder [MDD]). We used linear mixed effects models to test main, additive, and interactive effects of exposomic and polygenic risk (independent variables) on AL (dependent variable). Mediation models tested the mediating role of AL on the pathway from exposomic and polygenic risk to youth mental health. Models adjusted for demographics and genetic principal components. RESULTS. We observed disparities in AL with non-Hispanic White youth having significantly lower AL compared to Hispanic and Non-Hispanic Black youth. In the diverse sample, childhood exposomic burden was associated with AL in adolescence (beta=0.25, 95%CI 0.22–0.29, P<.001). In European ancestry participants (n=2,928), polygenic risk of both T2D and depression was associated with AL (T2D-PRS beta=0.11, 95%CI 0.07–0.14, P<.001; MDD-PRS beta=0.05, 95%CI 0.02–0.09, P=.003). Both polygenic scores showed significant interaction with exposomic risk such that, with greater polygenic risk, the association between exposome and AL was stronger. AL partly mediated the pathway to youth mental health from exposomic risk and from MDD-PRS, and fully mediated the pathway from T2D-PRS. CONCLUSIONS. AL can be quantified in youth using anthropometric and biological measures and is mapped to exposomic and polygenic risk. Main and interactive environmental and genetic effects support a diathesis-stress model. Findings suggest that both environmental and genetic risk be considered when modeling stress-related health conditions. |
format | Online Article Text |
id | pubmed-10635214 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-106352142023-11-13 Allostatic load in early adolescence: gene / environment contributions and relevance for mental health Hoffman, Kevin W. Tran, Kate T. Moore, Tyler M. Gataviņš, Mārtiņš M. Visoki, Elina DiDomenico, Grace E. Schultz, Laura M. Almasy, Laura Hayes, Matthew R. Daskalakis, Nikolaos P. Barzilay, Ran medRxiv Article BACKGROUND. Allostatic load is the cumulative “wear and tear” on the body due to chronic adversity. We aimed to test poly-environmental (exposomic) and polygenic contributions to allostatic load and their combined contribution to early adolescent mental health. METHODS. We analyzed data on N = 5,035 diverse youth (mean age 12) from the Adolescent Brain Cognitive Development Study (ABCD). Using dimensionality reduction method, we calculated and overall allostatic load score (AL) using body mass index [BMI], waist circumference, blood pressure, blood glycemia, blood cholesterol, and salivary DHEA. Childhood exposomic risk was quantified using multi-level environmental exposures before age 11. Genetic risk was quantified using polygenic risk scores (PRS) for metabolic system susceptibility (type 2 diabetes [T2D]) and stress-related psychiatric disease (major depressive disorder [MDD]). We used linear mixed effects models to test main, additive, and interactive effects of exposomic and polygenic risk (independent variables) on AL (dependent variable). Mediation models tested the mediating role of AL on the pathway from exposomic and polygenic risk to youth mental health. Models adjusted for demographics and genetic principal components. RESULTS. We observed disparities in AL with non-Hispanic White youth having significantly lower AL compared to Hispanic and Non-Hispanic Black youth. In the diverse sample, childhood exposomic burden was associated with AL in adolescence (beta=0.25, 95%CI 0.22–0.29, P<.001). In European ancestry participants (n=2,928), polygenic risk of both T2D and depression was associated with AL (T2D-PRS beta=0.11, 95%CI 0.07–0.14, P<.001; MDD-PRS beta=0.05, 95%CI 0.02–0.09, P=.003). Both polygenic scores showed significant interaction with exposomic risk such that, with greater polygenic risk, the association between exposome and AL was stronger. AL partly mediated the pathway to youth mental health from exposomic risk and from MDD-PRS, and fully mediated the pathway from T2D-PRS. CONCLUSIONS. AL can be quantified in youth using anthropometric and biological measures and is mapped to exposomic and polygenic risk. Main and interactive environmental and genetic effects support a diathesis-stress model. Findings suggest that both environmental and genetic risk be considered when modeling stress-related health conditions. Cold Spring Harbor Laboratory 2023-10-28 /pmc/articles/PMC10635214/ /pubmed/37961462 http://dx.doi.org/10.1101/2023.10.27.23297674 Text en https://creativecommons.org/licenses/by-nc-nd/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which allows reusers to copy and distribute the material in any medium or format in unadapted form only, for noncommercial purposes only, and only so long as attribution is given to the creator. |
spellingShingle | Article Hoffman, Kevin W. Tran, Kate T. Moore, Tyler M. Gataviņš, Mārtiņš M. Visoki, Elina DiDomenico, Grace E. Schultz, Laura M. Almasy, Laura Hayes, Matthew R. Daskalakis, Nikolaos P. Barzilay, Ran Allostatic load in early adolescence: gene / environment contributions and relevance for mental health |
title | Allostatic load in early adolescence: gene / environment contributions and relevance for mental health |
title_full | Allostatic load in early adolescence: gene / environment contributions and relevance for mental health |
title_fullStr | Allostatic load in early adolescence: gene / environment contributions and relevance for mental health |
title_full_unstemmed | Allostatic load in early adolescence: gene / environment contributions and relevance for mental health |
title_short | Allostatic load in early adolescence: gene / environment contributions and relevance for mental health |
title_sort | allostatic load in early adolescence: gene / environment contributions and relevance for mental health |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10635214/ https://www.ncbi.nlm.nih.gov/pubmed/37961462 http://dx.doi.org/10.1101/2023.10.27.23297674 |
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