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Influence of endogenous estrogen on a network model of female brain integrity
Recent reports document sex differences in midlife brain integrity and metabolic health, such that more relationships are detectable between metabolic syndrome (MetS) components and markers of brain health in females than in males. Midlife is characterized by a rapid decrease in endogenous estrogen...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9997143/ https://www.ncbi.nlm.nih.gov/pubmed/36908891 http://dx.doi.org/10.1016/j.nbas.2022.100053 |
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author | Foret, Janelle T. Caillaud, Marie Gourley, Drew D. Dekhtyar, Maria Tanaka, Hirofumi Haley, Andreana P. |
author_facet | Foret, Janelle T. Caillaud, Marie Gourley, Drew D. Dekhtyar, Maria Tanaka, Hirofumi Haley, Andreana P. |
author_sort | Foret, Janelle T. |
collection | PubMed |
description | Recent reports document sex differences in midlife brain integrity and metabolic health, such that more relationships are detectable between metabolic syndrome (MetS) components and markers of brain health in females than in males. Midlife is characterized by a rapid decrease in endogenous estrogen levels for women which is thought to increase risk for cardiometabolic disease and neurocognitive decline. Our study used network models, designed to explore the interconnectedness and organization of relationships among many variables at once, to compare the influence of endogenous estrogen and chronological age on a network of brain and metabolic health in order to investigate the utility of estrogen as a biomarker for brain vulnerability. Data were analyzed from 82 females (ages 40–62). Networks consisted of known biomarkers of risk for late-life cognitive decline: the five components of MetS; Brain-predicted age difference calculated on gray and white matter volume; white matter hyperintensities; Default Mode Network functional connectivity; cerebral concentrations of N-acetyl aspartate, glutamate and myo-inositol; and serum concentrations of estradiol. A second network replaced estradiol with chronological age. Expected influence (EI) of estradiol on the network was −1.190, relative to chronological age at −0.524, indicating that estradiol had a stronger expected influence over the network than age. A negative expected influence indicates that higher levels of estradiol would be expected to decrease the number of relationships in the model, which is thought to indicate lower risk. Overall, levels of estradiol appear more influential than chronological age at midlife for relationships between brain integrity and metabolic health. |
format | Online Article Text |
id | pubmed-9997143 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-99971432023-03-09 Influence of endogenous estrogen on a network model of female brain integrity Foret, Janelle T. Caillaud, Marie Gourley, Drew D. Dekhtyar, Maria Tanaka, Hirofumi Haley, Andreana P. Aging Brain Article Recent reports document sex differences in midlife brain integrity and metabolic health, such that more relationships are detectable between metabolic syndrome (MetS) components and markers of brain health in females than in males. Midlife is characterized by a rapid decrease in endogenous estrogen levels for women which is thought to increase risk for cardiometabolic disease and neurocognitive decline. Our study used network models, designed to explore the interconnectedness and organization of relationships among many variables at once, to compare the influence of endogenous estrogen and chronological age on a network of brain and metabolic health in order to investigate the utility of estrogen as a biomarker for brain vulnerability. Data were analyzed from 82 females (ages 40–62). Networks consisted of known biomarkers of risk for late-life cognitive decline: the five components of MetS; Brain-predicted age difference calculated on gray and white matter volume; white matter hyperintensities; Default Mode Network functional connectivity; cerebral concentrations of N-acetyl aspartate, glutamate and myo-inositol; and serum concentrations of estradiol. A second network replaced estradiol with chronological age. Expected influence (EI) of estradiol on the network was −1.190, relative to chronological age at −0.524, indicating that estradiol had a stronger expected influence over the network than age. A negative expected influence indicates that higher levels of estradiol would be expected to decrease the number of relationships in the model, which is thought to indicate lower risk. Overall, levels of estradiol appear more influential than chronological age at midlife for relationships between brain integrity and metabolic health. Elsevier 2022-10-14 /pmc/articles/PMC9997143/ /pubmed/36908891 http://dx.doi.org/10.1016/j.nbas.2022.100053 Text en © 2022 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Foret, Janelle T. Caillaud, Marie Gourley, Drew D. Dekhtyar, Maria Tanaka, Hirofumi Haley, Andreana P. Influence of endogenous estrogen on a network model of female brain integrity |
title | Influence of endogenous estrogen on a network model of female brain integrity |
title_full | Influence of endogenous estrogen on a network model of female brain integrity |
title_fullStr | Influence of endogenous estrogen on a network model of female brain integrity |
title_full_unstemmed | Influence of endogenous estrogen on a network model of female brain integrity |
title_short | Influence of endogenous estrogen on a network model of female brain integrity |
title_sort | influence of endogenous estrogen on a network model of female brain integrity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9997143/ https://www.ncbi.nlm.nih.gov/pubmed/36908891 http://dx.doi.org/10.1016/j.nbas.2022.100053 |
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