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Framingham Coronary Heart Disease Risk Score Can be Predicted from Structural Brain Images in Elderly Subjects
Recent literature has presented evidence that cardiovascular risk factors (CVRF) play an important role on cognitive performance in elderly individuals, both those who are asymptomatic and those who suffer from symptoms of neurodegenerative disorders. Findings from studies applying neuroimaging meth...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4249461/ https://www.ncbi.nlm.nih.gov/pubmed/25520654 http://dx.doi.org/10.3389/fnagi.2014.00300 |
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author | Rondina, Jane Maryam Squarzoni, Paula Souza-Duran, Fabio Luis Tamashiro-Duran, Jaqueline Hatsuko Scazufca, Marcia Menezes, Paulo Rossi Vallada, Homero Lotufo, Paulo A. de Toledo Ferraz Alves, Tania Correa Busatto Filho, Geraldo |
author_facet | Rondina, Jane Maryam Squarzoni, Paula Souza-Duran, Fabio Luis Tamashiro-Duran, Jaqueline Hatsuko Scazufca, Marcia Menezes, Paulo Rossi Vallada, Homero Lotufo, Paulo A. de Toledo Ferraz Alves, Tania Correa Busatto Filho, Geraldo |
author_sort | Rondina, Jane Maryam |
collection | PubMed |
description | Recent literature has presented evidence that cardiovascular risk factors (CVRF) play an important role on cognitive performance in elderly individuals, both those who are asymptomatic and those who suffer from symptoms of neurodegenerative disorders. Findings from studies applying neuroimaging methods have increasingly reinforced such notion. Studies addressing the impact of CVRF on brain anatomy changes have gained increasing importance, as recent papers have reported gray matter loss predominantly in regions traditionally affected in Alzheimer’s disease (AD) and vascular dementia in the presence of a high degree of cardiovascular risk. In the present paper, we explore the association between CVRF and brain changes using pattern recognition techniques applied to structural MRI and the Framingham score (a composite measure of cardiovascular risk largely used in epidemiological studies) in a sample of healthy elderly individuals. We aim to answer the following questions: is it possible to decode (i.e., to learn information regarding cardiovascular risk from structural brain images) enabling individual predictions? Among clinical measures comprising the Framingham score, are there particular risk factors that stand as more predictable from patterns of brain changes? Our main findings are threefold: (i) we verified that structural changes in spatially distributed patterns in the brain enable statistically significant prediction of Framingham scores. This result is still significant when controlling for the presence of the APOE 4 allele (an important genetic risk factor for both AD and cardiovascular disease). (ii) When considering each risk factor singly, we found different levels of correlation between real and predicted factors; however, single factors were not significantly predictable from brain images when considering APOE4 allele presence as covariate. (iii) We found important gender differences, and the possible causes of that finding are discussed. |
format | Online Article Text |
id | pubmed-4249461 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-42494612014-12-17 Framingham Coronary Heart Disease Risk Score Can be Predicted from Structural Brain Images in Elderly Subjects Rondina, Jane Maryam Squarzoni, Paula Souza-Duran, Fabio Luis Tamashiro-Duran, Jaqueline Hatsuko Scazufca, Marcia Menezes, Paulo Rossi Vallada, Homero Lotufo, Paulo A. de Toledo Ferraz Alves, Tania Correa Busatto Filho, Geraldo Front Aging Neurosci Neuroscience Recent literature has presented evidence that cardiovascular risk factors (CVRF) play an important role on cognitive performance in elderly individuals, both those who are asymptomatic and those who suffer from symptoms of neurodegenerative disorders. Findings from studies applying neuroimaging methods have increasingly reinforced such notion. Studies addressing the impact of CVRF on brain anatomy changes have gained increasing importance, as recent papers have reported gray matter loss predominantly in regions traditionally affected in Alzheimer’s disease (AD) and vascular dementia in the presence of a high degree of cardiovascular risk. In the present paper, we explore the association between CVRF and brain changes using pattern recognition techniques applied to structural MRI and the Framingham score (a composite measure of cardiovascular risk largely used in epidemiological studies) in a sample of healthy elderly individuals. We aim to answer the following questions: is it possible to decode (i.e., to learn information regarding cardiovascular risk from structural brain images) enabling individual predictions? Among clinical measures comprising the Framingham score, are there particular risk factors that stand as more predictable from patterns of brain changes? Our main findings are threefold: (i) we verified that structural changes in spatially distributed patterns in the brain enable statistically significant prediction of Framingham scores. This result is still significant when controlling for the presence of the APOE 4 allele (an important genetic risk factor for both AD and cardiovascular disease). (ii) When considering each risk factor singly, we found different levels of correlation between real and predicted factors; however, single factors were not significantly predictable from brain images when considering APOE4 allele presence as covariate. (iii) We found important gender differences, and the possible causes of that finding are discussed. Frontiers Media S.A. 2014-12-01 /pmc/articles/PMC4249461/ /pubmed/25520654 http://dx.doi.org/10.3389/fnagi.2014.00300 Text en Copyright © 2014 Rondina, Squarzoni, Souza-Duran, Tamashiro-Duran, Scazufca, Menezes, Vallada, Lotufo, de Toledo Ferraz Alves and Busatto Filho. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Rondina, Jane Maryam Squarzoni, Paula Souza-Duran, Fabio Luis Tamashiro-Duran, Jaqueline Hatsuko Scazufca, Marcia Menezes, Paulo Rossi Vallada, Homero Lotufo, Paulo A. de Toledo Ferraz Alves, Tania Correa Busatto Filho, Geraldo Framingham Coronary Heart Disease Risk Score Can be Predicted from Structural Brain Images in Elderly Subjects |
title | Framingham Coronary Heart Disease Risk Score Can be Predicted from Structural Brain Images in Elderly Subjects |
title_full | Framingham Coronary Heart Disease Risk Score Can be Predicted from Structural Brain Images in Elderly Subjects |
title_fullStr | Framingham Coronary Heart Disease Risk Score Can be Predicted from Structural Brain Images in Elderly Subjects |
title_full_unstemmed | Framingham Coronary Heart Disease Risk Score Can be Predicted from Structural Brain Images in Elderly Subjects |
title_short | Framingham Coronary Heart Disease Risk Score Can be Predicted from Structural Brain Images in Elderly Subjects |
title_sort | framingham coronary heart disease risk score can be predicted from structural brain images in elderly subjects |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4249461/ https://www.ncbi.nlm.nih.gov/pubmed/25520654 http://dx.doi.org/10.3389/fnagi.2014.00300 |
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