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Framingham coronary heart disease risk score can be predicted from structural brain images in elderly subjects

Rondina, JM; Squarzoni, P; Souza-Duran, FL; Tamashiro-Duran, JH; Scazufca, M; Menezes, PR; Vallada, H; ... Filho, GB; + view all (2014) Framingham coronary heart disease risk score can be predicted from structural brain images in elderly subjects. Frontiers in Aging Neuroscience , 6 , Article 300. 10.3389/fnagi.2014.00300. Green open access

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Abstract

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.

Type: Article
Title: Framingham coronary heart disease risk score can be predicted from structural brain images in elderly subjects
Open access status: An open access version is available from UCL Discovery
DOI: 10.3389/fnagi.2014.00300
Publisher version: http://dx.doi.org/10.3389/fnagi.2014.00300
Language: English
Additional information: © 2014 Rondina, Squarzoni, Souza-Duran, Tamashiro-Duran, Scazufca, Menezes, Vallada, Lotufo, de Toledo Ferraz Alves and Busatto Filho. 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.
Keywords: Framingham score, cardiovascular risk factors, magnetic resonance imaging, pattern recognition, multivariate analysis, MILD COGNITIVE IMPAIRMENT, APOLIPOPROTEIN-E EPSILON-4, EARLY ALZHEIMERS-DISEASE, VOXEL-BASED MORPHOMETRY, POSTERIOR CINGULATE CORTEX, MIDLIFE BLOOD-PRESSURE, GRAY-MATTER VOLUME, CARDIOVASCULAR RISK, APOE EPSILON-4, VASCULAR RISK
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Clinical and Movement Neurosciences
URI: http://discovery.ucl.ac.uk/id/eprint/1572108
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