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

Author(s)

Rondina, Jane Maryam ^{[1, 2]} ; Squarzoni, Paula ^{[1, 3]} ; Souza-Duran, Fabio Luis ^{[1, 3]} ; Tamashiro-Duran, Jaqueline Hatsuko ^{[1, 3]} ; Scazufca, Marcia ^[4] ; Menezes, Paulo Rossi ^[5] ; Vallada, Homero ^{[3, 4]} ; Lotufo, Paulo A. ^[6] ; Alves, Tania Correade Toledo Ferraz ^{[1, 3, 4]} ; Filho, Geraldo Busatto ^{[1, 3, 4]}

Affiliation

^[1] Univ Sao Paulo, Fac Med, Dept Psychiat, Lab Psychiat Neuroimaging LIM 21, Sao Paulo, SP - Brazil

^[2] UCL, Dept Comp Sci, Ctr Comp Stat & Machine Learning, London - England

^[3] Univ Sao Paulo, NAPNA, Sao Paulo, SP - Brazil

^[4] Univ Sao Paulo, Dept & Inst Psychiat, Sao Paulo, SP - Brazil

^[5] Univ Sao Paulo, Dept Prevent Med, Sao Paulo, SP - Brazil

^[6] Univ Sao Paulo, Ctr Clin & Epidemiol Res, Sao Paulo, SP - Brazil

• Document type: Journal article
• Source: FRONTIERS IN AGING NEUROSCIENCE; v. 6, DEC 1 2014.
• Web of Science Citations: 2

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. (AU)

• FAPESP's process: 04/15336-5 - Brain abnormalities associated with cardiovascular risk factors: a population-based study using voxel-a-voxel morphometry by magnetic resonance and measures of glucose metabolism by positron-emission tomography
• Grantee: Geraldo Busatto Filho
• Support Opportunities: Regular Research Grants
• FAPESP's process: 13/03231-3 - Patterns of cortical atrophy and cognitive deficits associated with healthy aging: a structural magnetic resonance imaging study
• Grantee: Paula Squarzoni da Silveira
• Support Opportunities: Scholarships in Brazil - Doctorate