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  Gray matter structural networks are associated with cardiovascular risk factors in healthy older adults

Kharabian, S., Beyer, F., Lampe, L., Loeffler, M., Luck, T., Riedel-Heller, S. G., et al. (2018). Gray matter structural networks are associated with cardiovascular risk factors in healthy older adults. Journal of Cerebral Blood Flow and Metabolism, 38(2), 360-372. doi:10.1177/0271678X17729111.

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 Creators:
Kharabian, Shahrzad1, Author           
Beyer, Frauke1, Author           
Lampe, Leonie1, 2, Author           
Loeffler, Markus2, 3, Author
Luck, Tobias2, 4, Author
Riedel-Heller, Steffi G.4, Author
Schroeter, Matthias L.1, 2, 5, Author           
Stumvoll, Michael6, Author
Villringer, Arno1, 5, Author           
Witte, Veronica1, Author           
Affiliations:
1Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634549              
2Leipzig Research Center for Civilization Diseases (LIFE), University of Leipzig, Germany, ou_persistent22              
3Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Germany, ou_persistent22              
4Institute of Social Medicine, Occupational Health and Public Health (ISAP), University Hospital Leipzig, Germany, ou_persistent22              
5Clinic for Cognitive Neurology, University of Leipzig, Germany, ou_persistent22              
6Integrated Research and Treatment Center Adiposity Diseases, University of Leipzig, Germany, ou_persistent22              

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Free keywords: Alzheimer's disease; Aging; Brain structure; Gray matter modifiers; Independent component analysis; Structural covariance
 Abstract: While recent ‘big data' analyses discovered structural brain networks that alter with age and relate to cognitive decline, identifying modifiable factors that prevent these changes remains a major challenge. We therefore aimed to determine the effects of common cardiovascular risk factors on vulnerable gray matter (GM) networks in a large and well-characterized population-based cohort. In 616 healthy elderly (258 women, 60–80 years) of the LIFE-Adult-Study, we assessed the effects of obesity, smoking, blood pressure, markers of glucose and lipid metabolism as well as physical activity on major GM-networks derived using linked independent component analysis. Age, sex, hypertension, diabetes, white matter hyperintensities, education and depression were considered as confounders. Results showed that smoking, higher blood pressure, and higher glycated hemoglobin (HbA1c) were independently associated with lower GM volume and thickness in GM-networks that covered most areas of the neocortex. Higher waist-to-hip ratio was independently associated with lower GM volume in a network of multimodal regions that correlated negatively with age and memory performance. In this large cross-sectional study, we found selective negative associations of smoking, higher blood pressure, higher glucose, and visceral obesity with structural covariance networks, suggesting that reducing these factors could help to delay late-life trajectories of GM aging.

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Language(s): eng - English
 Dates: 2017-07-082017-05-042017-07-172017-08-312018-02-01
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1177/0271678X17729111
PMID: 28857651
PMC: PMC5951018
Other: Epub 2017
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Funding organization : European Union (EU)
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Funding program : European Regional Development Fund (ERDF)
Funding organization : European Commission (EC)
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Funding organization : Free State of Saxony
Project name : -
Grant ID : 713-241202 ; 14505/2470 ; 14575/2470
Funding program : -
Funding organization : LIFE – Leipzig Research Center for Civilization Diseases at the University of Leipzig
Project name : Obesity Mechanisms / SFB 1052
Grant ID : -
Funding program : -
Funding organization : Deutsche Forschungsgemeinschaft (DFG)

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Title: Journal of Cerebral Blood Flow and Metabolism
Source Genre: Journal
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Affiliations:
Publ. Info: New York : Lippincott Williams & Wilkins
Pages: - Volume / Issue: 38 (2) Sequence Number: - Start / End Page: 360 - 372 Identifier: ISSN: 0271-678X
CoNE: https://pure.mpg.de/cone/journals/resource/954925503202