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Brain structure and obesity
Open accessAbstract
Obesity is associated with increased risk for cardiovascular health problems including diabetes, hypertension, and stroke. These cardiovascular afflictions increase risk for cognitive decline and dementia, but it is unknown whether these factors, specifically obesity and Type II diabetes, are associated with specific patterns of brain atrophy. We used tensor‐based morphometry (TBM) to examine gray matter (GM) and white matter (WM) volume differences in 94 elderly subjects who remained cognitively normal for at least 5 years after their scan. Bivariate analyses with corrections for multiple comparisons strongly linked body mass index (BMI), fasting plasma insulin (FPI) levels, and Type II Diabetes Mellitus (DM2) with atrophy in frontal, temporal, and subcortical brain regions. A multiple regression model, also correcting for multiple comparisons, revealed that BMI was still negatively correlated with brain atrophy (FDR <5%), while DM2 and FPI were no longer associated with any volume differences. In an Analysis of Covariance (ANCOVA) model controlling for age, gender, and race, obese subjects with a high BMI (BMI > 30) showed atrophy in the frontal lobes, anterior cingulate gyrus, hippocampus, and thalamus compared with individuals with a normal BMI (18.5–25). Overweight subjects (BMI: 25–30) had atrophy in the basal ganglia and corona radiata of the WM. Overall brain volume did not differ between overweight and obese persons. Higher BMI was associated with lower brain volumes in overweight and obese elderly subjects. Obesity is therefore associated with detectable brain volume deficits in cognitively normal elderly subjects. Hum Brain Mapp, 2010. © 2009 Wiley‐Liss, Inc.
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Cites
Neuropathological stageing of Alzheimer-related changes.
Braak, H., & Braak, E. (1991) · Acta Neuropathologica · doi:10.1007/bf00308809 · Cited by 16,123
Voxel-Based Morphometry—The Methods
Ashburner, J., & Friston, K. J. (2000) · NeuroImage · doi:10.1006/nimg.2000.0582 · Cited by 8,676
The Alzheimer’s disease neuroimaging initiative (ADNI): MRI methods
Jack, C. R., Bernstein, M. A., Fox, N. C., Thompson, P., Alexander, G., Harvey, D., Borowski, B., Britson, P. J., L. Whitwell, J., Ward, C., et al. (2008) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.21049 · Cited by 4,347
The Cardiovascular Health Study: design and rationale.
Fried, L. P., Borhani, N. O., Enright, P., Furberg, C. D., Gardin, J. M., Kronmal, R. A., Kuller, L. H., Manolio, T. A., Mittelmark, M. B., Newman, A., et al. (1991) · Annals of Epidemiology · doi:10.1016/1047-2797(91)90005-w · Cited by 3,652
Self-citationEdgington, E., Edgington, E., & Onghena, P. (2007) · doi:10.1201/9781420011814 · Cited by 2,030
Cortisol levels during human aging predict hippocampal atrophy and memory deficits
Lupien, S. J., de Leon, M., de Santi, S., Convit, A., Tarshish, C., Nair, N. P. V., Thakur, M., McEwen, B. S., Hauger, R. L., & Meaney, M. J. (1998) · Nature Neuroscience · doi:10.1038/271 · Cited by 1,653
Aerobic fitness reduces brain tissue loss in aging humans.
Colcombe, S. J., Erickson, K. I., Raz, N., Webb, A. G., Cohen, N. J., McAuley, E., & Kramer, A. F. (2003) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/58.2.m176 · Cited by 1,017
Growth patterns in the developing brain detected by using continuum mechanical tensor maps
Thompson, P. M., Giedd, J. N., Woods, R. P., MacDonald, D., Evans, A. C., & Toga, A. W. (2000) · Nature · doi:10.1038/35004593 · Cited by 850
Self-citationRisk of Dementia among Persons with Diabetes Mellitus: A Population-based Cohort Study
Leibson, C. L., Rocca, W. A., Hanson, V. A., Cha, R., Kokmen, E., O'Brien, P. C., & Palumbo, P. J. (1997) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a009106 · Cited by 700
Conversion of Mild Cognitive Impairment to Alzheimer Disease Predicted by Hippocampal Atrophy Maps
Apostolova, L. G., Dutton, R. A., Dinov, I. D., Hayashi, K. M., Toga, A. W., Cummings, J. L., & Thompson, P. M. (2006) · Archives of Neurology · doi:10.1001/archneur.63.5.693 · Cited by 553
Self-citationBrain abnormalities in human obesity: A voxel-based morphometric study
Pannacciulli, N., Del Parigi, A., Chen, K., Le, D. S. N. T., Reiman, E. M., & Tataranni, P. A. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.01.047 · Cited by 523
Lopez, O. L., Jagust, W. J., Dulberg, C., Becker, J. T., DeKosky, S. T., Fitzpatrick, A., Breitner, J., Lyketsos, C., Jones, B., Kawas, C., et al. (2003) · Archives of Neurology · doi:10.1001/archneur.60.10.1394 · Cited by 477
Self-citationObesity, diabetes and cognitive deficit: The Framingham Heart Study
Elias, M. F., Elias, P. K., Sullivan, L. M., Wolf, P. A., & D’Agostino, R. B. (2005) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2005.08.019 · Cited by 395
Wolf, P., Beiser, A., Elias, M., Au, R., Vasan, R., & Seshadri, S. (2007) · Current Alzheimer Research · doi:10.2174/156720507780362263 · Cited by 254
Body mass index and magnetic resonance markers of brain integrity in adults
Gazdzinski, S., Kornak, J., Weiner, M. W., & Meyerhoff, D. J. (2008) · Annals of Neurology · doi:10.1002/ana.21377 · Cited by 191
Classification of vascular dementia in the Cardiovascular Health Study Cognition Study
Lopez, O. L., Kuller, L. H., Becker, J. T., Jagust, W. J., DeKosky, S. T., Fitzpatrick, A., Breitner, J., Lyketsos, C., Kawas, C., & Carlson, M. (2005) · Neurology · doi:10.1212/01.wnl.0000159860.19413.c4 · Cited by 109
Self-citationDiabetes mellitus and gait dysfunction: possible explanatory factors
Brach, J. S., Talkowski, J. B., Strotmeyer, E. S., & Newman, A. B. (2008) · Physical Therapy · doi:10.2522/ptj.20080016 · Cited by 101
Fasting Insulin Levels and Cognitive Decline in Older Women without Diabetes
van Oijen, M., Okereke, O. I., Kang, J. H., Pollak, M. N., Hu, F. B., Hankinson, S. E., & Grodstein, F. (2008) · Neuroepidemiology · doi:10.1159/000126909 · Cited by 44
Cited by
Reward, dopamine and the control of food intake: implications for obesity
Volkow, N. D., Wang, G.-J., & Baler, R. D. (2011) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.11.001 · Cited by 1,400
Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements
Tustison, N. J., Cook, P. A., Klein, A., Song, G., Das, S. R., Duda, J. T., Kandel, B. M., van Strien, N., Stone, J. R., Gee, J. C., et al. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.05.044 · Cited by 670
Obesity: Overview of an Epidemic
Mitchell, N. S., Catenacci, V. A., Wyatt, H. R., & Hill, J. O. (2011) · Psychiatric Clinics of North America · doi:10.1016/j.psc.2011.08.005 · Cited by 526
Impact of Metabolic Syndrome on Cognition and Brain: A Selected Review of the Literature
Yates, K. F., Sweat, V., Yau, P. L., Turchiano, M. M., & Convit, A. (2012) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/atvbaha.112.252759 · Cited by 444
Kim, P., Leckman, J. F., Mayes, L. C., Feldman, R., Wang, X., & Swain, J. E. (2010) · Behavioral Neuroscience · doi:10.1037/a0020884 · Cited by 440
Metadata
- Authors
- Raji, C. A., Ho, A. J., Parikshak, N. N., Becker, J. T., Lopez, O. L., Kuller, L. H., Hua, X., Leow, A. D., Toga, A. W., & Thompson, P. M.
- Venue
- Human Brain Mapping
- Publisher
- Wiley
- Published
- 2009-08-06
- Volume
- 31
- Issue
- 3
- Pages
- 353-364
- ISSN
- 1065-9471 (ISSN-L)
- 1097-0193
- OpenAlex
- W2069147780
- Cited by
- 686
- References
- 18
- FWCI
- 19.57
- Type
- journal article
- Language
- en
- Open access
- green
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