Unfavourable gender effect of high body mass index on brain metabolism and connectivity.

Aged; Aged, 80 and over; Alzheimer Disease/metabolism; Body Mass Index; Brain/metabolism; Female; Fluorodeoxyglucose F18/metabolism; Humans; Male; Membrane Potentials/physiology; Neural Pathways/physiopathology; Neurodegenerative Diseases/metabolism; Neuropsychological Tests; Obesity/complications/metabolism; Positron-Emission Tomography/methods; Risk Factors; Sex Factors

Abstract :

[en] The influence of Body Mass Index (BMI) on neurodegeneration in dementia has yet to be elucidated. We aimed at exploring the effects of BMI levels on cerebral resting-state metabolism and brain connectivity, as crucial measures of synaptic function and activity, in a large group of patients with Alzheimer's Dementia (AD) (n = 206), considering gender. We tested the correlation between BMI levels and brain metabolism, as assessed by (18)F-FDG-PET, and the modulation of the resting-state functional networks by BMI. At comparable dementia severity, females with high BMI can withstand a lower degree of brain metabolism dysfunction, as shown by a significant BMI-brain metabolism correlation in the temporal-parietal regions, which are typically vulnerable to AD pathology (R = 0.269, p = 0.009). Of note, high BMI was also associated with reduced connectivity in frontal and limbic brain networks, again only in AD females (p < 0.05 FDR-corrected, k = 100 voxels). This suggests a major vulnerability of neural systems known to be selectively involved in brain compensatory mechanisms in AD females. These findings indicate a strong gender effect of high BMI and obesity in AD, namely reducing the available reserve mechanisms in female patients. This brings to considerations for medical practice and health policy.

Disciplines :

Radiology, nuclear medicine & imaging

Author, co-author :

Malpetti, Maura

Sala, Arianna ; UniSR

Vanoli, Emilia Giovanna

Gianolli, Luigi

Luzi, Livio

Perani, Daniela

Language :

English

Title :

Unfavourable gender effect of high body mass index on brain metabolism and connectivity.

Publication date :

2018

Journal title :

Scientific Reports

eISSN :

2045-2322

Publisher :

Nature Publishing Group, London, United Kingdom

Volume :

Issue :

Pages :

12584

Peer reviewed :

Peer Reviewed verified by ORBi

Available on ORBi :

since 02 June 2021

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Bibliography

Emmerzaal, T. L., Kiliaan, A. J. & Gustafson, D. R. 2003–2013: A decade of body mass index, Alzheimer’s disease, and dementia. J. Alzheimer’s Dis. 43, 739–755 (2015)
García-Ptacek, S., Faxén-Irving, G., Cermáková, P., Eriksdotter, M. & Religa, D. Body mass index in dementia. Eur. J. Clin. Nutr. 1–6 https://doi.org/10.1038/ejcn.2014.199 (2014)
Smith, E., Hay, P., Campbell, L. & Trollor, J. N. A review of the association between obesity and cognitive function across the lifespan: Implications for novel approaches to prevention and treatment. Obes. Rev. 12, 740–755 (2011)
Elias, M. F., Elias, P. K., Sullivan, L. M., Wolf, P. A. & D’Agostino, R. B. Lower cognitive function in the presence of obesity and hypertension: the Framingham heart study. Int. J. Obes. 27, 260–268 (2003)
Gunstad, J. et al. Elevated body mass index is associated with executive dysfunction in otherwise healthy adults. Compr. Psychiatry 48, 57–61 (2007)
Liang, J., Matheson, B. E., Kaye, W. H. & Boutelle, K. N. Neurocognitive correlates of obesity and obesity-related behaviors in children and adolescents. Int. J. Obes. 38, 494–506 (2014)
Xu, W. L. et al. Midlife overweight and obesity increase late-life dementia risk: A population-based twin study. Neurology 76, 1568–1574 (2011)
Whitmer, R. A. Obesity in middle age and future risk of dementia: a 27 year longitudinal population based study. BMJ 330, 1360–0 (2005)
Fitzpatrick, A. L. et al. Midlife and late-life obesity and the risk of dementia: cardiovascular health study. Arch. Neurol. 66, 336–42 (2009)
Stewart, R. et al. A 32-Year Prospective Study of Change in Body Weight and Incident Dementia. Arch. Neurol. 62, 55 (2005)
Knopman, D. S., Edland, S. D., Cha, R. H., Petersen, R. C. & Rocca, W. A. Incident dementia in women is preceded by weight loss by at least a decade. Neurology 69, 739–746 (2007)
Dahl, A. K. & Hassing, L. B. Obesity and cognitive aging. Epidemiol. Rev. 35, 22–32 (2013)
Perani, D. FDG-PET and amyloid-PET imaging: the diverging paths. Curr. Opin. Neurol. 27, 405–413 (2014)
Iaccarino, L., Sala, A., Caminiti, S. P. & Perani, D. The emerging role of PET imaging in dementia. F1000Research 6, 1830 (2017)
Livingston, G. et al. Dementia prevention, intervention, and care. Lancet 390, 2673–2734 (2017)
Barulli, D. & Stern, Y. Efficiency, capacity, compensation, maintenance, plasticity: emerging concepts in cognitive reserve. Trends Cogn. Sci. 17, 502–9 (2013)
Garibotto, V. et al. Education and occupation as proxies for reserve in aMCI converters and AD: FDG-PET evidence. Neurology 71, 1342–1349 (2008)
Malpetti, M. et al. Gender differences in healthy aging and Alzheimer’s Dementia: A 18 F-FDG-PET study of brain and cognitive reserve. Hum. Brain Mapp. 00, (2017)
Morbelli, S. et al. Metabolic networks underlying cognitive reserve in prodromal Alzheimer disease: a European Alzheimer disease consortium project. J. Nucl. Med. 54, 894–902 (2013)
Perani, D. et al. The impact of bilingualism on brain reserve and metabolic connectivity in Alzheimer’s dementia. Proc. Natl. Acad. Sci. 114, 1690–1695 (2017)
Karp, A. et al. Relation of education and occupation-based socioeconomic status to incident Alzheimer’s disease. Am. J. Epidemiol. 159, 175–83 (2004)
Fraser, M. A., Shaw, M. E. & Cherbuin, N. A systematic review and meta-analysis of longitudinal hippocampal atrophy in healthy human ageing. Neuroimage 112, 364–374 (2015)
Raji, C. A. et al. Brain structure and obesity. Hum. Brain Mapp. 31, 353–364 (2010)
Walther, K., Birdsill, A. C., Glisky, E. L. & Ryan, L. Structural brain differences and cognitive functioning related to body mass index in older females. Hum. Brain Mapp. 31, 1052–1064 (2009)
Bobb, J. F., Schwartz, B. S., Davatzikos, C. & Caffo, B. Cross-sectional and longitudinal association of body mass index and brain volume. Hum. Brain Mapp. 35, 75–88 (2014)
Ho, A. J. et al. Obesity is linked with lower brain volume in 700 AD and MCI patients. Neurobiol. Aging 31, 1326–1339 (2010)
Ho, A. J. et al. Hippocampal volume is related to body mass index in Alzheimer’s disease. Neuroreport 22, 10–4 (2011)
Horwitz, B., Duara, R. & Rapoport, S. I. Intercorrelations of glucose metabolic rates between brain regions: application to healthy males in a state of reduced sensory input. J. Cereb. Blood Flow Metab. 4, 484–499 (1984)
Kullmann, S. et al. The obese brain: Association of body mass index and insulin sensitivity with resting state network functional connectivity. Hum. Brain Mapp. 33, 1052–1061 (2012)
García-García, I. et al. Alterations of the salience network in obesity: A resting-state fMRI study. Hum. Brain Mapp. 34, 2786–2797 (2013)
Volkow, N. D., Wang, G. J. & Baler, R. D. Reward, dopamine and the control of food intake: Implications for obesity. Trends Cogn. Sci. 15, 37–46 (2011)
Ogden, C. L., Carroll, M. D., Kit, B. K. & Flegal, K. M. Prevalence of Childhood and Adult Obesity in the United States, 2011–2012. Jama 311, 806 (2014)
Moser, V. A. & Pike, C. J. Obesity and sex interact in the regulation of Alzheimer’s disease. Neurosci. Biobehav. Rev. 67, 102–118 (2016)
Gustafson, D. R. et al. Mid-life adiposity factors relate to blood-brain barrier integrity in late life. J. Intern. Med. 262, 643–650 (2007)
Gustafson, D., Lissner, L., Bengtsson, C., Bjorkelund, C. & Skoog, I. A 24-year follow-up of body mass index and cerebral atrophy. Neurology 63, 1876–1881 (2004)
Mueller, K. et al. Sex-dependent influences of obesity on cerebral white matter investigated by diffusion-tensor imaging. PLoS One 6, (2011)
Verdile, G. et al. Inflammation and Oxidative Stress: The Molecular Connectivity between Insulin Resistance, Obesity, and Alzheimer’s Disease. Mediators Inflamm. 2015, 1–17 (2015)
McKhann, G. M. et al. The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers. Dement. 7, 263–9 (2011)
Perani, D. et al. Validation of an optimized SPM procedure for FDG-PET in dementia diagnosis in a clinical setting. NeuroImage Clin. 6, 445–454 (2014)
Varrone, A. et al. EANM procedure guidelines for PET brain imaging using [18F]FDG, version 2. Eur. J. Nucl. Med. Mol. Imaging 36, 2103–10 (2009)
Gallivanone, F. et al. The impact of different 18FDG PET healthy subject scans for comparison with single patient in SPM analysis. Q. J. Nucl. Med. Mol. Imaging 61, 115–132 (2017)
Della Rosa, P. A. et al. A Standardized [18F]-FDG-PET Template for Spatial Normalization in Statistical Parametric Mapping of Dementia. Neuroinformatics 12, 575–593 (2014)
Lee, D. S. et al. Metabolic connectivity by interregional correlation analysis using statistical parametric mapping (SPM) and FDG brain PET; methodological development and patterns of metabolic connectivity in adults. Eur. J. Nucl. Med. Mol. Imaging 35, 1681–1691 (2008)
Shirer, W. R., Ryali, S., Rykhlevskaia, E., Menon, V. & Greicius, M. D. Decoding subject-driven cognitive states with whole-brain connectivity patterns. Cereb. Cortex 22, 158–165 (2012)
Seeley, W. W. et al. Dissociable Intrinsic Connectivity Networks for Salience Processing and Executive Control. J. Neurosci. 27, 2349–2356 (2007)
Tomasi, D. & Volkow, N. D. Association between functional connectivity hubs and brain networks. Cereb. Cortex 21, 2003–2013 (2011)
Tziortzi, A. C. et al. Imaging dopamine receptors in humans with [11C]-(+)-PHNO: Dissection of D3 signal and anatomy. Neuroimage 54, 264–277 (2011)
Xia, M., Wang, J. & He, Y. BrainNet Viewer: a network visualization tool for human brain connectomics. PLoS One 8, e68910 (2013)