@article{3d740a23a37b4869bd021f8092ba4926,
title = "Obesity is linked with lower brain volume in 700 AD and MCI patients",
abstract = "Obesity is associated with lower brain volumes in cognitively normal elderly subjects, but no study has yet investigated the effects of obesity on brain structure in patients with mild cognitive impairment (MCI) or Alzheimer's disease (AD). To determine if higher body mass index (BMI) is associated with brain volume deficits in cognitively impaired elderly subjects, we analyzed brain magnetic resonance imaging (MRI) scans of 700 MCI or AD patients from 2 different cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Cardiovascular Health Study-Cognition Study (CHS-CS). Tensor-based morphometry (TBM) was used to create 3-dimensional maps of regional tissue excess or deficits in subjects with MCI (ADNI, n = 399; CHS-CS, n = 77) and AD (ADNI, n = 188; CHS, n = 36). In both AD and MCI groups, higher body mass index was associated with brain volume deficits in frontal, temporal, parietal, and occipital lobes; the atrophic pattern was consistent in both ADNI and CHS populations. Cardiovascular risk factors, especially obesity, should be considered as influencing brain structure in those already afflicted by cognitive impairment and dementia.",
keywords = "ADNI, Alzheimer's disease, Body mass index (BMI), Brain structure, Mild cognitive impairment, Tensor-based morphometry",
author = "Ho, {April J.} and Raji, {Cyrus A.} and Becker, {James T.} and Lopez, {Oscar L.} and Kuller, {Lewis H.} and Xue Hua and Suh Lee and Derrek Hibar and Dinov, {Ivo D.} and Stein, {Jason L.} and Jack, {Clifford R.} and Weiner, {Michael W.} and Toga, {Arthur W.} and Thompson, {Paul M.}",
note = "Funding Information: Algorithm development and image analysis for this study was funded by grants (to PT) from the NIBIB ( R01 EB007813 , R01 EB008281 , R01 EB008432 ), NICHD ( R01 HD050735 ), and NIA ( R01 AG020098 ), and National Institutes of Health through the NIH Roadmap for Medical Research Grants U54-RR021813 (Center for Computational Biology) (to AWT and PT). Funding Information: The authors have no competing financial or other interests that might have affected this research. The study reported in this article was supported, in part, by funds from the National Institute of Aging (to OLL; AG20098 , AG05133 ) (and to LK; AG15928 ), and by contract numbers N01-HC-85079 through N01-HC-85086 , N01-HC-35129 , N01 HC-15103 , N01 HC-55222 , N01-HC-75150 , N01-HC-45133 , and grant number U01 HL080295 from the National Heart, Lung, and Blood Institute , with additional contribution from the National Institute of Neurological Disorders and Stroke. A full list of principal CHS investigators and institutions may be found at www.chs-nhlbi.org/pi.htm . Funding Information: This study was also funded by an American Heart Association Predoctoral Grant (to CAR; 0815465D ), and by NITP (Neuroimaging Training Program), ARCS , and National Science Foundation Graduate Research Fellowship Program funding (to AJH). CAR was supported by the Radiological Society of North America Medical Student Research Grant ( RMS0717 ).",
year = "2010",
month = aug,
doi = "10.1016/j.neurobiolaging.2010.04.006",
language = "English (US)",
volume = "31",
pages = "1326--1339",
journal = "Neurobiology of aging",
issn = "0197-4580",
publisher = "Elsevier Inc.",
number = "8",
}