@article {1120, title = {Brain structure and obesity.}, journal = {Hum Brain Mapp}, volume = {31}, year = {2010}, month = {2010 Mar}, pages = {353-64}, abstract = {

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.

}, keywords = {Age Factors, Aged, Analysis of Variance, Body Mass Index, Brain, Continental Population Groups, Diabetes Mellitus, Type 2, Fasting, Female, Humans, Insulin, Magnetic Resonance Imaging, Male, Nerve Fibers, Myelinated, Nerve Fibers, Unmyelinated, Obesity, Organ Size, Regression Analysis, Sex Factors}, issn = {1097-0193}, doi = {10.1002/hbm.20870}, author = {Raji, Cyrus A and Ho, April J and Parikshak, Neelroop N and Becker, James T and Lopez, Oscar L and Kuller, Lewis H and Hua, Xue and Leow, Alex D and Toga, Arthur W and Thompson, Paul M} } @article {1208, title = {Obesity is linked with lower brain volume in 700 AD and MCI patients.}, journal = {Neurobiol Aging}, volume = {31}, year = {2010}, month = {2010 Aug}, pages = {1326-39}, 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{\textquoteright}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{\textquoteright}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 = {Aged, Aged, 80 and over, Alzheimer Disease, Atrophy, Body Mass Index, Brain, Cognition Disorders, Cohort Studies, Female, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Obesity, Organ Size, Prospective Studies, Risk Factors}, issn = {1558-1497}, doi = {10.1016/j.neurobiolaging.2010.04.006}, author = {Ho, April J and Raji, Cyrus A and Becker, James T and Lopez, Oscar L and Kuller, Lewis H and Hua, Xue and Lee, Suh and Hibar, Derrek and Dinov, Ivo D and Stein, Jason L and Jack, Clifford R and Weiner, Michael W and Toga, Arthur W and Thompson, Paul M} } @article {1225, title = {The effects of physical activity, education, and body mass index on the aging brain.}, journal = {Hum Brain Mapp}, volume = {32}, year = {2011}, month = {2011 Sep}, pages = {1371-82}, abstract = {

Normal human aging is accompanied by progressive brain tissue loss and cognitive decline; however, several factors are thought to influence brain aging. We applied tensor-based morphometry to high-resolution brain MRI scans to determine whether educational level or physical activity was associated with brain tissue volumes in the elderly, particularly in regions susceptible to age-related atrophy. We mapped the 3D profile of brain volume differences in 226 healthy elderly subjects (130F/96M; 77.9 {\textpm} 3.6 SD years) from the Cardiovascular Health Study-Cognition Study. Statistical maps revealed the 3D profile of brain regions whose volumes were associated with educational level and physical activity (based on leisure-time energy expenditure). After controlling for age, sex, and physical activity, higher educational levels were associated with ~2-3\% greater tissue volumes, on average, in the temporal lobe gray matter. After controlling for age, sex, and education, greater physical activity was associated with ~2-2.5\% greater average tissue volumes in the white matter of the corona radiata extending into the parietal-occipital junction. Body mass index (BMI) was highly correlated with both education and physical activity, so we examined BMI as a contributing factor by including physical activity, education, and BMI in the same model; only BMI effects remained significant. This is one of the largest MRI studies of factors influencing structural brain aging, and BMI may be a key factor explaining the observed relationship between education, physical activity, and brain structure. Independent contributions to brain structure could not be teased apart as all these factors were highly correlated with one another.

}, keywords = {Aged, Aged, 80 and over, Aging, Analysis of Variance, Body Mass Index, Brain, Brain Mapping, Educational Status, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Motor Activity, Neuropsychological Tests, Statistics as Topic}, issn = {1097-0193}, doi = {10.1002/hbm.21113}, author = {Ho, April J and Raji, Cyrus A and Becker, James T and Lopez, Oscar L and Kuller, Lewis H and Hua, Xue and Dinov, Ivo D and Stein, Jason L and Rosano, Caterina and Toga, Arthur W and Thompson, Paul M} }