Higher body mass index in older adults is associated with lower gray matter volume: implications for memory performance

Masouleh, Shahrzad Kharabian; Arélin, Katrin; Horstmann, Annette; Lampe, Leonie; Kipping, Judy; Luck, Tobias; Riedel‐Heller, Steffi G.; Schroeter, Matthias L.; Stümvoll, Michael; Villringer, Arno; Witte, A. Veronica

doi:10.1016/j.neurobiolaging.2015.12.020

Cited by 88 publications

(75 citation statements)

References 81 publications

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“…Analyzing two separate community based samples (1586 adults with a mean age of 46 years and 758 adults with a mean age of 50 years), Janowitz et al showed largely overlapping negative associations between rGMV and waist circumference for both samples, that included bilateral frontal, temporal and occipital lobes, somatosensory and motor cortex, insula, cingulate gyrus, hippocampal formation, subcortical structures (i.e., thalamus, caudate nucleus, putamen, globus pallidus) and the cerebellum 6 . Similar observations were made in a sample of 617 older subjects (mean age 68 years), additionally linking these structural alterations to impaired memory performance 8 . Importantly, results of both studies were not significantly affected by obesity-associated comorbidities, such as type 2 diabetes, hypertension and dyslipidemia.…”

Section: Discussionsupporting

confidence: 69%

The obese brain as a heritable phenotype: a combined morphometry and twin study

et al. 2016

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Background Body weight and adiposity are heritable traits. To date it remains unknown whether obesity-associated brain structural alterations are under a similar level of genetic control. Methods For this study we utilized magnetic resonance imaging (MRI) data from the Human Connectome Project. Voxel based morphometry (VBM) was used to investigate associations between body mass index (BMI) and regional gray matter volume (GMV) in a sample of 875 young adults with a wide BMI range (386m/489f; age 28.8 ± 3.7y; BMI 26.6 ± 5.3 kg*m-2), that included 86 pairs of monozygotic twins and 82 pairs of dizygotic twins. Twin data were analyzed by applying the additive genetic, common environmental and residual effects (ACE) model to determine heritability of brain regions that were associated with BMI. Results We observed positive associations between BMI and GMV in the ventromedial prefrontal cortex and the right cerebellum and widespread negative associations within the prefrontal cortex, cerebellum, temporal lobes and distinct subcortical structures. Varying degrees of heritability were found for BMI-associated brain regions, with highest heritability estimates for cerebellar GMV and subcortical structures. Conclusions These data indicate that brain regions associated with obesity are subject to differing levels of genetic control and environmental influences. Specific brain regions with high heritability might represent an inherent vulnerability factor for obesity.

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Section: Discussionsupporting

confidence: 69%

The obese brain as a heritable phenotype: a combined morphometry and twin study

et al. 2016

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“…This leads us to believe that our sample represents subjects vulnerable to the adverse effects of obesity on cognition who have not yet experienced prodromal dementia‐related weight loss. Other studies reporting BMI to be associated with gray matter volume decline and cognitive deficits in old‐age [Kharabian Masouleh et al, ; Walther et al, ] support this association of obesity and brain damage in older subjects.…”

Section: Discussionmentioning

confidence: 82%

“…This allowed us to reduce number of comparisons and investigate specific cognitive domains. Composite scores for executive function, memory performance and processing speed were calculated as follows [Kharabian Masouleh et al, ]: executive functions = [z_phonemic fluency + z_semantic fluency + z_TMT(part B + part A)/part A]/3; memory = (z_sum_learning þ z_recall þ z_recognition)/3; processing speed = −z (TMT [part A]).…”

Section: Methodsmentioning

confidence: 99%

Higher body mass index is associated with reduced posterior default mode connectivity in older adults

Beyer

Masouleh

Huntenburg

et al. 2017

Human Brain Mapping

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Obesity is a complex neurobehavioral disorder that has been linked to changes in brain structure and function. However, the impact of obesity on functional connectivity and cognition in aging humans is largely unknown. Therefore, the association of body mass index (BMI), resting-state network connectivity, and cognitive performance in 712 healthy, well-characterized older adults of the Leipzig Research Center for Civilization Diseases (LIFE) cohort (60-80 years old, mean BMI 27.6 kg/m ± 4.2 SD, main sample: n = 521, replication sample: n = 191) was determined. Statistical analyses included a multivariate model selection approach followed by univariate analyses to adjust for possible confounders. Results showed that a higher BMI was significantly associated with lower default mode functional connectivity in the posterior cingulate cortex and precuneus. The effect remained stable after controlling for age, sex, head motion, registration quality, cardiovascular, and genetic factors as well as in replication analyses. Lower functional connectivity in BMI-associated areas correlated with worse executive function. In addition, higher BMI correlated with stronger head motion. Using 3T neuroimaging in a large cohort of healthy older adults, independent negative associations of obesity and functional connectivity in the posterior default mode network were observed. In addition, a subtle link between lower resting-state connectivity in BMI-associated regions and cognitive function was found. The findings might indicate that obesity is associated with patterns of decreased default mode connectivity similar to those seen in populations at risk for Alzheimer's disease. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc.

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“…Although not fully elucidated, there is a growing body of evidence suggesting that sleep is crucial for the removal of neurotoxic byproducts (Berezuk, et al, 2015,Lucey and Bateman, 2014,Sanchez-Espinosa, et al, 2014,Spira, et al, 2013,Sprecher, et al, 2015,Xie, et al, 2013). However, poor sleep (reduced, fragmented, with apneas) leads to metabolic and cardiovascular dysfunction (Mesas, et al, 2014,Mullington, et al, 2009,Roux, et al, 2000,Strand, et al, 2015), which are also associated with imaging (Goldstein, et al, 2002,Kharabian Masouleh, et al, 2016,Kumar, et al, 2015,Langbaum, et al, 2012,Moran, et al, 2015,Peng, et al, 2015,Soininen, et al, 1992,Villeneuve, et al, 2014) and neuropathological (Gelber, et al, 2015) findings of neurodegeneration, to which depression may also contribute (Elcombe, et al, 2015). Therefore, EDS and fatigue can possibly be an epiphenomenon of impaired clearance/accumulation of metabolic neurotoxic byproducts during sleep or neurodegeneration of areas related to maintenance of wakefulness.…”

Section: Discussionmentioning

confidence: 99%

Excessive daytime sleepiness and fatigue may indicate accelerated brain aging in cognitively normal late middle-aged and older adults

et al. 2017

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Excessive daytime sleepiness (EDS) and fatigue increases with age. The aim of this study was to investigate the association between EDS and fatigue with cortical thickness and hippocampal volume in cognitively normal, late middle-aged and older adults. We performed a cross-sectional observational study of 1374 cognitively-normal subjects aged 50 years and older who had a structural MRI. Regional cortical thickness and hippocampal volume were measured. Multiple linear regression models were fit to explore associations between EDS and fatigue and structural MRI measures in different brain regions, adjusting for multiple covariates. EDS was defined as Epworth Sleepiness Scale ≥10. Fatigue severity was assessed with the Beck Depression Inventory-2. 208 participants had EDS, 27 had significant fatigue, and 11 had both. Participants with EDS or fatigue had significantly lower cognitive scores, more disturbed sleep, and medical comorbidities. The presence of EDS was associated with both global and regional atrophy, whereas fatigue was more associated with frontal and temporal changes. Cortical thinning predicted by EDS and fatigue was maximal in the temporal region with average reduction of 34.2 µm (95% CI, −54.1, −14.3; P=.001) and 90.2 µm (95% CI, −142.1, −38.2; P=.001), respectively. Fatigue was also associated with hippocampal volume reduction of −374.2 mm3 (95%CI, −670.8, −77.7; P=.013). Temporal cortical thinning predicted by presence of EDS and fatigue was equivalent to more than 3.5 and nine additional years of aging, respectively. EDS and fatigue were associated with cortical thickness reduction primarily in regions with increased age-susceptibility, which may indicate accelerated brain aging.

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Higher body mass index in older adults is associated with lower gray matter volume: implications for memory performance

Cited by 88 publications

References 81 publications

The obese brain as a heritable phenotype: a combined morphometry and twin study

The obese brain as a heritable phenotype: a combined morphometry and twin study

Higher body mass index is associated with reduced posterior default mode connectivity in older adults

Excessive daytime sleepiness and fatigue may indicate accelerated brain aging in cognitively normal late middle-aged and older adults

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