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| 001 | 866306 | ||
| 005 | 20210130003356.0 | ||
| 024 | 7 | _ | |a 10.3389/fnagi.2019.00202 |2 doi |
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| 100 | 1 | _ | |a Beyer, Frauke |b 0 |
| 245 | _ | _ | |a A Metabolic Obesity Profile Is Associated With Decreased Gray Matter Volume in Cognitively Healthy Older Adults |
| 260 | _ | _ | |a Lausanne |c 2019 |b Frontiers Research Foundation |
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| 520 | _ | _ | |a Obesity is a risk factor for cognitive decline and gray matter volume loss in aging. Studies have shown that different metabolic factors, e.g., dysregulated glucose metabolism and systemic inflammation, might mediate this association. Yet, even though these risk factors tend to co-occur, they have mostly been investigated separately, making it difficult to establish their joint contribution to gray matter volume structure in aging. Here, we therefore aimed to determine a metabolic profile of obesity that takes into account different anthropometric and metabolic measures to explain differences in gray matter volume in aging. We included 748 elderly, cognitively healthy participants (age range: 60 – 79 years, BMI range: 17 – 42 kg/m2) of the LIFE-Adult Study. All participants had complete information on body mass index, waist-to-hip ratio, glycated hemoglobin, total blood cholesterol, high-density lipoprotein, interleukin-6, C-reactive protein, adiponectin and leptin. Voxelwise gray matter volume was extracted from T1-weighted images acquired on a 3T Siemens MRI scanner. We used partial least squares correlation to extract latent variables with maximal covariance between anthropometric, metabolic and gray matter volume and applied permutation/bootstrapping and cross-validation to test significance and reliability of the result. We further explored the association of the latent variables with cognitive performance. Permutation tests and cross-validation indicated that the first pair of latent variables was significant and reliable. The metabolic profile was driven by negative contributions from body mass index, waist-to-hip ratio, glycated hemoglobin, C-reactive protein and leptin and a positive contribution from adiponectin. It positively covaried with gray matter volume in temporal, frontal and occipital lobe as well as subcortical regions and cerebellum. This result shows that a metabolic profile characterized by high body fat, visceral adiposity and systemic inflammation is associated with reduced gray matter volume and potentially reduced executive function in older adults. We observed the highest contributions for body weight and fat mass, which indicates that factors underlying sustained energy imbalance, like sedentary lifestyle or intake of energy-dense food, might be important determinants of gray matter structure in aging. |
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| 700 | 1 | _ | |a Kratzsch, Jürgen |0 P:(DE-HGF)0 |b 2 |
| 700 | 1 | _ | |a Schroeter, Matthias L. |0 P:(DE-HGF)0 |b 3 |
| 700 | 1 | _ | |a Röhr, Susanne |0 P:(DE-HGF)0 |b 4 |
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| 700 | 1 | _ | |a Villringer, Arno |0 P:(DE-HGF)0 |b 6 |
| 700 | 1 | _ | |a Witte, A. Veronica |0 P:(DE-HGF)0 |b 7 |e Corresponding author |
| 773 | _ | _ | |a 10.3389/fnagi.2019.00202 |g Vol. 11, p. 202 |0 PERI:(DE-600)2558898-9 |p 202 |t Frontiers in aging neuroscience |v 11 |y 2019 |x 1663-4365 |
| 856 | 4 | _ | |y OpenAccess |u https://juser.fz-juelich.de/record/866306/files/frontiers.pdf |
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