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Sex differences in the relationship between abdominal fat distribution and structural brain networks

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Heinrich,  Matthias
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Beyer,  Frauke
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Kharabian,  Shahrzad
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Mueller,  Karsten
Department Cognitive Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Schroeter,  Matthias L.
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Villringer,  Arno
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Witte,  A. Veronica
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Sacher,  Julia
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Heinrich, M., Beyer, F., Loeffler, M., Stumvoll, M., Kharabian, S., Raschpichler, M., et al. (2017). Sex differences in the relationship between abdominal fat distribution and structural brain networks. Neuropsychopharmacology, 42(Suppl. 1): M53, S145-S146.


Cite as: https://hdl.handle.net/21.11116/0000-0004-F8AD-2
Abstract
Background: Accumulating evidence from neuroimaging studies in obesity suggests an inverse relationship between gray matter volume and abdominal fat accumulation. Abdominal visceral adiposity correlates negatively with verbal memory and attention, and represents a risk factor for dementia. Women seem to be more vulnerable to risk of developing cognitive impairment and dementia in association with abdominal visceral adiposity than with overall adiposity, as measured by BMI. Early patterns of grey matter loss can already be detected during mid-life, a time of substantial changes in body fat distribution, increased visceral fat accumulation, and ovarian-hormone fluctuations in women. So far, we do not know whether sex hormones affect the relationship between visceral abdominal fat accumulation and grey matter structure, in part because large cohort studies simultaneously including brain, abdominal and hormonal data are lacking. To address this issue, therefore, we examined whether sex hormones modulate the relationship between visceral adipose tissue volume (VAT) and structural grey matter (GM) networks.
Methods: All analyses were performed in the comprehensively phenotyped adult cohort of the population-based Leipzig Research Center for Civilization Diseases (LIFE) study (N= 975, 474 females, 19-79 years of age). Participants with previous stroke, cancer, major neuropsychiatric pathologies and any current medication affecting the central nervous system were excluded. High-resolution T1-weighted images were assessed at a Siemens Verio 3 Tesla Scanner with a 32-channel head coil with an MPRAGE (ADNI) sequence with 1 mm isotropic voxels, 176 slices, TR=2300 ms, TE=2.98 ms, and inversion time (TI)=900 ms. Gray matter (GM) was preprocessed using FreeSurfer (www.freesurfer.net) and FSL-VBM (fsl.fmrib.ox.ac.uk). For the neuroimaging data-analysis, we applied a linked independent component analysis (FLICA: FMRIB’s Linked Independent Component Analysis) of (a) grey matter volume, (b) cortical thickness and (3) pial surface to identify structural neural networks. For the abdominal MR imaging data analysis, we segmented visceral and subcutaneous adipose tissue using a semi automatic macro in ImageJ. Serum levels for estrogen, progesterone and testosterone were analyzed by liquid chromatography tandem-mass spectrometry (LC-MS/MS) techniques.
Results: Inter-rater variability for abdominal adipose tissue segmentation was excellent for both visceral (VAT, ICC= 0.98) and subcutaneous adipose tissue (SCAT, ICC=0.97). VAT was significantly higher in men than women (t(918.71)=12.22, p<0.001, alpha=0.05). The best model predicting VAT from age was a quadratic fit for men (adjusted R2=0.931, p<0.001) a polynomial fit of third degree (adjusted R2=0.851, p<0.001), with an inflection-point at 47 years of age, for women. VAT was significantly negatively associated with a large-scale, age-sensitive grey matter network, previously associated with heightened risk for dementia. Men showed a significantly steeper negative association between VAT and structural grey matter network than women (p<0.0024). Furthermore, estradiol (adjusted R2= 0.05, p<0.002) and progesterone (adjusted R2= 0.12, p<0.001) levels show a positive association with this structural network in women, even when correcting for age.

Conclusions: The present data indicate a sex-specific interaction between visceral adipose fat and a structural grey matter network previously linked to cognitive impairment and dementia: While in men this inverse relationship can be consistently displayed throughout all age groups, premenopausal women do not show a significant negative association between visceral abdominal fat and structural grey matter load. Furthermore, our findings provide first evidence for a protective role of ovarian hormones estrogen and progesterone in maintaining the structural grey matter network organization, that, when compromised, has been associated with increased dementia-risk. This evidence supports a perimenopausal vulnerability model for the female brain during midlife, when women, possibly due to the loss of ovarian hormone production, start to experience increased visceral fat accumulation, which represents a risk factor for structural grey matter loss.