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Hippocampal cerebrovascular reactivity is associated with obesity in women. An arterial spin labeling study.
Lidia Glodzik1,2, Henry Rusinek2, Wai Tsui1, Yi Li1, Pippa Storey2, Ricardo Osorio1, Tracy Butler1, and Mony de Leon1

1Psychiatry, NYU School of Medicine, New York, NY, United States, 2Radiology, NYU School of Medicine, New York, NY, United States

Synopsis

Cerebrovascular reactivity to carbon dioxide (CVR-CO2) is impaired in conditions affecting cerebral vasculature. Obesity increases the risk of Alzheimer’s disease (AD). The hippocampus plays a prominent role in cognition and it is one of the earliest brain structures affected during the progression of AD. It remains uncertain how obesity affects cerebral vasculature in AD vulnerable regions. We examined the relationship between body mass index and neocortical and hippocampal vasoreactivity. Our pulsed ASL sequence combined a flow-sensitive alternating inversion-recovery labeling scheme with balanced steady-state free precession to optimize spatial resolution and lower sensitivity to susceptibility artifacts. Cerebral blood flow (CBF) measurements were done during rest and rebreathing challenge designed to increased CO2 level. In obese women (BMI≥30, n=36) hippocampal vasoreactivity was 80% lower than in their non-obese peers. No relationship was observed in men or with respect to cortical vasoreactivity.

Introduction

Cerebrovascular reactivity to carbon dioxide (CVR-CO2) can be considered a measure of vascular health and it is impaired in conditions affecting cerebral vasculature 1,2. Vascular risk factors in general and obesity in particular increase the risk of neurodegenerative diseases like Alzheimer’s disease (AD) 3. The hippocampus plays a prominent role in cognition and it is one of the earliest brain structures affected during the progression of AD 4. However it remains uncertain how obesity affects cerebral vasculature in AD vulnerable regions. We investigated the effects of obesity on hippocampal and cortical vasoreactivity in a group of cognitively healthy adult and elderly.

Methods

Study subjects. Two hundred sixty two men (n=101) and woman (n=161). Mean age of the whole group was 69.3 ± 6.8 years, education 16.9 ± 2.3 years. All underwent medical (including body mass index (BMI)) and cognitive examination.

Arterial spin labeling. We used a pulsed ASL sequence combining a flow-sensitive alternating inversion-recovery labeling scheme with balanced steady-state free precession (bSSFP) readout 5,6. The bSSFP readout was chosen in preference to echo planar imaging because of its higher spatial resolution and lower sensitivity to susceptibility artifacts. To optimize hippocampal sampling, perfusion data were acquired using one oblique slice passing through the left and right hippocampus and middle temporal gyrus.

Cerebral blood flow (CBF) sampling. Hippocampal and cortical regions of interest (ROI) were defined directly on high-resolution ASL images (to minimize partial volume errors), using an in-house-developed software (https://wp.nyu.edu/firevoxel/). Cortical ROI was defined on the same slice as hippocampal ROIs and encompassed temporal, parietal and in some cases also occipital cortex.

Vasoreactivity. To estimate CVR-CO2 CO2 level was increased using a re-breathing protocol 7,8. Subjects were asked to breathe through a mouthpiece and a respiratory tube. The rebreathing apparatus included a HEPA bacterial/viral filter and a standard gas-anesthesia tube of 35 mm diameter and a custom-adjusted length. Nose was clamped to force inspiration of partially exhaled air. Oxygen saturation, heart rate and CO2 content in the expired air were monitored during image acquisition using Medrad Veris system. The CVR-CO2 response to an increase in blood CO2 was calculated as:

CVR-CO2= ((CBFCO2 -CBFrest) / CBFrest)*100) / ΔCO2.

where: CBFCO2 indicates CBF calculated during the session when subjects breathed through a respiratory tube, CBFrest indicates CBF calculated during the imaging session without the tube; ΔCO2 indicates the difference in end tidal CO2 between the two sessions.

Results

In the entire group BMI was related to hippocampal but not cortical reactivity (r= -.17, p=.006). Further analyses revealed a significant effect of sex (interaction term sex*BMI β = -1.003, p=.013). The relationship between BMI and hippocampal vasoreactivity was evident only in women (r= -.31, p<.001). In obese women (BMI≥30, n=36) hippocampal vasoreactivity was 80% lower than in their non-obese peers. No relationship was observed in men or with respect to cortical vasoreactivity.

Discussion

ASL imaging coupled with rebreathing protocol was sensitive enough to track functional changes related to a common vascular risk factor. Consistent with particular vulnerability of the hippocampus to both ischemia and neurodegeneration 9 we did not see relationship between BMI and vasoreactivity in the neocortex in our group of cognitively intact individuals. Moreover, our results are in agreement with earlier reports emphasizing sex differences in risk factors for conversion to AD 10 and showing sex-specific relationship between BMI and amyloid deposition 11.

Conclusions

Imaging vasoreactivity in disease-specific region may provide information about mechanism underlying link between vascular disease and neurodegeneration

Acknowledgements

Funding for this study comes from NIH grants HL111724, AG022374, AG12101, AG08051, HL118624, and Alzheimer’s Association NIRG-09-132490.

References

1 Last, D. et al. Global and Regional Effects of Type 2 Diabetes on Brain Tissue Volumes and Cerebral Vasoreactivity. Diabetes Care 30, 1193-1199 (2007).

2 Groschel, K., Terborg, C., Riecker, A., Witte, O. W. & Kastrup, A. Effects of physiological aging and cerebrovascular risk factors on the hemodynamic response to brain activation: A functional transcranial doppler study. Clinical Neurophysiology 118, e35-e36 (2007).

3 Kivipelto, M. et al. Obesity and vascular risk factors at midlife and the risk of dementia and Alzheimer disease. Arch. Neurol 62, 1556-1560 (2005).

4 Glodzik-Sobanska, L. et al. The role of quantitative structural imaging in the early diagnosis of Alzheimer's disease. Neuroimaging Clinics of North America 15, 803-826 (2005).

5 Boss, A. et al. FAIR-TrueFISP imaging of cerebral perfusion in areas of high magnetic susceptibility differences at 1.5 and 3 Tesla. J Magn Reson. Imaging 25, 924-931 (2007).

6 Rusinek, H. et al. Cerebral perfusion in insulin resistance and type two diabetes. Journal of Cerebral Blood Flow & Metabolism 35(1), 95-102 (2015).

7 Rusinek, H. et al. Hippocampal blood flow in normal aging measured with arterial spin labeling at 3T. Magnetic Resonance in Medicine 65, 128-137 (2011).

8 Glodzik, L., Randall, C., Rusinek, H. & de Leon, M. Cerebrovascular reactivity to carbon dioxide in Alzheimer's disease. Journal of Alzheimer's Disease 35, 427-440 (2013).

9 Zarow, C. et al. Correlates of Hippocampal Neuron Number in Alzheimer's Disease and Ischemic Vascular Dementia. Ann Neurol 57, 896-903 (2005).

10 Kim, S. et al. Gender differences in risk factors for transition from mild cognitive impairment to Alzheimers disease: A CREDOS study. Comprehensive Psychiatry 62, 114-122 (2015).

11 Glodzik, L. et al. Effects of vascular risk factors, statins, and antihypertensive drugs on PiB deposition in cognitively normal subjects. Alzheimers Dement (Amst) 2, 95-104 (2016).

Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)
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