Disturbed neurovascular coupling in type 2 diabetes mellitus patients: Evidence from a comprehensive fMRI analysis

Bo Hu, Lin-Feng Yan, Qian Sun, Ying Yu, Jin Zhang, Yu-Jie Dai, Yang Yang, Yu-Chuan Hu, Hai-Yan Nan, Xin Zhang, Chun-Ni Heng, Jun-Feng Hou, Qing-Quan Liu, Chang-Hua Shao, Fei Li, Kai-Xiang Zhou, Hang Guo, Guang-Bin Cui, Wen Wang, Bo Hu, Lin-Feng Yan, Qian Sun, Ying Yu, Jin Zhang, Yu-Jie Dai, Yang Yang, Yu-Chuan Hu, Hai-Yan Nan, Xin Zhang, Chun-Ni Heng, Jun-Feng Hou, Qing-Quan Liu, Chang-Hua Shao, Fei Li, Kai-Xiang Zhou, Hang Guo, Guang-Bin Cui, Wen Wang

Abstract

Background: Previous studies presumed that the disturbed neurovascular coupling to be a critical risk factor of cognitive impairments in type 2 diabetes mellitus (T2DM), but distinct clinical manifestations were lacked. Consequently, we decided to investigate the neurovascular coupling in T2DM patients by exploring the MRI relationship between neuronal activity and the corresponding cerebral blood perfusion.

Methods: Degree centrality (DC) map and amplitude of low-frequency fluctuation (ALFF) map were used to represent neuronal activity. Cerebral blood flow (CBF) map was used to represent cerebral blood perfusion. Correlation coefficients were calculated to reflect the relationship between neuronal activity and cerebral blood perfusion.

Results: At the whole gray matter level, the manifestation of neurovascular coupling was investigated by using 4 neurovascular biomarkers. We compared these biomarkers and found no significant changes. However, at the brain region level, neurovascular biomarkers in T2DM patients were significantly decreased in 10 brain regions. ALFF-CBF in left hippocampus and fractional ALFF-CBF in left amygdala were positively associated with the executive function, while ALFF-CBF in right fusiform gyrus was negatively related to the executive function. The disease severity was negatively related to the memory and executive function. The longer duration of T2DM was related to the milder depression, which suggests T2DM-related depression may not be a physiological condition but be a psychological condition.

Conclusion: Correlations between neuronal activity and cerebral perfusion maps may be a method for detecting neurovascular coupling abnormalities, which could be used for diagnosis in the future. Trial registry number: This study has been registered in ClinicalTrials.gov (NCT02420470) on April 2, 2015 and published on July 29, 2015.

Keywords: Arterial spin-labeling (ASL); Blood oxygenation level dependent (BOLD); Cognitive impairment; Functional magnetic resonance imaging (fMRI); Neurovascular coupling; Type 2 diabetes mellites (T2DM).

Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.

Figures

Fig. 1
Fig. 1
Spatial distribution of averaged CBF, ALFF, fALFF, DCP and DCN maps. These maps were averaged across subjects within each group. T2DM = diabetes mellitus; HC = healthy control.
Fig. 2
Fig. 2
Significant differences of 4 brain region-based neurovascular coupling biomarkers. (a) ALFF-CBF biomarker; (b) DCN-CBF biomarker; (c) fALFF-CBF biomarker; (d) DCP-CBF biomarker. l = left; r = right; MFGOP = middle frontal gyrus orbital part; LNP = lenticular nucleus pallidum; MFG = middle frontal gyrus; STG = superior temporal gyrus; MTG = middle temporal gyrus; MCPG = median cingulate and paracingulate gyri. Error bars represent the standard deviations and dots represent outliers.
Fig. 3
Fig. 3
Four kinds of brain region-based neurovascular coupling biomarkers. (a) ALFF-CBF biomarker; (b) fALFF-CBF biomarker; (c) DCP-CBF biomarker; (d) DCN-CBF biomarker. The numbers of brain regions were consistent with the numbers in Automated Anatomic labeling (AAL) atlas. Lines referred to the average correlation coefficients of brain regions within each group, and shadows of the corresponding color referred to the standard deviations. Brain regions with significant differences were labeled.
Fig. 4
Fig. 4
The consistency of brain region-based correlation coefficients of different types. (a) Four kinds of neurovascular coupling biomarkers were calculated by using only parametric maps of HC group. Even the calculating methods of ALFF map, fALFF map, DCP map, and DCN map were totally different, the distribution and fluctuation of their brain region-based correlation coefficients with CBF map were similar. (b) The reconstructed brain maps of these 4 types of brain region-based correlation coefficients.
Fig. 5
Fig. 5
Correlation analysis between brain function and disease severity. CVLT = California Verbal-Learning Test; Stroop = Stroop Color Word Test; SDS = Self-Rating Depression Scale; IC = Incongruent Correct; PBG = Postprandial Blood Glucose; HbA1c = hemoglobin A1c; Time = disease duration.
Fig. 6
Fig. 6
Correlation analysis between brain function and neurovascular biomarkers. Stroop = Stroop Color Word Test; SDS = Self-Rating Depression Scale; IC = Incongruent Correct; IRT = Incongruent Reaction Time; PRC = Pronunciation Relevant Correct; PRRT = Pronunciation Relevant Reaction Time.
Fig. 7
Fig. 7
Significant differences of 3 brain region-based neurovascular coupling biomarkers without GSR. (a) ALFF-CBF biomarker; (b) fALFF-CBF biomarker; (c) DCP-CBF biomarker. G = With GSR, NG = No GSR; l = left; r = right; MFGOP = middle frontal gyrus orbital part; MFG = middle frontal gyrus; STG = superior temporal gyrus; MTG = middle temporal gyrus; MCPG = median cingulate and paracingulate gyri; SFGOP = superior frontal gyrus orbital part; PhG = Para hippocampal gyrus. Error bars represent the standard deviations and dots represent outliers.

References

    1. Aggleton J.P., Pralus A., Nelson A.J., Hornberger M. Thalamic pathology and memory loss in early Alzheimer's disease: moving the focus from the medial temporal lobe to Papez circuit. Brain. 2016;139:1877–1890.
    1. Andres D.S., Darbin O. Complex dynamics in the basal ganglia: health and disease beyond the motor system. J. Neuropsychiatr. Clin. Neurosci. 2018;30:101–114.
    1. Attwell D., Buchan A.M., Charpak S., Lauritzen M., Macvicar B.A., Newman E.A. Glial and neuronal control of brain blood flow. Nature. 2010;468:232–243.
    1. Balduzzi D., Riedner B.A., Tononi G. A BOLD window into brain waves. Proc. Natl. Acad. Sci. U. S. A. 2008;105:15641–15642.
    1. Ben-David B.M., Nguyen L.L., van Lieshout P.H. Stroop effects in persons with traumatic brain injury: selective attention, speed of processing, or color-naming? A meta-analysis. J. Int. Neuropsychol. Soc. 2011;17:354–363.
    1. Biessels G.J., Deary I.J., Ryan C.M. Cognition and diabetes: a lifespan perspective. Lancet Neurol. 2008;7:184–190.
    1. Biswal B., Yetkin F.Z., Haughton V.M., Hyde J.S. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn. Reson. Med. 1995;34:537–541.
    1. Brownlee M. Biochemistry and molecular cell biology of diabetic complications. Nature. 2001;414:813–820.
    1. Buzsaki G., Draguhn A. Neuronal oscillations in cortical networks. Science. 2004;304:1926–1929.
    1. Catani M., Dell'acqua F., Thiebaut de Schotten M. A revised limbic system model for memory, emotion and behaviour. Neurosci. Biobehav. Rev. 2013;37:1724–1737.
    1. Chen X., Lu B., Yan C.G. vol. 39. 2018. Reproducibility of R-fMRI Metrics on the Impact of Different Strategies for Multiple Comparison Correction and Sample Sizes; pp. 300–318.
    1. Cohen J.D., Dunbar K., McClelland J.L. On the control of automatic processes: a parallel distributed processing account of the Stroop effect. Psychol. Rev. 1990;97:332–361.
    1. Cooper C., Sommerlad A., Lyketsos C.G., Livingston G. Modifiable predictors of dementia in mild cognitive impairment: a systematic review and meta-analysis. Am. J. Psychiatry. 2015;172:323–334.
    1. De Silva T.M., Faraci F.M. Microvascular dysfunction and cognitive impairment. Cell. Mol. Neurobiol. 2016;36:241–258.
    1. Duarte J.V., Pereira J.M., Quendera B., Raimundo M., Moreno C., Gomes L., Carrilho F., Castelo-Branco M. Early disrupted neurovascular coupling and changed event level hemodynamic response function in type 2 diabetes: an fMRI study. J. Cereb. Blood Flow Metab. 2015;35:1671–1680.
    1. Eklund A., Nichols T.E., Knutsson H. Cluster failure: why fMRI inferences for spatial extent have inflated false-positive rates. Proc. Natl. Acad. Sci. U. S. A. 2016;113:7900–7905.
    1. Fox M.D., Snyder A.Z., Vincent J.L., Corbetta M., Van Essen D.C., Raichle M.E. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl. Acad. Sci. U. S. A. 2005;102:9673–9678.
    1. Fox M.D., Zhang D., Snyder A.Z., Raichle M.E. The global signal and observed anticorrelated resting state brain networks. J. Neurophysiol. 2009;101:3270–3283.
    1. Goldin A., Beckman J.A., Schmidt A.M., Creager M.A. Advanced glycation end products: sparking the development of diabetic vascular injury. Circulation. 2006;114:597–605.
    1. Hardigan T., Ward R., Ergul A. Cerebrovascular complications of diabetes: focus on cognitive dysfunction. Clin. Sci. (Lond.) 2016;130:1807–1822.
    1. Hempel R., Onopa R., Convit A. Type 2 diabetes affects hippocampus volume differentially in men and women. Diabetes Metab. Res. Rev. 2012;28:76–83.
    1. Hendrikse J., Petersen E.T., Golay X. Vascular disorders: insights from arterial spin labeling. Neuroimaging Clin. N. Am. 2012;22 (259-269, x-xi)
    1. Hubbard E.M., Ramachandran V.S. Neurocognitive mechanisms of synesthesia. Neuron. 2005;48:509–520.
    1. Kisler K., Nelson A.R., Rege S.V., Ramanathan A., Wang Y., Ahuja A., Lazic D., Tsai P.S., Zhao Z., Zhou Y. vol. 20. 2017. Pericyte degeneration leads to neurovascular uncoupling and limits oxygen supply to brain; pp. 406–416.
    1. Liang X., Zou Q., He Y., Yang Y. Coupling of functional connectivity and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain. Proc. Natl. Acad. Sci. U. S. A. 2013;110:1929–1934.
    1. Liu D., Duan S., Zhang J., Zhou C., Liang M., Yin X., Wei P., Wang J. Aberrant brain regional homogeneity and functional connectivity in middle-aged T2DM patients: a resting-state functional MRI study. Front. Hum. Neurosci. 2016;10:490.
    1. Macpherson H., Formica M., Harris E., Daly R.M. Brain functional alterations in type 2 diabetes - a systematic review of fMRI studies. Front. Neuroendocrinol. 2017;47:34–46.
    1. Mogi M., Horiuchi M. Neurovascular coupling in cognitive impairment associated with diabetes mellitus. Circ. J. 2011;75:1042–1048.
    1. Munoz M.F., Puebla M., Figueroa X.F. Control of the neurovascular coupling by nitric oxide-dependent regulation of astrocytic Ca(2+) signaling. Front. Cell. Neurosci. 2015;9:59.
    1. Musen G., Jacobson A.M., Bolo N.R., Simonson D.C., Shenton M.E., McCartney R.L., Flores V.L., Hoogenboom W.S. Resting-state brain functional connectivity is altered in type 2 diabetes. Diabetes. 2012;61:2375–2379.
    1. Nicolakakis N., Hamel E. Neurovascular function in Alzheimer's disease patients and experimental models. J. Cereb. Blood Flow Metab. 2011;31:1354–1370.
    1. Okereke O.I., Kang J.H., Cook N.R., Gaziano J.M., Manson J.E., Buring J.E., Grodstein F. Type 2 diabetes mellitus and cognitive decline in two large cohorts of community-dwelling older adults. J. Am. Geriatr. Soc. 2008;56:1028–1036.
    1. Palta P., Schneider A.L., Biessels G.J., Touradji P., Hill-Briggs F. Magnitude of cognitive dysfunction in adults with type 2 diabetes: a meta-analysis of six cognitive domains and the most frequently reported neuropsychological tests within domains. J. Int. Neuropsychol. Soc. 2014;20:278–291.
    1. Pollock J.M., Tan H., Kraft R.A., Whitlow C.T., Burdette J.H., Maldjian J.A. Arterial spin-labeled MR perfusion imaging: clinical applications. Magn. Reson. Imaging Clin. N. Am. 2009;17:315–338.
    1. Rancillac A., Geoffroy H., Rossier J. Impaired neurovascular coupling in the APPxPS1 mouse model of Alzheimer's disease. Curr. Alzheimer Res. 2012;9:1221–1230.
    1. Roberts R.O., Knopman D.S., Geda Y.E., Cha R.H., Pankratz V.S., Baertlein L., Boeve B.F., Tangalos E.G., Ivnik R.J., Mielke M.M., Petersen R.C. Association of diabetes with amnestic and nonamnestic mild cognitive impairment. Alzheimers Dement. 2014;10:18–26.
    1. Rosengarten B., Paulsen S., Burr O., Kaps M. Neurovascular coupling in Alzheimer patients: effect of acetylcholine-esterase inhibitors. Neurobiol. Aging. 2009;30:1918–1923.
    1. Saad Z.S., Gotts S.J., Murphy K., Chen G., Jo H.J., Martin A., Cox R.W. Trouble at rest: how correlation patterns and group differences become distorted after global signal regression. Brain Connect. 2012;2:25–32.
    1. Serlin Y., Levy J., Shalev H. Vascular pathology and blood-brain barrier disruption in cognitive and psychiatric complications of type 2 diabetes mellitus. Cardiovasc. Psychiatry Neurol. 2011;2011
    1. Sheng J., Shen Y., Qin Y., Zhang L., Jiang B., Li Y., Xu L., Chen W., Wang J. vol. 39. 2018. Spatiotemporal, metabolic, and therapeutic characterization of altered functional connectivity in major depressive disorder; pp. 1957–1971.
    1. Shibasaki H. Cortical activities associated with voluntary movements and involuntary movements. Clin. Neurophysiol. 2012;123:229–243.
    1. Tarantini S., Hertelendy P., Tucsek Z., Valcarcel-Ares M.N., Smith N., Menyhart A., Farkas E., Hodges E.L., Towner R., Deak F., Sonntag W.E., Csiszar A., Ungvari Z., Toth P. Pharmacologically-induced neurovascular uncoupling is associated with cognitive impairment in mice. J. Cereb. Blood Flow Metab. 2015;35:1871–1881.
    1. Tomasi D., Volkow N.D. Functional connectivity density mapping. Proc. Natl. Acad. Sci. U. S. A. 2010;107:9885–9890.
    1. Toth P., Tarantini S., Tucsek Z., Ashpole N.M., Sosnowska D., Gautam T., Ballabh P., Koller A., Sonntag W.E., Csiszar A., Ungvari Z. Resveratrol treatment rescues neurovascular coupling in aged mice: role of improved cerebromicrovascular endothelial function and downregulation of NADPH oxidase. Am. J. Physiol. Heart Circ. Physiol. 2014;306:H299–H308.
    1. Tzourio-Mazoyer N., Landeau B., Papathanassiou D., Crivello F., Etard O., Delcroix N., Mazoyer B., Joliot M. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage. 2002;15:273–289.
    1. Vetri F., Xu H., Paisansathan C., Pelligrino D.A. Impairment of neurovascular coupling in type 1 diabetes mellitus in rats is linked to PKC modulation of BK(Ca) and Kir channels. Am. J. Physiol. Heart Circ. Physiol. 2012;302:H1274–H1284.
    1. Vetri F., Qi M., Xu H., Oberholzer J., Paisansathan C. Impairment of neurovascular coupling in Type 1 Diabetes Mellitus in rats is prevented by pancreatic islet transplantation and reversed by a semi-selective PKC inhibitor. Brain Res. 2017;1655:48–54.
    1. Wang Y.F., Ji X.M., Lu G.M., Zhang L.J. Resting-state functional MR imaging shed insights into the brain of diabetes. Metab. Brain Dis. 2016;31:993–1002.
    1. Weissenbacher A., Kasess C., Gerstl F., Lanzenberger R., Moser E., Windischberger C. Correlations and anticorrelations in resting-state functional connectivity MRI: a quantitative comparison of preprocessing strategies. Neuroimage. 2009;47:1408–1416.
    1. Wong R.H., Raederstorff D., Howe P.R. Acute resveratrol consumption improves neurovascular coupling capacity in adults with type 2 diabetes mellitus. Nutrients. 2016;8
    1. Xia W., Wang S., Sun Z., Bai F., Zhou Y., Yang Y., Wang P., Huang Y., Yuan Y. Altered baseline brain activity in type 2 diabetes: a resting-state fMRI study. Psychoneuroendocrinology. 2013;38:2493–2501.
    1. Yang L., Yan Y., Wang Y., Hu X., Lu J., Chan P., Yan T., Han Y. Gradual disturbances of the amplitude of low-frequency fluctuations (ALFF) and fractional ALFF in Alzheimer spectrum. Front. Neurosci. 2018;12:975.
    1. Zang Y.F., He Y., Zhu C.Z., Cao Q.J., Sui M.Q., Liang M., Tian L.X., Jiang T.Z., Wang Y.F. Altered baseline brain activity in children with ADHD revealed by resting-state functional MRI. Brain Dev. 2007;29:83–91.
    1. Zhou H., Lu W., Shi Y., Bai F., Chang J., Yuan Y., Teng G., Zhang Z. Impairments in cognition and resting-state connectivity of the hippocampus in elderly subjects with type 2 diabetes. Neurosci. Lett. 2010;473:5–10.
    1. Zhou H., Zhang X., Lu J. Progress on diabetic cerebrovascular diseases. Bosn. J. Basic Med. Sci. 2014;14:185–190.
    1. Zhou X., Zhang J., Chen Y., Ma T., Wang Y., Wang J., Zhang Z. Aggravated cognitive and brain functional impairment in mild cognitive impairment patients with type 2 diabetes: a resting-state functional MRI study. J. Alzheimers Dis. 2014;41:925–935.
    1. Zhu J., Zhuo C., Xu L., Liu F., Qin W., Yu C. Altered coupling between resting-state cerebral blood flow and functional connectivity in schizophrenia. Schizophr. Bull. 2017;43:1363–1374.
    1. Zuo X.N., Di Martino A., Kelly C., Shehzad Z.E., Gee D.G., Klein D.F., Castellanos F.X., Biswal B.B., Milham M.P. The oscillating brain: complex and reliable. Neuroimage. 2010;49:1432–1445.

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