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Research progress on the effect of type 2 diabetes on the brain microstructure and structural network
YANG Liming  HUANG Mingming  YIN Yi  LIU Jing  YU Hui 

Cite this article as: Yang LM, Huang MM, Yin Y, et al. Research progress on the effect of type 2 diabetes on the brain microstructure and structural network. Chin J Magn Reson Imaging, 2020, 11(7): 589-592. DOI:10.12015/issn.1674-8034.2020.07.023.


[Abstract] Type 2 diabetes Mellitus (T2DM) is a chronic metabolic disease with multiple system complications. In addition to the well-known renal, eye, foot, and cardiovascular complications, T2DM can cause central nervous system dysfunction, characterized by a multidisciplinary decline in cognitive function. Due to its insidious onset, the key of treatment is to early diagnosis and timely intervention. Diffusion tensor imaging (DTI) can non-invasively detect the changes of the microstructure of living tissue. In recent years, the application of this technique in neuroimaging of T2MD has made a lot of achievements, finding out the changes of the microstructure of many brain regions in patients with T2DM, and the changes of the microstructure of local brain regions have significant correlation with cognitive ability and clinical parameters. In addition, DTI combined with graph theory can provide a quantitative characterization of the changes in white matter connectivity, which provides a new insight into the pathogenesis of cognitive decline in patients with T2DM. Therefore, this article will review the progress of neuroimaging in patients with type 2 diabetes from the above two aspects.
[Keywords] diabetes mellitus, type 2；nerve net；cognition disorders；magnetic resonance imaging

YANG Liming Department of Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China

HUANG Mingming Department of Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China

YIN Yi Department of Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China

LIU Jing Department of Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China

YU Hui* Department of Radiology, Affiliated Hospital of Guizhou Medical University, Guiyang 550004, China

*Corresponding to: Yu H, E-mail: 331693861@qq.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This article is supported by the National Natural Science Found No. 81560281 and the Guiyang Science and Technology Bureau Fund No. 2017-5-8
Received  2020-01-22
Accepted  2020-05-21
DOI: 10.12015/issn.1674-8034.2020.07.023
Cite this article as: Yang LM, Huang MM, Yin Y, et al. Research progress on the effect of type 2 diabetes on the brain microstructure and structural network. Chin J Magn Reson Imaging, 2020, 11(7): 589-592. DOI:10.12015/issn.1674-8034.2020.07.023.

[1]
Reske-Nielsen E, Lundbaek K, Gregersen G, et al. Pathological changes in the central and peripheral nervous system of young long-term diabetics. The terminal neuro-muscular apparatus. Diabetologia, 1970, 6(2): 98-103.
[2]
Palta P, Schneider ALC, Biessels GJ, et al. 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(3): 278-291.
[3]
Ciudin A, Espinosa A, Simó-Servat O, et al. Type 2 diabetes is an independent risk factor for dementia conversion in patients with mild cognitive impairment. J Diabetes Complications, 2017, 31(8): 1272-1274.
[4]
De La Monte SM, Tong M, Wands JR. The 20-year voyage aboard the journal of Alzheimer’s disease: docking at 'type 3 diabetes’, environmental/exposure factors, pathogenic mechanisms, and potential treatments. J Alzheimer’s Dis, 2018, 62(3): 1381-1390.
[5]
Baglietto-Vargas D, Shi J, Yaeger DM, et al. Diabetes and Alzheimer’s disease crosstalk. Neurosci Biobehav Rev, 2016, 64: 272-287.
[6]
De Felice FG, Ferreira ST. Inflammation, defective insulin signaling, and mitochondrial dysfunction as common molecular denominators connecting type 2 diabetes to Alzheimer disease. Diabetes, 2014, 63(7): 2262-2272.
[7]
Sheen YJ, Sheu WH. Association between hypoglycemia and dementia in patients with type 2 diabetes. Diabetes Res Clin Pract, 2016, 116: 279-287.
[8]
Mehta HB, Mehta V, Goodwin JS. Association Of Hypoglycemia With Subsequent Dementia In Older Patients With Type 2 Diabetes Mellitus. J Gerontol A Biol Sci Med Sci, 2019, 74(5): 750.
[9]
Tae WS, Ham BJ, Pyun SB, et al. Current clinical applications of diffusion-tensor imaging in neurological disorders. J Clin Neurol (Seoul, Korea), 2018, 14(2): 129-140.
[10]
Beaulieu C. The basis of anisotropic water diffusion in the nervous system: a technical review. NMR Biomed, 2002, 15(7-8): 435-455.
[11]
Zheng K, Wang H, Li J, et al. Structural networks analysis for depression combined with graph theory and the properties of fiber tracts via diffusion tensor imaging. Neurosci Lett, 2019, 694: 34-40.
[12]
Sanjari Moghaddam H, Ghazi Sherbaf F, Aarabi MH. Brain microstructural abnormalities in type 2 diabetes mellitus: a systematic review of diffusion tensor imaging studies. Front Neuroendocrinol, 2019, 55: 100782-100782.
[13]
Zhang J, Wang Y, Wang J, et al. White matter integrity disruptions associated with cognitive impairments in type 2 diabetic patients. Diabetes, 2014, 63(11): 3596-3605.
[14]
Sun Q, Chen GQ, Wang XB, et al. Alterations of white matter integrity and hippocampal functional connectivity in type 2 diabetes without mild cognitive impairment. Front Neuroanat, 2018, 12: 21.
[15]
Kim DJ, Yu JH, Shin MS, et al. Hyperglycemia reduces efficiency of brain networks in subjects with type 2 diabetes. PLoS One, 2016, 11(6): e0157268.
[16]
Yau PL, Javier D, Tsui W, et al. Emotional and neutral declarative memory impairments and associated white matter microstructural abnormalities in adults with type 2 diabetes. Psychiatry Res, 2009, 174(3): 223-230.
[17]
Yau PL, Kluger A, Borod JC, et al. Neural substrates of verbal memory impairments in adults with type 2 diabetes mellitus. J Clin Exp Neuropsychol, 2014, 36(1): 74-87.
[18]
Van Bussel FC, Backes WH, Hofman PA, et al. Altered hippocampal white matter connectivity in type 2 diabetes mellitus and memory decrements. J Neuroendocrinol, 2016, 28(3): 12366-12366.
[19]
Xie Y, Zhang Y, Qin W, et al. White matter microstructural abnormalities in type 2 diabetes mellitus: a diffusional kurtosis imaging analysis. AJNR Am J Neuroradiol, 2017, 38(3): 617-625.
[20]
Reijmer YD, Brundel M, De Bresser J, et al. Microstructural white matter abnormalities and cognitive functioning in type 2 diabetes: a diffusion tensor imaging study. Diabetes Care, 2013, 36(1): 137-144.
[21]
Hoogenboom WS, Marder TJ, Flores VL, et al. Cerebral white matter integrity and resting-state functional connectivity in middle-aged patients with type 2 diabetes. Diabetes, 2014, 63(2): 728-738.
[22]
Milne NT, Bucks RS, Davis WA, et al. Hippocampal atrophy, asymmetry, and cognition in type 2 diabetes mellitus. Brain Behav, 2017, 8(1): e00741.
[23]
Zhang YW, Zhang JQ, Liu C, et al. Memory dysfunction in type 2 diabetes mellitus correlates with reduced hippocampal CA1 and subiculum volumes. Chin Med J (Engl), 2015, 128(4): 465-471.
[24]
Bruehl H, Sweat V, Tirsi A, et al. Obese adolescents with type 2 diabetes mellitus have hippocampal and frontal lobe volume reductions. Neurosci Med, 2011, 2(1): 34-42.
[25]
Zhou H, Lu W, Shi Y, et al. Impairments in cognition and resting-state connectivity of the hippocampus in elderly subjects with type 2 diabetes. Neurosci Lett, 2010, 473(1): 5-10.
[26]
Wang CX, Fu KL, Liu HJ, et al. Spontaneous brain activity in type 2 diabetics revealed by amplitude of low-frequency fluctuations and its association with diabetic vascular disease: a resting-state FMRI study. PLoS one, 2014, 9(10): e108883.
[27]
Yavas E, Gonzalez S, Fanselow MS. Interactions between the hippocampus, prefrontal cortex, and amygdala support complex learning and memory. F1000Res, 2019, 8: F1000-1292.
[28]
Sigurdsson T, Duvarci S. Hippocampal-prefrontal interactions in cognition, behavior and psychiatric disease. Front Syst Neurosci, 2016, 9: 190-190.
[29]
Xiong Y, Sui Y, Xu Z, et al. A Diffusion tensor imaging study on white matter abnormalities in patients with type 2 diabetes using tract-based spatial statistics. AJNR Am J Neuroradiol, 2016, 37(8): 1462-1469.
[30]
Yoon S, Cho H, Kim J, et al. Brain changes in overweight/obese and normal-weight adults with type 2 diabetes mellitus. Diabetologia, 2017, 60(7): 1207-1217.
[31]
Nouwen A, Chambers A, Chechlacz M, et al. Microstructural abnormalities in white and gray matter in obese adolescents with and without type 2 diabetes. Neuroimage Clin, 2017, 16: 43-51.
[32]
Alfaro FJ, Gavrieli A, Saade-Lemus P, et al. White matter microstructure and cognitive decline in metabolic syndrome: a review of diffusion tensor imaging. Metabolism, 2018, 78: 52-68.
[33]
Wang M, Norman JE, Srinivasan VJ, et al. Metabolic, inflammatory, and microvascular determinants of white matter disease and cognitive decline. Am J Neurodegener Dis, 2016, 5(5): 171-177.
[34]
Rosenberg J, Lechea N, Pentang GN, et al. What magnetic resonance imaging reveals: a systematic review of the relationship between type II diabetes and associated brain distortions of structure and cognitive functioning. Front Neuroendocrinol, 2019, 52: 79-112.
[35]
Chen Z, Sun J, Yang Y, et al. Cortical thinning in type 2 diabetes mellitus and recovering effects of insulin therapy. J Clin Neurosci, 2015, 22(2): 275-279.
[36]
Reijmer YD, Leemans A, Brundel M, et al. Disruption of the cerebral white matter network is related to slowing of information processing speed in patients with type 2 diabetes. Diabetes, 2013, 62(6): 2112-2115.
[37]
Zhang J, Liu Z, Li Z, et al. Disrupted white matter network and cognitive decline in type 2 diabetes patients. J Alzheimer's Dis, 2016, 53(1): 185-195.
[38]
Zhang Y, Cao Y, Xie Y, et al. Altered brain structural topological properties in type 2 diabetes mellitus patients without complications. J Diabetes, 2019, 11(2): 129-138.
[39]
Chen GQ, Zhang X, Xing Y, et al. Resting-state functional magnetic resonance imaging shows altered brain network topology in Type 2 diabetic patients without cognitive impairment. Oncotarget, 2017, 8(61): 104560-104570.
[40]
Van Bussel FC, Backes WH, Van Veenendaal TM, et al. Functional brain networks are altered in type 2 diabetes and prediabetes: signs for compensation of cognitive decrements? The maastricht study. Diabetes, 2016, 65(8): 2404-2413.
[41]
Qin C, Liang Y, Tan X, et al. Altered whole-brain functional topological organization and cognitive function in type 2 diabetes mellitus patients. Front Neurol, 2019, 10: 599-599.
[42]
Buckner RL, Dinicola LM. The brain’s default network: updated anatomy, physiology and evolving insights. Nature Rev Neurosci, 2019, 20(10): 593-608.
[43]
Uddin LQ, Kelly AM, Biswal BB, et al. Functional connectivity of default mode network components: correlation, anticorrelation, and causality. Hum Brain Mapp, 2009, 30(2): 625-637.
[44]
Tan X, Liang Y, Zeng H, et al. Altered functional connectivity of the posterior cingulate cortex in type 2 diabetes with cognitive impairment. Brain Imaging Behav, 2019, 13(6): 1699-1707.
[45]
Liu H, Liu J, Peng L, et al. Changes in default mode network connectivity in different glucose metabolism status and diabetes duration. Neuroimage. Clin, 2019, 21: 101629.
[46]
Marrale M, Collura G, Brai M, et al. Physics, techniques and review of neuroradiological applications of diffusion kurtosis imaging (DKI). Clin Neuroradiol, 2016, 26(4): 391-403.
[47]
Arab A, Wojna-Pelczar A, Khairnar A, et al. Principles of diffusion kurtosis imaging and its role in early diagnosis of neurodegenerative disorders. Brain Res Bull, 2018, 139: 91-98.
[48]
Andica C, Kamagata K, Hatano T, et al. MR biomarkers of degenerative brain disorders derived from diffusion imaging. J Magn Reson Imaging, 2019, 10: 1002.
[49]
Xiong Y, Sui Y, Zhang S, et al. Brain microstructural alterations in type 2 diabetes: diffusion kurtosis imaging provides added value to diffusion tensor imaging. Eur Radiol, 2019, 29(4): 1997-2008.
[50]
Zhang H, Schneider T, Wheeler-Kingshott CA, et al. NODDI: practical in vivo neurite orientation dispersion and density imaging of the human brain. Neuroimage, 2012, 61(4): 1000-1016.
[51]
Xiong Y, Zhang S, Shi J, et al. Application of neurite orientation dispersion and density imaging to characterize brain microstructural abnormalities in type-2 diabetics with mild cognitive impairment. J Magn Reson Imaging, 2019, 50(3): 889-898.
[52]
Song YK, Li XB, Huang XL, et al. A study of neurite orientation dispersion and density imaging in wilson's disease. J Magn Reson Imaging, 2018, 48(2): 423-430.

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