Research progress of magnetic resonance imaging in type 2 diabetes mellitus related cognitive dysfunction

doi:10.11817/j.issn.1673-9248.2020.05.008

Abstract

Abstract:

Hyperglycemia is an independent risk factor for cognitive dysfunction and may accelerate the progression of mild cognitive impairment to dementia. Diabetes mellitus is one of the most serious public health problems in the 21st century around the world. With the number of diabetic patients increased, more attention has been paid to type 2 diabetes mellitus related cognitive dysfunction. The type 2 diabetes mellitus related cognitive dysfunction mainly displays in the memory, attention, information processing speed and executive functions, etc.. Magnetic resonance imaging (MRI) studies have shown that, compared with patients without diabetes, type 2 diabetes mellitus patients can be present more often with the reduction of the brain volume, the incidence of lacunar cerebral infarction, the loss of cerebral white matter fiber tracts integrity, and the diminishment of brain activation function, the decline of brain function of interval nuclear structure connection, and the change of the cerebral metabolic material level.

Key words: Type 2 diabetes mellitus, Cognitive impairment, Magnetic resonance imaging

Mengchun Li, Hui Zhao, Yun Xu. Research progress of magnetic resonance imaging in type 2 diabetes mellitus related cognitive dysfunction[J]. Chinese Journal of Cerebrovascular Diseases(Electronic Edition), 2020, 14(05): 292-296.

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References 60

1	Ogurtsova K, Da Rocha Fernandes JD, Huang Y, et al. IDF Diabetes Atlas: Global estimates for the prevalence of diabetes for 2015 and 2040 [J]. Diabetes Res Clin Pract, 2017, 128: 40-50.
2	Wang L, Gao P, Zhang M, et al. Prevalence and ethnic pattern of diabetes and prediabetes in China in 2013 [J]. JAMA, 2017, 317(24): 2515-2523.
3	Dik MG, Jonker C, Comijs HC, et al. Contribution of metabolic syndrome components to cognition in older individuals [J]. Diabetes Care, 2007, 30(10): 2655-2660.
4	Biessels GJ, Deary IJ, Ryan CM. Cognition and diabetes: a lifespan perspective [J]. Lancet Neurol, 2008, 7(2): 184-190.
5	Umegaki H. Type 2 diabetes as a risk factor for cognitive impairment: current insights [J]. Clin Interv Aging, 2014, 9: 1011-1019.
6	Folstein MF, Folstein SE, Mchugh PR.“Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician [J]. J Psychiatr Res, 1975, 12(3): 189-198.
7	Nasreddine ZS, Phillips NA, Bedirian V, et al. The Montreal Cognitive Assessment, MoCA: a brief screening tool for mild cognitive impairment [J]. J Am Geriatr Soc, 2005, 53(4): 695-699.
8	Leite KS, Miotto EC, Nitrini R, et al. Boston Naming Test (BNT) original, Brazilian adapted version and short forms: normative data for illiterate and low-educated older adults [J]. Int Psychogeriatr, 2017, 29(5): 825-833.
9	邹君惠, 陈歆, 顾雨铖, 等. 脑白质微结构完整性与高血压患者认知功能的相关性 [J]. 国际脑血管病杂志, 2019, 27(1): 21-30.
10	顾雨铖, 刘任远, 秦若梦, 等. 总MRI脑小血管病评分与认知功能的相关性 [J]. 国际脑血管病杂志, 2018, 26(7): 521-527.
11	Uiterwijk R, Van Oostenbrugge RJ, Huijts M, et al. Total cerebral small vessel disease MRI score is associated with cognitive decline in executive function in patients with hypertension [J]. Front Aging Neurosci, 2016, 8: 301.
12	郭起浩. Stroop色词测验在早期识别阿尔茨海默病中的作用 [J]. 中华神经医学杂志, 2005, 4(7): 701-704.
13	Mccrimmon RJ, Ryan CM, Frier BM. Diabetes and cognitive dysfunction [J]. Lancet, 2012, 379(9833): 2291-2299.
14	Logothetis NK. What we can do and what we cannot do with fMRI [J]. Nature, 2008, 453(7197): 869-878.
15	Zilliox LA, Chadrasekaran K, Kwan JY, et al. Diabetes and cognitive impairment [J]. Curr Diab Rep, 2016, 16(9): 87.
16	Biessels GJ, Reijmer YD. Brain changes underlying cognitive dysfunction in diabetes: what can we learn from MRI? [J]. Diabetes, 2014, 63(7): 2244-2252.
17	Kumar R, Anstey KJ, Cherbuin N, et al. Association of type 2 diabetes with depression, brain atrophy, and reduced fine motor speed in a 60- to 64-year-old community sample [J]. Am J Geriatr Psychiatry, 2008, 16(12): 989-998.
18	Roberts RO, Knopman DS, Przybelski SA, et al. Association of type 2 diabetes with brain atrophy and cognitive impairment [J]. Neurology, 2014, 82(13): 1132-1141.
19	Jongen C, Van Der Grond J, Kappelle LJ, et al. Automated measurement of brain and white matter lesion volume in type 2 diabetes mellitus [J]. Diabetologia, 2007, 50(7): 1509-1516.
20	Gold SM, Dziobek I, Sweat V, et al. Hippocampal damage and memory impairments as possible early brain complications of type 2 diabetes [J]. Diabetologia, 2007, 50(4): 711-719.
21	De Felice FG, Ferreira ST. Inflammation, defective insulin signaling, and mitochondrial dysfunction as common molecular denominators connecting type 2 diabetes to Alzheimer disease [J]. Diabetes, 2014, 63(7): 2262-2272.
22	Kimura N. Diabetes mellitus induces alzheimer's disease pathology: histopathological evidence from animal models [J]. Int J Mol Sci, 2016, 17(4): 503.
23	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]. J Alzheimers Dis, 2018, 62(3): 1381-1390.
24	Moulton CD, Costafreda SG, Horton P, et al. Meta-analyses of structural regional cerebral effects in type 1 and type 2 diabetes [J]. Brain Imaging Behav, 2015, 9(4): 651-662.
25	Li M, Huang L, Yang D, et al. Atrophy patterns of hippocampal subfields in T2DM patients with cognitive impairment [J]. Endocrine, 2020, 68(3): 536-548.
26	Zhang YW, Zhang JQ, Liu C, et al. Memory dysfunction in type 2 diabetes mellitus correlates with reduced hippocampal CA1 and subiculum volumes [J]. Chin Med J (Engl), 2015, 128(4): 465-471.
27	Groeneveld O, Reijmer Y, Heinen R, et al. Brain imaging correlates of mild cognitive impairment and early dementia in patients with type 2 diabetes mellitus [J]. Nutr Metab Cardiovasc Dis, 2018, 28(12): 1253-1260.
28	Zhang Y, Zhang X, Zhang J, et al. Gray matter volume abnormalities in type 2 diabetes mellitus with and without mild cognitive impairment [J]. Neurosci Lett, 2014, 562: 1-6.
29	Van Elderen SG, De Roos A, De Craen AJ, et al. Progression of brain atrophy and cognitive decline in diabetes mellitus: a 3-year follow-up [J]. Neurology, 2010, 75(11): 997-1002.
30	Pantoni L. Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges [J]. Lancet Neurol, 2010, 9(7): 689-701.
31	盛励, 曹文杰, 黄新梅, 等. 2型糖尿病患者脑白质病变相关危险因素分析 [J]. 中国临床医学, 2017, 24(1): 103-107.
32	Falvey CM, Rosano C, Simonsick EM, et al. Macro- and microstructural magnetic resonance imaging indices associated with diabetes among community-dwelling older adults [J]. Diabetes Care, 2013, 36(3): 677-682.
33	李梦春, 罗财妹, 秦若梦, 等. 2型糖尿病合并认知功能障碍患者的脑白质结构变化的影像学特征分析 [J]. 中国临床神经科学, 2019, 27(6): 624-632, 657.
34	Kloppenborg RP, Nederkoorn PJ, Grool AM, et al. Cerebral small-vessel disease and progression of brain atrophy: the SMART-MR study [J]. Neurology, 2012, 79(20): 2029-2036.
35	Marchant NL, Reed BR, Sanossian N, et al. The aging brain and cognition: contribution of vascular injury and abeta to mild cognitive dysfunction [J]. JAMA Neurol, 2013, 70(4): 488-95.
36	王志鹏, 高仲磊, 卫孟佳. 血管周围间隙扩大在2型糖尿病患者脑小血管性病变中的预测价值 [J]. 中国临床医生杂志, 2019, 47(8): 941-944.
37	吴光任, 卢斐翠, 沈礼利, 等. 血管周围间隙在评估2型糖尿病患者脑小血管性病变的临床应用 [J]. 医学影像学杂志, 2017, 27(12): 2410-2412.
38	Shaikh S, Kumar A, Bansal A. Diffusion tensor imaging: An overview [J]. Neurol India, 2018, 66(6): 1603-1611.
39	Van Bussel FC, Backes WH, Hofman PA, et al. Altered hippocampal white matter connectivity in type 2 diabetes mellitus and memory decrements [J]. J Neuroendocrinol, 2016, 28(3): 12366.
40	Yau PL, Kluger A, Borod JC, et al. Neural substrates of verbal memory impairments in adults with type 2 diabetes mellitus [J]. J Clin Exp Neuropsychol, 2014, 36(1): 74-87.
41	王飞, 罗剑锋, 丁玎, 等. 糖尿病对老年人总体认知功能水平及各认知领域的影响 [J]. 中国临床神经科学, 2019, 27(1): 29-38.
42	Ryan JP, Fine DF, Rosano C. Type 2 diabetes and cognitive impairment: contributions from neuroimaging [J]. J Geriatr Psychiatry Neurol, 2014, 27(1): 47-55.
43	Moheet A, Mangia S, Seaquist ER. Impact of diabetes on cognitive function and brain structure [J]. Ann N Y Acad Sci, 2015, 1353: 60-71.
44	Zhang Y, Cao Y, Xie Y, et al. Altered brain structural topological properties in type 2 diabetes mellitus patients without complications [J]. J Diabetes, 2019, 11(2): 129-138.
45	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 [J]. Diabetes, 2014, 63(2): 728-738.
46	Xie Y, Zhang Y, Qin W, et al. White matter microstructural abnormalities in type 2 diabetes mellitus: a diffusional kurtosis imaging analysis [J]. AJNR Am J Neuroradiol, 2017, 38(3): 617-625.
47	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]. J Magn Reson Imaging, 2019, 50(3): 889-898.
48	Chen YC, Jiao Y, Cui Y, et al. Aberrant brain functional connectivity related to insulin resistance in type 2 diabetes: a resting-state fMRI study [J]. Diabetes Care, 2014, 37(6): 1689-1696.
49	陈志晔, 刘梦琦, 刘梦雨, 等. 2型糖尿病患者脑部静息态的功能磁共振成像 [J]. 南方医科大学学报, 2014, 34(8): 1083-1091.
50	刘代洪. 2型糖尿病伴轻度认知功能障碍患者脑静息态功能MRI研究 [J]. 磁共振成像, 2015, 16(3): 161-167.
51	Cui Y, Jiao Y, Chen HJ, et al. Aberrant functional connectivity of default-mode network in type 2 diabetes patients [J]. Eur Radiol, 2015, 25(11): 3238-3246.
52	Musen G, Jacobson AM, Bolo NR, et al. Resting-state brain functional connectivity is altered in type 2 diabetes [J]. Diabetes, 2012, 61(9): 2375-2379.
53	Kim DJ, Yu JH, Shin MS, et al. Hyperglycemia reduces efficiency of brain networks in subjects with type 2 diabetes [J]. PLoS One, 2016, 11(6): e0157268.
54	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 [J]. Diabetes, 2013, 62(6): 2112-2115.
55	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 [J]. Diabetes Care, 2013, 36(1): 137-144.
56	Zhang J, Liu Z, Li Z, et al. Disrupted white matter network and cognitive decline in type 2 diabetes patients [J]. J Alzheimers Dis, 2016, 53(1): 185-195.
57	Miller BL. A review of chemical issues in 1H NMR spectroscopy: N-acetyl-L-aspartate, creatine and choline [J]. NMR Biomed, 1991, 4(2): 47-52.
58	Lin Y, Zhou J, Sha L, et al. Metabolite differences in the lenticular nucleus in type 2 diabetes mellitus shown by proton MR spectroscopy [J]. AJNR Am J Neuroradiol, 2013, 34(9): 1692-1696.
59	Tong J, Geng H, Zhang Z, et al. Brain metabolite alterations demonstrated by proton magnetic resonance spectroscopy in diabetic patients with retinopathy [J]. Magn Reson Imaging, 2014, 32(8): 1037-1042.
60	Geissler A, Frund R, Scholmerich J, et al. Alterations of cerebral metabolism in patients with diabetes mellitus studied by proton magnetic resonance spectroscopy [J]. Exp Clin Endocrinol Diabetes, 2003, 111(7): 421-427.

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