2型糖尿病合并高血压对脑结构联合损伤效应的VBM研究

doi:10.12117/jccmi.2019.11.002

Abstract
Figure/Table
References (19)
Related Citation (15)

Download: PDF (0 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract Objective: To explore the combined damage of type 2 diabetes(T2DM) and hypertension(HTN) on the cerebral gray matter and cognitive function. Methods: Seventeen diabetic participants with hypertension(T2DM+HTN) and 17 demographic matched diabetic participants without hypertension(T2DM) were enrolled and accepted voxel-based morphometry analysis and neuropsychological assessment. Demographic parameters, gray matter volumes and neuropsychological scores were compared between the two groups. Then the regions which showed significantly difference were selected as regions of interests(ROI) for the correlation analysis between the volume of gray matter and neuropsychological scores. P<0.05 was considered as statistically significant. Result: There was no significant difference of demographic parameters between the two groups. Compared with T2DM, T2DM+HTN had decreased gray matter volumes in the temporopolar area(superior and middle temporal gyrus) and fusiform gyrus, which were both negatively correlated with TMT-A. Conclusion: T2DM and HTN have combined damage on the brain structure and cognitive function, which might mainly affected the temporopolar area(superior and middle temporal gyrus) and fusiform gyrus and have a higher probability of developing MCI.

Key words： Diabetes mellitus, type 2 Hypertension Brain injuries Magnetic resonance imaging

Received: 17 December 2018

PACS:	Ｒ587.1
	Ｒ743.2
	R445.2

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	ZHANG Dong-sheng
	YAN Xue-jiao
	ZHANG Xiao-ling
	ZHE Xia
	TANG Min
	GAO Jie

Cite this article:

ZHANG Dong-sheng,YAN Xue-jiao,ZHANG Xiao-ling, et al. Evaluating of voxel-based morphometry on combined damage of type 2 diabetes and hypertension[J]. JOURNAL OF CHINA MEDICAL IMAGING, 2019, 30(11): 765-768.

URL:

http://www.jccmi.com.cn/EN/10.12117/jccmi.2019.11.002 OR http://www.jccmi.com.cn/EN/Y2019/V30/I11/765

[1]彭娟，罗天友，陈莉，等. 2型糖尿病患者脑局部一致性的静息态功能MRI研究[J]. 中国医学影像技术，2017，33（1）：6-10. [2]vanden Berg E, Reijmer YD, de Bresser J, et al. A 4 year follow-up study of cognitive functioning in patients with type 2 diabetes mellitus[J]. Diabetologia, 2010, 53(1): 58-65. [3]刘带洪，段姗姗，张久权，等. 基于亚频段低频振幅分析2型糖尿病患者静息态脑功能的MRI研究[J]. 中华放射学杂志，2015，49（11）：801-806. [4]Colosia AD, Palencia R, Khan S. Prevalence of hypertension and obesity in patients with type 2 diabetes mellitus in observational studies: a systematic literature review[J]. Diabetes Metab Syndr Obes, 2013, 6: 327-338. [5]Nagai M, Hoshide S, Ishikawa J, et al. Ambulatory blood pressure as an independent determinant of brain atrophy and cognitive function in elderly hypertension[J]. J Hypertension, 2008, 26(8): 1636-1641. [6]Beason-Held LL, Moghekar A, Zonderman AB, et al. Longitudinal changes in cerebral blood flow in the older hypertensive brain[J]. Stroke, 2007, 38(6): 1766-1773. [7]Dahle CL, Jacobs BS, Raz N. Aging, vascular risk, and cognition: blood glucose, pulse pressure, and cognitive performance in healthy adults[J]. Psychol Aging, 2009, 24(1): 154-162. [8]Gifford KA, Badaracco M, Liu D, et al. Blood pressure and cognition among older adults: a meta-analysis[J]. Archives Clin Neuropsychol, 2013, 28(7): 649-664. [9]Ashburner J, Friston KJ. Voxel-based morphometry—the methods[J]. NeuroImage, 2000, 11(6 Pt 1): 805-821. [10]Wu G, Lin L, Zhang Q, et al. Brain gray matter changes in type 2 diabetes mellitus: A meta-analysis of whole-brain voxel-based morphometry study[J]. J Diabet Complication, 2017, 31(12): 1698-1703. [11]Kern KC, Wright CB, Bergfield KL, et al. Blood pressure control in aging predicts cerebral atrophy related to small-vessel white matter lesions[J]. Front Aging Neurosci, 2017, 9: 132. [12]Cholerton B, Baker LD, Craft S. Insulin, cognition, and dementia[J]. Eur J Pharmacol, 2013, 719(1-3): 170-179. [13]Bautista LE, Vera LM, Arenas IA, et al. Independent association between inflammatory markers(C-reactive protein, interleukin-6, and TNF-alpha) and essential hypertension[J]. J Human Hypertension, 2005, 19(2): 149-154. [14]Yu X, Yang Z, Yu M. Correlation of tumor necrosis factor alpha and interleukin 6 with hypertensive renal damage[J]. Ren Failure, 2010, 32(4): 475-479. [15]Lourenco MV, Clarke JR, Frozza RL, et al. TNF-alpha mediates PKR-dependent memory impairment and brain IRS-1 inhibition induced by Alzheimer’s beta-amyloid oligomers in mice and monkeys[J]. Cell Metabol, 2013, 18(6): 831-843. [16]Fox MD, Corbetta M, Snyder AZ, et al. Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems[J]. Proc Nation Academy Science USA, 2006, 103(26): 10046-10051. [17]Ray M, Zhang W. Analysis of Alzheimer’s disease severity across brain regions by topological analysis of gene co-expression networks[J]. BMC Syst Biol, 2010, 4: 136. [18]Langner R, Kellermann T, Boers F, et al. Modality-specific perceptual expectations selectively modulate baseline activity in auditory, somatosensory, and visual cortices[J]. Cereb Cortex, 2011, 21(12): 2850-2862. [19]McGuinness B, Todd S, Passmore P, et al. Blood pressure lowering in patients without prior cerebrovascular disease for prevention of cognitive impairment and dementia[J]. Cochrane Database Syst Rev, 2009, (4): CD004034.