糖尿病患者海马体积、神经代谢物与认知功能的相关性研究
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摘要
本文综述部分主要阐述了2型糖尿病患者海马与认知功能障碍的影像学研究进展。介绍了2型糖尿病患者认知功能和海马损害的特点。并分别介绍了MRI不同序列在2型糖尿病患者海马损伤诊断和评估方面的优势、进展和不足,展望了MRI在研究糖尿病患者海马损害和认知变化方面的发展和研究方向。
本文研究部分立足于糖尿病患者海马体积、神经代谢物与认知功能的相关性研究,通过2型糖尿病患者海马神经代谢物和海马体积的测量分析海马神经代谢物及体积的变化,同时检测每名患者认知评分观察认知的改变,最终通过统计学分析建立2型糖尿病患者海马神经代谢物和体积与认知评分之间变化的线性关系。最后得出结论MRI是一种活体无创性的识别及评估糖尿病认知功能损害的可视化、定量方法,对其认知功能的损害可做出早期的预警和治疗评估有所帮助。
Nowadays, ,diabetes and its complication are one of the main reasons leading to paralysis and death with the development of living. Central nervous system damage and complications of diabetes have become the focus of clinical practice. Central nervous system impairment, especially cognitive impairment, is the most serious and ultimate consequences of central nervous system damage of diabetes. With the development of MRI and the imaging of central nervous system , MRI has developed to Clinical diagnostic methods from morphology studying to Morphology, physiology and function combined. So it is possible to establish a method of non-invasive in vivo to diagnosis cognitive impairment in patients with diabetes.
Objective::
Hippocampal volume in patients with diabetes and to explore neural metabolite changes associated with cognitive function, to find a response to the pathological basis of cognitive impairment and early diagnosis of diabetes and evaluation of cognitive impairment in patients with the disease, an important auxiliary tool to monitor efficacy.
Method:
According to selection criteria, select diabetic and normal control group 63 samples who comes to China-Japan union hospital for treatment, they were detected by proton magnetic resonance spectroscopy(1H-MRS) .All samples are measured three Metabolites of hippocampal neurons including Choline, N-acetyl aspartic, inositol and creatine ratio, Hippocampal volume and Montreal cognitive and mini-mental scale score .
Inputs data in Excel, and analysis statistic by software SPSS 17.0. the measured data which meets normally distributed expressed with x±s, and the measured data which meets non- normally distributed expressed with median(M(QL,QU )).The balancing test of two groups of age, years of education using t-test, data were compared between the two groups meet t normally distributed , homogeneity of variance using independent samples t-test , data of two groups meet normally distributed, Variance arrhythmia using t '-test; Two groups of data do not meet the normal distribution using rank sum test; linear correlation analysis between the data uses dual variable correlation analysis (Bivariate), Calculate the Spearman Correlation coefficient.
Result:
1. The 32 samples of diabetes patient and 31 of healthy, the average age of the control group is 58.54±7.03, the average age of the diabetes is 60.01+6.99. There is no significant difference between the two groups.The time of educational control group is 11.30+2.54 and diabetes group is 11.75+2.44. There is also no significant difference between the two groups. Systolic and diastolic blood pressure showed no significant difference between the two groups.
2. The three metabolites ratio of diabetic group is Cho/Cr=1.41(1.22,1.56,),NAA/Cr=0.86(0.59,1.32,),MI/Cr =0.31 (0.17,0.43,),control group is Cho/Cr=1.20(1.06,1.48),NAA/Cr=1.24(1.06,1.48), MI/Cr=0.24(0.17,0.41).Non-normal data using rank sum test to compare differences between groups, PCho/Cr=0.0284, P NAA/Cr= 0.0011,P<0.05, with a statistically significant difference. P MI/Cr=0.5587,P>0.05, has not a statistically significant difference.
3. Hippocampal volume of diabetic group is 3.27 (3,4), normal control group 3.48(3.01,3.91).There is a significant difference between the two groups by Rank sum test (P =0.023, P<0.05).
4. Montreal Cognitive of diabetic groups is 22.52+3.97, normal control is 25.15+2.84.The two groups data is analysed by t-test,and P = 0.0347,p<0.05.There is a statistically difference. Mini-mental scale score of diabetic group is 24(23,25) and normal control group is 27(28,29), Rank sum test to compare results : P=0.0021, p<0.05, with a statistically significant difference.
5. Linear correlation analysis between the data of diabetic group uses dual variable correlation analysis (Bivariate), and Calculate the Spearman Correlation coefficient.The Results is Cho / Cr with the MMSE( r= -0.46,p=0.013), MoCA(r= -0.54,p=0.003) there exists negative correlation; NAA / Cr with the MMSE(r=0.36,p=0.023), MoCA (r=0.67,p=0.011)there exists positive correlation; Volum positive correlation with the MoCA(r=0.78,p=0.002).
Conclusion:
1.Changes in cognitive function in patients with diabetes showed a decline in NAA and Cho elevated and volume contraction.
2.Diabetes NAA / Cr NAA / Cr with the MMSE, MoCA has a linear positive correlation; Cho / Cr with the MMSE, MoCA has a linear negative correlation; hippocampal volume positive linear correlation with the MoCA.
本文研究部分立足于糖尿病患者海马体积、神经代谢物与认知功能的相关性研究,通过2型糖尿病患者海马神经代谢物和海马体积的测量分析海马神经代谢物及体积的变化,同时检测每名患者认知评分观察认知的改变,最终通过统计学分析建立2型糖尿病患者海马神经代谢物和体积与认知评分之间变化的线性关系。最后得出结论MRI是一种活体无创性的识别及评估糖尿病认知功能损害的可视化、定量方法,对其认知功能的损害可做出早期的预警和治疗评估有所帮助。
Nowadays, ,diabetes and its complication are one of the main reasons leading to paralysis and death with the development of living. Central nervous system damage and complications of diabetes have become the focus of clinical practice. Central nervous system impairment, especially cognitive impairment, is the most serious and ultimate consequences of central nervous system damage of diabetes. With the development of MRI and the imaging of central nervous system , MRI has developed to Clinical diagnostic methods from morphology studying to Morphology, physiology and function combined. So it is possible to establish a method of non-invasive in vivo to diagnosis cognitive impairment in patients with diabetes.
Objective::
Hippocampal volume in patients with diabetes and to explore neural metabolite changes associated with cognitive function, to find a response to the pathological basis of cognitive impairment and early diagnosis of diabetes and evaluation of cognitive impairment in patients with the disease, an important auxiliary tool to monitor efficacy.
Method:
According to selection criteria, select diabetic and normal control group 63 samples who comes to China-Japan union hospital for treatment, they were detected by proton magnetic resonance spectroscopy(1H-MRS) .All samples are measured three Metabolites of hippocampal neurons including Choline, N-acetyl aspartic, inositol and creatine ratio, Hippocampal volume and Montreal cognitive and mini-mental scale score .
Inputs data in Excel, and analysis statistic by software SPSS 17.0. the measured data which meets normally distributed expressed with x±s, and the measured data which meets non- normally distributed expressed with median(M(QL,QU )).The balancing test of two groups of age, years of education using t-test, data were compared between the two groups meet t normally distributed , homogeneity of variance using independent samples t-test , data of two groups meet normally distributed, Variance arrhythmia using t '-test; Two groups of data do not meet the normal distribution using rank sum test; linear correlation analysis between the data uses dual variable correlation analysis (Bivariate), Calculate the Spearman Correlation coefficient.
Result:
1. The 32 samples of diabetes patient and 31 of healthy, the average age of the control group is 58.54±7.03, the average age of the diabetes is 60.01+6.99. There is no significant difference between the two groups.The time of educational control group is 11.30+2.54 and diabetes group is 11.75+2.44. There is also no significant difference between the two groups. Systolic and diastolic blood pressure showed no significant difference between the two groups.
2. The three metabolites ratio of diabetic group is Cho/Cr=1.41(1.22,1.56,),NAA/Cr=0.86(0.59,1.32,),MI/Cr =0.31 (0.17,0.43,),control group is Cho/Cr=1.20(1.06,1.48),NAA/Cr=1.24(1.06,1.48), MI/Cr=0.24(0.17,0.41).Non-normal data using rank sum test to compare differences between groups, PCho/Cr=0.0284, P NAA/Cr= 0.0011,P<0.05, with a statistically significant difference. P MI/Cr=0.5587,P>0.05, has not a statistically significant difference.
3. Hippocampal volume of diabetic group is 3.27 (3,4), normal control group 3.48(3.01,3.91).There is a significant difference between the two groups by Rank sum test (P =0.023, P<0.05).
4. Montreal Cognitive of diabetic groups is 22.52+3.97, normal control is 25.15+2.84.The two groups data is analysed by t-test,and P = 0.0347,p<0.05.There is a statistically difference. Mini-mental scale score of diabetic group is 24(23,25) and normal control group is 27(28,29), Rank sum test to compare results : P=0.0021, p<0.05, with a statistically significant difference.
5. Linear correlation analysis between the data of diabetic group uses dual variable correlation analysis (Bivariate), and Calculate the Spearman Correlation coefficient.The Results is Cho / Cr with the MMSE( r= -0.46,p=0.013), MoCA(r= -0.54,p=0.003) there exists negative correlation; NAA / Cr with the MMSE(r=0.36,p=0.023), MoCA (r=0.67,p=0.011)there exists positive correlation; Volum positive correlation with the MoCA(r=0.78,p=0.002).
Conclusion:
1.Changes in cognitive function in patients with diabetes showed a decline in NAA and Cho elevated and volume contraction.
2.Diabetes NAA / Cr NAA / Cr with the MMSE, MoCA has a linear positive correlation; Cho / Cr with the MMSE, MoCA has a linear negative correlation; hippocampal volume positive linear correlation with the MoCA.
引文
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[2] Knig H,Aubert RE,Hemrna WH.Global burden of dibaetes,1995-2025: Prevalenee,numerieal estimates,and PorjeCtions.Dibaeets Care, 1998,21(9): 1414-31.
[3]李小明,胡予.糖尿病与阿尔茨海默病关系的研究进展[J].中国老年医学杂志, 2009,(2): 168-170.
[4] Steiner J,Rafols D,Park HK,et a1.Attenuation of iNOS mRNA exacerbates hypoper fusion and upregulates endothelin-1 expression in hippocampus and cortex after brain trauma[J].Nitric Oxide,2004,10(3):162-169
[5] BozokiA,Giordani B,Heidebrink JL,et al.Mild cognitive impairments predictdementia in nondemented elderly patientswithmemory loss[J].ArchNeuro, 2001, 58(3): 411-416.
[6] Petersen RC, Smith GE, Waring SC, et al. Mild cognitive impairment:clinical characterization and outcome. Arch Neurol. 1999,56(3): 303-308.
[7] Stewart R,Liolitsa D.Tpye 2 dibaetes mellitus,congitive impaimrent and demnetia.Dibaet Med ,1999,16(2):93-112
[8]李敏,张丽.老年2型糖尿病与轻度认知功能障碍的关系研究[J].中国全科医学,2011,14(5B):1537-1539.
[9] Whitmer R,Arenberg D.Type 2 diabetes and risk of cognitive impairment and dementia[J].Cur Neurol Neurosci Rep,2007,7(15):373-380.
[10]杨礼,秦琴保,.老年高干人群轻度认知功能障碍调查及危险因素分析[J].中国神经精神疾病杂志,2011,(8).
[11] Nasreddine ZS,Philips NA,Bedirian V,et al. The montreal cog-nitive assessment,MoCA:a brief screening too l for mild cognitive impairment[J].J Am Geriatrics Soc,2005,53:695-699.
[12] Ammon-Treiber S.Effects of opioid antagonists and morphine in ahippocampal hypoxia/hypoglycemia model[J].Neuropharmacology,2005,49(8):1160-1169.
[13]高原,肖谦等.应用体视学方法比较糖尿病大鼠和正常大鼠海马的体积[J].中国老年学杂志,2010,30(20):2959-2960.
[14] Den Heijer T,Vermeer SE,Van Dijk EJ,et al.Type 2 diabetes and atrophy of medial temporal lobe structures on brain MRI[J].Diabetologia, 2003, 46(12):1604-1610.
[15] Masdeu J C, Zubieta J L, Arbizu J. Neuroimaging as a marker of the onset and progression of Alzheimer s disease[J]. J Neurol Sci,2005,236(122):55-64.
[16] Atiya M, Hyman B T, Albert M S, et al. Structural magnetic resonance imaging in established and prodromal Alzheimer disease:a review[J]. Alzheimer Dis Assoc Disord, 2003,17(9):177-195.
[17]陈拥彬,刘德明.糖尿病脑病海马神经元凋亡的实验研究[J].咸宁学院学报(医学版),2006,19(4):295-297.
[18]马学毅,盛树立,胡景胜,等.糖尿病大鼠认知功能障碍及形态学改变关系的研究[J].中国糖尿病杂志,1999,7(3):150-153.
[19] Briellmann RS,Kalnins RM,Berkovic SF,et al.hippocampal pathologyin refractory temporal lobeepilepsy T2-weighted signal change reflects dentategliosis [J].Neurology,2002,58(2): 265-271.
[20]丁蓓.轻度认知功能障碍的神经影像学研究进展[J].国外医学临床放射学分册,2007,30(2):77-80.
[21] Saka E, Dogan E A, Topcuoglu M A, et al. Linear measures of temporal lobe atrophy on brain magnetic resonance imaging (MRI) but not visual rating of white matter changes can help discrimination of mild cognitive impairment ( MCI ) and Alzheimer s disease (AD)[J]. Arch Gerontol Geriatri,2007,44 (2):141-151.
[22]楼海燕.磁共振成像及波谱技术对血管性认知功能损害的海马形态和功能改变的研究.华中科技大学博士学位论文,2004.
[23] Podell M,Hadjieonstantinou M,Snlith MAetal.Proton magnetic resonance Imaging and SpectroscoPy identify,netabolic changes in the striatum in the MPTP Feline model of parkinsonism[J].ExpNeurol,2003,179(2):159-166.
[24] Jackson GD,Berkovic SF,Duncan JS,et al.Optimizing the diagnosis of hippocamp alsclerosisusing MR imaging[J].AJNR,1993,14(3):753-76.
[25] Detre JA,Wang Z,Bogdan AR,et al.Regional variation in brain lactate in leigh syndrome by localized 1H magnetic resonance spectroscopey.Ann Neurol ,1991,29:218-221.
[26] Doraiswamy PM,Chen JG,Charles HC.Brain magnetic resonance spectroscopy: role in assessing outcomes in Alzheimer’s disease.CNS Drugs,2000,14:457-472.
[27]彭洪娟,赵斌.HMRS基本原理及成像技术[J].医学影像学杂志, 2004,12:1033-1035.
[28] Frederrick BD,Lyoo IK,Satlin A,et al.In vivo proton magnetic resonance spectroscopy of the temporal lobe in Alzheimer s disease.Prog Neuropsychopharmacol Biol Psychiatry,2004,28(8):1313-1322.
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