Association Between Cerebral White Matter Lesions And Nsulin Resistance And Cognitive Impairment

Objectives1.By observing insulin resistance ( IR ) and checking the Serum advanced glycosylation end prodrcts (AGEs) of patients with cerebral white matte lesions (CWML)and patients without it, to investigate the relationship between CWML and IR and AGEs, and the correlation between AGEs and IR.2. To explore the pathogenesis that AGEs and IR lead to CWML, so that theoretical basis for early diagnosis and early intervention of CWML could be provided.3. To explore the correlation between WMLs and cognitive impairment.Methods1.Case selecting:From March to December 2010, 176 in-patients from Gerontology and Neurology departments of Shandong University affiliated Qianfoshan Hospital were selected. After strict screening, 92 were enrolled into this experiment with 50 male and 42 female, and the age varied between 52-82, with the mean age 67±5.7 .2. Exclusion criteria were as follows:2.1 Patients with serious chronic diseases, such as renal failure, severe lung disease, severe liver function impairment, arteriosclerosis obliterans, and sleep apnea syndrome;2.2 Other diseases which might cause white matter lesions, such as multiple sclerosis, viral encephalitis, metabolic encephalopathy, toxic encephalopathy (such as carbon monoxide poisoning), radiation encephalopathy,and familial central nervous system diseases (such as CADASIL );2.3 Patients with brain tumor, brain trauma, massive stroke and epilepsy;2.4 Patients who had been taking insulin and long-acting hypoglycemic drug recently. 3.Test method3.1 All patients were supposed to take MRI scanning of the brain. According to Fazekas rating scale, the patients were divided into two groups : the positive group(including grade 1,2 and 3), 46 cases, and the negative group(grade 0), 46 cases. Fazekas rating scale: No lesion: grade 0; Speckle lesions: grade 1; Partly integrated lesions: grade 2; Widely integrated lesions : grade 3.3.2 The following items were checked for each patient: blood pressure, blood lipids, blood glucose, glycated hemoglobin, fasting insulin, insulin resistance index (HOMA-IR), and advanced glycation end products.3.3 All selected patients were supposed to take neuropsychological scale testing, including the Montreal Cognitive Assessment (MoCA), Mini Mental Mental State Examination (MMSE), and Hamilton Depression Rating Scale (HAMD).4. Statistical MethodsAll results were processed by SPSS13.0 statistical software. Logistic multiple regression was used to analyze the important risk factors of WMLs.. P < 0.05 represented a difference with statistical significance .Results1.Insulin resistance and AGEs of WMLs positive patients were higher than that of WMLs negative group. Univariate Logistic Regression analysis showed that the difference has a statistical significance(P<0.05).2. After Cerebral white matter lesions classification, insulin resistance index by the single factor analysis of variance between different level had statistical significance . Advanced glycosylation end prodrcts,had not the same result. But mergering level 1 and 2 with 3 comparison, there was a statistically significant difference.3.Multivariate unconditional Logistic Regression analysis (likelihood ratio Forward test) showed that age, body mass index,hypertension, insulin resistance and AGEs were partially related to WMLs(P<0.05), and the OR was1.398,6.178,5.588,3.184 and 3.797 respectively.4.MoCA, MMSE score of Cerebral white matter lesions positive group compared to white matter lesions negative groups was statistically significant differences . Cognitive dysfunction caused by WMLs are mainly in memory, language and calculation and visual spatial function. The degree of Cerebral white matter lesions with cognitive impairment severity in patients were positively correlated. Conclusion1. Insulin resistance and AGEs are important risk factors for WMLs. The higher the insulin resistance and AGEs are, the more severe WMLs will be.2. Cognitive dysfunction caused by WMLs are mainly in memory, language and calculation and visual spatial function. The more severe WMLs is, the more cognitive decline will be.