Risk Factors for Cognitive Impairment in Patients with Type 2 Diabetes

Abstract

Objectives. To investigate the risk factors for cognitive impairment in Chinese type 2 diabetes mellitus (T2DM) patients of advanced age and to identify effective biomarkers of mild cognitive impairment (MCI) in these patients. Methods. Chinese T2DM patients (n=120) aged 50–70 years were divided into groups with impaired (mild, moderate, and severe) and normal cognitive function based on Montreal Cognitive Assessment and Mini-Mental State Examination scores. Data regarding demographic characteristics, clinical features of diabetes, biochemical markers, and metabolomics were collected. Results. Age, educational level, duration of diabetes, fasting blood glucose (FBG), HbA1c, total cholesterol (TC), triglyceride (TG), and 24-hour urine protein were significantly associated with cognitive impairment in T2DM patients of advanced age. The severity of fundus retinopathy and the incidence of macrovascular disease also differed significantly among the groups (P<0.05). Metabolomics analysis suggested that increased levels of glutamate (Glu), phenylalanine (Phe), tyrosine (Tyr), proline (Pro), and homocysteine (Hcy) and a decreased level of glutamine (Gln) were significantly associated with cognitive impairment in the T2DM patients (P<0.05). Receiver operating characteristic curve analysis demonstrated that Glu, Gln, Phe, and Pro levels were significant predictors of cognitive impairment in the T2DM patients. Conclusions. Age, educational level, duration of diabetes, and the levels of FBG, HbA1c, TC, TG, and 24-hour urine protein were considered as independent risk factors for cognitive impairment in older T2DM patients. Macrovascular and microvascular diseases also were closely associated with cognitive impairment in these patients. Together, Glu and Gln levels may represent a good predictive biomarker for the early diagnosis of cognitive impairment in T2DM patients.

Neuroprotective Effects of ZiBuPiYin Recipe on db/db Mice via PI3K-Akt Signaling Pathway by Activating Grb2

“…As shown in Figure 1(a), body weight of DM mice was significantly heavier compared to control mice while ZBPYR administration had no significant effects on body weight. RBG levels of DM/ZBPYR mice were significantly lower than DM mice from the 3rd week to the 6th Neural Plasticity cognitive decline and poor cognitive performance [27].…”

“…Additionally, the administration of ZBPYR also significantly decreased the blood glucose levels at 60 min (0.64 times) after insulin injection ( Figure 1(d) ). DM mice exhibited impaired glucose tolerance and insulin sensitivity which are associated with the development of cognitive decline and poor cognitive performance [ 27 ]. Treatment with ZBPYR could improve the impaired glucose tolerance and insulin sensitivity of DM mice.…”

Applications of Multivariate Statistical and Data Mining Analyses to the Search for Biomarkers of Sensorineural Hearing Loss, Tinnitus, and Vestibular Dysfunction

“…In the search for biomarkers of SNHL, tinnitus and vestibular dysfunction, classification methods such as linear discriminant analysis, support vector machines, random forest classification, Bayesian classifiers and OPLS-DA, can be applied to behavioral, neurophysiological and neurochemical data to predict the probability of a disease or disorder developing, in order to intervene and provide treatments that will prevent or impede the pathological changes. In the context of metabolomics, MVAs and data mining methods have already been proven to be useful in the prediction of disease [e.g., ( 8 , 9 , 11 – 13 , 78 – 80 )]. OPLS-DA is an example of an MVA that has successfully been applied to metabolomic data in order to predict hearing loss in rats ( 35 , 65 ) and may be particularly useful in the search for biomarkers of SNHL, tinnitus, and vestibular dysfunction [e.g., ( 81 )].…”

Transcranial Doppler for Early Prediction of Cognitive Impairment after Aneurysmal Subarachnoid Hemorrhage and the Associated Clinical Biomarkers

“…The predominance of impaired cognitive functions is especially higher in diabetic patients [ 45 ] and older patients [ 36 ], as they showed macrovascular and microvascular disorders that were related to the cognitive impairment in these patients [ 45 ].…”