Periphery Biomarkers Predicting Conversion of Type 2 Diabetes to Pre-Alzheimer-Like Cognitive Decline: A Multicenter Follow-Up Study.

Background: The prevalence of Alzheimer's disease (AD) is increasing, therefore, identifying biomarkers to predict those vulnerable to AD is imperative. Type 2 diabetes (T2D) serves as an independent risk factor for AD. Early prediction of T2D patients who may be more susceptible to AD, so as to achieve early intervention, is of great significance to reduce the prevalence of AD. Objective: To establish periphery biomarkers that could predict conversion of T2D into pre-AD-like cognitive decline. Methods: A follow-up study was carried out from 159 T2D patients at baseline. The correlations of cognitive states (by MMSE score) with multi-periphery biomarkers, including APOE genotype, plasma amyloid-ß level, platelet GSK-3ß activity, and olfactory score were analyzed by logistic regression. ROC curve was used for establishing the prediction model. Additionally, MRI acquired from 38 T2D patients for analyzing the correlation among cognitive function, biomarkers and brain structure. Results: Compared with the patients who maintained normal cognitive functions during the follow-up period, the patients who developed MCI showed worse olfactory function, higher platelet GSK-3ß activity, and higher plasma Aß42/Aß40 ratio. We conducted a predictive model which T2D patients had more chance of suffering from pre-AD-like cognitive decline. The MRI data revealed MMSE scores were positively correlated with brain structures. However, platelet GSK-3ß activity was negatively correlated with brain structures. Conclusions: Elevated platelet GSK-3ß activity and plasma Aß42/Aß40 ratio with reduced olfactory function are correlated with pre-AD-like cognitive decline in T2D patients, which used for predicting which T2D patients will convert into pre-AD-like cognitive decline in very early stage.

GSK-3ß activation mediates apolipoprotein E4-associated cognitive impairment in type 2 diabetes mellitus: A multicenter, cross-sectional study.

AIM: Both the activation of glycogen synthase kinase-3ß (GSK-3ß) and the presence of ApoE ε4 genotype have been found to respectively correlate with cognitive decline in patients with type 2 diabetes mellitus (T2DM), who further show a high incidence of developing Alzheimer's disease. However, the relationship between ApoE ε4 and GSK-3ß in the cognitive impairment of T2DM patients remains unclear. METHODS: ApoE genotypes and platelet GSK-3ß level were measured in 1139 T2DM patients recruited from five medical centers in Wuhan, China. Cognitive functions were assessed by Mini-Mental State Examination (MMSE). The association and the relationships among apolipoprotein E (ApoE) genotypes, GSK-3ß activity and cognitive function were analyzed by regression and mediating effect analyses, respectively. RESULTS: T2DM patients with ApoE ε4 but not ApoE ε2 haplotype showed poorer cognitive function and elevated platelet GSK-3ß activity, when using ApoE ε3 as reference. The elevation of GSK-3ß activity was positively correlated the diabetes duration, as well as plasma glycated hemoglobin (HbA1c) and glucose levels. Moreover, correlation and regression analysis also revealed significant pairwise correlations among GSK-3ß activity, ApoE gene polymorphism and cognitive function. Lastly, using Baron and Kenny modeling, we unveiled a mediative role of GSK-3ß activity between ApoE ε4 and cognitive impairment. CONCLUSION: We reported here that the upregulation of GSK-3ß activity mediates the exacerbation of cognitive impairment by ApoE ε4-enhanced cognitive impairment in T2DM patients, suggesting GSK-3ß inhibitors as promising drugs for preserving cognitive function in T2DM patients, especially to those with ApoE ε4 genotype.

Olfactory Threshold Test as a Quick Screening Tool for Cognitive Impairment: Analysis of Two Independent Cohorts.

BACKGROUND: Olfactory dysfunction appears prior to cognitive decline, and thus it has been suggested to be an early predictor of Alzheimer's disease. However, it is currently not known whether and how olfactory threshold test could serve as a quick screening tool for cognitive impairment. OBJECTIVE: To define olfactory threshold test for screening cognitive impairment in two independent cohorts. METHODS: The participants are comprised of two cohorts in China, 1,139 inpatients with type 2 diabetes mellitus (T2DM, Discovery cohort) and 1,236 community-dwelling elderly (Validation cohort). Olfactory and cognitive functions were evaluated by Connecticut Chemosensory Clinical Research Center test and Mini-Mental State Examination (MMSE), respectively. Regression analyses and receiver operating characteristic (ROC) analyses were carried out to determine the relation and discriminative performance of the olfactory threshold score (OTS) regarding identification of cognition impairment. RESULTS: Regression analysis showed that olfactory deficit (reducing OTS) was correlated with cognitive impairment (reducing MMSE score) in two cohorts. ROC analysis revealed that the OTS could distinguish cognitive impairment from cognitively normal individuals, with mean area under the curve values of 0.71 (0.67, 0.74) and 0.63 (0.60, 0.66), respectively, but it failed to discriminate dementia from mild cognitive impairment. The cut-off point of 3 showed the highest validity for the screening, with the diagnostic accuracy of 73.3% and 69.5%. CONCLUSION: Reducing OTS is associated with cognitive impairment in T2DM patients and the community-dwelling elderly. Therefore, olfactory threshold test may be used as a readily accessible screening tool for cognitive impairment.

Periphery Biomarkers for Objective Diagnosis of Cognitive Decline in Type 2 Diabetes Patients.

Introduction: Type 2 diabetes mellitus (T2DM) is an independent risk factor of Alzheimer's disease (AD), and populations with mild cognitive impairment (MCI) have high incidence to suffer from AD. Therefore, discerning who may be more vulnerable to MCI, among the increasing T2DM populations, is important for early intervention and eventually decreasing the prevalence rate of AD. This study was to explore whether the change of plasma ß-amyloid (Aß) could be a biomarker to distinguish MCI (T2DM-MCI) from non-MCI (T2DM-nMCI) in T2DM patients. Methods: Eight hundred fifty-two T2DM patients collected from five medical centers were assigned randomly to training and validation cohorts. Plasma Aß, platelet glycogen synthase kinase-3ß (GSK-3ß), apolipoprotein E (ApoE) genotypes, and olfactory and cognitive functions were measured by ELISA, dot blot, RT-PCR, Connecticut Chemosensory Clinical Research Center (CCCRC) olfactory test based on the diluted butanol, and Minimum Mental State Examination (MMSE) test, respectively, and multivariate logistic regression analyses were applied. Results: Elevation of plasma Aß1-42/Aß1-40 is an independent risk factor of MCI in T2DM patients. Although using Aß1-42/Aß1-40 alone only reached an AUC of 0.631 for MCI diagnosis, addition of the elevated Aß1-42/Aß1-40 to our previous model (i.e., activated platelet GSK-3ß, ApoE ε4 genotype, olfactory decline, and aging) significantly increased the discriminating efficiency of T2DM-MCI from T2DM-nMCI, with an AUC of 0.846 (95% CI: 0.794-0.897) to 0.869 (95% CI: 0.822-0.916) in the training cohort and an AUC of 0.848 (95% CI: 0.815-0.882) to 0.867 (95% CI: 0.835-0.899) in the validation cohort, respectively. Conclusion: A combination of the elevated plasma Aß1-42/Aß1-40 with activated platelet GSK-3ß, ApoE ε4 genotype, olfactory decline, and aging could efficiently diagnose MCI in T2DM patients. Further longitudinal studies may consummate the model for early prediction of AD.

Platelet biomarkers identifying mild cognitive impairment in type 2 diabetes patients.

Type 2 diabetes mellitus (T2DM) is an independent risk factor of Alzheimer's disease (AD). Therefore, identifying periphery biomarkers correlated with mild cognitive impairment (MCI) is of importance for early diagnosis of AD. Here, we performed platelet proteomics in T2DM patients with MCI (T2DM-MCI) and without MCI (T2DM-nMCI). Pearson analysis of the omics data with MMSE (mini-mental state examination), Aß1-42/Aß1-40 (ß-amyloid), and rGSK-3ß(T/S9) (total to Serine-9-phosphorylated glycogen synthase kinase-3ß) revealed that mitophagy/autophagy-, insulin signaling-, and glycolysis/gluconeogenesis pathways-related proteins were most significantly involved. Among them, only the increase of optineurin, an autophagy-related protein, was simultaneously correlated with the reduced MMSE score, and the increased Aß1-42/Aß1-40 and rGSK-3ß(T/S9), and the optineurin alone could discriminate T2DM-MCI from T2DM-nMCI. Combination of the elevated platelet optineurin and rGSK-3ß(T/S9) enhanced the MCI-discriminating efficiency with AUC of 0.927, specificity of 86.7%, sensitivity of 85.3%, and accuracy of 0.859, which is promising for predicting cognitive decline in T2DM patients.

Platelet biomarkers for a descending cognitive function: A proteomic approach.

Memory loss is the most common clinical sign in Alzheimer's disease (AD); thus, searching for peripheral biomarkers to predict cognitive decline is promising for early diagnosis of AD. As platelets share similarities to neuron biology, it may serve as a peripheral matrix for biomarkers of neurological disorders. Here, we conducted a comprehensive and in-depth platelet proteomic analysis using TMT-LC-MS/MS in the populations with mild cognitive impairment (MCI, MMSE = 18-23), severe cognitive impairments (AD, MMSE = 2-17), and the age-/sex-matched normal cognition controls (MMSE = 29-30). A total of 360 differential proteins were detected in MCI and AD patients compared with the controls. These differential proteins were involved in multiple KEGG pathways, including AD, AMP-activated protein kinase (AMPK) pathway, telomerase RNA localization, platelet activation, and complement activation. By correlation analysis with MMSE score, three positively correlated pathways and two negatively correlated pathways were identified to be closely related to cognitive decline in MCI and AD patients. Partial least squares discriminant analysis (PLS-DA) showed that changes of nine proteins, including PHB, UQCRH, CD63, GP1BA, FINC, RAP1A, ITPR1/2, and ADAM10 could effectively distinguish the cognitively impaired patients from the controls. Further machine learning analysis revealed that a combination of four decreased platelet proteins, that is, PHB, UQCRH, GP1BA, and FINC, was most promising for predicting cognitive decline in MCI and AD patients. Taken together, our data provide a set of platelet biomarkers for predicting cognitive decline which may be applied for the early screening of AD.