ABSTRACT
BACKGROUND: Alzheimer's disease (AD) and mild cognitive impairment (MCI) are two neurodegenerative diseases. Most patients with MCI will develop AD. Early detection of AD and MCI is a crucial issue in terms of secondary prevention. Therefore, more diagnostic models need to be developed to distinguish AD patients from MCI patients. METHODS: In our research, the expression matrix and were screened from Gene Expression Omnibus (GEO) databases. A 14-gene diagnostic model was constructed with lasso logistic analysis. The efficiency and accuracy of diagnostic model have also been validated. In order to clarify the expression differences of 14 genes in health donor, AD and MCI, the blood samples of patients and healthy individuals were collected. The mRNA expression of the 14 genes in blood sample were detected. The SH-SY5Y cell injury model was constructed and biological function of POU2AF1 and ANKRD22 in SH-SY5Y have been proved. RESULTS: We obtained 16 genes which have an area under curve (AUC) ≥0.6. After that, a diagnostic model based on 14 genes was constructed. Validation in independent cohort showed that the diagnostic model has a good diagnostic efficiency. The expressions of 6 genes in AD patients were significantly lower than those in healthy individuals and MCI patients, while the expressions of 8 genes in AD patients were significantly higher than those in healthy individuals and MCI patients. In in vitro experiments, we found that two key genes POU2AF1 and ANKRD22 could regulate neuronal development by regulating cell viability and IL-6 expression. CONCLUSION: The diagnostic model established in this study has a good diagnose efficiency. Most of these genes in diagnostic model also showed diagnostic value in AD patients. This research also can help doctors make better diagnosis for the treatment and prevention of AD.
ABSTRACT
BACKGROUND: Nonlinguistic cognitive impairment has become an important issue for aphasic patients, but currently there are few neuropsychological cognitive assessment tests for it. To get more information on cognitive impairment of aphasic patients, this study aimed to develop a new cognitive assessment test battery for aphasic patients, the Non-language-based Cognitive Assessment (NLCA), and evaluate its utility in Chinese-speaking patients with aphasia. METHODS: The NLCA consists of five nonverbal tests, which could assess five nonlinguistic cognitive domains such as visuospatial functions, attention test, memory, reasoning, and executive functions of aphasic patients. All tests are modified from the nonverbal items of the current existed tests with some changes to the characteristics of Chinese culture. The NLCA was tested in 157 participants (including 57 aphasic patients, 50 mild cognitive impairment (MCI) patients, and 50 normal controls), and was compared with other well-established relative neuropsychological tests on the reliability, validity, and utility. RESULTS: The NLCA was fully applicable in the MCI patients and the normal controls, almost working in the aphasic patients (57/62 patients, 91.9%). The NLCA scores were 66.70 ± 6.30, 48.67 ± 15.04, and 77.58 ± 2.56 for the MCI group, the aphasic group, and the control group, respectively , and a significant difference was found among three groups (F = 118.446, P < 0.001). The Cronbach's alpha of the NLCA as an index of internal consistency was 0.805, and the test-retest and interrater reliability was adequate (r=0.977 and r= 0.970, respectively). The correlations of the cognitive subtests and their validation instruments were between 0.540 and 0.670 (all P < 0.05). Spearman's correlation analysis indicated that the coefficient of internal consistency of each subtest itself was higher than other subtests. When choosing the Montreal Cognitive Assessment score of <26 as the diagnostic criteria of cognitive impairment, the area under the curve for all participants in the control and MCI groups was 0.942 (95% confidence interval: 0.895-0.989), and an optimal cutoff point of 75.00 seemed to provide the best balance between sensitivity and specificity. Age (r = -0.406, P < 0.001) was the main influence factor for the NLCA. CONCLUSIONS: The NLCA could efficiently differentiate the cognitive impairment patients from the normal controls and is a reliable and valid cognitive assessment test battery to specially find nonlinguistic cognitive function for aphasic patients.
