OBJECTIVE: This study aimed to determine the effect of age on the protein profile of Malay individuals and its association with cognitive competency.
METHODS: A total of 160 individuals were recruited and grouped accordingly. Cognitive competency of each subject was assessed with several neuropsychological tests. Plasma samples were collected and analyzed with Q Exactive HF Orbitrap. Proteins were identified and quantitated with MaxQuant and further analyzed with Perseus to determine differentially expressed proteins. PANTHER, Reactome, and STRING were applied for bioinformatics output.
RESULTS: Our data showed that the Malay individuals are vulnerable to the deterioration of cognitive function with aging, and most of the proteins were differentially expressed in concordance. Several physiological components and pathways were shown to be involved, giving a hint of a promising interpretation on the induction of aging toward the state of the Malays' cognitive function. Nevertheless, some proteins have shown a considerable interaction with the generated protein network, which provides a direction of focus for further investigation.
CONCLUSION: This study demonstrated notable changes in the expression of several proteins as age increased. These changes provide a promising platform for understanding the biochemical factors affecting cognitive function in the Malay population. The exhibited network of protein-protein interaction suggests the possibility of implementing regulatory intervention in ameliorating Malay cognitive function.
Objective: We aimed to study the prevalence of visual memory dysfunction among epilepsy patients and identify the predictors that could contribute to the impairment.
Materials and Methods: This was a cross-sectional study. We analyzed 250 patients with epilepsy from neurology clinic at our tertiary center. Assessment of visual memory was done using Wechsler Memory Scale-IV (WMS-IV) with scores from subsets of visual reproduction I, II and designs I, II contributing to visual memory index (VMI) score. The correlation between continuous variables was analyzed using Pearson correlation; whereas the VMI scores of different factors were analyzed via a 1-way ANOVA test. The statistical significance was set at P < 0.05.
Results: The prevalence of visual memory dysfunction in our epilepsy population was 37.2%. Analysis of individual predictors showed that older patients, lower educational level, combined generalized and focal types of epilepsy, longer duration of epilepsy, greater number of antiepileptic drugs (AEDs) used, and abnormal neuroimaging contributed to poor visual memory. Multiple logistic regression analysis showed that educational level, types of epilepsy, and the number of AEDs used were significant predictors for visual memory impairment.
Conclusion: Visual memory dysfunction in patients with epilepsy was due to manifold confounding factors. Our findings enabled us to identify patients with visual memory dysfunction and modifiable factors that contribute to it. WMS-IV is a suitable assessment tool to determine visual memory function, which can help clinicians to optimize the patients' treatment.