ABSTRACT
With the development of society, the incidence of dementia and type 2 diabetes (T2DM) in the elderly has been increasing. Although the correlation between T2DM and mild cognitive impairment (MCI) has been confirmed in the previous literature, the interaction mechanism remains to be clarified. To explore the co-pathogenic genes in the blood of MCI and T2DM patients, clarify the correlation between T2DM and MCI, achieve the purpose of early disease prediction, and provide new ideas for the prevention and treatment of dementia. We downloaded T2DM and MCI microarray data from GEO databases and identified the differentially expressed genes associated with MCI and T2DM. We obtained co-expressed genes by intersecting differentially expressed genes. Then, we performed GO and KEGG enrichment analysis of co-DEGs. Next, we constructed the PPI network and found the hub genes in the network. By constructing the ROC curve of hub genes, the most valuable genes for diagnosis were obtained. Finally, the correlation between MCI and T2DM was clinically verified by means of a current situation investigation, and the hub gene was verified by qRT-PCR. A total of 214 co-DEGs were selected, 28 co-DEGs were up-regulated, and 90 co-DEGs were down-regulated. Functional enrichment analysis showed that co-DEGs were mainly enriched in metabolic diseases and some signaling pathways. The construction of the PPI network identified the hub genes in MCI and T2DM co-expression genes. We identified nine hub genes of co-DEGs, namely LNX2, BIRC6, ANKRD46, IRS1, TGFB1, APOA1, PSEN1, NPY, and ALDH2. Logistic regression analysis and person correlation analysis showed that T2DM was correlated with MCI, and T2DM increased the risk of cognitive impairment. The qRT-PCR results showed that the expressions of LNX2, BIRC6, ANKRD46, TGFB1, PSEN1, and ALDH2 were consistent with the results of bioinformatic analysis. This study screened the co-expressed genes of MCI and T2DM, which may provide new therapeutic targets for the diagnosis and treatment of diseases.
ABSTRACT
Background: Alzheimer's disease (AD), type 2 diabetes mellitus (T2DM), and Major Depressive Disorder (MDD) have a higher incidence rate in modern society. Although increasing evidence supports close associations between the three, the mechanisms underlying their interrelationships remain elucidated. Objective: The primary purpose is to explore the shared pathogenesis and the potential peripheral blood biomarkers for AD, MDD, and T2DM. Methods: We downloaded the microarray data of AD, MDD, and T2DM from the Gene Expression Omnibus database and constructed co-expression networks by Weighted Gene Co-Expression Network Analysis to identify differentially expressed genes. We took the intersection of differentially expressed genes to obtain co-DEGs. Then, we performed GO and KEGG enrichment analysis on the common genes in the AD, MDD, and T2DM-related modules. Next, we utilized the STRING database to find the hub genes in the protein-protein interaction network. ROC curves were constructed for co-DEGs to obtain the most diagnostic valuable genes and to make drug predictions against the target genes. Finally, we conducted a present condition survey to verify the correlation between T2DM, MDD and AD. Results: Our findings indicated 127 diff co-DEGs, 19 upregulated co-DEGs, and 25 down-regulated co-DEGs. Functional enrichment analysis showed co-DEGs were mainly enriched in signaling pathways such as metabolic diseases and some neurodegeneration. Protein-protein interaction network construction identified hub genes in AD, MDD and T2DM shared genes. We identified seven hub genes of co-DEGs, namely, SMC4, CDC27, HNF1A, RHOD, CUX1, PDLIM5, and TTR. The current survey results suggest a correlation between T2DM, MDD and dementia. Moreover, logistic regression analysis showed that T2DM and depression increased the risk of dementia. Conclusion: Our work identified common pathogenesis of AD, T2DM, and MDD. These shared pathways might provide novel ideas for further mechanistic studies and hub genes that may serve as novel therapeutic targets for diagnosing and treating.
ABSTRACT
Diabetes mellitus (DM) is known to be a risk factor for dementia, especially in the elderly population, and close associations between diabetes and Alzheimer disease (AD) have been determined. Peroxisome proliferator-activated receptor-gamma (PPAR-γ) agonists are insulin-sensitising drugs. In addition to their anti-diabetic properties, their effectiveness in preventing and decreasing cognitive impairment are the most recent characteristics that have been studied. For this study, we conducted a systematic review and meta-analysis to critically analyse and evaluate the existing data on the effects of PPAR-γ agonist therapy on the cognitive status of patients. For this purpose, we first analysed both early intervention and later treatment with PPAR-γ agonists, according to the disease status. The involved studies indicated that early PPAR-γ agonist intervention is beneficial for patients and that high-dose PPAR-γ therapy may have a better clinical effect, especially in reversing the effects of cognitive impairment. Furthermore, the efficacy of pioglitazone (PIO) seems to be promising, particularly for patients with comorbid diabetes. PIO presented a better clinical curative effect and safety, compared with rosiglitazone (RSG). Thus, PPAR-γ agonists play an important role in the inflammatory response of AD or DM patients, and clinical therapeutics should focus more on relevant metabolic indices.
ABSTRACT
Background: The many studies revealing a connection between serum uric acid (SUA) and dementia have reported conflicting results. This study sought to investigate the relations between SUA and cognitive function in older adults. Materials and methods: The sample was 2,767 American adults aged ≥60 years from the National Health and Nutrition Examination Survey 2011-2014. Cognitive performance was evaluated by the Consortium to Establish a Registry for Alzheimer's Disease test, animal fluency test, digit symbol substitution test, and composite z-score. Multivariate linear regression analyses were conducted to estimate the association between SUA and cognitive function. Results: SUA level and cognitive function were significantly, positively correlated. Age significantly correlated with the association between SUA and cognitive function. Conclusion: These findings support a connection between SUA and cognition, showing a positive link between SUA and cognitive scores among older American adults. We contend that a slight rise in uric acid within the normal range is advantageous for enhanced cognition. To confirm the precise dose-time-response relation, more tests will be needed.
ABSTRACT
Alzheimer's disease (AD) is a chronic, progressive neurodegenerative disease characterized by memory loss, inability to carry out everyday daily life, and noticeable behavioral changes. The essential neuropathologic criteria for an AD diagnosis are extracellular ß-amyloid deposition and intracellular accumulation of hyperphosphorylated tau. However, the exact pathogenic mechanisms underlying AD remain elusive, and current treatment options show only limited success. New research indicates that the gut microbiota contributes to AD development and progression by accelerating neuroinflammation, promoting senile plaque formation, and modifying neurotransmitter production. This review highlights laboratory and clinical evidence for the pathogenic role of gut dysbiosis on AD and provides potential cues for improved AD diagnostic criteria and therapeutic interventions based on the gut microbiota.
