Novel plasma protein biomarkers: A time-dependent predictive model for Alzheimer's disease.

BACKGROUND: The accurate prediction of Alzheimer's disease (AD) is crucial for the efficient management of its progression. The objective of this research was to construct a new risk predictive model utilizing novel plasma protein biomarkers for predicting AD incidence in the future and analyze their potential biological correlation with AD incidence. METHODS: A cohort of 440 participants aged 60 years and older from the Alzheimer's Disease Neuroimaging Initiative (ADNI) longitudinal cohort was utilized. The baseline plasma proteomics data was employed to conduct Cox regression, LASSO regression, and cross-validation to identify plasma protein signatures predictive of AD risk. Subsequently, a multivariable Cox proportional hazards model based on these signatures was constructed. The performance of the risk prediction model was evaluated using time-dependent receiver operating characteristic (t-ROC) curves and Kaplan-Meier curves. Additionally, we analyzed the correlations between protein signature expression in plasma and predicted AD risk, the time of AD onset, the expression of protein signatures in cerebrospinal fluid (CSF), the expression of CSF and plasma biomarkers, and APOE ε4 genotypes. Colocalization and Mendelian randomization analyses was conducted to investigate the association between protein features and AD risk. GEO database was utilized to analyze the differential expression of protein features in the blood and brain of AD patients. RESULTS: We identified seven protein signatures (APOE, CGA, CRP, CCL26, CCL20, NRCAM, and PYY) that independently predicted AD incidence in the future. The risk prediction model demonstrated area under the ROC curve (AUC) values of 0.77, 0.76, and 0.77 for predicting AD incidence at 4, 6, and 8 years, respectively. Furthermore, the model remained stable in the range of the 3rd to the 12th year (ROC ≥ 0.74). The low-risk group, as defined by the model, exhibited a significantly later AD onset compared to the high-risk group (P < 0.0001). Moreover, all protein signatures exhibited significant correlations with AD risk (P < 0.001) and the time of AD onset (P < 0.01). There was no strong correlation between the protein expression levels in plasma and CSF, as well as AD CSF biomarkers. APOE, CGA, and CRP exhibited significantly lower expression levels in APOE ε4 positive individuals (P < 0.05). Additionally, colocalization analysis reveals a significant association between AD and SNP loci in APOE. Mendelian randomization analysis shows a negative correlation between NRCAM and AD risk. Transcriptomic analysis indicates a significant downregulation of NRCAM and PYY in the peripheral blood of AD patients (P < 0.01), while APOE, CGA, and NRCAM are significantly downregulated in the brains of AD patients (P < 0.0001). CONCLUSION: Our research has successfully identified protein signatures in plasma as potential risk biomarkers that can independently predict AD onset in the future. Notably, this risk prediction model has demonstrated commendable predictive performance and stability over time. These findings underscore the promising utility of plasma protein signatures in dynamically predicting the risk of AD, thereby facilitating early screening and intervention strategies.

Analysis of key targets for 5-hydroxymethyl-2-furfural-induced lung cancer based on network toxicology, network informatics, and in vitro experiments.

5-hydroxymethyl-2-furfural (5-HMF) is a by-product of Maillard reaction and widely exists in food and environment, which may lead to lung cancer. However, the relevant mechanism is unknown. This study aims to predict the key targets of 5-HMF-induced lung cancer through network toxicology, analyze the relationship between the key targets and lung cancer through network informatics, and further validate them through in vitro experiments. By using ChEMBL, STITCH, GeneCards, and OMIM databases, 51 toxic targets were identified. GO and KEGG enrichment analyses indicated a strong correlation between toxic targets and lung cancer. Through protein-protein interaction (PPI) analysis, MAPK3, MAPK1, and SRC were identified as key targets implicated in 5-HMF-induced lung cancer. The HPA database showed high expression of these three key targets in lung cancer tissues. Kaplan-Meier database demonstrated that the higher expression of these key targets in lung cancer patients was associated with a poorer prognosis. The TIMER database revealed that the high expression of these key targets had a significant impact on the level of immune cell infiltration in lung cancer, particularly impacting CD4+ T cells and macrophages. Finaly, in In vitro experiments demonstrated that prolonged exposure to 5-HMF induced malignant transformation of BEAS-2B cells and the upregulation of key targets. The findings suggest that 5-HMF is a contributing factor in the development of lung cancer, with MAPK3, MAPK1, and SRC potentially playing crucial roles in this process.

SP1-Induced Upregulation of lncRNA LINC00659 Promotes Tumour Progression in Gastric Cancer by Regulating miR-370/AQP3 Axis.

Growing evidence demonstrates that long noncoding RNAs (lncRNAs) play critical roles in various human tumors. LncRNA LINC00659 (LINC00659) is a newly identified lncRNA and its roles in tumors remain largely unclear. In this study, we elucidated the potential functions and molecular mechanisms of LINC00659 on the biological behaviors of gastric cancer (GC), and also explored its clinical significance. We firstly demonstrated that LINC00659 levels were distinctly up-regulated in both GC specimens and cells using bioinformatics analysis and RT-PCR. The results of ChIP assays and luciferase reporter assays confirmed that upregulation of LINC00659 was activated by SP1 in GC. Clinical assays revealed that higher levels of LINC00659 were associated with TNM stage, lymphatic metastasis, and poorer prognosis. Moreover, LINC00659 was confirmed to be an independent prognostic marker for the patients with GC using multivariate assays. Lost-of-function assays indicated that knockdown of LINC00659 suppressed the proliferation, metastasis, and EMT progress of GC cells in vitro. Mechanistic investigation indicated that LINC00659 served as a competing endogenous RNA (ceRNA) for miR-370, thereby resulting in the upregulation of leading to the depression of its endogenous target gene AQP3. Overall, our present study revealed that the LINC00659/miR-370/AQP3 axis contributes to GC progression, which may provide clues for the exploration of cancer biomarkers and therapeutic targets for GC.

Clinical significance of potential drug-drug interactions in older adults with psychiatric disorders: a retrospective study.

BACKGROUND: Polypharmacy increases the risk of potential drug-drug interactions (pDDIs). This retrospective analysis was conducted to detect pDDIs and adverse drug reactions (ADRs) among older adults with psychiatric disorder, and identify pDDIs with clinical significance. METHODS: A retrospective analysis was carried out based on the medical records of older adults with psychiatric disorders. Data on demographic characteristics, substance abuse, medical history, and medications were extracted. The Lexi-Interact online database was used to detect pDDIs. The minimal clinically important difference (MCID) was set as the change in the Treatment Emergent Symptom Scale (TESS) score between admission and discharge. The median and interquartile ranges were used for continuous variables, and frequencies were calculated for dichotomous variables. Poisson regression was implemented to determine the factors influencing the number of ADR types. The influencing factors of each ADR and the clinical significance of the severity of the ADR were analysed using binary logistic regression. P < 0.05 was considered statistically significant. RESULTS: A total of 308 older adults were enrolled, 171 (55.52%) of whom had at least 1 pDDI. Thirty-six types of pDDIs that should be avoided were found, and the most frequent pDDI was the coadministration of lorazepam and olanzapine (55.5%). A total of 26 ADRs induced by pDDIs were identified, and the most common ADR was constipation (26.05%). There was a 9.4 and 10.3% increase in the number of ADR types for each extra medical diagnosis and for each extra drug, respectively. There was a 120% increase in the number of ADR types for older adults hospitalized for 18-28 days compared with those hospitalized for 3-17 days. There was an 11.1% decrease in the number of ADR types for each extra readmission. The length of hospitalization was a risk factor for abnormal liver function (P < 0.05). The use of a large number of drugs was a risk factor for gastric distress (P < 0.05) and dizziness and fainting (P < 0.05). None of the four pDDIs, including coadministrations of olanzapine and lorazepam, quetiapine and potassium chloride, quetiapine and escitalopram, and olanzapine and clonazepam, showed clinical significance of ADR severity (P > 0.05). CONCLUSIONS: pDDIs are prevalent in older adults, and the rate is increasing. However, many pDDIs may have no clinical significance in terms of ADR severity. Further research on assessing pDDIs, and possible measures to prevent serious ADRs induced by DDIs is needed to reduce the clinical significance of pDDIs.

Leonurine protects against ulcerative colitis by alleviating inflammation and modulating intestinal microflora in mouse models.

Inflammatory bowel disease (IBD) is a chronic inflammatory disease of the colon. The aim of the present study was to explore the effects of leonurine (YMJ) on inflammation and intestinal microflora in colonic tissues of a dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) mouse model. Mice were randomly divided into control (n=5), DSS (n=5, treated with DSS) and DSS+YMJ (n=5, treated with DSS and YMJ) groups. Body weight was recorded, disease activity index (DAI) was calculated, and colon histopathology was evaluated using hematoxylin and eosin staining. Serum interleukin (IL)-6, tumor necrosis factor-α (TNF-α) and IL-1ß levels were examined using ELISA. Expression levels of nuclear factor-κB (p65) and phosphorylated (p)-p65 were evaluated via western blotting. 16S ribosomal RNA was extracted from mouse feces. Composition or abundance changes of intestinal microflora were analyzed. The results indicated that YMJ treatment (DSS+YMJ group) significantly increased body weight, reduced DAI scores and increased colon length in UC mouse models compared with those in the DSS group (P<0.05). YMJ significantly reduced inflammatory infiltration, significantly decreased serum TNF-α, IL-6 and IL-1ß levels (P<0.05) and significantly downregulated the p-p65/p65 ratio compared with the DSS group (P<0.05). YMJ increased the quantity of the intestinal flora and improved intestinal microflora diversity in the mice of the DSS group. Specifically, YMJ partly regulated intestinal microflora in feces, including a reduction of Bifidobacterium, and an increase in Parasutterella and Ackermania. In conclusion, YMJ improved disease outcomes of the UC mice, reduced the levels of serum inflammatory factors and increased the ratio of beneficial bacteria in the intestinal tract.

CYP2A13 Acts as the Main Metabolic CYP450s Enzyme for Activating Leonurine in Human Bronchial Epithelial Cells.

BACKGROUND Leonurine is an active component of the traditional Chinese medicine Leonurus japonicus. This study aimed to investigate the effects of overexpressed CYP450s on the metabolic activity of leonurine. MATERIAL AND METHODS BEAS-2B cells stably expressing CYP1A1, 1A2, 2A13, 2B6, and 3A4 were constructed. CYP450s expression was identified using reverse-transcription PCR and Western blot assay. CCK-8 assay was used to evaluate the effect of leonurine on cell activity. Leonurine was incubated in vitro with CYP1A1, 1A2, 2A13, 2B6, and 3A4 metabolic enzymes to evaluate the clearance rate of CYP450 enzymes for leonurine. UPLC-MS was used to detect changes of drug concentration and discover the main metabolic enzymes affecting leonurine. RESULTS BEAS-2B cells stably expressing CYP1A1, 1A2, 2A13, 2B6, and 3A4 were successfully constructed. According to primary mass spectra and secondary mass spectra of leonurine, the main metabolic enzymes were 312.1550 [H+] and 181.0484. Compared to the control group, residue of leonurine in CYP2A13 group was significantly reduced (F=5.307, p=0.024). Compared to the 0-min group, the clearance rate of leonurine in the CYP2A13-treated group was significantly decreased at 120 min after treatment (F=7.273, p=0.007). CCK-8 results also showed that activity of BEAS-2B cells that overexpress CYP2A13 gradually decreased with increased concentration of leonurine. Although CYP2A13 demonstrated good metabolic activity for leonurine, we found that CYP1A1, 1A2, 2B6, and 3A4 had no metabolic effects on leonurine. CONCLUSIONS Leonurine can be effectively activated through CYP2A13 enzyme metabolism, and further inhibits activity of human lung epithelial cells (BEAS-2B). Therefore, CYP2A13 is a main metabolic enzyme for leonurine in BEAS-2B cells.