METHODS: A systematic search was conducted on PubMed, EBSCOHost, and Web of Science. We identified 22 casecontrol studies that matched our inclusion and exclusion criteria. Information such as study characteristics, genetic polymorphisms associated with SLE, and organ manifestations was extracted and reported in this review.
RESULTS: In total, 30 polymorphisms in 16 genes were found to be associated with SLE among Asians. All included polymorphisms also reported associations with various SLE clinical features. The association of rs1234315 in TNFSF4 linking to SLE susceptibility (P=4.17x10-17 OR=1.45 95% CI=1.34-1.59) and musculoskeletal manifestation (P=3.35x10-9, OR=1.37, 95%CI= 1.23-1.51) might be the most potential biomarkers to differentiate SLE between Asian and other populations. In fact, these associated genetic variants were found in loci that were implicated in immune systems, signal transduction, gene expression that play important roles in SLE pathogenesis.
DISCUSSIONS AND CONCLUSIONS: This review summarized the potential correlation between 30 genetic polymorphisms associated with SLE and its clinical manifestations among Asians. More efforts in dissecting the functional implications and linkage disequilibrium of associated variants may be required to validate these findings.
MATERIALS AND METHODS: MicroRNA software predicted that miR21 targets VCL while miR29a targets CX3CL1. Twenty benign prostatic hyperplasia (BPH) and 16 high grade CaP formalinfixed paraffin embedded (FFPE) specimens were analysed. From the bone scan results, high grade CaP samples were further classified into CaP with no BM and CaP with BM. Transient transfection with respective microRNA inhibitors was done in both RWPE1 (normal) and PC3 cell lines. QPCR was performed in all FFPE samples and transfected cell lines to measure VCL and CX3CL1 levels.
RESULTS: QPCR confirmed that VCL messenger RNA (mRNA) was significantly down regulated while CX3CL1 was upregulated in all FFPE specimens. Transient transfection with microRNA inhibitors in PC3 cells followed by qPCR of the targeted genes showed that VCL mRNA was significantly up regulated while CX3CL1 mRNA was significantly downregulated compared to the RWPE1 case.
CONCLUSIONS: The downregulation of VCL in FFPE specimens is most likely regulated by miR21 based on the in vitro evidence but the exact mechanism of how miR21 can regulate VCL is unclear. Upregulated in CaP, CX3CL1 was found not regulated by miR29a. More microRNA screening is required to understand the regulation of this chemokine in CaP with bone metastasis. Understanding miRNAmRNA interactions may provide additional knowledge for individualized study of cancers.
METHODS: A total of 160 serum samples (Discovery, n = 60 and Validation, n = 100) of obese and lean individuals with stable Body Mass Index (BMI) values were retrieved from The Malaysian Cohort biobank. Metabolic profiles were obtained using LC-MS/Q-TOF in dual-polarity mode. Metabolites were identified using a molecular feature and chemical formula algorithm, followed by a differential analysis using MetaboAnalyst 5.0. Validation of potential metabolites was conducted by assessing their presence through collision-induced dissociation (CID) using a targeted tandem MS approach.
RESULTS: A total of 85 significantly differentially expressed metabolites (p-value <0.05; -1.5 < FC > 1.5) were identified between the lean and the obese individuals, with the lipid class being the most prominent. A stepwise logistic regression revealed three metabolites associated with increased risk of obesity (14-methylheptadecanoic acid, 4'-apo-beta,psi-caroten-4'al and 6E,9E-octadecadienoic acid), and three with lower risk of obesity (19:0(11Me), 7,8-Dihydro-3b,6a-dihydroxy-alpha-ionol 9-[apiosyl-(1->6)-glucoside] and 4Z-Decenyl acetate). The model exhibited outstanding performance with an AUC value of 0.95. The predictive model underwent evaluation across four machine learning algorithms consistently demonstrated the highest predictive accuracy of 0.821, aligning with the findings from the classical logistic regression statistical model. Notably, the presence of 4'-apo-beta,psi-caroten-4'-al showed a statistically significant difference between the lean and obese individuals among the metabolites included in the model.
CONCLUSIONS: Our findings highlight the significance of lipids in obesity-related metabolic alterations, providing insights into the pathophysiological mechanisms contributing to obesity. This underscores their potential as biomarkers for metabolic dysregulation associated with obesity.
AIMS: The aim of this study was to analyze the mutations in genes involved in CRC including MLH1, MSH2, KRAS, and APC genes.
METHODS: A total of 76 patients were recruited. We used the polymerase chain reaction-denaturing high-performance liquid chromatography for the detection of mutations in the mismatch repair (MMR) and APC genes and the PCR single-strand conformation polymorphism for screening of the KRAS gene mutations.
RESULTS: We identified 17 types of missense mutations in 38 out of 76 patients in our patients. Nine mutations were identified in the APC gene, five mutations were detected in the KRAS gene, and two mutations were identified in the MSH2 gene. Only one mutation was identified in MLH1. Out of these 17 mutations, eight mutations (47 %) were predicted to be pathogenic. Seven patients were identified with multiple mutations (3: MSH2 and KRAS, 1: KRAS and APC, 1: MLH1 and APC, 2: APC and APC).
CONCLUSIONS: We have established the PCR-DHPLC and PCR-SSCP for screening of mutations in CRC patients. This study has given a snapshot of the spectrum of mutations in the four genes that were analyzed. Mutation screening in patients and their family members will help in the early detection of CRC and hence will reduce mortality due to CRC.