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.
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.
METHODS: A case-control study was conducted involving 600 people with type 2 diabetes (300 chronic kidney disease cases, 300 controls) who participated in The Malaysian Cohort project. Retrospective subanalysis was performed on the chronic kidney disease cases to assess chronic kidney disease progression from the recruitment phase. We genotyped 32 single nucleotide polymorphisms using mass spectrometry. The probability of chronic kidney disease and predicted rate of newly detected chronic kidney disease progression were estimated from the significant gene-environment interaction analyses.
RESULTS: Four single nucleotide polymorphisms (eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228) and five environmental factors (age, sex, smoking, waist circumference and HDL) were significantly associated with chronic kidney disease. Gene-environment interaction analyses revealed significant probabilities of chronic kidney disease for sex (PPARGC1A rs8192678), smoking (eNOS rs2070744, PPARGC1A rs8192678 and KCNQ1 rs2237895), waist circumference (eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228) and HDL (eNOS rs2070744 and PPARGC1A rs8192678). Subanalysis indicated that the rate of newly detected chronic kidney disease progression was 133 cases per 1000 person-years (95% CI: 115, 153), with a mean follow-up period of 4.78 (SD 0.73) years. There was a significant predicted rate of newly detected chronic kidney disease progression in gene-environment interactions between KCNQ1 rs2283228 and two environmental factors (sex and BMI).
CONCLUSIONS: Our findings suggest that the gene-environment interactions of eNOS rs2070744, PPARGC1A rs8192678, KCNQ1 rs2237895 and KCNQ1 rs2283228 with specific environmental factors could modify the probability for chronic kidney disease.