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.
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.