Background: Systemic lupus erythematosus (SLE) is a common autoimmune disease, and its pathogenesis remains unclear. The alteration of genetic materials is believed to play a role in SLE development. This study evaluated the association between the genetic variants of microRNA‐21 (miR‐21) and microRNA‐155 (miR‐155) and SLE.Methods: The SNaPshot genotyping method was used to detect the genotypes of selected SNPs in patients and controls. The expression of miR‐21 and miR‐155 was analyzed using reverse transcription‐quantitative polymerase chain reaction (RT‐qPCR). The functional annotation and the biological effects of SNPs were assessed by HaploReg V4.1 and Regulome DB V2.0 software. The Hardy–Weinberg equilibrium test was used to gather statistics, and odds ratios (ORs) and 95% confidence intervals (CIs) were evaluated by logistic regression.Results: The distribution difference of TA genotype in rs767649 was observed (TA vs. T/T: OR = 0.68, 95%CI, 0.48–0.95, p = 0.026). There was a significant difference in the T/A + A/A (T/A + A/A vs. T/T: OR = 0.68, 95%CI, 0.49–0.94, p = 0.020). A significant difference in T allele distribution was found in the depressed complement of SLE (T vs. A: OR = 0.67, 95%CI, 0.47–0.95, p = 0.026). There were significant differences in genetic variants of rs13137 between the positive and the negative SSB antibodies (Anti‐SSB) (T vs. A: OR = 0.67, 95%CI, 0.47–0.95, p = 0.026; T/A + T/T vs. AA: OR = 2.23, 1.18–4.49, p = 0.013). The expression levels of miR‐21 and miR‐155 were significantly higher in patients than in controls (p < 0.001).Conclusions: This study provides novel insight that genetic variants of rs767649 and rs13137 are associated with susceptibility to SLE.

Background: Maternal obesity significantly influences fetal development and health later in life; however, the molecular mechanisms behind it remain unclear. This study aims to investigate signature genes related to maternal obesity and fetal programming based on a genomic-wide transcriptional placental study using a combination of different bioinformatics tools.Methods: The dataset (GSE128381) was obtained from Gene Expression Omnibus (GEO). The data of 100 normal body mass index (BMI) and 27 obese mothers were included in the analysis. Differentially expressed genes (DEGs) were evaluated by limma package. Thereafter, functional enrichment analysis was implemented. Then, weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) analysis were used to further screening of signature genes. Simple linear regression analysis was used to assess the correlation between signature genes and newborn birth weight. Gene set enrichment analysis (GSEA) was implemented to study signaling pathways related to signature genes. The expression of the signature genes was also explored in 48 overweight mothers in the same dataset.Results: A total of 167 DEGs were obtained, of which 122 were up-regulated while 45 were down-regulated. The dataset was then clustered into 11 modules by WGCNA, and the MEbrown was found as the most significant module related to maternal obesity and fetal programming (cor = 0.2, p = 0.03). The LASSO analysis showed that PTX3, NCF2, HOXB5, ABCA6, and C1orf162 are signature genes related to maternal obesity and fetal programming, which were increased in the placenta of obese mothers compared to those with normal BMI. The area under the curve (AUC) of the signature genes in the receiver operating characteristic curve (ROC) was 0.709, 0.660, 0.674, 0.667, and 0.717, respectively. Simple linear regression analysis showed that HOXB5 was associated with newborn birth weight. GSEA analysis revealed that these signature genes positively participate in various signaling pathways/functions in the placenta.Conclusion: PTX3, NCF2, HOXB5, ABCA6, and C1orf162 are novel signature genes related to maternal obesity and fetal programming, of which HOXB5 is implicated in newborn birth weight.