Background: To perceive a comprehensive illustration of the systemic lupus erythematosus (SLE), as a complex and multifactorial disease, draw a biological challenge. Dealing with this challenge needs employing sophisticated bioinformatics algorithms to discover the unknown aspects. This study aimed to distinguish key molecular characteristics of SLE pathogenesis, which may serve as effective targets for therapeutic intervention. Methods: In the present study, six gene expression microarray datasets included SLE patients (n=220) and healthy controls (n=135) were collected. We integrated the datasets by cross-platform normalization. Subsequently, through BNrich method, the structures of Bayesian networks (BNs) were extracted from SLE, TCR and BCR signaling pathways and the parameters of BNs were estimated using integrated datasets. Finally, a meta-analysis was performed to distinguish the signaling pathways alterations in the SLE pathogenesis. Results: We identified the most dysregulated genes involved in the clearance mechanism (most inhibition in MACROH2A2 and H4C9, most activation in SNRPD3, MACROH2A1 and RO60). Augmented autoantigens presentation by MHCII (HLA-DQA1, HLA-DOB and HLA-DPB1) and CD80 and CD86 to CD28 biological functions were also observed. The increased expression of FCGR1A, C8G, C7 and C9 genes and decreasing biological functions in edges from C1R and C1S to C2 and from C1R to C4B, all involved in end-organ damage, were detected. On the other hand, many of subnetworks alterations of TCR and BCR reported in previous research (PI3K/AKT, MAPK, AP-1 transcription factor). Conclusions: Overall, the BNrich as a hybridized network construction method, which integrates intergenic relations inferred from signaling pathways and gene expression profiling, can be employed to study complex diseases. Here we applied BNrich and highlighted significant genes and intergenic relationships and systemic alterations in SLE, TCR and BCR signaling pathways.