DNA repair and systemic lupus erythematosus

Meas, Rithy; Burak, M.J.; Sweasy, Joann B.

doi:10.1016/j.dnarep.2017.06.020

Cited by 32 publications

(23 citation statements)

References 111 publications

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“…During the past decade, significant progress has been made to elucidate a role for aberrant DNA repair in the development of lupus. Recent evidence indicates that patients with SLE have higher levels of DNA damage than normal subjects, and that polymorphisms in genes involved in the preservation of the genomic stability increase the risk for SLE (32)(33)(34). Furthermore, experience from animal models reinforces the importance of defective repair in the development of SLElike disease (35), suggesting that therapeutic potential of targeting DNA damage and DNA repair responses in SLE pathogenesis (36,37).…”

Section: Discussionmentioning

confidence: 99%

Oxidative DNA Damage Accelerates Skin Inflammation in Pristane-Induced Lupus Model

et al. 2020

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Systemic Lupus Erythematosus (SLE) is a chronic inflammatory autoimmune disease in which type I interferons (IFN) play a key role. The IFN response can be triggered when oxidized DNA engages the cytosolic DNA sensing platform cGAS-STING, but the repair mechanisms that modulate this process and govern disease progression are unclear. To gain insight into this biology, we interrogated the role of oxyguanine glycosylase 1 (OGG1), which repairs oxidized guanine 8-Oxo-2 ′-deoxyguanosine (8-OH-dG), in the pristane-induced mouse model of SLE. Ogg1 −/− mice showed increased influx of Ly6C hi monocytes into the peritoneal cavity and enhanced IFN-driven gene expression in response to short-term exposure to pristane. Loss of Ogg1 was associated with increased auto-antibodies (anti-dsDNA and anti-RNP), higher total IgG, and expression of interferon stimulated genes (ISG) to longer exposure to pristane, accompanied by aggravated skin pathology such as hair loss, thicker epidermis, and increased deposition of IgG in skin lesions. Supporting a role for type I IFNs in this model, skin lesions of Ogg1 −/− mice had significantly higher expression of type I IFN genes (Isg15, Irf9, and Ifnb). In keeping with loss of Ogg1 resulting in dysregulated IFN responses, enhanced basal and cGAMP-dependent Ifnb expression was observed in BMDMs from Ogg1 −/− mice. Use of the STING inhibitor, H151, reduced both basal and cGAMP-driven increases, indicating that OGG1 regulates Ifnb expression through the cGAS-STING pathway. Finally, in support for a role for OGG1 in the pathology of cutaneous disease, reduced OGG1 expression in monocytes associated with skin involvement in SLE patients and the expression of OGG1 was significantly lower in lesional skin compared with non-lesional skin in patients with Discoid Lupus. Taken together, these data support an important role for OGG1 in protecting against IFN production and SLE skin disease.

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Section: Discussionmentioning

confidence: 99%

Oxidative DNA Damage Accelerates Skin Inflammation in Pristane-Induced Lupus Model

et al. 2020

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“…Called as "the Great Imposter," systemic lupus erythematosus (SLE) is a chronic and complex autoimmune disease with multisystem manifestations [1,2]. The disease prevalence is estimated about 5 million people worldwide, and it occurs mostly before the age of 45 years [3][4][5]. The loss of central and peripheral tolerance to self, as a result of genetic susceptibility or environmental factors, is proposed to be a crucial first step in the SLE development [6,7].…”

Section: Introductionmentioning

confidence: 99%

An integrative Bayesian network approach to highlight key drivers in systemic lupus erythematosus

et al. 2020

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Background: A comprehensive intuition of the systemic lupus erythematosus (SLE), as a complex and multifactorial disease, is a biological challenge. Dealing with this challenge needs employing sophisticated bioinformatics algorithms to discover the unknown aspects. This study aimed to underscore key molecular characteristics of SLE pathogenesis, which may serve as effective targets for therapeutic intervention. Methods: In the present study, the human peripheral blood mononuclear cell (PBMC) microarray datasets (n = 6), generated by three platforms, which included SLE patients (n = 220) and healthy control samples (n = 135) were collected. Across each platform, we integrated the datasets by cross-platform normalization (CPN). Subsequently, through BNrich method, the structures of Bayesian networks (BNs) were extracted from KEGG-indexed SLE, TCR, and BCR signaling pathways; the values of the node (gene) and edge (intergenic relationships) parameters were estimated within each integrated datasets. Parameters with the FDR < 0.05 were considered significant. Finally, a mixture model was performed to decipher the signaling pathway alterations in the SLE patients compared to healthy controls. Results: In the SLE signaling pathway, we identified the dysregulation of several nodes involved in the (1) clearance mechanism (SSB, MACROH2A2, TRIM21, H2AX, and C1Q gene family), (2) autoantigen presentation by MHCII (HLA gene family, CD80, IL10, TNF, and CD86), and (3) end-organ damage (FCGR1A, ELANE, and FCGR2A). As a remarkable finding, we demonstrated significant perturbation in CD80 and CD86 to CD28, CD40LG to CD40, C1QA and C1R to C2, and C1S to C4A edges. Moreover, we not only replicated previous studies regarding alterations of subnetworks involved in TCR and BCR signaling pathways (PI3K/AKT, MAPK, VAV gene family, AP-1 transcription factor) but also distinguished several significant edges between genes (PPP3 to NFATC gene families). Our findings unprecedentedly showed that different parameter values assign to the same node based on the pathway topology (the PIK3CB parameter values were 1.7 in TCR vs − 0.5 in BCR signaling pathway). Conclusions: Applying the BNrich as a hybridized network construction method, we highlight under-appreciated systemic alterations of SLE, TCR, and BCR signaling pathways in SLE. Consequently, having such a systems biology approach opens new insights into the context of multifactorial disorders.

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“…Called as "the Great Imposter", systemic lupus erythematosus (SLE) is a chronic and complex autoimmune disease with multi-system manifestations in which many questions about its etiology remain unanswered [1,2]. The disease prevalence rate estimated about 5 million people worldwide and it occurs mostly before age 45 years [3][4][5]. The loss of central and peripheral tolerance to self is proposed to be a crucial first step in the progress of SLE [6].…”

Section: Introductionmentioning

confidence: 99%

“…In the present study, to construct trained BNs and identify significant nodes and edges in SLE, as a complex autoimmune disease, we (1) integrated peripheral blood mononuclear cells (PBMCs) microarray gene expression by cross-platform normalization [23]; (2) employed SLE, TCR and BCR signaling pathways as underlying structures of BNs;(3) estimated the parameters of BNs by integrated datasets [22,24]; (4) merged the obtained significant parameters of BNs in desired pathways as "meta-analysis" data integration [23]; (5) highlighted signaling pathways alterations involved in the SLE pathogenesis. Finally, we (6) demonstrated that some of the genes and intergenic relationships have a vital role and can be used as effective targets for therapeutic intervention in SLE patients.…”

Section: Introductionmentioning

confidence: 99%

An integrative Bayesian network approach to highlight key drivers in systemic lupus erythematosus

Maleknia

Salehi

Sharifi‐Zarchi

et al. 2020

Preprint

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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.

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DNA repair and systemic lupus erythematosus

Cited by 32 publications

References 111 publications

Oxidative DNA Damage Accelerates Skin Inflammation in Pristane-Induced Lupus Model

Oxidative DNA Damage Accelerates Skin Inflammation in Pristane-Induced Lupus Model

An integrative Bayesian network approach to highlight key drivers in systemic lupus erythematosus

An integrative Bayesian network approach to highlight key drivers in systemic lupus erythematosus

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