End-stage renal disease is different from chronic kidney disease in upregulating ROS-modulated proinflammatory secretome in PBMCs - A novel multiple-hit model for disease progression

Abstract

Background: The molecular mechanisms underlying chronic kidney disease (CKD) transition to end-stage renal disease (ESRD) and CKD acceleration of cardiovascular and other tissue inflammations remain poorly determined.

Methods: We conducted a comprehensive data analyses on 7 microarray datasets in peripheral blood mononuclear cells (PBMCs) from patients with CKD and ESRD from NCBI-GEO databases, where we examined the expressions of 2641 secretome genes (SG).

Results: 1) 86.7% middle class (molecular weight >500 Daltons) uremic toxins (UTs) were encoded by SGs; 2) Upregulation of SGs in PBMCs in patients with ESRD (121 SGs) were significantly higher than that of CKD (44 SGs); 3) Transcriptomic analyses of PBMC secretome had advantages to identify more comprehensive secretome than conventional secretomic analyses; 4) ESRD-induced SGs had strong proinflammatory pathways; 5) Proinflammatory cytokines-based UTs such as IL-1β and IL-18 promoted ESRD modulation of SGs; 6) ESRD-upregulated co-stimulation receptors CD48 and CD58 increased secretomic upregulation in the PBMCs, which were magnified enormously in tissues; 7) M1-, and M2-macrophage polarization signals contributed to ESRD- and CKD-upregulated SGs; 8) ESRD- and CKD-upregulated SGs contained senescence-promoting regulators by upregulating proinflammatory IGFBP7 and downregulating anti-inflammatory TGF-β1 and telomere stabilizer SERPINE1/PAI-1; 9) ROS pathways played bigger roles in mediating ESRD-upregulated SGs (11.6%) than that in CKD-upregulated SGs (6.8%), and half of ESRD-upregulated SGs were ROS-independent.

Conclusions: Our analysis suggests novel secretomic upregulation in PBMCs of patients with CKD and ESRD, act synergistically with uremic toxins, to promote inflammation and potential disease progression. Our findings have provided novel insights on PBMC secretome upregulation to promote disease progression and may lead to the identification of new therapeutic targets for novel regimens for CKD, ESRD and their accelerated cardiovascular disease, other inflammations and cancers. (Total words: 279).

Keywords: (CKD); (ESRD); (ROS); Chronic kidney disease; End-stage renal disease; PBMC secretome; Reactive oxygen species; Trained immunity.

Fig. 1

Venn diagram analysis of the secretomic upregulation and downregulation in the PBMCs from patients with CKD and ESRD. This secretomic regulation can be broken into six categories. (Gene lists for each category are listed in Supplement Table 4.)

Fig. 2a

Top 10 pathways of upregulated and downregulated SGs in CKD from IPA. These pathways were highly diversified in signaling pathways and were not classified into any signaling pathways in a statistically significant manner (cutoff: P value < 0.05, |z-score|>2). (Lists of all pathways associated with these up- and downregulated SGs in CKD via IPA are listed in Supplement Table 5.)

Fig. 2b

22 SGs out of total 121 (18.2%) upregulated SGs in the PBMCs from patients with ESRD were classified in five active pathways according to IPA core analysis (cutoff: |z-score|>2). The other 99 SGs (81.8%) were in a diversified manner similar to that in CKD. (Lists for all pathways associated with these up- and downregulated SGs in ESRD via IPA are listed in Supplement Table 5.)

Fig. 2c

The Venn Diagram Analysis of the five signaling pathways specified in Fig. 2B. Interleukin 1 receptor-associated kinase 3 (IRAK3) is involved in two pathways (IL-8 signaling and Neuroinflammation Signaling Pathway). C-X-C Motif Chemokine Ligand 8 (CXCL8) is involved in three pathways (IL-8 Signaling, Cardiac Hypertrophy and Neuroinflammation Signaling Pathway). (Gene list for these five pathways associated with these up- and downregulated SGs in ESRD via IPA are listed in Supplement Table 6.)

Fig. 2d

A total of 113 active pathways were identified in ESRD down-regulated SGs according to IPA (cutoff: |z-score|>2). The top 10 active pathways are shown (top). Only six active pathways (5.31%) were positively activated by downregulated SGs in ESRD (bottom), including SPINK1 Pancreatic Cancer Pathway, Inhibition of Matrix Metalloproteases, PPAR Signaling, Apelin Cardiac Fibroblast Signaling Pathway, Antioxidant Action of Vitamin C, and PTEN Signaling. The rest of the pathways were downregulated. (Gene list for these 113 pathways associated with these up- and downregulated SGs in ESRD via IPA are listed in Supplement Table 7.)

Fig. 2f

The Venn Diagram of transcript factors analysis in Table 3B. E2F1 was shared by CKD-upregulated SGs and ESRD-downregulated SGs in ESRD. In addition, nuclear respiratory factor 2 (Nrf2), a key transcription factor in Redox Oxygen Species (ROS), was shared in two groups of SGs, CKD-downregulated SGs and ESRD-downregulated SGs, indicating these two transcription factors may serve as an important inhibitor of disease progression.

Fig. 3a

The Venn Diagram results on the three groups such as 35 UT genes (encode total 30 UTs), 44 CKD upregulated SGs and 121 ESRD-upregulated SGs showed that 1) UTs have no overlaps with CKD-upregulated SGs; 2) UTs have two toxins (CFD, and RETN) overlapped with ESRD-upregulated SGs; 3) ESRD-upregulated SGs have four SGs (ADAM9, C3, HSP90B1, and S100A12) overlapped with CKD-upregulated SGs. In addition, one signaling pathway “Role of Cytokines in Mediating Communication between Immune Cells” was shared by the top 10 pathways associated with UTs and the five active pathways upregulated by SGs in ESRD.

Fig. 3b

The ClueGo v2.5.4 from Cytoscape v3.7.2 used as a secondary software to confirm a close functional relationship between UT-encoded genes and up-regulated SGs in ESRD. (Group-specific and connective function are listed in supplement Table 8.)

Fig. 3c

The Venn Diagram Analysis results showed that 1) all of the four cytokines (IL24, IL36RN, PF4, EDA) downregulated in CKD are overlapped that downregulated in ESRD; 2) the one cytokine upregulated in CKD is overlapped with that downregulated in ESRD; and 3) six cytokines upregulated in ESRD are not overlapped with the other three groups.

Fig. 3d

Novel mechanism I. Proinflammatory cytokines (primary) play significant roles in combination with uremic toxins and other mechanisms in upregulating SGs (secondary), promoting the pathogenesis of ESRD and inflammations. We used the proinflammatory cytokines as prototypic secretomic proteins to demonstrate the mutual promotion and modulation among the secretomic proteins as the role-switching of “primary” and “secondary” cytokines during ESRD.

Fig. 4a

New RNA-seq (RNA-sequencing) data from Human Protein Atlas (https://www.proteinatlas.org) indicated that CD48 and CD58 are expressed in every one of 27 tissue examined; and that their ligand (CD2) is also expressed in every one of 27 tissues examined, which are correlated with the CD2 protein expression data collected in the GeneCards database shown above.

Fig. 4b

CD2 protein can be highly enriched in cytotoxic T-lymphocyte, natural killer cell, bone marrow stromal cell, helper T-lymphocyte, B lymphocyte and monocyte according to Proteomics Database (https://www.proteomicsdb.org/).

Fig. 4c

Novel mechanism. Co-stimulation receptors CD48 and CD58 can initiate signaling cascades via their interactions with their ligand CD2 to amplify the expression changes of SGs upregulated in the PBMCs in patients with ESRD.

Fig. 5

Novel mechanism. Macrophage polarization pathways participate CKD-, and ESRD-upregulated secretomic changes in the PBMCs in patients with CKD and ESRD; M1-, and M2-polarization signaling pathways involving in upregulating SGs are diversified.

Fig. 6

Novel mechanism. Uremic toxins-promoted secretome accelerated renal disease and inflammation by inducing cellular senescence and senescence-associated secretory phenotype (SASP) according to p53 signaling and insulin growth factor (IGF) related pathways (PI3K/Akt) in ESRD.

Fig. 7a

All of the 2641 SGs were testified in NOX2 and Nrf2 knockout GEO datasets (GSE7810, GSE100671) and total of 1030 SGs (39.0% of all SGs) were found in these two datasets (cutoff: P value < 0.05). We classified these 1030 SGs into 4 categories: 1) ROS-suppressed SGs, 2) ROS-promoted SGs, 3) ROS-uncertain SGs, and 4) ROS-independent SGs by analyzing expression changes in NOX2 and Nrf2 knockout GEO.

Fig. 7b

Novel Mechanism: Reactive oxygen species (ROS)-related mechanisms, regulated by ROS generating enzyme NADPH oxidase 2 (NOX2) and antioxidant transcription factor Nrf2 pathways, modulated the secretomic changes during kidney dysfunction. The modulation was closely related to the balance of ROS and antioxidants and the imbalance contributes to the alteration of ROS-dependent SGs which could promote disease progression.

Fig. 8

A: Our new finding suggested a new model that not only passive accumulation of uremic toxins, but also other active upregulation of secretome during ESRD contributes to disease progression through proinflammatory and profibrotic pathways and molecules. B: This active accumulation modulated by both ROS-dependent and –independent pathways could promote systemic inflammation and fibrosis to accelerate disease progression. Uremic toxin-related cytokine switching, macrophage polarization and co-signaling by the interaction of CD48 and CD58 with CD2 were important pathways associated with ROS-independent SGs. Of note, there has been researches identified those pathways could modulate and interact with ROS-dependent pathway. C: The active accumulation of secretomic changes are the key mediators when combined with and modulated by other risk factors as multiple hits in the transition from CKD to ESRD. D: Ranking of all the mechanisms in our research by the numbers of SGs upregulated in each entry suggested that ROS serves as an important complementary role for prior knowledge of CKD progression, multiple-hit model of CKD progression.