Association of ITGAX and ITGAM gene polymorphisms with susceptibility to IgA nephropathy

Glomerular transcriptomics predicts long term outcome and identifies therapeutic strategies for patients with assumed benign IgA nephropathy

Some patients diagnosed with benign IgA nephropathy (IgAN) develop a progressive clinical course, not predictable by known clinical or histopathological parameters. To assess if gene expression can differentiate between progressors and non-progressors with assumed benign IgAN, we tested microdissected glomeruli from archival kidney biopsy sections from adult patients with stable clinical remission (21 non-progressors) or from 15 patients that had undergone clinical progression within a 25-year time frame. Based on 1 240 differentially expressed genes from patients with suitable sequencing results, we identified eight IgAN progressor and nine non-progressor genes using a two-component classifier. These genes, including APOL5 and ZXDC, predicted disease progression with 88% accuracy, 75% sensitivity and 100% specificity on average 21.6 years before progressive disease was clinically documented. APOL lipoproteins are associated with inflammation, autophagy and kidney disease while ZXDC is a zinc-finger transcription factor modulating adaptive immunity. Ten genes from our transcriptomics data overlapped with an external genome wide association study dataset, although the gene set enrichment test was not statistically significant. We also identified 45 drug targets in the DrugBank database, including angiotensinogen, a target of sparsentan (dual antagonist of the endothelin type A receptor and the angiotensin II type 1 receptor) currently investigated for IgAN treatment. Two validation cohorts were used for substantiating key results, one by immunohistochemistry and the other by nCounter technology. Thus, glomerular mRNA sequencing from diagnostic kidney biopsies from patients with assumed benign IgAN can differentiate between future progressors and non-progressors at the time of diagnosis.

Candidate Genes for IgA Nephropathy in Pediatric Patients: Exome-Wide Association Study

IgA nephropathy (IgAN) is an autoimmune disorder which is believed to be non-monogenic. We performed an exome-wide association study of 70 children with IgAN and 637 healthy donors. The HLA allele frequencies were compared between the patients and healthy donors from the bone marrow registry of the Pirogov University. We tested 78,020 gene markers for association and performed functional enrichment analysis and transcription factor binding preference detection. We identified 333 genetic variants, employing three inheritance models. The most significant association with the disorder was observed for rs143409664 (PRAG1) in the case of the additive and dominant models (PBONF = 1.808 × 10-15 and PBONF = 1.654 × 10-15, respectively), and for rs13028230 (UBR3) in the case of the recessive model (PBONF = 1.545 × 10-9). Enrichment analysis indicated the strongly overrepresented "immune system" and "kidney development" terms. The HLA-DQA1*01:01:01G allele (p = 0.0076; OR, 2.021 [95% CI, 1.322-3.048]) was significantly the most frequent among IgAN patients. Here, we characterized, for the first time, the genetic background of Russian IgAN patients, identifying the risk alleles typical of the population. The most important signals were detected in previously undescribed loci.

Current Understanding of Complement Proteins as Therapeutic Targets for the Treatment of Immunoglobulin A Nephropathy

Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis worldwide and a frequent cause of kidney failure. Currently, the diagnosis necessitates a kidney biopsy, with routine immunofluorescence microscopy revealing IgA as the dominant or co-dominant immunoglobulin in the glomerular immuno-deposits, often with IgG and sometimes IgM or both. Complement protein C3 is observed in most cases. IgAN leads to kidney failure in 20-40% of patients within 20 years of diagnosis and reduces average life expectancy by about 10 years. There is increasing clinical, biochemical, and genetic evidence that the complement system plays a paramount role in the pathogenesis of IgAN. The presence of C3 in the kidney immuno-deposits differentiates the diagnosis of IgAN from subclinical glomerular mesangial IgA deposition. Markers of complement activation via the lectin and alternative pathways in kidney-biopsy specimens are associated with disease activity and are predictive of poor outcome. Levels of select complement proteins in the circulation have also been assessed in patients with IgAN and found to be of prognostic value. Ongoing genetic studies have identified at least 30 loci associated with IgAN. Genes within some of these loci encode complement-system regulating proteins that can interact with immune complexes. The growing appreciation for the central role of complement components in IgAN pathogenesis highlighted these pathways as potential treatment targets and sparked great interest in pharmacological agents targeting the complement cascade for the treatment of IgAN, as evidenced by the plethora of ongoing clinical trials.

The genetic polymorphisms of immune-related genes contribute to the susceptibility and survival of lymphoma

BACKGROUND

Though immunological abnormalities have been proven involved in the pathogenesis of lymphoma, the underlying mechanism remains unclear.

METHODS

We investigated 25 single nucleotide polymorphisms (SNPs) of 21 immune-related genes and explored their roles in lymphoma. The genotyping assay of the selected SNPs was used by the Massarray platform. Logistic regression and Cox proportional hazards models were used to analyze the associations of SNPs and the susceptibility of lymphoma or clinical characteristics of lymphoma patients. In addition, Least Absolute Shrinkage and Selection Operator regression was used to further analyze the relationships with the survival of lymphoma patients and candidate SNPs, and the significant difference between genotypes was verified by the expression of RNA.

RESULTS

By comparing 245 lymphoma patients with 213 healthy controls, we found eight important SNPs related to the susceptibility of lymphoma, which were involved in JAK-STAT, NF-κB and other functional pathways. We further analyzed the relationships between SNPs and clinical characteristics. Our results showed that both IL6R (rs2228145) and STAT5B (rs6503691) significantly contributed to the Ann Arbor stages of lymphoma. And the STAT3 (rs744166), IL2 (rs2069762), IL10 (rs1800871), and PARP1 (rs907187) manifested a significant relationship with the peripheral blood counts in lymphoma patients. More importantly, the IFNG (rs2069718) and IL12A (rs6887695) were associated with the overall survival (OS) of lymphoma patients remarkably, and the adverse effects of GC genotypes could not be offset by Bonferroni correction for multiple comparison in rs6887695 especially. Moreover, we determined that the mRNA expression levels of IFNG and IL12A were significantly decreased in patients with shorter-OS genotypes.

CONCLUSIONS

We used multiple methods of analysis to predict the correlations between lymphoma susceptibility, clinical characteristics or OS with SNPs. Our findings reveal that immune-related genetic polymorphisms contribute to the prognosis and treatment of lymphoma, which may serve as promising predictive targets.

Transcriptomic analysis reveals genetic factors regulating early steroid-induced osteonecrosis of the femoral head

The present study aimed to explore the signaling pathways involved in development of early steroid-induced osteonecrosis of the femoral head (SONFH) and identify diagnostic biomarkers regulating peripheral blood in SONFH patients. We downloaded transcriptome data and identified differentially expressed genes (DEGs) using the R software. We used ClusterProfiler to perform enrichment analysis of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes, and analyzed protein-protein interactions using the STRING database. Network X was used to visualize the networks in Python. A total of 584 DEGs were identified, of which 294 and 290 were upregulated and downregulated, respectively. Enrichment analysis showed that the DEGs were mainly involved in red blood cell differentiation, cell protein catabolism, gas transportation, activation of myeloid leukocytes, phagocytosis, and inflammatory response. Pathway analysis revealed that these DEGs were involved in regulation of mitophagy-animal, human T-cell leukemia virus-1 infection, Forkhead box O, phagocytosis, osteoclast differentiation, and cytokine-cytokine receptor interaction. Quantitative real-time polymerase chain reaction results were consistent with findings from protein-protein interaction network analysis. Several genes, including peroxiredoxin 2, haptoglobin, matrix metallopeptidase 8, formyl peptide receptor 2, and integrin subunit alpha X, promote SONFH occurrence by regulating the redox, inflammatory response, and osteoblast and osteoclast structure and function pathways. They may be important targets for designing approaches for early diagnosis and treatment of SONFH.

Changes in Protein Structural Motifs upon Post-Translational Modification in Kidney Cancer

Post-translational modification (PTM) leads to conformational changes in protein structure, modulates the biological function of proteins, and, consequently, changes the signature of metabolic transformations and the immune response in the body. Common PTMs are reversible and serve as a mechanism for modulating metabolic trans-formations in cells. It is likely that dysregulation of post-translational cellular signaling leads to abnormal proliferation and oncogenesis. We examined protein PTMs in the blood samples from patients with kidney cancer. Conformational changes in proteins after modification were analyzed. The proteins were analyzed using ultra-high resolution HPLC-MS/MS and structural analysis was performed with the AMBER and GROMACS software packages. Fifteen proteins containing PTMs were identified in blood samples from patients with kidney cancer. For proteins with PDB structures, a comparative analysis of the structural changes accompanying the modifications was performed. Results revealed that PTMs are localized in stable and compact space protein globule motifs that are exposed to a solvent. The phenomenon of modification is accompanied, as a rule, by an increase in the area available for the solvent of the modified amino acid residue and its active environment.

Irf1- and Egr1-activated transcription plays a key role in macrophage polarization: A multiomics sequencing study with partial validation

BACKGROUND

Macrophage polarization has a causal role in the pathogenesis and resolution of various clinical diseases. DNA-binding transcription factors (TFs) have been identified as essential factors during gene transcription. Better insight into the TFs that regulate macrophage polarization could provide novel therapeutic targets.

METHODS

IFN-γ (50 ng/mL) or IL4 (20 ng/mL) was utilized to stimulate bone marrow-derived macrophages from mice for 24 h for M1- and M2-polarized macrophage model construction, respectively. First, ATAC-seq (Assay for Targeting Accessible-Chromatin with high throughout sequencing) and motif analysis were conducted to identify potential transcription factors (TFs) involved in M1 and M2 macrophage polarization. Second, essential TFs were identified through RNA-seq, after which, their expression was compared between M0-polarized and M1/M2-polarized macrophages. Furthermore, a multiomic analysis of RNA-seq (siRNA knock down of the identified TFs), ChIP-seq and ATAC-seq was utilized to explore the TF-regulated molecular network. GO and KEGG analyses were used to expound the main functions of the TF-regulated molecular network. Finally, the top 5 TF-regulated genes were validated through flow cytometry, ELISA and qPCR. The cut-off values for high-throughput sequencing and qPCR were FDR < 0.05 and P < 0.05, respectively.

RESULTS

Compared with M0 macrophages, 10,771 and 4,848 peaks were identified by ATAC-seq during M1 and M2 macrophage polarization, respectively (FDR < 0.05). Fifty and 62 TF binding motifs were identified for the TFs that participate in M1 and M2 macrophage polarization, respectively. The most significantly highly expressed TFs in M1 and M2 macrophages were identified by RNA-seq as Irf1 and Egr1, with LogFC values of 3.2 and 2.8, respectively. Multiomic analyses further found that Irf1 regulated the transcription of 90 genes and that Egr1 regulated the transcription of 116 genes. The Irf1-regulated molecular network played a key role in the inflammatory response and viral defence of M1 macrophages, and 116 Egr1-regulated genes included anti-inflammatory and cell proliferation genes. Validation experiments indicated that IFN-γ-induced Gbp5, Nos2, CD86, Cxcl10 and Cxcl5 expression was significantly downregulated in siIrf1-BMDMs, and IL4-induced Itgax, Nipal1, Bhlhe40, CD206 and Ffar4 expression was significantly downregulated in siEgr1-BMDMs (P < 0.05).

CONCLUSIONS

Through multiomic analyses of epigenetic sequencing and RNA-seq with partial validation, the current study found that Irf1- and Egr1-induced transcription plays key roles in M1 and M2 macrophage polarization, respectively.