Interleukins (ILs), key cytokine family of inflammatory response, are closely associated with kidney function. However, the causal effect of various ILs on kidney function needs further investigation. Here we show two-sample summary-level Mendelian randomization (MR) analysis that examined the causality between serum IL levels and kidney function. Genetic variants with strong association with serum IL levels were obtained from a previous genome-wide association study meta-analysis. Summary-level data for estimated glomerular filtration rate (eGFR) were obtained from CKDGen database. As a main MR analysis, multiplicative random-effects inverse-variance weighted method was performed. Pleiotropy-robust MR analysis, including MR-Egger with bootstrapped error and weighted median methods, were also implemented. We tested the causal estimates from nine ILs on eGFR traits. Among the results, higher genetically predicted serum IL-1 receptor antagonist level was significantly associated with higher eGFR values in the meta-analysis of CKDGen and the UK Biobank data. In addition, the result was consistent towards eGFR decline phenotype of the outcome database. Otherwise, nonsignificant association was identified between other genetically predicted ILs and eGFR outcome. These findings support the clinical importance of IL-1 receptor antagonist-associated pathway in relation to kidney function in the general individuals, particularly highlighting the importance of IL-1 receptor antagonist.

Background Interleukins (ILs), key cytokine family of inflammatory response, are closely associated with kidney function. However, the causal effect of various ILs on kidney function needs further investigation. Methods We performed two-sample summary-level mendelian randomization (MR) analysis. Genetic variants with strong association with serum IL levels were obtained from a previous genome-wide association study meta-analysis. Summary-level data for eGFR were obtained from CKDGen database. A replication analysis was performed in the independent UK Biobank data. As a main MR analysis, multiplicative random-effect inverse-variance weighed method was performed. Pleiotropy-robust MR analysis, including MR-Egger with bootstrapped error and weighed-median methods, were also implemented. Results We tested the causal estimates from nine ILs on eGFR traits. Among the results, higher genetically predicted serum IL-1ra level was significantly associated with higher eGFR values, both in the CKDGen and the UK Biobank data. In addition, the result was consistent towards eGFR decline phenotype of the outcome database. Otherwise, nonsignificant association was identified between other genetically predicted ILs and eGFR outcome. Conclusions These findings support the clinical importance of IL-1 associated pathway in relation to kidney function in the general individuals, particularly highlighting the importance of IL-1ra.

Background: Glomerular diseases encompass a group of kidney diseases that may share common gene expression pathways. We aimed to analyze glomerular-specific gene expression profiles across various glomerular diseases. Methods: We performed spatial transcriptomic profiling using formalin-fixed paraffin-embedded kidney biopsy specimens of controls and patients with five types of glomerular diseases using the GeoMx Digital Spatial Profiler. We identified common differentially expressed genes (DEGs) across glomerular diseases and performed Gene Ontology (GO) annotation by using the ToppGene suite. Results: A total of 35 DEGs were consistently downregulated in glomeruli across the disease compared to the control, while none of the DEGs were consistently upregulated. Twelve of 35 downregulated DEGs, including the two hub genes FOS and JUN, were annotated with molecular function GO terms related to DNA-binding transcription factor activity. Other notable DEGs consistently downregulated and annotated in the pathway analysis included NR4A3, KLF9, EGR1, and ATF3. The annotated biological process GO terms included response to lipid-related (17/35 DEGs), response to steroid hormone (12/35 DEGs), or cell cycle regulation (10/35 DEGs). Conclusions: Identifying common DEGs by spatial transcriptomic analysis provides insights into the underlying molecular mechanisms of glomerular diseases and may lead to novel assessment or therapeutic strategies.

Introduction:C3 glomerulopathy (C3G) is a rare but clinically significant glomerulopathy. However, little is known about its transcriptomic profile. We investigated the substructure-specific gene expression profile of C3G using the recently introduced spatial transcriptomics technology.Methods:We performed spatial transcriptomic profiling using GeoMx Digital Spatial Profiler with formalin-fixed paraffin-embedded kidney biopsy specimens of three C3G cases and seven controls from donor kidney biopsy. Additionally, 41 samples of other glomerulonephritis, including focal segmental glomerulosclerosis, membranous nephropathy, and minimal change disease, were included as disease controls. Gene expression levels were compared by DESeq2 method to identify differentially expressed genes (DEGs). We performed gene ontology (GO) annotation through the ToppGene suite and mapped interactions among the DEGs using the STRING database.Results:We identified 229 and 157 highly expressed DEGs in the glomeruli of C3G compared to those of donor and disease controls, respectively, with consistently highest fold changes in POSTN, COL1A2, and IFI44L. Protease binding, structural molecule activity, and extracellular matrix structural constituent were among the top enriched GO terms in the glomeruli of C3G, with consistent features seen in the network analysis. In contrast, no significant GO enrichment was found among the 563 and 347 lowly expressed DEGs in the glomeruli of C3G compared to the controls. The tubulointerstitial transcriptomic profiles of C3G were similar to those of the controls.Conclusion:In the glomerulus of C3G, genes related to the extracellular matrix and interferon activity were the most upregulated. Significant disease-specific transcriptomic alterations in C3G provide potential insights into the pathophysiology.