Identification of Genes Associated with Familial Focal Segmental Glomerulosclerosis Through Transcriptomics and In Silico Analysis, Including RPL27, TUBB6, and PFDN5

Abstract

Focal segmental glomerulosclerosis (FSGS) is a major cause of nephrotic syndrome and often leads to progressive kidney failure. Its varying clinical presentation suggests potential genetic diversity, requiring further molecular investigation. This study aims to elucidate some of the genetic and molecular mechanisms underlying FSGS. The study focuses on the use of bioinformatic analysis of gene expression data to identify genes associated with familial FSGS. A comprehensive in silico analysis was performed using the GSE99340 data set from Gene Expression Omnibus (GEO) comparing gene expression in glomerular and tubulointerstitial tissues from FSGS patients (n = 10) and Minimal Change Disease (MCD) patients (n = 8). These findings were validated using transcriptomics data obtained using RNA sequencing from FSGS (n = 3) and control samples (n = 3) from the UAE. Further validation was conducted using qRT-PCR on an independent FFPE cohort (FSGS, n = 6; MCD, n = 7) and saliva samples (FSGS, n = 3; Control, n = 7) from the UAE. Three genes (TUBB6, RPL27, and PFDN5) showed significant differential expression (p < 0.01) when comparing FSGS and MCD with healthy controls. These genes are associated with cell junction organization and synaptic pathways of the neuron, supporting the link between FSGS and the neural system. These genes can potentially be useful as diagnostic biomarkers for FSGS and to develop new treatment options.

Keywords: Focal segmental glomerulosclerosis (FSGS); Minimal change disease (MCD); genetic; glomerular; tubulointerstitial.

Figure 1

Progression of focal segmented glomerulosclerosis. The image shows the development of focal segmental glomerulosclerosis (FSGS), which initiates with the detachment of specialized glomerular visceral epithelial cells called podocytes from the glomerular basement membrane (GBM). This causes the GBM to protrude outward and adhere to the inner lining of Bowman’s capsule. The inflamed region affected by FSGS is highlighted in dark red. The surrounding healthy kidney tissue is shown in light red. This illustration was generated by biorender.com.

Figure 2

Flow chart of in silico data normalization and filtration.

Figure 3

In silico data for GSEA-enriched pathways. Illustrates the GSEA (a,b) output for datasets C5: ontology and (c,d) C7,: immunologic signature gene sets, comparing FSGS and MCD. In this comparison, FSGS is characterized by its focus on the glomerulus, whereas MCD focuses on the tubulointerstitial, with some inclusion of FSGS patients. The similarity of the tubulointerstitial characteristics in both groups led us to utilize this tissue from both FSGS and MCD for comparison with the glomerular tissue of FSGS. The heat map highlights higher expressions in red, while lower expressions are indicated in green.

Figure 4

Absolute GSEA-enriched pathways. An example of each dataset’s output from the gene set analysis. (a) C5: Ontology and (b) C7: Immunologic signature gene sets, respectively. The heat map highlights higher expressions in red, while lower expressions are indicated in green.

Figure 5

Comparison between in silico and RNA sequencing analyses of FSGS using InteractiVenn. (a) In the C5 dataset, four genes (TGFB2, DNM3, HDAC9, WTIP) were common to both. (b) In the C7 dataset 6 genes (ADARB1, TGFB2, TFAM, ZCCHC24, EIF1, TUBB6) were common to both “http://www.interactivenn.net (accessed on 29 June 2024)”.

Figure 6

Comparative gene expression analysis of FSGS and MCD. The figure compares the expression levels of three genes (RPL27, TUBB6, and PFDN5) in FSGS and MCD tissues. The in silico study examined gene expressions in glomerular and tubulointerstitial regions, revealing that (a) TUBB6 had higher expression in FSGS (glomerular), whereas (b) PFDN5 and (c) RPL27 had lower expression in FSGS (glomerular). The RNA sequencing analysis (d–f), comparing controls to FSGS, demonstrated higher expression levels of all three genes in FSGS patients. GLOM; glomerulus, TUB; tubulointerstitial, FSGS: Focal segmented glomerulosclerosis. p value. * p < 0.05, *** p < 0.01.

Figure 7

TUBB6, PFDN5, and RPL27 gene expression levels in different kidney-specific cells. These data were obtained from primary data submitted to CZ CELLxGENE Discover. Source: “https://cellxgene.cziscience.com/gene-expression (accessed on 13 October 2024)”.

Figure 8

Illustrations of the fold changes in RPL27, TUBB6, and PFDN5 were obtained from RNA sequencing analysis and in silico. (a) Presentation of the corresponding fold change in FSGS target genes from in silico analysis and (b) RNAseq data. p value. * p < 0.05, *** p < 0.01.

Figure 9

Relative fold changes in three significant genes, TUBB6, RPL27, and PFDN5, were obtained from qPCR. The results demonstrate that FSGS and MCD patients show elevated expression of these three genes compared to healthy controls. p value. *** p < 0.01.

Figure 10

WES identified novel mutations in FSGS patients. In a family with FSGS, all patients were found to be heterozygous for (a) a significant mutation in the 5′ UTR of the NFASC gene (c.-184T>C). (b) Additionally, a novel missense mutation was identified in the UBXN2B gene (c.233G>A) and (c) the NUDT14 gene (c.146A>T), along with (d) an intronic mutation in the LAMB1 gene (c.38-28C>A). These mutations were significant in the GSEA analysis.The figure illustrates an Integrated Genomics Viewer (IGV) representation of a heterozygous mutation. The blue color represents the wild-type sequence, whereas the red color indicates the mutant sequence.

Figure 11

Three-generation pedigree of a UAE Family with FSGS. The proband (↙) is the mother (210) of four affected sons (301–304) with FSGS and five healthy daughters (305–309). Three FSGS patients (↗) from this family were included in the RNA-seq analysis. Participants are labeled A–F, with black representing those with FSGS and white for healthy individuals.