Transcriptomic and Proteomic Profiling Provides Insight into Mesangial Cell Function in IgA Nephropathy

Abstract

IgA nephropathy (IgAN), the most common GN worldwide, is characterized by circulating galactose-deficient IgA (gd-IgA) that forms immune complexes. The immune complexes are deposited in the glomerular mesangium, leading to inflammation and loss of renal function, but the complete pathophysiology of the disease is not understood. Using an integrated global transcriptomic and proteomic profiling approach, we investigated the role of the mesangium in the onset and progression of IgAN. Global gene expression was investigated by microarray analysis of the glomerular compartment of renal biopsy specimens from patients with IgAN (n=19) and controls (n=22). Using curated glomerular cell type-specific genes from the published literature, we found differential expression of a much higher percentage of mesangial cell-positive standard genes than podocyte-positive standard genes in IgAN. Principal coordinate analysis of expression data revealed clear separation of patient and control samples on the basis of mesangial but not podocyte cell-positive standard genes. Additionally, patient clinical parameters (serum creatinine values and eGFRs) significantly correlated with Z scores derived from the expression profile of mesangial cell-positive standard genes. Among patients grouped according to Oxford MEST score, patients with segmental glomerulosclerosis had a significantly higher mesangial cell-positive standard gene Z score than patients without segmental glomerulosclerosis. By investigating mesangial cell proteomics and glomerular transcriptomics, we identified 22 common pathways induced in mesangial cells by gd-IgA, most of which mediate inflammation. The genes, proteins, and corresponding pathways identified provide novel insights into the pathophysiologic mechanisms leading to IgAN.

Keywords: IgA nephropathy; mesangial cells; transcriptional profiling.

Figure 1.

Hierarchical clustering of patient and control samples. Clustering of the glomerular microarray data on the basis of whole-genome expression values using Euclidean distance with the Ward averaging method. Using whole-genome expression profiles, samples from patients with IgAN were clearly distinguishable from living donor controls.

Figure 2.

Principal coordinate analysis of the samples on the basis of the cell type–positive standard genes. Mesangial cell–positive standard genes could divide the samples into two separate groups (left panel). Podocyte-positive standard genes resulted in an overlapping population (right panel). Eig1 for mesangial cell–positive standards was 147.9, which was almost three times the eig1 for podocyte-positive standard genes (48.6). Eig1 represents the first value from eigenvector from the principal coordinate analysis.

Figure 3.

Correlations of clinical data and patient Z scores. Patient Z score is calculated on the basis of the positive standard genes and represents the deviation of all of the positive standard genes from each individual patient compared with the rest of the patients. Using mesangial-positive standard genes, the patient Z score correlated significantly with (A) serum creatinine and (B) eGFR. However, patient Z score of podocyte-positive standard genes showed no significant correlation with either (C) serum creatinine or (D) eGFR. Grouping the patients according to their Oxford MEST score of segmental glomerulosclerosis (S; zero or one) showed a significant difference in (E) the patients’ mesangial standard gene Z score but not when (F) the patients’ podocyte standard gene Z score was used. Error bars represent SEM. *P<0.05.

Figure 4.

gd-IgA treatment of human mesangial cells. Hierarchical clustering analysis of the cell proteomic data using the Ward averaging method. gd-IgA–treated cells were completely separated from the untreated cells.