Evolving Clinical Applications of Tissue Transcriptomics in Kidney Disease

Abstract

Nephrotic syndrome is classically categorized by the histopathology with examples including focal segmental glomerulosclerosis (FSGS) and minimal change disease. Pediatric patients are also classified by whether their nephrotic syndrome is sensitive to, dependent on, or resistant to steroids. However, this traditional classification system overlooks the frequent clinical conundrum when, for example, one patient with FSGS responds briskly to steroids, and another quickly progresses to end stage kidney disease despite therapy. Two patients may have similar histopathologic appearances on kidney biopsy but entirely different clinical characteristics, rates of progression, and treatment responses. Transcriptional regulation of gene activation and posttranscriptional processing of mRNA may drive the unique and heterogeneous phenotypes which are incompletely understood in kidney disease and are a recent focus of research. Gene expression profiles provide insight on active transcriptional programs in tissues, are being used to understand biologic mechanisms of progressive chronic kidney disease, and may help to identify patients with shared mechanisms of kidney damage. This mini-review discusses clinically relevant techniques of bulk tissue and single cell transcriptomics, as well as strengths and limitations of each methodology. Further, we summarize recent examples in kidney research achieved through transcriptomics. This review offers an outlook on the role of transcriptomics in an integrative systems biology model with the goal of defining unique disease subgroups, finding targets for drug development, and aligning the right drug with the right patient.

Keywords: chronic kidney disease; glomerular disease; nephrotic syndrome; single cell transcriptomics; transcriptomics.

Figure 1

(A) Schematic of DropSeq workflow stepwise. Step 1: kidney biopsy tissue is digested into live single cells. Step 2 cells: cells, lysis buffer, and beads are injected into the microfluidic device where oil flowing across the stream pinches off droplets. Step 3: the lysed cell releases RNA for capture by bead primers. Step 4: droplets are broken to release beads with their cell-specific RNAs. Step 5: mRNA is reverse transcribed and cDNA is amplified for sequencing. Step 6: Data that has been mapped to the genome is analyzed to create a tSNE or Violin plot. UMI: Unique molecular identifier. STAMPs: Single Cell Transcriptomes attached to Microparticles. (B) T-Distributed Stochastic Neighbor Embedding (tSNE) plot representation of cell types in kidney tissue. Each cell is represented by a single point and points are grouped by similar gene expression profiles. In this plot, 15 clusters were identified and assigned a color as shown on the right. These 15 clusters were labeled as a specific cell type based on known genetic expression markers.