Multi-Scalar Data Integration Links Glomerular Angiopoietin-Tie Signaling Pathway Activation With Progression of Diabetic Kidney Disease

Abstract

Diabetic kidney disease (DKD) is the leading cause of end-stage kidney disease (ESKD). Prognostic biomarkers reflective of underlying molecular mechanisms are critically needed for effective management of DKD. A three-marker panel was derived from a proteomics analysis of plasma samples by an unbiased machine learning approach from participants (N = 58) in the Clinical Phenotyping and Resource Biobank study. In combination with standard clinical parameters, this panel improved prediction of the composite outcome of ESKD or a 40% decline in glomerular filtration rate. The panel was validated in an independent group (N = 68), who also had kidney transcriptomic profiles. One marker, plasma angiopoietin 2 (ANGPT2), was significantly associated with outcomes in cohorts from the Cardiovascular Health Study (N = 3,183) and the Chinese Cohort Study of Chronic Kidney Disease (N = 210). Glomerular transcriptional angiopoietin/Tie (ANG-TIE) pathway scores, derived from the expression of 154 ANG-TIE signaling mediators, correlated positively with plasma ANGPT2 levels and kidney outcomes. Higher receptor expression in glomeruli and higher ANG-TIE pathway scores in endothelial cells corroborated potential functional effects in the kidney from elevated plasma ANGPT2 levels. Our work suggests that ANGPT2 is a promising prognostic endothelial biomarker with likely functional impact on glomerular pathogenesis in DKD.

Figure 1

Overall study workflow. The SOMAscan plasma proteomics data from C-PROBE group A were used to identify individual protein markers associated with DKD progression. A marker panel that jointly predicts DKD progression was constructed using Lasso method and further validated in the C-PROBE group B, CHS, and C-STRIDE cohorts. For understanding of the potential biological mechanisms underlying the association of promising markers with the kidney outcome, ANG-TIE signaling cascade was curated and quantified using bulk transcriptomic gene expression profiles. The association of ANG-TIE pathway activation score with the circulating ANGPT2 level and kidney outcome was evaluated. Cell type–specific pathway activation was evaluated in key kidney cell types using scRNAseq analysis from KPMP DKD research biopsies.

Figure 2

Identification and validation of the biomarker panel for DKD progression. Volcano plot demonstrating the associations of circulating proteins with risk of progression to the outcome (A). HR in log₂ scale (x-axis) and statistical significance of associations in log₁₀ scale (y-axis) are presented. Forest plot of the multivariate Cox proportional hazards model in C-PROBE discovery group A (N = 58) (B) and validation group B (N = 68) (C). *P < 0.05; **P < 0.01. ACR, albumin-to-creatinine ratio.

Figure 3

Validation of the association of plasma ANGPT2 with the risk of outcome in external cohorts using two different assay platforms. A: ANGPT2 concentrations measured by two different assay platforms, SOMAscan and ELISA, are significantly correlated with each other in patients from C-PROBE cohort A. B and C: Forest plot showing significant association of ANGPT2 with outcome in multivariate Cox proportional hazards model in DKD patients from CHS cohort (B) and C-STRIDE cohort where ANGPT2 concentrations were measured using ELISA (C). *P < 0.05; **P < 0.01. ACR, albumin-to-creatinine ratio.

Figure 4

ANG-TIE signaling pathway in bulk kidney transcriptome. A: Network visualization of the literature-curated ANG-TIE signaling cascade network. B: Association of plasma ANGPT2 with glomerular ANG-TIE signaling pathway score in (n = 32) C-PROBE cohort B participants. C: The glomerular ANG-TIE signaling pathway score is significantly higher in progressors compared with nonprogressors in patients from C-PROBE cohort B. D: The ANG-TIE signaling pathway score is significantly higher in patients with advanced DKD compared with early DKD (n = 28) from GSE142025 data set. Definition of early and advanced DKD is adapted from the original paper as described in the method session. E: The pathway scores were grouped into glomerular (podocytes, mesangial cells, vascular smooth muscle, and ECs) and tubulointerstitial (proximal tubular, descending and ascending thin limb, think ascending limb, connecting tubular, intercalated and principal) cells based on cellular origin. TEK gene expression is significantly higher in glomeruli than tubulointerstitia in data derived from normal kidney tissue panel of Lindenmeyer et al. from Nephroseq. For C–E, Student t test was used to compare the difference between groups.

Figure 5

ANG-TIE signaling pathway mapping in scRNAseq kidney biopsy data. A: Findings of a combined analysis of 56,906 cells from KPMP data sets demonstrated TEK gene expression is enriched in ECs, followed by mesangial cell/EC cluster; sporadic expression was also observed in PT1 cells. B: Dot plot showing increased TEK expression (by color intensity of the dots) in patients with DKD compared with living donors. C: Violin plots showing ANG-TIE pathway activation scores are significantly higher in glomerular cells compared with tubulointerstitial cells of kidney biopsy samples from patients with DKD. D: Violin plots showing the ANG-TIE pathway activation scores are significantly higher in cells expressing higher TEK compared with cells expressing low level of TEK, in both EC clusters of DKD patients. For C and D, Mann-Whitney U test was used for comparisons of the difference between groups. ATL, ascending thin loop of Henle; CNT, connecting tubule; DCT, distal convoluted tubule; DTL, descending loop of Henle; FIB, fibroblast; IC, intercalated cell; LOH, loop of Henle; MC, mesangial cell; MYL, myeloid cell; PC, principal cell; PEC, parietal epithelial cell; POD, podocyte; PT, proximal tubular epithelial cell; TAL, thick ascending loop of Henle; TI, tubulointerstitial; vSMC, vascular smooth muscle cell.