Single-Cell Resolution Drug Effects of Renin-Angiotensin-Aldosterone Blockade in ZSF1 Rat Diabetic Kidney Disease

Michael S Balzer; Jianfu Zhou; Amin Abedini; Ziyuan Ma; Yanjuan Hou; Tejaswini Yadav; Manuel Grundmann; Mira Pavkovic; Katalin Susztak

doi:10.1681/ASN.0000000995

. 2026 Jan 7;37(7):1438–1456. doi: 10.1681/ASN.0000000995

Single-Cell Resolution Drug Effects of Renin-Angiotensin-Aldosterone Blockade in ZSF1 Rat Diabetic Kidney Disease

Michael S Balzer ^1,^2,^3,^4,^5,^✉, Jianfu Zhou ^1,^2,³, Amin Abedini ^1,^2,³, Ziyuan Ma ^1,^2,^3,^✉, Yanjuan Hou ^1,^2,³, Tejaswini Yadav ⁴, Manuel Grundmann ⁶, Mira Pavkovic ⁶, Katalin Susztak ^1,^2,^3,^7,^✉

PMCID: PMC13337198 PMID: 41563360

Visual Abstract

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Keywords: ACE inhibitors, cardiovascular disease, immunology and pathology, outcomes, renin-angiotensin system, transcriptional profiling, diabetic kidney disease

Abstract

Key Points

Cathepsin D regulated enalapril effects in distal nephron injury states of diabetic kidney disease.
Enalapril reduced proinflammatory triggering receptor expressed on myeloid cells 2+ macrophages interacting with distal nephron cells.
Enalapril-associated gene signatures stratified human kidneys by fibrosis and function outcomes.

Background

Diabetic kidney disease is the leading cause of kidney failure worldwide. Renin-angiotensin-aldosterone system inhibitors, such as enalapril, have been used for decades as antiproteinuric, antihypertensive, and kidney-protective agents. Still, the exact cell type of action and the molecular mechanism of drug action are elusive. Previous work has primarily emphasized injury patterns in the proximal nephron, leaving potential contributions of other nephron segments insufficiently characterized.

Methods

Here, we leveraged state-of-the-art single-cell transcriptomics in the Zucker spontaneously hypertensive fatty obese rat to elucidate potential target cells and driver molecules exerting enalapril drug effects.

Results

We identified injured cell states of the distal nephron in the context of prolonged enalapril treatment. We showed cathepsin D, a tissue renin-angiotensin-aldosterone system effector, as an important regulator of enalapril effects and revealed triggering receptor expressed on myeloid cells 2+ residential macrophages as top receivers of distal nephron–derived signals. Finally, we showed that enalapril-associated gene signatures allow stratification of human kidney samples by disease-relevant outcome measures such as kidney function and fibrosis.

Conclusions

We reported cathepsin D as an important regulator of enalapril effects, involving cross-talk between the distal nephron and triggering receptor expressed on myeloid cells 2+ residential macrophages. We also demonstrated that enalapril-associated gene signatures allow stratification of human kidney samples by disease-relevant outcome measures.

Introduction

Diabetic kidney disease (DKD) is the leading cause of CKD, kidney failure, and the need for KRT worldwide.¹ More than 850 million people are affected by CKD worldwide.² Despite recent therapeutic advances with sodium-glucose cotransporter 2 inhibitors demonstrating reduction of composite kidney end points,^3,4 the mainstay of current therapies for DKD still relies on inhibition of the renin-angiotensin-aldosterone system (RAAS).^5,6

Even after >30 years of CKD treatment experience with RAAS inhibitors (RAASis), their exact cellular mechanism of action remains not fully established. Classically, beneficial effects of RAAS inhibition were described to involve modulation of the circulating RAAS, such as reduced production of angiotensin II (Ang II) through angiotensin-converting enzyme (ACE) inhibition in lung endothelium or blocking Ang II effects at its type 1 receptor in efferent arterioles of the kidney glomerulus as well as in mesangial and tubular cells.⁷ Although the circulating RAAS is a regulator of systemic volume, electrolyte balance, and BP, more recently, this dogma was appended by the description of a tissue RAAS exerting local effects involving proliferation, growth, protein synthesis, and specific organ functions in the kidney, heart, and other organs.^8–10 For example, the kidney expresses many RAAS components, such as renin in juxtaglomerular cells¹¹; ACE in proximal tubule and collecting duct¹²; angiotensinogen predominantly in proximal tubule¹³; Ang II effects at its type 1 receptor in glomeruli, proximal tubule, and tubulointerstitium¹⁴; and mineralocorticoid receptor in the distal nephron.⁸ However, there is no clear agreement on which cell types are specifically targeted by ACE inhibitors or angiotensin-receptor blockers during CKD and DKD.¹⁵

The obese Zucker spontaneously hypertensive fatty (ZSF1) rat model exhibits many of the phenotypic characteristics of human DKD, such as proteinuria, structural kidney lesions, hyperglycemia, dyslipidemia, hypertension, oxidative stress, and obesity.^16–20 We have previously defined the single-nuclear transcriptomic landscape of functionally and structurally established DKD in ZSF1 rats as young as 25–26 weeks and have shown that pharmacologic intervention by soluble guanylate cyclase modulation can modify disease markedly.²¹ In that analysis, proximal tubule and stroma cells were prioritized to be important targets of soluble guanylate cyclase modulation.²¹ Given that the RAAS is intricately implicated in the progression of a diabetic phenotype²¹ and that its inhibition has been the cornerstone of DKD therapy,²² we were interested to identify the responsible cell types and molecular underpinnings of the therapeutic effects of prolonged RAAS inhibition in the context of this RAAS-dependent model using state-of-the-art single-cell methodologies.

In this study, we sought to define the cellular targets and molecular mechanisms underlying the therapeutic effects of prolonged RAAS inhibition in DKD using the obese ZSF1 rat model. By applying state-of-the-art single-cell and spatially resolved approaches, we aimed to identify kidney cell populations responsive to enalapril treatment and to delineate intercellular communication pathways associated with RAAS inhibition in advanced DKD. Furthermore, we aimed to assess the translational relevance of RAASi-associated molecular signatures by integrating findings from the ZSF1 rat model with human kidney datasets.

Methods

In-depth methods are detailed in the Supplemental Material.

ZSF1 Rat Model

ZSF1 obese rats were randomly divided into two groups (vehicle, enalapril) and compared with ZSF1 lean rats as controls (all 12-week-old males, Charles River). Vehicle or enalapril was dissolved in drinking water and administered for 22 weeks. BP was measured at baseline, 4, 14, and 22 study weeks. Blood and urine biochemistry assays were performed at baseline and at 22 study weeks. Kidneys, hearts, and livers were stained with periodic acid–Schiff stain and Sirius red. Immunofluorescence staining was performed for cathepsin D, SLC12A3, and dolichus biflorus agglutinin. Kidney tissue protein was assayed with Olink and the Peggy Sue platform (Simple Western). Sample sizes were determined based on prior experience with the ZSF1 rat model and on previously published studies using comparable experimental designs and end points, including BP, renal histology, and biochemical measures of kidney injury and fibrosis.

Preparation of Rat Single-Cell Suspension

Rats were perfused with chilled PBS, and single cells were isolated using a previously established protocol.²³ After digestion, debris removal, and dead cell removal, cells were processed with the 10X Genomics pipeline, quality controlled using an Agilent Bioanalyzer, and sequenced on an Illumina Novaseq 6000 system.

Single-Cell RNA-Seq Data Analysis

Single-cell RNA sequencing (scRNA-seq) data analysis included alignment, ambient RNA correction, sample integration, batch correction, doublet removal, differential gene expression analysis, integration of rat and human DKD datasets, cross-dataset hierarchical replicability analysis, differential proportion analysis, and gene set enrichment analysis. Subanalyses after subclustering of distal nephron tubule, glomerular, and myeloid cells included trajectory analysis, RNA velocity analysis, gene ontology over-representation analysis, cellular indexing of transcriptomes and epitopes by sequencing imputed ab-derived tags integration, weighted gene coexpression network analysis (WGCNA), and ligand–receptor interaction analysis.

Spatial Transcriptomics Data Analysis

Human kidney spatial transcriptomics data were analyzed for spatial proximity of CTSD+ connecting tubule cells and TREM2+ macrophages.

Bulk RNA-Seq Data Analysis

Microdissected human kidney tubule bulk RNA-seq samples with sufficient clinical data were subjected to hierarchical clustering analysis. Enalapril treatment–associated differentially expressed genes (DEGs) in the distal nephron served as input gene list.

Results

RAAS Inhibition through Enalapril Ameliorated Hypertension, Proteinuria, and Kidney Fibrosis in the ZSF1 Rat Model of DKD

We recently characterized the diabetic ZSF1 rat kidney at single-cell resolution and confirmed that it not only mirrors the phenotype of human DKD but also closely matches human cell type–specific transcriptomes.²¹ Although our earlier study used single-nuclear methodology, we now applied single-cell transcriptomics to better capture immune cell states often missed in nuclear datasets.²⁴

Rats were treated with or without enalapril over 22 weeks and analyzed at 34 weeks of age, when DKD is fully established (Figure 1A). A stable enalapril dose of 20 mg/kg (Supplemental Figure 1A) significantly lowered BP (Figure 1B) but had no effect on blood glucose, body weight, or glomerular filtration (Figure 1, C and D, and Supplemental Figure 1B). Obese rats displayed marked albuminuria and glomerular enlargement, both significantly reduced by enalapril (Figure 1E). Proteomic analysis of 92 kidney proteins (Olink platform) revealed diabetes-associated elevations in apoptosis (CASP3), fibrosis (TGFB1, TGFBR3, PDGFB), and inflammation markers (CCL5, CXCL9, ectodysplasin A2 receptor [EDA2R], IL1B, IL6, IL17A), several of which normalized after treatment (Figure 1F). Proteins, such as EDA2R, have recently been found in a human proteomics study analyzing four independent cohorts of individuals with type 1 and type 2 diabetes and early and late DKD to be associated with progression to kidney failure.²⁵ Notably, six of seven proteins previously linked to kidney failure progression in human cohorts (including EDA2R and CCL5) were elevated in ZSF1 kidneys and reduced by enalapril, further validating the model's relevance. Enalapril also decreased serum injury markers kidney injury molecule-1 and neutrophil gelatinase–associated lipocalin (Figure 1G). Kidneys and hearts of obese rats were larger and heavier (Supplemental Figure 1, C and D) and showed increased fibrosis (Figure 1H and Supplemental Figure 1E).

**RAAS inhibition through enalapril ameliorated** **hypertension, proteinuria, and kidney fibrosis in the ZSF1 rat model of DKD.** (A) Experimental layout. (B) Systolic BP, MBP, and diastolic BP measurements over time; P for multiple t test comparisons between Ob+E and Ob groups; means±SEM. (C) Whole blood glucose levels at study end (22 weeks); P for ANOVA comparisons. (D) Kidney function, as measured by BUN and whole blood creatinine levels at study end (22 weeks); P for ANOVA comparisons. (E) Glomerular function, as measured by UACR and glomerular area at study end (22 weeks); P for ANOVA comparisons. (F) Normalized expression of Olink exploratory panel proteins in kidney tissue; x denotes proteins reported as strongly associated with progression to kidney failure (Kobayashi *et al.*²⁵) that were included in the Olink panel; P for ANOVA or Kruskal–Wallis comparisons. (G) Levels of serum injury markers KIM-1 and NGAL; P for ANOVA comparisons. (H) Left: representative light microscopy of PAS- (top panels) and Sirius red–stained kidneys (bottom panels); scale bars=100 µm. Right: quantification of fibrotic area; P for ANOVA comparisons. DKD, diabetic kidney disease; KIM-1, kidney injury molecule-1; MBP, mean BP; NGAL, neutrophil gelatinase–associated lipocalin; Ob, obese; Ob+E, obese+enalapril; PAS, periodic acid–Schiff; RAAS, renin-angiotensin-aldosterone system; scRNA-seq, single-cell RNA sequencing; UACR, urine albumin-creatinine ratio; ZSF1, Zucker spontaneously hypertensive fatty.

In summary, the ZSF1 rat model recapitulated functional and histologic features of human DKD, and enalapril treatment effectively improved hypertension, proteinuria, molecular injury markers, and fibrosis.

The Single-Cell Transcriptomic Landscape of the Diabetic ZSF1 Rat Showed Immune Cell Enrichment and Endothelial and Tubular Cell Depletion

To identify key cell types and targets of enalapril effects, we performed scRNA-seq on rat kidneys. After stringent quality control, including ambient RNA correction, doublet removal, cell filtering based on unique molecular identifier counts, and mitochondrial percentage, we integrated 114,615 high-quality single cells into a batch-corrected dataset (Figure 2A and Supplemental Figure 2, A–G). Unsupervised clustering indicated 21 cell clusters covering all major kidney compartments (Figure 2A, Supplemental Data 1, and Supplemental Figure 2, H and I). Cell cluster transcriptomes strongly correlated with two independent human single-nuclei datasets^26,27 and mirrored our prior ZSF1 rat single-nuclear data²¹ (Figure 2B and Supplemental Figure 3), as confirmed by hierarchical replicability analysis (Figure 2, C and D, and Supplemental Data 2). Cross-dataset consensus²⁸ was especially strong among distal nephron cells (Figure 2, B–D).

As expected, the single-cell dataset revealed much greater immune cell diversity compared with single-nuclei datasets. All cell types were present across all samples with minimal batch effects (Figure 2E and Supplemental Figure 4). Obese diabetic rats showed enrichment of lymphoid and myeloid cells, whereas lean controls and enalapril-treated rats retained more tubular cells (Figure 2F). Differential proportion analysis confirmed that enalapril prevented immune cell influx and preserved tubular populations, including proximal tubule, thick ascending limb (TAL), distal convoluted tubule (DCT), connecting tubule, and collecting duct intercalated cells (Supplemental Figure 5). However, diabetes-associated loss of glomerular endothelial cells was not prevented.

In summary, the ZSF1 DKD transcriptomic landscape was consistent across single-cell and single-nuclei approaches, mirrored human DKD, and was marked by tubular loss, endothelial rarefaction, and immune infiltration—many of which were ameliorated by RAAS inhibition.

Enalapril Downregulated Cathepsin D in Diabetic Distal Nephron and Myeloid Cells

To dissect the molecular effects of enalapril, we analyzed RNA and protein expression of known tissue RAAS effector genes²⁹ across nephron segments (Figure 3A).

First, cell type–specific gene expression analysis confirmed that proximal tubule and stromal cells exhibited high RAAS effector expression,²¹ with Agtr1b in stroma, Ren in juxtaglomerular cells (Supplemental Figure 6A), and Agt, Ace2, and Hsd11b1 in proximal tubule cells (Figure 3B). Distal nephron segments selectively expressed Cyp17a1 and Lnpep (TAL), Hsd11b2 and Egfr (collecting duct), and Nr3c2 and Ctsd (connecting tubule and principal cell) (Figure 3B). These patterns were validated using the Human Protein Atlas and orthogonal single-nuclei rat data (Figure 3B and Supplemental Figure 6B).

Differential gene expression analysis across healthy, diabetic, and enalapril-treated groups (Supplemental Data 3 and Supplemental Data 4) showed that diabetes-associated DEGs were most abundant in distal nephron cells (TAL, DCT, connecting tubule, principal cell), stroma, and myeloid cells, with varying degrees of rescue by enalapril (Supplemental Figures 7 and 8). Defining “enalapril rescue” as reversal of diabetes-induced expression changes in DEGs (Supplemental Figure 9A), we found that proximal tubule and stromal cells, despite high RAAS effector expression, showed little rescue (Figure 3, B and C, and Supplemental Figure 9, A and B). Instead, rescue occurred in endothelial (Endo), TAL/MD, connecting tubule, and myeloid (Macro) cells (Figure 3C).

Among RAAS effectors, enalapril significantly rescued Rnpep and Nr3c1 expression in Endo, Igf2r in TAL, and most strikingly, Ctsd in distal tubules (TAL/MD, connecting tubule) and myeloid cells (Figure 3, D and E, and Supplemental Figure 9A). Cathepsin D protein levels, elevated in diabetic kidneys, were normalized by enalapril (Figure 3F and Supplemental Figure 9C). Ctsd ranked among the strongest DKD-upregulated genes in distal nephron cells alongside Spp1 and Clu (Figure 3G), with highest expression in aldosterone-sensitive regions (DCT, connecting tubule, principal cell) (Figure 3H and Supplemental Figure 9D), confirmed by immunofluorescence (Figure 3I and Supplemental Figure 10). These findings aligned with prior single-cell/nuclei studies in diabetic mice^30,31 (Supplemental Figure 11).

In summary, enalapril rescued relatively few tissue RAAS effectors, mainly in endothelial, distal nephron, and myeloid cells. Cathepsin D emerged as a key molecule, showing the strongest rescue in distal nephron and myeloid compartments, leading us to prioritize these cell types for deeper analysis.

Ctsd+ Connecting Tubule Cells of the Distal Nephron Were Enriched in Diabetic Kidneys and Depleted on Enalapril Treatment

We next focused on the distal nephron. To identify potential injury and enalapril treatment–associated signatures, we performed iterative subclustering of all nonproximal tubule cells (descending thin limb, TAL/MD, TAL, DCT, connecting tubule, principal cell) (Figure 4A), yielding 11,533 high-quality cells (Figure 4B). This revealed distinct subclusters for each segment, plus additional injury (Clu), stress (Spp1, Igfbp4), immune (C3, Nfkbia), and proliferative (Mki67, Spc24) states (Supplemental Data 5 and Supplemental Figure 12A). We distinguished DCT1 from DCT2, the latter marked by calcium-handling genes such as Vdr and Calb1 alongside sodium/magnesium transporters (Slc12a3, Trpm6)^32,33 (Figure 4C). Expression of mineralocorticoid receptor (Nr3c2) differentiated aldosterone-insensitive DCT_1 from aldosterone-sensitive subclusters (DCT_2, Ctsd+ connecting tubule, connecting tubule, and principal cell) (Figure 4C and Supplemental Figure 12A), consistent with previous mouse studies.³⁴

Subclusters enriched in diabetic kidneys included Spp1+, Immune, and Ctsd+ connecting tubule (Figure 4D). Ctsd+ connecting tubule cells coexpressed Stat3 and Cfh (Supplemental Figure 12A). Complement factor H was previously linked to failed repair²⁶ and kidney failure.³⁵ These injury-prone subclusters were significantly reduced by enalapril treatment (Figure 4D) and showed high numbers of DKD-specific DEGs (Supplemental Figure 12B). Ctsd expression was highest in Ctsd+ connecting tubule cells and downregulated by enalapril exclusively in injury (log2 fold change=−0.75) and Spp1+ (log2 fold change=−0.32) clusters (Supplemental Figure 12C).

In summary, Ctsd+ connecting tubule cells were enriched in diabetic kidneys and depleted by enalapril.

Ctsd Was a Hub Gene for a Transitional Cell State Linking the Healthy Distal Nephron with Diabetic Injury Phenotypes

Trajectory and RNA velocity analyses revealed a continuous transition from injury (Injury, Spp1+, Immune) toward DCT, connecting tubule, and principal cell clusters (Figure 4E and Supplemental Figure 12, D and E). Notably, Ctsd+ connecting tubule cells bridged injury and healthy nephron states (Figure 4F), representing a transitional population. Genes expressed along this lineage were grouped into modules (Supplemental Data 6). Module 4, enriched in Ctsd+ connecting tubule cells, involved kidney development and growth regulation pathways (Figure 4, G and H). Injury modules (e.g., module 1) captured processes such as wound healing, immune response, and cell adhesion (Supplemental Figure 13).

WGCNA confirmed that Ctsd+ connecting tubule cells were highly enriched for modules with Ctsd as a key hub gene (blue, green) (Figure 4, I and J, Supplemental Data 7, and Supplemental Figure 14).

In summary, we identified a transitional cell state linking injury and healthy distal nephron, with Ctsd as a central regulator, implicating these cells in epithelial–immune cross-talk and extracellular matrix (ECM) deposition.

Ctsd as a Marker for Proinflammatory Trem2+ Residential Macrophages

We next explored cell–cell interactions from distal nephron cells to other compartments. In obese rats, inferred interactions from DCT/connecting tubule/principal cells increased approximately 20-fold compared with lean controls and were partly rescued by enalapril (Figure 5A). Most signals targeted myeloid cells (Figure 5B).

Given the marked myeloid infiltration (Figure 2, E and F, and Supplemental Figure 5) and strong enalapril-rescue signals in macrophages (Figure 3C), we subclustered myeloid cells (11,069 cells across 12 clusters) (Figure 5C and Supplemental Data 8), validating identities with an orthogonal cellular indexing of transcriptomes and epitopes by sequencing dataset³⁶ (Supplemental Figure 15). Three subsets of residential macrophages (Res_Macs) emerged, marked by Cx3cr1, Lyve1, or Trem2 (Figure 5D).

Trem2 and Ctsd were coexpressed in a distinct Res_Mac subset, both upregulated in diabetic kidneys and downregulated by enalapril (Figure 5E). WGCNA confirmed Ctsd as a hub gene specific for Trem2_Res_Macs (Figure 5F, Supplemental Data 9, and Supplemental Figure 16A). Triggering receptor expressed on myeloid cells 2 (Trem2)^high macrophages are known for roles in homeostasis and inflammation in adipose, liver, heart, and brain tissues^37–40 and have been observed in obese patients and diabetic kidneys.⁴¹ Trem2_Res_Macs expressed stress and ECM-related markers such as Spp1, Fabp5, and Mmp12 (Supplemental Figure 16B), suggesting their involvement in stress response, the development of a diabetic milieu, and ECM breakdown processes.

Using MacSpectrum,⁴² we found that Trem2_Res_Macs had the second highest inflammatory score after CD16⁺ monocytes (Figure 5G). Less inflammatory cells (CD14_Mono, Cx3cr1_Res_Mac) dominated healthy and enalapril-treated samples, while highly inflammatory populations (Trem2_Mac, CD16_Mono) were enriched in diabetic kidneys and depleted by enalapril (Figure 5H and Supplemental Figures 16, C and D, and 17).

In summary, enalapril depleted a Trem2+ macrophage subset with a strong proinflammatory phenotype, coexpressing Ctsd.

TREM2+ Residential Macrophages Were in Close Spatial Proximity to and Interacted Strongly with Distal Nephron Tubule Cells

To validate our findings in humans, we used spatial transcriptomics on DKD and control kidney cortex (Supplemental Data 10 and Supplemental Figure 18). We observed focal areas coexpressing CTSD, SLC12A3, and TRPV5, representing CTSD+ connecting tubule cells (Figure 6A). CTSD+ connecting tubule cells and TREM2+C1QC+ macrophages were both strongly enriched in DKD tissue, particularly in close proximity to each other within the cortex (Figure 6, B–G). Immediate neighborhoods of TREM2+ macrophages differed substantially between control and DKD tissue. Absolute neighbor counts revealed shifts in the abundance of specific tubular and stromal cell types within approximately 1.6× nearest-neighbor spacing (approximately 160 µm) (Figure 6H). Deconvolution of spots with a ZSF1 rat single-cell reference mapped to human genes confirmed the presence of TREM2+ and CTSD+ niches (Figure 6I and Supplemental Figures 19 and 20A). Pairwise permutation testing further indicated that TREM2+ macrophages were significantly more likely to localize near CTSD+ connecting tubule spots than near other cell types (Figure 6J). Finally, spatial proximity between TREM2+ and CTSD+ cells was independently confirmed by immunofluorescence (Figure 6K and Supplemental Figure 20B).

Cell–cell interaction analysis in rats showed >4× more myeloid–epithelial interactions in DKD versus lean kidneys, largely reversed by enalapril (Figure 6L and Supplemental Figure 21, A and B). Trem2_Res_Macs were identified to be mainly receiving target cells, whereas distal nephron cells, especially descending thin limb, connecting tubule, and principal cells, demonstrated a secretory phenotype (Figure 6M and Supplemental Figure 21C). Connecting tubules mainly signaled via amyloid-beta precursor protein (APP), SPP1, growth arrest-specific, and laminin pathways; APP signaling⁴³ uniquely targeted Trem2_Res_Macs and was suppressed by enalapril (Figure 6, N and O, and Supplemental Figure 21D).

In summary, TREM2+ macrophages were enriched in diabetic kidneys, closely associated spatially with distal nephron cells, and were highly responsive to enalapril treatment, with APP signaling emerging as a key mediator (Supplemental Figure 21E).

CTSD Was Particularly Enriched in Kidneys from DKD Patients and Correlated with Outcome-Relevant Parameters

To assess clinical relevance, we analyzed cathepsin D and other tissue RAAS effectors using bulk RNA-seq from microdissected glomerular and tubular compartments.⁴⁴ CTSD was significantly upregulated in diseased tubules, with the highest levels in DKD patients (Figure 7A). Higher CTSD expression correlated with lower GFR and greater fibrosis, especially in females (Figure 7B), whereas systolic BP showed no effect (Supplemental Figure 22A). DKD patients without RAASi use had higher CTSD levels and lower GFR than those treated with RAASis (Figure 7C) and higher CTSD levels were correlated with lower eGFR only in patients without RAAS inhibition (Supplemental Figure 22B), mirroring findings in the ZSF1 model (Supplemental Figure 22C).

Similarly, RAAS effectors upregulated in DKD (CTSD, CMA1, CPA3, CTSG, HSD11B1, NLN, NR3C1, PREP) correlated positively with fibrosis and negatively with GFR (Figure 7D and Supplemental Figure 23A). Conversely, downregulated RAAS effectors (AGT, ACE, ACE2, CTSA, CYP17A1, ENPEP, GPER1, HSD11B2, IGF2R, KLK1, MME, NR3C2) correlated inversely (Figure 7D and Supplemental Figure 23B), highlighting a strong link between tissue RAAS activity, fibrosis, and kidney function.

Finally, we used enalapril-associated DEGs from the distal nephron to cluster 378 human kidney tubule samples (Figure 7E and Supplemental Data 11). Three clusters emerged with balanced demographics. Patients with high expression of enalapril-associated DEGs (n=109, red cluster 3) had lower eGFR, steeper eGFR slope, and higher levels of kidney fibrosis (Figure 7, E and F). These patients also showed reduced REN, ACE2, and AGT expression despite low RAASi use (Figure 7G), while RAAS effectors such as CTSD, AGTR1, ATP6AP2, EGFR, NR3C2, and NR3C1 were elevated, mirroring rat data (Supplemental Figure 24A). Importantly, clustering based on enalapril-associated DEGs proved robust across subpopulations, remaining stable when stratified by DKD status, sex, or RAASi use (Supplemental Figure 24B). The enalapril target gene signature was validated in our spatial data, demonstrating considerable enrichment in DKD versus Control (Figure 7H), especially in kidney cortex areas enriched with CTSD+ connecting tubule cells (Figures 6D and 7I).

In summary, cathepsin D expression was highest in DKD patients, associated with worse outcomes, and responsive to RAAS inhibition. Enalapril-associated gene signatures effectively stratified human kidney samples by fibrosis and function.

Discussion

Although RAASis have been used to treat DKD for decades, the precise cellular targets driving their therapeutic effects have remained unclear. Here, using single-cell transcriptomics in a ZSF1 rat model of DKD, we identified key driver cell types and molecules affected by enalapril. We discovered novel injury states in distal nephron cells, highlighted cathepsin D as a major regulator, and revealed close spatial interactions between TREM2+ residential macrophages and distal tubules. Finally, we demonstrated that enalapril-associated gene regulation patterns stratify human kidneys by function and fibrosis.

Previously, we created the first single-cell atlas of diabetic rat kidneys²¹ and found strong transcriptomic parallels with human DKD. Building on that with single-cell (not nuclei) methods allowed better resolution of immune cell states. Notably, we identified a Trem2+ residential macrophage cluster with strong inflammatory activation. TREM2 is a lipid-sensing receptor increasingly implicated in diverse diseases, including neurodegeneration, obesity, and fibrosis.^37–41,45 TREM2+ macrophages modulate inflammation in settings such as coronavirus disease 2019 lung injury⁴⁶ and ischemia⁴⁷ and localize to fibrotic niches.^48–50 Although these macrophages can both drive and resolve inflammation,^51–53 in DKD, we observed a proinflammatory Trem2_Res_Mac population depleted by enalapril. These cells expressed disease-associated markers (Fabp5, Gpnmb, Igf1, Itgax, Spp1)⁵⁴ and communicated extensively with distal nephron cells, suggesting functional significance.

Interestingly, distal nephron cells, not proximal tubule cells, showed the strongest enalapril rescue effects—an unexpected finding, as proximal tubules dominate most kidney single-cell datasets.^24,55 Although proximal tubule and stroma cells express many RAAS effectors, enalapril preferentially rescued distal nephron cells and myeloid cells. Given the distal nephron's role in fine sodium regulation⁵⁶ and BP control,^57–61 this aligns well with known physiology. We further confirmed transcriptomic continuity across DCT1, DCT2, connecting tubule, and principal cell segments^34,62–64 and identified injury-associated transitional cell states.

Ctsd+ connecting tubule cells served as a bridging phenotype between injury, stress, and immune signature clusters (defined by genes such as Clu, Spp1, Igfbp4, Nfkbia, etc.) and healthy distal nephron expressing typical markers of DCT, connecting tubule, and principal cells, respectively. This transitional nature of Ctsd-expressing connecting tubules was underlined by strong expression of genes enriching for ontology terms related to renal system development (e.g., Adamts1, Foxc1, Osr2, Rida, Sox9, etc.) and regulation of developmental growth (e.g., Apoe, Plac8, Sema3f, Sema5a, Sema6d, Serpine1) fitting with the known plasticity of distal nephron cells.^65–68

These transitional Ctsd+ connecting tubule cells specifically expressed Ctsd at high levels. Our data are in keeping with prior evidence from rodent studies demonstrating Ctsd expression predominantly in the injured distal nephron^69–71 and from human transplant biopsies with acute tubular necrosis, in which cathepsin D protein expression was highest in damaged tubular cells, although the exact cell type identity could not be delineated with certainty.⁷⁰ Exploiting scRNA-seq, spatial transcriptomics, and immunofluorescence, we now close this knowledge gap and report Ctsd/cathepsin D coexpression with connecting tubule marker Trpv5/TRPV5. Moreover, strong upregulation of Ctsd/cathepsin D in diabetic kidneys was ameliorated both on the RNA and protein level in enalapril-treated diabetic animals. This was driven by a profound enrichment of Ctsd+ connecting tubules in diabetic kidneys, a transitional cell type depleted in enalapril-treated rats. The importance of Ctsd+ distal nephron cells was underlined by prior serum integrative omics studies reporting cathepsin D as a surrogate marker for DKD progression⁷² and by evidence from urinary proteomics studies identifying cathepsin D as a marker for both failed AKI recovery⁷³ and rapid eGFR decline in type 1 diabetes.⁷⁴

Almost four decades ago, a landmark study in which a 2-week course of captopril led to a 50% decrease of proteinuria in ten individuals with advanced DKD marks the beginning of the success story of RAAS inhibition as a treatment strategy for DKD.⁷⁵ Studies systematically demonstrating the beneficial effects of RAASis on CKD progression in diabetic and nondiabetic participants alike followed in the two decades after.^76–81 Beyond the wide-known circulating RAAS, which starts with renin release from the juxtaglomerular apparatus and leads—via cleavage of angiotensinogen to angiotensin I (Ang I), ACE-mediated cleavage into Ang II—to downstream mineralocorticoid, proliferative, inflammatory, and fibrotic effects, a complementary tissue-based RAAS is increasingly recognized to act independently from the circulating RAAS.^9,29 For example, angiotensin (1–12) peptide was recently described as a potential alternative of Ang I for cleavage by ACE, chymase, or neprilysin, raising the possibility of alternative renin-independent pathways for the generation of active peptides from angiotensinogen.^8,82 The known activity of cathepsin D, cathepsin G, and tissue kallikrein to directly accept angiotensinogen, as a substrate to release Ang I or Ang II, further strengthens this hypothesis.⁸³ Recently, an atlas of the extended RAAS has been described, delineating coexpression patterns of 37 effector genes at the tissue level.²⁹ Exploiting scRNA-seq, not only did we herein elevate this concept to a kidney cell type–specific distribution of RAAS effector gene expression but we also for the first time elucidated gene regulatory effects of a RAASi in a DKD model system. Finally, we leveraged the enalapril treatment effect–associated gene signature to stratify in an unbiased way human kidney samples into groups with grossly different levels of fibrosis as well as GFR, suggesting the relevance of a RAAS inhibition–associated gene signature for outcome-associated parameters in humans.

To place our findings into a broader clinical perspective, it is important to emphasize that the CTSD+ transitional phenotype we describe not only refines mechanistic understanding of RAAS inhibition but also has potential implications for patient stratification and therapeutic monitoring. Our integration of multiple techniques (scRNA-seq, spatial transcriptomics, and protein validation) provides converging evidence for this phenotype, yet we acknowledge that some discrepancies across methods may arise due to differences in sensitivity, resolution, and technical biases. We therefore interpret these findings in light of their translational potential, while recognizing that further validation in human cohorts and functional studies will be required before clinical implementation.

Although our spatial and ligand–receptor analyses support a close association between CTSD+ distal nephron cells and TREM2+ macrophages, these data cannot distinguish direct cell–cell contact from signaling through secreted factors; future mechanistic studies will be required to validate the precise mode of interaction. Notably, under pathophysiologic conditions, cathepsin D has been reported to shift from its canonical lysosomal localization toward a secretory phenotype, a process described in cancer and other disease contexts where cathepsin D is hypersecreted and regulated by glycosylation or other posttranslational modifications.^84,85 Cathepsins more broadly are known to exert nonlysosomal, extracellular roles in tissue remodeling and inflammation.⁸⁶ Such a mechanism could explain how cathepsin D+ distal nephron cells signal to neighboring immune cells such as TREM2+ macrophages in DKD.

Our study has the following limitations: First, by choosing a single-cell rather than nuclei approach, we achieved higher resolution in capturing immune cell states but lost granularity in resolving glomerular populations such as podocytes, mesangial, and parietal epithelial cells, as well as vascular compartments. Consequently, we cannot draw conclusions about specific enalapril effects on these cell types. Second, although enalapril's renoprotective effects in ZSF1 rats likely involved BP reduction, the relative contribution is hard to isolate. While the 10X Visium platform provides robust spatial resolution at the level of tissue regions and cell neighborhoods, it cannot fully resolve single-cell boundaries or subcellular localization. Thus, further validation with higher-resolution methods could be of interest to refine these findings, particularly regarding connecting tubule–immune cell interactions. Finally, only male rats were included in this study, and we did not investigate sex-specific cell states, which have been noted in nephron cells⁸⁷ and TREM2+ macrophages.⁸⁸

In summary, we report novel injury states in the distal nephron, identify cathepsin D as a key effector of enalapril treatment, highlight TREM2+ macrophages as key communication hubs, and demonstrate that these findings translate to human DKD, with important implications for outcome stratification.

Acknowledgments

The authors thank the University of Pennsylvania Diabetes Research Center (DRC) for the use of the next-generation sequencing Core (P30-DK19525).

Footnotes

See related editorial, “Evaluating Kidney Responses to Angiotensin-Converting Enzyme Inhibition at the Single-Cell Level,” on pages 1370–1372.

Disclosures

Disclosure forms, as provided by each author, are available with the online version of the article at http://links.lww.com/JSN/F635.

Author Contributions

Conceptualization: Michael S. Balzer, Katalin Susztak.

Data curation: Amin Abedini, Michael S. Balzer.

Formal analysis: Michael S. Balzer, Manuel Grundmann, Yanjuan Hou, Ziyuan Ma, Mira Pavkovic, Jianfu Zhou.

Funding acquisition: Michael S. Balzer, Katalin Susztak.

Investigation: Michael S. Balzer, Manuel Grundmann, Ziyuan Ma, Mira Pavkovic, Tejaswini Yadav.

Methodology: Michael S. Balzer.

Project administration: Michael S. Balzer, Katalin Susztak.

Resources: Michael S. Balzer, Katalin Susztak.

Supervision: Michael S. Balzer, Katalin Susztak.

Validation: Michael S. Balzer, Yanjuan Hou, Tejaswini Yadav.

Visualization: Michael S. Balzer.

Writing – original draft: Michael S. Balzer, Katalin Susztak.

Writing – review & editing: Amin Abedini, Michael S. Balzer, Manuel Grundmann, Yanjuan Hou, Ziyuan Ma, Mira Pavkovic, Katalin Susztak, Tejaswini Yadav, Jianfu Zhou.

Funding

M.S. Balzer: Deutsche Forschungsgemeinschaft (BA6205/2-1), Else Kröner-Fresenius-Stiftung (Memorial Fellowship), Dr. Werner Jackstädt-Stiftung, and Berlin Institute of Health (Clinician Scientist Program). K. Susztak: Bayer AG and NIH (DK076077, DK087635, DK105821, and DK132630).

Declarative Statements

All animal experiments were conducted in accordance with the NIH Guide for the Care and Use of Laboratory Animals or an equivalent standard that meets or exceeds the ethical and welfare requirements outlined in the NIH Guide. All protocols were approved by the appropriate institutional animal care and use committee.

Data Availability Statements

Original data generated for the study are available in a public access repository. Data Type: Aggregated Data; Raw Data/Source Data; and Software Executable Code. Repository Name: Gene Expression Omnibus (GEO) and GitHub. Linkable Citation: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE233078. Raw, processed, and metadata for scRNA-seq are available at GEO accession number GSE233078. Raw, processed, and metadata for spatial transcriptomics are available at GEO accession number GSE211785. Code to reproduce all parts of the analysis are provided via a GitHub repository (https://github.com/ms-balzer/ZSF1_RAASi/). Processed data are available via an interactive website (http://www.susztaklab.com/ZSF1_RAASi/). Further information and requests for resources and reagents should be directed to the lead contact.

Supplemental Material

This article contains the following supplemental material online at http://links.lww.com/JSN/F636, http://links.lww.com/JSN/F637, http://links.lww.com/JSN/F638, http://links.lww.com/JSN/F639, http://links.lww.com/JSN/F640, http://links.lww.com/JSN/F641, http://links.lww.com/JSN/F642, http://links.lww.com/JSN/F643, http://links.lww.com/JSN/F644, http://links.lww.com/JSN/F645, http://links.lww.com/JSN/F646, http://links.lww.com/JSN/F647.

Supplemental Methods

Supplemental Figure 1. Diabetic ZSF1 rats recapitulated phenotypic changes of DKD with marked disease improvement by enalapril treatment.

Supplemental Figure 2. Single-cell transcriptomic landscape of the diabetic ZSF1 rat.

Supplemental Figure 3. Cross-species cell type mapping of the ZSF1 rat kidney dataset to the Kidney Precision Medicine Project human kidney reference.

Supplemental Figure 4. Cell fraction changes.

Supplemental Figure 5. Differential proportion analysis.

Supplemental Figure 6. Tissue RAAS effector gene regulation by enalapril in ZSF1 rats.

Supplemental Figure 7. Differentially expressed genes Obese versus Lean.

Supplemental Figure 8. Differentially expressed genes Obese+enalapril versus Obese.

Supplemental Figure 9. Differential expression of RAAS effector genes in DKD and after enalapril treatment.

Supplemental Figure 10. Cathepsin D expression in the distal nephron and its regulation by enalapril.

Supplemental Figure 11. Cathepsin D expression in murine diabetic kidney single-cell and single-nuclear datasets.

Supplemental Figure 12. Distal nephron differentially expressed genes.

Supplemental Figure 13. Biologic processes along the distal nephron lineage tree.

Supplemental Figure 14. WGCNA of distal nephron.

Supplemental Figure 15. Myeloid cell subclustering and CITE-seq validation.

Supplemental Figure 16. WGCNA of myeloid cells, enrichment of Trem2+ residential macrophages in diabetic kidneys, and cell–cell interactions between distal nephron and myeloid cells.

Supplemental Figure 17. Differential proportion analysis of myeloid cells.

Supplemental Figure 18. Spatial relationship of CTSD+ distal nephron and TREM2+ residential macrophages.

Supplemental Figure 19. Deconvolution of human Control and DKD spatial transcriptomics with ZSF1 rat single-cell reference.

Supplemental Figure 20. Spatial deconvolution and TREM2/cathepsin D proximity.

Supplemental Figure 21. Ligand–receptor relationship of the distal nephron and TREM2+ residential macrophages.

Supplemental Figure 22. RAAS effector regulation in human DKD.

Supplemental Figure 23. RAAS effectors upregulated and downregulated in human DKD.

Supplemental Figure 24. RAAS effectors upregulated and downregulated in rat distal nephron.

Supplemental Data 1. DEGs all clusters (separate file).

Supplemental Data 2. Hierarchical replicability analysis (separate file).

Supplemental Data 3. DEGs obese versus lean (separate file).

Supplemental Data 4. DEGs obese+enalapril versus obese (separate file).

Supplemental Data 5. DEGs distal nephron (separate file).

Supplemental Data 6. DEGs along pseudotime distal nephron (separate file).

Supplemental Data 7. WGCNA distal nephron (separate file).

Supplemental Data 8. DEGs myeloid cells (separate file).

Supplemental Data 9. WGCNA myeloid cells (separate file).

Supplemental Data 10. DEGs spatial transcriptomics (separate file).

Supplemental Data 11. Baseline characteristics human cohort (separate file).

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PERMALINK

Single-Cell Resolution Drug Effects of Renin-Angiotensin-Aldosterone Blockade in ZSF1 Rat Diabetic Kidney Disease

Michael S Balzer

Jianfu Zhou

Amin Abedini

Ziyuan Ma

Yanjuan Hou

Tejaswini Yadav

Manuel Grundmann

Mira Pavkovic

Katalin Susztak

Visual Abstract

Abstract

Key Points

Background

Methods

Results

Conclusions

Introduction

Methods

ZSF1 Rat Model

Preparation of Rat Single-Cell Suspension

Single-Cell RNA-Seq Data Analysis

Spatial Transcriptomics Data Analysis

Bulk RNA-Seq Data Analysis

Results

RAAS Inhibition through Enalapril Ameliorated Hypertension, Proteinuria, and Kidney Fibrosis in the ZSF1 Rat Model of DKD

Figure 1.

The Single-Cell Transcriptomic Landscape of the Diabetic ZSF1 Rat Showed Immune Cell Enrichment and Endothelial and Tubular Cell Depletion

Figure 2.

Enalapril Downregulated Cathepsin D in Diabetic Distal Nephron and Myeloid Cells

Figure 3.

Ctsd+ Connecting Tubule Cells of the Distal Nephron Were Enriched in Diabetic Kidneys and Depleted on Enalapril Treatment

Figure 4.

Ctsd Was a Hub Gene for a Transitional Cell State Linking the Healthy Distal Nephron with Diabetic Injury Phenotypes

Ctsd as a Marker for Proinflammatory Trem2+ Residential Macrophages

Figure 5.

TREM2+ Residential Macrophages Were in Close Spatial Proximity to and Interacted Strongly with Distal Nephron Tubule Cells

Figure 6.

CTSD Was Particularly Enriched in Kidneys from DKD Patients and Correlated with Outcome-Relevant Parameters

Figure 7.

Discussion

Acknowledgments

Footnotes

Disclosures

Author Contributions

Funding

Declarative Statements

Data Availability Statements

Supplemental Material

References

Associated Data

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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