Microvascular pericytes and perivascular fibroblasts have recently been identified as the source of scar-producing myofibroblasts that appear after injury of the kidney. We show that cross talk between pericytes and endothelial cells concomitantly dictates development of fibrosis and loss of microvasculature after injury. When either platelet-derived growth factor receptor (R)-␤ signaling in pericytes or vascular endothelial growth factor (VEGF)R2 signaling in endothelial cells was blocked by circulating soluble receptor ectodomains, both fibrosis and capillary rarefaction were markedly attenuated during progressive kidney injury. Blockade of either receptor-mediated signaling pathway prevented pericyte differentiation and proliferation, but VEGFR2 blockade also attenuated recruitment of inflammatory macrophages throughout disease progression. Whereas injury down-regulated angiogenic VEGF164, the dys-angiogenic isomers VEGF120 and VEGF188 were up-regulated, suggesting that pericyte-myofibroblast differentiation triggers endothelial loss by a switch in secretion of VEGF isomers. These findings link fibrogenesis inextricably with microvascular rarefaction for the first time, add new significance to fibrogenesis, and identify novel therapeutic targets. (Am J Pathol 2011, 178:911-923;

Pericytes are the major source of scar-producing myofibroblasts following kidney injury; however, the mechanisms of this transition are unclear. To clarify this, we examined Collagen 1 (α1)-green fluorescent protein (GFP) reporter mice (pericytes and myofibroblasts express GFP) following ureteral obstruction or ischemia-reperfusion injury and focused on the role of platelet-derived growth factor (PDGF)-receptor (PDGFR) signaling in these two different injury models. Pericyte proliferation was noted after injury with reactivation of α-smooth muscle actin expression, a marker of the myofibroblast phenotype. PDGF expression increased in injured tubules, endothelium, and macrophages after injury, whereas PDGFR subunits α and β were expressed exclusively in interstitial GFP-labeled pericytes and myofibroblasts. When PDGFRα or PDGFRβ activation was inhibited by receptor-specific antibody following injury, proliferation and differentiation of pericytes decreased. The antibodies also blunted the injury-induced transcription of PDGF, transforming growth factor β1, and chemokine CCL2. They also reduced macrophage infiltration and fibrosis. Imatinib, a PDGFR tyrosine kinase inhibitor, attenuated pericyte proliferation and kidney fibrosis in both fibrogenic models. Thus, PDGFR signaling is involved in pericyte activation, proliferation, and differentiation into myofibroblasts during progressive kidney injury. Hence, pericytes may be a novel target to prevent kidney fibrosis by means of PDGFR signaling blockade.

Pericytes have been identified as the major source of precursors of scar-producing myofibroblasts during kidney fibrosis. The underlying mechanisms triggering pericyte-myofibroblast transition are poorly understood. Transforming growth factor β-1 (TGF-β1) is well recognized as a pluripotent cytokine that drives organ fibrosis. We investigated the role of TGF-β1 in inducing profibrotic signaling from epithelial cells to activate pericyte-myofibroblast transition. Increased expression of TGF-β1 was detected predominantly in injured epithelium after unilateral ureteral obstruction, whereas downstream signaling from the TGF-β1 receptor increased in both injured epithelium and pericytes. In mice with ureteral obstruction that were treated with the pan anti-TGF-β antibody (1D11) or TGF-β receptor type I inhibitor (SB431542), kidney pericyte-myofibroblast transition was blunted. The consequence was marked attenuation of fibrosis. In addition, epithelial cell cycle G2/M arrest and production of profibrotic cytokines were both attenuated. Although TGF-β1 alone did not trigger pericyte proliferation in vitro, it robustly induced α smooth muscle actin (α-SMA). In cultured kidney epithelial cells, TGF-β1 stimulated G2/M arrest and production of profibrotic cytokines that had the capacity to stimulate proliferation and transition of pericytes to myofibroblasts. In conclusion, this study identified a novel link between injured epithelium and pericyte-myofibroblast transition through TGF-β1 during kidney fibrosis.

Background: Cardiac surgery-associated acute kidney injury (CSA-AKI) is a major complication that results in increased morbidity and mortality after cardiac surgery. Most established prediction models are limited to the analysis of nonlinear relationships and fail to fully consider intraoperative variables, which represent the acute response to surgery. Therefore, this study utilized an artificial intelligence-based machine learning approach thorough perioperative data-driven learning to predict CSA-AKI. Methods: A total of 671 patients undergoing cardiac surgery from August 2016 to August 2018 were enrolled. AKI following cardiac surgery was defined according to criteria from Kidney Disease: Improving Global Outcomes (KDIGO). The variables used for analysis included demographic characteristics, clinical condition, preoperative biochemistry data, preoperative medication, and intraoperative variables such as time-series hemodynamic changes. The machine learning methods used included logistic regression, support vector machine (SVM), random forest (RF), extreme gradient boosting (XGboost), and ensemble (RF + XGboost). The performance of these models was evaluated using the area under the receiver operating characteristic curve (AUC). We also utilized SHapley Additive exPlanation (SHAP) values to explain the prediction model. Results: Development of CSA-AKI was noted in 163 patients (24.3%) during the first postoperative week. Regarding the efficacy of the single model that most accurately predicted the outcome, RF exhibited the greatest AUC (0.839, 95% confidence interval [CI] 0.772-0.898), whereas the AUC (0.843, 95% CI 0.778-0.899) of ensemble model (RF + XGboost) was even greater than that of the RF model alone. The top 3 most influential features in the RF importance matrix plot were intraoperative urine output, units of packed red blood cells (pRBCs) transfused during surgery, and preoperative hemoglobin level. The SHAP summary plot was used to illustrate the positive or negative effects of the top 20 features attributed to the RF. We also used the SHAP dependence plot to explain how a single feature affects the output of the RF prediction model.

Fibrosis of the peritoneal cavity remains a serious, life-threatening problem in the treatment of kidney failure with peritoneal dialysis. The mechanism of fibrosis remains unclear partly because the fibrogenic cells have not been identified with certainty. Recent studies have proposed mesothelial cells to be an important source of myofibroblasts through the epithelial-mesenchymal transition; however, confirmatory studies in vivo are lacking. Here, we show by inducible genetic fate mapping that type I collagen-producing submesothelial fibroblasts are specific progenitors of a-smooth muscle actin-positive myofibroblasts that accumulate progressively in models of peritoneal fibrosis induced by sodium hypochlorite, hyperglycemic dialysis solutions, or TGF-b1. Similar genetic mapping of Wilms' tumor-1-positive mesothelial cells indicated that peritoneal membrane disruption is repaired and replaced by surviving mesothelial cells in peritoneal injury, and not by submesothelial fibroblasts. Although primary cultures of mesothelial cells or submesothelial fibroblasts each expressed a-smooth muscle actin under the influence of TGF-b1, only submesothelial fibroblasts expressed a-smooth muscle actin after induction of peritoneal fibrosis in mice. Furthermore, pharmacologic inhibition of the PDGF receptor, which is expressed by submesothelial fibroblasts but not mesothelial cells, attenuated the peritoneal fibrosis but not the remesothelialization induced by hypochlorite. Thus, our data identify distinctive fates for injured mesothelial cells and submesothelial fibroblasts during peritoneal injury and fibrosis.