International Journal of Molecular Sciences
Article Follistatin-Like-1 (FSTL1) Is a Fibroblast-Derived Growth Factor That Contributes to Progression of Chronic Kidney Disease
Nicholas A. Maksimowski 1,*, Xuewen Song 2, Eun Hui Bae 3 , Heather Reich 2,4, Rohan John 4,5,6, York Pei 1,2,4, James W. Scholey 1,2,4,6,7 and Nephrotic Syndrome Study Network (NEPTUNE) †
1 Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A8, Canada; [email protected] (Y.P.); [email protected] (J.W.S.) 2 Division of Nephrology, University Health Network, Toronto, ON M5G 2C4, Canada; [email protected] (X.S.); [email protected] (H.R.) 3 Departments of Internal Medicine, Chonnam National University Medical School, Gwangju 61469, Korea; [email protected] 4 Toronto General Hospital Research Institute, University Health Network, Toronto, ON M5G 2C4, Canada; [email protected] 5 Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON M5G 2C4, Canada 6 Department of Pathology, University Health Network, Toronto, ON M5G 2C4, Canada 7 Department of Physiology, University of Toronto, Toronto, ON M5G 2C4, Canada * Correspondence: [email protected] † Membership of Nephrotic Syndrome Study Network (NEPTUNE) is provided in the Acknowledgments. Abstract: Our understanding of the mechanisms responsible for the progression of chronic kidney Citation: Maksimowski, N.A.; disease (CKD) is incomplete. Microarray analysis of kidneys at 4 and 7 weeks of age in Col4a3-/- mice, a Song, X.; Bae, E.H.; Reich, H.; John, R.; model of progressive nephropathy characterized by proteinuria, interstitial fibrosis, and inflammation, Pei, Y.; Scholey, J.W.; Nephrotic revealed that Follistatin-like-1 (Fstl1) was one of only four genes significantly overexpressed at Syndrome Study Network 4 weeks of age. mRNA levels for the Fstl1 receptors, Tlr4 and Dip2a, increased in both Col4a-/- mice (NEPTUNE). Follistatin-Like-1 and mice subjected to unilateral ureteral obstruction (UUO). RNAscope® (Advanced Cell Diagnostics, (FSTL1) Is a Fibroblast-Derived Fstl1 Growth Factor That Contributes to Newark CA, USA) localized to interstitial cells, and in silico analysis of single cell transcriptomic Progression of Chronic Kidney data from human kidneys showed Fstl1 confined to interstitial fibroblasts/myofibroblasts. In vitro, Disease. Int. J. Mol. Sci. 2021, 22, 9513. FSTL1 activated AP1 and NFκB, increased collagen I (COL1A1) and interleukin-6 (IL6) expression, https://doi.org/10.3390/ and induced apoptosis in cultured kidney cells. FSTL1 expression in the NEPTUNE cohort of ijms22179513 humans with focal segmental glomerulosclerosis (FSGS), membranous nephropathy (MN), and IgA nephropathy (IgAN) was positively associated with age, eGFR, and proteinuria by multiple linear Academic Editor: Andrea Huwiler regression, as well as with interstitial fibrosis and tubular atrophy. Clinical disease progression, defined as dialysis or a 40 percent reduction in eGFR, was greater in patients with high baseline Received: 4 August 2021 FSTL1 mRNA levels. FSTL1 is a fibroblast-derived cytokine linked to the progression of experimental Accepted: 26 August 2021 and clinical CKD. Published: 1 September 2021
Keywords: kidney; FSTL1; fibrosis; inflammation; cytokines; apoptosis; nephrotic syndrome Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. 1. Introduction The prevalence and progression of chronic kidney disease (CKD) remains a global clinical challenge, and the development of end stage kidney disease is a costly outcome re- quiring therapies like dialysis and kidney transplantation. This underscores the important Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. need to develop new and effective treatments to lessen the burden of CKD, but we require This article is an open access article a better understanding of the pathogenesis of CKD progression in order to identify new distributed under the terms and targets for therapy [1]. conditions of the Creative Commons The decline in glomerular filtration in CKD, including diseases that affect the kidney Attribution (CC BY) license (https:// glomerulus, is associated with pathology in the kidney tubulointerstitium. These changes creativecommons.org/licenses/by/ include interstitial inflammation and fibrosis, loss of the peritubular capillary network 4.0/). and loss of tubular epithelial cell number and volume, recognized as tubular atrophy [1,2].
Int. J. Mol. Sci. 2021, 22, 9513. https://doi.org/10.3390/ijms22179513 https://www.mdpi.com/journal/ijms Int. J. Mol. Sci. 2021, 22, 9513 2 of 38
Indeed, tubulointerstitial fibrosis strongly correlates with GFR decline in a number of kidney diseases including glomerulopathies [3]. Blockade of the renin angiotensin system remains the first line approach to limiting progression of CKD and reducing end stage kidney disease (ESKD), especially in the setting of proteinuria, while new data suggest that the use of sodium glucose co-transport-2 (SGLT2) inhibitors may affect progression broadly, and this is an active area of ongoing investigation [4]. There remains an unmet need for new and targeted therapies to slow the progression of CKD towards ESKD. In order to identify new treatment targets for CKD, we studied Col4a3-/- mice with homozygous deletion of the gene that encodes the a3 chain of collagen IV. Mutations in genes encoding the a3.a4.a5 collagen IV network led to glomerular basement membrane (GBM) structural abnormalities that occur at the time of the normal molecular switch from the a1.a2.a1 collagen IV to the mature collagen IV. This change in basement membrane proteins leads to depletion of podocytes, progressive glomerular sclerosis, tubulointerstitial inflammation and fibrosis, and the development of kidney failure [5,6]. Although devel- oped as a model of Alport Syndrome, the disease phenotype re-capitulates classic features of proteinuric CKD in humans. In this regard, recent clinical studies have implicated collagen IVa3 in the pathogenesis of some forms of focal segmental glomerulosclerosis and in the pathogenesis of diabetic nephropathy [5,7]. We performed unbiased global gene-expression profiling in kidneys of Col4a3-/- and wild-type (WT) mice at 4 and 7 weeks of age. Surprisingly, we identified only four dif- ferentially expressed genes in 4 week old mice. Follistatin-like-1 (Fstl1) was one of the genes, and the early increase in expression persisted through to 7 weeks of age. Studies have implicated FSTL1 in lung development and fibrosis, as well as cardiac injury, but information about its role in the pathogenesis of experimental CKD is incomplete [8–11]. Moreover, there are no studies of FSTL1 in humans with CKD associated with proteinuria. In the current report, we sought to address this gap. We studied the expression and localization of FSTL1 in Col4a3-/- mice, and related expression to genes implicated in kidney fibrosis, inflammation, and apoptosis. We also studied the effect of FSTL1 on cultured human kidney cells, and then extended the work to mice with unilateral ureteral obstruction. Finally, we utilized human transcriptomic data as well as functional and structural data from the NEPTUNE Consortium to determine if FSTL1 expression relates to kidney function, interstitial fibrosis, and progression of CKD in humans.
2. Results 2.1. Breeding Strategy for Col4a3-/- Mice and Experimental Design We generated Col4a3-/- (KO) and Col4a3+/+ (WT) male mice, and studied gene expres- sion in whole kidneys from 4 and 7 week old mice (Figure1A). Body weights and kidney weights were similar in the two groups at 4 and 7 weeks of age. KO mice exhibited a 3-fold increase in the urinary albumin excretion rate (UalbV) at 4 weeks of age (p < 0.05). The UalbV continued to increase in the KO mice, reaching a 7-fold increase at 7 weeks of age (Table1). Figure2 shows light micrographic images of kidneys from WT mice and Col4a3-/- mice (at 7 weeks of age). Panel A shows PAS-stained sections of glomeruli and tubules from WT mice and Col4a3-/- mice and Masson Trichome (MTC) stains to show interstitial fibrosis (green in lower right panel). Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 3 of 41 Int. J. Mol. Sci. 2021, 22, 9513 3 of 38
A
B
Figure 1. Schematic diagram summarizing experimental workflow. (A) breeding strategy for generating experimental groups for analysis. (B) Whole kidney samples from 4 and 7 week old wild type (WT) and Col4a3-/- (KO) mice were Figure 1. Schematic diagram summarizing experimental workflow. (A) breeding strategy for generating experimental subjected to microarray expression profiling. groups for analysis. (B) Whole kidney samples from 4 and 7 week old wild type (WT) and Col4a3–/– (KO) mice were subjected to microarray expression profiling.
Table 1. Clinical characteristic for Alport and wild-type mice.
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4 Weeks 7 Weeks
WT (n = 8) KO (n = 8) WT (n = 8) KO (n = 8)
Int. J. Mol. Sci. 2021, 22, 9513 Body weight (g) 16.63 ± 0.74 17.60 ± 0.46 21.17 ± 0.50 19.51 ± 0.934 of 38 LKW(g)/BW (Kg) 7.08 ± 0.17 7.61 ± 0.33 7.43 ± 0.18 8.82 ± 0.17 RKW(g)/BW (Kg) 7.08 ± 0.17 7.69 ± 0.31 7.69 ± 0.07 8.84 ± 0.21 PTableCr (μMol/L) 1. Clinical characteristic16.80 for Alport ± 1.32 and wild-type16.00 ± 1.00 mice. 18.25 ± 1.65 35.80 ± 14.06 UalbV (mg/dl) 20.45 ± 2.25 65.66 ± 6.33 20.14 ± 1.45 144.31 ± 12.84 4 Weeks 7 Weeks Body weight, left kidney weight to body weight ratio, right kidney weight to body weight ratio, protein creatinine, and urinary albuminWT (n = levels 8) for KO4 and (n 7= week 8) old WTwild ( ntype= 8) (WT) and KO Col4a3 (n = 8)–/– (KO)Body mice weight (values (g) are mean ± SEM). 16.63 ± 0.74 17.60 ± 0.46 21.17 ± 0.50 19.51 ± 0.93 LKW(g)/BW (Kg) 7.08 ± 0.17 7.61 ± 0.33 7.43 ± 0.18 8.82 ± 0.17 RKW(g)/BWFigure 2 shows (Kg) light micrographic 7.08 ± 0.17 images 7.69 ±of0.31 kidneys from 7.69 ± WT0.07 mice and 8.84 Col4a3± 0.21 –/– µ ± ± ± ± micePCr (at( Mol/L) 7 weeks of age). Panel 16.80 A shows1.32 PAS 16.00-stained1.00 sections 18.25 of glomerul1.65i 35.80 and tubules14.06 UalbV (mg/dl) 20.45 ± 2.25 65.66 ± 6.33 20.14 ± 1.45 144.31 ± 12.84 from WT mice and Col4a3–/– mice and Masson Trichome (MTC) stains to show interstitial Body weight, left kidney weight to body weight ratio, right kidney weight to body weight ratio, protein creatinine, fibrosisand urinary (green albumin in lower levels for right 4 and panel). 7 week old wild type (WT) and Col4a3-/- (KO) mice (values are mean ± SEM).
Figure 2. Comparisons of the Kidney Tissue Morphology of Kidney of WT and Col4a3-/- mice. Images from glomerulus Figure(left) and 2. Comparisons tubulointerstitium of the (right) Kidney are Tissue presented. Morphology Periodic of Acid Kidney Schiff of staining WT and (PAS); Col4a3 Masson’s–/– mice. Images trichrome from staining glomerulus (MTC). (lIneft)Col4a3 and tubulointerstitium-/- mice, crescents (right) are packing are presented. the Bowman’s Periodic space Acid (redSchiff arrows). staining Detachment(PAS); Masson’s of tubular trichrome epithelial staining cells (MTC). from Inbasement Col4a3–/– membrane mice, crescents (red arrowheads), are packing tubularthe Bowman’s cast (red space asterisks), (red arrows). and collagen Detachment deposits (blackof tubular arrows) epithelial are also cells indicated. from basementScale bars, membra 50 µm.ne (red arrowheads), tubular cast (red asterisks), and collagen deposits (black arrows) are also indicated. Scale bars, 50 μm. The molecular switch from the immature collagen IV network (a1a2a1) to the mature collagenThe molecular IV network switch (a3a4a5) from is evidentthe immature in the heatcollagen map IV of collagennetwork gene(a1a2 expressiona1) to the mature at 4 and collagen7 weeks IV of network age in the (aCol4a33a4a5)-/- is (KO)evident and inCol4a3 the heat+/+ map(WT) of mice collagen (Figure gene3A). expression At 7 weeks at of4 andage 7Col4a3 weeksand of ageCol4a4 in thewere Col4a3 more–/– highly (KO) and expressed Col4a3 than+/+ (WT)Col4a1 miceand (FigureCol4a2 3A).in the At Col4a37 weeks+/+ ofmice, age butCol4 thea3 persistenceand Col4a4 ofwere Col4a1 more and highly Col4a2 expressed expression than is evident Col4a1in and the Col4Col4a3a2 -/-in mice the Col4a3while+/+ levels mice, of butCol4a3 the persistence, Col4a4, Col4a5 of Col4anda1 Col4a2and Col4area2 down-regulated expression is evident (Figure in 3theB–G). Col4a3 The– /–decrease mice while in mRNAlevels of levels Col4a for3, Col4Col4a3a4, isCol4 expecteda5 and Col4 but ita2 is are interesting down-regulated to note that(Figure deletion 3B– G).of theThe genedecrease for Col4a3in mRNAleads levels to reduced for Col4 expressiona3 is expected of Col4a4 but it isand interestingCol4a5 relative to note to that the deletionCol4a3+/+ of micethe gene (Figure for 3ColE,F).4a3 leads to reduced expression of Col4a4 and Col4a5 relative to the ThereCol4a3 were+/+ mice five (Figure genes differentially3E,F). expressed in Col4a3-/- mice compared to Col4a3+/+ mice at 4 weeks of age. These five genes were identified using Significance Analysis of Microarrays (SAM) and a FDR of <1% (Figure4). Expression levels at both 4 weeks (Figure5A–F ) and 7 weeks (Figure5G–K) of age are depicted in Figure5. As expected, Col4a3 mRNA levels were lower in Col4a3-/- mice compared to Col4a3+/+ mice (Figure5A ) while Zfp747, a zinc finger transcription factor, was also decreased in the kidneys of 4 week old Col4a3-/- mice (Figure5F). The expression of Follistatin-like 1 ( Fstl1), Microfibril Int. J. Mol. Sci. 2021, 22, 9513 5 of 38
associated protein 4 (Mfap4), and Caldesmon 1 (Cald1) were all increased in Col4a3-/- mice compared to Col4a3+/+ mice at 4 weeks of age (Figure5C–E) and the differential expression was also present at 7 weeks of age (Figure5H–J). FSTL1 is an extracellular growth factor. MFAP4 is an extracellular protein implicated in cell-matrix interactions and it binds to collagen. CALD1 is an intracellular protein that binds actin and may regulate cell contraction. It is tempting to speculate that these later two up-regulated genes may serve to help stabilize the immature collagen network that persists in the Col4a3-/- mice and facilitate the structural integrity of the glomerular podocyte. As a start, we focused on Fstl1. We performed Western blot analyses of the kidneys of 4 and 7 week old WT and Col4a3 KO mice (Figure6). There was a significant increase in the protein expression of FSTL1 at 4 and 7 weeks of age. The magnitude of change was less in the mice at 4 weeks of age, as Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEWexpected from our mRNA analyses. FSTL1 is a secreted glycoprotein protein. As such,5 of the 41 glycosylation state plays a role in its molecular weight [12]. Therefore, both bands were used to quantify FSTL1 expression. The findings are concordant with our mRNA analyses.
FigureFigure 3. 3. MicroarrayMicroarray expression expression of of collagen collagen 4 4 alpha alpha 1 1-6.-6. ( (AA)) Heatmap Heatmap with with unsupervised unsupervised hierarchical hierarchical cluster cluster analysis analysis of of col4col4 genes genes in in kidneys kidneys of of 4 4 and and 7 7 we weekek old Col4a3–-/-/– andand wild wild-type-type mice mice ( (nn == 8 8 per per group). group). Each Each column column reflects reflects a a kidney kidney sample,sample, and and each each row row represents represents an an individual individual gene. gene. Red Red and and blue blue color color intensities intensities correlate correlate with with the the scaled scaled up up-regulation-regulation andand downregulation downregulation of of the the gene, gene, respectively. respectively. (B (B––GG) )Graphical Graphical representation representation of of microarray microarray expression expression from from panel panel A. A. ValuesValues are mean ± SEM.SEM. Pp valuesvalues were were determined determined by by 1 1-way-way ANOVA. ANOVA. * p value < 0 0.05..05. ** ** pp valuevalue < < 0 0.01..01. *** *** pp valuevalue < < 0 0.001..001. ******** pp valuevalue < < 0 0.0001..0001.
There were five genes differentially expressed in Col4a3–/– mice compared to Col4a3+/+ mice at 4 weeks of age. These five genes were identified using Significance Analysis of Microarrays (SAM) and a FDR of <1% (Figure 4). Expression levels at both 4 weeks (Figure 5A–F) and 7 weeks (Figure 5G–K) of age are depicted in Figure 5. As expected, Col4a3 mRNA levels were lower in Col4a3–/– mice compared to Col4a3+/+ mice (Figure 5A) while Zfp747, a zinc finger transcription factor, was also decreased in the kidneys of 4 week old Col4a3−/− mice (Figure 5F). The expression of Follistatin-like 1 (Fstl1), Microfibril associated protein 4 (Mfap4), and Caldesmon 1 (Cald1) were all increased in Col4a3–/– mice compared to Col4a3+/+ mice at 4 weeks of age (Figure 5C–E) and the differential expression was also present at 7 weeks of age (Figure 5H–J). FSTL1 is an extracellular growth factor. MFAP4 is an extracellular protein implicated in cell-matrix interactions and it binds to collagen. CALD1 is an intracellular protein that binds actin and may regulate cell contraction. It is tempting to speculate that these later two up-regulated genes may serve to help stabilize the immature collagen network that persists in the Col4a3–/– mice and facilitate the structural integrity of the glomerular podocyte. As a start, we focused on Fstl1.
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Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 6 of 41 Int. J. Mol. Sci. 2021, 22, 9513 6 of 38
FigureFigure 4. 4. DifferentialDifferential Gene ExpressionExpression inin WT WT vs. vs. KO KO mice mice at at 4 Weeks4 Weeks of Age.of Age. Explanation Explanation of the of statisticalthe statistical parameters parameters used Figureusedto identify to 4.identify Differential the 5 the differently 5 differentlyGene expressedExpression expressed genes in WT genes at vs. 4 weeks atKO 4 weeks mice of age at of in 4age Weeks WT in vs. WT of KO vs.Age. mice. KO Explanation mice. of the statistical parameters used to identify the 5 differently expressed genes at 4 weeks of age in WT vs. KO mice.
Figure 5. Microarray expression of genes differentially expressed at 4 and 7 weeks of age. (A) Heatmap with unsupervised Figure 5. Microarray expression of genes differentially expressed at 4 and 7 weeks of age. (A) Heatmap with unsupervised -/- Figurehierarchicalhierarchical 5. Microarray cluster cluster analysis analysis expression of of the the of five fivegenes genes differentially that were expresseddifferentially at 4 expressedand 7 weeks atat4 4of weeksweeks age. (A ofof) ageHeatmapage inin thethe with kidneyskidneys unsupervised ofofCol4a3 Col4a3– -/- hierarchical/–mice. mice. The The analysis clusteranalysis showsanalysis shows the ofthe gene the gene five expression expres genession that inkidneys inwere kidneys differentially of 4 of and 4 7and week expressed 7 week old Col4a3 old at 4Col4a3 weeksand–/– wild-type ofand age wild in the mice-type kidneys (nmice= 8 perof(n Col4a3= group). 8 per– /group).–( Bmice.–F) Graphical The(B–F analysis) Graphical representation shows representation the gene of mRNA expression of mRNA levels in inlevels kidneys 4 week in 4 oldof week 4 wildand old 7 type weekwild mice typeold versus Col4a3mice versus 4–/– week and 4wild-type old weekCol4a3 old mice -/-Col4a3mice. (n –/=– (mice.8G per–K ) group).(GraphicalG–K) Graphical (B– representationF) Graphical representation representation of microarray of microarray of expression mRNA expression levels in 7 week inin 47 weekwe oldek wild old wildwild type type versustype versus mice 7 week versus 7 week old 4 Col4a3old week Col4a3 -/-oldmice. –Col4a3/– mice. Values– /Values– mice. are (aremeanG– meanK) ±GraphicalSEM, ± SEM, and representationand significance significance wasof wasmicroarray defined defined as expression as a p avalue p value of in Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 7 of 41 As such, the glycosylation state plays a role in its molecular weight [12]. Therefore, both Int. J. Mol. Sci. 2021, 22, 9513 bands were used to quantify FSTL1 expression. The findings are concordant with7 of our 38 mRNA analyses. FigureFigure 6.6.FSTL1 FSTL1 ProteinProtein ExpressionExpression inin WTWT andand KOKO mousemouse kidney.kidney. ( A(A)) Representative Representative immunoblot immunoblot andand quantification quantification ofof FSTL1FSTL1 inin 4 4 week week WT WT and and KO KO mouse mouse kidney. kidney. (B )(B Representative) Representative immunoblot immunoblot and and quantification quantification of FSTL1 of FSTL1 in 7 weekin 7 week WT andWT KOand mouse KO mouse kidney. kidney. Values Values are the meanare the± meanSEM (black ± SEM bars). (blackp values bars). werep values determined were determined by Student’s byt tests, Student’s and significance t tests, and wassignificance defined aswas a p definedvalue < as 0.05. a p value < 0.05. 2.2.2.2. LocalizationLocalization ofof Fstl1Fstl1 inin thethe KidneyKidney ® ToTo identify identify the the cellular cellular origin origin of FSTL1 of FSTL1 expression expression we first we used first RNAscope used RNAscope® to localize to –/– +/+ Fstl1localizein 7Fstl1 week in old7 weekCol4a3 old-/- Col4a3and Col4a3 and+/+ Col4a3mice. Figuremice. Figure7A shows 7A shows representative representative light +/+ micrographs.light micrographs. Very Very little little expression expression was was identified identified inthe in theCol4a3 Col4a3+/+ mice mice but but in in accordaccord withwith the the microarray microarray analysis, analysis, therethere was was a a marked marked increase increase in in Fstl1Fstl1 expressionexpression in in the the kidneyskidneys of the 7 week old old Col4a3Col4a3–-/-/– mice.mice. The The cells cells expressing expressing Fstl1Fstl1 werewere present present in the in thekidney kidney cortex cortex and anduniformly uniformly in the in interstitial the interstitial space, space, either either in capillary in capillary endothel endothelialial cells, cells,pericytes, pericytes, or resident or resident interstitial interstitial fibroblasts. fibroblasts. We then We studied then studied publicly publicly available available single singlesingle- single-cellcell RNA RNA sequencing sequencing (scRNA (scRNA-seq)-seq) data data from from human human kidneys kidneys with with transplant transplant nephropathy.nephropathy.Figure Figure7B–E 7B–Eshows show thiss this analysis. analysis.Fstl1 Fstl1expression expression localized localized to fibroblasts to fibroblasts and myofibroblastsand myofibroblasts in the in kidney, the kidney, with very with little very expression little expression in pericytes in pericytes or endothelial or endothelial cells in thiscells human in this dataset.human dataset. 2.3. Expression of Cognate Receptors for FSTL1 in the Kidney FSTL1 signal transduction involves three receptor proteins: TLR4, CD14 and DIP2A. This led us to examine expression levels of these putative cognate receptors. As illustrated in the heat map and analyses in Figure8A, we identified transcript levels for all three proteins. Expression levels of Tlr4 and Cd14 are significantly higher in the kidneys of 4 and 7 week old Col4a3-/- mice compared to Col4a3+/+ mice (Figure8D,E,H,I). There was no significant increase in Dip2a expression at either time point (Figure8C,G). AP1 is a transcription factor that is a dimer of a family of proteins and the most classical dimer is composed of the proteins FOS and JUN, characterized as early response genes. We utilized a list of genes for proteins of the AP1 family [13] and then performed an unsupervised hierarchical cluster analysis of AP1 gene expression in the kidneys of our mice. Figure9 depicts the expression levels of these genes. There is a generalized but not universal upregulation of the expression of these AP1 genes at 7 weeks of age in the Col4a3 KO mice. Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 8 of 41 Int. J. Mol. Sci. 2021, 22, 9513 8 of 38 A B C D E Figure 7. Fstl1 expression localization in the kidney. (A) Light microscopic images at three magnifications of RNAscope® FigureFstl1 localization 7. Fstl1 expression in wild localization type mice (upper in the kidney. three panels) (A) Light and microscopicCol4a3-/- mice images (lower at threethree panels).magnifications (B–E) Cellof RNAscope Clustering® Fstl1and localizationFstl1 expression in wild from type the mice Kidney (upper Interactive three panels) Transcriptomics and Col4a3−/− (KIT),mice (lower human three rejecting panels). kidney (B–E) allograft Cell Clustering biopsy and cells Fstl1(http://humphreyslab.com/SingleCell expression from the Kidney Interactive, accessed Transcriptomics on 15 March 2021). (KIT), human rejecting kidney allograft biopsy cells (http://humphreyslab.com/SingleCell, 15 March 2021). 2.3. Expression of Cognate Receptors for FSTL1 in the Kidney FSTL1 signal transduction involves three receptor proteins: TLR4, CD14 and DIP2A. This led us to examine expression levels of these putative cognate receptors. As illustrated in the heat map and analyses in Figure 8A, we identified transcript levels for all three Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 9 of 41 Int. J. Mol. Sci. 2021, 22, 9513 proteins. Expression levels of Tlr4 and Cd14 are significantly higher in the kidneys of 4 9 of 38 and 7 week old Col4a3–/– mice compared to Col4a3+/+ mice (Figure 8D–E,H–I). There was no significant increase in Dip2a expression at either time point (Figure 8C,G). Figure 8. Fstl1Figureand 8. Fstl1 cognate and cognate receptor receptor expression. expression. ((AA)) Heatmap with with unsupervised unsupervised hierarchical hierarchical cluster analysis cluster of Fstl1 analysis, of Fstl1, –/– Dip2a, Cd14, and Tlr4 genes in kidneys of 4 and 7 week old Col4a3 -/-and wild-type mice (n = 8 per group). (B–E) Graphical Dip2a, Cd14representation, and Tlr4 genes of microarray in kidneys expression of 4 and in 74 weekweek old old wildCol4a3 type versusand wild-type4 week old miceCol4a3 (–n/– =mice. 8 per (F– group).I) Graphical (B– E) Graphical representationrepresentation of microarray of microarray expression expression in in 47 week week old old wild wild type versus type 7 versus week old 4 Col4a3 week–/– mice. old Col4a3Values are-/- meanmice. ± SEM, (F– I) Graphical and significance was defined as a p value of < 0.05 by Student’s t tests. -/- ± representationInt. J. Mol. of Sci. microarray 2021, 22, x FOR expression PEER REVIEW in 7 week old wild type versus 7 week old Col4a3 mice. Values are mean10 of 41 SEM, and significance was defined as a p valueAP1 of is a< transcription0.05 by Student’s factor t thattests. is a dimer of a family of proteins and the most classical dimer is composed of the proteins FOS and JUN, characterized as early response genes. We utilized a list of genes for proteins of the AP1 family [13] and then performed an unsupervised hierarchical cluster analysis of AP1 gene expression in the kidneys of our mice. Figure 9 depicts the expression levels of these genes. There is a generalized but not universal upregulation of the expression of these AP1 genes at 7 weeks of age in the Col4a3 KO mice. Figure 9. AP1Figure Heatmap. 9. AP1 Heatmap. (A) Heatmap (A) Heatmap with with unsupervised unsupervised hierarchical hierarchical cluster cluster analysis analysis of AP1 genes of AP1 in kidneys genes of in 4 kidneysand 7 of 4 and –/– 7 week old Col4a3week old-/- Col4a3and wild-type and wild-type mice mice (n (=n 8= 8 per per group).group). 2.4. p42/44 MAPK and Activator Protein 1 (AP1) Signaling in Response to rhFSTL1 We have previously implicated tubular epithelial cells, mainly of the proximal tubule and collecting duct, as well as interstitial fibroblasts in the progression of chronic kidney disease in Col4a3–/– mice [5,6]. We therefore chose to study the effect of FSTL1 on p42/p44 MAPK phosphorylation and AP1-mediated gene expression in HK2 cells. Treatment with rhFSTL1 led to time-dependent phosphorylation of p42/44 MPAK (ERK) (Figure 10A,B). Biopsies from patients with fibrotic conditions, including kidney fibrosis, showed higher levels of nuclear AP1 transcription factors, while activation of AP1 can lead to interstitial fibrosis in several organs. Next, we studied the effect of rhFSTL1 on AP1 activation in kidney epithelial HK2 cells. We transfected HK2 cells with an AP1 luciferase reporter plasmid and measured promoter activity in response to rhFSTL1 stimulation. Treatment with rhFSTL1 was associated with 2 to 3-fold activation of AP1-mediated gene expression, as assessed by luciferase activity (p < 0.0006) (Figure 10C). Connie and coworkers defined a set of 17 genes regulated by AP1. We studied the expression of this AP1 signature in the 4 and 7 week old Col4a3–/– and Col4a3+/+ mice. The heat map in Figure 10D illustrates the gene expression pattern. The majority of genes in the AP1 signature are up-regulated in 7 week old Col4a3–/– mice compared to Col4a3+/+ mice, and the magnitude of the changes in a selected set of these genes (Hbegf, Plaur, Mmp10, and Ilr1) is shown in Figure 10E–H. Finally, we related Fstl1 expression to the expression of four of these genes that are key fibrosis-associated genes, namely, alpha smooth muscle actin (Acta2) (r = 0.84, p < 0.0085) (Figure 10I), transforming growth factor beta 1 (Tgfb1) (r = 0.96, p < 0.001) (Figure 10J), collagen 1a1 (Col1a1) (r = 0.90, p < 0.0025) (Figure 10K), and fibronectin-1 (Fn1) (r = 0.97, p < 0.0001) (Figure 10L) by qPCR. Int. J. Mol. Sci. 2021, 22, 9513 10 of 38 2.4. p42/44 MAPK and Activator Protein 1 (AP1) Signaling in Response to rhFSTL1 We have previously implicated tubular epithelial cells, mainly of the proximal tubule and collecting duct, as well as interstitial fibroblasts in the progression of chronic kidney disease in Col4a3-/- mice [5,6]. We therefore chose to study the effect of FSTL1 on p42/p44 MAPK phosphorylation and AP1-mediated gene expression in HK2 cells. Treatment with rhFSTL1 led to time-dependent phosphorylation of p42/44 MPAK (ERK) (Figure 10A,B). Biopsies from patients with fibrotic conditions, including kidney fibrosis, showed higher levels of nuclear AP1 transcription factors, while activation of AP1 can lead to interstitial fibrosis in several organs. Next, we studied the effect of rhFSTL1 on AP1 activation in kidney epithelial HK2 cells. We transfected HK2 cells with an AP1 luciferase reporter plasmid and measured promoter activity in response to rhFSTL1 stimulation. Treatment with rhFSTL1 was associated with 2 to 3-fold activation of AP1-mediated gene expression, as assessed by luciferase activity (p < 0.0006) (Figure 10C). Connie and coworkers defined a set of 17 genes regulated by AP1. We studied the expression of this AP1 signature in the 4 and 7 week old Col4a3-/- and Col4a3+/+ mice. The heat map in Figure 10D illustrates the gene expression pattern. The majority of genes in the AP1 signature are up-regulated in 7 week old Col4a3-/- mice compared to Col4a3+/+ mice, and the magnitude of the changes in a selected set of these genes (Hbegf, Plaur, Mmp10, and Ilr1) is shown in Figure 10E–H. Finally, we related Fstl1 expression to the expression of four of these genes that are key fibrosis-associated genes, namely, alpha smooth muscle actin (Acta2)(r = 0.84, p < 0.0085) (Figure 10I), transforming growth factor beta 1 (Tgfb1)(r = 0.96, p < 0.001) (Figure 10J), collagen 1a1 (Col1a1)(r = 0.90, p < 0.0025) (Figure 10K), and fibronectin-1 (Fn1)(r = 0.97, p < 0.0001) (Figure 10L) by qPCR. 2.5. p38 MAPK and NFκB Signaling in Response to Fstl1 We have also implicated infiltrating inflammatory cells and cytokines in the progres- sion of chronic kidney disease in Col4a3-/- mice. Since MAPKs, including p38, promote inflammation, we explored activation of p38 by rhFSTL1 in HK2 cells. We first studied the effect of rhFSTL1 on p38 MAPK phosphorylation. Treatment with rhFSTL1 led to time-dependent phosphorylation of p38 MAPK (Figure 11A). We next studied the effect of rhFSTL1 on NFκB activation in kidney epithelial HK2 cells. We transfected HK2 cells with an NFκB luciferase reporter plasmid and measured promoter activity in response to rhFSTL1 stimulation. rhFSTL1 was associated with a 2-fold activation of NFκB-mediated gene expression, as assessed by luciferase activity (p < 0.0047) (Figure 11B). Pahl and coworkers assembled a list of 113 genes regulated by NFκB. We studied the expression of this NFκB signature in the 4 and 7 week old Col4a3-/- and Col4a3+/+ mice. The heat map in Figure 11C illustrates the gene expression pattern that emerged from this unsuper- vised hierarchical analysis. The majority of genes in the NFκB signature are up-regulated in 7 week old Col4a3-/- mice compared to Col4a3+/+ mice. The expression levels of Il6 (p = 0.003)(Figure 11D), Ccl2 (p = 0.003) (Figure 11E), Icam1 (p = 0.003) (Figure 11F), and Vcam1 (p = 0.003) (Figure 11G) were significantly greater in 7 week old Col4a3-/- mice than in Col4a3+/+ mice. Finally, we related Fstl1 expression levels to the expression of 2 of these genes that are important inflammation-associated genes, namely, monocyte chemoattractant proptein-1 or Ccl2 (r = 0.89, p < 0.0028) (Figure 11H) and Tnfa (r = 0.90, p < 0.0022) (Figure 11I) by qPCR. Western blot analysis showed that rhFSTL1 increased COL1A1 (p = 0.0034) and COX2 protein expression in HK2 cells (p = 0.0087) (Figure 12B). Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 11 of 41 Int. J. Mol. Sci. 2021, 22, 9513 11 of 38 A ** ** B 1 . 5 ** C ** * * K 1 . 0 R E - t / k R E - 0 . 5 p 0 . 0 0 5 1 0 3 0 6 0 1 2 0 M i n u t e s D E H b e g f F P la u r G M m p 1 0 H Il1 rl1 8 .0 7 .0 7 .0 9 .5 0.1237 <0.0001 0.0003 <0.0001 6 .5 7 .5 6 .5 n n n n o o 9 .0 o i o i i i s s s 6 .0 s s s s s e e e 7 .0 6 .0 e r r r r p p p p 5 .5 x x 8 .5 x x E E E E 6 .5 5 .5 2 2 2 2 5 .0 g g g g o o o o L L 8 .0 L L 6 .0 5 .0 4 .5 7 .5 5 .5 4 .5 4 .0 W T K O W T K O W T K O W T K O 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k I F s t l 1 v s A c t a 2 J F s t l 1 v s T g f b 1 K F s t l 1 v s C o l 1 a 1 L F s t l 1 v s F n 1 1 3 . 0 9 . 5 1 0 . 0 1 3 9 . 5 1 2 . 5 9 . 0 1 2 9 . 0 1 1 2 . 0 1 2 a 1 a b 1 t f n 8 . 5 l 8 . 5 1 1 c g F o A T 1 1 . 5 C 8 . 0 8 . 0 1 0 1 1 . 0 r 0.9662 r 0.8431 7 . 5 r 0.8967 r 0.9693 P (two-tailed) 0.0085 P (two-tailed) <0.0001 P (two-tailed) 0.0025 P (two-tailed) <0.0001 1 0 . 5 7 . 5 7 . 0 9 8 . 0 8 . 5 9 . 0 9 . 5 1 0 . 0 1 0 . 5 8 . 0 8 . 5 9 . 0 9 . 5 1 0 . 0 1 0 . 5 8 . 0 8 . 5 9 . 0 9 . 5 1 0 . 0 1 0 . 5 8 . 0 8 . 5 9 . 0 9 . 5 1 0 . 0 1 0 . 5 F s t l 1 F s t l 1 F s t l 1 F s t l 1 Figure 10. p42/p44 MAPK (ERK) activation and AP1-related gene expression. (A) Representative immunoblots for phosphorylatedFigure 10. p42/p44 (P-ERK) MAPK and total (ERK) (t-ERK) activation extracellular and AP1 signal-regulated-related gene expression kinase in.immortalized (A) Representative human immunoblots proximal tubule for epithelialphosphorylated cells that were(P-ERK) treated and total with (t rhFSTL1-ERK) extracellular for either 0,signal 5, 10,-regulated 30, 60, orkinase 120 min.in immortalized (B) Densitometry human proximal intensities tubule were quantifiedepithelial and cells normalized that were to treated total ERK with (n rhFSTL1= 3). Values for either are mean 0, 5, ±10,SEM. 30, 60,p valuesor 120 weremin. ( determinedB) Densitometry by one-way intensities ANOVA. were quantified and normalized to total ERK (n = 3). Values are mean ± SEM. P values were determined by one-way ANOVA. Significance was defined as a p value of < 0.05. (C) Immortalized human proximal tubule epithelial cells were transfected Significance was defined as a p value of < 0.05. (C) Immortalized human proximal tubule epithelial cells were transfected withwith an AP1 an AP1 luciferase luciferase reporter reporter plasmid. plasmid. The The experimental experimental group group of of cells cells were wereincubated incubated in rhFSTL1 for 24 24 h h ( (nn == 3 3per per group).group). Luciferase Luciferase activity activity was was subsequently subsequently determined. determined. Values Values are are the the mean mean± ±SEM SEM (black (black bars).bars). Values are mean ±± SEM,SEM, and significanceand significance was was defined defined as a asp valuea p value of FigureFigure 11. p38 11. MAPKp38 MAPK activation activation and and NF NκFB-relatedκB-related expression. expression.( A(A)) RepresentativeRepresentative immunoblots immunoblots for for phosphorylated phosphorylated (P- (P-p38) and totalp38) (t-p38)and total p38 (t-p38) in immortalized p38 in immortalized human human proximal proximal tubule tubule epithelial epithelial cells cells that that were were treatedtreated with with rhFSTL1 rhFSTL1 for for either either 0, 5, 0, 5, 10, 30, 60, or 120 min. Densitometry intensities were quantified and normalized to total p38 (n = 3). Values are mean 10, 30, 60, or 120 min. Densitometry intensities were quantified and normalized to total p38 (n = 3). Values are mean ± ± SEM, and P values were determined by one-way ANOVA. Significance was defined as a p value of < 0.05. (B) SEM,Immortalized and p values human were determined proximal tubule by one-way epithelial ANOVA. cells were Significance transfected with was definedan NFκB as luciferase a p value reporter of < 0.05. plasmid. (B) Immortalized Cells humanwere proximal incubated tubule in rhFSTL1 epithelial for 24 cells h (n were= 3 per transfected group) and withluciferase an NF activityκB luciferase was determined. reporter Values plasmid. are the Cells mean were ± SEM incubated in rhFSTL1(black bars). for 24 Significance h (n = 3 per was group) defined and as a luciferasep value of < activity 0.05. (C)was Heatmap determined. with unsupervised Values are hier thearchical mean cluster± SEM analysis (black bars). –/– Significanceof NFκB was related defined genes as in a kidneysp value of 4 < and 0.05. 7 (weekC) Heatmap old Col4a3 with and unsupervised wild-type mice hierarchical (n = 8 per cluster group). analysis (D–G) Graphical of NFκB related –/– representation of selected gene mRNA levels-/- in 7 week old wild type versus 7 week old Col4a3 mice. Values are the genesmean in kidneys ± SEM (black of 4 and bars). 7 weekp values old wereCol4a3 determinedand wild-type by Student’s mice t tests, (n = and 8 per significance group). (wasD– Gdefined) Graphical as a p value representation <0.05. of -/- selected(H,I gene) Fstl1 mRNA mRNA levels levels in were 7 week correlated old wild with type Ccl2 versus and Tnfa 7 week mRNA old levels.Col4a3 Pearson’smice. Valuescorrelation are coefficientthe mean ± (r) SEM was (black bars).determined,p values were and determined two-tailed p byvalues Student’s derived.t tests,Linear and regression significance generated was definedthe line ofas best a p value fit (solid < 0.05. lines) (H with,I) Fstl1 95%mRNA levelsconfidence were correlated intervals with (dottedCcl2 lines).and Tnfa SignificancemRNA was levels. defined Pearson’s as a p correlationvalue < 0.05. coefficient (r) was determined, and two-tailed p values derived. Linear regression generated the line of best fit (solid lines) with 95% confidence intervals (dotted lines). Significance was defined as a p value < 0.05. Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 14 of 41 Int. J. Mol. Sci. 2021, 22, 9513 13 of 38 Figure 12. rhFSTL1 treatment of cultured human kidney cells. (A) Representative Western blots for collagen type I Figure 12. rhFSTL1 treatment of cultured human kidney cells. (A) Representative Western blots for collagen type I alpha1 alpha1 chain (COL1a1) and β-actin in immortalized human proximal tubule epithelial cells treated with rhFSTL1 for chain (COL1a1) and β-actin in immortalized human proximal tubule epithelial cells treated with rhFSTL1 for 24 h. Densitometry24 h. Densitometry intensities intensities were quantified were quantified and normalized and normalized to total to total (n = ( n3).= 3). (B) (B Representative) Representative Western Western blot blotss for for cyclooxygenasecyclooxygenase 2 2 (C (COX2)OX2) and and ββ-actin-actin in in immortalized immortalized human human proximal proximal tubule tubule epithelial epithelial cells cells that that were were treated treated with with rhFSTL1rhFSTL1 for for 24 24 h h.. Densitometry Densitometry intensities intensities were were quantified quantified and and normalized normalized to to total total (n (n == 3). 3). Values Values are are the the mean mean ±± SEMSEM (black(black bars). bars). Pp valuesvalues were were determined determined by by Student’s Student’s t ttests,tests, and and significance significance was was defined defined as as a a pp valuevalue < < 0 0.05..05. 2.6. Apoptosis in Response to rhFSTL1 2.6. Apoptosis in Response to rhFSTL1 Pathology studies have shown that tubular atrophy and cell loss are features of Pathology studies have shown that tubular atrophy and cell loss are features of chronic chronic kidney disease but a role for FSTL1 in apoptosis in the kidney is unknown. kidney disease but a role for FSTL1 in apoptosis in the kidney is unknown. Accordingly, we Accordingly, we studied the effect of rhFSTL1 on apoptosis in HK2 cells. Treatment with studied the effect of rhFSTL1 on apoptosis in HK2 cells. Treatment with rhFSTL1 increased rhFSTL1 increased PARP cleavage and CASP3 activation, as assessed by Western blot PARP cleavage and CASP3 activation, as assessed by Western blot analysis (Figure 13A). analysis (Figure 13A). Densitometry showed a 3-fold rise in CASP3 activation (p < 0.0001) Densitometry showed a 3-fold rise in CASP3 activation (p < 0.0001) and a 2-fold rise in and a 2-fold rise in PARP cleavage (p = 0.0013) (Figure 13B,C, respectively). Interestingly, PARP cleavage (p = 0.0013) (Figure 13B,C, respectively). Interestingly, pre-treatment with pre-treatment with naloxone, a TLR4 receptor antagonist attenuated the effects of rhFSTL1 naloxone, a TLR4 receptor antagonist attenuated the effects of rhFSTL1 on these measures on these measures of apoptosis (Figure 13B,C). We then studied the expression of 12 genes of apoptosis (Figure 13B,C). We then studied the expression of 12 genes implicated in implicated in apoptosis in 4 and 7 week old Col4a3–/– and Col4a3+/+ mice. The heat map in apoptosis in 4 and 7 week old Col4a3-/- and Col4a3+/+ mice. The heat map in Figure 13C Figureillustrates 13C illustrates the gene expression the gene expression pattern that pattern emerged that from emerged this unsupervised from this unsupervised hierarchical hierarchclusterical analysis. cluster There analysis. was There no dominant was no dominant expression expression pattern in pattern the 7 weekin the old7 weekCol4a3 old-/- –/– +/+ Col4a3mice compared mice compared to 7 week to old7 weekCol4a3 old+/+ Col4a3mice. However,mice. However, the expression the expression levels oflevels several of severalpro-apoptotic pro-apoptotic genes genes including includingBax (p Bax = 0.0004) (p = 0.0004) (Figure (Figure 13E), 13FasE),( pFas = 0.026)(p = 0.026) (Figure (Figure 13F ), 13RelaF), Rel(p a< (p 0.001) < 0.001) (Figure (Figure 13 G),13G),Casp3 Casp(3p (p< < 0.0006) 0.0006) (Figure(Figure 1313H),H), and CCasp8asp8 ((pp = = 0.0003)0.0003) –/– +/+ (Figure(Figure 13 13I),I), were were significantly significantly greater greater in in 7 7 week week old old Col4a3-/- micemice than than in in Col4a3Col4a3+/+ mice.mice. Finally,Finally, we we related Fstl1Fstl1expression expression levels levels to to the the expression expression of theseof these six pro-apoptotic six pro-apoptotic genes: genesBax (: rBax= 0.63 (r =, p0.63, = 0.0948) p = 0.0948) (Figure (Figure 13J), Fas13J),( rFas= 0.58,(r = 0.58,p = 0.13) p = 0.13) (Figure (Figure 13K), 13RelaK), Rel(r =a ( 0.93,r = 0.93,p < 0.0008p < 0.0008)) (Figure (Figure 13L), 13Casp3L), Ca(spr =3 0.54,(r = 0.54,p < 0.16) p < 0.16) (Figure (Figure 13M), 13 andM),Casp8 and (Car =sp 0.83,8 (r =p 0.83, = 0.011) p = (Figure0.011) ( Figure13N). Although 13N). Although the relationships the relationships for all six for genes all six exhibited genes exhibited similar trends,similar onlytrends, two onlyassociations two associations were statistically were statistically significant: significant:Rela and RelCasp8a and. Casp8. 2.7. STRING Analysis of FSTL1 Protein–Protein Interactions We next used STRING analysis to generate a list of proteins that may interact with FSTL1. Figure 14B shows the network as the number of proteins and interactions increase, and colored lines show the type of interaction between two nodes or proteins. The three shells shown in Figure 14B represent a protein–protein interaction network that starts with five proteins, which is then increased to 10 proteins, and then 15 proteins. Figure 14C shows a shell with 20 FSTL1-interacting proteins. We designated the list of 20 proteins generated by this STRING analysis of interactions to be an FSTL1 signature. Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 15 of 41 Int. J. Mol. Sci. 2021, 22, 9513 14 of 38 A B C D E B a x F F a s G R e la C a sp 3 C a sp 8 8 .0 8 .0 1 1 .5 H 7 .0 I 1 2 .0 0.0004 0.0260 <0.0001 0.0006 0.0003 1 1 .0 1 1 .5 n n n n 7 .5 n 6 .5 o o o o o i i i i i s s s s 7 .5 s 1 0 .5 s s s s s e e e e e 1 1 .0 r r r r r p p p p 7 .0 p 1 0 .0 6 .0 x x x x x E E E E E 1 0 .5 2 2 2 2 7 .0 2 9 .5 g g g g g o o o o o 6 .5 5 .5 L L L L L 1 0 .0 9 .0 6 .5 6 .0 8 .5 5 .0 9 .5 W T K O W T K O W T K O W T K O W T K O 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k J F s t l 1 v s B a x K F s t l 1 v s F a s F s t l 1 v s R e l a M F s t l 1 v s C a s p 3 N F s t l 1 v s C a s p 8 8 . 0 8 . 0 L 1 1 . 5 7 . 0 1 2 . 0 1 1 . 0 1 1 . 5 7 . 5 6 . 5 7 . 5 8 1 0 . 5 3 1 1 . 0 a p p x s l a s s a 7 . 0 e 6 . 0 a a F B R C 1 0 . 0 C 1 0 . 5 7 . 0 6 . 5 5 . 5 r 0.629 r 0.5807 9 . 5 r 0.9312 r 0.5372 1 0 . 0 r 0.8295 P (two-tailed) 0.0948 P (two-tailed) 0.1312 P (two-tailed) 0.0008 P (two-tailed) 0.1697 P (two-tailed) 0.0109 6 . 5 6 . 0 9 . 0 5 . 0 9 . 5 8 . 0 8 . 5 9 . 0 9 . 5 1 0 . 0 1 0 . 5 8 . 0 8 . 5 9 . 0 9 . 5 1 0 . 0 1 0 . 5 8 . 0 8 . 5 9 . 0 9 . 5 1 0 . 0 1 0 . 5 8 . 0 8 . 5 9 . 0 9 . 5 1 0 . 0 1 0 . 5 8 . 0 8 . 5 9 . 0 9 . 5 1 0 . 0 1 0 . 5 F s t l 1 F s t l 1 F s t l 1 F s t l 1 F s t l 1 Figure 13. Fstl1 apoptosis. (A) Representative Western blots for poly (ADP-Ribose) polymerase 1 (PARP), Caspase 3 (CASP3),Figure 13. and Fstl1β-actin apoptosis. in immortalized (A) Representative human proximal Western tubule blots epithelialfor poly (ADP cells- treatedRibose) with polymerase rhFSTL1 1± (PARP),naloxone Caspase for 24 h. 3 ((CASP3),B,C) Quantitative and β-actin densitometry in immortalized of immunoblots human proximal for PARP tubule and epithelial CASP3, cells respectively. treated with Intensities rhFSTL1 were ± naloxone quantified for 24 and h. normalized(B,C) Quantitative to β-actin densitometry (n = 3). Values of immunoblots are the mean for± SEM PARP (black and CASP3,bars). p respectively.values were determined Intensities were by Student’s quantifiedt tests, and andnormalized significance to β-actin was defined(n = 3). Value as a ps arevalue the of mean <0.05. ± SEM (D) (black Heat mapbars). with P values unsupervised were determined hierarchical by Student’s cluster analysist tests, and of apoptotic-relatedsignificance was defined genes in as kidneys a p value of of 4 and<0.05. 7 week(D) Heat old mapCol4a3 with-/- andunsupervised wild-type hierarchical mice (n = 8 cluster per group). analysis (E– Iof) Graphicalapoptotic- related genes in kidneys of 4 and 7 week old Col4a3–/– and wild-type mice (n = 8 per group). (E–I) Graphical representation representation of mRNA levels for selected apoptosis-related genes in 7 week old wild type versus 7 week old Col4a3-/- of mRNA levels for selected apoptosis-related genes in 7 week old wild type versus 7 week old Col4a3–/– mice. Values are mice. Values are the mean ± SEM (black bars). p values were determined by Student’s t tests, and significance was defined the mean ± SEM (black bars). P values were determined by Student’s t tests, and significance was defined as a P value as<0 a.05.p value (J–N) Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 16 of 41 We next used STRING analysis to generate a list of proteins that may interact with FSTL1. Figure 14B shows the network as the number of proteins and interactions increase, and colored lines show the type of interaction between two nodes or proteins. The three shells shown in Figure 14B represent a protein–protein interaction network that starts with five proteins, which is then increased to 10 proteins, and then 15 proteins. Figure 14C Int. J. Mol. Sci. 2021, 22, 9513 15 of 38 shows a shell with 20 FSTL1-interacting proteins. We designated the list of 20 proteins generated by this STRING analysis of interactions to be an FSTL1 signature. FigureFigure 14. 14. ProteinProtein–protein–protein interaction interaction (PPI) (PPI) analysis analysis of ofFSTL1 FSTL1.. (A) (A Descriptions) Descriptions of nodes of nodes and and edges edges used used in in the the PPI PPI interactioninteraction map. map. (B) (B STRING) STRING interaction interaction map map showing showing protein protein–protein–protein association association between between FSTL1 FSTL1 and and 5, 10,5, 10, and and 15 15 proteins.proteins. (C)( C STRING) STRING interaction interaction map map showing showing protein protein–protein–protein association association between between FSTL1 FSTL1 and and 20 20 proteins proteins (listed (listed in in FigureFigure 15 15with with the the confidence confidence scores scores generated generated by bySTRING STRING).). Figure 15 shows the 20 proteins comprising the largest network. This lists the protein names and provides the color code for the corresponding node (protein). We then examined mRNA levels of these proteins in microarray expression data from 4 and 7 week old Col4a3-/- and Col4a3+/+ mice. Figure 16A illustrates the gene expression pattern that emerged from an unsupervised hierarchical analysis in the four groups. In general, most of the genes representing the FSTL1 signature were over-expressed in the 7 week old Col4a3-/-. We explored the relative expression of eight representative genes in this signature (Figure 16B–I). The expression of the extracellular proteins LAMB1 (p = 0.0008) (Figure 16B), LAMC1 (p < 0.0001) (Figure 16C), and FN1 (p < 0.001) (Figure 16D), and VCAN (p < 0.001) (Figure 16E) were all significantly increased in the 7 week old Col4a3-/- compared to the Int. J. Mol. Sci. 2021, 22, 9513 16 of 38 7 week old Col4a3+/+ mice. The expression levels of 2 bone morphogenic proteins, BMP2 and BMP4, were similar in the 7 week old Col4a3-/- and Col4a3+/+ mice (Figure 16F,G). Interestingly, expression levels of two proteins in the FSTL1 signature that regulate the Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 17 of 41 accumulation of extracellular matrix proteins, TIMP1 and LTBP1, were also increased in 7 week old Col4a3-/- mice compared to 7 week old Col4a3+/+ mice (Figure 16H,I). Figure 15. STRING interaction map show showinging protein protein–protein–protein association between Fstl1 and 20 proteins.proteins. Figure 15 shows the 20 proteins comprising the largest network. This lists the protein names2.8. Studies and of provides the Expression the color of Fstl1 code and Itsfor Cognate the corresponding Receptors in Mice node Subjected (protein). to Unilateral We then Ureteral Obstruction (UUO) examined mRNA levels of these proteins in microarray expression data from 4 and 7 week old Col4a3UUO– is/– associatedand Col4a3 with+/+ mice. the rapidFigure development 16A illustrates of inflammationthe gene expression and fibrosis, pattern and that is emergeda standard from model an unsupervised of CKD. Figure hierarchical 17A shows analysis the experimental in the four design. groups. Under In general, isoflurane most ofanesthesia, the genes 7 week representing old wild the type FSTL1 mice weresignature subjected were to over sham-expressed surgery or in ligation the 7 week of the leftold ureter (UUO). mRNA analysis and RNAscope® analysis of Fstl1 mRNA localization was Col4a3−/−. We explored the relative expression of eight representative genes in this performed in the left kidney after 7 days. Figure 17B–G shows the analysis of expression signature (Figure 16B–I). The expression of the extracellular proteins LAMB1 (p = 0.0008) of genes implicated in inflammation, Ccl2 (Figure 17B) and Tnfa (Figure 17C), and genes (Figure 16B), LAMC1 (p < 0.0001) (Figure 16C), and FN1 (p < 0.001) (Figure 16D), and involved in fibrosis, Acta2 (Figure 17D), Tgfb1 (Figure 17E), Col1a1 (Figure 17F), and Fn1 VCAN (p < 0.001) (Figure 16E) were all significantly increased in the 7 week old Col4a3–/– (Figure 17G) by qPCR. As expected, the expression of this set of genes is markedly up- compared to the 7 week old Col4a3+/+ mice. The expression levels of 2 bone morphogenic regulated in mice subjected to UUO compared to sham-operated mice. We characterized proteins, BMP2 and BMP4, were similar in the 7 week old Col4a3–/– and Col4a3+/+ mice kidney inflammation and fibrosis in the UUO mouse in previous studies [14]. UUO (Figure 16F,G). Interestingly, expression levels of two proteins in the FSTL1 signature that recapitulates many of the cellular processes responsible for progressive kidney injury regulate the accumulation of extracellular matrix proteins, TIMP1 and LTBP1, were also which is a commonly used model of CKD [15,16]. Figure 18 depicts light micrographic increased in 7 week old Col4a3–/– mice compared to 7 week old Col4a3+/+ mice (Figure images of kidneys from sham-operated and UUO mice (7 days after surgery). Figure 19 16H,I). shows the analysis of expression of Fstl1 (Figure 19D) and the cognate receptors Tlr4 (Figure 19B) and Dip2a (Figure 19C). The expression of all three genes is up-regulated in mice subjected to UUO compared to sham-operated mice at 7 days. Remarkably, the expression of Fstl1 rose almost 10-fold (p < 0.0001). We then used RNAscope® to localize Fstl1 in both groups of mice. Figure 19B shows representative light micrographs at 20× and 40× magnification. It was difficult to discern any Fstl1 expression by RNAscope® in the kidneys of mice subjected to sham operation. However, in mice subjected to UUO, cells expressing Fstl1 were present in the interstitial space, just as we had observed in the 7 week old Col4a3-/- mice. Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 18 of 41 Int. J. Mol. Sci. 2021, 22, 9513 17 of 38 A B L a m b 1 C L a m c1 D F n 1 E V c a n 1 0 .0 0.0008 9 .5 <0.0001 1 3 <0.0001 7 <0.0001 1 2 n n n n o o o 9 .5 o 9 .0 6 i i i i s s s s 1 1 s s s s e e e e r r r r p p p 9 .0 p 8 .5 1 0 5 x x x x E E E E 2 2 2 2 9 g g g g o o o 8 .5 o 8 .0 4 L L L L 8 8 .0 7 .5 7 3 W T K O W T K O W T K O W T K O 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k F B m p 2 G B m p 4 H T im p 1 I L tb p 1 6 .5 0.7087 1 1 .0 0.9517 1 5 <0.0001 8 .0 0.0451 n n n n o o o 6 .0 1 0 .5 o 7 .5 i i i i s s s s 1 0 s s s s e e e e r r r r p p p 5 .5 1 0 .0 p 7 .0 x x x x E E E E 2 2 2 2 5 g g g g o o o 5 .0 9 .5 o 6 .5 L L L L 4 .5 9 .0 0 6 .0 W T K O W T K O W T K O W T K O 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k 7 w k Figure 16. Expression analysis of FSTL1 signature genes derived from the STRING analysis of the FSTL1 protein–protein interaction (PPI) network. (A) Heat map with unsupervised hierarchical cluster analysis of the FSTL1 driven PPI network Figure 16. Expression analysis of FSTL1 signature genes derived from the STRING analysis of the FSTL1 protein–protein genes in kidneys of 4 and 7 week old Col4a3-/- mice and wild-type mice (n = 8 per group). (B–I) Graphical representation of interaction (PPI) network. (A) Heat map with unsupervised hierarchical cluster analysis of the FSTL1 driven PPI network mRNA levels for selected FSTL1 signature genes in 7 week old wild type versus 7 week old Col4a3-/- mice. Values are the genes in kidneys of 4 and 7 week old Col4a3–/– mice and wild-type mice (n = 8 per group). (B–I) Graphical representation mean ± SEM (black bars). p values were determined by Student’s t tests, and significance was defined as a p value < 0.05. of mRNA levels for selected FSTL1 signature genes in 7 week old wild type versus 7 week old Col4a3–/– mice. Values are the mean ± SEM (black bars). P values were determined by Student’s t tests, and significance was defined as a p value < 0.05. 2.8. Studies of the Expression of Fstl1 and Its Cognate Receptors in Mice Subjected to Unilateral Ureteral Obstruction (UUO) UUO is associated with the rapid development of inflammation and fibrosis, and is a standard model of CKD. Figure 17A shows the experimental design. Under isoflurane anesthesia, 7 week old wild type mice were subjected to sham surgery or ligation of the left ureter (UUO). mRNA analysis and RNAscope® analysis of Fstl1 mRNA localization was performed in the left kidney after 7 days. Figure 17B–G shows the analysis of expression of genes implicated in inflammation, Ccl2 (Figure 17B) and Tnfa (Figure 17C), and genes involved in fibrosis, Acta2 (Figure 17D), Tgfb1 (Figure 17E), Col1a1 (Figure 17F), and Fn1 (Figure 17G) by qPCR. As expected, the expression of this set of genes is markedly up-regulated in mice subjected to UUO compared to sham-operated mice. We characterized kidney inflammation and fibrosis in the UUO mouse in previous studies Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 19 of 41 [14]. UUO recapitulates many of the cellular processes responsible for progressive kidney injury which is a commonly used model of CKD [15,16]. Figure 18 depicts light micrographic images of kidneys from sham-operated and UUO mice (7 days after surgery). Figure 19 shows the analysis of expression of Fstl1 (Figure 19D) and the cognate receptors Tlr4 (Figure 19B) and Dip2a (Figure 19C). The expression of all three genes is up- regulated in mice subjected to UUO compared to sham-operated mice at 7 days. Remarkably, the expression of Fstl1 rose almost 10-fold (p < 0.0001). We then used RNAscope® to localize Fstl1 in both groups of mice. Figure 19B shows representative light micrographs at 20× and 40× magnification. It was difficult to discern any Fstl1 expression Int. J. Mol. Sci. 2021, 22, 9513 18 of 38 by RNAscope® in the kidneys of mice subjected to sham operation. However, in mice subjected to UUO, cells expressing Fstl1 were present in the interstitial space, just as we had observed in the 7 week old Col4a3–/– mice. A A c t a 2 B C c l 2 T n f a D C 4 0 6 0 0 0.0065 1 0 0 0 0.0031 0.0199 8 0 0 3 0 A A N A 4 0 0 N R N 6 0 0 R R m 2 0 m m 2 a a 2 f t l 4 0 0 c c n 2 0 0 T A C 1 0 2 0 0 0 0 0 S h a m U U O S h a m U U O S h a m U U O W T W T W T W T W T W T E T g f b 1 F C o l 1 a 1 F n 1 0.0090 G <0.0001 4 0 1 0 0 <0.0001 6 0 8 0 3 0 A A N A N 4 0 R N R 6 0 R m m 2 0 m 1 1 a b 1 f 4 0 1 l n g 2 0 o F T 1 0 C 2 0 0 0 0 S h a m U U O S h a m U U O S h a m U U O W T W T W T W T W T W T Figure 17. UnilateralFigure 17. ureteralUnilateral obstructionureteral obstruction (UUO) (UUO) and andFstl1 Fstl1expression. expression. (A (A) Schematic) Schematic diagram diagram summarizing summarizing experimental experimental workflow and collection of tissue from 7 week old C57B6 mice subjected to sham (n = 4) or UUO (n = 5) surgery. 7 days workflow andafter collection surgery, of mice tissue were from sacrificed, 7 week and old kidney C57B6 tissue mice was subjected collected to forsham analysis (n = of 4) mRNA or UUO level (sn. (=B, 5)C) surgery. Graphical7 days after surgery, micerepresentation were sacrificed, of mRNA and levels kidney for selected tissue wasgenes collected implicated forin kidney analysis inflammation of mRNA (Ccl2 levels., Tnfa) (inB ,7C week) Graphical old wild type representation of mRNA levelssham for versus selected 7 week genesold UUO implicated mice. Values in are kidney mean ± inflammationSEM (black bars). ( Ccl2P values, Tnfa were) in determined 7 week oldby Student’s wild type t tests, sham versus and significance was defined as a p value <0.05. (D–G) Graphical representation of mRNA levels for selected genes 7 week old UUOimplicated mice. in Values kidney arefibrosis mean (Acta±2, SEMTgfb1, (blackCol1a1, F bars).n1) in 7p weekvalues old wild were type determined sham versusby 7 week Student’s old UUOt tests,mice. Values and significance are mean ± SEM (black bars). P values were determined by Student’s t tests, and significance was a p value < 0.05. was definedInt. J. as Mol. a Sci.p value 2021, 22 <, x0.05. FOR PEER (D– REVIEWG) Graphical representation of mRNA levels for selected genes implicated20 of in 41 kidney fibrosis (Acta2, Tgfb1, Col1a1, Fn1) in 7 week old wild type sham versus 7 week old UUO mice. Values are mean ± SEM (black bars). p values were determined by Student’s t tests, and significance was a p value < 0.05. Figure 18. Fstl1FigureHistology 18. Fstl1 Hi ofstology sham of and sham UUO and UUO mice. mice. Periodic Periodic acid–Schiffacid–Schiff (PAS) (PAS) (left (left panels), panels), Masson Masson Trichrome Trichrome (MTC) (MTC) (middle panels), and alpha-Smooth Muscle Actin (SMA) (right panels) in sham-operated mice (upper panels) and mice (middle panels), and alpha-Smooth Muscle Actin (SMA) (right panels) in sham-operated mice (upper panels) and mice subjected to UUO for 7 days (lower panels). subjected to UUO for 7 days (lower panels). A <0.0001 B <0.0001 C <0.0001 2 5 1 0 3 2 0 8 A A A N 2 N N 1 5 6 R R R m m m a 1 4 2 l 1 0 4 r t p l i s 1 T F D 5 2 0 0 0 S h a m U U O S h a m U U O S h a m U U O D Figure 19. Fstl1 expression and localization in UUO. (A–C) mRNA levels for Fstl1 and its putative receptors (Tlr4 and Dip2a) were determined by quantitative polymerase chain reaction in kidneys of C57B6 mice (sham n = 4, UUO n = 5). Values are the mean ± SEM (black bars). P values were determined by Student’s t test, and significance was defined as a p value of < 0.05. (D) Light microscopic images at three magnifications of RNASCOPE® Fstl1 localization in sham-operated mice (upper three panels) and mice subjected to UUO for 7 days (lower three panels). Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 20 of 41 Figure 18. Fstl1 Histology of sham and UUO mice. Periodic acid–Schiff (PAS) (left panels), Masson Trichrome (MTC) Int. J. Mol. Sci. 2021, 22, 9513 19 of 38 (middle panels), and alpha-Smooth Muscle Actin (SMA) (right panels) in sham-operated mice (upper panels) and mice subjected to UUO for 7 days (lower panels). A <0.0001 B <0.0001 C <0.0001 2 5 1 0 3 2 0 8 A A A N 2 N N 1 5 6 R R R m m m a 1 4 2 l 1 0 4 r t p l i s 1 T F D 5 2 0 0 0 S h a m U U O S h a m U U O S h a m U U O D Figure 19. Fstl1 expression and localization in UUO. (A–C) mRNA levels for Fstl1 and its putative receptors (Tlr4 and Figure 19. Fstl1 expression and localization in UUO. (A–C) mRNA levels for Fstl1 and its putative receptors (Tlr4 and Dip2a) Dip2a) were determined by quantitative polymerase chain reaction in kidneys of C57B6 mice (sham n = 4, UUO n = 5). n n wereValues determined are the mean by quantitative ± SEM (black polymerase bars). P values chain were reaction determined in kidneys by Student’s of C57B6 t micetest, and (sham significance= 4, UUO was defined= 5). Values as a p arevalue the meanof < 0.05.± SEM (D) Light (black microscopic bars). p values images were at determined three magnifications by Student’s of RNASCOPEt test, and significance® Fstl1 localization was defined in sham as a-operatedp value ® ofmice< 0.05 (upper.(D) Lightthree microscopicpanels) and mice images subjected at three to magnifications UUO for 7 days of RNASCOPE(lower three panels).Fstl1 localization in sham-operated mice (upper three panels) and mice subjected to UUO for 7 days (lower three panels). 2.9. Studies of the Expression of Kidney Fstl1 Expression in the NEPTUNE Cohort 2.9.1. Patient Characteristics We studied three NEPTUNE cohorts. Table2 shows clinical and pathologic in- dices of the 3 cohorts. There were 111 subjects in the focal segmental glomerulosclerosis (FSGS) cohort: 66 males and 45 females; 39 subjects in the IgA nephropathy (IgAN) co- hort: 28 males and 11 females; and 61 subjects in the membranous nephropathy (MN) cohort: 39 males and 22 females (Table2). There were missing values for some clin- ical and laboratory parameters, and we did not input missing values for our analy- ses. The average age of the FSGS group was 32.6 ± 2.0 years with a mean eGFR of 72.9 ± 3.2 mL/min/1.73 m2. The average age of the IgAN group was 36.1 ± 2.7 years with a mean eGFR of 67.5 ± 5.6 mL/min/1.73 m2. The average age of the MN group was 50.9 ± 1.8 years with a mean eGFR of 80.3 ± 3.2 mL/min/1.73 m2. Table2 shows the mean values for the timed urine protein, creatinine, and albumin measures in each group. A loss of function over the course of follow-up, defined as a 40 percent decline in eGFR with an eGFR of less than 90 mL/min/1.73 m2, was observed in 27 subjects in the FSGS cohort, 10 subjects in the IgAN cohort, and 13 subjects in the MN cohort. Int. J. Mol. Sci. 2021, 22, 9513 20 of 38 Table 2. Demographic and clinical characteristics of patients with FSGS, IgAN, and MN. ALL FSGS IgAN MN Age 38.54 ± 1.364 32.62 ± 1.957 36.08 ± 2.664 50.89 ± 1.792 Sex (male/female) (133/78) (66/45) (28/11) (39/22) BMI 28.51 ± 0.4938 27.39 ± 0.7284 28.24 ± 0.9308 30.72 ± 0.8484 Sitting Systolic 123.6 ± 1.209 122.7 ± 1.558 123.1 ± 2.67 125.5 ± 2.575 Sitting Diastolic 76 ± 0.8592 74.96 ± 1.212 75.85 ± 1.936 77.97 ± 1.557 Hematocrit % 39.08 ± 0.389 38.83 ± 0.5635 38.54 ± 0.8987 39.88 ± 0.654 eGFR 74.06 ± 2.214 72.93 ± 3.247 67.46 ± 5.559 80.32 ± 3.255 Centrally measured timed urine protein 243.8 ± 23.2 199.3 ± 27.74 119.9 ± 18.73 385.6 ± 52.7 Centrally measured timed urine creatinine 69.01 ± 3.536 69.07 ± 5.286 62.35 ± 5.869 72.86 ± 6.701 Centrally measured timed urine albumin 1778 ± 169 1492 ± 208.3 927 ± 146.7 2737 ± 382 Interstitial fibrosis (%) 18.71 ± 1.658 20.98 ± 2.496 20.65 ± 3.155 12.38 ± 2.179 Tubular atrophy (%) 17.48 ± 1.654 19.44 ± 2.489 19.62 ± 3.175 11.71 ± 2.22 Patient reached ESKD or 40% loss of eGFR (and eGFR<90) 50 27 10 13 FSGS, focal segmental glomerulosclerosis; IgAN, IgA nephropathy; MN, membranous glomerulonephropathy. BMI, body mass index; eGFR, estimated glomerular filtration rate. Values are mean ± SEM. 2.9.2. Correlation of FSTL1 mRNA Expression with Clinical Variables We first studied FSTL1 mRNA expression in micro-dissected kidney tubulointerstitial samples in all three cohorts as a group. Tubulointerstitial FSTL1 mRNA expression was similar in females compared to males (p = 0.31; Figure 20A) and did not correlate with age (Figure 20B) or BMI (Figure 20G). There were modest correlations with sitting systolic blood pressure (r = 0.20, p = 0.0056) (Figure 20C) and sitting diastolic blood pressure (r = 0.14, p = 0.048) (Figure 20D). There was a relationship between FSTL1 mRNA expression and eGFR (r = -0.49, p < 0.0001) (Figure 20E) such that the higher the mRNA levels for FSTL1, the lower the eGFR. There was also a significant relationship between centrally measured and timed UPCR values and FSTL1 mRNA levels (Figure 20F). Multiple linear regression analysis showed that FSTL1 expression related to age, eGFR, and UPCR but not to sex or sitting blood pressure measures (Table3). Table 3. Multiple linear regression analysis of FSTL1 expression. Model: y = β0 + β1x1 + β2x2 + β3x3 + β4x4 + β5x5 + β6x6 Predictor Coefficient Estimate Standard Error t-Statistic p-Value FSTL1 β0 4.0903 0.4391 9.3144 <0.001 Age β1 −0.0099 0.0029 −3.4147 0.0008 Sex β2 0.0976 0.1078 0.9054 0.3667 BPSS β3 0.0035 0.0041 0.8616 0.3903 BPSD β4 −0.0031 0.0057 −0.5522 0.5817 eGFR β5 −0.0134 0.0018 −7.4402 <0.001 UPCR β6 0.071 0.0131 5.4027 <0.001 Age; Sex; Systolic, sitting systolic blood pressure; Diastolic, sitting diastolic blood pressure; eGFR, estimated glomerular filtration rate; UPCR, centrally measured timed urinary protein creatinine ratio. Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 22 of 41 Int. J. Mol. Sci. 2021, 22, 9513 21 of 38 A B r -0.02902 C r 0.197 D r 0.1413 e 1 5 0 r 1 0 0 e 2 0 0 P (two-tailed) 0.0483 P (two-tailed) 0.6864 r P (two-tailed) 0.0056 u u s s s s e r 8 0 e r P 1 5 0 P d d 1 0 0 o o o l 6 0 o l e B B g 1 0 0 c c i i A l l 4 0 o o t t s s 5 0 a y i S 5 0 D 2 0 g g n i n i t t t i t i 0 S 0 S 0 0 2 4 6 0 2 4 6 0 2 4 6 F S T L 1 F S T L 1 F S T L 1 E r -0.4482 F G r 0.08618 2 0 0 r 0.3687 P (two-tailed) <0.0001 6 0 P (two-tailed) 0.2346 4 0 P (two-tailed) <0.0001 1 5 0 3 0 4 0 R I F 1 0 0 M 2 0 R G B C e 2 0 P U 1 0 5 0 0 0 0 2 4 6 0 2 4 6 0 2 4 6 - 1 0 F S T L 1 F S T L 1 F S T L 1 Figure 20. Relationship of tubulointerstitial FSTL1 expression to clinical variables in the cohort of FSGS, IgAN, and MN. (A) FSTL1FiguremRNA 20. Relationship levels in male of tubulointerstitial subjects compared FSTL1 to female expression subjects. to (clinicalB–G) FSTL1 variablesmRNA in the levels cohort correlated of FSGS, against IgAN, (B )and age, MN. (C) sitting(A) FSTL1 systolic mRNA blood levels pressure, in male (D) subjects sitting diastolic compar blooded to female pressure, subjects. (E) estimated (B–G) glomerularFSTL1 mRNA filtration levels ratecorrelated (eGFR), against (F) Urine (B) Proteinage, (C to) sitting Creatinine systolic Ratio blood (UPCR), pressure, and ( (DG)) sitting Body Massdiastolic Index blood (BMI). pressure, Pearson’s (E) estimated correlation glomerular coefficient filtration (r) was determined, rate (eGFR), and(F) two-tailedUrine Proteinp values to Creatinine derived. SignificanceRatio (UPCR), was and determined (G) Body asMass a p valueIndex of (BMI). <0.05. Pearson’s Linear regression correlation generated coefficient the ( liner) was of bestdetermined, fit (solid lines)and two with-tailed 95% confidenceP values derived. intervals Significance (dotted lines). was Significance determined was as determined a p value as of a<0p .05.value Linear of <0.05. regression generated the line of best fit (solid lines) with 95% confidence intervals (dotted lines). Significance was determined as a p value of <0.05. 2.9.3. FSTL1 mRNA Levels and Kidney Outcomes TableKidney 3. Multiple disease linear progression regression wasanalysis defined of FSTL1 as a expression. composite reaching ESKD or a 40% loss of eGFR (with a baseline eGFR<90). Table4 shows the percent and number of individuals reaching the compositeModel: outcome y = β for0 + β kidney1x1 + β2 diseasex2 + β3x3 progression + β4x4 + β5x5 in+ β FSGS,6x6 IgAN, and MN, divided into four groups based on the quartilesStandard for FSTL1 mRNA levels at the time of Predictor Coefficient Estimate t-Statistic p-Value biopsy. In the first three quartiles, 18 to 22 percent ofError the individuals reached the composite endpointFSTL1 while 38 percentβ0 reached4.0903 thecomposite 0.4391 outcome in9.3144 the fourth quartile<0.001 with theAge highest FSTL1 mRNAβ1 levels. Figure−0.0099 21 is a forest0.0029 plot showing−3.4147 the unadjusted0.0008 odds ratioSex and confidence intervalsβ2 of reaching0.0976 the composite0.1078 outcome0.9054 for the second0.3667 to fourth quartiles compared to the first quartile (lowest FSTL1 mRNA levels). The unadjusted odds BPSS β3 0.0035 0.0041 0.8616 0.3903 ratio was 2.67 (1.05, 6.76) for subjects in the fourth quartile. BPSD β4 −0.0031 0.0057 −0.5522 0.5817 eGFR β5 −0.0134 0.0018 −7.4402 <0.001 Table 4. FSTL1 quartile expression. Baseline FSTL1 mRNA levels divided into quartiles. UPCR β6 0.071 0.0131 5.4027 <0.001 Age; Sex; Systolic, sitting systolic blood Quartilepressure; Analysis Diastolic, sitting diastolic blood pressure; eGFR, estimated glomerular filtration rate; UPCR, centrally measured timed urinary protein creatinine Quartile 1 2 3 4 ratio. Percentage (%) 18% 22% 18% 38% n 9/49 11/49 9/49 18/48 2.9.3.Range FSTL1 mRNA Levels 1.6–2.7 and Kidney Outcomes 2.7–3.1 3.1–3.7 3.7–5.6 The numberKidney (n) disease and percentage progression of patients was in eachdefinedFSTL1 asquartile a composite that reached reaching the composite ESKD or endpoint. a 40% Theloss compositeof eGFR end(with point a baseline has two components: eGFR<90). End Table Stage 4 Kidney shows Failure the perce (ESKD)nt orand a 40 number percent decrease of individuals in eGFR compared to baseline eGFR (with a baseline eGFR < 90 mls/min). Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 24 of 41 Int. J. Mol. Sci. 2021, 22, 9513 22 of 38 Figure 21. Forest Plot of End Point Analysis. The odds ratio (OR) with 95 percent confidence intervals for reaching the end Figurepoint 21. in Forest the second, Plot of third,End Point and fourthAnalysis. quartiles The odds of baseline ratio (OR)FSTL1 withmRNA 95 percent levels. confidence The first intervals quartile wasfor reaching the reference the end group. point in the second, third, and fourth quartiles of baseline FSTL1 mRNA levels. The first quartile was the reference group. The OR was not adjusted for baseline clinical variables. The OR was not adjusted for baseline clinical variables. We then compared baseline measures of eGFR, interstitial fibrosis (IF), and tubular atrophy (TA) in subjects in the first and fourth quartiles for FSTL1 mRNA levels (Figure 22). Values for eGFR were significantly lower in subjects in the fourth quartile (p < 0.001) (Figure 22A). Values for IF (Figure 22B) and TA (Figure 22C) were significantly higher in subjects in the fourth quartile (p < 0.001, and p < 0.001, respectively). In accordance with the measures of IF, mean mRNA levels for genes implicated in kidney fibrosis, namely, COL1A1 (Figure 22D), ACTA2 (Figure 22E), and TGFB1 (Figure 22F), were greater in the fourth quartile group compared to the first quartile group (p < 0.001 for each mRNA). In accordance with the measures of TA, mean mRNA levels for genes implicated in apoptosis, namely, CASP3 (Figure 22G), CASP8 (Figure 22H), and BAX (Figure 22I), were greater in the fourth quartile group compared to the first quartile group (p < 0.001 for both CASP3 and CASP8, and p = 0.0017 for BAX) (Figure 22C). There were also differences in the mean mRNA levels for genes implicated in inflammation: TNFA (p = 0.0002) (Figure 22J) and CCL2 (p < 0.0001) (Figure 22K) but not for FN1 (Figure 22L). 2.9.4. FSTL1 mRNA Levels and Kidney Structure and Function We then studied associations between eGFR, IF, TA, and FSTL1 mRNA levels sep- arately in each of the three cohorts. FSTL1 mRNA levels were strongly associated with eGFR in each cohort: FSGS (r = −0.45, p < 0.0001) (Figure 23A), IgAN (r = −0.68, p < 0.0011) (Figure 23B), and MN (r = −0.41, p < 0.001) (Figure 23C). FSTL1 mRNA levels were also strongly associated with IF in each cohort: FSGS (r = −0.45, p < 0.0001) (Figure 23D), IgAN (r = −0.75, p < 0.0001) (Figure 23E), and MN (r = −0.54, p < 0.00014) (Figure 23F). Finally, FSTL1 mRNA levels were strongly associated with TA in each cohort: FSGS (r = −0.45, p < 0.0001) (Figure 23G), IgAN (r = −0.75, p < 0.0001) (Figure 23H), and MN (r = −0.53, p < 0.0007) (Figure 23I). 2.9.5. Associations between FSTL1 mRNA Levels and Genes Implicated in Fibrosis, Inflammation, and Apoptosis, in Each of the Three Cohorts FSTL1 mRNA levels were strongly associated with TGFB1 mRNA levels in each Figure 22. A Comparison of Baselinecohort: Laboratory FSGS (r = Variables 0.46, p < and 0.0001) Gene (Figure Expression 24A), Levels IgAN B (etweenr = 0.58, Firstp < and 0.0005) Fourth (Figure FSTL1 24 B), and Quartiles. (A) eGFR. (B) InterstitialMN (fibrosisr = 0.51 percentage, p < 0.001) (IF). (Figure (C) tubular 24C). FSTL1atrophymRNA percentage levels (TA). were (D strongly) Collagen associated Type I with COL1A1 mRNA levels: FSGS (r = 0.85, p < 0.0001) (Figure 24D), IgAN (r = 0.89, p < 0.0001) Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 24 of 41 Int. J. Mol. Sci. 2021, 22, 9513 23 of 38 (Figure 24E), and MN (r = 0.85, p < 0.00014) (Figure 24F) and for ACTA2 mRNA levels: FSGS (r = 0.59, p < 0.0001) (Figure 24J), IgAN (r = 0.53, p < 0.0001) (Figure 24K), and MN (r = 0.70, p < 0.00014) (Figure 24L). There was a trend that occurred for FN1 that did not reach statistical significance (Figure 24G–I). FSTL1 mRNA levels were strongly associated with CCL2 mRNA levels: FSGS (r = 0.69, Figure 21. Forest Plot of End Pointp < Analysis. 0.0001) (Figure The odds 25A), ratio IgAN (OR) (r with = 0.80, 95 ppercent< 0.0011) confidence (Figure 25intervalsB), and for MN reaching (r = 0.70, the end point in the second, third, and fourthp < 0.001 quartiles) (Figure of 25 baselineC) andassociated FSTL1 mRNA with TNFA levels.mRNA The first levels: quartile FSGS (rwas = 0.49, the referencep < 0.0001) group. The OR was not adjusted for baseline(Figure clinical 25D), IgANvariables. (r = 0.55, p < 0.0001) (Figure 25E), and MN (r = 0.44, p < 0.00014) (Figure 25F). Figure 22. A Comparison of Baseline Laboratory Variables and Gene Expression Levels Between First and Fourth FSTL1 Figure 22. A Comparison of Baseline Laboratory Variables and Gene Expression Levels Between First and Fourth FSTL1 Quartiles. (A) eGFR. (B) Interstitial fibrosis percentage (IF). (C) tubular atrophy percentage (TA). (D) Collagen Type I Alpha Quartiles. (A) eGFR. (B) Interstitial fibrosis percentage (IF). (C) tubular atrophy percentage (TA). (D) Collagen Type I 1 Chain (COL1A1) expression. (E) Actin Alpha 2, Smooth Muscle (ACTA2) expression. (F) Transforming growth factor beta (TGFB1) expression. (G) Caspase 3 (CASP3) expression. (H) Caspase 8 (CASP8) expression. (I) BCL2 Associated X, Apoptosis Regulator (BAX) expression. (J) Tumor Necrosis Factor (TNFA) expression. (K) C-C Motif Chemokine Ligand 2 (CCL2) expression. (L) Fibronectin 1 (FN1) expression. Values are the mean ± SEM (black bars). p values were determined by Student’s t tests, and significance was defined as a p value < 0.05. Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 25 of 41 Alpha 1 Chain (COL1A1) expression. (E) Actin Alpha 2, Smooth Muscle (ACTA2) expression. (F) Transforming growth factor beta (TGFB1) expression. (G) Caspase 3 (CASP3) expression. (H) Caspase 8 (CASP8) expression. (I) BCL2 Associated X, Apoptosis Regulator (BAX) expression. (J) Tumor Necrosis Factor (TNFA) expression. (K) C-C Motif Chemokine Ligand 2 (CCL2) expression. (L) Fibronectin 1 (FN1) expression. Values are the mean ± SEM (black bars). P values were determined by Student’s t tests, and significance was defined as a p value <0.05. 2.9.4. FSTL1 mRNA Levels and Kidney Structure and Function We then studied associations between eGFR, IF, TA, and FSTL1 mRNA levels separately in each of the three cohorts. FSTL1 mRNA levels were strongly associated with eGFR in each cohort: FSGS (r = −0.45, p < 0.0001) (Figure 23A), IgAN (r = −0.68, p < 0.0011) (Figure 23B), and MN (r = −0.41, p < 0.001) (Figure 23C). FSTL1 mRNA levels were also strongly associated with IF in each cohort: FSGS (r = −0.45, p < 0.0001) (Figure 23D), IgAN (r = −0.75, p < 0.0001) (Figure 23E), and MN (r = −0.54, p < 0.00014) (Figure 23F). Finally, FSTL1 mRNA levels were strongly associated with TA in each cohort: FSGS (r = −0.45, p < 0.0001) (Figure 23G), IgAN (r = −0.75, p < 0.0001) (Figure 23H), and MN (r = −0.53, p < Int. J. Mol. Sci. 2021, 22, 9513 0.0007) (Figure 23I). 24 of 38 Figure 23. Clinical FSTL1 expression in FSGS (red), IgAN (orange), and MN (purple). (A) eGFR correlated to FSTL1 mRNA Figure 23. Clinical FSTL1 expression in FSGS (red), IgAN (orange), and MN (purple). (A) eGFR correlated to FSTL1 mRNA levels in FSGS patients. (B) eGFR correlated to FSTL1 mRNA levels in IgAN patients. (C) eGFR correlated to FSTL1 mRNA levels in FSGS patients. (B) eGFR correlated to FSTL1 mRNA levels in IgAN patients. (C) eGFR correlated to FSTL1 mRNA levels in MN patients. (D) Interstitial fibrosis (IF) correlated to FSTL1 mRNA levels in FSGS patients. (E) Interstitial fibrosis levels in MN patients. (D) Interstitial fibrosis (IF) correlated to FSTL1 mRNA levels in FSGS patients. (E) Interstitial fibrosis (IF) correlated to FSTL1 mRNA levels in IgAN patients. (F) Interstitial fibrosis (IF) correlated to FSTL1 mRNA levels in (IF) correlated to FSTL1 mRNA levels in IgAN patients. (F) Interstitial fibrosis (IF) correlated to FSTL1 mRNA levels in MN patients. (G) Tubular atrophy (TA) correlated to FSTL1 mRNA levels in FSGS patients. (H) Tubular atrophy (TA) MN patients. (G) Tubular atrophy (TA) correlated to FSTL1 mRNA levels in FSGS patients. (H) Tubular atrophy (TA) correlated to FSTL1 mRNA levels in IgAN patients. (I) Tubular atrophy (TA) correlated to FSTL1 mRNA levels in MN correlated to FSTL1 mRNA levels in IgAN patients. (I) Tubular atrophy (TA) correlated to FSTL1 mRNA levels in MN patients. Pearson’s correlation coefficient (r) was determined, and two-tailed p values derived. Significance was determined patients. Pearson’s correlation coefficient (r) was determined, and two-tailed P values derived. Significance was as a p value of <0.05. Linear regression generated the line of best fit (solid lines) with 95% confidence intervals (dotted lines). determined as a p value of <0.05. Linear regression generated the line of best fit (solid lines) with 95% confidence intervals (dotted lines). Finally, we looked at apoptosis-related genes. FSTL1 mRNA levels were modestly associ- ated with BAX mRNA levels: FSGS (r = 0.29, p < 0.0036) (Figure 26A), IgAN (r = 0.32, p < 0.06) 2.9.5.(Figure Associations 26B), and MNbetween (r = 0.26, FSTL1p < 0.06) mRNA (Figure Levels 26C). FSTL1and GenesmRNA Implicated levels were in more Fibrosis strongly, Inflammationassociated with, andCASP3 ApoptosismRNA, levels:in Each FSGS of the (r = Three 0.44, p Cohorts< 0.0001) (Figure 26D), IgAN (r = 0.38, p FSTL1< 0.03) (FiguremRNA 26 E), levels and MN were (r = strongly 0.41, p < 0.0018) associated (Figure with 26F), TGFB1 and CASP8 mRNAmRNA levels levels in in each FSGS (r = 0.37, p < 0.0001) (Figure 26G) and MN (r = 0.40, p < 0.0028) (Figure 26I). There was a cohort: FSGS (r = 0.46, p < 0.0001) (Figure 24A), IgAN (r = 0.58, p < 0.0005) (Figure 24B), trend that occurred for CASP8 that did not reach statistical significance in IgAN (Figure 26H). and MN (r = 0.51, p < 0.001) (Figure 24C). FSTL1 mRNA levels were strongly associated Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 26 of 41 with COL1A1 mRNA levels: FSGS (r = 0.85, p < 0.0001) (Figure 24D), IgAN (r = 0.89, p < 0.0001) (Figure 24E), and MN (r = 0.85, p < 0.00014) (Figure 24F) and for ACTA2 mRNA levels: FSGS (r = 0.59, p < 0.0001) (Figure 24J), IgAN (r = 0.53, p < 0.0001) (Figure 24K), and Int. J. Mol. Sci. 2021, 22, 9513 25 of 38 MN (r = 0.70, p < 0.00014) (Figure 24L). There was a trend that occurred for FN1 that did not reach statistical significance (Figure 24G–I). A F S G S B I g A N C M N 4 r 0.4559 4 4 r 0.5828 r 0.5082 P (two-tailed) <0.0001 P (two-tailed) 0.0005 P (two-tailed) <0.0001 3 3 3 1 1 1 B B B F F F 2 2 2 G G G T T T 1 1 1 0 0 0 0 2 4 6 0 2 4 6 0 2 4 6 F S T L 1 F S T L 1 F S T L 1 I g A N F S G S M N D E 5 F 6 r 0.8868 6 r 0.8514 r 0.847 P (two-tailed) <0.0001 4 P (two-tailed) <0.0001 P (two-tailed) <0.0001 4 4 1 3 a 1 1 1 l a a o 1 1 l l 2 2 C 2 o o C C 1 0 0 2 4 6 2 4 6 0 F S T L 1 F S T L 1 - 2 0 2 4 6 - 2 F S T L 1 F S G S M N [ F S T L 1 v s F N 1 ] G I g A N 0 . 4 r -0.1839 H I r -0.3152 0 . 3 r -0.2266 P (two-tailed) 0.3306 0 . 2 0 0 . 3 P (two-tailed) 0.4911 P (two-tailed) 0.5028 0 . 1 5 0 . 2 0 . 2 1 0 . 1 0 1 N N 0 . 1 F 1 F 0 . 1 N 0 . 0 5 F 0 . 0 0 . 0 0 . 0 0 2 4 6 2 4 6 2 4 6 - 0 . 0 5 F S T L 1 - 0 . 1 F S T L 1 F S T L 1 - 0 . 1 - 0 . 1 0 F S G S I g A N M N J r 0.5886 K r 0.5317 L 1 0 1 0 1 0 P (two-tailed) <0.0001 P (two-tailed) 0.0017 r 0.6982 8 8 8 P (two-tailed) <0.0001 2 2 6 2 6 6 A A A T T T C C C A A A 4 4 4 2 2 2 0 0 0 0 2 4 6 0 2 4 6 0 2 4 6 F S T L 1 F S T L 1 F S T L 1 Figure 24. Relationship of FSTL1 mRNA Levels to the Expression of Genes Implicated in Fibrosis in FSGS (red), IgAN (orange), and MN (purple). Table1. expression correlated to FSTL1 mRNA levels in FSGS (A), in IgAN (B), and MN (C). COL1A1Figure expression24. Relationship correlated of FSTL1 to FSTL1 mRNAmRNA Levels levels to inthe FSGS Expression (D), in IgAN of Genes (E), andImplicated in MN ( Fin). FibrosisFN1 expression in FSGS correlated (red), IgAN to FSTL1(orange)mRNA, and levels MN (purple) in FSGS. ( GTable), in IgAN1. expression (H), and correlated MN (I). ACTA2 to FSTL1expression mRNA correlatedlevels in FSGS to FSTL1 (A), mRNAin IgAN levels (B), and in FSGS MN ((JC),). inCOL1A1 IgAN (K expression), and MN corre (L). Pearson’slated to FSTL1 correlation mRNA coefficient levels in ( rFSGS) was ( determined,D), in IgAN and(E), and two-tailed in MNp (Fvalues). FN1derived. expression Significance correlated wasto FSTL1 determined mRNA as levels a p value in FSGS of <0.05. (G), in Linear IgAN regression (H), and MN generated (I). ACTA2 the line expression of best fit correlated (solid lines) to FSTL1 with 95% mRNA confidence levels in intervalsFSGS (J), (dotted in IgAN lines). (K), and MN (L). Pearson’s correlation coefficient (r) was determined, and two-tailed P values derived. Significance was determined as a p value of <0.05. Linear regression generated the line of best fit (solid lines) with 95% confidence intervals (dotted lines). Int. J. Mol. Sci. 2021, 22, x FOR PEER REVIEW 27 of 41 FSTL1 mRNA levels were strongly associated with CCL2 mRNA levels: FSGS (r = 0.69, p < 0.0001) (Figure 25A), IgAN (r = 0.80, p < 0.0011) (Figure 25B), and MN (r = 0.70, p Int. J. Mol. Sci. 2021, 22, 9513 < 0.001) (Figure 25C) and associated with TNFA mRNA levels: FSGS (r = 0.49, p < 0.0001) 26 of 38 (Figure 25D), IgAN (r = 0.55, p < 0.0001) (Figure 25E), and MN (r = 0.44, p < 0.00014) (Figure 25F). F S G S I g A N M N A B C r 0.7007 1 5 r 0.6895 1 5 1 0 r 0.801 P (two-tailed) <0.0001 P (two-tailed) <0.0001 P (two-tailed) <0.0001 8 1 0 1 0 2 6 2 2 L L L C C C C C C 4 5 5 2 0 0 0 0 2 4 6 0 2 4 6 0 2 4 6 F S T L 1 F S T L 1 F S T L 1 M N D I g A N F E 0 . 6 F S G S 1 . 0 r 0.5469 r 0.4373 1 . 5 0 . 8 P (two-tailed) 0.0019 r 0.4901 P (two-tailed) 0.0026 0 . 4 0 . 6 A 1 . 0 P (two-tailed) <0.0001 A F F N N T 0 . 4 T A 0 . 2 F 0 . 5 N 0 . 2 T 0 . 0 0 . 0 0 . 0 0 2 4 6 2 4 6 0 2 4 6 F S T L 1 F S T L 1 F S T L 1 - 0 . 5 Figure 25. Relationship of FSTL1 mRNA Levels to the Expression of Genes Implicated in Inflammation in FSGS (red), IgAN (orange), and MN (purple). CCL2 expression correlated to FSTL1 mRNA levels in FSGS (A), in IgAN (B), and MN (C). TNFA Figure 25. Relationship of FSTL1 mRNA Levels to the Expression of Genes Implicated in Inflammation in FSGS (red), expressionInt. correlatedJ. Mol.IgAN Sci. (orange) 2021 to, 22FSTL1, xand FOR MN PEERmRNA (purple) REVIEW levels. CCL2 inexpression in FSGS correlated (D), in to IgAN FSTL1 ( EmRNA), and levels MN in (F FSGS). Pearson’s (A), in IgAN correlation (B), and MN coefficient28 of 41 (r) with two-tailed (C).p TNFAvalues expression were calculated. correlated to Significance FSTL1 mRNA was levels determined in in FSGS (D as), in a pIgANvalue (E), of and <0.05. MN ( LinearF). Pearson’s regression correlation generated the line of best fitcoefficient (solid lines) (r) with with two- 95%tailed confidencep values were intervalscalculated. Significance (dotted lines). was determined as a p value of <0.05. Linear regression generated the line of best fit (solid lines) with 95% confidence intervals (dotted lines). F S G S Finally, we looked at apoptosisI g A N -related genes. FSTL1 mRNAM N levels were modestly A r 0.2788 B C 5 associated with4 BAX mRNA r 0.3264 levels: FSGS (r = 0.29, p4 < 0.0036) (rFigure0.2556 26A), IgAN (r = 0.32, P (two-tailed) 0.0036 P (two-tailed) 0.0550 4 p < 0.06) (Figure 26P (two-tailed)B), and MN0.0683 (r = 0.26, p < 0.06) (Figure 26C). FSTL1 mRNA levels were 3 3 more strongly associated with CASP3 mRNA levels: FSGS (r = 0.44, p < 0.0001) (Figure 3 X X X A A A 26D), IgAN (r =2 0.38, p < 0.03) (Figure 26E), and MN2 (r = 0.41, p < 0.0018) (Figure 26F), and B B B 2 CASP8 mRNA levels in FSGS (r = 0.37, p < 0.0001) (Figure 26G) and MN (r = 0.40, p < 0.0028) 1 1 1 (Figure 26I). There was a trend that occurred for CASP8 that did not reach statistical 0 significance in IgAN0 (Figure 26H). 0 0 2 4 6 0 2 4 6 0 2 4 6 F S T L 1 F S T L 1 F S T L 1 D F S G S E I g A N F M N 5 r 0.4421 4 r 0.3752 4 r 0.4079 P (two-tailed) <0.0001 P (two-tailed) 0.0344 P (two-tailed) 0.0018 4 3 3 3 3 3 3 P P P S S 2 S 2 A A A C C C 2 1 1 1 0 0 0 0 2 4 6 0 2 4 6 0 2 4 6 F S T L 1 F S T L 1 F S T L 1 F S G S I g A N M N G r 0.3708 H r 0.1751 I 3 3 3 r 0.396 P (two-tailed) <0.0001 P (two-tailed) 0.3548 P (two-tailed) 0.0028 2 2 2 8 8 8 P P P S S S A A A C C C 1 1 1 0 0 0 0 2 4 6 0 2 4 6 0 2 4 6 F S T L 1 F S T L 1 F S T L 1 Figure 26. Relationship of FSTL1 mRNA levels to the Expression of Genes implicated in Apoptosis in FSGS (red), IgAN (orange), andFigure MN (purple). 26. RelationshipBAX expressionof FSTL1 mRNA correlated levels to the to FSTL1 ExpressionmRNA of Genes levels implicated in FSGS in (ApoptosisA), in IgAN in FSGS (B), (red) and, IgAN MN (C). CASP3 expression correlated(orange), and to MNFSTL1 (purple)mRNA. BAX levelsexpression in incorrelated FSGS (toD ),FSTL1 in IgAN mRNA ( Elevels), and in FSGS MN ( AF),). inCASP8 IgAN (Bexpression), and MN (C correlated). to CASP3 expression correlated to FSTL1 mRNA levels in in FSGS (D), in IgAN (E), and MN (F). CASP8 expression correlated FSTL1 mRNAtolevels FSTL1 inmRNA in FSGS levels (inG ),in inFSGS IgAN (G), (inH ),IgAN and (H MN), and (I ).MN Pearson’s (I). Pearson’s correlation correlation coefficient coefficient ( (r)r )with with two two-tailed-tailed p p values were calculated.values Significance were calculated. was Signifi determinedcance was determined as a p value as a ofp value <0.05. of <0.05. Linear Linear regression regression generated generated the the line line of best of bestfit fit (solid (solid lines) with 95% confidence intervals (dotted lines). lines) with 95% confidence intervals (dotted lines). 3. Discussion There is still a limited understanding of the mechanism(s) responsible for the progression of CKD [17]. Here, we present an experimental design and microarray-based approach to identify new genes that may play a role in the progression of tubule- interstitial (TI) injury. We utilized Col4a3–/– mice because they develop early proteinuria followed by TI inflammation and fibrosis leading to mortality by 9–10 weeks of age [5,7]. Proteinuria is an important risk factor for loss of kidney function in human kidney disease [18]. Although developed as a model of Alport Syndrome, studies of Col4a3–/– mice may also provide insights into the pathogenesis of a wider spectrum of kidney disease because the Col4a3 gene plays a role in both sporadic and familial FSGS as well as diabetic nephropathy [19,20]. Moreover, changes in the TI of the kidney, in particular fibrosis and tubular atrophy, correlate inversely with GFR [21,22]. We first conducted an analysis of differential gene expression in 4 week old and 7 week old Col4a3+/+ mice and Col4a3–/– mice. Albuminuria is already elevated at 4 weeks of Int. J. Mol. Sci. 2021, 22, 9513 27 of 38 3. Discussion There is still a limited understanding of the mechanism(s) responsible for the pro- gression of CKD [17]. Here, we present an experimental design and microarray-based approach to identify new genes that may play a role in the progression of tubule-interstitial (TI) injury. We utilized Col4a3-/- mice because they develop early proteinuria followed by TI inflammation and fibrosis leading to mortality by 9–10 weeks of age [5,7]. Protein- uria is an important risk factor for loss of kidney function in human kidney disease [18]. Although developed as a model of Alport Syndrome, studies of Col4a3-/- mice may also provide insights into the pathogenesis of a wider spectrum of kidney disease because the Col4a3 gene plays a role in both sporadic and familial FSGS as well as diabetic nephropa- thy [19,20]. Moreover, changes in the TI of the kidney, in particular fibrosis and tubular atrophy, correlate inversely with GFR [21,22]. We first conducted an analysis of differential gene expression in 4 week old and 7 week old Col4a3+/+ mice and Col4a3-/- mice. Albuminuria is already elevated at 4 weeks of age, but as we have previously reported, there is little focal glomerulosclerosis, interstitial fibrosis, or inflammation evident in light microscopy. Electronic microscopy will show focal thinning and splitting of the GBM [5,7]. Serum creatinine levels are similar in 4 week old Col4a3+/+ mice and 4 week old Col4a3-/- mice so that GFR has not yet declined. As expected, Col4a3-/- mice already exhibit higher levels of expression of the mature collagens, Col4a3, Col4a4 than Col4a5, at 4 weeks of age, compared to the immature collagens, Col4a1 and Col4a2. This developmental switch in collagen gene expression does not occur in Col4a3-/- mice, and the maintenance of expression of Col4a1 and Col4a2 is especially evident at 7 weeks of age. This abnormal gene expression pattern is associated with even higher albumin excretion rates and a rise in serum creatinine in the Col4a3-/- mice [7]. Our first major observation was that only four genes, apart from Col4a3, were differ- entially expressed in the kidneys of 4 week old Col4a3+/+ mice compared to 4 week old Col4a3-/-. Zfp747 was the only other down-regulated gene. Zfp747 is one of approximately 350 genes in the family of Kruppell-associated box (KRAB) domain-containing zinc finger proteins. The function of this protein is unknown although other family members have been implicated in the regulation of gene transcription and DNA methylation. It has not been studied in kidney disease. The gene Mfap4 encoding microfibril associated protein 4 was up-regulated at 4 weeks of age. This extracellular matrix protein binds to collagens, elastin, and fibrillin-1, and it is a paralog of fibronectin. Recent studies have linked Mfap4 to liver fibrosis, cardiac dysfunction, and kidney fibrosis [23–25]. The gene Cald1 encodes caldesmin-1, an intracellular protein that regulates cell contraction and interacts with the actin cytoskeleton. Interestingly, Cald1 mRNA levels are also elevated in the glomeruli of humans with diabetic nephropathy [26]. There was a sustained increase in expression of both Mfap4 and Cald1 in the kidneys of 7 week old Col4a3-/- mice. Fstl1 was the third gene in which the mRNA levels were elevated at 4 weeks of age, and we chose to focus our studies on Fstl1 because it is a secreted extracellular protein known to be a ligand for Toll-like receptors [27]. Fstl1 has been linked to pulmonary fibrosis and inflammation, particularly in experimental arthropathies [28,29]. Fstl1 may play a role in cisplatin-induced acute kidney injury [30]. Studies in a remnant kidney model of CKD suggested that it functioned as an endocrine factor produced by the heart, secreted, and then delivered to the kidney by renal blood flow [30]. In contrast, the Protein Atlas suggested that it was endogenously expressed in kidney tubular epithelial cells, and studies suggested that in UUO kidneys, Fstl1 was expressed in cells of the loop of Henle and/or collecting duct [31]. Accordingly, our next major finding was that Fstl1 is expressed in cells in the interstitial compartment of the kidney. Our RNAScope© analysis also showed that there is very little expression in normal kidneys. Single cell transcriptomic data localized expression to fibroblasts/myofibroblasts and not in tubular epithelial cells. We previously described cell populations contributing to progression signature gene expression, and one of the important themes that emerged from this work was that fibroblasts contributed to Int. J. Mol. Sci. 2021, 22, 9513 28 of 38 CKD progression in Col4a3-/- mice [6]. Taken together, these findings show that Fstl1 is fibroblast-derived. To further explore the potential paracrine role of Fstl1 in the kidney we next looked at the expression of putative Fstl1 receptors in the kidney: three receptors have been identified. The first is Toll-like receptor-four (Tlr4)[27]. Tlr4 is expressed in tubular epithelial cells as well as in infiltrating monocytes/macrophages Leucocytes, including macrophages, and renal epithelial cells express the Tlr4 receptor, and it does play a role in kidney injury [32]. Zhang and coworkers showed that deletion of the gene for Tlr4 attenuated cisplatin-induced kidney injury. In order to determine if the effect is due to loss of Tlr4 in myeloid cells or loss of Tlr4 in renal tubular cells the investigators generated bone marrow chimeric mice. They found that the protective effect of Tlr4 gene deletion was due to loss of expression in kidney tubular cells [32]. This work supports our notion that FSTL1 could function as a paracrine factor in the kidney to affect the progression of chronic kidney disease by engaging Tlr4 receptors on kidney tubular cells. Cd14 is also linked to the ligand- like function of Fstl1, and it is predominantly expressed in monocytes/macrophages [27]. Interestingly tubular epithelial expression of Cd14 is up-regulated in murine models of kidney injury [33]. Disco Interacting Protein 2 Homolog A (Dip2a) is the third receptor linked to Fstl1 cell signaling but little is known about the intracellular pathways activated by the receptor [34]. Vascular tissue including the kidney expresses Dip2a [12,34]. We next found that both Tlr4 and Cd14 were up-regulated in Col4a3-/- mice. Tlr4 expression was increased at 7 weeks of age while Cd14 was already increased at 4 weeks of age in Col4a3-/- mice compared to Col4a3+/+ mice. These findings support the hypothesis that activation of this ligand/receptor pathway increases in Col4a3-/- mice and thus Fstl1 can readily function in a paracrine manner in the kidney. To test this hypothesis in vitro, we studied the effect of rhFSTL1 on cultured kidney epithelial cells and focused on three biological processes important in chronic kidney disease pathogenesis: fibrosis, inflammation, and apoptosis. AP1-mediated gene expression is postulated to play a key role in the regulation of gene expression related to fibrosis [35]. rhFSTL1 activates ERK in a time-dependent manner, and AP1 is downstream of ERK activation. rhFSTL1 also activated AP1-mediated gene expression in kidney tubular cells based on the activation of an AP1 promoter construct that drove firefly luciferase expression. It is possible that fibroblast derived FSTL1 could function in a paracrine manner to activate canonical MAPK (ERK) signaling in tubular cells converging on AP1. We then compared the expression levels of a defined set of genes that are regulated by AP1 in 4 and 7 week old Col4a3-/- mice compared to Col4a3+/+ mice. There was a marked increase in the expression of the majority of the AP1-mediated genes including plasminogen activator, urokinase receptor (Plaur), matrix metalloproteinase 10 (Mmp10), and interleukin1 receptor-like1 (Il1rl1). Plaur promotes plasmin formation and plays a role in the regulation of extracellular matrix protein degradation as well as the activation of growth factors including TGFB1. Mmp10 also regulates extracellular matrix protein degradation [36]. Taken together, the changes in the expression of these two genes emphasize the important role of extracellular matrix remodeling in the progression of fibrosis in the kidneys of Col4a3-/- mice. Il1rl1 is a member of the interleukin 1 receptor family, and it may be pro-inflammatory linking AP1-regulated gene expression to inflammation in the kidney [37]. Although it is very unlikely that FSTL1 is the only ligand contributing to the activation of these genes in vivo, we also saw strong correlations between Fstl1 mRNA levels and the mRNA levels of alpha smooth muscle actin (Acta2), transforming growth factor beta (Tgfb1), Col1a1, and Fn1. Indeed, over 80–90 percent of the variability in the levels of these genes is associated with the variability in Fstl1. Western blot analysis showed that rhFSTL1 led to an increase in COL1A1 protein expression. We then studied the effect of rhFSTL1 on cultured kidney epithelial cells and focused on inflammation. NFκB-mediated gene expression is postulated to play a key role in the regulation of gene expression related to inflammation [38]. One of the canonical MAPKs, p38, is classically upstream of NFκB. rhFSTL1 activates p38 in a time-dependent manner, Int. J. Mol. Sci. 2021, 22, 9513 29 of 38 and NFκB is downstream of ERK activation [39]. rhFSTL1 also activated NFκB-mediated gene expression in kidney tubular cells based on the activation of an NFκB promoter construct that also drove firefly luciferase expression. It is therefore possible that fibroblast- derived FSTL1 could function in a paracrine manner to activate canonical MAPK (p38) signaling in tubular cells converging on NFκB. We next compared the expression levels of a defined set of genes that are regulated by NFκB in 4 and 7 week old Col4a3-/- mice compared to Col4a3+/+ mice. There were marked increases in expression in most of the NFκB -mediated genes including Il6, Ccl2, Icam1, and Vcam1. The latter three genes play a role in the recruitment of inflammatory cells including monocytes/macrophages to the kidney [40,41]. These observations are consistent with our recent report that a progression gene signature in Col4a3-/- mice reflected at least in part, increased infiltrating inflammatory cells [6]. Again, FSTL1 is not the only ligand to increase expression of these genes in vivo, but we were able to see strong correlations between Fstl1 mRNA levels and the mRNA levels of Ccl2 and Tnfa, two cytokines implicated in the progression of chronic kidney disease [42]. Almost 90 percent of the variability in the levels of these genes relates to the variability in Fstl1, based on Spearman correlation analysis. Western blot analysis showed that rhFSTL1 led to an increase in COX2 protein expression. Finally, we then studied the effect of rhFSTL1 on cultured kidney epithelial cells and focused on apoptosis because tubular atrophy is a common finding in chronic kidney disease [43]. rhFSTL1 treatment led to PARP cleavage and CASP3 activation in kidney tubular cells in vitro. Interestingly, this effect was downstream of TLR4 because pre- treatment with the TLR4 receptor antagonist, naloxone, abrogated the effect. Fibroblast derived FSTL1 could function in a paracrine manner to induce apoptosis in adjacent kidney tubular cells and contribute to the loss of kidney tubular cell mass or tubular atrophy. We next compared expression levels of a set of genes that play a role in apoptosis in 4 and 7 week old Col4a3-/- mice compared to Col4a3+/+ mice. There was a marked increase in expression in most of the apoptosis genes, including Bax, Fas, Rela, Casp3, and Casp8, although it is again likely that many different ligands influence the expression of these genes in vivo. We were able to see strong correlations between Fstl1 mRNA levels and the mRNA levels of Bax, Rela, and Casp8. Fstl1 accounted for between 60 and 90 percent of the variability in the levels of these genes, based on Spearman correlation analysis. Taken together, these in vivo and in vitro findings suggest that FSTL1 promotes the progression of chronic kidney disease in Col4a3-/- mice and that it functions in a paracrine manner to influence the biology of tubular cells and infiltrating monocytes/macrophages, although we did not examine the latter directly. Adams and coworkers studied the role of FSTL1 in acute kidney injury secondary to cisplatin and they suggested that FSTL1 was protective [30]. They utilized a mouse with a hypomorphic Fstl1 gene and found that there was less inflammation in the hypomorphic mice and more kidney injury after administration of cisplain. This is interesting because they examined mRNA levels of Il6 and Tnfa. They assessed tubular injury by measuring Kim1, and these findings suggest that the role of FSTL1 in kidney injury may be context specific [30]. Our finding of the localization of Fstl1 in the interstitial compartment of the kidney is the first study to employ an in situ hybridization-like technique. Antibody-based studies have previously localized FSTL1 to the loop of Henle [30,44], but RNAScope© is not dependent on antibody specificity or confounded by kidney cell auto-fluorescence. This may account for our novel finding. Single cell transcriptomic data from human kidneys confirmed that Fstl1 was restricted to the interstitial compartment and localized in fibroblasts and activated myofibroblasts. Moreover, studies of cutaneous wound healing strongly implicated FSTL1 in scar formation, and localized its expression to fibroblasts, in accordance with our work [45,46]. A novel feature of our studies was the definition of an Fstl1 gene signature. In order to perform an unbiased assessment of the potential role of Fstl1 in the progression of CKD in Col4a3-/- mice we completed an in silico analysis of FSTL1 protein–protein interactions using STRING analysis. This analysis was independent of our studies of gene expression, and it generated a novel network of proteins linked to FSTL1 based on evidence Int. J. Mol. Sci. 2021, 22, 9513 30 of 38 in the experimental literature—in a sense, an FSTL1 signature. We created four networks consisting of 5 to 20 proteins by limiting the output of the number of interacting proteins. A colored node represents each protein in the network. The color of the edge connecting two nodes indicates the type of interaction. For example, “experimentally derived” data linking FSTL1 to another protein is a purple edge while “gene co-occurrence” between FSTL1 and another protein is a dark blue edge. In STRING, each protein–protein interaction generates scores that in combination yield a final interaction score. The interaction score does not indicate the strength or even the specificity of the protein–protein interaction, but the final score does indicate the confidence or likelihood that an interaction is true given the evidence used to calculate the score. The scores can range from 0 to 1. The higher the score the greater the confidence [47]. Scores for the individual proteins in the FSTL1 interaction network are shown in the last column of Figure 15, Panel A and range from 0.915–0.973, suggesting that the analysis yielded proteins with a high likelihood of interacting with FSTL1. We then generated a heat map based on the expression levels of the genes for the proteins in the 20 protein STRING diagram. Several of the genes in this list of proteins were over-expressed in the 7 week old Col4a3-/- mice compared to the 7 week old Col4a+/+ mice as illustrated in the heat map. A number of extracellular matrix proteins are part of this FSTL1 signature, including laminins (LAMB1and LAMC) and fibronectin (FN1) along with extracellular proteins that regulate matrix protein turnover. This group included the tissue inhibitor of metalloproteinase-one (TIMP1) and Latent Transforming Growth Factor Beta Binding Protein-one (LTBP1), the latter a protein involved in the activity of TGFB1, a pro-fibrotic cytokine. Bone morphogenic proteins were also part of the STRING network (BMP2 and BMP4). Together with our observations on AP1, the STRING analysis also relates FSTL1 to re-modeling of the extracellular matrix and the development of interstitial fibrosis, a critical event that is characteristic of progressive CKD [48]. We extended our studies of Fstl1 and its receptors Tlr4 and Dip2a in another exper- imental model of chronic kidney disease: murine UUO. This model of kidney injury is associated with marked increases in the expression of genes involved in kidney fibrosis (Acta2, Tgfb1, Col1a1, and Fn1) and inflammation (Ccl2 and Tnfa) 7 days after ligation of the ureter. There was a 10-fold increase in Fstl1 and an 8-fold increase in Tlr4 expression after 7 days. Dip2a also increased 4-fold. An RNAScope© analysis also showed that there is very little expression in the normal kidney and that the increase in Fstl1 in the UUO kidney occurs in the interstitial compartment, as we had observed in the Col4a3-/- mice. Fstl1 and its cognate receptors are therefore up-regulated in two different models of experimental CKD, one associated with early glomerular injury and progressive proteinuria and another associated with urinary tract obstruction. These observations spurred us to extend our analysis of Col4a3-/- mice to human CKD. Our studies of human CKD involved subjects recruited to the NEPTUNE consortium study of proteinuric CKD with three common kidney diseases: focal segmental glomeru- losclerosis (FSGS), IgA nephropathy (IgAN) and membranous nephropathy (MGN). We examined these diseases because each is a glomerular disease process characterized by progressive injury, declining function, and proteinuria. Interestingly, COL4A mutations have emerged in patients with CKD beyond Alport syndrome, including FSGS, increasing the relevance of our studies in Col4a3-/- mice [19]. There are several strengths related to the use of this cohort of patients. First, extensive clinical data and long-term follow-up of kidney outcomes are available. Kidney biopsy samples were microdissected at baseline and gene expression profiles were derived from both the glomerular and tubule-interstitial compartments. In addition, kidney biopsy samples were subjected to protocol assessment of kidney injury including tubulo-interstitial fibrosis (IF) and tubular atrophy (TA). These experimental protocols allow for the study of gene expression and the relationship of gene expression to both clinical variables and pathological assessment of the kidney biopsy. Finally, the protocol-driven collection of longitudinal clinical data allows for the study of relationships between gene expression and kidney outcomes. Int. J. Mol. Sci. 2021, 22, 9513 31 of 38 We first studied the three cohorts as a single group to relate FSTL1 expression to clinical variables like age, sex, BMI, blood pressure, eGFR, and urinary protein excretion (UPCR). We chose to look at sex because it is an important determinant of kidney outcomes while BMI and blood pressure relate to poor kidney outcomes. We first observed that FSTL1 expression in the kidney tubule-interstitial compartment was similar in males than females at baseline (recruitment to NEPTUNE). Univariate analysis of FSTL1 mRNA levels and age, BMI, blood pressure (both sitting systolic and diastolic pressure) showed no significant relationships between these variables and FSTL1 mRNA levels. In contrast, there was a significant inverse relationship between eGFR and FSTL1 mRNA levels such that the higher the FSTL1 expression, the lower the eGFR value at recruitment to NEPTUNE. Interestingly, we observed a positive relationship between the UPCR. This suggests that proteinuria may be an important determinant of FSTL1 expression, although we did not define a causal relationship. Given the above findings, we performed a multiple linear regression analysis in which we related FSTL1 expression to age, sex, BPSS, BPSD, eGFR, and UPCR. Age, eGFR, and UPCR were associated with FSTL1 expression in the three groups of subjects as a whole. In an unadjusted analysis of the relationship between FSTL1 mRNA quartiles and the composite clinical outcome of ESKD or a 40% loss of kidney function, we found that the odds ratio of reaching this composite was 2.67 (1.05, 6.76) in the highest quartile of FSTL1 mRNA levels compared to the first, second, and third quartiles. We compared mean values for eGFR, interstitial fibrosis (IF), and tubular atrophy (TA) between the first and fourth quartile for FSTL1 mRNA levels and mean values for eGFR were significantly lower in the fourth quartile compared to the first quartile while mean values for IF and TA were greater. In accord with the increase in IF mean values for the mRNA levels of COL1A1, ACTA2, and TGFB1 were all increased in the fourth quartile compared to the first quartile. In a similar manner, genes for the apoptosis proteins, CASP3 and CASP8 were higher in the fourth quartile like the measures of TA. There was also an increase in genes related to inflammation (CCL2 and TNFA). Taken together, high FSTL1 mRNA levels in the kidney identify subjects with lower eGFR, more chronic kidney injury based on IF and TA, and higher levels of genes implicated in fibrosis, inflammation, and apoptosis, cellular processes responsible for progressive loss of function. We next divided the NEPTUNE cohort into the three groups based on underlying pathological diagnosis and looked at the correlation between FSTL1 mRNA levels and kidney function IF, and TA in each cohort separately. The relationships in all three groups re-capitulated the analysis of the whole group. There were positive associations between FSTL1 levels and genes involved in fibrosis and apoptosis that were similar in all three cohorts. Once again, these relationships do not establish causality but together strengthen the hypothesis that kidney expression of FSTL1 contributes to progressive loss of function, kidney fibrosis, and loss of functioning nephron mass, and taken together with our in vitro observations do not support the hypothesis that FSTL1 limits kidney injury. Moreover, changes in kidney expression of FSTL1 are important and it is tempting to speculate that paracrine effects of fibroblast-derived FSTL1 are responsible for the relationships that we have identified in experimental and clinical CKD. An important limitation of the current study is that we did not establish the mech- anism(s) responsible for the early and sustained increase in kidney FSTL1 expression in Col4a3-/- mice. Sundaram and coworkers were studying the role of FSTL1 keratinocytes in chronic wound healing [45]. FSTL1 promotes wound healing by virtue of its effects on fibrosis, analogous to the role we think that it plays in chronic kidney disease [45]. Chronic fibrotic disease may be wound healing gone awry, at least in part, as first articulated by Wayne Border in a review on TGFB1 [49]. Sundaram discovered that a post-transcriptional switch regulated expression of FSTL1. This switch is due to microRNA-198 (miR-198) encoded in the 30-umtranslated FSTL1 transcript. A protein called KH-type splicing reg- ulatory protein (KHSRP) influences the processing of the FSTL1 mRNA transcript and Int. J. Mol. Sci. 2021, 22, 9513 32 of 38 decreases translation to the mature protein. TGFB1 reduces the expression of KHSRP and increases the translation of FSTL1 [45]. There was no increase in Tgfb1 mRNA levels in the 4 week old Col4a3-/- mice, but acti- vation of TGFB1 is independent of transcript levels so it may still promote early increases in FSTL1 if there is a release of mature TGFB1 from its latent complex [50]. Increased reactive oxygen species can activate TGFB1 and the binding and internalization of albumin by proximal tubule cells generate superoxides [50,51]. Such an effect could contribute to early TGFB1 activation in the kidney interstitial space in Col4a3-/- mice. There was a three-fold rise in albuminuria in the 4-week-old Col4a3-/- mice compared to the 4-week-old Col4a3+/+ mice. This mechanism cannot account for the rise in Fstl1 in the UUO mice because this model of kidney injury is not associated with albuminuria. However, UUO is associated with increased oxidative stress likely due to mechanical strain on the tubular epithelial cells. Moreover, we did see increases in Tgfb1 mRNA levels in the UUO mice. Although increased oxidative stress may be a common pathway leading to TGFB1 activation and a subsequent increase in FSTL1 in the kidney, it is also possible that activation of the renin angiotensin system contributes to TGFB1 activation. Border and coworkers reported that angiotensin II also activates TGFB1 [52]. Angiotensin II generation increases in both the Col4a3-/- mice and in mice subjected to UUO [53]. Overall, the contribution of these processes to the increase in FSTL1 occurring in the kidney will require future study. Our study has other limitations. We did not perform any immunohistochemistry of FSTL1 or any dual labeling immunohistochemistry to improve localization to particular kidney segments. The utilization of a kidney single cell transcriptional dataset along with RNAscope® in our experimental model allowed us to take an independent approach to the localization of FSTL1. Dual labeling is thus a future goal so that we may gain a better understating of the kidney cells responsible for the secretion of FSTL1. We did not study the impact of deletion of the gene for Fstl1 in either the Col4a3-/- mice or in the mice subjected to UUO. Deletion of the gene for Fstl1 is neonatal lethal. This has limited past approaches to the use of hypomorphic alleles. The generation of a fibroblast-specific Fstl1 gene knockout mouse is the most definitive approach to defining the effect of Fstl1 on progressive fibrosis, but the generation of a mouse that also has Col4a3 gene deletion would require a complex breeding strategy. Subjecting transgenic mice to UUO would be more straightforward with the caveat that this mouse model is not associated with proteinuria. Moreover, future work will be required to determine kidney tissue concentrations of FSTL1 to better support in vitro studies of the effect of FSTL1 on kidney cells and mononuclear cells, including studies on cell proliferation. Another important limitation of our report is the absence of an attempt to block FSTL1 activity. Neutralizing antibodies have blocked FSTL1 bioactivity in models of lung injury [54] but the specific reagents used by these investigators are not commercially available. Finally, our analysis of the relationship between FSTL1 levels and kidney outcomes in the NEPTUNE cohort was unadjusted. Therefore, our analysis is exploratory, hypothesis-generating, and meant to support a more definitive future analysis using Kaplan–Meier (K-M) survival curve and Cox proportional-hazards modeling. The predictive value of FSTL1 remains to be determined. Finally, we did not relate urinary FSTL1 to expression in the kidney and to interstitial fibrosis in the kidney. This analysis would help determine if urinary FSTL1 might be a non-invasive marker of kidney fibrosis. In conclusion, our studies show that FSTL1 is a fibroblast-derived cytokine expressed in the kidney and up-regulated in both experimental and clinical chronic kidney disease. Our in vivo, in vitro, and in silico analyses suggest that FSTL1 contributes to fibrosis, inflammation, and apoptosis in the kidney. FSTL1 may be a new treatment target in chronic kidney disease. 4. Material and Methods 4.1. Animals All animal experiments conducted in this study were approved by the University of Toronto Faculty of Medicine Animal Care Committee (protocol no. 20011495) per the Int. J. Mol. Sci. 2021, 22, 9513 33 of 38 Regulations of the Animals for Research Act in Ontario and the Guidelines of the Canadian Council on Animal Care. Col4a3-/- mice (stock no. 002908) on the 129X1/SvJ background, WT controls (stock no. 000691), and C57BL/6J mice (stock no.000664) were purchased from The Jackson Laboratory (Bar Harbor, ME, USA). Mice were housed at the Division of Comparative Medicine (University of Toronto, Toronto, ON, Canada) in a 12-h dark–light cycle and fed standard rodent diet (2018 Teklad global 18% protein) purchased from Envigo (Huntingdon, UK), with free access to water. Only male mice were used in this study. Mice were randomly assigned to control and treatment groups. Investigators were not blinded unless otherwise stated. Numbers of biological replicates are stated within figure legends. 4.2. Cell Culture Immortalized human proximal tubule epithelial (HK-2) cells were cultured in Gibco DMEM/F-12 (Thermo Fisher Scientific, Waltham, MA, USA) supplemented with 10% fetal bovine serum (Thermo Fisher Scientific), 10 ng/mL epidermal growth factor (Millipore- Sigma, Burlington, MA, USA), 5 µg/mL transferrin (MilliporeSigma), 5 µg/mL insulin (MilliporeSigma), 0.05 µM hydrocortisone (MilliporeSigma), 50 U/mL penicillin (Thermo Fisher Scientific), and 50 µg/mL streptomycin (Thermo Fisher Scientific). Cells were main- tained at 37 ◦C with 5% CO2. HK-2 cells were subcultured in six-well plates and then starved of serum overnight. For phosphorylated ERK and p38 immunoblots, cells were treated with DMEM/F-12 medium for control and 125 ng/mL rhFSTL1 (Novus Biologicals NBP2-23056) in DMEM/F-12 medium for either 5, 10, 30, 60, or 120 min. For PARP and CASP3, cells were treated with DMEM/F-12 medium for control, 125 ng/mL rhFSTL1 in DMEM/F-12 medium for 16 h, or 1 µm of Naloxone in DMEM/F12 for 8 h the subsequently treated with 125 ng/mL rhFSTL1 in DMEM/F-12 medium for 16 h. For COX2, cells were treated with DMEM/F-12 medium for control or 125 ng/mL rhFSTL1 in DMEM/F-12 medium for 18 h. For COL1A1, cells were treated with DMEM/F-12 medium for control or 125 ng/mL rhFSTL1 in DMEM/F-12 medium for 48 h. 4.3. Immunoblotting Total protein extract was transferred to a tube with 5× SDS sample loading buffer and boiled at 95 ◦C for 5 min. Proteins were separated by SDS-PAGE and then transferred onto PVDF membranes. Membranes were blocked and subsequently incubated with primary antibodies overnight at 4 ◦C. Primary antibodies were used at a dilution of 1:1000, except where otherwise indicated. The following rabbit primary antibodies were purchased from Cell Signaling Technology: phospho-p44/42 MAPK (ERK1/2; cat no. 9101), p44/42 MAPK (ERK1/2; cat no. 9102), phospho-p38 MAPK (1:500; cat no. 9211), p38 MAPK (1:500; cat no. 9212), COX2 (cat no. 12282), PARP (cat no. 9542), CASP3 (cat no. 9664). COL1a1 was purchased from Cedarlane (product code: CL50151AP-1) The mouse primary antibody for b-actin (1:4000; cat no. A5441) was purchased from MilliporeSigma. Membranes were incubated with HRP-conjugated goat anti-rabbit (cat no. 7074) and bands were detected by enhanced chemiluminescence with the Luminata Forte Western HRP Substrate (MilliporeSigma). Densitometry was performed with Scion Image (Scion Corporation, Frederick, MD). For FSTL1 membranes were blocked and subsequently incubated with FSTL1 (R&D system, cat no. AF1738) overnight at 4 ◦C at a dilution of 0.1 µg/mL. Membranes were then incubated with HRP-conjugated mouse anti-goat IgG antibody (merck-millipore). Bands were detected using (ImageQuant LAS 4000 mini, GE Healthcare) and Densitometry was performed with Scion Image (Scion Corporation, Frederick, MD, USA). 4.4. RNAscope® RNA Chromogenic in situ hybridization Visualization of mRNA transcript was per- formed using RNAScope® 2.5 (Advanced Cell Diagnostics, Hayward, CA, USA), according to the manufacturer’s instructions. A 20ZZ probe (RNAscope® Target Probe C1) was designed and named Mm-Fstl1 targeting 100–1102 of NM_008047.5. Int. J. Mol. Sci. 2021, 22, 9513 34 of 38 4.5. Luciferase Cells were transfected with Renilla luciferase control reporter vector pRL-TK and a luciferase reporter for either NFκB or AP-1 vector and incubated with fresh growth medium (DMEM/F-12) for 24 h, and then starved of serum (serum-free DMEM/F-12) for 24 h. Cells were then treated with 125 ng/mL rhFSTL1 for 24 h. The control group was treated with serum free DMEM/F-12 for 24 h. Reporter activities were measured using the Promega, Madison Wisconsin dual-luciferase assay kit. The luciferase activity was normalized to the Renilla luciferase activity. 4.6. Quantitative PCR Total RNA was purified using the RNeasy Mini Kit (Qiagen, Hilden, Germany) by fol- lowing the manufacturer’s protocol. cDNA was synthesized from purified template RNA with the QuantiTect Reverse Transcription Kit (Qiagen). Quantitative PCR was performed with Applied Biosystems TaqMan Gene Expression Assays (Thermo Fisher Scientific) run on a ViiA 7 Real-Time PCR System (Thermo Fisher Scientific). The mouse TaqMan Gene Expression Assays that were used include: Mm00433371_m1; Fstl1, Mm00445273_m1; Tlr4, Mm01150153_m1; Dip2a, Mm00441242_m1; Ccl2, Mm00443258_m1; Tnfa, Mm00725412_s1; Acta2, Mm01178820_m1; Tgfb1, Mm00801666_g1; Col1a1, Mm01256744_m1; Fn1. Values were determined using the relative standard curve method. Gapdh served as the house- keeping gene. 4.7. Histological Staining Three-micrometer formalin-fixed, paraffin-embedded kidney sections were used for periodic acid-Schiff (PAS), Masson’s trichrome (MTC), and α-SMA (SMA) staining. The rabbit primary antibody for α-SMA (cat no. ab5694) was purchased from Abcam. PAS and MTC as well as α-SMA were performed at the University Health Network Pathology Research Program Laboratory (Toronto, ON, Canada). 4.8. Heatmaps Heatmaps were generated using the gplots package in RStudio version 3.5.2. 4.9. Unilateral Ureteral Obstruction (UUO) Unilateral ureteral obstruction (UUO) 7 week old male C57BL/6J, mice were anes- thetized with inhalational 3% isoflurane and administered analgesic (buprenorphine, 0.1 mg/kg s.c.). A midline dorsal incision was made to expose the left kidney ureter which was ligated with a 4–0 suture. The contralateral (right) kidney served as the control. Body temperature was maintained during the procedure using a 37 ◦C heating pad. Inci- sions were closed using 4–0 sutures. After 7 days, the mice were euthanized, and kidneys were harvested. 4.10. Data Collection and Study Cohort Percutaneous kidney biopsies were obtained from patients after informed consent and with approval of the local ethics committees at each of the participating kidney centers. Written consent and assent were obtained. This covers all aspects of the study including clinical data, biospecimens and any derivatives. Clinical and gene expression information from patients is accessible in a non-identifiable manner. The University of Michigan institutional review board in the Department of Medicine (UMich IRBMED) is the institutional review board of record [55]. Biopsies from 211 subjects (78 females and 133 males) with nephrotic syndrome (FSGS, IgAN, MN) were microdissected into glomerular and tubulointerstitial components. Kidney biopsy tissue was manually micro-dissected to separate the tubulointerstitial com- partment from the glomerular compartment. Total RNA was isolated, reverse transcribed, linearly amplified and hybridized on an Affymetrix 2.1 ST platform as described previ- Int. J. Mol. Sci. 2021, 22, 9513 35 of 38 ously [55–57]. Gene expression was normalized, quantified, and annotated at the Entrez Gene level. Visual assessment was performed according to the Nephrotic Syndrome Study Net- work Digital Pathology Scoring System (NDPSS), on de-identified whole slide images of kidney biopsies according to the NEPTUNE digital pathology protocol (NDPP) [55]. Visual quantitative assessment of IF and TA was reported as 0–100%. Pathological assessment of IF and TA was performed according. Estimated glomerular filtration rate (eGFR) (mL/min/1.73 m2) was calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) formula for partici- pants ≥18 years old and the modified CKiD-Schwartz formula for participants <18 years old. Progression of eGFR was evaluated with a composite of 40% decline in eGFR from base- line or ESKD. ESKD was defined as the initiation of dialysis, receipt of kidney transplant or eGFR < 15 mL/min/1.73 m2 at two visits. 4.11. Statistics Statistics Numbers of cohorts and n values for each experiment are indicated in figure legends. Unless stated otherwise, data are reported as the mean ± SEM. Statistical analyses were performed using GraphPad Prism 7 (GraphPad Software, San Diego, CA, USA). p values were determined by two-tailed Student’s t-tests for comparisons between two groups or one-way ANOVA with Tukey’s multiple comparisons tests for comparisons between three groups or more. Author Contributions: Conceptualization, N.A.M. and J.W.S., Y.P.; generated experimental data, N.A.M., X.S.; formal analysis, N.A.M., X.S., R.J.; writing—original draft preparation, N.A.M., J.W.S., Y.P.; writing—review and editing, N.A.M., J.W.S., Y.P., H.R., R.J., X.S., E.H.B.; J.W.S. and Y.P. con- tributed to the manuscript equally. All authors have read and agreed to the published version of the manuscript. Funding: This research was funded by the Nephrotic Syndrome Study Network Consortium (NEP- TUNE). The Nephrotic Syndrome Rare Disease Clinical Research Network III (NEPTUNE) is part of the Rare Diseases Clinical Research Network (RDCRN), funded by the National Institutes of Health (NIH) and led by the National Center for Advancing Translational Sciences (NCATS) through its Office of Rare Diseases Research (ORDR). NEPTUNE (U54DK083912) is funded under a collaboration between NCATS and the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). Additional funding and/or programmatic support is provided by the University of Michigan, NephCure Kidney International and the Halpin Foundation. All RDCRN consortia are supported by the RDCRN Data Management and Coordinating Center (DMCC) (U2CTR002818). Institutional Review Board Statement: The study was conducted according to the guidelines of the Declaration of Helsinki, and approved by the University Health Network Research Ethics Board (CAPCR ID: 09-0122 May 21, 2009). All animal experiments were approved by the University of Toronto Faculty of Medicine Animal Care Committee and the Research Ethics Board (protocol #20011495) and conducted in accordance to Canadian Council on Animal Care (CCAC) guidelines. Informed Consent Statement: Informed consent was obtained from all subjects involved in the study. Acknowledgments: We thank team members from The Centre for Phenogenomics, the University Health Network PRP Laboratory, and The Centre for Applied Genomics, for their technical assistance. We would also like to thank Rachel Laframboise for contributing to the editing and proofreading of this manuscript. Suh from the Department of Internal Medicine, Chonnam National University Medical School and Chonnam National University Hospital, Gwangju, Korea for providing histology images. This work was supported by grants from the Canadian Institutes of Health Research (JWS), The Kidney Foundation of Canada (JWS), and the Alport Syndrome Foundation (JWS). Some of the instruments used in this study were supported by The 3D (Diet, Digestive Tract and Disease) Centre funded by the Canadian Foundation for Innovation and Ontario Research Fund, project numbers 19442 and 30961. Some of this work has been presented in abstract form at ASN Kidney Week. Members of the Nephrotic Syndrome Study Network (NEPTUNE): NEPTUNE Enrolling Centers: Cleveland Clinic, Cleveland, OH: K Dell *, J Sedor **, M Schachere #, J Negrey #. Children’s Hospital, Los Angeles, CA: K Lemley *, S Tang #. Children’s Mercy Hospital, Kansas City, MO: T Srivastava *, Int. J. Mol. Sci. 2021, 22, 9513 36 of 38 S Morrison #. Cohen Children’s Hospital, New Hyde Park, NY: C Sethna *, O Bullaro #. Columbia University, New York, NY: P Canetta *, A Pradhan #. Emory University, Atlanta, GA: L Greenbaum *, C Wang **, C Kang #. Harbor-University of California Los Angeles Medical Center: S Adler *, J LaPage #. John H. Stroger Jr. Hospital of Cook County, Chicago, IL: A Athavale *, M Itteera. Johns Hopkins Medicine, Baltimore, MD: M Atkinson *, T Dell #. Mayo Clinic, Rochester, MN: F Fervenza *, M Hogan **, J Lieske *, V Chernitskiy #. Montefiore Medical Center, Bronx, NY: F Kaskel *, M Ross *, P Flynn #. NIDDK Intramural, Bethesda MD: J Kopp *, J Blake #. New York University Medical Center, New York, NY: H Trachtman *, O Zhdanova **, F Modersitzki #, S Vento #. Stanford University, Stanford, CA: R Lafayette *, K Mehta #. Temple University, Philadelphia, PA: C Gadegbeku *, S Quinn- Boyle #. University Health Network Toronto: M Hladunewich **, H Reich **, P Ling #, M Romano #. University of Miami, Miami, FL: A Fornoni *, C Bidot #. University of Michigan, Ann Arbor, MI: M Kretzler *, D Gipson *, A Williams #, C Klida #. University of North Carolina, Chapel Hill, NC: V Derebail *, K Gibson *, E Cole #, J Ormond-Foster #. University of Pennsylvania, Philadelphia, PA: L Holzman *, K Meyers **, K Kallem #, A Swenson #. University of Texas Southwestern, Dallas, TX: K Sambandam *, Z Wang #, M Rogers #. University of Washington, Seattle, WA: A Jefferson *, S Hingorani **, K Tuttle **§, M Bray #, E Pao #, A Cooper #§. Wake Forest University Baptist Health, Winston-Salem, NC: JJ Lin *, Stefanie Baker #. Data Analysis and Coordinating Center: M Kretzler *, L Barisoni **, J Bixler, H Desmond, S Eddy, D Fermin, C Gadegbeku **, B Gillespie **, D Gipson **, L Holzman **, V Kurtz, M Larkina, S Li, S Li, CC Lienczewski, J Liu, T Mainieri, L Mariani **, M Sampson **, J Sedor **, A Smith, A Williams, J Zee. Digital Pathology Committee: Carmen Avila-Casado (University Health Network, Toronto), Serena Bagnasco (Johns Hopkins University), Joseph Gaut (Washington University in St Louis), Stephen Hewitt (National Cancer Institute), Jeff Hodgin (University of Michigan), Kevin Lemley (Children’s Hospital of Los Angeles), Laura Mariani (University of Michigan), Matthew Palmer (University of Pennsylvania), Avi Rosenberg (Johns Hopkins University), Virginie Royal (University of Montreal), David Thomas (University of Miami), Jarcy Zee (University of Pennsylvania) Co-Chairs: Laura Barisoni (Duke University) and Cynthia Nast (Cedar Sinai). * Principal Investigator; ** Co-investigator; # Study Coordinator. § Providence Medical Research Center, Spokane, WA. Conflicts of Interest: The authors declare no conflict of interest. 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