Perirenal fat β₃-adrenergic signaling alleviates renal fibrosis via regulating Bcat2/BCAA-TNFα pathway in diabetic kidney disease

Hongtu Hu; Rui Ji; Zikang Liu; Yuxin Ai; Shuiqin Gong; Mengying Yao; Wang Xin; Yuqi Zhu; Yinghui Huang

doi:10.1038/s41467-026-77325-2

. 2026 Aug 31;17:10352. doi: 10.1038/s41467-026-77325-2

Perirenal fat β₃-adrenergic signaling alleviates renal fibrosis via regulating Bcat2/BCAA-TNFα pathway in diabetic kidney disease

Hongtu Hu ^1,^2,^#, Rui Ji ^1,^#, Zikang Liu ³, Yuxin Ai ¹, Shuiqin Gong ¹, Mengying Yao ¹, Wang Xin ¹, Yuqi Zhu ¹, Yinghui Huang ^1,^✉

PMCID: PMC13623953 PMID: 42811043

Abstract

Tubulointerstitial fibrosis predicts irreversible kidney function loss in diabetic kidney disease (DKD), but adipose-derived signals that shape fibrogenesis are poorly defined. Here, we show that perirenal fat (PRF), an adipose depot contiguous with the kidney, is enriched for β₃-adrenergic receptor (ADRB3) and that ADRB3 expression is reduced in human DKD and male mouse DKD models. In db/db and streptozotocin/high-fat diet mice, increased PRF mass associates with albuminuria and serum creatinine, whereas PRF removal attenuates tubular lipid accumulation, mitochondrial injury and fibrosis. Brown adipocyte-lineage ADRB3 deletion enlarges PRF and increases adipocyte TNFα release by suppressing Bcat2-dependent branched-chain amino-acid catabolism through CREB1/METTL3-mediated m6A regulation. ADRB3 activation or PRF-restricted ADRB3 restoration reduces PRF inflammation and renal fibrosis, while iBAT-restricted restoration does not reproduce this renal protection. These findings identify a PRF ADRB3-Bcat2/BCAA-TNFα pathway that contributes to diabetic renal fibrosis.

Subject terms: Diabetes complications, Mechanisms of disease, End-stage renal disease

The authors identify perirenal fat ADRB3 signaling as a regulator of diabetic kidney fibrosis through a Bcat2/BCAA-TNFα pathway, suggesting adipose-kidney crosstalk as a potential therapeutic target.

Introduction

Diabetic kidney disease (DKD) is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD)¹. Approximately 20–40% of diabetic patients develop DKD during the course of their disease, which is often progressive². Current therapies can slow but not reverse DKD progression, reflecting an incomplete understanding of its underlying mechanisms³. Tubulointerstitial fibrosis is a hallmark of DKD and corresponds to irreversible loss of kidney function⁴. Sustained hyperglycemia and metabolic stress induce oxidative injury and inflammation in renal tubular cells, driving extracellular matrix accumulation and fibrosis⁵. However, interventions targeting oxidative stress or metabolism have not fully halted DKD, highlighting the need to define additional pathogenic mechanisms⁶.

Emerging evidence implicates visceral adiposity in DKD pathogenesis⁷. Adipose tissue secretes pro-inflammatory cytokines and chemokines that exacerbate renal inflammation and injury. In particular, perirenal fat (PRF), a depot of brown adipose tissue encasing the kidney, has been associated with DKD risk^8,9. Recently, we found that increased PRF thickness or volume predicts both onset and progression of DKD¹⁰. Although targeting inflammatory pathways serves as a candidate therapeutic strategy for DKD, the mechanisms by which PRF influences renal pathology remain unknown.

ADRB3 (β₃-adrenergic receptor) is highly expressed in brown adipocytes, which mediates lipolysis and thermogenesis¹¹. ADRB3 signaling promotes energy expenditure and fatty acid oxidation in adipose tissue¹². Notably, ADRB3 expression is reduced in obesity and metabolic disease, potentially impairing adipose function¹³. Although PRF is enriched in brown adipocytes and serves endocrine roles, its ADRB3 biology and impact on DKD have not yet been explored.

Here, we report that ADRB3 is abundant in PRF and markedly downregulated in DKD. To investigate its role, we generated brown fat-specific ADRB3 knockout (ADRB3^BKO) mice and induced DKD by streptozotocin (STZ) and high-fat diet (HFD). ADRB3 deficiency expanded the PRF depot and adipocyte size, and exacerbated renal tubular injury and interstitial fibrosis in DKD models. Mechanistically, transcriptomic profiling of PRF adipocytes revealed that ADRB3 loss disrupted Bcat2-mediated branched-chain amino acid (BCAA) catabolism, leading to increased TNFα secretion. Crucially, PRF removal, ADRB3 agonism (BRL 37344), Bcat2 re-expression or neutralization of TNFα significantly attenuated renal fibrosis in tubular epithelial cells. These findings identify a PRF-renal axis in DKD, whereby ADRB3 modulates adipocyte inflammatory signaling to influence kidney fibrosis.

Results

Renal fibrosis is upregulated in DKD

To investigate the renal pathological changes in the DKD state, we used renal specimens from DKD patients confirmed by renal biopsy as well as from the control group (paracancerous nephrectomy) (n = 20). H&E staining showed that renal tubular damage was significantly aggravated in DKD patients compared with the control group (Supplementary Fig. 1A). PAS and Masson staining showed tubular basement membrane thickening and renal interstitial fibrosis in DKD patients (Supplementary Fig. 1B, C). Meanwhile, the expression levels of renal fibrosis markers, including α-smooth muscle actin (αSMA) and Fibronectin (FN1), were significantly increased in DKD patients (Supplementary Fig. 1D, E). To further validate the findings in DKD patients, we used db/db mice to establish an animal model of DKD (Supplementary Fig. 1F). Compared with the control group (db/m), db/db mice had significantly increased body weight and blood glucose (Supplementary Fig. 1G, H). Renal function, assessed by serum creatinine (Cr) and the urinary albumin-to-creatinine ratio (UACR), was significantly impaired in 24-week-old db/db mice, indicating the successful establishment of the DKD animal model (Supplementary Fig. 1I, J). Further pathological staining results also showed severe pathological damage (increased tubular damage score and mesangial matrix expansion) in the kidneys of db/db mice (Supplementary Fig. 1K, L). Fibrotic area was significantly increased in db/db mice as well (Supplementary Fig. 1M–O). These results collectively suggest that renal fibrosis is significantly upregulated in DKD.

PRF is significantly increased in DKD and associated with renal function

To explore the underlying etiology of renal fibrosis in DKD status, RNA sequencing was performed utilizing the kidney tissues from the two groups of patients. The results of Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene clustering map showed that, in addition to the fibrotic pathway, there were significant alterations in lipid metabolism-related pathways (Fig. 1A, B). PRF was visibly increased in db/db mice compared with db/m mice (Fig. 1C). Given the reported involvement of PRF in metabolic regulation and metabolic diseases¹⁴, we measured the PRF area in the region of interest (ROI) using 7T MRI, and the results showed a significant increase in PRF in mice within the ROI (Fig. 1D). In addition, adipocyte volume and lipid content were also significantly increased in the PRF of db/db mice (Fig. 1E–G). To further explore the role of PRF in DKD, we analyzed the correlation between PRF and renal function, and the results showed that PRF area in db/db mice was positively correlated with serum Cr and UACR, but not associated with blood glucose levels (Fig. 1H–J). Taken together, these results suggest that PRF is significantly increased in DKD and negatively associated with renal function.

Fig. 1 — A KEGG over-representation analysis of the top differentially expressed gene (DEG)-related pathways (two-sided Fisher’s exact test with Benjamini–Hochberg FDR correction). B Heatmap of fibrosis-related genes in kidneys from controls and DKD patients (GEO: GSE166239). C Gross PRF appearance in db/m and db/db mice. D 7 T T1-weighted MRI pseudocolor maps and PRF-area quantification (n = 8 mice per group). E Representative H&E staining of PRF. F, G PRF triglyceride (TG) and total cholesterol (TCH) content (n = 8 mice per group). H–J Two-tailed Pearson correlations between PRF area and blood glucose, serum creatinine and UACR in individual mice (n = 8 mice per group). Data are mean ± SEM (D, F, G). Statistics: two-tailed unpaired Student’s t-test for (D, F, G); two-tailed Pearson correlation for (H–J). Exact P values are shown in the figure. Source data are provided as a Source Data file.

Removal of PRF significantly alleviated renal pathological damage and renal fibrosis in db/db mice

To further investigate the role of PRF in DKD, we surgically removed PRF in db/db mice as previously described in ref. ¹⁵ (Fig. 2A). Removal of PRF did not reduce body weight or blood glucose levels in db/db mice compared with the sham-operated controls (Fig. 2B, C). Notably, comprehensive profiling of circulating metabolites and lipid parameters revealed that PRF removal markedly remodeled the systemic metabolic milieu. Specifically, serum insulin and β-hydroxybutyrate levels were significantly decreased, whereas serum lactate levels were unchanged (Supplementary Fig. 2A–C). In parallel, PRF removal increased serum adiponectin and reduced circulating leptin, resistin, and PAI-1 (Supplementary Fig. 2D–G). Moreover, PRF removal significantly lowered serum triglycerides and free fatty acids, and reduced relative ceramide content, while total cholesterol, high-density lipoprotein (HDL), and low-density lipoprotein (LDL) levels remained largely unchanged (Supplementary Fig. 2I–N). In addition, branched-chain amino acids (Leu, Ile, Val) within PRF were altered following PRF removal (Supplementary Fig. 2H), supporting a shift in the local PRF metabolic microenvironment.

Despite minimal effects on body weight and glycemia, PRF removal significantly reduced UACR levels (Fig. 2D). Histological analyses further demonstrated that PRF removal markedly ameliorated renal pathological damage in db/db mice, as evidenced by HE, PAS, and Masson staining (Fig. 2E–G). In addition, co-immunofluorescence staining of αSMA, FN1, and the renal tubular marker lotus-tetragonal lectin (LTL) showed that PRF removal alleviated renal fibrosis (Fig. 2H). Consistently, Western blotting confirmed that PRF removal reduced αSMA and FN1 expression in renal tubules of db/db mice (Fig. 2I). Furthermore, Oil Red O (ORO), dihydroethidium (DHE), and succinate dehydrogenase (SDH) staining (a key enzyme of the tricarboxylic acid cycle) collectively indicated that PRF removal effectively mitigated renal lipid accumulation, oxidative stress, and metabolic dysfunction in DKD (Fig. 2J–L).

To investigate the effect of PRF on renal tubular cells, we isolated primary renal tubular epithelial cells (TECs) and found that renal fibrotic features were also alleviated by PRF removal (Fig. 2M). Given that mitochondria are vital organelles for fatty acid metabolism, we next assessed mitochondrial function. Oxygen consumption rate (OCR), ATP production, and immunofluorescence staining of TFAM (a mitochondrial biogenesis marker) showed that PRF removal improved mitochondrial function in TECs of db/db mice (Fig. 2N–P). Collectively, these results indicate that PRF removal significantly alleviates renal pathological damage and renal fibrosis in db/db mice, and is accompanied by favorable changes in circulating metabolites and lipid profiles.

ADRB3 expression is downregulated in PRF and associated with renal function

Next, we explored the possible reasons for the increase in PRF (Fig. 3A). KEGG analysis showed that lipid metabolism-related pathways were significantly downregulated in individuals with obesity (Fig. 3B), and among the lipid metabolism-related genes, Fatty acid binding protein 1 (FABP1), Peroxisome proliferator-activated receptor alpha (PPARA) and ADRB3 were the most significantly downregulated (Fig. 3C), suggesting that these three genes may be key regulatory genes. Therefore, we further analyzed the expression changes of these genes in PRF. RT-PCR and Western blotting results showed that ADRB3 was most significantly downregulated in PRF of db/db mice (Fig. 3D–H). Furthermore, immunohistochemistry and immunofluorescence staining also confirmed the downregulation of ADRB3 expression in PRF in db/db mice (Fig. 3I, J), indicating that ADRB3 suppression may contribute to the increase of PRF. To further explore the relationship between ADRB3 and renal function, we performed correlation analysis, confirming that ADRB3 expression was negatively correlated with serum Cr and UACR levels, rather than blood glucose levels (Fig. 3K–M).

Further, considering the heterogeneity of PRF cell composition, we isolated PRFs from 12-week-old db/m and db/db mice to investigate their cellular composition and relationship with ADRB3 expression. We performed single-cell transcriptomic sequencing (Fig. 3N). The output was subjected to quality control and analysis using the Seurat clustering algorithm. All samples were processed with unsupervised clustering, identifying 10 cell clusters within the PRF samples (Fig. 3O, P). The most abundant cell population was adipocytes, followed by adipose stem/progenitor cells (ASPCs), endothelial cells, and monocytes/macrophages. Given the critical role of brown adipocytes in PRF and DKD, we first analyzed ADRB3 expression across cell clusters. Cluster abundance revealed a significantly reduced number of brown adipocytes within PRF samples from db/db mice (Supplementary Fig. 3A), suggesting potential brown adipocyte depletion in this model. To further investigate adipocyte composition changes in DKD, we labeled adipocytes as brown, beige, and white using marker genes. Cluster abundance analysis revealed significantly reduced brown adipocyte numbers and markedly increased white adipocyte numbers in PRF samples from db/db mice (Fig. 3Q). Immunofluorescence further confirmed a significant reduction in brown adipocyte numbers within PRF of db/db mice (Supplementary Fig. 3B, C). Brown adipocytes in PRF perform crucial energy metabolism and secretory functions compared to white and beige fat¹⁶, and can undergo whitening under pathological stimuli, which suggests the important role of brown adipocytes in DKD⁹. To further determine whether the thermogenic subpopulation within the PRF, despite constituting only a minority of PRF adipocytes, plays a functionally significant role, we locally suppressed the thermogenic program in the PRF by administering bilateral injections of AAV-shUcp1 or AAV-shCtrl prior to STZ/HFD treatment (Supplementary Fig. 3D). Local AAV delivery was primarily confined to the PRF (Supplementary Fig. 3E), and UCP1 expression in the PRF was significantly reduced at both the mRNA and protein levels, whereas UCP1 expression in the interscapular brown adipose tissue (iBAT) remained largely unchanged (Supplementary Fig. 3F, G). Local UCP1 knockdown in the PRF significantly promoted adipocyte hypertrophy and lipid accumulation (Supplementary Fig. 3H–J), accompanied by impaired mitochondrial function in PRF adipocytes (Supplementary Fig. 3K, L). Importantly, these local changes were associated with worsening renal dysfunction, manifested by elevated UACR and BUN levels (Supplementary Fig. 3N, O), exacerbated renal histopathological damage and fibrosis (Supplementary Fig. 3P–R), and impaired mitochondrial function in primary renal TECs isolated from these mice (Supplementary Fig. 3S–U), although blood glucose levels remained largely unchanged (Supplementary Fig. 3M). These data indicate that the suppression of thermogenic programs within the PRF is sufficient to exacerbate PRF mitochondrial damage and aggravate DKD-associated renal injury, supporting the notion that the thermogenic subpopulation within the PRF, despite its small size, plays a functionally significant role. Further analysis also revealed significantly reduced expression of ADRB3 in brown adipocytes within the PRF of db/db mice (Fig. 3R, S). Overall, these findings reveal that ADRB3 expression is downregulated in brown adipocytes of PRF and associated with renal function.

Brown fat-specific knockout of ADRB3 increases PRF expansion in DKD

Given that ADRB3 expression is downregulated in brown adipocytes of the PRF and brown adipocytes are metabolically active and exhibit a strong response to β-adrenergic signaling, this suggests that they may play a crucial role in ADRB3-mediated metabolic and inflammatory regulation within the PRF^16,17. We next explored the role of ADRB3 by generating brown fat-specific ADRB3 knockout mice (ADRB3^BKO) using UCP1-Cre and establishing DKD by STZ injection combined with HFD (Fig. 4A and Supplementary Fig. 4A, B). ADRB3 expression was markedly higher in PRF than in other organs (e.g., heart, liver, spleen, lung, and kidney), and was significantly reduced in the PRF of ADRB3^BKO mice (Fig. 4B, C).

Fig. 4 — A Experimental scheme for generating ADRB3^BKO (UCP1-Cre;Adrb3^fl/fl) mice and study timeline. [Created in BioRender. Hu, H. (2026) https://BioRender.com/cs6kgre]. B qPCR of Adrb3 in major organs showing selective loss in PRF (n = 8 mice per group). C Western blotting and densitometry of ADRB3 in PRF from ADRB3^fl/fl (ctrl) and ADRB3^BKO mice (n = 8 mice per group). D, E Body weight and fasting blood glucose in the indicated groups (n = 8 mice per group). F 7 T T1-weighted MRI pseudocolor maps with ROI encompassing both kidneys and quantification of PRF area (n = 8 mice per group). G, H Biochemical lipid content of PRF: triglycerides (TG) and total cholesterol (TCH) (n = 8 mice per group). I H&E staining of PRF and adipocyte size quantification (n = 8 mice per group). J Schematic of primary PRF adipocyte isolation. [Created in BioRender. Hu, H. (2026) https://BioRender.com/cs6kgre]. K Oil Red O (ORO) staining of primary adipocytes and quantification (n = 8 biologically independent experiments). L Seahorse traces of oxygen consumption rate (OCR) in primary adipocytes (n = 3 biologically independent experiments). M Cellular ATP in primary adipocytes (n = 8 biologically independent experiments). N–P PRF cytokines measured by ELISA: IL-1β (N), IL-6 (O) and TNF-α (P) (n = 8 biologically independent experiments). Data are mean ± SEM (B–I, K, M, and N–P). Two-tailed two-way ANOVA with Sidak’s multiple-comparisons test (D–H, K, M, and N–P), repeated-measures two-way ANOVA (L), and two-tailed unpaired Student’s t-test (B, C, I). Exact P values are shown in the figure. Source data are provided as a Source Data file.

Given the heterogeneity of PRF and the possibility that UCP1 expression may be downregulated under HFD, we performed in situ validation of Cre activity and ADRB3 deletion in PRF. By crossing UCP1-Cre;Adrb3^flox/flox mice with Rosa26-LSL-tdTomato, we observed robust tdTomato labeling in PRF, confirming an effective Cre-mediated recombination in the perirenal region under STZ + HFD conditions (Supplementary Fig. 4C–E). Consistently, immunofluorescence analyses demonstrated that tdTomato-positive cells in PRF were largely aligned with UCP1-positive adipocytes, and ADRB3 signals were markedly diminished in the PRF of ADRB3^BKO mice compared with controls, supporting an efficient deletion of ADRB3 at the tissue level (Supplementary Fig. 4F).

Knockout of ADRB3 in PRF significantly increased PRF area in the DKD mouse model, while having minimal effects on body weight or blood glucose in saline-treated mice (Fig. 4D–F). Moreover, ADRB3 deletion had little impact on PRF lipid content in controls but significantly increased lipid accumulation in PRF under DKD conditions (Fig. 4G, H). H&E staining further showed enlarged adipocyte size in PRF of ADRB3^BKO mice in the DKD state (Fig. 4I). To assess adipocyte metabolic function, we isolated primary adipocytes from PRF (Fig. 4J). ORO staining, OCR, and ATP production assays indicated that ADRB3 deletion markedly enhanced lipid accumulation and impaired mitochondrial function in PRF adipocytes in DKD mice (Fig. 4K–M).

Importantly, beyond inflammatory cytokines, adipose tissue can influence systemic metabolism through adipokines and hormone-like factors¹⁸. Consistent with this concept, we quantified multiple secreted factors and found that PRF and circulating adipokines were substantially altered by ADRB3 deletion in DKD, including a significant change in adiponectin levels (Fig. 4N–P and Supplementary Fig. 4G–Q). These data support that ADRB3 deficiency in PRF remodels the endocrine output of PRF in DKD, in addition to promoting local inflammatory signaling.

Collectively, these results indicate that brown fat-targeted ADRB3 deletion in PRF promotes PRF expansion, mitochondrial dysfunction, and broad changes in adipose-derived secreted factors in DKD mice.

Knockout of ADRB3 in PRF aggravates renal pathological injury, metabolic stress, and fibrosis in DKD

We next evaluated whether ADRB3 deletion in PRF influences renal injury and fibrosis. Under saline conditions, ADRB3^BKO mice showed no significant changes in UACR or BUN relative to controls. However, under DKD conditions, both UACR and BUN were markedly elevated, and ADRB3^BKO mice exhibited significantly worse renal functional indices compared with ADRB3^ctrl mice (Supplementary Fig. 4R, S). Histological analyses revealed aggravated renal tubular injury and increased mesangial matrix expansion in ADRB3^BKO mice in the DKD state (Supplementary Fig. 4T), supporting that PRF ADRB3 deficiency exacerbates renal pathological damage during DKD progression.

Furthermore, renal metabolic stress was exacerbated in ADRB3^BKO DKD mice, as evidenced by decreased SDH staining, increased DHE fluorescence, and augmented lipid accumulation (Supplementary Fig. 4U). These findings suggest that ADRB3 deletion in PRF aggravates renal mitochondrial dysfunction, oxidative stress, and ectopic lipid deposition under DKD conditions.

We then examined renal fibrosis. Immunofluorescence staining, Masson trichrome staining, and Western blotting consistently showed that ADRB3 deletion in PRF significantly promoted renal fibrotic remodeling in DKD mice (Fig. 5A–C). In parallel, PRF-derived inflammatory mediators and adipose-derived secreted factors were increased in the DKD state, with TNFα remaining one of the most prominently elevated factors across groups (Fig. 5D–I and Supplementary Fig. 4G–Q). To determine the impact on renal tubular cells, we isolated primary TECs from each group. OCR, ATP production, and TFAM immunofluorescence demonstrated that ADRB3 deletion in PRF significantly impaired mitochondrial function in TECs from DKD mice (Fig. 5J–M). In addition, immunofluorescence staining for ORO, αSMA, and FN1 indicated increased lipid accumulation and fibrotic marker expression in TECs of ADRB3^BKO DKD mice (Fig. 5N, O).

Fig. 5 — A Representative kidney sections from ADRB3^fl/fl and ADRB3^BKO mice under saline or STZ/HFD showing Masson trichrome (fibrosis) and immunofluorescence for FN1 (red), αSMA (green), LTL (white) and DAPI (blue) (n = 8 mice per group). B Quantification of fibrosis area (Masson) and fluorescence intensities of αSMA and FN1 (n = 8 mice per group). C Western blotting of isolated renal tubules with densitometry for αSMA and FN1 (n = 8 mice per group). D–F qPCR of Il1b, Il6, and Tnf mRNA in PRF (n = 8 mice per group). G–I PRF cytokine content for IL-1β, IL-6, and TNF-α (n = 8 mice per group). J Seahorse traces of oxygen-consumption rate (OCR) in primary TECs (n = 3 biologically independent experiments). K Cellular ATP in TECs (n = 8 biologically independent experiments). L–M TFAM immunofluorescence in TECs and quantification (n = 8 biologically independent experiments). N Oil Red O (ORO) staining of TECs with quantification of ORO-positive area (n = 8 biologically independent experiments). O Immunofluorescence of FN1 (red) and αSMA (green) in TECs with quantification (n = 8 biologically independent experiments). Data are mean ± SEM (B–I and K–O). Two-tailed two-way ANOVA with Sidak’s multiple-comparisons test (B–I, K, M–O); repeated-measures two-way ANOVA (J). Exact P values are shown in the figure. Source data are provided as a Source Data file.

Together, these results suggest that ADRB3 deficiency in PRF aggravates renal injury and fibrosis in DKD, potentially through exacerbating PRF adipocyte dysfunction and altering adipose-derived endocrine/inflammatory outputs.

PRF-restricted restoration of ADRB3 is sufficient to ameliorate the renal phenotype

To further determine whether the exacerbated renal phenotype observed in ADRB3^BKO mice is attributable to local loss of ADRB3 in PRF, we first performed a PRF-restricted restoration experiment using localized FLEX-AAV-ADRB3 delivery (Supplementary Fig. 5A). Prior to STZ/HFD induction, FLEX-AAV-ADRB3 or FLEX-AAV-control was bilaterally injected into the PRF of UCP1-Cre;ADRB3^fl/fl (ADRB3^BKO) mice. Local FLEX-AAV delivery resulted in robust recombination and ADRB3 restoration in PRF, with minimal detectable spread to iBAT (Supplementary Fig. 5B–D).

Local restoration of ADRB3 in PRF significantly attenuated adipocyte hypertrophy and lipid accumulation and reduced TNFα production in both PRF and serum (Supplementary Fig. 5E–G). These local improvements were accompanied by significant renal protective effects, manifested by reduced UACR and BUN, improved renal histological damage, and decreased fibrosis markers (Supplementary Fig. 5H–L). These results indicate that correcting ADRB3 signaling within PRF is sufficient to improve the renal phenotype even when ADRB3 deficiency persists in other UCP1-lineage adipose tissues.

PRF-derived thermogenic adipocytes exhibit a distinct response to ADRB3 loss compared with interscapular BAT-derived thermogenic adipocytes

To further compare the intrinsic responses of thermogenic adipocytes from different adipose tissue sources to ADRB3 deficiency, we isolated primary adipocytes from PRF and iBAT of ADRB3^BKO mice and co-cultured them with TECs under identical in vitro conditions (Supplementary Fig. 5M). Although both cell types could suppress mitochondrial function in TECs (Supplementary Fig. 5O, P), PRF-derived adipocytes induced a more pronounced increase in TNFα production (Supplementary Fig. 5N) and more severe TEC mitochondrial dysfunction, lipid accumulation, and profibrotic responses than iBAT-derived adipocytes (Supplementary Fig. 5Q–S).

iBAT-restricted ADRB3 restoration corrects local iBAT dysfunction but does not reproduce PRF-dependent renal protection

To directly test whether restoration of ADRB3 signaling within classical iBAT is sufficient to influence the PRF inflammatory and renal phenotypes, we next performed an iBAT-restricted rescue experiment. FLEX-AAV-ADRB3 or matched FLEX-AAV-control was bilaterally injected into iBAT of UCP1-Cre;ADRB3^fl/fl mice before STZ/HFD induction (Supplementary Fig. 6A). EGFP fluorescence and immunoblotting confirmed preferential local delivery and ADRB3 restoration in iBAT, with minimal detectable signal in PRF (Supplementary Fig. 6B–D).

Functionally, iBAT-restricted ADRB3 restoration reduced iBAT adipocyte hypertrophy and improved mitochondrial readouts in primary iBAT adipocytes, including OCR, ATP production, and TFAM fluorescence (Supplementary Fig. 6E–H). Thus, the local iBAT rescue strategy effectively restored ADRB3 expression and improved the structural and mitochondrial phenotype of iBAT adipocytes.

Despite this effective local correction of iBAT, iBAT-restricted ADRB3 restoration did not significantly reduce PRF TNFα or circulating TNFα levels and did not alter blood glucose (Supplementary Fig. 6I–K). It also failed to significantly improve ACR, BUN, renal histopathological injury, mesangial matrix expansion, or fibrotic area in ADRB3^BKO DKD mice (Supplementary Fig. 6L–O). Together with the PRF-restricted rescue and PRF-versus-iBAT co-culture data, these findings support PRF as the predominant, although not necessarily exclusive, adipose depot mediating the ADRB3-dependent adipose-kidney axis under the experimental conditions examined.

Genetic ADRB3 overexpression in PRF mitigates PRF dysfunction and attenuates DKD renal injury

Given the heterogeneity of PRF adipocytes and the significant role of PRF in systemic metabolism, we further employed AAV tagged with an adipocyte-specific promoter to determine whether restoring ADRB3 expression could improve PRF dysfunction and renal damage in DKD, as illustrated (Supplementary Fig. 7A). Efficient ADRB3 overexpression in PRF was confirmed at both mRNA and protein levels (Supplementary Fig. 7B, C).

Histological analyses showed that ADRB3 overexpression reduced adipocyte hypertrophy in PRF under DKD conditions (Supplementary Fig. 7D). Consistently, ADRB3 overexpression significantly lowered pro-inflammatory cytokine levels in PRF and serum, including TNFα, IL-1β, and IL-6 (Supplementary Fig. 7E–J), and favorably remodeled adipose-derived endocrine outputs, as reflected by increased adiponectin and reduced leptin, resistin, and PAI-1 (Supplementary Fig. 7K–N), with concordant changes also observed in the circulation (Supplementary Fig. 7O–R). Importantly, ADRB3 overexpression did not markedly alter blood glucose levels in the DKD model (Supplementary Fig. 7S), yet significantly reduced ACR and improved renal function (BUN) (Supplementary Fig. 7T, U).

Pathological assessments further demonstrated that ADRB3 overexpression attenuated DKD-associated renal injury and fibrosis, as evidenced by reduced tubular injury scores, mesangial matrix expansion, and fibrotic area, together with improved histological staining (HE, PAS, and Masson) (Supplementary Fig. 7V, W). Moreover, ADRB3 gain-of-function improved renal lipid accumulation and mitochondrial function readouts, as shown by ORO staining and TFAM immunofluorescence (Supplementary Fig. 7X, Y).

Collectively, these gain-of-function data provide independent genetic evidence that overexpression of ADRB3 can counteract PRF dysfunction and ameliorate DKD renal injury, thereby supporting the key conclusions drawn from ADRB3 loss-of-function models.

Pharmacological activation of ADRB3 attenuates renal pathological injury and renal fibrosis in DKD

BRL37344 (BRL), a selective ADRB3 agonist¹⁹, was administered by intraperitoneal injection to evaluate whether pharmacological activation of ADRB3 signaling ameliorates DKD-associated renal injury and fibrosis (Fig. 6A). RT-qPCR and immunoblot analyses demonstrated that BRL treatment restored ADRB3 expression in PRF that was reduced under DKD conditions (Fig. 6B, C). In parallel, BRL significantly reduced PRF adipocyte hypertrophy in DKD mice (Fig. 6D).

Consistent with this, BRL markedly decreased pro-inflammatory cytokine levels in PRF, including IL-1β, IL-6, and TNFα (Fig. 6E and Supplementary Fig. 8A, B). In addition, BRL treatment favorably remodeled adipose-derived endocrine outputs, as reflected by increased adiponectin and reduced leptin, resistin, and PAI-1 levels in PRF and/or circulation (Supplementary Fig. 8C–M).

We next assessed renal outcomes. BRL significantly improved renal function in DKD mice, as indicated by reduced ACR and lower BUN levels, without significantly altering body weight or blood glucose levels (Fig. 6F–I). Histological and molecular analyses further showed that BRL attenuated DKD-associated renal pathological damage, lipid deposition, and fibrosis, as evidenced by HE, PAS, Masson, and ORO staining, immunofluorescence analyses, and reduced fibrotic marker expression by Western blotting (Fig. 6J–M and Supplementary Fig. 8N).

To delineate the cellular basis for these effects, we performed in vitro studies using primary PRF adipocytes and renal TECs. BRL (1 μM) significantly increased ADRB3 mRNA levels in primary adipocytes and improved mitochondrial function, as shown by OCR and ATP measurements (Supplementary Fig. 8O–Q). We then established an adipocyte-TEC co-culture system (Supplementary Fig. 8R). Consistent with the in vivo findings, BRL significantly reduced TNFα levels in the culture medium (Supplementary Fig. 8R) and improved mitochondrial function and lipid accumulation in TECs, as indicated by OCR/ATP assays, TFAM immunofluorescence, and ORO staining (Supplementary Fig. 8S–W). Moreover, BRL attenuated fibrotic responses in TECs, as reflected by reduced αSMA and FN1 expression (Supplementary Fig. 8X).

Taken together, these results indicate that pharmacological activation of ADRB3 ameliorates PRF dysfunction and is associated with reduced renal injury and fibrosis in DKD.

ADRB1 is compensatorily upregulated in PRF of ADRB3-deficient mice, but ADRB1 overexpression does not phenocopy ADRB3 activation

Previous study has reported that ADRB1 may be upregulated as a compensatory response in ADRB3 knockout models²⁰. To address this possibility, we examined ADRB1 and ADRB2 expression in PRF from ADRB3^ctrl and ADRB3^BKO mice. RT-qPCR analysis showed that ADRB1 mRNA levels were slightly increased in ADRB3^BKO PRF compared with controls, and ADRB2 expression was unchanged (Supplementary Fig. 9A). Consistently, Western blotting confirmed that ADRB1 protein levels were slightly increased between ADRB3^ctrl and ADRB3^BKO mice (Supplementary Fig. 9B). These data indicate that ADRB3 deficiency induces a degree of compensatory upregulation of ADRB1.

To further test whether enhanced ADRB1 signaling could account for the observed phenotypes, we performed complementary gain-of-function experiments. Primary PRF adipocytes from saline or STZ/HFD-treated mice were transfected with an ADRB1 overexpression plasmid and then co-cultured with TECs (Supplementary Fig. 9C). Although ADRB1 overexpression modulated adipocyte-TECs paracrine signaling, it did not fully reproduce the ADRB3 activation phenotype on TECs metabolic and injury readouts. Specifically, ADRB1 overexpression only partially improved TECs mitochondrial function (OCR/ATP) and TFAM staining, with limited effects on TECs lipid accumulation and fibrotic markers (αSMA and FN1) (Supplementary Fig. 9D–J).

Together, these results argue against ADRB1 compensatory upregulation as a major confounder in the ADRB3 loss-of-function model and further support a predominant role for ADRB3-dependent signaling in PRF in regulating adipocyte-TECs crosstalk and DKD-associated tubular dysfunction.

Neutralization of TNFα alleviates renal pathological damage and renal fibrosis exacerbated by ADRB3 deficiency in PRF

Our data indicate that ADRB3 deficiency in PRF is associated with increased TNFα production and worsened renal injury/fibrosis in DKD. To evaluate whether targeting TNFα mitigates these phenotypes, we administered a neutralizing anti-TNFα antibody or isotype control to ADRB3^ctrl and ADRB3^BKO mice subjected to STZ + HFD-induced DKD, as previously described²¹ (Supplementary Fig. 10A). Anti-TNFα treatment did not significantly alter body weight or blood glucose levels in either genotype (Supplementary Fig. 10B, C) but significantly improved renal functional indices, including reduced UACR and BUN, with a more pronounced improvement in ADRB3^BKO DKD mice (Supplementary Fig. 10D, E).

Histological analyses further showed that anti-TNFα treatment attenuated DKD-associated renal pathological damage and fibrosis in both ADRB3^ctrl and ADRB3^BKO mice, as evidenced by improved HE/MASSON staining, reduced lipid deposition, restored SDH activity, and decreased fibrotic burden (Supplementary Fig. 10F–H). Consistently, when primary TECs were isolated from each group, anti-TNFα treatment significantly improved mitochondrial function and reduced lipid accumulation and profibrotic responses, particularly in TECs derived from ADRB3^BKO DKD mice (Supplementary Fig. 10I–M).

To directly test whether adipocyte-derived factors mediate these effects and whether TNFα neutralization is sufficient to reverse tubular dysfunction, we performed an additional conditioned-media experiment. Primary adipocytes were isolated from ADRB3^ctrl and ADRB3^BKO mice to generate conditioned media (CM), followed by treatment with anti-TNFα antibody or isotype control prior to exposure to primary TECs (Supplementary Fig. 10N). Compared with CM from ADRB3^ctrl adipocytes, CM from ADRB3-deficient adipocytes induced marked mitochondrial dysfunction, lipid loading, and profibrotic responses in TECs. Importantly, neutralizing TNFα in ADRB3-deficient adipocyte CM significantly restored TEC mitochondrial respiration and ATP production (Supplementary Fig. 10O, P), increased TFAM fluorescence (Supplementary Fig. 10Q), reduced lipid accumulation by ORO staining (Supplementary Fig. 10R), and decreased fibrotic marker expression (αSMA and FN1) (Supplementary Fig. 10S).

Taken together, these findings support that TNFα is a key mediator linking ADRB3-deficient PRF/adipocytes to tubular metabolic stress and profibrotic remodeling in DKD, and that TNFα neutralization can ameliorate renal dysfunction and fibrosis exacerbated by ADRB3 deficiency.

Antioxidant treatment mitigates oxidative stress and partially rescues renal injury and fibrosis in ADRB3-deficient DKD mice

Brown/beige adipose tissue has been reported to participate in BCAA catabolism and redox homeostasis, and impaired BCAA handling may promote oxidative stress, which can in turn amplify TNFα and other pro-inflammatory pathways²². Given the markedly increased DHE signal observed in ADRB3-deficient mice under DKD conditions, we tested whether elevated reactive oxygen species (ROS) contributes to renal injury by administering the antioxidant N-acetylcysteine (NAC)²³ to ADRB3^ctrl and ADRB3^BKO mice subjected to STZ + HFD-induced DKD model (Supplementary Fig. 11A).

NAC treatment reduced PRF adipocyte hypertrophy in ADRB3^BKO DKD mice (Supplementary Fig. 11B) and significantly decreased circulating and PRF TNFα levels (Supplementary Fig. 11C, D). Importantly, NAC improved renal functional indices, as shown by reduced UACR and decreased BUN in both genotypes, with a more pronounced benefit in ADRB3^BKO DKD mice (Supplementary Fig. 11E, F). Consistent with reduced oxidative stress, NAC lowered systemic lipid peroxidation (MDA) (Supplementary Fig. 11G) and alleviated renal pathological damage and fibrosis, as demonstrated by improved H&E staining, restored SDH activity, and reduced Masson-positive fibrotic area (Supplementary Fig. 11H).

At the tissue level, NAC markedly attenuated renal oxidative stress readouts, including reduced DHE fluorescence and decreased staining for oxidative DNA/lipid damage markers (4-HNE and 8-OHdG), with quantification confirming a significant reduction in oxidative injury signals, particularly in ADRB3^BKO DKD mice (Supplementary Fig. 11I).

Together, these results support that excessive oxidative stress contributes to the aggravated renal injury and fibrosis observed in ADRB3-deficient DKD mice, and that antioxidant treatment can mitigate ROS-associated damage and improve renal fibrosis.

Knockout of ADRB3 in PRF enhances TNFα production in association with impaired BCAA catabolism

Our data indicate that ADRB3 deficiency in PRF exacerbates renal injury and fibrosis in DKD, concomitant with increased TNFα production. To explore upstream mechanisms, we isolated primary adipocytes from ADRB3^ctrl and ADRB3^BKO mice under DKD conditions and performed RNA-seq (Fig. 7A, B). Pathway enrichment analyses (KEGG and GSEA) revealed that genes involved in branched-chain amino acid (BCAA) catabolism, including valine, leucine, and isoleucine degradation, were significantly downregulated in ADRB3^BKO adipocytes (Fig. 7C, D and Supplementary Fig. 12A). Consistently, targeted measurements demonstrated the accumulation of BCAAs in PRF from ADRB3^BKO DKD mice (Fig. 7E).

Fig. 7 — A Schematic of primary PRF adipocyte isolation and RNA-seq. [Created in BioRender. Hu, H. (2026) https://BioRender.com/cs6kgre]. B Rank plot of DEGs in primary adipocytes from ADRB3^fl/fl and ADRB3^BKO DKD mice (two-sided DESeq2 Wald test with Benjamini–Hochberg FDR correction). C KEGG over-representation of DEGs (two-sided Fisher exact test with Benjamini–Hochberg FDR correction). D GSEA showing downregulated VALINE_LEUCINE_AND_ISOLEUCINE_DEGRADATION in ADRB3^BKO adipocytes. E Targeted metabolomics of PRF BCAAs (Leu, Ile, Val) in primary adipocytes (n = 8 biologically independent experiments). F TNF-α levels in adipocyte culture medium (n = 8 biologically independent experiments). G OCR traces (n = 3 biologically independent experiments). H Heatmap of BCAA-degradation genes. I Volcano plot highlighting Bcat2 (two-sided DESeq2 Wald test with Benjamini–Hochberg FDR correction). J BCAT2 immunofluorescence in PRF (n = 8 biologically independent experiments). K TNF-α after BCAT2 overexpression (n = 8 biologically independent experiments). L OCR traces (n = 3 biologically independent experiments). M αSMA/FN1 immunofluorescence in TECs exposed to conditioned media (n = 8 biologically independent experiments). Data are mean ± SEM (E, F, J, K, and M). Two-tailed two-way ANOVA with Sidak’s multiple-comparisons test (E, K); two-tailed one-way ANOVA with Tukey’s post-test (F); two-tailed repeated-measures two-way ANOVA (G, L). Exact P values are shown in the figure. Source data are provided as a Source Data file.

To test whether elevated BCAAs can influence adipocyte inflammatory output and tubular metabolic status, we co-cultured primary adipocytes with primary TECs and supplemented increasing doses of BCAAs. BCAA supplementation dose-dependently increased TNFα expression/secretion in adipocytes and impaired mitochondrial function in TECs (Fig. 7F, G and Supplementary Fig. 12B–D).

We next assessed whether restoring BCAA catabolic flux could mitigate TNFα release and the downstream profibrotic responses. Treatment with BT2²⁴, a pharmacologic modulator that enhances BCAA oxidation through inhibition of BCKDK²⁵, significantly reduced TNFα secretion and attenuated profibrotic responses in the adipocyte-TECs co-culture system (Supplementary Fig. 12E–G). However, since BT2 has been reported to have broader metabolic effects beyond BCKDK/BCKDH regulation, we complemented BT2 with genetic manipulation of key BCAA-oxidation nodes to strengthen the causal inference. Knockdown of BCKDH components (si-Bckdha) similarly enhanced TNFα release and worsened TECs phenotypes, supporting that reduced BCAA oxidative capacity is sufficient to promote inflammatory output in adipocytes (Supplementary Fig. 12H–J). In addition, re-supplementation of BCAAs blunted the protective effects of ADRB3 activation by BRL and re-induced TNFα release and TEC profibrotic changes (Supplementary Fig. 12K–M). Collectively, these results support that ADRB3 deficiency is associated with impaired BCAA catabolism in PRF adipocytes, and that elevated BCAAs can promote adipocyte TNFα release and worsen tubular metabolic and profibrotic phenotypes.

BCAT2 links impaired BCAA metabolism to NF-κB activation and TNFα production in PRF adipocytes

To identify specific mediators driving the BCAA-TNFα axis, we profiled BCAA catabolism-related genes in primary PRF adipocytes. Among the significantly altered genes, Bcat2, encoding the first rate-limiting enzyme in the initial transamination step of BCAA catabolism, showed one of the most robust decreases upon ADRB3 knockout (Fig. 7H–J). To test whether restoring BCAT2 is sufficient to mitigate inflammatory output, we overexpressed Bcat2 in primary adipocytes. Bcat2 overexpression significantly reduced TNFα levels, including reversing the ADRB3^BKO-associated increase (Fig. 7K). Bcat2 overexpression also improved mitochondrial respiration and ATP production in adipocytes (Fig. 7L and Supplementary Fig. 12N, O). In parallel, siRNA-mediated knockdown of Bcat2 in primary adipocytes increases TNFα production and elevates BCAA levels (Supplementary Fig. 12P, Q).

As transcriptomic reanalysis suggested enrichment of NF-κB-related signatures^26,27 (Supplementary Fig. 12R), and impaired BCAA handling has been linked to inflammatory pathway activation, we examined functional consequences on TECs using the adipocyte-TEC co-culture model. Conditioned media/co-culture from Bcat2-overexpressing adipocytes reduced TECs lipid accumulation and profibrotic marker expression (Fig. 7M and Supplementary Fig. 12S–U). Taken together, these data position BCAT2-dependent BCAA metabolism as a critical node coupling ADRB3 activity to NF-κB-associated inflammatory signaling and TNFα release in PRF adipocytes.

ADRB3 deficiency reduces BCAT2 expression through CREB1/METTL3-mediated m6A modification

Next, we investigated the mechanism underlying the downregulation of Bcat2 expression. mRNA analysis in PRF revealed reduced Bcat2 expression in PRF of DKD mice, and ADRB3 knockout further inhibited its expression (Fig. 8A). We first hypothesized that Bcat2 expression is regulated at the transcriptional level. Using transcription factor prediction tools²⁸, we identified 28 potential Bcat2 expression regulators (Fig. 8B). cAMP-responsive element binding protein1 (CREB1) was identified as the core Bcat2 transcriptional regulator and was upregulated in PRF of DKD mice (Fig. 8B and Supplementary Fig. 12V). Interestingly, recent studies have confirmed that ADRB3 can regulate the target gene expression through enhancing the cAMP/PKA/CREB1 pathway²⁹. Additionally, by isolating adipocytes and overexpressed CREB1, we found that both mRNA and protein expression levels of Bcat2 were significantly reduced (Fig. 8C, D). We then investigated whether CREB1 regulates Bcat2 transcription. ChIP-PCR results showed that CREB1 protein was not enriched on the Bcat2 gene fragment, indicating that CREB1 cannot directly induce Bcat2 transcription (Supplementary Fig. 12W). Recent studies have reported that ADRB3 may be involved in RNA modification, and our GSEA results also confirmed that ADRB3 knockout upregulates the RNA degradation pathway (Fig. 8E). Since N6-methyladenosine (m6A) is the primary form of mRNA modification³⁰, we performed immunofluorescence staining and found that ADRB3 knockout increased m6A modification in PRF (Fig. 8F). In adipocytes, m6A modification enzymes primarily include m6A methyltransferases (METTL3, METTL14, WTAP, KIAA1429), demethylases (FTO, ALKBH5), and recognition proteins (YTHDF1/2/3, IGF2BP1/2/3)³¹. Thus, we further explored whether CREB1 could influence the mRNA stability of Bcat2 by regulating the expression of m6A modification enzymes. mRNA analysis showed that overexpression of CREB1 significantly increased the expression of METTL3 and METTL14, while having no effect on other m6A modification enzymes, with the most significant increase observed in METTL3 (Fig. 8G). Therefore, we speculate that CREB1 regulates METTL3 through transcriptional control. Protein-DNA docking simulations revealed the optimal binding pattern between the CREB1 protein and the METTL3 gene (Fig. 8H). ChIP-PCR results further demonstrated the enrichment of CREB1 protein in the METTL3 gene fragment (Fig. 8I). Luciferase assays confirmed that CREB1 enhances METTL3 transcription through directly binding to its promoter region via the sequence “ACATGATGCCATA” (5′ → 3′) (Fig. 8J–M).

Fig. 8 — A qPCR of Bcat2 mRNA in ADRB3^fl/fl and ADRB3^BKO mice under saline or STZ/HFD (n = 8 biologically independent experiments). B Transcription-factor prediction identifies CREB1 as a candidate Bcat2 promoter regulator. C, D CREB1 overexpression decreases Bcat2 mRNA and protein (n = 8 biologically independent experiments). E GSEA indicates RNA-degradation pathway activation in ADRB3^BKO. F Global m6A immunostaining in PRF with quantification (n = 8 biologically independent experiments). G qPCR of m6A regulators in primary adipocytes (n = 3 biologically independent experiments). H Structural model of CREB1 bound to the METTL3 promoter. I ChIP-PCR of CREB1 enrichment at the METTL3 promoter (n = 3 biologically independent experiments). J–M Luciferase assays testing METTL3 promoter truncations and CREB1-site mutation (n = 3 biologically independent experiments). N, O m6A-RIP-qPCR (n = 3 biologically independent experiments). P Polysome profiling of Bcat2 (n = 3 biologically independent experiments). Q OPP-labeling/puromycylation of nascent BCAT2 (n = 3 biologically independent experiments). R Working model. [Created in BioRender. Hu, H. (2026) https://BioRender.com/cs6kgre]. Data are mean ± SEM (A, C, D, F, G, I, K, M–Q). Two-tailed unpaired Student’s t-test (A, C, D, F, I, N–Q); two-tailed two-way ANOVA with Sidak’s multiple-comparisons test (K, M); two-tailed multiple t-tests with Benjamini–Hochberg FDR correction for (G). Exact P values are shown in the figure. Source data are provided as a Source Data file.

Subsequently, we further investigated whether METTL3 mediates m6A modification of Bcat2. We isolated primary adipocytes from PRF, overexpressed or knocked down METTL3, and measured m6A content using RNA immunoprecipitation (RIP) assays. The m6A content of Bcat2 transcripts in the OE-METTL3 group was significantly higher than in the OE-ctrl group, while it was significantly reduced in the si-METTL3 group (Fig. 8N, O). Given that m6A affects mRNA degradation³², we used the transcription inhibitor actinomycin D to verify whether Mettl3 regulates the stability of Bcat2 transcripts. Primary adipocytes were transduced to overexpress METTL3 and treated with actinomycin D, and mRNA abundance was measured by RT-PCR. The results showed that Bcat2 mRNA degradation was comparable between the OE-METTL3 and OE-ctrl groups (Supplementary Fig. 12X). To investigate whether METTL3-mediated m6A inhibits Bcat2 translation, we performed polysome analysis in the aforementioned adipocytes. The ratio of polysomes (a marker of increased translation) to monosomes in Bcat2 transcripts was significantly lower in OE-METTL3 adipocytes compared to OE-ctrl adipocytes (Fig. 8P). To complement these studies, we used O-propargyl-puromycin (OPP) pulldown analysis to measure protein synthesis³³. We treated primary adipocytes with OPP to label newly translated proteins. OPP-labeled proteins were purified via biotin/streptavidin pulldown and analyzed by Western blotting using a BCAT2 antibody. Bcat2 translation rates were significantly lower in the OE-METTL3 group compared to the OE-ctrl group (Fig. 8Q). Overall, these results suggest that METTL3-induced m6A methylation inhibits the translational capacity of Bcat2 transcripts (Fig. 8R). Furthermore, we investigated whether the reduction of Bcat2 expression following ADRB3 knockout depends on METTL3-mediated m6A modification. Primary adipocytes from the perirenal fat of ADRB3ctrl and ADRB3BKO mice were treated with the METTL3-targeted inhibitor STM2457. RT-PCR showed that ADRB3 knockout significantly reduced Bcat2 mRNA levels, whereas this decrease was no longer observed after STM2457 treatment, indicating that the reduction of Bcat2 expression following ADRB3 knockout depends on METTL3-mediated m6A modification (Supplementary Fig. 12Y).

Discussion

In this study, we identify a mechanism of DKD progression in which diminished ADRB3 activity in PRF promotes renal fibrosis. ADRB3 expression is abundant in PRF and is downregulated in the DKD state, correlating with increased fat accumulation and worsened kidney function. Brown fat-specific ADRB3 knockout expanded PRF and exacerbated DKD pathology, whereas pharmacological ADRB3 activation had protective effects. Transcriptomic and biochemical analyses revealed that ADRB3 loss impairs BCAA metabolism by downregulating BCAT2, leading to NF-κB activation and elevated TNFα secretion. In vivo TNFα neutralization reversed the aggravated fibrosis in ADRB3^BKO DKD mice, identifying TNFα as a key mediator of PRF-kidney crosstalk. These findings support therapeutic strategies that target PRF metabolic health or the downstream TNFα axis.

Consistent with prior clinical and experimental observations, both DKD patients and animal models exhibit markedly increased tubular injury and interstitial fibrosis relative to controls⁶, reinforcing the central role of tubulointerstitial pathology in DKD progression³⁴. While DKD was historically viewed as a primarily glomerular disorder, tubular injury and fibrosis often precede overt glomerulosclerosis³⁵. Progressive matrix accumulation heralds a “point of no return” toward nephron loss and irreversibility³⁶. No anti-fibrotic therapy has yet been approved specifically for DKD³⁷. The pathobiology of diabetic renal fibrosis involves hyperglycemia-driven metabolic stress, reactive oxygen species (ROS), and pro-fibrotic growth factors such as TGFβ³⁶. Additional mechanisms include mitochondrial dysfunction and metabolic reprogramming in proximal tubules: suppressed fatty acid oxidation promotes lipid loading and fibrosis³⁸, and hyperglycemia can induce a maladaptive metabolic shift leading to apoptosis and fibrogenesis³⁹. These advances have not translated into fully effective therapies, implying that upstream triggers remain undefined. Our data position PRF inflammation as one such upstream driver; surgical or functional modulation of PRF altered renal outcomes in diabetic models, providing proof-of-concept for inter-organ targeting of renal fibrosis. Notably, PRF removal was accompanied by favorable remodeling of circulating metabolites, adipokines, and lipid profiles, supporting the concept that PRF clearance may confer renoprotection through both local (paracrine inflammatory pressure on the adjacent kidney) and systemic (endocrine/metabolic) mechanisms.

Multi-organ signaling is increasingly recognized in DKD, with proposed liver–kidney⁴⁰, muscle-kidney⁴¹, brain-kidney⁴², and vascular-kidney⁴³ axes. We extend this paradigm by defining an adipose (PRF)-kidney axis. Visceral adipose tissue in obesity/diabetes secretes pro-inflammatory cytokines and lipids that injure distant organs⁴⁴. The specific contribution of PRF, however, remains unclear. In diabetic models, we show that PRF mass expansion and adipocyte hypertrophy correlate with worse renal function and fibrosis. This accords with clinical data identifying PRF volume as an independent predictor of chronic kidney disease (CKD) in type 2 diabetes⁹. Moreover, inflammation within perirenal adipose tissue has been reported to precipitate renal dysfunction even at prediabetic stages⁴⁵, underscoring its potent paracrine influence. PRF contains substantial brown/brite adipose¹⁷; notably, PRF is a mixed depot that is predominantly white adipose tissue but harbors a significant thermogenic subset. Although brown fat is typically metabolically beneficial, dysfunctional or inflamed brown fat can become pathogenic⁴⁶. Our findings suggest that diminished ADRB3-driven sympathetic input shifts PRF brown adipocytes toward an inflammatory, white fat–like phenotype that produces high levels of TNFα capable of injuring adjacent kidney tissue.

Importantly, because the UCP1-Cre model deletes ADRB3 in UCP1-lineage adipocytes across multiple thermogenic depots, tissues outside PRF, particularly iBAT, could in principle contribute to the renal phenotype^47,48. We therefore used complementary depot-restricted and cellular approaches⁴⁹. PRF-restricted FLEX-AAV-ADRB3 restoration reduced PRF TNFα production and substantially ameliorated renal injury, fibrosis, and tubular mitochondrial dysfunction, whereas iBAT remained ADRB3-deficient. Conversely, the additional iBAT-restricted FLEX-AAV-ADRB3 rescue restored ADRB3 expression, adipocyte morphology, and mitochondrial function within iBAT, but did not significantly reduce PRF or circulating TNFα and did not reproduce the renal protection achieved by PRF-restricted restoration. In parallel, adipocyte-TEC co-culture experiments showed that PRF-derived adipocytes from ADRB3-deficient mice induced more severe TNFα production, mitochondrial dysfunction, lipid accumulation, and profibrotic responses than iBAT-derived adipocytes. These findings support the thermogenic subset within PRF as functionally important and identify PRF as the predominant, although not exclusive, depot driving the ADRB3-dependent PRF-kidney axis in DKD. This interpretation is consistent with the recognized metabolic and endocrine roles of thermogenic adipose tissue and PRF^50,51.

TNFα was the most upregulated cytokine in ADRB3-deficient PRF, and conditioned media from these adipocytes induced marked lipid accumulation and fibrotic activation in renal tubular cells. TNFα is a well-established driver of inflammation in adipose tissue and kidney⁵². In obesity, hypertrophied adipocytes and infiltrating M1 macrophages secrete TNFα, promoting lipolysis, local insulin resistance, and propagation of adipose inflammation⁵³. In the kidney, TNFα impairs mitochondrial function in TECs, increases oxidative stress, and activates pro-fibrotic transcriptional programs including NF-κB, NFAT, and AP-1⁵⁴. Elevated renal or circulating TNFα associates with accelerated DKD progression⁵⁵. Although systemic anti-TNF therapy has yielded mixed results and safety concerns in DKD⁵⁶, our data provide mechanistic evidence for TNFα causality within a defined inflammatory axis: TNFα neutralization in diabetic mice reduced albuminuria and serum creatinine, attenuated tubular and interstitial fibrosis, most prominently in ADRB3^BKO DKD mice, and restored tubular mitochondrial and lipid metabolic integrity. These findings validate TNFα as a tractable effector linking diseased PRF to renal injury.

Unbiased RNA sequencing revealed broad suppression of BCAA degradation genes in ADRB3-deficient PRF; targeted metabolomics confirmed BCAA accumulation. BCAA metabolism is increasingly recognized as an immunometabolic node in insulin resistance and inflammation^57,58. Recent work identified Bcat2, the first rate-limiting enzyme in BCAA catabolism, as a key regulator of adipose inflammation⁵⁹. In ADRB3^BKO PRF, Bcat2 expression was markedly reduced, suggesting a metabolic bottleneck. Re-expression of Bcat2 curtailed NF-κB activation and normalized TNFα secretion, supporting a model in which impaired BCAA clearance promotes inflammatory signaling. Mechanistically, BCAA excess can engage mTOR pathways and enhance ROS, both converging on NF-κB transcriptional activation⁶⁰. Together, these findings support an additional mechanistic layer in which impaired BCAA catabolism is associated with increased oxidative stress, which amplifies TNFα-driven inflammatory signaling and contributes to renal injury. Importantly, by attenuating ROS with N-acetylcysteine (NAC), we observed improvements in both kidney fibrosis/function and PRF inflammatory output, strengthening the causal role of oxidative stress in this axis and linking BCAA metabolic impairment to a ROS-TNFα feed-forward loop. Thus, restoring BCAA flux in ADRB3-deficient adipocytes interrupts an NF-κB-dependent feed-forward loop of cytokine amplification. Together, these results link β₃-adrenergic signaling in thermogenic adipocytes to BCAA immunometabolism and inflammatory cytokine output.

As reported, ADRB3 activation promotes lipolysis and mitochondrial uncoupling in brown fat, enhancing energy expenditure⁶¹. In ADRB3^BKO mice, we observed enlarged lipid droplets in PRF and evidence of mitochondrial dysfunction in both adipose and renal compartments; lipid overloading of PRF may itself provoke inflammation via lipotoxic and inflammasome pathways⁶². ADRB3 signaling induces anti-inflammatory adipokines and can restrain immune cell recruitment to adipose tissue⁶³; activation of thermogenic fat also improves systemic glucose and lipid clearance, potentially relieving glucotoxic and lipotoxic stress on the kidney⁶⁴. ADRB3 signaling regulates PRF endocrine output beyond TNFα, shifting PRF away from a pro-inflammatory, low-adiponectin state and toward a more metabolically favorable adipokine profile that may benefit the kidney. Thus, ADRB3 downregulation in DKD likely contributes to a dual hit-local PRF inflammation and adverse systemic metabolism-predisposing to renal injury. In our models, β₃ agonism with BRL 37344 reduced PRF mass, lowered TNFα output, and mitigated DKD fibrosis. Although BRL 37344 is not clinically used, FDA-approved β₃ agonists exist; rational repurposing or next-generation agents that activate PRF while minimizing desensitization will require evaluation. Given the potential for receptor downregulation with chronic stimulation, intermittent dosing or combination therapy aimed at dampening inflammation may be needed.

This study has several limitations. First, although our data support a key role for ADRB3-responsive thermogenic adipocytes in the PRF-kidney axis, PRF is a mixed depot that is predominantly composed of white adipocytes, and the constitutive UCP1-Cre model used here interrogates ADRB3 function in UCP1-lineage thermogenic adipocytes rather than in all PRF adipocytes. Second, because constitutive UCP1-Cre-mediated deletion affects multiple UCP1-lineage depots, tissues outside PRF, particularly iBAT, could in principle contribute to the phenotype. To mitigate this concern, we added PRF-restricted and iBAT-restricted FLEX-AAV-ADRB3 restoration experiments as well as a direct PRF-versus-iBAT adipocyte/TEC co-culture comparison. These experiments support PRF as the predominant functionally relevant depot but do not exclude every possible systemic metabolic contribution of iBAT. Third, the original adiponectin-promoter AAV-ADRB3 overexpression approach is broader in adipocyte targeting than the UCP1-lineage compartment and is not intrinsically depot-restricted; it should therefore be interpreted as supportive gain-of-function evidence rather than as a strict reciprocal complement to the UCP1-Cre loss-of-function model. Finally, although TNFα emerged as a central mediator, additional contributions from other adipose-derived mediators, white adipocytes within PRF, and broader systemic metabolic adaptations cannot be excluded.

In summary, this study clarifies how diabetes-induced changes in adipose tissue can exacerbate kidney disease. Impaired BCAT2-mediated BCAA catabolism activates NF-κB, elevating TNFα secretion. TNFα, in turn, drives tubular mitochondrial dysfunction, lipid accumulation, and fibrosis, accelerating DKD. In mice, either neutralizing TNFα or pharmacologically re-activating ADRB3 normalizes PRF inflammation and attenuates renal injury, underscoring the PRF-kidney axis as a tractable therapeutic target. Clinical studies should now determine whether PRF volume, circulating TNFα, or BCAA signatures predict DKD progression and therapeutic responsiveness, enabling personalized interventions that disrupt pathogenic adipose-renal crosstalk.

Methods

This study complied with all relevant ethical regulations. Human sample use was approved by the Ethics Committee of Xinqiao Hospital, Army Medical University (No. 2023-YAN-143-01), and all participants provided written informed consent. Animal procedures followed the National Institutes of Health Guidelines for the Care and Use of Laboratory Animals and were approved by the Animal Experimentation Ethics Committee at Army Medical University (No. AMUWEC20255474).

Collection of human renal samples

Kidney biopsy samples were collected as a standard part of the clinical diagnostic procedure, as detailed in Supplementary Table S1, and were obtained from the Department of Nephrology and the Department of Pathology, Renmin Hospital of Wuhan University. Control kidney samples were obtained from unaffected areas adjacent to cancerous tissues. Informed consent was obtained from all participants, and all procedures involving human subjects were approved by the Ethics Committee of Xinqiao Hospital, Army Medical University (No. 2023-YAN-143-01), following the Declaration of Helsinki guidelines. Clinical information was de-identified and reported in aggregate; no information that directly identifies individual participants is included. Sex and age were abstracted from clinical records, no participant compensation was provided, and sex-specific analyses were not performed because the human cohort was used for pathological validation and was not powered for sex-disaggregated inference.

Generation of brown fat ADRB3 knock-out mouse strain (ADRB3^BKO)

ADRB3^flox/flox knock-out mice with a C57BL/6J genetic background were purchased from Cyagen Biosciences (Suzhou, China). Recombinant transgenic offspring were generated by expression with UCP1-Cre recombinase (Cyagen Biosciences, China; catalogue no. C001259), producing an F1 generation with ADRB3 targeted expression. Mice with genotype ADRB3^flox/flox, UCP1-Cre⁺ were categorised as the knock-out group (ADRB3^BKO), while ADRB3^flox/flox, UCP1-Cre⁻ mice served as the control group (ADRB3^ctrl). In addition, UCP1-Cre mice were additionally crossed with Rosa26-LSL-tdTomato reporter mice to visualize UCP1-Cre activity in PRF, and tdTomato fluorescence was assessed by immunofluorescence co-staining with UCP1 and adipocyte markers. The generation and characterization of these mice was performed under blinded conditions. All animal experimental procedures followed the National Institutes of Health (NIH) Guidelines for the Care and Use of Laboratory Animals (Revised 2011), and all animal procedures were approved by the Animal Experimentation Ethics Committee at Army Medical University (No. AMUWEC20255474).

DKD mouse models

Two DKD mouse models were used in this study. First, male db/db and db/m mice (12 weeks old) with a BKS genetic background were obtained from Cytogenes Biosciences (Suzhou, China). Second, male ADRB3^BKO mice (6 weeks old) and wild-type C57BL/6N mice (6 weeks old, male) were injected intraperitoneally with STZ (65 mg/kg daily) for 3 consecutive days and maintained on a high-fat diet (HFD; 60 kcal% fat, 20 kcal% carbohydrate and 20 kcal% protein) for 12 weeks. Standard-chow groups received regular chow ad libitum. Mice were housed under specific pathogen-free conditions with a 12 h light/12 h dark cycle, ambient temperature of 22 ± 2 °C and relative humidity of 45–65%, with free access to food and water. Only male mice were used in mouse experiments to reduce variability associated with estrous cycling; therefore, sex as a biological variable was not tested in the animal studies. BRL 37344 (ADRB3 agonist; 2.5 mg/kg) was administered by intraperitoneal injection once daily for 2 weeks. Recombinant AAV vectors expressing ADRB3 (AAV-ADRB3) or control vector were delivered via tail vein injection (1 × 10¹¹ vg per mouse) at 6 weeks of age prior to STZ/HFD induction. To restore ADRB3 selectively in PRF UCP1-lineage adipocytes, a FLEX-AAV-ADRB3 vector or matched FLEX-AAV-control vector was bilaterally injected into PRF of UCP1-Cre;ADRB3^flox/flox mice (1 × 10¹¹ vg per mouse) at 6 weeks of age prior to STZ/HFD induction. To restore ADRB3 selectively in iBAT UCP1-lineage adipocytes, the same FLEX-AAV-ADRB3 or matched FLEX-AAV-control vector was bilaterally injected into iBAT using the same total viral dose and timing. For antioxidant treatment, N-acetylcysteine (NAC) was provided in drinking water (0.5 g/L) for 4 weeks during the late stage of STZ/HFD feeding.

Surgical removal of PRF

To investigate the effect of PRF on DKD, 12-week-old db/db mice were anaesthetized by intraperitoneal injection of pentobarbital (50 mg/kg body weight), and PRF was removed and sutured, while the control group was subjected to a sham-operated treatment¹⁵.

7T MRI for perirenal fat quantification

Mice were imaged on a 7.0-T small-animal MRI system (Bruker, Germany) equipped with a volume transmit/receive coil (inner diameter ~35 mm) under 1.5–2.0% isoflurane in 100% O₂; respiration and temperature (37 ± 0.5 °C, warm air) were monitored and maintained throughout acquisition. High-resolution coronal T₁-weighted spin-echo (or fast spin-echo) datasets encompassing both kidneys and surrounding retroperitoneal space were acquired (typical parameters: TR 600–800 ms, TE 10–12 ms, echo train 4, FOV ~ 30 × 30 mm, matrix 256 × 256, in-plane resolution ~0.12 mm, slice thickness 0.6 mm, 0.1 mm gap). Raw magnitude images were intensity-standardized across animals using a reference phantom placed adjacent to the abdomen and converted to pseudo-color heat maps to enhance fat-soft tissue contrast. An elliptical region of interest (ROI) tightly circumscribing each kidney and contiguous perirenal adipose compartment was first manually defined in representative lean db/m mice by two blinded observers; this ROI mask was then propagated (rigid body registration) to all slices in db/m and db/db (or ADRB3^ctrl/ADRB3^BKO) cohorts and adjusted as needed to include the entire fat sheath without intruding into bowel mesentery. PRF volume was segmented semi-automatically by intensity thresholding (fat-rich voxels >mean kidney parenchyma +2 SD) followed by manual correction; bilateral volumes were summed and normalized to body weight or kidney volume as indicated. Inter-observer reproducibility (intra-class correlation) exceeded 0.9; all analyses were conducted blinded to genotype/treatment.

Anti-TNFα neutralization/isotype control in vivo

To test the causal role of TNFα in PRF-driven renal fibrosis, ADRB3^ctrl and ADRB3^BKO mice undergoing the DKD (STZ/HFD) protocol were block-randomized at 12 weeks post-STZ by body weight, and albuminuria into anti-TNFα or isotype IgG arms; investigators were blinded to treatment. Purified anti-mouse TNFα monoclonal antibody (rat IgG1, clone XT3.11 or equivalent; Bio X Cell; endotoxin <2 EU/mg) and matched rat IgG1κ isotype were diluted in sterile PBS. Antibody (10 mg/kg body weight) or isotype control was administered intraperitoneally twice weekly for 4 weeks.

Isolation of primary adipocytes

PRF was sheared in chyme form and the cells were digested using collagenase and then filtered through a 70 µm filter membrane to obtain preadipocytes. Pre-adipocytes were treated with differentiation medium (10% FBS DMEM/F12 medium supplemented with 0.02 mM insulin, 0.5 mM IBMX, 1 μM rosiglitazone, 1 nM triiodothyronine, and 100 nM dexamethasone) for 4 days, and then maintained in 0.02 mM insulin and 1 nM triiodothyronine medium, and harvested on 6–8 days.

Isolation of primary tubular cells (TECs)

TECs were isolated from different group of mice. In brief, kidney tissues were obtained under aseptic conditions and washed twice or three times with a phosphate-buffered saline (PBS) solution. The renal cortex was then minced and ground in an 80 μm stainless steel mesh sieve and rinsed thoroughly with a PBS solution. The sub-mesh liquid is poured into a 150 μm stainless steel sieve, collected and rinsed with PBS. Centrifugation at 1000 r/min for 5 min is then performed, after which the supernatant is discarded.

Cell culture

TECs and primary adipocytes were cultured in DMEM/F12 medium (Invitrogen) supplemented with 10% fetal bovine serum (FBS; GIBCO, Australia). Primary adipocytes were treated with BRL 37344 (1 μM) and/or BT2 (a BCKDK inhibitor) to modulate ADRB3 signaling and BCAA oxidation, respectively, and/or supplemented with a BCAA mixture (leucine, isoleucine, and valine) at the indicated concentrations. For gain- and loss-of-function analyses, primary adipocytes were transfected with overexpression plasmids (e.g., ADRB1 or BCAT2) or with siRNAs targeting Bcat2 or Bckdha (sequences listed in Table S2) using Lipofectamine 3000 or Lipofectamine RNAiMAX (Thermo Fisher Scientific) according to the manufacturers’ protocols, and transfection efficiency/knockdown was validated by qPCR and/or Western blotting.

Coculture of TECs and adipocytes

TECs were inoculated in the lower chamber of a six-well Transwell plate (Corning, Lowell, MA, USA) with a pore size of 0.4 μm, and adipose cells were inoculated in the upper insert. Adipocytes were cocultured with TECs for 24 h. For conditioned-medium (CM) experiments, adipocytes were cultured under the indicated conditions and CM was collected, centrifuged to remove debris, and applied to TECs for the indicated time. Where indicated, CM was pre-incubated with neutralizing anti-TNFα antibody or isotype control prior to TEC exposure, followed by assessment of mitochondrial function, lipid accumulation, and profibrotic responses in TECs.

siRNA transfection

Primary adipocytes (or TECs) were seeded in 6-well or 12-well plates and transfected at ~60–70% confluence in antibiotic-free medium. For siRNA knockdown (si-Bcat2, si-Bckdha, si-Mettl3; negative control: scrambled siRNA), siRNA-Lipofectamine RNAiMAX complexes were prepared in Opti-MEM according to the manufacturer’s instructions. Briefly, siRNA was diluted in Opti-MEM to achieve a final concentration of 25–50 nM in each well, and Lipofectamine RNAiMAX was diluted separately in Opti-MEM. The diluted reagents were combined, incubated for 10–15 min at room temperature, and added dropwise to cells. After 6 h, the medium was replaced with complete growth medium. Cells were harvested at 48 h for RT-qPCR and at 48 h for Western blotting to validate knockdown efficiency.

Plasmid overexpression transfection

For plasmid overexpression (Bcat2, ADRB1, METTL3, CREB1, or corresponding empty vectors), cells were transfected using Lipofectamine 3000. In brief, plasmid DNA was diluted in Opti-MEM and mixed with P3000 reagent, while Lipofectamine 3000 was diluted separately in Opti-MEM. The mixtures were combined, incubated for 10–15 min at room temperature, and added to cells in antibiotic-free medium. After 6 h, the medium was replaced with complete growth medium. Overexpression was confirmed by RT-qPCR and/or immunoblotting 24–48 h post-transfection.

Measurement of PRF by MRI in mice

Initially, we conducted MRI scans at 7T on both db/m and db/db mice. Subsequently, the acquired MRI T1 images were converted into pseudo-color images, utilizing differences in fat density. This was achieved by defining an elliptical region of interest (ROI) in db/m mice and subsequently applying the resulting ROI mask to db/db images.

Histology

At the experimental endpoint, mice were euthanized by intraperitoneal injection of an overdose of pentobarbital sodium (150 mg/kg). Once death was confirmed by cessation of respiration and heartbeat, both the kidney and PRF were promptly collected and fixed in a 4% paraformaldehyde with a pH of 7.4 for subsequent histological examination, adhering to the standard protocol. Briefly, paraffin sections (5 µm) were subjected to dewaxing procedures and subsequently prepared for staining using periodic acid-Schiff (PAS), MASSON trichrome, hematoxylin and eosin (HE), periodic acid-silver methenamine (PASM) techniques.

Western blotting

Following treatment, cells or kidney tissues were lysed in RIPA buffer supplemented with phenylmethanesulfonyl fluoride and a protease inhibitor mixture (Roche) for 30 min at 4 °C. Following total protein separation on 8–10% SDS-PAGE gels, the protein was then transferred onto PVDF membranes, which were blocked with 5% milk for 1 h. Afterwards, the membranes were subjected to overnight incubation with primary antibodies at 4 °C (1:1000 unless otherwise indicated) and with HRP-labeled secondary antibodies (1:5000). Following three washes of the membranes, the bands were visualized utilizing the ECL chemiluminescence kit (Biosharp, China). Finally, the bands were subjected to analysis using the ChemiDoc MP Imaging System (Bio-Rad, USA). The primary antibodies used include anti-αSMA (ab179467, abcam), anti-FN1 (ab2413, abcam), anti-FABP1 (ab171739, abcam), anti-PPARA (ab314112, abcam), anti-ADRB1 (GTX23546, GeneTex), anti-ADRB2 (GTX642174, GeneTex), anti-ADRB3 (ab94506, abcam), anti-Bcat2 (GTX33036, GeneTex), anti-CREB1 (GTX640158, GeneTex), and anti-β-actin (GTX109639, GeneTex), followed by the addition of HRP-labeled secondary antibodies.

Immunohistochemistry (IHC)

Paraffin-embedded tissue sections were deparaffinized in xylene and rehydrated through graded ethanol to distilled water. Antigen retrieval was performed in citrate buffer (10 mM sodium citrate, pH 6.0) or EDTA buffer (pH 9.0) using a microwave/pressure cooker, followed by cooling to room temperature. Endogenous peroxidase activity was quenched with 3% H₂O₂ for 10 min, and sections were washed with PBS. Sections were blocked with 5% BSA for 60 min at room temperature, then incubated with primary antibodies, including anti-αSMA (ab179467, abcam), anti-FN1 (ab2413, abcam), anti-ADRB3 (ab94506, abcam), anti-4-HNE (GTX01087, GeneTex), and anti-8-OHdG (ab48508, abcam), diluted in antibody diluent (1:200 unless otherwise indicated) overnight at 4 °C in a humidified chamber. After washing, sections were incubated with HRP-conjugated secondary antibody (1:500) (or polymer-based HRP detection reagent) for 30–60 min at room temperature. Signal was developed with 3,3’-diaminobenzidine (DAB) until appropriate staining intensity was achieved. Sections were counterstained with hematoxylin, dehydrated through graded ethanol, cleared in xylene, and mounted with resinous mounting medium. Images were acquired using a bright-field microscope. Quantification was performed in a blinded manner using ImageJ.

Immunofluorescence (IF) assay

For IF analysis, the sections were incubated with LTL (FL-1321-2, Vector Laboratories), anti-m6A (ab151230, Abcam), anti-PLIN1 (9349, Cell Signaling Technology), anti-tdTomato (600-401-379, Rockland Immunochemicals), anti-αSMA (ab179467, abcam), anti-FN1 (ab2413, abcam), anti-Bcat2 (ab307833, abcam), anti-TFAM (ab176558, abcam), and anti-ADRB3 (ab94506, abcam), diluted 1:200 unless otherwise indicated. Following this, the samples were further incubated with fluorescent secondary antibodies (1:500) for 1 h. Subsequent to thorough washing, the nuclei of the samples were counterstained with DAPI, allowing for observation and capturing of images under the microscope (Olympus, Tokyo, Japan).

Oil red O (ORO), dihydroethidium (DHE), succinate dehydrogenase (SDH) staining and ATP measurement

Kidney tissues or TECs were subjected to fixation utilizing 4% paraformaldehyde (Sigma-Aldrich Corp., St. Louis, MO, USA). Subsequently, the samples were stained with ORO solution (Sigma, USA), DHE solution (Sigma, USA) and SDH solution (Sigma, USA) to enable the visualization of intracellular oil droplets under the microscope, followed by image capture. The working solution was then eluted using 60% isopropanol (Servicebio, China). Finally, the samples were observed under a microscope at a magnification of 400×. For ATP measurement, ATP content was measured using an ATP Determination Kit (abcam, USA). In addition, 4-hydroxynonenal (4-HNE) and 8-hydroxy-2’-deoxyguanosine (8-OHdG) staining were performed to assess lipid peroxidation and oxidative DNA damage, respectively.

Single-cell transcriptomic sequencing and analysis

PRF was isolated from 12-week-old db/m and db/db mice and immediately placed in ice-cold PBS. PRF was finely minced and digested using collagenase to obtain a single-cell suspension. The digested tissue was filtered through a 70 μm cell strainer to remove debris, followed by washing and red blood cell lysis when necessary. The resulting cells were resuspended in staining buffer, and viable single cells were enriched (excluding dead cells by viability dye) to generate a high-quality suspension for single-cell transcriptomic sequencing. Single-cell RNA-seq libraries were prepared following the manufacturer’s standard protocol and sequenced on an Illumina platform to generate gene-by-cell count matrices.

For downstream analysis, raw count matrices were subjected to quality control to remove low-quality cells, doublets, and cells with high mitochondrial transcript fractions. Datasets from db/m and db/db PRF were normalized and integrated, and unsupervised clustering was performed using the Seurat pipeline. Dimensionality reduction was conducted using PCA followed by UMAP for visualization. Cell clusters were annotated based on canonical marker genes, yielding major PRF cell populations including adipocytes, adipose stem/progenitor cells (ASPCs), endothelial cells, and monocytes/macrophages. To resolve adipocyte heterogeneity, adipocytes were further classified as brown, beige, and white using established marker genes (including thermogenic markers such as UCP1). Differential expression and pathway enrichment analyses (including KEGG) were performed to identify DKD-associated transcriptional changes within key PRF compartments, and cluster abundance was compared between groups to assess compositional remodeling in DKD.

RNA sequencing and transcriptomic analysis

PRF was isolated from ADRB3^ctrl and ADRB3^BKO mice subjected to the streptozotocin/high-fat diet (STZ/HFD) DKD protocol; differentiated adipocytes (day 6–8) were harvested after collagenase digestion and ex vivo differentiation (see Supplementary Methods for media composition). Cell pellets were rinsed in ice-cold PBS, flash-frozen in liquid N₂, and stored at −80 °C until extraction. Total RNA was isolated with TRIzol, followed by column cleanup and on-column DNase I digestion. RNA integrity was confirmed on an Agilent 2100 Bioanalyzer (RIN ≥ 7.5); quantity was measured by Qubit. Poly(A)+-selected, strand-specific libraries were prepared from 500 ng RNA using the NEBNext Ultra II Directional kit with unique dual indexes, PCR-amplified (≤12 cycles), size-selected (~300 bp inserts), pooled equimolarly, and sequenced (150-bp paired-end) on an Illumina NovaSeq 6000 (≥ 40 M read pairs/sample). Raw FASTQs were trimmed and quality-filtered with fastp (adapter removal; Q < 20 trimming; min length 36 nt), then aligned to the mouse GRCm39 (mm39) reference using STAR (two-pass mode); gene counts were obtained with featureCounts (GENCODE M31). Public renal datasets (GSE2508; GSE166239) were downloaded from GEO and reprocessed analogously against GRCh38. Count matrices were analyzed in DESeq2 (R v4.3); genes with <10 total counts were excluded; size-factor normalization and variance-stabilizing transformation were applied; DEGs were defined by |log₂FC| ≥ 1, FDR < 0.05 (Benjamini–Hochberg), with apeglm shrinkage for display. Pathway interrogation used clusterProfiler for KEGG/GO over-representation and preranked GSEA (Hallmark/Reactome sets), focusing on lipid metabolism, BCAA catabolism, inflammation, and NF-κB signaling. Visualization (volcano, heatmap, enrichment bubble, interaction networks) was performed in R and Cytoscape. Newly generated RNA-seq data have been deposited in the NCBI Sequence Read Archive under accession PRJNA1443278; accession numbers for public datasets are provided in the “Data Availability” statement.

Targeted LC-MS/MS measurement of BCAAs

Valine, leucine and isoleucine were quantified in PRF lysates or primary adipocyte samples using targeted liquid chromatography-tandem mass spectrometry. Sample numbers matched the corresponding figure legends and Source Data file, typically n = 8 biological replicates per group. Samples were homogenized in chilled 80% methanol containing internal standards, centrifuged at 12,000 × g for 10 min at 4 °C, and supernatants were analyzed on a triple-quadrupole LC-MS/MS platform in multiple-reaction-monitoring mode using standard calibration curves. Peaks were manually inspected, normalized to protein content or tissue weight as indicated, and analyzed using the statistical procedures described below. Individual metabolite values are provided in the Source Data file.

Quantitative real-time polymerase chain reaction (qPCR)

Total RNA was extracted from cultured cells using an RNA extraction kit. The total RNA was then reverse-transcribed according to the manufacturer’s instructions. PCR amplification using fluorescent dye (Ultrasybr) was performed using Roche 480 II fluorescence quantitative PCR apparatus. Quantitative analysis was performed by 2^−△△CT. The sequence of RNA primers is shown in Table S2.

Luciferase reporter assay (LUC)

The mouse Mettl3 promoter fragment (wild type) was cloned into the pGL3-Basic luciferase reporter vector, and promoter truncations and a binding-site mutant (mutating the predicted CREB1 motif sequence “ACATGATGCCATA”) were generated by PCR and site-directed mutagenesis and sequence-verified. Cells were seeded in 24-well plates and co-transfected with the firefly reporter plasmid (WT/mutant/truncations), a CREB1 overexpression plasmid or empty vector, and a Renilla luciferase plasmid as an internal control using Lipofectamine 3000. After 48 h, cells were lysed, and luciferase activities were measured using a Dual-Luciferase Reporter Assay System according to the manufacturer’s instructions. Firefly luciferase activity was normalized to Renilla luciferase activity and expressed as relative luciferase units (RLU) or fold change versus control; experiments were performed with at least three independent biological replicates.

Chromatin immunoprecipitation-PCR (ChIP-PCR)

Chromatin immunoprecipitation was performed to examine CREB1 occupancy on the Mettl3/Bcat2 promoter using standard procedures. Briefly, cells were crosslinked with 1% formaldehyde for 10 min at room temperature and quenched with 125 mM glycine, washed with cold PBS, and lysed to isolate nuclei. Chromatin was sheared by sonication to ~200–500 bp fragments, and an aliquot was saved as input. Equal amounts of chromatin were incubated overnight at 4 °C with anti-CREB1 antibody or species-matched IgG control, followed by capture with protein A/G magnetic beads, stringent washes, and elution. Crosslinks were reversed at 65 °C, samples were treated with RNase A and proteinase K, and ChIP DNA was purified and analyzed by PCR using primers spanning the predicted CREB1-binding regions within the Mettl3 promoter (and control regions). ChIP-PCR enrichment was calculated as % input and/or fold enrichment over IgG using the ΔCt method, with at least three independent biological replicates.

Biochemical measurements

Mice were examined monthly to monitor body weight and blood glucose levels. Blood samples were taken from the mice to measure serum urea nitrogen (BUN) and serum creatinine (Cr).

Measurement of urinary albumin-to-creatinine ratio (UACR)

Twenty-four-hour urine samples from the mice were collected utilizing metabolic cages. The UACR was determined utilizing the Albumin Assay Kit (Jiancheng, Nanjing, China) and the Creatinine (Cr) Assay Kit (Jiancheng, Nanjing, China). Absorbance was measured at 630 and 546 nm using a microplate reader (PerkinElmer, Massachusetts, USA). Serum insulin, β-hydroxybutyrate, lactate, free fatty acids (FFA), malondialdehyde (MDA), and ceramide content were additionally quantified using commercial assay kits. Branched-chain amino acids (leucine, isoleucine, and valine) in PRF were measured as indicated.

Measurement of triglyceride (TG) and total cholesterol (TCH)

Plasma was harvested following centrifugation at 3000 × g for 20 min. The PRF tissue was subsequently homogenized in PBS buffer, and the resulting supernatant was obtained following centrifugation at 5000 × g for 12 min. To determine the levels of TG and TCH in these samples, the manufacturer’s instructions provided by Sigma-Aldrich (St. Louis, MO, USA) were followed.

Enzyme-linked immunosorbent assay (ELISA)

The culture medium was collected after centrifugation of the cells. Concentrations of TNF-α were quantified using a high-sensitivity electrochemiluminescent immunoassay (MSD, Meso Scale Discovery, USA), following the manufacturer’s instructions. Concentrations of IL-1β, IL-6, adipokines and related factors (adiponectin, leptin, resistin, and PAI-1) in culture medium were quantified using a mouse enzyme-linked immunosorbent assay (ELISA) kit (Invitrogen, USA). Additional ELISA assays were performed for adipokines and related factors (adiponectin, leptin, resistin, and PAI-1) and, where indicated, insulin, following the manufacturers’ instructions.

Oxygen consumption rate (OCR) measurement

Mitochondrial oxygen consumption was assessed using the Mitochondrial Stress Test Kit (103015100, Agilent). OCR was measured using the Seahorse Bioscience XFe96 extracellular flux analyser (XFe96, Seahorse Bioscience) as previously described.

m6A RNA immunoprecipitation (RIP) and quantification

m6A enrichment on target transcripts was measured by methylated RNA immunoprecipitation (MeRIP; m6A-RIP) followed by RT-qPCR. Total RNA was extracted from primary adipocytes using TRIzol (or equivalent) and treated with DNase I to remove genomic DNA contamination. Purified RNA (typically 2–10 μg per reaction) was fragmented to ~100–200 nt using RNA fragmentation buffer under controlled conditions, and the reaction was stopped immediately on ice. Fragmented RNA was incubated with an anti-m6A antibody or species-matched IgG control in immunoprecipitation (IP) buffer containing RNase inhibitor at 4 °C with rotation. Antibody-RNA complexes were captured using protein A/G magnetic beads, washed stringently to reduce nonspecific binding, and eluted. RNA was recovered from the IP and input fractions by proteinase K digestion followed by phenol/chloroform extraction or column purification. cDNA was synthesized from equal volumes of input and IP RNA using a reverse transcription kit, and target transcript abundance in the m6A-IP fraction was quantified by qPCR. m6A enrichment was calculated as percentage of input and/or fold enrichment over IgG. All experiments were performed with at least three independent biological replicates.

O-propargyl-puromycin (OPP) labeling and streptavidin pulldown

Cells were incubated with O-propargyl-puromycin (OPP) for a short pulse to label nascent polypeptides. After washing, cells were lysed in RIPA buffer with protease inhibitors, and equal amounts of protein were subjected to click-chemistry biotinylation using biotin-azide. Biotinylated nascent proteins were enriched with streptavidin magnetic beads, extensively washed, and eluted in SDS sample buffer. Eluates and input lysates were analyzed by SDS-PAGE and immunoblotting to quantify newly synthesized proteins, with densitometry normalized to input.

Quantitative and statistical analyses

Sample sizes were selected based on prior DKD mouse and primary-cell experiments, pilot variability and the number of matched biological replicates available for each assay; no formal statistical power calculation was performed. Unless otherwise stated, each point represents one mouse or one biologically independent experiment, and data are presented as mean ± standard error of the mean. Statistical analyses were performed using GraphPad Prism 8.0 and R 4.3.0. Two-sided tests were used unless explicitly stated. For two-group comparisons, two-tailed unpaired Student’s t-tests were used. For comparisons involving more than two groups, one-way or two-way ANOVA was used with Tukey, Sidak or Benjamini–Hochberg correction as stated in the figure legends. Repeated-measures two-way ANOVA was used for longitudinal or OCR time-course data. Pearson correlation analyses were two-tailed. Statistical significance was set at P < 0.05, and exact P values are shown in the corresponding figures. Image quantification was performed using ImageJ 1.53. Sequencing analyses used fastp v0.23, STAR v2.7, featureCounts/Subread v2.0, DESeq2 v1.40, Seurat v4, clusterProfiler v4 and Cytoscape 3.10 where applicable.

Reporting summary

Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

Supplementary information

Supplementary Information^{(11MB, pdf)}

Reporting Summary^{(9MB, pdf)}

Transparent Peer Review file^{(39.2KB, pdf)}

Source data

Source data^{(2.2MB, xlsx)}

Acknowledgements

We thank all study participants and the clinical and animal-care staff who contributed to this work.

Author contributions

H.H. designed the experiments and performed imaging, cell culture, biochemical assays, Seahorse experiments, lentivirus production and data analysis. R.J. performed cell culture and RNA-seq analyses and helped with immunoblotting. Z.L. and Y.A. helped with cell culture and experimental design. S.G., M.Y., Y.Z., and W.X. helped with animal experiments. Y.H. designed the study, supervised the project, revised the manuscript and acquired funding. All authors agree to be accountable for all aspects of the work and to ensure its integrity and accuracy.

Peer review

Peer review information

Nature Communications thanks Bing Guo and other anonymous reviewers for their contribution to the peer review of this work. A peer review file is available.

Funding

This work was supported by research grants from Natural Science Foundation of China (Nos. 82322012, 82170705), National Key R&D Program of China (No. 2022YFC2502500), National Science and Technology Major Project (No. 2025ZD0547600), Chongqing Science and Technology Talent Program (Nos. CSTB2025NSCQ-JQX0018, CQYC20220511193), and Science and Technology Innovation Projects of Xinqiao Hospital (Nos. 2023XKRC004, 2023XRC02).

Data availability

RNA-seq data generated in this study have been deposited in the NCBI Sequence Read Archive under accession PRJNA1443278. Public datasets used in this study are available from the Gene Expression Omnibus under accession GSE166239 and GSE2508. Targeted BCAA metabolite measurements and data underlying graphs are provided in the Source Data file. All other data are available within the Article, Supplementary Information and Source Data file. Source data are provided with this paper.

Code availability

No custom code or mathematical algorithm central to the conclusions was developed for this study. Data were analyzed using standard software and packages as described in “Methods”.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

These authors contributed equally: Hongtu Hu, Rui Ji.

Supplementary information

The online version contains supplementary material available at https://doi.org/10.1038/s41467-026-77325-2.

References

1.Alicic, R. Z., Rooney, M. T. & Tuttle, K. R. Diabetic kidney disease: challenges, progress, and possibilities. Clin. J. Am. Soc. Nephrol.12, 2032–2045 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
2.Gupta, S., Dominguez, M. & Golestaneh, L. Diabetic kidney disease: an update. Med. Clin. North Am.107, 689–705 (2023). [DOI] [PubMed] [Google Scholar]
3.Thomas, M. C. et al. Diabetic kidney disease. Nat. Rev. Dis. Prim.1, 15018 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Tuttle, K. R. et al. Molecular mechanisms and therapeutic targets for diabetic kidney disease. Kidney Int.102, 248–260 (2022). [DOI] [PubMed] [Google Scholar]
5.Nastase, M. V., Zeng-Brouwers, J., Wygrecka, M. & Schaefer, L. Targeting renal fibrosis: mechanisms and drug delivery systems. Adv. Drug Deliv. Rev.129, 295–307 (2018). [DOI] [PubMed] [Google Scholar]
6.Mori, Y. et al. KIM-1 mediates fatty acid uptake by renal tubular cells to promote progressive diabetic kidney disease. Cell Metab.33, 1042–1061.e1047 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Lin, X., Chen, Z., Huang, H., Zhong, J. & Xu, L. Diabetic kidney disease progression is associated with decreased lower-limb muscle mass and increased visceral fat area in T2DM patients. Front. Endocrinol.13, 1002118 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Yang, J. et al. Perirenal fat thickness is associated with metabolic dysfunction-associated fatty liver disease in type 2 diabetes mellitus. Diab. Metab. Syndr. Obes.16, 1953–1965 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Kang, P., Sun, B., Hao, J., Wang, C. & Chen, X. Perirenal fat and chronic kidney disease: a systematic review and meta-analysis. Kidney Blood Press Res.50, 240–248 (2025). [DOI] [PubMed] [Google Scholar]
10.Hu, H. et al. The utility of perirenal fat in determining the risk of onset and progression of diabetic kidney disease. Int. J. Endocrinol.2022, 2550744 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Tian, R., Zhang, T., Dong, H., Seim, I. & Yang, G. Cetacean loss of the master adipose tissue regulator beta(3)-adrenergic receptor may underlie their thick blubber and an Oligocene radiation and dispersal. Nat. Commun.16, 9235 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Ciecwiez, S. M. et al. Functional polymorphism in the ADRB3 gene, encoding the beta-3 adrenergic receptor, and response to intra-detrusor injection of botulinum toxin-A in women with overactive bladder. J. Clin. Med.11, 7491 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Blondin, D. P. et al. Human brown adipocyte thermogenesis is driven by beta2-AR stimulation. Cell Metab.32, 287–300.e287 (2020). [DOI] [PubMed] [Google Scholar]
14.Cuatrecasas, G. et al. Dapagliflozin added to metformin reduces perirenal fat layer in type 2 diabetic patients with obesity. Sci. Rep.14, 10832 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
15.Nogalska, A., Stelmanska, E., Sledzinski, T. & Swierczynski, J. Surgical removal of perirenal and epididymal adipose tissue decreases serum leptin concentration and increases lipogenic enzyme activities in remnant adipose tissue of old rats. Gerontology55, 224–228 (2009). [DOI] [PubMed] [Google Scholar]
16.Zhang, H., Li, Y., Ibanez, C. F. & Xie, M. Perirenal adipose tissue contains a subpopulation of cold-inducible adipocytes derived from brown-to-white conversion. eLife13, RP93151 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Liu, B. X., Sun, W. & Kong, X. Q. Perirenal fat: a unique fat pad and potential target for cardiovascular disease. Angiology70, 584–593 (2019). [DOI] [PubMed] [Google Scholar]
18.Sun, L. et al. Alterations in mitochondrial biogenesis and respiratory activity, inflammation of the senescence-associated secretory phenotype, and lipolysis in the perirenal fat and liver of rats following lifelong exercise and detraining. FASEB J.35, e21890 (2021). [DOI] [PubMed] [Google Scholar]
19.Cannavo, A. et al. beta3AR-dependent brain-derived neurotrophic factor (BDNF) generation limits chronic postischemic heart failure. Circ. Res.132, 867–881 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Susulic, V. S. et al. Targeted disruption of the beta 3-adrenergic receptor gene. J. Biol. Chem.270, 29483–29492 (1995). [DOI] [PubMed] [Google Scholar]
21.Weinlich, R. et al. Protective roles for caspase-8 and cFLIP in adult homeostasis. Cell Rep.5, 340–348 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Verkerke, A. R. P. et al. BCAA-nitrogen flux in brown fat controls metabolic health independent of thermogenesis. Cell187, 2359–2374.e2318 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Liu, X., Hu, W., Sun, J. & Wu, B. Fructose intake driven glycolysis-ROS-EGFR axis specifically promotes the generation and pathogenicity of Th17 cells. Nat. Commun.16, 11115 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Bollinger, E. et al. Restoration of branched chain amino acid catabolism improves kidney function in preclinical cardiovascular-kidney-metabolic syndrome models. Kidney Int.108, 310–316 (2025). [DOI] [PubMed] [Google Scholar]
25.Guo, X. et al. Lymphatic endothelial branched-chain amino acid catabolic defects undermine cardiac lymphatic integrity and drive HFpEF. Circulation151, 1651–1666 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
26.Zhang, Y. W. et al. GPRC5C drives branched-chain amino acid metabolism in leukemogenesis. Blood Adv.7, 7525–7538 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Garcia, B. et al. Effects of branched-chain amino acids on the inflammatory response induced by LPS in Caco-2 cells. Metabolites14, 76 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Wang, J. TFTF: an R-based integrative tool for decoding human transcription factor-target interactions. Biomolecules14, 749 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Jin, Z. et al. Vertical sleeve gastrectomy-derived gut metabolite licoricidin activates beige fat thermogenesis to combat obesity. Theranostics13, 3103–3116 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Ouyang, L. et al. ALKBH1-demethylated DNA N6-methyladenine modification triggers vascular calcification via osteogenic reprogramming in chronic kidney disease. J. Clin. Invest.131, e146985 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Song, T., Yang, Y., Jiang, S. & Peng, J. Novel insights into adipogenesis from the perspective of transcriptional and RNA N6-methyladenosine-mediated post-transcriptional regulation. Adv. Sci.7, 2001563 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Huang, W. et al. N6-methyladenosine methyltransferases: functions, regulation, and clinical potential. J. Hematol. Oncol.14, 117 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Kang, Q. et al. Adipose METTL14-elicited N(6) -methyladenosine promotes obesity, insulin resistance, and NAFLD through suppressing beta adrenergic signaling and lipolysis. Adv. Sci.10, e2301645 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Sanz, A. B., Sanchez-Niño, M. D., Ramos, A. M. & Ortiz, A. Regulated cell death pathways in kidney disease. Nat. Rev. Nephrol.19, 281–299 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Yao, L. et al. Mitochondrial dysfunction in diabetic tubulopathy. Metabolism131, 155195 (2022). [DOI] [PubMed] [Google Scholar]
36.Mohandes, S. et al. Molecular pathways that drive diabetic kidney disease. J. Clin. Invest.133, e165654 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Alicic, R. Z., Cox, E. J., Neumiller, J. J. & Tuttle, K. R. Incretin drugs in diabetic kidney disease: biological mechanisms and clinical evidence. Nat. Rev. Nephrol.17, 227–244 (2021). [DOI] [PubMed] [Google Scholar]
38.Xi, Y. et al. ACSL5 promotes lipid deposition and lipoapoptosis in proximal tubular epithelial cells of diabetic kidney disease. Mol. Cell Endocrinol.595, 112418 (2025). [DOI] [PubMed] [Google Scholar]
39.Srivastava, S. P. et al. Endothelial SIRT3 regulates myofibroblast metabolic shifts in diabetic kidneys. iScience24, 102390 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Yang, M. et al. Crosstalk between the liver and kidney in diabetic nephropathy. Eur. J. Pharm.931, 175219 (2022). [DOI] [PubMed] [Google Scholar]
41.Zhang, A. et al. miRNA-23a/27a attenuates muscle atrophy and renal fibrosis through muscle-kidney crosstalk. J. Cachexia Sarcopenia Muscle9, 755–770 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Rao, N. L. et al. Receptor for advanced glycation end product, organ crosstalk, and pathomechanism targets for comprehensive molecular therapeutics in diabetic ischemic stroke. Biomolecules12, 1712 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Hu, S. et al. Crosstalk among podocytes, glomerular endothelial cells and mesangial cells in diabetic kidney disease: an updated review. Cell Commun. Signal22, 136 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Emont, M. P. et al. A single-cell atlas of human and mouse white adipose tissue. Nature603, 926–933 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Chen, X. et al. Perirenal fat thickness is significantly associated with the risk for development of chronic kidney disease in patients with diabetes. Diabetes70, 2322–2332 (2021). [DOI] [PubMed] [Google Scholar]
46.Sugimoto, S. et al. Brown adipose tissue-derived MaR2 contributes to cold-induced resolution of inflammation. Nat. Metab.4, 775–790 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
47.Claflin, K. E. et al. Conditional gene targeting using UCP1-Cre mice directly targets the central nervous system beyond thermogenic adipose tissues. Mol. Metab.55, 101405 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Kim K. et al. Uncoupling protein 1-driven Cre (Ucp1-Cre) is expressed in the epithelial cells of mammary glands and various non-adipose tissues. Mol. Metab.84, 101948 (2024). [DOI] [PMC free article] [PubMed]
49.Matsushita, N. et al. Highly selective transgene expression through the flip-excision switch system by using a unilateral spacer sequence. Cell Rep. Methods3, 100393 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
50.Jalloul, W., Grierosu, I. C., Jalloul, D., Stefanescu, C. & Ghizdovat, V. Functional complexity of thermogenic adipose tissue: from thermogenesis to metabolic and fibroinflammatory crosstalk. Int. J. Mol. Sci.26, 9045 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
51.Kashiwagi, E. Perirenal fat in disease progression: from inflammatory mediator to therapeutic target. Int. J. Urol.32, 1314–1320 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
52.Wang, T. & He, C. Pro-inflammatory cytokines: the link between obesity and osteoarthritis. Cytokine Growth Factor Rev.44, 38–50 (2018). [DOI] [PubMed] [Google Scholar]
53.Sciarretta, F. et al. Lipocalin-2 promotes adipose-macrophage interactions to shape peripheral and central inflammatory responses in experimental autoimmune encephalomyelitis. Mol. Metab.76, 101783 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
54.Kaesler, N. et al. Mapping cardiac remodeling in chronic kidney disease. Sci. Adv.9, eadj4846 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]
55.Lv, Z. et al. TRAIL induces podocyte PANoptosis via death receptor 5 in diabetic kidney disease. Kidney Int.107, 317–331 (2025). [DOI] [PubMed] [Google Scholar]
56.Speeckaert, M. M., Speeckaert, R., Laute, M., Vanholder, R. & Delanghe, J. R. Tumor necrosis factor receptors: biology and therapeutic potential in kidney diseases. Am. J. Nephrol.36, 261–270 (2012). [DOI] [PubMed] [Google Scholar]
57.Petersen, M. C. & Shulman, G. I. Mechanisms of insulin action and insulin resistance. Physiol. Rev.98, 2133–2223 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
58.Xu, M., Hu, D., Liu, X., Li, Z. & Lu, L. Branched-chain amino acids and inflammation management in endurance sports: molecular mechanisms and practical implications. Nutrients17, 1335 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]
59.Patrick, M. et al. Metabolon formation regulates branched-chain amino acid oxidation and homeostasis. Nat. Metab.4, 1775–1791 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]
60.Jiang, H. et al. Branched-chain amino acids promote thrombocytopoiesis by activating mTOR signaling. J. Thromb. Haemost.21, 3224–3235 (2023). [DOI] [PubMed] [Google Scholar]
61.Lin, J. R. et al. Brown adipocyte ADRB3 mediates cardioprotection via suppressing exosomal iNOS. Circ. Res.131, 133–147 (2022). [DOI] [PubMed] [Google Scholar]
62.Kratky, D., Obrowsky, S., Kolb, D. & Radovic, B. Pleiotropic regulation of mitochondrial function by adipose triglyceride lipase-mediated lipolysis. Biochimie96, 106–112 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
63.Mukherjee, S. & Yun, J. W. Prednisone stimulates white adipocyte browning via β₃-AR/p38 MAPK/ERK signaling pathway. Life Sci.288, 120204 (2022). [DOI] [PubMed] [Google Scholar]
64.Huang, Q. et al. Two novel functional single nucleotide polymorphisms of ADRB3 are associated with type 2 diabetes in the Chinese population. J. Clin. Endocrinol. Metab.98, E1272–E1277 (2013). [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Information^{(11MB, pdf)}

Reporting Summary^{(9MB, pdf)}

Transparent Peer Review file^{(39.2KB, pdf)}

Source data^{(2.2MB, xlsx)}

Data Availability Statement

No custom code or mathematical algorithm central to the conclusions was developed for this study. Data were analyzed using standard software and packages as described in “Methods”.

[CR1] 1.Alicic, R. Z., Rooney, M. T. & Tuttle, K. R. Diabetic kidney disease: challenges, progress, and possibilities. Clin. J. Am. Soc. Nephrol.12, 2032–2045 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR2] 2.Gupta, S., Dominguez, M. & Golestaneh, L. Diabetic kidney disease: an update. Med. Clin. North Am.107, 689–705 (2023). [DOI] [PubMed] [Google Scholar]

[CR3] 3.Thomas, M. C. et al. Diabetic kidney disease. Nat. Rev. Dis. Prim.1, 15018 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR4] 4.Tuttle, K. R. et al. Molecular mechanisms and therapeutic targets for diabetic kidney disease. Kidney Int.102, 248–260 (2022). [DOI] [PubMed] [Google Scholar]

[CR5] 5.Nastase, M. V., Zeng-Brouwers, J., Wygrecka, M. & Schaefer, L. Targeting renal fibrosis: mechanisms and drug delivery systems. Adv. Drug Deliv. Rev.129, 295–307 (2018). [DOI] [PubMed] [Google Scholar]

[CR6] 6.Mori, Y. et al. KIM-1 mediates fatty acid uptake by renal tubular cells to promote progressive diabetic kidney disease. Cell Metab.33, 1042–1061.e1047 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR7] 7.Lin, X., Chen, Z., Huang, H., Zhong, J. & Xu, L. Diabetic kidney disease progression is associated with decreased lower-limb muscle mass and increased visceral fat area in T2DM patients. Front. Endocrinol.13, 1002118 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR8] 8.Yang, J. et al. Perirenal fat thickness is associated with metabolic dysfunction-associated fatty liver disease in type 2 diabetes mellitus. Diab. Metab. Syndr. Obes.16, 1953–1965 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR9] 9.Kang, P., Sun, B., Hao, J., Wang, C. & Chen, X. Perirenal fat and chronic kidney disease: a systematic review and meta-analysis. Kidney Blood Press Res.50, 240–248 (2025). [DOI] [PubMed] [Google Scholar]

[CR10] 10.Hu, H. et al. The utility of perirenal fat in determining the risk of onset and progression of diabetic kidney disease. Int. J. Endocrinol.2022, 2550744 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR11] 11.Tian, R., Zhang, T., Dong, H., Seim, I. & Yang, G. Cetacean loss of the master adipose tissue regulator beta(3)-adrenergic receptor may underlie their thick blubber and an Oligocene radiation and dispersal. Nat. Commun.16, 9235 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR12] 12.Ciecwiez, S. M. et al. Functional polymorphism in the ADRB3 gene, encoding the beta-3 adrenergic receptor, and response to intra-detrusor injection of botulinum toxin-A in women with overactive bladder. J. Clin. Med.11, 7491 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR13] 13.Blondin, D. P. et al. Human brown adipocyte thermogenesis is driven by beta2-AR stimulation. Cell Metab.32, 287–300.e287 (2020). [DOI] [PubMed] [Google Scholar]

[CR14] 14.Cuatrecasas, G. et al. Dapagliflozin added to metformin reduces perirenal fat layer in type 2 diabetic patients with obesity. Sci. Rep.14, 10832 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR15] 15.Nogalska, A., Stelmanska, E., Sledzinski, T. & Swierczynski, J. Surgical removal of perirenal and epididymal adipose tissue decreases serum leptin concentration and increases lipogenic enzyme activities in remnant adipose tissue of old rats. Gerontology55, 224–228 (2009). [DOI] [PubMed] [Google Scholar]

[CR16] 16.Zhang, H., Li, Y., Ibanez, C. F. & Xie, M. Perirenal adipose tissue contains a subpopulation of cold-inducible adipocytes derived from brown-to-white conversion. eLife13, RP93151 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR17] 17.Liu, B. X., Sun, W. & Kong, X. Q. Perirenal fat: a unique fat pad and potential target for cardiovascular disease. Angiology70, 584–593 (2019). [DOI] [PubMed] [Google Scholar]

[CR18] 18.Sun, L. et al. Alterations in mitochondrial biogenesis and respiratory activity, inflammation of the senescence-associated secretory phenotype, and lipolysis in the perirenal fat and liver of rats following lifelong exercise and detraining. FASEB J.35, e21890 (2021). [DOI] [PubMed] [Google Scholar]

[CR19] 19.Cannavo, A. et al. beta3AR-dependent brain-derived neurotrophic factor (BDNF) generation limits chronic postischemic heart failure. Circ. Res.132, 867–881 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR20] 20.Susulic, V. S. et al. Targeted disruption of the beta 3-adrenergic receptor gene. J. Biol. Chem.270, 29483–29492 (1995). [DOI] [PubMed] [Google Scholar]

[CR21] 21.Weinlich, R. et al. Protective roles for caspase-8 and cFLIP in adult homeostasis. Cell Rep.5, 340–348 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR22] 22.Verkerke, A. R. P. et al. BCAA-nitrogen flux in brown fat controls metabolic health independent of thermogenesis. Cell187, 2359–2374.e2318 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR23] 23.Liu, X., Hu, W., Sun, J. & Wu, B. Fructose intake driven glycolysis-ROS-EGFR axis specifically promotes the generation and pathogenicity of Th17 cells. Nat. Commun.16, 11115 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR24] 24.Bollinger, E. et al. Restoration of branched chain amino acid catabolism improves kidney function in preclinical cardiovascular-kidney-metabolic syndrome models. Kidney Int.108, 310–316 (2025). [DOI] [PubMed] [Google Scholar]

[CR25] 25.Guo, X. et al. Lymphatic endothelial branched-chain amino acid catabolic defects undermine cardiac lymphatic integrity and drive HFpEF. Circulation151, 1651–1666 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR26] 26.Zhang, Y. W. et al. GPRC5C drives branched-chain amino acid metabolism in leukemogenesis. Blood Adv.7, 7525–7538 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR27] 27.Garcia, B. et al. Effects of branched-chain amino acids on the inflammatory response induced by LPS in Caco-2 cells. Metabolites14, 76 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR28] 28.Wang, J. TFTF: an R-based integrative tool for decoding human transcription factor-target interactions. Biomolecules14, 749 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR29] 29.Jin, Z. et al. Vertical sleeve gastrectomy-derived gut metabolite licoricidin activates beige fat thermogenesis to combat obesity. Theranostics13, 3103–3116 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR30] 30.Ouyang, L. et al. ALKBH1-demethylated DNA N6-methyladenine modification triggers vascular calcification via osteogenic reprogramming in chronic kidney disease. J. Clin. Invest.131, e146985 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR31] 31.Song, T., Yang, Y., Jiang, S. & Peng, J. Novel insights into adipogenesis from the perspective of transcriptional and RNA N6-methyladenosine-mediated post-transcriptional regulation. Adv. Sci.7, 2001563 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR32] 32.Huang, W. et al. N6-methyladenosine methyltransferases: functions, regulation, and clinical potential. J. Hematol. Oncol.14, 117 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR33] 33.Kang, Q. et al. Adipose METTL14-elicited N(6) -methyladenosine promotes obesity, insulin resistance, and NAFLD through suppressing beta adrenergic signaling and lipolysis. Adv. Sci.10, e2301645 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR34] 34.Sanz, A. B., Sanchez-Niño, M. D., Ramos, A. M. & Ortiz, A. Regulated cell death pathways in kidney disease. Nat. Rev. Nephrol.19, 281–299 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR35] 35.Yao, L. et al. Mitochondrial dysfunction in diabetic tubulopathy. Metabolism131, 155195 (2022). [DOI] [PubMed] [Google Scholar]

[CR36] 36.Mohandes, S. et al. Molecular pathways that drive diabetic kidney disease. J. Clin. Invest.133, e165654 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR37] 37.Alicic, R. Z., Cox, E. J., Neumiller, J. J. & Tuttle, K. R. Incretin drugs in diabetic kidney disease: biological mechanisms and clinical evidence. Nat. Rev. Nephrol.17, 227–244 (2021). [DOI] [PubMed] [Google Scholar]

[CR38] 38.Xi, Y. et al. ACSL5 promotes lipid deposition and lipoapoptosis in proximal tubular epithelial cells of diabetic kidney disease. Mol. Cell Endocrinol.595, 112418 (2025). [DOI] [PubMed] [Google Scholar]

[CR39] 39.Srivastava, S. P. et al. Endothelial SIRT3 regulates myofibroblast metabolic shifts in diabetic kidneys. iScience24, 102390 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR40] 40.Yang, M. et al. Crosstalk between the liver and kidney in diabetic nephropathy. Eur. J. Pharm.931, 175219 (2022). [DOI] [PubMed] [Google Scholar]

[CR41] 41.Zhang, A. et al. miRNA-23a/27a attenuates muscle atrophy and renal fibrosis through muscle-kidney crosstalk. J. Cachexia Sarcopenia Muscle9, 755–770 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR42] 42.Rao, N. L. et al. Receptor for advanced glycation end product, organ crosstalk, and pathomechanism targets for comprehensive molecular therapeutics in diabetic ischemic stroke. Biomolecules12, 1712 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR43] 43.Hu, S. et al. Crosstalk among podocytes, glomerular endothelial cells and mesangial cells in diabetic kidney disease: an updated review. Cell Commun. Signal22, 136 (2024). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR44] 44.Emont, M. P. et al. A single-cell atlas of human and mouse white adipose tissue. Nature603, 926–933 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR45] 45.Chen, X. et al. Perirenal fat thickness is significantly associated with the risk for development of chronic kidney disease in patients with diabetes. Diabetes70, 2322–2332 (2021). [DOI] [PubMed] [Google Scholar]

[CR46] 46.Sugimoto, S. et al. Brown adipose tissue-derived MaR2 contributes to cold-induced resolution of inflammation. Nat. Metab.4, 775–790 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR47] 47.Claflin, K. E. et al. Conditional gene targeting using UCP1-Cre mice directly targets the central nervous system beyond thermogenic adipose tissues. Mol. Metab.55, 101405 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR48] 48.Kim K. et al. Uncoupling protein 1-driven Cre (Ucp1-Cre) is expressed in the epithelial cells of mammary glands and various non-adipose tissues. Mol. Metab.84, 101948 (2024). [DOI] [PMC free article] [PubMed]

[CR49] 49.Matsushita, N. et al. Highly selective transgene expression through the flip-excision switch system by using a unilateral spacer sequence. Cell Rep. Methods3, 100393 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR50] 50.Jalloul, W., Grierosu, I. C., Jalloul, D., Stefanescu, C. & Ghizdovat, V. Functional complexity of thermogenic adipose tissue: from thermogenesis to metabolic and fibroinflammatory crosstalk. Int. J. Mol. Sci.26, 9045 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR51] 51.Kashiwagi, E. Perirenal fat in disease progression: from inflammatory mediator to therapeutic target. Int. J. Urol.32, 1314–1320 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR52] 52.Wang, T. & He, C. Pro-inflammatory cytokines: the link between obesity and osteoarthritis. Cytokine Growth Factor Rev.44, 38–50 (2018). [DOI] [PubMed] [Google Scholar]

[CR53] 53.Sciarretta, F. et al. Lipocalin-2 promotes adipose-macrophage interactions to shape peripheral and central inflammatory responses in experimental autoimmune encephalomyelitis. Mol. Metab.76, 101783 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR54] 54.Kaesler, N. et al. Mapping cardiac remodeling in chronic kidney disease. Sci. Adv.9, eadj4846 (2023). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR55] 55.Lv, Z. et al. TRAIL induces podocyte PANoptosis via death receptor 5 in diabetic kidney disease. Kidney Int.107, 317–331 (2025). [DOI] [PubMed] [Google Scholar]

[CR56] 56.Speeckaert, M. M., Speeckaert, R., Laute, M., Vanholder, R. & Delanghe, J. R. Tumor necrosis factor receptors: biology and therapeutic potential in kidney diseases. Am. J. Nephrol.36, 261–270 (2012). [DOI] [PubMed] [Google Scholar]

[CR57] 57.Petersen, M. C. & Shulman, G. I. Mechanisms of insulin action and insulin resistance. Physiol. Rev.98, 2133–2223 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR58] 58.Xu, M., Hu, D., Liu, X., Li, Z. & Lu, L. Branched-chain amino acids and inflammation management in endurance sports: molecular mechanisms and practical implications. Nutrients17, 1335 (2025). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR59] 59.Patrick, M. et al. Metabolon formation regulates branched-chain amino acid oxidation and homeostasis. Nat. Metab.4, 1775–1791 (2022). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR60] 60.Jiang, H. et al. Branched-chain amino acids promote thrombocytopoiesis by activating mTOR signaling. J. Thromb. Haemost.21, 3224–3235 (2023). [DOI] [PubMed] [Google Scholar]

[CR61] 61.Lin, J. R. et al. Brown adipocyte ADRB3 mediates cardioprotection via suppressing exosomal iNOS. Circ. Res.131, 133–147 (2022). [DOI] [PubMed] [Google Scholar]

[CR62] 62.Kratky, D., Obrowsky, S., Kolb, D. & Radovic, B. Pleiotropic regulation of mitochondrial function by adipose triglyceride lipase-mediated lipolysis. Biochimie96, 106–112 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]

[CR63] 63.Mukherjee, S. & Yun, J. W. Prednisone stimulates white adipocyte browning via β₃-AR/p38 MAPK/ERK signaling pathway. Life Sci.288, 120204 (2022). [DOI] [PubMed] [Google Scholar]

[CR64] 64.Huang, Q. et al. Two novel functional single nucleotide polymorphisms of ADRB3 are associated with type 2 diabetes in the Chinese population. J. Clin. Endocrinol. Metab.98, E1272–E1277 (2013). [DOI] [PubMed] [Google Scholar]

PERMALINK

Perirenal fat β₃-adrenergic signaling alleviates renal fibrosis via regulating Bcat2/BCAA-TNFα pathway in diabetic kidney disease

Hongtu Hu

Rui Ji

Zikang Liu

Yuxin Ai

Shuiqin Gong

Mengying Yao

Wang Xin

Yuqi Zhu

Yinghui Huang

Abstract

Introduction

Results

Renal fibrosis is upregulated in DKD

PRF is significantly increased in DKD and associated with renal function

Fig. 1. PRF is increased in DKD and associates with renal dysfunction.

Removal of PRF significantly alleviated renal pathological damage and renal fibrosis in db/db mice

Fig. 2. Removal of PRF alleviates renal pathological injury and fibrosis in db/db mice.

ADRB3 expression is downregulated in PRF and associated with renal function

Fig. 3. ADRB3 expression is downregulated in PRF in diabetes and correlates with renal function.

Brown fat-specific knockout of ADRB3 increases PRF expansion in DKD

Fig. 4. Brown adipocyte-specific deletion of ADRB3 enlarges perirenal fat and increases TNFα secretion.

Knockout of ADRB3 in PRF aggravates renal pathological injury, metabolic stress, and fibrosis in DKD

Fig. 5. Brown adipocyte–specific loss of ADRB3 aggravates renal injury and fibrosis.

PRF-restricted restoration of ADRB3 is sufficient to ameliorate the renal phenotype

PRF-derived thermogenic adipocytes exhibit a distinct response to ADRB3 loss compared with interscapular BAT-derived thermogenic adipocytes

iBAT-restricted ADRB3 restoration corrects local iBAT dysfunction but does not reproduce PRF-dependent renal protection

Genetic ADRB3 overexpression in PRF mitigates PRF dysfunction and attenuates DKD renal injury

Pharmacological activation of ADRB3 attenuates renal pathological injury and renal fibrosis in DKD

Fig. 6. Activation of ADRB3 in PRF attenuates renal pathological injury and fibrosis in DKD.

ADRB1 is compensatorily upregulated in PRF of ADRB3-deficient mice, but ADRB1 overexpression does not phenocopy ADRB3 activation

Neutralization of TNFα alleviates renal pathological damage and renal fibrosis exacerbated by ADRB3 deficiency in PRF

Antioxidant treatment mitigates oxidative stress and partially rescues renal injury and fibrosis in ADRB3-deficient DKD mice

Knockout of ADRB3 in PRF enhances TNFα production in association with impaired BCAA catabolism

Fig. 7. Knockout of ADRB3 in PRF rewires branched-chain amino-acid (BCAA) metabolism and promotes TNF-α secretion.

BCAT2 links impaired BCAA metabolism to NF-κB activation and TNFα production in PRF adipocytes

ADRB3 deficiency reduces BCAT2 expression through CREB1/METTL3-mediated m6A modification

Fig. 8. CREB1 upregulates METTL3-mediated m6A to suppress BCAT2 translation in PRF adipocytes.

Discussion

Methods

Collection of human renal samples

Generation of brown fat ADRB3 knock-out mouse strain (ADRB3BKO)

DKD mouse models

Surgical removal of PRF

7T MRI for perirenal fat quantification

Anti-TNFα neutralization/isotype control in vivo

Isolation of primary adipocytes

Isolation of primary tubular cells (TECs)

Cell culture

Coculture of TECs and adipocytes

siRNA transfection

Plasmid overexpression transfection

Measurement of PRF by MRI in mice

Histology

Western blotting

Immunohistochemistry (IHC)

Immunofluorescence (IF) assay

Oil red O (ORO), dihydroethidium (DHE), succinate dehydrogenase (SDH) staining and ATP measurement

Single-cell transcriptomic sequencing and analysis

RNA sequencing and transcriptomic analysis

Targeted LC-MS/MS measurement of BCAAs

Quantitative real-time polymerase chain reaction (qPCR)

Luciferase reporter assay (LUC)

Chromatin immunoprecipitation-PCR (ChIP-PCR)

Biochemical measurements

Measurement of urinary albumin-to-creatinine ratio (UACR)

Measurement of triglyceride (TG) and total cholesterol (TCH)

Enzyme-linked immunosorbent assay (ELISA)

Oxygen consumption rate (OCR) measurement

m6A RNA immunoprecipitation (RIP) and quantification

O-propargyl-puromycin (OPP) labeling and streptavidin pulldown

Quantitative and statistical analyses

Reporting summary

Supplementary information

Source data

Acknowledgements

Author contributions

Peer review

Peer review information

Generation of brown fat ADRB3 knock-out mouse strain (ADRB3^BKO)