Expression and Mechanistic Insights into PDK4 in Hypertensive Renal Damage

Expression and Mechanistic Insights into PDK4 in Hypertensive Renal Damage | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Expression and Mechanistic Insights into PDK4 in Hypertensive Renal Damage zhen sun, yiming shao, yvhan bao, shuhua yv This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8443693/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background and Objective: Hypertensive renal damage (HRD) currently lacks effective early biomarkers and intervention targets. Pyruvate dehydrogenase kinase isozyme 4 (PDK4) plays well‑defined roles in various diseases, but its mechanism in HRD has not been systematically elucidated. This study aimed to explore the role of PDK4—a key molecule that has not been fully studied—in HRD by integrating bioinformatics analysis and experimental validation. Methods: ① Bioinformatics analysis was performed based on the GEO database (GSE37455) to screen differentially expressed genes and conduct functional enrichment analysis. ② Clinical serum samples from HRD patients were collected, and PDK4 levels were measured by ELISA to analyze their correlation with renal function indicators and diagnostic performance. ③ An injury model was established by stimulating human renal tubular epithelial cells (HK‑2) with Ang II, and PDK4 expression was detected. PDK4 was knocked down using lentivirus to evaluate its effects on oxidative stress (ROS) and epithelial‑mesenchymal transition (EMT). ④ RNA‑seq was performed on PDK4‑knockdown cells, and downstream signaling pathways were analyzed by enrichment analysis. Results: ① Bioinformatics analysis indicated that PDK4 is highly expressed in HRD, and related differentially expressed genes were enriched in pathways such as inflammation and apoptosis. ② Clinical samples showed that serum PDK4 expression was highest in the HRD group, negatively correlated with eGFR, and positively correlated with creatinine, urinary protein, etc. The ROC curve revealed an AUC of 0.982 for PDK4 in diagnosing HRD. ③ In cell experiments, Ang II induced upregulation of PDK4 expression, and its knockdown alleviated oxidative stress and EMT progression. ④ RNA‑seq analysis demonstrated that PDK4 knockdown affects pathways including inflammation, oxidative stress, and Wnt. Conclusion: PDK4 is highly expressed in HRD and promotes renal injury by regulating oxidative stress and fibrotic processes, suggesting its value as a potential biomarker and therapeutic target for HRD. This study provides the first systematic evidence of the high expression of PDK4 in HRD and its injury‑promoting mechanism, indicating that PDK4 may serve as a potential novel biomarker and therapeutic target. PDK4 Epithelial-mesenchymal transition Human renal tubular epithelial cells Hypertensive renal damage Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 1. Introduction HRD is regarded as one of the consequences of long-term poor blood pressure control and is the second leading cause of end-stage renal disease after diabetes [1] . Its pathogenesis includes oxidative stress, EMT, inflammation, podocyte injury, among others [2] , and the underlying mechanisms remain incompletely understood. Pyruvate dehydrogenase kinase isozyme 4 (PDK4) is a kinase that regulates glucose and fatty acid metabolism and homeostasis by phosphorylating the PDHA1 and PDHA2 subunits of pyruvate dehydrogenase. It can phosphorylate pyruvate dehydrogenase, thereby modulating aerobic respiration and linking the glycolytic pathway with the tricarboxylic acid cycle. As a key enzyme in energy regulation, it is involved in many pathophysiological processes in the human body [3, 4] . As a critical enzyme, PDK4 shows abnormal expression in various cardiovascular and renal diseases, affecting cellular and tissue energy metabolism, apoptosis, oxidative stress, ferroptosis, and inflammatory responses [5] . Previous research by scholar Khang et al. found that in streptozotocin-induced diabetic rats, ischemia-reperfusion injury increased PDK4 expression, accompanied by a significant rise in ROS expression and the production of related inflammatory molecules such as tumor necrosis factor-alpha (TNF-α). Both dichloroacetate and shPDK4 were able to alleviate the oxidative stress and inflammatory factor production caused by ischemia-reperfusion [6] . Nuclear factor erythroid 2-related factor 2 (Nrf2) and its inhibitor Kelch-like ECH-associated protein 1 (KEAP1) are key regulators of cellular antioxidant stress [7, 8] . Research by Forman et al. discovered that in HK-2 cells treated with high concentrations of glucose and palmitic acid, PDK4 upregulated KEAP1 expression by inhibiting autophagy, leading to the inactivation of Nrf2 [9] . Thus, PDK4 is involved in the development and progression of diabetic nephropathy. However, as a key regulator of energy metabolism, its specific role, expression pattern, and clinical significance in HRD have not been elucidated. To address this knowledge gap, the present study adopted an integrated research strategy: first, through bioinformatics mining of the public GEO database, PDK4 was screened and identified as a candidate key gene; second, functional validation of PDK4's differential expression and mechanism of action was performed in an in vitro HRD cell model; finally, its clinical relevance was explored by testing clinical serum samples. This closed-loop research approach, spanning from computational prediction to experimental validation and further to clinical evidence, aims to provide solid and multi‑dimensional evidence for the role of PDK4 in hypertensive renal damage. 2. Study Subjects, Material and Methods 2.1 Study Subjects: A total of 13 patients with hypertension accompanied by renal damage (HRD group), 13 patients with hypertension without renal damage (HT group), and 13 healthy individuals (control group) diagnosed and treated at Zhengzhou Central Hospital from March 2024 to March 2025 were selected as observation subjects. Inclusion criteria for the HRD group : ① Diagnosed with primary hypertension according to the Chinese Guidelines for Primary Hypertension Management [10] , with a disease duration of more than 5 years; ② Presence of persistent mild to moderate proteinuria; ③ Accompanied by hypertensive retinal arteriosclerotic changes; ④ Exclusion of primary and secondary renal diseases. Exclusion criteria : ① Acute coronary syndrome, stroke, or heart failure (NYHA class III–IV) within the past 3 months; ② Active infection, malignant tumor, or life expectancy < 1 year; ③ Other primary renal diseases (IgA nephropathy, diabetic nephropathy, polycystic kidney disease, etc.); ④ Pregnant or lactating women; ⑤ Use of systemic corticosteroids or immunosuppressants within the past 4 weeks; ⑥ Failure to provide signed informed consent. All procedures involving human participants in this study were conducted in accordance with the ethical standards of the Declaration of Helsinki. The study protocol was approved by the Ethics Committee of Zhengzhou Central Hospital (Approval No.: ZXYY2025182). Prior to inclusion in the study, the purpose, procedures, potential risks, and benefits were fully explained to all participants, and written informed consent was obtained from each participant. 2.2 Experimental Cells: Human renal tubular epithelial cells (HK-2), purchased from Procell, product number CL-0109. 2.3 Main Reagents: HK-2 cell-specific medium (Procell, product number CM-0109); Angiotensin II (MCE, product number HY-13948); PDK4 polyclonal antibody (Proteintech, product number BS71191); α-smooth muscle actin polyclonal antibody (Proteintech, product number 14395-1-AP-50ul); E-cadherin polyclonal antibody (Proteintech, product number 20874-1-AP-50ul); Vimentin polyclonal antibody (Proteintech, product number 10366-1-AP-50ul); GAPDH Mouse Monoclonal Antibody (Bioworld, product number AP0063); NovoScript Plus All-in-one 1st Strand cDNA Synthesis SuperMix (Novoprotein, product number E047-01B); NovoStart SYBR qPCR SuperMix Plus (Novoprotein, product number E096-01A). The PDK4 enzyme-linked immunosorbent assay (ELISA) kit was purchased from Jiangsu Enzyme Immunity Industrial Co., Ltd. 2.4 Interference Fragments and Primers siRNA-PDK4 and siRNA-NC transfection lentiviruses were purchased from Shanghai GenePharma Co., Ltd. qRT-PCR primers were synthesized by Sangon Biotech (Shanghai) Co., Ltd. The sequences are as follows: Name F/R Sequence (5'-3') Human-PDK4 F AGACAGGAAACCCAAGCCAC Human-PDK4 R GGCATCTTGGACCACTGCTA Human-Actin F GGTAACATTGTGCTCAGTGGTGG Human-Actin R AACGACCTTAATCTTCATGCTGC 2.5 Detection of PDK4 Expression in Patient Serum by ELISA Fasting antecubital venous blood (1.5–2 ml) was collected from patients and centrifuged at 3000 rpm for 10 minutes. The serum was separated, labeled, and stored at − 80°C. The concentration of PDK4 in the serum was measured using an enzyme-linked immunosorbent assay (ELISA), and all procedures were strictly followed according to the manufacturer's instructions of the ELISA kit. 2.6 Cell Culture HK-2 cells were cultured in MEM medium supplemented with 10% fetal bovine serum, 100 U/mL penicillin, and 100 U/mL streptomycin, and incubated at 37°C with 5% CO₂. Cells from passages 4 to 8 were used for the experiments. 2.7 Detection of RNA Expression Levels by qPCR After treatment, HK-2 cells were collected, and the supernatant was discarded. The cells were lysed with 1 mL of TRIzol reagent on ice for 10–15 minutes, followed by total RNA extraction and reverse transcription into cDNA. The obtained cDNA was used for qPCR reactions. The reaction conditions were as follows: 95°C for 1 minute; followed by 35–45 cycles of 95°C for 20 seconds and 60°C for 1 minute. This two-step protocol ensured high amplification specificity. Raw data were obtained, and the mRNA expression level of PDK4 was calculated using the 2⁻ΔΔCt method. 2.8 Western Blotting (WB) Detection of Protein Expression Levels HK-2 cells from each group were lysed using RIPA lysis buffer containing a protease inhibitor cocktail (1:100) and a phosphatase inhibitor cocktail (1:100) to extract proteins. Protein concentration was determined using the BCA method. Proteins were separated by electrophoresis on a 12.5% separation gel under constant voltage (120V) for approximately 1.5 hours until the bromophenol blue reached the bottom of the gel, and then transferred to a PVDF membrane under constant current (300mA) for 120 minutes. The membrane was blocked with 5% skimmed milk at room temperature on a shaker for 1 hour, followed by overnight incubation with the primary antibody at 4°C. Subsequently, the membrane was incubated with the secondary antibody at room temperature on a shaker for 2 hours. The membrane was washed with TBST. Immunoblot signals were developed using an ECL detection reagent, and the grayscale values of the target bands were quantified using ImageJ software. 2.9 Flow Cytometry Detection of Cellular Oxidative Stress (ROS) Levels Cells were seeded in plates at a density of < 5×10⁵ cells per milliliter. The six-well plates were divided into the following groups: control group (Con), NC-PDK4 + AngII group, and sh-PDK4 + AngII group. All procedures were strictly performed according to the instructions of the ROS detection kit. Finally, the cells were trypsinized to prepare a single‑cell suspension, resuspended in 0.5–1 mL of PBS, and analyzed by flow cytometry. 2.10 Bioinformatics Analysis The dataset GSE37455 was obtained from the GEO database, which includes 20 cases of hypertensive nephropathy kidney tissue samples and 21 cases of normal human kidney tissue samples. Differential gene expression analysis was performed using the limma package in R. The differentially expressed genes (DEGs) were subjected to Gene Ontology (GO) analysis to identify significant functional terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to identify significant pathways. 2.11 Transcriptome Sequencing (RNA-seq) HK‑2 cells were divided into two groups and transfected with NC‑PDK4 or sh‑PDK4 using lentiviral technology. When cell density reached approximately 90%, the cells were digested, centrifuged, and resuspended in 1 mL of TRIzol for transcriptome sequencing. Differential gene expression analysis was performed on the two groups (each containing two biological replicates) using the limma package in R. Genes meeting the criteria of |log₂(fold change)| > 1 and adjusted p‑value < 0.05 were identified as differentially expressed genes (DEGs). GO and KEGG pathway enrichment analyses were performed on the DEGs and visualized. Terms with an adjusted p‑value < 0.05 were defined as significantly enriched items for the DEGs. 2.12 Statistical Analysis Statistical analysis and graphing were performed using SPSS 22.0 and GraphPad Prism 10.1.2 software. The chi‑square test was used to compare gender ratios between groups. Measurement data are presented as mean ± standard deviation. Differences between two groups were compared using the independent samples t‑test. Comparisons among three or more groups were analyzed by one‑way ANOVA, with inter‑group differences assessed by the least significant difference (LSD) t‑test. A P‑value < 0.05 was considered statistically significant. 3. Results 3.1 Bioinformatics Analysis Suggests PDK4 as a Core Gene in HRD To screen for potential diagnostic biomarkers associated with HRD, we performed differential expression analysis on the gene expression profile data from the GSE37455 dataset in the GEO database. A total of 27 DEGs were obtained, among which 16 genes were upregulated and 11 genes were downregulated. A volcano plot was generated (as shown in Fig. 1 A), and a protein‑protein interaction (PPI) network was constructed. The circular plot (as shown in Fig. 1 B) illustrates the connections and complex interaction relationships among these differentially expressed genes, suggesting that PDK4 is a core gene in HRD. GO functional enrichment analysis is divided into biological processes, cellular components, and molecular functions. The results obtained (as shown in Fig. 1 C) indicate that these DEGs are associated with various pathophysiological processes such as endothelial cell differentiation, renal cell infiltration, multi-organism immunity, oxidative stress, and inflammation, suggesting that the pathogenesis of HRD may be related to the aforementioned processes. KEGG functional enrichment analysis (as shown in Fig. 1 D) reveals that these DEGs are enriched in related signaling pathways such as IL‑17, MAPK, tumor necrosis factor (TNF), apoptosis, and inflammation, indicating that the pathogenesis of HRD is associated with the above A: Volcano plot of DEGs. B: Protein-protein interaction analysis results of the screened key genes, where blue dots represent downregulated genes and red dots represent upregulated genes. C: GO functional enrichment analysis. D: KEGG functional enrichment analysis. 3.2 AngII Upregulates PDK4 Expression in HK‑2 Cells To verify the hypothesis derived from bioinformatics analysis that PDK4 expression is elevated, we conducted the following in vitro experiments:Fig. 2 A shows the results of cell viability detected by CCK‑8. Under the effect of AngII at a concentration of 1×10⁻⁶ M, the cell survival rate decreased most significantly; therefore, this concentration was selected as the optimal modeling concentration for HRD in subsequent experiments. HK‑2 cells were divided into two groups: the experimental group was treated with 1×10⁻⁶ M AngII for 48 h, and the control group received no treatment. The mRNA expression of PDK4 in each group was detected by qPCR, and the results are shown in Fig. 2 B. AngII significantly increased the mRNA expression of PDK4. The protein expression levels of PDK4 in the two groups were detected by Western blot (WB), and the results are shown in Fig. 2 C and 2 D. AngII also significantly elevated the protein expression level of PDK4. All the above differences were statistically significant .(P < 0.05). A: CCK‑8 assay results showing the most pronounced effect of 1×10⁻⁶ M AngII. B: Relative mRNA expression level of PDK4. C, D: Immunoblot images and quantitative analysisresults of PDK4 and GAPDH protein expression. 3.3 Lentiviral technology was used to knock down PDK4 expression HK-2 cells were transfected with lentiviral particles, divided into NC‑PDK4 and sh‑PDK4 groups. After 72 h of transfection, observation under an inverted fluorescence microscope with blue-light excitation showed that green fluorescence covered almost the entire field of view (as shown in Fig. 3A), indicating a transfection efficiency exceeding 90%. Western blot (WB) was used to detect PDK4 protein expression levels in the two groups to evaluate knockdown efficiency. The results (Fig. 3B) showed a significant decrease in protein expression in the sh‑PDK4 group, confirming successful transfection of HK-2 cells and meeting the efficiency requirements for subsequent experiments (P < 0.05). Fig. 3 Lentiviral Transfection A: The results of inverted fluorescence microscopy. The left side shows normal HK-2 cells, and the right side shows HK-2 cells after lentiviral transfection. B: The immunoblot results and quantitative analysis of PDK4 and GAPDH protein expression after transfection. 3.4 Knockdown of PDK4 Reduces HRD Oxidative Stress and EMT Levels To investigate whether PDK4 is involved in the pathological and physiological process of ROS generation, HK-2 cells were divided into three groups, as shown in Fig. 4 A. The results, shown in Fig. 4 A, indicate that after AngII induction, the ROS levels in HK-2 cells increased. However, knockdown of PDK4 reversed this effect, with a statistically significant difference (P < 0.05), suggesting that PDK4 may be involved in the occurrence and development of ROS generation in HRD. To investigate whether PDK4 is involved in the EMT process of HRD, HK-2 cells were divided into three groups: control group, AngII group, and sh-PDK4 + AngII group. WB was used to detect the protein expression levels of α-SMA, vimentin, and E-cadherin in the three groups. The results, shown in Fig. 4 B, indicate that AngII upregulated the expression of α-SMA and vimentin and downregulated the expression of E-cadherin in HK-2 cells. However, knockdown of PDK4 reversed these effects, thereby reversing the EMT process and alleviating the fibrosis level in HK-2 cells. (P < 0.05) A: Flow cytometry results and quantitative analysis. B: Immunoblot results and quantitative analysis of α-SMA, vimentin, and E-cadherin protein expression. 3.5 PDK4 RNA-seq To explore the signaling pathways associated with PDK4 and predict its mechanism in HRD, we performed transcriptome sequencing. HK-2 cells were divided into two groups and transfected with NC-PDK4 and sh-PDK4 using lentivirus, followed by RNA-seq. The results are shown in Fig. 5A shows a volcano plot of DEGs, with log2(Fold Change) on the x-axis and -log10(P-value) on the y-axis. Red points represent upregulated genes, and blue points represent downregulated genes. The DEGs were subjected to GO and KEGG functional enrichment analysis to explore related signaling pathways and mechanisms. The GO analysis results, shown in Fig. 5B, suggest that DEGs are mainly involved in signaling pathways related to metabolism, immunity, apoptosis, extracellular matrix synthesis, fibrosis, inflammation, cell migration, and adhesion. The KEGG analysis, shown in Fig. 5C, reveals that DEGs are primarily enriched in pathological processes such as diabetic cardiomyopathy, insulin secretion, ferroptosis, cell adhesion, and complement activation. Additionally, significant associations were found with the classical cancer signaling pathway Wnt [11] and the cardiopulmonary function metabolism signaling pathway Apelin [12, 13] . Fig. 5 RNA-seq A: DEGs analysis of the NC-PDK4 group and sh-PDK4 group.B: GO functional enrichment analysis.C: KEGG functional enrichment analysis. 3.6 Detection of PDK4 Expression in Serum by ELISA To further translate the research findings toward clinical relevance, we measured serum PDK4 levels in patients. The results showed a significant positive correlation between its levels and disease severity. Notably, this clinical trend closely aligns with the conclusions of upregulated expression/function derived from both bioinformatics analysis and cell experiments, forming a mutually corroborating chain of evidence. Patient serum was collected, and PDK4 expression levels in serum (in pg/mL) were measured by ELISA, with statistically significant differences observed among all groups (P < 0.05). As shown in Fig. 6 , serum PDK4 in the healthy control group (157.61 ± 5.37 pg/mL) was significantly lower than that in the hypertension without renal damage group (HT group: 204.23 ± 4.43 pg/mL) and the hypertensive renal damage group (HRD group: 242.65 ± 4.64 pg/mL). The mean values among the three groups showed statistically significant differences (F = 77.71, P < 0.05), and the scatter plot displays the data distribution for each group. No significant differences were found among the three groups in gender, age, BMI, or blood lipids (as shown in Table 1 , t-values = 0.659, 0.650, 0.364, 0.344, 0.656, 0.789, 2.308, P > 0.05). As shown in Table 2 , PDK4 correlated with estimated glomerular filtration rate (eGFR), serum creatinine (Scr), 24-hour urinary microalbumin (mg/24h), and duration of hypertension (years). It was negatively correlated with eGFR and positively correlated with Scr, 24-hour urinary microalbumin, and duration of hypertension (years), indicating that PDK4 holds certain value in predicting patients' renal function and extent of damage. Table 3 suggests that PDK4 has high diagnostic value for HRD, with an area under the ROC curve (AUC) of 0.982, as shown in Fig. 7 , and a significance level of P < 0.05. Using the presence or absence of hypertensive renal damage (HRD) as the dependent variable and PDK4 expression level as a covariate, binary logistic regression analysis was performed to assess the relative risk (OR value) of PDK4 expression level. The OR value was 1.216, as shown in Table 4 , meaning that for each one-unit increase in PDK4 expression level, the risk of developing HRD increases by 21.6% (P HT group (204.23 ± 4.43 pg/mL) > control group (157.61 ± 5.37 pg/mL), with statistically significant differences among the groups (P 0.05 Gender 0.834 P > 0.05 Bmi 0.364 P > 0.05 LDL-C 0.344 P > 0.05 Total cholesterol 0.656 P > 0.05 Triglycerides 0.789 P > 0.05 HDL-C 2.308 P > 0.05 Table 2 Correlation Coefficients between PDK4 Expression Levels and HRD Indicators Item Correlation Coefficient Significance eGFR -0.571 P < 0.05 UA 0.255 P = 0.117 Scr 0.514 P < 0.05 24‑h urine protein (mg/24h) 0.269 P = 0.097 24‑h urinary microalbumin (mg/24h) 0.322 P < 0.05 Duration of hypertension (years) 0.664 P < 0.05 Table 3 Diagnostic Value of PDK4 AUC(95%CI) Youden's index Cut‑off value Sensitivity (%) Specificity (%) Hypertensive renal damage 0.982(0.950 ~ 1.000) 0.923 219.6(pg/ml) 100 92.3 Table 4 Relative Risk (OR Value) of PDK4 Significance OR Value 95% CI for OR Value PDK4 Expression Level P < 0.05 1.216 (1.020 ~ 1.450) 4. Discussion As a critical mitochondrial enzyme [14] , PDK4 plays a complex role in diabetic renal damage. Zhao et al. found that knocking down PDK4 in high‑glucose‑induced podocytes suppressed the expression of inflammatory factors (IL‑1β, IL‑6, TNF‑α) and reduced apoptosis [15] . Additionally, research by Tian et al. suggested that inhibiting PDK4 in HK‑2 cells and mouse models may enhance antioxidant capacity and improve iron metabolism by activating the Nrf2 pathway, thereby alleviating oxidative stress and ferroptosis [16] . PDK4 is also involved in other renal injury processes. One study, through bioinformatics and experimental validation, confirmed that PDK4 is a potential diagnostic gene for membranous nephropathy, and its expression is closely associated with ferroptosis and immune cell infiltration [17] . Diabetes and hypertension are the two leading causes of chronic kidney disease [18] . However, the role of PDK4 in hypertensive renal damage (HRD) remains incompletely understood. This study explored the expression pattern, clinical significance, and potential mechanism of PDK4 in HRD, providing preliminary evidence for the diagnosis and treatment of HRD. Bioinformatics analysis revealed that PDK4 is a core differentially expressed gene in HRD. Subsequently, in vitro cell experiments confirmed that PDK4 is highly expressed in the HRD cell model, and knockdown of PDK4 alleviated HK‑2 cell injury (e.g., EMT, ROS). Importantly, differential expression of PDK4 was observed in the serum of HRD patients, and its expression increased with the severity of injury. PDK4 protein levels showed a significant positive correlation with renal function impairment indicators. This tripartite evidence collectively establishes the key role of PDK4. Subsequent RNA‑seq also predicted the mechanism of action of PDK4, providing a theoretical basis for future research. HRD is characterized by worsening renal function and renal fibrosis [19] . Under hypertensive conditions, activation of the local renal renin-angiotensin system leads to elevated angiotensin II (Ang II) levels and epithelial-mesenchymal transition (EMT) [20] . Renal epithelial cells dedifferentiate into fibroblast-like phenotypes, accompanied by loss of the epithelial-specific marker E-cadherin, acquisition of mesenchymal markers such as α-smooth muscle actin (α-SMA) and vimentin, and excessive deposition of extracellular matrix, ultimately resulting in renal tubulointerstitial fibrosis [21–23] . Related studies also suggest that the pathogenesis of HRD primarily involves activation of the renin-angiotensin system (RAS), leading to afferent arteriole contraction, ischemic glomerular injury, and activation of reactive oxygen species (ROS) among others [24] . Long-term poorly controlled hypertension damages renal tubular cells, thereby promoting EMT and renal interstitial fibrosis [25] . Consistent with the findings from bioinformatics analysis, this study observed in the in vitro HRD HK‑2 cell model that AngII induction aggravated ROS levels and EMT in HK‑2 cells, whereas lentiviral transfection‑mediated knockdown of PDK4 alleviated these AngII‑induced damaging effects. These results suggest that knocking down PDK4 can significantly inhibit AngII‑induced ROS and EMT. Future research may further examine the expression levels of classic renal fibrosis markers [26] , such as Collagen I and Fibronectin. Moreover, numerous studies have shown that ROS and inflammatory responses mutually reinforce each other in renal injury, forming a vicious cycle [27, 28] . Therefore, future studies should still investigate whether PDK4 also regulates inflammatory signaling pathways, such as by detecting the secretion levels of key inflammatory factors (e.g., IL‑6, IL‑1β, TNF‑α) and the activation of classic inflammatory signaling pathways like NF‑κB [29, 30] . This will more firmly establish the value of PDK4 as a therapeutic target.Although this study confirmed the effects of PDK4 on ROS and EMT in renal tubular epithelial cells, these findings have not yet been validated in in vivo models, such as spontaneously hypertensive rats (SHR). Given that the internal environment is influenced by various complex factors including hemodynamics and endocrine regulation, the precise pathogenic role of PDK4 in vivo and the therapeutic effects of targeting PDK4 inhibition will be the focus of future research. Analysis of clinical data confirms that PDK4 is not only significantly correlated with key renal function indicators but also serves as an independent risk factor for the disease (OR > 1) and demonstrates good diagnostic performance. These findings, together with results from bioinformatics analysis, serum tests, and cell experiments, consistently show upregulation of PDK4 in HRD, supporting its potential as a diagnostic biomarker for HRD. However, the sample size for clinical validation is relatively small and derived from a single center, which may lead to selection bias to some extent. Although the inter-group differences and diagnostic efficacy of PDK4 in this study are statistically significant, its reliability as a biomarker still requires further validation in multi-center, large-scale prospective cohorts to obtain more universal clinical data. PDK4 is a key regulator of energy metabolism. It phosphorylates and inhibits the activity of pyruvate dehydrogenase (PDH), thereby reducing acetyl‑CoA generation, which modulates the tricarboxylic acid cycle and suppresses aerobic respiration [31–34] . The PDK isoforms exhibit tissue‑specific expression patterns: PDK1 and PDK4 are highly expressed in heart, pancreatic islets, and skeletal muscle; PDK3 is mainly present in testis, brain, and kidney; while PDK2 appears to be widely expressed in many tissues [35] . In vitro cell experiments indicated that PDK4 is involved in the biological processes of EMT and ROS. Building on this, to further explore its specific mechanism of action, we performed RNA‑seq analysis. The results showed that the DEGs caused by PDK4 knockdown were primarily enriched in pathways related to metabolism, apoptosis, ferroptosis, and cardiopulmonary function. This suggests that PDK4 may influence EMT and ROS generation by regulating these pathways. Of course, these remain predictive hypotheses that require further experimental validation. 5. Conclusion This study employed bioinformatics analysis, RNA-seq, and experimental validation to investigate the role of PDK4 in HRD. The results indicate that PDK4 may be a key promoting factor in HRD progression, and intervention strategies targeting PDK4 could provide new theoretical foundations and potential therapeutic targets for the clinical management of HRD.Although this study provides preliminary evidence for the role of PDK4 in HRD, several limitations remain. First, due to the limited clinical sample size, the diagnostic thresholds and stability of PDK4 require further refinement in larger population cohorts. Second, this study is currently confined to in vitro cellular experiments and lacks in-depth confirmation of phenotypes and signaling pathways through in vivo animal studies. The complex microenvironment in vivo will be a primary objective for our future investigations. In summary, current research on PDK4 in kidney diseases has largely focused on diabetic nephropathy or other forms of renal injury, while its specific role in HRD remains incompletely understood. This study provides a relatively systematic characterization of PDK4's role in HRD by integrating bioinformatics, in vitro experiments, and clinical sample analysis.The most prominent strength of this study lies in its multi‑level, mutually validating research strategy. Bioinformatics analysis provided preliminary screening and theoretical evidence; cell experiments, consistent with the bioinformatics results, established direct relationships; and finally, clinical serum testing confirmed its potential translational and clinical application value. The consistency of results across these three levels significantly enhances the reliability and persuasiveness of the conclusions, avoiding the limitations of any single research method. In this study, bioinformatics analysis identified PDK4 as a potential biomarker for HRD, with its expression and diagnostic value subsequently validated through clinical data and cellular models. Furthermore, RNA-seq was employed to predict its underlying mechanisms. This research preliminarily explores the expression patterns, clinical significance, and potential mechanisms of PDK4 in HRD, providing supplementary evidence for the role of this gene in specific renal pathologies and suggesting that PDK4 represents a promising target with clinical application potential. Declarations Ethics Approval and Informed Consent Ethics approval and consent to participate This study was approved by the Medical Ethics Committee of Zhengzhou Central Hospital (Approval No. ZXYY2025182). Informed consent was obtained from all individual participants included in the study. Consent for Publication Consent for publication Not applicable. 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Supplementary Files GelsBlots.zip Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 19 Feb, 2026 Reviewers agreed at journal 11 Feb, 2026 Reviews received at journal 23 Jan, 2026 Reviewers agreed at journal 22 Jan, 2026 Reviewers agreed at journal 20 Jan, 2026 Reviewers invited by journal 05 Jan, 2026 Editor assigned by journal 05 Jan, 2026 Editor invited by journal 05 Jan, 2026 Submission checks completed at journal 02 Jan, 2026 First submitted to journal 02 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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13:36:21","extension":"png","order_by":43,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":40347,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-8443693/v1/e2ff33f6ed07e3f9abe480fb.png"},{"id":99793828,"identity":"3e831c14-bc00-4f8b-b00a-e14fd1b61569","added_by":"auto","created_at":"2026-01-08 13:32:30","extension":"xml","order_by":44,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":64900,"visible":true,"origin":"","legend":"","description":"","filename":"dc830c03501f4958870a01da1f9efdb61structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8443693/v1/f8d4e25593b5ec0623c4e3e6.xml"},{"id":99794537,"identity":"0ab103d9-625a-4878-a68b-b2a21b45f066","added_by":"auto","created_at":"2026-01-08 13:35:18","extension":"html","order_by":45,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":66977,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8443693/v1/03b5a7bfa05af2d94b3b8852.html"},{"id":99623060,"identity":"44c38114-6ce2-4afc-a6bd-b07aef11d240","added_by":"auto","created_at":"2026-01-06 14:35:45","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":410172,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBioinformatics Analysis of HRD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA: Volcano plot of DEGs. B: Protein-protein interaction analysis results of the screened key genes, where blue dots represent downregulated genes and red dots represent upregulated genes. C: GO functional enrichment analysis. D: KEGG functional enrichment analysis.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8443693/v1/97075092c607a5496326d3c1.jpg"},{"id":99793273,"identity":"34037e4a-43d3-44bc-abaf-2f613df1877f","added_by":"auto","created_at":"2026-01-08 13:31:18","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":12418890,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression of PDK4 in HK‑2 Cells\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA: CCK‑8 assay results showing the most pronounced effect of 1×10⁻⁶ M AngII. B: Relative mRNA expression level of PDK4. C, D: Immunoblot images and quantitative analysisresults of PDK4 and GAPDH protein expression.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig.2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8443693/v1/fe44163667055e8b3647d569.jpg"},{"id":99793223,"identity":"05b8239a-055b-4430-a3ea-8dd713cc6b62","added_by":"auto","created_at":"2026-01-08 13:31:12","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":20116895,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLentiviral Transfection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA: The results of inverted fluorescence microscopy. The left side shows normal HK-2 cells, and the right side shows HK-2 cells after lentiviral transfection. B: The immunoblot results and quantitative analysis of PDK4 and GAPDH protein expression after transfection.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig.3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8443693/v1/752dd472d4ac1e6906eb85dc.jpg"},{"id":99793758,"identity":"fa615a8c-fedc-44be-ac9f-be1266cc69ae","added_by":"auto","created_at":"2026-01-08 13:32:19","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":19692481,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eExpression Levels of ROS and EMT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA: Flow cytometry results and quantitative analysis. B: Immunoblot results and quantitative analysis of α-SMA, vimentin, and E-cadherin protein expression.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig.4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8443693/v1/1655bb3217c37670b65f54ed.jpg"},{"id":99793272,"identity":"cb6b794d-9199-4f08-8a86-50fb43102f25","added_by":"auto","created_at":"2026-01-08 13:31:18","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":19958937,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRNA-seq\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA: DEGs analysis of the NC-PDK4 group and sh-PDK4 group.B: GO functional enrichment analysis.C: KEGG functional enrichment analysis.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig.5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8443693/v1/411b13608feb40473c31b77b.jpg"},{"id":99623062,"identity":"7d38f512-4768-466a-94c3-83e4e6f800d0","added_by":"auto","created_at":"2026-01-06 14:35:45","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":573926,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eELISA results of serum detection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePDK4 expression level: HRD group (242.65 ± 4.64 pg/mL) \u0026gt; HT group (204.23 ± 4.43 pg/mL) \u0026gt; control group (157.61 ± 5.37 pg/mL), with statistically significant differences among the groups (P \u0026lt; 0.05).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig.6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8443693/v1/78a37744a8d9113560d0ee2b.jpg"},{"id":99793586,"identity":"8bb9c26b-5a5f-41fe-9c64-ce7fcb9f8563","added_by":"auto","created_at":"2026-01-08 13:31:54","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":2532292,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC Curve Analysis of the Diagnostic Value of PDK4\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Fig.7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8443693/v1/5bb0b2337ae1b32baebb51b7.jpg"},{"id":99804817,"identity":"2eee855a-5b60-4413-a614-4d5ebdcf6eb2","added_by":"auto","created_at":"2026-01-08 14:14:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":77057787,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8443693/v1/5ef22889-5b4f-4cb9-9c07-4c9346bfaf08.pdf"},{"id":99623064,"identity":"e5c8445d-90f8-434e-83e0-f1d5c8368427","added_by":"auto","created_at":"2026-01-06 14:35:45","extension":"zip","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":2662705,"visible":true,"origin":"","legend":"","description":"","filename":"GelsBlots.zip","url":"https://assets-eu.researchsquare.com/files/rs-8443693/v1/0c71fa1699f9edec79cfc256.zip"}],"financialInterests":"No competing interests reported.","formattedTitle":"Expression and Mechanistic Insights into PDK4 in Hypertensive Renal Damage","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eHRD is regarded as one of the consequences of long-term poor blood pressure control and is the second leading cause of end-stage renal disease after diabetes\u003csup\u003e[1]\u003c/sup\u003e. Its pathogenesis includes oxidative stress, EMT, inflammation, podocyte injury, among others \u003csup\u003e[2]\u003c/sup\u003e, and the underlying mechanisms remain incompletely understood.\u003c/p\u003e \u003cp\u003ePyruvate dehydrogenase kinase isozyme 4 (PDK4) is a kinase that regulates glucose and fatty acid metabolism and homeostasis by phosphorylating the PDHA1 and PDHA2 subunits of pyruvate dehydrogenase. It can phosphorylate pyruvate dehydrogenase, thereby modulating aerobic respiration and linking the glycolytic pathway with the tricarboxylic acid cycle. As a key enzyme in energy regulation, it is involved in many pathophysiological processes in the human body \u003csup\u003e[3, 4]\u003c/sup\u003e. As a critical enzyme, PDK4 shows abnormal expression in various cardiovascular and renal diseases, affecting cellular and tissue energy metabolism, apoptosis, oxidative stress, ferroptosis, and inflammatory responses \u003csup\u003e[5]\u003c/sup\u003e. Previous research by scholar Khang et al. found that in streptozotocin-induced diabetic rats, ischemia-reperfusion injury increased PDK4 expression, accompanied by a significant rise in ROS expression and the production of related inflammatory molecules such as tumor necrosis factor-alpha (TNF-α). Both dichloroacetate and shPDK4 were able to alleviate the oxidative stress and inflammatory factor production caused by ischemia-reperfusion \u003csup\u003e[6]\u003c/sup\u003e. Nuclear factor erythroid 2-related factor 2 (Nrf2) and its inhibitor Kelch-like ECH-associated protein 1 (KEAP1) are key regulators of cellular antioxidant stress \u003csup\u003e[7, 8]\u003c/sup\u003e. Research by Forman et al. discovered that in HK-2 cells treated with high concentrations of glucose and palmitic acid, PDK4 upregulated KEAP1 expression by inhibiting autophagy, leading to the inactivation of Nrf2 \u003csup\u003e[9]\u003c/sup\u003e. Thus, PDK4 is involved in the development and progression of diabetic nephropathy. However, as a key regulator of energy metabolism, its specific role, expression pattern, and clinical significance in HRD have not been elucidated.\u003c/p\u003e \u003cp\u003eTo address this knowledge gap, the present study adopted an integrated research strategy: first, through bioinformatics mining of the public GEO database, PDK4 was screened and identified as a candidate key gene; second, functional validation of PDK4's differential expression and mechanism of action was performed in an in vitro HRD cell model; finally, its clinical relevance was explored by testing clinical serum samples. This closed-loop research approach, spanning from computational prediction to experimental validation and further to clinical evidence, aims to provide solid and multi‑dimensional evidence for the role of PDK4 in hypertensive renal damage.\u003c/p\u003e"},{"header":"2. Study Subjects, Material and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Subjects:\u003c/h2\u003e \u003cp\u003eA total of 13 patients with hypertension accompanied by renal damage (HRD group), 13 patients with hypertension without renal damage (HT group), and 13 healthy individuals (control group) diagnosed and treated at Zhengzhou Central Hospital from March 2024 to March 2025 were selected as observation subjects.\u003c/p\u003e \u003cp\u003e \u003cem\u003eInclusion criteria for the HRD group\u003c/em\u003e:\u003c/p\u003e \u003cp\u003e① Diagnosed with primary hypertension according to the Chinese Guidelines for Primary Hypertension Management \u003csup\u003e[10]\u003c/sup\u003e, with a disease duration of more than 5 years; ② Presence of persistent mild to moderate proteinuria; ③ Accompanied by hypertensive retinal arteriosclerotic changes; ④ Exclusion of primary and secondary renal diseases.\u003c/p\u003e \u003cp\u003e \u003cem\u003eExclusion criteria\u003c/em\u003e:\u003c/p\u003e \u003cp\u003e① Acute coronary syndrome, stroke, or heart failure (NYHA class III\u0026ndash;IV) within the past 3 months; ② Active infection, malignant tumor, or life expectancy\u0026thinsp;\u0026lt;\u0026thinsp;1 year; ③ Other primary renal diseases (IgA nephropathy, diabetic nephropathy, polycystic kidney disease, etc.); ④ Pregnant or lactating women; ⑤ Use of systemic corticosteroids or immunosuppressants within the past 4 weeks; ⑥ Failure to provide signed informed consent.\u003c/p\u003e \u003cp\u003e All procedures involving human participants in this study were conducted in accordance with the ethical standards of the Declaration of Helsinki. The study protocol was approved by the Ethics Committee of Zhengzhou Central Hospital (Approval No.: ZXYY2025182). Prior to inclusion in the study, the purpose, procedures, potential risks, and benefits were fully explained to all participants, and written informed consent was obtained from each participant.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Experimental Cells:\u003c/h2\u003e \u003cp\u003eHuman renal tubular epithelial cells (HK-2), purchased from Procell, product number CL-0109.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Main Reagents:\u003c/h2\u003e \u003cp\u003eHK-2 cell-specific medium (Procell, product number CM-0109); Angiotensin II (MCE, product number HY-13948); PDK4 polyclonal antibody (Proteintech, product number BS71191); α-smooth muscle actin polyclonal antibody (Proteintech, product number 14395-1-AP-50ul); E-cadherin polyclonal antibody (Proteintech, product number 20874-1-AP-50ul); Vimentin polyclonal antibody (Proteintech, product number 10366-1-AP-50ul); GAPDH Mouse Monoclonal Antibody (Bioworld, product number AP0063); NovoScript Plus All-in-one 1st Strand cDNA Synthesis SuperMix (Novoprotein, product number E047-01B); NovoStart SYBR qPCR SuperMix Plus (Novoprotein, product number E096-01A). The PDK4 enzyme-linked immunosorbent assay (ELISA) kit was purchased from Jiangsu Enzyme Immunity Industrial Co., Ltd.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Interference Fragments and Primers\u003c/h2\u003e \u003cp\u003esiRNA-PDK4 and siRNA-NC transfection lentiviruses were purchased from Shanghai GenePharma Co., Ltd. qRT-PCR primers were synthesized by Sangon Biotech (Shanghai) Co., Ltd. The sequences are as follows:\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eName\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF/R\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSequence (5'-3')\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman-PDK4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAGACAGGAAACCCAAGCCAC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman-PDK4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGCATCTTGGACCACTGCTA\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman-Actin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGGTAACATTGTGCTCAGTGGTGG\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHuman-Actin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAACGACCTTAATCTTCATGCTGC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Detection of PDK4 Expression in Patient Serum by ELISA\u003c/h2\u003e \u003cp\u003eFasting antecubital venous blood (1.5\u0026ndash;2 ml) was collected from patients and centrifuged at 3000 rpm for 10 minutes. The serum was separated, labeled, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C. The concentration of PDK4 in the serum was measured using an enzyme-linked immunosorbent assay (ELISA), and all procedures were strictly followed according to the manufacturer's instructions of the ELISA kit.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Cell Culture\u003c/h2\u003e \u003cp\u003eHK-2 cells were cultured in MEM medium supplemented with 10% fetal bovine serum, 100 U/mL penicillin, and 100 U/mL streptomycin, and incubated at 37\u0026deg;C with 5% CO₂. Cells from passages 4 to 8 were used for the experiments.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Detection of RNA Expression Levels by qPCR\u003c/h2\u003e \u003cp\u003eAfter treatment, HK-2 cells were collected, and the supernatant was discarded. The cells were lysed with 1 mL of TRIzol reagent on ice for 10\u0026ndash;15 minutes, followed by total RNA extraction and reverse transcription into cDNA. The obtained cDNA was used for qPCR reactions. The reaction conditions were as follows: 95\u0026deg;C for 1 minute; followed by 35\u0026ndash;45 cycles of 95\u0026deg;C for 20 seconds and 60\u0026deg;C for 1 minute. This two-step protocol ensured high amplification specificity. Raw data were obtained, and the mRNA expression level of PDK4 was calculated using the 2⁻ΔΔCt method.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Western Blotting (WB) Detection of Protein Expression Levels\u003c/h2\u003e \u003cp\u003eHK-2 cells from each group were lysed using RIPA lysis buffer containing a protease inhibitor cocktail (1:100) and a phosphatase inhibitor cocktail (1:100) to extract proteins. Protein concentration was determined using the BCA method. Proteins were separated by electrophoresis on a 12.5% separation gel under constant voltage (120V) for approximately 1.5 hours until the bromophenol blue reached the bottom of the gel, and then transferred to a PVDF membrane under constant current (300mA) for 120 minutes. The membrane was blocked with 5% skimmed milk at room temperature on a shaker for 1 hour, followed by overnight incubation with the primary antibody at 4\u0026deg;C. Subsequently, the membrane was incubated with the secondary antibody at room temperature on a shaker for 2 hours. The membrane was washed with TBST. Immunoblot signals were developed using an ECL detection reagent, and the grayscale values of the target bands were quantified using ImageJ software.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.9 Flow Cytometry Detection of Cellular Oxidative Stress (ROS) Levels\u003c/h2\u003e \u003cp\u003eCells were seeded in plates at a density of \u0026lt;\u0026thinsp;5\u0026times;10⁵ cells per milliliter. The six-well plates were divided into the following groups: control group (Con), NC-PDK4\u0026thinsp;+\u0026thinsp;AngII group, and sh-PDK4\u0026thinsp;+\u0026thinsp;AngII group. All procedures were strictly performed according to the instructions of the ROS detection kit. Finally, the cells were trypsinized to prepare a single‑cell suspension, resuspended in 0.5\u0026ndash;1 mL of PBS, and analyzed by flow cytometry.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.10 Bioinformatics Analysis\u003c/h2\u003e \u003cp\u003eThe dataset GSE37455 was obtained from the GEO database, which includes 20 cases of hypertensive nephropathy kidney tissue samples and 21 cases of normal human kidney tissue samples. Differential gene expression analysis was performed using the limma package in R. The differentially expressed genes (DEGs) were subjected to Gene Ontology (GO) analysis to identify significant functional terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to identify significant pathways.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e2.11 Transcriptome Sequencing (RNA-seq)\u003c/h2\u003e \u003cp\u003eHK‑2 cells were divided into two groups and transfected with NC‑PDK4 or sh‑PDK4 using lentiviral technology. When cell density reached approximately 90%, the cells were digested, centrifuged, and resuspended in 1 mL of TRIzol for transcriptome sequencing. Differential gene expression analysis was performed on the two groups (each containing two biological replicates) using the limma package in R. Genes meeting the criteria of |log₂(fold change)| \u0026gt; 1 and adjusted p‑value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were identified as differentially expressed genes (DEGs). GO and KEGG pathway enrichment analyses were performed on the DEGs and visualized. Terms with an adjusted p‑value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were defined as significantly enriched items for the DEGs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e2.12 Statistical Analysis\u003c/h2\u003e \u003cp\u003eStatistical analysis and graphing were performed using SPSS 22.0 and GraphPad Prism 10.1.2 software. The chi‑square test was used to compare gender ratios between groups. Measurement data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation. Differences between two groups were compared using the independent samples t‑test. Comparisons among three or more groups were analyzed by one‑way ANOVA, with inter‑group differences assessed by the least significant difference (LSD) t‑test. A P‑value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Bioinformatics Analysis Suggests PDK4 as a Core Gene in HRD\u003c/h2\u003e \u003cp\u003eTo screen for potential diagnostic biomarkers associated with HRD, we performed differential expression analysis on the gene expression profile data from the GSE37455 dataset in the GEO database. A total of 27 DEGs were obtained, among which 16 genes were upregulated and 11 genes were downregulated. A volcano plot was generated (as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA), and a protein‑protein interaction (PPI) network was constructed. The circular plot (as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB) illustrates the connections and complex interaction relationships among these differentially expressed genes, suggesting that PDK4 is a core gene in HRD.\u003c/p\u003e \u003cp\u003eGO functional enrichment analysis is divided into biological processes, cellular components, and molecular functions. The results obtained (as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eC) indicate that these DEGs are associated with various pathophysiological processes such as endothelial cell differentiation, renal cell infiltration, multi-organism immunity, oxidative stress, and inflammation, suggesting that the pathogenesis of HRD may be related to the aforementioned processes.\u003c/p\u003e \u003cp\u003eKEGG functional enrichment analysis (as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eD) reveals that these DEGs are enriched in related signaling pathways such as IL‑17, MAPK, tumor necrosis factor (TNF), apoptosis, and inflammation, indicating that the pathogenesis of HRD is associated with the above\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA: Volcano plot of DEGs. B: Protein-protein interaction analysis results of the screened key genes, where blue dots represent downregulated genes and red dots represent upregulated genes. C: GO functional enrichment analysis. D: KEGG functional enrichment analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.2 AngII Upregulates PDK4 Expression in HK‑2 Cells\u003c/h2\u003e \u003cp\u003eTo verify the hypothesis derived from bioinformatics analysis that PDK4 expression is elevated, we conducted the following in vitro experiments:Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA shows the results of cell viability detected by CCK‑8. Under the effect of AngII at a concentration of 1\u0026times;10⁻⁶ M, the cell survival rate decreased most significantly; therefore, this concentration was selected as the optimal modeling concentration for HRD in subsequent experiments. HK‑2 cells were divided into two groups: the experimental group was treated with 1\u0026times;10⁻⁶ M AngII for 48 h, and the control group received no treatment. The mRNA expression of PDK4 in each group was detected by qPCR, and the results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB. AngII significantly increased the mRNA expression of PDK4. The protein expression levels of PDK4 in the two groups were detected by Western blot (WB), and the results are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD. AngII also significantly elevated the protein expression level of PDK4. All the above differences were statistically significant .(P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA: CCK‑8 assay results showing the most pronounced effect of 1\u0026times;10⁻⁶ M AngII. B: Relative mRNA expression level of PDK4. C, D: Immunoblot images and quantitative analysisresults of PDK4 and GAPDH protein expression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Lentiviral technology was used to knock down PDK4 expression\u003c/h2\u003e \u003cp\u003eHK-2 cells were transfected with lentiviral particles, divided into NC‑PDK4 and sh‑PDK4 groups. After 72 h of transfection, observation under an inverted fluorescence microscope with blue-light excitation showed that green fluorescence covered almost the entire field of view (as shown in Fig.\u0026nbsp;3A), indicating a transfection efficiency exceeding 90%. Western blot (WB) was used to detect PDK4 protein expression levels in the two groups to evaluate knockdown efficiency. The results (Fig.\u0026nbsp;3B) showed a significant decrease in protein expression in the sh‑PDK4 group, confirming successful transfection of HK-2 cells and meeting the efficiency requirements for subsequent experiments (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFig.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e3\u003c/b\u003e Lentiviral Transfection\u003c/p\u003e \u003cp\u003eA: The results of inverted fluorescence microscopy. The left side shows normal HK-2 cells, and the right side shows HK-2 cells after lentiviral transfection. B: The immunoblot results and quantitative analysis of PDK4 and GAPDH protein expression after transfection.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Knockdown of PDK4 Reduces HRD Oxidative Stress and EMT Levels\u003c/h2\u003e \u003cp\u003eTo investigate whether PDK4 is involved in the pathological and physiological process of ROS generation, HK-2 cells were divided into three groups, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eA. The results, shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, indicate that after AngII induction, the ROS levels in HK-2 cells increased. However, knockdown of PDK4 reversed this effect, with a statistically significant difference (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), suggesting that PDK4 may be involved in the occurrence and development of ROS generation in HRD.\u003c/p\u003e \u003cp\u003eTo investigate whether PDK4 is involved in the EMT process of HRD, HK-2 cells were divided into three groups: control group, AngII group, and sh-PDK4\u0026thinsp;+\u0026thinsp;AngII group. WB was used to detect the protein expression levels of α-SMA, vimentin, and E-cadherin in the three groups. The results, shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e4\u003c/span\u003eB, indicate that AngII upregulated the expression of α-SMA and vimentin and downregulated the expression of E-cadherin in HK-2 cells. However, knockdown of PDK4 reversed these effects, thereby reversing the EMT process and alleviating the fibrosis level in HK-2 cells. (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA: Flow cytometry results and quantitative analysis. B: Immunoblot results and quantitative analysis of α-SMA, vimentin, and E-cadherin protein expression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.5 PDK4 RNA-seq\u003c/h2\u003e \u003cp\u003eTo explore the signaling pathways associated with PDK4 and predict its mechanism in HRD, we performed transcriptome sequencing. HK-2 cells were divided into two groups and transfected with NC-PDK4 and sh-PDK4 using lentivirus, followed by RNA-seq.\u0026nbsp;The results are shown in Fig.\u0026nbsp;5A shows a volcano plot of DEGs, with log2(Fold Change) on the x-axis and -log10(P-value) on the y-axis. Red points represent upregulated genes, and blue points represent downregulated genes.\u003c/p\u003e \u003cp\u003eThe DEGs were subjected to GO and KEGG functional enrichment analysis to explore related signaling pathways and mechanisms. The GO analysis results, shown in Fig.\u0026nbsp;5B, suggest that DEGs are mainly involved in signaling pathways related to metabolism, immunity, apoptosis, extracellular matrix synthesis, fibrosis, inflammation, cell migration, and adhesion. The KEGG analysis, shown in Fig.\u0026nbsp;5C, reveals that DEGs are primarily enriched in pathological processes such as diabetic cardiomyopathy, insulin secretion, ferroptosis, cell adhesion, and complement activation. Additionally, significant associations were found with the classical cancer signaling pathway Wnt \u003csup\u003e[11]\u003c/sup\u003e and the cardiopulmonary function metabolism signaling pathway Apelin \u003csup\u003e[12, 13]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFig.\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003e5\u003c/b\u003e RNA-seq\u003c/p\u003e \u003cp\u003eA: DEGs analysis of the NC-PDK4 group and sh-PDK4 group.B: GO functional enrichment analysis.C: KEGG functional enrichment analysis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Detection of PDK4 Expression in Serum by ELISA\u003c/h2\u003e \u003cp\u003eTo further translate the research findings toward clinical relevance, we measured serum PDK4 levels in patients. The results showed a significant positive correlation between its levels and disease severity. Notably, this clinical trend closely aligns with the conclusions of upregulated expression/function derived from both bioinformatics analysis and cell experiments, forming a mutually corroborating chain of evidence.\u003c/p\u003e \u003cp\u003ePatient serum was collected, and PDK4 expression levels in serum (in pg/mL) were measured by ELISA, with statistically significant differences observed among all groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). As shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e6\u003c/span\u003e, serum PDK4 in the healthy control group (157.61\u0026thinsp;\u0026plusmn;\u0026thinsp;5.37 pg/mL) was significantly lower than that in the hypertension without renal damage group (HT group: 204.23\u0026thinsp;\u0026plusmn;\u0026thinsp;4.43 pg/mL) and the hypertensive renal damage group (HRD group: 242.65\u0026thinsp;\u0026plusmn;\u0026thinsp;4.64 pg/mL). The mean values among the three groups showed statistically significant differences (F\u0026thinsp;=\u0026thinsp;77.71, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), and the scatter plot displays the data distribution for each group.\u003c/p\u003e \u003cp\u003eNo significant differences were found among the three groups in gender, age, BMI, or blood lipids (as shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, t-values\u0026thinsp;=\u0026thinsp;0.659, 0.650, 0.364, 0.344, 0.656, 0.789, 2.308, P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, PDK4 correlated with estimated glomerular filtration rate (eGFR), serum creatinine (Scr), 24-hour urinary microalbumin (mg/24h), and duration of hypertension (years). It was negatively correlated with eGFR and positively correlated with Scr, 24-hour urinary microalbumin, and duration of hypertension (years), indicating that PDK4 holds certain value in predicting patients' renal function and extent of damage.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e suggests that PDK4 has high diagnostic value for HRD, with an area under the ROC curve (AUC) of 0.982, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e7\u003c/span\u003e, and a significance level of P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Using the presence or absence of hypertensive renal damage (HRD) as the dependent variable and PDK4 expression level as a covariate, binary logistic regression analysis was performed to assess the relative risk (OR value) of PDK4 expression level.\u003c/p\u003e \u003cp\u003eThe OR value was 1.216, as shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, meaning that for each one-unit increase in PDK4 expression level, the risk of developing HRD increases by 21.6% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Thus, PDK4 also demonstrates certain value in the diagnosis and prognosis prediction of HRD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePDK4 expression level: HRD group (242.65\u0026thinsp;\u0026plusmn;\u0026thinsp;4.64 pg/mL)\u0026thinsp;\u0026gt;\u0026thinsp;HT group (204.23\u0026thinsp;\u0026plusmn;\u0026thinsp;4.43 pg/mL)\u0026thinsp;\u0026gt;\u0026thinsp;control group (157.61\u0026thinsp;\u0026plusmn;\u0026thinsp;5.37 pg/mL), with statistically significant differences among the groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGeneral Information of Patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.260\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBmi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.344\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal cholesterol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.656\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriglycerides\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation Coefficients between PDK4 Expression Levels and HRD Indicators\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eItem\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCorrelation Coefficient\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSignificance\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eeGFR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-0.571\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.255\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.117\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScr\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.514\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24‑h urine protein (mg/24h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;=\u0026thinsp;0.097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e24‑h urinary microalbumin (mg/24h)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.322\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of hypertension (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.664\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDiagnostic Value of PDK4\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAUC(95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYouden's index\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCut‑off value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSensitivity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSpecificity (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertensive renal damage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.982(0.950\u0026thinsp;~\u0026thinsp;1.000)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e219.6(pg/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRelative Risk (OR Value) of PDK4\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSignificance\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOR Value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI for OR Value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePDK4 Expression Level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.216\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e(1.020\u0026thinsp;~\u0026thinsp;1.450)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eAs a critical mitochondrial enzyme \u003csup\u003e[14]\u003c/sup\u003e, PDK4 plays a complex role in diabetic renal damage. Zhao et al. found that knocking down PDK4 in high‑glucose‑induced podocytes suppressed the expression of inflammatory factors (IL‑1β, IL‑6, TNF‑α) and reduced apoptosis \u003csup\u003e[15]\u003c/sup\u003e. Additionally, research by Tian et al. suggested that inhibiting PDK4 in HK‑2 cells and mouse models may enhance antioxidant capacity and improve iron metabolism by activating the Nrf2 pathway, thereby alleviating oxidative stress and ferroptosis \u003csup\u003e[16]\u003c/sup\u003e. PDK4 is also involved in other renal injury processes. One study, through bioinformatics and experimental validation, confirmed that PDK4 is a potential diagnostic gene for membranous nephropathy, and its expression is closely associated with ferroptosis and immune cell infiltration \u003csup\u003e[17]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eDiabetes and hypertension are the two leading causes of chronic kidney disease \u003csup\u003e[18]\u003c/sup\u003e. However, the role of PDK4 in hypertensive renal damage (HRD) remains incompletely understood. This study explored the expression pattern, clinical significance, and potential mechanism of PDK4 in HRD, providing preliminary evidence for the diagnosis and treatment of HRD.\u003c/p\u003e \u003cp\u003eBioinformatics analysis revealed that PDK4 is a core differentially expressed gene in HRD. Subsequently, in vitro cell experiments confirmed that PDK4 is highly expressed in the HRD cell model, and knockdown of PDK4 alleviated HK‑2 cell injury (e.g., EMT, ROS). Importantly, differential expression of PDK4 was observed in the serum of HRD patients, and its expression increased with the severity of injury. PDK4 protein levels showed a significant positive correlation with renal function impairment indicators. This tripartite evidence collectively establishes the key role of PDK4. Subsequent RNA‑seq also predicted the mechanism of action of PDK4, providing a theoretical basis for future research.\u003c/p\u003e \u003cp\u003eHRD is characterized by worsening renal function and renal fibrosis \u003csup\u003e[19]\u003c/sup\u003e. Under hypertensive conditions, activation of the local renal renin-angiotensin system leads to elevated angiotensin II (Ang II) levels and epithelial-mesenchymal transition (EMT) \u003csup\u003e[20]\u003c/sup\u003e. Renal epithelial cells dedifferentiate into fibroblast-like phenotypes, accompanied by loss of the epithelial-specific marker E-cadherin, acquisition of mesenchymal markers such as α-smooth muscle actin (α-SMA) and vimentin, and excessive deposition of extracellular matrix, ultimately resulting in renal tubulointerstitial fibrosis \u003csup\u003e[21\u0026ndash;23]\u003c/sup\u003e. Related studies also suggest that the pathogenesis of HRD primarily involves activation of the renin-angiotensin system (RAS), leading to afferent arteriole contraction, ischemic glomerular injury, and activation of reactive oxygen species (ROS) among others \u003csup\u003e[24]\u003c/sup\u003e. Long-term poorly controlled hypertension damages renal tubular cells, thereby promoting EMT and renal interstitial fibrosis \u003csup\u003e[25]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eConsistent with the findings from bioinformatics analysis, this study observed in the in vitro HRD HK‑2 cell model that AngII induction aggravated ROS levels and EMT in HK‑2 cells, whereas lentiviral transfection‑mediated knockdown of PDK4 alleviated these AngII‑induced damaging effects. These results suggest that knocking down PDK4 can significantly inhibit AngII‑induced ROS and EMT. Future research may further examine the expression levels of classic renal fibrosis markers \u003csup\u003e[26]\u003c/sup\u003e, such as Collagen I and Fibronectin. Moreover, numerous studies have shown that ROS and inflammatory responses mutually reinforce each other in renal injury, forming a vicious cycle \u003csup\u003e[27, 28]\u003c/sup\u003e. Therefore, future studies should still investigate whether PDK4 also regulates inflammatory signaling pathways, such as by detecting the secretion levels of key inflammatory factors (e.g., IL‑6, IL‑1β, TNF‑α) and the activation of classic inflammatory signaling pathways like NF‑κB \u003csup\u003e[29, 30]\u003c/sup\u003e. This will more firmly establish the value of PDK4 as a therapeutic target.Although this study confirmed the effects of PDK4 on ROS and EMT in renal tubular epithelial cells, these findings have not yet been validated in in vivo models, such as spontaneously hypertensive rats (SHR). Given that the internal environment is influenced by various complex factors including hemodynamics and endocrine regulation, the precise pathogenic role of PDK4 in vivo and the therapeutic effects of targeting PDK4 inhibition will be the focus of future research.\u003c/p\u003e \u003cp\u003eAnalysis of clinical data confirms that PDK4 is not only significantly correlated with key renal function indicators but also serves as an independent risk factor for the disease (OR\u0026thinsp;\u0026gt;\u0026thinsp;1) and demonstrates good diagnostic performance. These findings, together with results from bioinformatics analysis, serum tests, and cell experiments, consistently show upregulation of PDK4 in HRD, supporting its potential as a diagnostic biomarker for HRD. However, the sample size for clinical validation is relatively small and derived from a single center, which may lead to selection bias to some extent. Although the inter-group differences and diagnostic efficacy of PDK4 in this study are statistically significant, its reliability as a biomarker still requires further validation in multi-center, large-scale prospective cohorts to obtain more universal clinical data.\u003c/p\u003e \u003cp\u003ePDK4 is a key regulator of energy metabolism. It phosphorylates and inhibits the activity of pyruvate dehydrogenase (PDH), thereby reducing acetyl‑CoA generation, which modulates the tricarboxylic acid cycle and suppresses aerobic respiration \u003csup\u003e[31\u0026ndash;34]\u003c/sup\u003e. The PDK isoforms exhibit tissue‑specific expression patterns: PDK1 and PDK4 are highly expressed in heart, pancreatic islets, and skeletal muscle; PDK3 is mainly present in testis, brain, and kidney; while PDK2 appears to be widely expressed in many tissues \u003csup\u003e[35]\u003c/sup\u003e. In vitro cell experiments indicated that PDK4 is involved in the biological processes of EMT and ROS. Building on this, to further explore its specific mechanism of action, we performed RNA‑seq analysis. The results showed that the DEGs caused by PDK4 knockdown were primarily enriched in pathways related to metabolism, apoptosis, ferroptosis, and cardiopulmonary function. This suggests that PDK4 may influence EMT and ROS generation by regulating these pathways. Of course, these remain predictive hypotheses that require further experimental validation.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study employed bioinformatics analysis, RNA-seq, and experimental validation to investigate the role of PDK4 in HRD. The results indicate that PDK4 may be a key promoting factor in HRD progression, and intervention strategies targeting PDK4 could provide new theoretical foundations and potential therapeutic targets for the clinical management of HRD.Although this study provides preliminary evidence for the role of PDK4 in HRD, several limitations remain. First, due to the limited clinical sample size, the diagnostic thresholds and stability of PDK4 require further refinement in larger population cohorts. Second, this study is currently confined to in vitro cellular experiments and lacks in-depth confirmation of phenotypes and signaling pathways through in vivo animal studies. The complex microenvironment in vivo will be a primary objective for our future investigations.\u003c/p\u003e \u003cp\u003eIn summary, current research on PDK4 in kidney diseases has largely focused on diabetic nephropathy or other forms of renal injury, while its specific role in HRD remains incompletely understood. This study provides a relatively systematic characterization of PDK4's role in HRD by integrating bioinformatics, in vitro experiments, and clinical sample analysis.The most prominent strength of this study lies in its multi‑level, mutually validating research strategy. Bioinformatics analysis provided preliminary screening and theoretical evidence; cell experiments, consistent with the bioinformatics results, established direct relationships; and finally, clinical serum testing confirmed its potential translational and clinical application value. The consistency of results across these three levels significantly enhances the reliability and persuasiveness of the conclusions, avoiding the limitations of any single research method.\u003c/p\u003e \u003cp\u003eIn this study, bioinformatics analysis identified PDK4 as a potential biomarker for HRD, with its expression and diagnostic value subsequently validated through clinical data and cellular models. Furthermore, RNA-seq was employed to predict its underlying mechanisms. This research preliminarily explores the expression patterns, clinical significance, and potential mechanisms of PDK4 in HRD, providing supplementary evidence for the role of this gene in specific renal pathologies and suggesting that PDK4 represents a promising target with clinical application potential.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics Approval and Informed Consent\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate This study was approved by the Medical Ethics Committee of Zhengzhou Central Hospital (Approval No. ZXYY2025182). Informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for Publication\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eConsent for publication Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003cem\u003eData Availability Statement\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials The representative raw data supporting the findings of this study are included in this published article [and its supplementary information files]. Other data that support the findings of this study are available from the corresponding author on reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eUDANI S, LAZICH I, BAKRIS G L. Epidemiology of hypertensive kidney disease [J]. Nat Rev Nephrol, 2011, 7(1): 11\u0026ndash;21.\u003c/li\u003e\n\u003cli\u003eMENNUNI S, RUBATTU S, PIERELLI G, et al. 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Reducing Oxidative Stress and Inflammation by Pyruvate Dehydrogenase Kinase 4 Inhibition Is Important in Prevention of Renal Ischemia-Reperfusion Injury in Diabetic Mice [J]. Diabetes Metab J, 2024, 48(3): 405\u0026ndash;17.\u003c/li\u003e\n\u003cli\u003eADELUSI T I, DU L, HAO M, et al. Keap1/Nrf2/ARE signaling unfolds therapeutic targets for redox imbalanced-mediated diseases and diabetic nephropathy [J]. Biomed Pharmacother, 2020, 123: 109732.\u003c/li\u003e\n\u003cli\u003eGUPTA A, BEHL T, SEHGAL A, et al. Therapeutic potential of Nrf-2 pathway in the treatment of diabetic neuropathy and nephropathy [J]. Mol Biol Rep, 2021, 48(3): 2761\u0026ndash;74.\u003c/li\u003e\n\u003cli\u003eFORMAN H J, ZHANG H. Targeting oxidative stress in disease: promise and limitations of antioxidant therapy [J]. Nat Rev Drug Discov, 2021, 20(9): 689\u0026ndash;709.\u003c/li\u003e\n\u003cli\u003e《中国高血压基层管理指南》修订委员会. 中国高血压基层管理指南 [M]. 人民卫生出版社.\u003c/li\u003e\n\u003cli\u003eLIU J, XIAO Q, XIAO J, et al. Wnt/\u0026beta;-catenin signalling: function, biological mechanisms, and therapeutic opportunities [J]. Signal Transduct Target Ther, 2022, 7(1): 3.\u003c/li\u003e\n\u003cli\u003eCHAPMAN F A, MAGUIRE J J, NEWBY D E, et al. Targeting the apelin system for the treatment of cardiovascular diseases [J]. Cardiovasc Res, 2023, 119(17): 2683\u0026ndash;96.\u003c/li\u003e\n\u003cli\u003eYAN J, WANG A, CAO J, et al. Apelin/APJ system: an emerging therapeutic target for respiratory diseases [J]. Cell Mol Life Sci, 2020, 77(15): 2919\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eSUGDEN M C, HOLNESS M J. Recent advances in mechanisms regulating glucose oxidation at the level of the pyruvate dehydrogenase complex by PDKs [J]. Am J Physiol Endocrinol Metab, 2003, 284(5): E855\u0026ndash;62.\u003c/li\u003e\n\u003cli\u003eZHAO T, JIN Q, KONG L, et al. microRNA-15b-5p shuttled by mesenchymal stem cell-derived extracellular vesicles protects podocytes from diabetic nephropathy via downregulation of VEGF/PDK4 axis [J]. J Bioenerg Biomembr, 2022, 54(1): 17\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eTIAN S, YANG X, LIN Y, et al. PDK4-mediated Nrf2 inactivation contributes to oxidative stress and diabetic kidney injury [J]. Cell Signal, 2024, 121: 111282.\u003c/li\u003e\n\u003cli\u003eHAN M, WANG Y, HUANG X, et al. Prediction of biomarkers associated with membranous nephropathy: Bioinformatic analysis and experimental validation [J]. Int Immunopharmacol, 2024, 126: 111266.\u003c/li\u003e\n\u003cli\u003eL\u0026oacute;PEZ-NOVOA J M, MART\u0026iacute;NEZ-SALGADO C, RODR\u0026iacute;GUEZ-PE\u0026ntilde;A A B, et al. Common pathophysiological mechanisms of chronic kidney disease: therapeutic perspectives [J]. Pharmacol Ther, 2010, 128(1): 61\u0026ndash;81.\u003c/li\u003e\n\u003cli\u003eWANG F, ZHANG Y, GAO M, et al. TMEM16A inhibits renal tubulointerstitial fibrosis via Wnt/\u0026beta;-catenin signaling during hypertension nephropathy [J]. Cell Signal, 2024, 117: 111088.\u003c/li\u003e\n\u003cli\u003eCUEVAS C A, TAPIA-ROJAS C, CESPEDES C, et al. \u0026beta;-Catenin-Dependent Signaling Pathway Contributes to Renal Fibrosis in Hypertensive Rats [J]. Biomed Res Int, 2015, 2015: 726012.\u003c/li\u003e\n\u003cli\u003eLAN H Y. Tubular epithelial-myofibroblast transdifferentiation mechanisms in proximal tubule cells [J]. Curr Opin Nephrol Hypertens, 2003, 12(1): 25\u0026ndash;9.\u003c/li\u003e\n\u003cli\u003eRUIZ-ORTEGA M, EGIDO J. Angiotensin II modulates cell growth-related events and synthesis of matrix proteins in renal interstitial fibroblasts [J]. Kidney Int, 1997, 52(6): 1497\u0026ndash;510.\u003c/li\u003e\n\u003cli\u003eSUN H J. Current Opinion for Hypertension in Renal Fibrosis [J]. 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Etiopathology of chronic tubular, glomerular and renovascular nephropathies: clinical implications [J]. J Transl Med, 2011, 9: 13.\u003c/li\u003e\n\u003cli\u003eANDERS H J, SCHAEFER L. Beyond tissue injury-damage-associated molecular patterns, toll-like receptors, and inflammasomes also drive regeneration and fibrosis [J]. J Am Soc Nephrol, 2014, 25(7): 1387\u0026ndash;400.\u003c/li\u003e\n\u003cli\u003eLIU T, ZHANG L, JOO D, et al. NF-\u0026kappa;B signaling in inflammation [J]. Signal Transduct Target Ther, 2017, 2: 17023\u0026ndash;.\u003c/li\u003e\n\u003cli\u003eABBOT E L, MCCORMACK J G, REYNET C, et al. Diverging regulation of pyruvate dehydrogenase kinase isoform gene expression in cultured human muscle cells [J]. Febs j, 2005, 272(12): 3004\u0026ndash;14.\u003c/li\u003e\n\u003cli\u003eWYNN R M, KATO M, CHUANG J L, et al. Pyruvate dehydrogenase kinase-4 structures reveal a metastable open conformation fostering robust core-free basal activity [J]. J Biol Chem, 2008, 283(37): 25305\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eKULKARNI S S, SALEHZADEH F, FRITZ T, et al. Mitochondrial regulators of fatty acid metabolism reflect metabolic dysfunction in type 2 diabetes mellitus [J]. Metabolism, 2012, 61(2): 175\u0026ndash;85.\u003c/li\u003e\n\u003cli\u003eGRASSIAN A R, METALLO C M, COLOFF J L, et al. Erk regulation of pyruvate dehydrogenase flux through PDK4 modulates cell proliferation [J]. Genes Dev, 2011, 25(16): 1716\u0026ndash;33.\u003c/li\u003e\n\u003cli\u003eBOWKER-KINLEY M M, DAVIS W I, WU P, et al. Evidence for existence of tissue-specific regulation of the mammalian pyruvate dehydrogenase complex [J]. Biochem J, 1998, 329 ( Pt 1)(Pt 1): 191\u0026ndash;6.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"PDK4, Epithelial-mesenchymal transition, Human renal tubular epithelial cells, Hypertensive renal damage","lastPublishedDoi":"10.21203/rs.3.rs-8443693/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8443693/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground and Objective:\u0026nbsp;Hypertensive renal damage (HRD) currently lacks effective early biomarkers and intervention targets. Pyruvate dehydrogenase kinase isozyme 4 (PDK4) plays well‑defined roles in various diseases, but its mechanism in HRD has not been systematically elucidated. This study aimed to explore the role of PDK4—a key molecule that has not been fully studied—in HRD by integrating bioinformatics analysis and experimental validation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethods:\u0026nbsp;① Bioinformatics analysis was performed based on the GEO database (GSE37455) to screen differentially expressed genes and conduct functional enrichment analysis. ② Clinical serum samples from HRD patients were collected, and PDK4 levels were measured by ELISA to analyze their correlation with renal function indicators and diagnostic performance. ③ An injury model was established by stimulating human renal tubular epithelial cells (HK‑2) with Ang II, and PDK4 expression was detected. PDK4 was knocked down using lentivirus to evaluate its effects on oxidative stress (ROS) and epithelial‑mesenchymal transition (EMT). ④ RNA‑seq was performed on PDK4‑knockdown cells, and downstream signaling pathways were analyzed by enrichment analysis.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults: ① Bioinformatics analysis indicated that PDK4 is highly expressed in HRD, and related differentially expressed genes were enriched in pathways such as inflammation and apoptosis. ② Clinical samples showed that serum PDK4 expression was highest in the HRD group, negatively correlated with eGFR, and positively correlated with creatinine, urinary protein, etc. The ROC curve revealed an AUC of 0.982 for PDK4 in diagnosing HRD. ③ In cell experiments, Ang II induced upregulation of PDK4 expression, and its knockdown alleviated oxidative stress and EMT progression. ④ RNA‑seq analysis demonstrated that PDK4 knockdown affects pathways including inflammation, oxidative stress, and Wnt.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusion: PDK4 is highly expressed in HRD and promotes renal injury by regulating oxidative stress and fibrotic processes, suggesting its value as a potential biomarker and therapeutic target for HRD. This study provides the first systematic evidence of the high expression of PDK4 in HRD and its injury‑promoting mechanism, indicating that PDK4 may serve as a potential novel biomarker and therapeutic target.\u003c/p\u003e","manuscriptTitle":"Expression and Mechanistic Insights into PDK4 in Hypertensive Renal Damage","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-06 14:35:40","doi":"10.21203/rs.3.rs-8443693/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-02-20T01:29:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"53471548299027302331236067172866875394","date":"2026-02-12T00:21:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-23T16:37:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"278723570093983942487602313929306832619","date":"2026-01-22T14:25:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"29325297902522382653747990706378359856","date":"2026-01-20T07:06:21+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-05T08:23:10+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-05T08:17:04+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-05T06:52:16+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-02T18:55:49+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nephrology","date":"2026-01-02T18:46:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"75786cfc-0137-469e-a0be-aea94ea80edb","owner":[],"postedDate":"January 6th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-01-06T14:35:40+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-06 14:35:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8443693","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8443693","identity":"rs-8443693","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}