The TDC batches used in this study (listed in Table 1) were supplied by Shanxi Buchang Pharmaceuticals Co., Ltd. (Shanxi, China). The botanical ingredients Uncariae Ramulus Cum Uncis, Prunellae Spica, Suis Fellis Pulvis, Taxilli Herba, Salviae Miltiorrhizae Radix et Rhizoma, Astragali Radix, Chuanxiong Rhizoma, Plantaginis Semen, Notoginseng Radix et Rhizoma, and Stephania tetrandra S. Moore were authenticated by Professor Qu from Inner Mongolia Medical University (Inner Mongolia, China). Reference standards, including Geniposidic acid (catalog no. DSTDJ004002, purity ≥98%), Salvianolic acid B (Sal B; DSTDD000904, purity ≥98%), Rutin (DSTDL001701, purity ≥99%), Tetrandrine (DSTDF000401, purity ≥98%), and Calycosin-7-glucoside (DSTDM001301, purity ≥98%), were purchased from Chengdu Destar Biotechnology Co., Ltd. (Chengdu, China).

All LC-MS grade formic acid, methanol, and phosphoric acid were obtained from Fisher Scientific (Fair Lawn, NJ, United States). Angiotensin II (Ang II; catalog no. PSD241025-768, purity ≥95%) was acquired from Chengdu Pusi Biotechnology Co. (Chengdu, China). Purified water used in the experiments was sourced from Wahaha Group Co., Ltd. (Hangzhou, China).

The reference standards Geniposidic acid, Sal B, Rutin, Tetrandrine, and Calycosin-7-glucoside were each dissolved in methanol to prepare stock solutions at concentrations of 324, 215, 212, 251, and 210 μg/mL, respectively.

Approximately 2 g of TDC was placed in a stoppered conical flask and extracted with 50 mL of 70% ethanol. The mixture was thoroughly shaken and then subjected to ultrasonic extraction for 90 min. After extraction, the solution was centrifuged for 5 min to obtain the supernatant, which was evaporated to dryness. The residue was reconstituted in 10 mL of 15% methanol and filtered through a 0.22 μm membrane to prepare the final test solution (Zhang et al., 2024). Sample solutions of each herb were prepared as described above.

Sprague-Dawley (SD) rats (n = 12; male; SPF grade; body weight 200 ± 2 g) were obtained from the Animal Center of Inner Mongolia Medical University (Inner Mongolia, China) under certificate number SCXK(m)2020-0003. All animal procedures were approved by the Ethics Committee of Inner Mongolia Medical University (approval no. YKD202301192). Following a 3-day acclimatization, the animals were randomly divided into control and TDC (n = 6 per group). Rats in the TDC group received a suspension of TDC at a dose of 0.91 g/kg by oral gavage, approximating the clinically relevant human equivalent dose (TDC dose = 6 g × 9.1/60 kg). Control rats were administered an equal volume of purified water (10 mL/kg) once daily for three consecutive days. Food and water were withheld for 16 h before the final administration.

Blood samples were collected from the fundus venosus at 0.5, 1.0, 1.5, and 2.0 h after the final dose and transferred into 1.5 mL tubes containing sodium heparin. Plasma was separated by centrifugation at 3,000 r/min for 10 min at 4°C and stored at −20°C. For each time point, 500 μL of plasma (including control) was mixed with 4.5 mL methanol, vortexed for 1 min, centrifuged at 2,000 r/min for 10 min at 4°C, and vacuum-dried. The dried residue was reconstituted in 100 μL methanol, centrifuged again at 12,000 r/min for 10 min, and the resulting supernatant was stored at 4°C in vials with protective liners.

The chemical constituents of TDC were analyzed using a Dionex Ultimate 3000 UPLC system coupled with a Q Exactive quadrupole-orbitrap mass spectrometer (Thermo Fisher Scientific, United States), equipped with a heated electrospray ionization (ESI) source. Chromatographic separation was performed at 40°C using an Agilent ZORBAX SB-Aq column (4.6 × 150 mm, 5 μm). The mobile phase consisted of solvent A (0.1% formic acid in water) and solvent B (methanol), with the following gradient elution program: 5%–5% B (0–5 min), 5%–30% B (5–10 min), 30%–60% B (10–18 min), 60%–80% B (18–25 min), 80%–90% B (25–35 min), and 90%–90% B (35–40 min). The injection volume was 5 μL, and the flow rate was maintained at 0.3 mL/min.

The spray voltages were set at +3.80 kV for positive and −3.20 kV for negative ion modes. The ion transfer tube temperatures were set at 300°C (positive mode) and 400°C (negative mode), while the auxiliary gas heater was maintained at 350°C. Data acquisition was performed in positive and negative ionization modes using full-scan (m/z 110–1200) and data-dependent MS2 (dd-MS2), with a normalized collision energy of 30 eV.

Data acquisition and analysis were performed using Xcalibur 3.0 software (Thermo Fisher Scientific, United States). A detailed in-house database was constructed, incorporating the names, molecular formulas, ionization characteristics, and multistage mass spectral fragmentation patterns of the chemical constituents derived from the herbal components of the TDC decoction (Liu Z. P. et al., 2025; Sun et al., 2024). Unknown chromatographic peaks were interpreted by comparing their primary and secondary mass spectral data with entries from the in-house database and reference compound spectra, enabling the identification of potential chemical constituents.

Chromatographic analysis was conducted using a Waters XTERRA MS C18 column (2.1 × 250 mm, 3.5 μm). The mobile phase consisted of solvent A (0.2% phosphoric acid in water) and solvent B (methanol). Gradient elution was applied as follows: 0–12 min, 15%–20% B; 12–24 min, 20%–40% B; 24–45 min, 40%–60% B; 45–53 min, 60%–78% B; and 53–65 min, 78%–95% B. The injection volume was 10 μL, with a 1 mL/min flow rate. UV detection was performed at 254 nm, and the column temperature was maintained at 30°C.

Method validation included evaluations of precision, reproducibility, and sample stability. Precision was assessed by injecting the same sample solution six consecutive times daily. Reproducibility was verified using six independently prepared solutions from the same TDC batch. Sample stability was evaluated by analyzing the same solution at 0, 4, 10, 16, 24, and 30 h post-preparation (Li D. et al., 2024). The similarity among chromatograms of different samples was evaluated using the Similarity Evaluation System for Chromatographic Fingerprint of Traditional Chinese Medicine (Version 2012, Chinese Pharmacopoeia Commission), with correlation coefficients included in the analysis.

All data are presented as mean ± standard deviation. Statistical comparisons were performed using an unpaired t-test with GraphPad Prism 8.0. A p-value less than 0.05 was considered indicative of statistical significance.

A total of 82 compounds were identified in TDC based on their mass-to-charge ratios (m/z) and secondary fragmentation patterns (Supplementary Table S1). Analysis using both positive and negative ion modes (Figures 1A,B) classified these compounds into several categories: 13 flavonoids, 2 coumarins, 34 organic acids, 4 glucosides, 2 terpenes, 14 quinones, 4 alkaloids, 2 amino acids, and 7 other compounds (Figure 1E).

Comparative analysis of mass spectra from TDC extracts, blank plasma, and plasma samples post-administration, along with detailed primary and secondary mass spectrometry data for each chromatographic peak, led to the identification of 51 prototype compounds absorbed into the bloodstream (Figures 1C,D; Supplementary Table S2). These included 24 organic acids, 3 flavonoids, 12 quinones, 2 coumarins, 3 alkaloids, 2 terpenes, and 5 compounds of other types (Figure 1F). Several of these constituents were definitively identified by matching retention times and mass spectra with those of reference standards. The absorbed plasma components likely represent the bioactive substances responsible for TDC’s therapeutic effects against HRD.

The qualitative analysis of TDC’s chemical composition was the foundation for fingerprint development by providing key compositional data. Chromatographic profiling was performed using the Similarity Evaluation System for Chromatographic Fingerprints of Traditional Chinese Medicine (2012 version). Sample S1 was designated as the reference, and a median method with a 0.1 time window width was applied. Following multi-point correction and data alignment, a standard control fingerprint was generated. Overlaid HPLC fingerprints from ten different TDC batches were also produced (Figure 2A). Similarity indices among these batches ranged from 0.902 to 0.998 (Table 3), indicating high batch consistency.

Salvianolic acid B (Sal B, Peak 17) was selected as the internal reference peak, and 25 common fingerprint peaks were identified across the ten batches. Precision testing of the 25 compounds using six replicates showed that the relative standard deviations (RSDs) for stability, precision, and repeatability were below 5%. Reference standards confirmed the identification of Geniposidic acid (Peak 1), Tetrandrine (Peak 9), Calycosin-7-glucoside (Peak 10), Rutin (Peak 14), and Sal B (Peak 17) (Figure 2B).

Fingerprint comparisons between TDC and its herbal components (Figure 2C) revealed 25 distinct chromatographic peaks. Among these, shared peaks were attributed to specific herbs: 4 peaks from Uncariae Ramulus Cum Unci (Peaks 3, 4, 14, 16), 4 from Prunellae Spica (Peaks 7, 12, 16, 22), 1 from Suis Fellis Pulvis (Peak 20), 3 from Taxilli Herba (Peaks 18, 24, 25), 4 from Salviae Miltiorrhizae Radix et Rhizoma (Peaks 15, 16, 17, 19), 3 from Astragali Radix (Peaks 10, 21, 23), 4 from Chuanxiong Rhizoma (Peaks 2, 4, 6, 13), 2 from Plantaginis Semen (Peaks 1, 11), 1 from Notoginseng Radix et Rhizoma (Peak 11), and 3 from Stephania tetrandra S. Moore (Peaks 5, 8, 9). The relative contribution of each herb to the fingerprint profile was quantified and is summarized in Table 4.

A total of 82 chemical constituents were identified from TDC extracts, and 51 prototype compounds were detected in rat plasma following TDC administration. Chemometric fingerprint analysis revealed five distinctive characteristic peaks. Comparative analysis using a Venn diagram indicated that Sal B may serve as a potential Q-marker for TDC (Figure 3).

Cell viability was assessed using the CCK-8 assay (Figure 4A), which determined the half-maximal inhibitory concentration (IC₅₀) of Sal B to be 628.8 μg/mL. To evaluate Sal B’s therapeutic efficacy against HRD, key biomarkers associated with inflammation and renal injury, including interleukin-6 (IL-6), neutrophil gelatinase-associated lipocalin (NGAL), and transforming growth factor-beta (TGF-β), were quantitatively measured. These markers were significantly elevated in the model group compared to the control (p < 0.01; Figure 4B), while Sal B treatment significantly decreased their levels (p < 0.05), suggesting its anti-inflammatory, anti-fibrotic, and nephroprotective potential.

Transcriptomic profiling of HEK293T cells following Sal B exposure revealed distinct expression changes. Principal component analysis (PCA) demonstrated that the first three components accounted for 67.45%, 8.8%, and 6.33% of the total variance, respectively (Figure 4C). Differentially expressed genes (DEGs) were identified using thresholds of |Log₂ fold change| > 1 and p < 0.05 (Cao et al., 2023). Compared with the Control group, the Model group showed 90 significant DEGs (45 upregulated and 45 downregulated), while the TDC group showed 210 DEGs (120 upregulated and 90 downregulated). Between the TDC and Model groups, 195 DEGs were identified (104 upregulated and 91 downregulated) (Figures 4D,E).

To explore the potential biological mechanisms influenced by Sal B, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted on the DEGs (Chen et al., 2024; Wen et al., 2024). The top 20 enriched pathways were visualized using bubble plots (Figures 4F,G).

Using an absolute logFC >1 as the threshold, 396 DEGs were identified between the Model and Control groups, and 501 DEGs were found between the TDC and Model groups. Intersecting these datasets yielded 113 overlapping DEGs. Further comparison of these 113 DEGs with proteomic data comprising 2,925 proteins from the Finnish database identified seven shared targets. The MR analysis was then performed to assess the potential causal relationship between these candidates and HRD (Figure 5A).

Among the seven overlapping genes, only one demonstrated a statistically significant association (p < 0.05). Inverse-variance weighted (IVW) analysis indicated that Killer Cell Lectin Like Receptor D1 (KLRD1) serves as a protective factor against HRD (Figure 5B; Table 5). Furthermore, the MR-Egger intercept test (p > 0.05), Cochran’s Q test (p > 0.05), and MR-PRESSO analysis (p > 0.05) revealed no evidence of pleiotropy or heterogeneity (Table 6). Leave-one-out (LOO) sensitivity analysis confirmed that the MR estimates were not driven by any single SNP (Figure 5C). KLRD1 was significantly downregulated at the expression level in the HRD Model group compared to Controls (****p < 0.0001). Sal B treatment partially restored its expression (***p < 0.001) (Figure 5D).

Partial Least Squares Discriminant Analysis (PLS-DA) was employed to evaluate the metabolomic profiles of the Control, Model, and TDC groups (Li J. et al., 2024). As illustrated in Figure 6A, the three groups displayed distinct metabolic signatures. Applying the criteria of absolute logFC >1, VIP >1, and p < 0.05 in the PLS-DA model (Teng and Wang, 2025; Xue et al., 2024), a total of 123 differentially accumulated metabolites (DAMs) were identified between the Control and Model groups 79 were downregulated and 44 were upregulated (Figure 6B). In comparison, 95 DAMs were detected between the TDC and Model groups, including 67 upregulated and 28 downregulated metabolites.

Furthermore, bioinformatics analysis was carried out to investigate the functional roles of these metabolites by constructing Venn diagrams (Figure 6C). The comparative analysis screened 5 DAMs as overlapping candidates for further functional characterization (Figure 6D). Correlation analysis between these 5 metabolites and key targets identified KLRD1 as a central molecule of interest. α,α′-diethyl-3,4,4′-stilbenetriol showed a significant negative correlation with KLRD1 expression (p < 0.05) (Figure 6E), suggesting that both may contribute critically to the therapeutic effects of Sal B in the context of HRD.