Table 3.
List of seven differential metabolites, focalized based on untargeted metabolomic analysis.
| NO. | Metabolites | VIP Value | pFDR | r Value (Metabolic Ratio) a | r Value (mRNA level) b | AUC-ROC | Change Trend c | Detected From | Detected By |
|---|---|---|---|---|---|---|---|---|---|
| 1 | Valine | 1.21 | 0.012 | −0.63 | −0.56 | 0.89 | ↓ | serum | GC-MS |
| 1.57 | 0.000 | −0.75 | −0.64 | 1.00 | ↓ | liver | GC-MS | ||
| 2 | Leucine | 1.27 | 0.006 | −0.66 | −0.57 | 0.92 | ↓ | serum | GC-MS |
| 1.60 | 0.000 | −0.76 | −0.68 | 1.00 | ↓ | liver | GC-MS | ||
| 3 | Isoleucine | 1.12 | 0.009 | −0.68 | −0.52 | 0.91 | ↓ | serum | GC-MS |
| 1.60 | 0.000 | −0.74 | −0.71 | 1.00 | ↓ | liver | GC-MS | ||
| 4 | Phenylalanine | 1.07 | 0.007 | −0.77 | −0.62 | 0.94 | ↓ | serum | LC-MS |
| 1.52 | 0.000 | −0.78 | −0.71 | 1.00 | ↓ | liver | GC-MS | ||
| 5 | Tyrosine | 1.26 | 0.006 | −0.79 | −0.65 | 0.92 | ↓ | serum | GC-MS |
| 1.55 | 0.000 | −0.68 | −0.71 | 1.00 | ↓ | liver | GC-MS | ||
| 6 | TDCA | 1.98 | 0.028 | −0.74 | −0.51 | 0.84 | ↓ | serum | LC-MS |
| 4.56 | 0.000 | −0.77 | −0.77 | 0.98 | ↓ | liver | LC-MS | ||
| 7 | LysoPC(18:0) | 1.58 | 0.005 | 0.58 | 0.69 | 0.94 | ↑ | serum | LC-MS |
| 1.19 | 0.001 | 0.75 | 0.69 | 0.97 | ↑ | liver | LC-MS |
a Correlation coefficients of Spearman correlation analysis between differential metabolites and metabolic ratio. b Correlation coefficients of Spearman correlation analysis between differential metabolites and mRNA level of CYP1A2. c Change trends of differential metabolites based on area normalization data in untargeted metabolomics. ↓ decreasing change trend after β-naphthoflavone administration. ↑ increasing change trend after β-naphthoflavone administration. The value of the metabolic ratio reflects the activity of CYP1A2, and a higher value represents greater activity. CYP1A2 mRNA expression was calculated using the 2−ΔCt method. Ct: cycle threshold. ΔCt = Ct of CYP1a2 - Ct of β-actin; LysoPC(18:0): Lysophosphatidylcholines(18:0); TDCA: taurodeoxycholic acid.