Metabolite information |
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| HMDB ID | HMDB0000062 |
| Synonyms |
(-)-(R)-3-Hydroxy-4-(trimethylammonio)butyrate(-)-Carnitine(-)-L-Carnitine(R)-(3-Carboxy-2-hydroxypropyl)trimethylammonium hydroxide(R)-Carnitine(S)-Carnitine1-Carnitine3-Carboxy-2-hydroxy-N,N,N-trimethyl-1-propanaminium3-Carboxy-2-hydroxy-N,N,N-trimethyl-1-propanaminium hydroxide, inner salt3-Hydroxy-4-trimethylammoniobutanoate3-Hydroxy-4-trimethylammoniobutanoic acidBicarnesineCarnicorCarnikingCarniking 50CarnileanCarnipassCarnipass 20CarniteneCarnitineCarnitorD-CarnitineDL-CarnitineKarnitinL CarnitineL-(-)-CarnitineL-gamma-Trimethyl-beta-hydroxybutyrobetaineLevocarnitinaLevocarnitineLevocarnitinumR-(-)-3-Hydroxy-4-trimethylaminobutyrateVitamin BTdelta-Carnitinegamma-Trimethyl-ammonium-beta-hydroxybutirategamma-Trimethyl-beta-hydroxybutyrobetainegamma-Trimethyl-hydroxybutyrobetaine |
| Chemical formula | C7H15NO3 |
| IUPAC name | (3R)-3-hydroxy-4-(trimethylazaniumyl)butanoate |
| CAS registry number | 541-15-1 |
| Monoisotopic molecular weight | 161.105193351 |
Chemical taxonomy |
|
| Super class | Organic nitrogen compounds |
| Class | Organonitrogen compounds |
| Sub class | Quaternary ammonium salts |
Biological properties |
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| Pathways (Pathway Details in HMDB) |
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| Reference | Country | Specimen | Marker function | Participants (Case) | Participants (Control) | |||||||||
| Cancer type | Stage | Number | Gender (M,F) | Age mean (range) (M/F) | Smoking status | Type | Number | Gender (M,F) | Age mean (range) (M/F) | Smoking status | ||||
| Mazzone et al. 2016 | US | serum | – | adenocarcinoma, squamous cell carcinoma | I, II, III | 94 | 55.3%, 44.7% | 68.7 | – | at-risk controls | 190 | 50.5%, 49.5% | 66.2 | – |
| Yang et al. 2010 | China | urine | diagnosis | adenocarcinoma, squamous cell carcinoma | – | 35 | 23, 12 | 61.8 ± 13.3, 57.4 ± 9.8 | – | healthy | 32 | 27, 5 | 57.1 ± 9.9 / 45.6 ± 10.8 | – |
| Wu et al. 2014 | China | urine | diagnosis | NSCLC | – | 20 | 10, 10 | 38-74 | – | healthy | 20 | 10, 10 | 35-66 | – |
| Chen et al. 2015b | China | serum | – | lung cancer | – | 30 | – | 61.58 ± 10.67 | – | healthy | 30 | – | 60.35 ± 12.48 | – |
| Chen et al. 2015b | China | serum | – | lung cancer | – | 30 | – | 61.58 ± 10.67 | – | before vs. after treatment (operation) | 30 | – | 61.58 ± 10.67 | – |
| Chen et al. 2015b | China | serum | – | lung cancer (postoperative) | – | 30 | – | 61.58 ± 10.67 | – | healthy | 30 | – | 60.35 ± 12.48 | – |
| Li et al. 2015 | China | tissue | diagnosis | adenocarcinoma, squamous cell carcinoma | – | 52 | – | – | – | tumor vs. adjacent normal tissue | 21 | – | – | – |
| Callejon-Leblic et al. 2016 | Spain | bronchoalveolar lavage fluid | diagnosis | lung cancer | – | 24 | 16, 8 | 66 ± 11 | – | noncancerous lung diseases | 31 | 23, 8 | 56 ± 13 | – |
| Klupczynska et al. 2017 | Poland | serum | diagnosis | adenocarcinoma, squamous cell carcinoma | I, II | 50 | 28, 22 | 65 (53-86) | – | healthy | 25 | 14, 11 | 64 (50-78) | – |
| Moreno et al. 2018 | Spain | tissue | therapy, diagnosis | adenocarcinoma | I, II, III | 33 | 24, 9 | 62.11 ± 9.73 | – | tumor vs. adjacent normal tissue | 33 | 24, 9 | 62.11 ± 9.73 | – |
| Moreno et al. 2018 | Spain | tissue | therapy, diagnosis | squamous cell carcinoma | I, II, III | 35 | 35, 0 | 68.71 ± 7.46 | – | tumor vs. adjacent normal tissue | 35 | 35, 0 | 68.71 ± 7.46 | – |
| Callej?n-Leblic et al. 2019 | Spain | blood | diagnosis | NSCLC, SCLC | II, III, IV | 30 | 25, 5 | 67 ± 12 | former, current, non-smoker | healthy | 30 | 14, 16 | 56 ± 14 | former, non-smoker |
| Ahmed et al. 2021 | Canada | Serum | diagnosis | NSCLC pre-surgery | I, II | 32 | 12,20 | 63.8 ± 7.0 | former, current, non-smoker | NSCLC post-surgery | 32 | 12,20 | 63.8 ± 7.0 | former, current, non-smoker |
| Qi et al. 2021 | China | blood | diagnosis | adenocarcinoma, squamous cell carcinoma, small cell lung cancer, other types, unknown types | I, II, III, IV | 98 | 51, 47 | Median: 50 (32-69) | – | healthy | 75 | 36, 39 | Median: 50 (31-69) | – |
| Kowalczyk et al. 2021 | Poland | Tissue | diagnosis | squemous cell carcinoma (SCC) | I, II, III | 54 | 39, 15 | 64.45 ± 8.02 | – | healthy control | 20 | 13, 7 | 61.5 ± 12.06 | – |
| Kowalczyk et al. 2021 | Poland | Tissue | diagnosis | squemous cell carcinoma (SCC) | I, II, III | 54 | 39, 15 | 64.45 ± 8.02 | – | adenocarcinoma (ADC) | 33 | 23, 10 | 64.77 ± 8.44 | – |
| Reference | Chromatography | Ion source | Positive/Negative mode | Mass analyzer | Identification level |
| Mazzone et al. 2016 | LC | ESI | positive | linear ion-trap | MS/MS |
| Yang et al. 2010 | LC | ESI | positive | QTRAP | MS/MS |
| Wu et al. 2014 | LC | ESI | positive | Q-TOF | MS/MS |
| Chen et al. 2015b | LC | ESI | positive | Q-TOF | – |
| Chen et al. 2015b | LC | ESI | positive | Q-TOF | – |
| Chen et al. 2015b | LC | ESI | positive | Q-TOF | – |
| Li et al. 2015 | LC | AFADESI | both | Q-Orbitrap, Q-TOF | MS/MS |
| Callejon-Leblic et al. 2016 | DI | ESI | positive | Q-TOF | MS/MS |
| Klupczynska et al. 2017 | LC | ESI | positive | Q-Orbitrap | MS/MS |
| Moreno et al. 2018 | LC, GC | ESI, EI | both | LC: linear ion-trap, GC: single-quadrupole | LC: MS/MS |
| Moreno et al. 2018 | LC, GC | ESI, EI | both | LC: linear ion-trap, GC: single-quadrupole | LC: MS/MS |
| Callej?n-Leblic et al. 2019 | DI | ESI | positive | Q-TOF | MS/MS |
| Ahmed et al. 2021 | LC | ESI | both | Q-TOF | – |
| Qi et al. 2021 | LC | ESI | both | Q-Orbitrap | MS/MS |
| Kowalczyk et al. 2021 | LC | ESI | both | Q-TOF | – |
| Kowalczyk et al. 2021 | LC | ESI | both | Q-TOF | – |
| Reference | Data processing software | Database search |
| Mazzone et al. 2016 | Metabolon LIMS system | Metabolon LIMS system |
| Yang et al. 2010 | MarkerView | HMDB, KEGG, Pubchem, mass bank |
| Wu et al. 2014 | MassLynx | HMDB, metlin, lipidmaps |
| Chen et al. 2015b | Mass Hunter Qualitative Analysis Software (Agilent Technologies) | METLIN |
| Chen et al. 2015b | Mass Hunter Qualitative Analysis Software (Agilent Technologies) | METLIN |
| Chen et al. 2015b | Mass Hunter Qualitative Analysis Software (Agilent Technologies) | METLIN |
| Li et al. 2015 | Markerview (AB SCIEX) | LIPID MAPS, Massbank, HMDB, METLIN |
| Callejon-Leblic et al. 2016 | Markerview | HMDB, METLIN |
| Klupczynska et al. 2017 | MZmine 2.19 software | In-house library |
| Moreno et al. 2018 | – | KEGG, HMDB |
| Moreno et al. 2018 | – | KEGG, HMDB |
| Callej?n-Leblic et al. 2019 | – | HMDB, Metlin |
| Ahmed et al. 2021 | MassHunter, Mass Profiler Professional | HMDB, METLIN |
| Qi et al. 2021 | ProteoWizard, XCMS, Xcalibur, CAMERA | mzCloud, ChemSpider, LipidBlast and Fiehn HILIC |
| Kowalczyk et al. 2021 | Mass Hunter Qualitative Analysis Software, Mass Profiler Professional | METLIN, KEGG, LIPIDMAPS, and HMDB |
| Kowalczyk et al. 2021 | Mass Hunter Qualitative Analysis Software, Mass Profiler Professional | METLIN, KEGG, LIPIDMAPS, and HMDB |
| Reference | Difference method | Mean concentration (case) | Mean concentration (control) | Fold change (case/control) | P-value | FDR | VIP |
| Mazzone et al. 2016 | two- sample independent t test | 0.995517± 0.2106721 | 1.023201± 0.1734553 | 0.97 | 0.24 | 0.35 | – |
| Yang et al. 2010 | OSC PLS-DA | – | – | 3.70 | – | – | 1.79 |
| Wu et al. 2014 | OPLS-DA, student’s t-test | – | – | 2.83 | 0.01 | – | 2.82 |
| Chen et al. 2015b | PCA, PLS-DA, independent t test | – | – | 1.70 | 1.00e-03 | – | 1.57 |
| Chen et al. 2015b | PCA, PLS-DA, independent t test | – | – | 1.39 | 1.00e-03 | – | 1.39 |
| Chen et al. 2015b | PCA, PLS-DA, independent t test | – | – | 1.22 | 1.00e-03 | – | 1.17 |
| Li et al. 2015 | t-test, PLS-DA, OPLS-DA | – | – | – | – | – | 3.72 |
| Callejon-Leblic et al. 2016 | PLS-LDA, one-way ANOVA | – | – | 0.92 | 0.02 | – | 2.67 |
| Klupczynska et al. 2017 | t-test | – | – | 1.12 | 2.49e-03 | 0.02 | – |
| Moreno et al. 2018 | paired two-sample t-test, PLS-DA | – | – | 0.83 | 0.01 | 0.03 | – |
| Moreno et al. 2018 | paired two-sample t-test, PLS-DA | – | – | 0.76 | 1.28e-05 | 2.71e-05 | – |
| Callej?n-Leblic et al. 2019 | PCA, PLS-DA, one-way ANOVA | – | – | 1.44 | 2.00e-04 | – | 2.11 |
| Ahmed et al. 2021 | Pair t-test | – | – | 3.00 | <0.0001 | – | – |
| Qi et al. 2021 | PCA, OPLS-DA, Student’s t test | – | – | 1.17 | 2.17e-06 | – | 8.75 |
| Kowalczyk et al. 2021 | Mann–Whitney U-test and Benjamini–Hochberg false discovery rate, partial least squares discriminant analysis (PLS-DA) | – | – | – | 0.02 | – | – |
| Kowalczyk et al. 2021 | Mann–Whitney U-test and Benjamini–Hochberg false discovery rate, partial least squares discriminant analysis (PLS-DA) | – | – | – | 0.02 | – | – |
| Reference | Classification method | Cutoff value | AUROC 95%CI | Sensitivity (%) | Specificity (%) | Accuracy (%) |
| Mazzone et al. 2016 | – | – | – | – | – | – |
| Yang et al. 2010 | – | – | – | – | – | – |
| Wu et al. 2014 | ROC curve analysis | – | Carnitine+Acylcarnitine C3+Acylcarnitine C7:1+Acylcarnitine C8:2+Acylcarnitine C8:1+Acylcarnitine C8+Acylcarnitine C9:1+Acylcarnitine C10:3+Acylcarnitine C10:3+[Acylcarnitine C10:2+OH]+[Acylcarnitine C10:1+OH]+Acylcarnitine C12:4=0.958 (0.902-1.013) Taurine+Hippuric Acid+Tyrosine+Uric Acid+Carnitine+Acylcarnitine C3+Acylcarnitine C7:1+Acylcarnitine C8:2+Acylcarnitine C8:1+Acylcarnitine C8+Acylcarnitine C9:1+Acylcarnitine C10:3+Acylcarnitine C10:3+[Acylcarnitine C10:2+OH]+[Acylcarnitine C10:1+OH]+Acylcarnitine C12:4=1.000 (1.000-1.000) | – | – | – |
| Chen et al. 2015b | – | – | – | – | – | – |
| Chen et al. 2015b | – | – | – | – | – | – |
| Chen et al. 2015b | – | – | – | – | – | – |
| Li et al. 2015 | ROC curve analysis | – | – | – | – | – |
| Callejon-Leblic et al. 2016 | ROC curve analysis | – | 0.87 | – | – | – |
| Klupczynska et al. 2017 | ROC curve analysis (Monte-Carlo cross validation) | – | 0.656 (0.511–0.776) | 0.52 | 0.76 | – |
| Moreno et al. 2018 | – | – | – | – | – | – |
| Moreno et al. 2018 | – | – | – | – | – | – |
| Callej?n-Leblic et al. 2019 | ROC curve | – | 0.73 | – | – | – |
| Ahmed et al. 2021 | – | – | – | – | – | – |
| Qi et al. 2021 | – | – | – | – | – | – |
| Kowalczyk et al. 2021 | – | – | – | – | – | – |
| Kowalczyk et al. 2021 | – | – | – | – | – | – |