Showing information for HMDB0002712 ('1,5-anhydroglucitol', '1,5-anhydrosorbitol')


Metabolite information

HMDB ID HMDB0002712
Synonyms
1,5-AG
1,5-Anhydroglucitol
1,5-anhydro-D-Glucitol
1,5-anhydro-D-Sorbitol
1-Deoxyglucose
Adult-onset diabetes
Csf
Cytoplasma
Niddm
Non-insulin-dependent diabetes mellitus
Prostate gland
Chemical formula C6H12O5
IUPAC name
(2R,3S,4R,5S)-2-(hydroxymethyl)oxane-3,4,5-triol
CAS registry number 154-58-5
Monisotopic molecular weight 164.068473494

Chemical taxonomy

Super class Organic oxygen compounds
Class Organooxygen compounds
Sub class Carbohydrates and carbohydrate conjugates

Biological properties

Pahtways
Author-emphasized biomarker in the paper(s)

Lung cancer metabolomics studies that identify HMDB0002712 ('1,5-anhydroglucitol', '1,5-anhydrosorbitol')


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
Roś-Mazurczyk et al. 2017 serum diagnosis adenocarcinoma, squamous cell carcinoma I, II, III 31 17, 14 52-72 healthy 92 52, 40 52-73
Fahrmann et al. 2015 plasma diagnosis adenocarcinoma I, II, III, IV 52 17, 35 65.9 ± 9.66 healthy 31 11, 20 64.1 ± 8.97
Fahrmann et al. 2015 serum diagnosis adenocarcinoma I, II, III, IV 49 17, 32 65.9 ± 9.87 healthy 31 11, 20 64.1 ± 8.97
Miyamoto et al. 2015 blood diagnosis NSCLC, SCLC, mesothelioma, secondary metastasis to lung I, II, III, IV 11 4, 7 67 (61-73) / 67 (47-76) smoker, non-smoker healthy 11 5, 6 69 (61-83) / 54 (44-61) unknown
Miyamoto et al. 2015 blood diagnosis adenocarcinoma unknown (mostly late stage) 18 10, 8 67 (50-85) / 62 (53-72) former, current healthy 20 8, 12 64 (49-80) / 66 (58-82) former, current
Moreno et al. 2018 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
Mazzone et al. 2016 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
Fahrmann et al. 2015 serum diagnosis adenocarcinoma I, II, III, IV 43 21, 22 67.3 ± 10.10 healthy 43 21, 22 65.9 ± 8.05
Moreno et al. 2018 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
Fahrmann et al. 2015 plasma diagnosis adenocarcinoma I, II, III, IV 43 21, 22 67.3 ± 10.10 healthy 43 21, 22 65.9 ± 8.05
Wikoff et al. 2015b tissue diagnosis adenocarcinoma I 39 15, 24 72.33 ± 8.78 smoker, non-smoker tumor vs. adjacent normal tissue 39 15, 24 72.33 ± 8.78 smoker, non-smoker
Reference Chromatography Ion source Positive/Negative mode Mass analyzer Identification level
Roś-Mazurczyk et al. 2017 GC TOF In-source fragmentation
Fahrmann et al. 2015 GC EI TOF
Fahrmann et al. 2015 GC EI TOF
Miyamoto et al. 2015 GC EI TOF MS/MS
Miyamoto et al. 2015 GC EI TOF MS/MS
Moreno et al. 2018 LC, GC ESI, EI positive, negative LC: linear ion‐trap, GC: single‐quadrupole LC: MS/MS
Mazzone et al. 2016 GC EI quadrupole MS/MS
Fahrmann et al. 2015 GC EI TOF
Moreno et al. 2018 LC, GC ESI, EI positive, negative LC: linear ion‐trap, GC: single‐quadrupole LC: MS/MS
Fahrmann et al. 2015 GC EI TOF
Wikoff et al. 2015b GC EI TOF
Reference Data processing software Database search
Roś-Mazurczyk et al. 2017 Leco ChromaTOF-GC Replib, Mainlib and Fiehn libraries
Fahrmann et al. 2015 UC Davis Metabolomics BinBase database
Fahrmann et al. 2015 UC Davis Metabolomics BinBase database
Miyamoto et al. 2015 ChromaTOF software (Leco) UC Davis Metabolomics BinBase database
Miyamoto et al. 2015 ChromaTOF software (Leco) UC Davis Metabolomics BinBase database
Moreno et al. 2018 KEGG, HMDB
Mazzone et al. 2016 Metabolon LIMS system Metabolon LIMS system
Fahrmann et al. 2015 UC Davis Metabolomics BinBase database
Moreno et al. 2018 KEGG, HMDB
Fahrmann et al. 2015 UC Davis Metabolomics BinBase database
Wikoff et al. 2015b BinBase NIST11, BinBase
Reference Difference method Mean concentration (case) Mean concentration (control) Fold change (case/control) P-value FDR VIP
Roś-Mazurczyk et al. 2017 two-sample T test, U Mann-Whitney test, Benjamini-Hochberg approach 11.743 ± 7.108 11.998 ± 8.638 0.978746457742957 0.79547 0.85012
Fahrmann et al. 2015 regress (by the covariates: age, gender and smoking history [packs per year]), permutation test 10848 ± 5435 11979 ± 5203 0.91 0.64 0.874
Fahrmann et al. 2015 regress (by the covariates: age, gender and smoking history [packs per year]), permutation test 11324 ± 4806 13410 ± 5674 0.84 0.635 0.819
Miyamoto et al. 2015 Analysis of Covariance 92187.8181818182 88164 1.04564014996845 0.531017589459075
Miyamoto et al. 2015 Analysis of Covariance 95587.3888888889 85305.45 1.12053085575293 0.437208228389904
Moreno et al. 2018 paired two‐sample t‐test, PLS-DA 0.937942913871908 0.150430427248231 0.205728839756926
Mazzone et al. 2016 two- sample independent t test 1.0200968± 0.3469864 0.9498011± 0.3815291 1.07401096924398 0.1331728 0.230609873
Fahrmann et al. 2015 regress (by the covariates: age, gender and smoking history [packs per year]), permutation test 12259 ± 6475 15142 ± 7933 0.81 0.053 0.265
Moreno et al. 2018 paired two‐sample t‐test, PLS-DA 0.933325701515037 0.0389948811741565 0.0506806436107116
Fahrmann et al. 2015 regress (by the covariates: age, gender and smoking history [packs per year]), permutation test 6630 ± 3591 8125 ± 3432 0.82 0.017 0.102
Wikoff et al. 2015b OPLS-DA 1.2 0.037
Reference Classification method Cutoff value AUROC 95%CI Sensitivity (%) Specificity (%) Accuracy (%)
Roś-Mazurczyk et al. 2017 ROC curve
Fahrmann et al. 2015 random forest
Fahrmann et al. 2015 random forest
Miyamoto et al. 2015
Miyamoto et al. 2015
Moreno et al. 2018
Mazzone et al. 2016
Fahrmann et al. 2015 random forest
Moreno et al. 2018
Fahrmann et al. 2015 random forest
Wikoff et al. 2015b