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Showing information for HMDB0000163 ('maltose')

Metabolite information
HMDB ID	HMDB0000163
Synonyms	1-alpha-D-Glucopyranosyl-4-alpha-D-glucopyranose 1-alpha-delta-Glucopyranosyl-4-alpha-delta-glucopyranose 4-O-a-D-Glucopyranosyl-D-glucose 4-O-a-D-Glucopyranosyl-a-D-mannopyranose 4-O-alpha-D-Glucopyranosyl-D-glucopyranose 4-O-alpha-D-Glucopyranosyl-D-glucose 4-O-alpha-D-Glucopyranosyl-alpha-D-mannopyranose 4-O-alpha-delta-Glucopyranosyl-delta-glucopyranose 4-O-alpha-delta-Glucopyranosyl-delta-glucose 4-O-α-D-glucopyranosyl-α-D-mannopyranose 4-[alpha-D-glucopyranosido]-alpha-Glucopyranose 4-[alpha-D-glucosido]-D-Glucose 4-[alpha-delta-glucopyranosido]-alpha-Glucopyranose 4-[alpha-delta-glucosido]-delta-Glucose Advantose 100 Cextromaltose Coffee Coffee bean Cucurbits Cytoplasma D-[+]-Maltose Digestion Extracellular region Faecal Faeces Fauna Fecal Finetose Finetose F Flora Gourds Gramineae Kidneys Legume Madoros Malt sugar Maltobiose Maltodiose Maltos Maltose Maltose HH Maltose HHH Maltose solution Malzzucker Martos-10 Papilionoideae Pd Soy Soya Soya bean Soybean Stool Sunmalt Sunmalt S Thrombocyte alpha-D-GLCP-[1->4]-D-GLCP alpha-D-Glucopyranosyl-[1->4]-D-glucopyranose alpha-D-Glucopyranosyl-[1->4]-D-glucose alpha-Malt sugar alpha-delta-GLCP-[1->4]-delta-GLCP alpha-delta-Glucopyranosyl-[1->4]-delta-glucopyranose alpha-delta-Glucopyranosyl-[1->4]-delta-glucose delta-Maltose delta-[+]-Maltose
Chemical formula	C12H22O11
IUPAC name	(2R,3S,4S,5R,6R)-2-(hydroxymethyl)-6-{[(2R,3S,4R,5S,6S)-4,5,6-trihydroxy-2-(hydroxymethyl)oxan-3-yl]oxy}oxane-3,4,5-triol
CAS registry number	69-79-4
Monisotopic molecular weight	342.116211546
Chemical taxonomy
Super class	Organic oxygen compounds
Class	Organooxygen compounds
Sub class	Carbohydrates and carbohydrate conjugates
Biological properties
Pahtways	Glycogen synthetase deficiency Glycogenosis, Type III. Cori disease, Debrancher glycogenosis Glycogenosis, Type IV. Amylopectinosis, Anderson disease Glycogenosis, Type VI. Hers disease Mucopolysaccharidosis VI. Sly syndrome Starch and Sucrose Metabolism Sucrase-isomaltase deficiency
Author-emphasized biomarker in the paper(s)	Fahrmann et al. 2015

Lung cancer metabolomics studies that identify HMDB0000163 ('maltose')

Reference	Country	Specimen	Marker function	Participants (Case)						Participants (Control)
Reference	Country	Specimen	Marker function	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	–	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	–
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
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	–
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	–
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	–
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
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	–
Sun et al. 2019	–	serum	diagnosis	lung cancer	I, II, III, IV	31	21, 10	54.1 ± 9.9	smoker, non-smoker	healthy	29	15, 14	52.1 ± 14.6	smoker, non-smoker
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	–
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	–
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
Mazzone et al. 2016	GC	EI	–	quadrupole	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
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
Miyamoto et al. 2015	GC	EI	–	TOF	MS/MS
Fahrmann et al. 2015	GC	EI	–	TOF	–
Sun et al. 2019	GC	–	–	–	–
Fahrmann et al. 2015	GC	EI	–	TOF	–
Fahrmann et al. 2015	GC	EI	–	TOF	–
Wikoff et al. 2015b	GC	EI	–	TOF	–

Reference	Data processing software	Database search
Mazzone et al. 2016	Metabolon LIMS system	Metabolon LIMS system
Miyamoto et al. 2015	ChromaTOF software (Leco)	UC Davis Metabolomics BinBase database
Moreno et al. 2018	–	KEGG, HMDB
Fahrmann et al. 2015	–	UC Davis Metabolomics BinBase database
Moreno et al. 2018	–	KEGG, HMDB
Miyamoto et al. 2015	ChromaTOF software (Leco)	UC Davis Metabolomics BinBase database
Fahrmann et al. 2015	–	UC Davis Metabolomics BinBase database
Sun et al. 2019	–	BinBase, KEGG
Fahrmann et al. 2015	–	UC Davis Metabolomics BinBase database
Fahrmann et al. 2015	–	UC Davis Metabolomics BinBase database
Wikoff et al. 2015b	BinBase	NIST11, BinBase

Differential analysis
Classification analysis

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	0.6658766± 0.5577826	0.6572626± 0.5734163	1.01310587275162	0.9043071	0.790949301	–
Miyamoto et al. 2015	Analysis of Covariance	1061.45454545455	988.636363636364	1.07365517241379	0.818579605509709	–	–
Moreno et al. 2018	paired two‐sample t‐test, PLS-DA	–	–	0.774640260300949	0.147937057880348	0.203587361785181	–
Fahrmann et al. 2015	regress (by the covariates: age, gender and smoking history [packs per year]), permutation test	183 ± 200	132 ± 169	1.38	0.078	0.258	–
Moreno et al. 2018	paired two‐sample t‐test, PLS-DA	–	–	0.753318032428868	0.0476639483358995	0.0614472225719673	–
Miyamoto et al. 2015	Analysis of Covariance	1297.5	779.95	1.66356817744727	0.0131538257068894	–	–
Fahrmann et al. 2015	regress (by the covariates: age, gender and smoking history [packs per year]), permutation test	375 ± 480	198 ± 85	1.89	0.004	0.117	–
Sun et al. 2019	Student t test, PLS-DA	–	–	1.71977997334083	0.000228	0.002408	0.51667
Fahrmann et al. 2015	regress (by the covariates: age, gender and smoking history [packs per year]), permutation test	309 ± 262	139 ± 73	2.218	0	0.001	–
Fahrmann et al. 2015	regress (by the covariates: age, gender and smoking history [packs per year]), permutation test	704 ± 718	326 ± 302	2.16	0	0.015	–
Wikoff et al. 2015b	OPLS-DA	–	–	1.6	–	0.47	–

Reference	Classification method	Cutoff value	AUROC 95%CI	Sensitivity (%)	Specificity (%)	Accuracy (%)
Mazzone et al. 2016	–	–	–	–	–	–
Miyamoto et al. 2015	–	–	–	–	–	–
Moreno et al. 2018	–	–	–	–	–	–
Fahrmann et al. 2015	random forest	–	0.617 (0.496, 0.738) maltose+maltotriose+cystine+3-Phosphoglycerate+citrulline=0.699 (0.583, 0.815) maltose+maltotriose+cystine+3-Phosphoglycerate+citrulline+pyrophosphate+tryptophan+adenosine-5-Phosphate=0.670 (0.552, 0.789)	55.8	69.8	62.8
Moreno et al. 2018	–	–	–	–	–	–
Miyamoto et al. 2015	–	–	–	–	–	–
Fahrmann et al. 2015	random forest	–	–	–	–	–
Sun et al. 2019	ROC curve analysis	–	–	–	–	–
Fahrmann et al. 2015	random forest	–	–	–	–	–
Fahrmann et al. 2015	random forest	–	0.741 (0.629, 0.853) maltose+maltotriose+cystine+3-Phosphoglycerate+citrulline=0.880 (0.805, 0.954) maltose+maltotriose+cystine+3-Phosphoglycerate+citrulline+pyrophosphate+tryptophan+adenosine-5-Phosphate=0.883 (0.812, 0.955)	–	–	72.3
Wikoff et al. 2015b	–	–	–	–	–	–