Figures & data
Table 1. Urinary metabolic profiling studies used for noninvasive diagnosis of different types of cancer.
Table 2. Urinary metabolic profiling studies used for noninvasive diagnosis of metabolic disorders and in born errors of metabolism.
Table 3. Urinary metabolic profiling studies used for noninvasive diagnosis of miscellaneous diseases and disorders.
Table 4. Salivary metabolic profiling studies used for noninvasive diagnosis of different diseases and disorders.
Table 5. Metabolic profiling studies using exhaled breath for noninvasive diagnosis of different diseases and disorders.
Table 6. Metabolic profiling studies using feces for noninvasive diagnosis of different diseases and disorders.
Frickenschmidt A
, FrohlichH, BullingerDet al. Metabonomics in cancer diagnosis: mass spectrometry-based profiling of urinary nucleosides from breast cancer patients. Biomarkers13(4), 435–449 (2008).
Fan X
, BaiJ, ShenP. Diagnosis of breast cancer using HPLC metabonomics fingerprints coupled with computational methods. Conf. Proc. IEEE Eng. Med. Biol. Soc.6, 6081–6084 (2005).
Jung J
, JungY, BangEJet al. Noninvasive diagnosis and evaluation of curative surgery for gastric cancer by using NMR-based metabolomic profiling. Annals Surg. Oncol.21(Suppl. 4), S736–S742 (2014).
Furina RR
, RyzhkovVL, MitrakovaNNet al. [The method for early diagnosis of the gastric cancer based metabolomics research]. Eksp. Klin. Gastroenterol.10, 14–17 (2014).
Yang J
, XuG, ZhengYet al. Diagnosis of liver cancer using HPLC-based metabonomics avoiding false-positive result from hepatitis and hepatocirrhosis diseases. J. Chromatogr. B. Anal. Technol. Biomed. Life Sci.813(1–2), 59–65 (2004).
Wang WZ
, ZhaoXJ, LiX, ChenJ, LiFL, XuGW. [Lung cancer diagnosis based on urinary modified nucleoside metabolic profiling]. Zhongguo Yi Xue Ke Xue Yuan Xue Bao.29(6), 738–741 (2007).
Duarte IF
, RochaCM, GilAM. Metabolic profiling of biofluids: potential in lung cancer screening and diagnosis. Expert Rev. Mol. Diag.13(7), 737–748 (2013).
Cao DL
, YeDW, ZhangHL, ZhuY, WangYX, YaoXD. A multiplex model of combining gene-based, protein-based, and metabolite-based with positive and negative markers in urine for the early diagnosis of prostate cancer. Prostate71(7), 700–710 (2011).
Kosmides AK
, KamisogluK, CalvanoSE, CorbettSA, AndroulakisIP. Metabolomic fingerprinting: challenges and opportunities. Crit. Rev. Biomed. Eng.41(3), 205–221 (2013).
Shinka T
, InoueY, PengH, Zhen-WeiX, OseM, KuharaT. Urine screening of five-day-old newborns: metabolic profiling of neonatal galactosuria. J. Chromatogr. B Biomed. Sci. Appl.732(2), 469–477 (1999).
Wang M
, YangX, RenLet al. Biomarkers identified by urinary metabonomics for noninvasive diagnosis of nutritional rickets. J. Proteome Res.13(9), 4131–4142 (2014).
Kouremenos KA
, PittJ, MarriottPJ. Metabolic profiling of infant urine using comprehensive two-dimensional gas chromatography: Application to the diagnosis of organic acidurias and biomarker discovery. J. Chromatogr. A1217(1), 104–111 (2010).
Xiong X
, ShengX, LiuD, ZengT, PengY, WangY. A GC/MS-based metabolomic approach for reliable diagnosis of phenylketonuria. Anal. Bioanal. Chem.407(29), 8825–8833 (2015).
Wei H
, PasmanW, RubinghCet al. Urine metabolomics combined with the personalized diagnosis guided by Chinese medicine reveals subtypes of pre-diabetes. Mol. Biosyst.8(5), 1482–1491 (2012).
Hou LJ
, WangHW, WeiXXet al. Urinary metabonomics for diagnosis of depression in hepatitis B virus-infected patients. Iran. Red Crescent Med. J.17(4), e27359 (2015).
Pike AW
, KleinJL, GotlinRW, FennesseyPV. The role of steroid metabolic profiling as an aid in the diagnosis of familial precocious puberty, a subgroup of true precocious puberty. J. Inherit. Metabol. Dis.9(2), 147–155 (1986).
Austdal M
, TangerasLH, SkrastadRBet al. First trimester urine and serum metabolomics for prediction of preeclampsia and gestational hypertension: a prospective screening study. Int. J. Mol. Sci.16(9), 21520–21538 (2015).
Godoy MM
, LopesEP, SilvaROet al. Hepatitis C virus infection diagnosis using metabonomics. J. Viral Hepatitis17(12), 854–858 (2010).
Blydt-Hansen TD
, SharmaA, GibsonIW, MandalR, WishartDS. Urinary metabolomics for noninvasive detection of borderline and acute T cell-mediated rejection in children after kidney transplantation. Am. J. Transplant.14(10), 2339–2349 (2014).
De Preter V
. Metabolomics in the clinical diagnosis of inflammatory bowel disease. Digest. Dis.33(Suppl. 1), 2–10 (2015).
Van QN
, KloseJR, LucasDAet al. The use of urine proteomic and metabonomic patterns for the diagnosis of interstitial cystitis and bacterial cystitis. Dis. Markers19(4–5), 169–183 (2003).
Priori R
, ScrivoR, BrandtJet al. Metabolomics in rheumatic diseases: the potential of an emerging methodology for improved patient diagnosis, prognosis, and treatment efficacy. Autoimmun. Rev.12(10), 1022–1030 (2013).
Lam CW
, LawCY, ToKKet al. NMR-based metabolomic urinalysis: a rapid screening test for urinary tract infection. Clin. Chim. Acta436, 217–223 (2014).
Lam CW
, LawCY, SzeKH, ToKK. Quantitative metabolomics of urine for rapid etiological diagnosis of urinary tract infection: evaluation of a microbial-mammalian co-metabolite as a diagnostic biomarker. Clin. Chim. Acta438, 24–28 (2015).
Sugimoto M
, WongDT, HirayamaA, SogaT, TomitaM. Capillary electrophoresis mass spectrometry-based saliva metabolomics identified oral, breast and pancreatic cancer-specific profiles. Metabolomics6(1), 78–95 (2010).
Mikkonen JJ
, SinghSP, HerralaM, LappalainenR, MyllymaaS, KullaaAM. Salivary metabolomics in the diagnosis of oral cancer and periodontal diseases. J. Periodontal Res. doi:10.1111/jre.12327 (2015) ( Epub ahead of print).
Bertram HC
, EggersN, EllerN. Potential of human saliva for nuclear magnetic resonance-based metabolomics and for health-related biomarker identification. Anal. Chem.81(21), 9188–9193 (2009).
Zhang A
, SunH, WangX. Saliva metabolomics opens door to biomarker discovery, disease diagnosis, and treatment. Appl. Biochem. Biotechnol.168(6), 1718–1727 (2012).
Cuevas-Cordoba B
, Santiago-GarciaJ. Saliva: a fluid of study for OMICS. Omics18(2), 87–97 (2014).
Ai JY
, SmithB, WongDT. Bioinformatics advances in saliva diagnostics. Int. J. Oral Sci.4(2), 85–87 (2012).
Wei J
, XieG, ZhouZet al. Salivary metabolite signatures of oral cancer and leukoplakia. Int. J. Cancer129(9), 2207–2217 (2011).
Mangler M
, FreitagC, LanowskaM, StaeckO, SchneiderA, SpeiserD. Volatile organic compounds (VOCs) in exhaled breath of patients with breast cancer in a clinical setting. Ginekol. Pol.83(10), 730–736 (2012).
Li J
, PengY, LiuYet al. Investigation of potential breath biomarkers for the early diagnosis of breast cancer using gas chromatography-mass spectrometry. Clin. Chim. Acta436, 59–67 (2014).
de Laurentiis G
, ParisD, MelckDet al. Metabonomic analysis of exhaled breath condensate in adults by nuclear magnetic resonance spectroscopy. Eur. Respir. J.32(5), 1175–1183 (2008).
Basanta M
, JarvisRM, XuYet al. Non-invasive metabolomic analysis of breath using differential mobility spectrometry in patients with chronic obstructive pulmonary disease and healthy smokers. Analyst135(2), 315–320 (2010).
Montuschi P
, ParisD, MelckDet al. NMR spectroscopy metabolomic profiling of exhaled breath condensate in patients with stable and unstable cystic fibrosis. Thorax67(3), 222–228 (2012).
Monge ME
, PerezJJ, DwivediPet al. Ion mobility and liquid chromatography/mass spectrometry strategies for exhaled breath condensate glucose quantitation in cystic fibrosis studies. Rapid Comm. Mass Spec.27(20), 2263–2271 (2013).
Qin T
, LiuH, SongQet al. The screening of volatile markers for hepatocellular carcinoma. Cancer Epidemiol. Biomark. Prev.19(9), 2247–2253 (2010).
Krilaviciute A
, HeissJA, LejaM, KupcinskasJ, HaickH, BrennerH. Detection of cancer through exhaled breath: a systematic review. Oncotarget6(36), 38643–38657 (2015).
Lamote K
, NackaertsK, Van MeerbeeckJP. Strengths, weaknesses, and opportunities of diagnostic breathomics in pleural mesothelioma-a hypothesis. Cancer Epidemiol. Biomark. Prev.23(6), 898–908 (2014).
Montuschi P
, ParisD, MontellaSet al. Nuclear magnetic resonance-based metabolomics discriminates primary ciliary dyskinesia from cystic fibrosis. Am. J. Respir. Crit. Care Med.190(2), 229–233 (2014).
de Laurentiis G
, ParisD, MelckDet al. Separating smoking-related diseases using NMR-based metabolomics of exhaled breath condensate. J. Proteome Res.12(3), 1502–1511 (2013).
Ahmed I
, GreenwoodR, Costello BdeL, RatcliffeNM, ProbertCS. An investigation of fecal volatile organic metabolites in irritable bowel syndrome. PLoS ONE8(3), e58204 (2013).
Le Gall G
, NoorSO, RidgwayKet al. Metabolomics of fecal extracts detects altered metabolic activity of gut microbiota in ulcerative colitis and irritable bowel syndrome. J. Proteome Res.10(9), 4208–4218 (2011).
Walker A
, LucioM, PfitznerBet al. Importance of sulfur-containing metabolites in discriminating fecal extracts between normal and Type-2 diabetic mice. J. Proteome Res.13(10), 4220–4231 (2014).