{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T01:27:48Z","timestamp":1780450068986,"version":"3.54.1"},"reference-count":43,"publisher":"MDPI AG","issue":"14","license":[{"start":{"date-parts":[[2021,7,8]],"date-time":"2021-07-08T00:00:00Z","timestamp":1625702400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Collezione Nazionale di Composti Chimici e Centro Screening (CNCCS) Consortium","award":["Project B, Sp 2, WP2, 2019"],"award-info":[{"award-number":["Project B, Sp 2, WP2, 2019"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Molecules"],"abstract":"<jats:p>A new strategy that takes advantage of the synergism between NMR and UHPLC\u2013HRMS yields accurate concentrations of a high number of compounds in biofluids to delineate a personalized metabolic profile (SYNHMET). Metabolite identification and quantification by this method result in a higher accuracy compared to the use of the two techniques separately, even in urine, one of the most challenging biofluids to characterize due to its complexity and variability. We quantified a total of 165 metabolites in the urine of healthy subjects, patients with chronic cystitis, and patients with bladder cancer, with a minimum number of missing values. This result was achieved without the use of analytical standards and calibration curves. A patient\u2019s personalized profile can be mapped out from the final dataset\u2019s concentrations by comparing them with known normal ranges. This detailed picture has potential applications in clinical practice to monitor a patient\u2019s health status and disease progression.<\/jats:p>","DOI":"10.3390\/molecules26144167","type":"journal-article","created":{"date-parts":[[2021,7,8]],"date-time":"2021-07-08T21:05:54Z","timestamp":1625778354000},"page":"4167","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Personalized Metabolic Profile by Synergic Use of NMR and HRMS"],"prefix":"10.3390","volume":"26","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9449-9820","authenticated-orcid":false,"given":"Greta","family":"Petrella","sequence":"first","affiliation":[{"name":"Department of Chemical Science and Technology, University of Rome \u201cTor Vergata\u201d, 00133 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7721-4961","authenticated-orcid":false,"given":"Camilla","family":"Montesano","sequence":"additional","affiliation":[{"name":"Chemistry Department, University of Rome \u201cSapienza\u201d, 00185 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sara","family":"Lentini","sequence":"additional","affiliation":[{"name":"Department of Chemical Science and Technology, University of Rome \u201cTor Vergata\u201d, 00133 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Giorgia","family":"Ciufolini","sequence":"additional","affiliation":[{"name":"Department of Chemical Science and Technology, University of Rome \u201cTor Vergata\u201d, 00133 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Domitilla","family":"Vanni","sequence":"additional","affiliation":[{"name":"Department of Chemical Science and Technology, University of Rome \u201cTor Vergata\u201d, 00133 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7309-0703","authenticated-orcid":false,"given":"Roberto","family":"Speziale","sequence":"additional","affiliation":[{"name":"IRBM S.p.A., 00071 Pomezia, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrea","family":"Salonia","sequence":"additional","affiliation":[{"name":"Urological Research Institute, IRCCS Ospedale San Raffaele, 20132 Milan, Italy"},{"name":"Division of Experimental Oncology, URI Urological Research Institute, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Francesco","family":"Montorsi","sequence":"additional","affiliation":[{"name":"Urological Research Institute, IRCCS Ospedale San Raffaele, 20132 Milan, Italy"},{"name":"Division of Experimental Oncology, URI Urological Research Institute, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Vincenzo","family":"Summa","sequence":"additional","affiliation":[{"name":"IRBM S.p.A., 00071 Pomezia, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3781-6770","authenticated-orcid":false,"given":"Riccardo","family":"Vago","sequence":"additional","affiliation":[{"name":"Urological Research Institute, IRCCS Ospedale San Raffaele, 20132 Milan, Italy"},{"name":"Division of Experimental Oncology, URI Urological Research Institute, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5430-9965","authenticated-orcid":false,"given":"Laura","family":"Orsatti","sequence":"additional","affiliation":[{"name":"IRBM S.p.A., 00071 Pomezia, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Edith","family":"Monteagudo","sequence":"additional","affiliation":[{"name":"IRBM S.p.A., 00071 Pomezia, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5012-1714","authenticated-orcid":false,"given":"Daniel Oscar","family":"Cicero","sequence":"additional","affiliation":[{"name":"Department of Chemical Science and Technology, University of Rome \u201cTor Vergata\u201d, 00133 Rome, Italy"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2021,7,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s11306-005-1102-8","article-title":"Metabolomics: Building on a century of biochemistry to guide human health","volume":"1","author":"German","year":"2005","journal-title":"Metabolomics"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1016\/0009-8981(90)90228-K","article-title":"Diagnosis of alcaptonuria: Rapid analysis of homogentisic acid by HPLC","volume":"189","author":"Bory","year":"1990","journal-title":"Clin. Chim. Acta."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1819","DOI":"10.1152\/physrev.00035.2018","article-title":"Metabolomics for investigating physiological and pathophysiological processes","volume":"99","author":"Wishart","year":"2019","journal-title":"Physiol. Rev."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4017","DOI":"10.1021\/acs.jproteome.8b00567","article-title":"Combining Mass Spectrometry and NMR Improves Metabolite Detection and Annotation","volume":"17","author":"Bhinderwala","year":"2018","journal-title":"J. Proteome Res."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"473","DOI":"10.1038\/nrd.2016.32","article-title":"Emerging applications of metabolomics in drug discovery and precision medicine","volume":"15","author":"Wishart","year":"2016","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.trac.2011.08.009","article-title":"Metabolite identification and quantitation in LC-MS\/MS-based metabolomics","volume":"32","author":"Xiao","year":"2012","journal-title":"TrAC\u2014Trends Anal. Chem."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"391","DOI":"10.1007\/s11306-014-0704-4","article-title":"Combining DI-ESI\u2013MS and NMR datasets for metabolic profiling","volume":"11","author":"Marshall","year":"2015","journal-title":"Metabolomics"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.pnmrs.2017.01.001","article-title":"Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics","volume":"100","author":"Marshall","year":"2017","journal-title":"Prog. Nucl. Magn. Reson. Spectrosc."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.cca.2016.10.037","article-title":"Assessment of 1H NMR-based metabolomics analysis for normalization of urinary metals against creatinine","volume":"464","author":"Nair","year":"2017","journal-title":"Clin. Chim. Acta."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Teul, J., Deja, S., Celi\u0144ska-Janowicz, K., Z\u0105bek, A., M\u0142ynarz, P., Bar\u0107, P., Junka, A., Smutnicka, D., Bartoszewicz, M., and Pa\u0142ka, J. (2020). LC-QTOF-MS and 1H NMR Metabolomics Verifies Potential Use of Greater Omentum for Klebsiella pneumoniae Biofilm Eradication in Rats. Pathogens., 9.","DOI":"10.3390\/pathogens9050399"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Hanifa, M.A., Skott, M., Maltesen, R.G., Rasmussen, B.S., Nielsen, S., Fr\u00f8ki\u00e6r, J., Ring, T., and Wimmer, R. (2020). Tissue, urine and serum NMR metabolomics dataset from a 5\/6 nephrectomy rat model of chronic kidney disease. Data Br., 33.","DOI":"10.1016\/j.dib.2020.106567"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Trimigno, A., Khakimov, B., Savorani, F., Poulsen, S.K., Astrup, A., Dragsted, L.O., and Engelsen, S.B. (2020). Human urine 1H NMR metabolomics reveals alterations of the protein and carbohydrate metabolism when comparing habitual Average Danish diet vs. healthy New Nordic diet. Nutrition, 79\u201380.","DOI":"10.1016\/j.nut.2020.110867"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1245","DOI":"10.1007\/s11010-020-03987-1","article-title":"Testosterone deficiency accelerates early stage atherosclerosis in miniature pigs fed a high-fat and high-cholesterol diet: Urine 1H NMR metabolomics targeted analysis","volume":"476","author":"Deng","year":"2020","journal-title":"Mol. Cell. Biochem."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Alinaghi, M., Nguyen, D.N., Bertram, H.C., and Sangild, P.T. (2020). Direct implementation of intestinal permeability test in nmr metabolomics for simultaneous biomarker discovery\u2014a feasibility study in a preterm piglet model. Metabolites, 10.","DOI":"10.3390\/metabo10010022"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Gu, H., Pan, Z., Xi, B., Hainline, B.E., Shanaiah, N., Asiago, V., Gowda, G.A.N., and Raftery, D. (2009). 1H NMR metabolomics study of age profiling in children. NMR Biomed.","DOI":"10.1002\/nbm.1395"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Bouatra, S., Aziat, F., Mandal, R., Guo, A.C., Wilson, M.R., Knox, C., Bjorndahl, T.C., Krishnamurthy, R., Saleem, F., and Liu, P. (2013). The Human Urine Metabolome. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0073076"},{"key":"ref_17","first-page":"363","article-title":"Statistical Heterospectroscopy, an Approach to the Integrated Analysis of NMR and UPLC-MS Data Sets: Application in Metabonomic Toxicology Studies","volume":"9","author":"Nicholson","year":"2004","journal-title":"Nat. Rev. Drug Discov."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1839","DOI":"10.4155\/bio-2017-0214","article-title":"Matrix effects and application of matrix effect factor","volume":"9","author":"Zhou","year":"2017","journal-title":"Bioanalysis"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"426","DOI":"10.1093\/clinchem\/30.3.426","article-title":"Use of high-resolution proton nuclear magnetic resonance spectroscopy for rapid multi-component analysis of urine","volume":"30","author":"Bales","year":"1984","journal-title":"Clin. Chem."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1256","DOI":"10.1093\/clinchem\/44.6.1256","article-title":"Paraquat-induced renal injury studied by 1H nuclear magnetic resonance spectroscopy of urine","volume":"44","author":"Bairaktari","year":"1998","journal-title":"Clin. Chem."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"547","DOI":"10.1016\/j.jchromb.2009.01.007","article-title":"Normalization strategies for metabonomic analysis of urine samples","volume":"877","author":"Warrack","year":"2009","journal-title":"J. Chromatogr. B"},{"key":"ref_22","first-page":"171","article-title":"Comparison of Uncertainties Related to Standardization of Urine Samples with Volume and Creatinine Concentration","volume":"48","author":"Garde","year":"2004","journal-title":"Ann. Occup. Hyg."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"924","DOI":"10.1373\/clinchem.2004.032292","article-title":"Comparison of Specific Gravity and Creatinine for Normalizing Urinary Reproductive Hormone Concentrations","volume":"50","author":"Miller","year":"2004","journal-title":"Clin. Chem."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1093\/occmed\/kqr084","article-title":"Creatinine adjustment of biological monitoring results","volume":"61","author":"Cocker","year":"2011","journal-title":"Occup. Med."},{"key":"ref_25","unstructured":"(2021, June 14). World Health Organization Biological Monitoring of Chemical Exposure in the Workplace: Guidelines. Available online: https:\/\/apps.who.int\/iris\/bitstream\/handle\/10665\/41856\/WHO_HPR_OCH_96.1.pdf;jsessionid=31E4ACD0F4E0FF269122167B8C89C255?sequence=1."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1038\/s41585-019-0185-3","article-title":"Cancer metabolomic markers in urine: Evidence, techniques and recommendations","volume":"16","author":"Dinges","year":"2019","journal-title":"Nat. Rev. Urol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.csbj.2016.02.005","article-title":"A guide to the identification of metabolites in NMR-based metabonomics\/metabolomics experiments","volume":"14","author":"Dona","year":"2016","journal-title":"Comput. Struct. Biotechnol. J."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1007\/s11306-011-0366-4","article-title":"Missing values in mass spectrometry based metabolomics: An undervalued step in the data processing pipeline","volume":"8","author":"Hrydziuszko","year":"2012","journal-title":"Metabolomics"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Wittmann, B.M., Stirdivant, S.M., Mitchell, M.W., Wulff, J.E., McDunn, J.E., Li, Z., Dennis-Barrie, A., Neri, B.P., Milburn, M.V., and Lotan, Y. (2014). Bladder cancer biomarker discovery using global metabolomic profiling of urine. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0115870"},{"key":"ref_30","unstructured":"(2021, July 01). A Community-Built Calibration System._ The Case Study of Quantification of Metabolites in Grape Juice by qNMR Spectroscopy | Elsevier Enhanced Reader. Available online: https:\/\/reader.elsevier.com\/reader\/sd\/pii\/S0039914020301466?token=498612BB72768CFBAFAB5F1CBEB76F7FE71A646F8304AF18A6E6004E28A988B6AB22E44F8F1F6035B6F24C6C9DB984D9&originRegion=eu-west-1&originCreation=20210701143417."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"820","DOI":"10.1053\/j.ajkd.2013.12.006","article-title":"GFR estimation: From physiology to public health","volume":"63","author":"Levey","year":"2014","journal-title":"Am. J. Kidney Dis."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"999","DOI":"10.1177\/0192623318800709","article-title":"Traditional Renal Biomarkers and New Approaches to Diagnostics","volume":"46","author":"Nabity","year":"2018","journal-title":"Toxicol. Pathol."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1177\/1091581818819791","article-title":"Investigating the Value of Urine Volume, Creatinine, and Cystatin C for Urinary Biomarkers Normalization for Drug Development Studies","volume":"38","author":"Adedeji","year":"2019","journal-title":"Int. J. Toxicol."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"D608","DOI":"10.1093\/nar\/gkx1089","article-title":"HMDB 4.0: The human metabolome database for 2018","volume":"46","author":"Wishart","year":"2018","journal-title":"Nucleic Acids Res."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Li, B., He, X., Jia, W., and Li, H. (2017). Novel Applications of Metabolomics in Personalized Medicine: A Mini-Review. Molecules, 22.","DOI":"10.3390\/molecules22071173"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1007\/s11306-019-1555-9","article-title":"Recognition of early and late stages of bladder cancer using metabolites and machine learning","volume":"15","author":"Kouznetsova","year":"2019","journal-title":"Metabolomics"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"766","DOI":"10.3945\/jn.114.205476","article-title":"Urine excretion of caffeine and select caffeine metabolites is common in the US population and associated with caffeine intake","volume":"145","author":"Rybak","year":"2015","journal-title":"J. Nutr."},{"key":"ref_38","first-page":"159","article-title":"Five caffeine metabolite ratios to measure tobacco-induced CYP1A2 activity and their relationships with urinary mutagenicity and urine flow","volume":"8","author":"Lanuza","year":"1999","journal-title":"Cancer Epidemiol. Biomarkers Prev."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"784","DOI":"10.1016\/j.eururo.2018.09.001","article-title":"Epidemiology of Bladder Cancer: A Systematic Review and Contemporary Update of Risk Factors in 2018","volume":"74","author":"Cumberbatch","year":"2018","journal-title":"Eur. Urol."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2850","DOI":"10.1016\/j.jacc.2016.09.972","article-title":"The Emerging Role of Metabolomics in the Diagnosis and Prognosis of Cardiovascular Disease","volume":"68","author":"Ussher","year":"2016","journal-title":"J. Am. Coll. Cardiol."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1039\/b818802e","article-title":"An optimized buffer system for NMR-based urinary metabonomics with effective pH control, chemical shift consistency and dilution minimization","volume":"134","author":"Xiao","year":"2009","journal-title":"Analyst"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2692","DOI":"10.1038\/nprot.2007.376","article-title":"Metabolic profiling, metabolomic and metabonomic procedures for NMR spectroscopy of urine, plasma, serum and tissue extracts","volume":"2","author":"Beckonert","year":"2007","journal-title":"Nat. Protocols"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1002\/cmr.a.20223","article-title":"How the 1D-NOESY suppresses solvent signal in metabonomics NMR spectroscopy: An examination of the pulse sequence components and evolution","volume":"38 A","author":"Mckay","year":"2011","journal-title":"Concepts Magn. Reson. Part A Bridg. Educ. Res."}],"container-title":["Molecules"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1420-3049\/26\/14\/4167\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:28:03Z","timestamp":1760164083000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1420-3049\/26\/14\/4167"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,7,8]]},"references-count":43,"journal-issue":{"issue":"14","published-online":{"date-parts":[[2021,7]]}},"alternative-id":["molecules26144167"],"URL":"https:\/\/doi.org\/10.3390\/molecules26144167","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-442781\/v1","asserted-by":"object"}]},"ISSN":["1420-3049"],"issn-type":[{"value":"1420-3049","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,7,8]]}}}