TY - JOUR
T1 - Recommendations and Standardization of Biomarker Quantification Using NMR-based Metabolomics with Particular Focus on Urinary Analysis
AU - Emwas, Abdul-Hamid M.
AU - Roy, Raja
AU - McKay, Ryan T.
AU - Ryan, Danielle
AU - Brennan, Lorraine
AU - Tenori, Leonardo
AU - Luchinat, Claudio
AU - Gao, Xin
AU - Zeri, Ana Carolina
AU - Gowda, G. A. Nagana
AU - Raftery, Daniel
AU - Steinbeck, Christoph
AU - Salek, Reza M
AU - Wishart, David S.
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2016/1/20
Y1 - 2016/1/20
N2 - NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to non-destructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Indeed, precise metabolite quantification is a necessary prerequisite to move any chemical biomarker or biomarker panel from the lab into the clinic. Among the many biofluids (urine, serum, plasma, cerebrospinal fluid and saliva) commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, easily obtained, needs little sample preparation and does not require any invasive medical procedures for collection. Furthermore, urine captures and concentrates many “unwanted” or “undesirable” compounds throughout the body, thereby providing a rich source of potentially useful disease biomarkers. However, the incredible variation in urine chemical concentrations due to effects such as gender, age, diet, life style, health conditions, and physical activity make the analysis of urine and the identification of useful urinary biomarkers by NMR quite challenging. In this review, we discuss a number of the most significant issues regarding NMR-based urinary metabolomics with a specific emphasis on metabolite quantification for disease biomarker applications. We also propose a number of data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, as well as recommendations regarding sample preparation and biomarker assessment.
AB - NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to non-destructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Indeed, precise metabolite quantification is a necessary prerequisite to move any chemical biomarker or biomarker panel from the lab into the clinic. Among the many biofluids (urine, serum, plasma, cerebrospinal fluid and saliva) commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, easily obtained, needs little sample preparation and does not require any invasive medical procedures for collection. Furthermore, urine captures and concentrates many “unwanted” or “undesirable” compounds throughout the body, thereby providing a rich source of potentially useful disease biomarkers. However, the incredible variation in urine chemical concentrations due to effects such as gender, age, diet, life style, health conditions, and physical activity make the analysis of urine and the identification of useful urinary biomarkers by NMR quite challenging. In this review, we discuss a number of the most significant issues regarding NMR-based urinary metabolomics with a specific emphasis on metabolite quantification for disease biomarker applications. We also propose a number of data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, as well as recommendations regarding sample preparation and biomarker assessment.
UR - http://hdl.handle.net/10754/593365
UR - http://pubs.acs.org/doi/10.1021/acs.jproteome.5b00885
UR - http://www.scopus.com/inward/record.url?scp=84957637000&partnerID=8YFLogxK
U2 - 10.1021/acs.jproteome.5b00885
DO - 10.1021/acs.jproteome.5b00885
M3 - Article
C2 - 26745651
SN - 1535-3893
VL - 15
SP - 360
EP - 373
JO - Journal of Proteome Research
JF - Journal of Proteome Research
IS - 2
ER -