BACKGROUND: Metabolic profiling of biofluid specimens is an established method for investigating disease states in clinical studies but is only recently being applied to large-scale human population studies. As part of protocol development for the UK Biobank study, a (1)H nuclear magnetic resonance (NMR)-based metabonomic analysis of specimen storage effects and analytical reproducibility was carried out using urine and serum specimens from 40 volunteers. METHODS: Aliquots of each specimen were stored for t = 0 and t = 24 h at 4 degrees C prior to freezing, and in the case of serum samples for a further 12 h (t = 36), to determine whether the storage times affected specimen composition and quality. A blinded split-specimen matching exercise was implemented to assign candidate spectral pairs stored for different times using multivariate statistical analysis of the NMR data. RESULTS: Using a chemometric strategy, split specimens at time t = 0 and t = 24 or 36 h after storage at 4 degrees C were easily paired and the split-specimen matching task was reduced to a workable size. (1)H NMR profiling established that the t = 24 h urine and serum groups showed no systematic metabolite changes, indicating biochemical stability. Some small differences in serum specimens stored for t = 36 h at 4 degrees C were detectable only by multivariate analysis, and were attributed to generalized alterations in proteins and protein fragments, and possibly trimethylamine-N-oxide. No other specific metabolite was implicated. CONCLUSIONS: For the purposes of NMR-based analysis, storage of urine and serum for up to t = 24 h at 4 degrees C does not detectably affect the metabolic profile and the methodology is robust. Future application of multivariate methods to data-rich studies should substantially enhance information recovery from epidemiological studies.
BACKGROUND: Metabolic profiling of biofluid specimens is an established method for investigating disease states in clinical studies but is only recently being applied to large-scale human population studies. As part of protocol development for the UK Biobank study, a (1)H nuclear magnetic resonance (NMR)-based metabonomic analysis of specimen storage effects and analytical reproducibility was carried out using urine and serum specimens from 40 volunteers. METHODS: Aliquots of each specimen were stored for t = 0 and t = 24 h at 4 degrees C prior to freezing, and in the case of serum samples for a further 12 h (t = 36), to determine whether the storage times affected specimen composition and quality. A blinded split-specimen matching exercise was implemented to assign candidate spectral pairs stored for different times using multivariate statistical analysis of the NMR data. RESULTS: Using a chemometric strategy, split specimens at time t = 0 and t = 24 or 36 h after storage at 4 degrees C were easily paired and the split-specimen matching task was reduced to a workable size. (1)H NMR profiling established that the t = 24 h urine and serum groups showed no systematic metabolite changes, indicating biochemical stability. Some small differences in serum specimens stored for t = 36 h at 4 degrees C were detectable only by multivariate analysis, and were attributed to generalized alterations in proteins and protein fragments, and possibly trimethylamine-N-oxide. No other specific metabolite was implicated. CONCLUSIONS: For the purposes of NMR-based analysis, storage of urine and serum for up to t = 24 h at 4 degrees C does not detectably affect the metabolic profile and the methodology is robust. Future application of multivariate methods to data-rich studies should substantially enhance information recovery from epidemiological studies.
Authors: Elizabeth J Want; Ian D Wilson; Helen Gika; Georgios Theodoridis; Robert S Plumb; John Shockcor; Elaine Holmes; Jeremy K Nicholson Journal: Nat Protoc Date: 2010-06 Impact factor: 13.491
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Authors: Helen M Moore; Andrea B Kelly; Scott D Jewell; Lisa M McShane; Douglas P Clark; Renata Greenspan; Daniel F Hayes; Pierre Hainaut; Paula Kim; Elizabeth Mansfield; Olga Potapova; Peter Riegman; Yaffa Rubinstein; Edward Seijo; Stella Somiari; Peter Watson; Heinz-Ulrich Weier; Claire Zhu; Jim Vaught Journal: J Proteome Res Date: 2011-06-21 Impact factor: 4.466
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Authors: Magda Bictash; Timothy M Ebbels; Queenie Chan; Ruey Leng Loo; Ivan K S Yap; Ian J Brown; Maria de Iorio; Martha L Daviglus; Elaine Holmes; Jeremiah Stamler; Jeremy K Nicholson; Paul Elliott Journal: J Clin Epidemiol Date: 2010-01-08 Impact factor: 6.437