Br J Nutr. 2011 Jan;105(1):71-9. Epub 2010 Aug 23.
Elnenaei MO, Chandra R, Mangion T, Moniz C.
Clinical Biochemistry Department, King's College Hospital, Denmark Hill, London SE5 9RS, UK.
Inter-individual response differences to vitamin D and Ca supplementation may be under genetic control through vitamin D and oestrogen receptor genes, which may influence their absorption and/or metabolism. Metabolomic studies on blood and urine from subjects supplemented with Ca and vitamin D reveal different metabolic profiles that segregate with genotype. Genotyping was performed for oestrogen receptor 1 gene (ESR1) and vitamin D receptor gene (VDR) in fifty-six postmenopausal women.
Thirty-six women were classified as low bone density as determined by a heel ultrasound scan and twenty women had normal bone density acting as 'controls'.
Those with low bone density (LBD) were supplemented with oral Ca and vitamin D and were classified according to whether they were 'responders' or 'non-responders' according to biochemical results before and after therapy compared to controls receiving no supplementation.
Metabolomic studies on serum and urine were done for the three groups at 0 and 3 months of therapy using NMR spectroscopy with pattern recognition.
The 'non-responder' group showed a higher frequency of polymorphisms in the ESR1 (codons 10 and 325) and VDR (Bsm1 and Taq1), compared with to the 'responders'. The wild-type genotype for Fok1 was more frequent in those with LBD (70 %) compared with the control group (10 %).
Distinctive patterns of metabolites were displayed by NMR studies at baseline and 3 months of post-treatment, segregating responders from non-responders and controls. Identification of potential 'non-responders' to vitamin D and Ca, before therapy, based on a genomic and/or metabolomic profile would allow targeted selection of optimal therapy on an individual basis.
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Clipped from http://www.metabolomics.ca/
To date, the HMP has identified and quantified (i.e. determined the normal concentration ranges for) 309 metabolites in CSF, 1122 metabolites in serum, 458 metabolites in urine and approximately 300 metabolites in other tissues and biofluids. Clearly more concentration data would be desirable and this is one of the long term goals of the HMP and other affiliated metabolomic projects around the world.
Metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind" - specifically, the study of their small-molecule metabolite profiles.1 The metabolome represents the collection of all metabolites in a biological cell, tissue, organ or organism, which are the end products of cellular processes2. Thus, while mRNA gene expression data and proteomic analyses do not tell the whole story of what might be happening in a cell, metabolic profiling can give an instantaneous snapshot of the physiology of that cell. One of the challenges of systems biology and functional genomics is to integrate proteomic, transcriptomic, and metabolomic information to give a more complete picture of living organisms.