The plasma proteome identifies expected and novel proteins correlated with micronutrient status in undernourished nepalese children.
J Nutr. 2013 Oct;143(10):1540-8. doi: 10.3945/jn.113.175018. Epub 2013 Aug 21.
Cole RN, Ruczinski I, Schulze K, Christian P, Herbrich S, Wu L, Devine LR, O'Meally RN, Shrestha S, Boronina TN, Yager JD, Groopman J, West KP Jr.
Mass Spectrometry and Proteomics Core Facility.
Micronutrient deficiencies are common in undernourished societies yet remain inadequately assessed due to the complexity and costs of existing assays. A plasma proteomics-based approach holds promise in quantifying multiple nutrient:protein associations that reflect biological function and nutritional status. To validate this concept, in plasma samples of a cohort of 500 6- to 8-y-old Nepalese children, we estimated cross-sectional correlations between vitamins A (retinol), D (25-hydroxyvitamin D), and E (α-tocopherol), copper, and selenium, measured by conventional assays, and relative abundance of their major plasma-bound proteins, measured by quantitative proteomics using 8-plex iTRAQ mass tags.
The prevalence of low-to-deficient status was
- 8.8% (<0.70 μmol/L) for retinol,
- 19.2% (<50 nmol/L) for 25-hydroxyvitamin D,
- 17.6% (<9.3 μmol/L) for α-tocopherol,
- 0% (<10 μmol/L) for copper, and
- 13.6% (<0.6 μmol/L) for selenium.
We identified 4705 proteins, 982 in >50 children.
Employing a linear mixed effects model, we observed the following correlations:
- retinol:retinol-binding protein 4 (r = 0.88),
- 25-hydroxyvitamin D:vitamin D-binding protein (r = 0.58),
- α-tocopherol:apolipoprotein C-III (r = 0.64),
- copper:ceruloplasmin (r = 0.65), and
- selenium:selenoprotein P isoform 1 (r = 0.79) (all P < 0.0001),
passing a false discovery rate threshold of 1% (based on P value-derived q values). Individual proteins explained 34-77% (R(2)) of variation in their respective nutrient concentration. Adding second proteins to models raised R(2) to 48-79%, demonstrating a potential to explain additional variation in nutrient concentration by this strategy. Plasma proteomics can identify and quantify protein biomarkers of micronutrient status in undernourished children. The maternal micronutrient supplementation trial, from which data were derived as a follow-up activity, was registered at clinicaltrials.gov as NCT00115271.
FIGURE 2 Plasma 25-hydroxyvitamin D and VDBP relative abundance distributions in Nepalese children 6–8 y of age (n= 500). (A) Frequency distribution of 25-hydroxyvitamin D concentrations: range, 18.6–173.5 nmol/L, 19.2% (n= 96) deficient (,50 nmol/L,dark gray), and 80.8% (n=404,medium gray) adequate ($50 nmol/L) in status. (B,C) Plasma 25-hydroxyvitamin D by relative abundance of VDBP by traditional master plasma pool normalization and LME-adjusted methods, respectively (see Fig. 1 for details). LME, linear mixed effects (model); VDBP, vitamin D binding protein; 25(OH)D, 25-hydroxyvitamin D.
Vitamin D status was measured by an immunoassay method that captures total 25-hydroxyvitamin D, a conventional bio-marker of vitaminD intake and photoproduction, and the major ligand for VDBP. Although strongly correlated with VDBP (r= 0.56), the relatively low observed variation in plasma vitamin 25-hydroxyvitamin D explained by VDBP (34%) may be because VDBP circulates in concentrations 100-fold >25-hydroxyvitamin D, binds to other vitamin D metabolites, and has many non-vitamin D-related functions such as actin scavenging and fatty acid binding (37). Our findings demonstrate a need to find other vitamin D-networked proteins to increase explained variance and strengthen the potential to predict vitamin D status. The glycoprotein plexin-D1 entered our model, raising explained variance to 48%.
Interestingly, although it was observed in only 23% of samples, plexin-D1 exhibited a stronger correlation with 25-hydroxyvitamin D than did VDBP (Table 1). Plexin-D1 is a member of transmembrane surface receptors that transduce pleiotropic signals of semaphorins, widely involved in genesis and maintenance of neural, vascular, immune, and osteoid tissues (38–40). Metabolic linkages between plexin-D1 and vitamin D have not been established but are plausible given the roles of both plexins and vitamin D metabolites in skeletal (39–41), immune (39,42,43), angiogenic, and vascular (39,44–46) development and homeostasis.
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Thus: measurement of just Vitamin D Binding Protein + glycoprotein plexin-D1 allows an OK estimation of Vitamin D level.
VitaminDWiki guesses that future versions of this test will allow an estimation within + - 20%, which would be quite acceptable