Potential of the Plasma Nutriproteome to Predict Micronutrient Distributions in Undernourished Settings

Abstract

Objectives: Micronutrient deficiencies are common but remain ‘hidden' due to difficulty of assessment.  We explored the plasma proteome to identify nutrient-correlated biomarkers that may predict multiple micronutrient status and deficiencies, possibly on a single platform in the future.  Methods: We measured, in 500 6-8 year old Nepalese children, plasma concentrations of >20 vitamin/mineral indicators and acute phase proteins (APP) by conventional assays, and relative abundance of proteins by quantitative mass spectrometry, bioinformatics and linear mixed effects models (Herbrich S et al, 2012; Cole R et al, 2013). We identified ~980 proteins in >10% of subjects, and evaluated their strength of correlation with micronutrient and APP distributions. Comparisons were corrected for multiple comparisons, with a 10% threshold for false discoveries. Results: 142 proteins were correlated with plasma retinol, 6 with 25(OH) vitamin D, 119 with α-tocopherol, 12 with γ-tocopherol, 6 with PIVKA-II (reflecting vitamin K status), 89 for vitamin B6, 35 for ferritin and 7 for transferrin receptor (reflecting iron status), 232 for copper, 3 for selenium and none for folate, thyroglobulin (reflecting iodine status) or vitamin B12 (q>0.1 for all comparisons).  Initial models with up to 6 covariates suggest an ability to explain 60-80% of the variation (R2) in retinol, α-tocopherol, vitamin B6 and copper, ~50% of the variation in ferritin and, the carotenoid, β-cryptoxanthin and 80-85% of variation in CRP and AGP. Other nutrient-protein models will be presented. Conclusions: Plasma nutrient-correlated proteomes exist that, with absolute quantification of candidate proteins, could provide a basis for multiple micronutrient status assessment of populations in the future.