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.