A landmark study published in Nature Genetics has uncovered a genetic variant that significantly influences how the human body metabolizes vitamin A, shedding light on why certain populations experience higher rates of deficiency despite similar dietary intakes. The international research team, led by scientists at the University of Cambridge and the University of Cape Town, analyzed genomic data from over 45,000 individuals across diverse ethnic groups and identified a mutation in the BCMO1 gene that reduces the conversion of plant-based beta-carotene into active vitamin A by up to 70%.
This finding carries profound implications for global nutrition strategies. Vitamin A deficiency affects an estimated 190 million preschool-aged children worldwide, primarily in sub-Saharan Africa and South Asia, and is a leading cause of preventable childhood blindness and immune dysfunction. While conventional solutions have focused on supplementation programs and food fortification, this research demonstrates that genetic factors may explain why some communities derive less benefit from plant-based sources like sweet potatoes and leafy greens—staples of many food security initiatives.
The study employed cutting-edge metabolomic profiling to track vitamin A metabolites in participants with different BCMO1 variants. Those carrying the inefficient variant showed markedly lower retinol levels even when consuming equivalent amounts of beta-carotene-rich foods. Notably, the mutation was found in 40-60% of populations in South Asia and Africa, compared to just 10-15% in European cohorts.
Dr. Priya Nair, lead author of the study, emphasized the practical applications: “This discovery means we need to rethink blanket recommendations about plant sources of vitamin A. For populations with high prevalence of this variant, pre-formed vitamin A from animal products or supplements may be far more effective.” The research team is now collaborating with public health agencies to develop targeted screening tools that could identify at-risk individuals and optimize nutrition interventions based on genetic profiles.
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