Origins of the 2009 H1N1 influenza pandemic in swine in Mexico
- Icahn School of Medicine at Mount Sinai, United States
- National Institutes of Health, United States
- Laboratorio Avi-Mex, Mexico
Abstract
Asia is considered an important source of influenza A virus (IAV) pandemics, owing to large, diverse viral reservoirs in poultry and swine. However, the zoonotic origins of the 2009 A/H1N1 influenza pandemic virus (pdmH1N1) remain unclear, due to conflicting evidence from swine and humans. There is strong evidence that the first human outbreak of pdmH1N1 occurred in Mexico in early 2009. However, no related swine viruses have been detected in Mexico or any part of the Americas, and to date the most closely related ancestor viruses were identified in Asian swine. Here, we use 58 new whole-genome sequences from IAVs collected in Mexican swine to establish that the swine virus responsible for the 2009 pandemic evolved in central Mexico. This finding highlights how the 2009 pandemic arose from a region not considered a pandemic risk, owing to an expansion of IAV diversity in swine resulting from long-distance live swine trade.
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Origins of the 2009 H1N1 influenza pandemic in swine in Mexico
eLife 5:e16777.
https://doi.org/10.7554/eLife.16777
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Background: The role of circulating metabolites on child development is understudied. We investigated associations between children's serum metabolome and early childhood development (ECD).
Methods: Untargeted metabolomics was performed on serum samples of 5,004 children aged 6-59 months, a subset of participants from the Brazilian National Survey on Child Nutrition (ENANI-2019). ECD was assessed using the Survey of Well-being of Young Children's milestones questionnaire. The graded response model was used to estimate developmental age. Developmental quotient (DQ) was calculated as the developmental age divided by chronological age. Partial least square regression selected metabolites with a variable importance projection ≥ 1. The interaction between significant metabolites and the child's age was tested.
Results: Twenty-eight top-ranked metabolites were included in linear regression models adjusted for the child's nutritional status, diet quality, and infant age. Cresol sulfate (β = -0.07; adjusted-p < 0.001), hippuric acid (β = -0.06; adjusted-p < 0.001), phenylacetylglutamine (β = -0.06; adjusted-p < 0.001), and trimethylamine-N-oxide (β = -0.05; adjusted-p = 0.002) showed inverse associations with DQ. We observed opposite directions in the association of DQ for creatinine (for children aged -1 SD: β = -0.05; p =0.01; +1 SD: β = 0.05; p =0.02) and methylhistidine (-1 SD: β = - 0.04; p =0.04; +1 SD: β = 0.04; p =0.03).
Conclusion: Serum biomarkers, including dietary and microbial-derived metabolites involved in the gut-brain axis, may potentially be used to track children at risk for developmental delays.
Funding: Supported by the Brazilian Ministry of Health and the Brazilian National Research Council.
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