Amirthagowri Ambalavanan

This paper investigates how interactions between infant polygenic risk and maternal human milk components predict childhood atopy, finding that integrating these factors improves prediction accuracy.

ESNA detects higher-order genetic interactions using genome-wide SNP data, identifying 914 SNP network modules associated with respiratory outcomes in children.

The paper investigates how human milk components interact with infant genomics to affect gut microbiota and risk of childhood asthma and atopy.

This study identifies persistent DNA methylation changes linked to prenatal NO2 exposure in early childhood and links some changes to wheeze and atopy.