Padmaja Subbarao

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.

The paper conducts a multi-ancestry, trans-generational GWAS meta-analysis of gestational diabetes and glycemic traits, identifying novel loci and highlighting limited pregnancy-specific genetic effects.

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

This study shows that breast milk extracellular vesicles from mothers with asthma differentially modulate cytokine release by airway smooth muscle cells depending on the donor and recipient cell type.

RAMEN dissects gene-environment contributions to DNA methylome variability in cord blood, finding genetics explains the largest proportion of DNAme variance.

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

CellsPickMe improves blood cell deconvolution in longitudinal DNA methylation studies by integrating cord and adult references, enhancing accuracy across developmental stages.

The paper develops a DNA methylation score to quantify the impact of maternal smoking on newborn health outcomes in European and South Asian populations, finding consistent associations with smaller birth size and lower birth weight.

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

Maternal consumption of non-nutritive sweeteners during pregnancy increases adiposity and insulin resistance in mouse and human offspring.