Integrated chromosomal microarray analysis and whole-exome sequencing in prenatal diagnosis of congenital hearts disease with maternal diabetes: a novel insight into gene environment interaction.

OBJECTIVES

To assess the diagnostic efficacy of integrated chromosomal microarray analysis (CMA) and whole-exome sequencing (WES) in prenatal CHD diagnosis among diabetic pregnancies and examine potential gene-environment interactions affecting cardiac morphogenesis.

MATERIAL AND

METHODS

This prospective investigation enrolled 160 diabetic gravidae (Type 1, Type 2, or gestational) whose fetuses demonstrated CHD on echocardiography. All specimens underwent both CMA and WES analyses. Maternal glycemic parameters were quantified, with HbA1c stratified as < 6.5%, 6.5-8.0%, or > 8.0%. Genetic findings were correlated with CHD severity and glycemic control. A multivariate risk prediction model was constructed.

RESULTS

Molecular analysis identified pathogenic variants in 87 cases (54.4%): 27 (16.9%) via CMA, 38 (23.8%) via WES, and 22 (13.8%) through both methodologies. Detection rates varied significantly across diabetes subtypes (66.7%, 54.2%, 50.0% for Type 1, Type 2, and gestational diabetes, respectively; p = 0.039). Cardiac transcription factor genes demonstrated significant enrichment in severe CHD (p = 0.011). Notably, fetuses harboring identical genetic variants exposed to poor glycemic control (HbA1c > 8.0%) exhibited significantly higher rates of severe CHD compared with adequately controlled cohorts (p = 0.033). Even in genetically negative specimens, severe CHD prevalence correlated directly with hyperglycemia (p = 0.003). The combined risk prediction model achieved AUC = 0.771.

CONCLUSIONS

Concurrent implementation of CMA and WES substantially enhances diagnostic yield in prenatal CHD detection associated with maternal diabetes. Our data demonstrates significant gene-environment interactions wherein maternal hyperglycemia potentiates phenotypic expression of cardiac developmental gene variants, elucidating pathogenetic mechanisms and supporting individualized risk stratification.