Lupo, Philip J PHD

Children with Down syndrome (DS) have a higher burden of many co-occurring conditions including 1) structural birth defects, which are associated with significant morbidity and mortality; 2) abnormal hematopoiesis, which includes a 20-fold increased risk of acute leukemia; and 3) neurodevelopmental disorders, which significantly impact functional independence and quality of life. Important gaps in knowledge limit health supervision guidelines and targets for intervention. In this application, we seek to address these gaps by leveraging the Texas Birth Defects Registry, one of the world’s largest and most diverse population-based active birth defects surveillance systems, to develop the Down syndrome Early Childhood Omics, Deep phenotyping, and Epidemiology In Texas: DECODE IT Cohort to include >1,000 children with DS, representing a diverse population historically excluded from DS research.

Children with Down syndrome (DS), which occurs due to trisomy 21, have a 20-fold increased risk of acute lymphoblastic leukemia (ALL), but the basis for the increased risk of leukemia remains unclear, including the potential interplay between other DS phenotypic features and ALL susceptibility. This study will build upon our previous genome-wide association study, as well as our ongoing genomic profiling and phenotyping efforts, to: 1) perform a comprehensive analysis of heritable variation associated with risk of ALL in children with DS, with a focus on structural, rare, and chromosome 21 variants; and 2) conduct deep phenotyping of children with DS-ALL to identify the impact of DS-related phenotypes on leukemia susceptibility and outcomes. Findings from this study may lead to improved genetic testing and counseling strategies for children with DS, and insights into genes driving DS-ALL may guide development of targeted therapies to improve outcomes in this vulnerable and high-risk patient population.

In our prior work, we have identified multiple novel congenital anomaly-cancer associations by linking data from population-based birth-defects and cancer registries from four states. Here, we propose to expand this study to seven additional states to analyze a cohort representing >25 million live births and approximately 35% of the US population. We will also search for genetic mechanisms driving these associations through the analysis of whole-genome sequencing data in 20,000 children with congenital anomalies or pediatric cancer, including 2000 sequenced tumors.