Random Field Modelling of genetic and epigenetic association underlying congenital heart defects in the presence of disease heterogeneity

Project Summary/Abstract This proposal is submitted for an extension of the NHLBI K01 award, entitled ?Random field modeling of genetic and epigenetic associations for congenital heart defects in the presence of disease heterogeneity?. Dr.

Ming Li is the principal investigator of this study, and is within the final year of this K01 award (01/01/2018 ? 12/31/2021). In the past year, Dr.

Li?s research team has experienced substantial research interruptions and additional administrative responsibilities due to the COVID-19 pandemic. This extension is expected to provide Dr. Li the necessary time to complete the ongoing K01 projects and to make successfully transition to future R01 studies.

Dr.

Li?s career goal is to become an independent statistical geneticist and genetic epidemiologist in cardiovascular diseases, particularly in congenital heart defects (CHDs). In the past three years, Dr.

Li has been developing innovative biostatistical methods for detecting genetic and epigenetic factors associated with the risk of CHDs.

The proposed methods are being applied to samples from the National Birth Defect Prevention Study (NBDPS), the largest multi-site population-based study of birth defects ever conducted. So far, substantial progresses have been made with a number of key findings published in peer-review journals.

Additional findings were also presented at the major conferences and submitted for publications, but also experienced delays largely due to COVID-19 interruptions.

These results have provided insights into the underlying pathophysiological and etiological processes that result in CHDs, and will also serve as a foundation for Dr. Li to make propose additional R01 studies.

The future R01 studies will mainly be focused on two aspects: 1) to apply the newly developed biostatical methods to other existing NHLBI data sources, such as the Pediatric Cardiac Genomics Consortium (PCGC) and Trans-Omics for Precision Medicine (TOPMed); and 2) to further develop innovative biostatistical methods for disease prediction and precision intervention based on the genetic, epigenetic, transcriptional and maternal lifestyle profiles.

The continuation of this research will integrate data sources across NIH institutions (i.e.

NICHD and NHLBI), and also may provide a direction for translational research leading to more precise preconceptional counseling and interventions.

Such research directions are also consistent with NHLBI?s emphasized research areas as described in multiple notices of special interests (e.g. NOT-HL-20-815).