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A doctor with a pregnant woman during a medical consultation in a gynecological office, showing some medical schemes for understanding of the pregnancy. The image is cropped so there are no faces seen.

 

Maternal smoking has consistently been linked to low baby birthweight. Using a Provost’s Undergraduate Research Award (PURA), Richard Xu, a computer science and molecular and cellular biology double major, is trying to find out how the fetus’s genome and epigenome interact to affect birthweight when pregnant women smoke.

“Given that the genome and epigenome are intertwined, this line of research, if successful, may lead to exciting discoveries at the crossroads of genome, epigenome and environment, with implications for understanding and preventing many important pediatric and adult diseases,” said Xu, a fourth year student who is working under the guidance of Hongkai Ji, professor of biostatistics in the Johns Hopkins Bloomberg School of Public Health. His faculty advisers are Michael Schatz, Bloomberg Distinguished Associate Professor of Computer Science and Biology and Kyle Cunningham, professor of biology.

To date, there is no established method to integrate genome, epigenome, and the environment and to assess their effects on health outcomes. Xu plans to first apply established statistical methods to conduct a genome-wide search to identify novel gene-smoking interactions and gene-methylation interactions on offspring birthweight.

He also plans to assess the mediation and interaction of gene variants and methylation on the smoking-birthweight association. In addition to conventional genome-wide and epigenome-wide association analyses, Xu will use machine learning and other advanced statistical methods to bring the multi-dimensional big data together to shed light on the genomic-epigenomic interactions contributing to low birthweight.

Xu has been involved in a wide range of research projects dating back to high school, including summers spent in remote areas in China assisting with implementing clinical trials to help prevent stroke. His roles ranged from field team data collection, and data management and cleaning, to data analysis and manuscript preparation—work that led to Xu’s co-authoring paper in The American Journal of Clinical Nutrition. In the past year, he has worked with a multidisciplinary team in both the Bloomberg School of Public Health and the Whiting School of Engineering, resulting in his first-authored paper which is currently under revision for publication in Clinical Epigenetics.

Thanks to these diverse experiences, Xu realizes that improving population health requires knowledge from many disciplines and collaborative teamwork.

“I am inspired to leverage my double majors and continue to acquire essential knowledge and skills in order to harness big and complex data, so that my work may help advance human health at both the personal and population level,” he said.