New research “library” may show patterns in congenital heart defects

Up to 1.3 million Americans are currently living with congenital heart defects – which can cause a wide array of life-altering health problems – and nearly 100 new babies are born with heart defects every day in the U.S. alone. But what bothers Texas A&M Health Science Center researcher Dr. Vincent VanBuren even more is that 85 out of the 100 predicted defects have no known cause. Most defects caused by chromosomal abnormalities or single genes have likely been identified, VanBuren says, making those that remain among the hardest to pin down. To aid in the search for answers, VanBuren’s team have developed a dataset library for future researchers, revealed this month in the peer-reviewed journal PLOS ONE, that sketches a lineup of likely suspects for these devastating abnormalities.

Baby having heart checked

A tool developed by researchers at the Texas A&M Health Science Center College of Medicine will aid future research on congenital heart defects, a disease that affects 40,000 newborns each year in the U.S. alone.

“These defects remain a mystery, because it is difficult to study the effects of multiple variables at once,” VanBuren said. “Most of these remaining defects are caused by a more complicated set of factors than a single gene defect.” So he set out to compare patterns of gene behavior that might offer clues since such patterns may only appear after collating a large amount of data from many different studies.

VanBuren has spent his academic career devising ways to use computer programming to interpret complex data sets. In the mid-2000s, he led a team that developed StarNet, a web-based tool that enables scientists to simply point and click to explore similarities in results across a vast number of research studies. VanBuren saw an opportunity to use StarNet to analyze the interplay among thousands of genes that could be producing holes or other abnormalities in the heart chambers.

A team of researchers and coders spent four years collecting data from 239 experiments and writing software to track patterns in gene expression. The software identified clusters of genes likely to be working together in heart development. It also identified the proteins that are key in triggering swells of activity across genes.

Using VanBuren’s StarNet tool and the new overlap of genes shown in the data sets, researchers can now quickly access a library of data and well-informed hypotheses to begin filling in the gaps about how the heart is formed.

“Doing so will ultimately identify opportunities for medical interventions that can better address or even prevent these life-altering heart defects.”

Learn more about opportunities for collaboration or VanBuren’s research in computational systems biology.

, , , No Comment