UWM data expert helps crack genetic code of disease

A University of Wisconsin-Milwaukee researcher is part of an international team that published a paper in the prestigious journal Nature Genetics on Monday, identifying 17 new genetic variations associated with heart disease.

Paul Auer, an assistant professor of biostatistics in UWM's Joseph J. Zilber School of Public Health, uses mathematics and computers to sift through genomic datasets and find mutations that help scientists better understand and advance disease prevention and treatment.

In the study published Monday, Auer and his fellow researchers searched the genetic data for 20 known risk factors for heart disease, such as raised levels of cholesterol or hemoglobin in the blood. Using data from previous studies, they then created a detailed map that the scientific community can freely access, called a dense imputation panel.

The panel holds so much detail, it can fill in the gaps or “impute” data missing from lower resolution genetic studies — much like a dense overlay placed over a sparse map, Auer explained in an interview.

The research team used the detailed map to identify 17 new human genetic variations associated with heart disease risk factors. Sixteen of the 17 would have been extremely difficult to find without the level of data provided by the new map, and six of them were rare, according to the scientific paper.

The map allowed the scientists to search for genetic variations that are much less frequent than ever before, but that individually explain a greater genetic risk, according to the Sanger Institute.

Once a mutation is identified, pharmaceutical companies can develop drugs to target the protein attached to the gene, and alter the progression of the disease, Auer said.

Genetics have been implicated in cardiovascular and blood diseases for some time, but because these diseases are complex, specific genetic causes are extremely difficult to find. Genetic studies have helped researchers identify protein targets for statins that treat cholesterol, for example.

In the new study, scientists looked at where in the genome the 17 new variations associated with heart disease risk factors lie to see what they revealed about changes they make to the body, and how that could make a person more or less susceptible to disease.

The new study shows how large-scale genomic datasets can be used to help identify potential novel biological targets for studying cardiovascular and other diseases, according to Nicole Soranzo of the Sanger Institute in Cambridge England. Auer and Soranzo were the study's senior authors.

"As efforts continue to characterize the genetic underpinnings of complex diseases, the methods we have developed in this study are expected to enable the next wave of discoveries of what causes these diseases, and how we might develop new treatment,” Soranzo explained.

While the study focused on traits linked to heart disease, the panel covers the entire human genome, according to Auer.  So it could be used to glean a deeper understanding of genetic contributions to disease in any part of the human body, he said.

"Our study provides a refined method to use the panel alongside other analysis techniques to find rare variants that contribute to complex genetic conditions like heart disease or diabetes," Auer said. “We have also narrowed down the number of variants that are potential causes to a smaller set that we can follow up on further,” he said.

In addition to Auer and Soranzo, Valentina Iotchkova of the Sanger Institute and the European Bioinformatics Institute was a first author.