Massive international study discovers genes involved in heart disease

Over the past 15 years, more than 200 sites in the human genome have been linked to the risk of coronary artery disease, the leading cause of death worldwide. Still, researchers don’t fully understand how these genomic variations alter the function of proteins, cells, or tissues to cause disease—knowledge that could inform the development of new treatments.

In a massive study, scientists from the international CARDIoGRAMplusC4D consortium compiled and analyzed DNA data from more than 1 million people, including more than 200,000 with coronary artery disease.

The researchers discovered 68 new genome regions, or loci, associated with increased CAD risk, bringing the total to more than 250. They also developed a broad approach that incorporates eight diverse lines of evidence and used it to systematically identify 220 genes. candidate causal factors underlying the associated loci. They verified the role of one of these putative causative genes through genome editing and cell-based experiments, showing the power of their method in revealing how specific genes might be involved in CAD development.

“This project is an example of team science with six first authors contributing equally and representing multiple cohorts and extensive analytical experience,” he said. Brooke Wolford, PhD, postdoctoral researcher in the Department of Computational Medicine and Bioinformatics at the UM School of Medicine.

The work, published in Genetics of Natureprovides a more complete picture of the genetic roots of CAD, outlines a list of genes and genetic variants for future studyand demonstrates an analytical framework for identifying causative genes that can be used to improve research on other diseases involving genome-wide association studies (GWAS).

The researchers have shared their findings openly in the Knowledge portal on cardiovascular diseasesdeveloped by scientists at the Broad Institute of MIT and Harvard in Cambridge, Massachusetts.

“This collaborative effort represents a substantial advance in the field of coronary artery disease genetics,” said study co-author Krishna Aragam, a scientist with the Cardiovascular Disease Initiative at the Broad Institute and a cardiologist at New York General Hospital. Massachusetts.

“We hope that our approach will encourage groups involved in GWAS of other traits and diseases to systematically interrogate genetic loci with various orthogonal lines of evidence and make the resources widely available for reference by others. Such studies do not end with the publication of gene lists, but rather pave the way for new mechanistic investigations.”

“We have shown that a systematic, disease-tailored approach can effectively pinpoint the true genetic roots of disease and offer a more precise insight into disease mechanism, which will be critical in translating statistical insights into biological meaning and, in ultimately finding innovative treatments for the dangerous ones. diseases such as coronary artery disease,” said Adam Butterworth, co-senior author of the study and professor of molecular epidemiology at the University of Cambridge.

causal clues

With the advent of large biobanks and cohorts in recent years, the research community has been able to mine ever larger data sets for genetic associations with disease. In the current study, the researchers wanted to broaden the search for genetic links to heart disease and show that their approach could uncover the functional implications of disease-related loci.

“The current era of discovery genetics is not just about discovery, but also about asking what links each discovered genetic locus to the disease in question,” Aragam said.

In the new study, consortium scientists collected genetic and medical data from 1 million people of predominantly European descent from the UK Biobank, the CARDIoGRAMplusC4D Consortium, prospective cohorts, hospital biobanks, and clinical trials, including nearly 200,000 people with arterial disease. coronary.

They performed a GWAS meta-analysis of the entire data set, scanning DNA sites in each person’s genome to identify genetic variants that are more likely to be found in people with the disease. They found 241 sites in the genome that were associated with CAD risk, including 30 that had never been linked to the disease.

Most of the new genome sites were linked to very small changes in CAD risk, suggesting that few, if any, common genetic variants remain with significant effects on CAD risk across study populations. primarily of European descent.

To increase their power of discovery, the researchers combined their large data set with data from Biobank Japan on tens of thousands of people of East Asian descent, including 29,000 with CAD. The pooled analysis revealed an additional 38 genome sites linked to CAD risk.

“Future GWAS that include more ancestrally diverse populations are likely to return more information than those that are limited to participants of European ancestry,” Butterworth said.

The team wanted to go further and find not only these GWAS “hits,” but also link them to nearby genes that cause CAD when disrupted. There are a variety of methods to find out which gene near a GWAS stroke is likely to have a causal role in the disease, so the researchers decided to pioneer an innovative and systematic approach that incorporates evidence from eight of these methods. Some of the methods look for the closest or most potentially disruptive variants, while others look for genes known to be altered in people with the disease.

The researchers applied their framework to all 279 CAD-associated genome sites to systematically search for causative genes in a consistent manner. Those that were prioritized for three or more of the eight measures were considered highly likely to be the causative genes underlying the GWAS successes. The team verified one of these causative genes, MYO9Busing genome editing and cell-based experiments, and found that it appears to mediate CAD risk by regulating vascular cell motility.

Predictive power

To explore the potential clinical use of their findings, the researchers generated a new polygenic risk score that incorporates more than 2 million variants in the genome and predicts both incident and recurrent CAD risk. The score was based on data from about three times as many people as the pre-existing risk score for CAD. Although the team’s score better predicted an individual’s risk of new and recurrent CAD, the improvement was surprisingly modest given the large increase in the GWAS sample size. This suggests that greater ancestral diversity and advances in polygenic scoring methods are more likely to lead to substantial improvements in polygenic risk scoring performance than can be achieved through ever-larger single-ancestry GWAS.

The team hopes that other researchers will use their findings to further explore the functional impacts of potential causative genes.

“The current study demonstrates the importance of the ‘variant to function’ approach in improving our understanding of disease biology,” said Aragam. “We hope that our results will lead others to decipher new disease mechanisms so that we can find new ways to treat CAD, a condition that continues to affect so many around the world.”

The work involved nearly one hundred researchers from more than 20 countries, with key roles played by Tao Jiang, Anuj Goel, Stavroula Kanoni, Brooke Wolford, Deepak Atri, Rajat M Gupta, Jeanette Erdmann, Nilesh J Samani, Heribert Schunkert, Hugh Watkins, Cristen J Willer, Panos Deloukas, and Sekar Kathiresan. Collaborating institutions include the University of Michigan, the University of Oxford, Queen Mary University of London, the University of Leicester, the University of Munich and the University of Lubeck.

The work was funded in part by the National Heart, Lung, and Blood Institute, the National Institutes of Health, the US Department of Health and Human Services, the National Human Genome Research Institute, the American Association of of the Heart, the UK Medical Research Council, Health Data Research UK and the British Heart Foundation.

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