Mutations associated with perioperative complications: the clinical utility of genetic data

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Mutations associated with perioperative complications: the clinical utility of genetic data

A recent study published in the British Journal of Anaesthesia drew on the genetic and electronic health record (EHR) data of more than 40K participants in the Michigan Genomics Initiative (MGI) to discover whether genetic information could inform doctors of possible anesthetic complications in patients who did not have a family history or clinical features of such susceptibility.

The results strengthen the existing argument that genetic data has an important place in clinical decision-making.

“Genetic data,” says lead author Nicholas Douville, MD, PhD, “has the unrealized potential of directly changing the health care we provide for individual patients. This study provides a key first step to accomplishing that goal.”

Douville, a Precision Health member and clinical lecturer in anesthesiology at U-M, explains the value of focusing on a surgical setting. “The perioperative period is an attractive target for precision medicine, because a trip to the operating room is associated with a higher rate of complications, generates a large volume of clinical data, and accounts for a disproportionate amount of health care expenditures. Greater than 50 million patients undergo surgery each year in the U.S.  Of these patients, approximately 13% will develop a complication associated with their procedure.” Genetic data could be one more tool in predicting complications, but “health care providers in fields like anesthesiology and surgery have limited exposure to genetic data and are not trained to contextualize this information,” Douville said.

Researchers focused on three anesthetic complications for the study: malignant hyperthermia, butyrlcholinesterase deficiency, and factor V Leiden. Although relatively rare, these conditions were selected for this initial work “because susceptibility can be easily identified using available genetic data, and the risk of potentially life-threatening complications can be greatly reduced through straightforward modifications in the anesthetic management,” said Douville. Ultimately, the study team hopes apply this methodology to higher-frequency complications with more complex genetic inheritance.

“We would definitely like to incorporate genetic information into clinical decision-making,” said Douville, “however, the real novelty of our approach is in the integration of a variety of data sources available from the electronic health record. Very few diseases have the straightforward genetic basis of the three conditions studied in this project. The vast majority of conditions combine genetic risk with a variety of other social and lifestyle factors.  Our ultimate goal would be to incorporate a variety of factors, such as polygenic risk, past conditions, medications, laboratory findings, social history, tobacco use, etc.,” and from these determine the overall risk of a patient developing key complications.

“We are currently at the first step in this process,” said Douville, pointing out the importance of making these risk predictions useful to clinicians who are already overloaded with alerts and flags in an EHR. The next questions to ask, he said, are “What do the clinicians ultimately do with this information, and do these changes in care lead to meaningful improvement in clinical outcomes? We are starting to answer these follow-up questions.”