Precision Medicine Tool May Accurately Predict Bariatric Surgery Outcomes

Researchers from the University at Buffalo (UB) have demonstrated that a tool originally designed to predict a patient’s risk level for various addictions using genetic and psychosocial factors can also accurately predict bariatric surgery outcomes.

These findings, detailed in two papers recently published in the Journal of Personalized Medicine and Biomedicines, are the result of an ongoing, longitudinal study examining how best to optimize outcomes following bariatric surgery.

The press release notes that while bariatric surgery is often successful for patients with severe obesity, the procedure can result in negative outcomes, like weight regain, in a small percentage of individuals.

Being able to better forecast which patients are at risk for these adverse outcomes could significantly improve their care, the researchers indicated. Some patients are also at risk of developing new addictive behaviors following the procedure, further underscoring the need for better prediction methods in bariatrics.

“There is a percentage of patients who have a negative outcome after bariatric surgery,” explained Panayotis K. Thanos, PhD, corresponding author on the papers, and senior research scientist in the Department of Pharmacology and Toxicology and the Clinical and Research Institute on Addictions in the Jacobs School of Medicine and Biomedical Sciences at UB. “Some patients regain weight, and some develop addictions that they didn’t have before, such as alcohol abuse or smoking.”

To address this, the research team set out to investigate whether genetic and psychosocial factors could be used to predict these negative outcomes.

Genetic and psychosocial testing was administered to 34 bariatric surgery patients at Kaleida Health’s Comprehensive Weight Loss and Bariatric Surgery Center at Buffalo General Medical Center before and after they underwent bariatric surgery.

The Genetic Addiction Risk Severity (GARS) test was then leveraged to measure gene variants within each patient’s sample associated with the release of the molecule dopamine, an important player in the brain’s reward signaling system.

The researchers found that 76 percent of the cohort had a genetic risk for addictive behaviors.

Further, the results showed that patients with a genetic variant known as DRD2 polymorphism were significantly more responsive to weight loss treatment. The research team indicated that these findings are consistent with earlier studies indicating that carriers of the DRD2 variant exhibit better compliance in dopaminergic agonist therapy and days completed in treatment compared to non-carriers.

The results also highlighted that some of the data collected from the psychosocial questionnaires were associated with body mass index and body weight six months following bariatric surgery.

The researchers suggested that the findings demonstrate precision medicine’s potential role in improving bariatric care.

“You hear a lot about precision medicine, but how do you translate that to the patient? With this study, precision medicine ties in very well. We obtain psychosocial and genetic information from individual patients and then use it as a precision approach to optimizing outcomes,” Thanos stated. “The idea is that as we collect more data, we will be able to provide more information for clinicians so they can say, ‘OK, here are some things that predict success or that we may need to customize in order to overcome some obstacle.’”

In the future, the research team will continue to monitor these patients for the development of any new addictive behaviors.

“These important longitudinal data can help patients undergoing bariatric surgery reduce potential future addictive behavioral transfer, such as alcohol abuse or gambling,” said Teresa Quattrin, MD, UB Distinguished Professor in the Department of Pediatrics and an endocrinologist with UBMD Pediatrics, who is co-corresponding author on both papers.

Correction [10/03/2023]: A previous version of this article stated that the research was conducted at the University of Buffalo. This article has been revised to reflect that the research actually took place at the University at Buffalo.