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TOPLINE:
, new evidence reveals.
METHODOLOGY:
- A machine learning genetic risk score can identify people with the hungry gut obesity phenotype, which has been found to be associated with greater weight loss with the glucagon-like peptide 1 receptor agonists (GLP-1 RA) liraglutide and exenatide.
- For this study, researchers calculated the genetic risk score for 84 adults undergoing weight loss interventions at Mayo Clinic who were prescribed the GLP-1 RA semaglutide.
- Study participants were classified as the obesity phenotype hungry gut positive (n = 51) or hungry gut negative (n = 33).
- The researchers measured total body weight loss at 3, 6, 9, and 12 months and assessed the ability of the score to predict the response to semaglutide (defined as ≥ 5% of total body weight loss measured at 12 months).
TAKEAWAY:
- At 3 and 6 months, there were no significant differences in weight loss between the hungry gut positive and hungry gut negative groups.
- By 9 months, participants in the positive group lost 14.4% of their total body weight compared with 10.3% in case of participants in the negative group (P = .045).
- After a total of 12 months, the positive group lost 19.5% of their total body weight compared with 10.0% in case of participants in the negative group (P = .01).
- When used to predict the response to semaglutide, the area under the curve for the machine-learning genetic risk score was 0.76 (95% CI, 0.57-0.94; P = .04).
IN PRACTICE:
We can now tell with confidence who is going to respond to semaglutide, said Andres Acosta, MD, PhD, associate professor of medicine at Mayo Clinic. “For nonresponders, we can think about other interventions or medications that we have available.”
SOURCE:
This study was presented on May 20, 2024, at the annual Digestive Disease Week® (DDW) (Abstract 638).
LIMITATIONS:
Further prospective studies are needed to assess the validity of the test in a more diverse population and with different weight loss interventions.
DISCLOSURES:
This study was supported by a partnership between Mayo Clinic and Phenomix Sciences. Dr. Acosta is a cofounder of Phenomix Sciences.
A version of this article appeared on Medscape.com.
TOPLINE:
, new evidence reveals.
METHODOLOGY:
- A machine learning genetic risk score can identify people with the hungry gut obesity phenotype, which has been found to be associated with greater weight loss with the glucagon-like peptide 1 receptor agonists (GLP-1 RA) liraglutide and exenatide.
- For this study, researchers calculated the genetic risk score for 84 adults undergoing weight loss interventions at Mayo Clinic who were prescribed the GLP-1 RA semaglutide.
- Study participants were classified as the obesity phenotype hungry gut positive (n = 51) or hungry gut negative (n = 33).
- The researchers measured total body weight loss at 3, 6, 9, and 12 months and assessed the ability of the score to predict the response to semaglutide (defined as ≥ 5% of total body weight loss measured at 12 months).
TAKEAWAY:
- At 3 and 6 months, there were no significant differences in weight loss between the hungry gut positive and hungry gut negative groups.
- By 9 months, participants in the positive group lost 14.4% of their total body weight compared with 10.3% in case of participants in the negative group (P = .045).
- After a total of 12 months, the positive group lost 19.5% of their total body weight compared with 10.0% in case of participants in the negative group (P = .01).
- When used to predict the response to semaglutide, the area under the curve for the machine-learning genetic risk score was 0.76 (95% CI, 0.57-0.94; P = .04).
IN PRACTICE:
We can now tell with confidence who is going to respond to semaglutide, said Andres Acosta, MD, PhD, associate professor of medicine at Mayo Clinic. “For nonresponders, we can think about other interventions or medications that we have available.”
SOURCE:
This study was presented on May 20, 2024, at the annual Digestive Disease Week® (DDW) (Abstract 638).
LIMITATIONS:
Further prospective studies are needed to assess the validity of the test in a more diverse population and with different weight loss interventions.
DISCLOSURES:
This study was supported by a partnership between Mayo Clinic and Phenomix Sciences. Dr. Acosta is a cofounder of Phenomix Sciences.
A version of this article appeared on Medscape.com.
TOPLINE:
, new evidence reveals.
METHODOLOGY:
- A machine learning genetic risk score can identify people with the hungry gut obesity phenotype, which has been found to be associated with greater weight loss with the glucagon-like peptide 1 receptor agonists (GLP-1 RA) liraglutide and exenatide.
- For this study, researchers calculated the genetic risk score for 84 adults undergoing weight loss interventions at Mayo Clinic who were prescribed the GLP-1 RA semaglutide.
- Study participants were classified as the obesity phenotype hungry gut positive (n = 51) or hungry gut negative (n = 33).
- The researchers measured total body weight loss at 3, 6, 9, and 12 months and assessed the ability of the score to predict the response to semaglutide (defined as ≥ 5% of total body weight loss measured at 12 months).
TAKEAWAY:
- At 3 and 6 months, there were no significant differences in weight loss between the hungry gut positive and hungry gut negative groups.
- By 9 months, participants in the positive group lost 14.4% of their total body weight compared with 10.3% in case of participants in the negative group (P = .045).
- After a total of 12 months, the positive group lost 19.5% of their total body weight compared with 10.0% in case of participants in the negative group (P = .01).
- When used to predict the response to semaglutide, the area under the curve for the machine-learning genetic risk score was 0.76 (95% CI, 0.57-0.94; P = .04).
IN PRACTICE:
We can now tell with confidence who is going to respond to semaglutide, said Andres Acosta, MD, PhD, associate professor of medicine at Mayo Clinic. “For nonresponders, we can think about other interventions or medications that we have available.”
SOURCE:
This study was presented on May 20, 2024, at the annual Digestive Disease Week® (DDW) (Abstract 638).
LIMITATIONS:
Further prospective studies are needed to assess the validity of the test in a more diverse population and with different weight loss interventions.
DISCLOSURES:
This study was supported by a partnership between Mayo Clinic and Phenomix Sciences. Dr. Acosta is a cofounder of Phenomix Sciences.
A version of this article appeared on Medscape.com.