SUN-670 Association Between a Body Mass Index (BMI) Genetic Risk Score and BMI Change Following Metabolic/Bariatric Surgery Among Adolescents

Abstract Disclosure: E.M. Bomberg: Novo Nordisk. L.G. Spector: None. A. Raduski: None. Z. Lu: None. C. Im: None. T.M. Jenkins: None. T.H. Inge: Standard Bariatrics, Teleflex, Medtronic, Mediflix, Independent Medical Expert Consulting Services, Wolters Kluwer (UpToDate). J.R. Ryder: Boehringer Ingelheim, Eli Lilly & Company, Recordati, Calorify. Background: Body mass index (BMI) reductions following metabolic/bariatric surgery (MBS) are highly variable. We sought to evaluate if genetic risk for obesity, as determined by a BMI genetic risk score (GRS), is associated with 6- and 12-month weight loss response after MBS (vertical sleeve gastrectomy, roux-en-Y gastric bypass) among adolescents with obesity enrolled in Teen Longitudinal Assessment of Bariatric Surgery (Teen LABS; NCT00474318). We secondarily sought to determine if a BMI GRS might help differentiate 10-year non-responders with responders. Methods: We included adolescents who underwent MBS and had 6-month outcomes available (e.g., BMI), and limited analyses to those of European ancestry given a lack of available multi-ancestry BMI GRS. Genotyping was performed using an InfiniumTM Global Screening Array. A BMI GRS was constructed for each participant based on ∼2.1 million genetic variants (Khera et al., Cell, 2019). We used linear regression to analyze associations between a BMI GRS and 6- and 12-month BMI and weight change, and logistic regression to compare 10-year responders to non-responders (higher versus lower %BMI change) as determined by latent class analyses (LCA). We performed sensitivity analyses with participants categorized into BMI GRS quartiles (lowest to highest). Models were adjusted for baseline BMI/weight (as appropriate), age, sex, and 15 principal ancestry components. Results: Among 128 adolescents (73% female, mean age 17.2 ± 2.0 years and baseline BMI 51.6 ± 1.6 kg/m2; BMI GRS range -1.70 to 2.42), mean 6- and 12-month (n=121) BMI reductions were 13.6 ± 4.0 and 16.6 ± 5.7 kg/m2, respectively. A 1-unit increase in the BMI GRS was associated with a statistically significantly 5.85 kg higher baseline weight (p=0.045); however, it was not statistically significantly associated with baseline BMI (p=0.135). A 1-unit increase in BMI GRS was associated with a 0.76 kg/m2 greater 6-month BMI reduction (p=0.030); however, not with 12-month BMI change. LCA identified 4 distinct response trajectory categories based on 10-year %BMI change: (1; worst response) +1.7 ± 19.0%, (2) -10.1 ± 9.5%, (3) -29.0 ± 10.9%, and (4; best response) -48.5 ± 7.6%. The BMI GRS was not statistically significantly different between 10-year non-responders (categories 1-2; n=71) and responders (categories 3-4; n=57). When assessing response by BMI GRS quartile, compared to those in the lowest BMI GRS quartile those in the highest quartile had a 1.93 kg/m2 (3.56%) greater 6-month BMI reduction (p=0.026); however, no other statistically significant associations were found. Conclusion: Following MBS, a higher BMI GRS was associated with greater 6-month, however not 12-month, BMI reduction, and a BMI GRS did not significantly differentiate 10-year non-responders with responders. Further research is needed to elucidate potential predictors of response to MBS in adolescents with obesity. Presentation: Sunday, July 13, 2025