Polygenic risk score for predicting weight loss after bariatric surgery
Juan de Toro-Martín, Frédéric Guénard, André Tchernof, Louis Pérusse, Simon Marceau, Marie-Claude Vohl
Juan de Toro-Martín, Frédéric Guénard, André Tchernof, Louis Pérusse, Simon Marceau, Marie-Claude Vohl
View: Text | PDF
Clinical Research and Public Health Genetics

Polygenic risk score for predicting weight loss after bariatric surgery

Abstract

BACKGROUND. The extent of weight loss among patients undergoing bariatric surgery is highly variable. Herein, we tested the contribution of genetic background to such interindividual variability after biliopancreatic diversion with duodenal switch. METHODS. Percentage of excess body weight loss (%EBWL) was monitored in 865 patients over a period of 48 months after bariatric surgery, and two polygenic risk scores were constructed with 186 and 11 (PRS186 and PRS11) single nucleotide polymorphisms previously associated with body mass index (BMI). RESULTS. The accuracy of the %EBWL logistic prediction model — including initial BMI, age, sex, and surgery modality, and assessed as the area under the receiver operating characteristics (ROC) curve adjusted for optimism (AUCadj = 0.867) — significantly increased after the inclusion of PRS186 (ΔAUCadj = 0.021; 95% CI of the difference [95% CIdiff] = 0.005–0.038) but not PRS11 (ΔAUCadj= 0.008; 95% CIdiff= –0.003–0.019). The overall fit of the longitudinal linear mixed model for %EBWL showed a significant increase after addition of PRS186 (–2 log-likelihood = 12.3; P = 0.002) and PRS11 (–2 log-likelihood = 9.9; P = 0.007). A significant interaction with postsurgery time was found for PRS186 (β = –0.003; P = 0.008) and PRS11 (β = –0.008; P = 0.03). The inclusion of PRS186 and PRS11 in the model improved the cost-effectiveness of bariatric surgery by reducing the percentage of false negatives from 20.4% to 10.9% and 10.2%, respectively. CONCLUSION. These results revealed that genetic background has a significant impact on weight loss after biliopancreatic diversion with duodenal switch. Likewise, the improvement in weight loss prediction after addition of polygenic risk scores is cost-effective, suggesting that genetic testing could potentially be used in the presurgical assessment of patients with severe obesity. FUNDING. Heart and Stroke Foundation of Canada (G-17-0016627) and Canada Research Chair in Genomics Applied to Nutrition and Metabolic Health (no. 950-231-580).

Authors

Juan de Toro-Martín, Frédéric Guénard, André Tchernof, Louis Pérusse, Simon Marceau, Marie-Claude Vohl

×

Figure 4

Effect of polygenic risk scores on weight loss evolution over time.

Options: View larger image (or click on image) Download as PowerPoint
Effect of polygenic risk scores on weight loss evolution over time. (A) ...
(A) Predicted versus actual longitudinal percentage of excess body weight loss (%EBWL) according to an initial model considering only fixed effects (postsurgery cubic time, age, sex, initial BMI, and surgery modality) and the final multivariable linear mixed model considering fixed and random effects (intercept and postsurgery cubic time terms). (B) Graphical representation of the quantitative impact of the extreme values (Min and Max) of polygenic risk scores PRS186 and PRS11 on %EBWL at the end of the follow-up period (48 months). Estimates are calculated for the standard patient, defined as a 42-year-old woman with a mean initial BMI of 50 undergoing laparoscopic surgery. β Estimates and P values of time interaction are shown. Blue shaded areas are 95% confidence intervals. (C) Gray lines show the linear predictor of %EBWL inferred from the final model (fixed effects: postsurgery cubic time, age, sex, initial BMI, and surgery modality; random effects: intercept and postsurgery cubic time terms). Green and red lines show the linear predictor of %EBWL estimated for the maximum and minimum PRS186 and PRS11 values. Gray, red, and green shaded areas are 95% CIs.