Polygenic risk score for predicting weight loss after bariatric surgery
Juan de Toro-Martín, … , Simon Marceau, Marie-Claude Vohl
Juan de Toro-Martín, … , Simon Marceau, Marie-Claude Vohl
Published September 6, 2018
Citation Information: JCI Insight. 2018;3(17):e122011. https://doi.org/10.1172/jci.insight.122011.
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Clinical Research and Public Health Genetics Article has an altmetric score of 8

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

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Figure 3

Effect of polygenic risk scores on weight loss trajectory groups.

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Effect of polygenic risk scores on weight loss trajectory groups. (A) Hi...
(A) Histograms displaying the different distribution of polygenic risk scores PRS186 and PRS11 in patients assigned to LWL or HWL+NWL trajectory groups. As shown, increasing values of PRS186 and PRS11 are significantly associated with a greater probability of being in the LWL group. Odds ratios (OR) and P values are for the linear trend test in the multivariable binary logistic model. HWL, NWL, and HWL: high-, normal-, and low-weight-loss trajectory groups. (B) Graphical representation of the area under the ROC curve (AUC) for PRS186 and PRS11. The AUC for initial BMI (iBMI) is also shown. (C) Impact of maximum (red lines) and minimum (green lines) values of PRS186 and PRS11 on the probability of being in the LWL group as a function of iBMI (gray lines). Gray, red, and green shaded areas represent 95% confidence intervals. (D) The AUC of the final logistic prediction models, including all the demographic and clinical predictors before (Final Model: sex, age, type of surgery, and iBMI) and after the inclusion of polygenic risk scores (Model + PRS186 and Model + PRS11) are shown.