Predicting Weight Loss After Vertical Sleeve Gastrectomy Using a Whole-genome Sequencing-derived Polygenic Risk Score in the All of Us Cohort.

OBJECTIVE

To create a genome-wide polygenic risk score (PRS) to improve prediction of a 12-month percentage weight loss (WL) after vertical sleeve gastrectomy (VSG).

BACKGROUND

Variability in post-VSG WL is not well explained by clinical factors. The All of Us program provides access to a 414,830 short-read whole-genome sequencing resource, enabling unbiased discovery of genetic predictors after VSG.

METHODS

VSG counts, demographic, anthropomorphic and vital sign information were obtained from the linked electronic health record. The discovery cohort (DC) included participants from version 7 carried into version 8 while the validation cohort (VC) included those newly added to v8. We defined good responders and nonresponders as having WL±1SD from the mean. Following quality filtering, we applied a 2-stage penalized-regression, followed by elastic-net logistic regression, to identify 1583 stable variants and derive β-weights. We then tested this PRS on the DC into a prediction model.

RESULTS

We identified 395 participants in the DC and 336 participants in the VC, respectively. Of these, VSG, 44 were classified as good responders (≥37% WL) and 55 as nonresponders (≤19% WL). In the VC, 55 were classified as good responders and 48 as nonresponders. Adding the PRS to models to clinical predictors increased the area under the curve following logistic regression by 0.03; P <4.3 × 10 -14 , random forest by 0.03; P <9.1 × 10 -7 , decision tree by 0.05; P = 1.2 × 10 -3 , and gradient boosting by 0.08; P <8.3 × 10 -10 .

CONCLUSIONS

Use of short-read whole-genome sequencing from All of Us (AoU) can be effectively used to generate PRS to enhance predictive WL accuracy. This work has implications for outcomes of both bariatric surgery and other surgical procedures.