Genetic Testing to Predict Weight Loss and Diabetes Remission and Long-Term Sustainability after Bariatric Surgery: A Pilot Study

Ciudin, Andreea; Fidilio, Enzamaría; Ortiz, Angel; Pich, Sara; Salas, Eduardo; Mesa, Jordi; Hernández, Cristina; Simó‐Servat, Olga; Lecube, Albert; Simó, Rafael

doi:10.3390/jcm8070964

Cited by 17 publications

(11 citation statements)

References 14 publications

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“…After conducting a primary investigation of genes associated with weight loss after RYGB, these 17 single nucleotide polymorphisms (SNP) were identified as having the most potential clinical utility. Ciudin et al similarly created a predictive model using 57 genes to ascertain the weight regain 60 months after RYGB [37]. The 57 SNPs were found to be associated with obesity, appetite regulation, and weight loss in response to bariatric surgery.…”

Section: Genetic Risk Scorementioning

confidence: 99%

A Systematic Review of Genetic Correlates of Weight Loss After Bariatric Surgery

et al. 2021

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This systematic review synthesized research evaluating the relationship between genetic predictors and weight loss after bariatric surgery. Fifty-seven studies were identified that examined single genes or genetic risk scores. Uncoupling protein (UCP) rs660339 was associated with excess weight loss after surgery in 4 of 6 studies. The most commonly assessed genes were fat mass and obesity-associated (FTO) gene (n = 10) and melanocortin-4 receptor (MC4R) (n = 14). Both were inconsistently related to weight loss. Genetic risk scores predicted weight loss in 6 of 7 studies. This evidence suggests the potential of using genetic variants and genetic risk scores to predict the amount of weight loss anticipated after bariatric surgery and identify patients who may be at risk for suboptimal weight reduction.

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Section: Genetic Risk Scorementioning

confidence: 99%

A Systematic Review of Genetic Correlates of Weight Loss After Bariatric Surgery

et al. 2021

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“…In addition, Nutri inCode also includes selected variants of published GWAS studies or replication studies related to genetic susceptibility to regulate appetite and develop type 2 diabetes and obesity [22,23]. Finally, in the present study, the panel has been enriched with new 11 SNPs compared to our pilot study (Table 1) [17].…”

Section: Genotypingmentioning

confidence: 99%

“…The possibility of elucidating the best combination of SNPs responsible for the variability of the response to BS in terms of weight loss offers the opportunity to design individualized therapy strategies. Our group has recently showed that an algorithm based on the selection of SNPs associated with predisposition to obesity, appetite regulation, and weight loss was able to predict the percentage of excess body weight loss (%EWL) after BS with high sensitivity and specificity [17]. It should be noted that this was a pilot study including only women who undergo a Roux-en-Y gastric bypass (RYGB), precluding the extrapolation of the results to the whole population.…”

Section: Introductionmentioning

confidence: 99%

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A Clinical-Genetic Score for Predicting Weight Loss after Bariatric Surgery: The OBEGEN Study

Ciudin

Fidilio

Gutiérrez-Carrasquilla

et al. 2021

JPM

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Around 30% of the patients that undergo bariatric surgery (BS) do not reach an appropriate weight loss. The OBEGEN study aimed to assess the added value of genetic testing to clinical variables in predicting weight loss after BS. A multicenter, retrospective, longitudinal, and observational study including 416 patients who underwent BS was conducted (Clinical.Trials.gov- NCT02405949). 50 single nucleotide polymorphisms (SNPs) from 39 genes were examined. Receiver Operating Characteristic (ROC) curve analysis were used to calculate sensitivity and specificity. Satisfactory response to BS was defined as at nadir excess weight loss >50%. A good predictive model of response [area under ROC of 0.845 (95% CI 0.805–0.880), p < 0.001; sensitivity 90.1%, specificity 65.5%] was obtained by combining three clinical variables (age, type of surgery, presence diabetes) and nine SNPs located in ADIPOQ, MC4R, IL6, PPARG, INSIG2, CNR1, ELOVL6, PLIN1 and BDNF genes. This predictive model showed a significant higher area under ROC than the clinical score (p = 0.0186). The OBEGEN study shows the key role of combining clinical variables with genetic testing to increase the predictability of the weight loss response after BS. This finding will permit us to implement a personalized medicine which will be associated with a more cost-effective clinical practice.

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“…Weight and BMI nadir were considered the minimum values reached after the BS; %EWL, TWL, and %TWL were calculated following standardized outcome reporting guidelines [22]. The post-BS weight regain was defined as a 10% regain of the minimal weight after BS, as previously described [23].…”

Section: Clinical and Anthropometric Variablesmentioning

confidence: 99%

Evaluation of Resting Energy Expenditure in Subjects with Severe Obesity and Its Evolution After Bariatric Surgery

et al. 2021

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Purpose One major determinant of weight loss is resting energy expenditure (REE). However, data regarding REE is scarce in patients with severe obesity (SO)—BMI>50kg/m2. Most studies used equation in order to estimate REE and not indirect calorimetry (IC) (gold standard). Additionally, there is no reliable data on the impact of bariatric surgery (BS) on REE. Objectives (a) To evaluate the REE in patients with SO; (b) to compare REE measured by IC (mREE) to that calculated by Mifflin St-Jeor equation (eREE); (c) to evaluate the impact of BS on REE and the relationship with evolution post-BS. Material and Methods Single-center observational study including consecutive patients with SO between January 2010 and December 2015, candidates for BS. mREE was determined at baseline, and 1 and 12 months post-BS by IC, using a Vmax metabolic monitor. Results Thirty-nine patients were included: mean age 46.5±11.77 years, 64.1%women. Preoperative mREE was 2320.38±750.81 kcal/day. One month post-BS, the mREE significantly decreased (1537.6 ± 117.46 kcal/day, p = 0.023) and remained unchanged at 12 months (1526.00 ± 123.35 kcal/day; p =0.682). Reduction in mREE after the BS was a predictor of reaching successful weight loss (nadir) and weight regain (5 years follow-up) (AUCROC of 0.841 (95%CI [0.655–0.909], p=0.032) and AUCROC of 0.855 (95% CI [0.639–0.901]), p= 0.027, respectively). eREE was not valid to identify these changes. Conclusion In patients with SO, a significant reduction of mREE occurs 1 month post-BS, unchanged at 12 months, representing the major conditioning of successful weight loss and maintenance post-BS. Graphical abstract

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Genetic Testing to Predict Weight Loss and Diabetes Remission and Long-Term Sustainability after Bariatric Surgery: A Pilot Study

Cited by 17 publications

References 14 publications

A Systematic Review of Genetic Correlates of Weight Loss After Bariatric Surgery

A Systematic Review of Genetic Correlates of Weight Loss After Bariatric Surgery

A Clinical-Genetic Score for Predicting Weight Loss after Bariatric Surgery: The OBEGEN Study

Evaluation of Resting Energy Expenditure in Subjects with Severe Obesity and Its Evolution After Bariatric Surgery

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