Society: AGA

Background: Sound evidence support the effectiveness of the transoral outlet reduction (TORe) with full-thickness endoscopic suturing (FTS) or argon plasma coagulation (APC) alone to address post-RYGB weight regain. Although clinically effective, its effects on gut hormone dynamics and their relationship with weight loss and clinical success rates are still unknown, demanding an investigation.
Methods: This is a substudy of a previous randomized clinical trial. Adult patients with post-RYGB significant weight regain and dilated GJA underwent TORe with APC alone or APC plus FTS (FTS-APC). Serum levels of ghrelin, GLP-1, and PYY were measured at fasting, 30, 60, 90, and 120 minutes after a standardized liquid meal. We used the Student T-test to compare continuous variables and the analysis of variance for repeated measures to analyze and compare the variation of hormonal levels over time. A p-value<.05 was considered statistically significant for a 95% confidence interval.
Results: Thirty-six patients (19 APC vs. 17 FTS-APC) successfully underwent blood sampling at baseline and 12 months (90% follow-up rate). There was no significant baseline difference between patients according to allocation group, history of cholecystectomy, or clinical success (≥10%TWL at 12 months) – Table 1. In all analyses, the typical postprandial decrease in ghrelin levels was delayed by 30 minutes. Other than that, no significant changes in ghrelin levels were noted. GLP-1 levels significantly decreased at 12 months in both allocation groups. We noted similar findings when splitting the sample according to the history of cholecystectomy and clinical success. The APC group presented an increase in PYY levels at 90 minutes, while FTS-SPC did not. The area under the curve between 30-120 minutes significantly increased in the first group (p=0.02) but did not change in the latter (p=0.41). When splitting the sample according to the history of cholecystectomy, we noted that naïve patients had significantly lower PYY levels at baseline (p=0.01). Moreover, cholecystectomized patients experienced a significant increase in the AUC for PYY levels, while naïve patients did not, leading to a higher AUC at 12 months in the former group (p=0.0001). PYY levels and behavior over time were similar when comparing clinical success and failure cases. There was no significant association between the allocation group and the history of cholecystectomy (p=0.053), meaning that both variables independently influence the changes in PYY levels.
Conclusions: Our findings collectively suggest that APC-TORe triggers a more pronounced enteroendocrine response, especially in cholecystectomized patients. GLP-1 levels decrease after TORe, despite the technique employed. Opportunistically, prescribing GLP-1 analogs routinely seems reasonable to further enhance the hormonal response after TORe.

Figure 1 – Demographic characteristics according to allocation group, clinical success, and history of cholecystectomy.

Figure 1 – Demographic characteristics according to allocation group, clinical success, and history of cholecystectomy.

Figure 2 – Graphs showing behavior over time of Ghrelin, GLP-1, and PYY levels at baseline and at 12 months.

Figure 2 – Graphs showing behavior over time of Ghrelin, GLP-1, and PYY levels at baseline and at 12 months.

Background: Obesity and metabolic complications have reached epidemic proportions, contributing to significant social, financial, and healthcare burden. Bariatric surgery is very effective, safe and increasingly utilized to treat obesity. However, there is a paucity of literature describing use of anti-obesity medications (AOMs) following bariatric surgery. We aim to identify prevalence and trends of adjunct AOM use following bariatric surgery.

Materials and Methods: A population-based commercial database (IBM® Explorys® database, IBM, Armonk, NY) was utilized to identify all adult subjects who had undergone bariatric surgery (Roux-en-Y gastric bypass or sleeve gastrectomy). Those who were prescribed U.S. Food and Drug Administration approved AOMs (semaglutide, liraglutide, topiramate, phentermine/topiramate, naltrexone/bupropion, orlistat) within 5 years after surgery were further identified. Data was analyzed to characterize AOMs utilization among different age, demographic, and comorbid populations.

Results: 59,160 adults who had undergone bariatric surgery were included. Among the AOMs studied, prevalence was highest for topiramate (8%), followed by liraglutide (2.9%), phentermine/topiramate (1.03%), naltrexone/bupropion (0.95%) semaglutide (0.52%) and orlistat (0.17%). On univariable analysis, age distribution varied, with highest utilization (odds ratio; 95% confidence interval) among those age 35-39 years for topiramate (1.53; 1.39-1.69), 40-44 years for phentermine/topiramate (1.41; 1.12-1.76) and naltrexone/bupropion (1.35; 1.07-1.72), 45-49 years for semaglutide (1.36; 1.01-1.85), and 65-69 years for liraglutide (1.55; 1.35-1.78) and orlistat (2.25; 1.38-3.67). African American race was associated with higher utilization among all AOMs. Among comorbidities, components of metabolic syndrome (obesity, hypertension, hyperlipidemia, diabetes mellitus) were most associated with higher likelihood of being prescribed AOMs.

Conclusion: AOMs are underutilized following bariatric surgery. It is pertinent to recognize that, while bariatric surgery is often pursued after failed attempts at medical weight loss, obesity is a chronic relapsing disease and AOMs should continue to be considered following surgery and may offer more successful and sustainable weight loss when used in conjunction.

Background
Bariatric surgery procedures (ie sleeve gastrectomy (SG) and laparoscopic adjustable gastric banding (LABG)) are reserved for patients with class III obesity/class II obesity with a comorbidity. Recently, there has been an interest in utilizing surgery in all patients with class I/II obesity regardless of comorbidity. Additionally, a significant number of eligible patients are not interested in undergoing surgery. Endoscopic sleeve gastroplasty (ESG) can be an alternative weight loss tool but lacks reimbursement. Our objective was to model scenarios of different initial class of obesity, to measure the cost-effectiveness of lifestyle intervention (LI), SG, LAGB, and ESG from a healthcare perspective.

Methods
We constructed a decision-analytic Markov model of a cohort of 30-year-old patients with different initial class of obesity without specific comorbidity: class III (BMI 42), class II (BMI 37), and class I (BMI 34). The cost-effectiveness of LI, SG, LAGB, and ESG was directly compared. We used a 30-year time horizon and 1-year cycle length. (Figure 1) Annual costs and disutility were added to each weight-based health state to account for obesity-related conditions. Outcome measures were reported in incremental cost-effectiveness ratios (ICERs), with a willingness-to-pay threshold of $100,000/quality-adjusted life-year (QALY).

Results
In a patient with class III obesity, all strategies dominated (more effective and less costly) when compared to LI. ESG and SG were dominant when compared to LAGB. SG was the cost-effective strategy compared to ESG (ICER $28,923/QALY, Figure 2a) SG remained cost-effective at the WTP threshold if it cost less than $45,476. In a patient with class II obesity, all strategies were cost-effective compared to LI. SG was the dominant strategy, with a lower total cost of $5,873 and improved effectiveness of 0.68 QALYs. (Figure 2b) In a patient with class I obesity, ESG was the dominant strategy, with a lower total cost of $12,896 and improved effectiveness of 0.05 QALY. ESG remained cost-effective at the WTP if it cost less than $29,420. (Figure 2c) National projections of overall cost showed if only SG is utilized, this resulted in a total cost of $626.5 billion for class I obesity patients and a cost savings of $62.3 billion for class III obesity patients. If only ESG is utilized, this resulted in a total cost of $147.1 billion for class I obesity patients, and a cost savings of $142.9 billion for class III obesity patients. (Figure 2d)

Conclusions
In patients with class I obesity, ESG was the cost-effective intervention compared to SG, LAGB and LI. In class II and III obesity, SG was the cost-effective intervention. However, in patients unwilling to undergo SG, then ESG was the cost-effective intervention. This suggests supporting ESG reimbursement to reduce costs and improve the obesity epidemic outcomes

Model diagram demonstrating weight loss intervention options and health states

Model diagram demonstrating weight loss intervention options and health states

Figure 2a: Cost effectiveness acceptability curve for a patient with intial class 3 obesity (BMI 42)<br /> Figure 2b: Cost effectiveness acceptability curve for a patient with initial class 2 obesity (BMI 37)<br /> Figure 2c: Cost effectiveness acceptability curve for a patient with initial class 1 obesity (BMI 34)<br /> Figure 2d: National projections of direct health care expenditures by procedure

Figure 2a: Cost effectiveness acceptability curve for a patient with intial class 3 obesity (BMI 42)
Figure 2b: Cost effectiveness acceptability curve for a patient with initial class 2 obesity (BMI 37)
Figure 2c: Cost effectiveness acceptability curve for a patient with initial class 1 obesity (BMI 34)
Figure 2d: National projections of direct health care expenditures by procedure

Introduction:
Mutations in the leptin-melanocortin pathway (LMP) are associated with severe obesity. It has been shown that carriers of heterozygous genetic variants in the LMP have greater weight recurrence following Roux-en-Y gastric bypass (RYGB) compared to non-carriers (PMID 35654930). Transoral outlet reduction (TORe) is a safe and effective endoscopic technique for management of weight recurrence after RYGB. It uses an endoscopic suturing system (Apollo OverStitch™) to tighten the gastrojejunal anastomosis, leading to significant and sustained weight loss. The impact of TORe after RYGB in patients with a variant in the LMP is unknown. We aimed to evaluate weight loss outcomes of TORe over one year in patients with weight recurrence after RYGB, with or without heterozygous variants in the LMP.
Methods:
We performed a retrospective review of patients who were genotyped for an LMP variant and had RYGB surgery followed by TORe procedure. We excluded patients with active malignancy or pregnancy. Patients were classified as “carriers” or “non-carriers” of variants in the LMP. Patient demographic and medical information were abstracted from the electronic medical records with weight records up to one year after TORe procedure. Total body weight loss percentage (%TBWL) at 1, 3, 6, 9 and 12 months was calculated based on baseline weight at TORe. All continuous data are summarized as the mean and standard deviation (SD). A 2-sample t-test was conducted to compare %TBWL between groups.
Results:
A total of 59 patients were included, with 26 (44%) carriers and 33 (56%) non-carriers. There were no significant differences at baseline among the groups (table 1A). The most common genetic variant was PCSK1, seen in 42% (11) carriers. %TBWL after TORe was lower in carriers compared to non-carriers at 1, 3, 6, 9 and 12 months, and achieved significance at one year follow-up in carriers vs. non-carriers (2.1 ± 8.3 vs. 8.9 ± 8.2, p= 0.021) (table 1B, figure 1a). A higher number of non-carriers achieved >5%TBWL and >10%TBWL at 6, 9 and 12 months compared to carriers (figure 1b and 1c).
Discussion:
Patients with a LMP variant and that underwent RYGB show decreased weight loss at one year after undergoing TORe. Genotyping patients experiencing significant weight recurrence after RYGB may help with designing individualized weight loss interventions to improve weight maintenance after surgery and revisional procedures.

Table 1A and B: Baseline characteristics of genotyped patients undergoing TORe; %TBWL outcomes of genotyped patients undergoing TORe<br /> Abbreviations: %TBWL: Total Body Weight Loss Percentage; SD: Standard Deviation

Table 1A and B: Baseline characteristics of genotyped patients undergoing TORe; %TBWL outcomes of genotyped patients undergoing TORe
Abbreviations: %TBWL: Total Body Weight Loss Percentage; SD: Standard Deviation

Figure 1: a) %TBWL in carriers and non-carriers; b) Percentage of carriers and non-carriers achieving >5% TBWL; c) Percentage of carriers and non-carriers achieving >10% TBWL

Figure 1: a) %TBWL in carriers and non-carriers; b) Percentage of carriers and non-carriers achieving >5% TBWL; c) Percentage of carriers and non-carriers achieving >10% TBWL

Background: Obesity is accompanied by high socioeconomic burden. Despite significant advances in management of obesity, there are variable responses to weight loss medications. There is growing interest in identifying predictors of response. For example, in patients treated with liraglutide, weight loss >1kg and prolongation of gastric emptying of solids >50min at 5 weeks predicted >4kg weight loss at 16 weeks (PMID:36193713). Aim: To analyze the potential role of genetic variations on the weight loss effect in adults of the US Food and Drug Administration–approved medications, notably GLP-1 agonists, naltrexone-bupropion, phentermine-topiramate, and orlistat. Methods: We searched the literature from inception to November 15, 2022 with no restrictions, and included both interventional and observational studies. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. Two investigators extracted data independently using prespecified criteria. All variants studied in at least 3 studies were included in the random effects meta-analysis. Due to heterogeneity of measured outcomes, effect sizes were calculated as standardized mean differences (SMD) calculated by the difference in mean weight loss between the allelic groups (variant vs reference) divided by the pooled standard deviation. For binary outcomes, we conducted a linear transformation of the natural log of the odds ratio to SMD. Results: The search strategy identified 363 citations. After removing duplicates and screening titles, abstracts, and full-texts, 14 studies were included in the qualitative analysis and 7 studies in the meta-analysis. Of the 14 studies in the qualitative analysis, 3 were placebo-controlled, randomized clinical trials (RCTs), 1 was a post-hoc analysis of prior RCTs, and 10 were observational studies that assessed single nucleotide variants (SNV) in CNR1, GLP-1 R, MC4R, TCF7L2, CTRB1/2, ADIPOQ, SORCS1, and ANKK1 (Fig. 1). These studies evaluated interactions of different alleles with the weight loss efficacy of GLP-1 agonists (13 studies: liraglutide 8, exenatide 4, both 1) or naltrexone/bupropion (1 study). Alleles of CNR1 gene (rs1049353), GLP-1 R gene (rs6923761, rs10305420), TCF7L2 gene (rs7903146) were associated with differential weight loss in at least one study involving GLP-1 agonist(s). However, the meta-analysis did not identify any significant interaction between alleles and the weight-lowering effect of the various medications (Fig. 2). Conclusion: Systematic review of pharmacogenetic interactions for exenatide, liraglutide, and naltrexone-bupropion identified impact on weight loss, but the directionality of the association was not consistent across studies, as documented in the meta-analysis. Pharmacogenetic effects on weight loss in response to medications require further study.

Figure 1: Flow diagram highlighting the interaction between various single nucleotide variants (SNV) and weight lowering medications.<b> </b>Each small square represents a different study in the literature, and the outcome of interest is weight loss, expressed as significant effect of the variant or reference allele (shown as “in favor” in the figure). Some studies evaluated the effects of different SNV and are included multiple times.

Figure 1: Flow diagram highlighting the interaction between various single nucleotide variants (SNV) and weight lowering medications. Each small square represents a different study in the literature, and the outcome of interest is weight loss, expressed as significant effect of the variant or reference allele (shown as “in favor” in the figure). Some studies evaluated the effects of different SNV and are included multiple times.

Figure 2: Forest plot evaluating the association of GLP-1 agonists with single nucleotide variants in <i>GLP-1R</i> gene (rs692376, rs10305420) and <i>TCF7L2</i> gene (rs7903146).

Figure 2: Forest plot evaluating the association of GLP-1 agonists with single nucleotide variants in GLP-1R gene (rs692376, rs10305420) and TCF7L2 gene (rs7903146).

Kia Vosoughi

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