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. 2021 Apr;29(4):662-671.
doi: 10.1002/oby.23120.

Selection of Antiobesity Medications Based on Phenotypes Enhances Weight Loss: A Pragmatic Trial in an Obesity Clinic

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Selection of Antiobesity Medications Based on Phenotypes Enhances Weight Loss: A Pragmatic Trial in an Obesity Clinic

Andres Acosta et al. Obesity (Silver Spring). 2021 Apr.

Erratum in

Abstract

Objective: Little is known about the predictors of response to obesity interventions.

Methods: In 450 participants with obesity, body composition, resting energy expenditure, satiety, satiation, eating behavior, affect, and physical activity were measured by validated studies and questionnaires. These variables were used to classify obesity phenotypes. Subsequently, in a 12-month, pragmatic, real-world trial performed in a weight management center, 312 patients were randomly assigned to phenotype-guided treatment or non-phenotype-guided treatment with antiobesity medications: phentermine, phentermine/topiramate, bupropion/naltrexone, lorcaserin, and liraglutide. The primary outcome was weight loss at 12 months.

Results: Four phenotypes of obesity were identified in 383 of 450 participants (85%): hungry brain (abnormal satiation), emotional hunger (hedonic eating), hungry gut (abnormal satiety), and slow burn (decreased metabolic rate). In 15% of participants, no phenotype was identified. Two or more phenotypes were identified in 27% of patients. In the pragmatic clinical trial, the phenotype-guided approach was associated with 1.75-fold greater weight loss after 12 months with mean weight loss of 15.9% compared with 9.0% in the non-phenotype-guided group (difference -6.9% [95% CI -9.4% to -4.5%], P < 0.001), and the proportion of patients who lost >10% at 12 months was 79% in the phenotype-guided group compared with 34% with non-phenotype-guided treatment group.

Conclusions: Biological and behavioral phenotypes elucidate human obesity heterogeneity and can be targeted pharmacologically to enhance weight loss.

Trial registration: ClinicalTrials.gov NCT03374956.

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Conflict of interest statement

Phenomix Sciences has obtained an exclusive license to AA and MC’s biomarker technology, submitted patent, and know‐how to develop a biomarker to predict response to obesity pharmacotherapy. Additionally, AA is a stockholder in Gila Therapeutics and Phenomix Sciences; he serves as a consultant for Rhythm Pharmaceuticals and General Mills. MC is a stockholder in Phenomix Sciences and Enterin and serves as a consultant to Takeda, Allergan, Kallyope, GlaxoSmithKline, Rhythm, and Arena with compensation to Mayo Clinic. MMC is a consultant for Roche Diabetes Care GmbH. BAD has served as a consultant for Boston Scientific, Metamodix, BFKW, DyaMx, and USGI Medical; has received research support for Boston Scientific, Apollo Endosurgery, USGI, Spatz Medical, GI Dynamics, Caim Diagnostics, Aspire Bariatrics, and Medtronic; and has been a speaker for Johnson & Johnson, Endogastric Solutions, and Olympus. The other authors declared no conflict of interest.

Figures

Figure 1
Figure 1
Pathophysiological classification of obesity. (A) Illustration of obesity pathophysiology based on energy balance and key components that contribute to human obesity. (B) Distribution of participants based on pathophysiological phenotypes in 450 patients with obesity (BMI > 30 kg/m2). NEAT, nonexercise activity thermogenesis.
Figure 2
Figure 2
Obesity phenotype characteristics per gender. Obesity phenotypes are associated with pathophysiological characteristics; (A) hungry brain, increased food intake until fullness during ad libitum buffet meal; (B) emotional hunger; increased HADS‐anxiety level; (C) hungry gut, rapid gastric emptying rate; (D) slow burn, lower than predicted REE. Red triangles = participants without specified obesity phenotype, blue squares = participants with specified obesity phenotype. HADS, Hospital Anxiety and Depression Score; REE, resting energy expenditure.
Figure 3
Figure 3
PG pharmacotherapy for obesity management improves weight loss outcomes. (A) Percentage of patients achieving levels of weight loss after 1 year of either non‐PG (n = 228) or PG (n = 84) treatment. (B) The average percentage of total body weight loss from BSL in non‐PG (red circles) and PG (blue squares) treatment at 3, 6, and 12 months. **P < 0.01, ***P < 0.001. BSL, baseline; PG, phenotype guided.

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References

    1. Heymsfield SB, Wadden TA. Mechanisms, pathophysiology, and management of obesity. N Engl J Med 2017;376:254‐266. - PubMed
    1. GBD 2015 Obesity Collaborators ; Afshin A, Forouzanfar MH, Reitsma MB, et al. Health effects of overweight and obesity in 195 countries over 25 years. N Engl J Med 2017;377:13‐27. - PMC - PubMed
    1. Loos RJF, Janssens A. Predicting polygenic obesity using genetic information. Cell Metab 2017;25:535‐543. - PubMed
    1. MacLean PS, Blundell JE, Mennella JA, Batterham RL. Biological control of appetite: a daunting complexity. Obesity (Silver Spring) 2017;25(suppl 1):S8‐S16. - PMC - PubMed
    1. Khera R, Murad MH, Chandar AK, et al. Association of pharmacological treatments for obesity with weight loss and adverse events: a systematic review and meta‐analysis. JAMA 2016;315:2424‐2434. - PMC - PubMed

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