Evidence map›Paper›PMID 39127792›Full record

ReviewInternational journal of obesity (2005)2025

Precision medicine for obesity: current evidence and insights for personalization of obesity pharmacotherapy.

Diego Anazco, Andres Acosta

Abstract readReview
In one paragraph

Review in International journal of obesity (2005), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

23 citing papers in PubMed.

  1. Article
  2. GutiMeta · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Review
  8. Article
  9. Cells · 2026
    Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Review
  15. Review
  16. Article
  17. Review
  18. Polysaccharides from the Cherry Peel ofFoods (Basel, Switzerland) · 2026
    Article
  19. Review
  20. Precision Medicine for Obesity Treatment.Journal of the Endocrine Society · 2025
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Diego AnazcoPrecision Medicine for Obesity Program, Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, MN, USA.ORCID 0000-0003-1829-7001
Andres AcostaPrecision Medicine for Obesity Program, Division of Gastroenterology and Hepatology, Department of Medicine, Mayo Clinic, Rochester, MN, USA. acosta.andres@mayo.edu.ORCID 0000-0003-2286-489X

Funding

Phenotype-Tailored Lifestyle intervention for Obesity: A Randomized TrialR01DK139028 · NIDDK · MAYO CLINIC ROCHESTER · PI Andres J Acosta · 2024 to 2026
$2.0M
Mechanisms of Enteroendocrine L-Cell Dysfunction and Bile Adaptations to Weight LossK23DK114460 · NIDDK · MAYO CLINIC ROCHESTER · PI ACOSTA, ANDRES J · 2018 to 2022
$980k
NIDDK NIH HHS K23 DK114460NIDDK NIH HHS R01 DK139028
6 · The paper itself

Abstract

Obesity is a chronic and complex disease associated with increased morbidity, mortality, and financial burden. It is expected that by 2030 one of two people in the United States will have obesity. The backbone for obesity management continues to be lifestyle interventions, consisting of calorie deficit diets and increased physical activity levels, however, these interventions are often insufficient to achieve sufficient and maintained weight loss. As a result, multiple patients require additional interventions such as antiobesity medications or bariatric interventions in order to achieve clinically significant weight loss and improvement or resolution of obesity-associated comorbidities. Despite the recent advances in the field of obesity pharmacotherapy that have resulted in never-before-seen weight loss outcomes, comorbidity improvement, and even reduction in cardiovascular mortality, there is still a significant interindividual variability in terms of response to antiobesity medications, with a subset of patients not achieving a clinically significant weight loss. Currently, the trial-and-error paradigm for the selection of antiobesity medications results in increased costs and risks for developing side effects, while also reduces engagement in weight management programs for patients with obesity. The implementation of a precision medicine framework to the selection of antiobesity medications might help reduce heterogeneity and optimize weight loss outcomes by identifying unique subsets of patients, or phenotypes, that have a better response to a specific intervention. The detailed study of energy balance regulation holds promise, as actionable behavioral and physiologic traits could help guide antiobesity medication selection based on previous mechanistic studies. Moreover, the rapid advances in genotyping, multi-omics, and big data analysis might hold the key to discover additional signatures or phenotypes that might respond better to a certain intervention and might permit the widespread adoption of a precision medicine approach for obesity management.

Indexed as

Anti-Obesity AgentsObesityPrecision MedicineHumansWeight LossAnti-Obesity Agents

Identifiers

PMID39127792
PMCPMC11931505

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.