Evidence mapPaperPMID 41212412Full record

ReviewJournal of endocrinological investigation2025

Precision obesity medicine: A phenotype-guided framework for pharmacologic therapy across the lifespan.

Dario Tuccinardi, Davide Masi, Mikiko Watanabe, Valeria Zanghi Buffi, Francesco De Domenico, Sabrina Berti, Valentina Cipriani, Melania Manco, Silvia Manfrini, Uberto Pagotto

Abstract readReview
In one paragraph

Review in Journal of endocrinological investigation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
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  10. 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

10 authors.

Dario TuccinardiDepartment of Endocrinology and Diabetes, University Campus Bio-Medico of Rome, Rome, 00128, Italy. D.Tuccinardi@policlinicocampus.it.ORCID http://orcid.org/0000-0002-9139-7159
Davide MasiDepartment of Experimental Medicine, Section of Medical Pathophysiology, Food Science and Endocrinology, Sapienza University of Rome, Rome, 00161, Italy.
Mikiko WatanabeDepartment of Experimental Medicine, Section of Medical Pathophysiology, Food Science and Endocrinology, Sapienza University of Rome, Rome, 00161, Italy. mikiko.watanabe@uniroma1.it.
Valeria Zanghi BuffiDepartment of Endocrinology and Diabetes, University Campus Bio-Medico of Rome, Rome, 00128, Italy.
Francesco De DomenicoDepartment of Endocrinology and Diabetes, University Campus Bio-Medico of Rome, Rome, 00128, Italy.
Sabrina BertiDepartment of Clinical and Surgical Sciences, University of Bologna, Bologna, 40126, Italy.
Valentina CiprianiFondazione Policlinico Universitario Campus Bio-Medico, 00128, Rome, Italy.
Melania MancoResearch Unit for Preventive and Predictive Medicine, Bambino Gesù Children's Hospital, IRCCS, Rome, Italy.
Silvia Manfrini *Department of Endocrinology and Diabetes, University Campus Bio-Medico of Rome, Rome, 00128, Italy.
Uberto Pagotto *Department of Clinical and Surgical Sciences, University of Bologna, Bologna, 40126, Italy.

Funding

EUROPEAN UNION NextGenerationEU, under the Italian Ministry of University and Research (MUR) PRIN 2022 program, Mission 4, Component 1, CUP C53D23006490001.
6 · The paper itself

Abstract

objectiveObesity is a biologically complex and heterogeneous disease that requires individualized, phenotype- and complication-oriented therapeutic strategies. The introduction of advanced pharmacotherapies, including GLP-1 receptor agonists (GLP-1 RA), dual Glucose-dependent Insulinotropic Polypeptide/Glucagon-like Peptide-1 (GIP/GLP-1) agonists, and emerging triple agonists, has facilitated a shift from weight-centric goals to precision-based obesity care. This review provides a clinical framework for pharmacologic treatment, organized by phenotype, obesity-related complications, age, and behavioral traits.

designNarrative review of randomized trials, meta-analyses, real-world evidence, and international guidelines through May 2025. Evidence was synthesized across key obesity phenotypes, cardiometabolic, hepatic, renal, mechanical, behavioral, and stratified by life stage, including pediatric, reproductive-age, and older adults, with attention to safety, cost-effectiveness, and special populations.

resultsIn established Atherosclerotic Cardiovascular Disease, semaglutide significantly reduces major adverse cardiovascular events. Tirzepatide offers cardiometabolic benefits for high-risk people without overt disease. Both agents improve symptoms and function in Heart Failure with Preserved Ejection Fraction, irrespective of glycemia or weight loss. In Chronic Kidney Disease, they decrease albuminuria and eGFR decline. In Metabolic Dysfunction-Associated Steatotic Liver Disease, GLP-1 RAs and GIP/GLP-1 RAs demonstrate marked histological improvements. Mechanical complications such as osteoarthritis and sleep apnea are improved by anti-obesity medications-induced weight loss. GLP-1 RAs and naltrexone/bupropion prove effective against binge and emotional eating. In youths, liraglutide and semaglutide are both approved and effective. Liraglutide and orlistat preserve lean mass alongside resistance training and adequate protein intake in older and sarcopenic people.

conclusionsAn anti-obesity treatment framework focused on both phenotype and complication burden improves the personalization of obesity care and supports clinical decision-making throughout a person’s lifespan.

Indexed as

Anti-Obesity AgentsLongevityObesityPrecision MedicineHumansPhenotypeSemaglutideTirzepatideAnti-Obesity AgentsSemaglutideTirzepatideAnti-obesity pharmacotherapyIncretin-based therapiesPersonalized obesity medicinePhenotype-guided treatmentPrecision medicine in obesity

Identifiers

PMID41212412
PMCPMC12640352

What Socratic holds

Texttitle and abstract
LicenceCC BY
Read underepoch 390

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 Socratic graph.