Peer-reviewedCC BY 4.0Frontiers in Pharmacology13 Oct 2026

Insights from multi-omics on GLP-1 receptor agonists in type 2 diabetes and obesity

Asma A. Elashi¹
Laila Hedaya¹
Viviana Maggio²
Khaled Naja¹
Manfredi Rizzo^2,3
Mohamed A. Elrayess^1,4

4 affiliations

¹Biomedical Research Center, QU Health, Qatar University
²School of Medicine, Promise Department, University of Palermo
³Department of Medicine, Ras Al Khaimah (RAK) Medical and Health Sciences University
⁴College of Medicine, QU Health, Qatar University

Abstract

Glucagon like peptide-1 receptor agonists (GLP-1RAs) have revolutionized the management of T2D and obesity. T2D clustering highlights distinct phenotypes that differ in GLP-1RA benefit. While they have markedly improved quality of life for many individuals, converging evidence indicates that genetic variation, metabolomic remodeling, and gut microbiota composition contribute to substantial inter-individual variability in GLP-1RA efficacy and tolerability. GLP-1RAs, in return, can variably affect the metabolome and microbiome composition in treated individuals. This review focuses on human multi-omics GLP-1RA intervention studies, complemented by relevant mechanistic preclinical evidence. Genetic variation in GLP1R, TCF7L2 , and other loci has been associated with differences in glycaemic and weight outcomes, although most findings remain preliminary, inconsistent across populations, or not yet replicated. Pharmacometabolomic studies show recurrent of lipid-related pathways including, glycerophospholipids, sphingolipids, ceramides, amino acids, and bile acids, with drug-specific signatures. GLP-1RAs are also associated with changes in gut microbial composition, including taxa such as Akkermansia and Bacteroides , although the direction and clinical significance of these changes vary across studies due to methodological and population heterogeneity. Multi-omics and AI-based models show promise for predicting treatment response by integrating genetic, metabolic, microbial, and clinical data to supporting more effective and individualized therapy and advancing precision medicine.

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Cite

BibTeX RIS

BibTeX

@article{elashi2026insights,
  title = {{Insights from multi-omics on GLP-1 receptor agonists in type 2 diabetes and obesity}},
  author = {Asma A. Elashi and Laila Hedaya and Viviana Maggio and Khaled Naja and Manfredi Rizzo and Mohamed A. Elrayess},
  journal = {Frontiers in Pharmacology},
  year = {2026},
  month = oct,
  doi = {10.3389/fphar.2026.1812193},
  url = {https://www.frontiersin.org/articles/10.3389/fphar.2026.1812193/full},
  note = {CC BY 4.0},
}

RIS

TY  - JOUR
TI  - Insights from multi-omics on GLP-1 receptor agonists in type 2 diabetes and obesity
AU  - Asma A. Elashi
AU  - Laila Hedaya
AU  - Viviana Maggio
AU  - Khaled Naja
AU  - Manfredi Rizzo
AU  - Mohamed A. Elrayess
PY  - 2026
DA  - 2026/10/13
JO  - Frontiers in Pharmacology
DO  - 10.3389/fphar.2026.1812193
UR  - https://www.frontiersin.org/articles/10.3389/fphar.2026.1812193/full
AB  - Glucagon like peptide-1 receptor agonists (GLP-1RAs) have revolutionized the management of T2D and obesity. T2D clustering highlights distinct phenotypes that differ in GLP-1RA benefit. While they have markedly improved quality of life for many individuals, converging evidence indicates that genetic variation, metabolomic remodeling, and gut microbiota composition contribute to substantial inter-individual variability in GLP-1RA efficacy and tolerability. GLP-1RAs, in return, can variably affect the metabolome and microbiome composition in treated individuals. This review focuses on human multi-omics GLP-1RA intervention studies, complemented by relevant mechanistic preclinical evidence. Genetic variation in GLP1R, TCF7L2 , and other loci has been associated with differences in glycaemic and weight outcomes, although most findings remain preliminary, inconsistent across populations, or not yet replicated. Pharmacometabolomic studies show recurrent of lipid-related pathways including, glycerophospholipids, sphingolipids, ceramides, amino acids, and bile acids, with drug-specific signatures. GLP-1RAs are also associated with changes in gut microbial composition, including taxa such as Akkermansia and Bacteroides , although the direction and clinical significance of these changes vary across studies due to methodological and population heterogeneity. Multi-omics and AI-based models show promise for predicting treatment response by integrating genetic, metabolic, microbial, and clinical data to supporting more effective and individualized therapy and advancing precision medicine.
SN  - 1663-9812
ER  -

Abstract

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