Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2025 Apr 10;26(8):3572.
doi: 10.3390/ijms26083572.

Advances in Metabolomics: A Comprehensive Review of Type 2 Diabetes and Cardiovascular Disease Interactions

Lilian Fernandes Silva  1   2 , Markku Laakso  1   3
Affiliations
Review

Advances in Metabolomics: A Comprehensive Review of Type 2 Diabetes and Cardiovascular Disease Interactions

Lilian Fernandes Silva et al. Int J Mol Sci. .

Abstract

Type 2 diabetes (T2D) and cardiovascular diseases (CVDs) are major public health challenges worldwide. Metabolomics, the exhaustive assessment of metabolites in biological systems, offers important insights regarding the metabolic disturbances related to these disorders. Recent advances toward the integration of metabolomics into clinical practice to facilitate the discovery of novel biomarkers that can improve the diagnosis, prognosis, and treatment of T2D and CVDs are discussed in this review. Metabolomics offers the potential to characterize the key metabolic alterations associated with disease pathophysiology and treatment. T2D is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms; therefore, the disease-causing pathways of T2D are not completely understood. Recent studies have identified several robust clusters of T2D variants representing biologically meaningful, distinct pathways, such as the beta cell and proinsulin cluster related to pancreatic insulin secretion, obesity, lipodystrophy, the liver/lipid cluster, glycemia, and blood pressure, and metabolic syndrome clusters representing different pathways causing insulin resistance. Regarding CVDs, recent studies have allowed the metabolomic profile to delineate pathways that contribute to atherosclerosis and heart failure, as well as to the development of targeted therapy. This review also covers the role of metabolomics in integrated metabolic genomics and other omics platforms to better understand disease mechanisms, along with the transition toward precision medicine. This review further investigates the use of metabolomics in multi-metabolite modeling to enhance risk prediction models for predicting the first occurrence of major adverse cardiovascular events among individuals with T2D, highlighting the value of such approaches in optimizing the preventive and therapeutic models used in clinical practice.

Keywords: cardiovascular disease; coronary artery disease; metabolites; metabolomics; type 2 diabetes.

PubMed Disclaimer

Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Main strengths and limitations of NMR spectroscopy and mass spectrometry techniques.
Figure 2
Figure 2
Integrative profiling and the future directions of integrative metabolic profiling in T2D.
Figure 3
Figure 3
Comparative analysis of type 2 diabetes and cardiovascular diseases.
Figure 4
Figure 4
Future advancements in metabolomics, aiming at integration into clinical practice.
See this image and copyright information in PMC

References

    1. Buergel T., Steinfeldt J., Ruyoga G., Pietzner M., Bizzarri D., Vojinovic D., zu Belzen J.U., Loock L., Kittner P., Christmann L., et al. Metabolomic profiles predict individual multidisease outcomes. Nat. Med. 2022;28:2309–2320. doi: 10.1038/s41591-022-01980-3. - DOI - PMC - PubMed
    1. World Health Organization . Urgent Action Needed as Global Diabetes Cases Increase Four-Fold Over Past Decades. World Health Organization; Geneva, Switzerland: 2025.
    1. Yin X., Chan L.S., Bose D., Jackson A.U., VandeHaar P., Locke A.E., Fuchsberger C., Stringham H.M., Welch R., Yu K., et al. Genome-wide association studies of metabolites in Finnish men identify disease-relevant loci. Nat. Commun. 2022;13:1644. doi: 10.1038/s41467-022-29143-5. - DOI - PMC - PubMed
    1. Yin X., Bose D., Kwon A., Hanks S.C., Jackson A.U., Stringham H.M., Welch R., Oravilahti A., Silva L.F., Locke A.E., et al. Integrating transcriptomics, metabolomics, and GWAS helps reveal molecular mechanisms for metabolite levels and disease risk. Am. J. Hum. Genet. 2022;109:1727–1741. doi: 10.1016/j.ajhg.2022.08.007. - DOI - PMC - PubMed
    1. Xie R., Seum T., Sha S., Trares K., Holleczek B., Brenner H., Schöttker B. Improving 10-year cardiovascular risk prediction in patients with type 2 diabetes with metabolomics. Cardiovasc. Diabetol. 2025;24:18. doi: 10.1186/s12933-025-02581-3. - DOI - PMC - PubMed

MeSH terms

LinkOut - more resources