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Cited by 10Bioinformatics and Genomic NetworksGenetic Associations and EpidemiologyChronic Kidney Disease and Diabetes

Insights into the molecular underpinning of type 2 diabetes complications

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Singh, Archit, Bocher, Ozvan, Zeggini, Eleftheria·2025·Human Molecular Genetics
DOI 10.1093/hmg/ddae203PMC PMC11891870
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Abstract

Type 2 diabetes (T2D) complications pose a significant global health challenge. Omics technologies have been employed to investigate these complications and identify the biological pathways involved. In this review, we focus on four major T2D complications: diabetic kidney disease, diabetic retinopathy, diabetic neuropathy, and cardiovascular complications. We discuss advancements in omics research, summarizing findings from genetic, epigenomic, transcriptomic, proteomic, and metabolomic studies across different ancestries and disease-relevant tissues. We stress the importance of integrating multi-omics techniques to elucidate the biological mechanisms underlying T2D complications and advocate for ancestrally diverse studies. Ultimately, these insights will improve risk prediction for T2D complications and inform translation strategies.

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  • Omics data, including transcriptomics, proteomics, and metabolomics, have injected mechanistic insights into predictive modeling for diabetic complications.

    “Omics data, including transcriptomics, proteomics, and metabolomics, have injected mechanistic insights into predictive modeling for diabetic complications [158–160].”

    From Artificial intelligence-powered prediction of diabetic complications: from clinical data to molecular omics (2026) · cites this paper as [158]

    The Abstract says transcriptomic, proteomic, and metabolomic studies have identified biological mechanisms underlying type 2 diabetes complications. The Discussion and future directions section says further multi-omics integration will likely improve prediction; it does not establish that these mechanistic insights have already been incorporated into predictive models. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

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Cited by

Sorted by citations

Authors
Singh, A., Bocher, O., & Zeggini, E.
Affiliations
  • Helmholtz Munich (DE)
  • TUM Klinikum (DE)
Corresponding author
Zeggini, Eleftheria
ORCID
Venue
Human Molecular Genetics
Publisher
Oxford University Press (OUP)
Published
2025-01-14
Volume
34
Issue
6
Pages
469-480
ISSN
  • 0964-6906 (ISSN-L)
  • 1460-2083
DOI
10.1093/hmg/ddae203
PMC
PMC11891870
OpenAlex
W4406382007
Cited by
10
References
4
Citations by year
2026: 5 · 2025: 5
FWCI
0.89
Type
journal article
Language
en
Open access
Licence
Locations
  • Human Molecular Genetics (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
Funders
European Union’s Horizon 2020 research and innovation program (101017802)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Health Sciences › Medicine › Nephrology › Chronic Kidney Disease and Diabetes
Keywords
type 2 diabetes complications, diabetic nephropathy, diabetic retinopathy, diabetic neuropathy, cardiovascular complications, multi-omics integration, epigenomics, transcriptomics, proteomics, metabolomics, genetic risk prediction, ancestry diversity
MeSH terms
Cardiovascular Diseases, Diabetes Mellitus, Type 2, Diabetic Nephropathies, Diabetic Neuropathies, Diabetic Retinopathy, Humans, Proteomics, Diabetes Complications, Metabolomics, Epigenomics

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