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Review
. 2024 Mar;24(3):27-44.
doi: 10.1007/s11892-024-01533-7. Epub 2024 Jan 31.

Lessons and Applications of Omics Research in Diabetes Epidemiology

Gechang Yu #  1   2   3 , Henry C H Tam #  1   2   3 , Chuiguo Huang #  1   2   3 , Mai Shi #  1   2   3 , Cadmon K P Lim  1   2   3 , Juliana C N Chan  1   2   3 , Ronald C W Ma  4   5   6
Affiliations
Review

Lessons and Applications of Omics Research in Diabetes Epidemiology

Gechang Yu et al. Curr Diab Rep. 2024 Mar.

Abstract

Purpose of review: Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies.

Recent findings: We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.

Keywords: Biobanking; Biomarkers; Diabetes; Epidemiology; Epigenetics; Genetics; Phenotype; Precision medicine.

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Conflict of interest statement

JCNC, CKPL, RCWM are co-founders of GemVCare, a technology start-up initiated with support from the Hong Kong Government Innovation and Technology Commission and its Technology Start-up Support Scheme for Universities (TSSSU).

Figures

Fig. 1
Fig. 1
The integration of multi-omics analyses in individuals from cohorts can help to drive the development of precision medicine in diabetes. Legend: each layer represents increasing complexity which have arisen from the genome, epigenome, transcriptome, proteome, metabolome and exposome. These information, representing deep phenotyping of individuals, may provide information that can help inform and guide disease classification and treatment selection, as well as predict future risk of complications. Precision Medicine in Diabetes reflects the overall efforts to utilize these as well as clinical information to guide treatment selection and clinical decisions
See this image and copyright information in PMC

References

    1. Magliano DJ, Boyko EJ, IDF Diabetes Atlas Committee. IDF Diabetes Atlas. IDF diabetes atlas. Brussels: International Diabetes Federation © International Diabetes Federation, 2021.
    1. Chung WK, Erion K, Florez JC, Hattersley AT, Hivert MF, Lee CG, et al. Precision medicine in diabetes: a consensus report from the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD) Diabetes Care. 2020;43(7):1617–1635. doi: 10.2337/dci20-0022. - DOI - PMC - PubMed
    1. Kirwan JA, Brennan L, Broadhurst D, Fiehn O, Cascante M, Dunn WB, et al. Preanalytical Processing and biobanking procedures of biological samples for metabolomics research: a white paper, Community Perspective (for "Precision Medicine and Pharmacometabolomics Task Group"-The Metabolomics Society Initiative) Clin Chem. 2018;64(8):1158–1182. doi: 10.1373/clinchem.2018.287045. - DOI - PubMed
    1. Peakman TC, Elliott P. The UK Biobank sample handling and storage validation studies. Int J Epidemiol. 2008;37(Suppl 1):i2–6. doi: 10.1093/ije/dyn019. - DOI - PubMed
    1. Altobelli E, Chiarelli F, Valenti M, Verrotti A, Blasetti A, Di Orio F. Family history and risk of insulin-dependent diabetes mellitus: a population-based case-control study. Acta Diabetol. 1998;35(1):57–60. doi: 10.1007/s005920050102. - DOI - PubMed

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