Lessons and Applications of Omics Research in Diabetes Epidemiology
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. Summary 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..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:24 |
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| Enthalten in: |
Current diabetes reports - 24(2024), 3 vom: 31. Jan., Seite 27-44 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Yu, Gechang [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
Biobanking |
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| Anmerkungen: |
© The Author(s) 2024 |
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| doi: |
10.1007/s11892-024-01533-7 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
SPR054808774 |
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| 520 | |a 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. Summary 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. | ||
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| 700 | 1 | |a Lim, Cadmon K. P. |4 aut | |
| 700 | 1 | |a Chan, Juliana C. N. |4 aut | |
| 700 | 1 | |a Ma, Ronald C. W. |4 aut | |
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