Biomarkers for type 2 diabetes
Background: The prevalence and incidence of type 2 diabetes (T2D), representing >90% of all cases of diabetes, are increasing rapidly worldwide. Identification of individuals at high risk of developing diabetes is of great importance as early interventions might delay or even prevent full-blown d...
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| Format: | Article |
| Language: | English |
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Elsevier
2019-09-01
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| Series: | Molecular Metabolism |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2212877819305770 |
| _version_ | 1819039381196898304 |
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| author | Markku Laakso |
| author_facet | Markku Laakso |
| author_sort | Markku Laakso |
| collection | DOAJ |
| description | Background: The prevalence and incidence of type 2 diabetes (T2D), representing >90% of all cases of diabetes, are increasing rapidly worldwide. Identification of individuals at high risk of developing diabetes is of great importance as early interventions might delay or even prevent full-blown disease. T2D is a complex disease caused by multiple genetic loci in interplay with lifestyle and environmental factors. Recently over 400 distinct association signals were published; these explain 18% of the risk of T2D. Scope of review: In this review there is a major focus on risk factors and genetic and non-genetic biomarkers for the risk of T2D identified especially in large prospective population-based studies, and studies testing causality of the biomarkers for T2D in Mendelian randomization studies. Another focus is on understanding genome-phenome interplay in the classification of individuals with T2D into subgroups. Major conclusions: Several recent large population-based studies and their meta-analyses have identified multiple potential genetic and non-genetic biomarkers for the risk of T2D. Combination of genetic variants and physiologically characterized pathways improves the classification of individuals with T2D into subgroups, and is also paving the way to a precision medicine approach, in T2D. Keywords: Type 2 diabetes, Biomarkers, Mendelian randomization, Genomics |
| first_indexed | 2024-12-21T08:52:18Z |
| format | Article |
| id | doaj.art-ab1401647a674b1cae6140fe943ff15d |
| institution | Directory Open Access Journal |
| issn | 2212-8778 |
| language | English |
| last_indexed | 2024-12-21T08:52:18Z |
| publishDate | 2019-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Molecular Metabolism |
| spelling | doaj.art-ab1401647a674b1cae6140fe943ff15d2022-12-21T19:09:38ZengElsevierMolecular Metabolism2212-87782019-09-0127S139S146Biomarkers for type 2 diabetesMarkku Laakso0Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, 70210, Kuopio, FinlandBackground: The prevalence and incidence of type 2 diabetes (T2D), representing >90% of all cases of diabetes, are increasing rapidly worldwide. Identification of individuals at high risk of developing diabetes is of great importance as early interventions might delay or even prevent full-blown disease. T2D is a complex disease caused by multiple genetic loci in interplay with lifestyle and environmental factors. Recently over 400 distinct association signals were published; these explain 18% of the risk of T2D. Scope of review: In this review there is a major focus on risk factors and genetic and non-genetic biomarkers for the risk of T2D identified especially in large prospective population-based studies, and studies testing causality of the biomarkers for T2D in Mendelian randomization studies. Another focus is on understanding genome-phenome interplay in the classification of individuals with T2D into subgroups. Major conclusions: Several recent large population-based studies and their meta-analyses have identified multiple potential genetic and non-genetic biomarkers for the risk of T2D. Combination of genetic variants and physiologically characterized pathways improves the classification of individuals with T2D into subgroups, and is also paving the way to a precision medicine approach, in T2D. Keywords: Type 2 diabetes, Biomarkers, Mendelian randomization, Genomicshttp://www.sciencedirect.com/science/article/pii/S2212877819305770 |
| spellingShingle | Markku Laakso Biomarkers for type 2 diabetes Molecular Metabolism |
| title | Biomarkers for type 2 diabetes |
| title_full | Biomarkers for type 2 diabetes |
| title_fullStr | Biomarkers for type 2 diabetes |
| title_full_unstemmed | Biomarkers for type 2 diabetes |
| title_short | Biomarkers for type 2 diabetes |
| title_sort | biomarkers for type 2 diabetes |
| url | http://www.sciencedirect.com/science/article/pii/S2212877819305770 |
| work_keys_str_mv | AT markkulaakso biomarkersfortype2diabetes |