Perspectives on genetic studies of type 2 diabetes from the genome‐wide association studies era to precision medicine
Abstract Genome‐wide association studies (GWAS) have facilitated a substantial and rapid increase in the number of confirmed genetic susceptibility variants for complex diseases. Approximately 700 variants predisposing individuals to the risk for type 2 diabetes have been identified through GWAS unt...
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| Format: | Article |
| Language: | English |
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Wiley
2024-04-01
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| Series: | Journal of Diabetes Investigation |
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| Online Access: | https://doi.org/10.1111/jdi.14149 |
| _version_ | 1797234190665646080 |
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| author | Minako Imamura Shiro Maeda |
| author_facet | Minako Imamura Shiro Maeda |
| author_sort | Minako Imamura |
| collection | DOAJ |
| description | Abstract Genome‐wide association studies (GWAS) have facilitated a substantial and rapid increase in the number of confirmed genetic susceptibility variants for complex diseases. Approximately 700 variants predisposing individuals to the risk for type 2 diabetes have been identified through GWAS until 2023. From 2018 to 2022, hundreds of type 2 diabetes susceptibility loci with smaller effect sizes were identified through large‐scale GWAS with sample sizes of 200,000 to >1 million. The clinical translation of genetic information for type 2 diabetes includes the development of novel therapeutics and risk predictions. Although drug discovery based on loci identified in GWAS remains challenging owing to the difficulty of functional annotation, global efforts have been made to identify novel biological mechanisms and therapeutic targets by applying multi‐omics approaches or searching for disease‐associated coding variants in isolated founder populations. Polygenic risk scores (PRSs), comprising up to millions of associated variants, can identify individuals with higher disease risk than those in the general population. In populations of European descent, PRSs constructed from base GWAS data with a sample size of approximately 450,000 have predicted the onset of diseases well. However, European GWAS‐derived PRSs have limited predictive performance in non‐European populations. The predictive accuracy of a PRS largely depends on the sample size of the base GWAS data. The results of GWAS meta‐analyses for multi‐ethnic groups as base GWAS data and cross‐population polygenic prediction methodology have been applied to establish a universal PRS applicable to small isolated ethnic populations. |
| first_indexed | 2024-04-24T16:28:08Z |
| format | Article |
| id | doaj.art-664e738e011f402bb015a3d4de63db5b |
| institution | Directory Open Access Journal |
| issn | 2040-1116 2040-1124 |
| language | English |
| last_indexed | 2024-04-24T16:28:08Z |
| publishDate | 2024-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | Journal of Diabetes Investigation |
| spelling | doaj.art-664e738e011f402bb015a3d4de63db5b2024-03-30T10:00:09ZengWileyJournal of Diabetes Investigation2040-11162040-11242024-04-0115441042210.1111/jdi.14149Perspectives on genetic studies of type 2 diabetes from the genome‐wide association studies era to precision medicineMinako Imamura0Shiro Maeda1Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine University of the Ryukyus Nishihara‐Cho JapanDepartment of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine University of the Ryukyus Nishihara‐Cho JapanAbstract Genome‐wide association studies (GWAS) have facilitated a substantial and rapid increase in the number of confirmed genetic susceptibility variants for complex diseases. Approximately 700 variants predisposing individuals to the risk for type 2 diabetes have been identified through GWAS until 2023. From 2018 to 2022, hundreds of type 2 diabetes susceptibility loci with smaller effect sizes were identified through large‐scale GWAS with sample sizes of 200,000 to >1 million. The clinical translation of genetic information for type 2 diabetes includes the development of novel therapeutics and risk predictions. Although drug discovery based on loci identified in GWAS remains challenging owing to the difficulty of functional annotation, global efforts have been made to identify novel biological mechanisms and therapeutic targets by applying multi‐omics approaches or searching for disease‐associated coding variants in isolated founder populations. Polygenic risk scores (PRSs), comprising up to millions of associated variants, can identify individuals with higher disease risk than those in the general population. In populations of European descent, PRSs constructed from base GWAS data with a sample size of approximately 450,000 have predicted the onset of diseases well. However, European GWAS‐derived PRSs have limited predictive performance in non‐European populations. The predictive accuracy of a PRS largely depends on the sample size of the base GWAS data. The results of GWAS meta‐analyses for multi‐ethnic groups as base GWAS data and cross‐population polygenic prediction methodology have been applied to establish a universal PRS applicable to small isolated ethnic populations.https://doi.org/10.1111/jdi.14149Genome‐wide association studiesPolygenic risk scoresType 2 diabetes |
| spellingShingle | Minako Imamura Shiro Maeda Perspectives on genetic studies of type 2 diabetes from the genome‐wide association studies era to precision medicine Journal of Diabetes Investigation Genome‐wide association studies Polygenic risk scores Type 2 diabetes |
| title | Perspectives on genetic studies of type 2 diabetes from the genome‐wide association studies era to precision medicine |
| title_full | Perspectives on genetic studies of type 2 diabetes from the genome‐wide association studies era to precision medicine |
| title_fullStr | Perspectives on genetic studies of type 2 diabetes from the genome‐wide association studies era to precision medicine |
| title_full_unstemmed | Perspectives on genetic studies of type 2 diabetes from the genome‐wide association studies era to precision medicine |
| title_short | Perspectives on genetic studies of type 2 diabetes from the genome‐wide association studies era to precision medicine |
| title_sort | perspectives on genetic studies of type 2 diabetes from the genome wide association studies era to precision medicine |
| topic | Genome‐wide association studies Polygenic risk scores Type 2 diabetes |
| url | https://doi.org/10.1111/jdi.14149 |
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