Progress in genetics of type 2 diabetes and diabetic complications

Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life‐style intervention more...

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Published inJournal of Diabetes Investigation Vol. 14; no. 4; pp. 503 - 515
Main Authors Shojima, Nobuhiro, Yamauchi, Toshimasa
Format Journal Article
LanguageEnglish
Published Japan Wiley 01.04.2023
John Wiley & Sons, Inc
John Wiley and Sons Inc
Subjects
Amino acids
Asian people
Association analysis
Biobanks
Diabetes
Diabetes Complications
Diabetes mellitus (non-insulin dependent)
Diabetes Mellitus, Type 2
Diabetes Mellitus, Type 2 - complications
Diabetes Mellitus, Type 2 - genetics
Diabetic complications
Disease
Diseases of the endocrine glands. Clinical endocrinology
Environmental factors
Evolution & development
Gene expression
Gene loci
Genetic Predisposition to Disease
Genome-wide association studies
Genome-Wide Association Study
Genome-Wide Association Study - methods
Genomes
Genotype & phenotype
Humans
Inflammation
Insulin resistance
Meta-analysis
Metabolomics
Minority & ethnic groups
Molecular modelling
Polymorphism, Single Nucleotide
Population genetics
Precision medicine
Proteomics
RC648-665
Review
Risk Factors
Type 2 diabetes
Japan
Type 2 diabetes
Precision medicine
Diabetic complications
Online AccessGet full text
ISSN2040-1116
2040-1124
2040-1124
DOI10.1111/jdi.13970

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Abstract Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life‐style intervention more accurately for individuals. Genome‐wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large‐scale genome‐wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi‐polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi‐omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications. Genome‐wide association studies (GWAS) were conducted and new genetic loci were identified that modulate the risk of developing type 2 diabetes and diabetic complications. The polygenic risk score and multi‐omics analysis have begun to decipher the molecular mechanisms of diabetes and its complications.
AbstractList Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life-style intervention more accurately for individuals. Genome-wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large-scale genome-wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi-polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi-omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications.
Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life-style intervention more accurately for individuals. Genome-wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large-scale genome-wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi-polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi-omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications.Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life-style intervention more accurately for individuals. Genome-wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large-scale genome-wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi-polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi-omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications.
Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life‐style intervention more accurately for individuals. Genome‐wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large‐scale genome‐wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi‐polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi‐omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications. Genome‐wide association studies (GWAS) were conducted and new genetic loci were identified that modulate the risk of developing type 2 diabetes and diabetic complications. The polygenic risk score and multi‐omics analysis have begun to decipher the molecular mechanisms of diabetes and its complications.
Abstract Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is expected to predict the risk of developing diabetes and complications and to predict the effects of medications and life‐style intervention more accurately for individuals. Genome‐wide association studies (GWAS) have been conducted in European and Asian populations and new genetic loci have been identified that modulate the risk of developing type 2 diabetes. Novel loci were discovered by GWAS in diabetic complications with increasing sample sizes. Large‐scale genome‐wide association analysis and polygenic risk scores using biobank information is making it possible to predict the development of type 2 diabetes. In the ADVANCE clinical trial of type 2 diabetes, a multi‐polygenic risk score was useful to predict diabetic complications and their response to treatment. Proteomics and metabolomics studies have been conducted and have revealed the associations between type 2 diabetes and inflammatory signals and amino acid synthesis. Using multi‐omics analysis, comprehensive molecular mechanisms have been elucidated to guide the development of targeted therapy for type 2 diabetes and diabetic complications.
Author Nobuhiro Shojima
Toshimasa Yamauchi
AuthorAffiliation 1 Department of Diabetes and Metabolic Diseases, Graduate School of Medicine The University of Tokyo Tokyo Japan
AuthorAffiliation_xml – name: 1 Department of Diabetes and Metabolic Diseases, Graduate School of Medicine The University of Tokyo Tokyo Japan
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  givenname: Toshimasa
  surname: Yamauchi
  fullname: Yamauchi, Toshimasa
  email: tyamau@m.u-tokyo.ac.jp
  organization: The University of Tokyo
BackLink https://cir.nii.ac.jp/crid/1872835442871241600$$DView record in CiNii
https://www.ncbi.nlm.nih.gov/pubmed/36639962$$D View this record in MEDLINE/PubMed
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Copyright 2023 The Authors. published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.
2023 The Authors. Journal of Diabetes Investigation published by Asian Association for the Study of Diabetes (AASD) and John Wiley & Sons Australia, Ltd.
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Keywords Type 2 diabetes
Precision medicine
Diabetic complications
Language English
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2021; 30
2020; 8
2020; 5
2020; 52
2021; 599
1997; 15
2019; 68
2011; 20
2005; 308
2014; 57
2014; 8
2006; 12
2020; 582
2015; 11
2020; 105
2018; 67
2017; 177
2007; 56
2016; 59
2021; 13
2014; 507
2013; 36
2014; 506
2020
2015; 21
2016; 65
2011; 44
2011; 43
2020; 69
2017; 19
2018; 50
2012; 7
2012; 8
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Snippet Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic data is...
Abstract Type 2 diabetes results from a complex interaction between genetic and environmental factors. Precision medicine for type 2 diabetes using genetic...
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SubjectTerms Amino acids
Asian people
Association analysis
Biobanks
Diabetes
Diabetes Complications
Diabetes mellitus (non-insulin dependent)
Diabetes Mellitus, Type 2
Diabetes Mellitus, Type 2 - complications
Diabetes Mellitus, Type 2 - genetics
Diabetic complications
Disease
Diseases of the endocrine glands. Clinical endocrinology
Environmental factors
Evolution & development
Gene expression
Gene loci
Genetic Predisposition to Disease
Genome-wide association studies
Genome-Wide Association Study
Genome-Wide Association Study - methods
Genomes
Genotype & phenotype
Humans
Inflammation
Insulin resistance
Meta-analysis
Metabolomics
Minority & ethnic groups
Molecular modelling
Polymorphism, Single Nucleotide
Population genetics
Precision medicine
Proteomics
RC648-665
Review
Risk Factors
Type 2 diabetes
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Title Progress in genetics of type 2 diabetes and diabetic complications
URI https://cir.nii.ac.jp/crid/1872835442871241600
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Volume 14
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