Cargando…
Prioritising Risk Factors for Type 2 Diabetes: Causal Inference through Genetic Approaches
PURPOSE OF THE REVIEW: Causality has been demonstrated for few of the many putative risk factors for type 2 diabetes (T2D) emerging from observational epidemiology. Genetic approaches are increasingly being used to infer causality, and in this review, we discuss how genetic discoveries have shaped o...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5960479/ https://www.ncbi.nlm.nih.gov/pubmed/29779155 http://dx.doi.org/10.1007/s11892-018-1009-1 |
_version_ | 1783324587171250176 |
---|---|
author | Wittemans, Laura B. L. Lotta, Luca A. Langenberg, Claudia |
author_facet | Wittemans, Laura B. L. Lotta, Luca A. Langenberg, Claudia |
author_sort | Wittemans, Laura B. L. |
collection | PubMed |
description | PURPOSE OF THE REVIEW: Causality has been demonstrated for few of the many putative risk factors for type 2 diabetes (T2D) emerging from observational epidemiology. Genetic approaches are increasingly being used to infer causality, and in this review, we discuss how genetic discoveries have shaped our understanding of the causal role of factors associated with T2D. RECENT FINDINGS: Genetic discoveries have led to the identification of novel potential aetiological factors of T2D, including the protective role of peripheral fat storage capacity and specific metabolic pathways, such as the branched-chain amino acid breakdown. Consideration of specific genetic mechanisms contributing to overall lipid levels has suggested that distinct physiological processes influencing lipid levels may influence diabetes risk differentially. Genetic approaches have also been used to investigate the role of T2D and related metabolic traits as causal risk factors for other disease outcomes, such as cancer, but comprehensive studies are lacking. SUMMARY: Genome-wide association studies of T2D and metabolic traits coupled with high-throughput molecular phenotyping and in-depth characterisation and follow-up of individual loci have provided better understanding of aetiological factors contributing to T2D. |
format | Online Article Text |
id | pubmed-5960479 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-59604792018-05-25 Prioritising Risk Factors for Type 2 Diabetes: Causal Inference through Genetic Approaches Wittemans, Laura B. L. Lotta, Luca A. Langenberg, Claudia Curr Diab Rep Genetics (AP Morris, Section Editor) PURPOSE OF THE REVIEW: Causality has been demonstrated for few of the many putative risk factors for type 2 diabetes (T2D) emerging from observational epidemiology. Genetic approaches are increasingly being used to infer causality, and in this review, we discuss how genetic discoveries have shaped our understanding of the causal role of factors associated with T2D. RECENT FINDINGS: Genetic discoveries have led to the identification of novel potential aetiological factors of T2D, including the protective role of peripheral fat storage capacity and specific metabolic pathways, such as the branched-chain amino acid breakdown. Consideration of specific genetic mechanisms contributing to overall lipid levels has suggested that distinct physiological processes influencing lipid levels may influence diabetes risk differentially. Genetic approaches have also been used to investigate the role of T2D and related metabolic traits as causal risk factors for other disease outcomes, such as cancer, but comprehensive studies are lacking. SUMMARY: Genome-wide association studies of T2D and metabolic traits coupled with high-throughput molecular phenotyping and in-depth characterisation and follow-up of individual loci have provided better understanding of aetiological factors contributing to T2D. Springer US 2018-05-19 2018 /pmc/articles/PMC5960479/ /pubmed/29779155 http://dx.doi.org/10.1007/s11892-018-1009-1 Text en © The Author(s) 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Genetics (AP Morris, Section Editor) Wittemans, Laura B. L. Lotta, Luca A. Langenberg, Claudia Prioritising Risk Factors for Type 2 Diabetes: Causal Inference through Genetic Approaches |
title | Prioritising Risk Factors for Type 2 Diabetes: Causal Inference through Genetic Approaches |
title_full | Prioritising Risk Factors for Type 2 Diabetes: Causal Inference through Genetic Approaches |
title_fullStr | Prioritising Risk Factors for Type 2 Diabetes: Causal Inference through Genetic Approaches |
title_full_unstemmed | Prioritising Risk Factors for Type 2 Diabetes: Causal Inference through Genetic Approaches |
title_short | Prioritising Risk Factors for Type 2 Diabetes: Causal Inference through Genetic Approaches |
title_sort | prioritising risk factors for type 2 diabetes: causal inference through genetic approaches |
topic | Genetics (AP Morris, Section Editor) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5960479/ https://www.ncbi.nlm.nih.gov/pubmed/29779155 http://dx.doi.org/10.1007/s11892-018-1009-1 |
work_keys_str_mv | AT wittemanslaurabl prioritisingriskfactorsfortype2diabetescausalinferencethroughgeneticapproaches AT lottalucaa prioritisingriskfactorsfortype2diabetescausalinferencethroughgeneticapproaches AT langenbergclaudia prioritisingriskfactorsfortype2diabetescausalinferencethroughgeneticapproaches |