Cargando…
Human genetics as a model for target validation: finding new therapies for diabetes
Type 2 diabetes is a global epidemic with major effects on healthcare expenditure and quality of life. Currently available treatments are inadequate for the prevention of comorbidities, yet progress towards new therapies remains slow. A major barrier is the insufficiency of traditional preclinical m...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5423999/ https://www.ncbi.nlm.nih.gov/pubmed/28447115 http://dx.doi.org/10.1007/s00125-017-4270-y |
_version_ | 1783235043198500864 |
---|---|
author | Thomsen, Soren K. Gloyn, Anna L. |
author_facet | Thomsen, Soren K. Gloyn, Anna L. |
author_sort | Thomsen, Soren K. |
collection | PubMed |
description | Type 2 diabetes is a global epidemic with major effects on healthcare expenditure and quality of life. Currently available treatments are inadequate for the prevention of comorbidities, yet progress towards new therapies remains slow. A major barrier is the insufficiency of traditional preclinical models for predicting drug efficacy and safety. Human genetics offers a complementary model to assess causal mechanisms for target validation. Genetic perturbations are ‘experiments of nature’ that provide a uniquely relevant window into the long-term effects of modulating specific targets. Here, we show that genetic discoveries over the past decades have accurately predicted (now known) therapeutic mechanisms for type 2 diabetes. These findings highlight the potential for use of human genetic variation for prospective target validation, and establish a framework for future applications. Studies into rare, monogenic forms of diabetes have also provided proof-of-principle for precision medicine, and the applicability of this paradigm to complex disease is discussed. Finally, we highlight some of the limitations that are relevant to the use of genome-wide association studies (GWAS) in the search for new therapies for diabetes. A key outstanding challenge is the translation of GWAS signals into disease biology and we outline possible solutions for tackling this experimental bottleneck. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00125-017-4270-y) contains a slideset of the figures for download, which is available to authorised users. |
format | Online Article Text |
id | pubmed-5423999 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-54239992017-05-25 Human genetics as a model for target validation: finding new therapies for diabetes Thomsen, Soren K. Gloyn, Anna L. Diabetologia Review Type 2 diabetes is a global epidemic with major effects on healthcare expenditure and quality of life. Currently available treatments are inadequate for the prevention of comorbidities, yet progress towards new therapies remains slow. A major barrier is the insufficiency of traditional preclinical models for predicting drug efficacy and safety. Human genetics offers a complementary model to assess causal mechanisms for target validation. Genetic perturbations are ‘experiments of nature’ that provide a uniquely relevant window into the long-term effects of modulating specific targets. Here, we show that genetic discoveries over the past decades have accurately predicted (now known) therapeutic mechanisms for type 2 diabetes. These findings highlight the potential for use of human genetic variation for prospective target validation, and establish a framework for future applications. Studies into rare, monogenic forms of diabetes have also provided proof-of-principle for precision medicine, and the applicability of this paradigm to complex disease is discussed. Finally, we highlight some of the limitations that are relevant to the use of genome-wide association studies (GWAS) in the search for new therapies for diabetes. A key outstanding challenge is the translation of GWAS signals into disease biology and we outline possible solutions for tackling this experimental bottleneck. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00125-017-4270-y) contains a slideset of the figures for download, which is available to authorised users. Springer Berlin Heidelberg 2017-04-26 2017 /pmc/articles/PMC5423999/ /pubmed/28447115 http://dx.doi.org/10.1007/s00125-017-4270-y Text en © The Author(s) 2017 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 | Review Thomsen, Soren K. Gloyn, Anna L. Human genetics as a model for target validation: finding new therapies for diabetes |
title | Human genetics as a model for target validation: finding new therapies for diabetes |
title_full | Human genetics as a model for target validation: finding new therapies for diabetes |
title_fullStr | Human genetics as a model for target validation: finding new therapies for diabetes |
title_full_unstemmed | Human genetics as a model for target validation: finding new therapies for diabetes |
title_short | Human genetics as a model for target validation: finding new therapies for diabetes |
title_sort | human genetics as a model for target validation: finding new therapies for diabetes |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5423999/ https://www.ncbi.nlm.nih.gov/pubmed/28447115 http://dx.doi.org/10.1007/s00125-017-4270-y |
work_keys_str_mv | AT thomsensorenk humangeneticsasamodelfortargetvalidationfindingnewtherapiesfordiabetes AT gloynannal humangeneticsasamodelfortargetvalidationfindingnewtherapiesfordiabetes |