Precision medicine in Type 2 Diabetes
(2019) In Journal of Internal Medicine 285(1). p.40-48- Abstract
The Precision Medicine Initiative defines precision medicine as "an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person." This approach will facilitate more accurate treatment and prevention strategies in contrast to a one-size-fits-all approach, in which disease treatment and prevention strategies are developed for generalized usage. Diabetes is clearly more heterogeneous than the conventional sub-classification into type 1 and type 2 diabetes. Monogenic forms of diabetes like MODY and neonatal diabetes have paved the way for precision medicine in diabetes, as carriers of unique mutations require unique treatment. Diagnosis of... (More)
The Precision Medicine Initiative defines precision medicine as "an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person." This approach will facilitate more accurate treatment and prevention strategies in contrast to a one-size-fits-all approach, in which disease treatment and prevention strategies are developed for generalized usage. Diabetes is clearly more heterogeneous than the conventional sub-classification into type 1 and type 2 diabetes. Monogenic forms of diabetes like MODY and neonatal diabetes have paved the way for precision medicine in diabetes, as carriers of unique mutations require unique treatment. Diagnosis of diabetes in the past has been dependent upon measuring one metabolite, glucose. By instead including 6 variables in a clustering analysis, we could break down diabetes into 5 distinct subgroups, with better prediction of disease progression and outcome. The severe insulin resistant diabetes (SIRD) cluster showed the highest risk of kidney disease and highest prevalence of non-alcoholic fatty liver disease whereas patients in the insulin deficient cluster 2 (SIDD) had the highest risk of retinopathy. In the future this will certainly be improved and expanded by including genetic, epigenetic and other biomarker to allow better prediction of outcome and choice of more precise treatment. This article is protected by copyright. All rights reserved.
(Less)
- author
- Prasad, Rashmi B LU and Groop, Leif LU
- organization
- publishing date
- 2019
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Journal of Internal Medicine
- volume
- 285
- issue
- 1
- pages
- 40 - 48
- publisher
- Wiley-Blackwell
- external identifiers
-
- pmid:30403316
- scopus:85057985665
- ISSN
- 1365-2796
- DOI
- 10.1111/joim.12859
- language
- English
- LU publication?
- yes
- id
- 5bdd11ec-fc8b-4320-bd80-dfb88224f21b
- date added to LUP
- 2018-11-29 18:34:02
- date last changed
- 2024-04-15 17:53:39
@article{5bdd11ec-fc8b-4320-bd80-dfb88224f21b,
abstract = {{<p>The Precision Medicine Initiative defines precision medicine as "an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person." This approach will facilitate more accurate treatment and prevention strategies in contrast to a one-size-fits-all approach, in which disease treatment and prevention strategies are developed for generalized usage. Diabetes is clearly more heterogeneous than the conventional sub-classification into type 1 and type 2 diabetes. Monogenic forms of diabetes like MODY and neonatal diabetes have paved the way for precision medicine in diabetes, as carriers of unique mutations require unique treatment. Diagnosis of diabetes in the past has been dependent upon measuring one metabolite, glucose. By instead including 6 variables in a clustering analysis, we could break down diabetes into 5 distinct subgroups, with better prediction of disease progression and outcome. The severe insulin resistant diabetes (SIRD) cluster showed the highest risk of kidney disease and highest prevalence of non-alcoholic fatty liver disease whereas patients in the insulin deficient cluster 2 (SIDD) had the highest risk of retinopathy. In the future this will certainly be improved and expanded by including genetic, epigenetic and other biomarker to allow better prediction of outcome and choice of more precise treatment. This article is protected by copyright. All rights reserved.</p>}},
author = {{Prasad, Rashmi B and Groop, Leif}},
issn = {{1365-2796}},
language = {{eng}},
number = {{1}},
pages = {{40--48}},
publisher = {{Wiley-Blackwell}},
series = {{Journal of Internal Medicine}},
title = {{Precision medicine in Type 2 Diabetes}},
url = {{http://dx.doi.org/10.1111/joim.12859}},
doi = {{10.1111/joim.12859}},
volume = {{285}},
year = {{2019}},
}