Phenotypic and genetic classification of diabetes
(2022) In Diabetologia 65(11). p.1758-1769- Abstract
The historical subclassification of diabetes into predominantly types 1 and 2 is well appreciated to inadequately capture the heterogeneity seen in patient presentations, disease course, response to therapy and disease complications. This review summarises proposed data-driven approaches to further refine diabetes subtypes using clinical phenotypes and/or genetic information. We highlight the benefits as well as the limitations of these subclassification schemas, including practical barriers to their implementation that would need to be overcome before incorporation into clinical practice. Graphical abstract: [Figure not available: see fulltext.].
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/e7652d0c-1742-45e7-94a3-b6ea42829ffc
- author
- Deutsch, Aaron J. ; Ahlqvist, Emma LU and Udler, Miriam S.
- organization
- publishing date
- 2022
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Cluster analysis, Disease subtypes, Genetics, MODY, Personalised medicine, Polygenic score, Precision medicine, Review, Type 1 diabetes, Type 2 diabetes, ANDIS
- in
- Diabetologia
- volume
- 65
- issue
- 11
- pages
- 1758 - 1769
- publisher
- Springer
- external identifiers
-
- pmid:35953726
- scopus:85135786191
- ISSN
- 0012-186X
- DOI
- 10.1007/s00125-022-05769-4
- language
- English
- LU publication?
- yes
- id
- e7652d0c-1742-45e7-94a3-b6ea42829ffc
- date added to LUP
- 2022-09-12 12:30:39
- date last changed
- 2024-04-04 13:21:55
@article{e7652d0c-1742-45e7-94a3-b6ea42829ffc,
abstract = {{<p>The historical subclassification of diabetes into predominantly types 1 and 2 is well appreciated to inadequately capture the heterogeneity seen in patient presentations, disease course, response to therapy and disease complications. This review summarises proposed data-driven approaches to further refine diabetes subtypes using clinical phenotypes and/or genetic information. We highlight the benefits as well as the limitations of these subclassification schemas, including practical barriers to their implementation that would need to be overcome before incorporation into clinical practice. Graphical abstract: [Figure not available: see fulltext.].</p>}},
author = {{Deutsch, Aaron J. and Ahlqvist, Emma and Udler, Miriam S.}},
issn = {{0012-186X}},
keywords = {{Cluster analysis; Disease subtypes; Genetics; MODY; Personalised medicine; Polygenic score; Precision medicine; Review; Type 1 diabetes; Type 2 diabetes; ANDIS}},
language = {{eng}},
number = {{11}},
pages = {{1758--1769}},
publisher = {{Springer}},
series = {{Diabetologia}},
title = {{Phenotypic and genetic classification of diabetes}},
url = {{http://dx.doi.org/10.1007/s00125-022-05769-4}},
doi = {{10.1007/s00125-022-05769-4}},
volume = {{65}},
year = {{2022}},
}