Subtypes of type 2 diabetes determined from clinical parameters
(2020) In Diabetes 69(10). p.2086-2093- Abstract
Type 2 diabetes (T2D) is defined by a single metabolite, glucose, but is increasingly recognized as a highly heterogeneous disease, including individuals with varying clinical characteristics, disease progression, drug response, and risk of complications. Identification of subtypes with differing risk profiles and disease etiologies at diagnosis could open up avenues for personalized medicine and allow clinical resources to be focused to the patients who would be most likely to develop diabetic complications, thereby both im-proving patient health and reducing costs for the health sector. More homogeneous populations also offer increased power in experimental, genetic, and clinical studies. Clinical parameters are easily available and... (More)
Type 2 diabetes (T2D) is defined by a single metabolite, glucose, but is increasingly recognized as a highly heterogeneous disease, including individuals with varying clinical characteristics, disease progression, drug response, and risk of complications. Identification of subtypes with differing risk profiles and disease etiologies at diagnosis could open up avenues for personalized medicine and allow clinical resources to be focused to the patients who would be most likely to develop diabetic complications, thereby both im-proving patient health and reducing costs for the health sector. More homogeneous populations also offer increased power in experimental, genetic, and clinical studies. Clinical parameters are easily available and reflect relevant disease pathways, including the effects of both genetic and environmental exposures. We used six clinical parameters (GAD autoantibodies, age at diabetes onset, HbA1c, BMI, and measures of insulin resistance and insulin secretion) to cluster adult-onset diabetes patients into five subtypes. These sub-types have been robustly reproduced in several populations and associated with different risks of complications, comor-bidities, genetics, and response to treatment. Importantly, the group with severe insulin-deficient diabetes (SIDD) had increased risk of retinopathy and neuropathy, whereas the severe insulin-resistant diabetes (SIRD) group had the highest risk for diabetic kidney disease (DKD) and fatty liver, empha-sizing the importance of insulin resistance for DKD and hepatosteatosis in T2D. In conclusion, we believe that sub-classification using these highly relevant parameters could provide a framework for personalized medicine in diabetes.
(Less)
- author
- Ahlqvist, Emma LU ; Prasad, Rashmi B. LU and Groop, Leif LU
- organization
- publishing date
- 2020
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- ANDIS, diabetes, diabetics
- in
- Diabetes
- volume
- 69
- issue
- 10
- pages
- 8 pages
- publisher
- American Diabetes Association Inc.
- external identifiers
-
- pmid:32843567
- scopus:85091469876
- ISSN
- 0012-1797
- DOI
- 10.2337/dbi20-0001
- language
- English
- LU publication?
- yes
- id
- 348596dc-76d5-4f47-8c10-002634223a1d
- date added to LUP
- 2020-10-23 12:49:43
- date last changed
- 2024-06-14 00:37:31
@article{348596dc-76d5-4f47-8c10-002634223a1d,
abstract = {{<p>Type 2 diabetes (T2D) is defined by a single metabolite, glucose, but is increasingly recognized as a highly heterogeneous disease, including individuals with varying clinical characteristics, disease progression, drug response, and risk of complications. Identification of subtypes with differing risk profiles and disease etiologies at diagnosis could open up avenues for personalized medicine and allow clinical resources to be focused to the patients who would be most likely to develop diabetic complications, thereby both im-proving patient health and reducing costs for the health sector. More homogeneous populations also offer increased power in experimental, genetic, and clinical studies. Clinical parameters are easily available and reflect relevant disease pathways, including the effects of both genetic and environmental exposures. We used six clinical parameters (GAD autoantibodies, age at diabetes onset, HbA<sub>1c</sub>, BMI, and measures of insulin resistance and insulin secretion) to cluster adult-onset diabetes patients into five subtypes. These sub-types have been robustly reproduced in several populations and associated with different risks of complications, comor-bidities, genetics, and response to treatment. Importantly, the group with severe insulin-deficient diabetes (SIDD) had increased risk of retinopathy and neuropathy, whereas the severe insulin-resistant diabetes (SIRD) group had the highest risk for diabetic kidney disease (DKD) and fatty liver, empha-sizing the importance of insulin resistance for DKD and hepatosteatosis in T2D. In conclusion, we believe that sub-classification using these highly relevant parameters could provide a framework for personalized medicine in diabetes.</p>}},
author = {{Ahlqvist, Emma and Prasad, Rashmi B. and Groop, Leif}},
issn = {{0012-1797}},
keywords = {{ANDIS; diabetes; diabetics}},
language = {{eng}},
number = {{10}},
pages = {{2086--2093}},
publisher = {{American Diabetes Association Inc.}},
series = {{Diabetes}},
title = {{Subtypes of type 2 diabetes determined from clinical parameters}},
url = {{http://dx.doi.org/10.2337/dbi20-0001}},
doi = {{10.2337/dbi20-0001}},
volume = {{69}},
year = {{2020}},
}