This letter aims to increase interest in better classification of type 2 diabetes. This can be done in a simple and cheap way via determination of autoantibodies. Autoantibody analysis can be used to detect the 7-12% of people with diabetes that is phenotypic of type 2 diabetes but is, in fact, latent autoimmune diabetes in adults (LADA), which may be regarded as a variant of type 1 diabetes. This may help to explain why some individuals with type 2 diabetes do not go into remission after reducing their weight, while others do, and why remission sometimes ends earlier than expected. Improved classification of diabetes may play an important role in determining adequate therapy.
Keyphrases
- type diabetes
- glycemic control
- cardiovascular disease
- machine learning
- deep learning
- systemic lupus erythematosus
- solid phase extraction
- weight loss
- body mass index
- molecularly imprinted
- multiple sclerosis
- ulcerative colitis
- stem cells
- skeletal muscle
- adipose tissue
- mass spectrometry
- mesenchymal stem cells
- bone marrow
- liquid chromatography