New research suggests that there are five types of diabetes, rather than simply Type 1 or Type 2. Understanding diabetes as a group of five distinct diseases could result in improved diagnosis and more effective, personalized treatment.
Type 1 and Type 2 Diabetes
Diabetes is currently classified as two distinct diseases:
- Type 1 diabetes is an autoimmune condition where the insulin-producing beta cells in the pancreas are destroyed. Type 1 diabetes is incurable and requires regular insulin administration.
- Type 2 diabetes is a metabolic disorder where either not enough insulin is produced, or insulin is ineffectively used, resulting in hyperglycemia. Risk factors include being overweight/obese, increased age, and physical inactivity.
Around 90% of people with diabetes have Type 2; however, this category is highly heterogeneous. New research published in The Lancet Diabetes and Endocrinology now expands this classification to five patient clusters, which could help to improve personalized medicine approaches in diabetes.
The Five Types of Diabetes
Here is an overview of each type and the approximate percentage of the study population it represents:
Cluster 1 Severe Autoimmune Diabetes (6%)
Patients were young, healthy people with a relatively low BMI, displaying poor blood sugar control and with insulin deficiency (broadly similar to the current Type 1 classification). The presence of glutamate decarboxylase antibodies (GADA) was also detected.
Cluster 2 Severe Insulin-Deficient Diabetes (18%)
Patients were very similar to those in cluster 1 (young, healthy weight, unable to produce insulin), but the lack of insulin production is not due to the immune system (GADA-negative patients). People in this cluster have the highest risk of diabetic retinopathy.
Cluster 3 Severe Insulin-Resistant Diabetes (15%)
Observed in patients who were generally overweight/had a high BMI, and were producing insulin but were no longer responding correctly to it. The people in this cluster were the most insulin resistant in the study, and also had a higher propensity for developing diabetic kidney disease than people in Clusters 3 and 4.
Cluster 4 Mild Obesity-Related Diabetes (22%)
These patients were highly overweight, but were more metabolically “normal” then people in Cluster 3, lacking insulin resistance.
Cluster 5 Mild Age-Related Diabetes (39%)
Patients developed only mild glucose control problems and disease, when they were significantly older than patients in the other groups.
Implications for Diagnosis and Personalized Diabetes Treatment
The study authors suggest that this new classification of diabetes types could be a first step towards precision medicine in diabetes, with a more tailored and targeted approach to treatment.
For example, the three severe subtypes could be treated more aggressively than the mild clusters, and cluster 2 patients could potentially have treatment options more similar to cluster 1. Currently cluster 2 would be classified as Type 2 diabetes as the disease is not autoimmune; however, the study data suggests that people in this cluster may have a beta cell defect rather than Type 2 risk factors. This means that treatment should potentially mirror current Type 1 patients rather than Type 2.
As the different clusters also have different risk levels for retinopathy and diabetic kidney disease, early diagnosis and treatment of these complications could improve patient outcomes.
Replication Required Before Updating Diabetes Classifications and Guidelines
While this research is highly promising, it’s important to remember it is just a first step. The study was carried out in Sweden and Finland, requiring replication across the globe to account for genetic and environmental differences in diabetes development and progression.
Hopefully, this study will lead to further research, improved classification, and more steps along the road to personalized medicine in diabetes.
Ahlqvist et al. Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol https://doi.org/10.1016/S2213-8587(18)30051-2.
Pearson. Personalized medicine in diabetes: the role of ‘omics’ and biomarkers. Diabet Med 2016; 33(6):712-7.
Kleinberger and Pollin. Personalized medicine in diabetes mellitus: current opportunities and future prospects. Ann N Y Acad ScI 2015; 1346(1):45-56.
Cernea and Cahn. Diabetes mellitus: in search of an improved classification and treatment algorithm. Revista Română de Medicină de Laborator 2016; 24(1): DOI: 10.1515/rrlm-2016-0001.