|Year : 2019 | Volume
| Issue : 2 | Page : 75-77
Types of diabetes: Two or five
Department of Endocrinology, Superspeciality Hospital Government Medical College, Nagpur, Maharashtra, India
|Date of Web Publication||17-Sep-2019|
Dr. Parimal Tayde
Department of Endocrinology, Super Specialty Hospital Government Medical College, Nagpur, Maharashtra
Source of Support: None, Conflict of Interest: None
Traditionally, diabetes is classified as type 1 and type 2 based upon the phenotypic differences. However recent research denotes that there are at least five well characterized subtypes.This classification provides novel insights in the natural history and treatment options for diabetes mellitus.
Keywords: Diabetes blood glucose types insulin-dependent diabetes mellitus, diabetes mellitus, Type 1
|How to cite this article:|
Tayde P. Types of diabetes: Two or five. J Mahatma Gandhi Inst Med Sci 2019;24:75-7
| Introduction|| |
Diabetes mellitus is a chronic disorder characterized by hyperglycemia resulting from defects in insulin secretion, insulin action, or both. It is projected that India will be the world capital of diabetes by the year 2025.
| The Heterogeneity of Diabetes|| |
Traditionally, we have learnt and taught that there are two types of diabetes: Type 1 and Type 2. Then, there is gestational diabetes which often goes in remission in the postpartum period. Type 1 diabetes is characterized by absolute insulin deficiency and often the presence of autoantibodies against pancreatic islet beta-cells. Type 2 diabetes is characterized predominantly by insulin resistance. This classification appears way too simplistic in today's times, but it is still relevant from a practical perspective of the treating physician. This is so because the patients expect a clear answer as to whether or not they need insulin and what is the natural course of their disease.
Other new types of diabetes have emerged. These include maturity-onset diabetes of the young (MODY) and latent autoimmune diabetes in adults (LADA).
MODY is a form of monogenic diabetes due to mutations in genes involved in pancreatic embryogenesis, beta-cell function, or glucose sensing.
LADA is actually a variant of Type 1 diabetes. LADA affects <10% of people with diabetes. It is defi ned by the presence of glutamic acid decarboxylase antibodies (GADA). It is s phenotypically indistinguishable from Type 2 diabetes at the time of diagnosis, but becomes increasingly similar to Type 1 diabetes
This was about the traditional classification of diabetes, but it must be noted that the classification guidelines for diabetes have not been updated for 20 years – despite emerging evidence that diabetes has got high heterogeneity.
Another limitation with the current treatment guidelines is that they respond to poor metabolic control once it is developed, but they cannot predict which patients are more prone to develop complications and hence need intensive treatment. Early and intensive treatment is so crucial for the prevention of complications due to poor glycemic control, so-called metabolic memory.
Diabetes can be considered as a group of chronic metabolic disorders that have a common feature of hyperglycemia. However, it should be noted that the elevation in blood glucose is the net result of a number of genetic and acquired factors. These factors finally lead to a reduction in the amount of insulin or reduce its effectiveness for maintaining euglycemia. Thus, hyperglycemia is a common manifestation, but there is heterogeneity in the genetic and acquired factors so clinical presentation and progression of the disease are likely to be heterogeneous.
Based on this concept of heterogeneity, there has been a new Research from Lund University Diabetes Centre in Sweden and the Institute for Molecular Medicine Finland. Prof. Groop and his team carried out their research which has led to the redefined classification of diabetes. The researchers propose that instead of classifying diabetes into two types, there are five distinct types to be considered. This classification is claimed to help us to better predict individuals most prone to develop complications and also to allow a more personalized approach to treatment.
| Methods|| |
In their study, published in Lancet Diabetes Endocrinology and Metabolism, the researchers analyzed the data of five study cohorts – All New Diabetics in Scania (ANDIS), the Scania Diabetes Registry, All New Diabetics in Uppsala, Diabetes Registry Vaasa, and Malmö Diet and Cancer CardioVascular Arm. These included a total of 14,775 subjects from Sweden and Finland [Table 1]. All of them were newly diagnosed with diabetes.
The researchers collected information on the following parameters – age at diagnosis, body mass index, glutamate decarboxylase antibodies (GADA), hemoglobin A1c levels, and homeostatic model assessment 2 (HOMA2) – to estimate beta-cell function and HOMA2 insulin resistance using C-peptide concentrations. In addition, genotyping of ANDIS participants was done, and the participants of non-Swedish origin were excluded. The researchers also compared their disease progression, complications, and treatment.
| Results of the Study|| |
The study revealed five distinct forms of diabetes, three of which were severe and two were mild. They were categorized as follows:
- Cluster 1: (SAID) This is called severe autoimmune diabetes (what we currently known as Type 1 diabetes). It is characterized by insulin deficiency and the presence of autoantibodies. People in this cluster were relatively young at the time of diagnosis, and they were not overweight. This group included 6%–15% of subjects
- Cluster 2: (SIDD) This is called severe insulin-deficient diabetes. It is characterized by younger age, insulin deficiency, and poor metabolic control but without autoantibodies. This was identified in 9%–20% of subjects. Why is it so? Why don't they have antibodies if the phenotype is similar to classic Type 1? There is no clear answer, but it is proposed that these individuals may have a defect in the insulin synthesis and secretion which could be nonautoimmune in nature
- Cluster 3: (SIRD) This is severe insulin-resistant diabetes. It is characterized by severe insulin resistance and significantly higher risk of kidney disease. This cluster also has the highest prevalence of nonalcoholic fatty liver disease (NAFLD). This was identified in 11%–17% of subjects
- Cluster 4: (MOD) This is mild obesity-related diabetes. It is most common in obese individuals. This affected 18%–23% of subjects
- Cluster 5: (MARD) This is mild age-related diabetes. It is most common in elderly individuals. This was the most common form, affecting 39%–47% of people in the study.
| Implications in Clinical Practice: Step Toward Precision Medicine|| |
It must be stressed that this new classification system is not suggesting getting rid of Type 1 and Type 2 diagnoses. Rather, it is suggesting that there are subtypes and this is a new way of classifying within the diagnosis.
Cluster 1 is similar to Type 1 diabetes, while the other four clusters were “subtypes” of Type 2. It is interesting to note that each of these five types was also genetically distinct, and there were no genetic mutations that were shared across all the five clusters.
Currently, Type 2 diabetes is an umbrella term, but actually it includes the last four clusters in the above classification.
People in Cluster 3 (SIRD) had the highest risk of nephropathy. This highlights the association between insulin resistance and kidney disease. Insulin resistance has been associated with increased salt sensitivity, glomerular hypertension, hyperfiltration, and reduced renal function, all hallmarks of diabetic kidney disease. Hepatic insulin resistance IS A a feature of NAFLD. A single nucleotide polymorphism in the TM6SF2 gene was associated with SIRD in this study.
People in Cluster 2 had the highest risk of diabetic retinopathy.
Both Clusters 2 and 3 are severe forms of diabetes which were earlier masked within Type 2 diabetes. Patients in these clusters may benefit from aggressive treatment to prevent diabetes complications.
Further analysis revealed that some of the patients in each of the five clusters were inappropriately being treated. As an example, just 42% of patients in Cluster 1 and 29% of patients in Cluster 2 received insulin therapy at the time of diagnosis.
As discussed above, existing treatment guidelines suggest a response to poor metabolic control once it has developed but cannot predict which patients need intensified treatment. This study can be considered as a first step toward tailored treatments for diabetes.
| Limitations of the Classification|| |
Further research is needed to refine these five clusters using biomarker genotypes and genetic risk scores. The clusters are totally based on population from two Nordic countries, and there might be considerable differences in other populations. It cannot be ascertained that newer clusters denote different etiologies of diabetes.
Only two types of antibodies were studied, so the effect of other antibodies on clusters is unknown.
There were no data on some known risk factors for diabetic complications, such as blood pressure and lipid profile.
There are two categories of “mild” diabetes. However, this might lead to assumption by the patient that it is not a serious condition and does not need an aggressive approach.
Another important limitation of this classification system is that it does not guide which therapy is to be preferred in a given subgroup. Considering the large number of available drugs to choose from, the therapeutic decision always remains challenging.
A web-based tool which will assign patients to different clusters after entering the necessary data is under development.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Tuomi T, Groop LC, Zimmet PZ, Rowley MJ, Knowles W, Mackay IR. Antibodies to glutamic acid decarboxylase reveal latent autoimmune diabetes mellitus in adults with a non-insulin-dependent onset of disease. Diabetes 1993;42:359-62.
Brownlee M. The pathobiology of diabetic complications: A unifying mechanism. Diabetes 2005;54:1615-25.
Ahlqvist E, Storm P, Käräjämäki A, Martinell M, Dorkhan M, Carlsson A, et al.
Novel subgroups of adult-onset diabetes and their association with outcomes: A data-driven cluster analysis of six variables. Lancet Diabetes Endocrinol 2018;6:361-9.
Gnudi L, Coward RJ, Long DA. Diabetic nephropathy: Perspective on novel molecular mechanisms. Trends Endocrinol Metab 2016;27:820-30.