The push for a more personalized approach to diabetes management has been reenergized by recent research that suggests solely classifying diabetes into type 1 or type 2 diabetes (T1D, T2D) is antiquated.
The Swedish, Finnish study, which looked at data from five cohort studies (ANDIS, SDR, ANDIU, DIREVA, and MDC-CVA) and was published in March in The Lancet, Diabetes & Endocrinology, has helped to identify five distinct diabetes subtypes. The subtypes included diabetics who were newly diagnosed, as well as diabetics who have had the disease for years. The study will undoubtedly aid in the efforts to personalize treatments and potentially reduce the risk of diabetes complications.
The researchers had diabetic individuals clustered according to six main variables: age at diagnosis, body mass index (BMI), glycated hemoglobin (HbA1c), pancreatic β-cell function, insulin resistance, and presence of glutamate decarboxylase antibodies (GADA). Whereas cluster 1, positive for GADA, essentially represents T1D, clusters 2 through 5 represent subtypes of T2D. Although the study is a step forward, there could be many more subtypes revealed once additional studies are completed. Preferably, future research will focus on studies with larger patient numbers, multiple ethnic populations, and an expanded set of influencing variables (such as genetic determinants and environmental factors).
The five identified clusters published in The Lancet can be seen in the table below:
Diabetes continues to be divided into either T2D or T1D. T2D is characterized by insulin resistance and pancreatic β-cell dysfunction, the latter possibly caused by a defect in insulin signaling in β-cells. This disease is commonly associated with obesity, dyslipidemia, hypertension, inflammation, and endothelial dysfunction. Unlike T2D, T1D is an autoimmune disease that permanently destroys beta cells of the pancreatic islet, which means that the body can no longer produce insulin—the hormone that is needed for the transport of glucose from blood into cells. The disease may occur at any age, but most commonly starts in childhood or adolescence.
A more tailored approach
With the recognition of the newly identified subtypes, the choice, sequence, and combination of drugs chosen by physicians could be altered significantly, bringing about a more tailored approach towards each of the unique diabetes populations. Currently for T2D, most patients are treated similarly. When and if lifestyle changes such as diet and exercise do not achieve desired glycemic goals, the routine first line of treatment is metformin.
If the HbA1c target is not achieved after approximately three months on metformin, there are a variety of second-line treatment options that will be considered for combination therapy with metformin: a sulfonylurea, thiazolidinedione, dipeptidyl peptidase-4 inhibitor, sodium-glucose co-transporter-2 inhibitor, glucagon-like peptide-1 receptor agonist, or insulin. If HbA1c targets remain unmet after dual therapy, patients will be put onto a triple therapy, and possibly a more complex combination insulin therapy.
In the study described, metformin was used taken mostly by individuals within cluster 2, while being seldom used in clusters 1 and 3. This information is important, as it would help physicians recognize which diabetic populations (cluster 2) might respond better to conventional metformin treatment as a first-line therapy, whereas other populations (clusters 1 and 3) might benefit from using a different first-line drug. Insulin was prescribed mostly to clusters 1 and 2, with very few individuals receiving insulin in clusters 3 through 5.
Insulin pharmaceutical giants Sanofi, Novo Nordisk, and Eli Lilly would clearly be interested in identifying these specific populations that benefit most from insulin therapy, especially those that might benefit from early treatment with insulin. Although an immediate overhaul of diabetes treatment guidelines is not in the foreseeable future, changes in management are bound to come once additional data become available.
Valuable insight for diabetes diagnostics
The study also provides valuable insight and direction for the future of diabetes diagnostics.
Novel diagnostic capabilities that could help optimize treatment and identify patients at high risk of developing diabetic complications would be ideal. Key opinion leaders (KOLs) interviewed by GlobalData have expressed the need for innovative diagnostics, diagnostics that would not only allow for earlier detection of T2D, but also help to identify specific T2D subpopulations that could benefit from tailored therapy.
Despite the large number of drugs available to treat diabetes patients, there is still a large unmet need to improve the management of the disease. Additional analyses, genetic studies, precise diabetes phenotyping, and large comparative treatment studies are warranted. One such study, GRADE, is funded by the National Institute of Diabetes and Digestive and Kidney Diseases, and is in the process of following patients on commonly prescribed T2D drugs for a period of up to seven years, with glycemic results expected in 2021. Thus, although current diabetes guidelines are a useful framework, revisions will need to be incorporated to better reflect current and future evidence for personalized management.
GlobalData (2017). PharmaPoint: Type 2 Diabetes – Global Drug Forecast and Market Analysis to 2026 – GDHC152PIDR