At present, diabetes diagnoses are generally classified as type 1 diabetes (or juvenile diabetes, in which the beta cells in a patient's pancreas produce little or no insulin) or type 2 diabetes (adult onset diabetes, characterized by insulin resistance, in which insulin is not processed properly), with some rare subtypes such as gestational diabetes and latent autoimmune diabetes of adults (LADA), a form of type 1 diabetes mellitus that presents in adulthood. Diagnosis generally focuses on blood glucose levels, such as the A1C test. But the results from the ANDIS study, presented by researchers from the Lund University Diabetes Center (LUDC) and the Institute for Molecular Medicine Finland (FIMM), suggest that there might be as many as five separate disease classifications for diabetes, most of them subgroups of type 2 diabetes. Researchers also hailed from the University of Helsinki (Institute for Molecular Medicine Finland FIMM, HiLIFE), Vaasa Central Hospital, Helsinki University Central Hospital and Folkhälsan Research Center. Their work was published in The Lancet Diabetes & Endocrinology in a paper titled "Novel subgroups of adult-onset diabetes and their association with outcomes: a data-driven cluster analysis of six variables."
The ANDIS (All New Diabetics In Skåne) study involves all newly diagnosed diabetic patients in Southern Sweden, plus two additional Swedish cohorts and the Diabetes Registry Vassa (DIREVA) study from Finland, for a total of approximately 15,000 study participants. In the study, 13,720 newly diagnosed diabetics between the ages of 18 and 97 were monitored since 2008.
According to a FIMM press release penned by Mari Kaunisto, at present, approximately 85 to 90 percent of all diabetes cases are diagnosed as type 2. The team for this study were able to identify five different subtypes that diverge from today's diagnoses, based on six measurements: age at diagnosis, body mass index, long-term glycemic control, insulin resistance, insulin secretion and the presence of auto-antibodies associated with autoimmune diseases.
As the authors noted in the paper, "We did data-driven cluster analysis (k-means and hierarchical clustering) in patients with newly diagnosed diabetes (n=8980) from the Swedish All New Diabetics in Scania cohort. Clusters were based on six variables ... and were related to prospective data from patient records on development of complications and prescription of medication. Replication was done in three independent cohorts: the Scania Diabetes Registry (n=1466), All New Diabetics in Uppsala (n=844), and Diabetes Registry Vaasa (n=3485). Cox regression and logistic regression were used to compare time to medication, time to reaching the treatment goal, and risk of diabetic complications and genetic associations."
“Today, diagnoses are performed by measuring blood sugar. A more accurate diagnosis can be made by also considering the factors accounted for in our study. This is the first step towards personalised treatment of diabetes,” said Prof. Leif Groop of LUDC and the University of Helsinki, lead author of the study.
“Current diagnostics and classification of diabetes are insufficient and unable to predict future complications or choice of treatment,” he added, highlighting this work as “the first step towards personalized treatment of diabetes.”
The five classifications the researchers posit are as follows:
Group 1, SAID (severe autoimmune diabetes): essentially corresponds to type 1 diabetes and LADA (latent autoimmune diabetes in adults). This group is characterized by onset at young age, poor metabolic control, impaired insulin production and the presence of GADA (glutamic acid decarboxylase autoantibodies) antibodies. (GADA autoantibodies are presently the most common predictive marker for diagnosing type 1 diabetes.)
Group 2, SIDD (severe insulin-deficient diabetes): individuals with high HbA1C, impaired insulin secretion and moderate insulin resistance. Group 2 had the highest incidence of retinopathy.
Group 3, SIRD (severe insulin-resistant diabetes): this group is characterized by obesity and severe insulin resistance. Group 3 had the highest incidence of kidney damage.
Group 4, MOD (mild obesity-related diabetes): includes obese patients who fall ill at a relatively young age.
Group 5, MARD (mild age-related diabetes): is the largest group (about 40 percent) and consists of the most elderly patients.
Beyond the different disease characteristics such as insulin resistance and production, the researchers reported that all five subtypes of diabetes were genetically distinct. When they repeated their analysis in three studies from Sweden and Finland, results corresponded closely, with the only significant difference being that there were more patients with mile age-related diabetes in Finland.
“The patients with severe insulin-resistant or severe insulin-deficient diabetes have the most to gain from the new diagnostics as they are the ones who are currently most incorrectly treated,” commented department head Tiinamaija Tuomi from the Helsinki University Central Hospital. “This will enable earlier treatment to prevent complications in patients who are most at risk of being affected.”
Following the results from this study, the team also intends to conduct similar studies in China and India to look for differences and similarities in individuals of different ethnicities.
“This will give us even better opportunities to tailor the treatment to each individual,” said Emma Ahlqvist, associate professor and lead author of the publication.
At present, some 425 million people worldwide are diabetic. According to the World Health Organization (WHO), the prevalence of diabetes among adults rose from 4.7 percent in 1980 to 8.5 percent in 2014, and an estimated 1.6 million deaths were attributed to diabetes in 2015. WHO predicts that diabetes will become the seventh leading cause of death by 2030, and the International Diabetes Federation forecasts that some 629 million people will have diabetes by 2045. One in two (212 million) diabetics were undiagnosed in 2017, according to the International Diabetes Federation, and diabetes-related healthcare costs totaled at least $727 billion last year, accounting for 12 percent of all healthcare spending on adults.
Funding for this research came from several sources, including the Swedish Research Council, European Research Council, Vinnova, Academy of Finland, Novo Nordisk Foundation, Scania University Hospital, Sigrid Juselius Foundation, Innovative Medicines Initiative 2 Joint Undertaking, Vasa Hospital district, Jakobstadsnejden Heart Foundation, Folkhälsan Research Foundation, Ollqvist Foundation and Swedish Foundation for Strategic Research.