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Gearing towards personalization of diabetes treatment

Dr. Joseph Delano Fule Robles
11 Jun 2018
Professor Ronald Ma

Diabetes mellitus (DM) is increasingly diagnosed in younger individuals. This poses challenges such as long exposure to diabetes and its complications and the need for tailor-made treatment protocols that fit a specific group of diabetic patients.

“The shift is from the concept of ‘the lower [the glucose levels] the better’ to knowledge from trials done in the past few years showing that intensive blood glucose lowering may be harmful in a subgroup of patients. The challenge now is to know how to match the right treatment to the right patients,” said Professor Ronald Ma of the Chinese University of Hong Kong (CUHK).

A recent data-driven cluster analysis in patients newly diagnosed with diabetes (n=8,980) in Sweden showed that some clusters of patients are more prone to diabetic complications than other clusters. [Lancet Diabetes Endocrinol 2018;6:361-369]

In the study, patients were clustered based on the presence of anti-glutamic acid decarboxylase [GAD] antibodies, age at diagnosis, body mass index, HbA1c, beta-cell function and insulin resistance indices.

Based on the study, patients with severe insulin-resistant DM had significantly higher risk for diabetic kidney disease, while those with severe insulin-deficient DM had higher risk for retinopathy.

“Similar to other developed countries, upon diagnosis of DM, good glucose control will be achieved with initial treatment but later on, the trend follows a gradual decline in glycaemic control despite best efforts, reflecting progressive decline in beta-cell function,” explained Ma. [Diabetes Care 2017;40:928-935] “This issue highlights high rates of disease progression and complications despite treatment, and the need to identify if there are specific subgroups who are particularly at risk.”

“Instead of grouping patients into type 1 [T1DM] or type 2 DM [T2DM], there is a lot more heterogeneity that we need to recognize. There are some subphenotypes and different genetic forms, and we should not treat all patients similarly,” Ma added.

A prospective case cohort with 2,755 patients showed that specific genetic variables (ie, single nucleotide polymorphism [SNP] variants rs478333 and rs7754840) were predictors for kidney disease in T2DM. [Kidney Int 2016;89:411-420]

According to the UKPDS 25 study, an underlying autoimmune process predicts a patient’s need for insulin treatment. For instance, insulin treatment is more commonly needed by patients with anti-GAD or anti-islet cell antibody (ICA) compared with patients without antibodies (anti-GAD, 84 percent; anti-ICA, 94 percent; no antibodies, 14 percent; p<0.0001). [Lancet 1997;3501288-1293]

“These data present us with a better view on how we could treat patients better. Tools such as molecular and genetic testing can help us see the real face of DM that may otherwise be hidden,” commented Ma. [J Diabetes Investig 2018, doi: 10.1111/jdi.12830]

The prevalence of diabetes in China is 10.9 percent, with more than one-third of the population having prediabetes. Twenty percent of patients are diagnosed with T2DM before 40 years of age. [JAMA 2017;317:2515-2523; Lancet Diabetes Endocrinol 2014;2:935-943]

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