Clinical Dilemmas in Diabetes - Группа авторов

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and of non‐alcoholic fatty liver disease were highest in the first and third cluster, respectively. This latter cluster also had the highest risk of chronic kidney disease [54]. HOMA measures have significant limitations and poor predictive value for progression to diabetes [55] – although in fairness the investigators used C‐peptide rather than insulin to estimate β‐cell function. Whether this will help guide therapeutic interventions and improve outcomes in individual patients remains to be ascertained.

      Another approach to characterizing different sub‐types of diabetes is based on common genetic variation and its influence on quantitative traits such as glucose tolerance in response to a standardized challenge. For example, Dimas et al. identified 5 clusters of genetic risk loci that altered glycemic traits [56]. In this study examining data from ~58 000 non‐diabetic subjects, one cluster altered insulin sensitivity. A second cluster altered fasting glucose while a third cluster altered the ratio of proinsulin to insulin in the fasting state. Another cluster was primarily characterized by defects in post‐challenge insulin secretion. The final cluster of risk loci did not alter glycemic traits. While this exercise has certainly helped understand the effect of genotype on phenotype, the effect size of each risk allele on a given phenotypic trait is so small as be unhelpful in terms of predicting individual clinical behavior.

      Pharmacogenomics has also held promise as a way of classifying diabetes. This hope was reinforced by the discovery that the target for thiazolidinediones and sulfonylureas are risk loci for type 2 diabetes. Unfortunately, their effect on response to therapy is difficult to discern at an individual level and genotype at PPARG and KCNJ11 should not alter therapeutic choices in type 2 diabetes [57, 58].

      Multiple roads lead to the pathophysiologic defects that cause hyperglycemia. While autoimmune diabetes can be characterized quite readily in many patients, the remaining patients are far more heterogeneous. Efforts to reinvent the classification, at least to date, have not appreciably changed, or guided, the management of individual patients – the notable exception being monogenic forms of diabetes. Nevertheless, appreciating the underlying defects as well as the limitations of autoantibody and β‐cell function testing should help improve the care of patients with unclear classification and with associated comorbidities.

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