COMMENTARY

Type 2 Diabetes in Lean Individuals: A Different Disease?

Ali A. Torkamani, PhD

Disclosures

August 02, 2012

Stratifying Type 2 Diabetes Cases by BMI Identifies Genetic Risk Variants in LAMA1 and Enrichment for Risk Variants in Lean Compared to Obese Cases

Perry JR, Voight BF, Yengo L, et al
PLoS Genet. 2012;8:e1002741

Summary

Genome-wide association studies (GWAS) have identified approximately 50 genetic loci associated with type 2 diabetes in lean and obese individuals.[1,2,3] However, many of these genetic factors are only indirectly related to type 2 diabetes risk through their influence on obesity and feeding behaviors.[4,5,6]

Reasoning that a population of lean individuals with type 2 diabetes would be enriched for genetic factors that directly influence the development of the disease independent of obesity and lifestyle behaviors, a multinational group of investigators performed 2 separate GWAS: the first used data from multiple datasets and involved 2112 lean type 2 diabetes cases, 4123 obese cases, and 54,412 population controls; and the second replication cohort included an additional 2881 lean cases, 8702 obese cases, and 18,957 controls. Data from these studies showed a new association in the lean cases between a genetic variant and type 2 diabetes and found that 29 of 36 other known type 2 diabetes risk loci were more strongly associated with lean cases than with obese cases.

Viewpoint

Environmental influences, particularly dietary habits, are known to play a major role in the development of this disease. However, body mass index can vary widely in patients with type 2 diabetes, indicating that factors unrelated to obesity and diet are likely implicated in development of the disease.

As expected, this study confirmed that genetic factors that contribute directly to disease risk independent of environmental factors are more strongly associated with diabetes in lean patients than in obese patients.

This difference in direct genetic susceptibility vs environmental interactions may inform the underlying mechanism driving disease in any specific individual and may inform strategies for intervention. For example, one might expect that in individuals in whom obesity and feeding behavior are the primary driving forces behind the development of diabetes, alteration of eating habits may have a stronger influence on disease course as compared with a similar intervention in lean cases of type 2 diabetes. Similarly, in lean cases of diabetes, accurate dissection of the genetic underpinnings of disease may inform specific pharmaceutical interventions that correct the physiologic imbalance driving disease.

Although it remains to be seen whether diabetes cases can be accurately stratified into different disease subtypes based on genetic and clinical characteristics, results of this study suggest that such stratification may be possible in the future.

Abstract

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