Pharmacogenetics and target identification in diabetes

Evaluation of the effect of MTNR1B rs10830963 gene variant on the therapeutic efficacy of nateglinide in treating type 2 diabetes among Chinese Han patients

Genetic polymorphisms in the MTNR1B gene is associated with type 2 diabetes mellitus (T2DM); however, there is no evidence about its impact on the therapeutic efficacy of nateglinide. This prospective case-control study was designed to investigate the effect of MTNR1B rs10830963 gene variant on the therapeutic efficacy of nateglinide in treating T2DM. We genotyped untreated T2DM patients (N = 200) and healthy controls (N = 200) using the method of the high resolution of melting curve (HRM). Newly diagnosed T2DM patients (n = 60) with CYP2C9*1 and SLCO1B1 521TT genotypes were enrolled and given oral nateglinide (360 mg/d) for 8 weeks. The outcome was measured by collecting the venous blood samples before and at the 8th week of the treatment. The risk G allelic frequency of MTNR1B rs10830963 was higher in T2DM patients than the healthy subjects (P < 0.05). Post 8-week of treatment, newly diagnosed T2DM patients showed a less reduction in fasting plasma glucose levels and less increase in the carriers of genotype CG + GG at rs10830963 when compared with the CC genotype (P < 0.05). MTNR1B rs10830963 polymorphism was associated with the therapeutic efficacy of nateglinide in T2DM patients. Also, the CC homozygotes had a better effect than G allele carriers.Trial registration Chinese Clinical Trial Register ChiCTR13003536, date of registration: May 14, 2013.

The Need for Precision Medicine to be Applied to Diabetes

Precision medicine refers to the tailoring of medical treatment for an individual based on large amounts of biologic and extrinsic data. The fast advancing fields of molecular biology, gene sequencing, machine learning, and other technologies enable precision medicine to utilize this detailed information to enhance clinical management decision-making for an individual in the real time of the disease course. Traditional clinical decision making is based on reacting to a relatively limited number of phenotypes that are determined by history, physical examination, and conventional lab tests. Precision medicine depends on highly detailed profiling of the patient's genetic, morphologic, and metabolic makeup. The precision medicine approach can be applied to individuals with diabetes to select treatments most likely to offer benefit and least likely to cause side effects, offering prospects of improved clinical outcomes and economic costs savings over current empiric practices. As genetic, metabolomic, immunologic, and other sophisticated testing becomes less expensive and more widespread in the medical record, it is expected that precision medicine will become increasingly applied to diabetes care.

Effects of TCF7L2 rs7903146 variant on metformin response in patients with type 2 diabetes

The response to metformin, the most commonly used drug for the treatment of type 2 diabetes (T2D), is highly variable. The common variant rs7903146 C>T within the transcription factor 7-like 2 gene (TCF7L2) is the strongest genetic risk factor associated with T2D to date. In this study, we explored the effects of the TCF7L2 rs7903146 genotype on metformin response in T2D. The study included 86 newly diagnosed patients with T2D, incident users of metformin. Levels of fasting glucose, insulin, HbA1c, total cholesterol, HDL-cholesterol, LDL-cholesterol, triglycerides, and anthropometric parameters were measured prior to metformin therapy, and 6 and 12 months after the treatment. Genotyping of the TCF7L2 rs7903146 was performed by the Sequenom MassARRAY® iPLEX® platform. At baseline, the diabetes risk allele (T) showed an association with lower triglyceride levels (p = 0.037). After 12 months of metformin treatment, the T allele was associated with 25.9% lower fasting insulin levels (95% CI 10.9-38.3%, p = 0.002) and 29.1% lower HOMA-IR index (95% CI 10.1-44.1%, p = 0.005), after adjustment for baseline values. Moreover, the T allele was associated with 6.7% lower fasting glucose levels (95% CI 1.1-12.0%, p = 0.021), adjusted for baseline glucose and baseline HOMA-%B levels, after 6 months of metformin treatment. This effect was more pronounced in the TT carriers who had 16.8% lower fasting glucose levels (95% CI 7.0-25.6%, p = 0.002) compared to the patients with CC genotype. Our results suggest that the TCF7L2 rs7903146 variant affects markers of insulin resistance and glycemic response to metformin in newly diagnosed patients with T2D within the first year of metformin treatment.

The application of post-translational modification oriented serum proteomics to assess experimental diabetes with complications

Proteome analysis of serum from type 2 diabetics with complications may lead to the discovery of diagnostic or prognostic biomarkers. To circumvent the principal barrier of serum proteomics, our investigation aimed to evaluate whether a study of post-translational modification enriched serum proteins could be valuable for the discovery of biomarkers or metabolic pathways related to type 2 diabetes pathogenesis. Type 2 diabetes was induced from high-fat diet fed Sprague Dawley rats with streptozotocin injection. Once diabetic status was confirmed, serum samples from either fasted healthy or diabetic rats were pooled and profiled by two-dimensional difference gel electrophoresis or comparative 2D electrophoresis after protein enrichments using immobilized metal ion, concanavalin A, and lentil affinity chromatography, respectively. Differential expressed proteins were identified and the associated networks were established by an Ingenuity Pathway Analysis. As a result, induced rats became severe diabetic and accompanied by hyperlipidemia, fatty liver, and glomerular hypertrophy. There were 3 total, 14 phosphorylated and 23 glycosylated protein targets differentially expressed. Proteins could be linked to HNF4A, HNF1A, and NFκB transcriptional factors and antigen presentation, humoral immune response, and inflammatory response pathways. Predicted organ toxicity in kidney, heart, and liver matched with our histopathological results. In conclusion, post-translational modification based serum protein enrichment could be a valuable approach to enhance the resolution of serum proteomics without depleting potentially valuable abundant proteins. Our results also indicated the potential association of the hepatic secretome and hepatocyte nuclear factors in the pathogenesis of type 2 diabetes and its complications.

A Global Overview of Precision Medicine in Type 2 Diabetes

The detailed characterization of human biology and behaviors is now possible at scale owing to innovations in biomarkers, bioimaging, and wearable technologies; "big data" from electronic medical records, health insurance databases, and other platforms becoming increasingly accessible; and rapidly evolving computational power and bioinformatics methods. Collectively, these advances are creating unprecedented opportunities to better understand diabetes and many other complex traits. Identifying hidden structures within these complex data sets and linking these structures to outcome data may yield unique insights into the risk factors and natural history of diabetes, which in turn may help optimize the prevention and management of the disease. This emerging area is broadly termed "precision medicine." In this Perspective, we give an overview of the evidence and barriers to the development and implementation of precision medicine in type 2 diabetes. We also discuss recently presented paradigms through which complex data might enhance our understanding of diabetes and ultimately our ability to tackle the disease more effectively than ever before.