Clinical translation of genetic predictors for type 2 diabetes

Dementia risk reduction: why haven't the pharmacological risk reduction trials worked? An in-depth exploration of seven established risk factors

Identifying the leading health and lifestyle factors for the risk of incident dementia and Alzheimer's disease has yet to translate to risk reduction. To understand why, we examined the discrepancies between observational and clinical trial evidence for seven modifiable risk factors: type 2 diabetes, dyslipidemia, hypertension, estrogens, inflammation, omega-3 fatty acids, and hyperhomocysteinemia. Sample heterogeneity and paucity of intervention details (dose, timing, formulation) were common themes. Epidemiological evidence is more mature for some interventions (eg, non-steroidal anti-inflammatory drugs [NSAIDs]) than others. Trial data are promising for anti-hypertensives and B vitamin supplementation. Taken together, these risk factors highlight a future need for more targeted sample selection in clinical trials, a better understanding of interventions, and deeper analysis of existing data.

Building Molecular Interaction Networks from Microarray Data for Drug Target Screening

Potential drug targets for the disease treatment can be identified from microarray studies on differential gene expression of patients and healthy participants. Here, we describe a method to use the information of differentially expressed (DE) genes obtained from microarray studies to build molecular interaction networks for identification of pivotal molecules as potential drug targets. The quality control and normalization of the microarray data are conducted with R packages simpleaffy and affy, respectively. The DE genes with adjusted P values less than 0.05 and log fold changes larger than 1 or less than -1 are identified by limma package to construct a molecular interaction network with InnateDB. The genes with significant connectivity are identified by the Cytoscape app jActiveModules. The interactions among the genes within a module are tested by psych package to determine their associations. The gene pairs with significant association and known protein structures according to the Protein Data Bank are selected as potential drug targets. As an example for drug target screening, we demonstrate how to identify potential drug targets from a molecular interaction network constructed with the DE genes of significant connectivity, using a microarray dataset of type 2 diabetes mellitus.

Approaches to the prevention of type 2 diabetes in Gibraltar

The incidence of type 2 diabetes mellitus is rising worldwide, with the number of people with the condition expected to reach 552 million by 2030. This is largely due to changing demographics, ageing populations and a worldwide increase in obesity rates. This article explores diabetes in Gibraltar. The main focus is the incidence of type 2 diabetes, in the context of the characteristics of the adult population and how these relate to risk factors, such as obesity, smoking and genetics. Thereis a brief exploration of the history of Gibraltar and how its particular circumstances may account for an increased incidence of diabetes. Finally, the evolution of the local diabetes service and future developments are discussed, along with innovative approaches to diabetes prevention, which may be adapted for use in other communities.

Islet biology, the CDKN2A/B locus and type 2 diabetes risk

Type 2 diabetes, fuelled by the obesity epidemic, is an escalating worldwide cause of personal hardship and public cost. Diabetes incidence increases with age, and many studies link the classic senescence and ageing protein p16(INK4A) to diabetes pathophysiology via pancreatic islet biology. Genome-wide association studies (GWASs) have unequivocally linked the CDKN2A/B locus, which encodes p16 inhibitor of cyclin-dependent kinase (p16(INK4A)) and three other gene products, p14 alternate reading frame (p14(ARF)), p15(INK4B) and antisense non-coding RNA in the INK4 locus (ANRIL), with human diabetes risk. However, the mechanism by which the CDKN2A/B locus influences diabetes risk remains uncertain. Here, we weigh the evidence that CDKN2A/B polymorphisms impact metabolic health via islet biology vs effects in other tissues. Structured in a bedside-to-bench-to-bedside approach, we begin with a summary of the evidence that the CDKN2A/B locus impacts diabetes risk and a brief review of the basic biology of CDKN2A/B gene products. The main emphasis of this work is an in-depth look at the nuanced roles that CDKN2A/B gene products and related proteins play in the regulation of beta cell mass, proliferation and insulin secretory function, as well as roles in other metabolic tissues. We finish with a synthesis of basic biology and clinical observations, incorporating human physiology data. We conclude that it is likely that the CDKN2A/B locus influences diabetes risk through both islet and non-islet mechanisms.

Differential methylation of TCF7L2 promoter in peripheral blood DNA in newly diagnosed, drug-naïve patients with type 2 diabetes

TCF7L2 is the susceptibility gene for Type 2 diabetes (T2D) with the largest effect on disease risk that has been discovered to date. However, the mechanisms by which TCF7L2 contributes to the disease remain largely elusive. In addition, epigenetic mechanisms, such as changes in DNA methylation patterns, might have a role in the pathophysiology of T2D. This study aimed to investigate the differences in terms of DNA methylation profile of TCF7L2 promoter gene between type 2 diabetic patients and age- and Body Mass Index (BMI)- matched controls. We included 93 type 2 diabetic patients that were recently diagnosed for T2D and exclusively on diet (without any pharmacological treatment). DNA was extracted from whole blood and DNA methylation was assessed using the Sequenom EpiTYPER system. Type 2 diabetic patients were more insulin resistant than their matched controls (mean HOMA IR 2.6 vs 1.8 in controls, P<0.001) and had a poorer beta-cell function (mean HOMA B 75.7 vs. 113.6 in controls, P<0.001). Results showed that 59% of the CpGs analyzed in TCF7L2 promoter had significant differences between type 2 diabetic patients and matched controls. In addition, fasting glucose, HOMA-B, HOMA-IR, total cholesterol and LDL-cholesterol correlated with methylation in specific CpG sites of TCF7L2 promoter. After adjustment by age, BMI, gender, physical inactivity, waist circumference, smoking status and diabetes status uniquely fasting glucose, total cholesterol and LDL-cholesterol remained significant. Taken together, newly diagnosed, drug-naïve type 2 diabetic patients display specific epigenetic changes at the TCF7L2 promoter as compared to age- and BMI-matched controls. Methylation in TCF7L2 promoter is further correlated with fasting glucose in peripheral blood DNA, which sheds new light on the role of epigenetic regulation of TCF7L2 in T2D.

TCF7L2 gene polymorphisms and type 2 diabetes risk: a comprehensive and updated meta-analysis involving 121,174 subjects

Recently, many new loci associated with type 2 diabetes have been uncovered by genetic association studies and genome-wide association studies. As more reports are made, particularly with respect to varying ethnicities, there is a need to determine more precisely the effect sizes in each major racial group. In addition, some reports have claimed ethnic-specific associations with alternative single-nucleotide polymorphisms (SNPs), and to that end there has been a degree of confusion. We conducted a meta-analysis using an additive genetic model. Eight polymorphisms in 155 studies with 121174 subjects (53385 cases and 67789 controls) were addressed in this meta-analysis. Significant associations were found between type 2 diabetes and rs7903146, rs12255372, rs11196205, rs7901695, rs7895340 and rs4506565, with summary odds ratios (ORs) (95% confidence interval) of 1.39 (1.34-1.45), 1.33 (1.27-1.40), 1.20 (1.14-1.26), 1.32 (1.25-1.39), 1.21 (1.13-1.29) and 1.39 (1.29-1.49), respectively. In addition, no significant associations were found between the two polymorphisms (rs290487 and rs11196218) and type 2 diabetes. The summary ORs for the six statistically significant associations (P < 0.05) were further evaluated by estimating the false-positive report probability, with results indicating that all of the six significant associations were considered noteworthy, and may plausibly be true associations. Significant associations were found between the six polymorphisms (rs7903146, rs12255372, rs11196205, rs7901695, rs7895340 and rs4506565) in the TCF7L2 gene and type 2 diabetes risk, and the other two polymorphisms (rs11196218 and rs290487) were not found to be significantly associated with type 2 diabetes. Subgroups analyses show that significant associations are not found between the six SNPs (rs7903146, rs12255372, rs11196205, rs7901695, rs7895340, and rs4506565) and the type 2 diabetes in some ethnic populations.

Effect of communicating genetic and phenotypic risk for type 2 diabetes in combination with lifestyle advice on objectively measured physical activity: protocol of a randomised controlled trial

BACKGROUND

Type 2 diabetes (T2D) is associated with increased risk of morbidity and premature mortality. Among those at high risk, incidence can be halved through healthy changes in behaviour. Information about genetic and phenotypic risk of T2D is now widely available. Whether such information motivates behaviour change is unknown. We aim to assess the effects of communicating genetic and phenotypic risk of T2D on risk-reducing health behaviours, anxiety, and other cognitive and emotional theory-based antecedents of behaviour change.

METHODS

In a parallel group, open randomised controlled trial, approximately 580 adults born between 1950 and 1975 will be recruited from the on-going population-based, observational Fenland Study (Cambridgeshire, UK). Eligible participants will have undergone clinical, anthropometric, and psychosocial measurements, been genotyped for 23 single-nucleotide polymorphisms associated with T2D, and worn a combined heart rate monitor and accelerometer (Actiheart(®)) continuously for six days and nights to assess physical activity. Participants are randomised to receive either standard lifestyle advice alone (control group), or in combination with a genetic or a phenotypic risk estimate for T2D (intervention groups). The primary outcome is objectively measured physical activity. Secondary outcomes include self-reported diet, self-reported weight, intention to be physically active and to engage in a healthy diet, anxiety, diabetes-related worry, self-rated health, and other cognitive and emotional outcomes. Follow-up occurs eight weeks post-intervention. Values at follow-up, adjusted for baseline, will be compared between randomised groups.

DISCUSSION

This study will provide much needed evidence on the effects of providing information about the genetic and phenotypic risk of T2D. Importantly, it will be among the first to examine the impact of genetic risk information using a randomised controlled trial design, a population-based sample, and an objectively measured behavioural outcome. Results of this trial, along with recent evidence syntheses of similar studies, should inform policy concerning the availability and use of genetic risk information.

Parental longevity and diabetes risk in the Diabetes Prevention Program

BACKGROUND

Longevity clusters in families, and parental longevity may be associated with lower risk of chronic diseases in their children. It is unknown if diabetes risk is associated with parental longevity.

METHODS

We evaluated participants in the Diabetes Prevention Program with a parental history questionnaire at study entry. We classified them into five groups: premature death (parental death at age < 50 years), parental longevity (living to at least 80 years), and three intermediate groups (alive by age 49 but dying at age 50-59, 60-69, or 70-79). Those with alive parents and younger than 80 years were excluded. We analyzed separately effects of paternal (n = 2,165) and maternal (n = 1,739) longevity on diabetes incidence and risk after an average follow-up of 3.2 years.

RESULTS

At baseline, more diabetes risk factors (parental history of diabetes, coronary heart disease, higher body mass index, homeostasis model assessment for insulin resistance, and corrected insulin response) were found in participants whose parents died prematurely. Diabetes incidence was 9.5 cases/100 person-years in the 229 whose fathers died prematurely. In the 618 with paternal longevity, the rate was 6.6 cases/100 person-years (hazard ratio [95% confidence interval] = 0.68 [0.49-0.94]). The rates were 10.7 cases/100 person-years (n = 156) and 7.3 cases/100 person-years (n = 699, hazard ratio = 0.67 [95% confidence interval 0.47-0.95]) for those with maternal premature death or longevity, respectively. Associations with demographic and diabetes risk factors had minimal influence on the reduced risk found in those with paternal (adjusted hazard ratio = 0.78, 95% confidence interval 0.52-1.16) and maternal (adjusted hazard ratio = 0.64, 95% confidence interval 0.41-1.01) longevity.

CONCLUSION

Parental longevity is associated with lower diabetes incidence in adults at high risk of type 2 diabetes.

Current views on type 2 diabetes

Type 2 diabetes mellitus (T2DM) affects a large population worldwide. T2DM is a complex heterogeneous group of metabolic disorders including hyperglycemia and impaired insulin action and/or insulin secretion. T2DM causes dysfunctions in multiple organs or tissues. Current theories of T2DM include a defect in insulin-mediated glucose uptake in muscle, a dysfunction of the pancreatic beta-cells, a disruption of secretory function of adipocytes, and an impaired insulin action in liver. The etiology of human T2DM is multifactorial, with genetic background and physical inactivity as two critical components. The pathogenesis of T2DM is not fully understood. Animal models of T2DM have been proved to be useful to study the pathogenesis of, and to find a new therapy for, the disease. Although different animal models share similar characteristics, each mimics a specific aspect of genetic, endocrine, metabolic, and morphologic changes that occur in human T2DM. The purpose of this review is to provide the recent progress and current theories in T2DM and to summarize animal models for studying the pathogenesis of the disease.