Insulin resistance (IR), an impaired cellular, tissue and whole body response to insulin, is a major pathophysiological defect of type 2 diabetes mellitus. Although IR is closely associated with obesity, the identity of the molecular defect(s) underlying obesity-induced IR in skeletal muscle remains controversial; reduced post-receptor signalling of the insulin receptor substrate 1 (IRS1) adaptor protein and downstream effectors such as protein kinase B (PKB) have previously been implicated. We examined expression and/or activation of a number of components of the insulin-signalling cascade in skeletal muscle of 22 healthy young men (with body mass index (BMI) range, 20–37 kg/m2). Whole body insulin sensitivity (M value) and body composition was determined by the hyperinsulinaemic (40 mU. min−1.m−2.), euglycaemic clamp and by dual energy X-ray absorptiometry (DEXA) respectively. Skeletal muscle (vastus lateralis) biopsies were taken before and after one hour of hyperinsulinaemia and the muscle insulin signalling proteins examined by western blot and immunoprecipitation assay. There was a strong inverse relationship between M-value and BMI. The most striking abnormality was significantly reduced insulin-induced activation of p42/44 MAP kinase, measured by specific assay, in the volunteers with poor insulin sensitivity. However, there was no relationship between individuals' BMI or M-value and protein expression/phosphorylation of IRS1, PKB, or p42/44 MAP kinase protein, under basal or hyperinsulinaemic conditions. In the few individuals with poor insulin sensitivity but preserved p42/44 MAP kinase activation, other signalling defects were evident. These findings implicate defective p42/44 MAP kinase signalling as a potential contributor to obesity-related IR in a non-diabetic population, although clearly multiple signalling defects underlie obesity associated IR.

Hyperpolarization-activated cyclic nucleotide-gated (HCN) channels are encoded by four genes (HCN1–4) and, through activation by cyclic AMP (cAMP), represent a point of convergence for several psychosis risk genes. On the basis of positive preliminary data, we sought to test whether genetic variation in HCN1–4 conferred risk of depression or cognitive impairment in the Generation Scotland: Scottish Family Health Study. HCN1, HCN2, HCN3, and HCN4 were genotyped for 43 haplotype-tagging SNPs and tested for association with DSM-IV depression, neuroticism, and a battery of cognitive tests assessing cognitive ability, memory, verbal fluency, and psychomotor performance. No association was found between any HCN channel gene SNP and risk of depression, neuroticism, or on any cognitive measure. The current study does not support a genetic role for HCN channels in conferring risk of depression or cognitive impairment in individuals from the Scottish population.

OBJECTIVE

The study objective was to describe the effect of socioeconomic status (SES) on mortality among people with type 2 diabetes.

RESEARCH DESIGN AND METHODS

We used a population-based national electronic diabetes database for 35- to 84-year-olds in Scotland for 2001–2007 linked to mortality records. SES was derived from an area-based measure with Q5 and Q1 representing the most deprived and affluent quintiles, respectively. Poisson regression was used to estimate relative risks (RRs) for mortality among people with type 2 diabetes compared with the population without diabetes stratified by age (35–64 and 65–84 years), sex, duration of diabetes (<2 and ≥2 years), and SES.

RESULTS

Complete data were available for 210,994 eligible individuals (99.4%), and there were 33,842 deaths. Absolute mortality from all causes among people with type 2 diabetes increased with increasing age and socioeconomic deprivation and was higher for men than women. RR for mortality associated with type 2 diabetes was highest for women aged 35–64 years in Q1 with diabetes duration <2 years at 4.83 (95% CI 3.15–7.40) and lowest for men aged 65–84 years in Q5 with diabetes duration ≥2 years at 1.13 (1.03–1.24).

CONCLUSIONS

SES modifies the association between type 2 diabetes and mortality so that RR for mortality is lower among more deprived populations. Age, sex, and duration of diabetes also interact with type 2 diabetes to influence RR of mortality. Differences in prevalence of comorbidities may explain these findings.

OBJECTIVE

We have previously observed that genetic profiles determined by the combination of five functionally significant single nucleotide polymorphisms (SNPs) (rs1800795, rs5498, rs5361, rs1024611, and rs679620) of genes encoding prototypical inflammatory molecules are associated with history of ischemic stroke. Here we tested the ability of this multigenic model to predict stroke risk in a large population-based prospective cohort of subjects with type 2 diabetes.

RESEARCH DESIGN AND METHODS

This study was conducted using a prospective cohort of individuals with type 2 diabetes participating in the Go-DARTS (Genetics of Diabetes Audit and Research in Tayside Scotland) study, which includes genetic and clinical information of patients with diabetes within the Tayside region of Scotland, U.K. The above-mentioned inflammatory SNPs were investigated in 2,182 Go-DARTS participants. We created an inflammatory risk score (IRS), ranging from 0 to 5, according to the number of “at-risk” genotypes concomitantly carried by a given individual. The primary outcome was the occurrence of fatal or nonfatal stroke of any kind. Mean follow-up time was 6.2 ± 1.1 years.

RESULTS

The incidence of stroke increased according to the IRS. The IRS was significantly and independently associated with increased stroke risk after adjustment for other conventional risk factors (hazard ratio 1.34 [95% CI 1.1–1.7]; P = 0.009). The highest hazard ratio for stroke was found in subjects concomitantly carrying >3 proinflammatory variations and in subjects without previous cardiovascular diseases.

CONCLUSIONS

This large prospective cohort study provides evidence that SNPs of genes encoding prototypical inflammatory molecules may be used to create multigenic models that predict stroke risk in subjects with type 2 diabetes.

Background

Common variation in the Fat Mass and Obesity related (FTO) gene is associated with increased body fat and susceptibility to type 2 diabetes (T2D). We hypothesized that this would also associate with metabolic phenotypes of insulin resistance, and increased risk of cardiovascular morbidity and mortality.

Methods and Results

FTO rs9939609 genotype was determined in 4897 patients with T2D in the prospective Genetics of Diabetes Audit and Research Study in Tayside Scotland (Go-DARTS) study. The A allele was associated with lower plasma HDL cholesterol (mean difference 0.03 mmol/L, p=0.008), higher triglycerides (0.1 mmol/L, p=0.007), higher atherogenic index of plasma (0.03, p=0.003) and, as expected, increased BMI (0.77 kg/m2, p=8.8×10−6). During a mean follow up of 3.6 years the A allele was also associated with increased risk (HR 2.36, CI 1.49-3.74, p=0.0002) of fatal and non fatal myocardial infarction (total 324 events) in a model including baseline age, gender, prevalent myocardial infarction, smoking status, statin and insulin use. This association diminished but remained significant when obesity related traits such as BMI, glycated haemoglobin and lipid parameters were also included (HR 2.01 CI 1.18-3.45, p=0.011). There was a strong interaction of FTO genotype and statin use and cardiovascular outcome (p=0.001) such that cardiovascular morbidity and mortality was completely abrogated in individuals prescribed statins.

Conclusion

The increased fat mass in carriers of the A allele of rs9939609 of FTO is associated not only with increased risk of T2D, but also with an increase in atherogenic lipid profile, and myocardial infarction in these patients. This variant may therefore in future contribute to more effective targeting of specific preventative therapy.

OBJECTIVE

The antidiabetic properties of metformin are mediated through its ability to activate the AMP-activated protein kinase (AMPK). Activation of AMPK can suppress tumor formation and inhibit cell growth in addition to lowering blood glucose levels. We tested the hypothesis that metformin reduces the risk of cancer in people with type 2 diabetes.

RESEARCH DESIGN AND METHODS

In an observational cohort study using record-linkage databases and based in Tayside, Scotland, U.K., we identified people with type 2 diabetes who were new users of metformin in 1994–2003. We also identified a set of diabetic comparators, individually matched to the metformin users by year of diabetes diagnosis, who had never used metformin. In a survival analysis we calculated hazard ratios for diagnosis of cancer, adjusted for baseline characteristics of the two groups using Cox regression.

RESULTS

Cancer was diagnosed among 7.3% of 4,085 metformin users compared with 11.6% of 4,085 comparators, with median times to cancer of 3.5 and 2.6 years, respectively (P < 0.001). The unadjusted hazard ratio (95% CI) for cancer was 0.46 (0.40–0.53). After adjusting for sex, age, BMI, A1C, deprivation, smoking, and other drug use, there was still a significantly reduced risk of cancer associated with metformin: 0.63 (0.53–0.75).

CONCLUSIONS

These results suggest that metformin use may be associated with a reduced risk of cancer. A randomized trial is needed to assess whether metformin is protective in a population at high risk for cancer.

For most associations of common single nucleotide polymorphisms (SNPs) with common diseases, the genetic model of inheritance is unknown. The authors extended and applied a Bayesian meta-analysis approach to data from 19 studies on 17 replicated associations with type 2 diabetes. For 13 SNPs, the data fitted very well to an additive model of inheritance for the diabetes risk allele; for 4 SNPs, the data were consistent with either an additive model or a dominant model; and for 2 SNPs, the data were consistent with an additive or recessive model. Results were robust to the use of different priors and after exclusion of data for which index SNPs had been examined indirectly through proxy markers. The Bayesian meta-analysis model yielded point estimates for the genetic effects that were very similar to those previously reported based on fixed- or random-effects models, but uncertainty about several of the effects was substantially larger. The authors also examined the extent of between-study heterogeneity in the genetic model and found generally small between-study deviation values for the genetic model parameter. Heterosis could not be excluded for 4 SNPs. Information on the genetic model of robustly replicated association signals derived from genome-wide association studies may be useful for predictive modeling and for designing biologic and functional experiments.

OBJECTIVE

Metformin is actively transported into the liver by the organic cation transporter (OCT)1 (encoded by SLC22A1). In 12 normoglycemic individuals, reduced-function variants in SLC22A1 were shown to decrease the ability of metformin to reduce glucose excursion in response to oral glucose. We assessed the effect of two common loss-of-function polymorphisms in SLC22A1 on metformin response in a large cohort of patients with type 2 diabetes.

RESEARCH DESIGN AND METHODS

The Diabetes Audit and Research in Tayside Scotland (DARTS) database includes prescribing and biochemistry information and clinical phenotypes of all patients with diabetes within Tayside, Scotland, from 1992 onwards. R61C and 420del variants of SLC22A1 were genotyped in 3,450 patients with type 2 diabetes who were incident users of metformin. We assessed metformin response by modeling the maximum A1C reduction in 18 months after starting metformin and investigated whether a treatment target of A1C <7% was achieved. Sustained metformin effect on A1C between 6 and 42 months was also assessed, as was the time to metformin monotherapy failure. Covariates were SLC22A1 genotype, BMI, average drug dose, adherence, and creatinine clearance.

RESULTS

A total of 1,531 patients were identified with a definable metformin response. R61C and 420del variants did not affect the initial A1C reduction (P = 0.47 and P = 0.92, respectively), the chance of achieving a treatment target (P = 0.83 and P = 0.36), the average A1C on monotherapy up to 42 months (P = 0.44 and P = 0.75), or the hazard of monotherapy failure (P = 0.85 and P = 0.56).

CONCLUSIONS

The SLC22A1 loss-of-function variants, R61C and 420del, do not attenuate the A1C reduction achieved by metformin in patients with type 2 diabetes.

OBJECTIVE—This study examined how differences in the BMI distribution of type 2 diabetic case subjects affected genome-wide patterns of type 2 diabetes association and considered the implications for the etiological heterogeneity of type 2 diabetes.

RESEARCH DESIGN AND METHODS—We reanalyzed data from the Wellcome Trust Case Control Consortium genome-wide association scan (1,924 case subjects, 2,938 control subjects: 393,453 single-nucleotide polymorphisms [SNPs]) after stratifying case subjects (into “obese” and “nonobese”) according to median BMI (30.2 kg/m2). Replication of signals in which alternative case-ascertainment strategies generated marked effect size heterogeneity in type 2 diabetes association signal was sought in additional samples.

RESULTS—In the “obese-type 2 diabetes” scan, FTO variants had the strongest type 2 diabetes effect (rs8050136: relative risk [RR] 1.49 [95% CI 1.34–1.66], P = 1.3 × 10−13), with only weak evidence for TCF7L2 (rs7901695 RR 1.21 [1.09–1.35], P = 0.001). This situation was reversed in the “nonobese” scan, with FTO association undetectable (RR 1.07 [0.97–1.19], P = 0.19) and TCF7L2 predominant (RR 1.53 [1.37–1.71], P = 1.3 × 10−14). These patterns, confirmed by replication, generated strong combined evidence for between-stratum effect size heterogeneity (FTO: PDIFF = 1.4 × 10−7; TCF7L2: PDIFF = 4.0 × 10−6). Other signals displaying evidence of effect size heterogeneity in the genome-wide analyses (on chromosomes 3, 12, 15, and 18) did not replicate. Analysis of the current list of type 2 diabetes susceptibility variants revealed nominal evidence for effect size heterogeneity for the SLC30A8 locus alone (RRobese 1.08 [1.01–1.15]; RRnonobese 1.18 [1.10–1.27]: PDIFF = 0.04).

CONCLUSIONS—This study demonstrates the impact of differences in case ascertainment on the power to detect and replicate genetic associations in genome-wide association studies. These data reinforce the notion that there is substantial etiological heterogeneity within type 2 diabetes.

Introduction

Cellulitis is a common problem, caused by spreading bacterial inflammation of the skin, with redness, pain, and lymphangitis. Up to 40% of affected people have systemic illness. Erysipelas is a form of cellulitis with marked superficial inflammation, typically affecting the lower limbs and the face. The most common pathogens in adults are streptococci and Staphylococcus aureus. Cellulitis and erysipelas can result in local necrosis and abscess formation. Around a quarter of affected people have more than one episode of cellulitis within 3 years.

Methods and outcomes

We conducted a systematic review and aimed to answer the following clinical questions: What are the effects of treatments for cellulitis and erysipelas? What are the effects of treatments to prevent recurrence of cellulitis and erysipelas? We searched: Medline, Embase, The Cochrane Library and other important databases up to May 2007 (BMJ Clinical Evidence reviews are updated periodically, please check our website for the most up-to-date version of this review). We included harms alerts from relevant organisations such as the US Food and Drug Administration (FDA) and the UK Medicines and Healthcare products Regulatory Agency (MHRA).

Results

We found 14 systematic reviews, RCTs, or observational studies that met our inclusion criteria. We performed a GRADE evaluation of the quality of evidence for interventions.

Conclusions

In this systematic review we present information relating to the effectiveness and safety of the following interventions: antibiotics, comparative effects of different antibiotic regimens, duration of antibiotics, and treatment of predisposing factors.

Key Points

Cellulitis is a common problem caused by spreading bacterial inflammation of the skin, with redness, pain, and lymphangitis. Up to 40% of people have systemic illness. Erysipelas is a form of cellulitis with marked superficial inflammation, typically affecting the lower limbs and the face.Risk factors include lymphoedema, leg ulcer, toe web intertrigo, and traumatic wounds.The most common pathogens in adults are streptococci and Staphylococcus aureus.Cellulitis and erysipelas can result in local necrosis and abscess formation. Around a quarter of people have more than one episode of cellulitis within 3 years.

Antibiotics cure 50−100% of infections, but we don't know which antibiotic regimen is most successful. We don't know whether antibiotics are as effective when given orally as when given intravenously, or whether intramuscular administration is more effective than intravenous.A 5-day course of antibiotics may be as effective as a 10-day course at curing the infection and preventing early recurrence.

Although there is consensus that treatment of predisposing factors can prevent recurrence of cellulitis or erysipelas, we found no studies that assessed the benefits of this approach.

Objective

Linkage of the chromosome 1q21-25 region to type 2 diabetes has been demonstrated in multiple ethnic groups. We performed common variant fine-mapping across a 23Mb interval in a multiethnic sample to search for variants responsible for this linkage signal.

Research Design and Methods

In all, 5,290 SNPs were successfully genotyped in 3,179 T2D cases and controls from eight populations with evidence of 1q linkage. Samples were ascertained using strategies designed to enhance power to detect variants causal for 1q-linkage. Following imputation, we estimate ~80% coverage of common variation across the region (r2>0.8, Europeans). Association signals of interest were evaluated through in silico replication and de novo genotyping in approximately 8,500 cases and 12,400 controls.

Results

Association mapping of the 23Mb region identified two strong signals, both restricted to the subset of European-descent samples. The first mapped to the NOS1AP (CAPON) gene region (lead SNP: rs7538490, OR 1.38 (95% CI, 1.21-1.57), p=1.4×10-6 in 999 cases and 1,190 controls): the second within an extensive region of linkage disequilibrium that includes the ASH1L and PKLR genes (lead SNP: rs11264371, OR 1.48 [1.18-1.76], p=1.0×10-5, under a dominant model). However, there was no evidence for association at either signal on replication, and, across all data (>24,000 subjects), no indication that these variants were causally-related to T2D status.

Conclusion

Detailed fine-mapping of the 23Mb region of replicated linkage has failed to identify common variant signals contributing to the observed signal. Future studies should focus on identification of causal alleles of lower frequency and higher penetrance.

OBJECTIVES—Genome-wide association studies have dramatically increased the number of common genetic variants that are robustly associated with type 2 diabetes. A possible clinical use of this information is to identify individuals at high risk of developing the disease, so that preventative measures may be more effectively targeted. Here, we assess the ability of 18 confirmed type 2 diabetes variants to differentiate between type 2 diabetic case and control subjects.

RESEARCH DESIGN AND METHODS—We assessed index single nucleotide polymorphisms (SNPs) for the 18 independent loci in 2,598 control subjects and 2,309 case subjects from the Genetics of Diabetes Audit and Research Tayside Study. The discriminatory ability of the combined SNP information was assessed by grouping individuals based on number of risk alleles carried and determining relative odds of type 2 diabetes and by calculating the area under the receiver-operator characteristic curve (AUC).

RESULTS—Individuals carrying more risk alleles had a higher risk of type 2 diabetes. For example, 1.2% of individuals with >24 risk alleles had an odds ratio of 4.2 (95% CI 2.11–8.56) against the 1.8% with 10–12 risk alleles. The AUC (a measure of discriminative accuracy) for these variants was 0.60. The AUC for age, BMI, and sex was 0.78, and adding the genetic risk variants only marginally increased this to 0.80.

CONCLUSIONS—Currently, common risk variants for type 2 diabetes do not provide strong predictive value at a population level. However, the joint effect of risk variants identified subgroups of the population at substantially different risk of disease. Further studies are needed to assess whether individuals with extreme numbers of risk alleles may benefit from genetic testing.

We studied genes involved in pancreatic β cell function and survival, identifying associations between SNPs in WFS1 and diabetes risk in UK populations that we replicated in an Ashkenazi population and in additional UK studies. In a pooled analysis comprising 9,533 cases and 11,389 controls, SNPs in WFS1 were strongly associated with diabetes risk. Rare mutations in WFS1 cause Wolfram syndrome; using a gene-centric approach, we show that variation in WFS1 also predisposes to common type 2 diabetes.

Background

Common variants of the PPARA gene have been found to associate with ischaemic heart disease in non diabetic men. The L162V variant was found to be protective while the C2528G variant increased risk. L162V has also been associated with altered lipid measures. We therefore sought to determine the effect of PPARA gene variation on susceptibility to myocardial infarction in patients with type 2 diabetes. 1810 subjects with type 2 diabetes from the prospective Go-DARTS study were genotyped for the L162V and C2528G variants in the PPARA gene and the association of the variants with incident non-fatal myocardial infarction was examined. Cox's proportional hazards was used to interrogate time to event from recruitment, and linear regression for analysing association of genotype with quantitative clinical traits.

Results

The V162 allele was associated with decreased risk of non-fatal myocardial infarction (HR = 0.31, 95%CI 0.10–0.93 p = 0.037) whereas the C2528 allele was associated with increased risk (HR = 2.77 95%CI 1.34–5.75 p = 0.006). Similarly V162 was associated with a later mean age of diagnosis with type 2 diabetes and C2582 an earlier age of diagnosis. C2528 was also associated with increased total cholesterol and LDL cholesterol, which did not account for the observed increased risk. Haplotype analysis demonstrated that when both rare variants occurred on the same haplotype the effect of each was abrogated.

Conclusion

Genetic variation at the PPARA locus is important in determining cardiovascular risk in both male and female patients with diabetes. This genotype associated risk appears to be independent of the effect of these genotypes on lipid profiles and age of diagnosis with diabetes.

Objective

To compare risks of cardiovascular outcomes between patients with type 2 diabetes and patients with established coronary heart disease.

Design

Cross sectional study and cohort study using routinely collected datasets.

Setting

Tayside, Scotland (population 400 000) during 1988-95.

Subjects

In the cross sectional study, among patients aged 45-64, 1155 with type 2 diabetes were compared with 1347 who had had a myocardial infarction in the preceding 8 years. In the cohort study 3477 patients of all ages with newly diagnosed type 2 diabetes were compared with 7414 patients who had just had a myocardial infarction.

Main outcome measures

Risk ratios for death from all causes, cardiovascular death, and hospital admission for myocardial infarction were calculated by Cox proportional hazards analysis and adjusted for age and sex.

Results

In the cross sectional study the adjusted risk ratio for death from all causes was 2.27 (95% confidence interval 1.82 to 2.83) for patients who had had myocardial infarction compared with those with diabetes, and the risk ratio for hospital admission for myocardial infarction was 1.33 (1.14 to 1.55). In the cohort study, patients who had just had a myocardial infarction had a higher risk of death from all causes (adjusted risk ratio 1.35 (1.25 to 1.44)), cardiovascular death (2.93 (2.54 to 3.41)), and hospital admission for myocardial infarction (3.10 (2.57 to 3.73)).

Conclusions

Patients with type 2 diabetes were at lower risk of cardiovascular outcomes than patients with established coronary heart disease.

What is already known on this topicA recent influential study suggested that patients with type 2 diabetes without established cardiovascular disease have as high a risk of cardiovascular events and death as non-diabetic patients who have had a myocardial infarctionSome clinicians therefore advocate aggressive treatment of cardiovascular risk factors in the presence of diabetesWhat this study addsPatients with type 2 diabetes are at lower risk of death from all causes or cardiovascular causes and of hospital admission for myocardial infarction than patients with established coronary heart disease

Helen Colhoun and colleagues report findings from a Scottish registry linkage study regarding contemporary risks for cardiovascular events and all-cause mortality among individuals diagnosed with type 1 diabetes.

Background

Randomized controlled trials have shown the importance of tight glucose control in type 1 diabetes (T1DM), but few recent studies have evaluated the risk of cardiovascular disease (CVD) and all-cause mortality among adults with T1DM. We evaluated these risks in adults with T1DM compared with the non-diabetic population in a nationwide study from Scotland and examined control of CVD risk factors in those with T1DM.

Methods and Findings

The Scottish Care Information-Diabetes Collaboration database was used to identify all people registered with T1DM and aged ≥20 years in 2005–2007 and to provide risk factor data. Major CVD events and deaths were obtained from the national hospital admissions database and death register. The age-adjusted incidence rate ratio (IRR) for CVD and mortality in T1DM (n = 21,789) versus the non-diabetic population (3.96 million) was estimated using Poisson regression. The age-adjusted IRR for first CVD event associated with T1DM versus the non-diabetic population was higher in women (3.0: 95% CI 2.4–3.8, p<0.001) than men (2.3: 2.0–2.7, p<0.001) while the IRR for all-cause mortality associated with T1DM was comparable at 2.6 (2.2–3.0, p<0.001) in men and 2.7 (2.2–3.4, p<0.001) in women. Between 2005–2007, among individuals with T1DM, 34 of 123 deaths among 10,173 who were <40 years and 37 of 907 deaths among 12,739 who were ≥40 years had an underlying cause of death of coma or diabetic ketoacidosis. Among individuals 60–69 years, approximately three extra deaths per 100 per year occurred among men with T1DM (28.51/1,000 person years at risk), and two per 100 per year for women (17.99/1,000 person years at risk). 28% of those with T1DM were current smokers, 13% achieved target HbA1c of <7% and 37% had very poor (≥9%) glycaemic control. Among those aged ≥40, 37% had blood pressures above even conservative targets (≥140/90 mmHg) and 39% of those ≥40 years were not on a statin. Although many of these risk factors were comparable to those previously reported in other developed countries, CVD and mortality rates may not be generalizable to other countries. Limitations included lack of information on the specific insulin therapy used.

Conclusions

Although the relative risks for CVD and total mortality associated with T1DM in this population have declined relative to earlier studies, T1DM continues to be associated with higher CVD and death rates than the non-diabetic population. Risk factor management should be improved to further reduce risk but better treatment approaches for achieving good glycaemic control are badly needed.

Please see later in the article for the Editors' Summary

Editors' Summary

Background. People with diabetes are more likely to have cardiovascular disease such as heart attacks and strokes. They also have a higher risk of dying prematurely from any cause. Controlling blood sugar (glucose), blood pressure, and cholesterol can help reduce these risks. Some people with type 1 diabetes can achieve tight blood glucose control through a strict regimen that includes a carefully calculated diet, frequent physical activity, regular blood glucose testing several times a day, and multiple daily doses of insulin. Other drugs can reduce blood pressure and cholesterol levels. Keeping one's weight in the normal range and not smoking are important ways in which all people, including those with type 1 diabetes can reduce their risks of heart disease and premature death.

Why Was This Study Done? Researchers and doctors have known for almost two decades what patients with type 1 diabetes can do to minimize the complications from the disease and thereby reduce their risks for cardiovascular disease and early death. So for some time now, patients should have been treated and counseled accordingly. This study was done to evaluate the current risks for have cardiovascular disease and premature death amongst people living with type 1 diabetes in a high-income country (Scotland).

What Did the Researchers Do and Find? From a national register of all people with type 1 diabetes in Scotland, the researchers selected those who were older than 20 years and alive at any time from January 2005 to May 2008. This included about 19,000 people who had been diagnosed with type 1 diabetes before 2005. Another 2,600 were diagnosed between 2005 and 2008. They also obtained data on heart attacks and strokes in these patients from hospital records and on deaths from the natural death register. To obtain a good picture of the current relative risks, they compared the patients with type 1 diabetes with the non-diabetic general Scottish population with regard to the risk of heart attacks/strokes and death from all causes. They also collected information on how well the people with diabetes controlled their blood glucose, on their weight, and whether they smoked.

They found that the current risks compared with the general Scottish population are quite a bit lower than those of people with type 1 diabetes in earlier decades. However, people with type 1 diabetes in Scotland still have much higher (more than twice) the risk of heart attacks, strokes, or premature death than the general population. Moreover, the researchers found a high number of deaths in younger people with diabetes from coma—caused by either too much blood sugar (hyperglycemia) or too little (hypoglycemia). Severe hyperglycemia and hypoglycemia happen when blood glucose control is poor. When the scientists looked at test results for HbA1c levels (a test that is done once or twice a year to see how well patients controlled their blood sugar over the previous 3 months) for all patients, they found that the majority of them did not come close to controlling their blood glucose within the recommended range.

When the researchers compared body mass index (a measure of weight that takes height into account) and smoking between the people with type 1 diabetes and the general population, they found similar proportions of smokers and overweight or obese people.

What Do these Findings Mean? The results represent a snapshot of the recent situation regarding complications from type 1 diabetes in the Scottish population. The results suggest that within this population, strategies over the past two decades to reduce complications from type 1 diabetes that cause cardiovascular disease and death are working, in principle. However, there is much need for further improvement. This includes the urgent need to understand why so few people with type 1 diabetes achieve good control of their blood sugar, and what can be done to improve this situation. It is also important to put more effort into keeping people with diabetes from taking up smoking or getting them to quit, as well as preventing them from getting overweight or promoting weight reduction, because this could further reduce the risks of cardiovascular disease and premature death.

Additional Information

Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.1001321

National Diabetes Information Clearinghouse, a service of the US National Institute of Diabetes and Digestive and Kidney Diseases, has information on heart disease and diabetes, on general complications of diabetes, and on the HbA1c test (on this site and some others called A1C test) that measures control of blood sugar over the past 3 months

Diabetes.co.uk provides general information on type 1 diabetes, its complications, and what people with the disease can do to reduce their risks

The Canadian Diabetes Association offers a cardiovascular risk self-assessment tool and other relevant information

The American Diabetes Association has information on the benefits and challenges of tight blood sugar control and how it is tested

The Juvenile Diabetes Research Foundation funds research to prevent, cure, and treat type 1 diabetes

Diabetes UK provides extensive information on diabetes for patients, carers, and clinicians

Objectives

To investigate patterns of self monitoring of blood glucose concentration in diabetic patients who use insulin and to determine whether frequency of self monitoring is related to glycaemic control.

Setting

Diabetes database, Tayside, Scotland.

Subjects

Patients resident in Tayside in 1993-5 who were using insulin and were registered on the database and diagnosed with insulin dependent (type 1) or non-insulin dependent (type 2) diabetes before 1993.

Main outcome measures

Number of glucose monitoring reagent strips dispensed (reagent strip uptake) derived from records of prescriptions. First recorded haemoglobin A1c concentration in the study period, and reagent strips dispensed in the previous 6 months.

Results

Among 807 patients with type 1 diabetes, 128 (16%) did not redeem any prescriptions for glucose monitoring reagent strips in the 3 year study period. Only 161 (20%) redeemed prescriptions for enough reagent strips to test glucose daily. The corresponding figures for the 790 patients with type 2 diabetes who used insulin were 162 (21%; no strips) and 131 (17%; daily tests). Reagent strip uptake was influenced both by age and by deprivation category. There was a direct relation between uptake and glycaemic control for 258 patients (with recorded haemoglobin A1c concentrations) with type 1 diabetes. In a linear regression model the decrease in haemoglobin A1c concentration for every extra 180 reagent strips dispensed was 0.7%. For the 290 patients with type 2 diabetes who used insulin there was no such relation.

Conclusions

Self monitoring of blood glucose concentration is associated with improved glycaemic control in patients with type 1 diabetes. Regular self monitoring in patients with type 1 and type 2 diabetes is uncommon.

Key messagesSeveral studies have indicated the importance of self monitoring of blood glucose concentration for prevention of complications in patients with diabetesUptake of reagent strips for self monitoring of blood glucose among diabetic patients who used insulin was low, with only 20% of patients with type 1 diabetes and 17% of those with type 2 diabetes obtaining enough strips to test blood glucose concentration once dailyReagent strip uptake depends on characteristics such as age and social deprivation category, and patient groups with low uptake should be identified and targetedThere was a direct association between strip uptake in the previous 6 months and glycaemic control in patients with type 1 diabetes but not in those with type 2 diabetes

Background

Obesity is highly associated with elevated serum triglycerides, hepatic steatosis and type 2 diabetes (T2D). The I148M (rs738409) genetic variant of patatin-like phospholipase domain-containing 3 gene (PNPLA3) is known to modulate hepatic triglyceride accumulation, leading to steatosis. No association between PNPLA3 I148M genotype and T2D in Europeans has been reported. Aim of this study is to examine the relationship between PNPLA3 I148M genotypes and serum triglycerides, insulin resistance and T2D susceptibility by testing a gene-environment interaction model with severe obesity.

Methods and Findings

PNPLA3 I148M was genotyped in a large obese cohort, the SOS study (n = 3,473) and in the Go-DARTS (n = 15,448), a T2D case-control study. Metabolic parameters were examined across the PNPLA3 I148M genotypes in participants of the SOS study at baseline and at 2- and 10-year follow up after bariatric surgery or conventional therapy. The associations with metabolic parameters were validated in the Go-DARTS study. Serum triglycerides were found to be lower in the PNPLA3 148M carriers from the SOS study at baseline and from the Go-DARTS T2D cohort. An increased risk for T2D conferred by the 148M allele was found in the SOS study (O.R. 1.09, 95% C.I. 1.01-1.39, P = 0.040) and in severely obese individuals in the Go-DARTS study (O.R. 1.37, 95% C.I. 1.13-1.66, P = 0.001). The 148M allele was no longer associated with insulin resistance or T2D after bariatric surgery in the SOS study and no association with the 148M allele was observed in the less obese (BMI<35) individuals in the Go-DARTS study (P for interaction  = 0.002). This provides evidence for the obesity interaction with I48M allele and T2D risk in a large-scale cross-sectional and a prospective interventional study.

Conclusions

Severely obese individuals carrying the PNPLA3 148M allele have lower serum triglyceride levels, are more insulin resistant and more susceptible to T2D. This study supports the hypothesis that obesity-driven hepatic lipid accumulation may contribute to T2D susceptibility.

Background:

Managed clinical networks have been used to coordinate chronic disease management across geographical regions in the United Kingdom. Our objective was to review how clinical networks and multidisciplinary team-working can be supported by Web-based information technology while clinical requirements continually change.

Methods:

A Web-based population information system was developed and implemented in November 2000. The system incorporates local guidelines and shared clinical information based upon a national dataset for multispecialty use. Automated data linkages were developed to link to the master index database, biochemistry, eye screening, and general practice systems and hospital diabetes clinics. Web-based data collection forms were developed where computer systems did not exist. The experience over the first 10 years (to October 2010) was reviewed.

Results:

The number of people with diabetes in Tayside increased from 9694 (2.5% prevalence) in 2001 to 18,355 (4.6%) in 2010. The user base remained stable (~400 users), showing a high level of clinical utility was maintained. Automated processes support a single point of data entry with 10,350 clinical messages containing 40,463 data items sent to external systems during year 10. The system supported quality improvement of diabetes care; for example, foot risk recording increased from 36% in 2007 to 73.3% in 2010.

Conclusions:

Shared-care datasets can improve communication between health care service providers. Web-based technology can support clinical networks in providing comprehensive, seamless care across a geographical region for people with diabetes. While health care requirements evolve, technology can adapt, remain usable, and contribute significantly to quality improvement and working practice.

OBJECTIVE

The causal nature of associations between circulating triglycerides, insulin resistance, and type 2 diabetes is unclear. We aimed to use Mendelian randomization to test the hypothesis that raised circulating triglyceride levels causally influence the risk of type 2 diabetes and raise normal fasting glucose levels and hepatic insulin resistance.

RESEARCH DESIGN AND METHODS

We tested 10 common genetic variants robustly associated with circulating triglyceride levels against the type 2 diabetes status in 5,637 case and 6,860 control subjects and four continuous outcomes (reflecting glycemia and hepatic insulin resistance) in 8,271 nondiabetic individuals from four studies.

RESULTS

Individuals carrying greater numbers of triglyceride-raising alleles had increased circulating triglyceride levels (SD 0.59 [95% CI 0.52–0.65] difference between the 20% of individuals with the most alleles and the 20% with the fewest alleles). There was no evidence that the carriers of greater numbers of triglyceride-raising alleles were at increased risk of type 2 diabetes (per weighted allele odds ratio [OR] 0.99 [95% CI 0.97–1.01]; P = 0.26). In nondiabetic individuals, there was no evidence that carriers of greater numbers of triglyceride-raising alleles had increased fasting insulin levels (SD 0.00 per weighted allele [95% CI −0.01 to 0.02]; P = 0.72) or increased fasting glucose levels (0.00 [−0.01 to 0.01]; P = 0.88). Instrumental variable analyses confirmed that genetically raised circulating triglyceride levels were not associated with increased diabetes risk, fasting glucose, or fasting insulin and, for diabetes, showed a trend toward a protective association (OR per 1-SD increase in log10 triglycerides: 0.61 [95% CI 0.45–0.83]; P = 0.002).

CONCLUSIONS

Genetically raised circulating triglyceride levels do not increase the risk of type 2 diabetes or raise fasting glucose or fasting insulin levels in nondiabetic individuals. One explanation for our results is that raised circulating triglycerides are predominantly secondary to the diabetes disease process rather than causal.

Cardiovascular disease candidate genes, including genes previously associated with type 2 diabetes and diabetic nephropathy, were not associated with diabetic retinopathy, although a limited number of variants merit further investigation in larger cohorts.

Purpose.

To investigate whether variants in cardiovascular candidate genes, some of which have been previously associated with type 2 diabetes (T2D), diabetic retinopathy (DR), and diabetic nephropathy (DN), are associated with DR in the Candidate gene Association Resource (CARe).

Methods.

Persons with T2D who were enrolled in the study (n = 2691) had fundus photography and genotyping of single nucleotide polymorphisms (SNPs) in 2000 candidate genes. Two case definitions were investigated: Early Treatment Diabetic Retinopathy Study (ETDRS) grades ≥14 and ≥30. The χ2 analyses for each CARe cohort were combined by Cochran-Mantel-Haenszel (CMH) pooling of odds ratios (ORs) and corrected for multiple hypothesis testing. Logistic regression was performed with adjustment for other DR risk factors. Results from replication in independent cohorts were analyzed with CMH meta-analysis methods.

Results.

Among 39 genes previously associated with DR, DN, or T2D, three SNPs in P-selectin (SELP) were associated with DR. The strongest association was to rs6128 (OR = 0.43, P = 0.0001, after Bonferroni correction). These associations remained significant after adjustment for DR risk factors. Among other genes examined, several variants were associated with DR with significant P values, including rs6856425 tagging α-l-iduronidase (IDUA) (P = 2.1 × 10−5, after Bonferroni correction). However, replication in independent cohorts did not reveal study-wide significant effects. The P values after replication were 0.55 and 0.10 for rs6128 and rs6856425, respectively.

Conclusions.

Genes associated with DN, T2D, and vascular diseases do not appear to be consistently associated with DR. A few genetic variants associated with DR, particularly those in SELP and near IDUA, should be investigated in additional DR cohorts.

Objective

The causal nature of associations between circulating triglycerides, insulin resistance and type 2 diabetes is unclear. We aimed to use Mendelian randomization to test the hypothesis that raised circulating triglyceride levels causally influence the risk of type 2 diabetes, raised normal fasting glucose levels, and hepatic insulin resistance.

Research design and methods

We tested 10 common genetic variants robustly associated with circulating triglyceride levels against type 2 diabetes status in 5637 cases, 6860 controls, and four continuous outcomes (reflecting glycemia and hepatic insulin resistance) in 8271 non-diabetic individuals from four studies.

Results

Individuals carrying greater numbers of triglyceride-raising alleles had increased circulating triglyceride levels (0.59 SD [95% CI: 0.52, 0.65] difference between the 20% of individuals with the most alleles and the 20% with the fewest alleles). There was no evidence that carriers of greater numbers of triglyceride-raising alleles were at increased risk of type 2 diabetes (per weighted allele odds ratio (OR) 0.99 [95% CI: 0.97, 1.01]; P = 0.26). In non-diabetic individuals, there was no evidence that carriers of greater numbers of triglyceride-raising alleles had increased fasting insulin levels (0.00 SD per weighted allele [95% CI: −0.01, 0.02]; P = 0.72) or increased fasting glucose levels (0.00 SD per weighted allele [95% CI: −0.01, 0.01]; P = 0.88). Instrumental variable analyses confirmed that genetically raised circulating triglyceride levels were not associated with increased diabetes risk, fasting glucose or fasting insulin, and, for diabetes, showed a trend towards a protective association (OR per 1 SD increase in log10-triglycerides: 0.61 [95% CI: 0.45, 0.83]; P = 0.002).

Conclusion

Genetically raised circulating triglyceride levels do not increase the risk of type 2 diabetes, or raise fasting glucose or fasting insulin levels in non-diabetic individuals. One explanation for our results is that raised circulating triglycerides are predominantly secondary to the diabetes disease process rather than causal.

Metformin is the most commonly used pharmacological therapy for type 2 diabetes. We carried out a GWA study on glycaemic response to metformin in 1024 Scottish patients with type 2 diabetes. Replication was in two cohorts consisting of 1783 Scottish patients and 1113 patients from the UK Prospective Diabetes Study. In a meta-analysis (n=3920) we observed an association (P=2.9 *10−9) for a SNP rs11212617 at a locus containing the ataxia telangiectasia mutated (ATM) gene with an odds ratio of 1.35 (95% CI 1.22 to 1.49) for treatment success. In a rat hepatoma cell line, inhibition of ATM with KU-55933 attenuated the phosphorylation and activation of AMPK in response to metformin. We conclude that ATM, a gene known to be involved in DNA repair and cell cycle control, plays a role in the effect of metformin upstream of AMPK, and variation in this gene alters glycaemic response to metformin.