A Genome-Wide Association Study Provides New Evidence That CACNA1C Gene is Associated With Diabetic Cataract

PURPOSE: Diabetic cataract is one of the major eye complications of diabetes. It was reported that cataract occurs two to five times more frequently in patients with diabetes compared with those with no diabetes. The purpose of this study was to identify genetic contributors of diabetic cataract based on a genome-wide association approach using a well-defined Scottish diabetic cohort. METHODS: We adapted linked e-health records to define diabetic cataract. A diabetic cataract case in this study was defined as a type 2 diabetic patient who has ever been recorded in the linked e-health records to have cataracts in both eyes or who had previous cataract extraction surgeries in at least one eye. A control in this study was defined as a type 2 diabetic individual who has never been diagnosed as cataract in the linked e-health records and had no history of cataract surgeries. A standard genome-wide association approach was applied. RESULTS: Overall, we have 2341 diabetic cataract cases and 2878 controls in the genetics of diabetes audit and research in Tayside Scotland (GoDARTS) dataset. We found that the P value of rs2283290 in the CACNA1C gene was 8.81 × 10(−10), which has reached genome-wide significance. We also identified that the blood calcium level was statistically different between diabetic cataract cases and controls. CONCLUSIONS: We identified supporting evidence that CACNA1C gene is associated with diabetic cataract. The role of calcium in the cataractogenesis needs to be reevaluated in future studies

Risk of cardiovascular disease and total mortality in adults with type 1 diabetes: Scottish registry linkage study

<p>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.</p> <p>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.</p> <p>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.</p&gt

Biomarkers of rapid chronic kidney disease progression in type 2 diabetes.

Here we evaluated the performance of a large set of serum biomarkers for the prediction of rapid progression of chronic kidney disease (CKD) in patients with type 2 diabetes. We used a case-control design nested within a prospective cohort of patients with baseline eGFR 30-60 ml/min per 1.73 m(2). Within a 3.5-year period of Go-DARTS study patients, 154 had over a 40% eGFR decline and 153 controls maintained over 95% of baseline eGFR. A total of 207 serum biomarkers were measured and logistic regression was used with forward selection to choose a subset that were maximized on top of clinical variables including age, gender, hemoglobin A1c, eGFR, and albuminuria. Nested cross-validation determined the best number of biomarkers to retain and evaluate for predictive performance. Ultimately, 30 biomarkers showed significant associations with rapid progression and adjusted for clinical characteristics. A panel of 14 biomarkers increased the area under the ROC curve from 0.706 (clinical data alone) to 0.868. Biomarkers selected included fibroblast growth factor-21, the symmetric to asymmetric dimethylarginine ratio, β2-microglobulin, C16-acylcarnitine, and kidney injury molecule-1. Use of more extensive clinical data including prebaseline eGFR slope improved prediction but to a lesser extent than biomarkers (area under the ROC curve of 0.793). Thus we identified several novel associations of biomarkers with CKD progression and the utility of a small panel of biomarkers to improve prediction.We acknowledge all the SUMMIT partners (http://www.imi-summit.eu/) for their assistance with this project. This work was funded by the Innovative Medicine Initiative under grant agreement no. IMI/115006 (the SUMMIT consortium) and the Go-DARTS cohort was funded by the Chief Scientists Office Scotland.This is the accepted manuscript of a paper published in Kidney International (Looker et al., Kidney International, 2015 doi: 10.1038/ki.2015.199). The final version is available at http://dx.doi.org/10.1038/ki.2015.19

Cohort Profile:Scottish Diabetes Research Network Type 1 Bioresource Study (SDRNT1BIO)

No abstract available

Apolipoprotein CIII and N-terminal prohormone b-type natriuretic peptide as independent predictors for cardiovascular disease in type 2 diabetes

Background and aims: Developing sparse panels of biomarkers for cardiovascular disease in type 2 diabetes would enable risk stratification for clinical decision making and selection into clinical trials. We examined the individual and joint performance of five candidate biomarkers for incident cardiovascular disease (CVD) in type 2 diabetes that an earlier discovery study had yielded. Methods: Apolipoprotein CIII (apoCIII), N-terminal prohormone B-type natriuretic peptide (NT-proBNP), high sensitivity Troponin T (hsTnT), Interleukin-6, and Interleukin-15 were measured in baseline serum samples from the Collaborative Atorvastatin Diabetes trial (CARDS) of atorvastatin versus placebo. Among 2105 persons with type 2 diabetes and median age of 62.9 years (range 39.2–77.3), there were 144 incident CVD (acute coronary heart disease or stroke) cases during the maximum 5-year follow up. We used Cox Proportional Hazards models to identify biomarkers associated with incident CVD and the area under the receiver operating characteristic curves (AUROC) to assess overall model prediction. Results: Three of the biomarkers were singly associated with incident CVD independently of other risk factors; NT-proBNP (Hazard Ratio per standardised unit 2.02, 95% Confidence Interval [CI] 1.63, 2.50), apoCIII (1.34, 95% CI 1.12, 1.60) and hsTnT (1.40, 95% CI 1.16, 1.69). When combined in a single model, only NT-proBNP and apoCIII were independent predictors of CVD, together increasing the AUROC using Framingham risk variables from 0.661 to 0.745. Conclusions: The biomarkers NT-proBNP and apoCIII substantially increment the prediction of CVD in type 2 diabetes beyond that obtained with the variables used in the Framingham risk score

Ethnic differences in Glycaemic control in people with type 2 diabetes mellitus living in Scotland

Background and Aims: Previous studies have investigated the association between ethnicity and processes of care and intermediate outcomes of diabetes, but there are limited population-based studies available. The aim of this study was to use population-based data to investigate the relationships between ethnicity and glycaemic control in men and women with diabetes mellitus living in Scotland.<p></p> Methods: We used a 2008 extract from the population-based national electronic diabetes database of Scotland. The association between ethnicity with mean glycaemic control in type 2 diabetes mellitus was examined in a retrospective cohort study, including adjustment for a number of variables including age, sex, socioeconomic status, body mass index (BMI), prescribed treatment and duration of diabetes.<p></p> Results: Complete data for analyses were available for 56,333 White Scottish adults, 2,535 Pakistanis, 857 Indians, 427 Chinese and 223 African-Caribbeans. All other ethnic groups had significantly (p<0.05) greater proportions of people with suboptimal glycaemic control (HbA1c >58 mmol/mol, 7.5%) compared to the White Scottish group, despite generally younger mean age and lower BMI. Fully adjusted odds ratios for suboptimal glycaemic control were significantly higher among Pakistanis and Indians (1.85, 95% CI: 1.68–2.04, and 1.62,95% CI: 1.38–1.89) respectively.<p></p> Conclusions: Pakistanis and Indians with type 2 diabetes mellitus were more likely to have suboptimal glycaemic control than the white Scottish population. Further research on health services and self-management are needed to understand the association between ethnicity and glycaemic control to address ethnic disparities in glycaemic control.<p></p&gt

Reservoir-Excess Pressure Parameters Independently Predict Cardiovascular Events in Individuals With Type 2 Diabetes

The parameters derived from reservoir-excess pressure analysis (RPA) have prognostic utility in several populations. However, evidence in type 2 diabetes (T2DM) remains scarce. We determined if these parameters were associated with T2DM, and whether they would predict cardiovascular events in individuals with T2DM.We studied 306people with T2DM and cardiovascular disease (CVD)(DMCVD:70.4±7.8yrs), 348people with T2DM but without CVD (DM:67.7±8.4yrs) and 178peoplewithout T2DM or CVD (CTRL:67.2±8.9yrs). RPA-derived parameters including reservoir pressure integral (INTPR), peak reservoir pressure (MAXPR), excess pressure integral (INTXSP), systolic rate constant (SRC) and diastolic rate constant (DRC) were obtained by radial artery tonometry. INTPR was lower in DMCVD and DM than CTRL. MAXPR was lower, and INTXSP was greater in DMCVD than DM and CTRL. SRC was lower in a stepwise manner among groups(DMCVD<DM<CTRL).DRC was greater in DMCVD than CTRL. In the sub group of individuals with T2DM (n=642), 14 deaths (6 cardiovascular and 9non-cardiovascular causes) and 108cardiovascular events occurred during a 3-yr follow-up period. Logistic regression analysis revealed that INTPR [odds ratio 0.59(95%CI:0.45-0.79)] and DRC [odds ratio 1.60(95%CI:1.25-2.06)] were independent predictors of cardiovascular events during follow-up after adjusting for conventional risk factors(both p<0.001). Further adjustments for potential confounders had no influence on associations. These findings demonstrate that altered RPA-derived parameters are associated with T2DM. Furthermore, baseline values of INTPR and DRC independently predict cardiovascular events in individuals with T2DM, indicating the potential clinical utility of these parameters for risk stratification in T2DM

Use of Vascular Assessments and Novel Biomarkers to Predict Cardiovascular Events in Type 2 Diabetes:The SUMMIT VIP Study

Cardiovascular disease (CVD) risk prediction represents an increasing clinical challenge in the treatment of diabetes. We used a panel of vascular imaging, functional assessments, and biomarkers reflecting different disease mechanisms to identify clinically useful markers of risk for cardiovascular (CV) events in subjects with type 2 diabetes (T2D) with or without manifest CVD

Contemporary Risk of Hip Fracture in Type 1 and Type 2 Diabetes:A National Registry Study From Scotland

The purpose of this study was to compare contemporary risk of hip fracture in type 1 and type 2 diabetes with the nondiabetic population. Using a national diabetes database, we identified those with type 1 and type 2 diabetes who were aged 20 to 84 years and alive anytime from January 1, 2005 to December 31, 2007. All hospitalized events for hip fracture in 2005 to 2007 for diabetes patients were linked and compared with general population counts. Age- and calendar-year-adjusted incidence rate ratios were calculated by diabetes type and sex. One hundred five hip fractures occurred in 21,033 people (59,585 person-years) with type 1 diabetes; 1421 in 180,841 people (462,120 person-years) with type 2 diabetes; and 11,733 hip fractures over 10,980,599 person-years in the nondiabetic population (3.66 million people). Those with type 1 diabetes had substantially elevated risks of hip fracture compared with the general population incidence risk ratio (IRR) of 3.28 (95% confidence interval [CI] 2.52–4.26) in men and 3.54 (CI 2.75–4.57) in women. The IRR was greater at younger ages, but absolute risk difference was greatest at older ages. In type 2 diabetes, there was no elevation in risk among men (IRR 0.97 [CI 0.92–1.02]) and the increase in risk in women was small (IRR 1.05 [CI 1.01–1.10]). There remains a substantial elevation relative risk of hip fracture in people with type 1 diabetes, but the relative risk is much lower than in earlier studies. In contrast, there is currently little elevation in overall hip fracture risk with type 2 diabetes, but this may mask elevations in risk in particular subgroups of type 2 diabetes patients with different body mass indexes, diabetes duration, or drug exposure

Serum kidney injury molecule 1 and β2-microglobulin perform as well as larger biomarker panels for prediction of rapid decline in renal function in type 2 diabetes

Aims/hypothesis: As part of the Surrogate Markers for Micro- and Macrovascular Hard Endpoints for Innovative Diabetes Tools (SUMMIT) programme we previously reported that large panels of biomarkers derived from three analytical platforms maximised prediction of progression of renal decline in type 2 diabetes. Here, we hypothesised that smaller (n ≤ 5), platform-specific combinations of biomarkers selected from these larger panels might achieve similar prediction performance when tested in three additional type 2 diabetes cohorts. Methods: We used 657 serum samples, held under differing storage conditions, from the Scania Diabetes Registry (SDR) and Genetics of Diabetes Audit and Research Tayside (GoDARTS), and a further 183 nested case–control sample set from the Collaborative Atorvastatin in Diabetes Study (CARDS). We analysed 42 biomarkers measured on the SDR and GoDARTS samples by a variety of methods including standard ELISA, multiplexed ELISA (Luminex) and mass spectrometry. The subset of 21 Luminex biomarkers was also measured on the CARDS samples. We used the event definition of loss of >20% of baseline eGFR during follow-up from a baseline eGFR of 30–75 ml min−1 [1.73 m]−2. A total of 403 individuals experienced an event during a median follow-up of 7 years. We used discrete-time logistic regression models with tenfold cross-validation to assess association of biomarker panels with loss of kidney function. Results: Twelve biomarkers showed significant association with eGFR decline adjusted for covariates in one or more of the sample sets when evaluated singly. Kidney injury molecule 1 (KIM-1) and β2-microglobulin (B2M) showed the most consistent effects, with standardised odds ratios for progression of at least 1.4 (p < 0.0003) in all cohorts. A combination of B2M and KIM-1 added to clinical covariates, including baseline eGFR and albuminuria, modestly improved prediction, increasing the area under the curve in the SDR, Go-DARTS and CARDS by 0.079, 0.073 and 0.239, respectively. Neither the inclusion of additional Luminex biomarkers on top of B2M and KIM-1 nor a sparse mass spectrometry panel, nor the larger multiplatform panels previously identified, consistently improved prediction further across all validation sets. Conclusions/interpretation: Serum KIM-1 and B2M independently improve prediction of renal decline from an eGFR of 30–75 ml min−1 [1.73 m]−2 in type 2 diabetes beyond clinical factors and prior eGFR and are robust to varying sample storage conditions. Larger panels of biomarkers did not improve prediction beyond these two biomarkers