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Background: Identification of individuals with high risk for first-ever myocardial infarction (MI) can be improved. The objectives of the study were to survey multiple protein biomarkers for association with the 10-year risk of incident MI and identify a clinically significant risk model that adds information to current common risk models., Methods and Results: We used an immunoassay platform that uses a sensitive, sample-efficient molecular counting technology to measure 51 proteins in samples from the fourth survey (1994) in the Tromsø Study, a longitudinal study of men and women in Tromsø, Norway. A case control design was used with 419 first-ever MI cases (169 females/250 males) and 398 controls (244 females/154 males). Of the proteins measured, 17 were predictors of MI when considered individually after adjustment for traditional risk factors either in men, women, or both. The 6 biomarkers adjusted for traditional risk factors that were selected in a multivariable model (odds ratios [OR] per standard deviation) using a stepwise procedure were apolipoprotein B/apolipoprotein A1 ratio (1.40), kallikrein (0.73), lipoprotein a (1.29), matrix metalloproteinase 9 (1.30), the interaction term IP-10/CXCL10×women (0.69), and the interaction term thrombospondin 4×men (1.38). The composite risk of these biomarkers added significantly to the traditional risk factor model with a net reclassification improvement of 14% (P=0.0002), whereas the receiver operating characteristic area increased from 0.757 to 0.791, P=0.0004., Conclusions: Novel protein biomarker models improve identification of 10-year MI risk above and beyond traditional risk factors with 14% better allocation to either high or low risk group., (© 2015 American Heart Association, Inc.)

Aims: Insulin sensitivity and acute insulin response measure key components of Type 2 diabetes aetiology that contribute independently to risk in the Insulin Resistance Atherosclerosis Study. As insulin sensitivity and acute insulin response are not routinely measured in a clinical setting, we evaluated three fasting biomarker models, homeostasis model assessment of insulin sensitivity (HOMA-%S), β-cell function (HOMA-%B) and a Diabetes Risk Score, as potential surrogates for risk associated with insulin sensitivity, acute insulin response and the interaction of these two measures, the disposition index., Methods: Models were calculated from baseline plasma biomarker concentrations for 664 participants who underwent a frequently sampled intravenous glucose tolerance test. To assess relationships among biomarker models and test measures, we calculated improvement in risk estimation gained by combining each fasting measure with each frequently sampled intravenous glucose tolerance test measure using logistic regression., Results: The strongest correlates of acute insulin response, insulin sensitivity and disposition index were HOMA-%B (r(s)(2) = 0.23), HOMA-%S (r(s)(2) = 0.48) and Diabetes Risk Score (r(s)(2) = 0.34), respectively. Individual areas under the curves for prediction of diabetes were 0.549 (HOMA-%B), 0.694 (HOMA-%S), 0.700 (insulin sensitivity), 0.714 (acute insulin response), 0.756 (Diabetes Risk Score) and 0.817 (disposition index). Models combining acute insulin response with Diabetes Risk Score (area under the curve 0.798) or HOMA-%S (area under the curve 0.805) nearly equalled disposition index, outperforming other individual measures (P < 0.05). Insulin sensitivity plus Diabetes Risk Score (area under the curve 0.760) was better than insulin sensitivity (P = 0.03), but not better than Diabetes Risk Score alone. HOMA-%S plus insulin sensitivity (area under the curve 0.704) was not significantly better than either alone., Conclusions: The Diabetes Risk Score and HOMA-%S were excellent surrogates for insulin sensitivity, capturing the predictive power of insulin sensitivity. Diabetes Risk Score captured some of the additional predictive power of acute insulin response, but the HOMA models did not. No fasting model was as predictive as disposition index, but the Diabetes Risk Score was the best surrogate., (© 2012 The Authors. Diabetic Medicine © 2012 Diabetes UK.)

Background: This study compares a previously developed Diabetes Risk Score to commonly used clinical tools for type 2 diabetes risk evaluation in the Insulin Resistance Atherosclerosis Study (IRAS) cohort, a multi-ethnic US cohort. Available as a clinical test, the PreDx® Diabetes Risk Score uses fasting concentrations of adiponectin, C-reactive protein, ferritin, interleukin-2 receptor alpha, HbA(1c) , glucose and insulin, plus age and gender to predict 5-year risk of diabetes. It was developed in a Northern European population., Methods: The Diabetes Risk Score was measured using archived fasting plasma specimens from 722 non-diabetic IRAS participants, 17.6% of whom developed diabetes during 5.2 years median follow-up (inter-quartile range: 5.1-5.4 years). The study included non-Hispanic whites (41.8%), Hispanics (34.5%) and African Americans (23.7%). Performance of the algorithm was evaluated by area under the receiver operating characteristic curve (AROC) and risk reclassification against other tools., Results: The Diabetes Risk Score discriminates participants who developed diabetes from those who did not significantly better than fasting glucose (AROC = 0.763 versus 0.710, p = 0.003). The Diabetes Risk Score performed equally well in subpopulations defined by race/ethnicity or gender. The Diabetes Risk Score provided a significant net reclassification improvement of 0.24 (p = 0.01) when comparing predefined low/moderate/high Diabetes Risk Score categories to metabolic syndrome risk factor counting. The Diabetes Risk Score complemented the use of the oral glucose tolerance test by identifying high risk patients with impaired fasting glucose but normal glucose tolerance, 33% of whom converted., Conclusions: Measuring the Diabetes Risk Score of elevated-risk US patients could help physicians decide which patients warrant more intensive intervention. The Diabetes Risk Score performed equally well across the ethnic subpopulations present in this cohort., (Copyright © 2012 John Wiley & Sons, Ltd.)

Purpose: To assess performance of a biomarker-based score that predicts the five-year risk of diabetes (Diabetes Risk Score, DRS) in an independent cohort that included 15-year follow-up., Method: DRS was developed on the Inter99 cohort, and validated on the Botnia cohort. Performance was benchmarked against other risk-assessment tools comparing calibration, time to event analysis, and net reclassification., Results: The area under the receiver-operating characteristic curve (AUC) was 0.84 for the Inter99 cohort and 0.78 for the Botnia cohort. In the Botnia cohort, DRS provided better discrimination than fasting plasma glucose (FPG), homeostasis model assessment of insulin resistance, oral glucose tolerance test or risk scores derived from Framingham or San Antonio Study cohorts. Overall reclassification with DRS was significantly better than using FPG and glucose tolerance status (p < 0.0001). In time to event analysis, rates of conversion to diabetes in low, moderate, and high DRS groups were significantly different (p < 0.001)., Conclusion: This study validates DRS performance in an independent population, and provides a more accurate assessment of T2DM risk than other methods.

Objective: The purpose of this study was to develop a model for assessing the 5-year risk of developing type 2 diabetes from a panel of 64 circulating candidate biomarkers., Research Design and Methods: Subjects were selected from the Inter99 cohort, a longitudinal population-based study of approximately 6,600 Danes in a nested case-control design with the primary outcome of 5-year conversion to type 2 diabetes. Nondiabetic subjects, aged >or=39 years, with BMI >or=25 kg/m(2) at baseline were selected. Baseline fasting serum samples from 160 individuals who developed type 2 diabetes and from 472 who did not were tested. An ultrasensitive immunoassay was used to measure of 58 candidate biomarkers in multiple diabetes-associated pathways, along with six routine clinical variables. Statistical learning methods and permutation testing were used to select the most informative biomarkers. Risk model performance was estimated using a validated bootstrap bias-correction procedure., Results: A model using six biomarkers (adiponectin, C-reactive protein, ferritin, interleukin-2 receptor A, glucose, and insulin) was developed for assessing an individual's 5-year risk of developing type 2 diabetes. This model has a bootstrap-estimated area under the curve of 0.76, which is greater than that for A1C, fasting plasma glucose, fasting serum insulin, BMI, sex-adjusted waist circumference, a model using fasting glucose and insulin, and a noninvasive clinical model., Conclusions: A model incorporating six circulating biomarkers provides an objective and quantitative estimate of the 5-year risk of developing type 2 diabetes, performs better than single risk indicators and a noninvasive clinical model, and provides better stratification than fasting plasma glucose alone.

A technique based on cold argon and oxygen plasmas permits radiocarbon dates to be obtained on paintings that contain inorganic pigments. (To listen to a podcast about this feature, please go to the Analytical Chemistry website at http://pubs.acs.org/journal/ancham.).

Chk1 is a key regulator of the S and G2/M checkpoints and is activated following DNA damage by agents such as the topoisomerase I inhibitor camptothecin (CPT). It has been proposed that Chk1 inhibitors used in combination with such a DNA damaging agent to treat tumors would potentiate cytotoxicity and increase the therapeutic index, particularly in tumors lacking functional p53. The aim of this study was to determine whether gene expression analysis could be used to inform lead optimization of a novel series of Chk1 inhibitors. The candidate small-molecule Chk1 inhibitors were used in combination with CPT to identify potential markers of functional Chk1 inhibition, as well as resulting cell cycle progression, using cDNA-based microarrays. Differential expression of several of these putative marker genes was further validated by RT-PCR for use as a medium-throughput assay. In the presence of DNA damage, Chk1 inhibitors altered CPT-dependent effects on the expression of cell cycle and DNA repair genes in a manner consistent with a Chk1-specific mechanism of action. Furthermore, differential expression of selected marker genes, cyclin E2, EGR1, and DDIT3, was dose dependent for Chk1 inhibition. RT-PCR results for these genes following treatment with a panel of Chk1 inhibitors showed a strong correlation between marker gene response and the ability of each compound to abrogate cell cycle arrest in situ following CPT-induced DNA damage. These results demonstrate the utility of global expression analysis to identify surrogate markers, providing an alternative method for rapid compound characterization to support advancement decisions in early drug discovery.

A light-element radioactive ion-beam capability has been developed at the LBNL 88-Inch Cyclotron. The system is based on the coupled-cyclotrons method and utilizes short-lived species, e.g., 11C, 14O, 13N produced by (p,n) and (p,alpha) reactions at the LBNL Biomedical Isotope Facility Cyclotron. In a first experiment, 197Au(11C,xn)208-xAt excitation functions have been measured for energies ranging from the Coulomb barrier up to 110 MeV using a beam of 11C with intensities up to (1-2)x10(8) ions/sec on target. The results of this experiment are compared to measurements of 197Au(12C, xn)209-xAt excitation functions.

Coronary angiography and left ventriculography is commonly used to identify those patients with incomplete infarctions and therefore, a need for revascularization. The authors compared coronary angiography and left ventriculography with thallium 201 tomography using oral dipyridamole to identify patients with potential ischemia in the infarct zone indicating viable tissue. Forty-five patients (37 men, 8 women) with acute myocardial infarctions (29 anterior, 16 inferior) who received intravenous thrombolytic therapy were studied. On the basis of the left ventriculograms, only 16 patients were judged to have residual function in the infarct zone. Six of these patients had no thallium redistribution in the infarct zone, indicating lack of residual ischemia. Of the 29 patients with no residual function in the infarct zone, 18 had redistribution in the infarct zone, suggesting residual ischemic myocardium and thus viable tissue. Among the 32 patients with open infarct vessels, 15 had no redistribution in the infarct zone, but of the remaining 13 patients with occluded infarct vessels, 9 had redistribution in the infarct zone indicating residual ischemia and thus viable tissue. The authors' data suggest that neither wall motion analysis by left ventriculography nor the angiographic status of the infarct vessel identifies those patients with residual ischemia as evidenced by thallium tomography using oral dipyridamole.

Thrombolytic therapy has become the treatment of choice for patients with acute myocardial infarction. Researchers are not yet able to identify patients with salvage of myocardium who are at risk for recurrent coronary events. Thus, a prospective trial was performed in 46 patients with myocardial infarction (28 anterior and 18 inferior) who received thrombolytic therapy to determine if early thallium tomography (4.7 days) using oral dipyridamole would identify more patients with residual ischemia than early symptom-limited exercise treadmill tests (5.5 days). There were no complications during the exercise treadmill tests or oral dipyridamole thallium tomography. Mean duration of exercise was 11 +/- 3 minutes and the peak heart rate was 126 beats/min. Thirteen patients had positive test results. After oral dipyridamole all patients had abnormal thallium uptake on the early images. Positive scans with partial "filling in" of the initial perfusion defects were evident in 34 patients. Angina developed in 13 patients and was easily reversed with intravenous aminophylline. Both symptom-limited exercise treadmill tests and thallium tomography using oral dipyridamole were safely performed early after myocardial infarction in patients receiving thrombolytic therapy. Thallium tomography identified more patients with residual ischemia than exercise treadmill tests (74 vs 28%). Further studies are required to determine whether the results of thallium tomography after oral dipyridamole can be used to optimize patient management and eliminate the need for coronary angiography in some patients.