Relationship between apolipoprotein(a) size polymorphism and coronary heart disease in overweight subjects

BACKGROUND: Overweight is associated with an increased cardiovascular risk which is only partially explained by conventional risk factors. The objective of this study was to evaluate lipoprotein(a) [Lp(a)] plasma levels and apolipoprotein(a) [apo(a)] phenotypes in relation to coronary heart disease (CHD) in overweight subjects. METHODS: A total of 275 overweight (BMI ≥ 27 kg/m(2)) subjects, of which 155 had experienced a CHD event, 337 normal weight subjects with prior CHD and 103 CHD-free normal weight subjects were enrolled in the study. Lp(a) levels were determined by an ELISA technique and apo(a) isoforms were detected by a high-resolution immunoblotting method. RESULTS: Lp(a) levels were similar in the three study groups. Overweight subjects with CHD had Lp(a) concentrations significantly higher than those without [median (interquartile range): 20 (5–50.3) versus 12.6 (2.6–38.6) mg/dl, P < 0.05]. Furthermore, overweight subjects with CHD showed a higher prevalence of low molecular weight apo(a) isoforms than those without (55.5% versus 40.8%, P < 0.05) and with respect to the control group (55.5% versus 39.8%, P < 0.05). Stepwise regression analysis showed that apo(a) phenotypes, but not Lp(a) levels, entered the model as significant independent predictors of CHD in overweight subjects. CONCLUSIONS: Our data indicate that small-sized apo(a) isoforms are associated with CHD in overweight subjects. The characterization of apo(a) phenotypes might serve as a reliable biomarker to better assess the overall CHD risk of each subject with elevated BMI, leading to more intensive treatment of modifiable cardiovascular risk factors

Prognostic value of CT coronary angiography in diabetic and non-diabetic subjects with suspected CAD: importance of presenting symptoms

AIM: To assess the prognostic relevance of 64-slice computed tomography coronary angiography (CT-CA) and symptoms in diabetics and non-diabetics referred for cardiac evaluation. METHODS: We followed 210 patients with diabetes type 2 (DM) and 203 non-diabetic patients referred for CT-CA for ruling out coronary artery disease (CAD). Patients were without known history of CAD and were divided into four categories on the basis of symptoms at presentation (none, atypical angina, typical angina and dyspnoea). Clinical end points were major cardiac events (MACE): cardiac-related death, non-fatal myocardial infarction, unstable angina and cardiac revascularizations. Cox proportional hazard models, with and without adjustment for risk factors and multiplicative interaction term (obstructive CAD 7 DM), were developed to predict outcome. RESULTS: DM patients with dyspnoea or who were asymptomatic showed a higher prevalence of obstructive CAD than non-diabetics (p\u2009 64\u20090.01). At mean follow-up of 20.4 months, DM patients had worse cardiac event-free survival in comparison with non-DM patients (90% vs. 81%, p\u2009=\u20090.02). In multivariate analysis, CT-CA evidence of obstructive CAD (in DM patients: HR: 6.4; 95% CI: 2.3-17.5; p\u2009100 in non-DM patients (HR: 5.6; 95% CI: 1.4-21.5; p\u2009=\u20090.01). In Cox regression analysis of the overall population, interaction term obstructive CAD 7 DM resulted in non-significance. CONCLUSIONS: Among DM patients, dyspnoea carried a high event risk with a MACE rate four times higher. CT-CA findings were strongly predictive of outcome and proved valuable for further risk stratification

Genome-wide association and meta-analysis in populations from Starr County, Texas, and Mexico City identify type 2 diabetes susceptibility loci and enrichment for expression quantitative trait loci in top signals

AIMS/HYPOTHESIS: We conducted genome-wide association studies (GWASs) and expression quantitative trait loci (eQTL) analyses to identify and characterise risk loci for type 2 diabetes in Mexican-Americans from Starr County, TX, USA. METHOD: Using 1.8 million directly interrogated and imputed genotypes in 837 unrelated type 2 diabetes cases and 436 normoglycaemic controls, we conducted Armitage trend tests. To improve power in this population with high disease rates, we also performed ordinal regression including an intermediate class with impaired fasting glucose and/or glucose tolerance. These analyses were followed by meta-analysis with a study of 967 type 2 diabetes cases and 343 normoglycaemic controls from Mexico City, Mexico. RESULT: The top signals (unadjusted p value <1×10(−5)) included 49 single nucleotide polymorphisms (SNPs) in eight gene regions (PER3, PARD3B, EPHA4, TOMM7, PTPRD, HNT [also known as RREB1], LOC729993 and IL34) and six intergenic regions. Among these was a missense polymorphism (rs10462020; Gly639Val) in the clock gene PER3, a system recently implicated in diabetes. We also report a second signal (minimum p value 1.52× 10(−6)) within PTPRD, independent of the previously implicated SNP, in a population of Han Chinese. Top meta-analysis signals included known regions HNF1A and KCNQ1. Annotation of top association signals in both studies revealed a marked excess of trans-acting eQTL in both adipose and muscle tissues. CONCLUSIONS/INTERPRETATION: In the largest study of type 2 diabetes in Mexican populations to date, we identified modest associations of novel and previously reported SNPs. In addition, in our top signals we report significant excess of SNPs that predict transcript levels in muscle and adipose tissues

Novel prokaryotic expression of thioredoxin-fused insulinoma associated protein tyrosine phosphatase 2 (IA-2), its characterization and immunodiagnostic application

Background The insulinoma associated protein tyrosine phosphatase 2 (IA-2) is one of the immunodominant autoantigens involved in the autoimmune attack to the beta-cell in Type 1 Diabetes Mellitus. In this work we have developed a complete and original process for the production and recovery of the properly folded intracellular domain of IA-2 fused to thioredoxin (TrxIA-2ic) in Escherichia coli GI698 and GI724 strains. We have also carried out the biochemical and immunochemical characterization of TrxIA-2icand design variants of non-radiometric immunoassays for the efficient detection of IA-2 autoantibodies (IA-2A). Results The main findings can be summarized in the following statements: i) TrxIA-2ic expression after 3 h of induction on GI724 strain yielded ≈ 10 mg of highly pure TrxIA-2ic/L of culture medium by a single step purification by affinity chromatography, ii) the molecular weight of TrxIA-2ic (55,358 Da) could be estimated by SDS-PAGE, size exclusion chromatography and mass spectrometry, iii) TrxIA-2ic was properly identified by western blot and mass spectrometric analysis of proteolytic digestions (63.25 % total coverage), iv) excellent immunochemical behavior of properly folded full TrxIA-2ic was legitimized by inhibition or displacement of [35S]IA-2 binding from IA-2A present in Argentinian Type 1 Diabetic patients, v) great stability over time was found under proper storage conditions and vi) low cost and environmentally harmless ELISA methods for IA-2A assessment were developed, with colorimetric or chemiluminescent detection. Conclusions E. coli GI724 strain emerged as a handy source of recombinant IA-2ic, achieving high levels of expression as a thioredoxin fusion protein, adequately validated and applicable to the development of innovative and cost-effective immunoassays for IA-2A detection in most laboratories.Fil: Guerra, Luciano Lucas. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Faccinetti, Natalia Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Trabucchi, Aldana. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Rovitto, Bruno David. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Sabljic, Adriana Victoria. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Poskus, Edgardo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Iacono, Ruben Francisco. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; ArgentinaFil: Valdez, Silvina Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Instituto de Estudios de la Inmunidad Humoral Prof. Ricardo A. Margni; Argentin

A critical review of mathematical models and data used in diabetology

The literature dealing with mathematical modelling for diabetes is abundant. During the last decades, a variety of models have been devoted to different aspects of diabetes, including glucose and insulin dynamics, management and complications prevention, cost and cost-effectiveness of strategies and epidemiology of diabetes in general. Several reviews are published regularly on mathematical models used for specific aspects of diabetes. In the present paper we propose a global overview of mathematical models dealing with many aspects of diabetes and using various tools. The review includes, side by side, models which are simple and/or comprehensive; deterministic and/or stochastic; continuous and/or discrete; using ordinary differential equations, partial differential equations, optimal control theory, integral equations, matrix analysis and computer algorithms