Lower risk of death and cardiovascular events in patients with diabetes initiating glucagon-like peptide-1 receptor agonists or sodium-glucose cotransporter-2 inhibitors: A real-world study in two Italian cohorts

Aim: To examine the efficacy and safety of glucagon-like peptide-1 receptor agonists (GLP-1RAs) and sodium-glucose cotransporter-2 (SGLT2) inhibitors compared with other antihyperglycaemic agents (AHAs) in large and unselected populations of the Lombardy and Apulia regions in Italy. Materials and Methods: An observational cohort study of first-time users of GLP-1RAs, SGLT2 inhibitors or other AHAs was conducted from 2010 to 2018. Death and cardiovascular (CV) events were evaluated using conditional Cox models in propensity-score-matched populations. Adjusted hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated for each region and in a meta-analysis for pooled risks. Results: After propensity-score matching, the Lombardy cohort included 18 716 and 11 683 patients and the Apulia cohort 9772 and 6046 patients for the GLP-1RA and SGLT2 inhibitor groups, respectively. Use of GLP-1RAs was associated with lower rates of death (HR 0.61, CI 0.56-0.65, Lombardy; HR 0.63, CI 0.55-0.71, Apulia), cerebrovascular disease and ischaemic stroke (HR 0.70, CI 0.63-0.79; HR 0.72, CI 0.60-0.87, Lombardy), peripheral vascular disease (HR 0.72, CI 0.64-0.82, Lombardy; HR 0.80, CI 0.67-0.98, Apulia), and lower limb complications (HR 0.67, CI 0.56-0.81, Lombardy; HR 0.69, CI 0.51-0.93, Apulia). Compared with other AHAs, SGLT2 inhibitor use decreased the risk of death (HR 0.47, CI 0.40-0.54, Lombardy; HR 0.43, CI 0.32-0.57, Apulia), cerebrovascular disease (HR 0.75, CI 0.61-0.91, Lombardy; HR 0.72, CI 0.54-0.96, Apulia), and heart failure (HR 0.56, CI 0.46-0.70, Lombardy; HR 0.57, CI 0.42-0.77, Apulia). In the pooled cohorts, a reduction in heart failure was also observed with GLP-1RAs (HR 0.89, 95% CI 0.82-0.97). Serious adverse events were quite low in frequency. Conclusion: Our findings from real-world practice confirm the favourable effect of GLP-1RAs and SGLT2 inhibitors on death and CV outcomes across both regions consistently. Thus, these drug classes should be preferentially considered in a broad type 2 diabetes population beyond those with CV disease

Long-term vitamin E supplementation fails to reduce lipid peroxidation in people at cardiovascular risk: analysis of underlying factors

BACKGROUND: Antioxidant supplementation with vitamin E had no effect in the prevention of cardiovascular diseases (CVD) in three recent large, randomized clinical trials. In order to reassess critically the role of vitamin E in CVD prevention, it is important to establish whether these results are related to a lack of antioxidant action. METHODS: We examined the in vivo antioxidant effect of vitamin E (300 mg/day for about three years) in 144 participants in the Primary Prevention Project (females and males, aged ≥ 50 y, with at least one major CV risk factor, but no history of CVD). Urinary 8-epi-PGF(2α) (isoprostane F(2α)-III or 15-F(2t)-isoP), a validated biomarker of lipid peroxidation, was measured by mass spectrometry. RESULTS: Urinary excretion of 8-epi-PGF(2α) [pg/mg creatinine, median (range)] was 141 (67–498) in treated and 148 (76–561) in untreated subjects (p = 0.10). Taking into account possible confounding variables, multiple regression analysis confirmed that vitamin E had no significant effect on this biomarker. Levels of 8-epi-PGF(2α) were in the normal range for most subjects, except smokers and those with uncontrolled blood pressure or hyperglycemia. CONCLUSIONS: Prolonged vitamin E supplementation did not reduce lipid peroxidation in subjects with major cardiovascular risk factors. The observation that the rate of lipid peroxidation was near normal in a large proportion of subjects may help explain why vitamin E was not effective as an antioxidant in the PPP study and was ineffective for CVD prevention in large scale trials

EFSA's OpenFoodTox: An open source toxicological database on chemicals in food and feed and its future developments

Since its creation in 2002, the European Food Safety Authority (EFSA) has produced risk assessments for over 5000 substances in >2000 Scientific Opinions, Statements and Conclusions through the work of its Scientific Panels, Units and Scientific Committee. OpenFoodTox is an open source toxicological database, available both for download and data visualisation which provides data for all substances evaluated by EFSA including substance characterisation, links to EFSA's outputs, applicable legislations regulations, and a summary of hazard identification and hazard characterisation data for human health, animal health and ecological assessments. The database has been structured using OECD harmonised templates for reporting chemical test summaries (OHTs) to facilitate data sharing with stakeholders with an interest in chemical risk assessment, such as sister agencies, international scientific advisory bodies, and others. This manuscript provides a description of OpenFoodTox including data model, content and tools to download and search the database. Examples of applications of OpenFoodTox in chemical risk assessment are discussed including new quantitative structure–activity relationship (QSAR) models, integration into tools (OECD QSAR Toolbox and AMBIT-2.0), assessment of environmental footprints and testing of threshold of toxicological concern (TTC) values for food related compounds. Finally, future developments for OpenFoodTox 2.0 include the integration of new properties, such as physico-chemical properties, exposure data, toxicokinetic information; and the future integration within in silico modelling platforms such as QSAR models and physiologically-based kinetic models. Such structured in vivo, in vitro and in silico hazard data provide different lines of evidence which can be assembled, weighed and integrated using harmonised Weight of Evidence approaches to support the use of New Approach Methodologies (NAMs) in chemical risk assessment and the reduction of animal testing

RAS gene polymorphisms, classical risk factors and the advent of coronary artery disease in the Portuguese population

<p>Abstract</p> <p>Background</p> <p>Several polymorphisms within the renin-angiotensin system cluster of genes have been associated with the advent of coronary artery disease (CAD) or related pathologies. We investigated the distribution of 5 of these polymorphisms in order to find any association with CAD development and distinguish if any of the biochemical and behavioural factors interact with genetic polymorphisms in the advent of the disease.</p> <p>Methods</p> <p><it>ACE </it>I/D (rs4340), <it>ACE </it>A11860G (rs4343), <it>AT1R </it>A1166C (rs5186), <it>AGT </it>T174M (rs4762) and <it>AGT </it>M235T (rs699) gene polymorphisms were PCR-RFLP analysed in 298 CAD patients and 510 controls from Portugal. Several biochemical and behavioural markers were obtained.</p> <p>Results</p> <p><it>ACE </it>I/D DD and <it>ACE</it>11860 GG genotypes are risk factors for CAD in this population. The simultaneous presence of <it>ACE </it>I/D I and <it>ACE</it>11860 A alleles corresponds to a significant trend towards a decrease in CAD incidence. We found several synergistic effects between the studied polymorphisms and classical risk factors such as hypertension, obesity, diabetes and dyslipidaemia: the presence of the DD genotype of <it>ACE </it>I/D (and also <it>ACE</it>11860 GG) increases the odds of developing CAD when associated to each one of these classical risk factors, particularly when considering the male and early onset CAD subgroup analysis; <it>AGT</it>235 TT also increases the CAD risk in the presence of hypertension and dyslipidaemia, and <it>AT1R</it>1166 interacts positively with hypertension, smoking and obesity.</p> <p>Conclusion</p> <p><it>ACE </it>polymorphisms were shown to play a major role in individual susceptibility to develop CAD. There is also a clear interaction between RAS predisposing genes and some biochemical/environmental risk factors in CAD onset, demonstrating a significant enhancement of classical markers particularly by <it>ACE </it>I/D and <it>ACE</it>11860.</p

CATMoS: Collaborative Acute Toxicity Modeling Suite.

BACKGROUND: Humans are exposed to tens of thousands of chemical substances that need to be assessed for their potential toxicity. Acute systemic toxicity testing serves as the basis for regulatory hazard classification, labeling, and risk management. However, it is cost- and time-prohibitive to evaluate all new and existing chemicals using traditional rodent acute toxicity tests. In silico models built using existing data facilitate rapid acute toxicity predictions without using animals. OBJECTIVES: The U.S. Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) Acute Toxicity Workgroup organized an international collaboration to develop in silico models for predicting acute oral toxicity based on five different end points: Lethal Dose 50 (LD50 value, U.S. Environmental Protection Agency hazard (four) categories, Globally Harmonized System for Classification and Labeling hazard (five) categories, very toxic chemicals [LD50 (LD50≤50mg/kg)], and nontoxic chemicals (LD50>2,000mg/kg). METHODS: An acute oral toxicity data inventory for 11,992 chemicals was compiled, split into training and evaluation sets, and made available to 35 participating international research groups that submitted a total of 139 predictive models. Predictions that fell within the applicability domains of the submitted models were evaluated using external validation sets. These were then combined into consensus models to leverage strengths of individual approaches. RESULTS: The resulting consensus predictions, which leverage the collective strengths of each individual model, form the Collaborative Acute Toxicity Modeling Suite (CATMoS). CATMoS demonstrated high performance in terms of accuracy and robustness when compared with in vivo results. DISCUSSION: CATMoS is being evaluated by regulatory agencies for its utility and applicability as a potential replacement for in vivo rat acute oral toxicity studies. CATMoS predictions for more than 800,000 chemicals have been made available via the National Toxicology Program's Integrated Chemical Environment tools and data sets (ice.ntp.niehs.nih.gov). The models are also implemented in a free, standalone, open-source tool, OPERA, which allows predictions of new and untested chemicals to be made. https://doi.org/10.1289/EHP8495