Data exploration and knowledge extraction: their application to the study of endocrine disrupting chemicals

Interest in computer-aided methods for investigating the biological field has increased significantly. One method is Quantitative Structure-Activity Relationships (QSAR), a valuable technique for predicting the effects of a substance from its chemical structure. A challenging application of QSAR is in characterizing the (bio)activity profiles of chemicals. Endocrine disrupters (EDs) are exogenous substances interfering with the function of the endocrine system and represent an interesting field of application for in silico methods. EDs targets include nuclear receptors, particularly effects mediated by the oestrogen receptor (ER). They are also mentioned as substances requiring a more detailed control and specific authorisation within REACH, the new European legislation on chemicals. QSAR represents a challenging method to approach data gap about EDs since REACH substantially boosted interest on computational chemistry to replace experimental testing. This work: aimed to explore the status, availability and reliability of non-testing methods applied to endocrine disruption via oestrogen receptors and eventually to propose new models easily exploitable in regulatory contexts. The work evaluated existing QSAR models present in literature to assess their validity on the basis of the OECD principles for QSAR validation. Different kinds of models have been analysed and they were externally validated with new data found in the literature. Furthermore, new QSAR binary classifiers have been developed using different data mining techniques (e.g.: classification trees, fuzzy logic, neural networks) based on a very large and heterogeneous dataset of chemical compounds. The focus was given to both binding (RBA) and transcriptional activity (RA) better to characterize the effects of EDs. A possible combination of the models was also explored. A very good accuracy was achieved for both RA and RBA (>85%). These models can be a valuable complement to in vivo and in vitro studies in the toxicological characterisation of chemical compounds

Sex differences in stroke and major adverse clinical events in patients with atrial fibrillation::A systematic review and meta-analysis of 993,600 patients

Background: Atrial fibrillation (AF) is the most commonly diagnosed arrhythmia, which is associated with an increased risk of stroke. Several studies have suggested that female AF patients could have a greater risk for stroke and thromboembolic events (TE). Methods: A systematic literature review update and meta-analysis was conducted using Pubmed. The search used the terms “atrial fibrillation”, “gender”, “sex”, “female”, “women”, “stroke”, “thromboembolism”. Main aim of the study was to compare and male AF patients for occurrence of stroke and TE. Secondary outcomes were: major bleeding, cardiovascular (CV) death and all-cause death. Results: Forty-four studies were included in the analysis including 993,603 patients (48.9% women). After pooling the data, there was a higher risk of stroke for women vs. male AF patients (hazard ratio [HR]: 1.24; 95% confidence intervals [CIs]: 1.14–1.36). Overall, TE risk was not different between female and male patients, despite sensitivity analysis left some uncertainties. No sex differences were found for major bleeding, CV death and all-cause death. A significant relationship between increasing age and the difference in stroke risk between female and male AF patients was found (Delta HR: 1.01; 95% CI: 1.00–1.03 for each year of age increase). Conclusions: Female patients with AF are at increased risk of stroke compared to men. A significant relationship between increasing age and stroke risk in women compared to men was found, most evident at age > 65 years. Female sex may act as a stroke risk modifier, particularly in elderly and very elderly AF subjects, conferring a significant increase in stroke risk

Long-Term Relationship Between Atrial Fibrillation, Multimorbidity and Oral Anticoagulant Drug Use

Objectives: To analyze the relationship between atrial fibrillation (AF) and Charlson comorbidity index (CCI) in a population-based cohort study over a long-term follow-up period, in relation to oral anticoagulant (OAC) prescriptions and outcomes. Patients and Methods: We used data from the administrative health databases of Lombardy. All patients with AF and age 40 years and older and who were admitted to the hospital in 2002 were considered for analysis and followed up to 2014. AF diagnosis and CCI were established according to codes from the International Classification of Diseases, Ninth Revision. Results: In 2002, 24,040 patients were admitted with a diagnosis of AF. CCI was higher in patients with AF than in those without AF (1.8\ub12.1 vs 0.2\ub10.9; P<.001). Over 12 years of follow-up, AF was associated with an increased risk of higher CCI (beta coefficient, 1.69; 95% CI, 1.67-1.70). In patients with AF, CCI was inversely associated with OAC prescription at baseline (P<.001) and at the end of the follow-up (P=.03). Patients with AF and a high CCI ( 654) had a higher cumulative incidence of stroke, major bleeding, and all-cause death (all P<.001), compared with those with low CCI (range, 0-3). Adjusted Cox regression analysis revealed that time-dependent continuous CCI was associated with an increased risk for stroke, major bleeding, and all-cause death (all P<.001). Conclusions: In hospitalized patients, AF is associated with an increase in CCI that is inversely associated with OAC prescriptions during follow-up. CCI is independently associated with an increased risk of stroke, major bleeding, and all-cause death

Ligand-based prediction of hERG-mediated cardiotoxicity based on the integration of different machine learning techniques

<p>Drug-induced cardiotoxicity is a common side effect of drugs in clinical use or under postmarket surveillance and is commonly due to off-target interactions with the cardiac human-ether-a-go-go-related (hERG) potassium channel. Therefore, prioritizing drug candidates based on their hERG blocking potential is a mandatory step in the early preclinical stage of a drug discovery program. Herein, we trained and properly validated 30 ligandbased classifiers of hERG-related cardiotoxicity based on 7,963 curated compounds extracted by the freely accessible repository ChEMBL (version 25). Different machine learning algorithms were tested, namely, random forest, K-nearest neighbors, gradient boosting, extreme gradient boosting, multilayer perceptron, and support vector machine. The application of 1) the best practices for data curation, 2) the feature selection method VSURF, and 3) the synthetic minority oversampling technique (SMOTE) to properly handle the unbalanced data, allowed for the development of highly predictive models (BAMAX = 0.91, AUCMAX = 0.95). Remarkably, the undertaken temporal validation approach not only supported the predictivity of the herein presented classifiers but also suggested their ability to outperform those models commonly used in the literature. From a more methodological point of view, the study put forward a new computational workflow, freely available in the GitHub repository (https://github.com/PDelre93/hERG-QSAR), as valuable for building highly predictive models of hERG-mediated cardiotoxicity.</p&gt

Prescribing trends of glucose-lowering drugs in older adults from 2010 to 2021. a population-based study of Northern Italy

Aims: To describe glucose-lowering drugs prescribing pattern in a large population of older diabetics from 2010 to 2021. Methods: Using linkable administrative health databases, we included patients aged 65-90 years treated with glucose-lowering drugs. Prevalence rate of drugs was collected within each study year. A stratified analysis by gender, age and coexistence of cardiovascular disease (CVD) was conducted. Results: A total of 251 737 and 308 372 patients were identified in 2010 and 2021, respectively. Use of metformin (68.4% to 76.6%), DPP-4i (1.6% to 18.4%), GLP-1-RA (0.4% to 10.2%), SGLT2i (0.6% to 11.1%) increased, while sulfonylureas (53.6% to 20.7%) and glinides (10.5% to 3.5%) decreased over time. Metformin, glitazones, GLP1-RA, SGLT2i and DPP4i (except for 2021) usage decreased with aging, in contrast to sulfonylureas, glinides and insulin. The coexistence of CVD was associated with a higher prescription of glinides, insulin, DPP-4i, GLP1-RA and SGLT2i, particularly in 2021. Conclusions: We found a significant increase in the prescriptions of GLP-1 RA and SGLT2i in older diabetics, mainly in those with CVD. However, drugs without CV benefits including sulfonylureas and DPP-4i continued to be highly prescribed in older patients. There is still room to improve the management in this population according to recommendations

Risk of dementia and death in patients with atrial fibrillation: A competing risk analysis of a population-based cohort

12noPrevious studies have stated that atrial fibrillation (AF) is associated with a higher risk of dementia. However, none have examined the competition between death and incident dementia in patients with AF. We evaluated the risk of incident dementia in patients with AF in comparison to people without this arrhythmia, considering of the competing risk of death. METHODS: AF and non-AF cohorts were identified using the large administrative database of the Lombardy Region and followed for ten years. Patients with incident dementia were identified if they had an ICD 9 code referring to dementia at hospital discharge or a prescription for any anti-dementia drug. The association of AF with dementia or death was assessed with the multivariable Cox proportional-regression model, sensitivity analysis with a 1:1 propensity score matching and competing-risk analysis. RESULTS: In 2003 a total of 27,431 patients were hospitalized for AF in the Lombardy Region, while the cohort of non-AF counted 1,600,200 people. AF was associated with a higher risk of dementia (17%) and death (51%) at multivariable Cox analysis. These results were confirmed by the model fitted after propensity score matching. However, competing risk analysis found the association between AF and incident dementia was no longer significant (HR 0.99; 95% CI 0.94-1.04). CONCLUSIONS: In this real-world population the association between AF and dementia was no longer statistically significant when death was considered a competing risk.reservedmixedMarzona, Irene; Baviera, Marta; Vannini, Tommaso; Tettamanti, Mauro; Cortesi, Laura; Riva, Emma; Nobili, Alessandro; MARCON, Gabriella; Fortino, Ida; Bortolotti, Angela; Merlino, Luca; Roncaglioni, Maria CarlaMarzona, Irene; Baviera, Marta; Vannini, Tommaso; Tettamanti, Mauro; Cortesi, Laura; Riva, Emma; Nobili, Alessandro; Marcon, Gabriella; Fortino, Ida; Bortolotti, Angela; Merlino, Luca; Roncaglioni, Maria Carl

High-dose ivermectin for early treatment of COVID-19 (COVER study): a randomised, double-blind, multicentre, phase II, dose-finding, proof-of-concept clinical trial

: High concentrations of ivermectin demonstrated antiviral activity against SARS-CoV-2 in vitro. The aim of this study was to assess the safety and efficacy of high-dose ivermectin in reducing viral load in individuals with early SARS-CoV-2 infection. This was a randomised, double-blind, multicentre, phase II, dose-finding, proof-of-concept clinical trial. Participants were adults recently diagnosed with asymptomatic/oligosymptomatic SARS-CoV-2 infection. Exclusion criteria were: pregnant or lactating women; CNS disease; dialysis; severe medical condition with prognosis <6 months; warfarin treatment; and antiviral/chloroquine phosphate/hydroxychloroquine treatment. Participants were assigned (ratio 1:1:1) according to a randomised permuted block procedure to one of the following arms: placebo (arm A); single-dose ivermectin 600 μg/kg plus placebo for 5 days (arm B); and single-dose ivermectin 1200 μg/kg for 5 days (arm C). Primary outcomes were serious adverse drug reactions (SADRs) and change in viral load at Day 7. From 31 July 2020 to 26 May 2021, 32 participants were randomised to arm A, 29 to arm B and 32 to arm C. Recruitment was stopped on 10 June because of a dramatic drop in cases. The safety analysis included 89 participants and the change in viral load was calculated in 87 participants. No SADRs were registered. Mean (S.D.) log10 viral load reduction was 2.9 (1.6) in arm C, 2.5 (2.2) in arm B and 2.0 (2.1) in arm A, with no significant differences (P = 0.099 and 0.122 for C vs. A and B vs. A, respectively). High-dose ivermectin was safe but did not show efficacy to reduce viral load

Rationale and design of the CV-PREVITAL study: an Italian multiple cohort randomised controlled trial investigating innovative digital strategies in primary cardiovascular prevention

Introduction Prevention of cardiovascular disease (CVD) is of key importance in reducing morbidity, disability and mortality worldwide. Observational studies suggest that digital health interventions can be an effective strategy to reduce cardiovascular (CV) risk. However, evidence from large randomised clinical trials is lacking.Methods and analysis The CV-PREVITAL study is a multicentre, prospective, randomised, controlled, open-label interventional trial designed to compare the effectiveness of an educational and motivational mobile health (mHealth) intervention versus usual care in reducing CV risk. The intervention aims at improving diet, physical activity, sleep quality, psycho-behavioural aspects, as well as promoting smoking cessation and adherence to pharmacological treatment for CV risk factors. The trial aims to enrol approximately 80 000 subjects without overt CVDs referring to general practitioners' offices, community pharmacies or clinics of Scientific Institute for Research, Hospitalization and Health Care (Italian acronym IRCCS) affiliated with the Italian Cardiology Network. All participants are evaluated at baseline and after 12 months to assess the effectiveness of the intervention on short-term endpoints, namely improvement in CV risk score and reduction of major CV risk factors. Beyond the funded life of the study, a long-term (7 years) follow-up is also planned to assess the effectiveness of the intervention on the incidence of major adverse CV events. A series of ancillary studies designed to evaluate the effect of the mHealth intervention on additional risk biomarkers are also performed.Ethics and dissemination This study received ethics approval from the ethics committee of the coordinating centre (Monzino Cardiology Center; R1256/20-CCM 1319) and from all other relevant IRBs and ethics committees. Findings are disseminated through scientific meetings and peer-reviewed journals and via social media. Partners are informed about the study's course and findings through regular meetings