Biology subjects

Bender, A.

Publications and source records attributed to Bender, A..

44 records · Page 3Linked to original sources

bioRxiv2020

Systematic analysis of protein targets associated with adverse events of drugs from clinical trials and post-marketing reports

Adverse drug reactions (ADRs) are undesired effects of medicines that can harm patients and are a significant source of attrition in drug development. ADRs are anticipated by routinely screening drugs against secondary pharmacology protein panels. However, there is still a lack of quantitative information on the links between these off-target proteins and the risk of ADRs in humans. Here, we present a systematic analysis of associations between measured and predicted in vitro bioactivities of drugs, and adverse events (AEs) in humans from two sources of data: the Side Effect Resource (SIDER), derived from clinical trials, and the Food and Drug Administration Adverse Event Reporting System (FAERS), derived from post-marketing surveillance. The ratio of a drug’s in vitro potency against a given protein relative to its therapeutic unbound drug plasma concentration was used to select proteins most likely to be relevant to in vivo effects. In examining individual target bioactivities as predictors of AEs, we found a trade-off between the Positive Predictive Value and the fraction of drugs with AEs that can be detected, however considering sets of multiple targets for the same AE can help identify a greater fraction of AE-associated drugs. Of the 45 targets with statistically significant associations to AEs, 30 are included on existing safety target panels. The remaining 15 targets include 8 carbonic anhydrases, of which CA5B was significantly associated with cholestatic jaundice. We include the full quantitative data on associations between in vitro bioactivities and AEs in humans in this work, which can be used to make a more informed selection of safety profiling targets.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pharmacology and toxicology↗

bioRxiv2019

Modelling geospatial distributions of the triatomine vectors of Trypanosoma cruzi in Latin America

Approximately 150 triatomine species are known to be infected with the Chagas parasite, Trypanosoma cruzi, but they differ in the risk they pose to human populations. The largest risk comes from species that have a domestic life cycle and these species have been targeted by indoor residual spraying campaigns, which have been successful in many locations. It is now important to consider residual transmission that may be linked to persistent populations of dominant vectors, or to secondary or minor vectors. The aim of this project was to define the geographical distributions of the community of triatomine species in Latin America. Presence-only data with over 12, 000 observations of triatomine vectors were extracted from a public database and target-group background data were generated to account for sampling bias in the presence data. Geostatistical regression was then applied to estimate species distributions and fine-scale distribution maps were generated for thirty triatomine vector species. The results for Panstrongylus geniculatus, P. megistus, Triatoma barberi, T. brasiliensis, and T. pseudomaculata are presented in detail and the model validation results for each of the 30 species are presented in full. The predictive maps for all species are made publicly available so that they can be used to assess the communities of vectors present within different regions of the endemic zone. The maps are presented alongside key indicators for the capacity of each species to transmit T. cruzi to humans. These indicators include infection prevalence, evidence for human blood meals, and colonisation or invasion of homes. A summary of these indicators shows that the majority of the 30 species mapped by this study have the potential to transmit T. cruzi to humans.\n\nAuthor summaryThe Pan American Health Organisations Strategy and Plan of Action for Chagas Disease Prevention, Control and Care highlights the importance of eliminating those triatomine vector species that colonise homes, and has had great success in many locations. Since indoor residual spraying campaigns have targeted these species, their importance relative to other vectors has diminished and their geographical distributions may also have changed. It is now vital to consider the full community of vector species, including previously dominant vectors as well as secondary or minor vector species, in order to target residual transmission to humans. Our aim was to define the geographical distributions of the most commonly reported triatomine species in Latin America. We extracted reports of triatomine vector species observed at specific locations from a public database and we used a geostatistical model to generate fine-scale predictive maps for thirty triatomine vector species. We present these maps alongside a summary of key indicators related to the capacity of each species to transmit the Chagas parasite to humans. We show that most of the 30 species that we have mapped pose a potential threat to human populations.

ecology↗

bioRxiv2019

A systems genomics approach to uncover patient-specific pathogenic pathways in a complex disease

We describe a novel precision medicine workflow, the integrated single nucleotide polymorphism network platform (iSNP), designed to identify the exact mechanisms of how SNPs affect cellular regulatory networks, and how SNP co-occurrences contribute to disease pathogenesis in ulcerative colitis (UC). Using SNP profiles of 377 UC patients, we mapped the regulatory effects of the SNPs to a human signalling network containing protein-protein, miRNA-mRNA and transcription factor binding interactions. Unsupervised clustering algorithms grouped these patient-specific networks into four distinct clusters based on two large disease hubs, NFKB1 and PKCB. Pathway analysis identified the epigenetic modification as common and the T-cell specific responses as differing signalling pathways in the clusters. By integrating individual transcriptomes in active and quiescent disease setting to the patient networks, we validated the impact of non-coding SNPs. The iSNP approach identified regulatory effects of disease-associated non-coding SNPs, and identified how pathogenesis pathways are activated via different genetic modifications.

bioinformatics↗

bioRxiv2019

Does Sex Modify an Association of Electrophysiological Substrate with Sudden Cardiac Death? The Atherosclerosis Risk in Communities (ARIC) Study

BackgroundSex is a well-recognized risk factor for sudden cardiac death (SCD). Sex differences in electrophysiological (EP) substrate of SCD are known. However, it remains unknown whether sex can modify an association of EP substrate with SCD.\n\nMethodsParticipants from the Atherosclerosis Risk in Communities study with analyzable ECGs (n=14,725; age, 54.2{+/-}5.8 yrs; 55% female, 74% white) were included. EP substrate was characterized by traditional 12-lead ECG (heart rate, QRS, QTc, Cornell voltage), spatial ventricular gradient (SVG) and sum absolute QRST integral (SAI QRST) metrics. Two competing outcomes were adjudicated SCD and nonSCD. Interaction of ECG metrics with sex was studied in Cox proportional hazards and Fine-Gray competing risk models. Relative hazard ratio (RHR) and relative sub-hazard ratio (RSHR) with a 95% confidence interval for SCD and nonSCD risk for women relative to men were calculated. Model 1 was adjusted for prevalent cardiovascular disease (CVD) and risk factors. Time-updated model 2 was additionally adjusted for incident non-fatal CVD.\n\nResultsOver a median follow-up of 24.4 years, there were 530 SCDs (incidence 1.72 (1.58-1.88)/1000 person-years) and 2,178 nonSCDs (incidence 7.09; (6.80-7.39)/ 1000 person-years). Women experienced a greater than men risk of SCD associated with Cornell voltage (RHR 1.18(1.06-1.32); P=0.003), SAI QRST (RHR 1.16(1.04-1.30); P=0.007), area SVG magnitude (RHR 1.24(1.05-1.45); P=0.009), and peak SVG magnitude (RHR 1.22(1.04-1.44); P=0.018), independently from incident CVD. Greater risk of SCD for women than men associated with QRS duration (RHR 1.24(1.07-1.44); P=0.004) and QTc (RSHR 1.15(1.02-1.30); P=0.025) was explained by incident CVD. Furthermore, women had greater odds of SCD associated with heart rate (RSHR 1.19(1.01-1.40); P=0.036), independently of incident CVD.\n\nConclusionsSex modifies an association of EP substrate with SCD. In women, global EP substrate is associated with up to 27% greater risk of SCD than in men. Development of sex-specific risk scores of SCD is necessary. Further studies of mechanisms behind sex differences in EP substrate of SCD are warranted.

epidemiology↗

bioRxiv2019

Dynamic Predictive Accuracy of Electrocardiographic Biomarkers of Sudden Cardiac Death within a Survival Framework: The Atherosclerosis Risk in Communities (ARIC) study

BackgroundThe risk of sudden cardiac death (SCD) is known to be dynamic. However, an accuracy of a dynamic SCD prediction, and \"expiration date\" of ECG biomarkers is unknown. Our goal was to measure dynamic predictive accuracy of ECG biomarkers of SCD and competing outcomes.\n\nMethodsAtherosclerosis Risk In Community study participants with analyzable digital ECGs were included (n=15,768; 55% female, 73% white, age 54.2{+/-}5.8 y). ECGs of 5 follow-up visits were analyzed. Global electrical heterogeneity (GEH) and traditional ECG metrics were measured. Adjudicated SCD served as the primary outcome; non-sudden cardiac death served as competing outcome. Time-dependent area under the (receiver operating characteristic) curve (AUC) analysis was performed to assess prediction accuracy of a continuous biomarker in a period of 3,6,9 months, and 1,2,3,5,10, and 15 years, using survival analysis framework.\n\nResultsOver a median 24.4 y follow-up, there were 581 SCDs (incidence 1.77 (95%CI 1.63-1.92)/1,000 person-years), and 838 nonSCDs [2.55 (95%CI 2.39-2.73)]. Resting heart rate was the strongest (AUC 0.930) short-term (3-month) non-specific SCD predictor, whereas spatial peak QRS-T angle predicted specifically SCD 15 years after ECG recording (AUC 0.719). QRS duration (AUC 0.885) and QTc (AUC 0.711) short-term predicted advanced structural heart disease better than SCD. \"Expiration date\" for most ECG biomarkers was two years after ECG recording. GEH significantly improved reclassification of SCD risk beyond age, sex, race, diabetes, hypertension, coronary heart disease and stroke.\n\nConclusionShort-term predictors of SCD, nonSCD, and biomarkers of long-term SCD risk differed, reflecting differences in transient vs. persistent SCD substrates.

epidemiology↗

bioRxiv2019

The Trouble Interpreting fMRI Studies in Populations with Cerebrovascular Risk: The Use of a Subject-Specific Hemodynamic Response Function in a Study of Age, Vascular Risk, and Memory

Functional magnetic resonance imaging (fMRI) is commonly used to investigate the neural bases of behavior ranging from basic cognitive mechanisms to aging to psychological disorders. However, the BOLD signal captured by fMRI is an indirect measure of neural function and is affected by many factors that are non-neural in origin. These non-neural factors, however, do affect brain vasculature such as the shape and timing of the hemodynamic response function (HRF) during task-evoked fMRI that, in turn, can cause inappropriate and/or misleading interpretations of fMRI differences between groups. In this study, we tested the proposition that vascular health risks, which often go unmeasured in neuroimaging studies, and aging interact to modify the shape and/or timing of the HRF (height, time-to-peak, width), which then affect the differences in patterns of brain activity in a task-evoked memory encoding paradigm. Adult participants (aged 20-74) answered questions about their health history and underwent two fMRI tasks: viewing of a flashing checkerboard using a slow event-related design and a paired associates memory encoding task during a fast event-related design. We found that aging and vascular risk had the largest impacts on the maximum peak value of the HRF. Using a subject-specific HRF resulted in an overall dampening of the estimated brain activity in both task-positive and task-negative regions due to a reduction in the inter-individual variance of that activity. Across three vascular risk factors, using a subject-specific HRF resulted in more consistent brain regions that reached significance and larger effect sizes compared with the canonical HRF. A slight advantage in the reliability of brain-behavior correlations also was found. The findings from this study have far reaching consequences for the interpretation of task-evoked fMRI activity, especially in populations known to experience alterations to brain vasculature including adults of all ages that have higher vascular risk, the majority of older adults, and people with neurocognitive disorders in which vasculature differences may play a role including dementia.\n\nHighlightsO_LIOlder age was associated with smaller maximum peak of the hemodynamic response.\nC_LIO_LIYounger and middle-aged adults with more vascular risk had higher HRF peaks.\nC_LIO_LIUsing a subject-specific HRF resulted in a \"dampening\" of brain activity.\nC_LIO_LIA subject-specific HRF resulted in more consistent aging and vascular risk effects.\nC_LI

neuroscience↗

bioRxiv2018

Distinct oncogenes drive distinct genome and epigenome alterations in human mammary epithelial cells

Gene expression differences, combined with distinct patterns of genomic rearrangements and epigenetic modifications, have laid the bases of molecular classification of breast cancer. Different molecular subtypes are thought to originate from different cell lineages in the mammary gland, but the early activation of an oncogene could also play a role. It is, however, difficult to discriminate the respective inputs of oncogene activation or cell type of origin in the natural history of the tumor. In this work, we have designed an experimental strategy aiming at determining whether activation of distinct oncogenic pathways in human mammary epithelial cells (HMEC) could lead to different patterns of genetic and epigenetic changes. We show that initial activation of CCNE1, WNT1 and RASv12, which activate distinct oncogenic pathways, in shp53 immortalized HMECs results in different and reproducible profiles of mRNA and miRNA expression, copy number alterations (CNA) and DNA methylation modifications. Noticeably, HMECs transformed by RAS bore very specific profiles of CNAs and DNA methylation, clearly distinct from those shown by CCNE1 and WNT1 transformed HMECs.\n\nGenes impacted by CNAs and CpG methylation in the RAS and the CCNE1/WNT1 clusters showed clear differences, illustrating the activation of distinct pathways. Our data show that early activation of distinct oncogenic pathways leads to active adaptive events resulting in specific sets of CNAs and DNA methylation changes. We, thus, propose that activation of different oncogenes could have a role in reshaping the genetic landscape of breast cancer subtypes.\n\nAuthor summaryGenetic and epigenetic changes are at the center of cancer development. Breast cancer molecular subtypes are defined on differences in genetic and epigenetic profiles and it is generally assumed these subtypes originate from different cell lineages in the mammary gland. We propose that founding oncogenic mutations could also have an impact. To address this question, we designed an experimental model, based on the ectopic expression of different oncogenes in human mammary epithelial cells (HMEC), and monitored genetic and DNA methylation changes occurring at different stages of cell transformation. We show that transformation of HMEC by distinct oncogenes resulted in clearly different and reproducible patterns of genetic and DNA methylation changes. Genes whose expression was modified by either CNAs or CpG methylation were consistent with the dominant pathways activated and reflected the phenotypes in the respective models. We propose that DNA methylation and CNA changes correspond to adaptive responses to the activation of the oncogenic pathways. Our data strongly suggest that early activation of distinct oncogenic insults will not only impinge on the phenotypic characteristics of the resulting tumors, but also have a strong impact on their genomic and epigenetic landscapes.

cancer biology↗

bioRxiv2017

Cancer Cell Line Profiler (CCLP): a webserver for the prediction of compound activity across the NCI60 panel

SummaryCCLP (Cancer Cell Line Profiler) is a webserver for the prediction of compound activity across the NCI60 panel. CCLP uses a multi-task Random Forest model trained on 941,831 data-points that integrates structural information from 17,142 compounds and multi-omics data sets from 59 cancer cell lines. In addition, CCLP also implements conformal prediction to provide individual prediction errors at several confidence levels. CCLP computes compound descriptors for a set of input molecules and predicts their activity across the NCI60 panel. The output of running CCLP consists of one barplot per input compound displaying the predicted activities and errors across the NCI60 panel, as well as a text file reporting the predicted activities and errors in prediction\n\nAvailabilityCCLP is freely available on the web at cclp.marseille.inserm.fr

bioinformatics↗