Pharmacogenomics in asthma treatment

Med posamezniki obstajajo velike razlike v učinku protiastmatične terapije, ki so pogojene predvsem z različnim genetskim zapisom. Namen farmakogenomike je poiskati tiste polimorfizme, ki so povezani z vsemi učinki določenega zdravila. Farmakogenomika pri astmi zaenkrat proučuje predvsem vpliv genov, ki kodirajo receptorje za zdravila, komponente postreceptorske signalne transdukcije in transkripcijske dejavnike. Največ raziskav je bilo narejenih na področju farmakogenomike beta2 agonistov. Mutacija Arg/Arg na mestu 16 gena ADRB2, ter mutacije v genih LTC4S, ALOX5 in CRHR1 spremenijo odziv na protiastmatično terapijo. Cilj farmakogenomike astme pa je poiskati čimbolj učinkovito protiastmatično zdravilo z čimmanj stranskimi učinki individualno za vsakega posameznika na podlagi njegovega genotipa.There are substantial differences in the effect of antiasthmatic therapy between individuals which are dependent on the diversity of the genetic code. The purpose of pharmacogenomics is to find out those polymorphisms, which are connected with all effects of certain drug. For now the pharmacogenomics of asthma above all study the influence of the genes which code for drug receptors, signal transduction components and transcription factors. Most studies were done in the field of pharmacogenomics of beta2 agonists. Gene mutations that are known to alter the response to asthma therapy include Arg/Arg at position 16 in ADRB2 gene, mutations of LTC4S and ALOX5 and CRHR1 variants. The goal of pharmacogenomics is to find out most efficient drug without adverse side effects individually suited for each patient on basis of his genotype

Computer aided method for colour calibration and analysis of digital rock photographs

The methods used in geology to determine colour and colour coverage are expensive, time consuming, and/ or subjective. Estimates of colour coverage can only be approximate since they are based on rough comparison- based measuring etalons and subjective estimation, which is dependent upon the skill and experience of the person performing the estimation. We present a method which accelerates, simpli es, and objecti es these tasks using a computer application. It automatically calibrates the colours of a digital photo, and enables the user to read colour values and coverage, even after returning from eld work. Colour identi cation is based on the Munsell colour system. For the purposes of colour calibration we use the X-Rite ColorChecker Passport colour chart placed onto the photographed scene. Our computer application detects the ColorChecker colour chart, and nds a colour space transformation to calibrate the colour in the photo. The user can then use the application to read colours within selected points or regions of the photo. The results of the computerised colour calibration were compared to the reference values of the ColorChecker chart. The values slightly deviate from the exact values, but the deviation is around the limit of human capability for visual comparison. We have devised an experiment, which compares the precision of the computerised colour analysis and manual colour analysis performed on a variety of rock samples with the help of geology students using Munsell Rock-color Chart. The analysis showed that the precision of manual comparative identi cation on multi- coloured samples is somewhat problematic, since the choice of representative colours and observation points for a certain part of a sample are subjective. The computer based method has the edge in veri ability and repeatability of the analysis since the application the original photo to be saved with colour calibration, and tagging of colour- analysed points and regions

Understanding disparities in Slovenian rural areas: various new indicatiors

It has been widely accepted that regional development disparities are multi-faceted: on the one hand they hinder the development potentials of structurally weak rural areas, whilst on the other they stimulate faster development in distinctive, leading areas, thus re-creating old and generating new, more complex, regional differences. The paper focuses on quantitative ways of understanding the nature of rural disparities in Slovenia where the vast majority of national territory is defined as "rural" by OECD indicators. From the methodological perspective, single- and multi-level indicators were observed at the municipal level (LAU-2). Various indicators have been developed, with several looking at new generators of difference as well as indicators tailored to examine development disparities present in Slovenian rural areas. The results gained by extensive quantitative analysis could be used as scientific starting points that could inform rural policy decision makers in various rural regions. The focus on new indicators is particularly important as it highlights the challenges of such research whilst stressing the critical need for continued research into new generators and forms of disparities that may have negative consequences on rural areas, as well as possibly providing opportunities for previously problematic rural areas to address long-term development troubles

Exploration of Pharmacogenomic Biomarkers in Chronic Immune Diseases Using Single-Cell RNA Sequencing

Biological therapies have revolutionized management of the severe cases of Chronic Immune Diseases refractory to the standard therapies. However, many patients do not respond to the selected biological therapy, loose response over time, or develop adverse effects. A personalized approach to treatment of these patients, based on reliable biomarkers is thus clearly needed. Non-invasive approaches, such as use of the peripheral blood immune cells, are favored for novel biomarker discovery. However, the attention has shifted away from the bulk immune cells and towards specific immune cell sub-populations. Thus, the single-cell RNA sequencing (scRNA-seq) can prove highly valuable. By simultaneously capturing and profiling all the cells in a sample, scRNA-seq allows the analysis of cellular heterogeneity and gene expression in all immune cell sub-populations, targeted or adversely affected by the biological treatment. In our ongoing research, scRNA-seq was utilized to analyze samples from Inflammatory Bowel Disease and Childhood Asthma patients with varied response to the biological therapy. Confounding effects of disease conditions and (biological) therapies on marker genes were eliminated using computational integration in order to identify conserved marker genes across all states. It turned out, that a reliable identification of the different immune cell sub-populations in this setting is quite challenging due to subjective cell-landscape clustering resolution. Several resolutions and automated annotation approaches were subsequently tested and validated.A reference-based approach (Seurat-Azimuth) combined with manual cluster validation proved superior. Alas, manual cluster validation is time consuming. Annotation validation is important, especially to provide additional insights into unidentified clusters, which are essential for the identification of predictive biomarkers for personalized therapies in the vast heterogeneity of immune cell landscapes residing behind pathophysiology of chronic immune diseases.Book of abstract: 4th Belgrade Bioinformatics Conference, June 19-23, 202

Medication use in uncontrolled pediatric asthma:Results from the SysPharmPediA study

Background: Uncontrolled pediatric asthma has a large impact on patients and their caregivers. More insight into determinants of uncontrolled asthma is needed. We aim to compare treatment regimens, inhaler techniques, medication adherence and other characteristics of children with controlled and uncontrolled asthma in the: Systems Pharmacology approach to uncontrolled Paediatric Asthma (SysPharmPediA) study. Material and methods: 145 children with moderate to severe doctor-diagnosed asthma (91 uncontrolled and 54 controlled) aged 6–17 years were enrolled in this multicountry, (Germany, Slovenia, Spain, and the Netherlands) observational, case-control study. The definition of uncontrolled asthma was based on asthma symptoms and/or exacerbations in the past year. Patient-reported adherence and clinician-reported medication use were assessed, as well as lung function and inhalation technique. A logistic regression model was fitted to assess determinants of uncontrolled pediatric asthma. Results: Children in higher asthma treatment steps had a higher risk of uncontrolled asthma (OR (95%CI): 3.30 (1.56–7.19)). The risk of uncontrolled asthma was associated with a larger change in FEV1% predicted post and pre-salbutamol (OR (95%CI): 1.08 (1.02–1.15)). Adherence and inhaler techniques were not associated with risk of uncontrolled asthma in this population. Conclusion: This study showed that children with uncontrolled moderate-to-severe asthma were treated in higher treatment steps compared to their controlled peers, but still showed a higher reversibility response to salbutamol. Self-reported adherence and inhaler technique scores did not differ between controlled and uncontrolled asthmatic children. Other determinants, such as environmental factors and differences in biological profiles, may influence the risk of uncontrolled asthma in this moderate to severe asthmatic population

Genome-wide association study of inhaled corticosteroid response in admixed children with asthma

Background Inhaled corticosteroids (ICS) are the most widely prescribed and effective medication to control asthma symptoms and exacerbations. However, many children still have asthma exacerbations despite treatment, particularly in admixed populations, such as Puerto Ricans and African Americans. A few genome‐wide association studies (GWAS) have been performed in European and Asian populations, and they have demonstrated the importance of the genetic component in ICS response. Objective We aimed to identify genetic variants associated with asthma exacerbations in admixed children treated with ICS and to validate previous GWAS findings. Methods A meta‐analysis of two GWAS of asthma exacerbations was performed in 1347 admixed children treated with ICS (Hispanics/Latinos and African Americans), analysing 8.7 million genetic variants. Those with P ≤ 5 × 10−6 were followed up for replication in 1697 asthmatic patients from six European studies. Associations of ICS response described in published GWAS were followed up for replication in the admixed populations. Results A total of 15 independent variants were suggestively associated with asthma exacerbations in admixed populations (P ≤ 5 × 10−6). One of them, located in the intergenic region of APOBEC3B and APOBEC3C, showed evidence of replication in Europeans (rs5995653, P = 7.52 × 10−3) and was also associated with change in lung function after treatment with ICS (P = 4.91 × 10−3). Additionally, the reported association of the L3MBTL4‐ARHGAP28 genomic region was confirmed in admixed populations, although a different variant was identified. Conclusions and clinical relevance This study revealed the novel association of APOBEC3B and APOBEC3C with asthma exacerbations in children treated with ICS and replicated previously identified genomic regions. This contributes to the current knowledge about the multiple genetic markers determining responsiveness to ICS which could lead in the future the clinical identification of those asthma patients who are not able to respond to such treatment

Pharmacogenomic associations of adverse drug reactions in asthma: systematic review and research prioritisation

A systematic review of pharmacogenomic studies capturing adverse drug reactions (ADRs) related to asthma medications was undertaken, and a survey of Pharmacogenomics in Childhood Asthma (PiCA) consortia members was conducted. Studies were eligible if genetic polymorphisms were compared with suspected ADR(s) in a patient with asthma, as either a primary or secondary outcome. Five studies met the inclusion criteria. The ADRs and polymorphisms identified were change in lung function tests (rs1042713), adrenal suppression (rs591118), and decreased bone mineral density (rs6461639) and accretion (rs9896933, rs2074439). Two of these polymorphisms were replicated within the paper, but none had external replication. Priorities from PiCA consortia members (representing 15 institution in eight countries) for future studies were tachycardia (SABA/LABA), adrenal suppression/crisis and growth suppression (corticosteroids), sleep/behaviour disturbances (leukotriene receptor antagonists), and nausea and vomiting (theophylline). Future pharmacogenomic studies in asthma should collect relevant ADR data as well as markers of efficacy

Classifying asthma control using salivary and fecal bacterial microbiome in children with moderate-to-severe asthma

Background: Uncontrolled asthma can lead to severe exacerbations and reduced quality of life. Research has shown that the microbiome may be linked with asthma characteristics; however, its association with asthma control has not been explored. We aimed to investigate whether the gastrointestinal microbiome can be used to discriminate between uncontrolled and controlled asthma in children. Methods: 143 and 103 feces samples were obtained from 143 children with moderate-to-severe asthma aged 6 to 17 years from the SysPharmPediA study. Patients were classified as controlled or uncontrolled asthmatics, and their microbiome at species level was compared using global (alpha/beta) diversity, conventional differential abundance analysis (DAA, analysis of compositions of microbiomes with bias correction), and machine learning [Recursive Ensemble Feature Selection (REFS)]. Results: Global diversity and DAA did not find significant differences between controlled and uncontrolled pediatric asthmatics. REFS detected a set of taxa, including Haemophilus and Veillonella, differentiating uncontrolled and controlled asthma with an average classification accuracy of 81% (saliva) and 86% (feces). These taxa showed enrichment in taxa previously associated with inflammatory diseases for both sampling compartments, and with COPD for the saliva samples. Conclusion: Controlled and uncontrolled children with asthma can be differentiated based on their gastrointestinal microbiome using machine learning, specifically REFS. Our results show an association between asthma control and the gastrointestinal microbiome. This suggests that the gastrointestinal microbiome may be a potential biomarker for treatment responsiveness and thereby help to improve asthma control in children