ORCID Profile
0000-0002-1472-9535
Current Organisations
University of Southampton
,
Universität des Saarlandes
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Publisher: European Centre for Disease Control and Prevention (ECDC)
Date: 27-10-2022
DOI: 10.2807/1560-7917.ES.2022.27.43.2101089
Abstract: Tracking person-to-person SARS-CoV-2 transmission in the population is important to understand the epidemiology of community transmission and may contribute to the containment of SARS-CoV-2. Neither contact tracing nor genomic surveillance alone, however, are typically sufficient to achieve this objective. We demonstrate the successful application of the integrated genomic surveillance (IGS) system of the German city of Düsseldorf for tracing SARS-CoV-2 transmission chains in the population as well as detecting and investigating travel-associated SARS-CoV-2 infection clusters. Genomic surveillance, phylogenetic analysis, and structured case interviews were integrated to elucidate two genetically defined clusters of SARS-CoV-2 isolates detected by IGS in Düsseldorf in July 2021. Cluster 1 (n = 67 Düsseldorf cases) and Cluster 2 (n = 36) were detected in a surveillance dataset of 518 high-quality SARS-CoV-2 genomes from Düsseldorf (53% of total cases, s led mid-June to July 2021). Cluster 1 could be traced back to a complex pattern of transmission in nightlife venues following a putative importation by a SARS-CoV-2-infected return traveller (IP) in late June 28 SARS-CoV-2 cases could be epidemiologically directly linked to IP. Supported by viral genome data from Spain, Cluster 2 was shown to represent multiple independent introduction events of a viral strain circulating in Catalonia and other European countries, followed by diffuse community transmission in Düsseldorf. IGS enabled high-resolution tracing of SARS-CoV-2 transmission in an internationally connected city during community transmission and provided infection chain-level evidence of the downstream propagation of travel-imported SARS-CoV-2 cases.
Publisher: Elsevier BV
Date: 08-2022
Publisher: Wiley
Date: 21-07-2022
DOI: 10.1111/RESP.14325
Abstract: Asthma and chronic obstructive pulmonary disease (COPD) are two prevalent and complex diseases that require personalized management. Although a strategy based on treatable traits (TTs) has been proposed, the prevalence and relationship of TTs to the diagnostic label and disease severity established by the attending physician in a real‐world setting are unknown. We assessed how the presence/absence of specific TTs relate to the diagnosis and severity of ‘asthma’, ‘COPD’ or ‘asthma + COPD’. The authors selected 30 frequently occurring TTs from the NOVELTY study cohort (NOVEL observational longiTudinal studY NCT02760329), a large ( n = 11,226), global study that systematically collects data in a real‐world setting, both in primary care clinics and specialized centres, for patients with ‘asthma’ ( n = 5932, 52.8%), ‘COPD’ ( n = 3898, 34.7%) or both (‘asthma + COPD’ n = 1396, 12.4%). The results indicate that (1) the prevalence of the 30 TTs evaluated varied widely, with a mean ± SD of 4.6 ± 2.6, 5.4 ± 2.6 and 6.4 ± 2.8 TTs atient in those with ‘asthma’, ‘COPD’ and ‘asthma + COPD’, respectively ( p 0.0001) (2) there were no large global geographical variations, but the prevalence of TTs was different in primary versus specialized clinics (3) several TTs were specific to the diagnosis and severity of disease, but many were not and (4) both the presence and absence of TTs formed a pattern that is recognized by clinicians to establish a diagnosis and grade its severity. These results provide the largest and most granular characterization of TTs in patients with airway diseases in a real‐world setting to date.
Publisher: Elsevier BV
Date: 08-2022
DOI: 10.1016/J.RMED.2022.106863
Abstract: Patients with mild asthma represent a substantial proportion of the population with asthma, yet there are limited data on their true burden of disease. We aimed to describe the clinical and healthcare resource utilisation (HCRU) burden of physician-assessed mild asthma. Patients with mild asthma were included from the NOVEL observational longiTudinal studY (NOVELTY NCT02760329), a global, 3-year, real-world prospective study of patients with asthma and/or chronic obstructive pulmonary disease from community practice (specialised and primary care). Diagnosis and severity were based on physician discretion. Clinical burden included physician-reported exacerbations and patient-reported measures. HCRU included inpatient and outpatient visits. Overall, 2004 patients with mild asthma were included 22.8% experienced ≥1 exacerbation in the previous 12 months, of whom 72.3% experienced ≥1 severe exacerbation. Of 625 exacerbations reported, 48.0% lasted >1 week, 27.7% were preceded by symptomatic worsening lasting >3 days, and 50.1% required oral corticosteroid treatment. Health status was moderately impacted (St George's Respiratory Questionnaire score: 23.5 [standard deviation ± 17.9]). At baseline, 29.7% of patients had asthma symptoms that were not well controlled or very poorly controlled (Asthma Control Test score <20), increasing to 55.6% for those with ≥2 exacerbations in the previous year. In terms of HCRU, at least one unscheduled ambulatory visit for exacerbations was required by 9.5% of patients, including 9.2% requiring ≥1 emergency department visit and 1.1% requiring ≥1 hospital admission. In this global s le representing community practice, a significant proportion of patients with physician-assessed mild asthma had considerable clinical burden and HCRU.
Publisher: Elsevier BV
Date: 09-2020
Publisher: Springer Science and Business Media LLC
Date: 26-05-2021
DOI: 10.1038/S41586-021-03583-3
Abstract: Fast and reliable detection of patients with severe and heterogeneous illnesses is a major goal of precision medicine 1,2 . Patients with leukaemia can be identified using machine learning on the basis of their blood transcriptomes 3 . However, there is an increasing ide between what is technically possible and what is allowed, because of privacy legislation 4,5 . Here, to facilitate the integration of any medical data from any data owner worldwide without violating privacy laws, we introduce Swarm Learning—a decentralized machine-learning approach that unites edge computing, blockchain-based peer-to-peer networking and coordination while maintaining confidentiality without the need for a central coordinator, thereby going beyond federated learning. To illustrate the feasibility of using Swarm Learning to develop disease classifiers using distributed data, we chose four use cases of heterogeneous diseases (COVID-19, tuberculosis, leukaemia and lung pathologies). With more than 16,400 blood transcriptomes derived from 127 clinical studies with non-uniform distributions of cases and controls and substantial study biases, as well as more than 95,000 chest X-ray images, we show that Swarm Learning classifiers outperform those developed at in idual sites. In addition, Swarm Learning completely fulfils local confidentiality regulations by design. We believe that this approach will notably accelerate the introduction of precision medicine.
Publisher: Cold Spring Harbor Laboratory
Date: 23-07-2021
DOI: 10.1101/2021.07.21.21260624
Abstract: Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended GWAS meta-analysis of a well-characterized cohort of 3,260 COVID-19 patients with respiratory failure and 12,483 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen (HLA) region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a highly pleiotropic ∼0.9-Mb inversion polymorphism and characterized the potential effects of the inversion in detail. Our data, together with the 5 th release of summary statistics from the COVID-19 Host Genetics Initiative, also identified a new locus at 19q13.33, including NAPSA , a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.
Publisher: Oxford University Press (OUP)
Date: 28-06-2021
DOI: 10.1093/CID/CIAB588
Abstract: Tracing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission chains is still a major challenge for public health authorities, when incidental contacts are not recalled or are not perceived as potential risk contacts. Viral sequencing can address key questions about SARS-CoV-2 evolution and may support reconstruction of viral transmission networks by integration of molecular epidemiology into classical contact tracing. In collaboration with local public health authorities, we set up an integrated system of genomic surveillance in an urban setting, combining a) viral surveillance sequencing, b) genetically based identification of infection clusters in the population, c) integration of public health authority contact tracing data, and d) a user-friendly dashboard application as a central data analysis platform. Application of the integrated system from August to December 2020 enabled a characterization of viral population structure, analysis of 4 outbreaks at a maximum care hospital, and genetically based identification of 5 putative population infection clusters, all of which were confirmed by contact tracing. The system contributed to the development of improved hospital infection control and prevention measures and enabled the identification of previously unrecognized transmission chains, involving a martial arts gym and establishing a link between the hospital to the local population. Integrated systems of genomic surveillance could contribute to the monitoring and, potentially, improved management of SARS-CoV-2 transmission in the population.
Publisher: Springer Science and Business Media LLC
Date: 08-04-2023
DOI: 10.1186/S12931-023-02394-6
Abstract: No short patient-reported outcome (PRO) instruments assess overall health status across different obstructive lung diseases. Thus, the wording of the introduction to the Chronic Obstructive Pulmonary Disease (COPD) Assessment Test (CAT) was modified to permit use in asthma and/or COPD. This tool is called the Chronic Airways Assessment Test (CAAT). The psychometric properties of the CAAT were evaluated using baseline data from the NOVELTY study (NCT02760329) in patients with physician-assigned asthma, asthma + COPD or COPD. Analyses included exploratory/confirmatory factor analyses, differential item functioning and analysis of construct validity. Responses to the CAAT and CAT were compared in patients with asthma + COPD and those with COPD. CAAT items were internally consistent (Cronbach’s alpha: 0.7) within each diagnostic group (n = 510). Models for structural and measurement invariance were strong. Tests of differential item functioning showed small differences between asthma and COPD in in idual items, but these were not consistent in direction and had minimal overall impact on the total score. The CAAT and CAT were highly consistent when assessed in all NOVELTY patients who completed both (N = 277, Pearson’s correlation coefficient: 0.90). Like the CAT itself, CAAT scores correlated moderately (0.4–0.7) to strongly ( 0.7) with other PRO measures and weakly ( 0.4) with spirometry measures. CAAT scores appear to reflect the same health impairment across asthma and COPD, making the CAAT an appropriate PRO instrument for patients with asthma and/or COPD. Its brevity makes it suitable for use in clinical studies and routine clinical practice. Trial registration : NCT02760329.
Publisher: Oxford University Press (OUP)
Date: 15-07-2022
DOI: 10.1093/HMG/DDAC158
Abstract: Given the highly variable clinical phenotype of Coronavirus disease 2019 (COVID-19), a deeper analysis of the host genetic contribution to severe COVID-19 is important to improve our understanding of underlying disease mechanisms. Here, we describe an extended genome-wide association meta-analysis of a well-characterized cohort of 3255 COVID-19 patients with respiratory failure and 12 488 population controls from Italy, Spain, Norway and Germany/Austria, including stratified analyses based on age, sex and disease severity, as well as targeted analyses of chromosome Y haplotypes, the human leukocyte antigen region and the SARS-CoV-2 peptidome. By inversion imputation, we traced a reported association at 17q21.31 to a ~0.9-Mb inversion polymorphism that creates two highly differentiated haplotypes and characterized the potential effects of the inversion in detail. Our data, together with the 5th release of summary statistics from the COVID-19 Host Genetics Initiative including non-Caucasian in iduals, also identified a new locus at 19q13.33, including NAPSA, a gene which is expressed primarily in alveolar cells responsible for gas exchange in the lung.
Publisher: Cold Spring Harbor Laboratory
Date: 06-2023
DOI: 10.1101/2023.05.31.542897
Abstract: To perform most behaviors, animals must send commands from higher-order processing centers in the brain to premotor circuits that reside in ganglia distinct from the brain, such as the mammalian spinal cord or insect ventral nerve cord. How these circuits are functionally organized to generate the great ersity of animal behavior remains unclear. An important first step in unraveling the organization of premotor circuits is to identify their constituent cell types and create tools to monitor and manipulate these with high specificity to assess their function. This is possible in the tractable ventral nerve cord of the fly. To generate such a toolkit, we used a combinatorial genetic technique (split-GAL4) to create 195 sparse driver lines targeting 198 in idual cell types in the ventral nerve cord. These included wing and haltere motoneurons, modulatory neurons, and interneurons. Using a combination of behavioral, developmental, and anatomical analyses, we systematically characterized the cell types targeted in our collection. Taken together, the resources and results presented here form a powerful toolkit for future investigations of neural circuits and connectivity of premotor circuits while linking them to behavioral outputs.
Publisher: Springer Science and Business Media LLC
Date: 08-07-2021
DOI: 10.1038/S41586-021-03767-X
Abstract: The genetic make-up of an in idual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-19 1,2 , host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases 3–7 . They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.
Publisher: Elsevier BV
Date: 11-2021
Publisher: MDPI AG
Date: 05-07-2022
Abstract: Chronic obstructive pulmonary disease (COPD) is a disease with an inflammatory phenotype with increasing prevalence in the elderly. Expanded population of mutant blood cells carrying somatic mutations is termed clonal hematopoiesis of indeterminate potential (CHIP). The association between CHIP and COPD and its relevant effects on DNA methylation in aging are mainly unknown. Analyzing the deep-targeted licon sequencing from 125 COPD patients, we found enhanced incidence of CHIP mutations (~20%) with a predominance of DNMT3A CHIP-mediated hypomethylation of Phospholipase D Family Member 5 (PLD5), which in turn is positively correlated with increased levels of glycerol phosphocholine, pro-inflammatory cytokines, and deteriorating lung function.
Publisher: Springer Science and Business Media LLC
Date: 10-12-2021
DOI: 10.1007/S00439-021-02397-7
Abstract: The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive in iduals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Robert Bals.