The interplay of type I and type II interferons in murine autoimmune cholangitis as a basis for sex-biased autoimmunity

We have reported on a murine model of autoimmune cholangitis, generated by altering the AU-rich element (ARE) by deletion of the interferon gamma (IFN-γ) 3\u27 untranslated region (coined ARE-Del−/−), that has striking similarities to human primary biliary cholangitis (PBC) with female predominance. Previously, we suggested that the sex bias of autoimmune cholangitis was secondary to intense and sustained type I and II IFN signaling. Based on this thesis, and to define the mechanisms that lead to portal inflammation, we specifically addressed the hypothesis that type I IFNs are the driver of this disease. To accomplish these goals, we crossed ARE-Del−/− mice with IFN type I receptor alpha chain (Ifnar1) knockout mice. We report herein that loss of type I IFN receptor signaling in the double construct of ARE-Del−/− Ifnar1−/− mice dramatically reduces liver pathology and abrogated sex bias. More importantly, female ARE-Del−/− mice have an increased number of germinal center (GC) B cells as well as abnormal follicular formation, sites which have been implicated in loss of tolerance. Deletion of type I IFN signaling in ARE-Del−/− Ifnar1−/− mice corrects these GC abnormalities, including abnormal follicular structure. Conclusion: Our data implicate type I IFN signaling as a necessary component of the sex bias of this murine model of autoimmune cholangitis. Importantly these data suggest that drugs that target the type I IFN signaling pathway would have potential benefit in the earlier stages of PBC. (Hepatology 2018;67:1408-1419)

Building an International One Health Strain Level Database to Characterise the Epidemiology of AMR Threats: ESBL—AmpC Producing E. coli as An Example—Challenges and Perspectives

(This article belongs to the Special Issue Epidemiology of ESBL-Producing Enterobacteriaceae)Antimicrobial resistance (AMR) is one of the top public health threats nowadays. Among the most important AMR pathogens, Escherichia coli resistant to extended spectrum cephalosporins (ESC-EC) is a perfect example of the One Health problem due to its global distribution in animal, human, and environmental sources and its resistant phenotype, derived from the carriage of plasmid-borne extended-spectrum and AmpC β-lactamases, which limits the choice of effective antimicrobial therapies. The epidemiology of ESC-EC infection is complex as a result of the multiple possible sources involved in its transmission, and its study would require databases ideally comprising information from animal (livestock, companion, wildlife), human, and environmental sources. Here, we present the steps taken to assemble a database with phenotypic and genetic information on 10,763 ESC-EC isolates retrieved from multiple sources provided by 13 partners located in eight European countries, in the frame of the DiSCoVeR Joint Research project funded by the One Health European Joint Programme (OH-EJP), along with its strengths and limitations. This database represents a first step to help in the assessment of different geographical and temporal trends and transmission dynamics in animals and humans. The work performed highlights aspects that should be considered in future international efforts, such as the one presented here.This research was funded by Promoting One Health in Europe through joint actions on foodborne zoonoses, antimicrobial resistance, and emerging microbiological hazards–One Health EJP, grant number 773830 (DiSCoVeR). Research at the German Federal Institute for Risk Assessment, Germany, was partially supported by the internal project BfR-BIOS-08-43-001. Research at the National Institute for Agrarian and Veterinary Research (INIAV) was partially supported by the project PTDC/CVT-CVT/28469/2017 financed by the “Fundação para a Ciência e Tecnologia” (FCT), Portugal. Research at the National Veterinary Research Institute (PIWet), Poland, was also partially supported by the Polish Ministry of Education and Science from the funds for science in the years 2018–2022 allocated for the implementation of a co-financed international project. The environmental isolates from Ireland were collected as part of the AREST project, which is jointly funded by the Environmental Protection Agency, under the EPA Research Programme 2014–2020, and the Health Service Executive (2017-HW-LS-1). The isolates collected from pig farms in Ireland were collected as part of a Walsh Scholarship project funded by Teagasc (ref 2018027). Research at the VISAVET Health Surveillance Centre (Spain) was partially supported by the project Antimicrobial resistance transmission dynamics in the human-animal interface: Shaping the risk posed by epidemic plasmids (PID2021-125136OB-I00, Ministerio de Ciencia, Innovación y Universidades, MICINN).info:eu-repo/semantics/publishedVersio

ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors

Assessing associations between the AURKAHMMR-TPX2-TUBG1 functional module and breast cancer risk in BRCA1/2 mutation carriers

While interplay between BRCA1 and AURKA-RHAMM-TPX2-TUBG1 regulates mammary epithelial polarization, common genetic variation in HMMR (gene product RHAMM) may be associated with risk of breast cancer in BRCA1 mutation carriers. Following on these observations, we further assessed the link between the AURKA-HMMR-TPX2-TUBG1 functional module and risk of breast cancer in BRCA1 or BRCA2 mutation carriers. Forty-one single nucleotide polymorphisms (SNPs) were genotyped in 15,252 BRCA1 and 8,211 BRCA2 mutation carriers and subsequently analyzed using a retrospective likelihood appr

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling. © 2018 The Author(s).Peer reviewe