A logic-based diagram of signalling pathways central to macrophage activation.

BACKGROUND: The complex yet flexible cellular response to pathogens is orchestrated by the interaction of multiple signalling and metabolic pathways. The molecular regulation of this response has been studied in great detail but comprehensive and unambiguous diagrams describing these events are generally unavailable. Four key signalling cascades triggered early-on in the innate immune response are the toll-like receptor, interferon, NF-kappaB and apoptotic pathways, which co-operate to defend cells against a given pathogen. However, these pathways are commonly viewed as separate entities rather than an integrated network of molecular interactions. RESULTS: Here we describe the construction of a logically represented pathway diagram which attempts to integrate these four pathways central to innate immunity using a modified version of the Edinburgh Pathway Notation. The pathway map is available in a number of electronic formats and editing is supported by yEd graph editor software. CONCLUSION: The map presents a powerful visual aid for interpreting the available pathway interaction knowledge and underscores the valuable contribution well constructed pathway diagrams make to communicating large amounts of molecular interaction data. Furthermore, we discuss issues with the limitations and scalability of pathways presented in this fashion, explore options for automated layout of large pathway networks and demonstrate how such maps can aid the interpretation of functional studies

Combined population genomic screening for three high-risk conditions in Australia: a modelling study

BACKGROUND: No previous health-economic evaluation has assessed the impact and cost-effectiveness of offering combined adult population genomic screening for mutliple high-risk conditions in a national public healthcare system. METHODS: This modeling study assessed the impact of offering combined genomic screening for hereditary breast and ovarian cancer, Lynch syndrome and familial hypercholesterolaemia to all young adults in Australia, compared with the current practice of clinical criteria-based testing for each condition separately. The intervention of genomic screening, assumed as an up-front single cost in the first annual model cycle, would detect pathogenic variants in seven high-risk genes. The simulated population was 18–40 year-olds (8,324,242 individuals), modelling per-sample test costs ranging AU$100–$1200 (base-case AU$200) from the year 2023 onwards with testing uptake of 50 FINDINGS: Over the population lifetime (to age 80 years), the model estimated that genomic screening per-100,000 individuals would lead to 747 QALYs gained by preventing 63 cancers, 31 CHD cases and 97 deaths. In the total model population, this would translate to 31,094 QALYs gained by preventing 2612 cancers, 542 non-fatal CHD events and 4047 total deaths. At AU$200 per-test, genomic screening would require an investment of AU$832 million for screening of 50$23,926 (∼£12,050/€14,110/US$15,345) per QALY gained over the status quo. In scenario analysis with 3$4758/QALY was obtained. Sensitivity analysis for the base case indicated that combined genomic screening would be cost-effective under 70% of simulations, cost-saving under 25% and not cost-effective under 5%. Threshold analysis showed that genomic screening would be cost-effective under the AU$50,000/QALY willingness-to-pay threshold at per-test costs up to AU$325 (∼£164/€192/US$208). INTERPRETATION: Our findings suggest that offering combined genomic screening for high-risk conditions to young adults would be cost-effective in the Australian public healthcare system, at currently realistic testing costs. Other matters, including psychosocial impacts, ethical and societal issues, and implementation challenges, also need consideration. FUNDING: Australian Government, Department of Health, Medical Research Future Fund, Genomics Health Futures Mission (APP2009024). National Heart Foundation Future Leader Fellowship (102604)

Host Defense against Viral Infection Involves Interferon Mediated Down-Regulation of Sterol Biosynthesis

Upon infection, our immune cells produce a small protein called interferon, which in turn signals a protective response through a series of biochemical reactions that involves lowering the cells' ability to make cholesterol by targeting a gene essential for controlling the pathway for cholesterol metabolism

Construction of a large scale integrated map of macrophage pathogen recognition and effector systems

<p>Abstract</p> <p>Background</p> <p>In an effort to better understand the molecular networks that underpin macrophage activation we have been assembling a map of relevant pathways. Manual curation of the published literature was carried out in order to define the components of these pathways and the interactions between them. This information has been assembled into a large integrated directional network and represented graphically using the modified Edinburgh Pathway Notation (mEPN) scheme.</p> <p>Results</p> <p>The diagram includes detailed views of the toll-like receptor (TLR) pathways, other pathogen recognition systems, NF-kappa-B, apoptosis, interferon signalling, MAP-kinase cascades, MHC antigen presentation and proteasome assembly, as well as selected views of the transcriptional networks they regulate. The integrated pathway includes a total of 496 unique proteins, the complexes formed between them and the processes in which they are involved. This produces a network of 2,170 nodes connected by 2,553 edges.</p> <p>Conclusions</p> <p>The pathway diagram is a navigable visual aid for displaying a consensus view of the pathway information available for these systems. It is also a valuable resource for computational modelling and aid in the interpretation of functional genomics data. We envisage that this work will be of value to those interested in macrophage biology and also contribute to the ongoing Systems Biology community effort to develop a standard notation scheme for the graphical representation of biological pathways.</p

CD200 receptor restriction of myeloid cell responses antagonizes antiviral immunity and facilitates cytomegalovirus persistence within mucosal tissue

CD200 receptor (CD200R) negatively regulates peripheral and mucosal innate immune responses. Viruses, including herpesviruses, have acquired functional CD200 orthologs, implying that viral exploitation of this pathway is evolutionary advantageous. However, the role that CD200R signaling plays during herpesvirus infection in vivo requires clarification. Utilizing the murine cytomegalovirus (MCMV) model, we demonstrate that CD200R facilitates virus persistence within mucosal tissue. Specifically, MCMV infection of CD200R-deficient mice (CD200R-/-) elicited heightened mucosal virus-specific CD4 T cell responses that restricted virus persistence in the salivary glands. CD200R did not directly inhibit lymphocyte effector function. Instead, CD200R-/- mice exhibited enhanced APC accumulation that in the mucosa was a consequence of elevated cellular proliferation. Although MCMV does not encode an obvious CD200 homolog, productive replication in macrophages induced expression of cellular CD200. CD200 from hematopoietic and non-hematopoietic cells contributed independently to suppression of antiviral control in vivo. These results highlight the CD200-CD200R pathway as an important regulator of antiviral immunity during cytomegalovirus infection that is exploited by MCMV to establish chronicity within mucosal tissue

Tpc1 is an important Zn(II)(2)Cys(6) transcriptional regulator required for polarized growth and virulence in the rice blast fungus

The establishment of polarity is a critical process in pathogenic fungi, mediating infection-related morphogenesis and host tissue invasion. Here, we report the identification of TPC1 (Transcription factor for Polarity Control 1), which regulates invasive polarized growth in the rice blast fungus Magnaporthe oryzae. TPC1 encodes a putative transcription factor of the fungal Zn(II)(2)Cys(6) family, exclusive to filamentous fungi. Tpc1-deficient mutants show severe defects in conidiogenesis, infection-associated autophagy, glycogen and lipid metabolism, and plant tissue colonisation. By tracking actin-binding proteins, septin-5 and autophagosome components, we show that Tpc1 regulates cytoskeletal dynamics and infection-associated autophagy during appressorium-mediated plant penetration. We found that Tpc1 interacts with Mst12 and modulates its DNA-binding activity, while Tpc1 nuclear localisation also depends on the MAP kinase Pmk1, consistent with the involvement of Tpc1 in this signalling pathway, which is critical for appressorium development. Importantly, Tpc1 directly regulates NOXD expression, the p22(phox) subunit of the fungal NADPH oxidase complex via an interaction with Mst12. Tpc1 therefore controls spatial and temporal regulation of cortical F-actin through regulation of the NADPH oxidase complex during appressorium re-polarisation. Consequently, Tpc1 is a core developmental regulator in filamentous fungi, linking the regulated synthesis of reactive oxygen species and the Pmk1 pathway, with polarity control during host invasion

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries

A Solve-RD ClinVar-based reanalysis of 1522 index cases from ERN-ITHACA reveals common pitfalls and misinterpretations in exome sequencing

Purpose Within the Solve-RD project (https://solve-rd.eu/), the European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies aimed to investigate whether a reanalysis of exomes from unsolved cases based on ClinVar annotations could establish additional diagnoses. We present the results of the “ClinVar low-hanging fruit” reanalysis, reasons for the failure of previous analyses, and lessons learned. Methods Data from the first 3576 exomes (1522 probands and 2054 relatives) collected from European Reference Network for Intellectual disability, TeleHealth, Autism and Congenital Anomalies was reanalyzed by the Solve-RD consortium by evaluating for the presence of single-nucleotide variant, and small insertions and deletions already reported as (likely) pathogenic in ClinVar. Variants were filtered according to frequency, genotype, and mode of inheritance and reinterpreted. Results We identified causal variants in 59 cases (3.9%), 50 of them also raised by other approaches and 9 leading to new diagnoses, highlighting interpretation challenges: variants in genes not known to be involved in human disease at the time of the first analysis, misleading genotypes, or variants undetected by local pipelines (variants in off-target regions, low quality filters, low allelic balance, or high frequency). Conclusion The “ClinVar low-hanging fruit” analysis represents an effective, fast, and easy approach to recover causal variants from exome sequencing data, herewith contributing to the reduction of the diagnostic deadlock