A Helminth Immunomodulator Exploits Host Signaling Events to Regulate Cytokine Production in Macrophages

Parasitic worms alter their host's immune system to diminish the inflammatory responses directed against them, using very efficient immunomodulating molecules. We have previously shown that the helminth immunomodulator cystatin (AvCystatin) profoundly reduces the progression of inflammatory diseases via modulation of macrophages. Here we elucidate the signaling events in macrophages triggered by AvCystatin. Labeled AvCystatin was predominantly taken up by macrophages and subsequently induced the phosphorylation of the mitogen-activated protein kinases (MAPK) ERK1/2 and p38. IL-10 expression induced by AvCystatin in macrophages was tyrosine kinase sensitive and dependent on activation of both MAP kinases, in clear contrast to expression of IL-12/23p40. In addition, phosphorylation of the transcription factors CREB and STAT3 was induced by AvCystatin and regulated by phospho-ERK. Chemical inhibition of phosphoinositide 3-kinase (PI3K) reduced AvCystatin-induced cytokine release; however, AKT, the downstream target of PI3K, was not activated following AvCystatin exposure. To characterize signaling elements involved in alteration of the macrophage phenotype we applied mathematical modeling. Experimental testing of the in silico generated hypotheses identified dual specificity phosphatase (DUSP) 1 and 2, as regulators in AvCystatin triggered macrophages in vitro and in vivo. In particular, DUSP1 was subsequently found to be responsible for regulation of ERK- and p38-phosphorylation and controlled the IL-10 expression in macrophages by AvCystatin. Thus, we show that AvCystatin exploits activation and deactivation pathways of MAP kinases to induce regulatory macrophages. This study provides insights into molecular mechanisms of macrophage manipulation by parasites and highlights the utility of mathematical modeling for the elucidation of regulatory circuits of immune cells

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction.

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 (95% confidence interval (CI), 4.84-5.29) for men of European ancestry to 3.74 (95% CI, 3.36-4.17) for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher (95% CI, 2.14-2.22), and men of East Asian ancestry 0.73-times lower (95% CI, 0.71-0.76), than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction

Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10−15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62–4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification

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

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

Helminth-derived immunomodulators: can understanding the worm produce the pill?

Helminths may protect humans against allergic and autoimmune diseases and, indeed, defined helminth-derived products have recently been shown to prevent the development of such inflammatory diseases in mouse models. Here, we propose that helminth-derived products not only have therapeutic potential but can also be used as unique tools for defining key molecular events in the induction of an anti-inflammatory response and, therefore, for defining new therapeutic target