13 research outputs found
Rapidly Escalating Hepcidin and Associated Serum Iron Starvation Are Features of the Acute Response to Typhoid Infection in Humans
BACKGROUND: Iron is a key pathogenic determinant of many infectious diseases. Hepcidin, the hormone responsible for governing systemic iron homeostasis, is widely hypothesized to represent a key component of nutritional immunity through regulating the accessibility of iron to invading microorganisms during infection. However, the deployment of hepcidin in human bacterial infections remains poorly characterized. Typhoid fever is a globally significant, human-restricted bacterial infection, but understanding of its pathogenesis, especially during the critical early phases, likewise is poorly understood. Here, we investigate alterations in hepcidin and iron/inflammatory indices following experimental human typhoid challenge.
METHODOLOGY/PRINCIPAL FINDINGS: Fifty study participants were challenged with Salmonella enterica serovar Typhi and monitored for evidence of typhoid fever. Serum hepcidin, ferritin, serum iron parameters, C-reactive protein (CRP), and plasma IL-6 and TNF-alpha concentrations were measured during the 14 days following challenge. We found that hepcidin concentrations were markedly higher during acute typhoid infection than at baseline. Hepcidin elevations mirrored the kinetics of fever, and were accompanied by profound hypoferremia, increased CRP and ferritin, despite only modest elevations in IL-6 and TNF-alpha in some individuals. During inflammation, the extent of hepcidin upregulation associated with the degree of hypoferremia.
CONCLUSIONS/SIGNIFICANCE: We demonstrate that strong hepcidin upregulation and hypoferremia, coincident with fever and systemic inflammation, are hallmarks of the early innate response to acute typhoid infection. We hypothesize that hepcidin-mediated iron redistribution into macrophages may contribute to S. Typhi pathogenesis by increasing iron availability for macrophage-tropic bacteria, and that targeting macrophage iron retention may represent a strategy for limiting infections with macrophage-tropic pathogens such as S. Typhi
Glioma-associated microglia/macrophages augment tumorigenicity in canine astrocytoma, a naturally occurring model of human glioma.
BackgroundGlioma-associated microglia/macrophages (GAMs) markedly influence glioma progression. Under the influence of transforming growth factor beta (TGFB), GAMs are polarized toward a tumor-supportive phenotype. However, neither therapeutic targeting of GAM recruitment nor TGFB signaling demonstrated efficacy in glioma patients despite efficacy in preclinical models, underscoring the need for a comprehensive understanding of the TGFB/GAM axis. Spontaneously occurring canine gliomas share many features with human glioma and provide a complementary translational animal model for further study. Given the importance of GAM and TGFB in human glioma, the aims of this study were to further define the GAM-associated molecular profile and the relevance of TGFB signaling in canine glioma that may serve as the basis for future translational studies.MethodsGAM morphometry, levels of GAM-associated molecules, and the canonical TGFB signaling axis were compared in archived samples of canine astrocytomas versus normal canine brain. Furthermore, the effect of TGFB on the malignant phenotype of canine astrocytoma cells was evaluated.ResultsGAMs diffusely infiltrated canine astrocytomas. GAM density was increased in high-grade tumors that correlated with a pro-tumorigenic molecular signature and upregulation of the canonical TGFB signaling axis. Moreover, TGFB1 enhanced the migration of canine astrocytoma cells in vitro.ConclusionsCanine astrocytomas share a similar GAM-associated immune landscape with human adult glioma. Our data also support a contributing role for TGFB1 signaling in the malignant phenotype of canine astrocytoma. These data further support naturally occurring canine glioma as a valid model for the investigation of GAM-associated therapeutic strategies for human malignant glioma
Opposite associations of hepcidin with serum iron and transferrin saturation in the presence and absence of inflammation.
<p>Associations between (A) hepcidin and serum iron, (B) hepcidin and transferrin saturation (Tsat), (C) ferritin and serum iron, and (D) ferritin and Tsat, when acute inflammation (defined as CRP>5 mg/L, open circles) or when no inflammation (CRP<5 mg/L, closed circles) was evident. The analysis considered all data obtained between challenge day and Day 14 post-challenge for each study participant, whether diagnosed with typhoid or not. To normalize data, each parameter was log-transformed prior to analysis. The analysis accounts for individuals contributing more than single data points by using regression with clustered errors (Serum Iron analyses (A) and (C): CRP <5 mg/L: 118 observations, 47 clusters; CRP >5 mg/L: 69 observations, 36 clusters. Tsat analyses (B) and (D): CRP <5 mg/L: 117 observations, 46 clusters; CRP >5 mg/L: 69 observations, 36 clusters). Regression with clustered errors adjusts the confidence intervals of the regression coefficients to account for intra-cluster correlation, as is likely when multiple observations from the same individuals are included. Pearson correlation coefficients and p-values are stated.</p
Changes in hepcidin, iron and inflammatory indices between baseline–the day of typhoid challenge–and the day of typhoid diagnosis.
<p>Serum samples were available from both day of typhoid challenge and day of typhoid diagnosis from 19 individuals from Study A (placebo arm of vaccine/typhoid challenge study). (A) temperature, (B) hepcidin, (C) serum iron, (D) transferrin saturation, (E) CRP, (F) ferritin and (G) hemoglobin were measured on the day of challenge and day of typhoid diagnosis. P-values represent results of paired t tests based on geometric means for hepcidin (baseline, 10.4 ng/mL [95% CI: 7.1–15.3]; diagnosis, 98.2 ng/mL [75.9–126.9]), ferritin (baseline, 46.3 μg/L [30.8–69.8]; diagnosis, 86.4μg/L [56.9–131.0]) and CRP (baseline: 1.46 mg/L [0.84–2.54]; diagnosis, 34.1 mg/L [24.2–48.2]), and arithmetic means for temperature (baseline, 36.3°C [36.1–36.5]; diagnosis, 37.6°C [37.3–37.9]), serum iron (baseline, 12.6 μmol/L [9.9–15.3]; diagnosis, 4.4 μmol/L [2.7–6.1]), transferrin saturation (baseline, 22.3% [17.2–27.4]; diagnosis, 7.4% [4.7–10.2]) and hemoglobin (baseline, 14.3 g/dL [13.6–15.1]; diagnosis 13.9 g/dL [13.1–14.8]).</p
Hepcidin is suppressed by erythropoiesis in hemoglobin E β-thalassemia and β-thalassemia trait.
Hemoglobin E (HbE) β-thalassemia is the most common severe thalassemia syndrome across Asia, and millions of people are carriers. Clinical heterogeneity in HbE β-thalassemia is incompletely explained by genotype, and the interaction of phenotypic variation with hepcidin is unknown. The effect of thalassemia carriage on hepcidin is also unknown, but it could be relevant for iron supplementation programs aimed at combating anemia. In 62 of 69 Sri Lankan patients with HbE β-thalassemia with moderate or severe phenotype, hepcidin was suppressed, and overall hepcidin inversely correlated with iron accumulation. On segregating by phenotype, there were no differences in hepcidin, erythropoiesis, or hemoglobin between severe or moderate disease, but multiple linear regression showed that erythropoiesis inversely correlated with hepcidin only in severe phenotypes. In moderate disease, no independent predictors of hepcidin were identifiable; nevertheless, the low hepcidin levels indicate a significant risk for iron overload. In a population survey of Sri Lankan schoolchildren, β-thalassemia (but not HbE) trait was associated with increased erythropoiesis and mildly suppressed hepcidin, suggesting an enhanced propensity to accumulate iron. In summary, the influence of erythropoiesis on hepcidin suppression associates with phenotypic disease variation and pathogenesis in HbE β-thalassemia and indicates that the epidemiology of β-thalassemia trait requires consideration when planning public health iron interventions
Baseline characteristics of study populations on the day of typhoid challenge.
<p><sup>a</sup> p<0.05, t test</p><p><sup>b</sup> p>0.05</p><p><sup>c</sup> arithmetic mean (+/- standard deviation) reported unless stated otherwise.</p><p>Baseline characteristics of study populations on the day of typhoid challenge.</p
Kinetics of perturbations in IL-6 and TNF-alpha in individuals diagnosed with typhoid infection following experimental <i>Salmonella</i> Typhi challenge.
<p>(A) Plasma IL-6 and (B) TNF-alpha concentrations were measured in 13 individuals from Study B who received typhoid diagnosis following challenge with <i>Salmonella</i> Typhi. Analyte values are plotted relative to the day of typhoid diagnosis, TD = day 0; since not all individuals were diagnosed on the same day post-challenge, baseline samples from the day of challenge (Chall) are considered together, as are data from the final day 14 visit (Final). (Left-hand panels) Data available from each individual for each day were plotted using box and whiskers, representing median values and interquartile ranges (IQR); whiskers represent the data point occurring furthest from the first or third quartile but still within 1.5*IQR of the quartile; outliers (further than 1.5*IQR from the quartile) are shown as isolated data points. Smoothed curves were also interpolated from the mean data for each day and overlaid on the plots. The Wald test was employed after fitting linear mixed effects models to test the null hypothesis that there is no difference between parameter values between days. Pairwise differences between baseline values on the day of typhoid challenge (Chall) and other days were examined by t-tests after accounting for subject-specific variability. Significant perturbations from baseline are indicated with asterisks (***p<0.001). (Right-hand panels) Smoothed interpolated curves as described above, but depicting 95% pointwise prediction intervals (thick error bar) and conservative simultaneous Bonferroni bounds (thin error bar) of the interpolated curves.</p
Kinetics of perturbations in hepcidin, iron and inflammatory parameters in individuals diagnosed with typhoid infection following experimental <i>Salmonella</i> Typhi challenge.
<p>(A) Temperatures, (B) serum hepcidin concentrations, (C) serum iron, (D) transferrin saturations, (E) hemoglobin, (F) CRP, and (G) ferritin concentrations were measured in 13 individuals from Study B who received typhoid diagnosis following challenge with <i>Salmonella</i> Typhi. Analyte values are plotted relative to the day of typhoid diagnosis, TD = day 0; since not all individuals were diagnosed on the same day post-challenge, baseline samples from the day of challenge (Chall) are considered together, as are data from the final day 14 visit (Final). (Left-hand panels) Data available from each individual for each day were plotted using box and whiskers, representing median values and interquartile ranges (IQR); whiskers represent the data point occurring furthest from the first or third quartile but still within 1.5*IQR of the quartile; outliers (further than 1.5*IQR from the quartile) are shown as isolated data points. Smoothed curves were also interpolated from the mean data for each day and overlaid on the plots. The Wald test was employed after fitting linear mixed effects models to test the null hypothesis that there is no difference between parameter values between days. Pairwise differences between baseline values on the day of typhoid challenge (Chall) and other days were examined by t-tests after accounting for subject-specific variability. Significant perturbations from baseline are indicated with asterisks (*p<0.05, **p<0.01, ***p<0.001). For ferritin, outliers at (a) 1014.07 μg/L and 1075.24 μg/L, (b) 2433.54 μg/L, and (c) 1008.87 μg/L are beyond the y-axis limits and not depicted on the figure, but are included in the analysis. (Right-hand panels) Smoothed interpolated curves as described above, but depicting 95% pointwise prediction intervals (thick error bar) and conservative simultaneous Bonferroni bounds (thin error bar) of the interpolated curves.</p