Comparison of statistical models to estimate parasite growth rate in the induced blood stage malaria model

Background: The efficacy of vaccines aimed at inhibiting the growth of malaria parasites in the blood can be assessed by comparing the growth rate of parasitaemia in the blood of subjects treated with a test vaccine compared to controls. In studies using induced blood stage malaria (IBSM), a type of controlled human malaria infection, parasite growth rate has been measured using models with the intercept on the y-axis fixed to the inoculum size. A set of statistical models was evaluated to determine an optimal methodology to estimate parasite growth rate in IBSM studies. Methods: Parasite growth rates were estimated using data from 40 subjects published in three IBSM studies. Data was fitted using 12 statistical models: log-linear, sine-wave with the period either fixed to 48 h or not fixed; these models were fitted with the intercept either fixed to the inoculum size or not fixed. All models were fitted by individual, and overall by study using a mixed effects model with a random effect for the individual. Results: Log-linear models and sine-wave models, with the period fixed or not fixed, resulted in similar parasite growth rate estimates (within 0.05 log parasites per mL/day). Average parasite growth rate estimates for models fitted by individual with the intercept fixed to the inoculum size were substantially lower by an average of 0.17 log parasites per mL/day (range 0.06-0.24) compared with non-fixed intercept models. Variability of parasite growth rate estimates across the three studies analysed was substantially higher (3.5 times) for fixed-intercept models compared with non-fixed intercept models. The same tendency was observed in models fitted overall by study. Modelling data by individual or overall by study had minimal effect on parasite growth estimates. Conclusions: The analyses presented in this report confirm that fixing the intercept to the inoculum size influences parasite growth estimates. The most appropriate statistical model to estimate the growth rate of blood-stage parasites in IBSM studies appears to be a log-linear model fitted by individual and with the intercept estimated in the log-linear regression. Future studies should use this model to estimate parasite growth rates

Serum ferritin concentration predicts hepatic fibrosis better than hepatic iron concentration in human HFE-Haemochromatosis

Background & AimsFerritin is purported to have proinflammatory and profibrogenic effects on hepatic stellate cells. Thus, rather than acting as a passive indicator of hepatic iron concentration (HIC) in haemochromatosis, ferritin may directly influence fibrosis. This study evaluated whether serum ferritin is a better predictor of hepatic fibrosis compared to variables previously associated with increased fibrosis risk in haemochromatosis

Epigenetic analysis confirms no accelerated brain aging in schizophrenia

Abstract Epigenetic aging is associated with several biological mechanisms and diseases. We assessed two brain data sets, one small (n = 48) and one large (n = 392), to test epigenetic aging in schizophrenia. DNA methylation age from frontal cortex was significantly correlated with chronological age but no significant differences in DNA methylation age acceleration between schizophrenia cases and controls were observed in both data sets. Our results were consistent with a previous study investigating schizophrenia and epigenetic aging in superior temporal gyrus. Future studies targeting different brain regions and defined cell types are warranted to further investigate accelerated brain aging in schizophrenia

Hepatic Iron Deposition Does Not Predict Extrahepatic Iron Loading in Mouse Models of Hereditary Hemochromatosis

Hereditary hemochromatosis is characterized by tissue iron loading and associated organ damage. However, the phenotype can be highly variable. The relationship between iron loading of different organs and the temporal nature of its deposition is still not well understood. We examined the progression of tissue iron loading in three mouse models to advance our understanding of the natural history of iron deposition in hereditary hemochromatosis. Wild-type, Hfe(-/-), Tfr2(-/-), and Hfe(-/-) /Tfr2(-/-) mice were analyzed at 3, 5, 10, 26, and 52 weeks, respectively. Hepatic, splenic, cardiac, and pancreatic iron concentrations were determined. Expression of both iron-regulatory and fibrosis genes was determined by quantitative real-time PCR in livers and hearts of 52-week-old mice. In all models, hepatic iron increased rapidly, plateauing before 10 weeks at different levels, depending on the genotype. Iron deposition in the pancreas and heart occurred after maximal iron loading of the liver was reached and was most marked in the Hie /Tfr2-/- mice. Although a significant positive correlation was identified between pancreatic and cardiac iron in all models at 52 weeks, there was no correlation between hepatic and either pancreatic or cardiac iron. There is variability in the timing and extent of tissue iron loading within a genotype, suggesting that hepatic iron levels in hereditary hemochromatosis may not accurately predict the iron content of other organs. (Am J Pathol 2012, 181:1173-1179; http://dx.doi.org/10.1016/j.ajpath.2012.06.025

HLA class I associations with EBV+ post-transplant lymphoproliferative disorder

Epstein-Barr virus (EBV) is frequently associated with post-transplant lymphoproliferative disorders (EBV+ PTLD). In these cases, impaired Epstein-Barr virus (EBV)-specific CD8(+) T-cell immunity is strongly implicated and antigen presentation within the malignant B-cell is intact Interestingly, several studies have reported HLA class I alleles with protective or susceptibility associations. However, results are conflicting, likely influenced by methodology including inconsistent use of multiple hypothesis testing. By contrast, HLA class I associations have been repeatedly reported for classical Hodgkin Lymphoma (cHL), in which EBV is also implicated in a proportion of cases. In contrast to EBV+ PTLD which expresses the immunodominant EBV latency III EBNA3A/B/C proteins, EBV+ cHL is restricted to the subdominant EBNAl/LMP1/LMP2 proteins. Herein, we report a study of HLA class I associations in EBV+ PTLD, with 263 patients with lymphoma (cHL or PTLD) evaluated. Two Australian population cohorts, n = 23,736 and n = 891 were used for comparison. Contrary to previous reports, no HLA class I associations with EBV+ PTLD were found, whereas for cHL known HLA class I associations were confirmed, with HLA-A*02 homozygous individuals having the lowest odds of developing EBV+ cHL. Our results suggest that HLA class I does not influence susceptibility to the viral latency III expressing lymphoma, EBV+ PTLD. Further studies are required for definitive confirmation. (C) 2015 Published by Elsevier B.V

Expression and methylation of BDNF in the human brain in schizophrenia

<b>OBJECTIVES: </b>\ud \ud To examine the combined effect of the BDNF Val66Met (rs6265) polymorphism and BDNF DNA methylation on transcriptional regulation of the BDNF gene.\ud \ud <b>METHODS: </b>\ud \ud DNA methylation profiles were generated for CpG sites proximal to Val66Met, within BDNF promoter I and exon V for prefrontal cortex samples from 25 schizophrenia and 25 control subjects. Val66Met genotypes and BDNF mRNA expression data were generated by transcriptome sequencing. Expression, methylation and genotype data were correlated and examined for association with schizophrenia.\ud \ud <b>RESULTS: </b>\ud \ud There was 43% more of the BDNF V-VIII-IX transcript in schizophrenia samples. BDNF mRNA expression and DNA methylation of seven CpG sites were not associated with schizophrenia after accounting for age and PMI effects. BDNF mRNA expression and DNA methylation were not altered by Val66Met after accounting for age and PMI effects. DNA methylation of one CpG site had a marginally significant positive correlation with mRNA expression in schizophrenia subjects.\ud \ud <b>CONCLUSIONS: </b>\ud \ud Schizophrenia risk was not associated with differential BDNF mRNA expression and DNA methylation. A larger age-matched cohort with comprehensive clinical history is required to accurately identify the effects of genotype, mRNA expression and DNA methylation on schizophrenia risk