Pharmacogenomics of Interferon-ß Therapy in Multiple Sclerosis: Baseline IFN Signature Determines Pharmacological Differences between Patients

Multiple sclerosis (MS) is a heterogeneous disease. In order to understand the partial responsiveness to IFNbeta in Relapsing Remitting MS (RRMS) we studied the pharmacological effects of IFNbeta therapy. Large scale gene expression profiling was performed on peripheral blood of 16 RRMS patients at baseline and one month after the start of IFNbeta therapy. Differential gene expression was analyzed by Significance Analysis of Microarrays. Subsequent expression analyses on specific genes were performed after three and six months of treatment. Peripheral blood mononuclear cells (PBMC) were isolated and stimulated in vitro with IFNbeta. Genes of interest were measured and validated by quantitative realtime PCR. An independent group of 30 RRMS patients was used for validation. Pharmacogenomics revealed a marked variation in the pharmacological response to IFNbeta between patients. A total of 126 genes were upregulated in a subset of patients whereas in other patients these genes were downregulated or unchanged after one month of IFNbeta therapy. Most interestingly, we observed that the extent of the pharmacological response correlates negatively with the baseline expression of a specific set of 15 IFN response genes (R = -0.7208; p = 0.0016). The negative correlation was maintained after three (R = -0.7363; p = 0.0027) and six (R = -0.8154; p = 0.0004) months of treatment, as determined by gene expression levels of the most significant correlating gene. Similar results were obtained in an independent group of patients (n = 30; R = -0.4719; p = 0.0085). Moreover, the ex vivo results could be confirmed by in vitro stimulation of purified PBMCs at baseline with IFNbeta indicating that differential responsiveness to IFNbeta is an intrinsic feature of peripheral blood cells at baseline. These data imply that the expression levels of IFN response genes in the peripheral blood of MS patients prior to treatment could serve a role as biomarker for the differential clinical response to IFNbet

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Optimizing Predictive Performance of Bayesian Forecasting for Vancomycin Concentration in Intensive Care Patients

Purpose: Bayesian forecasting is crucial for model-based dose optimization based on therapeutic drug monitoring (TDM) data of vancomycin in intensive care (ICU) patients. We aimed to evaluate the performance of Bayesian forecasting using maximum a posteriori (MAP) estimation for model-based TDM. Methods: We used a vancomycin TDM data set (n = 408 patients). We compared standard MAP-based Bayesian forecasting with two alternative approaches: (i) adaptive MAP which handles data over multiple iterations, and (ii) weighted MAP which weights the likelihood contribution of data. We evaluated the percentage error (PE) for seven scenarios including historical TDM data from the preceding day up to seven days. Results: The mean of median PEs of all scenarios for the standard MAP, adaptive MAP and weighted MAP method were − 7.7%, −4.5% and − 6.7%. The adaptive MAP also showed the narrowest inter-quartile range of PE. In addition, regardless of MAP method, including historical TDM data further in the past will increase prediction errors. Conclusions: The proposed adaptive MAP method outperforms standard MAP in predictive performance and may be considered for improvement of model-based dose optimization. The inclusion of historical data beyond either one day (standard MAP and weighted MAP) or two days (adaptive MAP) reduces predictive performance

Correction to: Optimizing Predictive Performance of Bayesian Forecasting for Vancomycin Concentration in Intensive Care Patients (10.1007/s11095-20-02908-7)

This article was updated to correct Figs. 1 and 4 as author corrections were overlooked during the production process

T helper type 1 and 17 cells determine efficacy of interferon-beta in multiple sclerosis and experimental encephalomyelitis

Item does not contain fulltextInterferon-beta (IFN-beta) is the major treatment for multiple sclerosis. However, this treatment is not always effective. Here we have found congruence in outcome between responses to IFN-beta in experimental autoimmune encephalomyelitis (EAE) and relapsing-remitting multiple sclerosis (RRMS). IFN-beta was effective in reducing EAE symptoms induced by T helper type 1 (T(H)1) cells but exacerbated disease induced by T(H)17 cells. Effective treatment in T(H)1-induced EAE correlated with increased interleukin-10 (IL-10) production by splenocytes. In T(H)17-induced disease, the amount of IL-10 was unaltered by treatment, although, unexpectedly, IFN-beta treatment still reduced IL-17 production without benefit. Both inhibition of IL-17 and induction of IL-10 depended on IFN-gamma. In the absence of IFN-gamma signaling, IFN-beta therapy was ineffective in EAE. In RRMS patients, IFN-beta nonresponders had higher IL-17F concentrations in serum compared to responders. Nonresponders had worse disease with more steroid usage and more relapses than did responders. Hence, IFN-beta is proinflammatory in T(H)17-induced EAE. Moreover, a high IL-17F concentration in the serum of people with RRMS is associated with nonresponsiveness to therapy with IFN-beta.1 april 201