Long-term health benefits of stroke prevention with apixaban versus vitamin K antagonist warfarin in patients with non-valvular atrial fibrillation in Germany: a population-based modelling study.

BACKGROUND: Patients with non-valvular atrial fibrillation (NVAF) have a five times higher stroke risk. For more than 50 years, vitamin K antagonists (VKAs) have been the primary medication for stroke prevention. Apixaban, a non-vitamin K oral anticoagulant (NOAC), has demonstrated better efficacy and safety characteristics than the VKA warfarin in the ARISTOTLE trial. This study aims to quantify the potential societal effects of using apixaban instead of VKA in the German NVAF population from 2017 to 2030. METHODS: Using an existing Markov model and a dynamic population approach, we modelled the health benefits of apixaban in patients with NVAF compared to VKA therapy in the German population from 2017 to 2030. RESULTS: The results represent the extrapolated direct long-term health benefits of apixaban over VKA therapy for the German NVAF population. From 2017 until 2030, the use of apixaban instead of a VKA could avoid 52,185 major clinical events. This includes 15,383 non-fatal strokes or SEs, 22,483 non-fatal major bleeds, and 14,319 all-cause deaths, which correspond to 109,887 life years gained. CONCLUSION: This study demonstrated that using apixaban instead of VKA for stroke prevention can lead to considerable reduction in cardiovascular events.

The methylazoxymethanol acetate (MAM-E17) rat model: molecular and functional effects in the hippocampus.

Administration of the DNA-alkylating agent methylazoxymethanol acetate (MAM) on embryonic day 17 (E17) produces behavioral and anatomical brain abnormalities, which model some aspects of schizophrenia. This has lead to the premise that MAM rats are a neurodevelopmental model for schizophrenia. However, the underlying molecular pathways affected in this model have not been elucidated. In this study, we investigated the molecular phenotype of adult MAM rats by focusing on the frontal cortex and hippocampal areas, as these are known to be affected in schizophrenia. Proteomic and metabonomic analyses showed that the MAM treatment on E17 resulted primarily in deficits in hippocampal glutamatergic neurotransmission, as seen in some schizophrenia patients. Most importantly, these results were consistent with our finding of functional deficits in glutamatergic neurotransmission, as identified using electrophysiological recordings. Thus, this study provides the first molecular evidence, combined with functional validation, that the MAM-E17 rat model reproduces hippocampal deficits relevant to the pathology of schizophrenia.

Behavioral and molecular biomarkers in translational animal models for neuropsychiatric disorders.

Modeling neuropsychiatric disorders in animals poses a significant challenge due to the subjective nature of diverse often overlapping symptoms, lack of objective biomarkers and diagnostics, and the rudimentary understanding of the pathophysiology. Successful translational research requires animal models that can inform about disease mechanisms and therapeutic targets. Here, we review behavioral and neurobiological findings from selected animal models, based on presumed etiology and risk factors, for schizophrenia, bipolar disorder, and major depressive disorder. We focus on the use of appropriate statistical tools and newly developed Research Domain Criteria (RDoC) to link biomarkers from animal models with the human disease. We argue that this approach will lead to development of only the most robust animal models for specific psychiatric disorders and may ultimately lead to better understanding of the pathophysiology and identification of novel biomarkers and therapeutic targets.

Quantification of proteins using data-independent analysis (MSE) in simple andcomplex samples: a systematic evaluation.

A MS-based method for the quantification of proteins termed data-independent analysis (or MS(E)) has been introduced recently. Although this method has been applied to the analysis of various types of biological samples, a thorough evaluation to assess the performance of this approach has yet to be conducted. Presented here is the first systematic and comprehensive study investigating the MS(E) approach for quantitative analysis of low-, medium-, and high-complexity samples. We demonstrate that this method has a linear dynamic range spanning three orders of magnitude with a limit of quantification of 61 amol/uL in low-complexity samples and 488 amol/uL in high-complexity samples. In addition, comprehensive sequence coverage was obtained and accurate quantification achieved for expression ratios ranging from 1:1.5 to 1:6. However, underestimation of ratios was detected independent of sample type, consistent with other quantitative proteomic methods. The present study provides validation of the MS(E) approach for accurate quantitative proteomic analysis of biological samples while, at the same time, proving high sequence coverage of target proteins.

Identification of a candidate genetic variant for the high prevalence of type II diabetes in Polynesians.

The prevalence of non-insulin-dependent diabetes mellitus (type II diabetes) in Polynesia is among the highest recorded worldwide and is substantially higher than in neighboring human populations. Such large differences in the frequency of a phenotype between populations may be explained by large allele frequency differences between populations in genes associated with the phenotype. To identify genes that may explain the high between-population variation in type II diabetes prevalence in the Pacific, we determined the frequency of 10 type II diabetes-associated alleles in 23 Polynesians, 23 highland New Guineans and 19 Han Chinese, calculated population-pairwise Fst values for each allele and compared these values to the distribution of Fst values from approximately 100,000 SNPs from the same populations. The susceptibility allele in the PPARGC1A gene is at a frequency of 0.717 in Polynesians, 0.368 in Chinese but is absent in the New Guineans. The striking frequency difference between Polynesians and New Guineans is highly unusual (Fst=0.703, P=0.007) and we therefore suggest that this allele may play a role in the large difference in type II diabetes prevalence between Polynesians and neighboring populations.