56 research outputs found

    Impact of glucuronide interferences on therapeutic drug monitoring of posaconazole by tandem mass spectrometry

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    Background: Posaconazole is a novel antifungal drug for oral application intended especially for therapy of invasive mycoses. Due to variable gastrointestinal absorption, adverse side effects, and suspected drug-drug interactions, therapeutic drug monitoring (TDM) of posaconazole is recommended. Method: A fast ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method for quantification of posaconazole with a run-time <3 min was developed and compared to a LC-MS/MS method and HPLC method with fluorescence detection. Results: During evaluation of UPLC-MS/MS, two earlier eluting peaks were observed in the MRM trace of posaconazole. This was only seen in patient samples, but not in spiked calibrator samples. Comparison with LC-MS/MS disclosed a significant bias with higher concentrations measured by LC-MS/MS, while UPLC-MS/MS showed excellent agreement with the commercially available HPLC method. In the LC-MS/MS procedure, comparably wide and left side shifted peaks were noticed. This could be ascribed to in-source fragmentation of conjugate metabolites during electrospray ionisation. Precursor and product ion scans confirmed the assumption that the additional compounds are posaconazole glucuronides. Reducing the cone voltage led to disappearance of the glucuronide peaks. Slight modification of the LC-MS/MS method enabled separation of the main interference, leading to significantly reduced deviation. Conclusions: These results highlight the necessity to reliably eliminate interference from labile drug metabolites for correct TDM results, either by sufficient separation or selective MS conditions. The presented UPLC-MS/MS method provides a reliable and fast assay for TDM of posaconazole. Clin Chem Lab Med 2010; 48:1723-31

    Pattern-sensitive Time-series Anonymization and its Application to Energy-Consumption Data

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    Time series anonymization is an important problem. One prominent example of time series are energy consumption records, which might reveal details of the daily routine of a household. Existing privacy approaches for time series, e.g., from the field of trajectory anonymization, assume that every single value of a time series contains sensitive information and reduce the data quality very much. In contrast, we consider time series where it is combinations of tuples that represent personal information. We propose (n; l; k)-anonymity, geared to anonymization of time-series data with minimal information loss, assuming that an adversary may learn a few data points. We propose several heuristics to obtain (n; l; k)-anonymity, and we evaluate our approach both with synthetic and real data. Our experiments confirm that it is sufficient to modify time series only moderately in order to fulfill meaningful privacy requirements

    Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa

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    Characterized primarily by a low body-mass index, anorexia nervosa is a complex and serious illness1, affecting 0.9-4% of women and 0.3% of men2-4, with twin-based heritability estimates of 50-60%5. Mortality rates are higher than those in other psychiatric disorders6, and outcomes are unacceptably poor7. Here we combine data from the Anorexia Nervosa Genetics Initiative (ANGI)8,9 and the Eating Disorders Working Group of the Psychiatric Genomics Consortium (PGC-ED) and conduct a genome-wide association study of 16,992 cases of anorexia nervosa and 55,525 controls, identifying eight significant loci. The genetic architecture of anorexia nervosa mirrors its clinical presentation, showing significant genetic correlations with psychiatric disorders, physical activity, and metabolic (including glycemic), lipid and anthropometric traits, independent of the effects of common variants associated with body-mass index. These results further encourage a reconceptualization of anorexia nervosa as a metabo-psychiatric disorder. Elucidating the metabolic component is a critical direction for future research, and paying attention to both psychiatric and metabolic components may be key to improving outcomes

    Common Genetic Variation And Age at Onset Of Anorexia Nervosa

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    Background Genetics and biology may influence the age at onset of anorexia nervosa (AN). The aims of this study were to determine whether common genetic variation contributes to AN age at onset and to investigate the genetic associations between age at onset of AN and age at menarche. Methods A secondary analysis of the Psychiatric Genomics Consortium genome-wide association study (GWAS) of AN was performed which included 9,335 cases and 31,981 screened controls, all from European ancestries. We conducted GWASs of age at onset, early-onset AN (< 13 years), and typical-onset AN, and genetic correlation, genetic risk score, and Mendelian randomization analyses. Results Two loci were genome-wide significant in the typical-onset AN GWAS. Heritability estimates (SNP-h2) were 0.01-0.04 for age at onset, 0.16-0.25 for early-onset AN, and 0.17-0.25 for typical-onset AN. Early- and typical-onset AN showed distinct genetic correlation patterns with putative risk factors for AN. Specifically, early-onset AN was significantly genetically correlated with younger age at menarche, and typical-onset AN was significantly negatively genetically correlated with anthropometric traits. Genetic risk scores for age at onset and early-onset AN estimated from independent GWASs significantly predicted age at onset. Mendelian randomization analysis suggested a causal link between younger age at menarche and early-onset AN. Conclusions Our results provide evidence consistent with a common variant genetic basis for age at onset and implicate biological pathways regulating menarche and reproduction.Peer reviewe

    A genome-wide association study of anorexia nervosa suggests a risk locus implicated in dysregulated leptin signaling

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    J. Kaprio, A. Palotie, A. Raevuori-Helkamaa ja S. Ripatti ovat työryhmän Eating Disorders Working Group of the Psychiatric Genomics Consortium jäseniä. Erratum in: Sci Rep. 2017 Aug 21;7(1):8379, doi: 10.1038/s41598-017-06409-3We conducted a genome-wide association study (GWAS) of anorexia nervosa (AN) using a stringently defined phenotype. Analysis of phenotypic variability led to the identification of a specific genetic risk factor that approached genome-wide significance (rs929626 in EBF1 (Early B-Cell Factor 1); P = 2.04 x 10(-7); OR = 0.7; 95% confidence interval (CI) = 0.61-0.8) with independent replication (P = 0.04), suggesting a variant-mediated dysregulation of leptin signaling may play a role in AN. Multiple SNPs in LD with the variant support the nominal association. This demonstrates that although the clinical and etiologic heterogeneity of AN is universally recognized, further careful sub-typing of cases may provide more precise genomic signals. In this study, through a refinement of the phenotype spectrum of AN, we present a replicable GWAS signal that is nominally associated with AN, highlighting a potentially important candidate locus for further investigation.Peer reviewe

    Shared genetic risk between eating disorder- and substance-use-related phenotypes:Evidence from genome-wide association studies

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    First published: 16 February 202

    Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders

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    Genetic influences on psychiatric disorders transcend diagnostic boundaries, suggesting substantial pleiotropy of contributing loci. However, the nature and mechanisms of these pleiotropic effects remain unclear. We performed analyses of 232,964 cases and 494,162 controls from genome-wide studies of anorexia nervosa, attention-deficit/hyper-activity disorder, autism spectrum disorder, bipolar disorder, major depression, obsessive-compulsive disorder, schizophrenia, and Tourette syndrome. Genetic correlation analyses revealed a meaningful structure within the eight disorders, identifying three groups of inter-related disorders. Meta-analysis across these eight disorders detected 109 loci associated with at least two psychiatric disorders, including 23 loci with pleiotropic effects on four or more disorders and 11 loci with antagonistic effects on multiple disorders. The pleiotropic loci are located within genes that show heightened expression in the brain throughout the lifespan, beginning prenatally in the second trimester, and play prominent roles in neurodevelopmental processes. These findings have important implications for psychiatric nosology, drug development, and risk prediction.Peer reviewe
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