6 research outputs found

    A research roadmap for next-generation sequencing informatics.

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    Next-generation sequencing technologies are fueling a wave of new diagnostic tests. Progress on a key set of nine research challenge areas will help generate the knowledge required to advance effectively these diagnostics to the clinic

    Optimization of Next-Generation Sequencing Informatics Pipelines for Clinical Laboratory Practice

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    We direct your readers’ attention to the principles and guidelines (see Supplementary Guidelines) developed by the Next-generation Sequencing: Standardization of Clinical Testing II (Nex-StoCT II) informatics workgroup, which was convened by the Centers for Disease Control and Prevention (CDC). This work represents the first effort to systematically review current practices and present consensus recommendations for the design, optimization, and implementation of an informatics pipeline for clinical next-generation sequencing (NGS) in compliance with existing regulatory and professional quality standards1. Workgroup participants included informatics experts, clinical and research laboratory professionals, physicians with experience in NGS results interpretation, NGS test platform and software developers, and participants from US government agencies and professional organizations. The primary focus was the design, optimization, and implementation of an NGS informatics pipeline for the detection of germline sequence variants; however, the workgroup also discussed use of NGS for cancer and infectious disease testing. The typical NGS analytical process and selected workgroup recommendations are summarized in Table 1, Supplementary Fig. 1 and the Supplementary Guidelines

    Illness progression in chronic fatigue syndrome: a shifting immune baseline.

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    BACKGROUND: Validation of biomarkers for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) across data sets has proven disappointing. As immune signature may be affected by many factors, our objective was to explore the shift in discriminatory cytokines across ME/CFS subjects separated by duration of illness. METHODS: Cytokine expression collected at rest across multiple studies for female ME/CFS subjects (i) 18 years or younger, ill for 2 years or less (n = 18), (ii) 18–50 years of age, ill for 7 years (n = 22), and (iii) age 50 years or older (n = 28), ill for 11 years on average. Control subjects were matched for age and body mass index (BMI). Data describing the levels of 16 cytokines using a chemiluminescent assay was used to support the identification of separate linear classification models for each subgroup. In order to isolate the effects of duration of illness alone, cytokines that changed significantly with age in the healthy control subjects were excluded a priori. RESULTS: Optimal selection of cytokines in each group resulted in subsets of IL-1α, 6, 8, 15 and TNFα. Common to any 2 of 3 groups were IL-1α, 6 and 8. Setting these 3 markers as a triple screen and adjusting their contribution according to illness duration sub-groups produced ME/CFS classification accuracies of 75–88 %. The contribution of IL-1α, higher in recently ill adolescent ME/CFS subjects was progressively less important with duration. While high levels of IL-8 screened positive for ME/CFS in the recently afflicted, the opposite was true for subjects ill for more than 2 years. Similarly, while low levels of IL-6 suggested early ME/CFS, the reverse was true in subjects over 18 years of age ill for more than 2 years. CONCLUSIONS: These preliminary results suggest that IL-1α, 6 and 8 adjusted for illness duration may serve as robust biomarkers, independent of age, in screening for ME/CFS. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12865-016-0142-3) contains supplementary material, which is available to authorized users
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