58 research outputs found
Affect fluctuations examined with ecological momentary assessment in patients with current or remitted depression and anxiety disorders
BACKGROUND: There is increasing interest in day-to-day affect fluctuations of patients with depressive and anxiety disorders. Few studies have compared repeated assessments of positive affect (PA) and negative affect (NA) across diagnostic groups, and fluctuation patterns were not uniformly defined. The aim of this study is to compare affect fluctuations in patients with a current episode of depressive or anxiety disorder, in remitted patients and in controls, using affect instability as a core concept but also describing other measures of variability and adjusting for possible confounders. METHODS: Ecological momentary assessment (EMA) data were obtained from 365 participants of the Netherlands Study of Depression and Anxiety with current (n = 95), remitted (n = 178) or no (n = 92) DSM-IV defined depression/anxiety disorder. For 2 weeks, five times per day, participants filled-out items on PA and NA. Affect instability was calculated as the root mean square of successive differences (RMSSD). Tests on group differences in RMSSD, within-person variance, and autocorrelation were performed, controlling for mean affect levels. RESULTS: Current depression/anxiety patients had the highest affect instability in both PA and NA, followed by remitters and then controls. Instability differences between groups remained significant when controlling for mean affect levels, but differences between current and remitted were no longer significant. CONCLUSIONS: Patients with a current disorder have higher instability of NA and PA than remitted patients and controls. Especially with regard to NA, this could be interpreted as patients with a current disorder being more sensitive to internal and external stressors and having suboptimal affect regulation
Angiopoietin-2 Promotes Inflammatory Activation in Monocytes of Systemic Sclerosis Patients
Angiopoietin-2 (Ang-2), a ligand of the tyrosine kinase receptor Tie2, is essential for vascular development and blood vessel stability and is also involved in monocyte activation. Here, we examined the role of Ang-2 on monocyte activation in patients with systemic sclerosis (SSc). Ang-2 levels were measured in serum and skin of healthy controls (HCs) and SSc patients by ELISA and array profiling, respectively. mRNA expression of ANG2 was analyzed in monocytes, dermal fibroblasts, and human pulmonary arterial endothelial cells (HPAECs) by quantitative PCR. Monocytes were stimulated with Ang-2, or with serum from SSc patients in the presence of a Tie2 inhibitor or an anti-Ang2 neutralizing antibody. Interleukin (IL)-6 and IL-8 production was analyzed by ELISA. Ang-2 levels were elevated in the serum and skin of SSc patients compared to HCs. Importantly, serum Ang-2 levels correlated with clinical disease parameters, such as skin involvement. Lipopolysaccharide (LPS) LPS, R848, and interferon alpha2a (IFN-alpha) stimulation up-regulated the mRNA expression of ANG2 in monocytes, dermal fibroblasts, and HPAECs. Finally, Ang-2 induced the production of IL-6 and IL-8 in monocytes of SSc patients, while the inhibition of Tie2 or the neutralization of Ang-2 reduced the production of both cytokines in HC monocytes stimulated with the serum of SSc patients. Therefore, Ang-2 induces inflammatory activation of SSc monocytes and neutralization of Ang-2 might be a promising therapeutic target in the treatment of SSc
Vulnerability for new episodes in recurrent major depressive disorder:protocol for the longitudinal DELTA-neuroimaging cohort study
Introduction Major depressive disorder (MDD) is widely prevalent and severely disabling, mainly due to its recurrent nature. A better understanding of the mechanisms underlying MDD-recurrence may help to identify high-risk patients and to improve the preventive treatment they need. MDD-recurrence has been considered from various levels of perspective including symptomatology, affective neuropsychology, brain circuitry and endocrinology/metabolism. However, MDD-recurrence understanding is limited, because these perspectives have been studied mainly in isolation, cross-sectionally in depressed patients. Therefore, we aim at improving MDD-recurrence understanding by studying these four selected perspectives in combination and prospectively during remission.Methods and analysis In a cohort design, we will include 60 remitted, unipolar, unmedicated, recurrent MDD-participants (35-65years) with 2 MDD-episodes. At baseline, we will compare the MDD-participants with 40 matched controls. Subsequently, we will follow-up the MDD-participants for 2.5years while monitoring recurrences. We will invite participants with a recurrence to repeat baseline measurements, together with matched remitted MDD-participants. Measurements include questionnaires, sad mood-induction, lifestyle/diet, 3T structural (T1-weighted and diffusion tensor imaging) and blood-oxygen-level-dependent functional MRI (fMRI) and MR-spectroscopy. fMRI focusses on resting state, reward/aversive-related learning and emotion regulation. With affective neuropsychological tasks we will test emotional processing. Moreover, we will assess endocrinology (salivary hypothalamic-pituitary-adrenal-axis cortisol and dehydroepiandrosterone-sulfate) and metabolism (metabolomics including polyunsaturated fatty acids), and store blood for, for example, inflammation analyses, genomics and proteomics. Finally, we will perform repeated momentary daily assessments using experience sampling methods at baseline. We will integrate measures to test: (1) differences between MDD-participants and controls; (2) associations of baseline measures with retro/prospective recurrence-rates; and (3) repeated measures changes during follow-up recurrence. This data set will allow us to study different predictors of recurrence in combination.Ethics and dissemination The local ethics committee approved this study (AMC-METC-Nr.:11/050). We will submit results for publication in peer-reviewed journals and presentation at (inter)national scientific meetings.Trial registration number NTR3768.</p
Public health and valorization of genome-based technologies: a new model
<p>Abstract</p> <p>Background</p> <p>The success rate of timely translation of genome-based technologies to commercially feasible products/services with applicability in health care systems is significantly low. We identified both industry and scientists neglect health policy aspects when commercializing their technology, more specifically, Public Health Assessment Tools (PHAT) and early on involvement of decision makers through which market authorization and reimbursements are dependent. While Technology Transfer (TT) aims to facilitate translation of ideas into products, Health Technology Assessment, one component of PHAT, for example, facilitates translation of products/processes into healthcare services and eventually comes up with recommendations for decision makers. We aim to propose a new model of valorization to optimize integration of genome-based technologies into the healthcare system.</p> <p>Methods</p> <p>The method used to develop our model is an adapted version of the Fish Trap Model and the Basic Design Cycle.</p> <p>Results</p> <p>We found although different, similarities exist between TT and PHAT. Realizing the potential of being mutually beneficial justified our proposal of their relative parallel initiation. We observed that the Public Health Genomics Wheel should be included in this relative parallel activity to ensure all societal/policy aspects are dealt with preemptively by both stakeholders. On further analysis, we found out this whole process is dependent on the Value of Information. As a result, we present our LAL (Learning Adapting Leveling) model which proposes, based on market demand; TT and PHAT by consultation/bi-lateral communication should advocate for relevant technologies. This can be achieved by public-private partnerships (PPPs). These widely defined PPPs create the innovation network which is a developing, consultative/collaborative-networking platform between TT and PHAT. This network has iterations and requires learning, assimilating and using knowledge developed and is called absorption capacity. We hypothesize that the higher absorption capacity, higher success possibility. Our model however does not address the phasing out of technology although we believe the same model can be used to simultaneously phase out a technology.</p> <p>Conclusions</p> <p>This model proposes to facilitate optimization/decrease the timeframe of integration in healthcare. It also helps industry and researchers to come to a strategic decision at an early stage, about technology being developed thus, saving on resources, hence minimizing failures.</p
GRaNIE and GRaNPA: inference and evaluation of enhancer-mediated gene regulatory networks
Enhancers play a vital role in gene regulation and are critical in mediating the impact of noncoding genetic variants associated with complex traits. Enhancer activity is a cell-type-specific process regulated by transcription factors (TFs), epigenetic mechanisms and genetic variants. Despite the strong mechanistic link between TFs and enhancers, we currently lack a framework for jointly analysing them in cell-type-specific gene regulatory networks (GRN). Equally important, we lack an unbiased way of assessing the biological significance of inferred GRNs since no complete ground truth exists. To address these gaps, we present GRaNIE (Gene Regulatory Network Inference including Enhancers) and GRaNPA (Gene Regulatory Network Performance Analysis). GRaNIE (https://git.embl.de/grp-zaugg/GR aNIE) builds enhancer-mediated GRNs based on covariation of chromatin accessibility and RNA-seq across samples (e.g. individuals), while GRaNPA (https://git.embl.de/grp-zaugg/GRaNPA) assesses the performance of GRNs for predicting cell-type-specific differential expression. We demonstrate their power by investigating gene regulatory mechanisms underlying the response of macrophages to infection, cancer and common genetic traits including autoimmune diseases. Finally, our methods identify the TF PURA as a putative regulator of pro-inflammatory macrophage polarisation
Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology:The impact of researchers choices on the selection of treatment targets using the experience sampling methodology
OBJECTIVE: One of the promises of the experience sampling methodology (ESM) is that a statistical analysis of an individual’s emotions, cognitions and behaviors in everyday-life could be used to identify relevant treatment targets. A requisite for clinical implementation is that outcomes of such person-specific time-series analyses are not wholly contingent on the researcher performing them. METHODS: To evaluate this, we crowdsourced the analysis of one individual patient’s ESM data to 12 prominent research teams, asking them what symptom(s) they would advise the treating clinician to target in subsequent treatment. RESULTS: Variation was evident at different stages of the analysis, from preprocessing steps (e.g., variable selection, clustering, handling of missing data) to the type of statistics and rationale for selecting targets. Most teams did include a type of vector autoregressive model, examining relations between symptoms over time. Although most teams were confident their selected targets would provide useful information to the clinician, not one recommendation was similar: both the number (0–16) and nature of selected targets varied widely. CONCLUSION: This study makes transparent that the selection of treatment targets based on personalized models using ESM data is currently highly conditional on subjective analytical choices and highlights key conceptual and methodological issues that need to be addressed in moving towards clinical implementation
Comprehensive global genome dynamics of Chlamydia trachomatis show ancient diversification followed by contemporary mixing and recent lineage expansion.
Chlamydia trachomatis is the world's most prevalent bacterial sexually transmitted infection and leading infectious cause of blindness, yet it is one of the least understood human pathogens, in part due to the difficulties of in vitro culturing and the lack of available tools for genetic manipulation. Genome sequencing has reinvigorated this field, shedding light on the contemporary history of this pathogen. Here, we analyze 563 full genomes, 455 of which are novel, to show that the history of the species comprises two phases, and conclude that the currently circulating lineages are the result of evolution in different genomic ecotypes. Temporal analysis indicates these lineages have recently expanded in the space of thousands of years, rather than the millions of years as previously thought, a finding that dramatically changes our understanding of this pathogen's history. Finally, at a time when almost every pathogen is becoming increasingly resistant to antimicrobials, we show that there is no evidence of circulating genomic resistance in C. trachomatis
Pregnancies and Time to Pregnancy in Women With and Without a PreviousChlamydia trachomatisInfection
Background: A Chlamydia trachomatis infection (chlamydia) can result
in tubal factor infertility in women. To assess if this association results in
fewer pregnant women, we aimed to assess pregnancy incidences and time
to pregnancy among women with a previous chlamydia infection compared
with women without one and who were participating in the Netherlands
Chlamydia Cohort Study (NECCST).
Methods: The NECCST is a cohort of women of reproductive age tested
for chlamydia in a chlamydia screening trial between 2008 and 2011 and
reinvited for NECCST in 2015 to 2016. Chlamydia status (positive/negative)
was defined using chlamydia screening trial–nucleic acid amplification test
results, chlamydia immunoglobulin G presence in serum, or self-reported
chlamydia infections. Data on pregnancies were collected via questionnaires in 2015–2016 and 2017–2018. Overall p
Longitudinal analysis of T-cell receptor repertoires reveals persistence of antigen-driven CD4+ and CD8+ T-cell clusters in systemic sclerosis
The T-cell receptor (TCR) is a highly polymorphic surface receptor that allows T-cells to recognize antigenic peptides presented on the major histocompatibility complex (MHC). Changes in the TCR repertoire have been observed in several autoimmune conditions, and these changes are suggested to predispose autoimmunity. Multiple lines of evidence have implied an important role for T-cells in the pathogenesis of Systemic Sclerosis (SSc), a complex autoimmune disease. One of the major questions regarding the roles of T-cells is whether expansion and activation of T-cells observed in the diseases pathogenesis is antigen driven. To investigate the temporal TCR repertoire dynamics in SSc, we performed high-throughput sequencing of CD4+ and CD8+ TCRβ chains on longitudinal samples obtained from four SSc patients collected over a minimum of two years. Repertoire overlap analysis revealed that samples taken from the same individual over time shared a high number of TCRβ sequences, indicating a clear temporal persistence of the TCRβ repertoire in CD4+ as well as CD8+ T-cells. Moreover, the TCRβs that were found with a high frequency at one time point were also found with a high frequency at the other time points (even after almost four years), showing that frequencies of dominant TCRβs are largely consistent over time. We also show that TCRβ generation probability and observed TCR frequency are not related in SSc samples, showing that clonal expansion and persistence of TCRβs is caused by antigenic selection rather than convergent recombination. Moreover, we demonstrate that TCRβ diversity is lower in CD4+ and CD8+ T-cells from SSc patients compared with memory T-cells from healthy individuals, as SSc TCRβ repertoires are largely dominated by clonally expanded persistent TCRβ sequences. Lastly, using “Grouping of Lymphocyte Interactions by Paratope Hotspots” (GLIPH2), we identify clusters of TCRβ sequences with homologous sequences that potentially recognize the same antigens and contain TCRβs that are persist in SSc patients. In conclusion, our results show that CD4+ and CD8+ T-cells are highly persistent in SSc patients over time, and this persistence is likely a result from antigenic selection. Moreover, persistent TCRs form high similarity clusters with other (non-)persistent sequences that potentially recognize the same epitopes. These data provide evidence for an antigen driven expansion of CD4+/CD8+ T-cells in SSc
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