Dendritic cell immunotherapy followed by cART interruption during HIV-1 infection induces plasma protein markers of cellular immunity and neutrophil recruitment

Objectives To characterize the host response to dendritic cell-based immunotherapy and subsequent combined antiretroviral therapy (cART) interruption in HIV-1-infected individuals at the plasma protein level. Design An autologous dendritic cell (DC) therapeutic vaccine was administered to HIV-infected individuals, stable on cART. The effect of vaccination was evaluated at the plasma protein level during the period preceding cART interruption, during analytical therapy interruption and at viral reactivation. Healthy controls and post-exposure prophylactically treated healthy individuals were included as controls. Methods Plasma marker (‘analyte’) levels including cytokines, chemokines, growth factors, and hormones were measured in trial participants and control plasma samples using a multiplex immunoassay. Analyte levels were analysed using principle component analysis, cluster analysis and limma. Blood neutrophil counts were analysed using linear regression. Results Plasma analyte levels of HIV-infected individuals are markedly different from those of healthy controls and HIV-negative individuals receiving post-exposure prophylaxis. Viral reactivation following cART interruption also affects multiple analytes, but cART interruption itself only has only a minor effect. We find that Thyroxine-Binding Globulin (TBG) levels and late-stage neutrophil numbers correlate with the time off cART after DC vaccination. Furthermore, analysis shows that cART alters several regulators of blood glucose levels, including C-peptide, chromogranin-A and leptin. HIV reactivation is associated with the upregulation of CXCR

Proteomic changes in serum of first onset, antidepressant drug-naïve major depression patients

Major depressive disorder (MDD) is a complex and multi-factorial disorder. Although genetic factors and other molecular aspects of MDD have been widely studied, the underlying pathological mechanisms are still mostly unknown. We sought to investigate the pathophysiology of MDD by identifying and characterising serum molecular differences and their correlation to symptom severity in first onset, antidepressant drug-naïve MDD patients. We performed an exploratory molecular profiling study on serum samples of MDD patients and controls using multiplex immunoassay and label-free liquid chromatography mass spectrometry in data independent mode (LC-MSE). We included two independent cohorts of first onset, antidepressant drug-naïve MDD patients (n = 23 and 15) and matched controls (n = 42 and 21) in our study in order to validate the results. The main outcome included the following list of circulatory molecules changing and/or correlating to symptom severity: angiotensin-converting enzyme, acute phase proteins (e.g. ferritin and serotransferrin), brain-derived neurotrophic factor, complement component C4-B, cortisol, cytokines (e.g. macrophage migration inhibitory factor and interleukin-16), extracellular newly identified receptor for advanced glycosylation end products-binding protein, growth hormone and superoxide dismutase-1. This study provides evidence of an increased pro-inflammatory and oxidative stress response, followed by a hyperactivation of the HPA-axis in the acute stages of first onset MDD, as well as a dysregulation in growth factor pathways. These findings help to elucidate MDD related pathways in more detail and further studies may lead to identification of novel drug targets, inc

Multimodel inference for biomarker development: an application to schizophrenia

In the present study, to improve the predictive performance of a model and its reproducibility when applied to an independent data set, we investigated the use of multimodel inference to predict the probability of having a complex psychiatric disorder. We formed training and test sets using proteomic data (147 peptides from 77 proteins) from twoindependent collections of first-onset drug-naive schizophrenia patients and controls. A set of prediction models was produced by applying lasso regression with repeated tenfold cross-validation to the training set. We used feature extraction and model averaging across the set of models to form two prediction models. The resulting models clearly demonstrated the utility of a multimodel based approach to make good (training set AUC > 0.80) and reproducible predictions (test set AUC > 0.80) for the probability of having schizophrenia. Moreover, we identified four proteins (five peptides) whose effect on the probability of having schizophrenia was modified by sex, one of which was a novel potential biomarker of schizophrenia, foetal haemoglobin. The evidence of effect modification suggests that future schizophrenia studies should be conducted in males and females separately. Future biomarker studies should consider adopting a multimodel approach and going beyond the main effects of features

Development of a blood-based molecular biomarker test for identification of schizophrenia before disease onset

Recent research efforts have progressively shifted towards preventative psychiatry and prognostic identification of individuals before disease onset. We describe the development of a serum biomarker test for the identification of individuals at risk of developing schizophrenia based on multiplex immunoassay profiling analysis of 957 serum samples. First, we conducted a meta-analysis of five independent cohorts of 127 first-onset drug-naive schizophrenia patients and 204 controls. Using least absolute shrinkage and selection operator regression, we identified an optimal panel of 26 biomarkers that best discriminated patients and controls. Next, we successfully validated this biomarker panel using two independent validation cohorts of 93 patients and 88 controls, which yielded an area under the curve (AUC) of 0.97 (0.95-1.00) for schizophrenia detection. Finally, we tested its predictive performance for identifying patients before onset of psychosis using two cohorts of 445 pre-onset or at-risk individuals. The predictive performance achieved by the panel was excellent for identifying USA military personnel (AUC: 0.90 (0.86-0.95)) and help-seeking prodromal individuals (AUC: 0.82 (0.71-0.93)) who developed schizophrenia up to 2 years after baseline sampling. The performance increased further using the latter cohort following the incorporation of CAARMS (Comprehensive Assessment of At-Risk Mental State) positive subscale symptom scores into the model (AUC: 0.90 (0.82-0.98)). The current findings may represent the first successful step towards a test that could address the clinical need for early intervention in psychiatry. Further developments of a combined molecular/symptom-based test will aid clinicians in the identification of vulnerable patients early in the disease process, allowing more effective therapeutic intervention before overt disease onset

Erratum: Global, regional, and national comparative risk assessment of 84 behavioural, environmental and occupational, and metabolic risks or clusters of risks for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017

Interpretation: By quantifying levels and trends in exposures to risk factors and the resulting disease burden, this assessment offers insight into where past policy and programme efforts might have been successful and highlights current priorities for public health action. Decreases in behavioural, environmental, and occupational risks have largely offset the effects of population growth and ageing, in relation to trends in absolute burden. Conversely, the combination of increasing metabolic risks and population ageing will probably continue to drive the increasing trends in non-communicable diseases at the global level, which presents both a public health challenge and opportunity. We see considerable spatiotemporal heterogeneity in levels of risk exposure and risk-attributable burden. Although levels of development underlie some of this heterogeneity, O/E ratios show risks for which countries are overperforming or underperforming relative to their level of development. As such, these ratios provide a benchmarking tool to help to focus local decision making. Our findings reinforce the importance of both risk exposure monitoring and epidemiological research to assess causal connections between risks and health outcomes, and they highlight the usefulness of the GBD study in synthesising data to draw comprehensive and robust conclusions that help to inform good policy and strategic health planning

The Consumption of Counterfeit Goods: `Here Be Pirates?'

Social science, policy and popular discourse around counterfeiting regularly position consumers of counterfeit goods as part of a technological elite or as motivated by anti-capitalist or anti-corporate positions. In order to explore this construction and highlight its associated limitations, this article presents quantitative data collected through postal and web-based questionnaires looking at the frequency, location and motivations for the purchase of counterfeit leisure items for consumers in the United Kingdom.The article suggests that the purchase and consumption of counterfeit goods is commonplace across a broader variety of age, gender and socio-economic status categories than often assumed.The study also highlights the value of viewing the consumption of counterfeit goods as social and situated, occurring within existing social networks and familiar locations, and as closely related to other consumption practices