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RationalePeripheral airway obstruction is a key feature of chronic obstructive pulmonary disease (COPD), but the mechanisms of airway loss are unknown. This study aims to identify the molecular and cellular mechanisms associated with peripheral airway obstruction in COPD.MethodsTen explanted lung specimens donated by patients with very severe COPD treated by lung transplantation and five unused donor control lungs were sampled using systematic uniform random sampling (SURS), resulting in 240 samples. These samples were further examined by micro-computed tomography (CT), quantitative histology and gene expression profiling.ResultsMicro-CT analysis showed that the loss of terminal bronchioles in COPD occurs in regions of microscopic emphysematous destruction with an average airspace size of ≥500 and InterpretationThe reduction in terminal bronchioles observed in lungs from patients with COPD occurs in a hot spot of microscopic emphysema, where there is upregulation of IFNG signalling, co-stimulatory immune checkpoint genes and genes related to the inflammasome pathway, and increased infiltration of immune cells. These could be potential targets for therapeutic interventions in COPD.

Background HEARTBiT is a whole blood-based gene profiling assay using the nucleic acid counting NanoString technology for the exclusionary diagnosis of acute cellular rejection in heart transplant patients. The HEARTBiT score measures the risk of acute cellular rejection in the first year following heart transplant, distinguishing patients with stable grafts from those at risk for acute cellular rejection. Here, we provide the analytical performance characteristics of the HEARTBiT assay and the results on pilot clinical validation. Methods We used purified RNA collected from PAXgene blood samples to evaluate the characteristics of a 12-gene panel HEARTBiT assay, for its linearity range, quantitative bias, precision, and reproducibility. These parameters were estimated either from serial dilutions of individual samples or from repeated runs on pooled samples. Results We found that all 12 genes showed linear behavior within the recommended assay input range of 125 ng to 500 ng of purified RNA, with most genes showing 3% or lower quantitative bias and around 5% coefficient of variation. Total variation resulting from unique operators, reagent lots, and runs was less than 0.02 units standard deviation (SD). The performance of the analytically validated assay (AUC = 0.75) was equivalent to what we observed in the signature development dataset. Conclusion The analytical performance of the assay within the specification input range demonstrated reliable quantification of the HEARTBiT score within 0.02 SD units, measured on a 0 to 1 unit scale. This assay may therefore be of high utility in clinical validation of HEARTBiT in future biomarker observational trials.

Many of the biomarkers in current clinical use have become accepted via debate, consensus, or merely the passage of time. Biomarkers can no longer become accepted in this way, as they would fail to meet the current regulatory standards of modern medicine. Contemporary biomarkers must be tested in highly regulated human clinical trials. This article focuses on various aspects of discovery, development, clinical validation, and translation of biomarkers. Keywords: biomarkers; validation; regulatory guidance

Tau post-translational modifications (PTMs) are associated with progressive tau accumulation and neuronal loss in tauopathies, including forms of frontotemporal lobar degeneration (FTLD) and Alzheimer’s disease (AD). Proteolytic cleavage of tau by active caspases, including caspase-6, represents an underexplored tau PTM implicated in tau pathology. Caspase-cleaved tau is toxic and prone to self-aggregation in experimental models. To elucidate the presence and temporal course of caspase activation, tau cleavage, and neuronal death, we generated two neoepitope monoclonal antibodies (mAbs) against caspase-6 tau proteolytic sites and cortical neurons from induced pluripotent stem cells (iPSCs) with the frontotemporal dementia (FTD)-causing V337M MAPT mutation. FTLD V337M MAPT and AD postmortem brains showed positivity for both cleaved tau mAbs as well as active caspase-6. Relative to isogenic wild-type MAPT controls, V337M MAPT neurons showed a time-dependent increase in pathogenic tau in the form of tau oligomers, caspase-cleaved tau, and p-tau. Accumulation of toxic tau species in 3-month V337M MAPT neurons also increased vulnerability to stress, which was pharmacologically rescued by caspase inhibition. We propose a model in which time-dependent accumulation of caspase-cleaved tau in V337M MAPT neurons promotes neurotoxicity that is reversed by caspase-6 inhibition. Caspase-cleaved tau may be a biomarker of tauopathy, and caspases could be viable targets for therapeutic intervention against tau pathogenesis in FTLD and other tauopathies.SignificanceThe mechanisms leading to tau pathology in frontotemporal dementia (FTD) and Alzheimer’s disease (AD) remain elusive. Experimental studies in AD demonstrate that tau cleavage by active caspase-6 contributes to tau pathology since cleaved tau may be toxic and prone to self-aggregation. Yet, the role of caspase-cleaved tau in promoting toxicity and cell death is unclear. Here, we generated two neoepitope monoclonal antibodies against caspase-6 tau and evaluated tau cleavage in postmortem human brains, iPSC-induced cortical neurons with the FTD-causing V337M MAPT mutation, and isogenic wild-type MAPT controls. Our results demonstrate a time-dependent accumulation of caspase-cleaved tau and increased neurotoxicity in the mutant iNs that is reversed by caspase-6 inhibition. Caspases could be viable therapeutic targets against tau pathology in tauopathies.

Background Chronic obstructive pulmonary disease (COPD) is an age-related condition that has been associated with early telomere attrition; the clinical implications of telomere shortening in COPD are not well known. In this study we aimed to determine the relationship of the epigenetic regulation of telomeric length in peripheral blood with the risk of exacerbations and hospitalization in patients with COPD. Methods Blood DNA methylation profiles were obtained from 292 patients with COPD enrolled in the placebo arm of the Macrolide Azithromycin to Prevent Rapid Worsening of Symptoms Associated with Chronic Obstructive Pulmonary Disease (MACRO) Study and who were followed for 1-year. We calculated telomere length based on DNA methylation markers (DNAmTL) and related this biomarker to the risk of exacerbation and hospitalization and health status (St. George Respiratory Questionnaire [SGRQ]) score over time using a Cox proportional hazards model. We also used linear models to investigate the associations of DNAmTL with the rates of exacerbation and hospitalization (adjusted for chronological age, lung function, race, sex, smoking, body mass index and cell composition). Results Participants with short DNAmTL demonstrated increased risk of exacerbation (P = 0.02) and hospitalization (P = 0.03) compared to those with longer DNAmTL. DNAmTL age acceleration was associated with higher rates of exacerbation (P = 1.35 × 10–04) and hospitalization (P = 5.21 × 10–03) and poor health status (lower SGRQ scores) independent of chronological age (P = 0.03). Conclusion Telomeric age based on blood DNA methylation is associated with COPD exacerbation and hospitalization and thus a promising biomarker for poor outcomes in COPD.

Background Many risk models for predicting mortality, hospitalizations, or both in patients with heart failure have been developed but do not have sufficient discriminatory ability. The purpose of this study was to identify predictive biomarkers of hospitalizations in heart failure patients using omics-based technologies applied to blood and electrical monitoring of the heart. Methods Blood samples were collected from 58 heart failure patients during enrollment into this study. Each patient wore a 48-hour Holter monitor that recorded the electrical activity of their heart. The blood samples were profiled for gene expression using microarrays and protein levels using multiple reaction monitoring. Statistical deconvolution was used to estimate cellular frequencies of common blood cells. Classification models were developed using clinical variables, Holter variables, cell types, gene transcripts, and proteins to predict hospitalization status. Results Of the 58 patients recruited, 13 were hospitalized within 3 months after enrollment. These patients had lower diastolic and systolic blood pressures, higher brain natriuretic peptide levels, most had higher blood creatinine levels, and had been diagnosed with heart failure for a longer time period. The best-performing clinical model had an area under the receiver operating characteristic curve of 0.76. An ensemble biomarker panel consisting of Holter variables, cell types, gene transcripts, and proteins had an area under the receiver operating characteristic curve of 0.88. Conclusions Molecular-based analyses as well as sensory data might provide sensitive biomarkers for the prediction of hospitalizations in heart failure patients. These approaches may be combined with traditional clinical models for the development of improved risk prediction models for heart failure.

Background Etiologies of acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are heterogeneous. We phenotyped severe AECOPD based on molecular pathogen detection of sputum samples collected at hospitalization of COPD patients and determined their outcomes. Methods We phenotyped 72 sputum samples of COPD patients who were hospitalized with a primary diagnosis of AECOPD using a molecular array that detected common bacterial and viral respiratory pathogens. Based on these results, the patients were classified into positive or negative pathogen groups. The pathogen-positive group was further divided into virus or bacteria subgroups. Admission day 1 blood samples were assayed for N-terminal prohormone brain natriuretic peptide, CRP, and complete blood counts. Results A total of 52 patients had a positive result on the array, while 20 patients had no pathogens detected. The most common bacterial pathogen detected was Haemophilus influenzae and the most common virus was rhinovirus. The pathogen-negative group had the worse outcomes with longer hospital stays (median 6.5 vs 5 days for bacteria-positive group, P=0.02) and a trend toward increased 1-year mortality (P=0.052). The bacteria-positive group had the best prognosis, whereas the virus-positive group had outcomes somewhere in between the bacteria-positive and pathogen-negative groups. Conclusion Molecular diagnostics on sputum can rapidly phenotype serious AECOPD into bacteria-, virus-, or pathogen-negative groups. The bacteria-positive group appears to have the best prognosis, while pathogen-negative group has the worst. These data suggest that AECOPD is a heterogeneous event and that accurate phenotyping of AECOPD may lead to novel management strategies that are personalized and more precise.

The incoming health records to the BC Cancer Registry are processed between two to three years behind real-time. In response, we developed a Natural Language Processing (NLP) software to automate the electronic chart review workflow. For the same task that costs hundreds of hours of trained labour, our pipeline extracts data within minutes. During preliminary evaluation, an MD student yielded 93.0% and 98.2% accuracies on a sample of operative and pathology breast cancer documents (for a total number of 2,563 data points processed). In comparison, our prototype achieved 89.6% and 91.4% accuracies, respectively. Future plans include improving the performance of the pipeline and eventually adapt it to accepting a more comprehensive range of electronic health records across cancer types and diseases. In the context of BC’s digital healthcare transformation initiatives, this customized software may provide time and cost savings for both the Registry and cancer researchers.

BACKGROUND: The transition from normal lung anatomy to minimal and established fibrosis is an important feature of the pathology of idiopathic pulmonary fibrosis (IPF). The purpose of this report is to examine the molecular and cellular mechanisms associated with this transition. METHODS: Pre-operative thoracic Multidetector Computed Tomography (MDCT) scans of patients with severe IPF (n = 9) were used to identify regions of minimal(n = 27) and established fibrosis(n = 27). MDCT, Micro-CT, quantitative histology, and next-generation sequencing were used to compare 24 samples from donor controls (n = 4) to minimal and established fibrosis samples. FINDINGS: The present results extended earlier reports about the transition from normal lung anatomy to minimal and established fibrosis by showing that there are activations of TGFBI, T cell co-stimulatory genes, and the down-regulation of inhibitory immune-checkpoint genes compared to controls. The expression patterns of these genes indicated activation of a field immune response, which is further supported by the increased infiltration of inflammatory immune cells dominated by lymphocytes that are capable of forming lymphoid follicles. Moreover, fibrosis pathways, mucin secretion, surfactant, TLRs, and cytokine storm-related genes also participate in the transitions from normal lung anatomy to minimal and established fibrosis. INTERPRETATION: The transition from normal lung anatomy to minimal and established fibrosis is associated with genes that are involved in the tissue repair processes, the activation of immune responses as well as the increased infiltration of CD4, CD8, B cell lymphocytes, and macrophages. These molecular and cellular events correlate with the development of structural abnormality of IPF and probably contribute to its pathogenesis. ispartof: EBIOMEDICINE vol:66 ispartof: location:Netherlands status: published

Objectives Antidepressants are first-line treatments for major depressive disorder (MDD), but 40–60% of patients will not respond, hence, predicting response would be a major clinical advance. Machine learning algorithms hold promise to predict treatment outcomes based on clinical symptoms and episode features. We sought to independently replicate recent machine learning methodology predicting antidepressant outcomes using the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) dataset, and then externally validate these methods to train models using data from the Canadian Biomarker Integration Network in Depression (CAN-BIND-1) dataset. Methods We replicated methodology from Nie et al (2018) using common algorithms based on linear regressions and decision trees to predict treatment-resistant depression (TRD, defined as failing to respond to 2 or more antidepressants) in the STAR*D dataset. We then trained and externally validated models using the clinical features found in both datasets to predict response (≥50% reduction on the Quick Inventory for Depressive Symptomatology, Self-Rated [QIDS-SR]) and remission (endpoint QIDS-SR score ≤5) in the CAN-BIND-1 dataset. We evaluated additional models to investigate how different outcomes and features may affect prediction performance. Results Our replicated models predicted TRD in the STAR*D dataset with slightly better balanced accuracy than Nie et al (70%-73% versus 64%-71%, respectively). Prediction performance on our external methodology validation on the CAN-BIND-1 dataset varied depending on outcome; performance was worse for response (best balanced accuracy 65%) compared to remission (77%). Using the smaller set of features found in both datasets generally improved prediction performance when evaluated on the STAR*D dataset. Conclusion We successfully replicated prior work predicting antidepressant treatment outcomes using machine learning methods and clinical data. We found similar prediction performance using these methods on an external database, although prediction of remission was better than prediction of response. Future work is needed to improve prediction performance to be clinically useful.

AimTau truncation (tr-tau) by active caspase-6 (aCasp-6) generates toxic tau fragments prone to self-aggregation. Yet, the relationship between aCasp-6, different forms of tr-tau, and hyperphosphorylated tau (p-tau) accumulation in human brains with Alzheimer’s disease (AD) and other tauopathies remains unclear.MethodsWe generated two neoepitope monoclonal antibodies against tr-tau sites (D402 and D13) targeted by aCasp-6. Then, we used 5-plex immunofluorescence to quantify the neuronal and astroglial burden of aCasp-6, tr-tau, p-tau, and their co-occurrence in healthy controls, AD, and primary tauopathies.ResultsCasp-6 activation was strongest in AD, followed by Pick’s disease (PiD), but almost absent in 4-repeat (4R) tauopathies. In neurons, the tr-tau burden was much more abundant in AD than in 4R tauopathies, and disproportionally higher when normalizing by p-tau pathology. Tr-tau astrogliopathy was detected in low numbers in 4R tauopathies. Unexpectedly, about half of tr-tau positive neurons in AD lacked p-tau aggregates.ConclusionsEarly modulation of aCasp-6 to reduce tr-tau pathology is a promising therapeutic strategy for AD, and possibly PiD, but is unlikely to benefit 4R tauopathies. The large percentage of tr-tau-positive neurons lacking p-tau suggests that not all neurons that are vulnerable to tau pathology are detected by a conventional p-tau Ser 202 antibody and that AD has distinct mechanisms of tangle formation. Therapeutic strategies against tr-tau pathology could be necessary to modulate tau abnormalities in AD. The disproportionally higher burden of tr-tau in AD supports the investigation of biofluid biomarkers against N-terminus tr-tau, which could detect AD and differentiate it from 4R tauopathies at a single patient level.3 - sentence summaryTau truncation (tr-tau) by active caspase-6 (aCasp-6) generates toxic tau fragments prone to self-aggregation, but the relationship between aCasp-6, tr-tau, and hyperphosphorylated tau (p-tau) accumulation in Alzheimer’s disease (AD) and other tauopathies remains unclear. We generated two neoepitope monoclonal antibodies against tr-tau sites (D402 and D13) targeted by aCasp-6 and used 5-plex immunofluorescence to quantify the neuronal and astroglial burden of aCasp-6, tr-tau, p-tau, and their co-occurrence in brains from healthy controls, AD, and primary tauopathies. We detected relatively high Casp-6 activation in AD, followed by Pick’s disease (PiD). aCasp-6 was almost absent in 4-repeat (4R) tauopathies, suggesting that early modulation of aCasp-6 to reduce tr-tau pathology is a promising therapeutic strategy in AD, and possibly PiD, but is unlikely to benefit 4R tauopathies.

Nawaf M Alotaibi,1,2 Virginia Chen,1,3,4 Zsuzsanna Hollander,1,3,4 Cameron J Hague,5 Darra T Murphy,5 Jonathon A Leipsic,5 Mari L DeMarco,1,6 J Mark FitzGerald,7,8 Bruce M McManus,1,3,4,6 Raymond T Ng,4,9 Don D Sin1,3,7 1Centre for Heart Lung Innovation, James Hogg Research Centre, St Paul’s Hospital, Vancouver, BC, Canada; 2Division of Pulmonary Medicine, Department of Medicine, College of Medicine, King Saud University, Riyadh, Saudi Arabia; 3Institute for Heart Lung Health, 4PROOF Centre of Excellence, 5Department of Radiology, St Paul’s Hospital, 6Department of Pathology and Laboratory Medicine, 7Division of Respiratory Medicine, Department of Medicine, University of British Columbia, 8The Lung Centre, Vancouver General Hospital, 9Department of Computer Sciences, University of British Columbia, Vancouver, BC, Canada Rationale: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) are caused by a variety of different etiologic agents. Our aim was to phenotype COPD exacerbations using imaging (chest X-ray [CXR] and computed tomography [CT]) and to determine the possible role of the blood tests (C-reactive protein [CRP], the N-terminal prohormone brain natriuretic peptide [NT-proBNP]) as diagnostic biomarkers. Materials and methods: Subjects who were hospitalized with a primary diagnosis of AECOPD and who had had CXRs, CT scans, and blood collection for CRP and NT-proBNP were assessed in this study. Radiologist blinded to the clinical and laboratory characteristics of the subjects interpreted their CXRs and CT images. ANOVA and Spearman’s correlation were performed to test for associations between these imaging parameters and the blood-based biomarkers NT-proBNP and CRP; logistic regression models were used to assess the performance of these biomarkers in predicting the radiological parameters. Results: A total of 309 subjects were examined for this study. Subjects had a mean age of 65.6±11.1 years, 66.7% of them were males, and 62.4% were current smokers, with a mean FEV1 54.4%±21.5% of predicted. Blood NT-proBNP concentrations were associated with cardiac enlargement (area under the curve [AUC] =0.72, P

Chronic Obstructive Pulmonary Disease (COPD) is an age-related condition that is linked to cellular senescence [1]. In COPD, contributors to cellular senescence include oxidative stress from environmental factors such as cigarette smoking and persistent lung inflammation [2]. These factors can also augment replicative senescence, which is characterised by progressive telomere attrition, ultimately leading to cell cycle arrest and death. Patients with COPD have shorter telomeres [3] and faster rates of telomere attrition [4] compared to controls; however, the clinical impact of cellular or replicative senescence in COPD remains uncertain. Footnotes This manuscript has recently been accepted for publication in the European Respiratory Journal . It is published here in its accepted form prior to copyediting and typesetting by our production team. After these production processes are complete and the authors have approved the resulting proofs, the article will move to the latest issue of the ERJ online. Please open or download the PDF to view this article. Conflict of interest: A.I. Hernandez Cordero has nothing to disclose. Conflict of interest: C.X. Yang has nothing to disclose. Conflict of interest: S. Milne has nothing to disclose. Conflict of interest: X. Li has nothing to disclose. Conflict of interest: Z. Hollander reports funding from Genome Canada, Genome British Columbia, Genome Quebec, the Canadian Institutes of Health Research, PROOF Centre of Excellence, St. Paul's Hospital Foundation and Providence Health Care for the Rapid Transition Program (RTP) cohort included in the manuscript. Conflict of interest: V. Chen reports funding from Genome Canada, Genome British Columbia, Genome Quebec, the Canadian Institutes of Health Research, PROOF Centre of Excellence, St. Paul's Hospital Foundation and Providence Health Care for the Rapid Transition Program (RTP) cohort included in the manuscript. Conflict of interest: R. Ng reports funding from Genome Canada, Genome British Columbia, Genome Quebec, the Canadian Institutes of Health Research, PROOF Centre of Excellence, St. Paul's Hospital Foundation and Providence Health Care for the Rapid Transition Program (RTP) cohort included in the manuscript. Conflict of interest: S.J. Tebbutt has nothing to disclose. Conflict of interest: J.M. Leung reports research research grant funding to their institution from Canadian Institutes of Health Research, Michael Smith Foundation for Health Research, BC Lung Association and Genome BC, outside the scope of the current manuscript. Conflict of interest: D.D. Sin declares grants from AstraZeneca for an investigator-initiated randomised controlled trial in COPD; consulting fees from Novaira for sitting on an advisory board for COPD; and honoraria for speaking engagements from AstraZeneca, Boehringer Ingelheim and Grifols, all in the 36 months prior to manuscript submission.

Aims Heart failure with preserved ejection fraction (HFpEF) accounts for 30–50% of patients with heart failure (HF). A major obstacle in HF management is the difficulty in differentiating between HFpEF and heart failure with reduced ejection fraction (HFrEF) using conventional clinical and laboratory investigations. The aim of this study is to develop robust transcriptomic and proteomic biomarker signatures that can differentiate HFpEF from HFrEF. Methods and results A total of 210 HF patients were recruited in participating institutions from the Alberta HEART study. An expert clinical adjudicating panel differentiated between patients with HFpEF and HFrEF. The discovery cohort consisted of 61 patients, and the replication cohort consisted of 70 patients. Transcriptomic and proteomic data were analysed to find panels of differentiating HFpEF from HFrEF. In the discovery cohort, a 22-transcript panel was found to differentiate HFpEF from HFrEF in male patients with a cross-validation AUC of 0.74, as compared with 0.70 for N-terminal pro-B-type natriuretic peptide (NT-proBNP) in those same patients. An ensemble of the transcript panel and NT-pro-BNP yielded a cross-validation AUC of 0.80. This performance improvement was also observed in the replication cohort. An ensemble of the transcriptomic panel with NT-proBNP produced a replication AUC of 0.90, as compared with 0.74 for NT-proBNP alone and 0.73 for the transcriptomic panel. Conclusions We have identified a male-specific transcriptomic biomarker panel that can differentiate between HFpEF and HFrEF. These biosignatures could be further replicated on other patients and potentially be developed into a blood test for better management of HF patients.

There is a great interest in developing biomarkers to enable precision medicine and improve health outcomes of patients with COPD. However, biomarker development is extremely challenging and expensive, and translation of research endeavors to date has been largely unsuccessful. In most cases, biomarkers fail because of poor replication of initial promising results in independent cohorts and/or inability to transfer the biomarker from a discovery platform to a clinical assay. Ultimately, new biomarker assays must address 5 questions for optimal clinical translation. They include the following: is the biomarker likely to be (1) superior (will the test outperform current standards?); (2) actionable (will the test change patient management?); (3) valuable (will the test improve patient outcomes?); (4) economical (will the implementation of the biomarker in the target population be cost-saving or cost-effective?); and (5) clinically deployable (is there a pathway for the biomarker and analytical technology to be implemented in a clinical laboratory?)? In this article we review some of the major barriers to biomarker development in COPD and provide possible solutions to overcome these limitations, enabling translation of promising biomarkers from discovery experiments to clinical implementation.

Background Adjuvant chemotherapy (ACT) improved survival in the NCIC Clinical Trials Group JBR.10 trial of resected stage IB/II non–small-cell lung cancer. A prognostic 15-gene expression signature was developed, which may also predict for benefit from ACT. An exploratory economic analysis was conducted to assess the potential cost-effectiveness of using the 15-gene signature in guiding ACT decisions. Methods A decision analytic model was populated by study patients with quantitative reverse transcription polymerase chain reaction tumor profiling, current costs, and quality-adjusted survival. Analysis was performed over the 6-year follow-up from the perspective of the Canadian public health care system in 2015 Canadian dollars (discounted 5%/year). Incremental cost-effectiveness and cost-utility ratios were determined for ACT versus observation using clinical stage, gene signature, or a combined approach to select treatment. Results The mean survival gain of ACT versus observation was higher using the gene signature (1.86 years) compared with clinical stage (1.28 years). Although more costly, ACT guided by the gene signature remained cost-effective at $10,421/life-year gained (95% confidence interval [CI], $466-$19,568 Canadian), comparable to stage-directed selection ($7081/life-year gained; 95% CI, −$2370 to $14,721; P = .52). Incremental cost-utility ratios were $13,452/quality-adjusted life-year (95% CI, $373-$31,949) and $9194/quality-adjusted life-year (95% CI, −$4104 to $23,952), respectively ( P = .53). Comparing the standard and test-and-treat approaches, use of the gene signature did not significantly alter survival compared with the standard strategy, but it reduced the ACT rate by 25%. Conclusion If validated, the use of the 15-gene expression signature to select patients for ACT may increase the survival gain of treatment in patients with high-risk stage IB/II non–small-cell lung cancer, while avoiding toxicities in low-risk patients.

Much research has been done within the social sciences on the interpretation and influence of stigma on human behaviour and health, which result in out-of-group exclusion, distancing, cognitive separation, status loss, discrimination, in-group pressure, and often lead to disengagement, non-adherence to treatment plan, and prescriptions by the doctor. However, little work has been conducted on computational identification of stigma in general and in social media discourse in particular. In this paper, we develop the annotation scheme for stigma based on social science theories, and perform a corpus study on the data from Facebook groups on vaccination. The data from pro-vaccination and anti-vaccination discussion groups are annotated by trained annotators and by MTurk annotators. We analyze the annotations using LIWC (Linguistic Inquiry and Word Count) software and TF-IDF in order to identify differentiating features between stigmatizing vs. non-stigmatizing content. Our corpus study lays a valuable foundation in computational modeling of social stigma, as it can serve as validation/interpretation of the social science theories through the prism of laypeople understanding. The annotated corpora can be subsequently used for automatic stigma identification. Moreover, the annotation scheme can be applied to study stigma across different themes and diseases and can be utilized during public health informational campaigns and health interventions.

Pulmonary exacerbations (PEx) are clinically impactful events for individuals with CF. Unfortunately, many CF individuals with PEx fail to regain their baseline lung function despite treatment. The objective of this study was to use unbiased proteomic technology to identify novel blood protein biomarkers that change following intravenous (IV) antibiotic treatment and to explore if changes correlate with clinical response by the end of treatment. Blood samples from 25 PEx events derived from 22 unique CF adults were collected within 24 hours of hospital admission, day 5, day 10, and IV antibiotic completion. Three-hundred and forty-six blood proteins were evaluated with label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) quantitative proteomics and immunoassays. Forty-seven plasma proteins changed significantly following 5 days of IV antibiotic treatment (q-value ≤ 0.10). Early change in IGF2R from hospital admission to day 5 correlated with overall change in symptom score (CFRSD-CRISS) by the end of treatment (r = −0.48, p-value = 0.04). Several plasma proteins identified and quantified by label-free LC-MS/MS changed early following treatment with IV antibiotics and many of these proteins are involved in complement activation and inflammatory/immune-related pathways. Early change in IGF2R correlated with symptom response following IV antibiotic treatment and requires further validation as a predictive biomarker of symptom response.

Background Nine mRNA transcripts associated with acute cellular rejection (ACR) in previous microarray studies were ported to the clinically amenable NanoString nCounter platform. Here we report the diagnostic performance of the resulting blood test to exclude ACR in heart allograft recipients: HEARTBiT. Methods Blood samples for transcriptomic profiling were collected during routine post-transplantation monitoring in 8 Canadian transplant centres participating in the Biomarkers in Transplantation initiative, a large (n = 1622) prospective observational study conducted between 2009 and 2014. All adult cardiac transplant patients were invited to participate (median age = 56 [17 to 71]). The reference standard for rejection status was histopathology grading of tissue from endomyocardial biopsy (EMB). All locally graded ISHLT ≥ 2R rejection samples were selected for analysis (n = 36). ISHLT 1R (n = 38) and 0R (n = 86) samples were randomly selected to create a cohort approximately matched for site, age, sex, and days post-transplantation, with a focus on early time points (median days post-transplant = 42 [7 to 506]). Results ISHLT ≥ 2R rejection was confirmed by EMB in 18 and excluded in 92 samples in the test set. HEARTBiT achieved 47% specificity (95% confidence interval [CI], 36%-57%) given ≥ 90% sensitivity, with a corresponding area under the receiver operating characteristic curve of 0.69 (95% CI, 0.56-0.81). Conclusions HEARTBiT’s diagnostic performance compares favourably to the only currently approved minimally invasive diagnostic test to rule out ACR, AlloMap (CareDx, Brisbane, CA) and may be used to inform care decisions in the first 2 months post-transplantation, when AlloMap is not approved, and most ACR episodes occur.

Background Effects of systemic corticosteroids on blood gene expression are largely unknown. This study determined gene expression signature associated with short-term oral prednisone therapy in patients with chronic obstructive pulmonary disease (COPD) and its relationship to 1-year mortality following an acute exacerbation of COPD (AECOPD). Methods Gene expression in whole blood was profiled using the Affymetrix Human Gene 1.1 ST microarray chips from two cohorts: 1) a prednisone cohort with 37 stable COPD patients randomly assigned to prednisone 30 mg/d + standard therapy for 4 days or standard therapy alone and 2) the Rapid Transition Program (RTP) cohort with 218 COPD patients who experienced AECOPD and were treated with systemic corticosteroids. All gene expression data were adjusted for the total number of white blood cells and their differential cell counts. Results In the prednisone cohort, 51 genes were differentially expressed between prednisone and standard therapy group at a false discovery rate of

In CF, pulmonary exacerbations (PEx) can lead to permanent loss in lung function and thus should be prevented. Previously, we identified a blood protein biosignature consisting of 6 proteins capable of predicting short-term PEx events in CF adults. In this study, we utilized blood samples from the placebo arm of a randomized controlled trial to assess whether this candidate protein biosignature was also capable of predicting short-term PEx events in CF children and adolescents. This pilot study provides preliminary evidence that blood inflammation can be monitored to predict short-term PEx risk in CF children and adolescents.

Background Azithromycin reduces pulmonary exacerbation (PEx) risk in cystic fibrosis (CF), but not all individuals benefit. The goal of this study was to discover blood protein biomarkers predictive of clinical response to azithromycin treatment in children and adolescents with CF. Methods Novel proteomic technologies were applied to examine 188 serum and plasma protein samples from 40 patients with CF who were randomized to receive azithromycin in the AZ0004 trial. Early changes in blood protein levels from day 0 to day 28 of treatment were examined in relation to changes in FEV1 percent predicted and weight by days 28 and 168, and to predict PEx risk by day 168. Results Early changes in the levels of 15 plasma proteins following 28 days of azithromycin significantly correlated with changes in FEV1 percent predicted from day 0 to day 28 (Q value Conclusions Early changes in blood protein biomarkers following azithromycin treatment were associated with short-term changes, but not longer term changes, in lung function. Early change in serum calprotectin level was predictive of response to azithromycin in terms of modifying PEx risk.

Background: The rate of lung-function decline in chronic obstructive pulmonary disease (COPD) varies substantially among individuals. We sought to develop and validate an individualized prediction model for forced expiratory volume at 1 second (FEV1) in current smokers with mild-to-moderate COPD.Methods: Using data from a large long-term clinical trial (the Lung Health Study), we derived mixed-effects regression models to predict future FEV1 values over 11 years according to clinical traits. We modelled heterogeneity by allowing regression coefficients to vary across individuals. Two independent cohorts with COPD were used for validating the equations.Results: We used data from 5594 patients (mean age 48.4 yr, 63% men, mean baseline FEV1 2.75 L) to create the individualized prediction equations. There was significant between-individual variability in the rate of FEV1 decline, with the interval for the annual rate of decline that contained 95% of individuals being -124 to -15 mL/yr for smokers and -83 to 15 mL/yr for sustained quitters. Clinical variables in the final model explained 88% of variation around follow-up FEV1. The C statistic for predicting severity grades was 0.90. Prediction equations performed robustly in the 2 external data sets.Interpretation: A substantial part of individual variation in FEV1 decline can be explained by easily measured clinical variables. The model developed in this work can be used for prediction of future lung health in patients with mild-to-moderate COPD.Trial registration: Lung Health Study ClinicalTrials.gov, no. NCT00000568; Pan-Canadian Early Detection of Lung Cancer Study ClinicalTrials.gov, no. NCT00751660

Introduction Smoking is the number one modifiable environmental risk factor for chronic obstructive pulmonary disease (COPD). Clinical, epidemiological and increasingly "omics" studies assess or adjust for current smoking status using only self-report, which may be inaccurate. Objective measures such as exhaled carbon monoxide (eCO) may also be problematic owing to limitations in the measurements and the relatively short half life of the molecule. In this study, we determined the impact of different case definitions of current cigarette smoking on gene expression in peripheral blood of patients with COPD. Methods Peripheral blood gene expression from 573 former- and current-smokers with COPD in the ECLIPSE study was used to find genes whose expression was associated with smoking status. Current smoking was defined using self-report, eCO concentrations, or both. Linear regression was used to determine the association of current smoking status with gene expression adjusting for age, sex and propensity score. Pathway enrichment analyses were performed on genes with P Result Using self-report or eCO, only two genes were differentially expressed between current and ex-smokers, with no enrichment in biological processes. When current smoking was defined using both eCO and self-report, four genes were differentially expressed (LRRN3, PID1, FUCA1, GPR15) with enrichment in 40 biological pathways related to metabolic processes, response to hypoxia and hormonal stimulus. Additionally, the combined definition provided better distributions of test statistics for differential gene expression. Conclusion A combined phenotype of eCO and self report allows for better discovery of genes and pathways related to current smoking. Implications Studies relying only on self report of smoking status to assess or adjust for the impact of smoking may not fully capture its effect and will lead to residual confounding of results.

BackgroundDNA methylation profiling of peripheral blood leukocytes has many research applications, and characterizing the changes in DNA methylation of specific white blood cell types between newborn and adult could add insight into the maturation of the immune system. As a consequence of developmental changes, DNA methylation profiles derived from adult white blood cells are poor references for prediction of cord blood cell types from DNA methylation data. We thus examined cell-type specific differences in DNA methylation in leukocyte subsets between cord and adult blood, and assessed the impact of these differences on prediction of cell types in cord blood.ResultsThough all cell types showed differences between cord and adult blood, some specific patterns stood out that reflected how the immune system changes after birth. In cord blood, lymphoid cells showed less variability than in adult, potentially demonstrating their naïve status. In fact, cord CD4 and CD8 T cells were so similar that genetic effects on DNA methylation were greater than cell type effects in our analysis, and CD8 T cell frequencies remained difficult to predict, even after optimizing the library used for cord blood composition estimation. Myeloid cells showed fewer changes between cord and adult and also less variability, with monocytes showing the fewest sites of DNA methylation change between cord and adult. Finally, including nucleated red blood cells in the reference library was necessary for accurate cell type predictions in cord blood.ConclusionChanges in DNA methylation with age were highly cell type specific, and those differences paralleled what is known about the maturation of the postnatal immune system.

BACKGROUND Cholesterol efflux capacity (CEC) is a measure of HDL function that, in cell-based studies, has demonstrated an inverse association with cardiovascular disease. The cell-based measure of CEC is complex and low-throughput. We hypothesized that assessment of the lipoprotein proteome would allow for precise, high-throughput CEC prediction. METHODS After isolating lipoprotein particles from serum, we used LC-MS/MS to quantify 21 lipoprotein-associated proteins. A bioinformatic pipeline was used to identify proteins with univariate correlation to cell-based CEC measurements and generate a multivariate algorithm for CEC prediction (pCE). Using logistic regression, protein coefficients in the pCE model were reweighted to yield a new algorithm predicting coronary artery disease (pCAD). RESULTS Discovery using targeted LC-MS/MS analysis of 105 training and test samples yielded a pCE model comprising 5 proteins (Spearman r = 0.86). Evaluation of pCE in a case–control study of 231 specimens from healthy individuals and patients with coronary artery disease revealed lower pCE in cases (P = 0.03). Derived within this same study, the pCAD model significantly improved classification (P < 0.0001). Following analytical validation of the multiplexed proteomic method, we conducted a case–control study of myocardial infarction in 137 postmenopausal women that confirmed significant separation of specimen cohorts in both the pCE (P = 0.015) and pCAD (P = 0.001) models. CONCLUSIONS Development of a proteomic pCE provides a reproducible high-throughput alternative to traditional cell-based CEC assays. The pCAD model improves stratification of case and control cohorts and, with further studies to establish clinical validity, presents a new opportunity for the assessment of cardiovascular health.

Background Severe inotrope-dependent acute heart failure (AHF) is associated with poor clinical outcomes. There are currently no well-defined blood biomarkers of response to treatment that can guide management or identify recovery in this patient population. In the present study, we characterized the levels of novel and emerging circulating biomarkers of heart failure in patients with AHF over the first 30 days of medical management or mechanical circulatory support (MCS). We hypothesized a shared a plasma proteomic treatment response would be identifiable in both patient groups, representing reversal of the AHF phenotype. Methods and results Time course plasma samples of the first 30 days of therapy, obtained from patients managed medically (n = 8) or with implantable MCS (n = 5), underwent semi-targeted and candidate biomarker analyses, using multiple reaction monitoring (MRM) mass spectrometry, antibody arrays, and enzyme-linked immunosorbent assays. Differentially expressed proteins were identified using robust limma for MRM and antibody array data. Patients managed medically or with implantable MCS had a shared proteomic signature of six plasma proteins: circulating cardiotrophin 1, cardiac troponin T, clusterin, and dickopff 1 increased, while levels of C-reactive protein and growth differentiation factor 15 decreased in both groups over the 30 day time course. Conclusions We have characterized the temporal proteomic signature of clinical recovery in AHF patients managed medically or with MCS, over the first 30 days of treatment. Changes in biomarker expression over the time course of treatment may provide a basis for understanding the biological basis of AHF, potentially identifying novel markers and pathophysiologic mechanisms of recovery.

Chronic obstructive pulmonary disease (COPD) is one of the major causes of morbidity and mortality in the world. Regrettably, there are no biomarkers to objectively diagnose COPD exacerbations, which are the major drivers of hospitalization and deaths from COPD. Moreover, there are no biomarkers to guide therapeutic choices or to risk stratify patients for imminent exacerbations and no objective biomarkers of disease activity or disease progression. Although there has been a tremendous investment in COPD biomarker discovery over the past 2 decades, clinical translation and implementation have not matched these efforts. In this article, we outline the challenges of biomarker development in COPD and provide an overview of a developmental pipeline that may be able to surmount these challenges and bring novel biomarker solutions to accelerate therapeutic discoveries and to improve the care and outcomes of the millions of individuals worldwide with COPD.

BACKGROUND Up-to-date estimates of burden of diseases are required for evidence-based decision-making. The objectives of this study were to determine the excess costs of COPD and its trend from 2001 to 2010 in British Columbia, Canada. METHODS We used British Columbia's administrative health data to construct a cohort of patients with COPD and a matched comparison cohort of subjects without COPD. We followed each patient from the time of first COPD-related health-care event (or equivalent time for the comparison cohort). Direct medical costs (in 2010 Canadian dollars [$]) were calculated based on billing records pertaining to hospital admissions, outpatient services use, medication dispensations, and community care services. We determined the excess medical costs of COPD by calculating the difference in overall medical costs between the COPD and the comparison cohorts. RESULTS The COPD and comparison cohorts comprised 153,570 and 246,801 people, respectively (for both cohorts, mean age at entry was 66.9 years; 47.2% female patients). The excess costs of COPD during the study period were $5,452 per patient-year. Inpatient, outpatient, medication, and community care costs were responsible for 57%, 16%, 22%, and 5% of the excess costs, respectively. Excess costs increased by $296/person-y (P ≤ .01), with hospital costs demonstrating the largest increase over time ($258/person-y; P ≤ .01). CONCLUSIONS The direct economic burden of COPD is high and has increased significantly between 2001 and 2010 over and above the increase in the health-care costs of the general population. Further investigation is required to elucidate the underlying reasons for the temporal increase in COPD direct costs.

Despite the significant morbidity and mortality related to pulmonary exacerbations in cystic fibrosis (CF), there remains no reliable predictor of imminent exacerbation.To identify blood-based biomarkers to predict imminent (4 months from stable blood draw) CF pulmonary exacerbations using targeted proteomics.104 subjects provided plasma samples when clinically stable and were randomly split into discovery (n=70) and replication (n=34) cohorts. Multiple reaction monitoring mass spectrometry (MRM-MS) was used to measure 117 peptides (79 proteins) from plasma. Plasma proteins with differential abundance between subjects who did versus did not develop an imminent exacerbation were analysed and proteins with fold difference1.5 between the groups were included in an MRM-MS classifier model to predict imminent exacerbations. Performance characteristics were compared with clinical predictors and candidate plasma protein biomarkers.Six proteins were included in the final MRM-MS protein panel. The area under the curve (AUC) for the prediction of imminent exacerbations was highest for the MRM-MS protein panel (AUC 0.74) in comparison to FEV1% predicted (AUC 0.55) and the top candidate plasma protein biomarkers, including C-reactive protein (AUC 0.61) and interleukin-6 (AUC 0.60). The MRM-MS protein panel performed similarly in the replication cohort (AUC 0.73).Using MRM-MS, a six-protein panel measured from plasma can distinguish individuals with versus without an imminent exacerbation. With further replication and assay development, this biomarker panel may be clinically applicable for prediction of exacerbations in individuals with CF.

Background Systemic inflammation decreases with IV antibiotics during the treatment of CF pulmonary exacerbations (PEx). We used multiple reaction monitoring mass spectrometry and immunoassays to monitor blood proteins during PEx treatment to determine if early changes could be used to predict PEx outcomes following treatment. Methods Blood samples from 25 PEx (22 unique adults) were collected within 24h of admission, day 5, day 10, and at IV antibiotic completion. Ninety-two blood proteins involved in host immunity and inflammation were measured. Results Levels of several blood proteins changed from admission to end of IV antibiotics, most increasing with treatment. Early changes (admission to day 5) in fibrinogen levels had the strongest correlation with overall improvement in CFRSD-CRISS and FEV 1 % predicted by the end of treatment. Conclusions Several plasma proteins changed significantly with IV antibiotics. Future studies will evaluate fibrinogen as an early biomarker of PEx treatment response in CF.

RATIONALE: Chronic obstructive pulmonary disease (COPD) is the third leading cause of death worldwide. Gene expression profiling across multiple regions of the same lung identified genes significantly related to emphysema.OBJECTIVE: To determine whether the lung and epithelial expression of 127 emphysema-related genes is also related to lung function in independent cohorts and whether any of these genes could be used as biomarkers in the peripheral blood of COPD patients.METHODS: We determined whether the expression levels of the 127 emphysema genes were under genetic control in lung tissue (n=1,111). We then determined whether the mRNA levels of these genes in lung tissue (n=727), small airway epithelial cells (n=238) and peripheral blood (n=620) were significantly related to lung function measurements.MEASUREMENTS AND MAIN RESULTS: The expression 63 of the 127 (50%) genes was under genetic control in lung tissue. The lung and epithelial mRNA expression of a subset of the emphysema-associated genes, including ASRGL1, LPHN2, and EDNRB, were strongly associated with lung function. In peripheral blood, the expression of 40 genes was significantly associated with lung function; of which 29 (73%) genes were also associated with lung function in lung tissue yet with opposite direction of effect for 24 of the 29 genes including those involved in hypoxia and B cell related responses.CONCLUSION: Integrative genomics uncovered a significant overlap of emphysema genes associations with lung function between lung and blood with opposite directions between the two. The results support the use of peripheral blood to detect disease biomarkers.