LabKey Server: an open source platform for scientific data integration, analysis and collaboration

Sexual behaviour among Kenyan adolescents enrolled in an efficacy trial of a smartphone game to prevent HIV: a cross-sectional analysis of baseline data

Sexual behaviour of adolescents is contextual, with various determinants affecting sexual activity and age of sexual debut. Insight into sexual activity among young adolescents has the potential to influence appropriate sexual and reproductive health interventions. For this analysis, adolescents were recruited as part of the Tumaini smartphone game efficacy trial. Data collection included a self-administered behavioural survey and blood test for HIV and HSV-2. Descriptive statistics were calculated for demographics and measures of sexual behaviour and behavioural intent based on gender and sexual experience, with associations assessed using chi-square tests, t-tests and Wilcoxon rank sum tests as appropriate. We enrolled 996 adolescents, mean age 14 years and 2.2% HSV-2 positivity. Overall, 15% of the adolescents were sexually experienced, this being associated with lower socio-economic status (p = 0.01), household food insecurity (p = 0.008), a living situation without both parents (p < 0.01), substance use (p = 0.02), no adult conversation about future goals (p = 0.003), conversations about condoms (p = 0.01), with some gender disparity within these factors. Among those sexually experienced, 21.7% reported unwilling sex; 17.5% had engaged in transactional sex; 57.8% had willing first sex, of whom 60.9% reported no condom use. Among those abstaining, female adolescents were less likely to contemplate condom use at first sex (p = 0.006). Our findings determine that young sexually active adolescents are likely engaging in unprotected sex and having unwilling sexual experiences. Socio-economic status, living situation and parental monitoring remain significant factors associated with sexual experience among young adolescents. In this context, early adolescence is an opportunity to provide age- and developmentally appropriate education about safer sex practices.Trial registration: ClinicalTrials.gov identifier: NCT04437667.

Interventional study to improve pertussis and influenza vaccination uptake in pregnant women

OBJECTIVES

Pertussis and influenza are endemic infections and associated with relevant morbidity and mortality in newborns and young infants. The Swiss Federal Office of Public Health has recommended influenza vaccination since 2011 and pertussis vaccination in pregnancy (ViP) since 2013 and expanded to repetition in each pregnancy since 2017. ViP is safe and effective in preventing severe diseases, but implementation is a challenge. We hypothesized that the proportion of women receiving ViP is persistently low despite existing national recommendations. Our primary objective was to compare the proportion of pertussis and influenza vaccine recommendations for and its acceptance by pregnant women before and after an information campaign tailored to obstetricians. Secondly, we aimed to identify reasons for missing or declining ViP.

STUDY DESIGN

We conducted a prospective, single-center, single-arm implementation study in the maternity ward at the University Women's Hospital Basel. We performed standardized interviews with women hospitalized for postpartum care before (October to December 2019, Phase 1, n = 262) and after an information campaign (October to December 2020, Phase 2, n = 233) and compared categorical variables using chi-squared or Fisher's exact test and continuous variables using Whitney Mann U test.

RESULTS

We found no significant differences in the proportion of recommendation for pertussis ViP (80 % vs. 84 %, p = 0.25) and implementation (76 % vs. 78 %, p = 0.63) between Phase 1 and 2. Main reasons for missing or declining vaccinations were lack of recommendation (62.8 %) and safety concerns regarding the unborn child (17.7 %). In contrast, the proportion of recommendation for influenza ViP (45 % vs. 63 %, p < 0.001) and implementation (29 % vs. 43 %, p < 0.001) increased significantly.

CONCLUSION

Proactive recommendations by obstetricians play a key role in the implementation of ViP but is still insufficient in our setting. We believe that future efforts should aim to explore possible hurdles that impede recommendations by obstetricians for ViP. The focus should be on the needs and experiences of obstetricians in private practice, but also other health care professionals involved in care of pregnant women. Local campaigns do not seem effective enough, therefore national campaigns with new strategies are desirable.

A genotype-to-phenotype approach suggests under-reporting of single nucleotide variants in nephrocystin-1 (NPHP1) related disease (UK 100,000 Genomes Project)

Autosomal recessive whole gene deletions of nephrocystin-1 (NPHP1) result in abnormal structure and function of the primary cilia. These deletions can result in a tubulointerstitial kidney disease known as nephronophthisis and retinal (Senior-Løken syndrome) and neurological (Joubert syndrome) diseases. Nephronophthisis is a common cause of end-stage kidney disease (ESKD) in children and up to 1% of adult onset ESKD. Single nucleotide variants (SNVs) and small insertions and deletions (Indels) have been less well characterised. We used a gene pathogenicity scoring system (GenePy) and a genotype-to-phenotype approach on individuals recruited to the UK Genomics England (GEL) 100,000 Genomes Project (100kGP) (n = 78,050). This approach identified all participants with NPHP1-related diseases reported by NHS Genomics Medical Centres and an additional eight participants. Extreme NPHP1 gene scores, often underpinned by clear recessive inheritance, were observed in patients from diverse recruitment categories, including cancer, suggesting the possibility of a more widespread disease than previously appreciated. In total, ten participants had homozygous CNV deletions with eight homozygous or compound heterozygous with SNVs. Our data also reveals strong in-silico evidence that approximately 44% of NPHP1 related disease may be due to SNVs with AlphaFold structural modelling evidence for a significant impact on protein structure. This study suggests historical under-reporting of SNVS in NPHP1 related diseases compared with CNVs.

H3N2 influenza hemagglutination inhibition method qualification with data driven statistical methods for human clinical trials

Introduction

Hemagglutination inhibition (HAI) antibody titers to seasonal influenza strains are important surrogates for vaccine-elicited protection. However, HAI assays can be variable across labs, with low sensitivity across diverse viruses due to lack of standardization. Performing qualification of these assays on a strain specific level enables the precise and accurate quantification of HAI titers. Influenza A (H3N2) continues to be a predominant circulating subtype in most countries in Europe and North America since 1968 and is thus a focus of influenza vaccine research.

Methods

As a part of the National Institutes of Health (NIH)-funded Collaborative Influenza Vaccine Innovation Centers (CIVICs) program, we report on the identification of a robust assay design, rigorous statistical analysis, and complete qualification of an HAI assay using A/Texas/71/2017 as a representative H3N2 strain and guinea pig red blood cells and neuraminidase (NA) inhibitor oseltamivir to prevent NA-mediated agglutination.

Results

This qualified HAI assay is precise (calculated by the geometric coefficient of variation (GCV)) for intermediate precision and intra-operator variability, accurate calculated by relative error, perfectly linear (slope of -1, R-Square 1), robust (<25% GCV) and depicts high specificity and sensitivity. This HAI method was successfully qualified for another H3N2 influenza strain A/Singapore/INFIMH-16-0019/2016, meeting all pre-specified acceptance criteria.

Discussion

These results demonstrate that HAI qualification and data generation for new influenza strains can be achieved efficiently with minimal extra testing and development. We report on a qualified and adaptable influenza serology method and analysis strategy to measure quantifiable HAI titers to define correlates of vaccine mediated protection in human clinical trials.

Challenges and opportunities for implementing hypofractionated radiotherapy in Africa: lessons from the HypoAfrica clinical trial

The rising cancer incidence and mortality in sub-Saharan Africa (SSA) warrants an increased focus on adopting or developing approaches that can significantly increase access to treatment in the region. One such approach recommended by the recent Lancet Oncology Commission for sub-Saharan Africa is hypofractionated radiotherapy (HFRT), which can substantially increase access to radiotherapy by reducing the overall duration of time (in days) each person spends being treated. Here we highlight challenges in adopting such an approach identified during the implementation of the HypoAfrica clinical trial. The HypoAfrica clinical trial is a longitudinal, multicentre study exploring the feasibility of applying HFRT for prostate cancer in SSA. This study has presented an opportunity for a pragmatic assessment of potential barriers and facilitators to adopting HFRT. Our results highlight three key challenges: quality assurance, study harmonisation and machine maintenance. We describe solutions employed to resolve these challenges and opportunities for longer term solutions that can facilitate scaling-up use of HFRT in SSA in clinical care and multicentre clinical trials. This report provides a valuable reference for the utilisation of radiotherapy approaches that increase access to treatment and the conduct of high-quality large-scale/multi-centre clinical trials involving radiotherapy.

Trial registration

Not available yet.

Italian, European, and international neuroinformatics efforts: An overview

Neuroinformatics is a research field that focusses on software tools capable of identifying, analysing, modelling, organising and sharing multiscale neuroscience data. Neuroinformatics has exploded in the last two decades with the emergence of the Big Data phenomenon, characterised by the so-called 3Vs (volume, velocity and variety), which provided neuroscientists with an improved ability to acquire and process data faster and more cheaply thanks to technical improvements in clinical, genomic and radiological technologies. This situation has led to a 'data deluge', as neuroscientists can routinely collect more study data in a few days than they could in a year just a decade ago. To address this phenomenon, several neuroimaging-focussed neuroinformatics platforms have emerged, funded by national or transnational agencies, with the following goals: (i) development of tools for archiving and organising analytical data (XNAT, REDCap and LabKey); (ii) development of data-driven models evolving from reductionist approaches to multidimensional models (RIN, IVN, HBD, EuroPOND, E-DADS and GAAIN BRAIN); and (iii) development of e-infrastructures to provide sufficient computational power and storage resources (neuGRID, HBP-EBRAINS, LONI and CONP). Although the scenario is still fragmented, there are technological and economical attempts at both national and international levels to introduce high standards for open and Findable, Accessible, Interoperable and Reusable (FAIR) neuroscience worldwide.

Local data commons: the sleeping beauty in the community of data commons

Background

Public Data Commons (PDC) have been highlighted in the scientific literature for their capacity to collect and harmonize big data. On the other hand, local data commons (LDC), located within an institution or organization, have been underrepresented in the scientific literature, even though they are a critical part of research infrastructure. Being closest to the sources of data, LDCs provide the ability to collect and maintain the most up-to-date, high-quality data within an organization, closest to the sources of the data. As a data provider, LDCs have many challenges in both collecting and standardizing data, moreover, as a consumer of PDC, they face problems of data harmonization stemming from the monolithic harmonization pipeline designs commonly adapted by many PDCs. Unfortunately, existing guidelines and resources for building and maintaining data commons exclusively focus on PDC and provide very little information on LDC.

Results

This article focuses on four important observations. First, there are three different types of LDC service models that are defined based on their roles and requirements. These can be used as guidelines for building new LDC or enhancing the services of existing LDC. Second, the seven core services of LDC are discussed, including cohort identification and facilitation of genomic sequencing, the management of molecular reports and associated infrastructure, quality control, data harmonization, data integration, data sharing, and data access control. Third, instead of commonly developed monolithic systems, we propose a new data sharing method for data harmonization that combines both divide-and-conquer and bottom-up approaches. Finally, an end-to-end LDC implementation is introduced with real-world examples.

Conclusions

Although LDCs are an optimal place to identify and address data quality issues, they have traditionally been relegated to the role of passive data provider for much larger PDC. Indeed, many LDCs limit their functions to only conducting routine data storage and transmission tasks due to a lack of information on how to design, develop, and improve their services using limited resources. We hope that this work will be the first small step in raising awareness among the LDCs of their expanded utility and to publicize to a wider audience the importance of LDC.

Establishing a colorectal cancer research database from routinely collected health data: the process and potential from a pilot study

Objective

Colorectal cancer is a common cause of death and morbidity. A significant amount of data are routinely collected during patient treatment, but they are not generally available for research. The National Institute for Health Research Health Informatics Collaborative in the UK is developing infrastructure to enable routinely collected data to be used for collaborative, cross-centre research. This paper presents an overview of the process for collating colorectal cancer data and explores the potential of using this data source.

Methods

Clinical data were collected from three pilot Trusts, standardised and collated. Not all data were collected in a readily extractable format for research. Natural language processing (NLP) was used to extract relevant information from pseudonymised imaging and histopathology reports. Combining data from many sources allowed reconstruction of longitudinal histories for each patient that could be presented graphically.

Results

Three pilot Trusts submitted data, covering 12 903 patients with a diagnosis of colorectal cancer since 2012, with NLP implemented for 4150 patients. Timelines showing individual patient longitudinal history can be grouped into common treatment patterns, visually presenting clusters and outliers for analysis. Difficulties and gaps in data sources have been identified and addressed.

Discussion

Algorithms for analysing routinely collected data from a wide range of sites and sources have been developed and refined to provide a rich data set that will be used to better understand the natural history, treatment variation and optimal management of colorectal cancer.

Conclusion

The data set has great potential to facilitate research into colorectal cancer.

A SARS-CoV-2 Spike Ferritin Nanoparticle Vaccine Is Protective and Promotes a Strong Immunological Response in the Cynomolgus Macaque Coronavirus Disease 2019 (COVID-19) Model

The COVID-19 pandemic has had a staggering impact on social, economic, and public health systems worldwide. Vaccine development and mobilization against SARS-CoV-2 (the etiologic agent of COVID-19) has been rapid. However, novel strategies are still necessary to slow the pandemic, and this includes new approaches to vaccine development and/or delivery that will improve vaccination compliance and demonstrate efficacy against emerging variants. Here, we report on the immunogenicity and efficacy of a SARS-CoV-2 vaccine comprising stabilized, pre-fusion spike protein trimers displayed on a ferritin nanoparticle (SpFN) adjuvanted with either conventional aluminum hydroxide or the Army Liposomal Formulation QS-21 (ALFQ) in a cynomolgus macaque COVID-19 model. Vaccination resulted in robust cell-mediated and humoral responses and a significant reduction in lung lesions following SARS-CoV-2 infection. The strength of the immune response suggests that dose sparing through reduced or single dosing in primates may be possible with this vaccine. Overall, the data support further evaluation of SpFN as a SARS-CoV-2 protein-based vaccine candidate with attention to fractional dosing and schedule optimization.

Quantitative imaging biomarkers of immune-related adverse events in immune-checkpoint blockade-treated metastatic melanoma patients: a pilot study

PURPOSE

To develop quantitative molecular imaging biomarkers of immune-related adverse event (irAE) development in malignant melanoma (MM) patients receiving immune-checkpoint inhibitors (ICI) imaged with 18F-FDG PET/CT.

METHODS

18F-FDG PET/CT images of 58 MM patients treated with anti-PD-1 or anti-CTLA-4 ICI were retrospectively analyzed for indication of irAE. Three target organs, most commonly affected by irAE, were considered: bowel, lung, and thyroid. Patient charts were reviewed to identify which patients experienced irAE, irAE grade, and time to irAE diagnosis. Target organs were segmented using a convolutional neural network (CNN), and novel quantitative imaging biomarkers - SUV percentiles (SUVX%) of 18F-FDG uptake within the target organs - were correlated with the clinical irAE status. Area under the receiver-operating characteristic curve (AUROC) was used to quantify irAE detection performance. Patients who did not experience irAE were used to establish normal ranges for target organ 18F-FDG uptake.

RESULTS

A total of 31% (18/58) patients experienced irAE in the three target organs: bowel (n=6), lung (n=5), and thyroid (n=9). Optimal percentiles for identifying irAE were bowel (SUV95%, AUROC=0.79), lung (SUV95%, AUROC=0.98), and thyroid (SUV75%, AUROC=0.88). Optimal cut-offs for irAE detection were bowel (SUV95%>2.7 g/mL), lung (SUV95%>1.7 g/mL), and thyroid (SUV75%>2.1 g/mL). Normal ranges (95% confidence interval) for the SUV percentiles in patients without irAE were bowel [1.74, 2.86 g/mL], lung [0.73, 1.46 g/mL], and thyroid [0.86, 1.99 g/mL].

CONCLUSIONS

Increased 18F-FDG uptake within irAE-affected organs provides predictive information about the development of irAE in MM patients receiving ICI and represents a potential quantitative imaging biomarker for irAE. Some irAE can be detected on 18F-FDG PET/CT well before clinical symptoms appear.

Aberrant newborn T cell and microbiota developmental trajectories predict respiratory compromise during infancy

Neonatal immune-microbiota co-development is poorly understood, yet age-appropriate recognition of - and response to - pathogens and commensal microbiota is critical to health. In this longitudinal study of 148 preterm and 119 full-term infants from birth through one year of age, we found that postmenstrual age or weeks from conception is a central factor influencing T cell and mucosal microbiota development. Numerous features of the T cell and microbiota functional development remain unexplained; however, by either age metric and are instead shaped by discrete perinatal and postnatal events. Most strikingly, we establish that prenatal antibiotics or infection disrupt the normal T cell population developmental trajectory, influencing subsequent respiratory microbial colonization and predicting respiratory morbidity. In this way, early exposures predict the postnatal immune-microbiota axis trajectory, placing infants at later risk for respiratory morbidity in early childhood.

Interactive Analysis, Exploration, and Visualization of RNA-Seq Data with SeqCVIBE

The rise of modern gene expression profiling techniques, such as RNA-Seq, has generated a wealth of high-quality datasets spanning all fields of current biological research. The large data sets and the continually expanding applications for which they can be mined, such as the investigation of alternative splicing and others, have created novel challenges for data management, exploration, analysis, and visualization. Although a large variety of RNA-Seq data analysis software packages has emerged, both open-source and commercial, most fail to simultaneously address the above challenges, while they lack obvious functionalities, such as estimating RNA abundance over non-annotated genomic regions of interest in real time. We have developed SeqCVIBE, an R Shiny web application for the interactive exploration, analysis, visualization, and genome browsing of large RNA-Seq datasets. SeqCVIBE allows for multiple on-the-fly visualizations and calculations, such as differential expression analysis, averaging genomic signals over specific regions of the genome, and calculating RNA abundances over custom, potentially non-annotated regions, such as novel long non-coding RNAs. In addition, SeqCVIBE comprises a database for pre-analyzed data, where users can navigate and explore results, as well as perform a variety of basic on-the-fly analyses and export the outcomes. Finally, we demonstrate the value of SeqCVIBE in the elucidation of the interplay of a novel lincRNA, WiNTRLINC1, and Wnt signaling in colon cancer.

Suppression of human and simian immunodeficiency virus replication with the CCR5-specific antibody Leronlimab in two species

The CCR5-specific antibody Leronlimab is being investigated as a novel immunotherapy that can suppress HIV replication with minimal side effects. Here we studied the virological and immunological consequences of Leronlimab in chronically CCR5-tropic HIV-1 infected humans (n = 5) on suppressive antiretroviral therapy (ART) and in ART-naïve acutely CCR5-tropic SHIV infected rhesus macaques (n = 4). All five human participants transitioned from daily combination ART to self-administered weekly subcutaneous (SC) injections of 350 mg or 700 mg Leronlimab and to date all participants have sustained virologic suppression for over seven years. In all participants, Leronlimab fully occupied CCR5 receptors on peripheral blood CD4+ T cells and monocytes. In ART-naïve rhesus macaques acutely infected with CCR5-tropic SHIV, weekly SC injections of 50 mg/kg Leronlimab fully suppressed plasma viremia in half of the macaques. CCR5 receptor occupancy by Leronlimab occurred concomitant with rebound of CD4+ CCR5+ T-cells in peripheral blood, and full CCR5 receptor occupancy was found in multiple anatomical compartments. Our results demonstrate that weekly, self-administered Leronlimab was safe, well-tolerated, and efficacious for long-term virologic suppression and should be included in the arsenal of safe, easily administered, longer-acting antiretroviral treatments for people living with HIV-1. Trial Registration: ClinicalTrials.gov Identifiers: NCT02175680 and NCT02355184.

A SARS-CoV-2 ferritin nanoparticle vaccine elicits protective immune responses in nonhuman primates

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants stresses the continued need for next-generation vaccines that confer broad protection against coronavirus disease 2019 (COVID-19). We developed and evaluated an adjuvanted SARS-CoV-2 spike ferritin nanoparticle (SpFN) vaccine in nonhuman primates. High-dose (50 μg) SpFN vaccine, given twice 28 days apart, induced a Th1-biased CD4 T cell helper response and elicited neutralizing antibodies against SARS-CoV-2 wild-type and variants of concern, as well as against SARS-CoV-1. These potent humoral and cell-mediated immune responses translated into rapid elimination of replicating virus in the upper and lower airways and lung parenchyma of nonhuman primates following high-dose SARS-CoV-2 respiratory challenge. The immune response elicited by SpFN vaccination and resulting efficacy in nonhuman primates supports the utility of SpFN as a vaccine candidate for SARS-causing betacoronaviruses.

An omic and multidimensional spatial atlas from serial biopsies of an evolving metastatic breast cancer

Mechanisms of therapeutic resistance and vulnerability evolve in metastatic cancers as tumor cells and extrinsic microenvironmental influences change during treatment. To support the development of methods for identifying these mechanisms in individual people, here we present an omic and multidimensional spatial (OMS) atlas generated from four serial biopsies of an individual with metastatic breast cancer during 3.5 years of therapy. This resource links detailed, longitudinal clinical metadata that includes treatment times and doses, anatomic imaging, and blood-based response measurements to clinical and exploratory analyses, which includes comprehensive DNA, RNA, and protein profiles; images of multiplexed immunostaining; and 2- and 3-dimensional scanning electron micrographs. These data report aspects of heterogeneity and evolution of the cancer genome, signaling pathways, immune microenvironment, cellular composition and organization, and ultrastructure. We present illustrative examples of how integrative analyses of these data reveal potential mechanisms of response and resistance and suggest novel therapeutic vulnerabilities.

Antibody-based CCR5 blockade protects Macaques from mucosal SHIV transmission

In the absence of a prophylactic vaccine, the use of antiretroviral therapy (ART) as pre-exposure prophylaxis (PrEP) to prevent HIV acquisition by uninfected individuals is a promising approach to slowing the epidemic, but its efficacy is hampered by incomplete patient adherence and ART-resistant variants. Here, we report that competitive inhibition of HIV Env-CCR5 binding via the CCR5-specific antibody Leronlimab protects rhesus macaques against infection following repeated intrarectal challenges of CCR5-tropic SHIVSF162P3. Injection of Leronlimab weekly at 10 mg/kg provides significant but partial protection, while biweekly 50 mg/kg provides complete protection from SHIV acquisition. Tissue biopsies from protected macaques post challenge show complete CCR5 receptor occupancy and an absence of viral nucleic acids. After Leronlimab washout, protected macaques remain aviremic, and adoptive transfer of hematologic cells into naïve macaques does not transmit viral infection. These data identify CCR5 blockade with Leronlimab as a promising approach to HIV prophylaxis and support initiation of clinical trials.

Blocking the IL-1 receptor reduces cardiac transplant ischemia and reperfusion injury and mitigates CMV-accelerated chronic rejection

Ischemia-reperfusion injury (IRI) is an important risk factor for accelerated cardiac allograft rejection and graft dysfunction . Utilizing a rat heart isogeneic transplant model, we identified inflammatory pathways involved in IRI in order to identify therapeutic targets involved in disease. Pathway analyses identified several relevant targets, including cytokine signaling by the IL-1 receptor (IL-1R) pathway and inflammasome activation. To investigate the role of IL-1R signaling pathways during IRI, we treated syngeneic cardiac transplant recipients at 1-hour posttransplant with Anakinra, a US Food and Drug Administration (FDA)-approved IL-1R antagonist; or parthenolide, a caspase-1 and nuclear factor kappa-light-chain-enhancer of activated B cells inhibitor that blocks IL-1β maturation. Both Anakinra and parthenolide significantly reduced graft inflammation and cellular recruitment in the treated recipients relative to nontreated controls. Anakinra treatment administered at 1-hour posttransplant to recipients of cardiac allografts from CMV-infected donors significantly increased the time to rejection and reduced viral loads at rejection. Our results indicate that reducing IRI by blocking IL-1Rsignaling pathways with Anakinra or inflammasome activity with parthenolide provides a promising approach for extending survival of cardiac allografts from CMV-infected donors.

National Institute for Health Research Health Informatics Collaborative: development of a pipeline to collate electronic clinical data for viral hepatitis research

Objective

The National Institute for Health Research (NIHR) Health Informatics Collaborative (HIC) is a programme of infrastructure development across NIHR Biomedical Research Centres. The aim of the NIHR HIC is to improve the quality and availability of routinely collected data for collaborative, cross-centre research. This is demonstrated through research collaborations in selected therapeutic areas, one of which is viral hepatitis.

Design

The collaboration in viral hepatitis identified a rich set of datapoints, including information on clinical assessment, antiviral treatment, laboratory test results and health outcomes. Clinical data from different centres were standardised and combined to produce a research-ready dataset; this was used to generate insights regarding disease prevalence and treatment response.

Results

A comprehensive database has been developed for potential viral hepatitis research interests, with a corresponding data dictionary for researchers across the centres. An initial cohort of 960 patients with chronic hepatitis B infections and 1404 patients with chronic hepatitis C infections has been collected.

Conclusion

For the first time, large prospective cohorts are being formed within National Health Service (NHS) secondary care services that will allow research questions to be rapidly addressed using real-world data. Interactions with industry partners will help to shape future research and will inform patient-stratified clinical practice. An emphasis on NHS-wide systems interoperability, and the increased utilisation of structured data solutions for electronic patient records, is improving access to data for research, service improvement and the reduction of clinical data gaps.

Characterization of a Novel Compound That Stimulates STING-Mediated Innate Immune Activity in an Allele-Specific Manner

The innate immune response to cytosolic DNA involves transcriptional activation of type I interferons (IFN-I) and proinflammatory cytokines. This represents the culmination of intracellular signaling pathways that are initiated by pattern recognition receptors that engage DNA and require the adaptor protein Stimulator of Interferon Genes (STING). These responses lead to the generation of cellular and tissue states that impair microbial replication and facilitate the establishment of long-lived, antigen-specific adaptive immunity. Ultimately this can lead to immune-mediated protection from infection but also to the cytotoxic T cell-mediated clearance of tumor cells. Intriguingly, pharmacologic activation of STING-dependent phenotypes is known to enhance both vaccine-associated immunogenicity and immune-based anti-tumor therapies. Unfortunately, the STING protein exists as multiple variant forms in the human population that exhibit differences in their reactivity to chemical stimuli and in the intensity of molecular signaling they induce. In light of this, STING-targeting drug discovery efforts require an accounting of protein variant-specific activity. Herein we describe a small molecule termed M04 that behaves as a novel agonist of human STING. Importantly, we find that the molecule exhibits a differential ability to activate STING based on the allelic variant examined. Furthermore, while M04 is inactive in mice, expression of human STING in mouse cells rescues reactivity to the compound. Using primary human cells in ex vivo assays we were also able to show that M04 is capable of simulating innate responses important for adaptive immune activation such as cytokine secretion, dendritic cell maturation, and T cell cross-priming. Collectively, this work demonstrates the conceivable utility of a novel agonist of human STING both as a research tool for exploring STING biology and as an immune potentiating molecule.

Viral opportunistic infections in Mauritian cynomolgus macaques undergoing allogeneic stem cell transplantation mirror human transplant infectious disease complications

Allogeneic hematopoietic stem cell transplantation (HSCT) and xenotransplantation are accompanied by viral reactivations and virus-associated complications resulting from immune deficiency. Here, in a Mauritian cynomolgus macaque model of fully MHC-matched allogeneic HSCT, we report reactivations of cynomolgus polyomavirus, lymphocryptovirus, and cytomegalovirus, macaque viruses analogous to HSCT-associated human counterparts BK virus, Epstein-Barr virus, and human cytomegalovirus. Viral replication in recipient macaques resulted in characteristic disease manifestations observed in HSCT patients, such as polyomavirus-associated hemorrhagic cystitis and tubulointerstitial nephritis or lymphocryptovirus-associated post-transplant lymphoproliferative disorder. However, in most cases, the reconstituted immune system, alone or in combination with short-term pharmacological intervention, exerted control over viral replication, suggesting engraftment of functional donor-derived immunity. Indeed, the donor-derived reconstituted immune systems of two long-term engrafted HSCT recipient macaques responded to live attenuated yellow fever 17D vaccine (YFV 17D) indistinguishably from untransplanted controls, mounting 17D-targeted neutralizing antibody responses and clearing YFV 17D within 14 days. Together, these data demonstrate that this macaque model of allogeneic HSCT recapitulates clinical situations of opportunistic viral infections in transplant patients and provides a pre-clinical model to test novel prophylactic and therapeutic modalities.

Eight practices for data management to enable team data science

INTRODUCTION

In clinical and translational research, data science is often and fortuitously integrated with data collection. This contrasts to the typical position of data scientists in other settings, where they are isolated from data collectors. Because of this, effective use of data science techniques to resolve translational questions requires innovation in the organization and management of these data.

METHODS

We propose an operational framework that respects this important difference in how research teams are organized. To maximize the accuracy and speed of the clinical and translational data science enterprise under this framework, we define a set of eight best practices for data management.

RESULTS

In our own work at the University of Rochester, we have strived to utilize these practices in a customized version of the open source LabKey platform for integrated data management and collaboration. We have applied this platform to cohorts that longitudinally track multidomain data from over 3000 subjects.

CONCLUSIONS

We argue that this has made analytical datasets more readily available and lowered the bar to interdisciplinary collaboration, enabling a team-based data science that is unique to the clinical and translational setting.

A randomized, crossover comparison of ketamine and electroconvulsive therapy for treatment of major depressive episodes: a Canadian biomarker integration network in depression (CAN-BIND) study protocol

BACKGROUND

Recent evidence underscores the utility of rapid-acting antidepressant interventions, such as ketamine, in alleviating symptoms of major depressive episodes (MDE). However, to date, there have been limited head-to-head comparisons of intravenous (IV) ketamine infusions with other antidepressant treatment strategies in large randomized trials. This study protocol describes an ongoing multi-centre, prospective, randomized, crossover, non-inferiority trial comparing acute treatment of individuals meeting diagnostic criteria for a major depressive episode (MDE) with ketamine and electroconvulsive therapy (ECT) on efficacy, speed of therapeutic effects, side effects, and health care resource utilization. A secondary aim is to compare a 6-month maintenance strategy for ketamine responders to standard of care ECT maintenance. Finally, through the measurement of clinical, cognitive, neuroimaging, and molecular markers we aim to establish predictors and moderators of treatment response as well as treatment-elicited effects on these outcomes.

METHODS

Across four participating Canadian institutions, 240 patients with major depressive disorder or bipolar disorder experiencing a MDE are randomized (1:1) to a course of ECT or racemic IV ketamine (0.5 mg/kg) administered 3 times/week for 3 or 4 weeks. Non-responders (< 50% improvement in Montgomery-Åsberg Depression Rating Scale [MADRS] scores) crossover to receive the alternate treatment. Responders during the randomization or crossover phases then enter the 6-month maintenance phase during which time they receive clinical assessments at identical intervals regardless of treatment arm. ECT maintenance follows standard of care while ketamine maintenance involves: weekly infusions for 1 month, then bi-weekly infusions for 2 months, and finally monthly infusions for 3 months (returning to bi-weekly in case of relapse). The primary outcome measure is change in MADRS scores after randomized treatment as assessed by raters blind to treatment modality.

DISCUSSION

This multi-centre study will help identify molecular, imaging, and clinical characteristics of patients with treatment-resistant and/or severe MDEs who would benefit most from either type of therapeutic strategy. In addition to informing clinical practice and influencing health care delivery, this trial will add to the robust platform and database of CAN-BIND studies for future research and biomarker discovery.

TRIAL REGISTRATION

ClinicalTrials.gov identifier NCT03674671. Registered September 17, 2018.

RNA-Seq of human whole blood: Evaluation of globin RNA depletion on Ribo-Zero library method

Peripheral blood is a highly accessible biofluid providing a rich source of information about human physiology and health status. However, for studies of the blood transcriptome with RNA sequencing (RNA-Seq) techniques, high levels of hemoglobin mRNAs (hgbRNA) present in blood can occupy valuable sequencing space, impacting detection and quantification of non-hgbRNAs. In this study, we evaluated two methods for preparing ribosomal RNA (rRNA)-depleted sequencing libraries for RNA-Seq of whole blood, one of which is also designed to deplete hgbRNAs. Two experiments were performed: one evaluating library performance across 6 human blood samples and the other examining library reproducibility and performance in a two-subject subset. We find that addition of hgbRNA depletion to the rRNA-depletion protocol for library preparation from blood RNA effectively reduces highly abundant hgbRNA reads; however, it does not result in a statistically significant increase in differentially expressed genes in our patient-control study. Bioinformatic removal of globin gene counts in non-hgbRNA depleted libraries provides improvement in overall performance of these libraries. We conclude that use of a standard ribosomal RNA depletion method for library preparation coupled with bioinformatic removal of globin gene counts is sufficient for reproducible and sensitive measurement of both coding and noncoding RNAs in the blood transcriptome.

Modelling disease risk for amyloid A (AA) amyloidosis in non-human primates using machine learning

Objective: Amyloid A (AA) amyloidosis is found in humans and non-human primates, but quantifying disease risk prior to clinical symptoms is challenging. We applied machine learning to identify the best predictors of amyloidosis in rhesus macaques from available clinical and pathology records. To explore potential biomarkers, we also assessed whether changes in circulating serum amyloid A (SAA) or lipoprotein profiles accompany the disease. Methods: We conducted a retrospective study using 86 cases and 163 controls matched for age and sex. We performed data reduction on 62 clinical, pathological and demographic variables, and applied multivariate modelling and model selection with cross-validation. To test the performance of our final model, we applied it to a replication cohort of 2,775 macaques. Results: The strongest predictors of disease were colitis, gastrointestinal adenocarcinoma, endometriosis, arthritis, trauma, diarrhoea and number of pregnancies. Sensitivity and specificity of the risk model were predicted to be 82%, and were assessed at 79 and 72%, respectively. Total, low density lipoprotein and high density lipoprotein cholesterol levels were significantly lower, and SAA levels and triglyceride-to-HDL ratios were significantly higher in cases versus controls. Conclusion: Machine learning is a powerful approach to identifying macaques at risk of AA amyloidosis, which is accompanied by increased circulating SAA and altered lipoprotein profiles.

Artificial Intelligence for Surveillance in Public Health

OBJECTIVES

To introduce and summarize current research in the field of Public Health and Epidemiology Informatics.

METHODS

The 2018 literature concerning public health and epidemiology informatics was searched in PubMed and Web of Science, and the returned references were reviewed by the two section editors to select 15 candidate best papers. These papers were then peer-reviewed by external reviewers to give the editorial team an enlightened selection of the best papers.

RESULTS

Among the 805 references retrieved from PubMed and Web of Science, three were finally selected as best papers. All three papers are about surveillance using digital tools. One study is about the surveillance of flu, another about emerging animal infectious diseases and the last one is about foodborne illness. The sources of information are Google news, Twitter, and Yelp restaurant reviews. Machine learning approaches are most often used to detect signals.

CONCLUSIONS

Surveillance is a central topic in public health informatics with the growing use of machine learning approaches in regards of the size and complexity of data. The evaluation of the approaches developed remains a serious challenge.

Laboratory information management software for engineered mini-protein therapeutic workflow

Background

Protein based therapeutics are one of the fastest growing classes of novel medical interventions in areas such as cancer, infectious disease, and inflammation. Protein engineering plays an important role in the optimization of desired therapeutic properties such as reducing immunogenicity, increasing stability for storage, increasing target specificity, etc. One category of protein therapeutics is nature-inspired bioengineered cystine-dense peptides (CDPs) for various biological targets. These engineered proteins are often further modified by synthetic chemistry. For example, candidate mini-proteins can be conjugated into active small molecule drugs. We refer to modified mini-proteins as “Optides” (Optimized peptides). To efficiently serve the multidisciplinary lab scientists with varied therapeutic portfolio research goals in a non-commercial setting, a cost effective extendable laboratory information management system (LIMS) is/was needed.

Results

We have developed a LIMS named Optide-Hunter for a generalized engineered protein compounds workflow that tracks entities and assays from creation to preclinical experiments. The implementation and custom modules are built using LabKey server, which is an Open Source platform for scientific data integration and analysis. Optide-Hunter contains a compound registry, in-silico assays, high throughput production, large-scale production, in vivo assays and data extraction from a specimen-tracking database. It is used to store, extract, and view data for various therapeutics projects. Optide-Hunter also includes external processing stand-alone software (HPLCPeakClassifierApp) for automated chromatogram classification. The HPLCPeakClassifierApp is used for pre-processing of HPLC data prior to loading to Optide-Hunter. The custom implementation is done using data transformation modules in R, SQL, javascript, and java and is Open Source to assist new users in customizing it for their unique workflows. Instructions for exploring a deployed version of Optide-Hunter can be found at https://www.labkey.com/case%20study/optide-hunter

Conclusion

The Optide-Hunter LIMS system is designed and built to track the process of engineering, producing and prioritizing protein therapeutic candidates. It can be easily adapted and extended for use in small or large research laboratories where multidisciplinary scientists are collaborating to engineer compounds for potential therapeutic or protein science applications. Open Source exploration of Optide-Hunter can help any bioinformatics scientist adapt, extend, and deploy an equivalent system tailored to each laboratory’s workflow.

Sex differences in sympathetic gene expression and cardiac neurochemistry in Wistar Kyoto rats

The stellate ganglia are the predominant source of sympathetic innervation to the heart. Remodeling of sympathetic nerves projecting to the heart has been observed in several cardiovascular diseases, and sympathetic dysfunction contributes to cardiac pathology. Wistar Kyoto rats are a common model for the study of cardiovascular diseases, but we lack a profile of the baseline transcriptomic and neurochemical characteristics of their cardiac sympathetic neurons. Most studies of cardiovascular disease have used male animals only, but in the future both male and female animals will be used for these types of studies; therefore, we sought to characterize the transcriptome of male and female stellate ganglia and to correlate that with catecholamine and acetylcholine content in the heart. We have generated a dataset of baseline RNA expression in male and female Wistar Kyoto rat stellate ganglia using RNA-seq, and have measured neurotransmitter levels in heart and stellate ganglia using HPLC and mass spectrometry. We identified numerous gene expression differences between male and female stellates, including genes encoding important developmental factors, receptors and neuropeptides. Female hearts had significantly higher neurotransmitter content than male hearts; however, no significant differences were detected in expression of the genes encoding neurotransmitter synthetic enzymes. Similarly, no statistically significant differences were identified between the sexes in cardiac tyrosine hydroxylase levels.

Chronically elevated androgen and/or consumption of a Western-style diet impairs oocyte quality and granulosa cell function in the nonhuman primate periovulatory follicle

PURPOSE

To investigate the impact of chronically elevated androgens in the presence and absence of an obesogenic diet on oocyte quality in the naturally selected primate periovulatory follicle.

METHODS

Rhesus macaques were treated using a 2-by-2 factorial design (n = 10/treatment) near the onset of menarche with implants containing either cholesterol (C) or testosterone (T, 4-5-fold increase above C) and a standard or "Western-style" diet alone (WSD) or in combination (T+WSD). Following ~ 3.5 years of treatment, females underwent controlled ovulation (COv, n = 7-10/treatment) cycles, and contents of the naturally selected periovulatory follicle were aspirated. Follicular fluid (FF) was analyzed for cytokines, chemokines, growth factors, and steroids. RNA was extracted from luteinizing granulosa cells (LGCs) and assessed by RNA-seq.

RESULTS

Only healthy, metaphase (M) I/II-stage oocytes (100%) were retrieved in the C group, whereas several degenerated oocytes were recovered in other groups (33-43% of T, WSD, and T+WSD samples). Levels of two chemokines and one growth factor were reduced (p < 0.04) in FF of follicles with a MI/MII oocyte in WSD+T (CCL11) or T and WSD+T groups (CCL2 and FGF2) compared to C and/or WSD. Intrafollicular cortisol was elevated in T compared to C follicles (p < 0.02). Changes in the expression pattern of 640+ gene products were detected in LGC samples from follicles with degenerated versus MI/MII-stage oocytes. Pathway analysis on RNAs altered by T and/or WSD found enrichment of genes mapping to steroidogenic and immune cell pathways.

CONCLUSIONS

Female primates experiencing hyperandrogenemia and/or consuming a WSD exhibit an altered intrafollicular microenvironment and reduced oocyte quality/competency, despite displaying menstrual cyclicity.

CaosDB—Research Data Management for Complex, Changing, and Automated Research Workflows

We present CaosDB, a Research Data Management System (RDMS) designed to ensure seamless integration of inhomogeneous data sources and repositories of legacy data in a FAIR way. Its primary purpose is the management of data from biomedical sciences, both from simulations and experiments during the complete research data lifecycle. An RDMS for this domain faces particular challenges: research data arise in huge amounts, from a wide variety of sources, and traverse a highly branched path of further processing. To be accepted by its users, an RDMS must be built around workflows of the scientists and practices and thus support changes in workflow and data structure. Nevertheless, it should encourage and support the development and observation of standards and furthermore facilitate the automation of data acquisition and processing with specialized software. The storage data model of an RDMS must reflect these complexities with appropriate semantics and ontologies while offering simple methods for finding, retrieving, and understanding relevant data. We show how CaosDB responds to these challenges and give an overview of its data model, the CaosDB Server and its easy-to-learn CaosDB Query Language. We briefly discuss the status of the implementation, how we currently use CaosDB, and how we plan to use and extend it.

mGAP: the macaque genotype and phenotype resource, a framework for accessing and interpreting macaque variant data, and identifying new models of human disease

Background

Non-human primates (NHPs), particularly macaques, serve as critical and highly relevant pre-clinical models of human disease. The similarity in human and macaque natural disease susceptibility, along with parallel genetic risk alleles, underscores the value of macaques in the development of effective treatment strategies. Nonetheless, there are limited genomic resources available to support the exploration and discovery of macaque models of inherited disease. Notably, there are few public databases tailored to searching NHP sequence variants, and no other database making use of centralized variant calling, or providing genotype-level data and predicted pathogenic effects for each variant.

Results

The macaque Genotype And Phenotype (mGAP) resource is the first public website providing searchable, annotated macaque variant data. The mGAP resource includes a catalog of high confidence variants, derived from whole genome sequence (WGS). The current mGAP release at time of publication (1.7) contains 17,087,212 variants based on the sequence analysis of 293 rhesus macaques. A custom pipeline was developed to enable annotation of the macaque variants, leveraging human data sources that include regulatory elements (ENCODE, RegulomeDB), known disease- or phenotype-associated variants (GRASP), predicted impact (SIFT, PolyPhen2), and sequence conservation (Phylop, PhastCons). Currently mGAP includes 2767 variants that are identical to alleles listed in the human ClinVar database, of which 276 variants, spanning 258 genes, are identified as pathogenic. An additional 12,472 variants are predicted as high impact (SnpEff) and 13,129 are predicted as damaging (PolyPhen2). In total, these variants are predicted to be associated with more than 2000 human disease or phenotype entries reported in OMIM (Online Mendelian Inheritance in Man). Importantly, mGAP also provides genotype-level data for all subjects, allowing identification of specific individuals harboring alleles of interest.

Conclusions

The mGAP resource provides variant and genotype data from hundreds of rhesus macaques, processed in a consistent manner across all subjects (https://mgap.ohsu.edu). Together with the extensive variant annotations, mGAP presents unprecedented opportunity to investigate potential genetic associations with currently characterized disease models, and to uncover new macaque models based on parallels with human risk alleles.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5559-7) contains supplementary material, which is available to authorized users.

Single-cell sequencing of primate preimplantation embryos reveals chromosome elimination via cellular fragmentation and blastomere exclusion

Aneuploidy that arises during meiosis and/or mitosis is a major contributor to early embryo loss. We previously showed that human preimplantation embryos encapsulate missegregated chromosomes into micronuclei while undergoing cellular fragmentation and that fragments can contain chromosomal material, but the source of this DNA was unknown. Here, we leveraged the use of a nonhuman primate model and single-cell DNA-sequencing (scDNA-seq) to examine the chromosomal content of 471 individual samples comprising 254 blastomeres, 42 polar bodies, and 175 cellular fragments from a large number (N = 50) of disassembled rhesus cleavage-stage embryos. Our analysis revealed that the aneuploidy and micronucleation frequency is conserved between humans and macaques, and that fragments encapsulate whole and/or partial chromosomes lost from blastomeres. Single-cell/fragment genotyping showed that these chromosome-containing cellular fragments (CCFs) can be maternally or paternally derived and display double-stranded DNA breaks. DNA breakage was further indicated by reciprocal subchromosomal losses/gains between blastomeres and large segmental errors primarily detected at the terminal ends of chromosomes. By combining time-lapse imaging with scDNA-seq, we determined that multipolar divisions at the zygote or two-cell stage were associated with CCFs and generated a random mixture of chromosomally normal and abnormal blastomeres with uniparental or biparental origins. Despite frequent chromosome missegregation at the cleavage-stage, we show that CCFs and nondividing aneuploid blastomeres showing extensive DNA damage are prevented from incorporation into blastocysts. These findings suggest that embryos respond to chromosomal errors by encapsulation into micronuclei, elimination via cellular fragmentation, and selection against highly aneuploid blastomeres to overcome chromosome instability during preimplantation development.

OMeta: an ontology-based, data-driven metadata tracking system

Background

The development of high-throughput sequencing and analysis has accelerated multi-omics studies of thousands of microbial species, metagenomes, and infectious disease pathogens. Omics studies are enabling genotype-phenotype association studies which identify genetic determinants of pathogen virulence and drug resistance, as well as phylogenetic studies designed to track the origin and spread of disease outbreaks. These omics studies are complex and often employ multiple assay technologies including genomics, metagenomics, transcriptomics, proteomics, and metabolomics. To maximize the impact of omics studies, it is essential that data be accompanied by detailed contextual metadata (e.g., specimen, spatial-temporal, phenotypic characteristics) in clear, organized, and consistent formats. Over the years, many metadata standards developed by various metadata standards initiatives have arisen; the Genomic Standards Consortium’s minimal information standards (MIxS), the GSCID/BRC Project and Sample Application Standard. Some tools exist for tracking metadata, but they do not provide event based capabilities to configure, collect, validate, and distribute metadata. To address this gap in the scientific community, an event based data-driven application, OMeta, was created that allows users to quickly configure, collect, validate, distribute, and integrate metadata.

Results

A data-driven web application, OMeta, has been developed for use by researchers consisting of a browser-based interface, a command-line interface (CLI), and server-side components that provide an intuitive platform for configuring, capturing, viewing, and sharing metadata. Project and sample metadata can be set based on existing standards or based on projects goals. Recorded information includes details on the biological samples, procedures, protocols, and experimental technologies, etc. This information can be organized based on events, including sample collection, sample quantification, sequencing assay, and analysis results. OMeta enables configuration in various presentation types: checkbox, file, drop-box, ontology, and fields can be configured to use the National Center for Biomedical Ontology (NCBO), a biomedical ontology server. Furthermore, OMeta maintains a complete audit trail of all changes made by users and allows metadata export in comma separated value (CSV) format for convenient deposition of data into public databases.

Conclusions

We present, OMeta, a web-based software application that is built on data-driven principles for configuring and customizing data standards, capturing, curating, and sharing metadata.

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2580-9) contains supplementary material, which is available to authorized users.

An Innovative Framework for Bioimage Annotation and Studies

The collection and analysis of clinical data are needed to investigate diseases and to define medical protocols and treatments. Bioimages, medical annotations and patient history are clinical data acquired and studied to perform a correct diagnosis and to propose an appropriate therapy. Currently, hospital departments manage these data using legacy systems which do not often allow data integration among different departments or health structures. Thus, in many cases clinical information sharing and exchange are difficult to implement. This is also the case for biomedical images for which data integration or data overlapping is usually not available. Image annotations and comparison can be crucial for physicians in many case studies. In this paper, a general purpose framework for bioimage management and annotations is proposed. Moreover, a simple-to-use information system has been developed to integrate clinical and diagnosis codes. The framework allows physicians (1) to integrate DICOM images from different platforms and (2) to report notes and highlights directly on images, thus offering, among the others, to query and compare similar clinical cases. This contribution is the result of a framework aimed to support oncologists in managing DICOM images and clinical data from different departments. Data integration is performed using a here-proposed XML-based module also utilized to trace temporal changes in image annotations.

Proteomic profiles by multiplex microsphere suspension array

Advances in high-throughput proteomic approaches have provided substantial momentum to novel disease-biomarker discovery research and have augmented the quality of clinical studies. Applications based on multiplexed microsphere suspension array technology are making strong in-roads into the clinical diagnostic/prognostic practice. Conventional proteomic approaches are designed to discover a broad set of proteins that are associated with a specific medical condition. In comparison, multiplex microsphere immunoassays use quantitative measurements of selected set(s) of specific/particular molecular markers such as cytokines, chemokines, pathway signaling or disease-specific markers for detection, metabolic disorders, cancer, and infectious agents causing human, plant and animal diseases. This article provides a foundation to the multiplexed microsphere suspension array technology, with an emphasis on the improvements in the technology, data analysis approaches, and applications to translational and clinical research with implications for personalized and precision medicine.

Transcriptomic and neurochemical analysis of the stellate ganglia in mice highlights sex differences

The stellate ganglia are the predominant source of sympathetic innervation to the heart. Remodeling of the nerves projecting to the heart has been observed in several cardiovascular diseases, however studies of adult stellate ganglia are limited. A profile of the baseline transcriptomic and neurochemical characteristics of the stellate ganglia in adult C57Bl6j mice, a common model for the study of cardiovascular diseases, may aid future investigations. We have generated a dataset of baseline measurements of mouse stellate ganglia using RNAseq, HPLC and mass spectrometry. Expression differences between male and female mice were identified. These differences included physiologically important genes for growth factors, receptors and ion channels. While the neurochemical profiles of male and female stellate ganglia were not different, minor differences in neurotransmitter content were identified in heart tissue.

Multi-lectin Affinity Chromatography and Quantitative Proteomic Analysis Reveal Differential Glycoform Levels between Prostate Cancer and Benign Prostatic Hyperplasia Sera

Currently prostate-specific antigen is used for prostate cancer (PCa) screening, however it lacks the necessary specificity for differentiating PCa from other diseases of the prostate such as benign prostatic hyperplasia (BPH), presenting a clinical need to distinguish these cases at the molecular level. Protein glycosylation plays an important role in a number of cellular processes involved in neoplastic progression and is aberrant in PCa. In this study, we systematically interrogate the alterations in the circulating levels of hundreds of serum proteins and their glycoforms in PCa and BPH samples using multi-lectin affinity chromatography and quantitative mass spectrometry-based proteomics. Specific lectins (AAL, PHA-L and PHA-E) were used to target and chromatographically separate core-fucosylated and highly-branched protein glycoforms for analysis, as differential expression of these glycan types have been previously associated with PCa. Global levels of CD5L, CFP, C8A, BST1, and C7 were significantly increased in the PCa samples. Notable glycoform-specific alterations between BPH and PCa were identified among proteins CD163, C4A, and ATRN in the PHA-L/E fraction and among C4BPB and AZGP1 glycoforms in the AAL fraction. Despite these modest differences, substantial similarities in glycoproteomic profiles were observed between PCa and BPH sera.

T cell developmental arrest in former premature infants increases risk of respiratory morbidity later in infancy

The inverse relationship between gestational age at birth and postviral respiratory morbidity suggests that infants born preterm (PT) may miss a critical developmental window of T cell maturation. Despite a continued increase in younger PT survivors with respiratory complications, we have limited understanding of normal human fetal T cell maturation, how ex utero development in premature infants may interrupt normal T cell development, and whether T cell development has an effect on infant outcomes. In our longitudinal cohort of 157 infants born between 23 and 42 weeks of gestation, we identified differences in T cells present at birth that were dependent on gestational age and differences in postnatal T cell development that predicted respiratory outcome at 1 year of age. We show that naive CD4+ T cells shift from a CD31-TNF-α+ bias in mid gestation to a CD31+IL-8+ predominance by term gestation. Former PT infants discharged with CD31+IL8+CD4+ T cells below a range similar to that of full-term born infants were at an over 3.5-fold higher risk for respiratory complications after NICU discharge. This study is the first to our knowledge to identify a pattern of normal functional T cell development in later gestation and to associate abnormal T cell development with health outcomes in infants.

Hepatocytic expression of human sodium-taurocholate cotransporting polypeptide enables hepatitis B virus infection of macaques

Hepatitis B virus (HBV) is a major global health concern, and the development of curative therapeutics is urgently needed. Such efforts are impeded by the lack of a physiologically relevant, pre-clinical animal model of HBV infection. Here, we report that expression of the HBV entry receptor, human sodium-taurocholate cotransporting polypeptide (hNTCP), on macaque primary hepatocytes facilitates HBV infection in vitro, where all replicative intermediates including covalently closed circular DNA (cccDNA) are present. Furthermore, viral vector-mediated expression of hNTCP on hepatocytes in vivo renders rhesus macaques permissive to HBV infection. These in vivo macaque HBV infections are characterized by longitudinal HBV DNA in serum, and detection of HBV DNA, RNA, and HBV core antigen (HBcAg) in hepatocytes. Together, these results show that expressing hNTCP on macaque hepatocytes renders them susceptible to HBV infection, thereby establishing a physiologically relevant model of HBV infection to study immune clearance and test therapeutic and curative approaches.

Allogeneic stem cell transplantation in fully MHC-matched Mauritian cynomolgus macaques recapitulates diverse human clinical outcomes

Allogeneic hematopoietic stem cell transplantation (HSCT) is a critically important therapy for hematological malignancies, inborn errors of metabolism, and immunodeficiency disorders, yet complications such as graft-vs.-host disease (GvHD) limit survival. Development of anti-GvHD therapies that do not adversely affect susceptibility to infection or graft-vs.-tumor immunity are hampered by the lack of a physiologically relevant, preclinical model of allogeneic HSCT. Here we show a spectrum of diverse clinical HSCT outcomes including primary and secondary graft failure, lethal GvHD, and stable, disease-free full donor engraftment using reduced intensity conditioning and mobilized peripheral blood HSCT in unrelated, fully MHC-matched Mauritian-origin cynomolgus macaques. Anti-GvHD prophylaxis of tacrolimus, post-transplant cyclophosphamide, and CD28 blockade induces multi-lineage, full donor chimerism and recipient-specific tolerance while maintaining pathogen-specific immunity. These results establish a new preclinical allogeneic HSCT model for evaluation of GvHD prophylaxis and next-generation HSCT-mediated therapies for solid organ tolerance, cure of non-malignant hematological disease, and HIV reservoir clearance.

Rhesus macaques are not ideal for studying response to allogeneic hematopoietic stem cell transplant (allo-HSCT) owing to complex MHC genetics that prevent full MHC-matching. Here the authors show that inbred Mauritian-origin cynomolgus macaques are a superior preclinical model of allogeneic stem cell transplantation that mimics diverse clinical outcomes of human allo-HSCT.

Algorithms and design strategies towards automated glycoproteomics analysis

Glycoproteomics involves the study of glycosylation events on protein sequences ranging from purified proteins to whole proteome scales. Understanding these complex post-translational modification (PTM) events requires elucidation of the glycan moieties (monosaccharide sequences and glycosidic linkages between residues), protein sequences, as well as site-specific attachment of glycan moieties onto protein sequences, in a spatial and temporal manner in a variety of biological contexts. Compared with proteomics, bioinformatics for glycoproteomics is immature and many researchers still rely on tedious manual interpretation of glycoproteomics data. As sample preparation protocols and analysis techniques have matured, the number of publications on glycoproteomics and bioinformatics has increased substantially; however, the lack of consensus on tool development and code reuse limits the dissemination of bioinformatics tools because it requires significant effort to migrate a computational tool tailored for one method design to alternative methods. This review discusses algorithms and methods in glycoproteomics, and refers to the general proteomics field for potential solutions. It also introduces general strategies for tool integration and pipeline construction in order to better serve the glycoproteomics community. © 2016 Wiley Periodicals, Inc. Mass Spec Rev 36:475-498, 2017.

Successful Repeated Hepatic Gene Delivery in Mice and Non-human Primates Achieved by Sequential Administration of AAV5ch and AAV1

In the gene therapy field, re-administration of adeno-associated virus (AAV) is an important topic because a decrease in therapeutic protein expression might occur over time. However, an efficient re-administration with the same AAV serotype is impossible due to serotype-specific, anti-AAV neutralizing antibodies (NABs) that are produced after initial AAV treatment. To address this issue, we explored the feasibility of using chimeric AAV serotype 5 (AAV5^ch) and AAV1 for repeated liver-targeted gene delivery. To develop a relevant model, we immunized animals with a high dose of AAV5^ch-human secreted embryonic alkaline phosphatase (hSEAP) that generates high levels of anti-AAV5^ch NAB. Secondary liver transduction with the same dose of AAV1-human factor IX (hFIX) in the presence of high levels of anti-AAV5^ch NAB proved to be successful because expression/activity of both reporter transgenes was observed. This is the first time that two different transgenes are shown to be produced by non-human primate (NHP) liver after sequential administration of clinically relevant doses of both AAV5^ch and AAV1. The levels of transgene proteins achieved after delivery with AAV5^ch and AAV1 illustrate the possibility of both serotypes for liver targeting. Furthermore, transgene DNA and RNA biodistribution patterns provided insight into the potential cause of decrease or loss of transgene protein expression over time in NHPs.

A bioinformatics roadmap for the human vaccines project

Biomedical research has become a data intensive science in which high throughput experimentation is producing comprehensive data about biological systems at an ever-increasing pace. The Human Vaccines Project is a new public-private partnership, with the goal of accelerating development of improved vaccines and immunotherapies for global infectious diseases and cancers by decoding the human immune system. To achieve its mission, the Project is developing a Bioinformatics Hub as an open-source, multidisciplinary effort with the overarching goal of providing an enabling infrastructure to support the data processing, analysis and knowledge extraction procedures required to translate high throughput, high complexity human immunology research data into biomedical knowledge, to determine the core principles driving specific and durable protective immune responses.

Whole genome sequencing predicts novel human disease models in rhesus macaques

Rhesus macaques are an important pre-clinical model of human disease. To advance our understanding of genomic variation that may influence disease, we surveyed genome-wide variation in 21 rhesus macaques. We employed best-practice variant calling, validated with Mendelian inheritance. Next, we used alignment data from our cohort to detect genomic regions likely to produce inaccurate genotypes, potentially due to either gene duplication or structural variation between individuals. We generated a final dataset of >16 million high confidence variants, including 13 million in Chinese-origin rhesus macaques, an increasingly important disease model. We detected an average of 131 mutations predicted to severely alter protein coding per animal, and identified 45 such variants that coincide with known pathogenic human variants. These data suggest that expanded screening of existing breeding colonies will identify novel models of human disease, and that increased genomic characterization can help inform research studies in macaques.

Resource: Mapping the Triticum aestivum proteome

Yield and quality improvement of bread wheat (Triticum aestivum) is a focus in efforts to meet new demands from population growth and changing human diets. As the complexity of the wheat genome is unravelled, determining how it is used to build the protein machinery of wheat plants is a key next step in explaining detailed aspects of wheat growth and development. The specific functions of wheat organs during vegetative development and the role of metabolism, protein degradation and remobilisation in driving grain production are the foundations of crop performance and have recently become accessible through studies of the wheat proteome. We present a large scale, publicly accessible proteome mapping of wheat consisting of 24 organ and developmental samples. Tissue specific sub-proteomes and ubiquitously expressed markers of the wheat proteome are identified, alongside hierarchical assessment of protein functional classes, their presence in different tissues and correlations between the abundance of functional classes of proteins. Gene-specific identifications and protein family relationships are accounted for in the organisation of the data and 202 new protein-coding transcripts identified by proteogenomic mapping. The interactive database will serve as a vehicle to build, refine and deposit confirmed targeted proteomic assays for wheat proteins and protein families to assess function (www.wheatproteome.org).

Pathogen metadata platform: software for accessing and analyzing pathogen strain information

BACKGROUND

Pathogen metadata includes information about where and when a pathogen was collected and the type of environment it came from. Along with genomic nucleotide sequence data, this metadata is growing rapidly and becoming a valuable resource not only for research but for biosurveillance and public health. However, current freely available tools for analyzing this data are geared towards bioinformaticians and/or do not provide summaries and visualizations needed to readily interpret results.

RESULTS

We designed a platform to easily access and summarize data about pathogen samples. The software includes a PostgreSQL database that captures metadata useful for disease outbreak investigations, and scripts for downloading and parsing data from NCBI BioSample and BioProject into the database. The software provides a user interface to query metadata and obtain standardized results in an exportable, tab-delimited format. To visually summarize results, the user interface provides a 2D histogram for user-selected metadata types and mapping of geolocated entries. The software is built on the LabKey data platform, an open-source data management platform, which enables developers to add functionalities. We demonstrate the use of the software in querying for a pathogen serovar and for genome sequence identifiers.

CONCLUSIONS

This software enables users to create a local database for pathogen metadata, populate it with data from NCBI, easily query the data, and obtain visual summaries. Some of the components, such as the database, are modular and can be incorporated into other data platforms. The source code is freely available for download at https://github.com/wchangmitre/bioattribution .

Whole-genome characterization in pedigreed non-human primates using genotyping-by-sequencing (GBS) and imputation

BACKGROUND

Rhesus macaques are widely used in biomedical research, but the application of genomic information in this species to better understand human disease is still in its infancy. Whole-genome sequence (WGS) data in large pedigreed macaque colonies could provide substantial experimental power for genetic discovery, but the collection of WGS data in large cohorts remains a formidable expense. Here, we describe a cost-effective approach that selects the most informative macaques in a pedigree for 30X WGS, followed by low-cost genotyping-by-sequencing (GBS) at 30X on the remaining macaques in order to generate sparse genotype data at high accuracy. Dense variants from the selected macaques with WGS data are then imputed into macaques having only sparse GBS data, resulting in dense genome-wide genotypes throughout the pedigree.

RESULTS

We developed GBS for the macaque genome using a digestion with PstI, followed by sequencing of size-selected fragments at 30X coverage. From GBS sequence data collected on all individuals in a 16-member pedigree, we characterized high-confidence genotypes at 22,455 single nucleotide variant (SNV) sites that were suitable for guiding imputation of dense sequence data from WGS. To characterize dense markers for imputation, we performed WGS at 30X coverage on nine of the 16 individuals, yielding 10,193,425 high-confidence SNVs. To validate the use of GBS data for facilitating imputation, we initially focused on chromosome 19 as a test case, using an optimized panel of 833 sparse, evenly-spaced markers from GBS and 5,010 dense markers from WGS. Using the method of "Genotype Imputation Given Inheritance" (GIGI), we evaluated the effects on imputation accuracy of 3 different strategies for selecting individuals for WGS, including 1) using "GIGI-Pick" to select the most informative individuals, 2) using the most recent generation, or 3) using founders only.  We also evaluated the effects on imputation accuracy of using a range of from 1 to 9 WGS individuals for imputation. We found that the GIGI-Pick algorithm for selection of WGS individuals outperformed common heuristic approaches, and that genotype numbers and accuracy improved very little when using >5 WGS individuals for imputation. Informed by our findings, we used 4 macaques with WGS data to impute variants at up to 7,655,491 sites spanning all 20 autosomes in the 12 remaining macaques, based on their GBS genotypes at only 17,158 loci. Using a strict confidence threshold, we imputed an average of 3,680,238 variants per individual at >99 % accuracy, or an average 4,458,883 variants per individual at a more relaxed threshold, yielding >97 % accuracy.

CONCLUSIONS

We conclude that an optimal tradeoff between genotype accuracy, number of imputed genotypes, and overall cost exists at the ratio of one individual selected for WGS using the GIGI-Pick algorithm, per 3-5 relatives selected for GBS. This approach makes feasible the collection of accurate, dense genome-wide sequence data in large pedigreed macaque cohorts without the need for more expensive WGS data on all individuals.

Discovering biomarkers for antidepressant response: protocol from the Canadian biomarker integration network in depression (CAN-BIND) and clinical characteristics of the first patient cohort

BACKGROUND

Major Depressive Disorder (MDD) is among the most prevalent and disabling medical conditions worldwide. Identification of clinical and biological markers ("biomarkers") of treatment response could personalize clinical decisions and lead to better outcomes. This paper describes the aims, design, and methods of a discovery study of biomarkers in antidepressant treatment response, conducted by the Canadian Biomarker Integration Network in Depression (CAN-BIND). The CAN-BIND research program investigates and identifies biomarkers that help to predict outcomes in patients with MDD treated with antidepressant medication. The primary objective of this initial study (known as CAN-BIND-1) is to identify individual and integrated neuroimaging, electrophysiological, molecular, and clinical predictors of response to sequential antidepressant monotherapy and adjunctive therapy in MDD.

METHODS

CAN-BIND-1 is a multisite initiative involving 6 academic health centres working collaboratively with other universities and research centres. In the 16-week protocol, patients with MDD are treated with a first-line antidepressant (escitalopram 10-20 mg/d) that, if clinically warranted after eight weeks, is augmented with an evidence-based, add-on medication (aripiprazole 2-10 mg/d). Comprehensive datasets are obtained using clinical rating scales; behavioural, dimensional, and functioning/quality of life measures; neurocognitive testing; genomic, genetic, and proteomic profiling from blood samples; combined structural and functional magnetic resonance imaging; and electroencephalography. De-identified data from all sites are aggregated within a secure neuroinformatics platform for data integration, management, storage, and analyses. Statistical analyses will include multivariate and machine-learning techniques to identify predictors, moderators, and mediators of treatment response.

DISCUSSION

From June 2013 to February 2015, a cohort of 134 participants (85 outpatients with MDD and 49 healthy participants) has been evaluated at baseline. The clinical characteristics of this cohort are similar to other studies of MDD. Recruitment at all sites is ongoing to a target sample of 290 participants. CAN-BIND will identify biomarkers of treatment response in MDD through extensive clinical, molecular, and imaging assessments, in order to improve treatment practice and clinical outcomes. It will also create an innovative, robust platform and database for future research.

TRIAL REGISTRATION

ClinicalTrials.gov identifier NCT01655706 . Registered July 27, 2012.