Activation of human T cell clones through the UM4D4/CDw60 surface antigen

UM4D4 is a recently defined antigen that is expressed on ~25% of peripheral blood T cells, but on the majority of T cells in inflammatory synovial fluid. Anti-UM4D4 activates peripheral blood T cells in the presence of accessory cells and/or phorbol ester. UM4D4 has been assigned to a new antigen cluster termed CDw60. The present study examined the ability of anti-UM4D4 to activate T cell clones derived from the synovial fluid of patients with rheumatoid arthritis. UM4D4 was expressed at varying levels on both lectin-generated and antigen-specific clones, including clones of CD4+, CD8+, and CD4-CD8- phenotypes. Anti-UM4D4 used in soluble form as a single stimulus was typically mitogenic for the CD4+ and some of the CD8+ clones, but not for the CD4-CD8- clones. Phorbol ester boosted the response to anti-UM4D4 in some clones, had no effect in others, and diminished the responses in some cases. In contrast to anti-UM4D4, anti-CD3 was generally not mitogenic in soluble form, although it was mitogenic when conjugated to beads. The data show that T cell clones derived from an inflammatory T cell infiltrate can be readily activated through the UM4D4/CDw60 antigen.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/28512/1/0000309.pd

Potential Mechanisms for Cancer Resistance in Elephants and Comparative Cellular Response to DNA Damage in Humans

Importance: Evolutionary medicine may provide insights into human physiology and pathophysiology, including tumor biology. Objective: To identify mechanisms for cancer resistance in elephants and compare cellular response to DNA damage among elephants, healthy human controls, and cancer-prone patients with Li-Fraumeni syndrome (LFS). Design, Setting, and Participants: A comprehensive survey of necropsy data was performed across 36 mammalian species to validate cancer resistance in large and long-lived organisms, including elephants (n = 644). The African and Asian elephant genomes were analyzed for potential mechanisms of cancer resistance. Peripheral blood lymphocytes from elephants, healthy human controls, and patients with LFS were tested in vitro in the laboratory for DNA damage response. The study included African and Asian elephants (n = 8), patients with LFS (n = 10), and age-matched human controls (n = 11). Human samples were collected at the University of Utah between June 2014 and July 2015. Exposures: Ionizing radiation and doxorubicin. Main Outcomes and Measures: Cancer mortality across species was calculated and compared by body size and life span. The elephant genome was investigated for alterations in cancer-related genes. DNA repair and apoptosis were compared in elephant vs human peripheral blood lymphocytes. Results: Across mammals, cancer mortality did not increase with body size and/or maximum life span (eg, for rock hyrax, 1% [95% CI, 0%-5%]; African wild dog, 8% [95% CI, 0%-16%]; lion, 2% [95% CI, 0%-7%]). Despite their large body size and long life span, elephants remain cancer resistant, with an estimated cancer mortality of 4.81% (95% CI, 3.14%-6.49%), compared with humans, who have 11% to 25% cancer mortality. While humans have 1 copy (2 alleles) of TP53, African elephants have at least 20 copies (40 alleles), including 19 retrogenes (38 alleles) with evidence of transcriptional activity measured by reverse transcription polymerase chain reaction. In response to DNA damage, elephant lymphocytes underwent p53-mediated apoptosis at higher rates than human lymphocytes proportional to TP53 status (ionizing radiation exposure: patients with LFS, 2.71% [95% CI, 1.93%-3.48%] vs human controls, 7.17% [95% CI, 5.91%-8.44%] vs elephants, 14.64% [95% CI, 10.91%-18.37%]; P \u3c .001; doxorubicin exposure: human controls, 8.10% [95% CI, 6.55%-9.66%] vs elephants, 24.77% [95% CI, 23.0%-26.53%]; P \u3c .001). Conclusions and Relevance: Compared with other mammalian species, elephants appeared to have a lower-than-expected rate of cancer, potentially related to multiple copies of TP53. Compared with human cells, elephant cells demonstrated increased apoptotic response following DNA damage. These findings, if replicated, could represent an evolutionary-based approach for understanding mechanisms related to cancer suppression

Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque

Carotid intima media thickness (cIMT) and plaque determined by ultrasonography are established measures of subclinical atherosclerosis that each predicts future cardiovascular disease events. We conducted a meta-analysis of genome-wide association data in 31,211 participants of European ancestry from nine large studies in the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. We then sought additional evidence to support our findings among 11,273 individuals using data from seven additional studies. In the combined meta-analysis, we identified three genomic regions associated with common carotid intima media thickness and two different regions associated with the presence of carotid plaque (P < 5 × 10 -8). The associated SNPs mapped in or near genes related to cellular signaling, lipid metabolism and blood pressure homeostasis, and two of the regions were associated with coronary artery disease (P < 0.006) in the Coronary Artery Disease Genome-Wide Replication and Meta-Analysis (CARDIoGRAM) consortium. Our findings may provide new insight into pathways leading to subclinical atherosclerosis and subsequent cardiovascular events

Patient-orientated longitudinal study of multiple sclerosis in south west England (The South West Impact of Multiple Sclerosis Project, SWIMS) 1: protocol and baseline characteristics of cohort

<p>Abstract</p> <p>Background</p> <p>There is a need for greater understanding of the impact of multiple sclerosis (MS) from the perspective of individuals with the condition. The South West Impact of MS Project (SWIMS) has been designed to improve understanding of disease impact using a patient-centred approach. The purpose is to (1) develop improved measurement instruments for clinical trials, (2) evaluate longitudinal performance of a variety of patient-reported outcome measures, (3) develop prognostic predictors for use in individualising drug treatment for patients, particularly early on in the disease course.</p> <p>Methods</p> <p>This is a patient-centred, prospective, longitudinal study of multiple sclerosis and clinically isolated syndrome (CIS) in south west England. The study area comprises two counties with a population of approximately 1.7 million and an estimated 1,800 cases of MS. Self-completion questionnaires are administered to participants every six months (for people with MS) or 12 months (CIS). Here we present descriptive statistics of the baseline data provided by 967 participants with MS.</p> <p>Results</p> <p>Seventy-five percent of those approached consented to participate. The male:female ratio was 1.00:3.01 (n = 967). Average (standard deviation) age at time of entry to SWIMS was 51.6 (11.5) years (n = 961) and median (interquartile range) time since first symptom was 13.3 (6.8 to 24.5) years (n = 934). Fatigue was the most commonly reported symptom, with 80% of participants experiencing fatigue at baseline. Although medication use for symptom control was common, there was little evidence of effectiveness, particularly for fatigue. Nineteen percent of participants were unable to classify their subtype of MS. When patient-reported subtype was compared to neurologist assessment for a sample of participants (n = 396), agreement in disease sub-type was achieved in 63% of cases. There were 836 relapses, reported by 931 participants, in the twelve months prior to baseline. Twenty-three percent of the relapsing-remitting group and 12% of the total sample were receiving disease-modifying therapy at baseline.</p> <p>Conclusions</p> <p>Demographics of this sample were similar to published data for the UK. Overall, the results broadly reflect clinical experience in confirming high symptom prevalence, with relatively little complete symptom relief. Participants often had difficulty in defining MS relapses and their own MS type.</p

Use of directed acyclic graphs (DAGs) to identify confounders in applied health research: review and recommendations

Abstract Background Directed acyclic graphs (DAGs) are an increasingly popular approach for identifying confounding variables that require conditioning when estimating causal effects. This review examined the use of DAGs in applied health research to inform recommendations for improving their transparency and utility in future research. Methods Original health research articles published during 1999–2017 mentioning ‘directed acyclic graphs’ (or similar) or citing DAGitty were identified from Scopus, Web of Science, Medline and Embase. Data were extracted on the reporting of: estimands, DAGs and adjustment sets, alongside the characteristics of each article’s largest DAG. Results A total of 234 articles were identified that reported using DAGs. A fifth (n = 48, 21%) reported their target estimand(s) and half (n = 115, 48%) reported the adjustment set(s) implied by their DAG(s). Two-thirds of the articles (n = 144, 62%) made at least one DAG available. DAGs varied in size but averaged 12 nodes [interquartile range (IQR): 9–16, range: 3–28] and 29 arcs (IQR: 19–42, range: 3–99). The median saturation (i.e. percentage of total possible arcs) was 46% (IQR: 31–67, range: 12–100). 37% (n = 53) of the DAGs included unobserved variables, 17% (n = 25) included ‘super-nodes’ (i.e. nodes containing more than one variable) and 34% (n = 49) were visually arranged so that the constituent arcs flowed in the same direction (e.g. top-to-bottom). Conclusion There is substantial variation in the use and reporting of DAGs in applied health research. Although this partly reflects their flexibility, it also highlights some potential areas for improvement. This review hence offers several recommendations to improve the reporting and use of DAGs in future research

An interdisciplinary team communication framework and its application to healthcare 'e-teams' systems design

<p>Abstract</p> <p>Background</p> <p>There are few studies that examine the processes that interdisciplinary teams engage in and how we can design health information systems (HIS) to support those team processes. This was an exploratory study with two purposes: (1) To develop a framework for interdisciplinary team communication based on structures, processes and outcomes that were identified as having occurred during weekly team meetings. (2) To use the framework to guide 'e-teams' HIS design to support interdisciplinary team meeting communication.</p> <p>Methods</p> <p>An ethnographic approach was used to collect data on two interdisciplinary teams. Qualitative content analysis was used to analyze the data according to structures, processes and outcomes.</p> <p>Results</p> <p>We present details for team meta-concepts of structures, processes and outcomes and the concepts and sub concepts within each meta-concept. We also provide an exploratory framework for interdisciplinary team communication and describe how the framework can guide HIS design to support 'e-teams'.</p> <p>Conclusion</p> <p>The structures, processes and outcomes that describe interdisciplinary teams are complex and often occur in a non-linear fashion. Electronic data support, process facilitation and team video conferencing are three HIS tools that can enhance team function.</p

Use of Quantitative Pharmacology in the Development of HAE1, a High-Affinity Anti-IgE Monoclonal Antibody

HAE1, a high-affinity anti-IgE monoclonal antibody, is discussed here as a case study in the use of quantitative pharmacology in the development of a second-generation molecule. In vitro, preclinical, and clinical data from the first-generation molecule, omalizumab, were heavily leveraged in the HAE1 program. A preliminary mechanism-based pharmacokinetic/pharmacodynamic (PK/PD) model for HAE1 was developed using an existing model for omalizumab, together with in vitro binding data for HAE1 and omalizumab. When phase I data were available, the model was refined by simultaneously modeling PK/PD data from omalizumab studies with the available HAE1 phase I data. The HAE1 clinical program was based on knowledge of the quantitative relationship between a pharmacodynamic biomarker, suppression of free IgE, and clinical response (e.g., lower exacerbation rates) obtained in pivotal studies with omalizumab. A clinical trial simulation platform was developed to predict free IgE levels and clinical responses following attainment of a target free IgE level (≤10 IU/ml). The simulation platform enabled selection of four doses for the phase II dose-ranging trial by two independent methods: dose-response non-linear fitting and linear mixed modeling. Agreement between the two methods provided confidence in the doses selected. Modeling and simulation played a large role in supporting acceleration of the HAE1 program by enabling data-driven decision-making, often based on confirmation of projections and/or learning from incoming new data

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.