Immune Responses to Viral Gene Therapy Vectors

Several viral vector-based gene therapy drugs have now received marketing approval. A much larger number of additional viral vectors are in various stages of clinical trials for the treatment of genetic and acquired diseases, with many more in pre-clinical testing. Efficiency of gene transfer and ability to provide long-term therapy make these vector systems very attractive. In fact, viral vector gene therapy has been able to treat or even cure diseases for which there had been no or only suboptimal treatments. However, innate and adaptive immune responses to these vectors and their transgene products constitute substantial hurdles to clinical development and wider use in patients. This review provides an overview of the type of immune responses that have been documented in animal models and in humans who received gene transfer with one of three widely tested vector systems, namely adenoviral, lentiviral, or adeno-associated viral vectors. Particular emphasis is given to mechanisms leading to immune responses, efforts to reduce vector immunogenicity, and potential solutions to the problems. At the same time, we point out gaps in our knowledge that should to be filled and problems that need to be addressed going forward

Challenges in the care of individuals with severe primary insulin-like growth factor-I deficiency (SPIGFD): an international, multi-stakeholder perspective

BACKGROUND: Severe primary insulin-like growth factor-I (IGF-I) deficiency (SPIGFD) is a rare growth disorder characterized by short stature (standard deviation score [SDS] ≤ 3.0), low circulating concentrations of IGF-I (SDS ≤ 3.0), and normal or elevated concentrations of growth hormone (GH). Laron syndrome is the best characterized form of SPIGFD, caused by a defect in the GH receptor (GHR) gene. However, awareness of SPIGFD remains low, and individuals living with SPIGFD continue to face challenges associated with diagnosis, treatment and care. OBJECTIVE: To gather perspectives on the key challenges for individuals and families living with SPIGFD through a multi-stakeholder approach. By highlighting critical gaps in the awareness, diagnosis, and management of SPIGFD, this report aims to provide recommendations to improve care for people affected by SPIGFD globally. METHODS: An international group of clinical experts, researchers, and patient and caregiver representatives from the SPIGFD community participated in a virtual, half-day meeting to discuss key unmet needs and opportunities to improve the care of people living with SPIGFD. RESULTS: As a rare disorder, limited awareness and understanding of SPIGFD amongst healthcare professionals (HCPs) poses significant challenges in the diagnosis and treatment of those affected. Patients often face difficulties associated with receiving a formal diagnosis, delayed treatment initiation and limited access to appropriate therapy. This has a considerable impact on the physical health and quality of life for patients, highlighting a need for more education and clearer guidance for HCPs. Support from patient advocacy groups is valuable in helping patients and their families to find appropriate care. However, there remains a need to better understand the burden that SPIGFD has on individuals beyond height, including the impact on physical, emotional, and social wellbeing. CONCLUSIONS: To address the challenges faced by individuals and families affected by SPIGFD, greater awareness of SPIGFD is needed within the healthcare community, and a consensus on best practice in the care of individuals affected by this condition. Continued efforts are also needed at a global level to challenge existing perceptions around SPIGFD, and identify solutions that promote equitable access to appropriate care. Medical writing support was industry-sponsored

Effect of CpG Depletion of Vector Genome on CD8+ T Cell Responses in AAV Gene Therapy

Adeno associated viral (AAV) vectors have emerged as a preferred platform for in vivo gene replacement therapy and represent one of the most promising strategies to treat monogenetic disorders such as hemophilia. However, immune responses to gene transfer have hampered human gene therapy in clinical trials. Over the past decade, it has become clear that innate immune recognition provides signals for the induction of antigen-specific responses against vector or transgene product. In particular, TLR9 recognition of the vector's DNA genome in plasmacytoid dendritic cells (pDCs) has been identified as a key factor. Data from clinical trials and pre-clinical studies implement CpG motifs in the vector genome as drivers of immune responses, especially of CD8+ T cell activation. Here, we demonstrate that cross-priming of AAV capsid-specific CD8+ T cells depends on XCR1+ dendritic cells (which are likely the main cross-presenting cell that cooperates with pDCs to activate CD8+ T cells) and can be minimized by the elimination of CpG motifs in the vector genome. Further, a CpG-depleted vector expressing human coagulation factor IX showed markedly reduced (albeit not entirely eliminated) CD8+ T cell infiltration upon intramuscular gene transfer in hemophilia B mice when compared to conventional CpG+ vector (comprised of native sequences), resulting in better preservation of transduced muscle fibers. Therefore, this deimmunization strategy is helpful in reducing the potential for CD8+ T cell responses to capsid or transgene product. However, CpG depletion had minimal effects on antibody responses against capsid or transgene product, which appear to be largely independent of CpG motifs

Identifying invasive species threats, pathways, and impacts to improve biosecurity

Managing invasive species with prevention and early-detection strategies can avert severe ecological and economic impacts. Horizon scanning, an evidence-based process combining risk screening and consensus building to identify threats, has become a valuable tool for prioritizing invasive species management and prevention. We assembled a working group of experts from academic, government, and nonprofit agencies and organizations, and conducted a multi-taxa horizon scan for Florida, USA, the first of its kind in North America. Our primary objectives were to identify high-risk species and their introduction pathways, to detail the magnitude and mechanism of potential impacts, and, more broadly, to demonstrate the utility of horizon scanning. As a means to facilitate future horizon scans, we document the process used to generate the list of taxa for screening. We evaluated 460 taxa for their potential to arrive, establish, and cause negative ecological and socioeconomic impacts, and identified 40 potential invaders, including alewife, zebra mussel, crab-eating macaque, and red swamp crayfish. Vertebrates and aquatic invertebrates posed the greatest invasion threat, over half of the high-risk taxa were omnivores, and there was high confidence in the scoring of high-risk taxa. Common arrival pathways were ballast water, biofouling of vessels, and escape from the pet/aquarium/horticulture trade. Competition, predation, and damage to agriculture/forestry/aquaculture were common impact mechanisms. We recommend full risk analysis for the high-risk taxa; increased surveillance at Florida's ports, state borders, and high-risk pathways; and periodic review and revision of the list. Few horizon scans detail the comprehensive methodology (including list-building), certainty estimates for all scoring categories and the final score, detailed pathways, and the magnitude and mechanism of impact. Providing this information can further inform prevention efforts and can be efficiently replicated in other regions. Moreover, harmonizing methodology can facilitate data sharing and enhance interpretation of results for stakeholders and the general public.</p

Making Connections: A Handbook for Effective Formal Mentoring Programs in Academia

This book, Making Connections: A Handbook for Effective Formal Mentoring Programs in Academia, makes a unique and needed contribution to the mentoring field as it focuses solely on mentoring in academia. This handbook is a collaborative institutional effort between Utah State University’s (USU) Empowering Teaching Open Access Book Series and the Mentoring Institute at the University of New Mexico (UNM). This book is available through (a) an e-book through Pressbooks, (b) a downloadable PDF version on USU’s Open Access Book Series website), and (c) a print version available for purchase on the USU Empower Teaching Open Access page, and on Amazon

Sushi in the United States, 1945-1970

Sushi first achieved widespread popularity in the United States in the mid-1960s. Many accounts of sushi’s US establishment foreground the role of a small number of key actors, yet underplay the role of a complex web of large-scale factors that provided the context in which sushi was able to flourish. This article critically reviews existing literature, arguing that sushi’s US popularity arose from contingent, long-term, and gradual processes. It examines US newspaper accounts of sushi during 1945–1970, which suggest the discursive context for US acceptance of sushi was considerably more propitious than generally acknowledged. Using California as a case study, the analysis also explains conducive social and material factors, and directs attention to the interplay of supply- and demand-side forces in the favorable positioning of this “new” food. The article argues that the US establishment of sushi can be understood as part of broader public acceptance of Japanese cuisine

An Empirical Comparison of Consumer Innovation Adoption Models: Implications for Subsistence Marketplaces

So called “pro-poor” innovations may improve consumer wellbeing in subsistence marketplaces. However, there is little research that integrates the area with the vast literature on innovation adoption. Using a questionnaire where respondents were asked to provide their evaluations about a mobile banking innovation, this research fills this gap by providing empirical evidence of the applicability of existing innovation adoption models in subsistence marketplaces. The study was conducted in Bangladesh among a geographically dispersed sample. The data collected allowed an empirical comparison of models in a subsistence context. The research reveals the most useful models in this context to be the Value Based Adoption Model and the Consumer Acceptance of Technology model. In light of these findings and further examination of the model comparison results the research also shows that consumers in subsistence marketplaces are not just motivated by functionality and economic needs. If organizations cannot enhance the hedonic attributes of a pro-poor innovation, and reduce the internal/external constraints related to adoption of that pro-poor innovation, then adoption intention by consumers will be lower

Quality indicators for patients with traumatic brain injury in European intensive care units

Background: The aim of this study is to validate a previously published consensus-based quality indicator set for the management of patients with traumatic brain injury (TBI) at intensive care units (ICUs) in Europe and to study its potential for quality measur

Changing care pathways and between-center practice variations in intensive care for traumatic brain injury across Europe

Purpose: To describe ICU stay, selected management aspects, and outcome of Intensive Care Unit (ICU) patients with traumatic brain injury (TBI) in Europe, and to quantify variation across centers. Methods: This is a prospective observational multicenter study conducted across 18 countries in Europe and Israel. Admission characteristics, clinical data, and outcome were described at patient- and center levels. Between-center variation in the total ICU population was quantified with the median odds ratio (MOR), with correction for case-mix and random variation between centers. Results: A total of 2138 patients were admitted to the ICU, with median age of 49 years; 36% of which were mild TBI (Glasgow Coma Scale; GCS 13–15). Within, 72 h 636 (30%) were discharged and 128 (6%) died. Early deaths and long-stay patients (> 72 h) had more severe injuries based on the GCS and neuroimaging characteristics, compared with short-stay patients. Long-stay patients received more monitoring and were treated at higher intensity, and experienced worse 6-month outcome compared to short-stay patients. Between-center variations were prominent in the proportion of short-stay patients (MOR = 2.3, p < 0.001), use of intracranial pressure (ICP) monitoring (MOR = 2.5, p < 0.001) and aggressive treatme

Machine learning algorithms performed no better than regression models for prognostication in traumatic brain injury

Objective: We aimed to explore the added value of common machine learning (ML) algorithms for prediction of outcome for moderate and severe traumatic brain injury. Study Design and Setting: We performed logistic regression (LR), lasso regression, and ridge regression with key baseline predictors in the IMPACT-II database (15 studies, n = 11,022). ML algorithms included support vector machines, random forests, gradient boosting machines, and artificial neural networks and were trained using the same predictors. To assess generalizability of predictions, we performed internal, internal-external, and external validation on the recent CENTER-TBI study (patients with Glasgow Coma Scale <13, n = 1,554). Both calibration (calibration slope/intercept) and discrimination (area under the curve) was quantified. Results: In the IMPACT-II database, 3,332/11,022 (30%) died and 5,233(48%) had unfavorable outcome (Glasgow Outcome Scale less than 4). In the CENTER-TBI study, 348/1,554(29%) died and 651(54%) had unfavorable outcome. Discrimination and calibration varied widely between the studies and less so between the studied algorithms. The mean area under the curve was 0.82 for mortality and 0.77 for unfavorable outcomes in the CENTER-TBI study. Conclusion: ML algorithms may not outperform traditional regression approaches in a low-dimensional setting for outcome prediction after moderate or severe traumatic brain injury. Similar to regression-based prediction models, ML algorithms should be rigorously validated to ensure applicability to new populations