Purpose

To describe the motivations, expectations, and other factors men with X-linked retinoschisis (XLRS) consider when making decisions to participate in an early phase ocular gene therapy clinical trial.

Design

Qualitative interview study.

Methods

Men with XLRS who were considering participation in a phase I/IIa ocular gene therapy clinical trial at the National Eye Institute were eligible for this study. Trial participants (n = 9) were interviewed prior to receiving the gene transfer and then at 3 and 12 months later. Trial participation decliners (n = 2) were interviewed at an initial visit and 12 months later. Those screened for the trial and found ineligible (n = 2) were interviewed at an initial visit only. Interviews were transcribed, coded, and analyzed thematically.

Results

Interview participants described decision making factors as risk-benefit assessments, personal intuition, trust in the study team, and religious faith. Altruism and the potential for therapeutic benefit were the main motives for trial participation, whereas the uncertainty of risks and benefits was the reason 2 men declined participation. Although most participants hoped for direct benefit, no one expected to benefit. Almost all interview participants considered their decision straightforward and were satisfied with their decision when interviewed over time. Meaningful relationships with the study team and perceived secondary benefits to participation contributed to positive trial experiences.

Conclusions

Engaging prospective research participants in a discussion about their hopes, expectations, and personal factors provides a more complete understanding of patient decision making and may help support informed choices to participate in clinical trials for XLRS.

Inborn errors of immunity (IEI) are a genetically heterogeneous group of disorders with a broad clinical spectrum. Identification of molecular and functional bases of these disorders is important for diagnosis, treatment, and an understanding of the human immune response. We identified 6 unrelated males with neutropenia, infections, lymphoproliferation, humoral immune defects, and in some cases bone marrow failure associated with 3 different variants in the X-linked gene TLR8, encoding the endosomal Toll-like receptor 8 (TLR8). Interestingly, 5 patients had somatic variants in TLR8 with <30% mosaicism, suggesting a dominant mechanism responsible for the clinical phenotype. Mosaicism was also detected in skin-derived fibroblasts in 3 patients, demonstrating that mutations were not limited to the hematopoietic compartment. All patients had refractory chronic neutropenia, and 3 patients underwent allogeneic hematopoietic cell transplantation. All variants conferred gain of function to TLR8 protein, and immune phenotyping demonstrated a proinflammatory phenotype with activated T cells and elevated serum cytokines associated with impaired B-cell maturation. Differentiation of myeloid cells from patient-derived induced pluripotent stem cells demonstrated increased responsiveness to TLR8. Together, these findings demonstrate that gain-of-function variants in TLR8 lead to a novel childhood-onset IEI with lymphoproliferation, neutropenia, infectious susceptibility, B- and T-cell defects, and in some cases, bone marrow failure. Somatic mosaicism is a prominent molecular mechanism of this new disease.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven't been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven't been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

The Human Phenotype Ontology (HPO)-a standardized vocabulary of phenotypic abnormalities associated with 7000+ diseases-is used by thousands of researchers, clinicians, informaticians and electronic health record systems around the world. Its detailed descriptions of clinical abnormalities and computable disease definitions have made HPO the de facto standard for deep phenotyping in the field of rare disease. The HPO's interoperability with other ontologies has enabled it to be used to improve diagnostic accuracy by incorporating model organism data. It also plays a key role in the popular Exomiser tool, which identifies potential disease-causing variants from whole-exome or whole-genome sequencing data. Since the HPO was first introduced in 2008, its users have become both more numerous and more diverse. To meet these emerging needs, the project has added new content, language translations, mappings and computational tooling, as well as integrations with external community data. The HPO continues to collaborate with clinical adopters to improve specific areas of the ontology and extend standardized disease descriptions. The newly redesigned HPO website (www.human-phenotype-ontology.org) simplifies browsing terms and exploring clinical features, diseases, and human genes.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.