The DO-KB Knowledgebase: a 20-year journey developing the disease open science ecosystem.

In 2003, the Human Disease Ontology (DO, https://disease-ontology.org/) was established at Northwestern University. In the intervening 20 years, the DO has expanded to become a highly-utilized disease knowledge resource. Serving as the nomenclature and classification standard for human diseases, the DO provides a stable, etiology-based structure integrating mechanistic drivers of human disease. Over the past two decades the DO has grown from a collection of clinical vocabularies, into an expertly curated semantic resource of over 11300 common and rare diseases linking disease concepts through more than 37000 vocabulary cross mappings (v2023-08-08). Here, we introduce the recently launched DO Knowledgebase (DO-KB), which expands the DO's representation of the diseaseome and enhances the findability, accessibility, interoperability and reusability (FAIR) of disease data through a new SPARQL service and new Faceted Search Interface. The DO-KB is an integrated data system, built upon the DO's semantic disease knowledge backbone, with resources that expose and connect the DO's semantic knowledge with disease-related data across Open Linked Data resources. This update includes descriptions of efforts to assess the DO's global impact and improvements to data quality and content, with emphasis on changes in the last two years.

Modeling the enigma of complex disease etiology.

BACKGROUND: Complex diseases often present as a diagnosis riddle, further complicated by the combination of multiple phenotypes and diseases as features of other diseases. With the aim of enhancing the determination of key etiological factors, we developed and tested a complex disease model that encompasses diverse factors that in combination result in complex diseases. This model was developed to address the challenges of classifying complex diseases given the evolving nature of understanding of disease and interaction and contributions of genetic, environmental, and social factors. METHODS: Here we present a new approach for modeling complex diseases that integrates the multiple contributing genetic, epigenetic, environmental, host and social pathogenic effects causing disease. The model was developed to provide a guide for capturing diverse mechanisms of complex diseases. Assessment of disease drivers for asthma, diabetes and fetal alcohol syndrome tested the model. RESULTS: We provide a detailed rationale for a model representing the classification of complex disease using three test conditions of asthma, diabetes and fetal alcohol syndrome. Model assessment resulted in the reassessment of the three complex disease classifications and identified driving factors, thus improving the model. The model is robust and flexible to capture new information as the understanding of complex disease improves. CONCLUSIONS: The Human Disease Ontology's Complex Disease model offers a mechanism for defining more accurate disease classification as a tool for more precise clinical diagnosis. This broader representation of complex disease, therefore, has implications for clinicians and researchers who are tasked with creating evidence-based and consensus-based recommendations and for public health tracking of complex disease. The new model facilitates the comparison of etiological factors between complex, common and rare diseases and is available at the Human Disease Ontology website.

Model for Integration of Monogenic Diabetes Diagnosis Into Routine Care: The Personalized Diabetes Medicine Program.

OBJECTIVE: To implement, disseminate, and evaluate a sustainable method for identifying, diagnosing, and promoting individualized therapy for monogenic diabetes. RESEARCH DESIGN AND METHODS: Patients were recruited into the implementation study through a screening questionnaire completed in the waiting room or through the patient portal, physician recognition, or self-referral. Patients suspected of having monogenic diabetes based on the processing of their questionnaire and other data through an algorithm underwent next-generation sequencing for 40 genes implicated in monogenic diabetes and related conditions. RESULTS: Three hundred thirteen probands with suspected monogenic diabetes (but most diagnosed with type 2 diabetes) were enrolled from October 2014 to January 2019. Sequencing identified 38 individuals with monogenic diabetes, with most variants found in GCK or HNF1A. Positivity rates for ascertainment methods were 3.1% for clinic screening, 5.3% for electronic health record portal screening, 16.5% for physician recognition, and 32.4% for self-referral. The algorithmic criterion of non-type 1 diabetes before age 30 years had an overall positivity rate of 15.0%. CONCLUSIONS: We successfully modeled the efficient incorporation of monogenic diabetes diagnosis into the diabetes care setting, using multiple strategies to screen and identify a subpopulation with a 12.1% prevalence of monogenic diabetes by molecular testing. Self-referral was particularly efficient (32% prevalence), suggesting that educating the lay public in addition to clinicians may be the most effective way to increase the diagnosis rate in monogenic diabetes. Scaling up this model will assure access to diagnosis and customized treatment among those with monogenic diabetes and, more broadly, access to personalized medicine across disease areas.

Review of general and head and neck/oral and maxillofacial features of Charcot-Marie-Tooth disease and dental management considerations.

Charcot-Marie-Tooth disease (CMTD) is an uncommon progressive neuromuscular disorder of the peripheral nervous system and primarily leads to distal extremity weakness and sensory deficits. Frequently, affected patients manifest pes cavus, drop foot, and digit contractures that may pose significant challenges in ambulation and grasping objects. Although there are numerous articles of this syndrome in the medical literature, there is a limited number of dental publications. The objective of this article is to review the general and head and neck/oral and maxillofacial features of CMTD. General guidelines for dental management are also provided.

The Human Disease Ontology 2022 update.

The Human Disease Ontology (DO) (www.disease-ontology.org) database, has significantly expanded the disease content and enhanced our userbase and website since the DO's 2018 Nucleic Acids Research DATABASE issue paper. Conservatively, based on available resource statistics, terms from the DO have been annotated to over 1.5 million biomedical data elements and citations, a 10× increase in the past 5 years. The DO, funded as a NHGRI Genomic Resource, plays a key role in disease knowledge organization, representation, and standardization, serving as a reference framework for multiscale biomedical data integration and analysis across thousands of clinical, biomedical and computational research projects and genomic resources around the world. This update reports on the addition of 1,793 new disease terms, a 14% increase of textual definitions and the integration of 22 137 new SubClassOf axioms defining disease to disease connections representing the DO's complex disease classification. The DO's updated website provides multifaceted etiology searching, enhanced documentation and educational resources.

Open communication of Duchenne muscular dystrophy facilitates disclosure process by parents to unaffected siblings.

Duchenne muscular dystrophy (DMD) is a progressive childhood onset neuromuscular disease with no known cure. There is extensive literature about the impact of a diagnosis on the psychosocial well-being of unaffected siblings, with a need for additional research to provide information about optimal ways to disclose this information to unaffected children. We sought to explore the parental experiences of disclosing a sibling's diagnosis of DMD to unaffected children who were age 8-17 years old either at the time of their sibling's diagnosis or presently. Parents were recruited through Maryland Muscular Dystrophy Association, Parent Project Muscular Dystrophy, and Cincinnati Children's Hospital Medical Center Neuromuscular Center. An interview guide, rooted in family communication, was created to incorporate themes and topics found in literature specific to DMD and disclosure to unaffected siblings. We qualitatively explored these experiences through semi-structured interviews and performed thematic analysis using a coding system to identify overarching themes and subthemes. Several main themes regarding challenges to the disclosure process emerged. We identified the following themes in procedural aspects of disclosure: lack of provider support, importance of the DMD community, and open and gradual timeline of disclosure. Under emotional experiences, we identified these themes: overwhelming nature, elements of surprise disclosure, and balancing parental and sibling needs. Most questions from unaffected siblings related to procedural elements of care such as treatments and equipment. Additional unanticipated themes emerged that may contribute to the knowledge of family culture surrounding DMD: the complex role of Facebook as a family resource, deferring carrier testing for siblings, and inclusion of DMD in school projects. While the process of disclosure is complicated by a variety of factors such as lack of provider support and overwhelming emotional burden, families highlight the importance of open communication in discussion with unaffected children.

Newborn Screening Long Term Follow-Up in the Medical Home.

This demonstration project explored the feasibility of utilizing data from pediatric primary care providers to evaluate the long-term outcomes of children with disorders identified by newborn screening (NBS). Compliance with national guidelines for care and the morbidity for this population was also examined. Primary care practices were recruited and patients with sickle cell disease or who were deaf/hard of hearing were given the opportunity to enroll in the study. Data were collected on the quality of the medical home with practice data compared to family responses. Clinical outcomes for each patient were assessed by review of medical records and patient surveys. These data sources were compared to determine accuracy of primary care data, morbidity, and receipt of preventive care. Electronic data sharing was explored through transmission of Clinical Document Architecture (CDA) files. Care coordination was a challenge, even in highly accredited medical homes. Providers did not have complete information regarding clinical outcomes and children were not consistently receiving recommended preventive care. Electronic data sharing with public health departments encountered interface challenges. Primary care providers in the USA should not currently be used as a sole source to evaluate long-term outcomes of children with disorders identified by NBS.

Human Disease Ontology 2018 update: classification, content and workflow expansion.

The Human Disease Ontology (DO) (http://www.disease-ontology.org), database has undergone significant expansion in the past three years. The DO disease classification includes specific formal semantic rules to express meaningful disease models and has expanded from a single asserted classification to include multiple-inferred mechanistic disease classifications, thus providing novel perspectives on related diseases. Expansion of disease terms, alternative anatomy, cell type and genetic disease classifications and workflow automation highlight the updates for the DO since 2015. The enhanced breadth and depth of the DO's knowledgebase has expanded the DO's utility for exploring the multi-etiology of human disease, thus improving the capture and communication of health-related data across biomedical databases, bioinformatics tools, genomic and cancer resources and demonstrated by a 6.6× growth in DO's user community since 2015. The DO's continual integration of human disease knowledge, evidenced by the more than 200 SVN/GitHub releases/revisions, since previously reported in our DO 2015 NAR paper, includes the addition of 2650 new disease terms, a 30% increase of textual definitions, and an expanding suite of disease classification hierarchies constructed through defined logical axioms.

Genetic Counselors' Experience with and Opinions on the Management of Newborn Screening Incidental Carrier Findings.

Newborn screening (NBS) is a public health program whose aim is to identify infants who will be clinically affected with a serious metabolic, genetic, or endocrine disorder; however, the technology utilized by many NBS programs also detects infants who are heterozygous carriers for autosomal recessive conditions. Discussion surrounding disclosure of these incidental carrier findings remains controversial. The purpose of this study was to assess genetic counselors' attitudes about disclosure of carrier status results generated by NBS and to gather data on their experiences with incidental carrier findings. An electronic survey was distributed to genetic counselors of all specialties via the NSGC listserv, and a total of 235 survey responses were analyzed. Quantitative data were analyzed using IBM SPSS v24, and qualitative data were manually analyzed for thematic analysis. Results show that the counselor participants were overall in favor of routine disclosure. Those with experience in NBS were much more likely to strongly agree with one or more reasons for disclosure (p < 0.001), whereas those with five or fewer years of experience were more likely to strongly agree with one or more reasons for non-disclosure (p = 0.031). Qualitative analysis identified key motivating factors for disclosure, including helping parents to understand a positive screen, parents may otherwise be unaware of reproductive risk and they may not otherwise have access to this information, and, while genetic testing is inherently a complex and ambiguous process, this does not justify non-disclosure. The main motivating factor for non-disclosure was the need for better counseling and informed consent. The data suggest that implementation of an "opt-in/out" policy for parents to decide whether or not to receive incidental findings would be beneficial. The results of this study support the continued disclosure of incidental carrier findings; however, additional research is necessary to further determine and implement the most effective disclosure practices.

Modelling platelet-blood flow interaction using the subcellular element Langevin method.

In this paper, a new three-dimensional modelling approach is described for studying fluid-viscoelastic cell interaction, the subcellular element Langevin (SCEL) method, with cells modelled by subcellular elements (SCEs) and SCE cells coupled with fluid flow and substrate models by using the Langevin equation. It is demonstrated that: (i) the new method is computationally efficient, scaling as (N) for N SCEs; (ii) cell geometry, stiffness and adhesivity can be modelled by directly relating parameters to experimentally measured values; (iii) modelling the fluid-platelet interface as a surface leads to a very good correlation with experimentally observed platelet flow interactions. Using this method, the three-dimensional motion of a viscoelastic platelet in a shear blood flow was simulated and compared with experiments on tracking platelets in a blood chamber. It is shown that the complex platelet-flipping dynamics under linear shear flows can be accurately recovered with the SCEL model when compared with the experiments. All experimental details and electronic supplementary material are archived at http://biomath.math.nd.edu/scelsupplementaryinformation/.