An open source knowledge graph ecosystem for the life sciences.

Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, and methods exist to construct them automatically. However, tackling complex biomedical integration problems requires flexibility in the way knowledge is modeled. Moreover, existing KG construction methods provide robust tooling at the cost of fixed or limited choices among knowledge representation models. PheKnowLator (Phenotype Knowledge Translator) is a semantic ecosystem for automating the FAIR (Findable, Accessible, Interoperable, and Reusable) construction of ontologically grounded KGs with fully customizable knowledge representation. The ecosystem includes KG construction resources (e.g., data preparation APIs), analysis tools (e.g., SPARQL endpoint resources and abstraction algorithms), and benchmarks (e.g., prebuilt KGs). We evaluated the ecosystem by systematically comparing it to existing open-source KG construction methods and by analyzing its computational performance when used to construct 12 different large-scale KGs. With flexible knowledge representation, PheKnowLator enables fully customizable KGs without compromising performance or usability.

Vestibular Testing and Impairments in Postoperative Pediatric Cerebellar Mutism Syndrome: A Case Series.

BACKGROUND: Postoperative pediatric cerebellar mutism syndrome (CMS) may occur following a process affecting the posterior cranial fossa. Recent evidence demonstrates disabling and potentially lasting motor components of this syndrome, including ataxia, hemiparesis, and oculomotor dysfunction. These impairments may contribute to vestibular deficits. METHODS: This case series contributes data to quantify vestibular dysfunction in postoperative CMS. The pair consisted of one female and one male. RESULTS: Vestibular testing demonstrated both peripheral and central dysfunction. CONCLUSIONS: Given these findings, a thorough vestibular assessment may be indicated as part of a comprehensive evaluation following a postoperative CMS diagnosis. Further research is needed to understand the pathophysiology, treatment, and long-term outcomes of postoperative pediatric CMS.

Experiences of young adults with cerebral palsy in pediatric care transitioning to adult care.

AIM: To increase understanding regarding the experiences and values of young adults with cerebral palsy (CP), and their caregivers, regarding pediatric rehabilitation-related care, including perceived barriers and potential facilitators to transition to adult care. METHOD: This was a qualitative descriptive study that used 20 semi-structured interviews (13 caregivers and seven patient-caregiver dyads). RESULTS: We identified four major themes: (1) the value and security of long-term relationships; (2) feeling 'rudderless' navigating the logistics of transition; (3) differences in pediatric versus adult models of care; and (4) perceived lack of provider expertise and comfort in adult care settings. Young adults with CP who had not yet transitioned to adult rehabilitation care and their caregivers placed high value on provider relationships and expertise, advanced planning, communication, and coordination of care. INTERPRETATION: Identified barriers and potential facilitators to the transition to adult rehabilitation care reflected the uncertainty that accompanies leaving an established healthcare relationship. Challenges related to the logistics of this transition, differences in models of care, and perceived lack of provider comfort and expertise in adult care settings were also noted. Our findings could be used to develop and study patient-centered and family-centered transition processes for individuals with CP to promote age-appropriate and developmentally appropriate lifespan care.

Utility of Early Magnetic Resonance Imaging to Enhance Outcome Prediction in Critically Ill Children with Severe Traumatic Brain Injury.

BACKGROUND: Many children with severe traumatic brain injury (TBI) receive magnetic resonance imaging (MRI) during hospitalization. There are insufficient data on how different patterns of injury on early MRI inform outcomes. METHODS: Children (3-17 years) admitted in 2010-2021 for severe TBI (Glasgow Coma Scale [GCS] score < 9) were identified using our site's trauma registry. We used multivariable modeling to determine whether the hemorrhagic diffuse axonal injury (DAI) grade and the number of regions with restricted diffusion (subcortical white matter, corpus callosum, deep gray matter, and brainstem) on MRI obtained within 7 days of injury were independently associated with time to follow commands and with Functional Independence Measure for Children (WeeFIM) scores at the time of discharge from inpatient rehabilitation. We controlled for the clinical variables age, preadmission cardiopulmonary resuscitation, pupil reactivity, motor GCS score, and fever (> 38 °C) in the first 12 h. RESULTS: Of 260 patients, 136 (52%) underwent MRI within 7 days of injury at a median of 3 days (interquartile range [IQR] 2-4). Patients with early MRI were a median age of 11 years (IQR 7-14), 8 (6%) patients received cardiopulmonary resuscitation, 19 (14%) patients had bilateral unreactive pupils, the median motor GCS score was 1 (IQR 1-4), and 82 (60%) patients had fever. Grade 3 DAI was present in 46 (34%) patients, and restricted diffusion was noted in the corpus callosum in 75 (55%) patients, deep gray matter in 29 (21%) patients, subcortical white matter in 23 (17%) patients, and the brainstem in 20 (15%) patients. After controlling for clinical variables, an increased number of regions with restricted diffusion, but not hemorrhagic DAI grade, was independently associated with longer time to follow commands (hazard ratio 0.68, 95% confidence interval 0.53-0.89) and worse WeeFIM scores (estimate ß - 4.67, 95% confidence interval - 8.33 to - 1.01). CONCLUSIONS: Regional restricted diffusion on early MRI is independently associated with short-term outcomes in children with severe TBI. Multicenter cohort studies are needed to validate these findings and elucidate the association of early MRI features with long-term outcomes in children with severe TBI.

Ontologizing health systems data at scale: making translational discovery a reality.

Common data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68-99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.

Developmental Outcomes Following Abusive Head Trauma in Infancy: A Systematic Review.

OBJECTIVE: A systematic review of the literature was conducted to identify measures used to evaluate developmental outcomes after abusive head trauma (AHT), as well as describe outcomes among those with AHT, and explore factors and interventions influencing such outcomes. DESIGN: This systematic review adheres to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. The protocol is in PROSPERO, registration number CRD42020179592. On April 17, 2020, OVID Medline, Embase, OVID PsycINFO, Web of Science, CINAHL, Cochrane Library, and Google Scholar were searched (since inception). Inclusion criteria included original, peer-reviewed study data; AHT exposure; infants younger than 24 months at time of AHT; and evaluation of developmental outcomes. Reviewers independently evaluated studies for inclusion and assessed risk of bias using the Effective Public Health Practice Project quality assessment tool for quantitative studies. A descriptive synthesis approach was utilized as variability of study designs, follow-up periods, and outcome assessment tools precluded a meta-analytic approach. RESULTS: Fifty-nine studies were included; 115 assessment tools were used to evaluate developmental outcomes; and 42 studies examined factors influencing outcomes. Two studies evaluated interventions. Five percent of studies ( n = 3) were rated low risk of bias. CONCLUSIONS: Notable variation was observed in terms of case ascertainment criteria. Developmental outcomes after AHT have been assessed in a manner that limits understanding of how AHT impacts development, as well as the efficacy of interventions intended to improve outcomes. Researchers and clinicians are encouraged to adopt consistent diagnostic and assessment approaches.

Knowledge-Driven Mechanistic Enrichment of the Preeclampsia Ignorome.

Preeclampsia is a leading cause of maternal and fetal morbidity and mortality. Currently, the only definitive treatment of preeclampsia is delivery of the placenta, which is central to the pathogenesis of the disease. Transcriptional profiling of human placenta from pregnancies complicated by preeclampsia has been extensively performed to identify differentially expressed genes (DEGs). The decisions to investigate DEGs experimentally are biased by many factors, causing many DEGs to remain uninvestigated. A set of DEGs which are associated with a disease experimentally, but which have no known association to the disease in the literature are known as the ignorome. Preeclampsia has an extensive body of scientific literature, a large pool of DEG data, and only one definitive treatment. Tools facilitating knowledge-based analyses, which are capable of combining disparate data from many sources in order to suggest underlying mechanisms of action, may be a valuable resource to support discovery and improve our understanding of this disease. In this work we demonstrate how a biomedical knowledge graph (KG) can be used to identify novel preeclampsia molecular mechanisms. Existing open source biomedical resources and publicly available high-throughput transcriptional profiling data were used to identify and annotate the function of currently uninvestigated preeclampsia-associated DEGs. Experimentally investigated genes associated with preeclampsia were identified from PubMed abstracts using text-mining methodologies. The relative complement of the text-mined- and meta-analysis-derived lists were identified as the uninvestigated preeclampsia-associated DEGs (n=445), i.e., the preeclampsia ignorome. Using the KG to investigate relevant DEGs revealed 53 novel clinically relevant and biologically actionable mechanistic associations.

Characterizing Patient Representations for Computational Phenotyping.

Patient representation learning methods create rich representations of complex data and have potential to further advance the development of computational phenotypes (CP). Currently, these methods are either applied to small predefined concept sets or all available patient data, limiting the potential for novel discovery and reducing the explainability of the resulting representations. We report on an extensive, data-driven characterization of the utility of patient representation learning methods for the purpose of CP development or automatization. We conducted ablation studies to examine the impact of patient representations, built using data from different combinations of data types and sampling windows on rare disease classification. We demonstrated that the data type and sampling window directly impact classification and clustering performance, and these results differ by rare disease group. Our results, although preliminary, exemplify the importance of and need for data-driven characterization in patient representation-based CP development pipelines.

Suicide After Stroke in the United States Veteran Health Administration Population.

OBJECTIVE: To evaluate risk for suicide among veterans with a history of stroke, seeking care within the Veterans Health Administration (VHA), we analyzed existing clinical data. DESIGN: This retrospective cohort study was approved and performed in accordance with the local Institutional Review Board. Veterans were identified via the VHA's Corporate Data Warehouse. Initial eligibility criteria included confirmed veteran status and at least 90 days of VHA utilization between fiscal years 2001-2015. Cox proportional hazards models were used to assess the association between history of stroke and suicide. Among those veterans who died by suicide, the association between history of stroke and method of suicide was also investigated. SETTING: VHA. PARTICIPANTS: Veterans with at least 90 days of VHA utilization between fiscal years 2001-2015 (N=1,647,671). Data from these 1,647,671 veterans were analyzed (1,405,762 without stroke and 241,909 with stroke). INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURES: Suicide and method of suicide. RESULTS: The fully adjusted model, which controlled for age, sex, mental health diagnoses, mild traumatic brain injury, and modified Charlson/Deyo Index (stroke-related diagnoses excluded), demonstrated a hazard ratio of 1.13 (95% confidence interval, 1.02-1.25; P=.02). The majority of suicides in both cohorts was by firearm, and a significantly larger proportion of suicides occurred by firearm in the group with stroke than the cohort without (81.2% vs 76.6%). CONCLUSIONS: Findings suggest that veterans with a history of stroke are at increased risk for suicide, specifically by firearm, compared with veterans without a history of stroke. Increased efforts are needed to address the mental health needs and lethal means safety of veterans with a history of stroke, with the goal of improving function and decreasing negative psychiatric outcomes, such as suicide.