Causal analysis for multivariate integrated clinical and environmental exposures data.

Electronic health records (EHRs) provide a rich source of observational patient data that can be explored to infer underlying causal relationships. These causal relationships can be applied to augment medical decision-making or suggest hypotheses for healthcare research. In this study, we explored a large-scale EHR dataset on patients with asthma or related conditions (N = 14,937).

FHIR PIT: a geospatial and spatiotemporal data integration pipeline to support subject-level clinical research.

Background: Environmental exposures such as airborne pollutant exposures and socio-economic indicators are increasingly recognized as important to consider when conducting clinical research using electronic health record (EHR) data or other sources of clinical data such as survey data. While numerous public sources of geospatial and spatiotemporal data are available to support such research, the data are challenging to work with due to inconsistencies in file formats and spatiotemporal resolutions, computational challenges with large file sizes, and a lack of tools for patient- or subject-level data integration.

Results: We developed FHIR PIT (HL7® Fast Healthcare Interoperability Resources Patient data Integration Tool) as an open-source, modular, data-integration software pipeline that consumes EHR data in FHIR® format and integrates the data at the level of the patient or subject with environmental exposures data of varying spatiotemporal resolutions and file formats.

Estimating realized relatedness in free-ranging macaques by inferring identity-by-descent segments.

Biological relatedness is a key consideration in studies of behavior, population structure, and trait evolution. Except for parent-offspring dyads, pedigrees capture relatedness imperfectly. The number and length of identical-by-descent DNA segments (IBD) yield the most precise relatedness estimates.

Ecological and anthropogenic effects on the genomic diversity of lemurs in Madagascar.

Ecological variation and anthropogenic landscape modification have had key roles in the diversification and extinction of mammals in Madagascar. Lemurs represent a radiation with more than 100 species, constituting roughly one-fifth of the primate order. Almost all species of lemurs are threatened with extinction, but little is known about their genetic diversity and demographic history.

Generating Biomedical Knowledge Graphs from Knowledge Bases, Registries, and Multiomic Data.

As large clinical and multiomics datasets and knowledge resources accumulate, they need to be transformed into computable and actionable information to support automated reasoning. These datasets range from laboratory experiment results to electronic health records (EHRs). Barriers to accessibility and sharing of such datasets include diversity of content, size and privacy.

AI and Social Determinants of Health in Health Care: A Personal Perspective.

As a biomedical data scientist, when I think of the future of artificial intelligence in health care, the potential fills me with both excitement and caution. A promising area of innovation, AI can be used to assess the impact of social determinants of health on health outcomes, though more standardization is needed.

Enhanced 2D Hand Pose Estimation for Gloved Medical Applications: A Preliminary Model.

(1) Background: As digital health technology evolves, the role of accurate medical-gloved hand tracking is becoming more important for the assessment and training of practitioners to reduce procedural errors in clinical settings. (2) Method: This study utilized computer vision for hand pose estimation to model skeletal hand movements during in situ aseptic drug compounding procedures. High-definition video cameras recorded hand movements while practitioners wore medical gloves of different colors.

BioBricks.ai: A Versioned Data Registry for Life Sciences Data Assets.

Researchers in biomedical research, public health and the life sciences often spend weeks or months discovering, accessing, curating, and integrating data from disparate sources, significantly delaying the onset of actual analysis and innovation. Instead of countless developers creating redundant and inconsistent data pipelines, BioBricks.ai offers a centralized data repository and a suite of developer-friendly tools to simplify access to scientific data.

Adapting Novel Augmented Reality Devices for Patient Simulations in Medical Education.

Extended reality (XR) simulations are becoming increasingly common in educational settings, particularly in medical education. Advancing XR devices to enhance these simulations is a booming field of research. This study seeks to understand the value of a novel, non-wearable mixed reality (MR) display during interactions with a simulated holographic patient, specifically in taking a medical history.

Immune gene regulation is associated with age and environmental adversity in a nonhuman primate.

Phenotypic aging is ubiquitous across mammalian species, suggesting shared underlying mechanisms of aging. Aging is linked to molecular changes to DNA methylation and gene expression, and environmental factors, such as severe external challenges or adversities, can moderate these age-related changes. Yet, it remains unclear whether environmental adversities affect gene regulation via the same molecular pathways as chronological, or 'primary', aging.

Selective classification with machine learning uncertainty estimates improves ACS prediction: A retrospective study in the prehospital setting.

Accurate identification of acute coronary syndrome (ACS) in the prehospital sestting is important for timely treatments that reduce damage to the compromised myocardium. Current machine learning approaches lack sufficient performance to safely rule-in or rule-out ACS. Our goal is to identify a method that bridges this gap.

Wildfires and climate justice: future wildfire events predicted to disproportionally impact socioeconomically vulnerable communities in North Carolina.

Wildfire events are becoming increasingly common across many areas of the United States, including North Carolina (NC). Wildfires can cause immediate damage to properties, and wildfire smoke conditions can harm the overall health of exposed communities. It is critical to identify communities at increased risk of wildfire events, particularly in areas with that have sociodemographic disparities and low socioeconomic status (SES) that may exacerbate incurred impacts of wildfire events.

Plasma complement and coagulation proteins as prognostic factors of negative symptoms: An analysis of the NAPLS 2 and 3 studies.

Introduction: Negative symptoms impact the quality of life of individuals with psychosis and current treatment options for negative symptoms have limited effectiveness. Previous studies have demonstrated that complement and coagulation pathway protein levels are related to later psychotic experiences, psychotic disorder, and functioning. However, the prognostic relationship between complement and coagulation proteins and negative symptoms is poorly characterised.

Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis.

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community.

Taking identity-by-descent analysis into the wild: Estimating realized relatedness in free-ranging macaques.

Biological relatedness is a key consideration in studies of behavior, population structure, and trait evolution. Except for parent-offspring dyads, pedigrees capture relatedness imperfectly. The number and length of DNA segments that are identical-by-descent (IBD) yield the most precise estimates of relatedness.

Differential expression of haptoglobin in individuals at clinical high risk of psychosis and its association with global functioning and clinical symptoms.

Background: Immune dysregulation has been observed in patients with schizophrenia or first-episode psychosis, but few have examined dysregulation in those at clinical high-risk (CHR) for psychosis. The aim of this study was to examine whether the peripheral blood-based proteome was dysregulated in those with CHR. Secondly, we examined whether baseline dysregulation was related to current and future functioning and clinical symptoms.

ExEmPLAR (Extracting, Exploring, and Embedding Pathways Leading to Actionable Research): a user-friendly interface for knowledge graph mining.

Summary: Knowledge graphs are being increasingly used in biomedical research to link large amounts of heterogenous data and facilitate reasoning across diverse knowledge sources. Wider adoption and exploration of knowledge graphs in the biomedical research community is limited by requirements to understand the underlying graph structure in terms of entity types and relationships, represented as nodes and edges, respectively, and learn specialized query languages for graph mining and exploration. We have developed a user-friendly interface dubbed ExEmPLAR (Extracting, Exploring, and Embedding Pathways Leading to Actionable Research) to aid reasoning over biomedical knowledge graphs and assist with data-driven research and hypothesis generation.

Linking enlarged choroid plexus with plasma analyte and structural phenotypes in clinical high risk for psychosis: A multisite neuroimaging study.

Background: Choroid plexus (ChP) enlargement exists in first-episode and chronic psychosis, but whether enlargement occurs before psychosis onset is unknown. This study investigated whether ChP volume is enlarged in individuals with clinical high-risk (CHR) for psychosis and whether these changes are related to clinical, neuroanatomical, and plasma analytes.

Methods: Clinical and neuroimaging data from the North American Prodrome Longitudinal Study 2 (NAPLS2) was used for analysis.

The Human Phenotype Ontology in 2024: phenotypes around the world.

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.