Leveraging generative AI to assist biocuration of medical actions for rare disease.

Motivation: Structured representations of clinical data can support computational analysis of individuals and cohorts, and ontologies representing disease entities and phenotypic abnormalities are now commonly used for translational research. The Medical Action Ontology (MAxO) provides a computational representation of treatments and other actions taken for clinical management. Currently, manual biocuration is used to annotate MAxO terms to rare diseases.

The Filament Union Sign: Prevalence and Clinical Outcomes of Incomplete Bone Remodeling Following Percutaneous Hallux Valgus Surgery.

Background: Minimally invasive hallux valgus surgery can rarely result in a distinct radiologic finding termed the "Filament Union sign," characterized by a thin, filamentous bone bridge at the osteotomy site <25% of the metatarsal head width and associated with minimal medial, lateral, or central remodeling. This study aimed to determine its prevalence and identify potential contributing factors.

Methods: A retrospective radiographic cohort study analyzed 726 feet that underwent percutaneous fourth-generation transverse osteotomy for hallux valgus correction between November 2017 and January 2023.

Advancing Age and Risk From the Elevated Atherogenic Index: Triglyceride (TG) to High-Density Cholesterol (HDL-C) Ratio.

Background: Low-density lipoprotein cholesterol (LDL-C) is associated with atherosclerotic cardiovascular disease (ASCVD), but this association diminishes with age. The triglyceride (TG) to high-density lipoprotein cholesterol (HDL-C) ratio, also known as the atherogenic index, is a surrogate marker for small-density low-density lipoprotein cholesterol (sdLDL-C), a more specific LDL-C biomarker associated with ASCVD. It is unclear if age influences the association between the atherogenic index and incident ASCVD.

Inborn errors of immunity: manifestation, treatment, and outcome - an ESID registry 1994-2024 report on 30,628 patients.

The patient registry (ESID-R), established in 1994, is one of the world's largest databases on inborn errors of immunity (IEI). IEI are genetic disorders predisposing patients to infections, autoimmunity, inflammation, allergies and malignancies. Treatments include antimicrobial therapy, immunoglobulin replacement, immune modulation, stem cell transplantation and gene therapy.

A Comprehensive Molecular and Serological Investigation of Hepatitis A Virus Among Patients With Suspected Acute Hepatitis: A Brazilian Study.

Hepatitis A Virus (HAV) infects millions of individuals annually and is a major cause of acute viral hepatitis worldwide. This study aims to (1) assess HAV infection in suspected acute hepatitis patients at public healthcare institutions in Brazil; (2) evaluate the proportion of immunized individuals against HAV; (3) identify HAV genotypes; (4) examine the association between HAV infection and demographic data, as well as exposure to risk factors. This is a prospective, observational multicenter study conducted in primary health services in Brazil from October 2019 to May 2023, involving 1721 patients with suspected acute hepatitis.

The non-market value of reclaiming natural landscape and biodiversity: a Dutch case study.

Unlabelled: Biodiversity and natural landscapes have been lost over time due to global agricultural expansion and urbanization. Our study assesses the non-market economic value of reclaiming natural landscapes in the Zuid-Limburg region of the Netherlands, a country in which large-scale intensive agriculture dominates rural landscapes. Through a discrete choice experiment conducted among non-residents of Zuid-Limburg, we find that individuals planning to visit the area are willing to contribute a similar (insignificantly different) monetary amount toward conservation efforts in the area as those who do not plan to visit.

Ontology-based modeling, integration, and analysis of heterogeneous clinical, pathological, and molecular kidney data for precision medicine.

Many data resources generate, process, store, or provide kidney related molecular, pathological, and clinical data. Reference ontologies offer an opportunity to support knowledge and data integration. The Kidney Precision Medicine Project (KPMP) team contributed to the representation and addition of 329 kidney phenotype terms to the Human Phenotype Ontology (HPO), and identified many subcategories of acute kidney injury (AKI) or chronic kidney disease (CKD).

Integrating Knowledge: The Power of Ontologies in Psychiatric Research and Clinical Informatics.

Ontologies are structured frameworks for representing knowledge by systematically defining concepts, categories, and their relationships. While widely adopted in biomedicine, ontologies remain largely absent in mental health research and clinical care, where the field continues to rely heavily on existing classification systems (e.g.

Determining the most effective shade system based on physiological and productive performance of Bos taurus bulls in a subtropical climate.

The aim was to identify the best of four shade systems based on the physiological and productive responses of Bos taurus bulls in a subtropical climate. A total of 804 bulls from Bos taurus, Bos indicus, and their crosses were randomly allotted to 12 pens (n = 67 bulls/pen), which were randomly assigned to one of four treatments (3 pens/treatment): (1) Conventional shade (CSS), (2) double shade (DSH), (3) dome without fans (DNF), and (4) dome with fans (DWF). Five Bos taurus bulls per pen were randomly selected for physiological evaluation and collection of blood samples.

Linking international registries to FHIR and Phenopackets with RareLink: a scalable REDCap-based framework for rare disease data interoperability.

While Research Electronic Data Capture (REDCap) has been widely adopted in rare disease research, its unconstrained data format often leads to implementations that lack native interoperability with global health data standards, limiting secondary data use. To address this, we developed and validated , an open-source framework implementing our previously-published ontology-based rare disease common data model, enabling standardised data exchange between REDCap, international registries, and downstream analysis tools. Its preconfigured pipelines interact with the local REDCap application programming interface and enable semi-automatic import or export of data to the Global Alliance for Genomics and Health (GA4GH) Phenopackets and Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) instances, conforming to the HL7 International Patient Summary and Genomics Reporting profiles.

Replacing non-biomedical concepts improves embedding of biomedical concepts.

Embeddings are semantically meaningful representations of words in a vector space, commonly used to enhance downstream machine learning applications. Traditional biomedical embedding techniques often replace all synonymous words representing biological or medical concepts with a unique token, ensuring consistent representation and improving embedding quality. However, the potential impact of replacing non-biomedical concept synonyms has received less attention.

Fine-tuning of conditional Transformers improves enzyme prediction and generation.

We introduce , a Protein Language Model (PLM) that employs a multifaceted learning strategy based on transfer learning from a decoder-based Transformer, conditional learning using specific functional keywords, and fine-tuning for the modeling of enzymes. Our experiments show that significantly enhances generalist PLMs like ProGen for the prediction and generation of enzymes belonging to specific Enzyme Commission (EC) categories. Our experiments demonstrate that generated sequences can diverge from natural ones, while retaining similar predicted tertiary structure, predicted functions and the active sites of their natural counterparts.

Human Phenotype Ontology Annotations for Rare Congenital Conditions: Application to Arthrogryposis Multiplex Congenita.

Arthrogryposis multiplex congenita (AMC) represents a large, rare group of congenital conditions. This study addressed major challenges in AMC research posed by the lack of systematic frameworks for data collection and the use of inconsistent terminologies and text descriptions. We aimed to systematically review the Human Phenotype Ontology (HPO) terms, encode AMC phenotypic traits as HPO terms, and pilot test the encoding process in a cohort of children with AMC.

Towards a standard benchmark for phenotype-driven variant and gene prioritisation algorithms: PhEval - Phenotypic inference Evaluation framework.

Background: Computational approaches to support rare disease diagnosis are challenging to build, requiring the integration of complex data types such as ontologies, gene-to-phenotype associations, and cross-species data into variant and gene prioritisation algorithms (VGPAs). However, the performance of VGPAs has been difficult to measure and is impacted by many factors, for example, ontology structure, annotation completeness or changes to the underlying algorithm. Assertions of the capabilities of VGPAs are often not reproducible, in part because there is no standardised, empirical framework and openly available patient data to assess the efficacy of VGPAs-ultimately hindering the development of effective prioritisation tools.

GA4GH Phenopacket-Driven Characterization of Genotype-Phenotype Correlations in Mendelian Disorders.

Comprehensively characterizing genotype-phenotype correlations (GPCs) in Mendelian disease would create new opportunities for improving clinical management and understanding disease biology. However, heterogeneous approaches to data sharing, reuse, and analysis have hindered progress in the field. We developed Genotype Phenotype Evaluation of Statistical Association (GPSEA), a software package that leverages the Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema to represent case-level clinical and genetic data about individuals.

Comparative Analysis of the Sensitivity, Specificity, Concordance, and 5-Year Predictive Power of Diabetes-Related Autoantibody Assays.

Interassay concordance and 5-year diabetes prediction of islet cell autoantibody detection using the radiobinding assay (TrialNet), two independently developed multiplex electrochemiluminescence detection methods, the luciferase immune precipitation system, detection by agglutination-PCR, and truncated GADA, and IA2βA radiobinding assays are reported. There was considerable discordance that varied by type of autoantibody across the assays. Type 1 diabetes prediction was relatively high and uniform, implying confirmation of increased diabetes risk among those who are multiple autoantibody positive, although substantial false positive rates need to be considered when autoantibodies alone are used for screening to identify high diabetes risk.

Consistent Performance of GPT-4o in Rare Disease Diagnosis Across Nine Languages and 4967 Cases.

Background: Large language models (LLMs) are increasingly used in the medical field for diverse applications including differential diagnostic support. The estimated training data used to create LLMs such as the Generative Pretrained Transformer (GPT) predominantly consist of English-language texts, but LLMs could be used across the globe to support diagnostics if language barriers could be overcome. Initial pilot studies on the utility of LLMs for differential diagnosis in languages other than English have shown promise, but a large-scale assessment on the relative performance of these models in a variety of European and non-European languages on a comprehensive corpus of challenging rare-disease cases is lacking.

The Unified Phenotype Ontology : a framework for cross-species integrative phenomics.

Phenotypic data are critical for understanding biological mechanisms and consequences of genomic variation, and are pivotal for clinical use cases such as disease diagnostics and treatment development. For over a century, vast quantities of phenotype data have been collected in many different contexts covering a variety of organisms. The emerging field of phenomics focuses on integrating and interpreting these data to inform biological hypotheses.

Rare disease gene association discovery in the 100,000 Genomes Project.

Up to 80% of rare disease patients remain undiagnosed after genomic sequencing, with many probably involving pathogenic variants in yet to be discovered disease-gene associations. To search for such associations, we developed a rare variant gene burden analytical framework for Mendelian diseases, and applied it to protein-coding variants from whole-genome sequencing of 34,851 cases and their family members recruited to the 100,000 Genomes Project. A total of 141 new associations were identified, including five for which independent disease-gene evidence was recently published.

Geometric influences on the regional organization of the mammalian brain.

The mammalian brain is comprised of anatomically and functionally distinct regions. Substantial work over the past century has pursued the generation of ever-more accurate maps of regional boundaries, using either expert judgement or data-driven clustering of functional, connectional, and/or architectonic properties. However, these approaches are often purely descriptive, have limited generalizability, and do not elucidate the underlying generative mechanisms that shape the regional organization of the brain.

An ontology-based rare disease common data model harmonising international registries, FHIR, and Phenopackets.

Although rare diseases (RDs) affect over 260 million individuals worldwide, low data quality and scarcity challenge effective care and research. This work aims to harmonise the Common Data Set by European Rare Disease Registry Infrastructure, Health Level 7 Fast Healthcare Interoperability Base Resources, and the Global Alliance for Genomics and Health Phenopacket Schema into a novel rare disease common data model (RD-CDM), laying the foundation for developing international RD-CDMs aligned with these data standards. We developed a modular-based GitHub repository and documentation to account for flexibility, extensions and further development.

Phenotypic Expansion of Knobloch Syndrome Type 2 in an Individual With a De Novo PAK2 Variant.

P21-activated kinase 2 (PAK2) is a serine/threonine kinase essential for a variety of cellular processes including signal transduction, cellular survival, proliferation, and migration. A recent report proposed monoallelic PAK2 variants cause Knobloch syndrome type 2 (KNO2)-a developmental disorder primarily characterized by ocular anomalies. Here, we identified a novel de novo heterozygous missense variant in PAK2, NM_002577.

Fetal imaging, phenotyping, and genomic testing in modern prenatal diagnosis.

Genetic tests available in the prenatal setting have expanded rapidly with next generation sequencing, and fetal imaging can detect a breadth of many structural and functional abnormalities. To identify a fetal genetic disease, deep phenotyping is increasingly important to generate a differential diagnosis, choose the most appropriate genetic tests, and inform the results of those tests. The Human Phenotype Ontology (HPO) organizes and defines the features of human disease to support deep phenotyping, and ongoing efforts are being made to improve the scope of the HPO to comprehensively include fetal phenotypes.

Efficient reinterpretation of rare disease cases using Exomiser.

Whole genome sequencing has transformed rare disease research; however, 50-80% of rare disease patients remain undiagnosed after such testing. Regular reanalysis can identify new diagnoses, especially in newly discovered disease-gene associations, but efficient tools are required to support clinical interpretation. Exomiser, a phenotype-driven variant prioritisation tool, fulfils this role; within the 100,000 Genomes Project (100kGP), diagnoses were identified after reanalysis in 463 (2%) of 24,015 unsolved patients after previous analysis for variants in known disease genes.