Michael Tiemeyer | PubMed Health

PubMed2025

The Data Distillery: A Graph Framework for Semantic Integration and Querying of Biomedical Data.

The Data Distillery Knowledge Graph (DDKG) is a framework for semantic integration and querying of biomedical data across domains. Built for the NIH Common Fund Data Ecosystem, it supports translational research by linking clinical and experimental datasets in a unified graph model. Clinical standards such as ICD-10, SNOMED, and DrugBank are integrated through UMLS, while genomics and basic science data are structured using ontologies and standards such as HPO, GENCODE, Ensembl, STRING, and ClinVar. The DDKG uses a property graph architecture based on the UBKG infrastructure and supports ontology-based ingestion, identifier normalization, and graph-native querying. The system is modular and can be extended with new datasets or schema modules. We demonstrate its utility for informatics queries across eight use cases, including regulatory variant analysis, tissue-specific expression, biomarker discovery, and cross-species variant prioritization. The DDKG is accessible via a public interface, a programmatic API, and downloadable builds for local use.

Journal Article↗

PubMed2022

Cystic Fibrosis Airway Mucus Hyperconcentration Produces a Vicious Cycle of Mucin, Pathogen, and Inflammatory Interactions that Promotes Disease Persistence.

The dynamics describing the vicious cycle characteristic of cystic fibrosis (CF) lung disease, initiated by stagnant mucus and perpetuated by infection and inflammation, remain unclear. Here we determine the effect of the CF airway milieu, with persistent mucoobstruction, resident pathogens, and inflammation, on the mucin quantity and quality that govern lung disease pathogenesis and progression. The concentrations of MUC5AC and MUC5B were measured and characterized in sputum samples from subjects with CF (N = 44) and healthy subjects (N = 29) with respect to their macromolecular properties, degree of proteolysis, and glycomics diversity. These parameters were related to quantitative microbiome and clinical data. MUC5AC and MUC5B concentrations were elevated, 30- and 8-fold, respectively, in CF as compared with control sputum. Mucin parameters did not correlate with hypertonic saline, inhaled corticosteroids, or antibiotics use. No differences in mucin parameters were detected at baseline versus during exacerbations. Mucin concentrations significantly correlated with the age and sputum human neutrophil elastase activity. Although significantly more proteolytic cleavages were detected in CF mucins, their macromolecular properties (e.g., size and molecular weight) were not significantly different than control mucins, likely reflecting the role of S-S bonds in maintaining multimeric structures. No evidence of giant mucin macromolecule reflecting oxidative stress-induced cross-linking was found. Mucin glycomic analysis revealed significantly more sialylated glycans in CF, and the total abundance of nonsulfated O-glycans correlated with the relative abundance of pathogens. Collectively, the interaction of mucins, pathogens, epithelium, and inflammatory cells promotes proteomic and glycomic changes that reflect a persistent mucoobstructive, infectious, and inflammatory state.

Cystic Fibrosis↗