OmiKG is a domain-specific knowledge graph that traces chronic disease back to its root causes, mapping the directed causal web from lifestyle and environment all the way down to clinical phenotype.
Existing biomedical ontologies (SNOMED CT, ICD, Gene Ontology) excel at classification but lack the causal architecture needed for chronic-disease reasoning. Chronic disease is a network disorder. OmiKG models the directed, multi-factor causal chains needed to reason from a symptom back to its true origin.
OmiKG models directed causal chains (A→B→C), not just taxonomies, so it reasons about why a symptom exists, not merely what to call it.
Walk backwards from clinical phenotype to dysfunction to upstream trigger, true root-cause reasoning, not surface management.
Each causal link carries a reference code back to its source passage, building an evidence map that general-purpose models cannot provide.
N-ary causal modeling captures how diet, deficiency or toxins independently converge on the same disease, beyond simple binary triples.
A PRISMA-aligned pipeline unifies thousands of PubMed passages before extracting knowledge, cutting noise and hallucinated relations.
Built on the Functional Medicine Matrix and P4 medicine: predictive, preventive, personalized and participatory by design.
Four layers (ATM → Dysfunctions → Systems → Phenotypes) and 25 categories, connected by 14 relation types aligned with SNOMED CT and the OBO Relations Ontology. The graph flows from upstream drivers to clinical outcomes, and can be read in both directions.
Lifestyle & environmental drivers: chronic stress, diet, toxins.
Core biological disturbances: HPA-axis dysregulation, chronic inflammation, oxidative stress.
Seven physiological systems as defined by the Functional Medicine framework (Communication, Defense & Repair, Biotransformation, and more).
Clinical manifestations: fatigue, elevated fasting glucose, chronic pain.
OmiKG Core is the reasoning engine. Plug it into products that put root-cause intelligence to work across care, prevention and risk.
Give clinicians transparent, evidence-traceable reasoning at the point of care, surfacing root causes and intervention points instead of isolated symptoms.
Power health coaches and digital wellness apps with individualized root-cause maps that turn lifestyle and biomarker data into tailored prevention plans.
Help insurers move from static scores to dynamic, mechanism-based health assessment, modeling how risk factors converge over time.
Analyze the health of communities and workforces at scale, spotting shared upstream drivers to guide preventive programs.
In a blinded expert evaluation, OmiKG identified the molecular mechanisms behind chronic disease far more completely than a leading LLM or a retrieval baseline.
OmiKG is a long-term research program. Every time we ship a new version of the OmiKG Core, we announce it here.
OmiKG has been accepted for an oral presentation at the AMIA 2026 Annual Symposium (November 7-11, Dallas, TX), the leading venue for biomedical and health informatics research.
First public release of the four-layer ontology and knowledge graph: 1,354 nodes and 2,492 evidence-linked triples (96.8% plausibility in a 250-triple expert sample), built from a PRISMA-aligned synthesis of PubMed literature.
OmiKG identifies 88% of expert-specified molecular mechanisms, including NLRP3/IL-1β, SREBP-1c and BCAA/mTOR pathways missed by other systems.
Next versions move beyond Type 2 Diabetes to Metabolic Syndrome and PCOS, and will quantify causal strength, not just confidence that a link exists.
OmiKG is being developed by OmiGroup as long-term research infrastructure for tracing chronic disease back to its root causes. Partner with us, or follow the research.
Interested in OmiKG for research, clinical, or commercial collaboration? Send us a message and we'll get back to you.
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