re-cep/vitiligo-knowledge-graph

Vitiligo Knowledge Graph

A knowledge graph of vitiligo research from the Vitiligo Initiative, an open, non-profit research platform. It links the drugs, genes, diseases, biomarkers, interventions and clinical trials of the vitiligo literature, and every relation carries the evidence it rests on: the paper, trial record or database entry, and where licensing allows, the sentence itself.

	Count
Entities	16,931
Relations	90,735
Measured relations	60,941
Evidence rows	214,466
Quoted sentences	78,706

A further 2,464 relations resting only on WHO ICTRP records are published separately under WHO's terms (see Licensing), bringing the total to 93,199 relations.

Snapshot of 8 November 2026. Research data, not medical advice.

Contents

Entities (entities): 6,858 diseases and adverse events (an adverse event is the node of the disease or finding it names, so "herpes zoster" in a trial's safety table and in a paper is one node), 4,223 targets (genes and proteins), 1,577 trials, 1,355 drugs, 1,201 interventions (procedures, phototherapy and combination regimens), 873 biomarkers, 807 biological pathways (WikiPathways CC0, Gene Ontology CC-BY-4.0, and Reactome), 23 outcomes, 10 cutaneous cell types, and related mechanisms and phenotypes.

Relations (relations): changes 28,592 · participates_in 21,086 · associated_with 19,394 · co_expressed_with 8,367 · treats 3,587 · tested_in 2,735 · inhibits 2,403 · causes 1,742 · investigates 1,577 · activates 1,060 · expressed_in 841 · targets 83 · combined_with 61 · occurs_in 4.

Evidence (evidence): one row per source of a relation. Incorporates full-text extraction across 2,712 PMC papers with BioRED BiomedBERT, direct human vitiligo skin punch biopsy co-expression measurements (GSE311770, N=105), human skin single-cell RNA-seq lineage expression measurements (GSE298871, 17,057 single cells across 17 biopsies), WikiPathways (CC0) and experimental Gene Ontology Biological Process (CC-BY-4.0) pathway hierarchies, and ChEMBL / DrugCentral human drug-target bioactivities ($p\text{Act} \ge 6.5$). A relation stated by several papers or measurements has several rows.

Schema

entities

Column	Description
id	Entity id, referenced by relations
kind	target, drug, disease, trial, biomarker, intervention, ...
key, name	Normalised key and display name
aliases	Other names
external_ids	Identifiers in source databases (registry ids, Open Targets, EFO, ...)

relations

Column	Description
id	Relation id, referenced by evidence
subject_id, predicate, object_id	The relation
confidence	0-1; registries and curated records rank above text mining
claim	asserted (a source states it) or observed (measured; 30,174 relations)
causal_level	For observed relations, the rung on the causal ladder
extraction_method	How it was obtained (see Sources)
evidence_count	Evidence rows for this relation in this release

evidence

Column	Description
relation_id	The relation it supports
source	Where it comes from: pmid:…, ctgov:NCT…, opentargets:…, reporter:…, ...
source_kind	posted_result, relation_extractor, pubtator3, curated_result, expression, trial, prior, gwas, trial_result, mechanism
relation_label	The text-mining label (BioRED types: Association, Positive_Correlation, ...)
score	The text miner's score, where there is one
section	The paper section a sentence came from
text, text_licence	The sentence, where its licence allows; otherwise null
details	Source-specific fields as JSON (a trial result's numbers, a gene's fold change and FDR, GWAS p-value and cohort, trial phase, ...)

Sources

Method	Relations	How it was made	Measured accuracy
posted_result	27,083	Results 752 trials posted to ClinicalTrials.gov: adverse events from trials of the same drugs in any disease, outcomes and comparisons from vitiligo trials. Each results group is read as the regimen it received, a drug known by any name MeSH gives it (AIN457 is secukinumab, Stelara ustekinumab); a group switched from placebo to drug, set side by side with another, or pooled is left out	Numbers as posted: 300 of 300 sampled rows match the registry. Groups: 59 of 63 sampled read right
relation_extractor	14,776	Full-text bodies and other text read by the Vitiligo Relation Extractor, with a loading rule (probability ≥ 0.8, no tables or figures, no co-administration, "treats" only for vitiligo)	45 of 60 correct (75%); 15 of 17 where vitiligo is one end
pubtator3	9,223	PubTator 3.0's relations from PubMed abstracts, checked against MeSH	Of hand-checked samples: 30 of 34 "treats vitiligo", 31 of 34 "gene associated with vitiligo"
structured	5,640	Trial registries (ClinicalTrials.gov, EU CTR, ISRCTN), Open Targets, and curated trial arms	Database statements
curated_result	1,488	Results read by hand from the papers of 839 trials: responder rates, scores, p-values and adverse events, each with its arm and the section it was read from	Curated; every value cites its place in the paper
expression	1,247	Genes lesional skin expresses differently in three GEO cohorts (GSE65127, GSE75819, GSE311770; a fourth, GSE53146, tested and not used), against the same patients' unaffected skin or healthy donors: limma's moderated t, pairs as pairs, FDR < 5% and a twofold change. A comparison is used only if it sees the melanocytes' pigment genes lower. 1,484 genes in all, 1,247 not otherwise linked to vitiligo	Measured; 73 genes agree across two or more cohorts and rank above those seen once
gwas	50	GWAS Catalog associations, with p-value and cohort	Measured
trial_result	21	Posted trial responder rates	Measured
mechanism_record	12	Curated mechanism hypotheses with their causal rung	Curated

Trials are the 2,262 vitiligo trials of the corpus: 1,577 here, and the trials registered only with WHO ICTRP in the ictrp_* configurations. Trials known only from their papers take their interventions from curated trial arms. Placebo and vehicle arms are recorded as tested, never as treatments.

A changes relation joins a regimen to what was measured in the people given it: what an arm received (a combination such as "NB-UVB + tacrolimus" is a regimen of its own) and either an outcome family (repigmentation, relapse, quality of life, ...) or an adverse event. Each evidence row is one value, with its numbers in details, and beside them what the trial's control group showed: an adverse event row reads "5 of 100 on the drug" next to "1 of 50 on vehicle". Values pooled across arms name no regimen and are left out; a placebo or untreated arm appears only as what a regimen was compared with. Outcomes are taken only from vitiligo trials; adverse events from trials of the same drugs in any disease.

Licensing

• This release (CC BY 4.0). Relations and pointers are released under CC BY 4.0. Quoted sentences are included only where their source permits it: 23,191 from open-access papers licensed CC BY or CC0, 588 from NIH RePORTER and 214 from ClinicalTrials.gov, whose posted results are likewise public records of the US government. Every other sentence is given as a pointer to its paper and section; its text is the publisher's or author's under the paper's own licence.
• ictrp_* (WHO ICTRP terms). Relations and evidence resting on records of WHO's International Clinical Trials Registry Platform, which permits reuse with attribution but not for commercial purposes. Credit WHO ICTRP as the source when using them.
• Excluded. Eight evidence entries derived from DrugBank, whose terms do not allow redistribution.
• Article licences were taken from Europe PMC. BioRED and PubTator 3.0 are NCBI resources; Open Targets is CC0; GWAS Catalog data are mostly CC0. Expression results are this project's analysis of GEO series, which NCBI makes available without restriction.

Limitations

• Half the relations are measurements (30,174): results trials posted or printed, and genes expressed differently in lesional skin. The rest are assertions: a source states them.
• A gene expressed differently in lesional skin is an association, not a cause: most of the strongest are the genes of the melanocytes the lesion has lost.
• A changes relation says a regimen was measured against an outcome, not that it worked, and an adverse event under a drug is what was recorded in the people taking it, not proof the drug caused it: read the numbers beside the control group's in its evidence.
• About a quarter of the text-mined relations from full texts are wrong. Check a relation against its evidence before relying on it.
• associated_with is the most common and least specific relation: it says two things are linked, not how.
• A relation's absence means no source in the corpus stated it, not that it is false.

Usage

from datasets import load_dataset

relations = load_dataset("re-cep/vitiligo-knowledge-graph", "relations", split="train")
entities = load_dataset("re-cep/vitiligo-knowledge-graph", "entities", split="train")
evidence = load_dataset("re-cep/vitiligo-knowledge-graph", "evidence", split="train")

The release is rebuilt with vitiligo graph release from the project repository.

Citation

If you use this dataset, cite the Vitiligo Initiative and the sources it builds on: PubTator 3.0 (Wei et al., Nucleic Acids Research 2024), BioRED (Luo et al., Briefings in Bioinformatics 2022), Open Targets, the GWAS Catalog, WHO ICTRP, ClinicalTrials.gov, and the GEO series GSE65127, GSE75819 and GSE311770.