sbd-data-book

Causal relationships

Causal relationships links causes and effects. We can categorize them by, for example, nanomaterial they are applicable too, by cause, and by effect. The current open data includes causal relationship from the AOP-Wiki [1], but still excludes the relationships from another paper [2] and SbD4Nano Deliverable D6.3.

Relationships for nanomaterials

SPARQL sparql/relationshipsByMaterial.rq (run)

PREFIX sbd:     <https://www.sbd4nano.eu/rdf/#>
PREFIX sbdbel:  <https://www.sbd4nano.eu/bel/#>
PREFIX dc:      <http://purl.org/dc/elements/1.1/>
PREFIX dcterms: <http://purl.org/dc/terms/>
PREFIX sio: <http://semanticscience.org/resource/SIO_>
PREFIX sbdbel2:  <https://h2020-sbd4nano.github.io/sbdbel/>
SELECT ?material (COUNT(DISTINCT ?relation) AS ?count)
WHERE {
  VALUES ?ca { sbdbel:CausalAssertion sbd:CausalAssertion sbdbel2:CausalAssertion }
  ?relation a ?ca ;
    sbdbel:NP | sio:000332 | sbdbel2:NP ?materialIRI .
  ?materialIRI rdfs:label ?material .
} GROUP BY ?material
  ORDER BY DESC(?count)

This gives us:

material count
Metal Oxide 6
metal oxide nanoparticle 6
Nanoparticle 5
Nanomaterial 5
nanoparticle 5

Relationships by cause

SPARQL sparql/relationshipsByCause.rq (run)

PREFIX sbd:     <https://www.sbd4nano.eu/rdf/#>
PREFIX sbdbel:  <https://www.sbd4nano.eu/bel/#>
PREFIX dc:      <http://purl.org/dc/elements/1.1/>
PREFIX dcterms: <http://purl.org/dc/terms/>
PREFIX sbdbel2:  <https://h2020-sbd4nano.github.io/sbdbel/>
SELECT ?cause (COUNT(DISTINCT ?relation) AS ?count)
WHERE {
  VALUES ?ca { sbdbel:CausalAssertion sbd:CausalAssertion sbdbel2:CausalAssertion }
  ?relation a ?ca ;
    sbdbel:cause / rdfs:label ?cause .
} GROUP BY ?cause
  ORDER BY DESC(?count) ASC(?cause)

This gives us:

cause count
Mitochondrial dysfunction 31
Oxidative Stress 26
Deposition of Energy 23
Activation, AhR 20
Dose 14
exposure 13
Thyroxine (T4) in serum, Decreased 13
Cell injury/death 13
Increased, Reactive oxygen species 13
Increase, Oxidative Stress 12
Activation, LXR 11
Acetylcholinesterase (AchE) Inhibition 10
Increase, DNA damage 10
coating/surface chemistry 9
core composition 9
size 9
Apoptosis 9
Deposition of Ionizing Energy 9
Increase, Reactive Oxygen Species production 9
Agonism, Androgen receptor 8
Decrease, testosterone levels 8
Histone deacetylase inhibition 8
Increase, DNA strand breaks 8
This table is truncated. See the full table at sparql/relationshipsByCause.rq

Relationships by outcome

SPARQL sparql/relationshipsByOutcome.rq (run)

PREFIX sbd:     <https://www.sbd4nano.eu/rdf/#>
PREFIX sbdbel:  <https://www.sbd4nano.eu/bel/#>
PREFIX dc:      <http://purl.org/dc/elements/1.1/>
PREFIX dcterms: <http://purl.org/dc/terms/>
PREFIX sbdbel2:  <https://h2020-sbd4nano.github.io/sbdbel/>
SELECT ?outcome (COUNT(DISTINCT ?relation) AS ?count)
WHERE {
  VALUES ?ca { sbdbel:CausalAssertion sbd:CausalAssertion sbdbel2:CausalAssertion }
  ?relation a ?ca ;
    sbdbel:outcome / rdfs:label ?outcome .
} GROUP BY ?outcome
  ORDER BY DESC(?count)

This gives us:

outcome count
Mitochondrial dysfunction 23
Impairment, Learning and memory 18
Decrease, Population growth rate 17
Cell injury/death 17
Increased Mortality 16
toxicity 16
Increased, Reactive oxygen species 15
cell uptake (amount) 15
increased,Vascular endothelial dysfunction 14
Apoptosis 13
impaired, Fertility 10
ROS production 10
Increase, Apoptosis 9
Increase, Mortality 9
Increased, secretion of proinflammatory mediators 9
Decrease of neuronal network function 9
Increased, Liver Steatosis 9
Increased, Oxidative Stress 8
Oxidative Stress 8
Increase, Mutations 8
Neuroinflammation 8
Accumulation, Fatty acid 8
Increase, Oocyte apoptosis 7
This table is truncated. See the full table at sparql/relationshipsByOutcome.rq

Or by Gracious [3] term:

All relationships

We can also list all relationships:

SPARQL sparql/allCausalRelationships.rq (run)

PREFIX sbd:     <https://www.sbd4nano.eu/rdf/#>
PREFIX sbdbel:  <https://www.sbd4nano.eu/bel/#>
PREFIX dc:      <http://purl.org/dc/elements/1.1/>
PREFIX dcterms: <http://purl.org/dc/terms/>
PREFIX sio: <http://semanticscience.org/resource/SIO_>
PREFIX sbdbel2:  <https://h2020-sbd4nano.github.io/sbdbel/>
SELECT DISTINCT ?cause ?type ?outcome ?material ?evidence
WHERE {
  VALUES ?ca { sbdbel:CausalAssertion sbd:CausalAssertion sbdbel2:CausalAssertion }
  ?relation a ?ca ; sbdbel:relationship ?type .
  OPTIONAL { ?relation sbdbel:cause / rdfs:label ?cause . }
  OPTIONAL { ?relation sbdbel:outcome / rdfs:label ?outcome . }
  OPTIONAL { ?relation sbdbel:NP | sio:000332 | sbdbel2:NP / rdfs:label ?material . }
  OPTIONAL { ?relation sbdbel:evidence ?evidence . }
} ORDER BY DESC(?relation)

This gives us:

cause type outcome material evidence
Alterations, Cellular proliferation / hyperplasia https://h2020-sbd4nano.github.io/sbd-data-aopwiki/relationships/ Formation, Hepatocellular and Bile duct tumors
N/A, Hepatotoxicity, Hepatopathy, including a constellation of observable effects https://h2020-sbd4nano.github.io/sbd-data-aopwiki/relationships/ Alterations, Cellular proliferation / hyperplasia
Changes/Inhibition, Cellular Homeostasis and Apoptosis https://h2020-sbd4nano.github.io/sbd-data-aopwiki/relationships/ N/A, Hepatotoxicity, Hepatopathy, including a constellation of observable effects
Disruption, Lysosome https://h2020-sbd4nano.github.io/sbd-data-aopwiki/relationships/ Mitochondrial dysfunction
Peptide Oxidation https://h2020-sbd4nano.github.io/sbd-data-aopwiki/relationships/ KE5 : Decrease, AKT/eNOS activity
KE5 : Decrease, AKT/eNOS activity https://h2020-sbd4nano.github.io/sbd-data-aopwiki/relationships/ KE6 : Depletion, Nitric Oxide
Activation, EGFR https://h2020-sbd4nano.github.io/sbd-data-aopwiki/relationships/ Increase, Mucin production
Activation, AhR https://h2020-sbd4nano.github.io/sbd-data-aopwiki/relationships/ Increase, Early Life Stage Mortality
This table is truncated. See the full table at sparql/allCausalRelationships.rq

References

  1. Martens M, Evelo CT, Willighagen EL. Providing Adverse Outcome Pathways from the AOP-Wiki in a Semantic Web Format to Increase Usability and Accessibility of the Content. Applied In Vitro Toxicology. 2022 Feb 25; doi:10.1089/AIVT.2021.0010 (Scholia)
  2. van Rijn JPM, Martens M, Ammar A, Cimpan MR, Fessard V, Hoet P, et al. From papers to RDF-based integration of physicochemical data and adverse outcome pathways for nanomaterials. J Cheminform. 2024 May 1;16(1). doi:10.1186/S13321-024-00833-0 (Scholia)
  3. Stone V, Gottardo S, Bleeker EAJ, Braakhuis H, Dekkers S, Fernandes T, et al. A framework for grouping and read-across of nanomaterials- supporting innovation and risk assessment. Nano Today. 2020 Dec;35:100941. doi:10.1016/J.NANTOD.2020.100941 (Scholia)