Laboratory Tests
- Adrianne Stefanski - Biocurator 🔬
- Tellen D. Bennett - Clinician 🏥
- James A. Feinstein - Clinician 🏥
- Blake Martin - Clinician 🏥
- Nicole Vasilevsky - Biocurator 🔬
- Xingmin Aaron Zhang - Biocurator 🔬
- Leigh Carmody - Biocurator 🔬
- Peter N. Robinson - Biocurator 🔬
The goal of this project was to map measurement results drawn from the Observational Medical Outcomes Partnership (OMOP) common data model to the Open Biomedical Ontologies (OBO). Specifically, we aimed to annotate all unique test results LOINC codes assigned to at least 1 patient (n=902 codes; 2,706 test results) to an OBO ontology.
“The Open Biological and Biomedical Ontology (OBO) Foundry is a collective of ontology developers that are committed to collaboration and adherence to shared principles. The mission of the OBO Foundry is to develop a family of interoperable ontologies that are both logically well-formed and scientifically accurate.” -OBO Foundry
Currently, there are very few annotations (i.e. mappings or connecting of similar concepts from different sources) that exist between clinical terminologies and the OBO ontologies. Creating these mappings enables transition into a reproducible research framework where clinical observations can be viewed within the context of their underlying molecular mechanism(s).
This task will use the Human Phenotype Ontology (HPO), the uber-anatomy (UBERON)/Chemical Entities of Biological Interest (ChEBI):
The Human Phenotype Ontology (HPO) provides a standardized vocabulary of phenotypic abnormalities encountered in human disease. Each term in the HPO describes a phenotypic abnormality, such as Atrial septal defect.
The Uber-Anatomy Ontology (UBERON) represents anatomy (i.e. body parts, organs and tissues) for multiple species.
The Chemical Entities of Biological Interest (ChEBI) represents molecular entities, specifically, small chemical compounds.
Our goal, was to map all unique LOINC laboratory test results (i.e. low, normal, or high), assigned to at least one pediatric patient, to HPO. For laboratory tests, each result is considered independently in order to find the best possible mapping to an ontology concept.
| LOINC | Result | HPO |
|---|---|---|
| LOINC_28606-2 : 1-Methylhistidine/Creatinine [Ratio] in Urine | Low | Decreased urinary 1-methylhistidine (HP_0410314) |
| LOINC_28606-2 : 1-Methylhistidine/Creatinine [Ratio] in Urine | Normal | NOT(Abnormal urinary 1-methylhistidine concentration) (HP_0410313) |
| LOINC_28606-2 : 1-Methylhistidine/Creatinine [Ratio] in Urine | High | Increased urinary 1-methylhistine (HP_0410315) |
The following tasks were performed to map LOINC laboratory test results to the HPO:
- Export each LOINC id and it’s ancestors from a pediatric (CHCO) instance of the OMOP common data model (data exported October, 2018). The SQL code that was used to retrieve these codes is stored as a GitHub Gist and can be found here. For convenience, the queries are also shown below:
SELECT
m.measurement_concept_id AS CONCEPT_ID,
c.concept_code AS CONCEPT_SOURCE_CODE,
c.concept_name AS CONCEPT_LABEL,
STRING_AGG(DISTINCT(CAST(c1.concept_id as string)), "|") AS ANCESTOR_CONCEPT_ID,
STRING_AGG(DISTINCT(c1.concept_code), "|") AS ANCESTOR_SOURCE_CODE,
STRING_AGG(DISTINCT(c1.concept_name), "|") AS ANCESTOR_LABEL,
FROM
CHCO_DeID_Oct2018.measurement m
JOIN CHCO_DeID_Oct2018.concept c ON m.measurement_concept_id = c.concept_id
JOIN CHCO_DeID_Oct2018.concept_ancestor ca ON ca.descendant_concept_id = c.concept_id
JOIN CHCO_DeID_Oct2018.concept c1 ON ca.ancestor_concept_id = c1.concept_id
WHERE
c.concept_name != "No matching concept"
AND c.vocabulary_id = "LOINC"
AND c.domain_id = "Measurement"
AND c.vocabulary_id = c1.vocabulary_id
AND c1.concept_name != "No matching concept"
AND c1.domain_id = "Measurement"
AND ca.min_levels_of_separation = 1
GROUP BY
CONCEPT_ID,
CONCEPT_SOURCE_CODE,
CONCEPT_LABEL;Two verification approaches were applied, the first was survey-based and the second involved manual mapping verification by a professional biocurator.
A subset (n=270) of pediatric-specific laboratory test result mappings were independently validated by five domain experts (i.e. three pediatric clinicians, a PhD-level molecular biologist, and a master’s-level epidemiologist). The study was approved by the Colorado Multiple Institutional Review Board (15-0445).
To perform this validation, a Qualtrics survey (see QR code) was designed so that each question featured a laboratory test description and set of reasonable HPO concepts.
The survey was completed by all experts between October and December (2018). After completion, any laboratory test mapping that did not meet agreement by at least one clinician and both the biologist/epidemiologist were re-evaluated with one clinician until consensus was reached (n=58 lab results). These terms were additionally vetted on the loinc2hpoAnnotation GitHub tracker by the entire team of HPO biocurators.
Results. Agreement on mapping was 95.9% between the clinicians, 79.3% between the epidemiologist and biologist, and 90.7% between the clinicians and the biologist and epidemiologist. The best mapping across all experts, was 92% in agreement with existing LOINC2HPO mappings.
The subset of 691 randomly selected LOINC codes were verified by a professional biocurator. A screenshot of the verification table is shown below. Additional information on this mapping process, including the new terms we requested in order to complete this mapping, can be found in the Human Phenotype Ontology GitHub tracker.
To verify or search the ontologies for alternative terms, the biocurator was asked to use the following resource:
- Verify each of the mappings, row-by-row considering each LOINC lab code result within the context of the ontologiy mappings that have been provided.
- The goal is to find the best mapping between a single ontology term and a LOINC laboratory test result.
Mapping (10/2018-11-2019); Clinician verification (survey) (10/2019-12/2018); Biocurator verification (01/2019-03/2019); Mapping finalized (10/13/2019)
We completed the mapping of 902 unique measurements and 2,706 unique measurement results.
| Mapping Type | Count |
|---|---|
| Manually Mapped | 2616 |
| UnMapped | 90 |