feat(associations): LOINC clinical-measurement sections (#1349)

backend/src/monarch_py/utils/association_type_mappings.yaml

@@ -115,3 +115,62 @@
   category: "biolink:CaseToGeneAssociation"
   subject_category: "biolink:Case"
   object_category: "biolink:Gene"
+# Clinical measurement (LOINC) sections. These edges all carry the generic
+# biolink:Association category, so each section is distinguished by predicate +
+# object category. The same mappings drive the reverse "... Clinical Measurements"
+# sections on the phenotype/chemical/anatomy/etc. pages via the object_label.
+- key: clinical_measurement_correlated_phenotypes
+  subject_label: Correlated Phenotypes
+  object_label: Correlated Clinical Measurements
+  category:
+  - "biolink:Association"
+  predicate:
+  - "biolink:correlated_with"
+  subject_category:
+  - "biolink:ClinicalMeasurement"
+  object_category:
+  - "biolink:PhenotypicFeature"
+- key: clinical_measurement_related_chemicals
+  subject_label: Related Chemicals
+  object_label: Related Clinical Measurements
+  category:
+  - "biolink:Association"
+  predicate:
+  - "biolink:related_to"
+  subject_category:
+  - "biolink:ClinicalMeasurement"
+  object_category:
+  - "biolink:ChemicalEntity"
+- key: clinical_measurement_related_anatomy
+  subject_label: Related Anatomy
+  object_label: Related Clinical Measurements
+  category:
+  - "biolink:Association"
+  predicate:
+  - "biolink:related_to"
+  subject_category:
+  - "biolink:ClinicalMeasurement"
+  object_category:
+  - "biolink:AnatomicalEntity"
+- key: clinical_measurement_related_proteins
+  subject_label: Related Proteins
+  object_label: Related Clinical Measurements
+  category:
+  - "biolink:Association"
+  predicate:
+  - "biolink:related_to"
+  subject_category:
+  - "biolink:ClinicalMeasurement"
+  object_category:
+  - "biolink:Protein"
+- key: clinical_measurement_related_cells
+  subject_label: Related Cells
+  object_label: Related Clinical Measurements
+  category:
+  - "biolink:Association"
+  predicate:
+  - "biolink:related_to"
+  subject_category:
+  - "biolink:ClinicalMeasurement"
+  object_category:
+  - "biolink:Cell"

backend/tests/unit/test_solr_parsers.py

@@ -23,6 +23,46 @@
 from monarch_py.utils.utils import dict_diff
 
 
+def test_parse_association_counts_clinical_measurement():
+    """A clinical-measurement (LOINC) section surfaces with its key/label even
+    though its edges share the generic biolink:Association category."""
+    from monarch_py.implementations.solr.solr_query_utils import (
+        build_association_count_suffixes,
+        build_association_counts_query,
+    )
+
+    node = "LOINC:2345-7"
+    fragment = (
+        'category:"biolink:Association" AND predicate:"biolink:correlated_with" '
+        'AND subject_category:"biolink:ClinicalMeasurement" '
+        'AND object_category:"biolink:PhenotypicFeature"'
+    )
+    suffixes = build_association_count_suffixes([node]).all_suffixes
+    direct = f'({fragment}) {suffixes["direct_subject"]}'
+    closure = f'({fragment}) {suffixes["closure_subject"]}'
+
+    # sanity: these queries are actually part of the built counts query
+    built = build_association_counts_query([node]).facet_queries
+    assert direct in built and closure in built
+
+    response = {
+        "responseHeader": {"QTime": 1, "params": {}},
+        "response": {"numFound": 0, "start": 0, "docs": []},
+        "facet_counts": {"facet_fields": {}, "facet_queries": {direct: 12, closure: 30}},
+    }
+    parsed = parse_association_counts(SolrQueryResult(**response), entities=[node]).model_dump()
+    assert parsed["items"] == [
+        {
+            "key": "clinical_measurement_correlated_phenotypes",
+            "label": "Correlated Phenotypes",
+            "category": "biolink:Association",
+            "count": 30,
+            "count_direct": 12,
+            "count_with_orthologs": None,
+        }
+    ]
+
+
 def test_parse_associations(association_response, associations):
     association_response["response"]["numFound"] = association_response["response"].pop("num_found")
     solr_response = SolrQueryResult(**association_response)

docs/sources-manifest.yaml

@@ -42,6 +42,9 @@ sources:
   - repo: monarch-initiative/hgnc-ingest
     branch: main
     filename: hgnc.md
+  - repo: monarch-initiative/loinc-ingest
+    branch: main
+    filename: loinc.md
   - repo: monarch-initiative/maxo-annotation-ingest
     branch: main
     filename: maxo.md

frontend/src/api/categories.ts

@@ -124,6 +124,8 @@ const colorMap: { [key: string]: string } = mapKeys(
 
     "biolink:Disease": colors.pink.dark,
 
+    "biolink:ClinicalMeasurement": colors.teal.dark,
+
     "biolink:MolecularEntity": colors.lime.dark,
     "biolink:CellularComponent": colors.lime.dark,
     "biolink:BiologicalProcess": colors.lime.dark,

frontend/src/components/TheTableOfContents.vue

@@ -80,6 +80,7 @@ const CATEGORIES = [
   "biolink:Disease",
   "biolink:PhenotypicFeature",
   "biolink:AnatomicalEntity",
+  "biolink:ClinicalMeasurement",
 ];
 const { node } = defineProps<{ node: ApiNode | null }>();
 /** toc entries */

frontend/src/pages/node/AssociationsTable.vue

@@ -148,6 +148,15 @@
         >
           <AppIcon :icon="getAgentTypeMeta(row.agent_type).icon" />
         </span>
+        <span
+          v-if="row.knowledge_level"
+          v-tooltip="
+            `<b>${getKnowledgeLevelMeta(row.knowledge_level).label}</b><br>${getKnowledgeLevelMeta(row.knowledge_level).description}`
+          "
+          :aria-label="`${getKnowledgeLevelMeta(row.knowledge_level).label}: ${getKnowledgeLevelMeta(row.knowledge_level).description}`"
+        >
+          <AppIcon :icon="getKnowledgeLevelMeta(row.knowledge_level).icon" />
+        </span>
         <AppButton
           v-tooltip="'View association details'"
           design="small"
@@ -232,6 +241,7 @@ import {
 import { getBreadcrumbs } from "@/pages/node/AssociationsSummary.vue";
 import SectionAssociationDetails from "@/pages/node/SectionAssociationDetails.vue";
 import { getAgentTypeMeta } from "@/util/agentType";
+import { getKnowledgeLevelMeta } from "@/util/knowledgeLevel";
 import { taxonFieldFor } from "@/util/taxonFilterConfig";
 import { fieldFor } from "@/util/typeConfig";
 

frontend/src/pages/node/SectionHierarchy.vue

@@ -61,6 +61,7 @@ const LABELS = new Map<string, string>([
   ["biolink:Disease", "Disease"],
   ["biolink:PhenotypicFeature", "Phenotype"],
   ["biolink:AnatomicalEntity", "Anatomical entity"],
+  ["biolink:ClinicalMeasurement", "Clinical measurement"],
 ]);
 
 const typeNoun = computed(

frontend/src/util/knowledgeLevel.ts

@@ -0,0 +1,54 @@
+/** Centralized metadata for Biolink KnowledgeLevelEnum values. */
+
+type KnowledgeLevelMeta = { icon: string; label: string; description: string };
+
+export const KNOWLEDGE_LEVEL_META: Record<string, KnowledgeLevelMeta> = {
+  knowledge_assertion: {
+    icon: "circle-check",
+    label: "Knowledge Assertion",
+    description:
+      "Directly asserted by a knowledge source or curator, representing an accepted fact",
+  },
+  logical_entailment: {
+    icon: "sitemap",
+    label: "Logical Entailment",
+    description:
+      "Derived by logical inference or reasoning from other statements",
+  },
+  prediction: {
+    icon: "chart-bar",
+    label: "Prediction",
+    description:
+      "Generated by a predictive or computational model; may be less certain",
+  },
+  statistical_association: {
+    icon: "equals",
+    label: "Statistical Association",
+    description: "Derived from a statistical association observed in data",
+  },
+  observation: {
+    icon: "eye",
+    label: "Observation",
+    description: "Based on a direct observation",
+  },
+  not_provided: {
+    icon: "circle-question",
+    label: "Not Provided",
+    description: "Knowledge level not available",
+  },
+};
+
+export const KNOWLEDGE_LEVEL_KEYS = Object.keys(KNOWLEDGE_LEVEL_META);
+
+const FALLBACK: KnowledgeLevelMeta = {
+  icon: "circle-question",
+  label: "Unknown",
+  description: "Unrecognized knowledge level",
+};
+
+/** Get icon, label, and description for a knowledge_level value. */
+export function getKnowledgeLevelMeta(
+  knowledgeLevel: string,
+): KnowledgeLevelMeta {
+  return KNOWLEDGE_LEVEL_META[knowledgeLevel] ?? FALLBACK;
+}

frontend/unit/knowledgeLevel.test.ts

@@ -0,0 +1,39 @@
+import { describe, expect, test } from "vitest";
+import {
+  getKnowledgeLevelMeta,
+  KNOWLEDGE_LEVEL_KEYS,
+  KNOWLEDGE_LEVEL_META,
+} from "@/util/knowledgeLevel";
+
+describe("getKnowledgeLevelMeta", () => {
+  test("returns correct metadata for a curated assertion", () => {
+    const meta = getKnowledgeLevelMeta("knowledge_assertion");
+    expect(meta.icon).toBe("circle-check");
+    expect(meta.label).toBe("Knowledge Assertion");
+    expect(meta.description).toContain("asserted");
+  });
+
+  test("returns correct metadata for a prediction", () => {
+    const meta = getKnowledgeLevelMeta("prediction");
+    expect(meta.icon).toBe("chart-bar");
+    expect(meta.label).toBe("Prediction");
+  });
+
+  test("returns fallback for unknown values", () => {
+    const meta = getKnowledgeLevelMeta("completely_unknown_level");
+    expect(meta.icon).toBe("circle-question");
+    expect(meta.label).toBe("Unknown");
+    expect(meta.description).toBe("Unrecognized knowledge level");
+  });
+});
+
+describe("KNOWLEDGE_LEVEL_META", () => {
+  test("every entry has icon, label, and description", () => {
+    for (const key of KNOWLEDGE_LEVEL_KEYS) {
+      const meta = KNOWLEDGE_LEVEL_META[key];
+      expect(meta.icon).toBeTruthy();
+      expect(meta.label).toBeTruthy();
+      expect(meta.description).toBeTruthy();
+    }
+  });
+});