-- ============================================================ -- PostgreSQL + Apache AGE 스키마 확장 -- Food (식품) + Biomarker (바이오마커) 노드 추가 -- ============================================================ -- 1. 식품 테이블 CREATE TABLE IF NOT EXISTS foods ( food_id SERIAL PRIMARY KEY, food_name TEXT NOT NULL, food_name_en TEXT, category TEXT NOT NULL, -- 'pro_inflammatory', 'anti_inflammatory', 'neutral' subcategory TEXT, -- 'high_fat', 'processed_meat', 'sugar', 'alcohol', 'omega3', 'antioxidant' description TEXT, serving_size TEXT, -- '100g', '1컵' 등 kcal_per_serving REAL, created_at TIMESTAMP DEFAULT NOW() ); -- 인덱스 CREATE INDEX idx_foods_category ON foods(category); CREATE INDEX idx_foods_subcategory ON foods(subcategory); -- 샘플 데이터 INSERT INTO foods (food_name, food_name_en, category, subcategory, description) VALUES ('고지방 식품', 'High-fat foods', 'pro_inflammatory', 'high_fat', '튀김, 패스트푸드 등'), ('포화지방', 'Saturated fat', 'pro_inflammatory', 'high_fat', '동물성 지방, 버터 등'), ('가공육', 'Processed meat', 'pro_inflammatory', 'processed_meat', '베이컨, 소시지, 햄'), ('적색육', 'Red meat', 'pro_inflammatory', 'red_meat', '소고기, 돼지고기'), ('알코올', 'Alcohol', 'pro_inflammatory', 'alcohol', '소주, 맥주, 와인'), ('설탕', 'Sugar', 'pro_inflammatory', 'sugar', '단 음료, 과자, 케이크'), ('트랜스지방', 'Trans fat', 'pro_inflammatory', 'trans_fat', '마가린, 쇼트닝'), ('오메가-3', 'Omega-3', 'anti_inflammatory', 'omega3', '등푸른 생선, 들기름'), ('커큐민', 'Curcumin', 'anti_inflammatory', 'antioxidant', '강황 추출물'), ('블루베리', 'Blueberry', 'anti_inflammatory', 'antioxidant', '항산화 과일') ON CONFLICT DO NOTHING; -- 2. 바이오마커 테이블 CREATE TABLE IF NOT EXISTS biomarkers ( biomarker_id SERIAL PRIMARY KEY, biomarker_name TEXT UNIQUE NOT NULL, biomarker_type TEXT NOT NULL, -- 'inflammatory_cytokine', 'lipid', 'glucose', 'hormone' normal_range_min REAL, normal_range_max REAL, unit TEXT, -- 'pg/mL', 'mg/dL' 등 description TEXT, created_at TIMESTAMP DEFAULT NOW() ); -- 인덱스 CREATE INDEX idx_biomarkers_type ON biomarkers(biomarker_type); -- 샘플 데이터 INSERT INTO biomarkers (biomarker_name, biomarker_type, normal_range_min, normal_range_max, unit, description) VALUES ('IL-1β', 'inflammatory_cytokine', 0, 5, 'pg/mL', 'Interleukin-1 beta, 염증성 사이토카인'), ('IL-6', 'inflammatory_cytokine', 0, 7, 'pg/mL', 'Interleukin-6, 염증성 사이토카인'), ('TNF-α', 'inflammatory_cytokine', 0, 8.1, 'pg/mL', 'Tumor Necrosis Factor alpha'), ('CRP', 'inflammatory_marker', 0, 3, 'mg/L', 'C-Reactive Protein, 염증 지표'), ('LDL', 'lipid', 0, 130, 'mg/dL', 'Low-Density Lipoprotein, 나쁜 콜레스테롤'), ('HDL', 'lipid', 40, 200, 'mg/dL', 'High-Density Lipoprotein, 좋은 콜레스테롤') ON CONFLICT DO NOTHING; -- 3. 식품-바이오마커 관계 테이블 (SQL 레벨) CREATE TABLE IF NOT EXISTS food_biomarker_effects ( id SERIAL PRIMARY KEY, food_id INTEGER REFERENCES foods(food_id), biomarker_id INTEGER REFERENCES biomarkers(biomarker_id), effect_type TEXT NOT NULL, -- 'increases', 'decreases', 'no_effect' magnitude TEXT, -- 'high', 'moderate', 'low' percent_change REAL, -- 증감률 (예: 30.0 = 30% 증가) mechanism TEXT, -- 'NLRP3_inflammasome', 'oxidative_stress' 등 evidence_pmid TEXT, -- PubMed ID study_type TEXT, -- 'RCT', 'Meta-analysis', 'Cohort' reliability REAL, -- 0.0 ~ 1.0 created_at TIMESTAMP DEFAULT NOW() ); -- 인덱스 CREATE INDEX idx_food_biomarker_effect ON food_biomarker_effects(effect_type); CREATE INDEX idx_food_biomarker_pmid ON food_biomarker_effects(evidence_pmid); -- 샘플 데이터 (IL-1β 증가시키는 식품) INSERT INTO food_biomarker_effects (food_id, biomarker_id, effect_type, magnitude, percent_change, mechanism, evidence_pmid, study_type, reliability) VALUES -- 고지방 식품 → IL-1β 증가 ((SELECT food_id FROM foods WHERE food_name = '고지방 식품'), (SELECT biomarker_id FROM biomarkers WHERE biomarker_name = 'IL-1β'), 'increases', 'high', 50.0, 'NLRP3_inflammasome_activation', '36776889', 'RCT', 0.95), -- 포화지방 → IL-1β 증가 ((SELECT food_id FROM foods WHERE food_name = '포화지방'), (SELECT biomarker_id FROM biomarkers WHERE biomarker_name = 'IL-1β'), 'increases', 'moderate', 35.0, 'myeloid_inflammasome', '40864681', 'RCT', 0.90), -- 가공육 → IL-1β 증가 ((SELECT food_id FROM foods WHERE food_name = '가공육'), (SELECT biomarker_id FROM biomarkers WHERE biomarker_name = 'IL-1β'), 'increases', 'moderate', 30.0, 'AGE_formation', '40952033', 'Cohort', 0.85), -- 알코올 → IL-1β 증가 ((SELECT food_id FROM foods WHERE food_name = '알코올'), (SELECT biomarker_id FROM biomarkers WHERE biomarker_name = 'IL-1β'), 'increases', 'high', 45.0, 'autophagy_inhibition', '30964198', 'RCT', 0.92), -- 오메가-3 → IL-1β 감소 ((SELECT food_id FROM foods WHERE food_name = '오메가-3'), (SELECT biomarker_id FROM biomarkers WHERE biomarker_name = 'IL-1β'), 'decreases', 'moderate', -30.0, 'anti_inflammatory', '12345678', 'Meta-analysis', 0.95) ON CONFLICT DO NOTHING; -- 4. 질병-바이오마커 관계 테이블 CREATE TABLE IF NOT EXISTS disease_biomarker_association ( id SERIAL PRIMARY KEY, disease_icd_code TEXT, -- ICD-10 코드 disease_name TEXT NOT NULL, biomarker_id INTEGER REFERENCES biomarkers(biomarker_id), association_strength REAL, -- 0.0 ~ 1.0 threshold_value REAL, -- 위험 기준값 description TEXT, evidence_pmid TEXT, created_at TIMESTAMP DEFAULT NOW() ); -- 샘플 데이터 INSERT INTO disease_biomarker_association (disease_icd_code, disease_name, biomarker_id, association_strength, threshold_value, description, evidence_pmid) VALUES ('K76.0', 'NAFLD (비알코올성 지방간)', (SELECT biomarker_id FROM biomarkers WHERE biomarker_name = 'IL-1β'), 0.85, 10.0, 'IL-1β 10 pg/mL 이상 시 NAFLD 위험 증가', '36776889'), ('I25', '죽상동맥경화증', (SELECT biomarker_id FROM biomarkers WHERE biomarker_name = 'IL-1β'), 0.90, 8.0, 'IL-1β 상승 시 심혈관 질환 위험', '39232165'), ('M06', '류마티스 관절염', (SELECT biomarker_id FROM biomarkers WHERE biomarker_name = 'IL-1β'), 0.92, 7.0, 'IL-1β가 관절 염증 악화 인자', '12345678') ON CONFLICT DO NOTHING; -- 5. 뷰: 식품별 바이오마커 영향 요약 CREATE OR REPLACE VIEW v_food_biomarker_summary AS SELECT f.food_name, f.category, b.biomarker_name, fbe.effect_type, fbe.magnitude, fbe.percent_change, fbe.mechanism, fbe.evidence_pmid, fbe.reliability FROM foods f JOIN food_biomarker_effects fbe ON f.food_id = fbe.food_id JOIN biomarkers b ON fbe.biomarker_id = b.biomarker_id ORDER BY f.category, fbe.effect_type, fbe.magnitude DESC; -- 6. 뷰: IL-1β 증가시키는 식품 목록 CREATE OR REPLACE VIEW v_il1beta_increasing_foods AS SELECT f.food_name, f.subcategory, fbe.magnitude AS 위험도, fbe.percent_change AS 증가율, fbe.mechanism AS 메커니즘, fbe.evidence_pmid AS 근거논문, fbe.reliability AS 신뢰도 FROM foods f JOIN food_biomarker_effects fbe ON f.food_id = fbe.food_id JOIN biomarkers b ON fbe.biomarker_id = b.biomarker_id WHERE b.biomarker_name = 'IL-1β' AND fbe.effect_type = 'increases' ORDER BY CASE fbe.magnitude WHEN 'high' THEN 1 WHEN 'moderate' THEN 2 WHEN 'low' THEN 3 END, fbe.percent_change DESC; -- 7. 함수: 특정 질병 환자가 피해야 할 식품 목록 CREATE OR REPLACE FUNCTION get_foods_to_avoid(disease_icd TEXT) RETURNS TABLE ( food_name TEXT, reason TEXT, biomarker TEXT, evidence_pmid TEXT ) AS $$ BEGIN RETURN QUERY SELECT DISTINCT f.food_name, '바이오마커 ' || b.biomarker_name || ' 증가로 ' || dba.disease_name || ' 위험' AS reason, b.biomarker_name AS biomarker, fbe.evidence_pmid FROM foods f JOIN food_biomarker_effects fbe ON f.food_id = fbe.food_id JOIN biomarkers b ON fbe.biomarker_id = b.biomarker_id JOIN disease_biomarker_association dba ON b.biomarker_id = dba.biomarker_id WHERE dba.disease_icd_code = disease_icd AND fbe.effect_type = 'increases' ORDER BY f.food_name; END; $$ LANGUAGE plpgsql; -- 8. 검색 최적화를 위한 전문 검색 인덱스 ALTER TABLE foods ADD COLUMN IF NOT EXISTS search_vector tsvector; UPDATE foods SET search_vector = to_tsvector('korean', coalesce(food_name, '') || ' ' || coalesce(description, '')); CREATE INDEX IF NOT EXISTS idx_foods_search ON foods USING GIN(search_vector); -- 완료 메시지 DO $$ BEGIN RAISE NOTICE '✅ 식품-바이오마커 스키마 확장 완료'; RAISE NOTICE ' - foods 테이블: 식품 마스터'; RAISE NOTICE ' - biomarkers 테이블: 바이오마커'; RAISE NOTICE ' - food_biomarker_effects 테이블: 식품-바이오마커 관계'; RAISE NOTICE ' - disease_biomarker_association 테이블: 질병-바이오마커 관계'; RAISE NOTICE ' - v_il1beta_increasing_foods 뷰: IL-1β 증가 식품'; RAISE NOTICE ' - get_foods_to_avoid(disease_icd) 함수: 질병별 피해야 할 식품'; END $$;