사상체질의학회지 (Journal of Sasang Constitutional Medicine)

  • 제32권2호
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  • Pages.10-21
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  • 2020
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  • 1226-4075(pISSN)
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  • 2287-786X(eISSN)
사상체질의학회 (The Society Of Sasang Constitutional Medicine)
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유전지표를 활용한 사상체질 분류모델

Predictive Models for Sasang Constitution Types Using Genetic Factors

  • 반효정 (한국한의학연구원 지능화추진팀) ;
  • 이시우 (한국한의학연구원 미래의학부) ;
  • 진희정 (한국한의학연구원 지능화추진팀)
  • Ban, Hyo-Jeong (Intellectual Information Team, Korea Institute of Oriental Medicine) ;
  • Lee, Siwoo (Future Medicine Division, Korea Institute of Oriental Medicine) ;
  • Jin, Hee-Jeong (Intellectual Information Team, Korea Institute of Oriental Medicine)
  • 투고 : 2020.04.20
  • 심사 : 2020.04.27
  • 발행 : 2020.06.30
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초록

Objectives Genome-wide association studies(GWAS) is a useful method to identify genetic associations for various phenotypes. The purpose of this study was to develop predictive models for Sasang constitution types using genetic factors. Methods The genotypes of the 1,999 subjects was performed using Axiom Precision Medicine Research Array (PMRA) by Life Technologies. All participants were prescribed Sasang Constitution-specific herbal remedies for the treatment, and showed improvement of original symptoms as confirmed by Korean medicine doctor. The genotypes were imputed by using the IMPUTE program. Association analysis was conducted using a logistic regression model to discover Single Nucleotide Polymorphism (SNP), adjusting for age, sex, and BMI. Results & Conclusions We developed models to predict Korean medicine constitution types using identified genectic factors and sex, age, BMI using Random Forest (RF), Support Vector Machine (SVM), and Neural Network (NN). Each maximum Area Under the Curve (AUC) of Teaeum, Soeum, Soyang is 0.894, 0.868, 0.767, respectively. Each AUC of the models increased by 6~17% more than that of models except for genetic factors. By developing the predictive models, we confirmed usefulness of genetic factors related with types. It demonstrates a mechanism for more accurate prediction through genetic factors related with type.

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