유럽인 자료로 산출된 양극성 장애 다유전자 위험 점수의 한국인 양극성 장애 환자에의 적용
Polygenic Risk Scores for Bipolar Disorder in Korean Populations in Comparison to European Populations
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초록
Objectives This study examined whether the polygenic risk score (PRS) calculated from the most recent genome-wide association study for bipolar disorder (BD) of European ancestry patients is significantly associated with BD diagnosis in the Korean population. Methods The study included 417 Korean patients with BD and 497 healthy controls. Genotyping was performed using the Korean Biobank Array. Summary statistics of the European samples from the Psychiatric Genomic Consortium were used as base data to generate the PRS for each individual. The program PRSice-2 was used to calculate the PRS. Logistic regression was conducted to determine the association between BD diagnosis and PRS for BD after adjusting for age and sex. Results PRS for BD was significantly higher in patients diagnosed with BD compared to healthy controls. The PRS at the p-value threshold of 0.01 best explained the variance of BD after adjusting for age and sex (R2=0.0061, p=0.039). Subgroup analyses were performed for bipolar I and II subgroups. In bipolar I patients, the PRS at the p-value threshold of 0.01 best explained the diagnosis (R2=0.0165, p=0.0055), whereas no significant result was found for bipolar II patients. Conclusion PRS for BD calculated for the Korean sample showed a significant association with the BD diagnosis. This result suggests an overlapping genetic risk for BD between the European and Korean populations.
Abstract
Objectives This study examined whether the polygenic risk score (PRS) calculated from the most recent genome-wide association study for bipolar disorder (BD) of European ancestry patients is significantly associated with BD diagnosis in the Korean population. Methods The study included 417 Korean patients with BD and 497 healthy controls. Genotyping was performed using the Korean Biobank Array. Summary statistics of the European samples from the Psychiatric Genomic Consortium were used as base data to generate the PRS for each individual. The program PRSice-2 was used to calculate the PRS. Logistic regression was conducted to determine the association between BD diagnosis and PRS for BD after adjusting for age and sex. Results PRS for BD was significantly higher in patients diagnosed with BD compared to healthy controls. The PRS at the p-value threshold of 0.01 best explained the variance of BD after adjusting for age and sex (R2=0.0061, p=0.039). Subgroup analyses were performed for bipolar I and II subgroups. In bipolar I patients, the PRS at the p-value threshold of 0.01 best explained the diagnosis (R2=0.0165, p=0.0055), whereas no significant result was found for bipolar II patients. Conclusion PRS for BD calculated for the Korean sample showed a significant association with the BD diagnosis. This result suggests an overlapping genetic risk for BD between the European and Korean populations.
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