Population-Specific Genetic Differences of Acute Coronary Syndrome in Han and Uyghur Chinese

Hongmei Lai¹Jinhang Zhu²Jing Tao¹Zitong Guo¹Xiaolin Yu¹Xin Shen¹Ting Wang¹Ying Wang¹Huan Cai¹Xiao Cai²Zhenbang Wei²YiNing Yang^1*

• ¹People's Hospital of Xinjiang Uygur Autonomous Region, Ürümqi, Xinjiang Uyghur Region, China
• ²WuXi Diagnostics Innovation Research Institute, Shanghai, China

Background: Acute Coronary Syndrome (ACS) is a critical cardiovascular condition with diverse clinical presentations, necessitating personalized therapeutic approaches. This study explores the genetic variation associated with ACS subtypes in the Han and Uyghur Chinese populations to support the development of precision medicine approaches tailored to ethnic-specific genetic backgrounds. Methods: A total of 985 ACS patients (668 Han and 317 Uyghur Chinese) representing different ACS subtypes were enrolled. Clinical characteristics and 66 genetic polymorphisms were analyzed. Statistical analyses were conducted to identify differences in genetic variants and clinical features across ACS subtypes and ethnic groups.Results: Significant clinical and genetic differences were observed between ACS subtypes and between ethnic groups. In the Han population, polymorphisms in CYP2D6 and PTGER3 were significantly associated with ACS subtypes (p ≤ 0.05). In the Uyghur population, six genes—ACY3, CACNA1C, CYP2C9, CYP2C19, CYP4F2, and VKORC1—showed significant associations (p ≤ 0.05). These findings indicate distinct genetic landscapes across the two ethnic groups. Furthermore, population-specific associations between genetic variants and artery narrowing were identified. Predictive models integrating clinical and genetic features achieved an AUC of 0.832 (95% CI: 0.774–0.889) in Uyghur patients and 0.674 (95% CI: 0.626–0.722) in Han patients, indicating a higher internal AUC of these genetic markers in the Uyghur population.Conclusions: This study highlights ethnic differences in the genetic architecture of ACS. The result also underscores the need for population-specific strategies in risk stratification and treatment. The identified genetic markers and predictive models may guide future research on ethnicity-specific risk stratification.