Proteome profiling of early gestational plasma reveals novel biomarkers of congenital heart disease
Yanan Yin, Li Cao, J. Wang, Yuling Chen, Haiou Yang, Subei Tan, Ke Cai, Zhe‐Qi Chen, Jie Xiang, Yuan‐Xin Yang, Hao‐Ran Geng, Zeyu Zhou, Anna Shen, Xiangyu Zhou, Yan Shi, Rui Zhao, Kun Sun, Chen Ding, Jian‐Yuan Zhao
Abstract
Prenatal diagnosis of congenital heart disease (CHD) relies primarily on fetal echocardiography conducted at mid-gestational age-the sensitivity of which varies among centers and practitioners. An objective method for early diagnosis is needed. Here, we conducted a case-control study recruiting 103 pregnant women with healthy offspring and 104 cases with CHD offspring, including VSD (42/104), ASD (20/104), and other CHD phenotypes. Plasma was collected during the first trimester and proteomic analysis was performed. Principal component analysis revealed considerable differences between the controls and the CHDs. Among the significantly altered proteins, 25 upregulated proteins in CHDs were enriched in amino acid metabolism, extracellular matrix receptor, and actin skeleton regulation, whereas 49 downregulated proteins were enriched in carbohydrate metabolism, cardiac muscle contraction, and cardiomyopathy. The machine learning model reached an area under the curve of 0.964 and was highly accurate in recognizing CHDs. This study provides a highly valuable proteomics resource to better recognize the cause of CHD and has developed a reliable objective method for the early recognition of CHD, facilitating early intervention and better prognosis.