Identification of preeclampsia-associated immune-related risk loci in the Chinese population.

OBJECTIVE

Preeclampsia, the most severe hypertensive disorder of pregnancy, is the leading cause of maternal death. While genetic factors are recognized as significant contributors to the susceptibility to preeclampsia, which poses varying risks in diverse ethnic groups, the discovery of genetic loci has been limited. The objective of this research is to investigate the genetic predisposition to pre-eclampsia among Chinese women and establish an early predictive model.

MATERIALS AND

METHODS

Two hospital-based cohorts of Chinese women were used. The discovery cohort underwent genome-wide association analysis (GWAS) to find new genetic susceptibilities linked to preeclampsia. The significant genetic loci were then validated in the validation cohort. The expression profiles of the risk genes were analyzed using RNA-seq and single-cell RNA-seq datasets, while protein tertiary structures were modeled across different genotypes. Machine-learning models were then trained to predict high-risk pregnancies of preeclampsia.

RESULTS

The identification of new genetic susceptibility loci, HLA-DQB1 and HLA-DRB5, associated with an increased risk of preeclampsia was achieved through GWAS. Within the validation cohort, three SNPs (rs147440497, rs141378803, and rs149025589) were identified within HLA-DRB5. Furthermore, antigen-presenting cells exhibited heightened expression of HLA-DRB5. Additionally, we noted a change in protein tertiary structure that could be linked to a substitution of phenylalanine with tyrosine at the rs147440497 position. A machine learning model that incorporates these alleles demonstrated promising predictive performance for preeclampsia risk, achieving a cross-validation ROC AUC of 0.83.

CONCLUSION

This study highlighted immune-related genetic loci that could function as biomarkers for the early prediction of preeclampsia in Chinese women.