Discovery of Pathogenic Variants Associated with Idiopathic Recurrent Pregnancy Loss Using Whole-Exome Sequencing

Area of Science:

• Genetics
• Reproductive Medicine
• Bioinformatics

Background:

• Idiopathic recurrent pregnancy loss (RPL) affects approximately 5% of couples, with heterogeneous causes including genetic factors.
• The precise biological mechanisms underlying pregnancy loss remain largely unknown.

Purpose of the Study:

• To identify potential genetic variants associated with idiopathic recurrent pregnancy loss (RPL) using whole-exome sequencing (WES).
• To explore the utility of combining WES with machine learning for variant detection in RPL.

Main Methods:

• Whole-exome sequencing (WES) was performed on 56 Korean patients with RPL and 40 controls.
• Bioinformatic analysis and machine learning tools were used to identify and predict the pathogenicity of variants.
• Sanger sequencing confirmed identified variants, and a replication study was conducted on 112 patients and 114 controls.

Main Results:

• Ten potential variants in nine genes, previously linked to spontaneous abortion, were detected in RPL patients.
• Several variants, including in MUC4, HABP2, and GAS2L2, were found exclusively in the patient group during replication.
• Functional clustering of detected genes suggested roles in secretion, cell protrusion, and cytoskeleton maintenance.

Conclusions:

• The combination of WES and machine learning is effective for identifying potential RPL-associated variants.
• Specific variants in genes like HABP2, MUC4, and GAS2L2 may play a role in the pathogenesis of RPL.
• Further WES data analysis is crucial for a comprehensive understanding of RPL causes.