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Updated: Apr 29, 2026

Pre-Implantation Genetic Testing for Aneuploidy on a Semiconductor Based Next-Generation Sequencing Platform
Published on: August 17, 2022
Structural genomic variation as risk factor for idiopathic recurrent miscarriage.
Liina Nagirnaja1, Priit Palta, Laura Kasak
1Human Molecular Genetics Research Group, Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.
Copy number variants (CNVs) are linked to recurrent miscarriage (RM). A specific 5p13.3 duplication significantly increases maternal RM risk, potentially impacting placental genes and pregnancy.
Area of Science:
- Genetics
- Reproductive Medicine
- Immunology
Background:
- Recurrent miscarriage (RM) affects ~3% of couples and has genetic factors.
- Copy number variants (CNVs) are implicated in reproductive disease susceptibility.
- Understanding genetic contributions to RM is crucial for improving reproductive outcomes.
Purpose of the Study:
- To investigate the genome-wide profile of CNVs in recurrent miscarriage (RM).
- To identify specific genetic rearrangements that modulate the risk of RM.
- To explore the functional implications of identified CNVs in RM.
Main Methods:
- Genome-wide screening of RM patients and controls.
- Functional profiling of genes within rearranged regions.
- Meta-analysis and population-based cohort comparisons to validate findings.
Main Results:
- Excessive cumulative CNV burden observed in some RM cases.
- Significant enrichment of immune-related pathways in genes affected by CNVs.
- A 61.6 kb duplication at 5p13.3 identified as a significant maternal risk factor for RM (OR=4.82, P=0.012).
- This duplication is rare globally (0.7%-1.2%) but more prevalent in RM cases (6.6%-7.5%).
- The duplication disrupts PDZD2 and GOLPH3 genes crucial for placental function.
Conclusions:
- CNVs, particularly the 5p13.3 duplication, represent a novel genetic risk factor for recurrent miscarriage.
- Disruption of placental genes PDZD2 and GOLPH3 may underlie the increased risk.
- Further research into genetic factors can improve understanding and management of RM.
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