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May 15, 2026Human Reproduction Update0 citations

Maternal genetic variants associated with aneuploid conception: a narrative review

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SHSiyao HaWLWenyi LiuPYPing Yuan

Key Points

  • This review aims to summarize the maternal genetic variants associated with aneuploid conceptions and highlight future research directions.
  • Systematic search of PubMed, Embase, and Cochrane Library for studies on maternal genetic variants and aneuploidy.
  • Review included genetic confirmation of aneuploidy in various contexts and focused on relevant genetic variants.
  • Data extraction included study identifiers, population characteristics, and classification of genetic variants.
  • Identified maternal variants associated with aneuploid conceptions across 28 studies.
  • Functionally categorized variants into meiotic recombination, spindle dynamics, and checkpoint enforcement.
  • Highlighted likely pathogenic variants in KIF18A, ELL3, and CEP120, with commercial NGS panel implications for some associated genes.

Abstract

BACKGROUND: Human aneuploid conception, a leading cause of infertility, pregnancy loss, and congenital disorders (e.g. Down's syndrome), arises from errors in chromosome segregation during oocyte meiosis or embryonic mitosis. While advanced maternal age is a well-established risk factor, significant inter-individual variation exists among younger women, suggesting a substantial role for maternal genetic determinants. OBJECTIVE AND RATIONALE: This review summarizes the identified maternal genetic variants associated with aneuploid conceptions and highlights directions for future research. SEARCH METHODS: We systematically searched PubMed, Embase, and the Cochrane Library (up to 12 January 2026), using key terms related to maternal genetics, genetic variants, aneuploidy, and pregnancy. Inclusion criteria were human studies, genetic confirmation of aneuploidy (in oocytes/embryos/products of conception/fetal cells), maternal variants (rare single-nucleotide variations, single-nucleotide polymorphisms, and small indels ≤50 bp), and English-language publications. Exclusion criteria were non-human studies, structural/non-aneuploid numerical abnormalities, paternal factors, and conference abstracts. Extracted data items included study identifiers, population characteristics, variant details, detection methods, clinical phenotypes, type and origin of aneuploidy, pathogenicity or effect assessment, and gene inclusion in currently commercially available infertility next-generation sequencing (NGS) panels. Rare variants were classified per American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) guidelines, whereas common variants were evaluated based on effect estimates and functional validation. Study quality was appraised using a modified Newcastle-Ottawa Scale. Supplementary searches explored associations between the identified genes and a broader range of reproductive phenotypes. OUTCOMES: From 28 studies covering the broad clinical spectrum of aneuploid pregnancies (including embryo arrest, implantation failure, pregnancy loss, hydatidiform mole, and fetal aneuploidy), we identified maternal variants associated with aneuploid conceptions. These were functionally categorized into meiotic recombination, spindle dynamics, checkpoint enforcement, and the maternal-to-zygotic transition. Among them, variants in several genes are supported by higher-quality evidence, including likely pathogenic rare variants in KIF18A, ELL3, and CEP120, as well as common variants in PLK4 and CCDC66. Although some identified genes (HFM1, MCM9, MEI1, BUB1B, NLRP2, NLRP7, and TLE6) are included in commercial infertility NGS panels, their direct association with aneuploidy requires further validation. WIDER IMPLICATIONS: This review proposes that 'aneuploidy predisposition' constitutes a critical, mechanism-driven dimension for the genetic diagnosis of infertility, complementing phenotype-based frameworks. This approach would best serve women with unexplained infertility and a normal karyotype who have either a history of recurrent aneuploidy or heterogeneous reproductive phenotypes across different cycles. Adopting this perspective refines clinical genetic testing paradigms and underscores the need to prioritize artificial intelligence-enhanced clinico-genomic association studies and develop polygenic risk models integrated with clinical factors. PROSPERO REGISTRATION NUMBER: CRD42025636217.

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Cite This Study

Ha et al. (2026) studied this question.

synapsesocial.com/papers/6a06b86ae7dec685947aad44https://doi.org/10.1093/humupd/dmag012
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