Molecular genetic diagnosis of autosomal dominant polycystic kidney disease – A systematic review

Abstract

Background: Autosomal dominant polycystic kidney disease (ADPKD) is a genetically heterogeneous disorder primarily caused by pathogenic variants in PKD1 and PKD2. Although molecular testing has revolutionized diagnosis, variability persists in testing strategies and diagnostic yields. This review aims to evaluate molecular genetic techniques used in ADPKD diagnosis and summarize evidence on their diagnostic performance. Method: Following a predefined protocol and PRISMA 2020 guidelines, PubMed, Scopus, and Web of Science were searched for studies published between January 2015 and August 2025. Eligible studies included ≥ 30 clinically diagnosed ADPKD participants and reported patient-level diagnostic data. Two investigators independently extracted information on testing methods, diagnostic yield, and identified genes. Results: From 23,718 records, 20 studies met inclusion criteria, with sample sizes ranging from 32 to 634 participants. Diagnostic methods included Sanger sequencing (SS), multiplex ligand-probe amplification (MLPA), long-range PCR (LR-PCR), targeted next-generation sequencing (NGS) panels, whole-exome sequencing (WES), and whole-genome sequencing (WGS). Detection rates ranged from 61% (LR-PCR) to 92% (targeted NGS). PKD1 and PKD2 variants accounted for 79.9% and 15.9% of cases, respectively. Additional variants were identified in GANAB, HNF1B, IFT140, PRKCSH, and PKHD1. Conclusion: Targeted NGS panels provided the highest diagnostic accuracy and cost-effectiveness for ADPKD. Complementary use of MLPA and LR-PCR improved detection of complex variants. Further optimization of sequencing workflows and variant interpretation will enhance diagnostic precision and clinical application. This review provides an evidence-based foundation for current diagnostic practices in ADPKD.

Keywords

ADPKD / Polycystic kidney / Autosomal dominant / Genotyping / PKD1 / PKD2

CRediT authorship contribution statement

N.C. and E.S. contributed equally to this work. Conceptualization, E.S.; methodology, N.C. and E.S.; literature search and data extraction, N.C. and E.S.; formal analysis, N.C. and E.S.; writing—original draft preparation, N.C. and E.S.; writing—review and editing, N.C. and E.S.; visualization, N.C. and E.S.; supervision, N.C. All authors have read and agreed to the published version of the manuscript.

Institutional review board statement

Not applicable

Funding

None

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supporting information

Supplementary data associated with this article can be found in the online version at doi:10.1016/j.gmg.2026.100099.

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