Targeted VNTR long read sequencing resolves a diagnostic bottleneck in ADTKD and detects de novo ADTKD-MUC1

Wenzel A, Reusch B, Knaup K, Zagorec N, Fistrek Prlic M, Becker K, Riehmer V, Müller RU, Pasutto F, Hoefele J, Wiesener MS, Huettel B, Erger F, Beck BB (2026)

Publication Type: Journal article

Publication year: 2026

Journal

Kidney International Nature Publishing Group: Open Access Hybrid Model Option A

DOI: 10.1016/j.kint.2026.06.040

Abstract

Introduction: The molecular diagnosis of autosomal dominant tubulointerstitial kidney disease due to MUC1 variants (ADTKD-MUC1) using high-throughput (short-read) sequencing methods remains challenging due to the presence of a coding long variable-number tandem repeat (VNTR) region wherein most known pathogenic variants are located. Methods: Here, we used targeted amplicon long-read sequencing to study the MUC1 VNTR in a retrospective cohort study of 78 individuals. Using a bioinformatic pipeline including newly developed specialized software, VNTRtools, we reconstructed patient-specific complete VNTR haplotypes, generated a synthetic VNTR reference, performed long-read realignment to this reference, and finally performed variant calling. Results: VNTRtools proved efficient, requiring seconds or minutes per sample to accurately identify all pathogenic MUC1 frameshift variants in positive controls, including atypical variants. Ten new diagnoses of ADTKD-MUC1 were made. Furthermore, we report a confirmed de novo case of ADTKD-MUC1 in a 32-year-old patient. We were able to structurally resolve and phase the interindividually highly variable VNTRs in most probands, enabling the high-confidence detection of pathogenic frameshift variants in 24 individuals. We also detected 18 previously unreported VNTR repeat unit types, demonstrating the highly polymorphic nature of MUC1’s VNTR. Conclusions: We propose a combined approach in which short-read VNTR analysis using the published alignment-free bioinformatic tools is used as a first-line test, followed by targeted long-read sequencing with VNTRtools analysis for confirmatory testing and in-depth VNTR characterization. This combined approach will lead to a higher diagnostic confidence in ADTKD-MUC1—especially in sporadic cases. Complete VNTR haplotype information will likely enable a better genetic understanding of this currently underdiagnosed disorder and may become relevant for future therapeutic approaches like targeted silencing of the pathogenic MUC1 allele.

Authors with CRIS profile

Karl Knaup Department of Medicine 4 – Nephrology and Hypertension Francesca Pasutto Medizinische Fakultät Michael Wiesener Interdisziplinäres Zentrum für Klinische Forschung (IZKF)

Involved external institutions

Universitätsmedizin Greifswald / Universitätsklinikum Greifswald DE Germany (DE) Universitätsklinikum Köln DE Germany (DE) University Hospital Dubrava HR Croatia (HR) Zagreb University Hospital Centre / Klinički bolnički centar Zagreb (KBC) HR Croatia (HR) Universität zu Köln DE Germany (DE) Universitätsklinikum Düsseldorf DE Germany (DE) Klinikum der Universität München (LMU Klinikum) DE Germany (DE) Max-Planck-Institut für Pflanzenzüchtungsforschung / Max Planck Institute for Plant Breeding Research DE Germany (DE)

How to cite

APA:

Wenzel, A., Reusch, B., Knaup, K., Zagorec, N., Fistrek Prlic, M., Becker, K.,... Beck, B.B. (2026). Targeted VNTR long read sequencing resolves a diagnostic bottleneck in ADTKD and detects de novo ADTKD-MUC1. Kidney International. https://doi.org/10.1016/j.kint.2026.06.040

MLA:

Wenzel, Andrea, et al. "Targeted VNTR long read sequencing resolves a diagnostic bottleneck in ADTKD and detects de novo ADTKD-MUC1." Kidney International (2026).

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