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Kidney international

July 24, 2026 · via Europe PMC

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

Wenzel A, Reusch B, Knaup KX, +10 more, Beck BB.

Journal ArticleOpen access

AI summary — for doctors, generated from the abstract only

Targeted long-read sequencing with VNTRtools improves diagnosis of MUC1-related ADTKD, including de novo cases.

What was studied

Retrospective cohort of 78 individuals analyzed with amplicon long-read sequencing of the MUC1 VNTR and custom software.

Key findings

  • Ten new ADTKD-MUC1 diagnoses were made, including a confirmed de novo case
  • Pathogenic frameshift variants were detected with high confidence in 24 individuals
  • 18 previously unreported VNTR repeat unit types found
  • Analysis took seconds to minutes per sample

Clinical relevance

Resolves a long-standing genetic diagnostic gap for unexplained familial tubulointerstitial disease.

Who should care

NephrologyPediatric Nephrology

Limitations

Retrospective, single-technique cohort with unresolved VNTR structures in some probands, and availability is limited to specialized labs.

Use short-read VNTR screening first and long-read confirmation for suspected ADTKD-MUC1.

This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.

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.

DOI

10.1016/j.kint.2026.06.040

PMID

42498060

Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.

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