A Balanced Chromosomal Rearrangement Disrupting the Telomerase RNA Component Gene Causes Short Telomere-Mediated Pulmonary Fibrosis
- Journal
- International journal of molecular sciences (Q1)
- Published
- 28 September 2026
- Study design
- Unclassified
- Evidence level
- Level 5, Expert Opinion (CEBM 5)
- Authors
- Noa Hourvitz, Monica Neustadter-Blackman, Avraham Unterman, Riham Smoom, Adi Mory, Hila Lederman Nahemias, et al.
- PMID
- 42883912
- DOI
- 10.3390/ijms27198667
Why clinicians should know about it
- Picked for Genetics (clinical) (paper of the day, 19 October 2026): Structural TERC disruption causing telomere disease
Abstract
Excessive telomere shortening contributes to pulmonary fibrosis (PF), with at least 30% of familial cases attributed to telomere biology disorders (TBDs). However, TBD-associated PF remains underdiagnosed because of unidentified disease-causing mutations and limited referral for telomere and genetic testing. Here, we combined telomeric restriction fragment analysis, telomere analysis by a long-read Nanopore sequencing method (NanoTelSeq), exome sequencing (ES), and optical genome mapping (OGM) to investigate the underlying cause of disease in a family affected by PF, microcephaly, and premature hair graying. We identified a familial balanced translocation associated with short telomeres, which involved a chromosome 3 breakpoint within the non-coding telomerase RNA component (TERC) gene, disrupting the 451-nucleotide telomerase RNA. Establishing the diagnosis enabled a TBD-tailored protocol and successful lung transplantation in the proband at age 49. These findings identified structural disruption of TERC as a previously unrecognized cause of TBD and broadened the genetic landscape of TBD beyond splicing, single nucleotide substitutions, and insertion/deletion variants. Furthermore, they demonatrate the importance of routine telomere length measurement alongside comprehensive genomic testing in familial PF.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.