A High-Throughput Single Telomere Length Analysis Approach for Diagnosis of Telomeopathic Diseases

Telomeres are the structures at the ends of chromosomes that protect these ends from degradation or joining to one another. Telomeres consist of repeat DNA sequences and the length is gradually eroded as the cell ages. Mounting evidence suggests a causal role for telomere dysfunction in a number of degenerative disorders. Their manifestations encompass common disease states such as idiopathic pulmonary fibrosis and bone marrow failure. Although these disorders seem to be clinically diverse, collectively they comprise a single syndrome spectrum defined by the short telomere defect. In rare cases, a patient’s telomere syndrome may appear as a condition called dyskeratosis congenita. This condition, which makes up about 1% of all telomere syndromes, is characterized by abnormal findings in the skin, mouth, and nails.

Single telomere length analysis (STELA) is a high-resolution single-molecule approach to determine telomere length distributions including those in the lower length ranges that are not so apparent with other commonly used technologies. However, STELA is labor intensive and based on Southern hybridization and is not well suited for the analysis of large cohorts, or for clinical laboratory applications. To overcome these limitations, investigators at Cardiff University (United Kingdom) and Queen Mary University London (United Kingdom) adapted STELA for high-throughput analysis (HT-STELA) of cancer cell populations and successfully applied this procedure to predict response to treatment in patients with chronic lymphocytic leukemia.

In the current study, the investigators employed HT-STELA to examine the full extent of telomere erosion in individuals with dyskeratosis congenita and related disorders, and to determine the utility of high-resolution telomere length analysis as a potential diagnostic test for telomeropathies.

HT-STELA was applied to a cohort of 171 unaffected individuals and a retrospective cohort of 172 short telomere mutation carriers. Results revealed that HT-STELA displayed a low measurement error with inter- and intra-assay coefficient of variance of 2.3% and 1.8%, respectively. While telomere length in unaffected individuals declined as a function of age, telomere length in mutation carriers appeared to increase due to a preponderance of shorter telomeres detected in younger individuals. These individuals were more severely affected, and age-adjusted telomere length differentials could be used to stratify the cohort for overall survival.

Telomere lengths of asymptomatic mutation carriers were shorter than controls, but longer than symptomatic mutation carriers, and telomere length heterogeneity was dependent on the diagnosis and mutational status. Thus, the data demonstrated that the ability of HT-STELA to detect short telomere lengths, that are not readily detected with other methods, meant it could provide powerful diagnostic discrimination and prognostic information.

Senior author Dr. Duncan M. Baird, professor of cancer and genetics at Cardiff University, said, "If a patient presents with a severe symptom such as bone marrow failure we can now test, more accurately and rapidly than ever before, if this is the result of a telomeropathy, thereby speeding up the process of providing a diagnosis for these patients. We believe the speed and accuracy of this technology will provide a step-change in the clinical utility of telomere testing."

The HT-STELA study was published in the March 11, 2021, online edition of the journal Human Genetics.

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Cardiff University
Queen Mary University London