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Digital telomere measurement by long-read sequencing distinguishes healthy aging from disease

Author

Listed:
  • Santiago E. Sanchez

    (Stanford University School of Medicine
    Stanford University School of Medicine
    Stanford University
    Stanford University School of Medicine)

  • Yuchao Gu

    (Stanford University School of Medicine
    Stanford University School of Medicine
    Stanford University School of Medicine)

  • Yan Wang

    (Stanford University School of Medicine
    Stanford University School of Medicine
    Stanford University School of Medicine)

  • Anudeep Golla

    (Stanford University School of Medicine)

  • Annika Martin

    (University of California)

  • William Shomali

    (Stanford University School of Medicine)

  • Dirk Hockemeyer

    (University of California
    Chan Zuckerberg Biohub
    University of California, Berkeley)

  • Sharon A. Savage

    (National Cancer Institute)

  • Steven E. Artandi

    (Stanford University School of Medicine
    Stanford University School of Medicine
    Stanford University School of Medicine)

Abstract

Telomere length is an important biomarker of organismal aging and cellular replicative potential, but existing measurement methods are limited in resolution and accuracy. Here, we deploy digital telomere measurement (DTM) by nanopore sequencing to understand how distributions of human telomere length change with age and disease. We measure telomere attrition and de novo elongation with up to 30 bp resolution in genetically defined populations of human cells, in blood cells from healthy donors and in blood cells from patients with genetic defects in telomere maintenance. We find that human aging is accompanied by a progressive loss of long telomeres and an accumulation of shorter telomeres. In patients with defects in telomere maintenance, the accumulation of short telomeres is more pronounced and correlates with phenotypic severity. We apply machine learning to train a binary classification model that distinguishes healthy individuals from those with telomere biology disorders. This sequencing and bioinformatic pipeline will advance our understanding of telomere maintenance mechanisms and the use of telomere length as a clinical biomarker of aging and disease.

Suggested Citation

  • Santiago E. Sanchez & Yuchao Gu & Yan Wang & Anudeep Golla & Annika Martin & William Shomali & Dirk Hockemeyer & Sharon A. Savage & Steven E. Artandi, 2024. "Digital telomere measurement by long-read sequencing distinguishes healthy aging from disease," Nature Communications, Nature, vol. 15(1), pages 1-11, December.
    • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-49007-4
    DOI: 10.1038/s41467-024-49007-4
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    References listed on IDEAS

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    1. Steven E. Artandi & Sandy Chang & Shwu-Luan Lee & Scott Alson & Geoffrey J. Gottlieb & Lynda Chin & Ronald A. DePinho, 2000. "Telomere dysfunction promotes non-reciprocal translocations and epithelial cancers in mice," Nature, Nature, vol. 406(6796), pages 641-645, August.
    2. Tom Vulliamy & Anna Marrone & Frederick Goldman & Andrew Dearlove & Monica Bessler & Philip J. Mason & Inderjeet Dokal, 2001. "The RNA component of telomerase is mutated in autosomal dominant dyskeratosis congenita," Nature, Nature, vol. 413(6854), pages 432-435, September.
    3. Tsung-Po Lai & Ning Zhang & Jungsik Noh & Ilgen Mender & Enzo Tedone & Ejun Huang & Woodring E. Wright & Gaudenz Danuser & Jerry W. Shay, 2017. "A method for measuring the distribution of the shortest telomeres in cells and tissues," Nature Communications, Nature, vol. 8(1), pages 1-14, December.
    4. Joe Nassour & Robert Radford & Adriana Correia & Javier Miralles Fusté & Brigitte Schoell & Anna Jauch & Reuben J. Shaw & Jan Karlseder, 2019. "Autophagic cell death restricts chromosomal instability during replicative crisis," Nature, Nature, vol. 565(7741), pages 659-663, January.
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