Published March 17, 2023 | Version v1
Journal article Open

Telomere length associates with chronological age and mortality across racially diverse pulmonary fibrosis cohorts

Description

Pulmonary fibrosis (PF) is characterized by profound scarring and poor survival. We investigated the association of leukocyte telomere length (LTL) with chronological age and mortality across racially diverse PF cohorts. LTL measurements among participants with PF stratified by race/ethnicity were assessed in relation to age and all-cause mortality, and compared to controls. Generalized linear models were used to evaluate the age-LTL relationship, Cox proportional hazards models were used for hazard ratio estimation, and the Cochran–Armitage test was used to assess quartiles of LTL. Standardized LTL shortened with increasing chronological age; this association in controls was strengthened in PF (R = −0.28; P < 0.0001). In PF, age- and sex-adjusted LTL below the median consistently predicted worse mortality across all racial groups (White, HR = 2.21, 95% CI = 1.79–2.72; Black, HR = 2.22, 95% CI = 1.05–4.66; Hispanic, HR = 3.40, 95% CI = 1.88–6.14; and Asian, HR = 2.11, 95% CI = 0.55–8.23). LTL associates uniformly with chronological age and is a biomarker predictive of mortality in PF across racial groups.

Data availability

All data supporting the findings described in this manuscript are available in the article and in the Supplementary Information and from the corresponding author upon request. Source data are provided with this paper. The processed telomere length data for the HRS control population are available at "hrsdata" with the identifier [https://hrsdata.isr.umich.edu/data-products/2008-telomere-data]. Response to data requests will be made within 6–8 weeks of receipt. The pulmonary fibrosis telomere length data that support the findings of this study are subject to controlled access via data use agreements due to reasons of clinical human data sensitivity and are available upon reasonable request from the corresponding author [A.A.].

Code for data cleaning and analysis is provided as part of the replication package. It is available at https://doi.org/10.5281/zenodo.7431322.

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Additional details

Identifiers

DOI
10.1038/s41467-023-37193-6
Other
oai:uchicago.tind.io:5647

Funding

National Institutes of Health
K23HL146942
National Institutes of Health
K23HL138190
National Institutes of Health
K23HL148498
National Institutes of Health
R01HL130796
National Institutes of Health
R01HL093096
National Institutes of Health
KL2TR001870
CHEST Foundation
Nina Ireland Program for Lung Health

UChicago Information

Division(s)
Biological Sciences Division
Department(s)
Genetics, Genomics, and Systems Biology, Human Genetics, Medicine, Public Health Sciences, Radiology