Accelerated Biological Aging in Familial Pulmonary Fibrosis

To the Editor:

Short telomere length in peripheral blood cells and lung epithelial cells are common features of Familial Pulmonary Fibrosis (FPF) and sporadic Idiopathic Pulmonary Fibrosis (IPF) (1). Telomere length decreases during normal aging, and we recently reported that asymptomatic first-degree relatives of patients with FPF (termed “at-risk relatives”) have shorter telomeres at enrollment and a faster annual decline in telomere length than expected (2).

Accumulation of epigenetic changes in chromatin is another hallmark of aging (3). Changes to DNA methylation at specific CpG sites have been proposed as a reliable mean of estimating the “biological age” of cells and tissues and termed the “Epigenetic Clock” (4). Biological age-predictive models have been developed based on methylation patterns across loci in different tissues from healthy subjects (4). While most individuals have a concordant biological and chronological age, chronic diseases are associated with accelerated epigenetic aging (5). In this study, we measured epigenetic age in patients with FPF and their asymptomatic relatives to understand whether accelerated epigenetic aging is present in FPF (figure 1a). The results indicate that epigenetic aging and short telomeres can overlap during FPF.

Figure 1. Epigenetic analysis of subjects with familial pulmonary fibrosis (FPF) and at-risk relatives indicates accelerated biological ageing.

a) Schematic representation of epigenetic age and features of biological ageing in FPF. b) Characteristics of participants selected for DNA-associated ageing analysis. Data are presented as mean±sd. c) ΔDNAge (difference between epigenetic age and chronological age) determined from DNA isolated from whole blood of healthy controls, at-risk subjects in FPF kindreds, and FPF patients. ΔDNAge of d) at-risk and e) FPF probands with mean telomere terminal restriction fragment length (MTL) as indicated (% adjusted for age based on MTL values observed in normal control subjects). f) ΔDNAge of at-risk and FPF probands with and without pathogenic rare variants (RVs) in telomere maintenance genes. Box and whisker plots represent median values and interquartile ranges. *: p<0.05; **: p<0.0001.

Participants were selected from the FPF Registry at Vanderbilt University Medical Center, which enrolls bloodline members of families in which two or more members have idiopathic interstitial pneumonia, including at least one with IPF. Affected proband donates a blood sample at registry enrollment. Asymptomatic first-degree relatives of patients with FPF participate in a prospective observational study that conducts serial screening high-resolution computed tomography examinations to identify subclinical FPF (6–8). Control participants are non-blood relatives who have married into FPF families. These studies were approved by the Vanderbilt University Institutional Review Board (IRB# 020343, 080780). The mean telomere terminal restriction fragment length (MTL) was measured in DNA extracted from whole blood via Southern blot and the percentile for age was calculated using the MTL of healthy control population as we have previously described (7). Pathogenic rare variants (RV) in telomere maintenance genes (TERT, TERC, RTEL1, PARN) were identified among FPF proband and at-risk relatives as described (9). For assessment of the Epigenetic Clock, genomic DNA was isolated from whole blood samples using Gentra puregene kit (Qiagen). DNA samples were submitted to Zymo Research to measure epigenetic age. Bisulfite conversion of DNA was performed according to the standard protocol (EZ DNA Methylation-Lightning^™ Kit) to differentiate unmethylated from methylated cytosine residues. High throughput methylation analysis followed by DNA methylation age analysis was performed using the Simplified Whole-panel Amplification Reaction Method based on Horvath clock (10). Data was analyzed using elastic net regression of DNA methylation levels (DNAge) according to Zymo Research’s proprietary DNAge predictor. DNA methylation levels of 353 CpG sites were used to calculate DNAge (5). Results were expressed as ΔDNAge = DNAge – chronological age at blood sample collection. All data were presented as median interquartile range and comparisons between two groups were analyzed by unpaired Mann-Whitney test. Statistical analysis was performed using Prism 10 (GraphPad).

In total, we analyzed 57 subjects with FPF, 54 asymptomatic at-risk relatives, and 23 control subjects. Participant characteristics are in figure 1b. The ΔDNAge was higher among at-risk FPF relatives (6.7 years, IQR 3.8 to 9.9 years) and FPF probands (3.6 years, IQR −0.85 to 8.1 years) compared to control subjects (0.2 years, IQR −3.2 to 3.3 years) (figure 1c). While the relationship between accelerated epigenetic aging and MTL has been examined in other studies (11–13), this association has not been investigated in IPF, where short telomeres are common and appear to impact disease progression (1, 14). For at-risk FPF relatives, ΔDNAge was independent of MTL (figure 1d). However, FPF probands with MTL=1% (adjusted for age) had greater ΔDNAge compared to those with longer telomeres (figure 1e), indicating that different aging processes can intersect in FPF. We investigated the influence of pathogenic telomere-related gene RV on epigenetic aging, and the results showed no difference in ΔDNAge among at-risk relatives and FPF probands with or without a pathogenic telomere-related gene RV (figure 1f). Together, these results indicate that epigenetic aging is increased in FPF patients and relatives at-risk for FPF. While the presence of accelerated epigenetic aging was largely independent of MTL and telomere-related RV status, these aging-related processes appear to co-exist in FPF patients with very short telomeres. Our data also indicate that most at-risk individuals have an epigenetic age that exceeds the values observed in a healthy control population. Since not all at-risk individuals develop PF, our findings suggest that accelerated epigenetic aging alone is not sufficient to cause clinical disease in FPF families. Further investigation is needed to assess the impact of epigenetic aging in conjunction with other factors during the development of fibrosis, such as cigarette smoke and apnea. A longitudinal assessment of DNAge could help identifying individual changes in epigenetic age before and after clinical disease and in association with changes in MTL. This study offers valuable insights into biological aging in families with FPF. Despite the limitations, such as the size of the cohort analyzed and the absence of longitudinal analysis, our research highlights the potential for a more comprehensive evaluation of biological aging progression in FPF in the future. Although we did not assess the impact of epigenetic aging on disease severity or survival time in FPF patients, nor the influence of aging on cellular functions, our findings indicate that FPF family members exhibit evidence of accelerated aging through two distinct aging-related biological processes. Understanding the causes of aging could play a crucial role in defining early disease mechanisms and prevention strategies.