
==== Front
Am J Respir Crit Care Med
Am J Respir Crit Care Med
ajrccm
American Journal of Respiratory and Critical Care Medicine
1073-449X
1535-4970
American Thoracic Society

39078175
202407-1290ED
10.1164/rccm.202407-1290ED
Editorials
Unveiling Biological Age: A New Frontier in Predicting Outcomes in Chronic Lung Disease
de Andrade Joao A. 1
Agudelo Garcia Paula A. 2
Mora Ana L. 2
1 Department of Medicine
Division of Allergy, Pulmonary, and Critical Care Medicine
Vanderbilt University Medical Center
Nashville, Tennessee
2 Department of Internal Medicine
Division of Pulmonary, Critical Care, and Sleep Medicine
The Ohio State University
Columbus, Ohio
30 7 2024
1 9 2024
30 7 2024
210 5 541543
Copyright © 2024 by the American Thoracic Society
2024
https://creativecommons.org/licenses/by-nc-nd/4.0/ This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0. For commercial usage and reprints, please e-mail Diane Gern (dgern@thoracic.org).
==== Body
pmcAging is not merely the inevitable consequence of time passing; rather, it represents a progressive deterioration of physiological processes and homeostasis, eventually leading to a degree of function that is incompatible with life. Lung function declines as one ages, and several chronic lung diseases, such as idiopathic pulmonary fibrosis (IPF), progressive interstitial lung diseases (ILDs), and chronic obstructive pulmonary disease (COPD), are believed to be associated with an accelerated aging process. ILDs, particularly IPF, represent a formidable challenge in pulmonary medicine. IPF is characterized by progressive scarring of the lung with relentless loss of function and ultimately death. Despite advances in understanding of its pathology and the availability of two drugs that slow disease progression, these entities invariably have a very poor prognosis (1), and more effective disease-modifying strategies are needed.

As aging is heterogeneous, and several factors such as diet, environment, and lifestyle choices can affect individuals with the same chronological age differently, the term “biological age” has been coined to describe how old our cells are. Biological age indeed captures physiological decline better than chronological age and can be more informative when trying to understand the biological roots of several chronic diseases. In this sense, lifespan is not equal to health span. Epigenetic clocks based on DNA methylation at selected sites have been used to determine the aging rate, predict mortality, and guide health interventions (2). Telomere attrition and transcript, protein, and metabolite abundances, in combination with clinical parameters, have been explored as potential biomarkers of systemic and tissue-specific aging (3–7). However, there are still numerous limitations in assessments, data integration, and validation that make difficult the generalization of current biomarkers.

Traditionally, age has been a critical determinant of IPF prognosis, with older individuals facing significantly reduced survival, which is further corroborated by the finding of reduction of peripheral blood telomere length (PB-TL) in IPF and other fibrotic ILDs. However, in an elegant work published in this issue of the Journal, Pugashetti and colleagues (pp. 639–647) challenge the simplistic association of chronological age and disease outcome, delving into the concept of biological age. They used proteomic profiling and causal mediation analysis in registry-based populations with IPF, non-IPF ILD, and COPD (8). The “casual mediation framework” is useful as one attempts to understand how one thing causes another by identifying the intermediate factor (i.e., “mediators”) between a factor (in this case “chronological age”) and an outcome (in this case survival). This is a method that allows one to develop a more nuanced understanding of complex relationships among variables and to gain insights into the underlying mechanisms driving these relationships.

The investigators’ core hypothesis was that biological age completely mediates the relationship between chronological age and survival in chronic lung disease. In this study, biological age was measured using semiquantitative proteomic approaches in a panel of plasma proteins. The discovery cohort was composed of patients with IPF (n = 874), and the validation cohort was composed of patients with non-IPF ILD (n = 983). The overall patient population was derived from an ancillary study of the PRECISIONS (Prospective Treatment Efficacy in IPF Using Genotype for NAC Selection) clinical trial, in which multiomics analysis was performed in stored blood samples from patients with fibrotic ILD who were enrolled in the prospective registries of the Pulmonary Fibrosis Foundation, the University of Virginia, the University of California, Davis, and the University of Chicago. Clinical and proteomic data from a subset of patients with COPD from SPIROMICS (Subpopulations and Intermediate Markers in COPD Study) (n = 295) were included as a comparator for aging-related disease. The discovery and validation cohorts were combined for the survival analysis.

One hundred forty proteins that had been previously associated with survival in IPF were analyzed (9). Nineteen proteins remained significant mediators of the chronological age–survival relationship in the validation cohort. Ultimately, a five-protein composite measure of biological age that included NT-proBNP, ADAMTS16, KLK4, ELN, and RET completely mediated the chronological age–survival association in the IPF discovery cohort and better discriminated survival than chronological age for the combined cohort. Although the set of 19 proteins highlights pathways previously identified in IPF lung, including TGF-b (LTBP2, CTHRC1, GDF15) and WNT and IGF (IGBP, RSPOL), the 5-protein set measure of biological age contains potential biological markers of systemic aging (NT-proBNP) (10) and of age-related diseases such as heart failure (ADAMTS16) (11) and cancer (KLK4) (12). Interestingly, PB-TL did not mediate the relationship, and the proportions mediated by the protein mediators were higher among untreated patients compared with those treated with antifibrotic and immunosuppressant therapies. Taken together, the findings reported in this study suggest that biological age, as measured by specific protein markers of systemic physiological and homeostatic decline, may be a more accurate predictor of survival among patients with ILD than chronological age alone. The study’s extension into COPD highlights the potential broader relevance of these findings across different chronic lung diseases. Although intriguing, thought provoking, and potentially paradigm shifting, these findings ought to be interpreted with caution as one appreciates the several limitations of this study.

A causal mediation framework can suggest that a mediator is in the causal pathway between a factor and an outcome but cannot prove causation. Furthermore, although the analysis took into consideration factors such as body mass index (BMI), disease severity, tobacco use, and therapy with antifibrotics or immunosuppressants, registries often lack data on other potentially important confounders, such as diet and environmental exposures. In combining the discovery and validation cohorts to maximize power, the authors had to accept a study population that was phenotypically more heterogeneous, which might explain the data suggesting that PB-TL did not attenuate the effect of chronological age. Finally, the study sample size was relatively small and locally phenotyped, and there were potential differences in protocols for plasma collection, handling, and storage, which introduces concerns around quality control and the accuracy of the measurements due to batch effects during the proteomic analysis.

The findings of this study will need to be validated in larger, prospectively recruited, and deeply phenotyped cohorts of patients with chronic lung disease by quantitative proteomic analysis using standardized protocols and assays. Moreover, as one considers its transition to the clinical care realm, the “biological age proteomic panel” will need to be compared or integrated with other easily (and, perhaps, cost-effectively) obtainable functional clinical data such as global measures of frailty that are also associated with survival in similar populations.

Notwithstanding these limitations, the implications of these findings for future research and clinical care are significant. Identifying and monitoring these protein mediators could enable clinicians to better stratify patients by their risk of disease progression and death, tailor treatment strategies accordingly, and enrich clinical trials. Moreover, understanding the mechanisms by which these proteins influence disease outcomes open avenues for development of novel therapies that target aging-related pathways, with the potential to alter the course of ILD.

In conclusion, this study adds to our understanding of the role of aging in the pathogenesis of chronic lung disease and represents one additional step toward personalized approaches to the management of this population. As we strive to improve outcomes for patients with ILD, furthering our understanding and targeting biological age represents a promising frontier in pulmonary medicine.

Originally Published in Press as DOI: 10.1164/rccm.202407-1290ED on July 30, 2024

Author disclosures are available with the text of this article at www.atsjournals.org.
==== Refs
References

1. Raghu G Remy-Jardin M Richeldi L Thomson CC Inoue Y Johkoh T et al. Idiopathic pulmonary fibrosis (an update) and progressive pulmonary fibrosis in adults: an official ATS/ERS/JRS/ALAT clinical practice guideline Am J Respir Crit Care Med 2022 205 e18 e47 35486072
2. Horvath S Raj K DNA methylation-based biomarkers and the epigenetic clock theory of ageing Nat Rev Genet 2018 19 371 384 29643443
3. Bortz J Guariglia A Klaric L Tang D Ward P Geer M et al. Biological age estimation using circulating blood biomarkers Commun Biol 2023 6 1089 37884697
4. Vaiserman A Krasnienkov D Telomere length as a marker of biological age: state-of-the-art, open issues, and future perspectives Front Genet 2020 11 630186 33552142
5. Jia M Agudelo Garcia PA Ovando-Ricardez JA Tabib T Bittar HT Lafyatis RA et al. Transcriptional changes of the aging lung Aging Cell 2023 22 e13969 37706427
6. Oblak L van der Zaag J Higgins-Chen AT Levine ME Boks MP A systematic review of biological, social and environmental factors associated with epigenetic clock acceleration Ageing Res Rev 2021 69 101348 33930583
7. Courtwright AM El-Chemaly S Telomeres in interstitial lung disease: the short and the long of it Ann Am Thorac Soc 2019 16 175 181 30540921
8. Pugashetti JV Kim JS Bose S Adegunsoye A Linderholm AL Chen CH et al. Biological age, chronological age and survival in pulmonary fibrosis: a causal mediation analysis Am J Respir Crit Care Med 2024 210 639 647 38843133
9. Oldham JM Huang Y Bose S Ma S-F Kim JS Schwab A et al. Proteomic biomarkers of survival in idiopathic pulmonary fibrosis Am J Respir Crit Care Med 2024 209 1111 1120 37847691
10. Muscari A Bianchi G Forti P Magalotti D Pandolfi P Zoli M et al. Pianoro Study Group N-terminal pro B-type natriuretic peptide (NT-proBNP): a possible surrogate of biological age in the elderly people Geroscience 2021 43 845 857 32780292
11. Yao Y Hu C Song Q Li Y Da X Yu Y et al. ADAMTS16 activates latent TGF-beta, accentuating fibrosis and dysfunction of the pressure-overloaded heart Cardiovasc Res 2020 116 956 969 31297506
12. Gong W Liu Y Seidl C Dreyer T Drecoll E Kotzsch M et al. Characterization of kallikrein-related peptidase 4 (KLK4) mRNA expression in tumor tissue of advanced high-grade serous ovarian cancer patients PLoS One 2019 14 e0212968 30811511
