Airway Telomere Length in Lung Transplant Recipients

Lung transplantation: Current insights and outcomes

Until now, the ability to predict or retard immune-mediated rejection events after lung transplantation is still limited due to the lack of specific biomarkers. The pressing need remains to early diagnose or predict the onset of chronic lung allograft dysfunction (CLAD) and its differential phenotypes that is the leading cause of death. Omics technologies (mainly genomics, epigenomics, and transcriptomics) combined with advanced bioinformatic platforms are clarifying the key immune-related molecular routes that trigger early and late events of lung allograft rejection supporting the biomarker discovery. The most promising biomarkers came from genomics. Both unregistered and NIH-registered clinical trials demonstrated that the increased percentage of donor-derived cell-free DNA in both plasma and bronchoalveolar lavage fluid showed a good diagnostic performance for clinically silent acute rejection events and CLAD differential phenotypes. A further success arose from transcriptomics that led to development of Molecular Microscope® Diagnostic System (MMDx) to interpret the relationship between molecular signatures of lung biopsies and rejection events. Other immune-related biomarkers of rejection events may be exosomes, telomer length, DNA methylation, and histone-mediated neutrophil extracellular traps (NETs) but none of them entered in registered clinical trials. Here, we discuss novel and existing technologies for revealing new immune-mediated mechanisms underlying acute and chronic rejection events, with a particular focus on emerging biomarkers for improving precision medicine of lung transplantation field.

Exploring the Causal Effects of Mineral Metabolism Disorders on Telomere and Mitochondrial DNA: A Bidirectional Two-Sample Mendelian Randomization Analysis

The aim of this study was to assess the causal relationships between mineral metabolism disorders, representative of trace elements, and key aging biomarkers: telomere length (TL) and mitochondrial DNA copy number (mtDNA-CN). Utilizing bidirectional Mendelian randomization (MR) analysis in combination with the two-stage least squares (2SLS) method, we explored the causal relationships between mineral metabolism disorders and these aging indicators. Sensitivity analysis can be used to determine the reliability and robustness of the research results. The results confirmed that a positive causal relationship was observed between mineral metabolism disorders and TL (p < 0.05), while the causal relationship with mtDNA-CN was not significant (p > 0.05). Focusing on subgroup analyses of specific minerals, our findings indicated a distinct positive causal relationship between iron metabolism disorders and both TL and mtDNA-CN (p < 0.05). In contrast, disorders in magnesium and phosphorus metabolism did not exhibit significant causal effects on either aging biomarker (p > 0.05). Moreover, reverse MR analysis did not reveal any significant causal effects of TL and mtDNA-CN on mineral metabolism disorders (p > 0.05). The combination of 2SLS with MR analysis further reinforced the positive causal relationship between iron levels and both TL and mtDNA-CN (p < 0.05). Notably, the sensitivity analysis did not indicate significant pleiotropy or heterogeneity within these causal relationships (p > 0.05). These findings highlight the pivotal role of iron metabolism in cellular aging, particularly in regulating TL and sustaining mtDNA-CN, offering new insights into how mineral metabolism disorders influence aging biomarkers. Our research underscores the importance of trace element balance, especially regarding iron intake, in combating the aging process. This provides a potential strategy for slowing aging through the adjustment of trace element intake, laying the groundwork for future research into the relationship between trace elements and healthy aging.

The Intersection of Aging and Lung Transplantation: its Impact on Transplant Evaluation, Outcomes, and Clinical Care

Purpose

Older adults (age ≥ 65 years) are the fastest growing age group undergoing lung transplantation. Further, international consensus document for the selection of lung transplant candidates no longer suggest a fixed upper age limit. Although carefully selected older adults can derive great benefit, understanding which older adults will do well after transplant with improved survival and health-related qualiy of life is key to informed decision-making. Herein, we review the epidemiology of aging in lung transplantation and its impact on outcomes, highlight selected physiological measures that may be informative when evaluating and managing older lung transplant patients, and identify directions for future research.

Recent Findings

In general, listing and transplanting older, sicker patients has contributed to worse clinical outcomes and greater healthcare use. Emerging evidence suggest that measures of physiological age, such as frailty, body composition, and neurocognitive and psychosocial function, may better identify risk for poor transplant outcomes than chronlogical age.

Summary

The evidence base to inform transplant decision-making and improvements in care for older adults is small but growing. Multipronged efforts at the intersection of aging and lung transplantation are needed to improve the clinical and patient centered outcomes for this large and growing cohort of patients. Future research should focus on identifying novel and ideally modifiable risk factors for poor outcomes specific to older adults, better approaches to measuring physiological aging (e.g., frailty, body composition, neurocognitive and psychosocial function), and the underlying mechanisms of physiological aging. Finally, interventions that can improve clinical and patient centered outcomes for older adults are needed.

Markers of rejection of a lung allograft: state of the art

Chronic lung allograft dysfunction (CLAD) affects approximately 50% of all lung transplant recipients by 5 post-operative years and is the leading cause of death in lung transplant recipients. Early CLAD diagnosis or ideally prediction of CLAD is essential to enable early intervention before significant lung injury occurs. New technologies have emerged to facilitate biomarker discovery, including epigenetic modification and single-cell RNA sequencing. This review examines new and existing technologies for biomarker discovery and the current state of research on biomarkers for identifying lung transplant rejection.