A protein-by-protein map of how human lungs age is being built from 86 donor tissue samples spanning a continuous age range. As people grow older, their lungs lose elasticity, repair themselves less effectively, and become more vulnerable to disease. Lung conditions already affect one in five people in the UK, cost the NHS £11 billion annually, and are the third leading cause of death. The problem is especially severe in North West England, which has some of the highest lung-disease mortality rates. Yet the molecular chain of events that drives lung aging remains poorly understood. This project aims to change that. By profiling thousands of proteins and their modifications across a continuous age spectrum—rather than just comparing young and old—the researcher will identify the precise molecular drivers of age-related lung decline. Early work has already flagged 186 proteins that change significantly with age, including enzymes that break down the lung’s structural scaffolding and others that misdirect repair processes. If successful, this fundamental science will reveal which proteins could be targeted with drugs to slow or reverse lung aging. That could lead to earlier detection of disease risk, better patient stratification, and treatments that keep lungs functioning longer—reducing the burden on a healthcare system already strained by an ageing population.
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Background & urgency – An estimated 17% of the population will be >65 by 2030, and this is projected to double by 2050. As individuals age, the body experiences structural and functional changes. For the respiratory tract, this often leads to decreased lung function, limited regenerative capacity, and increased susceptibility to diseases. The age-related changes originate from cumulative damage or inflammatory stress that living beings experience over a lifetime and elevates the risk of developing life-threatening conditions like cancer. With lung diseases affecting 1 in 5 people in the UK, ranking as the third leading cause of death, the healthcare system faces a significant burden. This challenge is particularly acute in North West England, which has some of the highest mortality rates from lung conditions, contributing to a UK-wide annual cost of £11billion. A burden that could be alleviated through innovative tools for early detection, patient stratification, and treatments targeting the molecular drivers of aging, which is the focus of this proposal. Prior work – I recently completed a pilot study combining bulk proteomics and single-cell RNA sequencing (scRNA-seq) comparing lung tissue from donors around 20 years old to around 70 years old, quantifying over 4,000 proteins. Significant age signatures were detected for 186 proteins. Excitingly, our findings revealed molecular drivers of pulmonary remodelling with disruptions to the delicate balance of extra-cellular matrix (ECM) maintenance proteases and their inhibitors – proteins that can be targeted for intervention. Specifically, we observe upregulation of HTRA1 alongside decreased inhibitory levels, leading to ECM breakdown. This triggers an increase in collagen and elastin production, which becomes misdirected due to reduced levels of MFAP4—the enzyme responsible for guiding elastin to its proper location. Elevated levels of chemokines, such as CXCL12, highlight inflammation that, combined with ECM breakdown, constrict the airway lumen. Aim & objectives – For this proposal, I plan to increase the sample size to 86 donors to achieve the statistical power to verify the uncovered molecular signature and detect further, subtle changes (<1.2-fold). Notably, the cohort features a continuous age profile, enabling the analysis of dynamic behaviour beyond simple up- or down-regulation. Project objectives: 1. Quantify changes in total protein abundance Profiling proteins and an initial combination of the results from a scRNA-seq screen, which has already been collected for this cohort. 2. Quantify the behaviour of PTMs Profiling post-translational modifications (phosphorylation, citrullination, and ubiquitylation) that are expected to play a role in aging. 3. Collagen crosslinking as a function of tissue stiffness Profiling natural crosslinks within the tissue (mostly of collagen) to identify drivers of lung tissue stiffening. 4. Innovative bioinformatics approaches Leveraging age-related changes in protein abundance to identify interesting targets and previously unidentified PTMs and point mutations. 5. Full integration of proteomics and scRNA-seq data Final combination with a focus to cell origin of proteins and (in-silico) validation of interesting hits from all analyses.
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