Multi-Omics: Airway Markers Flag Lung Allograft Decline
- Aug 10
- 4 min read
Chronic lung allograft dysfunction ends most lung transplants after the first year, and spirometry only flags it once the airway remodelling is permanent. A prospective Melbourne cohort of 69 recipients tried to move that window earlier, running multi-omics profiling on surveillance bronchoalveolar lavage out to 30 months post-transplant. What separated the 13 patients who later developed CLAD was not infection. It was an endothelial glycocalyx and neutrophil-recruitment program that switched on in every graft and then failed to switch off.
Key Takeaways
Multi-omics profiling of surveillance lavage flagged molecular signs of chronic lung allograft dysfunction before measurable lung function decline.
The pre-CLAD signature centred on endothelial glycocalyx remodelling and ceramide accumulation, not on bacterial or fungal overgrowth.
Stable grafts show rising microbial diversity and falling inflammatory gene expression over the first year; future CLAD patients never make that transition.
With 13 CLAD cases and no independent validation cohort, these markers are hypothesis-generating and need replication.
What Multi-Omics Integration Adds to a Lavage Sample
Of 101 enrolled recipients, 69 passed quality control: a Stable cohort of 56 CLAD-free patients, and a Biomarker cohort pairing 13 CLAD cases with 13 matched controls. Bulk RNA-seq ran on a NovaSeq 6000, untargeted metabolomics and lipidomics on a Q Exactive, alongside bacterial and fungal amplicon sequencing. All significant genes and molecules then went into MEFISTO, the time-aware extension of the MOFA+ framework described by Argelaguet and colleagues (2020), with months post-transplant as a continuous covariate. Surveillance lavage follows a clinical schedule, so treating time as a covariate is what keeps unevenly spaced samples usable.
Key Findings
Microbial diversity rises in healthy grafts: bacterial Shannon diversity increased 0.53 over 6 months (95% CI 0.304 to 0.757, p below 0.001) and fungal diversity 0.45 (p = 0.0014).
Normal first-year adaptation is large: 758 differentially expressed genes and 97 differentially abundant metabolites and lipids shifted in CLAD-free recipients.
Glycocalyx and granulocyte genes dominate the CLAD comparison: among 222 genes and 64 molecular features, HAPLN3, HS3ST3B1, SULF2, CHST2 and CSGALNACT1 rose alongside the neutrophil receptors CXCR1 and CSF3R.
Nitric oxide substrates fell while ceramides rose: L-arginine, citrulline and asymmetric dimethylarginine were depleted, whereas Cer 34:1;O2 and longer-chain species accumulated.
Timing, not magnitude, split the groups: the integrated Disease Latent Factor tracked CLAD over time (p below 0.001), and the same signature appeared transiently in stable grafts before resolving after 1.5 months.
Figure 1. Cohort construction and lung function trajectories in the multi-omics lung transplant study. Panel A traces 101 assessed recipients through exclusions to the 56-patient Stable cohort and the 26-patient Biomarker cohort. Panels B and C plot predicted FEV1 percentage against months post-transplant, individual traces in grey with spline-fitted group means overlaid; the CLAD curve peaks near 9 months, then falls. Adapted from Iacono et al. (2026), PLOS Medicine.
A Glycocalyx Signature That Never Switched Off
The endothelial glycocalyx is the proteoglycan layer lining the vascular lumen, and shedding it exposes endothelium to circulating leukocytes. Genes governing its synthesis and sulfation were among the most consistently elevated features in the CLAD group, paired with raised neutrophil receptors. The chronology is the interesting part. Stable recipients ran the same program in the weeks right after surgery, which is what ischaemia-reperfusion injury looks like, and then it faded; in CLAD patients it persisted.
Nitric Oxide Substrates Running Low
The metabolite layer arrived at the same place from a different angle. L-arginine and citrulline, substrate and co-product of endothelial nitric oxide synthase, were depleted in future CLAD patients, with asymmetric dimethylarginine following them down. Reduced nitric oxide availability degrades endothelial barrier function, which sits neatly beside the glycocalyx transcripts. Whether any of it is causal stays open; the design is observational, and the authors say so plainly.
One Aliquot, Four Data Layers
Reading inflammatory transcription next to the lipids it produces is what makes this dataset persuasive, since either layer alone would have looked like ordinary post-transplant inflammation. Lavage is volume-limited, so splitting one aliquot across four platforms is where projects quietly lose power, and the Omni-MS workflow at Dalton was built to take proteomic, metabolomic and lipidomic measurements from a single injection of one sample. For teams planning multi-omics biomarker discovery in scarce biofluids, that design keeps cross-platform batch structure out of every latent factor downstream, which is why our integrated omics service holds all layers on one instrument run.
Frequently Asked Questions
What is multi-omics analysis used for?
Multi-omics analysis measures two or more molecular layers, such as transcripts, metabolites and lipids, from one sample and models them jointly. The value is cross-validation: a gene expression change confirmed in the matching metabolite is hard to dismiss as noise. In biomarker programs it narrows candidate lists faster than any single layer.
Can multi-omics detect chronic lung allograft dysfunction before symptoms?
This study suggests it can, with caveats. The integrated signature separated future CLAD patients from stable recipients while spirometry still looked acceptable, but only 13 CLAD cases were available and no external validation set was tested. Read it as a research direction, not a clinic-ready assay.
How much sample does a multi-omics study of bronchoalveolar lavage need?
Less than most teams assume, if the workflow is designed for it. This study ran amplicon sequencing, RNA-seq, metabolomics and lipidomics from routine surveillance lavage rather than dedicated research collections. Single-injection LC-MS designs cut required volume further by avoiding a separate aliquot per assay.
Conclusion
What holds up is the direction of travel: stable grafts move toward higher microbial diversity and quieter inflammatory transcription, and future CLAD patients never make that turn. No usable test exists yet, since 13 cases without external validation cannot support a clinical threshold. Validating this signature in banked surveillance lavage would cost far less than a fresh prospective study.
Related Reading
See how we run these analyses in one lab: Dalton's multi-omics CRO services.
Citation
Iacono, G., Begka, C., Cardwell, B., Daunt, C., Chatzis, R., Pattaroni, C., Butler, A., Macowan, M., Levvey, B., Snell, G. I., Westall, G. P., & Marsland, B. J. (2026). Multi-omics biomarkers of endothelial dysregulation preceding chronic lung allograft dysfunction: A prospective cohort study. PLOS Medicine, 23(6), e1004725. https://doi.org/10.1371/journal.pmed.1004725
Note
This blog post summarizes findings from the above-cited research. Figures are adapted from the original publication. For full details, please refer to the source article.
By Seungjun Yeo, CEO at Dalton Bioanalytics. Specializing in multi-omics mass spectrometry for drug discovery and biomarker research.