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Deep Visual Proteomics maps proteotoxicity in a genetic liver disease

Deep Visual Proteomics maps proteotoxicity in a genetic liver disease

8.9.2025

Deep Visual Proteomics maps proteotoxicity in a genetic liver disease

Aims

Protein misfolding diseases, including α1-antitrypsin deficiency (AATD), pose substantial healthchallenges, with their cellular progression still poorly understood. We use spatial proteomics by massspectrometry and machine learning to map AATD in human liver tissue. Combining Deep VisualProteomics (DVP) with single-cell analysis we probe intact patient biopsies to resolve molecularevents during hepatocyte stress in pseudotime across fibrosis stages. We achieve proteome depth of up to 4,300 proteins from one-third of a single cell in formalin-fixed, paraffin-embedded tissue. Thisdataset reveals a potentially clinically actionable peroxisomal upregulation that precedes the canonicalunfolded protein response. Our single-cell proteomics data show α1-antitrypsin accumulation islargely cell-intrinsic, with minimal stress propagation between hepatocytes. We integrated proteomicdata with artificial intelligence-guided image-based phenotyping across several disease stages, revealing a late-stage hepatocyte phenotype characterized by globular protein aggregates and distinctproteomic signatures, notably including elevated TNFSF10 (also known as TRAIL) amounts. Thisphenotype may represent a critical disease progression stage. Our study offers new insights into AATD pathogenesis and introduces a powerful methodology for high-resolution, insitu proteomic analysis ofcomplex tissues. This approach holds potential to unravel molecular mechanisms in various protein misfolding disorders, setting a new standard for understanding disease progression at the single-cell level in human tissue.

Methods

Clinical cohorts and sample preparation

Patient biopsies and explant samples were obtained at two different sites, Odense University Hospital(OUH) and Aachen RWTH University Hospital (UKA). The sample origin is indicated in Supplementary Table. Following ethica guidelines, the clinical data provided here are deidentified by reporting only sample type, fibrosis score and site of origin.

Summary

Spatial omics technologies are revolutionizing our ability to deconvolute molecular events at single-cell resolution within a tissue context. Whereas much focus has been placed on spatial genomics and transcriptomics, recent advances in multiplexed imaging and proteomics are beginning to shed light on the functional proteomic layer. Mass spectrometry (MS)-based proteomics has made significant stridestowards biologically informative single-cell analysis, now enabling quantification of up to 5,000 proteins in cultured cells. In the tissue context, we have recently introduced Deep Visual Proteomics(DVP), which integrates staining, artificial intelligence-guided cell segmentation and classification, laser microdissection of single-cell shapes and high-sensitivity MS. DVP excels in digital pathologyapplications with pronounced spatial and visual components, providing simultaneous and deepproteomic characterization at the level of thousands of proteins.

We reasoned that these emerging technologies would be ideally suited to elucidate molecular eventsduring the progressive worsening of proteotoxicity as it unfolds in patients. Proteotoxicity, characterized by the accumulation of misfolded and aggregated proteins leading to cell damage, is a hallmark of many diseases, including neurodegenerative pathologies such as Alzheimer’s disease and Parkinson’s disease. The underlying cause of proteotoxicity is a disruption in protein homeostasis, resulting in an imbalance between protein synthesis, folding and clearance mechanisms.

To investigate proteotoxicity in a clinically relevant context, we focused on a disorder with unmetclinical need that exemplifies the challenges of protein misfolding and aggregation in a vital organ. The fibrogenic liver disease α1-antitrypsin (AAT) deficiency (AATD) is a genetic disorder caused by autosomal, codominant mutations in the SERPINA1 gene, resulting in misfolding and accumulation ofAAT in hepatocytes. Most severe AATD cases are caused by a homozygous Z-variant (Pi*ZZ genotype) with a peak incidence of 1:2,000 in individuals of European descent. Current hypothesessuggest that the severity of liver damage correlates with the amount of accumulated AAT. However, the mechanisms driving fibrogenesis or hepatocyte survival versus death remain unclear, leavingpotentially druggable targets unexplored.

To address this challenge, we curated a cohort of formalin-fixed paraffin-embedded (FFPE) biopsiesand liver explants from patients homozygous for the pathogenic Z-variant, encompassing all fibrosisstages (n = 34; Extended Data Fig. and Supplementary Table). Despite the same underlying disease-causing mutation at a similar median age (58 ± 10 (s.d.) years) and BMI (25.2 ± 4.0), fibrosis stagesvaried drastically, indicating unexplored molecular resilience or risk profiles.