Extracellular Vesicle Surface Protein Profiling in Metabolic Dysfunction‐associated Steatotic Liver Disease in Obesity

ABSTRACT Metabolic dysfunction‐associated steatotic liver disease (MASLD) is highly prevalent in obesity, but scalable tools for biological risk stratification remain limited. In this cross‐sectional, single‐centre discovery study (MULTISITE), we profiled circulating extracellular vesicle (cEV) surface proteins by EV Array in platelet‐poor plasma from individuals with obesity and MASLD ( n = 36), individuals with obesity without MASLD ( n = 24), and lean controls ( n = 27). Liver fat was quantified by magnetic resonance imaging proton density fat fraction (MRI‐PDFF). We assessed group differences, associations with continuous PDFF, and exploratory discriminatory performance using single markers, pairwise ratios, and sparse logistic models. We also performed an exploratory PDFF‐extremes enrichment analysis within obesity by comparing the top versus bottom 30% of the PDFF distribution ( n = 18 vs. n = 18), excluding the middle 40%. Across contrasts, single markers showed modest separation, whereas pairwise ratios provided stronger exploratory signals. In the discovery panel, uncorrected best‐ratio AUCs were 0.80–0.84 and sparse‐model AUCs were 0.79–0.84 under internal, non‐nested cross‐validation across MASLD‐focused contrasts. In the focused panel, CD36 and TREM2 were the strongest single‐marker signals for MASLD versus lean controls, whereas LRP‐1‐anchored ratios captured obesity‐ and liver fat‐associated patterns. In the PDFF‐extremes analysis, internally cross‐validated AUCs reached 0.87–0.89 in the discovery panel and 0.86 for LRP‐1/FATP5 in the focused panel; these estimates should be interpreted as exploratory, uncorrected discovery‐stage observations rather than validated classifier performance. Exploratory benchmarking showed that FLI, but not FIB‐4, discriminated MASLD‐related contrasts strongly, however, these analyses provide contextual benchmarking only and do not establish incremental clinical value of cEV markers beyond routine clinical predictors. These findings nominate biologically coherent cEV surface signatures for future validation in MASLD, anchored by lipid handling/scavenger pathways and complemented by stress, immune, and coagulation biology. Trial Registration : ClinicalTrials.gov: NCT05699863

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Publication Details

Journal
Journal of Extracellular Biology
Published
2026-09-01
DOI
https://doi.org/10.1002/jex2.70183
Primary Topic
Liver Disease Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

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article

Extracellular Vesicle Surface Protein Profiling in Metabolic Dysfunction‐associated Steatotic Liver Disease in Obesity

Katja Lund Cliff, Aase Handberg, Maiken Mellergaard, Rikke Bæk et al.
Journal of Extracellular Biology
Liver Disease Diagnosis and Treatment
article

Extracellular Vesicle Surface Protein Profiling in Metabolic Dysfunction‐associated Steatotic Liver Disease in Obesity

Katja Lund Cliff, Aase Handberg, Maiken Mellergaard, Rikke Bæk, Javier Donoso‐Quezada, Maléne Møller Jørgensen, Nahuel Aquiles García, Kirstine Kløve‐Mogensen, Malwina Ulanowska
article en

Abstract

ABSTRACT Metabolic dysfunction‐associated steatotic liver disease (MASLD) is highly prevalent in obesity, but scalable tools for biological risk stratification remain limited. In this cross‐sectional, single‐centre discovery study (MULTISITE), we profiled circulating extracellular vesicle (cEV) surface proteins by EV Array in platelet‐poor plasma from individuals with obesity and MASLD ( n = 36), individuals with obesity without MASLD ( n = 24), and lean controls ( n = 27). Liver fat was quantified by magnetic resonance imaging proton density fat fraction (MRI‐PDFF). We assessed group differences, associations with continuous PDFF, and exploratory discriminatory performance using single markers, pairwise ratios, and sparse logistic models. We also performed an exploratory PDFF‐extremes enrichment analysis within obesity by comparing the top versus bottom 30% of the PDFF distribution ( n = 18 vs. n = 18), excluding the middle 40%. Across contrasts, single markers showed modest separation, whereas pairwise ratios provided stronger exploratory signals. In the discovery panel, uncorrected best‐ratio AUCs were 0.80–0.84 and sparse‐model AUCs were 0.79–0.84 under internal, non‐nested cross‐validation across MASLD‐focused contrasts. In the focused panel, CD36 and TREM2 were the strongest single‐marker signals for MASLD versus lean controls, whereas LRP‐1‐anchored ratios captured obesity‐ and liver fat‐associated patterns. In the PDFF‐extremes analysis, internally cross‐validated AUCs reached 0.87–0.89 in the discovery panel and 0.86 for LRP‐1/FATP5 in the focused panel; these estimates should be interpreted as exploratory, uncorrected discovery‐stage observations rather than validated classifier performance. Exploratory benchmarking showed that FLI, but not FIB‐4, discriminated MASLD‐related contrasts strongly, however, these analyses provide contextual benchmarking only and do not establish incremental clinical value of cEV markers beyond routine clinical predictors. These findings nominate biologically coherent cEV surface signatures for future validation in MASLD, anchored by lipid handling/scavenger pathways and complemented by stress, immune, and coagulation biology. Trial Registration : ClinicalTrials.gov: NCT05699863

Journal of Extracellular BiologyVol. 5(9)
Aalborg University Hospital (DK), Fundación Miguel Lillo (AR), Aalborg University (DK)
Novo Nordisk Fonden
Reduced inequalities
Openalex Percentile: Top 10%
Liver Disease Diagnosis and Treatment
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