Liver and Kidney Tissues Under Opioid Exposure: Rewriting and Old Story Through Proteomics and MALDI-MSI.

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Our data revealed alterations in numerous protein expression. Differences were observed in pro- and antiapoptotic signaling, oxidative stress response, transport mechanisms, nucleic acid metabolism, and regulators of alternative splicing, among others. Liver tissue exhibited primarily adaptive changes, including upregulation of metabolic enzymes and subtle markers of oxidative stress. In contrast, the kidneys displayed a broader spectrum of proteomic alterations, affecting a wider array of functional pathways, suggesting that this organ may be more susceptible to morphine-induced toxicity or that of its metabolites. We employed also MALDI-MSI to examine lipidomic alterations: while no significant changes were detected in liver tissue, important lipidomic alterations were observed in the kidneys, further supporting their increased vulnerability to morphine exposure. Our results should be regarded as preliminary; however, they highlight a promising direction for identifying early stage protein markers of toxicity using proteomic approaches. Monitoring such markers could prove valuable in multidrug therapies, particularly for patients with a history of hepatic or renal impairment, contributing to the development of safer therapeutic strategies. Data are available via ProteomeXchange under the identifiers: PXD067999 (DDA) and PXD068084 (DIA).", "claims": [{"id": "claim-method", "statement": "Differential expression was assessed using a two-sample Student’s t-test with a permutation-based false discovery rate (FDR) control (250 permutations) implemented in Perseus (v.2.1.0). PLS regression was performed to determine the optimal number of latent variables (LVs) of the PLS model.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41579115", "locator": "sections[6] \"DIA Analysis\" paragraph 3", "quote": "Differential expression was assessed using a two-sample Student’s t-test with a permutation-based false discovery rate (FDR) control (250 permutations) implemented in Perseus (v.2.1.0)."}, {"asset": "source:pmid:41579115", "locator": "sections[8] \"Partial Least Square (PLS) Analysis\" paragraph 3", "quote": "PLS regression was performed to determine the optimal number of latent variables (LVs) of the PLS model."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifiers: for DDA experiments PXD067999 and 10.6019/PXD067999, for DIA experiments PXD068084.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41579115", "locator": "sections[17] \"(untitled)\" paragraph 1", "quote": "The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the data set identifiers: for DDA experiments PXD067999 and 10.6019/PXD067999, for DIA experiments PXD068084."}], "state": "complete"}, {"id": "claim-target-result", "statement": "After 10 days of morphine exposure, differential-expression analysis identified 205 significantly deregulated liver proteins and 381 significantly deregulated kidney proteins.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41579115", "locator": "sections[9] \"Results\" paragraph 2", "quote": "Applying a threshold of FDR < 0.05 and S0 < 0.1, 205 proteins (approximately 5% of those selected for quantification) were found to be significantly deregulated in the liver."}, {"asset": "source:pmid:41579115", "locator": "sections[9] \"Results\" paragraph 2", "quote": "To increase specificity, more stringent criteria were applied (FDR < 0.01, S0 < 0.1), resulting in 381 significantly deregulated proteins, of which 196 (52%) downregulated and 185 (48%) upregulated."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "After 10 days of morphine exposure, differential-expression analysis identified 205 significantly deregulated liver proteins and 381 significantly deregulated kidney proteins.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:41579115"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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