Unbiased Proteomic Approach Identifies Unique and Coincidental Plasma Biomarkers in Repetitive mTBI and AD Pathogenesis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:30618712", "kind": "science-record", "revision": 8, "content_hash": "sha256:1cdfd3bd7d9c4324e8402da81a7e570d1c0638dea53acd5cbbc5112594fb4663", "created_at": "2026-11-01T15:40:40Z", "updated_at": "2026-11-01T22:43:42Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Unbiased Proteomic Approach Identifies Unique and Coincidental Plasma Biomarkers in Repetitive mTBI and AD Pathogenesis.", "doi": "10.3389/fnagi.2018.00405", "pmid": "30618712", "authors": ["Joseph O Ojo", "Gogce Crynen", "Jon M Reed", "Rosa Ajoy", "Prashanthi Vallabhaneni", "Moustafa Algamal", "Paige Leary", "Naomi G Rafi", "Benoit Mouzon", "Michael Mullan", "Fiona Crawford"], "journal": "Frontiers in aging neuroscience", "year": 2018, "abstract": "The relationship between repetitive mild traumatic brain injury (r-mTBI) and Alzheimer's disease (AD) is well-recognized. However, the precise nature of how r-mTBI leads to or precipitates AD pathogenesis is currently not understood. Plasma biomarkers potentially provide non-invasive tools for detecting neurological changes in the brain, and can reveal overlaps between long-term consequences of r-mTBI and AD. In this study we address this by generating time-dependent molecular profiles of response to r-mTBI and AD pathogenesis in mouse models using unbiased proteomic analyses. To model AD, we used the well-validated hTau and PSAPP(APP/PS1) mouse models that develop age-related tau and amyloid pathological features, respectively, and our well-established model of r-mTBI in C57BL/6 mice. Plasma were collected at different ages (3, 9, and 15 months-old for hTau and PSAPP mice), encompassing pre-, peri- and post-\"onset\" of the cognitive and neuropathological phenotypes, or at different timepoints after r-mTBI (24 h, 3, 6, 9, and 12 months post-injury). Liquid chromatography/mass spectrometry (LC-MS) approaches coupled with Tandem Mass Tag labeling technology were applied to develop molecular profiles of protein species that were significantly differentially expressed as a consequence of mTBI or AD. Mixed model ANOVA after Benjamini-Hochberg correction, and a stringent cut-off identified 31 proteins significantly changing in r-mTBI groups over time and, when compared with changes over time in sham mice, 13 of these were unique to the injured mice. The canonical pathways predicted to be modulated by these changes were LXR/RXR activation, production of nitric oxide and reactive oxygen species and complement systems. We identified 18 proteins significantly changing in PSAPP mice and 19 proteins in hTau mice compared to their wild-type littermates with aging. Six proteins were found to be significantly regulated in all three models, i.e., r-mTBI, hTau, and PSAPP mice compared to their controls. The top canonical pathways coincidently changing in all three models were LXR/RXR activation, and production of nitric oxide and reactive oxygen species. This work suggests potential biomarkers for TBI and AD pathogenesis and for the overlap between these two, and warrant targeted investigation in human populations. Data are available via ProteomeXchange with identifier PXD010664.", "claims": [{"id": "claim-method", "statement": "After the median per peptide sequence from multiple fractions were calculated, mixed model ANOVA was used to test for significant proteins changing overtime within each group.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30618712", "locator": "sections[10] \"Data Processing and Statistical Analysis of Proteomics Data\" paragraph 2", "quote": "After the median per peptide sequence from multiple fractions were calculated, mixed model ANOVA was used to test for significant proteins changing overtime within each group."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Data are available via ProteomeXchange with identifier PXD010664.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:30618712", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Data are available via ProteomeXchange with identifier PXD010664."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:30618712"], "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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To model AD, we used the well-vali", "24 h, 3, 6, 9, and 12 months post-injury for proteomic analyses (A). The tauopathy group consisted", "Data Processing and Statistical Analysis of Proteomics Data PMi Preview software was used to survey"], "order_basis": "paper_text_order:0", "id": "assay:1"}, {"role": "data_generation", "definition_id": "animal_model", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["of response to r-mTBI and AD pathogenesis in mouse models using unbiased proteomic analyses. To", "d the well-validated hTau and PSAPP(APP/PS1) mouse models that develop age-related tau and amyl", "e expressing human tau on a C57BL/6 and null murine tau background (generated as previously desc", "and AD mouse models. Six different groups of mice were used in this study. The mTBI group consisted"], "order_basis": "paper_text_order:612", "id": "assay:2"}, {"role": "data_generation", "definition_id": "elisa", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["tor I expression levels using antibody based ELISA approach in repetitive mTBI mice at multiple", "njury. (A) Represents ratio of BCA corrected ELISA concentration values normalized to 24 h post", "a LRG expression levels using antibody based ELISA approach in repetitive mTBI mice at multiple", "bulin expression levels using antibody based ELISA approach in sham and repetitive mTBI mice at"], "order_basis": "paper_text_order:12317", "id": "assay:3"}, {"role": "analysis", "definition_id": "group_comparison", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["group_summary", "welch_t", "bootstrap_mean_difference", "group_comparison_anova"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["After the median per peptide sequence from multiple fractions were calculated, mixed model ANOVA was used to test for significant proteins changing overtime within each group."], "order_basis": "consumes_earlier_output", "id": "assay:4"}]}