Proteomic analysis of Parkinson’s disease patient cohorts show similarities in mechanism to Alzheimer’s disease
Bibliographic record
Abstract
Abstract Background Alzheimer’s Disease and Parkinson’s Disease (PD) share similarities in phenotype and an overlap between disease subtypes and diagnostic testing which implies a link between some of the neurodegenerative processes. Here, we report the initial results for proteomic assays on two longitudinal PD cohorts demonstrating dementia‐like protein dysregulation signatures as well as PD specific signatures in the largest proteomics collection of PD patients to date. Method We used aptamer‐based technology (SOMAmer assay, SomaLogic®) to measure 4003 proteins in 1599 serum samples collected from two observational longitudinal cohorts: Oxford Parkinson’s Disease Centre Discovery cohort (OPDC) and the UK Tracking Parkinson’s cohort. Clinical measures of disease progression included the Movement Disorders Society Unified Parkinson’s Disease Rating Scale part III (UPDRS) and Montreal Cognitive Assessment (MoCA) adjusted for education years. The sample set included 319 controls. We performed dysregulation analysis on log2 transformed data using linear models corrected for age, gender, and cohort. Enrichment analysis was implemented in the R library clusterProfiler using the KEGG and GO databases. Comprehensive co‐expression analysis was performed using WGCNA. Result Initial pathway analysis showed that the main significantly dysregulated protein pathways of case status were the Complement and coagulation cascades (p = 0.0086) and Protein digestion and absorption (p =0.0152). The Fat digestion and protein absorption pathway was enriched for dysregulated proteins associated to the UPDRS measure (p = 0.00142). Using co‐expression analysis we identified a module of 625 proteins with a significant relationship to disease status (p = 3.20x10‐07) and the movement (p = 2.35 x10‐05) and cognition (p = 0.005) endophenotypes. This module was enriched for proteins involved in axon guidance in addition to the complement and coagulation cascades and protein digestion and absorption found in initial analyses. Conclusion Using a comprehensive profiling analysis of protein expression in two unique longitudinal PD cohorts we demonstrate the overlap between neurodegenerative disease types as well as highlight unique PD associations with potential mechanistic links to gut processes. This will have implications for further analysis of these PD cohorts for further mechanistic analysis and more importantly biomarker detection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".