Systematic Review of Proteomics in Age-Related Macular Degeneration and Pathway Analysis of Significant Protein Changes
Bibliographic record
Abstract
Topic: Proteomics in age-related macular degeneration (AMD) research. Clinical Relevance: AMD is the leading cause of blindness in industrialized countries, with a poorly understood pathogenesis. Proteomics can identify significantly altered proteins in AMD patients, aiding in understanding the disease's pathophysiology and potentially improving diagnosis or treatment strategies. Methods: A systematic review of proteomic studies in AMD was conducted. Proteins significantly altered in dry and wet AMD and those tested as biomarkers were presented according to sample type (aqueous humor, plasma, urine, vitreous, retinal pigment epithelium/choroid, and tear film) and type of assay (mass spectrometry or aptamers) used in the individual studies. Proteins that exhibited at least a 2× fold change (FC) were further analyzed through functional enrichment analysis and protein-protein interaction networks (STRING database). Results: Twenty-two studies (case-control and cohorts) with a total of 6932 participants were included. The included studies showed significant heterogeneity, and most of them lacked sufficient power. Results suggested that various proteins and pathways are implicated in AMD, and there were differences when comparing results from the individual studies and unbiased results. Although many proteins differed significantly between AMD and control groups, most exhibited less than a 2-FC. Functional analysis of proteins with ≥|2|-FCs (identified by unbiased proteomics in multiple biofluids) highlighted lipid metabolism and protease regulation pathways as central to both dry and wet AMD. Complement and coagulation cascades, chaperones, and glycolysis pathways were significant in wet AMD, whereas matrix remodeling pathways were enriched mostly in dry AMD. Conclusion: Combining proteomics from various studies could reveal new protein-protein interaction networks and associated functional pathways that may suggest novel potential therapeutic targets for AMD. However, there is a scarcity of data available for early AMD from ocular biofluids, and it should be the aim of future proteomics studies. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.021 | 0.021 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".