Alterations in Blood Methylome as Potential Epigenetic Biomarker in Sporadic Parkinson's Disease
Bibliographic record
Abstract
OBJECTIVE: To characterize DNA methylation (DNAm) differences between sporadic Parkinson's disease (PD) and healthy control (HC) individuals enrolled in the Parkinson's Progression Markers Initiative (PPMI). METHODS: Using whole blood, we characterized longitudinal differences in DNAm between sporadic PD patients (n = 196) and HCs (n = 86) enrolled in PPMI. RNA sequencing (RNAseq) was used to conduct gene expression analyses for genes mapped to differentially methylated cytosine-guanine sites (CpGs). RESULTS: At the time of patient enrollment, 5,178 CpGs were differentially methylated (2,683 hypermethylated and 2,495 hypomethylated) in PD compared to HC. Of these, 579 CpGs underwent significant methylation changes over 3 years. Several differentially methylated CpGs were found near the cytochrome P450 family 2 subfamily E member 1 (CYP2E1) gene. Additionally, multiple hypermethylated CpGs were associated with the N-myc downregulated gene family member 4 (NDRG4) gene. RNA-Seq analyses showed 75 differentially expressed genes in PD patients compared to controls. An integrative analysis of both differentially methylated sites and differentially expressed genes revealed 20 genes that exhibited hypomethylation concomitant with overexpression. Additionally, 1 gene, cathepsin H (CTSH), displayed hypermethylation that was associated with its decreased expression. INTERPRETATION: We provide initial evidence of alterations in DNAm in blood of PD patients that may serve as potential epigenetic biomarker of disease. To evaluate the significance of these changes throughout the progression of PD, additional profiling at longer intervals and during the prodromal stages of disease will be necessary. ANN NEUROL 2024;95:1162-1172.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".