ArticleiScience2025
Mitochondrial methylcytosines as blood-based biomarkers for Alzheimer's disease dementia prognosis.
Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
20 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Alzheimer's Disease Dementia (ADD) prognosis is an unmet medical need. Mitochondrial dysfunction is an early AD etiopathogenic factor. The present study analyzed mitochondrial DNA (mtDNA) methylation patterns in blood samples from patients with mild cognitive impairment (MCI) who progressed to ADD (P), MCI remained stable (NP), and Cognitively Normal (CN) individuals. Differentially methylated sites were identified in the D-loop region in both CN vs. NP and NP vs. P comparisons, even before β-amyloid positivity. A Random Forest model was developed using mtDNA methylation data combined with cognitive and risk factor features. Model's performance was assessed by cross-validation and tested on an independent set, achieving 84.4% accuracy in training and 83.2% (95% CI: 75.2%-89.4%) in testing. For identifying P patients, sensitivity and specificity were 95.1% and 70.7%, respectively. The AUC-ROC was 90.3%. The developed model demonstrates predictive capacity in distinguishing cognitive decline and stability in MCI individuals, independently of their β-amyloid status.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.