The role of fatty acids in attention deficit hyperactivity disorder

Koç, Sümeyye; Gültekin, Fatih; Güler, Eray Metin

doi:10.30565/medalanya.1059552

Cited by 1 publication

(1 citation statement)

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“…Although PDZD2 is mostly implicated in pancreatic development, it is important to highlight that diabetes is an established risk factor of AD and further study on PDZD2 could uncover correlations with Alzheimer’s disease. NEURL1, Neuralized1, which is an E3 ubiquitin ligase 48 has been associated with learning and memory difficulties when it is downregulated 49 . SYNPR has been identified as the top marker genes for inhibitory neurons 50 .…”

Section: Resultsmentioning

confidence: 99%

Predicting early Alzheimer’s with blood biomarkers and clinical features

AlMansoori,

Jemimah,

Abuhantash

et al. 2024

Sci Rep

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Alzheimer’s disease (AD) is an incurable neurodegenerative disorder that leads to dementia. This study employs explainable machine learning models to detect dementia cases using blood gene expression, single nucleotide polymorphisms (SNPs), and clinical data from Alzheimer’s Disease Neuroimaging Initiative (ADNI). Analyzing 623 ADNI participants, we found that the Support Vector Machine classifier with Mutual Information (MI) feature selection, trained on all three data modalities, achieved exceptional performance (accuracy = 0.95, AUC = 0.94). When using gene expression and SNP data separately, we achieved very good performance (AUC = 0.65, AUC = 0.63, respectively). Using SHapley Additive exPlanations (SHAP), we identified significant features, potentially serving as AD biomarkers. Notably, genetic-based biomarkers linked to axon myelination and synaptic vesicle membrane formation could aid early AD detection. In summary, this genetic-based biomarker approach, integrating machine learning and SHAP, shows promise for precise AD diagnosis, biomarker discovery, and offers novel insights for understanding and treating the disease. This approach addresses the challenges of accurate AD diagnosis, which is crucial given the complexities associated with the disease and the need for non-invasive diagnostic methods.

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Section: Resultsmentioning

confidence: 99%