ArticleFrontiers in aging neuroscience2026
Artificial intelligence and multi-omics nominate TAZ as an insomnia-related diagnostic and druggable target for Parkinson's disease patients.
Article in Frontiers in aging neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed.
- Multi-Omics Integration Reveals the Genetic Mechanisms of Periodontitis and Predicts Therapeutic Drugs.International dental journal · 2026Article
- Assessment of tenecteplase target-associated pathogenic mechanisms underlying depression in acute ischemic stroke patients: insights from artificial intelligence-driven multi-omics analysis andFrontiers in neuroscience · 2026Article
- CENPM as a biomarker and therapeutic target for lymph node metastasis in thyroid carcinoma.Frontiers in genetics · 2026Article
- Identification and validation of mitophagy and astrocyte-related molecular signature in the pathogenesis of Alzheimer's disease: evidence from ensemble learning-driven multi-omics and clinical validation.Frontiers in neuroscience · 2026Article
- Decoding serum C-reactive protein-associated molecular patterns in aging and secondhand smoke exposure chronic obstructive pulmonary disease male patients: evidence from cross-sectional, multi-omic and clinical studies.Frontiers in medicine · 2026Article
- Implications of pentose phosphate metabolism and astrocyte co-expression patterns in the pathogenesis of Alzheimer's disease: evidence from artificial intelligence-driven omics and clinical validation.Frontiers in neuroscience · 2026Article
- Tracing fucosylation and astrocyte-associated pathogenic pattern in major depressive disorder: evidence from machine learning-based multi-omics and clinical validation.Frontiers in neuroscience · 2026Article
- Decoding astrocytic tryptophan metabolism in the pathogenesis of epilepsy: evidence from artificial intelligence-driven multi-omics and clinical validation.Frontiers in neuroscience · 2026Article
- A neuron-distributed DEK integrates ac4C modification and neuroinflammation in pathogenesis of Parkinson disease: evidence from Mendelian randomization, multi-omics andFrontiers in neuroscience · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Insomnia is one of the most common non-motor comorbidities of Parkinson's disease (PD) and often before the onset of motor symptoms. Identifying the molecular mechanisms of insomnia may facilitate the early diagnosis of PD and contribute to therapeutic development. Methods: Five human PD substantia nigra (SN) bulk-seq datasets (GSE20141, GSE7621, GSE20164, GSE20163, and GSE20333), with an insomnia-related gene list, were acquired from GEO and Genecard databases. First, the integration of GSE20141 and GSE7621 was analyzed to identify insomnia-related DEGs using limma and the WGCNA framework. GSE20164 and GSE20163 combination were used as a training set for insomnia-related hub gene recognition. Furthermore, the aforementioned four datasets, along with an independent validation set (GSE20333), were cross-validated for insomnia-related diagnostic model construction. The human PD-SN single-cell profile (GSE140231) was utilized for exploring the mechanisms underlying the heterogeneity of insomnia-related hub genes in spatial and temporal contexts. Furthermore, a cutting-edge artificial intelligence (AI)-driven framework (DrugRefLector) and molecular docking techniques was used to identify an optimal agent for the treatment of PD based on the GSE20164 and GSE20163 integrated dataset. Finally, an Results: TAZ (WWTR1) is associated with the increased expression of insomnia-related diagnostic markers linked to PD pathogenesis, mainly in neurons, and has excellent predictive performance for PD diagnosis. Furthermore, BRD-K97481123 can be considered as a potential therapeutic agent for the treatment of PD by targeting TAZ. Conclusion: By integrating AI pipelines and multi-omics, our study first traced TAZ mechanisms in PD pathogenesis and elaborated on TAZ's predictive and druggable potential for PD patients.
Indexed as
Identifiers
What OpenQuestion holds
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 OpenQuestion graph.