ArticleJournal of molecular neuroscience : MN2018
The Use of Multi-parametric Biomarker Profiles May Increase the Accuracy of ASD Prediction.
Article in Journal of molecular neuroscience : MN, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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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.
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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
12 citing papers in PubMed, 19 citations in OpenAlex.
- Combining Anti-Mitochondrial Antibodies, Anti-Histone, and PLA2/COX Biomarkers to Increase Their Diagnostic Accuracy for Autism Spectrum Disorders.Brain sciences · 2024Article
- The Rationale for Vitamin, Mineral, and Cofactor Treatment in the Precision Medical Care of Autism Spectrum Disorder.Journal of personalized medicine · 2023Review
- Discriminant analysis and binary logistic regression enable more accurate prediction of autism spectrum disorder than principal component analysis.Scientific reports · 2022Article
- Review
- Paving the Way toward Personalized Medicine: Current Advances and Challenges in Multi-OMICS Approach in Autism Spectrum Disorder for Biomarkers Discovery and Patient Stratification.Journal of personalized medicine · 2021Review
- Machine Learning Within Studies of Early-Life Environmental Exposures and Child Health: Review of the Current Literature and Discussion of Next Steps.Current environmental health reports · 2020Review
- Oxidative Stress in Autism Spectrum Disorder.Molecular neurobiology · 2020Review
- Preliminary evaluation of a novel nine-biomarker profile for the prediction of autism spectrum disorder.PloS one · 2020Article
- Iron Deficiency, Cognitive Functions, and Neurobehavioral Disorders in Children.Journal of molecular neuroscience : MN · 2019Review
- Generalizability and reproducibility of functional connectivity in autism.Molecular autism · 2019Article
- Diagnostic and Severity-Tracking Biomarkers for Autism Spectrum Disorder.Journal of molecular neuroscience : MN · 2018Review
- Reducing toxic stress in the neonatal intensive care unit to improve infant outcomes.Nursing outlookArticle
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 5 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Effective biomarkers are urgently needed to facilitate early diagnosis of autism spectrum disorder (ASD), permitting early intervention, and consequently improving prognosis. In this study, we evaluate the usefulness of nine biomarkers and their association (combination) in predicting ASD onset and development. Data were analyzed using multiple independent mathematical and statistical approaches to verify the suitability of obtained results as predictive parameters. All biomarkers tested appeared useful in predicting ASD, particularly vitamin E, glutathione-S-transferase, and dopamine. Combining biomarkers into profiles improved the accuracy of ASD prediction but still failed to distinguish between participants with severe versus mild or moderate ASD. Library-based identification was effective in predicting the occurrence of disease. Due to the small sample size and wide participant age variation in this study, we conclude that the use of multi-parametric biomarker profiles directly related to autism phenotype may help predict the disease occurrence more accurately, but studies using larger, more age-homogeneous populations are needed to corroborate our findings.
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Registered trials
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