ArticlePloS one2016
Identification of Biomarkers of Impaired Sensory Profiles among Autistic Patients.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 4 of them syntheses that pooled it.
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
20 citing papers in PubMed, 4 syntheses or guidelines pooled it, 42 citations in OpenAlex.
- Inflammatory cytokine alterations in autism spectrum disorder and attention-deficit/hyperactivity disorder: a systematic review and network meta-analysis.European child & adolescent psychiatry · 2026Pooled it
- Association of Peripheral Blood Levels of Cytokines With Autism Spectrum Disorder: A Meta-Analysis.Frontiers in psychiatry · 2021Pooled it
- Classifying oxidative stress by FRedox biology · 2017Pooled it
- Pooled it
- The cognitive effects of supplementation with sunflower phosphatidyl serine in healthy children aged 8 to 12 years: a randomized controlled trial.Nutrition journal · 2025Trial
- Impact of Auditory Integrative Training on Transforming Growth Factor-β1 and Its Effect on Behavioral and Social Emotions in Children with Autism Spectrum Disorder.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2018Trial
- Association of Clinical Severity in Autism Spectrum Disorder with Biomolecules Involved in Lipid Metabolism, Inflammation and miRNAs.Biomolecules · 2026Article
- The endocannabinoidome-gut microbiome-brain axis as a novel therapeutic target for autism spectrum disorder.Journal of biomedical science · 2025Review
- Assessing the COX-2/PGE2 Ratio and Anti-Nucleosome Autoantibodies as Biomarkers of Autism Spectrum Disorders: Using Combined ROC Curves to Improve Diagnostic Values.Current issues in molecular biology · 2024Article
- Low Plasma Levels of Contactin-Associated Protein-Like 2 in Children with Autism Spectrum Disorder: Links to Neural Development.Neuropsychiatric disease and treatment · 2024Article
- Discriminant analysis and binary logistic regression enable more accurate prediction of autism spectrum disorder than principal component analysis.Scientific reports · 2022Article
- Phosphatidylserine, inflammation, and central nervous system diseases.Frontiers in aging neuroscience · 2022Review
- Cytokines profile in neonatal and adult wild-type mice post-injection of U. S. pediatric vaccination schedule.Brain, behavior, & immunity - health · 2021Article
- Preliminary evaluation of a novel nine-biomarker profile for the prediction of autism spectrum disorder.PloS one · 2020Article
- Impact of Auditory Integration Therapy (AIT) on the Plasma Levels of Human Glial Cell Line-Derived Neurotrophic Factor (GDNF) in Autism Spectrum Disorder.Journal of molecular neuroscience : MN · 2019Article
- Possible Metabolic Alterations among Autistic Male Children: Clinical and Biochemical Approaches.Journal of molecular neuroscience : MN · 2019Article
- The Use of Multi-parametric Biomarker Profiles May Increase the Accuracy of ASD Prediction.Journal of molecular neuroscience : MN · 2018Article
- Immune Abnormalities in Autism Spectrum Disorder-Could They Hold Promise for Causative Treatment?Molecular neurobiology · 2018Review
- Impaired lipid metabolism markers to assess the risk of neuroinflammation in autism spectrum disorder.Metabolic brain disease · 2018Article
- In the search for reliable biomarkers for the early diagnosis of autism spectrum disorder: the role of vitamin D.Metabolic brain disease · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAutism is a neurodevelopmental disorder that displays significant heterogeneity. Comparison of subgroups within autism, and analyses of selected biomarkers as measure of the variation of the severity of autistic features such as cognitive dysfunction, social interaction impairment, and sensory abnormalities might help in understanding the pathophysiology of autism. METHODS AND
participantsIn this study, two sets of biomarkers were selected. The first included 7, while the second included 6 biomarkers. For set 1, data were collected from 35 autistic and 38 healthy control participants, while for set 2, data were collected from 29 out of the same 35 autistic and 16 additional healthy subjects. These markers were subjected to a principal components analysis using either covariance or correlation matrices. Moreover, libraries composed of participants categorized into units were constructed. The biomarkers used include, PE (phosphatidyl ethanolamine), PS (phosphatidyl serine), PC (phosphatidyl choline), MAP2K1 (Dual specificity mitogen-activated protein kinase kinase 1), IL-10 (interleukin-10), IL-12, NFκB (nuclear factor-κappa B); PGE2 (prostaglandin E2), PGE2-EP2, mPGES-1 (microsomal prostaglandin synthase E-1), cPLA2 (cytosolic phospholipase A2), 8-isoprostane, and COX-2 (cyclo-oxygenase-2).
resultsWhile none of the studied markers correlated with CARS and SRS as measure of cognitive and social impairments, six markers significantly correlated with sensory profiles of autistic patients. Multiple regression analysis identifies a combination of PGES, mPGES-1, and PE as best predictors of the degree of sensory profile impairment. Library identification resulted in 100% correct assignments of both autistic and control participants based on either set 1 or 2 biomarkers together with a satisfactory rate of assignments in case of sensory profile impairment using different sets of biomarkers.
conclusionThe two selected sets of biomarkers were effective to separate autistic from healthy control subjects, demonstarting the possibility to accurately predict the severity of autism using the selected biomarkers. The effectiveness of the identified libraries lied in the fact that they were helpful in correctly assigning the study population as control or autistic patients and in classifying autistic patients with different degree of sensory profile impairment.
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.