ArticleBMC psychiatry2025
Associations between amino acid levels and autism spectrum disorder severity.
Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Therapeutic potential of low-frequency transcranial magnetic stimulation in children with autism spectrum disorder: sensory and behavioral outcomes-a randomized trial.Frontiers in psychiatry · 2026Trial
- Article
- Microbiota-gut-brain axis and neuroendocrine pathways underlie divergent mechanisms of intermittent and continuous theta-burst stimulation in autism spectrum disorder.Cellular and molecular life sciences : CMLS · 2026Article
- Association and predictive value of blood branched-chain and excitatory amino acids with autism spectrum disorder severity.BMC pediatrics · 2026Article
- Amino acid profiles and clinical phenotypes in young children with autism spectrum disorder.Frontiers in neuroscience · 2026Article
- Sleep Disorders in Children with Autism Spectrum Disorder: Developmental Impact and Intervention Strategies.Brain sciences · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
backgroundAutism spectrum disorder (ASD) imposes a significant burden on both patients and society. Amino acid metabolism abnormalities are particularly relevant to ASD pathology due to their crucial role in neurotransmitter synthesis, synaptic function, and overall neurodevelopment. This study aims to explore the association between amino acid metabolic abnormalities and the severity of ASD by analyzing the amino acid concentrations in the blood of children with ASD.
methodsFasting peripheral blood samples were collected from 344 children with ASD, and amino acid concentrations were measured using liquid chromatography-tandem mass spectrometry (LC-MS/MS) while strictly following quality control measures. The association between amino acid concentrations and ASD severity was evaluated using logistic regression and restricted cubic spline (RCS) analysis. The ROC (receiver operating characteristic) curve, decision curve analysis (DCA), and calibration curve were used to construct and validate predictive models and nomograms, thereby assessing their predictive performance.
resultsMultivariate logistic regression analysis showed that aspartic acid (OR = 1.037, 95% CI: 1.009-1.068, P = 0.01), glutamic acid (OR = 1.009, 95% CI: 1.001-1.017, P = 0.03), phenylalanine (OR = 1.036, 95% CI: 1.003-1.072, P = 0.04), and leucine/isoleucine (OR = 1.021, 95% CI: 1.006-1.039, P = 0.01) were significantly positively correlated with the severity of ASD. On the other hand, tryptophan (OR = 0.935, 95% CI: 0.903-0.965, P < 0.01) and valine (OR = 0.987, 95% CI: 0.977-0.997, P = 0.01) were significantly negatively correlated with the severity of ASD. RCS analysis further revealed a nonlinear relationship between the concentrations of aspartic acid, proline, and glutamic acid and the risk of ASD. ROC curve analysis showed that the combined model achieved an AUC (area under the curve) of 0.806, indicating high diagnostic accuracy. Calibration and decision curve analysis further validated the predictive effectiveness and clinical utility of the model.
conclusionsThis study identifies potential amino acid biomarkers that may contribute to ASD severity assessment. Further research is needed to validate these findings and explore their clinical utility.
Indexed as
Identifiers
What Socratic 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 Socratic graph.