Modifiable Nutritional Biomarkers in Autism Spectrum Disorder: A Systematic Review and Meta-Analysis of Vitamin D, B12, and Homocysteine Exposure Spanning Prenatal Development Through Late Adolescence
Bibliographic record
Abstract
Autism Spectrum Disorder (ASD) has been associated with disruptions in one-carbon metabolism and vitamin D pathways. Nutritional exposures—particularly vitamin D, vitamin B12, and homocysteine—may influence neurodevelopmental outcomes. However, a comprehensive, lifespan-spanning synthesis of these modifiable nutritional biomarkers has not been conducted. This systematic review and stratified meta-analysis critically synthesized data on vitamin D, vitamin B12, and homocysteine to elucidate their relationships with ASD risk and symptomatology. Our central question was: How do levels of vitamin D, vitamin B12, and homocysteine—measured before and after birth—affect the risk, severity, and potential treatment outcomes for ASD? We conducted a PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) compliant systematic review and stratified meta-analysis (2015–2025) of 35 studies (11 randomized controlled trials, 24 observational), examining prenatal, neonatal, and postnatal biomarker levels. Eligibility criteria were defined using the PICOS (Population, Intervention, Comparator, Outcome, and Study Design) framework to ensure scientific rigor and clinical relevance, including studies involving human participants aged 0–18 years with a formal Autism Spectrum Disorder (ASD) diagnosis or prenatal exposures potentially linked to later ASD onset, while excluding animal studies, adult-only ASD populations, and studies lacking ASD cohorts or biomarker data. The search strategy, developed according to PRISMA, and Cochrane best practices, encompassed five major databases (PubMed/MEDLINE, Cochrane Library, Google Scholar, ClinicalTrials.gov, and ProQuest) alongside manual searches of key references, grey literature, and clinical trial registries to ensure comprehensive retrieval of both published and unpublished studies. Study quality was assessed using version 2 of the Cochrane risk-of-bias tool for RCTs (RoB2) and the Newcastle–Ottawa Scale (NOS) for observational studies; certainty of evidence was graded via GRADE (Grading of Recommendations Assessment, Development and Evaluation). Random-effects meta-analyses were stratified by biomarker and study design. Heterogeneity, small-study effects, and publication bias were evaluated using Cochran’s Q, I2, Egger’s test, and trim-and-fill. Prenatal vitamin D deficiency was associated with approximately two-fold increased odds of Autism Spectrum Disorder (ASD) in offspring (pooled OR ≈ 2.0; p < 0.05), while excessively elevated maternal B12 concentrations, often co-occurring with folate excess, were similarly linked to increased ASD risk. Meta-analytic comparisons revealed significantly lower circulating vitamin D (SMD ≈ −1.0; p < 0.001) and B12 levels (SMD ≈ −0.7; p < 0.001), alongside elevated homocysteine (SMD ≈ 0.7; p < 0.001), in children with ASD versus neurotypical controls. Early-life vitamin D/B12 insufficiency and elevated homocysteine are important, modifiable correlates of ASD risk and severity. Adequate maternal and child nutritional status could have risk-reducing and symptom-mitigating effects, although causality remains to be confirmed. This evidence supports tailored nutritional interventions as a component of ASD risk reduction and management strategies, within the bounds of overall developmental healthcare. The article processing charges (APC) were supported by “Dunărea de Jos” University of Galati, Romania. No external funding was received for the execution of the research. The review was not prospectively registered in PROSPERO or any other systematic review registry.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".