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Elucidating Biological Links in Autism Spectrum Disorder: From Blood-Based Risk Factor Identification to a Validated

Lin Lin1,2,3, Xixi Wang2, Peng Wang1

  • 1Women and Children's Hospital of Dalian University of Technology, Dalian, Liaoning Province, People's Republic of China.

Neuropsychiatric Disease and Treatment
|April 2, 2026
PubMed
Summary
This summary is machine-generated.

This study identified four key blood biomarkers—calcium, serum iron, vitamin D, and platelet distribution width—as significant risk factors for Autism Spectrum Disorder (ASD). A predictive model using these markers shows promise for early ASD screening.

Keywords:
ASDPSMRCSautism spectrum disorderclinical risk factorsdose-response relationshipnomogram prediction modelpropensity score matchingrestricted cubic spline

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Area of Science:

  • Biochemistry
  • Pediatrics
  • Genetics

Background:

  • Autism Spectrum Disorder (ASD) diagnosis relies on behavioral observation, highlighting the need for objective biomarkers.
  • Blood-based markers offer a non-invasive approach to identify individuals at risk for ASD.

Purpose of the Study:

  • To identify key blood-based risk factors for Autism Spectrum Disorder (ASD).
  • To develop and validate a clinical prediction model for ASD risk using identified biomarkers.

Main Methods:

  • Retrospective analysis of 879 children (ASD patients and controls).
  • Propensity score matching for age and sex balancing.
  • Multivariate logistic regression to identify risk factors from blood parameters, vitamins, and trace elements.
  • Construction and internal validation of a nomogram for ASD risk prediction.

Main Results:

  • Four independent risk factors for ASD identified: calcium, serum iron, vitamin D, and platelet distribution width (PDW).
  • Lower serum iron and vitamin D, higher PDW associated with increased ASD risk.
  • Calcium showed a non-linear association, peaking at 1.13 mmol/L.
  • Nomogram achieved high sensitivity (84.6%) and specificity (73.4%) in training, and (78.6%) and (79.0%) in validation sets.

Conclusions:

  • Calcium, iron, vitamin D, and PDW are feasible blood-based risk factors for ASD.
  • The developed nomogram model demonstrates strong predictive performance and clinical utility for early ASD screening.
  • This model shows significant potential for clinical translation in ASD risk assessment.