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Comparative study on serum levels of macro and trace elements in schizophrenia based on supervised learning methods.

Tong Lin1, Tiebing Liu2, Yucheng Lin1

  • 1The Key Laboratory of Machine Perception (Ministry of Education), School of EECS, Peking University, Beijing 100871, China.

Journal of Trace Elements in Medicine and Biology : Organ of the Society for Minerals and Trace Elements (GMS)
|April 8, 2017
PubMed
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Serum levels of macro and trace elements (MTE) show significant differences in individuals with schizophrenia (SCZ). These findings may aid in SCZ diagnosis and treatment, highlighting MTE

Area of Science:

  • Biochemistry
  • Psychiatry
  • Analytical Chemistry

Background:

  • The underlying causes and biological mechanisms of schizophrenia (SCZ) are not fully understood.
  • Investigating biochemical markers may offer new insights into SCZ pathophysiology.

Purpose of the Study:

  • To explore the relationship between serum concentrations of 39 macro and trace elements (MTE) and the risk of schizophrenia.
  • To identify potential biomarkers for SCZ diagnosis and prognosis.

Main Methods:

  • A case-control study involving 114 SCZ patients and 114 matched healthy controls.
  • Serum MTE levels were quantified using Inductively Coupled Plasma Atomic Emission Spectrometry (ICP-AES) and Mass Spectrometry (ICP-MS).
  • Supervised machine learning (Support Vector Machines, Naive Bayes) and statistical tests were employed to analyze MTE differences.
Keywords:
Macro elementsSchizophreniaSupervised learning methodsTrace elements

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Main Results:

  • Significant differences in serum MTE concentrations were observed between SCZ patients and controls.
  • Machine learning models achieved high prediction accuracies (up to 99.21%) for distinguishing between cases and controls based on MTE levels.
  • Over half of the analyzed MTE showed statistically significant variations between the two groups.

Conclusions:

  • Serum MTE levels exhibit notable differences in individuals with schizophrenia compared to healthy individuals.
  • These findings suggest potential applications for MTE analysis in SCZ diagnosis, prognosis, pharmacy, and nutrition.
  • Further research with larger sample sizes and control for confounding factors is recommended for robust interpretation.