Metallomics-based platforms for comparing the human blood serum profiles between bipolar disorder and schizophrenia patients

Abstract

Rationale An evaluation of bipolar disorder (BD) and schizophrenia (SCZ) was carried out, from a metallomics point of view, using native conditions, attempting to preserve the interaction between metals and biomolecules. Method For this task, blood serum samples from healthy individuals and patients were compared. In addition, the profiles of metal ions and metalloids involved in the pathologies were quantified, and a comparison was carried out of the protein profile in serum samples of healthy individuals and diseased patients. Results After optimization and accuracy evaluation of the method, different concentrations of Li, Mg, Mn and Zn were observed in the samples of BD patients and high levels of copper for SCZ patients, indicating an imbalance in the homeostasis of important micronutrients. The treatment, especially with lithium, may be related to competition between metallic ions. BD-related metallobiomolecules were detected, preserving the binding between metal ions and biomolecules, with four fractions detected in the ultraviolet range (280 nm). Four fractions were collected by high-performance liquid chromatography/inductively coupled plasma mass spectrometry (HPLC/ICP-MS) and the proteins were identified by liquid chromatography/tandem mass spectrometry (LC/MS/MS). The Ig lambda chain V-IV region Hil, immunoglobulin heavy constant gama 1 (IGHG1) and beta-2-glycoprotein 1 (or ApoH) was identified in SCZ samples, suggesting its relationship with mood disorders. Surprisingly, Protein IGKV2D-28 was identified only in BD samples, opening up new possibilities for studies regarding the role of this protein in BD. Conclusions This approach brings new perspectives to the comprehension of mood disorders, highlighting the importance of metallomics science in disease development. This strategy showed an innovative potential for evaluating mood disorders at the proteomic level, making it possible to identify proteins related to mood disorders and BD.