A study has identified blood-based metabolic signatures that may help explain why some cannabis users develop schizophrenia, while others do not. Researchers from the University of the Basque Country (UPV/EHU) and BioBizkaia Health Research Institute used untargeted plasma lipidomics to uncover potential biomarkers linked to schizophrenia, cannabis use disorder (CUD), or both.
The team analyzed blood samples from 104 individuals divided into four groups: schizophrenia patients, cannabis users with CUD, individuals with both conditions (dual diagnosis), and healthy controls. Using liquid chromatography-high resolution mass spectrometry, the study identified 119 lipid metabolites, including acylcarnitines, N-acyl amino acids, and sterol lipids.
“We found considerable differences between these groups of individuals. By comparing the quantities of certain metabolites (fatty acids), we were able to perfectly differentiate between the three patient populations,” said Leyre Urigüen, study coordinator and pharmacologist at UPV/EHU, in the team’s press release.
The researchers observed that two acylcarnitines – L-octanoylcarnitine and L-decanoylcarnitine – were significantly reduced across all patient groups compared to controls, pointing to impaired fatty acid oxidation. These molecules play roles in mitochondrial function and neuroprotection, and their reduction could indicate underlying energy metabolism deficits common to both schizophrenia and cannabis use.
In cannabis users with CUD, levels of two N-acyl amino acids – N-palmitoyl threonine and N-palmitoyl serine – were strongly downregulated, compared to the control group. These metabolites, which participate in neuromodulation and are part of the extended endocannabinoid system, were also reduced in patients with schizophrenia and those with dual diagnosis. Additionally, schizophrenia and dual diagnosis groups showed elevated levels of 7-dehydrodesmosterol, a sterol lipid involved in cholesterol biosynthesis. The increase may be linked to antipsychotic treatment (aripiprazole), which affects sterol metabolism.
The authors emphasize that the results, while promising, are insufficient in confirming the utility of these metabolites as biomarkers, and that larger studies are needed to validate the findings. “We are proposing a way of working that can be replicated by other groups,” said Urigüen, referring to the refined plasma lipidomics approach developed in collaboration with the IBeA research group. “That way, headway can be made in the specification of these metabolites.”
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