Lipids are the most abundant but poorly explored components of the human brain. Here, we present a lipidome map of the human brain comprising 75 regions, including 52 neocortical ones. The lipidome composition varies greatly among the brain regions, affecting 93% of the 419 analyzed lipids. These differences reflect the brain’s structural characteristics, such as myelin content (345 lipids) and cell type composition (353 lipids), but also functional traits: functional connectivity (76 lipids) and information processing hierarchy (60 lipids). Combining lipid composition and mRNA expression data further enhances functional connectivity association. Biochemically, lipids linked with structural and functional brain features display distinct lipid class distribution, unsaturation extent, and prevalence of omega-3 and omega-6 fatty acid residues. We verified our conclusions by parallel analysis of three adult macaque brains, targeted analysis of 216 lipids, mass spectrometry imaging, and lipidome assessment of sorted murine neurons.

Lipidomics is a newly emerged discipline involving the identification and quantification of thousands of lipids. As a part of the omics field, lipidomics has shown rapid growth both in the number of studies and in the size of lipidome datasets, thus, requiring specific and efficient data analysis approaches. This paper aims to provide guidelines for analyzing and interpreting lipidome data obtained using untargeted methods that rely on liquid chromatography coupled with mass spectrometry (LC-MS) to detect and measure the intensities of lipid compounds. We present a state-of-the-art untargeted LC-MS workflow for lipidomics, from study design to annotation of lipid features, focusing on practical, rather than theoretical, approaches for data analysis, and we outline possible applications of untargeted lipidomics for biological studies. We provide a detailed R notebook designed specifically for untargeted lipidome LC-MS data analysis, which is based on xcms software.

BACKGROUND: Schizophrenia is a psychiatric disorder known to affect brain structure and functionality. Structural changes in the brain at the level of gross anatomical structures have been fairly well studied, while microstructural changes, especially those associated with changes in the molecular composition of the brain, are still being investigated. Of special interest are lipids and metabolites, for which some previous studies have shown association with schizophrenia. AIM: To utilize a spatially resolved analysis of the brain lipidome composition to investigate the degree and nature of schizophrenia-associated lipidome alterations in the gray and white matter structures of two neocortical regions — the dorsolateral prefrontal cortex (Brodmann area 9, BA9) and the posterior part of the superior temporal gyrus (Brodmann area 22, posterior part, BA22p), as well compare the distribution of the changes between the two regions and tissue types. METHODS: We employed Matrix-Assisted Laser Desorption/Ionization Mass Spectrometric Imaging (MALDI-MSI), supplemented by a statistical analysis, to examine the lipid composition of brain sections. A total of 24 neocortical sections from schizophrenia patients (n=2) and a healthy control group (n=2), representing the two aforementioned neocortical areas, were studied, yielding data for 131 lipid compounds measured across more than a million MALDI-MSI pixels. RESULTS: Our findings revealed an uneven distribution of schizophrenia-related lipid alterations across the two neocortical regions. The BA22p showed double the differences in its subcortical white matter structures compared to BA9, while less bias was detected in the gray matter layers. While the schizophrenia-associated lipid differences generally showed good agreement between brain regions at the lipid class level for both gray and white matter, there were consistently more discrepancies for white matter structures. CONCLUSION: Our study found a consistent yet differential association of schizophrenia with the brain lipidome composition of distinct neocortical areas, particularly subcortical white matter. These findings highlight the need for broader brain coverage in future schizophrenia research and underscore the potential of spatially resolved molecular analysis methods in identifying structure-specific effects.

BACKGROUND: Functional and structural studies of the brain highlight the importance of white matter alterations in schizophrenia. However, molecular studies of the alterations associated with the disease remain insufficient. AIM: To study the lipidome and transcriptome composition of the corpus callosum in schizophrenia, including analyzing a larger number of biochemical lipid compounds and their spatial distribution in brain sections, and corpus callosum transcriptome data. To integrate the results of molecular approaches to create a comprehensive molecular perspective of the disease. METHODS: A total of 8 brain tissue samples (4 from healthy controls (HC) + 4 from schizophrenia patients (SZ)) were analyzed using high-performance liquid chromatography with mass spectrometry (HPLC-MS) and RNA sequencing for transcriptome profiling. Additionally, 6 brain tissue samples (3 HC + 3 SZ) were analyzed using matrix-assisted laser desorption/ionization mass spectrometric imaging (MALDI-MSI). This approach enabled the characterization of mRNA and lipids in brain tissue samples, and the spatial distribution of selected lipids within brain sections. RESULTS: The analysis revealed a general trend of reduced lipid levels in the corpus callosum of schizophrenia patients for lipid classes measured by mass spectrometric methods. Specifically, nine lipid classes detected via HPLC-MS showed significant differences in schizophrenia samples, with seven of them having lower median intensity. The results between HPLC-MS and MALDI-MSI were highly concordant. Transcriptome analysis identified 1,202 differentially expressed genes, clustered into four functional modules, one of which was associated with lipid metabolism. CONCLUSION: We identified a series of lipidome and transcriptome alterations in the corpus callosum of schizophrenia patients that were internally consistent and aligned well with previous findings on white matter lipidome changes in schizophrenia. These results add to the existing scope of molecular alterations associated with schizophrenia, shedding light on the biological processes potentially involved in its pathogenesis.

In the article by M.S. Osetrova et al. titled "Comparative Analysis of Corpus Callosum Lipidome and Transcriptome in Schizophrenia and Healthy Brain", published in the Consortium PSYCHIATRICUM journal (Volume 6, Issue 1), the editorial team made some technical errors. Without any malicious intent, the quantitative indicators in Figure 1 "Experiment design" were incorrectly stated: 1,254 genes instead of 14,254 in the RNAseq section and 385 peaks instead of 384 in the LC-MS section. The technical errors in Figure 1 have been corrected, and updated PDF and HTML versions of the article have been uploaded on the journal's website. The editorial team of the journal hopes that the mistakes could not significantly affect the perception and interpretation of the published work by readers, and should not become the reason for retraction. The editorial team apologizes to the authors and readers for the mistakes made.