Lipidomics of the brain, retina, and biofluids: from the biological landscape to potential clinical application in schizophrenia

Abstract

Schizophrenia is a serious neuropsychiatric disorder, yet a clear pathophysiology has not been identified. To date, neither the objective biomarkers for diagnosis nor specific medications for the treatment of schizophrenia are clinically satisfactory. It is well accepted that lipids are essential to maintain the normal structure and function of neurons in the brain and that abnormalities in neuronal lipids are associated with abnormal neurodevelopment in schizophrenia. However, lipids and lipid-like molecules have been largely unexplored in contrast to proteins and their genes in schizophrenia. Compared with the gene- and protein-centric approaches, lipidomics is a recently emerged and rapidly evolving research field with particular importance for the study of neuropsychiatric disorders such as schizophrenia, in which even subtle aberrant alterations in the lipid composition and concentration of the neurons may disrupt brain functioning. In this review, we aimed to highlight the lipidomics of the brain, retina, and biofluids in both human and animal studies, discuss aberrant lipid alterations in correlation with schizophrenia, and propose future directions from the biological landscape towards potential clinical applications in schizophrenia. Recent studies are in support of the concept that aberrations in some lipid species [e.g. phospholipids, polyunsaturated fatty acids (PUFAs)] lead to structural alterations and, in turn, impairments in the biological function of membrane-bound proteins, the disruption of cell signaling molecule accessibility, and the dysfunction of neurotransmitter systems. In addition, abnormal lipidome alterations in biofluids are linked to schizophrenia, and thus they hold promise in the discovery of biomarkers for the diagnosis of schizophrenia.

The foundations and development of lipidomics

“…In the last 20 years, development of lipidomics technologies has vastly improved by the following: i ) extensive characterization of the structures of known lipid classes and subclasses and uncovering both new classes and new molecular species of lipids (e.g., ( 4 , 74 , 134 , 135 , 136 , 137 , 138 )); ii ) sensitive quantification of lipid species at attomole to femtomole levels from a variety of biological samples (e.g., ( 132 , 139 , 140 , 141 , 142 , 143 , 144 , 145 , 146 )); iii ) applications for biomedical and biological studies through pathway/network analysis; iv ) biomarker development that facilitates prediction, diagnosis, and prognosis of disease states (see recent reviews for references ( 83 , 147 , 148 , 149 , 150 , 151 , 152 , 153 , 154 , 155 , 156 )); v ) determining the alterations of lipids in spatial distribution via mapping complex organs by MALDI imaging (see recent reviews for references ( 157 , 158 , 159 , 160 , 161 , 162 )); and vi ) advances in bioinformatics to facilitate real time data processing (e.g., ( 88 , 163 , 164 , 165 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 , 174 )).…”

Adaptation of Lipid Profiling in Depression Disease and Treatment: A Critical Review

“…They are followed by phosphatidylcholines (PC), phosphatidylserines (PS), phosphatidylinositols (PI), sphingomyelins (SM) and ceramides (Cer) [19]. The use of modern lipidomics approaches based on mass spectrometry (MS) allowed the understanding of brain lipidome, as well as to identify changes in brain and central nervous system lipidome related to several psychiatric diseases, namely schizophrenia and bipolar disorder [20,21], and some in MDD, as reviewed in this document.…”

Identifying transdiagnostic biological subtypes across schizophrenia, bipolar disorder, and major depressive disorder based on lipidomics profiles

“…Lipidomics has recently been developed as a powerful tool to investigate the natural characteristics of SCZ, BP, and MDD. The peripheral lipidomics profile alterations of these psychiatric disorders have been pervasively characterized using ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC–MS/MS) technology and have served as promising biomarkers for early diagnosis and clinical outcome prediction ( Oresic et al, 2011 ; Brunkhorst-Kanaan et al, 2019 ; Zhou et al, 2019 ; Bot et al, 2020 ; Hussain et al, 2020 ; Zhuo et al, 2020 ; Dickens et al, 2021 ). Therefore, taking advantage of lipidomics analysis may help identify biologically homogeneous subtypes across these psychiatric disorders.…”