Lipidomics, Biomarkers, and Schizophrenia: A Current Perspective

Altered lipidomics biosignatures in schizophrenia: A systematic review

Multiomics approaches have significantly aided the identification of molecular signatures in complex neuropsychiatric disorders. Lipidomics, one of the newest additions in the -omics family, sheds light on lipid profiles and is an emerging methodological tool to study schizophrenia pathobiology, as lipid dysregulation has been repeatedly observed in schizophrenia. In this review, we performed a detailed literature search for lipidomics studies in schizophrenia. Following elaborate inclusion/exclusion criteria, we focused on human studies in schizophrenia and schizophrenia-related diagnoses in brain and blood specimens, including serum plasma, platelets and red blood cells. Eighteen studies fulfilled our inclusion criteria, of which five were conducted in the brain, 12 in peripheral material and one in both. Here, we first provide background on lipidomics and the main lipid categories addressed, review in detail the included literature and look for common lipidomics patterns in brain and the periphery that emerge from these studies. Furthermore, we highlight current limitations in schizophrenia lipidomics research and underline the need for following up on lipidomics results with complementary molecular approaches.

Analysis of the lipidomic profile of vegetable oils and animal fats and changes during aging by UPLC-Q-exactive orbitrap mass spectrometry

Vegetable oil and animal fat residues are common evidence in the cases of homicide, arson, theft, and other crimes. However, the lipid composition and content changes during aging on complex carriers remain unclear. Therefore, this study dynamically monitored the lipid composition and content changes during aging of 13 different types of vegetable oils and animal fats on five different carriers using the UPLC-Q-Exactive Orbitrap MS method. A total of 6 subclasses of 93 lipids including lysophosphatidylcholine (2 species), phosphatidylcholine (2 species), diglyceride (5 species), triglyceride (81 species), acylGlcCampesterol ester (2 species), and acylGlcSitosterol ester (1 species), were first identified in fresh vegetable oils and animal fats. By comparing the LC-MS/MS chromatograms of fresh vegetable oils and animal fats, it was found that there were significant differences between the chromatograms of vegetable oils and animal fats, but it was difficult to distinguish between the chromatograms of vegetable oils or animal fats. After aging at 60 °C for 200 days, there was a significant decrease in the content of diglyceride, triglyceride, acylGlcCampesterol ester, and acylGlcSitosterol ester, while the content of lysophosphatidylcholine and phosphatidylcholine initially increased and then decreased. Furthermore, statistical analysis of lipid differences between vegetable oils and animal fats was performed using cluster heat maps, volcanic maps, PCA, and OPLS-DA. On average, 33 significantly different lipids were screened (VIP > 1, p < 0.05), which could serve as potential biomarkers for distinguishing vegetable oils and animal fats. It was found that the potential biomarkers still existed during aging of vegetable oils and animal fats (100 and 200 days). This research provides important reference information for the identification of vegetable oil and animal fat residues in complex carriers at crime scenes.

Identification of Plasma Biomarkers in Drug-Naïve Schizophrenia Using Targeted Metabolomics

OBJECTIVE

Schizophrenia (SCZ) is a severe psychiatric disorder with unknown etiology and lacking specific biomarkers. Herein, we aimed to explore plasma biomarkers relevant to SCZ using targeted metabolomics.

METHODS

Sixty drug-naïve SCZ patients and 36 healthy controls were recruited. Psychotic symptoms were assessed using the Positive and Negative Syndrome Scale. We analyzed the levels of 271 metabolites in plasma samples from all subjects using targeted metabolomics, and identified metabolites that differed significantly between the two groups. Then we evaluated the diagnostic power of the metabolites based on receiver operating characteristic curves, and explored metabolites associated with the psychotic symptoms in SCZ patients.

RESULTS

Twenty-six metabolites showed significant differences between SCZ patients and healthy controls. Among them, 12 metabolites were phosphatidylcholines and cortisol, ceramide (d18:1/22:0), acetylcarnitine, and γ-aminobutyric acid, which could significantly distinguish SCZ from healthy controls with the area under the curve (AUC) above 0.7. Further, a panel consisting of the above 4 metabolites had an excellent performance with an AUC of 0.867. In SCZ patients, phosphatidylcholines were positively related with positive symptoms, and cholic acid was positively associated with negative symptoms.

CONCLUSION

Our study provides insights into the metabolite alterations associated with SCZ and potential biomarkers for its diagnosis and symptom severity assessment.

Metabolomics and Self-Reported Depression, Anxiety, and Phobic Symptoms in the VA Normative Aging Study

Traditional approaches to understanding metabolomics in mental illness have focused on investigating a single disorder or comparisons between diagnoses, but a growing body of evidence suggests substantial mechanistic overlap in mental disorders that could be reflected by the metabolome. In this study, we investigated associations between global plasma metabolites and abnormal scores on the depression, anxiety, and phobic anxiety subscales of the Brief Symptom Inventory (BSI) among 405 older males who participated in the Normative Aging Study (NAS). Our analysis revealed overlapping and distinct metabolites associated with each mental health dimension subscale and four metabolites belonging to xenobiotic, carbohydrate, and amino acid classes that were consistently associated across all three symptom dimension subscales. Furthermore, three of these four metabolites demonstrated a higher degree of alteration in men who reported poor scores in all three dimensions compared to men with poor scores in only one, suggesting the potential for shared underlying biology but a differing degree of perturbation when depression and anxiety symptoms co-occur. Our findings implicate pathways of interest relevant to the overlap of mental health conditions in aging veterans and could represent clinically translatable targets underlying poor mental health in this high-risk population.

Current State of Fluid Lipid Biomarkers for Personalized Diagnostics and Therapeutics in Schizophrenia Spectrum Disorders and Related Psychoses: A Narrative Review

Schizophrenia spectrum disorders (SSD) are traditionally diagnosed and categorized through clinical assessment, owing to their complex heterogeneity and an insufficient understanding of their underlying pathology. However, disease progression and accurate clinical diagnosis become problematic when differentiating shared aspects amongst mental health conditions. Hence, there is a need for widely accessible biomarkers to identify and track the neurobiological and pathophysiological development of mental health conditions, including SSD. High-throughput omics applications involving the use of liquid chromatography-mass spectrometry (LC-MS) are driving a surge in biological data generation, providing systems-level insight into physiological and pathogenic conditions. Lipidomics is an emerging subset of metabolomics, largely underexplored amongst the omics systems. Lipid profiles in the brain are highly enriched with well-established functions, including maintenance, support, and signal transduction of neuronal signaling pathways, making them a prospective and exciting source of biological material for neuropsychiatric research. Importantly, changes in the lipid composition of the brain appear to extend into the periphery, as there is evidence that circulating lipid alterations correlate with alterations of psychiatric condition(s). The relative accessibility of fluid lipids offers a unique source to acquire a lipidomic "footprint" of molecular changes, which may support reliable diagnostics even at early disease stages, prediction of treatment response and monitoring of treatment success (theranostics). Here, we summarize the latest fluid lipidomics discoveries in SSD-related research, examining the latest strategies to integrate information into multi-systems overviews that generate new perspectives of SSD-related psychosis identification, development, and treatment.

Characterising phospholipids and free fatty acids in patients with schizophrenia: A case-control study

OBJECTIVES

Previous studies have indicated that schizophrenia (SCZ) is linked to abnormal phospholipid and fatty acid metabolism. However, comprehensive analysis of phospholipids and free fatty acids (FFAs) for SCZ is very limited. Herein, we sought to compare serum levels of phospholipids and FFAs between patients with SCZ and healthy controls (HCs).

METHODS

One hundred and nineteen SCZ patients and 109 HCs were enrolled in the study. The levels of 177 phospholipids and FFAs were measured in serum samples using a targeted liquid chromatography-mass spectrometry (LC-MS)-based platform.

RESULTS

One hundred and ten metabolites, including 16 FFAs, 25 phosphatidylcholines, 23 lysophosphatidylcholines, 11 phosphatidylcholine plasmalogens, 7 phosphatidylethanolamines, 9 lysophosphatidylethanolamines, 6 phosphatidylethanolamine plasmalogens, and 13 sphingomyelins, were observed to be significantly altered in SCZ patients compared to HCs. These disturbances may represent underlying pathophysiology, including but not limited to altered activity of phospholipases and acyltransferases, increased oxidative stress, dysfunctional oligodendrocyte glycosynapses, and elevated lipid mobilisation and β-oxidation.

CONCLUSIONS

Our findings suggest that complex lipid profile abnormalities are associated with SCZ. This study may contribute to investigating the role of phospholipid and FFA alterations in the pathoetiology of SCZ.

Effects of Psychostimulants and Antipsychotics on Serum Lipids in an Animal Model for Schizophrenia

Schizophrenia (SCZ) treatment is essentially limited to the use of typical or atypical antipsychotic drugs, which suppress the main symptoms of this mental disorder. Metabolic syndrome is often reported in patients with SCZ under long-term drug treatment, but little is known about the alteration of lipid metabolism induced by antipsychotic use. In this study, we evaluated the blood serum lipids of a validated animal model for SCZ (Spontaneously Hypertensive Rat, SHR), and a normal control rat strain (Normotensive Wistar Rat, NWR), after long-term treatment (30 days) with typical haloperidol (HAL) or atypical clozapine (CLZ) antipsychotics. Moreover, psychostimulants, amphetamine (AMPH) or lisdexamfetamine (LSDX), were administered to NWR animals aiming to mimic the human first episode of psychosis, and the effects on serum lipids were also evaluated. Discrepancies in lipids between SHR and NWR animals, which included increased total lipids and decreased phospholipids in SHR compared with NWR, were similar to the differences previously reported for SCZ patients relative to healthy controls. Administration of psychostimulants in NWR decreased omega-3, which was also decreased in the first episode of psychosis of SCZ. Moreover, choline glycerophospholipids allowed us to distinguish the effects of CLZ in SHR. Thus, changes in the lipid metabolism in SHR seem to be reversed by the long-term treatment with the atypical antipsychotic CLZ, which was under the same condition described to reverse the SCZ-like endophenotypes of this validated animal model for SCZ. These data open new insights for understanding the potential influence of the treatment with typical or atypical antipsychotics on circulating lipids. This may represent an outcome effect from metabolic pathways that regulate lipids synthesis and breakdown, which may be reflecting a cell lipids dysfunction in SCZ.

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

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.

[Membrane lipids in schizophrenia and early phases of psychosis: Potential biomarkers and therapeutic targets?]

The various roles of membrane lipids in human health has urged researchers to study their impact in neuropsychiatric diseases, especially in schizophrenia spectrum disorders and more recently in early stages of psychosis. The progress in mass spectrometry technologies now allows a more comprehensive analysis of phospholipids (PL) and their fatty acid (FA) molecular species. FA are defined by a carbon chain of variable length and are said to be unsaturated when their chain has one or more carbon-carbon double bonds. The PL are composed of a hydrophilic polar head with a phosphoric acid group and an hydrophobic part with FAs; they encompass glycerophospholipids and sphingolipids. The plasma membrane is a complex and dynamic structure consisting of a lipid bilayer composed of an outer layer and an inner layer of specific lipid composition. The permanent remodeling of membrane lipids involves phospholipases especially the phospholipase A2. Seventy percent of the brain consists of lipids from different classes and molecular species. Most of the brain lipids are composed of polyunsaturated fatty acid (PUFA)-enriched diacyl classes where omega-3 and omega-6 molecular species predominate. The balance between omega-3 and omega-6 is important for the neurodevelopment. PUFA are also involved in neurogenesis and neurotransmission. Sphingomyelin (SM) is a sphingolipid that influences inflammation, cell proliferation and lipid rafts formation. It is an important component of myelin sheaths of white matter and therefore is involved in cerebral connectivity. In rat models, deficiency in omega-3 causes abnormalities in dopaminergic neurotransmission, impacts on the functioning of some receptors (including cannabinoids CB1, glutamatergic N-methyl-D-aspartate receptor, NMDA), and increases sensitivity to hallucinogens. In contrast, omega-3 supplementation improves cognitive function and prevents psychotic-like behavior in some animal models for schizophrenia. It also reduces oxidative stress and prevents demyelination. The historical membrane hypothesis of schizophrenia has led to explore the lipids abnormality in this disorder. This hypothesis was initially based on the observation of an abnormal membrane prostaglandin production in schizophrenia caused by a membrane arachidonic acid deficiency. It has evolved emphasizing the various PUFA membrane's roles in particular regarding oxidative stress, inflammation and regulation of the NMDA receptors. In patients with mental disorders, low omega-3 index is more frequent than in the general population. This lipid abnormality could lead to myelination abnormalities and cognitive deficits observed in patients. It could also participate in oxidative stress abnormalities and inflammation reported in schizophrenia. On the other hand, low omega-3 index deficit was reported to be associated with an increased cardiovascular risk, and omega-3 supplementation may also have a positive cardiovascular impact in psychiatric patients, even more than in the general population. The presence of membrane lipid abnormalities is also found in patients during the first psychotic episode (FEP). The omega-3 supplementation improved the recovery rate and prevented the loss of gray matter in FEP. In patients at ultra-high risk to develop a psychotic disorder (UHR), omega-3 supplementation has been associated with a reduction of the rate of conversion to psychosis and with metabolic changes, such as decreased activity of phospholipase A2. However, this study has not as yet been replicated. Not all patients exhibit lipid abnormalities. Several studies, including studies from our team, have found a bimodal distribution of lipids in patients with schizophrenia. But some studies have found differences (in PUFA) in the acute phase whereas our studies (on phospholipids) are in chronic phases. It will be interesting to study in more depth the links between these two parameters. Furthermore, we identified a subgroup which was identified with a deficit in sphingomyelin and PUFA whereas others have found an increase of sphingomyelin. Individuals with this abnormal lipid cluster had more cognitive impairments and more severe clinical symptoms. Because the niacin test is an indirect reflection of arachidonic acid levels, it has been proposed to identify a subset of patients with membrane lipids anomalies. Niacin test response is influenced by several factors related to lipid metabolism, including cannabis use and phospholipase A2 activity. Despite progress, the function and impact of membrane lipids are still poorly understood in schizophrenia. They could serve as biomarkers for identifying biological subgroups among patients with schizophrenia. In UHR patients, their predictive value on the conversion to psychosis should be tested. Omega-3 supplementation could be a promising treatment thanks to its good tolerance and acceptability. It could be more appropriate for patients with PUFA anomalies in a more personalized medical approach.

Lipidome alterations in human prefrontal cortex during development, aging, and cognitive disorders

Lipids are essential to brain functions, yet they remain largely unexplored. Here we investigated the lipidome composition of prefrontal cortex gray matter in 396 cognitively healthy individuals with ages spanning 100 years, as well as 67 adult individuals diagnosed with autism (ASD), schizophrenia (SZ), and Down syndrome (DS). Of the 5024 detected lipids, 95% showed significant age-dependent concentration differences clustering into four temporal stages, and resulting in a gradual increase in membrane fluidity in individuals ranging from newborn to nonagenarian. Aging affects 14% of the brain lipidome with late-life changes starting predominantly at 50-55 years of age-a period of general metabolic transition. All three diseases alter the brain lipidome composition, leading-among other things-to a concentration decrease in glycerophospholipid metabolism and endocannabinoid signaling pathways. Lipid concentration decreases in SZ were further linked to genetic variants associated with disease, indicating the relevance of the lipidome changes to disease progression.

Metabolic profiling identifies phospholipids as potential serum biomarkers for schizophrenia

Schizophrenia (SCZ) is a multifactorial psychiatric disorder. However, the molecular pathogenesis of SCZ remains largely unknown, and no reliable diagnostic test is currently available. Phospholipid metabolism is known to be disturbed during disease processes of SCZ. In this study, we used an untargeted liquid chromatography-mass spectrometry (LC-MS)-based metabolic profiling approach to measure lipid metabolites in serum samples from 119 SCZ patients and 109 healthy controls, to identify potential lipid biomarkers for the discrimination between SCZ patients and healthy controls. 51 lipid metabolites were identified to be significant for discriminating SCZ patients from healthy controls, including phosphatidylcholines (PCs), lysophosphatidylcholines (LPCs), phosphatidylethanolamines (PEs), lysophosphatidylethanolamines (LPEs) and sphingomyelins (SMs). Compared to healthy controls, most PCs and LPCs, as well as all PEs in patients were decreased, while most LPEs and all SMs were increased. A panel of six lipid metabolites could effectively discriminate SCZ patients from healthy controls with an area under the receiver-operating characteristic curve of 0.991 in the training samples and 0.980 in the test samples. These findings suggest that extensive disturbances of phospholipids may be involved in the development of SCZ. This LC-MS-based metabolic profiling approach shows potential for the identification of putative serum biomarkers for the diagnosis of SCZ.

Metabolomic Biomarkers in Mental Disorders: Bipolar Disorder and Schizophrenia

Psychiatric disorders are some of the most impairing human diseases. Among them, bipolar disorder and schizophrenia are the most common. Both have complicated diagnostics due to their phenotypic, biological, and genetic heterogeneity, unknown etiology, and the underlying biological pathways, and molecular mechanisms are still not completely understood. Given the multifactorial complexity of these disorders, identification and implementation of metabolic biomarkers would assist in their early detection and diagnosis and facilitate disease monitoring and treatment responses. To date, numerous studies have utilized metabolomics to better understand psychiatric disorders, and findings from these studies have begun to converge. In this chapter, we briefly describe some of the metabolomic biomarkers found in these two disorders.

Enhanced Molecular Appreciation of Psychiatric Disorders Through High-Dimensionality Data Acquisition and Analytics

The initial diagnosis, molecular investigation, treatment, and posttreatment care of major psychiatric disorders (schizophrenia and bipolar depression) are all still significantly hindered by the current inability to define these disorders in an explicit molecular signaling manner. High-dimensionality data analytics, using large datastreams from transcriptomic, proteomic, or metabolomic investigations, will likely advance both the appreciation of the molecular nature of major psychiatric disorders and simultaneously enhance our ability to more efficiently diagnose and treat these debilitating conditions. High-dimensionality data analysis in psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results. All of these issues combine to constrain the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges through the implementation of transcriptomic, proteomic, or metabolomics signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of intelligent high-dimensionality data-based differential diagnosis in mental disease diagnosis and treatment, future research will need large, well-defined cohorts in combination with state-of-the-art technologies.

Serum lipidomic analysis for the discovery of biomarkers for major depressive disorder in drug-free patients

Lipidomic analysis can be used to efficiently identify hundreds of lipid molecular species in biological materials and has been recently established as an important tool for biomarker discovery in various neuropsychiatric disorders including major depressive disorder (MDD). In this study, quantitative targeted serum lipidomic profiling was performed on female subjects using liquid chromatography-mass spectrometry. Global lipid profiling of pooled serum samples from 10 patients currently with MDD (cMDD), 10 patients with remitted MDD (rMDD), and 10 healthy controls revealed 37 differentially regulated lipids (DRLs). DRLs were further verified using multiple-reaction monitoring (MRM) in each of the 25 samples from the three groups of independent cohorts. Using multivariate analysis and MRM data we identified serum biomarker panels of discriminatory lipids that differentiated between pairs of groups: lysophosphatidic acid (LPA)(16:1), triglycerides (TG)(44:0), and TG(54:8) distinguished cMDD from controls with 76% accuracy; lysophosphatidylcholines(16:1), TG(44:0), TG(46:0), and TG(50:1) distinguished between cMDD and rMDD at 65% accuracy; and LPA(16:1), TG(52:6), TG(54:8), and TG(58:10) distinguished between rMDD and controls with 60% accuracy. Our lipidomic analysis identified peripheral lipid signatures of MDD, which thereby provides providing important biomarker candidates for MDD.