Dysregulated Lipid Metabolism Precedes Onset of Psychosis

Metabolic complications of psychotropic medications in psychiatric disorders: Emerging role of de novo lipogenesis and therapeutic consideration

Although significant advances have been made in understanding the patho-physiology of psychiatric disorders (PDs), therapeutic advances have not been very convincing. While psychotropic medications can reduce classical symptoms in patients with PDs, their long-term use has been reported to induce or exaggerate various pre-existing metabolic abnormalities including diabetes, obesity and non-alcoholic fatty liver disease (NAFLD). The mechanism(s) underlying these metabolic abnormalities is not clear; however, lipid/fatty acid accumulation due to enhanced de novo lipogenesis (DNL) has been shown to reduce membrane fluidity, increase oxidative stress and inflammation leading to the development of the aforementioned metabolic abnormalities. Intriguingly, emerging evidence suggest that DNL dysregulation and fatty acid accumulation could be the major mechanisms associated with the development of obesity, diabetes and NAFLD after long-term treatment with psychotropic medications in patients with PDs. In support of this, several adjunctive drugs comprising of anti-oxidants and anti-inflammatory agents, that are used in treating PDs in combination with psychotropic medications, have been shown to reduce insulin resistance and development of NAFLD. In conclusion, the above evidence suggests that DNL could be a potential pathological factor associated with various metabolic abnormalities, and a new avenue for translational research and therapeutic drug designing in PDs.

Alterations to sphingolipid metabolism from antipsychotic administration in healthy volunteers are restored following the use of cannabidiol

Randomized clinical trials substantiate cannabidiol (CBD) as a next-generation antipsychotic, effective in alleviating positive and negative symptoms associated with psychosis, while minimising the adverse effects seen with established treatments. Although the mechanisms remain debated, CBD is known to induce drug-responsive changes in lipid-based retrograde neurotransmitters. Lipid aberrations are also frequently observed with antipsychotics, which may contribute to their efficacy or increase the risk of undesirables, including metabolic dysfunction, obesity and dyslipidaemia. Our study investigated CBD's impact following lipid responses triggered by interaction with second-generation antipsychotics (SGA) in a randomized phase I safety study. Untargeted mass spectrometry assessed the lipidomic profiles of human sera, collected from 38 healthy volunteers. Serum samples were obtained prior to commencement of any medication (t = 0), 3 days after consecutive administration of one of the five, placebo-controlled, treatment arms designed to achieve steady-state concentrations of each SGA (amisulpride, 150 mg/day; quetiapine, 300 mg/day; olanzapine 10 mg/day; risperidone, 3 mg/day), and after six successive days of SGA treatment combined with CBD (800 mg/day). Receiver operating characteristics (ROC) refined 3712 features to a putative list of 15 lipids significantly altered (AUC > 0.7), classified into sphingolipids (53 %), glycerolipids (27 %) and glycerophospholipids (20 %). Targeted mass spectrometry confirmed reduced sphingomyelin and ceramide levels with antipsychotics, which mapped along their catabolic pathway and were restored by CBD. These sphingolipids inversely correlated with body weight after olanzapine, quetiapine, and risperidone treatment, where CBD appears to have arrested or attenuated these effects. Herein, we propose CBD may alleviate aberrant sphingolipid metabolism and that further investigation into sphingolipids as markers for monitoring side effects of SGAs and efficacy of CBD is warranted.

Gender Differences in Prevalence and Associated Factors of Dyslipidemia in Initial-Treatment and Drug-Naïve Schizophrenia Patients

Background

Dyslipidemia is frequently comorbid with schizophrenia (SCZ), and both conditions often demonstrate significant gender differences in their clinical features. This study specifically focuses on investigating the prevalence of dyslipidemia and the factors that contribute to it in initial-treatment and drug-naïve (ITDN) SCZ patients, specifically focusing on gender differences.

Methods

A total of 224 male ITDN SCZ patients and 424 female ITDN SCZ patients were included in this study. Socio-demographic and general clinical data of the patients were collected, and routine biochemical parameters, such as lipid levels, fasting blood glucose, thyroid function, renal function, and blood cell counts, were measured. Patients were also assessed for psychopathology and disease severity using the Positive and Negative Syndrome Scale (PANSS) and the Clinical Global Impression Scale - Severity of Illness (CGI-SI), respectively. In addition, a lipids score was calculated for assessing the severity of dyslipidemia.

Results

The study revealed that the prevalence of dyslipidemia in male patients was 34.02% (83/224), whereas 33.25% (141/424) in females, indicating no statistically significant difference (χ2 = 0.04, p = 0.841). For males, the risk factors for dyslipidemia were high education levels and diastolic blood pressure (DBP), while red blood cell count (RBC) as a protective factor. Additionally, DBP was identified as a risk factor for dyslipidemia score. In females, systolic blood pressure (SBP) was identified as a risk factor for dyslipidemia, while being married and creatinine (CRE) levels were found to be protective factors. Moreover, SBP was revealed as a risk factor for dyslipidemia score.

Conclusion

No significant gender differences were observed in the prevalence of dyslipidemia among the ITDN SCZ patients. However, notable gender differences were identified in the factors influencing dyslipidemia and its severity within this group. These findings suggest the necessity of implementing gender-specific interventions to address the potential risk factors associated with dyslipidemia.

Can neurocognition, brain neurotrophic factor, triglyceride, and total cholesterol predict suicidal ideation in first-episode Han Chinese patients with schizophrenia?

OBJECTIVE

Previous studies have suggested that the suicide rate of patients with schizophrenia is high. This study investigates factors influencing suicidal ideation in first-episode schizophrenia patients, focusing on cognitive function, brain-derived neurotrophic factor (BDNF), triglyceride (TG), and total cholesterol (TC) in patients with first-episode schizophrenia.

METHODS

A total of 123 patients with first-episode schizophrenia and 38 healthy controls were included in the study. The patients were divided into suicidal and nonsuicidal ideation groups based on the Beck Scale for Suicidal Ideation, and they were assessed with Positive and Negative Syndrome Scale (PANSS). Cognitive function was assessed using the Chinese version of the MATRICS consensus cognitive battery (MCCB) and the serum BDNF, TG, and TC were detected. The main statistical methods include t-test, χ2 test, multivariate logistic regression analysis, receiver operating characteristic (ROC) curve analysis, and the DeLong test.

RESULTS

26.02% of patients exhibited suicidal ideation. Higher PANSS and TC levels were risk factors, while higher MCCB scores and BDNF levels were protective factors. ROC analysis indicated AUCs of 0.630, 0.724, and 0.762 for serum BDNF, PANSS, and MCCB, respectively, with a combined AUC of 0.870.

CONCLUSION

Serum BDNF level, PANSS score, and MCCB score can be used as auxiliary predictors of suicidal ideation in schizophrenic patients. Combining these three indicators can effectively predict suicidal ideation in schizophrenic patients.

Proteomic Biomarkers for the Prediction of Transition to Psychosis in Individuals at Clinical High Risk: A Multi-cohort Model Development Study

Psychosis risk prediction is one of the leading challenges in psychiatry. Previous investigations have suggested that plasma proteomic data may be useful in accurately predicting transition to psychosis in individuals at clinical high risk (CHR). We hypothesized that an a priori-specified proteomic prediction model would have strong predictive accuracy for psychosis risk and aimed to replicate longitudinal associations between plasma proteins and transition to psychosis. This study used plasma samples from participants in 3 CHR cohorts: the North American Prodrome Longitudinal Studies 2 and 3, and the NEURAPRO randomized control trial (total n = 754). Plasma proteomic data were quantified using mass spectrometry. The primary outcome was transition to psychosis over the study follow-up period. Logistic regression models were internally validated, and optimism-corrected performance metrics derived with a bootstrap procedure. In the overall sample of CHR participants (age: 18.5, SD: 3.9; 51.9% male), 20.4% (n = 154) developed psychosis within 4.4 years. The a priori-specified model showed poor risk-prediction accuracy for the development of psychosis (C-statistic: 0.51 [95% CI: 0.50, 0.59], calibration slope: 0.45). At a group level, Complement C8B, C4B, C5, and leucine-rich α-2 glycoprotein 1 (LRG1) were associated with transition to psychosis but did not surpass correction for multiple comparisons. This study did not confirm the findings from a previous proteomic prediction model of transition from CHR to psychosis. Certain complement proteins may be weakly associated with transition at a group level. Previous findings, derived from small samples, should be interpreted with caution.

Longitudinal Trajectories of Plasma Polyunsaturated Fatty Acids and Associations With Psychosis Spectrum Outcomes in Early Adulthood

BACKGROUND

Evidence supports associations between polyunsaturated fatty acids such as docosahexaenoic acid (DHA) and psychosis. However, polyunsaturated fatty acid trajectories in the general population have not been characterized, and associations with psychosis spectrum outcomes in early adulthood are unknown.

METHODS

Plasma omega-6 to omega-3 ratio and DHA (expressed as percentage of total fatty acids) were measured by nuclear magnetic spectroscopy at 7, 15, 17, and 24 years of age in participants of ALSPAC (Avon Longitudinal Study of Parents and Children). Curvilinear growth mixture modeling evaluated body mass index-adjusted trajectories of both measures. Outcomes were assessed at 24 years. Psychotic experiences (PEs), at-risk mental state status, psychotic disorder, and number of PEs were assessed using the Psychosis-Like Symptoms interview (n = 3635; 2247 [61.8%] female). Negative symptoms score was measured using the Community Assessment of Psychic Experiences (n = 3484; 2161 [62.0%] female). Associations were adjusted for sex, ethnicity, parental social class, and cumulative smoking and alcohol use.

RESULTS

Relative to stable average, the persistently high omega-6 to omega-3 ratio trajectory was associated with increased odds of PEs and psychotic disorder, but attenuated on adjustment for covariates (PEs adjusted odds ratio [aOR] = 1.63, 95% CI = 0.92-2.89; psychotic disorder aOR = 1.69, 95% CI = 0.71-4.07). This was also the case for persistently low DHA (PEs aOR = 1.42, 95% CI = 0.84-2.37; psychotic disorder aOR = 1.14, 95% CI = 0.49-2.67). Following adjustment, persistently high omega-6 to omega-3 ratio was associated with increased number of PEs (β = 0.41, 95% CI = 0.05-0.78) and negative symptoms score (β = 0.43, 95% CI = 0.14-0.72), as was persistently low DHA (number of PEs β = 0.45, 95% CI = 0.14-0.76; negative symptoms β = 0.35, 95% CI = 0.12-0.58).

CONCLUSIONS

Optimization of polyunsaturated fatty acid status during development warrants further investigation in relation to psychotic symptoms in early adulthood.

The identification of novel schizophrenia-related metabolites using untargeted lipidomics

Human lipidome still remains largely unexplored among Chinese schizophrenia patients. We aimed to identify novel lipid molecules associated with schizophrenia and cognition among schizophrenia patients. The current study included 96 male schizophrenia patients and 96 gender-matched healthy controls. Untargeted lipidomics profiling was conducted among all participants. Logistic regression models were used to assess metabolite associations with schizophrenia. We further assessed the incremental predictive value of identified metabolites beyond conventional risk factors on schizophrenia status. In addition, identified metabolites were tested for association with cognitive function among schizophrenia patients using linear regression models. A total of 34 metabolites were associated with schizophrenia. Addition of these identified metabolites to age, body mass index, smoking, and education significantly increased the risk reclassification of schizophrenia. Among the schizophrenia-related metabolites, 10 were further associated with cognition in schizophrenia patients, including four metabolites associated with immediate memory, two metabolites associated with delayed memory, three metabolites associated with visuospatial, four metabolites associated with language, one metabolite associated with attention, and two metabolites associated with the total score. Our findings provide novel insights into the biological mechanisms of schizophrenia, suggesting that lipid metabolites may serve as potential diagnostic or therapeutic targets of schizophrenia.

Dysregulation of Microbiota in Patients With First-Episode Psychosis Is Associated With Symptom Severity and Treatment Response

BACKGROUND

The gut microbiome has been implicated in the pathogenesis of mental disorders where the gut-brain axis acts as a bidirectional communication network.

METHODS

Herein, we investigated the compositional and functional differences of gut microbiome between patients with first-episode psychosis (FEP) (n = 26) and healthy control participants (n = 22) using whole-genome shotgun sequencing. In addition, we assessed the oral microbiome in patients with FEP (n = 13) and listed their taxonomic diversity.

RESULTS

Our findings suggest that there is a dysbiosis of gut microbiota in patients with FEP. Relative abundance of Bifidobacterium adolescentis, Prevotella copri, and Turicibacter sanguinis was markedly increased (linear discriminant analysis scores [log10] > 1, and Mann-Whitney U test; false discovery rate-adjusted p values < .05) in the FEP group compared with the healthy control participants. Pathway analysis indicated that several metabolic pathways, particularly deoxyribonucleotide biosynthesis, branched-chain amino acid biosynthesis, tricarboxylic acid cycle, and fatty acid elongation and biosynthesis, were dysregulated in the FEP group compared with the healthy control group. In addition, this preliminary study was able to identify specific gut microbes (at baseline) that were predictive of weight gain in the FEP group at a 1-year follow-up. Bacteroides dorei, Bifidobacterium adolescentis, Turicibacter sanguinis, Roseburia spp., and Ruminococcus lactaris were positively associated (eXtreme gradient boosting, XGBoost regression model, Shapley additive explanations, R2 = 0.82) with weight gain.

CONCLUSIONS

Our findings may suggest the involvement of gut microbiota in the pathogenesis of psychosis. The benefit of modulation of the gut microbiome in the treatment of psychotic disorders should be explored further.

Regional Vulnerability Indices in Youth With Persistent and Distressing Psychoticlike Experiences

Importance

Distressing and persistent psychoticlike experiences (PLEs) in youth are associated with greater odds of developing psychiatric conditions in adulthood. Despite this risk, it is unclear whether early PLEs show similar brain patterns compared with adults with psychiatric and neurologic conditions.

Objective

To examine the degree to which persistent and distressing PLEs exhibit neural metrics that show similarity to adults with chronic psychiatric and neurologic conditions.

Design, Setting, and Participants

This cohort study used Adolescent Brain Cognitive Development (ABCD) Study examining the persistence and distress associated with PLEs across the first 3 waves of data with baseline structural magnetic resonance imaging data. Analyzed data were collected between September 1, 2016, and September 27, 2021. Children were recruited from 21 research sites across the US.

Exposures

Psychoticlike experiences were assessed using the Prodromal Questionnaire-Brief Child Version, and participants were categorized into groups based on the persistence and distress associated with PLEs.

Main Outcomes and Measures

Cortical and subcortical regional vulnerability indices (RVIs) were created by quantifying the similarity of participants' baseline neuroimaging measures to the expected patterns found in adult neuropsychiatric samples. The PLE groups were compared on the following RVI cortical and subcortical metrics: schizophrenia spectrum disorders, bipolar disorder, major depressive disorder, Parkinson disease, Alzheimer disease, and metabolic diseases.

Results

Analyses examined PLE groups created from 8242 children in the ABCD sample (52.5% male; mean [SD] age, 9.93 [0.63] years; and 56.3% White), including persistent distressing PLEs (n = 329), transient distressing PLEs (n = 396), persistent nondistressing PLEs (n = 234), transient nondistressing PLEs (n = 390), and low distressing PLEs (n = 6893) groups. Participants with persistent or transient distressing PLEs broadly showed increased subcortical RVI scores across most RVI metrics, with persistent distressing PLEs additionally showing increased scores for cortical RVI metrics. The greatest effect sizes were found for persistent distressing PLEs with cortical RVI-schizophrenia spectrum disorders (β estimate, 1.055; 95% CI, 0.326-1.786) and RVI-Alzheimer disease (β estimate, 2.473; 95% CI, 0.930-4.018).

Conclusions and Relevance

In this cohort study of ABCD participants, the findings suggest that especially the persistent distressing PLEs in children were associated with neural metrics resembling those observed in adults with severe psychiatric and neurologic conditions. These findings support the potential use of brain-based risk scores for early identification and precision medicine approaches in the assessment of PLEs.

Recent Updates on Predicting Conversion in Youth at Clinical High Risk for Psychosis

PURPOSE OF REVIEW

This review highlights recent advances in the prediction and treatment of psychotic conversion. Over the past 25 years, research into the prodromal phase of psychotic illness has expanded with the promise of early identification of individuals at clinical high risk (CHR) for psychosis who are likely to convert to psychosis.

RECENT FINDINGS

Meta-analyses highlight conversion rates between 20 and 30% within 2-3 years using existing clinical criteria while research into more specific risk factors, biomarkers, and refinement of psychosis risk calculators has exploded, improving our ability to predict psychotic conversion with greater accuracy. Recent studies highlight risk factors and biomarkers likely to contribute to earlier identification and provide insight into neurodevelopmental abnormalities, CHR subtypes, and interventions that can target specific risk profiles linked to neural mechanisms. Ongoing initiatives that assess longer-term (> 5-10 years) outcome of CHR participants can provide valuable information about predictors of later conversion and diagnostic outcomes while large-scale international biomarker studies provide hope for precision intervention that will alter the course of early psychosis globally.

Prognostic models predicting transition to psychotic disorder using blood-based biomarkers: a systematic review and critical appraisal

Accumulating evidence suggests individuals with psychotic disorder show abnormalities in metabolic and inflammatory processes. Recently, several studies have employed blood-based predictors in models predicting transition to psychotic disorder in risk-enriched populations. A systematic review of the performance and methodology of prognostic models using blood-based biomarkers in the prediction of psychotic disorder from risk-enriched populations is warranted. Databases (PubMed, EMBASE and PsycINFO) were searched for eligible texts from 1998 to 15/05/2023, which detailed model development or validation studies. The checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS) was used to guide data extraction from eligible texts and the Prediction Model Risk of Bias Assessment Tool (PROBAST) was used to assess the risk of bias and applicability of the studies. A narrative synthesis of the included studies was performed. Seventeen eligible studies were identified: 16 eligible model development studies and one eligible model validation study. A wide range of biomarkers were assessed, including nucleic acids, proteins, metabolites, and lipids. The range of C-index (area under the curve) estimates reported for the models was 0.67-1.00. No studies assessed model calibration. According to PROBAST criteria, all studies were at high risk of bias in the analysis domain. While a wide range of potentially predictive biomarkers were identified in the included studies, most studies did not account for overfitting in model performance estimates, no studies assessed calibration, and all models were at high risk of bias according to PROBAST criteria. External validation of the models is needed to provide more accurate estimates of their performance. Future studies which follow the latest available methodological and reporting guidelines and adopt strategies to accommodate required sample sizes for model development or validation will clarify the value of including blood-based biomarkers in models predicting psychosis.

Chronic inflammation, neuroglial dysfunction, and plasmalogen deficiency as a new pathobiological hypothesis addressing the overlap between post-COVID-19 symptoms and myalgic encephalomyelitis/chronic fatigue syndrome

After five waves of coronavirus disease 2019 (COVID-19) outbreaks, it has been recognized that a significant portion of the affected individuals developed long-term debilitating symptoms marked by chronic fatigue, cognitive difficulties ("brain fog"), post-exertional malaise, and autonomic dysfunction. The onset, progression, and clinical presentation of this condition, generically named post-COVID-19 syndrome, overlap significantly with another enigmatic condition, referred to as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). Several pathobiological mechanisms have been proposed for ME/CFS, including redox imbalance, systemic and central nervous system inflammation, and mitochondrial dysfunction. Chronic inflammation and glial pathological reactivity are common hallmarks of several neurodegenerative and neuropsychiatric disorders and have been consistently associated with reduced central and peripheral levels of plasmalogens, one of the major phospholipid components of cell membranes with several homeostatic functions. Of great interest, recent evidence revealed a significant reduction of plasmalogen contents, biosynthesis, and metabolism in ME/CFS and acute COVID-19, with a strong association to symptom severity and other relevant clinical outcomes. These bioactive lipids have increasingly attracted attention due to their reduced levels representing a common pathophysiological manifestation between several disorders associated with aging and chronic inflammation. However, alterations in plasmalogen levels or their lipidic metabolism have not yet been examined in individuals suffering from post-COVID-19 symptoms. Here, we proposed a pathobiological model for post-COVID-19 and ME/CFS based on their common inflammation and dysfunctional glial reactivity, and highlighted the emerging implications of plasmalogen deficiency in the underlying mechanisms. Along with the promising outcomes of plasmalogen replacement therapy (PRT) for various neurodegenerative/neuropsychiatric disorders, we sought to propose PRT as a simple, effective, and safe strategy for the potential relief of the debilitating symptoms associated with ME/CFS and post-COVID-19 syndrome.

Lipid-correlated alterations in the transcriptome are enriched in several specific pathways in the postmortem prefrontal cortex of Japanese patients with schizophrenia

AIMS

Schizophrenia is a chronic relapsing psychiatric disorder that is characterized by many symptoms and has a high heritability. There were studies showing that the phospholipid abnormalities in subjects with schizophrenia (Front Biosci, S3, 2011, 153; Schizophr Bull, 48, 2022, 1125; Sci Rep, 7, 2017, 6; Anal Bioanal Chem, 400, 2011, 1933). Disturbances in prefrontal cortex phospholipid and fatty acid composition have been reported in subjects with schizophrenia (Sci Rep, 7, 2017, 6; Anal Bioanal Chem, 400, 2011, 1933; Schizophr Res, 215, 2020, 493; J Psychiatr Res, 47, 2013, 636; Int J Mol Sci, 22, 2021). For exploring the signaling pathways contributing to the lipid changes in previous study (Sci Rep, 7, 2017, 6), we performed two types of transcriptome analyses in subjects with schizophrenia: an unbiased transcriptome analysis solely based on RNA-seq data and a correlation analysis between levels of gene expression and lipids.

METHODS

RNA-Seq analysis was performed in the postmortem prefrontal cortex from 10 subjects with schizophrenia and 5 controls. Correlation analysis between the transcriptome and lipidome from 9 subjects, which are the same samples in the previous lipidomics study (Sci Rep, 7, 2017, 6).

RESULTS

Extraction of differentially expressed genes (DEGs) and further sequence and functional group analysis revealed changes in gene expression levels in phosphoinositide 3-kinase (PI3K)-Akt signaling and the complement system. In addition, a correlation analysis clarified alterations in ether lipid metabolism pathway, which is not found as DEGs in transcriptome analysis alone.

CONCLUSIONS

This study provided results of the integrated analysis of the schizophrenia-associated transcriptome and lipidome within the PFC and revealed that lipid-correlated alterations in the transcriptome are enriched in specific pathways including ether lipid metabolism pathway.

Lipid Metabolism Disorder in Cerebrospinal Fluid Related to Parkinson's Disease

BACKGROUND

Abnormal accumulation of lipids is found in dopamine neurons and resident microglia in the substantia nigra of patients with Parkinson's disease (PD). The accumulation of lipids is an important risk factor for PD. Previous studies have mainly focussed on lipid metabolism in peripheral blood, but little attention has been given to cerebrospinal fluid (CSF). We drew the lipidomic signature in CSF from PD patients and evaluated the role of lipids in CSF as biomarkers for PD diagnosis.

METHODS

Based on lipidomic approaches, we investigated and compared lipid metabolism in CSF from PD patients and healthy controls without dyslipidaemia in peripheral blood and explored the relationship of lipids between CSF and serum by Pearson correlation analysis.

RESULTS

A total of 231 lipid species were detected and classified into 13 families in the CSF. The lipid families, including phosphatidylcholine (PC), sphingomyelin (SM) and cholesterol ester (CE), had significantly increased expression compared with the control. Hierarchical clustering was performed to distinguish PD patients based on the significantly changed expression of 34 lipid species. Unsupervised and supervised methods were used to refine this classification. A total of 12 lipid species, including 3-hydroxy-dodecanoyl-carnitine, Cer(d18:1/24:1), CE(20:4), CE(22:6), PC(14:0/18:2), PC(O-18:3/20:2), PC(O-20:2/24:3), SM(d18:0/16:0), SM(d18:2/14:0), SM(d18:2/24:1), SM(d18:1/20:1) and SM(d18:1/12:0), were selected to draw the lipidomic signature of PD. Correlation analysis was performed and showed that the CE family and CE (22:6) in CSF had a positive association with total cholesterol in the peripheral blood from PD patients but not from healthy controls.

CONCLUSIONS

Our results revealed that the lipidomic signature in CSF may be considered a potential biomarker for PD diagnosis, and increased CE, PC and SM in CSF may reveal pathological changes in PD patients, such as blood-brain barrier leakage.

Role of de novo lipogenesis in inflammation and insulin resistance in alzheimer's disease

Patients with Alzheimer's disease (AD) display both peripheral tissue and brain insulin resistance, the later could be a potential risk factor for cognitive dysfunction. While certain degree of inflammation is required for inducing insulin resistance, underlying mechanism(s) remains unclear. Evidence from diverse research domains suggest that elevated intracellular fatty acids of de novo pathway can induce insulin resistance even without triggering inflammation; however, the effect of saturated fatty acids (SFAs) could be detrimental due the development of proinflammatory cues. In this context, evidence suggest that while lipid/fatty acid accumulation is a characteristic feature of brain pathology in AD, dysregulated de novo lipogenesis could be a potential source for lipid/fatty acid accumulation. Therefore, therapies aimed at regulating de novo lipogenesis could be effective in improving insulin sensitivity and cognitive function in patients with AD.

Membrane Lipids in Ultra-High-Risk Patients: Potential Predictive Biomarkers of Conversion to Psychosis

Alterations in membrane lipids are reported in schizophrenia. However, no conclusion can be drawn regarding the extended and predictive value of these alterations in persons at ultra-high risk of psychosis (UHR). Recent studies suggested that sterols' impact on psychiatric disorders was underestimated. Here, we simultaneously explored sterols, fatty acids (FA), and phospholipids (PL) in UHR persons for the first time. We analysed erythrocyte membrane lipids in 61 UHR persons, including 29 who later converted to psychosis (UHR-C) and 32 who did not (UHC-NC). We used gas chromatography for FA and liquid chromatography tandem with mass spectrometry for sterols and phospholipids. Among UHR individuals, elevated baseline membrane linoleic acid level was associated with conversion to psychosis (26.1% vs. 60.5%, p = 0.02). Combining sterols, FA, and PL membrane composition improved the prediction of psychosis onset (AUC = 0.73). This is the first report showing that membrane sterol participates, with other membrane lipids, in modulating the risk of psychosis. It suggests that membrane lipids could be used as biomarkers for personalised medicine in UHR patients.

Serum immune markers and transition to psychosis in individuals at clinical high risk

Individuals at clinical high risk (CHR) for psychosis have been found to have altered cytokine levels, but whether these changes are related to clinical outcomes remains unclear. We addressed this issue by measuring serum levels of 20 immune markers in 325 participants (n = 269 CHR, n = 56 healthy controls) using multiplex immunoassays, and then followed up the CHR sample to determine their clinical outcomes. Among 269 CHR individuals, 50 (18.6 %) developed psychosis by two years. Univariate and machine learning techniques were used to compare levels of inflammatory markers in CHR subjects and healthy controls, and in CHR subjects who had (CHR-t), or had not (CHR-nt) transitioned to psychosis. An ANCOVA identified significant group differences (CHR-t, CHR-nt and controls) and post-hoc tests indicated that VEGF levels and the IL-10/IL-6 ratio were significantly higher in CHR-t than CHR-nt, after adjusting for multiple comparisons. Using a penalised logistic regression classifier, CHR participants were distinguished from controls with an area-under the curve (AUC) of 0.82, with IL-6 and IL-4 levels the most important discriminating features. Transition to psychosis was predicted with an AUC of 0.57, with higher VEGF level and IL-10/IL-6 ratio the most important discriminating features. These data suggest that alterations in the levels of peripheral immune markers are associated with the subsequent onset of psychosis. The association with increased VEGF levels could reflect altered blood-brain-barrier (BBB) permeability, while the link with an elevated IL-10/IL-6 ratio points to an imbalance between anti- and pro-inflammatory cytokines.

Schizophrenia and cardiometabolic abnormalities: A Mendelian randomization study

Background: Individuals with a diagnosis of schizophrenia are known to be at high risk of premature mortality due to poor physical health, especially cardiovascular disease, diabetes, and obesity. The reasons for these physical health outcomes within this patient population are complex. Despite well-documented cardiometabolic adverse effects of certain antipsychotic drugs and lifestyle factors, schizophrenia may have an independent effect. Aims: To investigate if there is evidence that schizophrenia is causally related to cardiometabolic traits (blood lipids, anthropometric traits, glycaemic traits, blood pressure) and vice versa using bi-directional two-sample Mendelian randomization (MR) analysis. Methods: We used 185 genetic variants associated with schizophrenia from the latest Psychiatric Genomics Consortium GWAS (n = 130,644) in the forward analysis (schizophrenia to cardiometabolic traits) and genetic variants associated with the cardiometabolic traits from various consortia in the reverse analysis (cardiometabolic traits to schizophrenia), both at genome-wide significance (5 × 10-8). The primary method was inverse-variance weighted MR, supported by supplementary methods such as MR-Egger, as well as median and mode-based methods. Results: In the forward analysis, schizophrenia was associated with slightly higher low-density lipoprotein (LDL) cholesterol levels (0.013 SD change in LDL per log odds increase in schizophrenia risk, 95% CI, 0.001-0.024 SD; p = 0.027) and total cholesterol levels (0.013 SD change in total cholesterol per log odds increase in schizophrenia risk, 95% CI, 0.002-0.025 SD; p = 0.023). However, these associations did not survive multiple testing corrections. There was no evidence of a causal effect of cardiometabolic traits on schizophrenia in the reverse analysis. Discussion: Dyslipidemia and obesity in schizophrenia patients are unlikely to be driven primarily by schizophrenia itself. Therefore, lifestyle, diet, antipsychotic drugs side effects, as well as shared mechanisms for metabolic dysfunction and schizophrenia such as low-grade systemic inflammation could be possible reasons for the apparent increased risk of metabolic disease in people with schizophrenia. Further research is needed to examine the shared immune mechanism hypothesis.

Psychotic disorders as a framework for precision psychiatry

People with psychotic disorders can show marked interindividual variations in the onset of illness, responses to treatment and relapse, but they receive broadly similar clinical care. Precision psychiatry is an approach that aims to stratify people with a given disorder according to different clinical outcomes and tailor treatment to their individual needs. At present, interindividual differences in outcomes of psychotic disorders are difficult to predict on the basis of clinical assessment alone. Therefore, current research in psychosis seeks to build models that predict outcomes by integrating clinical information with a range of biological measures. Here, we review recent progress in the application of precision psychiatry to psychotic disorders and consider the challenges associated with implementing this approach in clinical practice.

A Marked Low-Grade Inflammation and a Significant Deterioration in Metabolic Status in First-Episode Schizophrenia: A Five-Year Follow-Up Study

The objective of this study was to evaluate how schizophrenia spectrum disorders and applied long-term (5.1 years) antipsychotic (AP) treatment affect the serum level of acylcarnitines (ACs), cytokines and metabolic biomarkers and to characterize the dynamics of inflammatory and metabolic changes in the early course of the disorder. A total of 112 adults participated in the study (54 patients with first-episode psychosis (FEP) and 58 control subjects). Biomolecule profiles were measured at the onset of first-episode psychosis and 0.6 years and 5.1 years after the initiation of APs. The results of the present study confirmed that specific metabolic-inflammatory imbalance characterizes AP-naïve patients. Short-term (0.6-years) AP treatment has a favourable effect on psychotic symptoms, as well as the recovery of metabolic flexibility and resolution of low-level inflammation. However, 5.1 years of AP treatment resulted in weight gain and increased serum levels of interleukin (IL)-2, IL-4, IL-6, IL-10, interferon-γ, hexoses, acetylcarnitine, short-chain ACs (C3, C4) and long-chain ACs (C16:2, C18:1, C18:2). In conclusion, despite the improvement in psychotic symptoms, 5.1 years of AP treatment was accompanied by a pronounced metabolic-inflammatory imbalance, which was confirmed by the presence of enhanced pro-inflammatory activity and increased obesity with changes in the metabolism of carbohydrates, lipids, and their metabolites.

Metabolic trajectories in childhood and adolescence: Effects on risk for schizophrenia

Abnormal glucose and lipid metabolism is common in antipsychotic-naive first-episode patients with schizophrenia, but it is unclear whether these changes can already be seen in premorbid or prodromal period, before the first psychotic episode. We examined insulin, total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and triglyceride trajectories in children and adolescents (9-18 years old), who were later diagnosed with schizophrenia, any non-affective psychosis (NAP) or affective disorder (AD). The study population consisted of a general population-based cohort "The Cardiovascular Risk in Young Finns Study", started in 1980 (n = 3596). Psychiatric diagnoses were derived from the Health Care Register up to the year 2018. Multivariate statistical analysis indicated no significant differences in insulin or lipid levels in children and adolescents who later developed schizophrenia (n = 41) compared to the cohort control group (n = 3202). In addition, no changes in these parameters were seen in the NAP (n = 74) or AD (n = 156) groups compared to the controls, but lower triglyceride levels in childhood/adolescence associated with earlier diagnosis of psychotic disorder in the NAP group. Taken together, our results do not support any gross-level insulin or lipid changes during childhood and adolescence in individuals with later diagnosis of schizophrenia-spectrum disorder. Since changes in glucose and lipid metabolism can be observed in neuroleptic-naive patients with schizophrenia, we hypothesize that the more marked metabolic changes develop during the prodrome closer to the onset of the first psychotic episode. The findings have relevance for studies on developmental hypotheses of schizophrenia.

Plasmalogen in the brain: Effects on cognitive functions and behaviors attributable to its properties

Ether phospholipid compositions are altered in the plasma or brain of patients with brain disorders, such as Alzheimer and Parkinson's disease, including those with psychiatric disorders like schizophrenia and bipolar disorders. Notably, plasmenyl ethanolamine has a unique chemical structure, i.e., a vinyl-ether bond at the sn-1 position, which mainly links with polyunsaturated fatty acids (PUFAs) at the sn-2 position. Those characteristic moieties give plasmalogen molecules unique biophysical and chemical properties that modulate membrane trafficking, lipid rafts, intramolecular PUFA moieties, and oxidative states. Previous reports suggested that a deficiency in plasmenyl ethanolamine leads to disturbances of the myelin structure, synaptic neurotransmission and intracellular signaling, apoptosis of neurons, and neuroinflammation, accompanied by cognitive disturbances and aberrant behaviors like hyperactivity in mice. Therefore, this review summarizes the relationship between the biological functions of plasmalogen. We also proposed biophysical properties that alter brain phospholipid compositions related to aberrant behaviors and cognitive dysfunction. Finally, a brief review of possible remedial plasmalogen replacement therapies for neurological, psychiatric, and developmental disorders attributable to disturbed plasmalogen compositions in the organs and cells was conducted.

Potential for prediction of psychosis and bipolar disorder in Child and Adolescent Mental Health Services: a longitudinal register study of all people born in Finland in 1987

Current strategies to predict psychosis identify only a small proportion of individuals at risk. Additional strategies are needed to increase capacity for pre-diction and prevention of serious mental illness, ideally during childhood and adolescence. One possible approach would be to investigate systems in which psychosis risk factors are concentrated during childhood. One notable such system is represented by Child and Adolescent Mental Health Services (CAMHS). Although psychotic disorders are uncommon in CAMHS, many risk factors for psychosis are highly prevalent in young people who enter this system. We hypothesized, therefore, that youth attending CAMHS would be a high-risk group for psychosis if followed into adulthood and, furthermore, that CAMHS systems would capture a substantial proportion of future psychosis cases. We constructed a total population cohort study of all Finns born in 1987 (N=55,875), linking together extensive register data on health care contacts from birth through age 28 years. We identified all individuals diagnosed with a psychotic or bipolar disorder by age 28 (N=1,785). The risk of psychosis/bipolar disorder by age 28 years was 1.8% for individuals who had not attended CAMHS during childhood or adolescence, whereas it was 12.8% for those with a history of any outpatient CAMHS contact (odds ratio, OR=7.9, 95% CI: 7.2-8.7). Furthermore, the risk of psychosis/bipolar disorder by age 28 years was 2.3% for individuals without a history of inpatient CAMHS admission, whereas it was 24.0% for those with a history of inpatient CAMHS admission (OR=13.3, 95% CI: 11.9-14.9), and 36.5% for those with a history of inpatient CAMHS admission in adolescence (age 13-17 years) (OR=24.2, 95% CI: 21.2-27.6). Individuals who attended CAMHS but received no mental disorder diagnosis had an equally high risk of subsequently developing a psychosis/bipolar disorder as individuals who did receive a diagnosis (OR=0.9, 99.5% CI: 0.7-1.1). Compared to other CAMHS attendees, individuals who developed psychosis or bipolar disorder were more likely to have had an initial CAMHS diagnosis of depressive or other mood disorder (OR=2.3, 99.5% CI: 1.6-3.0) and disruptive behaviour disorder (OR=1.7, 99.5% CI: 1.2-2.5). Of all psychosis/bipolar diagnoses by age 28 years, 50.2% occurred in individuals who had, at some point in childhood or adolescence, attended CAMHS, indicating that CAMHS represent not only a high-risk but also a high-capacity system for prediction of psychosis/bipolar disorder. These findings suggest an enormous, untapped potential for large-scale psychosis/bipolar disorder prediction and prevention research within existing specialist CAMHS.

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

Emerging evidence has demonstrated overlapping biological abnormalities underlying schizophrenia (SCZ), bipolar disorder (BP), and major depressive disorder (MDD); these overlapping abnormalities help explain the high heterogeneity and the similarity of patients within and among diagnostic categories. This study aimed to identify transdiagnostic subtypes of these psychiatric disorders based on lipidomics abnormalities. We performed discriminant analysis to identify lipids that classified patients (N = 349, 112 with SCZ, 132 with BP, and 105 with MDD) and healthy controls (N = 198). Ten lipids that mainly regulate energy metabolism, inflammation, oxidative stress, and fatty acylation of proteins were identified. We found two subtypes (named Cluster 1 and Cluster 2 subtypes) across patients with SCZ, BP, and MDD by consensus clustering analysis based on the above 10 lipids. The distribution of clinical diagnosis, functional impairment measured by Global Assessment of Functioning (GAF) scales, and brain white matter abnormalities measured by fractional anisotropy (FA) and radial diffusivity (RD) differed in the two subtypes. Patients within the Cluster 2 subtype were mainly SCZ and BP patients and featured significantly elevated RD along the genu of corpus callosum (GCC) region and lower GAF scores than patients within the Cluster 1 subtype. The SCZ and BP patients within the Cluster 2 subtype shared similar biological patterns; that is, these patients had comparable brain white matter abnormalities and functional impairment, which is consistent with previous studies. Our findings indicate that peripheral lipid abnormalities might help identify homogeneous transdiagnostic subtypes across psychiatric disorders.

Hippocampal circuit dysfunction in psychosis

Despite strong evidence of the neurodevelopmental origins of psychosis, current pharmacological treatment is not usually initiated until after a clinical diagnosis is made, and is focussed on antagonising striatal dopamine receptors. These drugs are only partially effective, have serious side effects, fail to alleviate the negative and cognitive symptoms of the disorder, and are not useful as a preventive treatment. In recent years, attention has turned to upstream brain regions that regulate striatal dopamine function, such as the hippocampus. This review draws together these recent data to discuss why the hippocampus may be especially vulnerable in the pathophysiology of psychosis. First, we describe the neurodevelopmental trajectory of the hippocampus and its susceptibility to dysfunction, exploring this region's proneness to structural and functional imbalances, metabolic pressures, and oxidative stress. We then examine mechanisms of hippocampal dysfunction in psychosis and in individuals at high-risk for psychosis and discuss how and when hippocampal abnormalities may be targeted in these groups. We conclude with future directions for prospective studies to unlock the discovery of novel therapeutic strategies targeting hippocampal circuit imbalances to prevent or delay the onset of psychosis.

Impaired Membrane Lipid Homeostasis in Schizophrenia

BACKGROUND AND HYPOTHESIS

Multiple lines of clinical, biochemical, and genetic evidence suggest that disturbances of membrane lipids and their metabolism are probably involved in the etiology of schizophrenia (SCZ). Lipids in the membrane are essential to neural development and brain function, however, their role in SCZ remains largely unexplored.

STUDY DESIGN

Here we investigated the lipidome of the erythrocyte membrane of 80 patients with SCZ and 40 healthy controls using ultra-performance liquid chromatography-mass spectrometry. Based on the membrane lipids profiling, we explored the potential mechanism of membrane phospholipids metabolism.

STUDY RESULTS

By comparing 812 quantified lipids, we found that in SCZ, membrane phosphatidylcholines and phosphatidylethanolamines, especially the plasmalogen, were significantly decreased. In addition, the total polyunsaturated fatty acids (PUFAs) in the membrane of SCZ were significantly reduced, resulting in a decrease in membrane fluidity. The accumulation of membrane oxidized lipids and the level of peripheral lipid peroxides increased, suggesting an elevated level of oxidative stress in SCZ. Further study of membrane-phospholipid-remodeling genes showed that activation of PLA2s and LPCATs expression in patients, supporting the imbalance of unsaturated and saturated fatty acyl remodeling in phospholipids of SCZ patients.

CONCLUSIONS

Our results suggest that the mechanism of impaired membrane lipid homeostasis is related to the activated phospholipid remodeling caused by excessive oxidative stress in SCZ. Disordered membrane lipids found in this study may reflect the membrane dysfunction in the central nervous system and impact neurotransmitter transmission in patients with SCZ, providing new evidence for the membrane lipids hypothesis of SCZ.

Identification of cerebrospinal fluid and serum metabolomic biomarkers in first episode psychosis patients

Psychotic disorders are currently diagnosed by examining the patient's mental state and medical history. Identifying reliable diagnostic, monitoring, predictive, or prognostic biomarkers would be useful in clinical settings and help to understand the pathophysiology of schizophrenia. Here, we performed an untargeted metabolomics analysis using ultra-high pressure liquid chromatography coupled with time-of-flight mass spectroscopy on cerebrospinal fluid (CSF) and serum samples of 25 patients at their first-episode psychosis (FEP) manifestation (baseline) and after 18 months (follow-up). CSF and serum samples of 21 healthy control (HC) subjects were also analyzed. By comparing FEP and HC groups at baseline, we found eight CSF and 32 serum psychosis-associated metabolites with non-redundant identifications. Most remarkable was the finding of increased CSF serotonin (5-HT) levels. Most metabolites identified at baseline did not differ between groups at 18-month follow-up with significant improvement of positive symptoms and cognitive functions. Comparing FEP patients at baseline and 18-month follow-up, we identified 20 CSF metabolites and 90 serum metabolites that changed at follow-up. We further utilized Ingenuity Pathway Analysis (IPA) and identified candidate signaling pathways involved in psychosis pathogenesis and progression. In an extended cohort, we validated that CSF 5-HT levels were higher in FEP patients than in HC at baseline by reversed-phase high-pressure liquid chromatography. To conclude, these findings provide insights into the pathophysiology of psychosis and identify potential psychosis-associated biomarkers.

Dopamine-induced pruning in monocyte-derived-neuronal-like cells (MDNCs) from patients with schizophrenia

The long lapse between the presumptive origin of schizophrenia (SCZ) during early development and its diagnosis in late adolescence has hindered the study of crucial neurodevelopmental processes directly in living patients. Dopamine, a neurotransmitter consistently associated with the pathophysiology of SCZ, participates in several aspects of brain development including pruning of neuronal extensions. Excessive pruning is considered the cause of the most consistent finding in SCZ, namely decreased brain volume. It is therefore possible that patients with SCZ carry an increased susceptibility to dopamine's pruning effects and that this susceptibility would be more obvious in the early stages of neuronal development when dopamine pruning effects appear to be more prominent. Obtaining developing neurons from living patients is not feasible. Instead, we used Monocyte-Derived-Neuronal-like Cells (MDNCs) as these cells can be generated in only 20 days and deliver reproducible results. In this study, we expanded the number of individuals in whom we tested the reproducibility of MDNCs. We also deepened the characterization of MDNCs by comparing its neurostructure to that of human developing neurons. Moreover, we studied MDNCs from 12 controls and 13 patients with SCZ. Patients' cells differentiate more efficiently, extend longer secondary neurites and grow more primary neurites. In addition, MDNCs from medicated patients expresses less D1R and prune more primary neurites when exposed to dopamine. Haloperidol did not influence our results but the role of other antipsychotics was not examined and thus, needs to be considered as a confounder.

Plasma lipid alterations in young adults with psychotic experiences: A study from the Avon Longitudinal Study of Parents and Children cohort

BACKGROUND

Psychotic experiences (PEs) are associated with an increased risk of future psychotic and non-psychotic mental disorders. The identification of biomarkers of PEs may provide insights regarding the underlying pathophysiology.

METHODS

The current study applied targeted lipidomic approaches to compare plasma lipid profiles in participants from the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort who did (n = 206) or did not (n = 206) have PEs when aged approximately 24 years.

RESULTS

In total, 202 lipids including 8 lipid classes were measured by using ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS). Eight lipid clusters were generated. Thirteen individual lipids were nominally significantly higher in the PEs group compared to the control group. After correction for multiple comparisons, 9 lipids comprising 3 lysophosphatidylcholines (LPCs), 2 phosphatidylcholines (PCs) and 4 triacylglycerols (TGs) remained significant. In addition, PEs cases had increased levels of TGs and LPCs with a low double bond count.

CONCLUSIONS

These findings indicate plasma lipidomic abnormalities in individuals experiencing PEs. The lipidomic profile measures could aid our understanding of the underlying pathophysiological mechanisms.

The Relationship Between Grey Matter Volume and Clinical and Functional Outcomes in People at Clinical High Risk for Psychosis

Objective

To examine the association between baseline alterations in grey matter volume (GMV) and clinical and functional outcomes in people at clinical high risk (CHR) for psychosis.

Methods

265 CHR individuals and 92 healthy controls were recruited as part of a prospective multi-center study. After a baseline assessment using magnetic resonance imaging (MRI), participants were followed for at least two years to determine clinical and functional outcomes, including transition to psychosis (according to the Comprehensive Assessment of an At Risk Mental State, CAARMS), level of functioning (according to the Global Assessment of Functioning), and symptomatic remission (according to the CAARMS). GMV was measured in selected cortical and subcortical regions of interest (ROI) based on previous studies (ie orbitofrontal gyrus, cingulate gyrus, gyrus rectus, inferior temporal gyrus, parahippocampal gyrus, striatum, and hippocampus). Using voxel-based morphometry, we analysed the relationship between GMV and clinical and functional outcomes.

Results

Within the CHR sample, a poor functional outcome (GAF < 65) was associated with relatively lower GMV in the right striatum at baseline (P < .047 after Family Wise Error correction). There were no significant associations between baseline GMV and either subsequent remission or transition to psychosis.

Conclusions

In CHR individuals, lower striatal GMV was associated with a poor level of overall functioning at follow-up. This finding was not related to effects of antipsychotic or antidepressant medication. The failure to replicate previous associations between GMV and later psychosis onset, despite studying a relatively large sample, is consistent with the findings of recent large-scale multi-center studies.

Plasma metabolic alterations and potential biomarkers in individuals at clinical high risk for psychosis

BACKGROUND

Early identification and treatment of clinical high-risk for psychosis (CHRP) are critical to prevent the onset of psychosis, but there is no objective biomarker for CHR-P diagnosis.

METHODS

Ninety medication naïve CHR-P subjects and eighty-six healthy controls (HCs) were recruited. The metabolic profiles of plasma samples were acquired using an untargeted metabolomics approach based on ultra-high-performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry. The obtained data were further mapped on the Kyoto Encyclopedia of Genes and Genomes for pathway analysis, and an ensemble learning method was applied to identify diagnostic biomarkers. Bayesian linear regression model was then used to explore predicative biomarkers of conversion to psychosis. Receiver-operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic or predicative value of potential biomarkers.

RESULTS

A total of one hundred and four differential metabolites and forty-eight differential pathways were identified. A panel of five metabolites was found that could effectively discriminate CHR-P from HCs with area under the ROC curve of 1 in the training set (70% of the samples) and 0.997 in the testing set (30% of the samples). The biosynthesis of unsaturated fatty acids pathway perturbed most significantly in CHR-P subjects. Twenty-three CHR-P subjects converted to psychotic disorders during two-year follow-up, and increased 1-stearoyl-2-arachidonoyl-sn-glycerol in plasma was potentially associated with the higher risk of conversion to psychosis.

CONCLUSIONS

These findings demonstrate the alterations of plasma metabolic profiles in CHR-P population, which may deliver valuable biomarkers for early identification and outcome prediction of CHR-P.

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.

Prenatal and Childhood Immuno-Metabolic Risk Factors for Adult Depression and Psychosis

Depression and psychosis have a developmental component to their origin. Epidemiologic evidence, which we synthesize in this nonsystematic review, suggests that early-life infection, inflammation, and metabolic alterations could play a role in the etiology of these psychiatric disorders. The risk of depression and psychosis is associated with prenatal maternal and childhood infections, which could be mediated by impaired neurodevelopment. Evidence suggests linear dose-response associations between elevated concentrations of circulating inflammatory markers in childhood, particularly the inflammatory cytokine interleukin 6, and the risk for depression and psychosis subsequently in early adulthood. Childhood inflammatory markers are also associated with persistence of depressive symptoms subsequently in adolescence and early adulthood. Developmental trajectories reflecting persistently high insulin levels during childhood and adolescence are associated with a higher risk of psychosis in adulthood, whereas increased adiposity during and after puberty is associated with the risk of depression. Together, these findings suggest that higher levels of infection, inflammation, and metabolic alterations commonly seen in people with depression and psychosis could be a cause for, rather than simply a consequence of, these disorders. Therefore, early-life immuno-metabolic alterations, as well as factors influencing these alterations such as adversity or maltreatment, could represent targets for prevention of these psychiatric disorders. Inflammation could also be an important treatment target for depression and psychosis. The field requires further research to examine sensitive periods when exposure to such immuno-metabolic alterations is most harmful. Interventional studies are also needed to test the potential usefulness of targeting early-life immuno-metabolic alterations for preventing adult depression and psychosis.

A Comprehensive Evaluation of Cross-Omics Blood-Based Biomarkers for Neuropsychiatric Disorders

The identification of peripheral multi-omics biomarkers of brain disorders has long been hindered by insufficient sample size and confounder influence. This study aimed to compare biomarker potential for different molecules and diseases. We leveraged summary statistics of five blood quantitative trait loci studies (N = 1980 to 22,609) and genome-wide association studies (N = 9725 to 500,199) from 14 different brain disorders, such as Schizophrenia (SCZ) and Alzheimer's Disease (AD). We applied summary-based and two-sample Mendelian Randomization to estimate the associations between blood molecules and brain disorders. We identified 524 RNA, 807 methylation sites, 29 proteins, seven cytokines, and 22 metabolites having a significant association with at least one of 14 brain disorders. Simulation analyses indicated that a cross-omics combination of biomarkers had better performance for most disorders, and different disorders could associate with different omics. We identified an 11-methylation-site model for SCZ diagnosis (Area Under Curve, AUC = 0.74) by analyzing selected candidate markers in published datasets (total N = 6098). Moreover, we constructed an 18-methylation-sites model that could predict the prognosis of elders with mild cognitive impairment (hazard ratio = 2.32). We provided an association landscape between blood cross-omic biomarkers and 14 brain disorders as well as a suggestion guide for future clinical discovery and application.

The interaction of lipids and inflammatory markers predict negative symptom severity in patients with schizophrenia

Finding biological predictors and novel mechanisms underlying negative symptoms of schizophrenia is of significant importance given the lack of effective treatments. Increasing data support a role for metabolic dysfunction and inflammation in reward processing deficits in psychiatric illness. Herein, we found an interaction between lipids and inflammation as a predictor of worse negative symptom severity in individuals with schizophrenia. Future studies may seek to further elucidate this relationship and thereby reveal novel treatment targets for negative symptoms.

Meta-Analysis of Brain Gene Expression Data from Mouse Model Studies of Maternal Immune Activation Using Poly(I:C)

Maternal immune activation (MIA) is a known risk factor for schizophrenia (SCZ) and autism spectrum disorder (ASD) and is often modelled in animal studies in order to study the effect of prenatal infection on brain function including behaviour and gene expression. Although the effect of MIA on gene expression are highly heterogeneous, combining data from multiple gene expression studies in a robust method may shed light on the true underlying biological effects caused by MIA and this could inform studies of SCZ and ASD. This study combined four RNA-seq and microarray datasets in an overlap analysis and ranked meta-analysis in order to investigate genes, pathways and cell types dysregulated in the MIA mouse models. Genes linked to SCZ and ASD and crucial in neurodevelopmental processes including neural tube folding, regulation of cellular stress and neuronal/glial cell differentiation were among the most consistently dysregulated in these ranked analyses. Gene ontologies including K+ ion channel function, neuron and glial cell differentiation, synaptic structure, axonal outgrowth, cilia function and lipid metabolism were also strongly implicated. Single-cell analysis identified excitatory and inhibitory cell types in the cortex, hippocampus and striatum that may be affected by MIA and are also enriched for genes associated with SCZ, ASD and cognitive phenotypes. This points to the cellular location of molecular mechanisms that may be consistent between the MIA model and neurodevelopmental disease, improving our understanding of its utility to study prenatal infection as an environmental stressor.

Metabolomic connections between schizophrenia, antipsychotic drugs and metabolic syndrome: A variety of players

BACKGROUND

Diagnosis of schizophrenia lacks of reliable medical diagnostic tests and robust biomarkers applied to clinical practice. Schizophrenic patients undergoing treatment with antipsychotics suffer a reduced life expectancy due to metabolic disarrangements that co-exist with their mental illness and predispose them to develop metabolic syndrome, also exacerbated by medication. Metabolomics is an emerging and potent technology able to accelerate this biomedical research. <P> Aim: This review focus on a detailed vision of the molecular mechanisms involved both in schizophrenia and antipsychotic-induced metabolic syndrome, based on innovative metabolites that consistently change in nascent metabolic syndrome, drug-naïve, first episode psychosis and/or schizophrenic patients compared to healthy subjects. <P> Main lines: Supported by metabolomic approaches, although not exclusively, noteworthy variations are reported mainly through serum samples of patients and controls in several scenes: 1) alterations in fatty acids, inflammatory response indicators, amino acids and biogenic amines, biometals and gut microbiota metabolites (schizophrenia); 2) alterations in metabolites involved in carbohydrate and gut microbiota metabolism, inflammation and oxidative stress (metabolic syndrome), some of them shared with the schizophrenia scene; 3) alterations of cytokines secreted by adipose tissue, phosphatidylcholines, acylcarnitines, Sirtuin 1, orexin-A and changes in microbiota composition (antipsychotic-induced metabolic syndrome). <P> Conclusion: Novel insights into the pathogenesis of schizophrenia and metabolic side-effects associated to its antipsychotic treatment, represent an urgent request for scientifics and clinicians. Leptin, carnitines, adiponectin, insulin or interleukin-6 represent some examples of candidate biomarkers. Cutting-edge technologies like metabolomics have the power of strengthen research for achieving preventive, diagnostic and therapeutical solutions for schizophrenia.

Brain lipidomics as a rising field in neurodegenerative contexts: Perspectives with Machine Learning approaches

Lipids are essential for cellular functioning considering their role in membrane composition, signaling, and energy metabolism. The brain is the second most abundant organ in terms of lipid concentration and diversity only after adipose tissue. However, in the central system (CNS) lipid dysregulation has been linked to the etiology, progression, and severity of neurodegenerative diseases such as Alzheimeŕs, Parkinson, and Multiple Sclerosis. Advances in the human genome and subsequent sequencing technologies allowed us the study of lipidomics as a promising approach to diagnosis and treatment of neurodegeneration. Lipidomics advances rapidly increased the amount and quality of data allowing the integration with other omic types as well as implementing novel bioinformatic and quantitative tools such as machine learning (ML). Integration of lipidomics data with ML, as a powerful quantitative predictive approach, led to improvements in diagnostic biomarker prediction, clinical data integration, network, and systems approaches for neural behavior, novel etiology markers for inflammation, and neurodegeneration progression and even Mass Spectrometry image analysis. In this sense, by exploiting lipidomics data with ML is possible to improve the identification of new biomarkers or unveil new molecular mechanisms associated with lipid impairment across neurodegeneration. In this review, we present the lipidomic neurobiology state-of-the-art highlighting its potential applications to study neurodegenerative conditions. Also, we present theoretical background, applications, and advances in the integration of lipidomics with ML. This review opens the door to new approaches in this rising field.