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

Immune-based Machine learning Prediction of Diagnosis and Illness State in Schizophrenia and Bipolar Disorder

BACKGROUND

Schizophrenia and bipolar disorder frequently face significant delay in diagnosis, leading to being missed or misdiagnosed in early stages. Both disorders have also been associated with trait and state immune abnormalities. Recent machine learning-based studies have shown encouraging results using diagnostic biomarkers in predictive models, but few have focused on immune-based markers. Our main objective was to develop supervised machine learning models to predict diagnosis and illness state in schizophrenia and bipolar disorder using only a panel of peripheral kynurenine metabolites and cytokines.

METHODS

The cross-sectional I-GIVE cohort included hospitalized acute bipolar patients (n = 205), stable bipolar outpatients (n = 116), hospitalized acute schizophrenia patients (n = 111), stable schizophrenia outpatients (n = 75) and healthy controls (n = 185). Serum kynurenine metabolites, namely tryptophan (TRP), kynurenine (KYN), kynurenic acid (KA), quinaldic acid (QUINA), xanthurenic acid (XA), quinolinic acid (QUINO) and picolinic acid (PICO) were quantified using liquid chromatography-tandem mass spectrometry (LC-MS/MS), while V-plex Human Cytokine Assays were used to measure cytokines (interleukin-6 (IL-6), IL-8, IL-17, IL-12/IL23-P40, tumor necrosis factor-alpha (TNF-ɑ), interferon-gamma (IFN-γ)). Supervised machine learning models were performed using JMP Pro 17.0.0. We compared a primary analysis using nested cross-validation to a split set as sensitivity analysis. Post-hoc, we re-ran the models using only the significant features to obtain the key markers.

RESULTS

The models yielded a good Area Under the Curve (AUC) (0.804, Positive Prediction Value (PPV) = 86.95; Negative Prediction Value (NPV) = 54.61) for distinguishing all patients from controls. This implies that a positive test is highly accurate in identifying the patients, but a negative test is inconclusive. Both schizophrenia patients and bipolar patients could each be separated from controls with a good accuracy (SCZ AUC 0.824; BD AUC 0.802). Overall, increased levels of IL-6, TNF-ɑ and PICO and decreased levels of IFN-γ and QUINO were predictive for an individual being classified as a patient. Classification of acute versus stable patients reached a fair AUC of 0.713. The differentiation between schizophrenia and bipolar disorder yielded a poor AUC of 0.627.

CONCLUSIONS

This study highlights the potential of using immune-based measures to build predictive classification models in schizophrenia and bipolar disorder, with IL-6, TNF-ɑ, IFN-γ, QUINO and PICO as key candidates. While machine learning models successfully distinguished schizophrenia and bipolar disorder from controls, the challenges in differentiating schizophrenic from bipolar patients likely reflect shared immunological pathways by the both disorders and confounding by a larger state-specific effect. Larger multi-centric studies and multi-domain models are needed to enhance reliability and translation into clinic.

Differential inflammatory profiles in carriers of reciprocal 22q11.2 copy number variants

BACKGROUND

Genetic copy number variants (CNVs; i.e., a deletion or duplication) at the 22q11.2 locus confer increased risk of neuropsychiatric disorders and immune dysfunction. Inflammatory profiles of 22q11.2 CNV carriers can shed light on gene-immune relationships that may be related to neuropsychiatric symptoms. However, little is known about inflammation and its relationship to clinical phenotypes in 22q11.2 CNV carriers. Here, we investigate differences in peripheral inflammatory markers in 22q11.2 CNV carriers and explore their relationship with psychosis risk symptoms and sleep disturbance.

METHODS

Blood samples and clinical assessments were collected from 22q11.2 deletion (22qDel) carriers (n=45), 22q11.2 duplication (22qDup) carriers (n=29), and typically developing (TD) control participants (n=92). Blood plasma levels of pro-inflammatory cytokines, including interleukin-6 (IL-6), interleukin-8 (IL-8), tumor necrosis factor-alpha (TNF-α) and interferon-gamma (IFN-γ), and anti-inflammatory cytokine interleukin-10 (IL-10) were measured using a MesoScale Discovery multiplex immunoassay. Plasma levels of C-reactive protein (CRP) were measured using Enzyme-linked Immunosorbent Assay (ELISA). Linear mixed effects models controlling for age, sex, and body mass index were used to: a) examine group differences in inflammatory markers between 22qDel, 22qDup, and TD controls, b) test differences in inflammatory markers between 22qDel carriers with psychosis risk symptoms (22qDelPS+) and those without (22qDelPS-), and c) conduct an exploratory analysis testing the effect of sleep disturbance on inflammation in 22qDel and 22qDup carriers. A false discovery rate correction was used to correct for multiple comparisons.

RESULTS

22qDup carriers exhibited significantly elevated levels of IL-8 relative to TD controls (q<0.001) and marginally elevated IL-8 levels relative to 22qDel carriers (q=0.08). There were no other significant differences in inflammatory markers between the three groups (q>0.13). 22qDelPS+ exhibited increased levels of IL-8 relative to both 22qDelPS- (q=0.02) and TD controls (p=0.002). There were no relationships between sleep and inflammatory markers that survived FDR correction (q>0.14).

CONCLUSION

Our results suggest that CNVs at the 22q11.2 locus may have differential effects on inflammatory processes related to IL-8, a key mediator of inflammation produced by macrophages and microglia. Further, these IL-8-mediated inflammatory processes may be related to psychosis risk symptoms in 22qDel carriers. Additional research is required to understand the mechanisms contributing to these differential levels of IL-8 between 22q11.2 CNV carriers and IL-8's association with psychosis risk.

Impact of second-generation antipsychotics monotherapy or combined therapy in cytokine, lymphocyte subtype, and thyroid antibodies for schizophrenia: a retrospective study

BACKGROUND

Schizophrenia (SCZ) shares high clinical relevance with the immune system, and the potential interactions of psychopharmacological drugs with the immune system are still an overlooked area. Here, we aimed to identify whether the second-generation antipsychotics (SGA) monotherapy or combined therapy of SGA with other psychiatric medications influence the routine blood immunity biomarkers of patients with SCZ.

METHODS

Medical records of inpatients with SCZ from January 2019 to June 2023 were retrospectively screened from June 2023 to August 2023. The demographic data and peripheral levels of cytokines (IL-2, IL-4, IL-6, TNF-α, INF-γ, and IL-17 A), lymphocyte subtype proportions (CD3+, CD4+, CD8 + T-cell, and natural killer (NK) cells), and thyroid autoimmune antibodies (thyroid peroxidase antibody (TPOAb), and antithyroglobulin antibody (TGAb)) were collected and analyzed.

RESULTS

30 drug-naïve patients, 64 SGA monotherapy (20 for first-episode SCZ, 44 for recurrent SCZ) for at least one week, 39 combined therapies for recurrent SCZ (18 with antidepressant, 10 with benzodiazepine, and 11 with mood stabilizer) for at least two weeks, and 23 used to receive SGA monotherapy (had withdrawn for at least two weeks) were included despite specific medication. No difference in cytokines was found between the SGA monotherapy sub-groups (p > 0.05). Of note, SGA monotherapy appeared to induce a down-regulation of IFN-γ in both first (mean [95% confidence interval]: 1.08 [0.14-2.01] vs. 4.60 [2.11-7.08], p = 0.020) and recurrent (1.88 [0.71-3.05] vs. 4.60 [2.11-7.08], p = 0.027) episodes compared to drug-naïve patients. However, the lymphocyte proportions and thyroid autoimmune antibodies remained unchanged after at least two weeks of SGA monotherapy (p > 0.05). In combined therapy groups, results mainly resembled the SGA monotherapy for recurrent SCZ (p > 0.05).

CONCLUSION

The study demonstrated that SGA monotherapy possibly achieved its comfort role via modulating IFN-γ, and SGA combined therapy showed an overall resemblance to monotherapy.

Immunophenotypes in psychosis: is it a premature inflamm-aging disorder?

Immunopsychiatric field has rapidly accumulated evidence demonstrating the involvement of both innate and adaptive immune components in psychotic disorders such as schizophrenia. Nevertheless, researchers are facing dilemmas of discrepant findings of immunophenotypes both outside and inside the brains of psychotic patients, as discovered by recent meta-analyses. These discrepancies make interpretations and interrogations on their roles in psychosis remain vague and even controversial, regarding whether certain immune cells are more activated or less so, and whether they are causal or consequential, or beneficial or harmful for psychosis. Addressing these issues for psychosis is not at all trivial, as immune cells either outside or inside the brain are an enormously heterogeneous and plastic cell population, falling into a vast range of lineages and subgroups, and functioning differently and malleably in context-dependent manners. This review aims to overview the currently known immunophenotypes of patients with psychosis, and provocatively suggest the premature immune "burnout" or inflamm-aging initiated since organ development as a potential primary mechanism behind these immunophenotypes and the pathogenesis of psychotic disorders.

Exploring causal mechanisms of psychosis risk

Robust epidemiological evidence of risk and protective factors for psychosis is essential to inform preventive interventions. Previous evidence syntheses have classified these risk and protective factors according to their strength of association with psychosis. In this critical review we appraise the distinct and overlapping mechanisms of 25 key environmental risk factors for psychosis, and link these to mechanistic pathways that may contribute to neurochemical alterations hypothesised to underlie psychotic symptoms. We then discuss the implications of our findings for future research, specifically considering interactions between factors, exploring universal and subgroup-specific factors, improving understanding of temporality and risk dynamics, standardising operationalisation and measurement of risk and protective factors, and developing preventive interventions targeting risk and protective factors.

Association between serum cytokines and timeframe for conversion from clinical high-risk to psychosis

AIM

Although many studies have explored the link between inflammatory markers and psychosis, there is a paucity of research investigating the temporal progression in individuals at clinical high-risk (CHR) who eventually develop full psychosis. To address this gap, we investigated the correlation between serum cytokine levels and Timeframe for Conversion to Psychosis (TCP) in individuals with CHR.

METHODS

We enrolled 53 individuals with CHR who completed a 5-year follow-up with a confirmed conversion to psychosis. Granulocyte macrophage-colony stimulating factor (GM-CSF), interleukin (IL)-1β, 2, 6, 8, 10, tumor necrosis factor-α (TNF-α), and vascular endothelial growth factor (VEGF) levels were measured at baseline and 1-year. Correlation and quantile regression analyses were performed.

RESULTS

The median TCP duration was 14 months. A significantly shorter TCP was associated with higher levels of TNF-α (P = 0.022) and VEGF (P = 0.016). A negative correlation was observed between TCP and TNF-α level (P = 0.006) and VEGF level (P = 0.04). Quantile regression indicated negative associations between TCP and GM-CSF levels below the 0.5 quantile, IL-10 levels below the 0.3 quantile, IL-2 levels below the 0.25 quantile, IL-6 levels between the 0.65 and 0.75 quantiles, TNF-α levels below the 0.8 quantile, and VEGF levels below the 0.7 quantile. A mixed linear effects model identified significant time effects for IL-10 and IL-2, and significant group effects for changes in IL-2 and TNF-α.

CONCLUSIONS

Our findings underscore that a more pronounced baseline inflammatory state is associated with faster progression of psychosis in individuals with CHR. This highlights the importance of considering individual inflammatory profiles during early intervention and of tailoring preventive measures for risk profiles.

The Underlying Neurobiological Mechanisms of Psychosis: Focus on Neurotransmission Dysregulation, Neuroinflammation, Oxidative Stress, and Mitochondrial Dysfunction

Psychosis, defined as a set of symptoms that results in a distorted sense of reality, is observed in several psychiatric disorders in addition to schizophrenia. This paper reviews the literature relevant to the underlying neurobiology of psychosis. The dopamine hypothesis has been a major influence in the study of the neurochemistry of psychosis and in development of antipsychotic drugs. However, it became clear early on that other factors must be involved in the dysfunction involved in psychosis. In the current review, it is reported how several of these factors, namely dysregulation of neurotransmitters [dopamine, serotonin, glutamate, and γ-aminobutyric acid (GABA)], neuroinflammation, glia (microglia, astrocytes, and oligodendrocytes), the hypothalamic-pituitary-adrenal axis, the gut microbiome, oxidative stress, and mitochondrial dysfunction contribute to psychosis and interact with one another. Research on psychosis has increased knowledge of the complexity of psychotic disorders. Potential new pharmacotherapies, including combinations of drugs (with pre- and probiotics in some cases) affecting several of the factors mentioned above, have been suggested. Similarly, several putative biomarkers, particularly those related to the immune system, have been proposed. Future research on both pharmacotherapy and biomarkers will require better-designed studies conducted on an all stages of psychotic disorders and must consider confounders such as sex differences and comorbidity.

Peripheral and central biomarkers associated with inflammation in antipsychotic naïve first episode psychosis: Pilot studies

BACKGROUND

Elevated serum pro-inflammatory molecules have been reported in early psychosis. What is not known is whether peripheral inflammatory biomarkers are associated with CNS biomarkers. In the brain, release of pro-inflammatory molecules by microglial hyperactivity may lead to neuronal apoptosis seen in neurodegenerative disorders and account for loss of brain tissue observed in psychotic disorders. Neurochemical changes, including elevated glutamate levels, are also associated with neuroinflammation, present in early psychosis and change with antipsychotic treatment.

METHODS

Antipsychotic naïve patients with first episode psychosis (FEP) were studied as part of a collaborative project of neuroinflammation. In Study 1 we explored associations between plasma inflammatory molecules and neurometabolites in the dorsal caudate using magnetic resonance spectroscopy (1H-MRS) in N = 13 FEP participants. Study 2 examined the relationship between inflammatory molecules in the Plasma and CSF in N = 20 FEP participants.

RESULTS

In Study 1, the proinflammatory chemokine MDC/CCL22 and IL10 were significantly positively correlated with Glutamate and Glx (glutamate + glutamine) levels in the dorsal caudate. In Study 2, plasma inflammatory molecules (MIP1β/CCL4, MCP1/CCL2, Eotaxin-1/CCL11 and TNFα) were significantly correlated with CSF MIP1β/CCL4, IL10, MCP1/CCL2 and Fractalkine/CX3CL1 and symptoms ratings.

DISCUSSION

Plasma inflammatory biomarkers are elevated in early psychosis, associated with neurochemical markers as well as CSF inflammatory molecules found in neurodegenerative disorders. Future studies are needed that combine both peripheral and central biomarkers in both FEP and HC to better understand a potential neuroinflammatory subtype of psychosis likely to respond to targeted interventions.

A randomised double-blind placebo-controlled trial of minocycline and/or omega-3 fatty acids added to treatment as usual for at risk Mental States: The NAYAB study

BACKGROUND

Inflammatory mechanisms are thought to contribute to the onset of psychosis in persons with an at-risk mental state (ARMS). We investigated whether the anti-inflammatory properties of minocycline and omega-3 polyunsaturated fatty acids (omega-3), alone or synergistically, would prevent transition to psychosis in ARMS in a randomised, double-blind, placebo-controlled trial in Pakistan.

METHODS

10,173 help-seeking individuals aged 16-35 years were screened using the Prodromal Questionaire-16. Individuals scoring 6 and over were interviewed using the Comprehensive Assessment of At-Risk Mental States (CAARMS) to confirm ARMS. Participants (n = 326) were randomised to minocycline, omega-3, combined minocycline and omega-3 or to double placebo for 6 months. The primary outcome was transition to psychosis at 12 months.

FINDINGS

Forty-five (13.8 %) participants transitioned to psychosis. The risk of transition was greater in those randomised to omega-3 alone or in combination with minocycline (17.3.%), compared to 10.4 % in those not exposed to omega-3; a risk-ratio (RR) of 1.67, 95 % CI [0.95, 2.92] p = 0.07. The RR for transitions on minocycline vs. no minocycline was 0.86, 95 % CI [0.50, 1.49] p > 0.10. In participants who did not become psychotic, CAARMS and depression symptom scores were reduced at six and twelve months (mean CAARMS difference = 1.43; 95 % CI [0.33, 1.76] p < 0.01 in those exposed to omega-3. Minocycline did not affect CAARMS or depression scores.

INTERPRETATION

In keeping with other studies, omega-3 appears to have beneficial effects on ARMS and mood symptom severity but it increased transition to psychosis, which may reflect metabolic or developmental consequences of chronic poor nutrition in the population. Transition to psychosis was too rare to reveal a preventative effect of minocycline but minocycline did not improve symptom severity. ARMS symptom severity and transition to psychosis appear to have distinct pathogeneses which are differentially modulated by omega-3 supplementation.

FUNDING

The study was funded by the Stanley Research Medical Institute.

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.

Systemic inflammation and cortical neurochemistry in never-medicated first episode-psychosis individuals

Studies of cellular and cytokine profiles have contributed to the inflammation hypothesis of schizophrenia; however, precise markers of inflammatory dysfunction remain elusive. A number of proton magnetic resonance spectroscopy (1H-MRS) studies in patients with first-episode psychosis (FEP) have shown higher brain levels of metabolites such as glutamate, myo-inositol (mI) and choline-containing compounds (tCho), suggesting neuroinflammation. Here, we present peripheral inflammatory profiles in antipsychotic-naive FEP patients and age-and-sex matched healthy controls, as well as cortical glutamate, mI and tCho levels using 1H-MRS. Inflammatory profiles were analyzed using cytokine production by peripheral blood mononuclear cells, that were either spontaneous or stimulated, in 48 FEP patients and 23 controls. 1H-MRS of the medial prefrontal cortex was obtained in 29 FEP patients and 18 controls. Finally, 16 FEP patients were rescanned after 4 weeks of treatment (open-label) with Risperidone. FEP patients showed a higher proportion of proinflammatory Th1/Th17 subset, and an increased spontaneous production of Interleukin (IL)-6, IL-2 and IL-4 compared with the control group. Results obtained from 1H-MRS showed no significant difference in either glutamate, mI or tCho between FEP and control groups. At baseline, CD8% showed a negative correlation with glutamate in FEP patients; after 4 weeks of risperidone treatment, the FEP group exhibited a decrease in glutamate levels which positively correlated with CD4 + T cells. Nevertheless, these correlations did not survive correction for multiple comparisons. FEP patients show evidence of immune dysregulation, affecting both the innate and adaptive immune response, with a predominantly Th2 signature. These findings, along with the changes produced by antipsychotic treatment, could be associated with both systemic and central inflammatory processes in schizophrenia.