Interleukin‐2/interleukin‐6 imbalance correlates with conversion to psychosis from a clinical high‐risk state

Zhang, Tianhong; Wei, Yanyan; Zeng, Jiahui; Ye, JiaYi; Tang, Xiaochen; Xu, Li-Hua; Hu, YeGang; Cui, Huiru; Tang, Yingying; Wang, Jijun

doi:10.1111/pcn.13476

Cited by 6 publications

(9 citation statements)

References 9 publications

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“…Our findings suggest a possible role of serum levels of IL-2 and IL-6 as state markers, which were shown to be particularly increased in CHR individuals who later converted to psychosis. Our pilot study [38] in 37 CHR individuals demonstrated that later conversion to psychosis is associated with lower baseline serum IL-2 levels, lower serum IL-6 levels, and higher IL-2/IL-6 ratios. This finding revealed a potential imbalance in Th1/ Th2 patterns in the course of conversion, suggesting that adding inflammatory biomarkers may improve predictive accuracy [39,40].…”

Section: Follow-up Differencesmentioning

confidence: 70%

Changes in Inflammatory Markers in Clinical High Risk of Developing Psychosis

et al. 2023

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Introduction: Immune alterations are associated with the progression of psychosis. However, there are few studies designed to longitudinally measure inflammatory biomarkers during psychotic episodes. We aimed to assess changes in biomarkers from the prodromal phase to psychotic episodes in individuals with clinical high risk (CHR) of psychosis and compare converters and non-converters to psychosis as well as healthy controls (HCs). Methods: We enrolled 394 individuals with CHR and 100 HCs. A total of 263 individuals with CHR completed the 1-year follow-up, and 47 had converted to psychosis. Interleukin (IL)-1β, 2, 6, 8, 10, tumor necrosis factor-α (TNF-α), and vascular endothelial growth factor levels were measured at baseline and 1 year after completion of the clinical assessment. Results: The baseline serum levels of IL-10, IL-2, and IL-6 were significantly lower in the conversion group than in the non-conversion group (IL-10, p = 0.010; IL-2, p = 0.023; IL-6, p = 0.012) and HC (IL-6: p = 0.034). Self-controlled comparisons showed that IL-2 changed significantly (p = 0.028), and IL-6 levels tended toward significance (p = 0.088) in the conversion group. In the non-conversion group, serum levels of TNF-α (p = 0.017) and VEGF (p = 0.037) changed significantly. Repeated measures analysis of variance revealed a significant time effect related to TNF-α (F = 4.502, p = 0.037, effect size (η2) = 0.051), a group effect related to IL-1β (F = 4.590, p = 0.036, η2 = 0.062), and IL-2 (F = 7.521, p = 0.011, η2 = 0.212), but no time × group effect. Discussion: Alterations in the serum levels of inflammatory cytokines were found to precede the first episode of psychosis in the CHR population, particularly for those who later converted to psychosis. Longitudinal analysis supports the varied roles of cytokines in individuals with CHR with later psychotic conversion or non-conversion outcomes.

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Section: Follow-up Differencesmentioning

confidence: 70%

Changes in Inflammatory Markers in Clinical High Risk of Developing Psychosis

et al. 2023

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“…The occurrence and development of psychosis is not only a change in behavioral appearance or brain function but also a characteristic change in the characteristics of immunoinflammatory markers in the early stage. The SHARP team 29,34,35 found that the imbalance of The results suggest that antipsychotic drugs should not be used prematurely in the at-risk population 27,28,40 as they are only valuable for <15% of the CHR population of a certain subtype [41][42][43] ; it is necessary to carry out individualized new intervention technologies for CHR subtypes of different biological dimensions. 3 Approximately 30% of the CHR population may recover naturally without intervention, and a large proportion of CHR are teenagers.…”

Section: Immune Dimension Of Inflammatory Cytokines and Complement Pr...mentioning

confidence: 99%

Comprehensive review of multidimensional biomarkers in the ShangHai At Risk for Psychosis (SHARP) program for early psychosis identification

Zhang,

Xu,

Tang

et al. 2023

PCN Reports

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Psychosis is recognized as one of the largest contributors to nonfatal health loss, and early identification can largely improve routine clinical activity by predicting the psychotic course and guiding treatment. Clinicians have used the clinical high‐risk for psychosis (CHR) paradigm to better understand the risk factors that contribute to the onset of psychotic disorders. Clinical factors have been widely applied to calculate the individualized risks for conversion to psychosis 1–2 years later. However, there is still a dearth of valid biomarkers to predict psychosis. Biomarkers, in the context of this paper, refer to measurable biological indicators that can provide valuable information about the early identification of individuals at risk for psychosis. The aim of this paper is to critically review studies assessing CHR and suggest possible biomarkers for application of prediction. We summarized the studies on biomarkers derived from the findings of the ShangHai at Risk for Psychosis (SHARP) program, including those that are considered to have the most potential. This comprehensive review was conducted based on expert opinions within the SHARP research team, and the selection of studies and results presented in this paper reflects the collective expertise of the team in the field of early psychosis identification. The three dimensions with potential candidates include neuroimaging dimension of brain structure and function, electrophysiological dimension of event‐related potentials (ERPs), and immune dimension of inflammatory cytokines and complement proteins, which proved to be useful in supporting the prediction of psychosis from the CHR state. We suggest that these three dimensions could be useful as risk biomarkers for treatment optimization. In the future, when available for the integration of multiple dimensions, clinicians may be able to obtain a comprehensive report with detailed information of psychosis risk and specific indications about preferred prevention.

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“…Of the 17 included studies, 16 were prognostic model development studies [15][16][17][18][19][36][37][38][39][40][41][42][43][44][45][46] and one study was a prognostic model external validation study [47]. All studies were conducted in outpatients.…”

Section: Study Characteristicsmentioning

confidence: 99%

“…All studies were conducted in outpatients. There were five models developed in the Shanghai At Risk for Psychosis (SHARP) study [18,19] and the extension of that study [44][45][46]. There were three model development studies each for the North American Prodrome Longitudinal Study (NAPLS 2) cohort [36,38,41] and for the EU Gene-Environment Interaction (EU-GEI) study [15,16,42].…”

Section: Study Characteristicsmentioning

confidence: 99%

“…Zhang et al [46] and Mondelli et al [42] did not find evidence for the predictive ability of IL-8 for transition to psychotic disorder. Zhang et al 2022 [44], Zhang et al 2023a [45] and Mondelli et al [42] all included different cytokine ratios in their models (IL-1β/IL-6, IL-2/IL-6 and IL-10/IL-6 respectively) with the aim of capturing inflammatory balance. Chan et al [47] and Mongan et al [15] both included Alpha-2-Macroglobulin as a predictor in their final models, though coefficients were in opposite directions.…”

Section: Narrative Synthesismentioning

confidence: 99%

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

Byrne,

Mongan,

Murphy

et al. 2023

Preprint

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BackgroundAccumulating 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.MethodsDatabases (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 risk of bias and applicability of the studies. A narrative synthesis of included studies was performed.Results17 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.DiscussionWhile 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.

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Interleukin‐2/interleukin‐6 imbalance correlates with conversion to psychosis from a clinical high‐risk state

Cited by 6 publications

References 9 publications

Changes in Inflammatory Markers in Clinical High Risk of Developing Psychosis

Changes in Inflammatory Markers in Clinical High Risk of Developing Psychosis

Comprehensive review of multidimensional biomarkers in the ShangHai At Risk for Psychosis (SHARP) program for early psychosis identification

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

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