Peripheral biomarkers of treatment-resistant schizophrenia: Genetic, inflammation and stress perspectives

Niacin skin flushing response in patients with schizophrenia: Associations with the efficacy of modified electroconvulsive therapy and clinical symptoms

OBJECTIVE

Schizophrenia (SZ) is a group of chronic neurodevelopmental disorders, and antipsychotic medication is the main clinical treatment. However, approximately one-third of patients demonstrate inadequate response to these medications, which is termed treatment-resistant schizophrenia (TRS). The primary objective of this study was to explore the clinical characteristics of patients with TRS, including positive, negative, general psychotic symptoms and niacin skin flushing response (NSFR), which is considered an auxiliary diagnostic biomarker for SZ, and the improvement of these characteristics after modified electroconvulsive therapy (MECT).

METHODS

This study included 32 patients with TRS, who received MECT combined with antipsychotic medication (SZ-MECT group), and 30 patients with non-treatment-resistant SZ (N-TRS), who received antipsychotic medication alone (SZ-N group). We assessed disease severity with the Positive and Negative Syndrome Scale (PANSS) and NSFR at baseline and at weeks 2, 4, and 6 in all patients.

RESULTS

At baseline, the SZ-MECT group had greater PANSS scores (P < 0.0001) and a more blunted NSFR (P = 0.020) than the SZ-N group did, and the PANSS-TOTAL scores were negatively correlated with the NSFR scores (r = -0.361, P = 0.0039). At week 6 after treatment, the SZ-MECT group presented significantly improved PANSS scores (P < 0.0001) and NSFR blunting (P = 0.010) that were comparable with those in the SZ-N group.

CONCLUSION

Compared with patients with N-TRS, patients with TRS presented more severe clinical symptoms and a more blunted NSFR, which significantly improved after MECT treatment. The NSFR may have good clinical application potential as an auxiliary assessment of severity and MECT efficacy in patients with schizophrenia.

Current perspectives on the recognition and management of treatment-resistant schizophrenia: challenges and opportunities

INTRODUCTION

Treatment-resistant schizophrenia (TRS) significantly impacts patients with schizophrenia, leading to a high disease burden, reduced quality of life, and functional impairment. Many patients fail to respond to standard antipsychotic treatments, requiring specialized therapeutic approaches. Clozapine remains the only approved treatment for patients with TRS, demonstrating effectiveness in reducing symptoms, hospitalizations, and risk of suicide. However, its use is often delayed due to concerns about adverse events, and the need for ongoing monitoring.

AREAS COVERED

This critical perspective incorporates insights from psychiatrists in Greece and a comprehensive literature analysis that includes clinical guidelines and systematic reviews. It highlights strategies for early diagnosis and timely initiation of clozapine, while emphasizing practical challenges in its use. Recommendations emphasize reducing treatment delays and overcoming barriers such as inadequate training and hesitancy among clinicians. A comprehensive literature search was conducted on PubMed, Google Scholar, and Cochrane Library without any date restrictions to ensure a thorough review of available evidence. The initial literature search was carried out in September 2024, with a subsequent search conducted in March 2025.

EXPERT OPINION

International guidelines consistently recommend clozapine as the first-line treatment for patients with TRS; nevertheless, the authors advocate enhanced awareness to optimize use. Most adverse events can be effectively managed with proper oversight, and early initiation is crucial to improving remission rates and the quality of life of patients with TRS. There is a need for systemic improvements in clinical practice, which requires evidence-based guidance to better address treatment efficacy in this challenging patient population.

Theoretical Potential of Hericium Erinaceus Supplementation as an Add-On to Antipsychotics in Chronic and Treatment-Resistant Schizophrenia

Schizophrenia is a serious mental illness that is a leading cause of disability worldwide. While antipsychotic agents are the most effective medications, up to one-third of patients experience treatment resistance, and approximately one-sixth of patients experience ultra-resistant illness. There is a growing body of evidence that inflammation, oxidative stress, and neurodegeneration may be contributing to pathophysiology and treatment response. Several agents with potential to improve inflammation and oxidative stress have been investigated, with some showing statistically significant benefits, though robust improvement in symptomatology has not been consistently demonstrated. Hericium erinaceus (HE) is an edible mushroom that has been used as a medicinal food for centuries. In pre-clinical studies, it has demonstrated anti-inflammatory, antioxidant, neuroprotective, and neurogenesis-promoting effects. The specific inflammatory markers that are impacted by HE align well with biomarkers shown to be altered in chronic and treatment resistant schizophrenia. Most clinical studies to date have assessed HE for the treatment of mild cognitive impairment, depression, and anxiety. In clinical studies, HE has been well tolerated, with the most common adverse effect of gastrointestinal disturbance. Given potential for HE to improve inflammation, reduce oxidative stress, and promote adult neurogenesis in the hippocampus, it is theorized that HE may have beneficial effects on symptomatology when used as an add-on to antipsychotic therapy in those with residual symptoms or treatment resistance. The goal of this review is to describe theoretical benefits and potential dosing strategies based on pre-clinical and clinical data.

Diagnosis of Schizophrenia and Its Subtypes Using MRI and Machine Learning

PURPOSE

The neurobiological heterogeneity present in schizophrenia remains poorly understood. This likely contributes to the limited success of existing treatments and the observed variability in treatment responses. Our objective was to employ magnetic resonance imaging (MRI) and machine learning (ML) algorithms to improve the classification of schizophrenia and its subtypes.

METHOD

We utilized a public dataset provided by the UCLA (University of California, Los Angeles) Consortium for Neuropsychiatric Research, containing structural MRI and resting-state fMRI (rsfMRI) data. We integrated all individuals within the dataset diagnosed with schizophrenia (N = 50), along with age- and gender-matched healthy individuals (N = 50). We extracted volumetrics of 66 subcortical and thickness of 72 cortical regions. Additionally, we obtained four graph-based measures for 116 intracranial regions from rsfMRI data, including degree, betweenness centrality, participation coefficient, and local efficiency. Employing conventional ML methods, we sought to distinguish the patients with schizophrenia from healthy individuals. Furthermore, we applied the methods for discriminating subtypes of schizophrenia. To streamline the feature set, various feature selection techniques were applied. Moreover, a validation phase involved employing the model on a dataset domestically acquired using the same imaging assessments (N = 13). Finally, we explored the correlation between neuroimaging features and behavioral assessments.

FINDING

The classification accuracy reached as high as 79% in distinguishing schizophrenia patients from healthy in the UCLA dataset. This result was achieved by the k-nearest neighbor algorithm, utilizing 12 brain neuroimaging features, selected by the feature selection method of minimum redundancy maximum relevance (MRMR). The model demonstrated effectiveness (72% accuracy) in estimating the patient's label for a new dataset acquired domestically. Using a linear support vector machine (SVM) on 62 features obtained from MRMR, patients with schizophrenic subtypes were classified with an accuracy of 64%. The highest Spearman correlation coefficient between the neuroimaging features and behavioral assessments was observed between the degree of the postcentral gyrus and mean reaction time in the verbal capacity task (r = 0.49, p = 0.001).

CONCLUSION

The findings of this study underscore the utility of MRI and ML algorithms in enhancing the diagnostic process for schizophrenia. Furthermore, these methods hold promise for detecting both brain-related abnormalities and cognitive impairments associated with this disorder.

Multimodal prediction of the need of clozapine in treatment resistant schizophrenia; a pilot study in first-episode psychosis

As many as one third of the patients diagnosed with schizophrenia do not respond to first-line antipsychotic medication. This group may benefit from the atypical antipsychotic medication clozapine, but initiation of treatment is often delayed, which may worsen prognosis. Predicting which patients do not respond to traditional antipsychotic medication at the onset of symptoms would provide fast-tracked treatment for this group of patients. We collected data from patient records of 38 first-episode psychosis patients, of whom seven did not respond to traditional antipsychotic medications. We used clinical data including medical records, voxel-based morphometry MRI data and inter-subject correlation fMRI data, obtained during movie viewing, to predict future treatment resistance. Using a neural network model, we correctly predicted future treatment resistance in six of the seven treatment resistance patients and 25 of 31 patients who did not require clozapine treatment. Prediction improved significantly when using imaging data in tandem with clinical data. The accuracy of the neural network model was significantly higher than the accuracy of a support vector machine algorithm. These results support the notion that treatment resistant schizophrenia could represent a separate entity of psychotic disorders, characterized by morphological and functional changes in the brain which could represent biomarkers detectable at early onset of symptoms.

Circulating inflammatory cytokines influencing schizophrenia: a Mendelian randomization study

Introduction

Schizophrenia (SCZ) is a severe psychiatric disorder whose pathophysiology remains elusive. Recent investigations have underscored the significance of systemic inflammation, particularly the impact of circulating inflammatory proteins, in SCZ.

Methods

This study explores the potential causal association between certain inflammatory proteins and SCZ. Bidirectional Mendelian randomization (MR) analyses were conducted utilizing data from expansive genome-wide association studies (GWAS). Data regarding circulating inflammatory proteins were sourced from the GWAS Catalog database, encompassing 91 inflammatory cytokines. SCZ-related data were derived from the Finngen database, incorporating 47,696 cases and 359,290 controls. Analytical methods such as inverse variance weighted, MR-Egger, weighted median, simple mode, and weighted mode were employed to evaluate the association between inflammatory cytokines and SCZ. Sensitivity analyses were also performed to affirm the robustness of the results.

Results

Following FDR adjustment, significant associations were observed between levels of inflammatory cytokines, including Fibroblast Growth Factor 5 (OR = 1.140, 95%CI = 1.045, 1.243, p = 0.003, FDR=0.015), C-C Motif Chemokine 4 (OR = 0.888, 95%CI = 0.816, 0.967, p = 0.006, FDR = 0.015), C-X-C Motif Chemokine 1 (OR = 0.833, 95%CI = 0.721, 0.962, p = 0.013, FDR = 0.064), and C-X-C Motif Chemokine 5 (OR = 0.870, 95%CI = 0.778, 0.973, p = 0.015, FDR = 0.074), and the risk of SCZ.

Conclusion

Our results from MR analysis suggest a potential causal link between circulating inflammatory cytokines and SCZ, thereby enriching our understanding of the interactions between inflammation and SCZ. Furthermore, these insights provide a valuable foundation for devising therapeutic strategies targeting inflammation.

Relationship between blood-based inflammatory indices and clinical score of schizophrenia patients: A cross-sectional study

Schizophrenia is a severe mental disorder that may involve inflammation. Inflammatory indices, such as the neutrophil to lymphocyte ratio (NLR), the monocyte to lymphocyte ratio (MLR), the platelet to lymphocyte ratio (PLR), and the systemic inflammation index (SII), are simple and inexpensive measures of inflammation that have been associated with various diseases. However, few studies have compared these indices and their relationships with clinical symptoms in schizophrenia. We conducted a cross-sectional study of 121 schizophrenia patients (101 males, 20 females). We measured the blood-based inflammatory indices (NLR, MLR, PLR, and SII) and assessed the clinical symptoms of schizophrenia using the Positive and Negative Syndrome Scale (PANSS). Statistical analyses were performed to examine the correlations and effects of the inflammatory indices on PANSS scores. We found that NLR, MLR, PLR, and SII were positively correlated with PANSS total score, PANSS positive score, PANSS negative score, and general psychopathology score (adjusted P < 0.02 for all correlations). Subgroup analysis showed that correlations between inflammatory indices and the clinical scores differed by gender. In males, all inflammatory indices were positively correlated with all clinical scores. On the other hand, in females, only NLR and SII were positively correlated with all clinical scores. After adjusting for confounders, we also found that NLR was a predictor of PANSS total score (β = 23, adjusted P < 0.02), PANSS positive score (β = 2.6, adjusted P = 0.03), PANSS negative score (β = 6.8, adjusted P < 0.02), and PANSS general psychopathology score (β = 13.6, adjusted P < 0.02), while SII was only a predictor for PANSS total score (β = -0.00003, adjusted P = 0.01) and general psychopathology scores (β = -0.00002, adjusted P < 0.02). These findings suggest that inflammation is involved in the pathophysiology and clinical manifestations of schizophrenia, and that blood-based inflammatory indices may serve as screening tools or indicators for the inflammatory status and severity of symptoms of schizophrenia patients.

Role of the immune-kynurenine pathway in treatment-resistant schizophrenia

BACKGROUND

The immune-inflammatory response system (IRS) and kynurenine pathway (KP) have been implicated in the pathophysiology of schizophrenia. Studies have shown inflammation-related effects on KP metabolism in patients with schizophrenia. This study investigated the relationship between KP metabolites, IRS, and the compensatory immune-regulatory reflex system (CIRS) in patients with treatment-resistant schizophrenia (TRS).

METHODS

Patients with (n = 53) and without TRS (n = 47), and healthy controls (HCs, n = 49) were enrolled. We quantified plasma levels of pro-inflammatory cytokines (interleukin [IL]-1β, IL-2, IL-6, soluble(s)IL-6 receptor, IL-8, IL-12, IL-17, IL-18, interferon-γ, and tumor necrosis factor[TNF]-α) and anti-inflammatory cytokines (IL-1 receptor antagonist, IL-4, IL-10, tumor growth factor [TGF]-β1, TGF-β2, soluble (s) IL-2 receptor subunit α, sIL-2 receptor subunit β, and sTNF-α receptor 1) and calculated the IRS/CIRS ratio. We also tested serum metabolites of the KP, including kynurenine (KYN), kynurenic acid (KYNA), and quinolinic acid (QUIN), along with the QUIN/KYNA ratio.

RESULTS

Patients with TRS had significantly higher IRS/CIRS ratio than non-TRS patients (p = 0.002) and HCs (p = 0.007), and significantly lower KYN (p = 0.001) and KYNA (p = 0.01) levels than HCs. Binary logistic regression analysis revealed that a younger age at illness onset (odds ratio [OR] = 0.91, p = 0.02) and a higher IRS/CIRS ratio (OR = 1.22; p = 0.007) were risk factors for patients with TRS. After further adjusted for age of onset, the QUIN/KYNA ratio (β = 0.97; p = 0.02) significantly moderated the relationship between IRS/CIRS and TRS, showing that in the higher QUIN/KYNA condition, higher IRS/CIRS ratio were significantly and more likely to be associated with patients with TRS (β = 0.12, z = 3.19, p = 0.001), whereas in the low QUIN/KYNA condition, the association between IRS/CIRS ratio and TRS was weak and insignificant.

CONCLUSIONS

The peripheral immune response was imbalanced in TRS and was preferentially directed towards the IRS compared to patients without TRS and healthy controls, which is likely to play a role in neurotoxicity. Additionally, peripheral KP activation was also imbalanced, as evidenced by significantly reduced KYN and KYNA levels in patients with TRS compared to healthy controls, but none of KP metabolisms were significantly difference in non-TRS patients compared to healthy controls. QUIN/KYNA ratio involving to the degree of activation of NMDA receptors, indicated the neurotoxic level of the KP activation. The interaction between IRS/CIRS and QUIN/KYNA ratio was significant in predicting TRS, and our findings suggest a potential role for the immune-kynurenine pathway in TRS pathogenesis.

Gene expression imputation provides clinical and biological insights into treatment-resistant schizophrenia polygenic risk

Genome-wide association studies (GWAS) have revealed the polygenic nature of treatment-resistant schizophrenia TRS. Gene expression imputation allowed the translation of GWAS results into regulatory mechanisms and the construction of gene expression (GReX) risk scores (GReX-RS).  In the present study we computed GReX-RS from the largest GWAS of TRS to assess its association with clinical features. We perform transcriptome imputation in the largest GWAS of TRS to find GReX associated with TRS using brain tissues. Then, for each tissue, we constructed a GReX-RS of the identified genes in a sample of 254 genotyped first episode of psychosis (FEP) patients to test its association with clinical phenotypes, including clinical symptomatology, global functioning and cognitive performance. Our analysis provides evidence that the polygenic basis of TRS includes genetic variants that modulate the expression of certain genes in certain brain areas (substantia nigra, hippocampus, amygdala and frontal cortex), which at the same time are related to clinical features in FEP patients, mainly persistence of negative symptoms and cognitive alterations in sustained attention, which have also been suggested as clinical predictors of TRS. Our results provide a clinical explanation of the polygenic architecture of TRS and give more insight into the biological mechanisms underlying TRS.

Relationship between clinical efficacy and plasma concentration-dose ratio of risperidone in patients with schizophrenia

This study aimed to retrospectively explore the relationship between clinical efficacy and plasma concentration-dose ratio of risperidone (RIS) in 252 patients with schizophrenia taking RIS orally. After the same dose of RIS treatment, the plasma concentration of RIS/9-hydroxyrisperidone (9-OH-RIS), the total plasma concentration of RIS, and the ratio of the steady-state plasma concentration to the daily dose of the total active product (C/D) showed individual difference. The RIS plasma concentration was significantly higher in patients taking high doses than those taking lower doses ( P  = 0.003). There was a statistically significant difference in C/D ratio between males and females ( P  = 0.003). There were significant differences in ratio of C/D and the total plasma concentration of RIS between patients under 60 years and over 60 years ( P  = 0.016; P  = 0.005). Logistic regression analysis showed that the therapeutic effect and adverse reactions of RIS were correlated with the ratio of C/D in patients with schizophrenia ( P  = 0.038; P  < 0.001). It has been suggested that the importance of monitoring of the plasma concentration of RIS in patients with schizophrenia and the ratio of C/D may be used as the reference for RIS personalized treatment.

Predictors of successful anti-inflammatory drug trials in patients with schizophrenia: A meta-regression and critical commentary

Given evidence pointing toward a role for immune dysregulation in the pathogenesis of schizophrenia, anti-inflammatory agents are promising adjunctive treatments that have potential to support a causal relationship for inflammation and psychopathology and lead to novel treatments for individuals. Indeed, previous meta-analyses have demonstrated small-to-medium effect sizes (ES) in favor of various anti-inflammatory agents, though there is significant heterogeneity and challenges in the interpretation of this literature. Identifying predictors, including sociodemographic variables, trial duration, and/or symptoms themselves, of successful anti-inflammatory trials may help identify which patients who might benefit from these compounds. We performed a meta-regression analysis of 63 adjunctive anti-inflammatory trial arms (2232 patients randomized to adjunctive anti-inflammatory agents and 2207 patients randomized to placebo).Potential predictors of effect size estimates for changes in psychopathology scores from baseline to endpoint included geography, trial duration, sample size, age, sex, race, smoking, body mass index, illness duration, age of onset of psychosis, study quality score and psychopathology scores (total and subscale) at baseline. Geography (β = 0.31, p = 0.011), smaller sample size (β = 0.33, p = 0.009), and higher study quality score (β = 0.44, p < 0.001) were significant predictors of larger ES estimates for change in total psychopathology in favor of anti-inflammatory agents. Smaller sample size (β = 0.37, p = 0.034) and higher study quality score (β = 0.55, p = 0.003) were significant predictors of larger ES estimates for change in negative psychopathology in favor of anti-inflammatory agents. Higher study quality score (β = 0.46, p = 0.019) was a significant predictor of larger ES estimates for change in general psychopathology in favor of anti-inflammatory agents. These findings should be interpreted with caution given concerns of publication bias regarding the geographic differences and small study effects. The lack of an association with other demographic variables should be seen as a primary limitation of the literature that needs to be considered in future studies. The association with study quality score suggests that future anti-inflammatory trials must consider demographic variables known to be associated with inflammation (e.g., BMI and smoking) and evidence of increased baseline inflammation should be incorporated in study design. Moreover, evidence of target engagement and endpoints thoughts to be associated with increased inflammation should be considered as well.

The Involvement of PGRMC1 Signaling in Cognitive Impairment Induced by Long-Term Clozapine Treatment in Rats

INTRODUCTION

Progesterone receptor component 1 (PGRMC1) has been identified as a potential target in atypical antipsychotic drug-induced metabolic disturbances as well as neuroprotection in the central nervous system. In our study, we aimed to figure out the essential role of PGRMC1 signaling pathway underlying clozapine-induced cognitive impairment.

METHODS

In male SD rats, we utilized recombinant adeno-associated viruses (BBB 2.0) and the specific inhibitor of PGRMC1 (AG205) to regulate the expression of PGRMC1 in the brain, with a special focus on the hippocampus. Treatments of clozapine and AG205 were conducted for 28 days, and subsequent behavioral tests including modified elevated plus maze and Morris water maze were conducted to evaluate the cognitive performance. Hippocampal protein expressions were measured by Western blotting.

RESULTS

Our study showed that long-term clozapine administration led to cognitive impairment as confirmed by behavioral tests as well as histopathological examination in the hippocampus. Clozapine inhibited neural survival through the PGRMC1/EGFR/GLP1R-PI3K-Akt signaling pathway, leading to a decrease in the downstream survival factor, brain-derived neurotrophic factor (BDNF), and simultaneously promoted neural apoptosis in the rat hippocampus. Intriguingly, by targeting at the hippocampal PGRMC1, we found that inhibiting PGRMC1 mimics, while its upregulation notably mitigates clozapine-induced cognitive impairment through PGRMC1 and its downstream signaling pathways.

CONCLUSION

PGRMC1-overexpression could protect hippocampus-dependent cognitive impairment induced by clozapine. This effect appears to arise, in part, from the upregulated expression of PGRMC1/EGFR/GLP1R and the activation of downstream PI3K-Akt-BDNF and caspase-3 signaling pathways.

Schizophrenia Synaptic Pathology and Antipsychotic Treatment in the Framework of Oxidative and Mitochondrial Dysfunction: Translational Highlights for the Clinics and Treatment

Schizophrenia is a worldwide mental illness characterized by alterations at dopaminergic and glutamatergic synapses resulting in global dysconnectivity within and between brain networks. Impairments in inflammatory processes, mitochondrial functions, energy expenditure, and oxidative stress have been extensively associated with schizophrenia pathophysiology. Antipsychotics, the mainstay of schizophrenia pharmacological treatment and all sharing the common feature of dopamine D2 receptor occupancy, may affect antioxidant pathways as well as mitochondrial protein levels and gene expression. Here, we systematically reviewed the available evidence on antioxidants' mechanisms in antipsychotic action and the impact of first- and second-generation compounds on mitochondrial functions and oxidative stress. We further focused on clinical trials addressing the efficacy and tolerability of antioxidants as an augmentation strategy of antipsychotic treatment. EMBASE, Scopus, and Medline/PubMed databases were interrogated. The selection process was conducted in respect of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) criteria. Several mitochondrial proteins involved in cell viability, energy metabolism, and regulation of oxidative systems were reported to be significantly modified by antipsychotic treatment with differences between first- and second-generation drugs. Finally, antioxidants may affect cognitive and psychotic symptoms in patients with schizophrenia, and although the evidence is only preliminary, the results indicate that further studies are warranted.

The deficit subtype of schizophrenia is associated with a pro-inflammatory phenotype but not with altered levels of zonulin: Findings from a case-control study

There is evidence that subclinical inflammation and increased gut permeability might be involved in the pathophysiology of schizophrenia. Less is known about these phenomena in patients with the deficit subtype of schizophrenia (D-SCZ) characterized by primary and enduring negative symptoms. Therefore, in the present study we aimed to compare the levels of zonulin (the marker of gut permeability) and immune-inflammatory markers in patients with D-SCZ, those with non-deficit schizophrenia (ND-SCZ) and healthy controls (HCs). A total of 119 outpatients with schizophrenia and 120 HCs were enrolled. The levels of 26 immune-inflammatory markers and zonulin were determined in serum samples. The following between-group differences were significant after adjustment for multiple testing and the effects of potential confounding factors: 1) higher levels of interleukin(IL)- 1β and C-reactive protein (CRP) in patients with D-SCZ compared to those with ND-SCZ and HCs; 2) higher levels of tumor necrosis factor-α and RANTES in both groups of patients with schizophrenia compared to HCs and 3) higher levels of IL-17 in patients with D-SCZ compared to HCs. No significant between-group differences in zonulin levels were found. Higher levels of IL-1β and CRP were associated with worse performance of attention after adjustment for age, education and chlorpromazine equivalents. Also, higher levels of IL-1β were correlated with greater severity of negative symptoms after adjustment for potential confounding factors. In conclusion, individuals with D-SCZ are more likely to show subclinical inflammation. However, findings from the present study do not support the hypothesis that this phenomenon is secondary to increased gut permeability.

Treatment-Resistant Schizophrenia, Clozapine Resistance, Genetic Associations, and Implications for Precision Psychiatry: A Scoping Review

Treatment-resistant schizophrenia (TRS) is often associated with severe burden of disease, poor quality of life and functional impairment. Clozapine is the gold standard for the treatment of TRS, although it is also known to cause significant side effects in some patients. In view of the burgeoning interest in the role of genetic factors in precision psychiatry, we conducted a scoping review to narratively summarize the current genetic factors associated with TRS, clozapine resistance and side effects to clozapine treatment. We searched PubMed from inception to December 2022 and included 104 relevant studies in this review. Extant evidence comprised associations between TRS and clozapine resistance with genetic factors related to mainly dopaminergic and serotoninergic neurotransmitter systems, specifically, TRS and rs4680, rs4818 within COMT, and rs1799978 within DRD2; clozapine resistance and DRD3 polymorphisms, CYP1A2 polymorphisms; weight gain with LEP and SNAP-25 genes; and agranulocytosis risk with HLA-related polymorphisms. Future studies, including replication in larger multi-site samples, are still needed to elucidate putative risk genes and the interactions between different genes and their correlations with relevant clinical factors such as psychopathology, psychosocial functioning, cognition and progressive changes with treatment over time in TRS and clozapine resistance.