Antipsychotic-Associated Weight Gain and Clinical Improvement Under Clozapine Treatment

Blood Cell Count Ratios at Baseline are Associated with Initial Clinical Response to Clozapine in Treatment-Resistant, Clozapine-Naïve, Schizophrenia-Spectrum Disorder

BACKGROUND

Clozapine is the recommended treatment for managing treatment-resistant schizophrenia (TRS), and immunological mechanisms may be involved in its unique antipsychotic efficacy. This study investigated whether baseline immune abnormalities measured with blood cell count ratios can predict the clinical response after initiating treatment with clozapine in patients with clozapine naïve TRS.

METHODS

A longitudinal design was developed, involving 32 patients diagnosed with treatment-resistant, clozapine-naïve schizophrenia-spectrum disorder. Patients were evaluated at baseline before clozapine starting and 8 weeks of follow-up. Psychopathological status and immune abnormalities (blood cell count ratios: neutrophil-lymphocyte ratio [NLR], monocyte-lymphocyte ratio [MLR], platelet-lymphocyte ratio [PLR] and basophil-lymphocyte ratio [BLR]) were evaluated in each visit.

RESULTS

Baseline NLR (b=- 0.364; p=0.041) and MLR (b =- 0.400; p=0.023) predicted the change in positive symptoms over the 8-week period. Patients who exhibited a clinical response showed higher baseline NLR (2.38±0.96 vs. 1.75±0.83; p=0.040) and MLR (0.21±0.06 vs. 0.17±0.02; p=0.044) compared to non-responders. In the ROC analysis, the threshold points to distinguish between responders and non-responders were approximately 1.62 for NLR and 0.144 for MLR, yielding AUC values of 0.714 and 0.712, respectively. No statistically significant differences were observed in the blood cell count ratios from baseline to the 8-week follow-up.

CONCLUSION

Our study emphasizes the potential clinical significance of baseline NLR and MLR levels as predictors of initial clozapine treatment response in patients with TRS. Future studies with larger sample sizes and longer follow-up periods should replicate our findings.

Pharmacomodulation of brain neuromedin U signaling as a potential therapeutic strategy

Neuromedin U (NMU) belongs to a family of multifunctional neuropeptides that modulate the activity of several neural networks of the brain. Acting via metabotropic receptor NMUR2, NMU plays a role in the regulation of multiple systems, including energy homeostasis, stress responses, circadian rhythms, and endocrine signaling. The involvement of NMU signaling in the central regulation of important neurophysiological processes and its disturbances is a potential target for pharmacological modulation. Number of preclinical studies have proven that both modified NMU analogues such as PASR8-NMU or F4R8-NMU and designed NMUR2 agonists, for example, CPN-116, CPN-124 exhibit a distinct pharmacological activity especially when delivered transnasally. Their application can potentially be useful in the more convenient and safe treatment of obesity, eating disorders, Alzheimer's disease-related memory impairment, alcohol addiction, and sleep disturbances. Accumulating findings suggest that pharmacomodulation of the central NMU signaling may be a promising strategy in the treatment of several neuropsychiatric disorders.

Factors associated with suicidal attempts in female patients with mood disorder

Aim

This study aims to establish a nomogram model to predict the relevance of SA in Chinese female patients with mood disorder (MD).

Method

The study included 396 female participants who were diagnosed with MD Diagnostic Group (F30-F39) according to the 10th Edition of Disease and Related Health Problems (ICD-10). Assessing the differences of demographic information and clinical characteristics between the two groups. LASSO Logistic Regression Analyses was used to identify the risk factors of SA. A nomogram was further used to construct a prediction model. Bootstrap re-sampling was used to internally validate the final model. The Receiver Operating Characteristic (ROC) curve and C-index was also used to evaluate the accuracy of the prediction model.

Result

LASSO regression analysis showed that five factors led to the occurrence of suicidality, including BMI (β = -0.02, SE = 0.02), social dysfunction (β = 1.72, SE = 0.24), time interval between first onset and first dose (β = 0.03, SE = 0.01), polarity at onset (β = -1.13, SE = 0.25), and times of hospitalization (β = -0.11, SE = 0.06). We assessed the ability of the nomogram model to recognize suicidality, with good results (AUC = 0.76, 95% CI: 0.71-0.80). Indicating that the nomogram had a good consistency (C-index: 0.756, 95% CI: 0.750-0.758). The C-index of bootstrap resampling with 100 replicates for internal validation was 0.740, which further demonstrated the excellent calibration of predicted and observed risks.

Conclusion

Five factors, namely BMI, social dysfunction, time interval between first onset and first dose, polarity at onset, and times of hospitalization, were found to be significantly associated with the development of suicidality in patients with MD. By incorporating these factors into a nomogram model, we can accurately predict the risk of suicide in MD patients. It is crucial to closely monitor clinical factors from the beginning and throughout the course of MD in order to prevent suicide attempts.

Vitamin D impact in affecting clozapine plasma exposure: A potential contribution of seasonality

Schizophrenia affects approximately 24 million people worldwide and clozapine is the most effective antipsychotic drug. Nevertheless, its use in therapy is limited due to adverse effects.Therapeutic drug monitoring is a clinical tool useful to reduce the clozapine toxicity. In the literature, papers showed how psychiatric disorders could be associated with low vitamin D levels, but a few studies focusing on its role in affecting clozapine exposure are available. A TDM repository was analyzed: clozapine and vitamin D levels measured with liquid chromatography were considered. 1261 samples obtained from 228 individuals were evaluated: 624 patients (49.5%) showed clozapine plasma levels in therapeutic range (350-600 ng/mL). Clozapine toxic plasma levels (>1000 ng/mL) were more present in winter (p = 0.025), compared to other seasons. Concerning vitamin D, a sub-analysis of 859 samples was performed: 326 (37.81%) were deficient ( ng/mL), 490 (57.12%) had insufficient concentrations (10-30 ng/mL), while 43 (5.02%) had sufficient (>30 ng/mL) levels. A correlation between vitamin D and clozapine plasma levels (p = 0.007, Pearson coefficient=0.093) was observed. The role of seasonal variation in clozapine plasma exposure in psychiatric patients treated with clozapine was suggested. Further studies in larger cohorts are needed in order to clarify these aspects.

Polygenic overlap with body-mass index improves prediction of treatment-resistant schizophrenia

Treatment resistant schizophrenia (TRS) is characterized by repeated treatment failure with antipsychotics. A recent genome-wide association study (GWAS) of TRS showed a polygenic architecture, but no significant loci were identified. Clozapine is shown to be the superior drug in terms of clinical effect in TRS; at the same time it has a serious side effect profile, including weight gain. Here, we sought to increase power for genetic discovery and improve polygenic prediction of TRS, by leveraging genetic overlap with Body Mass Index (BMI). We analysed GWAS summary statistics for TRS and BMI applying the conditional false discovery rate (cFDR) framework. We observed cross-trait polygenic enrichment for TRS conditioned on associations with BMI. Leveraging this cross-trait enrichment, we identified 2 novel loci for TRS at cFDR <0.01, suggesting a role of MAP2K1 and ZDBF2. Further, polygenic prediction based on the cFDR analysis explained more variance in TRS when compared to the standard TRS GWAS. These findings highlight putative molecular pathways which may distinguish TRS patients from treatment responsive patients. Moreover, these findings confirm that shared genetic mechanisms influence both TRS and BMI and provide new insights into the biological underpinnings of metabolic dysfunction and antipsychotic treatment.

The positive association between antipsychotic-induced weight gain and therapeutic response: New biotypes of schizophrenia

Co-occurrence of antipsychotic-induced weight gain (AIWG) and therapeutic response (TR) did exist in clinic but was rarely studied. This study aims to identify potential TR/ AIWG biotypes and explore the clinical, genetic and neuroimaging features. This study enrolled 3030 patients to identify potential TR/AIWG biotypes and explore the clinical, genetic and neuroimaging features. We found three biotypes: TR+nonAIWG (46.91%), TR+AIWG (18.82%), and nonTR+nonAIWG (34.27%). TR+AIWG showed lower weight and lipid level at baseline, but higher changing rate, and higher genetic risk of obesity than TR+nonAIWG and nonTR+nonAIWG. GWAS identified ADIPOQ gene related to TR+AIWG biotypes and top-ranked loci enriched in one-carbon metabolic process, which related to both schizophrenia and metabolic dysfunction. Genetically predicted TR+AIWG was associated with higher odds of diabetes (OR=1.05). The left supplementary motor area was significantly negatively correlated with PRS of obesity. The distinguishing ability with multi-omics data to identify TR+AIWG reached 0.787. In a word, the "thin" patients with a higher risk of obesity are the target population of early intervention.