Antipsychotic Treatment Response Research Articles

Aberrant connectivity in the hippocampus, bilateral insula and temporal poles precedes treatment resistance in first-episode psychosis: a prospective resting-state functional magnetic resonance imaging study with connectivity concordance mapping.

Functional connectivity resting-state functional magnetic resonance imaging has been proposed to predict antipsychotic treatment response in schizophrenia. However, only a few prospective studies have examined baseline resting-state functional magnetic resonance imaging data in drug-naïve first-episode schizophrenia patients with regard to subsequent treatment response. Data-driven approaches to conceptualize and measure functional connectivity patterns vary broadly, and model-free, voxel-wise, whole-brain analysis techniques are scarce. Here, we apply such a method, called connectivity concordance mapping to resting-state functional magnetic resonance imaging data acquired from an Asian sample (n = 60) with first-episode psychosis, prior to pharmaceutical treatment. Using a longitudinal design, 12 months after the resting-state functional magnetic resonance imaging, we measured and classified patients into two groups based on psychometric testing: treatment responsive and treatment resistant. Next, we compared the two groups' connectivity concordance maps that were derived from the resting-state functional magnetic resonance imaging data at baseline. We have identified consistently higher functional connectivity in the treatment-resistant group in a network including the left hippocampus, bilateral insula and temporal poles. These data-driven novel findings can help researchers to consider new regions of interest and facilitate biomarker development in order to identify treatment-resistant schizophrenia patients early, in advance of treatment and at the time of their first psychotic episode.

433. Cerebellar-Cortical Connectivity and Prediction of Antipsychotic Treatment Response in First-Episode Psychosis

433. Cerebellar-Cortical Connectivity and Prediction of Antipsychotic Treatment Response in First-Episode Psychosis

Higher-Order Intrinsic Brain Network Trajectories After Antipsychotic Treatment in Medication-Naïve Patients With First-Episode Psychosis

BackgroundIntrinsic brain network connectivity is already altered in first-episode psychosis (FEP), but the longitudinal trajectories of network connectivity, especially in response to antipsychotic treatment, remain poorly understood. The goal of this study was to investigate how antipsychotic medications affect higher-order intrinsic brain network connectivity in FEP. MethodsData from 87 antipsychotic medication-naïve patients with FEP and 87 healthy control participants were used. Medication-naïve patients received antipsychotic treatment for 16 weeks. Resting-state functional connectivity (FC) of the default mode, salience, dorsal attention, and executive control networks were assessed prior to treatment and at 6 and 16 weeks after treatment. We evaluated baseline and FC changes using linear mixed models to test group × time interactions within each network. Associations between FC changes after 16 weeks and response to treatment were also evaluated. ResultsPrior to treatment, significant group differences in all networks were found. However, significant trajectory changes in FC were found only in the default mode and executive control networks. Changes in FC in these networks were associated with treatment response. Several sensitivity analyses showed a consistent normalization of executive control network FC in response to antipsychotic treatment. ConclusionsHere, we found that alterations in intrinsic brain network FC were not only alleviated with antipsychotic treatment, but the extent of this normalization was also associated with the degree of reduction in symptom severity. Taken together, our data suggest modulation of intrinsic brain network connectivity (mainly frontoparietal connectivity) as a mechanism underlying antipsychotic treatment response in FEP.

An association between PPARα-L162V polymorphism and increased plasma LDL cholesterol levels after risperidone treatment

Peroxisome proliferator-activated receptor alpha (PPARα) and antipsychotic medications both influence polyunsaturated fatty acids (PUFA) homeostasis, and thus PPARα polymorphism may be linked to antipsychotic treatment response. Here we investigated whether the functional leucine 162 valine (L162V) polymorphism in PPARα influenced antipsychotic treatment in a group of psychosis patients (N = 186), as well as in a patient subgroup with risperidone, paliperidone, or combination treatment (N = 65). Antipsychotic-naïve first-episode patients and nonadherent chronic individuals were genotyped by polymerase chain reaction analysis. At baseline, and after 8 weeks of treatment with various antipsychotic medications, we assessed the patients’ Positive and Negative Syndrome Scale (PANSS) scores; PANSS factors; and metabolic syndrome-related parameters, including fasting plasma lipid and glucose levels, and body mass index. In the total patient group, PPARα polymorphism did not affect PANSS psychopathology or metabolic parameters. However, in the subgroup of patients with risperidone, paliperidone, or combination treatment, PPARα polymorphism influenced changes in plasma LDL cholesterol. Specifically, compared to PPARα-L162L homozygous patients, PPARα-L162V heterozygous individuals exhibited significantly higher increases of LDL cholesterol levels after antipsychotic treatment. The PPARα polymorphism had a strong effect size, but a relatively weak contribution to LDL cholesterol level variations (∼12.8 %).

Associations Between Structural Covariance Network and Antipsychotic Treatment Response in Schizophrenia.

Schizophrenia is associated with widespread cortical thinning and abnormality in the structural covariance network, which may reflect connectome alterations due to treatment effect or disease progression. Notably, patients with treatment-resistant schizophrenia (TRS) have stronger and more widespread cortical thinning, but it remains unclear whether structural covariance is associated with treatment response in schizophrenia. We organized a multicenter magnetic resonance imaging study to assess structural covariance in a large population of TRS and non-TRS, who had been resistant and responsive to non-clozapine antipsychotics, respectively. Whole-brain structural covariance for cortical thickness was assessed in 102 patients with TRS, 77 patients with non-TRS, and 79 healthy controls (HC). Network-based statistics were used to examine the difference in structural covariance networks among the 3 groups. Moreover, the relationship between altered individual differentiated structural covariance and clinico-demographics was also explored. Patients with non-TRS exhibited greater structural covariance compared with HC, mainly in the fronto-temporal and fronto-occipital regions, while there were no significant differences in structural covariance between TRS and non-TRS or HC. Higher individual differentiated structural covariance was associated with lower general scores of the Positive and Negative Syndrome Scale in the non-TRS group, but not in the TRS group. These findings suggest that reconfiguration of brain networks via coordinated cortical thinning is related to treatment response in schizophrenia. Further longitudinal studies are warranted to confirm if greater structural covariance could serve as a marker for treatment response in this disease.

DRD4 VNTR 4/4 homozygosity as a genetic biomarker for treatment selection in patients with schizophrenia

ObjectiveThere seems to be an association between the DRD4 48-bp VNTR polymorphisms and antipsychotic treatment response, but there is a rare reference to confirm this finding. Hence, the present study tried to investigate the association between DRD4 48-bp VNTR polymorphisms and the treatment response of antipsychotics in patients with schizophrenia in Taiwan, using a propensity score matching (PSM) method. MethodsA total of 882 participants were enrolled in this study and completed informed consent, research questionnaires, including demographic information and the revised Chinese version Beliefs about Voices Questionnaire, and blood sampling. For descreasing of the selection bias and confounding variables, the PSM nearest neighbor matching method was used to select 765 paitents with schizophrenia (ratio of 1:8 between 85 persistent auditory hallucination and 680 controls) with matched and controlled the age and gender. ResultsSchizophrenia patients with DRD4 4 R homozygosity had a lower rate of good antipsychotic treatment response than the other DRD4 genotype carriers (DRD4 non-4/4). Among those 4 R homozygosity carriers, 60 cases of 503 (11.9%) retain persistent auditory hallucinations. Furthermore, this subgroup of patients is accounted for up to 70.6% of cases with poor neuroleptic treatment response. ConclusionsA poor treatment outcome for patients with the 4 R homozygosity had presented,that comparing with those DRD non-4/4 genotype carriers. DRD4 VNTR 4 R homozygosity could be a genetic biomarker to predict poor antipsychotic treatment response in schizophrenia. Patients with DRD 4/4 probably receive novel antipsychotic medications preferentially or in combination with alternative therapy, such as psychotherapy or milieu therapy.

Association of DRD2, DRD4 and COMT genes variants and their gene-gene interactions with antipsychotic treatment response in patients with schizophrenia

Antipsychotic drugs are the first line of treatment in schizophrenia; although antipsychotic responses indicate a wide interindividual variety in patients with schizophrenia. This study aimed to investigate the association between four polymorphisms in DRD2, DRD4 and COMT genes and their gene-gene interactions with antipsychotic treatment response in patients with schizophrenia. A total of 101 patients with schizophrenia were recruited and stratified in treatment responder and treatment resistant groups based on the published criteria of resistant to treatment using PANSS. Clinical and demographic factors were analyzed. Genomic DNA was extracted from whole blood and genotyping for the four polymorphisms were done by ARMS-PCR, PCR-RFLP and gap-PCR. Gene-gene interactions were analyzed by logistic regression. In case of DRD2 A-241G, G allele was significantly associated with resistant to treatment. Regarding DRD4 120-bp duplication, 240/240 genotype was significantly associated with resistant to treatment comparing to other genotypes in a dominant model. The genotype combination of DRD4 240/240 and COMT Val/Val was significantly associated with treatment resistant. Among DRD2 AA genotype, COMT met allele carriers which also had a 120 bp allele of DRD4 had a significantly better response to antipsychotics. Moreover, analysis of clinical and demographic factors demonstrated a significantly longer duration of hospitalization and higher chlorpromazine-equivalent daily dose in resistant to treatment patients. Discovering the polymorphisms which effect treatment response to antipsychotics will provide the possibility of genetic screening before starting an antipsychotic treatment which enhances the chance of responding to antipsychotics and decreases drugs side effects and costs.

Extracellular vesicle biomarkers for complement dysfunction in schizophrenia.

Schizophrenia, a complex neuropsychiatric disorder, frequently experiences a high rate of misdiagnosis due to subjective symptom assessment. Consequently, there is an urgent need for innovative and objective diagnostic tools. In this study, we used cutting-edge extracellular vesicles' (EVs) proteome profiling and XGBoost-based machine learning to develop new markers and personalized discrimination scores for schizophrenia diagnosis and prediction of treatment response. We analysed plasma and plasma-derived EVs from 343 participants, including 100 individuals with chronic schizophrenia, 34 first-episode and drug-naïve patients, 35 individuals with bipolar disorder, 25 individuals with major depressive disorder and 149 age- and sex-matched healthy controls. Our innovative approach uncovered EVs-based complement changes in patients, specific to their disease-type and status. The EV-based biomarkers outperformed their plasma counterparts, accurately distinguishing schizophrenia individuals from healthy controls with an area under curve (AUC) of 0.895, 83.5% accuracy, 85.3% sensitivity and 82.0% specificity. Moreover, they effectively differentiated schizophrenia from bipolar disorder and major depressive disorder, with AUCs of 0.966 and 0.893, respectively. The personalized discrimination scores provided a personalized diagnostic index for schizophrenia and exhibited a significant association with patients' antipsychotic treatment response in the follow-up cohort. Overall, our study represents a significant advancement in the field of neuropsychiatric disorders, demonstrating the potential of EV-based biomarkers in guiding personalized diagnosis and treatment of schizophrenia.

Short-term antipsychotic treatment response in early-onset, typical-onset, and late-onset first episode schizophrenia.

In schizophrenia, the age at illness onset may reflect genetic loading and predict prognosis. We aimed to compare the pre-treatment symptom profiles and clinical symptom responses to antipsychotic treatment of individuals with late-onset schizophrenia (LOS; onset age: 40-59years) with individuals with early-onset schizophrenia (EOS; onset age<18years) or typical-onset schizophrenia (TOS; onset age: 18-39years). We conducted an 8-week cohort study in inpatient departments of five mental health hospitals in five cities in China. We included 106 individuals with LOS, 80 with EOS, and 214 with TOS. Their onset of schizophrenia was within three years and the disorders were minimally treated. The Positive and Negative Syndrome Scale (PANSS) was used to evaluate clinical symptoms at baseline and after 8weeks of antipsychotic treatment. Mixed effect models were used to compare symptom improvement within eight weeks. Antipsychotic therapy reduced all PANSS factor scores in all three groups. LOS had significantly better improvement in PANSS positive factor scores than EOS at week 8 after adjusting for sex, duration of illness, dose equivalents of antipsychotics at baseline, sites as fixed effects, and individuals as random effects. LOS was associated with reduced positive factor scores at week 8 when receiving 1mg olanzapine dose equivalent per 1kg body weight compared with EOS or TOS. In conclusion, LOS had better early improvement of positive symptoms than EOS and TOS. Thus, personalized treatment for schizophrenia should consider the age of onset.

Neuroimaging glutamatergic mechanisms differentiating antipsychotic treatment-response

Glutamatergic dysfunction is associated with failure to respond to antipsychotic medication in individuals with schizophrenia. Our objective was to combine neurochemical and functional brain imaging methods to investigate glutamatergic dysfunction and reward processing in such individuals compared with those with treatment responsive schizophrenia, and healthy controls. 60 participants played a trust task, while undergoing functional magnetic resonance imaging: 21 classified as having treatment-resistant schizophrenia, 21 patients with treatment-responsive schizophrenia, and 18 healthy controls. Proton magnetic resonance spectroscopy was also acquired to measure glutamate in the anterior cingulate cortex. Compared to controls, treatment responsive and treatment-resistant participants showed reduced investments during the trust task. For treatment-resistant individuals, glutamate levels in the anterior cingulate cortex were associated with signal decreases in the right dorsolateral prefrontal cortex when compared to those treatment-responsive, and with bilateral dorsolateral prefrontal cortex and left parietal association cortex when compared to controls. Treatment-responsive participants showed significant signal decreases in the anterior caudate compared to the other two groups. Our results provide evidence that glutamatergic differences differentiate treatment resistant and responsive schizophrenia. The differentiation of cortical and sub-cortical reward learning substrates has potential diagnostic value. Future novel interventions might therapeutically target neurotransmitters affecting the cortical substrates of the reward network.

The association between peripheral inflammation, brain glutamate and antipsychotic response in Schizophrenia: Data from the STRATA collaboration

Glutamate and increased inflammation have been separately implicated in the pathophysiology of schizophrenia and the extent of clinical response to antipsychotic treatment. Despite the mechanistic links between pro-inflammatory and glutamatergic pathways, the relationships between peripheral inflammatory markers and brain glutamate in schizophrenia have not yet been investigated. In this study, we tested the hypothesis that peripheral levels of pro-inflammatory cytokines would be positively associated with brain glutamate levels in schizophrenia. Secondary analyses determined whether this relationship differed according to antipsychotic treatment response. The sample consisted of 79 patients with schizophrenia, of whom 40 were rated as antipsychotic responders and 39 as antipsychotic non-responders. Brain glutamate levels were assessed in the anterior cingulate cortex (ACC) and caudate using proton magnetic resonance spectroscopy (1H-MRS) and blood samples were collected for cytokine assay on the same study visit (IL-6, IL-8, IL-10, TNF- α and IFN-γ). Across the whole patient sample, there was a positive relationship between interferon-gamma (IFN-γ) and caudate glutamate levels (r = 0.31, p = 0.02). In the antipsychotic non-responsive group only, there was a positive relationship between interleukin-8 (IL-8) and caudate glutamate (r = 0.46, p = 0.01). These findings provide evidence to link specific peripheral inflammatory markers and caudate glutamate in schizophrenia and may suggest that this relationship is most marked in patients who show a poor response to antipsychotic treatment.

Comparison of gut microbiome profile in patients with schizophrenia and healthy controls - A plausible non-invasive biomarker?

The human gut microbiome regulates brain function through the microbiome-gut-brain axis and is implicated in several neuropsychiatric disorders. However, the relationship between the gut microbiome and the pathogenesis of schizophrenia (SCZ) is poorly defined, and very few studies have examined the effect of antipsychotic treatment response. We aim to study the differences in the gut microbiota among drug-naïve (DN SCZ) and risperidone-treated SCZ patients (RISP SCZ), compared to healthy controls (HCs). We recruited a total of 60 participants, from the clinical services of a large neuropsychiatric hospital, which included DN SCZ, RISP SCZ and HCs (n = 20 each). Fecal samples were analyzed using 16s rRNA sequencing in this cross-sectional study. No significant differences were found in taxa richness (alpha diversity) but microbial composition differed between SCZ patients (both DN and RISP) and HCs (PERMANOVA, p = 0.02). Linear Discriminant Analysis Effect Size (LEfSe) and Random Forest model identified the top six genera, which significantly differed in abundance between the study groups. A specific genus-level microbial panel of Ruminococcus, UCG005, Clostridium_sensu_stricto_1 and Bifidobacterium could discriminate SCZ patients from HCs with an area under the curve (AUC) of 0.79, HCs vs DN SCZ (AUC: 0.68), HCs vs RISP SCZ (AUC: 0.93) and DN SCZ vs RISP SCZ (AUC: 0.87). Our study identified distinct microbial signatures that could aid in the differentiation of DN SCZ, RISP SCZ, and HCs. Our findings contribute to a better understanding of the role of the gut microbiome in SCZ pathophysiology and suggest potential targeted interventions.

Cognitive performance at first episode of psychosis and the relationship with future treatment resistance: Evidence from an international prospective cohort study.

Antipsychotic treatment resistance affects up to a third of individuals with schizophrenia, with recent research finding systematic biological differences between antipsychotic resistant and responsive patients. Our aim was to determine whether cognitive impairment at first episode significantly differs between future antipsychotic responders and resistant cases. Analysis of data from seven international cohorts of first-episode psychosis (FEP) with cognitive data at baseline (N=683) and follow-up data on antipsychotic treatment response: 605 treatment responsive and 78 treatment resistant cases. Cognitive measures were grouped into seven cognitive domains based on the pre-existing literature. We ran multiple imputation for missing data and used logistic regression to test for associations between cognitive performance at FEP and treatment resistant status at follow-up. On average patients who were future classified as treatment resistant reported poorer performance across most cognitive domains at baseline. Univariate logistic regressions showed that antipsychotic treatment resistance cases had significantly poorer IQ/general cognitive functioning at FEP (OR=0.70, p=.003). These findings remained significant after adjusting for additional variables in multivariable analyses (OR=0.76, p=.049). Although replication in larger studies is required, it appears that deficits in IQ/general cognitive functioning at first episode are associated with future treatment resistance. Cognitive variables may be able to provide further insight into neurodevelopmental factors associated with treatment resistance or act as early predictors of treatment resistance, which could allow prompt identification of refractory illness and timely interventions.

A pilot-study to examine motor cortical plasticity as a neuro-marker of antipsychotic treatment response in schizophrenia.

In a pilot study on 15 untreated first-episode schizophrenia participants, we examined how pre-treatment motor cortical plasticity - the brain's ability to change in response to an external perturbation - induced with intermittent theta burst stimulation, predicted prospectively ascertained (in 4-to-6 weeks) response to antipsychotic medications. We observed that participants with cortical plasticity in the opposite direction (possibly compensatory) had significantly greater improvements in their positive symptoms. This association persisted after correcting for multiple comparisons and controlling for potential confounders via linear regression. Inter-individual variability in cortical plasticity is a potential predictive biomarker in schizophrenia requiring further investigation and replication.

Striatum-related spontaneous coactivation patterns predict treatment response on positive symptoms of drug-naive first-episode schizophrenia with risperidone monotherapy.

Evidence from functional magnetic resonance imaging (fMRI) studies of schizophrenia suggests that interindividual variation in the stationary striatal functional circuit may be correlated with antipsychotic treatment response. However, little is known about the role of the dynamic striatum-related network in predicting patients' clinical improvement. The spontaneous coactivation pattern (CAP) technique has recently been found to be important for elucidating the non-stationary nature of functional brain networks. Forty-two drug-naive first-episode schizophrenia patients underwent fMRI and T1W imaging before and after 8 weeks of risperidone monotherapy. The striatum was divided into 3 subregions, including the putamen, pallidum, and caudate. Spontaneous CAPs and CAP states were utilized to measure the dynamic characteristics of brain networks. We used DPARSF and Dynamic Brain Connectome software to analyze each subregion-related CAP and CAP state for each group and then compared the between-group differences in the neural network biomarkers. We used Pearson's correlation analysis to determine the associations between the neuroimaging measurements with between-group differences and the improvement in patients' psychopathological symptoms. In the putamen-related CAPs, patients showed significantly increased intensity in the bilateral thalamus, bilateral supplementary motor areas, bilateral medial, and paracingulate gyrus, left paracentral lobule, left medial superior frontal gyrus, and left anterior cingulate gyrus compared with healthy controls. After treatment, thalamic signals in the putamen-related CAP 1 showed a significant increase, while the signals of the medial and paracingulate gyrus in the putamen-related CAP 3 revealed a significant decrease. The increase in thalamic signal intensity in the putamen-related CAP 1 was significantly and positively correlated with the percentage reduction in PANSS_P. This study is the first to combine striatal CAPs and fMRI to explore treatment response-related biomarkers in the early phase of schizophrenia. Our findings suggest that dynamic changes in CAP states in the putamen-thalamus circuit may be potential biomarkers for predicting patients' variation in the short-term treatment response of positive symptoms.

Predicting antipsychotic-induced weight gain in first episode psychosis - a field-wide systematic review and meta-analysis of non-genetic prognostic factors.

Whether non-genetic prognostic factors significantly influence the variable prognosis of antipsychotic-induced weight gain (AIWG) has not yet been systematically explored. Searches for both randomized and non-randomized studies were undertaken using four electronic databases, two trial registers, and via supplemental searching methods. Unadjusted and adjusted estimates were extracted. Meta-analyses were undertaken using a random-effects generic inverse model. Risk of bias and quality assessments were undertaken using Quality in Prognosis Studies (QUIPS) and Grading of Recommendations Assessment, Development and Evaluation (GRADE), respectively. Seventy-two prognostic factors were assessed across 27 studies involving 4426 participants. Only age, baseline body mass index (BMI), and sex were suitable for meta-analysis. Age (b=-0.044, 95%CI -0.157-0.069), sex (b=0.236, 95%CI -0.086-0.558), and baseline BMI (b=-0.013 95%CI -0.225-0.200) were associated with nonsignificant effects on AIWG prognosis. The highest quality GRADE rating was moderate in support of age, trend of early BMI increase, antipsychotic treatment response, unemployment, and antipsychotic plasma concentration. Trend of early BMI increase was identified as the most clinically significant prognostic factor influencing long-term AIWG prognosis. The strong prognostic information provided by BMI trend change within 12 weeks of antipsychotic initiation should be included within AIWG management guidance to highlight those at highest risk of worse long-term prognosis. Antipsychotic switching and resource-intensive lifestyle interventions should be targeted toward this cohort. Our results challenge previous research that several clinical variables significantly influence AIWG prognosis. We provide the first mapping and statistical synthesis of studies examining non-genetic prognostic factors of AIWG and highlight practice, policy, and research implications.

Multivariate prediction of antipsychotic treatment response in recent-onset psychosis: the role of environmental factors and brain functional connectivity.

Multivariate prediction of antipsychotic treatment response in recent-onset psychosis: the role of environmental factors and brain functional connectivity.

Deafness-Infertility Syndrome and Auditory Hallucinations

Deafness-Infertility Syndrome and Auditory Hallucinations

Featured Cover

The cover image is based on the Original Article Dorsal striatial hypoconnectivity predicts antipsychotic medication treatment response in first‐episode psychosis and unmedicated patients with schizophrenia by Eric A. Nelson et al., https://doi.org/10.1002/brb3.2625. image

Association between neuropeptide Y gene polymorphism and antipsychotics effect.

The pathogenesis of schizophrenia is associated with neuropeptide Y (NPY) gene polymorphism to explore the relationship between rs16141, rs16145, and rs5573 polymorphisms in the NPY gene and antipsychotics response in the Chinese population. The unrelated 228 Chinese Han patients with schizophrenia were enrolled in the present study. Genotypisation within NPY gene was performed using the KASP genotyping assays. Before treatment and on the weekends of the 2nd, 4th, and 8th weeks after treatment, the medication status of the patients was recorded and the positive and negative syndrome scale (PANSS) was used to evaluate the clinical effect. A reduction in total PANSS scores ≥50% were classified as good responders, while others were poor responders. We evaluated the association between NPY gene and antipsychotic efficacy by comparing allele and genotype distribution, correlation analysis, linkage imbalance, and five genetic models between the two groups. No significant associations were found in the rs16141, rs16145, and rs5573 of NPY and antipsychotic treatment response (all p > 0.05). There was no significant relationship between the three SNPs polymorphisms in the NPY gene and the changes of positive, negative and general psychopathology subscales scores at each stage (all p > 0.05). The distribution of genotype and allele frequencies of locus rs16141 was not statistically difference between good responders and poor responders (genotype: χ2 =4.088, p=0.043, p-correction = 0.129; allele: χ2 = 4.088, p = 0.027, p-correction = 0.081). The allele distribution of rs5573 was significantly different between groups, yet the difference was disappeared after correcting (χ2 = 4.136, p = 0.042, p-correction =0.126). The distribution frequencies of TA/TG and GG haplotypes constituted by rs16141 and rs5573 showed no statistical difference between the two groups (p > 0.05). In recessive inheritance mode, NPYrs5573 was found to be associated with antipsychotic drug response (G/G vs. A/A +A/G: p = 0.028, AIC = 197.2, BIC = 210.9). This study didn't found association between polymorphisms in the NPY gene locus (rs16141, rs16145, and rs5573) and the response to antipsychotics after Bonferroni correction. The polymorphism of NPY gene and the efficacy of antipsychotic drugs in patients with schizophrenia need further study.