Genome-wide association analysis of treatment resistant schizophrenia for variant discovery and polygenic assessment

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O’Connell, Robert Løvsletten Smith, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4614092/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 27 Sep, 2024 Read the published version in Human Genomics → Version 1 posted 9 You are reading this latest preprint version Abstract Background Treatment resistant schizophrenia (TRS) is broadly defined as inadequate response to adequate treatment and is associated with a substantial increase in disease burden. Clozapine is the only approved treatment for TRS, showing superior clinical effect on overall symptomatology compared to other drugs, and is the prototype of atypical antipsychotics. Risperidone, another atypical antipsychotic with a more distinctive dopamine 2 antagonism, is commonly used in treatment of schizophrenia. Here, we conducted a genome-wide association study on patients treated with clozapine (TRS) vs. risperidone (non-TRS) and investigated whether single variants and/or polygenic risk score for schizophrenia are associated with TRS status. We hypothesized that patients who are treated with clozapine and risperidone might exhibit distinct neurobiological phenotypes that match pharmacological profiles of these drugs and can be explained by genetic differences. The study population ( n = 1286) was recruited from a routine therapeutic drug monitoring service between 2005 and 2022. History of a detectable serum concentration of clozapine and risperidone defined the TRS ( n = 478) and non-TRS ( n = 808) group, respectively. Results We identified a suggestive association between TRS and a common variant within the LINC00523 gene with a significance just below the genome-wide threshold ( rs79229764 C > T , OR = 4.89; p = 1.8×10 − 7 ). Polygenic risk score for schizophrenia was significantly associated with TRS (OR = 1.4, p = 2.1×10 − 6 ). In a large post-mortem brain sample from schizophrenia donors (n = 214; CommonMind Consortium), gene expression analysis indicated that the rs79229764 variant allele might be involved in the regulation of GPR88 and PUDP , which plays a role in striatal neurotransmission and intellectual disability, respectively. Conclusions We report a suggestive genetic association at the rs79229764 locus with TRS and show that genetic liability for schizophrenia is positively associated with TRS. These results suggest a candidate locus for future follow-up studies to elucidate the molecular underpinnings of TRS. Our findings further demonstrate the value of both single variant and polygenic association analyses for TRS prediction. Figures Figure 1 Figure 2 Figure 3 Introduction Antipsychotics is the cornerstone of schizophrenia treatment, but up to 30% of patients do not respond adequately to standard treatment [ 1 ]. These treatment-resistant schizophrenia (TRS) patients suffer from greater symptom burden [ 1 ], and clozapine is the only evidence-based treatment for TRS with superior clinical effect on overall positive and negative symptoms [ 3 ]. All atypical antipsychotics broadly share antagonism at dopamine 2 (D 2 ) and serotonin 2A (5-HT 2A ) receptors, but they also have binding capabilities at other receptors [ 2 ]. Clozapine has transient and low affinity binding at D 2 receptors while favouring antagonism on 5-HT 2A receptors [ 2 ]. It exhibits the broadest coverage of molecular targets among all antipsychotics, including modulation of glutaminergic, cholinergic, and noradrenergic transmission [ 2 ]. Risperidone is a commonly used atypical antipsychotic with a more distinct receptor profile and particularly stronger D 2 antagonism than clozapine [ 2 ]. Patients who respond adequately to antipsychotics like risperidone are considered as ‘responders’ to D 2 receptor antagonism. Since clozapine can only be prescribed after failed response to two other antipsychotics, those who use clozapine may be considered as ‘non-responders’, meaning that symptom improvement is not sufficient with antagonism of these receptors but may require involvement of other neurotransmitter systems. Currently, knowledge on the underlying neurobiology of TRS is limited. While emerging evidence suggests that TRS has a polygenic architecture [ 4 ], previous studies have failed to identify specific gene variants that robustly correlate with TRS [ 5 ]. In a genome-wide investigation, Ruderfer et al. identified shared genetic underpinnings between schizophrenia pathophysiology and the mechanisms of action of antipsychotic drugs [ 6 ]. Here, we conducted a genome-wide association study (GWAS) on clozapine use, defined as proxy of resistant schizophrenia, vs. risperidone use, defined as proxy for responsive schizophrenia, in patients with confirmed therapeutic concentrations of these two drugs. We both analysed for associations with single variants and polygenic risk score for schizophrenia and hypothesized that genetic differences between patients treated with clozapine and risperidone might reflect aspects underlying the genetic architecture of antipsychotic response. Methods 2.1. Study population In clinical practice, therapeutic drug monitoring (TDM) may be applied to guide antipsychotic dosing to ensure sufficient treatment intensity, and thus exclude potential ‘pseudo resistance’ and erroneous diagnosis of TRS. The study utilized retrospective data/samples of patients from the routine TDM service at Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway, who in the period between January 2005 and August 2022 had performed i) TDM of clozapine or risperidone (no clozapine history) and ii) genotyping of cytochrome P450 (CYP) enzymes in ordinary clinical practice. In Norway, TDM is reimbursed and commonly used as a clinical tool in public psychiatric health service to assess adherence to medication and optimize dosing of drugs for maximizing clinical effect and/or minimizing side effects. Use of CYP genotyping is also reimbursed and increasingly used to guide dose optimization of psychiatric drugs. The study population consisted of patients of Norwegian inhabitants and is assumed to be of patients with Caucasian ancestry. The main inclusion criterion was the availability of biobanked (residual) blood samples from CYP genotyping and clinical concentration levels of clozapine or risperidone verified by TDM. Patients were phenotyped based on their history of using risperidone or clozapine at clinically relevant concentrations, as determined by their TDM history. The TRS group was defined by clozapine use, while the non-TRS group was defined by risperidone use. Further requirements for being included in the risperidone cohort were treatment with ≥ 2 mg/day risperidone at least once (dose range for psychotic disorders) and no previous use/TDM history of clozapine. TDM is routinely used for dose titration and monitoring of clozapine treatment in Norway, where Center for Psychopharmacology is the major laboratory performing analyses. The Regional Committee for Medical and Health Research Ethics and the Investigational Review Board at Diakonhjemmet Hospital approved the study. The study used anonymized data and residual blood samples from already performed routine analyses. In these cases, where study inclusion does not pose any burden to the patients, the Health Research Act of Norway allows for using samples and information collecting in clinical routine for research purpose without written informed patient consent. However, it is mandatory to send information to the patients, in advance of starting a project, about their legal rights to reserve against being included. Accordingly, letters were sent to all patients eligible for inclusion, where those requesting to opt-out were excluded from the study. 2.2. Serum concentration determination of antipsychotics Liquid chromatography with mass spectrometry (LC-MS) method with FDA certified and validated analytical assays were applied for determination of serum concentrations of clozapine and risperidone and their metabolites. Lower limit of quantification for clozapine and N -desmethylclozapine was 50 nmol/L, whereas this limit was 1 nmol/L and 2 nmol/L for risperidone and 9-hydroxyrisperidone, respectively. Serum concentration thresholds, based on consensus guidelines [ 7 ], were used as an informative measure to assess whether exposure to antipsychotic was adequate. These were clozapine 1070 nmol/L (350 µg/L) and risperidone active moiety 50 nmol/L (20 µg/L, risperidone plus 9-hydroxyrisperidone). 2.3. Genotyping and imputation As previously described in detail [ 8 ], DNA extracted from the whole blood was genotyped using the Human Omni Express-24 v.1.1 (Illumina Inc., San Diego, CA, USA), at deCODE Genetics (Reykjavik, Iceland), following standard Illumina protocols. Quality control and phasing of chromosome-wide haplotypes were performed with PLINK v1.93 [ 9 , 10 ] and Eagle2 [ 11 , 12 ], respectively. The first release of the haplotype reference consortium reference set was used for imputation of missing variants with Minimac3 [ 13 ]. Following imputation, exclusion criteria were variants with (1) minor allele frequency < 1% or (2) departure from Hardy–Weinberg equilibrium (P-value 5%), that exhibit relatedness (pairwise Identity-By-Descent ^ π > 0.2 according to PLINK v1.9). 1286 individuals with ~ 5.6 million common variants were included for further statistical analysis. 2.4. Statistical analysis The statistical analyses were performed using R statistics [ 14 ] for demographic characteristics of the study sample and follow-up analysis of the lead variant identified. Distribution of sex and age were compared between TRS and non-TRS patients using Pearson’s Chi-squared test and Welch’s two sample t-test, respectively. If risperidone patients were prescribed long-acting injectable formulations, total daily dosing was estimated by dividing the prescribed doses by dosing intervals. Estimated means of serum concentrations (nmol/L) and daily dose (mg/day) were calculated using linear mixed models with unique patient identifier as random effects. The GWAS of TRS versus non-TRS was conducted using logistic regression analyses implemented in PLINK v1.9 [ 9 , 10 ], controlling for participant age, sex, the first 10 genetic principal components and genotyping batch. Standard GWAS threshold (5 × 10 − 8 ) was used to define statistical significance of the GWAS analysis. LDproxy module provided by the LDlink platform [ 15 ] was used to perform linkage equilibrium analysis of the lead variant. For the expression quantitative trait loci (eQTL) analysis, genotype and post-mortem frontal brain cortex gene expression data were obtained from the CommonMind Consortium [ 16 ]. Only data from schizophrenia patients with European ethnicity (n = 214) were included in the study. Genotype QC and imputation were performed by the Consortium. The expression data was filtered and normalized using the DESeq2 R package [ 17 ]. The R package MatrixEQTL [ 18 ] was used for the cis-eQTL analysis, adjusting for age, gender and post-mortem interval. Variant-gene associations within 1 Mb of the identified lead variant were considered. P < 0.05 defined statistical significance of patient/treatment characteristics and gene expression analyses. For the GWAS sample, a schizophrenia polygenic risk score (PRS) was calculated based on the latest schizophrenia GWAS performed by the PGC [ 19 ] using the meta-analysis of European samples comprising 53,386 cases and 77,258 controls. The PRS was calculated using the PRS continuous shrinkage (PRS-cs) approach [ 20 ], adjusting for linkage disequilibrium (LD) based on the LD structure of the European sample of the 1000 Genomes Phase III [ 21 ] with default options and a shrinkage parameter of phi = 1 [ 20 ]. To facilitate the interpretability of the results, the PRS was standardized (mean = 0, SD = 1) before statistical analysis. To investigate if the PRS for schizophrenia as well as smoking, age, and sex is associated with TRS, a logistic regression analysis including TRS (yes/no) as the dependent variable was performed. The model included the PRS, age, sex, smoking (yes/no), as well as genotyping batch and the first 5 principal components for genetic ancestry for adjustment. Results Sample characteristics are presented in Table 1 . The study population (n = 1286) included n = 478 TRS patients and n = 808 non-TRS patients. There was a higher proportion of males among the TRS group compared to the non-TRS group (59% vs 53%, p = 0.009), but no difference in age distribution (Table 1 ). Mean daily dose estimates were 335 and 3.3 mg/day for patients who were treated with clozapine (TRS) and risperidone (non-TRS), respectively (Table 1 ). Furthermore, estimated serum concentration measurements for patients in the TRS and non-TRS group were 1201 nmol/L (393 ng/ml) for clozapine and 64 nmol/L for risperidone (active moiety including 9-hydroxyrisperidone), respectively (Table 1 ). Among the TRS group, median number of clozapine measurements during the study period was 14 (IQR: 5, 36) spanning 4.3 years (IQR: 0.7, 11.8) of TDM, whereas TDM history of the non-TRS group showed median of 3 (IQR: 1.8, 7) risperidone measurements over 0.8 years (IQR: 0.04, 4.8; Table 1 ). Table 1 Demographic and treatment characteristics of the study population. Variables TRS non-TRS p Number of patients, n 478 808 ─ Male, n (%) 284 (59) 430 (53) 0.031 Age, years; mean (SD) 48.7 (15.0) 48.7 (16.9) 0.99 Serum concentration, nmol/L; mean (95%CI) 1201 (1162,1240) 64 (30, 98) ─ Dose, mg/day; mean (95%CI) 335 (320, 350) 3.3 (3.2, 3.4) ─ History of TDM measurements, n ; median (IQR) 14 (5, 36) 3 (1.8, 7) ─ TDM duration, years; median (IQR) 4.3 (0.7, 11.8) 0.8 (0.04, 4.8) ─ IQR Interquartile range, SD Standard deviation, TDM Therapeutic drug monitoring, TRS treatment resistant schizophrenia. TRS and non-TRS groups comprised of patients who were treated with clozapine and risperidone, respectively. The GWAS on TRS did not show any associations reaching genome-wide significance ( p T ) on chromosome 14 with a p -value just above the genome-wide significance threshold ( p = 1.8 × 10 − 7 ; Fig. 1 ). We observed a 2.1-fold higher proportion of the risk allele carriers among TRS patients compared to non-TRS patients with allele frequencies of 3.7% and 1.7%, respectively; OR = 4.89, 95% CI = [2.6, 8.5]). Frequency of the minor allele variant is 4.2% among European populations ( https://www.ensembl.org/ ). LD structure from the 1000 Genomes phase 3-genome browser showed a low LD region (Supplementary Fig. 1) with variants that are in low to moderate LD with the rs79229764 haplotype among the European populations (R2 < 0.54; Supplementary Table 1). The rs79229764 variant is located within the exon of the long intergenic non-coding RNA 523 ( LINC00523 ) gene. NHGRI-EBI GWAS Catalog did not reveal any previous associations with the rs79229764 variant ( https://www.ebi.ac.uk/gwas/ ). Expression quantitative trait loci (eQTL) analysis of rs79229764 using the CommonMind Consortium post-mortem brain expression data [ 16 ] from n = 214 schizophrenia patients revealed gene associations with nominal significance. The top 3 most significant risk allele-gene relationships included increased expression of PUDP ( p = 0.001) and GPR88 ( p = 0.0047), and decreased expression of JMJD7 ( p = 0.003; Table 2 and Fig. 2 ). Table 2 The 3 most significant brain tissue gene expression associations of the lead variant rs79229764 C > T from CommonMind Consortium. Chromosome Position Gene name Beta p (unadjusted)* Gene Type X 6,667,865–7,148,158 PUDP 0.441 0.001 Protein coding 15 41,828,092 − 41,837,581 JMJD7 -0.592 0.003 Protein coding 1 100,538,139 − 100,542,021 GPR88 0.435 0.005 Protein coding Betas are included from the eQTL analysis which was adjusted for age, gender and post-mortem interval. Only data from schizophrenia patients with European ethnicity were included in the analysis. * p > 0.05 after multiple comparisons corrections. The schizophrenia PRS showed a significant, positive association with TRS, i.e., higher PRS was associated with being a TRS case (OR = 1.4, p = 2.1 × 10 − 6 ; Fig. 3 and Supplementary Table 2). In addition, we observed that smoking was significantly associated with TRS (OR = 1.4, p = 0.003; Fig. 3 and Supplementary Table 2). No association was observed between TRS and sex or age (Fig. 3 and Supplementary Table 2). Discussion In the current study, we conducted a genome-wide investigation of TRS based on clozapine (TRS) and risperidone (non-TRS) treatment at therapeutic serum concentrations in a well-phenotyped study cohort ( n = 1286). We found that genetic liability to schizophrenia, as measured by schizophrenia PRS was significantly associated with TRS. We also identified a suggestive variant in the LINC00523 gene ( rs79229764 C > T) with strong enrichment in clozapine vs. risperidone patients (OR = 4.89) and a significance level close to the genome-wide threshold ( p = 1.8 × 10 − 7 ). Follow-up eQTL analysis in post-mortem brain samples from schizophrenia donors ( n = 214) suggested transcriptional effects of rs79229764 on different genes. Although previous studies investigating the association between schizophrenia PRS and TRS had conflicting results [ 23 – 26 ], our finding is in line with a recent systematic review and meta-analysis that showed significant associations between schizophrenia PRS and TRS [ 27 ]. We have previously observed that higher schizophrenia PRS is associated with antipsychotic prescription pattern [ 28 , 29 ]. Together with the findings from the current study, these results suggest that schizophrenia PRS may have potential utility to aid in therapeutic decision making on antipsychotic treatment. Furthermore, this shows the ability of the study to use a combinatorial approach investigating pharmacogenomics of TRS at both overall and detailed levels. Interestingly, tobacco smoking was also significantly associated with TRS. Approximately 60% of patients with schizophrenia are smokers [ 30 , 31 ], and the “self-medication” hypothesis states that nicotine consumption via tobacco smoking reduces the negative and cognitive symptoms in patients with schizophrenia [ 32 ]. Supporting this hypothesis, among patients with TRS, smokers show worse cognitive performances and more severe negative symptoms compared to nonsmokers [ 33 ] which may be indicative of self-medication behaviour to alleviate these symptoms. While smoking is known to induce metabolism and reduce serum levels of clozapine, the present findings suggest that smoking of nicotine-containing products may be indicative of a higher disease burden, corresponding non-response to antipsychotics and TRS. The rs79229764 variant, identified as the closest to genome-wide significant association with TRS in our sample, is located in the exon of the LINC00523 gene on the chromosome 14 open reading frame 70, C14orf70), which encodes an intergenic lncRNA (LINC00523). LINC00523 is highly expressed in basal ganglia (particularly in nucleus accumbens), testis, and adrenal gland ( https://www.gtexportal.org/ ). LINC00523 has been previously shown to be downregulated in patients with type 2 diabetes mellitus (T2DM) [ 34 ]. This may be of clinical importance since T2DM, as well as tobacco smoking, are among the major risk factors of cardiovascular disease (CVD), which is reported to be the cause of death for 25% of patients with schizophrenia [ 35 ]. The contribution of unhealthy lifestyle [ 36 ] and metabolic adverse effects related to antipsychotic drugs (especially clozapine) [ 37 ] among patients with TRS are well-known, and current evidence also suggest that there may be a shared genetic liability between schizophrenia and CVD [ 38 ]. Investigation of the transcriptional effects of rs79229764 variant in post-mortem brain data of schizophrenia patients suggested upregulation of GRP88 and PUDP , and downregulation of JMJD7 . Of particular interest may be the GPR88 gene, which encodes an orphan G-protein coupled receptor of the class A rhodopsin family (GPR88) that has previously been suggested to be a candidate susceptibility gene for sporadic cases of schizophrenia and bipolar disorder [ 39 , 40 ]. GPR88 is robustly expressed in the GABAergic medium spiny neurons (MSN) of the striatum [ 41 – 43 ] and central extended amygdala [ 44 ]. MSNs of the striatum are involved in dopaminergic and glutamatergic signalling pathways [ 45 ], which have been indicated in the pathophysiology of schizophrenia and treatment-resistance [ 46 ]. Furthermore, GPR88 expression has been previously shown to be altered after administration of mood stabilizers [ 47 , 48 ], antidepressants [ 49 – 51 ], and drugs related to treatment of addiction [ 44 ] which highlights its relevance for the treatment of psychiatric disorders. Future studies should therefore elucidate the potential impact of the rs79229764 polymorphism and/or GPR88 expression for the risk of TRS. PUPD (or HDHD1 ) encodes a phosphatase which might be involved in RNA degradation [ 52 ]. Previous studies suggest involvement in cancer formation [ 53 ] and intellectual disability [ 54 ]. Associations with intellectual disability is in line with the latest evidence from the larger GWAS on TRS which showed polygenic correlations between TRS and poor cognitive performance and intelligence [ 4 ] and might indicate role of neurodevelopmental processes in formation of TRS [ 55 ]. One limitation of the current study is the relatively small sample size for a GWAS on complex traits such as TRS. At the same time, the patients who are referred to TDM and pharmacogenetic investigation usually suffer from more serious psychiatric conditions and require closer follow-up. Therefore, patients with gene variants associated with risk of treatment failure are likely to be overrepresented compared to standard patient populations which is supported by the high odds ratio of being carrier of the suggestive variant among clozapine-treated patients in our analysis. Another limitation is that we did not have access to clinical information of patients, which precluded a clinical assessment of treatment response status. However, the study utilizes longitudinal TDM data to include well-defined phenotypes of TRS and non-TRS patients where appropriate drug use was quantitatively evidenced by serum concentrations within the therapeutic ranges for the respective drugs [ 7 ]. With access to smoking status on the TDM requisition forms we were also able to identify and adjust for smoking as a predictor of TRS. Thus, the methodological approach in the current study facilitates use of robust phenotypes by accounting for smoking and eliminating pseudoresistance, an important confounding factor in TRS research, which may be driven by poor adherence or other factors [ 56 ]. Therefore, the strengths of the study may outweigh the above limitations. Conclusions We conducted a GWAS of TRS that utilized a therapeutic drug monitoring patient sample, where smoking status was known, and therapeutic concentrations of clozapine and risperidone confirmed. Although the study did not reveal any genome-wide significant associations, we identified a variant in the LINC0053 gene that was marginally associated with higher risk of TRS. Transcriptional effects of this variant suggest a role of striatal regulation and possible neurodevelopmental underpinnings in the pathophysiology of TRS. We also show that polygenic liability for schizophrenia was significantly associated with TRS. Our results suggest a candidate locus for future follow-up studies to elucidate the molecular underpinnings of TRS and demonstrate the value of combining single variant and polygenic association analyses to suggest potential utility of genetics in predicting TRS. Declarations Ethics approval and consent to participate The Regional Committee for Medical and Health Research Ethics and the Hospital Investigational Review Board approved the study. The study used anonymized data and residual blood samples from already performed routine analyses, therefore study inclusion did not pose any burden to the patients and written informed patient consent was not required. Consent for publication Not applicable. Availability of data and materials The data is not available to the public due to privacy and ethical restrictions, however the data supporting the findings may be available from the corresponding author upon reasonable request. Competing interests OAA is consultant to Cortechs.ai and Precision Health AS and received speaker’s honoraria from Lundbeck, Sunovion, Janssen and Otsuka. EM received speaker’s honoraria from Lundbeck and Otsuka. The other authors have no competing interests to declare that are relevant to the content of this article. Funding This work was supported by South-Eastern Norway Regional Health Authority (Grant No. 2020019) and the European Union's Horizon 2020 research and innovation program (REALMENT; Grant No. 964874). Authors' contributions HÇL drafted the manuscript and performed the research; HÇL, RLS, and KSO retrieved the data; HÇL analysed the TDM data, KSO performed the GWAS, EK performed polygenic risk score analyses, and IAA performed the eQTL analysis; EM designed the study; KSO, EK, RLS, IAA, SD, OAA, and EM assisted in writing the manuscript. References Kane JM, Agid O, Baldwin ML, Howes O, Lindenmayer J-P, Marder S, et al. Clinical Guidance on the Identification and Management of Treatment-Resistant Schizophrenia. J Clin Psychiatry. 2019;80:0–0. https://doi.org/10.4088/JCP.18com12123 . Huhn M, Nikolakopoulou A, Schneider-Thoma J, Krause M, Samara M, Peter N, et al. 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Academic Press; 2009 [cited 2023 Apr 17]. pp. 1–35. https://www.sciencedirect.com/science/article/pii/S0074774209890016 https://doi.org/10.1016/S0074-7742(09)89001-6 . Potkin SG, Kane JM, Correll CU, Lindenmayer J-P, Agid O, Marder SR, et al. The neurobiology of treatment-resistant schizophrenia: paths to antipsychotic resistance and a roadmap for future research. Npj Schizophr. 2020;6:1–10. https://doi.org/10.1038/s41537-019-0090-z . Brandish PE, Su M, Holder DJ, Hodor P, Szumiloski J, Kleinhanz RR, et al. Regulation of Gene Expression by Lithium and Depletion of Inositol in Slices of Adult Rat Cortex. Neuron. 2005;45:861–72. https://doi.org/10.1016/j.neuron.2005.02.006 . Ogden CA, Rich ME, Schork NJ, Paulus MP, Geyer MA, Lohr JB, et al. Candidate genes, pathways and mechanisms for bipolar (manic–depressive) and related disorders: an expanded convergent functional genomics approach. Mol Psychiatry. 2004;9:1007–29. https://doi.org/10.1038/sj.mp.4001547 . Boehm C, Newrzella D, Herberger S, Schramm N, Eisenhardt G, Schenk V, et al. Effects of antidepressant treatment on gene expression profile in mouse brain: cell type-specific transcription profiling using laser microdissection and microarray analysis. J Neurochem. 2006;97:44–9. https://doi.org/10.1111/j.1471-4159.2006.03750.x . Conti B, Maier R, Barr AM, Morale MC, Lu X, Sanna PP, et al. Region-specific transcriptional changes following the three antidepressant treatments electro convulsive therapy, sleep deprivation and fluoxetine. Mol Psychiatry. 2007;12:167–89. https://doi.org/10.1038/sj.mp.4001897 . Logue SF, Grauer SM, Paulsen J, Graf R, Taylor N, Sung MA, et al. The orphan GPCR, GPR88, modulates function of the striatal dopamine system: A possible therapeutic target for psychiatric disorders? Mol Cell Neurosci. 2009;42:438–47. https://doi.org/10.1016/j.mcn.2009.09.007 . Preumont A, Rzem R, Vertommen D, Van Schaftingen E. HDHD1, which is often deleted in X-linked ichthyosis, encodes a pseudouridine-5’-phosphatase. Biochem J. 2010;431:237–44. https://doi.org/10.1042/BJ20100174 . Yu J, Zhang W, Ding D, Hu Y, Guo G, Wang J, et al. Bioinformatics Analysis Combined With Experiments Predicts PUDP as a Potential Prognostic Biomarker for Hepatocellular Carcinoma Through Its Interaction With Tumor Microenvironment. Front Oncol. 2022;12:830174. https://doi.org/10.3389/fonc.2022.830174 . Gholipour F, Yoshiura K-I, Hosseinpourfeizi M, Elmi N, Teimourian S, Safaralizadeh R. Whole exome sequencing reveals pathogenic variants in KL and PUDP genes as the cause of intellectual disability in an Iranian family. Gene Rep. 2021;24:101299. https://doi.org/10.1016/j.genrep.2021.101299 . Owen MJ, Legge SE, Rees E, Walters JTR, O’Donovan MC. Genomic findings in schizophrenia and their implications. Mol Psychiatry. 2023;1–10. https://doi.org/10.1038/s41380-023-02293-8 . Howes OD, Thase ME, Pillinger T. Treatment resistance in psychiatry: state of the art and new directions. Mol Psychiatry. 2022;27:58–72. https://doi.org/10.1038/s41380-021-01200-3 . Additional Declarations No competing interests reported. Supplementary Files TRSGWASSupplementaryMaterial.docx Cite Share Download PDF Status: Published Journal Publication published 27 Sep, 2024 Read the published version in Human Genomics → Version 1 posted Editorial decision: Revision requested 27 Aug, 2024 Reviews received at journal 27 Aug, 2024 Reviews received at journal 24 Aug, 2024 Reviewers agreed at journal 17 Aug, 2024 Reviewers agreed at journal 17 Aug, 2024 Reviewers invited by journal 05 Aug, 2024 Editor assigned by journal 20 Jun, 2024 Submission checks completed at journal 20 Jun, 2024 First submitted to journal 20 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4614092","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":325148092,"identity":"2aebe354-94a3-47a9-8a70-d98cafff1348","order_by":0,"name":"Hasan Çağın Lenk","email":"","orcid":"","institution":"Diakonhjemmet Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hasan","middleName":"Çağın","lastName":"Lenk","suffix":""},{"id":325148094,"identity":"8cccc63d-7703-4e65-a336-1cd89e80ac59","order_by":1,"name":"Elise Koch","email":"","orcid":"","institution":"Oslo University Hospital, University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Elise","middleName":"","lastName":"Koch","suffix":""},{"id":325148095,"identity":"4e0ac313-d6de-4465-8d51-7858792e9e48","order_by":2,"name":"Kevin S. O’Connell","email":"","orcid":"","institution":"Oslo University Hospital, University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Kevin","middleName":"S.","lastName":"O’Connell","suffix":""},{"id":325148096,"identity":"5857d0dd-39b7-4591-942a-7cef16d9623b","order_by":3,"name":"Robert Løvsletten Smith","email":"","orcid":"","institution":"Diakonhjemmet Hospital","correspondingAuthor":false,"prefix":"","firstName":"Robert","middleName":"Løvsletten","lastName":"Smith","suffix":""},{"id":325148097,"identity":"6e110a08-3b5d-4def-b0e7-f28e5dc67377","order_by":4,"name":"Ibrahim A. Akkouh","email":"","orcid":"","institution":"Oslo University Hospital, University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Ibrahim","middleName":"A.","lastName":"Akkouh","suffix":""},{"id":325148098,"identity":"9158678c-9304-41c4-9281-c1cb99d62ca8","order_by":5,"name":"Srdjan Djurovic","email":"","orcid":"","institution":"Oslo University Hospital, University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Srdjan","middleName":"","lastName":"Djurovic","suffix":""},{"id":325148099,"identity":"d4e8b6ad-26fa-42d2-b62c-2ccedb525e8c","order_by":6,"name":"Ole A. Andreassen","email":"","orcid":"","institution":"Oslo University Hospital, University of Oslo","correspondingAuthor":false,"prefix":"","firstName":"Ole","middleName":"A.","lastName":"Andreassen","suffix":""},{"id":325148100,"identity":"6049cf28-effe-41bd-8fa8-cd7c3661a27e","order_by":7,"name":"Espen Molden","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDklEQVRIie3QPUsDMRjA8accpEswa0rkvoHwQCBWKPpVUgLXJbZOIggqCHURXO+TdE4R2qW168EtykFdHA4EKbh4fZkknLo55L8F8kueBCAU+s/tgQYoO9uFA+A/E1KRRpr8lUQ0+cU8jM3HxRmMYtI0k6KjjwcHd9MX1xi2YxC3zkdaad/IFHJJ6LInrTZHo5nFinAJ+xPtI5hRJSjk3SG3SpyuIlTOwpp0b7hFHzlZzA4/t2TwIdr6GtXi9bmWIFgV7W4hAvQjqkxjLeFZ3wiKm7eo1r2eVuQNnX7ikvDE+xb2MB+/04s8Zk2z5Ct9WQ3WK8ry/Cpm3Hh/DIBuxvvW+nji378joVAoFKrrCymWWOA8vBZJAAAAAElFTkSuQmCC","orcid":"","institution":"Diakonhjemmet Hospital","correspondingAuthor":true,"prefix":"","firstName":"Espen","middleName":"","lastName":"Molden","suffix":""}],"badges":[],"createdAt":"2024-06-21 00:23:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4614092/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4614092/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40246-024-00673-x","type":"published","date":"2024-09-27T15:58:12+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60610196,"identity":"510ad68b-41ab-4155-be14-be25f06cb5ca","added_by":"auto","created_at":"2024-07-18 18:25:20","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":713834,"visible":true,"origin":"","legend":"\u003cp\u003eManhattan plot showing the associations with risk of TRS. The −log10 transformed \u003cem\u003ep\u003c/em\u003e-values for each SNP are shown on the y-axis and chromosomal positions are indicated on the x-axis.\u0026nbsp; The dashed black line represents the standard GWAS p-value threshold of 5 × 10\u003csup\u003e-8\u003c/sup\u003e. The most significant SNP is highlighted by text.\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4614092/v1/596bf15f7e813d31516a814e.jpg"},{"id":60610193,"identity":"6433a916-a16c-4abe-9b67-d2594ac4e16d","added_by":"auto","created_at":"2024-07-18 18:25:18","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":132255,"visible":true,"origin":"","legend":"\u003cp\u003eImpact of \u003cem\u003ers79229764 C\u0026gt;T\u003c/em\u003e on brain tissue gene expression from CommonMind Consortium data.\u003cstrong\u003e \u003c/strong\u003eThe 3 most significant gene expression associations were illustrated. Normalized expression results are shown on the y-axis, while \u003cem\u003ers79229764 C\u0026gt;T\u003c/em\u003egenotypes are indicated on the x-axis. Gene names and unadjusted p-values from association analyses are shown at the top part of the plots.\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4614092/v1/729fcae0f7eb2169d79fe347.jpg"},{"id":60610195,"identity":"fda421a6-9b01-48a5-baac-c509404535b0","added_by":"auto","created_at":"2024-07-18 18:25:19","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":197390,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot showing the association between treatment resistant schizophrenia and schizophrenia polygenic risk score (PRS SCZ), smoking, age, and sex. Effects are reported as odds ratios (95% confidence interval).\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4614092/v1/a7ce9ea04307704c2ed78d70.jpg"},{"id":65627521,"identity":"4b531f69-311b-4e01-950e-e6325ff79d20","added_by":"auto","created_at":"2024-09-30 16:16:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1540386,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4614092/v1/f1996cb5-dce6-4945-b609-581afad974cb.pdf"},{"id":60610194,"identity":"1e833a33-df10-40cd-9a3a-1c70af5db106","added_by":"auto","created_at":"2024-07-18 18:25:18","extension":"docx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":200560,"visible":true,"origin":"","legend":"","description":"","filename":"TRSGWASSupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-4614092/v1/72756529efc6dd4b466b7444.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Genome-wide association analysis of treatment resistant schizophrenia for variant discovery and polygenic assessment","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAntipsychotics is the cornerstone of schizophrenia treatment, but up to 30% of patients do not respond adequately to standard treatment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These treatment-resistant schizophrenia (TRS) patients suffer from greater symptom burden [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e], and clozapine is the only evidence-based treatment for TRS with superior clinical effect on overall positive and negative symptoms [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAll atypical antipsychotics broadly share antagonism at dopamine 2 (D\u003csub\u003e2\u003c/sub\u003e) and serotonin 2A (5-HT\u003csub\u003e2A\u003c/sub\u003e) receptors, but they also have binding capabilities at other receptors [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Clozapine has transient and low affinity binding at D\u003csub\u003e2\u003c/sub\u003e receptors while favouring antagonism on 5-HT\u003csub\u003e2A\u003c/sub\u003e receptors [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. It exhibits the broadest coverage of molecular targets among all antipsychotics, including modulation of glutaminergic, cholinergic, and noradrenergic transmission [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Risperidone is a commonly used atypical antipsychotic with a more distinct receptor profile and particularly stronger D\u003csub\u003e2\u003c/sub\u003e antagonism than clozapine [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Patients who respond adequately to antipsychotics like risperidone are considered as \u0026lsquo;responders\u0026rsquo; to D\u003csub\u003e2\u003c/sub\u003e receptor antagonism. Since clozapine can only be prescribed after failed response to two other antipsychotics, those who use clozapine may be considered as \u0026lsquo;non-responders\u0026rsquo;, meaning that symptom improvement is not sufficient with antagonism of these receptors but may require involvement of other neurotransmitter systems.\u003c/p\u003e \u003cp\u003eCurrently, knowledge on the underlying neurobiology of TRS is limited. While emerging evidence suggests that TRS has a polygenic architecture [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], previous studies have failed to identify specific gene variants that robustly correlate with TRS [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In a genome-wide investigation, Ruderfer et al. identified shared genetic underpinnings between schizophrenia pathophysiology and the mechanisms of action of antipsychotic drugs [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Here, we conducted a genome-wide association study (GWAS) on clozapine use, defined as proxy of resistant schizophrenia, vs. risperidone use, defined as proxy for responsive schizophrenia, in patients with confirmed therapeutic concentrations of these two drugs. We both analysed for associations with single variants and polygenic risk score for schizophrenia and hypothesized that genetic differences between patients treated with clozapine and risperidone might reflect aspects underlying the genetic architecture of antipsychotic response.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e2.1. Study population\u003c/p\u003e \u003cp\u003eIn clinical practice, therapeutic drug monitoring (TDM) may be applied to guide antipsychotic dosing to ensure sufficient treatment intensity, and thus exclude potential \u0026lsquo;pseudo resistance\u0026rsquo; and erroneous diagnosis of TRS. The study utilized retrospective data/samples of patients from the routine TDM service at Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway, who in the period between January 2005 and August 2022 had performed i) TDM of clozapine or risperidone (no clozapine history) and ii) genotyping of cytochrome P450 (CYP) enzymes in ordinary clinical practice. In Norway, TDM is reimbursed and commonly used as a clinical tool in public psychiatric health service to assess adherence to medication and optimize dosing of drugs for maximizing clinical effect and/or minimizing side effects. Use of \u003cem\u003eCYP\u003c/em\u003e genotyping is also reimbursed and increasingly used to guide dose optimization of psychiatric drugs.\u003c/p\u003e \u003cp\u003eThe study population consisted of patients of Norwegian inhabitants and is assumed to be of patients with Caucasian ancestry. The main inclusion criterion was the availability of biobanked (residual) blood samples from CYP genotyping and clinical concentration levels of clozapine or risperidone verified by TDM. Patients were phenotyped based on their history of using risperidone or clozapine at clinically relevant concentrations, as determined by their TDM history. The TRS group was defined by clozapine use, while the non-TRS group was defined by risperidone use. Further requirements for being included in the risperidone cohort were treatment with \u0026ge;\u0026thinsp;2 mg/day risperidone at least once (dose range for psychotic disorders) and no previous use/TDM history of clozapine. TDM is routinely used for dose titration and monitoring of clozapine treatment in Norway, where Center for Psychopharmacology is the major laboratory performing analyses.\u003c/p\u003e \u003cp\u003e The Regional Committee for Medical and Health Research Ethics and the Investigational Review Board at Diakonhjemmet Hospital approved the study. The study used anonymized data and residual blood samples from already performed routine analyses. In these cases, where study inclusion does not pose any burden to the patients, the Health Research Act of Norway allows for using samples and information collecting in clinical routine for research purpose without written informed patient consent. However, it is mandatory to send information to the patients, in advance of starting a project, about their legal rights to reserve against being included. Accordingly, letters were sent to all patients eligible for inclusion, where those requesting to opt-out were excluded from the study.\u003c/p\u003e \u003cp\u003e2.2. Serum concentration determination of antipsychotics\u003c/p\u003e \u003cp\u003eLiquid chromatography with mass spectrometry (LC-MS) method with FDA certified and validated analytical assays were applied for determination of serum concentrations of clozapine and risperidone and their metabolites. Lower limit of quantification for clozapine and \u003cem\u003eN\u003c/em\u003e-desmethylclozapine was 50 nmol/L, whereas this limit was 1 nmol/L and 2 nmol/L for risperidone and 9-hydroxyrisperidone, respectively.\u003c/p\u003e \u003cp\u003eSerum concentration thresholds, based on consensus guidelines [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], were used as an informative measure to assess whether exposure to antipsychotic was adequate. These were clozapine 1070 nmol/L (350 \u0026micro;g/L) and risperidone active moiety 50 nmol/L (20 \u0026micro;g/L, risperidone plus 9-hydroxyrisperidone).\u003c/p\u003e \u003cp\u003e2.3. Genotyping and imputation\u003c/p\u003e \u003cp\u003eAs previously described in detail [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], DNA extracted from the whole blood was genotyped using the Human Omni Express-24 v.1.1 (Illumina Inc., San Diego, CA, USA), at deCODE Genetics (Reykjavik, Iceland), following standard Illumina protocols. Quality control and phasing of chromosome-wide haplotypes were performed with PLINK v1.93 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e] and Eagle2 [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], respectively. The first release of the haplotype reference consortium reference set was used for imputation of missing variants with Minimac3 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Following imputation, exclusion criteria were variants with (1) minor allele frequency\u0026thinsp;\u0026lt;\u0026thinsp;1% or (2) departure from Hardy\u0026ndash;Weinberg equilibrium (P-value\u0026thinsp;\u0026lt;\u0026thinsp;1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e), or individuals with (3) high rates of missing genotypes (\u0026gt;\u0026thinsp;5%), that exhibit relatedness (pairwise Identity-By-Descent ^ π\u0026thinsp;\u0026gt;\u0026thinsp;0.2 according to PLINK v1.9). 1286 individuals with ~\u0026thinsp;5.6\u0026nbsp;million common variants were included for further statistical analysis.\u003c/p\u003e \u003cp\u003e2.4. Statistical analysis\u003c/p\u003e \u003cp\u003eThe statistical analyses were performed using R statistics [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] for demographic characteristics of the study sample and follow-up analysis of the lead variant identified. Distribution of sex and age were compared between TRS and non-TRS patients using Pearson\u0026rsquo;s Chi-squared test and Welch\u0026rsquo;s two sample t-test, respectively. If risperidone patients were prescribed long-acting injectable formulations, total daily dosing was estimated by dividing the prescribed doses by dosing intervals. Estimated means of serum concentrations (nmol/L) and daily dose (mg/day) were calculated using linear mixed models with unique patient identifier as random effects.\u003c/p\u003e \u003cp\u003eThe GWAS of TRS versus non-TRS was conducted using logistic regression analyses implemented in PLINK v1.9 [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], controlling for participant age, sex, the first 10 genetic principal components and genotyping batch. Standard GWAS threshold (5 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e) was used to define statistical significance of the GWAS analysis. LDproxy module provided by the LDlink platform [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] was used to perform linkage equilibrium analysis of the lead variant.\u003c/p\u003e \u003cp\u003eFor the expression quantitative trait loci (eQTL) analysis, genotype and post-mortem frontal brain cortex gene expression data were obtained from the CommonMind Consortium [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Only data from schizophrenia patients with European ethnicity (n\u0026thinsp;=\u0026thinsp;214) were included in the study. Genotype QC and imputation were performed by the Consortium. The expression data was filtered and normalized using the DESeq2 R package [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The R package MatrixEQTL [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] was used for the cis-eQTL analysis, adjusting for age, gender and post-mortem interval. Variant-gene associations within 1 Mb of the identified lead variant were considered. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 defined statistical significance of patient/treatment characteristics and gene expression analyses.\u003c/p\u003e \u003cp\u003eFor the GWAS sample, a schizophrenia polygenic risk score (PRS) was calculated based on the latest schizophrenia GWAS performed by the PGC [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] using the meta-analysis of European samples comprising 53,386 cases and 77,258 controls. The PRS was calculated using the PRS continuous shrinkage (PRS-cs) approach [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], adjusting for linkage disequilibrium (LD) based on the LD structure of the European sample of the 1000 Genomes Phase III [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] with default options and a shrinkage parameter of phi\u0026thinsp;=\u0026thinsp;1 [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. To facilitate the interpretability of the results, the PRS was standardized (mean\u0026thinsp;=\u0026thinsp;0, SD\u0026thinsp;=\u0026thinsp;1) before statistical analysis. To investigate if the PRS for schizophrenia as well as smoking, age, and sex is associated with TRS, a logistic regression analysis including TRS (yes/no) as the dependent variable was performed. The model included the PRS, age, sex, smoking (yes/no), as well as genotyping batch and the first 5 principal components for genetic ancestry for adjustment.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eSample characteristics are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The study population (n\u0026thinsp;=\u0026thinsp;1286) included n\u0026thinsp;=\u0026thinsp;478 TRS patients and n\u0026thinsp;=\u0026thinsp;808 non-TRS patients. There was a higher proportion of males among the TRS group compared to the non-TRS group (59% vs 53%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009), but no difference in age distribution (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Mean daily dose estimates were 335 and 3.3 mg/day for patients who were treated with clozapine (TRS) and risperidone (non-TRS), respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Furthermore, estimated serum concentration measurements for patients in the TRS and non-TRS group were 1201 nmol/L (393 ng/ml) for clozapine and 64 nmol/L for risperidone (active moiety including 9-hydroxyrisperidone), respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Among the TRS group, median number of clozapine measurements during the study period was 14 (IQR: 5, 36) spanning 4.3 years (IQR: 0.7, 11.8) of TDM, whereas TDM history of the non-TRS group showed median of 3 (IQR: 1.8, 7) risperidone measurements over 0.8 years (IQR: 0.04, 4.8; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic and treatment characteristics of the study population.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTRS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003enon-TRS\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of patients, \u003cem\u003en\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e478\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e─\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale, \u003cem\u003en\u003c/em\u003e (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e284 (59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e430 (53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years; mean (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.7 (15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.7 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSerum concentration, nmol/L; mean (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1201 (1162,1240)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64 (30, 98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e─\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDose, mg/day; mean (95%CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e335 (320, 350)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.3 (3.2, 3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e─\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHistory of TDM measurements, \u003cem\u003en\u003c/em\u003e; median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (5, 36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (1.8, 7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e─\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTDM duration, years; median (IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.3 (0.7, 11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8 (0.04, 4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e─\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIQR\u003c/em\u003e Interquartile range, \u003cem\u003eSD\u003c/em\u003e Standard deviation, \u003cem\u003eTDM\u003c/em\u003e Therapeutic drug monitoring, \u003cem\u003eTRS\u003c/em\u003e treatment resistant schizophrenia. TRS and non-TRS groups comprised of patients who were treated with clozapine and risperidone, respectively.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe GWAS on TRS did not show any associations reaching genome-wide significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e), however identified a single nucleotide polymorphism (SNP; \u003cem\u003ers79229764 C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/em\u003e) on chromosome 14 with a \u003cem\u003ep\u003c/em\u003e-value just above the genome-wide significance threshold (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.8 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). We observed a 2.1-fold higher proportion of the risk allele carriers among TRS patients compared to non-TRS patients with allele frequencies of 3.7% and 1.7%, respectively; OR\u0026thinsp;=\u0026thinsp;4.89, 95% CI = [2.6, 8.5]). Frequency of the minor allele variant is 4.2% among European populations (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ensembl.org/\u003c/span\u003e\u003cspan address=\"https://www.ensembl.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). LD structure from the 1000 Genomes phase 3-genome browser showed a low LD region (Supplementary Fig.\u0026nbsp;1) with variants that are in low to moderate LD with the \u003cem\u003ers79229764\u003c/em\u003e haplotype among the European populations (R2\u0026thinsp;\u0026lt;\u0026thinsp;0.54; Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe \u003cem\u003ers79229764\u003c/em\u003e variant is located within the exon of the long intergenic non-coding RNA 523 (\u003cem\u003eLINC00523\u003c/em\u003e) gene. NHGRI-EBI GWAS Catalog did not reveal any previous associations with the \u003cem\u003ers79229764\u003c/em\u003e variant (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ebi.ac.uk/gwas/\u003c/span\u003e\u003cspan address=\"https://www.ebi.ac.uk/gwas/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Expression quantitative trait loci (eQTL) analysis of \u003cem\u003ers79229764\u003c/em\u003e using the CommonMind Consortium post-mortem brain expression data [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] from \u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;214 schizophrenia patients revealed gene associations with nominal significance. The top 3 most significant risk allele-gene relationships included increased expression of \u003cem\u003ePUDP\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and \u003cem\u003eGPR88\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0047), and decreased expression of \u003cem\u003eJMJD7\u003c/em\u003e (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003; Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe 3 most significant brain tissue gene expression associations of the lead variant \u003cem\u003ers79229764 C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/em\u003e from CommonMind Consortium.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChromosome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePosition\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGene name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e (unadjusted)*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGene Type\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,667,865\u0026ndash;7,148,158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePUDP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.441\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eProtein coding\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41,828,092\u0026thinsp;\u0026minus;\u0026thinsp;41,837,581\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eJMJD7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.592\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eProtein coding\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100,538,139\u0026thinsp;\u0026minus;\u0026thinsp;100,542,021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGPR88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eProtein coding\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eBetas are included from the eQTL analysis which was adjusted for age, gender and post-mortem interval. Only data from schizophrenia patients with European ethnicity were included in the analysis. * \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05 after multiple comparisons corrections.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe schizophrenia PRS showed a significant, positive association with TRS, i.e., higher PRS was associated with being a TRS case (OR\u0026thinsp;=\u0026thinsp;1.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.1 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Supplementary Table\u0026nbsp;2). In addition, we observed that smoking was significantly associated with TRS (OR\u0026thinsp;=\u0026thinsp;1.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Supplementary Table\u0026nbsp;2). No association was observed between TRS and sex or age (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Supplementary Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the current study, we conducted a genome-wide investigation of TRS based on clozapine (TRS) and risperidone (non-TRS) treatment at therapeutic serum concentrations in a well-phenotyped study cohort (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1286). We found that genetic liability to schizophrenia, as measured by schizophrenia PRS was significantly associated with TRS. We also identified a suggestive variant in the \u003cem\u003eLINC00523\u003c/em\u003e gene (\u003cem\u003ers79229764 C\u0026thinsp;\u0026gt;\u0026thinsp;T)\u003c/em\u003e with strong enrichment in clozapine vs. risperidone patients (OR\u0026thinsp;=\u0026thinsp;4.89) and a significance level close to the genome-wide threshold (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.8 \u0026times; 10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e). Follow-up eQTL analysis in post-mortem brain samples from schizophrenia donors (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;214) suggested transcriptional effects of \u003cem\u003ers79229764\u003c/em\u003e on different genes.\u003c/p\u003e \u003cp\u003eAlthough previous studies investigating the association between schizophrenia PRS and TRS had conflicting results [\u003cspan additionalcitationids=\"CR24 CR25\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], our finding is in line with a recent systematic review and meta-analysis that showed significant associations between schizophrenia PRS and TRS [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. We have previously observed that higher schizophrenia PRS is associated with antipsychotic prescription pattern [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Together with the findings from the current study, these results suggest that schizophrenia PRS may have potential utility to aid in therapeutic decision making on antipsychotic treatment. Furthermore, this shows the ability of the study to use a combinatorial approach investigating pharmacogenomics of TRS at both overall and detailed levels.\u003c/p\u003e \u003cp\u003eInterestingly, tobacco smoking was also significantly associated with TRS. Approximately 60% of patients with schizophrenia are smokers [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], and the \u0026ldquo;self-medication\u0026rdquo; hypothesis states that nicotine consumption via tobacco smoking reduces the negative and cognitive symptoms in patients with schizophrenia [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Supporting this hypothesis, among patients with TRS, smokers show worse cognitive performances and more severe negative symptoms compared to nonsmokers [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] which may be indicative of self-medication behaviour to alleviate these symptoms. While smoking is known to induce metabolism and reduce serum levels of clozapine, the present findings suggest that smoking of nicotine-containing products may be indicative of a higher disease burden, corresponding non-response to antipsychotics and TRS.\u003c/p\u003e \u003cp\u003eThe \u003cem\u003ers79229764\u003c/em\u003e variant, identified as the closest to genome-wide significant association with TRS in our sample, is located in the exon of the \u003cem\u003eLINC00523\u003c/em\u003e gene on the chromosome 14 open reading frame 70, C14orf70), which encodes an intergenic lncRNA (LINC00523). LINC00523 is highly expressed in basal ganglia (particularly in nucleus accumbens), testis, and adrenal gland (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.gtexportal.org/\u003c/span\u003e\u003cspan address=\"https://www.gtexportal.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). LINC00523 has been previously shown to be downregulated in patients with type 2 diabetes mellitus (T2DM) [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. This may be of clinical importance since T2DM, as well as tobacco smoking, are among the major risk factors of cardiovascular disease (CVD), which is reported to be the cause of death for 25% of patients with schizophrenia [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The contribution of unhealthy lifestyle [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e] and metabolic adverse effects related to antipsychotic drugs (especially clozapine) [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] among patients with TRS are well-known, and current evidence also suggest that there may be a shared genetic liability between schizophrenia and CVD [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInvestigation of the transcriptional effects of \u003cem\u003ers79229764\u003c/em\u003e variant in post-mortem brain data of schizophrenia patients suggested upregulation of \u003cem\u003eGRP88\u003c/em\u003e and \u003cem\u003ePUDP\u003c/em\u003e, and downregulation of \u003cem\u003eJMJD7\u003c/em\u003e. Of particular interest may be the \u003cem\u003eGPR88\u003c/em\u003e gene, which encodes an orphan G-protein coupled receptor of the class A rhodopsin family (GPR88) that has previously been suggested to be a candidate susceptibility gene for sporadic cases of schizophrenia and bipolar disorder [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. GPR88 is robustly expressed in the GABAergic medium spiny neurons (MSN) of the striatum [\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e] and central extended amygdala [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. MSNs of the striatum are involved in dopaminergic and glutamatergic signalling pathways [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], which have been indicated in the pathophysiology of schizophrenia and treatment-resistance [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Furthermore, GPR88 expression has been previously shown to be altered after administration of mood stabilizers [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e], antidepressants [\u003cspan additionalcitationids=\"CR50\" citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], and drugs related to treatment of addiction [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] which highlights its relevance for the treatment of psychiatric disorders. Future studies should therefore elucidate the potential impact of the \u003cem\u003ers79229764\u003c/em\u003e polymorphism and/or GPR88 expression for the risk of TRS.\u003c/p\u003e \u003cp\u003e \u003cem\u003ePUPD\u003c/em\u003e (or \u003cem\u003eHDHD1\u003c/em\u003e) encodes a phosphatase which might be involved in RNA degradation [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. Previous studies suggest involvement in cancer formation [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] and intellectual disability [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Associations with intellectual disability is in line with the latest evidence from the larger GWAS on TRS which showed polygenic correlations between TRS and poor cognitive performance and intelligence [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and might indicate role of neurodevelopmental processes in formation of TRS [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOne limitation of the current study is the relatively small sample size for a GWAS on complex traits such as TRS. At the same time, the patients who are referred to TDM and pharmacogenetic investigation usually suffer from more serious psychiatric conditions and require closer follow-up. Therefore, patients with gene variants associated with risk of treatment failure are likely to be overrepresented compared to standard patient populations which is supported by the high odds ratio of being carrier of the suggestive variant among clozapine-treated patients in our analysis. Another limitation is that we did not have access to clinical information of patients, which precluded a clinical assessment of treatment response status. However, the study utilizes longitudinal TDM data to include well-defined phenotypes of TRS and non-TRS patients where appropriate drug use was quantitatively evidenced by serum concentrations within the therapeutic ranges for the respective drugs [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. With access to smoking status on the TDM requisition forms we were also able to identify and adjust for smoking as a predictor of TRS. Thus, the methodological approach in the current study facilitates use of robust phenotypes by accounting for smoking and eliminating pseudoresistance, an important confounding factor in TRS research, which may be driven by poor adherence or other factors [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. Therefore, the strengths of the study may outweigh the above limitations.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eWe conducted a GWAS of TRS that utilized a therapeutic drug monitoring patient sample, where smoking status was known, and therapeutic concentrations of clozapine and risperidone confirmed. Although the study did not reveal any genome-wide significant associations, we identified a variant in the \u003cem\u003eLINC0053\u003c/em\u003e gene that was marginally associated with higher risk of TRS. Transcriptional effects of this variant suggest a role of striatal regulation and possible neurodevelopmental underpinnings in the pathophysiology of TRS. We also show that polygenic liability for schizophrenia was significantly associated with TRS. Our results suggest a candidate locus for future follow-up studies to elucidate the molecular underpinnings of TRS and demonstrate the value of combining single variant and polygenic association analyses to suggest potential utility of genetics in predicting TRS.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Regional Committee for Medical and Health Research Ethics and the Hospital Investigational Review Board approved the study. The study used anonymized data and residual blood samples from already performed routine analyses, therefore study inclusion did not pose any burden to the patients and written informed patient consent was not required.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data is not available to the public due to privacy and ethical restrictions, however the data supporting the findings may be available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOAA is consultant to Cortechs.ai and Precision Health AS and received speaker\u0026rsquo;s honoraria from Lundbeck, Sunovion, Janssen and Otsuka. EM received speaker\u0026rsquo;s honoraria from Lundbeck and Otsuka. The other authors have no competing interests to declare that are relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by South-Eastern Norway Regional Health Authority (Grant No. 2020019) and the European Union\u0026apos;s Horizon 2020 research and innovation program (REALMENT; Grant No. 964874).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eH\u0026Ccedil;L drafted the manuscript and performed the research; H\u0026Ccedil;L, RLS, and KSO retrieved the data; H\u0026Ccedil;L analysed the TDM data, KSO performed the GWAS, EK performed polygenic risk score analyses, and IAA performed the eQTL analysis; EM designed the study; KSO, EK, RLS, IAA, SD, OAA, and EM assisted in writing the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKane JM, Agid O, Baldwin ML, Howes O, Lindenmayer J-P, Marder S, et al. 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Genomic findings in schizophrenia and their implications. Mol Psychiatry. 2023;1\u0026ndash;10. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41380-023-02293-8\u003c/span\u003e\u003cspan address=\"10.1038/s41380-023-02293-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHowes OD, Thase ME, Pillinger T. Treatment resistance in psychiatry: state of the art and new directions. Mol Psychiatry. 2022;27:58\u0026ndash;72. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41380-021-01200-3\u003c/span\u003e\u003cspan address=\"10.1038/s41380-021-01200-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"human-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hugm","sideBox":"Learn more about [Human Genomics](http://humgenomics.biomedcentral.com/)","snPcode":"40246","submissionUrl":"https://submission.nature.com/new-submission/40246/3","title":"Human Genomics","twitterHandle":"@OAgenetics","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-4614092/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4614092/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTreatment resistant schizophrenia (TRS) is broadly defined as inadequate response to adequate treatment and is associated with a substantial increase in disease burden. Clozapine is the only approved treatment for TRS, showing superior clinical effect on overall symptomatology compared to other drugs, and is the prototype of atypical antipsychotics. Risperidone, another atypical antipsychotic with a more distinctive dopamine 2 antagonism, is commonly used in treatment of schizophrenia. Here, we conducted a genome-wide association study on patients treated with clozapine (TRS) vs. risperidone (non-TRS) and investigated whether single variants and/or polygenic risk score for schizophrenia are associated with TRS status. We hypothesized that patients who are treated with clozapine and risperidone might exhibit distinct neurobiological phenotypes that match pharmacological profiles of these drugs and can be explained by genetic differences. The study population (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1286) was recruited from a routine therapeutic drug monitoring service between 2005 and 2022. History of a detectable serum concentration of clozapine and risperidone defined the TRS (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;478) and non-TRS (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;808) group, respectively.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe identified a suggestive association between TRS and a common variant within the \u003cem\u003eLINC00523\u003c/em\u003e gene with a significance just below the genome-wide threshold (\u003cem\u003ers79229764 C\u0026thinsp;\u0026gt;\u0026thinsp;T\u003c/em\u003e, OR\u0026thinsp;=\u0026thinsp;4.89; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.8\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e). Polygenic risk score for schizophrenia was significantly associated with TRS (OR\u0026thinsp;=\u0026thinsp;1.4, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e). In a large post-mortem brain sample from schizophrenia donors (n\u0026thinsp;=\u0026thinsp;214; CommonMind Consortium), gene expression analysis indicated that the \u003cem\u003ers79229764\u003c/em\u003e variant allele might be involved in the regulation of \u003cem\u003eGPR88\u003c/em\u003e and \u003cem\u003ePUDP\u003c/em\u003e, which plays a role in striatal neurotransmission and intellectual disability, respectively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eWe report a suggestive genetic association at the rs79229764 locus with TRS and show that genetic liability for schizophrenia is positively associated with TRS. These results suggest a candidate locus for future follow-up studies to elucidate the molecular underpinnings of TRS. Our findings further demonstrate the value of both single variant and polygenic association analyses for TRS prediction.\u003c/p\u003e","manuscriptTitle":"Genome-wide association analysis of treatment resistant schizophrenia for variant discovery and polygenic assessment","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-18 18:25:12","doi":"10.21203/rs.3.rs-4614092/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-27T17:27:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-27T13:34:26+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-24T14:39:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"30737094473106613047043090691055202411","date":"2024-08-17T18:22:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"179036945537060860033025178560614568654","date":"2024-08-17T17:18:19+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-05T08:25:13+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-21T00:33:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-21T00:32:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"Human Genomics","date":"2024-06-21T00:18:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"human-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"hugm","sideBox":"Learn more about [Human Genomics](http://humgenomics.biomedcentral.com/)","snPcode":"40246","submissionUrl":"https://submission.nature.com/new-submission/40246/3","title":"Human Genomics","twitterHandle":"@OAgenetics","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d2df8057-e300-440c-8d23-e06d06677d47","owner":[],"postedDate":"July 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-09-30T16:07:40+00:00","versionOfRecord":{"articleIdentity":"rs-4614092","link":"https://doi.org/10.1186/s40246-024-00673-x","journal":{"identity":"human-genomics","isVorOnly":false,"title":"Human Genomics"},"publishedOn":"2024-09-27 15:58:12","publishedOnDateReadable":"September 27th, 2024"},"versionCreatedAt":"2024-07-18 18:25:12","video":"","vorDoi":"10.1186/s40246-024-00673-x","vorDoiUrl":"https://doi.org/10.1186/s40246-024-00673-x","workflowStages":[]},"version":"v1","identity":"rs-4614092","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4614092","identity":"rs-4614092","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}