Genetic overlap between treatment-resistant schizophrenia and smoking initiation

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Mohammad, Nadine Parker, Hasan Ç. Lenk, Lars Ystaas, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7768579/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Early detection of treatment-resistant schizophrenia (TRS) is of substantial clinical importance. While TRS is heritable, the associated genetic variants have been difficult to identify. Cigarette smoking is associated with non-response to antipsychotics, and smoking behavior and schizophrenia have a shared genetic basis. Thus, TRS may also have a shared genetic basis with smoking behavior. Here we aim to identify genetic variants associated with TRS, by leveraging overlapping genetic variants with smoking initiation to increase statistical power. We analyzed genome-wide data for TRS and smoking initiation with the conditional/conjunctional false discovery rate (cond/conjFDR) to identify shared loci, and LD score regression to determine genetic correlations. To investigate potential causal effects of shared loci, we performed Mendelian randomization (MR) analyses. Shared loci were mapped to genes, which were further investigated for enrichment of drug target genes. We observed a significant positive genetic correlation between TRS and smoking initiation (r g = 0.47 p = 0.0002). Leveraging the genetic overlap between TRS and smoking initiation, we identified four novel loci jointly associated with TRS and smoking initiation. The condFDR results improved polygenic prediction of TRS. MR showed putative evidence for a causal effect of genetic liability to TRS on smoking initiation. The functional genetic analyses showed that alpha-1-adrenergic receptors are likely involved in the pathophysiology of TRS and possibly related to the efficacy of clozapine versus other antipsychotic drugs. In conclusion, our results show that shared genetic mechanisms influence both TRS and smoking behavior, which provide new insights into the biological underpinnings of TRS. Biological sciences/Genetics/Genomics/Pharmacogenomics Health sciences/Diseases/Psychiatric disorders/Schizophrenia Treatment-resistant schizophrenia smoking clozapine genetics GWAS Figures Figure 1 Figure 2 Figure 3 Introduction Treatment-resistant schizophrenia (TRS) is defined as a failure of response to at least two antipsychotic drugs administered in adequate dose and duration, and occurs in about 30% of patients with schizophrenia 1 . TRS has been associated with increased mortality, higher rates of suicide attempts, and longer hospital stays, leading to substantial economic burdens due to healthcare utilization 2 . The antipsychotic drug clozapine is superior to other antipsychotics in terms of clinical effect and long-term outcomes 3 – 5 . However, due to the risk of rare but potentially fatal hematological adverse effects 5 – 7 , clozapine’s only indication is TRS. Clozapine treatment is effective in approximately 60% of TRS cases 8 , and may decrease mortality in schizophrenia 3 , 9 . Thus, early identification of TRS is of substantial clinical importance, but a significant challenge is the high clinical and biological heterogeneity that characterizes TRS 10 . Genome-wide association studies (GWAS) have identified hundreds of genetic loci harboring risk variants for schizophrenia 11 . While little progress has been made in identifying genetic associations with pharmacological treatment outcomes in psychiatry 12 , emerging evidence suggests that TRS may have a genetic component 13 , 14 . The identification of genetic variants associated with TRS is limited by insufficient sample sizes as well as variability in definitions of TRS status 15 . No genome-wide significant loci have yet been identified in a GWAS of TRS defined based on the use of clozapine, including the world´s largest sample of 30,826 individuals with schizophrenia (N TRS = 10,501 and N non−TRS = 20,325) 13 . The prevalence of cigarette smoking in schizophrenia is estimated to 70–80%, which is about three times the rate in the general population 16 . Hundreds of loci have been identified for tobacco use in a GWAS including over 1 million individuals 17 , where smoking phenotypes were positively genetically correlated with schizophrenia 17 . A Mendelian randomization study showed shown that genetic liability to cigarette smoking significantly increases the risk of developing schizophrenia 18 . However, the underlying factors driving the high smoking rates in schizophrenia patients are unclear 16 . It has been hypothesized that schizophrenia patients smoke to self-medicate or alleviate negative and cognitive symptoms 19 , 20 . Furthermore, cigarette smoking has been associated with non-response to antipsychotics 21 . In TRS, cigarette smoking has been associated with more severe negative symptoms 22 . While it is known that smoking induces CYP1A2 23 , which metabolizes antipsychotic drugs such as clozapine and olanzapine 24 , 25 , cigarette smoking also decreases the efficacy of olanzapine treatment independently of CYP1A2 genotype 26 . These findings indicate that smoking behavior and non-response to antipsychotics may have a shared genetic basis. Considering the limited understanding of the underlying genetics of TRS based on the GWAS findings so far, complementary statistical approaches are needed to gain better understanding of the genetic underpinnings of TRS and to explore the genetic relationship between TRS and smoking behavior. Hypothesizing that TRS has a shared genetic basis with smoking behavior, we aim to identify genetic variants associated with TRS, by leveraging overlapping genetic associations with smoking initiation to increase power for genetic discovery. Methods GWAS sample description We utilized publicly available GWAS summary statistics for TRS, which included 10,501 TRS cases and 20,325 non-TRS patients, with data derived from the CLOZUK and Psychiatric Genomics Consortium (PGC) cohorts 13 . For smoking initiation (“ever/never smoked regularly”), data were derived from a large-scale GWAS on smoking initiation in a population sample (N = 1,232,091) 17 . All GWAS data utilized in this study are from individuals of European ancestry. The Norwegian Institutional Review Board for the South-East Norway Region has evaluated the current protocol and found that no additional institutional review board approval was needed because no individual data were used. Conditional/conjunctional FDR and genetic correlation analysis To boost discovery of genetic variants associated with TRS, we applied the conditional false discovery rate (condFDR) approach 27 , 28 , using default settings ( Supplementary Methods ). The condFDR re-ranks genetic variants compared to p-value-based ranking and increases the power to discover loci associated with a primary phenotype (TRS) by leveraging associations with a secondary phenotype (smoking initiation) 27 – 29 . We then performed conjunctional FDR (conjFDR) analyses to identify shared variants between TRS and smoking initiation. In conjFDR, the process of the condFDR analysis is repeated switching the roles of the primary and secondary phenotypes. The largest condFDR value between the two runs is then used as the conjFDR value. A variant with a conjFDR less than 0.05 was considered as a shared variant (corresponding to 5 false positive per 100 reported associations). To estimate bivariate genetic correlations between TRS and smoking initiation, we utilized linkage disequilibrium score regression (LDSC) 30 . Locus definition, functional annotation and gene mapping To define genetic loci based on the association summary statistics produced with conjFDR, we used FUMA 31 with default settings. Using FUMA 31 , each lead SNP per identified locus was annotated with Combined Annotation Dependent Depletion (CADD) 32 scores, which predict how deleterious the SNP effect is on protein structure/function, and RegulomeDB 33 scores, which predict the likelihood of regulatory functionality of SNPs. To investigate previous phenotype associations, the identified loci were queried in the GWAS catalogue 34 . Loci were also queried in the GTEx portal (GTEx v8) 35 for known expression quantitative trait loci (eQTLs) across multiple tissues. Identified lead variants were mapped to genes using the Open Targets Genetics platform ( https://genetics.opentargets.org/ ) 36 that provides a Variant to Gene (V2G) association score for each variant-gene prediction, to assign likely causal genes for a given variant. For each lead variant, we considered the top three genes with the highest V2G score as well as the closest gene in case it was not among the top three genes with the highest V2G score. To identify drug-gene interactions, mapped genes were queried in the drug-gene interaction database (dgidb) v5.0.8 (06/12/2024) 37 . More details can be found in Supplementary Methods . Mendelian Randomization To estimate the potential causal relationship of TRS on smoking initiation as well as of smoking initiation on TRS, we used Mendelian randomization (R version 4.1.1, TwoSampleMR version 0.5.6) 38 and reported results for inverse variance weighted 39 , weighted median 40 , weighted mode 41 , and MR Egger 42 ( Supplementary Methods ). Since TRS did not have any genome wide significant SNPs (p < 5e-08), we used a reduced threshold for SNP inclusion (p < 1e-05) when TRS was set as the exposure. This is consistent with previous Mendelian randomization studies with GWAS of low statistical power 43 , 44 . Polygenic prediction of treatment-resistant schizophrenia Using PRSice-2 45 , polygenic scores (PGSs) were calculated using summary statistics for TRS 13 and smoking initiation 46 . We compared PGS based on standard GWAS-ranked lead SNPs with PGS based on condFDR-based ranking, applying the pleioPGS approach 47 , using variant effect sizes derived from the original TRS GWAS. We calculated the PGSs for specific numbers of lead SNPs rather than for significance thresholds to allow for direct comparison between the approaches, at equal numbers of SNPs in each set. We compared the top 100 (approximate number of SNPs p < 1E-5 in the original TRS GWAS) to 105,000 SNPs (number of independent SNPs p < 1 in the original TRS GWAS). Sex, age and the first 10 genetic principal components were included as covariates. The target sample includes 1,635 individuals (819 TRS and 816 non-TRS) from the therapeutic drug monitoring (TDM) service at the Center for Psychopharmacology in Diakonhjemmet Hospital, Oslo, Norway, between January 2005 and August 2022. TRS was defined based on the use/prescription of clozapine, the main drug indicated in TRS 48 , verified by detectable serum concentrations of clozapine. Non-TRS patients had no history of clozapine treatment and had only used other antipsychotics (according to TDM records). Of the 1,635 individuals, 912 were males (481 TRS and 431 non-TRS) and 723 were females (338 TRS and 385 non-TRS). The Regional Committee for Medical and Health Research Ethics and the Investigational Review Board at Diakonhjemmet Hospital approved the study. More information as well as information about genotyping and imputation can be found in Supplementary Methods . Genetically informed drug prioritization Genes identified from Open Targets Genetics 36 were studied within networks of protein-protein interactions (PPIs) of gene products, using the latest version of the human protein interactome 49 , consisting of 18,217 unique proteins (nodes) interconnected by 329,506 PPIs after removing self-loops. As most approved drugs do not target disease-associated proteins but bind to proteins in their network vicinity 50 , we defined a network not only including the genes identified from Open Targets Genetics 36 , but also genes in their immediate network proximity. To define a TRS network, we used the method network propagation 51 – 53 , implemented in the Cytoscape 54 application Diffusion 53 . Genes identified from Open Targets Genetics 36 were used as input query genes, and the top 1% of proteins from the diffusion output were included in the TRS network. The Drug Gene Interaction Database (DGIdb, ( https://www.dgidb.org/ ) v.5.0.8 37 was used to identify drug-gene interactions between approved drugs and genes in the TRS network. Gene-set enrichment analysis (GSEA) was performed to test for enrichment of drug-gene interactions within the TRS network (more details in Supplementary Methods ). Results Genetic overlap between treatment-resistant schizophrenia and smoking initiation Genetic correlation analyses showed a significant positive correlation between TRS and smoking initiation (r g = 0.4716, SE = 0.1277, z-score = 3.6921, p-value = 0.0002). The conditional QQ-plots indicate cross-trait polygenic enrichment between TRS and smoking initiation ( Figure S1 ). This is demonstrated by the leftward deflection, showing an increase in associations with TRS as a function of significance in smoking initiation. At conjFDR < 0.05, we identified four loci jointly associated with TRS and smoking initiation (Table 1 , Fig. 1 ). The same four loci were identified at condFDR < 0.05, with the only difference that the locus on chromosome 16 had another lead SNP (rs9928337). A list of all candidate variants in the identified loci is provided in Table S1 (condFDR) and Table S2 (conjFDR). Investigation of the four identified loci in the GWAS catalog 34 showed that one locus (lead SNP rs494904) has been previously associated with both alcohol use disorder and problematic alcohol use 55 , while no associations have been reported for the other identified loci. Table 1 Novel loci for treatment resistant schizophrenia (TRS) identified through conditional and conjunctional FDR analysis with smoking initiation. Lead SNP Locus (chr: start-end) A1/A2 # Mapped genes p-value in TRS GWAS Beta (SE) in TRS GWAS p-value in Smoking GWAS Beta (SE) in Smoking GWAS conjFDR rs12030126 1: 236808558–236854973 G/T LGALS8 , HEATR1 , ACTN2 3.51e-5 -0.112 (0.027) 2.14e-5 0.007 (0.002) 0.01752 rs494904 2: 45130410–45157336 C/T SIX3 , SIX2 5.77e-5 0.100 (0.025) 7.63e-11 0.010 (0.002) 0.02762 rs4076010 2: 137066601–137119376 T/C DARS1 , CXCR4 , MCM6 1.08e-4 0.090 (0.023) 2.283-3 0.004 (0.002) 0.04924 rs9935028 (rs9928337) 16: 25382373–25454780 G/A ZKSCAN2 , AQP8 , HS3ST4 , ( LCMT1 ) 3.56e-6 -0.104 (0.022) 9.07e-4 0.005 (0.002) 0.00861 Lead SNPs in independent genomic loci jointly associated with TRS and smoking initiation at cond/conjFDR threshold < 0.05. Genomic regions separated by less than 250 kb were merged into a single locus. The table lists chromosomal positions (chr) and includes the top three mapped genes identified through Open Targets Genetics 36 . The nearest gene to the index SNP (in GRCh37 coordinates) is in bold font. The gene LCMT1 was among the top three mapped genes to the lead SNP identified in condFDR (rs9928337). # A1 is the effect allele and A2 is the reference allele. Functional annotations for these loci do not suggest the lead SNPs to be deleterious (CADD scores < 12.37) 32 or likely to have regulatory functionality (RegulomeDB scores = 5–7) 33 . Assessment of the variant-gene relationships in the GTEx database 35 showed significant associations between the lead SNP rs12030126 on chromosome 1 and LGALS8 gene expression, with most significant associations in adipose tissue (p = 4.2e − 7 ), the anterior cingulate cortex (p = 1.7e − 5 ), and nucleus accumbens (p = 5.4e − 5 ). The SNP was also associated with HEATR1 gene expression, which was most significant in the esophagus (2.7e − 12 ) and cerebellum (p = 6.6e − 11 ), as well as with expression of ACTN2 in esophagus (2.8e − 19 ). The lead SNP rs9935028 on chromosome 16 was associated with expression of ZKSCAN2 in muscle (p = 2.5e − 9 ) and adipose tissue (p = 7.0e − 5 ). Further assessment of the mapped genes in the DGIdb 37 showed that AQP8 interacts with 7 approved drugs ( Table S3 ), most of which are prostaglandin analogs or derivates indicated for the treatment of hypertension and/or hormonal or reproductive functions. Moreover, CXCR4 interacts with 5 approved drugs primarily indicated for cancer treatment, and ACTN2 interacts with adenosine triphosphate ( Table S3 ). No interactions with approved drugs were identified for the other genes. Mendelian Randomization Although the GWAS of TRS lacked power to estimate causal effects on smoking initiation using genome-wide significant loci, a relaxed threshold (p < 1e-5) showed a putative causal link to smoking initiation (p < 0.05) using the inverse variance weighted, weighted median, and weighted mode methods ( Table S4 ). No evidence of a causal effect of smoking on TRS was seen ( Table S4 ). Polygenic prediction of treatment-resistant schizophrenia We compared the top 100–105,000 SNPs using original TRS GWAS p-value ranking and condFDR-based ranking ( Figure S1 ), hypothesizing that the boosted power from our conditional analysis would select more informative variants than standard GWAS, resulting in improved PGS performance. The PGS based on condFDR-ranked SNPs explained more of the variance in TRS compared to both the standard TRS PGS and the smoking initiation PGS ( Figure S1 ), with the highest variance explained (R 2 = 0.0079, p = 0.002) at 52,000 SNPs. The highest variance explained by the TRS PGS was at 65,000 SNPs (R 2 = 0.0065, p = 0.005), while condFDR-based ranking achieved equivalent predictive performance by using almost half the number of SNPs (R 2 = 0.0066 at 37,000 SNPs), which indicates a more efficient capture of relevant genetic signal with condFDR-based ranking. Figure 2 shows the PGS performance in TRS for the PGS based on condFDR-ranked SNPs and the standard TRS PGS at 10,000, 20,000, 30,000, 40,000, 50,000, and 105,000 SNPs. The smoking initiation PGS is also plotted for comparison. Genetically informed drug prioritization The genes included in the TRS network (N = 194) and the corresponding diffusion output values can be found in Table S5 . Drug target genes in the TRS network were enriched (p < 0.05) for targets of 11 drugs, most of which were alpha-1 adrenergic receptor agonist/antagonist, used to manage cardiovascular conditions. However, after correcting for the total number of drug-gene interactions (N = 25,290), none of the enrichments remained significant (FDR > 0.05) ( Table S6 ). The TRS network and the drugs identified based on gene-set enrichment analyses are shown in Fig. 3 . Discussion In the present study, we boosted discovery of genetic variants associated with TRS and identified four novel loci associated with TRS after conditioning on smoking initiation. Genetic correlation analysis showed a positive genetic correlation between TRS and smoking initiation, and Mendelian randomization analyses showed putative evidence for a causal effect of TRS on smoking initiation. In the independent validation sample, a PGS based on condFDR-ranked SNPs showed greater variance explained in TRS compared to the standard TRS PGS. From PPI network-based analyses and GSEA, we identified alpha-1-adrenergic receptors as potential targets for TRS. Applying the condFDR framework 27 – 29 , we increased discovery in an underpowered GWAS by leveraging genetic overlap with a second, well-powered GWAS 56 , 57 . We identified four novel loci for TRS, while no loci were identified in the original TRS GWAS 13 . Some of the mapped genes have been previously associated with schizophrenia. LGALS8 (mapped to rs12030126 on chromosome 1), encoding Galectin-8, is downregulated in the hippocampus of schizophrenia patients 58 . It has also been linked to cigarette smoking, with evidence suggesting that cigarette smoke-induced autophagy impairment leads to increased galectin-8 and inflammation 59 . While ZKSCAN2 (mapped to the rs9935028 on chromosome 16) has not been previously associated with schizophrenia, other members of the zinc finger transcription factors family (e.g., ZKSCAN3 and ZKSCAN4) have shown associations with gray matter reduction in schizophrenia 60 , 61 . Aquaporins such as AQP3 and AQP4 have been associated with the pathophysiology of schizophrenia 62 , 63 . While AQP8 (mapped to rs9935028 on chromosome 16) is expressed in the brain, its function in the CNS remains unclear 64 . Alpha-actinin-2, encoded by ACTN2 (mapped to the locus on chromosome 1, rs12030126), could indirectly associate with schizophrenia and possibly TRS through its role in interacting with glutamate N-methyl-D-aspartate (NMDA) receptors 65 , which have been linked to the pathophysiology of both schizophrenia and TRS 66 . The chemokine receptor type 4 ( CXCR4 , mapped to rs4076010 on chromosome 2) has also shown interactions with NMDA receptors, leading to the reduced NMDA receptor signaling that has been associated with the pathophysiology of schizophrenia 67 . Finally, mutations in the SIX3 gene (mapped to rs494904 on chromosome 2) have been associated with both schizophrenia 68 and smoking 69 . Several studies have shown significant genetic correlations between schizophrenia and smoking initiation (r g ranging between 0.10 and 0.16) 17 , 70 , 71 , indicating a shared genetic basis. In a GWAS of smoking behaviors among schizophrenia cases, it was demonstrated that a PGS for smoking initiation was partially shared between schizophrenia cases and the general population 70 . However, the molecular mechanisms underlying the schizophrenia-smoking association are not completely understood 70 . While a genetic overlap between schizophrenia and smoking behavior has been demonstrated in studies applying the cond/conj FDR method 72 , 73 , it remains unknown if shared genetic factors with smoking initiation are different among TRS and non-TRS patients. We demonstrate a significant positive genetic correlation between TRS and smoking initiation that is significantly higher than the genetic correlation between smoking initiation and schizophrenia, supporting a shared genetic basis between TRS and smoking initiation that is independent from the genetic contribution of schizophrenia. By leveraging the identified genetic overlap between TRS and smoking initiation, we show that a PGS based on condFDR-ranked SNPs explained the greatest variance in TRS compared to both the standard TRS PGS and the smoking initiation PGS, albeit the predicted value was small. This pleioPGS approach outperformed the standard GWAS-based ranking, utilizing less SNPs in the PGS, despite using the same SNP weightings, indicating a more efficient capture of relevant genetic signal with condFDR-based ranking. The network analyses implicated two alpha-1-adrenergic receptors (ADRA1B and ADRA1D), and we shortlist several drugs acting on these receptors. Results from several clinical trials have demonstrated that alpha-1-adrenergic receptor antagonists are efficacious in the treatment of negative symptoms and social functioning deficits in schizophrenia 74 – 76 . Clozapine, which shows superior efficacy compared to conventional antipsychotic drugs, shows significant affinity for alpha-adrenergic receptors, especially alpha-1-adrenergic receptors 77 . Of note, clozapine exerts an advantageous therapeutic effect on negative and cognitive symptoms, which are usually rather resistant to treatment with other antipsychotics 78 . Because clozapine displays significant affinities for several neurotransmitter receptors including muscarinic, histaminergic, and adrenergic receptors, with comparatively low D 2 dopamine receptor binding 77 , 79 , a critical question is which of these receptor affinities may contribute to clozapine’s superior therapeutic effect 79 , 80 . It has been hypothesized that clozapine’s superior efficacy is related to its alpha-adrenoceptor modulation, stating that alpha-1- and alpha-2-adrenoceptor blocking stabilizes the dysregulated central dopaminergic systems in schizophrenia 80 . Although the mechanisms involved remain to be fully understood, it has been suggested that antagonism of alpha-1-adrenergic receptors may suppress striatal hyperdopaminergia involved in positive symptoms, while alpha-2-adrenergic receptor antagonism may improve prefrontal dopaminergic functioning thereby reducing negative and cognitive symptoms 80 . Moreover, alpha-1-adrenoceptor antagonism has been related to the metabolic side effects of antipsychotics 77 , 81 , with clozapine being associated with the largest degree of metabolic dysfunction 82 . Interestingly, it has been suggested that clozapine’s effectiveness may be related to its metabolic side effects 56 , 82 . Taken together, these results indicate that alpha-adrenergic receptor antagonism may be considered as treatment for TRS after further investigation. It should be noted that the cond/conjFDR method does not identify the specific causal variants underlying the overlapping genomic loci, and that the detection of cross-trait enrichment is influenced by the power of the investigated GWAS 29 . Although our results highlight how data from low-powered GWASs can still be useful to study genetic architecture and overlap between traits, our results might be influenced by the small sample size of the TRS GWAS. However, despite identifying novel loci for TRS, larger GWAS of TRS are required to better understand the underlying genetics of TRS. In addition, the predictive ability of the PGS remains far from being clinically relevant, and larger GWAS of TRS will also improve SNP weights for polygenic prediction. The phenotyping of the TRS GWAS samples have not recorded comorbid smoking in the schizophrenia cases, and there could potentially be differences in smoking frequency between TRS and non-TRS patients. Moreover, the smoking GWAS samples may include schizophrenia cases, which could suggest that some of the genetic overlap may be due to shared phenotypes. In addition, nicotine and clozapine may have overlapping pharmacological mechanisms of action on acetylcholine receptors, which may be captured in the identified genetic overlap between smoking initiation and TRS defined by clozapine use. Finally, the individuals included in the GWAS used in our cond/conjFDR analyses were of predominantly European ancestry, which suggest that the findings may not translate to other ancestry groups. In conclusion, by conditioning on smoking initiation, we boosted discovery and identified four novel loci associated with TRS. These findings suggest that shared genetic mechanisms influence TRS and smoking behavior. In addition, the results indicate that alpha-1-adrenergic receptors are involved in the pathobiology of TRS and are likely being related to the superior efficacy of clozapine. Together, our results provide new insights into the biological underpinnings of TRS. Declarations Conflict of Interest Dr. Andreassen reported grants from Stiftelsen Kristian Gerhard Jebsen, South-East Regional Health Authority, Research Council of Norway, and European Union’s Horizon 2020 during the conduct of the study; personal fees from cortechs.ai (stock options), Lundbeck (speaker’s honorarium), and Sunovion (speaker’s honorarium) and Janssen (speaker’s honorarium) outside the submitted work. Dr. Anders M. Dale is Founding Director, holds equity in CorTechs Labs, Inc. (DBA Cortechs.ai), and serves on its Board of Directors. Dr. Dale is the President of J. Craig Venter Institute (JCVI) and is a member of the Board of Trustees of JCVI. He is an unpaid consultant for Oslo University Hospital. All other authors report no financial interests or potential conflicts of interest. Code and data availability The code for cond/conjFDR and pleioPGS is publicly available at https://github.com/precimed/pleiofdr and https://github.com/norment/open-science/tree/main/2021_VanderMeer_medRxiv_pleioPGS , respectively. Funding This work was partly performed on the TSD (Tjeneste for Sensitive Data) facilities, owned by the University of Oslo, operated and developed by the TSD service group at the University of Oslo, IT-Department (USIT). Computations were also performed on resources provided by UNINETT Sigma2—the National Infrastructure for High Performance Computing and Data Storage in Norway (NS9666S). We gratefully acknowledge support from the Research Council of Norway (RCN) (296030, 223273, 334920, 300309, 326813, 324252). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 964874 (REALMENT), and from the European Union’s Horizon 2021 research project (EU HORIZON-HLTH-2021, grant 101057454). Author contributions EK, KSO, and OAA conceived the study and were involved in study design. EK, HHM, and NP conducted analyses. EK drafted the initial manuscript. All authors contributed to data interpretation and editing of the manuscript. Acknowledgements We thank the research participants, employees, and researchers of the CLOZUK study, PGC, GSCAN, Center for Precision Psychiatry, University of Oslo, Norway, and Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway for making this research possible. References Kane JM, Correll CU. The Role of Clozapine in Treatment-Resistant Schizophrenia. JAMA Psychiatry 2016; 73(3): 187–188. Kowalec K, Lu Y, Sariaslan A, Song J, Ploner A, Dalman C et al. 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1","display":"","copyAsset":false,"role":"figure","size":48522,"visible":true,"origin":"","legend":"\u003cp\u003eManhattan plot showing genetic variants associated with TRS and smoking initiation by conjunctional FDR analysis, conjFDR \u0026lt; 0.05. The y-axis represents the -log10 transformed conjFDR values for each SNP, and the x-axis represents chromosomal positions. The dotted horizontal line indicates the threshold for significant shared associations (conjFDR \u0026lt; 0.05). Blue circles over the threshold represent lead SNPs with their respective top three genes with the highest variant-to-gene scores.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-7768579/v1/7a7f96b6fa789daa21352923.png"},{"id":94382499,"identity":"e616c115-020b-4b73-90b4-78d6e878791f","added_by":"auto","created_at":"2025-10-27 13:45:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":66220,"visible":true,"origin":"","legend":"\u003cp\u003eExplained variance (on the liability scale) in treatment-resistant schizophrenia (TRS) for polygenic scores (PGS) based on three different SNP rankings: TRS (green), smoking initiation (purple), and conditional FDR-based ranking of TRS conditioned on smoking initiation (pink). PGS were constructed for top 100 – 105,000 independent SNPs from the TRS GWAS summary statistics. The results of explained variance for all SNP ranges are presented in Figure S2.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-7768579/v1/cd287c6254a0b04284301fdb.png"},{"id":94381666,"identity":"a6cfb0a4-8593-4563-9e5c-b724719b99f1","added_by":"auto","created_at":"2025-10-27 13:44:02","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":130086,"visible":true,"origin":"","legend":"\u003cp\u003eTreatment-resistant schizophrenia network (\u003cstrong\u003eA\u003c/strong\u003e) and drug target genes in the network that were enriched for alpha-1 adrenergic receptor modulators (\u003cstrong\u003eB\u003c/strong\u003e). The input genes to build the network are highlighted in pink. Nodes refer to genes or drugs, and edges refer to gene-drug interactions or gene-gene interactions through identified protein-protein interactions between gene products (proteins).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-7768579/v1/da361af67fb69af3dd018781.png"},{"id":98434504,"identity":"935b7830-eab8-44b3-ae1c-e59eacc3e7e3","added_by":"auto","created_at":"2025-12-17 16:52:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1244498,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7768579/v1/61d51c9d-19d0-43ec-834f-c70d854fa851.pdf"},{"id":94381904,"identity":"09aa7f5e-4650-4d49-a836-da8ed28bf76e","added_by":"auto","created_at":"2025-10-27 13:44:25","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":62879,"visible":true,"origin":"","legend":"Supplementary_tables","description":"","filename":"SupplementarytablesTRSandsmoking.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7768579/v1/b9b1e64df0ccac221394d5f5.xlsx"},{"id":94382412,"identity":"476a2f79-ee44-45c5-a6d9-5a12a4bedd35","added_by":"auto","created_at":"2025-10-27 13:45:04","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":380826,"visible":true,"origin":"","legend":"Supplementary_materials","description":"","filename":"SupplementarymaterialsTRSandsmoking.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7768579/v1/79b37b77190a5a8067d32dcb.pdf"}],"financialInterests":"The authors have declared there is \u003cb\u003eNO\u003c/b\u003e conflict of interest to disclose","formattedTitle":"Genetic overlap between treatment-resistant schizophrenia and smoking initiation","fulltext":[{"header":"Introduction","content":"\u003cp\u003eTreatment-resistant schizophrenia (TRS) is defined as a failure of response to at least two antipsychotic drugs administered in adequate dose and duration, and occurs in about 30% of patients with schizophrenia\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. TRS has been associated with increased mortality, higher rates of suicide attempts, and longer hospital stays, leading to substantial economic burdens due to healthcare utilization\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The antipsychotic drug clozapine is superior to other antipsychotics in terms of clinical effect and long-term outcomes\u003csup\u003e\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. However, due to the risk of rare but potentially fatal hematological adverse effects\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, clozapine\u0026rsquo;s only indication is TRS. Clozapine treatment is effective in approximately 60% of TRS cases\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, and may decrease mortality in schizophrenia\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Thus, early identification of TRS is of substantial clinical importance, but a significant challenge is the high clinical and biological heterogeneity that characterizes TRS\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eGenome-wide association studies (GWAS) have identified hundreds of genetic loci harboring risk variants for schizophrenia\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. While little progress has been made in identifying genetic associations with pharmacological treatment outcomes in psychiatry\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e, emerging evidence suggests that TRS may have a genetic component\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. The identification of genetic variants associated with TRS is limited by insufficient sample sizes as well as variability in definitions of TRS status\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. No genome-wide significant loci have yet been identified in a GWAS of TRS defined based on the use of clozapine, including the world\u0026acute;s largest sample of 30,826 individuals with schizophrenia (N\u003csub\u003eTRS\u003c/sub\u003e = 10,501 and N\u003csub\u003enon\u0026minus;TRS\u003c/sub\u003e = 20,325)\u003csup\u003e13\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe prevalence of cigarette smoking in schizophrenia is estimated to 70\u0026ndash;80%, which is about three times the rate in the general population\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Hundreds of loci have been identified for tobacco use in a GWAS including over 1\u0026nbsp;million individuals\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, where smoking phenotypes were positively genetically correlated with schizophrenia\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. A Mendelian randomization study showed shown that genetic liability to cigarette smoking significantly increases the risk of developing schizophrenia\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. However, the underlying factors driving the high smoking rates in schizophrenia patients are unclear\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. It has been hypothesized that schizophrenia patients smoke to self-medicate or alleviate negative and cognitive symptoms\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Furthermore, cigarette smoking has been associated with non-response to antipsychotics\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. In TRS, cigarette smoking has been associated with more severe negative symptoms\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. While it is known that smoking induces CYP1A2\u003csup\u003e23\u003c/sup\u003e, which metabolizes antipsychotic drugs such as clozapine and olanzapine\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e, cigarette smoking also decreases the efficacy of olanzapine treatment independently of CYP1A2 genotype\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. These findings indicate that smoking behavior and non-response to antipsychotics may have a shared genetic basis.\u003c/p\u003e\u003cp\u003eConsidering the limited understanding of the underlying genetics of TRS based on the GWAS findings so far, complementary statistical approaches are needed to gain better understanding of the genetic underpinnings of TRS and to explore the genetic relationship between TRS and smoking behavior. Hypothesizing that TRS has a shared genetic basis with smoking behavior, we aim to identify genetic variants associated with TRS, by leveraging overlapping genetic associations with smoking initiation to increase power for genetic discovery.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eGWAS sample description\u003c/h2\u003e\u003cp\u003eWe utilized publicly available GWAS summary statistics for TRS, which included 10,501 TRS cases and 20,325 non-TRS patients, with data derived from the CLOZUK and Psychiatric Genomics Consortium (PGC) cohorts\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. For smoking initiation (\u0026ldquo;ever/never smoked regularly\u0026rdquo;), data were derived from a large-scale GWAS on smoking initiation in a population sample (N\u0026thinsp;=\u0026thinsp;1,232,091)\u003csup\u003e17\u003c/sup\u003e. All GWAS data utilized in this study are from individuals of European ancestry. The Norwegian Institutional Review Board for the South-East Norway Region has evaluated the current protocol and found that no additional institutional review board approval was needed because no individual data were used.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eConditional/conjunctional FDR and genetic correlation analysis\u003c/h3\u003e\n\u003cp\u003eTo boost discovery of genetic variants associated with TRS, we applied the conditional false discovery rate (condFDR) approach\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e, using default settings (\u003cb\u003eSupplementary Methods\u003c/b\u003e). The condFDR re-ranks genetic variants compared to p-value-based ranking and increases the power to discover loci associated with a primary phenotype (TRS) by leveraging associations with a secondary phenotype (smoking initiation)\u003csup\u003e\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. We then performed conjunctional FDR (conjFDR) analyses to identify shared variants between TRS and smoking initiation. In conjFDR, the process of the condFDR analysis is repeated switching the roles of the primary and secondary phenotypes. The largest condFDR value between the two runs is then used as the conjFDR value. A variant with a conjFDR less than 0.05 was considered as a shared variant (corresponding to 5 false positive per 100 reported associations). To estimate bivariate genetic correlations between TRS and smoking initiation, we utilized linkage disequilibrium score regression (LDSC)\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eLocus definition, functional annotation and gene mapping\u003c/h3\u003e\n\u003cp\u003eTo define genetic loci based on the association summary statistics produced with conjFDR, we used FUMA\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e with default settings. Using FUMA\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, each lead SNP per identified locus was annotated with Combined Annotation Dependent Depletion (CADD)\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e scores, which predict how deleterious the SNP effect is on protein structure/function, and RegulomeDB\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e scores, which predict the likelihood of regulatory functionality of SNPs. To investigate previous phenotype associations, the identified loci were queried in the GWAS catalogue\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. Loci were also queried in the GTEx portal (GTEx v8)\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e for known expression quantitative trait loci (eQTLs) across multiple tissues. Identified lead variants were mapped to genes using the Open Targets Genetics platform (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://genetics.opentargets.org/\u003c/span\u003e\u003cspan address=\"https://genetics.opentargets.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e)\u003csup\u003e36\u003c/sup\u003e that provides a Variant to Gene (V2G) association score for each variant-gene prediction, to assign likely causal genes for a given variant. For each lead variant, we considered the top three genes with the highest V2G score as well as the closest gene in case it was not among the top three genes with the highest V2G score. To identify drug-gene interactions, mapped genes were queried in the drug-gene interaction database (dgidb) v5.0.8 (06/12/2024)\u003csup\u003e37\u003c/sup\u003e. More details can be found in \u003cb\u003eSupplementary Methods\u003c/b\u003e.\u003c/p\u003e\n\u003ch3\u003eMendelian Randomization\u003c/h3\u003e\n\u003cp\u003eTo estimate the potential causal relationship of TRS on smoking initiation as well as of smoking initiation on TRS, we used Mendelian randomization (R version 4.1.1, TwoSampleMR version 0.5.6)\u003csup\u003e38\u003c/sup\u003e and reported results for inverse variance weighted\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, weighted median\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e, weighted mode\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, and MR Egger\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e (\u003cb\u003eSupplementary Methods\u003c/b\u003e). Since TRS did not have any genome wide significant SNPs (p\u0026thinsp;\u0026lt;\u0026thinsp;5e-08), we used a reduced threshold for SNP inclusion (p\u0026thinsp;\u0026lt;\u0026thinsp;1e-05) when TRS was set as the exposure. This is consistent with previous Mendelian randomization studies with GWAS of low statistical power\u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003ePolygenic prediction of treatment-resistant schizophrenia\u003c/h3\u003e\n\u003cp\u003eUsing PRSice-2\u003csup\u003e45\u003c/sup\u003e, polygenic scores (PGSs) were calculated using summary statistics for TRS\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e and smoking initiation\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. We compared PGS based on standard GWAS-ranked lead SNPs with PGS based on condFDR-based ranking, applying the pleioPGS approach\u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e, using variant effect sizes derived from the original TRS GWAS. We calculated the PGSs for specific numbers of lead SNPs rather than for significance thresholds to allow for direct comparison between the approaches, at equal numbers of SNPs in each set. We compared the top 100 (approximate number of SNPs p\u0026thinsp;\u0026lt;\u0026thinsp;1E-5 in the original TRS GWAS) to 105,000 SNPs (number of independent SNPs p\u0026thinsp;\u0026lt;\u0026thinsp;1 in the original TRS GWAS). Sex, age and the first 10 genetic principal components were included as covariates.\u003c/p\u003e\u003cp\u003eThe target sample includes 1,635 individuals (819 TRS and 816 non-TRS) from the therapeutic drug monitoring (TDM) service at the Center for Psychopharmacology in Diakonhjemmet Hospital, Oslo, Norway, between January 2005 and August 2022. TRS was defined based on the use/prescription of clozapine, the main drug indicated in TRS\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, verified by detectable serum concentrations of clozapine. Non-TRS patients had no history of clozapine treatment and had only used other antipsychotics (according to TDM records). Of the 1,635 individuals, 912 were males (481 TRS and 431 non-TRS) and 723 were females (338 TRS and 385 non-TRS). The Regional Committee for Medical and Health Research Ethics and the Investigational Review Board at Diakonhjemmet Hospital approved the study. More information as well as information about genotyping and imputation can be found in \u003cb\u003eSupplementary Methods\u003c/b\u003e.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eGenetically informed drug prioritization\u003c/h2\u003e\u003cp\u003eGenes identified from Open Targets Genetics\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e were studied within networks of protein-protein interactions (PPIs) of gene products, using the latest version of the human protein interactome\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, consisting of 18,217 unique proteins (nodes) interconnected by 329,506 PPIs after removing self-loops. As most approved drugs do not target disease-associated proteins but bind to proteins in their network vicinity\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e, we defined a network not only including the genes identified from Open Targets Genetics\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, but also genes in their immediate network proximity. To define a TRS network, we used the method network propagation\u003csup\u003e\u003cspan additionalcitationids=\"CR52\" citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, implemented in the Cytoscape\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e application Diffusion\u003csup\u003e\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. Genes identified from Open Targets Genetics\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e were used as input query genes, and the top 1% of proteins from the diffusion output were included in the TRS network. The Drug Gene Interaction Database (DGIdb, (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.dgidb.org/\u003c/span\u003e\u003cspan address=\"https://www.dgidb.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) v.5.0.8\u003csup\u003e37\u003c/sup\u003e was used to identify drug-gene interactions between approved drugs and genes in the TRS network. Gene-set enrichment analysis (GSEA) was performed to test for enrichment of drug-gene interactions within the TRS network (more details in \u003cb\u003eSupplementary Methods\u003c/b\u003e).\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eGenetic overlap between treatment-resistant schizophrenia and smoking initiation\u003c/h2\u003e\u003cp\u003eGenetic correlation analyses showed a significant positive correlation between TRS and smoking initiation (r\u003csub\u003eg\u003c/sub\u003e = 0.4716, SE\u0026thinsp;=\u0026thinsp;0.1277, z-score\u0026thinsp;=\u0026thinsp;3.6921, p-value\u0026thinsp;=\u0026thinsp;0.0002). The conditional QQ-plots indicate cross-trait polygenic enrichment between TRS and smoking initiation (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e). This is demonstrated by the leftward deflection, showing an increase in associations with TRS as a function of significance in smoking initiation. At conjFDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05, we identified four loci jointly associated with TRS and smoking initiation (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The same four loci were identified at condFDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05, with the only difference that the locus on chromosome 16 had another lead SNP (rs9928337). A list of all candidate variants in the identified loci is provided in \u003cb\u003eTable \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e (condFDR) and \u003cb\u003eTable S2\u003c/b\u003e (conjFDR). Investigation of the four identified loci in the GWAS catalog\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e showed that one locus (lead SNP rs494904) has been previously associated with both alcohol use disorder and problematic alcohol use\u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e, while no associations have been reported for the other identified loci.\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\u003eNovel loci for treatment resistant schizophrenia (TRS) identified through conditional and conjunctional FDR analysis with smoking initiation.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLead SNP\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLocus (chr: start-end)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eA1/A2\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMapped genes\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value in TRS GWAS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eBeta (SE) in TRS GWAS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003ep-value in Smoking GWAS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003eBeta (SE) in Smoking GWAS\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c9\"\u003e\u003cp\u003econjFDR\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ers12030126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1: 236808558\u0026ndash;236854973\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eG/T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eLGALS8\u003c/em\u003e, \u003cem\u003eHEATR1\u003c/em\u003e, \u003cb\u003eACTN2\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.51e-5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.112 (0.027)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.14e-5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.007 (0.002)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.01752\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ers494904\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2: 45130410\u0026ndash;45157336\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eC/T\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eSIX3\u003c/b\u003e, \u003cem\u003eSIX2\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.77e-5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.100 (0.025)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e7.63e-11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.010 (0.002)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.02762\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ers4076010\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2: 137066601\u0026ndash;137119376\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eT/C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cem\u003eDARS1\u003c/em\u003e, \u003cb\u003eCXCR4\u003c/b\u003e, \u003cem\u003eMCM6\u003c/em\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.08e-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e0.090 (0.023)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.283-3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.004 (0.002)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.04924\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ers9935028 (rs9928337)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e16: 25382373\u0026ndash;25454780\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eG/A\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003eZKSCAN2\u003c/b\u003e, \u003cem\u003eAQP8\u003c/em\u003e, \u003cem\u003eHS3ST4\u003c/em\u003e, (\u003cem\u003eLCMT1\u003c/em\u003e)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.56e-6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e-0.104 (0.022)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e9.07e-4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e\u003cp\u003e0.005 (0.002)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.00861\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003eLead SNPs in independent genomic loci jointly associated with TRS and smoking initiation at cond/conjFDR threshold\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Genomic regions separated by less than 250 kb were merged into a single locus. The table lists chromosomal positions (chr) and includes the top three mapped genes identified through Open Targets Genetics\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. The nearest gene to the index SNP (in GRCh37 coordinates) is in bold font. The gene \u003cem\u003eLCMT1\u003c/em\u003e was among the top three mapped genes to the lead SNP identified in condFDR (rs9928337). \u003csup\u003e#\u003c/sup\u003eA1 is the effect allele and A2 is the reference allele.\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eFunctional annotations for these loci do not suggest the lead SNPs to be deleterious (CADD scores\u0026thinsp;\u0026lt;\u0026thinsp;12.37)\u003csup\u003e32\u003c/sup\u003e or likely to have regulatory functionality (RegulomeDB scores\u0026thinsp;=\u0026thinsp;5\u0026ndash;7)\u003csup\u003e33\u003c/sup\u003e. Assessment of the variant-gene relationships in the GTEx database\u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e showed significant associations between the lead SNP rs12030126 on chromosome 1 and \u003cem\u003eLGALS8\u003c/em\u003e gene expression, with most significant associations in adipose tissue (p\u0026thinsp;=\u0026thinsp;4.2e\u003csup\u003e\u0026minus;\u0026thinsp;7\u003c/sup\u003e), the anterior cingulate cortex (p\u0026thinsp;=\u0026thinsp;1.7e\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e), and nucleus accumbens (p\u0026thinsp;=\u0026thinsp;5.4e\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e). The SNP was also associated with \u003cem\u003eHEATR1\u003c/em\u003e gene expression, which was most significant in the esophagus (2.7e\u003csup\u003e\u0026minus;\u0026thinsp;12\u003c/sup\u003e) and cerebellum (p\u0026thinsp;=\u0026thinsp;6.6e\u003csup\u003e\u0026minus;\u0026thinsp;11\u003c/sup\u003e), as well as with expression of \u003cem\u003eACTN2\u003c/em\u003e in esophagus (2.8e\u003csup\u003e\u0026minus;\u0026thinsp;19\u003c/sup\u003e). The lead SNP rs9935028 on chromosome 16 was associated with expression of \u003cem\u003eZKSCAN2\u003c/em\u003e in muscle (p\u0026thinsp;=\u0026thinsp;2.5e\u003csup\u003e\u0026minus;\u0026thinsp;9\u003c/sup\u003e) and adipose tissue (p\u0026thinsp;=\u0026thinsp;7.0e\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e). Further assessment of the mapped genes in the DGIdb\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e showed that \u003cem\u003eAQP8\u003c/em\u003e interacts with 7 approved drugs (\u003cb\u003eTable S3\u003c/b\u003e), most of which are prostaglandin analogs or derivates indicated for the treatment of hypertension and/or hormonal or reproductive functions. Moreover, \u003cem\u003eCXCR4\u003c/em\u003e interacts with 5 approved drugs primarily indicated for cancer treatment, and \u003cem\u003eACTN2\u003c/em\u003e interacts with adenosine triphosphate (\u003cb\u003eTable S3\u003c/b\u003e). No interactions with approved drugs were identified for the other genes.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eMendelian Randomization\u003c/h2\u003e\u003cp\u003eAlthough the GWAS of TRS lacked power to estimate causal effects on smoking initiation using genome-wide significant loci, a relaxed threshold (p\u0026thinsp;\u0026lt;\u0026thinsp;1e-5) showed a putative causal link to smoking initiation (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) using the inverse variance weighted, weighted median, and weighted mode methods (\u003cb\u003eTable S4\u003c/b\u003e). No evidence of a causal effect of smoking on TRS was seen (\u003cb\u003eTable S4\u003c/b\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003ePolygenic prediction of treatment-resistant schizophrenia\u003c/h2\u003e\u003cp\u003eWe compared the top 100\u0026ndash;105,000 SNPs using original TRS GWAS p-value ranking and condFDR-based ranking (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e), hypothesizing that the boosted power from our conditional analysis would select more informative variants than standard GWAS, resulting in improved PGS performance. The PGS based on condFDR-ranked SNPs explained more of the variance in TRS compared to both the standard TRS PGS and the smoking initiation PGS (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e), with the highest variance explained (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0079, p\u0026thinsp;=\u0026thinsp;0.002) at 52,000 SNPs. The highest variance explained by the TRS PGS was at 65,000 SNPs (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0065, p\u0026thinsp;=\u0026thinsp;0.005), while condFDR-based ranking achieved equivalent predictive performance by using almost half the number of SNPs (R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;0.0066 at 37,000 SNPs), which indicates a more efficient capture of relevant genetic signal with condFDR-based ranking. Figure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e shows the PGS performance in TRS for the PGS based on condFDR-ranked SNPs and the standard TRS PGS at 10,000, 20,000, 30,000, 40,000, 50,000, and 105,000 SNPs. The smoking initiation PGS is also plotted for comparison.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eGenetically informed drug prioritization\u003c/h2\u003e\u003cp\u003eThe genes included in the TRS network (N\u0026thinsp;=\u0026thinsp;194) and the corresponding diffusion output values can be found in \u003cb\u003eTable S5\u003c/b\u003e. Drug target genes in the TRS network were enriched (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) for targets of 11 drugs, most of which were alpha-1 adrenergic receptor agonist/antagonist, used to manage cardiovascular conditions. However, after correcting for the total number of drug-gene interactions (N\u0026thinsp;=\u0026thinsp;25,290), none of the enrichments remained significant (FDR\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (\u003cb\u003eTable S6\u003c/b\u003e). The TRS network and the drugs identified based on gene-set enrichment analyses are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn the present study, we boosted discovery of genetic variants associated with TRS and identified four novel loci associated with TRS after conditioning on smoking initiation. Genetic correlation analysis showed a positive genetic correlation between TRS and smoking initiation, and Mendelian randomization analyses showed putative evidence for a causal effect of TRS on smoking initiation. In the independent validation sample, a PGS based on condFDR-ranked SNPs showed greater variance explained in TRS compared to the standard TRS PGS. From PPI network-based analyses and GSEA, we identified alpha-1-adrenergic receptors as potential targets for TRS.\u003c/p\u003e\u003cp\u003eApplying the condFDR framework\u003csup\u003e\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e, we increased discovery in an underpowered GWAS by leveraging genetic overlap with a second, well-powered GWAS\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e. We identified four novel loci for TRS, while no loci were identified in the original TRS GWAS\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Some of the mapped genes have been previously associated with schizophrenia. \u003cem\u003eLGALS8\u003c/em\u003e (mapped to rs12030126 on chromosome 1), encoding Galectin-8, is downregulated in the hippocampus of schizophrenia patients\u003csup\u003e\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e\u003c/sup\u003e. It has also been linked to cigarette smoking, with evidence suggesting that cigarette smoke-induced autophagy impairment leads to increased galectin-8 and inflammation\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e. While \u003cem\u003eZKSCAN2\u003c/em\u003e (mapped to the rs9935028 on chromosome 16) has not been previously associated with schizophrenia, other members of the zinc finger transcription factors family (e.g., ZKSCAN3 and ZKSCAN4) have shown associations with gray matter reduction in schizophrenia\u003csup\u003e\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u003c/sup\u003e. Aquaporins such as AQP3 and AQP4 have been associated with the pathophysiology of schizophrenia\u003csup\u003e\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. While AQP8 (mapped to rs9935028 on chromosome 16) is expressed in the brain, its function in the CNS remains unclear \u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u003c/sup\u003e. Alpha-actinin-2, encoded by \u003cem\u003eACTN2\u003c/em\u003e (mapped to the locus on chromosome 1, rs12030126), could indirectly associate with schizophrenia and possibly TRS through its role in interacting with glutamate N-methyl-D-aspartate (NMDA) receptors\u003csup\u003e\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e, which have been linked to the pathophysiology of both schizophrenia and TRS\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. The chemokine receptor type 4 (\u003cem\u003eCXCR4\u003c/em\u003e, mapped to rs4076010 on chromosome 2) has also shown interactions with NMDA receptors, leading to the reduced NMDA receptor signaling that has been associated with the pathophysiology of schizophrenia\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e\u003c/sup\u003e. Finally, mutations in the \u003cem\u003eSIX3\u003c/em\u003e gene (mapped to rs494904 on chromosome 2) have been associated with both schizophrenia\u003csup\u003e\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e and smoking\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eSeveral studies have shown significant genetic correlations between schizophrenia and smoking initiation (r\u003csub\u003eg\u003c/sub\u003e ranging between 0.10 and 0.16)\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e, \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e, indicating a shared genetic basis. In a GWAS of smoking behaviors among schizophrenia cases, it was demonstrated that a PGS for smoking initiation was partially shared between schizophrenia cases and the general population\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. However, the molecular mechanisms underlying the schizophrenia-smoking association are not completely understood\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. While a genetic overlap between schizophrenia and smoking behavior has been demonstrated in studies applying the cond/conj FDR method\u003csup\u003e\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e\u003c/sup\u003e, it remains unknown if shared genetic factors with smoking initiation are different among TRS and non-TRS patients. We demonstrate a significant positive genetic correlation between TRS and smoking initiation that is significantly higher than the genetic correlation between smoking initiation and schizophrenia, supporting a shared genetic basis between TRS and smoking initiation that is independent from the genetic contribution of schizophrenia. By leveraging the identified genetic overlap between TRS and smoking initiation, we show that a PGS based on condFDR-ranked SNPs explained the greatest variance in TRS compared to both the standard TRS PGS and the smoking initiation PGS, albeit the predicted value was small. This pleioPGS approach outperformed the standard GWAS-based ranking, utilizing less SNPs in the PGS, despite using the same SNP weightings, indicating a more efficient capture of relevant genetic signal with condFDR-based ranking.\u003c/p\u003e\u003cp\u003eThe network analyses implicated two alpha-1-adrenergic receptors (ADRA1B and ADRA1D), and we shortlist several drugs acting on these receptors. Results from several clinical trials have demonstrated that alpha-1-adrenergic receptor antagonists are efficacious in the treatment of negative symptoms and social functioning deficits in schizophrenia\u003csup\u003e\u003cspan additionalcitationids=\"CR75\" citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e\u003c/sup\u003e. Clozapine, which shows superior efficacy compared to conventional antipsychotic drugs, shows significant affinity for alpha-adrenergic receptors, especially alpha-1-adrenergic receptors\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e\u003c/sup\u003e. Of note, clozapine exerts an advantageous therapeutic effect on negative and cognitive symptoms, which are usually rather resistant to treatment with other antipsychotics\u003csup\u003e\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e\u003c/sup\u003e. Because clozapine displays significant affinities for several neurotransmitter receptors including muscarinic, histaminergic, and adrenergic receptors, with comparatively low D\u003csub\u003e2\u003c/sub\u003e dopamine receptor binding\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e\u003c/sup\u003e, a critical question is which of these receptor affinities may contribute to clozapine\u0026rsquo;s superior therapeutic effect\u003csup\u003e\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e. It has been hypothesized that clozapine\u0026rsquo;s superior efficacy is related to its alpha-adrenoceptor modulation, stating that alpha-1- and alpha-2-adrenoceptor blocking stabilizes the dysregulated central dopaminergic systems in schizophrenia\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e. Although the mechanisms involved remain to be fully understood, it has been suggested that antagonism of alpha-1-adrenergic receptors may suppress striatal hyperdopaminergia involved in positive symptoms, while alpha-2-adrenergic receptor antagonism may improve prefrontal dopaminergic functioning thereby reducing negative and cognitive symptoms\u003csup\u003e\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e\u003c/sup\u003e. Moreover, alpha-1-adrenoceptor antagonism has been related to the metabolic side effects of antipsychotics\u003csup\u003e\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e, \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e\u003c/sup\u003e, with clozapine being associated with the largest degree of metabolic dysfunction\u003csup\u003e\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e. Interestingly, it has been suggested that clozapine\u0026rsquo;s effectiveness may be related to its metabolic side effects\u003csup\u003e\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e\u003c/sup\u003e. Taken together, these results indicate that alpha-adrenergic receptor antagonism may be considered as treatment for TRS after further investigation.\u003c/p\u003e\u003cp\u003eIt should be noted that the cond/conjFDR method does not identify the specific causal variants underlying the overlapping genomic loci, and that the detection of cross-trait enrichment is influenced by the power of the investigated GWAS\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Although our results highlight how data from low-powered GWASs can still be useful to study genetic architecture and overlap between traits, our results might be influenced by the small sample size of the TRS GWAS. However, despite identifying novel loci for TRS, larger GWAS of TRS are required to better understand the underlying genetics of TRS. In addition, the predictive ability of the PGS remains far from being clinically relevant, and larger GWAS of TRS will also improve SNP weights for polygenic prediction. The phenotyping of the TRS GWAS samples have not recorded comorbid smoking in the schizophrenia cases, and there could potentially be differences in smoking frequency between TRS and non-TRS patients. Moreover, the smoking GWAS samples may include schizophrenia cases, which could suggest that some of the genetic overlap may be due to shared phenotypes. In addition, nicotine and clozapine may have overlapping pharmacological mechanisms of action on acetylcholine receptors, which may be captured in the identified genetic overlap between smoking initiation and TRS defined by clozapine use. Finally, the individuals included in the GWAS used in our cond/conjFDR analyses were of predominantly European ancestry, which suggest that the findings may not translate to other ancestry groups.\u003c/p\u003e\u003cp\u003eIn conclusion, by conditioning on smoking initiation, we boosted discovery and identified four novel loci associated with TRS. These findings suggest that shared genetic mechanisms influence TRS and smoking behavior. In addition, the results indicate that alpha-1-adrenergic receptors are involved in the pathobiology of TRS and are likely being related to the superior efficacy of clozapine. Together, our results provide new insights into the biological underpinnings of TRS.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConflict of Interest\u003c/h2\u003e\n\u003cp\u003eDr. Andreassen reported grants from Stiftelsen Kristian Gerhard Jebsen, South-East Regional Health Authority, Research Council of Norway, and European Union\u0026rsquo;s Horizon 2020 during the conduct of the study; personal fees from cortechs.ai (stock options), Lundbeck (speaker\u0026rsquo;s honorarium), and Sunovion (speaker\u0026rsquo;s honorarium) and Janssen (speaker\u0026rsquo;s honorarium) outside the submitted work. Dr. Anders M. Dale is Founding Director, holds equity in CorTechs Labs, Inc. (DBA Cortechs.ai), and serves on its Board of Directors. Dr. Dale is the President of J. Craig Venter Institute (JCVI) and is a member of the Board of Trustees of JCVI. He is an unpaid consultant for Oslo University Hospital. All other authors report no financial interests or potential conflicts of interest.\u003c/p\u003e\n\u003ch2\u003eCode and data availability\u003c/h2\u003e\n\u003cp\u003eThe code for cond/conjFDR and pleioPGS is publicly available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/precimed/pleiofdr\u003c/span\u003e\u003c/span\u003e and \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/norment/open-science/tree/main/2021_VanderMeer_medRxiv_pleioPGS\u003c/span\u003e\u003c/span\u003e, respectively.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was partly performed on the TSD (Tjeneste for Sensitive Data) facilities, owned by the University of Oslo, operated and developed by the TSD service group at the University of Oslo, IT-Department (USIT). Computations were also performed on resources provided by UNINETT Sigma2\u0026mdash;the National Infrastructure for High Performance Computing and Data Storage in Norway (NS9666S). We gratefully acknowledge support from the Research Council of Norway (RCN) (296030, 223273, 334920, 300309, 326813, 324252). This project has received funding from the European Union\u0026rsquo;s Horizon 2020 research and innovation programme under grant agreement No 964874 (REALMENT), and from the European Union\u0026rsquo;s Horizon 2021 research project (EU HORIZON-HLTH-2021, grant 101057454).\u003c/p\u003e\n\u003ch2\u003eAuthor contributions\u003c/h2\u003e\n\u003cp\u003eEK, KSO, and OAA conceived the study and were involved in study design. EK, HHM, and NP conducted analyses. EK drafted the initial manuscript. All authors contributed to data interpretation and editing of the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe thank the research participants, employees, and researchers of the CLOZUK study, PGC, GSCAN, Center for Precision Psychiatry, University of Oslo, Norway, and Center for Psychopharmacology, Diakonhjemmet Hospital, Oslo, Norway for making this research possible.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKane JM, Correll CU. 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While TRS is heritable, the associated genetic variants have been difficult to identify. Cigarette smoking is associated with non-response to antipsychotics, and smoking behavior and schizophrenia have a shared genetic basis. Thus, TRS may also have a shared genetic basis with smoking behavior. Here we aim to identify genetic variants associated with TRS, by leveraging overlapping genetic variants with smoking initiation to increase statistical power. We analyzed genome-wide data for TRS and smoking initiation with the conditional/conjunctional false discovery rate (cond/conjFDR) to identify shared loci, and LD score regression to determine genetic correlations. To investigate potential causal effects of shared loci, we performed Mendelian randomization (MR) analyses. Shared loci were mapped to genes, which were further investigated for enrichment of drug target genes. We observed a significant positive genetic correlation between TRS and smoking initiation (r\u003csub\u003eg\u003c/sub\u003e = 0.47 p\u0026thinsp;=\u0026thinsp;0.0002). Leveraging the genetic overlap between TRS and smoking initiation, we identified four novel loci jointly associated with TRS and smoking initiation. The condFDR results improved polygenic prediction of TRS. MR showed putative evidence for a causal effect of genetic liability to TRS on smoking initiation. The functional genetic analyses showed that alpha-1-adrenergic receptors are likely involved in the pathophysiology of TRS and possibly related to the efficacy of clozapine versus other antipsychotic drugs. In conclusion, our results show that shared genetic mechanisms influence both TRS and smoking behavior, which provide new insights into the biological underpinnings of TRS.\u003c/p\u003e","manuscriptTitle":"Genetic overlap between treatment-resistant schizophrenia and smoking initiation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-25 09:02:57","doi":"10.21203/rs.3.rs-7768579/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e38d3bdc-7591-4625-8b2f-3d5637c94987","owner":[],"postedDate":"October 25th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56141652,"name":"Biological sciences/Genetics/Genomics/Pharmacogenomics"},{"id":56141653,"name":"Health sciences/Diseases/Psychiatric disorders/Schizophrenia"}],"tags":[],"updatedAt":"2025-12-16T08:59:01+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-25 09:02:57","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7768579","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7768579","identity":"rs-7768579","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}