Discovery of a novel pharmacogenomic biomarker on ANK3gene for liafensine, a triple reuptake inhibitor for treatment-resistant depression

Discovery of a novel pharmacogenomic biomarker on ANK3gene for liafensine, a triple reuptake inhibitor for treatment-resistant depression | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Discovery of a novel pharmacogenomic biomarker on ANK3 gene for liafensine, a triple reuptake inhibitor for treatment-resistant depression Wen Luo, Gang Wang, John W. Whitaker, Zafrin Dhali, Hong Sun, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6736436/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 Liafensine is a first-in-class triple reuptake inhibitor targeting transporters for serotonin, norepinephrine, and dopamine for treatment-resistant depression (TRD). It did not exhibit efficacy in non-biomarker-selected TRD patients in two Phase 2b studies. We utilized the blood samples from the patients enrolled in these two studies and extracted genomic DNA to conduct a genome‑wide association study aiming to find a biomarker which can predict liafensine response. A single single-nucleotide polymorphism (SNP), rs12217173, at ANK3 gene was identified as strongly associated with treatment response to liafensine (p = 6.61×10 -8 ) in the discovery set and was further confirmed in the replication sample set. In addition, this SNP was not associated with the efficacy of the duloxetine or escitalopram, suggesting it is a liafensine-specific biomarker. This finding was subsequently confirmed in a prospective clinical study. Thus, this study represents a novel approach to translate precision medicine into psychiatric diseases. Bioinformatics Computational Biology Medical Genetics Computational Neuroscience Depression TRD Biomarker Antidepressant ANK3 Pharmacogenomic Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Precision medicine using biomarkers to tailor drug treatment to those patients who can benefit the most is revolutionizing modern drug development. Particularly, in the field of oncology, many novel drugs have been approved with companion pharmacogenomic biomarkers. For example, lung cancer is divided into several subtypes which are classified by different pharmacogenomic biomarkers and are treated with different target therapies accordingly. 1 We believe a similar approach can be applied to other therapeutic areas, such as psychiatry, which has not had many biomarkers available to guide drug development. As a result, this may be one of the factors contributing to the high failure rate in psychiatric clinical studies. Treatment-resistant depression (TRD) is a severe form of major depressive disorder (MDD), in which patients have had an inadequate response to previous antidepressant treatments. Up to 55% of people with MDD meet the criteria for TRD. 2,3 It is a serious and life-threatening condition with high rates of individual and society-level morbidity, mortality, medical and economic costs. Although there are more than 20 drugs approved to treat MDD, the development of new drugs to treat TRD has been challenging. Only two drugs have been approved by the United States Food and Drug Administration: Symbyax® and Spravato®. Symbyax is a fixed‑dose combination of olanzapine and fluoxetine with clinical efficacy. However, its use is limited by adverse reactions such as metabolic dysfunction, weight gain, and extrapyramidal symptoms which are poorly tolerated by many patients. Spravato (esketamine) nasal spray, in conjunction with an oral antidepressant, is the only new drug approved for TRD over the last 15 years. It demonstrates rapid onset of treatment effect, but is associated with significant adverse reactions including sedation, dissociation, respiratory depression, and abuse and misuse. The risks of sedation, dissociation, and respiratory depression require monitoring by a healthcare provider for at least 2 hours at each treatment session. 4,5 Consequently, Spravato is available only through a Risk Evaluation and Mitigation Strategy program. Psychotherapeutic interventions in combination with an antidepressant may offer partial symptomatic relief in persons with TRD, but their efficacy as monotherapy is not established. 6-9 The significant unmet needs in TRD patients highlight the importance of developing new classes of treatment that balance the risk-benefit profile to deliver an optimal approach to manage TRD effectively. The monoamine hypothesis of depression postulates primary dysfunction of serotonin (5-HT), norepinephrine (NE), and dopamine (DA) systems in the brain. This hypothetical framework has guided development of antidepressants for many years. Selective serotonin reuptake inhibitors (SSRIs), and dual serotonin and norepinephrine reuptake inhibitors (SNRIs) are two commonly prescribed classes of antidepressants to treat MDD. Thus, a drug that can simultaneously modulate 5-HT, NE, and DA, a triple reuptake inhibitor (TRI), was postulated to be an attractive approach to treat TRD. Liafensine (formerly BMS-820836 and AMR-000013, also known as DB104) is a potent and selective inhibitor of the reuptake of three monoamines: 5‑HT, NE, and DA by targeting the 5‑HT transporter (SERT), NE transporter (NET), and DA transporter (DAT), respectively. It was brought through significant preclinical research and early development by Bristol Myers Squibb (BMS), then evaluated as monotherapy in Phase 2b clinical studies for the treatment of TRD patients who have experienced inadequate response in two separate trials, CN162006 and CN162007. 10 Both CN162006 and CN162007 were global, multicenter, randomized, double-blind studies. Each study has three phases: screening (Phase A), prospective treatment with duloxetine or escitalopram (Phase B), and randomized treatment (Phase C) (Figure 1a). CN162006 was a flexible-dose (0.5–2 mg/day) study and CN162007 was a fixed-dose (0.25, 0.5, 1 or 2 mg/day) study. Liafensine was well tolerated, with no evidence of dose-dependent discontinuations due to adverse events. However, it did not demonstrate efficacy compared to the control arms in the two Phase 2b TRD studies (Figure 1b). The addition of the dopamine activity of liafensine should in theory offer differential efficacy over SNRIs in some TRD patients. But this requires us to find a pharmacogenomic biomarker to identify the subset of patients who can benefit from liafensine. In contrast to oncology wherein most of the tumor biomarkers are considered to be driver gene mutations which are related to tumorigenesis as well as the drug response, the pathogenesis of psychiatric diseases is much more complicated as the brain is the most complex organ in humans. Therefore, in the current study, instead of focusing only on the drug target genes, we conducted genome-wide association research with archived samples from the two failed Phase 2b studies to identify novel genetic biomarkers that correlated with liafensine efficacy. Results From the randomized treatment phase (Phase C) of CN162006 and CN162007 studies, DNA or whole blood samples were available for 233 liafensine-treated patients. These samples were randomly divided into two independent sets: 186 for discovery set and 47 for replication set (Figure 1c). The DNA samples from the 186 patients from the discovery set were successfully genotyped and passed quality control. From the genotyping data, single-nucleotide polymorphisms (SNPs) from sex chromosomes, with missing call rates greater than 2%, or with minor allele frequency below 5% were removed, resulting in 1,789,293 SNPs for the subsequent analysis. The Montgomery-Åsberg Depression Rating Scale (MADRS) is a clinical assessment tool designed to measure the severity of depressive episodes in patients with mood disorders. The 10 items in the MADRS are each scored between 0 and 6. Zero represents normal or baseline, and 6 represents continuous or severe presence of symptoms. MADRS is widely used and one of the gold standards to measure the efficacy of antidepressant therapy. Thus, the 186‑patient discovery set was dichotomized into 92 responders and 94 non-responders using the overall median MADRS total score change as the cutoff. After performing genotype-phonotype association analysis, the strongest association for liafensine treatment effect is the SNP rs12217173 with a p-value of 6.61×10 -8 (Figure 2). This p-value almost reaches the genome‑wide significance cut-off of 5×10 -8 . We still considered this top SNP as significant given the small sample size of 186, which is far less than most genome‑wide association studies. This SNP is located on chromosome 10 in an intron of the ANK3 (Ankyrin 3) gene. Ankyrins are a family of proteins that are believed to link the integral membrane proteins to the underlying spectrin-actin cytoskeleton. The ANK3 gene is mainly expressed in the central and peripheral nervous system, 11 and is associated with several neuropsychiatric disorders. 12 Thus we named this biomarker as ANK3 biomarker and also termed as DGM4 (Denovo Genetic Marker 4). Subsequently we analyzed the efficacy of liafensine treatment in each of the three genotypes of rs12217173 (designated AA, AG, and GG) within the discovery set as shown in Figure 3a. Liafensine‑treated patients with the GG genotype at ANK3 biomarker exhibited clinically much better improvement in MADRS total score change from baseline compared to those with the AA or AG genotype (5.6‑point or 4.4‑point improvement in MADRS total score changes at Week 6, respectively) and compared to patients receiving duloxetine/escitalopram regardless of their genotype (4.2‑point improvement at Week 6). The findings from the ANK3 biomarker discovery set were confirmed using the DNA samples from the replication set as shown in Figure 3b. Liafensine‑treated patients with the GG genotype at ANK3 biomarker in the replication set exhibited a larger improvement in MADRS total score change from baseline compared to those with the AA or AG genotype (11.0‑point or 7.4‑point improvement at Week 6, respectively) and compared to patients from the control arm (7.0‑point improvement at Week 6). Thus, the GG genotype is defined as ANK3 positive, and the AA and AG genotypes are defined as ANK3 biomarker negative. To examine whether ANK3 biomarker can also predict the efficacy for other antidepressants, DNA samples from patients treated with duloxetine or escitalopram were also genotyped for their ANK3 biomarker status. In Phase B of both CN162006 and CN162007 studies, about half of the patients were responders from duloxetine or escitalopram treatment. Figure 4 shows that patients carrying GG genotype (ANK3 biomarker‑positive) did not exhibit a better response compared to patients carrying AA or AG genotypes (ANK3 biomarker‑negative) when treated with duloxetine (CN162006) or duloxetine/escitalopram (CN162007). We also examined the real-world data from 713 patients being treated at Beijing Anding hospital. Patients were categorized into two groups based on the reduction rate of HAMD-17 scores from baseline to week 8 after antidepressant monotherapy treatment. The DGM4 genotype ratios between the responders and non-responders are similar with a p-value of 0.735(Table 1). Therefore, ANK3 biomarker does not appear to be a generic pharmacogenomic biomarker for antidepressants in general (e.g., escitalopram as a SSRI or duloxetine as a SNRI), but rather a specific pharmacogenomic biomarker for predicting the treatment effect of liafensine or possibly for TRIs. Table 1 Major Demographic Characteristics and DGM4 Genotype Analysis Results Variable Response Group 1 (n = 434) Non-response Group 2 (n = 279) Sample size (n) 434 279 Mean age (years) 28.95 ± 8.16 27.50 ± 7.40 Mean age at onset (years) 24.67 ± 7.87 23.80 ± 7.38 Sex distribution Male: 144 (33.2%) Female: 290 (66.8%) Male: 73 (26.2%) Female: 206 (73.8%) DGM4 genotype AA: 100 (23.0%) AG: 217 (50.0%) GG: 117 (27.0%) AA: 65 (23.3%) AG: 132 (47.3%) GG: 82 (29.4%) 1, The response group: patients achieving a ≥50% reduction in HAMD-17 total score. 2, The non-response group: patients with a reduction of <50% in HAMD-17 total score at week 8 compared to baseline. In the CN162006 study, patients received flexibly dosed liafensine 0.5–2 mg at an average dose of 1.5 mg; all 29 DGM4-positive patients from CN162006 were included in the analysis. There were 4 fixed doses of liafensine (0.25, 0.5, 1, and 2 mg) in the CN162007 study and there was no significant treatment effect in the non-biomarker-selected population in any dose group. The primary objective of CN162007 was to compare the combined 1 mg and 2 mg doses vs control based on the levels of SERT and DAT occupancy established by positron emission tomography. Thus, only data from the 18 (out of 25) DGM4-positive patients treated with the 1 mg and 2 mg doses were included in the analysis. The 29 DGM4‑positive patients from CN162006 and 18 DGM4‑positive patients from CN162007 made up the 47 total liafensine treated DGM4-positive patients shown in Figure 5. To match the analysis in the DGM4-positive patients, only data from the 74 (out of 124) DGM4-negative patients on the 1 mg and 2 mg arms in CN162007 were included in the analysis. The 55 DGM4-negative patients from CN162006 and 74 DGM4‑negative patients from CN162007 made up the 129 total liafensine treated DGM4‑negative patients shown in Figure 5. Figure 5 shows that DGM4-positive patients, which account for about 20% of the total patients, demonstrated a 4.7‑point greater reduction in MADRS total score change at Week 6 from baseline compared to control (p = 0.025). A similar comparison was performed in DGM4‑negative patients, which represent about 80% of the total patients, and no meaningful difference in treatment effect was observed between liafensine and control. This analysis revealed why the BMS studies failed to show meaningful treatment effect in the non-biomarker-selected patient population as the treatment effect of the small subset of responders (DGM4-positive patients) was diluted by the larger subset of DGM4-negative patients. Discussion New drug development is a challenging process, which typically costs over a billion dollars and takes more than 10 years. Moreover, only 10% or less of the drug candidates entering Phase 1 eventually reach the market, and even in Phase 3, the last stage of this long process, 50% or more of the drugs fail, mostly due to lack of efficacy. The development failure rate is even higher in psychiatric disorders as the brain is the most complicated human organ, and the pathogenesis of many psychiatric disorders remains largely unknown. In addition, the gap between animal models and human psychiatric disorders, subjective rating scales instead of quantitative objective measures, and large placebo effects all contribute to the failures in psychiatric drug development. Many psychiatric drug development programs with rich clinical data and valuable clinical samples have been discarded after years or decades of research efforts from scientists, doctors, and patients, as well as hundreds of millions of dollars of spending, even when these programs had reached to Phase 2 or 3. Unlike oncology biomarkers which can often be derived from preclinical studies, it is difficult to recapitulate psychiatric diseases and genetic variabilities among patients in animal models. Therefore, the completed clinical trials containing outcome results obtained from the patients treated with the study drugs provide unparalleled values for biomarker discovery. Thus, this study had an ambitious objective of finding a potential biomarker which could predict a subset of responders for an abandoned psychiatric drug. TRIs, including liafensine, were expected to provide new hope for the treatment of TRD, as they can simultaneously target the transporters for all three key monoamines which are believed to be critical in depression. 13 However, none of the TRIs has been approved thus far. Liafensine demonstrated an excellent safety profile in 11 Phase 1 studies and 3 Phase 2 studies conducted by BMS, but it failed to demonstrate efficacy in a non-biomarker-selected patient population. Utilizing the previous BMS Phase 2b clinical data and bio-samples, we identified a specific pharmacogenomic biomarker (ANK3 biomarker) that was highly correlated (p = 6.61x10 -8 ) to liafensine treatment effect on symptoms of depression, and the liafensine treatment effect in ANK3 biomarker-positive patients was confirmed in the replication set. The ANK3 biomarker biomarker is a single SNP (rs12217173) and located in the ANK3 gene. ANK3 expression is mostly restricted to the nervous system and plays an important role in neuronal development, cell motility, proliferation, and signaling. ANK3 gene encoding ankyrin G, which links spectrin-actin cytoskeleton to membrane proteins including ion channels and transporters. 14-17 Since liafensine targets transporters of 5-HT, NE, and DA, there is a potential mechanistic link for the associated treatment response between liafensine and ANK3 gene . Variants in ANK3 have been linked to a broad range of neurological diseases, including depression, autism spectrum disorder, schizophrenia, and bipolar disorder. 12,18-21 Additionally, in a genetic mouse model with conditional disruption of forebrain ANK3 pyramidal neurons , it was found that repeated social defeat stress resulted in repeated episodes of dramatic behavioral changes ranging from hyperactivity to “depression-like” behavior. 22 ANK3 biomarker is located in an intron of the ANK3 gene. and it is not surprising as 90% of genetic variants associated with complex traits lie in non-coding regions of the genome. 23 There is increasing evidence that non‑coding DNA sequences, eg, introns, can play major role in splicing, gene expression, mRNA transport, etc. 24-27 Interestingly, we found that one of the neighboring SNPs, rs4612751, (only 1005 bp away from and in tight linkage equilibrium with ANK3 biomarker) overlapped with the open chromatin regions of fetal brain and disrupted the DNA-binding motif of HOAX10, one of 39 homeobox transcription factors that establish body structures during development and shape synaptic specificity of multiple neuronal classes. Thus, ANK3 biomarker positive biomarker may lead to increase expression of ANK3 gene, which in turn can anchor more dopamine transporters (DAT) to the membrane of presynaptic neurons modulate and lead to more efficient reuptake of dopamine from the synapse (lower dopamine level is believed to be one of the key factors of depression). The increased level of DAT on neurons presents more targets for liafensine, a potent DAT inhibitor, which can effectively block the reuptake of dopamine by DAT and results in more dopamine remaining in synapse to alleviate depressive syndrome. The correlation of liafensine activity with ANK3 biomarker is mostly mediated via DAT because ANK3 biomarker status is not correlated with efficacy of duloxetine (SNRI) or escitalopram (SSRI). Despite this possible hypothesis, the precise mechanism of ANK3 biomarker affecting ANK3 gene function and subsequent modification of liafensine efficacy remains to be elucidated in future research. A number of studies have been conducted to discover predictive biomarkers for psychiatric drugs, but most of them have not been validated in a subsequent prospective study. 28 Due to the potential bias and high false positive rate of genome scale retrospective analysis, it is vital to confirm the potential biomarkers in a new clinical trial and eventually develop it as a companion diagnostic test to select drug responders, i.e., true precision medicine. Certainly, one of the limitations of the current study is that this is also a retrospective finding. In addition, the sample size is relatively small compared to most genome‑wide studies due to the limited number of samples available from the prior clinical trials. Thus, we have conducted a prospective, randomized, double‑blind Phase 2b study to evaluate liafensine’s efficacy and safety in ANK3 biomarker‑positive TRD patients (ClinicalTrials.gov number: NCT05113771). The prospective study enrolled 189 ANK3 biomarker-positive TRD patients. The topline results from this prospective clinical trial (manuscript submitted to Nature Medicine [Wang G. NMED-A137802], see appendix) confirmed the key findings of the current study: MADRS total score change from baseline at Week 6 in ANK3 biomarker-positive TRD patients treated with liafensine has shown a 4.4-point improvement vs the placebo, which is highly statistically and clinically significant, and close to the 4.7 found in this retrospective study. All of the secondary clinical depression measure outcomes also demonstrated significant improvements in ANK3 biomarker-positive patients. In addition, consistent with what we discovered in this study, the 1 mg and 2 mg liafensine arms exhibited similar efficacy, with improvement in MADRS total score changes from baseline of 4.4 and 4.5 respectively. This work shows that a single SNP can be effectively used as a pharmacogenomic biomarker for a psychiatric drug. ANK3 biomarker may eventually become one of the first true companion diagnostics for a psychiatric drug and bring long-awaited precision medicine to the treatment of depression. Compared to the oncology biomarkers which often need to be assayed using tumor biopsies, germline SNP can be conveniently genotyped using blood, buccal swab, or even saliva. Future implementation of biomarkers like ANK3 biomarker will have potential to transform the clinical practice of psychiatric disease management which traditionally relies on personal experience instead of patients’ genetic makeup. More importantly, this approach of using biomarkers to rescue failed drugs may represent a new paradigm to develop innovative medicine in more efficient way by leveraging the rich information generated from so-called “failed” clinical studies. Declarations The trial protocols for CN162006 and CN162007 were reviewed and approved by the ethics review committee of Schulman Associates IRB (United States). 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Methods Study patients Both CN162006 (NCT01309945) and CN162007 (NCT01369095) were global, multicenter, randomized, double-blind, active controlled studies. 17 CN162006 was a flexible-dose study where patients with a history of inadequate response to 1-3 antidepressants and one prospective treatment (duloxetine) were randomized to be switched to flexibly dosed liafensine (0.5‑2 mg/day) or remain on duloxetine. CN162007) was a fixed-dose, dose-response study where patients with a history of inadequate response to 1-3 antidepressants and one prospective treatment (duloxetine/escitalopram) were randomized to be switched to a fixed dose of liafensine (0.25, 0.5, 1 or 2 mg/day) or remain on duloxetine/escitalopram (Figure 1a). CN162006 was conducted in Canada, Finland, France, South Africa, Sweden, and the United States between April 2011 and January 2013; CN162007 was conducted in Argentina, Austria, Australia, Canada, France, India, Italy, South Africa, Spain, the United Kingdom, and the United States (including Puerto Rico) between July 2011 and May 2013. Both studies were conducted by BMS in accordance with the aims and principles of the International Council for Harmonisation (ICH), Good Clinical Practice (GCP), and the Declaration of Helsinki. All patients provided written informed consent before study participation. Both studies included male and female patients aged 18 to 65 years with a diagnosis of MDD who were currently experiencing a major depressive episode (> 8 weeks but < 3 years in duration) as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria (American Psychiatric Association, 2000). Patients entering the prospective phase of the study were required to have a Hamilton Rating Scale for Depression‑17 Item (HAMD-17) total score of 18 or higher at screening and baseline, as well as a history of inadequate response (< 50% reduction in depressive severity) to treatment with 1 to 3 adequate trials (adequate dose and duration) of antidepressant medication (as assessed by the Antidepressant Treatment Response Questionnaire and clinician interview). In both studies, the primary efficacy endpoints were assessed from the end of the prospective phase to the end of the randomized phase. The primary endpoint was the change in MADRS total score from randomization to the end of treatment timepoint. Real world data from Beijing Anding Hospital Depression Cohort: Collecting between January 2017 and December 2022, all patients were diagnosed with major depressive disorder (MDD) using the Mini International Neuropsychiatric Interview (MINI) according to DSM-IV criteria. Psychiatric assessments, including the 17-item Hamilton Depression Rating Scale (HAMD-17), the Young Mania Rating Scale (YMRS), the 16-item Quick Inventory of Depressive Symptomatology-Self Report (QIDS-16), and the Patient Health Questionnaire-9 (PHQ-9), were conducted at baseline, week 8, and week 12. Detailed medication records were also collected during the study period. A total of 713 patients were included in the present study based on the following criteria: aged between 15 and 65 years, a baseline HAMD-17 score ≥14, no use of antidepressants prior to enrollment, initiation of antidepressant monotherapy after inclusion, and availability of outcome assessments at week 8. Patients were excluded if they had missing key clinical or medication data or if the efficacy of antidepressants treatment could not be determined, such as due to incomplete rating scale assessments or significant data loss. Study design and oversight After the liafensine program at BMS was terminated due to lack of efficacy in the Phase 2b studies, we acquired the program, attempting to rescue the drug by finding a predictive biomarker. Of the 887 subjects who enrolled in CN162006 and received prospective treatment with duloxetine 60 mg/day in Phase B, 346 subjects with inadequate response were randomly assigned to double-blind treatment in Phase C with either liafensine (172 subjects, 1 subject was not treated) or continuing duloxetine (174 subjects) (Figure 1a). Of the 979 subjects who enrolled in CN162007 and received prospective treatment with duloxetine/escitalopram (Phase B), 502 subjects with inadequate response in Phase B were randomly assigned to double-blind treatment (Phase C) as follows: 51 subjects to liafensine 0.25 mg/day, 51 subjects to liafensine 0.5 mg/day, 102 subjects to liafensine 1 mg/day, 100 subjects to liafensine 2 mg/day, and 198 subjects to continuation of the Phase B antidepressant (duloxetine 60 mg/day or escitalopram 20 mg/day) (Figure 1a). From Phase C of CN162006 and CN162007, DNA or whole blood samples were available for 415 patients, out of whom 84 from CN162006 and 149 from CN162007 (totaling 233) were treated with liafensine. These 233 liafensine-treated patients were then randomly divided (4:1 ratio) into two independent sets: 186 for discovery and 47 for replication, stratified by race, treatment dose, study (CN162006 and CN162007) to preserve the balance (Figure 1c). The discovery and replication sets also shared similar distribution for MADRS total score change from baseline. A genome-wide association study was performed on the 186-patient discovery set and the results were tested with the 47-patient replication set. All patients provided written informed consent for using the samples for pharmacogenomic study. Sample processing and genotyping Genomic DNA was extracted from 300 µL of whole blood samples using QIAamp DNA blood Mini Kit. The genomic DNA samples obtained from the 186 patients in the discovery set were genotyped by Illumina using their Infinium® Omni5Exome-4 v1.3 BeadChip array, which contains about 4.5 million SNPs across the human genome. The genotyping results of the selected top SNPs from the genome-wide association analysis of the 186-patient discovery set was confirmed by real-time polymerase chain reaction (RT-PCR) using Life Technologies TaqMan SNP genotyping assay kits and reagents. The TaqMan assay was also used to genotype the remaining 47-patient replication set, the 182 patients from the control arms in Phase C, and all other patients who participated in Phase B if their clinical samples were available. Statistical analysis In the 186-patient discovery set, the patients with MADRS total score change higher than the overall median were labeled as responders and as non-responders otherwise. This binary labelling was used as the phenotype variable for the genome-wide association analysis. The genome-wide scan results were analyzed using PLINK v1.90b4.5 for quality control (QC) and genotype-phenotype association analysis. 29 18 The significance of association between each SNP passed QC and the phenotype was assessed using the standard case-control model. The clinical data analysis on the selected SNPs was based on a multivariable mixed model for repeated measures with an unstructured covariance matrix, including fixed factors of baseline MADRS score, visit, treatment, interaction of treatment and visit, age, sex, race, region, and study by SAS software (SAS Institute). References 29. Purcell, S. , et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81 , 559-575 (2007). Additional Declarations The authors declare potential competing interests as follows: WL, JW, ZD, XL, HS, HL, and TS had/have equity in Denovo Biopharma and are/were employed at Denovo Biopharma. Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-6736436","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":461204132,"identity":"22610eb5-df8e-4b31-a02c-57bac0743f15","order_by":0,"name":"Wen Luo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYDACdiD+wAZmsjEkMIAQIcDMwMA4g2QtzDwwLQzEaDE4zGP42KbMJo9fIvnYgwcVd/L4Z59O/MBQYxONR4uxcc65tGLJGWnpBglnnhVLnMvdLMFwLC23AYcWs8M8ZtK5bYcTN5w5YyaRCGQ0nOHdIMHYcBi/Fsu2/wgt88/wbv5BUAtj24HEDcd7IFo2nOHdhtcW+8NsxYY955ITZ7a3gf2SuBGoxSIBj18k25s3PvhRZpfYz8x87OGPijuJ84AOu/GhxganFnRwAEIlEKkcScsoGAWjYBSMAiQAABX8X94e60JNAAAAAElFTkSuQmCC","orcid":"","institution":"Denovo Biopharma LLC","correspondingAuthor":true,"prefix":"","firstName":"Wen","middleName":"","lastName":"Luo","suffix":""},{"id":461204133,"identity":"a1a2635a-9df3-4ab0-8166-2bd5f09fba51","order_by":1,"name":"Gang Wang","email":"","orcid":"","institution":"Beijing Anding Hospital","correspondingAuthor":false,"prefix":"","firstName":"Gang","middleName":"","lastName":"Wang","suffix":""},{"id":461205931,"identity":"0a0026f4-8ad4-46ab-9e53-7c8987dfb236","order_by":2,"name":"John W. Whitaker","email":"","orcid":"","institution":"Denovo Biopharma LLC","correspondingAuthor":false,"prefix":"","firstName":"John","middleName":"W.","lastName":"Whitaker","suffix":""},{"id":461205932,"identity":"345e0bad-ec17-4c6e-8611-28ddd2dc4941","order_by":3,"name":"Zafrin Dhali","email":"","orcid":"","institution":"Denovo Biopharma LLC","correspondingAuthor":false,"prefix":"","firstName":"Zafrin","middleName":"","lastName":"Dhali","suffix":""},{"id":461205933,"identity":"fa499791-9791-4a12-9cb3-c58373375d76","order_by":4,"name":"Hong Sun","email":"","orcid":"","institution":"Denovo Biopharma LLC","correspondingAuthor":false,"prefix":"","firstName":"Hong","middleName":"","lastName":"Sun","suffix":""},{"id":461205934,"identity":"dbfd735a-44d7-4476-bdfb-36b246cb2440","order_by":5,"name":"Haiping Lu","email":"","orcid":"","institution":"Denovo Biopharma LLC","correspondingAuthor":false,"prefix":"","firstName":"Haiping","middleName":"","lastName":"Lu","suffix":""},{"id":461205935,"identity":"f903512b-695d-49ef-a796-ec4c99180103","order_by":6,"name":"Xiaojun Li","email":"","orcid":"","institution":"Denovo Biopharma LLC","correspondingAuthor":false,"prefix":"","firstName":"Xiaojun","middleName":"","lastName":"Li","suffix":""},{"id":461205936,"identity":"b24244e5-8a7e-4099-9de2-d16746412a26","order_by":7,"name":"Tao Shi","email":"","orcid":"","institution":"Denovo Biopharma LLC","correspondingAuthor":false,"prefix":"","firstName":"Tao","middleName":"","lastName":"Shi","suffix":""}],"badges":[],"createdAt":"2025-05-24 03:34:37","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":true,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-6736436/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6736436/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":83751608,"identity":"2d5e405b-22ba-4d8c-86da-1ee2407e9a21","added_by":"auto","created_at":"2025-06-02 07:07:50","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":503571,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCN162006 and CN162007 study design, results, and sample availability\u003c/strong\u003e. \u003cstrong\u003ea,\u003c/strong\u003e Both studies have three phases: In Phase A, Patients with a history of inadequate response to 1 to 3 adequate trials of antidepressant were enrolled; In Phase B, patients were prospectively treated with duloxetine (CN162006) or duloxetine or escitalopram (CN162007), and the inadequate responders were randomized; In Phase C, the randomized patients either continued with the drug being used in Phase B (as the control arm) or treated with liafensine. \u003cstrong\u003eb,\u003c/strong\u003e Mean change from baseline for MADRS total score during Phase B and Phase C (separated by the vertical yellow line). \u003cstrong\u003ec,\u003c/strong\u003e Number of subjects from BMS studies with samples available for the biomarker study. BMS‑820836 = liafensine; SE = standard error.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6736436/v1/614e6fa152ee342e66936f9e.png"},{"id":83751612,"identity":"285fa2e5-96ca-4531-9c7c-d960ed9deee5","added_by":"auto","created_at":"2025-06-02 07:07:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":311646,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eManhattan plot of genome-wide association study result for liafensine response in the discovery set. \u003c/strong\u003eThe figure illustrates the association between individual SNPs and a response to liafensine response in 186 TRD patients. The negative log of the P value for the association is plotted against the chromosomal location across the genome. The pink horizontal line indicates the genome-wide significance level of 5×10\u003csup\u003e−8\u003c/sup\u003e.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6736436/v1/d8988e8fb895d05705f1c1a5.png"},{"id":83751609,"identity":"319d2a53-bca2-4bd5-bb81-540d97d757e8","added_by":"auto","created_at":"2025-06-02 07:07:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":165734,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparisons of efficacy among rs12217173 genotypes in biomarker discovery and replication sets\u003c/strong\u003e. \u003cstrong\u003ea,\u003c/strong\u003eMean MADRS total score change from baseline in patients with different ANK3 biomarker genotypes (AA/AG/GG) treated with liafensine vs duloxetine (Dul) or escitalopram (Escit) control in the discovery set. N in the box indicates the number of patients. \u003cstrong\u003eb,\u003c/strong\u003e Similar analysis was conducted in the replication set. SE = standard error.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6736436/v1/db147074b64e281a46854064.png"},{"id":83752280,"identity":"8bdc37db-53d1-4c88-8052-05fc26d840b5","added_by":"auto","created_at":"2025-06-02 07:15:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":101894,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparisons of efficacy among ANK3 biomarker genotypes in the control arm\u003c/strong\u003e. Mean MADRS total score change from baseline in patients with different ANK3 biomarker genotypes (AA/AG/GG) treated with duloxetine (Dul)/escitalopram (Escit) in Phase B of CN162006 and CN162007. SE = standard error.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6736436/v1/e268c21566ac6956766db7a3.png"},{"id":83751618,"identity":"859da8f0-5912-4f5d-8a9b-4be26a65181f","added_by":"auto","created_at":"2025-06-02 07:07:51","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":93800,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTreatment effects in ANK3-positive and ANK3-negative patients\u003c/strong\u003e. Mean MADRS total score change from baseline for liafensine vs control (duloxetine [Dul] or escitalopram [Escit]) based on pooled data from CN162006 (flexible dose of 0.5‑2 mg averaging 1.5 mg) and CN162007 (fixed doses of 1 mg and 2 mg). SE = standard error.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6736436/v1/7e2a606bb7354eb2d86f2734.png"},{"id":83752743,"identity":"c7c0bd05-f16a-4811-973a-afce3bc2b94a","added_by":"auto","created_at":"2025-06-02 07:23:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1860947,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6736436/v1/54a86328-d47a-4db9-a340-96f99c7c07f4.pdf"}],"financialInterests":"The authors declare potential competing interests as follows: WL, JW, ZD, XL, HS, HL, and TS had/have equity in Denovo Biopharma and are/were employed at Denovo Biopharma.","formattedTitle":"\u003cp\u003eDiscovery of a novel pharmacogenomic biomarker on \u003cem\u003eANK3\u003c/em\u003egene for liafensine, a triple reuptake inhibitor for treatment-resistant depression\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePrecision medicine using biomarkers to tailor drug treatment to those patients who can benefit the most is revolutionizing modern drug development. Particularly, in the field of oncology, many novel drugs have been approved with companion pharmacogenomic biomarkers. For example, lung cancer is divided into several subtypes which are classified by different pharmacogenomic biomarkers and are treated with different target therapies accordingly.\u003csup\u003e1\u003c/sup\u003e We believe a similar approach can be applied to other therapeutic areas, such as psychiatry, which has not had many biomarkers available to guide drug development. As a result, this may be one of the factors contributing to the high failure rate in psychiatric clinical studies.\u003c/p\u003e\n\u003cp\u003eTreatment-resistant depression (TRD) is a severe form of major depressive disorder (MDD), in which patients have had an inadequate response to previous antidepressant treatments. Up to 55% of people with MDD meet the criteria for TRD.\u003csup\u003e2,3\u003c/sup\u003e It is a serious and life-threatening condition with high rates of individual and society-level morbidity, mortality, medical and economic costs. Although there are more than 20 drugs approved to treat MDD, the development of new drugs to treat TRD has been challenging. Only two drugs have been approved by the United States Food and Drug Administration: Symbyax\u0026reg; and Spravato\u0026reg;. Symbyax is a fixed‑dose combination of olanzapine and fluoxetine with clinical efficacy. However, its use is limited by adverse reactions such as metabolic dysfunction, weight gain, and extrapyramidal symptoms which are poorly tolerated by many patients. Spravato (esketamine) nasal spray, in conjunction with an oral antidepressant, is the only new drug approved for TRD over the last 15 years. It demonstrates rapid onset of treatment effect, but is associated with significant adverse reactions including sedation, dissociation, respiratory depression, and abuse and misuse. The risks of sedation, dissociation, and respiratory depression require monitoring by a healthcare provider for at least 2 hours at each treatment session.\u003csup\u003e4,5\u003c/sup\u003e Consequently, Spravato is available only through a Risk Evaluation and Mitigation Strategy program. Psychotherapeutic interventions in combination with an antidepressant may offer partial symptomatic relief in persons with TRD, but their efficacy as monotherapy is not established.\u003csup\u003e6-9\u003c/sup\u003e The significant unmet needs in TRD patients highlight the importance of developing new classes of treatment that balance the risk-benefit profile to deliver an optimal approach to manage TRD effectively.\u003c/p\u003e\n\u003cp\u003eThe monoamine hypothesis of depression postulates primary dysfunction of serotonin (5-HT), norepinephrine (NE), and dopamine (DA) systems in the brain. This hypothetical framework has guided development of antidepressants for many years. Selective serotonin reuptake inhibitors (SSRIs), and dual serotonin and norepinephrine reuptake inhibitors (SNRIs) are two commonly prescribed classes of antidepressants to treat MDD. Thus, a drug that can simultaneously modulate 5-HT, NE, and DA, a triple reuptake inhibitor (TRI), was postulated to be an attractive approach to treat TRD. Liafensine (formerly BMS-820836 and AMR-000013, also known as DB104) is a potent and selective inhibitor of the reuptake of three monoamines: 5‑HT, NE, and DA by targeting the 5‑HT transporter (SERT), NE transporter (NET), and DA transporter (DAT), respectively. It was brought through significant preclinical research and early development by Bristol Myers Squibb (BMS), then evaluated as monotherapy in Phase 2b clinical studies for the treatment of TRD patients who have experienced inadequate response in two separate trials, CN162006 and CN162007.\u003csup\u003e10\u003c/sup\u003e Both CN162006 and CN162007 were global, multicenter, randomized, double-blind studies. Each study has three phases: screening (Phase A), prospective treatment with duloxetine or escitalopram (Phase B), and randomized treatment (Phase C) (Figure 1a). CN162006 was a flexible-dose (0.5\u0026ndash;2 mg/day) study and CN162007 was a fixed-dose (0.25, 0.5, 1 or 2 mg/day) study. Liafensine was well tolerated, with no evidence of dose-dependent discontinuations due to adverse events. However, it did not demonstrate efficacy compared to the control arms in the two Phase 2b TRD studies (Figure 1b).\u003c/p\u003e\n\u003cp\u003eThe addition of the dopamine activity of liafensine should in theory offer differential efficacy over SNRIs in some TRD patients. But this requires us to find a pharmacogenomic biomarker to identify the subset of patients who can benefit from liafensine. In contrast to oncology wherein most of the tumor biomarkers are considered to be driver gene mutations which are related to tumorigenesis as well as the drug response, the pathogenesis of psychiatric diseases is much more complicated as the brain is the most complex organ in humans. Therefore, in the current study, instead of focusing only on the drug target genes, we conducted genome-wide association research with archived samples from the two failed Phase 2b studies to identify novel genetic biomarkers that correlated with liafensine efficacy.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFrom the randomized treatment phase (Phase C) of CN162006 and CN162007 studies, DNA or whole blood samples were available for 233 liafensine-treated patients. These samples were randomly divided into two independent sets: 186 for discovery set and 47 for replication set (Figure 1c). The DNA samples from the 186 patients from the discovery set were successfully genotyped and passed quality control. From the genotyping data, single-nucleotide polymorphisms (SNPs) from sex chromosomes, with missing call rates greater than 2%, or with minor allele frequency below 5% were removed, resulting in 1,789,293 SNPs for the subsequent analysis. The Montgomery-\u0026Aring;sberg Depression Rating Scale (MADRS) is a clinical assessment tool designed to measure the severity of depressive episodes in patients with mood disorders. The 10 items in the MADRS are each scored between 0 and 6. Zero represents normal or baseline, and 6 represents continuous or severe presence of symptoms. MADRS is widely used and one of the gold standards to measure the efficacy of antidepressant therapy. Thus, the 186‑patient discovery set was dichotomized into 92 responders and 94 non-responders using the overall median MADRS total score change as the cutoff. After performing genotype-phonotype association analysis, the strongest association for liafensine treatment effect is the SNP rs12217173 with a p-value of\u0026nbsp;6.61\u0026times;10\u003csup\u003e-8\u003c/sup\u003e (Figure 2). This p-value almost reaches the genome‑wide significance cut-off of 5\u0026times;10\u003csup\u003e-8\u003c/sup\u003e. We still considered this top SNP as significant given the small sample size of 186, which is far less than most genome‑wide association studies.\u0026nbsp;This SNP is located on chromosome 10 in an intron of the \u003cem\u003eANK3\u003c/em\u003e (Ankyrin 3) gene. Ankyrins are a family of proteins that are believed to link the integral membrane proteins to the underlying spectrin-actin cytoskeleton. The \u003cem\u003eANK3\u003c/em\u003e gene is mainly expressed in the central and peripheral nervous system,\u003csup\u003e11\u003c/sup\u003e and is associated with several neuropsychiatric disorders.\u003csup\u003e12\u003c/sup\u003e Thus we named this biomarker as ANK3 biomarker and also termed as DGM4 (Denovo Genetic Marker 4).\u003c/p\u003e\n\u003cp\u003eSubsequently we analyzed the efficacy of liafensine treatment in each of the three genotypes of rs12217173 (designated AA, AG, and GG) within the discovery set as shown in Figure 3a. Liafensine‑treated patients with the GG genotype at ANK3 biomarker exhibited clinically much better improvement in MADRS total score change from baseline compared to those with the AA or AG genotype (5.6‑point or 4.4‑point improvement in MADRS total score changes at Week 6, respectively) and compared to patients receiving duloxetine/escitalopram regardless of their genotype (4.2‑point improvement at Week 6).\u003c/p\u003e\n\u003cp\u003eThe findings from the ANK3 biomarker discovery set were confirmed using the DNA samples from the replication set as shown in Figure 3b. Liafensine‑treated patients with the GG genotype at ANK3 biomarker in the replication set exhibited a larger improvement in MADRS total score change from baseline compared to those with the AA or AG genotype (11.0‑point or 7.4‑point improvement at Week 6, respectively) and compared to patients from the control arm (7.0‑point improvement at Week 6). Thus, the GG genotype is defined as ANK3 positive, and the AA and AG genotypes are defined as ANK3 biomarker negative.\u003c/p\u003e\n\u003cp\u003eTo examine whether ANK3 biomarker can also predict the efficacy for other antidepressants, DNA samples from patients treated with duloxetine or escitalopram were also genotyped for their ANK3 biomarker status. In Phase B of both CN162006 and CN162007 studies, about half of the patients were responders from duloxetine or escitalopram treatment. Figure 4 shows that patients carrying GG genotype (ANK3 biomarker‑positive) did not exhibit a better response compared to patients carrying AA or AG genotypes (ANK3 biomarker‑negative) when treated with duloxetine (CN162006) or duloxetine/escitalopram (CN162007). \u0026nbsp;We also examined the real-world data from 713 patients being treated at Beijing Anding hospital. Patients were categorized into two groups based on the reduction rate of HAMD-17 scores from baseline to week 8 after antidepressant monotherapy treatment. The DGM4 genotype ratios between the responders and non-responders are similar with a p-value of 0.735(Table 1). \u0026nbsp;Therefore, ANK3 biomarker does not appear to be a generic pharmacogenomic biomarker for antidepressants in general (e.g., escitalopram as a SSRI or duloxetine as a SNRI), but rather a specific pharmacogenomic biomarker for predicting the treatment effect of liafensine or possibly for TRIs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eMajor Demographic Characteristics and DGM4 Genotype Analysis Results\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" width=\"695\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eResponse Group\u003csup\u003e1\u003c/sup\u003e (n = 434)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNon-response Group\u003csup\u003e2\u003c/sup\u003e (n = 279)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSample size (n)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e279\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMean age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e28.95 \u0026plusmn; 8.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e27.50 \u0026plusmn; 7.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMean age at onset (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24.67 \u0026plusmn; 7.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e23.80 \u0026plusmn; 7.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSex distribution\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMale: 144 (33.2%)\u003cbr\u003e\u0026nbsp;Female: 290 (66.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMale: 73 (26.2%)\u003cbr\u003e\u0026nbsp;Female: 206 (73.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDGM4 genotype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAA: 100 (23.0%)\u003cbr\u003e\u0026nbsp;AG: 217 (50.0%)\u003cbr\u003e\u0026nbsp;GG: 117 (27.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAA: 65 (23.3%)\u003cbr\u003e\u0026nbsp;AG: 132 (47.3%)\u003cbr\u003e\u0026nbsp;GG: 82 (29.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e1, The response group: patients achieving a \u0026ge;50% reduction in HAMD-17 total score.\u003c/p\u003e\n\u003cp\u003e2, The non-response group: patients with a reduction of \u0026lt;50% in HAMD-17 total score at week 8 compared to baseline.\u003c/p\u003e\n\u003cp\u003eIn the CN162006 study, patients received flexibly dosed liafensine 0.5\u0026ndash;2 mg at an average dose of 1.5 mg; all 29 DGM4-positive patients from CN162006 were included in the analysis. There were 4 fixed doses of liafensine (0.25, 0.5, 1, and 2 mg) in the CN162007 study and there was no significant treatment effect in the non-biomarker-selected population in any dose group. The primary objective of CN162007 was to compare the combined 1 mg and 2 mg doses vs control based on the levels of SERT and DAT occupancy established by positron emission tomography. Thus, only data from the 18 (out of 25) DGM4-positive patients treated with the 1 mg and 2 mg doses were included in the analysis. The 29 DGM4‑positive patients from CN162006 and 18 DGM4‑positive patients from CN162007 made up the 47 total liafensine treated DGM4-positive patients shown in Figure 5. To match the analysis in the DGM4-positive patients, only data from the 74 (out of 124) DGM4-negative patients on the 1 mg and 2 mg arms in CN162007 were included in the analysis. The 55 DGM4-negative patients from CN162006 and 74 DGM4‑negative patients from CN162007 made up the 129 total liafensine treated DGM4‑negative patients shown in Figure 5.\u003c/p\u003e\n\u003cp\u003eFigure 5 shows that DGM4-positive patients, which account for about 20% of the total patients, demonstrated a 4.7‑point greater reduction in MADRS total score change at Week 6 from baseline compared to control (p = 0.025). A similar comparison was performed in DGM4‑negative patients, which represent about 80% of the total patients, and no meaningful difference in treatment effect was observed between liafensine and control. This analysis revealed why the BMS studies failed to show meaningful treatment effect in the non-biomarker-selected patient population as the treatment effect of the small subset of responders (DGM4-positive patients) was diluted by the larger subset of DGM4-negative patients.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eNew drug development is a challenging process, which typically costs over a billion dollars and takes more than 10 years. Moreover, only 10% or less of the drug candidates entering Phase 1 eventually reach the market, and even in Phase 3, the last stage of this long process, 50% or more of the drugs fail, mostly due to lack of efficacy. The development failure rate is even higher in psychiatric disorders as the brain is the most complicated human organ, and the pathogenesis of many psychiatric disorders remains largely unknown. In addition, the gap between animal models and human psychiatric disorders, subjective rating scales instead of quantitative objective measures, and large placebo effects all contribute to the failures in psychiatric drug development. Many psychiatric drug development programs with rich clinical data and valuable clinical samples have been discarded after years or decades of research efforts from scientists, doctors, and patients, as well as hundreds of millions of dollars of spending, even when these programs had reached to Phase 2 or 3. Unlike oncology biomarkers which can often be derived from preclinical studies, it is difficult to recapitulate psychiatric diseases and genetic variabilities among patients in animal models. Therefore, the completed clinical trials containing outcome results obtained from the patients treated with the study drugs provide unparalleled values for biomarker discovery. Thus, this study had an ambitious objective of finding a potential biomarker which could predict a subset of responders for an abandoned psychiatric drug.\u003c/p\u003e\n\u003cp\u003eTRIs, including liafensine, were expected to provide new hope for the treatment of TRD, as they can simultaneously target the transporters for all three key monoamines which are believed to be critical in depression.\u003csup\u003e13\u003c/sup\u003e However, none of the TRIs has been approved thus far. Liafensine demonstrated an excellent safety profile in 11 Phase 1 studies and 3 Phase 2 studies conducted by BMS, but it failed to demonstrate efficacy in a non-biomarker-selected patient population. Utilizing the previous BMS Phase 2b clinical data and bio-samples, we identified a specific pharmacogenomic biomarker (ANK3 biomarker) that was highly correlated (p = 6.61x10\u003csup\u003e-8\u003c/sup\u003e) to liafensine treatment effect on symptoms of depression, and the liafensine treatment effect in ANK3 biomarker-positive patients was confirmed in the replication set.\u003c/p\u003e\n\u003cp\u003eThe ANK3 biomarker biomarker is a single SNP (rs12217173) and located in the \u003cem\u003eANK3\u003c/em\u003e gene. \u003cem\u003eANK3\u003c/em\u003e expression is mostly restricted to the nervous system and plays an important role in neuronal development, cell motility, proliferation, and signaling. \u003cem\u003eANK3\u003c/em\u003e gene encoding ankyrin G, which links spectrin-actin cytoskeleton to membrane proteins including ion channels and transporters.\u003csup\u003e14-17\u003c/sup\u003e Since liafensine targets transporters of 5-HT, NE, and DA, there is a potential mechanistic link for the associated treatment response between liafensine and \u003cem\u003eANK3 gene\u003c/em\u003e. Variants in \u003cem\u003eANK3\u003c/em\u003e have been linked to a broad range of neurological diseases, including depression, autism spectrum disorder, schizophrenia, and bipolar disorder.\u003csup\u003e12,18-21\u003c/sup\u003e Additionally, in a genetic mouse model with conditional disruption of forebrain \u003cem\u003eANK3\u003c/em\u003e pyramidal neurons , it was found that repeated social defeat stress resulted in repeated episodes of dramatic behavioral changes ranging from hyperactivity to \u0026ldquo;depression-like\u0026rdquo; behavior.\u003csup\u003e22\u003c/sup\u003e ANK3 biomarker is located in an intron of the \u003cem\u003eANK3\u003c/em\u003e gene. and it is not surprising as 90% of genetic variants associated with complex traits lie in non-coding regions of the genome.\u003csup\u003e23\u003c/sup\u003e There is increasing evidence that non‑coding DNA sequences, eg, introns, can play major role in splicing, gene expression, mRNA transport, etc.\u003csup\u003e24-27\u003c/sup\u003e Interestingly, we found that one of the neighboring SNPs, rs4612751, (only 1005 bp away from and in tight linkage equilibrium with ANK3 biomarker) overlapped with the open chromatin regions of fetal brain and disrupted the DNA-binding motif of HOAX10, one of 39 homeobox transcription factors that establish body structures during development and shape synaptic specificity of multiple neuronal classes. Thus, ANK3 biomarker positive biomarker may lead to increase expression of \u003cem\u003eANK3\u003c/em\u003e gene, which in turn can anchor more dopamine transporters (DAT) to the membrane of presynaptic neurons modulate and lead to more efficient reuptake of dopamine from the synapse (lower dopamine level is believed to be one of the key factors of depression). The increased level of DAT on neurons presents more targets for liafensine, a potent DAT inhibitor, which can effectively block the reuptake of dopamine by DAT and results in more dopamine remaining in synapse to alleviate depressive syndrome. The correlation of liafensine activity with ANK3 biomarker is mostly mediated via DAT because ANK3 biomarker status is not correlated with efficacy of duloxetine (SNRI) or escitalopram (SSRI). \u0026nbsp; Despite this possible hypothesis, the precise mechanism of ANK3 biomarker affecting \u003cem\u003eANK3\u003c/em\u003e gene function and subsequent modification of liafensine efficacy remains to be elucidated in future research.\u003c/p\u003e\n\u003cp\u003eA number of studies have been conducted to discover predictive biomarkers for psychiatric drugs, but most of them have not been validated in a subsequent prospective study.\u003csup\u003e28\u003c/sup\u003e Due to the potential bias and high false positive rate of genome scale retrospective analysis, it is vital to confirm the potential biomarkers in a new clinical trial and eventually develop it as a companion diagnostic test to select drug responders, i.e., true precision medicine. Certainly, one of the limitations of the current study is that this is also a retrospective finding. In addition, the sample size is relatively small compared to most genome‑wide studies due to the limited number of samples available from the prior clinical trials. Thus, we have conducted a prospective, randomized, double‑blind Phase 2b study to evaluate liafensine\u0026rsquo;s efficacy and safety in ANK3 biomarker‑positive TRD patients (ClinicalTrials.gov number: NCT05113771). The prospective study enrolled 189 ANK3 biomarker-positive TRD patients. The topline results from this prospective clinical trial (manuscript submitted to Nature Medicine [Wang G. NMED-A137802], see appendix) confirmed the key findings of the current study: MADRS total score change from baseline at Week 6 in ANK3 biomarker-positive TRD patients treated with liafensine has shown a 4.4-point improvement vs the placebo, which is highly statistically and clinically significant, and close to the 4.7 found in this retrospective study. All of the secondary clinical depression measure outcomes also demonstrated significant improvements in ANK3 biomarker-positive patients. In addition, consistent with what we discovered in this study, the 1\u0026nbsp;mg and 2\u0026nbsp;mg liafensine arms exhibited similar efficacy, with improvement in MADRS total score changes from baseline of 4.4 and 4.5 respectively.\u003c/p\u003e\n\u003cp\u003eThis work shows that a single SNP can be effectively used as a pharmacogenomic biomarker for a psychiatric drug. ANK3 biomarker may eventually become one of the first true companion diagnostics for a psychiatric drug and bring long-awaited precision medicine to the treatment of depression. Compared to the oncology biomarkers which often need to be assayed using tumor biopsies, germline SNP can be conveniently genotyped using blood, buccal swab, or even saliva. Future implementation of biomarkers like ANK3 biomarker will have potential to transform the clinical practice of psychiatric disease management which traditionally relies on personal experience instead of patients\u0026rsquo; genetic makeup. More importantly, this approach of using biomarkers to rescue failed drugs may represent a new paradigm to develop innovative medicine in more efficient way by leveraging the rich information generated from so-called \u0026ldquo;failed\u0026rdquo; clinical studies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cspan\u003eThe trial protocols for CN162006 and CN162007 were reviewed and approved by the ethics review committee of Schulman Associates IRB (United States).\u003c/span\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eGuo, H.\u003cem\u003e, et al.\u003c/em\u003e Biomarker-Targeted Therapies in Non\u0026ndash;Small Cell Lung Cancer: Current Status and Perspectives. \u003cem\u003eCells\u003c/em\u003e \u003cstrong\u003e11\u003c/strong\u003e, 3200 (2022).\u003c/li\u003e\n\u003cli\u003eMcIntyre, R.S.\u003cem\u003e, et al.\u003c/em\u003e Treatment-resistant depression: definition, prevalence, detection, management, and investigational interventions. \u003cem\u003eWorld Psychiatry\u003c/em\u003e \u003cstrong\u003e22\u003c/strong\u003e, 394-412 (2023).\u003c/li\u003e\n\u003cli\u003eRush, A.J.\u003cem\u003e, et al.\u003c/em\u003e Acute and longer-term outcomes in depressed outpatients requiring one or several treatment steps: a STAR*D report. \u003cem\u003eAm J Psychiatry\u003c/em\u003e \u003cstrong\u003e163\u003c/strong\u003e, 1905-1917 (2006).\u003c/li\u003e\n\u003cli\u003eMcIntyre, R.S.\u003cem\u003e, et al.\u003c/em\u003e Synthesizing the Evidence for Ketamine and Esketamine in Treatment-Resistant Depression: An International Expert Opinion on the Available Evidence and Implementation. \u003cem\u003eAm J Psychiatry\u003c/em\u003e \u003cstrong\u003e178\u003c/strong\u003e, 383-399 (2021).\u003c/li\u003e\n\u003cli\u003eSchatzberg, A.F. 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Pharmacogenomic scores in psychiatry: systematic review of current evidence. \u003cem\u003eTransl Psychiatry\u003c/em\u003e \u003cstrong\u003e14\u003c/strong\u003e, 322 (2024).\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy patients\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoth CN162006 (NCT01309945) and CN162007 (NCT01369095) were global, multicenter, randomized, double-blind, active controlled studies.\u003csup\u003e17\u003c/sup\u003e CN162006 was a flexible-dose study where patients with a history of inadequate response to 1-3 antidepressants and one prospective treatment (duloxetine) were randomized to be switched to flexibly dosed liafensine (0.5‑2 mg/day) or remain on duloxetine. CN162007) was a fixed-dose, dose-response study where patients with a history of inadequate response to 1-3 antidepressants and one prospective treatment (duloxetine/escitalopram) were randomized to be switched to a fixed dose of liafensine (0.25, 0.5, 1 or 2 mg/day) or remain on duloxetine/escitalopram (Figure 1a). CN162006 was conducted in Canada, Finland, France, South Africa, Sweden, and the United States between April 2011 and January 2013; CN162007 was conducted in Argentina, Austria, Australia, Canada, France, India, Italy, South Africa, Spain, the United Kingdom, and the United States (including Puerto Rico) between July 2011 and May 2013. Both studies were conducted by BMS in accordance with the aims and principles of the International Council for Harmonisation (ICH), Good Clinical Practice (GCP), and the Declaration of Helsinki. All patients provided written informed consent before study participation.\u003c/p\u003e\n\u003cp\u003eBoth studies included male and female patients aged 18 to 65 years with a diagnosis of MDD who were currently experiencing a major depressive episode (\u0026gt; 8 weeks but \u0026lt; 3 years in duration) as defined by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, criteria (American Psychiatric Association, 2000). Patients entering the prospective phase of the study were required to have a Hamilton Rating Scale for Depression‑17 Item (HAMD-17) total score of 18 or higher at screening and baseline, as well as a history of inadequate response (\u0026lt; 50% reduction in depressive severity) to treatment with 1 to 3 adequate trials (adequate dose and duration) of antidepressant medication (as assessed by the Antidepressant Treatment Response Questionnaire and clinician interview). In both studies, the primary efficacy endpoints were assessed from the end of the prospective phase to the end of the randomized phase. The primary endpoint was the change in MADRS total score from randomization to the end of treatment timepoint.\u003c/p\u003e\n\n\u003cp\u003eReal world data from Beijing Anding Hospital Depression Cohort: Collecting between January 2017 and December 2022, all patients were diagnosed with major depressive disorder (MDD) using the Mini International Neuropsychiatric Interview (MINI) according to DSM-IV criteria. Psychiatric assessments, including the 17-item Hamilton Depression Rating Scale (HAMD-17), the Young Mania Rating Scale (YMRS), the 16-item Quick Inventory of Depressive Symptomatology-Self Report (QIDS-16), and the Patient Health Questionnaire-9 (PHQ-9), were conducted at baseline, week 8, and week 12. Detailed medication records were also collected during the study period. A total of 713 patients were included in the present study based on the following criteria: aged between 15 and 65 years, a baseline HAMD-17 score \u0026ge;14, no use of antidepressants prior to enrollment, initiation of antidepressant monotherapy after inclusion, and availability of outcome assessments at week 8. Patients were excluded if they had missing key clinical or medication data or if the efficacy of antidepressants treatment could not be determined, such as due to incomplete rating scale assessments or significant data loss.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eStudy design and oversight\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter the liafensine program at BMS was terminated due to lack of efficacy in the Phase 2b studies, we acquired the program, attempting to rescue the drug by finding a predictive biomarker. Of the 887 subjects who enrolled in CN162006 and received prospective treatment with duloxetine 60 mg/day in Phase B, 346 subjects with inadequate response were randomly assigned to double-blind treatment in Phase C with either liafensine (172 subjects, 1 subject was not treated) or continuing duloxetine (174 subjects) (Figure 1a). Of the 979 subjects who enrolled in CN162007 and received prospective treatment with duloxetine/escitalopram (Phase B), 502 subjects with inadequate response in Phase B were randomly assigned to double-blind treatment (Phase C) as follows: 51 subjects to liafensine 0.25 mg/day, 51 subjects to liafensine 0.5 mg/day, 102 subjects to liafensine 1 mg/day, 100 subjects to liafensine 2 mg/day, and 198 subjects to continuation of the Phase B antidepressant (duloxetine 60 mg/day or escitalopram 20 mg/day) (Figure 1a).\u003c/p\u003e\n\u003cp\u003eFrom Phase C of CN162006 and CN162007, DNA or whole blood samples were available for 415 patients, out of whom 84 from CN162006 and 149 from CN162007 (totaling 233) were treated with liafensine. These 233 liafensine-treated patients were then randomly divided (4:1 ratio) into two independent sets: 186 for discovery and 47 for replication, stratified by race, treatment dose, study (CN162006 and CN162007) to preserve the balance (Figure 1c). The discovery and replication sets also shared similar distribution for MADRS total score change from baseline. A genome-wide association study was performed on the 186-patient discovery set and the results were tested with the 47-patient replication set. All patients provided written informed consent for using the samples for pharmacogenomic study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample processing and genotyping\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGenomic DNA was extracted from 300 \u0026micro;L of whole blood samples using QIAamp DNA blood Mini Kit. The genomic DNA samples obtained from the 186 patients in the discovery set were genotyped by Illumina using their Infinium\u0026reg; Omni5Exome-4 v1.3 BeadChip array, which contains about 4.5 million SNPs across the human genome. The genotyping results of the selected top SNPs from the genome-wide association analysis of the 186-patient discovery set was confirmed by real-time polymerase chain reaction (RT-PCR) using Life Technologies TaqMan SNP genotyping assay kits and reagents. The TaqMan assay was also used to genotype the remaining 47-patient replication set, the 182 patients from the control arms in Phase C, and all other patients who participated in Phase B if their clinical samples were available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the 186-patient discovery set, the patients with MADRS total score change higher than the overall median were labeled as responders and as non-responders otherwise. This binary labelling was used as the phenotype variable for the genome-wide association analysis.\u003c/p\u003e\n\u003cp\u003eThe genome-wide scan results were analyzed using PLINK v1.90b4.5 for quality control (QC) and genotype-phenotype association analysis.\u003csup\u003e29\u003c/sup\u003e\u003csup\u003e18\u003c/sup\u003e The significance of association between each SNP passed QC and the phenotype was assessed using the standard case-control model.\u003c/p\u003e\n\u003cp\u003eThe clinical data analysis on the selected SNPs was based on a multivariable mixed model for repeated measures with an unstructured covariance matrix, including fixed factors of baseline MADRS score, visit, treatment, interaction of treatment and visit, age, sex, race, region, and study by SAS software (SAS Institute).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReferences\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e29. Purcell, S.\u003cem\u003e, et al.\u003c/em\u003e PLINK: a tool set for whole-genome association and population-based linkage analyses. \u003cem\u003eAm J Hum Genet\u003c/em\u003e \u003cstrong\u003e81\u003c/strong\u003e, 559-575 (2007).\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Denovo Biopharma LLC","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"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},"keywords":"Depression, TRD, Biomarker, Antidepressant, ANK3, Pharmacogenomic","lastPublishedDoi":"10.21203/rs.3.rs-6736436/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6736436/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLiafensine is a first-in-class triple reuptake inhibitor targeting transporters for serotonin, norepinephrine, and dopamine for treatment-resistant depression (TRD). It did not exhibit efficacy in non-biomarker-selected TRD patients in two Phase 2b studies. We utilized the blood samples from the patients enrolled in these two studies and extracted genomic DNA to conduct a genome‑wide association study aiming to find a biomarker which can predict liafensine response. A single single-nucleotide polymorphism (SNP), rs12217173, at \u003cem\u003eANK3\u003c/em\u003e gene was identified as strongly associated with treatment response to liafensine (p\u0026nbsp;=\u0026nbsp;6.61×10\u003csup\u003e-8\u003c/sup\u003e) in the discovery set and was further confirmed in the replication sample set. In addition, this SNP was not associated with the efficacy of the duloxetine or escitalopram, suggesting it is a liafensine-specific biomarker. This finding was subsequently confirmed in a prospective clinical study. Thus, this study represents a novel approach to translate precision medicine into psychiatric diseases.\u003c/p\u003e","manuscriptTitle":"Discovery of a novel pharmacogenomic biomarker on ANK3gene for liafensine, a triple reuptake inhibitor for treatment-resistant depression","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-02 07:07:46","doi":"10.21203/rs.3.rs-6736436/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":"e80a2214-6693-44ca-a9ce-103014b51b8c","owner":[],"postedDate":"June 2nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":49259737,"name":"Bioinformatics"},{"id":49259738,"name":"Computational Biology"},{"id":49259739,"name":"Medical Genetics"},{"id":49259740,"name":"Computational Neuroscience"}],"tags":[],"updatedAt":"2025-06-02T07:07:46+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-02 07:07:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6736436","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6736436","identity":"rs-6736436","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}