The long-term patency of vein grafts is challenged by intimal hyperplasia. We sought to explore the intricate relationships between the transcription factor Egr-1, toll-like receptors (TLRs), and stem cell genes and also assessed oligodeoxynucleotide decoys (ODNs) as a strategy to prevent vein graft failures. A total of 42 New Zealand white rabbits were fed hyperlipidemic chow and classified into three groups. A double-stranded Egr-1 ODN was synthesized and infused in vein grafts prior to anastomosis with the common carotid artery. All vein grafts were retrieved at the conclusion of the predefined experimental period. Real-time quantitative polymerase chain reaction was performed to estimate expression patterns for several genes of interest. MYD88, TLR2-4, TLR8, NF-kB, TNF-α, IFNβ, and IFNγ; chemokines CCL4, CCL20, CCR2; numerous interleukins; and stem cell genes KFL4, NANOG, HOXA5, and HIF1α were universally downregulated in the ODN arm compared with the controls. By understanding these multifaceted interactions, our study offers actionable insights that may pave the way for innovative interventions in vascular reconstructions. Vascular reconstruction has heavily relied on vein grafts following the seminal work of Carrel and Guthrie in 1906 . The priCentral to this issue is Egr-1 (early growth response factor-1), a zinc finger transcription factor expressed in the vascular wall’s diverse cellular makeup . Its actIn the context of toll-like receptor (TLR) signaling pathways, a two-fold categorization emerges: MYD88-dependent, culminating in NF-κB activation, and TRIF-dependent. These pathways synergize in inducing proinflammatory cytokines, suggesting a potential connection to intimal hyperplasia. TLR activation, particularly through the MYD88 pathway, may provide another piece of the puzzle in understanding the mechanistic underpinnings of vein graft failure.Emerging evidence has also revealed that the expression of various stem cell genes (including KLF4 (Krüppel-like factor 4), HOXA5, NANOG, and HIF1α ) can be dysregulated by shear stress ,10,11. TThe present study navigates the intricate terrain of Egr-1, ODN, TLRs, and stem cell genes, formulating a coherent analysis of their interrelations. By probing these multifaceted interactions, we hope to shed light on innovative strategies to manage vein graft failures.No morbidity or fatalities were noted in any of the study subjects. MYD88: myeloid differentiation primary response 88; TLR: toll-like receptor; *: statistically significant comparisons).TLR2 was significantly downregulated in the ODN arm compared with both the control  and the mutated decoy  subgroups. TLR3 was also significantly reduced in ODN rabbits versus their untreated  and mutated  counterparts. Similarly, TLR4 expression curtailed following ODN treatment compared with both controls  and mutated analogs . On the other hand, TLR8  was only downregulated in the decoy group compared with the untreated controls. MYD88 followed the same expression pattern   and IFNβ  levels compared with both the untreated and the mutated arms. On the other hand, TNF-α  and IFNγ  were only attenuated in the decoy group compared with the controls .CCL20 expression was substantially decreased with ODN inoculation compared with not only the controls  but also the mutated decoys . Conversely, ODN treatment decreased CCL4  and CCR2  levels only in comparison with untreated animals .IL10  and IL18 production  was more potently reduced with ODN compared with both controls and mutated inoculations. That said, decoy infusion attenuated IL1b , IL2 , IL4 , and IL8  only compared with untreated subjects .Decoy inoculation significantly downregulated KLF4 , HOXA5 , and HIF1α  compared with both the untreated and mutated cohorts. However, NANOG expression  was reduced in the decoy group only compared with untreated controls .To better elucidate important pattern interplays, we performed an analysis of correlation coefficients. p = 0.04), as well as IL4 . TLR4 expression was positively associated with CCL4  but negatively with CCL20  and IL10 . CCL4 expression was inversely correlated with IL18 . Lastly, IFNγ levels were negatively associated with HOXA5  but positively with NANOG   .Intimal hyperplasia in venous grafts is a complex process that is influenced by versatile proinflammatory stimuli. It involves intricate intracellular pathways with both inhibitory and pro-proliferative proteins. Therefore, targeting a transcription factor that impacts multiple pathways could provide a strategic leverage point for graft failure prevention and treatment . TranscrEgr-1 is prevalent in a range of cell types within the vascular wall, notably endothelial cells, vascular smooth muscle cells, monocytes, and macrophages. Its expression can be triggered by various factors associated with vascular disease progression, such as shear and mechanical stresses, hypoxic conditions, insulin, glucose, angiotensin II, and immediate arterial injuries ,6,7. ResOur previous work benchmarked the efficacy of Egr-1 ODN in the treatment of vein grafts . DAPI stIn the present analysis, we built upon that preliminary experience by exploring expression pattern modifications of key cardiovascular stem cell genes, TLRs/ MYD88, and numerous other proinflammatory cytokines. Of note, decoy inoculation dramatically reduced the expression of all examined mediators, including TNFa; NF-kB; and chemokines CCL4, CCL20, and CCR2. The production of numerous interleukins  and interferons  was also uniformly curtailed with ODN infusions. The pronounced effect of the present decoy strategy reinforces the potential of transcription factors as valuable targets for addressing cardiovascular inflammation.Furthermore, ODN treatment effectively reduced the expression of TLR2, TLR3, TLR4, TLR8, and MYD88. Interestingly, the overexpression of TLR3 and TLR4 has been implicated in the severity of coronary artery disease . A growiLast but not least, decoy infusion extensively downregulated KLF4, NANOG, HOXA5, and HIF1α. As previously conveyed by our group, a hyperlipidemic diet induces the expression of the KLF4 gene, which, in turn, dysregulates nitric oxide synthesis, VE-cadherin transcription, intercellular connections, and macrophage/monocyte differentiation ,29,30,31It is worth noting that both the original and mutated ODNs are designed to interact with Egr-1. While the mutated form does have sequence alterations, its foundational design is derived from the original ODN. As such, it is not surprising for them to exhibit overlapping activities and influence the expression of some of the same genes. However, inherent differences between them also lead to unique interactions with certain pathways. Indeed, the majority of the target genes were downregulated only after Egr-1 ODN treatment. These include TLR2, TLR3, TLR4, NF-kB, IFNβ, chemokine CCL20, Il10, and most stem cell genes . Although large-scale randomized clinical trials are needed to validate these data in human patients, our findings are promising. Indeed, the present approach is straightforward, cost-effective, and does not necessitate specialized equipment. The technique theoretically tackles the stimuli of early failure due to harvest trauma . That said, certain limitations should be discussed. First, our research centered on examining mRNA expression patterns. While the evaluation of Egr-1’s binding activity following Egr-1 decoy ODN treatment was not within our IRB-approved study’s remit, it is a direction we plan to explore in upcoming studies.Second, our investigation primarily centers on whole tissue, even though we recognize that Egr-1 is not limited to the endothelium but is also expressed in SMCs and macrophage-type cells. Moving forward, we will attempt to delve into the distinct roles Egr-1 might play in each individual cell type. Furthermore, graft transfection with short-acting decoys cannot address patient-related risk factors, including tobacco smoking, dyslipidemia, or poorly controlled diabetes mellitus. Indisputably, following the gold-standard medical treatment is key to improving graft longevity. In the future, improving transfection techniques, employing decoys with prolonged action (such as short interfering RNA), and devising chimeric ODNs that target more than one transcription factor could potentially revolutionize this field. Our experimental model was previously described and validated . In brieA phosphorothioate-stabilized, double-stranded Egr-1 oligodeoxynucleotide decoy (ODN) was synthesized, containing two copies of the sequence 5′-GCGGGGGCG-3′, representing the Egr-1 consensus binding sequences . A mutant Egr-1 decoy ODN was used as a negative control and contained the sequence 5′-GCTAGGGCG-3′. Both ODNs were dissolved at a concentration of 40 mmol/L in normal saline solution. Preoperative care included intramuscular administration of xylazine and ketamine, followed by tracheal intubation and mechanical ventilation. Isoflurane was utilized to sustain anesthesia, and the auricular vein was used for administering fluids. A 2.5 cm segment of the right external jugular vein was harvested through a midline neck incision using a “no-touch” approach. The vein graft underwent cannulation and was then flushed with saline, secured, and encased in a plastic sheath. Infusion and pressurization of ODN solution  were performed at 300 mmHg for 20 min with the use of a balloon inflation device .Heparin (200 IU/kg) was administered intravenously, and the ipsilateral common carotid artery was clamped proximally and distally and divided. The vein graft was anastomosed to the divided artery in a reversed end-to-end fashion with interrupted 7/0 polypropylene sutures. Mean diameter measurements for common carotid arteries and venous grafts were 2.03 ± 0.29 mm and 1.78 ± 0.21 mm, respectively. No mismatch was noted at the completion of the anastomosis. After wound closure, all subjects were transferred to the Intensive Care Unit with ongoing monitoring.−1). Group B, consisting of 18 animals, had no treatment. Group C, including six animals, was treated with a fluorescein isothiocyanate (FITC)-labeled decoy.For the purposes of the experiment, the rabbits were classified into three distinct groups . Group AThe timing of sacrifice was set differently between the groups, with animals in Groups A and B being divided into thirds for sacrifice at 48 h, 6 weeks, and 12 weeks. Post-surgical examination included the dissection, fixing, and processing of grafts excised after 6 and 12 weeks, followed by paraffin embedding. Grafts removed after 48 h were used in quantitative real-time reverse transcription polymerase chain reaction (RT-PCR) to gauge the expression of several genes of interest.After a period of 48 h, the animals in Group C were sacrificed, with their patency being confirmed through the utilization of a color Duplex scan. The vein grafts from these subjects underwent homogenization and examination using RT-PCR to ascertain the expression level of key stem cell genes, TLRs, MYD88, and proinflammatory cytokines.RT-PCR was performed to estimate expression patterns for several genes of interest in extracted vein grafts . The pur−ΔΔCq method was used for quantification of the target gene [All primers for β-actin, TLR2, TLR3, TLR4, TLR8, MYD88, NF-kB, CCL4, CCL20, CCR2, IFN-β, IFN-γ, TNF-α, IL-1b, IL-2, IL-4, IL-8, IL10, IL-18, KLF4, HOXA5, NANOG, and HIF1α were synthesized with TIB Molbiol . The sequences of primer pairs were designed with the Beacon Designer V7.0 software . Primer sequences are provided in get gene .p-values were two-sided, and statistical significance was set at p < 0.05. All statistical calculations were performed using GraphPad Prism version 4.03 .All values were expressed as mean ± SD (standard deviation). Mean differences (MDs) with 95% confidence intervals (95% CI) were calculated. Statistical analysis was performed using one-way analysis of variance (ANOVA) followed by Tukey’s Multiple Comparison Test. Correlation between measured parameters was assessed with Pearson analysis. In the present study, the transfection of vein grafts with Egr-1 ODN diminished the production of proinflammatory mediators and profoundly downregulated the expression of MYD88, TLRs, and stem cell genes compared with the controls and mutated analogs. These insights provide novel targets for treatment and could be utilized to improve the longevity of venous grafts in cardiovascular surgery.


CYP2D9, and 3 of CYP2C19. We observed weak unadjusted nominal significant (p < 0.05) additive effects of PGx variants of DRD1, DRD2, DRD3, HTR1A, HTR2A, HTR3A, and COMT (10 variants) on antipsychotic response; DRD2, HTR2C, BDNF, ADRA2A, ADRB3, GNB3, INSIG2, LEP, MC4R, and SNAP25 (14 variants) on weight gain; HTR2C (one variant) on metabolic syndrome; DRD2 (one variant) on prolactin levels; COMT and BDNF (two variants) on TD; HLA-DRB1 (one variant) on CLA; CYP2D6 (four phenotypes) and CYP2C19 (two phenotypes) on antipsychotics plasma levels. In the future, well-designed longitudinal naturalistic multi-center PGx studies are needed to validate the effectiveness of PGx variants in antipsychotic outcomes before establishing any reproducible PGx passport in clinical practice.The inadequate efficacy and adverse effects of antipsychotics severely affect the recovery of patients with schizophrenia spectrum disorders (SSD). We report the evidence for associations between pharmacogenetic (PGx) variants and antipsychotics outcomes, including antipsychotic response, antipsychotic-induced weight/BMI gain, metabolic syndrome, antipsychotic-related prolactin levels, antipsychotic-induced tardive dyskinesia (TD), clozapine-induced agranulocytosis (CLA), and drug concentration level (pharmacokinetics) in SSD patients. Through an in-depth systematic search in 2010–2022, we identified 501 records. We included 29 meta-analyses constituting pooled data from 298 original studies over 69 PGx variants across 39 genes, 4 metabolizing phenotypes of  Schizophrenia spectrum disorders (SSD) are severe and chronic neurodevelopmental psychiatric disorders that inversely affect patients’ quality of life. Affected persons can experience auditory and visual hallucinations, detachment from reality, and a distorted ability to think and talk . The lifDespite recent advances in the treatment of SSD, the risk of relapse ranges from 41% to 79% within one year after the first episode, particularly after discontinuing medications . FurtherPrecision psychiatry is an emerging field that strives to create personalized therapeutic strategies for individuals based on their unique health conditions. By leveraging scientific and technological advancements, it aims to deliver timely and effective treatment to each patient. The implementation of precision psychiatry has shown considerable promise, with examples such as the I-SHARED project in the Netherlands, which supports treatment choices for depression using combined socio-demographic and clinical data . AnotherTo establish trustworthy genetic evidence for personalized treatment of SSD, we conducted a systematic review and meta-analysis of peer-reviewed meta-analyses published since 2010 that examined the associations between antipsychotic pharmacogenetics  variants and seven treatment outcomes in SSD. The outputs of this study can be used to construct polygenic risk scores (PRSs), combining multiple PGx variants. This could potentially accelerate the implementation of personalized treatment for SSD.CYP2D6) is an enzyme catalyzing the metabolism of 40% of antipsychotics [CYP2D6 gene is highly polymorphic, and the presence of each variant leads to the production of slightly different enzymes with either increased, normal, decreased, or even absent activities. Carriers of CYP2D6 non-functioning variant(s) metabolize the corresponding medications more slowly, known as poor metabolizers [CYP2D6 poor metabolizers should take a reduced dose of aripiprazole and clozapine due to slower metabolism to avoid potentially increasing drug exposure, thus leading to drug complications [CYP2C19 and CYP2D6 [CYP2D6 and CYP2C19 genotype information enables treatment recommendations for a wide range of antipsychotics [DRD2), in the treatment outcomes of antipsychotics. Hence, the identification of more genetic variants with potential clinical impact on the outcome of antipsychotic treatment is essential.PGx is a promising method that may aid in improving the efficacy of drugs used to treat diseases such as cancer and hypertension, as well as psychotropics in psychiatric disorders ,17,18. Pychotics . The CYPbolizers . Therefoications ,23. A red CYP2D6 . LikewisCYP2D6 poor metabolizers due to inheriting two nonfunctional alleles [Precision psychiatry relies on various sources of information to personalize treatment for patients, and one such important source is an individual’s genetic profile. A genetic profile can be easily determined and provides a stable source of information throughout a person’s life. A retrospective study in a psychiatric setting reported that variations in CYP450 activity might be the cause of adverse drug reactions, abnormal therapeutic drug monitoring, or non-response in 34.7% of patients with an intermediate to high probability . Additio alleles . This caThe number of existing PGx studies and subsequent systematic reviews has grown exponentially in the last decade, thanks to the rapid evolution of genetic testing technologies. Although overwhelmingly increasing studies offer more evidence to support the PGx-based decision-making for drug choices, clinicians may be confused by the uncertain validity of the results and contradicting evidence. To elaborate, shortcomings in the existing PGx research, including irreproducible results ,28, non-The latest Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed in this study .A search strategy using the PICO format was developed. The original search was conducted in January 2022 and updated in October 2022. MEDLINE, Embase, CINAHL, PsycINFO, and Web of Science were searched using keywords and index terms such as: (1) terms for population: ‘schizophrenia’ OR ‘antipsychotic’ OR ‘neuroleptic’; (2) terms for intervention: ‘pharmacogenetic’ OR ‘genome wide association’; (3) terms for outcome: ‘adverse reaction’ OR ‘treatment outcome’ OR ‘efficacy’; (4) terms for study design: ‘meta-analysis’.The search was limited to include only articles written in English and published in the last 12 years, as the study design and genetic techniques used in PGx have been modernized and remain comparable across the original studies and systematic reviews. Articles were considered eligible if they (1) were meta-analyses with a systematic search strategy for previously published original studies, (2) included people with a diagnosis of SSD or psychosis, and (3) investigated any association between genetic variants and treatment outcomes of antipsychotics. All articles were screened first by viewing the title and abstract level. Articles that met the inclusion criteria were reviewed at the full-text level.We included treatment responses to antipsychotics, antipsychotic-induced weight gain, BMI, metabolic syndrome, tardive dyskinesia (TD), clozapine-induced agranulocytosis (CIA), antipsychotic-related prolactin levels, and plasma levels of antipsychotic drugs.Data extraction was performed independently by Y.T. and A.S. Any discrepancies that arose were discussed, and decisions were made by agreement among evaluators. For each eligible meta-analysis study, data were extracted, including PMID/doi, the name of the first author, year of publication, review coverage, original research studies included in the meta-analysis, antipsychotic type, outcome/endpoints, the model used for meta-analyses, number of original studies included, number of pooled sample size, study population, genes, single nucleic polymorphisms (SNPs), comparisons, pooled effect size metrics used in the meta-analyses with 95% confidence intervals (CIs), and heterogeneity between included original studies.https://flourish.studio/, accessed on 3 November 2022). This revealed and visualized the distribution and the overlap of original studies across different meta-analysis studies, offering a comprehensive overview of the scope of the present study.The coverage of included meta-analysis studies was visualized using a network diagram created with Flourish , a web tool for meta-analysis of genetic association, to estimate meta-effect sizes [If multiple meta-analyses reported the same PGx variant and outcome using the same effect size metric, a new meta-analysis was conducted by combining all the original studies to recalculate the effect sizes. We used MetaGenyo , conference abstracts (n = 10), and articles without a meta-analysis (n = 39) or without a systematic search (n = 16), and one additional study was identified and included through manual search of references, as presented in the PRISMA flowchart , antipsychotic-induced weight/BMI gain , metabolic syndrome , antipsychotic-related prolactin levels , antipsychotic-induced tardive dyskinesia , clozapine-induced agranulocytosis , and plasma levels of antipsychotic drugs   . For treAs shown in HTR2A PGx variants  with clozapine response, and they found two PGx variants (rs6313 and rs6314) exhibited significant results [CYP2D6 and CYP2C19, the number of phenotypes of the corresponding enzyme was reported. For example, the study by Calafato et al. analyzed four metabolizer statuses of CYP2D6, including poor metabolizers (PMs), intermediate metabolizers (IMs), extensive metabolizers (EMs), and ultrarapid metabolizers (UMs) [We presented all the analyzed genes per type of medication and outcome in each study in rs (UMs)   exhibited statistically significant associations under at least one of the three genetic models, i.e., dominant, recessive, or additive. Other analyzed PGx variants in the remaining four genes  showed no significant associations . The association was not significant in Asians, where the C allele was the effect allele . The two other PGx SNPs, the HTR2A rs6314*C and HTR3A rs1062613*T, exhibited significant associations with response to clozapine, with a pooled OR of 1.75  and 2.13 , respectively [HTR2A rs6311*AA genotype was significantly associated with a better olanzapine response compared to G carriers, with a pooled OR of 1.85 . However, the additive model  showed no significant result  and 11.58  in PANSS total score in a Chinese population [DRD3 rs6280 and clozapine response in mixed populations of Caucasians and African Americans [Patients with the pulation . Yet, nomericans .COMT rs4680 responded better to atypical antipsychotics compared to the Valine  allele  [The carriers of the Methionine (Met) allele of the studies) . This asstudies) .HTR1A. The larger study on the HTR1A rs6295 showed that the rs6295*C allele was associated with improvement in negative symptoms in an additive model  but not for positive symptoms , compared to the G allele [There were two meta-analysis studies  genes and antipsychotic-induced weight gain [DRD2, HTR2C, BDNF, ADRA2A, ADRB3, GNB3, INSIG2, LEP, MC4R, and SNAP25) had at least one PGx variant showing significant association under at least one genetic model with weight gain. Another half  did not exhibit any significant effect on antipsychotic-induced weight gain based on the meta-analyses results  include results .n = 72) on AIWG in their meta-analyses  DRD2  were found to be significantly associated with AIWG under the additive model, with a pooled Hedge’s g of 0.31 , 0.25 , and 0.19 , respectively  and pooled OR of 1.96 . The raw data was not reported. Zhang et al. also showed that HTR2C rs518147*GG was associated with the risk of AIWG (compared to C carriers), with a pooled Hedge’s g of 0.18  and a pooled OR of 1.86  [Notably, five studies performed meta-analyses on rd, 2010 , Ma, 201rd, 2010 , Zhang, rd, 2010 , Suetanird, 2010 , Chen, 2rd, 2010 ). Zhang’studies) .LEP rs7799039  with AIen, 2014 , and Yosen, 2014  , with a pooled OR of 2.42  [Ma et al., 2014, examined three studies) . Other gDRD2 rs1800497*A1 carriers (compared to A2A2) with a pooled Hedge’s g of 0.25  [CYP2D6 and antipsychotic-related prolactin level [Two meta-analysis studies looked into antipsychotic-related prolactin levels  . Calafatin level   and TD [COMT rs4680 and BDNF rs6265) exhibited significant association with TD under a dominant or recessive model. Yet, no significant additive model effect was reported  [BDNF rs6265*Met polymorphism was associated with increased severity of TD  in Caucasians compared to ValVal carriers  or when comparing the MetMet genotype with Val carriers  [In total, 4 out of 29 included meta-analysis studies investigated the association between four genes  and TD ,58,59,60reported . The COMstudies) . There wNQO2, CYBA, MPO, HLA-DRB1, HLA-DQB1, HLA-DRB4, HLA-DRB5, HLA-DR2, and HLA-B) and CIA, defined by ANC< 500/μL [HLA-DRB1*04:02 and CIA remained significant after the application of the Bonferroni correction when carriers were compared to non-carriers   .CYP2D6 and CYP2C19. There were three meta-analysis studies investigating the impact of CYP genes on the pharmacokinetics of antipsychotics . Takuathung et al. did not find any impact of CYP1A2 PGx variants on the pharmacokinetics (concentration-to-dose ratio or concentration) of clozapine and olanzapine [CYP2D6 EMs and UMs and IMs but not between PMs and IMs [CYP2D6 normal metabolizers  than IMs or PMs. The same trend was observed for risperidone [CYP2D6 PMs were also associated with higher haloperidol and quetiapine exposure  curve, or apparent total clearance of the drug), compared to NMs. However, analysis of clozapine did not reveal any associations with CYP2D6 but rather with CYP2C19, with PMs nearly doubling the mean value of clozapine exposure in NMs [The metabolism of antipsychotics is regulated by CYP enzymes, especially ng, 2019 : CYP1A2 ng, 2019 : CYP2D6 ic, 2021 : CYP2D6 anzapine . Zhang e and IMs . Overall and IMs ), which peridone . Furthere in NMs   have been deemed actionable by the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA) [CYP2D6 metabolism was not supported by the meta-analyses [CYP2C19 phenotypes on clozapine metabolism is not reflected in the FDA’s drug label for this medication [The challenges surrounding the poor prognosis of patients with SSD persist. So far, the Royal Dutch Association for the Advancement of Pharmacy Pharmacogenetics Working Group (DPWG) has provided prescribing guidelines regarding six antipsychotics  and cy (EMA) . Notablyanalyses , and thedication . To dateHTR2A rs6313 allele on the response to clozapine was reported to be different between Caucasians and Asians [CYP complex gene allele frequencies could vary greatly among ethnic groups, with CYP2D6*10 existing in 58.7% of East Asians while only 0.2% of Europeans [It is well recognized that ethnicity can potentially impact the observed genetic associations in PGx studies; however, most of the studies in this field have a Eurocentric focus . This mad Asians . The T auropeans . Furtheruropeans . FurtherIn summary, conducting a well-designed PGx study requires considering, firstly, each antipsychotic is metabolized through not only a single gene but by several intertwined biological pathways. Each effector, including factors for gene regulation, RNA expression, post-translational modification, enzyme function, and protein structure, is regulated by sets of genes in interaction with each other and with the micro–macro environment. Secondly, beyond the gene–drug interaction, antipsychotics themselves interact with each other and with other concurrent medications through a labyrinthic relationship. It is reasonable to assume the interaction between drugs varies per each antipsychotic and the order of the medications. Furthermore, drug efficacy is highly affected by its consumed dosage, which is a direct outcome of patients’ adherence. It is conceivable that any misconduct, including ignoring, miscalculating, or underestimating any of these facts in PGx studies, will lead to highly biased results, deviated conclusions, and eventually less clinical applicability.Genome-wide association studies (GWAS) are designed to provide an unbiased approach to the discovery of associations of a genome-wide set of variants with a trait, such as human characteristics, diseases, and drug response. For instance, a two-stage GWAS of up to 76,755 SSD patients and 243,649 control individuals has linked SSD to common variant associations at 287 distinct genomic loci . HoweverFollowing the growth of GWAS, PRSs have gained popularity in predicting diseases and phenotypes, particularly after the success of PRSs in predicting the risk of SSD in 2009, which explained 3% of the variance . PRSs alThis study could serve as a starting point for constructing antipsychotic-related gene-based PRSs to predict treatment outcomes in patients with SSD. Additionally, this study also revealed the lack of meta-analyses on other important outcomes, such as cognitive function and specific metabolic outcomes . Despite limiting the scope of meta-analysis studies to those conducted after 2010, the study’s included meta-analyses have encompassed pre-existing research data, reducing the likelihood of missing important information.In conclusion, while meta-analyses conducted over the past decade have identified several PGx variants of statistical significance for antipsychotic treatment outcomes in SSD, their small effect sizes and discrepancies across ethnicities suggest that their clinical relevance may be limited. Existing PGx guidelines are based on non-replicated findings from single studies, and the clinical application of PGx remains limited. To improve the accuracy and applicability of PGx in routine practice, further studies are necessary to integrate the strengths of PRSs with established knowledge and to consider the impact of polypharmacy on treatment outcomes. Overall, despite the growing volume of research, PGx has not yet reached its full potential in this area, and much work remains to be carried out to fully achieve personalized treatment for patients with SSD.


Accumulation of 4-hydroxynonenal (4-HNE), a marker of lipid peroxidation, has various favorable and unfavorable effects on cancer cells; however, the clinicopathological significance of its accumulation in hepatocellular carcinoma (HCC) and its metabolic pathway remain unknown. This study analyzed 4-HNE accumulation and its clinicopathological significance in HCC. Of the 221 cases, 160 showed relatively low accumulation of 4-HNE in HCC tissues, which was an independent prognostic predictor. No correlation was found between 4-HNE accumulation and the expression of the antioxidant enzymes glutathione peroxidase 4, ferroptosis suppressor protein 1, and guanosine triphosphate cyclohydrolase 1. Therefore, we hypothesized that 4-HNE metabolism is up-regulated in HCC. A database search was focused on the transcriptional regulation of aldo-keto reductases, alcohol dehydrogenases, and glutathione-S-transferases, which are the metabolic enzymes of 4-HNE, and seven candidate transcription factor genes were selected. Among the candidate genes, the knockdown of SWI/SNF-related, matrix-associated, actin-dependent regulator of chromatin, subfamily a, member 4 (SMARCA4) increased 4-HNE accumulation. Immunohistochemical analysis revealed an inverse correlation between 4-HNE accumulation and SMARCA4 expression. These results suggest that SMARCA4 regulates 4-HNE metabolism in HCC. Therefore, targeting SMARCA4 provides a basis for a new therapeutic strategy for HCC via 4-HNE accumulation and increased cytotoxicity. Hepatocellular carcinoma (HCC) is a major malignancy, accounting for approximately 90% of primary liver cancer cases, and its carcinogenesis has been reported to be associated with hepatitis C virus (HCV) and hepatitis B virus (HBV) infection, alcohol, cirrhosis, and nonalcoholic steatohepatitis. It is the fourth leading cause of cancer-related death worldwide, and, therefore, new cancer therapies are critical to improve the prognosis of patients with HCC .Metabolic changes in cancer cells or metabolic reprogramming occurs during carcinogenesis and cancer progression ,3, resulThe metabolic pathway of 4-HNE can be broadly classified into two categories. First, enzymes of antioxidant genes, such as glutathione peroxidase 4 (GPX4), ferroptosis suppressor protein 1 (FSP1), and guanosine triphosphate cyclohydrolase 1 (GCH1) inhibit lipid peroxidation through independent pathways ,24,25,26In this study, we used immunohistochemical staining to elucidate the clinicopathological significance of 4-HNE accumulation in HCC, and examined the metabolic pathway of 4-HNE using database analysis and in vitro experiments. Our study findings suggest that SMARCA4 is a key regulator of 4-HNE metabolism and has potential as a novel therapeutic target.A total of 221 formalin-fixed paraffin-embedded (FFPE) samples of HCC that were resected and diagnosed at the Tokyo Medical and Dental University Hospital between 2008 and 2014 were used in this study. Each FFPE sample comprised of a section containing tumor and non-tumor areas. This study was approved by the ethics committee of Tokyo Medical and Dental University .FFPE tissues were sliced into 4-micrometer sections, which were then placed on silane-coated slides. IHC of 4-HNE, GPX4, FSP1, GCH1, and SMARCA4 was performed using the avidin and biotinylated enzyme (ABC) method  or the polymer method , and the staining was visualized using Vector 3,3′-Diaminobenzidine Substrate (Vector Laboratories). The details of the staining conditions are presented in The cytoplasmic expression levels of 4-HNE, GPX4, FSP1, and GST1 were evaluated, compared with those in non-tumor tissues, and scored as follows: 0, weak; 1, comparable; and 2, strong. For SMARCA4, nuclear expression was scored as follows: 1, comparable; 2, partially strong; and 3, strongly positive in whole tumor tissue. All tumor and non-tumor boundaries were identified, and viable tumor cells and non-tumor hepatocyte components of the borderline were compared. The most dominant staining attitude of both areas was used as the result, and the necrotic area was excluded from the evaluation.Twelve clinicopathological factors were analyzed as follows: age (<70 vs. ≥70 years), sex , alanine transaminase (≤50 vs. >50 IU/L), cirrhosis (yes vs. no), tumor size (≤5 cm vs. >5 cm), number of lesions (single vs. multiple), vascular invasion (yes vs. no), HCV infection (yes vs. no), HBV infection (yes vs. no), differentiation (well vs. moderate vs. poor), stage , and Ki-67 index (<30% vs. ≥30%).For univariate and multivariate analyses, 4-HNE accumulation and the expression of GPX4, FSP1, and GCH1 were analyzed.https://www.oncomine.org/ (accessed on 15 November 2020)), The Human Protein Atlas (https://www.proteinatlas.org/ (accessed on 31 September 2021) [http://chip-atlas.org/ (accessed on 31 September 2021) [p < 0.05), while those for the ChIP-Atlas were fold enrichment ≥ 1, log p-value < −1.3, threshold for significance = 50, and distance range from transcription start site (TSS) of −50 ≤ TSS ≤ +50.For the estimation of the metabolic cascade of 4-HNE, the following online databases were used: Oncomine (er 2021) ), and Cher 2021) ). The seThe HCC cell line HepG2 was purchased from the Japanese Collection of Research Bioresources Cell Bank and incubated in Dulbecco’s Modified Eagle’s Medium  with 10% fetal bovine serum  and 1% penicillin and streptomycin (Gibco). The cells were passaged at a ratio of 1:5 every 2–3 days.FOXP1, MCRS1, PROX1, RUVBL1, SMARCA4, SP1, and ZMYM3 were obtained from Thermo Fisher Scientific  according to the manufacturer’s instructions, and Opti-modified Eagle’s Medium (Gibco) was used. After 72 h, the cells were collected for enzyme-linked immunosorbent assay (ELISA) analysis.siRNAs targeting β-actin, FOXP1, MCRS1, PROX1, RUVBL1, SMARCA4, SP1, and ZMYM3 mRNA levels were measured, with β-actin as a normalization control. The primer sequences are shown in RNA was extracted from siRNA-transfected cells using the RNeasy Mini Kit  and was reverse transcribed to complementary DNA (cDNA) using TaqMan reverse transcription reagents . Messenger RNA (mRNA) expression was quantified on an ABI PRISM 7900HT Sequence Detection System (Applied Biosystems) using the THUNDERBIRD SYBR qPCR Mix . In this study, w/v sodium dodecyl sulfate, 1.0% w/v NP40, and 0.5% w/v deoxycholic acid) and allowed to rest on ice for 30 min, after which they were sonicated and centrifuged at 9000× g for 15 min. The supernatant was collected, and 4-HNE concentration was quantified using the Lipid Peroxidation (4-HNE) Assay Kit  according to the manufacturer’s instructions. This experiment was repeated two times.For sample preparation, 2 × 10⁵ siRNA-transfected cells were suspended in 300 µL radioimmunoprecipitation assay buffer . The error bars represent the standard deviation in this study.Immunostaining for 4-HNE and the antioxidant enzymes GPX4, FSP1, and GCH1 was performed. Representative images of the immunostaining are shown in p = 0.034; p = 0.005, Patients were stratified according to 4-HNE accumulation and the expression levels of GPX4, FSP1, and GCH1, and the correlation between the accumulation or expression levels and overall survival was analyzed a–h. Resup = 0.049), vascular invasion (p = 0.002), differentiation (p = 0.002), stage (p = 0.004), and Ki-67 score (p = 0.001), whereas GPX4 expression levels significantly correlated with the presence of cirrhosis (p = 0.004) and HCV infection (p = 0.016). Meanwhile, FSP1 and GCH1 expression did not show a marked correlation with clinicopathological factors (p = 0.003), GPX4 expression (p = 0.005), tumor size (p = 0.001), number of lesions (p = 0.006), and vascular invasion (p = 0.004) were significantly associated with prognosis (p = 0.004), 4-HNE score 0 , and relatively high GPX4 expression  were independent predictive factors for poor prognosis. Decreased 4-HNE accumulation may be advantageous for tumor cells to survive; therefore, we conducted a detailed analysis of the factors that contribute to the decrease in 4-HNE.Next, we analyzed the correlations of 4-HNE accumulation or the expression levels of GPX4, FSP1, and GCH1 with clinicopathological factors in HCC and found that 4-HNE accumulation significantly correlated with the number of lesions , nine genes for ALDHs , and eighteen genes for GSTs . In addition, using Oncomine, a gene expression comparison database, 12 of the above 40 genes were selected based on the condition that they are related to transcription and have higher mRNA expression in HCC than in normal hepatocytes . Using The Human Protein Atlas, a comparative database of protein expression, 12 genes that had protein expression in HCC tissues were selected. Finally, seven candidate genes, namely, FOXP1, MCRS1, PROX1, RUVBL1, SMARCA4, SP1, and ZMYM3, were identified as transcription factor-related genes associated with 4-HNE metabolism.A possible mechanism of 4-HNE metabolism may be involved in the relative reduction in 4-HNE accumulation in HCC. Therefore, the factors that regulate the expression of 4-HNE metabolic enzymes were formulated under several conditions, as shown in the flow chart in SMARCA4 knockdown . In addition, patients were stratified according to SMARCA4 expression levels, and the result of their association with the outcome is shown in p < 0.001).Considering ELISA results, SMARCA4 is a candidate transcription factor that regulates the expression of a group of metabolic enzymes; therefore, immunohistochemical analysis of the association between SMARCA4 expression and 4-HNE accumulation in HCC tissues was performed . The res4-HNE is the final metabolite of lipid peroxidation, resulting from the peroxidation of ω6 polyunsaturated fatty acids such as linolenic and arachidonic acids. It is associated with carcinogenesis and cancer progression, has highly reactive C=C and C=O, and forms adducts with intracellular substances such as proteins, nucleic acids, and phospholipids, leading to impaired intracellular signal transduction, genetic mutations, and cytotoxicity ,41. Thisv12 mutations, is involved in HCC carcinogenesis [http://chip-atlas.org/, accessed on 31 September 2021) showed that SMARCA4 regulates GSTA4, a 4-HNE metabolic enzyme. Of the GSTs, GSTA4 is known to have a particularly high metabolic capacity for 4-HNE [An inverse correlation between GPX4 expression and accumulation of 8-hydroxy-2′-deoxyguanosine, the end-product of oxidation, has been observed in diffuse large B-cell lymphoma (DLBCL) , whereasogenesis , whereasogenesis . A databor 4-HNE . GSTs coor 4-HNE .In this study, SMARCA4 negatively regulated 4-HNE accumulation in HCC, suggesting that it positively regulates the expression of 4-HNE metabolic enzymes and contributes to 4-HNE metabolism and its decrease in cancer tissues. This reduces the cytotoxicity of 4-HNE and may favor the survival of HCC cells. Furthermore, SMARCA4 upregulated the expression of HO-1, an antioxidant enzyme , which mIn addition, a poor prognosis was observed in the group with high expression of the antioxidant enzyme GPX4, suggesting that lipid peroxidation was suppressed in this group. In turn, this suggests that low 4-HNE expression may be partly due to the overexpression of GPX4, which is a key negative regulator of ferroptosis (nonapoptotic cell death related to lipid peroxidation) that has recently attracted attention . The oveSECISBP2, which regulates GPX4 expression, and its expression may be controlled by a similar mechanism in HCC [Despite these findings, this study has several limitations. The expression levels of GPX4, FSP1, and GCH1 in HCC differed from case to case; however, we were unable to investigate the molecular mechanisms that regulate this in the present study. Overexpression of GPX4 in DLBCL has been shown to upregulate m in HCC . MoreoveCollectively, our findings elucidate the clinicopathological significance of 4-HNE in HCC and the molecular mechanisms underlying the 4-HNE metabolic pathway. Future studies on the details of SMARCA4-mediated metabolism of 4-HNE and examination of preclinical models may help establish evidence for SMARCA4 as a therapeutic target and improve the prognosis of patients with HCC.


Genotype-environment interaction (GEI) presents challenges when aiming to select optimal cassava genotypes, often due to biased genetic estimates. Various strategies have been proposed to address the need for simultaneous improvements in multiple traits, while accounting for performance and yield stability. Among these methods are mean performance and stability (MPS) and the multi-trait mean performance and stability index (MTMPS), both utilizing linear mixed models. This study’s objective was to assess genetic variation and GEI effects on fresh root yield (FRY), along with three primary and three secondary traits. A comprehensive evaluation of 22 genotypes was conducted using a randomized complete block design with three replicates across 47 distinct environments (year x location) in Brazil. The broad-sense heritability ( It is one of the primary agricultural species and holds significant industrial potential, particularly in the starch extraction from its roots, which is considered the species’ primary product. However, all parts of the plant can be commercially utilized or explored as genetic plant resources  crossing to obtain progenies; ii) seedling production and field transplantation; iii) clonal evaluation trials (CET), the initial stage of agronomic evaluation characterized by a few environments and a high number of clones; iv) preliminary yield trials (PYT), represented by 2-3 field replications, fewer plants per plot (1 row with 6-8 plants), and 1-2 locations; v) advanced yield trials (AYT), with 3 replications, larger plots (4 rows with 16-24 plants), and 3-5 locations; vi) uniform yield trials (UYT), featuring 3-4 field replications, larger plots (4-6 rows with 40-60 plants), and 8-12 evaluation locations; and vii) cultivar value and use trials (VCU). Therefore, generally, starting from the AYT trials, cassava clones are already evaluated in multi-environment tests (METs) over several years to assess genotype-environment interaction (GEI) . These tMETs are conducted annually to examine the genotype × environment interaction (GEI), a natural phenomenon that incorporates the effects of genotypes and environments as well as the non-consistency in genotype ranking for specific traits. Assessing the importance of genetic and environmental factors is particularly important in the selection process, especially for traits with low heritability, as they may potentially exhibit more pronounced GEI effects .In recent decades, a range of statistical methods have been developed to model GEI, identify genotypes that are stable and well-adapted, and select target environments, including mega-environments that share similar climatic patterns. These methods vary from simple nonparametric analysis-of-variance techniques with fixed and/or linear-bilinear effects to more robust univariate and multivariate parametric methods. These advancements aim to achieve more advanced results and a more systematic characterization of GEI . More reIn the final phases of breeding programs, a significant challenge emerges due to the inherent imbalance in trials caused by replacing underperforming clones with new ones for testing in subsequent years. This results in varying numbers of genotypes being evaluated annually and across different locations, leading to a pronounced imbalance in the phenotypic data. Conventional approaches to studying the GEI face difficulties when dealing with such imbalanced data, resulting in disparate variances and covariances of fitted mean phenotypic values. These variances and covariances play a crucial role for breeders in selecting genotypes for further assessment or recommending them as new varieties. Furthermore, innovative mixed model-based approaches, like analytical factor analysis, facilitate the integration of kinship information by employing covariance matrices of random genetic effects .Beyond exhibiting high agronomic potential in specific target environments, novel cassava varieties must also demonstrate phenotypic stability to gain recommendation and adaption across wider geographical regions, whether for industrial use or direct consumption. Nevertheless, selecting genotypes with strong performance across multiple traits simultaneously presents a complex challenge due to undesirable correlations stemming from intricate trait relationships and genetic architectures . Most prTo ensure the delivery of varieties that meet consumer expectations and gain high adoption in the agricultural sector, the selection process should consider not only yield-related attributes but also characteristics associated with plant architecture, reproductive capacity, soil coverage to minimize weed interference, and root quality for improved commercial acceptance, particularly when the roots are intended for fresh consumption or processing in agroindustries that demand high-quality starch. As a result, multi-trait and multi-environment selection in cassava breeding programs is already being practiced . However22.1The METs conducted by the cassava breeding program at Embrapa Mandioca e Fruticultura in Cruz das Almas, Bahia, Brazil , encompassed a total of 11 AYT and 36 UYT trials across diverse agricultural potential environments Table S1A total of 22 genotypes underwent evaluation, including six clones in the final stage gate form the Embraoa breeding program , along with 10 improved varieties released for the target area , and six landraces used by the local farmers .The soil preparation for cultivation followed conventional practices, including desiccation of spontaneous plants, plowing, and harrowing to incorporate crop residues. Planting furrows were then created using a cassava planter, and fertilization was performed based on soil analysis. Manual planting was carried out horizontally in the furrows using standard cassava stems obtained from 12-month-old plants that were free of pests and diseases.For experimental design, the trials were organized following a randomized complete block design with three replications. Each plot comprised four rows, accommodating 25 plants per row, spaced at 0.90 m between rows and 0.80 m between individual plants. Fertilization and post-planting treatments adhered to the recommended practices for cassava cultivation (as outlined by 2.2-1), 2) shoot yield (ShY) represents the weight of the aboveground parts of all the plants in the plot, including stems, leaves, and petioles, also converted in tons per hectare (t ha-1), 3) dry matter content of the roots (DMC), determined in % using the specific gravimetric method (-1), 5) harvest index (HI), the ratio between the fresh weight of roots and the total biomass, including both aboveground and belowground parts of the plants, expressed as a percentage (%), 6) plant archictetucture (PIA), evaluated using a 1-5 rating scale, where: 1 excellent architecture (no branching or erect stems), 2 good architecture (branching above 1.60 m or low branching with at least 1.6 m of erect stems), 3 means moderate architecture (branching above 1.20 m or low branching with at least 1.2 m of erect stems), 4 poor architecture (branching above 0.80 m or low branching with at least 0.80 m of erect stems), and 5 very poor architecture (highly branched clones with less than 0.80 m of erect stems), 7) plant height (PH), measured using a graduated scale from the soil level to the plant meristem and is expressed in meters (m).At 12 months after planting, seven agronomic traits were measured: 1) fresh root yield (FRY) represents the total weight of all the roots in the plot and is measured in tons per hectare  dry 2.3After conducting the individual analysis of variance and ensuring the homogeneity of residual variances using the Shapiro-Wilk test, the joint analysis of variance was performed. A deviance analysis was performed considering the following mixed-effect model: The variance components were obtained using the restricted maximum likelihood (REML) using the expectation-maximization algorithm , and theFour heritability estimates were obtained: (i) Broad-sense heritability  for genotypes, environments, and genotype-environment interaction (GEI). These findings highlight the presence of genetic variability, leading to changes in genotype classification across various agronomic attributes analyzed. Furthermore, it underscores the importance of evaluating genotype performance while considering environmental variations Table 1.-1), representing a 30% superiority compared to the average of evaluated genotypes (23.80 t ha-1). In contrast, genotypes BR11-34-69, BRS Formosa, and Vassoura Preta exhibited the highest HI (>60.0%) in relation to the overall average of 54.33% (-1) and 2019.ERU.GA (with an average of 72.01%), respectively . Environmental influence was also significant, ranging from 10.39 t ha-1 in the 2016.ERU.SA environment to 50.28 t ha-1 in 2020.ERU.UFV. High DMC contents were observed in genotypes BRS Novo Horizonte, BRS Mulatinha, and BR12-107-002 (>37%). Although there was relatively smaller environmental variation for this trait (ranging from 30.79% in the 2021.ERU.AL environment to 38.26% in the 2019.ERU.NR environment). The ranking of genotypes based on the DRY trait highlighted BRS Novo Horizonte and BR11-34-69 as the most productive (>9.0 t ha-1), with only BRS Novo Horizonte exhibiting high DMC. The DRY trait varied from 2.55 t ha-1 in the 2021.ERU.UFGD environment to 12.56 t ha-1 in the 2021.ERU.NH4 environment, with an average range of genotypes for this trait across environments being 4.39 to 9.36 t ha-1.Genotypes BRS Novo Horizonte, BR11.34.64, BR11.34.45, BRS Mulatinha, and Correntão exhibited ShY above 23.0 t ha-107-002). Regarding the PH trait, genotypes BRS Tapioqueira, BR11-34-64, BR11-34-69, and BRS Poti Branca displayed the tallest plants (>2.4m), representing an 11% superiority compared to the average of tested genotypes. The average plant height across environments ranged from 1.57m (in the 2021.ERU.UFRB environment) to 3.03m (in the 2020.ERU.UFV environment).For the PIA trait, genotypes IAC-90, BR11-34-64, BR11-34-69, and BR12-107-002 exhibited scores below 2, indicating good plant architecture suitable for mechanized planting and harvesting. There was significant variation in this characteristic, ranging from 4.70 (genotype BRS Verdinha) to 1.29  to explain genetic variations in the dataset. These components explained a cumulative variance of 92.20% for R2, and Agronomic traits were categorized based on stability parameters: R2 and Regarding 3.4R2 and We selected the parameters R2 and Among the genotypes, BRS Poti Branca and BRS Novo Horizonte were assigned to Group 1 due to their high stability for FRY and ShY, as indicated by the R2 parameter. This indicates the challenge in selecting genotypes that are both stable and high performing, with a noticeable variability within the group. A smaller subset of genotypes (approximately 5) was grouped based on the R2, and BRS Caipira for Group 2 included a larger number of genotypes (approximately 13 genotypes) based on the R2. BR12-107-002 and BRS Verdinha were grouped in Group 1 for the For the DRY and DMC traits, Group 1 consisted of genotypes that had both high performance and stability, and it grouped the smallest number of genotypes. For DRY and DMC, the genotype BRS Novo Horizonte was allocated to Group 1 based on the R2 and For DRY, the largest number of genotypes was allocated to Group 2, particularly based on the R2 and R2 parameters, whereas Eucalipto and BRS Dourada were grouped based on the Group 3 comprised nine genotypes grouped based on the 3.5R2 and R2 and R2 and R2 parameter. Group 4 included a larger number of genotypes with high variability within the group, as indicated by the R2 parameter only grouped BRS Caipira.Using the R2 parameters. Group 3 encompassed a significant number of genotypes (13 for R2), with common genotypes such as BR11-34-64, BR11-34-69, BR11-34-41, BR11-24-156, and BR12-107-002. In contrast, Group 4 consisted of the smallest number of genotypes, with IAC-90 being grouped in all three parameters.For the PH trait, Group 1 consisted of 12 clones grouped based on the R2 parameters. These genotypes demonstrated high performance and consistent stability for PIA, regardless of the stability-to-performance ratio (0/100). The rank order of these genotypes remained unchanged regardless of the variation in ranking criteria. Interestingly, the R2 parameters. No other clones met the stability criteria for PIA in Group 4. Notably, the classification of genotypes in Group 4 did not exhibit significant variations with respect to different weight ratios between stability and agronomic performance, particularly for the For the PIA trait, BR12-107-002 was placed in Group 1, primarily based on the parameters 3.6R2 parameter exhibited greater variability, ranging from -3.08% (DMC) to 33.0% (FRY). Gains exceeding 25% were observed only for the DRY and FRY traits. Similar variability was observed for the MPS gains in the R2, and The MPS index selection differential for the 3.7R2 and R2 and A network diagram S3 was uR2 and R2 parameter (-0.50), albeit with moderate magnitude. Additionally, modest negative correlations were found between DMC × PIA for all three parameters, ranging from -0.26 to -0.43. Among these correlations, only the R2 parameter yielded significant results.Despite the variability, certain pairs of traits showed consistent correlations across the R2values exceeding 0.98 and showed a low residual correlation (0.16). Furthermore, they had variance inflation factor values below 10, indicating low multicollinearity. Consequently, these traits hold value for indirect selection and the utilization of multi-trait indices  that contribute significantly to the main trait, fresh root yield  and secondary traits (PH and PIA). These groupings often exhibited negative correlations, such as DMC × PIA and HI × ShY, which pose challenges in simultaneous selection of genotypes based on multi-trait indices. However, trail analysis demonstrated that a significant portion of the variation in FRY could be explained by the direct effects of two primary traits: DRY (0.97) and ShY (0.50). These traits exhibited 3.8R2 and R2 parameter, most traits exhibited gains ranging from 2.62% (HI) to 18.90% (FRY), except for PIA, which showed a reduction of 14.60% (which is desired in this case). For the The MTMPS index provides insights into the selection differential, selection gains, and heritability of selected across various agronomic traits Table 5.R2, and With a selection intensity of 30%, the MTMPS index enabled the selection of seven genotypes based on the R2 parameter, the selected genotypes were BR11-34-69 (1.83), BRS Novo Horizonte (1.85), BRS Kiriris (2.15), BR11-34-45 (2.19), BR11-34-64 (2.45), BR11-34-41 (2.66), and BRS Mulatinha (2.85). The R2 parameter highlights the selection of four genotypes in the final validation phase, with a significant contribution from FA1 (54.93%), primarily associated with FRY and DRY traits. Only BRS Novo Horizonte exhibits a balanced importance between FA1 and FA3, which is more related to DMC and PIA.For the Regarding the 44.1Significant progress has been made in cassava breeding programs, aiming to develop new varieties with improved genetic gains, performance, stability, and adaptability compared to traditional cultivars . GEI chaThe study underscores the challenge of selecting cassava genotypes that balance stability and high performance due to significant GEI effects. However, innovative approaches and understanding genetic parameters can help identify genotypes less influenced by environmental variations. The genotypic coefficient of variation  and BR11-34-45 (>35.0% DMC), suggesting suitability for predictable environments.In the final validation phase, relying solely on production performance or stability information is not sufficient for efficient genotype recommendation, as it is possible to identify genotypes with low agronomic performance but high stability between environments, and vice versa . For exaThe challenge of simultaneous selection for agronomic performance and yield stability has been reported by other authors in various crops using the WAASB model (weighted average of absolute scores) . SpecifiWhile yield stability index (YSI) and genotype stability index (GSI) have been proposed for selecting genotypes based on yield performance and stability, relying solely on the average stability value (ASV) parameter can lead to biased results. Additionally, these methods lack flexibility in economic weights or ranking scenarios. Additionally, these methods do not allow for varying economic weights or evaluating different ranking scenarios. The MPS selection index, on the other hand, leverages relationships between agronomic performance and production stability using conventional stability analysis methods. It aims to group genotypes with similar phenotypic behavior for both performance and stability. By utilizing the regression model proposed by R2 parameter represents the regression coefficient, with R2, thereby achieving high productivity and stability. Conversely, genotypes that are more unstable and have low productivity can be identified based on their distance from the ideal values in the regression parameters. Analyzing the The -1, which is 80% higher than the average root yield in the state of Bahia , ShY (9.0 t ha-1), and DMC (33%). BRS Verdinha exhibited a more branched growth (>4), which hinders mechanized planting, and a harvest index (HI) below 51%, along with average yield values. Overall, the MPS index represents a significant advancement over existing selection methods, as it identifies useful genetic relationships for breeders. It provides a robust methodological basis that is easy to manipulate and interpret for multi-character selection, with reduced sensitivity to outliers , while the genotype BR12-107-002 showed stability for PIA (<2) based on all three stability parameters. On the other hand, genotypes in Group4 were characterized by unpredictability and low agronomic performance, suggesting the influence of GEI. For example, the genotype IAC-90 showed low yields  across all three stability parameters, consistent with existing literature  exhibit high genetic correlation and are strongly influenced by environmental variation . TherefoAddressing multicollinearity issues is crucial to avoid bias in genetic parameter estimates during selection, especially when using conventional indices like The use of base and multiplicative selection indexes for multiple traits has been limited. The former does not incorporate genotypic and phenotypic variance-covariance matrices, thus ignoring GEI interactions, while the latter neglects economic weights. Furthermore, both base and multiplicative selection indexes fail to incorporate information on yield stability . In contThe MTMPS index allows genotype-ideotype selection (based on Euclidean distance) by considering multiple traits. The procedure involves the following steps: (i) using the correlation matrix between traits to identify eigenvalues  and eigenvectors of genotypes , (ii) performing principal component analysis on the characteristics to reduce the dimensionality of the data and identify the number of factors grouping the traits, and (iii) applying varimax rotation to estimate factorial loadings, considering eigenvalues >1, to interpret variable grouping and address multicollinearity concerns . AdditioThe ideotype concept is crucial in breeding strategies, aiming to obtain genotypes with high performance and stability across multiple traits in a specific target environment . In cassR2 parameters, respectively, as they exhibited low or zero GEI interaction even in the face of environmental variations.Using a selection intensity of 30%, the MTMPS index identified seven clones, most of which were new genotypes in the final validation phase. These selected clones demonstrated lower MTMPS values, indicating their proximity to the ideotype. Genotypes such as BR11-34-69 and BR11-34-64 were chosen based on all three stability parameters and were deemed suitable for cultivation in diverse environments. On the other hand, genotypes BRS Novo Horizonte, BRS Kiriris, and BR11-34-41 were selected based on the R2 >0.97). FRY and DRY were the most significant contributors to the first factor (FA1) of the MTMPS index in all three stability parameters, accounting for more than 56% of the contribution. Thus, the selection process prioritized cassava genotypes with higher potential for acceptance in starch and flour processing agro-industries, which desire higher FRY and DRY values. Notable improved genotypes included BRS Novo Horizonte, BRS Tapioqueira, and two genotypes in the final validation phase, BR11-34-69 and BR11-34-64.Analyzing strengths and weaknesses revealed that yield components had a greater contribution, followed by secondary variables, in explaining and influencing genotype selection. The traits DRY (0.96), ShY (0.48), and HI (0.38), which represent yield components, strongly influenced the highest FRY  that exhibit potential for simultaneous genetic gains in both quantitative traits  and qualitative traits  of agronomic interest for both industry and fresh consumption. By combining these approaches, the time required for recommending new genotypes can be reduced, while generating valuable information about parents with contrasting traits, stability in productive attributes, and a higher likelihood of expressing heterosis in the offspring.5Utilizing multivariate selection yielded significant insights into estimating genetic parameters, resulting in an average heritability (R2 and Group 1 consisted of highly productive and stable genotypes for primary traits like FRY, including varieties such as BRS Novo Horizonte and BR11-34-69, as well as for DMC with genotypes BRS Novo Horizonte and BR12-107-002. Regarding secondary characteristics like HI and PIA, genotypes BRS Formosa and BR12-107-002 showed the highest stability and better agronomic performance. Therefore, employing methods that consider both stability and productive performance can enhance the reliability of recommending new cassava cultivars. Moreover, using the MTMPS index with a selection intensity of 30% led to the identification of seven genotypes with higher stability based on the parameters of The original contributions presented in the study are included in the article/JS: Conceptualization, Data curation, Formal Analysis, Methodology, Writing – original draft. TO: Formal Analysis, Writing – review & editing. MC: Writing – review & editing, Data curation, Validation. EdO: Writing – review & editing, Conceptualization, Funding acquisition, Methodology, Project administration, Supervision.


Asthma is a heterogeneous entity encompassing distinct endotypes and varying phenotypes, characterized by common clinical manifestations, such as shortness of breath, wheezing, and variable airflow obstruction. Two major asthma endotypes based on molecular patterns are described: type 2 endotype  and T2 low endotype (obesity-related asthma). Long noncoding RNAs (lncRNAs) are transcripts of more than 200 nucleotides in length, currently involved in many diverse biological functions, such as chromatin remodeling, gene transcription, protein transport, and microRNA processing. Despite the efforts to accurately classify and discriminate all the asthma endotypes and phenotypes, if long noncoding RNAs could play a role as biomarkers in allergic asthmatic and adolescent obesity-related asthma, adolescents remain unknown. To compare expression levels of lncRNAs: HOTAIRM1, OIP5-AS1, MZF1-AS1, and GAS5 from whole blood of Healthy Adolescents (HA), Obese adolescents (O), allergic asthmatic adolescents (AA) and Obesity-related asthma adolescents (OA). We measured and compared expression levels from the whole blood of the groups mentioned above through RT-q-PCR. We found differentially expressed levels of these lncRNAs between the groups of interest. In addition, we found a discriminative value of previously mentioned lncRNAs between studied groups. Finally, we generated an interaction network through bioinformatics. Expression levels of OIP5-AS1, MZF1-AS1, HOTAIRM1, and GAS5 in whole blood from the healthy adolescent population, obese adolescents, allergic asthma adolescents, and obesity-related asthma adolescents are differently expressed. Moreover, these lncRNAs could act as molecular biomarkers that help to discriminate between all studied groups, probably through molecular mechanisms with several genes and miRNAs implicated. Asthma is a heterogeneous entity, now considered as an “umbrella diagnosis” because it encompasses several distinct diseases or endotypes and varying phenotypes , is characterized by common clinical manifestations, such as shortness of breath, wheezing and variable airflow obstruction . This heIn most cases is characterized by the infiltration of neutrophils in the epithelium of the respiratory tract and the appearance of more severe clinical scenarios where TNF-α, IL-1β, IL-6, IL-15, IL-23, IL-17, IL-21, and IL-22 are the centrally implicated cytokines .In this sense, obesity has become a growing pediatric health problem worldwide, affecting more than 124 million children and adolescents worldwide. In addition, and due to several studies that have linked poorer clinical outcomes to “low-grade inflammation”, a key component of obesity, asthma-related obesity has attracted increasing attention from researchers worldwide ,10.Nevertheless, even though several authors have focused on accurately classifying and discriminating all the asthma endotypes and phenotypes, there is still a significant knowledge gap between those entities, and certainly, the discovery of new molecular biomarkers is needed . In the In this study, we analyzed a total of 92 adolescent participants that were divided into four groups: 23 were healthy adolescents, 21 had obesity without asthma, 28 had allergic asthma without obesity, and 20 had obesity-related asthma. The four groups had similar ages, sex distribution, and Tanner distribution. In contrast, anthropometrics significantly differed between Obese and non-obese groups with similar time with obesity. In addition, OA patients had slightly higher Asthma severity with more moderate persistent patients. Finally, treatment was not different between AA and OA. All the main characteristics are presented in p < 0.0001; HA vs. OA, p < 0.0001; O vs. AA, p < 0.001, and O vs. OA, p < 0.001; HA vs. O, p > 0.999; AA vs. OA; p > 0.999). GAS5 , HOTAIRM1 and GAS5 showed similar expression behavior, higher expression levels were observed in both asthmatic phenotypes, allergic asthma, and obesity-related asthma compared with their counterparts, healthy and obese adolescents, respectively. Moreover, these lncRNAs do not show statistical differences between healthy donors versus obesity and allergic asthma versus obesity-related asthma: HOTAIRM1  p < 0.001; HA vs. OA, p < 0.0001; O vs. AA, p < 0.001, and O vs. OA, p < 0.001; HA vs. O, p < 0.001; AA vs. OA; p = 0.024), On the other hand, MZF1-AS1 only showed differences between the Allergic Asthmatic group compared to the others , respectively p < 0.0001, and AUC: 0.8024, 95% CI: 0.6539 to 0.9509, p = 0.0009), respectively, p = 0.0203) and MZF1-AS1 , respectively, Based on observed differences, we tested the potential discriminative role of the studied lncRNAs. Therefore we performed the area under the curve ROC analysis. In this analysis, we found that HOTAIRM1 and GAS5 may accurately discriminate asthmatic patients from those who have not presented that illness  Then, due to the high discriminative value of OIP5-AS1 and GAS5, we tested their cumulative value in the abovementioned groups. Therefore, we obtained the expression levels ratio from these lncRNAs based on this new quantitative variable. Next, we carried out an area under the ROC curve analysis, and interestingly this ratio accurately discriminates obesity alone from obesity-related asthma: AUC: 0.9026, 95% CI: 0.7855 to 1.000, Finally, we generated an interaction network in which we searched the base-pairing interactions of studied lncRNAs with several selected miRNAs and Genes. Interestingly, we found that OIP5-AS1, MZF1-AS1, HOTAIRM1, and GAS5 may indirectly interact with genes described as critical components of the pathophysiology of both significant asthma endotypes, In this study, we analyzed the expression levels of the lncRNAs: HOTAIRM1, GAS5, OIP5-AS1, and MZF1-AS1 from whole blood of healthy, obese, allergic asthmatic and obesity-related asthmatic adolescents through RT-qPCR. We found differentially expressed levels of these lncRNAs between the groups of interest. In addition, a discriminative value of the abovementioned lncRNAs between diverse studied groups was observed. For instance, HOTAIRM1 and GAS5 may help to discriminate all asthmatic patients from controls. Furthermore, OIP5-AS1 and GAS5 could help to differentiate obesity alone from obesity-related asthma, and OIP5-AS1 and MZF1-AS1 may help to discriminate between asthma endotypes. Finally, we generated an interaction network of the previously mentioned lncRNAs in which several classical genes related to asthma are indirectly involved through the interaction with diverse miRNAs.First, we found higher levels of lncRNAs: HOTAIRM1, GAS5, MZF1-AS1, and OIP5-AS1 in the allergic asthmatic and obesity-related asthma patients compared with their counterparts’ healthy adolescents and obesity without asthma adolescents, respectively. In this sense, several studies have related higher expression levels of the lncRNAs with more severe pathologic states. For instance, Lipin Wu and collaborators found that higher levels of OIP5-AS1 indicated poor prognosis in pancreatic ductal carcinoma. Meanwhile, the downregulation of the abovementioned lncRNA interfered with cell proliferation and migration, to which miR-429 was related . FurtherOn the other hand, Xiaoping Wang and colleagues proposed that lncRNA GAS5 may be a key component in the pathophysiology of childhood pneumonia by inhibiting cell apoptosis and promoting SHIP-1 expression via downregulating miR-155 . FurtherAfter that, we tested the discriminative value of these lncRNAs through the area under the curve ROC analysis and interestingly found that HOTAIRM1 and GAS5 can help discriminate between any asthma phenotype of healthy and obese patients. Furthermore, the expression levels of OIP5-AS1 and GAS5 may help to discriminate between obesity alone and obesity-related asthma. OIP5-AS1 has little or non-studies in obesity, whereas GAS5 has been implicated in obesity and insulin resistance by targeting some miRNAs, such as miR-21, that have been implicated in obesity, as well as in lung diseases . On the Moreover, they observed that patients with high expression levels of that lncRNA had lower overall survival compared to those with higher expression levels. Finally, the authors suggest that HOTAIRM1 may be a potential diagnostic and prognostic biomarker for such patients . DespiteFurthermore, our results suggest that OIP5-AS1 and lncRNA GAS5 could be a cornerstone that helps to explain how obesity is directly related to asthma. There is a significant knowledge gap where more molecular biomarkers are needed; we think that OIP-5AS1 and lncRNA GAS5 could help in the future to understand better molecular mechanisms involved in asthma and obesity pathophysiology . In thisFinally, the bioinformatics analysis showed us an exciting signature of genes and miRNAs. In this sense, since the discovery of mathematics, the human being has tried to find an explanation through numbers for our entire environment, and today thanks to the advancement of technology and, in this case of computing, it has become much easier to try to predict the behavior of biological systems with the help of diverse bioinformatics software and algorithms . In thisAs a limitation, the design of our study is cross-sectional. Therefore no prospective results were explored. Thus, further experiments with the OIP5/GAS5 signature should be designed to test its potential ability to predict the development of asthma in the context of obesity-related asthma. However, this study raises an essential issue about the characterization of endotypes and varying phenotypes in asthma, which is a very interesting finding and could help future research development.A cross-sectional study was carried out from August 2019 to January 2020. All patients were sampled by convenience in the Children’s Hospital of Mexico Federico Gómez, Mexico City.To accomplish our objective and minimize the measurement bias, we performed the long noncoding RNAs quantification in 4 different groups: (1) healthy adolescents (HA), (2) allergic asthma without obesity (AA), (3) obesity without asthma (OB), and (4) obesity-related asthma (OA). Furthermore, according to the declaration of Helsinki (2013) and the Mexican Regulation for Biomedical Research, all participants’ parents signed informed consent, and adolescents firmed assent before any procedure. Therefore, the study was approved by the research, ethics in research, and biosecurity committee of the Children’s Hospital of Mexico Federico Gómez with the approval numbers HIM/2013/015.SSa.1601 and HIM/2020/030.SSa.1667.RNA was isolated from 300 µL of peripheral blood, according to the Guanidine Thiocinate method  . The RNA® Green Master, Roche, Basel, Switzerland) were performed according to manufacturer instructions. Relative quantification was carried out by the 2−∆∆Ct method using Glyceraldehyde-3-Phosphate Dehydrogenase (GAPDH) as a reference gene.We used primers designed by QIAGEN to determine the expression of target genes: RT² lncRNA qPCR Assay for Human GAS5: (NCBI 60674), Catalog No.—#LPH-11340A-200_3410131; OIP5-AS1 (NCB1 729082), Catalog No.—#LPH15948A-200_3316050; MZF1-AS1 (NCBI 100131691), Catalog No.—# LPH25874A-200; HOTAIRM1 (NCBI 100506311), #LPH10483A-200_3442487 . The reverse transcriptase  and the PCR  was considered statistically significant.Statistical analyses were performed using Statistical Package for Social Sciences v24.0 software . To test the distribution of quantitative variables Kolmogorov-Smirnov test was performed. Quantitative data are presented as the medians and interquartile range (IQR). The Mann-Whitney U test was performed to analyze statistical differences between 2 groups, and the Kruskal-Wallis test was carried out to analyze statistical differences between more significant than two groups with Dunnet post hoc analysis. Fisher’s tests analyzed comparisons of proportions. Correlations were analyzed with a nonparametric Spearman correlation test. To evaluate the accuracy of predicting non-allergic asthma, receiver operating characteristic (ROC) curve analysis was performed, and the area under the curve (AUC) with the Youden’s index optimal cut-off point was calculated. A https://www.rna-society.org/rnainter/ (accessed on 25 August 2022)), RNA central ), LNCipedia (https://lncipedia.org/ (accessed on 27 August 2022)) and LncRRIsearch (http://rtools.cbrc.jp/LncRRIsearch/ (accessed on 2 September 2022)), we represented the direct and indirect interactions that OIP5-AS1, MZF1-AS1, HOTAIRM1, and GAS5 can have with several genes that have previously described as critical components of the pathophysiology of both major endotypes of asthma.An interaction network was created in which we searched the base-pairing interactions of studied lncRNAs with diverse miRNAs and Genes in diverse databases, such as RNA interactome Database (https://www.mirnet.ca/ (accessed on 5 September 2022) [Network analysis was performed with the mirNET 2.0 bioinformatic tool: er 2022) . And vis