Next Article in Journal
Influence of a High-Impact Multidimensional Rehabilitation Program on the Gut Microbiota of Patients with Multiple Sclerosis
Next Article in Special Issue
Hidden Role of Gut Microbiome Dysbiosis in Schizophrenia: Antipsychotics or Psychobiotics as Therapeutics?
Previous Article in Journal
Product Distributions of Cytochrome P450 OleTJE with Phenyl-Substituted Fatty Acids: A Computational Study
Previous Article in Special Issue
Glutathione Deficiency during Early Postnatal Development Causes Schizophrenia-Like Symptoms and a Reduction in BDNF Levels in the Cortex and Hippocampus of Adult Sprague–Dawley Rats
Article

Transcriptional Modulation of the Hippo Signaling Pathway by Drugs Used to Treat Bipolar Disorder and Schizophrenia

1
Institute for Innovation in Physical and Mental Health and Clinical Translation, School of Medicine, Deakin University, IMPACT, Geelong 3220, Australia
2
Genomics Centre, School of Life and Environmental Sciences, Deakin University, Burwood 3125, Australia
3
Florey Institute for Neuroscience and Mental Health, University of Melbourne, Parkville 3052, Australia
4
Department of Psychiatry, Royal Melbourne Hospital, University of Melbourne, Parkville 3052, Australia
5
Centre of Youth Mental Health, University of Melbourne, Parkville 3052, Australia
6
Orygen Youth Health Research Centre, Parkville 3052, Australia
*
Author to whom correspondence should be addressed.
Academic Editor: Juan F. Lopez-Gimenez
Int. J. Mol. Sci. 2021, 22(13), 7164; https://doi.org/10.3390/ijms22137164
Received: 21 June 2021 / Revised: 26 June 2021 / Accepted: 28 June 2021 / Published: 2 July 2021
(This article belongs to the Special Issue Molecular Mechanisms of Schizophrenia and Novel Targets)

Abstract

Recent reports suggest a link between positive regulation of the Hippo pathway with bipolar disorder (BD), and the Hippo pathway is known to interact with multiple other signaling pathways previously associated with BD and other psychiatric disorders. In this study, neuronal-like NT2 cells were treated with amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), valproate (0.5 mM), or vehicle control for 24 h. Genome-wide mRNA expression was quantified and analyzed using gene set enrichment analysis (GSEA), with genes belonging to Hippo, Wnt, Notch, TGF- β, and Hedgehog retrieved from the KEGG database. Five of the eight drugs downregulated the genes of the Hippo pathway and modulated several genes involved in the interacting pathways. We speculate that the regulation of these genes, especially by aripiprazole, clozapine, and quetiapine, results in a reduction of MAPK and NFκB pro-inflammatory signaling through modulation of Hippo, Wnt, and TGF-β pathways. We also employed connectivity map analysis to identify compounds that act on these pathways in a similar manner to the known psychiatric drugs. Thirty-six compounds were identified. The presence of antidepressants and antipsychotics validates our approach and reveals possible new targets for drug repurposing.
Keywords: Hippo pathway; psychotropic drugs; bipolar disorder; schizophrenia; inflammation; drug repurposing; connectivity map; psychiatry; neuroscience Hippo pathway; psychotropic drugs; bipolar disorder; schizophrenia; inflammation; drug repurposing; connectivity map; psychiatry; neuroscience

1. Introduction

The Hippo pathway is a signaling cascade that integrates a broad range of different biological, chemical, and mechanical cues to control several cellular processes through its downstream effectors YAP (yes-associated protein) and transcriptional co-activator with PDZ-binding motif (TAZ) [1,2]. It was first discovered in Drosophila melanogaster, where a genetic mutation in one of its core components (Hippo/Hpo) was associated with tissue overgrowth of the eyes, wings, and limbs, a phenotype that gave name to the pathway [1]. The Hippo pathway regulates cell proliferation, differentiation, and spatial patterning governing organ size, tissue homeostasis, and regeneration, and is highly conserved from Drosophila to mammals [1,2].
The canonical Hippo signaling pathway is a key regulator of organ size and tissue remodeling [2]. The non-canonical Hippo signaling pathway, due to its diverse interplay with a variety of signaling cascades, i.e., TGF-β, Wnt, Hedgehog (HH), and Notch signaling pathways [3], has been associated with diversified mechanisms according to different microenvironments [4]: neurogenesis [5], neuronal development [6], neuronal dendritic field formation [7,8], and, more recently, neuroinflammation [9] and immunology [10]. In the central nervous system, the Hippo pathway has been associated with the response to neuroinflammation [11], dendrite development and organization [7], the balance between apoptosis and proliferation of the neural progenitor cell pool [12], glioma proliferation [13], Huntington’s disease [14], and Alzheimer’s disease [15].
Due to its role in both healthy and pathologic processes in the central nervous system and its crosstalk with other signaling pathways, it is unsurprising that the genes involved in the Hippo pathway have recently been associated with various psychiatric conditions [16,17,18,19]. Indeed, Liu and colleagues [18], identified positive regulation in the transcription of Hippo pathway genes in post-mortem prefrontal cortex of bipolar disorder (BD) patients as significantly enriched compared to healthy controls. Together with 30 hub genes, including YAP, the authors suggested that this pathway might have important implications in understanding the pathophysiology of BD, and could be a source of new targets for treatment. Further, the Hippo pathway genes were also reported as hypermethylated in a twin affected with BD compared with the non-affected twin [16]. Although the Hippo pathway was not differentially methylated in a second pair of twins, the authors proposed that the patient-specific differences might reflect the effects of antipsychotic medications, resulting in hyper/hypomethylation differences. In addition, different components of the Hippo pathway appear to be targeted by chlorpromazine, an antipsychotic used to treat schizophrenia (SZ), leading to apoptosis in cancer cells [20]. Valproic acid used to treat BD is reported to interact with the Hippo pathway through RASSF1A in myeloid leukemia, allowing YAP to associate with p73 and induce the expression of pro-apoptotic genes [21].
Therefore, this study aimed to evaluate the effects of commonly prescribed psychoactive drugs used in treating affective disorders (BD and SZ) on the expression of genes in the Hippo pathway. We expect these medications to downregulate the genes involved in the Hippo pathway, as upregulation of the Hippo pathway was previously observed in people with BD compared to healthy controls [18].

2. Results

2.1. GSEA

The list of genes involved in the Hippo pathway was extracted from the KEGG database, and the acute effects of the eight drugs on these genes was analyzed by GSEA. Five of the eight drugs, amisulpride, aripiprazole, clozapine, quetiapine, and risperidone, significantly downregulated genes in the Hippo pathway, as shown in Table 1.

2.2. Hippo Core Genes and Transcription Factors

Having ascertained that five of the psychoactive drugs significantly altered the expression of genes in the Hippo pathway, we further investigated the effects of these drugs on a smaller set of genes. This smaller set of genes included the core genes of the Hippo pathway and its transcription factors, which are the critical effectors of the pathway (Figure 1 A–E).
Amisulpride, aripiprazole, clozapine, and quetiapine significantly reduced the expression of the transcription factors involved in the Hippo pathway (p = 0.007, p = 0.025, p = 0.001, and p = 0.008, respectively). Risperidone and quetiapine downregulated the core genes of the Hippo pathway (p= 0.03 and p = 0.02, respectively), and amisulpride (p = 0.05) showed a tendency to downregulate the core genes of the Hippo pathway.

2.3. Interacting Pathways

The Hippo signaling pathway interacts extensively with other closely related signaling pathways, including the TGF-β, WNT, Notch, and Hedgehog signaling pathways. Therefore, the effects of these drugs were further investigated on these pathways (Table 2).
The Wnt signaling pathway was transcriptionally downregulated by amisulpride (p = 0.0018), aripiprazole (p = 4.80 × 10−6), clozapine (p = 0.0013), and risperidone (p = 0.02; Table 2). These four drugs significantly regulated several individual genes in the Wnt pathway. While quetiapine also positively or negatively affected the transcription of a number of genes in the pathway, the overall effect of quetiapine on the Wnt signaling pathway was not significant (Figure 2).
Overall, amisulpride (p = 0.0032), aripiprazole (p = 0.043), and clozapine (p = 0.0033) reduced the expression of genes in the notch signaling pathway. Again, quetiapine increased or decreased the expression of several genes in the pathway, but did not have a significant overall effect (Figure 3).
Expression of genes in the hedgehog signaling pathway was decreased overall by clozapine (p = 0.025), and tended to be reduced by aripiprazole (p = 0.07, Figure 4). Clozapine significantly reduced the expression of CCND1, CCND2, and GLI2 (Figure 4).
Although no overall significant effects were observed in the regulation of the TGF-β pathway, several genes were up- or downregulated by the different drugs, with a tendency to be downregulated by clozapine (p = 0.07) and risperidone (p = 0.06) (Figure 5).

2.4. CMap

The genes in these signaling pathways that were regulated by the five drugs in the same direction (n = 22 genes with evidence of mean log fold change compared with the vehicle of p < 0.1; Table S1) were submitted for CMap analysis, which identified 36 drugs with a positive CMap enrichment score of >0 and p < 0.05 (Table 3).

3. Discussion

Consistent with our hypothesis, five drugs commonly used to treat BD and schizophrenia (amisulpride, aripiprazole, clozapine, quetiapine, and risperidone) significantly downregulated the expression of Hippo signaling pathway genes, together with differential effects of each drug on various interacting pathways. These results complement reports of upregulation of these sets of genes in samples derived from patients with BD [18,19], possibly indicating a targeted effect of these drugs to revert Hippo-related immune activation and inflammation involved in the pathophysiology of affective disorders.

3.1. Aripiprazole and Clozapine

The atypical antipsychotics aripiprazole and clozapine modulate dopaminergic receptors, as well as a range of other targets [22]. Our results show that these medications also modulate the Hippo signaling pathway genes, that is, they contribute to the downregulation of NF2 and WWC1 genes, accompanied by the downregulation of the Wnt and Notch pathways.
NF2 plays an indispensable role in the recruitment of MST1/2 and LATS1/2 to the plasma membrane, which enables LATS1/2 phosphorylation and repression of YAP/TAZ and MOB1 [23,24,25]. Complete abrogation of NF2 activity results in an inability to suppress the activity of YAP/TAZ [26,27]. WWC1, WWC2, and WWC3 are another family that positively regulates the Hippo pathway via the activation of LATS1/2 [28,29]. Importantly, loss of WWC activity results in the nuclear translocation of YAP/TAZ, enabling their activation as transcription factors [28,29].
The downregulation of NF2 and WWC1 observed following treatment with aripiprazole and clozapine could lead to YAP/TAZ nuclear translocation and its non-canonical activities: inhibition of TGF-β signaling [30,31] and modulation of the activity of the Wnt and Notch pathways [32,33]. YAP/TAZ activation is also associated with reduced activity of NFκB and pro-inflammatory cytokine production. This appears to be mediated by the inhibition of proteins and enzymes involved in downstream signaling cascades following pattern-recognition receptors (PPRs) activation [34,35] (reviewed [36]).
In addition, clozapine also downregulated the Hh pathway, accompanied by significant downregulation of GLI2, a downstream effector of SHH. The Hh signaling pathway has been associated with maintaining the stem propriety in cells in the hippocampus and cerebellum [37,38]. Similar results showed the inhibition of the Hh pathway and downregulation of GLI2 following treatment with clozapine, haloperidol, and chlorpromazine in ShhL2, C3H10T1/2, and T98G cells [39]. The finding that drugs used to treat schizophrenia can modulate the Hh pathway raises the possibility that alterations in Hh signaling might contribute to the disease aetiology, as suggested by Boyd et al. in 2015 [40].

3.2. Amisulpride

Similar to aripiprazole and clozapine, amisulpride also significantly downregulated the Wnt and Notch signaling pathways. The overall downregulation exerted by amisulpride in the Hippo signaling pathway seems to be primarily driven by effects on the expression of the transcription factors, particularly TCFs and TEADS (Figure 1A). T-cell factor/lymphoid enhancer-binding factor (TCF/LEF) proteins (TCFs) are the main downstream effectors of Wnt signaling [41] and associate with β-catenin in the nucleus to activate transcription of Wnt signaling target genes. The upregulation of LATS1 following treatment with amisulpride could lead to YAP/TAZ sequestration to the cytoplasm, which binds to β-catenin differently to nuclear YAP/TAZ, preventing translocation to the nucleus and therefore inhibiting Wnt signaling [42]. TEA domain transcription factors (TEADs) exert multiple regulatory effects on signaling pathways other than the Hippo, and the activity of these signaling pathways influences the activity of TEADs. For example, upregulation of the Wnt pathway results in the activation of TEADs whose increased transcriptional activity inhibits Wnt signaling, thus engaging a negative feedback system [43,44]. TGFβ mediated signaling also increases levels and activity of TEADs, but in this instance, increased TEAD activity increases TGFβ signaling, forming a positive feedback loop [45,46]. Finally, increased activity of TEADs also acts as a negative regulator of Hippo signaling by increasing the levels and activity of LATS and NF2 [47,48] (reviewed [49]).

3.3. Quetiapine and Risperidone

Quetiapine and risperidone have different mechanisms of action compared to the medications above [22], which may correspond with their effects on the Hippo signaling pathway. Quetiapine presented a broad range of effects with significant downregulation of the core Hippo genes and the transcriptional factors of the Hippo pathway, complemented by a variety of significant but multidirectional (up- and downregulated) effects on the interacting pathways. Although the precise effects of quetiapine remain to be elucidated, we speculate that it could involve effects besides the NF2 effects described above, as NF2 activity also upregulates numerous pro-inflammatory signaling pathways, including PI3K-AKT, MAPK, and ERK [27,50].
The opposite was found for risperidone, with the GSEA analysis indicating a trend for downregulation of genes in the Hippo signaling pathway, despite none of the genes reaching statistical significance.

3.4. Summary

Downregulation of NF2 and WWC1 was observed following administration of aripiprazole, clozapine, and quetiapine. Likely consequences include reduced inflammatory signaling mediated by MST1/2 and NF2, and reduced MAPK and NFκB activity levels following upregulation of YAP/TAZ. Aripiprazole also downregulates T-cell factors, potentially compromising Wnt signaling [51].
Several authors have demonstrated that MST1/2 directly regulates many aspects of immune activation and the activity of inflammatory pathways [52,53]. Examples of pathways upregulated include MAPK (mitogen-activated protein kinase) and p53 [36]. MST1/2 also plays a major role in Toll-like receptor (TLR) signaling and subsequent activation of NFκB and pro-inflammatory cytokine production [54,55]. Similarly, YAP deletion in astrocytes induced JAK-STAT pathways, inducing reactive astrogliosis, microglial activation, and BBB dysfunction in mice [56].
When considered as a whole, the net effects of these changes would reduce pro-inflammatory signaling mediated by MAPK and NFκB. This is of interest as aripiprazole [57], quetiapine [58], and clozapine [59,60] are known to inhibit NFκB. The data produced in this study suggests that such inhibition may be achieved, at least in part, by effects on Hippo, Wnt, and TGFβ signaling (Figure 6).

3.5. Drug Repurposing

We used CMap to search for drugs that target the Hippo pathway genes similarly to the drugs we used to treat the NT2 cells. The CMap analysis identified 39 compounds with a p-value < 0.05 acting on the signaling pathway genes similarly to amisulpride, aripiprazole, clozapine, quetiapine, and risperidone (Table 3). Nine of these compounds have mechanisms associated with a reduction in NFκB signaling: ursolic acid [61], carbimazole [62], NS−398 [63], sodium phenylbutyrate [64], furazolidone [65], iloprost [66], ergocalciferol [67], clozapine [59], and triflupromazine [68].
For example, ursolic acid (UA) is a natural pentacyclic triterpenoid carboxylic acid present in various plants and is a recurrent component of our diet [69]. As part of traditional medicine, it is known for its antioxidant, anti-inflammatory, and anticancer properties [70]. Checker and colleagues [71] investigated the immunomodulatory effects of UA on T-cell activation following several stimuli, and showed that UA inhibits the activation of NFκB and other transcription factors, as well as MAP Kinases. The neuroprotective effects of UA have also been studied in depression, with effects being associated with dopamine 1 and 2 receptor activation [72]. Likewise, antioxidant effects by inducing antioxidant defenses were demonstrated in Alzheimer’s disease [73]. The possible beneficial effects of UA in neurodegenerative and psychiatric conditions were recently reviewed [74,75].
The identification of the antipsychotics, including clozapine, piperacetazine, and triflupromazine by this CMap analysis adds weight to our contention that this is a valuable methodology to identify drugs which act in a similar manner to the drugs we tested, and gives confidence that they represent potential targets for repurposing to treat psychotic and affective disorders.

4. Materials and Methods

4.1. Cell Culture

NT2 human teratocarcinoma cells (CVCL_0034, ATCC, Manassas, VI, USA) were cultured, maintained and differentiated as previously described [76]. Briefly, to generate an enriched culture of differentiated neuronal cells, NT2 cells were treated with retinoic acid (Sigma-Aldrich, Sydney, Australia) at 1 × 10−5 M for 28 days. Following retinoic acid treatment, cells were plated for experiments in 24-well plates at 2 × 105 cells/well and treated with mitotic inhibitors (1 µM cytosine and 10 µM uridine, Sigma-Aldrich) for 7 days.
Once enriched cultures of differentiated neuronal cells (NT2-N) were obtained, the cells were treated with drugs commonly prescribed in psychiatry (amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), or valproate (0.5 mM); Sigma-Aldrich) or the appropriate vehicle control (DMSO 0.2% or Milli-Q water 0.5%) for 24 h (n = 4–5 per group). The dosages chosen for the in vitro treatment were determined based on previous dose–response studies so that, when used in combination, no single drug dominated the overall effect on gene expression nor affected cell viability. Such doses were carried out throughout the following projects [77]. The experimental procedure used was carried out throughout several projects in our lab, with previous publications also showing differences in gene expression after 24 h treatment [76,78]. In addition, the use of psychotropic drugs in vitro has shown alterations on gene expression after 24 h, and as early as after 1 h treatment [79,80].

4.2. Gene Expression

Following the 24-h drug treatment, cells were harvested using Trizol, and total RNA was extracted using RNeasy® mini kits (Qiagen, Melbourne, Australia) and quantified by spectrophotometry (NanoDrop 1000 Thermo Fisher Scientific, Waltham, MA, USA). The quality of the extracted RNA was evaluated using an Agilent 2100 Bioanalyzer (Agilent Technologies, Melbourne, Australia). RNAseq libraries were prepared from 1 ug of total RNA using a TruSeq RNA samples Preparation kit (Illumina, Victoria, Australia). The libraries were sequenced using a HiSeq 2500 flow cell (50 bp single end reads; Illumina) according to the manufacturer’s instructions.

4.3. Genome-Wide Gene Expression Analysis

The raw data were obtained in fastq format, and processed using the Deakin Genomics Centre RNAseq alignment and expression quantification pipeline (https://github.com/m-richardson/RNASeq_pipe, accessed on 1 July 2017). In summary, this involves: Raw read quality filtering and adapter trimming (ILLUMINACLIP:2:30:10:4, SLIDINGWINDOW:5:20, AVGQUAL:20 MINLEN:36) with Trimmomatic v35 [81], and alignment to the reference genome using STAR v2.5 in 2-pass mode (Human genome version GRCh38) [82]. The expression was quantified at the gene level, and individual sample counts were collated into a m × n matrix for differential abundance testing. Normalization (TMM) and removal of low expressed gene were performed using edgeR [83] in R [84] following the edgeR manual (<1 cpm in n samples, where n is the number of samples in the smallest group for comparison). Differential gene expression analysis was assessed using edgeR in R, and the Benjamini–Hochberg [85] corrected p-values were calculated to account for multiple testing. Genes with p-values of <0.05 were considered to be differentially expressed.

4.4. Gene Set Enrichment Analysis (GSEA)

GSEA was deployed using the R package cluster Profiler [86] from Bioconductor [87], with gene lists pre-ranked based on the sign of log fold changes multiplied by the log10-transformed of p-values from the differential analysis. The Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used as a reference database, and only gene sets with sizes ranging from 3 to 800 genes inclusive were considered. The resulting tables had enrichment scores and p-values calculated from 10,000 permutations, with accompanying false discovery rate q-values adjusted for multiple testing.

4.5. Interacting Pathways

The list of genes belonging to the Wnt signaling pathway, Notch signaling pathway, Hedgehog signaling pathway, Transforming Growth Factor Beta (TGF-β) signaling pathway were obtained from KEGG, and then tested for overall transcriptional regulation by the drugs. The distribution of logFC data was checked for normality using Kolmogorov–Smirnov tests. Drug treatment groups were compared against their respective controls using independent samples t-tests for normally distributed data and Mann–Whitney U tests for data not normally distributed.

4.6. Connectivity Map (CMap)

Genes in the Hippo pathway that were significantly increased or decreased by 4 or more of the drugs were assigned a tag ID recognizable by CMap using Human Genome U133 Plus 2.0 Array on Affymetrix (https://www.affymetrix.com/site/mainPage.affx; Thermo Fisher Scientific, accessed on 1 November 2020). The IDs were collated in sets of “up” or “down” regulated genes and submitted to CMap. The similarities between the gene expression patterns induced by the compounds in the CMap database and those caused by the psychoactive drugs used in this project were reported as connectivity scores ranging from +1 (increased similarity) to −1 (inverse similarity).

5. Conclusions

To our knowledge, this is the first study to evaluate the effects of mood stabilizers and antipsychotics on the expression of genes involved in the Hippo pathway and its interacting pathways. Remarkably, the effects and routes described here were previously observed in oncology, due to the role of the Hippo signaling pathway in tumorigenesis. In this context, further research investigating the effects of these genes and pathways in psychiatry is necessary. We acknowledge some limitations of our study. All experiments were conducted in neuronal-like cells without the induction of any disease state model; therefore, underlying disease-specific pathophysiological processes might alter the drug effects. In addition, we tested a single dose of each drug and measured its acute effects, hence these findings do not capture chronic administration effects or drug-drug interaction during polypharmacy.
The identification of new pathways associated with psychiatric conditions that can be targeted by known pharmacological treatments can highlight an opportunity for the development of new treatment options for these debilitating conditions. This represents an opportunity to offset the lack of mechanistic understanding in BD and SZ, as well as other psychiatric conditions, and the curtailment in research and development by major pharmaceutical companies [88]. The use of differential gene expression and connectivity maps in this study identified a number of drugs with known effects on proposed pathological mechanisms associated with psychiatric disorders. Some of the other drugs identified could be further explored as potential therapeutic options for psychiatric disorders.

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/ijms22137164/s1.

Author Contributions

Conceptualization, K.W. and M.B.; methodology, B.P., C.C.B., B.S., O.M.D. and K.W.; formal analysis, T.T.T.T. and K.W.; investigation, B.P., C.C.B., B.S., S.K. and T.C.; resources, K.W.; data curation, M.F.R.; writing—original draft preparation, B.P.; writing—review and editing, B.P., B.S., S.K., T.C., C.C.B., Z.S.J.L., T.T.T.T., M.F.R., L.G., J.H.K., G.M., M.B., O.M.D. and K.W.; visualization: B.P., Z.S.J.L. and L.G.; and funding acquisition, K.W. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by National Health & Medical Research Council (NHMRC), Project Grant (GNT1078928).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data available from author upon reasonable request.

Acknowledgments

MB is supported by a NHMRC Senior Principal Research Fellowship (1156072). The authors also thank Metabolomics Australia (MA) at The University of Melbourne, a member of Bioplatforms Australia Pty Lts funded through the Australian Government National Collaborative Research Infrastructure Strategy (NCRIS).

Conflicts of Interest

The authors declare no conflict of interest related to this work.

References

  1. Ma, S.; Meng, Z.; Chen, R.; Guan, K.-L. The Hippo Pathway: Biology and Pathophysiology. Annu. Rev. Biochem. 2019, 88, 577–604. [Google Scholar] [CrossRef]
  2. Zhao, B.; Li, L.; Guan, K.-L. Hippo Signaling at a Glance. J. Cell Sci. 2010, 123, 4001–4006. [Google Scholar] [CrossRef]
  3. Fu, V.; Plouffe, S.W.; Guan, K.-L. The Hippo Pathway in Organ Development, Homeostasis, and Regeneration. Curr. Opin. cell Biol. 2017, 49, 99–107. [Google Scholar] [CrossRef]
  4. Hong, L.; Li, X.; Zhou, D.; Geng, J.; Chen, L. Role of Hippo Signaling in Regulating Immunity. Cell. Mol. Immunol. 2018, 15, 1003–1009. [Google Scholar] [CrossRef]
  5. Zhu, Y.; Wang, L.; Yin, F.; Yu, Y.; Wang, Y.; Shepard, M.J.; Zhuang, Z.; Qin, J. Probing Impaired Neurogenesis in Human Brain Organoids Exposed to Alcohol. Integr. Biol. 2017, 9, 968–978. [Google Scholar] [CrossRef]
  6. Emoto, K. The Growing Role of the Hippo–NDR Kinase Signalling in Neuronal Development and Disease. J. Biochem. 2011, 150, 133–141. [Google Scholar] [CrossRef] [PubMed]
  7. Rojek, K.O.; Krzemień, J.; Doleżyczek, H.; Boguszewski, P.M.; Kaczmarek, L.; Konopka, W.; Rylski, M.; Jaworski, J.; Holmgren, L.; Prószyński, T.J. Amot and Yap1 Regulate Neuronal Dendritic Tree Complexity and Locomotor Coordination in Mice. PLoS Biol. 2019, 17. [Google Scholar] [CrossRef] [PubMed]
  8. Emoto, K. Signaling Mechanisms That Coordinate the Development and Maintenance of Dendritic Fields. Curr. Opin. Neurobiol. 2012, 22, 805–811. [Google Scholar] [CrossRef] [PubMed]
  9. Cheng, J.; Wang, S.; Dong, Y.; Yuan, Z. The Role and Regulatory Mechanism of Hippo Signaling Components in the Neuronal System. Front. Immunol. 2020, 11. [Google Scholar] [CrossRef] [PubMed]
  10. Zhou, Y.; Huang, T.; Zhang, J.; Cheng, A.S.L.; Yu, J.; Kang, W.; To, K.F. Emerging Roles of Hippo Signaling in Inflammation and YAP-Driven Tumor Immunity. Cancer Lett. 2018, 426, 73–79. [Google Scholar] [CrossRef]
  11. Yang, Y.; Gong, Z.; Wang, Z. Yes-Associated Protein Reduces Neuroinflammation through Upregulation of Sirt3 and Inhibition of JNK Signaling Pathway. J. Recept. Signal Transduct. 2019, 39, 479–487. [Google Scholar] [CrossRef]
  12. Lavado, A.; Park, J.Y.; Paré, J.; Finkelstein, D.; Pan, H.; Xu, B.; Fan, Y.; Kumar, R.P.; Neale, G.; Kwak, Y.D.; et al. The Hippo Pathway Prevents YAP/TAZ–Driven Hypertranscription and Controls Neural Progenitor Number. Dev. Cell 2018, 47, 576–591.e8. [Google Scholar] [CrossRef]
  13. Rivas, S.; Antón, I.M.; Wandosell, F. WIP-YAP/TAZ as A New Pro-Oncogenic Pathway in Glioma. Cancers 2018, 10, 191. [Google Scholar] [CrossRef]
  14. Mueller, K.A.; Glajch, K.E.; Huizenga, M.N.; Wilson, R.A.; Granucci, E.J.; Dios, A.M.; Tousley, A.R.; Iuliano, M.; Weisman, E.; LaQuaglia, M.J.; et al. Hippo Signaling Pathway Dysregulation in Human Huntington’s Disease Brain and Neuronal Stem Cells. Sci. Rep. 2018, 8, 11355. [Google Scholar] [CrossRef] [PubMed]
  15. Tanaka, H.; Homma, H.; Fujita, K.; Kondo, K.; Yamada, S.; Jin, X.; Waragai, M.; Ohtomo, G.; Iwata, A.; Tagawa, K.; et al. YAP-Dependent Necrosis Occurs in Early Stages of Alzheimer’s Disease and Regulates Mouse Model Pathology. Nat. Commun. 2020, 11. [Google Scholar] [CrossRef]
  16. Melka, M.G.; Castellani, C.A.; O’Reilly, R.; Singh, S.M. Insights into the Origin of DNA Methylation Differences between Monozygotic Twins Discordant for Schizophrenia. J. Mol. Psychiatry 2015, 3, 7. [Google Scholar] [CrossRef]
  17. O’Connell, K.S.; McGregor, N.W.; Lochner, C.; Emsley, R.; Warnich, L. The Genetic Architecture of Schizophrenia, Bipolar Disorder, Obsessive-Compulsive Disorder and Autism Spectrum Disorder. Mol. Cell. Neurosci. 2018, 88, 300–307. [Google Scholar] [CrossRef]
  18. Liu, Y.; Gu, H.-Y.; Zhu, J.; Niu, Y.-M.; Zhang, C.; Guo, G.-L. Identification of Hub Genes and Key Pathways Associated With Bipolar Disorder Based on Weighted Gene Co-Expression Network Analysis. Front. Physiol. 2019, 10. [Google Scholar] [CrossRef] [PubMed]
  19. Bame, M.; McInnis, M.; O’Shea, K.S. MicroRNA Alterations in Induced Pluripotent Stem Cell-Derived Neurons from Bipolar Disorder Patients: Pathways Involved in Neuronal Differentiation, Axon Guidance and Plasticity. Stem Cells Dev. 2020. [Google Scholar] [CrossRef] [PubMed]
  20. Yang, C.-E.; Lee, W.-Y.; Cheng, H.-W.; Chung, C.-H.; Mi, F.-L.; Lin, C.-W. The Antipsychotic Chlorpromazine Suppresses YAP Signaling, Stemness Properties, and Drug Resistance in Breast Cancer Cells. Chem. Biol. Interact. 2019, 302, 28–35. [Google Scholar] [CrossRef]
  21. Davood, Z.-A.; Shamsi, S.; Ghaedi, H.; Sahand, R.-I.; Mojtaba, G.; Mahdi, T.; Reza, M.; Ebrahimi, M.J.; Miri-Moosavi, R.S.; Boosaliki, S.; et al. Valproic Acid May Exerts Its Cytotoxic Effect through Rassf1a Expression Induction in Acute Myeloid Leukemia. Tumour Biol. 2016, 37, 11001–11006. [Google Scholar] [CrossRef]
  22. Horacek, J.; Bubenikova-Valesova, V.; Kopecek, M.; Palenicek, T.; Dockery, C.; Mohr, P.; Höschl, C. Mechanism of Action of Atypical Antipsychotic Drugs and the Neurobiology of Schizophrenia. CNS Drugs 2006, 20, 389–409. [Google Scholar] [CrossRef] [PubMed]
  23. Harvey, K.F.; Zhang, X.; Thomas, D.M. The Hippo Pathway and Human Cancer. Nat. Rev. Cancer 2013, 13, 246–257. [Google Scholar] [CrossRef] [PubMed]
  24. Yin, F.; Yu, J.; Zheng, Y.; Chen, Q.; Zhang, N.; Pan, D. Spatial Organization of Hippo Signaling at the Plasma Membrane Mediated by the Tumor Suppressor Merlin/NF2. Cell 2013, 154, 1342–1355. [Google Scholar] [CrossRef] [PubMed]
  25. Cooper, J.; Giancotti, F.G. Molecular Insights into NF2/Merlin Tumor Suppressor Function. FEBS Lett. 2014, 588, 2743–2752. [Google Scholar] [CrossRef]
  26. Sourbier, C.; Liao, P.-J.; Ricketts, C.J.; Wei, D.; Yang, Y.; Baranes, S.M.; Gibbs, B.K.; Ohanjanian, L.; Spencer Krane, L.; Scroggins, B.T.; et al. Targeting Loss of the Hippo Signaling Pathway in NF2-Deficient Papillary Kidney Cancers. Oncotarget 2018, 9, 10723–10733. [Google Scholar] [CrossRef]
  27. Chen, Z.; Li, S.; Mo, J.; Hawley, E.; Wang, Y.; He, Y.; Brosseau, J.-P.; Shipman, T.; Clapp, D.W.; Carroll, T.J.; et al. Schwannoma Development Is Mediated by Hippo Pathway Dysregulation and Modified by RAS/MAPK Signaling. JCI Insight 2020, 5. [Google Scholar] [CrossRef] [PubMed]
  28. Höffken, V.; Hermann, A.; Pavenstädt, H.; Kremerskothen, J. WWC Proteins: Important Regulators of Hippo Signaling in Cancer. Cancers 2021, 13, 306. [Google Scholar] [CrossRef] [PubMed]
  29. Zhang, Y.; Yan, S.; Chen, J.; Gan, C.; Chen, D.; Li, Y.; Wen, J.; Kremerskothen, J.; Chen, S.; Zhang, J.; et al. WWC2 Is an Independent Prognostic Factor and Prevents Invasion via Hippo Signalling in Hepatocellular Carcinoma. J. Cell. Mol. Med. 2017, 21, 3718–3729. [Google Scholar] [CrossRef] [PubMed]
  30. Park, H.W.; Kim, Y.C.; Yu, B.; Moroishi, T.; Mo, J.-S.; Plouffe, S.W.; Meng, Z.; Lin, K.C.; Yu, F.-X.; Alexander, C.M.; et al. Alternative Wnt Signaling Activates YAP/TAZ. Cell 2015, 162, 780–794. [Google Scholar] [CrossRef] [PubMed]
  31. Qin, Z.; Xia, W.; Fisher, G.J.; Voorhees, J.J.; Quan, T. YAP/TAZ Regulates TGF-β/Smad3 Signaling by Induction of Smad7 via AP-1 in Human Skin Dermal Fibroblasts. Cell Commun. Signal. 2018, 16, 18. [Google Scholar] [CrossRef]
  32. Deng, F.; Peng, L.; Li, Z.; Tan, G.; Liang, E.; Chen, S.; Zhao, X.; Zhi, F. YAP Triggers the Wnt/β-Catenin Signalling Pathway and Promotes Enterocyte Self-Renewal, Regeneration and Tumorigenesis after DSS-Induced Injury. Cell Death Dis. 2018, 9, 1–16. [Google Scholar] [CrossRef]
  33. Ouyang, T.; Meng, W.; Li, M.; Hong, T.; Zhang, N. Recent Advances of the Hippo/YAP Signaling Pathway in Brain Development and Glioma. Cell Mol. Neurobiol. 2020, 40, 495–510. [Google Scholar] [CrossRef]
  34. Lv, Y.; Kim, K.; Sheng, Y.; Cho, J.; Qian, Z.; Zhao, Y.-Y.; Hu, G.; Pan, D.; Malik, A.B.; Hu, G. YAP Controls Endothelial Activation and Vascular Inflammation Through TRAF6. Circ. Res. 2018, 123, 43–56. [Google Scholar] [CrossRef]
  35. Deng, Y.; Lu, J.; Li, W.; Wu, A.; Zhang, X.; Tong, W.; Ho, K.K.; Qin, L.; Song, H.; Mak, K.K. Reciprocal Inhibition of YAP/TAZ and NF-ΚB Regulates Osteoarthritic Cartilage Degradation. Nat. Commun. 2018, 9, 4564. [Google Scholar] [CrossRef] [PubMed]
  36. Wang, S.; Zhou, L.; Ling, L.; Meng, X.; Chu, F.; Zhang, S.; Zhou, F. The Crosstalk Between Hippo-YAP Pathway and Innate Immunity. Front. Immunol. 2020, 11. [Google Scholar] [CrossRef]
  37. Palma, V.; Lim, D.A.; Dahmane, N.; Sánchez, P.; Brionne, T.C.; Herzberg, C.D.; Gitton, Y.; Carleton, A.; Alvarez-Buylla, A.; Ruiz i Altaba, A. Sonic Hedgehog Controls Stem Cell Behavior in the Postnatal and Adult Brain. Development 2005, 132, 335–344. [Google Scholar] [CrossRef]
  38. Galvin, K.E.; Ye, H.; Erstad, D.J.; Feddersen, R.; Wetmore, C. Gli1 Induces G2/M Arrest and Apoptosis in Hippocampal but Not Tumor-Derived Neural Stem Cells. Stem Cells 2008, 26, 1027–1036. [Google Scholar] [CrossRef] [PubMed]
  39. Lauth, M.; Rohnalter, V.; Bergström, A.; Kooshesh, M.; Svenningsson, P.; Toftgård, R. Antipsychotic Drugs Regulate Hedgehog Signaling by Modulation of 7-Dehydrocholesterol Reductase Levels. Mol. Pharmacol. 2010, 78, 486–496. [Google Scholar] [CrossRef] [PubMed]
  40. Boyd, P.J.; Cunliffe, V.T.; Roy, S.; Wood, J.D. Sonic Hedgehog Functions Upstream of Disrupted-in-Schizophrenia 1 (Disc1): Implications for Mental Illness. Biol. Open 2015, 4, 1336–1343. [Google Scholar] [CrossRef]
  41. Hrckulak, D.; Kolar, M.; Strnad, H.; Korinek, V. TCF/LEF Transcription Factors: An Update from the Internet Resources. Cancers 2016, 8, 70. [Google Scholar] [CrossRef] [PubMed]
  42. Imajo, M.; Miyatake, K.; Iimura, A.; Miyamoto, A.; Nishida, E. A Molecular Mechanism That Links Hippo Signalling to the Inhibition of Wnt/β-Catenin Signalling. EMBO J. 2012, 31, 1109–1122. [Google Scholar] [CrossRef]
  43. Lin, K.C.; Moroishi, T.; Meng, Z.; Jeong, H.-S.; Plouffe, S.W.; Sekido, Y.; Han, J.; Park, H.W.; Guan, K.-L. Regulation of Hippo Pathway Transcription Factor TEAD by P38 MAPK-Induced Cytoplasmic Translocation. Nat. Cell Biol. 2017, 19, 996–1002. [Google Scholar] [CrossRef]
  44. Lin, K.C.; Park, H.W.; Guan, K.-L. Regulation of the Hippo Pathway Transcription Factor TEAD. Trends Biochem. Sci. 2017, 42, 862–872. [Google Scholar] [CrossRef]
  45. Lee, D.-H.; Park, J.O.; Kim, T.-S.; Kim, S.-K.; Kim, T.-H.; Kim, M.-C.; Park, G.S.; Kim, J.-H.; Kuninaka, S.; Olson, E.N.; et al. LATS-YAP/TAZ Controls Lineage Specification by Regulating TGFβ Signaling and Hnf4α Expression during Liver Development. Nat. Commun. 2016, 7, 11961. [Google Scholar] [CrossRef]
  46. Varelas, X.; Samavarchi-Tehrani, P.; Narimatsu, M.; Weiss, A.; Cockburn, K.; Larsen, B.G.; Rossant, J.; Wrana, J.L. The Crumbs Complex Couples Cell Density Sensing to Hippo-Dependent Control of the TGF-β-SMAD Pathway. Dev. Cell 2010, 19, 831–844. [Google Scholar] [CrossRef] [PubMed]
  47. Dai, X.; Liu, H.; Shen, S.; Guo, X.; Yan, H.; Ji, X.; Li, L.; Huang, J.; Feng, X.-H.; Zhao, B. YAP Activates the Hippo Pathway in a Negative Feedback Loop. Cell Res. 2015, 25, 1175–1178. [Google Scholar] [CrossRef]
  48. Moroishi, T.; Park, H.W.; Qin, B.; Chen, Q.; Meng, Z.; Plouffe, S.W.; Taniguchi, K.; Yu, F.-X.; Karin, M.; Pan, D.; et al. A YAP/TAZ-Induced Feedback Mechanism Regulates Hippo Pathway Homeostasis. Genes Dev. 2015, 29, 1271–1284. [Google Scholar] [CrossRef] [PubMed]
  49. Huh, H.D.; Kim, D.H.; Jeong, H.-S.; Park, H.W. Regulation of TEAD Transcription Factors in Cancer Biology. Cells 2019, 8, 600. [Google Scholar] [CrossRef]
  50. Schroeder, R.D.; Angelo, L.S.; Kurzrock, R. NF2/Merlin in Hereditary Neurofibromatosis 2 versus Cancer: Biologic Mechanisms and Clinical Associations. Oncotarget 2013, 5, 67–77. [Google Scholar] [CrossRef] [PubMed]
  51. Shy, B.R.; Wu, C.-I.; Khramtsova, G.F.; Zhang, J.Y.; Olopade, O.I.; Goss, K.H.; Merrill, B.J. Regulation of Tcf7l1 DNA Binding and Protein Stability as Principal Mechanisms of Wnt/β-Catenin Signaling. Cell Rep. 2013, 4, 1–9. [Google Scholar] [CrossRef] [PubMed]
  52. Zhou, D.; Medoff, B.D.; Chen, L.; Li, L.; Zhang, X.; Praskova, M.; Liu, M.; Landry, A.; Blumberg, R.S.; Boussiotis, V.A.; et al. The Nore1B/Mst1 Complex Restrains Antigen Receptor-Induced Proliferation of Naïve T Cells. Proc. Natl. Acad. Sci. USA 2008, 105, 20321–20326. [Google Scholar] [CrossRef]
  53. Mou, F.; Praskova, M.; Xia, F.; Van Buren, D.; Hock, H.; Avruch, J.; Zhou, D. The Mst1 and Mst2 Kinases Control Activation of Rho Family GTPases and Thymic Egress of Mature Thymocytes. J. Exp. Med. 2012, 209, 741–759. [Google Scholar] [CrossRef] [PubMed]
  54. Geng, J.; Sun, X.; Wang, P.; Zhang, S.; Wang, X.; Wu, H.; Hong, L.; Xie, C.; Li, X.; Zhao, H.; et al. Kinases Mst1 and Mst2 Positively Regulate Phagocytic Induction of Reactive Oxygen Species and Bactericidal Activity. Nat. Immunol. 2015, 16, 1142–1152. [Google Scholar] [CrossRef] [PubMed]
  55. Boro, M.; Singh, V.; Balaji, K.N. Mycobacterium Tuberculosis -Triggered Hippo Pathway Orchestrates CXCL1/2 Expression to Modulate Host Immune Responses. Sci. Rep. 2016, 6, 37695. [Google Scholar] [CrossRef] [PubMed]
  56. Huang, Z.; Wang, Y.; Hu, G.; Zhou, J.; Mei, L.; Xiong, W.-C. YAP Is a Critical Inducer of SOCS3, Preventing Reactive Astrogliosis. Cereb. Cortex 2016, 26, 2299–2310. [Google Scholar] [CrossRef] [PubMed]
  57. Khalilzadeh, M.; Hassanzadeh, F.; Aghamiri, H.; Dehpour, A.R.; Shafaroodi, H. Aripiprazole Prevents from Development of Vincristine-Induced Neuropathic Nociception by Limiting Neural NOS Overexpression and NF-KB Hyperactivation. Cancer Chemothe. Pharm. 2020, 86, 393–404. [Google Scholar] [CrossRef]
  58. Wang, H.; Liu, S.; Tian, Y.; Wu, X.; He, Y.; Li, C.; Namaka, M.; Kong, J.; Li, H.; Xiao, L. Quetiapine Inhibits Microglial Activation by Neutralizing Abnormal STIM1-Mediated Intercellular Calcium Homeostasis and Promotes Myelin Repair in a Cuprizone-Induced Mouse Model of Demyelination. Front. Cell. Neurosci. 2015, 9. [Google Scholar] [CrossRef]
  59. Jeon, S.; Kim, S.H.; Shin, S.Y.; Lee, Y.H. Clozapine Reduces Toll-like Receptor 4/NF-ΚB-Mediated Inflammatory Responses through Inhibition of Calcium/Calmodulin-Dependent Akt Activation in Microglia. Prog. Neuro Psychopharmacol. Biol. Psychiatry 2018, 81, 477–487. [Google Scholar] [CrossRef]
  60. Troib, A.; Azab, A.N. Effects of Psychotropic Drugs on Nuclear Factor Kappa B. Eur. Rev. Med. Pharmacol. Sci. 2015, 19, 1198–1208. [Google Scholar]
  61. Shishodia, S.; Majumdar, S.; Banerjee, S.; Aggarwal, B.B. Ursolic Acid Inhibits Nuclear Factor-KappaB Activation Induced by Carcinogenic Agents through Suppression of IkappaBalpha Kinase and P65 Phosphorylation: Correlation with down-Regulation of Cyclooxygenase 2, Matrix Metalloproteinase 9, and Cyclin D1. Cancer Res. 2003, 63, 4375–4383. [Google Scholar] [PubMed]
  62. Humar, M.; Dohrmann, H.; Stein, P.; Andriopoulos, N.; Goebel, U.; Roesslein, M.; Schmidt, R.; Schwer, C.I.; Loop, T.; Geiger, K.K.; et al. Thionamides Inhibit the Transcription Factor Nuclear Factor-KappaB by Suppression of Rac1 and Inhibitor of KappaB Kinase Alpha. J. Pharmacol. Exp. Ther. 2008, 324, 1037–1044. [Google Scholar] [CrossRef] [PubMed]
  63. Mack Strong, V.E.; Mackrell, P.J.; Concannon, E.M.; Mestre, J.R.; Smyth, G.P.; Schaefer, P.A.; Stapleton, P.P.; Daly, J.M. NS-398 Treatment after Trauma Modifies NF-KappaB Activation and Improves Survival. J. Surg. Res. 2001, 98, 40–46. [Google Scholar] [CrossRef]
  64. Roy, A.; Ghosh, A.; Jana, A.; Liu, X.; Brahmachari, S.; Gendelman, H.E.; Pahan, K. Sodium Phenylbutyrate Controls Neuroinflammatory and Antioxidant Activities and Protects Dopaminergic Neurons in Mouse Models of Parkinson’s Disease. PLoS ONE 2012, 7, e38113. [Google Scholar] [CrossRef]
  65. Yu, J.-G.; Ji, C.-H.; Shi, M.-H. The Anti-Infection Drug Furazolidone Inhibits NF-ΚB Signaling and Induces Cell Apoptosis in Small Cell Lung Cancer. Kaohsiung J. Med. Sci. 2020, 36, 998–1003. [Google Scholar] [CrossRef]
  66. Birukova, A.A.; Wu, T.; Tian, Y.; Meliton, A.; Sarich, N.; Tian, X.; Leff, A.; Birukov, K.G. Iloprost Improves Endothelial Barrier Function in Lipopolysaccharide-Induced Lung Injury. Eur. Respir. J. 2013, 41, 165–176. [Google Scholar] [CrossRef] [PubMed]
  67. Cohen-Lahav, M.; Shany, S.; Tobvin, D.; Chaimovitz, C.; Douvdevani, A. Vitamin D Decreases NFkappaB Activity by Increasing IkappaBalpha Levels. Nephrol. Dial. Transpl. 2006, 21, 889–897. [Google Scholar] [CrossRef] [PubMed]
  68. Feng, Z.; Xia, Y.; Gao, T.; Xu, F.; Lei, Q.; Peng, C.; Yang, Y.; Xue, Q.; Hu, X.; Wang, Q.; et al. The Antipsychotic Agent Trifluoperazine Hydrochloride Suppresses Triple-Negative Breast Cancer Tumor Growth and Brain Metastasis by Inducing G0/G1 Arrest and Apoptosis. Cell Death Dis. 2018, 9, 1–15. [Google Scholar] [CrossRef] [PubMed]
  69. Moreau, R.A.; Whitaker, B.D.; Hicks, K.B. Phytosterols, Phytostanols, and Their Conjugates in Foods: Structural Diversity, Quantitative Analysis, and Health-Promoting Uses. Prog. Lipid Res. 2002, 41, 457–500. [Google Scholar] [CrossRef]
  70. Ikeda, Y.; Murakami, A.; Ohigashi, H. Ursolic Acid: An Anti- and pro-Inflammatory Triterpenoid. Mol. Nutr. Food Res. 2008, 52, 26–42. [Google Scholar] [CrossRef]
  71. Checker, R.; Sandur, S.K.; Sharma, D.; Patwardhan, R.S.; Jayakumar, S.; Kohli, V.; Sethi, G.; Aggarwal, B.B.; Sainis, K.B. Potent Anti-Inflammatory Activity of Ursolic Acid, a Triterpenoid Antioxidant, Is Mediated through Suppression of NF-ΚB, AP-1 and NF-AT. PLoS ONE 2012, 7, e31318. [Google Scholar] [CrossRef] [PubMed]
  72. Machado, D.G.; Neis, V.B.; Balen, G.O.; Colla, A.; Cunha, M.P.; Dalmarco, J.B.; Pizzolatti, M.G.; Prediger, R.D.; Rodrigues, A.L.S. Antidepressant-like Effect of Ursolic Acid Isolated from Rosmarinus officinalis L. in Mice: Evidence for the Involvement of the Dopaminergic System. Pharmacol. Biochem. Behav. 2012, 103, 204–211. [Google Scholar] [CrossRef]
  73. Habtemariam, S. Iridoids and Other Monoterpenes in the Alzheimer’s Brain: Recent Development and Future Prospects. Molecules 2018, 23, 117. [Google Scholar] [CrossRef]
  74. Ramos-Hryb, A.B.; Pazini, F.L.; Kaster, M.P.; Rodrigues, A.L.S. Therapeutic Potential of Ursolic Acid to Manage Neurodegenerative and Psychiatric Diseases. CNS Drugs 2017, 31, 1029–1041. [Google Scholar] [CrossRef]
  75. Gudoityte, E.; Arandarcikaite, O.; Mazeikiene, I.; Bendokas, V.; Liobikas, J. Ursolic and Oleanolic Acids: Plant Metabolites with Neuroprotective Potential. Int. J. Mol. Sci. 2021, 22, 4599. [Google Scholar] [CrossRef]
  76. Bortolasci, C.C.; Spolding, B.; Kidnapillai, S.; Richardson, M.F.; Vasilijevic, N.; Martin, S.D.; Gray, L.J.; McGee, S.L.; Berk, M.; Walder, K. Effects of Psychoactive Drugs on Cellular Bioenergetic Pathways. World J. Biol. Psychiatry Off. J. World Fed. Soc. Biol. Psychiatry 2020, 1–15. [Google Scholar] [CrossRef]
  77. Kidnapillai, S.; Bortolasci, C.C.; Udawela, M.; Panizzutti, B.; Spolding, B.; Connor, T.; Sanigorski, A.; Dean, O.M.; Crowley, T.; Jamain, S.; et al. The Use of a Gene Expression Signature and Connectivity Map to Repurpose Drugs for Bipolar Disorder. World J. Biol. Psychiatry 2018, 1–9. [Google Scholar] [CrossRef] [PubMed]
  78. Bortolasci, C.C.; Spolding, B.; Callaly, E.; Martin, S.; Panizzutti, B.; Kidnapillai, S.; Connor, T.; Hasebe, K.; Mohebbi, M.; Dean, O.M.; et al. Mechanisms Underpinning the Polypharmacy Effects of Medications in Psychiatry. Int. J. Neuropsychopharmacol. 2018, 21, 582–591. [Google Scholar] [CrossRef]
  79. Melbourne, J.K.; Pang, Y.; Park, M.R.; Sudhalkar, N.; Rosen, C.; Sharma, R.P. Treatment with the Antipsychotic Risperidone Is Associated with Increased M1-like JAK-STAT1 Signature Gene Expression in PBMCs from Participants with Psychosis and THP-1 Monocytes and Macrophages. Int. Immunopharmacol. 2020, 79, 106093. [Google Scholar] [CrossRef] [PubMed]
  80. Meng, Z.; Gwag, T.; Sui, Y.; Park, S.-H.; Zhou, X.; Zhou, C. The Atypical Antipsychotic Quetiapine Induces Hyperlipidemia by Activating Intestinal PXR Signaling. JCI Insight 2019, 4, e125657. [Google Scholar] [CrossRef]
  81. Bolger, A.M.; Lohse, M.; Usadel, B. Trimmomatic: A Flexible Trimmer for Illumina Sequence Data. Bioinformatics 2014, 30, 2114–2120. [Google Scholar] [CrossRef] [PubMed]
  82. STAR: Ultrafast Universal RNA-Seq Aligner Bioinformatics Oxford Academic. Available online: https://Academic.Oup.com/Bioinformatics/Article/29/1/15/272537 (accessed on 2 June 2021).
  83. Robinson, M.D.; McCarthy, D.J.; Smyth, G.K. EdgeR: A Bioconductor Package for Differential Expression Analysis of Digital Gene Expression Data. Bioinformatics 2010, 26, 139–140. [Google Scholar] [CrossRef]
  84. R: A Language and Environment for Statistical Computing. Available online: https://www.gbif.org/tool/81287/R-A-Language-and-Environment-for-Statistical-Computing (accessed on 2 June 2021).
  85. Benjamini, Y.; Hochberg, Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. J. R. Stat. Soc. Ser. B 1995, 57, 289–300. [Google Scholar] [CrossRef]
  86. Yu, G.; Wang, L.-G.; Han, Y.; He, Q.-Y. ClusterProfiler: An R Package for Comparing Biological Themes Among Gene Clusters. OMICS A J. Integr. Biol. 2012, 16, 284–287. [Google Scholar] [CrossRef]
  87. Subramanian, A.; Tamayo, P.; Mootha, V.K.; Mukherjee, S.; Ebert, B.L.; Gillette, M.A.; Paulovich, A.; Pomeroy, S.L.; Golub, T.R.; Lander, E.S.; et al. Gene Set Enrichment Analysis: A Knowledge-Based Approach for Interpreting Genome-Wide Expression Profiles. Proc. Natl. Acad. Sci. USA 2005, 102, 15545–15550. [Google Scholar] [CrossRef] [PubMed]
  88. Kaiser, T.; Feng, G. Modeling Psychiatric Disorders for Developing Effective Treatments. Nat. Med. 2015, 21, 979–988. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Effects of five drugs in the core genes and transcriptional factors of the Hippo pathway. (A) Amisulpride. (B) Aripiprazole. (C) Clozapine. (D) Quetiapine. (E) Risperidone * p < 0.05, ** p < 0.005, and *** p < 0.001.
Figure 1. Effects of five drugs in the core genes and transcriptional factors of the Hippo pathway. (A) Amisulpride. (B) Aripiprazole. (C) Clozapine. (D) Quetiapine. (E) Risperidone * p < 0.05, ** p < 0.005, and *** p < 0.001.
Ijms 22 07164 g001aIjms 22 07164 g001b
Figure 2. Wnt signaling pathway genes regulated by psychotropic drug treatment in NT2-N cells expressed as log fold change relative to vehicle-treated cells. * p < 0.05, ** p < 0.005, and *** p < 0.001.
Figure 2. Wnt signaling pathway genes regulated by psychotropic drug treatment in NT2-N cells expressed as log fold change relative to vehicle-treated cells. * p < 0.05, ** p < 0.005, and *** p < 0.001.
Ijms 22 07164 g002
Figure 3. Notch signaling pathway genes regulated by psychotropic drug treatment in NT2-N cells expressed as log fold change relative to vehicle-treated cells. * p < 0.05, ** p < 0.005, and *** p < 0.001.
Figure 3. Notch signaling pathway genes regulated by psychotropic drug treatment in NT2-N cells expressed as log fold change relative to vehicle-treated cells. * p < 0.05, ** p < 0.005, and *** p < 0.001.
Ijms 22 07164 g003
Figure 4. Hedgehog signaling pathway genes regulated by psychotropic drug treatment in NT2-N cells expressed as log fold change relative to vehicle-treated cells. * p < 0.05, ** p < 0.005, and *** p < 0.001.
Figure 4. Hedgehog signaling pathway genes regulated by psychotropic drug treatment in NT2-N cells expressed as log fold change relative to vehicle-treated cells. * p < 0.05, ** p < 0.005, and *** p < 0.001.
Ijms 22 07164 g004
Figure 5. TGFβ signaling pathway genes regulated by psychotropic drug treatment in NT2-N cells expressed as log fold change relative to vehicle-treated cells. * p < 0.05, ** p < 0.005, and *** p < 0.001.
Figure 5. TGFβ signaling pathway genes regulated by psychotropic drug treatment in NT2-N cells expressed as log fold change relative to vehicle-treated cells. * p < 0.05, ** p < 0.005, and *** p < 0.001.
Ijms 22 07164 g005
Figure 6. Hippo signaling at a glance: effects of amisulpride, aripiprazole, clozapine, quetiapine, and risperidone. Legend: Ami = amisulpride; Ari = aripiprazole; Clo = clozapine; Que = quetiapine; Ris = risperidone; red arrows = inhibition; blue arrows = activation; dotted arrows = modulation; and black arrows = drugs action. In neuronal-like NT2 cells, inhibition of Hippo pathway reduces the production of pro-inflammatory cytokines through the crosstalk with TRL, MAPK, TGF-β, Wnt, and Notch signaling pathways. Aripiprazole, clozapine, and quetiapine downregulate NF2, leading to activation and nuclear translocation of YAP/TAZ which results in a reduction in NFκB and TGF-β signaling. NF2 also closely interacts with Hedgehog, TGF-β, Wnt, and Notch pathways. Modulation of MST1/2 expression also results in reduced pro-inflammatory signaling through Toll-like receptor (TRL) and MAPK signaling. Amisulpride, aripiprazole, clozapine, and risperidone downregulate Wnt signaling interfering with NFκB and pro-inflammatory cytokine production. Created with BioRender.com.
Figure 6. Hippo signaling at a glance: effects of amisulpride, aripiprazole, clozapine, quetiapine, and risperidone. Legend: Ami = amisulpride; Ari = aripiprazole; Clo = clozapine; Que = quetiapine; Ris = risperidone; red arrows = inhibition; blue arrows = activation; dotted arrows = modulation; and black arrows = drugs action. In neuronal-like NT2 cells, inhibition of Hippo pathway reduces the production of pro-inflammatory cytokines through the crosstalk with TRL, MAPK, TGF-β, Wnt, and Notch signaling pathways. Aripiprazole, clozapine, and quetiapine downregulate NF2, leading to activation and nuclear translocation of YAP/TAZ which results in a reduction in NFκB and TGF-β signaling. NF2 also closely interacts with Hedgehog, TGF-β, Wnt, and Notch pathways. Modulation of MST1/2 expression also results in reduced pro-inflammatory signaling through Toll-like receptor (TRL) and MAPK signaling. Amisulpride, aripiprazole, clozapine, and risperidone downregulate Wnt signaling interfering with NFκB and pro-inflammatory cytokine production. Created with BioRender.com.
Ijms 22 07164 g006
Table 1. Effects of psychoactive drugs on KEGG Hippo pathway gene expression.
Table 1. Effects of psychoactive drugs on KEGG Hippo pathway gene expression.
DrugESNESp-Valueq-Value
Clozapine−0.61−2.090.000130.0012
Aripiprazole−0.54−2.040.000150.0044
Risperidone−0.49−1.920.000240.0049
Quetiapine−0.60−1.790.000270.0052
Amisulpride−0.45−1.610.000850.016
Lithium−0.40−1.320.0480.21
Lamotrigine−0.29−1.150.140.35
Valproate0.310.890.670.66
Medications listed based on the p-value, lowest to highest. Abbreviations: ES = enrichment score; NES = normalized enrichment score.
Table 2. The effects of the drugs on genes involved in interacting pathways.
Table 2. The effects of the drugs on genes involved in interacting pathways.
WntNotchHedgehogTGF-β
LogFCp-ValueLogFCp-ValueLogFCp-ValueLogFCp-Value
MeanSEMMeanSEMMeanSEMMeanSEM
Amisulpride−0.130.040.0018−0.080.030.0032−0.030.020.18−0.080.050.19
Aripiprazole−0.210.044.80 × 10−6−0.070.030.043−0.040.020.07−0.050.10.66
Clozapine−0.110.030.0013−0.080.030.0033−0.050.020.025−0.210.080.07
Quetiapine−0.020.050.640.020.050.63−0.040.030.26−0.270.150.15
Risperidone−0.060.020.02−0.010.020.7200.010.67−0.050.020.06
Abbreviations: LogFC= logarithmic fold change; SEM = standard error of the mean.
Table 3. Compounds that affect the expression of the gene expression signature genes similar to the five drugs that affected the Hippo pathway.
Table 3. Compounds that affect the expression of the gene expression signature genes similar to the five drugs that affected the Hippo pathway.
RankCMap NameEnrichmentp-ValueClass
1Ursolic acid0.910.00008Triterpenoid
2Levothyroxine sodium0.890.00014Thyroid hormones
3Ajmaline0.940.00022Antiarrhythmic agent
457078850.870.00044Unknown
6Carbimazole0.900.00182Imidazole–thyroid function
70297417–0002b0.880.00324Unknown
9Ns-3980.870.00463COX-2 inhibitor (anti-inflammatory)
10Cefapirin0.780.00473Antibiotic
11Estrone0.770.00539Estrogen steroid
12Strophanthidin0.770.00561Cardiac glycoside
17Picotamide0.680.00937Platelet aggregation inhibitor
20Maprotiline0.720.0117Tetracyclic antidepressant
22Monastrol0.530.01256Antimitotic agent
24Sr-95639a (Aminopyridazine)0.720.01331Muscarinic agonist
28Benzethonium chloride0.780.02097Antiseptics and Disinfectants
30Ciprofibrate0.680.0228Fibrate (lipid-lowering agent)
3152552290.900.02286Unknown
32Methazolamide0.680.02316Carbonic anhydrase inhibitors
33Bumetanide0.680.02379Diuretic
37Sodium phenylbutyrate0.520.02663Urea cycle disorder treatment agents
38Tenoxicam0.670.02795NSAID (Nonsteroidal anti-inflammatory drug)
40Ah-238480.760.0291Prostanoid EP4 antagonist
41Furazolidone0.660.03058Oxazolidine–antibiotic agent
42Iloprost0.750.03201Vasodilator
43Minoxidil0.600.03344Vasodilator
46Hyoscyamine0.590.03475Anticholinergic/antispasmodic
45Prestwick-642 (Epicatechin)0.650.03475Catechin–antioxidant flavonoid
48Dihydrostreptomycin0.590.03529Antibiotic
49Nisoxetine0.650.03539Antidepressant -SNRI
50Ergocalciferol0.650.03589Vitamin D analogue
52Ceforanide0.650.03804Antibiotic
55Pheniramine0.580.04175Antihistamine
56Ifenprodil0.640.04245NMDA receptor antagonist
57Pha-007453600.460.04312Unknown
58Clozapine0.320.04422Atypical antipsychotic
60Diphemanil methylsulfate0.570.04552Muscarinic antagonist
63Piperacetazine0.630.04729Antipsychotic prodrug
66Trifluoperazine0.630.04882Phenothiazine antipsychotic
68Lidoflazine0.710.04974Vasodilator
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Back to TopTop