Network analysis of gene expression in peripheral blood identifies mTOR and NF-κB pathways involved in antipsychotic-induced extrapyramidal symptoms

Convergent lines of evidence supporting involvement of NFKB1 in schizophrenia

OBJECTIVES

NFKB1 was associated with treatment-refractory schizophrenia (SZ) and response to antipsychotics; however, the underlying mechanisms through which NFKB1 confers its risk for SZ are largely unknown. We aimed to investigate the potential role of NFKB1 in SZ.

METHODS

In the present study, we investigated the association of the risk SNP rs230529 of NFKB1 with gray matter density and with NFKB1 mRNA levels in various human brain regions. The spatiotemporal expression pattern of NFKB1 in human brains was explored. We constructed a miRNA-NFKB1-target gene regulatory network and analyzed its druggability through targeting NFKB1 for SZ treatment.

RESULTS

NFKB1 showed the highest expression levels in the cerebellum, in which these levels were stratified by genotypes of rs230529. Interestingly, the allelic state of rs230529 was significantly associated with regional gray matter density in multiple brain regions (including the cerebellum), which also differed between patients with schizophrenia and controls. Furthermore, regulatory targets of NFKB1 were enriched among SZ susceptibility genes. A substantial proportion of NFKB1 target genes were subject to combinatorial regulation by NFKB1 and miRNAs, constituting a hybrid NFKB1-miRNA-gene regulatory network. Some components of this network showed expression changes relevant to both the disease and the treatment. Finally, we detected the dynamic changes of NFKB1-miR-155-5p-GSK3B and NFKB1-miR-155-5p/let-7a-5p-IL6 networks in course of the treatment of SZ.

CONCLUSION

Taken together, our findings support the involvement of NFKB1-mediated dysregulation in the development of SZ.

Transcriptional biomarkers of response to pharmacological treatments in severe mental disorders: A systematic review

Variation in the expression level and activity of genes involved in drug disposition and action in tissues of pharmacological importance have been increasingly investigated in patients treated with psychotropic drugs. Findings are promising, but reliable predictive biomarkers of response have yet to be identified. Here we conducted a PRISMA-compliant systematic search of PubMed, Scopus and PsycInfo up to 12 September 2020 for studies investigating RNA expression levels in cells or biofluids from patients with major depressive disorder, schizophrenia or bipolar disorder characterized for response to psychotropic drugs (antidepressants, antipsychotics or mood stabilizers) or adverse effects. Among 5497 retrieved studies, 123 (63 on antidepressants, 33 on antipsychotics and 27 on mood stabilizers) met inclusion criteria. Studies were either focused on mRNAs (n = 96), microRNAs (n = 19) or long non-coding RNAs (n = 1), with only a minority investigating both mRNAs and microRNAs levels (n = 7). The most replicated results include genes playing a role in inflammation (antidepressants), neurotransmission (antidepressants and antipsychotics) or mitochondrial function (mood stabilizers). Compared to those investigating response to antidepressants, studies focused on antipsychotics or mood stabilizers more often showed lower sample size and lacked replication. Strengths and limitations of available studies are presented and discussed in light of the specific designs, methodology and clinical characterization of included patients for transcriptomic compared to DNA-based studies. Finally, future directions of transcriptomics of psychopharmacological interventions in psychiatric disorders are discussed.

A comprehensive analysis of prefoldins and their implication in cancer

Prefoldins (PFDNs) are evolutionary conserved co-chaperones, initially discovered in archaea but universally present in eukaryotes. PFDNs are prevalently organized into hetero-hexameric complexes. Although they have been overlooked since their discovery and their functions remain elusive, several reports indicate they act as co-chaperones escorting misfolded or non-native proteins to group II chaperonins. Unlike the eukaryotic PFDNs which interact with cytoskeletal components, the archaeal PFDNs can bind and stabilize a wide range of substrates, possibly due to their great structural diversity. The discovery of the unconventional RPB5 interactor (URI) PFDN-like complex (UPC) suggests that PFDNs have versatile functions and are required for different cellular processes, including an important role in cancer. Here, we summarize their functions across different species. Moreover, a comprehensive analysis of PFDNs genomic alterations across cancer types by using large-scale cancer genomic data indicates that PFDNs are a new class of non-mutated proteins significantly overexpressed in some cancer types.

Alteration in the mRNA expression profile of the autophagy-related mTOR pathway in schizophrenia patients treated with olanzapine

BACKGROUND

The mammalian target of rapamycin protein (mTOR) signaling pathway is involved in the pathogenesis of schizophrenia and the mechanism of extrapyramidal adverse reactions to antipsychotic drugs, which might be mediated by an mTOR-dependent autophagy impairment. This study aimed to examine the expression of mTOR pathway genes in patients with schizophrenia treated with olanzapine, which is considered an mTOR inhibitor and autophagy inducer.

METHODS

Thirty-two patients with acute schizophrenia who had been treated with olanzapine for four weeks (average dose 14.24 ± 4.35 mg/d) and 32 healthy volunteers were recruited. Before and after olanzapine treatment, the Positive and Negative Syndrome Scale (PANSS) was used to evaluate the symptoms of patients with schizophrenia, and the mRNA expression levels of mTOR pathway-related genes, including MTOR, RICTOR, RAPTOR, and DEPTOR, were detected in fasting venous blood samples from all subjects using real-time quantitative PCR.

RESULTS

The MTOR and RICTOR mRNA expression levels in patients with acute schizophrenia were significantly decreased compared with those of healthy controls and further significantly decreased after four weeks of olanzapine treatment. The DEPTOR mRNA expression levels in patients with acute schizophrenia were not significantly different from those of healthy controls but were significantly increased after treatment. The expression levels of the RAPTOR mRNA were not significantly different among the three groups. The pairwise correlations of MTOR, DEPTOR, RAPTOR, and RICTOR mRNA expression levels in patients with acute schizophrenia and healthy controls were significant. After olanzapine treatment, the correlations between the expression levels of the DEPTOR and MTOR mRNAs and between the DEPTOR and RICTOR mRNAs disappeared.

CONCLUSIONS

Abnormalities in the mTOR pathway, especially DEPTOR and mTORC2, might play important roles in the autophagy mechanism underlying the pathophysiology of schizophrenia and effects of olanzapine treatment.

Recognition and Management of Antipsychotic-Induced Parkinsonism in Older Adults: A Narrative Review

Background: Parkinsonism is a common side-effect of antipsychotic drugs especially in older adults, who also present with a higher frequency of neurodegenerative disorders like Idiopathic Parkinson’s disease (IPD). Distinguishing between antipsychotic-induced parkinsonism (AIP) and IPD is challenging due to clinical similarities. Up to 20% of older adults may suffer from persisting parkinsonism months after discontinuation of antipsychotics, suggesting underlying neurodegeneration. A review of the literature on AIP in older adults is presented, focusing on epidemiology, clinical aspects, and management. Methods: A literature search was undertaken on EMBASE, MEDLINE and PsycINFO, for articles on parkinsonism induced by antipsychotic drugs or other dopamine 2 receptor antagonists in subjects aged 65 or older. Results: AIP in older adults is the second most common cause of parkinsonism after IPD. Older age, female gender, exposure to high-potency first generation antipsychotics, and antipsychotic dosage are the main risk factors. The clinical presentation of AIP resembles that of IPD, but is more symmetrical, affects upper limbs more, and tends to have associated motor phenomena such as orofacial dyskinesias and akathisia. Presence of olfactory dysfunction in AIP suggests neurodegeneration. Imaging of striatal dopamine transporters is widely used in IPD diagnosis and could help to distinguish it from AIP. There is little evidence base for recommending pharmacological interventions for AIP, the best options being dose-reduction/withdrawal, or switching to a second-generation drug. Conclusions: AIP is a common occurrence in older adults and it is possible to differentiate it from IPD. Further research is needed into its pathophysiology and on its treatment.

Pharmacogenetics of Antipsychotic Drug Treatment: Update and Clinical Implications

Numerous genetic variants have been shown to be associated with antipsychotic response and adverse effects of schizophrenia treatment. However, the clinical application of these findings is limited. The aim of this narrative review is to summarize the most recent publications and recommendations related to the genetics of antipsychotic treatment and shed light on the clinical utility of pharmacogenetics/pharmacogenomics (PGx). We reviewed the literature on PGx studies with antipsychotic drugs (i.e., antipsychotic response and adverse effects) and commonly used commercial PGx tools for clinical practice. Publications and reviews were included with emphasis on articles published between January 2015 and April 2018. We found 44 studies focusing on antipsychotic response and 45 studies on adverse effects (e.g., antipsychotic-induced weight gain, movement disorders, hormonal abnormality, and clozapine-induced agranulocytosis/granulocytopenia), albeit with mixed results. Overall, several gene variants related to antipsychotic response and adverse effects in the treatment of patients with schizophrenia have been reported, and several commercial pharmacogenomic tests have become available. However, further well-designed investigations and replication studies in large and well-characterized samples are needed to facilitate the application of PGx findings to clinical practice.

Immunoendocrine Peripheral Effects Induced by Atypical Antipsychotics

Atypical antipsychotics (AAP) or second-generation antipsychotics are the clinical option for schizophrenia treatment during acute psychoses, but they are also indicated for maintenance during lifetime, even though they are being used for other psychiatric conditions in clinical practice such as affective disorders and autism spectrum disorder, among others. These drugs are differentiated from typical antipsychotics based on their clinical profile and are a better choice because they cause fewer side effects regarding extrapyramidal symptoms (EPS). Even though they provide clear therapeutic benefits, AAP induce peripheral effects that trigger phenotypic, functional, and systemic changes outside the Central Nervous System (CNS). Metabolic disease is frequently associated with AAP and significantly impacts the patient's quality of life. However, other peripheral changes of clinical relevance are present during AAP treatment, such as alterations in the immune and endocrine systems as well as the intestinal microbiome. These less studied alterations also have a significant impact in the patient's health status. This manuscript aims to revise the peripheral immunological, endocrine, and intestinal microbiome changes induced by AAP consumption recommended in the clinical guidelines for schizophrenia and other psychiatric disorders.

Construction and Analysis of Protein-Protein Interaction Network of Heroin Use Disorder

Heroin use disorder (HUD) is a complex disease resulting from interactions among genetic and other factors (e.g., environmental factors). The mechanism of HUD development remains unknown. Newly developed network medicine tools provide a platform for exploring complex diseases at the system level. This study proposes that protein–protein interactions (PPIs), particularly those among proteins encoded by casual or susceptibility genes, are extremely crucial for HUD development. The giant component of our constructed PPI network comprised 111 nodes with 553 edges, including 16 proteins with large degree (k) or high betweenness centrality (BC), which were further identified as the backbone of the network. JUN with the largest degree was suggested to be central to the PPI network associated with HUD. Moreover, PCK1 with the highest BC and MAPK14 with the secondary largest degree and 9^th highest BC might be involved in the development HUD and other substance diseases.

Improving pharmacogenetic prediction of extrapyramidal symptoms induced by antipsychotics

In previous work we developed a pharmacogenetic predictor of antipsychotic (AP) induced extrapyramidal symptoms (EPS) based on four genes involved in mTOR regulation. The main objective is to improve this predictor by increasing its biological plausibility and replication. We re-sequence the four genes using next-generation sequencing. We predict functionality "in silico" of all identified SNPs and test it using gene reporter assays. Using functional SNPs, we develop a new predictor utilizing machine learning algorithms (Discovery Cohort, N = 131) and replicate it in two independent cohorts (Replication Cohort 1, N = 113; Replication Cohort 2, N = 113). After prioritization, four SNPs were used to develop the pharmacogenetic predictor of AP-induced EPS. The model constructed using the Naive Bayes algorithm achieved a 66% of accuracy in the Discovery Cohort, and similar performances in the replication cohorts. The result is an improved pharmacogenetic predictor of AP-induced EPS, which is more robust and generalizable than the original.

New findings in pharmacogenetics of schizophrenia

PURPOSE OF REVIEW

This review highlights recent advances in the investigation of genetic factors for antipsychotic response and side effects.

RECENT FINDINGS

Antipsychotics prescribed to treat psychotic symptoms are variable in efficacy and propensity for causing side effects. The major side effects include tardive dyskinesia, antipsychotic-induced weight gain (AIWG), and clozapine-induced agranulocytosis (CIA). Several promising associations of polymorphisms in genes including HSPG2, CNR1, and DPP6 with tardive dyskinesia have been reported. In particular, a functional genetic polymorphism in SLC18A2, which is a target of recently approved tardive dyskinesia medication valbenazine, was associated with tardive dyskinesia. Similarly, several consistent findings primarily from genes modulating energy homeostasis have also been reported (e.g. MC4R, HTR2C). CIA has been consistently associated with polymorphisms in the HLA genes (HLA-DQB1 and HLA-B). The association findings between glutamate system genes and antipsychotic response require additional replications.

SUMMARY

The findings to date are promising and provide us a better understanding of the development of side effects and response to antipsychotics. However, more comprehensive investigations in large, well characterized samples will bring us closer to clinically actionable findings.

Cardiac Arrhythmias and Antiarrhythmic Drugs: An Autophagic Perspective

Degradation of cellular material by lysosomes is known as autophagy, and its main function is to maintain cellular homeostasis for growth, proliferation and survival of the cell. In recent years, research has focused on the characterization of autophagy pathways. Targeting of autophagy mediators has been described predominantly in cancer treatment, but also in neurological and cardiovascular diseases. Although the number of studies is still limited, there are indications that activity of autophagy pathways increases under arrhythmic conditions. Moreover, an increasing number of antiarrhythmic and non-cardiac drugs are found to affect autophagy pathways. We, therefore, suggest that future work should recognize the largely unaddressed effects of antiarrhythmic agents and other classes of drugs on autophagy pathway activation and inhibition.

Microarray gene-expression study in fibroblast and lymphoblastoid cell lines from antipsychotic-naïve first-episode schizophrenia patients

Schizophrenia (SZ) is a chronic psychiatric disorder whose onset of symptoms occurs in late adolescence and early adulthood. The etiology is complex and involves important gene-environment interactions. Microarray gene-expression studies on SZ have identified alterations in several biological processes. The heterogeneity in the results can be attributed to the use of different sample types and other important confounding factors including age, illness chronicity and antipsychotic exposure. The aim of the present microarray study was to analyze, for the first time to our knowledge, differences in gene expression profiles in 18 fibroblast (FCLs) and 14 lymphoblastoid cell lines (LCLs) from antipsychotic-naïve first-episode schizophrenia (FES) patients and healthy controls. We used an analytical approach based on protein-protein interaction network construction and functional annotation analysis to identify the biological processes that are altered in SZ. Significant differences in the expression of 32 genes were found when LCLs were assessed. The network and gene set enrichment approach revealed the involvement of similar biological processes in FCLs and LCLs, including apoptosis and related biological terms such as cell cycle, autophagy, cytoskeleton organization and response to stress and stimulus. Metabolism and other processes, including signal transduction, kinase activity and phosphorylation, were also identified. These results were replicated in two independent cohorts using the same analytical approach. This provides more evidence for altered apoptotic processes in antipsychotic-naïve FES patients and other important biological functions such as cytoskeleton organization and metabolism. The convergent results obtained in both peripheral cell models support their usefulness for transcriptome studies on SZ.

Biomarkers in schizophrenia: A focus on blood based diagnostics and theranostics

Identifying biomarkers that can be used as diagnostics or predictors of treatment response (theranostics) in people with schizophrenia (Sz) will be an important step towards being able to provide personalized treatment. Findings from the studies in brain tissue have not yet been translated into biomarkers that are practical in clinical use because brain biopsies are not acceptable and neuroimaging techniques are expensive and the results are inconclusive. Thus, in recent years, there has been search for blood-based biomarkers for Sz as a valid alternative. Although there are some encouraging preliminary data to support the notion of peripheral biomarkers for Sz, it must be acknowledged that Sz is a complex and heterogeneous disorder which needs to be further dissected into subtype using biological based and clinical markers. The scope of this review is to critically examine published blood-based biomarker of Sz, focusing on possible uses for diagnosis, treatment response, or their relationship with schizophrenia-associated phenotype. We sorted the studies into six categories which include: (1) brain-derived neurotrophic factor; (2) inflammation and immune function; (3) neurochemistry; (4) oxidative stress response and metabolism; (5) epigenetics and microRNA; and (6) transcriptome and proteome studies. This review also summarized the molecules which have been conclusively reported as potential blood-based biomarkers for Sz in different blood cell types. Finally, we further discusses the pitfall of current blood-based studies and suggest that a prediction model-based, Sz specific, blood oriented study design as well as standardize blood collection conditions would be useful for Sz biomarker development.

Applicability of gene expression and systems biology to develop pharmacogenetic predictors; antipsychotic-induced extrapyramidal symptoms as an example

Pharmacogenetics has been driven by a candidate gene approach. The disadvantage of this approach is that is limited by our current understanding of the mechanisms by which drugs act. Gene expression could help to elucidate the molecular signatures of antipsychotic treatments searching for dysregulated molecular pathways and the relationships between gene products, especially protein-protein interactions. To embrace the complexity of drug response, machine learning methods could help to identify gene-gene interactions and develop pharmacogenetic predictors of drug response. The present review summarizes the applicability of the topics presented here (gene expression, network analysis and gene-gene interactions) in pharmacogenetics. In order to achieve this, we present an example of identifying genetic predictors of extrapyramidal symptoms induced by antipsychotic.

Network analysis of gene expression in mice provides new evidence of involvement of the mTOR pathway in antipsychotic-induced extrapyramidal symptoms

To identify potential candidate genes for future pharmacogenetic studies of antipsychotic (AP)-induced extrapyramidal symptoms (EPS), we used gene expression arrays to analyze changes induced by risperidone in mice strains with different susceptibility to EPS. We proposed a systems biology analytical approach that combined the identification of gene co-expression modules related to AP treatment, the construction of protein-protein interaction networks with genes included in identified modules and finally, gene set enrichment analysis of constructed networks. In response to risperidone, mice strain with susceptibility to develop EPS showed downregulation of genes involved in the mammalian target of rapamycin (mTOR) pathway and biological processes related to this pathway. Moreover, we also showed differences in the phosphorylation pattern of the ribosomal protein S6 (rpS6), which is a major downstream effector of mTOR. The present study provides new evidence of the involvement of the mTOR pathway in AP-induced EPS and offers new and valuable markers for pharmacogenetic studies.