A genetic network model of cellular responses to lithium treatment and cocaine abuse in bipolar disorder

Study on the mechanism of Gegen Qinlian Decoction for treating type II diabetes mellitus by integrating network pharmacology and pharmacological evaluation

ETHNOPHARMACOLOGICAL RELEVANCE

Gegen Qinlian Decoction (GQD) is a classic traditional Chinese medicine prescription that is widely used to clinically treat diabetes mellitus. It is composed of Pueraria lobata (Willd.) Ohwi (ge gen), Scutellaria baicalensis Georgi (huang qin), Coptidis chinensis Franch. (huang lian), and Glycyrrhiza uralensis Fisch. (gan cao). However, the active ingredients in GQD and their mechanism of action are unclear.

AIM OF THE STUDY

In this study, we aimed to verify the efficacy of GQD in improving insulin resistance (IR) in diabetic mice and used network pharmacology to identify potential targets and pathways underlying its mechanism of action.

MATERIALS AND METHODS

A mouse model of diabetes was created by feeding mice a high-fat diet followed by an intraperitoneal injection of streptozotocin. These type II diabetic mice were administered either a clinical dose or a high dose of GQD, after which blood glucose and serum insulin levels were measured to assess its effects on IR. Network pharmacology was used to construct a 'component-pathway-target' network to elucidate the likely targets and pathways modulated in common by GQD components. Furthermore, mRNA transcript levels and protein expression levels of oestrogen receptor alpha (ESR1) were determined.

RESULTS

The in vivo experiment showed that GQD markedly decreased blood glucose and increased serum insulin levels in type II diabetic mice. Network pharmacology and bioinformatics analysis indicated that GQD regulated 82 corresponding proteins and 59 relevant biological pathways associated with diabetes. One such target was ESR1, which was significantly decreased at both the mRNA and protein levels in diabetic mice, but whose levels were significantly increased by GQD treatment.

CONCLUSIONS

This project provides a scientific basis for understanding the effectiveness of multi-component, multi-target compound formulas, as well as a new strategy for investigating therapeutic drugs for type II diabetes and other diseases.

Lithium response in bipolar disorder correlates with improved cell viability of patient derived cell lines

Lithium is an effective, well-established treatment for bipolar disorder (BD). However, the mechanisms of its action, and reasons for variations in clinical response, are unclear. We used neural precursor cells (NPCs) and lymphoblastoid cell lines (LCLs), from BD patients characterized for clinical response to lithium (using the "Alda scale" and "NIMH Retrospective Life chart method"), to interrogate cellular phenotypes related to both disease and clinical lithium response. NPCs from two biologically related BD patients who differed in their clinical response to lithium were compared with healthy controls. RNA-Seq and analysis, mitochondrial membrane potential (MMP), cell viability, and cell proliferation parameters were assessed, with and without in vitro lithium. These parameters were also examined in LCLs from 25 BD patients (16 lithium responders and 9 non-responders), and 12 controls. MMP was lower in both NPCs and LCLs from BD; but it was reversed with in vitro lithium only in LCLs, and this was unrelated to clinical lithium response. The higher cell proliferation observed in BD was unaffected by in vitro lithium. Cell death was greater in BD. However, LCLs from clinical lithium responders could be rescued by addition of in vitro lithium. In vitro lithium also enhanced BCL2 and GSK3B expression in these cells. Our findings indicate cellular phenotypes related to the disease (MMP, cell proliferation) in both NPCs and LCLs; and those related to clinical lithium response (cell viability, BCL2/GSK3B expression) in LCLs.

Exploring lithium's transcriptional mechanisms of action in bipolar disorder: a multi-step study

Lithium has been the first-line treatment for bipolar disorder (BD) for more than six decades. Although the molecular effects of lithium have been studied extensively and gene expression changes are generally believed to be involved, the specific mechanisms of action that mediate mood regulation are still not known. In this study, a multi-step approach was used to explore the transcriptional changes that may underlie lithium's therapeutic efficacy. First, we identified genes that are associated both with lithium exposure and with BD, and second, we performed differential expression analysis of these genes in brain tissue samples from BD patients (n = 42) and healthy controls (n = 42). To identify genes that are regulated by lithium exposure, we used high-sensitivity RNA-sequencing of corpus callosum (CC) tissue samples from lithium-treated (n = 8) and non-treated (n = 9) rats. We found that lithium exposure significantly affected 1108 genes (FDR < 0.05), 702 up-regulated and 406 down-regulated. These genes were mostly enriched for molecular functions related to signal transduction, including well-established lithium-related pathways such as mTOR and Wnt signaling. To identify genes with differential expression in BD, we performed expression quantitative trait loci (eQTL) analysis on BD-associated genetic variants from the most recent genome-wide association study (GWAS) using three different gene expression databases. We found 307 unique eQTL genes regulated by BD-associated variants, of which 12 were also significantly modulated by lithium treatment in rats. Two of these showed differential expression in the CC of BD cases: RPS23 was significantly down-regulated (p = 0.0036, fc = 0.80), while GRIN2A showed suggestive evidence of down-regulation in BD (p = 0.056, fc = 0.65). Crucially, GRIN2A was also significantly up-regulated by lithium in the rat brains (p = 2.2e-5, fc = 1.6), which suggests that modulation of GRIN2A expression may be a part of the therapeutic effect of the drug. These results indicate that the recent upsurge in research on this central component of the glutamatergic system, as a target of novel therapeutic agents for affective disorders, is warranted and should be intensified.

Genome-Wide DNA Methylation Changes Associated with Intermittent Explosive Disorder: A Gene-Based Functional Enrichment Analysis

BACKGROUND

Intermittent explosive disorder is defined as a recurrent, problematic, and impulsive aggression that affects 3% to 4% of the US population. While behavioral genetic studies report a substantial degree of genetic influence on aggression and impulsivity, epigenetic mechanisms underlying aggression and intermittent explosive disorder are not well known.

METHODS

The sample included 44 subjects (22 with a DSM-5 diagnosis of intermittent explosive disorder and 22 comparable subjects without intermittent explosive disorder). Peripheral blood DNA methylome was profiled using the Illumina Infinium HumanMethylation450 Beadchip. Intermittent explosive disorder-associated genome-wide DNA methylation changes were analyzed using the CpGassoc R package, with covariates age, sex, and race being adjusted. A gene-based functional enrichment analysis was performed to identify pathways that were overrepresented by genes harboring highly differentially methylated CpG sites.

RESULTS

A total of 27 CpG sites were differentially methylated in IED participants (P<5.0×10-5), but none reached genome-wide significant threshold. Functional enrichment analysis revealed that genes mapped by these CpG sites are involved in the inflammatory/immune system, the endocrine system, and neuronal differentiation.

CONCLUSIONS

Consistent with our previous studies showing an association of inflammatory response with aggressive behavior in intermittent explosive disorder subjects, our gene-based pathway analysis using differentially methylated CpG sites supports inflammatory response as an important mechanism involved in intermittent explosive disorder and reveals other novel biological processes possibly associated with intermittent explosive disorder.

Developmental programming: Interaction between prenatal BPA and postnatal overfeeding on cardiac tissue gene expression in female sheep

Epidemiologic studies and studies in rodents point to potential risks from developmental exposure to BPA on cardiometabolic diseases. Furthermore, it is becoming increasingly evident that the manifestation and severity of adverse outcomes is the result of interaction between developmental insults and the prevailing environment. Consistent with this premise, recent studies in sheep found prenatal BPA treatment prevented the adverse effects of postnatal obesity in inducing hypertension. The gene networks underlying these complex interactions are not known. mRNA-seq of myocardium was performed on four groups of four female sheep to assess the effects of prenatal BPA exposure, postnatal overfeeding and their interaction on gene transcription, pathway perturbations and functional effects. The effects of prenatal exposure to BPA, postnatal overfeeding, and prenatal BPA with postnatal overfeeding all resulted in transcriptional changes (85-141 significant differentially expressed genes). Although the effects of prenatal BPA and postnatal overfeeding did not involve dysregulation of many of the same genes, they affected a remarkably similar set of biological pathways. Furthermore, an additive or synergistic effect was not found in the combined treatment group, but rather prenatal BPA treatment led to a partial reversal of the effects of overfeeding alone. Many genes previously known to be affected by BPA and involved in obesity, hypertension, or heart disease were altered following these treatments, and AP-1, EGR1, and EGFR were key hubs affected by BPA and/or overfeeding. Environ. Mol. Mutagen. 58:4-18, 2017. © 2016 Wiley Periodicals, Inc.

Developmental programming: Interaction between prenatal BPA and postnatal overfeeding on cardiac tissue gene expression in female sheep

Epidemiologic studies and studies in rodents point to potential risks from developmental exposure to BPA on cardiometabolic diseases. Furthermore, it is becoming increasingly evident that the manifestation and severity of adverse outcomes is the result of interaction between developmental insults and the prevailing environment. Consistent with this premise, recent studies in sheep found prenatal BPA treatment prevented the adverse effects of postnatal obesity in inducing hypertension. The gene networks underlying these complex interactions are not known. mRNA-seq of myocardium was performed on four groups of four female sheep to assess the effects of prenatal BPA exposure, postnatal overfeeding and their interaction on gene transcription, pathway perturbations and functional effects. The effects of prenatal exposure to BPA, postnatal overfeeding, and prenatal BPA with postnatal overfeeding all resulted in transcriptional changes (85-141 significant differentially expressed genes). Although the effects of prenatal BPA and postnatal overfeeding did not involve dysregulation of many of the same genes, they affected a remarkably similar set of biological pathways. Furthermore, an additive or synergistic effect was not found in the combined treatment group, but rather prenatal BPA treatment led to a partial reversal of the effects of overfeeding alone. Many genes previously known to be affected by BPA and involved in obesity, hypertension, or heart disease were altered following these treatments, and AP-1, EGR1, and EGFR were key hubs affected by BPA and/or overfeeding. Environ. Mol. Mutagen. 58:4-18, 2017. © 2016 Wiley Periodicals, Inc.

From direct to indirect lithium targets: a comprehensive review of omics data

Metal ions are critical to a wide range of biological processes.

Lithium-responsive genes and gene networks in bipolar disorder patient-derived lymphoblastoid cell lines

Lithium (Li) is the mainstay mood stabilizer for the treatment of bipolar disorder (BD), although its mode of action is not yet fully understood nor is it effective in every patient. We sought to elucidate the mechanism of action of Li and to identify surrogate outcome markers that can be used to better understand its therapeutic effects in BD patients classified as good (responders) and poor responders (nonresponders) to Li treatment. To accomplish these goals, RNA-sequencing gene expression profiles of lymphoblastoid cell lines (LCLs) were compared between BD Li responders and nonresponders with healthy controls before and after treatment. Several Li-responsive gene coexpression networks were discovered indicating widespread effects of Li on diverse cellular signaling systems including apoptosis and defense response pathways, protein processing and response to endoplasmic reticulum stress. Individual gene markers were also identified, differing in response to Li between BD responders and nonresponders, involved in processes of cell cycle and nucleotide excision repair that may explain part of the heterogeneity in clinical response to treatment. Results further indicated a Li gene expression signature similar to that observed with clonidine treatment, an α2-adrenoceptor agonist. These findings provide a detailed mechanism of Li in LCLs and highlight putative surrogate outcome markers that may permit for advanced treatment decisions to be made and for facilitating recovery in BD patients.

Neurodevelopmental origins of bipolar disorder: iPSC models

Bipolar disorder (BP) is a chronic neuropsychiatric condition characterized by pathological fluctuations in mood from mania to depression. Adoption, twin and family studies have consistently identified a significant hereditary component to BP, yet there is no clear genetic event or consistent neuropathology. BP has been suggested to have a developmental origin, although this hypothesis has been difficult to test since there are no viable neurons or glial cells to analyze, and research has relied largely on postmortem brain, behavioral and imaging studies, or has examined proxy tissues including saliva, olfactory epithelium and blood cells. Neurodevelopmental factors, particularly pathways related to nervous system development, cell migration, extracellular matrix, H3K4 methylation, and calcium signaling have been identified in large gene expression and GWAS studies as altered in BP. Recent advances in stem cell biology, particularly the ability to reprogram adult somatic tissues to a pluripotent state, now make it possible to interrogate these pathways in viable cell models. A number of induced pluripotent stem cell (iPSC) lines from BP patient and healthy control (C) individuals have been derived in several laboratories, and their ability to form cortical neurons examined. Early studies suggest differences in activity, calcium signaling, blocks to neuronal differentiation, and changes in neuronal, and possibly glial, lineage specification. Initial observations suggest that differentiation of BP patient-derived neurons to dorsal telencephalic derivatives may be impaired, possibly due to alterations in WNT, Hedgehog or Nodal pathway signaling. These investigations strongly support a developmental contribution to BP and identify novel pathways, mechanisms and opportunities for improved treatments.

Epigenome-Wide Association Study of Aggressive Behavior

Aggressive behavior is highly heritable, while environmental influences, particularly early in life, are also important. Epigenetic mechanisms, such as DNA methylation, regulate gene expression throughout development and adulthood, and may mediate genetic and environmental effects on complex traits. We performed an epigenome-wide association study (EWAS) to identify regions in the genome where DNA methylation level is associated with aggressive behavior. Subjects took part in longitudinal survey studies from the Netherlands Twin Register (NTR) and participated in the NTR biobank project between 2004 and 2011 (N = 2,029, mean age at blood sampling = 36.4 years, SD = 12.4, females = 69.2%). Aggressive behavior was rated with the ASEBA Adult Self-Report (ASR). DNA methylation was measured in whole blood by the Illumina HM450k array. The association between aggressive behavior and DNA methylation level at 411,169 autosomal sites was tested. Association analyses in the entire cohort showed top sites at cg01792876 (chr8; 116,684,801, nearest gene = TRPS1, p = 7.6 × 10−7, False discovery rate (FDR) = 0.18) and cg06092953 (chr18; 77,905,699, nearest gene = PARD6G-AS1, p = 9.0 ×10−7, FDR = 0.18). Next, we compared methylation levels in 20 pairs of monozygotic (MZ) twins highly discordant for aggression. Here the top sites were cg21557159 (chr 11; 107,795,699, nearest gene = RAB39, p = 5.7 × 10−6, FDR = 0.99), cg08648367 (chr 19; 51,925,472, nearest gene = SIGLEC10, p = 7.6 × 10−6, FDR = 0.99), and cg14212412 (chr 6; 105,918,992, nearest gene = PREP, p = 8.0 × 10−6, FDR = 0.99). The two top hits based on the entire cohort showed the same direction of effect in discordant MZ pairs (cg01792876, Pdiscordant twins = 0.09 and cg06092953, Pdiscordant twins = 0.24). The other way around, two of the three most significant sites in discordant MZ pairs showed the same direction of effect in the entire cohort (cg08648367, Pentire EWAS = 0.59 and cg14212412, Pentire EWAS = 3.1 × 10−3). Gene ontology analysis highlighted significant enrichment of various central nervous system categories among higher-ranking methylation sites. Higher-ranking methylation sites also showed enrichment for DNase I hypersensitive sites and promoter regions, showing that DNA methylation in peripheral tissues is likely to be associated with aggressive behavior.

Cellular models to study bipolar disorder: A systematic review

BACKGROUND

There is an emerging interest in the use of cellular models to study psychiatric disorders. We have systematically reviewed the application of cellular models to understand the biological basis of bipolar disorder (BD).

METHOD

Published scientific literature in MEDLINE, PsychINFO and SCOPUS databases were identified with the following search strategy: [(Lymphoblastoid OR Lymphoblast OR Fibroblast OR Pluripotent OR Olfactory epithelium OR Olfactory mucosa) AND (Bipolar disorder OR Lithium OR Valproate OR Mania)]. Studies were included if they had used cell cultures derived from BD patients.

RESULTS

There were 65 articles on lymphoblastoid cell lines, 14 articles on fibroblasts, 4 articles on olfactory neuronal epithelium (ONE) and 2 articles on neurons reprogrammed from induced pluripotent stem cell lines (IPSC). Several parameters have been studied, and the most replicated findings are abnormalities in calcium signaling, endoplasmic reticulum (ER) stress response, mitochondrial oxidative pathway, membrane ion channels, circadian system and apoptosis related genes. These, although present in basal state, seem to be accentuated in the presence of cellular stressors (e.g. oxidative stress--rotenone; ER stress--thapsigargin), and are often reversed with in-vitro lithium.

CONCLUSION

Cellular modeling has proven useful in BD, and potential pathways, especially in cellular resilience related mechanisms have been identified. These findings show consistency with other study designs (genome-wide association, brain-imaging, and post-mortem brain expression). ONE cells and IPSC reprogrammed neurons represent the next generation of cell models in BD. Future studies should focus on family-based study designs and combine cell models with deep sequencing and genetic manipulations.

A bioinformatics approach reveals novel interactions of the OVOL transcription factors in the regulation of epithelial - mesenchymal cell reprogramming and cancer progression

Background

Mesenchymal to Epithelial Transition (MET) plasticity is critical to cancer progression, and we recently showed that the OVOL transcription factors (TFs) are critical regulators of MET. Results of that work also posed the hypothesis that the OVOLs impact MET in a range of cancers. We now test this hypothesis by developing a model, OVOL Induced MET (OI-MET), and sub-model (OI-MET-TF), to characterize differential gene expression in MET common to prostate cancer (PC) and breast cancer (BC).

Results

In the OI-MET model, we identified 739 genes differentially expressed in both the PC and BC models. For this gene set, we found significant enrichment of annotation for BC, PC, cancer, and MET, as well as regulation of gene expression by AP1, STAT1, STAT3, and NFKB1. Focusing on the target genes for these four TFs plus the OVOLs, we produced the OI-MET-TF sub-model, which shows even greater enrichment for these annotations, plus significant evidence of cooperation among these five TFs. Based on known gene/drug interactions, we prioritized targets in the OI-MET-TF network for follow-on analysis, emphasizing the clinical relevance of this work. Reflecting these results back to the OI-MET model, we found that binding motifs for the TF pair AP1/MYC are more frequent than expected and that the AP1/MYC pair is significantly enriched in binding in cancer models, relative to non-cancer models, in these promoters. This effect is seen in both MET models (solid tumors) and in non-MET models (leukemia). These results are consistent with our hypothesis that the OVOLs impact cancer susceptibility by regulating MET, and extend the hypothesis to include mechanisms not specific to MET.

Conclusions

We find significant evidence of the OVOL, AP1, STAT1, STAT3, and NFKB1 TFs having important roles in MET, and more broadly in cancer. We prioritize known gene/drug targets for follow-up in the clinic, and we show that the AP1/MYC TF pair is a strong candidate for intervention.

High throughput transcriptome profiling of lithium stimulated human mesenchymal stem cells reveals priming towards osteoblastic lineage

Human mesenchymal stem cells (hMSCs) present in the bone marrow are the precursors of osteoblasts, chondrocytes and adipocytes, and hold tremendous potential for osteoregenerative therapy. However, achieving directed differentiation into osteoblasts has been a major concern. The use of lithium for enhancing osteogenic differentiation has been documented in animal models but its effect in humans is not clear. We, therefore, performed high throughput transcriptome analysis of lithium-treated hMSCs to identify altered gene expression and its relevance to osteogenic differentiation. Our results show suppression of proliferation and enhancement of alkaline phosphatase (ALP) activity upon lithium treatment of hMSCs under non-osteogenic conditions. Microarray profiling of lithium-stimulated hMSC revealed decreased expression of adipogenic genes (CEBPA, CMKLR1, HSD11B1) and genes involved in lipid biosynthesis. Interestingly, osteoclastogenic factors and immune responsive genes (IL7, IL8, CXCL1, CXCL12, CCL20) were also downregulated. Negative transcriptional regulators of the osteogenic program (TWIST1 and PBX1) were suppressed while genes involved in mineralization like CLEC3B and ATF4 were induced. Gene ontology analysis revealed enrichment of upregulated genes related to mesenchymal cell differentiation and signal transduction. Lithium priming led to enhanced collagen 1 synthesis and osteogenic induction of lithium pretreated MSCs resulted in enhanced expression of Runx2, ALP and bone sialoprotein. However, siRNA-mediated knockdown of RRAD, CLEC3B and ATF4 attenuated lithium-induced osteogenic priming, identifying a role for RRAD, a member of small GTP binding protein family, in osteoblast differentiation. In conclusion, our data highlight the transcriptome reprogramming potential of lithium resulting in higher propensity of lithium "primed" MSCs for osteoblastic differentiation.

Discovering gene-environment interactions in glioblastoma through a comprehensive data integration bioinformatics method

Glioblastoma multiforme (GBM) is the most common and aggressive type of human brain tumor. Although considerable efforts to delineate the underlying pathophysiological pathways have been made during the last decades, only very limited progress on treatment have been achieved because molecular pathways that drive the aggressive nature of GBM are largely unknown. Recent studies have emphasized the importance of environmental factors and the role of gene-environment interactions (GEI) in the development of GBM. Factors such as small sample sizes and study costs have limited the conduct of GEI studies in brain tumors however. Additionally, advances in high-throughput microarrays have produced a wealth of information concerning molecular biology of glioma. In particular, microarrays have been used to obtain genetic and epigenetic changes between normal non-tumor tissue and glioma tissue. Due to the relative rarity of gliomas, microarray data for these tumors is often the product of small studies, and thus pooling this data becomes desirable. To address the challenge of small sample sizes and GEI study difficulties, we introduce a comprehensive bioinformatics method using genetic variations (copy number variations and small-scale variations) and environmental data integration that links with glioblastoma (GEG) to identify: (1) genes that interact with chemicals and have genetic variants linked to the development of GBM, (2) important pathways that may be influenced by environmental exposures (or endogenous chemicals), and (3) genes with variants in GBM that have been understudied in relation to GBM development. The first step in our GEG method identified genes responsive to environmental exposures using the Environmental Genome Project, Comparative Toxicology, and Seattle SNPs databases. These environmentally responsive genes were then compared to a curated list of genes containing copy number variation and/or mutations in GBM. This comparison produced a list of genes responsive to the environment and important to GBM that was then further analyzed using gene networking tools such as RSpider, Cytoscape, and DAVID. Using this GEG bioinformatics method we were able to identify 173 genes with the potential to be involved in GEI that may be important to the development of GBM. Sixty five of these environmentally responsive genes have not been reported as important to GBM development, despite several of them having substantial potential for response to chemicals and subsequent disease related actions. The main biological functions of these 173 genes include signaling by nerve growth factor, DNA repair, integrin cell surface interactions, biological oxidations, apoptosis, synaptic transmission, cell cycle checkpoints, and arachidonic acid metabolism. Importantly, some of these functions have been implicated in the development of several cancers, including glioma. In summary, our GEG bioinformatics approach revealed potential gene-environment interactions, and generated new data for hypothesis generation, in GBM.

State-related alterations of gene expression in bipolar disorder: a systematic review

OBJECTIVE

Alterations in gene expression in bipolar disorder have been found in numerous studies. It is unclear whether such alterations are related to specific mood states. As a biphasic disorder, mood state-related alterations in gene expression have the potential to point to markers of disease activity, and trait-related alterations might indicate vulnerability pathways. This review therefore evaluated the evidence for whether gene expression in bipolar disorder is state or trait related.

METHODS

A systematic review, using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guideline for reporting systematic reviews, based on comprehensive database searches for studies on gene expression in patients with bipolar disorder in specific mood states, was conducted. We searched Medline, Embase, PsycINFO, and The Cochrane Library, supplemented by manually searching reference lists from retrieved publications.

RESULTS

A total of 17 studies were included, comprising 565 patients and 418 control individuals. Six studies evaluated intraindividual alterations in gene expression across mood states. Two of five studies found evidence of intraindividual alterations in gene expression between a depressed state and a euthymic state. No studies evaluated intraindividual differences in gene expression between a manic state and a euthymic state, while only one case study evaluated differences between a manic state and a depressed state, finding altered expression in seven genes. No study investigated intraindividual variations in gene expression between a euthymic state and multiple states of various polarities (depressive, manic, hypomanic). Intraindividual alterations in expression of the same genes were not investigated across studies. Only one gene (the brain-derived neurotrophic factor gene; BDNF) was investigated across multiple studies, showing no alteration between bipolar disorder patients and control individuals.

CONCLUSIONS

There is evidence of some genes exhibiting state-related alterations in expression in bipolar disorder; however, this finding is limited by the lack of replication across studies. Further prospective studies are warranted, measuring gene expression in various affective phases, allowing for assessment of intraindividual differences.

Predicting new molecular targets for rhein using network pharmacology

Background

Drugs can influence the whole biological system by targeting interaction reactions. The existence of interactions between drugs and network reactions suggests a potential way to discover targets. The in silico prediction of potential interactions between drugs and target proteins is of core importance for the identification of new drugs or novel targets for existing drugs. However, only a tiny portion of drug-targets in current datasets are validated interactions. This motivates the need for developing computational methods that predict true interaction pairs with high accuracy. Currently, network pharmacology has used in identifying potential drug targets to predicting the spread of drug activity and greatly contributed toward the analysis of biological systems on a much larger scale than ever before.

Methods

In this article, we present a computational method to predict targets for rhein by exploring drug-reaction interactions. We have implemented a computational platform that integrates pathway, protein-protein interaction, differentially expressed genome and literature mining data to result in comprehensive networks for drug-target interaction. We used Cytoscape software for prediction rhein-target interactions, to facilitate the drug discovery pipeline.

Results

Results showed that 3 differentially expressed genes confirmed by Cytoscape as the central nodes of the complicated interaction network (99 nodes, 153 edges). Of note, we further observed that the identified targets were found to encompass a variety of biological processes related to immunity, cellular apoptosis, transport, signal transduction, cell growth and proliferation and metabolism.

Conclusions

Our findings demonstrate that network pharmacology can not only speed the wide identification of drug targets but also find new applications for the existing drugs. It also implies the significant contribution of network pharmacology to predict drug targets.

Overlap of genetic influences in phenotypes classically categorized as psychiatric vs medical disorders

Psychiatric disorders have traditionally been segregated from medical disorders in terms of drugs, treatment, insurance coverage and training of clinicians. This segregation is consistent with the long-standing observation that there are inherent differences between psychiatric disorders (diseases relating to thoughts, feelings and behavior) and medical disorders (diseases relating to physical processes). However, these differences are growing less distinct as we improve our understanding of the roles of epistasis and pleiotropy in medical genetics. Both psychiatric and medical disorders are predisposed in part by genetic variation, and psychiatric disorders tend to be comorbid with medical disorders. One hypothesis on this interaction posits that certain combinations of genetic variants (epistasis) influence psychiatric disorders due to their impact on the brain, but the associated genes are also expressed in other tissues so the same groups of variants influence medical disorders (pleiotropy). The observation that psychiatric and medical disorders may interact is not novel. Equally, both epistasis and pleiotropy are fundamental concepts in medical genetics. However, we are just beginning to understand how genetic variation can influence both psychiatric and medical disorders. In our recent work, we have discovered gene networks significantly associated with psychiatric and substance use disorders. Invariably, these networks are also significantly associated with medical disorders. Recognizing how genetic variation can influence both psychiatric and medical disorders will help us to understand the etiology of the individual and comorbid disease phenotypes, predict and minimize side effects in drug and other treatments, and help to reduce stigma associated with psychiatric disorders.