Abstract: Genetic patterns of inter-population variation are a result of different demographic and adaptive histories, which gradually shape the frequency distribution of the variants. However, the study of clinically relevant mutations has a Eurocentric bias. The Romani, the largest transnational minority ethnic group in Europe, originated in South Asia and received extensive gene flow from West Eurasia. Most medical genetic studies have only explored founder mutations related to Mendelian disorders in this population. Here we analyze exome sequences and genome-wide array data of 89 healthy Spanish Roma individuals to study complex traits and disease. We apply a different framework and focus on variants with both increased and decreased allele frequencies, taking into account their local ancestry. We report several OMIM traits enriched for genes with deleterious variants showing increased frequencies in Roma or in non-Roma (e.g., obesity is enriched in Roma, with an associated variant linked to South Asian ancestry; while non-insulin dependent diabetes is enriched in non-Roma Europeans). In addition, previously reported pathogenic variants also show differences among populations, where some variants segregating at low frequency in non-Roma are virtually absent in the Roma. Lastly, we describe frequency changes in drug-response variation, where many of the variants increased in Roma are clinically associated with metabolic and cardiovascular-related drugs. These results suggest that clinically relevant variation in Roma cannot only be characterized in terms of founder mutations. Instead, we observe frequency differences compared to non-Roma: some variants are absent, while other have drifted to higher frequencies. As a result of the admixture events, these clinically damaging variants can be traced back to both European and South Asian-related ancestries. This can be attributed to a different prevalence of some genetic disorders or to the fact that genetic susceptibility variants are mostly studied in populations of European descent, and can differ in individuals with different ancestries.

Abstract: Malaria caused by Plasmodium vivax can lead to severe morbidity and death. In addition, resistance has been reported to existing drugs in treating this malaria. Therefore, the identification of new human proteins associated with malaria is urgently needed for the development of additional drugs. In this study, we established an analysis framework to predict human-P. vivax protein associations using network topological profiles from a heterogeneous network structure of human and P. vivax, machine-learning techniques and statistical analysis. Novel associations were predicted and ranked to determine the importance of human proteins associated with malaria. With the best-ranking score, 411 human proteins were identified as promising proteins. Their regulations and functions were statistically analyzed, which led to the identification of proteins involved in the regulation of membrane and vesicle formation, and proteasome complexes as potential targets for the treatment of P. vivax malaria. In conclusion, by integrating related data, our analysis was efficient in identifying potential targets providing an insight into human-parasite protein associations. Furthermore, generalizing this model could allow researchers to gain further insights into other diseases and enhance the field of biomedical science.

Abstract: Protein-protein interaction networks have a crucial role in biological processes. Proteins perform multiple functions in forming physical and functional interactions in cellular systems. Information concerning an enormous number of protein interactions in a wide range of species has accumulated and has been integrated into various resources for molecular biology and systems biology. This chapter provides a review of the representative databases and the major computational methods used for protein-protein interactions.

Abstract: Introduction: Baicalein has been shown to have antitumor activities in several cancer types. However, its acting mechanisms remain to be further investigated. This work is aimed at exploring the functional long noncoding RNA (lncRNA)/microRNA (miRNA)/messenger RNA (mRNA) triplets in response to baicalein in hepatocellular carcinoma (HCC) cell to understand the mechanisms of baicalein in HCC. Methods: Differentially expressed lncRNAs (DELs) and miRNAs (DEMs) in HCC cell treated with baicalein were first screened using GSE95504 and GSE85511, respectively. miRNA targets for DELs were predicted and intersected with DEMs, after which the miRNA expression was validated using ENCORI and its prognostic value was assessed using Kaplan-Meier plotter. Potential miRNA targets were predicted by 3 prediction tools, after which expression level was validated at UALCAN and Human Protein Atlas. Kaplan-Meier plotter was used to evaluate the effects of these genes on overall survival and recurrence-free survival of HCC patients. Enrichment analyses for these genes were performed at DAVID. Results: Here, we identified 14 overlapping DELs and 26 overlapping DEMs in the baicalein treatment group than those in the DMSO treatment group. Subsequently, by analyzing expression and clinical significance of miRNAs, hsa-miR-4443 was found as a highly potential miRNA target. Then, targets of hsa-miR-4443 were predicted and analyzed, and we found AKT1 was the most potential target for hsa-miR-4443. Hence, the lncRNAs-hsa-miR-4443-AKT1 axis that can respond to baicalein was established. Conclusion: Collectively, we elucidated a role of lncRNAs-hsa-miR-4443-AKT1 pathway in response to baicalein treatment in HCC, which could help us understand the roles of baicalein in inhibiting cancer progression and may provide novel insights into the mechanisms behind HCC progression.

Abstract: Fibrotic diseases cover a spectrum of systemic and organ-specific maladies that affect a large portion of the population, currently without cure. The shared characteristic these diseases feature is their uncontrollable fibrogenesis deemed responsible for the accumulated damage in the susceptible tissues. Idiopathic Pulmonary Fibrosis, an interstitial lung disease, is one of the most common and studied fibrotic diseases and still remains an active research target. In this study we highlight unique and common (i) genes, (ii) biological pathways and (iii) candidate repurposed drugs among 9 fibrotic diseases. We identify 7 biological pathways involved in all 9 fibrotic diseases as well as pathways unique to some of these diseases. Based on our Drug Repurposing results, we suggest captopril and ibuprofen that both appear to slow the progression of fibrotic diseases according to existing bibliography. We also recommend nafcillin and memantine, which haven't been studied against fibrosis yet, for further wet-lab experimentation. We also observe a group of cardiomyopathy-related pathways that are exclusively highlighted for Oral Submucous Fibrosis. We suggest digoxin to be tested against Oral Submucous Fibrosis, since we observe cardiomyopathy-related pathways implicated in Oral Submucous Fibrosis and there is bibliographic evidence that digoxin may potentially clear myocardial fibrosis. Finally, we establish that Idiopathic Pulmonary Fibrosis shares several involved genes, biological pathways and candidate inhibiting-drugs with Dupuytren's Disease, IgG4-related Disease, Systemic Sclerosis and Cystic Fibrosis. We propose that treatments for these fibrotic diseases should be jointly pursued.

Abstract: Tuberous sclerosis complex (TSC) is an autosomal dominant genetic disorder caused by germline mutations in TSC1 or TSC2 genes, which leads to the hyperactivation of the mTORC1 pathway, an important negative regulator of autophagy. This leads to the development of hamartomas in multiple organs. The variability in symptoms presents a challenge for the development of completely effective treatments for TSC. One option is the treatment with mTORC1 inhibitors, which are targeted to block cell growth and restore autophagy. However, the therapeutic effect of rapamycin seems to be more efficient in the early stages of hamartoma development, an effect that seems to be associated with the paradoxical role of autophagy in tumor establishment. Under normal conditions, autophagy is directly inhibited by mTORC1. In situations of bioenergetics stress, mTORC1 releases the Ulk1 complex and initiates the autophagy process. In this way, autophagy promotes the survival of established tumors by supplying metabolic precursors during nutrient deprivation; paradoxically, excessive autophagy has been associated with cell death in some situations. In spite of its paradoxical role, autophagy is an alternative therapeutic strategy that could be explored in TSC. This review compiles the findings related to autophagy and the new therapeutic strategies targeting this pathway in TSC.

Abstract: Background: Mechanical ventilation could lead to ventilator-induced lung injury (VILI), but its underlying pathogenesis remains largely unknown. In this study, we aimed to determine the genes which were highly correlated with VILI as well as their expressions and interactions by analyzing the differentially expressed genes (DEGs) between the VILI samples and controls. Methods: GSE11434 was downloaded from the gene expression omnibus (GEO) database, and DEGs were identified with GEO2R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using DAVID. Next, we used the STRING tool to construct protein-protein interaction (PPI) network of the DEGs. Then, the hub genes and related modules were identified with the Cytoscape plugins: cytoHubba and MCODE. qRT-PCR was further used to validate the results in the GSE11434 dataset. We also applied gene set enrichment analysis (GSEA) to discern the gene sets that had a significant difference between the VILI group and the control. Hub genes were also subjected to analyses by CyTargetLinker and NetworkAnalyst to predict associated miRNAs and transcription factors (TFs). Besides, we used CIBERSORT to detect the contributions of different types of immune cells in lung tissues of mice in the VILI group. By using DrugBank, small molecular compounds that could potentially interact with hub genes were identified. Results: A total of 141 DEGs between the VILI group and the control were identified in GSE11434. Then, seven hub genes were identified and were validated by using qRT-PCR. Those seven hub genes were largely enriched in TLR and JAK-STAT signaling pathways. GSEA showed that VILI-associated genes were also enriched in NOD, antigen presentation, and chemokine pathways. We predicted the miRNAs and TFs associated with hub genes and constructed miRNA-TF-gene regulatory network. An analysis with CIBERSORT showed that the proportion of M0 macrophages and activated mast cells was higher in the VILI group than in the control. Small molecules, like nadroparin and siltuximab, could act as potential drugs for VILI. Conclusion: In sum, a number of hub genes associated with VILI were identified and could provide novel insights into the pathogenesis of VILI and potential targets for its treatment.

Abstract: Background: Diminished ovarian reserve (DOR) significantly increases the risk of female infertility and contributes to reproductive technology failure. Recently, the role of melatonin in improving ovarian reserve (OR) has attracted widespread attention. However, details on the pharmacological targets and mechanisms of melatonin-improved OR remain unclear. Objective: A systems pharmacology strategy was proposed to elucidate the potential therapeutic mechanism of melatonin on DOR at the molecular, pathway, and network levels. Methods: The systems pharmacological approach consisted of target identification, data integration, network construction, bioinformatics analysis, and molecular docking. Results: From the molecular perspective, 26 potential therapeutic targets were identified. They participate in biological processes related to DOR development, such as reproductive structure development, epithelial cell proliferation, extrinsic apoptotic signaling pathway, PI3K signaling, among others. Eight hub targets (MAPK1, AKT1, EGFR, HRAS, SRC, ESR1, AR, and ALB) were identified. From the pathway level, 17 significant pathways, including the PI3K-Akt signaling pathway and the estrogen signaling pathway, were identified. In addition, the 17 signaling pathways interacted with the 26 potential therapeutic targets to form 4 functional modules. From the network point of view, by regulating five target subnetworks (aging, cell growth and death, development and regeneration, endocrine and immune systems), melatonin could exhibit anti-aging, anti-apoptosis, endocrine, and immune system regulation effects. The molecular docking results showed that melatonin bound well to all hub targets. Conclusion: This study systematically and intuitively illustrated the possible pharmacological mechanisms of OR improvement by melatonin through anti-aging, anti-apoptosis, endocrine, and immune system regulation effects.

Abstract: Carcinogenicity testing plays an essential role in identifying carcinogens in environmental chemistry and drug development. However, it is a time-consuming and label-intensive process to evaluate the carcinogenic potency with conventional 2-years rodent animal studies. Thus, there is an urgent need for alternative approaches to providing reliable and robust assessments on carcinogenicity. In this study, we proposed a DeepCarc model to predict carcinogenicity for small molecules using deep learning-based model-level representations. The DeepCarc Model was developed using a data set of 692 compounds and evaluated on a test set containing 171 compounds in the National Center for Toxicological Research liver cancer database (NCTRlcdb). As a result, the proposed DeepCarc model yielded a Matthews correlation coefficient (MCC) of 0.432 for the test set, outperforming four advanced deep learning (DL) powered quantitative structure-activity relationship (QSAR) models with an average improvement rate of 37%. Furthermore, the DeepCarc model was also employed to screen the carcinogenicity potential of the compounds from both DrugBank and Tox21. Altogether, the proposed DeepCarc model could serve as an early detection tool (https://github.com/TingLi2016/DeepCarc) for carcinogenicity assessment.

Abstract: Background: Tingli Dazao Xiefei decoction (TDXD) has been shown to have a therapeutic effect on heart failure (HF). Nevertheless, its molecular mechanism for treating HF is still unclear. Materials and Methods: TDXD and HF targets were collected from the databases, and protein-protein interaction (PPI) analysis and enrichment analysis were performed on the overlapping targets. Then, AutoDock was employed for molecular docking. Finally, we used the left anterior descending coronary artery (LAD) ligation to induce HF model rats for in vivo experiments and verified the effect and mechanism of TDXD on HF. Results: Network pharmacological analysis showed that the main active components of TDXD in treating HF were quercetin, kaempferol, beta-carotene, isorhamnetin, and beta-sitosterol, and the core targets were IL-6, VEGFA, TNF, AKT1, and MAPK1. Multiple gene functions and signaling pathways were obtained by enrichment analysis, among which inflammation-related, PI3K/Akt, and MAPK signaling pathways were closely related to HF. Furthermore, the molecular docking results showed that the core targets had good binding ability with the main active components. Animal experiments showed that TDXD could effectively improve left ventricular ejection fraction (EF) and left ventricular fractional shortening (FS), decrease left ventricular internal diastolic diameter (LVIDd) and left ventricular internal systolic diameter (LVIDs), reduce the area of myocardial fibrosis, and decrease serum BNP, LDH, CK-MB, IL-6, IL-1beta, and TNF-alpha levels in HF rats. Meanwhile, TDXD could upregulate the expression of Bcl-2, downregulate the expression of Bax, and reduce cardiomyocyte apoptosis. At the same time, it was verified that TDXD could significantly decrease the expression of PI3K, P-Akt, and P-MAPK. Captopril showed similar effects. Conclusions: Combining network pharmacological analysis and experimental validation, this study verified that TDXD could improve cardiac function and protect against cardiac injury by inhibiting the activation of PI3K/Akt and MAPK signaling pathways.