OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders

From GWASs toward Mechanistic Understanding with Case Studies in Dermatogenetics

Many human skin diseases result from the complex interplay of genetic and environmental mechanisms that are largely unknown. GWASs have yielded insight into the genetic aspect of complex disease by highlighting regions of the genome or specific genetic variants associated with disease. Leveraging this information to identify causal genes and cell types will provide insight into fundamental biology, inform diagnostics, and aid drug discovery. However, the etiological mechanisms from genetic variant to disease are still unestablished in most cases. There now exists an unprecedented wealth of data and computational methods for variant interpretation in a functional context. It can be challenging to decide where to start owing to a lack of consensus on the best way to identify causal genetic mechanisms. This article highlights 3 key aspects of genetic variant interpretation: prioritizing causal genes, cell types, and pathways. We provide a practical overview of the main methods and datasets, giving examples from recent atopic dermatitis studies to provide a blueprint for variant interpretation. A collection of resources, including brief description and links to the packages and web tools, is provided for researchers looking to start in silico follow-up genetic analysis of associated genetic variants.

A Combined Manual Annotation and Deep-Learning Natural Language Processing Study on Accurate Entity Extraction in Hereditary Disease Related Biomedical Literature

We report a combined manual annotation and deep-learning natural language processing study to make accurate entity extraction in hereditary disease related biomedical literature. A total of 400 full articles were manually annotated based on published guidelines by experienced genetic interpreters at Beijing Genomics Institute (BGI). The performance of our manual annotations was assessed by comparing our re-annotated results with those publicly available. The overall Jaccard index was calculated to be 0.866 for the four entity types-gene, variant, disease and species. Both a BERT-based large name entity recognition (NER) model and a DistilBERT-based simplified NER model were trained, validated and tested, respectively. Due to the limited manually annotated corpus, Such NER models were fine-tuned with two phases. The F1-scores of BERT-based NER for gene, variant, disease and species are 97.28%, 93.52%, 92.54% and 95.76%, respectively, while those of DistilBERT-based NER are 95.14%, 86.26%, 91.37% and 89.92%, respectively. Most importantly, the entity type of variant has been extracted by a large language model for the first time and a comparable F1-score with the state-of-the-art variant extraction model tmVar has been achieved.

Material basis and pharmacodynamic mechanism of YangshenDingzhi granules in the intervention of viral pneumonia: Based on serum pharmacochemistry and network pharmacology

BACKGROUND

YangshenDingzhi granules (YSDZ) are clinically effective in preventing and treating COVID-19. The present study elucidates the underlying mechanism of YSDZ intervention in viral pneumonia by employing serum pharmacochemistry and network pharmacology.

METHODS

The chemical constituents of YSDZ in the blood were examined using ultra-performance liquid chromatography-quadrupole/orbitrap high-resolution mass spectrometry (UPLC-Q-Exactive Orbitrap MS). Potential protein targets were obtained from the SwissTargetPrediction database, and the target genes associated with viral pneumonia were identified using GeneCards, DisGeNET, and Online Mendelian Inheritance in Man (OMIM) databases. The intersection of blood component-related targets and disease-related targets was determined using Venny 2.1. Protein-protein interaction networks were constructed using the STRING database. The Metascape database was employed to perform enrichment analyses of Gene Ontology (GO) functions and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways for the targets, while the Cytoscape 3.9.1 software was utilized to construct drug-component-disease-target-pathway networks. Further, in vitro and in vivo experiments were performed to establish the therapeutic effectiveness of YSDZ against viral pneumonia.

RESULTS

Fifteen compounds and 124 targets linked to viral pneumonia were detected in serum. Among these, MAPK1, MAPK3, AKT1, EGFR, and TNF play significant roles. In vitro tests revealed that the medicated serum suppressed the replication of H1N1, RSV, and SARS-CoV-2 replicon. Further, in vivo testing analysis shows that YSDZ decreases the viral load in the lungs of mice infected with RSV and H1N1.

CONCLUSION

The chemical constituents of YSDZ in the blood may elicit therapeutic effects against viral pneumonia by targeting multiple proteins and pathways.

Scutellarin alleviates microglia-mediated neuroinflammation and apoptosis after ischemic stroke through the PI3K/AKT/GSK3β signaling pathway

Microglia are resident immune cells in the central nervous system that are rapidly activated to mediate neuroinflammation and apoptosis, thereby aggravating brain tissue damage after ischemic stroke (IS). Although scutellarin has a specific therapeutic effect on IS, the potential target mechanism of its treatment has not been fully elucidated. In this study, we explored the potential mechanism of scutellarin in treating IS using network pharmacology. Lipopolysaccharide (LPS) was used to induce an in vitro BV-2 microglial cell model, while middle cerebral artery occlusion (MCAO) was used to induce an in vivo animal model. Our findings indicated that scutellarin promoted the recovery of cerebral blood flow in MCAO rats at 3 days, significantly different from that in the MCAO group. Western blotting and immunofluorescence revealed that scutellarin treatment of BV-2 microglial cells resulted in a significant reduction in the protein expression levels and incidence of cells immunopositive for p-NF-κB, TNF-α, IL-1β, Bax, and C-caspase-3. In contrast, the expression levels of p-PI3K, p-AKT, p-GSK3β, and Bcl-2 were further increased, significantly different from those in the LPS group. The PI3K inhibitor LY294002 had similar effects to scutellarin by inhibiting neuroinflammation and apoptosis in activated microglia. The results of the PI3K/AKT/GSK3β signaling pathway and NF-κB pathway in vivo in MCAO models induced microglia at 3 days were consistent with those obtained from in vitro cells. These findings indicate that scutellarin plays a neuroprotective role by reducing microglial neuroinflammation and apoptosis mediated by the activated PI3K/AKT/GSK3β/NF-κB signaling pathway.

TCMSSD: A comprehensive database focused on syndrome standardization

BACKGROUD

Quantitative and standardized research on syndrome differentiation has always been at the forefront of modernizing Traditional Chinese Medicine (TCM) theory. However, the majority of existing databases primarily concentrate on the network pharmacology of herbal prescriptions, and there are limited databases specifically dedicated to TCM syndrome differentiation.

PURPOSE

In response to this gap, we have developed the Traditional Chinese Medical Syndrome Standardization Database (TCMSSD, http://tcmssd.ratcm.cn).

METHODS

TCMSSD is a comprehensive database that gathers data from various sources, including TCM literature such as TCM Syndrome Studies (Zhong Yi Zheng Hou Xue) and TCM Internal Medicine (Zhong Yi Nei Ke Xue) and various public databases such as TCMID and ETCM. In our study, we employ a deep learning approach to construct the knowledge graph and utilize the BM25 algorithm for syndrome prediction.

RESULTS

The TCMSSD integrates the essence of TCM with the modern medical system, providing a comprehensive collection of information related to TCM. It includes 624 syndromes, 133,518 prescriptions, 8,073 diseases (including 1,843 TCM-specific diseases), 8,259 Chinese herbal medicines, 43,413 ingredients, 17,602 targets, and 8,182 drugs. By analyzing input data and comparing it with the patterns and characteristics recorded in the database, the syndrome prediction tool generates predictions based on established correlations and patterns.

CONCLUSION

The TCMSSD fills the gap in existing databases by providing a comprehensive resource for quantitative and standardized research on TCM syndrome differentiation and laid the foundation for research on the biological basis of syndromes.

Potential immune-related therapeutic mechanisms of multiple traditional Chinese medicines on type 2 diabetic nephropathy based on bioinformatics, network pharmacology and molecular docking

BACKGROUND

The prevalence of type 2 diabetic nephropathy (T2DN) ranges from 20 % to 40 % among individuals with type 2 diabetes. Multiple immune pathways play a pivotal role in the pathogenesis of T2DN. This study aimed to investigate the immunomodulatory effects of active ingredients derived from 14 traditional Chinese medicines (TCMs) on T2DN.

METHODS

By removing batch effect on the GSE30528 and GSE96804 datasets, we employed a combination of weighted gene co-expression network analysis, least absolute shrinkage and selection operator analysis, protein-protein interaction network analysis, and the CIBERSORT algorithm to identify the active ingredients of TCMs as well as potential hub biomarkers associated with immune cells. Functional analysis was conducted using Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and gene set variation analysis (GSVA). Additionally, molecular docking was employed to evaluate interactions between active ingredients and potential immunotherapy targets.

RESULTS

A total of 638 differentially expressed genes (DEGs) were identified in this study, comprising 5 hub genes along with 4 potential biomarkers. Notably, CXCR1, CXCR2, and FOS exhibit significant associations with immune cells while displaying robust or favorable affinities towards the active ingredients kaempferol, quercetin, and luteolin. Furthermore, functional analysis unveiled intricate involvement of DEGs, hub genes and potential biomarkers in pathways closely linked to immunity and diabetes.

CONCLUSION

The potential hub biomarkers and immunotherapy targets associated with immune cells of T2DN comprise CXCR1, CXCR2, and FOS. Furthermore, kaempferol, quercetin, and luteolin demonstrate potential immunomodulatory effects in modulating T2DN through the regulation of CXCR1, CXCR2, and FOS expression.

Ancient eukaryotic protein interactions illuminate modern genetic traits and disorders

All eukaryotes share a common ancestor from roughly 1.5 - 1.8 billion years ago, a single-celled, swimming microbe known as LECA, the Last Eukaryotic Common Ancestor. Nearly half of the genes in modern eukaryotes were present in LECA, and many current genetic diseases and traits stem from these ancient molecular systems. To better understand these systems, we compared genes across modern organisms and identified a core set of 10,092 shared protein-coding gene families likely present in LECA, a quarter of which are uncharacterized. We then integrated >26,000 mass spectrometry proteomics analyses from 31 species to infer how these proteins interact in higher-order complexes. The resulting interactome describes the biochemical organization of LECA, revealing both known and new assemblies. We analyzed these ancient protein interactions to find new human gene-disease relationships for bone density and congenital birth defects, demonstrating the value of ancestral protein interactions for guiding functional genetics today.

Mutational landscape of risk variants in comorbid depression and obesity: a next-generation sequencing approach

Major depression (MD) and obesity are complex genetic disorders that are frequently comorbid. However, the study of both diseases concurrently remains poorly addressed and therefore the underlying genetic mechanisms involved in this comorbidity remain largely unknown. Here we examine the contribution of common and rare variants to this comorbidity through a next-generation sequencing (NGS) approach. Specific genomic regions of interest in MD and obesity were sequenced in a group of 654 individuals from the PISMA-ep epidemiological study. We obtained variants across the entire frequency spectrum and assessed their association with comorbid MD and obesity, both at variant and gene levels. We identified 55 independent common variants and a burden of rare variants in 4 genes (PARK2, FGF21, HIST1H3D and RSRC1) associated with the comorbid phenotype. Follow-up analyses revealed significantly enriched gene-sets associated with biological processes and pathways involved in metabolic dysregulation, hormone signaling and cell cycle regulation. Our results suggest that, while risk variants specific to the comorbid phenotype have been identified, the genes functionally impacted by the risk variants share cell biological processes and signaling pathways with MD and obesity phenotypes separately. To the best of our knowledge, this is the first study involving a targeted sequencing approach toward the study of the comorbid MD and obesity. The framework presented here allowed a deep characterization of the genetics of the co-occurring MD and obesity, revealing insights into the mutational and functional profile that underlies this comorbidity and contributing to a better understanding of the relationship between these two disabling disorders.

Genome-first evaluation with exome sequence and clinical data uncovers underdiagnosed genetic disorders in a large healthcare system

Population-based genomic screening may help diagnose individuals with disease-risk variants. Here, we perform a genome-first evaluation for nine disorders in 29,039 participants with linked exome sequences and electronic health records (EHRs). We identify 614 individuals with 303 pathogenic/likely pathogenic or predicted loss-of-function (P/LP/LoF) variants, yielding 644 observations; 487 observations (76%) lack a corresponding clinical diagnosis in the EHR. Upon further investigation, 75 clinically undiagnosed observations (15%) have evidence of symptomatic untreated disease, including familial hypercholesterolemia (3 of 6 [50%] undiagnosed observations with disease evidence) and breast cancer (23 of 106 [22%]). These genetic findings enable targeted phenotyping that reveals new diagnoses in previously undiagnosed individuals. Disease yield is greater with variants in penetrant genes for which disease is observed in carriers in an independent cohort. The prevalence of P/LP/LoF variants exceeds that of clinical diagnoses, and some clinically undiagnosed carriers are discovered to have disease. These results highlight the potential of population-based genomic screening.

Genetic variants for head size share genes and pathways with cancer

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.

Network pharmacology combined with lipidomics to reveal the regulatory effects and mechanisms of Kangzao granules in the hypothalamus of rats with central precocious puberty

Central precocious puberty (CPP) is a prevalent endocrine disorder that primarily affects children, specifically females, and is associated with various physical and psychological complications. Although Kangzao granules (KZG) are efficacious in managing CPP, the underlying mechanisms remain unclear. Therefore, this study aimed to elucidate the therapeutic mechanisms of KZG using network pharmacology, molecular docking, pharmacodynamics, and pathway validation. A putative compound-target-pathway network was constructed using Cytoscape, before KEGG and Gene Ontology enrichment analyses were conducted. Moreover, molecular docking was performed using AutoDockTools. Quality control of the 10 key components of KZG was carried out using UHPLC-ESI/LTQ-Orbitrap-MS/MS, and hypothalamic lipids were analyzed using UHPLC-Q-Exactive Orbitrap MS/MS. In total, 87 bioactive compounds that targeting 110 core proteins to alleviate CPP were identified in KZG. Lipidomic analysis revealed 18 differential lipids among the CPP, KZG, and control groups, wherein fatty acids were significantly reduced in the model group; however, these changes were effectively counteracted by KZG treatment. Molecular docking analysis revealed a strong binding affinity between flavonoids and RAC-alpha serine/threonine-protein kinase (AKT) when docked into the crystal structure. Moreover, a substantial disruption in lipid metabolism was observed in the model group; however, treatment with KZG efficiently reversed these alterations. Furthermore, the phosphoinositide 3-kinase/AKT signaling pathway was identified as a pivotal regulator of hypothalamic lipid metabolism regulator. Overall, this study highlights the effectiveness of a multidisciplinary approach that combines network pharmacology, lipidomics, molecular docking, and experimental validation in the elucidation of the therapeutic mechanisms of KZG in CPP treatment.

DDCM: A Computational Strategy for Drug Repositioning Based on Support-Vector Regression Algorithm

Computational drug-repositioning technology is an effective tool for speeding up drug development. As biological data resources continue to grow, it becomes more important to find effective methods to identify potential therapeutic drugs for diseases. The effective use of valuable data has become a more rational and efficient approach to drug repositioning. The disease-drug correlation method (DDCM) proposed in this study is a novel approach that integrates data from multiple sources and different levels to predict potential treatments for diseases, utilizing support-vector regression (SVR). The DDCM approach resulted in potential therapeutic drugs for neoplasms and cardiovascular diseases by constructing a correlation hybrid matrix containing the respective similarities of drugs and diseases, implementing the SVR algorithm to predict the correlation scores, and undergoing a randomized perturbation and stepwise screening pipeline. Some potential therapeutic drugs were predicted by this approach. The potential therapeutic ability of these drugs has been well-validated in terms of the literature, function, drug target, and survival-essential genes. The method's feasibility was confirmed by comparing the predicted results with the classical method and conducting a co-drug analysis of the sub-branch. Our method challenges the conventional approach to studying disease-drug correlations and presents a fresh perspective for understanding the pathogenesis of diseases.

The Approach to a Child with Dysmorphic Features: What the Pediatrician Should Know

The advancement of genetic knowledge and the discovery of an increasing number of genetic disorders has made the role of the geneticist progressively more complex and fundamental. However, most genetic disorders present during childhood; thus, their early recognition is a challenge for the pediatrician, who will be also involved in the follow-up of these children, often establishing a close relationship with them and their families and becoming a referral figure. In this review, we aim to provide the pediatrician with a general knowledge of the approach to treating a child with a genetic syndrome associated with dysmorphic features. We will discuss the red flags, the most common manifestations, the analytic collection of the family and personal medical history, and the signs that should alert the pediatrician during the physical examination. We will offer an overview of the physical malformations most commonly associated with genetic defects and the way to describe dysmorphic facial features. We will provide hints about some tools that can support the pediatrician in clinical practice and that also represent a useful educational resource, either online or through apps downloaded on a smartphone. Eventually, we will offer an overview of genetic testing, the ethical considerations, the consequences of incidental findings, and the main indications and limitations of the principal technologies.

Multi-technology integrated network pharmacology-based study on phytochemicals, active metabolites, and molecular mechanism of Psoraleae Fructus to promote melanogenesis

ETHNOPHARMACOLOGICAL RELEVANCE

According to the Compendium of Materia Medica (Shizhen Li, Ming dynasty) and Welfare Pharmacy (Song dynasty), Psoraleae Fructus (PF), a traditional Chinese medicine (TCM) has a bitter taste and warm nature, which has the effect of treating spleen and kidney deficiency and skin disease. Although PF has been widely used since ancient times and has shown satisfactory efficacy in treating vitiligo, the active substances and the mechanism of PF in promoting melanogenesis remain unclear.

AIM OF THE STUDY

To explore the active substances and action mechanisms of PF in promoting melanogenesis.

MATERIALS AND METHODS

Firstly, UPLC-UV-Q-TOF/MS was used to characterize the components in PF extract and identify the absorption components and metabolites of PF after oral administration at usual doses in rats. Secondly, the active substances and related targets and pathways were predicted by network pharmacology and molecular docking. Finally, pharmacodynamic and molecular biology experiments were used to verify the prediction results.

RESULTS

The experimental results showed that 15 compounds were identified in PF extract, and 44 compounds, consisting of 8 prototype components and 36 metabolites (including isomers) were identified in rats' plasma. Promising action targets (MAPK1, MAPK8, MAPK14) and signaling pathways (MAPK signaling pathway) were screened and refined to elucidate the mechanism of PF against vitiligo based on network pharmacology. Bergaptol and xanthotol (the main metabolites of PF), psoralen (prototype drug), and PF extract significantly increased melanin production in zebrafish embryos. Furthermore, bergaptol could promote the pigmentation of zebrafish embryos more than psoralen and PF extract. Bergaptol significantly increased the protein expression levels of p-P38 and decreased ERK phosphorylation in B16F10 cells, which was also supported by the corresponding inhibitor/activator combination study. Moreover, bergaptol increased the mRNA expression levels of the downstream microphthalmia-associated transcription factor (MITF) and tyrosinase in B16F10 cells. Our data elucidate that bergaptol may promote melanogenesis by regulating the p-P38 and p-ERK signaling pathway.

CONCLUSIONS

This study will lay a foundation for discovering potential new drugs for treating vitiligo and provide feasible ideas for exploring the mechanism of traditional Chinese medicine.

Preliminary Exploration of Potential Active Ingredients and Molecular Mechanisms of Yanggan Yishui Granules for Treating Hypertensive Nephropathy Using UPLC-Q-TOF/MS Coupled with Network Pharmacology and Molecular Docking Strategy

Hypertensive nephropathy (HN) is a prevalent complication of hypertension and stands as the second primary reason for end-stage renal disease. Research in clinical settings has revealed that Yanggan Yishui Granule (YGYSG) has significant therapeutic effects on HN. However, the material basis and action mechanisms of YGYSG against HN remain unclear. Consequently, this study utilized a comprehensive method integrating ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS), network pharmacology, and molecular docking to delineate the active ingredients and potential therapeutic mechanisms of YGYSG for treating HN. Firstly, sixty distinct components were recognized in total as potential active ingredients in YGYSG by UPLC-Q-TOF/MS. Subsequently, the mechanisms of YGYSG against HN were revealed for the first time using network pharmacology. 23 ingredients played key roles in the complete network and were the key active ingredients, which could affect the renin-angiotensin system, fluid shear stress and atherosclerosis, HIF-1 signaling pathway, and AGE-RAGE signaling pathway in diabetic complications by regulating 29 key targets such as TNF, IL6, ALB, EGFR, ACE, and MMP2. YGYSG could treat HN through the suppression of inflammatory response and oxidative stress, attenuating the proliferation of renal vascular smooth muscle cells, lessening glomerular capillary systolic pressure, and ameliorating renal dysfunction and vascular damage through the aforementioned targets and pathways. Molecular docking results revealed that most key active ingredients exhibited a high affinity for binding to the key targets. This study pioneers in clarifying the bioactive compounds and molecular mechanisms of YGYSG against HN and offers scientific reference into the clinical application.

Lysophosphatidylserine: A Signaling Lipid with Implications in Human Diseases

Lysophosphatidylserine (lyso-PS) has emerged as yet another important signaling lysophospholipid in mammals, and deregulation in its metabolism has been directly linked to an array of human autoimmune and neurological disorders. It has an indispensable role in several biological processes in humans, and therefore, cellular concentrations of lyso-PS are tightly regulated to ensure optimal signaling and functioning in physiological settings. Given its biological importance, the past two decades have seen an explosion in the available literature toward our understanding of diverse aspects of lyso-PS metabolism and signaling and its association with human diseases. In this Review, we aim to comprehensively summarize different aspects of lyso-PS, such as its structure, biodistribution, chemical synthesis, and SAR studies with some synthetic analogs. From a biochemical perspective, we provide an exhaustive coverage of the diverse biological activities modulated by lyso-PSs, such as its metabolism and the receptors that respond to them in humans. We also briefly discuss the human diseases associated with aberrant lyso-PS metabolism and signaling and posit some future directions that may advance our understanding of lyso-PS-mediated mammalian physiology.

Exome sequencing implicates ancestry-related Mendelian variation at SYNE1 in childhood-onset essential hypertension

Childhood-onset essential hypertension (COEH) is an uncommon form of hypertension that manifests in childhood or adolescence and, in the United States, disproportionately affects children of African ancestry. The etiology of COEH is unknown, but its childhood onset, low prevalence, high heritability, and skewed ancestral demography suggest the potential to identify rare genetic variation segregating in a Mendelian manner among affected individuals and thereby implicate genes important to disease pathogenesis. However, no COEH genes have been reported to date. Here, we identify recessive segregation of rare and putatively damaging missense variation in the spectrin domain of spectrin repeat containing nuclear envelope protein 1 (SYNE1), a cardiovascular candidate gene, in 3 of 16 families with early-onset COEH without an antecedent family history. By leveraging exome sequence data from an additional 48 COEH families, 1,700 in-house trios, and publicly available data sets, we demonstrate that compound heterozygous SYNE1 variation in these COEH individuals occurred more often than expected by chance and that this class of biallelic rare variation was significantly enriched among individuals of African genetic ancestry. Using in vitro shRNA knockdown of SYNE1, we show that reduced SYNE1 expression resulted in a substantial decrease in the elasticity of smooth muscle vascular cells that could be rescued by pharmacological inhibition of the downstream RhoA/Rho-associated protein kinase pathway. These results provide insights into the molecular genetics and underlying pathophysiology of COEH and suggest a role for precision therapeutics in the future.

Pathway-based, reaction-specific annotation of disease variants for elucidation of molecular phenotypes

Germline and somatic mutations can give rise to proteins with altered activity, including both gain and loss-of-function. The effects of these variants can be captured in disease-specific reactions and pathways that highlight the resulting changes to normal biology. A disease reaction is defined as an aberrant reaction in which a variant protein participates. A disease pathway is defined as a pathway that contains a disease reaction. Annotation of disease variants as participants of disease reactions and disease pathways can provide a standardized overview of molecular phenotypes of pathogenic variants that is amenable to computational mining and mathematical modeling. Reactome (https://reactome.org/), an open source, manually curated, peer-reviewed database of human biological pathways, in addition to providing annotations for >11 000 unique human proteins in the context of ∼15 000 wild-type reactions within more than 2000 wild-type pathways, also provides annotations for >4000 disease variants of close to 400 genes as participants of ∼800 disease reactions in the context of ∼400 disease pathways. Functional annotation of disease variants proceeds from normal gene functions, described in wild-type reactions and pathways, through disease variants whose divergence from normal molecular behaviors has been experimentally verified, to extrapolation from molecular phenotypes of characterized variants to variants of unknown significance using criteria of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Reactome's data model enables mapping of disease variant datasets to specific disease reactions within disease pathways, providing a platform to infer pathway output impacts of numerous human disease variants and model organism orthologs, complementing computational predictions of variant pathogenicity. Database URL: https://reactome.org/.

Potential mechanisms of traditional Chinese medicine in treating insomnia: A network pharmacology, GEO validation, and molecular-docking study

The purpose of this study is to investigate the potential mechanisms of Chinese herbs for the treatment of insomnia using a combination of data mining, network pharmacology, and molecular-docking validation. All the prescriptions for insomnia treated by the academician Qi Wang from 2020 to 2022 were collected. The Ancient and Modern Medical Case Cloud Platform v2.3 was used to identify high-frequency Chinese medicinal herbs and the core prescription. The Traditional Chinese Medicine Systems Pharmacology and UniProt databases were utilized to predict the effective active components and targets of the core herbs. Insomnia-related targets were collected from 4 databases. The intersecting targets were utilized to build a protein-protein interaction network and conduct gene ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis using the STRING database, Cytoscape software, and clusterProfiler package. Gene chip data (GSE208668) were obtained from the Gene Expression Omnibus database. The limma package was applied to identify differentially expressed genes (DEGs) between insomnia patients and healthy controls. To create a "transcription factor (TF)-miRNA-mRNA" network, the differentially expressed miRNAs were entered into the TransmiR, FunRich, Targetscan, and miRDB databases. Subsequently, the overlapping targets were validated using the DEGs, and further validations were conducted through molecular docking and molecular dynamics simulations. Among the 117 prescriptions, 65 herbs and a core prescription were identified. Network pharmacology and bioinformatics analysis revealed that active components such as β-sitosterol, stigmasterol, and canadine acted on hub targets, including interleukin-6, caspase-3, and hypoxia-inducible factor-1α. In GSE208668, 6417 DEGs and 7 differentially expressed miRNAs were identified. A "TF-miRNA-mRNA" network was constructed by 4 "TF-miRNA" interaction pairs and 66 "miRNA-mRNA" interaction pairs. Downstream mRNAs exert therapeutic effects on insomnia by regulating circadian rhythm. Molecular-docking analyses demonstrated good docking between core components and hub targets. Molecular dynamics simulation displayed the strong stability of the complex formed by small molecule and target. The core prescription by the academician Qi Wang for treating insomnia, which involves multiple components, targets, and pathways, showed the potential to improve sleep, providing a basis for clinical treatment of insomnia.

Broussonin E against acute respiratory distress syndrome: the potential roles of anti-inflammatory

We applied network pharmacology and molecular docking analyses to study the efficacy of Broussonin E (BRE) in acute respiratory distress syndrome (ARDS) treatment and to determine the core components, potential targets, and mechanism of action of BRE. The SwissTargetprediction and SEA databases were used to predict BRE targets, and the GeneCards and OMIM databases were used to predict ARDS-related genes. The drug targets and disease targets were mapped to obtain an intersecting drug target gene network, which was then uploaded into the String database for protein-protein interaction network analysis. The intersecting gene was also uploaded into the DAVID database for gene ontology enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis. Molecular docking analysis was performed to verify the interaction of BRE with the key targets. Finally, to validate the experiment in vivo, we established an oleic acid-induced ARDS rat model and evaluated the protective effect of BRE on ARDS by histological evaluation and enzyme-linked immunosorbent assay. Overall, 79 targets of BRE and 3974 targets of ARDS were predicted, and 79 targets were obtained after intersection. Key genes such as HSP90AA1, JUN, ESR1, MTOR, and PIK3CA play important roles in the nucleus and cytoplasm by regulating the tumor necrosis factor, nuclear factor-κB, and PI3K-Akt signaling pathways. Molecular docking results showed that small molecules of BRE could freely bind to the active site of the target proteins. In vivo experiments showed that BRE could reduce ARDS-related histopathological changes, release of inflammatory factors, and infiltration of macrophages and oxidative stress reaction. BRE exerts its therapeutic effect on ARDS through target and multiple pathways. This study also predicted the potential mechanism of BRE on ARDS, which provides the theoretical basis for in-depth and comprehensive studies of BRE treatment on ARDS.

Somatic variants as a cause of drug-resistant epilepsy including mesial temporal lobe epilepsy with hippocampal sclerosis

OBJECTIVE

The contribution of somatic variants to epilepsy has recently been demonstrated, particularly in the etiology of malformations of cortical development. The aim of this study was to determine the diagnostic yield of somatic variants in genes that have been previously associated with a somatic or germline epilepsy model, ascertained from resected brain tissue from patients with multidrug-resistant focal epilepsy.

METHODS

Forty-two patients were recruited across three categories: (1) malformations of cortical development, (2) mesial temporal lobe epilepsy with hippocampal sclerosis, and (3) nonlesional focal epilepsy. Participants were subdivided based on histopathology of the resected brain. Paired blood- and brain-derived DNA samples were sequenced using high-coverage targeted next generation sequencing to high depth (585× and 1360×, respectively). Variants were identified using Genome Analysis ToolKit (GATK4) MuTect-2 and confirmed using high-coverage Amplicon-EZ sequencing.

RESULTS

Sequence data on 41 patients passed quality control. Four somatic variants were validated following amplicon sequencing: within CBL, ALG13, MTOR, and FLNA. The diagnostic yield across 41 patients was 10%, 9% in mesial temporal lobe epilepsy with hippocampal sclerosis and 20% in malformations of cortical development.

SIGNIFICANCE

This study provides novel insights into the etiology of mesial temporal lobe epilepsy with hippocampal sclerosis, highlighting a potential pathogenic role of somatic variants in CBL and ALG13. We also report candidate diagnostic somatic variants in FLNA in focal cortical dysplasia, while providing further insight into the importance of MTOR and related genes in focal cortical dysplasia. This work demonstrates the potential molecular diagnostic value of variants in both germline and somatic epilepsy genes.

Data from electronic healthcare records expand our understanding of X-linked genetic diseases

Disease specific cohort studies have reported details on X linked (XL) disorders affecting females. We investigated the spectrum and penetrance of XL disorders seen in electronic health records (EHR). We generated a cohort of individuals diagnosed with XL disorders at Vanderbilt University Medical Center over 20 years. Our cohort included 477 males and 203 females diagnosed with 108 different XL genetic disorders. We found large differences between the female/male (F/M) ratios for various XL disorders regardless of their OMIM annotated mode of inheritance. We identified four XL recessive disorders affecting women previously only described in men. Biomarkers for XL disease had unique gender-specific patterns differing between modes of inheritance. EHRs provide large cohorts of XL genetic disorders that give new insights compared to the literature. Differences in the F/M ratios and biomarkers of XL disorders observed likely result from disease specific and sex dependent penetrance. We conclude that observed gender ratios associated with specific XL disorders may be more useful than those predicted by Mendelian genetics provided by OMIM. Our findings of a gender specific penetrance and severity for XL disorders show unexpected differences from Mendelian predictions. Further work is required to validate our findings in larger combined EHR cohorts.

Wogonin inhibits the migration and invasion of fibroblast-like synoviocytes by targeting PI3K/AKT/NF-κB pathway in rheumatoid arthritis

BACKGROUND

Rheumatoid arthritis (RA) is currently an autoimmune inflammatory disease with an unclear pathogenesis. Fibroblast-like synoviocytes (FLSs) have tumor-like properties, and their activation and secretion of pro-inflammatory factors are important factors in joint destruction. Wogonin (5,7-dihydroxy-8-methoxyflavone), a natural flavonoid isolated from Scutellaria baicalensis root, has been shown to have significant anti-inflammatory, anti-oxidative stress, and anti-tumor effects in a variety of diseases. However, the role of wogonin in RA has not yet been demonstrated.

PURPOSE

To investigate the inhibitory effect of wogonin on the invasive behavior of fibroblast-like synoviocytes and to explore the mechanism of action of wogonin in RA.

METHODS

CCK-8, EdU, cell migration and invasion, immunofluorescence staining, RT-qPCR, and protein blot analysis were used to study the inhibitory effects of wogonin on migration, invasion, and pro-inflammatory cytokine overexpression in the immortalized rheumatoid synovial cell line MH7A. The therapeutic effects of wogonin were validated in vivo using arthritis scores and histopathological evaluation of collagen-induced arthritis mice.

RESULTS

Wogonin inhibited the migration and invasion of MH7A cells, reduced the production of TNF-α, IL-1β, IL-6, MMP-3 and MMP-9, and increased the expression of IL-10. Moreover, wogonin also inhibited the myofibrillar differentiation of MH7A cells, increased the expression of E-cadherin (E-Cad) and decreased the expression of α-smooth muscle actin (α-SMA). In addition, wogonin treatment effectively ameliorated joint destruction in CIA mice. Further molecular mechanism studies showed that wogonin treatment significantly inhibited the activation of PI3K/AKT/NF-κB signaling pathway in TNF-α-induced arthritic FLSs.

CONCLUSION

Wogonin effectively inhibits migration, invasion and pro-inflammatory cytokine production of RA fibroblast-like synoviocytes through the PI3K/AKT/NF-κB pathway, and thus wogonin, as a natural flavonoid, has great potential for treating RA.

Wide metabolite coverage LC-MS/MS assay for the diagnosis of inherited metabolic disorders in urine

OBJECTIVE

The laboratory diagnosis of inherited metabolic disorders (IMD) has undergone significant development in recent decades, mainly due to the use of mass spectrometry, which allows rapid multicomponent analysis of a wide range of metabolites. Combined with advanced software tools, the diagnosis becomes more efficient as a benefit for both physicians and patients.

METHODS

A hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry assay for determination of urinary purines, pyrimidines, N-acylglycines, N-acetylated amino acids, sugars, sugar alcohols and other diagnostically important biomarkers was developed and validated. Evaluation of the results consisting of utilisation of robust scaling and advanced visualization tools is simple and even suitable for urgent requirements.

RESULTS

The developed method, covering 65 biomarkers, provides a comprehensive diagnostic platform for 51 IMD. For most analytes, linearity with R2 > 0.99, intra and inter-day accuracy between 80 and 120 % and precision lower than 20 % were achieved. Diagnostic workflow was evaluated on 47 patients and External Quality Assurance samples involving a total of 24 different IMD. Over seven years, more than 2300 urine samples from patients suspected for IMD have been routinely analysed.

CONCLUSIONS

This method offers the advantage of a broad coverage of intermediate metabolites of interest and therefore may be a potential alternative and simplification for clinical laboratories that use multiple methods for screening these markers.

Beyond the kidney: extra-renal manifestations of monogenic nephrolithiasis and their significance

BACKGROUND

The objective of this study was to explore the frequency of occurrence of extra-renal manifestations associated with monogenic nephrolithiasis.

METHODS

A literature review was conducted to identify genes that are monogenic causes of nephrolithiasis. The Online Mendelian Inheritance in Man (OMIM) database was used to identify associated diseases and their properties. Disease phenotypes were ascertained using OMIM clinical synopses and sorted into 24 different phenotype categories as classified in OMIM. Disease phenotypes caused by the same gene were merged into a phenotypic profile of a gene (PPG) such that one PPG encompasses all related disease phenotypes for a specific gene. The total number of PPGs involving each phenotype category was measured, and the median phenotype category was determined. Phenotype categories were classified as overrepresented or underrepresented if the number of PPGs involving them was higher or lower than the median, respectively. Chi-square test was conducted to determine whether the number of PPGs affecting a given category significantly deviated from the median.

RESULTS

Fifty-five genes were identified as monogenic causes of nephrolithiasis. A total of six significantly overrepresented and three significantly underrepresented phenotype categories were identified (p < 0.05). Four phenotypic categories (growth, neurological, skeletal, and abdomen/gastrointestinal) are significantly overrepresented after Bonferroni correction for multiple comparisons (p < 0.002). Among all phenotypes, impaired growth is the most common manifestation.

CONCLUSION

Recognizing the extra-renal manifestations associated with monogenic causes of kidney stones is critical for earlier diagnosis and optimal care in patients.

Integrated Single-Cell Transcriptomic Atlas of Human Kidney Endothelial Cells

Key Points

We created a comprehensive reference atlas of normal human kidney endothelial cells. We confirmed that endothelial cell types in the human kidney were also highly conserved in the mouse kidney.

Background

Kidney endothelial cells are exposed to different microenvironmental conditions that support specific physiologic processes. However, the heterogeneity of human kidney endothelial cells has not yet been systematically described.

Methods

We reprocessed and integrated seven human kidney control single-cell/single-nucleus RNA sequencing datasets of >200,000 kidney cells in the same process.

Results

We identified five major cell types, 29,992 of which were endothelial cells. Endothelial cell reclustering identified seven subgroups that differed in molecular characteristics and physiologic functions. Mapping new data to a normal kidney endothelial cell atlas allows rapid data annotation and analysis. We confirmed that endothelial cell types in the human kidney were also highly conserved in the mouse kidney and identified endothelial marker genes that were conserved in humans and mice, as well as differentially expressed genes between corresponding subpopulations. Furthermore, combined analysis of single-cell transcriptome data with public genome-wide association study data showed a significant enrichment of endothelial cells, especially arterial endothelial cells, in BP heritability. Finally, we identified M1 and M12 from coexpression networks in endothelial cells that may be deeply involved in BP regulation.

Conclusions

We created a comprehensive reference atlas of normal human kidney endothelial cells that provides the molecular foundation for understanding how the identity and function of kidney endothelial cells are altered in disease, aging, and between species. Finally, we provide a publicly accessible online tool to explore the datasets described in this work (https://vascularmap.jiangnan.edu.cn ).

CNVoyant: A Highly Performant and Explainable Multi-Classifier Machine Learning Approach for Determining the Clinical Significance of Copy Number Variants

The precise classification of copy number variants (CNVs) presents a significant challenge in genomic medicine, primarily due to the complex nature of CNVs and their diverse impact on genetic disorders. This complexity is compounded by the limitations of existing methods in accurately distinguishing between benign, uncertain, and pathogenic CNVs. Addressing this gap, we introduce CNVoyant, a machine learning-based multi-class framework designed to enhance the clinical significance classification of CNVs. Trained on a comprehensive dataset of 52,176 ClinVar entries across pathogenic, uncertain, and benign classifications, CNVoyant incorporates a broad spectrum of genomic features, including genome position, disease-gene annotations, dosage sensitivity, and conservation scores. Models to predict the clinical significance of copy number gains and losses were trained independently. Final models were selected after testing 29 machine learning architectures and 10,000 hyperparameter combinations each for deletions and duplications via 5-fold cross-validation. We validate the performance of the CNVoyant by leveraging a comprehensive set of 21,574 CNVs from the DECIPHER database, a highly regarded resource known for its extensive catalog of chromosomal imbalances linked to clinical outcomes. Compared to alternative approaches, CNVoyant shows marked improvements in precision-recall and ROC AUC metrics for binary pathogenic classifications while going one step further, offering multi-classification of clinical significance and corresponding SHAP explainability plots. This large-scale validation demonstrates CNVoyant's superior accuracy and underscores its potential to aid genomic researchers and clinical geneticists in interpreting the clinical implications of real CNVs.

Novel Variants Linked to the Prodromal Stage of Parkinson's Disease (PD) Patients

BACKGROUND AND OBJECTIVE

The symptoms of most neurodegenerative diseases, including Parkinson's disease (PD), usually do not occur until substantial neuronal loss occurs. This makes the process of early diagnosis very challenging. Hence, this research used variant call format (VCF) analysis to detect variants and novel genes that could be used as prognostic indicators in the early diagnosis of prodromal PD.

MATERIALS AND METHODS

Data were obtained from the Parkinson's Progression Markers Initiative (PPMI), and we analyzed prodromal patients with gVCF data collected in the 2021 cohort. A total of 304 participants were included, including 100 healthy controls, 146 prodromal genetic individuals, 21 prodromal hyposmia individuals, and 37 prodromal individuals with RBD. A pipeline was developed to process the samples from gVCF to reach variant annotation and pathway and disease association analysis.

RESULTS

Novel variant percentages were detected in the analyzed prodromal subgroups. The prodromal subgroup analysis revealed novel variations of 1.0%, 1.2%, 0.6%, 0.3%, 0.5%, and 0.4% for the genetic male, genetic female, hyposmia male, hyposmia female, RBD male, and RBD female groups, respectively. Interestingly, 12 potentially novel loci (MTF2, PIK3CA, ADD1, SYBU, IRS2, USP8, PIGL, FASN, MYLK2, USP25, EP300, and PPP6R2) that were recently detected in PD patients were detected in the prodromal stage of PD.

CONCLUSIONS

Genetic biomarkers are crucial for the early detection of Parkinson's disease and its prodromal stage. The novel PD genes detected in prodromal patients could aid in the use of gene biomarkers for early diagnosis of the prodromal stage without relying only on phenotypic traits.

Critical assessment of variant prioritization methods for rare disease diagnosis within the rare genomes project

BACKGROUND

A major obstacle faced by families with rare diseases is obtaining a genetic diagnosis. The average "diagnostic odyssey" lasts over five years and causal variants are identified in under 50%, even when capturing variants genome-wide. To aid in the interpretation and prioritization of the vast number of variants detected, computational methods are proliferating. Knowing which tools are most effective remains unclear. To evaluate the performance of computational methods, and to encourage innovation in method development, we designed a Critical Assessment of Genome Interpretation (CAGI) community challenge to place variant prioritization models head-to-head in a real-life clinical diagnostic setting.

METHODS

We utilized genome sequencing (GS) data from families sequenced in the Rare Genomes Project (RGP), a direct-to-participant research study on the utility of GS for rare disease diagnosis and gene discovery. Challenge predictors were provided with a dataset of variant calls and phenotype terms from 175 RGP individuals (65 families), including 35 solved training set families with causal variants specified, and 30 unlabeled test set families (14 solved, 16 unsolved). We tasked teams to identify causal variants in as many families as possible. Predictors submitted variant predictions with estimated probability of causal relationship (EPCR) values. Model performance was determined by two metrics, a weighted score based on the rank position of causal variants, and the maximum F-measure, based on precision and recall of causal variants across all EPCR values.

RESULTS

Sixteen teams submitted predictions from 52 models, some with manual review incorporated. Top performers recalled causal variants in up to 13 of 14 solved families within the top 5 ranked variants. Newly discovered diagnostic variants were returned to two previously unsolved families following confirmatory RNA sequencing, and two novel disease gene candidates were entered into Matchmaker Exchange. In one example, RNA sequencing demonstrated aberrant splicing due to a deep intronic indel in ASNS, identified in trans with a frameshift variant in an unsolved proband with phenotypes consistent with asparagine synthetase deficiency.

CONCLUSIONS

Model methodology and performance was highly variable. Models weighing call quality, allele frequency, predicted deleteriousness, segregation, and phenotype were effective in identifying causal variants, and models open to phenotype expansion and non-coding variants were able to capture more difficult diagnoses and discover new diagnoses. Overall, computational models can significantly aid variant prioritization. For use in diagnostics, detailed review and conservative assessment of prioritized variants against established criteria is needed.

Exploring the Potential Mechanisms of Guanxinshutong Capsules in Treating Pathological Cardiac Hypertrophy based on Network Pharmacology, Computer-Aided Drug Design, and Animal Experiments

Cardiovascular diseases (CVDs) are significant causes of morbidity and mortality worldwide, and pathological cardiac hypertrophy (PCH) is an essential predictor of many heart diseases. Guanxinshutong capsule (GXST) is a Chinese patent medicine widely used in the clinical treatment of CVD, In our previous research, we identified 111 compounds of GXST. In order to reveal the potential molecular mechanisms by which GXST treats PCH, this study employed network pharmacology methods to screen for the active ingredients of GXST in treating PCH and predicted the potential targets. The results identified 26 active ingredients of GXST and 110 potential targets for PCH. Through a protein-protein interaction (PPI) network, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, we confirmed AKT1, MAPK1, and MAPK3 as the core proteins in GXST treatment of PCH, thus establishing the PI3K/AKT and MAPK signaling pathways as the significant mechanisms of GXST in treating PCH. The results of molecular docking (MD) demonstrate that flavonoid naringenin and diterpenoid tanshinone iia have the highest binding affinity with the core protein. Before performing molecular dynamics simulations (MDSs), the geometric structure of naringenin and tanshinone iia was optimized using density functional theory (DFT) at the B97-3c level, and RESP2 atomic charge calculations were carried out at the B3LYP-D3(BJ)/def2-TZVP level. Further MDS results demonstrated that in the human body environment, the complex of naringenin and tanshinone iii with core proteins exhibited high stability, flexibility, and low binding free energy. Additionally, naringenin and tanshinone iia showed favorable absorption, distribution, metabolism, excretion, and toxicity (ADMET) characteristics and passed the drug similarity (DS) assessment. Ultrasound cardiograms and cardiac morphometric measurements in animal experiments demonstrate that GXST can improve the PCH induced by isoproterenol (ISO). Protein immunoblotting results indicate that GXST increases the expression of P-eNOS and eNOS by activating the PI3K/AKT signaling pathway and the MAPK signaling pathway, further elucidating the mechanism of action of GXST in treating PCH. This study contributes to the elucidation of the key ingredients and molecular mechanisms of GXST in treating PCH.

Biophysical characterization of high-confidence, small human proteins

Significant efforts have been made to characterize the biophysical properties of proteins. Small proteins have received less attention because their annotation has historically been less reliable. However, recent improvements in sequencing, proteomics, and bioinformatics techniques have led to the high-confidence annotation of small open reading frames (smORFs) that encode for functional proteins, producing smORF-encoded proteins (SEPs). SEPs have been found to perform critical functions in several species, including humans. While significant efforts have been made to annotate SEPs, less attention has been given to the biophysical properties of these proteins. We characterized the distributions of predicted and curated biophysical properties, including sequence composition, structure, localization, function, and disease association of a conservative list of previously identified human SEPs. We found significant differences between SEPs and both larger proteins and control sets. Additionally, we provide an example of how our characterization of biophysical properties can contribute to distinguishing protein-coding smORFs from non-coding ones in otherwise ambiguous cases.

Interpreting the Mechanism of Active Ingredients in Polygonati Rhizoma in Treating Depression by Combining Systemic Pharmacology and In Vitro Experiments

Polygonati Rhizoma (PR) has certain neuroprotective effects as a homology of medicine and food. In this study, systematic pharmacology, molecular docking, and in vitro experiments were integrated to verify the antidepressant active ingredients in PR and their mechanisms. A total of seven compounds in PR were found to be associated with 45 targets of depression. Preliminarily, DFV docking with cyclooxygenase 2 (COX2) showed good affinity. In vitro, DFV inhibited lipopolysaccharide (LPS)-induced inflammation of BV-2 cells, reversed amoeba-like morphological changes, and increased mitochondrial membrane potential. DFV reversed the malondialdehyde (MDA) overexpression and superoxide dismutase (SOD) expression inhibition in LPS-induced BV-2 cells and decreased interleukin-1β (IL-1β), tumor necrosis factor-α (TNF-α), and IL-6 mRNA expression levels in a dose-dependent manner. DFV inhibited both mRNA and protein expression levels of COX2 induced by LPS, and the activation of NACHT, LRR, and PYD domains-containing protein 3 (NLRP3) and caspase1 was suppressed, thus exerting an antidepressant effect. This study proves that DFV may be an important component basis for PR to play an antidepressant role.

Unraveling the anti-breast cancer activity of Cimicifugae rhizoma using biological network pathways and molecular dynamics simulation

Cimicifugae is a commonly used treatment for breast cancer, but the specific molecular mechanisms underlying its effectiveness remain unclear. In this research, we employ a combination of network pharmacology, molecular docking, and molecular dynamics simulations to uncover the most potent phytochemical within Cimicifugae rhizoma in order to delve into its interaction with the target protein in breast cancer treatment. We identified 18 active compounds and 89 associated targets, primarily associated to various biological processes such as lipid metabolism, the signaling pathway in diabetes, viral infections, and cancer-related pathways. Molecular docking analysis revealed that the two most active compounds, Formononetin and Cimigenol, exhibit strong binding to the target protein AKT1. Through molecular dynamics simulations, we found that the Cimigenol-AKT1 complex exhibits greater structural stability and lower interaction energy compared to the stigmasterol-AKT1 complex. Our study demonstrates that Cimicifugae rhizoma exerts its effects in breast cancer treatment through a multi-component, multi-target synergistic approach. Furthermore, we propose that Cimigenol, targeting AKT-1, represents the most effective compound, offering valuable insights into the molecular mechanisms underpinning its role in breast cancer therapy.

Bayesian estimation of gene constraint from an evolutionary model with gene features

Measures of selective constraint on genes have been used for many applications including clinical interpretation of rare coding variants, disease gene discovery, and studies of genome evolution. However, widely-used metrics are severely underpowered at detecting constraint for the shortest ∼25% of genes, potentially causing important pathogenic mutations to be overlooked. We developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, shet. Our estimates outperform existing metrics for prioritizing genes important for cell essentiality, human disease, and other phenotypes, especially for short genes. Our new estimates of selective constraint should have wide utility for characterizing genes relevant to human disease. Finally, our inference framework, GeneBayes, provides a flexible platform that can improve estimation of many gene-level properties, such as rare variant burden or gene expression differences.

DNA binding analysis of rare variants in homeodomains reveals homeodomain specificity-determining residues

Homeodomains (HDs) are the second largest class of DNA binding domains (DBDs) among eukaryotic sequence-specific transcription factors (TFs) and are the TF structural class with the largest number of disease-associated mutations in the Human Gene Mutation Database (HGMD). Despite numerous structural studies and large-scale analyses of HD DNA binding specificity, HD-DNA recognition is still not fully understood. Here, we analyze 92 human HD mutants, including disease-associated variants and variants of uncertain significance (VUS), for their effects on DNA binding activity. Many of the variants alter DNA binding affinity and/or specificity. Detailed biochemical analysis and structural modeling identifies 14 previously unknown specificity-determining positions, 5 of which do not contact DNA. The same missense substitution at analogous positions within different HDs often exhibits different effects on DNA binding activity. Variant effect prediction tools perform moderately well in distinguishing variants with altered DNA binding affinity, but poorly in identifying those with altered binding specificity. Our results highlight the need for biochemical assays of TF coding variants and prioritize dozens of variants for further investigations into their pathogenicity and the development of clinical diagnostics and precision therapies.

KCNJ3 is a novel candidate gene for autosomal dominant pure hereditary spastic paraplegia identified using whole genome sequencing

Hereditary spastic paraplegia (HSP) is a group of familial diseases characterized by progressive corticospinal tract degeneration. Clinically, patients present with lower-limb spasticity and weakness. To date, more than 80 genetic HSP types have been identified. Despite advances in molecular genetics, novel HSP gene discoveries are ongoing, with a low genetic diagnostic yield. In this study, we aimed to determine pathogenic variants in a family with HSP, which was not diagnosed through conventional genetic testing. We clinically characterized a large family and conducted whole genome sequencing (WGS) analysis of four affected and three unaffected individuals in the family to identify the genetic cause of HSP. This family had autosomal dominant pure (uncomplicated) late childhood-onset HSP. The patients' symptoms accelerated between the ages of 20 and 30. Brain magnetic resonance images typically showed white matter changes, a thin corpus callosum, and cerebellar atrophy. We identified a heterozygous missense variant, KCNJ3 c.1297T>G (p.Leu433Val), through WGS and family genetic analysis, confirmed by Sanger sequencing. We suggest that the identification of KCNJ3 c.1297T>G (p.Leu433Val) constitutes the discovery of a potential novel gene responsible for HSP in this family. This is the first study to report the possible role of a KCNJ3 variant in HSP pathogenesis. Our findings further expand the phenotypic and genotypic spectrum of HSP.

Innovative target mining stratagems to navigate drug repurposing endeavours

The conventional theory linking a single gene with a particular disease and a specific drug contributes to the dwindling success rates of traditional drug discovery. This requires a substantial shift focussing on contemporary drug design or drug repurposing, which entails linking multiple genes to diverse physiological or pathological pathways and drugs. Lately, drug repurposing, the art of discovering new/unlabelled indications for existing drugs or candidates in clinical trials, is gaining attention owing to its success rates. The rate-limiting phase of this strategy lies in target identification, which is generally driven through disease-centric and/or drug-centric approaches. The disease-centric approach is based on exploration of crucial biomolecules such as genes or proteins underlying pathological cascades of the disease of interest. Investigating these pathological interplays aids in the identification of potential drug targets that can be leveraged for novel therapeutic interventions. The drug-centric approach involves various strategies such as exploring the mechanism of adverse drug reactions that can unearth potential targets, as these untoward reactions might be considered desirable therapeutic actions in other disease conditions. Currently, artificial intelligence is an emerging robust tool that can be used to translate the aforementioned intricate biological networks to render interpretable data for extracting precise molecular targets. Integration of multiple approaches, big data analytics, and clinical corroboration are essential for successful target mining. This chapter highlights the contemporary strategies steering target identification and diverse frameworks for drug repurposing. These strategies are illustrated through case studies curated from recent drug repurposing research inclined towards neurodegenerative diseases, cancer, infections, immunological, and cardiovascular disorders.

Exploring genetic testing requests, genetic alterations and clinical associations in a cohort of children with autism spectrum disorder

Several studies show great heterogeneity in the type of genetic test requested and in the clinicopathological characteristics of patients with ASD. The following study aims, firstly, to explore the factors that might influence professionals' decisions about the appropriateness of requesting genetic testing for their patients with ASD and, secondly, to determine the prevalence of genetic alterations in a representative sample of children with a diagnosis of ASD. Methods: We studied the clinical factors associated with the request for genetic testing in a sample of 440 children with ASD and the clinical factors of present genetic alterations. Even though the main guidelines recommend genetic testing all children with an ASD diagnosis, only 56% of children with an ASD diagnosis were genetically tested. The prevalence of genetic alterations was 17.5%. These alterations were more often associated with intellectual disability and dysmorphic features. There are no objective data to explicitly justify the request for genetic testing, nor are there objective data to justify requesting one genetic study versus multiple studies. Remarkably, only 28% of males were genetically tested with the recommended tests (fragile X and CMA). Children with dysmorphic features and organic comorbidities were more likely to be genetic tested than those without. Previous diagnosis of ASD (family history of ASD) and attendance at specialist services were also associated with Genetically tested Autism Spectrum Disorder GTASD. Our findings emphasize the importance of establishing algorithms to facilitate targeted genetic consultation for individuals with ASD who are likely to benefit, considering clinical phenotypes, efficiency, ethics, and benefits.

Systematic HOIP interactome profiling reveals critical roles of linear ubiquitination in tissue homeostasis

Linear ubiquitination catalyzed by HOIL-1-interacting protein (HOIP), the key component of the linear ubiquitination assembly complex, plays fundamental roles in tissue homeostasis by executing domain-specific regulatory functions. However, a proteome-wide analysis of the domain-specific interactome of HOIP across tissues is lacking. Here, we present a comprehensive mass spectrometry-based interactome profiling of four HOIP domains in nine mouse tissues. The interaction dataset provides a high-quality HOIP interactome resource with an average of approximately 90 interactors for each bait per tissue. HOIP tissue interactome presents a systematic understanding of linear ubiquitination functions in each tissue and also shows associations of tissue functions to genetic diseases. HOIP domain interactome characterizes a set of previously undefined linear ubiquitinated substrates and elucidates the cross-talk among HOIP domains in physiological and pathological processes. Moreover, we show that linear ubiquitination of Integrin-linked protein kinase (ILK) decreases focal adhesion formation and promotes the detachment of Shigella flexneri-infected cells. Meanwhile, Hoip deficiency decreases the linear ubiquitination of Smad ubiquitination regulatory factor 1 (SMURF1) and enhances its E3 activity, finally causing a reduced bone mass phenotype in mice. Overall, our work expands the knowledge of HOIP-interacting proteins and provides a platform for further discovery of linear ubiquitination functions in tissue homeostasis.

Chemotherapeutic potential of betanin/capecitabine combination targeting colon cancer: experimental and bioinformatic studies exploring NFκB and cyclin D1 interplay

Introduction: Betanin (C₂₄H₂₆N₂O₁₃) is safe to use as food additives approved by the FDA with anti-inflammatory and anticancer effects in many types of cancer cell lines. The current experiment was designed to test the chemotherapeutic effect of the combination of betanin with the standard chemotherapeutic agent, capecitabine, against chemically induced colon cancer in mice. Methods: Bioinformatic approach was designed to get information about the possible mechanisms through which the drugs may control cancer development. Five groups of mice were assigned as, (i) saline, (ii) colon cancer, (iii) betanin, (iv) capecitabine and (v) betanin/capecitabine. Drugs were given orally for a period of six weeks. Colon tissues were separated and used for biological assays and histopathology. Results: In addition, the mRNA expression of TNF-α (4.58-fold), NFκB (5.33-fold), IL-1β (4.99-fold), cyclin D1 (4.07-fold), and IL-6 (3.55-fold) and protein levels showed several folds increases versus the saline group. Tumor histopathology scores in the colon cancer group (including cryptic distortion and hyperplasia) and immunostaining for NFκB (2.94-fold) were high while periodic-acid Schiff staining demonstrated poor mucin content (33% of the saline group). These pathologic manifestations were reduced remarkably in betanin/capecitabine group. Conclusion: Collectively, our findings demonstrated the usefulness of betanin/capecitabine combination in targeting colon cancer and highlighted that betanin is a promising adjuvant therapy to capecitabine in treating colon cancer patients.

Ginsenoside Rd Attenuates Myocardial Ischemia/Reperfusion Injury by Inhibiting Inflammation and Apoptosis through PI3K/Akt Signaling Pathway

Myocardial ischemia/reperfusion (I/R) injury is the leading cause of death worldwide. Ginsenoside Rd (GRd) has cardioprotective properties but its efficacy and mechanism of action in myocardial I/R injury have not been clarified. This study investigated GRd as a potent therapeutic agent for myocardial I/R injury. Oxygen-glucose deprivation and reperfusion (OGD/R) and left anterior descending (LAD) coronary artery ligation were used to establish a myocardial I/R injury model in vitro and in vivo. In vivo, GRd significantly reduced the myocardial infarct size and markers of myocardial injury and improved the cardiac function in myocardial I/R injury mice. In vitro, GRd enhanced cell viability and protected the H9c2 rat cardiomyoblast cell line from OGD-induced injury GRd. The network pharmacology analysis predicted 48 potential targets of GRd for the treatment of myocardial I/R injury. GO and KEGG enrichment analysis indicated that the cardioprotective effects of GRd were closely related to inflammation and apoptosis mediated by the PI3K/Akt signaling pathway. Furthermore, GRd alleviated inflammation and cardiomyocyte apoptosis in vivo and inhibited OGD/R-induced apoptosis and inflammation in cardiomyocytes. GRd also increased PI3K and Akt phosphorylation, suggesting activation of the PI3K/Akt pathway, whereas LY294002, a PI3K inhibitor, blocked the GRd-induced inhibition of OGD/R-induced apoptosis and inflammation in H9c2 cells. The therapeutic effect of GRd in vivo and in vitro against myocardial I/R injury was primarily dependent on PI3K/Akt pathway activation to inhibit inflammation and cardiomyocyte apoptosis. This study provides new evidence for the use of GRd as a cardiovascular drug.

Clinically significant changes in genes and variants associated with epilepsy over time: implications for re-analysis

Despite the significant advances in understanding the genetic architecture of epilepsy, many patients do not receive a molecular diagnosis after genomic testing. Re-analysing existing genomic data has emerged as a potent method to increase diagnostic yields-providing the benefits of genomic-enabled medicine to more individuals afflicted with a range of different conditions. The primary drivers for these new diagnoses are the discovery of novel gene-disease and variants-disease relationships; however, most decisions to trigger re-analysis are based on the passage of time rather than the accumulation of new knowledge. To explore how our understanding of a specific condition changes and how this impacts re-analysis of genomic data from epilepsy patients, we developed Vigelint. This approach combines the information from PanelApp and ClinVar to characterise how the clinically relevant genes and causative variants available to laboratories change over time, and this approach to five clinical-grade epilepsy panels. Applying the Vigelint pipeline to these panels revealed highly variable patterns in new, clinically relevant knowledge becoming publicly available. This variability indicates that a more dynamic approach to re-analysis may benefit the diagnosis and treatment of epilepsy patients. Moreover, this work suggests that Vigelint can provide empirical data to guide more nuanced, condition-specific approaches to re-analysis.

The omics era: a nexus of untapped potential for Mendelian chromatinopathies

The OMICs cascade describes the hierarchical flow of information through biological systems. The epigenome sits at the apex of the cascade, thereby regulating the RNA and protein expression of the human genome and governs cellular identity and function. Genes that regulate the epigenome, termed epigenes, orchestrate complex biological signaling programs that drive human development. The broad expression patterns of epigenes during human development mean that pathogenic germline mutations in epigenes can lead to clinically significant multi-system malformations, developmental delay, intellectual disabilities, and stem cell dysfunction. In this review, we refer to germline developmental disorders caused by epigene mutation as "chromatinopathies". We curated the largest number of human chromatinopathies to date and our expanded approach more than doubled the number of established chromatinopathies to 179 disorders caused by 148 epigenes. Our study revealed that 20.6% (148/720) of epigenes cause at least one chromatinopathy. In this review, we highlight key examples in which OMICs approaches have been applied to chromatinopathy patient biospecimens to identify underlying disease pathogenesis. The rapidly evolving OMICs technologies that couple molecular biology with high-throughput sequencing or proteomics allow us to dissect out the causal mechanisms driving temporal-, cellular-, and tissue-specific expression. Using the full repertoire of data generated by the OMICs cascade to study chromatinopathies will provide invaluable insight into the developmental impact of these epigenes and point toward future precision targets for these rare disorders.

Study on the potential mechanism of Qingxin Lianzi Yin Decoction on renoprotection in db/db mice via network pharmacology and metabolomics

BACKGROUND

Diabetic nephropathy (DN) was one of the most popular and most significant microvascular complications of diabetes mellitus. Qingxin Lianzi Yin Decoction (QXLZY) was a traditional Chinese classical formula, suitable for chronic urinary system diseases. QXLZY had good clinical efficacy in early DN, but the underlying molecular mechanism remained unrevealed.

PURPOSE

This study aimed to establish the content determination method of QXLZY index components and explore the mechanism of QXLZY on DN by network pharmacology and metabolomics studies.

METHODS

Firstly, the content determination methods of QXLZY were established with calycosin-7-O-β-d-glucoside, acteoside, baicalin and glycyrrhizic acid as index components. Secondly, pharmacological experiments of QXLZY were evaluated using db/db mice. UHPLC-LTQ-Orbitrap MS was used to carry out untargeted urine metabolomics, serum metabolomics, and kidney metabolomics studies. Thirdly, employing network pharmacology, key components and targets were analyzed. Finally, targeted metabolomics studies were performed on the endogenous constituents in biological samples for validation based on untargeted metabolomics results.

RESULTS

A method for the simultaneous determination of multiple index components in QXLZY was established, which passed the comprehensive methodological verification. It was simple, feasible, and scientific. The QXLZY treatment alleviated kidney injury of db/db mice, included the degree of histopathological damage and the level of urinary microalbumin/creatinine ratio. Untargeted metabolomics studies had identified metabolic dysfunction in pathways associated with amino acid metabolism in db/db mice. Treatment with QXLZY could reverse metabolite abnormalities and influence the pathways related to energy metabolism and amino acid metabolism. It had been found that pathways with a high degree were involved in signal transduction, prominently on amino acids metabolism and lipid metabolism, analyzed by network pharmacology. Disorders of amino acid metabolism did occur in db/db mice. QXLZY could revert the levels of metabolites, such as quinolinic acid, arginine, and asparagine.

CONCLUSION

This study was the first time to demonstrate that QXLZY alleviated diabetes-induced pathological changes in the kidneys of db/db mice by correcting disturbances in amino acid metabolism. This work could provide a new experimental basis and theoretical guidance for the rational application of QXLZY on DN, exploring the new pharmacological effect of traditional Chinese medicine, and promoting in-depth research and development.

A gene pathogenicity tool "GenePy" identifies missed biallelic diagnoses in the 100,000 Genomes Project

PURPOSE

The 100,000 Genomes Project diagnosed a quarter of affected participants, but 26% of diagnoses were not on the applied gene panel(s); with many being de novo variants. Assessing biallelic variants without a gene panel is more challenging.

METHODS

We sought to identify missed biallelic diagnoses using GenePy, which incorporates allele frequency, zygosity, and a user-defined deleterious metric, generating an aggregate GenePy score per gene, per participant. We calculated GenePy scores for 2862 recessive disease genes in 78,216 100,000 Genomes Project participants. For each gene, we ranked participant GenePy scores and scrutinized affected participants without a diagnosis, whose scores ranked among the top 5 for each gene. In cases which participant phenotypes overlapped with the disease gene of interest, we extracted rare variants and applied phase, ClinVar, and ACMG classification.

RESULTS

3184 affected individuals without a molecular diagnosis had a top-5-ranked GenePy score and 682 of 3184 (21%) had phenotypes overlapping with a top-ranking gene. In 122 of 669 (18%) phenotype-matched cases (excluding 13 withdrawn participants), we identified a putative missed diagnosis (2.2% of all undiagnosed participants). A further 334 of 669 (50%) cases have a possible missed diagnosis but require functional validation.

CONCLUSION

Applying GenePy at scale has identified 456 potential diagnoses, demonstrating the value of novel diagnostic strategies.

Silencing XIST on the future active X: Searching human and bovine preimplantation embryos for the repressor

X inactivation is the means of equalizing the dosage of X chromosomal genes in male and female eutherian mammals, so that only one X is active in each cell. The XIST locus (in cis) on each additional X chromosome initiates the transcriptional silence of that chromosome, making it an inactive X. How the active X in both males and females is protected from inactivation by its own XIST locus is not well understood in any mammal. Previous studies of autosomal duplications suggest that gene(s) on the short arm of human chromosome 19 repress XIST on the active X. Here, we examine the time of transcription of some candidate genes in preimplantation embryos using single-cell RNA sequencing data from human embryos and qRT-PCR from bovine embryos. The candidate genes assayed are those transcribed from 19p13.3-13.2, which are widely expressed and can remodel chromatin. Our results confirm that XIST is expressed at low levels from the future active X in embryos of both sexes; they also show that the XIST locus is repressed in both sexes when pluripotency factors are being upregulated, during the 4-8 cell and morula stages in human and bovine embryos - well before the early blastocyst (E5) when XIST on the inactive X in females starts to be upregulated. Our data suggest a role for DNMT1, UHRF1, SAFB and SAFB2 in XIST repression; they also exclude XACT and other 19p candidate genes and provide the transcriptional timing for some genes not previously assayed in human or bovine preimplantation embryos.

Network pharmacology and experimental validation to reveal the pharmacological mechanisms of Sini decoction against renal fibrosis

OBJECTIVE

To investigate the mechanism by which Sini decoction (, SND) improves renal fibrosis (Rf) in rats based on transforming growth factor β1/Smad (TGF-β1/Smad) signaling pathway.

METHODS

Network pharmacology was applied to obtain potentially involved signaling pathways in SND's improving effects on Rf. The targets of SND drug components and the targets of Rf were obtained by searching databases, such as the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCSMP) and GeenCard. The intersection targets of two searches were obtained and underwent signaling pathway analysis using a Venn diagram. Then experimental pharmacology was utilized to prove and investigate the effects of SND on target proteins in the TGF-β1/Smad signaling pathway. The Rf rat model was established by unilateral ureteral occlusion (UUO). The expression levels of transforming growth factor, matrix metalloproteinase-9 (MMP-9), matrix metal protease-2 (MMP-2), connective tissue growth factor (CTGF), and tissue inhibitor of metalloproteinase-1 (TIMP-1) were determined by Masson staining of rat renal tissue, and immunohistochemical methods. The expression levels of Smad3, Smad2, and Smad7 in renal tissue were determined by Western blotting (WB). The mechanism of the improving effects of SND on Rf was investigated based on TGF-β1/Smad signaling pathway.

RESULTS

A total of 12 drug components of Fuzi (Radix Aconiti Lateralis Preparata), 5 drug components of Ganjiang (Rhizoma Zingiber), and 9 drug components of Gancao (Radix Glycy et Rhizoma) were obtained from the database search, and 207 shared targets were found. A total of 1063 Rf targets were found in the database search. According to the Venn diagram, in total, 96 intersection targets were found in two database searches. The metabolic pathways involved included TGF-β signaling pathway, phosphatidylinositol-3-kinase/serine-threonine protein kinase signaling (PI3K/Akt) pathway, and hypoxia-inducible factor-1 (HIF-1) signaling pathway. Masson staining analysis showed that compared with the model group, the renal interstitial collagen deposition levels in the SSN and SND groups were significantly lower (P < 0.05). Immunohistochemical analysis, compared with the control group, the positive cell area expression levels of MMP-9/TIMP-1 and MMP-2/TIMP-1 in the kidney tissue of the model group were significantly decreased (P < 0.05, P < 0.01), and the positive cell area expression levels of CTGF and TGF-β1 were significantly increased (P < 0.01). Compared with the model group, the positive cell area expression levels of MMP-9/TIMP-1 and MMP-2/TIMP-1 in the kidney tissue of the SSN and SND groups were significantly increased (P < 0.05, P < 0.01), and the positive cell area expression levels of CTGF and TGF-β1 in the kidney tissue were significantly decreased (P < 0.05, P < 0.01). WB results showed that the SSN group and the SND group could reduce the expression of Smad2 and Smad3 (P < 0.05) and increase the expression of Smad7 (P < 0.05).

Network pharmacology and molecular docking to elucidate the common mechanism of hydroxychloroquine treatment in lupus nephritis and IgA nephropathy

OBJECTIVE

Hydroxychloroquine (HCQ), characterized by a broad effect on immune regulation, has been widely used in the treatment of autoimmune glomerulonephritis such as lupus nephritis (LN) and immunoglobulin A nephropathy (IgAN). The current research investigates whether HCQ plays a role in the treatment of LN and IgAN through common mechanisms since the pathogenesis of both LN and IgAN is closely related to immune complex deposition, complement activation, and ultimately inflammation.

METHODS

Seventy-two common targets were obtained related to the common mechanism of HCQ treatment of LN and IgAN. Targets associated with LN and IgAN were collected based on DisGeNET, GeneCards, and OMIM databases. Possible HCQ targets were obtained from the PubChem database and PharmMapper databases. The overlapping targets of HCQ ingredients, IgAN, and LN were discovered via the Venn 2.1.0 online platform. Through the DAVID database, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted. Cytoscape (v3.9.1) was used to build a protein-protein interaction (PPI) network. Molecular docking was performed by using AutoDockTools 1.5.6 software and PyMol software to match the binding activity between HCQ and the 10 core targets.

RESULTS

The results showed that core targets (including MMP 2, PPARG, IL-2, MAPK14, MMP 9, and SRC), three signaling pathways (including the PI3K-Akt, AGE-RAGE, and MAPK), and cell differentiation (including Th1, Th2, and Th17) might be related to the body's immunity and inflammation. These results suggested that HCQ might act on targets and pathways involved in inflammation and immune regulation to exert a common effect on the treatment of LN and IgAN.

CONCLUSIONS

The current study provided new evidence for the protective mechanism and clinical utility of HCQ against LN and IgAN.

Mechanisms of action of Shizhenqing granules for eczema treatment: Network pharmacology analysis and experimental validation

Background

Jiuwan decoction has been used to treat chronic eczema since the Qing Dynasty. According to clinical experience, Shizhenqing granules (SZQG), derived from the Jiuwan decoction, exert beneficial clinical effects on acute eczema and reduce recurrence. Therefore, we elucidated the underlying mechanisms of SZQG through network pharmacology, molecular docking, and experimental validation.

Methods

The main chemical components of SZQG were identified by ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). And the targets of SZQG against eczema were screened out through online databases. Then, the regulatory network map of the "herbal compound-potential target" and the target protein-protein interaction (PPI) network was constructed. The Gene Ontology (GO) analysis and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using by R language. Additionally, the interaction between the active compounds and the targets was verified by molecular docking technology. Finally, an experiment in vivo was used to verify the effect and mechanism of SZQG on eczema.

Results

Using UHPLC-MS/MS, 158 main chemical compounds of SZQG were identified, and 72 compounds were selected according to the criteria for further analysis. All 237 potential targets of SZQG in eczema were explored using multiple online databases. The network with 14 core targets was screened out, including STAT3, RELA, TNF, JUN, MAPK3, IL-6, PIK3CA, STAT1, MAPK14, MAPK1, IL-4, NFKBIA, IL1B, and MYC. KEGG analyses indicated that the therapeutic effects of SZQG on eczema were predominantly associated with cytokine-cytokine receptor interaction, TNF, MAPK, NF-κB, toll-like receptor, T cell receptor, and Th1 and Th2 cell differentiation signaling pathways. Furthermore, the good affinity between the core compounds and core targets was verified by molecular docking technology, particularly for RELA and MAPK. Animal experiments revealed that SZQG downregulated MAPK14, RELA, T-bet, and GATA3 mRNA expression, reduced immunoglobulin E (IgE) and interleukin-4 (IL-4) serum concentrations, and improved eczema-like lesions in model rats.

Conclusion

This study identified potential targets and signaling pathways of SZQG in the treatment of eczema, whereby RELA and MAPK14 may constitute the main therapeutic targets of SZQG in cytokine regulation and reduction of inflammatory responses.

PCAO2: an ontology for integration of prostate cancer associated genotypic, phenotypic and lifestyle data

Disease ontologies facilitate the semantic organization and representation of domain-specific knowledge. In the case of prostate cancer (PCa), large volumes of research results and clinical data have been accumulated and needed to be standardized for sharing and translational researches. A formal representation of PCa-associated knowledge will be essential to the diverse data standardization, data sharing and the future knowledge graph extraction, deep phenotyping and explainable artificial intelligence developing. In this study, we constructed an updated PCa ontology (PCAO2) based on the ontology development life cycle. An online information retrieval system was designed to ensure the usability of the ontology. The PCAO2 with a subclass-based taxonomic hierarchy covers the major biomedical concepts for PCa-associated genotypic, phenotypic and lifestyle data. The current version of the PCAO2 contains 633 concepts organized under three biomedical viewpoints, namely, epidemiology, diagnosis and treatment. These concepts are enriched by the addition of definition, synonym, relationship and reference. For the precision diagnosis and treatment, the PCa-associated genes and lifestyles are integrated in the viewpoint of epidemiological aspects of PCa. PCAO2 provides a standardized and systematized semantic framework for studying large amounts of heterogeneous PCa data and knowledge, which can be further, edited and enriched by the scientific community. The PCAO2 is freely available at https://bioportal.bioontology.org/ontologies/PCAO, http://pcaontology.net/ and http://pcaontology.net/mobile/.