Rare Diseases: Drug Discovery and Informatics Resource

FCMSTrans: Accurate Prediction of Disease-Associated nsSNPs by Utilizing Multiscale Convolution and Deep Feature Combination within a Transformer Framework

Nonsynonymous single-nucleotide polymorphisms (nsSNPs), implicated in over 6000 diseases, necessitate accurate prediction for expedited drug discovery and improved disease diagnosis. In this study, we propose FCMSTrans, a novel nsSNP predictor that innovatively combines the transformer framework and multiscale modules for comprehensive feature extraction. The distinctive attribute of FCMSTrans resides in a deep feature combination strategy. This strategy amalgamates evolutionary-scale modeling (ESM) and ProtTrans (PT) features, providing an understanding of protein biochemical properties, and position-specific scoring matrix, secondary structure, predicted relative solvent accessibility, and predicted disorder (PSPP) features, which are derived from four protein sequences and structure-oriented characteristics. This feature combination offers a comprehensive view of the molecular dynamics involving nsSNPs. Our model employs the transformer's self-attention mechanisms across multiple layers, extracting higher-level and abstract representations. Simultaneously, varied-level features are captured by multiscale convolutions, enriching feature abstraction at multiple echelons. Our comparative analyses with existing methodologies highlight significant improvements made possible by the integrated feature fusion approach adopted in FCMSTrans. This is further substantiated by performance assessments based on diverse data sets, such as PredictSNP, MMP, and PMD, with areas under the curve (AUCs) of 0.869, 0.819, and 0.693, respectively. Furthermore, FCMSTrans shows robustness and superiority by outperforming the current best predictor, PROVEAN, in a blind test conducted on a third-party data set, achieving an impressive AUC score of 0.7838. The Python code of FCMSTrans is available at https://github.com/gc212/FCMSTrans for academic usage.

Emerging approaches to induce immune tolerance to therapeutic proteins

Immunogenicity affects the safety and efficacy of therapeutic proteins. This review is focused on approaches for inducing immunological tolerance to circumvent the immunogenicity of therapeutic proteins in the clinic. The few immune tolerance strategies that are used in the clinic tend to be inefficient and expensive and typically involve global immunosuppression, putting patients at risk of infections. The hallmark of a desirable immune tolerance regimen is the specific alleviation of immune responses to the therapeutic protein. In the past decade, proof-of-principle studies have demonstrated that emerging technologies, including nanoparticle-based delivery of immunomodulators, cellular targeting and depletion, cellular engineering, gene therapy, and gene editing, can be leveraged to promote tolerance to therapeutic proteins. We discuss the potential of these novel approaches and the barriers that need to be overcome for translation into the clinic.

Rare disease research resources at the Rat Genome Database

Rare diseases individually affect relatively few people, but as a group they impact considerable numbers of people. The Rat Genome Database (https://rgd.mcw.edu) is a knowledgebase that offers resources for rare disease research. This includes disease definitions, genes, quantitative trail loci (QTLs), genetic variants, annotations to published literature, links to external resources, and more. One important resource is identifying relevant cell lines and rat strains that serve as models for disease research. Diseases, genes, and strains have report pages with consolidated data, and links to analysis tools. Utilizing these globally accessible resources for rare disease research, potentiating discovery of mechanisms and new treatments, can point researchers toward solutions to alleviate the suffering of those afflicted with these diseases.

Review of the Chinese Landscape in Phase I Clinical Trials for Noncancer Innovative Drugs Over 2015 to 2020

In recent years, the research and development (R&D) of innovative drugs in China has been dramatically accelerated. And the early clinical study is crucial for drug R&D. However, little is known involving the change of phase I trials for noncancer drugs. We retrieved the data of phase I clinical trials for noncancer innovative drugs on the Registration and Information Disclosure Platform for Drug Clinical Studies on the Center for Drug Evaluation. The number of clinical trials proliferating in recent years and the average annual growth rates of chemical and biological drugs were 55.5% and 42.1%, respectively. Most trials were distributed in Beijing, Shanghai, and other developed coastal cities. Moreover, the clinical trials of innovative drugs in China were focused on the digestive and endocrine systems, whereas the pediatric and orphan drugs were scarce. Based on the data assessment, this work provided comprehensive analysis and suggestions about Chinese drug R&D. Significant advancement has been made in mainland China with the implementation of available policies and the emergence of advanced technologies. Though shortcomings, including uneven geographic distribution and lack of pediatric and orphan drugs, still exist, we believe progress will continue to be made in mainland China.

Lessons learned from hemolytic uremic syndrome registries: recommendations for implementation

BACKGROUND

Hemolytic uremic syndrome (HUS) is a rare condition which diagnosed with the triad of thrombocytopenia, microangiopathic hemolytic anemia, and acute renal injury. There is a high requirement for research to discover treatments. HUS registries can be used as an important information infrastructure. In this study, we identified and compared the different features of HUS registries to present a guide for the development and implementation of HUS registries.

RESULTS

The purposes of registries were classified as clinical (9 registries), research (7 registries), and epidemiological (5 registries), and only 3 registries pursued all three types of purposes. The data set included demographic data, medical and family history, para-clinical and diagnostic measures, treatment and pharmacological data, complications, and outcomes. The assessment strategies of data quality included monthly evaluation and data audit, the participation of physicians to collect data, editing and correcting data errors, increasing the rate of data completion, following guidelines and data quality training, using specific data quality indicators, and real-time evaluation of data at the time of data entry. 8 registries include atypical HUS patients, and 7 registries include all patients regardless of age. Only two registries focused on children. 4 registries apply prospective and 4 applied both prospective, and retrospective data collection. Finally, specialized hospitals were the main data source for these registries.

CONCLUSION

Based on the findings, we suggested a learning framework for developing and implementing an HUS registry. This framework includes lessons learned and suggestions for HUS registry purposes, minimum data set, data quality assurance, data collection methods, inclusion and exclusion criteria as well as data sources. This framework can help researchers develop HUS registries.

Clinical application of whole-exome sequencing: A retrospective, single-center study

The aim of the present study was to assess the practical diagnostic value of whole-exome sequencing (WES) in patients with different phenotypes and to explore possible strategies to increase the capability of WES in identifying disease-causing genes. A total of 1,360 patients (aged from 1 day to 42 years old) with manifestations of genetic diseases were genotyped using WES and statistical analysis was performed on the results obtained. Within this cohort, the overall positive rate of identification of a disease-causing gene alteration was 44.41%. The positive identification rate where trio-samples were used (from the proband and both parents) was higher than that where a single proband sample was used (50.00 vs. 43.71%), and 604 positive cases with 150 genetic syndromes, 510 genes and 718 mutations were detected. Missense mutations were the most common variations (n=335, 45.27%) and visual or auditory abnormalities (58.51%) had the highest rate of association with a genetic abnormality. The positive detection rate of WES was elevated with the increase in the number of clinical symptoms from 1 to 8. The present study indicated that WES may be used as a valuable tool in the clinic and the positive rate depends more on the professional experience of clinicians rather than on the analytical capabilities of the data analyst. At the same time, particular attention must be paid to certain possible factors (such as the age of the patients as well as possible exon deletions), which may affect the diagnostic rate while applying this process.

Drug Repurposing for Rare Diseases

Currently, there are about 7000 identified rare diseases, together affecting 10% of the population. However, fewer than 6% of all rare diseases have an approved treatment option, highlighting their tremendous unmet needs in drug development. The process of repurposing drugs for new indications, compared with the development of novel orphan drugs, is a time-saving and cost-efficient method resulting in higher success rates, which can therefore drastically reduce the risk of drug development for rare diseases. Although drug repurposing is not novel, new strategies have been developed in recent years to do it in a systematic and rational way. Here, we review applied methodologies, recent accomplished progress, and the challenges associated in drug repurposing for rare diseases.

Studies on the Mechanism of Gegen Qinlian Decoction in Treating Diabetes Mellitus Based on Network Pharmacology

Diabetes mellitus (DM) is a chronic disease that is very common and seriously threatens patient health. Gegen Qinlian decoction (GQD) has long been applied clinically, but its mechanism in pharmacology has not been extensively and systematically studied. A GQD protein interaction network and diabetes protein interaction network were constructed based on the methods of system biology. Functional module analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and Gene Ontology (GO) enrichment analysis were carried out on the 2 networks. The hub nodes were filtered by comparative analysis. The topological parameters, interactions, and biological functions of the 2 networks were analyzed in multiple ways. By applying GEO-based external datasets to verify the results of our analysis that the Gene Set Enrichment Analysis (GSEA) displayed metabolic pathways in which hub genes played roles in regulating different expression states. Molecular docking is used to verify the effective components that can be combined with hub nodes. By comparing the 2 networks, 24 hub targets were filtered. There were 7 complex relationships between the networks. The results showed 4 topological parameters of the 24 selected hub targets that were much higher than the median values, suggesting that these hub targets show specific involvement in the network. The hub genes were verified in the GEO database, and these genes were closely related to the biological processes involved in glucose metabolism. Molecular docking results showed that 5,7,2', 6'-tetrahydroxyflavone, magnograndiolide, gancaonin I, isoglycyrol, gancaonin A, worenine, and glyzaglabrin produced the strongest binding effect with 10 hub nodes. This compound–target mode of interaction may be the main mechanism of action of GQD. This study reflected the synergistic characteristics of multiple targets and multiple pathways of traditional Chinese medicine and discussed the mechanism of GQD in the treatment of DM at the molecular pharmacological level.

The Biennial report: The collaboration between MAGI Research, Diagnosis and Treatment Center of Genetic and Rare Diseases and Near East University DESAM Institute

Background

Scientific collaboration is more common now than it was before. In many areas of biomedical science, collaborations between researchers with different scientific backgrounds and perspectives have enabled researchers to address complicated questions and solve complex problems.

Particularly, international collaborations and improvements in science and technology have shed light on solving the mechanisms that are involved in the etiology of many rare diseases. Hence, the diagnosis and treatment options have been improved for a number of rare diseases. The collaboration between Near East University DESAM Institute and MAGI Research, Diagnosis and Treatment Center of Genetic and Rare Diseases brought out significant results. Importantly, this collaboration contributed to the rare disease research by the identification of novel rare genetic disease-causing variations commonly in pediatric cases. Consequently, many pediatric unsolved cases have been diagnosed.

The main scope of this article is to emphasize the outcomes of the collaboration between Near East University DESAM Institute and MAGI Research, Diagnosis and Treatment Center of Genetic and Rare Diseases which contributed greatly to the scientific literature by identifying novel rare genetic disease-causing variation.

Evolution of Biochip Technology: A Review from Lab-on-a-Chip to Organ-on-a-Chip

Following the advancements in microfluidics and lab-on-a-chip (LOC) technologies, a novel biomedical application for microfluidic based devices has emerged in recent years and microengineered cell culture platforms have been created. These micro-devices, known as organ-on-a-chip (OOC) platforms mimic the in vivo like microenvironment of living organs and offer more physiologically relevant in vitro models of human organs. Consequently, the concept of OOC has gained great attention from researchers in the field worldwide to offer powerful tools for biomedical researches including disease modeling, drug development, etc. This review highlights the background of biochip development. Herein, we focus on applications of LOC devices as a versatile tool for POC applications. We also review current progress in OOC platforms towards body-on-a-chip, and we provide concluding remarks and future perspectives for OOC platforms for POC applications.

Ion Channels as Therapeutic Targets for Type 1 Diabetes Mellitus

Ion channels are integral proteins expressed in almost all living cells and are involved in muscle contraction and nutrient transport. They play a critical role in the normal functioning of the excitable tissues of the nervous system and regulate the action potential and contraction events. Dysfunction of genes encodes ion channel proteins, which disrupt the channel function and lead to a number of diseases, among which is type 1 diabetes mellitus (T1DM). Therefore, understanding the complex mechanism of ion channel receptors is necessary to facilitate the diagnosis and management of treatment. In this review, we summarize the mechanism of important ion channels and their potential role in the regulation of insulin secretion along with the limitations of ion channels as therapeutic targets. Furthermore, we discuss the recent investigations of the mechanism regulating the ion channels in pancreatic beta cells, which suggest that ion channels are active participants in the regulation of insulin secretion.

Biological Network Approaches and Applications in Rare Disease Studies

Network biology has the capability to integrate, represent, interpret, and model complex biological systems by collectively accommodating biological omics data, biological interactions and associations, graph theory, statistical measures, and visualizations. Biological networks have recently been shown to be very useful for studies that decipher biological mechanisms and disease etiologies and for studies that predict therapeutic responses, at both the molecular and system levels. In this review, we briefly summarize the general framework of biological network studies, including data resources, network construction methods, statistical measures, network topological properties, and visualization tools. We also introduce several recent biological network applications and methods for the studies of rare diseases.

VCF-Server: A web-based visualization tool for high-throughput variant data mining and management

BACKGROUND

Next-generation sequencing (NGS) has been widely used in both clinics and research. It has become the most powerful tool for diagnosing genetic disorders and investigating disease etiology through the discovery of genetic variants. Variants identified by NGS are stored in variant call format (VCF) files. However, querying and filtering VCF files are extremely difficult for researchers without programming skills. Furthermore, as the mutation data are increasing exponentially, there is an urgent need to develop tools to manage these variant data in a centralized way.

METHODS

The VCF-Server was developed as a web-based visualization tool to support the interactive analysis of genetic variant data. It allows researchers and medical geneticists to manage, annotate, filter, query, and export variants in a fast and effective way.

RESULTS

In this study, we developed the VCF-Server, a powerful and easily accessible tool for researchers and medical geneticists to perform variant analysis. Users can query VCFs, annotate, and filter variants without knowing programming code. Once the VCF file is uploaded, VCF-Server allows users to annotate the VCF with commonly used databases or user-defined variant annotations (including variant blacklist and whitelist). Variant information in the VCF is shown visually via the interactive graphical interface. Users can filter the variants with flexible filtering rules, and the prioritized variants can be exported locally for further analysis. As VCF-Server adopts a web file system, files in the VCF-Server can be stored and managed in a centralized way. Moreover, VCF-Server allows direct web-based analysis (accessible through either desktop computers or mobile devices) as well as local deployment.

CONCLUSIONS

With an easy-to-use graphical interface, VCF-Server allows researchers with little bioinformatics background to explore and mine mutation data, which may broaden the application of NGS technology in clinics and research. The tool is freely available for use at https://www.diseasegps.org/VCF-Server?lan = eng.

Exploring the Papillomaviral Proteome to Identify Potential Candidates for a Chimeric Vaccine against Cervix Papilloma Using Immunomics and Computational Structural Vaccinology

The human papillomavirus (HPV) 58 is considered to be the second most predominant genotype in cervical cancer incidents in China. HPV type-restriction, non-targeted delivery, and the highcost of existing vaccines necessitate continuing research on the HPV vaccine. We aimed to explore the papillomaviral proteome in order to identify potential candidates for a chimeric vaccine against cervix papilloma using computational immunology and structural vaccinology approaches. Two overlapped epitope segments (23⁻36) and (29⁻42) from the N-terminal region of the HPV58 minor capsid protein L2 are selected as capable of inducing both cellular and humoral immunity. In total, 318 amino acid lengths of the vaccine construct SGD58 contain adjuvants (Flagellin and RS09), two Th epitopes, and linkers. SGD58 is a stable protein that is soluble, antigenic, and non-allergenic. Homology modeling and the structural refinement of the best models of SGD58 and TLR5 found 96.8% and 93.9% favored regions in Rampage, respectively. The docking results demonstrated a HADDOCK score of -62.5 ± 7.6, the binding energy (-30 kcal/mol) and 44 interacting amino acid residues between SGD58-TLR5 complex. The docked complex are stable in 100 ns of simulation. The coding sequences of SGD58 also show elevated gene expression in Escherichia coli with 1.0 codon adaptation index and 59.92% glycine-cysteine content. We conclude that SGD58 may prompt the creation a vaccine against cervix papilloma.

CDG Therapies: From Bench to Bedside

Congenital disorders of glycosylation (CDG) are a group of genetic disorders that affect protein and lipid glycosylation and glycosylphosphatidylinositol synthesis. More than 100 different disorders have been reported and the number is rapidly increasing. Since glycosylation is an essential post-translational process, patients present a large range of symptoms and variable phenotypes, from very mild to extremely severe. Only for few CDG, potentially curative therapies are being used, including dietary supplementation (e.g., galactose for PGM1-CDG, fucose for SLC35C1-CDG, Mn²⁺ for TMEM165-CDG or mannose for MPI-CDG) and organ transplantation (e.g., liver for MPI-CDG and heart for DOLK-CDG). However, for the majority of patients, only symptomatic and preventive treatments are in use. This constitutes a burden for patients, care-givers and ultimately the healthcare system. Innovative diagnostic approaches, in vitro and in vivo models and novel biomarkers have been developed that can lead to novel therapeutic avenues aiming to ameliorate the patients’ symptoms and lives. This review summarizes the advances in therapeutic approaches for CDG.

Chitosan in Non-Viral Gene Delivery: Role of Structure, Characterization Methods, and Insights in Cancer and Rare Diseases Therapies

Non-viral gene delivery vectors have lagged far behind viral ones in the current pipeline of clinical trials of gene therapy nanomedicines. Even when non-viral nanovectors pose less safety risks than do viruses, their efficacy is much lower. Since the early studies to deliver pDNA, chitosan has been regarded as a highly attractive biopolymer to deliver nucleic acids intracellularly and induce a transgenic response resulting in either upregulation of protein expression (for pDNA, mRNA) or its downregulation (for siRNA or microRNA). This is explained as the consequence of a multi-step process involving condensation of nucleic acids, protection against degradation, stabilization in physiological conditions, cellular internalization, release from the endolysosome ("proton sponge" effect), unpacking and enabling the trafficking of pDNA to the nucleus or the siRNA to the RNA interference silencing complex (RISC). Given the multiple steps and complexity involved in the gene transfection process, there is a dearth of understanding of the role of chitosan's structural features (Mw and degree of acetylation, DA%) on each step that dictates the net transfection efficiency and its kinetics. The use of fully characterized chitosan samples along with the utilization of complementary biophysical and biological techniques is key to bridging this gap of knowledge and identifying the optimal chitosans for delivering a specific gene. Other aspects such as cell type and administration route are also at play. At the same time, the role of chitosan structural features on the morphology, size and surface composition of synthetic virus-like particles has barely been addressed. The ongoing revolution brought about by the recent discovery of CRISPR-Cas9 technology will undoubtedly be a game changer in this field in the short term. In the field of rare diseases, gene therapy is perhaps where the greatest potential lies and we anticipate that chitosans will be key players in the translation of research to the clinic.

Designing of CD8+ and CD8+-overlapped CD4+ epitope vaccine by targeting late and early proteins of human papillomavirus

BACKGROUND AND AIM

Human papillomavirus (HPV) is an oncogenic agent that causes over 90% of cases of cervical cancer in the world. Currently available prophylactic vaccines are type specific and have less therapeutic efficiency. Therefore, we aimed to predict the potential species-specific and therapeutic epitopes from the protein sequences of HPV45 by using different immunoinformatics tools.

METHODS

Initially, we determined the antigenic potential of late (L1 and L2) and early (E1, E2, E4, E5, E6, and E7) proteins. Then, major histocompatibility complex class I-restricted CD8⁺ T-cell epitopes were selected based on their immunogenicity. In addition, epitope conservancy, population coverage (PC), and target receptor-binding affinity of the immunogenic epitopes were determined. Moreover, we predicted the possible CD8⁺, nested interferon gamma (IFN-γ)-producing CD4⁺, and linear B-cell epitopes. Further, antigenicity, allergenicity, immunogenicity, and system biology-based virtual pathway associated with cervical cancer were predicted to confirm the therapeutic efficiency of overlapped epitopes.

RESULTS

Twenty-seven immunogenic epitopes were found to exhibit cross-protection (≥55%) against the 15 high-risk HPV strains (16, 18, 31, 33, 35, 39, 51, 52, 56, 58, 59, 68, 69, 73, and 82). The highest PC was observed in Europe (96.30%), North America (93.98%), West Indies (90.34%), North Africa (90.14%), and East Asia (89.47%). Binding affinities of 79 docked complexes observed as global energy ranged from -10.80 to -86.71 kcal/mol. In addition, CD8⁺ epitope-overlapped segments in CD4⁺ and B-cell epitopes demonstrated that immunogenicity and IFN-γ-producing efficiency ranged from 0.0483 to 0.5941 and 0.046 to 18, respectively. Further, time core simulation revealed the overlapped epitopes involved in pRb, p53, COX-2, NF-X1, and HPV45 infection signaling pathways.

CONCLUSION

Even though the results of this study need to be confirmed by further experimental peptide sensitization studies, the findings on immunogenic and IFN-γ-producing CD8⁺ and overlapped epitopes provide new insights into HPV vaccine development.