The unsolved rare genetic disease atlas? An analysis of the unexplained phenotypic descriptions in OMIM®

Developing a global nursing network for rare diseases to enhance patient care and support

Rare diseases, while individually rare, are common when considered collectively, affecting about one in 17 people across their lifetime. However, there is a lack of awareness of and education about rare diseases in nursing. To address this, the Global Nursing Network Rare Diseases (GNNRD) has been launched to connect nurses from within all fields of practice and at all levels of experience, with the aim of improving the lives of people with rare and undiagnosed diseases (RUDs). The GNNRD aims to empower nurses on a global scale through leadership, knowledge exchange and skill development and to provide a platform from which they can influence policy and advocate for patients and their families at regional, national and international levels. This article provides an overview of RUDs and some of the challenges experienced by patients and their families and describes the development and aims of the GNNRD.

Whole genome sequencing as a first-tier diagnostic test for infants in neonatal intensive care units: A pilot study in Brazil

In this pilot study, we aimed to evaluate the feasibility of whole genome sequencing (WGS) as a first-tier diagnostic test for infants hospitalized in neonatal intensive care units in the Brazilian healthcare system. The cohort presented here results from a joint collaboration between private and public hospitals in Brazil considering the initiative of a clinical laboratory to provide timely diagnosis for critically ill infants. We performed trio (proband and parents) WGS in 21 infants suspected of a genetic disease with an urgent need for diagnosis to guide medical care. Overall, the primary indication for genetic testing was dysmorphic syndromes (n = 14, 67%) followed by inborn errors of metabolism (n = 6, 29%) and skeletal dysplasias (n = 1, 5%). The diagnostic yield in our cohort was 57% (12/21) based on cases that received a definitive or likely definitive diagnostic result from WGS analysis. A total of 16 pathogenic/likely pathogenic variants and 10 variants of unknown significance were detected, and in most cases inherited from an unaffected parent. In addition, the reported variants were of different types, but mainly missense (58%) and associated with autosomal diseases (19/26); only three were associated with X-linked diseases, detected in hemizygosity in the proband an inherited from an unaffected mother. Notably, we identified 10 novel variants, absent from public genomic databases, in our cohort. Considering the entire diagnostic process, the average turnaround time from enrollment to medical report in our study was 53 days. Our findings demonstrate the remarkable utility of WGS as a diagnostic tool, elevating the potential of transformative impact since it outperforms conventional genetic tests. Here, we address the main challenges associated with implementing WGS in the medical care system in Brazil, as well as discuss the potential benefits and limitations of WGS as a diagnostic tool in the neonatal care setting.

Discussion on the Antipruritic Mechanism of Qiwei Antipruritic Based on Network Pharmacology and Molecular Docking Technology

Objective

To explore the mechanism of Qiwei antipruritic by using network pharmacology and molecular docking technology.

Methods

The components and related targets of Qiwei antipruritic were screened by using the traditional Chinese medicine system pharmacology database (TCMSP and symmap databases). GeneCards and OMIM databases were used to screen itch-related targets. The protein-protein interaction (PPI) network between active ingredient targets and pruritus disease targets was constructed using STRING database. Cytoscape 3.8.0 software was used to draw the visualization network of "drug-component-target-signaling pathway" and screen the core targets. Gene ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed using R software. AutoDock vina software was used to perform molecular docking of key targets and their corresponding key components.

Results

There were 44 main components of Qiwei antipruritic compound, 118 corresponding targets and 3869 itch-related genes. A total of 82 predicted targets of Qiwei antipruritic in the treatment of pruritus were obtained. Eleven key targets were screened. Among the 23 KEGG enriched pathways, 12 signaling pathways were related to skin pruritus. Molecular docking results showed that the core components of Qiwei antipruritic, including quercetin, kaempferol, β-sitosterol, stigmasterol, luteolin, and preskimmianine, had good binding ability with ESR1, PPARG, IL6, TP53, and EGFR, and the docking scores were all less than -4.

Conclusion

The mechanism of Qiwei antipruritic may be related to histamine activation mechanism, calcium channel mechanism, inhibition of inflammatory signaling pathway, inhibition of neurotransmitters, and regulation of immune pathways. The traditional Chinese medicine compound Qiwei antipruritic can treat clinical pruritus through multiple targets and pathways.

Resources and tools for rare disease variant interpretation

Collectively, rare genetic disorders affect a substantial portion of the world's population. In most cases, those affected face difficulties in receiving a clinical diagnosis and genetic characterization. The understanding of the molecular mechanisms of these diseases and the development of therapeutic treatments for patients are also challenging. However, the application of recent advancements in genome sequencing/analysis technologies and computer-aided tools for predicting phenotype-genotype associations can bring significant benefits to this field. In this review, we highlight the most relevant online resources and computational tools for genome interpretation that can enhance the diagnosis, clinical management, and development of treatments for rare disorders. Our focus is on resources for interpreting single nucleotide variants. Additionally, we present use cases for interpreting genetic variants in clinical settings and review the limitations of these results and prediction tools. Finally, we have compiled a curated set of core resources and tools for analyzing rare disease genomes. Such resources and tools can be utilized to develop standardized protocols that will enhance the accuracy and effectiveness of rare disease diagnosis.

Protective effect and mechanism of Polygonatum kingianum against hypoxia-induced injury

Background

Hypoxia is an essential cause of fatigue and aging, and is associated with the occurrence and development of many diseases. Polygonatum kingianum (PK) is a deficiency-nourishing Chinese herbal medicine utilized as both medicine and food, and it has long been used to ameliorate human conditions associated with fatigue and aging over 2000 years in China. PK is an important genuine-medicinal-materials cultivated in Yunnan, China, and is used by the Bai, Wa, and Zhuang nationalities as a traditional medicine for enhancing immunity, anti-fatigue, and anti-aging, while the preventive effect of PK on hypoxia-induced injury and the underlying mechanism are indefinite.

Aim of the study

The present study aimed to evaluate the anti-hypoxia efficacy and understand the corresponding mechanism of PK water extract.

Materials and methods

The main active ingredients and targets of PK were predicted using network pharmacology, and the anti-hypoxia activities of Gracillin and Liquiritigenin were verified by in vitro experiments. The pharmacodynamic experiments were conducted to evaluate the major signal pathways of PK for detecting anti-hypoxia activity.

Results

Fifty active ingredients and 371 potential targets were screened by network pharmacology, then, we confirmed that Gracillin and Liquiritigenin were the main active components of PK to exert anti-hypoxia effect in vitro. The pharmacodynamic experiments revealed that PK enhanced the extension rate of the survival time (ERST) and regulated the targets-related biochemical parameters of rats under hypoxia, showing significant anti-hypoxia effects on rats.

Conclusion

The network pharmacology results suggested that PK exerts its anti-hypoxia effect through a multi-component and multi-target manner. Simultaneously, we also observed that Gracillin (saponins) and Liquiritigenin (flavonoids) are the main active components of PK to play a role in anti-hypoxia. The anti-hypoxia effect of PK could be associated with scavenging excess free radicals, maintaining the activities of antioxidant enzymes, and inhibiting oxidative stress due to lipid peroxidation. These findings provide insight into the Polygonatum kingianum as promising medicines or healthcare products for preventing and treating hypoxia.

Stepwise use of genomics and transcriptomics technologies increases diagnostic yield in Mendelian disorders

Purpose: Multi-omics offer worthwhile and increasingly accessible technologies to diagnostic laboratories seeking potential second-tier strategies to help patients with unresolved rare diseases, especially patients clinically diagnosed with a rare OMIM (Online Mendelian Inheritance in Man) disease. However, no consensus exists regarding the optimal diagnostic care pathway to adopt after negative results with standard approaches. Methods: In 15 unsolved individuals clinically diagnosed with recognizable OMIM diseases but with negative or inconclusive first-line genetic results, we explored the utility of a multi-step approach using several novel omics technologies to establish a molecular diagnosis. Inclusion criteria included a clinical autosomal recessive disease diagnosis and single heterozygous pathogenic variant in the gene of interest identified by first-line analysis (60%-9/15) or a clinical diagnosis of an X-linked recessive or autosomal dominant disease with no causative variant identified (40%-6/15). We performed a multi-step analysis involving short-read genome sequencing (srGS) and complementary approaches such as mRNA sequencing (mRNA-seq), long-read genome sequencing (lrG), or optical genome mapping (oGM) selected according to the outcome of the GS analysis. Results: SrGS alone or in combination with additional genomic and/or transcriptomic technologies allowed us to resolve 87% of individuals by identifying single nucleotide variants/indels missed by first-line targeted tests, identifying variants affecting transcription, or structural variants sometimes requiring lrGS or oGM for their characterization. Conclusion: Hypothesis-driven implementation of combined omics technologies is particularly effective in identifying molecular etiologies. In this study, we detail our experience of the implementation of genomics and transcriptomics technologies in a pilot cohort of previously investigated patients with a typical clinical diagnosis without molecular etiology.

A framework to score the effects of structural variants in health and disease

While technological advances improved the identification of structural variants (SVs) in the human genome, their interpretation remains challenging. Several methods utilize individual mechanistic principles like the deletion of coding sequence or 3D genome architecture disruptions. However, a comprehensive tool using the broad spectrum of available annotations is missing. Here, we describe CADD-SV, a method to retrieve and integrate a wide set of annotations to predict the effects of SVs. Previously, supervised learning approaches were limited due to a small number and biased set of annotated pathogenic or benign SVs. We overcome this problem by using a surrogate training-objective, the Combined Annotation Dependent Depletion (CADD) of functional variants. We use human and chimpanzee derived SVs as proxy-neutral and contrast them with matched simulated variants as proxy-deleterious, an approach that has proven powerful for short sequence variants. Our tool computes summary statistics over diverse variant annotations and uses random forest models to prioritize deleterious structural variants. The resulting CADD-SV scores correlate with known pathogenic and rare population variants. We further show that we can prioritize somatic cancer variants as well as noncoding variants known to affect gene expression. We provide a website and offline-scoring tool for easy application of CADD-SV.

DECIPHER: Supporting the interpretation and sharing of rare disease phenotype-linked variant data to advance diagnosis and research

DECIPHER (https://www.deciphergenomics.org) is a free web platform for sharing anonymised phenotype-linked variant data from rare disease patients. Its dynamic interpretation interfaces contextualise genomic and phenotypic data to enable more informed variant interpretation, incorporating international standards for variant classification. DECIPHER supports almost all types of germline and mosaic variation in the nuclear and mitochondrial genome: sequence variants, short tandem repeats, copy-number variants and large structural variants. Patient phenotypes are deposited using Human Phenotype Ontology (HPO) terms, supplemented by quantitative data, which is aggregated to derive gene-specific phenotypic summaries. It hosts data from >250 projects from ~40 countries, openly sharing >40,000 patient records containing >51,000 variants and >172,000 phenotype terms. The rich phenotype-linked variant data in DECIPHER drives rare disease research and diagnosis by enabling patient matching within DECIPHER and with other resources, and has been cited in >2,600 publications. In this paper, we describe the types of data deposited to DECIPHER, the variant interpretation tools, and patient matching interfaces which make DECIPHER an invaluable rare disease resource. This article is protected by copyright. All rights reserved.

Association between pectus excavatum and congenital genetic disorders: A systematic review and practical guide for the treating physician

BACKGROUND

Pectus excavatum (PE) could be part of a genetic disorder, which then has implications regarding comorbidity, the surgical correction of PE, and reproductive choices. However, referral of a patient presenting with PE for genetic analysis is often delayed because additional crucial clinical signs may be subtle or even missed in syndromic patients. We reviewed the literature to inventory known genetic disorders associated with PE and create a standardized protocol for clinical evaluation.

METHODS

A systematic literature search was performed in electronic databases. Genetic disorders were considered associated with PE if studies reported at least five cases with PE. Characteristics of each genetic disorder were extracted from the literature and the OMIM database in order to create a practical guide for the clinician.

RESULTS

After removal of duplicates from the initial search, 1632 citations remained. Eventually, we included 119 full text articles, representing 20 different genetic disorders. Relevant characteristics and important clinical signs of each genetic disorder were summarized providing a standardized protocol in the form of a scoring list. The most important clinical sign was a positive family history for PE and/or congenital heart defect.

CONCLUSIONS

Twenty unique genetic disorders have been found associated with PE. We have created a scoring list for the clinician that systematically evaluates crucial clinical signs, thereby facilitating decision making for referral to a clinical geneticist.

The IDeaS initiative: pilot study to assess the impact of rare diseases on patients and healthcare systems

Background

Rare diseases (RD) are a diverse collection of more than 7–10,000 different disorders, most of which affect a small number of people per disease. Because of their rarity and fragmentation of patients across thousands of different disorders, the medical needs of RD patients are not well recognized or quantified in healthcare systems (HCS).

Methodology

We performed a pilot IDeaS study, where we attempted to quantify the number of RD patients and the direct medical costs of 14 representative RD within 4 different HCS databases and performed a preliminary analysis of the diagnostic journey for selected RD patients.

Results

The overall findings were notable for: (1) RD patients are difficult to quantify in HCS using ICD coding search criteria, which likely results in under-counting and under-estimation of their true impact to HCS; (2) per patient direct medical costs of RD are high, estimated to be around three–fivefold higher than age-matched controls; and (3) preliminary evidence shows that diagnostic journeys are likely prolonged in many patients, and may result in progressive, irreversible, and costly complications of their disease

Conclusions

The results of this small pilot suggest that RD have high medical burdens to patients and HCS, and collectively represent a major impact to the public health. Machine-learning strategies applied to HCS databases and medical records using sentinel disease and patient characteristics may hold promise for faster and more accurate diagnosis for many RD patients and should be explored to help address the high unmet medical needs of RD patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-021-02061-3.

Whole-genome sequencing as a first-tier diagnostic framework for rare genetic diseases

Rare diseases affect nearly 300 million people globally with most patients aged five or less. Traditional diagnostic approaches have provided much of the diagnosis; however, there are limitations. For instance, simply inadequate and untimely diagnosis adversely affects both the patient and their families. This review advocates the use of whole genome sequencing in clinical settings for diagnosis of rare genetic diseases by showcasing five case studies. These examples specifically describe the utilization of whole genome sequencing, which helped in providing relief to patients via correct diagnosis followed by use of precision medicine.

Pitfalls in Genetic Diagnostics: Why Phenotyping is Essential

New genetic testing technologies have revolutionized medicine within the past years. It is foreseeable that the development will continue with the introduction of new techniques. Nevertheless, despite improved technology, an exact clinical description of the phenotype is still necessary and it is important to critically question findings, both before initiating genetic testing and when interpreting the results. We present four brief case vignettes to point out difficulties associated with correctly interpreting genetic findings.

Cruxome: a powerful tool for annotating, interpreting and reporting genetic variants

Background

Next-generation sequencing (NGS) is an efficient tool used for identifying pathogenic variants that cause Mendelian disorders. However, the lack of bioinformatics training of researchers makes the interpretation of identified variants a challenge in terms of precision and efficiency. In addition, the non-standardized phenotypic description of human diseases also makes it difficult to establish an integrated analysis pathway for variant annotation and interpretation. Solutions to these bottlenecks are urgently needed.

Results

We develop a tool named “Cruxome” to automatically annotate and interpret single nucleotide variants (SNVs) and small insertions and deletions (InDels). Our approach greatly simplifies the current burdensome task of clinical geneticists and scientists to identify the causative pathogenic variants and build personal knowledge reference bases. The integrated architecture of Cruxome offers key advantages such as an interactive and user-friendly interface and the assimilation of electronic health records of the patient. By combining a natural language processing algorithm, Cruxome can efficiently process the clinical description of diseases to HPO standardized vocabularies. By using machine learning, in silico predictive algorithms, integrated multiple databases and supplementary tools, Cruxome can automatically process SNVs and InDels variants (trio-family or proband-only cases) and clinical diagnosis records, then annotate, score, identify and interpret pathogenic variants to finally generate a standardized clinical report following American College of Medical Genetics and Genomics/ Association for Molecular Pathology (ACMG/AMP) guidelines. Cruxome also provides supplementary tools to examine and visualize the genes or variations in historical cases, which can help to better understand the genetic basis of the disease.

Conclusions

Cruxome is an efficient tool for annotation and interpretation of variations and dramatically reduces the workload for clinical geneticists and researchers to interpret NGS results, simplifying their decision-making processes. We present an online version of Cruxome, which is freely available to academics and clinical researchers. The site is accessible at http://114.251.61.49:10024/cruxome/.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07728-6.

Network Pharmacology Identifies the Mechanisms of Action of TaohongSiwu Decoction Against Essential Hypertension

BACKGROUND TaohongSiwu decoction (THSWT), a traditional herbal formula, has been used to treat cardiovascular and cerebrovascular diseases such as essential hypertension (EH) in China. However, the pharmacological mechanism is not clear. To investigate the mechanisms of THSWT in the treatment of EH, we performed compounds, targets prediction and network analysis using a network pharmacology method. MATERIAL AND METHODS We selected chemical constituents and targets of THSWT according to TCMSP and UniProtKB databases and collected therapeutic targets on EH from Online Mendelian Inheritance in Man (OMIM), Drugbank and DisGeNET databases. The protein-protein interaction (PPI) was analyzed by using String database. Then network was constructed by using Cytoscape_v3.7.1, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment was performed by using Database for Annotation, Visualization and Integrated Discovery (DAVID) software. RESULTS The results of our network pharmacology research showed that the THSWT, composed of 6 Chinese herbs, contained 15 compounds, and 23 genes regulated the main signaling pathways related to EH. Moreover, the PPI network based on targets of THSWT on EH revealed the interaction relationship between targets. These core compounds were 6 of the 15 disease-related compounds in the network, kaempferol, quercetin, luteolin, Myricanone, beta-sitosterol, baicalein, and the core genes contained ADRB2, CALM1, HMOX1, JUN, PPARG, and VEGFA, which were regulated by more than 3 compounds and significantly associated with Calcium signaling pathway, cGMP-PKG signaling pathway, cAMP signaling pathway, PI3K-Akt signaling pathway, Rap1 signaling pathway, and Ras signaling pathway. CONCLUSIONS This network pharmacological study can reveal potential mechanisms of multi-target and multi-component THSWT in the treatment of EH, provide a scientific basis for studying the mechanism.

A Diagnosis for All Rare Genetic Diseases: The Horizon and the Next Frontiers

The introduction of exome sequencing in the clinic has sparked tremendous optimism for the future of rare disease diagnosis, and there is exciting opportunity to further leverage these advances. To provide diagnostic clarity to all of these patients, however, there is a critical need for the field to develop and implement strategies to understand the mechanisms underlying all rare diseases and translate these to clinical care.

The Canadian Rare Diseases Models and Mechanisms (RDMM) Network: Connecting Understudied Genes to Model Organisms

Advances in genomics have transformed our ability to identify the genetic causes of rare diseases (RDs), yet we have a limited understanding of the mechanistic roles of most genes in health and disease. When a novel RD gene is first discovered, there is minimal insight into its biological function, the pathogenic mechanisms of disease-causing variants, and how therapy might be approached. To address this gap, the Canadian Rare Diseases Models and Mechanisms (RDMM) Network was established to connect clinicians discovering new disease genes with Canadian scientists able to study equivalent genes and pathways in model organisms (MOs). The Network is built around a registry of more than 500 Canadian MO scientists, representing expertise for over 7,500 human genes. RDMM uses a committee process to identify and evaluate clinician-MO scientist collaborations and approve 25,000 Canadian dollars in catalyst funding. To date, we have made 85 clinician-MO scientist connections and funded 105 projects. These collaborations help confirm variant pathogenicity and unravel the molecular mechanisms of RD, and also test novel therapies and lead to long-term collaborations. To expand the impact and reach of this model, we made the RDMM Registry open-source, portable, and customizable, and we freely share our committee structures and processes. We are currently working with emerging networks in Europe, Australia, and Japan to link international RDMM networks and registries and enable matches across borders. We will continue to create meaningful collaborations, generate knowledge, and advance RD research locally and globally for the benefit of patients and families living with RD.

Unsolved recognizable patterns of human malformation: Challenges and opportunities

Due to the efforts of the clinical and scientific communities and boosted by recent advances in genetic technologies, we now understand the molecular mechanisms underlying most of the frequent and recognizable human malformation syndromes. However, some well-established human malformation syndromes remain without a molecular diagnosis despite intensive investigation. This issue of Seminars mines the phenotypic entries in OMIM and estimates that of the documented 2,034 unsolved entries likely to represent a rare genetic disease, only 160 are well-established and possibly amenable to investigation. This issue also reviews well-characterized and extensively investigated human malformation syndromes and associations that remain unsolved, including the following: Dubowitz syndrome (MIM 223370%), Hallermann-Streiff syndrome (MIM 234100%), PHACE syndrome (MIM 606519), Oculocerebrocutaneous syndrome (MIM 164180), Aicardi syndrome (MIM 304050%), Gomez-Lopez-Hernandez syndrome and Rhombencephalosynapsis (MIM 601853%), VACTERL (MIM 192350%), and Nablus syndrome (MIM #608156). Possible explanations for their intractability to molecular diagnosis are explored, including genetic and phenotypic heterogeneity, mosaicism, epigenetics, gene-environment interactions, and other non-Mendelian contributions. Finally, this issue of Seminars presents a path forward for these unsolved rare conditions and suggests a renewed focus on solving amendable OMIM disorders. It is clear that the way forward will require new technologies, global cooperation, and data sharing; these will also be necessary to help reach the vision of the International Rare Diseases Research Consortium (IRDiRC), that is to enable all people living with a rare disease to receive an accurate diagnosis, care and available therapy within 1 year of coming to medical attention.

Mendelian Gene Discovery: Fast and Furious with No End in Sight

Gene discovery for Mendelian conditions (MCs) offers a direct path to understanding genome function. Approaches based on next-generation sequencing applied at scale have dramatically accelerated gene discovery and transformed genetic medicine. Finding the genetic basis of ∼6,000-13,000 MCs yet to be delineated will require both technical and computational innovation, but will rely to a larger extent on meaningful data sharing.

The burden of rare diseases

The subject of rare disease numbers is rife with misconceptions, not just in websites and other layman's literature, but also in the medical literature. Various websites mention numbers that are not validated by any solid data, while in turn the medical literature cites the aforementioned websites as sources, thus perpetuating a number of myths about rare diseases and their burden. We review the existing literature on rare disease numbers, in an attempt to demystify the subject. Specifically, we summarize data pertaining to: (a) known number and cumulative prevalence of rare diseases; (b) rare disease-associated mortality; (c) rare disease-associated morbidity, including numbers on health care services related to rare diseases; and (d) orphan drug numbers.