Genome sequencing and implications for rare disorders

Genetics of inherited peripheral neuropathies and the next frontier: looking backwards to progress forwards

Inherited peripheral neuropathies (IPNs) encompass a clinically and genetically heterogeneous group of disorders causing length-dependent degeneration of peripheral autonomic, motor and/or sensory nerves. Despite gold-standard diagnostic testing for pathogenic variants in over 100 known associated genes, many patients with IPN remain genetically unsolved. Providing patients with a diagnosis is critical for reducing their 'diagnostic odyssey', improving clinical care, and for informed genetic counselling. The last decade of massively parallel sequencing technologies has seen a rapid increase in the number of newly described IPN-associated gene variants contributing to IPN pathogenesis. However, the scarcity of additional families and functional data supporting variants in potential novel genes is prolonging patient diagnostic uncertainty and contributing to the missing heritability of IPNs. We review the last decade of IPN disease gene discovery to highlight novel genes, structural variation and short tandem repeat expansions contributing to IPN pathogenesis. From the lessons learnt, we provide our vision for IPN research as we anticipate the future, providing examples of emerging technologies, resources and tools that we propose that will expedite the genetic diagnosis of unsolved IPN families.

Drug repurposing for rare diseases

Repurposing drugs for rare diseases is a creative and cost-efficient method for creating new treatment options for certain conditions. This technique entails repurposing existing pharmaceuticals for new uses by utilizing established information regarding pharmacological characteristics, modes of operation, safety profiles, and interactions with biological systems. Creating new treatments for uncommon diseases is frequently difficult because of factors including small patient groups, disease intricacy, and insufficient knowledge of disease pathobiology. Drug repurposing is a more efficient and cost-effective approach compared to developing new drugs from scratch. It typically requires collaboration among academia, pharmaceutical firms, and patient advocacy groups.

Atypical Diabetes: What Have We Learned and What Does the Future Hold?

As our understanding of the pathophysiology of diabetes evolves, we increasingly recognize that many patients may have a form of diabetes that does not neatly fit with a diagnosis of either type 1 or type 2 diabetes. The discovery and description of these forms of "atypical diabetes" have led to major contributions to our collective understanding of the basic biology that drives insulin secretion, insulin resistance, and islet autoimmunity. These discoveries now pave the way to a better classification of diabetes based on distinct endotypes. In this review, we highlight the key biological and clinical insights that can be gained from studying known forms of atypical diabetes. Additionally, we provide a framework for identification of patients with atypical diabetes based on their clinical, metabolic, and molecular features. Helpful clinical and genetic resources for evaluating patients suspected of having atypical diabetes are provided. Therefore, appreciating the various endotypes associated with atypical diabetes will enhance diagnostic accuracy and facilitate targeted treatment decisions.

Improving somatic exome sequencing performance by biological replicates

BACKGROUND

Next-generation sequencing (NGS) technologies offer fast and inexpensive identification of DNA sequences. Somatic sequencing is among the primary applications of NGS, where acquired (non-inherited) variants are based on comparing diseased and healthy tissues from the same individual. Somatic mutations in genetic diseases such as cancer are tightly associated with genomic instability. Genomic instability increases heterogenity, complicating sequencing efforts further, a task already challenged by the presence of short reads and repetitions in human DNA. This leads to low concordance among studies and limits reproducibility. This limitation is a significant problem since identified mutations in somatic sequencing are major biomarkers for diagnosis and the primary input of targeted therapies. Benchmarking studies were conducted to assess the error rates and increase reproducibility. Unfortunately, the number of somatic benchmarking sets is very limited due to difficulties in validating true somatic variants. Moreover, most NGS benchmarking studies are based on relatively simpler germline (inherited) sequencing. Recently, a comprehensive somatic sequencing benchmarking set was published by Sequencing Quality Control Phase 2 (SEQC2). We chose this dataset for our experiments because it is a well-validated, cancer-focused dataset that includes many tumor/normal biological replicates. Our study has two primary goals. First goal is to determine how replicate-based consensus approaches can improve the accuracy of somatic variant detection systems. Second goal is to develop highly predictive machine learning (ML) models by employing replicate-based consensus variants as labels during the training phase.

RESULTS

Ensemble approaches that combine alternative algorithms are relatively common; here, as an alternative, we study the performance enhancement potential of biological replicates. We first developed replicate-based consensus approaches that utilize the biological replicates available in this study to improve variant calling performance. Subsequently, we trained ML models using these biological replicates and achieved performance comparable to optimal ML models, those trained using high-confidence variants identified in advance.

CONCLUSIONS

Our replicate-based consensus approach can be used to improve variant calling performance and develop efficient ML models. Given the relative ease of obtaining biological replicates, this strategy allows for the development of efficient ML models tailored to specific datasets or scenarios.

Lived experiences of genetic diagnosis for rare disease patients: a qualitative interview study

BACKGROUND

Genetic diagnosis is often understood as a single event within the care pathway of rare disease patients. Legal, policy and ethical scholarship focusing on rare diseases and genetic information discusses questions of how to best deal with the process of genetic diagnosis and the communication of genetic information within a given health system. We co-created a research design with rare disease patients and their families in Austria to explore in-depth the experiences of genetic diagnosis for people affected by rare diseases. Our objective was to trace the whole pathway of genetic testing and understand how rare disease patients experience genetic diagnosis as part of their care pathway in the healthcare system.

RESULTS

Data was collected through in-depth semi-structured qualitative interviews with 14 patients with a suspected or diagnosed rare disease or their parents, focusing on their perception of the pathway of genetic diagnosis in Austria. This pathway included the initial triggering of genetic diagnosis, the process of testing and its immediate (communication of results, counselling) and long-term, wider aftermath. Patients missed a clear link to already established forms of care such as their primary care/treating physicians. They also advocate for an integrated and interdisciplinary care pathway.

CONCLUSIONS

Our study underscores the importance of a continuous care and communication pathway spanning from the initial genetic diagnosis process to post-test phases. It further shows the importance of exploring patients' perspectives through qualitative research methods to understand the intricate workings of public health policies and tools. Integrating genetic diagnosis into a broader care trajectory is crucial for a holistic approach to care for rare disease patients who often rely on regular interactions with the healthcare system. Achieving this holistic approach requires collaboration between experts in specific rare disease areas, primary care physicians, and support networks.

Artificial intelligence and database for NGS-based diagnosis in rare disease

Rare diseases (RDs) are rare complex genetic diseases affecting a conservative estimate of 300 million people worldwide. Recent Next-Generation Sequencing (NGS) studies are unraveling the underlying genetic heterogeneity of this group of diseases. NGS-based methods used in RDs studies have improved the diagnosis and management of RDs. Concomitantly, a suite of bioinformatics tools has been developed to sort through big data generated by NGS to understand RDs better. However, there are concerns regarding the lack of consistency among different methods, primarily linked to factors such as the lack of uniformity in input and output formats, the absence of a standardized measure for predictive accuracy, and the regularity of updates to the annotation database. Today, artificial intelligence (AI), particularly deep learning, is widely used in a variety of biological contexts, changing the healthcare system. AI has demonstrated promising capabilities in boosting variant calling precision, refining variant prediction, and enhancing the user-friendliness of electronic health record (EHR) systems in NGS-based diagnostics. This paper reviews the state of the art of AI in NGS-based genetics, and its future directions and challenges. It also compare several rare disease databases.

Cost-Effectiveness of Whole-Genome vs Whole-Exome Sequencing Among Children With Suspected Genetic Disorders

Importance

The diagnosis of rare diseases and other genetic conditions can be daunting due to vague or poorly defined clinical features that are not recognized even by experienced clinicians. Next-generation sequencing technologies, such as whole-genome sequencing (WGS) and whole-exome sequencing (WES), have greatly enhanced the diagnosis of genetic diseases by expanding the ability to sequence a large part of the genome, rendering a cost-effectiveness comparison between them necessary.

Objective

To assess the cost-effectiveness of WGS compared with WES and conventional testing in children with suspected genetic disorders.

Design, Setting, and Participants

In this economic evaluation, a bayesian Markov model was implemented from January 1 to June 30, 2023. The model was developed using data from a cohort of 870 pediatric patients with suspected genetic disorders who were enrolled and underwent testing in the Ospedale Pediatrico Bambino Gesù, Rome, Italy, from January 1, 2015, to December 31, 2022. The robustness of the model was assessed through probabilistic sensitivity analysis and value of information analysis.

Main Outcomes and Measures

Overall costs, number of definitive diagnoses, and incremental cost-effectiveness ratios per diagnosis were measured. The cost-effectiveness analyses involved 4 comparisons: first-tier WGS with standard of care; first-tier WGS with first-tier WES; first-tier WGS with second-tier WES; and first-tier WGS with second-tier WGS.

Results

The ages of the 870 participants ranged from 0 to 18 years (539 [62%] girls). The results of the analysis suggested that adopting WGS as a first-tier strategy would be cost-effective compared with all other explored options. For all threshold levels above €29 800 (US $32 408) per diagnosis that were tested up to €50 000 (US $54 375) per diagnosis, first-line WGS vs second-line WES strategy (ie, 54.6%) had the highest probability of being cost-effective, followed by first-line vs second-line WGS (ie, 54.3%), first-line WGS vs the standard of care alternative (ie, 53.2%), and first-line WGS vs first-line WES (ie, 51.1%). Based on sensitivity analyses, these estimates remained robust to assumptions and parameter uncertainty.

Conclusions and Relevance

The findings of this economic evaluation encourage the development of policy changes at various levels (ie, macro, meso, and micro) of international health systems to ensure an efficient adoption of WGS in clinical practice and its equitable access.

Clinical and genetic characteristics of a large international cohort of individuals with rare NR5A1/SF-1 variants of sex development

BACKGROUND

Steroidogenic factor 1 (SF-1/NR5A1) is essential for human sex development. Heterozygous NR5A1/SF-1 variants manifest with a broad range of phenotypes of differences of sex development (DSD), which remain unexplained.

METHODS

We conducted a retrospective analysis on the so far largest international cohort of individuals with NR5A1/SF-1 variants, identified through the I-DSD registry and a research network.

FINDINGS

Among 197 individuals with NR5A1/SF-1 variants, we confirmed diverse phenotypes. Over 70% of 46, XY individuals had a severe DSD phenotype, while 90% of 46, XX individuals had female-typical sex development. Close to 100 different novel and known NR5A1/SF-1 variants were identified, without specific hot spots. Additionally, likely disease-associated variants in other genes were reported in 32 individuals out of 128 tested (25%), particularly in those with severe or opposite sex DSD phenotypes. Interestingly, 48% of these variants were found in known DSD or SF-1 interacting genes, but no frequent gene-clusters were identified. Sex registration at birth varied, with <10% undergoing reassignment. Gonadectomy was performed in 30% and genital surgery in 58%. Associated organ anomalies were observed in 27% of individuals with a DSD, mainly concerning the spleen. Intrafamilial phenotypes also varied considerably.

INTERPRETATION

The observed phenotypic variability in individuals and families with NR5A1/SF-1 variants is large and remains unpredictable. It may often not be solely explained by the monogenic pathogenicity of the NR5A1/SF-1 variants but is likely influenced by additional genetic variants and as-yet-unknown factors.

FUNDING

Swiss National Science Foundation (320030-197725) and Boveri Foundation Zürich, Switzerland.

Rare disease variant curation from literature: assessing gaps with creatine transport deficiency in focus

BACKGROUND

Approximately 4-8% of the world suffers from a rare disease. Rare diseases are often difficult to diagnose, and many do not have approved therapies. Genetic sequencing has the potential to shorten the current diagnostic process, increase mechanistic understanding, and facilitate research on therapeutic approaches but is limited by the difficulty of novel variant pathogenicity interpretation and the communication of known causative variants. It is unknown how many published rare disease variants are currently accessible in the public domain.

RESULTS

This study investigated the translation of knowledge of variants reported in published manuscripts to publicly accessible variant databases. Variants, symptoms, biochemical assay results, and protein function from literature on the SLC6A8 gene associated with X-linked Creatine Transporter Deficiency (CTD) were curated and reported as a highly annotated dataset of variants with clinical context and functional details. Variants were harmonized, their availability in existing variant databases was analyzed and pathogenicity assignments were compared with impact algorithm predictions. 24% of the pathogenic variants found in PubMed articles were not captured in any database used in this analysis while only 65% of the published variants received an accurate pathogenicity prediction from at least one impact prediction algorithm.

CONCLUSIONS

Despite being published in the literature, pathogenicity data on patient variants may remain inaccessible for genetic diagnosis, therapeutic target identification, mechanistic understanding, or hypothesis generation. Clinical and functional details presented in the literature are important to make pathogenicity assessments. Impact predictions remain imperfect but are improving, especially for single nucleotide exonic variants, however such predictions are less accurate or unavailable for intronic and multi-nucleotide variants. Developing text mining workflows that use natural language processing for identifying diseases, genes and variants, along with impact prediction algorithms and integrating with details on clinical phenotypes and functional assessments might be a promising approach to scale literature mining of variants and assigning correct pathogenicity. The curated variants list created by this effort includes context details to improve any such efforts on variant curation for rare diseases.

IHH enhancer variant within neighboring NHEJ1 intron causes microphthalmia anophthalmia and coloboma

Genomic sequences residing within introns of few genes have been shown to act as enhancers affecting expression of neighboring genes. We studied an autosomal recessive phenotypic continuum of microphthalmia, anophthalmia and ocular coloboma, with no apparent coding-region disease-causing mutation. Homozygosity mapping of several affected Jewish Iranian families, combined with whole genome sequence analysis, identified a 0.5 Mb disease-associated chromosome 2q35 locus (maximal LOD score 6.8) harboring an intronic founder variant in NHEJ1, not predicted to affect NHEJ1. The human NHEJ1 intronic variant lies within a known specifically limb-development enhancer of a neighboring gene, Indian hedgehog (Ihh), known to be involved in eye development in mice and chickens. Through mouse and chicken molecular development studies, we demonstrated that this variant is within an Ihh enhancer that drives gene expression in the developing eye and that the identified variant affects this eye-specific enhancer activity. We thus delineate an Ihh enhancer active in mammalian eye development whose variant causes human microphthalmia, anophthalmia and ocular coloboma. The findings highlight disease causation by an intronic variant affecting the expression of a neighboring gene, delineating molecular pathways of eye development.

GRAPE: genomic relatedness detection pipeline

Classifying the degree of relatedness between pairs of individuals has both scientific and commercial applications. As an example, genome-wide association studies (GWAS) may suffer from high rates of false positive results due to unrecognized population structure. This problem becomes especially relevant with recent increases in large-cohort studies. Accurate relationship classification is also required for genetic linkage analysis to identify disease-associated loci. Additionally, DNA relatives matching service is one of the leading drivers for the direct-to-consumer genetic testing market. Despite the availability of scientific and research information on the methods for determining kinship and the accessibility of relevant tools, the assembly of the pipeline, which stably operates on a real-world genotypic data, requires significant research and development resources. Currently, there is no open source end-to-end solution for relatedness detection in genomic data, that is fast, reliable and accurate for both close and distant degrees of kinship, combines all the necessary processing steps to work on a real data, and is ready for production integration. To address this, we developed GRAPE: Genomic RelAtedness detection PipelinE. It combines data preprocessing, identity-by-descent (IBD) segments detection, and accurate relationship estimation. The project uses software development best practices, as well as Global Alliance for Genomics and Health (GA4GH) standards and tools. Pipeline efficiency is demonstrated on both simulated and real-world datasets. GRAPE is available from: https://github.com/genxnetwork/grape.

Clinical and molecular diagnosis of genodermatoses: Review and perspectives

Genodermatoses are a complex and heterogeneous group of genetic skin disorders characterized by variable expression and clinical and genetic heterogeneity, rendering their diagnosis challenging. DNA-based techniques, like whole-exome sequencing, can establish a diagnosis in 50% of cases. RNA-sequencing is emerging as an attractive tool that can obtain information regarding gene expression while integrating functional genomic data with regard to the interpretation of variants. This increases the diagnostic rate by an additional 10-15%. In the present review, we detail the clinical steps involved in the diagnosis of genodermatoses, as well as the current DNA-based technologies available to clinicians. Herein, the intention is to facilitate a better understanding of the possibilities and limitations of these diagnostic technologies. In addition, this review could guide dermatologists through new emerging techniques, such as RNA-sequencing and its applications to familiarizing them with future techniques. Currently, this multi-omics approach is likely the best strategy designed to promote the diagnosis of patients with genodermatoses and discover new skin disease genes that could result in novel targeted therapies.

In vivo adenine base editing corrects newborn murine model of Hurler syndrome

Mucopolysaccharidosis type I (MPS I) is a severe disease caused by loss-of-function mutation variants in the α-L-iduronidase (Idua) gene. In vivo genome editing represents a promising strategy to correct Idua mutations, and has the potential to permanently restore IDUA function over the lifespan of patients. Here, we used adenine base editing to directly convert A > G (TAG>TGG) in a newborn murine model harboring the Idua-W392X mutation, which recapitulates the human condition and is analogous to the highly prevalent human W402X mutation. We engineered a split-intein dual-adeno-associated virus 9 (AAV9) adenine base editor to circumvent the package size limit of AAV vectors. Intravenous injection of the AAV9-base editor system into MPS IH newborn mice led to sustained enzyme expression sufficient for correction of metabolic disease (GAGs substrate accumulation) and prevention of neurobehavioral deficits. We observed a reversion of the W392X mutation in 22.46 ± 6.74% of hepatocytes, 11.18 ± 5.25% of heart and 0.34 ± 0.12% of brain, along with decreased GAGs storage in peripheral organs (liver, spleen, lung and kidney). Collectively, these data showed the promise of a base editing approach to precisely correct a common genetic cause of MPS I in vivo and could be broadly applicable to the treatment of a wide array of monogenic diseases.

Roles of Skeletal Muscle in Development: A Bioinformatics and Systems Biology Overview

The ability to assess various cellular events consequent to perturbations, such as genetic mutations, disease states and therapies, has been recently revolutionized by technological advances in multiple "omics" fields. The resulting deluge of information has enabled and necessitated the development of tools required to both process and interpret the data. While of tremendous value to basic researchers, the amount and complexity of the data has made it extremely difficult to manually draw inference and identify factors key to the study objectives. The challenges of data reduction and interpretation are being met by the development of increasingly complex tools that integrate disparate knowledge bases and synthesize coherent models based on current biological understanding. This chapter presents an example of how genomics data can be integrated with biological network analyses to gain further insight into the developmental consequences of genetic perturbations. State of the art methods for conducting similar studies are discussed along with modern methods used to analyze and interpret the data.

MinION Whole-Genome Sequencing in Resource-Limited Settings: Challenges and Opportunities

Purpose of Review

The introduction of MinION whole-genome sequencing technology greatly increased and simplified complete genome sequencing in various fields of science across the globe. Sequences have been generated from complex organisms to microorganisms and are stored in genome databases that are readily accessible by researchers. Various new software for genome analysis, along with upgrades to older software packages, are being generated. New protocols are also being validated that enable WGS technology to be rapidly and increasingly used for sequencing in field settings.

Recent Findings

MinION WGS technology has been implemented in developed countries due to its advantages: portability, real-time analysis, and lower cost compared to other sequencing technologies. While these same advantages are critical in developing countries, MinION WGS technology is still under-utilized in resource-limited settings.

Summary

In this review, we look at the applications, advantages, challenges, and opportunities of using MinION WGS in resource-limited settings.

Mendelian gene identification through mouse embryo viability screening

BACKGROUND

The diagnostic rate of Mendelian disorders in sequencing studies continues to increase, along with the pace of novel disease gene discovery. However, variant interpretation in novel genes not currently associated with disease is particularly challenging and strategies combining gene functional evidence with approaches that evaluate the phenotypic similarities between patients and model organisms have proven successful. A full spectrum of intolerance to loss-of-function variation has been previously described, providing evidence that gene essentiality should not be considered as a simple and fixed binary property.

METHODS

Here we further dissected this spectrum by assessing the embryonic stage at which homozygous loss-of-function results in lethality in mice from the International Mouse Phenotyping Consortium, classifying the set of lethal genes into one of three windows of lethality: early, mid, or late gestation lethal. We studied the correlation between these windows of lethality and various gene features including expression across development, paralogy and constraint metrics together with human disease phenotypes. We explored a gene similarity approach for novel gene discovery and investigated unsolved cases from the 100,000 Genomes Project.

RESULTS

We found that genes in the early gestation lethal category have distinct characteristics and are enriched for genes linked with recessive forms of inherited metabolic disease. We identified several genes sharing multiple features with known biallelic forms of inborn errors of the metabolism and found signs of enrichment of biallelic predicted pathogenic variants among early gestation lethal genes in patients recruited under this disease category. We highlight two novel gene candidates with phenotypic overlap between the patients and the mouse knockouts.

CONCLUSIONS

Information on the developmental period at which embryonic lethality occurs in the knockout mouse may be used for novel disease gene discovery that helps to prioritise variants in unsolved rare disease cases.

Neuromuscular disorders: finding the missing genetic diagnoses

Neuromuscular disorders (NMDs) are a wide-ranging group of diseases that seriously affect the quality of life of affected individuals. The development of next-generation sequencing revolutionized the diagnosis of NMD, enabling the discovery of hundreds of NMD genes and many more pathogenic variants. However, the diagnostic yield of genetic testing in NMD cohorts remains incomplete, indicating a large number of genetic diagnoses are not identified through current methods. Fortunately, recent advancements in sequencing technologies, analytical tools, and high-throughput functional screening provide an opportunity to circumvent current challenges. Here, we discuss reasons for missing genetic diagnoses in NMD, how emerging technologies and tools can overcome these hurdles, and examine future approaches to improving diagnostic yields in NMD.

Unclassified white matter disorders: A diagnostic journey requiring close collaboration between clinical and laboratory services

BACKGROUND

Next generation sequencing studies have revealed an ever-increasing number of causes for genetic disorders of central nervous system white matter. A substantial number of disorders are identifiable from their specific pattern of biochemical and/or imaging findings for which single gene testing may be indicated. Beyond this group, the causes of genetic white matter disorders are unclear and a broader approach to genomic testing is recommended.

AIM

This study aimed to identify the genetic causes for a group of individuals with unclassified white matter disorders with suspected genetic aetiology and highlight the investigations required when the initial testing is non-diagnostic.

METHODS

Twenty-six individuals from 22 families with unclassified white matter disorders underwent deep phenotyping and genome sequencing performed on trio, or larger, family groups. Functional studies and transcriptomics were used to resolve variants of uncertain significance with potential clinical relevance.

RESULTS

Causative or candidate variants were identified in 15/22 (68.2%) families. Six of the 15 implicated genes had been previously associated with white matter disease (COL4A1, NDUFV1, SLC17A5, TUBB4A, BOLA3, DARS2). Patients with variants in the latter two presented with an atypical phenotype. The other nine genes had not been specifically associated with white matter disease at the time of diagnosis and included genes associated with monogenic syndromes, developmental disorders, and developmental and epileptic encephalopathies (STAG2, LSS, FIG4, GLS, PMPCA, SPTBN1, AGO2, SCN2A, SCN8A). Consequently, only 46% of the diagnoses would have been made via a current leukodystrophy gene panel test.

DISCUSSION

These results confirm the importance of broad genomic testing for patients with white matter disorders. The high diagnostic yield reflects the integration of deep phenotyping, whole genome sequencing, trio analysis, functional studies, and transcriptomic analyses.

CONCLUSIONS

Genetic white matter disorders are genetically and phenotypically heterogeneous. Deep phenotyping together with a range of genomic technologies underpin the identification of causes of unclassified white matter disease. A molecular diagnosis is essential for prognostication, appropriate management, and accurate reproductive counseling.

New Developments and Possibilities in Reanalysis and Reinterpretation of Whole Exome Sequencing Datasets for Unsolved Rare Diseases Using Machine Learning Approaches

Rare diseases impact the lives of 300 million people in the world. Rapid advances in bioinformatics and genomic technologies have enabled the discovery of causes of 20–30% of rare diseases. However, most rare diseases have remained as unsolved enigmas to date. Newer tools and availability of high throughput sequencing data have enabled the reanalysis of previously undiagnosed patients. In this review, we have systematically compiled the latest developments in the discovery of the genetic causes of rare diseases using machine learning methods. Importantly, we have detailed methods available to reanalyze existing whole exome sequencing data of unsolved rare diseases. We have identified different reanalysis methodologies to solve problems associated with sequence alterations/mutations, variation re-annotation, protein stability, splice isoform malfunctions and oligogenic analysis. In addition, we give an overview of new developments in the field of rare disease research using whole genome sequencing data and other omics.

The diagnostic journey of genetically defined neurodevelopmental disorders

BACKGROUND

The development of advanced genetic technologies has resulted in rapid identification of genetic etiologies of neurodevelopmental disorders (NDDs) and has transformed the classification and diagnosis of various NDDs. However, diagnostic genetics has far outpaced our ability to provide timely medical counseling, guidance, and care for patients with genetically defined NDDs. These patients and their caregivers present with an unmet need for care coordination across multiple domains including medical, developmental, and psychiatric care and for educational resources and guidance from care professionals. After a genetic diagnosis is made, families also face several barriers in access to informed diagnostic evaluations and medical support.

METHODS

As part of Care and Research in Neurogenetics (CARING), a multidisciplinary clinical program for children and adults with neurogenetic disorders, we conducted qualitative clinical interviews about the diagnostic journey of families. This included the overall timeline to receiving diagnoses, experiences before and after diagnosis, barriers to care, and resources that helped them to navigate the diagnostic process.

RESULTS

A total of 37 interviews were conducted with parents of children ages 16 months to 33 years. Several key themes were identified: (1) delays between initial caregiver observations and formal developmental or genetic diagnoses; (2) practical barriers to clinical evaluation and care, including long wait times for an appointment, lack of insurance coverage, availability of local evaluations, transportation difficulties, and native language differences; (3) the importance of being part of a patient advocacy group to help navigate the diagnostic journey; and (4) unique challenges faced by adults (18 years or older).

CONCLUSIONS

Families of children with complex neurodevelopmental and genetic disabilities face numerous challenges in finding adequate medical care and services for their child. They experience considerable delays in receiving timely diagnoses and face significant barriers that further delay the process of receiving access to services needed for the child's continued care. The gaps indicated in this study speak to the need for more comprehensive coordination of care for patients with intellectual and developmental disabilities, as well as the development of systematic, disorder-specific resources both for providers and families in order to improve patient outcomes.

PhenoApt leverages clinical expertise to prioritize candidate genes via machine learning

In recent years, exome sequencing (ES) has shown great utility in the diagnoses of Mendelian disorders. However, after rigorous filtering, a typical ES analysis still involves the interpretation of hundreds of variants, which greatly hinders the rapid identification of causative genes. Since the interpretations of ES data require comprehensive clinical analyses, taking clinical expertise into consideration can speed the molecular diagnoses of Mendelian disorders. To leverage clinical expertise to prioritize candidate genes, we developed PhenoApt, a phenotype-driven gene prioritization tool that allows users to assign a customized weight to each phenotype, via a machine-learning algorithm. Using the ability to rank causative genes in top-10 lists as an evaluation metric, baseline analysis demonstrated that PhenoApt outperformed previous phenotype-driven gene prioritization tools by a relative increase of 22.7%-140.0% in three independent, real-world, multi-center cohorts (cohort 1, n = 185; cohort 2, n = 784; and cohort 3, n = 208). Additional trials showed that, by adding weights to clinical indications, which should be explained by the causative gene, PhenoApt performance was improved by a relative increase of 37.3% in cohort 2 (n = 471) and 21.4% in cohort 3 (n = 208). Moreover, PhenoApt could assign an intrinsic weight to each phenotype based on the likelihood of its being a Mendelian trait using term frequency-inverse document frequency techniques. When clinical indications were assigned with intrinsic weights, PhenoApt performance was improved by a relative increase of 23.7% in cohort 2 and 15.5% in cohort 3. For the integration of PhenoApt into clinical practice, we developed a user-friendly website and a command-line tool.

Emerging Role of Clinical Genetics in CKD

Chronic kidney disease (CKD) afflicts 15% of adults in the United States, of whom 25% have a family history. Genetic testing is supportive in identifying and possibly confirming diagnoses of CKD, thereby guiding care. Advances in the clinical genetic evaluation include next-generation sequencing with targeted gene panels, whole exome sequencing, and whole genome sequencing. These platforms provide DNA sequence reads with excellent coverage throughout the genome and have identified novel genetic causes of CKD. New pathologic genetic variants identified in previously unrecognized biological pathways have elucidated disease mechanisms underlying CKD etiologies, potentially establishing prognosis and guiding treatment selection. Molecular diagnoses using genetic sequencing can detect rare, potentially treatable mutations, avoid misdiagnoses, guide selection of optimal therapy, and decrease the risk of unnecessary and potentially harmful interventions. Genetic testing has been widely adopted in pediatric nephrology; however, it is less frequently used to date in adult nephrology. Extension of clinical genetic approaches to adult patients may achieve similar benefits in diagnostic refinement and treatment selection. This review aimed to identify clinical CKD phenotypes that may benefit the most from genetic testing, outline the commonly available platforms, and provide examples of successful deployment of these approaches in CKD.

Orphan Medicine Incentives: How to Address the Unmet Needs of Rare Disease Patients by Optimizing the European Orphan Medicinal Product Landscape Guiding Principles and Policy Proposals by the European Expert Group for Orphan Drug Incentives (OD Expert Group)

Today policy makers face the challenge to devise a policy framework that improves orphan medicinal product (OMP) development by creating incentives to deliver treatments where there are none and to authorize innovative and transformative treatments where treatments already exist. The European Expert Group on Orphan Drug Incentives (hereafter, OD Expert Group) came together in 2020 to develop policy proposals to facilitate EU policy makers to meet this challenge. The group brings together representatives of the broad rare disease community, including researchers, academia, patient representatives, members of the investor community, rare disease companies and trade associations. The group’s work builds on the recognition that only an ambitious policy agenda developed in a multi-stakeholder setting can bring about the quantum leap needed to address unmet needs of rare disease patients today. Along the OMP development path, the OD Expert Group has identified four main needs that a policy revision should address: 1) Need to improve the R&D ecosystem for basic research and company take-up of development. 2) Need to improve the system of financial incentives and rewards. 3) Need to improve the flexibility, predictability and speed of the regulatory pathway. 4) Need to improve the coherence and predictability of demand and pricing for OMPs. This article presents the results of the OD Expert Group work as a set of guiding principles that the revision of the policy framework should follow and a set of 14 policy proposals that address the main needs of OMP development in Europe today.

Mining massive genomic data of two Swiss Braunvieh cattle populations reveals six novel candidate variants that impair reproductive success

Background

This study was carried out on the two Braunvieh populations reared in Switzerland, the dairy Brown Swiss (BS) and the dual-purpose Original Braunvieh (OB). We performed a genome-wide analysis of array data of trios (sire, dam, and offspring) from the routine genomic selection to identify candidate regions showing missing homozygosity and phenotypic associations with five fertility, ten birth, and nine growth-related traits. In addition, genome-wide single SNP regression studies based on 114,890 single nucleotide polymorphisms (SNPs) for each of the two populations were performed. Furthermore, whole-genome sequencing data of 430 cattle including 70 putative haplotype carriers were mined to identify potential candidate variants that were validated by genotyping the current population using a custom array.

Results

Using a trio-based approach, we identified 38 haplotype regions for BS and five for OB that segregated at low to moderate frequencies. For the BS population, we confirmed two known haplotypes, BH1 and BH2. Twenty-four variants that potentially explained the missing homozygosity and associated traits were detected, in addition to the previously reported TUBD1:p.His210Arg variant associated with BH2. For example, for BS we identified a stop-gain variant (p.Arg57*) in the MRPL55 gene in the haplotype region on chromosome 7. This region is associated with the ‘interval between first and last insemination’ trait in our data, and the MRPL55 gene is known to be associated with early pregnancy loss in mice. In addition, we discuss candidate missense variants in the CPT1C, MARS2, and ACSL5 genes for haplotypes mapped in BS. In OB, we highlight a haplotype region on chromosome 19, which is potentially caused by a frameshift variant (p.Lys828fs) in the LIG3 gene, which is reported to be associated with early embryonic lethality in mice. Furthermore, we propose another potential causal missense variant in the TUBGCP5 gene for a haplotype mapped in OB.

Conclusions

We describe, for the first time, several haplotype regions that segregate at low to moderate frequencies and provide evidence of causality by trait associations in the two populations of Swiss Braunvieh. We propose a list of six protein-changing variants as potentially causing missing homozygosity. These variants need to be functionally validated and incorporated in the breeding program.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00686-3.

High prevalence of multilocus pathogenic variation in neurodevelopmental disorders in the Turkish population

Neurodevelopmental disorders (NDDs) are clinically and genetically heterogenous; many such disorders are secondary to perturbation in brain development and/or function. The prevalence of NDDs is > 3%, resulting in significant sociocultural and economic challenges to society. With recent advances in family-based genomics, rare-variant analyses, and further exploration of the Clan Genomics hypothesis, there has been a logarithmic explosion in neurogenetic "disease-associated genes" molecular etiology and biology of NDDs; however, the majority of NDDs remain molecularly undiagnosed. We applied genome-wide screening technologies, including exome sequencing (ES) and whole-genome sequencing (WGS), to identify the molecular etiology of 234 newly enrolled subjects and 20 previously unsolved Turkish NDD families. In 176 of the 234 studied families (75.2%), a plausible and genetically parsimonious molecular etiology was identified. Out of 176 solved families, deleterious variants were identified in 218 distinct genes, further documenting the enormous genetic heterogeneity and diverse perturbations in human biology underlying NDDs. We propose 86 candidate disease-trait-associated genes for an NDD phenotype. Importantly, on the basis of objective and internally established variant prioritization criteria, we identified 51 families (51/176 = 28.9%) with multilocus pathogenic variation (MPV), mostly driven by runs of homozygosity (ROHs) - reflecting genomic segments/haplotypes that are identical-by-descent. Furthermore, with the use of additional bioinformatic tools and expansion of ES to additional family members, we established a molecular diagnosis in 5 out of 20 families (25%) who remained undiagnosed in our previously studied NDD cohort emanating from Turkey.

Deep clinicopathological phenotyping identifies a previously unrecognized pathogenic EMD splice variant

Exome sequencing (ES) has revolutionized rare disease management, yet only ~25%-30% of patients receive a molecular diagnosis. A limiting factor is the quality of available phenotypic data. Here, we describe how deep clinicopathological phenotyping yielded a molecular diagnosis for a 19-year-old proband with muscular dystrophy and negative clinical ES. Deep phenotypic analysis identified two critical data points: (1) the absence of emerin protein in muscle biopsy and (2) clinical features consistent with Emery-Dreifuss muscular dystrophy. Sequencing data analysis uncovered an ultra-rare, intronic variant in EMD, the gene encoding emerin. The variant, NM_000117.3: c.188-6A > G, is predicted to impact splicing by in silico tools. This case thus illustrates how better integration of clinicopathologic data into ES analysis can enhance diagnostic yield with implications for clinical practice.

Oligogenic Causes of Human Differences of Sex Development: Facing the Challenge of Genetic Complexity

BACKGROUND

Deviations of intrauterine sex determination and differentiation and postnatal sex development can result in a very heterogeneous group of differences of sex development (DSD) with a broad spectrum of phenotypes. Variants in genes involved in sexual development cause different types of DSD, but predicting the phenotype from an individual's genotype and vice versa remains challenging.

SUMMARY

Next Generation Sequencing (NGS) studies suggested that oligogenic inheritance contributes to the broad manifestation of DSD phenotypes. This review will focus on possible oligogenic inheritance in DSD identified by NGS studies with a special emphasis on NR5A1variants as an example of oligogenic origin associated with a broad range of DSD phenotypes. We thoroughly searched the literature for evidence regarding oligogenic inheritance in DSD diagnosis with NGS technology and describe the challenges to interpret contribution of these genes to DSD phenotypic variability and pathogenicity. Key Messages: Variants in common DSD genes like androgen receptor (AR), mitogen-activated protein kinase kinase kinase 1 (MAP3K1), Hydroxy-Delta-5-Steroid Dehydrogenase 3 Beta- And Steroid Delta-Isomerase 2 (HSD3B2), GATA Binding Protein 4 (GATA4), zinc finger protein friend of GATA family member 2 (ZFPM2), 17b-hydroxysteroid dehydrogenase type 3 (HSD17B3), mastermind-like domain-containing protein 1 (MAMLD1), and nuclear receptor subfamily 5 group A member 1 (NR5A1) have been detected in combination with additional variants in related genes in DSD patients with a broad range of phenotypes, implying a role of oligogenic inheritance in DSD, while still awaiting proof. Use of NGS approach for genetic diagnosis of DSD patients can reveal more complex genetic traits supporting the concept of oligogenic cause of DSD. However, assessing the pathomechanistic contribution of multiple gene variants on a DSD phenotype remains an unsolved conundrum.

Chromoanagenesis Event Underlies a de novo Pericentric and Multiple Paracentric Inversions in a Single Chromosome Causing Coffin-Siris Syndrome

Chromoanagenesis is a descriptive term that encompasses classes of catastrophic mutagenic processes that generate localized and complex chromosome rearrangements in both somatic and germline genomes. Herein, we describe a 5-year-old female presenting with a constellation of clinical features consistent with a clinical diagnosis of Coffin–Siris syndrome 1 (CSS1). Initial G-banded karyotyping detected a 90-Mb pericentric and a 47-Mb paracentric inversion on a single chromosome. Subsequent analysis of short-read whole-genome sequencing data and genomic optical mapping revealed additional inversions, all clustered on chromosome 6, one of them disrupting ARID1B for which haploinsufficiency leads to the CSS1 disease trait (MIM:135900). The aggregate structural variant data show that the resolved, the resolved derivative chromosome architecture presents four de novo inversions, one pericentric and three paracentric, involving six breakpoint junctions in what appears to be a shuffling of genomic material on this chromosome. Each junction was resolved to nucleotide-level resolution with mutational signatures suggestive of non-homologous end joining. The disruption of the gene ARID1B is shown to occur between the fourth and fifth exon of the canonical transcript with subsequent qPCR studies confirming a decrease in ARID1B expression in the patient versus healthy controls. Deciphering the underlying genomic architecture of chromosomal rearrangements and complex structural variants may require multiple technologies and can be critical to elucidating the molecular etiology of a patient’s clinical phenotype or resolving unsolved Mendelian disease cases.

Transcriptome profiling implicated in beneficiary actions of kimchi extracts against Helicobacter pylori infection

Dietary intervention to prevent Helicobacter pylori (H. pylori)-gastric cancer might be ideal because of no risk of bacterial resistance, safety, and rejuvenating action of atrophic gastritis. We have published data about the potential of fermented kimchi as nutritional approach for H. pylori. Hence recent advances in RNAseq analysis lead us to investigate the transcriptome analysis to explain these beneficiary actions of kimchi. gastric cells were infected with either H. pylori or H. pylori plus kimchi. 943 genes were identified as significantly increased or decreased genes according to H. pylori infection and 68 genes as significantly changed between H. pylori infection and H. pylori plus kimchi (p<0.05). Gene classification and Medline database showed DLL4, FGF18, PTPRN, SLC7A11, CHAC1, FGF21, ASAN, CTH, and CREBRF were identified as significantly increased after H. pylori, but significantly decreased with kimchi and NEO1, CLDN8, KLRG1, and IGFBP1 were identified as significantly decreased after H. pylori, but increased with kimchi. After KEGG and STRING-GO analysis, oxidative stress, ER stress, cell adhesion, and apoptosis genes were up-regulated with H. pylori infection but down-regulated with kimchi, whereas tissue regeneration, cellular anti-oxidative response, and anti-inflammation genes were reversely regulated with kimchi (p<0.01). Conclusively, transcriptomes of H. pylori plus kimchi showed significant biological actions.

The evolving genetic landscape of congenital disorders of glycosylation

Congenital Disorders of Glycosylation (CDG) are an expanding and complex group of rare genetic disorders caused by defects in the glycosylation of proteins and lipids. The genetic spectrum of CDG is extremely broad with mutations in over 140 genes leading to a wide variety of symptoms ranging from mild to severe and life-threatening. There has been an expansion in the genetic complexity of CDG in recent years. More specifically several examples of alternate phenotypes in recessive forms of CDG and new types of CDG following an autosomal dominant inheritance pattern have been identified. In addition, novel genetic mechanisms such as expansion repeats have been reported and several already known disorders have been classified as CDG as their pathophysiology was better elucidated. Furthermore, we consider the future and outlook of CDG genetics, with a focus on exploration of the non-coding genome using whole genome sequencing, RNA-seq and multi-omics technology.

Rare Neurovascular Diseases in Korea: Classification and Related Genetic Variants

Rare neurovascular diseases (RNVDs) have not been well-recognized in Korea. They involve the central nervous system and greatly affect the patients' lives. However, these diseases are difficult to diagnose and treat due to their rarity and incurability. We established a list of RNVDs by referring to the previous literature and databases worldwide to better understand the diseases and their current management status. We categorized 68 RNVDs based on their pathophysiology and clinical manifestations and estimated the prevalence of each disease in Korea. Recent advances in genetic, molecular, and developmental research have enabled further understanding of these RNVDs. Herein, we review each disease, while considering its classification based on updated pathologic mechanisms, and discuss the management status of RNVD in Korea.

Complex Modes of Inheritance in Hereditary Red Blood Cell Disorders: A Case Series Study of 155 Patients

Hereditary erythrocytes disorders include a large group of conditions with heterogeneous molecular bases and phenotypes. We analyzed here a case series of 155 consecutive patients with clinical suspicion of hereditary erythrocyte defects referred to the Medical Genetics Unit from 2018 to 2020. All of the cases followed a diagnostic workflow based on a targeted next-generation sequencing panel of 86 genes causative of hereditary red blood cell defects. We obtained an overall diagnostic yield of 84% of the tested patients. Monogenic inheritance was seen for 69% (107/155), and multi-locus inheritance for 15% (23/155). PIEZO1 and SPTA1 were the most mutated loci. Accordingly, 16/23 patients with multi-locus inheritance showed dual molecular diagnosis of dehydrated hereditary stomatocytosis/xerocytosis and hereditary spherocytosis. These dual inheritance cases were fully characterized and were clinically indistinguishable from patients with hereditary spherocytosis. Additionally, their ektacytometry curves highlighted alterations of dual inheritance patients compared to both dehydrated hereditary stomatocytosis and hereditary spherocytosis. Our findings expand the genotypic spectrum of red blood cell disorders and indicate that multi-locus inheritance should be considered for analysis and counseling of these patients. Of note, the genetic testing was crucial for diagnosis of patients with a complex mode of inheritance.

Studying Müllerian duct anomalies - from cataloguing phenotypes to discovering causation

Müllerian duct anomalies (MDAs) are developmental disorders of the Müllerian duct, the embryonic anlage of most of the female reproductive tract. The prevalence of MDAs is 6.7% in the general female population and 16.7% in women who exhibit recurrent miscarriages. Individuals affected by these anomalies suffer from high rates of infertility, first-trimester pregnancy losses, premature labour, placental retention, foetal growth retardation and foetal malpresentations. The aetiology of MDAs is complex and heterogeneous, displaying a range of clinical pictures that generally lack a direct genotype-phenotype correlation. De novo and familial cases sharing the same genomic lesions have been reported. The familial cases follow an autosomal-dominant inheritance, with reduced penetrance and variable expressivity. Furthermore, few genetic factors and molecular pathways underpinning Müllerian development and dysregulations causing MDAs have been identified. The current knowledge in this field predominantly derives from loss-of-function experiments in mouse and chicken models, as well as from human genetic association studies using traditional approaches, such as microarrays and Sanger sequencing, limiting the discovery of causal factors to few genetic entities from the coding genome. In this Review, we summarise the current state of the field, discuss limitations in the number of studies and patient samples that have stalled progress, and review how the development of new technologies provides a unique opportunity to overcome these limitations. Furthermore, we discuss how these new technologies can improve functional validation of potential causative alterations in MDAs.

Summary: Here, we review the current knowledge about Müllerian duct anomalies in the context of new high-throughput technologies and model systems and their implications in the prevention of these disorders.

Commonalities across computational workflows for uncovering explanatory variants in undiagnosed cases

PURPOSE

Genomic sequencing has become an increasingly powerful and relevant tool to be leveraged for the discovery of genetic aberrations underlying rare, Mendelian conditions. Although the computational tools incorporated into diagnostic workflows for this task are continually evolving and improving, we nevertheless sought to investigate commonalities across sequencing processing workflows to reveal consensus and standard practice tools and highlight exploratory analyses where technical and theoretical method improvements would be most impactful.

METHODS

We collected details regarding the computational approaches used by a genetic testing laboratory and 11 clinical research sites in the United States participating in the Undiagnosed Diseases Network via meetings with bioinformaticians, online survey forms, and analyses of internal protocols.

RESULTS

We found that tools for processing genomic sequencing data can be grouped into four distinct categories. Whereas well-established practices exist for initial variant calling and quality control steps, there is substantial divergence across sites in later stages for variant prioritization and multimodal data integration, demonstrating a diversity of approaches for solving the most mysterious undiagnosed cases.

CONCLUSION

The largest differences across diagnostic workflows suggest that advances in structural variant detection, noncoding variant interpretation, and integration of additional biomedical data may be especially promising for solving chronically undiagnosed cases.

Improving diagnostics of rare genetic diseases with NGS approaches

According to a rough estimate, one in fifteen people worldwide is affected by a rare disease. Rare diseases are therefore common in clinical practice; however, timely diagnosis of rare diseases is still challenging. Introduction of novel methods based on next-generation sequencing (NGS) technology offers a successful diagnosis of genetically heterogeneous disorders, even in case of unclear clinical diagnostic hypothesis. However, the application of novel technology differs among the centres and health systems significantly. Our goal is to discuss the impact of the implementation of NGS in the diagnosis of rare diseases and present advantages along with challenges of diagnostic approach. Systematic implementation of NGS in health systems can significantly improve the access of patients with rare diseases to diagnosis and reduce the dependence of national health systems for cross-border collaboration.

How to design a national genomic project-a systematic review of active projects

An increasing number of countries are investing efforts to exploit the human genome, in order to improve genetic diagnostics and to pave the way for the integration of precision medicine into health systems. The expected benefits include improved understanding of normal and pathological genomic variation, shorter time-to-diagnosis, cost-effective diagnostics, targeted prevention and treatment, and research advances.We review the 41 currently active individual national projects concerning their aims and scope, the number and age structure of included subjects, funding, data sharing goals and methods, and linkage with biobanks, medical data, and non-medical data (exposome). The main aims of ongoing projects were to determine normal genomic variation (90%), determine pathological genomic variation (rare disease, complex diseases, cancer, etc.) (71%), improve infrastructure (59%), and enable personalized medicine (37%). Numbers of subjects to be sequenced ranges substantially, from a hundred to over a million, representing in some cases a significant portion of the population. Approximately half of the projects report public funding, with the rest having various mixed or private funding arrangements. 90% of projects report data sharing (public, academic, and/or commercial with various levels of access) and plan on linking genomic data and medical data (78%), existing biobanks (44%), and/or non-medical data (24%) as the basis for enabling personal/precision medicine in the future.Our results show substantial diversity in the analysed categories of 41 ongoing national projects. The overview of current designs will hopefully inform national initiatives in designing new genomic projects and contribute to standardisation and international collaboration.

The History of Gene Hunting in Hereditary Spinocerebellar Degeneration: Lessons From the Past and Future Perspectives

Hereditary spinocerebellar degeneration (SCD) encompasses an expanding list of rare diseases with a broad clinical and genetic heterogeneity, complicating their diagnosis and management in daily clinical practice. Correct diagnosis is a pillar for precision medicine, a branch of medicine that promises to flourish with the progressive improvements in studying the human genome. Discovering the genes causing novel Mendelian phenotypes contributes to precision medicine by diagnosing subsets of patients with previously undiagnosed conditions, guiding the management of these patients and their families, and enabling the discovery of more causes of Mendelian diseases. This new knowledge provides insight into the biological processes involved in health and disease, including the more common complex disorders. This review discusses the evolution of the clinical and genetic approaches used to diagnose hereditary SCD and the potential of new tools for future discoveries.

Current and Emerging Clinical Treatment in Mitochondrial Disease

Primary mitochondrial disease (PMD) is a group of complex genetic disorders that arise due to pathogenic variants in nuclear or mitochondrial genomes. Although PMD is one of the most prevalent inborn errors of metabolism, it often exhibits marked phenotypic variation and can therefore be difficult to recognise. Current treatment for PMD revolves around supportive and preventive approaches, with few disease-specific therapies available. However, over the last decade there has been considerable progress in our understanding of both the genetics and pathophysiology of PMD. This has resulted in the development of a plethora of new pharmacological and non-pharmacological therapies at varying stages of development. Many of these therapies are currently undergoing clinical trials. This review summarises the latest emerging therapies that may become mainstream treatment in the coming years. It is distinct from other recent reviews in the field by comprehensively addressing both pharmacological non-pharmacological therapy from both a bench and a bedside perspective. We highlight the current and developing therapeutic landscape in novel pharmacological treatment, dietary supplementation, exercise training, device use, mitochondrial donation, tissue replacement gene therapy, hypoxic therapy and mitochondrial base editing.

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.

Transcriptome profiling analysis of the response to walnut polyphenol extract in Helicobacter pylori-infected cells

Dietary intervention to prevent Helicobacter pylori (H. pylori)-associated gastric diseases seems to be ideal with no risk of bacterial resistance, safe long-term intervention, and correcting pathogenic mechanisms including rejuvenation of precancerous atrophic gastritis and anti-mutagenesis. A transcriptome as set of all RNAs transcribed by certain tissues or cells demonstrates gene functions and reveals the molecular mechanism of specific biological processes against diseases. Here, we have performed RNAseq and bioinformatic analysis to explain proof of concept that walnut intake can rescue from H. pylori infection and explore unidentified mode of actions of walnut polyphenol extract (WPE). As results, BIRC3, SLC25A4, f3 transcription, VEGFA, AZU1, HMOX1, RAB3A, RELBTNIP1, ETFB, INPP5J, PPME1, RHOB, TPI1, FOSL1, JUND.RELB, KLF2, MUC1, NDRG1, ALDOA, ENO1, PFKP, GPI, GDF15, and NRTN genes were newly discovered to be enriched with WPE, whereas CCR4, BLNK, CCR7, CXCR4, CDO1, KLSG1, SELE, RASGRP2, PIK3R3, TSPAN32, HOXC-AS3, HCG8, BTNL8, and CXCL3 genes as inhibitory targets by WPE in H. pylori infection. We identified additional genes what WPE afforded actions of avoiding H. pylori-driven onco-inflammation and rejuvenating precancerous atrophic gastritis. Conclusively, after applying RNAseq analysis in order to document walnut intake for precision medicine against H. pylori infection, significant transcriptomic profiling applicable for validation were drawn.

A Multi-Strategy Sequencing Workflow in Inherited Retinal Dystrophies: Routine Diagnosis, Addressing Unsolved Cases and Candidate Genes Identification

The management of unsolved inherited retinal dystrophies (IRD) cases is challenging since no standard pipelines have been established. This study aimed to define a diagnostic algorithm useful for the diagnostic routine and to address unsolved cases. Here, we applied a Next-Generation Sequencing-based workflow, including a first step of panel sequencing (PS) followed by clinical-exome sequencing (CES) and whole-exome sequencing (WES), in 46 IRD patients belonging to 42 families. Twenty-six likely causal variants in retinal genes were found by PS and CES. CES and WES allowed proposing two novel candidate loci (WDFY3 and a X-linked region including CITED1), both abundantly expressed in human retina according to RT-PCR and immunohistochemistry. After comparison studies, PS showed the best quality and cost values, CES and WES involved similar analytical efforts and WES presented the highest diagnostic yield. These results reinforce the relevance of panels as a first step in the diagnostic routine and suggest WES as the next strategy for unsolved cases, reserving CES for the simultaneous study of multiple conditions. Standardizing this algorithm would enhance the efficiency and equity of clinical genetics practice. Furthermore, the identified candidate genes could contribute to increase the diagnostic yield and expand the mutational spectrum in these disorders.

Multi-Gene Next-Generation Sequencing for Molecular Diagnosis of Autosomal Recessive Congenital Ichthyosis: A Genotype-Phenotype Study of Four Italian Patients

Autosomal recessive congenital ichthyoses (ARCI) are rare genodermatosis disorders characterized by phenotypic and genetic heterogeneity. At least fourteen genes so far have been related to ARCI; however, despite genetic heterogeneity, phenotypes associated with mutation of different ARCI genes may overlap, thereby making difficult their clinical and molecular classification. In addition, molecular tests for diagnosis of such an extremely rare heterogeneous inherited disease are not easily available in clinical settings. In the attempt of identifying the genetic cause of the disease in four Italian patients with ARCI, we performed next-generation sequencing (NGS) analysis targeting 4811 genes that have been previously linked to human genetic diseases; we focused our analysis on the 13 known ARCI genes comprised in the panel. Nine different variants including three novel small nucleotide changes and two novel large deletions have been identified and validated in the ABCA12, ALOX12B, CYP4F22, and SULT2B1 genes. Notably, two patients had variants in more than one gene. The identification and validation of new pathogenic ABCA12, ALOX12B, CYP4F22, and SULT2B1 variants through multi-gene NGS in four cases of ARCI further highlight the importance of these genes in proper skin function and development.

Clinical Application of Whole Exome Sequencing to Identify Rare but Remediable Neurologic Disorders

Background: The aim of this study was to describe the application of whole exome sequencing (WES) in the accurate genetic diagnosis and personalized treatment of extremely rare neurogenetic disorders. Methods: From 2017 to 2019, children with neurodevelopmental symptoms were evaluated using WES in the pediatric neurology clinic and medical genetics center. The clinical presentation, laboratory findings including the genetic results from WES, and diagnosis-based treatment and outcomes of the four patients are discussed. Results: A total of 376 children with neurodevelopmental symptom were evaluated by WES, and four patients (1.1%) were diagnosed with treatable neurologic disorders. Patient 1 (Pt 1) showed global muscle hypotonia, dysmorphic facial features, and multiple anomalies beginning in the perinatal period. Pt 1 was diagnosed with congenital myasthenic syndrome 22 of PREPL deficiency. Pt 2 presented with hypotonia and developmental arrest and was diagnosed with autosomal recessive dopa-responsive dystonia due to TH deficiency. Pt 3, who suffered from intractable epilepsy and progressive cognitive decline, was diagnosed with epileptic encephalopathy 47 with a heterozygous FGF12 mutation. Pt 4 presented with motor delay and episodic ataxia and was diagnosed with episodic ataxia type II (heterozygous CACNA1A mutation). The patients’ major neurologic symptoms were remarkably relieved with pyridostigmine (Pt 1), levodopa (Pt 2), sodium channel blocker (Pt 3), and acetazolamide (Pt 4), and most patients regained developmental milestones in the follow-up period (0.4 to 3 years). Conclusions: The early application of WES helps in the identification of extremely rare genetic diseases, for which effective treatment modalities exist. Ultimately, WES resulted in optimal clinical outcomes of affected patients.

Targeted Next-Generation Sequencing in the Diagnosis of Facial Dysostoses

Background

Defects in the development of the first and second pharyngeal arches and their derivatives result in abnormal formation of the craniofacial complex, consequently giving rise to facial dysostoses (FDs). FDs represent a group of rare and highly heterogeneous disease entities that encompass mandibulofacial dysostoses (MFDs) with normal extremities and acrofacial dysostoses (AFDs) with limb anomalies in addition to craniofacial defects.

Methods

We examined 11 families with variable clinical symptoms of FDs, in most of which only one member was affected. We applied two custom gene panels—first comprising 37 genes related to the genetic disorders of craniofacial development such as FDs (On-Demand AmpliSeq Thermo Fisher Scientific gene panel with two primer pools) and second composed of 61 genes and 11 single nucleotide variants (SNVs) known to be involved in the development of skull malformations, mainly in the form of craniosynostoses (SureSelect Agilent Technologies). Targeted next-generation sequencing (NGS) was performed using the Ion Torrent S5 platform. To confirm the presence of each detected variant, we have analyzed a genomic region of interest using Sanger sequencing.

Results

In this paper, we summarized the results of custom targeted gene panel sequencing in the cohort of sixteen patients from 11 consecutive families affected by distinct forms of FDs. We have found three novel pathogenic variants in the TCOF1 gene—c.2145_2148dupAAAG p.(Ser717Lysfs^∗42), c.4370delA p.(Lys1457Argfs^∗118), c.83G>C p.(Arg28Pro) causing Treacher Collins syndrome type 1, two novel missense variants in the EFTUD2 gene–c.491A>G p.(Asp164Gly) and c.779T>A p.(Ile260Asn) in two female patients affected by acrofacial dysostosis Guion-Almeida type, one previously reported–c.403C>T (p.Arg135Cys), as well as one novel missense variant–c.128C>T p.(Pro43Leu) in the DHODH gene in the male patient with Miller syndrome and finally one known pathogenic variant c.574G>T p.(Glu192^∗) in the SF3B4 gene in the patient with Nager syndrome.

Conclusion

Our study confirms the efficiency and clinical utility of the targeted gene panel sequencing and shows that this strategy is suitable and efficient in the molecular screening of variable forms of FDs.

Identification of Novel BRCA1 and RAD50 Mutations Associated With Breast Cancer Predisposition in Tunisian Patients

Background

Deleterious mutations on BRCA1/2 genes are known to confer high risk of developing breast and ovarian cancers. The identification of these mutations not only helped in selecting high risk individuals that need appropriate prevention approaches but also led to the development of the PARP-inhibitors targeted therapy. This study aims to assess the prevalence of the most frequent BRCA1 mutation in Tunisia, c.211dupA, and provide evidence of its common origin as well as its clinicopathological characteristics. We also aimed to identify additional actionable variants using classical and next generation sequencing technologies (NGS) which would allow to implement cost-effective genetic testing in limited resource countries.

Patients and Methods

Using sanger sequencing, 112 breast cancer families were screened for c.211dupA. A set of patients that do not carry this mutation were investigated using NGS. Haplotype analysis was performed to assess the founder effect and to estimate the age of this mutation. Correlations between genetic and clinical data were also performed.

Results

The c.211dupA mutation was identified in 8 carriers and a novel private BRCA1 mutation, c.2418dupA, was identified in one carrier. Both mutations are likely specific to North-Eastern Tunisia. Haplotype analysis supported the founder effect of c.211dupA and showed its recent origin. Phenotype-genotype correlation showed that both BRCA1 mutations seem to be associated with a severe phenotype. Whole Exome Sequencing (WES) analysis of a BRCA negative family revealed a Variant of Unknown Significance, c.3647C > G on RAD50. Molecular modeling showed that this variant could be classified as deleterious as it is responsible for destabilizing the RAD50 protein structure. Variant prioritization and pathway analysis of the WES data showed additional interesting candidate genes including MITF and ANKS6.

Conclusion

We recommend the prioritization of BRCA1-c.211dupA screening in high risk breast cancer families originating from the North-East of Tunisia. We also highlighted the importance of NGS in detecting novel mutations, such as RAD50-c.3647C > G. In addition, we strongly recommend using data from different ethnic groups to review the pathogenicity of this variant and reconsider its classification in ClinVar.

Next Generation Sequencing and Bioinformatics Analysis of Family Genetic Inheritance

Mendelian and complex genetic trait diseases continue to burden and affect society both socially and economically. The lack of effective tests has hampered diagnosis thus, the affected lack proper prognosis. Mendelian diseases are caused by genetic mutations in a singular gene while complex trait diseases are caused by the accumulation of mutations in either linked or unlinked genomic regions. Significant advances have been made in identifying novel diseases associated mutations especially with the introduction of next generation and third generation sequencing. Regardless, some diseases are still without diagnosis as most tests rely on SNP genotyping panels developed from population based genetic analyses. Analysis of family genetic inheritance using whole genomes, whole exomes or a panel of genes has been shown to be effective in identifying disease-causing mutations. In this review, we discuss next generation and third generation sequencing platforms, bioinformatic tools and genetic resources commonly used to analyze family based genomic data with a focus on identifying inherited or novel disease-causing mutations. Additionally, we also highlight the analytical, ethical and regulatory challenges associated with analyzing personal genomes which constitute the data used for family genetic inheritance.