PhenoDB: a new web-based tool for the collection, storage, and analysis of phenotypic features

A Brazilian case of IFAP syndrome with severe congenital ichthyosis and limb malformations caused by a rare variant in MBTPS2

OBJECTIVE

The classic triad, which defines IFAP syndrome, is ichthyosis follicularis, alopecia, and photophobia. It is a rare X-linked genetic disorder characterized by multiple congenital anomalies with variable severity, caused by pathogenic variants in the MBTPS2 gene, which encodes a zinc metalloprotease that is essential for normal development. This study aimed to report a case of a Brazilian patient with IFAP syndrome presenting skeletal anomalies, which is a rare finding among patients from different families.

CASE DESCRIPTION

We describe a male proband with IFAP syndrome showing severe ichthyosis congenita, cryptorchidism, limb malformation, and comprising the BRESHECK syndrome features. Using whole-exome sequencing, we identified a rare missense variant in hemizygosity in the MBTPS2 gene, which had not been identified in other family members.

COMMENTS

This is the first diagnosis of IFAP syndrome in Brazil with a molecular investigation. The present case study thus expands our knowledge on the mutational spectrum of MBPTS2 associated with IFAP syndrome.

Phenotype-aware prioritisation of rare Mendelian disease variants

A molecular diagnosis from the analysis of sequencing data in rare Mendelian diseases has a huge impact on the management of patients and their families. Numerous patient phenotype-aware variant prioritisation (VP) tools have been developed to help automate this process, and shorten the diagnostic odyssey, but performance statistics on real patient data are limited. Here we identify, assess, and compare the performance of all up-to-date, freely available, and programmatically accessible tools using a whole-exome, retinal disease dataset from 134 individuals with a molecular diagnosis. All tools were able to identify around two-thirds of the genetic diagnoses as the top-ranked candidate, with LIRICAL performing best overall. Finally, we discuss the challenges to overcome most cases remaining undiagnosed after current, state-of-the-art practices.

Exome Sequencing Identifies a Biallelic GALNS Variant (p.Asp233Asn) Causing Mucopolysaccharidosis Type IVA in a Pakistani Consanguineous Family

Mucopolysaccharidoses (MPS) type IVA is a lysosomal storage disease that mainly affects the skeletal system and is caused by a deficiency of the enzyme N-acetylgalactosamine-6-sulfatase (GALNS). The condition can mistakenly be diagnosed as a primary skeletal dysplasia such as spondylo-epiphyseal dysplasia, which shares many similar phenotypic features. Here, we utilised whole exome sequencing to make the diagnosis of MPS IVA in a resource poor country. We report for the first time the identification of a biallelic GALNS missense variant (c.697G>A, p.Asp233Asn) in the Pakistani population and highlight the potential contribution that academic institutions can make in rare disease diagnosis in the absence of a developed clinical genetic service.

PhenoRerank: A re-ranking model for phenotypic concept recognition pre-trained on human phenotype ontology

The study aims at developing a neural network model to improve the performance of Human Phenotype Ontology (HPO) concept recognition tools. We used the terms, definitions, and comments about the phenotypic concepts in the HPO database to train our model. The document to be analyzed is first split into sentences and annotated with a base method to generate candidate concepts. The sentences, along with the candidate concepts, are then fed into the pre-trained model for re-ranking. Our model comprises the pre-trained BlueBERT and a feature selection module, followed by a contrastive loss. We re-ranked the results generated by three robust HPO annotation tools and compared the performance against most of the existing approaches. The experimental results show that our model can improve the performance of the existing methods. Significantly, it boosted 3.0% and 5.6% in F1 score on the two evaluated datasets compared with the base methods. It removed more than 80% of the false positives predicted by the base methods, resulting in up to 18% improvement in precision. Our model utilizes the descriptive data in the ontology and the contextual information in the sentences for re-ranking. The results indicate that the additional information and the re-ranking model can significantly enhance the precision of HPO concept recognition compared with the base method.

Predicting genes from phenotypes using human phenotype ontology (HPO) terms

The interpretation of genomic variants following whole exome sequencing (WES) can be aided using human phenotype ontology (HPO) terms to standardize clinical features and predict causative genes. We performed WES on 453 patients diagnosed prior to 18 years of age and identified 114 pathogenic (P) or likely pathogenic (LP) variants in 112 patients. We utilized PhenoDB to extract HPO terms from provider notes and then used Phen2Gene to generate a gene score and gene ranking from each list of HPO terms. We assigned Phen2Gene gene rankings to 6 rank classes, with class 1 covering raw gene rankings of 1 to 10 and class 2 covering rankings from 11 to 50 out of a total of 17,126 possible gene rankings. Phen2Gene ranked causative genes into rank class 1 or 2 in 27.7% of cases and the genes in rank class 1 were all associated with well-characterized phenotypes. We found significant associations between the gene score and the number of years, since the gene was first published, the number of HPO terms with an hierarchical depth greater or equal to 11, and the number of Online Mendelian Inheritance in Man terms associated with the phenotype and gene. We conclude that genes associated with recognizable phenotypes and terms deep in the HPO hierarchy have the best chance of producing a high gene score and ranking in class 1 to 2 using Phen2Gene software with HPO terms. Clinicians and laboratory staff should consider these results when HPO terms are employed to prioritize candidate genes.

The impact of GeneMatcher on international data sharing and collaboration

GeneMatcher (genematcher.org) is a tool designed to connect individuals with an interest in the same gene. Now used around the world to create collaborations and generate the evidence needed to support novel disease gene identification, GeneMatcher is a founding member of the Matchmaker Exchange (MME; matchmakerexchange.org) and strongest possible advocate for global data sharing including those in resource‐limited environments. As of October 1, 2021, there are 12,531 submitters from 94 countries who have submitted 58,134 submissions with 13,498 unique genes in the database. Among these genes, 8970 (64%) have matched at least once and the total number of matches is 378,806, growing by about 10,000 per month. GeneMatcher submitters increase by 80–120 each month and submissions grow by >800 per month, while unique genes and gene matches continue to grow steadily at rate of about 80 per month. The number of genes without a match peaked at 4371 in February of 2019 and despite the increase in the number of new submissions, the number of unique genes without a match continues to slowly decline, currently standing at 4,016. All submissions in GeneMatcher are available for matching across the MME.

Identification of NID1 as a novel candidate susceptibility gene for familial non-medullary thyroid carcinoma using whole-exome sequencing

The genetics underlying non-syndromic familial non-medullary thyroid carcinoma (FNMTC) is still poorly understood. To identify susceptibility genes for FNMTC, we performed whole-exome sequencing (WES) in a Brazilian family affected by papillary thyroid carcinoma (PTC) in three consecutive generations. WES was performed in four affected and two unaffected family members. Manual inspection in over 100 previously reported susceptibility genes for FNMTC showed that no variants in known genes co-segregated with disease phenotype in this family. Novel candidate genes were investigated using PhenoDB and filtered using Genome Aggregation (gnomAD) and Online Archive of Brazilian Mutations (ABraOM) population databases. The missense variant p.Ile657Met in the NID1 gene was the only variant that co-segregated with the disease, while absent in unaffected family members and controls. The allele frequency for this variant was <0.0001 in the gnomAD and ABbraOM databases. In silico analysis predicted the variant to be deleterious or likely damaging to the protein function. Somatic mutations in NID1 gene were found in nearly 500 cases of different cancer subtypes in the intOGen platform. Immunohistochemistry analysis showed NID1 expression in PTC cells, while it was absent in normal thyroid tissue. Our findings were corroborated using data from the TCGA cohort. Moreover, higher expression of NID1 was associated with higher likelihood of relapse after treatment and N1b disease in PTCs from the TCGA cohort. Although replication studies are needed to better understand the role of this variant in the FNMTC susceptibility, the NID1 variant (c.1971T>G) identified in this study fulfills several criteria that suggest it as a new FNMTC predisposing gene.

PhenoDB, GeneMatcher and VariantMatcher, tools for analysis and sharing of sequence data

Background

With the advent of whole exome (ES) and genome sequencing (GS) as tools for disease gene discovery, rare variant filtering, prioritization and data sharing have become essential components of the search for disease genes and variants potentially contributing to disease phenotypes. The computational storage, data manipulation, and bioinformatic interpretation of thousands to millions of variants identified in ES and GS, respectively, is a challenging task. To aid in that endeavor, we constructed PhenoDB, GeneMatcher and VariantMatcher.

Results

PhenoDB is an accessible, freely available, web-based platform that allows users to store, share, analyze and interpret their patients’ phenotypes and variants from ES/GS data. GeneMatcher is accessible to all stakeholders as a web-based tool developed to connect individuals (researchers, clinicians, health care providers and patients) around the globe with interest in the same gene(s), variant(s) or phenotype(s). Finally, VariantMatcher was developed to enable public sharing of variant-level data and phenotypic information from individuals sequenced as part of multiple disease gene discovery projects. Here we provide updates on PhenoDB and GeneMatcher applications and implementation and introduce VariantMatcher.

Conclusion

Each of these tools has facilitated worldwide data sharing and data analysis and improved our ability to connect genes to phenotypic traits. Further development of these platforms will expand variant analysis, interpretation, novel disease-gene discovery and facilitate functional annotation of the human genome for clinical genomics implementation and the precision medicine initiative.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-021-01916-z.

Clinical and molecular evaluation of 13 Brazilian patients with Gomez-López-Hernández syndrome

We aim to characterize patients with Gomez-López-Hernández syndrome (GLHS) clinically and to investigate them molecularly. A clinical protocol, including a morphological and neuropsychological assessment, was applied to 13 patients with GLHS. Single-nucleotide polymorphism (SNP) array and whole-exome sequencing were undertaken; magnetic resonance imaging was performed in 12 patients, including high-resolution, heavily T2-weighted sequences (HRT2) in 6 patients to analyze the trigeminal nerves. All patients presented alopecia; two did not present rhombencephalosynapsis (RES); trigeminal anesthesia was present in 5 of the 11 patients (45.4%); brachycephaly/brachyturricephaly and mid-face retrusion were found in 84.6 and 92.3% of the patients, respectively. One patient had intellectual disability. HRT2 sequences showed trigeminal nerve hypoplasia in four of the six patients; all four had clinical signs of trigeminal anesthesia. No common candidate gene was found to explain GLHS phenotype. RES does not seem to be an obligatory finding in respect of GLHS diagnosis. We propose that a diagnosis of GLHS should be considered in patients with at least two of the following criteria: focal non-scarring alopecia, rhombencephalosynapsis, craniofacial anomalies (brachyturrycephaly, brachycephaly or mid-face retrusion), trigeminal anesthesia or anatomic abnormalities of the trigeminal nerve. Studies focusing on germline whole genome sequencing or DNA and/or RNA sequencing of the alopecia tissue may be the next step for the better understanding of GLHS etiology.

Diagnosis of Rare Diseases: a scoping review of clinical decision support systems

BACKGROUND

Rare Diseases (RDs), which are defined as diseases affecting no more than 5 out of 10,000 people, are often severe, chronic and life-threatening. A main problem is the delay in diagnosing RDs. Clinical decision support systems (CDSSs) for RDs are software systems to support clinicians in the diagnosis of patients with RDs. Due to their clinical importance, we conducted a scoping review to determine which CDSSs are available to support the diagnosis of RDs patients, whether the CDSSs are available to be used by clinicians and which functionalities and data are used to provide decision support.

METHODS

We searched PubMed for CDSSs in RDs published between December 16, 2008 and December 16, 2018. Only English articles, original peer reviewed journals and conference papers describing a clinical prototype or a routine use of CDSSs were included. For data charting, we used the data items "Objective and background of the publication/project", "System or project name", "Functionality", "Type of clinical data", "Rare Diseases covered", "Development status", "System availability", "Data entry and integration", "Last software update" and "Clinical usage".

RESULTS

The search identified 636 articles. After title and abstracting screening, as well as assessing the eligibility criteria for full-text screening, 22 articles describing 19 different CDSSs were identified. Three types of CDSSs were classified: "Analysis or comparison of genetic and phenotypic data," "machine learning" and "information retrieval". Twelve of nineteen CDSSs use phenotypic and genetic data, followed by clinical data, literature databases and patient questionnaires. Fourteen of nineteen CDSSs are fully developed systems and therefore publicly available. Data can be entered or uploaded manually in six CDSSs, whereas for four CDSSs no information for data integration was available. Only seven CDSSs allow further ways of data integration. thirteen CDSS do not provide information about clinical usage.

CONCLUSIONS

Different CDSS for various purposes are available, yet clinicians have to determine which is best for their patient. To allow a more precise usage, future research has to focus on CDSSs RDs data integration, clinical usage and updating clinical knowledge. It remains interesting which of the CDSSs will be used and maintained in the future.

Synonymous Mutation in DKC1 Causes Telomerase RNA Insufficiency Manifesting as Familial Pulmonary Fibrosis

BACKGROUND

Idiopathic pulmonary fibrosis (IPF) is the most common of short telomere phenotypes. Familial clustering of IPF is common, but the genetic basis remains unknown in more than one-half of cases. We identified a 65-year-old man with familial IPF, short telomere length, and low telomerase RNA levels. He was diagnosed with a short telomere syndrome after developing hematologic complications post-lung transplantation, but no mutations were identified in a clinical testing pipeline.

RESEARCH QUESTION

What is the molecular basis underlying the familial IPF and low telomerase RNA levels in this patient?

STUDY DESIGN AND METHODS

We analyzed whole-genome sequence data and performed functional molecular studies on cells derived from the patient and his family.

RESULTS

We identified a previously unreported synonymous variant c.942G>A p.K314K in DKC1, the gene encoding the dyskerin ribonucleoprotein, which is required for telomerase RNA biogenesis. The mutation created a competing de novo exonic splicing enhancer, and the misspliced product was degraded by nonsense-mediated decay causing an overall dyskerin deficiency in mutation carriers. In silico tools identified other rare silent DKC1 variants that warrant functional evaluation if found in patients with short telomere-mediated disease.

INTERPRETATION

Our data point to silent mutation in telomere maintenance genes as a mechanism of familial pulmonary fibrosis. In contrast to DKC1 missense mutations, which primarily manifest in children as dyskeratosis congenita, hypomorphic mutations affecting dyskerin levels likely have a predilection to presenting in adults as pulmonary fibrosis.

An Improved Phenotype-Driven Tool for Rare Mendelian Variant Prioritization: Benchmarking Exomiser on Real Patient Whole-Exome Data

Next-generation sequencing has revolutionized rare disease diagnostics, but many patients remain without a molecular diagnosis, particularly because many candidate variants usually survive despite strict filtering. Exomiser was launched in 2014 as a Java tool that performs an integrative analysis of patients' sequencing data and their phenotypes encoded with Human Phenotype Ontology (HPO) terms. It prioritizes variants by leveraging information on variant frequency, predicted pathogenicity, and gene-phenotype associations derived from human diseases, model organisms, and protein-protein interactions. Early published releases of Exomiser were able to prioritize disease-causative variants as top candidates in up to 97% of simulated whole-exomes. The size of the tested real patient datasets published so far are very limited. Here, we present the latest Exomiser version 12.0.1 with many new features. We assessed the performance using a set of 134 whole-exomes from patients with a range of rare retinal diseases and known molecular diagnosis. Using default settings, Exomiser ranked the correct diagnosed variants as the top candidate in 74% of the dataset and top 5 in 94%; not using the patients' HPO profiles (i.e., variant-only analysis) decreased the performance to 3% and 27%, respectively. In conclusion, Exomiser is an effective support tool for rare Mendelian phenotype-driven variant prioritization.

The utility of exome sequencing for fetal pleural effusions

OBJECTIVE

We sought to evaluate the performance of exome sequencing (ES) in determining an underlying genetic etiology for cases of fetal pleural effusions.

STUDY DESIGN

We examined a prospective cohort series of fetal pleural effusions visualized sonographically between 1 April 2016 and 31 August 2017. Fetal pleural effusions attributed to twin sharing, anemia, or structural anomalies were excluded, as were all cases with a genetic diagnosis established by karyotype or chromosomal microarray analysis. The remaining cases with pleural effusions of unclear etiology were offered ES. ES was performed by clinical sequencing and/or sequencing under the Baylor-Hopkins Center for Mendelian Genomics' (BHCMG) research platform. All cases were evaluated for novel genes or phenotypic expansion of disease-causing genes.

RESULTS

ES was performed on six probands affected by pleural effusions. A pathogenic variant was identified in one case (16.7%). Four additional cases had variants of uncertain significance (VUS) in candidate genes of pathological interest. Neither clinical nor candidate genes were evident in the final case.

CONCLUSION

ES should be considered in the evaluation of prenatally detected idiopathic pleural effusions when other diagnostic workup for a genetic etiology has failed.

ZCCHC8, the nuclear exosome targeting component, is mutated in familial pulmonary fibrosis and is required for telomerase RNA maturation

In this study, Gable et al. follow a family with early onset pulmonary fibrosis and report the discovery of a new genetic cause of pulmonary fibrosis. They use multidimensional analysis methods, involving molecular studies, mouse model, and transcriptome-wide studies to show that heterozygous loss-of-function of the exosomal targeting protein ZCCHC8 to identify a novel cause of telomerase insufficiency in human disease.

Short telomere syndromes manifest as familial idiopathic pulmonary fibrosis; they are the most common premature aging disorders. We used genome-wide linkage to identify heterozygous loss of function of ZCCHC8, a zinc-knuckle containing protein, as a cause of autosomal dominant pulmonary fibrosis. ZCCHC8 associated with TR and was required for telomerase function. In ZCCHC8 knockout cells and in mutation carriers, genomically extended telomerase RNA (TR) accumulated at the expense of mature TR, consistent with a role for ZCCHC8 in mediating TR 3′ end targeting to the nuclear RNA exosome. We generated Zcchc8-null mice and found that heterozygotes, similar to human mutation carriers, had TR insufficiency but an otherwise preserved transcriptome. In contrast, Zcchc8^−/− mice developed progressive and fatal neurodevelopmental pathology with features of a ciliopathy. The Zcchc8^−/− brain transcriptome was highly dysregulated, showing accumulation and 3′ end misprocessing of other low-abundance RNAs, including those encoding cilia components as well as the intronless replication-dependent histones. Our data identify a novel cause of human short telomere syndromes-familial pulmonary fibrosis and uncover nuclear exosome targeting as an essential 3′ end maturation mechanism that vertebrate TR shares with replication-dependent histones.

Enabling Global Clinical Collaborations on Identifiable Patient Data: The Minerva Initiative

The clinical utility of computational phenotyping for both genetic and rare diseases is increasingly appreciated; however, its true potential is yet to be fully realized. Alongside the growing clinical and research availability of sequencing technologies, precise deep and scalable phenotyping is required to serve unmet need in genetic and rare diseases. To improve the lives of individuals affected with rare diseases through deep phenotyping, global big data interrogation is necessary to aid our understanding of disease biology, assist diagnosis, and develop targeted treatment strategies. This includes the application of cutting-edge machine learning methods to image data. As with most digital tools employed in health care, there are ethical and data governance challenges associated with using identifiable personal image data. There are also risks with failing to deliver on the patient benefits of these new technologies, the biggest of which is posed by data siloing. The Minerva Initiative has been designed to enable the public good of deep phenotyping while mitigating these ethical risks. Its open structure, enabling collaboration and data sharing between individuals, clinicians, researchers and private enterprise, is key for delivering precision public health.

Insights into genetics, human biology and disease gleaned from family based genomic studies

Identifying genes and variants contributing to rare disease phenotypes and Mendelian conditions informs biology and medicine, yet potential phenotypic consequences for variation of >75% of the ~20,000 annotated genes in the human genome are lacking. Technical advances to assess rare variation genome-wide, particularly exome sequencing (ES), enabled establishment in the United States of the National Institutes of Health (NIH)-supported Centers for Mendelian Genomics (CMGs) and have facilitated collaborative studies resulting in novel "disease gene" discoveries. Pedigree-based genomic studies and rare variant analyses in families with suspected Mendelian conditions have led to the elucidation of hundreds of novel disease genes and highlighted the impact of de novo mutational events, somatic variation underlying nononcologic traits, incompletely penetrant alleles, phenotypes with high locus heterogeneity, and multilocus pathogenic variation. Herein, we highlight CMG collaborative discoveries that have contributed to understanding both rare and common diseases and discuss opportunities for future discovery in single-locus Mendelian disorder genomics. Phenotypic annotation of all human genes; development of bioinformatic tools and analytic methods; exploration of non-Mendelian modes of inheritance including reduced penetrance, multilocus variation, and oligogenic inheritance; construction of allelic series at a locus; enhanced data sharing worldwide; and integration with clinical genomics are explored. Realizing the full contribution of rare disease research to functional annotation of the human genome, and further illuminating human biology and health, will lay the foundation for the Precision Medicine Initiative.

Identifying Genes Whose Mutant Transcripts Cause Dominant Disease Traits by Potential Gain-of-Function Alleles

Premature termination codon (PTC)-bearing transcripts are often degraded by nonsense-mediated decay (NMD) resulting in loss-of-function (LoF) alleles. However, not all PTCs result in LoF mutations, i.e., some such transcripts escape NMD and are translated to truncated peptide products that result in disease due to gain-of-function (GoF) effects. Since the location of the PTC is a major factor determining transcript fate, we hypothesized that depletion of protein-truncating variants (PTVs) within the gene region predicted to escape NMD in control databases could provide a rank for genic susceptibility for disease through GoF versus LoF. We developed an NMD escape intolerance score to rank genes based on the depletion of PTVs that would render them able to escape NMD using the Atherosclerosis Risk in Communities Study (ARIC) and the Exome Aggregation Consortium (ExAC) control databases, which was further used to screen the Baylor-Center for Mendelian Genomics disease database. This analysis revealed 1,996 genes significantly depleted for PTVs that are predicted to escape from NMD, i.e., PTVesc; further studies provided evidence that revealed a subset as candidate genes underlying Mendelian phenotypes. Importantly, these genes have characteristically low pLI scores, which can cause them to be overlooked as candidates for dominant diseases. Collectively, we demonstrate that this NMD escape intolerance score is an effective and efficient tool for gene discovery in Mendelian diseases due to production of truncated or altered proteins. More importantly, we provide a complementary analytical tool to aid identification of genes associated with dominant traits through a mechanism distinct from LoF.

Peripheral Cone Dystrophy: Expanded Clinical Spectrum, Multimodal and Ultrawide-Field Imaging, and Genomic Analysis

PURPOSE

To present new clinical features, multimodal and ultrawide-field imaging characteristics of peripheral cone dystrophy (PCD), and results of laboratory and genetic investigation to decipher the etiology.

METHODS

Retrospective observational case-series.

RESULTS

Three patients with PCD presented with bilateral paracentral scotomas and a mean visual acuity of 20/25. All exhibited confluent macular hyperautofluorescence with a central bull's eye lesion. Spectral-domain optical coherence tomography revealed loss of outer retinal elements, particularly the inner segment ellipsoid band and external limiting membrane, within the area of macular hyperautofluorescence. This area corresponded with a lightened fundus appearance and variable retinal pigment epithelium (RPE) abnormalities. Full field and multifocal electroretinography distinguished PCD from other photoreceptor dystrophies. Ultrawide-field imaging revealed irregular peripheral retinal lesions in a distribution greater nasally than temporally and not contiguous with the macular lesion. Functional and anatomic testing remained stable over a mean follow-up of 3 years. Laboratory investigation for causes of uveitis was negative. Whole exome sequencing identified rare variants in genes associated with macular or cone dystrophy or degeneration.

CONCLUSIONS

In contrast to the original description, the funduscopic and fluorescein angiographic appearance of PCD is abnormal, although the defects are subtle. Peripheral lesions may be observed in some patients. Bilateral, symmetric, macular hyperautofluorescence associated with outer retinal atrophy that spares the fovea is a characteristic of PCD. Pathogenic variants in the same gene were not shared across the cohort, suggesting genetic heterogeneity. Further evaluation is warranted.

SPG11 mutations cause widespread white matter and basal ganglia abnormalities, but restricted cortical damage

SPG11 mutations are the major cause of autosomal recessive Hereditary Spastic Paraplegia. The disease has a wide phenotypic variability indicating many regions of the nervous system besides the corticospinal tract are affected. Despite this, anatomical and phenotypic characterization is restricted. In the present study, we investigate the anatomical abnormalities related to SPG11 mutations and how they relate to clinical and cognitive measures. Moreover, we aim to depict how the disease course influences the regions affected, unraveling different susceptibility of specific neuronal populations. We performed clinical and paraclinical studies encompassing neuropsychological, neuroimaging, and neurophysiological tools in a cohort of twenty-five patients and age matched controls. We assessed cortical thickness (FreeSurfer software), deep grey matter volumes (T1-MultiAtlas tool), white matter microstructural damage (DTI-MultiAtlas) and spinal cord morphometry (Spineseg software) on a 3 T MRI scan. Mean age and disease duration were 29 and 13.2 years respectively. Sixty-four percent of the patients were wheelchair bound while 84% were demented. We were able to unfold a diffuse pattern of white matter integrity loss as well as basal ganglia and spinal cord atrophy. Such findings contrasted with a restricted pattern of cortical thinning (motor, limbic and parietal cortices). Electromyography revealed motor neuronopathy affecting 96% of the probands. Correlations with disease duration pointed towards a progressive degeneration of multiple grey matter structures and spinal cord, but not of the white matter. SPG11-related hereditary spastic paraplegia is characterized by selective neuronal vulnerability, in which a precocious and widespread white matter involvement is later followed by a restricted but clearly progressive grey matter degeneration.

A new method to measure the semantic similarity from query phenotypic abnormalities to diseases based on the human phenotype ontology

Background

Although rapid developed sequencing technologies make it possible for genotype data to be used in clinical diagnosis, it is still challenging for clinicians to understand the results of sequencing and make correct judgement based on them. Before this, diagnosis based on clinical features held a leading position. With the establishment of the Human Phenotype Ontology (HPO) and the enrichment of phenotype-disease annotations, there throws much more attention to the improvement of phenotype-based diagnosis.

Results

In this study, we presented a novel method called RelativeBestPair to measure similarity from the query terms to hereditary diseases based on HPO and then rank the candidate diseases. To evaluate the performance, we simulated a set of patients based on 44 complex diseases. Besides, by adding noise or imprecision or both, cases closer to real clinical conditions were generated. Thus, four simulated datasets were used to make comparison among RelativeBestPair and seven existing semantic similarity measures. RelativeBestPair ranked the underlying disease as top 1 on 93.73% of the simulated dataset without noise and imprecision, 93.64% of the simulated dataset with noise and without imprecision, 39.82% of the simulated dataset without noise and with imprecision, and 33.64% of the simulated dataset with both noise and imprecision.

Conclusion

Compared with the seven existing semantic similarity measures, RelativeBestPair showed similar performance in two datasets without imprecision. While RelativeBestPair appeared to be equal to Resnik and better than other six methods in the simulated dataset without noise and with imprecision, it significantly outperformed all other seven methods in the simulated dataset with both noise and imprecision. It can be indicated that RelativeBestPair might be of great help in clinical setting.

Patients with a Kabuki syndrome phenotype demonstrate DNA methylation abnormalities

Kabuki syndrome is a monogenic disorder caused by loss of function variants in either of two genes encoding histone-modifying enzymes. We performed targeted sequencing in a cohort of 27 probands with a clinical diagnosis of Kabuki syndrome. Of these, 12 had causative variants in the two known Kabuki syndrome genes. In 2, we identified presumptive loss of function de novo variants in KMT2A (missense and splice site variants), a gene that encodes another histone modifying enzyme previously exclusively associated with Wiedermann-Steiner syndrome. Although Kabuki syndrome is a disorder of histone modification, we also find alterations in DNA methylation among individuals with a Kabuki syndrome diagnosis relative to matched normal controls, regardless of whether they carry a variant in KMT2A or KMT2D or not. Furthermore, we observed characteristic global abnormalities of DNA methylation that distinguished patients with a loss of function variant in KMT2D or missense or splice site variants in either KMT2D or KMT2A from normal controls. Our results provide new insights into the relationship of genotype to epigenotype and phenotype and indicate cross-talk between histone and DNA methylation machineries exposed by inborn errors of the epigenetic apparatus.

Settling the score: variant prioritization and Mendelian disease

When investigating Mendelian disease using exome or genome sequencing, distinguishing disease-causing genetic variants from the multitude of candidate variants is a complex, multidimensional task. Many prioritization tools and online interpretation resources exist, and professional organizations have offered clinical guidelines for review and return of prioritization results. In this Review, we describe the strengths and weaknesses of widely used computational approaches, explain their roles in the diagnostic and discovery process and discuss how they can inform (and misinform) expert reviewers. We place variant prioritization in the wider context of gene prioritization, burden testing and genotype-phenotype association, and we discuss opportunities and challenges introduced by whole-genome sequencing.

Model Organisms Facilitate Rare Disease Diagnosis and Therapeutic Research

Efforts to identify the genetic underpinnings of rare undiagnosed diseases increasingly involve the use of next-generation sequencing and comparative genomic hybridization methods. These efforts are limited by a lack of knowledge regarding gene function, and an inability to predict the impact of genetic variation on the encoded protein function. Diagnostic challenges posed by undiagnosed diseases have solutions in model organism research, which provides a wealth of detailed biological information. Model organism geneticists are by necessity experts in particular genes, gene families, specific organs, and biological functions. Here, we review the current state of research into undiagnosed diseases, highlighting large efforts in North America and internationally, including the Undiagnosed Diseases Network (UDN) (Supplemental Material, File S1) and UDN International (UDNI), the Centers for Mendelian Genomics (CMG), and the Canadian Rare Diseases Models and Mechanisms Network (RDMM). We discuss how merging human genetics with model organism research guides experimental studies to solve these medical mysteries, gain new insights into disease pathogenesis, and uncover new therapeutic strategies.

Identification of STAC3 variants in non-Native American families with overlapping features of Carey-Fineman-Ziter syndrome and Moebius syndrome

Horstick et al. (2013) previously reported a homozygous p.Trp284Ser variant in STAC3 as the cause of Native American myopathy (NAM) in 5 Lumbee Native American families with congenital hypotonia and weakness, cleft palate, short stature, ptosis, kyphoscoliosis, talipes deformities, and susceptibility to malignant hyperthermia (MH). Here we present two non-Native American families, who were found to have STAC3 pathogenic variants. The first proband and her affected older sister are from a consanguineous Qatari family with a suspected clinical diagnosis of Carey-Fineman-Ziter syndrome (CFZS) based on features of hypotonia, myopathic facies with generalized weakness, ptosis, normal extraocular movements, cleft palate, growth delay, and kyphoscoliosis. We identified the homozygous c.851G>C;p.Trp284Ser variant in STAC3 in both sisters. The second proband and his affected sister are from a non-consanguineous, Puerto Rican family who was evaluated for a possible diagnosis of Moebius syndrome (MBS). His features included facial and generalized weakness, minimal limitation of horizontal gaze, cleft palate, and hypotonia, and he has a history of MH. The siblings were identified to be compound heterozygous for STAC3 variants c.851G>C;p.Trp284Ser and c.763_766delCTCT;p.Leu255IlefsX58. Given the phenotypic overlap of individuals with CFZS, MBS, and NAM, we screened STAC3 in 12 individuals diagnosed with CFZS and in 50 individuals diagnosed with MBS or a congenital facial weakness disorder. We did not identify any rare coding variants in STAC3. NAM should be considered in patients presenting with facial and generalized weakness, normal or mildly abnormal extraocular movement, hypotonia, cleft palate, and scoliosis, particularly if there is a history of MH.

International Cooperation to Enable the Diagnosis of All Rare Genetic Diseases

Provision of a molecularly confirmed diagnosis in a timely manner for children and adults with rare genetic diseases shortens their "diagnostic odyssey," improves disease management, and fosters genetic counseling with respect to recurrence risks while assuring reproductive choices. In a general clinical genetics setting, the current diagnostic rate is approximately 50%, but for those who do not receive a molecular diagnosis after the initial genetics evaluation, that rate is much lower. Diagnostic success for these more challenging affected individuals depends to a large extent on progress in the discovery of genes associated with, and mechanisms underlying, rare diseases. Thus, continued research is required for moving toward a more complete catalog of disease-related genes and variants. The International Rare Diseases Research Consortium (IRDiRC) was established in 2011 to bring together researchers and organizations invested in rare disease research to develop a means of achieving molecular diagnosis for all rare diseases. Here, we review the current and future bottlenecks to gene discovery and suggest strategies for enabling progress in this regard. Each successful discovery will define potential diagnostic, preventive, and therapeutic opportunities for the corresponding rare disease, enabling precision medicine for this patient population.

Lessons learned from additional research analyses of unsolved clinical exome cases

BACKGROUND

Given the rarity of most single-gene Mendelian disorders, concerted efforts of data exchange between clinical and scientific communities are critical to optimize molecular diagnosis and novel disease gene discovery.

METHODS

We designed and implemented protocols for the study of cases for which a plausible molecular diagnosis was not achieved in a clinical genomics diagnostic laboratory (i.e. unsolved clinical exomes). Such cases were recruited to a research laboratory for further analyses, in order to potentially: (1) accelerate novel disease gene discovery; (2) increase the molecular diagnostic yield of whole exome sequencing (WES); and (3) gain insight into the genetic mechanisms of disease. Pilot project data included 74 families, consisting mostly of parent-offspring trios. Analyses performed on a research basis employed both WES from additional family members and complementary bioinformatics approaches and protocols.

RESULTS

Analysis of all possible modes of Mendelian inheritance, focusing on both single nucleotide variants (SNV) and copy number variant (CNV) alleles, yielded a likely contributory variant in 36% (27/74) of cases. If one includes candidate genes with variants identified within a single family, a potential contributory variant was identified in a total of ~51% (38/74) of cases enrolled in this pilot study. The molecular diagnosis was achieved in 30/63 trios (47.6%). Besides this, the analysis workflow yielded evidence for pathogenic variants in disease-associated genes in 4/6 singleton cases (66.6%), 1/1 multiplex family involving three affected siblings, and 3/4 (75%) quartet families. Both the analytical pipeline and the collaborative efforts between the diagnostic and research laboratories provided insights that allowed recent disease gene discoveries (PURA, TANGO2, EMC1, GNB5, ATAD3A, and MIPEP) and increased the number of novel genes, defined in this study as genes identified in more than one family (DHX30 and EBF3).

CONCLUSION

An efficient genomics pipeline in which clinical sequencing in a diagnostic laboratory is followed by the detailed reanalysis of unsolved cases in a research environment, supplemented with WES data from additional family members, and subject to adjuvant bioinformatics analyses including relaxed variant filtering parameters in informatics pipelines, can enhance the molecular diagnostic yield and provide mechanistic insights into Mendelian disorders. Implementing these approaches requires collaborative clinical molecular diagnostic and research efforts.

Choices for return of primary and secondary genomic research results of 790 members of families with Mendelian disease

Although consensus is building that primary (PR) and secondary findings (SF) from genomic research should be offered to participants under some circumstances, data describing (1) actual choices of study participants and (2) factors associated with these choices are limited, hampering study planning. We conducted a cross-sectional analysis of choices made for return of PR and SF during informed consent by members of the first 247 families (790 individuals) enrolled in the Baylor-Hopkins Center for Mendelian Genomics, a genome sequencing study. Most (619; 78.3%) chose to receive SF and PR, 66 (8.4%) chose PR only, 65 (8.2%) wanted no results, and 40 (5.1%) chose SF only. Choosing SF was associated with an established clinical diagnosis in the proband (87.8 vs 79%, P=0.009) and European ancestry (EA) (87.7 vs 73%, P<0.008). Participants of non-European ancestry (NEA) were as likely as those of EA to choose SF when consented by a genetic counselor (GC) (82% NEA vs 88.3% EA, P=0.09) but significantly less likely when consented by a physician (67.4% NEA vs 85.4% EA, P=0.001). Controlling for proband diagnosis, individuals of NEA were 2.13-fold (95% CI: 1.11-4.08) more likely to choose SF when consented by a GC rather than a physician. Participants of NEA were 3-fold more likely than those of EA to decline all study results (14.7% NEA vs 5.4% EA, P<0.008). In this ethnically diverse population, whereas most participants desired PR and SF, more than 20% declined some or all results, highlighting the importance of research participant choice.

Bi-allelic IARS mutations in a child with intra-uterine growth retardation, neonatal cholestasis, and mild developmental delay

Recently, bi-allelic mutations in cytosolic isoleucyl-tRNA synthetase (IARS) have been described in three individuals with growth delay, hepatic dysfunction, and neurodevelopmental disabilities. Here we report an additional subject with this condition identified by whole-exome sequencing. Our findings support the association between this disorder and neonatal cholestasis with distinct liver pathology. Furthermore, we provide functional data on two novel missense substitutions and expand the phenotype to include mild developmental delay, skin hyper-elasticity, and hypervitaminosis D.

SLC13A5 is the second gene associated with Kohlschütter-Tönz syndrome

BACKGROUND

Kohlschütter-Tönz syndrome (KTZS) is a rare autosomal-recessive disease characterised by epileptic encephalopathy, intellectual disability and amelogenesis imperfecta (AI). It is frequently caused by biallelic mutations in ROGDI. Here, we report on individuals with ROGDI-negative KTZS carrying biallelic SLC13A5 mutations.

METHODS

In the present cohort study, nine individuals from four families with the clinical diagnosis of KTZS and absence of ROGDI mutations as well as one patient with unexplained epileptic encephalopathy were investigated by clinical and dental evaluation, parametric linkage analysis (one family), and exome and/or Sanger sequencing. Dental histological investigations were performed on teeth from individuals with SLC13A5-associated and ROGDI-associated KTZS.

RESULTS

Biallelic mutations in SLC13A5 were identified in 10 affected individuals. Epileptic encephalopathy usually presents in the neonatal and (less frequently) early infantile period. Yellowish to orange discolouration of both deciduous and permanent teeth, as well as wide interdental spaces and abnormal crown forms are major clinical signs of individuals with biallelic SLC13A5 mutations. Histological dental investigations confirmed the clinical diagnosis of hypoplastic AI. In comparison, the histological evaluation of a molar assessed from an individual with ROGDI-associated KTZS revealed hypocalcified AI.

CONCLUSIONS

We conclude that SLC13A5 is the second major gene associated with the clinical diagnosis of KTZS, characterised by neonatal epileptic encephalopathy and hypoplastic AI. Careful clinical and dental delineation provides clues whether ROGDI or SLC13A5 is the causative gene. Hypersensitivity of teeth as well as high caries risk requires individual dental prophylaxis and attentive dental management.

Exome sequencing in mostly consanguineous Arab families with neurologic disease provides a high potential molecular diagnosis rate

BACKGROUND

Neurodevelopment is orchestrated by a wide range of genes, and the genetic causes of neurodevelopmental disorders are thus heterogeneous. We applied whole exome sequencing (WES) for molecular diagnosis and in silico analysis to identify novel disease gene candidates in a cohort from Saudi Arabia with primarily Mendelian neurologic diseases.

METHODS

We performed WES in 31 mostly consanguineous Arab families and analyzed both single nucleotide and copy number variants (CNVs) from WES data. Interaction/expression network and pathway analyses, as well as paralog studies were utilized to investigate potential pathogenicity and disease association of novel candidate genes. Additional cases for candidate genes were identified through the clinical WES database at Baylor Miraca Genetics Laboratories and GeneMatcher.

RESULTS

We found known pathogenic or novel variants in known disease genes with phenotypic expansion in 6 families, disease-associated CNVs in 2 families, and 12 novel disease gene candidates in 11 families, including KIF5B, GRM7, FOXP4, MLLT1, and KDM2B. Overall, a potential molecular diagnosis was provided by variants in known disease genes in 17 families (54.8 %) and by novel candidate disease genes in an additional 11 families, making the potential molecular diagnostic rate ~90 %.

CONCLUSIONS

Molecular diagnostic rate from WES is improved by exome-predicted CNVs. Novel candidate disease gene discovery is facilitated by paralog studies and through the use of informatics tools and available databases to identify additional evidence for pathogenicity.

TRIAL REGISTRATION

Not applicable.

Novel bioinformatic developments for exome sequencing

With the widespread adoption of next generation sequencing technologies by the genetics community and the rapid decrease in costs per base, exome sequencing has become a standard within the repertoire of genetic experiments for both research and diagnostics. Although bioinformatics now offers standard solutions for the analysis of exome sequencing data, many challenges still remain; especially the increasing scale at which exome data are now being generated has given rise to novel challenges in how to efficiently store, analyze and interpret exome data of this magnitude. In this review we discuss some of the recent developments in bioinformatics for exome sequencing and the directions that this is taking us to. With these developments, exome sequencing is paving the way for the next big challenge, the application of whole genome sequencing.

Capturing phenotypes for precision medicine

Deep phenotyping followed by integrated computational analysis of genotype and phenotype is becoming ever more important for many areas of genomic diagnostics and translational research. The overwhelming majority of clinical descriptions in the medical literature are available only as natural language text, meaning that searching, analysis, and integration of medically relevant information in databases such as PubMed is challenging. The new journal Cold Spring Harbor Molecular Case Studies will require authors to select Human Phenotype Ontology terms for research papers that will be displayed alongside the manuscript, thereby providing a foundation for ontology-based indexing and searching of articles that contain descriptions of phenotypic abnormalities-an important step toward improving the ability of researchers and clinicians to get biomedical information that is critical for clinical care or translational research.

Facilitating a culture of responsible and effective sharing of cancer genome data

Rapid and affordable tumor molecular profiling has led to an explosion of clinical and genomic data poised to enhance the diagnosis, prognostication and treatment of cancer. A critical point has now been reached at which the analysis and storage of annotated clinical and genomic information in unconnected silos will stall the advancement of precision cancer care. Information systems must be harmonized to overcome the multiple technical and logistical barriers to data sharing. Against this backdrop, the Global Alliance for Genomic Health (GA4GH) was established in 2013 to create a common framework that enables responsible, voluntary and secure sharing of clinical and genomic data. This Perspective from the GA4GH Clinical Working Group Cancer Task Team highlights the data-aggregation challenges faced by the field, suggests potential collaborative solutions and describes how GA4GH can catalyze a harmonized data-sharing culture.

Novel bioinformatic developments for exome sequencing

With the widespread adoption of next generation sequencing technologies by the genetics community and the rapid decrease in costs per base, exome sequencing has become a standard within the repertoire of genetic experiments for both research and diagnostics. Although bioinformatics now offers standard solutions for the analysis of exome sequencing data, many challenges still remain; especially the increasing scale at which exome data are now being generated has given rise to novel challenges in how to efficiently store, analyze and interpret exome data of this magnitude. In this review we discuss some of the recent developments in bioinformatics for exome sequencing and the directions that this is taking us to. With these developments, exome sequencing is paving the way for the next big challenge, the application of whole genome sequencing.

A visual and curatorial approach to clinical variant prioritization and disease gene discovery in genome-wide diagnostics

Background

Genome-wide data are increasingly important in the clinical evaluation of human disease. However, the large number of variants observed in individual patients challenges the efficiency and accuracy of diagnostic review. Recent work has shown that systematic integration of clinical phenotype data with genotype information can improve diagnostic workflows and prioritization of filtered rare variants. We have developed visually interactive, analytically transparent analysis software that leverages existing disease catalogs, such as the Online Mendelian Inheritance in Man database (OMIM) and the Human Phenotype Ontology (HPO), to integrate patient phenotype and variant data into ranked diagnostic alternatives.

Methods

Our tool, “OMIM Explorer” (http://www.omimexplorer.com), extends the biomedical application of semantic similarity methods beyond those reported in previous studies. The tool also provides a simple interface for translating free-text clinical notes into HPO terms, enabling clinical providers and geneticists to contribute phenotypes to the diagnostic process. The visual approach uses semantic similarity with multidimensional scaling to collapse high-dimensional phenotype and genotype data from an individual into a graphical format that contextualizes the patient within a low-dimensional disease map. The map proposes a differential diagnosis and algorithmically suggests potential alternatives for phenotype queries—in essence, generating a computationally assisted differential diagnosis informed by the individual’s personal genome. Visual interactivity allows the user to filter and update variant rankings by interacting with intermediate results. The tool also implements an adaptive approach for disease gene discovery based on patient phenotypes.

Results

We retrospectively analyzed pilot cohort data from the Baylor Miraca Genetics Laboratory, demonstrating performance of the tool and workflow in the re-analysis of clinical exomes. Our tool assigned to clinically reported variants a median rank of 2, placing causal variants in the top 1 % of filtered candidates across the 47 cohort cases with reported molecular diagnoses of exome variants in OMIM Morbidmap genes. Our tool outperformed Phen-Gen, eXtasy, PhenIX, PHIVE, and hiPHIVE in the prioritization of these clinically reported variants.

Conclusions

Our integrative paradigm can improve efficiency and, potentially, the quality of genomic medicine by more effectively utilizing available phenotype information, catalog data, and genomic knowledge.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-016-0261-8) contains supplementary material, which is available to authorized users.

New tools for Mendelian disease gene identification: PhenoDB variant analysis module; and GeneMatcher, a web-based tool for linking investigators with an interest in the same gene

Identifying the causative variant from among the thousands identified by whole-exome sequencing or whole-genome sequencing is a formidable challenge. To make this process as efficient and flexible as possible, we have developed a Variant Analysis Module coupled to our previously described Web-based phenotype intake tool, PhenoDB (http://researchphenodb.net and http://phenodb.org). When a small number of candidate-causative variants have been identified in a study of a particular patient or family, a second, more difficult challenge becomes proof of causality for any given variant. One approach to this problem is to find other cases with a similar phenotype and mutations in the same candidate gene. Alternatively, it may be possible to develop biological evidence for causality, an approach that is assisted by making connections to basic scientists studying the gene of interest, often in the setting of a model organism. Both of these strategies benefit from an open access, online site where individual clinicians and investigators could post genes of interest. To this end, we developed GeneMatcher (http://genematcher.org), a freely accessible Website that enables connections between clinicians and researchers across the world who share an interest in the same gene(s).

Assessment of incidental findings in 232 whole-exome sequences from the Baylor-Hopkins Center for Mendelian Genomics

PURPOSE

In March 2013 the American College of Medical Genetics and Genomics published a list of 56 genes with the recommendation that pathogenic and likely pathogenic variants detected incidentally by clinical sequencing be reported to patients. As an initial step in determining the practical consequences of this recommendation in the research setting, we searched for variants in these genes in 232 whole-exome sequences from the Baylor-Hopkins Center for Mendelian Genomics.

METHODS

We identified rare, nonsynonymous, and splicing single-nucleotide variants and insertions/deletions and assessed variant classification using the Human Gene Mutation, Emory, and ClinVar databases. We analyzed the burden of mutation in each of the 56 genes and determined which variants should be reported to patients.

RESULTS

Our filtering resulted in 249 distinct variants, with a mean of 1.69 variants per individual. Half of these were novel missense mutations not classified by any of the three reference databases. Of 101 variants listed in the Human Gene Mutation Database, 48 were also in ClinVar and 3 were also in Emory; half of these shared variants were classified discordantly between databases. Some genes consistently had greater variation than others. In total, 0.86% of individuals had a reportable incidental variant.

CONCLUSION

These observations demonstrate some current challenges of assessing phenotypic consequences of incidental variants for counseling patients.

GeneMatcher: a matching tool for connecting investigators with an interest in the same gene

Here, we describe an overview and update on GeneMatcher (http://www.genematcher.org), a freely accessible Web-based tool developed as part of the Baylor-Hopkins Center for Mendelian Genomics. We created GeneMatcher with the goal of identifying additional individuals with rare phenotypes who had variants in the same candidate disease gene. We also wanted to facilitate connections to basic scientists working on orthologous genes in model systems with the goal of connecting their work to human Mendelian phenotypes. Meeting these goals will enhance the identification of novel Mendelian genes. Launched in September, 2013, GeneMatcher now has 2,178 candidate genes from 486 submitters spread across 38 countries entered in the database (June 1, 2015). GeneMatcher is also part of the Matchmaker Exchange (http://matchmakerexchange.org/) with an Application Programing Interface enabling submitters to query other databases of genetic variants and phenotypes without having to create accounts and data entries in multiple systems.

The Genetic Basis of Mendelian Phenotypes: Discoveries, Challenges, and Opportunities

Discovering the genetic basis of a Mendelian phenotype establishes a causal link between genotype and phenotype, making possible carrier and population screening and direct diagnosis. Such discoveries also contribute to our knowledge of gene function, gene regulation, development, and biological mechanisms that can be used for developing new therapeutics. As of February 2015, 2,937 genes underlying 4,163 Mendelian phenotypes have been discovered, but the genes underlying ∼50% (i.e., 3,152) of all known Mendelian phenotypes are still unknown, and many more Mendelian conditions have yet to be recognized. This is a formidable gap in biomedical knowledge. Accordingly, in December 2011, the NIH established the Centers for Mendelian Genomics (CMGs) to provide the collaborative framework and infrastructure necessary for undertaking large-scale whole-exome sequencing and discovery of the genetic variants responsible for Mendelian phenotypes. In partnership with 529 investigators from 261 institutions in 36 countries, the CMGs assessed 18,863 samples from 8,838 families representing 579 known and 470 novel Mendelian phenotypes as of January 2015. This collaborative effort has identified 956 genes, including 375 not previously associated with human health, that underlie a Mendelian phenotype. These results provide insight into study design and analytical strategies, identify novel mechanisms of disease, and reveal the extensive clinical variability of Mendelian phenotypes. Discovering the gene underlying every Mendelian phenotype will require tackling challenges such as worldwide ascertainment and phenotypic characterization of families affected by Mendelian conditions, improvement in sequencing and analytical techniques, and pervasive sharing of phenotypic and genomic data among researchers, clinicians, and families.

ClinGen--the Clinical Genome Resource

On autopsy, a patient is found to have hypertrophic cardiomyopathy. The patient’s family pursues genetic testing that shows a “likely pathogenic” variant for the condition on the basis of a study in an original research publication. Given the dominant inheritance of the condition and the risk of sudden cardiac death, other family members are tested for the genetic variant to determine their risk. Several family members test negative and are told that they are not at risk for hypertrophic cardiomyopathy and sudden cardiac death, and those who test positive are told that they need to be regularly monitored for cardiomyopathy on echocardiography. Five years later, during a routine clinic visit of one of the genotype-positive family members, the cardiologist queries a database for current knowledge on the genetic variant and discovers that the variant is now interpreted as “likely benign” by another laboratory that uses more recently derived population-frequency data. A newly available testing panel for additional genes that are implicated in hypertrophic cardiomyopathy is initiated on an affected family member, and a different variant is found that is determined to be pathogenic. Family members are retested, and one member who previously tested negative is now found to be positive for this new variant. An immediate clinical workup detects evidence of cardiomyopathy, and an intracardiac defibrillator is implanted to reduce the risk of sudden cardiac death.

Truncating mutations in the last exon of NOTCH3 cause lateral meningocele syndrome

Lateral meningocele syndrome (LMS, OMIM%130720), also known as Lehman syndrome, is a very rare skeletal disorder with facial anomalies, hypotonia and meningocele-related neurologic dysfunction. The characteristic lateral meningoceles represent the severe end of the dural ectasia spectrum and are typically most severe in the lower spine. Facial features of LMS include hypertelorism and telecanthus, high arched eyebrows, ptosis, midfacial hypoplasia, micrognathia, high and narrow palate, low-set ears and a hypotonic appearance. Hyperextensibility, hernias and scoliosis reflect a connective tissue abnormality, and aortic dilation, a high-pitched nasal voice, wormian bones and osteolysis may be present. Lateral meningocele syndrome has phenotypic overlap with Hajdu-Cheney syndrome. We performed exome resequencing in five unrelated individuals with LMS and identified heterozygous truncating NOTCH3 mutations. In an additional unrelated individual Sanger sequencing revealed a deleterious variant in the same exon 33. In total, five novel de novo NOTCH3 mutations were identified in six unrelated patients. One had a 26 bp deletion (c.6461_6486del, p.G2154fsTer78), two carried the same single base pair insertion (c.6692_93insC, p.P2231fsTer11), and three individuals had a nonsense point mutation at c.6247A > T (pK2083*), c.6663C > G (p.Y2221*) or c.6732C > A, (p.Y2244*). All mutations cluster into the last coding exon, resulting in premature termination of the protein and truncation of the negative regulatory proline-glutamate-serine-threonine rich PEST domain. Our results suggest that mutant mRNA products escape nonsense mediated decay. The truncated NOTCH3 may cause gain-of-function through decreased clearance of the active intracellular product, resembling NOTCH2 mutations in the clinically related Hajdu-Cheney syndrome and contrasting the NOTCH3 missense mutations causing CADASIL.

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

Online Mendelian Inheritance in Man, OMIM^®, is a comprehensive, authoritative and timely research resource of curated descriptions of human genes and phenotypes and the relationships between them. The new official website for OMIM, OMIM.org (http://omim.org), was launched in January 2011. OMIM is based on the published peer-reviewed biomedical literature and is used by overlapping and diverse communities of clinicians, molecular biologists and genome scientists, as well as by students and teachers of these disciplines. Genes and phenotypes are described in separate entries and are given unique, stable six-digit identifiers (MIM numbers). OMIM entries have a structured free-text format that provides the flexibility necessary to describe the complex and nuanced relationships between genes and genetic phenotypes in an efficient manner. OMIM also has a derivative table of genes and genetic phenotypes, the Morbid Map. OMIM.org has enhanced search capabilities such as genome coordinate searching and thesaurus-enhanced search term options. Phenotypic series have been created to facilitate viewing genetic heterogeneity of phenotypes. Clinical synopsis features are enhanced with UMLS, Human Phenotype Ontology and Elements of Morphology terms and image links. All OMIM data are available for FTP download and through an API. MIMmatch is a novel outreach feature to disseminate updates and encourage collaboration.

PhenUMA: a tool for integrating the biomedical relationships among genes and diseases

Background

Several types of genetic interactions in humans can be directly or indirectly associated with the causal effects of mutations. These interactions are usually based on their co-associations to biological processes, coexistence in cellular locations, coexpression in cell lines, physical interactions and so on. In addition, pathological processes can present similar phenotypes that have mutations either in the same genomic location or in different genomic regions. Therefore, integrative resources for all of these complex interactions can help us prioritize the relationships between genes and diseases that are most deserving to be studied by researchers and physicians.

Results

PhenUMA is a web application that displays biological networks using information from biomedical and biomolecular data repositories. One of its most innovative features is to combine the benefits of semantic similarity methods with the information taken from databases of genetic diseases and biological interactions. More specifically, this tool is useful in studying novel pathological relationships between functionally related genes, merging diseases into clusters that share specific phenotypes or finding diseases related to reported phenotypes.

Conclusions

This framework builds, analyzes and visualizes networks based on both functional and phenotypic relationships. The integration of this information helps in the discovery of alternative pathological roles of genes, biological functions and diseases. PhenUMA represents an advancement toward the use of new technologies for genomics and personalized medicine.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-014-0375-1) contains supplementary material, which is available to authorized users.

A drosophila genetic resource of mutants to study mechanisms underlying human genetic diseases

Invertebrate model systems are powerful tools for studying human disease owing to their genetic tractability and ease of screening. We conducted a mosaic genetic screen of lethal mutations on the Drosophila X chromosome to identify genes required for the development, function, and maintenance of the nervous system. We identified 165 genes, most of whose function has not been studied in vivo. In parallel, we investigated rare variant alleles in 1,929 human exomes from families with unsolved Mendelian disease. Genes that are essential in flies and have multiple human homologs were found to be likely to be associated with human diseases. Merging the human data sets with the fly genes allowed us to identify disease-associated mutations in six families and to provide insights into microcephaly associated with brain dysgenesis. This bidirectional synergism between fly genetics and human genomics facilitates the functional annotation of evolutionarily conserved genes involved in human health.

PhenoVar: a phenotype-driven approach in clinical genomics for the diagnosis of polymalformative syndromes

BACKGROUND

We propose a phenotype-driven analysis of encrypted exome data to facilitate the widespread implementation of exome sequencing as a clinical genetic screening test.Twenty test-patients with varied syndromes were selected from the literature. For each patient, the mutation, phenotypic data, and genetic diagnosis were available. Next, control exome-files, each modified to include one of these twenty mutations, were assigned to the corresponding test-patients. These data were used by a geneticist blinded to the diagnoses to test the efficiency of our software, PhenoVar. The score assigned by PhenoVar to any genetic diagnosis listed in OMIM (Online Mendelian Inheritance in Man) took into consideration both the patient's phenotype and all variations present in the corresponding exome. The physician did not have access to the individual mutations. PhenoVar filtered the search using a cut-off phenotypic match threshold to prevent undesired discovery of incidental findings and ranked the OMIM entries according to diagnostic score.

RESULTS

When assigning the same weight to all variants in the exome, PhenoVar predicted the correct diagnosis in 10/20 patients, while in 15/20 the correct diagnosis was among the 4 highest ranked diagnoses. When assigning a higher weight to variants known, or bioinformatically predicted, to cause disease, PhenoVar's yield increased to 14/20 (18/20 in top 4). No incidental findings were identified using our cut-off phenotypic threshold.

CONCLUSION

The phenotype-driven approach described could render widespread use of ES more practical, ethical and clinically useful. The implications about novel disease identification, advancement of complex diseases and personalized medicine are discussed.

Clinical utility of whole-exome sequencing in rare diseases: Galactosialidosis

Rare genetic disorders can go undiagnosed for years as the entire spectrum of phenotypic variation is not well characterized given the reduced number of patients reported in the literature and the low frequency at which these occur. Moreover, the current paradigm for clinical diagnostics defines disease diagnosis by a specified spectrum of phenotypic findings; when such parameters are either missing, or other findings not usually observed are seen, the phenotype driven approach to diagnosis may result in a specific etiological diagnosis not even being considered within the differential diagnosis. The novel implementation of genomic sequencing approaches to investigate rare genetic disorders is allowing not only the discovery of new genes, but also the phenotypic expansion of known Mendelian genetic disorders. Here we report the detailed clinical assessment of a patient with a rare genetic disorder with undefined molecular diagnosis. We applied whole-exome sequencing to this patient and unaffected parents in order to identify the molecular cause of her disorder. We identified compound heterozygous mutations in the CTSA gene, responsible for causing galactosialidosis; the molecular diagnosis was further confirmed by biochemical studies. This report expands on the clinical spectrum of this rare lysosomal disorder and exemplifies how genomic approaches are further elucidating the characterization and understanding of genetic diseases.

Next-generation sequencing applied to rare diseases genomics

Genomics has revolutionized the study of rare diseases. In this review, we overview the latest technological development, rare disease discoveries, implementation obstacles and bioethical challenges. First, we discuss the technology of genome and exome sequencing, including the different next-generation platforms and exome enrichment technologies. Second, we survey the pioneering centers and discoveries for rare diseases, including few of the research institutions that have contributed to the field, as well as an overview survey of different types of rare diseases that have had new discoveries due to next-generation sequencing. Third, we discuss the obstacles and challenges that allow for clinical implementation, including returning of results, informed consent and privacy. Last, we discuss possible outlook as clinical genomics receives wider adoption, as third-generation sequencing is coming onto the horizon, and some needs in informatics and software to further advance the field.

Integrating massively parallel sequencing into diagnostic workflows and managing the annotation and clinical interpretation challenge

Massively parallel sequencing has become a powerful tool for the clinical management of patients with applications in diagnosis, guidance of treatment, prediction of drug response, and carrier screening. A considerable challenge for the clinical implementation of these technologies is the management of the vast amount of sequence data generated, in particular the annotation and clinical interpretation of genomic variants. Here, we describe annotation steps that can be automated and common strategies employed for variant prioritization. The definition of best practice standards for variant annotation and prioritization is still ongoing; at present, there is limited consensus regarding an optimal clinical sequencing pipeline. We provide considerations to help define these. For the first time, clinical genetics and genomics is not limited by our ability to sequence, but our ability to clinically interpret and use genomic information in health management. We argue that the development of standardized variant annotation and interpretation approaches and software tools implementing these warrants further support. As we gain a better understanding of the significance of genomic variation through research, patients will be able to benefit from the full scope that these technologies offer.

Sclerocornea in a patient with van den Ende-Gupta syndrome homozygous for a SCARF2 microdeletion

Van den Ende-Gupta Syndrome (VDEGS) is an autosomal recessive disorder characterized by blepharophimosis, distinctive nose, hypoplastic maxilla, and skeletal abnormalities. Using homozygosity mapping in four VDEGS patients from three consanguineous families, Anastacio et al. [Anastacio et al. (2010); Am J Hum Genet 87:553-559] identified homozygous mutations in SCARF2, located at 22q11.2. Bedeschi et al. [2010] described a VDEGS patient with sclerocornea and cataracts with compound heterozygosity for the common 22q11.2 microdeletion and a hemizygous SCARF2 mutation. Because sclerocornea had been described in DiGeorge-velo-cardio-facial syndrome but not in VDEGS, they suggested that the ocular abnormalities were caused by the 22q11.2 microdeletion. We report on a 23-year-old male who presented with bilateral sclerocornea and the VDGEGS phenotype who was subsequently found to be homozygous for a 17 bp deletion in exon 4 of SCARF2. The occurrence of bilateral sclerocornea in our patient together with that of Bedeschi et al., suggests that the full VDEGS phenotype may include sclerocornea resulting from homozygosity or compound heterozygosity for loss of function variants in SCARF2.