Lipodystrophy in methylmalonic acidemia associated with elevated FGF21 and abnormal methylmalonylation

A distinct adipose tissue distribution pattern was observed in patients with methylmalonyl-CoA mutase deficiency, an inborn error of branched-chain amino acid (BCAA) metabolism, characterized by centripetal obesity with proximal upper and lower extremity fat deposition and paucity of visceral fat, that resembles familial multiple lipomatosis syndrome. To explore brown and white fat physiology in methylmalonic acidemia (MMA), body composition, adipokines, and inflammatory markers were assessed in 46 patients with MMA and 99 matched controls. Fibroblast growth factor 21 levels were associated with acyl-CoA accretion, aberrant methylmalonylation in adipose tissue, and an attenuated inflammatory cytokine profile. In parallel, brown and white fat were examined in a liver-specific transgenic MMA mouse model (Mmut-/- TgINS-Alb-Mmut). The MMA mice exhibited abnormal nonshivering thermogenesis with whitened brown fat and had an ineffective transcriptional response to cold stress. Treatment of the MMA mice with bezafibrates led to clinical improvement with beiging of subcutaneous fat depots, which resembled the distribution seen in the patients. These studies defined what we believe to be a novel lipodystrophy phenotype in patients with defects in the terminal steps of BCAA oxidation and demonstrated that beiging of subcutaneous adipose tissue in MMA could readily be induced with small molecules.

Toward robust clinical genome interpretation: Developing a consistent terminology to characterize Mendelian disease-gene relationships-allelic requirement, inheritance modes, and disease mechanisms

PURPOSE

The terminology used for gene-disease curation and variant annotation to describe inheritance, allelic requirement, and both sequence and functional consequences of a variant is currently not standardized. There is considerable discrepancy in the literature and across clinical variant reporting in the derivation and application of terms. Here, we standardize the terminology for the characterization of disease-gene relationships to facilitate harmonized global curation and to support variant classification within the ACMG/AMP framework.

METHODS

Terminology for inheritance, allelic requirement, and both structural and functional consequences of a variant used by Gene Curation Coalition members and partner organizations was collated and reviewed. Harmonized terminology with definitions and use examples was created, reviewed, and validated.

RESULTS

We present a standardized terminology to describe gene-disease relationships, and to support variant annotation. We demonstrate application of the terminology for classification of variation in the ACMG SF 2.0 genes recommended for reporting of secondary findings. Consensus terms were agreed and formalized in both Sequence Ontology (SO) and Human Phenotype Ontology (HPO) ontologies. Gene Curation Coalition member groups intend to use or map to these terms in their respective resources.

CONCLUSION

The terminology standardization presented here will improve harmonization, facilitate the pooling of curation datasets across international curation efforts and, in turn, improve consistency in variant classification and genetic test interpretation.

The Human Phenotype Ontology in 2024: phenotypes around the world

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.

The remarkable journey of one female individual with ornithine transcarbamylase deficiency diagnosed post-mortem

Urea cycle disorders (UCDs) comprise a group of inborn errors of metabolism with impaired ammonia clearance and an incidence of ~1:35 000 individuals. First described in the 1970s, the diagnosis and management of these disorders has evolved dramatically. We report on a 59-year-old woman with a UCD who contributed to advances in the understanding and treatment of this group of disorders. This individual was diagnosed with carbamoyl phosphate synthetase 1 deficiency based on a biochemical assay under a research context predating genetic sequencing, treated longitudinally as having this metabolic disorder, and was among the first participants to trial UCD pharmaceutical therapies. She ultimately succumbed to a SARS-CoV-2 infection while maintaining unexpectedly normal ammonium levels. Postmortem genetic testing revealed ornithine transcarbamylase deficiency. This individual's contributions to the field of UCDs is discussed herein.

Towards robust clinical genome interpretation: developing a consistent terminology to characterize disease-gene relationships - allelic requirement, inheritance modes and disease mechanisms

PURPOSE

The terminology used for gene-disease curation and variant annotation to describe inheritance, allelic requirement, and both sequence and functional consequences of a variant is currently not standardized. There is considerable discrepancy in the literature and across clinical variant reporting in the derivation and application of terms. Here we standardize the terminology for the characterization of disease-gene relationships to facilitate harmonized global curation, and to support variant classification within the ACMG/AMP framework.

METHODS

Terminology for inheritance, allelic requirement, and both structural and functional consequences of a variant used by Gene Curation Coalition (GenCC) members and partner organizations was collated and reviewed. Harmonized terminology with definitions and use examples was created, reviewed, and validated.

RESULTS

We present a standardized terminology to describe gene-disease relationships, and to support variant annotation. We demonstrate application of the terminology for classification of variation in the ACMG SF 2.0 genes recommended for reporting of secondary findings. Consensus terms were agreed and formalized in both sequence ontology (SO) and human phenotype ontology (HPO) ontologies. GenCC member groups intend to use or map to these terms in their respective resources.

CONCLUSION

The terminology standardization presented here will improve harmonization, facilitate the pooling of curation datasets across international curation efforts and, in turn, improve consistency in variant classification and genetic test interpretation.

Exploring Genes and Phenotypes Within Chromosomal Regions Using OMIM's GeneScout

Structural variation in genomes, such as copy number variants (CNVs), is under scrutiny for its contribution to phenotypic expression and evolution. Regions of homozygosity (ROH) are ripe for phenotype-gene discovery. Determining the genes and related phenotypes within genomic regions is key to studying potential functional and phenotypic consequences. Because individuals have multiple CNVs and ROHs in their genome, identifying genomic regions that are phenotypically significant is challenging. GeneScout is a web-based tool that can be used to search genomic regions to display and filter the genes and their associated phenotypes within regions of interest. Phenotypes and their associated gene(s) can then be filtered to show only the genes with phenotypes that have a particular inheritance pattern and/or specific clinical feature(s). Phenotypes can then be selected to compare the clinical synopses side-by-side in Online Mendelian Inheritance in Man (OMIM^® ). Additionally, two coordinate sets can be compared to determine either the regions of overlap or the unique regions (subtraction). The resulting coordinate ranges are displayed on the results page, and the results table displays only the genes and phenotypes present within the coordinate ranges. The interactive table includes gene-specific links to external resources such as ClinVar, ClinGen validity, ClinGen dosage, and gnomAD, and a diamond symbol next to the gene name indicates a gene that spans the start or end of a coordinate range. Searches and comparisons may be performed for coordinates in assemblies GRCh37 (hg19) and GRCh38 (hg38). The results page offers the option to liftover coordinates entered in GRCh37 to GRCh38 and updates the results table to display the gene content based on assembly GRCh38. The search coordinates and results table can be downloaded in a tab-delimited or Excel file. © 2022 Wiley Periodicals LLC. Basic Protocol: Searching GeneScout.

The Gene Curation Coalition: A global effort to harmonize gene-disease evidence resources

PURPOSE

Several groups and resources provide information that pertains to the validity of gene-disease relationships used in genomic medicine and research; however, universal standards and terminologies to define the evidence base for the role of a gene in disease and a single harmonized resource were lacking. To tackle this issue, the Gene Curation Coalition (GenCC) was formed.

METHODS

The GenCC drafted harmonized definitions for differing levels of gene-disease validity on the basis of existing resources, and performed a modified Delphi survey with 3 rounds to narrow the list of terms. The GenCC also developed a unified database to display curated gene-disease validity assertions from its members.

RESULTS

On the basis of 241 survey responses from the genetics community, a consensus term set was chosen for grading gene-disease validity and database submissions. As of December 2021, the database contained 15,241 gene-disease assertions on 4569 unique genes from 12 submitters. When comparing submissions to the database from distinct sources, conflicts in assertions of gene-disease validity ranged from 5.3% to 13.4%.

CONCLUSION

Terminology standardization, sharing of gene-disease validity classifications, and resolution of curation conflicts will facilitate collaborations across international curation efforts and in turn, improve consistency in genetic testing and variant interpretation.

Monochorionic twins with 15q26.3 duplication presenting with selective intrauterine growth restriction and discordant cardiac anomalies: A case report

BACKGROUND

Duplication of the distal end of chromosome 15q has been previously implicated in a characteristic overgrowth syndrome. Additionally, many patients have other congenital malformations, including cardiac, renal, genital, and musculoskeletal anomalies. However, some patients may present with intrauterine growth restriction and short stature. Different breakpoints within 15q, as well as different environmental factors, may underlie these varied presentations.

CASE PRESENTATION

We discuss monochorionic-diamniotic twins with a ~345 kb maternally inherited duplication in 15q26.3. The twins presented with discordant pathology-one twin with a single umbilical artery, selective intrauterine growth restriction, and multiple cardiac defects including aortic coarctation, aortic valve stenosis, and ventricular septal defect, whereas the other twin was unaffected. To our knowledge, this case represents the smallest reported duplication of distal 15q.

CONCLUSION

The discordant phenotype seen in the twins is likely due to a complex interplay between genetic and environmental causes. The affected infant presented prenatally with growth restriction and a single umbilical artery rather than overgrowth, potentially due to a unique breakpoint within 15q. This, in turn, may have produced hemodynamic perturbations between the twins, leading to discordant cardiac disease. Our report thus highlights the importance of genetic and nongenetic mechanisms underlying discordant anomalies in monochorionic twins.

Variant-level matching for diagnosis and discovery: Challenges and opportunities

Here we describe MyGene2, Geno2MP, VariantMatcher, and Franklin; databases that provide variant-level information and phenotypic features to researchers, clinicians, healthcare providers and patients. Following the footsteps of the Matchmaker Exchange project that connects exome, genome, and phenotype databases at the gene level, these databases have as one goal to facilitate connection to one another using Data Connect, a standard for discovery and search of biomedical data from the Global Alliance for Genomics and Health (GA4GH).

Seven years since the launch of the Matchmaker Exchange: The evolution of genomic matchmaking

The Matchmaker Exchange (MME) was launched in 2015 to provide a robust mechanism to discover novel disease-gene relationships. It operates as a federated network connecting databases holding relevant data using a common application programming interface, where two or more users are looking for a match for the same gene (two-sided matchmaking). Seven years from its launch, it is clear that the MME is making outstanding contributions to understanding the morbid anatomy of the genome. The number of unique genes present across the MME has steadily increased over time; there are currently >13,520 unique genes (~68% of all protein-coding genes) connected across the MME's eight genomic matchmaking nodes, GeneMatcher, DECIPHER, PhenomeCentral, MyGene2, seqr, Initiative on Rare and Undiagnosed Disease, PatientMatcher, and the RD-Connect Genome-Phenome Analysis Platform. The collective data set accessible across the MME currently includes more than 120,000 cases from over 12,000 contributors in 98 countries. The discovery of potential new disease-gene relationships is happening daily and international collaborative teams are moving these advances forward to publication, now numbering well over 500. Expansion of data sharing into routine clinical practice by clinicians, genetic counselors, and clinical laboratories has ensured access to discovery for even more individuals with undiagnosed rare genetic diseases. Tens of thousands of patients and their family members have been directly or indirectly impacted by the discoveries facilitated by two-sided genomic matchmaking. MME supports further connections to the literature (PubCaseFinder) and to human and model organism resources (Monarch Initiative) and scientists (ModelMatcher). Efforts are now underway to explore additional approaches to matchmaking at the gene or variant level where there is only one querier (one-sided matchmaking). Genomic matchmaking has proven its utility over the past 7 years and will continue to facilitate discoveries in the years to come.

Lumping versus splitting: How to approach defining a disease to enable accurate genomic curation

The dilemma of how to categorize and classify diseases has been debated for centuries. The field of medical genetics has historically approached nosology based on clinical phenotypes observed in patients and families. Advances in genomic sequencing and understanding of genetic contributions to disease often provoke a need to reassess these classifications. The Clinical Genome Resource (ClinGen) has developed frameworks to classify the strength of evidence underlying monogenic gene-disease relationships, variant pathogenicity, and clinical actionability. It is therefore necessary to define the disease entity being evaluated, which can be challenging for genes associated with multiple conditions and/or a broad phenotypic spectrum. We therefore developed criteria to guide "lumping and splitting" decisions and improve consistency in defining monogenic gene-disease relationships. Here, we outline the precuration process, the lumping and splitting guidelines with examples, and describe the implications for clinical diagnosis, informatics, and care management.

Centers for Mendelian Genomics: A decade of facilitating gene discovery

PURPOSE

Mendelian disease genomic research has undergone a massive transformation over the past decade. With increasing availability of exome and genome sequencing, the role of Mendelian research has expanded beyond data collection, sequencing, and analysis to worldwide data sharing and collaboration.

METHODS

Over the past 10 years, the National Institutes of Health-supported Centers for Mendelian Genomics (CMGs) have played a major role in this research and clinical evolution.

RESULTS

We highlight the cumulative gene discoveries facilitated by the program, biomedical research leveraged by the approach, and the larger impact on the research community. Beyond generating a list of gene-phenotype relationships and participating in widespread data sharing, the CMGs have created resources, tools, and training for the larger community to foster understanding of genes and genome variation. The CMGs have participated in a wide range of data sharing activities, including deposition of all eligible CMG data into the Analysis, Visualization, and Informatics Lab-space (AnVIL), sharing candidate genes through the Matchmaker Exchange and the CMG website, and sharing variants in Genotypes to Mendelian Phenotypes (Geno2MP) and VariantMatcher.

CONCLUSION

The work is far from complete; strengthening communication between research and clinical realms, continued development and sharing of knowledge and tools, and improving access to richly characterized data sets are all required to diagnose the remaining molecularly undiagnosed patients.

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.

GA4GH: International policies and standards for data sharing across genomic research and healthcare

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

Three decades of the Human Genome Organization

The Human Genome Organization (HUGO) was initially established in 1988 to help integrate international scientific genomic activity and to accelerate the diffusion of knowledge from the efforts of the human genome project. Its founding President was Victor McKusick. During the late 1980s and 1990s, HUGO organized lively gene mapping meetings to accurately place genes on the genome as chromosomes were being sequenced. With the completion of the Human Genome Project, HUGO went through some transitions and self-reflection. In 2020, HUGO (which hosts a large annual scientific meeting and comprises the renowned HUGO Gene Nomenclature Committee [HGNC], responsible for naming genes, and an outstanding Ethics Committee) was merged with the Human Genome Variation Society (HGVS; which defines the correct nomenclature for variation description) and the Human Variome Project (HVP; championed by the late Richard Cotton) into a single organization that is committed to assembling human genomic variation from all over the world. This consolidated effort, under a new Executive Board and seven focused committees, will facilitate efficient and effective communication and action to bring the benefits of increasing knowledge of genome diversity and biology to people all over the world.

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.

Orthopaedic Manifestations of Inborn Errors of Metabolism

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Inborn errors of metabolism are disorders of carbohydrate, amino acid, organic acid, or purine and pyrimidine metabolism; disorders of fatty acid oxidation; disorders of metal metabolism; and lysosomal storage defects that can cause metabolic derangements that have secondary musculoskeletal effects.

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Orthopaedic surgeons should be aware that patients with inborn errors of metabolism may be at high risk for spasticity, which may cause joint subluxations, scoliosis, and contractures, as well as poor bone quality, which is caused by malnutrition or disordered bone growth.

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Multidisciplinary care and follow-up are important to identify musculoskeletal problems in a timely manner in order to provide effective treatment.

Online Mendelian Inheritance in Man (OMIM®): Victor McKusick's magnum opus

Victor McKusick's many contributions to medicine are legendary, but his magnum opus is Mendelian Inheritance in Man (MIM), his catalog of Mendelian phenotypes and their associated genes. The catalog, originally published in 1966 in book form, became available on the internet as Online Mendelian Inheritance in Man (OMIM®) in 1987. The first of 12 editions of MIM included 1486 entries; this number has increased to over 25,000 entries in OMIM as of April 2021, which demonstrates the growth of knowledge about Mendelian phenotypes and their genes through the years. OMIM now has over 20,000 unique users a day, including users from every country in the world. Many of the early decisions made by McKusick, such as to maintain MIM data in a computer‐readable format, to separate phenotype entries from those for genes, and to give phenotypes and genes MIM numbers, have proved essential to the long‐term utility and flexibility of his catalog. Based on his extensive knowledge of genetics and vision of its future in the field of medicine, he developed a framework for the capture and summary of information from the published literature on phenotypes and their associated genes; this catalog continues to serve as an indispensable resource to the genetics community.

Viewing Victor McKusick's legacy through the lens of his bibliography

Victor McKusick's contributions to the field of medical genetics are legendary and include his contributions as a mentor, as creator of Mendelian Inheritance in Man (now Online Mendelian Inheritance in Man [OMIM®]), and as a leader in the field of medical genetics. McKusick's full bibliography includes 772 publications. Here we review the 453 papers authored by McKusick and indexed in PubMed, from his earliest paper published in the New England Journal of Medicine in 1949 to his last paper published in American Journal of Medical Genetics Part A in 2008. This review of his bibliography chronicles McKusick's evolution from an internist and cardiologist with an interest in genetics to an esteemed leader in the growing field of medical genetics. Review of his bibliography also provides a historical perspective of the development of the discipline of medical genetics. This field came into its own during his lifetime, transitioning from the study of interesting cases and families used to codify basic medical genetics principles to an accredited medical specialty that is expected to transform healthcare. Along the way, he helped to unite the fields of medical and human genetics to focus on mapping the human genome, culminating in completion of the Human Genome Project. This review confirms the critical role played by Victor McKusick as the founding father of medical genetics.

Next-generation sequencing and the evolution of data sharing

Disease gene identification often relies on identifying multiple affected individuals with similar phenotypes and candidate variants in the same gene. Phenotypic and genomic data sharing tools have facilitated connections that led to novel disease gene discoveries and better characterization and recognition of rare diseases. Additionally, data sharing has evolved. From gene-based matches to variant-level information with increasing use of phenotypic information. We expect that these initiatives will continue to expand in the future affording clinicians, researchers, and most importantly, patients and their families faster and more comprehensive answers.

KMT2B-related disorders: expansion of the phenotypic spectrum and long-term efficacy of deep brain stimulation

Heterozygous mutations in KMT2B are associated with an early-onset, progressive and often complex dystonia (DYT28). Key characteristics of typical disease include focal motor features at disease presentation, evolving through a caudocranial pattern into generalized dystonia, with prominent oromandibular, laryngeal and cervical involvement. Although KMT2B-related disease is emerging as one of the most common causes of early-onset genetic dystonia, much remains to be understood about the full spectrum of the disease. We describe a cohort of 53 patients with KMT2B mutations, with detailed delineation of their clinical phenotype and molecular genetic features. We report new disease presentations, including atypical patterns of dystonia evolution and a subgroup of patients with a non-dystonic neurodevelopmental phenotype. In addition to the previously reported systemic features, our study has identified co-morbidities, including the risk of status dystonicus, intrauterine growth retardation, and endocrinopathies. Analysis of this study cohort (n = 53) in tandem with published cases (n = 80) revealed that patients with chromosomal deletions and protein truncating variants had a significantly higher burden of systemic disease (with earlier onset of dystonia) than those with missense variants. Eighteen individuals had detailed longitudinal data available after insertion of deep brain stimulation for medically refractory dystonia. Median age at deep brain stimulation was 11.5 years (range: 4.5-37.0 years). Follow-up after deep brain stimulation ranged from 0.25 to 22 years. Significant improvement of motor function and disability (as assessed by the Burke Fahn Marsden's Dystonia Rating Scales, BFMDRS-M and BFMDRS-D) was evident at 6 months, 1 year and last follow-up (motor, P = 0.001, P = 0.004, and P = 0.012; disability, P = 0.009, P = 0.002 and P = 0.012). At 1 year post-deep brain stimulation, >50% of subjects showed BFMDRS-M and BFMDRS-D improvements of >30%. In the long-term deep brain stimulation cohort (deep brain stimulation inserted for >5 years, n = 8), improvement of >30% was maintained in 5/8 and 3/8 subjects for the BFMDRS-M and BFMDRS-D, respectively. The greatest BFMDRS-M improvements were observed for trunk (53.2%) and cervical (50.5%) dystonia, with less clinical impact on laryngeal dystonia. Improvements in gait dystonia decreased from 20.9% at 1 year to 16.2% at last assessment; no patient maintained a fully independent gait. Reduction of BFMDRS-D was maintained for swallowing (52.9%). Five patients developed mild parkinsonism following deep brain stimulation. KMT2B-related disease comprises an expanding continuum from infancy to adulthood, with early evidence of genotype-phenotype correlations. Except for laryngeal dysphonia, deep brain stimulation provides a significant improvement in quality of life and function with sustained clinical benefit depending on symptoms distribution.

Alternative genomic diagnoses for individuals with a clinical diagnosis of Dubowitz syndrome

Dubowitz syndrome (DubS) is considered a recognizable syndrome characterized by a distinctive facial appearance and deficits in growth and development. There have been over 200 individuals reported with Dubowitz or a "Dubowitz-like" condition, although no single gene has been implicated as responsible for its cause. We have performed exome (ES) or genome sequencing (GS) for 31 individuals clinically diagnosed with DubS. After genome-wide sequencing, rare variant filtering and computational and Mendelian genomic analyses, a presumptive molecular diagnosis was made in 13/27 (48%) families. The molecular diagnoses included biallelic variants in SKIV2L, SLC35C1, BRCA1, NSUN2; de novo variants in ARID1B, ARID1A, CREBBP, POGZ, TAF1, HDAC8, and copy-number variation at1p36.11(ARID1A), 8q22.2(VPS13B), Xp22, and Xq13(HDAC8). Variants of unknown significance in known disease genes, and also in genes of uncertain significance, were observed in 7/27 (26%) additional families. Only one gene, HDAC8, could explain the phenotype in more than one family (N = 2). All but two of the genomic diagnoses were for genes discovered, or for conditions recognized, since the introduction of next-generation sequencing. Overall, the DubS-like clinical phenotype is associated with extensive locus heterogeneity and the molecular diagnoses made are for emerging clinical conditions sharing characteristic features that overlap the DubS phenotype.

The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven’t been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

Genomic Data Sharing for Novel Mendelian Disease Gene Discovery: The Matchmaker Exchange

In the last decade, exome and/or genome sequencing has become a common test in the diagnosis of individuals with features of a rare Mendelian disorder. Despite its success, this test leaves the majority of tested individuals undiagnosed. This review describes the Matchmaker Exchange (MME), a federated network established to facilitate the solving of undiagnosed rare-disease cases through data sharing. MME supports genomic matchmaking, the act of connecting two or more parties looking for cases with similar phenotypes and variants in the same candidate genes. An application programming interface currently connects six matchmaker nodes-the Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources (DECIPHER), GeneMatcher, PhenomeCentral, seqr, MyGene2, and the Initiative on Rare and Undiagnosed Diseases (IRUD) Exchange-resulting in a collective data set spanning more than 150,000 cases from more than 11,000 contributors in 88 countries. Here, we describe the successes and challenges of MME, its individual matchmaking nodes, plans for growing the network, and considerations for future directions.

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.

How many rare diseases are there?

A lack of robust knowledge of the number of rare diseases and the number of people affected by them limits the development of approaches to ameliorate the substantial cumulative burden of rare diseases. Here, we call for coordinated efforts to more precisely define rare diseases.

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.

Pathogenic Variants in NUP214 Cause "Plugged" Nuclear Pore Channels and Acute Febrile Encephalopathy

We report biallelic missense and frameshift pathogenic variants in the gene encoding human nucleoporin NUP214 causing acute febrile encephalopathy. Clinical symptoms include neurodevelopmental regression, seizures, myoclonic jerks, progressive microcephaly, and cerebellar atrophy. NUP214 and NUP88 protein levels were reduced in primary skin fibroblasts derived from affected individuals, while the total number and density of nuclear pore complexes remained normal. Nuclear transport assays exhibited defects in the classical protein import and mRNA export pathways in affected cells. Direct surface imaging of fibroblast nuclei by scanning electron microscopy revealed a large increase in the presence of central particles (known as "plugs") in the nuclear pore channels of affected cells. This observation suggests that large transport cargoes may be delayed in passage through the nuclear pore channel, affecting its selective barrier function. Exposure of fibroblasts from affected individuals to heat shock resulted in a marked delay in their stress response, followed by a surge in apoptotic cell death. This suggests a mechanistic link between decreased cell survival in cell culture and severe fever-induced brain damage in affected individuals. Our study provides evidence by direct imaging at the single nuclear pore level of functional changes linked to a human disease.

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.

OMIM.org: leveraging knowledge across phenotype-gene relationships

For over 50 years Mendelian Inheritance in Man has chronicled the collective knowledge of the field of medical genetics. It initially cataloged the known X-linked, autosomal recessive and autosomal dominant inherited disorders, but grew to be the primary repository of curated information on both genes and genetic phenotypes and the relationships between them. Each phenotype and gene is given a separate entry assigned a stable, unique identifier. The entries contain structured summaries of new and important information based on expert review of the biomedical literature. OMIM.org provides interactive access to the knowledge repository, including genomic coordinate searches of the gene map, views of genetic heterogeneity of phenotypes in Phenotypic Series, and side-by-side comparisons of clinical synopses. OMIM.org also supports computational queries via a robust API. All entries have extensive targeted links to other genomic resources and additional references. Updates to OMIM can be found on the update list or followed through the MIMmatch service. Updated user guides and tutorials are available on the website. As of September 2018, OMIM had over 24,600 entries, and the OMIM Morbid Map Scorecard had 6,259 molecularized phenotypes connected to 3,961 genes.

Matchmaker Exchange

In well over half of the individuals with rare disease who undergo clinical or research next-generation sequencing, the responsible gene cannot be determined. Some reasons for this relatively low yield include unappreciated phenotypic heterogeneity; locus heterogeneity; somatic and germline mosaicism; variants of uncertain functional significance; technically inaccessible areas of the genome; incorrect mode of inheritance investigated; and inadequate communication between clinicians and basic scientists with knowledge of particular genes, proteins, or biological systems. To facilitate such communication and improve the search for patients or model organisms with similar phenotypes and variants in specific candidate genes, we have developed the Matchmaker Exchange (MME). MME was created to establish a federated network connecting databases of genomic and phenotypic data using a common application programming interface (API). To date, seven databases can exchange data using the API (GeneMatcher, PhenomeCentral, DECIPHER, MyGene2, matchbox, Australian Genomics Health Alliance Patient Archive, and Monarch Initiative; the latter included for model organism matching). This article guides usage of the MME for rare disease gene discovery. © 2017 by John Wiley & Sons, Inc.

"Matching" consent to purpose: The example of the Matchmaker Exchange

The Matchmaker Exchange (MME) connects rare disease clinicians and researchers to facilitate the sharing of data from undiagnosed patients for the purpose of novel gene discovery. Such sharing raises the odds that two or more similar patients with candidate genes in common may be found, thereby allowing their condition to be more readily studied and understood. Consent considerations for data sharing in MME included both the ethical and legal differences between clinical and research settings and the level of privacy risk involved in sharing varying amounts of rare disease patient data to enable patient matches. In this commentary, we discuss these consent considerations and the resulting MME Consent Policy as they may be relevant to other international data sharing initiatives.

Searching Online Mendelian Inheritance in Man (OMIM): A Knowledgebase of Human Genes and Genetic Phenotypes

Online Mendelian Inheritance in Man (OMIM) at OMIM.org is the primary repository of comprehensive, curated information on genes and genetic phenotypes and the relationships between them. This unit provides an overview of the types of information in OMIM and optimal strategies for searching and retrieving the information. OMIM.org has links to many related and complementary databases, providing easy access to more information on a topic. The relationship between genes and genetic disorders is highlighted in this unit. The basic protocol explains searching OMIM both from a gene perspective and a clinical features perspective. Two alternate protocols provide strategies for viewing gene-phenotype relationships: a gene map table and Quick View or Side-by-Side format for clinical features. OMIM.org is updated nightly, and the MIMmatch service, described in the support protocol, provides a convenient way to follow updates to entries, gene-phenotype relationships, and collaborate with other researchers. © 2017 by John Wiley & Sons, Inc.

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.

The Human Phenotype Ontology in 2017

Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human Phenotype Ontology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology.

KIF5A mutations cause an infantile onset phenotype including severe myoclonus with evidence of mitochondrial dysfunction

Missense mutations in kinesin family member 5A (KIF5A) cause spastic paraplegia 10. We report on 2 patients with de novo stop-loss frameshift variants in KIF5A resulting in a novel phenotype that includes severe infantile onset myoclonus, hypotonia, optic nerve abnormalities, dysphagia, apnea, and early developmental arrest. We propose that alteration and elongation of the carboxy-terminus of the protein has a dominant-negative effect, causing mitochondrial dysfunction in the setting of an abnormal kinesin "motor." These results highlight the role of expanded testing and whole-exome sequencing in critically ill infants and emphasize the importance of accurate test interpretation. Ann Neurol 2016;80:633-637.

The Matchmaker Exchange: a platform for rare disease gene discovery

There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for "the needle in a haystack" to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can "match" these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.

Human genome meeting 2016 : Houston, TX, USA. 28 February - 2 March 2016

O1 The metabolomics approach to autism: identification of biomarkers for early detection of autism spectrum disorder A. K. Srivastava, Y. Wang, R. Huang, C. Skinner, T. Thompson, L. Pollard, T. Wood, F. Luo, R. Stevenson O2 Phenome-wide association study for smoking- and drinking-associated genes in 26,394 American women with African, Asian, European, and Hispanic descents R. Polimanti, J. Gelernter O3 Effects of prenatal environment, genotype and DNA methylation on birth weight and subsequent postnatal outcomes: findings from GUSTO, an Asian birth cohort X. Lin, I. Y. Lim, Y. Wu, A. L. Teh, L. Chen, I. M. Aris, S. E. Soh, M. T. Tint, J. L. MacIsaac, F. Yap, K. Kwek, S. M. Saw, M. S. Kobor, M. J. Meaney, K. M. Godfrey, Y. S. Chong, J. D. Holbrook, Y. S. Lee, P. D. Gluckman, N. Karnani, GUSTO study group O4 High-throughput identification of specific qt interval modulating enhancers at the SCN5A locus A. Kapoor, D. Lee, A. Chakravarti O5 Identification of extracellular matrix components inducing cancer cell migration in the supernatant of cultivated mesenchymal stem cells C. Maercker, F. Graf, M. Boutros O6 Single cell allele specific expression (ASE) IN T21 and common trisomies: a novel approach to understand DOWN syndrome and other aneuploidies G. Stamoulis, F. Santoni, P. Makrythanasis, A. Letourneau, M. Guipponi, N. Panousis, M. Garieri, P. Ribaux, E. Falconnet, C. Borel, S. E. Antonarakis O7 Role of microRNA in LCL to IPSC reprogramming S. Kumar, J. Curran, J. Blangero O8 Multiple enhancer variants disrupt gene regulatory network in Hirschsprung disease S. Chatterjee, A. Kapoor, J. Akiyama, D. Auer, C. Berrios, L. Pennacchio, A. Chakravarti O9 Metabolomic profiling for the diagnosis of neurometabolic disorders T. R. Donti, G. Cappuccio, M. Miller, P. Atwal, A. Kennedy, A. Cardon, C. Bacino, L. Emrick, J. Hertecant, F. Baumer, B. Porter, M. Bainbridge, P. Bonnen, B. Graham, R. Sutton, Q. Sun, S. Elsea O10 A novel causal methylation network approach to Alzheimer’s disease Z. Hu, P. Wang, Y. Zhu, J. Zhao, M. Xiong, David A Bennett O11 A microRNA signature identifies subtypes of triple-negative breast cancer and reveals MIR-342-3P as regulator of a lactate metabolic pathway A. Hidalgo-Miranda, S. Romero-Cordoba, S. Rodriguez-Cuevas, R. Rebollar-Vega, E. Tagliabue, M. Iorio, E. D’Ippolito, S. Baroni O12 Transcriptome analysis identifies genes, enhancer RNAs and repetitive elements that are recurrently deregulated across multiple cancer types B. Kaczkowski, Y. Tanaka, H. Kawaji, A. Sandelin, R. Andersson, M. Itoh, T. Lassmann, the FANTOM5 consortium, Y. Hayashizaki, P. Carninci, A. R. R. Forrest O13 Elevated mutation and widespread loss of constraint at regulatory and architectural binding sites across 11 tumour types C. A. Semple O14 Exome sequencing provides evidence of pathogenicity for genes implicated in colorectal cancer E. A. Rosenthal, B. Shirts, L. Amendola, C. Gallego, M. Horike-Pyne, A. Burt, P. Robertson, P. Beyers, C. Nefcy, D. Veenstra, F. Hisama, R. Bennett, M. Dorschner, D. Nickerson, J. Smith, K. Patterson, D. Crosslin, R. Nassir, N. Zubair, T. Harrison, U. Peters, G. Jarvik, NHLBI GO Exome Sequencing Project O15 The tandem duplicator phenotype as a distinct genomic configuration in cancer F. Menghi, K. Inaki, X. Woo, P. Kumar, K. Grzeda, A. Malhotra, H. Kim, D. Ucar, P. Shreckengast, K. Karuturi, J. Keck, J. Chuang, E. T. Liu O16 Modeling genetic interactions associated with molecular subtypes of breast cancer B. Ji, A. Tyler, G. Ananda, G. Carter O17 Recurrent somatic mutation in the MYC associated factor X in brain tumors H. Nikbakht, M. Montagne, M. Zeinieh, A. Harutyunyan, M. Mcconechy, N. Jabado, P. Lavigne, J. Majewski O18 Predictive biomarkers to metastatic pancreatic cancer treatment J. B. Goldstein, M. Overman, G. Varadhachary, R. Shroff, R. Wolff, M. Javle, A. Futreal, D. Fogelman O19 DDIT4 gene expression as a prognostic marker in several malignant tumors L. Bravo, W. Fajardo, H. Gomez, C. Castaneda, C. Rolfo, J. A. Pinto O20 Spatial organization of the genome and genomic alterations in human cancers K. C. Akdemir, L. Chin, A. Futreal, ICGC PCAWG Structural Alterations Group O21 Landscape of targeted therapies in solid tumors S. Patterson, C. Statz, S. Mockus O22 Genomic analysis reveals novel drivers and progression pathways in skin basal cell carcinoma S. N. Nikolaev, X. I. Bonilla, L. Parmentier, B. King, F. Bezrukov, G. Kaya, V. Zoete, V. Seplyarskiy, H. Sharpe, T. McKee, A. Letourneau, P. Ribaux, K. Popadin, N. Basset-Seguin, R. Ben Chaabene, F. Santoni, M. Andrianova, M. Guipponi, M. Garieri, C. Verdan, K. Grosdemange, O. Sumara, M. Eilers, I. Aifantis, O. Michielin, F. de Sauvage, S. Antonarakis O23 Identification of differential biomarkers of hepatocellular carcinoma and cholangiocarcinoma via transcriptome microarray meta-analysis S. Likhitrattanapisal O24 Clinical validity and actionability of multigene tests for hereditary cancers in a large multi-center study S. Lincoln, A. Kurian, A. Desmond, S. Yang, Y. Kobayashi, J. Ford, L. Ellisen O25 Correlation with tumor ploidy status is essential for correct determination of genome-wide copy number changes by SNP array T. L. Peters, K. R. Alvarez, E. F. Hollingsworth, D. H. Lopez-Terrada O26 Nanochannel based next-generation mapping for interrogation of clinically relevant structural variation A. Hastie, Z. Dzakula, A. W. Pang, E. T. Lam, T. Anantharaman, M. Saghbini, H. Cao, BioNano Genomics O27 Mutation spectrum in a pulmonary arterial hypertension (PAH) cohort and identification of associated truncating mutations in TBX4 C. Gonzaga-Jauregui, L. Ma, A. King, E. Berman Rosenzweig, U. Krishnan, J. G. Reid, J. D. Overton, F. Dewey, W. K. Chung O28 NORTH CAROLINA macular dystrophy (MCDR1): mutations found affecting PRDM13 K. Small, A. DeLuca, F. Cremers, R. A. Lewis, V. Puech, B. Bakall, R. Silva-Garcia, K. Rohrschneider, M. Leys, F. S. Shaya, E. Stone O29 PhenoDB and genematcher, solving unsolved whole exome sequencing data N. L. Sobreira, F. Schiettecatte, H. Ling, E. Pugh, D. Witmer, K. Hetrick, P. Zhang, K. Doheny, D. Valle, A. Hamosh O30 Baylor-Johns Hopkins Center for Mendelian genomics: a four year review S. N. Jhangiani, Z. Coban Akdemir, M. N. Bainbridge, W. Charng, W. Wiszniewski, T. Gambin, E. Karaca, Y. Bayram, M. K. Eldomery, J. Posey, H. Doddapaneni, J. Hu, V. R. Sutton, D. M. Muzny, E. A. Boerwinkle, D. Valle, J. R. Lupski, R. A. Gibbs O31 Using read overlap assembly to accurately identify structural genetic differences in an ashkenazi jewish trio S. Shekar, W. Salerno, A. English, A. Mangubat, J. Bruestle O32 Legal interoperability: a sine qua non for international data sharing A. Thorogood, B. M. Knoppers, Global Alliance for Genomics and Health - Regulatory and Ethics Working Group O33 High throughput screening platform of competent sineups: that can enhance translation activities of therapeutic target H. Takahashi, K. R. Nitta, A. Kozhuharova, A. M. Suzuki, H. Sharma, D. Cotella, C. Santoro, S. Zucchelli, S. Gustincich, P. Carninci O34 The undiagnosed diseases network international (UDNI): clinical and laboratory research to meet patient needs J. J. Mulvihill, G. Baynam, W. Gahl, S. C. Groft, K. Kosaki, P. Lasko, B. Melegh, D. Taruscio O36 Performance of computational algorithms in pathogenicity predictions for activating variants in oncogenes versus loss of function mutations in tumor suppressor genes R. Ghosh, S. Plon O37 Identification and electronic health record incorporation of clinically actionable pharmacogenomic variants using prospective targeted sequencing S. Scherer, X. Qin, R. Sanghvi, K. Walker, T. Chiang, D. Muzny, L. Wang, J. Black, E. Boerwinkle, R. Weinshilboum, R. Gibbs O38 Melanoma reprogramming state correlates with response to CTLA-4 blockade in metastatic melanoma T. Karpinets, T. Calderone, K. Wani, X. Yu, C. Creasy, C. Haymaker, M. Forget, V. Nanda, J. Roszik, J. Wargo, L. Haydu, X. Song, A. Lazar, J. Gershenwald, M. Davies, C. Bernatchez, J. Zhang, A. Futreal, S. Woodman O39 Data-driven refinement of complex disease classification from integration of heterogeneous functional genomics data in GeneWeaver E. J. Chesler, T. Reynolds, J. A. Bubier, C. Phillips, M. A. Langston, E. J. Baker O40 A general statistic framework for genome-based disease risk prediction M. Xiong, L. Ma, N. Lin, C. Amos O41 Integrative large-scale causal network analysis of imaging and genomic data and its application in schizophrenia studies N. Lin, P. Wang, Y. Zhu, J. Zhao, V. Calhoun, M. Xiong O42 Big data and NGS data analysis: the cloud to the rescue O. Dobretsberger, M. Egger, F. Leimgruber O43 Cpipe: a convergent clinical exome pipeline specialised for targeted sequencing S. Sadedin, A. Oshlack, Melbourne Genomics Health Alliance O44 A Bayesian classification of biomedical images using feature extraction from deep neural networks implemented on lung cancer data V. A. A. Antonio, N. Ono, Clark Kendrick C. Go O45 MAV-SEQ: an interactive platform for the Management, Analysis, and Visualization of sequence data Z. Ahmed, M. Bolisetty, S. Zeeshan, E. Anguiano, D. Ucar O47 Allele specific enhancer in EPAS1 intronic regions may contribute to high altitude adaptation of Tibetans C. Zeng, J. Shao O48 Nanochannel based next-generation mapping for structural variation detection and comparison in trios and populations H. Cao, A. Hastie, A. W. Pang, E. T. Lam, T. Liang, K. Pham, M. Saghbini, Z. Dzakula O49 Archaic introgression in indigenous populations of Malaysia revealed by whole genome sequencing Y. Chee-Wei, L. Dongsheng, W. Lai-Ping, D. Lian, R. O. Twee Hee, Y. Yunus, F. Aghakhanian, S. S. Mokhtar, C. V. Lok-Yung, J. Bhak, M. Phipps, X. Shuhua, T. Yik-Ying, V. Kumar, H. Boon-Peng O50 Breast and ovarian cancer prevention: is it time for population-based mutation screening of high risk genes? I. Campbell, M.-A. Young, P. James, Lifepool O53 Comprehensive coverage from low DNA input using novel NGS library preparation methods for WGS and WGBS C. Schumacher, S. Sandhu, T. Harkins, V. Makarov O54 Methods for large scale construction of robust PCR-free libraries for sequencing on Illumina HiSeqX platform H. DoddapaneniR. Glenn, Z. Momin, B. Dilrukshi, H. Chao, Q. Meng, B. Gudenkauf, R. Kshitij, J. Jayaseelan, C. Nessner, S. Lee, K. Blankenberg, L. Lewis, J. Hu, Y. Han, H. Dinh, S. Jireh, K. Walker, E. Boerwinkle, D. Muzny, R. Gibbs O55 Rapid capture methods for clinical sequencing J. Hu, K. Walker, C. Buhay, X. Liu, Q. Wang, R. Sanghvi, H. Doddapaneni, Y. Ding, N. Veeraraghavan, Y. Yang, E. Boerwinkle, A. L. Beaudet, C. M. Eng, D. M. Muzny, R. A. Gibbs O56 A diploid personal human genome model for better genomes from diverse sequence data K. C. C. Worley, Y. Liu, D. S. T. Hughes, S. C. Murali, R. A. Harris, A. C. English, X. Qin, O. A. Hampton, P. Larsen, C. Beck, Y. Han, M. Wang, H. Doddapaneni, C. L. Kovar, W. J. Salerno, A. Yoder, S. Richards, J. Rogers, J. R. Lupski, D. M. Muzny, R. A. Gibbs O57 Development of PacBio long range capture for detection of pathogenic structural variants Q. Meng, M. Bainbridge, M. Wang, H. Doddapaneni, Y. Han, D. Muzny, R. Gibbs O58 Rhesus macaques exhibit more non-synonymous variation but greater impact of purifying selection than humans R. A. Harris, M. Raveenedran, C. Xue, M. Dahdouli, L. Cox, G. Fan, B. Ferguson, J. Hovarth, Z. Johnson, S. Kanthaswamy, M. Kubisch, M. Platt, D. Smith, E. Vallender, R. Wiseman, X. Liu, J. Below, D. Muzny, R. Gibbs, F. Yu, J. Rogers O59 Assessing RNA structure disruption induced by single-nucleotide variation J. Lin, Y. Zhang, Z. Ouyang P1 A meta-analysis of genome-wide association studies of mitochondrial dna copy number A. Moore, Z. Wang, J. Hofmann, M. Purdue, R. Stolzenberg-Solomon, S. Weinstein, D. Albanes, C.-S. Liu, W.-L. Cheng, T.-T. Lin, Q. Lan, N. Rothman, S. Berndt P2 Missense polymorphic genetic combinations underlying down syndrome susceptibility E. S. Chen P4 The evaluation of alteration of ELAM-1 expression in the endometriosis patients H. Bahrami, A. Khoshzaban, S. Heidari Keshal P5 Obesity and the incidence of apolipoprotein E polymorphisms in an assorted population from Saudi Arabia population K. K. R. Alharbi P6 Genome-associated personalized antithrombotical therapy for patients with high risk of thrombosis and bleeding M. Zhalbinova, A. Akilzhanova, S. Rakhimova, M. Bekbosynova, S. Myrzakhmetova P7 Frequency of Xmn1 polymorphism among sickle cell carrier cases in UAE population M. Matar P8 Differentiating inflammatory bowel diseases by using genomic data: dimension of the problem and network organization N. Mili, R. Molinari, Y. Ma, S. Guerrier P9 Vulnerability of genetic variants to the risk of autism among Saudi children N. Elhawary, M. Tayeb, N. Bogari, N. Qotb P10 Chromatin profiles from ex vivo purified dopaminergic neurons establish a promising model to support studies of neurological function and dysfunction S. A. McClymont, P. W. Hook, L. A. Goff, A. McCallion P11 Utilization of a sensitized chemical mutagenesis screen to identify genetic modifiers of retinal dysplasia in homozygous Nr2e3^rd7 mice Y. Kong, J. R. Charette, W. L. Hicks, J. K. Naggert, L. Zhao, P. M. Nishina P12 Ion torrent next generation sequencing of recessive polycystic kidney disease in Saudi patients B. M. Edrees, M. Athar, F. A. Al-Allaf, M. M. Taher, W. Khan, A. Bouazzaoui, N. A. Harbi, R. Safar, H. Al-Edressi, A. Anazi, N. Altayeb, M. A. Ahmed, K. Alansary, Z. Abduljaleel P13 Digital expression profiling of Purkinje neurons and dendrites in different subcellular compartments A. Kratz, P. Beguin, S. Poulain, M. Kaneko, C. Takahiko, A. Matsunaga, S. Kato, A. M. Suzuki, N. Bertin, T. Lassmann, R. Vigot, P. Carninci, C. Plessy, T. Launey P14 The evolution of imperfection and imperfection of evolution: the functional and functionless fractions of the human genome D. Graur P16 Species-independent identification of known and novel recurrent genomic entities in multiple cancer patients J. Friis-Nielsen, J. M. Izarzugaza, S. Brunak P18 Discovery of active gene modules which are densely conserved across multiple cancer types reveal their prognostic power and mutually exclusive mutation patterns B. S. Soibam P19 Whole exome sequencing of dysplastic leukoplakia tissue indicates sequential accumulation of somatic mutations from oral precancer to cancer D. Das, N. Biswas, S. Das, S. Sarkar, A. Maitra, C. Panda, P. Majumder P21 Epigenetic mechanisms of carcinogensis by hereditary breast cancer genes J. J. Gruber, N. Jaeger, M. Snyder P22 RNA direct: a novel RNA enrichment strategy applied to transcripts associated with solid tumors K. Patel, S. Bowman, T. Davis, D. Kraushaar, A. Emerman, S. Russello, N. Henig, C. Hendrickson P23 RNA sequencing identifies gene mutations for neuroblastoma K. Zhang P24 Participation of SFRP1 in the modulation of TMPRSS2-ERG fusion gene in prostate cancer cell lines M. Rodriguez-Dorantes, C. D. Cruz-Hernandez, C. D. P. Garcia-Tobilla, S. Solorzano-Rosales P25 Targeted Methylation Sequencing of Prostate Cancer N. Jäger, J. Chen, R. Haile, M. Hitchins, J. D. Brooks, M. Snyder P26 Mutant TPMT alleles in children with acute lymphoblastic leukemia from México City and Yucatán, Mexico S. Jiménez-Morales, M. Ramírez, J. Nuñez, V. Bekker, Y. Leal, E. Jiménez, A. Medina, A. Hidalgo, J. Mejía P28 Genetic modifiers of Alström syndrome J. Naggert, G. B. Collin, K. DeMauro, R. Hanusek, P. M. Nishina P31 Association of genomic variants with the occurrence of angiotensin-converting-enzyme inhibitor (ACEI)-induced coughing among Filipinos E. M. Cutiongco De La Paz, R. Sy, J. Nevado, P. Reganit, L. Santos, J. D. Magno, F. E. Punzalan , D. Ona , E. Llanes, R. L. Santos-Cortes , R. Tiongco, J. Aherrera, L. Abrahan, P. Pagauitan-Alan; Philippine Cardiogenomics Study Group P32 The use of “humanized” mouse models to validate disease association of a de novo GARS variant and to test a novel gene therapy strategy for Charcot-Marie-Tooth disease type 2D K. H. Morelli, J. S. Domire, N. Pyne, S. Harper, R. Burgess P34 Molecular regulation of chondrogenic human induced pluripotent stem cells M. A. Gari, A. Dallol, H. Alsehli, A. Gari, M. Gari, A. Abuzenadah P35 Molecular profiling of hematologic malignancies: implementation of a variant assessment algorithm for next generation sequencing data analysis and clinical reporting M. Thomas, M. Sukhai, S. Garg, M. Misyura, T. Zhang, A. Schuh, T. Stockley, S. Kamel-Reid P36 Accessing genomic evidence for clinical variants at NCBI S. Sherry, C. Xiao, D. Slotta, K. Rodarmer, M. Feolo, M. Kimelman, G. Godynskiy, C. O’Sullivan, E. Yaschenko P37 NGS-SWIFT: a cloud-based variant analysis framework using control-accessed sequencing data from DBGAP/SRA C. Xiao, E. Yaschenko, S. Sherry P38 Computational assessment of drug induced hepatotoxicity through gene expression profiling C. Rangel-Escareño, H. Rueda-Zarate P40 Flowr: robust and efficient pipelines using a simple language-agnostic approach;ultraseq; fast modular pipeline for somatic variation calling using flowr S. Seth, S. Amin, X. Song, X. Mao, H. Sun, R. G. Verhaak, A. Futreal, J. Zhang P41 Applying “Big data” technologies to the rapid analysis of heterogenous large cohort data S. J. Whiite, T. Chiang, A. English, J. Farek, Z. Kahn, W. Salerno, N. Veeraraghavan, E. Boerwinkle, R. Gibbs P42 FANTOM5 web resource for the large-scale genome-wide transcription start site activity profiles of wide-range of mammalian cells T. Kasukawa, M. Lizio, J. Harshbarger, S. Hisashi, J. Severin, A. Imad, S. Sahin, T. C. Freeman, K. Baillie, A. Sandelin, P. Carninci, A. R. R. Forrest, H. Kawaji, The FANTOM Consortium P43 Rapid and scalable typing of structural variants for disease cohorts W. Salerno, A. English, S. N. Shekar, A. Mangubat, J. Bruestle, E. Boerwinkle, R. A. Gibbs P44 Polymorphism of glutathione S-transferases and sulphotransferases genes in an Arab population A. H. Salem, M. Ali, A. Ibrahim, M. Ibrahim P46 Genetic divergence of CYP3A5*3 pharmacogenomic marker for native and admixed Mexican populations J. C. Fernandez-Lopez, V. Bonifaz-Peña, C. Rangel-Escareño, A. Hidalgo-Miranda, A. V. Contreras P47 Whole exome sequence meta-analysis of 13 white blood cell, red blood cell, and platelet traits L. Polfus, CHARGE and NHLBI Exome Sequence Project Working Groups P48 Association of adipoq gene with type 2 diabetes and related phenotypes in african american men and women: The jackson heart study S. Davis, R. Xu, S. Gebeab, P Riestra, A Gaye, R. Khan, J. Wilson, A. Bidulescu P49 Common variants in casr gene are associated with serum calcium levels in koreans S. H. Jung, N. Vinayagamoorthy, S. H. Yim, Y. J. Chung P50 Inference of multiple-wave population admixture by modeling decay of linkage disequilibrium with multiple exponential functions Y. Zhou, S. Xu P51 A Bayesian framework for generalized linear mixed models in genome-wide association studies X. Wang, V. Philip, G. Carter P52 Targeted sequencing approach for the identification of the genetic causes of hereditary hearing impairment A. A. Abuzenadah, M. Gari, R. Turki, A. Dallol P53 Identification of enhancer sequences by ATAC-seq open chromatin profiling A. Uyar, A. Kaygun, S. Zaman, E. Marquez, J. George, D. Ucar P54 Direct enrichment for the rapid preparation of targeted NGS libraries C. L. Hendrickson, A. Emerman, D. Kraushaar, S. Bowman, N. Henig, T. Davis, S. Russello, K. Patel P56 Performance of the Agilent D5000 and High Sensitivity D5000 ScreenTape assays for the Agilent 4200 Tapestation System R. Nitsche, L. Prieto-Lafuente P57 ClinVar: a multi-source archive for variant interpretation M. Landrum, J. Lee, W. Rubinstein, D. Maglott P59 Association of functional variants and protein physical interactions of human MUTY homolog linked with familial adenomatous polyposis and colorectal cancer syndrome Z. Abduljaleel, W. Khan, F. A. Al-Allaf, M. Athar , M. M. Taher, N. Shahzad P60 Modification of the microbiom constitution in the gut using chicken IgY antibodies resulted in a reduction of acute graft-versus-host disease after experimental bone marrow transplantation A. Bouazzaoui, E. Huber, A. Dan, F. A. Al-Allaf, W. Herr, G. Sprotte, J. Köstler, A. Hiergeist, A. Gessner, R. Andreesen, E. Holler P61 Compound heterozygous mutation in the LDLR gene in Saudi patients suffering severe hypercholesterolemia F. Al-Allaf, A. Alashwal, Z. Abduljaleel, M. Taher, A. Bouazzaoui, H. Abalkhail, A. Al-Allaf, R. Bamardadh, M. Athar

The management of pregnancy and delivery in 3-hydroxy-3-methylglutaryl-CoA lyase deficiency

3-hydroxy-3-methylglutaric (HMG)-CoA lyase is required for ketogenesis and leucine degradation. Patients with HMG-CoA lyase deficiency typically present with hypoketotic hypoglycemia and metabolic acidosis, which can be fatal if untreated. The patient is a 28-year-old female with HMG-CoA lyase deficiency who presented at 4 weeks gestation for prenatal care. Protein intake as well as carnitine supplementation were gradually increased to support maternal and fetal demands up to 65 g per day for protein and 80 mg/kg/day for carnitine. Fetal growth was appropriate. At 36 5/7 weeks, she presented with spontaneous rupture of membranes. Twice maintenance 10% glucose-containing intravenous fluids were initiated. During labor, vomiting and metabolic acidosis developed. Delivery was by cesarean. Preeclampsia developed postpartum. The patient recovered well and was discharged home on postpartum day 5. Stress of pregnancy and labor and delivery can lead to metabolic decompensation in HMG-CoA lyase deficiency. Patients should be monitored closely by a biochemical geneticist, dietitian, and high-risk obstetrician at a tertiary care center during their pregnancy. Fasting should be avoided. Intravenous 10% glucose-containing fluids should be provided to prevent catabolism and metabolic decompensation during labor and delivery. © 2016 Wiley Periodicals, Inc.

EPG5-related Vici syndrome: a paradigm of neurodevelopmental disorders with defective autophagy

Vici syndrome is a progressive neurodevelopmental multisystem disorder due to recessive mutations in the key autophagy gene EPG5. We report genetic, clinical, neuroradiological, and neuropathological features of 50 children from 30 families, as well as the neuronal phenotype of EPG5 knock-down in Drosophila melanogaster. We identified 39 different EPG5 mutations, most of them truncating and predicted to result in reduced EPG5 protein. Most mutations were private, but three recurrent mutations (p.Met2242Cysfs*5, p.Arg417*, and p.Gln336Arg) indicated possible founder effects. Presentation was mainly neonatal, with marked hypotonia and feeding difficulties. In addition to the five principal features (callosal agenesis, cataracts, hypopigmentation, cardiomyopathy, and immune dysfunction), we identified three equally consistent features (profound developmental delay, progressive microcephaly, and failure to thrive). The manifestation of all eight of these features has a specificity of 97%, and a sensitivity of 89% for the presence of an EPG5 mutation and will allow informed decisions about genetic testing. Clinical progression was relentless and many children died in infancy. Survival analysis demonstrated a median survival time of 24 months (95% confidence interval 0-49 months), with only a 10th of patients surviving to 5 years of age. Survival outcomes were significantly better in patients with compound heterozygous mutations (P = 0.046), as well as in patients with the recurrent p.Gln336Arg mutation. Acquired microcephaly and regression of skills in long-term survivors suggests a neurodegenerative component superimposed on the principal neurodevelopmental defect. Two-thirds of patients had a severe seizure disorder, placing EPG5 within the rapidly expanding group of genes associated with early-onset epileptic encephalopathies. Consistent neuroradiological features comprised structural abnormalities, in particular callosal agenesis and pontine hypoplasia, delayed myelination and, less frequently, thalamic signal intensity changes evolving over time. Typical muscle biopsy features included fibre size variability, central/internal nuclei, abnormal glycogen storage, presence of autophagic vacuoles and secondary mitochondrial abnormalities. Nerve biopsy performed in one case revealed subtotal absence of myelinated axons. Post-mortem examinations in three patients confirmed neurodevelopmental and neurodegenerative features and multisystem involvement. Finally, downregulation of epg5 (CG14299) in Drosophila resulted in autophagic abnormalities and progressive neurodegeneration. We conclude that EPG5-related Vici syndrome defines a novel group of neurodevelopmental disorders that should be considered in patients with suggestive features in whom mitochondrial, glycogen, or lysosomal storage disorders have been excluded. Neurological progression over time indicates an intriguing link between neurodevelopment and neurodegeneration, also supported by neurodegenerative features in epg5-deficient Drosophila, and recent implication of other autophagy regulators in late-onset neurodegenerative disease.

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.

Genotype-phenotype correlation of congenital anomalies in multiple congenital anomalies hypotonia seizures syndrome (MCAHS1)/PIGN-related epilepsy

Mutations in PIGN, resulting in multiple congenital anomalies-hypotonia-seizures syndrome, a glycosylphosphatidylinositol anchor deficiency, have been published in four families to date. We report four patients from three unrelated families with epilepsy and hypotonia in whom whole exome sequencing yielded compound heterozygous variants in PIGN. As with previous reports Patients 1 and 2 (full siblings) have severe global developmental delay, gastroesophageal reflux disease, and minor dysmorphic features, including high palate, bitemporal narrowing, depressed nasal bridge, and micrognathia; Patient 3 had early global developmental delay with later progressive spastic quadriparesis, intellectual disability, and intractable generalized epilepsy; Patient 4 had bilateral narrowing as well but differed by the presence of hypertelorism, markedly narrow palpebral fissures, and long philtrum, had small distal phalanges of fingers 2, 3, and 4, absent distal phalanx of finger 5 and similar toe anomalies, underdeveloped nails, unusual brain anomalies, and a more severe early clinical course. These patients expand the known clinical spectrum of the disease. The severity of the presentations in conjunction with the patients' mutations suggest a genotype-phenotype correlation in which congenital anomalies are only seen in patients with biallelic loss-of-function. In addition, PIGN mutations appear to be panethnic and may be an underappreciated cause of epilepsy.

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.