ClinGen's GenomeConnect registry enables patient-centered data sharing

ClinGen variant curation expert panel recommendations for classification of variants in GAMT, GATM and SLC6A8 for cerebral creatine deficiency syndromes

Cerebral creatine deficiency syndromes (CCDS) are inherited metabolic phenotypes of creatine synthesis and transport. There are two enzyme deficiencies, guanidinoacetate methyltransferase (GAMT), encoded by GAMT and arginine-glycine amidinotransferase (AGAT), encoded by GATM, which are involved in the synthesis of creatine. After synthesis, creatine is taken up by a sodium-dependent membrane bound creatine transporter (CRTR), encoded by SLC6A8, into all organs. Creatine uptake is very important especially in high energy demanding organs such as the brain, and muscle. To classify the pathogenicity of variants in GAMT, GATM, and SLC6A8, we developed the CCDS Variant Curation Expert Panel (VCEP) in 2018, supported by The Clinical Genome Resource (ClinGen), a National Institutes of Health (NIH)-funded resource. We developed disease-specific variant classification guidelines for GAMT-, GATM-, and SLC6A8-related CCDS, adapted from the American College of Medical Genetics/Association of Molecular Pathology (ACMG/AMP) variant interpretation guidelines. We applied specific variant classification guidelines to 30 pilot variants in each of the three genes that have variants associated with CCDS. Our CCDS VCEP was approved by the ClinGen Sequence Variant Interpretation Working Group (SVI WG) and Clinical Domain Oversight Committee in July 2022. We curated 181 variants including 72 variants in GAMT, 45 variants in GATM, and 64 variants in SLC6A8 and submitted these classifications to ClinVar, a public variant database supported by the National Center for Biotechnology Information. Missense variants were the most common variant type in all three genes. We submitted 32 new variants and reclassified 34 variants with conflicting interpretations. We report specific phenotype (PP4) using a points system based on the urine and plasma guanidinoacetate and creatine levels, brain magnetic resonance spectroscopy (MRS) creatine level, and enzyme activity or creatine uptake in fibroblasts ranging from PP4, PP4_Moderate and PP4_Strong. Our CCDS VCEP is one of the first panels applying disease specific variant classification algorithms for an X-linked disease. The availability of these guidelines and classifications can guide molecular genetics and genomic laboratories and health care providers to assess the molecular diagnosis of individuals with a CCDS phenotype.

The Brain Gene Registry: a data snapshot

Monogenic disorders account for a large proportion of population-attributable risk for neurodevelopmental disabilities. However, the data necessary to infer a causal relationship between a given genetic variant and a particular neurodevelopmental disorder is often lacking. Recognizing this scientific roadblock, 13 Intellectual and Developmental Disabilities Research Centers (IDDRCs) formed a consortium to create the Brain Gene Registry (BGR), a repository pairing clinical genetic data with phenotypic data from participants with variants in putative brain genes. Phenotypic profiles are assembled from the electronic health record (EHR) and a battery of remotely administered standardized assessments collectively referred to as the Rapid Neurobehavioral Assessment Protocol (RNAP), which include cognitive, neurologic, and neuropsychiatric assessments, as well as assessments for attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). Co-enrollment of BGR participants in the Clinical Genome Resource's (ClinGen's) GenomeConnect enables display of variant information in ClinVar. The BGR currently contains data on 479 participants who are 55% male, 6% Asian, 6% Black or African American, 76% white, and 12% Hispanic/Latine. Over 200 genes are represented in the BGR, with 12 or more participants harboring variants in each of these genes: CACNA1A, DNMT3A, SLC6A1, SETD5, and MYT1L. More than 30% of variants are de novo and 43% are classified as variants of uncertain significance (VUSs). Mean standard scores on cognitive or developmental screens are below average for the BGR cohort. EHR data reveal developmental delay as the earliest and most common diagnosis in this sample, followed by speech and language disorders, ASD, and ADHD. BGR data has already been used to accelerate gene-disease validity curation of 36 genes evaluated by ClinGen's BGR Intellectual Disability (ID)-Autism (ASD) Gene Curation Expert Panel. In summary, the BGR is a resource for use by stakeholders interested in advancing translational research for brain genes and continues to recruit participants with clinically reported variants to establish a rich and well-characterized national resource to promote research on neurodevelopmental disorders.

Improving prenatal diagnosis through standards and aggregation

Advances in sequencing and imaging technologies enable enhanced assessment in the prenatal space, with a goal to diagnose and predict the natural history of disease, to direct targeted therapies, and to implement clinical management, including transfer of care, election of supportive care, and selection of surgical interventions. The current lack of standardization and aggregation stymies variant interpretation and gene discovery, which hinders the provision of prenatal precision medicine, leaving clinicians and patients without an accurate diagnosis. With large amounts of data generated, it is imperative to establish standards for data collection, processing, and aggregation. Aggregated and homogeneously processed genetic and phenotypic data permits dissection of the genomic architecture of prenatal presentations of disease and provides a dataset on which data analysis algorithms can be tuned to the prenatal space. Here we discuss the importance of generating aggregate data sets and how the prenatal space is driving the development of interoperable standards and phenotype-driven tools.

Expansion of the Genotypic and Phenotypic Spectrum of ASH1L-Related Syndromic Neurodevelopmental Disorder

Pathogenic ASH1L variants have been reported in probands with broad phenotypic presentations, including intellectual disability, autism spectrum disorder, attention deficit hyperactivity disorder, seizures, congenital anomalies, and other skeletal, muscular, and sleep differences. Here, we review previously published individuals with pathogenic ASH1L variants and report three further probands with novel ASH1L variants and previously unreported phenotypic features, including mixed receptive language disorder and gait disturbances. These novel data from the Brain Gene Registry, an accessible repository of clinically derived genotypic and phenotypic data, have allowed for the expansion of the phenotypic and genotypic spectrum of this condition.

Clinical variants paired with phenotype: A rich resource for brain gene curation

PURPOSE

Clinically ascertained variants are under-utilized in neurodevelopmental disorder research. We established the Brain Gene Registry (BGR) to coregister clinically identified variants in putative brain genes with participant phenotypes. Here, we report 179 genetic variants in the first 179 BGR registrants and analyze the proportion that were novel to ClinVar at the time of entry and those that were absent in other disease databases.

METHODS

From 10 academically affiliated institutions, 179 individuals with 179 variants were enrolled into the BGR. Variants were cross-referenced for previous presence in ClinVar and for presence in 6 other genetic databases.

RESULTS

Of 179 variants in 76 genes, 76 (42.5%) were novel to ClinVar, and 62 (34.6%) were absent from all databases analyzed. Of the 103 variants present in ClinVar, 37 (35.9%) were uncertain (ClinVar aggregate classification of variant of uncertain significance or conflicting classifications). For 5 variants, the aggregate ClinVar classification was inconsistent with the interpretation from the BGR site-provided classification.

CONCLUSION

A significant proportion of clinical variants that are novel or uncertain are not shared, limiting the evidence base for new gene-disease relationships. Registration of paired clinical genetic test results with phenotype has the potential to advance knowledge of the relationships between genes and neurodevelopmental disorders.

Slice Testing-Considerations from Ordering to Reporting: A Joint Report of the Association for Molecular Pathology, College of American Pathologists, and National Society of Genetic Counselors

As the number of genes associated with various germline disorders continues to grow, it is becoming more difficult for clinical laboratories to maintain separate assays for interrogating disease-focused gene panels. One solution to this challenge is termed slice testing, where capture backbone is used to analyze data specific to a set of genes, and for this article, we will focus on exome. A key advantage to this strategy is greater flexibility by adding genes as they become associated with disease or the ability to accommodate specific provider requests. Here, we provide expert consensus recommendations and results from an Association for Molecular Pathology-sponsored survey of clinical laboratories performing exome sequencing to compare a slice testing approach with traditional static gene panels and comprehensive exome analysis. We explore specific considerations for slices, including gene selection, analytic performance, coverage, quality, and interpretation. Our goal is to provide comprehensive guidance for clinical laboratories interested in designing and using slice tests as a diagnostic.

Should secondary pharmacogenomic variants be actively screened and reported when diagnostic genome-wide sequencing is performed in a child?

This white paper was prepared by the Global Alliance for Genomics and Health Regulatory and Ethics Work Stream's Pediatric Task Team to review and provide perspective with respect to ethical, legal, and social issues regarding the return of secondary pharmacogenomic variants in children who have a serious disease or developmental disorder and are undergoing exome or genome sequencing to identify a genetic cause of their condition. We discuss actively searching for and reporting pharmacogenetic/genomic variants in pediatric patients, different methods of returning secondary pharmacogenomic findings to the patient/parents and/or treating clinicians, maintaining these data in the patient's health record over time, decision supports to assist using pharmacogenetic results in future treatment decisions, and sharing information in public databases to improve the clinical interpretation of pharmacogenetic variants identified in other children. We conclude by presenting a series of points to consider for clinicians and policymakers regarding whether, and under what circumstances, routine screening and return of pharmacogenomic variants unrelated to the indications for testing is appropriate in children who are undergoing genome-wide sequencing to assist in the diagnosis of a suspected genetic disease.

Multidisciplinary molecular consultation increases the diagnosis of pediatric epileptic encephalopathy and neurodevelopmental disorders

BACKGROUND

Epilepsy (EP) is a common neurological disease in which 70-80% are thought to have a genetic cause. In patients with epilepsy, neurodevelopmental delay (NDD) was prevalent. Next generation of sequencing has been widely used in diagnosing EP/NDD. However, the diagnostic yield remains to be 40%-50%. Many reanalysis pipelines and software have been developed for automated reanalysis and decision making for the diseases. Nevertheless, it is a highly challenging task for smaller genetic centers or a routine pediatric practice. To address the clinical and genetic "diagnostic odyssey," we organized a Multidisciplinary Molecular Consultation (MMC) team for molecular consultation for 202 children with EP/NDD patients referred by lower level hospitals.

METHODS

All the patients had undergone an aligned and sequential consultations and discussions by a "triple reanalysis" procedure by clinical, genetic specialists, and researchers.

RESULTS

Among the 202 cases for MMC, we totally identified 47 cases (23%) harboring causative variants in 24 genes and 15 chromosomal regions after the MMC. In the 15 cases with positive CNVs, 3 cases harbor the deletions or duplications in 16p11.2, and 2 cases for 1p36. The bioinformatical reanalysis revealed 47 positive cases, in which 12 (26%) were reported to be negative, VUS or incorrectly positive in pre-MMC reports. Additionally, among 87 cases with negative cases, 4 (5%) were reported to be positive in pre-MMC reports.

CONCLUSION

We established a workflow allowing for a "one-stop" collaborative assessments by experts of multiple fields and helps for correct the diagnosis of cases with falsenegative and -positive and VUS genetic reports and may have significant influences for intervention, prevention and genetic counseling of pediatric epilepsy and neurodevelopmental disorders.

Protein domains provide a new layer of information for classifying human variations in rare diseases

Introduction: Using the ACMG-AMP guidelines for the interpretation of sequence variants, it remains difficult to meet the criterion associated with the protein domain, PM1, which is assigned in only about 10% of cases, whereas the criteria related to variant frequency, PM2/BA1/BS1, is reported in 50% of cases. To improve the classification of human missense variants using protein domains information, we developed the DOLPHIN system (https://dolphin.mmg-gbit.eu). Methods: We used Pfam alignments of eukaryotes to define DOLPHIN scores to identify protein domain residues and variants that have a significant impact. In parallel, we enriched gnomAD variants frequencies for each domains' residue. These were validated using ClinVar data. Results: We applied this method to all potential human transcripts' variants, resulting in 30.0% being assigned a PM1 label, whereas 33.2% were eligible for a new benign support criterion, BP8. We also showed that DOLPHIN provides an extrapolated frequency for 31.8% of the variants, compared to the original frequency available in gnomAD for 7.6% of them. Discussion: Overall, DOLPHIN allows a simplified use of the PM1 criterion, an expanded application of the PM2/BS1 criteria and the creation of a new BP8 criterion. DOLPHIN could facilitate the classification of amino acid substitutions in protein domains that cover nearly 40% of proteins and represent the sites of most pathogenic variants.

Non-Invasive Biomarkers for Early Lung Cancer Detection

Worldwide, lung cancer (LC) is the most common cause of cancer death, and any delay in the detection of new and relapsed disease serves as a major factor for a significant proportion of LC morbidity and mortality. Though invasive methods such as tissue biopsy are considered the gold standard for diagnosis and disease monitoring, they have several limitations. Therefore, there is an urgent need to identify and validate non-invasive biomarkers for the early diagnosis, prognosis, and treatment of lung cancer for improved patient management. Despite recent progress in the identification of non-invasive biomarkers, currently, there is a shortage of reliable and accessible biomarkers demonstrating high sensitivity and specificity for LC detection. In this review, we aim to cover the latest developments in the field, including the utility of biomarkers that are currently used in LC screening and diagnosis. We comment on their limitations and summarise the findings and developmental stages of potential molecular contenders such as microRNAs, circulating tumour DNA, and methylation markers. Furthermore, we summarise research challenges in the development of biomarkers used for screening purposes and the potential clinical applications of newly discovered biomarkers.

Clinical validity assessment of genes frequently tested on intellectual disability/autism sequencing panels

PURPOSE

Neurodevelopmental disorders (NDDs), such as intellectual disability (ID) and autism spectrum disorder (ASD), exhibit genetic and phenotypic heterogeneity, making them difficult to differentiate without a molecular diagnosis. The Clinical Genome Resource Intellectual Disability/Autism Gene Curation Expert Panel (GCEP) uses systematic curation to distinguish ID/ASD genes that are appropriate for clinical testing (ie, with substantial evidence supporting their relationship to disease) from those that are not.

METHODS

Using the Clinical Genome Resource gene-disease validity curation framework, the ID/Autism GCEP classified genes frequently included on clinical ID/ASD testing panels as Definitive, Strong, Moderate, Limited, Disputed, Refuted, or No Known Disease Relationship.

RESULTS

As of September 2021, 156 gene-disease pairs have been evaluated. Although most (75%) were determined to have definitive roles in NDDs, 22 (14%) genes evaluated had either Limited or Disputed evidence. Such genes are currently not recommended for use in clinical testing owing to the limited ability to assess the effect of identified variants.

CONCLUSION

Our understanding of gene-disease relationships evolves over time; new relationships are discovered and previously-held conclusions may be questioned. Without periodic re-examination, inaccurate gene-disease claims may be perpetuated. The ID/Autism GCEP will continue to evaluate these claims to improve diagnosis and clinical care for NDDs.

De novo variants of CSNK2B cause a new intellectual disability-craniodigital syndrome by disrupting the canonical Wnt signaling pathway

CSNK2B encodes for casein kinase II subunit beta (CK2β), the regulatory subunit of casein kinase II (CK2), which is known to mediate diverse cellular pathways. Variants in this gene have been recently identified as a cause of Poirier-Bienvenu neurodevelopmental syndrome (POBINDS), but functional evidence is sparse. Here, we report five unrelated individuals: two of them manifesting POBINDS, while three are identified to segregate a new intellectual disability-craniodigital syndrome (IDCS), distinct from POBINDS. The three IDCS individuals carried two different de novo missense variants affecting the same codon of CSNK2B. Both variants, NP_001311.3; p.Asp32His and NP_001311.3; p.Asp32Asn, lead to an upregulation of CSNK2B expression at transcript and protein level, along with global dysregulation of canonical Wnt signaling. We found impaired interaction of the two key players DVL3 and β-catenin with mutated CK2β. The variants compromise the kinase activity of CK2 as evident by a marked reduction of phosphorylated β-catenin and consequent absence of active β-catenin inside nuclei of the patient-derived lymphoblastoid cell lines (LCLs). In line with these findings, whole-transcriptome profiling of patient-derived LCLs harboring the NP_001311.3; p.Asp32His variant confirmed a marked difference in expression of genes involved in the Wnt signaling pathway. In addition, whole-phosphoproteome analysis of the LCLs of the same subject showed absence of phosphorylation for 313 putative CK2 substrates, enriched in the regulation of nuclear β-catenin and transcription of the target genes. Our findings suggest that discrete variants in CSNK2B cause dominant-negative perturbation of the canonical Wnt signaling pathway, leading to a new craniodigital syndrome distinguishable from POBINDS.

Establishing the Medical Actionability of Genomic Variants

Actionability is an important concept in medicine that does not have a well-accepted standard definition, nor is there a general consensus on how to establish it. Medical actionability is often conflated with clinical utility, a related but distinct concept. This lack of clarity contributes to practice variation and inconsistent coverage decisions in genomic medicine, leading to the potential for systematic bias in the use of evidence-based interventions. We clarify how medical actionability and clinical utility are distinct and then discuss the spectrum of actionability, including benefits for the person, the family, and society. We also describe applications across the life course, including prediction, diagnosis, and treatment. Current challenges in assessing the medical actionability of identified genomic variants include gaps in the evidence, limited contexts with practice guidelines, and subjective aspects of medical actionability. A standardized and authoritative assessment of medical actionability is critical to implementing genomic medicine in a fashion that improves population health outcomes and reduces health disparities. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Epilepsy and related challenges in children with COL4A1 and COL4A2 mutations: A Gould syndrome patient registry

Recently, patient advocacy groups started using the name Gould syndrome to describe clinical features of COL4A1 and COL4A2 mutations. Gould syndrome is increasingly identified in genetic screening panels, and because it is a rare disease, there is a disproportionate burden on families to understand the disease and chart the course for clinical care. Among the chief concerns for caregivers of children with Gould syndrome are the challenges faced because of epilepsy, including severe manifestations such as infantile spasms. To document the concerns of the patient population, the Gould Syndrome Foundation established the Gould Syndrome Global Registry (GSGR).

METHODS

The Gould Syndrome Foundation developed questions for the GSGR with iterative input from patients and caregivers. An institutional review board issued an exemption determination before data collection began. Participants were recruited through social media and clinician referrals. All participants consented electronically, and the data were collected and managed using REDCap electronic data capture tools. De-identified data representing responses received between October 2019 and February 2021 were exported and analyzed with IBM SPSS 27 using descriptive statistics (mean, standard deviation, frequency, range, and percent).

RESULTS

Seventy families from twelve countries provided data for the registry, representing 100 affected people (40 adults and 60 children). This analysis represents a subanalysis of the 35 out of 60 children <=18 years of age who reported a history of seizures. Nearly half of these participants were diagnosed with infantile spasms. Participants with epilepsy frequently reported developmental delays (88.6%), stroke (60.0%), cerebral palsy (65.7%), and constipation (57.1%). Ten (28.6%) children use a feeding tube. Despite the fact that more than half of respondents reported stroke, only 34.3% reported ever receiving education on stroke recognition.

CONCLUSION

Here we describe the development and deployment of the first global registry for individuals and family members with Gould syndrome, caused by mutations in COL4A1 and COL4A2. It is important for pediatric neurologists to have access to resources to provide families upon diagnosis. Specifically, all families with Gould Syndrome must have access to infantile spasms awareness and stroke education materials. The Gould Syndrome Foundation is planning several improvements to this patient registry which will encourage collaboration and innovation for the benefit of people living with Gould syndrome.

Diffusion enables integration of heterogeneous data and user-driven learning in a desktop knowledge-base

Integrating reference datasets (e.g. from high-throughput experiments) with unstructured and manually-assembled information (e.g. notes or comments from individual researchers) has the potential to tailor bioinformatic analyses to specific needs and to lead to new insights. However, developing bespoke analysis pipelines from scratch is time-consuming, and general tools for exploring such heterogeneous data are not available. We argue that by treating all data as text, a knowledge-base can accommodate a range of bioinformatic data types and applications. We show that a database coupled to nearest-neighbor algorithms can address common tasks such as gene-set analysis as well as specific tasks such as ontology translation. We further show that a mathematical transformation motivated by diffusion can be effective for exploration across heterogeneous datasets. Diffusion enables the knowledge-base to begin with a sparse query, impute more features, and find matches that would otherwise remain hidden. This can be used, for example, to map multi-modal queries consisting of gene symbols and phenotypes to descriptions of diseases. Diffusion also enables user-driven learning: when the knowledge-base cannot provide satisfactory search results in the first instance, users can improve the results in real-time by adding domain-specific knowledge. User-driven learning has implications for data management, integration, and curation.

Recontacting registry participants with genetic updates through GenomeConnect, the ClinGen patient registry

PURPOSE

Variant classifications and gene-disease relationships may evolve. Professional societies have suggested patients share the responsibility to remain up-to-date on the implications genetic results have on their health, and that novel methods of recontact are needed. GenomeConnect, the ClinGen patient registry, has implemented a process to provide variant classification and gene-disease relationship updates to participants. Here, we report on our experience with this recontacting process.

METHODS

GenomeConnect shares data with ClinVar and Matchmaker Exchange enabling the identification of updates to variant classifications and gene-disease relationships. For any updates identified, the reporting laboratory is contacted, and updates are shared with participants opting to receive them.

RESULTS

Of 1,419 variants shared with ClinVar by GenomeConnect, 49 (3.4%) variant reclassifications were identified and 34 were shared with participants. Of 97 candidate genes submitted to Matchmaker Exchange, 10 (10.3%) gene-disease relationships have been confirmed and 9 were shared with participants. Details available from a subset of participants highlight that updated information is not always shared with the patient by testing laboratories.

CONCLUSION

Patient registries can provide a mechanism for patients and their providers to remain informed about changes to the interpretation and clinical significance of their genetic results, leading to important implications for care.

Rare disease patient matchmaking: development and outcomes of an internet case-finding strategy in the Undiagnosed Diseases Network

BACKGROUND

Although clinician, researcher, and patient resources for matchmaking exist, finding similar patients remains an obstacle for rare disease diagnosis. The goals of this study were to develop and test the effectiveness of an Internet case-finding strategy and identify factors associated with increased matching within a rare disease population.

METHODS

Public web pages were created for consented participants. Matches made, time to each inquiry and match, and outcomes were recorded and analyzed using descriptive statistics. A Poisson regression model was run to identify characteristics associated with matches.

RESULTS

385 participants were referred to the project and 158 had pages posted. 579 inquiries were received; 89.0% were from the general public and 24.7% resulted in a match. 81.6% of pages received at least one inquiry and 15.0% had at least one patient match. Primary symptom category of neurology, diagnosis, gene page, and photo were associated with increased matches (p ≤ 0.05).

CONCLUSIONS

This Internet case-finding strategy was of interest to patients, families, and clinicians, and similar patients were identified using this approach. Extending matchmaking efforts to the general public resulted in matches and suggests including this population in matchmaking activities can improve identification of similar patients.

Underrepresentation of Phenotypic Variability of 16p13.11 Microduplication Syndrome Assessed With an Online Self-Phenotyping Tool (Phenotypr): Cohort Study

Background

16p13.11 microduplication syndrome has a variable presentation and is characterized primarily by neurodevelopmental and physical phenotypes resulting from copy number variation at chromosome 16p13.11. Given its variability, there may be features that have not yet been reported. The goal of this study was to use a patient “self-phenotyping” survey to collect data directly from patients to further characterize the phenotypes of 16p13.11 microduplication syndrome.

Objective

This study aimed to (1) discover self-identified phenotypes in 16p13.11 microduplication syndrome that have been underrepresented in the scientific literature and (2) demonstrate that self-phenotyping tools are valuable sources of data for the medical and scientific communities.

Methods

As part of a large study to compare and evaluate patient self-phenotyping surveys, an online survey tool, Phenotypr, was developed for patients with rare disorders to self-report phenotypes. Participants with 16p13.11 microduplication syndrome were recruited through the Boston Children's Hospital 16p13.11 Registry. Either the caregiver, parent, or legal guardian of an affected child or the affected person (if aged 18 years or above) completed the survey. Results were securely transferred to a Research Electronic Data Capture database and aggregated for analysis.

Results

A total of 19 participants enrolled in the study. Notably, among the 19 participants, aggression and anxiety were mentioned by 3 (16%) and 4 (21%) participants, respectively, which is an increase over the numbers in previously published literature. Additionally, among the 19 participants, 3 (16%) had asthma and 2 (11%) had other immunological disorders, both of which have not been previously described in the syndrome.

Conclusions

Several phenotypes might be underrepresented in the previous 16p13.11 microduplication literature, and new possible phenotypes have been identified. Whenever possible, patients should continue to be referenced as a source of complete phenotyping data on their condition. Self-phenotyping may lead to a better understanding of the prevalence of phenotypes in genetic disorders and may identify previously unreported phenotypes.

Strategic vision for improving human health at The Forefront of Genomics

Starting with the launch of the Human Genome Project three decades ago, and continuing after its completion in 2003, genomics has progressively come to have a central and catalytic role in basic and translational research. In addition, studies increasingly demonstrate how genomic information can be effectively used in clinical care. In the future, the anticipated advances in technology development, biological insights, and clinical applications (among others) will lead to more widespread integration of genomics into almost all areas of biomedical research, the adoption of genomics into mainstream medical and public-health practices, and an increasing relevance of genomics for everyday life. On behalf of the research community, the National Human Genome Research Institute recently completed a multi-year process of strategic engagement to identify future research priorities and opportunities in human genomics, with an emphasis on health applications. Here we describe the highest-priority elements envisioned for the cutting-edge of human genomics going forward-that is, at 'The Forefront of Genomics'.

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.

Phenotypic and mutational spectrum of 21 Chinese patients with Alström syndrome

Alström syndrome (AS) is a monogenic syndromic ciliopathy caused by mutations in the ALMS1 (Alström Syndrome 1) gene. A total of 21 subjects with AS from 20 unrelated Chinese families were recruited. Our cohort consists of 9 females and 12 males, between 5 months and 20 years old. The first symptom(s) appeared between 3 and 24 months. They were recorded to be either visual impairments (83%) or dilated cardiomyopathy (17%). Median time from symptom onset to seeking medical attention was 6 months (3-36 months) and the median time needed to reach the final molecular diagnosis is 54 months (6-240 months). System involvement at the time of the survey was as follows: visual symptoms (100%), hearing Impairment (67%), endocrine symptoms (43%), neurological symptoms (19%), hepatic symptoms (14%), and renal Involvement (14%). These findings are comparable to data reported in the literature. However, the proportion of subjects with cognitive impairment (33%) and behavioral problems (19%) were higher. Thirty-three unique mutations were identified in the ALMS1 gene, of which 18 are novel mutations classified as pathogenic/likely pathogenic according to the American College of Medical Genetics (ACMG) guideline. Four recurrent mutations were identified in the cohort, in particular; c.2084C>A, p. (Ser695Ter), is suggestive to be a founder mutation in people of Chinese ancestry. The participation of AS subjects of differing ethnicities is essential to improve the algorithm in facial recognition/phenotyping, as well as to understand the mutation spectrum beyond than just those of European ancestry.

Representing glycophenotypes: semantic unification of glycobiology resources for disease discovery

While abnormalities related to carbohydrates (glycans) are frequent for patients with rare and undiagnosed diseases as well as in many common diseases, these glycan-related phenotypes (glycophenotypes) are not well represented in knowledge bases (KBs). If glycan-related diseases were more robustly represented and curated with glycophenotypes, these could be used for molecular phenotyping to help to realize the goals of precision medicine. Diagnosis of rare diseases by computational cross-species comparison of genotype-phenotype data has been facilitated by leveraging ontological representations of clinical phenotypes, using Human Phenotype Ontology (HPO), and model organism ontologies such as Mammalian Phenotype Ontology (MP) in the context of the Monarch Initiative. In this article, we discuss the importance and complexity of glycobiology and review the structure of glycan-related content from existing KBs and biological ontologies. We show how semantically structuring knowledge about the annotation of glycophenotypes could enhance disease diagnosis, and propose a solution to integrate glycophenotypes and related diseases into the Unified Phenotype Ontology (uPheno), HPO, Monarch and other KBs. We encourage the community to practice good identifier hygiene for glycans in support of semantic analysis, and clinicians to add glycomics to their diagnostic analyses of rare diseases.