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Phenotypic features of a hereditary connective tissue disorder, including craniofacial characteristics, hyperextensible skin, joint laxity, kyphoscoliosis, arachnodactyly, inguinal hernia, and diverticulosis associated with biallelic pathogenic variants in EFEMP1 have been previously described in four patients. Genome sequencing on a proband and her mother with comparable phenotypic features revealed that both patients were heterozygous for a stop‐gain variant c.1084C>T (p.Arg362*). Complementary RNA‐seq on fibroblasts revealed significantly reduced levels of mutant EFEMP1 transcript. Considering the absence of other molecular explanations, we extrapolated that EFEMP1 could be the cause of the patient's phenotypes. Furthermore, nonsense‐mediated decay was demonstrated for the mutant allele as the principal mechanism for decreased levels of EFEMP1 mRNA. We provide strong clinical and genetic evidence for the haploinsufficiency of EFEMP1 due to nonsense‐medicated decay to cause severe kyphoscoliosis, generalized hypermobility of joints, high and narrow arched palate, and potentially severe diverticulosis. To the best of our knowledge, this is the first report of an autosomal dominant EFEMP1‐associated hereditary connective tissue disorder and therefore expands the phenotypic spectrum of EFEMP1 related disorders. [ABSTRACT FROM AUTHOR]

Recurrent de novo missense variants in H4 histone genes have recently been associated with a novel neurodevelopmental syndrome that is characterized by intellectual disability and developmental delay as well as more variable findings that include short stature, microcephaly, and facial dysmorphisms. A 4‐year‐old male with autism, developmental delay, microcephaly, and a happy demeanor underwent evaluation through the Undiagnosed Disease Network. He was clinically suspected to have Angelman syndrome; however, molecular testing was negative. Genome sequencing identified the H4 histone gene variant H4C5 NM_003545.4: c.295T>C, p.Tyr99His, which parental testing confirmed to be de novo. The variant met criteria for a likely pathogenic classification and is one of the seven known disease‐causing missense variants in H4C5. A comparison of our proband's findings to the initial description of the H4‐associated neurodevelopmental syndrome demonstrates that his phenotype closely matches the spectrum of those reported among the 29 affected individuals. As such, this report corroborates the delineation of neurodevelopmental syndrome caused by de novo missense H4 gene variants. Moreover, it suggests that cases of clinically suspected Angelman syndrome without molecular confirmation should undergo exome or genome sequencing, as novel neurodevelopmental syndromes with phenotypes overlapping with Angelman continue to be discovered. [ABSTRACT FROM AUTHOR]

Genetic counselors (GCs) are increasingly filling important positions on research study teams, but there is limited literature describing the roles of GCs in these settings. GCs on the Undiagnosed Diseases Network (UDN) study team serve in a variety of roles across the research network and provide an opportunity to better understand genetic counselor roles in research. To quantitatively characterize the tasks regularly performed and professional fulfillment derived from these tasks, two surveys were administered to UDN GCs in a stepwise fashion. Responses from the first, free‐response survey elicited the scope of tasks which informed development of a second structured, multiple‐select survey. In survey 2, respondents were asked to select which roles they performed. Across 19 respondents, roles in survey 2 received a total of 947 selections averaging approximately 10 selections per role. When asked to indicate what roles they performed, respondent selected a mean of 50 roles (range 22–70). Survey 2 data were analyzed via thematic coding of responses and hierarchical cluster analysis to identify patterns in responses. From the thematic analysis, 20 non‐overlapping codes emerged in seven categories: clinical interaction and care, communication, curation, leadership, participant management, research, and team management. Three themes emerged from the categories that represented the roles of GCs in the UDN: clinical care, collaboration, and curation. Cluster analyses showed that responses were more similar among individuals at the same institution than between institutions. This study highlights the ways GCs apply their unique skill set in the context of a clinical translational research network. Additionally, findings from this study reinforce the wide applicability of core skills that are part of genetic counseling training. Clinical literacy, genomics expertise and analysis, interpersonal, psychosocial and counseling skills, education, professional practice skills, and an understanding of research processes make genetic counselors well suited for such roles and poised to positively impact research experiences and outcomes for participants. [ABSTRACT FROM AUTHOR]

Neurodegenerative disorders and leukodystrophies are progressive neurologic conditions that can occur following the disruption of intricately coordinated patterns of gene expression. Exome sequencing has been adopted as an effective diagnostic tool for determining the underlying genetic etiology of Mendelian neurologic disorders, however genome sequencing offer advantages in its ability to identify and characterize copy number, structural, and sequence variants in noncoding regions. Genome sequencing from peripheral leukocytes was performed on two patients with progressive neurologic disease of unknown etiology following negative genetic investigations including exome sequencing. RNA sequencing from peripheral blood was performed to determine gene expression patterns in one of the patients. Potential causative variants were matched to the patients' clinical presentation. The first proband was found to be heterozygous for a likely pathogenic missense variant in PLA2G6 (c.386T>C; p.Leu129Pro) and have an additional deep intronic variant in PLA2G6 (c.2035‐926G>A). RNA sequencing indicated this latter variant created a splice acceptor site leading to the incorporation of a pseudo‐exon introducing a premature termination codon. The second proband was heterozygous for a 261 kb deletion upstream of LMNB1 that included an enhancer region. Previous reports of copy number variants spanning this region of cis‐acting regulatory elements corroborated its pathogenicity. When combined with clinical presentations, these findings led to a definitive diagnosis of autosomal recessive infantile neuroaxonal dystrophy and autosomal dominant adult‐onset demyelinating leukodystrophy, respectively. In patients with progressive neurologic disease of unknown etiology, genome sequencing with the addition of RNA analysis where appropriate should be considered for the identification of causative noncoding pathogenic variants. [ABSTRACT FROM AUTHOR]

The Genome Empowerment Scale (GEmS), developed as a research tool, assesses perspectives of parents of children with undiagnosed disorders about to undergo exome or genome sequencing related to the process of empowerment. We defined genomic healthcare empowerment as follows: perceived ability to understand and seek new information related to the genomic sequencing, manage emotions related to the diagnostic process and outcomes, and utilize genomic sequencing information to the betterment of the individual/child and family. The GEmS consists of four scales, two are primarily emotion‐focused (Meaning of a Diagnosis, and Emotional Management of the Process) and two are action‐oriented (Seeking Information and Support, and Implications and Planning). The purpose of this research was to provide a strategy for interpreting results from the GEmS and present illustrative cases. These illustrations should serve to facilitate use of the GEmS in the clinical and research arena, particularly with respect to guiding genetic counseling processes for parents of children with undiagnosed conditions. [ABSTRACT FROM AUTHOR]

Background: Currently available structural variant (SV) detection methods do not span the complete spectrum of disease‐causing SVs. Optical genome mapping (OGM), an emerging technology with the potential to resolve diagnostic dilemmas, was performed to investigate clinically‐relevant SVs in a 4‐year‐old male with an epileptic encephalopathy of undiagnosed molecular origin. Methods: OGM was utilized to image long, megabase‐size DNA molecules, fluorescently labeled at specific sequence motifs throughout the genome with high sensitivity for detection of SVs greater than 500 bp in size. OGM results were confirmed in a CLIA‐certified laboratory via mate‐pair sequencing. Results: OGM identified a mosaic, de novo 90 kb deletion and inversion on the X chromosome disrupting the CDKL5 gene. Detection of the mosaic deletion, which had been previously undetected by chromosomal microarray, an infantile epilepsy panel including exon‐level microarray for CDKL5, exome sequencing as well as genome sequencing, resulted in a diagnosis of X‐linked dominant early infantile epileptic encephalopathy‐2. Conclusion: OGM affords an effective technology for the detection of SVs, especially those that are mosaic, since these remain difficult to detect with current NGS technologies and with conventional chromosomal microarrays. Further research in undiagnosed populations with OGM is warranted. [ABSTRACT FROM AUTHOR]

Background: Complex II is an essential component of the electron transport chain, linking it with the tricarboxylic acid cycle. Its four subunits are encoded in the nuclear genome, and deleterious variants in these genes, including SDHA (OMIM 600857), are associated with a wide range of symptoms including neurological disease, cardiomyopathy, and neoplasia (paraganglioma‐pheochromocytomas (PGL/PCC), and gastrointestinal stromal tumors). Deleterious variants of SDHA are most frequently associated with Leigh and Leigh‐like syndromes. Methods and Results: Here, we describe a case of a 9‐year‐old boy with tremor, nystagmus, hypotonia, developmental delay, significant ataxia, and progressive cerebellar atrophy. He was found to have biallelic variants in SDHA, a known pathogenic variant (c.91C>T (p.R31*)), and a variant of unknown significance (c.454G>A (p.E152K)). Deficient activity of complexes II and III was detected in fibroblasts from the patient consistent with a diagnosis of a respiratory chain disorder. Conclusion: We, therefore, consider whether c.454G>A (p.E152K) is, indeed, a pathogenic variant, and what implications it has for family members who carry the same variant. [ABSTRACT FROM AUTHOR]

Decreased sequencing costs have led to an explosion of genetic and genomic data. These data have revealed thousands of candidate human disease variants. Establishing which variants cause phenotypes and diseases, however, has remained challenging. Significant progress has been made, including advances by the National Institutes of Health (NIH)-funded Undiagnosed Diseases Network (UDN). However, 6000-13,000 additional disease genes remain to be identified. The continued discovery of rare diseases and their genetic underpinnings provides benefits to affected patients, of whom there are more than 400 million worldwide, and also advances understanding the mechanisms of more common diseases. Platforms employing model organisms enable discovery of novel gene-disease relationships, help establish variant pathogenicity, and often lead to the exploration of underlying mechanisms of pathophysiology that suggest new therapies. The Model Organism Screening Center (MOSC) of the UDN is a unique resource dedicated to utilizing informatics and functional studies in model organisms, including worm (Caenorhabditis elegans), fly (Drosophila melanogaster), and zebrafish (Danio rerio), to aid in diagnosis. The MOSC has directly contributed to the diagnosis of challenging cases, including multiple patients with complex, multi-organ phenotypes. In addition, the MOSC provides a framework for how basic scientists and clinicians can collaborate to drive diagnoses. Customized experimental plans take into account patient presentations, specific genes and variant(s), and appropriateness of each model organism for analysis. The MOSC also generates bioinformatic and experimental tools and reagents for the wider scientific community. Two elements of the MOSC that have been instrumental in its success are (1) multidisciplinary teams with expertise in variant bioinformatics and in human and model organism genetics, and (2) mechanisms for ongoing communication with clinical teams. Here we provide a position statement regarding the central role of model organisms for continued discovery of disease genes, and we advocate for the continuation and expansion of MOSC-type research entities as a Model Organisms Network (MON) to be funded through grant applications submitted to the NIH, family groups focused on specific rare diseases, other philanthropic organizations, industry partnerships, and other sources of support. [ABSTRACT FROM AUTHOR]

Every year individuals experience symptoms that remain undiagnosed by healthcare providers. In the United States, these rare diseases are defined as a condition that affects fewer than 200,000 individuals. However, there are an estimated 7000 rare diseases, and there are an estimated 25–30 million Americans in total (7.6–9.2% of the population as of 2018) affected by such disorders. The NIH Common Fund Undiagnosed Diseases Network (UDN) seeks to provide diagnoses for individuals with undiagnosed disease. Mass spectrometry-based metabolomics and lipidomics analyses could advance the collective understanding of individual symptoms and advance diagnoses for individuals with heretofore undiagnosed disease. Here, we report the mass spectrometry-based metabolomics and lipidomics analyses of blood plasma, urine, and cerebrospinal fluid from 148 patients within the UDN and their families, as well as from a reference population of over 100 individuals with no known metabolic diseases. The raw and processed data are available to the research community so that they might be useful in the diagnoses of current or future patients suffering from undiagnosed disorders. Measurement(s) Metabolomics • Lipidomics Technology Type(s) gas chromatography-mass spectrometry • Ultra High-performance Liquid Chromatography/Tandem Mass Spectrometry Factor Type(s) age group • sex Sample Characteristic - Organism Homo sapiens Sample Characteristic - Environment blood plasma material • urine material • cerebrospinal fluid material Sample Characteristic - Location United States of America Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13656581 [ABSTRACT FROM AUTHOR]

Genetic results have implications not only for the individual, but also for their family members. Research on family communication of genetic results has primarily focused on families affected by adult‐onset, dominant conditions as well as more common genetic conditions such as familial hypercholesterolemia, cardiomyopathies, and genetic hearing loss. This study therefore aimed to characterize genetic result communication in families with rare and undiagnosed conditions and identify factors that influence communication. One hundred and forty‐two individuals who received a diagnosis from the Undiagnosed Diseases Network (UDN), a study focused on providing diagnoses to individuals with undiagnosed conditions, were eligible to complete a survey assessing genetic results communication. Survey items assessed if communication was discussed with healthcare providers, with whom participants communicated genetic testing, why they chose to communicate with these family members, and what information they communicated. All respondents (5 adult UDN participants, 38 parents/guardians of UDN participants, and 2 identifying as both) shared genetic results with at least one family member. Individuals who identified as both were considered exclusively adult participants for the purpose of these analyses. Adult participants and parents/guardians of participants reported high levels of understanding (96%), utility (96%), and comfort communicating genetic results (89%). Additionally, parents/guardians were more likely to disclose genetic results due to a general desire to share (60% of parents/guardians vs. 14% adult participants), while adult participants reported that they shared results to communicate risk to family members (86% of adult participants vs. 24% of parents/guardians). Many respondents did not recall discussing with a healthcare provider how (64%) or what (42%) to communicate about results. The results of this study provide insight into the practice of result communication by individuals with rare and previously undiagnosed conditions, which can ideally inform development of more effective counseling strategies and guidelines to aid family communication. [ABSTRACT FROM AUTHOR]

Background: DYRK1A‐Related Intellectual Disability Syndrome is a rare autosomal dominant condition characterized by intellectual disability, speech and language delays, microcephaly, facial dysmorphism, and feeding difficulties. Affected individuals represent simplex cases that result from de novo heterozygous pathogenic variants in DYRK1A (OMIM 614104), or chromosomal structural rearrangements involving the DYRK1A locus. Due to the rarity of DYRK1A‐Related Intellectual Disability Syndrome, the spectrum of symptoms associated with this disease has not been completely defined. Methods and results: We present two unrelated cases of DYRK1A‐Related Intellectual Disability Syndrome resulting from variants in DYRK1A. Both probands presented to the National Institutes of Health (NIH) with multiple dysmorphic facial features, primary microcephaly, absent or minimal speech, feeding difficulties, and cognitive impairment; features that have been previously reported in individuals with DYRK1A. During NIH evaluation, additional features of enlarged cerebral subarachnoid spaces, retinal vascular tortuosity, and bilateral anomalous large optic discs with increased cup‐to‐disc ratio were identified in the first proband and multiple ophthalmologic abnormalities and sensorineural hearing loss were identified in the second proband. Conclusion: We recommend that the workup of future of patients include a comprehensive eye exam. Early establishment of physical, occupational, and speech therapy may help in the management of ataxia, hypertonia, and speech impairments common in these patients. [ABSTRACT FROM AUTHOR]

Encoding the slow skeletal muscle isoform of myosin binding protein‐C, MYBPC1 is associated with autosomal dominant and recessive forms of arthrogryposis. The authors describe a novel association for MYBPC1 in four patients from three independent families with skeletal muscle weakness, myogenic tremors, and hypotonia with gradual clinical improvement. The patients carried one of two de novo heterozygous variants in MYBPC1, with the p.Leu263Arg variant seen in three individuals and the p.Leu259Pro variant in one individual. Both variants are absent from controls, well conserved across vertebrate species, predicted to be damaging, and located in the M‐motif. Protein modeling studies suggested that the p.Leu263Arg variant affects the stability of the M‐motif, whereas the p.Leu259Pro variant alters its structure. In vitro biochemical and kinetic studies demonstrated that the p.Leu263Arg variant results in decreased binding of the M‐motif to myosin, which likely impairs the formation of actomyosin cross‐bridges during muscle contraction. Collectively, our data substantiate that damaging variants in MYBPC1 are associated with a new form of an early‐onset myopathy with tremor, which is a defining and consistent characteristic in all affected individuals, with no contractures. Recognition of this expanded myopathic phenotype can enable identification of individuals with MYBPC1 variants without arthrogryposis. [ABSTRACT FROM AUTHOR]

There are approximately 7,000 rare diseases affecting 25–30 million Americans, with 80% estimated to have a genetic basis. This presents a challenge for genetics practitioners to determine appropriate testing, make accurate diagnoses, and conduct up‐to‐date patient management. Exome sequencing (ES) is a comprehensive diagnostic approach, but only 25%–41% of the patients receive a molecular diagnosis. The remaining three‐fifths to three‐quarters of patients undergoing ES remain undiagnosed. The Stanford Center for Undiagnosed Diseases (CUD), a clinical site of the Undiagnosed Diseases Network, evaluates patients with undiagnosed and rare diseases using a combination of methods including ES. Frequently these patients have non‐diagnostic ES results, but strategic follow‐up techniques identify diagnoses in a subset. We present techniques used at the CUD that can be adopted by genetics providers in clinical follow‐up of cases where ES is non‐diagnostic. Solved case examples illustrate different types of non‐diagnostic results and the additional techniques that led to a diagnosis. Frequent approaches include segregation analysis, data reanalysis, genome sequencing, additional variant identification, careful phenotype‐disease correlation, confirmatory testing, and case matching. We also discuss prioritization of cases for additional analyses. [ABSTRACT FROM AUTHOR]

With the wide adoption of next‐generation sequencing (NGS)‐based genetic tests, genetic counselors require increased familiarity with NGS technology, variant interpretation concepts, and variant assessment tools. The use of exome and genome sequencing in clinical care has expanded the reach and diversity of genetic testing. Regardless of the setting where genetic counselors are performing variant interpretation or reporting, most of them have learned these skills from colleagues, while on the job. Though traditional, lecture‐based learning around these topics is important, there has been growing need for the inclusion of case‐based, experiential training of genomics and variant interpretation for genetic counseling students, with the goal of creating a strong foundation in variant interpretation for new genetic counselors, regardless of what area of practice they enter. To address this need, we established a genomics and variant interpretation rotation for Stanford's genetic counseling training program. In response to changes in the genomics landscape, this has now evolved into three unique rotation experiences, each focused on variant interpretation in the context of various genomic settings, including clinical laboratory, research laboratory, and healthy genomic analysis studies. Here, we describe the goals and learning objectives that we have developed for these variant interpretation rotations, and illustrate how these concepts are applied in practice. [ABSTRACT FROM AUTHOR]

Background: When applying genomic medicine to a rare disease patient, the primary goal is to identify one or more genomic variants that may explain the patient's phenotypes. Typically, this is done through annotation, filtering, and then prioritization of variants for manual curation. However, prioritization of variants in rare disease patients remains a challenging task due to the high degree of variability in phenotype presentation and molecular source of disease. Thus, methods that can identify and/or prioritize variants to be clinically reported in the presence of such variability are of critical importance. Methods: We tested the application of classification algorithms that ingest variant annotations along with phenotype information for predicting whether a variant will ultimately be clinically reported and returned to a patient. To test the classifiers, we performed a retrospective study on variants that were clinically reported to 237 patients in the Undiagnosed Diseases Network. Results: We treated the classifiers as variant prioritization systems and compared them to four variant prioritization algorithms and two single-measure controls. We showed that the trained classifiers outperformed all other tested methods with the best classifiers ranking 72% of all reported variants and 94% of reported pathogenic variants in the top 20. Conclusions: We demonstrated how freely available binary classification algorithms can be used to prioritize variants even in the presence of real-world variability. Furthermore, these classifiers outperformed all other tested methods, suggesting that they may be well suited for working with real rare disease patient datasets. [ABSTRACT FROM AUTHOR]