The Undiagnosed Diseases Network: Accelerating Discovery about Health and Disease

Multiple large language models versus experienced physicians in diagnosing challenging cases with gastrointestinal symptoms

Faced with challenging cases, doctors are increasingly seeking diagnostic advice from large language models (LLMs). This study aims to compare the ability of LLMs and human physicians to diagnose challenging cases. An offline dataset of 67 challenging cases with primary gastrointestinal symptoms was used to solicit possible diagnoses from seven LLMs and 22 gastroenterologists. The diagnoses by Claude 3.5 Sonnet covered the highest proportion (95% confidence interval [CI]) of instructive diagnoses (76.1%, [70.6%-80.9%]), significantly surpassing all the gastroenterologists (p < 0.05 for all). Claude 3.5 Sonnet achieved a significantly higher coverage rate (95% CI) than that of the gastroenterologists using search engines or other traditional resource (76.1% [70.6%-80.9%] vs. 45.5% [40.7%-50.4%], p < 0.001). The study highlights that advanced LLMs may assist gastroenterologists with instructive, time-saving, and cost-effective diagnostic scopes in challenging cases.

Mitochondrial trifunctional protein deficiency caused by a deep intronic deletion leading to aberrant splicing

Trifunctional protein deficiency (TFP) is a disorder of fatty acid beta-oxidation associated with metabolic, cardiac, and liver dysfunction in severe forms. We present two siblings diagnosed by newborn screening and confirmed by biochemical testing at birth. Their clinical course was complicated by recurrent rhabdomyolysis, retinopathy, and hypoparathyroidism. Both siblings were also diagnosed with focal segmental glomerulosclerosis (FSGS) and bone marrow failure and ultimately died of hypoxemic respiratory failure. Initial sequencing of the TFP-associated genes HADHA and HADHB showed only a paternally inherited variant in HADHB, NM_000183.3:c.1059del (p.Gly354AspfsTer10). Subsequent evaluation by the Undiagnosed Diseases Network with genome and transcriptome sequencing revealed a rare maternally inherited 17 base pair deletion in HADHB, NM_000183.3:c.1390-515_1390-499del, located in the final intron and resulting in a pseudoexon that harbors a premature termination codon. Both sisters were compound heterozygous for this and the paternal premature termination codon. No other variants were detected that were potentially causative for the FSGS and bone marrow failure on genome sequencing. A review of the literature at that time revealed several case reports of the uncommon clinical findings of FSGS, bone marrow failure, and pulmonary involvement in patients with TFP, confirming this clinical diagnosis as the complete explanation for these siblings.

Loss-of-function in RBBP5 results in a syndromic neurodevelopmental disorder associated with microcephaly

PURPOSE

Epigenetic dysregulation has been associated with many inherited disorders. RBBP5 (HGNC:9888) encodes a core member of the protein complex that methylates histone 3 lysine-4 and has not been implicated in human disease.

METHODS

We identify 5 unrelated individuals with de novo heterozygous variants in RBBP5. Three nonsense/frameshift and 2 missense variants were identified in probands with neurodevelopmental symptoms, including global developmental delay, intellectual disability, microcephaly, and short stature. Here, we investigate the pathogenicity of the variants through protein structural analysis and transgenic Drosophila models.

RESULTS

Both missense p.(T232I) and p.(E296D) variants affect evolutionarily conserved amino acids located at the interface between RBBP5 and the nucleosome. In Drosophila, overexpression analysis identifies partial loss-of-function mechanisms when the variants are expressed using the fly Rbbp5 or human RBBP5 cDNA. Loss of Rbbp5 leads to a reduction in brain size. The human reference or variant transgenes fail to rescue this loss and expression of either missense variant in an Rbbp5 null background results in a less severe microcephaly phenotype than the human reference, indicating both missense variants are partial loss-of-function alleles.

CONCLUSION

Haploinsufficiency of RBBP5 observed through de novo null and hypomorphic loss-of-function variants is associated with a syndromic neurodevelopmental disorder.

Deciphering the Complexity of FSHD: A Multimodal Approach as a Model for Rare Disorders

Rare diseases are heterogeneous diseases characterized by various symptoms and signs. Due to the low prevalence of such conditions (less than 1 in 2000 people), medical expertise is limited, knowledge is poor and patients' care provided by medical centers is inadequate. An accurate diagnosis is frequently challenging and ongoing research is also insufficient, thus complicating the understanding of the natural progression of the rarest disorders. This review aims at presenting the multimodal approach supported by the integration of multiple analyses and disciplines as a valuable solution to clarify complex genotype-phenotype correlations and promote an in-depth examination of rare disorders. Taking into account the literature from large-scale population studies and ongoing technological advancement, this review described some examples to show how a multi-skilled team can improve the complex diagnosis of rare diseases. In this regard, Facio-Scapulo-Humeral muscular Dystrophy (FSHD) represents a valuable example where a multimodal approach is essential for a more accurate and precise diagnosis, as well as for enhancing the management of patients and their families. Given their heterogeneity and complexity, rare diseases call for a distinctive multidisciplinary approach to enable diagnosis and clinical follow-up.

The Undiagnosed Diseases Network: Characteristics of solvable applicants and diagnostic suggestions for nonaccepted ones

PURPOSE

Can certain characteristics identify as solvable some undiagnosed patients who seek extensive evaluation and thorough record review, such as by the Undiagnosed Diseases Network (UDN)?

METHODS

The UDN is a national research resource to solve medical mysteries through team science. Applicants provide informed consent to access to their medical records. After review, expert panels assess if applicants meet inclusion and exclusion criteria to select participants. When not accepting applicants, UDN experts may offer suggestions for diagnostic efforts. Using minimal information from initial applications, we compare features in applicants who are not accepted with those who are accepted and either solved or still not solved by the UDN. The diagnostic suggestions offered to nonaccepted applicants and their clinicians were tallied.

RESULTS

Nonaccepted applicants were more often female, older at first symptoms and application, and longer in review compared with accepted applicants. The accepted and successfully diagnosed applicants were younger, shorter in review time, more often non-White, of Hispanic ethnicity, and presenting with nervous system features. Half of nonaccepted applicants were given suggestions for further local diagnostic evaluation. A few seemed to have 2 major diagnoses or a provocative environmental exposure history.

CONCLUSION

Comprehensive UDN record review generates possibly helpful advice.

Resolution of SLC6A1 variable expressivity in a multi-generational family using deep clinical phenotyping and Drosophila models

Purpose

Variants in SLC6A1 result in a rare neurodevelopmental disorder characterized by a variable clinical presentation of symptoms including developmental delay, epilepsy, motor dysfunction, and autism spectrum disorder. SLC6A1 haploinsufficiency has been confirmed as the predominant pathway of SLC6A1-related neurodevelopmental disorders (NDDs), however, the molecular mechanism underlying the variable clinical presentation remains unclear.

Methods

Here, through work of the Undiagnosed Diseases Network, we identify an undiagnosed individual with an inherited p.(A334S) variant of uncertain significance. To resolve this case and better understand the variable expressivity with SLC6A1, we assess the phenotypes of the proband with a cohort of cases diagnosed with SLC6A1-related NDDs. We then create an allelic series in the Drosophila melanogaster to functionally characterize case variants.

Results

We identify significant clinical overlap between the unsolved case and confirmed cases of SLC6A1-related NDDs and find a mild to severe clinical presentation associated with missense variants. We confirm phenotypes in flies expressing SLC6A1 variants consistent with a partial loss-of-function mechanism.

Conclusion

We conclude that the p.(A334S) variant is a hypomorphic allele and begin to elucidate the underlying variability in SLC6A1-related NDDs. These insights will inform clinical diagnosis, prognosis, treatment and inform therapeutic design for those living with SLC6A1-related NDDs.

Semiautomated approach focused on new genomic information results in time and effort-efficient reannotation of negative exome data

Most rare disease patients (75-50%) undergoing genomic sequencing remain unsolved, often due to lack of information about variants identified. Data review over time can leverage novel information regarding disease-causing variants and genes, increasing this diagnostic yield. However, time and resource constraints have limited reanalysis of genetic data in clinical laboratories setting. We developed RENEW, (REannotation of NEgative WES/WGS) an automated reannotation procedure that uses relevant new information in on-line genomic databases to enable rapid review of genomic findings. We tested RENEW in an unselected cohort of 1066 undiagnosed cases with a broad spectrum of phenotypes from the Mayo Clinic Center for Individualized Medicine using new information in ClinVar, HGMD and OMIM between the date of previous analysis/testing and April of 2022. 5741 variants prioritized by RENEW were rapidly reviewed by variant interpretation specialists. Mean analysis time was approximately 20 s per variant (32 h total time). Reviewed cases were classified as: 879 (93.0%) undiagnosed, 63 (6.6%) putatively diagnosed, and 4 (0.4%) definitively diagnosed. New strategies are needed to enable efficient review of genomic findings in unsolved cases. We report on a fast and practical approach to address this need and improve overall diagnostic success in patient testing through a recurrent reannotation process.

VarPPUD: Variant post prioritization developed for undiagnosed genetic disorders

Rare and ultra-rare genetic conditions are estimated to impact nearly 1 in 17 people worldwide, yet accurately pinpointing the diagnostic variants underlying each of these conditions remains a formidable challenge. Because comprehensive, in vivo functional assessment of all possible genetic variants is infeasible, clinicians instead consider in silico variant pathogenicity predictions to distinguish plausibly disease-causing from benign variants across the genome. However, in the most difficult undiagnosed cases, such as those accepted to the Undiagnosed Diseases Network (UDN), existing pathogenicity predictions cannot reliably discern true etiological variant(s) from other deleterious candidate variants that were prioritized through N-of-1 efforts. Pinpointing the disease-causing variant from a pool of plausible candidates remains a largely manual effort requiring extensive clinical workups, functional and experimental assays, and eventual identification of genotype- and phenotype-matched individuals. Here, we introduce VarPPUD, a tool trained on prioritized variants from UDN cases, that leverages gene-, amino acid-, and nucleotide-level features to discern pathogenic variants from other deleterious variants that are unlikely to be confirmed as disease relevant. VarPPUD achieves a cross-validated accuracy of 79.3% and precision of 77.5% on a held-out subset of uniquely challenging UDN cases, respectively representing an average 18.6% and 23.4% improvement over nine traditional pathogenicity prediction approaches on this task. We validate VarPPUD's ability to discriminate likely from unlikely pathogenic variants on synthetic, GAN-generated candidate variants as well. Finally, we show how VarPPUD can be probed to evaluate each input feature's importance and contribution toward prediction-an essential step toward understanding the distinct characteristics of newly-uncovered disease-causing variants.

Bayesian estimation of gene constraint from an evolutionary model with gene features

Measures of selective constraint on genes have been used for many applications including clinical interpretation of rare coding variants, disease gene discovery, and studies of genome evolution. However, widely-used metrics are severely underpowered at detecting constraint for the shortest ∼25% of genes, potentially causing important pathogenic mutations to be overlooked. We developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, shet. Our estimates outperform existing metrics for prioritizing genes important for cell essentiality, human disease, and other phenotypes, especially for short genes. Our new estimates of selective constraint should have wide utility for characterizing genes relevant to human disease. Finally, our inference framework, GeneBayes, provides a flexible platform that can improve estimation of many gene-level properties, such as rare variant burden or gene expression differences.

De novo variants in the non-coding spliceosomal snRNA gene RNU4-2 are a frequent cause of syndromic neurodevelopmental disorders

Around 60% of individuals with neurodevelopmental disorders (NDD) remain undiagnosed after comprehensive genetic testing, primarily of protein-coding genes1. Increasingly, large genome-sequenced cohorts are improving our ability to discover new diagnoses in the non-coding genome. Here, we identify the non-coding RNA RNU4-2 as a novel syndromic NDD gene. RNU4-2 encodes the U4 small nuclear RNA (snRNA), which is a critical component of the U4/U6.U5 tri-snRNP complex of the major spliceosome2. We identify an 18 bp region of RNU4-2 mapping to two structural elements in the U4/U6 snRNA duplex (the T-loop and Stem III) that is severely depleted of variation in the general population, but in which we identify heterozygous variants in 119 individuals with NDD. The vast majority of individuals (77.3%) have the same highly recurrent single base-pair insertion (n.64_65insT). We estimate that variants in this region explain 0.41% of individuals with NDD. We demonstrate that RNU4-2 is highly expressed in the developing human brain, in contrast to its contiguous counterpart RNU4-1 and other U4 homologs, supporting RNU4-2's role as the primary U4 transcript in the brain. Overall, this work underscores the importance of non-coding genes in rare disorders. It will provide a diagnosis to thousands of individuals with NDD worldwide and pave the way for the development of effective treatments for these individuals.

Transcriptome-Wide Association Studies (TWAS): Methodologies, Applications, and Challenges

Transcriptome-wide association study (TWAS) methodologies aim to identify genetic effects on phenotypes through the mediation of gene transcription. In TWAS, in silico models of gene expression are trained as functions of genetic variants and then applied to genome-wide association study (GWAS) data. This post-GWAS analysis identifies gene-trait associations with high interpretability, enabling follow-up functional genomics studies and the development of genetics-anchored resources. We provide an overview of commonly used TWAS approaches, their advantages and limitations, and some widely used applications. © 2024 Wiley Periodicals LLC.

Integrating non-mammalian model organisms in the diagnosis of rare genetic diseases in humans

Next-generation sequencing technology has rapidly accelerated the discovery of genetic variants of interest in individuals with rare diseases. However, showing that these variants are causative of the disease in question is complex and may require functional studies. Use of non-mammalian model organisms - mainly fruitflies (Drosophila melanogaster), nematode worms (Caenorhabditis elegans) and zebrafish (Danio rerio) - enables the rapid and cost-effective assessment of the effects of gene variants, which can then be validated in mammalian model organisms such as mice and in human cells. By probing mechanisms of gene action and identifying interacting genes and proteins in vivo, recent studies in these non-mammalian model organisms have facilitated the diagnosis of numerous genetic diseases and have enabled the screening and identification of therapeutic options for patients. Studies in non-mammalian model organisms have also shown that the biological processes underlying rare diseases can provide insight into more common mechanisms of disease and the biological functions of genes. Here, we discuss the opportunities afforded by non-mammalian model organisms, focusing on flies, worms and fish, and provide examples of their use in the diagnosis of rare genetic diseases.

International Undiagnosed Diseases Programs (UDPs): components and outcomes

Over the last 15 years, Undiagnosed Diseases Programs have emerged to address the significant number of individuals with suspected but undiagnosed rare genetic diseases, integrating research and clinical care to optimize diagnostic outcomes. This narrative review summarizes the published literature surrounding Undiagnosed Diseases Programs worldwide, including thirteen studies that evaluate outcomes and two commentary papers. Commonalities in the diagnostic and research process of Undiagnosed Diseases Programs are explored through an appraisal of available literature. This exploration allowed for an assessment of the strengths and limitations of each of the six common steps, namely enrollment, comprehensive clinical phenotyping, research diagnostics, data sharing and matchmaking, results, and follow-up. Current literature highlights the potential utility of Undiagnosed Diseases Programs in research diagnostics. Since participants have often had extensive previous genetic studies, research pipelines allow for diagnostic approaches beyond exome or whole genome sequencing, through reanalysis using research-grade bioinformatics tools and multi-omics technologies. The overall diagnostic yield is presented by study, since different selection criteria at enrollment and reporting processes make comparisons challenging and not particularly informative. Nonetheless, diagnostic yield in an undiagnosed cohort reflects the potential of an Undiagnosed Diseases Program. Further comparisons and exploration of the outcomes of Undiagnosed Diseases Programs worldwide will allow for the development and improvement of the diagnostic and research process and in turn improve the value and utility of an Undiagnosed Diseases Program.

Rare de novo gain-of-function missense variants in DOT1L are associated with developmental delay and congenital anomalies

Misregulation of histone lysine methylation is associated with several human cancers and with human developmental disorders. DOT1L is an evolutionarily conserved gene encoding a lysine methyltransferase (KMT) that methylates histone 3 lysine-79 (H3K79) and was not previously associated with a Mendelian disease in OMIM. We have identified nine unrelated individuals with seven different de novo heterozygous missense variants in DOT1L through the Undiagnosed Disease Network (UDN), the SickKids Complex Care genomics project, and GeneMatcher. All probands had some degree of global developmental delay/intellectual disability, and most had one or more major congenital anomalies. To assess the pathogenicity of the DOT1L variants, functional studies were performed in Drosophila and human cells. The fruit fly DOT1L ortholog, grappa, is expressed in most cells including neurons in the central nervous system. The identified DOT1L variants behave as gain-of-function alleles in flies and lead to increased H3K79 methylation levels in flies and human cells. Our results show that human DOT1L and fly grappa are required for proper development and that de novo heterozygous variants in DOT1L are associated with a Mendelian disease.

Simulation of undiagnosed patients with novel genetic conditions

Rare Mendelian disorders pose a major diagnostic challenge and collectively affect 300-400 million patients worldwide. Many automated tools aim to uncover causal genes in patients with suspected genetic disorders, but evaluation of these tools is limited due to the lack of comprehensive benchmark datasets that include previously unpublished conditions. Here, we present a computational pipeline that simulates realistic clinical datasets to address this deficit. Our framework jointly simulates complex phenotypes and challenging candidate genes and produces patients with novel genetic conditions. We demonstrate the similarity of our simulated patients to real patients from the Undiagnosed Diseases Network and evaluate common gene prioritization methods on the simulated cohort. These prioritization methods recover known gene-disease associations but perform poorly on diagnosing patients with novel genetic disorders. Our publicly-available dataset and codebase can be utilized by medical genetics researchers to evaluate, compare, and improve tools that aid in the diagnostic process.

Genomics Research with Undiagnosed Children: Ethical Challenges at the Boundaries of Research and Clinical Care

OBJECTIVE

To explore the perspectives of parents of undiagnosed children enrolled in genomic diagnosis research regarding their motivations for enrolling their children, their understanding of the potential burdens and benefits, and the extent to which their experiences ultimately aligned with or diverged from their original expectations.

STUDY DESIGN

In-depth interviews were conducted with parents, audio-recorded and transcribed. A structured codebook was applied to each transcript, after which iterative memoing was used to identify themes.

RESULTS

Fifty-four parents participated, including 17 (31.5%) whose child received a diagnosis through research. Themes describing parents' expectations and experiences of genomic diagnosis research included (1) the extent to which parents' motivations for participation focused on their hope that it would directly benefit their child, (2) the ways in which parents' frustrations regarding the research process confused the dual clinical and research goals of their participation, and (3) the limited clinical benefits parents ultimately experienced for their children.

CONCLUSIONS

Our results suggest that parents of undiagnosed children seeking enrollment in genomic diagnosis research are at risk of a form of therapeutic misconception-in this case, diagnostic misconception. These findings indicate the need to examine the processes and procedures associated with this research to communicate appropriately and balance the potential burdens and benefits of study participation.

Bayesian estimation of gene constraint from an evolutionary model with gene features

Measures of selective constraint on genes have been used for many applications including clinical interpretation of rare coding variants, disease gene discovery, and studies of genome evolution. However, widely-used metrics are severely underpowered at detecting constraint for the shortest ~25% of genes, potentially causing important pathogenic mutations to be overlooked. We developed a framework combining a population genetics model with machine learning on gene features to enable accurate inference of an interpretable constraint metric, s het . Our estimates outperform existing metrics for prioritizing genes important for cell essentiality, human disease, and other phenotypes, especially for short genes. Our new estimates of selective constraint should have wide utility for characterizing genes relevant to human disease. Finally, our inference framework, GeneBayes, provides a flexible platform that can improve estimation of many gene-level properties, such as rare variant burden or gene expression differences.

Unified views on variant impact across many diseases

Genomic studies of human disorders are often performed by distinct research communities (i.e., focused on rare diseases, common diseases, or cancer). Despite underlying differences in the mechanistic origin of different disease categories, these studies share the goal of identifying causal genomic events that are critical for the clinical manifestation of the disease phenotype. Moreover, these studies face common challenges, including understanding the complex genetic architecture of the disease, deciphering the impact of variants on multiple scales, and interpreting noncoding mutations. Here, we highlight these challenges in depth and argue that properly addressing them will require a more unified vocabulary and approach across disease communities. Toward this goal, we present a unified perspective on relating variant impact to various genomic disorders.

Participation in a national diagnostic research study: assessing the patient experience

INTRODUCTION

The Undiagnosed Diseases Network (UDN), a clinical research study funded by the National Institutes of Health, aims to provide answers for patients with undiagnosed conditions and generate knowledge about underlying disease mechanisms. UDN evaluations involve collaboration between clinicians and researchers and go beyond what is possible in clinical settings. While medical and research outcomes of UDN evaluations have been explored, this is the first formal assessment of the patient and caregiver experience.

METHODS

We invited UDN participants and caregivers to participate in focus groups via email, newsletter, and a private participant Facebook group. We developed focus group questions based on research team expertise, literature focused on patients with rare and undiagnosed conditions, and UDN participant and family member feedback. In March 2021, we conducted, recorded, and transcribed four 60-min focus groups via Zoom. Transcripts were evaluated using a thematic analysis approach.

RESULTS

The adult undiagnosed focus group described the UDN evaluation as validating and an avenue for access to medical providers. They also noted that the experience impacted professional choices and helped them rely on others for support. The adult diagnosed focus group described the healthcare system as not set up for rare disease. In the pediatric undiagnosed focus group, caregivers discussed a continued desire for information and gratitude for the UDN evaluation. They also described an ability to rule out information and coming to terms with not having answers. The pediatric diagnosed focus group discussed how the experience helped them focus on management and improved communication. Across focus groups, adults (undiagnosed/diagnosed) noted the comprehensiveness of the evaluation. Undiagnosed focus groups (adult/pediatric) discussed a desire for ongoing communication and care with the UDN. Diagnosed focus groups (adult/pediatric) highlighted the importance of the diagnosis they received in the UDN. The majority of the focus groups noted a positive future orientation after participation.

CONCLUSION

Our findings are consistent with prior literature focused on the patient experience of rare and undiagnosed conditions and highlight benefits from comprehensive evaluations, regardless of whether a diagnosis is obtained. Focus group themes also suggest areas for improvement and future research related to the diagnostic odyssey.

MYH2-associated myopathy caused by a novel splice-site variant

MYH2 encodes MyHCIIa, a myosin heavy chain found in fast type 2A fibers. Pathogenic variants in this gene have previously been implicated in dominant and recessive forms of myopathy. Three individuals reported here are part of a family in which four generations of individuals are affected by a slowly progressive, predominantly proximal myopathy in an autosomal dominant inheritance pattern. Affected individuals in this family lacked classic features of an MYH2-associated myopathy such as congenital contractures and ophthalmoplegia. A novel variant, MYH2 c.5673+1G>C, was detected in the proband and subsequently found to segregate with disease in five additional family members. Further studies demonstrated that this variant affects splicing, resulting in novel transcripts. These data and muscle biopsy findings in the proband, indicate that this family's MYH2 variant is causative of their myopathy, adding to our understanding of the clinical and molecular characteristics of the disease.

Integrated regulation of dopaminergic and epigenetic effectors of neuroprotection in Parkinson's disease models

Whole-exome sequencing of Parkinson's disease (PD) patient DNA identified single-nucleotide polymorphisms (SNPs) in the tyrosine nonreceptor kinase-2 (TNK2) gene. Although this kinase had a previously demonstrated activity in preventing the endocytosis of the dopamine reuptake transporter (DAT), a causal role for TNK2-associated dysfunction in PD remains unresolved. We postulated the dopaminergic neurodegeneration resulting from patient-associated variants in TNK2 were a consequence of aberrant or prolonged TNK2 overactivity, the latter being a failure in TNK2 degradation by an E3 ubiquitin ligase, neuronal precursor cell-expressed developmentally down-regulated-4 (NEDD4). Interestingly, systemic RNA interference protein-3 (SID-3) is the sole TNK2 ortholog in the nematode Caenorhabditis elegans, where it is an established effector of epigenetic gene silencing mediated through the dsRNA-transporter, SID-1. We hypothesized that TNK2/SID-3 represents a node of integrated dopaminergic and epigenetic signaling essential to neuronal homeostasis. Use of a TNK2 inhibitor (AIM-100) or a NEDD4 activator [N-aryl benzimidazole 2 (NAB2)] in bioassays for either dopamine- or dsRNA-uptake into worm dopaminergic neurons revealed that sid-3 mutants displayed robust neuroprotection from 6-hydroxydopamine (6-OHDA) exposures, as did AIM-100 or NAB2-treated wild-type animals. Furthermore, NEDD4 activation by NAB2 in rat primary neurons correlated to a reduction in TNK2 levels and the attenuation of 6-OHDA neurotoxicity. CRISPR-edited nematodes engineered to endogenously express SID-3 variants analogous to TNK2 PD-associated SNPs exhibited enhanced susceptibility to dopaminergic neurodegeneration and circumvented the RNAi resistance characteristic of SID-3 dysfunction. This research exemplifies a molecular etiology for PD whereby dopaminergic and epigenetic signaling are coordinately regulated to confer susceptibility or resilience to neurodegeneration.

Bi-allelic ATG4D variants are associated with a neurodevelopmental disorder characterized by speech and motor impairment

Autophagy regulates the degradation of damaged organelles and protein aggregates, and is critical for neuronal development, homeostasis, and maintenance, yet few neurodevelopmental disorders have been associated with pathogenic variants in genes encoding autophagy-related proteins. We report three individuals from two unrelated families with a neurodevelopmental disorder characterized by speech and motor impairment, and similar facial characteristics. Rare, conserved, bi-allelic variants were identified in ATG4D, encoding one of four ATG4 cysteine proteases important for autophagosome biogenesis, a hallmark of autophagy. Autophagosome biogenesis and induction of autophagy were intact in cells from affected individuals. However, studies evaluating the predominant substrate of ATG4D, GABARAPL1, demonstrated that three of the four ATG4D patient variants functionally impair ATG4D activity. GABARAPL1 is cleaved or "primed" by ATG4D and an in vitro GABARAPL1 priming assay revealed decreased priming activity for three of the four ATG4D variants. Furthermore, a rescue experiment performed in an ATG4 tetra knockout cell line, in which all four ATG4 isoforms were knocked out by gene editing, showed decreased GABARAPL1 priming activity for the two ATG4D missense variants located in the cysteine protease domain required for priming, suggesting that these variants impair the function of ATG4D. The clinical, bioinformatic, and functional data suggest that bi-allelic loss-of-function variants in ATG4D contribute to the pathogenesis of this syndromic neurodevelopmental disorder.

Personalized structural biology reveals the molecular mechanisms underlying heterogeneous epileptic phenotypes caused by de novo KCNC2 variants

Whole-exome sequencing (WES) in the clinic has identified several rare monogenic developmental and epileptic encephalopathies (DEE) caused by ion channel variants. However, WES often fails to provide actionable insight for rare diseases, such as DEEs, due to the challenges of interpreting variants of unknown significance (VUS). Here, we describe a "personalized structural biology" (PSB) approach that leverages recent innovations in the analysis of protein 3D structures to address this challenge. We illustrate this approach in an Undiagnosed Diseases Network (UDN) individual with DEE symptoms and a de novo VUS in KCNC2 (p.V469L), the Kv3.2 voltage-gated potassium channel. A nearby KCNC2 variant (p.V471L) was recently suggested to cause DEE-like phenotypes. Computational structural modeling suggests that both affect protein function. However, despite their proximity, the p.V469L variant is likely to sterically block the channel pore, while the p.V471L variant is likely to stabilize the open state. Biochemical and electrophysiological analyses demonstrate heterogeneous loss-of-function and gain-of-function effects, as well as differential response to 4-aminopyridine treatment. Molecular dynamics simulations illustrate that the pore of the p.V469L variant is more constricted, increasing the energetic barrier for K+ permeation, whereas the p.V471L variant stabilizes the open conformation. Our results implicate variants in KCNC2 as causative for DEE and guide the interpretation of a UDN individual. They further delineate the molecular basis for the heterogeneous clinical phenotypes resulting from two proximal pathogenic variants. This demonstrates how the PSB approach can provide an analytical framework for individualized hypothesis-driven interpretation of protein-coding VUS.

Advances in clinical genetics and its current challenges

The great advances in the development of genomic technologies and their incorporation into routine clinical practice is bringing about a change in which an individual's genetic information is becoming increasingly relevant to their medical care. This is known as genomic medicine. Its implementation is not without barriers, including difficulties in the assessment and interpretation of genomic data, deficient training of professionals and patients in this field, unequal access to units with expertise, and a lack of professional profiles and infrastructures necessary for the incorporation of genomic technologies into routine clinical practice. This article reviews the advances and challenges of genomic medicine.

The microRNA processor DROSHA is a candidate gene for a severe progressive neurological disorder

DROSHA encodes a ribonuclease that is a subunit of the Microprocessor complex and is involved in the first step of microRNA (miRNA) biogenesis. To date, DROSHA has not yet been associated with a Mendelian disease. Here, we describe two individuals with profound intellectual disability, epilepsy, white matter atrophy, microcephaly and dysmorphic features, who carry damaging de novo heterozygous variants in DROSHA. DROSHA is constrained for missense variants and moderately intolerant to loss-of-function (o/e = 0.24). The loss of the fruit fly ortholog drosha causes developmental arrest and death in third instar larvae, a severe reduction in brain size and loss of imaginal discs in the larva. Loss of drosha in eye clones causes small and rough eyes in adult flies. One of the identified DROSHA variants (p.Asp1219Gly) behaves as a strong loss-of-function allele in flies, while another variant (p.Arg1342Trp) is less damaging in our assays. In worms, a knock-in that mimics the p.Asp1219Gly variant at a worm equivalent residue causes loss of miRNA expression and heterochronicity, a phenotype characteristic of the loss of miRNA. Together, our data show that the DROSHA variants found in the individuals presented here are damaging based on functional studies in model organisms and likely underlie the severe phenotype involving the nervous system.

Beyond race: Recruitment of diverse participants in clinical genomics research for rare disease

Purpose: Despite recent attention to increasing diversity in clinical genomics research, researchers still struggle to recruit participants from varied sociodemographic backgrounds. We examined the experiences of parents from diverse backgrounds with enrolling their children in clinical genomics research on rare diseases. We explored the barriers and facilitators parents encountered and possible impacts of sociodemographic factors on their access to research.

Methods: We utilized semi-structured interviews with parents of children participating in the Undiagnosed Diseases Network. Interview data were analyzed using comparative content analysis.

Results: We interviewed 13 Hispanic, 11 non-Hispanic White, four Asian, and two biracial parents. Participants discussed different pathways to clinical genomics research for rare disease as well as how sociodemographic factors shaped families’ access. Themes focused on variation in: 1) reliance on providers to access research; 2) cultural norms around health communication; 3) the role of social capital in streamlining access; and 4) the importance of language-concordant research engagement.

Conclusion: Our findings suggest that variables beyond race/ethnicity may influence access in clinical genomics research. Future efforts to diversify research participation should consider utilizing varied recruitment strategies to reach participants with diverse sociodemographic characteristics.

Supporting undiagnosed participants when clinical genomics studies end

Many large research initiatives have cumulatively enrolled thousands of patients with a range of complex medical issues but no clear genetic etiology. However, it is unclear how researchers, institutions, and funders should manage the data and relationships with those participants who remain undiagnosed when these studies end. In this comment, we outline the current literature relevant to post-study obligations in clinical genomics research and discuss the application of current guidelines to research with undiagnosed participants.

Receiving Genomic Sequencing Results through the Victorian Undiagnosed Disease Program: Exploring Parental Experiences

Rare diseases cumulatively affect a significant number of people, and for many, a diagnosis remains elusive. The Victorian Undiagnosed Disease Program (UDP-Vic) utilizes deep phenotyping, advanced genomic sequencing and functional studies to diagnose children with rare diseases for which previous clinical testing has been non-diagnostic. Whereas the diagnostic outcomes of undiagnosed disease programs have been well-described, here, we explore how parents experience participation in the UDP-Vic and the impact of receiving both diagnostic and non-diagnostic genomic sequencing results for their children. Semi-structured interviews ranging in length from 25 to 105 min were conducted with 21 parents of children in the program. Ten participants were parents of children who received a diagnosis through the program, and eleven were parents of children who remain undiagnosed. Although the experiences of families varied, five shared themes emerged from the data: (1) searching for a diagnosis, (2) varied impact of receiving a result, (3) feelings of relief and disappointment, (4) seeking connection and (5) moving towards acceptance. The findings demonstrate the shared experience of parents of children with rare disease both before and after a genomic sequencing result. The results have implications for genetic counselors and clinicians offering genomic sequencing and supporting families of children with rare diseases.

Prospective Studies Comparing Structured vs Nonstructured Diagnostic Protocol Evaluations Among Patients With Fever of Unknown Origin: A Systematic Review and Meta-analysis

Importance

Patients meeting the criteria for fever of unknown origin (FUO) can be evaluated with structured or nonstructured approaches, but the optimal diagnostic method is unresolved.

Objective

To analyze differences in diagnostic outcomes among patients undergoing structured or nonstructured diagnostic methods applied to prospective clinical studies.

Data Sources

PubMed, Embase, Scopus, and Web of Science databases with librarian-generated query strings for FUO, PUO, fever or pyrexia of unknown origin, clinical trial, and prospective studies identified from January 1, 1997, to March 31, 2021.

Study Selection

Prospective studies meeting any adult FUO definition were included. Articles were excluded if patients did not precisely fit any existing adult FUO definition or studies were not classified as prospective.

Data Extraction and Synthesis

Abstracted data included years of publication and study period, country, setting (eg, university vs community hospital), defining criteria and category outcome, structured or nonstructured diagnostic protocol evaluation, sex, temperature threshold and measurement, duration of fever and hospitalization before final diagnoses, and contribution of potential diagnostic clues, biochemical and immunological serologic studies, microbiology cultures, histologic analysis, and imaging studies. Structured protocols compared with nonstructured diagnostic methods were analyzed using regression models.

Main Outcomes and Measures

Overall diagnostic yield was the primary outcome.

Results

Among the 19 prospective trials with 2627 unique patients included in the analysis (range of patient ages, 10-94 years; 21.0%-55.3% female), diagnoses among FUO series varied across and within World Health Organization (WHO) geographic regions. Use of a structured diagnostic protocol was not significantly associated with higher odds of yielding a diagnosis compared with nonstructured protocols in aggregate (odds ratio [OR], 0.98; 95% CI, 0.65-1.49) or between Western Europe (Belgium, France, the Netherlands, and Spain) (OR, 0.95; 95% CI, 0.49-1.86) and Eastern Europe (Turkey and Romania) (OR, 0.83; 95% CI, 0.41-1.69). Despite the limited number of studies in some regions, analyses based on the 6 WHO geographic areas found differences in the diagnostic yield. Western European studies had the lowest percentage of achieving a diagnosis. Southeast Asia led with infections at 49.0%. Noninfectious inflammatory conditions were most prevalent in the Western Pacific region (34.0%), whereas the Eastern Mediterranean region had the highest proportion of oncologic explanations (24.0%).

Conclusions and Relevance

In this systematic review and meta-analysis, diagnostic yield varied among WHO regions. Available evidence from prospective studies did not support that structured diagnostic protocols had a significantly better rate of achieving a diagnosis than nonstructured protocols. Clinicians worldwide should incorporate geographical disease prevalence in their evaluation of patients with FUO.

PRUNE1 c.933G>A synonymous variant induces exon 7 skipping, disrupts the DHHA2 domain, and leads to an atypical NMIHBA syndrome presentation: Case report and review of the literature

Prune exopolyphosphatase-1 (PRUNE1) encodes a member of the aspartic acid-histidine-histidine (DHH) phosphodiesterase superfamily that regulates cell migration and proliferation during brain development. In 2015, biallelic PRUNE1 loss-of-function variants were identified to cause the neurodevelopmental disorder with microcephaly, hypotonia, and variable brain abnormalities (NMIHBA, OMIM#617481). NMIHBA is characterized by the namesake features and structural brain anomalies including thinning of the corpus callosum, cerebral and cerebellar atrophy, and delayed myelination. To date, 47 individuals have been reported in the literature, but the phenotypic spectrum of PRUNE1-related disorders and their causative variants remains to be characterized fully. Here, we report a novel homozygous PRUNE1 NM_021222.2:c.933G>A synonymous variant identified in a 6-year-old boy with intellectual and developmental disabilities, hypotonia, and spastic diplegia, but with the absence of microcephaly, brain anomalies, or seizures. Fibroblast RNA sequencing revealed that the PRUNE1 NM_021222.1:c.933G>A variant resulted in an in-frame skipping of the penultimate exon 7, removing 53 amino acids from an important protein domain. This case represents the first synonymous variant and the third pathogenic variant known to date affecting the DHH-associated domain (DHHA2 domain). These findings extend the genotypic and phenotypic spectrums in PRUNE1-related disorders and highlight the importance of considering synonymous splice site variants in atypical presentations.

Diagnostic journeys: characterization of patients and diagnostic outcomes from an academic second opinion clinic

OBJECTIVES

Diagnostic programs and second opinion clinics have grown and evolved in the recent years to help patients with rare, puzzling, and complex conditions who often suffer prolonged diagnostic journeys, but there is a paucity of literature on the clinical characteristics of these patients and the efficacy of these diagnostic programs. This study aims to characterize the diagnostic journey, case features, and diagnostic outcomes of patients referred to a team-based second opinion clinic at Stanford.

METHODS

Retrospective chart review was performed for 237 patients evaluated for diagnostic second opinion in the Stanford Consultative Medicine Clinic over a 5 year period. Descriptive case features and diagnostic outcomes were assessed, and correlation between the two was analyzed.

RESULTS

Sixty-three percent of our patients were women. 49% of patients had a potential precipitating event within about a month prior to the start of their illness, such as medication change, infection, or medical procedure. A single clear diagnosis was determined in 33% of cases, whereas the remaining cases were assessed to have multifactorial contributors/diagnoses (20%) or remained unclear despite extensive evaluation (47%). Shorter duration of illness, fewer prior specialties seen, and single chief symptom were associated with higher likelihood of achieving a single clear diagnosis.

CONCLUSIONS

A single-site academic consultative service can offer additional diagnostic insights for about half of all patients evaluated for puzzling conditions. Better understanding of the clinical patterns and patient experiences gained from this study helps inform strategies to shorten their diagnostic odysseys.

Invertebrate Model Organisms as a Platform to Investigate Rare Human Neurological Diseases

Patients suffering from rare human diseases often go through a painful journey for finding a definite molecular diagnosis prerequisite of appropriate cures. With a novel variant isolated from a single patient, determination of its pathogenicity to end such "diagnostic odyssey" requires multi-step processes involving experts in diverse areas of interest, including clinicians, bioinformaticians and research scientists. Recent efforts in building large-scale genomic databases and in silico prediction platforms have facilitated identification of potentially pathogenic variants causative of rare human diseases of a Mendelian basis. However, the functional significance of individual variants remains elusive in many cases, thus requiring incorporation of versatile and rapid model organism (MO)-based platforms for functional analyses. In this review, the current scope of rare disease research is briefly discussed. In addition, an overview of invertebrate MOs for their key features relevant to rare neurological diseases is provided, with the characteristics of two representative invertebrate MOs, Drosophila melanogaster and Caenorhabditis elegans, as well as the challenges against them. Finally, recently developed research networks integrating these MOs in collaborative research are portraited with an array of bioinformatical analyses embedded. A comprehensive survey of MO-based research activities provided in this review will help us to design a wellstructured analysis of candidate genes or potentially pathogenic variants for their roles in rare neurological diseases in future.

Why rare disease needs precision medicine-and precision medicine needs rare disease

With one in ten suffering from one of 10,000 rare diseases, precision medicine opens a path toward identifying therapies for rare patients. Conversely, it is rare patients—through their collective experience and the knowledge captured in their genetics—who open the path toward identifying therapies for common patients.

Perceived utility and disutility of genomic sequencing for pediatric patients: Perspectives from parents with diverse sociodemographic characteristics

Given the limited therapeutic options for most rare diseases diagnosed through genomic sequencing (GS) and the proportion of patients who remain undiagnosed even after GS, it is important to characterize a broader range of benefits and potential harms of GS from the perspectives of families with diverse sociodemographic characteristics. We recruited parents of children enrolled in the Undiagnosed Diseases Network. Parents completed an in-depth interview, and we conducted a comparative content analysis of the data. Parents (n = 30) were demographically diverse, with 43.3% identifying as Hispanic, 33.3% primarily Spanish-speaking, and widely variable household income and education. Parents reported minimal changes in their child's health status following GS but did report a range of other forms of perceived utility, including improvements in their child's healthcare management and access, in their own psychological well-being, and in disease-specific social connections and research opportunities. Parents who received a diagnosis more frequently perceived utility across all domains; however, disutility also was reported by both those with and without a diagnosis. Impacts depended on multiple mediating factors, including parents' underlying expectations and beliefs, family sociodemographic characteristics, individual disease characteristics, and prior healthcare access. Our study suggests that the perceived utility of GS varies widely among parents and may depend on multiple individual, sociodemographic, and contextual factors that are relevant for pre- and post-GS counseling, for value assessment of GS, and for policymaking related to access to new genomic technologies.

Curation and expansion of Human Phenotype Ontology for defined groups of inborn errors of immunity

BACKGROUND

Accurate, detailed, and standardized phenotypic descriptions are essential to support diagnostic interpretation of genetic variants and to discover new diseases. The Human Phenotype Ontology (HPO), extensively used in rare disease research, provides a rich collection of vocabulary with standardized phenotypic descriptions in a hierarchical structure. However, to date, the use of HPO has not yet been widely implemented in the field of inborn errors of immunity (IEIs), mainly due to a lack of comprehensive IEI-related terms.

OBJECTIVES

We sought to systematically review available terms in HPO for the depiction of IEIs, to expand HPO, yielding more comprehensive sets of terms, and to reannotate IEIs with HPO terms to provide accurate, standardized phenotypic descriptions.

METHODS

We initiated a collaboration involving expert clinicians, geneticists, researchers working on IEIs, and bioinformaticians. Multiple branches of the HPO tree were restructured and extended on the basis of expert review. Our ontology-guided machine learning coupled with a 2-tier expert review was applied to reannotate defined subgroups of IEIs.

RESULTS

We revised and expanded 4 main branches of the HPO tree. Here, we reannotated 73 diseases from 4 International Union of Immunological Societies-defined IEI disease subgroups with HPO terms. We achieved a 4.7-fold increase in the number of phenotypic terms per disease. Given the new HPO annotations, we demonstrated improved ability to computationally match selected IEI cases to their known diagnosis, and improved phenotype-driven disease classification.

CONCLUSIONS

Our targeted expansion and reannotation presents enhanced precision of disease annotation, will enable superior HPO-based IEI characterization, and hence benefit both IEI diagnostic and research activities.

Patients as Partners in Rare Disease Diagnosis and Research

There is great value in understanding the patient perspective in rare disease diagnosis and research, and in partnering actively with patients and their families throughout the process. Meaningful and respectful interaction between patients and researchers leads to learning on both sides, and ultimately, to better research outcomes. Researchers can help patients understand how research is conducted and what the latest advances and perceived gaps in research are, and patients, who have direct experience living with their health conditions, can impart to researchers what is most important to them. We describe our engagement with patients in the Undiagnosed Diseases Network (UDN) program, as well as the lessons we have learned to date. In the UDN, patients have been instrumental in bringing meaning to the work of clinicians and researchers, building patient communities, making the network aware of unmet patient needs, advocating for additional research funding, and disseminating UDN research findings. Although patient engagement in the UDN has already had a significant positive impact on our work, we continue to strive to involve patients earlier in the process, in the research design itself, and in addressing power dynamics that may arise between clinicians, researchers, and patients.

Identifying digenic disease genes via machine learning in the Undiagnosed Diseases Network

Rare diseases affect millions of people worldwide, and discovering their genetic causes is challenging. More than half of the individuals analyzed by the Undiagnosed Diseases Network (UDN) remain undiagnosed. The central hypothesis of this work is that many of these rare genetic disorders are caused by multiple variants in more than one gene. However, given the large number of variants in each individual genome, experimentally evaluating combinations of variants for potential to cause disease is currently infeasible. To address this challenge, we developed the digenic predictor (DiGePred), a random forest classifier for identifying candidate digenic disease gene pairs by features derived from biological networks, genomics, evolutionary history, and functional annotations. We trained the DiGePred classifier by using DIDA, the largest available database of known digenic-disease-causing gene pairs, and several sets of non-digenic gene pairs, including variant pairs derived from unaffected relatives of UDN individuals. DiGePred achieved high precision and recall in cross-validation and on a held-out test set (PR area under the curve > 77%), and we further demonstrate its utility by using digenic pairs from the recent literature. In contrast to other approaches, DiGePred also appropriately controls the number of false positives when applied in realistic clinical settings. Finally, to enable the rapid screening of variant gene pairs for digenic disease potential, we freely provide the predictions of DiGePred on all human gene pairs. Our work enables the discovery of genetic causes for rare non-monogenic diseases by providing a means to rapidly evaluate variant gene pairs for the potential to cause digenic disease.

Advances in mouse genetics for the study of human disease

The mouse is the pre-eminent model organism for studies of mammalian gene function and has provided an extraordinarily rich range of insights into basic genetic mechanisms and biological systems. Over several decades, the characterization of mouse mutants has illuminated the relationship between gene and phenotype, providing transformational insights into the genetic bases of disease. However, if we are to deliver the promise of genomic and precision medicine, we must develop a comprehensive catalogue of mammalian gene function that uncovers the dark genome and elucidates pleiotropy. Advances in large-scale mouse mutagenesis programmes allied to high-throughput mouse phenomics are now addressing this challenge and systematically revealing novel gene function and multi-morbidities. Alongside the development of these pan-genomic mutational resources, mouse genetics is employing a range of diversity resources to delineate gene-gene and gene-environment interactions and to explore genetic context. Critically, mouse genetics is a powerful tool for assessing the functional impact of human genetic variation and determining the causal relationship between variant and disease. Together these approaches provide unique opportunities to dissect in vivo mechanisms and systems to understand pathophysiology and disease. Moreover, the provision and utility of mouse models of disease has flourished and engages cumulatively at numerous points across the translational spectrum from basic mechanistic studies to pre-clinical studies, target discovery and therapeutic development.

Functional analysis of a de novo variant in the neurodevelopment and generalized epilepsy disease gene NBEA

Neurobeachin (NBEA) was initially identified as a candidate gene for autism. Recently, variants in NBEA have been associated with neurodevelopmental delay and childhood epilepsy. Here, we report on a novel NBEA missense variant (c.5899G > A, p.Gly1967Arg) in the Domain of Unknown Function 1088 (DUF1088) identified in a child enrolled in the Undiagnosed Diseases Network (UDN), who presented with neurodevelopmental delay and seizures. Modeling of this variant in the Caenorhabditis elegans NBEA ortholog, sel-2, indicated that the variant was damaging to in vivo function as evidenced by altered cell fate determination and trafficking of potassium channels in neurons. The variant effect was indistinguishable from that of the reference null mutation suggesting that the variant is a strong hypomorph or a complete loss-of-function. Our experimental data provide strong support for the molecular diagnosis and pathogenicity of the NBEA p.Gly1967Arg variant and the importance of the DUF1088 for NBEA function.

A scalable Drosophila assay for clinical interpretation of human PTEN variants in suppression of PI3K/AKT induced cellular proliferation

Gene variant discovery is becoming routine, but it remains difficult to usefully interpret the functional consequence or disease relevance of most variants. To fill this interpretation gap, experimental assays of variant function are becoming common place. Yet, it remains challenging to make these assays reproducible, scalable to high numbers of variants, and capable of assessing defined gene-disease mechanism for clinical interpretation aligned to the ClinGen Sequence Variant Interpretation (SVI) Working Group guidelines for 'well-established assays'. Drosophila melanogaster offers great potential as an assay platform, but was untested for high numbers of human variants adherent to these guidelines. Here, we wished to test the utility of Drosophila as a platform for scalable well-established assays. We took a genetic interaction approach to test the function of ~100 human PTEN variants in cancer-relevant suppression of PI3K/AKT signaling in cellular growth and proliferation. We validated the assay using biochemically characterized PTEN mutants as well as 23 total known pathogenic and benign PTEN variants, all of which the assay correctly assigned into predicted functional categories. Additionally, function calls for these variants correlated very well with our recent published data from a human cell line. Finally, using these pathogenic and benign variants to calibrate the assay, we could set readout thresholds for clinical interpretation of the pathogenicity of 70 other PTEN variants. Overall, we demonstrate that Drosophila offers a powerful assay platform for clinical variant interpretation, that can be used in conjunction with other well-established assays, to increase confidence in the accurate assessment of variant function and pathogenicity.

Finding commonalities in rare diseases through the undiagnosed diseases network

Objective

When studying any specific rare disease, heterogeneity and scarcity of affected individuals has historically hindered investigators from discerning on what to focus to understand and diagnose a disease. New nongenomic methodologies must be developed that identify similarities in seemingly dissimilar conditions.

Materials and Methods

This observational study analyzes 1042 patients from the Undiagnosed Diseases Network (2015-2019), a multicenter, nationwide research study using phenotypic data annotated by specialized staff using Human Phenotype Ontology terms. We used Louvain community detection to cluster patients linked by Jaccard pairwise similarity and 2 support vector classifier to assign new cases. We further validated the clusters’ most representative comorbidities using a national claims database (67 million patients).

Results

Patients were divided into 2 groups: those with symptom onset before 18 years of age (n = 810) and at 18 years of age or older (n = 232) (average symptom onset age: 10 [interquartile range, 0-14] years). For 810 pediatric patients, we identified 4 statistically significant clusters. Two clusters were characterized by growth disorders, and developmental delay enriched for hypotonia presented a higher likelihood of diagnosis. Support vector classifier showed 0.89 balanced accuracy (0.83 for Human Phenotype Ontology terms only) on test data.

Discussions

To set the framework for future discovery, we chose as our endpoint the successful grouping of patients by phenotypic similarity and provide a classification tool to assign new patients to those clusters.

Conclusion

This study shows that despite the scarcity and heterogeneity of patients, we can still find commonalities that can potentially be harnessed to uncover new insights and targets for therapy.

Model organisms contribute to diagnosis and discovery in the undiagnosed diseases network: current state and a future vision

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.

A resource of lipidomics and metabolomics data from individuals with undiagnosed diseases

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.

The Increasing Impact of Translational Research in the Molecular Diagnostics of Neuromuscular Diseases

The diagnosis of neuromuscular diseases (NMDs) has been progressively evolving from the grouping of clinical symptoms and signs towards the molecular definition. Optimal clinical, biochemical, electrophysiological, electrophysiological, and histopathological characterization is very helpful to achieve molecular diagnosis, which is essential for establishing prognosis, treatment and genetic counselling. Currently, the genetic approach includes both the gene-targeted analysis in specific clinically recognizable diseases, as well as genomic analysis based on next-generation sequencing, analyzing either the clinical exome/genome or the whole exome or genome. However, as of today, there are still many patients in whom the causative genetic variant cannot be definitely established and variants of uncertain significance are often found. In this review, we address these drawbacks by incorporating two additional biological omics approaches into the molecular diagnostic process of NMDs. First, functional genomics by introducing experimental cell and molecular biology to analyze and validate the variant for its biological effect in an in-house translational diagnostic program, and second, incorporating a multi-omics approach including RNA-seq, metabolomics, and proteomics in the molecular diagnosis of neuromuscular disease. Both translational diagnostics programs and omics are being implemented as part of the diagnostic process in academic centers and referral hospitals and, therefore, an increase in the proportion of neuromuscular patients with a molecular diagnosis is expected. This improvement in the process and diagnostic performance of patients will allow solving aspects of their health problems in a precise way and will allow them and their families to take a step forward in their lives.

A state-based approach to genomics for rare disease and population screening

PURPOSE

The Alabama Genomic Health Initiative (AGHI) is a state-funded effort to provide genomic testing. AGHI engages two distinct cohorts across the state of Alabama. One cohort includes children and adults with undiagnosed rare disease; a second includes an unselected adult population. Here we describe findings from the first 176 rare disease and 5369 population cohort AGHI participants.

METHODS

AGHI participants enroll in one of two arms of a research protocol that provides access to genomic testing results and biobank participation. Rare disease cohort participants receive genome sequencing to identify primary and secondary findings. Population cohort participants receive genotyping to identify pathogenic and likely pathogenic variants for actionable conditions.

RESULTS

Within the rare disease cohort, genome sequencing identified likely pathogenic or pathogenic variation in 20% of affected individuals. Within the population cohort, 1.5% of individuals received a positive genotyping result. The rate of genotyping results corroborated by reported personal or family history varied by gene.

CONCLUSIONS

AGHI demonstrates the ability to provide useful health information in two contexts: rare undiagnosed disease and population screening. This utility should motivate continued exploration of ways in which emerging genomic technologies might benefit broad populations.