Genetic Modifiers and Rare Mendelian Disease

Functional analysis of cell lines derived from SMAD3-related Loeys-Dietz syndrome patients provides insights into genotype-phenotype relation

RATIONALE

Pathogenic (P)/likely pathogenic (LP) SMAD3 variants cause Loeys-Dietz syndrome type 3 (LDS3), which is characterized by arterial aneurysms, dissections and tortuosity throughout the vascular system combined with osteoarthritis.

OBJECTIVES

Investigate the impact of P/LP SMAD3 variants with functional tests on patient-derived fibroblasts and vascular smooth muscle cells (VSMCs), to optimize interpretation of SMAD3 variants.

METHODS

A retrospective analysis on clinical data from individuals with a P/LP SMAD3 variant and functional analyses on SMAD3 patient-derived VSMCs and SMAD3 patient-derived fibroblasts, differentiated into myofibroblasts.

RESULTS

Individuals with dominant negative (DN) SMAD3 variant in the MH2 domain exhibited more major events (66.7% vs. 44.0%, P = 0.054), occurring at a younger age compared to those with haploinsufficient (HI) variants. The age at first major event was 35.0 years [IQR 29.0-47.0] in individuals with DN variants in MH2, compared to 46.0 years [IQR 40.0-54.0] in those with HI variants (P = 0.065). Fibroblasts carrying DN SMAD3 variants displayed reduced differentiation potential, contrasting with increased differentiation potential in HI SMAD3 variant fibroblasts. HI SMAD3 variant VSMCs showed elevated SMA expression and altered expression of alternative MYH11 isoforms. DN SMAD3 variant myofibroblasts demonstrated reduced extracellular matrix formation compared to control cell lines.

CONCLUSION

Distinguishing between P/LP HI and DN SMAD3 variants can be achieved by assessing differentiation potential, and SMA and MYH11 expression. The differences between DN and HI SMAD3 variant fibroblasts and VSMCs potentially contribute to the differences in disease manifestation. Notably, myofibroblast differentiation seems a suitable alternative in vitro test system compared to VSMCs.

Expanded phenotype and cancer risk in patients with Beckwith-Wiedemann spectrum caused by CDKN1C variants

Beckwith-Wiedemann spectrum (BWSp) is caused by genetic and epigenetic alterations on chromosome 11 that regulate cell growth and division. Considering the diverse phenotypic landscape in BWSp, the characterization of the CDKN1C molecular subtype remains relatively limited. Here, we investigate the role of CDKN1C in the broader BWSp phenotype. Notably, patients with CDKN1C variants appear to exhibit a different tumor risk than other BWSp molecular subtypes. We performed a comprehensive literature review using the search term "CDKN1C Beckwith" to identify 113 cases of patients with molecularly confirmed CDKN1C-BWSp. We then assessed the genotype and phenotype in a novel cohort of patients with CDKN1C-BWSp enrolled in the BWS Research Registry. Cardinal and suggestive features were evaluated for all patients reported, and tumor risk was established based on available reports. The most common phenotypes included macroglossia, omphalocele, and ear creases/pits. Tumor types reported from the literature included neuroblastoma, acute lymphocytic leukemia, superficial spreading melanoma, and intratubular germ cell neoplasia. Overall, this study identifies unique features associated with CDKN1C variants in BWSp, enabling more accurate clinical management. The absence of Wilms tumor and hepatoblastoma suggests that screening for these tumors may not be necessary, while the neuroblastoma risk warrants appropriate screening recommendations.

Development of multiplexed orthogonal base editor (MOBE) systems

Base editors (BEs) enable efficient, programmable installation of point mutations while avoiding the use of double-strand breaks. Simultaneous application of two or more different BEs, such as an adenine BE (which converts A·T base pairs to G·C) and a cytosine BE (which converts C·G base pairs to T·A), is not feasible because guide RNA crosstalk results in non-orthogonal editing, with all BEs modifying all target loci. Here we engineer both adenine BEs and cytosine BEs that can be orthogonally multiplexed by using RNA aptamer-coat protein systems to recruit the DNA-modifying enzymes directly to the guide RNAs. We generate four multiplexed orthogonal BE systems that enable rates of precise co-occurring edits of up to 7.1% in the same DNA strand without enrichment or selection strategies. The addition of a fluorescent enrichment strategy increases co-occurring edit rates up to 24.8% in human cells. These systems are compatible with expanded protospacer adjacent motif and high-fidelity Cas9 variants, function well in multiple cell types, have equivalent or reduced off-target propensities compared with their parental systems and can model disease-relevant point mutation combinations.

Atypical Diabetes: What Have We Learned and What Does the Future Hold?

As our understanding of the pathophysiology of diabetes evolves, we increasingly recognize that many patients may have a form of diabetes that does not neatly fit with a diagnosis of either type 1 or type 2 diabetes. The discovery and description of these forms of "atypical diabetes" have led to major contributions to our collective understanding of the basic biology that drives insulin secretion, insulin resistance, and islet autoimmunity. These discoveries now pave the way to a better classification of diabetes based on distinct endotypes. In this review, we highlight the key biological and clinical insights that can be gained from studying known forms of atypical diabetes. Additionally, we provide a framework for identification of patients with atypical diabetes based on their clinical, metabolic, and molecular features. Helpful clinical and genetic resources for evaluating patients suspected of having atypical diabetes are provided. Therefore, appreciating the various endotypes associated with atypical diabetes will enhance diagnostic accuracy and facilitate targeted treatment decisions.

Functional prediction of the potential NGLY1 mutations associated with rare disease CDG

Genetic diseases are currently diagnosed by functional mutations. However, only some mutations are associated with disease. It is necessary to establish a quick prediction model for clinical screening. Pathogenic mutations in NGLY1 cause a rare autosomal recessive disease known as congenital disorder of deglycosylation (NGLY1-CDDG). Although NGLY1-CDDG can be diagnosed through gene sequencing, clinical relevance of a detected mutation in NGLY1 needs to be further confirmed. In this study, taken NGLY1-CDDG as an example, a comprehensive and practical predictive model for pathogenic mutations on NGLY1 through an NGLY1/Glycopeptide complex model was constructed, the binding sites of NGLY1 and glycopeptides were simulated, and an in vitro enzymatic assay system was established to facilitate quick clinical decisions for NGLY1-CDDG patients. The docking model covers 42 % of reported NGLY1-CDDG missense mutations (5/12). All reported mutations were subjected to in vitro enzymatic assay in which 18 mutations were dysfunctional (18/30). In addition, a full spectrum of functional R328 mutations was assayed and 11 mutations were dysfunctional (11/19). In this study, a model of NGLY1 and glycopeptides was built for potential functional mutations in NGLY1. In addition, the effect of potential regulatory compounds, including N-acetyl-l-cysteine and dithiothreitol, on NGLY1 was examined. The established in vitro assay may serve as a standard protocol to facilitate rapid diagnosis of all mutations in NGLY1-CDDG. This method could also be applied as a comprehensive and practical predictive model for the other rare genetic diseases.

The Influence of a Genetic Variant in CCDC78 on LMNA-Associated Skeletal Muscle Disease

Mutations in the LMNA gene-encoding A-type lamins can cause Limb-Girdle muscular dystrophy Type 1B (LGMD1B). This disease presents with weakness and wasting of the proximal skeletal muscles and has a variable age of onset and disease severity. This variability has been attributed to genetic background differences among individuals; however, such variants have not been well characterized. To identify such variants, we investigated a multigeneration family in which affected individuals are diagnosed with LGMD1B. The primary genetic cause of LGMD1B in this family is a dominant mutation that activates a cryptic splice site, leading to a five-nucleotide deletion in the mature mRNA. This results in a frame shift and a premature stop in translation. Skeletal muscle biopsies from the family members showed dystrophic features of variable severity, with the muscle fibers of some family members possessing cores, regions of sarcomeric disruption, and a paucity of mitochondria, not commonly associated with LGMD1B. Using whole genome sequencing (WGS), we identified 21 DNA sequence variants that segregate with the family members possessing more profound dystrophic features and muscle cores. These include a relatively common variant in coiled-coil domain containing protein 78 (CCDC78). This variant was given priority because another mutation in CCDC78 causes autosomal dominant centronuclear myopathy-4, which causes cores in addition to centrally positioned nuclei. Therefore, we analyzed muscle biopsies from family members and discovered that those with both the LMNA mutation and the CCDC78 variant contain muscle cores that accumulated both CCDC78 and RyR1. Muscle cores containing mislocalized CCDC78 and RyR1 were absent in the less profoundly affected family members possessing only the LMNA mutation. Taken together, our findings suggest that a relatively common variant in CCDC78 can impart profound muscle pathology in combination with a LMNA mutation and accounts for variability in skeletal muscle disease phenotypes.

Sterol O-Acyltransferase 1 (SOAT1): A Genetic Modifier of Niemann-Pick Disease, Type C1

Niemann-Pick disease type C1 (NPC1) is a lysosomal disorder due to impaired intracellular cholesterol transport out of the endolysosomal compartment.. Marked heterogeneity has been observed in individuals with the same NPC1 genotype, thus suggesting a significant effect of modifier genes. Prior work demonstrated that decreased SOAT1 activity decreased disease severity in an NPC1 mouse model. Thus, we hypothesized that a polymorphism associated with decreased SOAT1 expression might influence the NPC1 phenotype. Phenotyping and genomic sequencing of 117 individuals with NPC1 was performed as part of a Natural History trial. Phenotyping included determination of disease severity and disease burden. Significant clinical heterogeneity is present in individuals homozygous for the NPC1I1061T variant and in siblings. Analysis of the SOAT1 polymorphism, rs1044925 (A>C), showed a significant association of the C-allele with earlier age of neurological onset. The C-allele may be associated with a higher Annualized Severity Index Score as well as increased frequency of liver disease and seizures. A polymorphism associated with decreased expression of SOAT1 appears to be a genetic modifier of the NPC1 phenotype. This finding is consistent with prior data showing decreased phenotypic severity in Npc1-/-:Soat1-/- mice and supports efforts to investigate the potential of SOAT1 inhibitors as a potential therapy for NPC1.

Pleiotropy, epistasis and the genetic architecture of quantitative traits

Pleiotropy (whereby one genetic polymorphism affects multiple traits) and epistasis (whereby non-linear interactions between genetic polymorphisms affect the same trait) are fundamental aspects of the genetic architecture of quantitative traits. Recent advances in the ability to characterize the effects of polymorphic variants on molecular and organismal phenotypes in human and model organism populations have revealed the prevalence of pleiotropy and unexpected shared molecular genetic bases among quantitative traits, including diseases. By contrast, epistasis is common between polymorphic loci associated with quantitative traits in model organisms, such that alleles at one locus have different effects in different genetic backgrounds, but is rarely observed for human quantitative traits and common diseases. Here, we review the concepts and recent inferences about pleiotropy and epistasis, and discuss factors that contribute to similarities and differences between the genetic architecture of quantitative traits in model organisms and humans.

CRISPR-Based Gene Editing Techniques in Pediatric Neurological Disorders

The emergence of gene editing technologies offers a unique opportunity to develop mutation-specific treatments for pediatric neurological disorders. Gene editing systems can potentially alter disease trajectory by correcting dysfunctional mutations or therapeutically altering gene expression. Clustered regularly interspaced short palindromic repeats (CRISPR)-based approaches are attractive gene therapy platforms to personalize treatments because of their specificity, ease of design, versatility, and cost. However, many such approaches remain in the early stages of development, with ongoing efforts to optimize editing efficiency, minimize unintended off-target effects, and mitigate pathologic immune responses. Given the rapid evolution of CRISPR-based therapies, it is prudent for the clinically based child neurologist to have a conceptual understanding of what such therapies may entail, including both benefits and risks and how such therapies may be clinically applied. In this review, we describe the fundamentals of CRISPR-based therapies, discuss the opportunities and challenges that have arisen, and highlight preclinical work in several pediatric neurological diseases.

Single variant, yet "double trouble": TSC and KBG syndrome because of a large de novo inversion

Despite the advances in high-throughput sequencing, many rare disease patients remain undiagnosed. In particular, the patients with well-defined clinical phenotypes and established clinical diagnosis, yet missing or partial genetic diagnosis, may hold a clue to more complex genetic mechanisms of a disease that could be missed by available clinical tests. Here, we report a patient with a clinical diagnosis of Tuberous sclerosis, combined with unusual secondary features, but negative clinical tests including TSC1 and TSC2 Short-read whole-genome sequencing combined with advanced bioinformatics analyses were successful in uncovering a de novo pericentric 87-Mb inversion with breakpoints in TSC2 and ANKRD11, which explains the TSC clinical diagnosis, and confirms a second underlying monogenic disorder, KBG syndrome. Our findings illustrate how complex variants, such as large inversions, may be missed by clinical tests and further highlight the importance of well-defined clinical diagnoses in uncovering complex molecular mechanisms of a disease, such as complex variants and "double trouble" effects.

Implementing Whole Genome Sequencing (WGS) in Clinical Practice: Advantages, Challenges, and Future Perspectives

The integration of whole genome sequencing (WGS) into all aspects of modern medicine represents the next step in the evolution of healthcare. Using this technology, scientists and physicians can observe the entire human genome comprehensively, generating a plethora of new sequencing data. Modern computational analysis entails advanced algorithms for variant detection, as well as complex models for classification. Data science and machine learning play a crucial role in the processing and interpretation of results, using enormous databases and statistics to discover new and support current genotype-phenotype correlations. In clinical practice, this technology has greatly enabled the development of personalized medicine, approaching each patient individually and in accordance with their genetic and biochemical profile. The most propulsive areas include rare disease genomics, oncogenomics, pharmacogenomics, neonatal screening, and infectious disease genomics. Another crucial application of WGS lies in the field of multi-omics, working towards the complete integration of human biomolecular data. Further technological development of sequencing technologies has led to the birth of third and fourth-generation sequencing, which include long-read sequencing, single-cell genomics, and nanopore sequencing. These technologies, alongside their continued implementation into medical research and practice, show great promise for the future of the field of medicine.

CHD7 and SOX2 act in a common gene regulatory network during mammalian semicircular canal and cochlear development

Inner ear morphogenesis requires tightly regulated epigenetic and transcriptional control of gene expression. CHD7, an ATP-dependent chromodomain helicase DNA-binding protein, and SOX2, an SRY-related HMG box pioneer transcription factor, are known to contribute to vestibular and auditory system development, but their genetic interactions in the ear have not been explored. Here, we analyzed inner ear development and the transcriptional regulatory landscapes in mice with variable dosages of Chd7 and/or Sox2. We show that combined haploinsufficiency for Chd7 and Sox2 results in reduced otic cell proliferation, severe malformations of semicircular canals, and shortened cochleae with ectopic hair cells. Examination of mice with conditional, inducible Chd7 loss by Sox2CreER reveals a critical period (~E9.5) of susceptibility in the inner ear to combined Chd7 and Sox2 loss. Data from genome-wide RNA-sequencing and CUT&Tag studies in the otocyst show that CHD7 regulates Sox2 expression and acts early in a gene regulatory network to control expression of key otic patterning genes, including Pax2 and Otx2. CHD7 and SOX2 directly bind independently and cooperatively at transcription start sites and enhancers to regulate otic progenitor cell gene expression. Together, our findings reveal essential roles for Chd7 and Sox2 in early inner ear development and may be applicable for syndromic and other forms of hearing or balance disorders.

GPAD: a natural language processing-based application to extract the gene-disease association discovery information from OMIM

BACKGROUND

Thousands of genes have been associated with different Mendelian conditions. One of the valuable sources to track these gene-disease associations (GDAs) is the Online Mendelian Inheritance in Man (OMIM) database. However, most of the information in OMIM is textual, and heterogeneous (e.g. summarized by different experts), which complicates automated reading and understanding of the data. Here, we used Natural Language Processing (NLP) to make a tool (Gene-Phenotype Association Discovery (GPAD)) that could syntactically process OMIM text and extract the data of interest.

RESULTS

GPAD applies a series of language-based techniques to the text obtained from OMIM API to extract GDA discovery-related information. GPAD can inform when a particular gene was associated with a specific phenotype, as well as the type of validation-whether through model organisms or cohort-based patient-matching approaches-for such an association. GPAD extracted data was validated with published reports and was compared with large language model. Utilizing GPAD's extracted data, we analysed trends in GDA discoveries, noting a significant increase in their rate after the introduction of exome sequencing, rising from an average of about 150-250 discoveries each year. Contrary to hopes of resolving most GDAs for Mendelian disorders by now, our data indicate a substantial decline in discovery rates over the past five years (2017-2022). This decline appears to be linked to the increasing necessity for larger cohorts to substantiate GDAs. The rising use of zebrafish and Drosophila as model organisms in providing evidential support for GDAs is also observed.

CONCLUSIONS

GPAD's real-time analyzing capacity offers an up-to-date view of GDA discovery and could help in planning and managing the research strategies. In future, this solution can be extended or modified to capture other information in OMIM and scientific literature.

Drug Repurposing and Lysosomal Storage Disorders: A Trick to Treat

Rare diseases, or orphan diseases, are defined as diseases affecting a small number of people compared to the general population. Among these, we find lysosomal storage disorders (LSDs), a cluster of rare metabolic diseases characterized by enzyme mutations causing abnormal glycolipid storage. Drug repositioning involves repurposing existing approved drugs for new therapeutic applications, offering advantages in cost, time savings, and a lower risk of failure. We present a comprehensive analysis of existing drugs, their repurposing potential, and their clinical implications in the context of LSDs, highlighting the necessity of mutation-specific approaches. Our review systematically explores the landscape of drug repositioning as a means to enhance LSDs therapies. The findings advocate for the strategic repositioning of drugs, accentuating its role in expediting the discovery of effective treatments. We conclude that drug repurposing represents a viable pathway for accelerating therapeutic discovery for LSDs, emphasizing the need for the careful evaluation of drug efficacy and toxicity in disease-specific contexts.

Brain function in classic galactosemia, a galactosemia network (GalNet) members review

Classic galactosemia (CG, OMIM #230400, ORPHA: 79,239) is a hereditary disorder of galactose metabolism that, despite treatment with galactose restriction, affects brain function in 85% of the patients. Problems with cognitive function, neuropsychological/social emotional difficulties, neurological symptoms, and abnormalities in neuroimaging and electrophysiological assessments are frequently reported in this group of patients, with an enormous individual variability. In this review, we describe the role of impaired galactose metabolism on brain dysfunction based on state of the art knowledge. Several proposed disease mechanisms are discussed, as well as the time of damage and potential treatment options. Furthermore, we combine data from longitudinal, cross-sectional and retrospective studies with the observations of specialist teams treating this disease to depict the brain disease course over time. Based on current data and insights, the majority of patients do not exhibit cognitive decline. A subset of patients, often with early onset cerebral and cerebellar volume loss, can nevertheless experience neurological worsening. While a large number of patients with CG suffer from anxiety and depression, the increased complaints about memory loss, anxiety and depression at an older age are likely multifactorial in origin.

A Retrospective Longitudinal Study of 460 Patients with ABCA4-Associated Retinal Disease

PURPOSE

To investigate the distribution of genotypes and natural history of ABCA4-associated retinal disease in a large cohort of patients seen at a single institution.

DESIGN

Retrospective, single-institution cohort review.

PARTICIPANTS

Patients seen at the University of Iowa between November 1986 and August 2022 clinically suspected to have disease caused by sequence variations in ABCA4.

METHODS

DNA samples from participants were subjected to a tiered testing strategy progressing from allele-specific screening to whole genome sequencing. Charts were reviewed, and clinical data were tabulated. The pathogenic severity of the most common alleles was estimated by studying groups of patients who shared 1 allele. Groups of patients with shared genotypes were reviewed for evidence of modifying factor effects.

MAIN OUTCOME MEASURES

Age at first uncorrectable vision loss, best-corrected visual acuity, and the area of the I2e isopter of the Goldmann visual field.

RESULTS

A total of 460 patients from 390 families demonstrated convincing clinical features of ABCA4-associated retinal disease. Complete genotypes were identified in 399 patients, and partial genotypes were identified in 61. The median age at first vision loss was 16 years (range, 4-76 years). Two hundred sixty-five families (68%) harbored a unique genotype, and no more than 10 patients shared any single genotype. Review of the patients with shared genotypes revealed evidence of modifying factors that in several cases resulted in a > 15-year difference in age at first vision loss. Two hundred forty-one different alleles were identified among the members of this cohort, and 161 of these (67%) were found in only a single individual.

CONCLUSIONS

ABCA4-associated retinal disease ranges from a very severe photoreceptor disease with an onset before 5 years of age to a late-onset retinal pigment epithelium-based condition resembling pattern dystrophy. Modifying factors frequently impact the ABCA4 disease phenotype to a degree that is similar in magnitude to the detectable ABCA4 alleles themselves. It is likely that most patients in any cohort will harbor a unique genotype. The latter observations taken together suggest that patients' clinical findings in most cases will be more useful for predicting their clinical course than their genotype.

FINANCIAL DISCLOSURE(S)

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Inherited Retinal Degeneration Caused by Dehydrodolichyl Diphosphate Synthase Mutation-Effect of an ALG6 Modifier Variant

Modern advances in disease genetics have uncovered numerous modifier genes that play a role in the severity of disease expression. One such class of genetic conditions is known as inherited retinal degenerations (IRDs), a collection of retinal degenerative disorders caused by mutations in over 300 genes. A single missense mutation (K42E) in the gene encoding the enzyme dehydrodolichyl diphosphate synthase (DHDDS), which is required for protein N-glycosylation in all cells and tissues, causes DHDDS-IRD (retinitis pigmentosa type 59 (RP59; OMIM #613861)). Apart from a retinal phenotype, however, DHDDS-IRD is surprisingly non-syndromic (i.e., without any systemic manifestations). To explore disease pathology, we selected five glycosylation-related genes for analysis that are suggested to have disease modifier variants. These genes encode glycosyltransferases (ALG6, ALG8), an ER resident protein (DDOST), a high-mannose oligosaccharyl transferase (MPDU1), and a protein N-glycosylation regulatory protein (TNKS). DNA samples from 11 confirmed DHDDS (K42E)-IRD patients were sequenced at the site of each candidate genetic modifier. Quantitative measures of retinal structure and function were performed across five decades of life by evaluating foveal photoreceptor thickness, visual acuity, foveal sensitivity, macular and extramacular rod sensitivity, and kinetic visual field extent. The ALG6 variant, (F304S), was correlated with greater macular cone disease severity and less peripheral rod disease severity. Thus, modifier gene polymorphisms may account for a significant portion of phenotypic variation observed in human genetic disease. However, the consequences of the polymorphisms may be counterintuitively complex in terms of rod and cone populations affected in different regions of the retina.

Functional analysis of germline VANGL2 variants using rescue assays of vangl2 knockout zebrafish

Developmental studies have shown that the evolutionarily conserved Wnt Planar Cell Polarity (PCP) pathway is essential for the development of a diverse range of tissues and organs including the brain, spinal cord, heart and sensory organs, as well as establishment of the left-right body axis. Germline mutations in the highly conserved PCP gene VANGL2 in humans have only been associated with central nervous system malformations, and functional testing to understand variant impact has not been performed. Here we report three new families with missense variants in VANGL2 associated with heterotaxy and congenital heart disease p.(Arg169His), non-syndromic hearing loss p.(Glu465Ala) and congenital heart disease with brain defects p.(Arg135Trp). To test the in vivo impact of these and previously described variants, we have established clinically-relevant assays using mRNA rescue of the vangl2 mutant zebrafish. We show that all variants disrupt Vangl2 function, although to different extents and depending on the developmental process. We also begin to identify that different VANGL2 missense variants may be haploinsufficient and discuss evidence in support of pathogenicity. Together, this study demonstrates that zebrafish present a suitable pipeline to investigate variants of unknown significance and suggests new avenues for investigation of the different developmental contexts of VANGL2 function that are clinically meaningful.

Integration of multi-omics technologies for molecular diagnosis in ataxia patients

Background: Episodic ataxias are rare neurological disorders characterized by recurring episodes of imbalance and coordination difficulties. Obtaining definitive molecular diagnoses poses challenges, as clinical presentation is highly heterogeneous, and literature on the underlying genetics is limited. While the advent of high-throughput sequencing technologies has significantly contributed to Mendelian disorders genetics, interpretation of variants of uncertain significance and other limitations inherent to individual methods still leaves many patients undiagnosed. This study aimed to investigate the utility of multi-omics for the identification and validation of molecular candidates in a cohort of complex cases of ataxia with episodic presentation. Methods: Eight patients lacking molecular diagnosis despite extensive clinical examination were recruited following standard genetic testing. Whole genome and RNA sequencing were performed on samples isolated from peripheral blood mononuclear cells. Integration of expression and splicing data facilitated genomic variants prioritization. Subsequently, long-read sequencing played a crucial role in the validation of those candidate variants. Results: Whole genome sequencing uncovered pathogenic variants in four genes (SPG7, ATXN2, ELOVL4, PMPCB). A missense and a nonsense variant, both previously reported as likely pathogenic, configured in trans in individual #1 (SPG7: c.2228T>C/p.I743T, c.1861C>T/p.Q621*). An ATXN2 microsatellite expansion (CAG32) in another late-onset case. In two separate individuals, intronic variants near splice sites (ELOVL4: c.541 + 5G>A; PMPCB: c.1154 + 5G>C) were predicted to induce loss-of-function splicing, but had never been reported as disease-causing. Long-read sequencing confirmed the compound heterozygous variants configuration, repeat expansion length, as well as splicing landscape for those pathogenic variants. A potential genetic modifier of the ATXN2 expansion was discovered in ZFYVE26 (c.3022C>T/p.R1008*). Conclusion: Despite failure to identify pathogenic variants through clinical genetic testing, the multi-omics approach enabled the molecular diagnosis in 50% of patients, also giving valuable insights for variant prioritization in remaining cases. The findings demonstrate the value of long-read sequencing for the validation of candidate variants in various scenarios. Our study demonstrates the effectiveness of leveraging complementary omics technologies to unravel the underlying genetics in patients with unresolved rare diseases such as ataxia. Molecular diagnoses not only hold significant promise in improving patient care management, but also alleviates the burden of diagnostic odysseys, more broadly enhancing quality of life.

A novel homozygote nonsense variant of MSH4 leads to primary ovarian insufficiency and non-obstructive azoospermia

BACKGROUND

Both non-obstructive azoospermia (NOA) and primary ovarian insufficiency (POI) are pathological conditions characterized by premature and frequently complete gametogenesis failure. Considering that the conserved meiosis I steps are the same between oogenesis and spermatogenesis, inherited defects in meiosis I may result in common causes for both POI and NOA. The present research is a retrospective investigation on an Iranian family with four siblings of both genders who were affected by primary gonadal failure.

METHODS

Proband, an individual with NOA, was subjected to clinical examination, hormonal assessment, and genetic consultation. After reviewing the medical history of other infertile members of the family, patients with NOA went through genetic investigations including karyotyping and assessment of Y chromosome microdeletions, followed by Whole exome sequencing (WES) on the proband. After analyzing WES data, the candidate variant was validated using Sanger sequencing and traced in the family.

RESULTS

WES analysis of the proband uncovered a novel homozygote nonsense variant, namely c.118C>T in MSH4. This variant resulted in the occurrence of a premature stop codon in residue 40 of MSH4. Notably, the variant was absent in all public exome databases and in the exome data of 400 fertile Iranian individuals. Additionally, the variant was found to co-segregate with infertility in the family. It was also observed that all affected members had homozygous mutations, while their parents were heterozygous and the fertile sister had no mutant allele, corresponding to autosomal recessive inheritance. In addition, we conducted a review of variants reported so far in MSH4, as well as available clinical features related to these variants. The results show that the testicular sperm retrieval and ovarian stimulation cycles have not been successful yet.

CONCLUSION

Overall, the results of this study indicate that the identification of pathogenic variants in this gene will be beneficial in selecting proper therapeutic strategies. Also, the findings of this study demonstrate that clinicians should obtain the history of other family members of the opposite sex when diagnosing for POI and/or NOA.

A multi-layered network model identifies Akt1 as a common modulator of neurodegeneration

The accumulation of misfolded and aggregated proteins is a hallmark of neurodegenerative proteinopathies. Although multiple genetic loci have been associated with specific neurodegenerative diseases (NDs), molecular mechanisms that may have a broader relevance for most or all proteinopathies remain poorly resolved. In this study, we developed a multi-layered network expansion (MLnet) model to predict protein modifiers that are common to a group of diseases and, therefore, may have broader pathophysiological relevance for that group. When applied to the four NDs Alzheimer's disease (AD), Huntington's disease, and spinocerebellar ataxia types 1 and 3, we predicted multiple members of the insulin pathway, including PDK1, Akt1, InR, and sgg (GSK-3β), as common modifiers. We validated these modifiers with the help of four Drosophila ND models. Further evaluation of Akt1 in human cell-based ND models revealed that activation of Akt1 signaling by the small molecule SC79 increased cell viability in all models. Moreover, treatment of AD model mice with SC79 enhanced their long-term memory and ameliorated dysregulated anxiety levels, which are commonly affected in AD patients. These findings validate MLnet as a valuable tool to uncover molecular pathways and proteins involved in the pathophysiology of entire disease groups and identify potential therapeutic targets that have relevance across disease boundaries. MLnet can be used for any group of diseases and is available as a web tool at http://ssbio.cau.ac.kr/software/mlnet.

Model Organism Modifier (MOM): a user-friendly Galaxy workflow to detect modifiers from genome sequencing data using Caenorhabditis elegans

Genetic modifiers are variants modulating phenotypic outcomes of a primary detrimental variant. They contribute to rare diseases phenotypic variability, but their identification is challenging. Genetic screening with model organisms is a widely used method for demystifying genetic modifiers. Forward genetics screening followed by whole genome sequencing allows the detection of variants throughout the genome but typically produces thousands of candidate variants making the interpretation and prioritization process very time-consuming and tedious. Despite whole genome sequencing is more time and cost-efficient, usage of computational pipelines specific to modifier identification remains a challenge for biological-experiment-focused laboratories doing research with model organisms. To facilitate a broader implementation of whole genome sequencing in genetic screens, we have developed Model Organism Modifier or MOM, a pipeline as a user-friendly Galaxy workflow. Model Organism Modifier analyses raw short-read whole genome sequencing data and implements tailored filtering to provide a Candidate Variant List short enough to be further manually curated. We provide a detailed tutorial to run the Galaxy workflow Model Organism Modifier and guidelines to manually curate the Candidate Variant Lists. We have tested Model Organism Modifier on published and validated Caenorhabditis elegans modifiers screening datasets. As whole genome sequencing facilitates high-throughput identification of genetic modifiers in model organisms, Model Organism Modifier provides a user-friendly solution to implement the bioinformatics analysis of the short-read datasets in laboratories without expertise or support in Bioinformatics.

Optimal Protocols and Management of Clinical and Genomic Data Collection to Assist in the Early Diagnosis and Treatment of Multiple Congenital Anomalies

Standardized protocols have been designed and developed specifically for clinical information collection and obtaining trio genomic information from infants affected with congenital anomalies (CA) and their parents, as well as securing human biological resources. The protocols include clinical and genomic information collection on multiple CA that were difficult to diagnose using pre-existing screening methods. We obtained human-derived resources and genomic information from 138 cases, including 45 families of infants with CA and their parent trios. For the clinical information collection protocol, criteria for target patient selection and a consent system for collecting and utilizing research resources are crucial. Whole genome sequencing data were generated for all participants, and standardized protocols were developed for resource collection and manufacturing. We recorded the phenotype information according to the Human Phenotype Ontology term, and epidemiological information was collected through an environmental factor questionnaire. Updating and recording of clinical symptoms and genetic information that have been newly added or changed over time are significant. The protocols enabled long-term tracking by including the growth and development status that reflect the important characteristics of newborns. Using these clinical and genetic information collection protocols for CA, an essential platform for early genetic diagnosis and diagnostic research can be established, and new genetic diagnostic guidelines can be presented in the near future.

A Fixable Fluorescence-Quenched Substrate for Quantitation of Lysosomal Glucocerebrosidase Activity in Both Live and Fixed Cells

Fluorogenic substrates are emerging tools that enable studying enzymatic processes within their native cellular environments. However, fluorogenic substrates that function within live cells are generally incompatible with cellular fixation, preventing their tandem application with fundamental cell biology methods such as immunocytochemistry. Here we report a simple approach to enable the chemical fixation of a dark-to-light substrate, LysoFix-GBA, which enables quantification of glucocerebrosidase (GCase) activity in both live and fixed cells. LysoFix-GBA enables measuring responses to both chemical and genetic perturbations to lysosomal GCase activity. Further, LysoFix-GBA permits simple multiplexed co-localization studies of GCase activity with subcellular protein markers. This tool will aid studying the role of GCase activity in Parkinson's Disease, creating new therapeutic approaches targeting the GCase pathway. This approach also lays the foundation for an approach to create fixable substrates for other lysosomal enzymes.

A novel panel of Drosophila TAFAZZIN mutants in distinct genetic backgrounds as a resource for therapeutic testing

Barth Syndrome is a rare, X-linked disorder caused by mutation of the gene TAFAZZIN (TAZ). The corresponding Tafazzin protein is involved in the remodeling of cardiolipin, a phospholipid with critical roles in mitochondrial function. While recent clinical trials have been promising, there is still no cure for Barth Syndrome. Because TAZ is highly conserved, multiple animal and cell culture models exist for pre-clinical testing of therapeutics. However, since the same mutation in different patients can lead to different symptoms and responses to treatment, isogenized experimental models can't fully account for human disease conditions. On the other hand, isogenized animal models allow for sufficient numbers to thoroughly establish efficacy for a given genetic background. Therefore, a combined method for testing treatments in a panel of isogenized cohorts that are genetically distinct from each other would be transformative for testing emerging pre-clinical therapies. To aid in this effort, we've created a novel panel of 10 Drosophila lines, each with the same TAZ mutation in highly diverse genetic backgrounds, to serve as a helpful resource to represent natural variation in background genetics in pre-clinical studies. As a proof of principle, we test our panel here using nicotinamide riboside (NR), a treatment with established therapeutic value, to evaluate how robust this therapy is across the 10 genetic backgrounds in this novel reference panel. We find substantial variation in the response to NR across backgrounds. We expect this resource will be valuable in pre-clinical testing of emerging therapies for Barth Syndrome.

Proteomic Investigation of Differential Interactomes of Glypican 1 and a Putative Disease-Modifying Variant of Ataxia

In a currently 13-year-old girl of consanguineous Turkish parents, who developed unsteady gait and polyneuropathy at the ages of 3 and 6 years, respectively, we performed whole genome sequencing and identified a biallelic missense variant c.424C>T, p.R142W in glypican 1 (GPC1) as a putative disease-associated variant. Up to date, GPC1 has not been associated with a neuromuscular disorder, and we hypothesized that this variant, predicted as deleterious, may be causative for the disease. Using mass spectrometry-based proteomics, we investigated the interactome of GPC1 WT and the missense variant. We identified 198 proteins interacting with GPC1, of which 16 were altered for the missense variant. This included CANX as well as vacuolar ATPase (V-ATPase) and the mammalian target of rapamycin complex 1 (mTORC1) complex members, whose dysregulation could have a potential impact on disease severity in the patient. Importantly, these proteins are novel interaction partners of GPC1. At 10.5 years, the patient developed dilated cardiomyopathy and kyphoscoliosis, and Friedreich's ataxia (FRDA) was suspected. Given the unusually severe phenotype in a patient with FRDA carrying only 104 biallelic GAA repeat expansions in FXN, we currently speculate that disturbed GPC1 function may have exacerbated the disease phenotype. LC-MS/MS data are accessible in the ProteomeXchange Consortium (PXD040023).

A knowledge graph approach to predict and interpret disease-causing gene interactions

BACKGROUND

Understanding the impact of gene interactions on disease phenotypes is increasingly recognised as a crucial aspect of genetic disease research. This trend is reflected by the growing amount of clinical research on oligogenic diseases, where disease manifestations are influenced by combinations of variants on a few specific genes. Although statistical machine-learning methods have been developed to identify relevant genetic variant or gene combinations associated with oligogenic diseases, they rely on abstract features and black-box models, posing challenges to interpretability for medical experts and impeding their ability to comprehend and validate predictions. In this work, we present a novel, interpretable predictive approach based on a knowledge graph that not only provides accurate predictions of disease-causing gene interactions but also offers explanations for these results.

RESULTS

We introduce BOCK, a knowledge graph constructed to explore disease-causing genetic interactions, integrating curated information on oligogenic diseases from clinical cases with relevant biomedical networks and ontologies. Using this graph, we developed a novel predictive framework based on heterogenous paths connecting gene pairs. This method trains an interpretable decision set model that not only accurately predicts pathogenic gene interactions, but also unveils the patterns associated with these diseases. A unique aspect of our approach is its ability to offer, along with each positive prediction, explanations in the form of subgraphs, revealing the specific entities and relationships that led to each pathogenic prediction.

CONCLUSION

Our method, built with interpretability in mind, leverages heterogenous path information in knowledge graphs to predict pathogenic gene interactions and generate meaningful explanations. This not only broadens our understanding of the molecular mechanisms underlying oligogenic diseases, but also presents a novel application of knowledge graphs in creating more transparent and insightful predictors for genetic research.

DECIPHER: Improving Genetic Diagnosis Through Dynamic Integration of Genomic and Clinical Data

DECIPHER (Database of Genomic Variation and Phenotype in Humans Using Ensembl Resources) shares candidate diagnostic variants and phenotypic data from patients with genetic disorders to facilitate research and improve the diagnosis, management, and therapy of rare diseases. The platform sits at the boundary between genomic research and the clinical community. DECIPHER aims to ensure that the most up-to-date data are made rapidly available within its interpretation interfaces to improve clinical care. Newly integrated cardiac case-control data that provide evidence of gene-disease associations and inform variant interpretation exemplify this mission. New research resources are presented in a format optimized for use by a broad range of professionals supporting the delivery of genomic medicine. The interfaces within DECIPHER integrate and contextualize variant and phenotypic data, helping to determine a robust clinico-molecular diagnosis for rare-disease patients, which combines both variant classification and clinical fit. DECIPHER supports discovery research, connecting individuals within the rare-disease community to pursue hypothesis-driven research.

Germline CNV Detection through Whole-Exome Sequencing (WES) Data Analysis Enhances Resolution of Rare Genetic Diseases

Whole-Exome Sequencing (WES) has proven valuable in the characterization of underlying genetic defects in most rare diseases (RDs). Copy Number Variants (CNVs) were initially thought to escape detection. Recent technological advances enabled CNV calling from WES data with the use of accurate and highly sensitive bioinformatic tools. Amongst 920 patients referred for WES, 454 unresolved cases were further analysed using the ExomeDepth algorithm. CNVs were called, evaluated and categorized according to ACMG/ClinGen recommendations. Causative CNVs were identified in 40 patients, increasing the diagnostic yield of WES from 50.7% (466/920) to 55% (506/920). Twenty-two CNVs were available for validation and were all confirmed; of these, five were novel. Implementation of the ExomeDepth tool promoted effective identification of phenotype-relevant and/or novel CNVs. Among the advantages of calling CNVs from WES data, characterization of complex genotypes comprising both CNVs and SNVs minimizes cost and time to final diagnosis, while allowing differentiation between true or false homozygosity, as well as compound heterozygosity of variants in AR genes. The use of a specific algorithm for calling CNVs from WES data enables ancillary detection of different types of causative genetic variants, making WES a critical first-tier diagnostic test for patients with RDs.

Whole genome sequencing diagnostic yield for paediatric patients with suspected genetic disorders: systematic review, meta-analysis, and GRADE assessment

BACKGROUND

About 80% of the roughly 7,000 known rare diseases are single gene disorders, about 85% of which are ultra-rare, affecting less than one in one million individuals. NGS technologies, in particular whole genome sequencing (WGS) in paediatric patients suffering from severe disorders of likely genetic origin improve the diagnostic yield allowing targeted, effective care and management. The aim of this study is to perform a systematic review and meta-analysis to assess the effectiveness of WGS, with respect to whole exome sequencing (WES) and/or usual care, for the diagnosis of suspected genetic disorders among the paediatric population.

METHODS

A systematic review of the literature was conducted querying relevant electronic databases, including MEDLINE, EMBASE, ISI Web of Science, and Scopus from January 2010 to June 2022. A random-effect meta-analysis was run to inspect the diagnostic yield of different techniques. A network meta-analysis was also performed to directly assess the comparison between WGS and WES.

RESULTS

Of the 4,927 initially retrieved articles, thirty-nine met the inclusion criteria. Overall results highlighted a significantly higher pooled diagnostic yield for WGS, 38.6% (95% CI: [32.6 - 45.0]), in respect to WES, 37.8% (95% CI: [32.9 - 42.9]) and usual care, 7.8% (95% CI: [4.4 - 13.2]). The meta-regression output suggested a higher diagnostic yield of the WGS compared to WES after controlling for the type of disease (monogenic vs non-monogenic), with a tendency to better diagnostic performances for Mendelian diseases. The network meta-analysis showed a higher diagnostic yield for WGS compared to WES (OR = 1.54, 95%CI: [1.11 - 2.12]).

CONCLUSIONS

Although whole genome sequencing for the paediatric population with suspected genetic disorders provided an accurate and early genetic diagnosis in a high proportion of cases, further research is needed for evaluating costs, effectiveness, and cost-effectiveness of WGS and achieving an informed decision-making process.

TRIAL REGISTRATION

This systematic review has not been registered.

Faster and more accurate pathogenic combination predictions with VarCoPP2.0

BACKGROUND

The prediction of potentially pathogenic variant combinations in patients remains a key task in the field of medical genetics for the understanding and detection of oligogenic/multilocus diseases. Models tailored towards such cases can help shorten the gap of missing diagnoses and can aid researchers in dealing with the high complexity of the derived data. The predictor VarCoPP (Variant Combinations Pathogenicity Predictor) that was published in 2019 and identified potentially pathogenic variant combinations in gene pairs (bilocus variant combinations), was the first important step in this direction. Despite its usefulness and applicability, several issues still remained that hindered a better performance, such as its False Positive (FP) rate, the quality of its training set and its complex architecture.

RESULTS

We present VarCoPP2.0: the successor of VarCoPP that is a simplified, faster and more accurate predictive model identifying potentially pathogenic bilocus variant combinations. Results from cross-validation and on independent data sets reveal that VarCoPP2.0 has improved in terms of both sensitivity (95% in cross-validation and 98% during testing) and specificity (5% FP rate). At the same time, its running time shows a significant 150-fold decrease due to the selection of a simpler Balanced Random Forest model. Its positive training set now consists of variant combinations that are more confidently linked with evidence of pathogenicity, based on the confidence scores present in OLIDA, the Oligogenic Diseases Database ( https://olida.ibsquare.be ). The improvement of its performance is also attributed to a more careful selection of up-to-date features identified via an original wrapper method. We show that the combination of different variant and gene pair features together is important for predictions, highlighting the usefulness of integrating biological information at different levels.

CONCLUSIONS

Through its improved performance and faster execution time, VarCoPP2.0 enables a more accurate analysis of larger data sets linked to oligogenic diseases. Users can access the ORVAL platform ( https://orval.ibsquare.be ) to apply VarCoPP2.0 on their data.

Phenotypic specificity in patients with neurodevelopmental delay does not correlate with diagnostic yield of trio-exome sequencing

In this study, we aimed to examine the diagnostic yield achieved by applying a trio approach in exome sequencing (ES) and the interdependency between the clinical specificity in families with neurodevelopmental delay. Thirty-seven families were recruited and trio-ES as well as three criteria for estimating the clinical phenotypic specificity were suggested and applied to the underaged children. All our patients showed neurodevelopmental delay and most of them a large spectrum of congenital anomalies. Applying the pathogenicity guidelines of the American College of Medical Genetics (ACMG), likely pathogenic (29.7%) and pathogenic variants (8.1%) were found in 40,5% of our index patients. Additionally, we found four variants of uncertain significance (VUS; according to ACMG) and two genes of interest (GOI; going beyond ACMG classification) (GLRA4, NRXN2). Spastic Paraplegia 4 (SPG4) caused by a formerly known SPAST variant was diagnosed in a patient with a complex phenotype, in whom a second genetic disorder may be present. A potential pathogenic variant linked to severe intellectual disability in GLRA4 requires further investigation. No interdependency between the diagnostic yield and the clinical specificity of the phenotypes could be observed. In consequence, trio-ES should be used early in the diagnostic process, independently from the specificity of the patient.

The genetic era of childhood cancer: Identification of high-risk patients and germline sequencing approaches

Childhood cancer is a leading cause of death by disease in children ages 5-14, for which there are no preventive strategies. Due to early-age of diagnosis and short period of exposure to environmental factors, increasing evidence suggests childhood cancer could have strong association with germline alterations in predisposition cancer genes but, their frequency and distribution are largely unknown. Several efforts have been made to develop tools to identify children with increased risk of cancer who may benefit from genetic testing but their validation and application on a large scale is necessary. Research on genetic bases of childhood cancer is ongoing, in which several approaches for the identification of genetic variants related to cancer predisposition have been used. In this paper, we discuss the updated efforts, strategies, molecular mechanisms and clinical implications for germline predisposition gene alterations and the characterization of risk variants in childhood cancer.

Congenital Microcephaly: A Debate on Diagnostic Challenges and Etiological Paradigm of the Shift from Isolated/Non-Syndromic to Syndromic Microcephaly

Congenital microcephaly (CM) exhibits broad clinical and genetic heterogeneity and is thus categorized into several subtypes. However, the recent bloom of disease-gene discoveries has revealed more overlaps than differences in the underlying genetic architecture for these clinical sub-categories, complicating the differential diagnosis. Moreover, the mechanism of the paradigm shift from a brain-restricted to a multi-organ phenotype is only vaguely understood. This review article highlights the critical factors considered while defining CM subtypes. It also presents possible arguments on long-standing questions of the brain-specific nature of CM caused by a dysfunction of the ubiquitously expressed proteins. We argue that brain-specific splicing events and organ-restricted protein expression may contribute in part to disparate clinical manifestations. We also highlight the role of genetic modifiers and de novo variants in the multi-organ phenotype of CM and emphasize their consideration in molecular characterization. This review thus attempts to expand our understanding of the phenotypic and etiological variability in CM and invites the development of more comprehensive guidelines.

Genetically transitional disease: a new concept in genomic medicine

Traditional classification of genetic diseases as monogenic and polygenic has lagged far behind scientific progress. In this opinion article, we propose and define a new terminology, genetically transitional disease (GTD), referring to cases where a large-effect mutation is necessary, but not sufficient, to cause disease. This leads to a working disease nosology based on gradients of four types of genetic architecture: monogenic, polygenic, GTD, and mixed. We present four scenarios under which GTD may occur; namely, subsets of traditionally Mendelian disease, modifiable Tier 1 monogenic conditions, variable penetrance, and situations where a genetic mutational spectrum produces qualitatively divergent pathologies. The implications of the new nosology in precision medicine are discussed, in which therapeutic options may target the molecular cause or the disease phenotype.

Copy Number Variant Analysis of Spinocerebellar Ataxia Genes in a Cohort of Dutch Patients With Cerebellar Ataxia

Background and Objectives

The spinocerebellar ataxias (SCAs) are a genetically heterogeneous group of neurodegenerative disorders generally caused by single nucleotide variants (SNVs) or indels in coding regions or by repeat expansions in coding and noncoding regions of SCA genes. Copy number variants (CNVs) have now also been reported for 3 genes-ITPR1, FGF14, and SPTBN2-but not all SCA genes have been screened for CNVs as the underlying cause of the disease in patients. In this study, we aim to assess the prevalence of CNVs encompassing 36 known SCA genes.

Methods

A cohort of patients with cerebellar ataxia who were referred to the University Medical Center Groningen for SCA genetic diagnostics was selected for this study. Genome-wide single nucleotide polymorphism (SNP) genotyping was performed using the Infinium Global Screening Array. Following data processing, genotyping data were uploaded into NxClinical software to perform CNV analysis per patient and to visualize identified CNVs in 36 genes with allocated SCA symbols. The clinical relevance of detected CNVs was determined using evidence from studies based on PubMed literature searches for similar CNVs and phenotypic features.

Results

Of the 338 patients with cerebellar ataxia, we identified putative clinically relevant CNV deletions in 3 patients: an identical deletion encompassing ITPR1 in 2 patients, who turned out to be related, and a deletion involving PPP2R2B in another patient. Although the CNV deletion in ITPR1 was clearly the underlying cause of SCA15 in the 2 related patients, the clinical significance of the deletion in PPP2R2B remained unknown.

Discussion

We showed that CNVs detectable with the limited resolution of SNP array are a very rare cause of SCA. Nevertheless, we suggest adding CNV analysis alongside SNV analysis to SCA gene diagnostics using next-generation sequencing approaches, at least for ITPR1, to improve the genetic diagnostics for patients.

Familial Beckwith-Wiedemann syndrome in a multigenerational family: Forty years of careful phenotyping

Beckwith-Wiedemann Spectrum (BWSp) is an overgrowth and cancer predisposition disorder characterized by a wide spectrum of phenotypic manifestations including macroglossia, abdominal wall defects, neonatal hypoglycemia, and predisposition to embryonal tumors. In 1981, Best and Hoekstra reported four patients with BWSp in a single family which suggested autosomal dominant inheritance, but standard clinical testing for BWSp was not available during this time. Meticulous phenotyping of this family has occurred over the past 40 years of follow-up with additional family members being identified and samples collected for genetic testing. Genetic testing revealed a pathogenic mutation in CDKN1C, consistent with the most common cause of familial BWSp. CDKN1C mutations account for just 5% of sporadic cases of BWSp. Here, we report the variable presentation of BWSp across the individuals affected by the CDKN1C mutation and other extended family members spanning multiple generations, all examined by the same physician. Additional phenotypes thought to be atypical in patients with BWSp were reported which included cardiac abnormalities. The incidence of tumors was documented in extended family members and included rhabdomyosarcoma, astrocytoma, and thyroid carcinoma, which have previously been reported in patients with BWSp. These observations suggest that in addition to the inheritance of the CDKN1C variant, there are modifying factors in this family driving the phenotypic spectrum observed. Alternative theories are suggested to explain the etiology of clinical variability including diffused mosaicism, anticipation, and the presence of additional variants tracking in the family. This study highlights the necessity of long-term follow-up in patients with BWSp and consideration of individual familial characteristics in the context of phenotype and/or (epi)genotype associations.

Novel Insulin-Like Growth Factor 1 Gene Mutation: Broadening of the Phenotype and Implications for Insulin Resistance

PURPOSE

Insulin-like Growth Factor (IGF)1 gene mutations are extremely rare causes of pre- and post-natal growth retardation. Phenotype can be heterogenous with varying degrees of neurosensory deafness, cognitive defects, glucose metabolism impairment and short stature. This study describes a 12.6-year-old girl presenting severe short stature and insulin resistance, but with normal hearing and neurological development at the lower limit of normal.

METHODS

DNA was obtained from the proband and both parents for whole exome sequencing (WES). In silico analysis was performed to predict the impact of the IGF1 variant on IGF1 and insulin receptors (IGF1R and IR) signalling. Phosphorylation of the IGF1R at activating Tyr residues and cell proliferation analyses were used to assess the ability of each subject's IGF1 to bind and activate IGF1R.

RESULTS

The proband had low immunoreactive IGF1 in serum and WES revealed a novel homozygous IGF1 missense variant (c.247A > T), causing a change of serine 83 for cysteine (p.Ser83Cys; p.Ser35Cys in mature peptide). The proband's parents were heterozygous for this mutation. In silico analyses indicated the pathogenic potential of the variant with electrostatic variations with the potential of hampering the interaction with the IGF1R but strengthening the binding to IR. The mutant IGF1 protein had a significantly reduced activity on in vitro bioassays.

MAIN CONCLUSIONS

We describe a novel IGF1 mutation leading to severe loss of circulating IGF1 immunoreactivity and bioactivity, In silico modelling predicts that the mutant IGF1 could interfere with IR signalling, providing a possible explanation for the severe insulin resistance observed in the patient. The absence of significant hearing and neurodevelopmental involvement in the present case is unusual and broadens the clinical spectrum of IGF1 mutations.

A novel mutation in the collagen domain of EDA results in hypohidrotic ectodermal dysplasia by impacting the receptor‐binding capability

BACKGROUND

Hypohidrotic ectodermal dysplasia (HED) mainly results from gene mutations in the EDA/EDAR/NF-κB pathway. Function analysis of the mutations in the collagen domain of ectodysplasin A (EDA)result in HED has been rarely studied. This study aimed at determining the mechanism by which the novel collagen domain mutation of EDA results in HED.

METHODS

We analyzed the DNAs from a Chinese family with HED and performed bioinformatics analysis. A new three-dimensional structure model of the EDA trimer was built and used to predict the effect of the mutations on EDA. We performed a western blot to detect EDA1 proteins in cell lysates and supernatants. We then performed coimmunoprecipitation to determine whether the mutation would affect the interaction of EDA1 with the EDA receptor (EDAR). Dual luciferase reporter assay and immunofluorescence were performed to detect the effect of the mutant EDA1 protein on nuclear factor kappa B (NF-κB) activation.

RESULTS

A novel missense mutation (c.593G > A, p. Gly198Glu) in the collagen domain of EDA was detected. The mutation was predicted to be disease-causing. A three-dimensional structure model of the EDA trimer was first built in this study, in which the mutation site is located around the receptor binding domain. Functional studies showed that there was no difference in the secretion activity between the mutant EDA1 and the wild-type EDA1. However, the receptor-binding activity and the transcription activation of NF-κB were impaired by the mutation.

CONCLUSION

We identified a novel mutation (c.593G > A, p. Gly198Glu) in the collagen domain of EDA. Bioinformatics analysis and functional studies showed this mutation was damaging, indicating that mutations in the collagen domain of EDA could result in HED by affecting the receptor-binding activity of EDA and the transcriptional activity of NF-κB.

Research advances in treatment methods and drug development for rare diseases

As the incidence of rare diseases increases each year, the total number of rare disease patients worldwide is nearly 400 million. Orphan medications are drugs used to treat rare diseases. Orphan drugs, however, are rare and patients often struggle to utilize them and expensive medications during treatment. Orphan drugs have been the focus of new drug research and development for both domestic and international pharmaceutical companies as a result of the substantial investment being made in the field of rare diseases. Clinical breakthroughs have been made in every field, from traditional antibodies and small molecule drugs to gene therapy, stem cell therapy and small nucleic acid drugs. We here review the therapeutic means of rare diseases and drug development of rare diseases to show the progress of treatment of rare diseases in order to provide a reference for clinical use and new drug development of rare diseases in China.

Thyroid Function and COVID-19 Susceptibility and Its Severity: A Two-Sample Mendelian Randomization Study

Several observational studies have confirmed the relationship between thyroid hormones and coronavirus disease 2019 (COVID-19), but this correlation remains controversial. We performed a two-sample Mendelian randomization (MR) analysis based on the largest publicly available summary datasets. Summary statistics with 49 269 individuals for free thyroxine (FT4) and 54 288 for thyroid stimulating hormone (TSH) were used as exposure instruments. Genome-wide association studies of susceptibility (cases = 38 984; controls = 1 644 784), hospitalization (cases: 9986 = controls = 1 877 672), and very severe disease (cases = 5101; controls = 1 383 241) of COVID-19 were used as the outcome. We used the inverse-variance weighted (IVW) method as the primary analysis, and utilized MR-Egger regression, weighted median, and robust adjusted profile score (RAPS) for sensitivity analysis. Genetic predisposition to higher serum levels of FT4 within the normal range was negatively associated with the risk of COVID-19 hospitalization (odds ratio [OR] = 0.818; 95% CI, 0.718-0.932; P = 2.6 × 10-3) and very severe disease (OR = 0.758; 95% CI, 0.626-0.923; P = 5.8 × 10-3), but not susceptibility. There is no evidence that genetically predicted circulating TSH levels are associated with COVID-19 susceptibility and severity risk. Neither apparent pleiotropy nor heterogeneity were detected in the sensitivity analysis. In summary, we found that higher FT4 levels may reduce the risk of COVID-19 severity, suggesting that thyroid function testing may be required for patients with COVID-19.

Crosstalk between Glycogen-Selective Autophagy, Autophagy and Apoptosis as a Road towards Modifier Gene Discovery and New Therapeutic Strategies for Glycogen Storage Diseases

Glycogen storage diseases (GSDs) are rare metabolic monogenic disorders characterized by an excessive accumulation of glycogen in the cell. However, monogenic disorders are not simple regarding genotype–phenotype correlation. Genes outside the major disease-causing locus could have modulatory effect on GSDs, and thus explain the genotype–phenotype inconsistencies observed in these patients. Nowadays, when the sequencing of all clinically relevant genes, whole human exomes, and even whole human genomes is fast, easily available and affordable, we have a scientific obligation to holistically analyze data and draw smarter connections between genotype and phenotype. Recently, the importance of glycogen-selective autophagy for the pathophysiology of disorders of glycogen metabolism have been described. Therefore, in this manuscript, we review the potential role of genes involved in glycogen-selective autophagy as modifiers of GSDs. Given the small number of genes associated with glycogen-selective autophagy, we also include genes, transcription factors, and non-coding RNAs involved in autophagy. A cross-link with apoptosis is addressed. All these genes could be analyzed in GSD patients with unusual discrepancies between genotype and phenotype in order to discover genetic variants potentially modifying their phenotype. The discovery of modifier genes related to glycogen-selective autophagy and autophagy will start a new chapter in understanding of GSDs and enable the usage of autophagy-inducing drugs for the treatment of this group of rare-disease patients.

Prediction of Regulatory SNPs in Putative Minor Genes of the Neuro-Cardiovascular Variant in Fabry Reveals Insights into Autophagy/Apoptosis and Fibrosis

Even though a mutation in monogenic diseases leads to a “classic” manifestation, many disorders exhibit great clinical variability that could be due to modifying genes also called minor genes. Fabry disease (FD) is an X-linked inborn error resulting from the deficient or absent activity of alpha-galactosidase A (α-GAL) enzyme, that leads to deposits of globotriaosylceramide. With our proprietary software SNPclinic v.1.0, we analyzed 110 single nucleotide polymorphisms (SNPs) in the proximal promoter of 14 genes that could modify the FD phenotype FD. We found seven regulatory-SNP (rSNPs) in three genes (IL10, TGFB1 and EDN1) in five cell lines relevant to FD (Cardiac myocytes and fibroblasts, Astrocytes-cerebellar, endothelial cells and T helper cells 1-TH1). Each SNP was confirmed as a true rSNP in public eQTL databases, and additional software suggested the prediction of variants. The two proposed rSNPs in IL10, could explain components for the regulation of active B cells that influence the fibrosis process. The three predicted rSNPs in TGFB1, could act in apoptosis-autophagy regulation. The two putative rSNPs in EDN1, putatively regulate chronic inflammation. The seven rSNPs described here could act to modulate Fabry’s clinical phenotype so we propose that IL10, TGFB1 and EDN1 be considered minor genes in FD.

Genetic Background Matters: Population-Based Studies in Model Organisms for Translational Research

We are all similar but a bit different. These differences are partially due to variations in our genomes and are related to the heterogeneity of symptoms and responses to treatments that patients exhibit. Most animal studies are performed in one single strain with one manipulation. However, due to the lack of variability, therapies are not always reproducible when treatments are translated to humans. Panels of already sequenced organisms are valuable tools for mimicking human phenotypic heterogeneities and gene mapping. This review summarizes the current knowledge of mouse, fly, and yeast panels with insightful applications for translational research.

Rare genetic variants in genes and loci linked to dominant monogenic developmental disorders cause milder related phenotypes in the general population

Many rare monogenic diseases are known to be caused by deleterious variants in thousands of genes, however the same variants can also be found in people without the associated clinical phenotypes. The penetrance of these monogenic variants is generally unknown in the wider population, as they are typically identified in small clinical cohorts of affected individuals and families with highly penetrant variants. Here, we investigated the phenotypic effect of rare, potentially deleterious variants in genes and loci where similar variants are known to cause monogenic developmental disorders (DDs) in a large population cohort. We used UK Biobank to investigate phenotypes associated with rare protein-truncating and missense variants in 599 monoallelic DDG2P genes by using whole-exome-sequencing data from ∼200,000 individuals and rare copy-number variants overlapping known DD loci by using SNP-array data from ∼500,000 individuals. We found that individuals with these likely deleterious variants had a mild DD-related phenotype, including lower fluid intelligence, slower reaction times, lower numeric memory scores, and longer pairs matching times compared to the rest of the UK Biobank cohort. They were also shorter, had a higher BMI, and had significant socioeconomic disadvantages: they were less likely to be employed or be able to work and had a lower income and higher deprivation index. Our findings suggest that many genes routinely tested within pediatric genetics have deleterious variants with intermediate penetrance that may cause lifelong sub-clinical phenotypes in the general adult population.

Common genetic variation associated with Mendelian disease severity revealed through cryptic phenotype analysis

Clinical heterogeneity is common in Mendelian disease, but small sample sizes make it difficult to identify specific contributing factors. However, if a disease represents the severely affected extreme of a spectrum of phenotypic variation, then modifier effects may be apparent within a larger subset of the population. Analyses that take advantage of this full spectrum could have substantially increased power. To test this, we developed cryptic phenotype analysis, a model-based approach that infers quantitative traits that capture disease-related phenotypic variability using qualitative symptom data. By applying this approach to 50 Mendelian diseases in two cohorts, we identify traits that reliably quantify disease severity. We then conduct genome-wide association analyses for five of the inferred cryptic phenotypes, uncovering common variation that is predictive of Mendelian disease-related diagnoses and outcomes. Overall, this study highlights the utility of computationally-derived phenotypes and biobank-scale cohorts for investigating the complex genetic architecture of Mendelian diseases.

New Developments and Possibilities in Reanalysis and Reinterpretation of Whole Exome Sequencing Datasets for Unsolved Rare Diseases Using Machine Learning Approaches

Rare diseases impact the lives of 300 million people in the world. Rapid advances in bioinformatics and genomic technologies have enabled the discovery of causes of 20–30% of rare diseases. However, most rare diseases have remained as unsolved enigmas to date. Newer tools and availability of high throughput sequencing data have enabled the reanalysis of previously undiagnosed patients. In this review, we have systematically compiled the latest developments in the discovery of the genetic causes of rare diseases using machine learning methods. Importantly, we have detailed methods available to reanalyze existing whole exome sequencing data of unsolved rare diseases. We have identified different reanalysis methodologies to solve problems associated with sequence alterations/mutations, variation re-annotation, protein stability, splice isoform malfunctions and oligogenic analysis. In addition, we give an overview of new developments in the field of rare disease research using whole genome sequencing data and other omics.

Regulation of endothelial nitric oxide synthase in cardiac remodeling

OBJECTIVES

Our previous study demonstrated that endothelial nitric oxide synthase (eNOS) gene serves as a candidate for modifiers of hypertrophic cardiomyopathy (HCM), which alters severity of HCM phenotypes. Herein, we sought to further elucidate the role of eNOS on cardiac myocyte hypertrophy and fibrosis, the major phenotypes of HCM.

METHODS

Male eNOS-deficient mice (eNOS-/-) and wild type control mice (eNOS+/+, C57B1/6 J) were used in this study. Myocyte size was analyzed in hematoxylin/eosin stained sections using an image analyzing system. Cardiac β-myosin heavy chain (β-MHC) and α-skeletal actin (α-SKA) levels, markers of myocyte hypertrophy were evaluated by Western blot. Cardiac collagen volume fraction (CVF) was examined in picrosirius red stained section using an image analyzing system. Cardiac expression of tissue inhibitor of metalloproteinase 1 (TIMP-1) and transforming growth factor beta 1 (TGF-β1), markers of fibrosis, were determined by Western blot.

RESULTS

Compared to eNOS+/+ mice, we found that; 1) myocyte size was significantly increased in eNOS-/- mice; 2) cardiac expression of β-MHC was markedly elevated, while α-SKA levels remained unchanged in eNOS-/- mice; 3) cardiac total and interstitial CVF levels were significantly higher in eNOS-/- mice; and 4) cardiac TIMP-1 levels were significantly greater in eNOS-/- mice, however, cardiac TGF-β1 was not differently expressed between the two groups.

CONCLUSION

The current study revealed that eNOS plays a beneficial role in cardiac remodeling, preventing the heart from development of myocyte hypertrophy and cardiac fibrosis. These findings support our previous report that eNOS may modify the severity of HCM phenotypes.