NetActivity enhances transcriptional signals by combining gene expression into robust gene set activity scores through interpretable autoencoders.

Grouping gene expression into gene set activity scores (GSAS) provides better biological insights than studying individual genes. However, existing gene set projection methods cannot return representative, robust, and interpretable GSAS. We developed NetActivity, a machine learning framework that generates GSAS based on a sparsely-connected autoencoder, where each neuron in the inner layer represents a gene set. We proposed a three-tier training that yielded representative, robust, and interpretable GSAS. NetActivity model was trained with 1518 GO biological processes terms and KEGG pathways and all GTEx samples. NetActivity generates GSAS robust to the initialization parameters and representative of the original transcriptome, and assigned higher importance to more biologically relevant genes. Moreover, NetActivity returns GSAS with a more consistent definition and higher interpretability than GSVA and hipathia, state-of-the-art gene set projection methods. Finally, NetActivity enables combining bulk RNA-seq and microarray datasets in a meta-analysis of prostate cancer progression, highlighting gene sets related to cell division, key for disease progression. When applied to metastatic prostate cancer, gene sets associated with cancer progression were also altered due to drug resistance, while a classical enrichment analysis identified gene sets irrelevant to the phenotype. NetActivity is publicly available in Bioconductor and GitHub.

Macrocheilia as an Atypical Clinical Presentation of Capillary Malformation-Arteriovenous Malformation Type 2.

This case report describes a 53-year-old man with multiple erythematous macules and papules diffusely distributed on the frontal area, cheeks, eyelids, nose, and supralabial skin.

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2.

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people.

Narrowing the diagnostic gap: Genomes, episignatures, long-read sequencing, and health economic analyses in an exome-negative intellectual disability cohort.

PURPOSE: Genome sequencing (GS)-specific diagnostic rates in prospective tightly ascertained exome sequencing (ES)-negative intellectual disability (ID) cohorts have not been reported extensively. METHODS: ES, GS, epigenetic signatures, and long-read sequencing diagnoses were assessed in 74 trios with at least moderate ID. RESULTS: The ES diagnostic yield was 42 of 74 (57%). GS diagnoses were made in 9 of 32 (28%) ES-unresolved families. Repeated ES with a contemporary pipeline on the GS-diagnosed families identified 8 of 9 single-nucleotide variations/copy-number variations undetected in older ES, confirming a GS-unique diagnostic rate of 1 in 32 (3%). Episignatures contributed diagnostic information in 9% with GS corroboration in 1 of 32 (3%) and diagnostic clues in 2 of 32 (6%). A genetic etiology for ID was detected in 51 of 74 (69%) families. Twelve candidate disease genes were identified. Contemporary ES followed by GS cost US$4976 (95% CI: $3704; $6969) per diagnosis and first-line GS at a cost of $7062 (95% CI: $6210; $8475) per diagnosis. CONCLUSION: Performing GS only in ID trios would be cost equivalent to ES if GS were available at $2435, about a 60% reduction from current prices. This study demonstrates that first-line GS achieves higher diagnostic rate than contemporary ES but at a higher cost.

A new blood DNA methylation signature for Koolen-de Vries syndrome: Classification of missense KANSL1 variants and comparison to fibroblast cells.

Pathogenic variants in KANSL1 and 17q21.31 microdeletions are causative of Koolen-de Vries syndrome (KdVS), a neurodevelopmental syndrome with characteristic facial dysmorphia. Our previous work has shown that syndromic conditions caused by pathogenic variants in epigenetic regulatory genes have identifiable patterns of DNA methylation (DNAm) change: DNAm signatures or episignatures. Given the role of KANSL1 in histone acetylation, we tested whether variants underlying KdVS are associated with a DNAm signature. We profiled whole-blood DNAm for 13 individuals with KANSL1 variants, four individuals with 17q21.31 microdeletions, and 21 typically developing individuals, using Illumina's Infinium EPIC array. In this study, we identified a robust DNAm signature of 456 significant CpG sites in 8 individuals with KdVS, a pattern independently validated in an additional 7 individuals with KdVS. We also demonstrate the diagnostic utility of the signature and classify two KANSL1 VUS as well as four variants in individuals with atypical clinical presentation. Lastly, we investigated tissue-specific DNAm changes in fibroblast cells from individuals with KdVS. Collectively, our findings contribute to the understanding of the epigenetic landscape related to KdVS and aid in the diagnosis and classification of variants in this structurally complex genomic region.

Spliceosome malfunction causes neurodevelopmental disorders with overlapping features.

Pre-mRNA splicing is a highly coordinated process. While its dysregulation has been linked to neurological deficits, our understanding of the underlying molecular and cellular mechanisms remains limited. We implicated pathogenic variants in U2AF2 and PRPF19, encoding spliceosome subunits in neurodevelopmental disorders (NDDs), by identifying 46 unrelated individuals with 23 de novo U2AF2 missense variants (including 7 recurrent variants in 30 individuals) and 6 individuals with de novo PRPF19 variants. Eight U2AF2 variants dysregulated splicing of a model substrate. Neuritogenesis was reduced in human neurons differentiated from human pluripotent stem cells carrying two U2AF2 hyper-recurrent variants. Neural loss of function (LoF) of the Drosophila orthologs U2af50 and Prp19 led to lethality, abnormal mushroom body (MB) patterning, and social deficits, which were differentially rescued by wild-type and mutant U2AF2 or PRPF19. Transcriptome profiling revealed splicing substrates or effectors (including Rbfox1, a third splicing factor), which rescued MB defects in U2af50-deficient flies. Upon reanalysis of negative clinical exomes followed by data sharing, we further identified 6 patients with NDD who carried RBFOX1 missense variants which, by in vitro testing, showed LoF. Our study implicates 3 splicing factors as NDD-causative genes and establishes a genetic network with hierarchy underlying human brain development and function.

ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization.

BACKGROUND: Whole-exome sequencing (WES) and whole-genome sequencing (WGS) have become indispensable tools to solve rare Mendelian genetic conditions. Nevertheless, there is still an urgent need for sensitive, fast algorithms to maximise WES/WGS diagnostic yield in rare disease patients. Most tools devoted to this aim take advantage of patient phenotype information for prioritization of genomic data, although are often limited by incomplete gene-phenotype knowledge stored in biomedical databases and a lack of proper benchmarking on real-world patient cohorts. METHODS: We developed ClinPrior, a novel method for the analysis of WES/WGS data that ranks candidate causal variants based on the patient's standardized phenotypic features (in Human Phenotype Ontology (HPO) terms). The algorithm propagates the data through an interactome network-based prioritization approach. This algorithm was thoroughly benchmarked using a synthetic patient cohort and was subsequently tested on a heterogeneous prospective, real-world series of 135 families affected by hereditary spastic paraplegia (HSP) and/or cerebellar ataxia (CA). RESULTS: ClinPrior successfully identified causative variants achieving a final positive diagnostic yield of 70% in our real-world cohort. This includes 10 novel candidate genes not previously associated with disease, 7 of which were functionally validated within this project. We used the knowledge generated by ClinPrior to create a specific interactome for HSP/CA disorders thus enabling future diagnoses as well as the discovery of novel disease genes. CONCLUSIONS: ClinPrior is an algorithm that uses standardized phenotype information and interactome data to improve clinical genomic diagnosis. It helps in identifying atypical cases and efficiently predicts novel disease-causing genes. This leads to increasing diagnostic yield, shortening of the diagnostic Odysseys and advancing our understanding of human illnesses.

Epimutation detection in the clinical context: guidelines and a use case from a new Bioconductor package.

Epimutations are rare alterations of the normal DNA methylation pattern at specific loci, which can lead to rare diseases. Methylation microarrays enable genome-wide epimutation detection, but technical limitations prevent their use in clinical settings: methods applied to rare diseases' data cannot be easily incorporated to standard analyses pipelines, while epimutation methods implemented in R packages (ramr) have not been validated for rare diseases. We have developed epimutacions, a Bioconductor package (https://bioconductor.org/packages/release/bioc/html/epimutacions.html). epimutacions implements two previously reported methods and four new statistical approaches to detect epimutations, along with functions to annotate and visualize epimutations. Additionally, we have developed an user-friendly Shiny app to facilitate epimutations detection (https://github.com/isglobal-brge/epimutacionsShiny) to non-bioinformatician users. We first compared the performance of epimutacions and ramr packages using three public datasets with experimentally validated epimutations. Methods in epimutacions had a high performance at low sample sizes and outperformed methods in ramr. Second, we used two general population children cohorts (INMA and HELIX) to determine the technical and biological factors that affect epimutations detection, providing guidelines on how designing the experiments or preprocessing the data. In these cohorts, most epimutations did not correlate with detectable regional gene expression changes. Finally, we exemplified how epimutacions can be used in a clinical context. We run epimutacions in a cohort of children with autism disorder and identified novel recurrent epimutations in candidate genes for autism. Overall, we present epimutacions a new Bioconductor package for incorporating epimutations detection to rare disease diagnosis and provide guidelines for the design and data analyses.

CDKL5 Deficiency Disorder Without Epilepsy.

Cyclin-dependent kinase-like 5 (CDKL5) deficiency disorder (CDD) has epilepsy as a cardinal feature. Here we report two new female patients and review six previously published patients, one male and five females, with features of CDD but who never developed epilepsy. In contrast with the classical and severe CDD phenotype, they presented with milder gross motor delays, autism spectrum disorder, and no visual cortical impairment. Prolonged video electroencephalography was normal in adult cases but showed interictal frontal-temporal bilateral spikes and sharp waves in sleep in the three-year-old girl. Causative CDKL5 variants included two likely gene damaging (nonsense and frameshift) and six missense variants, being de novo or maternally inherited from asymptomatic females with skewed X-chromosome inactivation (two missense variants). Our data indicate that a milder form of CDD without epilepsy can occur in some cases without clear correlation with specific variants in the CDKL5 gene.

The Combined Treatment of Curcumin with Verapamil Ameliorates the Cardiovascular Pathology in a Williams-Beuren Syndrome Mouse Model.

Williams-Beuren syndrome (WBS) is a rare disorder caused by a recurrent microdeletion with hallmarks of cardiovascular manifestations, mainly supra-valvular aortic stenosis (SVAS). Unfortunately, there is currently no efficient treatment. We investigated the effect of chronic oral treatment with curcumin and verapamil on the cardiovascular phenotype of a murine model of WBS harbouring a similar deletion, CD (complete deletion) mice. We analysed systolic blood pressure in vivo and the histopathology of the ascending aorta and the left ventricular myocardium to determine the effects of treatments and their underlying mechanism. Molecular analysis showed significantly upregulated xanthine oxidoreductase (XOR) expression in the aorta and left ventricular myocardium of CD mice. This overexpression is concomitant with increased levels of nitrated proteins as a result of byproduct-mediated oxidative stress damage, indicating that XOR-generated oxidative stress impacts the pathophysiology of cardiovascular manifestations in WBS. Only the combined therapy of curcumin and verapamil resulted in a significant improvement of cardiovascular parameters via activation of the nuclear factor erythroid 2 (NRF2) and reduction of XOR and nitrated protein levels. Our data suggested that the inhibition of XOR and oxidative stress damage could help prevent the severe cardiovascular injuries of this disorder.

FOSL2 truncating variants in the last exon cause a neurodevelopmental disorder with scalp and enamel defects.

PURPOSE: We aimed to investigate the molecular basis of a novel recognizable neurodevelopmental syndrome with scalp and enamel anomalies caused by truncating variants in the last exon of the gene FOSL2, encoding a subunit of the AP-1 complex. METHODS: Exome sequencing was used to identify genetic variants in all cases, recruited through Matchmaker exchange. Gene expression in blood was analyzed using reverse transcription polymerase chain reaction. In vitro coimmunoprecipitation and proteasome inhibition assays in transfected HEK293 cells were performed to explore protein and AP-1 complex stability. RESULTS: We identified 11 individuals from 10 families with mostly de novo truncating FOSL2 variants sharing a strikingly similar phenotype characterized by prenatal growth retardation, localized cutis scalp aplasia with or without skull defects, neurodevelopmental delay with autism spectrum disorder, enamel hypoplasia, and congenital cataracts. Mutant FOSL2 messenger RNAs escaped nonsense-mediated messenger RNA decay. Truncated FOSL2 interacts with c-JUN, thus mutated AP-1 complexes could be formed. CONCLUSION: Truncating variants in the last exon of FOSL2 associate a distinct clinical phenotype by altering the regulatory degradation of the AP-1 complex. These findings reveal a new role for FOSL2 in human pathology.

Genomic and phenotypic characterization of 404 individuals with neurodevelopmental disorders caused by CTNNB1 variants.

PURPOSE: Germline loss-of-function variants in CTNNB1 cause neurodevelopmental disorder with spastic diplegia and visual defects (NEDSDV; OMIM 615075) and are the most frequent, recurrent monogenic cause of cerebral palsy (CP). We investigated the range of clinical phenotypes owing to disruptions of CTNNB1 to determine the association between NEDSDV and CP. METHODS: Genetic information from 404 individuals with collectively 392 pathogenic CTNNB1 variants were ascertained for the study. From these, detailed phenotypes for 52 previously unpublished individuals were collected and combined with 68 previously published individuals with comparable clinical information. The functional effects of selected CTNNB1 missense variants were assessed using TOPFlash assay. RESULTS: The phenotypes associated with pathogenic CTNNB1 variants were similar. A diagnosis of CP was not significantly associated with any set of traits that defined a specific phenotypic subgroup, indicating that CP is not additional to NEDSDV. Two CTNNB1 missense variants were dominant negative regulators of WNT signaling, highlighting the utility of the TOPFlash assay to functionally assess variants. CONCLUSION: NEDSDV is a clinically homogeneous disorder irrespective of initial clinical diagnoses, including CP, or entry points for genetic testing.

The early-life exposome modulates the effect of polymorphic inversions on DNA methylation.

Polymorphic genomic inversions are chromosomal variants with intrinsic variability that play important roles in evolution, environmental adaptation, and complex traits. We investigated the DNA methylation patterns of three common human inversions, at 8p23.1, 16p11.2, and 17q21.31 in 1,009 blood samples from children from the Human Early Life Exposome (HELIX) project and in 39 prenatal heart tissue samples. We found inversion-state specific methylation patterns within and nearby flanking each inversion region in both datasets. Additionally, numerous inversion-exposure interactions on methylation levels were identified from early-life exposome data comprising 64 exposures. For instance, children homozygous at inv-8p23.1 and higher meat intake were more susceptible to TDH hypermethylation (P = 3.8 × 10-22); being the inversion, exposure, and gene known risk factors for adult obesity. Inv-8p23.1 associated hypermethylation of GATA4 was also detected across numerous exposures. Our data suggests that the pleiotropic influence of inversions during development and lifetime could be substantially mediated by allele-specific methylation patterns which can be modulated by the exposome.

Systematic Collaborative Reanalysis of Genomic Data Improves Diagnostic Yield in Neurologic Rare Diseases.

Many patients experiencing a rare disease remain undiagnosed even after genomic testing. Reanalysis of existing genomic data has shown to increase diagnostic yield, although there are few systematic and comprehensive reanalysis efforts that enable collaborative interpretation and future reinterpretation. The Undiagnosed Rare Disease Program of Catalonia project collated previously inconclusive good quality genomic data (panels, exomes, and genomes) and standardized phenotypic profiles from 323 families (543 individuals) with a neurologic rare disease. The data were reanalyzed systematically to identify relatedness, runs of homozygosity, consanguinity, single-nucleotide variants, insertions and deletions, and copy number variants. Data were shared and collaboratively interpreted within the consortium through a customized Genome-Phenome Analysis Platform, which also enables future data reinterpretation. Reanalysis of existing genomic data provided a diagnosis for 20.7% of the patients, including 1.8% diagnosed after the generation of additional genomic data to identify a second pathogenic heterozygous variant. Diagnostic rate was significantly higher for family-based exome/genome reanalysis compared with singleton panels. Most new diagnoses were attributable to recent gene-disease associations (50.8%), additional or improved bioinformatic analysis (19.7%), and standardized phenotyping data integrated within the Undiagnosed Rare Disease Program of Catalonia Genome-Phenome Analysis Platform functionalities (18%).

The RD-Connect Genome-Phenome Analysis Platform: Accelerating diagnosis, research, and gene discovery for rare diseases.

Rare disease patients are more likely to receive a rapid molecular diagnosis nowadays thanks to the wide adoption of next-generation sequencing. However, many cases remain undiagnosed even after exome or genome analysis, because the methods used missed the molecular cause in a known gene, or a novel causative gene could not be identified and/or confirmed. To address these challenges, the RD-Connect Genome-Phenome Analysis Platform (GPAP) facilitates the collation, discovery, sharing, and analysis of standardized genome-phenome data within a collaborative environment. Authorized clinicians and researchers submit pseudonymised phenotypic profiles encoded using the Human Phenotype Ontology, and raw genomic data which is processed through a standardized pipeline. After an optional embargo period, the data are shared with other platform users, with the objective that similar cases in the system and queries from peers may help diagnose the case. Additionally, the platform enables bidirectional discovery of similar cases in other databases from the Matchmaker Exchange network. To facilitate genome-phenome analysis and interpretation by clinical researchers, the RD-Connect GPAP provides a powerful user-friendly interface and leverages tens of information sources. As a result, the resource has already helped diagnose hundreds of rare disease patients and discover new disease causing genes.

CIBERER: Spanish national network for research on rare diseases: A highly productive collaborative initiative.

CIBER (Center for Biomedical Network Research; Centro de Investigación Biomédica En Red) is a public national consortium created in 2006 under the umbrella of the Spanish National Institute of Health Carlos III (ISCIII). This innovative research structure comprises 11 different specific areas dedicated to the main public health priorities in the National Health System. CIBERER, the thematic area of CIBER focused on rare diseases (RDs) currently consists of 75 research groups belonging to universities, research centers, and hospitals of the entire country. CIBERER's mission is to be a center prioritizing and favoring collaboration and cooperation between biomedical and clinical research groups, with special emphasis on the aspects of genetic, molecular, biochemical, and cellular research of RDs. This research is the basis for providing new tools for the diagnosis and therapy of low-prevalence diseases, in line with the International Rare Diseases Research Consortium (IRDiRC) objectives, thus favoring translational research between the scientific environment of the laboratory and the clinical setting of health centers. In this article, we intend to review CIBERER's 15-year journey and summarize the main results obtained in terms of internationalization, scientific production, contributions toward the discovery of new therapies and novel genes associated to diseases, cooperation with patients' associations and many other topics related to RD research.

Diagnosis of Genetic White Matter Disorders by Singleton Whole-Exome and Genome Sequencing Using Interactome-Driven Prioritization.

BACKGROUND AND OBJECTIVES: Genetic white matter disorders (GWMD) are of heterogeneous origin, with >100 causal genes identified to date. Classic targeted approaches achieve a molecular diagnosis in only half of all patients. We aimed to determine the clinical utility of singleton whole-exome sequencing and whole-genome sequencing (sWES-WGS) interpreted with a phenotype- and interactome-driven prioritization algorithm to diagnose GWMD while identifying novel phenotypes and candidate genes. METHODS: A case series of patients of all ages with undiagnosed GWMD despite extensive standard-of-care paraclinical studies were recruited between April 2017 and December 2019 in a collaborative study at the Bellvitge Biomedical Research Institute (IDIBELL) and neurology units of tertiary Spanish hospitals. We ran sWES and WGS and applied our interactome-prioritization algorithm based on the network expansion of a seed group of GWMD-related genes derived from the Human Phenotype Ontology terms of each patient. RESULTS: We evaluated 126 patients (101 children and 25 adults) with ages ranging from 1 month to 74 years. We obtained a first molecular diagnosis by singleton WES in 59% of cases, which increased to 68% after annual reanalysis, and reached 72% after WGS was performed in 16 of the remaining negative cases. We identified variants in 57 different genes among 91 diagnosed cases, with the most frequent being RNASEH2B, EIF2B5, POLR3A, and PLP1, and a dual diagnosis underlying complex phenotypes in 6 families, underscoring the importance of genomic analysis to solve these cases. We discovered 9 candidate genes causing novel diseases and propose additional putative novel candidate genes for yet-to-be discovered GWMD. DISCUSSION: Our strategy enables a high diagnostic yield and is a good alternative to trio WES/WGS for GWMD. It shortens the time to diagnosis compared to the classical targeted approach, thus optimizing appropriate management. Furthermore, the interactome-driven prioritization pipeline enables the discovery of novel disease-causing genes and phenotypes, and predicts novel putative candidate genes, shedding light on etiopathogenic mechanisms that are pivotal for myelin generation and maintenance.