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The genetic basis of severe COVID-19 has been thoroughly studied, and many genetic risk factors shared between populations have been identified. However, reduced sample sizes from non-European groups have limited the discovery of population-specific common risk loci. In this second study nested in the SCOURGE consortium, we conducted a genome-wide association study (GWAS) for COVID-19 hospitalization in admixed Americans, comprising a total of 4702 hospitalized cases recruited by SCOURGE and seven other participating studies in the COVID-19 Host Genetic Initiative. We identified four genome-wide significant associations, two of which constitute novel loci and were first discovered in Latin American populations (BAZ2B and DDIAS). A trans-ethnic meta-analysis revealed another novel cross-population risk locus in CREBBP. Finally, we assessed the performance of a cross-ancestry polygenic risk score in the SCOURGE admixed American cohort. This study constitutes the largest GWAS for COVID-19 hospitalization in admixed Latin Americans conducted to date. This allowed to reveal novel risk loci and emphasize the need of considering the diversity of populations in genomic research.

Abstract Bardet–Biedl syndrome (BBS) is an autosomal recessive ciliopathy characterized by extensive inter- and intra-familial variability, in which oligogenic interactions have been also reported. Our main goal is to elucidate the role of mutational load in the clinical variability of BBS. A cohort of 99 patients from 77 different families with biallelic pathogenic variants in a BBS-associated gene was retrospectively recruited. Human Phenotype Ontology terms were used in the annotation of clinical symptoms. The mutational load in 39 BBS-related genes was studied in index cases using different molecular and next-generation sequencing (NGS) approaches. Candidate allele combinations were analysed using the in silico tools ORVAL and DiGePred. After clinical annotation, 76 out of the 99 cases a priori fulfilled established criteria for diagnosis of BBS or BBS-like. BBS1 alleles, found in 42% of families, were the most represented in our cohort. An increased mutational load was excluded in 41% of the index cases (22/54). Oligogenic inheritance was suspected in 52% of the screened families (23/45), being 40 tested by means of NGS data and 5 only by traditional methods. Together, ORVAL and DiGePred platforms predicted an oligogenic effect in 44% of the triallelic families (10/23). Intrafamilial variable severity could be clinically confirmed in six of the families. Our findings show that the presence of more than two alleles in BBS-associated genes correlated in six families with a more severe phenotype and associated with specific findings, highlighting the role of the mutational load in the management of BBS cases.

Abstract Rare variants affecting host defense against pathogens could be involved in COVID-19 severity and may help explain fatal outcomes in young and middle-aged patients. Our aim was to report the presence of rare genetic variants in certain genes, by using whole exome sequencing, in a selected group of COVID-19 patients under 65 years who required intubation or resulting in death (n = 44). To this end, different etiopathogenic mechanisms were explored using gene prioritization-based analysis in which genes involved in immune response, immunodeficiencies or blood coagulation were studied. We detected 44 different variants of interest, in 29 different patients (66%). Some of these variants were previously described as pathogenic and were located in genes mainly involved in immune response. A network analysis, including the 42 genes with candidate variants, showed three main components, consisting of 25 highly interconnected genes related to immune response and two additional networks composed by genes enriched in carbohydrate metabolism and in DNA metabolism and repair processes. In conclusion, we have detected candidate variants that may potentially influence COVID-19 outcome in our cohort of patients. Further studies are needed to confirm the ultimate role of the genetic variants described in the present study on COVID-19 severity.

Abstract The aim of this standard operational procedure is to standardize the methodology employed for the evaluation of pre- and post-treatment absorbed dose calculations in 90Y microsphere liver radioembolization. Basic assumptions include the permanent trapping of microspheres, the local energy deposition method for voxel dosimetry, and the patient–relative calibration method for activity quantification.The identity of 99mTc albumin macro-aggregates (MAA) and 90Y microsphere biodistribution is also assumed. The large observed discrepancies in some patients between 99mTc-MAA predictions and actual 90Y microsphere distributions for lesions is discussed. Absorbed dose predictions to whole non-tumoural liver are considered more reliable and the basic predictors of toxicity. Treatment planning based on mean absorbed dose delivered to the whole non-tumoural liver is advised, except in super-selective treatments. Given the potential mismatch between MAA simulation and actual therapy, absorbed doses should be calculated both pre- and post-therapy. Distinct evaluation between target tumours and non-tumoural tissue, including lungs in cases of lung shunt, are vital for proper optimization of therapy. Dosimetry should be performed first according to a mean absorbed dose approach, with an optional, but important, voxel level evaluation. Fully corrected 99mTc-MAA Single Photon Emission Computed Tomography (SPECT)/computed tomography (CT) and 90Y TOF PET/CT are regarded as optimal acquisition methodologies, but, for institutes where SPECT/CT is not available, non-attenuation corrected 99mTc-MAA SPECT may be used. This offers better planning quality than non dosimetric methods such as Body Surface Area (BSA) or mono-compartmental dosimetry. Quantitative 90Y bremsstrahlung SPECT can be used if dedicated correction methods are available. The proposed methodology is feasible with standard camera software and a spreadsheet. Available commercial or free software can help facilitate the process and improve calculation time.

Abstract Background Mesenchymal stromal cells (MSCs) constitute one of the cell types most frequently used in cell therapy. Although several studies have shown the efficacy of these cells to modulate inflammation in different animal models, the results obtained in human clinical trials have been more modest. Here, we aimed at improving the therapeutic properties of MSCs by inducing a transient expression of two molecules that could enhance two different properties of these cells. With the purpose of improving MSC migration towards inflamed sites, we induced a transient expression of the C-X-C chemokine receptor type 4 (CXCR4). Additionally, to augment the anti-inflammatory properties of MSCs, a transient expression of the anti-inflammatory cytokine, interleukin 10 (IL10), was also induced. Methods Human adipose tissue-derived MSCs were transfected with messenger RNAs carrying the codon-optimized versions of CXCR4 and/or IL10. mRNA-transfected MSCs were then studied, first to evaluate whether the characteristic phenotype of MSCs was modified. Additionally, in vitro and also in vivo studies in an LPS-induced inflamed pad model were conducted to evaluate the impact associated to the transient expression of CXCR4 and/or IL10 in MSCs. Results Transfection of MSCs with CXCR4 and/or IL10 mRNAs induced a transient expression of these molecules without modifying the characteristic phenotype of MSCs. In vitro studies then revealed that the ectopic expression of CXCR4 significantly enhanced the migration of MSCs towards SDF-1, while an increased immunosuppression was associated with the ectopic expression of IL10. Finally, in vivo experiments showed that the co-expression of CXCR4 and IL10 increased the homing of MSCs into inflamed pads and induced an enhanced anti-inflammatory effect, compared to wild-type MSCs. Conclusions Our results demonstrate that the transient co-expression of CXCR4 and IL10 enhances the therapeutic potential of MSCs in a local inflammation mouse model, suggesting that these mRNA-modified cells may constitute a new step in the development of more efficient cell therapies for the treatment of inflammatory diseases.

Abstract Inherited retinal dystrophies (IRD) are a highly heterogeneous group of rare diseases with a molecular diagnostic rate of >50%. Reclassification of variants of uncertain significance (VUS) poses a challenge for IRD diagnosis. We collected 668 IRD cases analyzed by our geneticists using two different clinical exome-sequencing tests. We identified 114 unsolved cases pending reclassification of 125 VUS and studied their genomic, functional, and laboratory-specific features, comparing them to pathogenic and likely pathogenic variants from the same cohort (N = 390). While the clinical exome used did not show differences in diagnostic rate, the more IRD-experienced geneticist reported more VUS (p = 4.07e-04). Significantly fewer VUS were reported in recessive cases (p = 2.14e-04) compared to other inheritance patterns, and of all the genes analyzed, ABCA4 and IMPG2 had the lowest and highest VUS frequencies, respectively (p = 3.89e-04, p = 6.93e-03). Moreover, few frameshift and stop-gain variants were found to be informed VUS (p = 6.73e-08 and p = 2.93e-06). Last, we applied five pathogenicity predictors and found there is a significant proof of deleteriousness when all score for pathogenicity in missense variants. Altogether, these results provided input for a set of rules that correctly reclassified ~70% of VUS as pathogenic in validation datasets. Disease- and setting-specific features influence VUS reporting. Comparison with pathogenic and likely pathogenic variants can prioritize VUS more likely to be reclassified as causal.

Abstract Inherited retinal diseases (IRDs), defined by dysfunction or progressive loss of photoreceptors, are disorders characterized by elevated heterogeneity, both at the clinical and genetic levels. Our main goal was to address the genetic landscape of IRD in the largest cohort of Spanish patients reported to date. A retrospective hospital-based cross-sectional study was carried out on 6089 IRD affected individuals (from 4403 unrelated families), referred for genetic testing from all the Spanish autonomous communities. Clinical, demographic and familiar data were collected from each patient, including family pedigree, age of appearance of visual symptoms, presence of any systemic findings and geographical origin. Genetic studies were performed to the 3951 families with available DNA using different molecular techniques. Overall, 53.2% (2100/3951) of the studied families were genetically characterized, and 1549 different likely causative variants in 142 genes were identified. The most common phenotype encountered is retinitis pigmentosa (RP) (55.6% of families, 2447/4403). The most recurrently mutated genes were PRPH2, ABCA4 and RS1 in autosomal dominant (AD), autosomal recessive (AR) and X-linked (XL) NON-RP cases, respectively; RHO, USH2A and RPGR in AD, AR and XL for non-syndromic RP; and USH2A and MYO7A in syndromic IRD. Pathogenic variants c.3386G > T (p.Arg1129Leu) in ABCA4 and c.2276G > T (p.Cys759Phe) in USH2A were the most frequent variants identified. Our study provides the general landscape for IRD in Spain, reporting the largest cohort ever presented. Our results have important implications for genetic diagnosis, counselling and new therapeutic strategies to both the Spanish population and other related populations.

Introduction unCoVer—Unravelling data for rapid evidence-based response to COVID-19—is a Horizon 2020-funded network of 29 partners from 18 countries capable of collecting and using real-world data (RWD) derived from the response and provision of care to patients with COVID-19 by health systems across Europe and elsewhere. unCoVer aims to exploit the full potential of this information to rapidly address clinical and epidemiological research questions arising from the evolving pandemic.Methods and analysis From the onset of the COVID-19 pandemic, partners are gathering RWD from electronic health records currently including information from over 22 000 hospitalised patients with COVID-19, and national surveillance and screening data, and registries with over 1 900 000 COVID-19 cases across Europe, with continuous updates. These heterogeneous datasets will be described, harmonised and integrated into a multi-user data repository operated through Opal-DataSHIELD, an interoperable open-source server application. Federated data analyses, without sharing or disclosing any individual-level data, will be performed with the objective to reveal patients’ baseline characteristics, biomarkers, determinants of COVID-19 prognosis, safety and effectiveness of treatments, and potential strategies against COVID-19, as well as epidemiological patterns. These analyses will complement evidence from efficacy/safety clinical trials, where vulnerable, more complex/heterogeneous populations and those most at risk of severe COVID-19 are often excluded.Ethics and dissemination After strict ethical considerations, databases will be available through a federated data analysis platform that allows processing of available COVID-19 RWD without disclosing identification information to analysts and limiting output to data aggregates. Dissemination of unCoVer’s activities will be related to the access and use of dissimilar RWD, as well as the results generated by the pooled analyses. Dissemination will include training and educational activities, scientific publications and conference communications.

Summary: There are >200 types of protein posttranslational modifications (PTMs) described in eukaryotes, each with unique proteome coverage and functions. We hypothesized that some genetic diseases may be caused by the removal of a specific type of PTMs by genomic variants and the consequent deregulation of particular functions. We collected >320,000 human PTMs representing 59 types and crossed them with >4M nonsynonymous DNA variants annotated with predicted pathogenicity and disease associations. We report >1.74M PTM-variant co-occurrences that an enrichment analysis distributed into 215 pairwise associations between 18 PTM types and 148 genetic diseases. Of them, 42% were not previously described. Removal of lysine acetylation exerts the most pronounced effect, and less studied PTM types such as S-glutathionylation or S-nitrosylation show relevance. Using pathogenicity predictions, we identified PTM sites that may produce particular diseases if prevented. Our results provide evidence of a substantial impact of PTM-specific removal on the pathogenesis of genetic diseases and phenotypes.

Type 2 diabetes mellitus (T2DM) has been associated with an increased risk of cancer, including colon cancer (CC). However, we recently reported no influence of T2DM on CC prognosis, suggesting that any effect might be at the early stages of tumor development. We hypothesized that T2DM may create an environment in the healthy tissue, which acts as a carcinogenesis driver in agreement with the field of cancerization concept. Here, we focused on early carcinogenesis by analyzing paired tumor and normal colonic mucosa samples from the same patients. The proteome of CC and paired mucosa was quantitatively analyzed in 28 individuals (12 diabetics and 16 nondiabetics) by mass spectrometry with isobaric labeling. Out of 3076 identified proteins, 425 were differentially expressed at the tumor in diabetics compared with nondiabetics. In the adjacent mucosa, 143 proteins were differentially expressed in diabetics and nondiabetics. An enrichment analysis of this signature pointed to mitochondria, ribosome, and translation. Only six proteins were upregulated by diabetes both in tumor and mucosa, of which five were mitochondrial proteins. Differential expression in diabetic versus nondiabetic mucosa was confirmed for MRPL53, MRPL18, and TIMM8B. Higher levels of MRPL18, TIMM8B, and EIF1A were also found in normal colon epithelial cells exposed to high‐glucose conditions. We conclude that T2DM is associated with specific molecular changes in the normal mucosa of CC patients, consistent with field of cancerization in a diabetic environment. The mitochondrial protein signature identifies a potential therapeutic target that could underlie the higher risk of CC in diabetics.

The potential involvement of type 2 diabetes mellitus (T2DM) as a risk factor for colon cancer (CC) has been previously reported. While several clinical studies show a higher incidence of CC and a lower survival rate in diabetics, others report no association. Our own experience indicates that diabetes does not seem to worsen the prognosis once the tumor is present. Despite this controversy, there are no wide‐spectrum molecular studies that delve into the impact of T2DM‐related mechanisms in colon carcinogenesis. Here, we present a transcriptomic and proteomic profiling of paired tumor and normal colon mucosa samples in a cohort of 42 CC patients, 23 of which have T2DM. We used gene set enrichment and network approaches to extract relevant pathways in diabetics, referenced them to current knowledge, and tested them using in vitro techniques. Through our transcriptomics approach, we identified an unexpected overlap of pathways overrepresented in diabetics compared to nondiabetics, in both tumor and normal mucosa, including diabetes‐related metabolic and signaling processes. Proteomic approaches highlighted several cancer‐related signaling routes in diabetics found only in normal mucosa, not in tumors. An integration of the transcriptome and proteome analyses suggested the deregulation of key pathways related to colon carcinogenesis which converged on tumor initiation axis TEAD/YAP‐TAZ as a potential initiator of the process. In vitro studies confirmed upregulation of this pathway in nontumor colon cells under high‐glucose conditions. In conclusion, T2DM associates with deregulation of cancer‐related processes in normal colon mucosa adjacent to tissue which has undergone a malignant transformation. These data support that in diabetic patients, the local microenvironment in normal colon mucosa may be a factor driving field cancerization promoting carcinogenesis. Our results set a new framework to study links between diabetes and colon cancer, including a new role of the TEAD/YAP‐TAZ complex as a potential driver.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Abstract Background Currently, the implementation of dosimetry in molecular radiotherapy (MRT) is not well investigated, and in view of the Council Directive (2013/59/Euratom), there is a need to understand the current availability of dosimetry-based MRT in clinical practice and research studies. The aim of this study was to assess the current practice of MRT and dosimetry across European countries. Methods An electronic questionnaire was distributed to European countries. This addressed 18 explicitly considered therapies, and for each therapy, a similar set of questions were included. Questions covered the number of patients and treatments during 2015, involvement of medical specialties and medical physicists, implementation of absorbed dose planning, post-therapy imaging and dosimetry, and the basis of therapy prescription. Results Responses were obtained from 26 countries and 208 hospitals, administering in total 42,853 treatments. The most common therapies were 131I-NaI for benign thyroid diseases and thyroid ablation of adults. The involvement of a medical physicist (mean over all 18 therapies) was reported to be either minority or never by 32% of the responders. The percentage of responders that reported that dosimetry was included on an always/majority basis differed between the therapies and showed a median value of 36%. The highest percentages were obtained for 177Lu-PSMA therapy (100%), 90Y microspheres of glass (84%) and resin (82%), 131I-mIBG for neuroblastoma (59%), and 131I-NaI for benign thyroid diseases (54%). The majority of therapies were prescribed based on fixed-activity protocols. The highest number of absorbed-dose based prescriptions were reported for 90Y microsphere treatments in the liver (64% and 96% of responses for resin and glass, respectively), 131I-NaI treatment of benign thyroid diseases (38% of responses), and for 131I-mIBG treatment of neuroblastoma (18% of responses). Conclusions There is a wide variation in MRT practice across Europe and for different therapies, including the extent of medical-physicist involvement and the implementation of dosimetry-guided treatments.

Abstract Background The European directive on basic safety standards (Council directive 2013/59 Euratom) mandates dosimetry-based treatment planning for radiopharmaceutical therapies. The directive comes into operation February 2018, and the aim of a report produced by the Internal Dosimetry Task Force of the European Association of Nuclear Medicine is to address this aspect of the directive. A summary of the report is presented. Results A brief review of five of the most common therapy procedures is included in the current text, focused on the potential to perform patient-specific dosimetry. In the full report, 11 different therapeutic procedures are included, allowing additional considerations of effectiveness, references to specific literature on quantitative imaging and dosimetry, and existing evidence for absorbed dose-effect correlations for each treatment. Individualized treatment planning with tracer diagnostics and verification of the absorbed doses delivered following therapy is found to be scientifically feasible for almost all procedures investigated, using quantitative imaging and/or external monitoring. Translation of this directive into clinical practice will have significant implications for resource requirements. Conclusions Molecular radiotherapy is undergoing a significant expansion, and the groundwork for dosimetry-based treatment planning is already in place. The mandated individualization is likely to improve the effectiveness of the treatments, although must be adequately resourced.

Proteomics techniques can identify thousands of phosphorylation sites in a single experiment, the majority of which are new and lack precise information about function or molecular mechanism. Here we present a fast method to predict potential phosphorylation switches by mapping phosphorylation sites to protein-protein interactions of known structure and analysing the properties of the protein interface. We predict 1024 sites that could potentially enable or disable particular interactions. We tested a selection of these switches and showed that phosphomimetic mutations indeed affect interactions. We estimate that there are likely thousands of phosphorylation mediated switches yet to be uncovered, even among existing phosphorylation datasets. The results suggest that phosphorylation sites on globular, as distinct from disordered, parts of the proteome frequently function as switches, which might be one of the ancient roles for kinase phosphorylation.

BACKGROUND:Multiple observational studies suggest an increased risk of colon cancer in patients with diabetes mellitus (DM). This can theoretically be the result of an influence of the diabetic environment on carcinogenesis or the tumor biologic behavior. AIM:To gain insight into the influence of a diabetic environment on colon cancer characteristics and outcomes. MATERIAL AND METHODS:Retrospective analysis of clinical records in an academic tertiary care hospital with detailed analysis of 81 diabetic patients diagnosed of colon cancer matched with 79 non-diabetic colon cancer patients. The impact of streptozotocin-induced diabetes on the growth of colon cancer xenografts was studied in mice. RESULTS:The incidence of DM in 1,137 patients with colorectal cancer was 16%. The diabetic colon cancer cases and non-diabetic colon cancer controls were well matched for demographic and clinical variables. The ECOG Scale Performance Status was higher (worse) in diabetics (ECOG ≥1, 29.1% of controls vs 46.9% of diabetics, p = 0.02), but no significant differences were observed in tumor grade, adjuvant therapy, tumor site, lymphovascular invasion, stage, recurrence, death or cancer-related death. Moreover, no differences in tumor variables were observed between patients treated or not with metformin. In the xenograft model, tumor growth and histopathological characteristics did not differ between diabetic and nondiabetic animals. CONCLUSION:Our findings point towards a mild or negligible effect of the diabetes environment on colon cancer behavior, once cancer has already developed.

Abstract Various post‐translational modifications (PTMs) fine‐tune the functions of almost all eukaryotic proteins, and co‐regulation of different types of PTMs has been shown within and between a number of proteins. Aiming at a more global view of the interplay between PTM types, we collected modifications for 13 frequent PTM types in 8 eukaryotes, compared their speed of evolution and developed a method for measuring PTM co‐evolution within proteins based on the co‐occurrence of sites across eukaryotes. As many sites are still to be discovered, this is a considerable underestimate, yet, assuming that most co‐evolving PTMs are functionally associated, we found that PTM types are vastly interconnected, forming a global network that comprise in human alone >50 000 residues in about 6000 proteins. We predict substantial PTM type interplay in secreted and membrane‐associated proteins and in the context of particular protein domains and short‐linear motifs. The global network of co‐evolving PTM types implies a complex and intertwined post‐translational regulation landscape that is likely to regulate multiple functional states of many if not all eukaryotic proteins.

The genome of Mycobacterium tuberculosis (H37Rv) contains 4,019 protein coding genes, of which more than thousand have been categorized as 'hypothetical' implying that for these not even weak functional associations could be identified so far. We here predict reliable functional indications for half of this large hypothetical orfeome: 497 genes can be annotated based on orthology, and another 125 can be linked to interacting proteins via integrated genomic context analysis and literature mining. The assignments include newly identified clusters of interacting proteins, hypothetical genes that are associated to well known pathways and putative disease-relevant targets. All together, we have raised the fraction of the proteome with at least some functional annotation to 88% which should considerably enhance the interpretation of large-scale experiments targeting this medically important organism.

Microarray experiments have been extensively used to define signatures, which are sets of genes that can be considered markers of experimental conditions (typically diseases). Paradoxically, in spite of the apparent functional role that might be attributed to such gene sets, signatures do not seem to be reproducible across experiments. Given the close relationship between function and protein interaction, network properties can be used to study to what extent signatures are composed of genes whose resulting proteins show a considerable level of interaction (and consequently a putative common functional role).We have analysed 618 signatures and 507 modules of co-expression in cancer looking for significant values of four main protein-protein interaction (PPI) network parameters: connection degree, cluster coefficient, betweenness and number of components. A total of 3904 gene ontology (GO) modules, 146 KEGG pathways, and 263 Biocarta pathways have been used as functional modules of reference.Co-expression modules found in microarray experiments display a high level of connectivity, similar to the one shown by conventional modules based on functional definitions (GO, KEGG and Biocarta). A general observation for all the classes studied is that the networks formed by the modules improve their topological parameters when an external protein is allowed to be introduced within the paths (up to the 70% of GO modules show network parameters beyond the random expectation). This fact suggests that functional definitions are incomplete and some genes might still be missing. Conversely, signatures are clearly not capturing the altered functions in the corresponding studies. This is probably because the way in which the genes have been selected in the signatures is too conservative. These results suggest that gene selection methods which take into account relationships among genes should be superior to methods that assume independence among genes outside their functional contexts.

An increasing number of evidences show that genes are not distributed randomly across eukaryotic chromosomes, but rather in functional neighborhoods. Nevertheless, the driving force that originated and maintains such neighborhoods is still a matter of controversy. We present the first detailed multispecies cartography of genome regions enriched in genes with related functions and study the evolutionary implications of such clustering. Our results indicate that the chromosomes of higher eukaryotic genomes contain up to 12% of genes arranged in functional neighborhoods, with a high level of gene co-expression, which are consistently distributed in phylogenies. Unexpectedly, neighborhoods with homologous functions are formed by different (non-orthologous) genes in different species. Actually, instead of being conserved, functional neighborhoods present a higher degree of synteny breaks than the genome average. This scenario is compatible with the existence of selective pressures optimizing the coordinated transcription of blocks of functionally related genes. If these neighborhoods were broken by chromosomal rearrangements, selection would favor further rearrangements reconstructing other neighborhoods of similar function. The picture arising from this study is a dynamic genomic landscape with a high level of functional organization.

Exploring non-coding regions is increasingly gaining importance in the diagnosis of inherited retinal dystrophies. Deep-intronic variants causing aberrant splicing have been identified, prompting the development of antisense oligonucleotides (ASOs) to modulate splicing. We performed a screening of five previously described USH2A deep-intronic variants among USH2A monoallelic patients with Usher syndrome (USH) or isolated retinitis pigmentosa. Sequencing of entire USH2A or USH genes was then conducted in unresolved or newly monoallelic cases. The splicing impact of identified variants was assessed using minigene assays, and ASOs were designed to correct splicing. The screening allowed to diagnose 30.95% of the studied patients. The sequencing of USH genes revealed 16 new variants predicted to affect splicing, with four confirmed to affect splicing through minigene assays. Two of them were unreported deep-intronic variants and predicted to include a pseudoexon in the pre-mRNA, and the other two could alter a regulatory cis-element. ASOs designed for three USH2A deep-intronic variants successfully redirected splicing in vitro. Our study demonstrates the improvement in genetic characterization of IRDs when analyzing non-coding regions, highlighting that deep-intronic variants significantly contribute to USH2A pathogenicity. Furthermore, successful splicing modulation through ASOs highlights their therapeutic potential for patients carrying deep-intronic variants.