Human Genetics

Non-coding variants altering mRNA splicing are increasingly recognized as important cause of Mendelian disorders. Deep intronic variants (DIV) that activate cryptic exons (CEs) cause ~20% inherited retinal diseases (IRD) cases, yet it remains challenging to predict intronic variant pathogenicity accurately, thus we used a high throughput splicing assay (HTSA) to measure the effects of rare deep intronic variants in recessive IRDs with one confirmed pathogenic variant. 640 very rare deep intronic variants were chosen in trans-position with known mutation from 76 patients. We tested them with HTSA, which consists of a split-GFP minigene, separated by an SMN1 gene intron into which the 270bp sequences flanking the DIVs were cloned. The plasmid library was transfected into 293HEK cells, and 48 hours later total RNA was extracted from the transfected cells. RNA transcripts produced by HTSA minigene were amplified by RT-PCR and sequenced. The intron sequences spliced between the two GFP exons were identified and quantified. 98 variants activated CE >100 times more in altered oligo compared to reference oligo and were classified as pathogenic in this experimental setting, validated in longer context, 26 variants were classified as VUS. Interestingly, only 6 from 90 variants (6,6%) were predicted to be pathogenic by in silico algorithms (Splice AI) which leaves room for significant improvement of prediction algorithms. The results of this experiment confirmed diagnosis for 50 of 78 patients (64%). So, 19,4% of deep intronic variants were shown to cause CE activation. This can lead to conclusion that significant portion of undiagnosed patients with recessive IRDs carry pathogenic intronic mutation which causes the disease.

Objective: The objective of this study was to detect genetic factors associated with dermatochalasis using a genome-wide association study (GWAS) across three large cohorts. Design: GWAS meta-analysis Participants: A total of 13,200 dermatochalasis cases and 962,513 controls were included. Methods: A GWAS meta-analysis of dermatochalasis combining data from the FinnGen, the Estonian Biobank and the UK Biobank was conducted. We also performed colocalization analyses, a phenome-wide association study and age-at-onset analysis, and assessed genetic correlations with various diseases and traits. Main outcome measures: Identification of genetic variants associated with dermatochalasis. Results: We identified 18 loci associated with dermatochalasis at genome-wide significance, 16 of which were novel. Most of these loci had genes involved in skin biology and cutaneous diseases, such as the genes encoding elastin (ELN) and Latent TGF-{beta} binding protein 1 (LTBP1). Phenome-wide association study revealed previous associations with morphology-related traits, while genetic correlation analysis highlighted multiple genetic correlations, especially with smoking and pain. Conclusions: We detected 18 genetic loci associated with dermatochalasis, characterized these loci in detail and demonstrated their relevance in skin biology and related processes. These findings give novel information on the genetic background of dermatochalasis and provide a solid basis for further research.

Genetic variants in PROM1 are associated with inherited blindness, but clinical phenotypes vary widely with currently no consensus on disease expectations or predicted patient outcomes. To address this issue, we performed chi-square correlation analysis on 190 published pathogenic and likely pathogenic variants from ClinVar Miner and the Human Gene Mutation Database. We identified a statistically significant increase in observed cases of dominantly inherited missense variants, which were associated with milder forms of macular dystrophy. Recessive inheritance of truncating frameshift variants was associated with more severe forms of inherited retinal degeneration such as rod-cone dystrophy. We also present case studies from 7 patients with phenotypes that are unique, unreported, or do not match the reported phenotype in online databases. We report two patients with VUS that have clinical phenotypes and dominantly inherited missense variants, one patient with a long natural history at our clinic, two patients with the same variant, but a different clinical diagnosis, and two patients with retinal deposits comprising subretinal drusenoid deposits (SDD) and soft drusen.

It is desirable to quantify the prediction accuracy of polygenic scores (PGS) for disease on the scale of liability and adjusted for case-control ascertainment in the test sample, because that allows comparison across prevalence and ascertainment. Previous expressions have focused in their derivation and implementation on linear regression on the observed 0-1 scale followed by a transformation of the coefficient of determination (R2) to the scale of liability, adjusted for ascertainment. Yet most statistical analyses with empirical data use logistic regression. The differences in scale have led to confusion and incorrect transformations in the literature. Here we provide a new derivation and simple equation, validated by simulation, that allows a direct transformation from the empirical results from logistic regression to the scale of liability.

Purpose A significant proportion of cases with rare inherited retinal disease (IRD) remain genetically unresolved following short-read whole genome sequencing (WGS). This study aimed to increase the diagnostic yield of two cohorts in a research setting. One cohort was previously screened by short-read WGS (n=120 cases), while the second cohort (n=28 cases) was not included in any previous short-read WGS studies. In contrast to the larger cohort, these cases only underwent either exome sequencing (ES) or single-molecule molecular inversion probe (smMIPs) sequencing as pre-screening in earlier studies. For all cases, we performed a stepwise, case by case reanalysis in which short-read WGS was generated (n=28 cases) and (re)analyzed short-read WGS data using an optimized approach. For a subset of cases (n=20) that remained unresolved, this was followed by long read WGS. Together, these steps aimed to improve the diagnostic yield in these cohorts. Methods Short-read WGS data of 148 IRD-cases were (re)analyzed using updated allele frequency databases, new variant caller and variant predictor tools, as well as updated and extended gene-panels to identify causal single nucleotide variants (SNVs) and structural variants (SVs). For 20 genetically unresolved cases with sufficient high-quality DNA available, long-read WGS was performed. Results The (re)analysis of short-read WGS data in the 120 previously WGS-screened unresolved cases resulted in a diagnostic yield of 15% (18/120). For the 28 individuals without prior WGS, performing WGS analysis within this study provided an additional yield of 32% (9/28). Furthermore, long-read WGS contributed two genetic diagnoses among the 20 long-read WGS-sequenced probands. Amongst other reasons, new genetic diagnoses were attributed to pathogenic variants in genes newly associated with IRDs and in genes that were not included in the gene panels applied in previous WGS studies. The Mobile Element Locator Tool facilitated the identification of two pathogenic Alu insertions in short-read WGS. Long-read WGS identified two additional pathogenic variants. Conclusion These results support periodic reanalysis of existing short-read WGS data as a key component of IRD genetic diagnostics, with selective long-read WGS representing a valuable additional approach for unresolved cases. Together, these complementary strategies offer a practical framework for improving molecular diagnosis and narrowing the remaining diagnostic gap in IRDs.

Structural variants (SVs) are larger genetic rearrangements such as deletions, duplications, and insertions and other forms of structural alterations. Given their large size, they can have an outsized effect on phenotype, however, the contribution of SVs to the genetic architecture of orofacial clefts (OFCs) is not well understood. In this study, we sought to better understand the contribution SVs to OFC risk by characterizing de novo SVs (dnSVs) in 1,549 probands with an OFC. Overall, we called 375 dnSVs in 307 probands (0.242 dnSVs per genome). The dnSV rate per genome was highest among individuals with cleft lip (CL, 0.29), followed by cleft lip and palate (CLP, 0.25) and cleft palate only (CP, 0.20), though differences across subtypes were not statistically significant. There were also no differences between sex or syndromic status, but we did identify a significant difference in the rate of duplications across OFC subtypes (p=0.005). Compared to CP (0.028), duplication rates were significantly higher for both CL (0.121; p = 0.003) and CLP (0.096; p = 0.002), suggesting a potential etiologic mechanism for CL/P. We systematically curated each dnSV to classify its potential for influencing OFC risk by examining the genes and regulatory elements disrupted by the SV and evidence for their role in craniofacial development or OFCs. We identified 22 dnSVs in regions associated with recurrent genomic disorders, including seven deletions and one duplication of the well-established OFC risk locus 22q11.2. Additionally, we identified 12 large (>1Mb) SVs, with eight meeting criteria for a likely pathogenic classification based on total gene involvement, and seven dnSVs disrupting well-known genes associated with autosomal dominant forms of OFC. The most notable was SATB2, for which we found four dnSVs, all in individuals with CP. Next, by combining evidence from recurrent dnSVs and de novo single nucleotide variants with Hi-C contact maps and predicted chromatin states from developing craniofacial tissues, we found new candidate genes for OFC risk including FHAD1, NBEA, NR3C2, and SPHKAP. Overall, dnSVs classified as likely pathogenic accounted for putative molecular diagnoses in approximately 1.67% of the cohort, with an additional 0.96% having variants of unknown significance with plausible risk for OFCs. Our results support dnSVs as an important component of OFC etiology and suggest their inclusion in analyses may improve diagnostic yield for affected individuals.

Abstract INTRODUCTION Despite major advances in genomic sequencing and analytical pipelines for rare disorders, more than 50% of affected individuals remain without a molecular diagnosis. One challenge is the interpretation of inherited variants exhibiting incomplete penetrance (IP). MATERIALS AND METHODS We developed a pipeline to systematically investigate inherited variants as the cause of rare disease in 4,325 families, consisting of affected probands and unaffected parents, from the Broad Center for Mendelian Genomics, part of the GREGoR Consortium. As a proof-of-concept of further omics follow-up, epigenomic and transcriptomic analyses were performed in one family harboring an inherited disease-causing frameshift variant in CHD8. RESULTS We identified 81 families where the affected proband harbored a putative disease-causing variant inherited from a reportedly unaffected parent. Clinical re-evaluation identified 30 families in which an inherited variant was considered diagnostic, including six previously missed diagnoses. In this cohort, inherited IP variants account for 1.6% of the diagnosed cases, with an overall diagnostic yield of 0.4% in the cohort. Methylation analysis of the CHD8 family confirmed a positive CHD8 clinical episignature in the male proband, but also in the reportedly unaffected mother. Transcriptomic analysis showed that despite similar CHD8 haploinsufficiency, the proband and mother displayed divergent downstream transcriptional effects. DISCUSSION This study highlights the importance of considering parentally inherited IP variants in rare disease, with at least 1 in 60 diagnostic variants inherited from a reportedly unaffected parent, and demonstrates the potential of integrating omics evaluation to improve variant interpretation.

Background: The inner ear is supplied by the labyrinthine artery, which is functionally close to an end artery with limited collateral reserve. Microvascular abnormalities have been implicated in sudden sensorineural hearing loss (SSNHL) and age-related hearing loss, yet inner-ear microvasculature cannot be assessed in vivo and current hearing genome-wide association studies (GWAS) are underpowered. We evaluated the shared genetic architecture of retinal arteriolar tortuosity (retina_AT) with blood pressure, cerebral small vessel disease (cSVD) and hearing phenotypes, and examined whether retinal microvasculature could serve as a candidate genetic window to inner-ear microvasculature. Methods: We used linkage-disequilibrium score regression (LDSC) to estimate SNP heritability for 19 phenotypes and genome-wide genetic correlations (rg) for 11 prespecified pairs. We ran approximate Bayes-factor colocalization (coloc.abf) between 19 independent retinal loci and systolic blood pressure (SBP), together with 95% credible-set fine-mapping, UCSC gene annotation, colocalization with GTEx aortic and tibial-artery expression QTL (eQTL) data and with white-matter hyperintensities (WMH), hearing-GWAS power calculations, and univariable and multivariable Mendelian randomization (MR) of blood pressure and heart rate on hearing. Results: Only retina_AT with SBP was significant genome-wide (rg = 0.10, P = 4.2x10, FDR q = 0.00042). The strongest retinal locus, 13q34, did not colocalize (PP.H3 = 0.996; peaks about 267 kb apart; allelic heterogeneity), whereas two secondary loci colocalized strongly--CSK at 15q24 (PP.H4 = 0.98; 3/3 credible variants within CSK) and PAWR at 12q21 (PP.H4 = 0.99; 3/5 within PAWR)--supported by tissue-matched, moderate eQTL evidence (PP.H4 = 0.71-0.75). At 13q34, retina_AT with WMH was an adequately powered null (PP.H4 = 0.019; only this region and phenotype were tested). On the hearing side, sharing of the blood-pressure magnitude (rg {approx} 0.10) was a near-powered null (about 1.5-fold larger sample needed for 80% power under that assumption, versus about 15-fold for weak rg {approx} 0.03 sharing), and rg [≥] 0.12 was excluded; MR found no robust causal effect. Conclusions: Retinal arteriolar tortuosity shows limited, distributed genetic sharing with blood pressure at the vascular-tone genes CSK and PAWR; no sharing with WMH was observed at 13q34 (only this region was tested). Retinal microvasculature may serve as a candidate genetic window to inner-ear microvasculature, but this analogy awaits direct testing by larger, vessel-oriented hearing GWAS and inner-ear tissue functional studies.

Pathogenic variants in the myocilin (MYOC) gene are the most common cause of Mendelian open-angle glaucoma. In 2022, the Clinical Genome Resource (ClinGen) Glaucoma Variant Curation Expert Panel (VCEP) published rule specifications for MYOC variant interpretation, including a pilot study of 81 variants. Here, we present the results of curating 271 MYOC variants reported in people with open-angle glaucoma using updated specification rules. Of all the variants, 11 were classified as benign (B), 45 as likely benign (LB), 166 as variants of uncertain significance (VUS), 35 as likely pathogenic (LP), and 14 as pathogenic (P). All LP/P variants were located within the conserved olfactomedin domain encoded by exon 3. The updated variant curation guidelines from the Glaucoma VCEP increased the number of clinically definitive classifications from 28% (74/265) to 39% (105/271), with 95% (41/43) of reclassified variants moving to greater clinical relevance. Functional evidence was lacking for 93% (154/166) of VUS. Additional functional evidence could further enhance classification by halving (85/166) the proportion of those classified as VUS. These findings highlight the role of rule calibration and rigorous functional evidence assessment toward improving variant classification with clinical utility for patients.

BackgroundGenome-wide association studies (GWAS) often fail to identify higher-order epistatic interactions that contribute to complex inheritance patterns of traits and diseases. While machine learning (ML) can capture non-linear relationships, extracting interpretable insights from these models remains a challenge. We propose a novel tree-based feature engineering framework that uses Classification and Regression Trees (CART) to explicitly encode high-order interaction decision paths as dummy variables. We investigate three path-based encoding strategies: (i) all decision paths, (ii) leaf-node paths only, and (iii) internal-node paths only. This approach aims to transform complex decision boundaries into discrete features that capture nonlinear interactions that are not readily captured by traditional association models. ResultsThe framework was evaluated using genetic data for ANCA-associated vasculitis (AAV). To manage the high dimensionality of the engineered feature space, we applied a comprehensive suite of ML methods across three tasks: (1) Ensemble Learning (Random Forest, XGBoost, and Gradient Boosting Machine); (2) Decision Tree Analysis (CART); and (3) Regression and Classification Tasks (Regularized Linear Regression/LASSO, Support Vector Machine, and Logistic Regression). Stepwise feature selection and regularization were employed to isolate the most informative interaction patterns. Results indicate that incorporating CART-derived interaction paths--particularly those from high-impact regions of the tree--significantly improves classification accuracy and model interpretability compared to using the original feature space alone. ConclusionsThe proposed framework provides a robust, scalable methodology for identifying high-order genetic interactions. By bridging the gap between the predictive power of ensemble ML and the necessity for mechanistic insight, this approach offers a clearer mapping of the combinatorial genetic processes underlying complex diseases. While applied here to AAV, the method is highly adaptable for exploring the genetic architecture of diverse populations and complex traits.

Neurodevelopmental disorders (NDDs) are clinically and genetically heterogeneous, and evidence linking additional genes to disease evolves rapidly. We developed SysNDD, an open-access, expert-curated resource that represents distinct gene-inheritance-disease associations as entities with standardized confidence, phenotype, and variant annotations. Each entity retains its curation history, so its evidence category can change as evidence accumulates. Currently, SysNDD contains 4,275 entities curated from 4,932 publications. Of these, 3,758 entities involving 3,271 genes describe NDDs; the remainder record non-NDD disorders, nearly all linked to NDD-associated genes, included for completeness. Regarding NDD evidence categories, 1,838 genes are Definitive, 179 Moderate, 1,248 Limited, and 6 Refuted. The entity model captures inheritance-specific disorders, including 220 genes with both autosomal dominant and autosomal recessive NDD associations. Comparison with seven other NDD gene resources showed complementary coverage, and evidence categories largely agreed with those of ClinGen, Gene2Phenotype, and PanelApp for shared gene-disease pairs. NDD genes formed distinct molecular modules, whereas associated disorders formed broad, overlapping phenotype groups that corresponded to those modules only selectively. SysNDD provides a continuously maintained, programmatically accessible framework for gene-disease evidence assessment, inheritance-aware interpretation, and systematic NDD research.

Introduction: Coronary artery disease (CAD) is a leading cause of death and disability worldwide. Although genome-wide association studies (GWAS) have identified over 300 loci associated with CAD risk, the molecular mechanisms linking these variants to disease and subclinical atherosclerosis are not fully understood. Methods: We performed integration of multi-ancestry CAD GWAS with transcriptomic data from the Multi-Ethnic Study of Atherosclerosis (MESA) obtained through the Trans-Omics for Precision Medicine (TOPMed) program. For integration, we applied Bayesian colocalization analysis with and without statistical fine-mapping to identify genes whose expression levels colocalize with CAD-associated loci. We further applied causal weighted gene co-expression network analysis (cWGCNA) to identify gene co-expression modules and key driver genes associated with subclinical atherosclerosis traits in MESA. Results: We identified 108 genes showing evidence of colocalization with CAD loci, including 24 shared between the two colocalization approaches and 48 novel genes not previously reported in CAD GWAS. Follow-up replication and validation analyses prioritized 5 novel (CCDC30, ZEB1-AS1, ZPR1, PLEKHJ1 and AC018816.3) and 8 previously reported genes (DHDDS, DDX59, LNPEP, DAGLA, ZKSCAN1, LIPA, OPRL1 and EIF2B2) with putative roles in both CAD and subclinical atherosclerosis. cWGCNA identified five gene modules significantly associated with subclinical atherosclerosis in MESA. Additionally, three key driver genes (ATG9B, PRAM1 and ZBTB46) identified by cWGCNA were also identified as CAD-colocalized genes. Discussion: Our integrative analysis highlights key genetic drivers and regulatory networks underlying CAD and subclinical atherosclerosis. These findings underscore the value of incorporating statistical fine-mapping in colocalization studies and demonstrate the utility of combining colocalization with co-expression network analysis to prioritize functional genes and pathways.

Craniofacial malformations account for one third of all congenital anomalies. Genetic factors play a vital role, yet the list of causal genes and their mechanisms are far from complete. As part of a larger effort to sequence patients with micrognathia and Pierre-Robin sequence, we identified two candidate pathogenic missense variants in C-terminal binding protein 1 (CTBP1) along with a heterozygous early stop missense variant in alkaline phosphatase (ALPL) in a proband with mandibular hypoplasia. Ctbp1 has been shown to regulate Wnt/{beta}-Catenin signaling but it has not yet been implicated in craniofacial development. Here we generated two orthologous variants of Ctbp1 mimicking the patient variants using genome editing in mice and explored the micrognathia phenotype in combination with a previously reported Alpl null allele. Ctbp1Q148H/G238S; Alplnull/Wt complex heterozygous mutants have smaller mandibles recapitulating the human mandibular hypoplasia. We identified that a reduction in cell proliferation and active {beta}-Catenin levels could possibly account for the micrognathia phenotype in the Ctbp1; Alpl complex heterozygous. These data uncover a novel role for Ctbp1 in craniofacial development and highlight the complex genetic and molecular signaling in the pathogenesis of craniofacial malformations.

Background: Short-rib polydactyly syndrome type IV (Beemer-Langer syndrome) is a lethal skeletal ciliopathy that can result from biallelic pathogenic variants in KIAA0586 (TALPID3). Earlier clinical observations suggested an unusually high occurrence of this phenotype in Romani families from the Carpathian Basin. Methods: Whole-exome sequencing was performed in affected individuals from five independent families, and the frequency of KIAA0586 c.1815G>A was assessed in a Hungarian Romani genetic database of 500 individuals. Results: The affected individuals were homozygous for c.1815G>A, a splice-disrupting variant previously shown to cause exon 14 skipping. Four families self-identified as Roma from Hungary and one affected individual was from Turkey. Six heterozygous carriers were identified among 500 individuals in the Hungarian Romani cohort, corresponding to an allele frequency of 0.6%. This was markedly higher than the frequencies cited from ALFA (0.01%) and gnomAD (0.0014%). The Hungarian-Romani and Turkish affected individuals also shared genotypes at informative markers flanking the variant, supporting a shared ancestral haplotype. Conclusions: These observations strengthen evidence that KIAA0586 c.1815G>A is a founder allele enriched in at least some Romani populations. The data support consideration of ancestry-informed carrier testing in appropriately counseled families. Historical admixture may explain the occurrence of the same haplotype in a Turkish case, but this remains a hypothesis requiring broader population-genomic confirmation.

Background Given the augmented sampling and ancestry stratification of the Genome Aggregation Database (gnomAD) v4.1 compared to v2.1.1, population evidence for globin gene variants was assessed for changes in the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) criteria fulfillment, which can alter downstream variant interpretation. Methods Variants and constraint metrics for -globin locus genes HBA1, HBA2, and HBZ, and {beta}-globin locus genes HBB, HBD, HBG1, HBG2, and HBE1, were extracted from gnomAD v2.1.1 and v4.1 callsets, harmonized, matched to ClinVar annotations, and evaluated against BA1, BS1, BS2, BS2_Supporting, and PM2_Supporting ACMG/AMP criteria using Clinical Genome Resource Hemoglobinopathy Variant Curation Expert Panel thresholds. Results Globin gene variants increased fourfold across gnomAD releases, with HBB contributing the largest share. In v4.1, 68.7% of quality-passing variants were ancestry-specific, 14.4% overlapped ClinVar and PM2_Supporting fulfillment rose from 81.5% to 93.5%. Among variants present in both releases, ACMG/AMP population-criterion assessments were largely concordant, with conflicting combinations in <1%. Conclusions Leveraging augmented sampling and improved ancestry representation, gnomAD v4.1 increased globin gene variant discovery, particularly for rare variants, enabling more precise allele frequency estimates and robust assessment of BA1, BS1, and PM2_Supporting, although criterion fulfillment remains release- and callset-specific.

We investigated the genetic basis of a previously unclassified congenital vascular anomaly in a patient with multifocal cutaneous vascular tumors. Through genomic analysis, we identified a novel heterozygous de novo germline variant in GA-binding protein-alpha (GABPA), an ETS family transcription factor. Histopathologic evaluation demonstrated capillary-venous lesions lacking glucose transporter 1 expression, distinguishing this entity from common infantile hemangioma. Notably, the tumor vasculature exhibited a prominent alpha-SMA-positive perivascular cell layer, with nuclear localized GABPA detected in endothelial and perivascular cells. The GABPA c.509T>G (p.L170R) variant is absent from large population databases, including gnomAD, DeCAF, and RGC-MCPS databases, indicating it is extremely rare. The affected leucine residue is highly conserved across species and located within the Pointed (PNT) domain, a critical region mediating GABPA protein-protein interactions. AlphaMissense predicts this substitution to be highly damaging. Structure-based analysis using an AlphaFold-predicted approach, combined with in silico mutagenesis and molecular interaction analyses, revealed that the L170R substitution introduces new electrostatic interactions while disrupting native hydrophobic contacts within the PNT domain. Functional assessment in zebrafish demonstrated that mosaic stromal expression of GABPA-L170R caused abnormal vascular architecture compared with GABPA-wild-type controls, establishing a direct link between this variant and disrupted vascular development. Collectively, the genetic rarity, evolutionary conservation, predicted structural perturbation, and disruptive effects on vascular development establish GABPA-L170R as likely disease-causing variant. These findings define a new molecular mechanism underlying congenital vascular tumor formation and expand the role for ETS-family transcriptional regulation in human vascular anomalies.

Rare diseases are individually uncommon but collectively prevalent. Their primary clinical challenge lies not in treatment but in diagnosis. In the early stages of clinical management, it is frequently unclear whether the observed phenotypes are associated with a rare disease. Leveraging machine learning methods to mine latent associations between these phenotypes and rare diseases for early diagnosis offers a viable strategy to alleviate this diagnostic dilemma. In the present study, we demonstrated that machine learning can effectively discriminate rare disease cases from their controls using observed and excluded phenotypes as features. Among them, the Random Forest model achieved the best classification performance with a certain degree of generalizability. Based on further analysis of the feature selection results, we conclude that the two factors, specificity and occurrence count, are important for phenotype selection in rare disease discrimination, and comparable importance should be attached to both observed and excluded phenotypes, during feature construction.

Despite substantial advances in diagnostic testing, 10-15% of Usher syndrome patients remain without a genetic diagnosis, having significant implications for genetic counseling and potential future therapeutic interventions. In this study, genome sequencing data from probands clinically presenting with Usher syndrome were analyzed. Two novel deep-intronic variants were identified in PCDH15, c.3983+3635A>G and c.3123-1728A>G, in two independent patients. Both deep-intronic variants were classified as likely pathogenic and predicted to alter PCDH15 pre-mRNA splicing. Using a minigene splice assay and iPSC-derived photoreceptor precursor cells from patients, we confirmed that both variants lead to the inclusion of a pseudoexon in the PCDH15 transcript introducing a stop codon and subsequent premature termination of protein translation. We designed and evaluated antisense oligonucleotides (ASOs) with the purpose of redirecting aberrant pre-mRNA splicing caused by both deep-intronic variants. For both variants, designed ASOs were successful in restoring normal splicing patterns, highlighting their potential as a future therapeutic intervention strategy to halt the progression of retinitis pigmentosa caused by these novel variants. Overall, these findings contribute to the understanding of Usher syndrome caused by deep-intronic pathogenic variants in PCDH15 and describe for the first time the use of an ASO-mediated splice correction strategy for individuals diagnosed with these variants.

Background: African populations remain underrepresented in global genomic reference databases, complicating germline variant interpretation in clinical and research settings. This concern is particularly relevant in Malawi, where population-matched allele-frequency resources are limited. We assessed germline variants in Malawian patients with diffuse large B-cell lymphoma (DLBCL) that were absent from commonly used global reference databases. Methods: Whole-exome sequencing data from 55 histologically confirmed DLBCL cases recruited at Kamuzu Central Hospital, Lilongwe, were analyzed. Germline variants were called using GATK HaplotypeCaller and annotated with Ensembl VEP v110. Cohort allele frequencies were compared with gnomAD v3.1.2, ExAC v1.0, and the 1000 Genomes Project Phase 3 using African (AFR) and European (EUR) reference subsets. Variants absent from all three databases were designated database-absent variants (DAVs); this designation indicates absence from the queried reference panels and does not establish population restriction. Functional consequence, genomic distribution, and enrichment in immune-related loci were evaluated. Results: We identified 127,456 PASS-filtered germline variants across 55 samples. Of these, 332 variants (0.26%) were absent from gnomAD, ExAC, and 1000 Genomes and were distributed across 289 genes (median, one variant per gene; range, 1-8). Predicted loss-of- function variants comprised 16.9% of DAVs compared with 7.8% of the full call set (odds ratio, 2.41; 95% confidence interval, 1.79-3.24; p < 0.001). Seventy-eight DAVs (23.5%) occurred in HLA class I loci (HLA-A, HLA-B, and HLA-C; Fisher's exact test, p < 0.001). Allele-frequency distributions differed from both AFR and EUR reference populations, with greater divergence from EUR (Kolmogorov-Smirnov D = 0.31) than AFR (D = 0.13). The cohort also showed an increased proportion of low-frequency variants relative to both references. Conclusions: Database-absent germline variants were observed in this Malawian DLBCL cohort, including variants with predicted loss-of-function consequences and variants in HLA class I loci. These findings highlight gaps in the representation of Malawian and Southern African genomes in commonly used reference resources and the resulting potential for uncertainty in variant interpretation. Because this case-only cohort lacked matched population controls and sequencing depth was limited, DAVs should not be interpreted as definitively Malawian-specific or pathogenic. Larger, well-covered studies including matched Malawian and Southern African controls are needed to establish population frequencies and improve equitable genomic interpretation.

IRX4 is a TALE- homeodomain transcription factor which is essential for cardiac development. In murine models, Irx4 deficiency leads to impaired ventricular function and results in cardiomyopathy. To elucidate the role of IRX4 in human congenital heart disease (CHD), Sanger sequencing of the IRX4 gene was performed in 205 individuals with non-syndromic CHD, 24 Down syndrome (DS) cases with CHD, 27 DS cases without CHD, and 150 healthy control individuals. Two novel (p.Ser24Asn and p.Thr217Iso) and one reported variant (rs2232376) were identified in non-syndromic CHD. Concurrently, rs2232376 was also detected in DS with CHD. The first novel (p.Ser24Asn) and reported (rs2232376) variants lie in the N-terminal region while the second novel (Thr217Iso) variant lies within the TALE homeodomain. In silico structural modelling suggested that both the novel variants (p.Ser24Asn and Thr217Iso) induce conformational changes in the IRX4 protein, potentially altering its DNA-binding affinity. A significant reduced expression of IRX4 muteins was noted in Western blotting by both variants (p.Ser24Asn and Thr217Iso). Furthermore, luciferase reporter assays demonstrated decline in the activity of Nanog promoter and HEY2 enhancer in response to both the variants which was further corroborated by decrease mRNA expression in qRT-PCR. Additional downstream targets, including Nfyc, Nppa, and Bmp10, also exhibited anomalous expression due to both the variants (p.Ser24Asn and Thr217Iso). Altogether, the aberrant expression of muteins as well as downstream target genes along with compromised activities of promoters substantiate the pathogenic potential of the identified IRX4 variants and underscore the critical role of IRX4 in regulating multiple stages of cardiogenesis.