npj Genomic Medicine

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.

Autism is highly heritable, yet many cases remain genetically unsolved even after short-read sequencing (SRS). Long-read sequencing (LRS) increases sensitivity for pathogenic variant discovery, especially for complex structural variants (SVs) in repetitive regions missed by SRS. However, LRS largely relies on blood-derived DNA; whether saliva can support genome-wide LRS at population scale remains to be seen. We report the first systematic evaluation of saliva-derived DNA for genome-wide LRS in autism, benchmarking 105 new saliva samples against 68 new blood samples and integrating 189 previously published LRS blood samples to expand the autism cohort and improve ultra-rare pathogenic variant discovery. A matched blood-saliva quad provided direct comparisons of variant detection between sample sources. Saliva samples contained substantially more nonhuman DNA than blood (mean 10% versus 0.005% of reads), reducing mean effective genome coverage from an estimated 28X to 24X after removal of nonhuman reads, compared with 34X in blood samples. Despite this reduction, saliva and blood samples yielded comparable numbers of validated (22,591 versus 23,064) and rare (209 versus 213) SVs per sample, which was also observed in the quad when matching coverage. Saliva LRS identified four new pathogenic and likely pathogenic variants missed by SRS. We report variants affecting MECP2, DNMT3A, CHD8, LMBRD2, POGZ, and PHF3; four additional candidates with potential relevance to autism; and an increase of diagnostic yield of 9-18%. Saliva-derived DNA support blood-comparable discovery of pathogenic variants missed by SRS, including SVs, with increased sequencing coverage compensating for nonhuman DNA contamination and reduced assembly contiguity, thus showing saliva DNA collection as a feasible strategy for large-scale LRS studies of patients and population-scale sequencing of cohorts.

Goh et al. recently reported that most recurrent copy number variants (CNVs) are far less penetrant for intellectual disability (ID) than previously estimated, and recommended that fourteen should no longer be reported. We show that the lower estimates arise mainly from assuming the population prevalence of ID alone, while case counts derive from broad diagnostic referral cohorts in which about half of individuals were referred for other indications. The proposed formula estimates a risk difference rather than penetrance, and cases and controls were selected, assayed and phenotyped differently. Restricting the outcome to ID also leaves the analysis unable to inform risk for autism, epilepsy, psychiatric, cardiac and other phenotypes. We recommend that families receive phenotype-specific absolute risks for carriers alongside background risks, and that reporting decisions be made locus by locus by guideline bodies, considering all relevant phenotypes. The recalculated estimates inform this debate but are not yet sufficient grounds for changing reporting practice.

Background There are currently no available biomarkers that predict the clinical outcome of ulcerative colitis (UC) patients after anti-TNF withdrawal. Here we developed a semi-supervised machine learning framework on RNA-seq data derived from rectal biopsies to predict relapse following anti-TNF discontinuation. Methods We included UC patients (n=136) enrolled in the prospective, randomized controlled BIOSTOP trial. Patients were assigned to a withdrawal group (stopped treatment immediately) or a maintenance group (stopped treatment after 2 years). A machine learning framework was trained on gene expression data from mucosal biopsies collected at baseline from the withdrawal group and validated in the maintenance group using baseline samples (test cohort) and 2-year follow-up samples (interference cohort). Results A semi-supervised machine learning model, combining a shared UMAP manifold representation with LabelSpreading on a targeted 38-gene panel achieved an AUC of 0.794, a sensitivity of 90.3%, and a specificity of 73.1% on the test cohort, and an AUC of 0.711, a sensitivity of 82.9%, and a specificity of 42.3% on the inference cohort. Applying Shapley Additive exPlanations (SHAP) we found that IL1B, TYROBP, REG1B, S100A8, and TNF showed the highest predictive importance for relapse risk, whereas MUC2, HMGCS2, and CDKN1A displayed the highest predictive importance for sustained remission. Conclusion The high sensitivity makes the model a promising screening tool to prevent withdrawal-related relapse, though its moderate specificity underscores the need for multi-center validation in larger, more diverse cohorts before clinical deployment.

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.

Several polyglutamine-encoding repeat expansions cause spinocerebellar ataxias (SCAs) and other movement disorders. SCAs are genetically heterogeneous with a substantial diagnostic gap. We used genome sequencing data from 266 individuals of European and Asian ancestry and screened genome-wide for repeat expansions using STRling, a dedicated repeat expansion caller. The cohort comprised patients with movement disorders, predominantly dystonia and ataxia, as well as unaffected participants. Further, we screened another 436 individuals with ataxia and 427 ethnically matched controls through fragment analysis of the most promising candidate locus in EP400. We applied targeted long-read sequencing to expansion carriers and one control individual to resolve the sequence structure of the repeat locus. Finally, we used microsatellite markers in chromosome 12q24.32-33 to test for a common founder. A genome-wide outlier analysis in STRling revealed a polyglutamine-encoding repeat expansion (GRCh38 chr12:132,062,525-132,062,590) in the E1A binding protein p400 (EP400) gene in two patients with ataxia. Through screening of additional ataxia patients, we identified in total 18 patients from 14 families with heterozygous repeat expansions in EP400. All expansion carriers were from Serbia. The repeat number in affected individuals ranged from 37 to 55, whereas the longest control allele had 32 repeats. We demonstrated that non-expanded alleles carried a CAA interruption within the 5-prime CAG tract; this interruption was lost in expanded alleles. Expansion carriers have pure SCA with onset mainly in their 40s and 50s. There is an inverse correlation between the number of repeats and age at onset. The EP400-encoded protein plays an essential role in chromatin remodeling, epigenetic regulation and DNA repair. Pathogenic sequence variants in EP400 have previously been implicated in a neurodevelopmental disorder. Our study identifies repeat expansions in EP400 as a novel and frequent cause of ataxia in Serbian patients. This finding further increases the diagnostic yield of ataxia testing and warrants investigation in ataxia patients worldwide. We add EP400 to the growing list of ataxia-associated repeat loci, which warrants inclusion in diagnostic ataxia panels.

ReNU syndrome is a severe neurodevelopmental disorder caused by de novo variants in the spliceosomal small nuclear RNA (snRNA) gene RNU4-2. Pathogenic variants cluster in two distinct structural regions of the U4 snRNA produced by RNU4-2, the T-loop and Stem III. Aberrant 5' splice site selection is a molecular hallmark of ReNU syndrome that correlates with phenotypic severity and could be leveraged as a quantitative biomarker to facilitate preclinical and clinical therapeutic development. We analysed RNA-sequencing data from two independent cohorts totalling 30 individuals with ReNU syndrome and 54 controls. We identified 483 alternative splicing events shared across both cohorts, with the highest concordance in 105 alternative 5' splice-site (A5SS) events. Using these 105 A5SS events, we derived a minimal reproducible signature from only six sites. The splicing signature perfectly distinguished 19 n.64_65insT individuals from 54 controls, and produced no false positives when applied to a further 5,984 whole blood controls. In addition, the signature was specific to variants within the U4-2 T-loop, which are associated with greater clinical severity. Further, we find evidence of alternative splicing events that are specific to variants in Stem III. In a patient-derived induced pluripotent stem cell (iPSC) model of the recurrent RNU4-2 n.64_64insT variant, the splicing signature was fully recapitulated across all stages of differentiation into cortical neuron-like cells. Together, these findings define a robust RNA biomarker for T-loop ReNU syndrome for use in therapeutic development, and illustrate a general framework for portable biomarker discovery in spliceopathies.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by repetitive behavior and impaired social interactions. Recent reports from human postmortem brain samples of ASD show transcriptome-wide dysregulations, including changes in differential gene expression and alternative splicing. An important mechanism regulating transcriptome function is the editing of double-stranded RNA by adenosine deaminases acting on RNA (ADARs), which play regulatory roles in neurodevelopment and innate immunity. We explore the ADAR editing changes associated with the use of Selective Serotonin Reuptake Inhibitors (SSRIs) in Arid1b haploinsufficient mouse models. Our results show dynamic changes in site-specific editing rates in autistic mice. We further demonstrate the transcriptome-wide effects of differential ADAR editing in terms of changes in miRNA-mRNA interactions. Moreover, our findings highlight a site-specific change in editing rates for evolutionarily conserved sites in mammals and ASD associated risk genes, such as Gria2. Our analysis of significant biological processes shows the association of differentially edited genes with processes vital for neurotransmission. Overall, our findings imply that the use of SSRIs can induce distinct ADAR editing signatures, potentially contributing to ASD pathology.

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.

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.

CUB and Sushi domains-containing CSMD proteins are involved in neuron development. Variants in the CSMD1-3 paralogs were GWAS-associated with cognition, attention-deficit hyperactivity disorder (ADHD), schizophrenia and brain structure, suggesting that these genes could be linked to neurodevelopmental disorders (NDD). Indeed, rare biallelic variants in all three CSMD paralogs were recently associated with epilepsy, while rare biallelic variants in CSMD1 were also linked with intellectual disability and cortical malformations. We identified nine individuals from eight families carrying CSMD2 biallelic missense variants in developmental delay/intellectual disability cohorts. Affected individuals presented with autism spectrum disorder (ASD), ADHD and brain anomalies. Consistent with gnomAD metrics that suggest CSMD2 haploinsufficiency, we also report two families segregating monoallelic CSMD2 frameshift variants, which complement a described de novo truncation variant in an ASD proband. We concomitantly report two phenotypically overlapping individuals with de novo CSMD2 missense variants and compare them to twelve de novo CSMD2 cases identified in published trio analyses. UK Biobank analyses showed nominally significant enrichment of ADHD, ASD and neuroticism in volunteers carrying at least one rare CSMD2 variant. In silico modelling and immunofluorescence assays showed that mutated residues in affected individuals with biallelic and de novo missense variants are clustering in two regions and that the encoded proteins showed impaired membrane localization and an increased cytoplasmic aggregation. Zebrafish crispant larvae for the orthologous csmd2 presented with microcephaly, smaller cerebellum, and reduced Purkinje cell size. Larvae also displayed decreased swimming velocity, diminished connectivity between the optic tecta, and abnormal peripheral neuronal branching. We demonstrate that rare, likely pathogenic variants in CSMD2 are associated with both autosomal recessive and dominant forms of NDD further substantiating the functional significance of CSMD paralogs in neurogenesis/synapse formation.

The accrual of somatic copy number alterations (CNAs) in the premalignant condition Barrett's oesophagus (BO) predicts transformation to oesophageal adenocarcinoma (OAC). The dynamics of CNA evolution, namely when CNAs first appear and their rate of clonal expansion, are unknown. Here we show that CNAs typically begin to accrue in BO many decades prior to first clinical detection of BO or cancer occurrence, and in some cases during childhood. We constructed a hierarchical Bayesian methodology called CARBINE to calculate the calendar year occurrence time of CNAs from single-timepoint contemporary genetic data. We analysed data from 80 individuals who had received longitudinal endoscopic surveillance of their BO and had known cancer progression status. Loss of heterozygosity (LOH) on chromosome 9p tended to be the first CNA event and often occurred when patients were between 10-30 years old. Genome doubling (GD), known to be a strong risk factor for cancer development, also typically originated multiple decades prior to cancer develop and the GD clone expanded very slowly. Patients who progressed to OAC had an enrichment of CNAs late in life. CNA accrual dynamics were more predictive of cancer risk than CNA burden measurements alone. Analysis of 97 OAC whole genomes, of which 38 had sufficient purity for CNA timing analysis, confirmed the early-life origins of CNAs found in the cancer and indicated that the seeds of OAC exist within an increasingly cancerised BO field for many years. CNA timing shows that the malignant transformation potential of BO may be recorded within the somatic genome in the first decades of life, giving a strong rationale for the effectiveness of risk stratification in early life for Barrett's patients.

Accurate characterization of tumor subtype is of paramount importance in guiding treatment decisions in pediatric cancers. Here, we present FRANK (Fully-connected RNA-based Augmentation Neural Klassifier), a machine learning approach for classifying pan-cancer pediatric tumors. We curated a set of 11,467 transcriptomes to build a high-quality training dataset representing 181 distinct childhood tumor and normal tissue types. We used extensive data augmentation techniques with a hierarchical penalty term to train a neural network capable of detecting tumor types with as few as three training examples. To evaluate the generalization of the trained model, we perform validation on nine datasets spanning 16,398 samples, achieving an overall accuracy of 98.3%. Furthermore, we demonstrated that FRANK outperformed other published pediatric pan-cancer RNA-seq classifiers on an external dataset. To evaluate the robustness, we showed that FRANK remained accurate when applied to long-read RNA-sequencing data, as well as to noisy and low-quality data.

To evaluate the clinical implementation of long-read genome sequencing (lrGS) and establish the population reference resources needed to support its use in diagnostics, we integrate two complementary initiatives: Genome of Sweden (GoS), Sweden's contribution to Genome of Europe (GoE), and the Genomic Medicine Sweden - Rare Diseases (GMS-RD) long-read sequencing pilot. The initial GoS release of 576 individuals provides population-scale maps of genetic and epigenetic variation. Among 485 GMS-RD probands, 161 (33.2%) receive a molecular diagnosis, with lrGS providing added clinical value in 40 (24.8%). As a first-line test, lrGS could have avoided at least 42 follow-up analyses and an additional testing cycle in 7.2% of probands, reducing costs and the burden on patients. By integrating population and clinical long-read genomics, Sweden establishes a national ecosystem for genomic research and clinical diagnostics. Our findings support the clinical implementation of lrGS and offer a scalable model for national collaboration.

Pontocerebellar hypoplasia (PCH) is a group of ultrarare, neurodegenerative disorders characterized by cerebellar and pontine hypoplasia. Genetic analysis over the last two decades has revealed an increasing number of pathogenic variants in a wide range of broadly expressed genes functioning in RNA processing, tRNA metabolism, and translation. However, the mechanisms linking these ubiquitous processes to brain region-specific vulnerability are unknown. Here, we established a multi-level variant-to-function in silico framework to predict the molecular consequences of PCH-associated variants in TSEN complex genes. These variants were predicted to have heterogeneous effects on diverse protein properties, including stability, subcellular localization, and degradation, supporting variant-specific rather than uniform disease mechanisms. Complementary transcriptomic analyses showed that PCH-associated genes were not globally enriched in the prenatal cerebellum. Instead, their expression was coordinated in a stage- and cell type-specific manner during cerebellar development. We therefore hypothesize that multiple PCH-associated genes are regulated by a common set of transcription factors, providing an explanation of the selective vulnerability of the cerebellum and to the phenotypic convergence of genetically diverse PCH subtypes. In summary, this study prioritizes candidate variants for biochemical, cellular, and in vivo validation, and identifies regulatory programs, cell lineages, and developmental windows for targeted, mechanistically informed disease modelling.

Background Short-read genome sequencing generates the signal necessary to detect balanced reciprocal translocations at single-nucleotide resolution, but standard structural variant callers represent them as breakend pairs. Structural variant callers produce thousands of breakend records per genome, the majority of which are false positives arising from segmental duplications, repetitive elements, and reference assembly artifacts. This specificity problem has prevented balanced translocation detection from entering routine genome sequencing workflows. We developed a highly specific pipeline to resolve balanced reciprocal translocations and applied it across five clinically distinct cohorts to characterize the prevalence and diagnostic contribution of balanced reciprocal translocations. Methods Short-read genome sequencing data from 16,131 individuals across five cohorts were analyzed: healthy participants from the 1000 Genomes Project (n=3,202), probands with structural birth defects and their family members (CHOP BDB cohort; n=2,875, including 1017 probands), probands enrolled in the GREGoR consortium (GREGoR cohort; n=3,574 probands), probands with undiagnosed disease and their family members enrolled in the Undiagnosed Diseases Network (UDN cohort; n=6,071 including 2,027 probands) and neonates who underwent rapid genome sequencing (CHOP Baby Eagle cohort; n=409). A computational pipeline was developed to characterize breakend events from standard structural variant callers to high-confidence balanced translocation calls by exploiting well-characterized properties of true balanced translocation signatures in short-read data. Translocation breakpoints were resolved to single-nucleotide precision and interrogated for disruption of known disease genes or potential regulatory consequence otherwise. A subset of the identified breakpoints was confirmed by Sanger sequencing. Results Balanced reciprocal translocations were identified in 0.196% of structural birth defect probands (2/1,017), 0.25% of the GREGoR probands (9/3,574), 0.39% of the UDN probands (8/2,027) and 0.24% of neonates who underwent rapid genome sequencing (1/409). Parental carrier frequency in the birth defects cohort was 0.269% (5/1,858), consistent with previously reported estimates in similarly ascertained families, and 0.098% (3/3,040) in the UDN cohort. All six translocations identified in the birth defects cohort were orthogonally validated using Sanger sequencing, confirming pipeline specificity. Approximately 31% of translocations across the three affected cohorts disrupted a known disease gene at the breakpoint, establishing or refining a molecular diagnosis in five cases previously unresolved. The single translocation identified in the newborn cohort disrupted no disease gene and was classified as a variant of uncertain significance.

Isolated focal dystonia is a rare movement disorder characterized by abnormalities in brain structure and function. The genes underlying isolated focal dystonia are not fully elucidated, and genetic studies are constrained by incomplete penetrance and small family sizes. Neuroimaging endophenotypes shared by patients and unaffected relatives can reveal genetic liability independently of clinical manifestation and offer a strategy for advancing gene discovery. We developed DystoniaGeneNet, a 3D convolutional neural network that predicts familial status from T1-weighted brain MRIs. We then used its predictions to guide genetic analyses in isolated focal dystonia. DystoniaGeneNet was trained on 40 patients with familial laryngeal dystonia and 40 healthy controls, then applied to independent cohorts of 21 patients with familial isolated focal dystonia, 364 patients with sporadic dystonia, and 98 unaffected relatives. Model predictions were incorporated into variant prioritization and segregation analysis in 214 individuals with whole-exome sequencing data, and results were replicated in another 738 independent exomes, in genetic data from a hospital-based biobank (892 dystonia cases, 2,475 controls), and in the All of Us Research Program genetic data (1,343 dystonia cases, 6,840 controls). DystoniaGeneNet discriminated familial dystonia from healthy controls in the training set and correctly classified 85.7% of independent familial cases, using a biomarker centred on the corpus callosum and inferior temporal gyrus. Across the discovery and replication cohorts, we identified rare, likely pathogenic genetic variants in RAP1GAP and TNN segregating with disease in families. Additional variants were found in singletons with isolated focal dystonia. In patients with clinically sporadic dystonia but predicted to have familial features, we observed multiple rare variants in ITSN2, including three high-confidence loss-of-function variants, and an enrichment of damaging missense variants in its Dbl homology domain. To determine the functional impact of discovered genetic variants, we assessed gene expression and splicing via qPCR and RNA sequencing (n = 74), revealing reduced RAP1GAP and ITSN2 expression in variant carriers. At the pathway level, rare nonsynonymous variants in brain-expressed matrisome genes were associated with dystonia (P = 0.012). Our strategy utilizing a deep learning-derived neuroimaging endophenotype to empower gene discovery uncovered RAP1GAP, TNN, and ITSN2 as novel genes associated with isolated focal dystonia. These genes converge on perisynaptic extracellular matrix-synapse signalling, implicating a mechanism linked to synaptic plasticity deficits, and identifying a molecular substrate for network-level brain abnormalities that characterize this disorder. Further, we exemplify a generalizable framework for leveraging endophenotypes in rare neurogenetic diseases with incomplete penetrance.

Using an analysis pipeline that combines machine learning-based feature selection with classical statistical modelling, we aimed to predict incident inflammatory bowel disease (IBD) and to identify candidate proteins associated with disease development. We used UK Biobank data in an observational cohort study of 52,331 participants with proteomics data and without a history of IBD. The cohort was split into an 80/20 train/test dataset, and three separate extreme gradient boosting models were trained on the training dataset. Using Shapley values, we ranked the predictive importance of 2,912 proteins for incident IBD, Crohn's disease (CD), and ulcerative colitis (UC). The top 20 proteins per outcome served as features in multivariate Cox models predicting 350 incident cases over 14 years. All three proteomics Cox models showed moderate discrimination in the test dataset, with the UC model performing the best (C-index: 0.68), followed by IBD (C-index: 0.65), and CD (C-index: 0.60). All proteomics models outperformed clinical models. Smoking remained the only significant clinical predictor in the combined proteomics + clinical model. 48 unique proteins were identified across the three models, with 16 reaching statistical significance (p< 0.05). Machine learning-based feature selection with statistical survival modelling identifies plasma proteins that predict incident IBD and highlight biologically plausible, potentially targetable pathways in the preclinical phase of IBD.

Fragile X Syndrome (FXS) is a neuro-developmental disorder caused by a CGG expansion in FMR1, leading to transcriptional silencing and loss of the encoded protein FMRP. Surprisingly, ~70% of FXS individuals express FMR1, but the RNA is mis-spliced to isoform FMR1-217, composed of exon 1 spliced to a pseudo-exon in intron 1 and cannot produce FMRP. Splice-switching ASOs rescue proper FMR1 splicing and restore FMRP. FMR1-217 mis-splicing increases with CGG repeat length and is negatively correlated with patient IQ. FMR1-217 is associated with ribosome footprints, indicating it is translated into a polypeptide that may impair cognition. R-loops form at the FMR1 locus and extend into the pseudo-exon, but splice-switching ASOs reduce FMR1-217 and elevate FMRP independently of R-loop formation. DRB-based transcription analysis identified impaired Pol II elongation at the 5 prime region of FMR1 in FXS cells, indicated by accumulation of hypophosphorylated Pol II at the transcription start site. Consistent with this, camptothecin-induced Pol II stalling increased FMR1-217 pseudo-exon inclusion. The splicing factors PTBP1 and PTBP2 regulate FMR1-217 splicing in a differentiation stage-dependent manner. Together, these findings indicate that FMR1-217 mis-splicing in FXS is associated with CGG repeat expansion, R-loop formation, impaired co-transcriptional Pol II elongation and context-dependent regulation by PTBP1/PTBP2.

Childhood apraxia of speech (CAS) is a neurodevelopmental disorder of speech-motor planning and programming, associated with literacy, academic, and psychosocial difficulties. We performed whole-exome sequencing in 11 families comprising 21 affected and 15 unaffected individuals with phenotyping spanning speech, language, cognition, literacy, and motor function. We identified 60 prioritized variant observations representing 22 unique variants across 20 genes with family-based segregation analysis assessed in informative relatives; 5 arose de novo. Our cohort included multiple affected siblings and extended relatives, with several families carrying multiple prioritized variants, suggesting cumulative or oligogenic susceptibility. Speech and literacy impairment co-occurred with oral-motor, feeding, and fine-motor difficulties. BrainSpan co-expression analysis identified MECP2 and ANK2 as the genes with the highest observed connectivity in the sampled postnatal network. Exploratory analysis of the KOLF2.1J perturbation atlas in undifferentiated human induced pluripotent stem cells identified a positive LMO3 expression-response score following NIPBL repression and opposing LMO3 and ANK2 response directions within a cohesin-associated perturbation cluster. These observations motivate testing in human neural cells. Functional enrichment, protein-association, and developmental-expression analyses supported shared biological themes involving chromatin regulation, neuronal signaling, and extracellular-matrix organization. Among six families, multiple affected relatives shared prioritized variants across a unique set of several genes, demonstrating multilocus candidate profiles whose individual and combined effects may contribute to CAS susceptibility. We propose four novel CAS candidate genes: LMO3 and PCDH10, previously linked to human accelerated regions, as well as MYCBP2 and PTPRS. Our work provides multiple testable hypotheses for future variant-specific functional validation in speech-motor development.