搜索结果：HGG advances

Reirradiation has re-emerged as a viable salvage modality for recurrent central nervous system (CNS) tumors in the modern era of precision radiotherapy. Advances in image guidance, biological understanding of normal-tissue repair, and integration of targeted systemic agents have expanded its therapeutic window. The 2025 ISRS meta-analysis (62 studies; n = 2640) established a median overall survival (OS) of ~ 10.2 months after re-irradiation (re-RT) of recurrent HGG, confirming that focal single-fraction SRS (16 Gy × 1) or hypofractionated SRS (25 Gy/5 fx) achieves optimal tumor control with acceptable neurologic toxicity (7% vs 4%). EQD₂ > 120-130 Gy markedly increases radionecrosis risk (p = 0.003). Integration of DNA-damage-repair (DDR) inhibitors, VEGF blockade, and tumor-treating fields (TTFields) is under active investigation. Re-RT in ependymoma, meningioma, and spinal tumors is also gaining renewed interest with proton and MR-guided adaptive techniques.

The inevitable progression of high-grade gliomas has prompted a need for data-backed identification of compromised tissue prior to detection on traditional serial imaging. Whole-brain magnetic resonance spectroscopy (WB-MRS) can fill this role to classify glioma progression prior to contrast enhancement. Voxel-level data can differentiate areas of perilesional tissue under supervised machine learning (ML) and has been shown to predict the likelihood of tumor progression within six months. In this study, we aim to improve the spatial utility of WB-MRS ML through unsupervised ML clustering for utility in intraoperative integration with existing neuronavigation platforms. This analysis involved 16 adult patients that developed recurrence of high-grade glioma (HGG) on serial imaging, including 13 with glioblastoma (GBM) and three with anaplastic astrocytomas. Postoperative WB-MRS images were used as data inputs. We investigated two unsupervised clustering methods to optimize the identification of compromised perilesional tissue from a previously published supervised model. All voxels within the new region of interest (ROI) are reclassified as future progression regardless of their classification from the supervised model. After hyperparameter tuning, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) shows an area under the curve (AUC) of 0.942, while K-Means Clustering shows an AUC of 0.874. DBSCAN also shows a superior accuracy, specificity, sensitivity, and F1-score to the original supervised model alone. The incorporation of unsupervised clustering enhances the utility of WB-MRS for identifying compromised perilesional tissue and predicting high-grade glioma progression. Unsupervised clustering incorporates critical geospatial data and offers a more surgically relevant approach to visualizing tumor progression. Early detection of high-grade glioma recurrence remains a major limitation of current imaging modalities, restricting the ability to guide timely and precise interventions. While prior work has demonstrated that WB-MRS combined with supervised ML can identify metabolically abnormal tissue at risk for progression, these approaches lack spatial coherence and clinical usability. In this study, we introduce a hybrid pipeline integrating supervised voxel-wise predictions with unsupervised spatial clustering (DBSCAN and K-means) to refine recurrence mapping. This approach significantly improves classification performance and generates spatially contiguous, clinically interpretable regions of interest. Importantly, these outputs can be exported as DICOM overlays, enabling direct integration into neuronavigation systems. While still in pilot phase, this work advances WB-MRS from a predictive tool toward a clinically integrable platform, with potential applications in surgical planning, biopsy targeting, and longitudinal disease monitoring in patients with high-grade glioma.

Prosody perception is an often overlooked aspect of human language despite its importance in facilitating spoken language comprehension. Sensitivity to prosodic cues varies between individuals, and prosody perception skills are shown to be associated with various language- and reading-related outcomes. Despite the importance of prosody perception in human communication, its underlying biology is poorly understood. This study investigates the genetic architecture of prosody (speech rhythm) perception and explores its evolutionary roots. We conducted a GWAS of prosody (n = 1,501) as measured by scores on the Test of Prosody via Syllable Emphasis ("TOPsy"). GWAS results yielded 14 suggestive significant signals (p < 5.00 &#xd7; 10-6). Gene set enrichment analysis identified shared genetic architecture between human prosody perception and key vocal learning brain regions in songbirds, suggesting that human prosody perception may have evolutionary convergence in communication mechanisms in animal vocal learning. Additionally, cross-trait polygenic score analyses suggest shared genetic influences between prosody perception and both word reading and musical beat synchronization, emphasizing how genetics influence prosody perception and its associations with communication-, education-, and music-related traits. These initial efforts could inform advances in communication sciences and disorders as well as educational contexts.

Inherited retinal diseases (IRDs) comprise a diverse group of disorders that frequently lead to progressive vision impairment and blindness. Despite advances in genetic testing, a significant number of IRD cases remain genetically unsolved, often due to unidentified disease-associated genes or variants. This study reports additional cases for the newly discovered IRD genes of the AP-5 complex. A comprehensive ophthalmological evaluation was performed for all patients, including retinal imaging (multimodal imaging), visual field testing, and electroretinogram (ERG) testing. Whole-genome and -exome sequencing (WGS and WES) were performed for clinically unsolved IRD patients, and data were analyzed to identify underlying causal variants. The identified variants were subsequently validated using Sanger sequencing. Five unrelated patients from Europe and Iran were identified with a distinctive macular degeneration associated with bi-allelic variants in AP5Z1 (HGNC: 22197) and AP5B1 (HGNC: 25104), subunits of the vesicular fifth adaptor protein (AP-5) complex. The AP-5 complex is the part of the intracellular trafficking machinery thought to be involved in cellular homeostasis and lysosomal functioning in the retinal pigment epithelium (RPE). The identification of bi-allelic variants in two proteins of the AP-5 complex expand the characterization of AP-5 genes in sustaining and preserving normal macular function.

The Thar Desert of northwestern India, despite its harsh ecology, has sustained settlement of ancient crafts and pastoral communities. Their persistence provides a unique opportunity to study how migration, ecology, and culture have shaped genetic diversity. We analyzed genome-wide SNP data from 176 individuals across eight occupational communities along with global Indian populations and diverse ancient genomes. Population history, ancestral migration, population structure, demography, admixture, and founder effects were elucidated using diverse population genetic statistical methods. The Thar groups occupy an intermediate position on the Indian north-south cline. Pastoralists and artisans (woodcarvers and Persian gold embossers) align with West Eurasian lineages, while potters and performers align with southern clines. Uniparental data confirmed heterogeneous Indian lineages. Gene-culture co-evolution was evident from the lactase-persistence allele being higher in pastoralists but lower in gold embossers despite shared ancestry. Noteworthy, despite the desert environment, the populations retain a high frequency of the SLC24A5 allele associated with lighter skin pigmentation in Europeans. Demographic analyses indicate an admixture of 60-80 generations before present and strong founder effects in certain groups, particularly tie and dye and Persian migrant artisans &#x223c;500-600 years ago. Ancient DNA (aDNA) comparisons confirmed continuity with the Indus Periphery and historical South Asian populations. The genetic landscape of the Thar is a palimpsest shaped by successive layers of settlement, migration, and cultural continuity. By establishing the genomic baseline of Thar's craft and pastoral communities, this study shows how ecology and endogamy, along with population history, shape distinct genetic landscapes. These findings provide essential context for studying genetic risk, adaptation, and human resilience in extreme environments.

We report three individuals with bi-allelic variants in RNU6ATAC, which encodes the U6atac minor spliceosomal small nuclear RNA (snRNA), causing a multisystem minor spliceopathy. Through RNA sequencing analysis, we identified a distinctive excess of minor intron retention (MIR) in two unrelated individuals, which guided the identification of bi-allelic RNU6ATAC variants. The discovery cohort presented with variable multisystem manifestations. One individual presented with refractory epilepsy, microcephaly, developmental delay, ataxia, bilateral toe syndactyly, hypereosinophilia, and short stature, whereas the other exhibited failure to thrive, short stature, primary hypothyroidism, combined variable immunodeficiency, eosinophilic colitis, ichthyosis vulgaris, scoliosis, and chronic inflammatory demyelinating polyneuropathy without neurodevelopmental involvement. Despite organ-specific variation, both individuals displayed impaired growth and eosinophil-driven inflammation. Recently, we identified a third affected individual from an independent cohort whose phenotype bridges these features, combining microcephaly, growth failure with severe immunodeficiency, and skeletal abnormalities. The distinctive excess of MIR outliers in the discovery cohort supports minor spliceosome dysfunction, mirroring the molecular signature of RNU4ATAC-opathy. These findings nominate RNU6ATAC as a disease-associated gene, defining an expanded clinical spectrum of minor spliceopathies. Our study supports the power of integrating genomic and transcriptomic approaches for diagnosing splicing disorders and highlights the critical role of spliceosomal snRNAs in human disease.

Sphingolipids are integral components of cell membranes and modulate cell survival, proliferation, and apoptosis. ASAH2 is a brain- and gut-enriched gene encoding the neutral N-acylsphingosine amidohydrolase 2, a poorly characterized member of the human ceramidase family. This enzyme plays a pivotal role in maintaining the sphingolipid homeostasis, which is crucial for neurogenesis and synaptic function in the central and peripheral nervous systems. In fact, a dysregulated sphingolipid metabolism is associated with progressive neurological conditions, including Alzheimer disease and Parkinson disease. Here, we report the identification of biallelic ASAH2 variants in an individual with a neurodevelopmental condition featuring cognitive impairment, neuropathy, ophthalmoplegia, and progressive cerebellar and extraocular muscles atrophy. Through exome sequencing, we identified very rare missense ASAH2 variants, predicted to be deleterious by in silico analyses. Muscle biopsy histopathologic evaluation revealed features suggestive of neuropathic damage. Lipidomic profiling revealed a hyper-accumulation of glucosylceramide in the subject's cells. Then, the functional investigation of the ASAH2 variants in Drosophila showed the production of an unstable protein and consistent loss-of-function neuromotor phenotypes. Our findings support ASAH2 as a candidate gene for a previously uncharacterized neurodevelopmental disorder with neuropathic features and progressive cerebellar atrophy, underscoring the important role of this ceramidase in human nervous systems.

Adolescent idiopathic scoliosis (AIS), the spontaneous development of a lateral spine curvature during puberty, is the most common pediatric spine disorder, affecting &#x223c;3% of children worldwide. As the underlying etiology remains unclear, AIS is treated purely symptomatically, initially by bracing and ultimately by highly invasive, costly surgeries. Genome-wide association studies (GWAS) have identified numerous risk loci in non-coding genomic regions, making it difficult to link them to a biological function. To address this, we performed a multi-tissue investigation to connect genetic risk to tissue-specific molecular pathology. We conducted RNA sequencing on the primary tissues implicated in AIS, paraspinal muscle and spinal cartilage, from patients and unaffected controls. In paraspinal muscle, we identified differentially expressed genes (DEGs) enriched for pathways related to muscle structure, myogenesis, and metabolism. Key upregulated genes include the transcription factor EGR1 and structural components such as MYH1. In spinal cartilage, we found enrichment of genes related to TGF&#x3b2; and FoxO signaling, as well as metabolic pathways. Notably, genes crucial for chondrocyte differentiation (e.g. SOX5 and SOX6) were significantly downregulated. We then examined genes at known GWAS loci and found that several risk-associated genes were differentially expressed in one or both tissues. To investigate the function of non-coding variants at these loci, we identified and validated several enhancer elements harboring AIS risk SNPs at the BCL2, ADGRG6, BNC2, and FTO loci. We reveal distinct pathological signatures in muscle and cartilage and lay the foundation for connecting non-coding genetic risk to the dysregulation of key developmental and structural pathways.

Advancements in whole-genome sequencing have increased the number of variants of uncertain significance (VUS) identified in human genomes. This has created a diagnostic bottleneck for genetic counselors tasked with sifting through these variants and determining those most likely to be causative for a patient's clinical presentation. Machine learning (ML) tools can aid in identifying pathogenic variants from VUS, but there is a need for gene-specific algorithms that predict pathogenic variants with high accuracy. To address this need, we present a workflow for developing gene-specific, ensemble-learning ML tools, that leverage outputs from other algorithms, locations of variants within the gene, and evolutionary conservation data to make a prediction of pathogenicity. Variants in SMARCA2 and SMARCA4 that are associated with rare neurodevelopmental diseases were used to screen 15 ML algorithms. A random forest learner was tuned to yield a final accuracy of 0.93 on holdout data. Generalizing this predictor to other BRG1/BRM-associated factor (BAF) complex proteins resulted in a sharp decline in performance. We trained a final predictor for all genes in the study to create a predictor that identifies pathogenic variants in these BAF subunits with an accuracy of 0.91 on holdout data. This predictor specific to BAF complex proteins performs with higher accuracy and area under the precision-recall curve than any other predictor. The decline in performance when generalized to other proteins emphasizes the need for the gene-specific calibration of predictors. Our workflow for the development of such models provides a quick, computationally inexpensive route for improving the ML tools available to genetic counselors.

Hyperlipidemia is a major risk factor for atherosclerosis and other serious cardiovascular diseases, yet it often presents without obvious symptoms in the absence of comorbidities, complicating early detection and management. Given the high heritability of lipid traits, genome-wide association studies (GWASs) have identified numerous loci associated with serum lipids; however, pinpointing the causal variants remains a challenge. Here, we investigated the 5q33.3 locus and identified HAVCR1 as a likely effector gene influencing lipid metabolism. By integrating functional genomics and experimental validation, we identified two non-linked variants, rs6882076 and rs17573010, that modulate HAVCR1 via allele-specific binding by IRF2 and GATA4, respectively. rs6882076 was refined from prior GWAS findings, while rs17573010 emerged from ancestry-specific analysis. These findings highlight the complexity of genetic regulation across populations and establish a mechanistic link between lipid metabolism and inflammation, offering insights into the genetic basis of hyperlipidemia and its potential translational relevance.

Over half of presumed genetic disease cases remain undiagnosed following short-read exome sequencing (SR-ES) or genome sequencing (SR-GS). Long-read GS (LR-GS) shows promise for uncovering etiologies missed by SR genetic testing, particularly structural variants (SVs). However, SV interpretation remains challenging due to limitations in call reliability, population allele frequency estimates, and functional impact prediction. To advance clinical LR-GS implementation, we analyzed the genomes of 19 children with suspected rare genetic conditions and prior negative or inconclusive clinical SR-GS/SR-ES as well as their parents using PacBio HiFi LR-GS. One additional family with limited DNA underwent Illumina SR-GS only, and 11 probands received SR-GS to complement small-variant detection. LR-GS data were processed using phased-assembly and read-based variant-calling pipelines validated in SV-positive control subjects, while SR-GS data were processed with the Illumina DRAGEN pipeline. Variants were prioritized using phenotype-driven approaches. Diagnostic variants (likely pathogenic or pathogenic) were identified in 2/20 (10%) families, while an additional 5/20 (25%) harbored findings of uncertain diagnostic significance, including variants of uncertain significance (VUSs) and variants in genes of uncertain significance (GUSs). All reported variants were detected independently of LR-GS by research SR-GS or by reanalysis of prior clinical SR data. Several LR-GS SV candidates were excluded after population allele frequency filtering, underscoring its importance in clinical SV interpretation. Overall, the observed 10% increase in diagnostic yield was achievable through SR analysis alone, as LR-GS was not required to identify diagnostic variants in this cohort. Functional studies are needed to clarify the clinical relevance of uncertain findings.

Rare genetic variation is considered a potential source of heritability in individuals with sporadic Alzheimer disease and related dementias (ADRD). The Variant-set test for association using annotation information (STAAR) framework leverages multiple functional annotations of genetic variants and combines association statistics from multiple variant aggregation-based methods, including burden, sequence kernel association test (SKAT), and aggregated Cauchy association test (ACAT-V), into a single measure of significance. Using whole-genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP), we comprehensively examined the association of rare genetic variation with ADRD in 23,454 individuals (37% individuals affected by ADRD) and with cognitively healthy elder status in 13,292 individuals (13% cognitively healthy elders) from diverse populations via the STAAR framework. We identified several genes significantly associated with ADRD or cognitively healthy status. However, our analysis revealed several limitations within the STAAR framework incorporating ultra-rare variants with dichotomous outcomes. To enhance the robustness of the framework, we proposed several computational refinements, including creating a burden of ultra-rare variants and employing more precise annotations to match the expected mechanism. After implementing the proposed modifications, the association with ADRD for ZNF200 was no longer statistically significant (&#x3b1; = 1 &#xd7; 10-7), while TBX19, PLXNB2, CARD11, and LINC01880 remained significantly associated with cognitively healthy status. We identified and addressed the computational limitations in the STAAR framework that could lead to potential spurious results for ultra-rare variant aggregates with an extremely low cumulative minor-allele count. Our proposed refinements produced more robust results for associations with rare variants in the context of dichotomous outcomes.

Oral and craniofacial diseases are common, yet their genetic basis and links to systemic health are incompletely understood. We performed genome-wide association analyses of 67 oral phenotypes in 500,348 FinnGen participants, identifying 102 genome-wide significant loci, including 45 previously unreported associations. 48 loci remained significant after category-level Bonferroni correction. Fine-mapping revealed 14 coding variants, such as a missense variant in USP31 for caries and in MANBA for oral leukoplakia, and a stop-gained variant in GPNMB for temporomandibular disorders. HLA analyses implicated DQA1 and DQB1 alleles in lichen planus and other mucosal disorders. We observed 378 statistically significant genetic correlations among oral traits, such as tooth loss and chronic apical periodontitis (rg = 0.91, 95% confidence interval (CI) [0.76, 1.05], P = 1.7 &#xd7; 10-34), and 419 significant correlations between oral and systemic diseases, including periodontal diseases with chronic laryngitis (rg = 0.97, 95% CI [0.58, 1.36], P = 1.2 &#xd7; 10-6) and bruxism with gastro-oesophageal reflux (rg = 0.51, 95% CI [0.38, 0.65], P = 1.1 &#xd7; 10-13). These results expand the catalog of oral disease loci, uncover Finnish-enriched risk alleles, and highlight shared inflammatory, immune, and structural pathways connecting oral and systemic health.

Genome sequencing (GS) has emerged as a transformative tool in the diagnosis of rare diseases with complex phenotypes. This technology uncovers structural, intronic, non-coding, and mitochondrial variants that traditional methods might miss, thereby facilitating the understanding of the underlying genomic basis of human disorders. We enrolled 10,305 patients with suspected rare diseases or hereditary cancer risk syndromes from 21 centers throughout Brazil. Their genomes were sequenced with short, paired-end reads, and diagnostic reports were provided for 9,448 of these patients. The overall diagnostic yield was 35.6%, and 4.6% of all positive reports had GS-exclusive findings (e.g., short copy-number variants overlapping fewer than three exons, deep intronic variants, short tandem repeat expansions, and mitochondrial structural variants-usually not detected by other diagnostic tests such as exome sequencing). Preliminary analysis of transcriptome sequencing (TS) or long-read GS combined with GS interpretation provided a small but welcome improvement in diagnostic yield (0.1% and 1.0% of positive reports, respectively). Almost 3,200 variant/phenotype interpretations were submitted to ClinVar. GS is proving to be an invaluable resource for shortening the diagnostic odyssey of patients with rare diseases, providing crucial genomic diagnostics, and enriching genetic databases with variant interpretations from underrepresented populations. Therefore, GS has the potential to significantly enhance the precision of healthcare in genetically diverse populations.

Dilated cardiomyopathy (DCM) results from systolic dysfunction, while restrictive cardiomyopathy (RCM) is due to diastolic dysfunction. The diverse pathophysiology of primary DCM and RCM suggests distinct underlying genetic mechanisms. A well-established disease gene for DCM and RCM is cardiac troponin I3 (TNNI3), which causes dominant and recessively inherited forms. In children, bi-allelic truncating TNNI3 variants have typically been associated with DCM, and heterozygous missense TNNI3 variants are associated with RCM. We report a 2-year-old female with severe RCM that is genetically caused by a homozygous TNNI3 nonsense variant, c.406C>T (p.Arg136&#x2217;), which results in a more distal (C-terminal) truncation than most previously reported disease-associated nonsense variants. In myocardial biopsies of the patient, TNNI3 protein abundance was diminished, suggesting that residual TNNI3 function may underlie RCM, while TNNI3 absence causes DCM. The RCM in this patient was treatment refractory and resulted in a heart transplant at the age of 28 months. Overall, recessive TNNI3 protein truncation causes severe pediatric RCM, suggesting that the allelic status, type of genetic alteration, and length of TNNI3 protein truncation determine cardiomyopathy onset and subtype manifestation.

An increased frequency of sporadic autosomal dominant disorders has been observed among children born to older fathers. This paternal age effect is thought to reflect an accumulation of new mutations in the male germ line as DNA replication and cell division continue to occur as men age. Genome-wide sequencing is useful for identifying disease-causing genetic variants in patients with suspected genetic diseases and for determining inheritance or de novo mutation of the variants when done in patient-parent trios. We analyzed paternal ages in 593 families who received trio or quad exome or genome sequencing for suspected genetic disease. The mean age of fathers of children with de novo disease-causing variants (35.09 years) was significantly greater than that of children with inherited disease-causing variants (33.78 years, p = 0.04). The mean age of mothers of children with de novo disease-causing variants (31.86 years) was not significantly greater than that of children with inherited disease-causing variants (30.80 years, p = 0.09). Interestingly, when the de novo disease-causing variants were broken down into subgroups by variant type, both mean paternal age and mean maternal age of children with de novo indel variants (paternal = 36.33 years, maternal = 33.34 years) were significantly higher than in children identified to have de novo single-nucleotide variants (paternal = 34.35 years, p = 0.03; maternal = 31.15 years, p = 0.004). This observation, which may have implications for how indels arise, requires further study.

Many datasets, including widely used biobanks, have more than one observation of numerous phenotypes for at least a portion of their sample. The majority of genome-wide association studies (GWASs) utilize only a single observation per individual, even when more than one observation may be available, and apply a standard model in which the additive allelic effect being estimated is assumed to be constant across the age or time range in the sample. Here, we test a set of simple approaches to utilize multiple observations per individual, under this same assumption, to characterize effects on GWAS power, SNP heritability, gene set enrichment, and polygenic prediction. We find that utilizing the mean or median of the available observations rather than a single observation improves the power to detect associated loci and enriched gene sets and yields higher out-of-sample polygenic score prediction accuracy. Despite growing biobanks, many deeply phenotyped samples are relatively small but have multiple observations. While explicitly modeling age- or time-dependent genetic effects can add nuance to genetic studies and estimates, most GWASs apply a standard, additive-only model; a simple approach of using the mean or median can improve power by reducing "noise" in the phenotype, utilize standard, optimized software, and be particularly impactful for smaller samples, including samples of diverse genetic ancestry existing in widely used biobanks such as the UK Biobank and the Health and Retirement Study.

People with HIV (PWH) exhibit accelerated aging and a higher prevalence of aging-related conditions, despite effective antiretroviral therapy. The biological mechanisms involved remain incompletely understood. Integrating genomic and metabolomic profiling may help uncover genes and pathways contributing to aging-related disease in this population. Using a genome-wide association study framework and untargeted metabolomic profiling, we searched for associations between human genetic variants and the plasma concentrations of 1,930 putative metabolites in 1,244 individuals enrolled in the Swiss HIV Cohort Study. We performed an expression quantitative trait loci (eQTL) colocalization analysis to explore biological links between genetic variants and metabolites, and used Mendelian randomization to search for causal relationships between metabolites and aging-related diseases. We identified 27 metabolites significantly associated with 12 genetic loci, including genes encoding the metabolic enzymes NAT8 and FUT2; 10 associations had been previously reported in general population studies, of which 8 were replicated in our analysis. The colocalization analyses provided evidence for a large overlap between genetic regulation of mRNA expression and metabolite levels, while Mendelian randomization suggested several causal effects. Our study uncovered genetic-metabolic associations observed in PWH and explored their biological relevance. These findings highlight the potential of integrated multi-omics profiling to deepen mechanistic understanding and inform future precision approaches to comorbidity management in this population.

Congenital disorders of glycosylation (CDGs) are a phenotypically diverse group of genetic conditions arising from pathogenic variants in various glycosylation pathways. The most prevalent are N-glycosylation disorders. Here, we present clinical and biochemical data on two siblings with a neurodevelopmental disorder and a pathogenic homozygous nonsense variant in ribophorin I (RPN1), an essential component of the oligosaccharyltransferase (OST) complex. Both affected individuals showed a classical type I serum transferrin profile, while lymphoblasts revealed that the variant resulted in a truncated RPN1 protein with reduced levels. The protein stability of other essential OST complex components, including STT3 OST complex catalytic subunit A (STT3A), RPN2, and dolichyl-diphosphooligosaccharide (DDOST), was also significantly reduced. Structural modeling of both OST-A and OST-B complexes shows that RPN1 truncation eliminates a C-terminal four-helix bundle, which interacts with the translating ribosome. This interaction is necessary and specific for the co-translational activity of the OST-A complex. Supporting this observation, hypoglycosylation of an OST-A-specific substrate protein was observed, while OST-B-specific substrates were unaffected. These data convey that a rare loss-of-function RPN1 variant causes an autosomal recessive CDG characterized by neurodevelopmental deficits.