HGG Advances最新文献

Heterozygous de novo or inherited gain-of-function mutations in the MTOR gene cause Smith-Kingsmore syndrome (SKS). SKS is a rare autosomal dominant condition, and individuals with SKS display macrocephaly/megalencephaly, developmental delay, intellectual disability, and seizures. A few dozen individuals are reported in the literature. Here, we report a cohort of 28 individuals with SKS that represent nine MTOR pathogenic variants. We conducted a detailed natural history study and found pathophysiological deficits among individuals with SKS in addition to the common neurodevelopmental symptoms. These symptoms include sleep-wake disturbance, hyperphagia, and hyperactivity, indicative of homeostatic imbalance. To characterize these variants, we developed cell models and characterized their functional consequences. We showed that these SKS variants display a range of mechanistic target of rapamycin (mTOR) activities and respond to the mTOR inhibitor, rapamycin, differently. For example, the R1480_C1483del variant we identified here and the previously known C1483F are more active than wild-type controls and less responsive to rapamycin. Further, we showed that SKS mutations dampened circadian rhythms and low-dose rapamycin improved the rhythm amplitude, suggesting that optimal mTOR activity is required for normal circadian function. As SKS is caused by gain-of-function mutations in MTOR, rapamycin was used to treat several patients. While higher doses of rapamycin caused delayed sleep-wake phase disorder in a subset of patients, optimized lower doses improved sleep. Our study expands the clinical and molecular spectrum of SKS and supports further studies for mechanism-guided treatment options to improve sleep-wake behavior and overall health.

The Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema was released in 2022 and approved by ISO as a standard for sharing clinical and genomic information about an individual, including phenotypic descriptions, numerical measurements, genetic information, diagnoses, and treatments. A phenopacket can be used as an input file for software that supports phenotype-driven genomic diagnostics and for algorithms that facilitate patient classification and stratification for identifying new diseases and treatments. There has been a great need for a collection of phenopackets to test software pipelines and algorithms. Here, we present Phenopacket Store. Phenopacket Store v.0.1.19 includes 6,668 phenopackets representing 475 Mendelian and chromosomal diseases associated with 423 genes and 3,834 unique pathogenic alleles curated from 959 different publications. This represents the first large-scale collection of case-level, standardized phenotypic information derived from case reports in the literature with detailed descriptions of the clinical data and will be useful for many purposes, including the development and testing of software for prioritizing genes and diseases in diagnostic genomics, machine learning analysis of clinical phenotype data, patient stratification, and genotype-phenotype correlations. This corpus also provides best-practice examples for curating literature-derived data using the GA4GH Phenopacket Schema.

Artificial intelligence (AI)/deep learning (DL) models that predict molecular phenotypes like gene expression directly from DNA sequences have recently emerged. While these models have proven effective at capturing the variation across genes, their ability to explain inter-individual differences has been limited. We hypothesize that the performance gap can be narrowed through the use of pre-trained embeddings from the Nucleotide Transformer, a large foundation model trained on 3,000+ genomes. We train a transformer model using the pre-trained embeddings and compare its predictive performance to Enformer, the current state-of-the-art model, using genotype and expression data from 290 individuals. Our model significantly outperforms Enformer in terms of correlation across individuals, and narrows the performance gap with an elastic net regression approach that uses just the genetic variants as predictors. Although simple regression models have their advantages in personalized prediction tasks, DL approaches based on foundation models pre-trained on diverse genomes have unique strengths in flexibility and interpretability. With further methodological and computational improvements with more training data, these models may eventually predict molecular phenotypes from DNA sequences with an accuracy surpassing that of regression-based approaches. Our work demonstrates the potential for large pre-trained AI/DL models to advance functional genomics.

The aim of this work was to identify the underlying genetic cause in a four-generation family segregating an unusual phenotype comprising a severe form of skeletal Class II malocclusion with gingival hyperplasia. SNP array identified a copy number gain on chromosome 1 (chr1); however, this chromosomal region did not segregate correctly in the extended family. Exome sequencing also failed to identify a candidate causative variant but highlighted co-segregating genetic markers on chr17 and chr19. Short- and long-read genome sequencing allowed us to pinpoint and characterize at nucleotide-level resolution a chromothripsis-like complex rearrangement (CR) inserted into the chr17 co-segregating region at the KCNJ2-SOX9 locus. The CR involved the gain of five different regions from chr1 that are shuffled, chained, and inserted as a single block (∼828 kb) at chr17q24.3. The inserted sequences contain craniofacial enhancers that are predicted to interact with KCNJ2/KCNJ16 through neo-topologically associating domain (TAD) formation to induce ectopic activation. Our findings suggest that the CR inserted at chr17q24.3 is the cause of the severe skeletal Class II malocclusion with gingival hyperplasia in this family and expands the panoply of phenotypes linked to variation at the KCNJ2-SOX9 locus. In addition, we highlight a previously overlooked potential role for misregulation of the KCNJ2/KCNJ16 genes in the pathomechanism of gingival hyperplasia associated with deletions and other rearrangements of the 17q24.2-q24.3 region (MIM 135400).

Neural tube closure defect pathomechanisms in human embryonic development are poorly understood. Here we identified spina bifida patients expressing novel variants of the TOGARAM gene family. TOGARAM1 has been associated with the ciliopathy Joubert syndrome, but its connection to spina bifida and role in neural development is unknown. We show that Togaram1 is expressed in the neural tube and Togaram1 knockout mice have abnormal cilia, reduced sonic hedgehog (Shh) signaling, abnormal neural tube patterning, and display neural tube closure defects. Neural stem cells from Togaram1 knockout embryos showed reduced cilia and defects in Shh signaling. Overexpression in IMCD3 and HEK293 cells of TOGARAM1 carrying the variant found in the spina bifida patient resulted in cilia defect along with reduced pericentriolar material one (PCM1), a critical constituent of centriolar satellites involved in transporting proteins toward the centrosome and primary cilia. Our results demonstrate the role of TOGARAM1 in regulating Shh signaling during early neural development that is critical for neural tube closure and elucidates potential mechanisms whereby the ciliopathy-associated gene TOGARAM1 gives rise to spina bifida aperta in humans.

Several empirical and theoretical studies suggest the presence of multiple enhancers per gene that collectively regulate gene expression, and that common sequence variation impacting on the activities of these enhancers is a major source of inter-individual gene expression variability. However, for the vast majority of genes, enhancers and the underlying regulatory variation remains unknown. Even for the genes with well-characterized enhancers, the nature of the combined effects from multiple enhancers and their variants, when known, on gene expression regulation remains unexplored. Here, we have evaluated the combined effects from five SCN5A enhancers and their regulatory variants that are known to collectively correlate with SCN5A cardiac expression and underlie QT interval association in the general population. Using small deletions centered at the regulatory variants in episomal reporter assays in a mouse cardiomyocyte cell line, we demonstrate that the variants and their flanking sequences play critical role in individual enhancer activities, likely being a transcription factor (TF) binding site. By oligonucleotide-based pulldown assays on predicted TFs, we identify the TFs likely driving allele-specific enhancer activities. Using all 32 possible allelic synthetic constructs in reporter assays, representing the five bi-allelic enhancers, we demonstrate combined additive effects on overall enhancer activities. Using transient enhancer assays in zebrafish embryos we demonstrate that four elements act as enhancers in vivo. Together, these studies uncover the TFs driving the enhancer activities of QT interval associated SCN5A regulatory variants, reveal the additive effects from allelic combinations of these regulatory variants, and prove their potential to act as enhancers in vivo.

Correct identification of the molecular consequences of pathogenic genetic variants is essential to the development of allele-specific therapies. However, such molecular effects may remain ambiguous following genetic sequence analysis alone. Here, we identify exonic codon-altering variants that are also predicted to disrupt normal RNA splicing in the context of inherited retinal disease. NR2E3 c.932G>A (p.Arg311Gln) is a variant commonly associated with enhanced S cone syndrome. Previous studies using mutagenized cDNA constructs have shown that the arginine to glutamine substitution at position 311 of NR2E3 does not meaningfully diminish function of the rod-specific transcription factor. Using retinal organoids, we explored the molecular consequences of NR2E3 c.932G>A when expressed endogenously during human rod photoreceptor cell development. Retinal organoids carrying the NR2E3 c.932G>A allele expressed a transcript containing a 186-nucleotide deletion of exon 6 within the ligand binding domain. This short transcript was not detected in control organoids or control human donor retina samples. A minigene containing exons 5 and 6 of NR2E3 showed sufficiency of the c.932G>A variant to cause the observed splicing defect. These results support the hypothesis that the pathogenic NR2E3 c.932G>A variant leads to photoreceptor disease by causing a splice defect and not through an amino acid substitution as previously supposed. They also explain the relatively mild effect of Arg311Gln on NR2E3 function in vitro. We also used in silico prediction tools to show that similar changes are likely to affect other inherited retinal disease variants in genes such as CEP290, ABCA4, and BEST1.

The aim of this study was to scan phenotypes in adulthood associated with polygenic risk scores (PRS) for childhood cancers with well-articulated genetic architectures-acute lymphoblastic leukemia (ALL), Ewing sarcoma, and neuroblastoma-to examine genetic pleiotropy. Furthermore, we aimed to determine which SNPs could drive associations. Per-SNP summary statistics were extracted for PRS calculation. Participants with white British ancestry were exclusively included for analyses. SNPs were queried from the UK Biobank genotype imputation data. Records from the cancer registry, death registry, and inpatient diagnoses were abstracted for phenome-wide scans. Firth logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) alongside corresponding p values, adjusting for age at recruitment and sex. A total of 244,332 unrelated white British participants were included. We observed a significant association between ALL-PRS and ALL (OR: 1.20e+24, 95% CI: 9.08e+14-1.60e+33). In addition, we observed a significant association between high-risk neuroblastoma PRS and nonrheumatic aortic valve disorders (OR: 43.9, 95% CI: 7.42-260). There were no significant phenotype associations with Ewing sarcoma and neuroblastoma PRS. Regarding individual SNPs, rs17607816 increased the risk of ALL (OR: 6.40, 95% CI: 3.26-12.57). For high-risk neuroblastoma, rs80059929 elevated the risk of atrioventricular block (OR: 3.04, 95% CI: 1.85-4.99). Our findings suggest that individuals with genetic susceptibility to ALL may face a lifelong risk for developing ALL, along with a genetic pleiotropic association between high-risk neuroblastoma and circulatory diseases.

Polygenic scores (PGSs) are a promising tool for estimating individual-level genetic risk of disease based on the results of genome-wide association studies (GWASs). However, their promise has yet to be fully realized because most currently available PGSs were built with genetic data from predominantly European-ancestry populations, and PGS performance declines when scores are applied to target populations different from the populations from which they were derived. Thus, there is a great need to improve PGS performance in currently under-studied populations. In this work we leverage data from two large and diverse cohorts the Million Veterans Program (MVP) and All of Us (AoU), providing us the unique opportunity to compare methods for building PGSs for multi-ancestry populations across multiple traits. We build PGSs for five continuous traits and five binary traits using both multi-ancestry and single-ancestry approaches with popular Bayesian PGS methods and both MVP META GWAS results and population-specific GWAS results from the respective African, European, and Hispanic MVP populations. We evaluate these scores in three AoU populations genetically similar to the respective African, Admixed American, and European 1000 Genomes Project superpopulations. Using correlation-based tests, we make formal comparisons of the PGS performance across the multiple AoU populations. We conclude that approaches that combine GWAS data from multiple populations produce PGSs that perform better than approaches that utilize smaller single-population GWAS results matched to the target population, and specifically that multi-ancestry scores built with PRS-CSx outperform the other approaches in the three AoU populations.

Biallelic pathogenic variants in the gene encoding nebulin (NEB) are a known cause of congenital myopathy. We present two brothers with congenital myopathy and compound heterozygous variants (NC_000002.12:g.151692086G>T; NM_001271208.2: c.2079C>A; p.(Cys693Ter) and NC_000002.12:g.151533439T>C; NM_001271208.2:c.21522+3A>G) in NEB. Transcriptomic sequencing on affected individual muscles revealed that the extended splice variant c.21522+3A>G causes exon 144 skipping. Nebulin isoforms containing exon 144 are known to be mutually exclusive with isoforms containing exon 143, and these isoforms are differentially expressed during development and in adult skeletal muscles. Affected individuals' MRI patterns of muscle involvement were compared with the known pattern of relative abundance of these two isoforms in muscle. We propose that the pattern of muscle involvement in these affected individuals better fits the distribution of exon 144-containing isoforms in muscle than with previously published MRI findings in NEB-related disease due to other variants. Our report introduces disease pathogenesis and manifestation as a result of alteration of isoform distributions in muscle.