Familial exome sequencing in rare pediatric phenotypes
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA177191 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:<p>To discover novel candidate genes associated with rare Mendelian phenotypes, we will conduct individual genomic and phenotypic characterization using genome-wide array, pedigree exome sequencing, candidate genotyping, and pertinent clinical testing to define phenotype. Pedigrees included in this submission will have a variety of clinical pathological phenotypes.</p>
| phs000553.v1.p1 | EGA
Project description:Familial exome sequencing in rare pediatric phenotypes
| PRJNA177192 | ENA
Project description:Rare germline variations in familial melanoma
| PRJNA335673 | ENA
Project description:<p>To discover novel candidate genes associated with rare Mendelian phenotypes, we will conduct individual genomic and phenotypic characterization using genome-wide array, pedigree exome sequencing, candidate genotyping, and pertinent clinical testing to define phenotype. Pedigrees included in this submission will have a variety of clinical pathological phenotypes.</p>
| phs000553 | dbGaP
Project description:The study of rare pediatric disorders is fundamentally limited by small patient numbers, making it challenging to draw meaningful conclusions about their molecular basis. To address this, we developed a framework that integrates clinical ontologies with proteomic profiling, enabling the systematic analysis of rare conditions in aggregate rather than isolation. We demonstrated this approach by analyzing urine and plasma samples from 1,140 children and adolescents, encompassing 394 distinct disease conditions and healthy controls. Using advanced mass spectrometry workflows, we achieved deep proteome coverage with over 5,000 proteins quantified in urine and 900 in plasma. By embedding SNOMED CT clinical terminology in a network structure and connecting it to proteomic data, we could group rare conditions based on their clinical relationships, allowing statistical analysis even for diseases with as few as two patients. This approach revealed molecular signatures across developmental stages and disease clusters while accounting for age- and sex-specific variation. Our framework provides a generalizable solution for studying heterogeneous patient populations where traditional case-control studies are impractical, bridging the gap between clinical classification and molecular profiling of rare diseases.
2025-06-10 | PXD058960 | Pride
Project description:Purpose: Evaluation of XCI status in a cohot of female patients with suspected rare genetic diseases using exome and RNA sequencing Results: We developed a method for estimating X inactivation status, using exome and transcriptome sequencing data from 112 female samples. We built a reference model for evaluation of XCI in 135 females from the GTEx consortium. We tested and validated the model on 14 female individuals with different types of undiagnosed rare genetic disorders who were clinically tested for X-skew using the AR gene assay and compared results to our outlier-based analysis technique. In comparison to the AR clinical test for identification of X inactivation, our method was concordant with AR method in 9 samples, discordant in 3, and provided measures of X inactivation in 2 samples with uninformative clinical results. We applied this method on an additional 98 females presenting to the clinic with phenotypes consistent with different hereditary disorders without a known genetic diagnosis. Here we show the use of transcriptome sequencing data to provide an accurate and complete estimation of X-inactivation and skew status in female patients.
2024-04-24 | GSE234607 | GEO
Project description:Background and Aims: Evidence for a genetic contribution to eosinophilic esophagitis (EoE) exists from family and genome-wide association studies. Extensive investigation into rare variants contributing to EoE has not been performed. The Aim is to evaluate families with multiple cases of EoE by genomic and transcriptomic sequencing to identify genes predisposing to EoE. Methods: We whole exome sequenced (WES) distant relative pairs (e.g., cousins) in extended EoE pedigrees and other affected relatives to identify rare, shared, potentially pathologic variants. Whole-transcriptome sequencing by RNA-Seq was performed in nuclear families with multiple EoE cases. We compared the overlap of genes from DNA and RNA sequencing for relevance to disease manifestations. Results: WES was performed in 50 familial cases in 21 EoE extended pedigrees. We observed 219 rare, candidate predisposition variants in 210 genes with complete sharing among all affected family members. Transcriptome sequencing was performed for 43 EoE cases in 18 nuclear kindreds, including 6 relatives without EoE. We observed 10,070 total differentially expressed genes compared to controls. We identified three genes (MUC16, ADGRE1, and TENM3) with evidence of rare variant sharing and differential gene expression among all affected family members. We identified 43 other genes with partial sharing of rare variants among affected family members and with differential gene expression. Several genes identified as prominent in EoE were also differentially expressed in unaffected relatives. Conclusions: Multiple genes related to immune response, barrier dysfunction, and cell adhesion were identified in familial EoE cases and unaffected family members supporting a genetic familial predisposition and a possible multi-hit background to disease pathophysiology.
2025-01-24 | GSE250595 | GEO
Project description:My Pediatric and Adult Rare Tumor (MyPART) Natural History Study of Rare Solid Tumors
| PRJNA909405 | ENA
Project description:My Pediatric and Adult Rare Tumor (MyPART) Natural History Study of Rare Solid Tumors
| PRJNA909406 | ENA
Project description:Mounting evidence suggests that copy number variations (CNVs) can contribute to cancer susceptibility. The main goal of this study was to evaluate the role of germline CNVs in melanoma predisposition in high-risk melanoma families. We used genome-wide tiling comparative genomic hybridization and SNP arrays to characterize CNVs in 335 individuals (240 melanoma cases) from American melanoma-prone families (22 with germline CDKN2A or CDK4 mutations). We found that the global burden of overall CNVs (or deletions or duplications separately) was not significantly associated with case-control or CDKN2A/CDK4 mutation status after accounting for the familial dependence. However, we identified several rare CNVs that either involved known melanoma genes (e.g. PARP1, CDKN2A) or co-segregated with melanoma (duplication on 10q23.23, 3p12.2 and deletions on 8q424.3, 2q22.1) in families without mutations in known melanoma high-risk genes. Some of these CNVs were correlated with expression changes in disrupted genes based on RNASeq data from a subset of melanoma cases included in the CNV study. These results suggest that rare co-segregating CNVs may influence melanoma susceptibility in some melanoma-prone families and genes found in our study warrant further evaluation in future genetic analyses of melanoma.
2016-12-01 | GSE85010 | GEO