A multi-omics approach using a mouse model of cardiac malformations for prioritization of human congenital heart disease contributing genes
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE171239 | GEO | 2021/06/28
REPOSITORIES: GEO
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Project description:Congenital heart disease (CHD) is the most common type of birth defect, affecting ~1% of all live births. Malformations of the cardiac outflow tract (OFT) account for ~30% of all CHD and include a range of CHDs from bicuspid aortic valve (BAV) to tetralogy of Fallot (TOF). We hypothesized that transcriptomic profiling of a mouse model of CHD would highlight disease-contributing genes implicated in congenital cardiac malformations in humans. To test this hypothesis, we utilized global transcriptional profiling differences from a mouse model of OFT malformations to prioritize damaging, de novo variants identified from exome sequencing datasets from published cohorts of CHD patients. Notch1 +/- ; Nos3 -/- mice display a spectrum of cardiac OFT malformations ranging from BAV, semilunar valve (SLV) stenosis to TOF. Global transcriptional profiling of the E13.5 Notch1 +/- ; Nos3 -/- mutant mouse OFTs and wildtype controls was performed by RNA sequencing (RNA-Seq). Analysis of the RNA-Seq dataset demonstrated genes belonging to the Hif1α, Tgf-β, Hippo, and Wnt signaling pathways were differentially expressed in the mutant OFT. Mouse to human comparative analysis was then performed to determine if patients with TOF and SLV stenosis display an increased burden of damaging, genetic variants in gene homologs that were dysregulated in Notch1 +/- ; Nos3 -/- OFT. We found an enrichment of de novo variants in the TOF population among the 1,352 significantly differentially expressed genes in Notch1 +/- ; Nos3 -/- mouse OFT but not the SLV population. This association was not significant when comparing only highly expressed genes in the murine OFT to de novo variants in the TOF population. These results suggest that transcriptomic datasets generated from the appropriate temporal, anatomic and cellular tissues from murine models of CHD may provide a novel approach for the prioritization of disease-contributing genes in patients with CHD.
| S-EPMC8421733 | biostudies-literature
Project description:Congenital heart disease (CHD) is the most common type of birth defect, affecting ~1% of all live births. Malformations of the cardiac outflow tract (OFT) account for ~30% of all CHD and include a range of CHDs from bicuspid aortic valve (BAV) to tetralogy of Fallot (TOF). We hypothesized that transcriptomic profiling of a mouse model of CHD would highlight disease-contributing genes implicated in congenital cardiac malformations in humans. To test this hypothesis, we utilized global transcriptional profiling differences from a mouse model of OFT malformations to prioritize damaging, de novo variants identified from exome sequencing datasets from published cohorts of CHD patients. Notch1+/-;Nos3-/- mice display a spectrum of cardiac OFT malformations ranging from BAV, semilunar valve (SLV) stenosis to TOF. Global transcriptional profiling of the E13.5 Notch1+/-;Nos3-/- mutant mouse OFTs and wildtype controls was performed by RNA sequencing (RNA-Seq). Analysis of the RNA-Seq dataset demonstrated genes belonging to the Hif1α, Tgf-β, Hippo, and Wnt signaling pathways were differentially expressed in the mutant OFT. Mouse to human comparative analysis was then performed to determine if patients with TOF and SLV stenosis display an increased burden of damaging, genetic variants in gene homologs that were dysregulated in Notch1+/-; Nos3-/- OFT. We found an enrichment of de novo variants in the TOF population among the 1,352 significantly differentially expressed genes in Notch1+/-;Nos3-/- mouse OFT but not the SLV population. This association was not significant when compared to only highly expressed genes in the murine OFT and of de novo variants in the TOF population. These results suggest that transcriptomic datasets generated from the appropriate temporal, anatomic and cellular tissues from murine models of CHD may provide a novel approach for the prioritization of disease-contributing genes in patients with CHD.
2021-06-28 | GSE171237 | GEO
Project description:Congenital heart disease (CHD) is the most common type of birth defect, affecting ~1% of all live births. Malformations of the cardiac outflow tract (OFT) account for ~30% of all CHD and include a range of CHDs from bicuspid aortic valve (BAV) to tetralogy of Fallot (TOF). We hypothesized that transcriptomic profiling of a mouse model of CHD would highlight disease-contributing genes implicated in congenital cardiac malformations in humans. To test this hypothesis, we utilized global transcriptional profiling differences from a mouse model of OFT malformations to prioritize damaging, de novo variants identified from exome sequencing datasets from published cohorts of CHD patients. Notch1+/-;Nos3-/- mice display a spectrum of cardiac OFT malformations ranging from BAV, semilunar valve (SLV) stenosis to TOF. Global transcriptional profiling of the E13.5 Notch1+/-;Nos3-/- mutant mouse OFTs and wildtype controls was performed by RNA sequencing (RNA-Seq). Analysis of the RNA-Seq dataset demonstrated genes belonging to the Hif1α, Tgf-β, Hippo, and Wnt signaling pathways were differentially expressed in the mutant OFT. Mouse to human comparative analysis was then performed to determine if patients with TOF and SLV stenosis display an increased burden of damaging, genetic variants in gene homologs that were dysregulated in Notch1+/-; Nos3-/- OFT. We found an enrichment of de novo variants in the TOF population among the 1,352 significantly differentially expressed genes in Notch1+/-;Nos3-/- mouse OFT but not the SLV population. This association was not significant when compared to only highly expressed genes in the murine OFT and of de novo variants in the TOF population. These results suggest that transcriptomic datasets generated from the appropriate temporal, anatomic and cellular tissues from murine models of CHD may provide a novel approach for the prioritization of disease-contributing genes in patients with CHD.
2021-06-28 | GSE171238 | GEO
Project description:A multi-omics approach using a mouse model of cardiac malformations for prioritization of human congenital heart disease contributing genes
| PRJNA718837 | ENA
Project description:A multi-omics approach using a mouse model of cardiac malformations for prioritization of human congenital heart disease contributing genes [scRNA-seq]
| PRJNA718840 | ENA
Project description:A multi-omics approach using a mouse model of cardiac malformations for prioritization of human congenital heart disease contributing genes [RNA-seq]
| PRJNA718841 | ENA
Project description:Klebsiella pneumoniae (Kp) is a globally disseminated opportunistic pathogen that can cause life-threatening infections. It has been found as the culprit of many infection outbreaks in hospital environments, being particularly aggressive towards newborns and adults under intensive care. Many Kp strains produce extended-spectrum β-lactamases, enzymes that promote resistance against antibiotics used to fight these infections. The presence of other resistance determinants leading to multidrug-resistance also limit therapeutic options, and the use of 'last-resort' drugs, such as polymyxins, is not uncommon. The global emergence and spread of resistant strains underline the need for novel antimicrobials against Kp and related bacterial pathogens. To tackle this great challenge, we generated multiple layers of 'omics' data related to Kp and prioritized proteins that could serve as attractive targets for antimicrobial development. Genomics, transcriptomics, structuromic and metabolic information were integrated in order to prioritize candidate targets, and this data compendium is freely available as a web server. Twenty-nine proteins with desirable characteristics from a drug development perspective were shortlisted, which participate in important processes such as lipid synthesis, cofactor production, and core metabolism. Collectively, our results point towards novel targets for the control of Kp and related bacterial pathogens.
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Project description:Risk metabolites of postmenopausal osteoporosis (PO) were explored to offer a theoretical basis for future therapy. The data E-GEOD-7429 were downloaded from ArrayExpress database. In total 20 samples deprived from postmenopausal women having low or high bone mineral density (BMD) were covered in this expression profile. After screening of differentially expressed genes (DEGs), gene-gene network was constructed taking the intersection between the DEGs and genes in the seed protein-protein interaction network. Then, the other five networks were established, including metabolite, phenotype, gene-metabolite, phenotype-gene, and phenotype-metabolite networks. Next, these 6 networks were integrated into one weighted multi-omics network to further identify the candidate metabolites using random walk with restart based on the PO-related seed genes, seed metabolites and phenotype. Using the score among nodes of the weighted composite network, the top 50 metabolites, and the top 100 co-expressed genes interacting with the top 50 metabolites were detected. A set of 601 DEGs between low BMD and high BMD samples were selected. Significantly, the top 5 metabolites were respectively glucosylgalactosyl hydroxylysine, all-trans-5,6-epoxyretinoic acid, tretinoin, colecalciferol, and rocaltrol. Moreover, 3 metabolites (estraderm, triphosadenine, and tretinoin) had a degree >50 in the co-expression network. Tretinoin was the member of the top 5 metabolites, and estraderm was a metabolite with the seventh interaction score. A series of metabolites, tretinoin and estraderm might be closely associated with the onset and progression of PO.
| S-EPMC6434278 | biostudies-literature
Project description:During late gestation, the fetal heart relies primarily on glucose and lactate to support rapid growth and development. While numerous studies describe changes in heart metabolism a few weeks after birth to preferentially utilize fatty acids, little is known about metabolic changes of the heart within the first day of life. Therefore, we used the ovine model of pregnancy to investigate metabolic differences between the near-term fetal and the newborn heart. We observed greater abundance of metabolites involved in butanoate and propanoate metabolism, and glycolysis/gluconeogenesis in the term fetal heart (FDR-corrected p<0.10) and differential expression in these pathways were confirmed with single-sample gene set enrichment analysis (ssGSEA) (FDR-corrected p<0.05). Immediately following birth, newborn hearts displayed enrichment in purine, fatty acid, and glycerophospholipid metabolic pathways, as well as oxidative phosphorylation with significant alterations in lipids and metabolites to support transcriptomic findings. While other studies suggest a switch from carbohydrate metabolism to fatty acid metabolism in the neonatal heart in as early as 2 weeks following birth, our data show that this metabolic switch in the heart begins by the first day of postnatal life. A better understanding of metabolic alterations that occur in the heart following birth may improve treatment of neonates at risk for heart failure.
2018-11-01 | GSE117343 | GEO
Project description:The clinical significance of copy number variants (CNVs) in congenital heart disease (CHD) continues to be a challenge. Although CNVs including genes can confer disease risk, relationships between gene dosage and phenotype are still being defined. Our goal was to perform a quantitative analysis of CNVs involving 100 well-defined CHD risk genes identified through previously published human association studies in subjects with anatomically defined cardiac malformations. A novel analytical approach permitting CNV gene frequency "spectra" to be computed over prespecified regions to determine phenotype-gene dosage relationships was employed. CNVs in subjects with CHD (n = 945), subphenotyped into 40 groups and verified in accordance with the European Paediatric Cardiac Code, were compared with two control groups, a disease-free cohort (n = 2,026) and a population with coronary artery disease (n = 880). Gains (?200 kb) and losses (?100 kb) were determined over 100 CHD risk genes and compared using a Barnard exact test. Six subphenotypes showed significant enrichment (P ? 0.05), including aortic stenosis (valvar), atrioventricular canal (partial), atrioventricular septal defect with tetralogy of Fallot, subaortic stenosis, tetralogy of Fallot, and truncus arteriosus. Furthermore, CNV gene frequency spectra were enriched (P ? 0.05) for losses at: FKBP6, ELN, GTF2IRD1, GATA4, CRKL, TBX1, ATRX, GPC3, BCOR, ZIC3, FLNA and MID1; and gains at: PRKAB2, FMO5, CHD1L, BCL9, ACP6, GJA5, HRAS, GATA6 and RUNX1. Of CHD subjects, 14% had causal chromosomal abnormalities, and 4.3% had likely causal (significantly enriched), large, rare CNVs. CNV frequency spectra combined with precision phenotyping may lead to increased molecular understanding of etiologic pathways.
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