10 research outputs found

    Genome-wide neonatal epigenetic changes associated with maternal exposure to the COVID-19 pandemic

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    Abstract Background During gestation, stressors to the fetus, including viral exposure or maternal psychological distress, can fundamentally alter the neonatal epigenome, and may be associated with long-term impaired developmental outcomes. The impact of in utero exposure to the COVID-19 pandemic on the newborn epigenome has yet to be described. Methods This study aimed to determine whether there are unique epigenetic signatures in newborns who experienced otherwise healthy pregnancies that occurred during the COVID-19 pandemic (Project RESCUE). The pre-pandemic control and pandemic cohorts (Project RESCUE) included in this study are part of a prospective observational and longitudinal cohort study that evaluates the impact of elevated prenatal maternal stress during the COVID-19 pandemic on early childhood neurodevelopment. Using buccal swabs collected at birth, differential DNA methylation analysis was performed using the Infinium MethylationEPIC arrays and linear regression analysis. Pathway analysis and gene ontology enrichment were performed on resultant gene lists. Results Widespread differential methylation was found between neonates exposed in utero to the pandemic and pre-pandemic neonates. In contrast, there were no apparent epigenetic differences associated with maternal COVID-19 infection during pregnancy. Differential methylation was observed among genomic sites that underpin important neurological pathways that have been previously reported in the literature to be differentially methylated because of prenatal stress, such as NR3C1. Conclusions The present study reveals potential associations between exposure to the COVID-19 pandemic during pregnancy and subsequent changes in the newborn epigenome. While this finding warrants further investigation, it is a point that should be considered in any study assessing newborn DNA methylation studies obtained during this period, even in otherwise healthy pregnancies

    Identification of novel candidate genes for 46,XY disorders of sex development (DSD) using a C57BL/6J-Y POS mouse model

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    Abstract Background Disorders of sex development (DSD) have an estimated frequency of 0.5% of live births encompassing a variety of urogenital anomalies ranging from mild hypospadias to a discrepancy between sex chromosomes and external genitalia. In order to identify the underlying genetic etiology, we had performed exome sequencing in a subset of DSD cases with 46,XY karyotype and were able to identify the causative genetic variant in 35% of cases. While the genetic etiology was not ascertained in more than half of the cases, a large number of variants of unknown clinical significance (VUS) were identified in those exomes. Methods To investigate the relevance of these VUS in regards to the patient’s phenotype, we utilized a mouse model in which the presence of a Y chromosome from the poschiavinus strain (Y POS ) on a C57BL/6J (B6) background results in XY undervirilization and sex reversal, a phenotype characteristic to a large subset of human 46,XY DSD cases. We assessed gene expression differences between B6-Y B6 and undervirilized B6-Y POS gonads at E11.5 and identified 515 differentially expressed genes (308 underexpressed and 207 overexpressed in B6-Y POS males). Results We identified 15 novel candidate genes potentially involved in 46,XY DSD pathogenesis by filtering the list of human VUS-carrying genes provided by exome sequencing with the list of differentially expressed genes from B6-Y POS mouse model. Additionally, we identified that 7 of the 15 candidate genes were significantly underexpressed in the XY gonads of mice with suppressed Sox9 expression in Sertoli cells suggesting that some of the candidate genes may be downstream of a well-known sex determining gene, Sox9. Conclusion The use of a DSD-specific animal model improves variant interpretation by correlating human sequence variants with transcriptome variation

    Optical genome mapping identifies a novel pediatric embryonal tumor with a ZNF532::NUTM1 fusion

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    The molecular characteristics of pediatric brain tumors have not only allowed for tumor subgrouping but have led to the introduction of novel treatment options for patients with specific tumor alterations. Therefore, an accurate histologic and molecular diagnosis is critical for optimized management of all pediatric patients with brain tumors, including central nervous system embryonal tumors. We present a case where optical genome mapping identified a ZNF532::NUTM1 fusion in a patient with a unique tumor best characterized histologically as a central nervous system embryonal tumor with rhabdoid features. Additional analyses including immunohistochemistry for NUT protein, methylation array, whole genome, and RNA-sequencing was done to confirm the presence of the fusion in the tumor. This is the first description of a pediatric patient with a ZNF532::NUTM1 fusion, yet the histology of this tumor is similar to that of adult cancers with ZNF::NUTM1 fusions reported in the literature. Although rare, the distinct pathology and underlying molecular characteristics of the ZNF532::NUTM1 tumor separates this from other embryonal tumors. Therefore, screening for this or similar NUTM1 rearrangements should be considered for all patients with unclassified central nervous system tumors with rhabdoid features to ensure accurate diagnosis. Ultimately, with additional cases, we may be able to better inform therapeutic management for these patients. © 2023 The Pathological Society of Great Britain and Ireland

    Additional file 3: Table S3. of Identification of novel candidate genes for 46,XY disorders of sex development (DSD) using a C57BL/6J-Y POS mouse model

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    Biological processes in which differentially expressed genes are involved. The list of 515 genes found to be differentially expressed between B6-Y POS and WT male embryonic gonads was analyzed using the Gene Ontology Consortium functional annotation software. The categories of Gene Ontology biological processes are shown in column 1. P value (column 5) is defined as the probability of seeing the indicated number of genes from the custom list (column 4) in the GO term gene list (column 3), given the total number of annotated genes in the whole genome. (DOCX 12 kb
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