Ontology highlight
ABSTRACT:
PROVIDER: PRJNA837911 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR19200923_1.fastq.gz | Fastqsanger.gz | |||
| SRR19200923_2.fastq.gz | Fastqsanger.gz | |||
| SRR19200924_1.fastq.gz | Fastqsanger.gz | |||
| SRR19200924_2.fastq.gz | Fastqsanger.gz | |||
| SRR19200925_1.fastq.gz | Fastqsanger.gz |
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Project description:The early detection of tissue and organ damage associated with autoimmune diseases (AID) has been identified as key to improve long-term survival, but non-invasive biomarkers are lacking. Elevated cell-free DNA (cfDNA) levels have been observed in AID and inflammatory bowel disease (IBD), prompting interest to use cfDNA as a potential non-invasive diagnostic and prognostic biomarker. Despite these known disease-related changes in concentration, it remains impossible to identify AID and IBD patients through cfDNA analysis alone. By using unsupervised clustering on large sets of shallow whole-genome sequencing (sWGS) cfDNA data, we uncover AID- and IBD-specific genome-wide patterns in plasma cfDNA in both the obstetric and general AID and IBD populations. Supervised learning of the genome-wide patterns allows AID prediction with 50% sensitivity at 95% specificity. Importantly, the method can identify pregnant women with AID during routine non-invasive prenatal screening. Since AID pregnancies have an increased risk of severe complications, early recognition or detection of new onset AID can redirect pregnancy management and limit potential adverse events. This method opens up new avenues for screening, diagnosis and monitoring of AID and IBD.
2022-09-14 | E-MTAB-11607 | biostudies-arrayexpress
Project description:we have conducted a comparative study of the different technologies available for the detection of chromosomal abnormalities in prenatal samples. Here we include results of the aCGH experiments
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Project description:<p>In the last decade, non-invasive prenatal diagnosis (NIPD) has emerged as an effective procedure for early detection of inherited diseases during pregnancy. This technique is based on using cell-free DNA (cfDNA) and fetal cfDNA (cffDNA) in maternal blood, and hence, has minimal risk for the mother and fetus compared with invasive techniques. NIPD is used today for identifying chromosomal abnormalities (in some instances) and for single-gene disorders (SGDs) of paternal origin. However, for SGDs of maternal origin, sensitivity poses a challenge that limits the testing to one genetic disorder at a time. Here we present a Bayesian method for the NIPD of monogenic diseases that is independent of the mode of inheritance and parental origin. Furthermore, we show that accounting for differences in the fragment length distribution of fetal- and maternal-derived cfDNA results in increased accuracy. Our model is the first to predict inherited insertions-deletions (indels). The method described can serve as a general framework for the NIPD of SGDs; this will facilitate easy integration of further improvements. One such improvement that is presented in the current study is a machine learning model that corrects errors based on patterns found in previously processed data. Overall, we show that next generation sequencing (NGS) can be used for the NIPD of a wide range of monogenic diseases, simultaneously. We believe that our study will lead to the achievement of a comprehensive NIPD for monogenic diseases.</p> <p>(Reprinted from Bayesian-based noninvasive prenatal diagnosis of single-gene disorders, with permission from Genome Research) </p>
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Project description:we have conducted a comparative study of the different technologies available for the detection of chromosomal abnormalities in prenatal samples. Here we include results of the aCGH experiments this series is composed of internal controls plus a year-long (2009-2010) consecutive series of pregnant women with indication for prenatal screening of chromosomal abnormalities a pdf and txt version of the table with 'sample name' plus relevant sample characteristics, including chromosomal abnormalities identified in our work is provided as a supplementary file on the Series record (below).
2014-01-07 | E-GEOD-26654 | biostudies-arrayexpress
Project description:This study aimed to evaluate the clinical value of copy number variations (CNVs) in fetuses with ultrasonic soft markers. Among 1131 fetuses, 729 had single ultrasonic soft marker, 322 had two ultrasonic soft markers, and 80 had three or more ultrasonic soft markers. All fetuses underwent single nucleotide polymorphism (SNP) array analysis. Among 1131 fetuses with ultrasonic soft markers, 46 had chromosomal abnormalities. In addition to the 46 fetuses with chromosomal abnormalities consistent with the results of the karyotyping analysis, the SNP array identified additional 6.1% (69/1131) abnormal CNVs. No significant difference was found in the rate of abnormal CNVs among the groups. The SNP array can fully complement conventional karyotyping in fetuses with ultrasonic soft markers, improve detection rate of chromosomal abnormalities, and affect pregnancy outcomes.
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2019-03-31 | E-MTAB-7163 | biostudies-arrayexpress
Project description:Chromosomal abnormalities of 564 miscarriages
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Project description:We performed all stimulatory experiments using THP1 cell line as a representative of primary human monocytes to show fundamental role of the cfDNA in healthy organisms. The experiments were conducted in duplicates using plasma containing cfDNA (NP) and the reference one with cfDNA removed by DNase (TP) to recognize unequivocally the effect of plasma cfDNA on transcriptome and proteome of monocytes. We used native human plasma samples obtained from healthy volunteers with no animal serum addition to cultivation medium in order to avoid the presence of uncharacterized animal cfDNA in the experiments.
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