Cell-free DNA fragment-size distribution analysis for non-invasive prenatal CNV prediction

Advancing Non-Invasive Prenatal Screening: A Targeted 1069-Gene Panel for Comprehensive Detection of Monogenic Disorders and Copy Number Variations

We introduce an innovative, non-invasive prenatal screening approach for detecting fetal monogenic alterations and copy number variations (CNVs) from maternal blood.

METHOD

Circulating free DNA (cfDNA) was extracted from maternal peripheral blood and processed using the VeriSeq NIPT Solution (Illumina, San Diego, CA, USA), with shallow whole-genome sequencing (sWGS) performed on a NextSeq550Dx (Illumina). A customized gene panel and bioinformatics tool, named the "VERA Revolution", were developed to detect variants and CNVs in cfDNA samples. Results were compared with genomic DNA (gDNA) extracted from fetal samples, including amniotic fluid and chorionic villus sampling and buccal swabs.

RESULTS

The study included pregnant women with gestational ages from 10 + 3 to 15 + 2 weeks (mean: 12.1 weeks). The fetal fraction (FF), a crucial measure of cfDNA test reliability, ranged from 5% to 20%, ensuring adequate DNA amount for analysis. Among 36 families tested, 14 showed a wild-type genotype. Identified variants included two deletions (22q11.2, and 4p16.3), two duplications (16p13 and 5p15), and eighteen single-nucleotide variants (one in CFTR, three in GJB2, three in PAH, one in RIT1, one in DHCR7, one in TCOF1, one in ABCA4, one in MYBPC3, one in MCCC2, two in GBA1 and three in PTPN11). Significant concordance was found between our panel results and prenatal/postnatal genetic profiles.

CONCLUSIONS

The "VERA Revolution" test highlights advancements in prenatal genomic screening, offering potential improvements in prenatal care.

Cell-Free DNA Fragmentomics: The Novel Promising Biomarker

Cell-free DNA molecules are released into the plasma via apoptotic or necrotic events and active release mechanisms, which carry the genetic and epigenetic information of its origin tissues. However, cfDNA is the mixture of various cell fragments, and the efficient enrichment of cfDNA fragments with diagnostic value remains a great challenge for application in the clinical setting. Evidence from recent years shows that cfDNA fragmentomics' characteristics differ in normal and diseased individuals without the need to distinguish the source of the cfDNA fragments, which makes it a promising novel biomarker. Moreover, cfDNA fragmentomics can identify tissue origins by inferring epigenetic information. Thus, further insights into the fragmentomics of plasma cfDNA shed light on the origin and fragmentation mechanisms of cfDNA during physiological and pathological processes in diseases and enhance our ability to take the advantage of plasma cfDNA as a molecular diagnostic tool. In this review, we focus on the cfDNA fragment characteristics and its potential application, such as fragment length, end motifs, jagged ends, preferred end coordinates, as well as nucleosome footprints, open chromatin region, and gene expression inferred by the cfDNA fragmentation pattern across the genome. Furthermore, we summarize the methods for deducing the tissue of origin by cfDNA fragmentomics.

A method for improving the accuracy of non-invasive prenatal screening by cell-free foetal DNA size selection

Background Non-invasive prenatal screening (NIPS) using cell-free foetal DNA (cfDNA) has been widely used for identifying common foetal aneuploidies (e.g. trisomy 21 (T21), trisomy (T18) and trisomy 13 (T13)) in clinical practice. The sensitivity and specificity of NIPS exceeds 99%, but the positive prediction value (PPV) is approximately 70% (combined T21, T18 and T13). Thus, some 30% of pregnant women who have positive NIPS results are eventually identified as normal by amniocentesis. These women therefore must undertake needless invasive tests and risk miscarrying healthy babies because of false positive NIPS results. Methods In order to achieve higher accuracy, we amended the standard NIPS (s-NIPS) protocol with an additional cfDNA size selecting step in agarose-electrophoresis. The advantage of the new method (named e-NIPS) was validated by comparing the results of e-NIPS and s-NIPS using 114 retrospective cases selected from 15,930 cases. Results Our results showed that the foetal cfDNA fraction can be enriched significantly by a size selection step. With this modification, all 98 negative cases and 9 of 11 false positive cases of s-NIPS were correctly identified by e-NIPS, resulting in an increased PPV from 71% to 77%. Additionally, a simulation test showed that e-NIPS is more reliable than s-NIPS, especially when the foetal cfDNA concentration and sequencing coverage are low. Conclusion cfDNA size selection is an important step in improving the accuracy of non-invasive prenatal screening for chromosomal abnormalities.

Bayesian-based noninvasive prenatal diagnosis of single-gene disorders

In the last decade, noninvasive 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 currently used 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 length distribution of fetal- and maternal-derived cfDNA fragments 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.

Analysis of human blood plasma cell-free DNA fragment size distribution using EvaGreen chemistry based droplet digital PCR assays

BACKGROUND

Plasma cell-free DNA (cfDNA) fragment size distribution provides important information required for diagnostic assay development. We have developed and optimized droplet digital PCR (ddPCR) assays that quantify short and long DNA fragments. These assays were used to analyze plasma cfDNA fragment size distribution in human blood.

METHODS

Assays were designed to amplify 76,135, 490 and 905 base pair fragments of human β-actin gene. These assays were used for fragment size analysis of plasma cell-free, exosome and apoptotic body DNA obtained from normal and pregnant donors.

RESULTS

The relative percentages for 76, 135, 490 and 905 bp fragments from non-pregnant plasma and exosome DNA were 100%, 39%, 18%, 5.6% and 100%, 40%, 18%,3.3%, respectively. The relative percentages for pregnant plasma and exosome DNA were 100%, 34%, 14%, 23%, and 100%, 30%, 12%, 18%, respectively. The relative percentages for non-pregnant plasma pellet (obtained after 2nd centrifugation step) were 100%, 100%, 87% and 83%, respectively.

CONCLUSION

Non-pregnant Plasma cell-free and exosome DNA share a unique fragment distribution pattern which is different from pregnant donor plasma and exosome DNA fragment distribution indicating the effect of physiological status on cfDNA fragment size distribution. Fragment distribution pattern for plasma pellet that includes apoptotic bodies and nuclear DNA was greatly different from plasma cell-free and exosome DNA.

New evidence that a large proportion of human blood plasma cell-free DNA is localized in exosomes

Cell-free DNA (cfDNA) in blood is used as a source of genetic material for noninvasive prenatal and cancer diagnostic assays in clinical practice. Recently we have started a project for new biomarker discovery with a view to developing new noninvasive diagnostic assays. While reviewing literature, it was found that exosomes may be a rich source of biomarkers, because exosomes play an important role in human health and disease. While characterizing exosomes found in human blood plasma, we observed the presence of cfDNA in plasma exosomes. Plasma was obtained from blood drawn into K3EDTA tubes. Exosomes were isolated from cell-free plasma using a commercially available kit. Sizing and enumeration of exosomes were done using electron microscopy and NanoSight particle counter. NanoSight and confocal microscopy was used to demonstrate the association between dsDNA and exosomes. DNA extracted from plasma and exosomes was measured by a fluorometric method and a droplet digital PCR (ddPCR) method. Size of extracellular vesicles isolated from plasma was heterogeneous and showed a mean value of 92.6 nm and a mode 39.7 nm. A large proportion of extracellular vesicles isolated from plasma were identified as exosomes using a fluorescence probe specific for exosomes and three protein markers, Hsp70, CD9 and CD63, that are commonly used to identify exosome fraction. Fluorescence dye that stain dsDNA showed the association between exosomes and dsDNA. Plasma cfDNA concentration analysis showed more than 93% of amplifiable cfDNA in plasma is located in plasma exosomes. Storage of a blood sample showed significant increases in exosome count and exosome DNA concentration. This study provide evidence that a large proportion of plasma cfDNA is localized in exosomes. Exosome release from cells is a metabolic energy dependent process, thus suggesting active release of cfDNA from cells as a source of cfDNA in plasma.

Structural Chromosomal Rearrangements Require Nucleotide-Level Resolution: Lessons from Next-Generation Sequencing in Prenatal Diagnosis

In this exciting era of "next-gen cytogenetics," integrating genomic sequencing into the prenatal diagnostic setting is possible within an actionable time frame and can provide precise delineation of balanced chromosomal rearrangements at the nucleotide level. Given the increased risk of congenital abnormalities in newborns with de novo balanced chromosomal rearrangements, comprehensive interpretation of breakpoints could substantially improve prediction of phenotypic outcomes and support perinatal medical care. Herein, we present and evaluate sequencing results of balanced chromosomal rearrangements in ten prenatal subjects with respect to the location of regulatory chromatin domains (topologically associated domains [TADs]). The genomic material from all subjects was interpreted to be "normal" by microarray analyses, and their rearrangements would not have been detected by cell-free DNA (cfDNA) screening. The findings of our systematic approach correlate with phenotypes of both pregnancies with untoward outcomes (5/10) and with healthy newborns (3/10). Two pregnancies, one with a chromosomal aberration predicted to be of unknown clinical significance and another one predicted to be likely benign, were terminated prior to phenotype-genotype correlation (2/10). We demonstrate that the clinical interpretation of structural rearrangements should not be limited to interruption, deletion, or duplication of specific genes and should also incorporate regulatory domains of the human genome with critical ramifications for the control of gene expression. As detailed in this study, our molecular approach to both detecting and interpreting the breakpoints of structural rearrangements yields unparalleled information in comparison to other commonly used first-tier diagnostic methods, such as non-invasive cfDNA screening and microarray analysis, to provide improved genetic counseling for phenotypic outcome in the prenatal setting.