NiPTUNE: an automated pipeline for noninvasive prenatal testing in an accurate, integrative and flexible framework

KF-NIPT: K-mer and fetal fraction-based estimation of chromosomal anomaly from NIPT data

BACKGROUND

Non-Invasive Prenatal Testing (NIPT) is a technique that allows pregnant women to screen for chromosomal abnormalities in their developing fetus without the need for invasive procedures like amniocentesis or chorionic villus sampling. However, current methods to detect anomaly from maternal cell-free DNAs (cfDNAs) that are based on the sequence read counts calculating z-scores face challenges with false positives and negatives. To address these challenges, we aimed to develop a novel NIPT algorithm named KF-NIPT, which is derived from the initials of k-mer and fetal fraction used in its development with the goal of significantly improving accuracy.

RESULTS

We developed a KF-NIPT, a new algorithm that estimate chromosomal anomaly by calculating K-mer-based sequence depth and fetal fraction from the whole genome sequencing (WGS) data. Moreover, we implemented a modified preprocessing pipeline for the WGS data, correcting the biases of the genomic mapping quality and the GC contents. The performance of our method was evaluated using publicly available NIPT data. We could demonstrate that our method has better accuracy and sensitivity compared to those of the previous methods.

CONCLUSIONS

We found that using k-mer and fetal fraction reduces errors in NIPT and have integrated this into a pipeline, showing that the traditional read count-based z-score method can be improved. KF-NIPT is implemented in the R and Python environment. The source code is available at https://github.com/eastbrain/KF-NIPT . KF-NIPT has been tested on Ubuntu Linux-64 server and Linux-64 on Windows using a WSL (Windows Subsystem for Linux).

Tell me y: anticipation of sex discrepancies in cell-free DNA testing due to maternal genetic abnormalities: a case report

Sex discordance between cell-free DNA (cfDNA) testing and ultrasound examination is rare but can cause significant patient discomfort and uncertainty. Here, we present two clinical cases where a closer examination of raw sequencing data allowed us to anticipate possible discrepancies caused by the insertion of Y-chromosome regions into the maternal genome. We used Illumina's VeriSeq NIPT Solution v2 and a proprietary bioinformatics pipeline to analyze cfDNA in the maternal bloodstream. Paired-end sequencing data were aligned to the reference genome (hg19). Non-duplicated aligned reads were aggregated into 100-kb bins, adjusted for CG bias, and further aggregated into 5-Mb windows. Z-scores were calculated for autosomes, sex chromosomes, and 5-Mb bins. The two clinical cases were classified as low-risk male fetuses according to the primary statistics (case A: NCVx = 0.3; NCVy = 40.6; native fetal fraction (FFi) = 5.1%, and case B: NCVx = -0.3, NCVy = 40.7, FFi = 10.8%); however, the Y-chromosome-based FF (FFy) was significantly lower than the default FF estimate (FFy ≅ 2% in both cases). Plots of X and Y chromosome Z-scores for each 5-Mb bin, according to genomic position, identified bins with Z-scores significantly higher than those expected for any pregnancy with a male fetus. The genomic coordinates of these bins overlapped with the amelogenin (AMELY) and protein kinase Y-linked (PRKY) genes, respectively. Amplification of these regions in the DNA isolated from the white blood cells fraction confirmed the presence of Y-chromosome insertions in the maternal genome. This study highlights a new source of discrepancy in cfDNA testing due to maternal genomic variations. These findings suggest the need for improvements to current bioinformatics pipelines to identify and exclude possible maternal perturbations from the classification algorithms used for aneuploidy and sex calls.

The Impact of Chromosomal Mosaicisms on Prenatal Diagnosis and Genetic Counseling-A Narrative Review

Genetic disorders represent a high-impact diagnosis for both patients and their families. Prenatal screening methods and, when recommended, genetic testing allow parents to make informed decisions about the course a pregnancy is going to take. Although offering certainty about the potential evolution and prognosis of the pregnancy, and then the newborn, is usually not possible, genetic counseling can offer valuable insights into genetic disorders. Chromosomal mosaicisms are genetic anomalies that affect only some cell lines in either the fetus or the placenta or both. They can affect autosomal or heterosomal chromosomes, and they can be either numerical or structural. The prognosis seems to be more severe if the genetic alterations are accompanied by malformations visible in ultrasounds. Several genetic techniques can be used to diagnose certain mosaicisms, depending on their nature. A novel approach in prenatal care is non-invasive prenatal screening (NIPS), also known as non-invasive prenatal testing (NIPT), which, although it does not always have diagnostic value, can provide valuable information about potential genetic anomalies, especially numerical, with high sensitivity (Se).

DNA Methylation in the Fields of Prenatal Diagnosis and Early Detection of Cancers

The central objective of the metamorphosis of discovery science into biomedical applications is to serve the purpose of patients and curtail the global disease burden. The journey from the discovery of DNA methylation (DNAm) as a biological process to its emergence as a diagnostic tool is one of the finest examples of such metamorphosis and has taken nearly a century. Particularly in the last decade, the application of DNA methylation studies in the clinic has been standardized more than ever before, with great potential to diagnose a multitude of diseases that are associated with a burgeoning number of genes with this epigenetic alteration. Fetal DNAm detection is becoming useful for noninvasive prenatal testing, whereas, in very preterm infants, DNAm is also shown to be a potential biological indicator of prenatal risk factors. In the context of cancer, liquid biopsy-based DNA-methylation profiling is offering valuable epigenetic biomarkers for noninvasive early-stage diagnosis. In this review, we focus on the applications of DNA methylation in prenatal diagnosis for delivering timely therapy before or after birth and in detecting early-stage cancers for better clinical outcomes. Furthermore, we also provide an up-to-date commercial landscape of DNAm biomarkers for cancer detection and screening of cancers of unknown origin.

Identification of Potential Biomarkers and Small Molecule Drugs for Bisphosphonate-Related Osteonecrosis of the Jaw (BRONJ): An Integrated Bioinformatics Study Using Big Data

This study aimed to identify potential molecular mechanisms and therapeutic targets for bisphosphonate-related osteonecrosis of the jaw (BRONJ), a rare but serious side effect of bisphosphonate therapy. This study analyzed a microarray dataset (GSE7116) of multiple myeloma patients with BRONJ (n = 11) and controls (n = 10), and performed gene ontology, a pathway enrichment analysis, and a protein-protein interaction network analysis. A total of 1481 differentially expressed genes were identified, including 381 upregulated and 1100 downregulated genes, with enriched functions and pathways related to apoptosis, RNA splicing, signaling pathways, and lipid metabolism. Seven hub genes (FN1, TNF, JUN, STAT3, ACTB, GAPDH, and PTPRC) were also identified using the cytoHubba plugin in Cytoscape. This study further screened small-molecule drugs using CMap and verified the results using molecular docking methods. This study identified 3-(5-(4-(Cyclopentyloxy)-2-hydroxybenzoyl)-2-((3-hydroxybenzo[d]isoxazol-6-yl) methoxy) phenyl) propanoic acid as a potential drug treatment and prognostic marker for BRONJ. The findings of this study provide reliable molecular insight for biomarker validation and potential drug development for the screening, diagnosis, and treatment of BRONJ. Further research is needed to validate these findings and develop an effective biomarker for BRONJ.

GenomeMixer and TRUST: Novel bioinformatics tools to improve reliability of Non-Invasive Prenatal Testing (NIPT) for fetal aneuploidies

Non-invasive prenatal testing (NIPT) screens for common fetal chromosomal abnormalities through analysis of circulating cell-free DNA in maternal blood by massive parallel sequencing. NIPT reliability relies on both the estimation of the fetal fraction (ff) and on the sequencing depth (sd) but how these parameters are linked is unknown. Several bioinformatics tools have been developed to determine the ff but there is no universal ff threshold applicable across diagnostics laboratories. Thus, we developed two tools allowing the implementation of a strategy for NIPT results validation in clinical practice: GenomeMixer, a semi-supervised approach to create synthetic sequences and to estimate confidence intervals for NIPT validation and TRUST to estimate the reliability of NIPT results based on confidence intervals found in this study. We retrospectively validated these new tools on 2 cohorts for a total of 1439 samples with 31 confirmed aneuploidies. Through the analysis of the interrelationship between ff, sd and chromosomal aberration detection, we demonstrate that these parameters are profoundly connected and cannot be considered independently. Our tools take in account this critical relationship to improve NIPT reliability and facilitate cross laboratory standardization of this screening test.