Megan P. Hall

Single-nucleotide polymorphism-based noninvasive prenatal screening in a high-risk and low-risk cohort.

OBJECTIVE: To estimate performance of a single-nucleotide polymorphism–based noninvasive prenatal screen for fetal aneuploidy in high-risk and low-risk populations on single venopuncture. METHODS: One thousand sixty-four maternal blood samples from 7 weeks of gestation and beyond were included; 1,051 were within specifications and 518 (49.3%) were low risk. Cell-free DNA was amplified, sequenced, and analyzed using the Next-generation Aneuploidy Test Using SNPs algorithm. Samples were called as trisomies 21, 18, 13, or monosomy X, or euploid, and male or female. RESULTS: Nine hundred sixty-six samples (91.9%) successfully generated a cell-free DNA result. Among these, sensitivity was 100% for trisomy 21 (58/58, confidence interval [CI] 93.8–100%), trisomy 13 (12/12, CI 73.5–100%), and fetal sex (358/358 female, CI 99.0–100%; 418/418 male, CI 99.1–100%), 96.0% for trisomy 18 (24/25, CI 79.7–99.9%), and 90% for monosomy X (9/10, CI 55.5–99.8%). Specificity for trisomies 21 and 13 was 100% (905/905, CI 99.6–100%; and 953/953, CI 99.6–100%, respectively) and for trisomy 18 and monosomy X was 99.9% (938/939, CI 99.4–100%; and 953/954, CI 99.4–100%, respectively). However, 16% (20/125) of aneuploid samples did not return a result; 50% (10/20) had a fetal fraction below the 1.5th percentile of euploid pregnancies. Aneuploidy rate was significantly higher in these samples (P<.001, odds ratio 9.2, CI 4.4–19.0). Sensitivity and specificity did not differ in low-risk and high-risk populations. CONCLUSIONS: This noninvasive prenatal screen performed with high sensitivity and specificity in high-risk and low-risk cohorts. Aneuploid samples were significantly more likely to not return a result; the number of aneuploidy samples was especially increased among samples with low fetal fraction. This underscores the importance of redraws or, in rare cases, invasive procedures based on low fetal fraction. LEVEL OF EVIDENCE: II

SNP-based non-invasive prenatal testing detects sex chromosome aneuploidies with high accuracy

This study aimed to develop a single‐nucleotide polymorphism‐based and informatics‐based non‐invasive prenatal test that detects sex chromosome aneuploidies early in pregnancy.

Detection of triploid, molar, and vanishing twin pregnancies by a single-nucleotide polymorphism–based noninvasive prenatal test

OBJECTIVE We sought to determine the ability of single-nucleotide polymorphism-based noninvasive prenatal testing (NIPT) to identify triploid, unrecognized twin, and vanishing twin pregnancies. STUDY DESIGN The study included 30,795 consecutive reported clinical cases received for NIPT for fetal whole-chromosome aneuploidies; known multiple gestations were excluded. Cell-free DNA was isolated from maternal blood samples, amplified via 19,488-plex polymerase chain reaction, and sequenced. Sequencing results were analyzed to determine fetal chromosome copy number and to identify the presence of additional fetal haplotypes. RESULTS Additional fetal haplotypes, indicative of fetal triploidy, vanishing twin, or undetected twin pregnancy, were identified in 130 (0.42%) cases. Clinical confirmation (karyotype for singleton pregnancies, ultrasound for multifetal pregnancies) was available for 58.5% (76/130) of cases. Of the 76 cases with confirmation, 42.1% were vanishing twin, 48.7% were viable twin, 5.3% were diandric triploids, and 3.9% were nontriploid pregnancies that lacked evidence of co-twin demise. One pregnancy had other indications suggesting triploidy but lacked karyotype confirmation. Of the 5 vanishing twin cases with a known date of demise, 100% of losses occurred in the first trimester; up to 8 weeks elapsed between loss and detection by NIPT. CONCLUSION This single-nucleotide polymorphism-based NIPT successfully identified vanished twin, previously unrecognized twin, and triploid pregnancies. As vanishing twins are more likely to be aneuploid, and undetected residual cell-free DNA could bias NIPT results, the ability of this method to identify additional fetal haplotypes is expected to result in fewer false-positive calls and prevent incorrect fetal sex calls.

Genomic imbalance in products of conception: single-nucleotide polymorphism chromosomal microarray analysis.

OBJECTIVE: To report the full cohort of identifiable anomalies, regardless of known clinical significance, in a large-scale cohort of postmiscarriage products-of-conception samples analyzed using a high-resolution single-nucleotide polymorphism (SNP)–based microarray platform. High-resolution chromosomal microarray analysis allows for the identification of visible and submicroscopic cytogenomic imbalances; the specific use of SNPs permits detection of maternal cell contamination, triploidy, and uniparental disomy. METHODS: Miscarriage specimens were sent to a single laboratory for cytogenomic analysis. Chromosomal microarray analysis was performed using a SNP-based genotyping microarray platform. Results were evaluated at the cytogenetic and microscopic (greater than 10 Mb) and submicroscopic (less than 10 Mb) levels. Maternal cell contamination was assessed using information derived from fetal and maternal SNPs. RESULTS: Results were obtained on 2,389 of 2,392 specimens (99.9%) that were less than 20 weeks of gestation. Maternal cell contamination was identified in 528 (22.0%) specimens. The remaining 1,861 specimens were considered to be of true fetal origin. Of these, 1,106 (59.4%) showed classical cytogenetic abnormalities: aneuploidy accounted for 945 (85.4%), triploidy for 114 (10.3%), and structural anomalies or tetraploidy for the remaining 47 (4.2%). Of the 755 (40.6%) cases considered normal at the cytogenetic level, SNP chromosomal microarray analysis revealed a clinically significant copy number change or whole-genome uniparental disomy in 12 (1.6%) and three (0.4%) cases, respectively. CONCLUSION: Chromosomal microarray analysis of products-of-conception specimens yields a high diagnostic return. Using SNPs extends the scope of detectable genomic abnormalities and facilitates reporting “true” fetal results. This supports the use of SNP chromosomal microarray analysis for cytogenomic evaluation of miscarriage specimens when clinically indicated. LEVEL OF EVIDENCE: III

Non-Invasive Prenatal Detection of Trisomy 13 Using a Single Nucleotide Polymorphism- and Informatics-Based Approach

Purpose To determine how a single nucleotide polymorphism (SNP)- and informatics-based non-invasive prenatal aneuploidy test performs in detecting trisomy 13. Methods Seventeen trisomy 13 and 51 age-matched euploid samples, randomly selected from a larger cohort, were analyzed. Cell-free DNA was isolated from maternal plasma, amplified in a single multiplex polymerase chain reaction assay that interrogated 19,488 SNPs covering chromosomes 13, 18, 21, X, and Y, and sequenced. Analysis and copy number identification involved a Bayesian-based maximum likelihood statistical method that generated chromosome- and sample-specific calculated accuracies. Results Of the samples that passed a stringent DNA quality threshold (94.1%), the algorithm correctly identified 15/15 trisomy 13 and 49/49 euploid samples, for 320/320 correct copy number calls. Conclusions This informatics- and SNP-based method accurately detects trisomy 13-affected fetuses non-invasively and with high calculated accuracy.

Incidence of X and Y Chromosomal Aneuploidy in a Large Child Bearing Population.

Background X&Y chromosomal aneuploidies are among the most common human whole-chromosomal copy number changes, but the population-based incidence and prevalence in the child-bearing population is unclear. Methods This retrospective analysis of prospectively collected data leveraged a routine non-invasive prenatal test (NIPT) using parental genotyping to estimate the population-based incidence of X&Y chromosome variations in this population referred for NIPT (generally due to advanced maternal age). Results From 141,916 women and 29,336 men, 119 X&Y chromosomal abnormalities (prevalence: 1 in 1,439) were identified. Maternal findings include: 43 cases of 45,X (40 mosaic); 30 cases of 47,XXX (12 mosaic); 3 cases of 46,XX uniparental disomy; 2 cases of 46,XY/46,XX; 23 cases of mosaicism of unknown type; 2 cases of 47,XX,i(X)(q10). Paternal findings include: 2 cases of 47,XXY (1 mosaic); 10 cases of 47,XYY (1 mosaic); 4 partial Y deletions. Conclusions Single chromosome aneuploidy was present in one of every 1,439 individuals considered in this study, showing 47,XXX; 47,XX,i(X)(q10); 47,XYY; 47,XXY, partial Y deletions, and a high level of mosaicism for 45,X. This expands significantly our understanding of X&Y chromosomal variations and fertility issues, and is critical for families and adults affected by these disorders. This current and extensive information on fertility will be beneficial for genetic counseling on prenatal diagnoses as well as for newly diagnosed postnatal cases.

Letter to the editor by megan Hall.

Sir, We read with interest the recent review by Santiago Munne entitled, “Preimplantation Genetic Diagnosis for Aneuploidy and Translocations Using Array Comparative Genomic Hybridization” (1). As part of the review of array comparative genome hybridization (aCGH), the author provides additional information on other 24-chromosome preimplantation genetic diagnosis/screening (PGD/PGS) techniques. As a commercial lab that offers single nucleotide polymorphism (SNP) microarray analysis for PGD/PGS, we would like to comment on a few claims that were made within this article regarding SNP microarrays. (Table 1) in the article summarizes the differences between 24-chromosome PGD/PGS techniques. This table contains a number of errors regarding SNP microarray detection capabilities as it groups the different approaches of SNP microarray analysis under a single heading of “SNPs”. SNP technologies that employ a combination of qualitative and quantitative data analysis detect far more abnormalities than those that use just one type of analysis. First, it is not accurate to say that “SNPs” cannot detect tetraploidy. SNP microarrays using qualitative/quantitative analysis can detect some forms of tetraploidy; this method will not detect 2:2 tetraploidy, though is indeed capable of detecting 3:1 tetraploidy. Second, SNP microarray technologies that use a qualitative/quantitative approach can detect meiotic and mitotic duplications without recombination (3); the table incorrectly states that SNP microarray approaches cannot detect these abnormalities. Lastly, it is an exaggeration to state that aCGH approaches are able to detect all unbalanced translocations and SNP microarray approaches can only detect some; both approaches are equally limited in their inability to detect very small deletions and duplications (both have a similar threshold in that they typically detect DNA segments greater than 6Mb). We also question a number of statements the author makes about aCGH and SNP microarray within the body of the paper. The author acknowledges that aCGH cannot detect haploidy or polyploidy but claims that this is a small limitation, as the majority of the haploid or polyploid embryos tested (7.7%) had additional detectable abnormalities; however, these additional abnormalities are not named. It is our experience that other abnormalities are not typically found with 69,XXX. Next, the author credits SNP microarray with the ability to detect uniparental disomy (UPD) but then goes on to use the incidence of UPD of chromosome 15 (UPD-15) to say that UPD in general is a very rare event. Chromosome15 is only one of six imprinted chromosomes (6, 7, 11, 14, 15, and 16), which if UPD is present, could lead to the birth of a baby with a severe genetic syndrome (4). We feel that detection of UPD prior to embryo transfer decisions is highly beneficial to, and desired by, couples undergoing IVF with PGD/PGS. Furthermore, in regards to PGD/PGS for reciprocal and Robertsonian translocations, we would like to clarify that not all SNP microarray approaches can differentiate between normal and balanced (carrier) embryos. Last, the author correctly points out that SNP microarray approaches require parental DNA analysis prior to the embryo sample analysis. However, our lab does not charge a cancellation fee for this parental analysis when IVF cycles are cancelled, thus patients do not pay for unnecessary parental testing. We appreciate that the author mentions SNP microarray analysis that employs a qualitative/quantitative approach will avoid many of the limitations inherent to the purely qualitative or quantitative approaches. However, the review references our article (Johnson DS et al. [2], reference 77 in the original paper) as an aCGH technology, when in fact we utilize a SNP-based approach with bioinformatics analysis. Natera’s PGD/PGS Parental SupportTM method utilizes SNP measurements of parental and embryonic samples, giving us the ability to analyze both qualitative and quantitative data from each chromosome to determine the embryonic chromosomal copy number. In addition, the Parental SupportTM method utilizes a much more sophisticated bioinformatics-based analysis (2) than the combined approach described in the article. New methods should always be validated against more established ones, but given the errors rates reported with FISH PGD/PGS (as stated by the author at the beginning of the paper), we strongly disagree that validation studies using FISH for reanalysis should be considered the gold standard (2, 5). Natera thus supports the creation of an oversight body to administer proficiency testing for laboratories offering 24-chromosome PGD/PGS. Sincerely,