Non-invasive prenatal aneuploidy testing: technologies and clinical implications

Chromosomal aneuploidies are defined as an abnormal number of chromosomes and may involve the autosomal or sex chromosomes. The majority of chromosomal aneuploidies are non-viable, leading to early miscarriage.¹ However, a subset may survive to the newborn period and beyond, including Trisomy 21 (Down syndrome), Trisomy 18 (Edwards syndrome), and Trisomy 13 (Patau syndrome). Together, these occur in approximately 1 in 450 live births.^2,3 When including sex chromosome aneuploidies, such as Monosomy X (Turner syndrome), this increases to approximately 1 in 250 live births.^2,3 Overall, Trisomy 21 is the most prevalent at-birth aneuploidy, and the most common congenital cause of mental retardation.^2-4 Other aneuploidies, including Trisomies 13 and 18, are associated with significant clinical morbidity and a high neonatal mortality rate. Thus, identification of such fetuses early in pregnancy would provide mothers/parents with sufficient time to consider reproductive options. Currently, the standard of care for pregnant women in developed countries involves discussion of the various prenatal diagnosis options, including non-invasive screening and invasive diagnostic methods.⁵ The current challenge is to design a non-invasive, highly accurate test. Recently available non-invasive prenatal testing (NIPT) approaches based on analysis of cell-free DNA (cfDNA) in maternal circulation hold the promise to reach this goal.

Traditional non-invasive screening methods

Traditional non-invasive prenatal screening for autosomal aneuploidies involves screening via a combination of ultrasound and serial detection of maternal serum markers in the first and second trimesters, with follow-up diagnosis by invasive procedures such as amniocentesis or chorionic villus sampling (CVS). Although designed to detect Trisomy 21, this integrated approach also detects Trisomies 13 and 18, and increased nuchal translucency as well as cystic hygroma and other indicators are associated with certain sex chromosome aneuploidies. However, these approaches have false-negative rates from 12% to 23%.^5-21 Additionally, detection rates range from only 75% to 96% (depending on the screening approach utilized) and are accompanied by false-positive rates ranging from 1.9% to 5.2%.^5-21 Importantly, positive screen results require a confirmatory invasive follow-up procedure.

Although the diagnostic accuracy of karyotyping cultured cells obtained by invasive procedures ranges from 97.5% to 99.8%,^22-26 invasive testing also carries up to a 1 in 300 risk of procedural-related miscarriage.^27-29 This, coupled with the high false-positive rates of traditional non-invasive screening methods, inevitably results in lost normal/unaffected pregnancies. Conversely, the high false-negative rates mean many affected pregnancies go undetected. There is therefore a clear need for an accurate, safe fetal genetic test that can be performed early in pregnancy.

Paradigm-shifting advances

Fetal cell-free DNA in maternal circulation.The discovery of fetal cfDNA in maternal circulation during pregnancy raised the possibility of new methods for non-invasive detection of fetal chromosomal abnormalities.^30,31 Fetal cfDNA is thought to be released by placental cells undergoing apoptosis, has been detected as early as 5 to 7 weeks’ gestation, and is cleared from maternal circulation within hours.³² Fetal cfDNA is heavily diluted with maternal cfDNA, comprising on average 10% to15% of the total cfDNA fraction, though there is substantial sample-to-sample variation.^33,34 The overall amount of fetal cfDNA is small (35-38 Thus, reliable detection of fetal chromosomal copy number based on cfDNA analysis requires polymerase chain reaction (PCR) amplification and analysis of the full (maternal + fetal) cfDNA complement.

Despite these technical issues, there now are numerous publications reporting the use of cfDNA for non-invasive prenatal testing (NIPT) for fetal chromosomal aneuploidies.^34,39-53 All approaches involve the analysis of the fetal and maternal cfDNA mixture isolated from maternal blood without isolating the fetal cfDNA. Although the precise technologies vary, all rely on cfDNA amplification followed by high-throughput DNA sequencing, coupled with sophisticated data analysis, to detect abnormal amounts of chromosome-specific fetal cfDNA in affected pregnancies. Thus, the discovery of fetal cfDNA required concurrent technological advances in DNA sequencing and post-hoc bioinformatics analysis to allow for development of non-invasive prenatal detection of fetal chromosomal aneuploidies.

Advances in DNA sequencing technologies. All commercial NIPT methods employ “next generation” sequencing (NGS), or sequencing-by-synthesis. These “wash-and-scan” methods flood reagents such as labeled nucleotides over anchored DNA templates, wash out excess reagent, scan to identify incorporated bases, and treat newly incorporated bases to prepare for another incorporation round.⁵⁴ Reactions can be prepared by massively parallel anchoring of numerous DNA molecules, dramatically increasing the number of DNA molecules that can be sequenced and, consequently, the amount of information produced, when compared to “first-generation” Sanger sequencing methods.^54,55 NGS approaches require amplification of the original sample and cannot produce the same read-length that first-generation sequencing generates,^54,55 generally sacrificing read-length for throughput. However, the shorter read-lengths are sufficient for accurate mapping of cfDNA-generated sequence reads to chromosomes-of-origin. Moreover, the massively parallel approach used by NGS allows coverage of the entire genome or, for targeted approaches, specific regions of the genome, with as high depth-of-coverage as needed. This generates sufficient data points to simultaneously identify fetal copy number at multiple chromosomes using cfDNA.

Next-generation sequencing approaches to NIPT: quantitative “counting” methods

Massively parallel shotgun sequencing (MPSS). MPSS is an NGS-based technique that generates DNA sequence reads from all chromosomes non-specifically. This allows for tens of millions of short DNA fragments (typically 25 to 36 base pairs long) to be sequenced rapidly and simultaneously in a single run. After an initial amplification step and sequencing the fetal and maternal cfDNA mixture, the chromosomal origin of each DNA fragment is obtained by comparison of the sequence data from each fragment to the human genome sequence. The number of reads mapping to the chromosome(s)-of-interest are then compared to the number of reads mapping to one or more presumably euploid reference chromosome(s). Since a trisomic fetus has 50% more genetic material originating from the extra chromosome-of-interest, this increases the proportion of DNA from that chromosome observed in the cfDNA. Specifically, if the ratio of the number of sequence reads from a chromosome-of-interest to the number of sequence reads from the reference chromosome(s) exceeds a predetermined threshold, fetal trisomy is inferred and is reported as positive or high-risk for trisomy for that chromosome. This approach is referred to as “counting.”

Since counting methods detect quantitative differences in the amount of fetal cfDNA present, and since fetal cfDNA comprises a small proportion of the total cfDNA, differences due to fetal trisomy are incremental. Importantly, these methods do not distinguish maternal from fetal cfDNA. Thus, the ability to detect increased chromosomal dosage resulting from fetal trisomy is directly related to the fetal cfDNA fraction in maternal circulation. At lower fetal fractions, the increase becomes marginal, and amplification efficiency variation between chromosomes becomes significant. This is particularly important at early gestational ages, as fetal fractions rise with increasing gestational age (although there is significant individual-to-individual variation), and in women with high BMI, as fetal fractions are inversely proportional to weight.^39,40,56 To distinguish these minor differences with high confidence requires a large number of reads; because MPSS sequences all chromosomes, approximately 6.3 million uniquely-mapped reads from the entire genome are required to ensure sufficient chromosome 21 counts for accurate copy number calls.^{41,43,46,49,57} Additionally, as only approximately 25% of MPSS-generated reads are uniquely mapped, approximately 25 million raw sequencing reads are required per sample to generate sufficient data for accurate analysis.⁴² This is especially important if other chromosomes (13, 18, X, and Y) are considered in the analysis. Thus, this approach represents enormous redundancy considering that the clinically-significant chromosomes represent only ~14% of the genome.

Counting methods are subject to variation in the amplification efficiency of individual chromosomes, which is thought to be linked to guanosine-cytosine (GC) base content.^39,43 This may alter the ratio of reads from the chromosome-of-interest to the reference chromosome(s), thus impacting identification of quantitative differences in sequence read number that would indicate fetal aneuploidy. Clinically, this translates to differences in the accuracy of fetal aneuploidy detection at different chromosomes. Indeed, sensitivities are the highest for Trisomy 21 (98.6% to 100%) and Trisomy 18 (97.4% to100%).^{34,40,42,44,45,47,49,50,51} Chromosomes 13 and X, however, amplify with greater variability than chromosomes 21 and 18, consequently demonstrating lower sensitivities: 80% to 91.7% for Trisomy 13 and 91.7% to 94.4% for Monosomy X.^{40,44,45,51,58} Bioinformatic GC bias correction has improved sensitivity and specificity somewhat when detecting Trisomy 13 and Trisomy 18.⁴⁶ However, GC correction has not been reported to improve sex chromosome aneuploidy detection.

Targeted sequencing. Targeted sequencing differs from MPSS by selectively amplifying and sequencing specific genomic regions-of-interest instead of random genomic regions from all chromosomes. Thus, nearly all sequences are useful in assigning fetal chromosomal copy number, significantly reducing the total number of analyzed reads and increasing efficiency.⁴⁷ Selective sequencing allows for focused analysis of clinically important chromosomes, including chromosomes 13, 18, 21, X, and Y. Identification of fetal aneuploidies from targeted cfDNA sequencing can be achieved either by quantitative counting or by genotype analysis of targeted single-nucleotide polymorphisms (SNPs). Targeted sequencing followed by counting is subject to the same limitations as MPSS-based methods. Indeed, data from this approach shows similar sensitivities and specificities to those reported from MPSS-based approaches, with the highest sensitivity reported for Trisomy 21 detection (100%), followed by Trisomy 18 (98%), and Trisomy 13 (80%).^34,48

Despite the differences in amplification methods, all counting-based NGS methods use various bioinformatics and statistical methods to identify fetal chromosomal copy number. A common approach among some of these post-hoc bioinformatics statistical algorithms is the utilization of a single-hypothesis rejection approach. This method identifies cut-offs based on previously analyzed cohorts, detecting aneuploidies in samples that fall outside these predetermined cut-offs. Methods that do not utilize SNPs cannot include the same cohort of internal sample metrics meant to identify samples with parameters indicative of a poor quality result, potentially resulting in missed calls. This is important at lower-to-intermediate fetal cfDNA fractions. Indeed, in one study reporting an overall 98.6% Trisomy 21 detection rate, isolated analysis of samples from 4% to 8% fetal fraction demonstrated a detection rate of only 75%.⁴⁰ Also, commercially available cfDNA-based NIPT tests that utilize counting methodologies typically do not routinely report X and Y chromosome copy number, but will report sex chromosome anomalies when detected. Reported “no-call” rates for counting methods specifically excluded Monosomy X from the analysis, resulting in no-call rates from 0.8% to 5.8%;^34,40,42,44 inclusion of Monosomy X increased this to >15%.⁴⁴ More recently, inclusion of the major sex chromosome aneuploidies (45,X; 47,XXX; 47,XXY; 47,XYY) resulted in an overall no-call rate of 5%.⁵⁸ While the incidence of false positives is estimated to be less than 1%, false-positive results have been reported for all counting methodologies.^{40,44,45,48,52,58-61}

SNP sequencing approaches to cell-free DNA: genotyping

The inclusion of genotypic information, generally SNPs, allows for a more complex and nuanced cfDNA analysis, generating significantly more information than next generation methods that consider only the number of reads to identify fetal chromosomal copy number. SNP-based sequencing methods thus employ a more qualitative approach that allows for the identification of the specific maternal and fetal cfDNA contribution to the sequence reads. In addition to determining copy number, the method can also reconstruct haplotypes and potentially identify abnormalities that escape detection using counting methods, such as triploidy and uniparental disomy. Moreover, they allow the use of sophisticated data models that can flag samples that have insufficient data to generate an accurate result, and as such should be repeated.  To date, two described approaches incorporate genotype information:

Allele ratios. The first genotypic approach amplifies and sequences SNPs, counting the number of observed maternal and fetal alleles and generating an allele ratio between a chromosome-of-interest and reference chromosome to determine copy number.⁶² This method is similar to the counting methods in that it identifies samples as aneuploid when the allele ratio falls beyond an established threshold. The requirement for a reference chromosome also means this approach is incapable of detecting triploidy, and as this study only focused on chromosome 21, it is not clear whether this method will accurately detect copy number imbalances at other chromosomes. This method has not yet been developed commercially or validated in a clinical trial.

Genotype analysis with maximum likelihood estimation. The second approach uses targeted amplification of SNPs followed by NGS and sophisticated informatics analysis to identify fetal chromosomal copy number.⁵¹ This method differs from the targeted sequencing approach in that it specifically targets SNPs instead of non-polymorphic regions and uses a genotype-based analytic method rather than a counting approach to detect fetal aneuploidy. The method employs a massively multiplexed PCR amplification targeting 19,488 SNPs in a single reaction—at least two orders of magnitude greater than other reports of multiplexed PCRs.⁴²

By measuring polymorphic loci, this approach extracts multiple pieces of information (including the number and identity of each allele) from each sequence read. It incorporates allelic information from the mother (and from the father, if available) to model a set of hypotheses that represent the different possible fetal genotypes (for example, monosomy, disomy, or trisomy), and which take into account different genetic inheritance patterns and crossover locations for every possible copy number count. Bayesian statistics then assign a probability to each hypothesis, and a maximum likelihood estimation analysis selects the most likely hypothesis and calculates the probability of that hypothesis being correct.⁵¹ This unique approach allows the method to incorporate certain quality control metrics that flag questionable samples which would likely return incorrect calls using counting methods. This reduces the number of missed calls; to date, no false-positive results have been reported in studies utilizing this specific method.⁶³ The probability generated by the informatics approach is used to calculate a personalized risk score for each chromosome in each sample.

Since the method analyzes the relative amount of alleles at polymorphic loci and does not utilize a reference chromosome, it is not subject to issues with amplification variation. Thus, it is expected to have consistent sensitivities across all regions interrogated; indeed, clinical data indicates sensitivities of >99% for Trisomy 21, Trisomy 18, and Trisomy 13.^51,63 It is also the only method that is capable of detecting—and has successfully reported detection of—triploidy.⁵³  The commercially available SNP NIPT test based on this methodology also routinely reports copy number for the X and Y chromosomes. Overall, this method reports an overall no-call rate of <6% for copy number calling at all five chromosomes implicated in at-birth abnormalities (13, 18, 21, X, and Y).^53,63

Clinical implementation

There is widespread agreement that these tests are not yet ready to replace invasive diagnostic procedures. This is partly because they currently detect only a subset of the chromosomal abnormalities that are uncovered using invasive procedures. Additionally, they have largely been validated in high-risk populations. Indeed, ACOG recommends testing for high-risk women, stating that more research is required to determine how these tests perform in low-risk populations.⁶⁴ Perhaps most significantly, the effects of mosaicism (fetal or placental) or other events such as trisomy rescue are unknown, and discordant results have already been reported.⁶⁵

Conclusion

Biochemical marker-based and ultrasound-based non-invasive fetal aneuploidy screening tests, although safe, have poor accuracy with high false-positive and false-negative rates.^{5-16,18-21,66} Indeed, about one of every six Trisomy 21 pregnancies will go undetected by the current non-invasive serum screening/ultrasound methodologies. Additionally, >95% of pregnant women designated “high risk” by these screens actually carry a healthy baby. This leads to unnecessary anxiety and miscarriage risk from follow-up invasive procedures. Non-invasive prenatal testing via analysis of cfDNA isolated from maternal plasma can significantly increase detection rates while decreasing false positives and false negatives. The accuracy of NIPT methods depends on the technology used and, for counting methods, on the fetal cfDNA fraction. Importantly, NIPT has not been fully validated in low-risk populations of pregnant women; thus, these methods are not currently recommended as a general screen for all pregnant women.

For NIPT to replace conventional cytogenetic analysis following CVS or amniocentesis, it must match the diagnostic accuracy and scope of detected anomalies. The diagnostic scope of traditional prenatal cytogenetic analysis has recently been extended to include detection of microdeletions and microduplications using new genomic technologies like microarray analysis. The recently completed NICHD Multicenter Prenatal Microarray Study indicated that 1.7% of routine low-risk cases and 6% of cases referred for structural ultrasound abnormalities had a clinically significant copy number change that was not detected by routine cytogenetic analysis.⁶⁶ This suggests that submicroscopic imbalances are more prevalent than Trisomy 21. Current efforts in NIPT are focused on expanding the diagnostic scope to include microdeletions. While it is not clear when such tests may be clinically available, the recent proof-of-principle study demonstrating their feasibility indicates that they are not far off.⁶⁷ The confounding effect of placental mosaicism will always hamper diagnostic accuracy, irrespective of the scope of assessed anomalies. The accuracy ceiling is therefore expected to match that observed from CVS studies, and will always be defined by mosaicism.

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