Droplet‑based digital PCR for non‑invasive prenatal genetic diagnosis of α and β‑thalassemia
- Authors:
- Published online on: August 9, 2021 https://doi.org/10.3892/br.2021.1458
- Article Number: 82
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Copyright: © Sawakwongpra et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
Introduction
Thalassemia is an autosomal recessive disease that is caused by the reduction in hemoglobin chain synthesis. It is estimated that thalassemia affects 17% of over 330,000 newborns worldwide each year (1). The two major types of thalassemia are α- and β-thalassemia. α-thalassemia is caused by the loss of one or both of the α-globin genes (2). The Southeast Asian deletion (SEA) variant is a large deletion of the α-globin gene region, and is the most common cause of α-thalassemia in the Asian population. Couples carrying the SEA deletion do not show symptoms, but will have a 25% chance of conceiving a baby with Hb Bart's hydrops fetalis and experiencing toxemia during pregnancy (3). β-thalassemia is caused by mutations in β-globin genes, which lead to reduced β-globin chain synthesis (4). Children born with β-thalassemia may show symptoms of anemia and other complications throughout their lives (5). Thailand has a high (30-50%) prevalence of α- and β-thalassemia (6), particularly in the northern and northeastern regions of the country (7). As thalassemia treatments are costly and time-consuming, the most effective means of limiting thalassemia incidence is to screen for the mutant genes before birth. Towards this goal, prenatal screening for thalassemia is becoming a part of primary health services in the majority of developed countries, particularly in Asia (8). Nonetheless, traditional prenatal diagnoses, such as chorionic villi sampling and amniocentesis, are invasive and may cause infection and miscarriage (9,10).
The discovery of cell-free fetal DNA (11), which is released from placental tissue into the maternal bloodstream, has enabled the development of non-invasive prenatal diagnosis (NIPD) for detecting disease-causing mutations in the fetus (12,13). In recent years, there has been substantial interest in developing NIPD for thalassemia. Reverse transcription-quantitative PCR (RT-qPCR) using the gap-PCR technique with primers designed to bind at the deletion breakpoints have been used to diagnose common deletions such as -a3.7, -a4.2, -THAI, -MED and -SEA (14,15). Similarly, the PCR-based techniques were also applied to diagnose Hb Bart's hydrops fetalis (16) and other forms of α-thalassemia (17-19). Next-generation sequencing (NGS) is a powerful technique for NIPD, as it has high sensitivity and enables the detection of low abundance cell free-fetal DNA (20-23). Several studies have shown high accuracy of NGS-based genome-wide single-nucleotide polymorphism genotyping and targeted sequencing for diagnosing β-thalassemia (24-26). However, the high costs of NGS-based techniques make them inappropriate in routine clinical practice.
Droplet digital PCR (ddPCR) is a sensitive and quantitative PCR-based technique that can amplify a low initial amount of target DNA molecules and enumerate different PCR products using probe-specific fluorescent signals (27,28). ddPCR has been used to detect circulating tumor DNA and cell-free fetal DNA (29-31). A study on SEA deletion α-(0) thalassemia showed a promising prospect of ddPCR (32). However, it is unclear whether the fetal DNA analyzed came directly from fetal tissues or cell-free fetal DNA in the maternal bloodstream (32). Furthermore, digital PCR-based NIPD could be improved by utilizing a nucleic acid size selection technique to enrich fetal DNA molecules (33).
The present study developed ddPCR-based assays for detecting fetal α- and β-thalassemia mutations in cell-free DNA from maternal plasma. The assays were evaluated on 22 pregnant women carrying SEA deletions, 16 carrying HbE mutations, and 8 carrying 41/42 (-CTTT) mutations.
Materials and methods
Patient recruitment
In the present study 46 singleton pregnant women who were thalassemia carriers [22 cases with SEA deletion, 16 cases with HbE (G>A), and 8 cases with 41/42 (-CTTT)] were recruited at Radjavithi Hospital, Bangkok, Thailand between March and July 2018 with approval from the Institutional Review Board of the hospital. Peripheral blood samples (10 ml) were collected from each participant for subsequent cell-free DNA extraction and ddPCR analysis. The α- and β-thalassemia status of each parent and fetus was determined by Hb typing, complete blood count tests and genotyping by PCR from amniotic fluids. Samples were collected with the approval from the Institutional Review Board of Radjavithi Hospital, Bangkok (approval no. 59194; date of approval 17th November 2016). Written informed consent was obtained from all subjects prior to inclusion in the study. Written informed consent from the parent or legal guardian of all subjects under the age of 18 was also obtained.
Cell-free DNA extraction from blood samples
Maternal blood samples (10 ml) were placed in BCT tubes (Streck™) and centrifuged at 1,600 x g for 10 min at 4˚C. The supernatant was centrifuged again at 16,000 x g for 10 min at 4˚C. The pellet was discarded and the supernatant was stored kept at -20˚C until required for extraction. Cell-free DNA was extracted from plasma (3 ml) using a QIAamp Circulating Nucleic acid kit according to the manufacturer's protocol (Qiagen GmbH).
Amniotic fluid DNA extraction
Amniotic fluids (5 ml) were collected during weeks 15-18 of gestation and centrifuged at 16,000 x g for 10 min at 4˚C. The supernatant was discarded, the pellet was washed twice with 1X PBS (1 ml) and stored at -80˚C in a sterile tube. The extraction step was performed according to the instruction manual of the QIAamp Blood Mini kit (Qiagen GmbH).
ddPCR
A ddPCR assay was developed for determining the copy number of the SEA allele. The HEX probe was designed to bind the genomic region inside the SEA deletion (NG_000006.1:g.26264_45564del19301) (34) whereas the FAM probe was designed to bind the genomic region just outside of the SEA locus (NG_000006.1:g.26140 to 26262), which is expected to be present in both a wild type fetus and a fetus with an SEA deletion (Table SI). For detecting HbE (G>A) and 41/42 (-CTTT), a rare mutation assay with specific probes designed to target the mutant and wild type amplicons was developed (Table SI).
ddPCR experiments were performed according to the manufacturer's protocol (Bio-Rad Laboratories, Inc.) with some modifications as described here. The master mix solution was prepared from 10 µl 2X ddPCR SuperMix for probes (Bio-Rad Laboratories, Inc.), 1 µl 20X prime PCR assay (Bio-Rad Laboratories, Inc.), and either 8 µl DNA (12 µg/ml) from plasma or 1 µl DNA (20 µg/ml) from amniotic fluid. Nuclease free water was added to adjust the final volume to 20 µl. A total of 13,500-15,000 droplets per reaction were created in a DG8 cartridge with 70 µl oil using a QX200 Droplet Generator (Bio-Rad Laboratories, Inc.). Droplets (40 µl) were transferred to a 96-well PCR plate and sealed with aluminium foil using PX1 (Bio-Rad Laboratories, Inc.) for 5 sec at 180˚C. Next the plate was placed in a T100 Thermal Cycler (Bio-Rad Laboratories, Inc.). PCR reactions began with a cycle of 10 min at 95˚C, followed by 40 cycles of 30 sec at 94˚C and 1 min at 54˚C, with an enzyme deactivation step for 10 min at 98˚C. Fluorescent signals from PCR products were measured using a QX200 Droplet Reader (Bio-Rad Laboratories, Inc.) and analyzed using QuantaSoft version 1.7.4 (Bio-Rad Laboratories, Inc.). ddPCR reactions for SEA cases were performed in duplicates. ddPCR reactions for HbE and 41/42 (-CTTT) cases were performed in triplicates.
Estimation of fetal fraction
Fetal fractions were estimated as previously described (27,35). Briefly, RASSF1A and ACTB alleles in plasma samples were digested with BstU I (Vivantis Technologies) at a ratio of 1 µg DNA to 1 U of enzyme for 1 h at 60˚C. The abundance of RASSF1A and ACTB alleles before and after digestion were measured using ddPCR analyses. ACTB locus, which is always unmethylated, acts as a control of BstU I activity (36). Conversely, as only the fetal RASSF1A locus is hypermethylated, the ratio of RASSF1A positive droplets before and after BstU I digestion approximate the fractional abundance of fetal DNA content of the sample.
Copy number variation (CNV) analysis to detect SEA deletion
QuantaSoft was used to determine the number of positive and negative droplets and analyze the relative CNV of SEA deletions. The average CNV value from triplicate wells was used to classify the fetal genotype using the following equation: CNV=(concentration of SEA allele/concentration of wild-type allele) x copy number of wild type allele.
Rare mutation assay to detect HbE and 41/42 (-CTTT) mutations
QuantaSoft was used to determine the number of positive droplets, negative droplets and double-positive droplets. A previously described sequential probability ratio test (SPRT) (33) was adopted to classify fetal HbE and 41/42 (-CTTT) genotypes. Briefly, the total number of DNA molecules in each sample was calculated under the assumption that the number of positive droplets (droplets with DNA materials) followed the Poisson distribution: The probability of observing k positive droplets is (λke-λ)/k!, where λ indicates the average number of DNA molecules per a droplet. Hence, by setting k=0, the number of DNA molecules can be calculated as: -ln(fraction of negative droplets) x number of droplets.
Next, the likelihood that the fetus has a specific genotype was calculated under the assumption that the numbers of negative and positive droplets for each allele followed the Binomial distribution. For example, if the fetal genotype is a homozygous mutant, then the fraction of mutant allele would be (1+fetal fraction)/2, whereas the fraction of wild type allele would be (1-fetal fraction)/2. Then, letting N be the total number of droplets, M be the total number of DNA molecules, mt be the number of positive droplets for the mutant allele, wt be the number of positive droplets for the wild type allele, and ff be the estimated fetal fraction, the likelihood of this observation can be expressed as:
 |
Two likelihood ratio tests were performed for each sample: One between the hypotheses that the fetal genotype is homozygous mutant and heterozygous, and another between the hypotheses that the fetal genotype is wild type and heterozygous. The threshold for accepting each test was set at type I and type II errors of 5% according to the SPRT criteria: ±log [(1-0.05)/0.05], which is ~±1.27 (33,37).
Real time PCR for melting curve analysis of SEA deletion from amniocentesis
The fetal genotypes were confirmed by high-resolution melting curve analysis in 10 samples were randomly selected from singleton parents for confirmation. Total reaction volume of 20 µl contained 10 µl Precision melt supermix (Bio-Rad Laboratories, Inc.), 1 µl of each primer and 5 µl of DNA sample. The sequences of the primers were NaI forward, 5'AGAAGCTGAGTGATGGGTCCG-3' and reverse, 5'ACAAACGCCCGTCCGACTCAA-3'; and NaIII reverse 5'-TGGACTTAAGTGATCCTCCTGCCC-3',. The amplification step began at 95˚C for 3 min followed by 40 PCR cycles at 95˚C for 20 sec, 60˚C for 20 sec, and 72˚C for 20 sec. Finally, a high-resolution melting cycle from 85-95˚C at a rate of 0.1˚C per 2 sec was performed (38). Dissociation curve analysis was performed using CFX96 Manager version 1.3 (Bio-Rad Laboratories, Inc.).
Statistical analyses
The sequential probability ratio test (SPRT) technique was used to analyze ddPCR results to identify the most likely fetal genotypes (39). For analysis, 5% type I and type II error thresholds were set. Numerical calculations were performed in Microsoft Excel according to the Poisson and Binomial distribution models described above.
Results
Patient characteristics
A total of 46 couples who were at high risk of having children with thalassemia were recruited in the present study. The median age (age range) of pregnant mothers was 27 (15-39) years old. The median gestational age (range) was 18 (17-27) weeks. The median BMI (range) of participants was 21.8 (15.7-32.8). The cohort consisted of 22 (48%) couples with SEA deletion, 16 (35%) couples with an HbE (G>A) mutation, and 8 (17%) couples with an 41/42 (-CTTT) mutation.
Classification performance of fetal SEA genotype
Analysis of ddPCR fluorescent signals showed clear separations between negative and positive droplets as well as lower abundances of the SEA locus in Bart's hydrops fetalis case as would be expected (Fig. 1A and B). The complete absence of positive droplets for the SEA locus in the amniocentesis sample of the Bart's hydrops fetalis case confirmed that the designed probe was highly specific to the SEA locus (Fig. 1C and D). SEA locus copy numbers estimated from cell-free DNA samples significantly differ across wild type, heterozygous and Bart's hydrops fetalis samples (Mann Whitney U test P=0.0124 for the comparison between the wild type and heterozygous cases; P=0.000311 for the comparison between heterozygous and Bart's hydrops fetalis cases). The average copy numbers for the wild type, heterozygous and Bart's hydrops fetalis groups were 2.27, 1.38 and 0.76, respectively (Fig. 2). To ensure the high quality of ground truth fetal genotypes, high resolution melting curve analyses on selected samples was also performed and 100% concordance was obtained (Fig. S1). Most samples exhibited the expected copy numbers of the SEA locus, except for one wild type case that may have been affected by a very low (3%) fetal fraction (Table I). The optimal copy number cut-off for distinguishing affected (Bart's hydrops fetalis) from unaffected (wild type and heterozygous) fetuses was ~1.155, which yielded 95.38% sensitivity [95% confidence interval (CI): 87.29-98.74] and 91.01% specificity (95% CI: 83.25-95.37) (Fig. 3A). The area under the receiver operating characteristic (AUROC) curve was 0.98. The optimal copy number cut-off for distinguishing the presence of SEA deletion in the fetus (Bart's hydrops fetalis and heterozygous) was 1.920, which yielded 98.53% sensitivity (95% CI: 92.13-99.92) and 75% specificity (95% CI: 53.13-88.81) (Fig. 3B). The AUROC curve in this scenario was 0.96.
Amniocentesis results from high resolution melting curve analysis
Amniocentesis DNA samples were collected from 10 randomly selected singleton parents to confirm the SEA genotypes. Amongst the 10 samples, 4 were diagnosed as Bart's hydrops fetalis, 5 were from normal fetuses and 1 was from a heterozygous fetus. The median maternal age was 27 (15-36) years old. The median gestational age was 18 (17-19) weeks. Dissociation curve analysis showed that the melting temperature for the wild-type fetuses was 91.5±0.15˚C, whereas the melting temperature for Bart's hydrops fetalis was 87.8±0.02˚C. Heterozygous fetuses showed peaks at the melting temperatures of both the wild-type and Bart's hydrops fetalis as expected.
Classification performance of fetal HbE (G>A) and 41/42 (-CTTT) genotype
Cell-free DNA from maternal plasma of 16 HbE carriers and 8 41/42(-CTTT) carriers was next investigated. ddPCR was performed using probes targeting either the wild type or mutant allele. The ground truth genotypes for several samples were confirmed with high-resolution melting curve analyses (Figs. S1 and 2). ddPCR results were then analyzed based on a published sequential probability ratio test method (33). At type I and type II errors of 5%, out of 16 HbE cases, the results for 3 patients were inconclusive, and 10 out of the remaining 13 cases were correctly classified. For 41/42 (-CTTT), the results for 4 out of 8 cases were inconclusive, and 2 out of the remaining 4 cases were correctly classified (Tables II and III). It should be noted that all inconclusive results still retain the correct genotypes and may be correctly classified if more ddPCR reactions are performed.
 | Table IIIDetailed parental genotypes and droplet digital PCR test results for 41/42 (-CTTT) β thalassemia. |
Typical causes of poor ddPCR assay performances include a low fetal fraction, low amount of amplifiable DNA, and poor binding between ddPCR probes and target alleles, all of which would hinder confident determination of the fetal genotype. Although a low fetal fraction is linked to inconclusive results (Fig. 4A, lower fetal fractions among inconclusive cases; Mann-Whitney U test P=0.0173), it cannot explain misclassifications. The 12-25% fetal fractions amongst misclassified samples are high and should be adequate for NIPD applications. There is also no apparent difference in the amount of amplified DNA between correctly classified and misclassified cases (Fig. 4B). Finally, to test whether poor probe binding could explain the observed results, the coefficient of variation (CV) of the mutant-to-wild type droplet ratios from the triplicate ddPCR experiments and the percentage of positive droplets of each patient sample to the classification result were compared. The rationale here was that poor probe binding should result in a low percentage of positive droplets and a high variability across replicate experiments. This revealed a clear association between the variability of triplicate ddPCR experiments and the genotype classification accuracy (Fig. 5). Amongst the 11 samples with <15% CV, seven were correctly classified, two were misclassified, and two were inconclusive. Conversely, amongst the remaining 13 samples with 16-83% CV, only five were correctly classified, three were misclassified and five were inconclusive. The analysis also showed a borderline significant correlation between the CV of triplicate ddPCR results and the fraction of total positive droplets (Spearman Rank correlation=-0.4417 with permutation test P=0.0306).
Discussion
The growing interest in non-invasive prenatal testing has driven the development of various assays for diagnosing monogenic diseases from cell-free fetal DNA (24-26,30,31,33). One of the main challenges is the interference from high maternal DNA background that can overwhelm the signal from circulating fetal DNA fragments (40). Prior studies have focused on autosomal dominant monogenic diseases, such as achondroplasia, myotonic dystrophy and some forms of β-thalassemia, where the mutated fetal allele could be clearly distinguished from wild type maternal DNA (41-44). However, this consideration does not apply to autosomal recessive diseases and several other situations that involve maternal inherited alleles (44). Notably, the digital relative mutation dosage and SPRT methods have improved the confidence of assessment of the fetal genotype in the presence of the background maternal DNA (33,45). These techniques enabled interpretation of fetal status and detection of small allelic imbalances when the mother carries the pathologic allele.
ddPCR is a high-sensitivity and high-specificity technique that improves upon conventional PCR and has been utilized in prenatal diagnoses of thalassemia (29,46). Early studies of SEA deletion α-(0) thalassemia using RT-qPCR demonstrated high sensitivities for Bart's hydrops fetalis detection. However, these methods could not clearly distinguish between heterozygous and wild type fetuses (37,46,47). A study using the ddPCR technique on fetal genomic DNA samples provided the first accurate classification of fetal SEA genotype, suggesting that ddPCR is suitable for non-invasive prenatal diagnosis of SEA deletion (32). Nonetheless, no prior study had applied ddPCR to cell-free DNA without sample preprocessing, such as enrichment of fetal DNA by size selection, to the best of our knowledge.
The present study is the first to showcase the application of ddPCR to identify the copy number of SEA deletion in unprocessed cell-free DNA obtained from maternal plasma, thereby eliminating the need for invasive fetal DNA collection and sample preprocessing. The SEA CNV assay accurately classified 20 out of 22 samples, and detected Hb Bart's hydrops fetalis with 95% sensitivity and 91% specificity. A possible explanation for the misclassified cases may be a low fetal fraction (3% in one case) and instability of the cell-free fetal DNA in the SEA region (16). These findings demonstrate the readiness of ddPCR-based assay for NIPD of SEA deletion α-(0) thalassemia.
Although the current performances of ddPCR for HbE and 41/42 (-CTTT) point mutations still do not meet the requirements for clinical use, the results for HbE are promising. Out of 16 samples, 10 were correctly classified, and three may be correctly classified with additional ddPCR experiments, whilst three misclassifications were made. The association between inaccurate classifications and high variability amongst triplicate ddPCR experiments and a low percentage of positive droplets suggests that these errors were likely caused by poor binding between ddPCR probes and target alleles. Some remedies for this issue include designing additional probes for targeting mutated DNA molecules, pre-amplifying the sample, and performing size selection to enrich fetal DNA fragments (48,49).
The present study developed ddPCR-based assays for identifying the fetal thalassemia status from unprocessed cell-free DNA extracted from maternal plasma. Although the 20 kb deletions of the SEA region can be reliably detected, the detection accuracies for HbE and 41/42 (-CTTT) point mutations were too low for recommendation of this technique for clinical use. The critical limitation of this work is the small number of HbE and 41/42 (-CTTT) samples, especially the complete lack of cases with a homozygous mutant allele. Further studies with a larger sample size and additional ddPCR probe designs are required to improve and validate the utility of these assays.
Supplementary Material
Dissociation curve analysis of SEA deletion. (A) The wild type fetus melting temperature peak was 91.5±0.15˚C. (B) The Bart's hydrops fetalis melting temperature peak was 87.8±0.02˚C. (C) Heterozygous fetus shows the melting temperature of both types.
Real time PCR graph showing the decrease in fluorescence signal of the different genotypes Graph of the fluorescence signal for the (A) wild type, (B) Bart's hydrops fetalis and (C) Heterozygous genotypes. RFU, relative fluorescence unit.
Oligonucleotide sequences of the digital droplet PCR probes and the PCR conditions used.
Acknowledgements
Not applicable.
Funding
This study was supported by funding from Radjavithi Hospital (grant no. 59194) and the Research Fund of Chulabhorn International College of Medicine, Thammasat University.
Availability of data and materials
The datasets used and/or analyzed during the present study are available from the corresponding author on reasonable request.
Authors' contributions
SPO, SJ managed the project. SPO, WQ, SC and KS conceived and designed the study. SJ recruited patients and collected data. WN, SPR and KT collected samples and extracted cell-free DNA. KS performed the experiments. SS and KS analyzed the data and interpreted the results. KS, SPO and SS wrote and revised the manuscript. SS, SJ and SPO supervised the project. All authors provided critical comments and contributed to the revision of the manuscript. KS and SPO confirm the authenticity of all the raw data.
Ethics approval and consent to participate
Samples were collected with the approval from the Institutional Review Board of Radjavithi Hospital, Bangkok (approval no. 59194 date of approval, 17th November 2016). Written informed consent was obtained from all subjects prior to inclusion in the study. Written informed consent from the parents or legal guardians of all subjects under the age of 18 was also obtained.
Patient consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
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