Introduction: Prenatal diagnosis of thalassemia disease was usually based on invasive technique. Noninvasive diagnosis using cell-free fetal DNA (cff-DNA) was described with various laboratory techniques. The aim of this study was to identify the performance of dPCR for analyzing cff-DNA in maternal plasma to diagnose fetal beta-thalassemia diseases. Methods: Thirty-five couples at risk of fetal beta-thalassemia disease caused by four common mutations of HBB were enrolled at 12–18 weeks. The dPCR assay was designed to detect and quantify paternally inherited beta-thalassemia allele (PIB) and maternally inherited beta-thalassemia allele (MIB) from cff-DNA in maternal plasma. Results: Of 29 couples with different paternal/maternal mutations, all cases who inherited paternal mutation had detectable PIB-M. The MIB-mutant/wild-type (MIB-M/MIB-N) ratio in the mothers whose fetuses did not inherit maternal mutation was 0.87 ± 0.07 which was significantly lower than that of the mothers whose fetuses inherited maternal mutation, 1.01 ± 0.05. The sensitivity and specificity of MIB-M/MIB-N ratio >0.95 in predicting fetus inheriting maternal mutation were 100 and 92.3%, respectively. In four couples with same paternal/maternal mutation, IB-M/IB-N ratio of >0.95 correctly predicted the presence of an inheritance of at least one beta-thalassemia allele. In two couples with paternal Hb E/beta-thalassemia, the presence of PIB-M and the MIB-M/MIB-N ratio of >0.95 correctly predicted the presence of paternal/maternal mutations, respectively. Conclusions: The method of analyzing cff-DNA in maternal plasma by dPCR is efficient for prenatal diagnosis of beta-thalassemia.
What does this study add to current knowledge?
dPCR can detect mutations presenting in a small amount and overcome the maternal DNA interference.
Based on relative mutation dosage, dPCR is an effective method with high sensitivity and specificity in predicting fetus inheriting maternal mutation.
What are the main clinical implications?
Invasive prenatal diagnosis for fetal beta-thalassemia can be avoided.
An algorithm using dPCR of cell-free fetal DNA (cff-DNA) as a noninvasive prenatal diagnosis of beta-thalassemia is proposed for applying in clinical practice.
Prenatal diagnosis for genetic diseases is conventionally based on molecular or cytogenetic analysis of fetal cells from chorionic villi, amniotic fluid, or fetal blood obtained from invasive obstetric procedures. The procedures are associated with a significant risk of fetal loss [1‒3]. The discovery of detectable cell-free fetal DNA (cff-DNA) in maternal plasma has made possible a noninvasive approach to prenatal diagnosis .
Analysis of cff-DNA in maternal plasma has been used successfully in many genetic conditions. The early works involved detection of paternally inherited alleles, such as Y chromosome-specific sequence for exclusion of X-linked inherited diseases [5‒7], and detection of Rh (D) antigen to predict a risk for fetal alloimmune hemolytic anemia [8, 9].
Several studies described the noninvasive prenatal diagnosis in thalassemia disease [10‒25]. In case that the parents are carriers of thalassemia with different mutations, the presence of paternal mutation in maternal plasma indicates that the fetus carries the mutation and either is a carrier of the disease or, when also inherits the maternal mutation, has a disease. Methods for the detection include quantitative real-time polymerase chain reaction (qPCR) [10, 13, 16, 22], PCR and MassARRAY assays [12, 15], droplet digital PCR (dPCR) [21, 23], and next-generation sequencing (NGS) [18, 19, 24]. The mass spectrometry has a higher sensitivity when comparing to qPCR and is a preferable method. NGS is a new method with high sensitivity for noninvasive prenatal diagnosis of thalassemia [18, 19, 24]. However, the equipment is not widely available and is costly.
Sirichotiyakul et al.  described a prenatal diagnosis of homozygous Southeast Asian deletional alpha zero-thalassemia by comparing the difference of cycle threshold by qPCR between wild-type and deletion alleles. By using the cut-off difference between the cycle thresholds of 0.51, the sensitivity for detection of homozygous alpha zero-thalassemia was 98.4% and the false-positive rate was 20.8%. The report demonstrated a feasible use of relative amount of DNA for diagnosis of a genetic disease when both parents carry the same mutation. However, with the limitation of qPCR, there are false negativity and positivity. More sensitive and specific techniques are needed to improve the effectiveness of the prenatal diagnosis. Lam et al.  described the use of relative haplotype dosage (RHDO) by targeted massively parallel sequencing of maternal plasma in prenatal diagnosis of beta-thalassemia with a good result; however, the method is not widely available.
dPCR is a third generation of PCR that enables the detection of alleles presenting in a small amount. dPCR platform operates by creating thousands of partitions, each containing PCRs. The rare mutation will amplify within its own compartment, permitting the absolute quantification and better detection of small copy numbers . The final PCR product will be detected by fluorescence probes, and the absolute count of the rare mutation among wild-type DNAs will be obtained [27, 28]. The method has been used in various clinical conditions, such as quantification of chimerism, gene expression in cancers, and noninvasive prenatal diagnosis of thalassemia [21, 22, 29‒31].
The major limitation of diagnosing autosomal recessive disease by cff-DNA in maternal plasma is the differentiation between fetal-derived DNA and maternal DNA. In this study, we proposed to investigate the use of cff-DNA in maternal plasma analysis by using dPCR for pregnancies at risk for beta-thalassemia disease caused by common beta-thalassemia mutations. The difference in quantity between the mutation and wild-type DNA was expected to be used for establishing a disease, carrier, or normal status.
Materials and Methods
A prospective diagnostic study was conducted at Maharaj Nakorn Chiang Mai Hospital, a tertiary center and medical school, Thailand, between April 2019 and March 2022. The study was ethically approved by the Institutional Review Boards, Faculty of Medicine, Chiang Mai University, Research ID: PED-2561-05262. Pregnancy couples at risk of having an offspring with homozygous beta-thalassemia, or Hb E/beta-thalassemia caused by the 4 common mutations of HBB, codon 17 (A>T), IVS1nt1 (G>T), codon 41/42 (-TTCT), and codon 26 (G>A), were enrolled into the study and followed up at Chiang Mai University Hospital between 12 and 22 weeks of gestation. Informed written consents were obtained from the pregnant women and their spouses before blood collection. 10 mL of whole blood in EDTA tube was collected from the pregnant women and their spouses.
The pregnant women were followed up as per standard antenatal care guideline. In the cases that they underwent prenatal invasive diagnosis procedure, the fetal HBB genotype data, detected by multiplex PCR with high-resolution melting analysis, were recorded. If the couple chose not to undergo prenatal invasive diagnosis, the fetal HBB genotype data obtained from neonatal cord blood study were recorded. The HBB genotype results from cff-DNA were compared with the fetal genotype.
Plasma Cell-Free DNA Extraction
The 10-mL EDTA blood was kept at 4°C until processing within 2 h after collection. Plasma samples were separated by two-step centrifugation. Plasma cell-free DNA was extracted by the QIAamp Circulating Nucleic Acid Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instruction.
Primer and Probe Sequences
The primers and probes used to detect the 3 common mutations of HBB, codon 17 (A>T), codon 41/42 (-TTCT), and codon 26 (G>A), were as described previously by Suwannakhon and Sanguansermsri . The primers and probes used to detect the IVS1nt1 (G>T) mutation were as described by Teh et al. . The sequences of primers and probes are as shown in online supplementary Table 1 (see www.karger.com/doi/10.1159/000528033 for all online suppl. material).
The dPCR assay was designed to detect and quantify paternally inherited beta-thalassemia allele (PIB) and maternally inherited beta-thalassemia allele (MIB) from cff-DNA in maternal plasma. The quantification was performed using the QIAcuity Digital PCR System (Qiagen). The assay included the reaction setup, thermal cycling conditions, data acquisition, and analysis. The 40 μL of reaction mixture for each test sample included 1X QIAcuity Probe PCR master mix, 0.4 μM of each wild-type and mutant alleles TaqMan probe, 0.8 μM of each primer, and 5 μL of plasma cell-free DNA. The reaction mixtures were loaded into nanoplate 26k, 24-well plate (Qiagen). The nanoplate was transferred to the QIAcuity instrument. The dPCR cycles consisted of polymerase activation 95°C for 2 min, then 40 cycles of denaturation 95°C for 15 s, and annealing-extension 60°C for 1 min. The DNA product count was reported as numbers of positive and negative partitions.
The 24-well plate of dPCR is used for investigations of two families. Each 12 wells for one family were set as follows: five wells of multiplex primers and probes to detect MIB-mutant allele (MIB-M) and MIB wild-type allele (MIB-N), one well of positive heterozygous MIB control, one well of no-template control, three wells of multiplex primers and probes to detect PIB-mutant allele (PIB-M) and PIB wild-type allele (PIB-N), one positive heterozygous PIB control, and one no-template control.
Analysis of dPCR Results
The total PIB-M count from triplicated analysis was compared between the fetuses who inherited or not inherited the paternal mutation. The presence of PIB-M indicated the presence of the paternally inherited mutation in the fetus. The possible diagnosis was either beta-thalassemia carrier of the paternally inherited mutation or beta-thalassemia disease from compound heterozygosity of paternally inherited and maternally inherited mutations. On the other hand, the absence of PIB-M indicated that the possible diagnosis of the fetus was either normal (no HBB mutations) or beta-thalassemia carrier of the maternally inherited mutation.
The total MIB-M/MIB-N ratio from quintuplicated analysis was used to distinguish the presence of maternally inherited mutation in the fetus. The MIB-M/MIB-N ratio was compared between the fetuses who inherited or not inherited the maternal mutation.
In the couples with the same HBB mutations, the mutation mutant/normal ratio was compared between the fetuses who inherited or not inherited the mutation. Note that the numbers of positive PIB and MIB were obtained from the number of partitions with positive amplification in the nanoplate of dPCR, whereas the absolute copy number was not calculated.
The statistical analysis was performed using the statistical package for the social sciences (SPSS) software version 26.0 (IBM Corp. Released 2019. IBM SPSS Statistics for Windows, Version 26.0; IBM Corp., Armonk, NY, USA). Continuous data were presented as mean ± standard deviation and categorical data as percentage, respectively. The means between two groups were compared using Student’s t test. The diagnostic cut-off point of MIB-M/MIB-N ratio, sensitivity, and specificity were analyzed by the receiver operating characteristic curve.
Thirty-five pregnancy couples at risk of having an offspring with severe beta-thalassemia diseases were enrolled. The gestational age at blood collection was 18.4 ± 2.0 weeks. Twenty-six couples (74.3%) were at risk of having a fetus with Hb E/beta-thalassemia, seven (21.0%) at risk of homozygous beta-thalassemia (3 with different paternal and maternal mutations and 4 with the same mutation), and two (5.7%) at risk of both Hb E/beta-thalassemia and homozygous beta-thalassemia as the fathers had Hb E/beta-thalassemia. In 41 beta-thalassemia carriers, there were 14 codon 17 (A>T), 9 IVS1nt1 (G>T), and 18 codon 41/42 (-TTCT) mutations. Both fathers with Hb E/beta-thalassemia had codon 41/42 (-TTCT)/codon 26 (G>A) mutations.
In 29 couples with different paternal and maternal mutations, PIB-M was present in 17 (58.6%) samples. All cases with paternally inherited mutation had detectable PIB-M. The MIB-M/MIB-N ratio in fetuses who did not inherit maternal mutation was significantly lower than those from fetuses who inherited maternal mutation, 0.87 ± 0.07 and 1.01 ± 0.05, respectively, p value <0.001. Examples of dPCR results are presented in Figures 1 and 2. The PIB-M number, PIB-M/PIB-N ratio, and MIB-M/MIB-N ratio according to fetal HBB genotype are shown in Table 1 and Figure 3.
Figure 4 shows the receiver operating characteristic curve of MIB-M/MIB-N ratio in predicting fetus inheriting maternal mutation with an area under curve of 0.976 (95% CI 0.925–1.000, p value <0.001). The sensitivity and specificity of MIB-M/MIB-N ratio of >0.95 in prediction of fetus inheriting maternal mutation were 100 and 92.3% (false-positive rate of 7.7%), respectively. Also, comparison of prenatal noninvasive diagnosis of beta-thalassemia by dPCR results with prenatal invasive diagnosis is presented in Table 2.
In four couples with same paternal and maternal mutation, the mutant/normal ratio was 0.90 in one fetus with normal HBB, 1.01 and 1.11 in two fetuses who had heterozygous mutation, and 1.45 in one fetus with homozygous mutation. The IB-M/IB-N ratio of >0.95 correctly predicted the presence of an inheritance of at least one beta-thalassemia allele.
In two couples with paternal Hb E/beta-thalassemia, both fetuses had beta-thalassemia disease. The PIB-M was present in both cases, 25 and 35 positive partition numbers, respectively, and the MIB-M/MIB-N ratio was 0.96 and 1.10. The presence of PIB-M and the MIB-M/MIB-N ratio of >0.95 correctly predicted the presence of paternal and maternal mutations, respectively.
This study shows that using dPCR for analyzing cff-DNA in maternal plasma to diagnose beta-thalassemia in fetuses is feasible. The method is rapid, simple, and accurate. The presence of PIB-M accurately indicates that fetus inherits paternal mutation, and likewise, the absence of PIB-M accurately excludes the paternal inheritance in the fetus.
For maternally inherited mutations, the MIB-M and MIB-N from cff-DNA of mother with fetus who inherits maternal mutation hypothetically are 1:1; therefore, the ratio is 1.0. The absence of maternally inherited mutation should lower the MIB-M/MIB-N ratio to less than 1.0, and the presence of maternally inherited mutation should raise the MIB-M/MIB-N ratio to approximately 1.0. This study shows that MIB-M/MIB-N ratio >0.95 can be used to predict the presence of maternal mutation in the fetus.
The current prenatal noninvasive diagnosis methods are mostly applied to diseases with autosomal dominant inheritance [33, 34]. For diseases inherited by autosomal recessive inheritance, the maternal cff-DNA interferes with the diagnosis. The methods that have been used to identify maternally inherited mutation include haplotyping-based approach and mutant/wild-type allelic ratio or relative mutation dosage [18, 20, 24‒26]. In this study, the use of dPCR has overcome the limitation of detecting mutations presenting in a small amount, and the relative mutation dosage can accurately identify the inheritance of maternal mutation. Therefore, our results seem promising for noninvasive prenatal diagnosis of other autosomal recessive disorders using dPCR. Our findings indicated that with dPCR, among fetuses at risk, all affected fetuses were prenatally identified, though in this early phase of experience the affected cases should be confirmed for the definitive diagnosis with invasive procedures. The false-positive result rate was very low (7.7% in this study), signifying that the invasive diagnostic procedures could safely be avoided in a great number. On the other hand, negative results of mutations (absence of PIB-M, MIB-M/MIB-N ratio of lower than 0.95) can exclude the disease with confidence.
The sources of error of noninvasive diagnosis methods by analyzing cff-DNA could be from the low fetal fraction of the cell-free DNA and the limited sensitivity of the detection method. Low fetal fraction can result from both fetal and maternal factors . The fetal factors are the early gestational age, mostly accepted from 9 weeks of gestation and fetal fraction of 8–10%. Certain aneuploidies including trisomy 13, 18, and monosomy X are associated with low fetal fraction. The maternal factors include obesity, assisted reproductive technology, and conditions affecting DNA turnover. In this study, the dPCR is highly sensitive and specific for predicting the fetal mutation. Of note, as most pregnant women in this study underwent a cordocentesis procedure, the mean gestational age at blood collection of 18 weeks is higher than those in other studies. The higher mean gestational age is likely an important factor attributing the precise results in this study. Further study in pregnancies with earlier gestational age is needed before the method can be used in early gestation. For clinical use, a parallel procedure to detect and measure fetal-derived cell-free DNA is necessary to ascertain the true-negative results.
The false-positive rate in this study, observed only in predicting fetus inheriting maternal mutation, is likely associated with the overlapping of the MIB-M/MIB-N ratio between cases with or without maternal mutation. To improve the false-positive rate, the use of RHDO analysis by dPCR in combination with MIB-M/MIB-N ratio should be helpful. RHDO by NGS has shown high accuracy in noninvasive prenatal diagnosis of thalassemia [24, 36]. Additionally, the more proper cut-off, instead of 0.95, identified by further studies with larger sample size, may improve the false-positive rate.
The strengths of this study are as follows: (1) the technique used in this study is relatively rapid, simple, and not as expensive as NGS technique, probably leading to more available in widely use. Turnaround time of the dPCR is 2–3 days, and the cost per test is approximately 200–300 USD, while the turnaround time of NGS is 7–14 days and the cost per test is approximately 1,000–2,000 USD. Accordingly, the results of this study could be feasible to be tested in other groups of population. (2) Prospective nature of the study, in terms that the diagnoses using cff-DNA in maternal plasma were analyzed, completely blinded to the final diagnoses which were available after prenatal diagnosis or after birth, could make the results more reliable. The weaknesses of this study include the following: (1) the sample is rather small, especially the cases with the same mutation, and further studies are needed to confirm the findings. (2) The gestational age of dPCR tests was relatively late (means: 18 weeks of gestation), and only few cases of late first trimester were included.
In conclusion, the method of analyzing cff-DNA in maternal plasma to prenatally diagnose beta-thalassemia by dPCR is efficient. The method can greatly reduce the needs for invasive obstetrical procedures for prenatal diagnosis of beta-thalassemia diseases and can be applied to other HBB mutations and other single gene disorders. In practice, a procedure to detect and measure fetal-derived cell-free DNA should be implemented along with the detection of HBB mutations to ensure the adequacy of the tested sample. Finally, we propose an algorithm for clinical use of dPCR of cff-DNA as noninvasive prenatal diagnosis of beta-thalassemia as presented in Figure 5.
We would like to express our gratitude to MFM team who helped us in patient recruitment and collecting data.
Statement of Ethics
This study received ethnical approval from the institute review boards of Faculty of Medicine, Chiang Mai University (Ethics Committee 4; Research ID PED-2561-05262). Written informed consent was obtained from all subjects involved in the study.
Conflict of Interest Statement
The authors declare that they have no competing interests.
The study was funded by the Thailand Research Fund DPG-6280003. There is no role of funder in data preparation and manuscript writing.
Pimlak Charoenkwan: conceptualization, proposal draft, formal analysis, manuscript writing, and final approval. Kuntharee Traisrisilp: conceptualization, proposal draft, data collection, manuscript writing, and final approval. Supatra Sirichotiyakul: data collection, manuscript revising, and final approval. Arunee Phusua: laboratory investigation, manuscript revising, and final approval. Torpong Sanguansermsri: conceptualization, manuscript revising, and final approval. Theera Tongsong: conceptualization, formal analysis, manuscript revising, and final approval.
Data Availability Statement
All data generated or analyzed during this study are included in this article and its online supplementary material. Further inquiries can be directed to the corresponding author.