Combined Count- and Size-Based Analysis of Maternal Plasma DNA for Noninvasive Prenatal Detection of Fetal Subchromosomal Aberrations Facilitates Elucidation of the Fetal and/or Maternal Origin of the Aberrations.
Cell-free DNA in maternal plasma consists of a mixture of fetal and maternal DNA. The counting approach enumerates both fetal and maternal DNA molecules in a maternal plasma sample. It compares the relative representation of a particular genomic region in the plasma of a pregnant woman in relation to the corresponding values in a group of healthy pregnant women carrying normal fetuses. Hence, an abnormal result from the count-based approach could result from more than one clinical scenario, namely the presence of a copy number aberration (CNA) in (a) the fetus, (b) the mother, or (c) both (8, 10). Thus, if the mother carries a CNA, one could not discern if the fetus has inherited the aberration. Indeed, the presence of maternal copy number variants is one of the reported causes confounding NIPT results (11). Snyder et al. demonstrated in 2 cases that discordant NIPT results might be attributable to the presence of maternal copy number variants (11). In a recent study, Yin et al. reported that maternal copy number variants were present in 35 out of the 55 (63.7%) samples with false-positive NIPT results in their cohort of 1456 samples (12). Based on this finding, Yin et al. recommend a follow-up test of the maternal DNA to exclude maternal copy number variants in cases with positive NIPT results for fetal subchromosomal aberrations.
Recently, our group developed an approach that takes advantage of the size difference between fetal and maternal DNA molecules in maternal plasma for the detection of fetal aneuploidies (13). Briefly, DNA molecules derived from the fetus have a shorter size distribution compared with those derived from the mother (14, 15). Hence, the presence of an extra fetal chromosome in fetal trisomy would shorten the size distribution of DNA in maternal plasma derived from that chromosome. This size-based approach detects an altered proportion of short fragments from the aneuploid chromosome in the plasma. This approach has allowed the detection of multiple types of fetal whole-chromosome aneuploidies, including trisomies 21, 18, 13, and monosomy X, with high accuracy (13).
In this study, we investigated if the size-based analysis could also be used as an independent method to confirm the subchromosomal CNAs detected by count-based analysis. In addition, we investigated if a combination of size-based and count-based analyses might be able to differentiate the origin, i.e., fetal, maternal, or both, of the aberrations detected by maternal plasma DNA sequencing. We hypothesized that if both the fetus and mother had CNAs in a particular chromosomal region, then there would be no net difference in the size distribution of that region when compared with another chromosomal region without any CNAs. On the other hand, if there was a relative overrepresentation of fetal DNA when compared with maternal DNA in a particular chromosomal region, such as when (a) the fetus had a microduplication while the mother is normal, or (b) the mother had a microdeletion while the fetus was normal, then there would be shortening in the overall size distribution. Conversely, if there was an underrepresentation of fetal DNA when compared with maternal DNA in a particular chromosomal region, such as when (a) the fetus had a microdeletion while the mother was normal, or (b) the mother had a microduplication while the fetus was normal, then there would be lengthening in the overall size distribution.
Materials and Methods
SAMPLE COLLECTION AND PROCESSING
Women with singleton pregnancies were recruited from the Departments of Obstetrics and Gynaecology of the Prince of Wales Hospital and Kwong Wah Hospital in Hong Kong, the Radboud University Nijmegen Medical Center in The Netherlands, and the Asan Medical Center in Seoul, with written informed consent and institutional ethics committee approval. Maternal peripheral blood samples were collected and processed as previously described (16). DNA was extracted from the plasma with the QIAamp DSP DNA Blood Mini Kit (16).
Ten cases with CNAs derived from either the fetus or the mother, or both, were included in this study (Table 1). Six of them have been included in a previous study evaluating only the count-based approach (7). The remaining 4 were new cases that have not been analyzed before. Maternal and fetal karyotype information was known before plasma DNA analysis.
PLASMA DNA SEQUENCING
We prepared DNA libraries of the new cases using a KAPA Library Preparation Kit (Kapa Biosystems) following the manufacturer's instructions. The adaptor ligated plasma DNA was enriched by a 12-cycle PCR. Each library was sequenced with 1 lane of a flow cell on a HiSeq 2500 sequencer (Illumina) or 2 lanes of a flow cell on a HiSeq 1500 sequencer (Illumina). We performed 50 cycles of paired-end sequencing. Paired-end reads were aligned and filtered as previously described (13). After alignment, the size of each sequenced DNA fragment was determined from the start and end coordinates of the paired-end reads.
For the 6 cases that had been included in a previous study, paired-end sequencing data of these maternal plasma DNA samples were reanalyzed as described below. The plasma DNA libraries of these cases were prepared previously with the Paired-End Sequencing Sample Preparation Kit (Illumina) and sequenced with 1 lane of a flow cell on a HiSeq 2000 sequencer (Illumina).
Singleton pregnant cases with normal fetal and maternal karyotypes were used as controls. Since the 4 new cases and the 6 cases that had been included in the previous study were prepared with different library preparation kits, 2 different sets of controls were used in the analyses of these 2 groups of test cases. The new and old control sets consist of 10 and 8 samples, respectively. Each set was prepared with the same library preparation kit and sequenced with the same number of lanes as the corresponding group of test cases.
To perform the count-based analysis, each chromosome was divided into 100-kb bins and locally weighted scatterplot smoothing (LOESS) was performed to obtain the GC-corrected read counts as previously described (17). The GC-corrected read counts were used in all the calculations involved in the count-based analysis. We determined the mean values and SDs of the genomic representation (GR) of the tested region of the controls, and calculated a count-based z score for the tested region of each sample using the following equation (7):
Count-based z score = [GR.sub.sample] - mean [GR.sub.control]/SD [GR.sub.control] (1)
Count-based z scores of >3 and <-3 were used as the cutoff scores for indicating a copy number gain and a copy number loss, respectively.
CALCULATION OF ABERRATION-CONTAINING FRACTION IN MATERNAL PLASMA
Aberration-containing fraction in the plasma ([F.sub.CNA]) refers to the proportion of plasma DNA derived from cells with a CNA. Theoretically, if only the fetus carried the aberration, only those fetal-derived plasma DNA molecules would contain the aberration, and [F.sub.CNA] would be equal to the fetal DNA fraction in plasma. Analogously, if only the mother carried the aberration, only those maternally derived plasma DNA molecules would contain the aberration, and [F.sub.CNA] would be equal to the maternal DNA fraction in plasma. On the other hand, if both the mother and the fetus carried the aberration that was not mosaic in nature, all plasma DNA molecules would be derived from cells containing the aberration, and [F.sub.CNA] would be 100%. CNA
To calculate [F.sub.CNA], the entire genome was divided into 2687 1-Mb segments, called bins. A count-based z score was calculated for each bin as described above. For each case, we used the 1-Mb bin with the highest z score in the region showing CNA for the calculation of [F.sub.CNA]. The [F.sub.CNA] was calculated as follows (7):
[F.sub.CNA] = [absolute value ([GR.sub.sample] - mean [GR.sub.control]/mean [GR.sub.control])] X 100% X 2, (2)
where [GR.sub.sample] is the genomic representation of the 1-Mb bin with the highest z score in the affected region for the test case, and [GR.sub.control] is the mean of the genomic representation of that bin of the controls.
To perform the size-based analysis, GC correction was not performed. We first calculated a parameter, termed [DELTA]F, for each of the tested regions, which was defined as the difference in the proportion of short DNA fragments between the tested and the reference regions using the following equation (13):
[DELTA]F = P[([less than or equal to] 150 bp).sub.test] - P [([less than or equal to] 150bp).sub.ref], (3)
where P[([less than or equal to] 150 bp).sub.test] denotes the proportion of sequenced fragments originating from the tested region with sizes [less than or equal to] 150 bp, and P[([less than or equal to] 150 bp).sub.ref] denotes the proportion of sequenced fragments originating from the reference region with sizes [less than or equal to] 150 bp. The reference region was defined as all the genomic regions excluding the tested regions.
The same groups of controls used in the count-based analysis were used in the size-based analysis. A size-based z score of the tested region was then calculated using the mean and SD values of [DELTA]F of the controls (13).
Size-based z score = [[DELTA]F.sub.sample] - mean [[DELTA]F.sub.control]/SD [[DELTA]F.sub.control], (4)
In this analysis, it was assumed that euploid cases and cases with CNAs followed the same pattern regarding the differences in the fragment size distributions between fetal and maternal cell-free DNA. A size-based z score of >3 would indicate an increased proportion of short fragments for the tested region, while a size-based z score of <-3 would indicate a reduced proportion of short fragments for the tested region.
PRINCIPLE AND WORKFLOW OF COMBINED COUNT--AND SIZE-BASED ANALYSIS
The principle and workflow of the combined count--and size-based analysis of maternal plasma DNA for the noninvasive prenatal detection of fetal subchromosomal CNAs are illustrated in Fig. 1. The count-based approach was first used to determine if the tested genomic region was over- or underrepresented in a maternal plasma sample. To determine if there was an over- or underrepresentation in the tested genomic region, the GR of the tested region of the test case was compared with the mean GR of the control cases to obtain the count-based z score. Since DNA molecules derived from the mother and the fetus were counted in the same way, an abnormal result from the count-based analysis would indicate either the fetus, the mother, or both of them might have a CNA.
Given that the magnitude of the count-based z score of the abnormal region correlates with the proportion of plasma DNA harboring the aberration (18), we calculated the [F.sub.CNA] based on the plasma genomic representations of the regions showing CNAs in each case. The [F.sub.CNA] was calculated to determine if the aberration was present in the mother. Given that over 99% of maternal plasma samples would have a fetal DNA fraction of <50% (18, 19), cases with [F.sub.CNA] >50% would suggest that the mother carried the copy number aberration.
For cases with [F.sub.CNA] < 50%, the CNA was potentially present in the fetus. Size-based analysis would be useful to confirm the aberration detected in the count-based analysis (Figs. 1 and 2). In the size-based analysis, the [DELTA]F of the tested region that compared the fragment size distributions of the tested region with that of the reference regions of the same sample was first determined. The [DELTA]F of the tested region of the test case was then compared with the mean [DELTA]F of the tested region of the control cases to obtain the size-based z score. Cases with CNAs derived solely from the fetus would have a size-based z score in the same direction as the count-based z scores, namely a positive value would suggest a duplication. Conversely, a negative value would suggest a deletion (Fig. 2).
For cases in which the mother carried the CNA, size-based analysis would be useful to determine whether the fetus had inherited the aberration from the mother (Figs. 1 and 2). Cases in which the fetus had inherited the aberration from the mother would have a size-based z score within the normal range because there was no change in the relative proportion of fetal and maternal DNA for the affected region compared with other genomic regions (Fig. 2). On the other hand, cases with CNAs only present in the mother would have a size-based z score in the opposite direction to the count-based z scores (Fig. 2). Thus, a positive count-based z score and a negative size-based z score would suggest a maternal duplication. Conversely, a negative count-based z score and a positive size-based z score would suggest a maternal deletion (Fig. 2).
COMBINED COUNT--AND SIZE-BASED ANALYSIS OF MATERNAL PLASMA DNA
The 4 new cases and its corresponding control samples were each sequenced with 1 lane of a flow cell on a HiSeq 2500 sequencer or 2 lanes of a flow cell on a HiSeq 1500 sequencer, resulting in a mean of 229 million (range: 144 million to 312 million) alignable and non-duplicated reads per case, which was equivalent to 7.65-folds of the haploid genome. The 6 cases that had been included in the previous study and its corresponding control samples were each sequenced with 1 lane of a flow cell, resulting in a mean of 160 million (range: 109 million to 187 million) alignable and nonduplicated reads per case, which was equivalent to 5.35-folds of the haploid genome.
As a proof-of-principle study, we performed the combined count- and size-based analyses on seven target regions, which included one 3-Mb region and one 6-Mb region on chromosome 3 (chr3: 59000000-62000000; chr3: 192000000-198000000), two 2-Mb regions and one 32-Mb region on chromosome 4 (chr4: 60000000 -62000000; chr4: 97000000-99000000; chr4: 158000 000 -190000000), one 4-Mb region on chromosome 12 (chr12: 12000000-16000000), and one 3-Mb region on chromosome 22 (chr22: 19000000-22000000), for each case (Table 2; also see Table 1 in the data supplement that accompanies the online version of this article at http://www. clinchem.org/content/vol63/issue2). The target regions were selected such that they covered all the known CNAs in our sample set.
For M10219, we detected a 3-Mb microduplication on chromosome 22 with a count-based z score of 12.6 (Table 2). For K1, K2, and HK310, we detected a 3-Mb microdeletion in the same region with count-based z scores of -7.7, -12.8, and -7.8, respectively (Table 2). For M8205, we detected a 6-Mb microduplication (count-based z score: 24.0) and a 32-Mb microdeletion (count-based z score: -24.7) on chromosomes 3 and 4, respectively (Table 2). For each case, the [F.sub.CNA] was below 50%, suggesting that the aberration was potentially present in the fetus only (Table 2). In all cases, the size-based z scores were in the same direction as the count-based z scores (Table 2). All the deleted regions detected by the count-based analysis had a size-based z score of <-3, indicating that the affected region had a significantly longer size distribution. On the contrary, all the duplicated regions detected by the count-based analysis had a size-based z score of >3, indicating that the affected region had a significantly shorter size distribution. Hence, the results of the size-based analysis confirmed those of the count-based analysis, which suggested that the fetus was the sole source of the aberrations detected in maternal plasma. These results were consistent with the clinical information of the five cases (Table 1).
For M14-13489-F1, we detected a 2-Mb microduplication on chromosome 4 with a count-based z score of 96.2 (Table 2). For DNA 11-04530, we detected a 2-Mb microdeletion in another region on chromosome 4 with a count-based z score of -63.4. The [F.sub.CNA] were 69.5 and 82.5, respectively. For the regions with abnormal count-based z scores, the corresponding size-based z score was -3.6 for M14-13489-F1 and 5.3 for DNA 11-04530. Hence, in both cases, the size-based z-scores were in the opposite direction to the count-based z-scores, suggesting that the aberrations would be present in the mothers only. These results were consistent with the clinical information (Table 1).
For DNA12-17476, M11879, and PW503, we detected a 3-Mb microduplication on chromosome 3 (count-based z score: 139.9), a 4-Mb microduplication on chromosome 12 (count-based z score: 114.9), and a 3-Mb microduplication on chromosome 22 (count-based z score: 67.2), respectively (Table 2). The [F.sub.CNA] of these 3 cases were 79.1%, 97.5%, and 100.0%, respectively. Size-based analysis of the target regions showed size-based z scores that were within the normal range for these 3 cases (size-based z scores: 2.2 for DNA 12-17476; 1.1 for PW503 and 0.0 for M11879), indicating that both the mother and the fetus in these 3 cases harbored the microduplications. These results were also consistent with the clinical information (Table 1).
No aberrations were detected in the other tested regions for each case with our combined analyses (see online Supplemental Table 1). Interestingly, with the count-based approach alone, a 6-Mb region on chromosome 3 in M10219 and a 32-Mb region on chromosome 4 in both DNA11-04530 and M11879 were over-represented with count-based z scores of 3.6, 3.6, and 6.5, respectively (see online Supplemental Table 1). The [F.sub.CNA] were 6.5%, 3.5%, and 6.8%, respectively. However, the size-based z scores were 2.1, -2.4, and -1.9, respectively (see online Supplemental Table 1). Hence, the aberrations detected by the count-based analysis were not confirmed by the size-based analysis, and these regions were classified as normal. These results were consistent with the array CGH analysis.
DNA12-17476, M11879, and PW503 were pregnancies involving fetuses that had inherited a microduplication of 2.5 Mb on chromosome 3, a microduplication of 3.5 Mb on chromosome 12, and a microduplication of 2.4 Mb on chromosome 22, respectively, from their mothers. Because the mother herself carried the microduplication, both our previous and current studies showed very high count-based z scores for the regions involved (Table 2) (7). However, the count-based analysis by itself did not reveal whether the fetus had inherited the microduplication from the mother. By use of the size-based approach, the regions involved for the three cases showed size-based z scores within the normal range. This observation is consistent with our hypothesis that when an aberration is derived from both the fetus and the mother, the size distribution of maternal plasma DNA in the affected region would remain unchanged, since the relative contributions from the fetus and mother are not altered in the affected region compared with other unaffected regions. On the other hand, as in M14-13489-F1, when the fetus had not inherited the microduplication from the mother, the proportion of short fragments in the affected region would be reduced, leading to a negative size-based z score in contrast to the positive count-based z score. Hence, this study demonstrates the feasibility of using the combined analysis of maternal plasma to determine whether a fetus has inherited a CNA from its mother who herself is a carrier of the CNA noninvasively.
Despite having a high detection rate and a low false-positive rate, NIPT for fetal chromosomal aneuploidies using cell-free DNA in maternal plasma is currently used as a screening test due to an insufficiently high positive predictive value (PPV). The PPV of the test would be expected to be even lower if subchromosomal CNAs were included since individual members of these conditions are even rarer than the whole chromosomal aneuploidies. In addition, the number of false positives due to multiple comparisons would increase as more targets were tested. As reported by Yin et al., 20 of their 55 false-positive samples might be attributable to sequencing and statistical errors (12). In our combined protocol, the size-based analysis can serve as an independent method to confirm the aberration detected by the count-based analysis. From our current dataset, we saw an indication that one could potentially minimize the number of false positives due to statistical errors with the combined count--and size-based approach. We believe that with the use of the combined approach, the PPV of the plasma-based test for fetal subchromosomal CNAs can be improved, and hence the number of invasive procedures can be reduced. In particular, the combined approach may significantly increase the PPV for NIPT of rare pathogenic CNAs. It would be worthwhile to explore the accuracy and robustness of this combined protocol with a larger sample cohort, and consider replicate analyses in future studies.
To achieve a resolution of 2 Mb for the detection of fetal subchromosomal CNAs with a diagnostic 95% sensitivity and a diagnostic 99% specificity at a fetal DNA fraction of 5%, both the count-based and the size-based approaches would need to analyze around 200 million molecules (7). On the other hand, since the median fetal DNA fraction in the first trimester is approximately 15% (18, 20), or 10% (21) about 20 or 50 million molecules would be required to achieve the same performance. This estimation is based on the previously reported mathematical relationship whereby every 2-fold increase in fetal DNA fraction would lead to a 4-fold decrease of molecules required for the same test performance (22). Since the same set of sequencing data could be used for both types of analyses, our combined protocol only requires additional reagent costs for the paired-end sequencing compared with the counting-only protocol that requires reagents for single-end sequencing. In addition, the time requirements for bioinformatics processing needed by the 2 protocols are comparable.
In summary, we have demonstrated that size analysis of plasma DNA in pregnant women can accurately detect fetal subchromosomal CNAs. The combined use of the size-based and count-based methods can further determine whether the fetus, the mother, or both of them carry the aberration. This combined approach would be very valuable in helping clinicians to interpret the results of NIPT.
Author Contributions: AH authors confirmed they have contributed to the intellectual content of this paper and have met the following 3 requirements: (a) significant contributions to the conception and design, acquisition of data, or analysis and interpretation of data; (b) drafting or revising the article for intellectual content; and (c) final approval of the published article.
Authors' Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest:
Employment or Leadership: K.C.A. Chan, Xcelom and Cirina; Y.M.D. Lo, Cltntcal Chemtstry, AACC, Xcelom, and Cirina; R.W.K. Chiu, Xcelom and Cirina.
Consultant or Advisory Role: K.C.A. Chan, Xcelom; Y.M.D. Lo, Sequenom; R.W.K. Chiu, Sequenom and Xcelom.
Stock Ownership: K.C.A. Chan, Sequenom, Xcelom, and Cirina; Y.M.D. Lo, Xcelom, Cirina, and Sequenom; R.W.K. Chiu, Xcelom, Cirina, and Sequenom.
Honoraria: None declared.
Research Funding: Hong Kong Research Grants Council Theme-Based Research Scheme (T12-403/15); Y.M.D. Lo, Sequenom; R.W.K. Chiu, Sequenom.
Expert Testimony: None declared.
Patents: S.C.Y. Yu, P. Jiang, K.C.A. Chan, R.W.K. Chiu, and Y.M.D. Lo, US patent application no. 62/107,227.
Other Remuneration: Y.M.D. Lo, Illumina (IP licensing) and Sequenom (IP licensing).
Role of Sponsor: The funding organizations played no role in the design of study, choice of enrolled patients, review and interpretation of data, and final approval of manuscript.
Acknowledgments: We thank Lean Beulen for sample collection and Ingrid Gomes for technical assistance. We also thank Professor Hye-Sung Won for case recruitment.
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Stephanie C.Y. Yu, [1,2] [[dagger]] Peiyong Jiang, [1,2] [[dagger]] K.C. Allen Chan, [1,2] [[dagger] Brigitte H.W. Faas,  Kwong W. Choy,  Wing C. Leung,  Tak Y. Leung,  Y.M. Dennis Lo, [1,2] and Rossa W.K. Chiu [1,2] *
 Centre for Research into Circulating Fetal Nucleic Acids, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong SAR, China;  Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China;  Radboud University Nijmegen Medical Center, Department of Human Genetics, Nijmegen, The Netherlands;  Department of Obstetrics and Gynaecology, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, New Territories, Hong Kong SAR, China;  Kwong Wah Hospital, Kowloon, Hong Kong SAR, China.
* Address correspondence to this author at: Department of Chemical Pathology, The Chinese University of Hong Kong, Prince of Wales Hospital, 30-32 Ngan Shing St.,
Shatin, New Territories, Hong Kong SAR, China. Fax +852-26365090; e-mail firstname.lastname@example.org.
[[dagger]] Stephanie C.Y. Yu, Peiyong Jiang, and K.C. Allen Chan contributed equally to this work, and all 3 of them should be considered as first authors.
Received January 12,2016; accepted October 10,2016.
Previously published online at DOI: 10.1373/clinchem.2016.254813
 Nonstandard abbreviations: MPS, massively parallel sequencing; NIPT, noninvasive prenatal testing; CNA, copy number aberration; LOESS, locally weighted scatterplot smoothing; GR, genomic representation; PPV, positive predictive value.
Caption: Fig. 1. A case with a copy number gain on chromosome 2 (Chr 2) in the fetus is used as an example to illustrate the principle and workflow of the combined count-and size-based analysis of maternal plasma DNA for detecting CNAs.
DNA molecules derived from the fetus (thick red fragments) have a shorter size distribution than those derived from the mother (black fragments). The reference region was defined as all the genomic regions excluding the tested regions. See the sections Count-Based Analysis and Size-Based Analysis within Materials and Methods for information with respect to the equations.
Table 1. Sample information. Case Gestational Fetal Chromosomal age, weeks sex aberration, size M10219 (a) 12 3/7 M 22q11.2 Microduplication (2.4 Mb) K1 (a) 24 1/7 F 22q11.2 Microdeletion K2 (a) 28 4/7 M 22q11.2 Microdeletion HK310 (a) 22 5/7 M 22q11.2 Microdeletion M8205 (a) 21 4/7 F 3q29 Microduplication (5.1 Mb) 4q32.1-q35.2 Microdeletion (32.9 Mb) M14-13489-F1 12 2/7 M Microduplication on chr 4 (1.6 Mb) DNA11-04530 14 F Microdeletion on chr 4 (1.33 Mb) DNA12-17476 16 1/7 M Microduplication on chr 3 (2.5 Mb) M11879 22 5/7 F 12p13.2-p12.3 Micro- duplication (3.5 Mb) PW503 (a) 20 2/7 F 22q11.2 Microduplication (2.4 Mb) Case Genomic Methods Mother Fetus coordinates, used to hg19 confirm karyotype M10219 (a) chr22: (b) 18 Array CGH Absent Present 909 032-21 357 982 K1 (a) NA FISH Absent Present K2 (a) NA FISH Absent Present HK310 (a) NA QF-PCR & Absent Present FISH M8205 (a) chr3: 192 641 Array CGH Absent Present 936-197 770 406 chr4: 157 803 276-190 721 966 M14-13489-F1 chr4: 60205 Array CGH Present Absent 642-61 769479 DNA11-04530 chr4: 97 045 Array CGH Present Absent 747-98 376 622 DNA12-17476 chr3: 59206 Array CGH Present Present 485-61 731 047 M11879 chr12: 11 956 Array CGH Present Present 600-15 480 481 PW503 (a) chr22: 18 909 Array CGH Present Present 032-21 357 982 (a) Cases that have been included in a previous study [Yu et al. (7)]. (b) chr, chromosome; Array CGH, array comparative genomic hybridization. Table 2. CNA detected by the combined count-and size-based analysis of maternal plasma DNA. Case Genomic coordinates of the Size Fetal region showing CNA, hg19 of the fraction, % region M10219 chr22: (a) 19 000 000-22 3 Mb 17.8 (b) 000 000 K1 chr22: 19 000 000-22 000 000 3 Mb 10.5 (b) K2 chr22: 19 000 000-22 000 000 3 Mb 17.4 (b) HK310 chr22: 19 000 000-22 000 000 3 Mb 9.2 (b) M8205 chr3: 192 000 000-198 000 000 6 Mb 10.9 (b) chr4: 158 000 000-190 000 000 32 Mb 13.4 (b) M14-13489-F1 chr4: 60 000 000-62 000 000 2 Mb 11.6 (c) DNA11-04530 chr4: 97 000 000-99 000 000 2 Mb 4.0 (c) DNA12-17476 chr3: 59 000 000-62 000 000 3 Mb 12.1 (c) M11879 chr12: 12 000 000-16 000 000 4 Mb 14.2 (c) PW503 chr22: 19 000 000-22 000 000 3 Mb 18.4 (c) Case Count- Aberration- Aberration Size-based based containing present in z score score fraction, % mother? M10219 12.6 19.5 No 6.5 K1 -7.7 11.8 No -3.5 K2 -12.8 18.9 No -4.6 HK310 -7.8 11.7 No -5.9 M8205 24.0 15.5 No 8.6 -24.7 9.7 No -16.3 M14-13489-F1 96.2 69.5 Yes -3.6 DNA11-04530 -63.4 82.5 Yes 5.3 DNA12-17476 139.9 79.1 Yes 2.2 M11879 114.9 97.5 Yes 0.0 PW503 67.2 100.0 Yes 1.1 Case Fetus affected? M10219 Yes K1 Yes K2 Yes HK310 Yes M8205 Yes Yes M14-13489-F1 No DNA11-04530 No DNA12-17476 Yes M11879 Yes PW503 Yes (a) chr, chromosome. (b) The fetal DNA fractions of these samples were estimated based on the plasma genomic representations of the regions showing CNAs [Yu et al. (7)]. (c) The fetal DNA fractions of these samples were estimated through size analysis of the maternal plasma DNA as previously described [Yu et al. (73)]. Fig. 2. Interpretation of results for the combined count-and size-based analysis. There are 6 possible scenarios. Green upward-pointing arrow indicates a positive z score (>3). Red downward-pointing arrow indicates a negative z score (<-3). Double arrows indicate a large magnitude count-based z score. The [F.sub.CNA] is calculated to determine if the aberration is present in the mother. [F.sub.CAN] >50% suggests that the mother carries the copy number aberration. Mother Fetus Count-based z score Normal Copy number gain [up arrow] Normal Copy number loss [down arrow] Copy number gain Copy number gain [up arrow][up arrow] Copy number loss Copy number loss [down arrow][down arrow] Copy number gain Normal [up arrow][up arrow] Copy number loss Normal [down arrow][down arrow] Mother [F.sub.CAN] Size-based z score Normal <50% [up arrow] Normal <50% [down arrow] Copy number gain >50% Normal Copy number loss >50% Normal Copy number gain >50% [down arrow] Copy number loss >50% [up arrow]
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|Title Annotation:||Molecular Diagnostics and Genetics|
|Author:||Yu, Stephanie C.Y.; Jiang, Peiyong; Chan, K.C. Allen; Faas, Brigitte H.W.; Choy, Kwong W.; Leung, Wi|
|Date:||Feb 1, 2017|
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