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External Quality Assessment for Detection of Fetal Trisomy 21, 18, and 13 by Massively Parallel Sequencing in Clinical Laboratories
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External Quality Assessment for Detection of Fetal Trisomy 21, 18, and 13 by Massively Parallel Sequencing in Clinical Laboratories Q18
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Rui Zhang,* Hongyun Zhang,y Yulong Li,z Yanxi Han,* Jiehong Xie,* and Jinming Li* From the National Center for Clinical Laboratories* and the Graduate School,z Peking Union Medical College, Chinese Academy of Medical Sciences, National Center for Clinical Laboratories, Beijing Hospital, Beijing; and the BGI Clinical Laboratories-Shenzhen,y Shenzhen, People’s Republic of China Accepted for publication October 21, 2015.
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Address correspondence to Jinming Li, National Center for Clinical Laboratories, 1 Dahua Rd, Dongdan, Beijing 100730, People’s Republic of China. E-mail: jmli@nccl. org.cn.
An external quality assessment for detection of trisomy 21, 18, and 13 by massively parallel sequencing was implemented by the National Center for Clinical Laboratories of People’s Republic of China in 2014. Simulated samples were prepared by mixing fragmented abnormal DNA with plasma from non-pregnant women. The external quality assessment panel, comprising 5 samples from pregnant healthy women, 2 samples with sex chromosome aneuploidies, and 13 samples with different concentrations of fetal fractions positive for trisomy 21, 18, and 13, was then distributed to participating laboratories. In total, 55.6% (47 of 84) of respondents correctly identified each of the samples in the panel. Seventeen false-negative and 87 gray zone results were reported, most [102 of 104 (98.1%)] of which were derived from for trisomy samples with effective fetal fractions <4%. No laboratories generated false-positive results. In addition, we observed varied diagnostic capabilities of different assays, with the assay on the basis of NextSeq CN500 performing better than others, whereas Z values generated by BGISEQ-100 fluctuated greatly. There were no significant correlations between the numbers of unique sequence reads and Z values from any trisomy sample generated by BGISEQ-100. Overall, most clinical laboratories detected samples containing effective fetal fractions >4%. Our study shows need for further laboratory training in the management of samples with low fetal fractions. For some assays, precision of Z values needs to be improved. (J Mol Diagn 2016, -: 1e9; http://dx.doi.org/10.1016/j.jmoldx.2015.10.003)
Chromosomal aneuploidy is a common cause of birth defects, and trisomy 21 (T21), trisomy 18 (T18), and trisomy 13 (T13) are the most frequently occurring chromosomal abnormalities. Currently, the standard screening procedures for detecting chromosomal abnormalities involve a combination of first-trimester serum screening for biochemical markers, such as pregnancy-associated plasma protein-A, free b-human chorionic gonadotropin, and ultrasound measurement of the nuchal translucency thickness, with or without a measurement of second-trimester markers. Depending on the results of these screens, the definitive prenatal diagnosis, which includes amniocentesis or chorionic villus sampling, followed by chromosomal analysis, is performed in high-risk pregnancies. However, depending on the screening strategy used, the standard prenatal aneuploidy screening can only identify 50% to 95% of the
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anomalies, with false-positive screen rates of 5%.1,2 Hence, the sensitivity of current screening programs for fetal chromosomal aneuploidy is unsatisfactory, and the high rates of false-positive results lead to unnecessary invasive sampling, which add stress to the pregnancies. In recent years, noninvasive prenatal testing (NIPT) using cell-free DNA (cfDNA) sequences isolated from maternal blood samples has been introduced into clinical practice for the detection of T21, T18, and T13. Several approaches have been reported for the analysis of chromosomal cfDNA fragments using next-generation DNA sequencing Supported by the National Population and Family Planning Commission Q2 of the People’s Republic of China Special Fund for Health-Scientific Research in the Public Interest grant 201402018. Q3 Disclosures: None declared.
Copyright ª 2016 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jmoldx.2015.10.003
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Figure 1
A flow diagram of the preparation, validation, and distribution of the samples in noninvasive prenatal testing external quality assessment
scheme.
technology, including whole genome massively parallel sequencing (MPS),3e5 targeted MPS,6,7 and analysis of single-nucleotide polymorphisms.8,9 The results of multiple clinical trials of NIPT were promising and demonstrated high sensitivity (up to 99%) and specificity, with low falsepositive rates (<0.1%).10e13 The International Society for Prenatal Diagnosis,14 the American College of Obstetricians and Gynecologists,15 and the American College of Medical Genetics and Genomics16 supported the proposal that pregnant women at high risk should be provided NIPT as a screening option for routine clinical care after receiving appropriate counseling. As the testing transitioned from clinical trials to clinical care, NIPT has become commercially available. There are many reports regarding the use of NIPT in the clinical laboratories.17e19 Recently, in People’s Republic of China, commercial vendors have simplified these bioinformatics analysis tools, and increasing clinical laboratories have shown interest in this new method for T21, T18, and T13 screening. Under the circumstances, external quality assessment (EQA) becomes an essential management measure to assess the proficiency and performance of various NIPT assays. It also ensures that laboratories maintain robust laboratory diagnostic capacities. However, it is hard to obtain enough clinical samples from pregnant
women having a fetus with trisomy. Therefore, we produced artificial specimens to simulate clinical samples. Herein, we described the first nationwide EQA study in People’s Republic of China, organized by the National Center for Clinical Laboratories (Beijing, People’s Republic of China), and discussed laboratory and assay performance for NIPT.
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Materials and Methods NIPT Panel Composition and Preparation Panels were prepared by the National Center for Clinical Laboratories using placental tissues with chromosomal aneuploidy, cultured cell lines, YH DNA (First Asian Diploid Genome, http://yh.genomics.org.cn, last accessed September 21, 2015),20 and peripheral venous blood from non-pregnant healthy women (Figure 1). First, genomic ½F1 DNA (gDNA) was extracted from placental tissues with T21, T18, T13, and abnormal sex chromosomes (XO/ XXX). Two cell lines (AG09802 and GM02732) with trisomies of chromosomes 21 and 13 were purchased from the Coriell Cell Repositories (Coriell, NJ). T21 and T18 DNAs were extracted from cultured cell lines using the DNA mini kit (Qiagen, Venlo, the Netherlands) and mixed with YH
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EQA for NIPT in Clinical Laboratories Table 1
Trisomy 21
Sample no.
Classification
No. of correct data sets/total no. of data sets (%)
1401 1402 1403 1404 1405 1406 1407 1408 1409 1410 1411 1412 1413 1414 1415 1416 1417 1418 1419 1420
Normal chromosome 8% T21 3.50% T18 XXX positive 8% T13 10% T18e70% chimera Normal chromosome 8% T18 Normal chromosome 10% T21e30% chimera 10% T18e30% chimera Normal chromosome 5% T13 5% T21 10% T21e70% chimera Normal chromosome 3.50% T13 5% T18 3.50% T21 XO positive
84/84 84/84 84/84 84/84 84/84 84/84 84/84 84/84 84/84 62/84 84/84 84/84 84/84 84/84 84/84 84/84 84/84 84/84 84/84 84/84
(100) (100) (100) (100) (100) (100) (100) (100) (100) (73.8) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100)
No. of gray zone data sets/ total no. of data sets (%) 0 0 0 0 0 0 0 0 0 20/84 (23.8) 0 0 0 0 0 0 0 0 0 0
NIPT, noninvasive prenatal testing.
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311 312 Trisomy 18 Trisomy 13 313 No. of gray 314 No. of correct No. of gray zone No. of positive zone data 315 data sets/total sets/total data sets/total data sets/total 316 no. of data no. of data no. of data no. of data 317 sets (%) sets (%) sets (%) sets (%) 318 319 84/84 (100) 0 84/84 (100) 0 320 84/84 (100) 0 84/84 (100) 0 321 66/84 (78.6) 18/84 (21.4) 84/84 (100) 0 322 84/84 (100) 0 84/84 (100) 0 323 84/84 (100) 0 83/84 (98.8) 1/84 (1.2) 324 84/84 (100) 0 84/84 (100) 0 325 84/84 (100) 0 84/84 (100) 0 326 84/84 (100) 0 84/84 (100) 0 327 84/84 (100) 0 84/84 (100) 0 328 84/84 (100) 0 84/84 (100) 0 329 44/84 (52.4) 26/84 (31.0) 84/84 (100) 0 330 84/84 (100) 0 84/84 (100) 0 331 84/84 (100) 0 83/84 (98.8) 1/84 (1.2) 332 84/84 (100) 0 84/84 (100) 0 333 84/84 (100) 0 84/84 (100) 0 334 84/84 (100) 0 84/84 (100) 0 335 84/84 (100) 0 62/84 (73.8) 21/84 (25.0) 336 84/84 (100) 0 84/84 (100) 0 337 84/84 (100) 0 84/84 (100) 0 338 84/84 (100) 0 84/84 (100) 0 339 340 341 342 with a FLUOstar Omega plate reader (BMG LABTECH). 343 The total concentration of 30 replicate samples was 344 345 recorded, and the average was used as the content of 346 cfDNA in 600 mL mixed plasma [value B (ng/mL)]. Last, 347 the fragmented gDNA samples extracted from placental 348 tissues were diluted by mixing with plasma to be used for preparation of 20 samples. Table 1 summarizes the ½T1 349 350 composition of the panel. The panel comprised 5 samples 351 from pregnant healthy women, 2 samples with sex chro352 mosome aneuploidies, and 13 samples positive for T21, 353 T18, and T13. To simulate samples positive for chro354 mosomal abnormalities, gDNA extracted from the 355 different abnormal placental tissues or cell lines was 356 357 chosen to reflect various abnormal cell-free fetal DNA, 358 such as T21, T18, T13, T21 chimera, and T18 chimera. In 359 addition, different amounts of gDNA were used to reflect 360 various fetal fraction ( ff) levels that could be present in 361 clinical samples, including 3.5%, 5%, and 8% ff. The 362 volumes of fragmented gDNA to be added into 50-mL 363 BD tubes were calculated according to the following 364 formula: A C/(A C þ B E) Z D, where D was the 365 desired ff to be simulated, C was the total volume of 366 fragmented gDNA, and E was the volume of plasma. 367 After production of each of the 20 samples, the prepa368 369 rations were dispensed in 700-mL volumes into 1.5-mL 370 siliconized vials. The vials were labeled by the National 371 Center for Clinical Laboratories NIPT 2014 and were 372
Panel Composition and Performance of 84 Laboratories for NIPT Testing
DNA to obtain different proportions of chimeric T21 and chimeric T18 DNA. gDNA was quantified using a FLUOstar Omega plate reader (BMG LABTECH, Ortenberg, Germany), fragmented with a focused ultrasonicator (Covaris, Inc., Woburn, MA), and then purified in a two-step process using AMPure XP beads (Agencourt Bioscience Corp., Beverly, MA). The expected size distribution of the resulting DNA fragments was 100 to 200 bp, which was confirmed by agarose gel electrophoresis, and fragmented DNA was quantified [value A (ng/mL)] using a FLUOstar Omega plate reader (BMG LABTECH). Second, samples of peripheral venous blood were collected from non-pregnant healthy women using EDTA tubes. Plasma was then separated from the blood samples by a two-step centrifugation method: whole blood was centrifuged at 1600 g for 10 minutes at 4 C, and the supernatants were transferred to 2.0-mL tubes. Samples were then centrifuged again under 16,000 g for 10 minutes in 4 C, and supernatants were transferred into clean bottles for storage and then allocated to 50-mL BD tubes (Becton Dickinson, Franklin Lakes, NJ). All plasma samples were pooled to obtain mixed plasma, and all procedures were completed within 4 hours. Cell-free DNA was extracted from 600 mL of mixed plasma using the Extraction and Purification Kit for Human Peripheral Blood Genomic DNA (BGI-Wuhan, Wuhan, People’s Republic of China), and DNA was quantified
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Commercial providers BGI BGI Daan Berry Genomics CapitalBio Illumina
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Information of Each Assay Involved in the EQA
ABI
Illumina Illumina
Sequencing platforms
Minimum no. of raw sequence data
Minimum Thresholds of Z values no. of unique sequence reads Positive Gray zone Negative
0.15 ng/mL 3 ng/mL >0.200 ng/mL 10 pM 1 nmol/L
>5M >6M NR >3.5M NR
>3.2M >2M 3.0M >1.8M 3.0M
2 ng/mL >3 pM >2 ng/mL >1 nmol/L >0.20 ng/mL 0.2 ng/mL 20 nmol/L >5 ng/mL
10M >5M 10M NR NR NR 6M 6M
4M 3M 4M >3M 3M >2M 4M >5M
No. of Minimum library data concentration sets
BGISEQ-100 (OEM of Ion Proton) 21 BGISEQ-1000 (OEM of CG) 3 DA8600 (OEM of Ion Proton) 3 NextSeq CN500 (OEM of NextSeq 500) 39 BioelectronSeq 4000 10 (OEM of Ion Proton) NextSeq 500 1 1 1 Ion Proton 1 1 1 Hiseq2000 1 Hiseq2500 1
>4 >4 >3.11 3 >3 0 > 3.5 >3 >3.5 >3 >3 >3 >4 >3.5
1.96w4 1.96w4 2.39w3.11 NA 2w3
<1.96 <1.96 <2.39 <3 <2
2.5w3.5 1.96w3 2.8w3.5 2w3 NA NA 2w4 2.5e3.5
2.5w2.5 <1.96 2.8w2.8 <2 <2 <3 <2 <2.5
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EQA, external quality assessment; NA, not applicable; NR, no requirement.
randomly assigned numbers from 1 through 20. The panels were stored at 70 C before shipment to the participating laboratories.
NIPT panel and clinical samples from their routine work. The pooled library was sequenced with a NextSeq CN500 sequencer using standard single-end 36 reads.
Validation of the NIPT Panel
Participants and Data Analysis
The NIPT panel was evaluated by the Shenzhen Birth Defect Screening Project Laboratory (BGI-Shenzhen, Shenzhen, People’s Republic of China) and by Berry Genomics (Beijing, People’s Republic of China) with the same processes as their routine patient sample testing. The BGI-Shenzhen group used a BGISEQ-100 sequencer (BGI-Wuhan). DNA samples were extracted from the NIPT panel using a Nucleic Acid Purification Kit (BGI-Wuhan) and then used for the construction of libraries using a Detection Kit for Noninvasive Fetal Trisomy (T21, T18, and T13; BGI-Wuhan), according to the manufacturer’s instructions. The libraries were quantified using a Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA), and 10 libraries with different labels were pooled and quantified. The pooled library was sequenced using a Universal Reaction Kit for Sequencing (BGI-Wuhan) and a BGISEQ-100 sequencer. The Berry Genomics group used a NextSeq CN500 sequencer (Berry Genomics-Hangzhou, Hangzhou, People’s Republic of China). DNA was extracted using the Cell-Free DNA Extraction Kit (Berry Genomics-Hangzhou) and constructed into libraries with a Libraries Construction and Purification Kit (Berry Genomics-Hangzhou). The StepOnePlus (Applied Biosystems, Carlsbad, CA) and Qubit 2.0 Fluorometer systems (Life Technologies, Carlsbad, CA) were used for the quantification and validation of the genomic libraries. Ninety-six libraries with different tags were pooled and quantified, including 20 samples in the
Coded test panels of frozen samples were shipped on dry ice to 85 clinical laboratories. All laboratories were assigned the same coded samples and were required to use their routine procedures. Detailed instructions for storage conditions and assay procedures were provided. Because the samples contained fragmented gDNA by sonication, end repair was needed in assay procedure, which was different from routine test. Laboratories were asked to submit their results of testing for fetal trisomy, Z values, and the threshold of Z values for positivity online within 2 weeks of the receipt of the test panel. To calculate Z values, the number of reads aligned to the reference genome in NIPT was counted and compared with that of the same chromosome of a reference pool of euploid pregnancy samples. The Z value of a chromosome represents the number of SDs away from the reference mean percentage of representation of that chromosome.3,21 A Z value more than threshold indicates a statistically significant deviation between the sample and reference for the chromosome. Questionnaires were also sent to obtain information regarding the procedures used (the platforms and reagents used for DNA extraction, protocols for construction, and sequencing of DNA libraries) and the assay-specific quality control (QC) criteria (minimum total DNA per sample, minimum library concentration, and minimum number of unique sequence reads alignable to the genome). All of the results that differed from the reference were considered unacceptable. All data analyses were performed using SPSS version 16.0. Q8
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EQA for NIPT in Clinical Laboratories 559 560 No. of correct data sets/ 561 No. of correct data sets/total no. No. of correct data sets/total no. total no. of data sets of 562 of data sets of trisomy 21 (%) of data sets of trisomy 18 (%) trisomy 13 (%) 563 Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample 564 1402 1410 1414 1415 1419 1403 1406 1408 1411 1418 1405 1413 1417 Assay 565 566 BGISEQ-100 21/21 5/21 21/21 21/21 21/21 16/21 21/21 21/21 1/21 21/21 21/21 21/21 5/21 567 (100) (23.8) (100) (100) (100) (76.2) (100) (100) (4.78) (100) (100) (100) (23.8) 568 BGISEQ-1000 3/3 0 3/3 3/3 3/3 2/3 21/21 21/21 0 21/21 3/3 3/3 3/3 569 (100) (100) (100) (100) (66.7) (100) (100) (100) (100) (100) (100) 570 3/3 3/3 3/3 3/3 DA8600 3/3 3/3 3/3 3/3 3/3 3/3 3/3 3/3 3/3 571 (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) 572 NextSeq 39/39 39/39 39/39 39/39 39/39 39/39 39/39 39/39 39/39 39/39 39/39 39/39 39/39 573 CN500 (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) 574 BioelectronSeq 10/10 10/10 10/10 10/10 10/10 3/10 10/10 10/10 0 10/10 10/10 10/10 10/10 575 4000 (100) (100) (100) (100) (100) (30) (100) (100) (100) (100) (100) (100) 576 NextSeq 500 3/3 2/3 3/3 3/3 3/3 0 3/3 3/3 0 3/3 3/3 3/3 0 577 (100) (66.7) (100) (100) (100) (100) (100) (100) (100) (100) 578 1/3 3/3 3/3 3/3 2/3 Ion Proton 3/3 66.7 3/3 3/3 3/3 3/3 3/3 3/3 579 (33.3) (100) (100) (100) (66.7) (100) (2/3) (100) (100) (100) (100) (100) (100) 580 Hiseq2000 1/1 0 1/1 1/1 1/1 0 1/1 1/1 0 1/1 1/1 1/1 0 581 (100) (100) (100) (100) (100) (100) (100) (100) (100) 582 Hiseq2500 1/1 1/1 1/1 1/1 1/1 0 1/1 1/1 0 1/1 0 0 0 583 (100) (100) (100) (100) (100) (100) (100) (100) 584 585 586 Comparison of quantitative data was made using the t-test. massively parallel sequencing to test the panel. The most 587 Correlations of variables were evaluated with Spearman common assay used was Berry Genomics NextSeq CN500 588 correlation analysis. P < 0.05 was regarded to be statisti[39 of 84 (46.4%)], followed by BGISEQ-100 [21 of 589 cally significant. 84 (25.0%)], BioelectronSeq 4000 (CapitalBio, Beijing, 590 People’s Republic of China) [10 of 84 (11.9%)], BGISEQ591 1000 (BGI-Wuhan) [3 of 84 (3.6%)], DA8600 (Daan, 592 Results Guangzhou, People’s Republic of China) [3 of 84 (3.6%)], 593 594 NextSeq 500 (Illumina, San Diego, CA) [3 of 84 (3.6%)], Validation of NIPT Panel 595 Ion Proton (Applied Biosystems, Carlsbad, CA) [3 of 84 596 Samples containing effective ff >3.5% (including 70% (3.6%)], HiSeq 2000 (Illumina) [1 of 84 (1.2%)], and HiSeq 597 chimera samples containing 10% ff) were reported as posi2500 (Illumina) [1 of 84 (1.2%)]. QC requirements and the tive by both BGI-Shenzhen and Berry Genomics. The T21 thresholds of each assay are summarized in Table 2. All of ½T2 598 599 and T18 samples containing 3.5% ff were also correctly the laboratories declared that the results were reported when 600 identified by the two laboratories. Meanwhile, the T13 QC passed. The thresholds of most assays, except those of 601 sample containing 3.5% ff was initially recorded as gray NextSeq CN500 and of one assay using the Ion Proton 602 zone by BGI-Shenzhen but was confirmed to be positive platform, contain gray zones. 603 after retesting of the sample. Furthermore, 30% T21 and 604 T18 chimera samples were counted as negative by BGI605 NIPT Performance Testing 606 Shenzhen. In contrast, Berry Genomics correctly identified 607 all of the trisomy samples using NextSeq CN500 sequencer. The T21 samples containing ff values of 8%, 5%, and 3.5% 608 No false-positive results were reported by either of the and the T18 samples containing ff values of 8% and 5% were 609 laboratories. correctly identified by all 84 laboratories (Table 1). The T18 610 sample containing 3.5% ff was correctly identified by 78.6% 611 of the data sets, whereas 21.4% of laboratories reported gray Panel Distribution and Response 612 zone. All of the laboratories, except one laboratory using 613 Hiseq 2500, which reported gray zone, correctly identified the Each of the 85 laboratories, including 73 clinical/hospital 614 T13 samples containing 8% and 5% ff. Meanwhile, the T13 laboratories and 12 commercial laboratories, reported results 615 sample containing 3.5% ff was correctly identified by 73.8% before the closing date. A data set from one of the clinical 616 617 of the data sets, with 25.0% of laboratories reporting gray zone laboratories did not include all of the results for the panel. 618 and 1.2% of laboratories reporting negative. The T21 and T18 As a result, the data from this laboratory were not included 619 samples containing 10% (70% chimera) ff were also correctly in the analysis presented herein. Each laboratory used 620 Table 3
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Performance of Different Assays for Each Trisomy Sample
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T18, and T13 samples, 0.48% (2 of 420), 3.3% (14 of 420), and 0.4% (1 of 252) of the results were false negatives, respectively. In addition, 4.8% (20 of 420), 10.5% (44 of 420), and 9.1% (23 of 252) of the results for these samples were reported as gray zone, respectively. Table 3 summarizes the performance levels of the different ½T3 assay systems used. NextSeq CN500, which was the most widely used assay in this QC study, correctly identified all of the positive samples. Each of the other assays used, except the assay on the basis of HiSeq 2500, generated correct data sets for the T21, T18, and T13 samples containing effective ff >4%. We next compared Z values generated by the assays used by >10 laboratories (Figure 2). For tests detecting T18 and ½F2 T13, NextSeq 500 generated higher Z values than BGISEQ100 and BioelectronSeq 4000. The Z values of the three assays were similar when T21 was detected. Z values generated by BGISEQ-100 fluctuated greatly. The numbers of unique sequence reads reported by the laboratories using the NextSeq CN500 were much higher than BGISEQ-100 and BioelectronSeq 4000 (P < 0.0001) (Figure 3). There were no ½F3 significant correlations between the numbers of unique sequence reads and Z values from any sample generated by NextSeq 500, BGISEQ-100, and BioelectronSeq 4000 (P > 0.05).
Discussion
identified in all of the data sets. Conversely, the T21 sample containing 10% (30% chimera) ff was correctly identified in 73.8% of the data sets, whereas 23.8% of laboratories reported gray zone and 2.4% of laboratories reported negative. The T18 sample with 10% (30% chimera) ff was correctly identified in 52.4% of the data sets, with 31.0% of laboratories reporting gray zone and 16.7% of laboratories reporting negative. Five samples from pregnant healthy women and the two samples with sex chromosome aneuploidies were correctly identified by all of the laboratories. In total, only 55.6% (47 of 84) of the respondents correctly identified all of the samples in the panel. No falsepositive results were reported by any of the 84 laboratories; however, 17 false-negative and 87 gray zone results were reported, most [102 of 104 (98.1%)] of which were derived from trisomy samples with effective ff <4%. For the T21,
Multiple clinical validation studies presented high sensitivities, specificities, and negative predictive values for detection of T21, T18, and T13 by NIPT. These findings resulted in NIPT, by sequencing of cfDNA, being introduced as a method for clinical prenatal care. However, the EQA system for NIPT by next-generation DNA sequencing was not available. Ideally, the samples should be obtained from plasmas of pregnant women, but it is not feasible because of the limited amount of clinical samples. Herein, we prepared simulated samples by mixing fragmented abnormal gDNA with the plasma from non-pregnant women. Studies have previously shown that 80% of fetal-derived DNA has a size range of <193 bp,22 and a portion of fetal DNA molecules in plasma are <150 bp.23 The size distribution of the fragmented DNA in our artificial samples was 100 to 200 bp, which includes most of the sizes of fetal fraction.24 Both whole-genome and targeted MPS determine fetal ploidy state by comparing the ratio of cfDNA fragments from particular chromosomes in a test sample/reference values from euploid pregnancy samples.21,24,25 The Z value was then calculated to represent statistical deviations in the number of counts and ploidy state for that chromosome. Therefore, the synthetic samples are suitable for NIPT on the basis of MPS, such as MaterniT21 Plus,26 Verifi,27 Harmony Prenatal Test,25 and all assays in our study. There were also three limitations. First, the NIPT samples do not contain the fragments <100 bp, which could not assess the true efficiency of the testing laboratories in
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Figure 2 The Z values generated for trisomy samples in noninvasive prenatal testing panel by assays on the basis of BGISEQ-100, Bioelectron Seq 4000, and NextSeq CN500. The top, middle, and bottom lines in each box represent the 75th, 50th, and 25th percentiles of Z values, respectively. The error bars represent the maximum and minimum Z values.
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Figure 3
The numbers of unique sequence reads generated for the trisomy samples in noninvasive prenatal testing panel by assays on the basis of BGISEQ100, Bioelectron Seq 4000, and NextSeq CN500. The top, middle, and bottom lines in each box represent the 75th, 50th, and 25th percentiles of unique sequence reads, respectively. The error bars represent the maximum and minimum unique sequence reads. Numbers below the plot represent the chromosomal aneuploidies detected.
extracting short fetal DNA molecules. In addition, the distribution is different between random fragmented DNA and the cell-free DNA from apoptotic cells.24 Second, the DNA fragments in the plasma of non-pregnant women used in the study are shorter than those in the plasma of pregnant women.22 Third, the samples are not applicable for laboratories using the single-nucleotide polymorphism method, which use maternal genotypic information and recombination frequencies to construct possible fetal genotypes.28 Then, each hypothesis is compared with actual plasma measurements, and a relative likelihood for each hypothesis is calculated. Because the artificial fetal DNA is not genetically related to the background plasma DNA in our artificial samples, NIPT on the basis of the single-nucleotide polymorphism method, like Panorama Prenatal Test,28 is not suitable for our panel. However, given that all of the laboratories performed NIPT by MPS in this EQA, artificially fabricated samples are suitable to assess the performance of different workflows in individual laboratories. For T21 and T18 chimera samples in the EQA panel, cell lines were used, which were readily available and well-characterized.29 Notably, it is important to confirm the status of cells by karyotypic analyses when new gDNA samples are prepared, because numerical aberrations in chromosomes might occur occasionally during the passage of cell lines.30 Overall, most laboratories participating in this study have reliable diagnostic capacities for NIPT tests. No falsepositive results were reported by any of the 84 laboratories. Problems mainly existed in false-negative results, all of which were caused by the failure to consistently identify the samples containing effective ff <4%. According to previous clinical trials and routine clinical testing, the minimum ff needed for reliable NIPT results is regarded as
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approximately 4%,10,31 which is consistent with the results obtained by our analysis. Many factors can affect the ratio of fetal fraction, including delay of plasma separation, DNA extraction, gestation age, and overweight pregnant women.31,32 There are several approaches to quantify the ff for all pregnancies (ie, both male and female fetus), such as methods on the basis of locus-specific DNA methylation,33 MPS,34 and real-time quantitative PCR.35 However, quantification of ff is not routinely performed in clinical laboratories of People’s Republic of China, and clinical laboratories have no idea about whether the fetal DNA is adequate. Minimum ff should be another important QC parameter,36,37 and to measure ff would be helpful for laboratories to interpret the results when ff is lower than the limit of detection. We also noticed that T18 and T13 samples were correctly identified by fewer participants compared with T21 samples, which might correlate with GC-content bias. Chromosomes 13 and 18 both have a relatively lower GC percentage compared with chromosome 21; thereby, the CVs of read counts were higher.3 Thus, the Q9 sensitivities for T18 and T13 tend to be lower than T21.38 Several GC-biasecorrection models have been proposed to improve their sensitivities.39,40 In addition, DNA copy number losses or deletions in the maternal plasma could theoretically cause false-negative results,41 although no relevant clinical cases have been reported. Therefore, the biological reason of possible DNA copy number losses or deletions on chromosome 18 or 13 in plasma of nonpregnant women used could not be ruled out. Noticeably, 4.8% (20 of 420), 10.5% (44 of 420), and 9.1% (23 of 252) of the results for the T21, T18, and T13 samples, respectively, were reported as gray zone. In some assays,27 gray zone was used to address the samples
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unclassified and those results were followed by karyotype analysis. Other assays, such as the MaterniT21 PLUS assay, gave a straightforward threshold.26 In our study, the gray zone results were suggested to retest the sample according to the manuals for some assays. For example, the assays on the basis of the BGISEQ-100 platform recommend that if the Z value for a particular sample is between 1.96 and 4, the sample should be retested. If the Z value of the second test is 3, the sample should be reported as positive. Conversely, if Z < 3, the sample should be reported as negative. However, for the samples with low ff, retests could not lead to much improvement. Figure 2 showed that Z values of samples 1410, 1411, and 1417, reported by BGISEQ-100, varied in a large range. Therefore, retests could also miss the positive samples in a portion of laboratories according to the distribution of Z values. It might be better for the women whose results are gray zone to receive further genetic counseling, comprehensive ultrasound evaluation, and diagnostic testing.42 The laboratories using the NextSeq CN500 performed best and correctly identified all of the positive samples in the panel. NextSeq 500 generated much higher Z values than the threshold of 3. We also noticed that all of the CVs of Z values generated by BGISEQ-100 and BioelectronSeq 4000 were higher than NextSeq CN500 for the trisomy samples. Benn and Cuckle36 showed that SDs of measured ff for chromosome 21 were smaller for high unique reads, which would improve the precision of Z values and the performance of the tests. Therefore, higher aligned unique sequence reads generated by NextSeq 500 might contribute to better performance of the platform. However, Z values were not associated with the numbers of aligned reads for positive samples detected by any of the three assays in our study. So, factors influencing the correct read representation, like incorrect assignment of fragments because of sequencing errors or polymorphisms, GC-content bias introduced by PCR,43 and mappability of short reads to the repeat-rich regions of the genome,44 should be also essential for fetal aneuploidy detection. In conclusion, most clinical laboratories could detect samples containing effective ff >4%. Our study showed requirement for further laboratory training in the management of samples with low ff. For some assays, the precision of Z values needs to be improved. In our EQA for NIPT, detailed data analysis for the results was provided, so that all of the participants were aware about the performance of various methods and laboratories. We also provided the opportunity to retest samples if laboratories wanted to analyze their results. In the future, EQA for NIPT will be performed twice a year. The participants will be informed of the limitations of the test panel beforehand.
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2. Wright D, Syngelaki A, Bradburi I, Akolekar R, Nicolaides KH: Firsttrimester screening for trisomies 21, 18 and 13 by ultrasound and biochemical testing. Fetal Diagn Ther 2014, 35:118e126 3. Chiu RW, Chan KC, Gao Y, Lau VY, Zheng W, Leung TY, Foo CH, Xie B, Tsui NB, Lun FM, Zee BC, Lau TK, Cantor CR, Lo YM: Noninvasive prenatal diagnosis of fetal chromosomal aneuploidy by massively parallel genomic sequencing of DNA in maternal plasma. Proc Natl Acad Sci U S A 2008, 105:20458e20463 4. Lo YM, Chan KC, Sun H, Chen EZ, Jiang P, Lun FM, Zheng YW, Leung TY, Lau TK, Cantor CR, Chiu RW: Maternal plasma DNA sequencing reveals the genome-wide genetic and mutational profile of the fetus. Sci Transl Med 2010, 2:61ra91 5. Palomaki GE, Kloza EM, Lambert-Messerlian GM, Haddow JE, Neveux LM, Ehrich M, van den Boom D, Bombard AT, Deciu C, Grody WW, Nelson SF, Canick JA: DNA sequencing of maternal plasma to detect Down syndrome: an international clinical validation study. Genet Med 2011, 13:913e920 6. Sparks AB, Struble CA, Wang ET, Song K, Oliphant A: Noninvasive prenatal detection and selective analysis of cell-free DNA obtained from maternal blood: evaluation for trisomy 21 and trisomy 18. Am J Obstet Gynecol 2012, 206:319.e1e319.e9 7. Ashoor G, Syngelaki A, Wagner M, Birdir C, Nicolaides KH: Chromosome-selective sequencing of maternal plasma cell-free DNA for first-trimester detection of trisomy 21 and trisomy 18. Am J Obstet Gynecol 2012, 206:322.e1e322.e5 8. Nicolaides KH, Syngelaki A, Gil M, Atanasova V, Markova D: Validation of targeted sequencing of single-nucleotide polymorphisms for non-invasive prenatal detection of aneuploidy of chromosomes13, 18, 21, X and Y. Prenat Diagn 2013, 33:575e579 9. Nicolaides KH, Syngelaki A, Gil MM, Quezada MS, Zinevich Y: Prenatal detection of triploidy from cell-free DNA testing in maternal blood. Fetal Diagn Ther 2014, 35:212e217 10. Norton ME, Brar H, Weiss J, Karimi A, Laurent LC, Caughey AB, Rodriguez MH, Williams J 3rd, Mitchell ME, Adair CD, Lee H, Jacobsson B, Tomlinson MW, Oepkes D, Hollemon D, Sparks AB, Oliphant A, Song K: Non-Invasive Chromosomal Evaluation (NICE) Study: results of a multicenter prospective cohort study for detection of fetal trisomy 21 and trisomy 18. Am J Obstet Gynecol 2012, 207:137.e1e137.e8 11. Dan S, Wang W, Ren J, Li Y, Hu H, Xu Z: Clinical application of massively parallel sequencing-based prenatal noninvasive fetal trisomy test for trisomies21 and 18 in 11,105 pregnancies with mixed risk factors. Prenat Diagn 2012, 32:1225e1232 12. Gil MM, Akolekar R, Quezada MS, Bregant B, Nicolaides KH: Analysis of cell-free DNA in maternal blood in screening for aneuploidies: meta-analysis. Fetal Diagn Ther 2014, 35:156e173 13. Bianchi DW, Parker RL, Wentworth J, Madankumar R, Saffer C, Das AF, Craig JA, Chudova DI, Devers PL, Jones KW, Oliver K, Rava RP, Sehnert AJ; CARE Study Group: DNA sequencing versus standard prenatal aneuploidy screening. N Engl J Med 2014, 27: 799e808 14. Benn P, Borell A, Chiu R, Cuckle H, Dugoff L, Faas B, Gross S, Johnson J, Maymon R, Norton M, Odibo A, Schielen P, Spencer K, Huang T, Wright D, Yaron Y: Position statement from the Aneuploidy Screening Committee on behalf of the Board of the International Society for Prenatal Diagnosis. Prenat Diagn 2013, 33:622e629 15. American College of Obstetricians Gynecologists Committee on Genetics: Committee opinion No. 545: noninvasive prenatal testing for fetal aneuploidy. Obstet Gynecol 2012, 120:1532e1534 16. Gregg AR, Gross SJ, Best RG, Monaghan KG, Bajaj K, Skotko BG, Thompson BH, Watson MS: ACMG statement on noninvasive prenatal screening for fetal aneuploidy. Genet Med 2013, 15:395e398 17. Futch T, Spinosa J, Bhatt S, de Feo E, Rava RP, Sehnert AJ: Initial clinical laboratory experience in noninvasive prenatal testing for fetal aneuploidy from maternal plasma DNA samples. Prenat Diagn 2013, 33:569e574 18. Norton ME, Jacobsson B, Swamy GK, Laurent LC, Ranzini AC, Brar H, Tomlinson MW, Pereira L, Spitz JL, Hollemon D, Cuckle H,
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Musci TJ, Wapner RJ: Cell-free DNA analysis for noninvasive examination of trisomy. N Engl J Med 2015, 372:1589e1597 Vrachnis N, Vlachadis N, Creatsas G: DNA sequencing versus standard prenatal aneuploidy screening. N Engl J Med 2014, 371:578 Wang J, Wang W, Li R, Li Y, Tian G, Goodman L, et al: The diploid genome sequence of an Asian individual. Nature 2008, 456:60e65 Thung DT, Beulen L, Hehir-Kwa J, Faas BH: Implementation of whole genome massively parallel sequencing for noninvasive prenatal testing in laboratories. Expert Rev Mol Diagn 2015, 15:111e124 Chan KC, Zhang J, Hui AB, Wong N, Lau TK, Leung TN, Lo KW, Huang DW, Lo YM: Size distributions of maternal and fetal DNA in maternal plasma. Clin Chem 2004, 50:88e92 Fan HC, Blumenfeld YJ, Chitkara U, Hudgins L, Quake SR: Analysis of the size distributions of fetal and maternal cell-free DNA by pairedend sequencing. Clin Chem 2010, 56:1279e1286 Fan HC, Blumenfeld YJ, Chitkara U, Hudgins L, Quake SR: Noninvasive diagnosis of fetal aneuploidy by shotgun sequencing DNA from maternal blood. Proc Natl Acad Sci U S A 2008, 105:16266e16271 Sparks AB, Wang ET, Struble CA, Barrett W, Stokowski R, McBride C, Zahn J, Lee K, Shen N, Doshi J, Sun M, Garrison J, Sandler J, Hollemon D, Pattee P, Tomita-Mitchell A, Mitchell M, Stuelpnagel J, Song K, Oliphant A: Selective analysis of cell-free DNA in maternal blood for evaluation of fetal trisomy. Prenat Diagn 2012, 32:3e9 McCullough RM, Almasri EA, Guan X, Geis JA, Hicks SC, Mazloom AR, Deciu C, Oeth P, Bombard AT, Paxton B, Dharajiya N, Saldivar JS: Noninvasive prenatal chromosomal aneuploidy testingeclinical experience: 100,000 clinical samples. PLoS One 2014, 9:e109173 Bianchi DW, Platt LD, Goldberg JD, Abuhamad AZ, Sehnert AJ, Rava RP: Genome-wide fetal aneuploidy detection by maternal plasma DNA sequencing. Obstet Gynecol 2012, 119:890e901 Zimmermann B, Hill M, Gemelos G, Demko Z, Banjevic M, Baner J, Ryan A, Sigurjonsson S, Chopra N, Dodd M, Levy B, Rabinowitz M: Noninvasive prenatal aneuploidy testing of chromosomes 13, 18, 21, X, and Y, using targeted sequencing of polymorphic loci. Prenat Diagn 2012, 32:1233e1241 Gargis AS, Kalman L, Berry MW, Bick DP, Dimmock DP, Hambuch T, et al: Assuring the quality of next-generation sequencing in clinical laboratory practice. Nat Biotechnol 2012, 30:1033e1036 Filatov L, Golubovskaya V, Hurt JC, Byrd LL, Phillips JM, Kaufmann WK: Chromosomal instability is correlated with telomere erosion and inactivation of G2 checkpoint function in human fibroblasts expressing human papillomavirus type 16 E6 oncoprotein. Oncogene 1998, 16:1825e1838 Wang E, Batey A, Struble C, Musci T, Song K, Oliphant A: Gestational age and maternal weight effects on fetal cell-free DNA in maternal plasma. Prenat Diagn 2013, 33:662e666 Poon LC, Musci T, Song K, Syngelaki A, Nicolaides KH: Maternal plasma cell-free fetal and maternal DNA at 11-13 weeks’ gestation:
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External Quality Assessment for Detection of Fetal Trisomy 21, 18, and 13 by Massively Parallel Sequencing in Clinical Laboratories Q18
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Rui Zhang,* Hongyun Zhang,y Yulong Li,z Yanxi Han,* Jiehong Xie,* and Jinming Li* From the National Center for Clinical Laboratories* and the Graduate School,z Peking Union Medical College, Chinese Academy of Medical Sciences, National Center for Clinical Laboratories, Beijing Hospital, Beijing; and the BGI Clinical Laboratories-Shenzhen,y Shenzhen, People’s Republic of China Accepted for publication October 21, 2015.
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Address correspondence to Jinming Li, National Center for Clinical Laboratories, 1 Dahua Rd, Dongdan, Beijing 100730, People’s Republic of China. E-mail: jmli@nccl. org.cn.
An external quality assessment for detection of trisomy 21, 18, and 13 by massively parallel sequencing was implemented by the National Center for Clinical Laboratories of People’s Republic of China in 2014. Simulated samples were prepared by mixing fragmented abnormal DNA with plasma from non-pregnant women. The external quality assessment panel, comprising 5 samples from pregnant healthy women, 2 samples with sex chromosome aneuploidies, and 13 samples with different concentrations of fetal fractions positive for trisomy 21, 18, and 13, was then distributed to participating laboratories. In total, 55.6% (47 of 84) of respondents correctly identified each of the samples in the panel. Seventeen false-negative and 87 gray zone results were reported, most [102 of 104 (98.1%)] of which were derived from for trisomy samples with effective fetal fractions <4%. No laboratories generated false-positive results. In addition, we observed varied diagnostic capabilities of different assays, with the assay on the basis of NextSeq CN500 performing better than others, whereas Z values generated by BGISEQ-100 fluctuated greatly. There were no significant correlations between the numbers of unique sequence reads and Z values from any trisomy sample generated by BGISEQ-100. Overall, most clinical laboratories detected samples containing effective fetal fractions >4%. Our study shows need for further laboratory training in the management of samples with low fetal fractions. For some assays, precision of Z values needs to be improved. (J Mol Diagn 2016, -: 1e9; http://dx.doi.org/10.1016/j.jmoldx.2015.10.003)
Chromosomal aneuploidy is a common cause of birth defects, and trisomy 21 (T21), trisomy 18 (T18), and trisomy 13 (T13) are the most frequently occurring chromosomal abnormalities. Currently, the standard screening procedures for detecting chromosomal abnormalities involve a combination of first-trimester serum screening for biochemical markers, such as pregnancy-associated plasma protein-A, free b-human chorionic gonadotropin, and ultrasound measurement of the nuchal translucency thickness, with or without a measurement of second-trimester markers. Depending on the results of these screens, the definitive prenatal diagnosis, which includes amniocentesis or chorionic villus sampling, followed by chromosomal analysis, is performed in high-risk pregnancies. However, depending on the screening strategy used, the standard prenatal aneuploidy screening can only identify 50% to 95% of the
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anomalies, with false-positive screen rates of 5%.1,2 Hence, the sensitivity of current screening programs for fetal chromosomal aneuploidy is unsatisfactory, and the high rates of false-positive results lead to unnecessary invasive sampling, which add stress to the pregnancies. In recent years, noninvasive prenatal testing (NIPT) using cell-free DNA (cfDNA) sequences isolated from maternal blood samples has been introduced into clinical practice for the detection of T21, T18, and T13. Several approaches have been reported for the analysis of chromosomal cfDNA fragments using next-generation DNA sequencing Supported by the National Population and Family Planning Commission Q2 of the People’s Republic of China Special Fund for Health-Scientific Research in the Public Interest grant 201402018. Q3 Disclosures: None declared.
Copyright ª 2016 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.jmoldx.2015.10.003
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Figure 1
A flow diagram of the preparation, validation, and distribution of the samples in noninvasive prenatal testing external quality assessment
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technology, including whole genome massively parallel sequencing (MPS),3e5 targeted MPS,6,7 and analysis of single-nucleotide polymorphisms.8,9 The results of multiple clinical trials of NIPT were promising and demonstrated high sensitivity (up to 99%) and specificity, with low falsepositive rates (<0.1%).10e13 The International Society for Prenatal Diagnosis,14 the American College of Obstetricians and Gynecologists,15 and the American College of Medical Genetics and Genomics16 supported the proposal that pregnant women at high risk should be provided NIPT as a screening option for routine clinical care after receiving appropriate counseling. As the testing transitioned from clinical trials to clinical care, NIPT has become commercially available. There are many reports regarding the use of NIPT in the clinical laboratories.17e19 Recently, in People’s Republic of China, commercial vendors have simplified these bioinformatics analysis tools, and increasing clinical laboratories have shown interest in this new method for T21, T18, and T13 screening. Under the circumstances, external quality assessment (EQA) becomes an essential management measure to assess the proficiency and performance of various NIPT assays. It also ensures that laboratories maintain robust laboratory diagnostic capacities. However, it is hard to obtain enough clinical samples from pregnant
women having a fetus with trisomy. Therefore, we produced artificial specimens to simulate clinical samples. Herein, we described the first nationwide EQA study in People’s Republic of China, organized by the National Center for Clinical Laboratories (Beijing, People’s Republic of China), and discussed laboratory and assay performance for NIPT.
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Materials and Methods NIPT Panel Composition and Preparation Panels were prepared by the National Center for Clinical Laboratories using placental tissues with chromosomal aneuploidy, cultured cell lines, YH DNA (First Asian Diploid Genome, http://yh.genomics.org.cn, last accessed September 21, 2015),20 and peripheral venous blood from non-pregnant healthy women (Figure 1). First, genomic ½F1 DNA (gDNA) was extracted from placental tissues with T21, T18, T13, and abnormal sex chromosomes (XO/ XXX). Two cell lines (AG09802 and GM02732) with trisomies of chromosomes 21 and 13 were purchased from the Coriell Cell Repositories (Coriell, NJ). T21 and T18 DNAs were extracted from cultured cell lines using the DNA mini kit (Qiagen, Venlo, the Netherlands) and mixed with YH
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EQA for NIPT in Clinical Laboratories Table 1
Trisomy 21
Sample no.
Classification
No. of correct data sets/total no. of data sets (%)
1401 1402 1403 1404 1405 1406 1407 1408 1409 1410 1411 1412 1413 1414 1415 1416 1417 1418 1419 1420
Normal chromosome 8% T21 3.50% T18 XXX positive 8% T13 10% T18e70% chimera Normal chromosome 8% T18 Normal chromosome 10% T21e30% chimera 10% T18e30% chimera Normal chromosome 5% T13 5% T21 10% T21e70% chimera Normal chromosome 3.50% T13 5% T18 3.50% T21 XO positive
84/84 84/84 84/84 84/84 84/84 84/84 84/84 84/84 84/84 62/84 84/84 84/84 84/84 84/84 84/84 84/84 84/84 84/84 84/84 84/84
(100) (100) (100) (100) (100) (100) (100) (100) (100) (73.8) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100)
No. of gray zone data sets/ total no. of data sets (%) 0 0 0 0 0 0 0 0 0 20/84 (23.8) 0 0 0 0 0 0 0 0 0 0
NIPT, noninvasive prenatal testing.
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311 312 Trisomy 18 Trisomy 13 313 No. of gray 314 No. of correct No. of gray zone No. of positive zone data 315 data sets/total sets/total data sets/total data sets/total 316 no. of data no. of data no. of data no. of data 317 sets (%) sets (%) sets (%) sets (%) 318 319 84/84 (100) 0 84/84 (100) 0 320 84/84 (100) 0 84/84 (100) 0 321 66/84 (78.6) 18/84 (21.4) 84/84 (100) 0 322 84/84 (100) 0 84/84 (100) 0 323 84/84 (100) 0 83/84 (98.8) 1/84 (1.2) 324 84/84 (100) 0 84/84 (100) 0 325 84/84 (100) 0 84/84 (100) 0 326 84/84 (100) 0 84/84 (100) 0 327 84/84 (100) 0 84/84 (100) 0 328 84/84 (100) 0 84/84 (100) 0 329 44/84 (52.4) 26/84 (31.0) 84/84 (100) 0 330 84/84 (100) 0 84/84 (100) 0 331 84/84 (100) 0 83/84 (98.8) 1/84 (1.2) 332 84/84 (100) 0 84/84 (100) 0 333 84/84 (100) 0 84/84 (100) 0 334 84/84 (100) 0 84/84 (100) 0 335 84/84 (100) 0 62/84 (73.8) 21/84 (25.0) 336 84/84 (100) 0 84/84 (100) 0 337 84/84 (100) 0 84/84 (100) 0 338 84/84 (100) 0 84/84 (100) 0 339 340 341 342 with a FLUOstar Omega plate reader (BMG LABTECH). 343 The total concentration of 30 replicate samples was 344 345 recorded, and the average was used as the content of 346 cfDNA in 600 mL mixed plasma [value B (ng/mL)]. Last, 347 the fragmented gDNA samples extracted from placental 348 tissues were diluted by mixing with plasma to be used for preparation of 20 samples. Table 1 summarizes the ½T1 349 350 composition of the panel. The panel comprised 5 samples 351 from pregnant healthy women, 2 samples with sex chro352 mosome aneuploidies, and 13 samples positive for T21, 353 T18, and T13. To simulate samples positive for chro354 mosomal abnormalities, gDNA extracted from the 355 different abnormal placental tissues or cell lines was 356 357 chosen to reflect various abnormal cell-free fetal DNA, 358 such as T21, T18, T13, T21 chimera, and T18 chimera. In 359 addition, different amounts of gDNA were used to reflect 360 various fetal fraction ( ff) levels that could be present in 361 clinical samples, including 3.5%, 5%, and 8% ff. The 362 volumes of fragmented gDNA to be added into 50-mL 363 BD tubes were calculated according to the following 364 formula: A C/(A C þ B E) Z D, where D was the 365 desired ff to be simulated, C was the total volume of 366 fragmented gDNA, and E was the volume of plasma. 367 After production of each of the 20 samples, the prepa368 369 rations were dispensed in 700-mL volumes into 1.5-mL 370 siliconized vials. The vials were labeled by the National 371 Center for Clinical Laboratories NIPT 2014 and were 372
Panel Composition and Performance of 84 Laboratories for NIPT Testing
DNA to obtain different proportions of chimeric T21 and chimeric T18 DNA. gDNA was quantified using a FLUOstar Omega plate reader (BMG LABTECH, Ortenberg, Germany), fragmented with a focused ultrasonicator (Covaris, Inc., Woburn, MA), and then purified in a two-step process using AMPure XP beads (Agencourt Bioscience Corp., Beverly, MA). The expected size distribution of the resulting DNA fragments was 100 to 200 bp, which was confirmed by agarose gel electrophoresis, and fragmented DNA was quantified [value A (ng/mL)] using a FLUOstar Omega plate reader (BMG LABTECH). Second, samples of peripheral venous blood were collected from non-pregnant healthy women using EDTA tubes. Plasma was then separated from the blood samples by a two-step centrifugation method: whole blood was centrifuged at 1600 g for 10 minutes at 4 C, and the supernatants were transferred to 2.0-mL tubes. Samples were then centrifuged again under 16,000 g for 10 minutes in 4 C, and supernatants were transferred into clean bottles for storage and then allocated to 50-mL BD tubes (Becton Dickinson, Franklin Lakes, NJ). All plasma samples were pooled to obtain mixed plasma, and all procedures were completed within 4 hours. Cell-free DNA was extracted from 600 mL of mixed plasma using the Extraction and Purification Kit for Human Peripheral Blood Genomic DNA (BGI-Wuhan, Wuhan, People’s Republic of China), and DNA was quantified
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Zhang et al Table 2
Q11 Q12
Commercial providers BGI BGI Daan Berry Genomics CapitalBio Illumina
Q14 Q15
Information of Each Assay Involved in the EQA
ABI
Illumina Illumina
Sequencing platforms
Minimum no. of raw sequence data
Minimum Thresholds of Z values no. of unique sequence reads Positive Gray zone Negative
0.15 ng/mL 3 ng/mL >0.200 ng/mL 10 pM 1 nmol/L
>5M >6M NR >3.5M NR
>3.2M >2M 3.0M >1.8M 3.0M
2 ng/mL >3 pM >2 ng/mL >1 nmol/L >0.20 ng/mL 0.2 ng/mL 20 nmol/L >5 ng/mL
10M >5M 10M NR NR NR 6M 6M
4M 3M 4M >3M 3M >2M 4M >5M
No. of Minimum library data concentration sets
BGISEQ-100 (OEM of Ion Proton) 21 BGISEQ-1000 (OEM of CG) 3 DA8600 (OEM of Ion Proton) 3 NextSeq CN500 (OEM of NextSeq 500) 39 BioelectronSeq 4000 10 (OEM of Ion Proton) NextSeq 500 1 1 1 Ion Proton 1 1 1 Hiseq2000 1 Hiseq2500 1
>4 >4 >3.11 3 >3 0 > 3.5 >3 >3.5 >3 >3 >3 >4 >3.5
1.96w4 1.96w4 2.39w3.11 NA 2w3
<1.96 <1.96 <2.39 <3 <2
2.5w3.5 1.96w3 2.8w3.5 2w3 NA NA 2w4 2.5e3.5
2.5w2.5 <1.96 2.8w2.8 <2 <2 <3 <2 <2.5
Q13
Q16
EQA, external quality assessment; NA, not applicable; NR, no requirement.
randomly assigned numbers from 1 through 20. The panels were stored at 70 C before shipment to the participating laboratories.
NIPT panel and clinical samples from their routine work. The pooled library was sequenced with a NextSeq CN500 sequencer using standard single-end 36 reads.
Validation of the NIPT Panel
Participants and Data Analysis
The NIPT panel was evaluated by the Shenzhen Birth Defect Screening Project Laboratory (BGI-Shenzhen, Shenzhen, People’s Republic of China) and by Berry Genomics (Beijing, People’s Republic of China) with the same processes as their routine patient sample testing. The BGI-Shenzhen group used a BGISEQ-100 sequencer (BGI-Wuhan). DNA samples were extracted from the NIPT panel using a Nucleic Acid Purification Kit (BGI-Wuhan) and then used for the construction of libraries using a Detection Kit for Noninvasive Fetal Trisomy (T21, T18, and T13; BGI-Wuhan), according to the manufacturer’s instructions. The libraries were quantified using a Bioanalyzer 2100 (Agilent Technologies, Santa Clara, CA), and 10 libraries with different labels were pooled and quantified. The pooled library was sequenced using a Universal Reaction Kit for Sequencing (BGI-Wuhan) and a BGISEQ-100 sequencer. The Berry Genomics group used a NextSeq CN500 sequencer (Berry Genomics-Hangzhou, Hangzhou, People’s Republic of China). DNA was extracted using the Cell-Free DNA Extraction Kit (Berry Genomics-Hangzhou) and constructed into libraries with a Libraries Construction and Purification Kit (Berry Genomics-Hangzhou). The StepOnePlus (Applied Biosystems, Carlsbad, CA) and Qubit 2.0 Fluorometer systems (Life Technologies, Carlsbad, CA) were used for the quantification and validation of the genomic libraries. Ninety-six libraries with different tags were pooled and quantified, including 20 samples in the
Coded test panels of frozen samples were shipped on dry ice to 85 clinical laboratories. All laboratories were assigned the same coded samples and were required to use their routine procedures. Detailed instructions for storage conditions and assay procedures were provided. Because the samples contained fragmented gDNA by sonication, end repair was needed in assay procedure, which was different from routine test. Laboratories were asked to submit their results of testing for fetal trisomy, Z values, and the threshold of Z values for positivity online within 2 weeks of the receipt of the test panel. To calculate Z values, the number of reads aligned to the reference genome in NIPT was counted and compared with that of the same chromosome of a reference pool of euploid pregnancy samples. The Z value of a chromosome represents the number of SDs away from the reference mean percentage of representation of that chromosome.3,21 A Z value more than threshold indicates a statistically significant deviation between the sample and reference for the chromosome. Questionnaires were also sent to obtain information regarding the procedures used (the platforms and reagents used for DNA extraction, protocols for construction, and sequencing of DNA libraries) and the assay-specific quality control (QC) criteria (minimum total DNA per sample, minimum library concentration, and minimum number of unique sequence reads alignable to the genome). All of the results that differed from the reference were considered unacceptable. All data analyses were performed using SPSS version 16.0. Q8
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EQA for NIPT in Clinical Laboratories 559 560 No. of correct data sets/ 561 No. of correct data sets/total no. No. of correct data sets/total no. total no. of data sets of 562 of data sets of trisomy 21 (%) of data sets of trisomy 18 (%) trisomy 13 (%) 563 Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample Sample 564 1402 1410 1414 1415 1419 1403 1406 1408 1411 1418 1405 1413 1417 Assay 565 566 BGISEQ-100 21/21 5/21 21/21 21/21 21/21 16/21 21/21 21/21 1/21 21/21 21/21 21/21 5/21 567 (100) (23.8) (100) (100) (100) (76.2) (100) (100) (4.78) (100) (100) (100) (23.8) 568 BGISEQ-1000 3/3 0 3/3 3/3 3/3 2/3 21/21 21/21 0 21/21 3/3 3/3 3/3 569 (100) (100) (100) (100) (66.7) (100) (100) (100) (100) (100) (100) 570 3/3 3/3 3/3 3/3 DA8600 3/3 3/3 3/3 3/3 3/3 3/3 3/3 3/3 3/3 571 (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) 572 NextSeq 39/39 39/39 39/39 39/39 39/39 39/39 39/39 39/39 39/39 39/39 39/39 39/39 39/39 573 CN500 (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) (100) 574 BioelectronSeq 10/10 10/10 10/10 10/10 10/10 3/10 10/10 10/10 0 10/10 10/10 10/10 10/10 575 4000 (100) (100) (100) (100) (100) (30) (100) (100) (100) (100) (100) (100) 576 NextSeq 500 3/3 2/3 3/3 3/3 3/3 0 3/3 3/3 0 3/3 3/3 3/3 0 577 (100) (66.7) (100) (100) (100) (100) (100) (100) (100) (100) 578 1/3 3/3 3/3 3/3 2/3 Ion Proton 3/3 66.7 3/3 3/3 3/3 3/3 3/3 3/3 579 (33.3) (100) (100) (100) (66.7) (100) (2/3) (100) (100) (100) (100) (100) (100) 580 Hiseq2000 1/1 0 1/1 1/1 1/1 0 1/1 1/1 0 1/1 1/1 1/1 0 581 (100) (100) (100) (100) (100) (100) (100) (100) (100) 582 Hiseq2500 1/1 1/1 1/1 1/1 1/1 0 1/1 1/1 0 1/1 0 0 0 583 (100) (100) (100) (100) (100) (100) (100) (100) 584 585 586 Comparison of quantitative data was made using the t-test. massively parallel sequencing to test the panel. The most 587 Correlations of variables were evaluated with Spearman common assay used was Berry Genomics NextSeq CN500 588 correlation analysis. P < 0.05 was regarded to be statisti[39 of 84 (46.4%)], followed by BGISEQ-100 [21 of 589 cally significant. 84 (25.0%)], BioelectronSeq 4000 (CapitalBio, Beijing, 590 People’s Republic of China) [10 of 84 (11.9%)], BGISEQ591 1000 (BGI-Wuhan) [3 of 84 (3.6%)], DA8600 (Daan, 592 Results Guangzhou, People’s Republic of China) [3 of 84 (3.6%)], 593 594 NextSeq 500 (Illumina, San Diego, CA) [3 of 84 (3.6%)], Validation of NIPT Panel 595 Ion Proton (Applied Biosystems, Carlsbad, CA) [3 of 84 596 Samples containing effective ff >3.5% (including 70% (3.6%)], HiSeq 2000 (Illumina) [1 of 84 (1.2%)], and HiSeq 597 chimera samples containing 10% ff) were reported as posi2500 (Illumina) [1 of 84 (1.2%)]. QC requirements and the tive by both BGI-Shenzhen and Berry Genomics. The T21 thresholds of each assay are summarized in Table 2. All of ½T2 598 599 and T18 samples containing 3.5% ff were also correctly the laboratories declared that the results were reported when 600 identified by the two laboratories. Meanwhile, the T13 QC passed. The thresholds of most assays, except those of 601 sample containing 3.5% ff was initially recorded as gray NextSeq CN500 and of one assay using the Ion Proton 602 zone by BGI-Shenzhen but was confirmed to be positive platform, contain gray zones. 603 after retesting of the sample. Furthermore, 30% T21 and 604 T18 chimera samples were counted as negative by BGI605 NIPT Performance Testing 606 Shenzhen. In contrast, Berry Genomics correctly identified 607 all of the trisomy samples using NextSeq CN500 sequencer. The T21 samples containing ff values of 8%, 5%, and 3.5% 608 No false-positive results were reported by either of the and the T18 samples containing ff values of 8% and 5% were 609 laboratories. correctly identified by all 84 laboratories (Table 1). The T18 610 sample containing 3.5% ff was correctly identified by 78.6% 611 of the data sets, whereas 21.4% of laboratories reported gray Panel Distribution and Response 612 zone. All of the laboratories, except one laboratory using 613 Hiseq 2500, which reported gray zone, correctly identified the Each of the 85 laboratories, including 73 clinical/hospital 614 T13 samples containing 8% and 5% ff. Meanwhile, the T13 laboratories and 12 commercial laboratories, reported results 615 sample containing 3.5% ff was correctly identified by 73.8% before the closing date. A data set from one of the clinical 616 617 of the data sets, with 25.0% of laboratories reporting gray zone laboratories did not include all of the results for the panel. 618 and 1.2% of laboratories reporting negative. The T21 and T18 As a result, the data from this laboratory were not included 619 samples containing 10% (70% chimera) ff were also correctly in the analysis presented herein. Each laboratory used 620 Table 3
Q17
Performance of Different Assays for Each Trisomy Sample
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T18, and T13 samples, 0.48% (2 of 420), 3.3% (14 of 420), and 0.4% (1 of 252) of the results were false negatives, respectively. In addition, 4.8% (20 of 420), 10.5% (44 of 420), and 9.1% (23 of 252) of the results for these samples were reported as gray zone, respectively. Table 3 summarizes the performance levels of the different ½T3 assay systems used. NextSeq CN500, which was the most widely used assay in this QC study, correctly identified all of the positive samples. Each of the other assays used, except the assay on the basis of HiSeq 2500, generated correct data sets for the T21, T18, and T13 samples containing effective ff >4%. We next compared Z values generated by the assays used by >10 laboratories (Figure 2). For tests detecting T18 and ½F2 T13, NextSeq 500 generated higher Z values than BGISEQ100 and BioelectronSeq 4000. The Z values of the three assays were similar when T21 was detected. Z values generated by BGISEQ-100 fluctuated greatly. The numbers of unique sequence reads reported by the laboratories using the NextSeq CN500 were much higher than BGISEQ-100 and BioelectronSeq 4000 (P < 0.0001) (Figure 3). There were no ½F3 significant correlations between the numbers of unique sequence reads and Z values from any sample generated by NextSeq 500, BGISEQ-100, and BioelectronSeq 4000 (P > 0.05).
Discussion
identified in all of the data sets. Conversely, the T21 sample containing 10% (30% chimera) ff was correctly identified in 73.8% of the data sets, whereas 23.8% of laboratories reported gray zone and 2.4% of laboratories reported negative. The T18 sample with 10% (30% chimera) ff was correctly identified in 52.4% of the data sets, with 31.0% of laboratories reporting gray zone and 16.7% of laboratories reporting negative. Five samples from pregnant healthy women and the two samples with sex chromosome aneuploidies were correctly identified by all of the laboratories. In total, only 55.6% (47 of 84) of the respondents correctly identified all of the samples in the panel. No falsepositive results were reported by any of the 84 laboratories; however, 17 false-negative and 87 gray zone results were reported, most [102 of 104 (98.1%)] of which were derived from trisomy samples with effective ff <4%. For the T21,
Multiple clinical validation studies presented high sensitivities, specificities, and negative predictive values for detection of T21, T18, and T13 by NIPT. These findings resulted in NIPT, by sequencing of cfDNA, being introduced as a method for clinical prenatal care. However, the EQA system for NIPT by next-generation DNA sequencing was not available. Ideally, the samples should be obtained from plasmas of pregnant women, but it is not feasible because of the limited amount of clinical samples. Herein, we prepared simulated samples by mixing fragmented abnormal gDNA with the plasma from non-pregnant women. Studies have previously shown that 80% of fetal-derived DNA has a size range of <193 bp,22 and a portion of fetal DNA molecules in plasma are <150 bp.23 The size distribution of the fragmented DNA in our artificial samples was 100 to 200 bp, which includes most of the sizes of fetal fraction.24 Both whole-genome and targeted MPS determine fetal ploidy state by comparing the ratio of cfDNA fragments from particular chromosomes in a test sample/reference values from euploid pregnancy samples.21,24,25 The Z value was then calculated to represent statistical deviations in the number of counts and ploidy state for that chromosome. Therefore, the synthetic samples are suitable for NIPT on the basis of MPS, such as MaterniT21 Plus,26 Verifi,27 Harmony Prenatal Test,25 and all assays in our study. There were also three limitations. First, the NIPT samples do not contain the fragments <100 bp, which could not assess the true efficiency of the testing laboratories in
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Figure 2 The Z values generated for trisomy samples in noninvasive prenatal testing panel by assays on the basis of BGISEQ-100, Bioelectron Seq 4000, and NextSeq CN500. The top, middle, and bottom lines in each box represent the 75th, 50th, and 25th percentiles of Z values, respectively. The error bars represent the maximum and minimum Z values.
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EQA for NIPT in Clinical Laboratories
Figure 3
The numbers of unique sequence reads generated for the trisomy samples in noninvasive prenatal testing panel by assays on the basis of BGISEQ100, Bioelectron Seq 4000, and NextSeq CN500. The top, middle, and bottom lines in each box represent the 75th, 50th, and 25th percentiles of unique sequence reads, respectively. The error bars represent the maximum and minimum unique sequence reads. Numbers below the plot represent the chromosomal aneuploidies detected.
extracting short fetal DNA molecules. In addition, the distribution is different between random fragmented DNA and the cell-free DNA from apoptotic cells.24 Second, the DNA fragments in the plasma of non-pregnant women used in the study are shorter than those in the plasma of pregnant women.22 Third, the samples are not applicable for laboratories using the single-nucleotide polymorphism method, which use maternal genotypic information and recombination frequencies to construct possible fetal genotypes.28 Then, each hypothesis is compared with actual plasma measurements, and a relative likelihood for each hypothesis is calculated. Because the artificial fetal DNA is not genetically related to the background plasma DNA in our artificial samples, NIPT on the basis of the single-nucleotide polymorphism method, like Panorama Prenatal Test,28 is not suitable for our panel. However, given that all of the laboratories performed NIPT by MPS in this EQA, artificially fabricated samples are suitable to assess the performance of different workflows in individual laboratories. For T21 and T18 chimera samples in the EQA panel, cell lines were used, which were readily available and well-characterized.29 Notably, it is important to confirm the status of cells by karyotypic analyses when new gDNA samples are prepared, because numerical aberrations in chromosomes might occur occasionally during the passage of cell lines.30 Overall, most laboratories participating in this study have reliable diagnostic capacities for NIPT tests. No falsepositive results were reported by any of the 84 laboratories. Problems mainly existed in false-negative results, all of which were caused by the failure to consistently identify the samples containing effective ff <4%. According to previous clinical trials and routine clinical testing, the minimum ff needed for reliable NIPT results is regarded as
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approximately 4%,10,31 which is consistent with the results obtained by our analysis. Many factors can affect the ratio of fetal fraction, including delay of plasma separation, DNA extraction, gestation age, and overweight pregnant women.31,32 There are several approaches to quantify the ff for all pregnancies (ie, both male and female fetus), such as methods on the basis of locus-specific DNA methylation,33 MPS,34 and real-time quantitative PCR.35 However, quantification of ff is not routinely performed in clinical laboratories of People’s Republic of China, and clinical laboratories have no idea about whether the fetal DNA is adequate. Minimum ff should be another important QC parameter,36,37 and to measure ff would be helpful for laboratories to interpret the results when ff is lower than the limit of detection. We also noticed that T18 and T13 samples were correctly identified by fewer participants compared with T21 samples, which might correlate with GC-content bias. Chromosomes 13 and 18 both have a relatively lower GC percentage compared with chromosome 21; thereby, the CVs of read counts were higher.3 Thus, the Q9 sensitivities for T18 and T13 tend to be lower than T21.38 Several GC-biasecorrection models have been proposed to improve their sensitivities.39,40 In addition, DNA copy number losses or deletions in the maternal plasma could theoretically cause false-negative results,41 although no relevant clinical cases have been reported. Therefore, the biological reason of possible DNA copy number losses or deletions on chromosome 18 or 13 in plasma of nonpregnant women used could not be ruled out. Noticeably, 4.8% (20 of 420), 10.5% (44 of 420), and 9.1% (23 of 252) of the results for the T21, T18, and T13 samples, respectively, were reported as gray zone. In some assays,27 gray zone was used to address the samples
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Q10
unclassified and those results were followed by karyotype analysis. Other assays, such as the MaterniT21 PLUS assay, gave a straightforward threshold.26 In our study, the gray zone results were suggested to retest the sample according to the manuals for some assays. For example, the assays on the basis of the BGISEQ-100 platform recommend that if the Z value for a particular sample is between 1.96 and 4, the sample should be retested. If the Z value of the second test is 3, the sample should be reported as positive. Conversely, if Z < 3, the sample should be reported as negative. However, for the samples with low ff, retests could not lead to much improvement. Figure 2 showed that Z values of samples 1410, 1411, and 1417, reported by BGISEQ-100, varied in a large range. Therefore, retests could also miss the positive samples in a portion of laboratories according to the distribution of Z values. It might be better for the women whose results are gray zone to receive further genetic counseling, comprehensive ultrasound evaluation, and diagnostic testing.42 The laboratories using the NextSeq CN500 performed best and correctly identified all of the positive samples in the panel. NextSeq 500 generated much higher Z values than the threshold of 3. We also noticed that all of the CVs of Z values generated by BGISEQ-100 and BioelectronSeq 4000 were higher than NextSeq CN500 for the trisomy samples. Benn and Cuckle36 showed that SDs of measured ff for chromosome 21 were smaller for high unique reads, which would improve the precision of Z values and the performance of the tests. Therefore, higher aligned unique sequence reads generated by NextSeq 500 might contribute to better performance of the platform. However, Z values were not associated with the numbers of aligned reads for positive samples detected by any of the three assays in our study. So, factors influencing the correct read representation, like incorrect assignment of fragments because of sequencing errors or polymorphisms, GC-content bias introduced by PCR,43 and mappability of short reads to the repeat-rich regions of the genome,44 should be also essential for fetal aneuploidy detection. In conclusion, most clinical laboratories could detect samples containing effective ff >4%. Our study showed requirement for further laboratory training in the management of samples with low ff. For some assays, the precision of Z values needs to be improved. In our EQA for NIPT, detailed data analysis for the results was provided, so that all of the participants were aware about the performance of various methods and laboratories. We also provided the opportunity to retest samples if laboratories wanted to analyze their results. In the future, EQA for NIPT will be performed twice a year. The participants will be informed of the limitations of the test panel beforehand.
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