Clinical Implications and Limitations of Noninvasive Prenatal Testing for Detecting Fetal Copy Number Variations: A Multicenter Study in Shaanxi Province, China

Introduction

Genomic copy number variations (CNVs) involving the deletions or duplications of DNA segments constitute a major category of genetic variation associated with severe birth defects and neurodevelopmental disorders [1,2]. Unlike common aneuploidies (eg, trisomy 21), pathogenic CNVs (pCNVs) often involve dosage-sensitive genes that can lead to microdeletion and microduplication syndromes. These conditions manifest as intellectual disabilities, developmental delays, and organ malformations, yet many affected fetuses show no specific abnormalities on routine prenatal ultrasound [3–6]. The resulting diagnostic gap creates a substantial clinical and public health challenge, as early detection is crucial for informed reproductive decision-making and perinatal management.

With the rapid development of high-throughput sequencing and bioinformatics, a increasing number of studies suggests that noninvasive prenatal testing (NIPT) can detect microdeletion and microduplication syndromes with 40% to 50% accuracy, depending on the population risk and sequencing depth, conferring a certain clinical utility [7,8]. A critical knowledge gap remains regarding the real-world performance of NIPT for identifying specific CNV sizes and locations in diverse populations, particularly in non-selected or low-risk cohorts in which false positives can lead to unnecessary invasive procedures and maternal anxiety [9].

Therefore, the specific aim of this retrospective multicenter study was to evaluate the real-world diagnostic performance and limitations of NIPT for fetal CNVs in Shaanxi Province, China. This study provided comprehensive evidence on the positive predictive value (PPV) of NIPT for CNVs, and the influence of regional demographic factors. These findings are intended to refine clinical counseling strategies and optimize the diagnostic workflow for fetal CNVs.

Material and Methods

ETHICAL STATEMENTS:

This study was approved by the Ethics Committee of the First Affiliated Hospital of Xi’an Jiaotong University (2022–1393). Prior to the procedure, all participants received comprehensive genetic counseling, were fully informed of the risks associated with amniocentesis, and signed informed consent, which included consent for their data to be used in a research study.

STUDY DESIGN AND PARTICIPANTS:

This retrospective observational cohort study was conducted at the First Affiliated Hospital of Xi’an Jiaotong University, a regional referral center for NIPT and prenatal diagnosis in Shaanxi Province, China. The study period spanned from June 2023 to November 2024.

A total of 18 525 eligible participants who received NIPT prenatal screening were collected from the referral network of 38 hospitals; however, all sequencing and bioinformatic analysis were conducted at the Gene Joint Laboratory, First Affiliated Hospital of Xi’an Jiaotong University. Additionally, a total of 137 pregnant women who consented to prenatal diagnosis due to abnormal NIPT results were selected at the same period. Also, parental chromosome karyotype analysis or CNV sequencing were performed for genetic origin analysis.

INCLUSION AND EXCLUSION CRITERIA FOR NIPT SAMPLES:

The inclusion criterion was pregnant women who underwent NIPT screening at our center during the study period. This included women with high-risk indications (eg, advanced maternal age, abnormal serology) as well as those opting for NIPT as a first-tier screen.

The exclusion criteria were as follows: (1) multiple pregnancies (triplets or higher); (2) known maternal chromosomal abnormalities; (3) history of allogeneic transplantation, stem cell therapy, or recent blood transfusion (within 1 year), which could interfere with cell-free fetal DNA analysis; and (4) history of malignancy.

INCLUSION AND EXCLUSION CRITERIA FOR AMNIOCENTESIS:

All pregnant women received adequate genetic counseling before surgery, were fully informed about the risks of amniocentesis, and signed informed consent.

The inclusion criterion was pregnant women who pursued prenatal diagnosis due to abnormal NIPT screening at our center during the study period. NIPT indicated high risk of target chromosome (chromosome 13, 18, 21) aneuploidies, sex chromosome aneuploidies, other chromosome aneuploidies, and chromosome deletion or duplication.

The exclusion criteria were pregnant women with abnormal NIPT who refused prenatal diagnosis, considered abortion, and/or had preoperative axillary temperature >37.2°C twice, bleeding tendency, or pelvic or intrauterine infection signs.

CRITERIA FOR PARENTAL CNV SEQUENCING:

The inclusion criteria were as follows: (1) all pregnant women and the fathers underwent prenatal diagnosis due to abnormal CNVs via NIPT; (2) all parents provided informed consent and were willing to cooperate in the collection of peripheral blood samples; (3) no clear contraindications existed to sample collection (eg, severe coagulopathy); and (4) the clinical data were complete, and the phenotypic information and family history of the participants could be traced.

The exclusion criterion was one or both parents declining to participate in the validation.

IDENTIFICATION AND CONTROL OF VERIFICATION BIAS:

In this study, the potential sources of validation bias mainly included the following: (1) PPV estimates calculated only based on the subset of patients who opted for invasive prenatal diagnosis (129/218 positive cases); (2) subgroup analyses (eg, by city) limited by small numbers; (3) existence of some differences in baseline characteristics (such as disease severity and family cooperation) between the validation population and the total study population due to incomplete clinical data, loss to follow-up, or refusal to be tested.

To reduce the effect of validation bias, the following control measures were taken. (1) The inclusion criteria of the validation population were clarified to ensure the consistency of the validation process. (2) Descriptive analysis was performed on participants who did not complete the verification, to compare the differences in demographic characteristics and clinical phenotypes between participants who did not complete the verification and those who completed the verification, and to assess the potential impact of bias on the results.

NIPT SCREENING:

An amount of 10 mL peripheral blood was collected from the pregnant women. Plasma was separated by centrifugation. Circulating cell-free DNA was extracted by the fetal chromosome aneuploidy (T13/T18/T21) gene detection kit (BGI Biotechnology, China) to construct a library for sequencing. Each sample was sequenced using the MGISEQ-2000 platform. Samples that passed quality control criteria (Q30 ³85%, fetal fraction >4%, and uniquely mapped sequencing data >15 Mb per sample) were compared with the human genome reference sequence map, and additional findings beyond the scope of the standard NIPT report were identified through bioinformatic analysis.

AMNIOCENTESIS:

Under the guidance of ultrasound, 35 mL amniotic fluid was extracted by transabdominal puncture with a 22G needle, of which 20 mL was used for chromosome karyotype analysis and 5 mL was used for CNV sequencing.

CHROMOSOME KARYOTYPE ANALYSIS:

An amount of 20 mL amniotic fluid was equally packed into two 15-mL sterile centrifuge tubes and centrifuged at 1500 r/min for 10 min; the supernatant was discarded. The amniotic fluid cells were cultured independently by 2 lines in KaryoMAX RPMI 1640 medium supplemented with 10% fetal bovine serum and 1% phytohemagglutinin, at 37 °C in a 5% CO incubator. Banding was done with Giemsa staining and read using the MetaSystems imaging system according to the International System for Human Cytogenetics Nomenclature (ISCN) 2024.

CNV SEQUENCING AND BIOINFORMATIC ANALYSIS:

Genomic DNA was extracted from 5 mL amniotic fluid using nucleic acid extraction kits (MagPure Universal DNA KF, MGBio), and DNA concentration and purity were determined. The extracted genomic DNA was used to establish a library with the chromosome copy number aberration detection kit produced by Wuhan BGI Co, LTD, and the operation was performed according to the instructions. An Illumina Nextseq 500 high-throughput sequencing platform was used for sequencing. CNVs were classified as pathogenic, likely pathogenic, variants of uncertain significance, or benign based on American College of Medical Genetics and Genomics guidelines and databases (OMIM, DECIPHER, ClinGen).

STATISTICAL ANALYSIS:

Graphpad (10.2.3) software was used to process the data. Continuous variables are described as medians and ranges. The chi-square test or Fisher exact test was used for comparisons, and 95% confidence intervals (CIs) were calculated for PPVs. Subgroup analyses were considered exploratory. A P value <0.05 was considered statistically significant.

Results

INCIDENCE OF CNVS DETECTED BY NIPT AND ASSOCIATED FACTORS:

Among the 18 525 NIPT cases, 588 (3.17%,588/18525) presented abnormal results: 370 indicated high risk for chromosome aneuploidy, and 218 (1.18%, 218/18525) indicated abnormal CNVs. Of these, 137 pregnant women underwent prenatal diagnosis due to abnormal NIPT results from June 2023 to November 2024 (Figure 1). With our hospital serving as a referral center for NIPT in Shaanxi Province, China, our study collected samples from 38 hospitals across 7 prefecture-level cities, involving the cities of Xi’an, Weinan, Yulin, Hanzhong, Shangluo, Tongchuan, and Xianyang.

Analysis of the NIPT cohort revealed 29.00% (5373/18525) were ≥35 years of age; 21.70% (4021/18525) had abnormal serological screening; 2.66%(493/18525) had abnormal ultrasound findings; 97.80% (18116/18525) were singleton pregnancies; 95.09% (17616/18525) were natural conceptions; and 46.22% (85633/18525) were primiparous (Table 1).

Comparing women with abnormal CNV results (n=218) with those with normal results revealed significant differences (P<0.05) in gravidity, abnormal ultrasound findings, and city of residence. No significant differences were found for age, serological screening, or pregnancy method (P>0.05). Shangluo city had the highest rate of abnormal CNV findings by NIPT (2.08%; P<0.05).

PERFORMANCE OF NIPT SCREENING FOR CNV DETECTION:

Among the 218 pregnant women with abnormal CNVs through NIPT, 129 proceeded with fetal chromosome karyotype analysis and CNV sequencing, achieving a prenatal diagnosis rate of 59.17% (129/218). Parental blood samples were collected for CNV sequencing to ascertain genetic origin. Of 129 cases, 22 displayed abnormal ultrasound findings, predominantly fetal ventricular hyperechoic spots and fetal choroid plexus cysts. Following CNV sequencing validation, 62 cases were confirmed to align with NIPT results, yielding an overall PPV of 48.06% (62/129; 95% CI, 39.6%–56.6%). The PPV was significantly higher in cases with ultrasound abnormalities than in those without ultrasound abnormalities (69.57% vs 43.4%,16/23 vs 46/106; P<0.05). However, age, gravidity, and means of pregnancy showed no significant association with PPV (Table 2).

FACTORS INFLUENCING PPV AND PATHOGENICITY:

Table 3 shows the PPV and pathogenicity rate stratified by chromosome loci, size, type, city of residence, and gestational age. Abnormal CNVs were most frequent on chromosomes 18, 13, X, 22, and 21, comprising 62.02% (80/129). In contrast, no aberrations were observed on chromosomes 9 and 19 (Figure 2). Chromosome 18 exhibited the highest PPV of 83.33% (15/18), with 3 pCNVs, while chromosomes 13, 21, and X had moderate PPVs, at 52.17% (12/23), 50.00% (4/8) and 47.06% (7/17), respectively (P<0.05). The PPV for chromosome 22 was considerably lower, at 28.57% (4/14). There were 73 cases with CNV duplication, 54 cases with CNV deletion, and 2 cases with both duplication and deletion. Duplications had a higher PPV (56.00%, 42/75) than did deletions (41.07%, 23/56). Most CNVs were smaller than 5 Mb (73.64%, 95/129), with a PPV of 54.74% (52/95). CNVs between 5 and 10 Mb and larger than 10 Mb displayed lower PPVs but higher pathogenicity rate among true positives (P<0.05). Notably, 50% (9/18) of pCNVs were <5 Mb. The PPV showed a not statistically significant upward trend with increasing gestational age.

Hanzhong and Xi’an had higher PPVs of 55.56% (5/9) and 53.33% (40/75), respectively. Shangluo had a moderate PPV of 44.44% (4/9) while Weinan had the lowest PPV. The PPV for Yulin was 40.91% (9/22) but with a highest pathogenicity rate of 55.56% (5/9).

Genetic origin analysis was available for 45 cases, with 41 inherited paternally and 4 occurring de novo. Among the 67 false positives, maternal CNVs accounted for 41.8% (28/67), including 6 maternal pCNVs. NIPT data analysis suggested 5 fetal CNVs and 23 maternal CNVs as the source of the false positive signal. One case (case 9) was confirmed to exist an extra pCNV not detected by NIPT.

COMMON CNV SEGMENT IN MOST CASES:

In the cohort of 129 patients, the most frequently abnormal CNVs detected in NIPT were 22q11.21(n=14: 5 duplicates, 9 deletions), Xp22.31 (n=4, del), and 18p11.31-p11.23 (n=5: 4 duplicates, 1 deletion). Among the 5 cases suspected of 22q microduplication syndrome, 3 were true positives and 2 were false positves, yielding a PPV of 60%. Surprisingly, no cases of 22q11.21 microdeletion syndrome (DiGeorge syndrome) were detected. Among the 9 cases of suspected DiGeorge syndrome, 1 was a true positive with a variant of uncertain significance CNV, and 8 were false positives. In the cases of Xp22.31 deletions, there was 1 true positive and 3 false positives. There were 5 cases involving 18p11.31-p11.23, consisting of 4 duplications and 1 deletion. The PPV of that segment was reached 100% and all were pCNVs, as shown in Table 4.

CLINICAL FOLLOW-UP AND PREGNANCY OUTCOME:

Out of 129 cases, 18 exhibited pCNV. Of these, 14 were consistent with NIPT results, 3 cases (cases 1, 11, and 14) were identified as additional CNVs beyond those identified by NIPT, and 1 case (case 9) was completely different from the NIPT result (Table 5). Among the 7 cases with duplicated pCNVs, 3 presented with the 22q11.2 microduplication syndrome. Genetic origin analysis revealed 4 cases to be de novo and 6 to be maternally inherited. Following detailed genetic counseling, participants in 7 cases opted to terminate the pregnancy, while 3 chose to continue the pregnancy and newborns without any abnormal clinical phenotypes. Case 5 presented intrauterine fetal demise during routine prenatal examination, and case 10 delivered a stillborn child at 31 gestational weeks due to intrahepatic cholestasis of pregnancy. Unfortunately, 8 cases were lost to follow-up.

Additionally, among women undergoing prenatal diagnosis due to NIPT indicating aneuploidy, 8 were identified with abnormal CNVs instead of aneuploidy abnormality. In these cases, 3 led to pregnancy termination, 3 resulted in live births, with an infant (case 21) weighing less than 3 standard deviations. Two cases were lost to follow-up. Table 5 presents a detailed summary of pCNVs indicated by prenatal diagnosis in the 26 cases (18 from a CNV indication, 8 from an aneuploidy indication).

Discussion

In this study, we investigated the efficiency of NIPT for the detection of fetal CNVs and evaluated its clinical value in a large Chinese cohort of 18 525 pregnant women. Our core findings indicate that while NIPT can identify potential fetal CNVs with a moderate overall PPV of approximately 48% (95% CI, 39.6–56.6%), its performance varies significantly depending on chromosomal location, CNV type, the presence of ultrasound abnormalities, and geographic origin. The prevalence of pCNVs among confirmed cases was highest in Yulin. Furthermore, a substantial proportion of false positives were attributed to maternal genomic aberrations.

The observed overall PPV in our cohort was 48.06% (62/129), aligning with international benchmarks which generally report CNV PPVs between 30% and 50%, depending on the sequencing depth and algorithms used [10–12]. Compared with a similar large-scale study [13] in Shanxi Province evaluating NIPT in 32 394 pregnancies, our study specifically focused on the more complex landscape of CNVs in a distinct population (Shaanxi vs Shanxi). While their study confirmed the high sensitivity of NIPT for common trisomies (T21, T18, T13), our data suggest that for CNVs, the false-positive rate remains a significant challenge, often driven by maternal duplications and deletions that mask or mimic fetal signals. This moderate PPV underscores the critical need for confirmatory invasive prenatal diagnosis following a positive NIPT CNV result, as nearly half of these findings represent false positives. Importantly, among the true positives, only 28.57% were classified as pCNVs, highlighting that even when a CNV is confirmed, its clinical significance requires careful interpretation. This rate of pathogenicity among true positives is consistent with the understanding that many CNVs are benign or of uncertain significance [14].

Our analysis identified several factors significantly affecting NIPT’s accuracy for CNV detection. Consistent with prior research [10,11], factors such as maternal age, serological screening, method of pregnancy, and number of fetuses did not increase the incidence of fetal CNVs. Ultrasound abnormalities were the strongest predictor of a true positive CNV result. This reinforces the clinical value of integrating ultrasound assessment with NIPT results. When an ultrasound abnormality coexists with a positive NIPT CNV finding, the likelihood of a true fetal CNV is substantially increased, strengthening the case for prenatal diagnosis and potentially aiding in the interpretation of pathogenicity.

NIPT demonstrated a markedly higher PPV for CNVs on chromosome 18 (PPV 83.33%), compared with other chromosomes, particularly chromosome 22 (28.57%). This disparity likely reflects differences in genomic complexity, GC content, or the density of repetitive regions affecting sequencing coverage and bioinformatic analysis across chromosomes [15–17]. The exceptionally high PPV (100%) and pathogenicity rate observed for the 18p11.31-p11.23 segment warrants further investigation, potentially indicating a region where NIPT is highly reliable. However, the detection efficiency of other CNVs was low to moderate.

Duplication CNVs exhibited a higher PPV (56.00%) than deletions (41.07%), a finding also reported by others [18]. This difference may be attributed to technical challenges in detecting deletions, potentially due to lower signal-to-noise ratios or mapping biases. Intriguingly, CNVs smaller than 5 Mb showed a significantly higher PPV (54.74%) than larger CNVs. This is counter-intuitive given the technical challenges often associated with detecting smaller CNVs [19,20]. However, it is crucial to note that despite the higher PPV for small CNVs, 50% of the pathogenic CNVs identified in our study were smaller than 5 Mb. This highlights the clinical significance of small CNVs and underscores that, while technically challenging, their detection is vital, as they can be pathogenic. The lower PPV for larger CNVs might be influenced by factors such as placental mosaicism or maternal contributions, more readily confounding the signal for larger alterations.

While Shangluo showed a higher screening positive rate, and Yulin showed a higher proportion of pathogenic cases, these findings should be interpreted with caution due to the small sample sizes in the subgroup analyses. These variances may reflect random fluctuation rather than distinct regional genetic backgrounds.

NIPT has been frequently used for screening fetal CNVs, with a PPV of approximately 50%. However, its clinical utility remains debatable [21–23]. The accuracy of NIPT may be influenced by factors such as CNVs carried by pregnant woman, sequencing coverage, bioinformatics algorithms, and fetal DNA fraction [24–26]. In the present study, maternal genomic aberrations represent a significant source of false positives, accounting for 41.8% (28/67) of cases. This includes benign maternal CNVs and clinically significant maternal findings (6 cases), which can confound the fetal signal. Hence, to improve the accuracy of NIPT for fetal CNVs, it is imperative to discover more sophisticated methodologies for NIPT genetic origin analysis, augment its predictive capacity for fetal CNVs, and reduce unnecessary invasive procedures and psychological stress for pregnant women. Wang et al [1] identified genetic origin by comparing the chimerism ratio of CNV and the concentration of cell-free fetal DNA, resulting in PPVs in the fetal-CNV group of up to 85.71%. Xiang et al [27] developed a new pipeline that classifies CNVs into those of fetal, maternal, and maternal-fetal origin based on NIPT data, which led to a notable increase in the PPV of NIPT for detecting 22q11.2 DS from 87% to 94% and a reduction in the number of invasive tests by 8%. Huang et al [28] proposed an innovative NIPT method of collaborative allele targeted enrichment sequencing, which detected 54 fetal aneuploids, 8 microdeletion and microduplication syndromes, and 8 single gene variants among 1129 samples, achieving a sensitivity of 100% and a specificity of 99.3%. This novel NIPT assay is adept at pinpointing and neutralizing prevalent sources of NIPT interference factors, such as maternal CNVs and loss of heterozygosity. This groundbreaking test is termed NIPT2.0 in China, and expert consensus on the clinical application strategy of NIPT2.0 has been published [29].

Several limitations in this study should be acknowledged. First, the retrospective nature introduces selection bias. Only 59.17% of screen-positive women underwent invasive diagnosis. The true sensitivity and specificity cannot be fully calculated, as negative NIPT cases were not systematically verified. Women with more concerning results or ultrasound findings might have been more likely to undergo invasive testing, potentially inflating the observed PPV. Second, systematic follow-up on NIPT-negative cases was lacking, preventing the calculation of true sensitivity and specificity (false negatives). Third, maternal CNV status was not systematically separated in the initial screening phase, which likely contributed to the false-positive rate. Future research should focus on “NIPT-Plus” technologies that can better differentiate maternal vs fetal origins of CNVs and larger prospective cohorts to validate regional genetic differences.

Conclusions

In summary, NIPT demonstrates moderate performance for fetal CNV detection, with clinical utility primarily in selected high-risk pregnancies. The presence of ultrasound anomalies significantly increased PPV. Given the risk of false positives (often due to maternal CNVs) and verification bias, invasive diagnostic testing is mandatory for establishing a diagnosis. We recommend an ultrasound-guided algorithm whereby NIPT results are interpreted in the context of fetal structural scans and parental history.