Clinical application value of targeted amplicon sequencing technology in fetuses with uniparental disomy-related imprinting disorders: a multicenter study

Clinical application value of targeted amplicon sequencing technology in fetuses with uniparental disomy-related imprinting disorders: a multicenter study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Clinical application value of targeted amplicon sequencing technology in fetuses with uniparental disomy-related imprinting disorders: a multicenter study Ning Liu, Shengwen Huang, Bin Zhang, Yi Zhou, Chunyan Jin, Ping Sun, and 16 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5756870/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Nov, 2025 Read the published version in Journal of Translational Medicine → Version 1 posted 5 You are reading this latest preprint version Abstract Background To explore the application value of targeted amplicon sequencing (TA-seq) technology based on multiplex PCR and high-throughput sequencing in prenatal detection of uniparental disomy (UPD)-related imprinting disorders (ImpDis). Methods This retrospective study included 370 samples suspected of UPD from 42 hospitals across China. Of these, 294 samples were successfully tested by TA-seq and methylation multiplex ligation-dependent probe amplification (MS-MLPA), with MS-MLPA serving as the gold standard. Results TA-seq identified 36 positives and 258 negatives, of which 30 positives and 255 negatives were consistent with the findings from MS-MLPA. The sensitivity, specificity, positive predictive value, and negative predictive value of TA-seq were 90.9% (30/33), 97.7% (255/261), 83.3% (30/36), and 98.8% (255/258), respectively. The concordance between the two methods was 96.9% (285/294). Additionally, we observed potential false positives in UPD-related ImpDis testing indications. For instance, the '≥ 5 Mb ROH detected by SNP-array on chromosomes 6, 7, 11, 14, 15, or 20' group exhibited a positive rate of 11.0% (14/127), while the 'familial or de novo balanced Robertsonian translocation or isochromosome involving chromosome 14 or 15 based on CVS or amniocentesis' group and the 'de novo sSMC with no apparent euchromatic material in the fetus' group both demonstrated positive rates of 0% (0/23 and 0/6, respectively). Conclusions TA-seq proves to be a valuable method for prenatal screening of UPD-related ImpDis, significantly reducing false positives and thus easing the economic burden and anxiety for expectant parents. Its straightforward operation, adaptability, and reliability make it promising for future clinical use. Figures Figure 1 Figure 2 Figure 3 Introduction Imprinted genes are a group of genes regulated by epigenetic mechanisms, which are monoallelically expressed in a parent-of-origin-dependent manner. Abnormal imprinting—where both parental alleles are expressed or silenced simultaneously—can result in imprinting disorders (ImpDis). To date, a total of 13 distinct ImpDis have been clearly identified, primarily associated with chromosomes 6, 7, 11, 14, 15, and 20[ 1 ]. There are 4 types of molecular alterations in ImpDis, including uniparental disomy (UPD), copy number variation (CNV), single nucleotide variation (SNV), and imprinting defects[ 2 ]. UPD is an important alteration related to ImpDis. To date, nine UPD-related ImpDis have been well documented, including transient neonatal diabetes mellitus, Silver–Russell syndrome, Beckwith–Wiedemann syndrome, Temple syndrome, Kagami–Ogata syndrome, Prader–Willi syndrome, Angelman syndrome, Pseudohypoparathyroidism type 1B, and Mulchandani–Bhoj–Conlin syndrome[ 3 ]. UPD refers to the situation in which both homologous chromosomes are inherited exclusively from one parent. The typical mechanism of UPD involves two non-disjunction events occurring during meiosis and mitosis[ 4 ]. UPD can be further classified into heterodisomy (UPhD), isodisomy (UPiD), mixed UPD (mUPD), and segmental UPD. UPhD is defined as a pair of homologous chromosomes inherited from one parent. UPiD is defined as the duplication of a single chromosome inherited from one parent. mUPD is a mixed form of UPiD and UPhD, while segmental UPD refers to only part of a chromosome inherited from the same parent. UPD is not clinically rare, with an overall prevalence of approximately 1 in 2,000 births in the general population[ 5 ]. Nevertheless, only a small proportion of UPDs are pathogenic, resulting in imprinting disorders[ 1 , 6 ] or autosomal recessive disorders[ 7 ]. ImpDis have a profound effect on both the survival and overall quality of life for patients. Prenatal screening and diagnosis can help reduce the risk of these conditions. In 2020, the American College of Medical Genetics and Genomics (ACMG) released the first global statement on the prenatal and postnatal diagnosis of UPD[ 3 ]. China has also issued several consensus statements and guidelines regarding prenatal UPD testing in recent years, all of which emphasize the necessity of prenatal UPD and related ImpDis testing[ 8 – 11 ]. To date, several methods have been developed for prenatal UPD-related ImpDis testing, such as short tandem repeat analysis (STR), single nucleotide polymorphism array (SNP-array), exome sequencing (ES), targeted amplicon sequencing (TA-seq), and methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA). The applicability and cost of these methods vary significantly[ 2 , 9 ]. TA-seq involves multiplex PCR amplification of genomic regions of interest, followed by high-throughput sequencing. This technique is characterized by robustness, high sensitivity, and cost-effectiveness[ 12 ], making it widely applicable in various fields, such as pathogenic microorganisms, tumors, and genetic diseases[ 13 , 14 ]. Here, we developed a novel TA-seq technique for the prenatal detection of nine UPD-related ImpDis, and undertook a retrospective multicenter study to evaluate the performance of this approach. Materials and Methods Participant samples and clinical data were collected with informed consent and ethical approval from the Medical Ethics Committee of the First Affiliated Hospital of Zhengzhou University (Ethics Review Number: 2023-KY-0905-003). SUBJECTS We initially collected 370 samples of singleton pregnancies with a diverse set of UPD testing indications from 42 hospitals across China. Sample types included chorionic villi, amniotic fluid, cord blood, and products of conception. The inclusion criteria were primarily based on the UPD testing statement published by the American College of Medical Genetics and Genomics (ACMG) [ 3 ], with minor modifications. The exclusion criteria included: (1) twin or multiple pregnancies; (2) imprinting disorder caused by CNV; (3) consanguineous parents; (4) triploidy. GENOMIC DNA EXTRACTION AND QUALITY CONTROL Genomic DNA was extracted using the MagPure DNA Micro Kit (Magen, China), following the manufacturer’s instructions. The quality of the genomic DNA was assessed through agarose gel electrophoresis and quantified using a Qubit 3.0 fluorometer. To exclude maternal cell contamination, STR analysis was performed by quantitative fluorescence polymerase chain reaction (QF-PCR) utilizing the Microreader 21 Direct ID System (Microreader Genetics, China). PCR products were analyzed on an ABI 3130XL sequencer (Applied Biosystems, USA), and genotypes were scored with GeneMapper 4.0 (Applied Biosystems, USA). TA-SEQ According to the polymorphic SNP databases (dbSNP, gnomAD, ExAC, and 1000 Genomes), multiplex PCR primers were designed based on 1,230 SNP loci across the imprinted regions on chromosomes 6, 7, 11, 14, 15, and 20 (Fig. 2 ). The multiplex PCR reaction was performed in a 20 µL reaction system, including 5 µL of genomic DNA (4 ng/µL), 2 µL of M-primer (containing an index), 3 µL of UPD primer pool, and 10 µL of 2× multiplex PCR mix. The amplification conditions were as follows: 95°C for 2 minutes; 20 cycles of 95°C for 30 seconds and 60°C for 4 minutes; finally 72°C for 5 minutes; 4℃ forever. After products purification, the DNA fragments were used to construct a DNA library for high-throughput sequencing. The libraries were sequenced in single-end mode at 40 bp using the Nextseq 550AR sequencer (Annoroad, China). Each sample obtained a sequencing depth of approximately 1,000,000 raw reads. After sequencing, adapters and low-quality sequences were removed by Cutadapt (version 1.10). Reads were mapped to the human reference genome (GRCh37/hg19) using Burrows-Wheeler Aligner (version 0.7.15) with the mem algorithm. VarScan (version 2.4.3) was utilized for SNV calling. To predict UPiD, we calculated the probability of heterozygosity (number of heterozygous sites / total number of sites) for all amplicon regions across each chromosome. This probability value was then transformed by the log function to determine the likelihood of UPiD. The parental origin of each UPiD was determined to be ≥ 95% through calculating the sequence similarity if biological parents were available. To predict UPhD, it is essential to use biological parent samples. First, the sum of homozygous and heterozygous sites that are identical between the fetal and parental sequences is calculated. Next, the ratio of the sum to the intersection of the sites from both sequences is calculated. If the ratio is ≥ 95%, it can be judged as paternal or maternal UPhD. The formula used for determination of UPD is as follows: \(\:y=\prod\:f\left({x}_{i}\right)\) , where \(\:{x}_{i}\) represents the population frequency at each site; for UPiD, \(\:f\) represents the probability that the fetus is homozygous; and for UPhD, \(\:f\) represents the probability that the fetus shares the same genotype as its biological parents. MS-MLPA MS-MLPA serves as the gold standard. Methylation analysis of 7 imprinted loci ( PLAGL1, HYMAI, GRB10, MEST, H19, KCNQ1OT1, MEG3, MEG8, SNRPN, PEG3, NESP55, GNAS-AS1, GNASXL , and GNAS A/B ) was performed by MS-MLPA using the SALSA MS-MLPA Probemix ME034-C1 Multi-locus Imprinting kit (MRC-Holland, The Netherlands) according to the manufacturer’s protocol. To ensure the stability and accuracy of the results, all MS-MLPA experiments were uniformly conducted in the Genetic and Prenatal Diagnosis Center Laboratory of the First Affiliated Hospital of Zhengzhou University and were performed and analyzed by the same experimenter. Amplified products were analyzed using the ABI 3130XL sequencer (Applied Biosystems, USA) with the GeneMapper 4.0 (Applied Biosystems, USA). Values corresponding to peak areas were used for further data processing by Coffalyser V7 software (MRC-Holland, The Netherlands). The formula used for methylation dosage ratio (MR) was as follows: \(\:\text{M}\text{R}=(\text{P}\text{x}\:/\:\text{P}\text{c}\text{t}\text{r}\text{l}){\text{D}\text{i}\text{g}}_{}\:/\:(\text{P}\text{x}\:/\:\text{P}\text{c}\text{t}\text{r}\text{l}){\text{U}\text{n}\text{d}\text{i}\text{g}}_{}\) , where Px is the peak area of a given target probe, Pctrl is the sum of the peak areas of all control probes, Dig stands for HhaI digested sample, and Undig stands for undigested sample. STATISTICAL ANALYSIS Positive detection rate, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and concordance were analyzed using SPSS version 26 (IBM SPSS, USA). Categorical variables are presented as percentages, while continuous variables are presented as mean ± standard deviation. RESULTS SUBJECTS A total of 370 samples were recruited initially from 42 hospitals. Then 76 samples were excluded due to CNV, triploidy, consanguineous parents, maternal cell contamination, or insufficient DNA concentration for experiments. The remaining 294 samples were successfully assayed by TA-seq and MS-MLPA (Fig. 1 ). Maternal ages ranged from 19 to 45 years, with an average of 30.9 ± 5.2 years. The gestational weeks for chorionic villus sampling, amniocentesis, products of conception, and cordocentesis were 9‒13 (11.8 ± 1.1), 16‒33 (20.4 ± 3.5), 6‒26 (10.6 ± 4.3), and 26‒36 (30.1 ± 2.5), respectively. The types of 294 samples were mainly amniotic fluid, including 209 cases of amniotic fluid, 38 cases of chorionic villi, 38 cases of products of conception, and 9 cases of umbilical cord blood. There were great differences in the sample size among the 6 testing indication groups. The ‘≥ 5Mb region of homozygosity (ROH) detected by SNP-array on chromosomes 6, 7, 11, 14, 15, or 20’ group (GROUP-ROH) contained the largest number of samples (n = 127), followed by the ‘trisomy or monosomy of chromosomes 6, 7, 11, 14, 15, or 20 was detected by non-invasive prenatal screening, but disomy or mosaicism was detected by prenatal diagnosis’ group (GROUP-NIPS), which had 78 samples. The remaining indication groups, including ‘≥ 10% mosaicism for trisomy or monosomy detected by prenatal diagnosis’ (GROUP-MOSAIC), ‘familial or de novo balanced Robertsonian translocation or isochromosome involving chromosome 14 or 15 based on CVS or amniocentesis’ (GROUP-RT), ‘whole-genome paternal UPD detected by SNP-array’ (GROUP-CHM), and ‘de novo small supernumerary marker chromosomes (sSMC) with no apparent euchromatic material in the fetus’ (GROUP-sSMC) contained 43, 23, 17, and 6 cases, respectively. In addition, in GROUP-RH, 95.7% (22/23) of cases were chromosome 14-related. MS-MLPA RESULTS 294 samples underwent MS-MLPA testing, with no microdeletions found within the probe range, ensuring that methylation alteration was not due to microdeletions. MS-MLPA detected 33 cases of methylation alteration (Supplementary Table 1), including 1 case with loss of methylation (LoM) of PLAG1 :TSS-DMR, 7 cases with gain of methylation (GoM) of PLAG1 :TSS-DMR, 1 case with GoM of MEG3 :TSS-DMR and LoM of MEG8 :int2-DMR, 2 cases with LoM of MEG3 :TSS-DMR and GoM of MEG8 :int2-DMR, 5 cases with GoM of SNRPN , and 17 cases with GoM of all paternal imprinted alleles and LoM of all maternal imprinted alleles. TA-SEQ PERFORMANCE The total positive detection rate of TA-seq was 12.2% (36/294). Compared to the gold standard (MS-MLPA), TA-seq detected 30 true positives, 6 false positives, 3 false negatives, and 255 true negatives. The sensitivity, specificity, PPV, and NPV of TA-seq were 90.9% (30/33), 97.7% (255/261), 83.3% (30/36), and 98.8% (255/258), respectively. The concordance between the two methods was 96.9% (285/294). FALSE NEGATIVES AND FALSE POSITIVES One false negative case belonged to GROUP-NIPS with the specific indication that ‘trisomy 15 was detected by NIPS but disomy 15 by CNV-seq.’ The other two false negatives belonged to GROUP-ROH, with the specific indication that ‘25.7 Mb ROH on chromosome 15 detected by SNP-array at 15q14q22.2’ and ‘37.3 Mb ROH on chromosome 14 detected by SNP-array at 14q11.2q23.1,’ respectively (Table 1 ; Supplementary Fig. 1A-1C). Five false positives belonged to GROUP-ROH with the lengths of ROH from 5.7 to 11 Mb. The remaining one case, in GROUP-NIPS, had the specific indication that ‘trisomy 7 was detected by NIPS but disomy 7 by CNV-seq’ (Table 1 ; Supplementary Fig. 1D-1I). Table 1 Summary of 3 false negatives and 6 false positives. a TA-seq MS-MLPA Indication group Specific indications 1 Not detected GoM of SNRPN GROUP-NIPS trisomy 15 was detected by NIPS but disomy 15 by CNV-seq 2 Not detected GoM of SNRPN GROUP-ROH 25.7 Mb ROH on chromosome 15 detected by SNP-array at 15q14q22.2 3 Not detected GoM of MEG3 :TSS-DMR and LoM of MEG8 :int2-DMR GROUP-ROH 37.3 Mb ROH on chromosome 14 detected by SNP-array at 14q11.2q23.1 4 UPD(6) No methylation alteration GROUP-ROH 7.2 Mb ROH detected by SNP-array at 6q24.1q24.3 5 UPD(6) No methylation alteration GROUP-ROH 5.7 Mb ROH detected by SNP-array at 6q23.3q24.2. 6 UPD(6) No methylation alteration GROUP-ROH 11 Mb ROH detected by SNP-array at 6q23.3q25.1 7 UPD(7) No methylation alteration GROUP-ROH 25.6 Mb ROH detected by SNP-array at 7q22.3q32.3 8 UPD(11) No methylation alteration GROUP-NIPS trisomy 7 was detected by NIPS but disomy 7 by CNV-seq 9 UPD(20) No methylation alteration GROUP-ROH 10.4 Mb ROH detected by SNP-array at 20q13.2q13.33 a Abbreviations: LoM, loss of methylation; GoM, gain of methylation. CNV-seq, copy number variation sequencing; ROH, region of homozygosity. POSITIVE DETECTION RATES OF TA-SEQ AND MS-MLPA UNDER 6 TESTING INDICATION GROUPS The sample sizes under different indication groups varied widely, while the trends of positive detection rates between TA-seq and MS-MLPA were similar (Fig. 3 ). GROUP-CHM had the highest positive detection rates for TA-seq and MS-MLPA, both of which were 100% (17/17). GROUP-ROH had the positive detection rates of 13.4% (17/127) and 11.0% (14/127) for TA-seq and MS-MLPA, respectively. GROUP-MOSAIC had the positive detection rates of 2.3% (1/43) for both methods. GROUP-NIPS had the positive detection rates of 1.3% (1/78) for both methods. In GROUP-RT and GROUP-sSMC, no positive cases were identified by TA-seq or MS-MLPA. Discussion In this study we performed a multicenter retrospective study a novel established TA-seq technique for prenatal detection of UPD-related ImpDis. TA-seq exhibits high sensitivity, specificity, PPV, and NPV, indicating high detection efficiency, beyond its good concordance with MS-MLPA. CAUSES OF FALSE NEGATIVES AND FALSE POSITIVES The SNP-array results allow us to readily determine the causes of the two false negatives: As the ROHs (14q11.2q23.1 and 15q14q22.2) fall outside the imprinted regions of 14q32.2 and 15q11.2q13, respectively, they were necessarily missed by TA-seq in single-sample mode. The remaining false negative, despite not being tested by SNP-array, we speculate that its UPD type may either be mUPD with ROH outside the imprinted region or be UPhD without any ROH. Indeed, missed detection of UPhD in single-sample mode is a common problem for all DNA sequence-based techniques (including STR, SNP-array, WES, etc.). Hoppman et al. [ 15 ]reported that 33% of UPD cases could be missed by single-sample SNP-array due to the lack of extended ROH. Since TA-seq was designed to focus on imprinted regions rather than the entire chromosome, single-sample TA-seq may have a higher missed detection rate compared to other techniques. This problem could be solved by performing TA-seq in a trio-based mode. We previously carried out trio-based TA-seq on peripheral blood samples, successfully identifying all instances of mUPD and UPhD (unreported data). Even though we have great confidence in prenatal samples, more samples are required for further study. Moreover, the trio-based analysis can help determine UPD pathogenicity and specific ImpDis. For instance, paternal UPD(6) or maternal UPD(7) is pathogenic, but maternal UPD(6) or paternal UPD(7) is not. The single-sample analysis can only provide a UPD result without parental origin, making it impossible to determine its pathogenicity. As for UPD(11), (14), (15), or (20), although both paternal and maternal UPD are pathogenic, they will lead to different ImpDis. For instance, maternal UPD(11) and paternal UPD(11) can cause Silver–Russell syndrome and Beckwith–Wiedemann syndrome, respectively; paternal UPD(15) and maternal UPD(15) can cause Angelman syndrome and Prader–Willi syndrome, respectively. It is obvious that the trio-based analysis would be more conducive to disease diagnosis and treatment than the single-sample analysis. Regrettably, given the retrospective study design, the parental samples were not available. We plan to carry out a prospective cohort study using trio-based TA-seq in the future. False positives are twice as common as false negatives due to several factors, including limited SNP loci, ROH calculation methods, threshold settings, and consanguinity. False positives increase the workload for subsequent diagnosis and genetic counseling, along with parental psychological stress. We will continue to improve the false positive rate by expanding the coverage area of the amplicons, increasing the number of positive samples, improving ROH calculation methods, and optimizing thresholds. DIFFERENCES IN POSITIVE DETECTION RATES UNDER DIFFERENT TESTING INDICATION GROUPS Positive detection rates ranged from 0–100% under 6 testing indication groups. GROUP-CHM and GROUP-ROH exhibit the high positive rates, suggesting that large ROH are the most effective indicators for UPD. We also observed that in GROUP-ROH chromosome 6, 14, or 15 had higher true positive rates than chromosome 7, 11, or 20. The low true positive rates for 7, 11, or 20 could be due to the population polymorphic ROHs that have been reported in some domestic and international population studies, such as 7q11.22q11.23[ 16 ], 11p11.2p11.12[ 16 , 17 ], and 20q11.21q11.23[ 16 , 18 ]. In this study we observed 20 samples with 7q11.22q11.23, 7 samples with 11p11.2p11.12, and 9 samples with 20q11.21q11.23, which accounts for 46.5%, 26.9%, and 60% of the samples with ≥ 5Mb ROH on chromosome 7, 11, or 20, respectively. All these samples were proved to be false positives, suggesting that ROHs at those chromosomal locations are not reliable indicators of UPD for the Chinese population. Recent studies have reported that high-risk of aneuploidy through NIPS is also an indicator for detecting UPD. For instance, Ngo et al.[ 19 ] reported 2 cases of UPD(9), 1 case of UPD(15), and 2 cases of UPD(16) among 35 high-risk pregnant women detected by NIPS. Hu et al.[ 20 ] found 30 cases of UPD from 528 high-risk pregnant women, including 5 cases of UPD(6), 5 cases of UPD(7), 1 case of UPD(11), 1 case of UPD(14), and 1 case of UPD(15). Additionally, there are several case reports involving UPD(6) [ 21 ] and UPD(15) [ 22 , 23 ]. In our study, we enrolled 78 cases with high-risk of NIPS, including 3, 44, 6, 9, 11, and 5 cases for trisomy 6, 7, 11, 14, 15, and 20, respectively. MS-MLPA finally confirmed 1 case with methylation anomaly of chromosome 15. Combining all of the above evidence, it appears that the high risk of NIPS for different chromosomes has varying weights for UPD indication; specifically, aneuploidy of chromosomes 6 or 15 is more indicative. Addtionally, we observed a high false positive rate under different indication groups, and TA-seq could greatly decrease false positives. Using trio-based TA-seq as a testing strategy, we believe UPD-related ImpDis could be effectively tested together with a reduced diagnosis cost and psychological stress of pregnant women. ADVANTAGES AND APPLICATION OF TA-SEQ STR anlysis, SNP-array, and WES are currently-used methods for detecting UPD-related imprinting disorders. Due to the probe coverage of SNP-array and WES, they are able to detect mUPD cases with ROH occurring in non-imprinted regions, which cannot be detected by STR analysis or TA-seq. However, SNP-array and WES are primarily used to detect CNV and SNV, but their costs are too high for UPD detection. Both STR analysis and TA-seq are relatively low-cost, but the former relies on first-generation sequencing platforms. This implies additional experimental space and costs for a prenatal molecular testing laboratory utilizing next-generation sequencing platforms. In contrast, TA-seq demonstrates superior compatibility because its sequencing strategy aligns seamlessly with NIPS or CNV-seq, thereby reducing experimental time and workload. Furthermore, TA-seq could compensate for the shortcomings of CNV-seq, which cannot detect UPD-related ImpDis. LIMITATIONS OF THIS STUDY There are also limitations in this study. The first is the lack of validation of trio-based TA-seq using prenatal samples, and the second is the limited number of true positive cases. Moreover, the true positives are concentrated on chromosomes 6, 14, and 15. Therefore, we need to further enlarge the positive samples especially for chromosomes 7, 11, and 20 in the future to more fully assess the potential clinical efficacy of TA-seq. Abbreviations ImpDis, imprinting disorders; CNV, copy number variation; SNV, single nucleotide variation; UPD, uniparental disomy; UPhD, uniparental heterodisomy; UPiD, uniparental isodisomy; mUPD, mixed uniparental disomy; ACMG, American College of Medical Genetics and Genomics; TA-seq, targeted amplicon sequencing; MS-MLPA, methylation-specific multiplex ligation-dependent probe amplification; STR, short tandem repeat; SNP-array, single nucleotide polymorphism array; ES, exome sequencing; QF-PCR, quantitative fluorescence polymerase chain reaction; NIPS, non-invasive prenatal screening; sSMC, small supernumerary marker chromosomes; ROH, regions of homozygosity; GROUP-ROH, ‘≥ 5Mb ROH detected by SNP-array on chromosomes 6, 7, 11, 14, 15, or 20’ group; GROUP-NIPS, ‘trisomy or monosomy of chromosomes 6, 7, 11, 14, 15, or 20 was detected by non-invasive prenatal screening, but disomy or mosaicism was detected by prenatal diagnosis’ group; GROUP-MOSAIC, ‘≥ 10% mosaicism for trisomy or monosomy detected by prenatal diagnosis’ group; GROUP-RT, ‘familial or de novo balanced Robertsonian translocation or isochromosome involving chromosome 14 or 15 based on CVS or amniocentesis’ group; GROUP-CHM, ‘whole-genome paternal UPD detected by SNP-array’ group; GROUP-sSMC, ‘de novo small supernumerary marker chromosomes with no apparent euchromatic material in the fetus’ group. Declarations Acknowledgements We gratefully acknowledge all the participants and staff involved in this multicenter observational study. Especially we thank to Annoroad Gene Technology for technical support. Authors’ contributions Ning Liu and Xiangdong Kong conceived and designed the study, wrote the study protocol, and contributed to the acquisition of clinical data. Lina Liu, Yin Feng and Panlai Shi performed the experiments, statistical analyses. All of the authors reviewed and commented on the manuscript and approved the final version. Funding This study was supported by Special Fund for Key Research, Development and Promotion of Science and Technology of Henan Province (222102520018). Availability of data and materials The datasets used in the current study are available from the corresponding author on reasonable request. Ethics approval and consent to participate Donors and patient provided written informed consent. Consent for publication All authors consent for publication. Competing interests The authors declare that they have no competing interests. Author details 1 The First Affiliated Hospital of Zhengzhou University, Henan, China. 2 Guizhou Provincial People's Hospital, Guizhou, China. 3 Changzhou Maternal and Child Health Care Hospital, Jiangsu, China. 4 The First Affiliated Hospital, Sun Yat-sen University, Guangdong, China. 5 The Affiliated Taizhou People's Hospital of Nanjing Medical University, Jiangsu, China. 6 Qilu Hospital of Shandong University, Shandong, China. 7 Wuxi Maternal and Child Health Care Hospital, Jiangsu, China. 8 Sichuan Provincial Maternity and Child Health Care Hospital, Sichuan, China. 9 Shiyan People's Hospital, Hubei, China. 10 Jinan Maternal and Child Health Care Hospital, Shandong, China. 11 The Second Affiliated Hospital of Zhengzhou University, Henan, China. 12 Liaocheng People's Hospital, Shandong, China. 13 Guiyang Maternal and Child Health Care Hospital. 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Regions of homozygosity identified by oligonucleotide SNP arrays: evaluating the incidence and clinical utility. Eur J Hum Genet 2015, 23:663-71. Li LH, Ho SF, Chen CH, Wei CY, Wong WC, Li LY, Hung SI, Chung WH, Pan WH, Lee MT, et al. Long contiguous stretches of homozygosity in the human genome. Hum Mutat 2006, 27:1115-21. Ngo C, Baluyot M, Bennetts B, Carmichael J, Clark A, Darmanian A, Gayagay T, Jones L, Nash B, Clark M, et al. SNP chromosome microarray genotyping for detection of uniparental disomy in the clinical diagnostic laboratory. Pathology 2023, 55:818-26. Hu T, Wang J, Zhu Q, Zhang Z, Hu R, Xiao L, Yang Y, Liao N, Liu S, Wang H, et al. Clinical experience of noninvasive prenatal testing for rare chromosome abnormalities in singleton pregnancies. Front Genet 2022, 13. Xing T, Hu Y, Yang J, Chang D, Shang X. A Case of Maternal Uniparental Disomy of Chromosome 6 with Intrauterine Growth Restriction. Altern Ther Health Med 2023, 29:188-99. Shubina J, Barkov IY, Stupko OK, Kuznetsova MV, Goltsov AY, Kochetkova TO, Trofimov DY, Sukhikh GT. Prenatal diagnosis of Prader-Willi syndrome due to uniparental disomy with NIPS: Case report and literature review. Mol Genet Genomic Med 2020, 8:e1448. Hong DK, Park JE, Kang KM, Shim SH, Shim SH, Han YJ, Cho HY, Cha DH. Prenatal Diagnosis of Uniparental Disomy in Cases of Rare Autosomal Trisomies Detected Using Noninvasive Prenatal Test: A Case of Prader-Willi Syndrome. Diagnostics (Basel) 2023, 13. Supplementary Files SupplementaryTableandfigure.docx Cite Share Download PDF Status: Published Journal Publication published 11 Nov, 2025 Read the published version in Journal of Translational Medicine → Version 1 posted Editorial decision: Major revision 01 Jun, 2025 Reviewers agreed at journal 01 May, 2025 Reviewers invited by journal 01 May, 2025 Editor assigned by journal 05 Jan, 2025 First submitted to journal 02 Jan, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5756870","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":450851073,"identity":"b126443b-44ea-4c6c-bdcc-df1875f215bd","order_by":0,"name":"Ning 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hospital","correspondingAuthor":false,"prefix":"","firstName":"Xueyan","middleName":"","lastName":"Wang","suffix":""},{"id":450851081,"identity":"07055774-841e-4e4d-a394-3eed21cfeab0","order_by":8,"name":"Yueyue Hu","email":"","orcid":"","institution":"Shiyan Renmin Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yueyue","middleName":"","lastName":"Hu","suffix":""},{"id":450851082,"identity":"3eabb56e-2add-4f3e-9b9b-31bb46d9119b","order_by":9,"name":"Hua Jin","email":"","orcid":"","institution":"Jinan Maternal and child Health Care Hospital","correspondingAuthor":false,"prefix":"","firstName":"Hua","middleName":"","lastName":"Jin","suffix":""},{"id":450851083,"identity":"11740e4c-4fc6-48be-908a-60d2ec6018b7","order_by":10,"name":"Bing Wang","email":"","orcid":"","institution":"The Second Affiliated Hospital of Zhengzhou 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Hospital","correspondingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Li","suffix":""},{"id":450851087,"identity":"c941841f-768e-49b9-ab08-2519122bedb9","order_by":14,"name":"Xuejing Sun","email":"","orcid":"","institution":"Liaocheng dongchangfu District maternity and child healthcare Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xuejing","middleName":"","lastName":"Sun","suffix":""},{"id":450851088,"identity":"ca694d32-cf8e-4281-b46a-b6780fda9c4a","order_by":15,"name":"Weiqiang Liu","email":"","orcid":"","institution":"Shenzhen Longgang District Maternity and Child Healthcare Hospital","correspondingAuthor":false,"prefix":"","firstName":"Weiqiang","middleName":"","lastName":"Liu","suffix":""},{"id":450851089,"identity":"3f7750d2-67d5-40f2-9212-847cf554f645","order_by":16,"name":"Youhua Wei","email":"","orcid":"","institution":"Maternity and child Health Care of Zaozhuang","correspondingAuthor":false,"prefix":"","firstName":"Youhua","middleName":"","lastName":"Wei","suffix":""},{"id":450851090,"identity":"70ef5866-ae62-4466-864d-64f9d5c368d6","order_by":17,"name":"Lina Liu","email":"","orcid":"","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Lina","middleName":"","lastName":"Liu","suffix":""},{"id":450851091,"identity":"c9a06ea3-319f-40bd-8690-50a671d143d9","order_by":18,"name":"Yin Feng","email":"","orcid":"","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Yin","middleName":"","lastName":"Feng","suffix":""},{"id":450851092,"identity":"4f34c047-fba0-4366-9ee1-6e8c94d99f6d","order_by":19,"name":"Kai Mu","email":"","orcid":"","institution":"Zibo Maternal and Child Health Hospital","correspondingAuthor":false,"prefix":"","firstName":"Kai","middleName":"","lastName":"Mu","suffix":""},{"id":450851093,"identity":"bd017ed3-16b9-41bd-84e5-c3d505a282b0","order_by":20,"name":"Panlai Shi","email":"","orcid":"","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Panlai","middleName":"","lastName":"Shi","suffix":""},{"id":450851094,"identity":"47dd2ca8-c23e-4406-b150-15e62543c871","order_by":21,"name":"Xiangdong Kong","email":"","orcid":"https://orcid.org/0000-0003-4364-6672","institution":"The First Affiliated Hospital of Zhengzhou University","correspondingAuthor":false,"prefix":"","firstName":"Xiangdong","middleName":"","lastName":"Kong","suffix":""}],"badges":[],"createdAt":"2025-01-03 08:54:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5756870/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5756870/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12967-025-07329-x","type":"published","date":"2025-11-11T15:57:09+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":82147944,"identity":"92b98524-8a6a-4ce6-b4ca-9fedcdc116bd","added_by":"auto","created_at":"2025-05-07 07:05:32","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":155403,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of TA-seq and MS-MLPA results. CNV, copy number variation; MCC, maternal cell contamination; MS-MLPA, methylation multiplex ligation-dependent probe amplification; NPV, negative predictive value; PPV, positive predictive value; TA-seq, targeted amplicon sequencing.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5756870/v1/578c259d42e9f15d94cb2b3d.jpg"},{"id":82144962,"identity":"e14094ad-db13-40f5-90ee-ad9cd3bc7b90","added_by":"auto","created_at":"2025-05-07 06:49:32","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":271193,"visible":true,"origin":"","legend":"\u003cp\u003eCircos plot displaying the imprinted regions and SNP loci on chromosomes 6, 7, 11, 14, 15, and 20. Fuchsia, red, and green bars represent centromeric regions, imprinted regions, and SNP loci of the imprinted genes, respectively. Blue and orange fonts represent paternally expressed genes and maternally expressed genes, respectively.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5756870/v1/5c31c32ff21fe2810e1cb5fc.jpg"},{"id":82146891,"identity":"500e5b86-fe59-4bf0-b783-2447b91065de","added_by":"auto","created_at":"2025-05-07 06:57:32","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":40512,"visible":true,"origin":"","legend":"\u003cp\u003eStatistical chart of the positives using TA-seq and MS-MLPA in GROUP-ROH, GROUP-MOSAIC, and GROUP-NIPS. The GROUP-RT and GROUP-sSMC, and GROUP-CHM are not displayed due to their positive detection rates of 0, 0 and 100%, respectively.)\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5756870/v1/3a07e8c84dfb188982f30453.jpg"},{"id":96105181,"identity":"b99289fc-0992-4d3c-aa5b-1d4cda493588","added_by":"auto","created_at":"2025-11-17 16:09:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1489032,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5756870/v1/31943bb2-2592-489a-8e27-1dee2b47a7b2.pdf"},{"id":82146892,"identity":"364d29fe-9cb4-43e2-96d3-4d08048e60eb","added_by":"auto","created_at":"2025-05-07 06:57:32","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":232421,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTableandfigure.docx","url":"https://assets-eu.researchsquare.com/files/rs-5756870/v1/5e31f5a7fc00bcb08681a5c5.docx"}],"financialInterests":"","formattedTitle":"Clinical application value of targeted amplicon sequencing technology in fetuses with uniparental disomy-related imprinting disorders: a multicenter study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eImprinted genes are a group of genes regulated by epigenetic mechanisms, which are monoallelically expressed in a parent-of-origin-dependent manner. Abnormal imprinting\u0026mdash;where both parental alleles are expressed or silenced simultaneously\u0026mdash;can result in imprinting disorders (ImpDis). To date, a total of 13 distinct ImpDis have been clearly identified, primarily associated with chromosomes 6, 7, 11, 14, 15, and 20[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. There are 4 types of molecular alterations in ImpDis, including uniparental disomy (UPD), copy number variation (CNV), single nucleotide variation (SNV), and imprinting defects[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. UPD is an important alteration related to ImpDis. To date, nine UPD-related ImpDis have been well documented, including transient neonatal diabetes mellitus, Silver\u0026ndash;Russell syndrome, Beckwith\u0026ndash;Wiedemann syndrome, Temple syndrome, Kagami\u0026ndash;Ogata syndrome, Prader\u0026ndash;Willi syndrome, Angelman syndrome, Pseudohypoparathyroidism type 1B, and Mulchandani\u0026ndash;Bhoj\u0026ndash;Conlin syndrome[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eUPD refers to the situation in which both homologous chromosomes are inherited exclusively from one parent. The typical mechanism of UPD involves two non-disjunction events occurring during meiosis and mitosis[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. UPD can be further classified into heterodisomy (UPhD), isodisomy (UPiD), mixed UPD (mUPD), and segmental UPD. UPhD is defined as a pair of homologous chromosomes inherited from one parent. UPiD is defined as the duplication of a single chromosome inherited from one parent. mUPD is a mixed form of UPiD and UPhD, while segmental UPD refers to only part of a chromosome inherited from the same parent. UPD is not clinically rare, with an overall prevalence of approximately 1 in 2,000 births in the general population[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Nevertheless, only a small proportion of UPDs are pathogenic, resulting in imprinting disorders[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] or autosomal recessive disorders[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eImpDis have a profound effect on both the survival and overall quality of life for patients. Prenatal screening and diagnosis can help reduce the risk of these conditions. In 2020, the American College of Medical Genetics and Genomics (ACMG) released the first global statement on the prenatal and postnatal diagnosis of UPD[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. China has also issued several consensus statements and guidelines regarding prenatal UPD testing in recent years, all of which emphasize the necessity of prenatal UPD and related ImpDis testing[\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo date, several methods have been developed for prenatal UPD-related ImpDis testing, such as short tandem repeat analysis (STR), single nucleotide polymorphism array (SNP-array), exome sequencing (ES), targeted amplicon sequencing (TA-seq), and methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA). The applicability and cost of these methods vary significantly[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. TA-seq involves multiplex PCR amplification of genomic regions of interest, followed by high-throughput sequencing. This technique is characterized by robustness, high sensitivity, and cost-effectiveness[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], making it widely applicable in various fields, such as pathogenic microorganisms, tumors, and genetic diseases[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Here, we developed a novel TA-seq technique for the prenatal detection of nine UPD-related ImpDis, and undertook a retrospective multicenter study to evaluate the performance of this approach.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e Participant samples and clinical data were collected with informed consent and ethical approval from the Medical Ethics Committee of the First Affiliated Hospital of Zhengzhou University (Ethics Review Number: 2023-KY-0905-003).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSUBJECTS\u003c/h2\u003e \u003cp\u003eWe initially collected 370 samples of singleton pregnancies with a diverse set of UPD testing indications from 42 hospitals across China. Sample types included chorionic villi, amniotic fluid, cord blood, and products of conception. The inclusion criteria were primarily based on the UPD testing statement published by the American College of Medical Genetics and Genomics (ACMG) [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], with minor modifications. The exclusion criteria included: (1) twin or multiple pregnancies; (2) imprinting disorder caused by CNV; (3) consanguineous parents; (4) triploidy.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGENOMIC DNA EXTRACTION AND QUALITY CONTROL\u003c/h3\u003e\n\u003cp\u003eGenomic DNA was extracted using the MagPure DNA Micro Kit (Magen, China), following the manufacturer\u0026rsquo;s instructions. The quality of the genomic DNA was assessed through agarose gel electrophoresis and quantified using a Qubit 3.0 fluorometer. To exclude maternal cell contamination, STR analysis was performed by quantitative fluorescence polymerase chain reaction (QF-PCR) utilizing the Microreader 21 Direct ID System (Microreader Genetics, China). PCR products were analyzed on an ABI 3130XL sequencer (Applied Biosystems, USA), and genotypes were scored with GeneMapper 4.0 (Applied Biosystems, USA).\u003c/p\u003e\n\u003ch3\u003eTA-SEQ\u003c/h3\u003e\n\u003cp\u003eAccording to the polymorphic SNP databases (dbSNP, gnomAD, ExAC, and 1000 Genomes), multiplex PCR primers were designed based on 1,230 SNP loci across the imprinted regions on chromosomes 6, 7, 11, 14, 15, and 20 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The multiplex PCR reaction was performed in a 20 \u0026micro;L reaction system, including 5 \u0026micro;L of genomic DNA (4 ng/\u0026micro;L), 2 \u0026micro;L of M-primer (containing an index), 3 \u0026micro;L of UPD primer pool, and 10 \u0026micro;L of 2\u0026times; multiplex PCR mix. The amplification conditions were as follows: 95\u0026deg;C for 2 minutes; 20 cycles of 95\u0026deg;C for 30 seconds and 60\u0026deg;C for 4 minutes; finally 72\u0026deg;C for 5 minutes; 4℃ forever. After products purification, the DNA fragments were used to construct a DNA library for high-throughput sequencing. The libraries were sequenced in single-end mode at 40 bp using the Nextseq 550AR sequencer (Annoroad, China). Each sample obtained a sequencing depth of approximately 1,000,000 raw reads. After sequencing, adapters and low-quality sequences were removed by Cutadapt (version 1.10). Reads were mapped to the human reference genome (GRCh37/hg19) using Burrows-Wheeler Aligner (version 0.7.15) with the mem algorithm. VarScan (version 2.4.3) was utilized for SNV calling.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo predict UPiD, we calculated the probability of heterozygosity (number of heterozygous sites / total number of sites) for all amplicon regions across each chromosome. This probability value was then transformed by the log function to determine the likelihood of UPiD. The parental origin of each UPiD was determined to be \u0026ge;\u0026thinsp;95% through calculating the sequence similarity if biological parents were available. To predict UPhD, it is essential to use biological parent samples. First, the sum of homozygous and heterozygous sites that are identical between the fetal and parental sequences is calculated. Next, the ratio of the sum to the intersection of the sites from both sequences is calculated. If the ratio is \u0026ge;\u0026thinsp;95%, it can be judged as paternal or maternal UPhD.\u003c/p\u003e \u003cp\u003eThe formula used for determination of UPD is as follows: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:y=\\prod\\:f\\left({x}_{i}\\right)\\)\u003c/span\u003e\u003c/span\u003e, where \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{x}_{i}\\)\u003c/span\u003e\u003c/span\u003e represents the population frequency at each site; for UPiD, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:f\\)\u003c/span\u003e\u003c/span\u003e represents the probability that the fetus is homozygous; and for UPhD, \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:f\\)\u003c/span\u003e\u003c/span\u003e represents the probability that the fetus shares the same genotype as its biological parents.\u003c/p\u003e\n\u003ch3\u003eMS-MLPA\u003c/h3\u003e\n\u003cp\u003eMS-MLPA serves as the gold standard. Methylation analysis of 7 imprinted loci (\u003cem\u003ePLAGL1, HYMAI, GRB10, MEST, H19, KCNQ1OT1, MEG3, MEG8, SNRPN, PEG3, NESP55, GNAS-AS1, GNASXL\u003c/em\u003e, and \u003cem\u003eGNAS A/B\u003c/em\u003e) was performed by MS-MLPA using the SALSA MS-MLPA Probemix ME034-C1 Multi-locus Imprinting kit (MRC-Holland, The Netherlands) according to the manufacturer\u0026rsquo;s protocol. To ensure the stability and accuracy of the results, all MS-MLPA experiments were uniformly conducted in the Genetic and Prenatal Diagnosis Center Laboratory of the First Affiliated Hospital of Zhengzhou University and were performed and analyzed by the same experimenter. Amplified products were analyzed using the ABI 3130XL sequencer (Applied Biosystems, USA) with the GeneMapper 4.0 (Applied Biosystems, USA). Values corresponding to peak areas were used for further data processing by Coffalyser V7 software (MRC-Holland, The Netherlands). The formula used for methylation dosage ratio (MR) was as follows: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\text{M}\\text{R}=(\\text{P}\\text{x}\\:/\\:\\text{P}\\text{c}\\text{t}\\text{r}\\text{l}){\\text{D}\\text{i}\\text{g}}_{}\\:/\\:(\\text{P}\\text{x}\\:/\\:\\text{P}\\text{c}\\text{t}\\text{r}\\text{l}){\\text{U}\\text{n}\\text{d}\\text{i}\\text{g}}_{}\\)\u003c/span\u003e\u003c/span\u003e, where Px is the peak area of a given target probe, Pctrl is the sum of the peak areas of all control probes, Dig stands for HhaI digested sample, and Undig stands for undigested sample.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSTATISTICAL ANALYSIS\u003c/h2\u003e \u003cp\u003ePositive detection rate, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and concordance were analyzed using SPSS version 26 (IBM SPSS, USA). Categorical variables are presented as percentages, while continuous variables are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSUBJECTS\u003c/h2\u003e \u003cp\u003eA total of 370 samples were recruited initially from 42 hospitals. Then 76 samples were excluded due to CNV, triploidy, consanguineous parents, maternal cell contamination, or insufficient DNA concentration for experiments. The remaining 294 samples were successfully assayed by TA-seq and MS-MLPA (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Maternal ages ranged from 19 to 45 years, with an average of 30.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.2 years. The gestational weeks for chorionic villus sampling, amniocentesis, products of conception, and cordocentesis were 9‒13 (11.8\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1), 16‒33 (20.4\u0026thinsp;\u0026plusmn;\u0026thinsp;3.5), 6‒26 (10.6\u0026thinsp;\u0026plusmn;\u0026thinsp;4.3), and 26‒36 (30.1\u0026thinsp;\u0026plusmn;\u0026thinsp;2.5), respectively. The types of 294 samples were mainly amniotic fluid, including 209 cases of amniotic fluid, 38 cases of chorionic villi, 38 cases of products of conception, and 9 cases of umbilical cord blood.\u003c/p\u003e \u003cp\u003eThere were great differences in the sample size among the 6 testing indication groups. The \u0026lsquo;\u0026ge; 5Mb region of homozygosity (ROH) detected by SNP-array on chromosomes 6, 7, 11, 14, 15, or 20\u0026rsquo; group (GROUP-ROH) contained the largest number of samples (n\u0026thinsp;=\u0026thinsp;127), followed by the \u0026lsquo;trisomy or monosomy of chromosomes 6, 7, 11, 14, 15, or 20 was detected by non-invasive prenatal screening, but disomy or mosaicism was detected by prenatal diagnosis\u0026rsquo; group (GROUP-NIPS), which had 78 samples. The remaining indication groups, including \u0026lsquo;\u0026ge; 10% mosaicism for trisomy or monosomy detected by prenatal diagnosis\u0026rsquo; (GROUP-MOSAIC), \u0026lsquo;familial or de novo balanced Robertsonian translocation or isochromosome involving chromosome 14 or 15 based on CVS or amniocentesis\u0026rsquo; (GROUP-RT), \u0026lsquo;whole-genome paternal UPD detected by SNP-array\u0026rsquo; (GROUP-CHM), and \u0026lsquo;de novo small supernumerary marker chromosomes (sSMC) with no apparent euchromatic material in the fetus\u0026rsquo; (GROUP-sSMC) contained 43, 23, 17, and 6 cases, respectively. In addition, in GROUP-RH, 95.7% (22/23) of cases were chromosome 14-related.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMS-MLPA RESULTS\u003c/h3\u003e\n\u003cp\u003e294 samples underwent MS-MLPA testing, with no microdeletions found within the probe range, ensuring that methylation alteration was not due to microdeletions. MS-MLPA detected 33 cases of methylation alteration (Supplementary Table\u0026nbsp;1), including 1 case with loss of methylation (LoM) of \u003cem\u003ePLAG1\u003c/em\u003e:TSS-DMR, 7 cases with gain of methylation (GoM) of \u003cem\u003ePLAG1\u003c/em\u003e:TSS-DMR, 1 case with GoM of \u003cem\u003eMEG3\u003c/em\u003e:TSS-DMR and LoM of \u003cem\u003eMEG8\u003c/em\u003e:int2-DMR, 2 cases with LoM of \u003cem\u003eMEG3\u003c/em\u003e:TSS-DMR and GoM of \u003cem\u003eMEG8\u003c/em\u003e:int2-DMR, 5 cases with GoM of \u003cem\u003eSNRPN\u003c/em\u003e, and 17 cases with GoM of all paternal imprinted alleles and LoM of all maternal imprinted alleles.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eTA-SEQ PERFORMANCE\u003c/h2\u003e \u003cp\u003eThe total positive detection rate of TA-seq was 12.2% (36/294). Compared to the gold standard (MS-MLPA), TA-seq detected 30 true positives, 6 false positives, 3 false negatives, and 255 true negatives. The sensitivity, specificity, PPV, and NPV of TA-seq were 90.9% (30/33), 97.7% (255/261), 83.3% (30/36), and 98.8% (255/258), respectively. The concordance between the two methods was 96.9% (285/294).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eFALSE NEGATIVES AND FALSE POSITIVES\u003c/h2\u003e \u003cp\u003eOne false negative case belonged to GROUP-NIPS with the specific indication that \u0026lsquo;trisomy 15 was detected by NIPS but disomy 15 by CNV-seq.\u0026rsquo; The other two false negatives belonged to GROUP-ROH, with the specific indication that \u0026lsquo;25.7 Mb ROH on chromosome 15 detected by SNP-array at 15q14q22.2\u0026rsquo; and \u0026lsquo;37.3 Mb ROH on chromosome 14 detected by SNP-array at 14q11.2q23.1,\u0026rsquo; respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Supplementary Fig.\u0026nbsp;1A-1C).\u003c/p\u003e \u003cp\u003eFive false positives belonged to GROUP-ROH with the lengths of ROH from 5.7 to 11 Mb. The remaining one case, in GROUP-NIPS, had the specific indication that \u0026lsquo;trisomy 7 was detected by NIPS but disomy 7 by CNV-seq\u0026rsquo; (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Supplementary Fig.\u0026nbsp;1D-1I).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of 3 false negatives and 6 false positives.\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTA-seq\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMS-MLPA\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIndication group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSpecific indications\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot detected\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGoM of \u003cem\u003eSNRPN\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGROUP-NIPS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003etrisomy 15 was detected by NIPS but disomy 15 by CNV-seq\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot detected\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGoM of \u003cem\u003eSNRPN\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGROUP-ROH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.7 Mb ROH on chromosome 15 detected by SNP-array at 15q14q22.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot detected\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGoM of \u003cem\u003eMEG3\u003c/em\u003e:TSS-DMR and LoM of \u003cem\u003eMEG8\u003c/em\u003e:int2-DMR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGROUP-ROH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37.3 Mb ROH on chromosome 14 detected by SNP-array at 14q11.2q23.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUPD(6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo methylation alteration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGROUP-ROH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.2 Mb ROH detected by SNP-array at 6q24.1q24.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUPD(6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo methylation alteration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGROUP-ROH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5.7 Mb ROH detected by SNP-array at 6q23.3q24.2.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUPD(6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo methylation alteration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGROUP-ROH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11 Mb ROH detected by SNP-array at 6q23.3q25.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUPD(7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo methylation alteration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGROUP-ROH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.6 Mb ROH detected by SNP-array at 7q22.3q32.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUPD(11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo methylation alteration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGROUP-NIPS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003etrisomy 7 was detected by NIPS but disomy 7 by CNV-seq\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUPD(20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo methylation alteration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGROUP-ROH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10.4 Mb ROH detected by SNP-array at 20q13.2q13.33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003ea\u003c/sup\u003eAbbreviations: LoM, loss of methylation; GoM, gain of methylation. CNV-seq, copy number variation sequencing; ROH, region of homozygosity.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePOSITIVE DETECTION RATES OF TA-SEQ AND MS-MLPA UNDER 6 TESTING INDICATION GROUPS\u003c/h2\u003e \u003cp\u003eThe sample sizes under different indication groups varied widely, while the trends of positive detection rates between TA-seq and MS-MLPA were similar (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). GROUP-CHM had the highest positive detection rates for TA-seq and MS-MLPA, both of which were 100% (17/17). GROUP-ROH had the positive detection rates of 13.4% (17/127) and 11.0% (14/127) for TA-seq and MS-MLPA, respectively. GROUP-MOSAIC had the positive detection rates of 2.3% (1/43) for both methods. GROUP-NIPS had the positive detection rates of 1.3% (1/78) for both methods. In GROUP-RT and GROUP-sSMC, no positive cases were identified by TA-seq or MS-MLPA.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study we performed a multicenter retrospective study a novel established TA-seq technique for prenatal detection of UPD-related ImpDis. TA-seq exhibits high sensitivity, specificity, PPV, and NPV, indicating high detection efficiency, beyond its good concordance with MS-MLPA.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eCAUSES OF FALSE NEGATIVES AND FALSE POSITIVES\u003c/h2\u003e \u003cp\u003eThe SNP-array results allow us to readily determine the causes of the two false negatives: As the ROHs (14q11.2q23.1 and 15q14q22.2) fall outside the imprinted regions of 14q32.2 and 15q11.2q13, respectively, they were necessarily missed by TA-seq in single-sample mode. The remaining false negative, despite not being tested by SNP-array, we speculate that its UPD type may either be mUPD with ROH outside the imprinted region or be UPhD without any ROH. Indeed, missed detection of UPhD in single-sample mode is a common problem for all DNA sequence-based techniques (including STR, SNP-array, WES, etc.). Hoppman et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]reported that 33% of UPD cases could be missed by single-sample SNP-array due to the lack of extended ROH. Since TA-seq was designed to focus on imprinted regions rather than the entire chromosome, single-sample TA-seq may have a higher missed detection rate compared to other techniques. This problem could be solved by performing TA-seq in a trio-based mode. We previously carried out trio-based TA-seq on peripheral blood samples, successfully identifying all instances of mUPD and UPhD (unreported data). Even though we have great confidence in prenatal samples, more samples are required for further study.\u003c/p\u003e \u003cp\u003eMoreover, the trio-based analysis can help determine UPD pathogenicity and specific ImpDis. For instance, paternal UPD(6) or maternal UPD(7) is pathogenic, but maternal UPD(6) or paternal UPD(7) is not. The single-sample analysis can only provide a UPD result without parental origin, making it impossible to determine its pathogenicity. As for UPD(11), (14), (15), or (20), although both paternal and maternal UPD are pathogenic, they will lead to different ImpDis. For instance, maternal UPD(11) and paternal UPD(11) can cause Silver\u0026ndash;Russell syndrome and Beckwith\u0026ndash;Wiedemann syndrome, respectively; paternal UPD(15) and maternal UPD(15) can cause Angelman syndrome and Prader\u0026ndash;Willi syndrome, respectively. It is obvious that the trio-based analysis would be more conducive to disease diagnosis and treatment than the single-sample analysis. Regrettably, given the retrospective study design, the parental samples were not available. We plan to carry out a prospective cohort study using trio-based TA-seq in the future.\u003c/p\u003e \u003cp\u003eFalse positives are twice as common as false negatives due to several factors, including limited SNP loci, ROH calculation methods, threshold settings, and consanguinity. False positives increase the workload for subsequent diagnosis and genetic counseling, along with parental psychological stress. We will continue to improve the false positive rate by expanding the coverage area of the amplicons, increasing the number of positive samples, improving ROH calculation methods, and optimizing thresholds.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eDIFFERENCES IN POSITIVE DETECTION RATES UNDER DIFFERENT TESTING INDICATION GROUPS\u003c/h2\u003e \u003cp\u003ePositive detection rates ranged from 0\u0026ndash;100% under 6 testing indication groups. GROUP-CHM and GROUP-ROH exhibit the high positive rates, suggesting that large ROH are the most effective indicators for UPD. We also observed that in GROUP-ROH chromosome 6, 14, or 15 had higher true positive rates than chromosome 7, 11, or 20. The low true positive rates for 7, 11, or 20 could be due to the population polymorphic ROHs that have been reported in some domestic and international population studies, such as 7q11.22q11.23[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], 11p11.2p11.12[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], and 20q11.21q11.23[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In this study we observed 20 samples with 7q11.22q11.23, 7 samples with 11p11.2p11.12, and 9 samples with 20q11.21q11.23, which accounts for 46.5%, 26.9%, and 60% of the samples with \u0026ge;\u0026thinsp;5Mb ROH on chromosome 7, 11, or 20, respectively. All these samples were proved to be false positives, suggesting that ROHs at those chromosomal locations are not reliable indicators of UPD for the Chinese population.\u003c/p\u003e \u003cp\u003eRecent studies have reported that high-risk of aneuploidy through NIPS is also an indicator for detecting UPD. For instance, Ngo et al.[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] reported 2 cases of UPD(9), 1 case of UPD(15), and 2 cases of UPD(16) among 35 high-risk pregnant women detected by NIPS. Hu et al.[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] found 30 cases of UPD from 528 high-risk pregnant women, including 5 cases of UPD(6), 5 cases of UPD(7), 1 case of UPD(11), 1 case of UPD(14), and 1 case of UPD(15). Additionally, there are several case reports involving UPD(6) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and UPD(15) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. In our study, we enrolled 78 cases with high-risk of NIPS, including 3, 44, 6, 9, 11, and 5 cases for trisomy 6, 7, 11, 14, 15, and 20, respectively. MS-MLPA finally confirmed 1 case with methylation anomaly of chromosome 15. Combining all of the above evidence, it appears that the high risk of NIPS for different chromosomes has varying weights for UPD indication; specifically, aneuploidy of chromosomes 6 or 15 is more indicative.\u003c/p\u003e \u003cp\u003eAddtionally, we observed a high false positive rate under different indication groups, and TA-seq could greatly decrease false positives. Using trio-based TA-seq as a testing strategy, we believe UPD-related ImpDis could be effectively tested together with a reduced diagnosis cost and psychological stress of pregnant women.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eADVANTAGES AND APPLICATION OF TA-SEQ\u003c/h2\u003e \u003cp\u003eSTR anlysis, SNP-array, and WES are currently-used methods for detecting UPD-related imprinting disorders. Due to the probe coverage of SNP-array and WES, they are able to detect mUPD cases with ROH occurring in non-imprinted regions, which cannot be detected by STR analysis or TA-seq.\u0026nbsp;However, SNP-array and WES are primarily used to detect CNV and SNV, but their costs are too high for UPD detection. Both STR analysis and TA-seq are relatively low-cost, but the former relies on first-generation sequencing platforms. This implies additional experimental space and costs for a prenatal molecular testing laboratory utilizing next-generation sequencing platforms. In contrast, TA-seq demonstrates superior compatibility because its sequencing strategy aligns seamlessly with NIPS or CNV-seq, thereby reducing experimental time and workload. Furthermore, TA-seq could compensate for the shortcomings of CNV-seq, which cannot detect UPD-related ImpDis.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003eLIMITATIONS OF THIS STUDY\u003c/h2\u003e \u003cp\u003eThere are also limitations in this study. The first is the lack of validation of trio-based TA-seq using prenatal samples, and the second is the limited number of true positive cases. Moreover, the true positives are concentrated on chromosomes 6, 14, and 15. Therefore, we need to further enlarge the positive samples especially for chromosomes 7, 11, and 20 in the future to more fully assess the potential clinical efficacy of TA-seq.\u003c/p\u003e \u003c/div\u003e "},{"header":"Abbreviations","content":"\u003cp\u003eImpDis, imprinting disorders; CNV, copy number variation; SNV, single nucleotide variation; UPD, uniparental disomy; UPhD, uniparental heterodisomy; UPiD, uniparental isodisomy; mUPD, mixed uniparental disomy; ACMG, American College of Medical Genetics and Genomics; TA-seq, targeted amplicon sequencing; MS-MLPA, methylation-specific multiplex ligation-dependent probe amplification; STR, short tandem repeat; SNP-array, single nucleotide polymorphism array; ES, exome sequencing; QF-PCR, quantitative fluorescence polymerase chain reaction; NIPS, non-invasive prenatal screening; sSMC, small supernumerary marker chromosomes; ROH, regions of homozygosity; GROUP-ROH, \u0026lsquo;\u0026ge; 5Mb ROH detected by SNP-array on chromosomes 6, 7, 11, 14, 15, or 20\u0026rsquo; group; GROUP-NIPS, \u0026lsquo;trisomy or monosomy of chromosomes 6, 7, 11, 14, 15, or 20 was detected by non-invasive prenatal screening, but disomy or mosaicism was detected by prenatal diagnosis\u0026rsquo; group; GROUP-MOSAIC, \u0026lsquo;\u0026ge; 10% mosaicism for trisomy or monosomy detected by prenatal diagnosis\u0026rsquo; group; GROUP-RT, \u0026lsquo;familial or de novo balanced Robertsonian translocation or isochromosome involving chromosome 14 or 15 based on CVS or amniocentesis\u0026rsquo; group; GROUP-CHM, \u0026lsquo;whole-genome paternal UPD detected by SNP-array\u0026rsquo; group; GROUP-sSMC, \u0026lsquo;de novo small supernumerary marker chromosomes with no apparent euchromatic material in the fetus\u0026rsquo; group.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch3\u003eAcknowledgements\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eWe gratefully acknowledge all the participants and staff involved in this multicenter observational study. Especially we thank to Annoroad Gene Technology for technical support.\u003c/strong\u003e\u003c/p\u003e\n\u003ch3\u003eAuthors\u0026rsquo; contributions\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eNing Liu and Xiangdong Kong conceived and designed the study, wrote the study protocol, and contributed to the acquisition of clinical data. Lina Liu, Yin Feng and Panlai Shi performed the experiments, statistical analyses. All of the authors reviewed and commented on the manuscript and approved the final version.\u003c/strong\u003e\u003c/p\u003e\n\u003ch3\u003eFunding\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eThis study was supported by\u0026nbsp;\u003c/strong\u003eSpecial Fund for Key Research, \u003cstrong\u003eDevelopment and Promotion of Science and Technology of Henan Province (222102520018).\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ch3\u003eAvailability of data and materials\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eThe datasets used in the current study are available from the corresponding author on reasonable request.\u003c/strong\u003e\u003c/p\u003e\n\u003ch3\u003eEthics approval and consent to participate\u003c/h3\u003e\n\u003cp\u003eDonors and patient provided written informed consent.\u003c/p\u003e\n\u003ch3\u003eConsent for publication\u003c/h3\u003e\n\u003cp\u003eAll authors consent for publication.\u003c/p\u003e\n\u003ch3\u003eCompeting interests\u003c/h3\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch3\u003eAuthor details\u003c/h3\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eThe First Affiliated Hospital of Zhengzhou University, Henan, China. \u003csup\u003e2\u003c/sup\u003eGuizhou Provincial People\u0026apos;s Hospital, Guizhou, China. \u003csup\u003e3\u003c/sup\u003eChangzhou Maternal and Child Health Care Hospital, Jiangsu, China. \u003csup\u003e4\u003c/sup\u003eThe First Affiliated Hospital, Sun Yat-sen University, Guangdong, China. \u003csup\u003e5\u003c/sup\u003eThe Affiliated Taizhou People\u0026apos;s Hospital of Nanjing Medical University, Jiangsu, China. \u003csup\u003e6\u003c/sup\u003eQilu Hospital of Shandong University, Shandong, China. \u003csup\u003e7\u003c/sup\u003eWuxi Maternal and Child Health Care Hospital, Jiangsu, China. \u003csup\u003e8\u003c/sup\u003eSichuan Provincial Maternity and Child Health Care Hospital, Sichuan, China. \u0026nbsp;\u003csup\u003e9\u003c/sup\u003eShiyan People\u0026apos;s Hospital, Hubei, China. \u003csup\u003e10\u003c/sup\u003eJinan Maternal and Child Health Care Hospital, Shandong, China. \u003csup\u003e11\u003c/sup\u003eThe Second Affiliated Hospital of Zhengzhou University, Henan, China. \u003csup\u003e12\u003c/sup\u003eLiaocheng People\u0026apos;s Hospital, Shandong, China. \u003csup\u003e13\u003c/sup\u003eGuiyang Maternal and Child Health Care Hospital. Guiyang Children\u0026apos;s Hospital, Guizhou, China. \u003csup\u003e14\u003c/sup\u003eNanjing Drum Tower Hospital, The Affiliated Hospital of Naning University Medical School, Jiangsu, China. \u003csup\u003e15\u003c/sup\u003eLiaocheng Dongchangfu District Maternity and Child Healthcare Hospital, Shandong, China. \u003csup\u003e16\u003c/sup\u003eShenzhen Longgang District Maternity and Child Healthcare Hospital, Guangdong, China. \u003csup\u003e17\u003c/sup\u003eMaternity And Child Health Care of Zaozhuang, Shandong, China. \u003csup\u003e18\u003c/sup\u003eZibo Maternal And Child Health Hospital, Shandong, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eEggermann T, Monk D, de Nanclares GP, Kagami M, Giabicani E, Riccio A, Tumer Z, Kalish JM, Tauber M, Duis J, et al. Imprinting disorders. Nat Rev Dis Primers 2023, 9:33.\u003c/li\u003e\n\u003cli\u003eBeygo J, Russo S, Tannorella P, Santen G, Dufke A, Schlaich E, Eggermann T. Prenatal testing for imprinting disorders: A laboratory perspective. Prenat Diagn 2023, 43:973-82.\u003c/li\u003e\n\u003cli\u003eDel GD, Shinawi M, Astbury C, Tayeh MK, Deak KL, Raca G. Diagnostic testing for uniparental disomy: a points to consider statement from the American College of Medical Genetics and Genomics (ACMG). Genet Med 2020, 22:1133-41.\u003c/li\u003e\n\u003cli\u003eBenn P. Uniparental disomy: Origin, frequency, and clinical significance. Prenat Diagn 2021, 41:564-72.\u003c/li\u003e\n\u003cli\u003eNakka P, Pattillo SS, O\u0026apos;Donnell-Luria AH, McManus KF, Mountain JL, Ramachandran S, Sathirapongsasuti JF. Characterization of Prevalence and Health Consequences of Uniparental Disomy in Four Million Individuals from the General Population. Am J Hum Genet 2019, 105:921-32.\u003c/li\u003e\n\u003cli\u003eZhu L, Zhang H, Li Z, Liu W, Sun X. [Clinical practice guidelines for the diagnosis of regions of homozygosity and uniparental disomy]. Zhonghua Yi Xue Yi Chuan Xue Za Zhi 2021, 38:1140-4.\u003c/li\u003e\n\u003cli\u003eNiida Y, Ozaki M, Shimizu M, Ueno K, Tanaka T. Classification of Uniparental Isodisomy Patterns That Cause Autosomal Recessive Disorders: Proposed Mechanisms of Different Proportions and Parental Origin in Each Pattern. Cytogenet Genome Res 2018, 154:137-46.\u003c/li\u003e\n\u003cli\u003eLiu W, Lu J, Zhang J, Li R, Lin S, Zhang Y, Wang Y, Yin A. [A consensus recommendation for the interpretation and reporting of copy number variation and regions of homozygosity in prenatal genetic diagnosis]. Zhonghua Yi Xue Yi Chuan Xue Za Zhi 2020, 37:701-8.\u003c/li\u003e\n\u003cli\u003eCyto AGGO, Liu N, Shi P, Liu L, Kong X. [Expert consensus on the prenatal diagnosis and genetic counseling for uniparental disomy-related imprinting disorders]. Zhonghua Yi Xue Yi Chuan Xue Za Zhi 2024, 41:685-95.\u003c/li\u003e\n\u003cli\u003e[Guideline for the application of chromosomal microarray analysis in prenatal diagnosis (2023)]. Zhonghua Fu Chan Ke Za Zhi 2023, 58:565-75.\u003c/li\u003e\n\u003cli\u003eCommittee FBDP, Hu T, Liu S. [Guidelines for the application of copy number variation testing in prenatal diagnosis]. Zhonghua Yi Xue Yi Chuan Xue Za Zhi 2020, 37:909-17.\u003c/li\u003e\n\u003cli\u003eOnda Y, Takahagi K, Shimizu M, Inoue K, Mochida K. Multiplex PCR Targeted Amplicon Sequencing (MTA-Seq): Simple, Flexible, and Versatile SNP Genotyping by Highly Multiplexed PCR Amplicon Sequencing. Front Plant Sci 2018, 9:201.\u003c/li\u003e\n\u003cli\u003eYang H, Luo H, Zhang G, Zhang J, Peng Z, Xiang J. A multiplex PCR amplicon sequencing assay to screen genetic hearing loss variants in newborns. BMC Med Genomics 2021, 14:61.\u003c/li\u003e\n\u003cli\u003eDuan H, Li J, Jiang Z, Shi X, Hu Y. Noninvasive screening of fetal RHD genotype in Chinese pregnant women with serologic RhD‐negative phenotype. Transfusion 2023.\u003c/li\u003e\n\u003cli\u003eHoppman N, Rumilla K, Lauer E, Kearney H, Thorland E. Patterns of homozygosity in patients with uniparental disomy: detection rate and suggested reporting thresholds for SNP microarrays. Genet Med 2018, 20:1522-7.\u003c/li\u003e\n\u003cli\u003eChaves TF, Oliveira LF, Ocampos M, Barbato IT, de Luca GR, Barbato FJ, de Camargo PL, Bernardi P, Maris AF. Long contiguous stretches of homozygosity detected by chromosomal microarrays (CMA) in patients with neurodevelopmental disorders in the South of Brazil. BMC Med Genomics 2019, 12:50.\u003c/li\u003e\n\u003cli\u003eWang JC, Ross L, Mahon LW, Owen R, Hemmat M, Wang BT, El NM, Kopita KA, Randolph LM, Chase JM, et al. Regions of homozygosity identified by oligonucleotide SNP arrays: evaluating the incidence and clinical utility. Eur J Hum Genet 2015, 23:663-71.\u003c/li\u003e\n\u003cli\u003eLi LH, Ho SF, Chen CH, Wei CY, Wong WC, Li LY, Hung SI, Chung WH, Pan WH, Lee MT, et al. Long contiguous stretches of homozygosity in the human genome. Hum Mutat 2006, 27:1115-21.\u003c/li\u003e\n\u003cli\u003eNgo C, Baluyot M, Bennetts B, Carmichael J, Clark A, Darmanian A, Gayagay T, Jones L, Nash B, Clark M, et al. SNP chromosome microarray genotyping for detection of uniparental disomy in the clinical diagnostic laboratory. Pathology 2023, 55:818-26.\u003c/li\u003e\n\u003cli\u003eHu T, Wang J, Zhu Q, Zhang Z, Hu R, Xiao L, Yang Y, Liao N, Liu S, Wang H, et al. Clinical experience of noninvasive prenatal testing for rare chromosome abnormalities in singleton pregnancies. Front Genet 2022, 13.\u003c/li\u003e\n\u003cli\u003eXing T, Hu Y, Yang J, Chang D, Shang X. A Case of Maternal Uniparental Disomy of Chromosome 6 with Intrauterine Growth Restriction. Altern Ther Health Med 2023, 29:188-99.\u003c/li\u003e\n\u003cli\u003eShubina J, Barkov IY, Stupko OK, Kuznetsova MV, Goltsov AY, Kochetkova TO, Trofimov DY, Sukhikh GT. Prenatal diagnosis of Prader-Willi syndrome due to uniparental disomy with NIPS: Case report and literature review. Mol Genet Genomic Med 2020, 8:e1448.\u003c/li\u003e\n\u003cli\u003eHong DK, Park JE, Kang KM, Shim SH, Shim SH, Han YJ, Cho HY, Cha DH. Prenatal Diagnosis of Uniparental Disomy in Cases of Rare Autosomal Trisomies Detected Using Noninvasive Prenatal Test: A Case of Prader-Willi Syndrome. Diagnostics (Basel) 2023, 13.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5756870/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5756870/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTo explore the application value of targeted amplicon sequencing (TA-seq) technology based on multiplex PCR and high-throughput sequencing in prenatal detection of uniparental disomy (UPD)-related imprinting disorders (ImpDis).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis retrospective study included 370 samples suspected of UPD from 42 hospitals across China. Of these, 294 samples were successfully tested by TA-seq and methylation multiplex ligation-dependent probe amplification (MS-MLPA), with MS-MLPA serving as the gold standard.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eTA-seq identified 36 positives and 258 negatives, of which 30 positives and 255 negatives were consistent with the findings from MS-MLPA. The sensitivity, specificity, positive predictive value, and negative predictive value of TA-seq were 90.9% (30/33), 97.7% (255/261), 83.3% (30/36), and 98.8% (255/258), respectively. The concordance between the two methods was 96.9% (285/294). Additionally, we observed potential false positives in UPD-related ImpDis testing indications. For instance, the '\u0026ge; 5 Mb ROH detected by SNP-array on chromosomes 6, 7, 11, 14, 15, or 20' group exhibited a positive rate of 11.0% (14/127), while the 'familial or de novo balanced Robertsonian translocation or isochromosome involving chromosome 14 or 15 based on CVS or amniocentesis' group and the 'de novo sSMC with no apparent euchromatic material in the fetus' group both demonstrated positive rates of 0% (0/23 and 0/6, respectively).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eTA-seq proves to be a valuable method for prenatal screening of UPD-related ImpDis, significantly reducing false positives and thus easing the economic burden and anxiety for expectant parents. Its straightforward operation, adaptability, and reliability make it promising for future clinical use.\u003c/p\u003e","manuscriptTitle":"Clinical application value of targeted amplicon sequencing technology in fetuses with uniparental disomy-related imprinting disorders: a multicenter study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-07 06:49:27","doi":"10.21203/rs.3.rs-5756870/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2025-06-01T14:47:05+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2025-05-02T03:18:22+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-02T03:16:52+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-01-06T02:27:48+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Translational Medicine","date":"2025-01-03T03:54:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-translational-medicine","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jtrm","sideBox":"Learn more about [Journal of Translational Medicine](http://translational-medicine.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/jtrm/default.aspx","title":"Journal of Translational Medicine","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6550ddf1-2a11-4ca7-ba7d-a618117c493d","owner":[],"postedDate":"May 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T16:05:05+00:00","versionOfRecord":{"articleIdentity":"rs-5756870","link":"https://doi.org/10.1186/s12967-025-07329-x","journal":{"identity":"journal-of-translational-medicine","isVorOnly":false,"title":"Journal of Translational Medicine"},"publishedOn":"2025-11-11 15:57:09","publishedOnDateReadable":"November 11th, 2025"},"versionCreatedAt":"2025-05-07 06:49:27","video":"","vorDoi":"10.1186/s12967-025-07329-x","vorDoiUrl":"https://doi.org/10.1186/s12967-025-07329-x","workflowStages":[]},"version":"v1","identity":"rs-5756870","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5756870","identity":"rs-5756870","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}