Small Copy Number Variations Research Articles

CNV_MCD: Detection of copy number variations based on minimum covariance determinant using next-generation sequencing data

Copy number variation (CNV), a pivotal form of genomic structural variation, plays a critical role in the genetic diversity of cancer genomes. In numerous studies, the identification of CNVs is commonly approached as an issue of outlier detection. To address this, read depth (RD) signals for genomic segments are first extracted from next-generation sequencing (NGS) data. CNVs are detected by assigning outlier scores to genomic segments based on the distance between their RD signals and those of adjacent segments. However, the mean and covariance estimators of the global distribution commonly utilized for calculating distance are susceptible to the effect of CNVs, resulting in inaccurate CNV detection. To solve this problem, we introduce a new method, CNV_MCD, for detecting CNVs based on the minimum covariance determinant (MCD). CNV_MCD employs the MCD method to estimate the mean and covariance of the RD profile, circumventing the need for direct computation of these parameters and ensuring the minimization of the determinant of the covariance matrix. This approach enables the calculation of a robust distance for each genomic segment, which serves as an outlier score. Furthermore, we implement a fast median filtering to correct for baseline drift in the outlier scores and use a chi-squared approximation to determine the cutoff distance for CNVs. These enhancements facilitate the detection of small CNVs, establishing CNV_MCD as a complementary method for CNV detection in low-coverage sequencing data. Extensive experiments on both simulated and real datasets demonstrate that CNV_MCD outperforms other popular CNV detection methods. Overall, our method offers a more robust and reliable technique for CNV detection, playing a crucial role in elucidating the genetic mechanisms underlying complex diseases such as cancer.

High positive predictive value of CNVs detected by clinical exome sequencing in suspected genetic diseases

BackgroundGenetic disorders often manifest as abnormal fetal or childhood development. Copy number variations (CNVs) represent a significant genetic mechanism underlying such disorders. Despite their importance, the effectiveness of clinical exome sequencing (CES) in detecting CNVs, particularly small ones, remains incompletely understood. We aimed to evaluate the detection of both large and small CNVs using CES in a substantial clinical cohort, including parent–offspring trios and proband only analysis.MethodsWe conducted a retrospective analysis of CES data from 2428 families, collected from 2018 to 2021. Detected CNV were categorized as large or small, and various validation techniques including chromosome microarray (CMA), Multiplex ligation-dependent probe amplification assay (MLPA), and/or PCR-based methods, were employed for cross-validation.ResultsOur CNV discovery pipeline identified 171 CNV events in 154 cases, resulting in an overall detection rate of 6.3%. Validation was performed on 113 CNVs from 103 cases to assess CES reliability. The overall concordance rate between CES and other validation methods was 88.49% (100/113). Specifically, CES demonstrated complete consistency in detecting large CNV. However, for small CNVs, consistency rates were 81.08% (30/37) for deletions and 73.91% (17/23) for duplications.ConclusionCES demonstrated high sensitivity and reliability in CNV detection. It emerges as an economical and dependable option for the clinical CNV detection in cases of developmental abnormalities, especially fetal structural abnormalities.

Confirmation and pathogenicity of small copy number variations incidentally detected via a targeted next-generation sequencing–based preimplantation genetic testing for aneuploidy platform

ObjectiveTo evaluate the technical accuracy, inheritance, and pathogenicity of small copy number variants (CNVs) detected by a targeted next-generation sequencing (NGS)-based PGT-A platform. DesignRetrospective observational study performed between 2020-2022. Subjects12,157 patients who underwent clinical PGT-A performed by targeted NGS for whole chromosome and large segmental aneuploidies. ExposureAn incidental finding was reported when a CNV gain/loss of at least three consecutive amplicons appeared in at least two embryos from the same IVF cycle. Main Outcome MeasuresThe primary outcome measures were the specificity, incidence, inheritance, and pathogenicity of small CNVs detected by the PGT-A platform. Accuracy of the PGT-A platform CNV calls was assessed via concordance with the CNV calls (size and genomic location) on chromosomal microarray of the gamete provider(s). Parental origin of the CNV and pathogenicity classifications were also reported. ResultsIn 75 of 12,157 unique PGT-A patients (0.62%;95%CI:0.5-0.8%), an incidental finding that met reporting criteria was identified. Chromosomal microarray follow-up was requested for all cases and results were received for one or both members of 65 reproductive couples. In all cases, one of the gamete providers was confirmed to have the CNV identified in the embryos (100.0%: N=65/65 95%CI:94.5-100). The identified CNV was of maternal origin in 34 cases (52.3%) and of paternal origin in 31 cases (47.7%). A significant correlation was identified between PGT-A-predicted CNV sizes and chromosomal microarray detected sizes (r=0.81) and genomic coordinates on parental DNA. Twenty-six (40%) of the CNVs were classified as benign/likely benign, 30 (46.2%) as a variant of uncertain significance (VUS), and 9 (13.8%) as pathogenic/likely pathogenic. ConclusionCertain PGT-A platforms may enable the detection of inherited, small CNVs with extremely high specificity without prior knowledge of parental status. The majority of CNVs in this data set were confirmed to be benign/likely benign or a VUS; however, pathogenic/likely pathogenic CNVs associated with a broad range of phenotypic features may also be detected, although a reliable negative predictive value for small CNVs with current PGT-A technologies is unknown due to the many technical challenges.

Comparison of exon-level copy number variants in CytoScan XON assay and next-generation sequencing in clinical samples

Background and aimsNext-generation sequencing (NGS)-based copy number variants (CNVs) have high false-positive rates. The fewer the exons involved, the higher the false-positive rate. A CytoScan XON assay was developed to assess exon-level CNVs. Materials and methodsTwenty-three clinically relevant exon-level CNVs in 20 patient blood samples found in previous NGS studies were compared with the results from the CytoScan XON and multiplex ligation-dependent probe amplification (MLPA). ResultsFifteen of the 23 exon-level CNVs were consistent with the NGS results. Among these, eight were confirmed using MLPA. In six out of eight discrepancies between the CytoScan Xon and NGS, MLPA was performed, and three were negative, indicating that the CNVs in NGS were false positives. The CytoScan XON exhibits a sensitivity of 72.7% for small exon-level CNVs, along with a specificity of 100%. The assay could not detect the three exon-level CNVs in PKD1 and TSC2 that were detected using both NGS and MLPA. This could be due to the distribution of the probes in some areas, and the CNV-calling regions containing multiple exons. ConclusionThe CytoScan XON assay is a promising complementary tool for the detection of exon-level CNVs, provided that the users carefully examine the distribution of probes and calling regions.

Identification of TP53 germline variants in pediatric patients undergoing tumor testing: strategy and prevalence.

TP53 alterations are common in certain pediatric cancers, making identification of putative germline variants through tumor genomic profiling crucial for disease management. We analyzed TP53 alterations in 3123 tumors from 2788 pediatric patients sequenced using tumor-only or tumor-normal paired panels. Germline confirmatory testing was performed when indicated. Somatic and germline variants were classified based on published guidelines. In 248 tumors from 222 patients, 284 tier 1/2 TP53 sequence and small copy number variants were detected. Following germline classification, 86.6% of 142 unique variants were pathogenic or likely pathogenic. Confirmatory testing on 118 patients revealed germline TP53 variants in 28 of them (23 pathogenic or likely pathogenic and 5 of uncertain significance), suggesting a minimum Li-Fraumeni syndrome incidence of 0.8% (23/2788) in this cohort, 10.4% (23/222) in patients with TP53 variant-carrying tumors, and 19.5% (23/118) with available normal samples. About 25% (7/28) of patients with germline TP53 variants did not meet Li-Fraumeni syndrome diagnostic or testing criteria, while 20.9% (28/134) with confirmed or inferred somatic origins did. TP53 biallelic inactivation occurred in 75% of germline carrier tumors and was also prevalent in other groups, causing an elevated tumor-observed variant allelic fraction. Somatic evidence, however, including low variant allele fraction correctly identified only 27.8% (25/90) of patients with confirmed somatic TP53 variants. The high incidence and variable phenotype of Li-Fraumeni syndrome in this cohort highlights the importance of assessing germline status of TP53 variants identified in all pediatric tumors. Without clear somatic evidence, distinguishing somatic from germline origins is challenging. Classifying germline and somatic variants should follow appropriate guidelines.

Multi-omic profiling of simultaneous ductal carcinoma in situ and invasive breast cancer

PurposeThe progression of ductal carcinoma in situ (DCIS) to invasive breast carcinoma (IBC) in humans is highly variable. To better understand the relationship between them, we performed a multi-omic characterization of co-occurring DCIS and IBC lesions in a cohort of individuals.MethodsFormalin-fixed paraffin-embedded tissue samples from 50 patients with co-occurring DCIS and IBC lesions were subjected to DNA-seq and whole transcriptome RNA-seq. Paired DCIS and IBC multi-omics profiles were then interrogated for DNA mutations, gene expression profiles and pathway analysis.ResultsMost small variants and copy number variations were shared between co-occurring DCIS and IBC lesions, with IBC exhibiting on average a higher degree of additional mutations. However, 36% of co-occurring lesions shared no common mutations and 49% shared no common copy number variations. The most frequent genomic variants in both DCIS and IBC were PIK3CA, TP53, KMT2C, MAP3K1, GATA3 and SF3B1, with KMT2C being more frequent in DCIS and TP53 and MAP3K1 more frequent in IBC, though the numbers are too small for definitive conclusions. The most frequent copy number variations were seen in MCL1, CKSB1 and ERBB2. ERBB2 changes were not seen in IBC unless present in the corresponding DCIS. Transcriptional profiles were highly distinct between DCIS and IBC, with DCIS exhibiting upregulation of immune-related signatures, while IBC showed significant overexpression in genes and pathways associated with cell division and proliferation. Interestingly, DCIS and IBC exhibited significant differential expression of different components of extracellular matrix (ECM) formation and regulation, with DCIS showing overexpression of ECM-membrane interaction components while IBC showed upregulation of genes associated with fibronectin and invadopodia.ConclusionWhile most co-occurring DCIS and IBC were mutationally similar and suggestive of a common clonal progenitor, transcriptionally the lesions are highly distinct, with IBC expressing key pathways that facilitate invasion and proliferation. These results are suggestive of additional levels of regulation, epigenetic or other, that facilitate the acquisition of invasive properties during tumor evolution.

High-resolution genomic profiling and locus-specific FISH in subcutaneous and visceral adipose tissue of obese patients.

Obesity is known as a heterogeneous and multifactorial disease. The distribution of body fat is crucial for the development of metabolic complications. Comprehensive genetic analyses on different fat tissues are rare but necessary to provide more detailed information. Therefore, we performed genetic analyses of three patients with obesity using high resolution genome wide SNP array (blood, visceral fat tissue) and fluorescence in situ hybridization (FISH) analyses (visceral and subcutaneous fat tissue). Altogether, we identified 31 small Copy Number Variations (losses: 1p31.1, 1p22.2, 1q21.3, 2q34, 2q37.1, 3q28, 6p25.3, 7q31.33, 7q33, 8p23.3, 10q22.3, 11p15.4, 11p15.1, 11p14.2, 11p12, 13q12.3, 15q11.2-q13.1, 15q13.3, 20q13.2, 22q11.21; gains: 2q22.1-q22.2, 3p14.3, 4p16.3, 4q32.2, 6q27, 7p14.3, 7q34, 11p12, 12p11.21, 16p11.2-p11.1, 17q21.31) and 289 small copy-neutral Loss of Heterozygosity (cn-LOH). For the chromosomal region 15q11.2-q13.1, we detected a microdeletion (Prader-Willi-Syndrome) in one patient. Interestingly, we identified chromosomal SNP differences between EDTA-blood and visceral fat tissue (deletion and gain). Small losses of 7q31.33, 7q33, 11p14.2, 11p12, 13q12.3 as well as small gain of 7q34 were detected only in fat tissue and not in blood. Furthermore, FISH analyses on 7q31.33, 7q33 and 11p12 revealed differences between subcutaneous and visceral fat tissue. Generally, the deletions were detected more frequent in visceral fat tissue. Predominantly detected cn-LOH vs. CNV suggests a meaning of these cn-LOH for the pathogenesis of obesity. We conclude that the SNP array and FISH analyses used is applicable to generate more information for basic research on difficult cell subpopulations (e.g., visceral adipose tissue) and could opens up new diagnostic aspects in the field of obesity. Altogether, the significance of these mostly not yet described genetic aberrations in different fat tissues needs to confirmed in a larger series.

Extended application of PGT-M strategies for small pathogenic CNVs.

The preimplantation genetic testing for aneuploidy (PGT-A) platform is not currently available for small copy-number variants (CNVs), especially those < 1 Mb. Through strategies used in PGT for monogenic disease (PGT-M), this study intended to perform PGT for families with small pathogenic CNVs. Couples who carried small pathogenic CNVs and underwent PGT at the Reproductive and Genetic Hospital of CITIC-Xiangya (Hunan, China) between November 2019 and April 2023 were included in this study. Haplotype analysis was performed through two platforms (targeted sequencing and whole-genome arrays) to identify the unaffected embryos, which were subjected to transplantation. Prenatal diagnosis using amniotic fluid was performed during 18-20 weeks of pregnancy. PGT was successfully performed for 20 small CNVs (15 microdeletions and 5 microduplications) in 20 families. These CNVs distributed on chromosomes 1, 2, 6, 7, 13, 15, 16, and X with sizes ranging from 57 to 2120 kb. Three haplotyping-based PGT-M strategies were applied. A total of 89 embryos were identified in 25 PGT cycles for the 20 families. The diagnostic yield was 98.9% (88/89). Nineteen transfers were performed for 17 women, resulting in a 78.9% (15/19) clinical pregnancy rate after each transplantation. Of the nine women who had healthy babies, eight accepted prenatal diagnosis and the results showed no related pathogenic CNVs. Our results show that the extended haplotyping-based PGT-M strategy application for small pathogenic CNVs compensated for the insufficient resolution of PGT-A. These three PGT-M strategies could be applied to couples with small pathogenic CNVs.

Genome-wide investigation to assess copy number variants in the Italian local chicken population.

Copy number variants (CNV) hold significant functional and evolutionary importance. Numerous ongoing CNV studies aim to elucidate the etiology of human diseases and gain insights into the population structure of livestock. High-density chips have enabled the detection of CNV with increased resolution, leading to the identification of even small CNV. This study aimed to identify CNV in local Italian chicken breeds and investigate their distribution across the genome. Copy number variants were mainly distributed across the first six chromosomes and primarily associated with loss type CNV. The majority of CNV in the investigated breeds were of types 0 and 1, and the minimum length of CNV was significantly larger than that reported in previous studies. Interestingly, a high proportion of the length of chromosome 16 was covered by copy number variation regions (CNVR), with the major histocompatibility complex being the likely cause. Among the genes identified within CNVR, only those present in at least five animals across breeds (n = 95) were discussed to reduce the focus on redundant CNV. Some of these genes have been associated to functional traits in chickens. Notably, several CNVR on different chromosomes harbor genes related to muscle development, tissue-specific biological processes, heat stress resistance, and immune response. Quantitative trait loci (QTL) were also analyzed to investigate potential overlapping with the identified CNVR: 54 out of the 95 gene-containing regions overlapped with 428 QTL associated to body weight and size, carcass characteristics, egg production, egg components, fat deposition, and feed intake. The genomic phenomena reported in this study that can cause changes in the distribution of CNV within the genome over time and the comparison of these differences in CNVR of the local chicken breeds could help in preserving these genetic resources.

A novel case of 16q22.3 duplication syndrome in a child with overgrowth: case report and literature review

BackgroundDistal chromosome 16 duplication syndrome (also known as 16q partial trisomy) is a very rare genetic disorder recently described in few clinical reports. 16q trisomy is generally associated with a multisystemic phenotype including intrauterine growth restriction (IUGR), brain and cardiac defects, intellectual disability (ID) and an increased risk of both prenatal and postnatal lethality. Smaller copy number variants (CNV) within the 16q region create partial trisomies, which occur less frequently than full trisomy 16q.Case presentationWe present the clinical case of a 12-years-old male with a 16q22.3q24.1 de novo heterozygous duplication whose phenotype was characterized by ID, facial dysmorphisms, stature and weight overgrowth. To date, only five other cases of this syndrome have been reported in scientific literature, and none of them comprised overgrowth.ConclusionsOur case report highlights the great heterogeneity in clinical manifestations and provides new evidence for better defining the phenotypic picture for smaller 16q distal CNVs, suggesting unusual features.

Rare copy number variation in the GR@ACE/DEGESCO dementia dataset of spanish population

AbstractBackgroundRecent studies have found that duplications or deletions of DNA fragments, known as copy number variants (CNVs), may play a role in missing heritability for complex human diseases.MethodIn that sense, we conducted a scan for CNVs in the GR@ACE/DEGESCO dementia dataset of Spanish population1 (n = 20,080 individuals using Axiom 815K Spanish biobank array (Thermo Fisher)). We ran CNV calling algorithms from PennCNV software to obtain high‐confidence calls for CNVs. After extensive quality control (QC) for individuals (sex discrepancies, excess of heterozygosity, high missingness, familiar relations and population outliers were excluded), CNVs (&gt;50kb and nSNPs&gt;10 were included), removing spurious CNVs in telomeric/centromeric regions, gene QC (ANOVA comparisons between DNA origin source evaluated in controls), 8,275 controls and 7,818 dementia cases were selected for following analysis.ResultGlobal burden analyses revealed highly significant differences between dementia cases and controls (dem/ctrl) in CNV rate of deletions (p = 2.69E‐04, meanctrl‐dem = 1.53‐1.38) but not in duplications (p = 0.535, meanctrl‐dem = 1.63‐1.61). However, only the number of genes affected by CNVs was significantly different in deletions (p = 0.042, meanctrl‐dem = 3.62‐3.10; duplications p = 0.448, meanctrl‐dem = 5.93‐5.68). We also observed a nominal deletion‐gene‐affected association by genes related to nervous system development pathway or intellectual disability such as VPS13B2 (nine cases affected), PKP3 (Freqctrl‐dem 0.17‐0.25%) and FBRSL13 (Freqctrl‐dem 0.15‐0.26%). The current study did not detect significant differences in CNVs that affect known Alzheimer’s disease (AD) loci identified by recent genome‐wide association studies4 (deletions Fisher test p = 0.0875, duplications Fisher Test p = 0.5853). Nevertheless, we found three important AD genes with CNVs potentially associated to dementia. Specifically, we detected MAPT protective deletions (Freqctrl‐dem 0.16‐0.01%), ABCA7 risk deletions (Freqctrl‐dem 0.05‐0.14%) and APP CNVs detected in five dementia cases (0.064%). Because the technology used in our study has limitations in detecting small CNVs, future studies must carefully assess the presence of smaller CNVs and their relationship with dementia.ConclusionWe have detected potential CNVs in the Spanish population for Alzheimer’s disease, however, because the technology used in our study has limitations in detecting small CNVs, future studies must carefully assess the presence of smaller CNVs and their relationship with dementia.

Identification of the first homozygous intragenic deletion in the YY1AP1 gene in a consanguineous family: New insights into the phenotypic variability associated with Grange syndrome.

Grange syndrome (GRNG-MIM#135580) is a rare recessive disorder associating variable features including diffuse vascular stenosis, brachysyndactyly, osteopenia with increased bone fragility, cardiac malformations, and variable developmental delay. Since its first description in 1998, only 15 individuals from 10 families have been reported, carrying homozygous or compound heterozygous frameshift or nonsense variants in YY1AP1. In a patient with cutaneous and bone syndactyly and a hemorrhagic stroke at the age of 16 months, consistent with a clinical diagnosis of GRNG, we performed exome sequencing after negative array-CGH and congenital limb malformation panel results. Copy number variant analysis from exome data identified a homozygous intragenic out-of-frame deletion of 1.84 kb encompassing exons seven and eight of YY1AP1, confirming a molecular diagnosis of GRNG. Genetic counseling led to the identification of additional family members compatible with GRNG. Here, we provide new insights into the phenotypic variability associated with GRNG and highlight the utility of the detection of small copy number variants to identify the molecular causes of heterogeneous malformative genetic disorders.

A cryptic microdeletion del(12)(p11.21p11.23) within an unbalanced translocation t(7;12)(q21.13;q23.1) implicates new candidate loci for intellectual disability and Kallmann syndrome

In a patient diagnosed with both Kallmann syndrome (KS) and intellectual disability (ID), who carried an apparently balanced translocation t(7;12)(q22;q24)dn, array comparative genomic hybridization (aCGH) disclosed a cryptic heterozygous 4.7 Mb deletion del(12)(p11.21p11.23), unrelated to the translocation breakpoint. This novel discovery prompted us to consider the possibility that the combination of KS and neurological disorder in this patient could be attributed to gene(s) within this specific deletion at 12p11.21-12p11.23, rather than disrupted or dysregulated genes at the translocation breakpoints. To further support this hypothesis, we expanded our study by screening five candidate genes at both breakpoints of the chromosomal translocation in a cohort of 48 KS patients. However, no mutations were found, thus reinforcing our supposition. In order to delve deeper into the characterization of the 12p11.21-12p11.23 region, we enlisted six additional patients with small copy number variations (CNVs) and analyzed eight individuals carrying small CNVs in this region from the DECIPHER database. Our investigation utilized a combination of complementary approaches. Firstly, we conducted a comprehensive phenotypic-genotypic comparison of reported CNV cases. Additionally, we reviewed knockout animal models that exhibit phenotypic similarities to human conditions. Moreover, we analyzed reported variants in candidate genes and explored their association with corresponding phenotypes. Lastly, we examined the interacting genes associated with these phenotypes to gain further insights. As a result, we identified a dozen candidate genes: TSPAN11 as a potential KS candidate gene, TM7SF3, STK38L, ARNTL2, ERGIC2, TMTC1, DENND5B, and ETFBKMT as candidate genes for the neurodevelopmental disorder, and INTS13, REP15, PPFIBP1, and FAR2 as candidate genes for KS with ID. Notably, the high-level expression pattern of these genes in relevant human tissues further supported their candidacy. Based on our findings, we propose that dosage alterations of these candidate genes may contribute to sexual and/or cognitive impairments observed in patients with KS and/or ID. However, the confirmation of their causal roles necessitates further identification of point mutations in these candidate genes through next-generation sequencing.

O-210 Detection of small copy number variations as incidental findings in PGT-A: clinical utility from a multisite experience including 12,157 patients

Abstract Study question What is the technical accuracy and clinical utility of reporting small copy number variants (CNVs below 3Mb) detected by a targeted next-generation sequencing-based PGT-A platform? Summary answer Some pathogenic or likely pathogenic CNVs &amp;lt;3Mb can be accurately detected by this assay, increasing clinical utility of PGT-A for a subset of IVF patients. What is known already CNVs are linked to a wide range of phenotypes, spanning from syndromes that include reduced penetrance and variable expressivity to more severe phenotypes. Prenatally, the prevalence of pathogenic CNVs is approximately 1.5%. Most PGT-A platforms that rely on whole genome amplification and shallow sequencing have a resolution limit of 5-10 Mb, preventing the detection of smaller CNVs. Here, we report an innovative PGT-A assay that interrogates thousands of targeted sites in the genome to provide robust copy number analysis allowing for the identification of some small CNVs (incidental findings, IF), outside the primary scope of detecting whole-chromosome aneuploidies in PGT-A. Study design, size, duration Retrospective observational study performed between 2020-2022, involving 12,157 patients who underwent PGT-A performed by targeted-NGS (PGTseq-A) for whole chromosome and large segmental aneuploidies. If an IF &amp;lt; 3 Mb was detected in multiple embryos, the couple was advised to undergo follow-up analysis by chromosomal microarray (CMA) to confirm the parental origin of the CNV, define its breakpoints and determine whether it is classified as benign-likely benign (B/LB), variant of uncertain significance (VUS) or pathogenic-likely pathogenic (P/LP). Participants/materials, setting, methods The PGTseq-A assay employed amplifies 5,000 amplicons across the genome to evaluate copy number. Validation was performed using 5-cell samples from cell lines with known CNVs, and trophectoderm biopsies from embryos with known parental structural rearrangements. An IF was reported when a gain/loss of at least three consecutive amplicons appeared in at least two embryos from the same cycle. Transfer data was reviewed to determine which embryos were transferred. This study received IRB approval. Main results and the role of chance In 77 out of 12,157 PGT-A patients (0.63%;95%CI:0.5-0.8%), an IF that met reporting criteria was identified. To determine the size and pathogenicity, a CMA follow up was requested and performed on 67 couples. In all cases, one of the partners was confirmed to have the CNV identified in the embryos (100.0%: N 67/67 95%CI:94.6-100). The identified CNV was of maternal origin in 36 cases (53.7%) and of paternal origin in 31 cases (46.2%). A strong correlation was identified between PGT-A-predicted CNVs and the genomic coordinates defined by the CMA on parental DNA (r = 0.86). All CNVs intervals predicted by the PGT-A included the CMA genomic region. Twenty-seven (40.2%) were classified as B/LB, 31 (46.2%) as a VUS, and 9 (13.4%) as P/LP. Six of the nine P/LP cases (66.6%) involved imbalances of 16p. The remaining P/LP cases involved deletions of X, 15q and 18p11.32. From a review of transfer data, patients typically transferred embryos negative for IFs as first option regardless of the morphology and pathogenicity classification of CNV-positive sibling embryos. Specifically, in 8 cycles where a detected CNV was classified as B, LB or as VUS, negative embryos were prioritized for transfer despite their poorer morphology. Limitations, reasons for caution De novo CNVs were not considered by design because the reported CNVs had to be present in at least two embryos from the same cohort. Furthermore, the detection of small CNVs is not uniform in the genome and the negative predictive value of the assay for non-targeted regions is null. Wider implications of the findings This PGT-A assay accurately detects small pathogenic CNVs without prior knowledge of parental inheritance, enhancing clinical utility in a subset of patients. Additionally, reporting of VUS and B/LB findings may impact couples’ decision-making concerning embryo selection, reinforcing that scientific rigor is a necessity when evaluating the capabilities of PGT-A. Trial registration number not applicable

Abstract 6162: High resolution detection of HER2 copy number variation in admixed breast cancer cell lines and HER2+ FFPE donor tissue using a digital PCR multigene reference panel

Abstract The measurement of HER2 (ERBB2) gene amplification guides both the prognosis and treatment of breast cancer, as amplification correlates with worse outcomes and the recommendation for anti-HER2 treatment. Digital PCR (dPCR) can serve as a useful tool for the direct quantification of copy number variants (CNV) in this gene, without the need for calibration standards as required for qPCR, or labor-intensive histological techniques such as FISH. Furthermore, increasing the number of available partitions in a digital PCR reaction can yield substantial gains in precision, thus offering the potential for ultra-high resolution discrimination of copy number changes. In this study, we evaluated the utility of a multiplex dPCR assay for the high-resolution detection of HER2 copy number variation in clinically relevant samples. The precision achievable by digital PCR correlates with the number of partitions, and the resolution of small CNV differences greatly relies on high precision. We utilized a dPCR setup with ~100,000 physical partitions per reaction, which allowed for a theoretical precision (relative confidence) of 1%, assuming optimal input and template. Five single-plex primer and probe sets, published by the National Institute of Standards and Technology, were assembled and optimized into a multiplex configuration. The final 5-plex consisted of four reference genes and HER2 as the target of interest. The accuracy and precision of the optimized five-plex assay was tested in nine breast cancer cell lines with established HER2 amplification ratios, ranging from 1.3 to 70 fold. The assay demonstrated the precise and accurate measurement of the HER2 amplification ratio across all nine cell lines over a wide dynamic range of sample input. Along with increasing the reaction partition number, the use of multiple reference genes also improved the precision of the HER2 amplification ratio measurement and avoided inaccurate copy number calls due to outlier references. The resolution of the assay was evaluated using admixed samples simulating low tumor fraction. A minimum of a 1.03 fold difference (3% difference from wild type) was detected with statistical significance. Assay concordance was evaluated against IHC-characterized HER2+ FFPE donor tissue with concordant FISH/CISH results. The assay demonstrated robust performance in clinically relevant sample types, supporting further investigation of dPCR as a complementary or even alternative diagnostic approach to current methods. Citation Format: Tyler Landrith, Samantha Smith, Jennifer Chan, Mari Christensen, Yu Chuan Tai, Megan Gonzales, William Yee, Nicolas Newton, Wouter Pattje, Patrick Bogard, Wei Yang. High resolution detection of HER2 copy number variation in admixed breast cancer cell lines and HER2+ FFPE donor tissue using a digital PCR multigene reference panel [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6162.

Rare copy number variation analysis identifies disease-related variants in atrioventricular septal defect patients.

Atrioventricular septal defect (AVSD) is a deleterious subtype of congenital heart diseases (CHD) characterized by atrioventricular canal defect. The pathogenic genetic changes of AVSD remain elusive, particularly for copy number variation (CNV), a large segment variation of the genome, which is one of the major forms of genetic variants resulting in congenital heart diseases. In the present study, we recruited 150 AVSD cases and 100 healthy subjects as controls for whole exome sequencing (WES). We identified total 4255 rare CNVs using exon Hidden Markov model (XHMM) and screened rare CNVs by eliminating common CNVs based on controls and Database of Genomic Variants (DGV). Each patient contained at least 9 CNVs, and the CNV burden was prominently presented in chromosomes 19,22,21&16. Small CNVs (<500kb) were frequently observed. By leveraging gene-based burden test, we further identified 20 candidate AVSD-risk genes. Among them, DYRK1A, OBSCN and TTN were presented in the core disease network of CHD and highly and dynamically expressed in the heart during the development, which indicated they possessed the high potency to be AVSD-susceptible genes. These findings not only provided a roadmap for finally unveiling the genetic cause of AVSD, but also provided more resources and proofs for clinical genetics.

A novel scatterplot-based method to detect copy number variation (CNV).

Objective: Most methods to detect copy number variation (CNV) have high false positive rates, especially for small CNVs and in real-life samples from clinical studies. In this study, we explored a novel scatterplot-based method to detect CNVs in microarray samples. Methods: Illumina SNP microarray data from 13,254 individuals were analyzed with scatterplots and by PennCNV. The data were analyzed without the prior exclusion of low-quality samples. For CNV scatterplot visualization, the median signal intensity of all SNPs located within a CNV region was plotted against the median signal intensity of the flanking genomic region. Since CNV causes loss or gain of signal intensities, carriers of different CNV alleles pop up in clusters. Moreover, SNPs within a deletion are not heterozygous, whereas heterozygous SNPs within a duplication show typical 1:2 signal distribution between the alleles. Scatterplot-based CNV calls were compared with standard results of PennCNV analysis. All discordant calls as well as a random selection of 100 concordant calls were individually analyzed by visual inspection after noise-reduction. Results: An algorithm for the automated scatterplot visualization of CNVs was developed and used to analyze six known CNV regions. Use of scatterplots and PennCNV yielded 1019 concordant and 108 discordant CNV calls. All concordant calls were evaluated as true CNV-findings. Among the 108 discordant calls, 7 were false positive findings by the scatterplot method, 80 were PennCNV false positives, and 21 were true CNVs detected by the scatterplot method, but missed by PennCNV (i.e., false negative findings). Conclusion: CNV visualization by scatterplots allows for a reliable and rapid detection of CNVs in large studies. This novel method may thus be used both to confirm the results of genome-wide CNV detection software and to identify known CNVs in hitherto untyped samples.

CNV-PCC: An efficient method for detecting copy number variations from next-generation sequencing data.

Copy number variations (CNVs) significantly influence the diversity of the human genome and the occurrence of many complex diseases. The next-generation sequencing (NGS) technology provides rich data for detecting CNVs, and the read depth (RD)-based approach is widely used. However, low CN (copy number of 3-4) duplication events are challenging to identify with existing methods, especially when the size of CNVs is small. In addition, the RD-based approach can only obtain rough breakpoints. We propose a new method, CNV-PCC (detection of CNVs based on Principal Component Classifier), to identify CNVs in whole genome sequencing data. CNV-PPC first uses the split read signal to search for potential breakpoints. A two-stage segmentation strategy is then implemented to enhance the identification capabilities of low CN duplications and small CNVs. Next, the outlier scores are calculated for each segment by PCC (Principal Component Classifier). Finally, the OTSU algorithm calculates the threshold to determine the CNVs regions. The analysis of simulated data results indicates that CNV-PCC outperforms the other methods for sensitivity and F1-score and improves breakpoint accuracy. Furthermore, CNV-PCC shows high consistency on real sequencing samples with other methods. This study demonstrates that CNV-PCC is an effective method for detecting CNVs, even for low CN duplications and small CNVs.

139. Feasibility of comprehensive whole genome profiling in hematological malignancies

Whole genome sequencing (WGS) has been recently proposed as a replacement for routine karyotype and FISH analyses of myeloid and lymphoid neoplasms. WGS allows for the unbiased and comprehensive detection of multiple types of genomic aberrations, from single nucleotide to structural variants, which could streamline current genomic testing algorithms and clinical laboratory workflows for hematologic malignancies. In this study, we explored the feasibility of whole genome profiling of myeloid and lymphoid neoplasms by sequencing eleven AML, MPN, MDS, B-ALL, and T-ALL genomes with an average depth of sequencing coverage of ∼40X, and comparing genome analyses data to their available cytogenetic and molecular panel results. 81% of clinically relevant SNVs were detected by WGS, with false negatives being mostly variants at low frequencies (VAF <10%). Nine new variants were detected by WGS in an AML, B-ALL and T-ALL samples, eight of which were classified as VUS, and one (FLT3 p.Tyr572Cys) in B-ALL as likely pathogenic. 95% of clinically relevant copy-number variants (CNVs) were detected by WGS, with false negatives being mostly small (<150Kb) or mosaic CNVs present in <15% of the sample. The identification of the clinically relevant translocations in these samples (such as ETV6/RUNX1 and CRLF2 rearrangements) using WGS data is currently being investigated. This feasibility study demonstrated the potential of using WGS as the replacement of molecular panels and chromosome microarray in hematologic malignancies, particularly at the time of initial diagnosis.

A rigorous in silico genomic interrogation at 1p13.3 reveals 16 autosomal dominant candidate genes in syndromic neurodevelopmental disorders.

Genome-wide chromosomal microarray is extensively used to detect copy number variations (CNVs), which can diagnose microdeletion and microduplication syndromes. These small unbalanced chromosomal structural rearrangements ranging from 1 kb to 10 Mb comprise up to 15% of human mutations leading to monogenic or contiguous genomic disorders. Albeit rare, CNVs at 1p13.3 cause a variety of neurodevelopmental disorders (NDDs) including development delay (DD), intellectual disability (ID), autism, epilepsy, and craniofacial anomalies (CFA). Most of the 1p13.3 CNV cases reported in the pre-microarray era encompassed a large number of genes and lacked the demarcating genomic coordinates, hampering the discovery of positional candidate genes within the boundaries. In this study, we present four subjects with 1p13.3 microdeletions displaying DD, ID, autism, epilepsy, and CFA. In silico comparative genomic mapping with three previously reported subjects with CNVs and 22 unreported DECIPHER CNV cases has resulted in the identification of four different sub-genomic loci harboring five positional candidate genes for DD, ID, and CFA at 1p13.3. Most of these genes have pathogenic variants reported, and their interacting genes are involved in NDDs. RT-qPCR in various human tissues revealed a high expression pattern in the brain and fetal brain, supporting their functional roles in NDDs. Interrogation of variant databases and interacting protein partners led to the identification of another set of 11 potential candidate genes, which might have been dysregulated by the position effect of these CNVs at 1p13.3. Our studies define 1p13.3 as a genomic region harboring 16 NDD candidate genes and underscore the critical roles of small CNVs in in silico comparative genomic mapping for disease gene discovery. Our candidate genes will help accelerate the isolation of pathogenic heterozygous variants from exome/genome sequencing (ES/GS) databases.