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PubMed2026

MarkerMatch: a proximity-based probe-matching algorithm for joint analysis of copy-number variants from different genotyping arrays.

MOTIVATION: Copy-number variants (CNVs) are a form of genetic structural variation with increasing importance in complex human disorders. Both DNA sequencing and microarray data can be used to detect CNVs, which can be used in genetic association tests. Unlike genotypes, CNV detection in microarrays requires the use of observed intensity signals at each probe, which limits the imputability for analyses that span multiple array types. Thus far, a consensus set of probes (those present on all arrays) has been used to circumvent the problem of differing array-specific sensitivities. This has led to excessive reduction in overall sensitivity since arrays can have an undesirably low probe overlap. To overcome this limitation, we developed MarkerMatch, a proximity-based algorithm that matches probes across different genotyping microarrays to maximize the number of probes considered in the CNV calling algorithm, thereby increasing the resolution and sensitivity while preserving precision. RESULTS: By analyzing CNV calls from 4906 individuals genotyped across three different arrays, we show that the MarkerMatch approach improves sensitivity by increasing the density of probes available for CNV calling while maintaining precision or improving it relative to the current practice (e.g. use of consensus probes only). We further demonstrate that MarkerMatch matches the CNV detection from current practice in terms of F1 score and PPV for larger CNVs. We also optimize MarkerMatch parameters, DMAX and Method, and find an optimal DMAX setting at 10 kb, with no clear optimal candidate based on Method, indicating that parameters for this metric should be determined on a use case basis. AVAILABILITY: The R package for MarkerMatch is available at: https://github.com/FranjoIM/MarkerMatch. The code used for analysis and implementation is available at: https://doi.org/10.5281/zenodo.18460979. The live notebook is available at https://fivankovic.notion.site/2026-markermatch.

DNA Copy Number Variations↗

PubMed2025

MarkerMatch: A Proximity-Based Probe-Matching Algorithm for Joint Analysis of Copy-Number Variants from Different Genotyping Arrays.

MOTIVATION: Copy-number variants (CNVs) are a form of genetic structural variation with increasing importance in complex human disorders. Both DNA sequencing and microarray data can be used to call CNVs, which can be used in association tests, such as association between CNV number and disease status. Unlike genotypes, CNV detection in microarrays requires the use of observed intensity signals at each probe, which limits the imputability for analyses that span multiple array types. Thus far, a consensus set of probes (the intersection encompassing the probes that occur in common on all arrays) has been used to circumvent the problem of differing array-specific sensitivities. This has, however, led to excessive reduction in overall sensitivity of CNV calls as arrays can have an undesirably low overlap of probe sets. To overcome this limitation, we developed MarkerMatch, a proximity-based algorithm that matches probes across different genotyping microarrays to maximize the number of probes considered in the CNV calling algorithm, thereby increasing the resolution and sensitivity while preserving precision. RESULTS: By analyzing CNV calls from 4,906 individuals genotyped across three different arrays (Global Screening Array, Omni2.5 array, and Omni Express Exome array), we show that the MarkerMatch approach improves sensitivity by increasing the density of probes available for CNV calling while maintaining precision or improving it relative to the current practice (e.g., use of consensus probes only). We further demonstrate that MarkerMatch exceeds the output from current practice in terms of F1 score, Fowlkes-Mallows index, and Jaccard index. We also optimize MarkerMatch parameters, D MAX and Method, and find an optimal D MAX setting at 10kb, with no clear optimal candidate based on Method, indicating that parameters for this metric should be determined on a use case basis.

Journal Article↗

PubMed2025

LYCEUM: learning to call copy number variants on low-coverage ancient genomes.

MOTIVATION: Copy number variants (CNVs) are pivotal in driving phenotypic variation that facilitates species adaptation. They are significant contributors to various disorders, making ancient genomes crucial for uncovering the genetic origins of disease susceptibility across populations. However, detecting CNVs in ancient DNA (aDNA) samples poses substantial challenges due to several factors: (i) aDNA is often highly degraded; (ii) contamination from microbial DNA and DNA from closely related species introduces additional noise into sequencing data; and finally, (iii) the typically low-coverage of aDNA renders accurate CNV detection particularly difficult. Conventional CNV calling algorithms, which are optimized for high-coverage read-depth signals, underperform under such conditions. RESULTS: To address these limitations, we introduce LYCEUM, the first machine learning-based CNV caller for aDNA. To overcome challenges related to data quality and scarcity, we employ a two-step training strategy. First, the model is pre-trained on whole genome sequencing data from the 1000 Genomes Project, teaching it CNV-calling capabilities similar to conventional methods. Next, the model is fine-tuned using high-confidence CNV calls derived from only a few existing high-coverage aDNA samples. During this stage, the model adapts to making CNV calls based on the downsampled read depth signals of the same aDNA samples. LYCEUM achieves accurate detection of CNVs even in typically low-coverage ancient genomes. We also observe that the segmental deletion calls made by LYCEUM show correlation with the demographic history of the samples and exhibit patterns of negative selection inline with natural selection. AVAILABILITY AND IMPLEMENTATION: LYCEUM is available at https://github.com/ciceklab/LYCEUM.

DNA Copy Number Variations↗

PubMed2024

Copy number variant scan in more than four thousand Holstein cows bred in Lombardy, Italy.

Copy Number Variants (CNV) are modifications affecting the genome sequence of DNA, for instance, they can be duplications or deletions of a considerable number of base pairs (i.e., greater than 1000 bp and up to millions of bp). Their impact on the variation of the phenotypic traits has been widely demonstrated. In addition, CNVs are a class of markers useful to identify the genetic biodiversity among populations related to adaptation to the environment. The aim of this study was to detect CNVs in more than four thousand Holstein cows, using information derived by a genotyping done with the GGP (GeneSeek Genomic Profiler) bovine 100K SNP chip. To detect CNV the SVS 8.9 software was used, then CNV regions (CNVRs) were detected. A total of 123,814 CNVs (4,150 non redundant) were called and aggregated into 1,397 CNVRs. The PCA results obtained using the CNVs information, showed that there is some variability among animals. For many genes annotated within the CNVRs, the role in immune response is well known, as well as their association with important and economic traits object of selection in Holstein, such as milk production and quality, udder conformation and body morphology. Comparison with reference revealed unique CNVRs of the Holstein breed, and others in common with Jersey and Brown. The information regarding CNVs represents a valuable resource to understand how this class of markers may improve the accuracy in prediction of genomic value, nowadays solely based on SNPs markers.

Cattle↗

PubMed2026

Contribution of copy number variants to schizophrenia in East Asian populations.

Studies on schizophrenia-associated rare copy number variants (CNVs) have predominantly focused on people of European (EUR) ancestry. Here we present a rare CNV study of schizophrenia in East Asian (EAS) populations, comprising 20,903 cases and 23,258 controls. We observed a significantly elevated genome-wide rare CNV burden in EAS cases compared with controls. Cross-population comparisons showed largely consistent rare CNV effects on schizophrenia risk. In the EAS sample, we identified nine genome-wide-significant schizophrenia-associated rare CNV loci. Meta-analysis with EUR data yielded 14 significant loci, including 8 that reached genome-wide significance for the first time. Genes within these 14 loci were significantly less tolerant to loss-of-function variants than genes in other CNV loci. The new rare CNVs associated with schizophrenia in EAS populations showed higher carrier frequencies in EAS than in EUR populations (0.38% versus 0.0017%). Overall, this study underscores the importance of increasing population diversity to fully capture the genetic underpinnings of schizophrenia.

Journal Article↗

PubMed2026

Identification of rare maternal copy number variants by genome-wide analysis of noninvasive prenatal screening data in 113,017 pregnant women.

OBJECTIVES: Knowledge of copy number variants (CNVs) is relevant to maternal and fetal health and can be obtained from noninvasive prenatal screening (NIPS) of pregnancy. However, genome-wide analysis of maternal CNVs using NIPS data has not been conducted in large populations. METHODS: For CNV analysis, the human genome was segmented into 10 kilobase pairs (Kb) bins, and the relative sequencing depth of each bin was calculated. The circular binary segmentation algorithm was used to estimate CNVs. Detected CNVs from two pregnancies of the same participant were compared to validate the reproducibility. All CNVs were merged into CNV regions (CNVRs) to evaluate their frequency, distributions, and relationship with disease-related genes and regions. RESULTS: In this study, 113,017 pregnant women were recruited. A total of 363,886 CNVs larger than 50 Kb were detected in 101,779 individuals and merged into 43,005 CNVRs. For evaluating the reproducibility of CNVs, 90.18% of deletions and 88.07% of duplications were consistent. In general, 78.13% of individuals carried CNVRs that overlapped protein-coding genes, while 14.76% overlapped OMIM genes. We detected 246 novel CNVRs, 134 (54.47%) involving protein-coding genes. For the perspective of maternal-fetal health, we identified 4,984 (4.41%) individuals as carriers of 5,243 CNVs containing known pathogenic or likely pathogenic regions, including 22q11.2 region and DMD gene.. CONCLUSIONS: NIPS sequencing data is a reliable source for maternal CNV detection. These CNVs constitute an integrate component in maternal-fetal health management.

Humans↗

PubMed2026

Copy number variants in BRCA1 and BRCA2 genes in Polish patients with breast and ovarian cancer.

PURPOSE: BRCA1 and BRCA2 are key susceptibility genes in hereditary breast and ovarian cancer (HBOC), with mutational status guiding PARP inhibitor therapy. While single-nucleotide variants (SNVs) predominate, the prevalence of copy number variants (CNVs) varies significantly across different populations. This study aims to determine the incidence of BRCA1/2 CNVs in the Polish population, where data remain scarce due to non-mandatory CNV testing. METHODS: We retrospectively analysed the results of genetic tests assessing the presence of BRCA1/2 CNVs performed in 2720 individuals tested at the Lower Silesian Oncology Centre (2021-2024), including 2702 breast/ovarian cancer patients and 18 unaffected relatives. The mean age was 54.7 ± 15.15 years. Genetic testing involved DNA extraction, NGS, and MLPA for CNV confirmation. Variants were classified according to ACMG-AMP guidelines and verified through independent testing. RESULTS: In this study, no BRCA2 CNVs were identified, consistent with previous Central European findings. Pathogenic BRCA1 CNVs were detected in 0.85% of the analyzed cohort and in 0.52% of the cancer patient subgroup, affecting 23 individuals from 13 families. Eight distinct BRCA1 CNVs were detected, the most common being exon 21 deletion. Affected families exhibited a high incidence of HBOC-related cancers, with early-onset breast cancer and a notable proportion of triple-negative breast cancer cases. CONCLUSIONS: This study highlights the clinical significance of BRCA1 CNVs in Polish patients with HBOC-spectrum cancers and their families. Although rare, these variants were associated with aggressive cancer phenotypes and early onset. Given their diagnostic and therapeutic implications, BRCA1 CNVs should be routinely analysed in high-risk families to ensure accurate detection and personalised treatment planning.

Humans↗

PubMed2021

1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans.

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

Brain↗

PubMed2025

CLINICAL AND COGNITIVE PHENOTYPING OF COPY NUMBER VARIANTS ASSOCIATED WITH NEURODEVELOPMENTAL DISORDERS FROM A MULTI-ANCESTRY BIOBANK.

Clinical biobanks with electronic health records (EHRs) linked to genotype data continue to expand yielding an opportunity to further characterize disease-relevant genomic risk factors, yet few recall-by-genotype studies from biobanks have been published to date. For example, copy number variants (CNVs) that significantly increase risk for multiple neurodevelopmental disorders (NDDs) and negatively affect neurocognition, may present in up to 2% of population cohorts, with public health implications for ascertaining NDD CNV carriers. From BioMe, a multi-ancestry biobank derived from the Mount Sinai healthcare system (New York, NY), 892 adult participants were recontacted for deep phenotyping, including 335 NDD CNV carriers as well as comparators, 217 individuals with schizophrenia and 340 controls. Clinical and cognitive assessments were administered to each participant. There was no disclosure of genetic information. Eight percent of recontacted biobank participants completed the study (30 NDD CNV carriers across 15 unique loci, 20 schizophrenia and 23 controls). The study sample had a mean age of 48.8 (10.2) years, was 66% female and of diverse ancestry, 36% African, 34% Hispanic, and 26% European. Overall, 70% of 30 NDD-CNV carriers harbored at least one neuropsychiatric or developmental phenotype, including 40% with mood or anxiety disorders. Further, 22 NDD CNV carriers were significantly impaired compared to controls on digit span backwards (Beta=-1.76, FDR=0.04) and digit span sequencing (Beta=-2.01, FDR=0.04), but higher performing than schizophrenia on verbal learning (Beta=4.5, FDR=0.05). Thirty NDD CNV carriers were successfully recruited from a multi-ancestry biobank, as well as healthy controls and low-functioning individuals with schizophrenia. Deep phenotyping corroborated past reports, while also identifying discordance with EHRs. Future recall-by-genotype studies may further benchmark the study design and elucidate feasibility.

Biobank↗

PubMed2026

Recall-by-genotype of neurodevelopmental disorder copy number variants in a multi-ancestry, healthcare-system biobank.

Clinical biobanks linking electronic health records (EHRs) with genotype data enable the study of genomic risk factors in real-world populations. However, recall-by-genotype (RbG) of psychiatric risk variants in diverse healthcare-system biobanks remains scarce. Leveraging BioMe, a multi-ancestry biobank within the Mount Sinai Health System, we recalled carriers of rare copy number variants (CNVs) that confer increased risk for neurodevelopmental disorders (NDDs) to establish empirical benchmarks for RbG implementation. We recontacted 892 participants: 335 NDD CNV carriers, 217 individuals with schizophrenia without NDD CNVs, and 340 neurotypical controls without NDD CNVs. Participants completed clinical and cognitive assessments. Overall, 18% of recontacted participants responded to recruitment, and 8% completed the study: 30 NDD CNV carriers, 20 individuals with schizophrenia, and 23 controls. The mean age was 48.8 years, 66% were female, and self-reported ancestry was 37% African, 34% Hispanic, and 26% European. Seventy percent of NDD CNV carriers had at least one neuropsychiatric or developmental condition, including mood or anxiety disorders (40%). Among 22 NDD CNV carriers at loci implicated in impaired cognition, performance was lower than controls on Digit Span Backward (β = -1.76, FDR = 0.04) and Digit Span Sequencing (β = -2.01, FDR = 0.04). NDD CNV carriers also outperformed the schizophrenia group on verbal learning (β = 4.5, FDR = 0.05). Recall of individuals-including those with psychiatric illness-yielded phenotypes not captured in EHRs and provides empirical benchmarks relevant to RbG implementation and precision psychiatry in diverse healthcare systems.

Journal Article↗

PubMed2026

Long-read based detection of large copy number variants with potential functional significance using the ContextSV structural variant caller.

Long-read sequencing enables improved detection of structural variants (SVs) in the human genome due to its substantially increased read lengths. However, currently widely used long-read SV callers primarily rely on alignment-based evidence, limiting their ability to detect large and complex SVs and potentially missing disease-relevant events. To address these limitations, we developed ContextSV, a framework that integrates alignment evidence with copy number predictions derived from sequencing coverage and single-nucleotide variant allele frequencies to improve SV detection, particularly for large copy number variants (CNVs). We additionally developed ContextScore, a machine learning-based classification model to assign SV confidence scores based on genomic context features and integrated it within ContextSV. Through benchmarking analyses on both simulated and real datasets, we demonstrate that ContextSV improves detection of large CNVs and inversions that may be missed by existing long-read SV callers. We further illustrate its utility by identifying and experimentally validating multiple large SVs in the KOLF2.1J reference stem cell line that were not detected by other methods. Collectively, our results demonstrate that ContextSV serves as a valuable complement to existing long-read SV detection approaches by improving sensitivity for large and clinically relevant SVs.

Humans↗

PubMed2026

Genetic Screening of Colombian Patients With Early-Onset Parkinson Disease.

BACKGROUND AND OBJECTIVES: Early-onset Parkinson disease (EOPD), defined as symptom onset before 50 years of age, accounts for approximately 10% of patients and is suggested to have a greater genetic component than typical late-onset forms of the disease. Recessive variants in PRKN, PINK1, and DJ-1, are the most common genetic cause of EOPD, however, most studies are in patients of white ancestry. This study aims to analyze genetic variants in PRKN, PINK1, and DJ-1 in Colombian patients to help address the gap in EOPD genetic research of South American populations. METHODS: We analyzed 43 unrelated patients with EOPD using Sanger sequencing for the PRKN, PINK1, and DJ-1 genes and employed multiplex ligation-dependent probe amplification to detect copy number variants. Additionally, long-read whole-genome sequencing was conducted on 3 unresolved patients with age at onset before 30 years of age (long-read sequencing [LRS] patient A-C). RESULTS: We identified known pathogenic single-nucleotide variants and copy number variants in the PRKN gene accounting for 2 patients' disease (4.6% of patients). We observed 2 pathogenic variants in PRKN (c.155delA; p.N52Mfs*29 and c.1083+1G>A) in patient 1, who reported an age at onset of 16 years. We further detected a homozygous duplication of PRKN exons 5-6 in an additional patient, age at onset of 18 years. DISCUSSION: Our study helps characterize genetic contributors to EOPD in Colombian patients, demonstrating genetic forms (PRKN, PINK1, and DJ-1) are rare. Our results highlight a need to include diverse populations in research to improve genetic understanding of disease.

Journal Article↗

PubMed2026

Clinical and Genetic Spectrum of Large AIP Deletions.

Familial isolated pituitary adenoma (FIPA) accounts for approximately 2%-5% of all pituitary adenomas, with inactivating variants of the aryl hydrocarbon receptor-interacting protein (AIP) gene representing the most frequent known genetic cause. Clinically, patients with AIP variants often have young-onset macroadenomas with growth hormone hypersecretion, although disease severity and penetrance are variable. Most reported AIP variants are point mutations, whereas large deletions are rare and potentially underdiagnosed. Accurate detection of AIP copy-number variants requires methods such as multiplex ligation-dependent probe amplification or validated copy-number analysis of next-generation sequencing data, as Sanger sequencing alone may fail to identify these alterations. Due to the rarity of the disease, it is unknown whether large deletions in the ubiquitously expressed AIP gene are associated with potentially more severe phenotype. Available data suggest that large deletions may occur in 8%-10% of AIP mutation-positive pedigrees, highlighting the importance of incorporating copy-number variant detection into AIP testing workflows. We analysed data from all published patients with large AIP deletions (n = 25) and report here two novel large AIP deletions (Exons 3-4 and Exons 2-6 deletions) and three additional three families, including an Albanian kindred associated with metastatic Hürthle cell thyroid carcinoma. No major differences compared with other AIP variants were found in age at diagnosis, tumour size, hormonal profile, sex distribution or presence of other tumours. A role for AIP variants in thyroid carcinogenesis is unlikely.

Humans↗

PubMed2025

Optical mapping in Black genomes: Distinct LCR22 structures and 22q11.2 deletion syndrome mechanisms.

PURPOSE: The genomic architecture of 22q11.2 deletion syndrome (22q11.2DS) has primarily been studied in White populations, despite evidence suggesting a lower prevalence in Black individuals. This study aims to improve our understanding of the population-specific organization of 22q11.2 genomic structures. METHODS: Optical mapping data from 106 genomes, representing various Black and White individuals, were analyzed to assess the structure and variation of the 22q11.2 low copy repeats (LCR22s). RESULTS: Extensive variability in copy-number and orientation of LCR22 elements was observed between Black and White genomes. Several novel copy-number variants and haplotype configurations were identified, some being private or more prevalent within specific groups. Notably, copy-number variants diversity was particularly striking among Black genomes. Comparisons of Black and White families with de novo 22q11.2DS probands revealed unique nonallelic homologous recombination scenarios, with Black families exhibiting recombination patterns that are not previously observed. CONCLUSION: Perhaps the unique and highly variable LCR22 haplotype configurations in Black individuals contribute to the lower observed prevalence of 22q11.2DS by inhibiting the likelihood of nonallelic homologous recombination, the mechanism that leads to the syndrome.

Humans↗

PubMed2026

PULPO: pipeline of understanding large-scale patterns of oncogenomic signatures.

SUMMARY: PULPO v1.0 is a novel; fully automated pipeline designed for the preprocess and extraction of mutational signatures from raw Optical Genome Mapping (OGM) data. Built using Snakemake and executed within an isolated, Conda-managed environment, PULPO transforms complex cytogenetic alterations, captured at ultra-high resolution, into Catalogue of somatic mutations in cancer mutational signatures (COSMIC). This innovative approach not only enables researchers to work directly from raw OGM inputs but also streamlines the traditionally complex process of signature extraction, making advanced oncogenomic analyses accessible to users with varying levels of bioinformatics expertise. By facilitating the integration of comprehensive structural variants (SVs) and copy number variants (CNVs) data with established signature catalogues, PULPO paves the way for improved diagnostic accuracy and personalized therapeutic strategies. AVAILABILITY AND IMPLEMENTATION: The pipeline is open source and freely available under the MIT License at https://github.com/OncologyHNJ/PULPO-v.1.0 and DOI in Zenodo: https://zenodo.org/records/17749097.

Software↗

PubMed2024

Common genetic variants associated with urinary phthalate levels in children: A genome-wide study.

INTRODUCTION: Phthalates, or dieters of phthalic acid, are a ubiquitous type of plasticizer used in a variety of common consumer and industrial products. They act as endocrine disruptors and are associated with increased risk for several diseases. Once in the body, phthalates are metabolized through partially known mechanisms, involving phase I and phase II enzymes. OBJECTIVE: In this study we aimed to identify common single nucleotide polymorphisms (SNPs) and copy number variants (CNVs) associated with the metabolism of phthalate compounds in children through genome-wide association studies (GWAS). METHODS: The study used data from 1,044 children with European ancestry from the Human Early Life Exposome (HELIX) cohort. Ten phthalate metabolites were assessed in a two-void pooled urine collected at the mean age of 8 years. Six ratios between secondary and primary phthalate metabolites were calculated. Genome-wide genotyping was done with the Infinium Global Screening Array (GSA) and imputation with the Haplotype Reference Consortium (HRC) panel. PennCNV was used to estimate copy number variants (CNVs) and CNVRanger to identify consensus regions. GWAS of SNPs and CNVs were conducted using PLINK and SNPassoc, respectively. Subsequently, functional annotation of suggestive SNPs (p-value < 1E-05) was done with the FUMA web-tool. RESULTS: We identified four genome-wide significant (p-value < 5E-08) loci at chromosome (chr) 3 (FECHP1 for oxo-MiNP_oh-MiNP ratio), chr6 (SLC17A1 for MECPP_MEHHP ratio), chr9 (RAPGEF1 for MBzP), and chr10 (CYP2C9 for MECPP_MEHHP ratio). Moreover, 115 additional loci were found at suggestive significance (p-value < 1E-05). Two CNVs located at chr11 (MRGPRX1 for oh-MiNP and SLC35F2 for MEP) were also identified. Functional annotation pointed to genes involved in phase I and phase II detoxification, molecular transfer across membranes, and renal excretion. CONCLUSION: Through genome-wide screenings we identified known and novel loci implicated in phthalate metabolism in children. Genes annotated to these loci participate in detoxification, transmembrane transfer, and renal excretion.

Humans↗

PubMed2026

Comparative analysis of distinct genomic landscapes in young-onset gBRCA1/2 breast cancer.

Carriers of germline BRCA1/2 pathogenic variants (gBRCA1/2 PVs) have elevated young-onset breast cancer risk. To define the pretreatment genomic landscapes of young-onset gBRCA-associated breast cancer, we evaluated 136 treatment-naive tumors diagnosed before age 50 in the prospective POSH study and 66 noncarriers from The Cancer Genome Atlas. Using whole-exome sequencing, we analyzed somatic variation, allele-specific loss of heterozygosity (asLOH), homologous recombination deficiency (HRD), and single-base substitution (SBS) signatures. gBRCA1 and gBRCA2 breast cancers had high rates of asLOH but differed significantly in average HRD scores and median SBS composition of signatures SBS1 (aging-associated), SBS18 (ROS-associated), and SBS3 (HRD-associated). Compared with gBRCA2 tumors, gBRCA1 tumors with asLOH were significantly enriched for alterations in hallmark ROS, DNA repair, and epithelial-mesenchymal transition pathways. In ER-positive, HER2-negative tumors from gBRCA1/2 carriers compared with noncarriers, we found significant enrichment of RB1, TP53, FAT1, and MYC single-nucleotide variants, indels, and copy number variants associated with CDK4/6 inhibitor (CDK4/6i) resistance. Together, these findings demonstrate significant differences between gBRCA1- and gBRCA2-associated breast cancers, and preexisting CDK4/6i resistance mechanisms, supporting prospective trials comparing individualized therapy for gBRCA1 versus gBRCA2 carriers and comparing poly(ADP-ribose) polymerase inhibitors versus CDK4/6i for ER-positive gBRCA1/2-associated breast cancer.

Humans↗

PubMed2026

Evaluation of the efficacy of optical genome mapping in prenatal diagnosis: a retrospective cohort study.

BACKGROUND: Optical genome mapping (OGM) is an emerging cytogenetic method for concurrently detecting structural variants (SVs) and copy number variants (CNVs). However, its clinical application in prenatal diagnosis remains underexplored. METHODS: This study retrospectively evaluated the clinical validity of OGM in prenatal diagnosis by comparing with two routine genetic testing methods: karyotyping and chromosomal microarray analysis (CMA). Both positive and negative cases detected by routine genetic methods were enrolled to evaluate the technical concordance of OGM and its capability to improve diagnostic rate in negative cases. The exclusion criteria were balanced centromeric translocations, mosaic cases with cellular fractions < 20%, and loss of heterozygosity (LOH) < 25 Mb. All samples subjected to OGM testing were anonymized and analyzed blindly. The results from OGM were compared with those from routine genetic testing, and statistical analyses were performed to assess technical concordance and diagnostic rate. RESULTS: Of 217 samples (166 positive samples and 51 negative samples for routine genetic testing), all were successfully tested with OGM, including 2 umbilical cord blood samples, 4 chorionic villi samples, and 211 cultured amniotic fluid samples. Of the 207 reportable chromosomal aberrations from 166 positive samples, the blinded concordance between OGM and CMA, karyotyping, and combination of karyotyping plus CMA was 97.81%, 96.36%, and 97.10%, respectively. OGM missed six aberrations initially, including one LOH, two marker chromosomes, and three microdeletions. However, after reanalysis, its concordance improved to 100% with CMA and 99.03% with karyotyping plus CMA. OGM also diagnosed one additional case of a 3-kb deletion in 51 negative samples, improving the diagnostic rate by 1.96%. Moreover, OGM reclassified the pathogenicity of two microdeletions from pathogenic to uncertain significance in 2 positive cases. Furthermore, OGM clarified the diagnosis suspected by routine genetic testing and improved diagnostic accuracy in some cases. CONCLUSION: As far as we know, this is the largest retrospective study on OGM in prenatal diagnosis, and it includes a broad range of sample types. The results showed that OGM exhibits high concordance among the tested methods and increases the diagnostic rate. Thus, OGM has the potential to become a first-line technique for prenatal diagnosis in the future.

Humans↗