Association Of Copy Number Variations Research Articles

CNVDeep: deep association of copy number variants with neurocognitive disorders

BackgroundCopy number variants (CNVs) have become increasingly instrumental in understanding the etiology of all diseases and phenotypes, including Neurocognitive Disorders (NDs). Among the well-established regions associated with ND are small parts of chromosome 16 deletions (16p11.2) and chromosome 15 duplications (15q3). Various methods have been developed to identify associations between CNVs and diseases of interest. The majority of methods are based on statistical inference techniques. However, due to the multi-dimensional nature of the features of the CNVs, these methods are still immature. The other aspect is that regions discovered by different methods are large, while the causative regions may be much smaller.ResultsIn this study, we propose a regularized deep learning model to select causal regions for the target disease. With the help of the proximal [20] gradient descent algorithm, the model utilizes the group LASSO concept and embraces a deep learning model in a sparsity framework. We perform the CNV analysis for 74,811 individuals with three types of brain disorders, autism spectrum disorder (ASD), schizophrenia (SCZ), and developmental delay (DD), and also perform cumulative analysis to discover the regions that are common among the NDs. The brain expression of genes associated with diseases has increased by an average of 20 percent, and genes with homologs in mice that cause nervous system phenotypes have increased by 18 percent (on average). The DECIPHER data source also seeks other phenotypes connected to the detected regions alongside gene ontology analysis. The target diseases are correlated with some unexplored regions, such as deletions on 1q21.1 and 1q21.2 (for ASD), deletions on 20q12 (for SCZ), and duplications on 8p23.3 (for DD). Furthermore, our method is compared with other machine learning algorithms.ConclusionsOur model effectively identifies regions associated with phenotypic traits using regularized deep learning. Rather than attempting to analyze the whole genome, CNVDeep allows us to focus only on the causative regions of disease.

Fetal Gene Regulatory Gene Deletions are Associated with Poor Cognition and Altered Cortical Morphology in Schizophrenia and Community-Based Samples.

Schizophrenia spectrum disorders (SSDs) are characterized by substantial clinical and genetic heterogeneity. Multiple recurrent copy number variants (CNVs) increase risk for SSDs; however, how known risk CNVs and broader genome-wide CNVs influence clinical variability is unclear. The current study examined associations between borderline intellectual functioning or childhood-onset psychosis, known risk CNVs, and burden of deletions affecting genes in 18 previously validated neurodevelopmental gene-sets in 618 SSD individuals. CNV associations were assessed for replication in 235 SSD relatives and 583 controls, and 9,930 youth from the Adolescent Brain Cognitive Development (ABCD) Study. Known SSD- and neurodevelopmental disorder (NDD)-risk CNVs were associated with borderline intellectual functioning in SSD cases (odds ratios (OR) = 7.09 and 4.57, respectively); NDD-risk deletions were nominally associated with childhood-onset psychosis (OR = 4.34). Furthermore, deletion of genes involved in regulating gene expression during fetal brain development was associated with borderline intellectual functioning across SSD cases and non-cases (OR = 2.58), with partial replication in the ABCD cohort. Exploratory analyses of cortical morphology showed associations between fetal gene regulatory gene deletions and altered gray matter volume and cortical thickness across cohorts. Results highlight contributions of known risk CNVs to phenotypic variability in SSD and the utility of a neurodevelopmental framework for identifying mechanisms that influence phenotypic variability in SSDs, as well as the broader population, with implications for personalized medicine approaches to care.

Association of copy number variation in X chromosome-linked PNPLA4 with heterotaxy and congenital heart disease.

Heterotaxy (HTX) is a thoracoabdominal organ anomaly syndrome and commonly accompanied by congenital heart disease (CHD). The aim of this study was to analyze rare copy number variations (CNVs) in a HTX/CHD cohort and to examine the potential mechanisms contributing to HTX/CHD. Chromosome microarray analysis was used to identify rare CNVs in a cohort of 120 unrelated HTX/CHD patients, and available samples from parents were used to confirm the inheritance pattern. Potential candidate genes in CNVs region were prioritized via the DECIPHER database, and PNPLA4 was identified as the leading candidate gene. To validate, we generated PNPLA4 -overexpressing human induced pluripotent stem cell lines as well as pnpla4 -overexpressing zebrafish model, followed by a series of transcriptomic, biochemical and cellular analyses. Seventeen rare CNVs were identified in 15 of the 120 HTX/CHD patients (12.5%). Xp22.31 duplication was one of the inherited CNVs identified in this HTX/CHD cohort, and PNPLA4 in the Xp22.31 was a candidate gene associated with HTX/CHD. PNPLA4 is expressed in the lateral plate mesoderm, which is known to be critical for left/right embryonic patterning as well as cardiomyocyte differentiation, and in the neural crest cell lineage. Through a series of in vivo and in vitro analyses at the molecular and cellular levels, we revealed that the biological function of PNPLA4 is importantly involved in the primary cilia formation and function via its regulation of energy metabolism and mitochondria-mediated ATP production. Our findings demonstrated a significant association between CNVs and HTX/CHD. Our data strongly suggested that an increased genetic dose of PNPLA4 due to Xp22.31 duplication is a disease-causing risk factor for HTX/CHD.

Emergence of the ZNF675 Gene During Primate Evolution-Influenced Human Neurodevelopment Through Changing HES1 Autoregulation.

In this study, we investigated recurrent copy number variations (CNVs) in the 19p12 locus, which are associated with neurodevelopmental disorders. The two genes in this locus, ZNF675 and ZNF681, arose via gene duplication in primates, and their presence in several pathological CNVs in the human population suggests that either or both of these genes are required for normal human brain development. ZNF675 and ZNF681 are members of the Krüppel-associated box zinc finger (KZNF) protein family, a class of transcriptional repressors important for epigenetic silencing of specific genomic regions. About 170 primate-specific KZNFs are present in the human genome. Although KZNFs are primarily associated with repressing retrotransposon-derived DNA, evidence is emerging that they can be co-opted for other gene regulatory processes. We show that genetic deletion of ZNF675 causes developmental defects in cortical organoids, and our data suggest that part of the observed neurodevelopmental phenotype is mediated by a gene regulatory role of ZNF675 on the promoter of the neurodevelopmental gene Hes family BHLH transcription factor 1 (HES1). We also find evidence for the recently evolved regulation of genes involved in neurological disorders, microcephalin 1 and sestrin 3. We show that ZNF675 interferes with HES1 auto-inhibition, a process essential for the maintenance of neural progenitors. As a striking example of how some KZNFs have integrated into preexisting gene expression networks, these findings suggest the emergence of ZNF675 has caused a change in the balance of HES1 autoregulation. The association of ZNF675 CNV with human developmental disorders and ZNF675-mediated regulation of neurodevelopmental genes suggests that it evolved into an important factor for human brain development.

Genome-wide association study of copy number variations with shank traits in a F2 crossbred chicken population.

Copy number variations (CNVs) are large-scale changes in the DNA sequence that can affect the genetic structure and phenotype of an organism. The purpose of this study was to investigate the existing CNVs and their associations with the shank diameter (ShD) and shank length (ShL) traits using data from an F2 crossbred chicken population. To carry out the study, 312 chickens were genotyped using the Illumina 60k SNP Beadchip. The shank traits of the birds were measured from day 1 to 12 weeks of age. penncnv and cnvruler tools were used to find copy numbers and regions with copy number changes (CNVR), respectively. The CNVRanger package was used to perform a genome-wide association study between shank traits and CNVs. Gene ontology research in CNVRs was carried out using the david database. In this investigation, 966 CNVs and 606 regions with copy number changes were discovered. The copy number states and variations were randomly distributed along the length of the autosomal chromosomes. Weeks 1-4, 9 and 12 of growth revealed a significant association of copy number variations with shank traits, false discovery rate (FDR-corrected p-value < 0.01), and the majority of CNVs that were statistically significant were found on chromosomes 1-3. These CNV segments are nearby genes such as KCNJ12, FGF6 and MYF5, which are fundamental to growth and development. In addition, gene set analyses revealed terms related to muscle physiology, regulation of cellular processes and potassium channels.

OSCAA: A two-dimensional Gaussian mixture model for copy number variation association analysis.

Copy number variants (CNVs) are prevalent in the human genomeand are found to havea profound effect on genomic organization and human diseases. Discovering disease-associated CNVs is critical for understanding the pathogenesis of diseases and aiding their diagnosis and treatment. However, traditional methods for assessing the association between CNVs and disease risks adopt a two-stage strategy conducting quantitative CNV measurements first and then testing for association, which may lead to biased association estimation and low statistical power, serving as a major barrier in routine genome-wide assessment of such variation. In this article, we developed One-Stage CNV-disease Association Analysis(OSCAA), a flexible algorithm to discover disease-associated CNVs for both quantitative and qualitative traits. OSCAA employs a two-dimensional Gaussian mixture model that is built upon the PCs from copy number intensities, accounting for technical biases in CNV detection while simultaneously testing for their effect on outcome traits. In OSCAA, CNVs are identified and their associations with disease risk are evaluated simultaneously in a single step, taking into account the uncertainty of CNV identification in the statistical model. Our simulations demonstrated that OSCAA outperformed the existing one-stage method and traditional two-stage methods by yielding a more accurate estimate of the CNV-disease association, especially for short CNVs or CNVs with weak signals. In conclusion, OSCAA is a powerful and flexible approach for CNV association testing with high sensitivity and specificity, which can be easily applied to different traits and clinical risk predictions.

GATK-gCNV enables the discovery of rare copy number variants from exome sequencing data.

Copy number variants (CNVs) are major contributors to genetic diversity and disease. While standardized methods, such as the genome analysis toolkit (GATK), exist for detecting short variants, technical challenges have confounded uniform large-scale CNV analyses from whole-exome sequencing (WES) data. Given the profound impact of rare and de novo coding CNVs on genome organization and human disease, we developed GATK-gCNV, a flexible algorithm to discover rare CNVs from sequencing read-depth information, complete with open-source distribution via GATK. We benchmarked GATK-gCNV in 7,962 exomes from individuals in quartet families with matched genome sequencing and microarray data, finding up to 95% recall of rare coding CNVs at a resolution of more than two exons. We used GATK-gCNV to generate a reference catalog of rare coding CNVs in WES data from 197,306 individuals in the UK Biobank, and observed strong correlations between per-gene CNV rates and measures of mutational constraint, as well as rare CNV associations with multiple traits. In summary, GATK-gCNV is a tunable approach for sensitive and specific CNV discovery in WES data, with broad applications.

Identification of Candidate Genes for Min Pig Villi Hair Traits by Genome-Wide Association of Copy Number Variation.

The Min pig is a famous native pig breed in northeast China, which has the special genetic character of villi hair growth in cold seasons. At present, little research has focused on the genetic mechanism of villi hair growth in Min pigs. Copy number variations (CNVs) are a type of variant that may influence many traits. In this study, we first investigated the phenotype of Large White × Min pigs' F2 pig villi hair in detail and then performed a CNV-based genome-wide association study (GWAS) between CNVs and pig villi hair appearance. Finally, a total number of 15 significant CNVRs were found to be associated with Min pig villi hair. The most significant CNVR was located on chromosome 1. Nearest gene annotation analysis indicated that the pig villi hair traits may be associated with the biological process of the G-protein-coupled receptor signaling pathway. QTL overlapping analysis found that among the CNVRs, 14 CNVRs could be co-located with known QTLs. Some genes such as MCHR2, LTBP2, and GFRA2 may be candidate genes for pig villi traits and are worth further study. Our study may provide a basic reference for the selection and breeding of cold-resistant pigs and outdoor breeding.

ParseCNV2: a versatile and integrated tool for copy number variation association studies.

ParseCNV2: a versatile and integrated tool for copy number variation association studies.

Genome-wide association analysis reveals 6 copy number variations associated with the number of cervical vertebrae in Pekin ducks.

As a critical developmental stage in vertebrates, the vertebral column formation process is under strict control; however, we observed variations in the number of cervical vertebrae in duck populations in our previous study. Here, we further explored the variations in the number of vertebrae in two duck populations: 421 Pekin duck × mallard F2 ducks and 850 Pekin ducks. Using resequencing data of 125 Pekin ducks with different numbers of cervical vertebrae and 352 Pekin duck × mallard F2 ducks with different numbers of thoracic vertebrae, we detected whole-genome copy number variations (CNVs) and implemented a genome-wide association study (GWAS) to identify the genetic variants related to the traits. The findings verified the existence of variations in the number of cervical vertebrae in duck populations. The number of cervical vertebrae in most ducks was 15, while that in a small number of the ducks was 14 or 16. The number of cervical vertebrae had a positive influence on the neck production, and one cervical vertebra addition could increase 11g or 2cm of duck neck. Genome-wide CNV association analysis identified six CNVs associated with the number of cervical vertebrae, and the associated CNV regions covered 15 genes which included WNT10A and WNT6. These findings improve our understanding of the variations in the number of vertebrae in ducks and lay a foundation for future duck breeding.

Abstract 15501: Rare Genomic Copy Number Variants Implicate New Candidate Genes for Bicuspid Aortic Valve

Introduction: Bicuspid Aortic Valve (BAV), the most common adult congenital heart defect, is a major cause of aortic insufficiency or stenosis requiring valve replacement and thoracic aortic aneurysms predisposing to acute aortic dissections. The spectrum of BAV ranges from early onset valve and aortic complications to sporadic late onset disease. We determined the frequency and gene content of rare genomic copy number variants (CNVs) in isolated BAV cases. Methods: We performed genome-wide SNP microarray analysis of familial BAV cases with early onset complications in the UTHealth BAV Research Registry (EBAV, n=394) and elderly probands from the International BAV Consortium (BAVCON, n=4216). CNVs were detected in Illumina genotypes using the PennCNV, QuantiSNP and cnvPartition algorithms. BAV cases were compared to 16,576 controls without known cardiovascular disease from the Database of Genotypes and Phenotypes. Only CNV calls with &gt;6 consecutive variants, &gt;20 kb in length, identified by at least two algorithms and intersected with known genes were included. For comparison, we assessed a cohort with left ventricular outflow tract obstructive lesions including BAV (LVOTO, n=1561) using identical methods. CNV burden and associations were tested using PLINK. Results: We identified 84 large recurrent CNVs in BAV cases that are absent or rare (&lt;0.1%) in controls. 34 rare CNVs overlap between BAV and LVOTO cases and involve candidate genes that interact with each other during heart development. The largest and most prevalent of the recurrent CNVs are 8p23 duplications involving GATA4 (OR 340, CI: 42-2700). CNVs of genes that cause BAV when mutated were significantly enriched in cases (n=135, P =1x10 -27 ). The overall burden of rare genic CNVs, specifically large deletions, was also increased in BAV cases (empiric P &lt; 1x10 -5 ) and was higher in younger EBAV cases than in older BAVCON cases. Conclusion: We identified likely pathogenic CNVs in more than 10% of BAV cases, implicating alterations of candidate genes at these loci in the pathogenesis of BAV.

ParseCNV2: efficient sequencing tool for copy number variation genome-wide association studies.

Improved copy number variation (CNV) detection remains an area of heavy emphasis for algorithm development; however, both CNV curation and disease association approaches remain in its infancy. The current practice of focusing on candidate CNVs, where researchers study specific CNVs they believe to be pathological while discarding others, refrains from considering the full spectrum of CNVs in a hypothesis-free GWAS. To address this, we present a next-generation approach to CNV association by natively supporting the popular VCF specification for sequencing-derived variants as well as SNP array calls using a PennCNV format. The code is fast and efficient, allowing for the analysis of large (>100,000 sample) cohorts without dividing up the data on a compute cluster. The scripts are condensed into a single tool to promote simplicity and best practices. CNV curation pre and post-association is rigorously supported and emphasized to yield reliable results of highest quality. We benchmarked two large datasets, including the UK Biobank (n > 450,000) and CAG Biobank (n > 350,000) both of which are genotyped at >0.5 M probes, for our input files. ParseCNV has been actively supported and developed since 2008. ParseCNV2 presents a critical addition to formalizing CNV association for inclusion with SNP associations in GWAS Catalog. Clinical CNV prioritization, interactive quality control (QC), and adjustment for covariates are revolutionary new features of ParseCNV2 vs. ParseCNV. The software is freely available at: https://github.com/CAG-CNV/ParseCNV2 .

Novel lipometabolism biomarker for chemotherapy and immunotherapy response in breast cancer

Emerging proof shows that abnormal lipometabolism affects invasion, metastasis, stemness and tumor microenvironment in carcinoma cells. However, molecular markers related to lipometabolism have not been further established in breast cancer. In addition, numerous studies have been conducted to screen for prognostic features of breast cancer only with RNA sequencing profiles. Currently, there is no comprehensive analysis of multiomics data to extract better biomarkers. Therefore, we have downloaded the transcriptome, single nucleotide mutation and copy number variation dataset for breast cancer from the TCGA database, and constructed a riskScore of twelve genes by LASSO regression analysis. Patients with breast cancer were categorized into high and low risk groups based on the median riskScore. The high-risk group had a worse prognosis than the low-risk group. Next, we have observed the mutated frequencies and the copy number variation frequencies of twelve lipid metabolism related genes LMRGs and analyzed the association of copy number variation and riskScore with OS. Meanwhile, the ESTIMATE and CIBERSORT algorithms assessed tumor immune fraction and degree of immune cell infiltration. In immunotherapy, it is found that high-risk patients have better efficacy in TCIA analysis and the TIDE algorithm. Furthermore, the effectiveness of six common chemotherapy drugs was estimated. At last, high-risk patients were estimated to be sensitive to six chemotherapeutic agents and six small molecule drug candidates. Together, LMRGs could be utilized as a de novo tumor biomarker to anticipate better the prognosis of breast cancer patients and the therapeutic efficacy of immunotherapy and chemotherapy.

Copy number variation association studies for sheep tail-relevant traits in Hulunbuir sheep.

Tail type is an important trait that influences meat quality and consumer purchasing attitudes. As a novel genetic marker, the study of genomic copy number variations (CNVs) provides a new research method to study the genetic mechanisms underlying trait formation. In the present paper, we conducted CNV-based association studies for sheep tail type and growth traits in Hulunbuir sheep. A total of 167 CNVs and 288 individuals were analyzed at the marker and individual level, respectively. Association studies of 10 traits were carried out using two mixed linear models. We found that three, one and one CNV loci were significantly associated with tail type, tail length and tail fat weight, respectively, which together contained a total of 52 candidate genes. Out of these genes, five have been documented to be associated with fat metabolism in sheep. Our findings provide a reference for further studies on fat deposition in sheep as well as a theoretical basis for breeding Hulunbuir sheep with the required tail type.

CNest: A novel copy number association discovery method uncovers 862 new associations from 200,629 whole-exome sequence datasets in the UK Biobank

Copy number variation (CNV) is known to influence human traits, having a rich history of research into common and rare genetic disease, and although CNV is accepted as an important class of genomic variation, progress on copy-number-based genome-wide association studies (GWASs) from next-generation sequencing (NGS) data has been limited. Here we present a novel method for large-scale copy number analysis from NGS data generating robust copy number estimates and allowing copy number GWASs (CN-GWASs) to be performed genome-wide in discovery mode. We provide a detailed analysis in the UK Biobank resource and a specifically designed software package. We use these methods to perform CN-GWAS analysis across 78 human traits, discovering over 800 genetic associations that are likely to contribute strongly to trait distributions. Finally, we compare CNV and SNP association signals across the same traits and samples, defining specific CNV association classes.

Higher affinity binding alleles and copy number variation of inhibitory KIR2DL1 gene influence the immune surveillance in head and neck squamous cell carcinoma in the population of Assam, North-East India

Killer Ig like receptor (KIR) and the human leukocyte antigen (HLA) complex shows extensive polymorphism which has significance in context of disease association and evolution of immune responses. We have examined here the allelic diversity and copy number variation (CNV) of KIR2DL1 binding affinity with its cognate ligand HLA-C and its association with Head and Neck Squamous Cell Carcinoma (HNSCC) in a hospital based case-control study with 204 HNSCC patients and 225 non cancer participants in populations of Assam, North-East India. KIR2DL1*003 was seen at highest frequency of 79.1%. HLA-C*04 and HLA-C*07 were the most frequent HLA-C allotypes (28.5% and 25% respectively). The combined genotype of KIR2DL1*003-HLA-C2 was positively associated with HNSCC (p = 0.0152; OR = 1.9, 95%CI 1.118–2.534) and was more frequent in younger age group patients suggesting positive association with early onset of disease (p = 0.0008 OR = 2.0, 95% CI 1.157–2.363). HNSCC patients with KIR2DL1*003-HLA-C2 genotype had higher CNV of KIR2DL1 gene hinting at higher NK activation threshold which was supported by affinity binding of KIR2DL1 alleles with HLA-CW4 and by higher SHP2 phosphatase activity. Positive association of CNV with tumor proliferation, angiogenesis, cancer relapse and advance tumor stage suggested compromise of NK activation for anti-tumor response, consistent with downregulated cytokine response. In conclusion, our data suggested that higher affinity binding alleles together with higher CNV of inhibitory KIR2DL1 compromised immune surveillance in HNSCC and opens up the possibility of the use of KIR-HLA allotyping as prognostic markers.

Exome-wide analysis of copy number variation shows association of the human leukocyte antigen region with asthma in UK Biobank

BackgroundThe role of copy number variants (CNVs) in susceptibility to asthma is not well understood. This is, in part, due to the difficulty of accurately measuring CNVs in large enough sample sizes to detect associations. The recent availability of whole-exome sequencing (WES) in large biobank studies provides an unprecedented opportunity to study the role of CNVs in asthma.MethodsWe called common CNVs in 49,953 individuals in the first release of UK Biobank WES using ClinCNV software. CNVs were tested for association with asthma in a stage 1 analysis comprising 7098 asthma cases and 36,578 controls from the first release of sequencing data. Nominally-associated CNVs were then meta-analysed in stage 2 with an additional 17,280 asthma cases and 115,562 controls from the second release of UK Biobank exome sequencing, followed by validation and fine-mapping.ResultsFive of 189 CNVs were associated with asthma in stage 2, including a deletion overlapping the HLA-DQA1 and HLA-DQB1 genes, a duplication of CHROMR/PRKRA, deletions within MUC22 and TAP2, and a duplication in FBRSL1. The HLA-DQA1, HLA-DQB1, MUC22 and TAP2 genes all reside within the human leukocyte antigen (HLA) region on chromosome 6. In silico analyses demonstrated that the deletion overlapping HLA-DQA1 and HLA-DQB1 is likely to be an artefact arising from under-mapping of reads from non-reference HLA haplotypes, and that the CHROMR/PRKRA and FBRSL1 duplications represent presence/absence of pseudogenes within the HLA region. Bayesian fine-mapping of the HLA region suggested that there are two independent asthma association signals. The variants with the largest posterior inclusion probability in the two credible sets were an amino acid change in HLA-DQB1 (glutamine to histidine at residue 253) and a multi-allelic amino acid change in HLA-DRB1 (presence/absence of serine, glycine or leucine at residue 11).ConclusionsAt least two independent loci characterised by amino acid changes in the HLA-DQA1, HLA-DQB1 and HLA-DRB1 genes are likely to account for association of SNPs and CNVs in this region with asthma. The high divergence of haplotypes in the HLA can give rise to spurious CNVs, providing an important, cautionary tale for future large-scale analyses of sequencing data.

Copy number variations identified in thyroid FNA specimens are associated with Hürthle cell cytomorphology.

The fine-needle aspiration (FNA) diagnosis of thyroid Hürthle cell neoplasms (HCNs) remains challenging. This study explored a possible association of copy number variations (CNVs) with Hürthle cell lesions of the thyroid. Thyroid FNA cases that were diagnosed as follicular lesion of undetermined significance (FLUS) or follicular neoplasm (FN)/HCN for which the ThyroSeq version 3 genomic classifier test was performed were retrieved. A total of 324 thyroid FNA cases (228 FLUS cases, 46 HCN cases, and 50 FN cases) were included in the study. FLUS cases were further classified as Hürthle cell type (follicular lesion of undetermined significance-Hürthle cell type [FLUS-HCT]; 20 cases) or non-Hürthle cell type (follicular lesion of undetermined significance-non-Hürthle cell type [FLUS-NHCT]; 208 cases). HCN and FLUS-HCT cases showed a higher prevalence of CNVs (23 of 66 [35%]) in comparison with those classified as FN or FLUS-NHCT (14 of 258 [5%]; P < .001). A total of 105 patients had histopathologic follow-up. Cases with CNVs were more likely to be neoplastic (18 of 26 [69%]) and associated with Hürthle cell changes (14 of 26 [54%]) in comparison with cases without any molecular alterations (neoplastic, 8 of 24 [33%]; Hürthle cell changes, 2 of 24 [8%]; P < .05). In HCN/FLUS-HCT cases with CNVs (n = 14), Hürthle cell changes (13 of 14 [93%]) and neoplasms (9 of 14 [64%]) were more likely to be seen on surgical follow-up in comparison with the 17 cases without CNVs (Hürthle cell changes, 6 of 17 [35%]; neoplastic, 3 of 17 [18%]; P < .05). CNVs identified in thyroid FNA cases are associated with Hürthle cell morphology and are suggestive of a neoplasm with Hürthle cell features in thyroid FNAs classified as FLUS-HCT/HCN. This finding may be helpful in triaging patients who would benefit from surgical management.

PeakCNV: A multi-feature ranking algorithm-based tool for genome-wide copy number variation-association study

Copy Number Variation (CNV) refers to a type of structural genomic alteration in which a segment of chromosome is duplicated or deleted. To date, many CNVs have been identified as causative genetic elements for several diseases and phenotypes. However, performing a CNV-based genome-wide association study is challenging due to inconsistency in length and occurrence of CNVs across different individuals under investigation. One of the most efficient strategies to address this issue is building CNV regions (genomic regions in which CNVs are overlapping - CNVRs). However, this approach is susceptible to a high false positive rate due to overlapping and co-occurring of confounding CNVRs with true positive CNVRs. Here, we develop PeakCNV that differentiates false-positive CNVRs from true positives by calculating a new metric, independence ranking score, (IR-score) via a feature ranking approach. We compared the performance of PeakCNV with other current existing tools by carrying out two case studies one using the CNV genotype data for individuals with prostate cancer (194 cases and 2,392 healthy individuals) and the second one for individuals with neurodevelopmental disorders (19,642 cases and 6,451 healthy individuals). Crucially, our benchmarking analyses on prostate cancer cohort indicated that PeakCNV identifies a fewer risk candidate CNVRs with shorter lengths compared to other tools. Importantly, these CNVRs cover a greater proportion of case over healthy individuals compared to other tools. The accuracy of PeakCNV in identifying relevant candidate CNVRs was reproducible in the case study on neurodevelopmental disorders. Using data from the FANTOM5 expression atlas and the Clinical Genomic Database, we show that the candidate CNVRs identified by PeakCNV for neurodevelopmental disorders overlap with a greater number of genes with the brain-enriched expression, and a greater number of genes that are associated with neurological conditions compared to candidate CNVRs identified by other tools. Taken together, PeakCNV outperformed current existing CNV association study tools by identifying more biologically meaningful CNVRs relevant to the phenotype of interest. PeakCNV is publicly available for the analysis of CNV-associated diseases and is accessible from https://rdrr.io/github/mahdieh1/PeakCNV.

Association Study between DUF1220 Copy Number and Severity of Social Impairment in Sex-balanced Simplex Cases of Autism.

Copy number variations (CNVs), which are genetic factors responsible for human evolution, have emerged as underlying pathogenic factors for a number of diseases such as autism spectrum disorders (ASD). DUF1220 coding sequences have been shown to be positively associated with the severity of symptoms in familial/multiplex cases of autism. However, this association has not been confirmed in simplex autism, and the potential impact of gender/sex has not been studied. Using saliva samples taken from Iranian children with non-syndromic simplex autism, different ethnicity/race and genetic backgrounds from previous studies, we assessed the association between DUF1220 CNVs and Autism Diagnostic Interview-Revised (ADI-R) domain scores in both males and females. In the male and female combined group with autism, in line with previous reports, our findings showed that there were no significant associations between DUF1220 CNVs with either total ADI-R score, social, communication, or repetitive diagnostic scores in simplex autism cases. Interestingly, however, in sex classified groups, despite the insignificant results, our findings in girls with autism showed a negative trend between DUF1220 CNVs and severity of symptoms for the social interaction and communication domains. By contrast, in male children with autism, the results showed a positive trend. It seems that association of DUF1220 CNV with the severity of symptoms in simplex children with autism may follow a sexually dimorphic pattern that needs to be re-examined in prospective studies.