Validity of the Family‐Based Association Test for Copy Number Variant Data in the Case of Non‐Linear Intensity‐Genotype Relationship

AbstractBackgroundCopy number variants (CNVs) are the gain or loss of DNA segments in the genome. Studies have shown that CNVs are linked to various disorders, including autism, intellectual disability, and schizophrenia.Consequently, the interest in studying a possible association of CNVs to specific disease traits is growing. However, due to the specific multi-dimensional characteristics of the CNVs, methods for testing the association between CNVs and the disease-related traits are still underdeveloped. We propose a novel multi-dimensional CNV kernel association test (MCKAT) in this paper. We aim to find significant associations between CNVs and disease-related traits using kernel-based methods.ResultsWe address the multi-dimensionality in CNV characteristics. We first design a single pair CNV kernel, which contains three sub-kernels to summarize the similarity between two CNVs considering all CNV characteristics. Then, aggregate single pair CNV kernel to the whole chromosome CNV kernel, which summarizes the similarity between CNVs in two or more chromosomes. Finally, the association between the CNVs and disease-related traits is evaluated by comparing the similarity in the trait with kernel-based similarity using a score test in a random effect model. We apply MCKAT on genome-wide CNV datasets to examine the association between CNVs and disease-related traits, which demonstrates the potential usefulness the proposed method has for the CNV association tests. We compare the performance of MCKAT with CKAT, a uni-dimensional kernel method. Based on the results, MCKAT indicates stronger evidence, smaller p-value, in detecting significant associations between CNVs and disease-related traits in both rare and common CNV datasets.ConclusionA multi-dimensional copy number variant kernel association test can detect significantly associated CNVs with any disease-related trait. MCKAT can help biologists detect significantly associated CNVs with any disease-related trait across a patient group instead of examining the CNVs case by case in each subject.

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PDS Is a New Susceptibility Gene to Autoimmune Thyroid Diseases: Association and Linkage Study

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/jc.2002-021460 ◽

2003 ◽

Vol 88 (5) ◽

pp. 2274-2280 ◽

Cited By ~ 26

Author(s):

Hassen Hadj Kacem ◽

Ahmed Rebai ◽

Noureddine Kaffel ◽

Saber Masmoudi ◽

Mohamed Abid ◽

...

Keyword(s):

Linkage Analysis ◽

Transmembrane Protein ◽

Susceptibility Gene ◽

Association Test ◽

Lod Score ◽

Autoimmune Thyroid ◽

The Family ◽

Family Based ◽

Idiopathic Myxedema ◽

Pds Gene

Autoimmune thyroid disease (AITD), including Graves’ disease (GD), Hashimoto thyroiditis (HT), and primary idiopathic myxedema, is caused by multiple genetic and environmental factors. Genes involved in immune response and/or thyroid physiology appear to influence susceptibility to disease. The PDS gene (7q31), responsible for Pendred syndrome (congenital sensorineural hearing loss and goiter), encodes a transmembrane protein known as pendrin. Pendrin is an apical porter of iodide in the thyroid. To evaluate the contribution of PDS gene in the genetic susceptibility of AITD, we examined four microsatellite markers in the gene region. Two hundred thirty-three unrelated patients (GD,141; HT, 54; primary idiopathic myxedema, 38), 15 multiplex AITD families (104 individuals/46 patients) and 154 normal controls were genotyped. Analysis of case-control data showed a significant association of D7S496 and D7S2459 with GD (P = 10−3) and HT (P = 1.07 10−24), respectively. The family-based association test showed significant association and linkage between AITDs and alleles 121 bp of D7S496 and 173 bp of D7S501. Results obtained by transmission disequilibrium test are in good agreement with those obtained by the family-based association test. Indeed, evidence for linkage and association of allele 121 bp of D7S496 with AITD was confirmed (P = 0.0114). Multipoint nonparametric linkage analysis using MERLIN showed intriguing evidence for linkage with marker D7S496 in families with only GD patients [Z = 2.12, LOD = 0.81, P = 0.026]. Single-point and multipoint parametric LOD score linkage analysis was also performed. Again, the highest multipoint parametric LOD score was found for marker D7S496 (LOD = 1.23; P = 0.0086) in families segregating for GD under a dominant model. This work suggests that the PDS gene should be considered a new susceptibility gene to AITDs with varying contributions in each pathology.

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Association test using Copy Number Profile Curves (CONCUR) enhances power in rare copy number variant analysis

PLoS Computational Biology ◽

10.1371/journal.pcbi.1007797 ◽

2020 ◽

Vol 16 (5) ◽

pp. e1007797

Author(s):

Amanda Brucker ◽

Wenbin Lu ◽

Rachel Marceau West ◽

Qi-You Yu ◽

Chuhsing Kate Hsiao ◽

...

Keyword(s):

Copy Number ◽

Copy Number Variant ◽

Association Test ◽

Copy Number Profile ◽

Variant Analysis

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Copy number variants in clinical WGS: deployment and interpretation for rare and undiagnosed disease

10.1101/245100 ◽

2018 ◽

Cited By ~ 3

Author(s):

Andrew M Gross ◽

Subramanian S. Ajay ◽

Vani Rajan ◽

Carolyn Brown ◽

Krista Bluske ◽

...

Keyword(s):

Copy Number ◽

De Novo ◽

Genetic Disorders ◽

Diagnostic Testing ◽

Copy Number Variants ◽

Uniparental Disomy ◽

Copy Number Variant ◽

Break Point ◽

Clinically Significant ◽

Family Based

AbstractPurposeCurrent diagnostic testing for genetic disorders involves serial use of specialized assays spanning multiple technologies. In principle, whole genome sequencing (WGS) has the potential to detect all genomic mutation types on a single platform and workflow. Here we sought to evaluate copy number variant (CNV) calling as part of a clinically accredited WGS test.MethodsUsing a depth-based copy number caller we performed analytical validation of CNV calling on a reference panel of 17 samples, compared the sensitivity of WGS-based variants to those from a clinical microarray, and set a bound on precision using orthogonal technologies. We developed a protocol for family-based analysis, annotation, filtering, visualization of WGS based CNV calls, and deployed this across a clinical cohort of 79 rare and undiagnosed cases.ResultsWe found that CNV calls from WGS are at least as sensitive as those from microarrays, while only creating a modest increase in the number of variants interpreted (~10 CNVs per case). We identified clinically significant CNVs in 15% of the first 79 cases analyzed. This pipeline also enabled identification of cases of uniparental disomy (UPD) and a 50% mosaic trisomy 14. Directed analysis of some CNVs enabled break-point level resolution of genomic rearrangements and phasing of de-novo CNVs.ConclusionRobust identification of CNVs by WGS is possible within a clinical testing environment, and further developments will bring improvements in resolution of smaller and more complex CNVs.

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Identification of Copy Number Variants in a Southern Chinese Cohort of Patients with Congenital Scoliosis

Genes ◽

10.3390/genes12081213 ◽

2021 ◽

Vol 12 (8) ◽

pp. 1213

Author(s):

Wenjing Lai ◽

Xin Feng ◽

Ming Yue ◽

Prudence W.H. Cheung ◽

Vanessa N.T. Choi ◽

...

Keyword(s):

Copy Number ◽

Copy Number Variants ◽

Copy Number Variant ◽

Congenital Scoliosis ◽

Sequencing Data ◽

Rare Cnvs ◽

Southern Chinese ◽

Lateral Curvature ◽

Chinese Cohort ◽

Family Based

Congenital scoliosis (CS) is a lateral curvature of the spine resulting from congenital vertebral malformations (CVMs) and affects 0.5–1/1000 live births. The copy number variant (CNV) at chromosome 16p11.2 has been implicated in CVMs and recent studies identified a compound heterozygosity of 16p11.2 microdeletion and TBX6 variant/haplotype causing CS in multiple cohorts, which explains about 5–10% of the affected cases. Here, we studied the genetic etiology of CS by analyzing CNVs in a cohort of 67 patients with congenital hemivertebrae and 125 family controls. We employed both candidate gene and family-based approaches to filter CNVs called from whole exome sequencing data. This identified 12 CNVs in four scoliosis-associated genes (TBX6, NOTCH2, DSCAM, and SNTG1) as well as eight recessive and 64 novel rare CNVs in 15 additional genes. Some candidates, such as DHX40, NBPF20, RASA2, and MYSM1, have been found to be associated with syndromes with scoliosis or implicated in bone/spine development. In particular, the Mysm1 mutant mouse showed spinal deformities. Our findings suggest that, in addition to the 16p11.2 microdeletion, other CNVs are potentially important in predisposing to CS.

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Comparison of the Family Based Association Test and Sib Transmission Disequilibrium Test for Dichotomous Trait

Korean Journal of Applied Statistics ◽

10.5351/kjas.2010.23.6.1103 ◽

2010 ◽

Vol 23 (6) ◽

pp. 1103-1113

Author(s):

Han-Sang Kim ◽

Young-Sin Oh ◽

Hae-Hiang Song

Keyword(s):

Transmission Disequilibrium Test ◽

Association Test ◽

Transmission Disequilibrium ◽

The Family ◽

Family Based ◽

Dichotomous Trait

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MCKAT: a multi-dimensional copy number variant kernel association test

BMC Bioinformatics ◽

10.1186/s12859-021-04494-w ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Nastaran Maus Esfahani ◽

Daniel Catchpoole ◽

Javed Khan ◽

Paul J. Kennedy

Keyword(s):

Copy Number ◽

Kernel Method ◽

Random Effect ◽

Random Effect Model ◽

Score Test ◽

Copy Number Variants ◽

Copy Number Variant ◽

Association Test ◽

Single Pair ◽

Related Trait

Abstract Background Copy number variants (CNVs) are the gain or loss of DNA segments in the genome. Studies have shown that CNVs are linked to various disorders, including autism, intellectual disability, and schizophrenia. Consequently, the interest in studying a possible association of CNVs to specific disease traits is growing. However, due to the specific multi-dimensional characteristics of the CNVs, methods for testing the association between CNVs and the disease-related traits are still underdeveloped. We propose a novel multi-dimensional CNV kernel association test (MCKAT) in this paper. We aim to find significant associations between CNVs and disease-related traits using kernel-based methods. Results We address the multi-dimensionality in CNV characteristics. We first design a single pair CNV kernel, which contains three sub-kernels to summarize the similarity between two CNVs considering all CNV characteristics. Then, aggregate single pair CNV kernel to the whole chromosome CNV kernel, which summarizes the similarity between CNVs in two or more chromosomes. Finally, the association between the CNVs and disease-related traits is evaluated by comparing the similarity in the trait with kernel-based similarity using a score test in a random effect model. We apply MCKAT on genome-wide CNV datasets to examine the association between CNVs and disease-related traits, which demonstrates the potential usefulness the proposed method has for the CNV association tests. We compare the performance of MCKAT with CKAT, a uni-dimensional kernel method. Based on the results, MCKAT indicates stronger evidence, smaller p-value, in detecting significant associations between CNVs and disease-related traits in both rare and common CNV datasets. Conclusion A multi-dimensional copy number variant kernel association test can detect statistically significant associated CNV regions with any disease-related trait. MCKAT can provide biologists with CNV hot spots at the cytogenetic band level that CNVs on them may have a significant association with disease-related traits. Using MCKAT, biologists can narrow their investigation from the whole genome, including many genes and CNVs, to more specific cytogenetic bands that MCKAT identifies. Furthermore, MCKAT can help biologists detect significantly associated CNVs with disease-related traits across a patient group instead of examining each subject’s CNVs case by case.

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