Characterization of autosomal copy-number variation in African Americans: the HyperGEN Study

Genomewide Association Study Identifies Copy Number Variants Associated With Warfarin Dose Response and Risk of Venous Thromboembolism in African Americans

The anticoagulant warfarin is commonly used to control and prevent thrombotic disorders, such as venous thromboembolism (VTE), which disproportionately afflicts African Americans. Despite the importance of copy number variants (CNVs), few studies have focused on characterizing and understanding their role in drug response and disease risk among African Americans. In this study, we conduct the first genome-wide analysis of CNVs to more comprehensively account for the contribution of genetic variation in warfarin dose requirement and VTE risk among African Americans. We used hidden Markov models to detect CNVs from high-throughput single-nucleotide polymorphism arrays for 340 African American participants in the International Warfarin Pharmacogenetics Consortium. We identified 11,570 CNVs resulting in 2,038 copy number variable regions (CNVRs) and found 3 CNVRs associated with warfarin dose requirement and 3 CNVRs associated with VTE risk in African Americans. CNVRs 1q31.2del and 6q14.1del were associated with increased warfarin dose requirement (β = 11.18 and 4.94, respectively; Pemp  = < 0.002); CNVR 19p13.31del was associated with decreased warfarin dose requirement (β = -1.41, Pemp  = 0.0004); CNVRs (2p22.1del and 5q35.1-q35.2del) were found to be associated with increased risk of VTE (odds ratios (ORs) = 1.88 and 14.9, respectively; Pemp  ≤0.02); and CNVR 10q26.12del was associated with a decreased risk of VTE (OR = 0.6; Pemp  = 0.05). Modeling of the 10q26.12del in HepG2 cells revealed that this deletion results in decreased fibrinogen gene expression, decreased fibrinogen and WDR11 protein levels, and decreased secretion of fibrinogen into the extracellular matrix. We found robust evidence that CNVRs could contribute to warfarin dose requirement and risk of VTE in African Americans and for 10q26.3del describe a possible pathogenic mechanism.

Evaluation of copy number variation detection for a SNP array platform

Background

Copy Number Variations (CNVs) are usually inferred from Single Nucleotide Polymorphism (SNP) arrays by use of some software packages based on given algorithms. However, there is no clear understanding of the performance of these software packages; it is therefore difficult to select one or several software packages for CNV detection based on the SNP array platform.

We selected four publicly available software packages designed for CNV calling from an Affymetrix SNP array, including Birdsuite, dChip, Genotyping Console (GTC) and PennCNV. The publicly available dataset generated by Array-based Comparative Genomic Hybridization (CGH), with a resolution of 24 million probes per sample, was considered to be the “gold standard”. Compared with the CGH-based dataset, the success rate, average stability rate, sensitivity, consistence and reproducibility of these four software packages were assessed compared with the “gold standard”. Specially, we also compared the efficiency of detecting CNVs simultaneously by two, three and all of the software packages with that by a single software package.

Results

Simply from the quantity of the detected CNVs, Birdsuite detected the most while GTC detected the least. We found that Birdsuite and dChip had obvious detecting bias. And GTC seemed to be inferior because of the least amount of CNVs it detected. Thereafter we investigated the detection consistency produced by one certain software package and the rest three software suits. We found that the consistency of dChip was the lowest while GTC was the highest. Compared with the CNVs detecting result of CGH, in the matching group, GTC called the most matching CNVs, PennCNV-Affy ranked second. In the non-overlapping group, GTC called the least CNVs. With regards to the reproducibility of CNV calling, larger CNVs were usually replicated better. PennCNV-Affy shows the best consistency while Birdsuite shows the poorest.

Conclusion

We found that PennCNV outperformed the other three packages in the sensitivity and specificity of CNV calling. Obviously, each calling method had its own limitations and advantages for different data analysis. Therefore, the optimized calling methods might be identified using multiple algorithms to evaluate the concordance and discordance of SNP array-based CNV calling.

The genome-wide landscape of copy number variations in the MUSGEN study provides evidence for a founder effect in the isolated Finnish population

Here we characterized the genome-wide architecture of copy number variations (CNVs) in 286 healthy, unrelated Finnish individuals belonging to the MUSGEN study, where molecular background underlying musical aptitude and related traits are studied. By using Illumina HumanOmniExpress-12v.1.0 beadchip, we identified 5493 CNVs that were spread across 467 different cytogenetic regions, spanning a total size of 287.83 Mb (∼9.6% of the human genome). Merging the overlapping CNVs across samples resulted in 999 discrete copy number variable regions (CNVRs), of which ∼6.9% were putatively novel. The average number of CNVs per person was 20, whereas the average size of CNV per locus was 52.39 kb. Large CNVs (>1 Mb) were present in 4% of the samples. The proportion of homozygous deletions in this data set (∼12.4%) seemed to be higher when compared with three other populations. Interestingly, several CNVRs were significantly enriched in this sample set, whereas several others were totally depleted. For example, a CNVR at chr2p22.1 intersecting GALM was more common in this population (P=3.3706 × 10(-44)) than in African and other European populations. The enriched CNVRs, however, showed no significant association with music-related phenotypes. Moreover, the most common CNV locations in world's normal population cohorts (6q14.1, 11q11) were overrepresented in this population. Thus, the genome-wide CNV investigation in this Finnish sample set demonstrated features that are characteristic to isolated populations. Novel CNVRs and the functional implications of CNVs revealed in this study elucidate structural variation present in this population isolate, and may also serve as candidate gene loci for music-related traits.

Utilizing extended pedigree information for discovery and confirmation of copy number variable regions among Mexican Americans

Copy number variation (CNV) remains poorly defined in many populations, including Mexican Americans. We report the discovery and genetic confirmation of copy number variable regions (CNVRs) in subjects of the San Antonio Family Heart and the San Antonio Family Diabetes Gallbladder Studies, both comprised of multigenerational pedigrees of Mexican American descent. In a discovery group of 1677 participants genotyped using Illumina Infinium Beadchips, we identified 2937 unique CNVRs, some with observation frequencies as low as 0.002, using a process that integrates pedigree information with CNV calls made by PennCNV and/or QuantiSNP. Quantitative copy number values had statistically significant (P ≤ 1.792e-5) heritability estimates ranging from 0.139 to 0.863 for 2776 CNVRs. Additionally, 920 CNVRs showed evidence of linkage to their genomic location, providing strong genetic confirmation. Linked CNVRs were enriched in a set of independently identified CNVRs from a second group of 380 samples, confirming that these CNVRs can be used as predefined CNVRs of high confidence. Interestingly, we identified 765 putatively novel variants that do not overlap with the Database of Genomic Variants. This study is the first to use linkage and heritability in multigenerational pedigrees as a confirmation approach for the discovery of CNVRs, and the largest study to date investigating copy number variation on a genome-wide scale in individuals of Mexican American descent. These results provide insight to the structural variation present in Mexican Americans and show the strength of multigenerational pedigrees to elucidate structural variation in the human genome.