Diagnostic efficacy and new variants in isolated and complex autism spectrum disorder using molecular karyotyping

Autism spectrum disorder (ASD) is a group of the neurodevelopment disorders presenting as an isolated ASD or more complex forms, where a broader clinical phenotype comprised of developmental delay and intellectual disability is present. Both the isolated and complex forms have a significant causal genetic component and submicroscopic genomic copy number variations (CNV) are the most common identifiable genetic factor in these patients. The data on microarray testing in ASD cohorts are still accumulating and novel loci are often identified; therefore, we aimed to evaluate the diagnostic efficacy of the method and the relevance of implementing it into routine genetic testing in ASD patients. A genome-wide CNV analysis using the Agilent microarrays was performed in a group of 150 individuals with an isolated or complex ASD. Altogether, 11 (7.3%) pathogenic CNVs and 15 (10.0%) variants of unknown significance (VOUS) were identified, with the highest proportion of pathogenic CNVs in the subgroup of the complex ASD patients (14.3%). An interesting case of previously unreported partial UPF3B gene deletion was identified among the pathogenic CNVs. Among the CNVs with unknown significance, four VOUS involved genes with possible correlation to ASD, namely genes SNTG2, PARK2, CADPS2 and NLGN4X. The diagnostic efficacy of aCGH in our cohort was comparable with those of the previously reported and identified an important proportion of genetic ASD cases. Despite the continuum of published studies on the CNV testing in ASD cohorts, a considerable number of VOUS CNVs is still being identified, namely 10.0% in our study.     

Transmission Disequilibrium of Small CNVs in Simplex Autism

We searched for disruptive, genic rare copy-number variants (CNVs) among 411 families affected by sporadic autism spectrum disorder (ASD) from the Simons Simplex Collection by using available exome sequence data and CoNIFER (Copy Number Inference from Exome Reads). Compared to high-density SNP microarrays, our approach yielded ∼2× more smaller genic rare CNVs. We found that affected probands inherited more CNVs than did their siblings (453 versus 394, p = 0.004; odds ratio [OR] = 1.19) and that the probands’ CNVs affected more genes (921 versus 726, p = 0.02; OR = 1.30). These smaller CNVs (median size 18 kb) were transmitted preferentially from the mother (136 maternal versus 100 paternal, p = 0.02), although this bias occurred irrespective of affected status. The excess burden of inherited CNVs among probands was driven primarily by sibling pairs with discordant social-behavior phenotypes (p < 0.0002, measured by Social Responsiveness Scale [SRS] score), which contrasts with families where the phenotypes were more closely matched or less extreme (p > 0.5). Finally, we found enrichment of brain-expressed genes unique to probands, especially in the SRS-discordant group (p = 0.0035). In a combined model, our inherited CNVs, de novo CNVs, and de novo single-nucleotide variants all independently contributed to the risk of autism (p < 0.05). Taken together, these results suggest that small transmitted rare CNVs play a role in the etiology of simplex autism. Importantly, the small size of these variants aids in the identification of specific genes as additional risk factors associated with ASD.     

The genetic architecture of autism spectrum disorders(ASDs) and the potential importance of common regulatory genetic variants

Currently, there is great interest in identifying genetic variants that contribute to the risk of developing autism spectrum disorders(ASDs), due in part to recent increases in the frequency of diagnosis of these disorders worldwide. While there is nearly universal agreement that ASDs are complex diseases, with multiple genetic and environmental contributing factors, there is less agreement concerning the relative importance of common vs rare genetic variants in ASD liability. Recent observations that rare mutations and copy number variants(CNVs) are frequently associated with ASDs, combined with reduced fecundity of individuals with these disorders, has led to the hypothesis that ASDs are caused primarily by de novo or rare genetic mutations. Based on this model, large-scale whole-genome DNA sequencing has been proposed as the most appropriate method for discovering ASD liability genes. While this approach will undoubtedly identify many novel candidate genes and produce important new insights concerning the genetic causes of these disorders, a full accounting of the genetics of ASDs will be incomplete absent an understanding of the contributions of common regulatory variants, which are likely to influence ASD liability by modifying the effects of rare variants or, by assuming unfavorable combinations, directly produce these disorders. Because it is not yet possible to identify regulatory genetic variants by examination of DNA sequences alone, their identification will require experimentation. In this essay, I discuss these issues and describe the advantages of measurements of allelic expression imbalance(AEI) of m RNA expression for identifying cis-acting regulatory variants that contribute to ASDs.     

Copy number variants in extended autism spectrum disorder families reveal candidates potentially involved in autism risk

Copy number variations (CNVs) are a major cause of genetic disruption in the human genome with far more nucleotides being altered by duplications and deletions than by single nucleotide polymorphisms (SNPs). In the multifaceted etiology of autism spectrum disorders (ASDs), CNVs appear to contribute significantly to our understanding of the pathogenesis of this complex disease. A unique resource of 42 extended ASD families was genotyped for over 1 million SNPs to detect CNVs that may contribute to ASD susceptibility. Each family has at least one avuncular or cousin pair with ASD. Families were then evaluated for co-segregation of CNVs in ASD patients. We identified a total of five deletions and seven duplications in eleven families that co-segregated with ASD. Two of the CNVs overlap with regions on 7p21.3 and 15q24.1 that have been previously reported in ASD individuals and two additional CNVs on 3p26.3 and 12q24.32 occur near regions associated with schizophrenia. These findings provide further evidence for the involvement of ICA1 and NXPH1 on 7p21.3 in ASD susceptibility and highlight novel ASD candidates, including CHL1, FGFBP3 and POUF41. These studies highlight the power of using extended families for gene discovery in traits with a complex etiology.     

Rare De Novo Copy Number Variants in Patients with Congenital Pulmonary Atresia

Background

Ongoing studies using genomic microarrays and next-generation sequencing have demonstrated that the genetic contributions to cardiovascular diseases have been significantly ignored in the past. The aim of this study was to identify rare copy number variants in individuals with congenital pulmonary atresia (PA).

Methods and Results

Based on the hypothesis that rare structural variants encompassing key genes play an important role in heart development in PA patients, we performed high-resolution genome-wide microarrays for copy number variations (CNVs) in 82 PA patient-parent trios and 189 controls with an Illumina SNP array platform. CNVs were identified in 17/82 patients (20.7%), and eight of these CNVs (9.8%) are considered potentially pathogenic. Five de novo CNVs occurred at two known congenital heart disease (CHD) loci (16p13.1 and 22q11.2). Two de novo CNVs that may affect folate and vitamin B₁₂ metabolism were identified for the first time. A de novo 1-Mb deletion at 17p13.2 may represent a rare genomic disorder that involves mild intellectual disability and associated facial features.

Conclusions

Rare CNVs contribute to the pathogenesis of PA (9.8%), suggesting that the causes of PA are heterogeneous and pleiotropic. Together with previous data from animal models, our results might help identify a link between CHD and folate-mediated one-carbon metabolism (FOCM). With the accumulation of high-resolution SNP array data, these previously undescribed rare CNVs may help reveal critical gene(s) in CHD and may provide novel insights about CHD pathogenesis.     

Identification of copy number variants from exome sequence data

Background

With advances in next generation sequencing technologies and genomic capture techniques, exome sequencing has become a cost-effective approach for mutation detection in genetic diseases. However, computational prediction of copy number variants (CNVs) from exome sequence data is a challenging task. Whilst numerous programs are available, they have different sensitivities, and have low sensitivity to detect smaller CNVs (1–4 exons). Additionally, exonic CNV discovery using standard aCGH has limitations due to the low probe density over exonic regions. The goal of our study was to develop a protocol to detect exonic CNVs (including shorter CNVs that cover 1–4 exons), combining computational prediction algorithms and a high-resolution custom CGH array.

Results

We used six published CNV prediction programs (ExomeCNV, CONTRA, ExomeCopy, ExomeDepth, CoNIFER, XHMM) and an in-house modification to ExomeCopy and ExomeDepth (ExCopyDepth) for computational CNV prediction on 30 exomes from the 1000 genomes project and 9 exomes from primary immunodeficiency patients. CNV predictions were tested using a custom CGH array designed to capture all exons (exaCGH). After this validation, we next evaluated the computational prediction of shorter CNVs. ExomeCopy and the in-house modified algorithm, ExCopyDepth, showed the highest capability in detecting shorter CNVs. Finally, the performance of each computational program was assessed by calculating the sensitivity and false positive rate.

Conclusions

In this paper, we assessed the ability of 6 computational programs to predict CNVs, focussing on short (1–4 exon) CNVs. We also tested these predictions using a custom array targeting exons. Based on these results, we propose a protocol to identify and confirm shorter exonic CNVs combining computational prediction algorithms and custom aCGH experiments.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-661) contains supplementary material, which is available to authorized users.     

Population Analysis of Large Copy Number Variants and Hotspots of Human Genetic Disease

Copy number variants (CNVs) contribute to human genetic and phenotypic diversity. However, the distribution of larger CNVs in the general population remains largely unexplored. We identify large variants in ~2500 individuals by using Illumina SNP data, with an emphasis on “hotspots” prone to recurrent mutations. We find variants larger than 500 kb in 5%–10% of individuals and variants greater than 1 Mb in 1%–2%. In contrast to previous studies, we find limited evidence for stratification of CNVs in geographically distinct human populations. Importantly, our sample size permits a robust distinction between truly rare and polymorphic but low-frequency copy number variation. We find that a significant fraction of individual CNVs larger than 100 kb are rare and that both gene density and size are strongly anticorrelated with allele frequency. Thus, although large CNVs commonly exist in normal individuals, which suggests that size alone can not be used as a predictor of pathogenicity, such variation is generally deleterious. Considering these observations, we combine our data with published CNVs from more than 12,000 individuals contrasting control and neurological disease collections. This analysis identifies known disease loci and highlights additional CNVs (e.g., 3q29, 16p12, and 15q25.2) for further investigation. This study provides one of the first analyses of large, rare (0.1%–1%) CNVs in the general population, with insights relevant to future analyses of genetic disease.     

Copy number variations identified in the chicken using a 60K SNP BeadChip

Copy number variation (CNV) is considered an important genetic variation, contributing to many economically important traits in the chicken. Although CNVs can be detected using a comparative genomic hybridization array, the high‐density SNP array has provided an alternative way to identify CNVs in the chicken. In the current study, a chicken 60K SNP BeadChip was used to identify CNVs in two distinct chicken genetic lines (White Leghorn and dwarf) using the penncnv program. A total of 209 CNV regions were identified, distributing on chromosomes 1–22 and 24–28 and encompassing 13.55 Mb (1.42%) of chicken autosomal genome area. Three of seven selected CNVs (73.2% individuals) were completely validated by quantitative PCR. To our knowledge, this is the first report in the chicken identifying CNVs using a SNP array. Identification of 190 new identified CNVs illustrates the feasibility of the chicken 60K SNP BeadChip to detect CNVs in the chicken, which lays a solid foundation for future analyses of associations of CNVs with economically important phenotypes in chickens.     

Precision-mapping and statistical validation of quantitative trait loci by machine learning

Background

DNA sequence diversity within the human genome may be more greatly affected by copy number variations (CNVs) than single nucleotide polymorphisms (SNPs). Although the importance of CNVs in genome wide association studies (GWAS) is becoming widely accepted, the optimal methods for identifying these variants are still under evaluation. We have previously reported a comprehensive view of CNVs in the HapMap DNA collection using high density 500 K EA (Early Access) SNP genotyping arrays which revealed greater than 1,000 CNVs ranging in size from 1 kb to over 3 Mb. Although the arrays used most commonly for GWAS predominantly interrogate SNPs, CNV identification and detection does not necessarily require the use of DNA probes centered on polymorphic nucleotides and may even be hindered by the dependence on a successful SNP genotyping assay.

Results

In this study, we have designed and evaluated a high density array predicated on the use of non-polymorphic oligonucleotide probes for CNV detection. This approach effectively uncouples copy number detection from SNP genotyping and thus has the potential to significantly improve probe coverage for genome-wide CNV identification. This array, in conjunction with PCR-based, complexity-reduced DNA target, queries over 1.3 M independent NspI restriction enzyme fragments in the 200 bp to 1100 bp size range, which is a several fold increase in marker density as compared to the 500 K EA array. In addition, a novel algorithm was developed and validated to extract CNV regions and boundaries.

Conclusion

Using a well-characterized pair of DNA samples, close to 200 CNVs were identified, of which nearly 50% appear novel yet were independently validated using quantitative PCR. The results indicate that non-polymorphic probes provide a robust approach for CNV identification, and the increasing precision of CNV boundary delineation should allow a more complete analysis of their genomic organization.     

Structural variation of chromosomes in autism spectrum disorder

Structural variation (copy number variation [CNV] including deletion and duplication, translocation, inversion) of chromosomes has been identified in some individuals with autism spectrum disorder (ASD), but the full etiologic role is unknown. We performed genome-wide assessment for structural abnormalities in 427 unrelated ASD cases via single-nucleotide polymorphism microarrays and karyotyping. With microarrays, we discovered 277 unbalanced CNVs in 44% of ASD families not present in 500 controls (and re-examined in another 1152 controls). Karyotyping detected additional balanced changes. Although most variants were inherited, we found a total of 27 cases with de novo alterations, and in three (11%) of these individuals, two or more new variants were observed. De novo CNVs were found in approximately 7% and approximately 2% of idiopathic families having one child, or two or more ASD siblings, respectively. We also detected 13 loci with recurrent/overlapping CNV in unrelated cases, and at these sites, deletions and duplications affecting the same gene(s) in different individuals and sometimes in asymptomatic carriers were also found. Notwithstanding complexities, our results further implicate the SHANK3-NLGN4-NRXN1 postsynaptic density genes and also identify novel loci at DPP6-DPP10-PCDH9 (synapse complex), ANKRD11, DPYD, PTCHD1, 15q24, among others, for a role in ASD susceptibility. Our most compelling result discovered CNV at 16p11.2 (p = 0.002) (with characteristics of a genomic disorder) at approximately 1% frequency. Some of the ASD regions were also common to mental retardation loci. Structural variants were found in sufficiently high frequency influencing ASD to suggest that cytogenetic and microarray analyses be considered in routine clinical workup.     

Convergence of Genes and Cellular Pathways Dysregulated in Autism Spectrum Disorders

Rare copy-number variation (CNV) is an important source of risk for autism spectrum disorders (ASDs). We analyzed 2,446 ASD-affected families and confirmed an excess of genic deletions and duplications in affected versus control groups (1.41-fold, p = 1.0 × 10⁻⁵) and an increase in affected subjects carrying exonic pathogenic CNVs overlapping known loci associated with dominant or X-linked ASD and intellectual disability (odds ratio = 12.62, p = 2.7 × 10⁻¹⁵, ∼3% of ASD subjects). Pathogenic CNVs, often showing variable expressivity, included rare de novo and inherited events at 36 loci, implicating ASD-associated genes (CHD2, HDAC4, and GDI1) previously linked to other neurodevelopmental disorders, as well as other genes such as SETD5, MIR137, and HDAC9. Consistent with hypothesized gender-specific modulators, females with ASD were more likely to have highly penetrant CNVs (p = 0.017) and were also overrepresented among subjects with fragile X syndrome protein targets (p = 0.02). Genes affected by de novo CNVs and/or loss-of-function single-nucleotide variants converged on networks related to neuronal signaling and development, synapse function, and chromatin regulation.     

Genome-wide mapping of copy number variation in humans: comparative analysis of high resolution array platforms

Accurate and efficient genome-wide detection of copy number variants (CNVs) is essential for understanding human genomic variation, genome-wide CNV association type studies, cytogenetics research and diagnostics, and independent validation of CNVs identified from sequencing based technologies. Numerous, array-based platforms for CNV detection exist utilizing array Comparative Genome Hybridization (aCGH), Single Nucleotide Polymorphism (SNP) genotyping or both. We have quantitatively assessed the abilities of twelve leading genome-wide CNV detection platforms to accurately detect Gold Standard sets of CNVs in the genome of HapMap CEU sample NA12878, and found significant differences in performance. The technologies analyzed were the NimbleGen 4.2 M, 2.1 M and 3×720 K Whole Genome and CNV focused arrays, the Agilent 1×1 M CGH and High Resolution and 2×400 K CNV and SNP+CGH arrays, the Illumina Human Omni1Quad array and the Affymetrix SNP 6.0 array. The Gold Standards used were a 1000 Genomes Project sequencing-based set of 3997 validated CNVs and an ultra high-resolution aCGH-based set of 756 validated CNVs. We found that sensitivity, total number, size range and breakpoint resolution of CNV calls were highest for CNV focused arrays. Our results are important for cost effective CNV detection and validation for both basic and clinical applications.     

Synergistic Interactions between Drosophila Orthologues of Genes Spanned by De Novo Human CNVs Support Multiple-Hit Models of Autism

Autism spectrum disorders (ASDs) are highly heritable and characterised by deficits in social interaction and communication, as well as restricted and repetitive behaviours. Although a number of highly penetrant ASD gene variants have been identified, there is growing evidence to support a causal role for combinatorial effects arising from the contributions of multiple loci. By examining synaptic and circadian neurological phenotypes resulting from the dosage variants of unique human:fly orthologues in Drosophila, we observe numerous synergistic interactions between pairs of informatically-identified candidate genes whose orthologues are jointly affected by large de novo copy number variants (CNVs). These CNVs were found in the genomes of individuals with autism, including a patient carrying a 22q11.2 deletion. We first demonstrate that dosage alterations of the unique Drosophila orthologues of candidate genes from de novo CNVs that harbour only a single candidate gene display neurological defects similar to those previously reported in Drosophila models of ASD-associated variants. We then considered pairwise dosage changes within the set of orthologues of candidate genes that were affected by the same single human de novo CNV. For three of four CNVs with complete orthologous relationships, we observed significant synergistic effects following the simultaneous dosage change of gene pairs drawn from a single CNV. The phenotypic variation observed at the Drosophila synapse that results from these interacting genetic variants supports a concordant phenotypic outcome across all interacting gene pairs following the direction of human gene copy number change. We observe both specificity and transitivity between interactors, both within and between CNV candidate gene sets, supporting shared and distinct genetic aetiologies. We then show that different interactions affect divergent synaptic processes, demonstrating distinct molecular aetiologies. Our study illustrates mechanisms through which synergistic effects resulting from large structural variation can contribute to human disease.     

Discovery of allelic variants of HOXA1 and HOXB1: genetic susceptibility to autism spectrum disorders

BACKGROUND: Family studies have demonstrated that the autism spectrum disorders (ASDs) have a major genetic etiologic component, but expression and penetrance of the phenotype are variable. Mice with null mutations of Hoxa1 or Hoxb1, two genes critical to hindbrain development, have phenotypic features frequently observed in autism, but no naturally occurring variants of either gene have been identified in mammals. METHODS: By sequencing regions of genomic DNA of patients with autism spectrum disorders, we detected a substitution variant at HOXA1 and an insertion variant at HOXB1, both in coding regions of the genes. Fifty-seven individuals ascertained for a diagnosis of an ASD, along with 166 of their relatives, were typed for these variants. Two non-ASD populations were typed, and the frequency of the newly identified alleles was determined in all groups. The genotypes of the ASD families were tested for conformation to Hardy-Weinberg proportions and Mendelian expectations for gene transmission. RESULTS: The frequency of the variants was 10-25% in persons of European or African origin. In the ASD families, there was a significant deviation from the HOXA1 genotype ratios expected from Hardy-Weinberg proportions (P = 0.005). Among affected offspring, a significant deviation from Mendelian expectation in gene transmission (P = 0.011) was observed. No statistically significant effects were detected when the same analyses were applied to the HOXB1 locus, but there was evidence of an interaction between HOXA1, HOXB1, and gender in susceptibility to ASDs. CONCLUSIONS: The results support a role for HOXA1 in susceptibility to autism, and add to the existing body of evidence implicating early brain stem injury in the etiology of ASDs.     

Recurrent Rare Genomic Copy Number Variants and Bicuspid Aortic Valve Are Enriched in Early Onset Thoracic Aortic Aneurysms and Dissections

Thoracic Aortic Aneurysms and Dissections (TAAD) are a major cause of death in the United States. The spectrum of TAAD ranges from genetic disorders, such as Marfan syndrome, to sporadic isolated disease of unknown cause. We hypothesized that genomic copy number variants (CNVs) contribute causally to early onset TAAD (ETAAD). We conducted a genome-wide SNP array analysis of ETAAD patients of European descent who were enrolled in the National Registry of Genetically Triggered Thoracic Aortic Aneurysms and Cardiovascular Conditions (GenTAC). Genotyping was performed on the Illumina Omni-Express platform, using PennCNV, Nexus and CNVPartition for CNV detection. ETAAD patients (n = 108, 100% European American, 28% female, average age 20 years, 55% with bicuspid aortic valves) were compared to 7013 dbGAP controls without a history of vascular disease using downsampled Omni 2.5 data. For comparison, 805 sporadic TAAD patients with late onset aortic disease (STAAD cohort) and 192 affected probands from families with at least two affected relatives (FTAAD cohort) from our institution were screened for additional CNVs at these loci with SNP arrays. We identified 47 recurrent CNV regions in the ETAAD, FTAAD and STAAD groups that were absent or extremely rare in controls. Nine rare CNVs that were either very large (>1 Mb) or shared by ETAAD and STAAD or FTAAD patients were also identified. Four rare CNVs involved genes that cause arterial aneurysms when mutated. The largest and most prevalent of the recurrent CNVs were at Xq28 (two duplications and two deletions) and 17q25.1 (three duplications). The percentage of individuals harboring rare CNVs was significantly greater in the ETAAD cohort (32%) than in the FTAAD (23%) or STAAD (17%) cohorts. We identified multiple loci affected by rare CNVs in one-third of ETAAD patients, confirming the genetic heterogeneity of TAAD. Alterations of candidate genes at these loci may contribute to the pathogenesis of TAAD.     

Prioritization of Copy Number Variation Loci Associated with Autism from AutDB–An Integrative Multi-Study Genetic Database

Copy number variants (CNVs) are thought to play an important role in the predisposition to autism spectrum disorder (ASD). However, their relatively low frequency and widespread genomic distribution complicates their accurate characterization and utilization for clinical genetics purposes. Here we present a comprehensive analysis of multi-study, genome-wide CNV data from AutDB (http://mindspec.org/autdb.html), a genetic database that accommodates detailed annotations of published scientific reports of CNVs identified in ASD individuals. Overall, we evaluated 4,926 CNVs in 2,373 ASD subjects from 48 scientific reports, encompassing ∼2.12×10⁹ bp of genomic data. Remarkable variation was seen in CNV size, with duplications being significantly larger than deletions, (P  =  3×10⁻¹⁰⁵; Wilcoxon rank sum test). Examination of the CNV burden across the genome revealed 11 loci with a significant excess of CNVs among ASD subjects (P<7×10⁻⁷). Altogether, these loci covered 15,610 kb of the genome and contained 166 genes. Remarkable variation was seen both in locus size (20 - 4950 kb), and gene content, with seven multigenic (≥3 genes) and four monogenic loci. CNV data from control populations was used to further refine the boundaries of these ASD susceptibility loci. Interestingly, our analysis indicates that 15q11.2-13.3, a genomic region prone to chromosomal rearrangements of various sizes, contains three distinct ASD susceptibility CNV loci that vary in their genomic boundaries, CNV types, inheritance patterns, and overlap with CNVs from control populations. In summary, our analysis of AutDB CNV data provides valuable insights into the genomic characteristics of ASD susceptibility CNV loci and could therefore be utilized in various clinical settings and facilitate future genetic research of this disorder.     

Replication of the 4p16 Susceptibility Locus in Congenital Heart Disease in Han Chinese Populations

Congenital heart disease (CHD) is the most common form of congenital human birth anomalies and a leading cause of perinatal and infant mortality. Some studies including our published genome-wide association study (GWAS) of CHD have indicated that genetic variants may contribute to the risk of CHD. Recently, Cordell et al. published a GWAS of multiple CHD phenotypes in European Caucasians and identified 3 susceptibility loci (rs870142, rs16835979 and rs6824295) for ostium secundum atrial septal defect (ASD) at chromosome 4p16. However, whether these loci at 4p16 confer the predisposition to CHD in Chinese population is unclear. In the current study, we first analyzed the associations between these 3 single nucleotide polymorphisms (SNPs) at 4p16 and CHD risk by using our existing genome-wide scan data and found all of the 3 SNPs showed significant associations with ASD in the same direction as that observed in Cordell’s study, but not with other subtypes- ventricular septal defect (VSD) and ASD combined VSD. As these 3 SNPs were in high linkage disequilibrium (LD) in Chinese population, we selected one SNP with the lowest P value in our GWAS scan (rs16835979) to perform a replication study with additional 1,709 CHD cases with multiple phenotypes and 1,962 controls. The significant association was also observed only within the ASD subgroup, which was heterogeneous from other disease groups. In combined GWAS and replication samples, the minor allele of rs16835979 remained significant association with the risk of ASD (OR = 1.22, 95% CI = 1.08–1.38, P = 0.001). Our findings suggest that susceptibility loci of ASD identified from Cordell’s European GWAS are generalizable to Chinese population, and such investigation may provide new insights into the roles of genetic variants in the etiology of different CHD phenotypes.     

Genetic Association Studies of Copy-Number Variation: Should Assignment of Copy Number States Precede Testing?

Recently, structural variation in the genome has been implicated in many complex diseases. Using genomewide single nucleotide polymorphism (SNP) arrays, researchers are able to investigate the impact not only of SNP variation, but also of copy-number variants (CNVs) on the phenotype. The most common analytic approach involves estimating, at the level of the individual genome, the underlying number of copies present at each location. Once this is completed, tests are performed to determine the association between copy number state and phenotype. An alternative approach is to carry out association testing first, between phenotype and raw intensities from the SNP array at the level of the individual marker, and then aggregate neighboring test results to identify CNVs associated with the phenotype. Here, we explore the strengths and weaknesses of these two approaches using both simulations and real data from a pharmacogenomic study of the chemotherapeutic agent gemcitabine. Our results indicate that pooled marker-level testing is capable of offering a dramatic increase in power (> 12-fold) over CNV-level testing, particularly for small CNVs. However, CNV-level testing is superior when CNVs are large and rare; understanding these tradeoffs is an important consideration in conducting association studies of structural variation.