Contribution of copy-number variation to Down syndrome-associated atrioventricular septal defects

Genome-wide association studies of Down syndrome associated congenital heart defects

Congenital heart defects (CHDs) are the most common structural birth defect and are present in 40-50% of children born with Down syndrome (DS). To characterize the genetic architecture of DS-associated CHD, we sequenced genomes of a multiethnic group of children with DS and a CHD (n=886: atrioventricular septal defects (AVSD), n=438; atrial septal defects (ASD), n=122; ventricular septal defects (VSD), n=170; other types of CHD, n=156) and DS with a structurally normal heart (DS+NH, n=572). We performed four GWAS for common variants (MAF>0.05) comparing DS with CHD, stratified by CHD-subtype, to DS+NH controls. Although no SNP achieved genome-wide significance, multiple loci in each analysis achieved suggestive significance (p<2×10-6). Of these, the 1p35.1 locus (near RBBP4) was specifically associated with ASD risk and the 5q35.2 locus (near MSX2) was associated with any type of CHD. Each of the suggestive loci contained one or more plausible candidate genes expressed in the developing heart. While no SNP replicated (p<2×10-6) in an independent cohort of DS+CHD (DS+CHD: n=229; DS+NH: n=197), most SNPs that were suggestive in our GWASs remained suggestive when meta-analyzed with the GWASs from the replication cohort. These results build on previous work to identify genetic modifiers of DS-associated CHD.

Human Genetics of Atrioventricular Septal Defect

Atrioventricular septal defects (AVSD), also known as a common atrioventricular canal (CAVC), are clinically severe heart malformations that affect about 1 out of every 2100 live births. AVSD makes up about 5% of all congenital heart defects. AVSD is associated with cytogenetic disorders such as Down syndrome and numerous other rare genetic syndromes, but also occurs as a simplex trait. Studies in mouse models have identified over 100 genetic mutations that have the potential to cause an AVSD. However, studies in humans indicate that AVSD is genetically heterogeneous, and that the cause in humans is very rarely a single-gene defect. Familial cases do occur albeit rarely, usually with autosomal dominant inheritance and variable expression. In addition, the frequent occurrence of AVSD in some syndromes with known genetic causes such as heterotaxy syndrome points to additional genes/pathways that increase AVSD risk. Accordingly, while the genetic underpinnings for most AVSD remain unknown, there have been advances in identifying genetic risk factors for AVSD in both syndromic and nonsyndromic cases. This chapter summarizes the current knowledge of the genetic basis for AVSD.

Beyond chromosome analysis: Additional genetic testing practice in a Down syndrome clinic

Down syndrome (DS) and other genetic conditions have been reported to co-occur in the same person. This study sought to examine the genetic evaluation beyond chromosome analysis of individuals with DS at one DS specialty clinic. Retrospective chart review of genetic testing performed beyond chromosome analysis, the indication for the genetic testing, and the result of the genetic testing from the electronic health record was performed. Demographic information was collected and summary statistics, including mean and frequency, were calculated. The charts of 637 individuals with DS were reviewed. Overall, 146 genetic tests in addition to routine chromosome analysis were performed on 92 individuals with DS. Tests included chromosomal microarray, gene panels, and whole exome sequencing. Tests were performed for the indication of: autism spectrum disorder, celiac disease, dementia, hematologic diseases, and others. Eleven individuals with DS were found to have a second genetic diagnosis. Individuals with DS in one multidisciplinary clinic for DS had a variety of genetic tests beyond chromosomes completed, for varied indications, and with some abnormal results leading to additional diagnoses. Additional genetic testing beyond chromosome analysis is a reasonable consideration for patients with DS who have features suggestive of a secondary diagnosis.

Epigenomic signature of major congenital heart defects in newborns with Down syndrome

BACKGROUND

Congenital heart defects (CHDs) affect approximately half of individuals with Down syndrome (DS), but the molecular reasons for incomplete penetrance are unknown. Previous studies have largely focused on identifying genetic risk factors associated with CHDs in individuals with DS, but comprehensive studies of the contribution of epigenetic marks are lacking. We aimed to identify and characterize DNA methylation differences from newborn dried blood spots (NDBS) of DS individuals with major CHDs compared to DS individuals without CHDs.

METHODS

We used the Illumina EPIC array and whole-genome bisulfite sequencing (WGBS) to quantitate DNA methylation for 86 NDBS samples from the California Biobank Program: (1) 45 DS-CHD (27 female, 18 male) and (2) 41 DS non-CHD (27 female, 14 male). We analyzed global CpG methylation and identified differentially methylated regions (DMRs) in DS-CHD versus DS non-CHD comparisons (both sex-combined and sex-stratified) corrected for sex, age of blood collection, and cell-type proportions. CHD DMRs were analyzed for enrichment in CpG and genic contexts, chromatin states, and histone modifications by genomic coordinates and for gene ontology enrichment by gene mapping. DMRs were also tested in a replication dataset and compared to methylation levels in DS versus typical development (TD) WGBS NDBS samples.

RESULTS

We found global CpG hypomethylation in DS-CHD males compared to DS non-CHD males, which was attributable to elevated levels of nucleated red blood cells and not seen in females. At a regional level, we identified 58, 341, and 3938 CHD-associated DMRs in the Sex Combined, Females Only, and Males Only groups, respectively, and used machine learning algorithms to select 19 Males Only loci that could distinguish CHD from non-CHD. DMRs in all comparisons were enriched for gene exons, CpG islands, and bivalent chromatin and mapped to genes enriched for terms related to cardiac and immune functions. Lastly, a greater percentage of CHD-associated DMRs than background regions were differentially methylated in DS versus TD samples.

CONCLUSIONS

A sex-specific signature of DNA methylation was detected in NDBS of DS-CHD compared to DS non-CHD individuals. This supports the hypothesis that epigenetics can reflect the variability of phenotypes in DS, particularly CHDs.

Epigenomic signature of major congenital heart defects in newborns with Down syndrome

Background

Congenital heart defects (CHDs) affect approximately half of individuals with Down syndrome (DS) but the molecular reasons for incomplete penetrance are unknown. Previous studies have largely focused on identifying genetic risk factors associated with CHDs in individuals with DS, but comprehensive studies of the contribution of epigenetic marks are lacking. We aimed to identify and characterize DNA methylation differences from newborn dried blood spots (NDBS) of DS individuals with major CHDs compared to DS individuals without CHDs.

Methods

We used the Illumina EPIC array and whole-genome bisulfite sequencing (WGBS) to quantitate DNA methylation for 86 NDBS samples from the California Biobank Program: 1) 45 DS-CHD (27 female, 18 male) and 2) 41 DS non-CHD (27 female, 14 male). We analyzed global CpG methylation and identified differentially methylated regions (DMRs) in DS-CHD vs DS non-CHD comparisons (both sex-combined and sex-stratified) corrected for sex, age of blood collection, and cell type proportions. CHD DMRs were analyzed for enrichment in CpG and genic contexts, chromatin states, and histone modifications by genomic coordinates and for gene ontology enrichment by gene mapping. DMRs were also tested in a replication dataset and compared to methylation levels in DS vs typical development (TD) WGBS NDBS samples.

Results

We found global CpG hypomethylation in DS-CHD males compared to DS non-CHD males, which was attributable to elevated levels of nucleated red blood cells and not seen in females. At a regional level, we identified 58, 341, and 3,938 CHD-associated DMRs in the Sex Combined, Females Only, and Males Only groups, respectively, and used machine learning algorithms to select 19 Males Only loci that could distinguish CHD from non-CHD. DMRs in all comparisons were enriched for gene exons, CpG islands, and bivalent chromatin and mapped to genes enriched for terms related to cardiac and immune functions. Lastly, a greater percentage of CHD-associated DMRs than background regions were differentially methylated in DS vs TD samples.

Conclusions

A sex-specific signature of DNA methylation was detected in NDBS of DS-CHD compared to DS non-CHD individuals. This supports the hypothesis that epigenetics can reflect the variability of phenotypes in DS, particularly CHDs.

Opportunities, barriers, and recommendations in down syndrome research

BACKGROUND

Recent advances in medical care have increased life expectancy and improved the quality of life for people with Down syndrome (DS). These advances are the result of both pre-clinical and clinical research but much about DS is still poorly understood. In 2020, the NIH announced their plan to update their DS research plan and requested input from the scientific and advocacy community.

OBJECTIVE

The National Down Syndrome Society (NDSS) and the LuMind IDSC Foundation worked together with scientific and medical experts to develop recommendations for the NIH research plan.

METHODS

NDSS and LuMind IDSC assembled over 50 experts across multiple disciplines and organized them in eleven working groups focused on specific issues for people with DS.

RESULTS

This review article summarizes the research gaps and recommendations that have the potential to improve the health and quality of life for people with DS within the next decade.

CONCLUSIONS

This review highlights many of the scientific gaps that exist in DS research. Based on these gaps, a multidisciplinary group of DS experts has made recommendations to advance DS research. This paper may also aid policymakers and the DS community to build a comprehensive national DS research strategy.

Genotypic and phenotypic variability of 22q11.2 microdeletions – an institutional experience

<abstract> <p>Patients with chromosome 22q11.2 deletion syndromes classically present with variable cardiac defects, parathyroid and thyroid gland hypoplasia, immunodeficiency and velopharyngeal insufficiency, developmental delay, intellectual disability, cognitive impairment, and psychiatric disorders. New technologies including chromosome microarray have identified smaller deletions in the 22q11.2 region. An increasing number of studies have reported patients presenting with various features harboring smaller 22q11.2 deletions, suggesting a need to better elucidate 22q11.2 deletions and their phenotypic contributions so that clinicians may better guide prognosis for families. We identified 16 pediatric patients at our institution harboring various 22q11.2 deletions detected by chromosomal microarray and report their clinical presentations. Findings include various neurodevelopmental delays with the most common one being attention deficit hyperactivity disorder (ADHD), one reported case of infant lethality, four cases of preterm birth, one case with dual diagnoses of 22q11.2 microdeletion and Down syndrome. We examined potential genotypic contributions of the deleted regions.</p> </abstract>

Identifying genetic factors that contribute to the increased risk of congenital heart defects in infants with Down syndrome

Atrioventricular septal defects (AVSD) are a severe congenital heart defect present in individuals with Down syndrome (DS) at a > 2000-fold increased prevalence compared to the general population. This study aimed to identify risk-associated genes and pathways and to examine a potential polygenic contribution to AVSD in DS. We analyzed a total cohort of 702 individuals with DS with or without AVSD, with genomic data from whole exome sequencing, whole genome sequencing, and/or array-based imputation. We utilized sequence kernel association testing and polygenic risk score (PRS) methods to examine rare and common variants. Our findings suggest that the Notch pathway, particularly NOTCH4, as well as genes involved in the ciliome including CEP290 may play a role in AVSD in DS. These pathways have also been implicated in DS-associated AVSD in prior studies. A polygenic component for AVSD in DS has not been examined previously. Using weights based on the largest genome-wide association study of congenital heart defects available (2594 cases and 5159 controls; all general population samples), we found PRS to be associated with AVSD with odds ratios ranging from 1.2 to 1.3 per standard deviation increase in PRS and corresponding liability r2 values of approximately 1%, suggesting at least a small polygenic contribution to DS-associated AVSD. Future studies with larger sample sizes will improve identification and quantification of genetic contributions to AVSD in DS.

Congenital heart defects associated with aneuploidy syndromes: New insights into familiar associations

The frequent occurrence of congenital heart defects (CHDs) in chromosome abnormality syndromes is well-known, and among aneuploidy syndromes, distinctive patterns have been delineated. We update the type and frequency of CHDs in the aneuploidy syndromes involving trisomy 13, 18, 21, and 22, and in several sex chromosome abnormalities (Turner syndrome, trisomy X, Klinefelter syndrome, 47,XYY, and 48,XXYY). We also discuss the impact of noninvasive prenatal screening (mainly, cell-free DNA analysis), critical CHD screening, and the growth of parental advocacy on their surgical management and natural history. We encourage clinicians to view the cardiac diagnosis as a "phenotype" which supplements the external dysmorphology examination. When detected prenatally, severe CHDs may influence decision-making, and postnatally, they are often the major determinants of survival. This review should be useful to geneticists, cardiologists, neonatologists, perinatal specialists, other pediatric specialists, and general pediatricians. As patients survive (and thrive) into adulthood, internists and related adult specialists will also need to be informed about their natural history and management.

Influence of allelic differences in Down syndrome

Both trisomic and non-trisomic genes may affect the incidence and severity of phenotypes associated with Down syndrome (DS). The importance of extra (trisomic) genetic material is emphasized in DS, with less emphasis to the allelic composition of candidate trisomic genes in defining the trisomic gene-phenotype relationship in DS. Allelic differences in non-trisomic genes have been shown to be important moderators of cardiac, leukemia, and developmental phenotypes associated with DS. Trisomic mouse models provide an in vivo genetic platform for examining the gene-phenotype relationship, including the influence of allelic variants, on DS-like phenotypes. DS mouse models have differing trisomic genetic makeup, and optimal development, viability and translational value of these mouse models may require a non-inbred genetic background with heterogeneity at many loci. Additionally, understanding the contribution of specific genes or regions to DS phenotypes often requires the utilization of genetically manipulated mice that may be established on a different inbred background than the trisomic mice. The impact of allelic differences of trisomic and background genes in human and model systems may offer insight into the variability in occurrence and severity of trisomic phenotypes.

Molecular mechanisms of congenital heart disease in down syndrome

Down syndrome (DS), as a typical genomic aneuploidy, is a common cause of various birth defects, among which is congenital heart disease (CHD). 40-60% neonates with DS have some kinds of CHD. However, the molecular pathogenic mechanisms of DS associated CHD are still not fully understood. This review summarizes available studies on DS associated CHD from seven aspects so as to provide a crucial and updated overview of what we known so far in this domain.

Relationships of Body Composition to Cardiac Structure and Function in Adolescents With Down Syndrome are Different than in Adolescents Without Down Syndrome

Median survival in Down syndrome (DS) is 60 years, but cardiovascular disease risk and its markers such as left ventricular mass (LVM) have received limited attention. In youth, LVM is typically scaled to height^2.7 as a surrogate for lean body mass (LBM), the strongest predictor of LVM, but whether this algorithm applies to DS, a condition which features short stature, is unknown. To examine the relationships of LVM and function with height, LBM, and moderate-to-vigorous physical activity(MVPA) in DS, DS youth aged 10-20 years, and age-, sex-, BMI-, race-matched nonDS controls underwent echocardiography for LVM, ejection fraction (EF), and left ventricular diastolic function (measured as E/E'); dual-energy X-ray absorptiometry (DXA)-measured LBM; accelerometry for MVPA. (DS vs. nonDS median [min-max]): DS had lower height (cm) (144.5 [116.7-170.3] vs. 163.3 [134.8-186.7]; p < 0.0001); LBM (kg) (33.48 [14.5-62.3] vs 41.8 [18.07-72.46], p < 0.0001); and LVM (g) (68.3 [32.1-135] vs 94.0 [43.9-164.6], p < 0.0001); similar EF (%) (65 [54-77] vs 64 [53-77], p = 0.59); and higher E/E' (8.41 [5.54-21.4] vs 5.81 [3.44-9.56], p < 0.0001). In height^2.7-adjusted models, LVM was lower in DS (β = - 7.7, p = 0.02). With adjustment for LBM, LVM was even lower in DS (β = - 15.1, p < 0.0001), a finding not explained by MVPA. E/E' remained higher in DS after adjustment for age, height, HR, SBP, and BMI (β = 2.6, p < 0.0001). DS was associated with stiffer left ventricles and lower LVM, the latter magnified with LBM adjustment. Scaling to height^2.7, the traditional approach for assessing LVM in youth, may underestimate LVM differences in DS. Whether lower LVM and diastolic function are intrinsic to DS, pathologic, or protective remains unknown.Clinical Trial Registration: NCT01821300.

Associations Between Medical History, Cognition, and Behavior in Youth With Down Syndrome: A Report From the Down Syndrome Cognition Project

The cause of the high degree of variability in cognition and behavior among individuals with Down syndrome (DS) is unknown. We hypothesized that birth defects requiring surgery in the first years of life (congenital heart defects and gastrointestinal defects) might affect an individual's level of function. We used data from the first 234 individuals, age 6-25 years, enrolled in the Down Syndrome Cognition Project (DSCP) to test this hypothesis. Data were drawn from medical records, parent interviews, and a cognitive and behavior assessment battery. Results did not support our hypothesis. That is, we found no evidence that either birth defect was associated with poorer outcomes, adjusting for gender, race/ethnicity, and socioeconomic status. Implications for study design and measurement are discussed.

Identifying Patients with Atrioventricular Septal Defect in Down Syndrome Populations by Using Self-Normalizing Neural Networks and Feature Selection

Atrioventricular septal defect (AVSD) is a clinically significant subtype of congenital heart disease (CHD) that severely influences the health of babies during birth and is associated with Down syndrome (DS). Thus, exploring the differences in functional genes in DS samples with and without AVSD is a critical way to investigate the complex association between AVSD and DS. In this study, we present a computational method to distinguish DS patients with AVSD from those without AVSD using the newly proposed self-normalizing neural network (SNN). First, each patient was encoded by using the copy number of probes on chromosome 21. The encoded features were ranked by the reliable Monte Carlo feature selection (MCFS) method to obtain a ranked feature list. Based on this feature list, we used a two-stage incremental feature selection to construct two series of feature subsets and applied SNNs to build classifiers to identify optimal features. Results show that 2737 optimal features were obtained, and the corresponding optimal SNN classifier constructed on optimal features yielded a Matthew’s correlation coefficient (MCC) value of 0.748. For comparison, random forest was also used to build classifiers and uncover optimal features. This method received an optimal MCC value of 0.582 when top 132 features were utilized. Finally, we analyzed some key features derived from the optimal features in SNNs found in literature support to further reveal their essential roles.

Analysis of Copy Number Variants on Chromosome 21 in Down Syndrome-Associated Congenital Heart Defects

One in five people with Down syndrome (DS) are born with an atrioventricular septal defect (AVSD), an incidence 2000 times higher than in the euploid population. The genetic loci that contribute to this risk are poorly understood. In this study, we tested two hypotheses: (1) individuals with DS carrying chromosome 21 copy number variants (CNVs) that interrupt exons may be protected from AVSD, because these CNVs return AVSD susceptibility loci back to disomy, and (2) individuals with DS carrying chromosome 21 genes spanned by microduplications are at greater risk for AVSD because these microduplications boost the dosage of AVSD susceptibility loci beyond a tolerable threshold. We tested 198 case individuals with DS+AVSD, and 211 control individuals with DS and a normal heart, using a custom microarray with dense probes tiled on chromosome 21 for array CGH (aCGH). We found that neither an individual chromosome 21 CNV nor any individual gene intersected by a CNV was associated with AVSD in DS. Burden analyses revealed that African American controls had more bases covered by rare deletions than did African American cases. Inversely, we found that Caucasian cases had more genes intersected by rare duplications than did Caucasian controls. We also showed that previously DS+AVSD (DS and a complete AVSD)-associated common CNVs on chromosome 21 failed to replicate. This research adds to the swell of evidence indicating that DS-associated AVSD is similarly heterogeneous, as is AVSD in the euploid population.

The Complex Genetic Basis of Congenital Heart Defects

Twenty years ago, chromosomal abnormalities were the only identifiable genetic causes of a small fraction of congenital heart defects (CHD). Today, a de novo or inherited genetic abnormality can be identified as pathogenic in one-third of cases. We refer to them here as monogenic causes, insofar as the genetic abnormality has a readily detectable, large effect. What explains the other two-thirds? This review considers a complex genetic basis. That is, a combination of genetic mutations or variants that individually may have little or no detectable effect contribute to the pathogenesis of a heart defect. Genes in the embryo that act directly in cardiac developmental pathways have received the most attention, but genes in the mother that establish the gestational milieu via pathways related to metabolism and aging also have an effect. A growing body of evidence highlights the pathogenic significance of genetic interactions in the embryo and maternal effects that have a genetic basis. The investigation of CHD as guided by a complex genetic model could help estimate risk more precisely and logically lead to a means of prevention.

Transgenerational cardiology: One way to a baby's heart is through the mother

Despite decades of progress, congenital heart disease remains a major cause of mortality and suffering in children and young adults. Prevention would be ideal, but formidable biological and technical hurdles face any intervention that seeks to target the main causes, genetic mutations in the embryo. Other factors, however, significantly modify the total risk in individuals who carry mutations. Investigation of these factors could lead to an alternative approach to prevention. To define the risk modifiers, our group has taken an "experimental epidemiologic" approach via inbred mouse strain crosses. The original intent was to map genes that modify an individual's risk of heart defects caused by an Nkx2-5 mutation. During the analysis of >2000 Nkx2-5(+/-) offspring from one cross we serendipitously discovered a maternal-age associated risk, which also exists in humans. Reciprocal ovarian transplants between young and old mothers indicate that the incidence of heart defects correlates with the age of the mother and not the oocyte, which implicates a maternal pathway as the basis of the risk. The quantitative risk varies between strain backgrounds, so maternal genetic polymorphisms determine the activity of a factor or factors in the pathway. Most strikingly, voluntary exercise by the mother mitigates the risk. Therefore, congenital heart disease can in principle be prevented by targeting a maternal pathway even if the embryo carries a causative mutation. Further mechanistic insight is necessary to develop an intervention that could be implemented on a broad scale, but the physiology of maternal-fetal interactions, aging, and exercise are notoriously complex and undefined. This suggests that an unbiased genetic approach would most efficiently lead to the relevant pathway. A genetic foundation would lay the groundwork for human studies and clinical trials.

Angiogenic Gene Expression in Down Syndrome Fetal Hearts

INTRODUCTION

Forty percent of Down syndrome (DS) fetuses have congenital heart defects (CHD). An abnormal angiogenic environment has been described in euploid fetuses with CHD. However, the underlying pathophysiologic pathway that contributes to CHD in DS remains unknown. The objective was to compare the expression of angiogenic factors and chronic hypoxia genes in heart tissue from DS and euploid fetuses with and without CHD.

METHODS

The gene expression profile was determined by real-time PCR quantification in heart tissue from 33 fetuses with DS, 23 euploid fetuses with CHD and 23 control fetuses.

RESULTS

Angiogenic factors mRNA expression was significantly increased in the DS group compared to the controls (soluble fms-like tyrosine kinase-1, 81%, p = 0.007; vascular endothelial growth factor A, 57%, p = 0.006, and placental growth factor, 32%, p = 0.0227). Significant increases in the transcript level of hypoxia-inducible factor-2α and heme oxygenase 1 were also observed in the DS group compared to the controls. The expression of angiogenic factors was similar in DS fetuses and CHD euploid fetuses with CHD.

CONCLUSION

Abnormal angiogenesis was detected in the hearts of DS fetuses with and without CHD. Our results suggest that DS determines an intrinsically angiogenic impairment that may be present in the fetal heart.

Genome-Wide Association Study of Down Syndrome-Associated Atrioventricular Septal Defects

The goal of this study was to identify the contribution of common genetic variants to Down syndrome−associated atrioventricular septal defect, a severe heart abnormality. Compared with the euploid population, infants with Down syndrome, or trisomy 21, have a 2000-fold increased risk of presenting with atrioventricular septal defects. The cause of this increased risk remains elusive. Here we present data from the largest heart study conducted to date on a trisomic background by using a carefully characterized collection of individuals from extreme ends of the phenotypic spectrum. We performed a genome-wide association study using logistic regression analysis on 452 individuals with Down syndrome, consisting of 210 cases with complete atrioventricular septal defects and 242 controls with structurally normal hearts. No individual variant achieved genome-wide significance. We identified four disomic regions (1p36.3, 5p15.31, 8q22.3, and 17q22) and two trisomic regions on chromosome 21 (around PDXK and KCNJ6 genes) that merit further investigation in large replication studies. Our data show that a few common genetic variants of large effect size (odds ratio >2.0) do not account for the elevated risk of Down syndrome−associated atrioventricular septal defects. Instead, multiple variants of low-to-moderate effect sizes may contribute to this elevated risk, highlighting the complex genetic architecture of atrioventricular septal defects even in the highly susceptible Down syndrome population.

Use of Affymetrix Arrays in the Diagnosis of Gene Copy-Number Variation

Diagnosing constitutional pathogenic copy number variants (CNVs) requires detecting submicroscopic segmental chromosomal imbalances. The Affymetrix GeneChip mapping array was one of the initial microarray platforms used to measure duplication and deletion of genetic material in DNA samples. Unlike oligonucleotide microarrays from NimbleGen and Agilent, developed around the same time to infer copy number status for the DNA sequence covered by the probe, the Affymetrix GeneChip system used 25-mer oligonucleotide probes designed to interrogate SNPs. Thus, it was possible to use the Affymetrix 'SNP chips' to both identify SNPs and to identify copy number status. Affymetrix now offers the CytoScan microarray platforms, which are optimized for copy-number analyses, and provides accompanying software. They also offer several other microarray platforms suitable for copy-number analyses. Here we discuss the application of the CytoScan high-density (HD) platform for the detection of genomic imbalance. We provide an overview of the sequence of computational analyses involved in identifying pathogenic CNVs and highlight important parameters for consideration in assessing the pathogenicity of a detected CNV.