Literature DB >> 23695279

Combined array CGH plus SNP genome analyses in a single assay for optimized clinical testing.

Joanna Wiszniewska1, Weimin Bi1, Chad Shaw1, Pawel Stankiewicz1, Sung-Hae L Kang2, Amber N Pursley1, Seema Lalani3, Patricia Hixson1, Tomasz Gambin4, Chun-hui Tsai5, Hans-Georg Bock6, Maria Descartes7, Frank J Probst3, Fernando Scaglia1, Arthur L Beaudet3, James R Lupski3, Christine Eng3, Sau Wai Cheung3, Carlos Bacino3, Ankita Patel1.   

Abstract

In clinical diagnostics, both array comparative genomic hybridization (array CGH) and single nucleotide polymorphism (SNP) genotyping have proven to be powerful genomic technologies utilized for the evaluation of developmental delay, multiple congenital anomalies, and neuropsychiatric disorders. Differences in the ability to resolve genomic changes between these arrays may constitute an implementation challenge for clinicians: which platform (SNP vs array CGH) might best detect the underlying genetic cause for the disease in the patient? While only SNP arrays enable the detection of copy number neutral regions of absence of heterozygosity (AOH), they have limited ability to detect single-exon copy number variants (CNVs) due to the distribution of SNPs across the genome. To provide comprehensive clinical testing for both CNVs and copy-neutral AOH, we enhanced our custom-designed high-resolution oligonucleotide array that has exon-targeted coverage of 1860 genes with 60,000 SNP probes, referred to as Chromosomal Microarray Analysis - Comprehensive (CMA-COMP). Of the 3240 cases evaluated by this array, clinically significant CNVs were detected in 445 cases including 21 cases with exonic events. In addition, 162 cases (5.0%) showed at least one AOH region >10 Mb. We demonstrate that even though this array has a lower density of SNP probes than other commercially available SNP arrays, it reliably detected AOH events >10 Mb as well as exonic CNVs beyond the detection limitations of SNP genotyping. Thus, combining SNP probes and exon-targeted array CGH into one platform provides clinically useful genetic screening in an efficient manner.

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Mesh:

Year:  2013        PMID: 23695279      PMCID: PMC3865406          DOI: 10.1038/ejhg.2013.77

Source DB:  PubMed          Journal:  Eur J Hum Genet        ISSN: 1018-4813            Impact factor:   4.246


Introduction

Variation in the human genome consists of two major types: (1) single nucleotide variation, in the form of DNA base-pair substitutions and short indels, and (2) structural variation affecting many base pairs, including inversions, translocations, insertions, deletions, and duplications resulting in copy number variation (CNV).[1] Advances in genome-wide analytical techniques, such as array comparative genomic hybridization (array CGH) and single nucleotide polymorphism (SNP) genotyping, can be used to detect CNVs. The number of identified CNVs has increased dramatically as the resolution of the detection technologies has improved.[2, 3, 4, 5, 6, 7] Rapidly, CNV detection has become an integral part of genetic studies of disease susceptibility, delineation of novel genomic disorders,[8, 9, 10] and analysis of data from genome-wide association studies.[11, 12] Both array CGH and SNP genotyping are routinely utilized by clinicians for the evaluation of patients with developmental delay (DD)/intellectual disability (ID), multiple congenital anomalies (MCA),[13] and neuropsychiatric disorders.[14] Genomic resolution by both array platforms (SNP and array CGH) used in clinical laboratories allows for the detection of genomic gains and losses of ∼400 kb in size.[15] Custom-designed oligonucleotide array CGH with greater resolution of the human genome, enabling detection of single-exon CNVs for clinically relevant genes, has also been implemented clinically.[16, 17] This approach increases diagnostic yield, but also increases the likelihood of detecting variants of uncertain clinical significance. While single-exon resolution throughout the genome is not feasible for SNP arrays, SNP arrays show higher sensitivity for the detection of low-level mosaic aneuploidies and chimerism[18] and offer the ability to detect copy number neutral regions of absence of heterozygosity (AOH).[19] Consanguinity can be revealed by AOH, because multiple regions of AOH are expected to be present in individuals from inbred populations, representing chromosomal segments that are identical by descent after transmission through parental lineages. The size and number of AOH blocks correlate with the degree of parental relatedness.[20] Researchers and clinicians are also using the location of homozygous regions for mapping information in consanguineous families to identify autosomal recessive disease-causing genes. When confined to a single chromosome, AOH regions may indicate uniparental disomy (UPD).[21, 22] Several mechanisms can lead to UPD, resulting in isodisomy if both transmitted homologs are identical, heterodisomy if both homologs from one parent are present or segmental isodisomy if part of the chromosome is isodisomic and the other part is heterodisomic.[23, 24] Although the true prevalence of UPD is not known, it is expected to be at least ∼1 in 3500 live births based upon information available in the ‘pre-genome analyses era'.[25] UPD is a well-known mechanism leading to human disease if a chromosome containing imprinted genes is involved or if a recessive disease-causing mutation is present.[25, 26] We now show that, by combining SNPs with our exon-targeted oligonucleotide array, detection for both copy number variation and copy-neutral AOH are optimized and enabled in a convenient, single genomic assay.

MATERIALS AND METHODS

Patients and sample preparation

A total of 3240 patient samples referred to the Medical Genetics Laboratory (http://www.bcm.edu/geneticlabs/) at Baylor College of Medicine from October 2010 to March 2012 were analyzed by the Chromosomal Microarray Analysis – Comprehensive (CMA-COMP) array. As an independent experimental SNP platform and quality assurance measure, 59 consecutive cases in which an AOH event (>10 Mb) was identified by the CMA-COMP array were also analyzed on an Illumina SNP array (Illumina Inc., San Diego, CA, USA). All studies were performed on patient DNA extracted from peripheral blood using the Puregene DNA blood kit (Gentra, Minneapolis, MN, USA) according to the manufacturer's instructions.

CMA-COMP

Microarray design

The custom-designed 400K CMA-COMP array used in this study was manufactured by Agilent Technologies, Inc. (Santa Clara, CA, USA), and contains ∼280 000 oligonucleotide probes targeting 1860 genes at the exon level of genome resolution (<500 bp), with an average backbone coverage of one probe per 30 kb, an improved design of a previously described version by Boone et al,[16] and 60 000 SNP probes in duplicate.

Analysis

DNA was digested with AluI and RsaI in order to allow detection of the SNPs located at the enzymes' recognition sites. The remaining procedures of DNA labeling and hybridization were performed according to the manufacturers' instructions, with minor modifications.[27] For detailed array analysis, see Supplementary I.

Reporting

CNVs were reported and classified into three categories: (1) abnormal, (2) unclear clinical significance, and (3) likely benign. Abnormal CNVs include aneuploidy, known microdeletion/duplication syndromes, genomic imbalances larger than 2 Mb, other known genomic disorders (eg, the 1.5-Mb CMT1A duplication) and copy number changes involving pathogenic single genes. In cases where a pathogenic CNV is identified that may be associated with a presymptomatic condition, we report these incidental findings to the referring physician in order to facilitate adequate counseling and prompt medical attention as needed,[28] consistent with current ACMG recommendations. CNVs of unclear clinical significance include those smaller than 2 Mb in size that have not been correlated with a clinical phenotype. CNVs are classified as likely benign if they are polymorphic in the normal population as determined by reviews of recent literature. Evaluation of potential medically actionable variants includes careful consideration of the size of the CNV, variant allele frequency, gene(s) involved, whether it represents a de novo or inherited event, and the reported phenotypic clinical findings in the child or other relevant family members.[29, 30] Additionally, AOH segments greater than 10 Mb in size were reported.

SNP genotyping platform

SNP array analysis was performed on the Illumina Infinium HD assay platform using HumanOmni1-Quad BeadChip (Illumina Inc.) with 200 ng of genomic DNA according to the manufacturer's instructions. The GenomeStudio software (Illumina, Inc.) was used for data processing and analysis. AOH regions larger than 10 Mb were used for comparison to the CMA-COMP results.

Results

Comparison of AOH calling by CMA-COMP and Illumina SNP array

Of the 3240 samples referred for the CMA-COMP array, 162 (5%) had at least one region of contiguous AOH larger than 10 Mb. A total of 59 consecutive cases with one or more AOH regions measuring >10 Mb in size as identified by the CMA-COMP array were also tested on the Illumina SNP array for quality control. Fifteen of these cases had interstitial, terminal, or centromeric AOH in single chromosomes (Table 1). The AOH regions were confirmed by the Illumina array in all 15 cases; however, the AOH calls in two cases were found to represent smaller-sized AOH regions by the higher-resolution Illumina SNP array. Twenty seven cases had AOH regions totaling 100 Mb or higher, which is suggestive of consanguinity. Such high levels of AOH were confirmed by the Illumina array for all these cases (Table 2). Therefore, the CMA-COMP platform, even though it has a lower density of SNP probes than the Illumina array, was able to reliably detect AOH events >10 Mb.
Table 1

Comparison of the results of CMA-COMP and Illumina array for AOH regions greater than 10 Mb in size and limited to single chromosomes

 CMA-COMP arrayIllumina SNP array  
ChromosomeGenomic intervalSize in MbGenomic intervalSize in MbLocationUPD confirmed
1166 983 908–183 983 60717.0167 228 031–183 982 10016.7Interstitial
338 493 212–52 622 08614.145 790 685–52 193 6856.4Interstitial
345 708 410–59 299 26613.647 077 306–53 281 955a6.2Interstitial
597 151 690–123 037 28825.9106 422 150–123 740 80217.3Interstitial
5163 685 643–178 577 21814.9163 735 878–176 745 70713.0Interstitial
5125 870 653–146 253 19920.4127 465 300–146 414 99318.9Interstitial
7107 850 309–120 523 87312.7109 017 420–120 492 48211.5Interstitial
835 551 788–61 354 16725.837 132 731–63 207 08926.1Centromeric
94 175 231–14 383 18310.21 486 230–14 377 81712.9InterstitialUPD
 88 061 835–128 350 61240.366 587 429–126 250 36259.7Interstitial
121–22 919 01522.91 607 841–22 154 16220.5Terminal
1435 601 054–50 516 08714.935 958 318–50 563 15414.6InterstitialNo UPD
1433 803 584–70 306 50436.533 742 889–70 200 05936.4InterstitialNo UPD
1432 945 633–94 103 81261.232 899 071–86 182 37453.3Interstitial
1521 317 493–68 226 07346.926 998 850–68 211 80141.2InterstitialUPD
X95 140 723–119 474 58424.395 721 890–11937854123.6Interstitial

Small non-contiguous segments of AOH were seen within the same AOH interval identified by the CMA-COMP.

Table 2

Comparison of the results of CMA-COMP and Illumina array for detection of AOH regions totaling 100 Mb or higher in size

 CMA-COMP arrayIllumina array
PatientsAOH level (Mb)Number of chromosomes involvedNumber of blocksAOH level (Mb)
Case 18711518851
Case 28632025787
Case 37071623702
Case 46781820681
Case 56541416609
Case 65141014529
Case 75011014506
Case 835288354
Case 9345811367
Case 1033279310
Case 11289910247
Case 1227688244
Case 1327089240
Case 1425289245
Case 1523456147
Case 1622388228
Case 1719455127
Case 1818777150
Case 1917767158
Case 2015867152
Case 2114166138
Case 2213867130
Case 2312957117
Case 241223490
Case 2511844107
Case 2611033108
Case 271075596

Uniparental disomy

Two cases were identified by CMA-COMP with AOH in a single chromosome within which all interrogated SNPs were homozygous, indicating the presence of uniparental isodisomy. One case showed isodisomy 1 and the other isodisomy 16. Maternal UPD16 has been associated with intrauterine growth restriction and fetal malformations.[31] Additionally, 45 cases analyzed by CMA-COMP showed AOH regions exceeding 10 Mb involving one chromosome only, indicating possible uniparental heterodisomy for that particular chromosome. Twelve of these cases involved chromosomes that contain imprinted regions associated with a clinical phenotype [chromosomes 7 (three cases), 14 (seven cases), and 15 (two cases)]. Methylation-specific PCR was performed on two (Figures 1a and b) of the seven cases with AOH limited to chromosome 14; in both cases, there was no evidence of UPD. The B allele frequency plot for a case with AOH of ∼61 Mb on chromosome 14 is shown in Figure 1c. Unfortunately, this case was lost to follow-up, so UPD could not be confirmed. For one case involving AOH on chromosome 15, an interstitial duplication of 15q11.2q13.1 and maternal uniparental trisomy was detected, genomic findings which are all consistent with a diagnosis of Prader–Willi syndrome. A detailed description of this clinical case is described elsewhere.[32] All other remaining cases with AOH on imprinted chromosomes were lost to follow-up.
Figure 1

Large regions of AOH limited to single chromosomes suggestive of heterodisomy. Top panels – CMA-COMP SNP data. Bottom panels – corresponding Illumina B allele frequency data. (a–c) Chromosome 14. Follow-up studies by methylation specific PCR showed presence of both maternal and paternal bands, indicating biparental chromosome 14 inheritance for cases shown in panels (a) and (b). Methylation studies were not available for the case shown in panel (c). (d) Chromosome 9. Follow-up parental SNP array analyses confirmed presence of maternal heterodisomy in this patient.

Of interest, one case had multiple AOH regions limited to chromosome 9 (Figure 2), which was confirmed by the Illumina SNP array. Analysis of the proband and parental genotypes indicated the presence of maternal heterodisomy 9.
Figure 2

CMA-COMP array showing a patient with consanguinity as demonstrated by the multiple blocks of AOH (shaded) on numerous chromosomes.

Consanguinity

Multiple AOH regions >10 Mb involving two or more chromosomes were identified in 115 cases by CMA-COMP, of which 44 cases were also performed on the Illumina SNP array. As shown in Table 2, the AOH calls between the two arrays are comparable in the 27 cases with AOH regions totaling ≥100 Mb. For cases in which the degree of parental relatedness was provided by the referring center (Table 3), we compared the total length of AOH regions to that which is expected from the coefficient of inbreeding (F). Patients whose parents are first cousins (third degree of relationship) are expected to have 1/16 of their genome homozygous or ∼179 Mb of total AOH regions. The total length of AOH regions observed was 225 Mb as shown in case 2. Consistent data were also observed in cases of fourth and sixth degree of parental relationship [expected 90 Mb and observed 89 and 82 for fourth degree (cases 3 and 4), and expected 22.5 Mb and observed 58 for sixth degree (case 5)].
Table 3

Extent of AOH regions detected in patients from known consanguineous families

 CMA-COMP array  
PatientsAOH level (Mb)Number of chromosomes involvedNumber of blocksParental relationshipExpected AOH
Case 1a7071623First-degree relatives716 Mb (F=1/4)
Case 2225910First cousins179 Mb (F=1/16)
Case 38944First cousins once removed90 Mb (F=1/32)
Case 48233First cousins once removed90 Mb (F=1/32)
Case 55833Second cousins once removed22.5 Mb (F=1/128)

Same as case 3 in Table 2.

Notably, our analyses identified 10 cases in which the observed total length of AOH regions was consistent with that expected for a first degree relationship (F=1/4 or ∼716 Mb). In those cases, the total length of AOH ranged from ∼506 Mb to 851 Mb, with a mean of 677 Mb. Amongst this group of subjects, consanguinity was confirmed in two patients, one of which was known to be the product of a sister–brother mating (Table 3, case 1).

Autosomal recessive disorders and AOH

We evaluated regions of AOH for gene content when the indication was a specific disease. In four patients with an autosomal recessive disorder, the associated gene localized within one of the AOH regions. Sequencing analysis performed elsewhere confirmed the presence of a homozygous mutation in two patients (Table 4).
Table 4

Correlation of AOH regions with autosomal recessive disorders

AR disorderGenes related to diagnosisTotal AOH >10 MbGene within AOH blockAOH size (Mb)Comment
Cohen syndromeVSP13B29VSP13B11Homozygous exonic deletion detected
HHH syndromeSLC25A15270SLC25A1540Homozygous mutation in SLC25A15 detected
SCID18 genes332CD3D8Homozygous mutation in CD3D detected
Usher syndromeDozens of genes214USH2A18 
One patient, the product of a consanguineous mating (second cousins once removed), presented with DD/ID and microcephaly, and MRI revealing a mild diffuse reduction in the volume of the cerebral hemispheric white matter with a borderline to increased size of the corpus callosum. CMA-COMP analysis showed AOH events larger than 10 Mb on chromosomes 8 and 14. The AOH event on chromosome 8 also harbored a homozygous deletion of ∼52 kb involving exons 4–14 of the VPS13B (vacuolar protein sorting 13 homolog B) gene (Figures 3a and b), which is associated with Cohen syndrome (OMIM #216550) and consistent with the clinical phenotype of this patient.
Figure 3

(a) A ∼52-kb homozygous deletion involving exons 4–14 of the VSP13B gene in a patient with Cohen syndrome detected by CMA-COMP array. (b) shows the SNP data plot with an AOH region on chromosome 8, wherein the VSP13B gene is located. (c) and (d) Comparison of the probe distribution between the exon-targeted CMA-COMP array and two other commercial SNP arrays for the portion of the VSP13B gene deleted in cases 6 and 7 (Table 4) (c) Case 6 (same case as in (a)) with a deletion of exons 4–14 (red dots represent the deleted oligos in the exons). Note that the locations of the SNPs (black dots) are outside of almost all of the exons, and therefore single exon deletions would not be detectable by these SNP arrays. (d) Case 7 in Table 4 – red dots represent the deleted oligonucleotides corresponding to exons 22–25 (represented by the hatch marks at the bottom of the figure) as detected by the CMA-COMP array. The black dots represent the SNP distribution within the same region. Again, note that most SNP probes are located within introns.

Intragenic CNVs

An advantage of the CMA-COMP array platform is its ability to detect very small, single-exon copy number changes. Pathogenic genomic deletions and/or duplications were detected in 14% (445/3240) of the cases. CNVs of unclear clinical significance were detected in an additional 13% (421/3240). Intragenic pathogenic CNVs were detected in 21 cases (Table 5) with an average of 21 probes (range 4–90). The smallest CNV was confirmed by sequencing to be 500 bp. A comparison of the distribution of the probes of the CMA-COMP to two commercial SNP arrays for the intragenic deletions involving exons of the VPS13B gene (Table 5, cases 6 and 7) is provided in Figures 3c and d. In addition to the VPS13B gene, intragenic deletions of both NRXN1 and DMD were detected in multiple patients as well as two cases involving genes that predispose to cancer.
Table 5

Pathogenic exonic CNVs detected by CMA-COMP array

CaseGeneDisease associationExon(s)Copy number changeChromosome LocationInheritanceGender
1NRXN1Autism and developmental disorders23Loss2p16.3UnknownF
2NRXN1Autism and developmental disorders3–5Loss2p16.3PaternalM
3NRXN1Autism and developmental disorders4–5Loss2p16.3UnknownM
4MSH6Hereditary nonpolyposis colorectal cancer5–6Loss2p16.3UnknownF
5TGFB1Corneal dystrophy8–10Loss5q31.1UnknownF
6VPS13BCohen syndrome4–14Homozygous loss8q22.2UnknownF
7VPS13BCohen syndrome22–25Loss8q22.2UnknownM
8BRCA2Increased risk of cancer13–14Loss13q13.1UnknownM
9UBE3AAngelman syndrome7–14Loss15q11.2MaternalF
10CHRNA7Intellectual disability and seizuresEntire geneLoss15q13.3UnknownF
11ANKRD11KBG syndrome4–13Loss16q24.3UnknownF
12ANKRD11KBG syndrome2–3Loss16q24.3UnknownF
13HNF1BPolycystic kidney disease, genital malformations, pancreatic atrophy and maturity-onset diabetes of the young type 57–8Loss17q12UnknownM
14DMDDuchenne muscular dystrophy15GainXp21.1UnknownM
15DMDDuchenne muscular dystrophy40–50LossXp21.1UnknownM
16DMDDuchenne muscular dystrophy63–64GainXp21.1UnknownM
17DMDDuchenne muscular dystrophy49–51LossXp21.1MaternalM
18MED12FG syndrome and Lujan–Fryns syndrome25–28GainXq13.1De novoM
19GPC3Simpson–Golabi–Behmel syndrome7GainXq26.2UnknownM
20FMR1X-linked intellectual disabilityEntire geneGainXq27.3UnknownM
21L1CAMX-linked hydrocephalus1–2LossXq28UnknownM

Discussion

With the addition of SNP probes to our exon coverage array, we provide a comprehensive approach for the identification of clinically relevant copy number neutral changes in addition to medically actionable CNVs in a single assay. The principles used to guide this unique array design were to: (1) empirically select the best performing probes to maximize detection and signal to noise ratio, (2) detect CNVs known to be associated with diseases and target coverage of the exons of these known disease genes, (3) maintain 30 kb backbone coverage, and (4) exclude most of the known LCR regions. The rationale for our array design to maximize detection of clinically relevant genomic changes has been independently validated by the observations of Haraksingh et al.[33] They compared the CNVs observed in the 1000 Genomes Project with all the currently commercially available high-resolution array platforms and concluded that the sensitivity, total number, size range, and breakpoint resolution of CNV calls were highest for CNV focused arrays that did not compromise the backbone tiling density of the rest of the genome. They also found that probe distribution greatly affected the performance of a platform. A disadvantage for SNP-only arrays is that the probe distribution is restricted by the non-uniform availability of informative SNPs throughout the genome. Additionally, probes that are optimized will provide maximum information for specific loci. In this study, the CMA-COMP array, with only 60 000 SNP probes, was concordant with a high-density SNP array in detecting AOH events and is thus an excellent tool for genome-wide screening for AOH in order to identify UPD, consanguinity, and map genomic intervals containing potential recessive loci. The percent of the genome manifesting AOH for each case was calculated for both platforms (data not shown) and there was complete concordance between the two platforms within 1–2%. Because of the lower density of SNP probes in the CMA-COMP array, there may be an overestimation of the genomic size of an AOH event, which occurred in two cases in Table 1. In one of these cases, the Illumina array revealed a smaller AOH (6 Mb) event, and in the other case, a series of smaller discrete AOH events interrupted by small regions of heterodisomy were seen in the Illumina array. The CMA-COMP did not resolve the discrete interval events; instead it showed a contiguous AOH event for this region. As both of these cases involved a non-imprinted chromosome, further studies were not recommended. Added value to the genomic analysis provided by SNP probes is the detection of uniparental isodisomy without requiring analysis of parental samples, as it is with other conventional assays that utilize STR markers. In addition, UPD of virtually any chromosome can be detected in one assay. While SNP arrays will detect virtually 100% of isodisomies,[24] not all cases of uniparental heterodisomy may be detected by SNP arrays unless a heterodisomic chromosome underwent a recombination event during meiosis, resulting in isodisomy interrupted by regions of heterozygosity, reflecting the presence of heterodisomy (hetero-isoUPD). In such cases, heterodisomy appears as a large block of AOH (isodisomic segment) confined to a single chromosome. Recently, Papenhausen et al[22] found that their cohort of nine confirmed UPD cases all showed an AOH block within the affected chromosome. Similar findings were also observed in five confirmed UPD cases and an additional three were consistent with the phenotype by Bruno et al.[34] However, not all AOH regions confined to a single chromosome indicate the presence of heterodisomy, as shown in our patients with AOH on chromosome 14. Similar observations were reported by Papenhausen et al,[22] who showed that only 29 out of 46 cases with a single segmental AOH event were confirmed to be UPD. Therefore, a single region of AOH could be a random finding representing a region of identity by descent or linkage disequilibrium (LD) because of a low recombination rate. Detection of isodisomy has obvious clinical relevance for cases in which chromosomes bearing imprinted genomic regions are involved, but it is also relevant in the context of autosomal recessive (AR) disorders. Most of the non-imprinted UPD cases described so far were ascertained by detection of a homozygous mutation in autosomal recessive genes that did not follow the expected Mendelian allele transmission pattern.[26] From a genetic counseling perspective, detection of isodisomy or hetero-isoUPD modifies recurrence risk for AR disease from 25% to <1%. The importance of parental follow-up studies to confirm carrier status in cases in which a homozygous mutation was detected in the child cannot be underemphasized. The identification of AOH has been previously employed for the determination of the genetic defects underlying genetically heterogeneous recessive disorders by a homozygosity mapping approach in a research setting. AOH regions determined by genome-wide SNPs analysis allows delineation of the critical disease-associated genomic interval and the number of potential candidate genes. Analysis of SNP data obtained for both affected and unaffected individuals enables further refinement of AOH regions and subsequent identification of candidate genes. Implementation of SNP arrays in clinical diagnostics allows the clinician to take advantage of this approach in their daily practice, especially because these data could be combined with clinically available whole-exome sequencing approaches. Clinicians can also utilize SNP genotyping information to devise a cost-effective strategy for determining the molecular etiology of genetically heterogeneous autosomal recessive diseases (e.g., deafness, retinitis pigmentosa, etc) by targeting sequence analysis for a suspected disease gene if it is located in an AOH block. Such was the case for the patients identified with SCID and Usher syndrome (Table 4). The CMA-COMP array also has the advantage of detecting intragenic copy number changes. While intragenic deletions and duplications are known to account for a significant portion of disease-causing mutations for genes such as DMD, only more recently with the implementation of array CGH are intragenic deletions and duplications being detected for many other genes. Examples of haploinsufficient, intragenic deletions and the molecular mechanism and possible consequences of these intragenic CNVs have been previously reported.[4, 12, 13, 16, 35, 36] Detection of intragenic copy number changes also has a role in the diagnosis of autosomal recessive disease, as demonstrated by the case with an intragenic heterozygous deletion of the VPS13B gene (case 7 in Table 4), which is associated with Cohen syndrome. Consistently, deletions have been reported as an important cause of Cohen syndrome.[37] Interestingly, genotype–phenotype correlations are being described for deletions occurring at different locations within a gene. For example, the more C-terminal deletions, such as case 1 (Table 5), including those affecting the beta isoform of Neurexin-1, present with an increased head size and a high frequency of epilepsy (88%) when compared with more N-terminal deletions of NRXN1, as seen in cases 2 and 3 (Table 5). Therefore, increasingly specific genotype–phenotype predictions are becoming available to assist with the genetic counseling of the copy number changes identified by array studies.[28, 35] However, genetic counseling can also become complicated by incidental findings, such as the intragenic deletions within MSH6 in case 4 and BRCA2 in case 8 (Table 5), which confers an increased life-time susceptibility to cancer in a 13-year-old female and a 10-year-old male, respectively. These findings require careful counseling to address prognosis and surveillance. These findings also have obvious implications for other family members that may also have inherited the CNV. While unexpected, these findings can have a profound impact on optimizing medical management and prevention for the whole family. As intragenic deletions of these genes have been observed,[36, 38] it is expected that incidental findings such as these will occur as arrays with targeted exonic coverage are increasingly used in clinical practice. In conclusion, combining both array CGH and SNP genotyping in a single platform optimizes the clinical diagnostic capability by offering the simultaneous detection of copy number neutral changes and small intragenic copy number changes.
  38 in total

1.  Clan genomics and the complex architecture of human disease.

Authors:  James R Lupski; John W Belmont; Eric Boerwinkle; Richard A Gibbs
Journal:  Cell       Date:  2011-09-30       Impact factor: 41.582

Review 2.  Use of array CGH in the evaluation of dysmorphology, malformations, developmental delay, and idiopathic mental retardation.

Authors:  Pawel Stankiewicz; Arthur L Beaudet
Journal:  Curr Opin Genet Dev       Date:  2007-04-30       Impact factor: 5.578

3.  Pathogenic aberrations revealed exclusively by single nucleotide polymorphism (SNP) genotyping data in 5000 samples tested by molecular karyotyping.

Authors:  D L Bruno; S M White; D Ganesamoorthy; T Burgess; K Butler; S Corrie; D Francis; L Hills; K Prabhakara; C Ngo; F Norris; R Oertel; M D Pertile; Z Stark; D J Amor; H R Slater
Journal:  J Med Genet       Date:  2011-10-29       Impact factor: 6.318

4.  Phenotypic spectrum and genotype-phenotype correlations of NRXN1 exon deletions.

Authors:  Christian P Schaaf; Philip M Boone; Srirangan Sampath; Charles Williams; Patricia I Bader; Jennifer M Mueller; Oleg A Shchelochkov; Chester W Brown; Heather P Crawford; James A Phalen; Nicole R Tartaglia; Patricia Evans; William M Campbell; Anne Chun-Hui Tsai; Lea Parsley; Stephanie W Grayson; Angela Scheuerle; Carol D Luzzi; Sandra K Thomas; Patricia A Eng; Sung-Hae L Kang; Ankita Patel; Pawel Stankiewicz; Sau W Cheung
Journal:  Eur J Hum Genet       Date:  2012-05-23       Impact factor: 4.246

Review 5.  Consensus statement: chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies.

Authors:  David T Miller; Margaret P Adam; Swaroop Aradhya; Leslie G Biesecker; Arthur R Brothman; Nigel P Carter; Deanna M Church; John A Crolla; Evan E Eichler; Charles J Epstein; W Andrew Faucett; Lars Feuk; Jan M Friedman; Ada Hamosh; Laird Jackson; Erin B Kaminsky; Klaas Kok; Ian D Krantz; Robert M Kuhn; Charles Lee; James M Ostell; Carla Rosenberg; Stephen W Scherer; Nancy B Spinner; Dimitri J Stavropoulos; James H Tepperberg; Erik C Thorland; Joris R Vermeesch; Darrel J Waggoner; Michael S Watson; Christa Lese Martin; David H Ledbetter
Journal:  Am J Hum Genet       Date:  2010-05-14       Impact factor: 11.025

6.  Exon deletions of the EP300 and CREBBP genes in two children with Rubinstein-Taybi syndrome detected by aCGH.

Authors:  Anne Chun-Hui Tsai; Cherilyn J Dossett; Carol S Walton; Andrea E Cramer; Patti A Eng; Beata A Nowakowska; Amber N Pursley; Pawel Stankiewicz; Joanna Wiszniewska; Sau Wai Cheung
Journal:  Eur J Hum Genet       Date:  2010-08-18       Impact factor: 4.246

7.  American College of Medical Genetics standards and guidelines for interpretation and reporting of postnatal constitutional copy number variants.

Authors:  Hutton M Kearney; Erik C Thorland; Kerry K Brown; Fabiola Quintero-Rivera; Sarah T South
Journal:  Genet Med       Date:  2011-07       Impact factor: 8.822

8.  Alu-specific microhomology-mediated deletion of the final exon of SPAST in three unrelated subjects with hereditary spastic paraplegia.

Authors:  Philip M Boone; Pengfei Liu; Feng Zhang; Claudia M B Carvalho; Charles F Towne; Sat Dev Batish; James R Lupski
Journal:  Genet Med       Date:  2011-06       Impact factor: 8.822

9.  Mechanisms of mosaicism, chimerism and uniparental disomy identified by single nucleotide polymorphism array analysis.

Authors:  Laura K Conlin; Brian D Thiel; Carsten G Bonnemann; Livija Medne; Linda M Ernst; Elaine H Zackai; Matthew A Deardorff; Ian D Krantz; Hakon Hakonarson; Nancy B Spinner
Journal:  Hum Mol Genet       Date:  2010-01-06       Impact factor: 6.150

Review 10.  Complex and segmental uniparental disomy updated.

Authors:  D Kotzot
Journal:  J Med Genet       Date:  2008-06-04       Impact factor: 6.318

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  58 in total

Review 1.  The genetic basis of disease.

Authors:  Maria Jackson; Leah Marks; Gerhard H W May; Joanna B Wilson
Journal:  Essays Biochem       Date:  2018-12-02       Impact factor: 8.000

Review 2.  Chromosomal Microarrays: Understanding Genetics of Neurodevelopmental Disorders and Congenital Anomalies.

Authors:  Jill A Rosenfeld; Ankita Patel
Journal:  J Pediatr Genet       Date:  2016-05-30

3.  Neurodevelopmental and neurobehavioral characteristics in males and females with CDKL5 duplications.

Authors:  Przemyslaw Szafranski; Sailaja Golla; Weihong Jin; Ping Fang; Patricia Hixson; Reuben Matalon; Daniel Kinney; Hans-Georg Bock; William Craigen; Janice L Smith; Weimin Bi; Ankita Patel; Sau Wai Cheung; Carlos A Bacino; Paweł Stankiewicz
Journal:  Eur J Hum Genet       Date:  2014-10-15       Impact factor: 4.246

4.  Truncating biallelic variant in DNAJA1, encoding the co-chaperone Hsp40, is associated with intellectual disability and seizures.

Authors:  Saud Alsahli; Ahmed Alfares; Francisco J Guzmán-Vega; Stefan T Arold; Duaa Ba-Armah; Fuad Al Mutairi
Journal:  Neurogenetics       Date:  2019-04-10       Impact factor: 2.660

Review 5.  Clinical genomics: from a truly personal genome viewpoint.

Authors:  James R Lupski
Journal:  Hum Genet       Date:  2016-05-25       Impact factor: 4.132

6.  Haploinsufficiency of the Chromatin Remodeler BPTF Causes Syndromic Developmental and Speech Delay, Postnatal Microcephaly, and Dysmorphic Features.

Authors:  Paweł Stankiewicz; Tahir N Khan; Przemyslaw Szafranski; Leah Slattery; Haley Streff; Francesco Vetrini; Jonathan A Bernstein; Chester W Brown; Jill A Rosenfeld; Surya Rednam; Sarah Scollon; Katie L Bergstrom; Donald W Parsons; Sharon E Plon; Marta W Vieira; Caio R D C Quaio; Wagner A R Baratela; Johanna C Acosta Guio; Ruth Armstrong; Sarju G Mehta; Patrick Rump; Rolph Pfundt; Raymond Lewandowski; Erica M Fernandes; Deepali N Shinde; Sha Tang; Juliane Hoyer; Christiane Zweier; André Reis; Carlos A Bacino; Rui Xiao; Amy M Breman; Janice L Smith; Nicholas Katsanis; Bret Bostwick; Bernt Popp; Erica E Davis; Yaping Yang
Journal:  Am J Hum Genet       Date:  2017-09-21       Impact factor: 11.025

Review 7.  Structural variation mutagenesis of the human genome: Impact on disease and evolution.

Authors:  James R Lupski
Journal:  Environ Mol Mutagen       Date:  2015-04-17       Impact factor: 3.216

8.  De Novo Disruption of the Proteasome Regulatory Subunit PSMD12 Causes a Syndromic Neurodevelopmental Disorder.

Authors:  Sébastien Küry; Thomas Besnard; Frédéric Ebstein; Tahir N Khan; Tomasz Gambin; Jessica Douglas; Carlos A Bacino; William J Craigen; Stephan J Sanders; Andrea Lehmann; Xénia Latypova; Kamal Khan; Mathilde Pacault; Stephanie Sacharow; Kimberly Glaser; Eric Bieth; Laurence Perrin-Sabourin; Marie-Line Jacquemont; Megan T Cho; Elizabeth Roeder; Anne-Sophie Denommé-Pichon; Kristin G Monaghan; Bo Yuan; Fan Xia; Sylvain Simon; Dominique Bonneau; Philippe Parent; Brigitte Gilbert-Dussardier; Sylvie Odent; Annick Toutain; Laurent Pasquier; Deborah Barbouth; Chad A Shaw; Ankita Patel; Janice L Smith; Weimin Bi; Sébastien Schmitt; Wallid Deb; Mathilde Nizon; Sandra Mercier; Marie Vincent; Caroline Rooryck; Valérie Malan; Ignacio Briceño; Alberto Gómez; Kimberly M Nugent; James B Gibson; Benjamin Cogné; James R Lupski; Holly A F Stessman; Evan E Eichler; Kyle Retterer; Yaping Yang; Richard Redon; Nicholas Katsanis; Jill A Rosenfeld; Peter-Michael Kloetzel; Christelle Golzio; Stéphane Bézieau; Paweł Stankiewicz; Bertrand Isidor
Journal:  Am J Hum Genet       Date:  2017-01-26       Impact factor: 11.025

9.  Copy number variant analysis using genome-wide mate-pair sequencing.

Authors:  James B Smadbeck; Sarah H Johnson; Stephanie A Smoley; Athanasios Gaitatzes; Travis M Drucker; Roman M Zenka; Farhad Kosari; Stephen J Murphy; Nicole Hoppman; Umut Aypar; William R Sukov; Robert B Jenkins; Hutton M Kearney; Andrew L Feldman; George Vasmatzis
Journal:  Genes Chromosomes Cancer       Date:  2018-07-30       Impact factor: 5.006

Review 10.  A challenge to the striking genotypic heterogeneity of retinitis pigmentosa: a better understanding of the pathophysiology using the newest genetic strategies.

Authors:  F S Sorrentino; C E Gallenga; C Bonifazzi; P Perri
Journal:  Eye (Lond)       Date:  2016-08-26       Impact factor: 3.775

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