Coverage Policy Manual
Policy #: 2010014
Category: Laboratory
Initiated: August 2017
Last Review: December 2023
  Genetic Test: Genetic Testing for Evaluation of Patients with Developmental Delay/Intellectual Disability or Autism

Description:
Chromosomal microarray (CMA) testing has been proposed for the detection of genetic imbalances in infants or children with characteristics of developmental delay/intellectual disability, autism spectrum disorder, and/or congenital anomalies. CMA testing increases the diagnostic yield over karyotyping in children with the aforementioned characteristics, and CMA testing may impact clinical management decisions. Next-generation sequencing panel testing allows for the simultaneous analysis of a large number of genes and, in patients with normal CMA testing, the next-generation testing has been proposed as a way to identify single-gene causes of syndromes that have autism as a significant clinical feature.
 
The goal of a cytogenetic evaluation is to identify chromosomal imbalances that cause a disorder. The most common imbalances are copy number variants (CNVs) or deletions and duplications of large segments of genomic material. CNVs are common in developmental delay /intellectual disability and autism spectrum disorder (ASD) but more often reflect the normal genetic variation (Mikhail, 2011). However, de novo CNVs are observed about 4 times more frequently in children with ASD than in normal individuals (Brandler, 2015). Less frequently, other abnormalities such as balanced translocations (ie, exchanges of equally sized DNA loci between chromosomes) may be pathogenic. For many well-described syndromes, the type and location of the associated chromosomal abnormality have been established by studying large patient samples. For others, few patients with similar abnormalities may have been evaluated to establish genotype-phenotype correlation. Finally, in some patients, the cytogenetic analysis will discover chromosomal abnormalities that require study to determine their significance.
 
Prior to the advent of chromosomal microarray (CMAs), the initial step in the cytogenetic analysis was G-banded karyotyping, which evaluates all chromosomes. High-resolution G-banding can detect changes as small as 3 to 5 megabases in size, although standard G-banding evaluates more than 10 megabases changes. In children with developmental delay/intellectual disability, a review by Stankiewicz and Beaudet found G-banded karyotyping diagnostic in approximately 3% to 5% of cases (Stankiewicz, 2007). In ASD, high-resolution karyotyping appears to identify abnormalities in up to 5% of cases (Stuart, 2007).
 
In contrast, molecular cytogenetic techniques can detect small submicroscopic chromosomal alterations. Fluorescent in situ hybridization (FISH), a targeted approach, is used to identify specific chromosomal abnormalities associated with suspected diagnoses such as DiGeorge syndrome. Prior to CMAs, FISH was also used to screen the rearrangement-prone subtelomeric regions. Subtelomeric FISH was found to identify abnormalities in children with developmental delay and intellectual disability, and was diagnostic in approximately 5% to 6% of those with negative karyotypes, but uncommonly in ASD (Moeschler, 2008; Schaefer, 2008).
 
Chromosomal Microarrays
Two types of CMAs are considered here: array comparative genomic hybridization (aCGH) and single nucleotide variants (SNV) arrays. The aCGH approach uses DNA samples from a patient and normal control. Each is labeled with distinct fluorescent dyes (red or green). The labeled samples are then mixed and hybridized to thousands of cloned or synthesized reference (normal) DNA fragments of known genomic locus immobilized on a glass slide (microarray) to conduct thousands of comparative reactions simultaneously. CNVs are determined by computer analysis of the array patterns and intensities of the hybridization signals. If the patient sequence is missing part of the normal sequence (a deletion) or has the normal sequence plus additional genomic material within that genomic location (eg, a duplication), the sequence imbalance is detected as a difference in fluorescence intensity. For this reason, aCGH cannot detect balanced chromosomal translations (equal exchange of material between chromosomes) or sequence inversions (same sequence is present in reverse base-pair order) because the fluorescence intensity would not change. A portion of the increased diagnostic yield from CMA over karyotyping comes from the discovery that chromosomal rearrangements that appear balanced (and therefore not pathogenic) by G-banded karyotype analysis are found to have small imbalances with greater resolution. It has been estimated that 40% of apparently balanced de novo or inherited translocations with abnormal phenotype are associated with cryptic deletion if analyzed by CMA testing.
 
Like aCGH, SNV arrays detect CNVs. In an SNV array, the 2 alleles for genes of interest are tagged with different fluorescent dyes. Comparative fluorescence intensity will be increased when there are duplications and diminished with deletions. The resolution provided by aCGH is higher than with SNV arrays. In addition, aCGH has better signal-to-background characteristics than SNV arrays. In contrast to aCGH, SNV arrays will also identify long stretches of DNA homozygosity, which may suggest uniparental disomy or consanguinity. Uniparental disomy occurs when a child inherits 2 copies of a chromosome from 1 parent and no copies from the other parent. Uniparental disomy can lead to syndromes such as Angelman and Prader-Willi.
 
Below is a summary of the cytogenetic tests used to evaluate children with developmental delay/intellectual disability and autism. It emphasizes the large difference in resolution between karyotyping and CMA.
 
    • Karyotyping has a resolution of 3000-5000 kb and Genome-wide analysis
    • CMA has a resolution of 50 kb and Genome-wide analysis
    • FISH has a resolution of 500 to 1000 kb (depending on probe) and Targeted analysis
 
Microarrays may be prepared by the laboratory using the technology or, more commonly, by commercial manufacturers, and sold to laboratories that must qualify and validate the product for use in their assay, in conjunction with computerized software for interpretation. The proliferation of laboratory-developed and commercially available platforms prompted the American College of Medical Genetics to publish guidelines for the design and performance expectations for clinical microarrays and associated software in the postnatal setting (Kearney, 2011).
 
Next-Generation Sequencing
Next-generation sequencing has been proposed to detect single-gene causes of autism and possibly identify a syndrome that involves autism in patients with normal array-based testing. Next-generation sequencing involves the sequencing of millions of fragments of genetic material in a massively parallel fashion. Next-generation sequencing can be performed on segments of the genetic material of various sizes¾from the entire genome (whole-genome sequencing) to small subsets of genes (targeted sequencing). Next-generation sequencing allows the detection of SNVs, CNVs, insertions, and deletions. With higher resolution comes a higher likelihood of detection of variants of uncertain significance.
 
Genetic Associations With Developmental Delay/Intellectual Disability and Autism Spectrum Disorder
For common phenotypes and syndromes, the pathogenicity of CNVs may be supported by considerable evidence; for uncommon phenotypes and uncommon CNVs determining pathogenicity requires a systematic evaluation that includes parental studies, examining databases for reported associations, and considering the molecular consequences of the identified variant. Parental studies (eg, “trio” testing of affected child, father, and mother) can identify an inherited CNV from an unaffected parent and therefore considered benign (Rodriguez-Revenga, 2013). A variety of databases index the clinical implications of CNVs and their associations with a particular phenotype. CNVs are continuously cataloged and, with growth in CMA testing and improved resolution, databases have become increasingly extensive (eg, DECIPHER, ClinVar). For uncommon CNVs, in addition to reports of CNV-phenotype associations, the location and size of the CNV can offer clues to pathogenicity; larger CNVs are more often pathogenic and the role of affected genes in brain circuitry and effect of CNV on gene expression can implicate pathogenicity. Although uncommon, an observed phenotype can result from unmasking a mutated recessive allele on the unaffected (non-CNV) chromosome (Kloosterman, 2014). Other considerations when determining pathogenicity include CNV dosage, X linkage, number of reports in the literature of an association between CNV and phenotype, and findings in “normal” individuals.
 
The American College of Medical Genetics has published guidelines for evaluating, interpreting, and reporting pathogenicity reflecting these principles (Kearney, 2011). The recommended categories of clinical significance for reporting are pathogenic, uncertain clinical significance (likely pathogenic, likely benign, or no subclassification), or benign. The International Standards for Cytogenomic Arrays Consortium more recently proposed “an evidence-based approach to guide the development of content on chromosomal microarrays and to support the interpretation of clinically significant copy number variation” (Riggs, 2012) The proposal defined levels of evidence that describe how well or how poorly detected variants or CNVs correlate with phenotype.
 
Regulatory Status
Clinical laboratories may develop and validate tests in-house and market them as a laboratory service; laboratory-developed tests must meet the general regulatory standards of the Clinical Laboratory Improvement Amendments. Lab tests for CMA testing and next-generation sequencing are available under the auspices of Clinical Laboratory Improvement Amendments. Laboratories that offer laboratory-developed tests must be licensed by the Clinical Laboratory Improvement Amendments for high-complexity testing. To date, the U.S. Food and Drug Administration (FDA) has chosen not to require any regulatory review of this test.
 
In 2010, the FDA indicated that it would require microarray manufacturers to seek clearance to sell their products for use in clinical cytogenetics.
 
CMA Testing
CMA testing is commercially available through many laboratories and includes targeted and whole-genome arrays, with or without SNV microarray analysis.
 
In January 2014, the Affymetrix CytoScan® Dx Assay (Thermo Fisher Scientific) was cleared by the FDA through the de novo 510(k) process. The FDA’s review of the CytoScan Dx Assay included an analytic evaluation of the test’s ability to detect accurately numerous chromosomal variations of different types, sizes, and genome locations compared with several analytically validated test methods. The FDA found that the CytoScan Dx Assay could detect CNVs across the genome and adequately detect CNVs in regions of the genome associated with developmental delay/intellectual disability. Reproducibility decreased with the CNV gain or loss size, particularly when less than approximately 400 kilobases (generally recommended as the lower reporting limit). As of July 2017, Affymetrix™ contains 2.7 million markers for copy number, 750,000 SNVs, and 1.9 million non-polymorphic probes (Affymetrix was acquired by Thermo Fisher Scientific in 2016). FDA product code: PFX.
 
FirstStepDx PLUS® (Lineagen) uses Lineagen’s custom-designed microarray platform manufactured by Affymetrix. As of July 2017, this microarray consists of a 2.8 million probe microarray for the detection of CNVs associated with neurodevelopmental disorders. The array includes probes that come standard on the Affymetrix CytoScan HD microarray, with an additional 88435 custom probes designed by Lineagen.
 
Ambry Genetics offers multiple tests (CMA and next-generation sequencing) designed for diagnosing ASD and neurodevelopmental disorders. As of July 2017, the CMA offered by Ambry Genetics includes over 2.6 million probes for copy number and 750,000 SNV probes. The expanded next-generation sequencing panel for neurodevelopmental disorders assesses 196 genes.
 
LabCorp offers the Reveal® SNP Microarray-Pediatric for individuals with nonsyndromic congenital anomalies, dysmorphic features, developmental delay/intellectual disability, and/or ASD. The Reveal microarray has 2,695 million probes as of July 2017.
 
Next-Generation Sequencing
A variety of commercial and academic laboratories offer next-generation sequencing panels designed for the evaluation of ASD, developmental delay/intellectual disability, and congenital anomalies, which vary in terms of the numbers of and specific genes tested.
 
Emory Genetics Laboratory offers a next-generation sequencing ASD panel of genes targeting genetic syndromes that include autism or autistic features. Greenwood Genetics Center offers a next-generation sequencing panel for syndromic autism that includes 83 genes. Fulgent Genetics offers a next-generation sequencing ASD panel that includes 121 genes.

Policy/
Coverage:
Effective March 2014
 
Meets Primary Coverage Criteria Or Is Covered For Contracts Without Primary Coverage Criteria
 
Chromosomal microarray analysis meets member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes for diagnosing a genetic abnormality in children with apparent nonsyndromic cognitive developmental delay/intellectual disability (DD/ID) or autism spectrum disorder (ASD) according to accepted Diagnostic and Statistical Manual of Mental Disorders-IV criteria when all of the following conditions are met (see definitions below):
 
    • Any indicated biochemical tests for metabolic disease have been performed, and results are non-diagnostic, and
    • FMR1 gene analysis (for Fragile X), when clinically indicated (e.g., ASD), is negative (not meant to exclude testing for DD/ID individuals for whom FMR1 testing is not clinically indicated); AND
    • In addition to a diagnosis of nonsyndromic DD/ID or ASD, the child has one or more of the following:
        • two or more major malformations, or
        • a single major malformation or multiple minor malformations, in an infant or child who is also small-for-dates, or
        • a single major malformation and multiple minor malformations, and
    • The results for the genetic testing have the potential to impact the clinical management of the patient, and
    • Testing is requested after the parent(s) have been engaged in face-to-face genetic counseling with a healthcare professional who has appropriate genetics training and experience.
 
Does Not Meet Primary Coverage Criteria Or Is Investigational For Contracts Without Primary Coverage Criteria
 
Chromosomal microarray analysis in all other cases of suspected genetic abnormality in children with developmental delay/intellectual disability or autism spectrum disorder does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes. For contracts without primary coverage criteria, chromosomal microarray analysis is considered investigational in all other cases of suspected genetic abnormality in children with developmental delay/intellectual disability or autism spectrum disorder. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 
Chromosomal microarray analysis to confirm the diagnosis of a disorder or syndrome that is routinely diagnosed based on clinical evaluation alone does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.  For contracts without primary coverage criteria, chromosomal microarray analysis to confirm the diagnosis of a disorder or syndrome that is routinely diagnosed based on clinical evaluation alone is not medically necessary. Services that are considered to be not medically necessary are specific contract exclusions in most member benefit certificates of coverage.
 
Chromosomal microarray analysis for prenatal genetic testing does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes. For contracts without primary coverage criteria, chromosomal microarray analysis is considered investigational for prenatal genetic testing. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 
Panel testing using next-generation sequencing in all cases of suspected genetic abnormality in children with developmental delay/intellectual disability or autism spectrum disorder does not meet member benefit certificate primary coverage criteria.
 
For members with contracts without primary coverage criteria, panel testing using next-generation sequencing in all cases of suspected genetic abnormality in children with developmental delay/intellectual disability or autism spectrum disorder is considered investigational. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 
Definitions:
Definitions, from the American College of Medical Genetics Guideline (ACMG, 1999), Evaluation of the Newborn with Single or Multiple Congenital Anomalies:
    • A malformation refers to abnormal structural development.
    • A major malformation is a structural defect that has a significant effect on function or social acceptability. Examples: ventricular septal defect or a cleft lip.
    • A minor malformation is a structural abnormality that has minimal effect on function or societal acceptance. Examples: preauricular ear pit or partial syndactyly (fusion) of the second and third toes.
    • A syndrome is a recognizable pattern of multiple malformations. Syndrome diagnoses are often relatively straightforward and common enough to be clinically recognized without specialized testing. Examples include Down syndrome, neural tube defects and achondroplasia. However, in the very young, or in the case of syndromes with variable presentation, confident identification may be difficult without additional testing.
 
Effective January 2012 – February 2014
 
Chromosomal microarray analysis meets member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes for diagnosing a genetic abnormality in children with apparent nonsyndromic cognitive developmental delay/intellectual disability (DD/ID) or autism spectrum disorder (ASD) according to accepted Diagnostic and Statistical Manual of Mental Disorders-IV criteria when all of the following conditions are met (see definitions below):
 
    • Any indicated biochemical tests for metabolic disease have been performed, and results are non-diagnostic, and
    • FMR1 gene analysis (for Fragile X), when clinically indicated, is negative, and
    • In addition to a diagnosis of nonsyndromic DD/ID or ASD, the child has one or more of the following:
        • two or more major malformations, or
        • a single major malformation or multiple minor malformations, in an infant or child who is also small-for-dates, or
        • a single major malformation and multiple minor malformations, and
    • The results for the genetic testing have the potential to impact the clinical management of the patient, and
    • Testing is requested after the parent(s) have been engaged in face-to-face genetic counseling with a healthcare professional who has appropriate genetics training and experience.
 
Chromosomal microarray analysis in all other cases of suspected genetic abnormality in children with developmental delay/intellectual disability or autism spectrum disorder does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes. For contracts without primary coverage criteria, chromosomal microarray analysis is considered investigational in all other cases of suspected genetic abnormality in children with developmental delay/intellectual disability or autism spectrum disorder. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 
Chromosomal microarray analysis to confirm the diagnosis of a disorder or syndrome that is routinely diagnosed based on clinical evaluation alone does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.  For contracts without primary coverage criteria, chromosomal microarray analysis to confirm the diagnosis of a disorder or syndrome that is routinely diagnosed based on clinical evaluation alone is not medically necessary. Services that are considered to be not medically necessary are specific contract exclusions in most member benefit certificates of coverage.
 
Chromosomal microarray analysis for prenatal genetic testing does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.  For contracts without primary coverage criteria, chromosomal microarray analysis is considered investigational for prenatal genetic testing. Investigational services are specific contract exclusions in most member benefit certificates of coverage.
 
Definitions:
Definitions, from the American College of Medical Genetics Guideline (ACMG, 1999), Evaluation of the Newborn with Single or Multiple Congenital Anomalies:
    • A malformation refers to abnormal structural development.
    • A major malformation is a structural defect that has a significant effect on function or social acceptability. Examples: ventricular septal defect or a cleft lip.
    • A minor malformation is a structural abnormality that has minimal effect on function or societal acceptance. Examples: preauricular ear pit or partial syndactyly (fusion) of the second and third toes.
    • A syndrome is a recognizable pattern of multiple malformations. Syndrome diagnoses are often relatively straightforward and common enough to be clinically recognized without specialized testing. Examples include Down syndrome, neural tube defects and achondroplasia. However, in the very young, or in the case of syndromes with variable presentation, confident identification may be difficult without additional testing.
 
Effective prior to January 2012
Array CGH (targeted or whole-genome) in the evaluation of children with cognitive developmental delay/mental retardation or autism spectrum disorder or for prenatal genetic testing does not meet member benefit certificate primary coverage criteria that there be scientific evidence of effectiveness in improving health outcomes.
 
Array CGH (targeted or whole-genome) in the evaluation of children with cognitive developmental delay/mental retardation or autism spectrum disorder or for prenatal genetic testing is considered investigational.  Investigational services are exclusions in most member benefit certificates of coverage.
 

Rationale:
Since this policy was initiated, the technology has rapidly increased in resolution, and chromosomal microarray has become the term of general use to accommodate all variations in the technology. Therefore, the title of the policy has been changed to include the new term, chromosomal microarray (CMA). In addition, the term aCGH, has been changed CMA in the description and rationale. Increased resolution arrays have been quickly translated to clinical services with a resulting increase in diagnostic yield, but also an increase in the potential for results of undetermined significance. Surveys conducted 2 to 3 years ago indicated that there is a lack of consensus between laboratories in the interpretation and reporting of CNVs, particularly those that are challenging (Tsuchiya, 2009). The ISCA database now offers increased standardization and classification of CNVs that have been previously reported, and should improve consensus in reporting.
 
Diagnosis of developmental delay/ intellectual disability or autism spectrum disorder
The diagnosis of developmental delay (DD) is reserved for children younger than age 5 years who have significant delay in two or more of the following developmental domains: gross or fine motor, speech/language, cognitive, social/personal, and activities of daily living (Moeschler, 2008). The diagnosis implies DD that may be significant and may predict life-long disability, although not all children diagnosed with DD will later be diagnosed with mental retardation.
 
Intellectual disability (ID), is a life-long disability diagnosed at or after age 5 when intelligence quotient (IQ) testing is considered valid and reliable. The Diagnostic and Statistical Manual of Mental Disorders of the American Psychiatric Association (DSM-IV), defines patients with ID as having an IQ less than 70, onset during childhood, and dysfunction or impairment in more than two of areas of adaptive behavior or systems of support.
 
According to the DSM-IV, pervasive developmental disorders (PDD) encompass five conditions: autistic disorder, Asperger disorder, pervasive developmental disorder-not otherwise specified (PDD-NOS), childhood disintegrative disorder, and Rett syndrome. While the term autism spectrum disorder (ASD) is not mentioned in the DSM-IV, it is now accepted to include the first three in this list. However, ASD, PDD, and autism are often used interchangeably (Caronna, 2008). These conditions are characterized by varying degrees of restrictions in communication and social interaction, and atypical behaviors.
 
Some children present with features of both DD/ID and of autism. For example, Yeargin-Allsopp et al. reported that nearly 70% of children with a validated diagnosis of ASD, sampled from 5 metropolitan Atlanta counties, had cognitive impairment (Yeargin-Allsopp, 2003). The evaluation pathway depends on the pediatrician, consulting specialists, and their consensus on the primary neurodevelopmental diagnosis.
 
Review of evidence
Post-natal CMA analysis
 
Several studies (see Appendix B in the Blue Cross Blue Shield TEC Assessment) have conducted CMA analysis on samples with known chromosomal abnormalities by standard karyotyping. In general, currently available CMA clinical services achieve near 100% sensitivity for known chromosomal abnormalities. False-positive rates (i.e., CNVs of undetermined clinical significance) on known normal samples were inconsistently reported and could not be summarized. One study evaluated the analytic validity of an oligo array and reported 99% sensitivity and 99% specificity with a resolution of 300–500 Kb for 10 selected cases with different known chromosomal abnormalities (Xiang, 2008).  
 
Several studies reported the diagnostic yield of CMA analysis in DD/ID or ASD patients with normal standard karyotype and in several cases normal FMR1 gene analysis and/or subtelomere FISH screening (see Appendix C in the Blue Cross Blue Shield TEC Assessment). Overall, diagnostic yield ranged from 5% to 16.7% in DD/MR patients and from 3.4%to 11.6% in patients with ASD; for this compilation, studies differed considerably in array resolution and in patient selection criteria. This compares well with a synthesis of studies recently published by the ISCA consortium, reporting an an average diagnostic yield of 12.2% across 33 studies (Miller, 2010).  Hochstenback et al. reported a CMA diagnostic yield of 19% for 36,325 DD/MR cytogenetic referrals in the Netherlands (Hochstenbach, 2009); and Shen et al. reported a 7% diagnostic yield among 933 ASD referrals (Shen, 2010). Cooper et al. studied CMA analyses from over 15,000 individuals with DD/ID, ASD, and/or various congenital abnormalities and compared them to CMA analyses from over 8,000 unaffected controls, finding a significant excess of large CNVs among cases compared to controls (Cooper, 2011). Using a common cutoff for CNV size, about 26% of cases had a CNV larger than 400 kilobases (kb) compared to about 12% of controls, suggesting that CNVs of this size account for approximately 14% of cases. CNVs larger than 400 kb were also significantly more common among cases with multiple congenital abnormalities.
 
Since the introduction of CMA analysis in about 2005, 18 new genomic disorders have been described, more than doubling the number of disorders described in the previous 20 years (Mefford, 2009). Using CMA in place of conventional cytogenetic testing would have missed 0.6-0.8% of all cases, i.e., those with balanced translocations (Hochstenbach, 2009) (Rauch, 2006).
 
A portion of the increased diagnostic yield from CMA analysis comes from the discovery that some chromosomal rearrangements that appear balanced (and therefore not pathogenic) by G-banded karyotype analysis are found to have small imbalances with greater resolution. It has been estimated that 40% of apparently balanced de novo or inherited translocations with abnormal phenotype are associated with cryptic deletion if analyzed by CMA (Schluth-Bolard, 2009). This contradicts earlier assumptions about inherited, apparently balanced rearrangements and shows that microarray analysis can allow for a less subjective and more accurate interpretation of an abnormal banding pattern (South, 2010).
 
Neither standard cytogenetic nor CMA analysis have been systematically studied for impact on clinical outcomes other than diagnosis (Subramonia-lyer, 2007) (Moeschler, 2006); Schaefer and Mendelsohn (Schaefer, 2008) acknowledge, for example, that a genetic diagnosis “typically will not change interventions for the [autism] patient.” Rather, clinical utility of genetic testing is primarily inferred based on the value of diagnosis to the family, estimation of recurrence risk, and on the importance of early detection and early intervention (Moeschler, 2006). Two studies indirectly addressed clinical outcomes other than diagnosis as a result of CMA analysis.
 
Saam et al. interviewed 14 physicians (2 neurologists, 12 medical geneticists) regarding management changes as a result of positive CMA test results from the University of Utah Cytogenetics Laboratory for 48 patients with DD or MR and normal karyotypes (Saam, 2008). Only 29% of patients had no management changes reported. For significant proportions of patients, the diagnostic odyssey was ended. However, this study was only a survey and did not attempt to quantitate the diagnostic tests avoided. Saam et al. also reported that 14.6% of patients with genetic diagnoses were referred to medical specialists, and 25% had improved access to insurance and educational services, but the study did not assess the benefits of specialist referrals or screening for comorbidities on patient outcomes, or describe and quantitate the improvement in access to community services (Saam, 2008).
 
Coulter et al. identified and reviewed, over the course of one year, the medical records of all patients at a tertiary children’s hospital who had CMA results showing an abnormal variant or a variant of possible significance (Coulter, 2011). A Board-certified medical geneticist reviewed the clinical notes from the ordering provider and abstracted recommendations for clinical actions (a specialist referral, imaging study, diagnostic test, or medication prescription) made specifically as a result of the CMA result. Of 1792 patients for whom CMA was ordered during the year reviewed, 131 had an abnormal variant and 104 had a variant of possible significance. Of these, 121 and 73 patients were included in the analysis. Overall, patients with an abnormal variant had a significantly higher rate of recommended clinical action (54%) than patients with a variant of possible significance (34%; p=0.01). Among patients with an abnormal variant and a diagnosis of DD/ID or congenital anomalies, about two-thirds of patients were referred for additional clinical action based on the CMA results, whereas referrals were made for 27% of patients with ASD and an abnormal variant. Referral rates were similar for patients with a CMA result of a variant of possible significance, with the exception of patients with congenital anomalies, who were referred for additional clinical action only 17% of the time. Patients younger than 2 years were significantly more likely to have clinical anomalies and were significantly more likely to have abnormal variants. Cases were described in which ancillary CMA results suggested clinical interventions for the present or future regarding possible co-morbid conditions. In no patients, however, were referrals linked to actual patient outcomes; the authors report that this study is ongoing.
 
Risk estimates for recurrence of disease in future births can be altered considerably by information from the genetic diagnosis. For example, the average sibling recurrence risk in ASD is 5% (Freitag, 2010).  However, if the cause is a dominant single gene disorder with full penetrance and a parent is a carrier, the sibling risk is 50%. If the disorder is recessive but characteristics are otherwise are the same, the sibling risk is 25%. If the cause is Fragile X, the recurrence risk in a brother is 50%, while a sister may be only mildly affected but will have a carrier risk of up to 50%. However, in the case of a de novo CNV (i.e., not carried by either parent), the sibling risk remains low, at the population average.
 
Knowledge of recurrence risk is expected to lead to improved future reproductive decision-making in families with children affected with DD/ID or ASD associated with specific mutations. Turner et al. studied the reproductive decisions of women from 38 families characterized by male members with mental retardation and a pattern consistent with chromosome X-linked transmission (Turner, 2008). Most of the women in these families spent many years knowing that they were at some risk of being carriers and of having a boy with MR. Prior to the availability of pathogenic mutation analysis, the birth rate for these families was below average for the district (United Kingdom-New South Wales), 1 in 27 versus 1 in 11 per year, respectively. After pathogenic mutation status was determined, both carriers and non-carriers (previously thought to be at risk) of the mutation had children at same rate with 74% of carriers choosing prenatal genetic evaluation. While the results of this study are suggestive, they do not show that knowledge of recurrence risk directly affected reproductive decisions. Saam et al., in the survey described previously, reported that recurrence risk evaluation was possible in about one-third of families after positive aCGH results, but did not study the impact of recurrence risk evaluation on reproductive planning (Saam, 2008).
 
As noted in the Description, guidelines emphasize the importance of cytogenetic evaluation to look for certain kinds of mutations that may be linked to specific conditions for early diagnosis and intervention. However, the benefits of early intervention for these disorders are uncertain. Few randomized trials have been conducted and the interventions differ considerably in the available studies, indicating that the field is still early in researching the critical elements of effective early intervention. For well-characterized genetic syndromes, it may be important to incorporate monitoring for comorbidities known to be associated with the condition. For example, 22q11 microdeletion syndrome (includes diGeorge and velo-cardio-facial syndromes) is associated with development of hearing impairment in a significant proportion of patients and subsequent delayed speech (Digilio, 1999). Velo-cardio-facial syndrome is also associated with heart defects (Freitag, 2010). Klinefelter syndrome may first be detected as developmental delay in early childhood; androgen treatment is an important component of therapy (Freitag, 2010). CMA analysis may also predict future conditions for which interventions are possible. In a report of 3 cases, one patient had a chromosomal deletion that included a gene associated with autosomal dominant Peutz-Jeghers syndrome (PJS); tumor screening protocols for males with PJS generally begin with upper and lower endoscopy with small-bowel follow-through radiographs beginning at age 8 years (Adam, 2009). Two other patients had a de novo deletion of chromosome 17p encompassing the TP53 tumor suppressor gene responsible for Li-Fraumeni syndrome (LFS); tumor screening protocols for LFS also begin in childhood. In another report, a child presenting to a neurology service with unusual behaviors was found to have a deletion that included exons of the DMD gene associated with Becker muscular dystrophy (BMD). Additional testing revealed a markedly elevated creatine kinase, and a thorough physical exam was consistent with BMD. This diagnosis explained some of the child’s behavior and prompted a plan for future surveillance for cardiac and other complications of BMD, as well as carrier testing and surveillance of the child’s mother (Coulter, 2011).
 
Prenatal CMA analysis
 
Prenatal fetal karyotyping is a routine test when the fetus is believed to be at high risk for a chromosomal abnormality as a result of a structural abnormality identified during an ultrasound exam, because of family history, or for other reasons agreed on by the patient and physician. However, karyotyping provides useful information in only a small percentage of these cases. Consistent with the increased diagnostic yield of CMA analysis, many laboratories are now providing this service in the prenatal setting. Currently, the microarrays used in this setting are most often targeted arrays, to reduce the number of results of uncertain significance and thus reduce parent anxiety and difficulties in decision-making. However, whole-genome analysis is also available. Hillman et al. conducted a systematic review and meta-analysis of studies reporting CMA analysis results in the prenatal setting or in the immediate post-natal setting following pregnancy termination for structural abnormalities detected by ultrasound (Hillman, 2011). A total of 751 participants in 8 studies were included for the overall meta-analysis; 409 of these had fetal anomalies using ultrasound. Overall, CMA analysis detected 3.6% more chromosomal imbalances than karyotyping when CMA results of unknown significance were included (1.1%). The CMA excess detection rate was higher in those with fetal anomalies by ultrasound, at 5.2% including results of unknown significance (1.9%). CMA analysis failed to detect one case of triploidy, and, as would be expected of the standard CMA technology, also failed to detect 14 cases of balanced translocations. The authors note the benefit of the additional detection by CMA but also the increase in results of unknown significance, and discuss the difficulties of interpretation in conjunction with prenatal decision-making. In recognition of the limitations and disadvantages of CMA in the prenatal setting, the American Congress of Obstetricians and Gynecologists published a Committee Opinion in November, 2009, recommending against CMA as a replacement for classic cytogenetics (ACOG, 2009).
 
Practice Guidelines and Position Statements
The American Academy of Neurology and the Practice Committee of the Child Neurology Society updated their guideline regarding the evaluation of unexplained global developmental delay/intellectual disability with information on genetic and metabolic (biochemical) testing in order to accommodate advances in the field (Michelson, 2011). The guidelines conclude that CMA testing has the highest diagnostic yield in children with DD/ID, that the often complex results require confirmation and careful interpretation, often with the assistance of a medical geneticist, and that CMA should be considered the first-line test. The guidelines acknowledge that “Research is sorely lacking on the medical, social, and financial benefits of having an accurate etiologic diagnosis.”
 
The American College of Medical Genetics (ACMG) published guidelines on array-based technologies and their clinical utilization for detecting chromosomal abnormalities (Manning, 2010). Chromosomal microarray testing for copy number variation is recommended as a first-line test in the initial postnatal evaluation of individuals with the following:
 
A. Multiple anomalies not specific to a well-delineated genetic syndrome
B. Apparently non-syndromic developmental delay/ intellectual disability
C. Autism spectrum disorders
 
ACMG also recommends against use of CMA in cases of multiple miscarriages.
 
Additional ACMG guidelines have been published for the design and performance expectations for clinical microarrays and associated software (Kearney, 2011) and for the interpretation and reporting of CNVs, (Kearney, 2011) both intended for the post-natal setting (see Description).
 
The International Standard Cytogenomic Array Consortium published a Consensus Statement in which they recommend offering CMA as the first-tier genetic test, in place of G-banded karyotype, for patients with unexplained DD/ID, ASD, or multiple congenital anomalies (MCA). “Except in special cases, such as those involving family history of multiple miscarriages, a karyotype is not cost effective in a child with DD/ID, ASD, or MCA and a negative array study. CMA testing is not inexpensive, but the cost is less than the cost of a G-banded karyotype plus a customized FISH test such as subtelomeric FISH, and the yield is greater.” (Miller, 2010)
 
Summary
CMA analysis offers a higher resolution approach to detecting the presence of chromosomal alterations that have been associated with cases of developmental delay/intellectual disability or autism spectrum disorder compared to karyotyping and ancillary testing. However, the diagnostic yield remains low in unselected populations without accompanying signs and/or symptoms. In individuals with apparent nonsyndromic developmental delay, intellectual disability, or suspected autism spectrum disorder and accompanying malformations, the diagnostic yield is much higher, and is higher than the yield of karyotype testing.
 
Evidence on the clinical benefit of CMA testing is largely anecdotal. Cases have been documented in which the information derived from testing ends a long diagnostic odyssey, aids in planning for surveillance or management of associated comorbidities, and assists in future reproductive decision-making. While systematic studies of the impact of CMA analysis on patient outcomes is lacking, the improvement in diagnostic yield has been well demonstrated, and feedback from physician specialty societies, academic medical centers, and in respected guidelines is consistent in supporting the clinical benefit of CMA testing for defined populations.
 
2014 Update
A literature search was conducted through February 2014. The following is a summary of the key identified literature.
 
Prenatal CMA analysis
Hillman et al conducted a prospective cohort study and systematic review and meta-analysis (Hillman, 2013). The cohort study involved 243 women undergoing CMA and karyotyping for a structural abnormality detected on prenatal ultrasound. There was an excess detection rate of abnormalities by CMA of 4.1% over conventional karyotyping, with a variant of unknown significance rate of 2.1% (95% confidence interval [CI], 1.3%-3.3%). The meta-analysis included studies through December 2012 that reported on prenatal microarray testing that were performed for any indication and was not limited to cases referred for abnormal fetal ultrasound findings. Twenty-five studies were included, 17 of which were not included in their 2011 systematic review. (37) The detection rate in the meta-analysis was 10% (95% CI, 8 to 13) with a variant of unknown significance rate of 1.4% (95% CI, 0.5% to 3.7%).
 
NGS
Analytic validity (the technical accuracy of the test in detecting a mutation that is present or in excluding a mutation that is absent)
 
No peer-reviewed, full-length publications on the analytic validity of the commercially available NGS ASD panels are identified.
 
Clinical validity (the diagnostic performance of the test [sensitivity, specificity, positive and negative predictive values] in detecting clinical disease)
 
No peer-reviewed, full-length publications on the clinical validity of the commercially available NGS ASD panels are identified.
 
Clinical utility (how the results of the diagnostic test will be used to change management of the patient and whether these changes in management lead to clinically important improvements in health outcomes)
 
No peer-reviewed, full-length publications on the clinical utility of the commercially available NGS ASD panels are identified.
 
Importantly, no published data on the rate of variants of unknown significance using NGS panels for autism have been identified.
 
In summary, published data on analytic and clinical validity, clinical utility and variants of unknown significance using next-generation sequencing (NGS) panels are lacking for the evaluation of patients with suspected genetic abnormality in children with DD/ID or ASD.
 
Practice Guidelines and Position Statements
American Congress of Obstetricians and Gynecologists Committee Opinion 581, 2013 (ACOG, 2013)
 
The College and the Society for Maternal-Fetal Medicine offer the following recommendations for the use of CMA in prenatal diagnosis:
 
    • In patients with a fetus with one or more major structural abnormalities identified on ultrasonographic examination and who are undergoing invasive prenatal diagnosis, chromosomal microarray analysis is recommended. This test replaces the need for fetal karyotype.
    • In patients with a structurally normal fetus undergoing invasive prenatal diagnostic testing, either fetal karyotyping or a chromosomal microarray analysis can be performed.
    • Most genetic mutations identified by chromosomal microarray analysis are not associated with increasing maternal age; therefore, the use of this test for prenatal diagnosis should not be restricted to women aged 35 years and older.
    •  In cases of intrauterine fetal demise or stillbirth when further cytogenetic analysis is desired, chromosomal microarray analysis on fetal tissue (ie, amniotic fluid, placenta, or products of conception) is recommended because of its increased likelihood of obtaining results and improved detection of causative abnormalities.
    • Limited data are available on the clinical utility of chromosomal microarray analysis to evaluate first-trimester and second-trimester pregnancy losses; therefore, this is not recommended at this time.
 
A 2013 guidelines update from the ACMG states that a stepwise or tiered approach to the clinical genetic diagnostic evaluation of autism spectrum disorder is recommended, with the recommendation being for first-tier to include FXS [fragile X syndrome] and CMA, and second tier to include MECP2 and PTEN testing (Schaefer, 2013). The guideline states that “this approach will evolve with continued advancements in diagnostic testing and improved understanding of the ASD phenotype. Multiple additional conditions have been reported in association with an ASD phenotype, but none of these has been evaluated in a large prospective cohort. Therefore, a future third tier of evaluation is a distinct possibility. Further studies would be needed to elevate the evidence to the point of recommended testing. Alternatively, advances in technology may permit bundling of individual tests into an extended, more readily accessible, and less expensive platform”. The accumulating evidence using next-generation sequencing (third tier testing) “will increase the diagnostic yield even more over the next few years.”
 
2017 Update
A literature search conducted through November 2017 did not reveal any new information that would prompt a change in the coverage statement.  The key identified literature is summarized below.
 
In 2016, investigators from Lineagen published 2 articles on CMA with FirstStepDx PLUS for ASD and neurodevelopmental disorders (Ho/Wassman, 2016; Ho/Twede, 2016). To be considered pathogenic, there had to be at least 2 publications that indicated that haplo-insufficiency or triplo-sensitivity of the region or gene(s) were causative of clinical features. The overall detection rate of CNVs was 28.1% (8.6% pathogenic and 19.4% variant of uncertain significance [VUS]) in 10,351 consecutive patients, with an average of 1.2 reportable CNVs per individual. In the 5694 patients with ASD, the detection rate was 5.4% pathogenic and 19.0% VUS. The most common referrals were made by neurologists (36%), developmental pediatricians (31%), pediatricians (16%), and medical geneticists (14%). The second report included 5487 patients with neurodevelopmental disorders who had been assessed over a period of 3.5 years (Ho/Twede, 2016). Overlap of patients in the 2 reports is unclear. The detection rate was 9.2% pathogenic and 20.2% VUS, compared with 9.0% pathogenic and 14.2% VUS in the CytoScan HD microarray. Thus, the addition of the custom probes to the standard CytoScan HD microarray significantly increased the VUS with little change in the detection of established pathogenic variants.
 
ONGOING AND UNPUBLISHED CLINICAL TRIALS
A search of ClinicalTrials.gov in November 2017 did not identify any ongoing or unpublished trials that would likely influence this review.
 
2018 Update
A literature search was conducted through November 2018.  There was no new information identified that would prompt a change in the coverage statement.  The key identified literature is summarized below.
 
PRACTICE GUIDELINES AND POSITION STATEMENTS
 
American Academy of Child and Adolescent Psychiatry
The American Academy of Child and Adolescent Psychiatry updated its guidelines on the assessment and treatment of children and adolescents with autism spectrum disorder (ASD) (AACAP, 2014). The Academy recommended that “all children with ASD should have a medical assessment, which typically includes physical examination, a hearing screen, a Wood's lamp examination for signs of tuberous sclerosis, and genetic testing, which may include G-banded karyotype, fragile X testing, or chromosomal microarray.”
 
2019 Update
Annual policy review completed with a literature search using the MEDLINE database through November 2019. No new literature was identified that would prompt a change in the coverage statement.
 
2020 Update
Annual policy review completed with a literature search using the MEDLINE database through November 2020. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
The national prevalence of developmental delay and intellectual disability were estimated at 4.1% and 1.2%, respectively, in US children based on data from the 2009 to 2017 National Health Interview Survey (Zablotsky, 2019).
 
The estimated prevalence of ASD in US children based on data from the 2009 to 2017 National Health Interview Survey was 2.5% (Zablotsky, 2019). ASD is 4 to 5 times more common in boys than girls, and white children are more often identified with ASD than black or Hispanic children. An accurate diagnosis can generally be made by age 2. The evaluation includes developmental screening and diagnostic evaluation (ie, hearing, vision, and neurologic testing; laboratory testing for metabolic disorders; and genetic testing).
 
The following is the summary of two studies published after 2015 by Chaves et all and Hu et all (Chaves, 2019; Hu, 2019). In 2019, Chaves et all conducted a study of 420 children in Brazil who have DD/ID/facial dysmorphism/ASD and neurodevelopmental disorders. Of these, the overall detection rate of copy number variant was 18%. In 2019, Hu et all conducted a study in China of 633 children with DD/ID/ASD. Of these, the overall detection rate of copy number variant was 20.06%.
 
The American College of Medical Genetics (ACMG) published a clinical practice resource on array-based technologies and their clinical utilization for detecting chromosomal abnormalities in 2010 and reaffirmed this in 2020 (Manning, 2010; Manning, 2020). CMA testing for copy number variants was recommended as a first-line test in the initial postnatal evaluation of individuals with the following:
 
    • Multiple anomalies not specific to a well-delineated genetic syndrome
    • Apparently nonsyndromic developmental delay/intellectual disability
    • ASD.
 
2021 Update
Annual policy review completed with a literature search using the MEDLINE database through November 2021. No new literature was identified that would prompt a change in the coverage statement.
 
2022 Update
Annual policy review completed with a literature search using the MEDLINE database through November 2022. No new literature was identified that would prompt a change in the coverage statement. The key identified literature is summarized below.
 
In 2020, the AAP issued a clinical report on identifying infants and young children with developmental disorders through surveillance and screening (Lipkin, 2020). The report proposed a screening model that included performing a complete medical evaluation and stated that a "child with suspected global developmental delay or intellectual disability should have laboratory testing done, including chromosomal microarray and fragile X testing [...] Further testing may be indicated when a diagnosis is not established with initial laboratory evaluation including whole exome sequencing and gene panels."
 
2023 Update
Annual policy review completed with a literature search using the MEDLINE database through November 2023. No new literature was identified that would prompt a change in the coverage statement.

CPT/HCPCS:
0156UCopy number (eg, intellectual disability, dysmorphology), sequence analysis
0170UNeurology (autism spectrum disorder [ASD]), RNA, next generation sequencing, saliva, algorithmic analysis, and results reported as predictive probability of ASD diagnosis
0209UCytogenomic constitutional (genome-wide) analysis, interrogation of genomic regions for copy number, structural changes and areas of homozygosity for chromosomal abnormalities
0234UMECP2 (methyl CpG binding protein 2) (eg, Rett syndrome), full gene analysis, including small sequence changes in exonic and intronic regions, deletions, duplications, mobile element insertions, and variants in non uniquely mappable regions
0260URare diseases (constitutional/heritable disorders), identification of copy number variations, inversions, insertions, translocations, and other structural variants by optical genome mapping
0318UPediatrics (congenital epigenetic disorders), whole genome methylation analysis by microarray for 50 or more genes, blood
81228Cytogenomic (genome wide) analysis; interrogation of genomic regions for copy number variants comparative genomic hybridization [CGH] microarray analysis)
81229Cytogenomic constitutional (genome wide) microarray analysis; interrogation of genomic regions for copy number and single nucleotide polymorphism (SNP) variants, comparative genomic hybridization (CGH) microarray analysis.
81277Cytogenomic neoplasia (genome wide) microarray analysis, interrogation of genomic regions for copy number and loss of heterozygosity variants for chromosomal abnormalities
81321PTEN (phosphatase and tensin homolog) (eg, Cowden syndrome, PTEN hamartoma tumor syndrome) gene analysis; full sequence analysis
81404Molecular pathology procedure, Level 5 (eg, analysis of 2-5 exons by DNA sequence analysis, mutation scanning or duplication/deletion variants of 6-10 exons, or characterization of a dynamic mutation disorder/triplet repeat by Southern blot analysis) ACADS (acyl-CoA dehydrogenase, C-2 to C-3 short chain) (eg, short chain acyl-CoA dehydrogenase deficiency), targeted sequence analysis (eg, exons 5 and 6) AQP2 (aquaporin 2 [collecting duct]) (eg, nephrogenic diabetes insipidus), full gene sequence ARX (aristaless related homeobox) (eg, X-linked lissencephaly with ambiguous genitalia, X-linked mental retardation), full gene sequence AVPR2 (arginine vasopressin receptor 2) (eg, nephrogenic diabetes insipidus), full gene sequence BBS10 (Bardet-Biedl syndrome 10) (eg, Bardet-Biedl syndrome), full gene sequence BTD (biotinidase) (eg, biotinidase deficiency), full gene sequence C10orf2 (chromosome 10 open reading frame 2) (eg, mitochondrial DNA depletion syndrome), full gene sequence CAV3 (caveolin 3) (eg, CAV3-related distal myopathy, limb-girdle muscular dystrophy type 1C), full gene sequence CD40LG (CD40 ligand) (eg, X-linked hyper IgM syndrome), full gene sequence CDKN2A (cyclin-dependent kinase inhibitor 2A) (eg, CDKN2A-related cutaneous malignant melanoma, familial atypical mole-malignant melanoma syndrome), full gene sequence CLRN1 (clarin 1) (eg, Usher syndrome, type 3), full gene sequence COX6B1 (cytochrome c oxidase subunit VIb polypeptide 1) (eg, mitochondrial respiratory chain complex IV deficiency), full gene sequence CPT2 (carnitine palmitoyltransferase 2) (eg, carnitine palmitoyltransferase II deficiency), full gene sequence CRX (cone-rod homeobox) (eg, cone-rod dystrophy 2, Leber congenital amaurosis), full gene sequence CYP1B1 (cytochrome P450, family 1, subfamily B, polypeptide 1) (eg, primary congenital glaucoma), full gene sequence EGR2 (early growth response 2) (eg, Charcot-Marie-Tooth), full gene sequence EMD (emerin) (eg, Emery-Dreifuss muscular dystrophy), duplication/deletion analysis EPM2A (epilepsy, progressive myoclonus type 2A, Lafora disease [laforin]) (eg, progressive myoclonus epilepsy), full gene sequence FGF23 (fibroblast growth factor 23) (eg, hypophosphatemic rickets), full gene sequence FGFR2 (fibroblast growth factor receptor 2) (eg, craniosynostosis, Apert syndrome, Crouzon syndrome), targeted sequence analysis (eg, exons 8, 10) FGFR3 (fibroblast growth factor receptor 3) (eg, achondroplasia, hypochondroplasia), targeted sequence analysis (eg, exons 8, 11, 12, 13) FHL1 (four and a half LIM domains 1) (eg, Emery-Dreifuss muscular dystrophy), full gene sequence FKRP (fukutin related protein) (eg, congenital muscular dystrophy type 1C [MDC1C], limb-girdle muscular dystrophy [LGMD] type 2I), full gene sequence FOXG1 (forkhead box G1) (eg, Rett syndrome), full gene sequence FSHMD1A (facioscapulohumeral muscular dystrophy 1A) (eg, facioscapulohumeral muscular dystrophy), evaluation to detect abnormal (eg, deleted) alleles FSHMD1A (facioscapulohumeral muscular dystrophy 1A) (eg, facioscapulohumeral muscular dystrophy), characterization of haplotype(s) (ie, chromosome 4A and 4B haplotypes) GH1 (growth hormone 1) (eg, growth hormone deficiency), full gene sequence GP1BB (glycoprotein Ib [platelet], beta polypeptide) (eg, Bernard-Soulier syndrome type B), full gene sequence (For common deletion variants of alpha globin 1 and alpha globin 2 genes, use 81257) HNF1B (HNF1 homeobox B) (eg, maturity-onset diabetes of the young [MODY]), duplication/deletion analysis HRAS (v-Ha-ras Harvey rat sarcoma viral oncogene homolog) (eg, Costello syndrome), full gene sequence HSD3B2 (hydroxy-delta-5-steroid dehydrogenase, 3 beta- and steroid delta-isomerase 2) (eg, 3-beta-hydroxysteroid dehydrogenase type II deficiency), full gene sequence HSD11B2 (hydroxysteroid [11-beta] dehydrogenase 2) (eg, mineralocorticoid excess syndrome), full gene sequence HSPB1 (heat shock 27kDa protein 1) (eg, Charcot-Marie-Tooth disease), full gene sequence INS (insulin) (eg, diabetes mellitus), full gene sequence KCNJ1 (potassium inwardly-rectifying channel, subfamily J, member 1) (eg, Bartter syndrome), full gene sequence KCNJ10 (potassium inwardly-rectifying channel, subfamily J, member 10) (eg, SeSAME syndrome, EAST syndrome, sensorineural hearing loss), full gene sequence LITAF (lipopolysaccharide-induced TNF factor) (eg, Charcot-Marie-Tooth), full gene sequence MEFV (Mediterranean fever) (eg, familial Mediterranean fever), full gene sequence MEN1 (multiple endocrine neoplasia I) (eg, multiple endocrine neoplasia type 1, Wermer syndrome), duplication/deletion analysis MMACHC (methylmalonic aciduria [cobalamin deficiency] cblC type, with homocystinuria) (eg, methylmalonic acidemia and homocystinuria), full gene sequence MPV17 (MpV17 mitochondrial inner membrane protein) (eg, mitochondrial DNA depletion syndrome), duplication/deletion analysis NDP (Norrie disease [pseudoglioma]) (eg, Norrie disease), full gene sequence NDUFA1 (NADH dehydrogenase [ubiquinone] 1 alpha subcomplex, 1, 7.5kDa) (eg, Leigh syndrome, mitochondrial complex I deficiency), full gene sequence NDUFAF2 (NADH dehydrogenase [ubiquinone] 1 alpha subcomplex, assembly factor 2) (eg, Leigh syndrome, mitochondrial complex I deficiency), full gene sequence NDUFS4 (NADH dehydrogenase [ubiquinone] Fe-S protein 4, 18kDa [NADH-coenzyme Q reductase]) (eg, Leigh syndrome, mitochondrial complex I deficiency), full gene sequence NIPA1 (non-imprinted in Prader-Willi/Angelman syndrome 1) (eg, spastic paraplegia), full gene sequence NLGN4X (neuroligin 4, X-linked) (eg, autism spectrum disorders), duplication/deletion analysis NPC2 (Niemann-Pick disease, type C2 [epididymal secretory protein E1]) (eg, Niemann-Pick disease type C2), full gene sequence NR0B1 (nuclear receptor subfamily 0, group B, member 1) (eg, congenital adrenal hypoplasia), full gene sequence PDX1 (pancreatic and duodenal homeobox 1) (eg, maturity-onset diabetes of the young [MODY]), full gene sequence PHOX2B (paired-like homeobox 2b) (eg, congenital central hypoventilation syndrome), full gene sequence PLP1 (proteolipid protein 1) (eg, Pelizaeus-Merzbacher disease, spastic paraplegia), duplication/deletion analysis PQBP1 (polyglutamine binding protein 1) (eg, Renpenning syndrome), duplication/deletion analysis PRNP (prion protein) (eg, genetic prion disease), full gene sequence PROP1 (PROP paired-like homeobox 1) (eg, combined pituitary hormone deficiency), full gene sequence PRPH2 (peripherin 2 [retinal degeneration, slow]) (eg, retinitis pigmentosa), full gene sequence PRSS1 (protease, serine, 1 [trypsin 1]) (eg, hereditary pancreatitis), full gene sequence RAF1 (v-raf-1 murine leukemia viral oncogene homolog 1) (eg, LEOPARD syndrome), targeted sequence analysis (eg, exons 7, 12, 14, 17) RET (ret proto-oncogene) (eg, multiple endocrine neoplasia, type 2B and familial medullary thyroid carcinoma), common variants (eg, M918T, 2647_2648delinsTT, A883F) RHO (rhodopsin) (eg, retinitis pigmentosa), full gene sequence RP1 (retinitis pigmentosa 1) (eg, retinitis pigmentosa), full gene sequence SCN1B (sodium channel, voltage-gated, type I, beta) (eg, Brugada syndrome), full gene sequence SCO2 (SCO cytochrome oxidase deficient homolog 2 [SCO1L]) (eg, mitochondrial respiratory chain complex IV deficiency), full gene sequence SDHC (succinate dehydrogenase complex, subunit C, integral membrane protein, 15kDa) (eg, hereditary paraganglioma-pheochromocytoma syndrome), duplication/deletion analysis SDHD (succinate dehydrogenase complex, subunit D, integral membrane protein) (eg, hereditary paraganglioma), full gene sequence SGCG (sarcoglycan, gamma [35kDa dystrophin-associated glycoprotein]) (eg, limb-girdle muscular dystrophy), duplication/deletion analysis SH2D1A (SH2 domain containing 1A) (eg, X-linked lymphoproliferative syndrome), full gene sequence SLC16A2 (solute carrier family 16, member 2 [thyroid hormone transporter]) (eg, specific thyroid hormone
81405Molecular pathology procedure, Level 6 (eg, analysis of 6-10 exons by DNA sequence analysis, mutation scanning or duplication/deletion variants of 11-25 exons, regionally targeted cytogenomic array analysis) Cytogenomic constitutional targeted microarray analysis of chromosome 22q13 by interrogation of genomic regions for copy number and single nucleotide polymorphism (SNP) variants for chromosomal abnormalities (When performing cytogenomic [genome-wide] analysis, for constitutional chromosomal abnormalities. See 81228, 81229, 81349)
81406Molecular pathology procedure, Level 7 (eg, analysis of 11-25 exons by DNA sequence analysis, mutation scanning or duplication/deletion variants of 26-50 exons) ACADVL (acyl-CoA dehydrogenase, very long chain) (eg, very long chain acyl-coenzyme A dehydrogenase deficiency), full gene sequence ACTN4 (actinin, alpha 4) (eg, focal segmental glomerulosclerosis), full gene sequence AFG3L2 (AFG3 ATPase family gene 3-like 2 [S. cerevisiae]) (eg, spinocerebellar ataxia), full gene sequence AIRE (autoimmune regulator) (eg, autoimmune polyendocrinopathy syndrome type 1), full gene sequence ALDH7A1 (aldehyde dehydrogenase 7 family, member A1) (eg, pyridoxine-dependent epilepsy), full gene sequence ANO5 (anoctamin 5) (eg, limb-girdle muscular dystrophy), full gene sequence ANOS1 (anosmin-1) (eg, Kallmann syndrome 1), full gene sequence APP (amyloid beta [A4] precursor protein) (eg, Alzheimer disease), full gene sequence ASS1 (argininosuccinate synthase 1) (eg, citrullinemia type I), full gene sequence ATL1 (atlastin GTPase 1) (eg, spastic paraplegia), full gene sequence ATP1A2 (ATPase, Na+/K+ transporting, alpha 2 polypeptide) (eg, familial hemiplegic migraine), full gene sequence ATP7B (ATPase, Cu++ transporting, beta polypeptide) (eg, Wilson disease), full gene sequence BBS1 (Bardet-Biedl syndrome 1) (eg, Bardet-Biedl syndrome), full gene sequence BBS2 (Bardet-Biedl syndrome 2) (eg, Bardet-Biedl syndrome), full gene sequence BCKDHB (branched-chain keto acid dehydrogenase E1, beta polypeptide) (eg, maple syrup urine disease, type 1B), full gene sequence BEST1 (bestrophin 1) (eg, vitelliform macular dystrophy), full gene sequence BMPR2 (bone morphogenetic protein receptor, type II [serine/threonine kinase]) (eg, heritable pulmonary arterial hypertension), full gene sequence BRAF (B-Raf proto-oncogene, serine/threonine kinase) (eg, Noonan syndrome), full gene sequence BSCL2 (Berardinelli-Seip congenital lipodystrophy 2 [seipin]) (eg, Berardinelli-Seip congenital lipodystrophy), full gene sequence BTK (Bruton agammaglobulinemia tyrosine kinase) (eg, X-linked agammaglobulinemia), full gene sequence CACNB2 (calcium channel, voltage-dependent, beta 2 subunit) (eg, Brugada syndrome), full gene sequence CAPN3 (calpain 3) (eg, limb-girdle muscular dystrophy [LGMD] type 2A, calpainopathy), full gene sequence CBS (cystathionine-beta-synthase) (eg, homocystinuria, cystathionine beta-synthase deficiency), full gene sequence CDH1 (cadherin 1, type 1, E-cadherin [epithelial]) (eg, hereditary diffuse gastric cancer), full gene sequence CDKL5 (cyclin-dependent kinase-like 5) (eg, early infantile epileptic encephalopathy), full gene sequence CLCN1 (chloride channel 1, skeletal muscle) (eg, myotonia congenita), full gene sequence CLCNKB (chloride channel, voltage-sensitive Kb) (eg, Bartter syndrome 3 and 4b), full gene sequence CNTNAP2 (contactin-associated protein-like 2) (eg, Pitt-Hopkins-like syndrome 1), full gene sequence COL6A2 (collagen, type VI, alpha 2) (eg, collagen type VI-related disorders), duplication/deletion analysis CPT1A (carnitine palmitoyltransferase 1A [liver]) (eg, carnitine palmitoyltransferase 1A [CPT1A] deficiency), full gene sequence CRB1 (crumbs homolog 1 [Drosophila]) (eg, Leber congenital amaurosis), full gene sequence CREBBP (CREB binding protein) (eg, Rubinstein-Taybi syndrome), duplication/deletion analysis DBT (dihydrolipoamide branched chain transacylase E2) (eg, maple syrup urine disease, type 2), full gene sequence DLAT (dihydrolipoamide S-acetyltransferase) (eg, pyruvate dehydrogenase E2 deficiency), full gene sequence DLD (dihydrolipoamide dehydrogenase) (eg, maple syrup urine disease, type III), full gene sequence DSC2 (desmocollin) (eg, arrhythmogenic right ventricular dysplasia/cardiomyopathy 11), full gene sequence DSG2 (desmoglein 2) (eg, arrhythmogenic right ventricular dysplasia/cardiomyopathy 10), full gene sequence DSP (desmoplakin) (eg, arrhythmogenic right ventricular dysplasia/cardiomyopathy 8), full gene sequence EFHC1 (EF-hand domain [C-terminal] containing 1) (eg, juvenile myoclonic epilepsy), full gene sequence EIF2B3 (eukaryotic translation initiation factor 2B, subunit 3 gamma, 58kDa) (eg, leukoencephalopathy with vanishing white matter), full gene sequence EIF2B4 (eukaryotic translation initiation factor 2B, subunit 4 delta, 67kDa) (eg, leukoencephalopathy with vanishing white matter), full gene sequence EIF2B5 (eukaryotic translation initiation factor 2B, subunit 5 epsilon, 82kDa) (eg, childhood ataxia with central nervous system hypomyelination/vanishing white matter), full gene sequence ENG (endoglin) (eg, hereditary hemorrhagic telangiectasia, type 1), full gene sequence EYA1 (eyes absent homolog 1 [Drosophila]) (eg, branchio-oto-renal [BOR] spectrum disorders), full gene sequence F8 (coagulation factor VIII) (eg, hemophilia A), duplication/deletion analysis FAH (fumarylacetoacetate hydrolase [fumarylacetoacetase]) (eg, tyrosinemia, type 1), full gene sequence FASTKD2 (FAST kinase domains 2) (eg, mitochondrial respiratory chain complex IV deficiency), full gene sequence FIG4 (FIG4 homolog, SAC1 lipid phosphatase domain containing [S. cerevisiae]) (eg, Charcot-Marie-Tooth disease), full gene sequence FTSJ1 (FtsJ RNA methyltransferase homolog 1 [E. coli]) (eg, X-linked mental retardation 9), full gene sequence FUS (fused in sarcoma) (eg, amyotrophic lateral sclerosis), full gene sequence GAA (glucosidase, alpha; acid) (eg, glycogen storage disease type II [Pompe disease]), full gene sequence GALC (galactosylceramidase) (eg, Krabbe disease), full gene sequence GALT (galactose-1-phosphate uridylyltransferase) (eg, galactosemia), full gene sequence GARS (glycyl-tRNA synthetase) (eg, Charcot-Marie-Tooth disease), full gene sequence GCDH (glutaryl-CoA dehydrogenase) (eg, glutaricacidemia type 1), full gene sequence GCK (glucokinase [hexokinase 4]) (eg, maturity-onset diabetes of the young [MODY]), full gene sequence GLUD1 (glutamate dehydrogenase 1) (eg, familial hyperinsulinism), full gene sequence GNE (glucosamine [UDP-N-acetyl]-2-epimerase/N-acetylmannosamine kinase) (eg, inclusion body myopathy 2 [IBM2], Nonaka myopathy), full gene sequence GRN (granulin) (eg, frontotemporal dementia), full gene sequence HADHA (hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase [trifunctional protein] alpha subunit) (eg, long chain acyl-coenzyme A dehydrogenase deficiency), full gene sequence HADHB (hydroxyacyl-CoA dehydrogenase/3-ketoacyl-CoA thiolase/enoyl-CoA hydratase [trifunctional protein], beta subunit) (eg, trifunctional protein deficiency), full gene sequence HEXA (hexosaminidase A, alpha polypeptide) (eg, Tay-Sachs disease), full gene sequence HLCS (HLCS holocarboxylase synthetase) (eg, holocarboxylase synthetase deficiency), full gene sequence HMBS (hydroxymethylbilane synthase) (eg, acute intermittent porphyria), full gene sequence HNF4A (hepatocyte nuclear factor 4, alpha) (eg, maturity-onset diabetes of the young [MODY]), full gene sequence IDUA (iduronidase, alpha-L-) (eg, mucopolysaccharidosis type I), full gene sequence INF2 (inverted formin, FH2 and WH2 domain containing) (eg, focal segmental glomerulosclerosis), full gene sequence IVD (isovaleryl-CoA dehydrogenase) (eg, isovaleric acidemia), full gene sequence JAG1 (jagged 1) (eg, Alagille syndrome), duplication/deletion analysis JUP (junction plakoglobin) (eg, arrhythmogenic right ventricular dysplasia/cardiomyopathy 11), full gene sequence KCNH2 (potassium voltage-gated channel, subfamily H [eag-related], member 2) (eg, short QT syndrome, long QT syndrome), full gene sequence KCNQ1 (potassium voltage-gated channel, KQT-like subfamily, member 1) (eg, short QT syndrome, long QT syndrome), full gene sequence KCNQ2 (potassium voltage-gated channel, KQT-like subfamily, member 2) (eg, epileptic encephalopathy), full gene sequence LDB3 (LIM domain binding 3) (eg, familial dilated cardiomyopathy, myofibrillar myopathy), full gene sequence LDLR (low den
81407Molecular pathology procedure, Level 8 (eg, analysis of 26 50 exons by DNA sequence analysis, mutation scanning or duplication/deletion variants of >50 exons, sequence analysis of multiple genes on one platform)
S3870Comparative genomic hybridization (cgh) microarray testing for developmental delay, autism spectrum disorder and/or intellectual disability

References: Blue Cross Blue Shield Association Technology Evaluation Center (TEC). TEC Special Report: “Array Comparative Genomic Hybridization (aCGH) for the Genetic Evaluation of Patients with Developmental Delay/Mental Retardation and Autism Spectrum Disorder. TEC Assessments 2009; 24 (Tab 10).

Freitag CM, Staal W, Klauck SM et al.(2010) Genetics of autistic disorders: review and clinical implications. Eur Child Adolesc Psychiatry 2010; 19(3):169-78.

Rodriguez-Revenga L, Mila M, Rosenberg C et al.(2007) Structural variation in the human genome: the impact of copy number variants on clinical diagnosis. Genet Med 2007; 9(9):600-6.

Zahir F, Friedman JM.(2007) The impact of array genomic hybridization on mental retardation research: a review of current technologies and their clinical utility. . Clin Genet 2007; 72(4):271-87.

American College of Medical Genetics (ACMG).(1999) Evaluation of the newborn with single or multiple congenital anomalies: a clinical guideline. American college of Medical Genetics Foundation Clinical Guidelines Project, sponsored by New York State Department of Health. 1999 Available at http://www.health.ny.gov/nysdoh/dpprd/index.htm.

Baldwin EL, Lee JY, Blake DM et al.(2008) Enhanced detection of clinically relevant genomic imbalances using a targeted plus whole genome oligonucleotide microarray. Genet Med 2008; 10(6):415-29.

Caronna EB, Milunsky JM, Tager-Flusberg H.(2008) Autism spectrum disorders: clinical and research frontiers. Arch Dis Child 2008; 93(6):518-23.

Chaves TF, Baretto N, Oliveira LF, et al.(2019) Copy Number Variations in a Cohort of 420 Individuals with Neurodevelopmental Disorders From the South of Brazil. Sci Rep. Nov 28 2019; 9(1): 17776. PMID 31780800

Cooper GM, Coe BP, Girirajan S et al.(2011) A copy number variation morbidity map of developmental delay. Nat Genet 2011; 43(9):838-46.

Cooper GM, Coe BP, Girirajan S, et al.(2011) A copy number variation morbidity map of developmental delay. Nat Genet. Sep 2011;43(9):838-846. PMID 21841781

Coulter ME, Miller DT, Harris DJ et al.(2011) Chromosomal microarray testing influences medical management. Genet Med 2011; 13(9):770-6.

Digilio MC, Pacifico C, Tieri L, et al.(1999) Audiological findings in patients with microdeletion 22q11 (di George/velocardiofacial syndrome). Br J Audiol 1999; 33(5):329-33.

Fan YS, Jayakar P, Zhu H et al(2007) Detection of pathogenic gene copy number variations in patients with mental retardation by genomewide oligonucleotide array comparative genomic hybridization. Hum Mutat 2007; 28(11):1124-32.

Freitag CM, Staal W, Klauck SM, et al.(2010) Genetics of autistic disorders: review and clinical implications. Eur Child Adolesc Psychiatry. Mar 2010;19(3):169-178. PMID 19941018

Hillman SC, McMullan DJ, Hall G et al.(2013) Use of prenatal chromosomal microarray: prospective cohort study and systematic review and meta-analysis. Ultrasound Obstet Gynecol 2013; 41(6):610-20.

Hillman SC, Pretlove S, Coomarasamy A et al.(2011) Additional information from array comparative genomic hybridization technology over conventional karyotyping in prenatal diagnosis: a systematic review and meta-analysis. Ultrasound Obstet Gynecol 2011; 37(1):6-14.

Ho KS, Twede H, Vanzo R, et al.(2016) Clinical Performance of an Ultrahigh Resolution Chromosomal Microarray Optimized for Neurodevelopmental Disorders. Biomed Res Int. 2016;2016:3284534. PMID 27975050

Ho KS, Wassman ER, Baxter AL, et al.(2016) Chromosomal Microarray Analysis of Consecutive Individuals with Autism Spectrum Disorders Using an Ultra-High Resolution Chromosomal Microarray Optimized for Neurodevelopmental Disorders. Int J Mol Sci. Dec 09 2016;17(12). PMID 27941670

Hochstenbach R, van Binsbergen E, Engelen J et al.(2009) Array analysis and karyotyping: workflow consequences based on a retrospective study of 36,325 patients with idiopathic developmental delay in the Netherlands. Eur J Med Genet 2009; 52(4):161-9.

Hochstenbach R, van Binsbergen E, Engelen J, et al.(2009) Array analysis and karyotyping: workflow consequences based on a retrospective study of 36,325 patients with idiopathic developmental delay in the Netherlands. Eur J Med Genet. Jul-Aug 2009;52(4):161-169. PMID 19362174

Hu T, Zhang Z, Wang J, et al.(2019) Chromosomal Aberrations in Pediatric Patients with Developmental Delay/Intellectual Disability: A Single-Center Clinical Investigation. Biomed Res Int. 2019; 2019: 9352581. PMID 31781653

Kearney HM, South ST, Wolff DJ et al.(2011) American College of Medical Genetics recommendations for the design and performance expectations for clinical genomic copy number microarrays intended for use in the postnatal setting for detection of constitutional abnormalities. Genet Med 2011; 13(7):676-9.

Kearney HM, Thorland EC, Brown KK, et al.(2011) American College of Medical Genetics standards and guidelines for interpretation and reporting of postnatal constitutional copy number variants. Genet Med. Jul 2011;13(7):680-685. PMID 21681106

Lipkin PH, Macias MM, Norwood KW, et al.(2020) Promoting Optimal Development: Identifying Infants and Young Children With Developmental Disorders Through Developmental Surveillance and Screening. Pediatrics. Jan 2020; 145(1). PMID 31843861

Manning M, Hudgins L.(2010) Array-based technology and recommendations for utilization in medical genetics practice for detection of chromosomal abnormalities. Genet Med 2010; 12(11):742-5.

Manning M, Hudgins L.(2010) Array-based technology and recommendations for utilization in medical genetics practice for detection of chromosomal abnormalities. Genet Med. Nov 2010;12(11):742-745. PMID 20962661

Manning M, Hudgins L.(2020) Addendum: Array-based technology and recommendations for utilization in medical genetics practice for detection of chromosomal abnormalities. Genet Med. Jun 08 2020. PMID 32514088

Mefford HC.(2009) Genotype to phenotype-discovery and characterization of novel genomic disorders in a "genotype-first" era. Genet Med 2009; 11(12):836-42.

Michelson DJ, Shevell MI, Sherr EH et al.(2011) Evidence Report: Genetic and metabolic testing on children with global developmental delay: Report of the Quality Standards Subcommittee of the American Academy of Neurology and the Practice Committee of the Child Neurology Society. Neurology 2011; 77(17):1629-35.

Michelson DJ, Shevell MI, Sherr EH, et al.(2011) Evidence Report: Genetic and metabolic testing on children with global developmental delay: Report of the Quality Standards Subcommittee of the American Academy of Neurology and the Practice Committee of the Child Neurology Society. Neurology. Oct 25 2011;77(17):1629-1635. PMID 21956720

Miller DT, Adam MP, Aradhya S et al.(2010) Consensus statement: chromosomal microarray is a first-tier clinical diagnostic test for individuals with developmental disabilities or congenital anomalies. Am J Hum Genet 2010; 86(5):749-64.

Moeschler JB, Shevell M;(2006) American Academy of Pediatrics Committee on Genetics. Clinical genetic evaluation of the child with mental retardation or developmental delays. Pediatrics 2006; 117(6):2304-16.

Moeschler JB.(2008) Genetic evaluation of intellectual disabilities. Semin Pediatr Neurol 2008; 15(1):2-9.

Rauch A, Hoyer J, Guth S et al.(2006) Diagnostic yield of various genetic approaches in patients with unexplained developmental delay or mental retardation. Am J Med Genet A 2006; 140(19):2063-74.

Rodriguez-Revenga L, Mila M, Rosenberg C et al.(2007) Structural variation in the human genome: the impact of copy number variants on clinical diagnosis. Genet Med 2007; 9(9):600-6.

Saam J, Gudgeon J, Aston E et al.(2008) How physicians use array comparative genomic hybridization results to guide patient management in children with developmental delay. Genet Med 2008; 10(3):181-6.

Saam J, Gudgeon J, Aston E, et al.(2008) How physicians use array comparative genomic hybridization results to guide patient management in children with developmental delay. Genet Med. Mar 2008;10(3):181-186. PMID 18344707

Schaefer GB, Mendelsohn NJ, Professional P et al.(2013) Clinical genetics evaluation in identifying the etiology of autism spectrum disorders: 2013 guideline revisions. Genet Med 2013; 15(5):399-407.

Schaefer GB, Mendelsohn NJ, Professional P, et al.(2013) Clinical genetics evaluation in identifying the etiology of autism spectrum disorders: 2013 guideline revisions. Genet Med. May 2013;15(5):399-407. PMID 23519317

Schaefer GB, Mendelsohn NJ.(2008) Clinical genetics evaluation in identifying the etiology of autism spectrum disorders. Genet Med 2008; 10(4):301-5.

Schluth-Bolard C, Delobel B, Sanlaville D et al.(2009) Cryptic genomic imbalances in de novo and inherited apparently balanced chromosomal rearrangements: array CGH study of 47 unrelated cases. Eur J Med Genet 2009; 52(5):291-6.

Shen Y, Dies KA, Holm IA et al.(2010) Clinical genetic testing for patients with autism spectrum disorders. Pediatrics 2010; 125(4):e727-35.

South ST, Lee C, Lamb AN, et al.(2013) ACMG Standards and Guidelines for constitutional cytogenomic microarray analysis, including postnatal and prenatal applications: revision 2013. Genet Med. Nov 2013;15(11):901-909. PMID 24071793

South ST, Rector L, Aston E et al.(2010) Large clinically consequential imbalances detected at the breakpoints of apparently balanced and inherited chromosome rearrangements. J Mol Diagn 2010; 12(5):725-9.

Stankiewicz P, Beaudet AL.(2007) Use of array CGH in the evaluation of dysmorphology, malformations, developmental delay, and idiopathic mental retardation. Curr Opin Genet Dev 2007; 17(3):182-92.

Subramonia-Iyer S, Sanderson S, Sagoo G et al.(2007) Array-based comparative genomic hybridization for investigating chromosomal abnormalities in patients with learning disability: systematic review metaanalysis of diagnostic and false-positive yields. . Genet Med 2007; 9(2):74-9.

Tammimies K, Marshall CR, Walker S, et al.(2015) Molecular diagnostic yield of chromosomal microarray analysis and whole-exome sequencing in children with autism spectrum disorder. JAMA. Sep 1 2015;314(9):895-903. PMID 26325558

The American College of Obstetricians and Gynecologists Committee Opinion Number 581, December 2013. The Use of Chromosomal Microarray Analysis in Prenatal Diagnosis. Available at www.acog.org. Last accessed March 2014.

Tsuchiya KD, Shaffer LG, Aradhya S et al.(2009) Variability in interpreting and reporting copy number changes detected by array-based technology in clinical laboratories. Genet Med 2009; 11(12):866-73.

Turner G, Boyle J, Partington MW et al.(2008) Restoring reproductive confidence in families with X-linked mental retardation by finding the causal mutation. Clin Genet 2008; 73(2):188-90.

Turner G, Boyle J, Partington MW, et al.(2008) Restoring reproductive confidence in families with X-linked mental retardation by finding the causal mutation. Clin Genet. Feb 2008;73(2):188-190. PMID 18070138

Vermeesch JR, Fiegler H, de Leeuw N et al.(2007) Guidelines for molecular karyotyping in constitutional genetic diagnosis. Eur J Hum Genet 2007; 15(11):1105-14.

Volkmar F, Siegel M, Woodbury-Smith M, et al.(2014) Practice parameter for the assessment and treatment of children and adolescents with autism spectrum disorder. J Am Acad Child Adolesc Psychiatry. Feb 2014;53(2):237-257. PMID 24472258

Volkmar F, Siegel M, Woodbury-Smith M, et al.(2014) Practice parameter for the assessment and treatment of children and adolescents with autism spectrum disorder. J Am Acad Child Adolesc Psychiatry. Feb 2014;53(2):237-257. PMID 24472258

Xiang B, Li A, Valentin D et al.(2008) Analytical and clinical validity of whole-genome oligonucleotide array comparative genomic hybridization for pediatric patients with mental retardation and developmental delay. Am J Med Genet A 2008; 146A(15):1942-54.

Yeargin-Allsopp M, Rice C, Karapurkar T et al.(2003) Prevalence of autism in a US metropolitan area. JAMA 2003; 289(1):49-55.

Zablotsky B, Black LI, Maenner MJ, et al.(2019) Prevalence and Trends of Developmental Disabilities among Children in the United States: 2009-2017. Pediatrics. Oct 2019; 144(4). PMID 31558576


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