BlueCross and BlueShield of Montana Medical Policy/Codes
Chromosomal Microarray (CMA) for the Genetic Evaluation of Patients with Developmental Delay (DD)/Intellectual Disability (ID) or Autism Spectrum Disorder (ASD)
Chapter: Genetic Testing
Current Effective Date: December 27, 2013
Original Effective Date: December 14, 2010
Publish Date: December 27, 2013
Revised Dates: March 22, 2012; December 10, 2013

Chromosomal microarray (CMA) testing has been proposed for detection of genetic imbalances in infants or children with characteristics of developmental delay/intellectual disability (DD/ID) or autism spectrum disorder (ASD).  G-banded karyotyping has for many years been the standard first-line test for this purpose.  G-banded karyotyping allows visualization and analysis of chromosomes for chromosomal rearrangements including genomic gains and losses.  CMA analysis performs a similar, although non-visual, analysis at a much higher resolution.  As a result, CMA has the potential to increase the diagnostic yield in this population and change clinical interpretation in some cases.

Children with signs of neurodevelopmental delays or disorders in the first few years of life may eventually be diagnosed with intellectual disability or autism syndromes, serious and lifelong conditions that present significant challenges to families and to public health.  Cases of DD/ID and of ASD may be associated with genetic abnormalities.  For children with clear, clinical symptoms and/or physiologic evidence of syndromic neurodevelopmental disorders, diagnoses are based primarily on clinical history and physical examination, and then may be confirmed with targeted genetic testing of specific genes associated with the diagnosed syndrome.  However, for children who do not present with an obvious syndrome, who are too young for full expression of a suspected syndrome, or who may have an atypical presentation, genetic testing may be used as a basis for establishing a diagnosis.

In published guidelines, the American Academy of Pediatrics (AAP) and the American Academy of Neurology (AAN), recommend cytogenetic evaluation to look for certain kinds of chromosomal abnormalities that may be causally related to their condition.  The AAN guidelines note that only in occasional cases will an etiologic diagnosis lead to specific therapy that improves outcomes but suggest the more immediate and general clinical benefits of achieving a specific genetic diagnosis from the clinical viewpoint, as follows (Michelson et al., 2011):

  • Limit additional diagnostic testing;
  • Anticipate and manage associated medical and behavioral comorbidities;
  • Improve understanding of treatment and prognosis; and
  • Allow counseling regarding risk of recurrence in future offspring and help with reproductive planning.

AAP and AAN guidelines also emphasize the importance of early diagnosis and intervention in an attempt to ameliorate or improve behavioral and cognitive outcomes over time.

Most commonly, genetic abnormalities associated with neurodevelopmental disorders are deletions and duplications of large segments of genomic material, called “copy number variants,” or CNVs.  For many well-described syndromes, the type and location of the chromosomal abnormality has been established with the study of a large number of cases and constitutes a genetic diagnosis; for others, only a small number of patients with similar abnormalities may exist to support a genotype-phenotype correlation.  Finally, for some patients, cytogenetic analysis will discover entirely new chromosomal abnormalities that will require additional study to determine their clinical significance.

Conventional methods of cytogenetic analysis, including karyotyping (e.g., G-banded) and fluorescence in situ hybridization (FISH), have relatively low resolution and a low diagnostic yield (i.e., proportion of tested patients found to have clinically relevant genomic abnormalities), leaving the majority of cases without identification of a chromosomal abnormality associated with the child’s condition.  CMA analysis is a newer cytogenetic analysis method that increases the chromosomal resolution for detection of CNVs, and, as a result, increases the genomic detail beyond that of conventional methods.  CMA results are clinically informative in the same way as results derived from conventional methods, and thus CMA represents an extension of standard methods with increased resolution.

CMA analysis to determine genetic etiology

CMA analysis detects CNVs by comparing a reference genomic sequence (“normal”) with the corresponding patient sequence.  Each sample has a different fluorescent label so that they can be distinguished, and both are co-hybridized to a sample of a specific reference (also normal) DNA fragment of known genomic locus.  If the patient sequence is missing part of the normal sequence (deletion) or has the normal sequence plus additional genomic material within that genomic location (e.g., a duplication of the same sequence), the sequence imbalance is detected as a difference in fluorescence intensity.  For this reason, standard CMA (non-single nucleotide polymorphisms [SNP], see following) cannot detect balanced CNVs (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.

CMA analysis uses thousands of cloned or synthesized DNA fragments of known genomic locus immobilized on a glass slide (microarray) to conduct thousands of comparative reactions at the same time.  The prepared sample and control DNA are hybridized to the fragments on the slide, and CNVs are determined by computer analysis of the array patterns and intensities of the hybridization signals.  Array resolution is limited only by the average size of the fragment used and by the chromosomal distance between loci represented by the reference DNA fragments on the slide.

There are some differences in CMA technology, most notably in the various types of microarrays.  They can differ first by construction; earliest versions were used of DNA fragments cloned from bacterial artificial chromosomes (BAC).  These have been largely replaced by oligonucleotide (oligos; short, synthesized DNA) arrays, which offer better reproducibility.  Finally, arrays that detect hundreds of thousands of single SNPs across the genome have some advantages as well.  Oligo/SNP hybrid arrays have been constructed to merge the advantages of each.  Regardless of the array components used, all microarrays allow the deposition of many thousands of short, DNA probe sequences on a small, solid surface in an orderly fashion.  The location of each known probe sequence allows the identification of the test sequence bound to it and, when compared to a control sequence, the identification of missing sequences or sequences with extra copies (i.e., CNVs).

Microarrays may be prepared by the laboratory utilizing 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 in-house developed and commercially available platforms prompted the American College of Medical Genetics (ACMG) to publish guidelines for the design and performance expectations for clinical microarrays and associated software in the postnatal setting (Kearney et al., 2011, p. 676-9)

Targeted CMA analysis provides high-resolution coverage of the genome primarily in areas containing known, clinically significant CNVs.  The ACMG guideline for designing microarrays recommends probe enrichment in clinically significant areas of the genome to maximize detection of known abnormalities but also recommends against the use of targeted arrays in the postnatal setting.  Rather, a broad genomic screen is recommended to identify atypical, complex, or completely new rearrangements, and to accurately delineate breakpoints.

Whole-genome CMA analysis has allowed the characterization of several new genetic syndromes, with other potential candidates currently under study.  However, the whole-genome arrays also have the disadvantage of potentially high numbers of apparent false-positive results, because benign CNVs are also found in phenotypically normal populations; both benign and pathogenic CNVs are continuously cataloged and to some extent made available in public reference databases to aid in clinical interpretation.  Additionally, some new CNVs are neither known to be benign nor causal; these CNVs may require detailed family history and family genetic testing to determine clinical significance and/or may require confirmation by subsequent accumulation of similar cases and so, for a time, may be considered a CNV of undetermined significance (some may eventually be confirmed true positives or causal, others false positives or benign).

To determine clinical relevance (consistent association with a disease) of CNV findings, the following actions are taken:

  • CNVs are confirmed by another method (e.g., FISH, MLPA, PCR).
  • CNVs detected are checked against public databases and, if available, against private databases maintained by the laboratory.  Known pathogenic CNVs associated with the same or similar phenotype as the patient are assumed to explain the etiology of the case; known benign CNVs are assumed to be nonpathogenic (Rodriguez-Revenga et al., 2007; Vermeesch et al., 2007; Stankiewicz and Beaudet, 2007).
  • A pathogenic etiology is additionally supported when a CNV includes a gene known to cause the phenotype when inactivated (microdeletion) or overexpressed (microduplication) (Vermeesch et al., 2007).
  • The laboratory may establish a size cutoff; potentially pathogenic CNVs are likely to be larger than benign polymorphic CNVs; cutoffs for CNVs not previously reported typically range from 300 kb to 1 Mb (Stankiewicz and Beaudet, 2007; Miller et al., 2010; Fan et al., 2007; Baldwin et al., 2008).
  • Parental studies are indicated when CNVs of appropriate size are detected and not found in available databases; CNVs inherited from a clinically normal parent are assumed to be benign polymorphisms whereas those appearing de novo are likely pathogenic; etiology may become more certain as other similar cases accrue (Rodriguez-Revenga et al., 2007; Zahir and Friedman, 2007).

ACMG has also published guidelines for the interpretation and reporting of CNVs in the postnatal setting, in order to promote consistency among laboratories and CMA results (Kearney et al., 2011, p. 680-5).  Three categories of clinical significance are recommended for reporting: pathogenic, benign, and uncertain clinical significance.

In 2008, the International Standards for Cytogenomic Arrays (ISCA) Consortium was organized (available online at <>); to date, it has established a public database containing de-identified whole genome microarray data from a subset of the ISCA Consortium member clinical diagnostic laboratories.  Array analysis was carried out on individuals with phenotypes including intellectual disability, autism, and developmental delay.  As of November 2011, there are over 28,500 total cases in the database.  Additional members are planning to contribute data; participating members use an opt-out, rather than an opt-in approach that was approved by the National Institutes of Health (NIH) and participating center institutional review boards.  The database is held at NCBI (National Center for Biotechnical Information)/NIH and curated by a committee of clinical genetics laboratory experts.

Use of the database includes an intralaboratory curation process, whereby laboratories are alerted to any inconsistencies amongst their own reported CNVs or other mutations, as well as any not consistent with the ISCA “known” pathogenic and “known” benign lists.  The intralaboratory conflict rate was initially about 3% overall; following release of the first ISCA curated track, the intralaboratory conflict rate decreased to about 1.5%.  A planned interlaboratory curation process, whereby a group of experts curates reported CNVs/mutations across laboratories, is currently in progress.

The Consortium recently proposed “an evidence-based approach to guide the development of content on chromosomal microarrays and to support interpretation of clinically significant copy number variation.”  The proposal defines levels of evidence (from the literature and/or the ISCA and other public databases) that describe how well or how poorly detected mutations or CNVs are correlated with phenotype.  The consortium will apparently coordinate a volunteer effort to describe the evidence for targeted regions across the genome.

The Consortium is also developing vendor-neutral recommendations for standards for the design, resolution, and content of cytogenomic arrays using an evidence-based process and an international panel of experts in clinical genetics, clinical laboratory genetics, genomics, and bioinformatics.

CMA analysis is commercially available from several laboratories as a laboratory-developed test.  Laboratory-developed tests performed by laboratories licensed for high-complexity testing under the Clinical Laboratory Improvement Amendments (CLIA) do not require U.S. Food and Drug Administration (FDA) clearance for marketing.

At a meeting hosted by the FDA in July 2010, the FDA indicated that the Agency will in the future require microarray manufacturers to seek clearance in order to sell their products for use in clinical cytogenetics.  Criteria for clearance, however, have not yet been published.

Diagnostic Criteria for DD/ID and ASD

Diagnostic and Statistical Manual of Mental Disorders-IV (DMS-IV) guidelines for mental retardation diagnosis include these main points:

  1. Onset before age 18; and
  2. Significant subaverage general intellectual functioning (IQ of 70 or less, or by clinical judgment of infant); and
  3. Significant limitation in adaptive functioning in at least two of the following:
    • Communication,
    • Self-care,
    • Home living,
    • Social and/or interpersonal skills,
    • Use of community resources,
    • Self-direction,
    • Functional academic skills,
    • Work,
    • Leisure,
    • Health, or
    • Safety.

Diagnostic and Statistical Manual of Mental Disorders-IV (DMS-IV) guidelines for learning disorders diagnosis include these main points:

  1. Achievement on standardized tests for reading, mathematics, or writing is substantially lower than expected for age, education level, and measured intelligence; and
  2. Lowered achievement level significantly interferes with academic achievement or activities of daily living (ADL) that require reading, mathematics, or writing; and
  3. If a concurrent sensory deficit is present, achievement is lower than would be expected to be associated with the deficit.

Diagnostic and Statistical Manual of Mental Disorders-IV (DMS-IV) guidelines for developmental coordination disorders diagnosis include these main points:

  1. Motor coordination in performance of daily activities is substantially below expected for the person’s age and measured intelligence, e.g., delays in milestones (walking, crawling, etc), clumsiness, poor handwriting, etc.; and
  2. Coordination disturbance significantly interferes with academic achievement or ADL; and
  3. Coordination disturbance is not related to a medical condition; and
  4. Coordination disturbance does not meet criteria for pervasive development disorder (PDD); and
  5. Coordination disturbance is in excess of difficulties associated with mental retardation, if present.

Diagnostic and Statistical Manual of Mental Disorders-IV (DMS-IV) guidelines for communication disorders diagnosis include these main points:

Expressive Language Disorder

  1. Scores on standardized tests are substantially below for both nonverbal intellectual capacity and receptive language development, e.g., limited vocabulary, sentences are of inappropriate length or complexity, etc); and
  2. Difficulties interfere with academic or occupational achievement, or social communication; and
  3. Does not meet criteria for mixed receptive-expressive language disorder or PDD; and
  4. Disturbance is in excess of difficulties associated with mental retardation, if present.

Mixed Receptive-Expressive Language Disorder

  1. Scores on standardized tests are substantially below for both nonverbal intellectual capacity and receptive language development, e.g., same symptoms as expressive language disorder plus difficulty understanding words, sentences, and/or types of words; and
  2. Difficulties interfere with academic or occupational achievement, or social communication; and
  3. Does not meet criteria for PDD; and
  4. Disturbance is in excess of difficulties associated with mental retardation, if present.

Phonological Disorder

  1. Failure to use expected speech sounds appropriate for age and dialect, e.g., errors in sound production, use, or organization, substituting or omitting sounds; and
  2. Difficulties interfere with academic or occupational achievement, or social communication; and
  3. Disturbance is in excess of difficulties associated with mental retardation, speech-motor or sensory deficit, or environmental deprivation, if any is present.

The following core features of ASD form the basis for diagnostic guidelines used by the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV):

  • Impaired social interaction and social development,
  • Impaired language, verbal and non-verbal communication,
  • Restrictive and repetitive behavior patterns.

Possible indicators of ASD include:

  • Does not babble, point, or make meaningful gestures by one year of age;
  • Does not speak one word by 16 months of age;
  • Does not combine two words by two years of age;
  • Loses language or social skills.

Other indicators that may be present are:

  • Does not respond to name;
  • Poor eye contact;
  • Doesn’t seem to know how to play with toys;
  • Excessively lines up toys or other objects;
  • Is attached to one particular toy or object;
  • Doesn’t smile;
  • At times seems to be hearing impaired;
  • Unprovoked aggressive or violent behavior toward self or others;
  • Problems with attention, concentration, or sleep;
  • Unusual or inappropriate responses to sensory stimuli;
  • Self-injury;
  • Property destruction;
  • Pica (a perverted appetite for substances not fit as food or of no nutritional value, e.g., clay, dried paint, starch, ice);
  • Defiance and tantrums; 
  • Not wanting to cuddle or to be cuddled; or
  • Physical over-activity or under-activity.

Children and adults with autism can exhibit any combination of these behaviors in any degree of severity.  Also, two children with the same ASD diagnosis can behave completely different from each other and have different capabilities.


Each benefit plan, summary plan description or contract defines which services are covered, which services are excluded, and which services are subject to dollar caps or other limitations, conditions or exclusions.  Members and their providers have the responsibility for consulting the member's benefit plan, summary plan description or contract to determine if there are any exclusions or other benefit limitations applicable to this service or supply.  If there is a discrepancy between a Medical Policy and a member's benefit plan, summary plan description or contract, the benefit plan, summary plan description or contract will govern.


Chromosomal microarray analysis may be considered medically necessary for diagnosing a genetic abnormality in children with apparent nonsyndromic cognitive developmental delay (DD)/intellectual disability (ID) or autism spectrum disorder (ASD), according to accepted Diagnostic and Statistical Manual of Mental Disorders-IV guidelines, when all of the following conditions (1-4) are met:

  1. Any indicated biochemical tests for metabolic disease have been performed, and results are non-diagnostic, AND
  2. FMR1 gene analysis (for Fragile X), when clinically indicated, is negative, AND
  3. In addition to a diagnosis of nonsyndromic DD/ID or ASD, the child has one or more of the following (see *Definitions below):
    • 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
  4. The results for the genetic testing have the potential to impact the clinical management of the patient.

NOTE: Before testing, the parent(s) should have engaged in face-to-face genetic counseling with a healthcare professional who has appropriate genetics training and experience.

Chromosomal microarray analysis to confirm the diagnosis of a disorder or syndrome that is routinely diagnosed based on clinical evaluation alone (see *Definitions below) is considered not medically necessary.

Chromosomal microarray analysis is considered experimental, investigational and unproven in all other cases of suspected genetic abnormality in children with DD/ID or ASD.

NOTE: For chromosomal microarray analysis for prenatal genetic testing see Medical Policy Preimplantation Genetic Testing (PGT).

* Definitions, from the American College of Medical Genetics Guideline, Evaluation of the Newborn with Single or Multiple Congenital Anomalies:

  1. A malformation refers to abnormal structural development.
  2. A major malformation is a structural defect that has a significant effect on function or social acceptability.  Examples include ventricular septal defect or a cleft lip.
  3. A minor malformation is a structural abnormality that has minimal effect on function or societal acceptance.  Examples include preauricular ear pit or partial syndactyly (fusion) of the second and third toes.
  4. 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.

Policy Guidelines

Effective in 2012, there are specific CPT codes for this testing:  81228 and 81229

Codes 81228 and 81229 cannot be reported together.

This testing might also be reported using a combination of molecular diagnostic codes (83890-83913) and array-based evaluation of molecular probes codes (88384-88386).


This policy is based on a Blue Cross Blue Shield Association (BCBSA) Technology Evaluation Center (TEC) Special Report on array comparative genomic hybridization (aCGH).  Since that TEC Report was written, the technology has rapidly increased in resolution, and chromosomal microarray (CMA) has become the term of general use to accommodate all variations in the technology.  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 two to three years ago indicated that there is a lack of consensus between laboratories in the interpretation and reporting of copy number variants (CNVs), particularly those that are challenging (Tsuchiya et al., 2009).  The International Standards for Cytogenomic Arrays (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 intellectual disability.

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 et al., 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 five metropolitan Atlanta counties, had cognitive impairment.  The evaluation pathway depends on the pediatrician, consulting specialists, and their consensus on the primary neurodevelopmental diagnosis.

Post-natal CMA analysis

Several studies have conducted CMA analysis on samples with known chromosomal abnormalities by standard karyotyping (BCBSA TEC Report, 2009).  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 kilobases (Kb) for 10 selected cases with different known chromosomal abnormalities (Xiang and Valentin, 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 (BCBSA TEC Report, 2009).  Overall, diagnostic yield ranged from 5% to 16.7% in DD/ID 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 average diagnostic yield of 12.2% across 33 studies (Miller et al., 2010).  Hochstenback et al. (2009) reported a CMA diagnostic yield of 19% for 36,325 DD/ID cytogenetic referrals in the Netherlands; and Shen et al. (2010) reported a 7% diagnostic yield among 933 ASD referrals.  Cooper et al. (2011) 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.  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 (Hochstenback et al., 2009; Rauch et al., 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, et al., 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 et al., 2010).

Neither standard cytogenetic nor CMA analysis have been systematically studied for impact on clinical outcomes other than diagnosis (Subramonia-lyer, et al., 2007; Moeschler and Shevell, 2006); Schaefer and Mendelsohn (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 and Shevell, 2006).  Two studies indirectly addressed clinical outcomes other than diagnosis as a result of CMA analysis.

Saam et al. (2008) interviewed 14 physicians (two 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 ID and normal karyotypes.  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.

Coulter et al. (2011) 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.  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 1,792 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 et al., 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 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. (2008) studied the reproductive decisions of women from 38 families characterized by male members with and a pattern consistent with chromosome X-linked transmission.  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 mental retardation/intellectual disability.  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., (2008) 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.

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 et al., 1999).  Velo-cardio-facial syndrome is also associated with heart defects (Freitag et al., 2010).  Klinefelter syndrome may first be detected as developmental delay in early childhood; androgen treatment is an important component of therapy (Freitag et al., 2010).  CMA analysis may also predict future conditions for which interventions are possible.  In a report of three 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 et al., 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 (Duchenne muscular dystrophy) 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 et al., 2011).

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, et al., 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 and Hudgins, 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:

  • Multiple anomalies not specific to a well-delineated genetic syndrome
  • Apparently non-syndromic developmental delay/ intellectual disability
  • 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 et al., 2011, p.676-9) and for the interpretation and reporting of CNVs, (Kearney et al., 2011, p. 680-5) both intended for the postnatal 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 et al., 2010).


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 DD/ID, or suspected ASD 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.  As a result, chromosomal microarray analysis may be considered medically necessary in individuals with developmental delay or autism spectrum disorders who meet the clinical criteria defined the Coverage section.


Disclaimer for coding information on Medical Policies           

Procedure and diagnosis codes on Medical Policy documents are included only as a general reference tool for each policy.  They may not be all-inclusive.           

The presence or absence of procedure, service, supply, device or diagnosis codes in a Medical Policy document has no relevance for determination of benefit coverage for members or reimbursement for providers.  Only the written coverage position in a medical policy should be used for such determinations.           

Benefit coverage determinations based on written Medical Policy coverage positions must include review of the member’s benefit contract or Summary Plan Description (SPD) for defined coverage vs. non-coverage, benefit exclusions, and benefit limitations such as dollar or duration caps.

ICD-9 Codes

299.00, 299.01, 315.00-315.9, 317-319

ICD-10 Codes

F70-F79, F80.0-F80.9, F82, F84.0, F88, F89, H93.25, R48.0

Procedural Codes: 81228, 81229, S3870
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  2. American College of Medical Genetics (ACMG).  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 .  (accessed 2011 December).
  3. Yeargin-Allsopp M, Rice C, Karapurkar T et al.  Prevalence of autism in a US metropolitan area.  JAMA 2003; 289(1):49-55. 
  4. Moeschler JB, Shevell M.  Clinical genetic evaluation of the child with mental retardation or developmental delays.  Pediatrics 2006; 117(6):2304-16. 
  5. Rauch A, Hoyer J, Guth S et al.  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. 
  6. Rodriguez-Revenga L, Mila M, Rosenberg C et al.  Structural variation in the human genome: the impact of copy number variants on clinical diagnosis.  Genetics in Medicine: Official Journal of the American College of Medical Genetics 2007; 9(9):600-6.
  7. Vermeesch JR, Fiegler H, de Leeuw N et al.  Guidelines for molecular karyotyping in constitutional genetic diagnosis.  Eur J Hum Genet 2007; 15(11):1105-14.
  8. Stankiewicz P, Beaudet AL.  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. 
  9. Fan YS, Jayakar P, Zhu H et al.  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. 
  10. Zahir F, Friedman JM.  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. 
  11. Subramonia-Iyer S, Sanderson S, Sagoo G et al.  Array-based comparative genomic hybridization for investigating chromosomal abnormalities in patients with learning disability: systematic review meta-analysis of diagnostic and false-positive yields.  Genetics in Medicine: Official Journal of the American College of Medical Genetics 2007; 9(2):74-9. 
  12. Caronna EB, Milunsky JM, Tager-Flusberg H.  Autism spectrum disorders: clinical and research frontiers.  Arch Dis Child 2008; 93(6):518-23. 
  13. Xiang B, Li A, Valentin D et al.  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. 
  14. Schaefer GB, Mendelsohn NJ.  Clinical genetics evaluation in identifying the etiology of autism spectrum disorders.  Genetics in Medicine: Official Journal of the American College of Medical Genetics 2008; 10(4):301-5. 
  15. Saam J, Gudgeon J, Aston E et al.  How physicians use array comparative genomic hybridization results to guide patient management in children with developmental delay.  Genetics in medicine: official journal of the American College of Medical Genetics 2008; 10(3):181-6. 
  16. Baldwin EL, Lee JY, Blake DM et al.  Enhanced detection of clinically relevant genomic imbalances using a targeted plus whole genome oligonucleotide microarray.  Genetics in medicine : official journal of the American College of Medical Genetics 2008; 10(6):415-29. 
  17. Turner G, Boyle J, Partington MW et al.  Restoring reproductive confidence in families with X-linked mental retardation by finding the causal mutation.  Clin Genet 2008; 73(2):188-90. 
  18. Adam MP, Justice AN, Schelley S et al.  Clinical utility of array comparative genomic hybridization: uncovering tumor susceptibility in individuals with developmental delay.  J Pediatr 2009; 154(1):143-6. 
  19. ACOG Committee Opinion No.  446: array comparative genomic hybridization in prenatal diagnosis.  Obstetrics and gynecology 2009; 114(5):1161-3. 
  20. Array Comparative Genomic Hybridization (aCGH) for the Genetic Evaluation of Patients with Developmental Delay/Mental Retardation and Autism Spectrum Disorder.  TEC Special Report.  Chicago, Illinois: Blue Cross Blue Shield Association Technology Evaluation Center Assessment Program  2009; 24(10). 
  21. Tsuchiya KD, Shaffer LG, Aradhya S et al.  Variability in interpreting and reporting copy number changes detected by array-based technology in clinical laboratories.  Genetics in medicine : official journal of the American College of Medical Genetics 2009; 11(12):866-73. 
  22. Moeschler JB.  Genetic evaluation of intellectual disabilities.  Semin Pediatr Neurol 2008; 15(1):2-9. 
  23. Hochstenbach R, van Binsbergen E, Engelen J et al.  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. 
  24. Mefford HC.  Genotype to phenotype-discovery and characterization of novel genomic disorders in a "genotype-first" era.  Genetics in Medicine: Official Journal of the American College of Medical Genetics 2009; 11(12):836-42. 
  25. Schluth-Bolard C, Delobel B, Sanlaville D et al.  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. 
  26. South ST, Rector L, Aston E et al.  Large clinically consequential imbalances detected at the breakpoints of apparently balanced and inherited chromosome rearrangements.  J Mol Diagn 2010; 12(5):725-9. 
  27. Freitag CM, Staal W, Klauck SM et al.  Genetics of autistic disorders: review and clinical implications.  Eur Child Adolesc Psychiatry 2010; 19(3):169-78. 
  28. Manning M, Hudgins L.  Array-based technology and recommendations for utilization in medical genetics practice for detection of chromosomal abnormalities.  Genetics in Medicine: Official Journal of the American College of Medical Genetics 2010; 12(11):742-5.
  29. Miller DT, Adam MP, Aradhya S et al.  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. 
  30. Shen Y, Dies KA, Holm IA et al.  Clinical genetic testing for patients with autism spectrum disorders.  Pediatrics 2010; 125(4):e727-35. 
  31. Cooper GM, Coe BP, Girirajan S et al.  A copy number variation morbidity map of developmental delay.  Nature genetics 2011; 43(9):838-46. 
  32. Coulter ME, Miller DT, Harris DJ et al.  Chromosomal microarray testing influences medical management.  Genetics in Medicine: Official Journal of the American College of Medical Genetics 2011; 13(9):770-6. 
  33. Kearney HM, Thorland EC, Brown KK et al.  American College of Medical Genetics standards and guidelines for interpretation and reporting of postnatal constitutional copy number variants.  Genetics in Medicine: Official Journal of the American College of Medical Genetics 2011; 13(7):680-5. 
  34. Hillman SC, Pretlove S, Coomarasamy A et al.  Additional information from array comparative genomic hybridization technology over conventional karyotyping in prenatal diagnosis: a systematic review and meta-analysis.  Ultrasound in obstetrics & gynecology: the official journal of the International Society of Ultrasound in Obstetrics and Gynecology 2011; 37(1):6-14. 
  35. Michelson DJ, Shevell MI, Sherr EH et al.  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.
  36. Kearney HM, South ST, Wolff DJ et al.  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.  Genetics in Medicine: Official Journal of the American College of Medical Genetics 2011; 13(7):676-9.
  37. Chromosomal Microarray (CMA) for the Genetic Evaluation of Patients with Developmental Delay (DD)/Intellectual Disability (ID) or Autism Spectrum Disorder (ASD).  Chicago, Illinois: Blue Cross Blue Shield Association Medical Policy Reference Manual 2011 December; Medicine 2.04.59.
June 2010 Medical Policy Development meeting
July 2010 Medical Policy Physician's Committee Meeting/approved 
March 2012  Policy updated with literature search; references 1, 2, 6, 10, 19, 20, 24, 29, 30, 33, 35 added. Term “array comparative genomic hybridization (aCGH)” changed to “chromosomal microarray (CMA) analysis” in title, policy statements, and text. Policy statements changed to medically necessary for infants and children with developmental delay, intellectual disability, or autism spectrum disorder under certain conditions; investigational for all other indications. Modified statement about specific types of genetic counselors to a more general description and the term “mental retardation” changed to “intellectual disability” throughout and in the title. 
December 2013 Policy formatting and language revised.  Coverage unchanged.
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Chromosomal Microarray (CMA) for the Genetic Evaluation of Patients with Developmental Delay (DD)/Intellectual Disability (ID) or Autism Spectrum Disorder (ASD)