National Medical Policy

National Medical Policy Subject: Policy Number: Single Nucleotide Polymorphism (SNP) Chromosomal Microarray Analysis for Prenatal Testing and Intellectual Disability, Developmental Delay, and Multiple Congenital Anomalies NMP516 Effective Date*: December 2012 Updated: January 2016 This National Medical Policy is subject to the terms in the IMPORTANT NOTICE at the end of this document For Medicaid Plans: Please refer to the appropriate State s Medicaid manual(s), publication(s), citation(s), and documented guidance for coverage criteria and benefit guidelines prior to applying Health Net Medical Policies The Centers for Medicare & Medicaid Services (CMS) For Medicare Advantage members please refer to the following for coverage guidelines first: Use Source Reference/Website Link National Coverage Determination (NCD) National Coverage Manual Citation Local Coverage Determination (LCD)* Article (Local)* X Other Palmetto GBA. MolDX. Molecular Diagnostic Services Program: http://www.palmettogba.com/palmetto/moldx.nsf/do cscathome/moldx None Use Health Net Policy Instructions Medicare NCDs and National Coverage Manuals apply to ALL Medicare members in ALL regions. Medicare LCDs and Articles apply to members in specific regions. To access your specific region, select the link provided under Reference/Website and follow the search instructions. Enter the topic and your specific state to find the coverage determinations for your region. *Note: Health Net must follow local coverage determinations (LCDs) of Medicare Administration Contractors (MACs) located outside their service area when those MACs have exclusive coverage of an item or service. (CMS Manual Chapter 4 Section 90.2) Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 1

If more than one source is checked, you need to access all sources as, on occasion, an LCD or article contains additional coverage information than contained in the NCD or National Coverage Manual. If there is no NCD, National Coverage Manual or region specific LCD/Article, follow the Health Net Hierarchy of Medical Resources for guidance. Current Policy Statement (Please refer the Health Net NMP on Comparative Genomic Hybridization) Health Net Inc. considers chromosomal microarray analysis (CMA), which includes single nucleotide polymorphism (SNP) and comparative genomic hybridization (CGH) testing, as medically necessary in any of the following situations*: 1. In patients with a fetus with one or more major structural abnormalities identified in ultrasonographic examination and who are undergoing invasive prenatal diagnosis. This test replaces the need for fetal karyotype. 2. In patients with a structurally normal fetus undergoing invasive prenatal diagnostic testing; (In this situation, either fetal karyotyping or a CMA can be performed). 3. In cases of intrauterine fetal demise or stillbirth when further cytogenetic analysis is desired, fetal tissue testing, (i.e., amniotic fluid, placenta, or products of conception) is recommended because of its increased likelihood of obtaining results and improved detection of causative abnormalities. 4. For the diagnostic evaluation of post-natal genetic abnormality in children with developmental delay (DD), intellectual delay (ID), or autism spectrum disorder (ASD) only if the examination is suggestive of an inherited disease or the results will have an impact on the member s subsequent treatment plan, pregnancy planning, or family member genetic counseling. Important Notes: 1. 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. 2. Comprehensive patient pretest and posttest genetic counseling from qualified personnel such as a genetic counselor or geneticist regarding the benefits, limitations, and test results, is essential. Not Medically Necessary Health Net, Inc. considers chromosomal microarray analysis (CMA) which includes SNP and CGH, not medically necessary to evaluate first-trimester and secondtrimester pregnancy losses, since limited data are available on the clinical utility of this testing. *Note: Chromosomal microarray analysis should not be ordered without informed consent, which should be documented in the medical record and include discussion of the potential to identify findings of uncertain significance, nonpaternity, consanguinity, and adult-onset disease. (The recommendations noted above are from ACOG, 2013) Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 2

Definitions DD Developmental delay ID Intellectual disability MCA Multiple congenital anomalies FISH Fluorescence in situ hybridization acgh Comparative genomic hybridization SNP` Single nucleotide polymorphism UPD Uniparental disomy CNV Copy number variants GDD Global developmental delay CMA Cytogenetic microarray Codes Related To This Policy NOTE: The codes listed in this policy are for reference purposes only. Listing of a code in this policy does not imply that the service described by this code is a covered or noncovered health service. Coverage is determined by the benefit documents and medical necessity criteria. This list of codes may not be all inclusive. On October 1, 2015, the ICD-9 code sets used to report medical diagnoses and inpatient procedures have been replaced by ICD-10 code sets. ICD-9 Codes 299.00 299.01 Autistic disorder 317-319 Mental Retardation 632 Missed abortion 634.01-639.9 Other pregnancy with abortive outcome 655.10-655.13 Chromosomal abnormality in fetus 740.0 759.0 Congenital anomalies 783.40-783.42 Lack of expected normal physiologic development 795.2 Nonspecific abnormal findings on chromosomal analysis V27.1 - V27.9 Outcomes of delivery. Single multiple births with stillborn V28.0 V28.9 Encounter for antenatal screening of mother V79.2 Special screening for mental retardation V82.71 V82.79 Genetic screening V82.89 Special screening for other specified conditions ICD-10 Codes F70-F79 Intellectual Disabilities F80.0-F89 Pervasive and specific developmental disorders F84.0-F84.9 Autistic disorder O02.1 Missed abortion Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 3

ICD-10 Codes O03.30-003.9 Spontaneous abortion O35.1XX0- Maternal care for (suspected) chromosomal abnormality in O35.9XX0 fetus, not applicable or unspecified QØØ.Ø-Q07.00 Congenital malformations of the nervous system Q10.0-Q18.9 Congenital malformations of eye, ear, face and neck R62.50-R62.51 Other and unspecified lack of expected normal physiological developments in childhood Z13.4 Encounter for screening for certain developmental disorders in childhood Z13.71-Z13.79 Encounter for screening for genetic and chromosomal anomalies Z36 Encounter for antenatal screening of mother Z37.1-Z37.9 Outcome of delivery. Single stillbirth multiple births. Some live, some stillbirths CPT Codes 81228 Cytogenetic constitutional (genome-wide) microarray analysis; Interrogation of genomic regions for copy number variants (eg, Bacterial Artificial Chromosome (BAC) or oligobased comparative genomic hybridization (CGH) microarray analysis 81229 Cytogenetic constitutional (genome-wide) microarray analysis; interrogation of genomic regions for copy number and single nucleotide polymorphism (SNP) variants for chromosomal abnormalities. HCPCS Codes N/A N/A Scientific Rationale Update January 2016 Per the American College of Obstetricians and Gynecologists (ACOG, Number 11, 2014), the Technology Assessment if Obstetrics and Gynecology, notes: In contrast to the conventional karyotype, which can detect genetic abnormalities that result from changes in the number or structure of chromosomes, microarray analysis can provide information at the submicroscopic level, demonstrating duplications and deletions of DNA throughout the human genome. DNA microarray technology is a molecular method used to study gene expression. Duplicated or deleted sections of DNA are known as copy number variants; the high resolution of chromosomal microarray analysis enables the detection of copy number variants that are 1/100 the size of those identified by current conventional G-banded karyotyping. It can be used to identify cytogenetic changes in tumors, to characterize subtle unbalanced translocations, to identify the origin of marker or supernumerary chromosomes, and to detect intrachromosomal duplications or deletions. With comparative genomic hybridization (CGH), the fetal DNA is labeled with one color of fluorescent dye, whereas the validated, control DNA is labeled with another color. Arrays of cdna clones are spotted onto a glass slide, known as the array, and hybridized with labeled cdna prepared from the tissue of interest. The more the gene is expressed in the tissue, the more intense the hybridization signal. The relative intensity of the different colors, and therefore relative DNA content of fetal versus control DNA, is compared. Scientific Rationale Update January 2015 A Blue Cross Blue Shield Technology Evaluation Center Special Report: Array Comparative Genomic Hybridization (acgh) for the Genetic Evaluation of Patients Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 4

with Developmental Delay/Mental Retardation and Autism Spectrum Disorder, updated October 2014, reported: Clinical utility is determined by the impact of a genetic diagnosis on outcomes that matter to the patient and family. Several outcomes are regarded as important in the setting of DD/MR or ASD, including estimation of recurrence rate for reproductive decision-making, avoidance of additional diagnostic tests and specialist consultations, and early and improved access to behavioral and educational services. However, neither standard cytogenetic analysis nor acgh have been systematically studied for impact on these kinds of outcomes. Rather, clinical utility of genetic testing is primarily inferred based on the value of knowledge to the family, estimation of recurrence risk, and on the importance of early detection and early intervention. In addition, the special report noted that current guidelines for early assessment of DD/MR and for ASD recommend genetic evaluation for those cases that cannot be readily diagnosed from clinical characteristics or other specific tests. Conventional cytogenetic analysis (e.g., G- banded karyotype, specific FISH assays, and subtelomeric screening) has been routinely used for many years, but has low resolution and low diagnostic yield. Array CGH specifically detects CNVs, which account for the majority of genomic abnormalities currently detectable by conventional cytogenetic testing. Array CGH does not detect balanced translocations or inversions, which account for a minority of clinically important genomic abnormalities. However, acgh has shown that a substantial proportion of apparently balanced translocations by conventional methods contain submicroscopic deletions (i.e., are actually unbalanced). CGH arrays have the advantage of greatly improved resolution, which allows detection of smaller, clinically significant genomic abnormalities not detectable by conventional assays (improving diagnostic yield), and more exact locus definition of conventionally detectable abnormalities (improving information for genotypephenotype correlation). While acgh technology is relatively new, the results are conceptually similar to those obtained by conventional methods, and should be evaluated as an extension of those methods. The results of neither conventional cytogenetic evaluation nor of acgh evaluation have been systematically studied for impact on patient outcomes other than diagnostic yield, which is an intermediate outcome. Impact of testing on the kinds of outcomes that matter to the patient and family has been directly addressed in very few studies. Thus, it is not possible to draw evidence-based conclusions regarding the clinical utility of acgh genetic evaluation. The same may also be said of conventional cytogenetic evaluation. Li et al (2014) investigated clinically relevant copy number variations (CNV) in patients with unexplained mental retardation/developmental delay (MR/DD) through chromosomal microarray analysis (CMA). Sixty-six patients with unexplained MR/DD were analyzed with CMA. All identified CNVs were verified with database of genomic variations (DGV), DECIPHER, ISCA and the literature. Nineteen clinically relevant CNVs were detected among the 16 individuals. The diagnostic yield for the MR/DD patients was 24.2%. The most common abnormality was Phelan-McDermid syndrome (3/16, 18.8%), which was followed by Prader-Willi syndrome/angelman syndrome (2/16, 12.5%) and Wolf-Hirschhorn syndrome (2/16, 12.5%). The authors concluded CNVs are one of the most common causes for unexplained MR/DD. CMA can improve the detection rate of CNVs and confer genetic testing with greater sensitivity in elucidating the diagnosis for unexplained MR/DD. Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 5

A review by Xu et al (2014) compared the accuracy of prenatal diagnosis for abnormal chromosome diseases by chromosome microarray technology and karyotyping. The studies obtained were filtered by using the QUADAS tool, and studies conforming to the quality standard were fully analyzed. There was one paper conforming to the QUADAS standards including 4406 gravidas with adaptability syndromes of prenatal diagnosis including elderly parturient women, abnormal structure by type-b ultrasound, and other abnormalities. Microarray technology yielded successful diagnoses in 4340 cases (98.8%), and there was no need for tissue culture in 87.9% of the samples. All aneuploids and non-parallel translocations in 4282 cases of non-chimera identified by karyotyping could be detected using microarray analysis technology, whereas parallel translocations and fetal triploids could not be detected by microarray analysis technology. In the samples with normal karyotyping results, type-b ultrasound showed that 6% of chromosomal deficiencies or chromosome duplications could be detected by microarray technology, and the same abnormal chromosomes were detected in 1.7% of elderly parturient women and samples with positive serology screening results. The reviewers concluded in the prenatal diagnosis test, compared with karyotyping, microarray technology could identify the extra cell genetic information with clinical significance, aneuploids, and non-parallel translocations; however, its disadvantage is that it could not identify parallel translocations and triploids. Tobler et al (2014) compared single nucleotide polymorphism (SNP) and comparative genomic hybridization (acgh) microarray platforms to evaluate embryos for parental translocation imbalances and aneuploidy. A retrospective review of preimplantation genetic diagnosis and screening (PGD/PGS) results of 498 embryos from 63 couples undergoing 75 in vitro fertilization cycles due to parental carriers of a reciprocal translocation was performed. There was no significant difference between SNP and acgh microarrays when comparing the prevalence of embryos that were euploid with no translocation imbalance, euploidy with a parental translocation imbalance or aneuploid with or without the parental chromosome imbalance. The clinical pregnancy rates were also equivalent for SNP (60 %) versus acgh (65 %) microarrays. Of 498 diagnosed embryos, 45 % (226/498) were chromosomally normal without translocation errors or aneuploidy, 22 % (112/498) were euploid but had a parentally derived unbalanced chromosomal segregant, 8 % (42/498) harbored both a translocation imbalance and aneuploidy and 24 % (118/498) of embryos were genetically balanced for the parental reciprocal translocation but were aneuploid for other chromosomes. The overall clinical pregnancy rate per IVF cycle following SNP or acgh microarray analysis was 61 % and was higher if the biopsy was done on blastocysts (65 %) versus cleavage stage embryos (59 %), although not statistically significant. The reviews concluded SNP or acgh microarray technologies demonstrate equivalent clinical findings that maximize the pregnancy potential in patients with known parental reciprocal chromosomal translocations. Levy et al (2014) sought to report the full cohort of identifiable anomalies, regardless of known clinical significance, in a large-scale cohort of postmiscarriage products-ofconception samples analyzed using a high-resolution single-nucleotide polymorphism (SNP)-based microarray platform. High-resolution chromosomal microarray analysis allows for the identification of visible and submicroscopic cytogenomic imbalances; the specific use of SNPs permits detection of maternal cell contamination, triploidy, and uniparental disomy. Miscarriage specimens were sent to a single laboratory for cytogenomic analysis. Chromosomal microarray analysis was performed using a SNP-based genotyping microarray platform. Results were evaluated at the cytogenetic and microscopic (greater than 10 Mb) and submicroscopic (less than 10 Mb) levels. Maternal cell contamination was assessed using information derived from fetal and maternal SNPs. Results were obtained on 2,389 of 2,392 specimens (99.9%) that were less than 20 weeks of gestation. Maternal cell contamination was Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 6

identified in 528 (22.0%) specimens. The remaining 1,861 specimens were considered to be of true fetal origin. Of these, 1,106 (59.4%) showed classical cytogenetic abnormalities: aneuploidy accounted for 945 (85.4%), triploidy for 114 (10.3%), and structural anomalies or tetraploidy for the remaining 47 (4.2%). Of the 755 (40.6%) cases considered normal at the cytogenetic level, SNP chromosomal microarray analysis revealed a clinically significant copy number change or wholegenome uniparental disomy in 12 (1.6%) and three (0.4%) cases, respectively. The authors concluded chromosomal microarray analysis of products-of-conception specimens yields a high diagnostic return. Using SNPs extends the scope of detectable genomic abnormalities and facilitates reporting "true" fetal results. This supports the use of SNP chromosomal microarray analysis for cytogenomic evaluation of miscarriage specimens when clinically indicated. Romero et al (2014) sought to characterize the proportion and type of genetic abnormalities in early pregnancy losses at different developmental stages; and hypothesized that these rates will differ. Women with pregnancy loss<20weeks gestation (n=86) were enrolled at the time of diagnosis. Maternal tissue without a fetal component was found in 13 samples, and one sample of monochorionic twins was treated as a single sample. An additional 9 samples were excluded from analysis due to 100% maternal cell contamination. Chromosomal microarray analysis (CMA) was performed on 64 samples. These included 15 pre-embryonic (no visible embryo on ultrasound), 31 embryonic (embryo measuring 60/7-96/7 weeks), and 27 fetal (100/7-196/7 weeks) losses. The overall rate of genetic abnormalities differed across developmental stages (9% pre-embryonic; 69.2% embryonic; 33.3% fetal, p<0.01). This difference persisted when comparing pre-embryonic to embryonic (p<0.01) and embryonic to fetal (p=0.02) but not pre-embryonic to fetal (p=0.12). The rate of aneuploidy also differed significantly across developmental stages (0% pre-embryonic vs 69.2% embryonic vs 25.9% fetal, p<0.001). Abnormalities were most common in embryonic cases, followed by fetal and then pre-embryonic. Maternal cell contamination (MCC) was noted in 47% of 46, XX cases assessed. The authors concluded genetic abnormalities detected by CMA are more likely to occur in the embryonic period compared to pre-embryonic or fetal stages. MCC is common in early pregnancy loss and should be excluded when results demonstrate 46,XX. Scientific Rationale Update January 2014 Chromosomal microarray analysis (CMA) which includes both comparative genetic hybridization and single nucleotide polymorphism arrays, have been shown in studies to have a higher diagnostic efficiency compared to routine chromosomal analysis for the identification of chromosomal aberrations. CMA has replaced florescence in situ hybridization based methods since it is efficient in identifying smaller rearrangements at FISH level of resolution. Therefore, CMA has been recommended by expert panels as the first tier testing for individuals with developmental delay, intellectual disability and/or multiple congenital anomalies in cases where there is no evidence of recognizable genetic syndromes. The American College of Medical Genetics (ACMG 2013 revisions) notes the following: Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 7

CMA has emerged as a powerful tool for clinical genetic testing. Currently, two methods of CMA are used in the clinical setting. Array-comparative genomic hybridization and single-nucleotide polymorphism arrays use different techniques to scan the genome for copy-number variants (CNVs). With the increased number of CMA studies, new information has emerged regarding the contribution of genome CNVs in autism spectrum disorders (ASDs). Estimates of CNV frequencies in unselected populations of individuals with an ASD are from 8 to 21%. Given this diagnostic yield, we have moved CMA to a first-tier test in place of a karyotype, as suggested in the 2008 guidelines. This is in keeping with recent consensus opinion that CMA is a first-tier test for individuals with developmental disabilities or congenital anomalies. Scientific Rationale Update December 2013 Genomic disorders are diseases that result from the loss or gain of chromosomal or DNA material. The most common genomic disorders are divided in two main categories, those resulting from copy number losses (i.e., deletion syndromes) and copy number gains (i.e., duplication syndromes). Chromosomal microarray analysis (CMA) has emerged as a powerful new tool to identify genomic abnormalities associated with a wide range of developmental disabilities including congenital malformations, cognitive impairment, and behavioral abnormalities. At this time, two main types of microarray-based chromosome tests or CMA are available for use in clinical diagnostics, array-based comparative genomic hybridization (acgh), also known as chromosome microarray or microarray-based comparative genomic hybridization, and single nucleotide polymorphism (SNP) microarray analysis or testing. These two tests significantly increase the detection rate in both prenatal and postnatal cases. Array comparative genomic hybridization (array CGH), also known as chromosome microarray or microarray-based comparative genomic hybridization, is the gold standard laboratory test for the detection of copy number variants (CNVs) that cause genomic disorders. The frequency of disease-causing CNVs is highest (20%-25%) in children with moderate to severe intellectual disability accompanied by malformations or dysmorphic features. Disease-causing CNVs are found in 5%-10% of cases of autism, being more frequent in severe phenotypes. CMA has replaced Giemsabanded karyotype as the first-tier test for genetic evaluation of children with developmental and behavioral disabilities. CMA is also known as molecular karyotyping, microarray-based genomic copy-number analysis or array-based comparative genomic hybridization (acgh). The use of CMA leads to a genetic diagnosis in 15 to 20% of patients with unexplained ID, which is substantially higher than chromosomal karyotyping. The higher yield of CMA is primarily because of its higher sensitivity for submicroscopic deletions and duplications. CMA provides much higher resolution than chromosomal karyotyping, identifying more genetic conditions, including single nucleotide polymorphisms (SNP). Chromosome abnormalities are a common cause of developmental delay (DD), intellectual disability (ID), multiple congenital anomalies (MCA), and other neurodevelopmental disorders. However, traditional cytogenetic techniques, such as karyotype analysis, will identify a chromosome abnormality in fewer than 10% of individuals with clinical features suggestive of a genetic syndrome. Standard Karyotype analysis identifies a chromosome abnormality in only 5% -10% of fetuses undergoing prenatal testing because of an increased risk of a chromosome disorder. Intellectual disability (ID) is a term synonymous with and is now preferred over the older term, mental retardation. It is a static encephalopathy with multiple etiologies Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 8

that encompasses a broad spectrum of functioning, disability, and strengths. The term global developmental delay is usually used to describe children younger than age five with significant cognitive deficits, because intelligence quotient (IQ) testing is less reliable in this age group; the cognitive deficits may be accompanied by other developmental deficits as well. In 2007 the American Association on Mental Retardation (AAMR) changed its name to the American Association on Intellectual and Developmental Disabilities (AAIDD). The AAIDD encourages the use of the term "intellectual disability" in place of "mental retardation" but stresses that the terms are synonymous. Some laboratories incorporate specific algorithms in their processing to better detect triploidy, either through the use of single nucleotide polymorphisms (SNP) arrays or through an initial assessment of a limited number of cells by fluorescence in situ hybridization (FISH). The American Academy of Neurology (AAN, 2013), completed a policy on Chromosomal Microarray Analysis for Intellectual Disabilities. It notes that the chromosomal microarray is able to detect copy number variants with much finer resolution and is not reliant on staining and visual resolution limits. The modern chromosomal microarray instead uses oligonucleotides of about 80 bases in length to target specific, matching regions of the genome. Absent or duplicated targets, or regions of the subjects DNA is thereby easily detected. These more refined tests have made it possible to routinely detect smaller deletions and duplications (CNVs) of less than 50 thousand bases. Other than a few very specific circumstances, microarrays are far superior to the traditional Kayrotype in sensitivity and diagnostic yield. Chromosomal microarray testing is technically referred to as the array comparative genomic hybridization (acgh). Patients with intellectual disabilities (ID) and dysmorphic features are the potential beneficiaries from the results of CMA testing. Per Pivalizza, (UpToDate, 2013) The optimal order or timing of tests to identify the etiology of intellectual disability (ID) is not certain. The staged approach and assessments recommended by the practice parameter of the American Academy of Neurology and the Child Neurology Society for the evaluation of the child with global developmental delay is noted below: Complete history and physical examination Perform comprehensive developmental assessment, including ntellectual and adaptive testing Complete vision and auditory screening Review newborn screening results Blood lead screening Perform a chromosomal microarray (CMA, also known as genomic microarray analysis) in all children with ID, unless a specific syndrome is suspected based on phenotypic characteristics and diagnosed by specific testing. (If CMA is not available, then a G-banded karyotype is an appropriate substitute). Blue Cross, Blue Shield Association, Technology Evaluation Center (TEC, 2009) completed an executive summary on a Special Report: Array Comparative Genomic Hybridization (acgh) for the Genetic Evaluation of Patients with Developmental Delay/Mental Retardation and Autism Spectrum Disorder. It notes the following: Authors comments and conclusions: Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 9

Current guidelines for early assessment of DD/MR and for ASD recommend genetic evaluation for those cases that cannot be readily diagnosed from clinical characteristics or other specific tests. Array CGH specifically detects CNVs, which account for the majority of genomic abnormalities currently detectable by conventional cytogenetic testing. Array CGH does not detect balanced translocations or inversions, which account for a minority of clinically important genomic abnormalities. CGH arrays have the advantage of greatly improved resolution, which allows detection of smaller, clinically significant genomic abnormalities not detectable by conventional assays (improving diagnostic yield), and more exact locus definition of conventionally detectable abnormalities (improving information for genotype-phenotype correlation). While acgh technology is relatively new, the results are conceptually similar to those obtained by conventional methods, and should be evaluated as an extension of those methods. The results of neither conventional cytogenetic evaluation nor of acgh evaluation have been systematically studied for impact on patient outcomes other than diagnostic yield, which is an intermediate outcome. Impact of testing on the kinds of outcomes that matter to the patient and family has been directly addressed in very few studies. Thus, it is not possible to draw evidence-based conclusions regarding the clinical utility of acgh genetic evaluation. The same may also be said of conventional cytogenetic evaluation. Expert consensus and clinical guidelines state that genetic information is of value because it establishes a causal explanation that is helpful to families. It is suggested that such genetic information avoids additional consultations and various types of diagnostic tests, assists with early and improved access to community services that may ameliorate or improve behavioral and cognitive outcomes, provides estimates of recurrence rates to better guide reproductive decision-making, and enables an understanding of prognosis and future needs. However, little evidence supports these outcomes. Array CGH technology is rapidly evolving and different kinds of arrays with different capabilities of detecting genomic abnormalities are clinically available from different laboratories; it is up to the ordering physician to know the limits of the particular technology employed by the laboratory. Some have called for broader efforts to standardize protocols, define quality criteria for successful analysis, and develop reporting guidelines; in addition, a national multicenter trial to address accuracy, indications, and efficacy has been suggested. Currently, a consortium of scientists from academic cytogenetics laboratories have agreed to develop a uniform, evidence-based Molecular Karyotype and shared national database to accumulate data on pathogenic versus benign deletions and duplications in the human genome. Such cooperative efforts should lead to more comparable results across platforms, more complete databases to aid in individual results interpretation, more uniform reporting, and more rapid accumulation of genotype-phenotype correlation information for future reference. Hochstenbach et al. (2009) Anomalies of chromosome number and structure are considered to be the most frequent cause of unexplained, non-syndromic developmental delay and mental retardation (DD/MR). High-resolution, genomewide, array-based segmental aneusomy profiling has emerged as a highly sensitive technique for detecting pathogenic genomic imbalances. A retrospective review of 29 Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 10

array-based studies of 36,325 patients with idiopathic developmental delay showed that a yield of at least approximately 19% pathogenic aberrations is attainable in unselected, consecutive DD/MR referrals if array platforms with 30-70 kb median probe spacing are used as an initial genetic testing method. This corresponds to roughly twice the rate of classical cytogenetics. This raises the question whether chromosome banding studies, combined with targeted approaches, such as fluorescence in situ hybridisation for the detection of microdeletions, still hold substantial relevance for the clinical investigation of these patients. To address this question, the authors reviewed the outcome of cytogenetic studies in all the DD/MR referrals in the Netherlands during the period 1996-2005, a period before the advent of array-based genome investigation. The authors estimate that in a minimum of 0.78% of all referrals a balanced chromosomal rearrangement would have remained undetected by array-based investigation. These include familial rearrangements (0.48% of all referrals), de novo reciprocal translocations and inversions (0.23% of all referrals), de novo Robertsonian translocations (0.04% of all referrals), and 69,XXX triploidy (0.03% of all referrals). We conclude that karyotyping, following an initial array-based investigation, would give only a limited increase in the number of pathogenic abnormalities, i.e. 0.23% of all referrals with a de novo, apparently balanced, reciprocal translocation or inversion (assuming that all of these are pathogenic), and 0.03% of all referrals with 69,XXX triploidy. The authors propose that, because of its high diagnostic yield, high-resolution array-based genome investigation should be the first investigation performed in cases of DD/MR, detecting>99% of all pathogenic abnormalities. However, laboratories that supplant karyotyping by array-based investigation should be aware that, as shown here, a chromosomal abnormality, with possible pathogenic consequences for the patient or the family, will escape detection in about 0.78% of all DD/MR referrals. Miller et al. (2010) Chromosomal microarray (CMA) is increasingly utilized for genetic testing of individuals with unexplained developmental delay/intellectual disability (DD/ID), autism spectrum disorders (ASD), or multiple congenital anomalies (MCA). Performing CMA and G-banded karyotyping on every patient substantially increases the total cost of genetic testing. The International Standard Cytogenomic Array (ISCA) Consortium held two international workshops and conducted a literature review of 33 studies, including 21,698 patients tested by CMA. The authors provide an evidence-based summary of clinical cytogenetic testing comparing CMA to G- banded karyotyping with respect to technical advantages and limitations, diagnostic yield for various types of chromosomal aberrations, and issues that affect test interpretation. CMA offers a much higher diagnostic yield (15%-20%) for genetic testing of individuals with unexplained DD/ID, ASD, or MCA than a G-banded karyotype ( approximately 3%, excluding Down syndrome and other recognizable chromosomal syndromes), primarily because of its higher sensitivity for submicroscopic deletions and duplications. Truly balanced rearrangements and lowlevel mosaicism are generally not detectable by arrays, but these are relatively infrequent causes of abnormal phenotypes in this population (<1%). Available evidence strongly supports the use of CMA in place of G-banded karyotyping as the first-tier cytogenetic diagnostic test for patients with DD/ID, ASD, or MCA. G-banded karyotype analysis should be reserved for patients with obvious chromosomal syndromes (e.g., Down syndrome), a family history of chromosomal rearrangement, or a history of multiple miscarriages. Chromosomal Microarray Analysis in Prenatal Diagnosis Per the American College of Obstetricians and Gynecologists (ACOG), Committee Opinion. The Use of Chromosomal Microarray Analysis in Prenatal Diagnosis. Number 581. December 2013. The College and the Society for Maternal-Fetal Medicine offer the following recommendations for the use of chromosomal microarray analysis in prenatal diagnosis: Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 11

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. Comprehensive patient pretest and posttest genetic counseling from qualified personnel such as a genetic counselor or geneticist regarding the benefits, limitations, and results of chromosomal microarray analysis is essential. Chromosomal microarray analysis should not be ordered without informed consent, which should be documented in the medical record and include discussion of the potential to identify findings of uncertain significance, nonpaternity, consanguinity, and adult-onset disease. Wapner et al. (2012) Chromosomal microarray analysis has emerged as a primary diagnostic tool for the evaluation of developmental delay and structural malformations in children. The authors aimed to evaluate the accuracy, efficacy, and incremental yield of chromosomal microarray analysis as compared with karyotyping for routine prenatal diagnosis. Samples from women undergoing prenatal diagnosis at 29 centers were sent to a central karyotyping laboratory. Each sample was split in two; standard karyotyping was performed on one portion and the other was sent to one of four laboratories for chromosomal microarray. The authors enrolled a total of 4406 women. Indications for prenatal diagnosis were advanced maternal age (46.6%), abnormal result on Down's syndrome screening (18.8%), structural anomalies on ultrasonography (25.2%), and other indications (9.4%). In 4340 (98.8%) of the fetal samples, microarray analysis was successful; 87.9% of samples could be used without tissue culture. Microarray analysis of the 4282 nonmosaic samples identified all the aneuploidies and unbalanced rearrangements identified on karyotyping but did not identify balanced translocations and fetal triploidy. In samples with a normal karyotype, microarray analysis revealed clinically relevant deletions or duplications in 6.0% with a structural anomaly and in 1.7% of those whose indications were advanced maternal age or positive screening results. In the context of prenatal diagnostic testing, chromosomal microarray analysis identified additional, clinically significant cytogenetic information as compared with karyotyping and was equally efficacious in identifying aneuploidies and unbalanced rearrangements but did not identify balanced translocations and triploidies. (Funded Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 12

by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; ClinicalTrials.gov number, NCT01279733). Scientific Rationale Initial Chromosome abnormalities are a well-established cause of congenital anomalies, dysmorphic features, developmental delay (DD), intellectual disability (ID), and other neurodevelopmental disorders. However, less than 10% of individuals with DD, ID, and/or multiple congenital anomalies (MCA) will have abnormalities detectable by conventional karyotype analysis or fluorescence in situ hybridization (FISH). Laboratory evaluation of patients with DD/ID, congenital anomalies, and dysmorphic features has changed significantly in the last several years with the introduction of microarray technologies [array based comparative genomic hybridization (CGH) and single nucleotide polymorphism (SNP) array analysis] for use in clinical diagnostics. With these techniques, a patient s genome is examined for detection of gains or losses of genetic material that typically are too small to be detectable by standard G- banded chromosome studies. acgh is able to detect much smaller chromosomal imbalances than standard karyotype and FISH analyses. acgh involves comparing the genomes of two individuals (the patient and a normal control). Chromosomal imbalances are identified through hybridization to a microarray containing thousands of DNA segments (i.e., bacterial artificial chromosome [BAC] or oligonucleotide probes) representing various regions throughout the genome. The microarray may be targeted in nature, assaying certain regions of the genome known to be associated with a specific syndrome or phenotype, or may be genome-wide. The microarrays vary by the number, size, and distribution of the probes, or targets, used. The use of a large number of small probes (oligonucleotides) that are more closely spaced leads to increased resolution and the ability to detect smaller abnormalities. Because of this increased resolution, acgh will identify chromosomal imbalances in approximately 10% of patients with a suspected chromosome disorder who have a normal karyotype by conventional cytogenetics. SNP microarrays are DNA sequence variations that occur when a single nucleotide in the genome sequence is altered. SNPs are sequence variants in which a single base pair differs from a specified reference sequence. For each SNP, a person generally has two alleles, one inherited from each parent. The absence of one allele in multiple contiguous SNPs indicates the presence of a chromosomal deletion, while an increase in SNP copy number indicates the presence of a chromosomal duplication. In addition to identifying genomic imbalances, SNP microarrays can detect copy number neutral abnormalities. Specifically, SNP microarrays may reveal long stretches of homozygosity that can indicate uniparental disomy (UPD) ( i.e., when both copies of a chromosome or chromosomal segment are inherited from a single parent) or possible consanguinity (i.e.parents related by blood). These copy number neutral abnormalities are associated with an increased chance of autosomal recessive conditions. The resolution of SNP microarrays is determined by the number of probes, their distribution or spacing, and by the statistical algorithms used to identify gains and losses (which differ among the various statistical software packages). SNP microarray testing involves hybridizing patient DNA to the microarray and comparing results with those obtained from a given set of control samples. A variety of software programs are used in the processing of microarray data. The resolution of SNP microarrays is determined by the length and spacing between probes and by the statistical algorithms used to identify gains and losses (which differ between the various statistical software packages available for analysis). Like acgh, SNP Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 13

microarrays offer a cytogenetic evaluation at a significantly higher resolution than a standard karyotype analysis, as well as the ability to look for genomic imbalances throughout the genome in a single assay. In addition, both types of microarray analysis may be used to evaluate apparently balanced translocations, as up to 40% of these anomalies are found to have submicroscopic imbalances at rearrangement breakpoints. The main issue with microarray testing, including SNP microarray analysis, is the identification of copy number variants (CNVs) of unknown clinical significance. CNVs are segments of DNA longer than 1 kilobase that differ in copy number from a reference genome. In addition, the microarrays will not detect balanced chromosome rearrangements (i.e., balanced translocations or inversions) or imbalances not covered by the probes on the microarray. SNP microarray testing has been investigated in patients with DD, ID, MCA, dysmorphic features, and/or related phenotypes. In addition, prenatal SNP microarray testing may be offered in cases of a suspected fetal chromosome abnormality. Testing may also be performed in the family members of individuals with previously identified chromosomal imbalances, and may be used for preimplantation genetic diagnosis. It has been suggested that establishing a clinical diagnosis by microarray analysis may allow for improved prognostication, a better assessment of treatment options, enhanced anticipatory guidance, a more accurate risk assessment for the patient and his or her family, and the avoidance of unnecessary tests and evaluations. However, no studies designed to evaluate the clinical utility of SNP microarray testing have been identified. SNP microarray testing is limited as the results of SNP microarray testing is dependant on the methods of data analysis, and currently there is no standard of practice when it comes to testing patients using this type of microarray. In addition, the identification of CNVs of unknown clinical significance poses a significant problem for SNP microarray testing. While CNV databases now exist and are gathering more data to facilitate the interpretation of such variants, it is evident that, at the present time, not all CNVs can be classified as pathogenic or benign. Recommendations from the ACMG include the following (Nov 2010): 1. CMA testing for CNV 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 nonsyndromic developmental delay/intellectual disability (DD/ID). Autism spectrum disorders. 2. Further determination of the use of CMA testing for the evaluation of the child with growth retardation, speech delay, and other less well-studied indications is recommended, particularly by prospective studies and aftermarket analysis. 3. Appropriate follow-up is recommended in cases of chromosome imbalance identified by CMA, to include cytogenetic/fish studies of the patient, parental evaluation, and clinical genetic evaluation and counseling. In October 2011, the American Academy of Pediatrics endorsed the following publication, 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 (Michelson et al 2011.) The report was a review of the evidence concerning the diagnostic yield of genetic and metabolic evaluation of children with global developmental delay or intellectual disability (GDD/ID). Per the report, In patients with GDD/ID, microarray testing is diagnostic on average in 7.8% (Class III), G- banded karyotyping is abnormal in at least 4% (Class II and III), and subtelomeric Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 14

fluorescence in situ hybridization is positive in 3.5% (Class I, II, and III). Testing for X-linked ID genes has a yield of up to 42% in males with an appropriate family history (Class III). FMR1 testing shows full expansion in at least 2%of patients with mild to moderate GDD/ID (Class II and III), and MeCP2 testing is diagnostic in 1.5% of females with moderate to severe GDD/ID (Class III). Tests for metabolic disorders have a yield of up to 5%, and tests for congenital disorders of glycosylation and cerebral creatine disorders have yields of up to 2.8% (Class III). Several genetic and metabolic screening tests have been shown to have a better than 1% diagnostic yield in selected populations of children with GDD/ID. These values should be among the many factors considered in planning the laboratory evaluation of such children. The report notes further, An etiologic diagnosis for GDD or ID only occasionally leads to a specific therapy that improves the child s outcome; however, it often leads to other benefits for the child and the child s family. These benefits include relieving caregivers of anxiety and uncertainty, empowering caregivers to become involved in support and research networks, limiting further diagnostic testing that may be costly or invasive, improving understanding of treatment and prognosis, anticipating and managing associated medical and behavioral comorbidities, allowing for counseling regarding recurrence risk, and preventing recurrence through screening for carriers and prenatal testing. Per the review, Microarray is the genetic test with the highest diagnostic yield in children with unexplained GDD/ID. The resolution of the current generation of commercially available, genome-wide, oligonucleotide-based microarray testing is 700 base pairs, 30 to 40 times higher than the oligo-based tests previously used in studies of GDD/ID and 1,000 times higher than older BAC-based microarrays. Laboratories now offer SNP microarray that detects and describes consanguinity or uniparental disomy. Studies on the yield of these more advanced microarray tests are anticipated in the near future. Currently, microarray testing can identify only unbalanced copy number changes and is insufficiently sensitive for detecting genetic disorders caused by inversions, balanced insertions, reciprocal translocations, polyploidy, low-level mosaicism (20% 25%), rearrangements in repeat sequences, point mutations, or duplications/deletions that are undetectable at the test s resolution level. The results of microarray testing are often complex and require confirmation and careful interpretation, often with the assistance of a medical geneticist. Faas et al (2012) evaluated both clinical and laboratory aspects of our new strategy offering quantitative fluorescence (QF)-PCR followed by non-targeted whole genome 250K single-nucleotide polymorphism array analysis instead of routine karyotyping for prenatal diagnosis of fetuses with structural anomalies. Upon the detection of structural fetal anomalies, parents were offered a choice between QF-PCR and 250K single-nucleotide polymorphism array analysis (QF/array) or QF-PCR and routine karyotyping (QF/karyo). Two hundred twenty fetal samples were included. In 153/220 cases (70%), QF/array analysis was requested. In 35/153 (23%), an abnormal QF-PCR result was found. The remaining samples were analyzed by array, which revealed clinically relevant aberrations, including two known microdeletions, in 5/118 cases. Inherited copy number variants were detected in 11/118 fetuses, copy number variants with uncertain clinical relevance in 3/118 and homozygous stretches in 2/118. In 67/220 (30%) fetuses, QF/karyo was requested: 23/67 (34%) were abnormal with QF-PCR, and in 3/67, an abnormal karyotype was found. Investigators concluded even though QF/array does not reveal a high percentage of submicroscopic aberrations in fetuses with unselected structural anomalies, it is preferred over QF/karyo, as it provides a whole genome scan at high resolution, without additional tests needed and with a low chance on findings not related to the ultrasound anomalies. Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 15

Bruno et al (2009) investigated replacement of time consuming, locus specific testing for specific microdeletion and microduplication syndromes with microarray analysis, which theoretically should detect all known syndromes with copy number variations (CNV) etiologies as well as new ones. Genome wide copy number analysis was performed on 117 patients using Affymetrix 250K microarrays. 434 CNVs (195 losses and 239 gains) were found, including 18 pathogenic CNVs and 9 identified as "potentially pathogenic". Almost all pathogenic CNVs were larger than 500 kb, significantly larger than the median size of all CNVs detected. Segmental regions of loss of heterozygosity larger than 5 Mb were found in 5 patients. Investigators concluded genome microarray analysis has improved diagnostic success in this group of patients. Several examples of recently discovered "new syndromes" were found suggesting they are more common than previously suspected and collectively are likely to be a major cause of mental retardation. The findings have several implications for clinical practice. The study revealed the potential to make genetic diagnoses that were not evident in the clinical presentation, with implications for pretest counselling and the consent process. The importance of contributing novel CNVs to high quality databases for genotype-phenotype analysis and review of guidelines for selection of individuals for microarray analysis is emphasized. Tucker et al (2011) studied 30 children with idiopathic MR and both unaffected parents of each child using Affymetrix 500 K GeneChip SNP arrays, Agilent Human Genome 244 K oligonucleotide arrays and NimbleGen 385 K Whole-Genome oligonucleotide arrays. They also determined whether CNVs called on these platforms were detected by Illumina Hap550 beadchips or SMRT 32 K BAC whole genome tiling arrays and tested 15 of the 30 trios on Affymetrix 6.0 SNP arrays. The Affymetrix 500 K, Agilent and NimbleGen platforms identified 3061 autosomal and 117 X chromosomal CNVs in the 30 trios. 147 of these CNVs appeared to be de novo, but only 34 (22%) were found on more than one platform. Performing genotypephenotype correlations, we identified 7 most likely pathogenic and 2 possibly pathogenic CNVs for MR. All 9 of these putatively pathogenic CNVs were detected by the Affymetrix 500 K, Agilent, NimbleGen and the Illumina arrays, and 5 were found by the SMRT BAC array. Both putatively pathogenic CNVs identified in the 15 trios tested with the Affymetrix 6.0 were identified by this platform. Investigators concluded the findings demonstrate that different results are obtained with different platforms and illustrate the trade-off that exists between sensitivity and specificity. The large number of apparently false positive CNV calls on each of the platforms supports the need for validating clinically important findings with a different technology Gijsbers et al (2009) assessed molecular karyotyping as first-round analysis of patients with mental retardation and/or multiple congenital abnormalities (MR/MCA). We used different commercially available SNP array platforms, the Affymetrix GeneChip 262K NspI, the Genechip 238K StyI, the Illumina HumanHap 300 and HumanCNV 370 BeadChip, to detect copy number variants (CNVs) in 318 patients with unexplained MR/MCA. Investigators found abnormalities in 22.6% of the patients, including six CNVs that overlap known microdeletion/duplication syndromes, eight CNVs that overlap recently described syndromes, 63 potentially pathogenic CNVs (in 52 patients), four large segments of homozygosity and two mosaic trisomies for an entire chromosome. Investigators concluded this study shows that high-density SNP array analysis reveals a much higher diagnostic yield as that of conventional karyotyping. SNP arrays have the potential to detect CNVs, mosaics, uniparental disomies and loss of heterozygosity in one experiment. We, therefore, propose a novel diagnostic approach to all MR/MCA patients by first analyzing every patient with an SNP array instead of conventional karyotyping. Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 16

Friedman et al (2009) performed 500 K Affymetrix GeneChip array genomic hybridization in 100 idiopathic intellectual disability trios, each comprised of a child with intellectual disability of unknown cause and both unaffected parents. Investigators found pathogenic genomic imbalance in 16 of these 100 individuals with idiopathic intellectual disability. In comparison, they found pathogenic genomic imbalance in 11 of 100 children with idiopathic intellectual disability in a previous cohort who had been studied by 100 K GeneChip array genomic hybridization. Among 54 intellectual disability trios selected from the previous cohort who were retested with 500 K GeneChip array genomic hybridization, they identified all 10 previously-detected pathogenic genomic alterations and at least one additional pathogenic copy number variant that had not been detected with 100 K GeneChip array genomic hybridization. Many benign copy number variants, including one that was de novo, were also detected with 500 K array genomic hybridization, but it was possible to distinguish the benign and pathogenic copy number variants with confidence in all but 3 (1.9%) of the 154 intellectual disability trios studied. Investigators concluded Affymetrix GeneChip 500 K array genomic hybridization detected pathogenic genomic imbalance in 10 of 10 patients with idiopathic developmental disability in whom 100 K GeneChip array genomic hybridization had found genomic imbalance, 1 of 44 patients in whom 100 K GeneChip array genomic hybridization had found no abnormality, and 16 of 100 patients who had not previously been tested. Effective clinical interpretation of these studies requires considerable skill and experience. Papenhausen et al (2011) analyzed over 13,000 samples primarily referred for developmental delay using the Affymetrix SNP/CN 6.0 version array platform. In addition to copy number, investigators focused on the relative distribution of allele homozygosity (HZ) throughout the genome to confirm a strong association of uniparental disomy (UPD) with regions of isoallelism found in most confirmed cases of UPD. Investigators sought to determine whether a long contiguous stretch of HZ (LCSH) greater than a threshold value found only in a single chromosome would correlate with UPD of that chromosome. Nine confirmed UPD cases were retrospectively analyzed with the array in the study, each showing the anticipated LCSH with the smallest 13.5Mb in length. This length is well above the average longest run of HZ in a set of control patients and was then set as the prospective threshold for reporting possible UPD correlation. Ninety-two cases qualified at that threshold, 46 of those had molecular UPD testing and 29 were positive. Including retrospective cases, 16 showed complete HZ across the chromosome, consistent with total isoupd. The average size LCSH in the 19 cases that were not completely HZ was 46.3Mb with a range of 13.5-127.8Mb. Three patients showed only segmental UPD. Both the size and location of the LCSH are relevant to correlation with UPD. Investigators concluded further studies will continue to delineate an optimal threshold for LCSH/UPD correlation. Review History December 2012 December 2013 January 2014 January 2015 January 2016 Medical Advisory Council, initial approval Update no revisions. Codes Updated. Policy to be sent to Geneticist for External Review. Update. Added 2013 ACOG recommendation regarding pre-natal testing as medically necessary. Added post-natal testing with specific requirements as medically necessary. Reviewed Codes. Update revised wording in policy statement but no change to Position or content. Update no revisions. Codes updated. Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 17

This policy is based on the following evidence-based guidelines: 1. Manning M, Hudgins L; Professional Practice and Guidelines Committee. Arraybased technology and recommendations for utilization in medical genetics practice for detection of chromosomal abnormalities. Genet Med. 2010 Nov;12(11):742-5. Available at: http://www.acmg.net/staticcontent/ppg/array_based_technology_and_recomm endations_for.13.pdf 2. Moeschler JB, Shevell M; American Academy of Pediatrics Committee on Genetics. Clinical genetic evaluation of the child with mental retardation or developmental delays. Pediatrics. 2006 Jun;117(6):2304-16. Available at: http://pediatrics.aappublications.org/content/117/6/2304.full?sid=33579297-0b39-4d1f-bf78-4c00f8b487c1 3. Johnson CP, Myers SM; American Academy of Pediatrics Council on Children With Disabilities. Identification and evaluation of children with autism spectrum disorders. Pediatrics. 2007 Nov;120 (5):1183-215. 4. 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 Oct 25;77(17):1629-35. Available at: http://www.neurology.org/content/77/17/1629.full.pdf&tnqh_x002b;html 7. Hayes GTE Report. Single Nucleotide Polymorphism (SNP) Chromosomal Microarray Analysis for Intellectual Disability, Developmental Delay, and/or Multiple Congenital Anomalies. Oct 2011. Updated Oct 2012. Archived May 22, 2013. 8. American College of Obstetricians and Gynecologists (ACOG). Ob-Gyns Recommend Chromosomal Microarray Analysis for Genetic Evaluation of Fetal Anomalies. November 21, 2013. 9. American College of Obstetricians and Gynecologists (ACOG). Committee Opinion. The Use of Chromosomal Microarray Analysis in Prenatal Diagnosis. Number 581. December 2013. (Replaces No. 446, November 2009). (See also Practical Bulletin 88). 10. Blue Cross, Blue Shield Association. Technology Evaluation Center (TEC). Special Report: Array Comparative Genomic Hybridization (acgh) for the Genetic Evaluation of Patients with Developmental Delay/Mental Retardation and Autism Spectrum Disorder. TEC Vol. 23, No. 10 Apr 2009. Updated Oct 2014. 11. Hayes. GTE Overview. Genomic Microarray Analysis for Intellectual Disability, Developmental Delay, Multiple Congenital Anomalies, and Autism Spectrum Disorders (Various Manufacturers). June 7, 2013. 12. Hayes. GTE Algorithm: Genomic Microarray Analysis in Fetuses with Multiple Congenital Anomalies. June 3, 2013. 13. Satya-Murti S, Cohen BH, Michelson D. Chromosomal Microarray Analysis for Intellectual Disabilities. American Academy of Neurology (AAN). August 20, 2013. 14. Hayes. GTE Report. Genomic Microarray Analysis for Intellectual Disability, Developmental Delay, Multiple Congenital Anomalies, and Autism Spectrum Disorders. May 2013. Update May 2014. Update May 6, 2015. 15. American College of Obstetricians and Gynecologists (ACOG). Technology Assessment if Obstetrics and Gynecology. Number 11, February 2014. (Replaces Technology Assessment Number 1, July 2002). References Update January 2016 1. Babkina N, Graham JM Jr. New genetic testing in prenatal diagnosis. Semin Fetal Neonatal Med. 2014; 19(3):214-219. 2. Schrijver I, Zehnder JL, Cherry AM. Tools for genetics and genomics: Cytogenetics and molecular genetics. UpToDate. June 27, 2014. Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 18

References Update January 2015 1. Bartnik M, Wiśniowiecka-Kowalnik B, Nowakowska B, et al. The usefulness of array comparative genomic hybridization in clinical diagnostics of intellectual disability in children. Dev Period Med. 2014 Jul-Sep;18(3):307-17. 2. Emy Dorfman L, Leite JC, Giugliani R, Riegel M. Microarray-based comparative genomic hybridization analysis in neonates with congenital anomalies: detection of chromosomal imbalances. J Pediatr (Rio J). 2014 Sep 6. 3. Lay-Son G, Espinoza K, Vial C, et al. Chromosomal microarrays testing in children with developmental disabilities and congenital anomalies. J Pediatr (Rio J). 2014 Oct 30. pii: S0021-7557(14)00150-8. 4. Levy B, Sigurjonsson S, Pettersen B, et al. Genomic imbalance in products of conception: single-nucleotide polymorphism chromosomal microarray analysis. Obstet Gynecol. 2014 Aug;124(2 Pt 1):202-9. 5. Li Y, Qiu W, Ye J, et al. Analysis of copy number variations in 66 children with unexplained mental retardation/developmental delay using chromosomal microarrays. Zhonghua Yi Xue Yi Chuan Xue Za Zhi. 2014 Dec;31(6):703-7. 6. Lo JO, Shaffer BL, Feist CD, Caughey AB. Chromosomal microarray analysis and prenatal diagnosis. Obstet Gynecol Surv. 2014 Oct;69(10):613-21. 7. Romero ST, Geiersbach KB, Paxton CN, et al. Differentiation of Genetic Abnormalities in Early Pregnancy Loss. Ultrasound Obstet Gynecol. 2014 Oct 31. 8. Tobler KJ, Brezina PR, Benner AT, et al. Two different microarray technologies for preimplantation genetic diagnosis and screening, due to reciprocal translocation imbalances, demonstrate equivalent euploidy and clinical pregnancy rates. J Assist Reprod Genet. 2014 Jul;31(7):843-50 9. Xu HB, Yang H, Liu G, Chen H. Systematic review of accuracy of prenatal diagnosis for abnormal chromosome diseases by microarray technology. Genet Mol Res. 2014 Oct 31;13(4):9115-21. References Update January 2014 1. Riggs E, Wain K, Riethmaier D, et al. Chromomal microarray impacts clinical management. Clin Genet. 2013 Jan 25. doi:10.1111/cge.12107. References Update December 2013 1. Alesi V, Bertoli M, Sinibaldi L, et al. The clinical utility and indications of chromosomal microarray analysis in prenatal diagnosis. BJOG. 2013;120(1):119-120. 2. Augustyn M. Diagnosis of autism spectrum disorder. UpToDate. October 1, 2013. 3. Bacino CA. Genomic disorders: An overview. UpToDate. October 2, 2013. 4. Beaudet AL. The utility of chromosomal microarray analysis in developmental and behavioral pediatrics. Child Dev. 01-JAN-2013; 84 (1): 121-32. 5. Cooper GM, Mefford HC. Detection of copy number variation using SNP genotyping. Methods Mol Biol 2011; 767:243. 6. Daroff: Bradley's Neurology in Clinical Practice, 6th ed. 2012 Saunders, An Imprint of Elsevier. Common Neurological Disorders and Complex Disease Genetics. 7. 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. 8. 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. 9. Pivalizza P. Intellectual disability (mental retardation) in children: Evaluation. UpToDate. August 2, 2013. Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 19

10. Reddy UM, Page GP, Saade GR, et al. NICHD Stillbirth Collaborative Research Network. Karyotype versus microarray testing for genetic abnormalities after stillbirth. N Engl J Med. 2012 Dec 6;367(23):2185-93. 11. Schaefer GB, Mendelsohn NJ; Professional Practice and Guidelines Committee. American College of Medical Genetics and Genomics. Clinical genetics evaluation in identifying the etiology of autism spectrum disorders. 2013 May;15(5):399-407. Available at: https://www.acmg.net/docs/pp-g-asd-schaffer-aopgim201332a.pdf 12. Sorte HS, Gjevik E, Sponheim E, et al. Copy number variation findings among 50 children and adolescents with autism spectrum disorder. Psychiatr Genet. 2013;23(2):61-69. 13. Veenstra DL, Piper M, Haddow JE, et al. Improving the efficiency and relevance of evidence-based recommendations in the era of whole-genome sequencing: an EGAPP methods update. Genet Med. 2013;15 (1):14-24. 14. Wapner RJ, Martin CL, Levy B, et al. Chromosomal microarray versus karyotyping for prenatal diagnosis. N Engl J Med. 2012 Dec 6;367(23):2175-84. doi: 10.1056/NEJMoa1203382. 15. Wei Y, Xu F, Li P. Technology-driven and evidence-based genomic analysis for integrated pediatric and prenatal genetics evaluation. J Genet Genomics. 2013;40(1):1-14. 16. Wellcome Trust Sanger Institute. Database of Chromosomal Imbalance and Phenotype in Humans using Ensembl Resources (DECIPHER). 2013. 17. Wiśniowiecka-Kowalnik B, Kastory-Bronowska M, Bartnik M, et al. Application of custom-designed oligonucleotide array CGH in 145 patients with autistic spectrum disorders. Eur J Hum Genet. 2012. Epub ahead of print. October 3, 2012. References Initial 1. Becvárová V, Hynek M, Putzová M, et al. Application of SNP array method in prenatal diagnosis].ceska Gynekol. 2011 Sep;76(4):261-7. 2. Bernardini L, Alesi V, Loddo S, et al. High-resolution SNP arrays in mental retardation diagnostics: how much do we gain? Eur J Hum Genet. 2010;18(2):178-185. 3. Bernhardt BA, Soucier D, Hanson K, et al. Women s experiences receiving abnormal prenatal chromosomal microarray testing results. Genet Med 2013;15:139 45 4. Bruno DL, Ganesamoorthy D, Schoumans J, et al. Detection of cryptic pathogenic copy number variations and constitutional loss of heterozygosity using high resolution SNP microarray analysis in 117 patients referred for cytogenetic analysis and impact on clinical practice. J Med Genet. 2009;46(2):123-131. 5. Faas BH, Feenstra I, Eggink AJ, et al. Non-targeted whole genome 250K SNP array analysis as replacement for karyotyping in fetuses with structural ultrasound anomalies: evaluation of a one-year experience. Prenat Diagn. 2012 Apr;32(4):362-70. 6. Faas BH, van der Burgt I, Kooper AJ, et al. Identification of clinically significant, submicroscopic chromosome alterations and UPD in fetuses with ultrasound anomalies using genome-wide 250k SNP array analysis. J Med Genet. 2010;47(9):586-594. 7. Friedman J, Adam S, Arbour L, et al. Detection of pathogenic copy number variants in children with idiopathic intellectual disability using 500 K SNP array genomic hybridization. BMC Genomics. 2009;10:526. 8. Ghanta S, Mitchell ME, Ames M, et al. Non-invasive prenatal detection of trisomy 21 using tandem single nucleotide polymorphisms. PLoS One. 2010 Oct 8;5(10):e13184. Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 20

9. Gijsbers AC, Lew JY, Bosch CA et al. A new diagnostic workflow for patients with mental retardation and/or multiple congenital abnormalities: test arrays first. Eur J Hum Genet. 2009 Nov;17(11):1394-402. 9. Li MM, Andersson HC. Clinical application of microarray-based molecular cytogenetics: an emerging new era of genomic medicine. J Pediatr. 2009;155(3):311-317. 10. McMullan DJ, Bonin M, Hehir-Kwa JY, et al. Molecular karyotyping of patients with unexplained mental retardation by SNP arrays: a multicenter study. Hum Mutat. 2009;30(7):1082-1092. 11. Papenhausen P, Schwartz S, Risheg H, et al. UPD detection using homozygosity profiling with a SNP genotyping microarray. Am J Med Genet A. 2011;155(4):757-768. 12. Savage MS, Mourad MJ, Wapner RJ. Evolving applications of microarray analysis in prenatal diagnosis. Curr Opin Obstet Gynecol. 2011 Apr;23(2):103-8. 13. Schaaf CP, Wiszniewska J, Beaudet AL. Copy number and SNP arrays in clinical diagnostics. Annu Rev Genomics Hum Genet. 2011;12:25-51. 14. Treff NR, Levy B, Su J, Northrop LE, Tao X, Scott RT Jr. SNP microarray-based 24 chromosome aneuploidy screening is significantly more consistent than FISH. Mol Hum Reprod. 2010;16(8):583-589. 15. Treff NR, Northrop LE, Kasabwala K, Su J, Levy B, Scott RT Jr. Single nucleotide polymorphism microarray-based concurrent screening of 24-chromosome aneuploidy and unbalanced translocations in preimplantation human embryos. Fertil Steril. 2011;95(5):1606-1612.e1-2. 16. Tucker T, Montpetit A, Chai D, et al. Comparison of genome-wide array genomic hybridization platforms for the detection of copy number variants in idiopathic mental retardation. BMC Med Genomics. 2011;4(1):25. Important Notice General Purpose. Health Net's National Medical Policies (the "Policies") are developed to assist Health Net in administering plan benefits and determining whether a particular procedure, drug, service or supply is medically necessary. The Policies are based upon a review of the available clinical information including clinical outcome studies in the peer-reviewed published medical literature, regulatory status of the drug or device, evidence-based guidelines of governmental bodies, and evidence-based guidelines and positions of select national health professional organizations. Coverage determinations are made on a case-by-case basis and are subject to all of the terms, conditions, limitations, and exclusions of the member's contract, including medical necessity requirements. Health Net may use the Policies to determine whether under the facts and circumstances of a particular case, the proposed procedure, drug, service or supply is medically necessary. The conclusion that a procedure, drug, service or supply is medically necessary does not constitute coverage. The member's contract defines which procedure, drug, service or supply is covered, excluded, limited, or subject to dollar caps. The policy provides for clearly written, reasonable and current criteria that have been approved by Health Net s National Medical Advisory Council (MAC). The clinical criteria and medical policies provide guidelines for determining the medical necessity criteria for specific procedures, equipment, and services. In order to be eligible, all services must be medically necessary and otherwise defined in the member's benefits contract as described this "Important Notice" disclaimer. In all cases, final benefit determinations are based on the applicable contract language. To the extent there are any conflicts between medical policy guidelines and applicable contract language, the contract language prevails. Medical policy is not intended to override the policy that defines the member s benefits, nor is it intended to dictate to providers how to practice medicine. Policy Effective Date and Defined Terms. The date of posting is not the effective date of the Policy. The Policy is effective as of the date determined by Health Net. All policies are subject to applicable legal and regulatory mandates and requirements for prior notification. If there is a discrepancy between the policy effective date and legal mandates and regulatory requirements, the requirements of law and regulation shall govern. * In some states, prior notice or posting on the website is required before a policy is deemed effective. For information regarding the effective dates of Policies, contact your provider representative. The Policies do not include definitions. All terms are defined by Health Net. For information regarding the definitions of terms used in the Policies, contact your provider representative. Policy Amendment without Notice. Health Net reserves the right to amend the Policies without notice to providers or Members. In some states, prior notice or website posting is required before an amendment is deemed effective. Single Nucleotide Polymorphism Chromosomal Microarray Analysis Jan 16 21

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