**5. Challenges of genetic evaluation in ASD**

gene assessment results are then integrated in the form of Gene Score Cards to display the scores and the evidence in a graphical user interface for the ASD-linked gene. Recently, a community-wide annotation functionality was incorporated into the Gene Scoring module, allowing users to download the Gene Scoring dataset, score genes of their choice, and submit

DECIPHER (Database of Chromosomal Imbalance and Phenotype in Humans Using Ensembl Resources) (http://decipher.sanger.ac.uk/) is an interactive web-based database that incorpo‐ rates a suite of tools designed to aid in the interpretation of submicroscopic chromosomal deletions and duplications [43]. Genetic and phenotypic information is publically available not only for individuals diagnosed with idiopathic ASD, but also for individuals diagnosed with a recognized microdeletion or microduplication syndrome in which a subset of affected

AutismKB (http://autismkb.cbi.pku.edu.cn/) is a web-based, searchable database hosted by the Center for Bioinformatics, Peking University [44]. AutismKB is an evidence-based knowledge resource for ASD genetics containing information on genes, copy number variants, and linkage regions associated with ASD. Analysis of the gene content in AutismKB is available for users in the form of GO term enrichment analysis using the DAVID functional annotation tool and pathway enrichment analysis. Much like the Gene Scoring Module of SFARI Gene (see section

The Autism Chromosome Rearrangement Database (http://projects.tcag.ca/autism/) is a webbased, searchable genetic database of chromosomal structural variation in ASD that is hosted by The Centre for Applied Genomics at the Hospital for Sick Children in Toronto, Canada [21]. The content of this database, which is derived both from published research articles and inhouse experimental results, includes cytogenetic and microarray data from individuals with

The Autism Genetic Database (http://wren.bcf.ku.edu/) is a web-based, searchable genetic database developed by researchers at the University of Kansas [45]. In addition to ASDassociated genes and CNVs, this database also includes information on known non-coding

Recent lines of evidence have placed non-coding RNAs under increased scrutiny with regards to their potential pathogenic role in ASD. A number of small nucleolar RNAs (snoRNAs) reside within the ASD-associated 15q11-q13 region. A mouse model engineered to mimic duplication of the 15q11-q13 region observed in ~1% of ASD cases exhibited overexpression of the snoRNA

their scores to SFARI for possible inclusion.

202 Recent Advances in Autism Spectrum Disorders - Volume I

4.2), the genes within AutismKB are scored.

**4.5. Autism Chromosome Rearrangement Database**

RNAs and chemically-induced fragile sites in the human genome.

**4.3. DECIPHER**

**4.4. AutismKB**

ASD.

individuals also develop ASD.

**4.6. Autism Genetic Database**

NGS and CMA have expanded the ability of clinical geneticists and researchers to identify potential genetic causes of ASD. However, there are many challenges still present in the field of genetic evaluation. A recent report in the *American Journal of Medical Genetics* found that many children with ASD fail to get genetic evaluation, and that parents and medical professionals need to be better educated about the potential benefits of genetic evaluation [49]. Educating parents on genetic evaluation is especially critical in light of a recent survey of nine parents regarding their child's participation in genetic research in ASD [50], in which parents valued having had their child enrolled for a variety of rea‐ sons, including the potential use of genetic results in tailoring intervention and in family planning, the establishment of connections with experts in the field of ASD, and network‐ ing with other families, among others.

Even with the increased sensitivity of genetic evaluation techniques, an underlying genetic cause of ASD is still only identified in a minority (< 25%) of ASD cases [51]. One of the major challenges in the clinical interpretation of NGS and CMA lies in differentiating between pathogenic and benign genetic variants identified in ASD patients. The pathogenic relevance of the vast majority of ASD-linked genetic variants remains unknown; such variants are frequently classified as variants of unknown significance, or VOUS. While the identification of a genetic lesion in an existing ASD susceptibility gene or CNV locus is suggestive of a possible genetic cause of disease, variants in these genes and CNV loci have also been observed in seemingly unaffected individuals. Furthermore, it is important to note that, while techno‐ logical advances have expanded the ability of clinical geneticists and researchers to identify these potential genetic causes of ASD, there is no genetic test available for the diagnosis of ASD. A recent report proposed a means of predicting a diagnosis of ASD based on the identification of candidate SNPs [39]. The accuracy of the predictive classifier was found to be 71.7% in individuals of Central European descent from validation datasets. However, the accuracy of the predictive classifier fell when tested in a Han Chinese cohort, a finding that stresses how genetic heterogeneity across populations complicates the use of such an ap‐ proach. In addition, the overall accuracy of the predictive classifier is likely too low to serve as an effective diagnostic tool.

*5.1.3. Incompelete penetrance and variable expressivity*

One of the major challenges in identifying potential causative genetic variation in ASD cases lies in the fact that a potentially disruptive variant in a gene or genomic loci may not always associate or segregate with disease. For example, a potentially pathogenic variant in a gene may not only be present in an ASD individual, but it may also be present in seemingly unaffected family members. Similarly, the pathogenic variant may also be observed in seemingly unaffected individuals in the general population. This phenomenon, referred to as

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Alternatively, a genetic variant may result in a range of disease severity in affected individuals, a phenomenon known as *variable expressivity*. For example, ~500 kb deletions and duplications at the 16p11.2 locus are among the most heavily studied ASD-associated CNVs. However, CNVs at this locus are also responsible for a range of other neurodevelopmental and neuro‐ psychiatric disorders, such as schizophrenia. CNVs at the 16p11.2 locus can also be inherited from seemingly unaffected family members and have been observed in unaffected individuals in the general population. This lack of correlation between genotype and phenotype as it relates to ASD-associated genetic variation may be in part due to differences in gene-environment

A recent report highlights some of the challenges inherent in the genetic evaluation of ASD individuals. A putative disruptive variant in the ASD-associated *SHANK3* gene was identified in a boy with autism [52]. The variant, which was inherited from a healthy mother, was a small insertion that would be predicted to result in a frameshift and premature stop. Based on this evidence, as well as the relatively high penetrance of *SHANK3* mutations in ASD and other neuropsychiatric diseases, one could conclude that this variant in the *SHANK3* gene was pathogenically relevant in this autistic male. However, follow-up studies revealed that this variant was unlikely to be present in the majority of *SHANK3* transcripts due to alternative splicing events. Furthermore, this variant was observed in 4 out of 382 control individuals without neuropsychiatric conditions, a rate >1%. This report not only illustrates the necessity of determining the frequency of a given potentially pathogenic variant in the general popula‐ tion but also warns against relying too heavily on computational, or *in silico,* predictions of the

**5.2. Ethical considerations in the reporting of ASD genetic screening results**

Informed consent, and the extent to which participants have been sufficiently informed as to the purpose of a research or clinical study, has long been an issue in the field of genet‐ ic evaluation. For example, the extent to which research findings will be released and made available is one that participants in genetic evaluation studies should be informed of beforehand. In some cases, the participants themselves may not be able to gain access to the findings of genetic evaluation. This is an issue that has only been compounded with the rise of NGS and CMA and subsequent explosion in the amount of genetic data

*incomplete penetrance*, complicates the interpretation of genetic evalaution.

interactions between individuals carrying such variation.

effects of that variant on gene function.

generated by these techniques.

A number of guidelines have already been proposed to aid clinicians and clinical geneticists in the interpretation and reporting of CNVs. With the increasing use of high resolution NGS technologies, similar guidelines will likely be proposed for the interpretation and reporting of single nucleotide variants (SNVs). Furthermore, tools and prioritization schema have also been developed to aid clinicians in the interpretation of genetic testing results. Here we discuss in greater detail the challenges in interpreting genetic screening results in ASD cases, the strategies that have been proposed for the interpretation and reporting of screening results, and the resources available to aid in that interpretation.

#### **5.1. Challenges in the interpretation of ASD genetic screening results**

#### *5.1.1. Technical limitations of NGS and CMA*

As previously mentioned, as the size of the sequenced target increases, so does the poten‐ tial number of false-positive and false-negative variants identified [11]. Such sequencing artifacts are particularly problematic for the detection of spontaneous, or *de novo* variants, as false-positive variants would appear to be *de novo* in origin when they are observed in an offspring's genome but not in parental genomes. Furthermore, the source of DNA used in sequencing studies can introduce sequencing artifacts. DNA from lymphoblastoid cell lines from individuals to be genetically evaluated is a commonly used template for se‐ quencing; however, the creation and culturing of these cell lines can introduce genetic changes that would appear as *de novo* variants when such cell lines are compared between parents and offspring. In order to remove or reduce the possibility of artifactual results, subsequent variant validation should be performed. In the case of single gene variants identified by NGS, a more targeted sequencing approach limited to the gene or region of interest would confirm the variant previously identified. In the case of CNVs identified by NGS or CMA, a targeted detection method such as quantitative real-time PCR or FISH is frequently used to confirm their discovery.

#### *5.1.2. Genetic heterogeneity*

While the genetic basis of many human diseases can be traced back to one or a few genes, the genetic basis of complex neuropsychiatric disorders such as ASD has proven to be far more complicated, with hundreds of genes and genomic loci associated with varying risks of disease. The recent utilization of NGS and CMA approaches in genetic evaluation of ASD cases has led to the detection of genetic variation not only in both existing and novel susceptibility genes and genomic loci. However, the strength of evidence for many of these novel candidate genes or genomic loci is minimal, and some degree of replication in follow-up studies will be required to fully assess the relevance of many of these newlyidentified variants.

#### *5.1.3. Incompelete penetrance and variable expressivity*

proach. In addition, the overall accuracy of the predictive classifier is likely too low to serve

A number of guidelines have already been proposed to aid clinicians and clinical geneticists in the interpretation and reporting of CNVs. With the increasing use of high resolution NGS technologies, similar guidelines will likely be proposed for the interpretation and reporting of single nucleotide variants (SNVs). Furthermore, tools and prioritization schema have also been developed to aid clinicians in the interpretation of genetic testing results. Here we discuss in greater detail the challenges in interpreting genetic screening results in ASD cases, the strategies that have been proposed for the interpretation and reporting of screening results,

As previously mentioned, as the size of the sequenced target increases, so does the poten‐ tial number of false-positive and false-negative variants identified [11]. Such sequencing artifacts are particularly problematic for the detection of spontaneous, or *de novo* variants, as false-positive variants would appear to be *de novo* in origin when they are observed in an offspring's genome but not in parental genomes. Furthermore, the source of DNA used in sequencing studies can introduce sequencing artifacts. DNA from lymphoblastoid cell lines from individuals to be genetically evaluated is a commonly used template for se‐ quencing; however, the creation and culturing of these cell lines can introduce genetic changes that would appear as *de novo* variants when such cell lines are compared between parents and offspring. In order to remove or reduce the possibility of artifactual results, subsequent variant validation should be performed. In the case of single gene variants identified by NGS, a more targeted sequencing approach limited to the gene or region of interest would confirm the variant previously identified. In the case of CNVs identified by NGS or CMA, a targeted detection method such as quantitative real-time PCR or FISH is

While the genetic basis of many human diseases can be traced back to one or a few genes, the genetic basis of complex neuropsychiatric disorders such as ASD has proven to be far more complicated, with hundreds of genes and genomic loci associated with varying risks of disease. The recent utilization of NGS and CMA approaches in genetic evaluation of ASD cases has led to the detection of genetic variation not only in both existing and novel susceptibility genes and genomic loci. However, the strength of evidence for many of these novel candidate genes or genomic loci is minimal, and some degree of replication in follow-up studies will be required to fully assess the relevance of many of these newly-

as an effective diagnostic tool.

204 Recent Advances in Autism Spectrum Disorders - Volume I

and the resources available to aid in that interpretation.

*5.1.1. Technical limitations of NGS and CMA*

frequently used to confirm their discovery.

*5.1.2. Genetic heterogeneity*

identified variants.

**5.1. Challenges in the interpretation of ASD genetic screening results**

One of the major challenges in identifying potential causative genetic variation in ASD cases lies in the fact that a potentially disruptive variant in a gene or genomic loci may not always associate or segregate with disease. For example, a potentially pathogenic variant in a gene may not only be present in an ASD individual, but it may also be present in seemingly unaffected family members. Similarly, the pathogenic variant may also be observed in seemingly unaffected individuals in the general population. This phenomenon, referred to as *incomplete penetrance*, complicates the interpretation of genetic evalaution.

Alternatively, a genetic variant may result in a range of disease severity in affected individuals, a phenomenon known as *variable expressivity*. For example, ~500 kb deletions and duplications at the 16p11.2 locus are among the most heavily studied ASD-associated CNVs. However, CNVs at this locus are also responsible for a range of other neurodevelopmental and neuro‐ psychiatric disorders, such as schizophrenia. CNVs at the 16p11.2 locus can also be inherited from seemingly unaffected family members and have been observed in unaffected individuals in the general population. This lack of correlation between genotype and phenotype as it relates to ASD-associated genetic variation may be in part due to differences in gene-environment interactions between individuals carrying such variation.

A recent report highlights some of the challenges inherent in the genetic evaluation of ASD individuals. A putative disruptive variant in the ASD-associated *SHANK3* gene was identified in a boy with autism [52]. The variant, which was inherited from a healthy mother, was a small insertion that would be predicted to result in a frameshift and premature stop. Based on this evidence, as well as the relatively high penetrance of *SHANK3* mutations in ASD and other neuropsychiatric diseases, one could conclude that this variant in the *SHANK3* gene was pathogenically relevant in this autistic male. However, follow-up studies revealed that this variant was unlikely to be present in the majority of *SHANK3* transcripts due to alternative splicing events. Furthermore, this variant was observed in 4 out of 382 control individuals without neuropsychiatric conditions, a rate >1%. This report not only illustrates the necessity of determining the frequency of a given potentially pathogenic variant in the general popula‐ tion but also warns against relying too heavily on computational, or *in silico,* predictions of the effects of that variant on gene function.

#### **5.2. Ethical considerations in the reporting of ASD genetic screening results**

Informed consent, and the extent to which participants have been sufficiently informed as to the purpose of a research or clinical study, has long been an issue in the field of genet‐ ic evaluation. For example, the extent to which research findings will be released and made available is one that participants in genetic evaluation studies should be informed of beforehand. In some cases, the participants themselves may not be able to gain access to the findings of genetic evaluation. This is an issue that has only been compounded with the rise of NGS and CMA and subsequent explosion in the amount of genetic data generated by these techniques.

The sheer volume of genetic information generated by NGS and CMA not only leads to the identification of potential genetic causes of a disease of interest, but also frequently leads to the detection of other variants that are no directly related to the disease under investigation but are related to other inherited human diseases. The extent to which these incidental findings should be reported is a subject of some controversy, particularly in those situations in which genetic predisposition to an adult-onset disease is discovered in a child being evaluated for genetic causes of childhood developmental disorders. One such situation was described in a recent news feature in *Nature* in which the family of a child who had undergone genetic testing for developmental disability had to be informed that the child carried a genetic predisposition to colon cancer after extensive debate between clinical geneticists and ethics reviewers as to the extent to which such genetic information should be reported [53]. The degree to which clinical geneticists should report incidental findings in research participants has been consid‐ ered by numerous authors [54-57], but as of yet there is not consensus. Many of these same ethical concerns must be considered in the reporting of genetic evaluation results in individuals with ASD.

cally-occurring disease [11]. An increased rate of *de novo* CNVs in sporadic cases compared to familial cases has been reported [21, 60], and rare *de novo* CNVs at specific genomic loci were found to associate with ASD in sporadic cases from the Simons Simplex Collection [24]. Exome sequencing studies using ASD cohorts have reported an increased rate of *de novo* genedisrupting events (i.e. nonsense, splice-site, and frameshift mutations) in affected children

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Whereas ASD genetic research is increasingly focused on *de novo* genetic variation, it should be remembered that the genetic basis of ASD was first established by studies demonstrating the high heritability of the disease, a fact that illustrates the continued importance of identi‐ fying inherited genetic variation in ASD cases. A number of inherited single gene variants and CNVs that segregate with disease in ASD families has been recently described [9, 61-64]; these and other findings clearly demonstrate the importance of identifying inherited variants that closely segregate with disease in affected families. It should be noted that determining the extent of variant segregation in ASD families can be complicated by the phenotypic heteroge‐ neity that a given variant can cause from one affected family member to another. Furthermore, a disease-causing variant may exclusively segregate with disease in males, even if the variant does not reside on the X chromosome, as is the case with a *SHANK1* mutation identified in a four-generation ASD family [61]. Detailed family history and genetic evaluation of both affected and unaffected family members is essential in determining the signficance of both *de*

In addition to the mechanism of variant inheritance and variant segregation with disease, another important consideration in interpretation of genetic screening results lies in the functional impact of the variant. In many cases, especially with the use of high-throughput screening technologies, variant function is predicted *in silico*. In the case of single gene mutations, variation that results in disruption of gene function, such as nonsense mutations, splice-site mutations, or frameshift mutations that introduce premature stop codons, are strong genetic candidates, especially if such gene-disrupting variants are identified in a known ASD suscepibility gene or a gene associated with an ASD-linked pathway. The interpretation of missense mutations is more complicated and requires assessment of evolutionary conservation using phyloP or Genomic Evolutionary Rate Profiling (GERP) conservation scores, as well as scoring of the functional impact using Grantham or PolyPhen-2. However, as previously mentioned [52], dependency on *in silico* predictions for variant function, even in well charac‐ terized ASD-linked genes, can lead to false conclusions. As such, experimental functional assays are essential to accurately determine the impact of a given variant on gene expression

Another consideration in the interpretation of genetic screening results in ASD cases is the degree of clinical correlation of a given variant with ASD. Hundreds of susceptibility genes and CNV loci linked with ASD have been identified and catalogued in online genetic databases

compared to their unaffected siblings [10].

*novo* and inherited variants in ASD cases.

or function of the encoded gene product.

*5.3.3. Clinical correlations of the variant with ASD*

*5.3.2. Functional impact of variant*

Another consideration lies in the use of genetic evaluation to determine the recurrence risk in the siblings of children with ASD and in family planning [50]. Given a recent estimate that the recurrence rate of ASD in siblings may be as high as ~20% [58], the identification of inherited variants that potentially impart susceptibility to ASD is of critical importance both in identi‐ fying at-risk siblings that have not yet begun to manifest symptoms of ASD and in making informed decisions with regards to family planning.

#### **5.3. Strategies for ASD genetic screening interpretation and reporting**

The American College of Medicine Genetics released practice guidelines for the use of genetic screening techniques in the evaluation of individuals with ASD in 2008 [59]. In the years that have followed, additional practice guidleines and consensus statements discussing the use of CMA in the genetic evaluation of ASD cases have been published [25, 26]. With its increasing usage in the genetic evaluation of ASD cases, similar practice guidelines and consensus statements regarding NGS will likely be forthcoming, and strategies for the interpretation of NGS data in the evaluation of neurological diseases have recently been proposed [14]. In this section we highlight some of the factors to consider in the interpretation of genetic screening results in ASD cases.

#### *5.3.1. Variant inheritance and segregation with ASD*

One of the key determinants in the interpretation of ASD genetic screening results is the mechanism of variant inheritance and how closely that variant segregates with ASD. Genetic variation can either arise *de novo* or be transmitted from one or both parents. There has been considerable interest in the ASD research community in the pathogenic relevance of *de novo* variants, especially within the context of sporadic ASD cases.

As they have been subjected to less stringent evolutionary selection, *de novo* variants tend to be more deleterious than inherited variants, making them excellent candidates for sporadi‐ cally-occurring disease [11]. An increased rate of *de novo* CNVs in sporadic cases compared to familial cases has been reported [21, 60], and rare *de novo* CNVs at specific genomic loci were found to associate with ASD in sporadic cases from the Simons Simplex Collection [24]. Exome sequencing studies using ASD cohorts have reported an increased rate of *de novo* genedisrupting events (i.e. nonsense, splice-site, and frameshift mutations) in affected children compared to their unaffected siblings [10].

Whereas ASD genetic research is increasingly focused on *de novo* genetic variation, it should be remembered that the genetic basis of ASD was first established by studies demonstrating the high heritability of the disease, a fact that illustrates the continued importance of identi‐ fying inherited genetic variation in ASD cases. A number of inherited single gene variants and CNVs that segregate with disease in ASD families has been recently described [9, 61-64]; these and other findings clearly demonstrate the importance of identifying inherited variants that closely segregate with disease in affected families. It should be noted that determining the extent of variant segregation in ASD families can be complicated by the phenotypic heteroge‐ neity that a given variant can cause from one affected family member to another. Furthermore, a disease-causing variant may exclusively segregate with disease in males, even if the variant does not reside on the X chromosome, as is the case with a *SHANK1* mutation identified in a four-generation ASD family [61]. Detailed family history and genetic evaluation of both affected and unaffected family members is essential in determining the signficance of both *de novo* and inherited variants in ASD cases.

#### *5.3.2. Functional impact of variant*

The sheer volume of genetic information generated by NGS and CMA not only leads to the identification of potential genetic causes of a disease of interest, but also frequently leads to the detection of other variants that are no directly related to the disease under investigation but are related to other inherited human diseases. The extent to which these incidental findings should be reported is a subject of some controversy, particularly in those situations in which genetic predisposition to an adult-onset disease is discovered in a child being evaluated for genetic causes of childhood developmental disorders. One such situation was described in a recent news feature in *Nature* in which the family of a child who had undergone genetic testing for developmental disability had to be informed that the child carried a genetic predisposition to colon cancer after extensive debate between clinical geneticists and ethics reviewers as to the extent to which such genetic information should be reported [53]. The degree to which clinical geneticists should report incidental findings in research participants has been consid‐ ered by numerous authors [54-57], but as of yet there is not consensus. Many of these same ethical concerns must be considered in the reporting of genetic evaluation results in individuals

Another consideration lies in the use of genetic evaluation to determine the recurrence risk in the siblings of children with ASD and in family planning [50]. Given a recent estimate that the recurrence rate of ASD in siblings may be as high as ~20% [58], the identification of inherited variants that potentially impart susceptibility to ASD is of critical importance both in identi‐ fying at-risk siblings that have not yet begun to manifest symptoms of ASD and in making

The American College of Medicine Genetics released practice guidelines for the use of genetic screening techniques in the evaluation of individuals with ASD in 2008 [59]. In the years that have followed, additional practice guidleines and consensus statements discussing the use of CMA in the genetic evaluation of ASD cases have been published [25, 26]. With its increasing usage in the genetic evaluation of ASD cases, similar practice guidelines and consensus statements regarding NGS will likely be forthcoming, and strategies for the interpretation of NGS data in the evaluation of neurological diseases have recently been proposed [14]. In this section we highlight some of the factors to consider in the interpretation of genetic screening

One of the key determinants in the interpretation of ASD genetic screening results is the mechanism of variant inheritance and how closely that variant segregates with ASD. Genetic variation can either arise *de novo* or be transmitted from one or both parents. There has been considerable interest in the ASD research community in the pathogenic relevance of *de novo*

As they have been subjected to less stringent evolutionary selection, *de novo* variants tend to be more deleterious than inherited variants, making them excellent candidates for sporadi‐

informed decisions with regards to family planning.

206 Recent Advances in Autism Spectrum Disorders - Volume I

*5.3.1. Variant inheritance and segregation with ASD*

variants, especially within the context of sporadic ASD cases.

**5.3. Strategies for ASD genetic screening interpretation and reporting**

with ASD.

results in ASD cases.

In addition to the mechanism of variant inheritance and variant segregation with disease, another important consideration in interpretation of genetic screening results lies in the functional impact of the variant. In many cases, especially with the use of high-throughput screening technologies, variant function is predicted *in silico*. In the case of single gene mutations, variation that results in disruption of gene function, such as nonsense mutations, splice-site mutations, or frameshift mutations that introduce premature stop codons, are strong genetic candidates, especially if such gene-disrupting variants are identified in a known ASD suscepibility gene or a gene associated with an ASD-linked pathway. The interpretation of missense mutations is more complicated and requires assessment of evolutionary conservation using phyloP or Genomic Evolutionary Rate Profiling (GERP) conservation scores, as well as scoring of the functional impact using Grantham or PolyPhen-2. However, as previously mentioned [52], dependency on *in silico* predictions for variant function, even in well charac‐ terized ASD-linked genes, can lead to false conclusions. As such, experimental functional assays are essential to accurately determine the impact of a given variant on gene expression or function of the encoded gene product.

#### *5.3.3. Clinical correlations of the variant with ASD*

Another consideration in the interpretation of genetic screening results in ASD cases is the degree of clinical correlation of a given variant with ASD. Hundreds of susceptibility genes and CNV loci linked with ASD have been identified and catalogued in online genetic databases such as AutDB, DECIPHER, and others. The identification of a novel, potentially pathogenic variant in one of these known susceptibility genes or CNV loci would be strong evidence for a causal role. To a lesser extent, a novel variant in a gene in an ASD-associated pathway or a gene previously shown by gene expression studies to be differentially regulated in ASD tissue would be a strong candidate. Another factor to consider is the frequency of a variant of interest in healthy control populations; the absence or significantly reduced frequency of the variant of interest in unaffected individuals would offer strong evidence for a causal role.

translocations, and CNVs approximately 1 kb or larger in size, that has been observed in both

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The Database of Genomic Variants (http://dgvbeta.tcag.ca/dgv/app/home?ref=NCBI36/hg18) is an curated online database hosted by the Centre for Applied Genomic that contains struc‐ tural variation, defined by the developers of the database as genomic alterations that involve segments of DNA that are larger than 50bp, in control individuals [67]. Users can search the database for genetic variants such as CNVs, insertions, inversions, and regions of uniparen‐

The dbGaP public repository (http://www.ncbi.nlm.nih.gov/gap/) was created by the Na‐ tional Institutes of Health for the purposes of collecting individual-level genotype and phe‐ notype data and associations between them [68]. The studies collected in dbGaP include genome-wide association studies, sequencing and diagnostic assays, and associations be‐ tween genotype and non-clinical traits. Users can browse association results, utilize the Phe‐ notype-Genotype Integrator (PheGenI) to search for phenotypic traits linked to GWAS data,

The development of lower-cost, high-throughput genome-wide genetic screening technolo‐ gies has revolutionized the field of genetic evaluation and now provides clinical geneticists and researchers the opportunity to detect genetic variation in ASD individuals like never be‐ fore. In doing so, the evidence for previously identified genetic susceptibility factors will ex‐ pand, and novel ASD candidate genes and genomic loci will be identified, resulting in a better understanding of the genetic basis of ASD. However, precautions must be taken to

The authors would like to thank the other members of MindSpec, Inc. (Ajay Kumar, M.S., Idan Menashe, Ph.D., Wayne Pereanu, Ph.D., Rainier Rodriguez, and Sue Spence), as well as

the Simons Foundation. AutDB is licensed to the Simons Foundation as SFARI Gene.

ensure that genetic screening results are interpreted and reported properly.

Eric C. Larsen, Catherine Croft Swanwick and Sharmila Banerjee-Basu

case and control populations [65].

*5.4.1.4. Database of Genomic Variants*

*5.4.2. Genotype-phenotype association*

and download data.

**Acknowledgements**

**Author details**

MindSpec, Inc., U.S.A.

**6. Conclusion**

tal disomy, as well as download database contents.

#### **5.4. Resources for ASD genetic screening interpretation**

A number of online resources are available to aid clinical geneticists in the interpretation of genetic screening results in ASD individuals. Many of these resources are aimed at differen‐ tiating between rare, potentially ASD-specific variants and benign variants observed in the general population. In this section we will describe some of these resources in greater detail.

#### *5.4.1. Genetic variation in control populations*

Differentiating between potentially pathogenic and benign genetic variants in ASD cases requires knowledge of the degree of genetic variation that resides within seemingly unaffected individuals in the general population. A number of online resources, several of which are hosted by the National Center for Biotechnology Information (NCBI) [65], have been devel‐ oped to allow clinical geneticists to visualize genetic variation identified in the general population. The genetic variation curated in these databases can range from single nucleotide polymorphisms to chromosomal structural variation and has proven invaluable in assessing the potential pathogenic relevance of novel genetic variants.

#### *5.4.1.1. dbSNP (database of single nucleotide polymorphisms)*

dbSNP (http://www.ncbi.nlm.nih.gov/snp) is a public domain database hosted by NCBI collecting a range of polymorphic genetic variation, including single nucleotide polymor‐ phisms (SNPs), small-scale multi-base deletions or insertions (also called deletion insertion polymorphisms or DIPs), and retroposable element insertions and microsatellite repeat variations (also called short tandem repeats or STRs) [65].

#### *5.4.1.2. 1,000 Genomes Project*

The 1,000 Genomes Project (http://www.1000genomes.org/) is a consortium employing highthroughput NGS techniques for the purposes of characterizing over 95% of genetic variants located in genomic regions accessible to sequencing and occurring at an allelic freuqency of 1% or higher in each of five major population groups [66].

#### *5.4.1.3. dbVar (database of genomic structural variation)*

dbVar (http://www.ncbi.nlm.nih.gov/dbvar/) is a searchable online database hosted by NCBI containing genomic structual variation, defined by the database as inversions, balanced translocations, and CNVs approximately 1 kb or larger in size, that has been observed in both case and control populations [65].

#### *5.4.1.4. Database of Genomic Variants*

such as AutDB, DECIPHER, and others. The identification of a novel, potentially pathogenic variant in one of these known susceptibility genes or CNV loci would be strong evidence for a causal role. To a lesser extent, a novel variant in a gene in an ASD-associated pathway or a gene previously shown by gene expression studies to be differentially regulated in ASD tissue would be a strong candidate. Another factor to consider is the frequency of a variant of interest in healthy control populations; the absence or significantly reduced frequency of the variant

A number of online resources are available to aid clinical geneticists in the interpretation of genetic screening results in ASD individuals. Many of these resources are aimed at differen‐ tiating between rare, potentially ASD-specific variants and benign variants observed in the general population. In this section we will describe some of these resources in greater detail.

Differentiating between potentially pathogenic and benign genetic variants in ASD cases requires knowledge of the degree of genetic variation that resides within seemingly unaffected individuals in the general population. A number of online resources, several of which are hosted by the National Center for Biotechnology Information (NCBI) [65], have been devel‐ oped to allow clinical geneticists to visualize genetic variation identified in the general population. The genetic variation curated in these databases can range from single nucleotide polymorphisms to chromosomal structural variation and has proven invaluable in assessing

dbSNP (http://www.ncbi.nlm.nih.gov/snp) is a public domain database hosted by NCBI collecting a range of polymorphic genetic variation, including single nucleotide polymor‐ phisms (SNPs), small-scale multi-base deletions or insertions (also called deletion insertion polymorphisms or DIPs), and retroposable element insertions and microsatellite repeat

The 1,000 Genomes Project (http://www.1000genomes.org/) is a consortium employing highthroughput NGS techniques for the purposes of characterizing over 95% of genetic variants located in genomic regions accessible to sequencing and occurring at an allelic freuqency of

dbVar (http://www.ncbi.nlm.nih.gov/dbvar/) is a searchable online database hosted by NCBI containing genomic structual variation, defined by the database as inversions, balanced

of interest in unaffected individuals would offer strong evidence for a causal role.

**5.4. Resources for ASD genetic screening interpretation**

the potential pathogenic relevance of novel genetic variants.

*5.4.1.1. dbSNP (database of single nucleotide polymorphisms)*

variations (also called short tandem repeats or STRs) [65].

1% or higher in each of five major population groups [66].

*5.4.1.3. dbVar (database of genomic structural variation)*

*5.4.1.2. 1,000 Genomes Project*

*5.4.1. Genetic variation in control populations*

208 Recent Advances in Autism Spectrum Disorders - Volume I

The Database of Genomic Variants (http://dgvbeta.tcag.ca/dgv/app/home?ref=NCBI36/hg18) is an curated online database hosted by the Centre for Applied Genomic that contains struc‐ tural variation, defined by the developers of the database as genomic alterations that involve segments of DNA that are larger than 50bp, in control individuals [67]. Users can search the database for genetic variants such as CNVs, insertions, inversions, and regions of uniparen‐ tal disomy, as well as download database contents.

#### *5.4.2. Genotype-phenotype association*

The dbGaP public repository (http://www.ncbi.nlm.nih.gov/gap/) was created by the Na‐ tional Institutes of Health for the purposes of collecting individual-level genotype and phe‐ notype data and associations between them [68]. The studies collected in dbGaP include genome-wide association studies, sequencing and diagnostic assays, and associations be‐ tween genotype and non-clinical traits. Users can browse association results, utilize the Phe‐ notype-Genotype Integrator (PheGenI) to search for phenotypic traits linked to GWAS data, and download data.
