Patent Application
20200157628
The present invention relates to genetic markers for Autism Spectrum Disorders (ASD).
Autism is a heritable neurodevelopmental condition characterized by impairments in social communication and by a preference for repetitive activities. Autism is not a distinct categorical disorder but is the prototype of a group of conditions defined as Pervasive Developmental Disorders (PDDs) or Autism Spectrum Disorders (ASD), which include Asperger's Disorder, Childhood Disintegrative Disorder, Pervasive developmental disorder-not otherwise specified (PDD-NOS) and Rett Syndrome. ASD is diagnosed in families of all racial, ethnic and social-economic backgrounds with incidence roughly four times higher in males compared to females. Overall population prevalence of autism has increased in recent years to a current estimate of 20 in 10,000 with incidence as high as 60 in 10,000 for all autism spectrum disorders.
Data from several epidemiological twin and family studies provide substantial evidence that autism has a significant and complex genetic etiology. The concordance rate in monozygotic twins is 60-90% (Bailey 1995), and the recurrence rate in siblings of affected probands has been reported to be between 5-10% (Jones & Szatmari 1988) representing a 50 fold increase in risk compared to the general population. Although autism spectrum disorders are among the most heritable complex disorders, the genetic risk is clearly not conferred in simple Mendelian fashion.
In a minority of cases (˜10%), autism is part of a broader recognizable disorder (e.g. fragile X syndrome, tuberous sclerosis) or is associated with cytogenetically-detectable chromosome abnormalities. Moreover, co-morbidity of autism with microdeletion syndromes (e.g. William-Beuren and Sotos) and other genomic disorders (e.g. Prader-Willi/Angelman) suggests chromosomal imbalances are involved in the underlying etiology. The most frequent cytogenetic anomaly is an interstitial, maternally-inherited duplication of 15q11-13 (1-3%) encompassing the Prader Willi/Angelman Syndrome critical region. There are also a large number of cases with deletions in the q11.2 and q13.3 regions of chromosome 22. The 22q11.2 region is associated with velo-cardio-facial Syndrome and deletions at 22q13.3 appear to also represent a clinically definable syndrome. Both deletions are associated with the autistic phenotypes. Other chromosome loci associated with anomalies with a higher frequency of events observed in syndromic forms of ASD include 7q (see TCAG www.chr7.org), 2q37, 5p14-15, 17p11.2. In addition, reciprocal duplications overlapping the William-Beuren deletion region have been associated with the autism phenotype.
Genome-wide linkage scans have found evidence for susceptibility loci on almost all chromosomes with 7q yielding the most consistent results. Other loci with significant linkage include 2q (IMOSAC 2001), 3q and most recently lip (AGP 10K study). In some instances, like 7q, there is considerable overlap between cytogenetic anomalies and linkage results. However, the lack of linkage found at 15q11-13 and 22q13.3 loci reflect considerable heterogeneity in ASD and suggest that these rearrangements are responsible for a particular ASD subtype involving genes that do not contribute to the phenotype in cytogenetically normal patients. Despite promising results, no specific genes within these linkage peaks have unequivocally been shown to contribute to autism.
Mutations associated with ASD have been reported in two neuroligin (NLGN3 and NLGN4) genes and more recently SHANK3; however, these account for only rare causes of ASD. Other genes have been implicated, but represent rare events or have not yet been validated by other studies.
Together these data suggest substantial genetic heterogeneity with the most likely cause of non-syndromic idiopathic ASD involving multiple epistatically-interacting loci.
The identification of large scale copy number variants (CNVs) represents a considerable source of genetic variation in the human genome that contributes to phenotypic variation and disease susceptibility found small inherited deletions in autistic kindreds suggesting possible susceptibility loci.
It would be desirable to identify genetic markers of ASD that facilitate in a determination of the risk of ASD in an individual, as well as to assist in the diagnosis of the condition.
A number of genetic markers have now been identified which are useful in assessing the risk of ASD in an individual, as well as being useful to diagnose the condition. The markers are useful both individually and in the form of a microarray to screen individuals for risk of ASD.
Thus, in one aspect of the present invention, a method of determining the risk of ASD in an individual is provided comprising: probing a nucleic acid-containing sample obtained from the individual for a gene encoding PTCHD1, wherein a determination that the gene comprises a deletion of at least a portion of exon 1 is indicative of a risk of ASD in the individual.
In another aspect of the present invention, a method of determining the risk of ASD in an individual is provided comprising: probing a nucleic acid-containing sample obtained from the individual for a mutation that modulates the expression of at least one gene selected from the group consisting of PTCHD1, SHANK3, NFIA, DPP6, DPP10, GPR98, PQBP1, ZNF41 and FTSJ1, wherein identification of a mutation that modulates the expression of at least one of said genes is indicative of a risk of ASD.
In another aspect of the invention, a method of determining the risk of ASD in an individual is provided comprising: screening a biological sample obtained from the individual for abnormal levels of at least one gene product expressed by a gene selected from the group consisting of PTCHD1, SHANK3, NFIA, DPP6, DPP10, GPR98, PQBP1, ZNF41 and FTSJ1, wherein a determination that at least one of said gene products is expressed at a level that varies from the level in a healthy non-ASD individual is indicative of a risk of ASD.
In a further aspect of the invention, a method of determining the risk of ASD in an individual is provided comprising: screening a nucleic acid-containing sample from the individual for genomic sequence variations that modulate the expression of PTCHD1.
These and other aspects of the present invention are described by reference to the following figures in which:
A method of determining the risk of an autism spectrum disorder (ASD) in an individual is provided comprising screening a biological sample obtained from the individual for a mutation that may modulate the expression of at least one gene selected from the group consisting of PTCHD1, SHANK3, NFIA, DPP6, DPP10, DPYD, GPR98, PQBP1, ZNF41 and FTSJ1. Such genes are referred to herein as “ASD-associated” genes.
The term “an autism spectrum disorder” or “an ASD” is used herein to refer to at least one condition that results in developmental delay of an individual such as autism, Asperger's Disorder, Childhood Disintegrative Disorder, Pervasive Developmental Disorder-Not Otherwise Specified (PDD-NOS) and Rett Syndrome (APA DSM-IV 2000).
In the present method of determining ASD risk in an individual, a biological sample obtained from the individual is utilized. A suitable biological sample may include, for example, a nucleic acid-containing sample or a protein-containing sample. Examples of suitable biological samples include saliva, urine, semen, other bodily fluids or secretions, epithelial cells, cheek cells, hair and the like. Although such non-invasively obtained biological samples are preferred for use in the present method, one of skill in the art will appreciate that invasively-obtained biological samples, may also be used in the method, including for example, blood, serum, bone marrow, cerebrospinal fluid (CSF) and tissue biopsies such as tissue from the cerebellum, spinal cord, prostate, stomach, uterus, small intestine and mammary gland samples. Techniques for the invasive process of obtaining such samples are known to those of skill in the art. The present method may also be utilized in prenatal testing for the risk of ASD using an appropriate biological sample such as amniotic fluid and chorionic villus.
In one aspect, the biological sample is screened for nucleic acid encoding selected genes in order to detect mutations associated with an ASD. It may be necessary, or preferable, to extract the nucleic acid from the biological sample prior to screening the sample. Methods of nucleic acid extraction are well-known to those of skill in the art and include chemical extraction techniques utilizing phenol-chloroform (Sambrook et al., 1989), guanidine-containing solutions, or CTAB-containing buffers. As well, as a matter of convenience, commercial DNA extraction kits are also widely available from laboratory reagent supply companies, including for example, the QIAamp DNA Blood Minikit available from QIAGEN (Chatsworth, Calif.), or the Extract-N-Amp blood kit available from Sigma (St. Louis, Mo.).
Once an appropriate nucleic acid sample is obtained, it is subjected to well-established methods of screening, such as those described in the specific examples that follow, to detect genetic mutations indicative of ASD, i.e. ASD-linked mutations. Mutations, such as genomic copy number variations (CNVs), which include gains and deletions of segments of DNA, for example, segments of DNA greater than about 1 kb, such as DNA segments between about 300 and 500 kb, as well as base pair mutations such as nonsense, missense and splice site mutations, including sequence mutations in both coding and regulatory regions of a gene, have been found to be indicative of ASD.
ASD-linked mutations such as CNVs are not restricted to a single chromosome, but rather have been detected on a multiple chromosomes such as the X chromosome, chromosome 15 and chromosome 21, and on various regions of the same chromosome such as at Xp11 and Xp22. Examples of CNVs that have been determined to be linked to ASD include a deletion on chromosome Xp22 including at least a portion of exon 1 of the PTCHD1 gene; a duplication on chromosome 15q11; and a deletion within the SHANK3 gene.
Genomic sequence variations of various types in different genes have been identified as indicative of ASD. CNVs in the DPP10 gene, including intronic gains, such as a 105 kb intronic gain, and exonic losses, such as a 478 kb exonic loss, both of which are more specifically identified in Table 1, have been identified; CNVs in the DPP6 gene, such as a 66 kb loss encompassing exons 2 and 3 and gains such as a CNV encompassing the entire DPP6 gene, a 270 kb exonic gain (exon 1), and a 16 kb intronic gain (see Table 1); CNVs in the SHANK3 gene such as a 276 kb loss; and CNVs in the DYPD gene such as a loss of the entire gene.
In one embodiment, genomic sequence variations that inhibit the expression of PTCHD1 have been linked to ASD. The terminology “inhibit expression” refers broadly to sequence variations that may inhibit, or at least reduce, any one of transcription and/or translation, as well as the activity of the PTCHD1 protein. For example, a CNV in the PTCHD1 gene comprising a large deletion of the coding region which results in at least a reduction of the expression of PTCHD1 protein has been found to be indicative of ASD. Although the CNV is not particularly restricted, the CNV deletion may include, for example, at least a portion of exon 1, but may additionally include surrounding regions as well, such as intron 1, in whole or in part, or a portion or more of the upstream region thereof.
Genomic sequence variations other than CNVs have also been found to be indicative of ASD, including, for example, missense mutations which result in amino acid changes in a protein that may also affect protein expression. In one embodiment, missense mutations in the PTCHD1 gene have been identified which are indicative of ASD, including missense mutations resulting in the following amino acid substitutions in the Ptchd1 protein: L73F, I173V, V195I, ML336-3371I and E479G.
To determine risk of ASD in an individual, it may be advantageous to screen for multiple genomic mutations, including CNVs and other mutations as indicated above applying array technology. In this regard, genomic sequencing and profiling, using well-established techniques as exemplified herein in the specific examples, may be conducted for an individual to be assessed with respect to ASD risk/diagnosis using a suitable biological sample obtained from the individual. Identification of one or more mutations associated with ASD would be indicative of a risk of ASD, or may be indicative of a diagnosis of ASD. This analysis may be conducted in combination with an evaluation of other characteristics of the individual being assessed, including for example, phenotypic characteristics.
In view of the determination of gene mutations which are linked to ASD, a method for determining risk of ASD in an individual is also provided in which the expression or activity of a product of an ASD-linked gene mutation is determined in a biological protein-containing sample obtained from the individual. Abnormal levels of the gene product or abnormal levels of the activity thereof, i.e. reduced or elevated levels, in comparison with levels that exist in healthy non-ASD individuals, are indicative of a risk of ASD, or may be indicative of ASD. Thus, a determination of the level and/or activity of the gene products of one or more of PTCHD1, SHANK3, NFIA, DPP6, DPP10, DYPD, GPR98, PQBP1, ZNF41 and FTSJ1, may be used to determine the risk of ASD in an individual, or to diagnose ASD. As one of skill in the art will appreciate, standard assays may be used to identify and quantify the presence and/or activity of a selected gene product.
Embodiments of the invention are described by reference to the following specific examples which is not to be construed as limiting.
The study included 426 ASD families. All of the index cases met Autism Diagnostic Interview-Revised (ADI-R) and Autism Diagnostic Observation Schedule (ADOS) criteria or on a clinical best estimate (Risi et al. J Am Acad Child Adolesc Psychiatry 2006; 45(9):1094-103). Thirty-two of these carried a cytogenetic chromosome rearrangement; 18 were detected by karyotyping 328 of 412 samples that originated from child diagnostic centres at the Hospital for Sick Children in Toronto and from St. John's, Newfoundland; 14 were already known to carry karyotypic anomalies (see Table 1 for information on these 32 patients). Affected and unaffected siblings were also assessed, and 56% (237/426) had one child (simplex) and 44% (189/426) had more than one child (multiplex) with ASD. Most cases were screened for fragile X mutations (75%) and if detected they were not included in the study. Most experiments were performed on blood genomic DNA (80%), otherwise the source was cell lines, e.g. lymphoblast cell lines. Population ancestry was estimated using STRUCTURE (Falush et al. Genetics 2003; 164(4):1567-87; Pritchard et al. Genetics 2000; 155(2):945-59).
For each sample, approximately 500,000 SNPs were genotyped using the combined two-chip Nspl and Styl GeneChip® Human Mapping Commercial or Early Access Arrays (Affymetrix, Inc., Santa Clara, Calif.) according to the manufacturer's instructions and as described previously (Kennedy et al. 2003 Nat Biotechnol. 21:1233-7, the contents of which are incorporated herein by reference). Briefly, 250 ng of genomic DNA was digested with Nspl and Styl restriction enzyme (New England Biolabs, Boston, Mass.), ligated to an adaptor and amplified by PCR. The PCR products were then fragmented with DNaseI to a size range of 250 bp to 2,000 bp, labelled, and hybridized to the array. After hybridization, arrays were washed on the Affymetrix fluidics stations, stained, and scanned using the Gene Chip Scanner 3000 7G and Gene Chip Operating System. Data has been submitted to the Gene Expression Omnibus database (accession GSE9222). Karyotypes were generated using standard clinical diagnostic protocols.
Nspl and Styl array scans were analyzed for copy number variation using a combination of DNA Chip Analyzer (dChip) (Li and Wong 2001 Genome Biology 2: 0032.1-0032.11), Copy Number Analysis for GeneChip (CNAG) (Nannya 2005 Cancer Res. 65:6071-9) and Genotyping Microarray based CNV Analysis (GEMCA) (Komura 2006 Genome Res. 16:1575-84). Each of these references is incorporated herein by reference.
Analysis with dChip (www.dchip.org) was performed as previously described (Zhao et al 2005 Cancer Res. 65:5561-70) in batches of ˜100 probands. Briefly, array scans were normalized at the probe intensity level with an invariant set normalization method. After normalization, a signal value was calculated for each SNP using a model-based (PM/MM) method. In this approach, image artifacts were identified and eliminated by an outlier detection algorithm. For both sets of arrays, the resulting signal values were averaged across all samples for each SNP to obtain the mean signal of a diploid genome. From the raw copy numbers, the inferred copy number at each SNP was estimated using a Hidden Markov Model (HMM).
For analyses with CNAG version 2.0 (www.genome.umin.jp), the reference pool was set to include all samples and performed an automatic batch pair-wise analysis using sex-matched controls. Test samples were compared to all samples within the reference pool and matched based on signal intensity standard deviations. The scan intensities for each ‘test’ sample were compared to the average intensities of the reference samples (typically the average of 5-12 samples) and used to calculate raw copy number changes. Underlying copy number changes were then inferred using a Hidden Markov Model (HMM) built into CNAG.
GEMCA analysis was performed essentially as described (Komura et al. Genome Res 2006; 16(12):1575-84) with the exception that two designated DNA samples (NA10851 and NA15510) were used as references for pair-wise comparison to all proband experiments. These results were further filtered by only including those CNVs that were common to both pair-wise experiments.
CNVs were merged if they were detected in the same individual by more than one algorithm using the outside probe boundaries.
Control samples consisted of (i) CNVs observed in 500 Europeans from the from the German PopGen project (Krawczak et al. Community Genet 2006; 9(1):55-61), and CNVs found in a cohort of 1000 Caucasian non-disease controls from the Ontario population (ref. 24). The ACRD that had 834 putative CNVs or breakpoints mapped to the genome was established. A CNV was considered ASD-specific if it was >10 kb, contained at least three probes and at least 20% of its total length was unique when compared to controls.
PCR validation of CNV calls was performed using Quantitative Multiplex PCR of short fluorescent fragments (QMPSF) (Redon et al. Nature. 444:444-54) or SYBR-Green 1 based real-time quantitative PCR (qPCR) using controls at the ACCN1, CFTR or FOXP2 loci (PMID: 14552656). For both methods, primers were designed using the program PRIMER3 (http://frodo.wi.mit.edu/). Balanced rearrangements were mapped primarily using FISH (Nannya et al. Cancer Res 2005; 65(14):6071-9). The microdel program (Komura et al., ibid) was used to score CNV losses.
For QMPSF, short genomic sequences (140-220 bp) within putative CNVs were PCR amplified using dye-labelled primers corresponding to unique sequences. Each reaction also included co-amplified control amplicons corresponding to either ACCN1 or CFTR located at 17q11.2 and 7q31.2, respectively. Briefly, 40 ng of genomic DNA was amplified by PCR in a final volume of 25 μl using AmpliTaq® DNA polymerase (manufactured for Applied Biosystems by Roche Molecular Systems, Inc.) After an initial step of denaturation at 95° C. for 5 minutes conditions were as follows: 25 PCR cycles of 94° C. for 30 seconds, annealing at 60° C. for 45 seconds, and extension at 72° C. for 30 seconds. A final extension step at 72° C. for 15 minutes followed. QMPSF amplicons were separated on an ABI 3730 xl DNA Analyzer (Applied Biosystems, Foster City, Calif.), and analyzed using ABI GeneMapper® software version 3.7 (Applied Biosystems). After adjustment of control amplicons to the same heights, the QMPSF pattern generated from test DNA was superimposed to that of the control DNA. For each putative CNV locus, the copy number ratio was determined by dividing the normalized peak height obtained from the test DNA by that of the control DNA. Peak ratios of >1.4 and <0.7 were indicative of copy number gains and losses, respectively. At least two independent QMPSF assays were required for CNV confirmation.
SYBR Green I-based real-time qPCR amplification was performed using a Mx3005P quantitative PCR system (Stratagene, La Jolla, USA). Non-fluorescent primers were designed to amplify short genomic fragments (<140 bp) in putative CNV loci. Each assay also included amplification of a control amplicon corresponding to FOXP2 at 7q31.1 for comparison. After optimization of primer sets with control genomic DNA using ‘Brilliant® SYBR® Green QPCR Master Mix’ (Stratagene), test samples were assayed in 15 μl reaction mixtures in 96-well plates containing: 7.5 μl of reaction mix, 1.8 μl of primer, 6.0 ng of genomic DNA at 1.2 ng/μl, 0.225 μl of reference dye with 1:500 dilution, and 0.475 μl of water. PCR conditions consisted of 10 minutes of polymerase activation at 95° C., followed by 40 cycles of: 95° C. for 15 seconds and a single step at 60° C. for 1 minute for annealing and elongation. These steps were then followed by a final cycle of 95° C. for 1 minute, 55° C. for 30 seconds, and 95° C. for 30 seconds. Standard curve quantification was analyzed by MxPro-Mx3005P software (version 3.20 Build 340) to calculate copy number changes. Coefficient of variation (CV) was calculated on all sample Ct values to remove possible outlier when CV was greater than 1%. The average quantity of the putative CNV locus was divided by the average quantity of the control amplicon on FOXP2. Ratios of >1.4 and <0.7 were indicative of copy number gains and losses, respectively. Each putative CNV locus had at least two independent assays.
A total of 426 ASD index cases were tested for CNV content including 394 typical idiopathic cases and 32 others that were enrolled based on prior knowledge of having a cytogenetic abnormality. The Affymetrix 500k SNP array was used because it provided the highest resolution screen available for both SNP genotype and CNV data. Using the SNPs, the ancestry of each sample was categorized (to guide selection of controls). Backgrounds of the samples were found to be: 90.3%, 4.5%, 4.5%, and 0.7%, European, European/mixed, Asian, or Yoruban, respectively.
To maximize CNV discovery, three calling algorithms were used as described above (see
This ‘stringent’ dataset contained 1312 CNVs (˜3 CNVs per genome, mean size 603 kb). Using q-PCR, 48% (12/26) and 96% (48/50) of random CNVs were validated in the full and stringent collections, respectively.
1Not seen in controls.
2Stringent dataset as called by >1 algorithms or arrays. Analysis with dChip was performed in batches of ~100 probands. For CNAG version 2.0, the reference pool was set to include all samples and performed an automatic batch pairwise analysis using sex-matched controls. For GEMCA two designated DNA samples (NA10851 and NA15510) were used as references for pairwise comparison to all proband experiments. These results were further filtered by only including those CNVs that were common to both pairwise experiments. In all instances CNVs were merged if they were detected in the same individual by more than one algorithm using the outside probe boundaries.
3CNV/genome breakdown by algorithm: dChip Merged (3.0/genome), CNAG Merged (5.6/genome), GEMCA (5.5/genome). Validation experiments using q-PCR and FISH are described in the text. Another form of validation comes from examining the trios where we can demonstrate inheritance in 48 (maternal is 25, paternal is 23) of the autism-specific stringent dataset. Also from the trios, 148 confirmed regions (inheritance assignment) in the stringent dataset that overlap with controls (maternal is 65, paternal is 83).
4Represents the total number of overlapping and/or recurrent CNVs, the number of overlapping/CNV loci, and the percentage of overlapping CNVs, out of the total dataset.
Five hundred European control samples were examined for their CNV content and similar numbers of CNVs (3695 in the full and 1558 in the stringent dataset) were found to those in the ASD cases (Table 4). This suggested germ-line chromosome instability was not a significant contributing mechanism. The ASD CNVs were then compared against the 500 European/Caucasian controls and the Database of Genomic Variants (a repository of structural variation in ‘non-disease’ populations) (Iafrate et al. Nat Genet 2004; 36(9):949-51) to establish autism-specific CNV datasets. The subsequent analysis then focused on the 276 CNVs in the stringent autism-specific category, which mapped across all 23 chromosomes (
Wide-ranging prevalence frequencies of cytogenetically detectable chromosomal abnormalities in ASD, and the inability of microarray scans to find balanced abnormalities, prompted karyotyping to be performed. Karyotyping (and FISH) also provided the ability to characterize the chromosomal context (e.g. ring chromosomes) of some of the CNV regions, something not possible using microarrays alone. Therefore, 313 unbiased idiopathic cases where blood was available were examined and 5.8% (18/313) cases were found to have balanced (11) or unbalanced (7) karyotypes (all unbalanced karyotypic changes (7) were also found by microarray analysis and are included in the CNV statistics). The genomic characteristics of all CNVs are shown in the Autism Chromosome Rearrangement Database (see
Structural variants found in ASD cases were initially prioritized to possibly be etiologic if they were not in controls and, (i) de novo in origin (25 cases) (see Table 5 below), (ii) overlapping (27 cases at 13 loci) in two or more unrelated samples (see Table 7 below), (iii) recurrent (same breakpoints) in two or more unrelated samples (four cases at two loci), (iv) or inherited (the remainder). In a proof of principle analysis, CNVs were found at known ASD loci: NLGN4 and 22q, 15q, SHANK3 and NRXN1 in categories i, ii, iii, and iv, respectively. ASD structural variants found in controls (eg. NRXN1) could also be involved.
1Table is sorted based on family type. Probands with abnormal karyotypes (CHR) (1-14) are separated from probands belonging to simplex (SPX) and multiplex (MPX) families with normal karyotypes(15-25).
2De novo event detected by either karyotype (k) or microarray (a)
3De novo CNV/translocation has been confirmed by at least one of karyotype, FISH, or qPCR. CNV size is based on array results. The breakpoints have not been accurately defined, and CNVs may be smaller or larger than posted.
4When only a single gene is involved if the CNV intersects (suggesting it may disrupt the gene) the term ‘exonic’ is used and if the CNV encompasses the entire gene the term ‘whole’ is used.
5For multiplex families the de novo events were not detected in affected siblings.
1Families are grouped based on simplex (SPX), multiplex (MPX) and chromosomal abnormalities (CHR). Simplex families with affected monozygotic twins is denoted as SPX-MZ. The de novo cases also appear in Table 2 and some of the family pedigrees are shown in FIG. 2 and Supplemental FIG. 2.
2CNV size is based on array results. The breakpoints have not been accurately defined, and CNVs may be smaller or larger than posted.
3When only a single gene is involved if the CNV intersects (suggesting it may disrupt the gene) the term ‘exonic’ is used and if the CNV encompasses the entire gene the term ‘whole’ is used.
4CNV is only called by one algorithm
By testing parental DNA and validating CNVs, a de novo mutation rate of 7.1% (4/56) and 2.0% (1/49) was observed in idiopathic simplex and multiplex families, respectively. There was parental information for 13 of 18 cases discovered to carry cytogenetic abnormalities and 7 (6 simplex, 1 multiplex) of these were de novo in origin. Since only 1/7 (from a simplex family) of these was balanced and directly interrupting a gene, it was estimated that this class of rearrangements had much less of a contribution than CNVs to the total rate of de novo and structural variation in the present cohort.
The collective data identified 25 de novo cases (Table 5) and in three, two or more events were identified. Notably, in family SK0152 (
The 13 loci where overlapping ASD-specific CNVs were found are likely indicative of ASD-susceptibility since they arise in two or more unrelated families. In six, gains and losses often encompassing entire genes were observed at the same locus (Table 6) suggesting general gene dysregulation to be involved.
Using q-PCR or by assessing SNP patterns, 196 inherited CNVs (90 maternal and 106 paternal) were confirmed. No sub-grouping of these demonstrated obvious parent-of-origin effects (the two chromosome 15q11-q13 duplications detected were both de novo in origin). A 160 kb deletion was detected in a male inherited from a carrier mother, leading to a null PTCHD1 in the proband and his dizygotic twin brother (
New ASD candidates identified were those with a structural change (either de novo or found in two or more unrelated ASD cases, or for the X chromosome an allele being transmitted maternally from an unaffected carrier) specific to that gene, including ANKRD11, DLGAP2, DPP6, DPP10, DPYD, PCDH9 and PTCHD1 (Tables 5 and 6). As previously noted, NLGN4, SHANK3 and NRXN1 were also identified. The PCDH9 and NRXN1 genes are also found as CNVs in controls in the DGV (Database of Genomic Variants).
Additional positional candidate genes identified were those found interrupted by balanced cytogenetic breakpoints including NEGR1, PIP5K1B, GABRG1, KLHL3, STK3, ST7, SATB2 (Table 1). Moreover, 77 CNVs in the stringent dataset overlapped with the Autism Chromosome Rearrangement Database providing a second line of evidence for involvement (
DPP6 and DPP10 emerge as being positional and functional candidates. DPP6 (˜1.5 Mb in size at 2q14.1) and DPP10 (˜1.3 Mb at 7q36.2) code for accessory trans-membrane dipeptidyl peptidase-like subunits that affect the expression and gating of Kv4.2 channels (KCND2). Kv4.2 channels function in regulation of neurotransmitter release and neuronal excitability in the glutamatergic synapse at the same sites where SHANK3 and the NLGN gene products are found. In addition, autism balanced breakpoints have been mapped near KCND2 at 7q31.
For DPP10 there are inherited CNV gains and losses (Table 5,
Structural variants overlapping loci involved in medical genetic conditions including Waardenburg Type IIA (3p14.1), speech and language disorder (7q31), mental retardation (MRX15q23-q24, 16 μl 1.2) and velocardialfacial syndrome (VCFS) (22q13) were identified (Table 5), amongst others. Identification of the structural variant at these loci led to clinical re-assessment and either identification or refinement of the diagnosis, for additional syndromic features. Other instances (eg. SK0186-PTCHD1 deletion) (
The identification of a de novo deletion (2.7 Mb) at 22q11.2 in two ASD brothers led to their re-examination and diagnosis for VCFS. The re-testing also further defined the siblings to be at opposite ends of the ASD spectrum (
A recurrent ˜500 kb duplication at 16p11.2 in two ASD families (SK0102 and NA0133) (
In sum, using the genome-wide scanning approach, numerous new putative-ASD loci (Tables 4 and 5,
CNVs that implicate ASD loci include the SHANK3, NLGN, and NRXN1-PSD genes and also identify novel loci at DPP6 and DPP10 (amongst others including PCDH9, RPS6KA2, RET from the full dataset) were identified.
Lastly, six unrelated ASD cases were identified (Table 6) that had either CNV gains or losses at the same locus which indicate that gene expression of genes in these regions are related to the development of speech and language and/or social communication in humans, as in SHANK3 and genes in the Williams-Beuren syndrome locus.
As set out above, a genome scan with Affymetrix 500K SNP Arrays was used to identify a CNV deletion on chromosome Xp22.11 that spans exon 1 of the PTCHD1 gene. Exon 1 is shown bolded in
The deletion was determined to be an ˜156 kb deletion on Xp22.11 on a male proband. The physical position of this CNV is chrX: 22,962,800-23,119,000 (UCSC 2004 Assembly). The deletion is flanked by SNP probes rs7055928 and rs1918560 (at 22.956 and 23.133 Mb from the Xp terminus, respectively). The most proximal and distal SNPs (from the Affymetrix SNP microarrays) within the deleted region, as determined by the SNP microarray analysis, are rs7879064 (23.119 Mb) and rs4828958 (22.972 Mb). PCR amplicons from within the deleted region were used to confirm the deletion by Qpcr (PCR primers and locations are given below). This deletion spans the entire exon 1 of the PTCHD1 gene (NM 173495). Analysis of both Sty and Nsp chips data identified this event and was further validated using PCR and QPCR techniques. The following primers were used:
This CNV is autism specific as it was not present in the Database of Genomic Variants (DGV) and in other controls. Furthermore, the segregation of this deletion was characterized in family and it was identified that the deletion was transmitted from a heterozygous mother. A male sibling also had language deficits.
Mutation screening of PTCHD1 in N=400 autism patients was conducted in the usual manner. The following primers were used:
The mutation screening revealed an 1173V mutation.
By sequencing the entire coding region of PTCHD1 in 900 unrelated ASD cases, six missense mutations were identified in six unrelated ASD probands (Table 7,
All these mutations resulted in the substitution of highly conserved amino acids, and were inherited from unaffected carrier mothers. Based on in silico protein modeling, three mutations (L73F, I173V, V195I) are present in a predicted amino acid loop that sits outside of the cell membrane. This loop is posited to interact with the ligand, Hh. Another mutation, the 2-amino acid substitution ML336-3371I was present within a predicted transmembrane domain. Finally, the E479G mutation was present within a predicted cytoplasmic amino acid loop. In five out of six families, these mutations segregated with the phenotype. Controls (439) were tested for the I173V and V195I mutations, 500 controls for ML336-3371I, and 282 controls for L73F and E479G. None of these mutations were present in controls. Furthermore, the fact that these mutations were all maternally inherited to male probands, and were not observed in our control populations, indicates that the mutations are associated with ASD. In turn, it is reasonable to assume that these mutations contribute to the etiology of autism, and perhaps in-combination with other disease-related loci, give rise to the ASD phenotype.
Interestingly, in two of the ASD families reported in Tables 7/8 (Family-2 & Family-4), other ASD-related CNVs were identified. In family 2, in addition to I173V mutation, a de novo ˜1.0 Mb loss at 1p21.3 resulting in deletion of the entire DPYD gene (NM_000110.3) was identified. DPYD encodes a rate-limiting enzyme, dihydropyrimidine dehydrogenase (DPD), involved in pyrimidine metabolism. Complete DPD deficiency results in highly variable clinical outcomes, with convulsive disorders, motor retardation, and mental retardation being the most frequent manifestations. In Family-4, in addition to the V195I mutation, a 66 Kb de novo loss at 7q36.2 was identified resulting in deletion of DPP6 exon 3, and 33 amino acids towards the N-terminal end of the DPP6 protein. These cases evidence digenic involvement in ASD.
The ability of these. PTCHD1-mutants to repress Gli2 expression was compared with wild type to determine if there was loss of function in the mutants. NIH10T1/2 fibroblasts were transfected with CMV-empty vector, a Gli-responsive promoter fused to the Luciferase gene (Gli2 pro), β-Gal (normalization) and PTCHD1 mutant expression plasmids. A mild loss of function of at least the E479G and ML336-711 mutants resulted in increased expression of Gli2 compared to wild type.
| Number | Date | Country | |
|---|---|---|---|
| 60960572 | Oct 2007 | US | |
| 61008294 | Dec 2007 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 14630205 | Feb 2015 | US |
| Child | 16694314 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | 12681229 | Jun 2010 | US |
| Child | 14630205 | US |
