Literature DB >> 23879678

Identification of candidate intergenic risk loci in autism spectrum disorder.

Susan Walker1, Stephen W Scherer.   

Abstract

BACKGROUND: Copy number variations (CNVs) and DNA sequence alterations affecting specific neuronal genes are established risk factors for Autism Spectrum Disorder (ASD). In what is largely considered a genetic condition, so far, these mutations account for ~20% of individuals having an ASD diagnosis. However, non-coding genomic sequence also contains functional elements introducing additional disease risk loci for investigation.
RESULTS: We have performed genome-wide analyses and identified rare inherited CNVs affecting non-genic intervals in 41 of 1491 (3%) of ASD cases examined. Examples of such intergenic CNV regions include 16q21 and 2p16.3 near known ASD risk genes CDH8 and NRXN1 respectively, as well as novel loci contiguous with ZHX2, MOCS1, LRRC4C, SEMA3C, and other genes.
CONCLUSIONS: Rare variants in intergenic regions may implicate new risk loci and genes in ASD and also present useful data for comparison with coming whole genome sequence datasets.

Entities:  

Mesh:

Year:  2013        PMID: 23879678      PMCID: PMC3734099          DOI: 10.1186/1471-2164-14-499

Source DB:  PubMed          Journal:  BMC Genomics        ISSN: 1471-2164            Impact factor:   3.969


Background

Newer genomic technologies like high-resolution microarrays and next generation exome sequencing have enabled the identification of many clinically relevant genetic variants for both Mendelian and complex disorders. Yet for many conditions the identified genes account for only a proportion of heritability. This observation coupled with the recognition of the functional relevance of non-genic regions [1] target these genomic segments as candidates for investigation for a role in disease. ASD encompasses a range of neurodevelopmental disorders characterised by social impairment, communication difficulties and restricted, repetitive behavioural patterns. ASD, which is clinically and genetically heterogeneous, demonstrates high heritability, familial clustering and ~4:1 male to female bias. While there has been progress identifying risk genes, most are still unknown [2]. Analyses of rare (<1% population frequency) CNVs, insertions and deletions (indels) and point mutations have most convincingly identified synaptic genes such as members of the Neuroligin (NLGN3, NLGN4)[3], Neurexin (NRXN1 [4], NRXN2 [5], NRXN3 [6]), SHANK (SHANK1 [7], SHANK2 [8], SHANK3 [9]) families and Gephyrin [10] as highly-penetrant risk loci [2]. ASD subjects with multiple genetic risk factors for ASD and associated medical conditions are also known [11]. In addition, there are a few examples of mutations in ASD cases identified in non-genic segments of DNA [12] and non-coding RNAs [13]. Similar findings are even better documented in studies of intellectual disability [14,15], which is observed in ~40% of cases of ASD. Focusing on the intergenic intervals of the genome, we performed a systematic genome-wide investigation to identify rare CNVs enriched in cases compared with controls [16] to identify known and novel ASD susceptibility loci.

Methods

A collection of 1491 unrelated ASD cases were genotyped using either the Illumina 1M (993) or the Affymetrix SNP 6.0 platforms (498). The ASD subjects, all diagnosed using gold-standard instruments including Autism Diagnostic Interview and Autism Diagnostic Observation Schedule, are described elsewhere [16,17]. Informed written consent was obtained from all participants, as approved by the Research Ethics Boards at The Hospital for Sick Children and McMaster University. For controls, 1287 samples from the SAGE cohort were genotyped on with the Illumina 1M and 1234 samples from the Ottawa Heart Institute (OHI) and 1123 from the POPGEN collections were genotyped on the Affymetrix SNP 6.0. CNV discovery was performed using previously described pipelines [16-18]. Three CNV detection tools were used for each platform (Birdsuite, iPattern and Genotyping Console for Affymetrix 6.0 and iPattern, QuantiSNP & PennCNV for Illumina 1 M). A subset of CNVs in both cases and controls were considered rare if they were present in <1% of the overall dataset and these were further analysed if they failed to intersect or fall within a known gene (according to the NCBI Reference Sequence (RefSeq), August 2011). Rare genic CNVs identified from these data have been reported previously and from these data approximately 10% of cases carry a de novo or rare inherited CNV thought to contribute to ASD in that individual [16,17,19,20]. All CNVs discussed were validated where DNA was available using independent laboratory methods such as long range or quantitative PCR and the mode of inheritance determined (Additional files 1 and 2).

Results and discussion

Microarray data from a cohort of 1491 unrelated ASD probands were analysed for rare copy number variants as described previously [16,17] and CNVs falling outside of known coding sequence were identified. A total of 212 non-coding genomic regions were determined as harboring overlapping CNVs in two or more unrelated ASD cases that were absent in control samples. Each region was examined for plausible biological function by comparison with multiple databases. Data was collated for evidence of expressed sequences from mRNA or EST data at GenBank or evolutionary conservation as well as functional predictions from the VISTA enhancer browser (http://enhancer.lbl.gov/) and Rfam (http://rfam.sanger.ac.uk/). The Database of Genomic Variants (http://dgvbeta.tcag.ca/dgv/app/home) was used to eliminate additional regions as non-ASD specific CNVs and regions with >80% masked as repetitive sequences were removed. Loci were also prioritised as being of potential clinical significance in ASD due to proximity to genes considered known or candidate ASD risk genes [17]. Fifteen intergenic regions emerged as plausible candidate ASD risk loci and in all instances the defining CNV events were inherited. In one of these regions, an additional case (SK0167-003) was found with an overlapping CNV described by Marshall et al. (2008) [19] (Table 1, Figure 1 and Additional files 1 and 2). In 14 of 15, the intergenic interval identified has not been described before and in three regions the CNV neighboured a known ASD gene, namely, CDH8 [21], C3orf58 [22] and NRXN1 [4]. In the case of the NRXN1 gene, upstream CNVs found in five individuals impact the same mRNA (AK127244) reported elsewhere with a CNV in a family with ASD (Table 1, Figure 1A) [23]. Examples of other intergenic CNVs identified highlight regions at 8q24.12 upstream of ZHX2, 6p21.2 upstream of MOCS1, 11p12 upstream of LRRC4C (Figure 1B) and 7q21.11 upstream of SEMA3C, as putative novel ASD rearrangements. In one case (8-14208-3350), deletions were identified at three separate loci; 4q13.1 upstream of EPHA5, 11p14.3 upstream of LUZP2 and 11p12 upstream of LRRC4C and another case (3-0496-003) carried a 46, XXY sex chromosome imbalance. Other CNVs found in these 41 cases are shown in Additional file 3 and any or all of these may be contributing to the genetic load for ASD [11,17]. Interestingly, all the CNVs identified through our analysis are inherited events. The significance of this observation is still to be determined but suggests incomplete and/or variable penetrance of phenotype, which is something often observed in ASD [6,7,17].
Table 1

ASD specific CNVs in intergenic regions

LocusGeneSampleCNVStartEndSizeFurthest distance from geneBin
2p16.3
NRXN1 AK127244 mRNA
1-0045-004
loss
51405882
51524684
118802
1124
ii
8-3394-003
loss
51439897
51479683
39786
8-3394-003
loss
51157414
51189362
31948
8-14144-2420
loss
51157414
51225851
68437
1-0496-003
gain
52220120
52238172
18052
1-0449-003
loss
52237072
52253660
16588
3p22.3
ARPP21
2-1213-003
loss
34984049
35102773
118724
563
ii
3-0100-000
gain
35086691
35094736
8045
3q24
C3orf58 ZIC1, ZIC4
1-0007-003
loss
146168760
146934953
766193
1383 1955, 1979
i
8-3093-004
loss
146575437
146631141
55704
4q13.1
EPHA5
8-14208-3350
loss
66505324
66633530
128206
840
i
8-14186-3050
loss
66515708
66633530
117822
1-0138-004
loss
66515708
66633530
117822
2-0082-004
loss
67045815
67134170
88355
1-0455-003
loss
67058506
67075558
17052
6p21.2
MOCS1
3-0139-000
gain
40021898
40078515
56617
168
i or ii
2-0139-003
gain
40023327
40062155
38828
1-0381-003
loss
40174188
40209324
35136
2-1368-003
loss
40174188
40210694
36506
7q21.11
SEMA3C
8-6258-03
loss
80431202
80512022
80820
96
i
1-0345-005
loss
80482597
80517630
35033
8p12
UNC5D NRG1
8-14243-3670
loss
34923482
34956067
32585
256 2183
i
3-0044-000
loss
34923482
34956067
32585
3-0300-000
loss
34925149
34957854
32705
8-14181-2940
loss
34923482
34956067
32585
8q24.13
ZHX2
8-3317-003
gain
123572785
123625681
52896
237
i or ii
3-0186-000
loss
123583028
123639417
56389
9q33.1
ASTN2
8-3055-004
loss
119254497
119374796
120299
98
i
3-0115-000
loss
119314967
119319559
4592
9q34.2
OLFM1 RXRA
2-1272-003
gain
136479329
136604233
124904
508 8
i
2-1189-003
gain
136480334
136598491
118157
11p14.3
LUZP2
8-14175-2820
loss
24177612
24316053
138441
160
i or ii
8-14059-1020
loss
24262511
24303132
40621
8-14208-3350
loss
24262511
24303132
40621
11p12
LRRC4C
8-14208-3350
gain
40304880
40703298
398418
196
iii
2-0272-003
loss
40379668
40550356
170688
SK0167-003
loss
40417554
40610400
192846
3-0208-000
loss
40468058
40492541
24483
11p12
LRRC4C
8-14032-600
loss
41990280
42021250
30970
1738
i or ii
8-3276-003
loss
42243624
42279094
35470
2-0286-003
loss
42243624
42279094
35470
11q13.2
MRGPRD
4-0023-003
loss
68486121
68493638
7517
10
i
2-1075-003
loss
68486121
68500238
14117
16q21
CDH8
8-14251-3750
loss
61650435
61787984
137549
1030
i or ii
  2-1175-003loss616586756175523296557  

Location and size of all CNVs discovered are listed with the proposed associated candidate gene. Bin denotes possible mechanism of action by i) altering sequence elements required for regulating expression of neighboring genes ii) affecting undiscovered genes or non-coding RNAs iii) disrupting uncharacterised isoforms of adjacent genes. Genome browser views of all loci are shown in Figure 1 and Additional file 1. All pedigrees are shown in Additional file 2. Additional sample SK0167-003 identified in reference [19].

Figure 1

Genome browser views of ASD specific CNVs at A) 2p16.3 B) 11p12 C) 8p12 and D) 4q13.1. In each case, representative isoforms of known RefSeq genes, mRNA and/or Expressed Sequence Tags are shown. Deletions and duplications are represented by red and blue bars, respectively. In Figure 1A) a dashed line indicates a diploid region located between two adjacent deletions in the same individual. Additional browser views from other loci shown in Table 1 are included in Additional file 1 A-J. In all cases where parental DNA was available, the CNVs shown were found to be inherited. Additional case SK0167-003 found in Marshall et al.[19].

ASD specific CNVs in intergenic regions Location and size of all CNVs discovered are listed with the proposed associated candidate gene. Bin denotes possible mechanism of action by i) altering sequence elements required for regulating expression of neighboring genes ii) affecting undiscovered genes or non-coding RNAs iii) disrupting uncharacterised isoforms of adjacent genes. Genome browser views of all loci are shown in Figure 1 and Additional file 1. All pedigrees are shown in Additional file 2. Additional sample SK0167-003 identified in reference [19]. Genome browser views of ASD specific CNVs at A) 2p16.3 B) 11p12 C) 8p12 and D) 4q13.1. In each case, representative isoforms of known RefSeq genes, mRNA and/or Expressed Sequence Tags are shown. Deletions and duplications are represented by red and blue bars, respectively. In Figure 1A) a dashed line indicates a diploid region located between two adjacent deletions in the same individual. Additional browser views from other loci shown in Table 1 are included in Additional file 1 A-J. In all cases where parental DNA was available, the CNVs shown were found to be inherited. Additional case SK0167-003 found in Marshall et al.[19]. The mechanism of action of these rare CNVs in the pathogenesis of ASD could be (i) through altering the necessary copy number or positional context of key DNA sequence elements required for regulating the proper expression of nearby genes [1], (ii) affecting still undiscovered genes or non-coding RNAs residing in the CNV regions and (iii) disrupting uncharacterized isoforms of the adjacent annotated genes. In the first scenario, we find CNVs both upstream (e.g. UNC5D (Figure 1C), MOCS1, ASTN2, SEMA3C, ZHX2, LUZP2, CDH8) and down-stream (C3orf58, RXRA, MRGPRD) of known ASD risk genes and putative novel loci. For at least three regions (4q13.1, 6p21.2 and 11p12 (shown in Figure 1D, Additional file 1C and Figure 1B respectively)), our CNV mapping data in fact identify two distinct clusters of CNVs at the same locus, all overlapping spliced ESTs and thus with a possible regulatory role. Secondly, three independent CNV deletions interrupting a collection of spliced expressed sequenced tags approximately 330 kb proximal to EPHA5 highlight a potentially newly discovered ASD risk gene (Figure 1D). Finally, longer isoforms of LRRC4C likely exist given the discovery of mRNAs DQ084201 and DQ084202. There are, of course, other functional DNA elements or modifications that need to be considered [24] as the mapping resolution increases.

Conclusions

Given the challenges faced in interpreting the clinical significance of multitudes of genetic variants found in for example, whole genome sequencing [25], accruing evidence across multiple studies will advocate loci outside of known genes or other regulatory elements for further study, particularly for rare variants. In this light, these data provide a useful resource for comparison as new data sets of both CNVs and nucleotide-level variants become available to help fine-map additional discover new ASD risk loci. This general research strategy can also be applied to other disease gene studies.

Competing interests

The authors declare that they have no competing interests.

Authors’ contributions

SW and SWS conceived the project and wrote the manuscript. SW designed the analysis, interpreted the data and conducted laboratory validation experiments. Both authors read and approved the final manuscript.

Additional file 1

Genome Browser views of loci with ASD specific CNVs. Click here for file

Additional file 2

Pedigree structure for all families listed in Table 1. Click here for file

Additional file 3

Table of all rare CNVs detected in the individuals described herein. Click here for file
  25 in total

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Journal:  Am J Hum Genet       Date:  2008-01-17       Impact factor: 11.025

3.  SHANK1 Deletions in Males with Autism Spectrum Disorder.

Authors:  Daisuke Sato; Anath C Lionel; Claire S Leblond; Aparna Prasad; Dalila Pinto; Susan Walker; Irene O'Connor; Carolyn Russell; Irene E Drmic; Fadi F Hamdan; Jacques L Michaud; Volker Endris; Ralph Roeth; Richard Delorme; Guillaume Huguet; Marion Leboyer; Maria Rastam; Christopher Gillberg; Mark Lathrop; Dimitri J Stavropoulos; Evdokia Anagnostou; Rosanna Weksberg; Eric Fombonne; Lonnie Zwaigenbaum; Bridget A Fernandez; Wendy Roberts; Gudrun A Rappold; Christian R Marshall; Thomas Bourgeron; Peter Szatmari; Stephen W Scherer
Journal:  Am J Hum Genet       Date:  2012-04-12       Impact factor: 11.025

4.  Contribution of SHANK3 mutations to autism spectrum disorder.

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Journal:  Am J Hum Genet       Date:  2007-10-16       Impact factor: 11.025

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Journal:  Science       Date:  2008-07-11       Impact factor: 47.728

6.  A noncoding, regulatory mutation implicates HCFC1 in nonsyndromic intellectual disability.

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Journal:  Am J Hum Genet       Date:  2012-09-20       Impact factor: 11.025

7.  Detection of clinically relevant genetic variants in autism spectrum disorder by whole-genome sequencing.

Authors:  Yong-hui Jiang; Ryan K C Yuen; Xin Jin; Mingbang Wang; Nong Chen; Xueli Wu; Jia Ju; Junpu Mei; Yujian Shi; Mingze He; Guangbiao Wang; Jieqin Liang; Zhe Wang; Dandan Cao; Melissa T Carter; Christina Chrysler; Irene E Drmic; Jennifer L Howe; Lynette Lau; Christian R Marshall; Daniele Merico; Thomas Nalpathamkalam; Bhooma Thiruvahindrapuram; Ann Thompson; Mohammed Uddin; Susan Walker; Jun Luo; Evdokia Anagnostou; Lonnie Zwaigenbaum; Robert H Ring; Jian Wang; Clara Lajonchere; Jun Wang; Andy Shih; Peter Szatmari; Huanming Yang; Geraldine Dawson; Yingrui Li; Stephen W Scherer
Journal:  Am J Hum Genet       Date:  2013-07-11       Impact factor: 11.025

8.  Mapping autism risk loci using genetic linkage and chromosomal rearrangements.

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Journal:  Nat Genet       Date:  2007-02-18       Impact factor: 38.330

9.  Deletions of NRXN1 (neurexin-1) predispose to a wide spectrum of developmental disorders.

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Journal:  Am J Med Genet B Neuropsychiatr Genet       Date:  2010-06-05       Impact factor: 3.568

10.  An integrated encyclopedia of DNA elements in the human genome.

Authors: 
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Journal:  J Comp Neurol       Date:  2014-09-22       Impact factor: 3.215

2.  Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder.

Authors:  Ryan K C Yuen; Daniele Merico; Matt Bookman; Jennifer L Howe; Bhooma Thiruvahindrapuram; Rohan V Patel; Joe Whitney; Nicole Deflaux; Jonathan Bingham; Zhuozhi Wang; Giovanna Pellecchia; Janet A Buchanan; Susan Walker; Christian R Marshall; Mohammed Uddin; Mehdi Zarrei; Eric Deneault; Lia D'Abate; Ada J S Chan; Stephanie Koyanagi; Tara Paton; Sergio L Pereira; Ny Hoang; Worrawat Engchuan; Edward J Higginbotham; Karen Ho; Sylvia Lamoureux; Weili Li; Jeffrey R MacDonald; Thomas Nalpathamkalam; Wilson W L Sung; Fiona J Tsoi; John Wei; Lizhen Xu; Anne-Marie Tasse; Emily Kirby; William Van Etten; Simon Twigger; Wendy Roberts; Irene Drmic; Sanne Jilderda; Bonnie MacKinnon Modi; Barbara Kellam; Michael Szego; Cheryl Cytrynbaum; Rosanna Weksberg; Lonnie Zwaigenbaum; Marc Woodbury-Smith; Jessica Brian; Lili Senman; Alana Iaboni; Krissy Doyle-Thomas; Ann Thompson; Christina Chrysler; Jonathan Leef; Tal Savion-Lemieux; Isabel M Smith; Xudong Liu; Rob Nicolson; Vicki Seifer; Angie Fedele; Edwin H Cook; Stephen Dager; Annette Estes; Louise Gallagher; Beth A Malow; Jeremy R Parr; Sarah J Spence; Jacob Vorstman; Brendan J Frey; James T Robinson; Lisa J Strug; Bridget A Fernandez; Mayada Elsabbagh; Melissa T Carter; Joachim Hallmayer; Bartha M Knoppers; Evdokia Anagnostou; Peter Szatmari; Robert H Ring; David Glazer; Mathew T Pletcher; Stephen W Scherer
Journal:  Nat Neurosci       Date:  2017-03-06       Impact factor: 24.884

3.  Whole Genome Sequencing as a Genetic Test for Autism Spectrum Disorder: From Bench to Bedside and then Back Again.

Authors:  Michael J Szego; Ma'n H Zawati
Journal:  J Can Acad Child Adolesc Psychiatry       Date:  2016-05-01

4.  Opportunities and challenges in modeling human brain disorders in transgenic primates.

Authors:  Charles G Jennings; Rogier Landman; Yang Zhou; Jitendra Sharma; Julia Hyman; J Anthony Movshon; Zilong Qiu; Angela C Roberts; Anna Wang Roe; Xiaoqin Wang; Huihui Zhou; Liping Wang; Feng Zhang; Robert Desimone; Guoping Feng
Journal:  Nat Neurosci       Date:  2016-08-26       Impact factor: 24.884

5.  Weak association of glyoxalase 1 (GLO1) variants with autism spectrum disorder.

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Review 6.  Cadherin-based transsynaptic networks in establishing and modifying neural connectivity.

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7.  SFARI genes and where to find them; modelling Autism Spectrum Disorder specific gene expression dysregulation with RNA-seq data.

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Review 8.  Genetic insights and neurobiological implications from NRXN1 in neuropsychiatric disorders.

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Journal:  Mol Psychiatry       Date:  2019-05-28       Impact factor: 15.992

9.  Noncoding copy-number variations are associated with congenital limb malformation.

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Journal:  Genet Med       Date:  2017-10-12       Impact factor: 8.822

10.  Performance of case-control rare copy number variation annotation in classification of autism.

Authors:  Worrawat Engchuan; Kiret Dhindsa; Anath C Lionel; Stephen W Scherer; Jonathan H Chan; Daniele Merico
Journal:  BMC Med Genomics       Date:  2015-01-15       Impact factor: 3.063

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