Associated disorders and their rate in autism (from Volkmar
1. Introduction
The field of genetics has made considerable scientific progress in the past several years and continues to evolve at a rapid pace. This progress parallels developments in genomic technology, where instrumentation and methodology are becoming increasingly sophisticated and cost-effective. Here, we review recent developments in understanding autism spectrum disorder (ASD) from a genomics perspective. A large catalog of common and rare variants has now been associated with ASD, and we are beginning to see some of these discoveries translate into pharmacogenomic intervention. This review provides an overview of genome-wide association studies (GWAS) and common genetic variants, followed by an overview of the status of rare variant research, which have risen to prominence with the proliferation of next-generation sequencing and techniques for identifying copy number variants. While these approaches need not be mutually exclusive, they provide a useful structure for organizing relevant genetic factors. Although there is much work to be done before these discoveries will enter the clinic, the past decade has seen us make major inroads in elucidating the causes of ASD and making tentative steps towards developing treatments.
1.1. Defining the autism phenotype
Autism is known to be highly heterogeneous, and this phenomenon has made definitions of the phenotype somewhat problematic. The American Psychiatric Association recently proposed revisions to its Diagnostic and Statistical Manual of Mental Disorders V (DSM-5) criteria for ASD (see Wing
For large-scale genome analyses, DSM criteria have been considered insufficiently precise, and cases are often selected using scores from the Autism Diagnostic Interview (ADI-R) [2], Autism Diagnostic Observation Schedule (ADOS) [3], and/or Social Responsiveness Scale (SRS) [4]. These instruments offer a more robust psychometric platform, and cases defined as “autism” are required to meet strict threshold criteria (e.g. all sub-dimensions of the ADI-R and ADOS). Individuals not quite meeting these criteria may be subsumed under the “broader” autism phenotype, which also typically includes Asperger syndrome, childhood disintegrative disorder and pervasive developmental disorder not otherwise specified. A diagnosis of Rett syndrome—which has a reportedly distinct pathophysiology, clinical course, and diagnostic strategy (Levy, Mandell & Schultz, 2009) [5] and will likely be removed in the impending publication of DSM-V—is typically exclusionary. Intellectual impairment, which is often co-morbid with ASD (Dawson
Standardization of diagnostic criteria has facilitated the accumulation of large ASD sample-sets, where institutions can share (de-identified) data. In this vein, initiatives such as the Autism Genome Project include data from several thousand ASD individuals, greatly increasing statistical power of relevant analyses.
1.2. Heritability of ASD
Although Skuse (2007) [8] cautions that heritability estimates of ASD may have been skewed by the co-inheritance of (low) intelligence or other variables, there is little doubt that genetic factors play a key role in autism. In the most widely-cited twin study, Bailey
1.3. Early genetic studies – insights from Rett syndrome and Fragile X
Early efforts to identify the genetic causes of ASD utilized linkage and association approaches. Linkage studies, more prominent in the 1980s and 1990s, typically focus on families or larger pedigrees and are well powered to identify rarer genetic variants. The most common linkage approach is the affected sib-pair design (see O’Roak & State, 2008) [13], which examines the transmission of genomic segments through generations. Linkage studies helped define the locus containing
Association studies take a different approach. Rather than track transmission of specific genomic regions through generations, association studies scan the breadth of the genome. Here, the goal is to determine
These early insights have played an important role in shaping our current understanding of ASD. Functional studies of
2. Genome wide association and common variants
Aside from notable successes with fragile X and Rett syndrome, early linkage and association studies have been inconsistent in resolving more complex genetic correlates of ASD, and candidate genes have often not being replicated between studies. These challenges may in part be accounted-for by their relatively low resolution/coverage, making it difficult to detect candidate loci other than those of major effect. A shift in technology was required to get beyond such challenges, which was engendered by the introduction of high-resolution single nucleotide polymorphism (SNP) arrays. SNP arrays provided coverage of many thousand (now several million) common SNPs, which could be examined at a relatively low cost across large sample sets.
Genome-wide association studies (GWAS) examine the frequency of SNPs in case
GWAS test for common variants (>1% population frequency), with the assumption that ASD are at least in part caused by the coinheritance of multiple risk variants, each of small individual effect (odds ratios typically between ~1:1 and ~1:5). This assumption is known as the common disease-common variant (CDCV) model (Risch & Merikangas, 1996) [20].
2.1. The 5p14.1 locus
A 2009 paper from our laboratory (Wang et al., 2009 [21]) was the first to identify common variants for ASD on a genome-wide scale. Our group examined 780 families (3,101 individuals) with affected children, a second, independent group of 1,204 affected individuals, and 6,491 controls. All were of European ancestry. We identified six genetic markers on chromosome 5 in the 5p14.1 region that confirmed susceptibility to ASD. This locus has been replicated in two additional independent cohort studies (Ma
As shown in Figure 1, the region straddles two genes,
Basing their analyses on the genomic region surrounding the rs4307059 locus, the authors used a bioinformatics approach (i.e. Genome Browser) to examine relevant expressed sequence tags (ESTs) and RNA (by Tiling Array within the 100-kb linkage disequilibrium at the GWAS peak). Only one functional element—a single noncoding RNA—was located. The 3.9-kb RNA corresponded to moesin pseudogene 1 (
Follow-up analyses by the group largely confirm that
The group next used genotype—determined from three associated SNPs from the original Wang
Although Western blot analyses did not identify significant differences in moesin protein levels between cases and controls, overexpressing
Taken as a whole, these results provide compelling support for 5p14.1 as a risk locus for ASD. Although sample sizes for some analyses were small (10 ASD-control pairs for postmortem studies), this quite rigorous series of experiments draws a clear path from GWAS result through functional validation. As such, these results help allay criticism of the GWAS approach as a means of candidate discovery. Thus, a 2010 review by McClellan and King (2010) [27] singled out the 5p14.1 locus as an example of the “perils of cryptic population stratification”. These comments seemed somewhat misguided in the light of rigorous methodologies developed by the GWAS community for controlling stratification (e.g. EigenStrat) [28], replication [22, 23], and now functional validation by the Kerin
Similarly, replication/validation of the 5p14.1 locus provides an important demonstration of the legitimacy of associations in intergenic regions. Again, McClellan and King had disputed the utility of such results, questioning how “genome-wide association studies come to be populated by risk variants with no known function?” It is important to emphasize that the GWAS approach typically does not tag the disease variant, but rather its approximate location—through linkage disequilibrium, this is typically 100kb or less. Moreover, as in the Kerin
Finally, these expression analyses provide a reminder about the capabilities of different genomic technologies. In the past twelve months, a number of high-profile next-generation sequencing (NGS) studies have been able to examine genomic correlates of ASD with unprecedented resolution. These types of studies—reviewed in greater depth below—have been interpreted as the future of ASD genetics and, to a large extent, this may be true. However, we note that DNA sequencing in the 5p14.1 region would not have identified the non-coding RNA at this locus. Thus, although NGS platforms used for RNA-sequencing are becoming increasingly sophisticated (Ozsolak & Milos, 2011) [29], microarray studies retain a place in guiding genomic discovery.
2.2. Other replicated common variants from candidate gene studies
A number of other common variants from candidate gene studies have been proposed as ASD risk factors. These include Contactin Associated Protein 2 (
Another locus indentified by the candidate gene approach is Engrailed 2 (
The oncogene
2.3. Unexplained variance
For the most significant discovery SNP identified in the Wang
Second, the results of our Crohn’s disease study suggest that in certain circumstances, there may be an explicit relationship between tagged variants and underlying rare variants. Thus, the distinction between loci harboring common
3. Rare variants – CNVs and next-generation sequencing
3.1. Copy number variation in ASD
CNVs are insertions, deletions, or translocations in the human genome that are universal in the general population (e.g. Pinto
One of the most widely-known CNVs is Down syndrome, which is characterized by an extra chromosome 21. Rett syndrome is also caused by a CNV, which includes a deletion in
Sebat
A number of subsequent studies have greatly expanded the number of candidate loci using the CNV approach. Our laboratory (Bucan
Glessner
In a similar approach, Pinto
Finally, Gai
Collectively, these CNV studies suggest that certain hotspots on the genome are particularly vulnerable to ASD, which include loci on chromosomes 1q21, 3p26, 15q11-q13, 16p11, and 22q11. These hotspots are part of large gene networks that are important to neural signaling and neurodevelopment and have additionally been associated with other neuropsychiatric disorders. In particular, a number of CNV studies in schizophrenia have highlighted structural mutations incorporating chromosomes 1q21, 15q13, and 22q11 (e.g. Glessner
3.2. Sequencing familial forms of ASD
To this point, we have focused primarily on the complex interactions of polygenic networks as the major cause of ASD. However, this is not exclusively the case. Paralleling the recent spate of CNV studies is a renewed focus on rare disorders. These include familial forms of complex diseases that are potentially monogenic or with less complex inheritance pattern. At the outset of this chapter, we emphasized the overlap with fragile X syndrome, where one third of cases are co-morbid for ASD. As mentioned, fragile X is caused by a failure to express the protein coded by
X-linked genes encoding neurologins
The identification of monogenic or possibly oligogenic autisms is likely to accelerate in the next several years as NGS becomes more widely available. In our group, we recently encountered a family of two parents, six healthy siblings, and two siblings with severe autism suggestive of autosomal recessive inheritance. Unsuccessful attempts using linkage and CNV approaches failed to identify a causal locus, but whole-exome sequencing at 20x coverage identified four genes, including one with a non-synonymous SNP in the protocadherin alpha 4 isoform1 precursor (
Known syndromes with ASD features include fragile X, neurofibromatosis type 1, down syndrome, tuberous sclerosis, neurofibromatosis (which confers a 100-fold increased risk for ASD Li
The proportion of ASD accounted for by rare variants remains to be determined. Irrespective, as with many other aspects of scientific inquiry, the study of these events will continue to play an important role in explicating the pathogenesis of ASD. El-Fishawy and State (2010) [72] point to hypercholesterolemia and hypertension (Brown, 1974; Lifton
Recent groundbreaking studies by Marchetto
|
|
|
|
Tuberous sclerosis | 11 | 1.1 | 0–3.8 |
Fragile X | 9 | 0.0 | 0–8.1 |
Down syndrome | 12 | 0.7 | 0–16.7 |
Neurofibromatosis 1 | 6 | 0 | 0–1.4 |
3.3. Large-scale next-generation sequencing
In April 2012,
O’Roak
Among the identified
Neale
The group next performed PPI analyses to determine whether interactions between genes associated with
In the third of these Nature papers, Sanders
Combining the exomes from their study with those from O’Roak
It is important to note, however, that for
In a fourth independent exome sequencing study involving 343 families from the Simons Simplex Collection Iossifov
The authors subsequently screened for
Collectively, all four of these exome sequencing studies converge upon the conclusion that ASD is highly heterogeneous, with several hundred or more loci potential risk variants. Simulations by the Neale
4. Toward a treatment?
Ultimately, the primary goal of genome research should be to propose targets for intervention. As mentioned above, a number of translational studies have begun to probe the metabotropic glutamate receptor, mGluR5, as a potential target for fragile X syndrome treatment. These studies have a theoretical basis in the hypothesis that protein-synthesis-dependent functions of metabotropic receptors are exaggerated in fragile X syndrome (Bear, Huber & Warren, 2004) [87]. Thus, the fragile X protein, FMRP, is thought to work in functional opposition to mGluR5 (and mGluR1). Where FMRP is absent, mGluR-dependent protein synthesis becomes over-activated, resulting in neurological and behavioral abnormalities.
Dölen
A range of translational studies have begun to target this pathway. These include efforts to inhibit the activity of individual mGluR5 (Jacquemont
5. Conclusions
ASD are clearly highly heritable disorders and advances in gene-finding technology in the past decade have rapidly accelerated gene discovery. As is typically the case, successive developments have made the problem more complex such that there are huge numbers of candidate genes, most of which remain to be replicated. In spite of this complexity, we can observe a number of patterns beginning to unfold 1) the relative scarcity of causal common variants, 2) the growing list of causal rare variants, and 3) the emergence of monogenic disorders with primary and secondary ASD phenotypes.
The monogenic autisms are particularly interesting from a treatment perspective, as they provide a mechanism for studying ASD phenotypes in model systems and are an obvious target for drug intervention. They are also amenable to clinical testing and the decreasing cost of research technologies means that this capacity is more widely available to clinicians. In fact, as the resolution of clinical instruments becomes more sophisticated, it is likely that the clinic will become a primary workplace for syndromic discovery.
A key requirement in driving gene discovery is the necessity of high-quality phenotype data. ASDs are notoriously heterogeneous, and are fractionated in terms of symptoms and trajectory. Mandy & Skuse (2008) [97] reviewed seven factor analysis studies of ASD symptoms, and found that all but one dissociated social and non-social factors. In a non-clinical sample of 3,000 twin pairs, Happé
The converse, of course, is also true, as a large number of candidate genes contribute to the majority of known ASD. With ~80% of genes expressed in the brain it is likely that this number will continue to grow, and here again careful phenotyping is critical to identifying functional consequences. Ultimately, the primary goal is not to determine the frequency of variation/mutation in cases versus controls, but to determine the pathway(s) and gene networks that lead to pathology. We will also need to identify other major biological players such as epigenetic factors, RNA regulatory elements, and environmental exposures, which are critical components of the ASD equation. While daunting, the elucidation of these elements will doubtlessly take us closer to developing effective treatments for ASD. Given the current rate of progress, we have cause for cautious optimism in this regard.
References
- 1.
Wing L, Gould J, Gillberg C. Autism spectrum disorders in the DSM-V: better or worse than the DSM-IV? Res Dev Disabil. 2011 Mar-Apr;32(2):768-73. - 2.
Lord C, Rutter M, Le Couteur A. Autism Diagnostic Interview-Revised: a revised version of a diagnostic interview for caregivers of individuals with possible pervasive developmental disorders. J Autism Dev Disord. 1994 Oct;24(5):659-85. - 3.
Lord C, Rutter M, Goode S, Heemsbergen J, Jordan H, Mawhood L, et al. Autism diagnostic observation schedule: a standardized observation of communicative and social behavior. J Autism Dev Disord. 1989 Jun;19(2):185-212. - 4.
Constantino JN, Davis SA, Todd RD, Schindler MK, Gross MM, Brophy SL, et al. Validation of a brief quantitative measure of autistic traits: comparison of the social responsiveness scale with the autism diagnostic interview-revised. J Autism Dev Disord. 2003 Aug;33(4):427-33. - 5.
Levy SE, Mandell DS, Schultz RT. Autism. Lancet. 2009 Nov 7;374(9701):1627-38. - 6.
Dawson M, Soulieres I, Gernsbacher MA, Mottron L. The level and nature of autistic intelligence. Psychol Sci. 2007 Aug;18(8):657-62. - 7.
Bolte S, Dziobek I, Poustka F. Brief report: The level and nature of autistic intelligence revisited. J Autism Dev Disord. 2009 Apr;39(4):678-82. - 8.
Skuse DH. Rethinking the nature of genetic vulnerability to autistic spectrum disorders. Trends Genet. 2007 Aug;23(8):387-95. - 9.
Bailey A, Le Couteur A, Gottesman I, Bolton P, Simonoff E, Yuzda E, et al. Autism as a strongly genetic disorder: evidence from a British twin study. Psychol Med. 1995 Jan;25(1):63-77. - 10.
Piven J, Palmer P, Jacobi D, Childress D, Arndt S. Broader autism phenotype: evidence from a family history study of multiple-incidence autism families. Am J Psychiatry. 1997 Feb;154(2):185-90. - 11.
Lauritsen MB, Pedersen CB, Mortensen PB. Effects of familial risk factors and place of birth on the risk of autism: a nationwide register-based study. J Child Psychol Psychiatry. 2005 Sep;46(9):963-71. - 12.
Fombonne E. Epidemiology of pervasive developmental disorders. Pediatr Res. 2009 Jun;65(6):591-8. - 13.
O'Roak BJ, State MW. Autism genetics: strategies, challenges, and opportunities. Autism Res. 2008 Feb;1(1):4-17. - 14.
Richards RI, Holman K, Kozman H, Kremer E, Lynch M, Pritchard M, et al. Fragile X syndrome: genetic localisation by linkage mapping of two microsatellite repeats FRAXAC1 and FRAXAC2 which immediately flank the fragile site. J Med Genet. 1991 Dec;28(12):818-23. - 15.
Rogers SJ, Wehner DE, Hagerman R. The behavioral phenotype in fragile X: symptoms of autism in very young children with fragile X syndrome, idiopathic autism, and other developmental disorders. J Dev Behav Pediatr. 2001 Dec;22(6):409-17. - 16.
Harris SW, Hessl D, Goodlin-Jones B, Ferranti J, Bacalman S, Barbato I, et al. Autism profiles of males with fragile X syndrome. Am J Ment Retard. 2008 Nov;113(6):427-38. - 17.
Curtis AR, Headland S, Lindsay S, Thomas NS, Boye E, Kamakari S, et al. X chromosome linkage studies in familial Rett syndrome. Hum Genet. 1993 Jan;90(5):551-5. - 18.
Ramocki MB, Zoghbi HY. Failure of neuronal homeostasis results in common neuropsychiatric phenotypes. Nature. 2008 Oct 16;455(7215):912-8. - 19.
Klein RJ, Zeiss C, Chew EY, Tsai JY, Sackler RS, Haynes C, et al. Complement factor H polymorphism in age-related macular degeneration. Science. 2005 Apr 15;308(5720):385-9. - 20.
Risch N, Merikangas K. The future of genetic studies of complex human diseases. Science. 1996 Sep 13;273(5281):1516-7. - 21.
Wang K, Zhang H, Ma D, Bucan M, Glessner JT, Abrahams BS, et al. Common genetic variants on 5p14.1 associate with autism spectrum disorders. Nature. 2009 May 28;459(7246):528-33. - 22.
Ma D, Salyakina D, Jaworski JM, Konidari I, Whitehead PL, Andersen AN, et al. A genome-wide association study of autism reveals a common novel risk locus at 5p14.1. Ann Hum Genet. 2009 May;73(Pt 3):263-73. - 23.
St Pourcain B, Wang K, Glessner JT, Golding J, Steer C, Ring SM, et al. Association between a high-risk autism locus on 5p14 and social communication spectrum phenotypes in the general population. Am J Psychiatry. 2010 Nov;167(11):1364-72. - 24.
Redies C, Hertel N, Hubner CA. Cadherins and neuropsychiatric disorders. Brain Res. 2012 Aug 27;1470:130-44. - 25.
Gepner B, Feron F. Autism: a world changing too fast for a mis-wired brain? Neurosci Biobehav Rev. 2009 Sep;33(8):1227-42. - 26.
Kerin T, Ramanathan A, Rivas K, Grepo N, Coetzee GA, Campbell DB. A noncoding RNA antisense to moesin at 5p14.1 in autism. Sci Transl Med. 2012 Apr 4;4(128):128ra40. - 27.
McClellan J, King MC. Genetic heterogeneity in human disease. Cell. 2010 Apr 16;141(2):210-7. - 28.
Li Q, Yu K. Improved correction for population stratification in genome-wide association studies by identifying hidden population structures. Genet Epidemiol. 2008 Apr;32(3):215-26. - 29.
Ozsolak F, Milos PM. RNA sequencing: advances, challenges and opportunities. Nat Rev Genet. 2011 Feb;12(2):87-98. - 30.
Alarcon M, Cantor RM, Liu J, Gilliam TC, Geschwind DH. Evidence for a language quantitative trait locus on chromosome 7q in multiplex autism families. Am J Hum Genet. 2002 Jan;70(1):60-71. - 31.
Alarcon M, Abrahams BS, Stone JL, Duvall JA, Perederiy JV, Bomar JM, et al. Linkage, association, and gene-expression analyses identify CNTNAP2 as an autism-susceptibility gene. Am J Hum Genet. 2008 Jan;82(1):150-9. - 32.
Arking DE, Cutler DJ, Brune CW, Teslovich TM, West K, Ikeda M, et al. A common genetic variant in the neurexin superfamily member CNTNAP2 increases familial risk of autism. Am J Hum Genet. 2008 Jan;82(1):160-4. - 33.
Vernes SC, Newbury DF, Abrahams BS, Winchester L, Nicod J, Groszer M, et al. A functional genetic link between distinct developmental language disorders. N Engl J Med. 2008 Nov 27;359(22):2337-45. - 34.
Lai CS, Fisher SE, Hurst JA, Vargha-Khadem F, Monaco AP. A forkhead-domain gene is mutated in a severe speech and language disorder. Nature. 2001 Oct 4;413(6855):519-23. - 35.
Cheng Y, Sudarov A, Szulc KU, Sgaier SK, Stephen D, Turnbull DH, et al. The Engrailed homeobox genes determine the different foliation patterns in the vermis and hemispheres of the mammalian cerebellum. Development. 2010 Feb;137(3):519-29. - 36.
Benayed R, Choi J, Matteson PG, Gharani N, Kamdar S, Brzustowicz LM, et al. Autism-associated haplotype affects the regulation of the homeobox gene, ENGRAILED 2. Biol Psychiatry. 2009 Nov 15;66(10):911-7. - 37.
Benayed R, Gharani N, Rossman I, Mancuso V, Lazar G, Kamdar S, et al. Support for the homeobox transcription factor gene ENGRAILED 2 as an autism spectrum disorder susceptibility locus. Am J Hum Genet. 2005 Nov;77(5):851-68. - 38.
Wang L, Jia M, Yue W, Tang F, Qu M, Ruan Y, et al. Association of the ENGRAILED 2 (EN2) gene with autism in Chinese Han population. Am J Med Genet B Neuropsychiatr Genet. 2008 Jun 5;147B(4):434-8. - 39.
Zhong H, Serajee FJ, Nabi R, Huq AH. No association between the EN2 gene and autistic disorder. J Med Genet. 2003 Jan;40(1):e4. - 40.
Campbell DB, Sutcliffe JS, Ebert PJ, Militerni R, Bravaccio C, Trillo S, et al. A genetic variant that disrupts MET transcription is associated with autism. Proc Natl Acad Sci U S A. 2006 Nov 7;103(45):16834-9. - 41.
Campbell DB, Li C, Sutcliffe JS, Persico AM, Levitt P. Genetic evidence implicating multiple genes in the MET receptor tyrosine kinase pathway in autism spectrum disorder. Autism Res. 2008 Jun;1(3):159-68. - 42.
Sousa I, Clark TG, Toma C, Kobayashi K, Choma M, Holt R, et al. MET and autism susceptibility: family and case-control studies. Eur J Hum Genet. 2009 Jun;17(6):749-58. - 43.
A genomewide screen for autism: strong evidence for linkage to chromosomes 2q, 7q, and 16p. Am J Hum Genet. 2001 Sep;69(3):570-81. - 44.
Eagleson KL, Campbell DB, Thompson BL, Bergman MY, Levitt P. The autism risk genes MET and PLAUR differentially impact cortical development. Autism Res. 2011 Feb;4(1):68-83. - 45.
Glessner JT, Hakonarson H. Common variants in polygenic schizophrenia. Genome Biol. 2009;10(9):236. - 46.
Ferreira MA, O'Donovan MC, Meng YA, Jones IR, Ruderfer DM, Jones L, et al. Collaborative genome-wide association analysis supports a role for ANK3 and CACNA1C in bipolar disorder. Nat Genet. 2008 Sep;40(9):1056-8. - 47.
Arcos-Burgos M, Jain M, Acosta MT, Shively S, Stanescu H, Wallis D, et al. A common variant of the latrophilin 3 gene, LPHN3, confers susceptibility to ADHD and predicts effectiveness of stimulant medication. Mol Psychiatry. 2010 Nov;15(11):1053-66. - 48.
Dickson SP, Wang K, Krantz I, Hakonarson H, Goldstein DB. Rare variants create synthetic genome-wide associations. PLoS Biol. 2010 Jan;8(1):e1000294. - 49.
Wang K, Dickson SP, Stolle CA, Krantz ID, Goldstein DB, Hakonarson H. Interpretation of association signals and identification of causal variants from genome-wide association studies. Am J Hum Genet. 2010 May 14;86(5):730-42. - 50.
Pinto D, Pagnamenta AT, Klei L, Anney R, Merico D, Regan R, et al. Functional impact of global rare copy number variation in autism spectrum disorders. Nature. 2010 Jul 15;466(7304):368-72. - 51.
Williams NM, Zaharieva I, Martin A, Langley K, Mantripragada K, Fossdal R, et al. Rare chromosomal deletions and duplications in attention-deficit hyperactivity disorder: a genome-wide analysis. Lancet. 2010 Oct 23;376(9750):1401-8. - 52.
Glessner JT, Wang K, Cai G, Korvatska O, Kim CE, Wood S, et al. Autism genome-wide copy number variation reveals ubiquitin and neuronal genes. Nature. 2009 May 28;459(7246):569-73. - 53.
Levinson DF, Duan J, Oh S, Wang K, Sanders AR, Shi J, et al. Copy Number Variants in Schizophrenia: Confirmation of Five Previous Findings and New Evidence for 3q29 Microdeletions and VIPR2 Duplications. Am J Psychiatry. 2011 Mar;168(3):302-16. - 54.
Chen X, Li X, Wang P, Liu Y, Zhang Z, Zhao G, et al. Novel association strategy with copy number variation for identifying new risk Loci of human diseases. PLoS One. 2010;5(8):e12185. - 55.
Sebat J, Lakshmi B, Malhotra D, Troge J, Lese-Martin C, Walsh T, et al. Strong association of de novo copy number mutations with autism. Science. 2007 Apr 20;316(5823):445-9. - 56.
Bucan M, Abrahams BS, Wang K, Glessner JT, Herman EI, Sonnenblick LI, et al. Genome-wide analyses of exonic copy number variants in a family-based study point to novel autism susceptibility genes. PLoS Genet. 2009 Jun;5(6):e1000536. - 57.
Guilmatre A, Dubourg C, Mosca AL, Legallic S, Goldenberg A, Drouin-Garraud V, et al. Recurrent rearrangements in synaptic and neurodevelopmental genes and shared biologic pathways in schizophrenia, autism, and mental retardation. Arch Gen Psychiatry. 2009 Sep;66(9):947-56. - 58.
Samaco RC, Hogart A, LaSalle JM. Epigenetic overlap in autism-spectrum neurodevelopmental disorders: MECP2 deficiency causes reduced expression of UBE3A and GABRB3. Hum Mol Genet. 2005 Feb 15;14(4):483-92. - 59.
Kim HG, Kishikawa S, Higgins AW, Seong IS, Donovan DJ, Shen Y, et al. Disruption of neurexin 1 associated with autism spectrum disorder. Am J Hum Genet. 2008 Jan;82(1):199-207. - 60.
Yi JJ, Ehlers MD. Ubiquitin and protein turnover in synapse function. Neuron. 2005 Sep 1;47(5):629-32. - 61.
Gai X, Xie HM, Perin JC, Takahashi N, Murphy K, Wenocur AS, et al. Rare structural variation of synapse and neurotransmission genes in autism. Mol Psychiatry. 2011 Mar 1. - 62.
Glessner JT, Reilly MP, Kim CE, Takahashi N, Albano A, Hou C, et al. Strong synaptic transmission impact by copy number variations in schizophrenia. Proc Natl Acad Sci U S A. 2010 Jun 8;107(23):10584-9. - 63.
Crespi B, Badcock C. Psychosis and autism as diametrical disorders of the social brain. Behav Brain Sci. 2008 Jun;31(3):241-61; discussion 61-320. - 64.
Muhle R, Trentacoste SV, Rapin I. The genetics of autism. Pediatrics. 2004 May;113(5):e472-86. - 65.
Danielsson S, Gillberg IC, Billstedt E, Gillberg C, Olsson I. Epilepsy in young adults with autism: a prospective population-based follow-up study of 120 individuals diagnosed in childhood. Epilepsia. 2005 Jun;46(6):918-23. - 66.
Osborne JP, Fryer A, Webb D. Epidemiology of tuberous sclerosis. Ann N Y Acad Sci. 1991;615:125-7. - 67.
Franz DN. Diagnosis and management of tuberous sclerosis complex. Semin Pediatr Neurol. 1998 Dec;5(4):253-68. - 68.
Morrow EM, Yoo SY, Flavell SW, Kim TK, Lin Y, Hill RS, et al. Identifying autism loci and genes by tracing recent shared ancestry. Science. 2008 Jul 11;321(5886):218-23. - 69.
Li W, Cui Y, Kushner SA, Brown RA, Jentsch JD, Frankland PW, et al. The HMG-CoA reductase inhibitor lovastatin reverses the learning and attention deficits in a mouse model of neurofibromatosis type 1. Curr Biol. 2005 Nov 8;15(21):1961-7. - 70.
Zafeiriou DI, Ververi A, Vargiami E. Childhood autism and associated comorbidities. Brain Dev. 2007 Jun;29(5):257-72. - 71.
Volkmar FR. Handbook of Autism and Pervasive Developmental Disorders. 3 ed. New Jersey: John Wiley & Sons; 2005. - 72.
El-Fishawy P, State MW. The genetics of autism: key issues, recent findings, and clinical implications. Psychiatr Clin North Am. 2010 Mar;33(1):83-105. - 73.
Brown MS, Goldstein JL. Expression of the familial hypercholesterolemia gene in heterozygotes: mechanism for a dominant disorder in man. Science. 1974 Jul 5;185(4145):61-3. - 74.
Lifton RP, Gharavi AG, Geller DS. Molecular mechanisms of human hypertension. Cell. 2001 Feb 23;104(4):545-56. - 75.
Marchetto MC, Carromeu C, Acab A, Yu D, Yeo GW, Mu Y, et al. A model for neural development and treatment of Rett syndrome using human induced pluripotent stem cells. Cell. 2010 Nov 12;143(4):527-39. - 76.
Muotri AR, Marchetto MC, Coufal NG, Oefner R, Yeo G, Nakashima K, et al. L1 retrotransposition in neurons is modulated by MeCP2. Nature. 2010 Nov 18;468(7322):443-6. - 77.
O'Roak BJ, Vives L, Girirajan S, Karakoc E, Krumm N, Coe BP, et al. Sporadic autism exomes reveal a highly interconnected protein network of de novo mutations. Nature. 2012 Apr 4. - 78.
Fischbach GD, Lord C. The Simons Simplex Collection: a resource for identification of autism genetic risk factors. Neuron. 2010 Oct 21;68(2):192-5. - 79.
Nishimura-Akiyoshi S, Niimi K, Nakashiba T, Itohara S. Axonal netrin-Gs transneuronally determine lamina-specific subdendritic segments. Proc Natl Acad Sci U S A. 2007 Sep 11;104(37):14801-6. - 80.
Neale BM, Kou Y, Liu L, Ma'ayan A, Samocha KE, Sabo A, et al. Patterns and rates of exonic de novo mutations in autism spectrum disorders. Nature. 2012 Apr 4. - 81.
Sanders SJ, Murtha MT, Gupta AR, Murdoch JD, Raubeson MJ, Willsey AJ, et al. De novo mutations revealed by whole-exome sequencing are strongly associated with autism. Nature. 2012 Apr 4. - 82.
Kamiya K, Kaneda M, Sugawara T, Mazaki E, Okamura N, Montal M, et al. A nonsense mutation of the sodium channel gene SCN2A in a patient with intractable epilepsy and mental decline. J Neurosci. 2004 Mar 17;24(11):2690-8. - 83.
Ogiwara I, Ito K, Sawaishi Y, Osaka H, Mazaki E, Inoue I, et al. De novo mutations of voltage-gated sodium channel alphaII gene SCN2A in intractable epilepsies. Neurology. 2009 Sep 29;73(13):1046-53. - 84.
Weiss LA, Escayg A, Kearney JA, Trudeau M, MacDonald BT, Mori M, et al. Sodium channels SCN1A, SCN2A and SCN3A in familial autism. Mol Psychiatry. 2003 Feb;8(2):186-94. - 85.
Iossifov I, Ronemus M, Levy D, Wang Z, Hakker I, Rosenbaum J, et al. De novo gene disruptions in children on the autistic spectrum. Neuron. 2012 Apr 26;74(2):285-99. - 86.
Gilman SR, Iossifov I, Levy D, Ronemus M, Wigler M, Vitkup D. Rare de novo variants associated with autism implicate a large functional network of genes involved in formation and function of synapses. Neuron. 2011 Jun 9;70(5):898-907. - 87.
Bear MF, Huber KM, Warren ST. The mGluR theory of fragile X mental retardation. Trends Neurosci. 2004 Jul;27(7):370-7. - 88.
Jacquemont S, Curie A, des Portes V, Torrioli MG, Berry-Kravis E, Hagerman RJ, et al. Epigenetic modification of the FMR1 gene in fragile X syndrome is associated with differential response to the mGluR5 antagonist AFQ056. Sci Transl Med. 2011 Jan 5;3(64):64ra1. - 89.
Dolen G, Osterweil E, Rao BS, Smith GB, Auerbach BD, Chattarji S, et al. Correction of fragile X syndrome in mice. Neuron. 2007 Dec 20;56(6):955-62. - 90.
Berry-Kravis E, Hessl D, Coffey S, Hervey C, Schneider A, Yuhas J, et al. A pilot open label, single dose trial of fenobam in adults with fragile X syndrome. J Med Genet. 2009 Apr;46(4):266-71. - 91.
Paribello C, Tao L, Folino A, Berry-Kravis E, Tranfaglia M, Ethell IM, et al. Open-label add-on treatment trial of minocycline in fragile X syndrome. BMC Neurol. 2010;10:91. - 92.
Wei H, Dobkin C, Sheikh AM, Malik M, Brown WT, Li X. The therapeutic effect of memantine through the stimulation of synapse formation and dendritic spine maturation in autism and fragile X syndrome. PLoS One. 2012;7(5):e36981. - 93.
Berry-Kravis E, Sumis A, Hervey C, Nelson M, Porges SW, Weng N, et al. Open-label treatment trial of lithium to target the underlying defect in fragile X syndrome. J Dev Behav Pediatr. 2008 Aug;29(4):293-302. - 94.
Berry-Kravis E, Knox A, Hervey C. Targeted treatments for fragile X syndrome. J Neurodev Disord. 2011 Sep;3(3):193-210. - 95.
Silverman JL, Smith DG, Rizzo SJ, Karras MN, Turner SM, Tolu SS, et al. Negative allosteric modulation of the mGluR5 receptor reduces repetitive behaviors and rescues social deficits in mouse models of autism. Sci Transl Med. 2012 Apr 25;4(131):131ra51. - 96.
Kelleher RJ, 3rd, Geigenmuller U, Hovhannisyan H, Trautman E, Pinard R, Rathmell B, et al. High-throughput sequencing of mGluR signaling pathway genes reveals enrichment of rare variants in autism. PLoS One. 2012;7(4):e35003. - 97.
Mandy WP, Skuse DH. Research review: What is the association between the social-communication element of autism and repetitive interests, behaviours and activities? J Child Psychol Psychiatry. 2008 Aug;49(8):795-808. - 98.
Happe F, Ronald A, Plomin R. Time to give up on a single explanation for autism. Nat Neurosci. 2006 Oct;9(10):1218-20. - 99.
Conciatori M, Stodgell CJ, Hyman SL, O'Bara M, Militerni R, Bravaccio C, et al. Association between the HOXA1 A218G polymorphism and increased head circumference in patients with autism. Biol Psychiatry. 2004 Feb 15;55(4):413-9. - 100.
Alarcon M, Yonan AL, Gilliam TC, Cantor RM, Geschwind DH. Quantitative genome scan and Ordered-Subsets Analysis of autism endophenotypes support language QTLs. Mol Psychiatry. 2005 Aug;10(8):747-57. - 101.
Roberts TP, Khan SY, Rey M, Monroe JF, Cannon K, Blaskey L, et al. MEG detection of delayed auditory evoked responses in autism spectrum disorders: towards an imaging biomarker for autism. Autism Res. 2010 Feb;3(1):8-18. - 102.
Mottron L, Dawson M, Soulieres I, Hubert B, Burack J. Enhanced perceptual functioning in autism: an update, and eight principles of autistic perception. J Autism Dev Disord. 2006 Jan;36(1):27-43.