Genetics of Autism

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Genetics of Autism

Autism is commonly known as heterogeneous syndrome with considerable impairments in neurodevelopment process and it’s still an unresolved mystery because it’s not known to till date whether it’s a combination of few neural disorders that exhibit similar aberrations in metabolic pathways or it’s an outcome of diverse intellectual disability disorders. It has been estimated that some abnormalities occur in brain circuitry besides metabolic pathway aberrations in autism spectrum disorder/ ASD (Geschwind, 2008). Cytogenetic studies of autistic children showed increasing trend in abnormal modification in chromosomes compared to general population compiled by (Xu et al.,(2004). A study investigating genetic etiology of ASD reported 15q11-13 maternal duplications in 1-3% idiopathic autistic patients (Veenstra-VanderWeele and Cook, 2004). Individuals carrying fragile X mutations have been identified as more prone to ASD and in a study 30% of the males with ASD had FXS while 7-8% of idiopathic autistic patients were found to have fragile X mutations (Muhle et al., 2004). During normal regulatory pathways, Fragile X mental retardation protein/FMRP in association with different transcripts is responsible for gene translation repression which results in augmentation in plasticity and also contribute in functional regulation of group 1 metabotropic glutamate receptors (mGluR) (Penagarikano et al., 2007). Consequences of functional impairment in FMRP is increment in mGluR5 functionality thus ultimately cause loss of synaptic plasticity. Several studies were conducted subsequently to make most of this fact and glutamate receptor antagonists to restore phenotype which is diminished by functional impairment in FRMP (McBride et al., 2005; Tucker et al., 2006; Yan et al., 2005b).

Copy Number Variations

Research studies report variations in the copy number of candidate genes which can be acquired either via heredity or by de novo pathways (Sebat et al., 2004). Modifications in the chromosomal region which extend beyond 1 kilo base is generally regarded as copy number variation contrary to SNPs that involve a single base pair. In a study, 3% of the autistic patients had de novo CNVs and they belonged to multiplex families (families having more than one autism patient) and 10% autism patients from simplex families (opposite to multiplex) were found to have de novo CNVs (Sebat et al., 2007). The detected CNVs in this study were seventy percent deletions and thirty percent duplications of DNA regions with sizes 160 kb to megabases and these reported de novo mutations were found in 1% of ASD patients which were mainly duplications (Sebat et al., 2007). Individuals with high intellectual disability or with dysmorphology are more likely to have de novo mutations (Jacquemont et al., 2006). Incidence rate of rare de novo mutations in ASD poses questions about its mechanisms responsible for mutations (Lupski, 2007). According to a study, increasing paternal age has been recognized as factor that increases the chances of acquiring ASD (Cantor et al., 2007; Reichenberg et al., 2006). Other possibility is vulnerability of some regions to environmental factors which influence chromatin structure or its gene expression, resulting in epigenetic autism etiology (Jiang et al., 2004). Contribution of rare CNVs to ASD was studied by Zhao et al. (2007) and he found males are more susceptible with ratio of 4:1 (male-female) Recent studies suggest that rare mutations are responsible in most of the cases of ASD and common variants participate by producing small effects via alleles.

De novo mutations that contribute to ASD generally are an outcome of multiple genes interaction while the common variants that have been identified so far are MET proto-oncogene (Campbell et al., 2006) and EN2 (Benayed et al., 2005), while the others including CNTNAP2 are present in large samples of they undergo independent replication. NLGN4 is known to cause mental retardation in autistic patients however 16p11 CNV was held responsible for development delay (Weiss et al., 2008). Any structural and functional impairment will disrupt brain parts that are linked with social and linguistic skills as it affects cortical and subcortical regions of brain. An example of this CNTNAP2 which is abundant in cerebral cortex and it is connected to circuitry which stimulate joint response (Alarcón et al., 2008) and it is regarded as social precursor which is first impairment observed at ASD onset.

The parts of brain which are influenced in ASD process information fast and in a coherent manner which is received from highly intellectual parts (Geschwind and Levitt, 2007). Any disturbance in neural transmission can affect this process such as synaptic dysfunction. Another reason which can disrupt this process is circuit miswiring which could be either short or long distant and a consequence of a number of factors e.g. loss of functional synaptic junctions and disruption in axon path finding (Geschwind and Levitt, 2007). These aberrations illustrate the differences in sensory processing, sensory motor integration and motor function including differences in global processing linked with ASD (Happe and Frith, 2006).

Neuroligins, type of brain-expressed transcripts that produce synapse and takes part in its functionality, have been extensively studied to comprehend the role of one or a collection of few chromosomal aberrations in ASD and the significance of a particular gene in ASD (Lise and El-Husseini, 2006). In the initial research studies of ASD, a small segment of the X chromosome was found missing in many affected females (Thomas et al., 1999). Later on, the sequence of a gene within this interval was determined, NLGN4X, and the study involved 158 subjects who had idiopathic autism and results of the showed presence of a truncating mutation in two patients who belong to single family. further screening was done using large groups autistic patients and the study outcomes failed to support the hypothesis of coding mutations occurrence in neuroligins indicating its contribution in ASD, though some studies report rare missense variants in NLGN4X (Blasi et al., 2006; Gauthier et al., 2005; Vincent et al., 2004; Yan et al., 2005a). There are other studies which provide evidence of rare missense variants and presence of balanced chromosomal aberrations that disturb NRXN1 functions (Feng et al., 2006; Kim et al., 2008).

De novo mutation and convergence

New exome sequence technology has revealed association of disruptive de novo mutations with ASD and ID and specific loci including voltage gated, protein 8 (CHD8), type II, alpha subunit(SCN2A), chromodomain helicase DNA binding dual specificity Tyrosine-phosphorylation-regulated kinase 1A(DYRK1A), sodium channel, ), CTNNB1, beta-catenin and catenin (cadherin-associated protein) have been identified as factors that converge three major functional pathways i.e. wnt signaling, synaptic function and chromatin remodeling. Figure 1 explains different types of truncating mutations which are common in intellectual disability and ASD obtained from Exome Sequencing Project Database.

Figure 1. De novo truncating mutations common in 5 types of ASD and Intellectual disability. Image courtesy (Krumm, O’Roak, Shendure, & Eichler, 2014)

Role of Glutamatergic Genes in ASD

Several studies have been conducted to determine the etiological contribution of Glutamatergic genes in ASD and some genes which are susceptible have been found from networks that are involved in neuronal regulatory functions (Gilman et al. 2011; Nelson et al. 2012). Though the effect that these genes impart on their own are insignificant and it is predicted that in association with other functional variants with different penetrance, it produce ASD specific phenotype besides this it is believed to be involved in other disorders e.g. ADHD (Lesch et al. 2013) along with familial genetic history. Collective impact of gene dosage variants and sequence are more crucial and results of copy number variations studies indicate CYFIP1, GNBL and MAPK3 contribution in ASD however the signaling mechanism has yet to be explored. DLGAP4, GRIN2A, GRM8, EIF2S2 and GRIK2 were the candidate Glutamatergic genes which were identified to be associated with ASD linkage association and CNV studies (Chiocchetti, Bour, & Freitag, 2014). Figure 2 shows schematic pathway diagram in which different Glutamatergic genes interact with each other during ASD onset. These genes are susceptible to wide range of aberrations which could be rare and highly penetrant or variants with least penetrance ultimately determining the etiology of autism. There is a need to enquire design empirical studies that target detection of low penetrant variants and investigate combined impact of variants and their epistatic cis- and trans-relation. An extensive research on the process through which Glutamatergic genes induce ASD is essential to identify the level when remodeling of regulatory pathways instigated by them.

Figure 2. Schematic diagram explaining Glutamatergic signaling pathway which participate in ASD .Image Courtesy (Chiocchetti et al., 2014)

Autism spliceform network/ASIN

According to a recent study, the neuropathology of ASD can be well explained through integration of isoform resolved protein interaction with genomic database (Corominas et al., 2014). Empirical data of this study suggests that autism spliceform network/ASIN which were developed via brain expressed gene variants compared to the theoretically explained PPI networks. Studies based on ASIN provide evidence of interaction of genes arising from pathogenic autism CNVs. From ASD candidate genes, researchers have developed 422 brain expressed isoforms consisting of 629 isoform based protein interactions interactome database which in near future will facilitate unraveling the genetic mystery of ASD. This study emphasized the significance of spliced isoforms of candidate genes for prospective PPI screens aimed to generate interactomes which are more specific to disease or tissue types. Brain expressed isoforms are more useful in ASD neuropathology study than PPIs taken from public databases as ASD is a purely neurodevelopment disorder and beside this the way new splicing isoforms interact with each other should be considered while investigating disease specific network (Corominas et al., 2014).

Animal models of Autism spectrum disorder

Development of animal model for study of ASD is hindered by complex pathways through which different genes interact and most of the studies were based on candidate gene disruption methods however this strategy was unfavorable as complete deletion of a protein in brain results in intense functional impairment in animal model or cause early death as reported in studies involving mouse models for Angelman and Smith– Lemliimparied Optiz syndromes (Homanics et al., 1997; Fitzky et al., 2001). Besides this, disease phenotype might not be recapitulated by null alleles plus the genes which have been identified as candidate genes for ASD are not null alleles and instead of complete non-functional protein production by autism susceptibility alleles, some structural changes are introduced that limit protein production and stability. Crossing in mouse models that are responsible for mutation transmission from suitable parent can help achieve control over genetic imprinting process (Jiang et al., 1998; Miura et al., 2002; Liljelund et al., 2005). The link between disease mutation and the selected mouse model genetic history is of crucial importance as target locus vulnerability differs with it as seen in Sert-null mice (Holmes et al., 2003), Tsc1 heterozygotes (Wilson et al., 2005) and Fmr 1-null mouse model studies (Dobkin et al., 2000). Strain characteristics shouldn’t be ignored while developing mouse models for ASD studies as some strains e.g. 129SvE has reduced or no corpus callosum and sometimes these strains show poor learning abilities (Balogh et al., 1999; Wahlsten et al., 2001). C3H/HeJ, SJL/J and FVB/NJ mouse strains are known to exhibit gene that cause retinal degeneration resulting in mouse blindness at an early age (The Jackson Laboratory, 2002). Autistic behavior can be introduced in animal model via changes in brain morphology, sensory functions and learning abilities and the genes regulating the biological pathways e.g. development, x-inactivation, imprinting and metabolism will induce autistic phenotype in animal models and it implies that development of genetic strategy which can target these complex, interlinked pathways to attain a global view of autism etiology. Identification of genes responsible for normal behavior in mice will unravel brain physiological pathways resulting in communication impairment signifying ASD incidence. Studies involving gene expression profiling in rodent models indicate abnormal social behavior induced by oxytocin and mice lacking vasopressin showed similar behavior (Insel et al., 1999; Lim et al., 2005). Beside this 5-HT1A- and 1B- knockouts (Zhuang et al., 1999; see also Gingrich and Hen, 2001), dopamine transporter knockout mice (Rodriguiz et al., 2004), or mice with low levels of NMDA receptors in brain (Mohn et al., 1999; Duncan et al., 2004) pave way for new genetic targets that can possibly be used in human studies. Mice model showing neuropathology related to ASD such as modifications in cerebellum can be used for behavioral testing e.g., the Engrailed mouse (Joyner et al., 1991; see also Murcia et al., 2004). The above discussion implies that behavioral phenotyping is an effective strategy to investigate which mouse model is suitable to perform genetic characterization of ASD.

Future Prospects

With the advancements in gene sequencing and molecular biology technologies now the process of candidate genes responsible for ASD seems practical. It is necessary to investigate the alterations in DNA sequence that augments susceptibility to ASD and it facilitates unraveling autism mystery.

Improvements in genotyping platforms have significantly enhanced the density and call accuracy of markers along with added advantage of low cost. This has made whole genome sequencing practical and it also offers evaluation of risks associated with common variants. These approaches have proven to be useful in detection of common alleles that impart small effects to complex syndrome (Hirschhorn and Daly, 2005; Klein et al., 2005; Saxena et al., 2007; Scott et al., 2007; Zeggini et al., 2007; Wellcome Trust Case Control Consortium, 2007). Considerable development in the microarray technology has paved the way for CNVs detection and characterization (Kumar et al., 2008; Sebat et al., 2007; The Autism Genome Project Consortium, 2007; Weiss et al., 2008; Marshall et al., 2008). It also permits high resolution identification of both rare and de novo alterations in genome and identification of candidate loci associated with ASD has now become easier. Next generation sequencing technologies such as 454 by Roche, Solid by Applied Biosystems and Solexa by Illumina provide platform for large-scale sequencing projects. In a single run using these platforms, hundreds to thousands of sequences can be identified. These technologies offer viable approaches or methods for identification and characterization of common and rare variations, gene expression and CNVs. However, still the primary challenge in this area is simultaneous phenotyping and development of diagnostic tools that can process sample sizes currently available for the study of common and rare genetic factors that possibly induce ASD.