**7. Candidate genes**

that may have toxic effects on brain development. An example is phenylketonuria, an autoso‐ mal recessive disorder that, if untreated, leads to excessively high levels of phenylalanine and

Mitochondria are intracellular organelles that have the function of producing energy. In the mitochondria ATP production, free oxygen radicals and reactive oxygen species (ROS) are produced and then normally removed from the cells by anti-oxidant enzymes. When the production of ROS and free radicals exceeds the limit, oxidative stress occurs, that is, ROS combine with lipids, nucleic acids and proteins in the cells leading to cell death by apoptosis or necrosis. Since brain cells have limited antioxidant activity, a high lipid content and high requirement for energy, it is more prone to the effects of oxidative stress. Some patients with ASD and mutations in mitochondrial DNA have already been reported (Fillano et al., 2002; Dhillon et al., 2011). The first study involving bioenergetic metabolism disorders in ASD was directed by Coleman & Blass (1995), who reported lactic acidosis in four children with autism. Later Lombard (1998) proposed that mitochondrial oxidative phosphorylation can cause abnormal brain metabolism in children with autism resulting in acidosis. A study by Pons et al. (2004) described five children with ASD who had abnormal respiratory chain en‐ zyme activity, characterized by the *A3243G* mutation. Graf et al. (2000) described two broth‐

toxic metabolites, resulting in intellectual disabilities and ASD (Manzi et al., 2008).

220 Recent Advances in Autism Spectrum Disorders - Volume I

ers with autism associated with a mitochondrial DNA *G8363A* RNA(Lys) mutation.

probably damaging cerebral areas that are linked to autistic symptoms.

Gurrieri, 2012).

**6. Chromosomal alterations**

All these diseases, in addition to peculiar and specific clinical signs and symptoms, have au‐ tism as a common manifestation. However, with so different genetic etiologies and proba‐ bly, the involvement of different interaction mechanisms, what do they have in common that explains the autistic behavior? The autistic behavior is attributed to changes in neurode‐ velopment and all these diseases cause changes in the brain structure and/or functioning,

In the clinical practice, the recognition of these conditions is fundamental, as it allows the targeting of laboratory tests and assists in the initial breakdown of etiological heterogeneity which categorizes specific cases of autism as syndromic or nonsyndromic. This definition is important because of possible implications in the prognosis and recurrence risk (Miles, 2011;

Numerical and structural chromosomal alterations, visible by conventional cytogenetic tech‐ niques, occur in about 6 to 7% of ASD cases and have already been described in all autoso‐ mal and sex chromosomes. These findings justify karyotyping by GTG banding as part of

Some human chromosomal aneuploidies are known to increase the risk for ASD; the most common, as identified in studies of individuals with autism, are trisomy 21 (Down syn‐ drome), monosomy of chromosome X in women (Turner syndrome), uniparental X disomy in men (Klinfelter syndrome), Y disomy and 45,X/46,XY mosaicism. Structural abnormalities include 15q11-13 duplication and deletions of 2q37, 22q11.2 and 22q13.3 (Betancour, 2011).

the etiological work-up protocol of carriers (Castermans et al., 2004; Shen et al., 2010).

According to recent findings, some common mutations, epigenetic mechanisms, chromo‐ some alterations, rare single gene mutations, copy number variations (CNVs) and single nu‐ cleotide polymorphisms (SNPs) result in the autistic phenotype. Because of national and international consortia, many linkage and genome-wide association studies have evolved which elucidated candidate genes and susceptibility of genomic regions relevant to ASD. In contrast to polygenic or complex genetic models for autism, suggested in the majority of cas‐ es, a few forms of ASD are known to be caused by single gene defects, such as in FRAXA (Chiocchetti & Klauck, 2011; Dhillon et al., 2011).

According to a review by Betancour (2011) more than 100 candidate genes for autistic be‐ havior are also related to syndromic or nonsyndromic intellectual disabilities. Many are also associated with epilepsy, with or without intellectual disabilities; this suggests that these neurodevelopment disorders have risk factors in common with ASD.

Mutations in a single gene may be autosomal dominant, recessive or X-linked. Some, not al‐ ways related to syndromic cases, are highly penetrating and appear at sufficiently high fre‐ quencies to be considered monogenic causes of autism. Of the growing list, the most important candidate genes are: *NLGN3*, *NLGN4*, *SHANK2*, *SHANK3*, *NRXN1*, *NRXN3*, *PTCHD1/PTCHD1AS*, *SHANK1*, *DPYD*, *ASTN2*, *DPP6*, *MBD5*, *CDH8* and *CNTNAP2*. It is important to note that most of these act on neurotransmission in the central nervous system (Sherer & Dawson, 2011).

et al., 2012). The use of these molecular sequencing tools has also enabled the identification of high frequencies of common variants in some genes, such as SNPs, in individuals with SD. SNPs, causing about 50% of all currently known variations in genetic material, are the most nu‐ merous variants in the genome. Moreover, SNPs are considered genetic markers that can be

Genetic Etiology of Autism http://dx.doi.org/10.5772/53106 223

Unlike CNVs, SNPs seem to be more penetrating in ASD. *De novo* SNPs, although less fre‐ quent, seem to have more deleterious effects and confer higher risk for autistic behavior (Chahrour et al., 2012). Associations between some SNPs of mitochondrial and nuclear genes and predisposition to ASD have been reported by several studies (Ramoz et al., 2004; Silverman et al., 2008; Smith et al., 2009). Studies have shown SNPs in the *GABRA2, GA‐ BRA3, GABRA4, SLC25A12, FOXP2, CNTNAP2, CNTNAP2* and *BDNF* genes (Li et al., 2005; Segurado et al., 2005; Alárcon et al., 2008; Cheng et al., 2009; Scott-Van Zeeland et al., 2010; Jiao et al.,2011). In the Genome-wide Association Studies (GWAS) involving 4305 individu‐ als with ASD and 6941 controls, strong association signals were revealed in six SNPs of two genes encoding neuronal cell-adhesion molecules, cadherin 10 (*CDH10*) and cadherin 9 (*CDH9*). These findings were replicated in two independent cohorts and implicated neuro‐

It is possible that screening for SNPs may identify new biological mechanisms that are in‐ volved in predisposition to ASD. However, GWAS, although promising, has revealed few common alleles and many results have still to be replicated (Ma et al., 2009; Manolio et al., 2009; Klein et al., 2010). It is clear that SNPs may have variable expressions or reduced pene‐ trance. But, while it is apparent that rare variations can play an important role in the genetic architecture of these diseases, the contribution of common variations to risk for ASD is less clear (Jiao et al., 2011; Sherer & Dawson, 2011). Additionally, a strong Association between SNPs in the 5p14.1 and 5p15.2 regions and ASD has also been reported (Wang et al., 2009).

However, the results of Stage 2 of the Autism Genome Project Genome-Wide Association Study, which incremented 1301 ASD families to the investigation bringing the total to 2705 families analyzed (Stages 1 and 2), showed that no single SNP has a significant association with ASD or selected phenotypes at the genome-wide level and concluded that common variants affect the risk for ASD but their individual effects are modest (Anney et al., 2012).

These controversial results about the role of SNPs in the predisposition for ASD do not rule out participation in the phenotype, but motivate the investigation of biological phenomenon that would explain their participation. Probably a single SNP does not affect the risk, but perhaps the additive effect of several SNPs, in specific combinations, with the participation of environmental determinants cannot be discarded in etiologically complex diseases.

From another standpoint, the Quantitative Trait Locus (QTL) approach is one of the most suitable methods to find susceptibility of loci. This approach follows the assumption that ASD occur as a continuum of severity, a position supported by findings of elevated levels of ASD symptoms in parents and siblings of cases compared to controls, and variations in ASD traits that have been found in the general population. One study to identify the loci that un‐ derlie ASD symptoms in children with attention-deficit/hyperactivity disorder (ADHD) in‐

used to identify genes associated with complex diseases (Malhotra & Sebat, 2012).

nal cell-adhesion molecules in the pathogenesis of ASD (Wang et al., 2009).

There are reports of more than two hundred candidate genes in the literature. According to Swanwick et al. (2011), they can be classified into four categories: 1) rare - genes involved in rare monogenic forms of ASD. This type of allelic variant includes rare polymorphisms and mutations directly related to ASD (*NRXN1* and *SHANK3*); 2) syndromic - genes related to syndromes with phenotypic manifestations in a significant subpopulation of carriers that in‐ clude autistic symptoms *(FMR1* and *MECP2*); 3) association - genes with common polymor‐ phisms that confer a small, probably additive risk, for ASD, that were identified from association studies derived from cases of unknown etiology (*MET* and *GABRB1*) and 4) functional - genes with functions related to the biology of ASD that are not included in the other categories (*CASDP2* and *ALOX5AP*). Among these, the ones that belong to the first two categories are the most strongly related to the pathogenesis of ASD (El-fishawy & State, 2010). There are indications that *de novo* point mutations occur in approximately 5 to 20% of the cases (O'Roak et al., 2011).

Persico and Bourgeron (2008) proposed that there are three main pathways involved in the pathogenesis of ASD. The first entails genes that affect cell migration, the second disruptions of the glutamate-GABA harmony and the third involves synaptic formation and maintenance and dendritic morphology. All these pathways play a fundamental role in the central nervous sys‐ tem, particularly in the serotonergic process (Berkel et al., 2010; Durand et al., 2007).

Recent studies have given more support to evidence that a large subset of genes, involved in the outgrowth and guidance of axons and dendrites, is implicated in the etiology of autism. How‐ ever, many studies are still needed in order to understand the role of isolated genes and gene re‐ gions in ASD and to identify the associations between them and to identify new candidate genes that act within the molecular pathways (Hussman et al., 2011; Griswold et al., 2012).

But despite the large number of previously identified candidate genes, the number of pa‐ tients with changes in these genes does not reach 1% of the total cases, which further high‐ lights the extreme heterogeneity seen in the pathogenesis of ASD. The findings have led to a paradigm shift in the concept of the genetic architecture of common neurodevelopmental diseases, stressing the importance of individual patterns, rare mutations and overlapping in genetic etiology. They have also converged on specific neurodevelopmental pathways, pro‐ viding insights into pathogenic mechanisms (Mitchell, 2011).
