Open access peer-reviewed chapter

Biomarkers-Directed Strategies to Treat Autism

Written By

Afaf El-Ansary and Hussain Al Dera

Submitted: October 13th, 2015 Reviewed: February 17th, 2016 Published: August 17th, 2016

DOI: 10.5772/62566

Chapter metrics overview

1,958 Chapter Downloads

View Full Metrics


Autism is a neurodevelopmental disorder characterized by social, communication, and behavioral symptoms. Recent research has attempted to identify the potential mechanisms that may contribute to the pathogenesis of autism. Biomarkers as noninvasive quantitative biological measures with accurate indication of a specific mechanism can lead to a better understanding of the pathogenesis required to design the most effective treatments of autism. There is also great hope that the discovery of valid and predictive biomarkers for this disorder will help earlier and more targeted methods for diagnosis and intervention. In this chapter, we discuss some of the current theorized mechanisms contributing to autism, including inflammation, oxidative stress, impaired detoxification, glutamate excitotoxicity, gut-microbiota-brain axis, impaired fatty acid profiling, and serotonin (5-HT)/oxytocin (OT) abnormalities as target to treat autism. Moreover, based on our understanding of the role of these mechanisms, selected treatment strategies are suggested. These strategies include nutraceuticals, probiotics/prebiotics and ω-3 supplementation, targeting glutamate transporters or selective 5-HT reuptake inhibitors, and intranasal OT treatment. Of course, the joint efforts of scientists, caregivers, and other stakeholders must combine to identify valid, clinically useful autism biomarkers that may lead to efficient treatment strategy and/or combined strategies.


  • autism
  • biomarkers
  • excitotoxicity
  • neuroinflammation
  • nutraceuticals
  • ω-3
  • oxidative stress
  • probiotic

1. Introduction

Autism is a neurodevelopmental disorder characterized by deficits in cognition and learning, behavior, social interaction, and communication. Among the challenging behaviors that negatively affect the child with autism is the social interaction impairment. Social interaction is defined as how an individual uses verbal and nonverbal communication during interpersonal exchanges. Children with autism usually present difficulty in recognizing the thoughts and feelings of others, and this is described as “mind blindness,” which can lead to ineffective communication [1]. Cognitive differences are also prevalent in children with autism. As a result, academic differences often exist due in part to weaknesses with executive functioning. The current management strategies, practice, and methods are put into place by professionals, researchers, and parents to compensate for the deficits in these areas. They are designed and selected in hopes of producing the maximum improvement in autistic behavior. Genetic heterogeneity was recorded earlier in twin, family, and linkage studies. The autism-related genes seem to be contributed on few etiological pathways related to detoxification, synaptic function, and neurogenesis [25]. As genes and environment rarely act independently to induce autism, the interaction between both at various developmental times usually plays an important role in the pathology of this disorder. Because development is a dynamic process, a constant interplay between genes and environment usually occurs [6]. Although the progressive increase in the prevalence of autism can be attributed to the increase in public awareness and the broadening of diagnostic construct, of course, it can be also related to the incidence of environmental factors [7, 8] and their interactions with yet unknown genetic vulnerability. Nutrients, heavy metal pollution, medications, and pesticides as the most commonly examined exposures during pregnancy are among the environmental neurotoxic insult on developing brains. Understanding how low-level chemical exposures influence the molecular, cellular, and behavioral outcomes relevant to autism will provide insight regarding gene-environment interactions and possibly yield novel intervention strategies. There is no metabolic biomarker or panel of markers that can precisely define autism, but examining different signaling pathways to identify any abnormalities in autistic patients compared to their normal peers can be enhanced to treat autism through the amelioration of these defected pathways.

Figure 1.

Role of genetic, environmental, and biological mechanisms in the etiology of autism.

Many studies related to the screening of biomarkers of autism were successful enough and reproducible to ascertain the role of oxidative stress, environmental toxicants, mitochondrial dysfunction, and immunology/inflammation as four main etiopathological mechanisms of autism. In addition, there is accumulating evidence pointing to the contribution of lipid abnormalities, gut microbiota, and glutamate excitotoxicity in generating biomarkers related to autism. Figure 1 demonstrates the relationship between genetic, environmental, and biological mechanisms in the etiology of autism.


2. Biomarkers related to autism

Screening for antioxidants includes the measurement of glutathione (GSH) as the primary antioxidant entrusted with the protection against oxidative stress, neuroinflammation, and mitochondrial damage. GSH is critically important in regulating the detoxification mechanism and modulating the production of oxidative stress-related parameters. Measuring reduced GSH, oxidized GSH (GSSG), or GSH status (GSH/GSSG) proves to be of great use in the determination of the patient’s oxidation status. In a trial that evaluated the detoxification mechanism in autism, a systematic review of 39 studies was conducted. It proved that many patients with autism have lower GSH/GSSG, indicating poor antioxidant and detoxification mechanisms [9]. Among the recorded detoxification markers that are studied in autism are p-hydroxyphenyllactate, pyroglutamate, benzoate, and hippurate. Elevated levels of hippurate and benzoate are related to impaired phase II detoxification via glycine conjugation [10]. Abnormal levels of pyroglutamate can indicate an impairment of GSH metabolism and a depleted GSH status.

In more recent studies, serum thioredoxin levels and F2-isoprostane are related to cognitive and social impairment severity in autistic patients [measured by Childhood Autism Rating Scales (CARS) or Social Responsiveness Scale (SRS), respectively] [1113]. A negative correlation between GSH peroxidase and CARS has also been reported [11]. Many studies prove that oxidative stress can easily be related to chronic inflammation, glutamate excitotoxicity, and increased mitochondrial dysfunction as etiological mechanisms in autism [14]. Additionally, the observed cellular damage in these patients may range from structural damage and mitotic arrest to apoptosis and cell necrosis depending on the severity of oxidative stress.

Figure 2 demonstrates the suggested relationship between these etiological mechanisms and apoptosis of neurons that might lead to abnormal brain maturation that presents as autistic features and behavioral deficits. Glutamate excitotoxicity, oxidative stress, and neuroinflammation are signaling pathways that might cause an increase and/or decrease of proapoptotic and antiapoptotic proteins, respectively. Under the effect of genetic change or the environment (e.g., heavy metal toxicity and altered gut microbiota), the activation of pathological apoptosis (elevation of caspases) impairs normal brain maturation and induces autistic phenotype.

Figure 2.

Suggested relationship between oxidative stress, glutamate excitotoxicity, neuroinflammation, and pathological apoptosis leading to autistic phenotype.

The realization that the microbiota-gut-brain axis plays a critical role in the etiology of autism has recently emerged. The regulation of this axis is essential for maintaining homeostasis, including that of the central nervous system (CNS). Nowadays, understanding microbiota-brain interactions has become exciting area of research, which may contribute new insights into individual variations in cognition, social interaction, mood, and sleep disorders as characteristic features of patients with autism [15, 16]. The ability of gut microbiota to communicate with the brain and in turn induce behavioral changes is emerging as an interesting concept in autism. The brain-gut axis is a bidirectional communication system composed of neural pathways, such as the enteric nervous system (ENS), vagus, sympathetic, and spinal nerves, as well as humoral pathways, which include cytokines, hormones, and neuropeptides as signaling molecules [16]. Brain excitotoxicity, oxidative stress, and neuroinflammation can directly or indirectly affect the composition of the gut microbiota. On the contrary, microbial overgrowth and their metabolites can modulate the brain normal function. Figure 3 demonstrates the suggested bidirectional interaction between the gut-microbiota and the brain as an etiological mechanism in autism.

Figure 3.

Gut-brain axis: pathways of communication between brain and gut microbiota.

This fact was confirmed by a study that has suggested a significant risk of autism in children born to mothers with severe infections during pregnancy [17]. Additionally, offspring of pregnant female monkeys exposed to antibodies produced postinfection usually develop pathologies of the CNS and exhibited behavioral changes similar to those seen in autistic children [18]. Autoantibodies triggered by systemic inflammation are generated during pregnancy and are now accepted to play a role in abnormal neurological and impaired blood-brain barrier (BBB) development in the fetus with a concomitant increased risk of autism [19]. The molecular trigger for autoantibody generation is poorly understood, but there is a possibility that autoantibodies against receptors for key microbiota metabolites, such as serotonin (5-HT), γ-aminobutyric acid (GABA), glutamate, tryptophan, and short-chain fatty acids (SCFA), may be directed by the immune system under conditions of aberrant metabolite accumulation in the blood as well as inappropriate immune system in early life or mimicry by gut bacteria [20].

These early observations provide a potential explanation for the gastrointestinal problems suffered by patients with autism. In support of this line of thinking, children with autism are shown to have increased permeability of the gastrointestinal tract, called “leaky gut,” causing microbial products to escape into the bloodstream and possibly reach the brain [21]. These products alter the immune system, resulting in a progression of the disease [22]. Differences in the gut microbiota between maternal infection activated (MIA) offspring and controls are observed due primarily to changes in the diversity of Clostridia and Bacteroidia [23]. The intestines of some autistic patients with intestinal abnormalities are known to bear Sutterellaand Clostridium bolteae[24], organisms lacking in control populations with similar gastrointestinal problems, together with lower Bifidobacteriumand Lactobacillusspecies. Table 1 demonstrates altered gut microbiota in individuals with autism in relation to social impairment.

Significantly ↑ in Clostridium histolyticum[24]
Significantly ↑ in Bacteroidetes [25]
Significantly ↓ in species of Bifidobacteriumand ↑ in Lactobacillus[26]
Significantly ↓ in species of Bifidobacteriumspp. [27]
Significantly ↓ in Bacteroidetes, ↑ in Firmicutes: Bacteroidetes, ↑ in Betaproteobacteria [28]
Significant ↑ in Sutterellaspp. [29]
Significant ↑ in Clostridium[30]
↑ in Clostridium, Bacteroidetes, Prophyromonas, Prevotella, Pseudomonas, Aeromonas, and Enterobacteriaceae; ↓ in Enterococcus, Lactobacillus, Streptococcus, and Staphylococcus[31]

Table 1.

Association between gut microbiota altered composition and social impairment as core symptom in autistic patients.

The metabolomic studies of urine from patients with autism have identified molecules associated with the microbiome, such as dimethylamine, hippuric acid, and phenylacetylglutamine [24, 32]. Decreased plasma levels of p-hydroxyphenyllactate, the metabolite of Bifidobacteriumand Lactobacillus, which is known to serve as an antioxidant both in the circulation and tissues, were also detected in urine of patients with autism [33].

SCFA, such as acetate, propionate, and butyrate, are neuroactive microbial metabolites that can cross the BBB and induce remarkable changes in brain function during development and thus lead to behavior abnormalities [3436]. Increased levels of total as well as individual SCFA levels have been associated with autism [37]. Propionate has also been shown to induce behavioral changes similar to autism when infused interventricularly to the brain [35]. It was also reported that increased butyrate levels in valproic acid (VPA) in utero-exposed male offspring could contribute to deficits in social behavior. Both butyrate and VPA neurotoxicity are associated with the impairment of fatty acids transport by the carnithine pathway. This can easily be related to mitochondrial dysfunction as an etiological mechanism in autism [34]. Both acids can also relate to intestinal inflammatory phenotype common in autistic patients through their inhibitory effects on histone deacetylase in the gut of exposed animals [38]. Modulating intestinal mucus composition through MUC-2 gene expression can affect epithelial protection, gut morphology, and gut microbiota composition [39]. Moreover, if blood butyrate levels are increased, it can affect various neuronal cells directly and thereby affect the maturation of oligodendrocytes and hippocampal neuronal cells in the brain during postnatal development and induce autistic features in treated animals [40, 41].

In the case of neurodevelopmental disorders, such as autism, the neuroimmune system could affect not only function but also brain development [42]. The inflammatory response elicited during pregnancy in the mother can induce inflammation in the fetus through the placenta [43].

Clinical and postmortem studies have shown that neuroinflammatory processes induced during the prenatal period usually remain altered throughout autism pathology. Abnormal inflammatory response to infection of different blood cell populations has been described in autistic children, and such patients usually suffer from chronic gastrointestinal disturbances [24, 37, 44]. It is well known that their mononuclear cells and lymphoblasts produce excessive proinflammatory cytokines, such as tumor necrosis factor-α (TNF-α), interleukin (IL)-6, and IL-1β, both basally [45] and after being stimulated with lipopolysaccharides (LPS) [46], compared to healthy controls. Astrogliosis and microglial activation, together with the overexpression of cytokines in different regions of the autistic brain, show that autistic patients demonstrate an altered neuroinflammatory response throughout their lives; they also show increased astrocyte and microglia inflammatory response in the cortex and the cerebellum [47, 48]. Moreover, increased expression of interferon-γ (IFN-γ), monocyte chemoattractant protein-1 (MCP-1), transforming growth factor-β1 (TGF-β1), IL-8, IL-6, and TNF-α and other genes associated with the immune response have been reported in those brain regions and in the cerebrospinal fluid [4850] (Figure 4).

Figure 4.

Early inflammation as an etiological mechanism in autism.

In a 2D gel-based proteomic analysis of urine, a total of 250 protein spots were detected in autistic samples compared to 195 in normal control subjects. Whereas 10 proteins were overexpressed, others were found to be underexpressed. Out of the significantly different urine analysis, three overexpressed peptides were identified as kininogen-1 (KNG-1)-50, IgG1 heavy chain variable region, and mannan-binding lectin serine protease-2 isoform-2 precursor-45. The abnormal formation of KNG-1 as an important regulator of urokinase plasminogen activator receptor is involved in cell migration and proliferation [51]. The increase of urinary KNG-1 levels in all the tested autistic children highlights the possibility of using this protein as a diagnostic marker.

Significant changes in the levels of aspartate, citrate, creatinine, hydroxyphenyllactate, indoleacetate, isoleucine, glutamate, and glutarate between autistic and control individuals were identified by West et al. [52]. They identified a decreased level of blood homocitrulline as a new biomarker in autism. Homocitrulline is a poorly understood molecule that is known to be formed inside the mitochondria from lysine and carbamoyl phosphate. The decreased blood level of this marker also suggests that its metabolism in the brain may also be disrupted. Homocitrulline levels are increased in urine and blood in patients with ornithine translocase deficiency, which diverts the reaction between carbamyl phosphate and lysine. Patients with ornithine translocase deficiency exhibit behavioral abnormalities similar to autism, such as developmental delay, spasticity, learning, and cognitive abnormalities, together with frequent seizures [53]. In addition, disrupted brain redox status and energy metabolism were reported in rats that received homocitrulline intraventricularly [54, 55]. These observations suggest that elevated brain levels of homocitrulline are deleterious; however, additional studies are needed to define the brain levels of homocitrulline and its potential role in the development of autism.

The role of polyunsaturated fatty acids (PUFA) in neurodevelopment is becoming clear. The brain and nervous tissue usually depend on ω-3 fatty acids, specifically docosahexaenoic acid (DHA) and eicosapentaenoic acid (EPA), for structural cell signaling purposes [56]. Among the ascertained and reproducible markers in autism are the elevated ω-6 PUFA, LA (n-6) together with ω-6:ω-3 ratio (n-6:n-3). Elevated n-6:n-3 ratios above 4–6:1 have been associated with neuroinflammation as an etiopathogenesis mechanism in autism [57]. In several studies, patients with autism exhibited elevated n-6:n-3 ratio and decreased n-3 fatty acid compared to intellectually impaired control [58, 59]. Fombonne et al. [60] reported that the absence of incidence of autism from 1991 to 2006 among an Inuit population was attributed to the consumption of large amount of fish.

Figure 5.

Unbalance between ω-6/ω-3 fatty acids as etiological mechanism in autism.

Glutamate and GABA as the main excitatory and inhibitory neurotransmitters in the human brain, respectively, have important roles during prenatal or postnatal brain development. Upon excitation of the presynaptic neuron, glutamate is released from the synaptic vesicles into the synaptic cleft. This is followed by the binding of the released glutamate to ionotropic (NMDAR and AMPAR) or metabotropic receptors (mGluR) on the postsynaptic neurons. The binding of glutamate to mGluRs triggers the activation of G-protein-dependent intracellular signaling cascade. The activation of ionotropic glutamate receptors AMPA, kainate, and NMDA by glutamate induces the opening of Na+ and Ca2+ ion channels. The overactivation of glutamate receptors by excessive glutamate results in the influx of high levels of calcium ions (Ca2+) into the postsynaptic cells, which in turn activate a cascade of proteases, lipases, nitric oxide synthase, and a number of enzymes that damage cell structures leading to cell death.

Early studies described the neurotoxic effect of the excitatory neurotransmitter glutamate [61]. In 1969, Olney [62] found that the subcutaneous injection of monosodium glutamate resulted in necrotic brain lesions in the hypothalamus of newborn mice, leading to a number of developmental abnormalities. These reports led to the introduction of the term “excitotoxicity,” describing cell damage induced by an excess of glutamate as the most important excitatory amino acids. The control of extracellular glutamate level at the synapse relatively depends on Na+-dependent glutamate transporters located perisynaptically on astrocytes or neurons. Dysfunction of these transporters usually contributed to severe excitotoxicity [63]. It is also true that the activity of glutamate transporters is regulated by the extracellular concentration of glutamate.

Glutamic acid decarboxylase (GAD) as a rate-limiting enzyme in glutamate/GABA cycle catalyzes the conversion of glutamate to GABA. GAD65 and GAD67 are two isoforms of GAD, expressed from two unlinked genes in the adult brain [64]. GAD67 is localized in chromosome 2q31.1, which is related to susceptibility for autism, so it might be a potential biomarker for GABAergic abnormalities demonstrated in autistic patients [65]. The reduction in the number of cerebellar Purkinje cells that express GAD67 abundantly has also been widely reported in autism [66]. A high percentage decrease of mRNA expression for GAD67 was observed in Purkinje cells of autistic individuals compared to control brains [67]. These findings suggest that the reduction in the GABA input to cerebellar nuclei disrupts the output to cerebral cortex and can be related to the motor and cognitive abnormalities seen in autistic patients. An early study has also reported the reduction of GAD65 and GAD67 protein in the parietal cortex and in the cerebellum of autistic brains [68]. There are also reports of increased glutamate levels in the blood and platelets of autistic patients [69, 70]. In addition, a significantly lower glutamate/glutamine ratio was reported by Abu-Shmais et al. [71]. Other studies have also shown that an increased release from presynaptic neurons can also contribute to excitotoxicity. Moreover, increased frequencies and amplitudes of action potential-evoked excitatory synaptic potentials have been observed in mouse models of autism. Therefore, many studies were conducted to clarify and analyze the functional status of glutamatergic and GABAergic neurotransmission in the autistic brain [72, 73]. Based on these studies, strong evidence indicates that dysfunctional excitatory and inhibitory synaptic activities underlie several of the characteristics of autism and support a hyperglutamatergic hypothesis of autism. This was attributed in some studies highlighting an imbalance between GABAergic and glutamatergic as inhibitory and excitatory neurotransmitters, respectively [73]. Another potential source of glutamate excitotoxicity is either the abnormal high release of glutamate or the decrease of glutamate transporters as proteins on the presynaptic neurons and astrocytes playing an important role in the reuptake and removal of glutamate from the synaptic cleft. Raghavendra Rao et al. [74] showed that glutamate transporter-1 (GLT-1) expression was significantly reduced (38–47%) in the rat brain 24 h after fluid percussion injury. The resulting decrease in transport leads to an excess of glutamate in the synaptic cleft. Either increased glutamate release from the presynaptic neuron or removal by glutamate transporters, as two mechanisms that might be related to glutamate excitotoxicity, has been proven in rodent models of autism [75, 76]. Purcell et al. [77] used 10 brain postmortem samples from individuals with autism to identify genes that were significantly up-regulated or down-regulated. These researchers found abnormalities in the AMPA-type glutamate receptors and glutamate transporters in the cerebellum of autistics compared to control involving these transporters directly in the pathogenesis of this disorder. This was ascertained when the down-regulation of glial glutamate transporters, GLT-1 and GLAST, was found effective in the generation of animal models of autism in which glutamate receptors are overstimulated [76].

Glutamate excitotoxicity can easily be related to low GSH level and this has been repeatedly reported in autistic patients. It is well known that more than 80% of extracellular glutamate is transported into astrocytes [78]. This in turn stimulates both GSH synthesis and cysteine inward flow as a prerequisite for the maintenance of high GSH level in astrocytes [79]. On the contrary, neurons import cysteine through EAAT2 and EAAT3 and this process is competitively inhibited by glutamate. Based on this, glutamate excitotoxicity will starve neurons of cysteine in favor of ensuring high GSH level in astrocytes.

Several reproducible studies have ascertained that individuals with autism demonstrate an abnormal brain 5-HT system [80, 81]. This was clinically presented as hyperserotonemia [80], altered 5-HT synthesis or 5-HT receptor affinity, and dystrophic serotonergic [8284]. In a recent study on postmortem brains, a significant decrease in both 5-HT2A and 5-HT1A binding was reported in autism [85]. Some researchers suggested an association of 5-HT dysfunction with repetitive and self-injurious behaviors [8688]. This gives support to the idea that peripheral alterations in the 5-HT system may be an important marker of central abnormalities in autism.

Oxytocin (OT) as a neuropeptide of great interest has been known to play important roles in social behavior in both animals and humans [89, 90]. OT-related studies in autism have repeatedly reported lower blood OT level in autistic patients compared to age- and gender-matched control subjects [12, 81, 91, 92]. The faulty processing of the OT prohormone to the active OT neuropeptide was also found [93] together with abnormalities and polymorphism in the OT receptor (OTR) gene, raising the possibility of OT resistance in autism [9498]. Multiple intersections of the 5-HT and OT systems have been ascertained and were found to influence behaviors such as sociability, aggression, and anxiety that are relevant to autism [99, 100].

With the move toward the development of disease treatment strategy, there is a great need for more specific diagnostic criteria of autism as a heterogeneous disorder. The diagnostic accuracy of biomarkers is most commonly measured by calculating its sensitivity and specificity. Receiver operating characteristic (ROC) curve analysis is a useful tool in the assessment of biomarker accuracy. The accuracy of a biomarker depends on how well it separates the groups being tested into those with and without the disease in question. In ROC analysis, the ratio of the abnormals found by the marker to the total number of abnormals known to have the disease is the true positive rate (or sensitivity), whereas the ratio of the normals found by the test to the total number of normals is the true negative rate (or specificity). The ROC curve is a graph of sensitivity (y‐axis) versus 1-specificity (x‐axis). Accuracy is measured by the area under the ROC curve. An area of 0.9 to 1 represents a perfect marker, an area of 0.8 to 0.6 represents good-fair marker, and an area of 0.5 represents a worthless marker [101]. More recently, combined ROC was introduced as a simple clinical method with great potential for assisting the diagnosis of autism through the increase of the AUC, specificity, and sensitivity and the diagnostic value of combined markers [102].


3. Biomarkers-directed treatment strategies

Positive roles between selected nutraceuticals or vitamins/minerals-based treatment strategies and the improvement of autistic features have been reported. In a comparative case-control treatment strategies, two groups each of 44 autistic patients, with an age range of 2 to 28 years, were given either micronutrient supplement containing (14 vitamins, 16 dietary minerals, 3 amino acids, and 3 antioxidants) without any autism medication or conventional medication without supplementation. Patients in both groups improved, but the level of improvement was remarkably higher in micronutrient recommended group than in the conventional medication group [103].

Similarly, in an observatory study, the administration of vitamin B12 and GSH along with low fructose and food additive/color organic diet of 10 children (4–10 years of age) for 3 to 6 months resulted in a significant improvement in the social interaction, concentration, writing, language, and behavior [104]. A meta-analysis of 18 studies revealed that the supplementation of vitamin B6, especially in combination with magnesium, improved the health of autistic patients [105, 106].

Complementary alternative medicine (CAM) treatments are usually recommended to promote health, to avoid side the effects of conventional drugs, or to ameliorate the core symptoms of autism. Prenatal exposure to VPA induces a rearrangement of early microbial colonization, leading to an increase of butyrate levels in the gastrointestinal tract of male offspring. Consequently, increased levels of butyrate in the gut may interfere directly with gene expression in intestinal cells or indirectly with gene expression of neuronal cells after crossing the BBB. This is usually accompanied with induced deleterious changes in the intestinal and brain functions that might explain certain autistic features. These results open the road to a novel strategy to treat autism through gut microbiome manipulation. The administration of probiotic or prebiotic may provide an excellent tool to treat autism based on our understanding of the role of gut-brain axis and microbial metabolites in the pathology of this disorder.

Clinical studies have shown that prenatal supplementation with n-3 PUFA may be beneficial for healthy neural development in both preterm and full-term infants [107109]. Regarding preterm infants, the timing of supplementation is of critical importance because these infants cannot fully use accumulated long-chain PUFA that usually start in the last trimester of gestation. Studies in full-term infants show that both prenatal and postnatal supplementations cause an improvement in cognition [110, 111]. Moreover, in humans, the outcome of infant n-3 PUFA supplementation on long-term brain development appears to be subtle [112114] compared to the rodent model studies [115], which demonstrate more pronounced beneficial effects of n-3 PUFA supplementation [115117]. Overall, our adequate dietary n-3 PUFA levels starting early in life may support optimal neural development in healthy full-term infants.

In a randomized, double-blind, placebo-controlled 6-week pilot study, Amminger et al. [118] investigated the effects of 1.5 g/d ω-3 fatty acids (0.84 g/d EPA and 0.7 g/d DHA) supplementation given in the form of seven pale-yellow, 1 g gelatin capsules of fish oil, each containing 120 mg EPA and 100 mg DHA plus 1 mg vitamin E to 13 autistic children (aged 5–17 years). The placebo was seven gelatin capsules of coconut oil that were of similar shape and size and also contained 1 mg vitamin E as well as 1 mg fish oil to mimic fish taste. The experimental daily dose of 1.5 g ω-3 fatty acids is based on a study in children with developmental coordination disorder by Richardson and Montgomery [119]. The findings of their trial suggested that ω-3 fatty acids may be effective in treating the aggression and impulsivity in autistic patients. The underlying mechanism of action is not fully understood but may be related to the modulation of serotonergic and dopaminergic neurotransmission [120]. This can be ascertained by considering the phenomenon that DHA or the EPA/ARA ratio might control aggression by depressing the noradrenergic system [112]. The more recent work of El-Ansary et al. [116] supports that the essential fatty acids/long-chain PUFA and ω-3/ω-6 ratios, phosphatidylethanolamine, phosphatidylserine, and phosphatidylcholine could be used as potential biomarkers that point to specific mechanisms in the development of autism and may help tailor treatment or prevention strategies (Figure 5). In the recent study of Weiser et al. [121], DHA supplementation greatly reduced the level of IL-6 as an acute inflammatory marker induced in the rodent model of autism exposed to the viral mimetic polyriboinosinic-polyribocytidylic acid during gestation. This gives preliminary evidence that ω-3 fatty acids may be an effective treatment strategy for children with autism.

A recent report by the Autism Genome Project Consortium identified a new linkage peak for autism in the region of chromosome 11 where the gene for EAAT2 is located [122]. Signs of astroglial, oligodendroglial, and microglial dysfunction were reported in the autistic brain, suggesting that all these cellular processes may represent presumptive targets for novel therapeutic strategies [123]. Additionally, a study investigating the effects of ceftriaxone and cefixime, activators of GLT-1, demonstrated that these drugs improved some symptoms of autism and decreased epilepsy seizures by increasing the expression of the GLT-1, which reduces extracellular glutamate levels [124].

Elevated levels of glutamate are present in high proteins, including wheat gluten and milk casein. This can explain the sensitivity of autistic children to both proteins as a rich source of glutamate. Some parents of autistic children try gluten/casein-restricted diet in an attempt to improve their child’s behavior, but evidence is lacking that following such diet improves the child’s challenging behaviors, cognitive and social functioning as core symptoms of autism [125]. Furthermore, following a gluten casein-free diet may place children at risk for suboptimal bone development [126].

Several animal models and research in typically developing volunteers suggest that the manipulation of the OT system may have a potential therapeutic effect in treating social deficits in autistic patients. Twelve weeks of intranasal treatment with OT (0.4 IU/kg/dose) was found effective in improving social impairment, repetitive behavior, and anxiety in children and adolescents with autism. Some measures suggest the safety and maintenance of the effect for 3 months after the discontinuation of intranasal OT treatment [127]. Meziane et al. [128] reported that an early OT treatment just after birth could be a novel therapeutic approach for the treatment of autism.

In a recent study, Carminati et al. [129] tested the therapeutic efficacy of venlafaxine, an antidepressant drug that inhibits the reuptake of 5-HT, and proved that venlafaxine at a low dose represents a substantial improvement in repetitive behaviors, restricted interests, social impairment, communication, and language. Venlafaxine probably acts via serotonergic mechanisms by affecting the selective 5-HT reuptake inhibitors. Figure 6 summarizes the biomarkers directed to treat autism.

Figure 6.

Biomarkers-directed strategies to treat autism.


  1. 1. Aspy R, Grossman BG.Designing Comprehensive Interventions for High-Functioning Individuals with Autism Spectrum Disorders: The Ziggurat Model. USA, AAPC Publishing; 2011.
  2. 2. Berkel S, Marshall CR, Weiss B, Howe J, Roeth R, Moog U, Endris V, Roberts W, Szatmari P, Pinto D. Mutations in the SHANK2 synaptic scaffolding gene in autism spectrum disorder and mental retardation.Nat Genet2010;42:489–491.
  3. 3. Pinto D, Pagnamenta AT, Klei L, Anney R, Merico D, Regan R, Conroy J, Magalhaes TR, Correia C, Abrahams BS. Functional impact of global rare copy number variation in autism spectrum disorders.Nature2010;466:368–372.
  4. 4. Gilman SR, Iossifov I, Levy D, Ronemus M, Wigler M, Vitkup D. Rarede novovariants associated with autism implicate a large functional network of genes involved in formation and function of synapses.Neuron2011;70:898–907.
  5. 5. State MW, Šestan N. The emerging biology of autism spectrum disorders.Science2012;337:1301.
  6. 6. Sanders SJ, Ercan-Sencicek AG, Hus V, Luo R, Murtha MT, Moreno-De-Luca D, Chu SH, Moreau MP, Gupta AR, Thomson SA. Multiple recurrentde novoCNVs, including duplications of the 7q11. 23 Williams syndrome region, are strongly associated with autism.Neuron2011;70:863–885.
  7. 7. Fombonne E. Epidemiology of pervasive developmental disorders.Pediatr Res2009;65:591–598.
  8. 8. Kim YS, Leventhal BL, Koh Y-J, Fombonne E, Laska E, Lim E-C, Cheon K-A, Kim S-J, Kim Y-K, Lee H. Prevalence of autism spectrum disorders in a total population sample.Am J Psychiatry2011;168:904–912.
  9. 9. Main P, Angley MT, O’Doherty CE, Thomas P, Fenech M. The potential role of the antioxidant and detoxification properties of glutathione in autism spectrum disorders: a systematic review and meta-analysis.Nutr Metab (Lond)2012;9:35.
  10. 10. Lord RS, Bralley JA. Clinical applications of urinary organic acids. Part I: detoxification markers.Altern Med Rev2008;13:205–215.
  11. 11. Mostafa GA, El-Hadidi ES, Hewedi DH, Abdou MM. Oxidative stress in Egyptian children with autism: relation to autoimmunity.J Neuroimmunol2010;219:114–118.
  12. 12. Alabdali A, Al-Ayadhi L, El-Ansary A. Association of social and cognitive impairment and biomarkers in autism spectrum disorders.J Neuroinflamm2014;11.
  13. 13. Q-b Zhang, Gao S-j, H-x Zhao. Thioredoxin: a novel, independent diagnosis marker in children with autism.Int J Dev Neurosci2015;40:92–96.
  14. 14. Rossignol D, Frye R. Mitochondrial dysfunction in autism spectrum disorders: a systematic review and meta-analysis.Mol Psychiatry2012;17:290–314.
  15. 15. Mulle JG, Sharp WG, Cubells JF. The gut microbiome: a new frontier in autism research.Curr Psychiatry Rep2013;15:1–9.
  16. 16. Burokas A, Moloney RD, Dinan TG, Cryan JF. Chapter one—microbiota regulation of the mammalian gut-brain axis.Adv Appl Microbiol2015;91:1–62.
  17. 17. Smith SE, Li J, Garbett K, Mirnics K, Patterson PH. Maternal immune activation alters fetal brain development through interleukin-6.J Neurosci2007;27:10695–10702.
  18. 18. Libbey JE, Fujinami RS. Role for antibodies in altering behavior and movement.Autism Res2010;3:147–152.
  19. 19. Angelidou A, Asadi S, Alysandratos K-D, Karagkouni A, Kourembanas S, Theoharides TC. Perinatal stress, brain inflammation and risk of autism-Review and proposal.BMC Pediatr2012;12:89.
  20. 20. Fetissov SO, Sinno MH, Coëffier M, Bole-Feysot C, DucrottéP, Hökfelt T, Déchelotte P. Autoantibodies against appetite-regulating peptide hormones and neuropeptides: putative modulation by gut microflora.Nutrition2008;24:348–359.
  21. 21. de Magistris L, Familiari V, Pascotto A, Sapone A, Frolli A, Iardino P, Carteni M, De Rosa M, Francavilla R, Riegler G. Alterations of the intestinal barrier in patients with autism spectrum disorders and in their first-degree relatives.J Pediatr Gastroenterol Nutr2010;51:418–424.
  22. 22. Turner JR. Intestinal mucosal barrier function in health and disease.Nat Rev Immunol2009;9:799–809.
  23. 23. Hsiao EY, Mc Bride SW, Hsien S, Sharon G, Hyde ER, McCue T, Codelli JA, Chow J, Reisman SE, Petrosino JF. Microbiota modulate behavioral and physiological abnormalities associated with neurodevelopmental disorders.Cell2013;155:1451–1463.
  24. 24. Parracho HM, Bingham MO, Gibson GR, McCartney AL. Differences between the gut microflora of children with autistic spectrum disorders and that of healthy children.J Med Microbiol2005;54:987–991.
  25. 25. Finegold SM, Dowd SE, Gontcharova V, Liu C, Henley KE, Wolcott RD, Youn E, Summanen PH, Granpeesheh D, Dixon D. Pyrosequencing study of fecal microflora of autistic and control children.Anaerobe2010;16:444–453.
  26. 26. Adams JB, Johansen LJ, Powell LD, Quig D, Rubin RA. Gastrointestinal flora and gastrointestinal status in children with autism—comparisons to typical children and correlation with autism severity.BMC Gastroenterol2011;11:22.
  27. 27. Wang L, Christophersen CT, Sorich MJ, Gerber JP, Angley MT, Conlon MA. Low relative abundances of the mucolytic bacteriumAkkermansia muciniphilaandBifidobacteriumspp. in feces of children with autism.Appl Environ Microbiol2011;77:6718–6721.
  28. 28. Williams BL, Hornig M, Buie T, Bauman ML, Cho Paik M, Wick I, Bennett A, Jabado O, Hirschberg DL, Lipkin WI. Impaired carbohydrate digestion and transport and mucosal dysbiosis in the intestines of children with autism and gastrointestinal disturbances.PLoS One2011;6:e24585.
  29. 29. Williams BL, Hornig M, Parekh T, Lipkin WI. Application of novel PCR-based methods for detection, quantitation, and phylogenetic characterization ofSutterellaspecies in intestinal biopsy samples from children with autism and gastrointestinal disturbances.MBio2012;3:e00261–00211.
  30. 30. Finegold SM, Molitoris D, Song Y, Liu C, Vaisanen M-L, Bolte E, McTeague M, Sandler R, Wexler H, Marlowe EM. Gastrointestinal microflora studies in late-onset autism.Clin Infect Dis2002;35:S6–S16.
  31. 31. De Angelis M, Piccolo M, Vannini L, Siragusa S, De Giacomo A, Serrazzanetti DI, Cristofori F, Guerzoni ME, Gobbetti M, Francavilla R. Fecal microbiota and metabolome of children with autism and pervasive developmental disorder not otherwise specified.PLoS One2013;8:e76993.
  32. 32. Yap IK, Angley M, Veselkov KA, Holmes E, Lindon JC, Nicholson JK. Urinary metabolic phenotyping differentiates children with autism from their unaffected siblings and age-matched controls.J Proteome Res2010;9:2996–3004.
  33. 33. Beloborodova N, Bairamov I, Olenin A, Shubina V, Teplova V, Fedotcheva N. Effect of phenolic acids of microbial origin on production of reactive oxygen species in mitochondria and neutrophils.J Biomed Sci2012;19:89.
  34. 34. MacFabe DF. Short-chain fatty acid fermentation products of the gut microbiome: implications in autism spectrum disorders.Microb Ecol Health Dis2012;23. doi: 10.3402/mehd.v23i0.19260.
  35. 35. MacFabe DF, Cain DP, Rodriguez-Capote K, Franklin AE, Hoffman JE, Boon F, Taylor AR, Kavaliers M, Ossenkopp K-P. Neurobiological effects of intraventricular propionic acid in rats: possible role of short chain fatty acids on the pathogenesis and characteristics of autism spectrum disorders.Behav Brain Res2007;176:149–169.
  36. 36. MacFabe DF, Cain NE, Boon F, Ossenkopp K-P, Cain DP. Effects of the enteric bacterial metabolic product propionic acid on object-directed behavior, social behavior, cognition, and neuroinflammation in adolescent rats: relevance to autism spectrum disorder.Behav Brain Res2011;217:47–54.
  37. 37. Wang LW, Tancredi DJ, Thomas DW. The prevalence of gastrointestinal problems in children across the United States with autism spectrum disorders from families with multiple affected members.J Dev Behav Pediatr2011;32:351–360.
  38. 38. Kataoka S, Takuma K, Hara Y, Maeda Y, Ago Y, Matsuda T. Autism-like behaviours with transient histone hyperacetylation in mice treated prenatally with valproic acid.J Neuropsychopharmacol2013;16:91–103.
  39. 39. Burger-van Paassen N, Vincent A, Puiman P, Van Der Sluis M, Bouma J, Boehm G, van Goudoever J, Van Seuningen I, Renes I. The regulation of intestinal mucin MUC2 expression by short-chain fatty acids: implications for epithelial protection.Biochem J2009;420:211–219.
  40. 40. D’Souza A, Onem E, Patel P, La Gamma EF, Nankova BB. Valproic acid regulates catecholaminergic pathways by concentration-dependent threshold effects on TH mRNA synthesis and degradation.Brain Res2009;1247:1–10.
  41. 41. Liu H, Hu Q, Kaufman A, D’Ercole AJ, Ye P. Developmental expression of histone deacetylase 11 in the murine brain.J Neurosci Res2008;86:537–543.
  42. 42. Patterson PH. Maternal infection: window on neuroimmune interactions in fetal brain development and mental illness.Curr Opin Neurobiol2002;12:115–118.
  43. 43. Stolp H, Dziegielewska K. Review: role of developmental inflammation and blood-brain barrier dysfunction in neurodevelopmental and neurodegenerative diseases.Neuropathol Appl Neurobiol2009;35:132–146.
  44. 44. Hornig M, Briese T, Buie T, Bauman ML, Lauwers G, Siemetzki U, Hummel K, Rota PA, Bellini WJ, O’Leary JJ. Lack of association between measles virus vaccine and autism with enteropathy: a case-control study.PLoS One2008;3:e3140.
  45. 45. Malik M, Sheikh AM, Wen G, Spivack W, Brown WT, Li X. Expression of inflammatory cytokines, Bcl2 and cathepsin D are altered in lymphoblasts of autistic subjects.Immunobiology2011;216:80–85.
  46. 46. Jyonouchi H, Sun S, Le H. Proinflammatory and regulatory cytokine production associated with innate and adaptive immune responses in children with autism spectrum disorders and developmental regression.J Neuroimmunol2001;120:170–179.
  47. 47. Morgan JT, Chana G, Pardo CA, Achim C, Semendeferi K, Buckwalter J, Courchesne E, Everall IP. Microglial activation and increased microglial density observed in the dorsolateral prefrontal cortex in autism.Biol Psychiatry2010;68:368–376.
  48. 48. Vargas DL, Nascimbene C, Krishnan C, Zimmerman AW, Pardo CA. Neuroglial activation and neuroinflammation in the brain of patients with autism.Ann Neurol2005;57:67–81.
  49. 49. Chez MG, Guido-Estrada N. Immune therapy in autism: historical experience and future directions with immunomodulatory therapy.Neurotherapeutics2010;7:293–301.
  50. 50. Garbett K, Ebert PJ, Mitchell A, Lintas C, Manzi B, Mirnics K, Persico AM. Immune transcriptome alterations in the temporal cortex of subjects with autism.Neurobiol Dis2008;30:303–311.
  51. 51. Suganya V, Geetha A, Sujatha S. Urine proteome analysis to evaluate protein biomarkers in children with autism.Clin Chim Acta2015;450:210–219.
  52. 52. West PR, Amaral DG, Bais P, Smith AM, Egnash LA, Ross ME, Palmer JA, Fontaine BR, Conard KR, Corbett BA. Metabolomics as a tool for discovery of biomarkers of autism spectrum disorder in the blood plasma of children.PLoS One2014;9:e112445.
  53. 53. Palmieri F. The mitochondrial transporter family (SLC25): physiological and pathological implications.Pflügers Arch2004;447:689–709.
  54. 54. Viegas CM, Busanello ENB, Tonin AM, de Moura AP, Grings M, Ritter L, Schuck PF, da CostaFerreira G, Sitta A, Vargas CR. Dual mechanism of brain damage induced in vivo by the major metabolites accumulating in hyperornithinemia-hyperammonemia-homocitrullinuria syndrome.Brain Res2011;1369:235–244.
  55. 55. Sokoro AA, Lepage J, Antonishyn N, McDonald R, Rockman-Greenberg C, Irvine J, Lehotay DC. Diagnosis and high incidence of hyperornithinemia-hyperammonemia-homocitrullinemia (HHH) syndrome in northern Saskatchewan.J Inherit Metab Dis2010;33:275–281.
  56. 56. Brenna JT, Carlson SE. Docosahexaenoic acid and human brain development: evidence that a dietary supply is needed for optimal development.J Hum Evol2014;77:99–106.
  57. 57. Simopoulos AP. Evolutionary aspects of diet: the ω-6/ω-3 ratio and the brain.Mol Neurobiol2011;44:203–215.
  58. 58. Vancassel S, Durand G, Barthelemy C, Lejeune B, Martineau J, Guilloteau D, Andres C, Chalon S. Plasma fatty acid levels in autistic children.Prostaglandins Leukot Essent Fatty Acids2001;65:1–7.
  59. 59. Ghezzo A, Visconti P, Abruzzo PM, Bolotta A, Ferreri C, Gobbi G, Malisardi G, Manfredini S, Marini M, Nanetti L. Oxidative stress and erythrocyte membrane alterations in children with autism: correlation with clinical features.PLoS One2013;8:e66418.
  60. 60. Fombonne E, Morel J, Macarthur J. No autism amongst Inuits from northern Quebec. InFifth International Meeting for Autism Research, Montreal, Quebec; 2006.
  61. 61. Lucas D, Newhouse J. The toxic effect of sodium L-glutamate on the inner layers of the retina.AMA Arch Ophthalmol1957;58:193–201.
  62. 62. Olney JW. Brain lesions, obesity, and other disturbances in mice treated with monosodium glutamate.Science1969;164:719–721.
  63. 63. Blaylock R, Strunecka A. Immune-glutamatergic dysfunction as a central mechanism of the autism spectrum disorders.Curr Med Chem2009;16:157–170.
  64. 64. Bu D-F, Erlander MG, Hitz BC, Tillakaratne N, Kaufman DL, Wagner-McPherson CB, Evans GA, Tobin AJ. Two human glutamate decarboxylases, 65-kDa GAD and 67-kDa GAD, are each encoded by a single gene.Proc Natl Acad Sci U S A1992;89:2115–2119.
  65. 65. Rabionet R, Jaworski JM, Ashley-Koch AE, Martin ER, Sutcliffe JS, Haines JL, DeLong GR, Abramson RK, Wright HH, Cuccaro ML. Analysis of the autism chromosome 2 linkage region: GAD1 and other candidate genes.Neurosci Lett2004;372:209–214.
  66. 66. Kern JK. Purkinje cell vulnerability and autism: a possible etiological connection.Brain Dev2003;25:377–382.
  67. 67. Yip J, Soghomonian J-J, Blatt GJ. Decreased GAD67 mRNA levels in cerebellar Purkinje cells in autism: pathophysiological implications.Acta Neuropathol2007;113:559–568.
  68. 68. Fatemi SH, Halt AR, Stary JM, Kanodia R, Schulz SC, Realmuto GR. Glutamic acid decarboxylase 65 and 67 kDa proteins are reduced in autistic parietal and cerebellar cortices.Biol Psychiatry2002;52:805–810.
  69. 69. Aldred S, Moore KM, Fitzgerald M, Waring RH. Plasma amino acid levels in children with autism and their families.J Autism Dev Disord2003;33:93–97.
  70. 70. Shinohe A, Hashimoto K, Nakamura K, Tsujii M, Iwata Y, Tsuchiya KJ, Sekine Y, Suda S, Suzuki K, Sugihara G-I. Increased serum levels of glutamate in adult patients with autism.Prog Neuro-psychopharmacol Biol Psychiatry2006;30:1472–1477.
  71. 71. Abu-Shmais GA, Al-Ayadhi LY, Al-Dbass AM, El-Ansary AK. Mechanism of nitrogen metabolism-related parameters and enzyme activities in the pathophysiology of autism.J Neurodev Disord2012;4:4.
  72. 72. Uzunova G, Pallanti S, Hollander E. Excitatory/inhibitory imbalance in autism spectrum disorders: implications for interventions and therapeutics.World J Biol Psychiatry2015:1–13.
  73. 73. El-Ansary A, Al-Ayadhi L. Neuroinflammation in autism spectrum disorders.Neuroinflammation2012;9:265.
  74. 74. Raghavendra Rao VL, Başkaya MK, Doğan A, Rothstein JD, Dempsey RJ. Traumatic brain injury down-regulates glial glutamate transporter (GLT-1 and GLAST) proteins in rat brain.J Neurochem1998;70:2020–2027.
  75. 75. Wei H, Ding C, Jin G, Yin H, Liu J, Hu F. Abnormal glutamate release in aged BTBR mouse model of autism.Int J Clin Exp Pathol2015;8:10689.
  76. 76. Tanaka K. Role of glutamate transporters in the pathophysiology of major mental illnesses.Nihon Shinkei Seishin Yakurigaku Zasshi2009;29:161–164.
  77. 77. Purcell A, Jeon O, Zimmerman A, Blue M, Pevsner J. Postmortem brain abnormalities of the glutamate neurotransmitter system in autism.Neurology2001;57:1618–1628.
  78. 78. Hertz L, Peng L. Energy metabolism at the cellular level of the CNS.Can J Physiol Pharmacol1992;70:S145–S157.
  79. 79. Bannai S, Tateishi N. Role of membrane transport in metabolism and function of glutathione in mammals.J Membr Biol1986;89:1–8.
  80. 80. Gabriele S, Sacco R, Persico AM. Blood serotonin levels in autism spectrum disorder: a systematic review and meta-analysis.Eur Neuropsychopharmacol2014;24:919–929.
  81. 81. Yang C-J, Tan H-P, Yang F-Y, Wang H-P, Liu C-L, He H-Z, Sang B, Zhu X-M, Du Y-J. The cortisol, serotonin and oxytocin are associated with repetitive behavior in autism spectrum disorder.Res Autism Spectr Disord2015;18:12–20.
  82. 82. Chugani DC, Muzik O, Rothermel R, Behen M, Chakraborty P, Mangner T, Da Silva EA, Chugani HT. Altered serotonin synthesis in the dentatothalamocortical pathway in autistic boys.Ann Neurol1997;42:666–669.
  83. 83. Makkonen I, Riikonen R, Kokki H, Airaksinen MM, Kuikka JT. Serotonin and dopamine transporter binding in children with autism determined by SPECT.Dev Med Child Neurol2008;50:593–597.
  84. 84. Nakamura K, Sekine Y, Ouchi Y, Tsujii M, Yoshikawa E, Futatsubashi M, Tsuchiya KJ, Sugihara G, Iwata Y, Suzuki K. Brain serotonin and dopamine transporter bindings in adults with high-functioning autism.Arch Gen Psychiatry2010;67:59–68.
  85. 85. Oblak A, Gibbs TT, Blatt GJ. Reduced serotonin receptor subtypes in a limbic and a neocortical region in autism.Autism Res2013;6:571–583.
  86. 86. Kolevzon A, Newcorn JH, Kryzak L, Chaplin W, Watner D, Hollander E, Smith CJ, Cook EH, Silverman JM. Relationship between whole blood serotonin and repetitive behaviors in autism.Psychiatry Res2010;175:274–276.
  87. 87. Sacco R, Curatolo P, Manzi B, Militerni R, Bravaccio C, Frolli A, Lenti C, Saccani M, Elia M, Reichelt KL. Principal pathogenetic components and biological endophenotypes in autism spectrum disorders.Autism Res2010;3:237–252.
  88. 88. Veenstra-VanderWeele J, Muller CL, Iwamoto H, Sauer JE, Owens WA, Shah CR, Cohen J, Mannangatti P, Jessen T, Thompson BJ. Autism gene variant causes hyperserotonemia, serotonin receptor hypersensitivity, social impairment and repetitive behavior.Proc Natl Acad Sci U S A2012;109:5469–5474.
  89. 89. Insel TR. The challenge of translation in social neuroscience: a review of oxytocin, vasopressin, and affiliative behavior.Neuron2010;65:768–779.
  90. 90. Meyer-Lindenberg A, Domes G, Kirsch P, Heinrichs M. Oxytocin and vasopressin in the human brain: social neuropeptides for translational medicine.Nat Rev Neurosci2011;12:524–538.
  91. 91. Modahl C, Green LA, Fein D, Morris M, Waterhouse L, Feinstein C, Levin H. Plasma oxytocin levels in autistic children.Biol Psychiatry1998;43:270–277.
  92. 92. Andari E, Duhamel J-R, Zalla T, Herbrecht E, Leboyer M, Sirigu A. Promoting social behavior with oxytocin in high-functioning autism spectrum disorders.Proc Natl Acad Sci U S A2010;107:4389–4394.
  93. 93. Green L, Fein D, Modahl C, Feinstein C, Waterhouse L, Morris M. Oxytocin and autistic disorder: alterations in peptide forms.Biol Psychiatry2001;50:609–613.
  94. 94. Wu S, Jia M, Ruan Y, Liu J, Guo Y, Shuang M, Gong X, Zhang Y, Yang X, Zhang D. Positive association of the oxytocin receptor gene (OXTR) with autism in the Chinese Han population.Biol Psychiatry2005;58:74–77.
  95. 95. Jacob S, Brune CW, Carter C, Leventhal BL, Lord C, Cook EH. Association of the oxytocin receptor gene (OXTR) in Caucasian children and adolescents with autism.Neurosci Lett2007;417:6–9.
  96. 96. Lerer E, Levi S, Salomon S, Darvasi A, Yirmiya N, Ebstein R. Association between the oxytocin receptor (OXTR) gene and autism: relationship to Vineland Adaptive Behavior Scales and cognition.Mol Psychiatry2008;13:980–988.
  97. 97. Yrigollen CM, Han SS, Kochetkova A, Babitz T, Chang JT, Volkmar FR, Leckman JF, Grigorenko EL. Genes controlling affiliative behavior as candidate genes for autism.Biol Psychiatry2008;63:911–916.
  98. 98. Ebstein RP, Knafo A, Mankuta D, ChewSH, SanLai P. The contributions of oxytocin and vasopressin pathway genes to human behavior.Horm Behav2012;61:359–379.
  99. 99. Dölen G, Darvishzadeh A, Huang KW, Malenka RC. Social reward requires coordinated activity of nucleus accumbens oxytocin and serotonin.Nature2013;501:179–184.
  100. 100. Dölen G. Autism: oxytocin, serotonin, and social reward.Soc Neurosci2015;10:450–465.
  101. 101. Pepe M, Longton G, Janes H. Estimation and comparison of receiver operating characteristic curves.Stata J2009;9:1.
  102. 102. Yang CJ, Liu CL, Sang B, Zhu XM, Du YJ. The combined role of serotonin and interleukin-6 as biomarker for autism.Neuroscience2015;284:290–296.
  103. 103. Mehl-Madrona L, Leung B, Kennedy C, Paul S, Kaplan BJ. Micronutrients versus standard medication management in autism: a naturalistic case-control study.J Child Adolesc Psychopharmacol2010;20:95–103.
  104. 104. Patel K, Curtis LT. A comprehensive approach to treating autism and attention-deficit hyperactivity disorder: a prepilot study.J Altern Complement Med2007;13:1091–1098.
  105. 105. Kidd PM. Autism, an extreme challenge to integrative medicine. Part II: medical management.Altern Med Rev2002;7:472–499.
  106. 106. Cornish S, Mehl-Madrona L. The role of vitamins and minerals in psychiatry.Integr Med Insights2008;3:33.
  107. 107. Henriksen C, Haugholt K, Lindgren M, Aurvåg AK, Rønnestad A, Grønn M, Solberg R, Moen A, Nakstad B, Berge RK. Improved cognitive development among preterm infants attributable to early supplementation of human milk with docosahexaenoic acid and arachidonic acid.Pediatrics2008;121:1137–1145.
  108. 108. Isaacs EB, Ross S, Kennedy K, Weaver LT, Lucas A, Fewtrell MS. 10-year cognition in preterms after random assignment to fatty acid supplementation in infancy.Pediatrics2011;128:e890–e898.
  109. 109. Makrides M, Gibson RA, McPhee AJ, Yelland L, Quinlivan J, Ryan P. Effect of DHA supplementation during pregnancy on maternal depression and neurodevelopment of young children: a randomized controlled trial.JAMA2010;304:1675–1683.
  110. 110. Dunstan J, Simmer K, Dixon G, Prescott S. Cognitive assessment of children at age 2½ years after maternal fish oil supplementation in pregnancy: a randomised controlled trial.Arch Dis Child2008;93:F45–F50.
  111. 111. Smithers LG, Gibson RA, Makrides M. Maternal supplementation with docosahexaenoic acid during pregnancy does not affect early visual development in the infant: a randomized controlled trial.Am J Clin Nutr2011;93:1293–1299.
  112. 112. Wurtman RJ. Synapse formation and cognitive brain development: effect of docosahexaenoic acid and other dietary constituents.Metabolism2008;57:S6–S10.
  113. 113. Bouwstra H, Dijck-Brouwer DJ, Decsi T, Boehm G, Boersma ER, Muskiet FA, Hadders-Algra M. Relationship between umbilical cord essential fatty acid content and the quality of general movements of healthy term infants at 3 months.Pediatr Res2006;59:717–722.
  114. 114. Fewtrell MS, Morley R, Abbott RA, Singhal A, Isaacs EB, Stephenson T, MacFadyen U, Lucas A. Double-blind, randomized trial of long-chain polyunsaturated fatty acid supplementation in formula fed to preterm infants.Pediatrics2002;110:73–82.
  115. 115. Carrié I, Guesnet P, Bourre J-M, Francès H. Diets containing long-chainn-3 polyunsaturated fatty acids affect behaviour differently during development than ageing in mice.Br J Nutr2000;83:439–447.
  116. 116. El-Ansary AK, Al-Daihan SK, El-Gezeery AR. On the protective effect of ω-3 against propionic acid-induced neurotoxicity in rat pups.Lipids Health Dis2011;10:19.
  117. 117. Coluccia A, Borracci P, Renna G, Giustino A, Latronico T, Riccio P, Carratù MR. Developmental ω-3 supplementation improves motor skills in juvenile-adult rats.Int J Dev Neurosci2009;27:599–605.
  118. 118. Amminger GP, Berger GE, Schäfer MR, Klier C, Friedrich MH, Feucht M. ω-3 fatty acids supplementation in children with autism: a double-blind randomized, placebo-controlled pilot study.Biol Psychiatry2007;61:551–553.
  119. 119. Richardson AJ, Montgomery P. The Oxford-Durham study: a randomized, controlled trial of dietary supplementation with fatty acids in children with developmental coordination disorder.Pediatrics2005;115:1360–1366.
  120. 120. Hibbeln JR, Linnoila M, Umhau JC, Rawlings R, George DT, Salem N. Essential fatty acids predict metabolites of serotonin and dopamine in cerebrospinal fluid among healthy control subjects, and early-and late-onset alcoholics.Biol Psychiatry1998;44:235–242.
  121. 121. Weiser MJ, Wynalda K, Salem N, Butt CM. Dietary DHA during development affects depression-like behaviors and biomarkers that emerge after puberty in adolescent rats.J Lipid Res2015;56:151–166.
  122. 122. Szatmari P, Paterson AD, Zwaigenbaum L, Roberts W, Brian J, Liu X-Q, Vincent JB, Skaug JL, Thompson AP, Senman L. Mapping autism risk loci using genetic linkage and chromosomal rearrangements.Nat Genet2007;39:319–328.
  123. 123. Zeidán-Chuliá F, Salmina AB, Malinovskaya NA, Noda M, Verkhratsky A, Moreira JCF. The glial perspective of autism spectrum disorders.Neurosci Biobehav Rev2014;38:160–172.
  124. 124. Ghanizadeh A, Michael B. β-Lactam antibiotics as a possible novel therapy for managing epilepsy and autism: a case report and review of literature.Iran J Child Neurol2015;9:99.
  125. 125. Millward C, Ferriter M, Calver S, Connell-Jones G. Gluten-and casein-free diets for autistic spectrum disorder.Cochrane Database Syst Rev2008;2.
  126. 126. Geraghty ME, Depasquale GM, Lane AE. Nutritional intake and therapies in autism a spectrum of what we know: part 1.Infant Child Adolesc Nutr2010;2:62–69.
  127. 127. Anagnostou E, Soorya L, Brian J, Dupuis A, Mankad D, Smile S, Jacob S. Intranasal oxytocin in the treatment of autism spectrum disorders: a review of literature and early safety and efficacy data in youth.Brain Res2014;1580:188–198.
  128. 128. Meziane H, Schaller F, Bauer S, Villard C, Matarazzo V, Riet F, Guillon G, Lafitte D, Desarmenien MG, Tauber M. An early postnatal oxytocin treatment prevents social and learning deficits in adult mice deficient for Magel2, a gene involved in Prader-Willi syndrome and autism.Biol Psychiatry2014.
  129. 129. Carminati GG, Gerber F, Darbellay B, Kosel MM, Deriaz N, Chabert J, Fathi M, Bertschy G, Ferrero F, Carminati F. Using venlafaxine to treat behavioral disorders in patients with autism spectrum disorder.Prog Neuro-psychopharmacol Biol Psychiatry2016;65:85–95.

Written By

Afaf El-Ansary and Hussain Al Dera

Submitted: October 13th, 2015 Reviewed: February 17th, 2016 Published: August 17th, 2016