Cluster analysis of autistic patients based on principal pathogenetic components

Finding Similarities in Differences Between Autistic Adults: Two Replicated Subgroups

Autism is heterogeneous, which complicates providing tailored support and future prospects. We aim to identify subgroups in autistic adults with average to high intelligence, to clarify if certain subgroups might need support. We included 14 questionnaire variables related to aging and/or autism (e.g., demographic, psychological, and lifestyle). Community detection analysis was used for subgroup identification in an original sample of 114 autistic adults with an adulthood diagnosis (autism) and 58 non-autistic adults as comparison group (COMP), and a replication sample (NAutism = 261; NCOMP = 287), both aged 30-89 years. Next, we identified subgroups and assessed external validity (for cognitive and psychological difficulties, and quality of life [QoL]) in the autism samples. To test specificity, we repeated the analysis after adding 123 adults with ADHD, aged 30-80 years. As expected, the autism and COMP groups formed distinct subgroups. Among autistic adults, we identified three subgroups of which two were replicated. One of these subgroups seemed most vulnerable on the cluster variables; this subgroup also reported the most cognitive and psychological difficulties, and lowest QoL. Adding the ADHD group did not alter results. Within autistic adults, one subgroup could especially benefit from support and specialized care, although this must be tested in future studies.

Autism spectrum disorder and a possible role of anti-inflammatory treatments: experience in the pediatric allergy/immunology clinic

Autism spectrum disorder (ASD1) is a behaviorally defined syndrome encompassing a markedly heterogeneous patient population. Many ASD subjects fail to respond to the 1st line behavioral and pharmacological interventions, leaving parents to seek out other treatment options. Evidence supports that neuroinflammation plays a role in ASD pathogenesis. However, the underlying mechanisms likely vary for each ASD patient, influenced by genetic, epigenetic, and environmental factors. Although anti-inflammatory treatment measures, mainly based on metabolic changes and oxidative stress, have provided promising results in some ASD subjects, the use of such measures requires the careful selection of ASD subjects based on clinical and laboratory findings. Recent progress in neuroscience and molecular immunology has made it possible to allow re-purposing of currently available anti-inflammatory medications, used for autoimmune and other chronic inflammatory conditions, as treatment options for ASD subjects. On the other hand, emerging anti-inflammatory medications, including biologic and gate-keeper blockers, exert powerful anti-inflammatory effects on specific mediators or signaling pathways. It will require both a keen understanding of the mechanisms of action of such agents and the careful selection of ASD patients suitable for each treatment. This review will attempt to summarize the use of anti-inflammatory agents already used in targeting ASD patients, and then emerging anti-inflammatory measures applicable for ASD subjects based on scientific rationale and clinical trial data, if available. In our experience, some ASD patients were treated under diagnoses of autoimmune/autoinflammatory conditions and/or post-infectious neuroinflammation. However, there are little clinical trial data specifically for ASD subjects. Therefore, these emerging immunomodulating agents for potential use for ASD subjects will be discussed based on preclinical data, case reports, or data generated in patients with other medical conditions. This review will hopefully highlight the expanding scope of immunomodulating agents for treating neuroinflammation in ASD subjects.

Endophenotype trait domains for advancing gene discovery in autism spectrum disorder

Autism spectrum disorder (ASD) is associated with a diverse range of etiological processes, including both genetic and non-genetic causes. For a plurality of individuals with ASD, it is likely that the primary causes involve multiple common inherited variants that individually account for only small levels of variation in phenotypic outcomes. This genetic landscape creates a major challenge for detecting small but important pathogenic effects associated with ASD. To address similar challenges, separate fields of medicine have identified endophenotypes, or discrete, quantitative traits that reflect genetic likelihood for a particular clinical condition and leveraged the study of these traits to map polygenic mechanisms and advance more personalized therapeutic strategies for complex diseases. Endophenotypes represent a distinct class of biomarkers useful for understanding genetic contributions to psychiatric and developmental disorders because they are embedded within the causal chain between genotype and clinical phenotype, and they are more proximal to the action of the gene(s) than behavioral traits. Despite their demonstrated power for guiding new understanding of complex genetic structures of clinical conditions, few endophenotypes associated with ASD have been identified and integrated into family genetic studies. In this review, we argue that advancing knowledge of the complex pathogenic processes that contribute to ASD can be accelerated by refocusing attention toward identifying endophenotypic traits reflective of inherited mechanisms. This pivot requires renewed emphasis on study designs with measurement of familial co-variation including infant sibling studies, family trio and quad designs, and analysis of monozygotic and dizygotic twin concordance for select trait dimensions. We also emphasize that clarification of endophenotypic traits necessarily will involve integration of transdiagnostic approaches as candidate traits likely reflect liability for multiple clinical conditions and often are agnostic to diagnostic boundaries. Multiple candidate endophenotypes associated with ASD likelihood are described, and we propose a new focus on the analysis of "endophenotype trait domains" (ETDs), or traits measured across multiple levels (e.g., molecular, cellular, neural system, neuropsychological) along the causal pathway from genes to behavior. To inform our central argument for research efforts toward ETD discovery, we first provide a brief review of the concept of endophenotypes and their application to psychiatry. Next, we highlight key criteria for determining the value of candidate endophenotypes, including unique considerations for the study of ASD. Descriptions of different study designs for assessing endophenotypes in ASD research then are offered, including analysis of how select patterns of results may help prioritize candidate traits in future research. We also present multiple candidate ETDs that collectively cover a breadth of clinical phenomena associated with ASD, including social, language/communication, cognitive control, and sensorimotor processes. These ETDs are described because they represent promising targets for gene discovery related to clinical autistic traits, and they serve as models for analysis of separate candidate domains that may inform understanding of inherited etiological processes associated with ASD as well as overlapping neurodevelopmental disorders.

Identification of subgroups of children in the Australian Autism Biobank using latent class analysis

BACKGROUND

The identification of reproducible subtypes within autistic populations is a priority research area in the context of neurodevelopment, to pave the way for identification of biomarkers and targeted treatment recommendations. Few previous studies have considered medical comorbidity alongside behavioural, cognitive, and psychiatric data in subgrouping analyses. This study sought to determine whether differing behavioural, cognitive, medical, and psychiatric profiles could be used to distinguish subgroups of children on the autism spectrum in the Australian Autism Biobank (AAB).

METHODS

Latent profile analysis was used to identify subgroups of children on the autism spectrum within the AAB (n = 1151), utilising data on social communication profiles and restricted, repetitive, and stereotyped behaviours (RRBs), in addition to their cognitive, medical, and psychiatric profiles.

RESULTS

Our study identified four subgroups of children on the autism spectrum with differing profiles of autism traits and associated comorbidities. Two subgroups had more severe clinical and cognitive phenotype, suggesting higher support needs. For the 'Higher Support Needs with Prominent Language and Cognitive Challenges' subgroup, social communication, language and cognitive challenges were prominent, with prominent sensory seeking behaviours. The 'Higher Support Needs with Prominent Medical and Psychiatric and Comorbidity' subgroup had the highest mean scores of challenges relating to social communication and RRBs, with the highest probability of medical and psychiatric comorbidity, and cognitive scores similar to the overall group mean. Individuals within the 'Moderate Support Needs with Emotional Challenges' subgroup, had moderate mean scores of core traits of autism, and the highest probability of depression and/or suicidality. A fourth subgroup contained individuals with fewer challenges across domains (the 'Fewer Support Needs Group').

LIMITATIONS

Data utilised to identify subgroups within this study was cross-sectional as longitudinal data was not available.

CONCLUSIONS

Our findings support the holistic appraisal of support needs for children on the autism spectrum, with assessment of the impact of co-occurring medical and psychiatric conditions in addition to core autism traits, adaptive functioning, and cognitive functioning. Replication of our analysis in other cohorts of children on the autism spectrum is warranted, to assess whether the subgroup structure we identified is applicable in a broader context beyond our specific dataset.

Preliminary Findings of Elevated Inflammatory Plasma Cytokines in Children with Autism Who Have Co-Morbid Gastrointestinal Symptoms

Autism spectrum disorder (AU) is present in approximately 2% of the population and is often associated with co-morbidities that can impact quality of life. One of the most common co-morbidities in autism is the presence of gastrointestinal (GI) symptoms consisting of irregular bowel habits such as constipation, diarrhea, or alternating bowel habit. Evidence of immune infiltration and immune activation has been shown in the ileum and colon of children with AU with GI symptoms. Moreover, immune dysfunction is a contributing factor in many GI diseases, and we hypothesize that it would be more apparent in children with AU that exhibit GI symptoms than those who do not present with GI symptoms. The aim of this preliminary study was to determine whether there are altered cytokine levels in plasma in children with AU with GI symptoms compared with children with AU without GI symptoms, typically developing (TD) children with GI symptoms and TD children without GI symptoms, from the same population-based cohort. Plasma cytokine levels were assessed by multiplex assays. No differences in plasma cytokines were observed in TD controls with or without GI symptoms; however, many innate (IL-1α, TNFα, GM-CSF, IFNα) and adaptive cytokines (IL-4, IL-13, IL-12p70) were increased in AU children with GI symptoms compared with children with AU with no GI symptoms. The mucosal relevant cytokine IL-15 was increased in AU with GI symptoms compared with all groups. In contrast, the regulatory cytokine IL-10, was reduced in AU with GI symptoms and may suggest an imbalance in pro-inflammatory/regulatory signals. These data suggest that children with AU and GI symptoms have an imbalance in their immune response that is evident in their circulating plasma cytokine levels. A finding that could point to potential therapeutic and/or monitoring strategies for GI issues in AU.

Features that best define the heterogeneity and homogeneity of autism in preschool-age children: A multisite case-control analysis replicated across two independent samples

The heterogeneous nature of children with symptoms of autism spectrum disorder (ASD) makes it difficult to identify risk factors and effective treatment options. We sought to identify behavioral and developmental features that best define the heterogeneity and homogeneity in 2-5-year-old children classified with ASD and subthreshold ASD characteristics. Children were enrolled in a multisite case-control study of ASD. Detailed behavioral and developmental data were gathered by maternal telephone interview, parent-administered questionnaires, child cognitive evaluation, and ASD diagnostic measures. Participants with a positive ASD screen score or prior ASD diagnosis were referred for comprehensive evaluation. Children in the ASD group met study criteria based on this evaluation; children who did not meet study criteria were categorized as having subthreshold ASD characteristics. There were 1480 children classified as ASD (81.6% boys) and 594 children classified as having subthreshold ASD characteristics (70.2% boys) in the sample. Factors associated with dysregulation (e.g., aggression, anxiety/depression, sleep problems) followed by developmental abilities (e.g., expressive and receptive language skills) most contributed to heterogeneity in both groups of children. Atypical sensory response contributed to homogeneity in children classified as ASD but not those with subthreshold characteristics. These findings suggest that dysregulation and developmental abilities are clinical features that can impact functioning in children with ASD and other DD, and that documenting these features in pediatric records may help meet the needs of the individual child. Sensory dysfunction could be considered a core feature of ASD and thus used to inform more targeted screening, evaluation, treatment, and research efforts. LAY SUMMARY: The diverse nature of autism spectrum disorder (ASD) makes it difficult to find risk factors and treatment options. We identified the most dissimilar and most similar symptom(s) in children classified as ASD and as having subthreshold ASD characteristics. Factors associated with dysregulation and developmental abilities contributed to diversity in both groups of children. Sensory dysfunction was the most common symptom in children with ASD but not those with subthreshold characteristics. Findings can inform clinical practice and research.

Applications of Unsupervised Machine Learning in Autism Spectrum Disorder Research: a Review

Large amounts of autism spectrum disorder (ASD) data is created through hospitals, therapy centers, and mobile applications; however, much of this rich data does not have pre-existing classes or labels. Large amounts of data—both genetic and behavioral—that are collected as part of scientific studies or a part of treatment can provide a deeper, more nuanced insight into both diagnosis and treatment of ASD. This paper reviews 43 papers using unsupervised machine learning in ASD, including k-means clustering, hierarchical clustering, model-based clustering, and self-organizing maps. The aim of this review is to provide a survey of the current uses of unsupervised machine learning in ASD research and provide insight into the types of questions being answered with these methods.

Heterogeneity thwarts autism explanatory power: A proposal for endophenotypes

Many researchers now believe that autism heterogeneity is likely to include many disorders, but most research is based on samples defined by the DSM-5 Autism Spectrum Disorder (ASD) criteria. However, individuals diagnosed with autism have complex and varied biological causes for their symptoms. Therefore, autism is not a unitary biological entity. And although autism is significantly different from typical development, autism is not a unitary clinical disorder because diagnosed individuals vary in symptom patterns, comorbidities, biomarkers, and gene variants. The DSM-5 ASD criteria were designed to reduce heterogeneity, and there have been many other efforts to reduce autism heterogeneity including using more stringent clinical criteria, dividing autism into low and high functioning groups, creating subgroups, and by studying larger samples. However, to date these efforts have not been successful. Heterogeneity is extensive and remains unexplained, and no autism pathophysiology has been discovered. Most importantly, heterogeneity has hindered the explanatory power of the autism diagnosis to discover drug regimens and effective behavioral treatments. The paper proposes that possible transdiagnostic endophenotypes may reduce autism heterogeneity. Searching for transdiagnostic endophenotypes requires exploring autism symptoms outside of the framework of the DSM-5 autism diagnosis. This paper proposes that researchers relax diagnostic criteria to increase the range of phenotypes to support the search for transdiagnostic endophenotypes. The paper proposes possible candidates for transdiagnostic endophenotypes. These candidates are taken from DSM-5 ASD criteria, from concepts that have resulted from researched theories, and from symptoms that are the result of subtyping. The paper then sketches a possible basis for a future transdiagnostic endophenotypes screening tool that includes symptoms of autism and other neurodevelopmental disorders.

Autism - A Comprehensive Array of Prominent Signs and Symptoms

BACKGROUND

Autism Spectrum Disorder (ASD) is a multifaceted neurodevelopmental condition characterized by multiple psychological and physiological impairments in young children. According to the recent reports, 1 out of every 58 newly-born children is suffering from autism. The aetiology of the disorder is complex and poorly understood, hindering the adaptation of targeted and effective therapies. There are no well- established diagnostic biomarkers for autism. Hence the analysis of symptoms by the pediatricians plays a critical role in the early intervention.

METHODS

In the present report, we have emphasized 24 behavioral, psychological and clinical symptoms of autism.

RESULTS

Impaired social interaction, restrictive and narrow interests, anxiety, depression; aggressive, repetitive, rigid and self-injurious behavior, lack of consistency, short attention span, fear, shyness and phobias, hypersensitivity and rapid mood alterations, high level of food and toy selectivity; inability to establish friendships or follow the instructions; fascination by round spinning objects and eating non-food materials are common psychological characteristics of autism. Speech or hearing impairments, poor cognitive function, gastrointestinal problems, weak immunity, disturbed sleep and circadian rhythms, weak motor neuromuscular interaction, lower level of serotonin and neurotransmitters, headache and body pain are common physiological symptoms.

CONCLUSION

A variable qualitative and quantitative impact of this wide range of symptoms is perceived in each autistic individual, making him/her distinct, incomparable and exceptional. Selection and application of highly personalized medical and psychological therapies are therefore recommended for the management and treatment of autism.

Validation strategies for subtypes in psychiatry: A systematic review of research on autism spectrum disorder

Heterogeneity within autism spectrum disorder (ASD) is recognized as a challenge to both biological and psychological research, as well as clinical practice. To reduce unexplained heterogeneity, subtyping techniques are often used to establish more homogeneous subtypes based on metrics of similarity and dissimilarity between people. We review the ASD literature to create a systematic overview of the subtyping procedures and subtype validation techniques that are used in this field. We conducted a systematic review of 156 articles (2001-June 2020) that subtyped participants (range N of studies = 17-20,658), of which some or all had an ASD diagnosis. We found a large diversity in (parametric and non-parametric) methods and (biological, psychological, demographic) variables used to establish subtypes. The majority of studies validated their subtype results using variables that were measured concurrently, but were not included in the subtyping procedure. Other investigations into subtypes' validity were rarer. In order to advance clinical research and the theoretical and clinical usefulness of identified subtypes, we propose a structured approach and present the SUbtyping VAlidation Checklist (SUVAC), a checklist for validating subtyping results.

Dysfunction of the Auditory Brainstem as a Neurophysiology Subtype of Autism Spectrum Disorder

Autism spectrum disorder (ASD) is very heterogeneous, particularly in language. Studies have suggested that language impairment is linked to auditory-brainstem dysfunction in ASD. However, not all ASD children have these deficits, which suggests potential subtypes of ASD. We classified ASD children into two subtypes according to their speech-evoked auditory brainstem response (speech-ABR) and explored the neural substrates for possible subtypes. Twenty-nine children with ASD and 25 typically developing (TD) peers were enrolled to undergo speech-ABR testing and structural magnetic resonance imaging (sMRI). There were significant differences between the ASD group and TD group in surface area, cortical volume and cortical thickness. According to speech-ABR results, ASD participants were divided into the ASD-typical (ASD-T) group and ASD-atypical (ASD-A) group. Compared with the ASD-T group, the ASD-A group had a lower score in language of the Gesell Developmental Diagnosis Scale (GDDS), increased left rostral middle frontal gyrus (lRMFG) area and decreased local gyrification index of the right superior temporal gyrus. GDDS-language and surface area of lRMFG were correlated to the wave-A amplitude in ASD. Surface area of lRMFG had an indirect effect on language performance via alteration of the wave-V amplitude. Thus, cortical deficits may impair language ability in children with ASD by causing subcortical dysfunction at preschool age. These evidences support dysfunction of the auditory brainstem as a potential subtype of ASD. Besides, this subtype-based method may be useful for various clinical applications.

Endocannabinoid System Unlocks the Puzzle of Autism Treatment via Microglia

Autism spectrum disorder (ASD) is a serious neurodevelopmental disorder and characterized by early childhood-onset impairments in social interaction and communication, restricted and repetitive patterns of behavior or interests. So far there is no effective treatment for ASD, and the pathogenesis of ASD remains unclear. Genetic and epigenetic factors have been considered to be the main cause of ASD. It is known that endocannabinoid and its receptors are widely distributed in the central nervous system, and provide a positive and irreversible change toward a more physiological neurodevelopment. Recently, the endocannabinoid system (ECS) has been found to participate in the regulation of social reward behavior, which has attracted considerable attention from neuroscientists and neurologists. Both animal models and clinical studies have shown that the ECS is a potential target for the treatment of autism, but the mechanism is still unknown. In the brain, microglia express a complete ECS signaling system. Studies also have shown that modulating ECS signaling can regulate the functions of microglia. By comprehensively reviewing previous studies and combining with our recent work, this review addresses the effects of targeting ECS on microglia, and how this can contribute to maintain the positivity of the central nervous system, and thus improve the symptoms of autism. This will provide insights for revealing the mechanism and developing new treatment strategies for autism.

Fractionating autism based on neuroanatomical normative modeling

Autism is a complex neurodevelopmental condition with substantial phenotypic, biological, and etiologic heterogeneity. It remains a challenge to identify biomarkers to stratify autism into replicable cognitive or biological subtypes. Here, we aim to introduce a novel methodological framework for parsing neuroanatomical subtypes within a large cohort of individuals with autism. We used cortical thickness (CT) in a large and well-characterized sample of 316 participants with autism (88 female, age mean: 17.2 ± 5.7) and 206 with neurotypical development (79 female, age mean: 17.5 ± 6.1) aged 6-31 years across six sites from the EU-AIMS multi-center Longitudinal European Autism Project. Five biologically based putative subtypes were derived using normative modeling of CT and spectral clustering. Three of these clusters showed relatively widespread decreased CT and two showed relatively increased CT. These subtypes showed morphometric differences from one another, providing a potential explanation for inconsistent case-control findings in autism, and loaded differentially and more strongly onto symptoms and polygenic risk, indicating a dilution of clinical effects across heterogeneous cohorts. Our results provide an important step towards parsing the heterogeneous neurobiology of autism.

Multivariate Analysis of Fecal Metabolites from Children with Autism Spectrum Disorder and Gastrointestinal Symptoms before and after Microbiota Transfer Therapy

Fecal microbiota transplant (FMT) holds significant promise for patients with Autism Spectrum Disorder (ASD) and gastrointestinal (GI) symptoms. Prior work has demonstrated that plasma metabolite profiles of children with ASD become more similar to those of their typically developing (TD) peers following this treatment. This work measures the concentration of 669 biochemical compounds in feces of a cohort of 18 ASD and 20 TD children using ultrahigh performance liquid chromatography-tandem mass spectroscopy. Subsequent measurements were taken from the ASD cohort over the course of 10-week Microbiota Transfer Therapy (MTT) and 8 weeks after completion of this treatment. Univariate and multivariate statistical analysis techniques were used to characterize differences in metabolites before, during, and after treatment. Using Fisher Discriminant Analysis (FDA), it was possible to attain multivariate metabolite models capable of achieving a sensitivity of 94% and a specificity of 95% after cross-validation. Observations made following MTT indicate that the fecal metabolite profiles become more like those of the TD cohort. There was an 82-88% decrease in the median difference of the ASD and TD group for the panel metabolites, and among the top fifty most discriminating individual metabolites, 96% report more comparable values following treatment. Thus, these findings are similar, although less pronounced, as those determined using plasma metabolites.

The definition and measurement of heterogeneity

Heterogeneity is an important concept in psychiatric research and science more broadly. It negatively impacts effect size estimates under case-control paradigms, and it exposes important flaws in our existing categorical nosology. Yet, our field has no precise definition of heterogeneity proper. We tend to quantify heterogeneity by measuring associated correlates such as entropy or variance: practices which are akin to accepting the radius of a sphere as a measure of its volume. Under a definition of heterogeneity as the degree to which a system deviates from perfect conformity, this paper argues that its proper measure roughly corresponds to the size of a system's event/sample space, and has units known as numbers equivalent. We arrive at this conclusion through focused review of more than 100 years of (re)discoveries of indices by ecologists, economists, statistical physicists, and others. In parallel, we review psychiatric approaches for quantifying heterogeneity, including but not limited to studies of symptom heterogeneity, microbiome biodiversity, cluster-counting, and time-series analyses. We argue that using numbers equivalent heterogeneity measures could improve the interpretability and synthesis of psychiatric research on heterogeneity. However, significant limitations must be overcome for these measures-largely developed for economic and ecological research-to be useful in modern translational psychiatric science.

Targeted Biomedical Treatment for Autism Spectrum Disorders

BACKGROUND

A diagnosis of autism spectrum disorders (ASD) represents presentations with impairment in communication and behaviour that vary considerably in their clinical manifestations and etiology as well as in their likely pathophysiology. A growing body of data indicates that the deleterious effect of oxidative stress, mitochondrial dysfunction, immune dysregulation and neuroinflammation, as well as their interconnections are important aspects of the pathophysiology of ASD. Glutathione deficiency decreases the mitochondrial protection against oxidants and tumor necrosis factor (TNF)-α; immune dysregulation and inflammation inhibit mitochondrial function through TNF-α; autoantibodies against the folate receptors underpin cerebral folate deficiency, resulting in disturbed methylation, and mitochondrial dysfunction. Such pathophysiological processes can arise from environmental and epigenetic factors as well as their combined interactions, such as environmental toxicant exposures in individuals with (epi)genetically impaired detoxification. The emerging evidence on biochemical alterations in ASD is forming the basis for treatments aimed to target its biological underpinnings, which is of some importance, given the uncertain and slow effects of the various educational interventions most commonly used.

METHODS

Literature-based review of the biomedical treatment options for ASD that are derived from established pathophysiological processes.

RESULTS

Most proposed biomedical treatments show significant clinical utility only in ASD subgroups, with specified pre-treatment biomarkers that are ameliorated by the specified treatment. For example, folinic acid supplementation has positive effects in ASD patients with identified folate receptor autoantibodies, whilst the clinical utility of methylcobalamine is apparent in ASD patients with impaired methylation capacity. Mitochondrial modulating cofactors should be considered when mitochondrial dysfunction is evident, although further research is required to identify the most appropriate single or combined treatment. Multivitamins/multiminerals formulas, as well as biotin, seem appropriate following the identification of metabolic abnormalities, with doses tapered to individual requirements. A promising area, requiring further investigations, is the utilization of antipurinergic therapies, such as low dose suramin.

CONCLUSION

The assessment and identification of relevant physiological alterations and targeted intervention are more likely to produce positive treatment outcomes. As such, current evidence indicates the utility of an approach based on personalized and evidence-based medicine, rather than treatment targeted to all that may not always be beneficial (primum non nocere).

Reconciling Dimensional and Categorical Models of Autism Heterogeneity: A Brain Connectomics and Behavioral Study

BACKGROUND

Heterogeneity in autism spectrum disorder (ASD) has hindered the development of biomarkers, thus motivating subtyping efforts. Most subtyping studies divide individuals with ASD into nonoverlapping (categorical) subgroups. However, continuous interindividual variation in ASD suggests that there is a need for a dimensional approach.

METHODS

A Bayesian model was employed to decompose resting-state functional connectivity (RSFC) of individuals with ASD into multiple abnormal RSFC patterns, i.e., categorical subtypes, henceforth referred to as "factors." Importantly, the model allowed each individual to express one or more factors to varying degrees (dimensional subtyping). The model was applied to 306 individuals with ASD (5.2-57 years of age) from two multisite repositories. Post hoc analyses associated factors with symptoms and demographics.

RESULTS

Analyses yielded three factors with dissociable whole-brain hypo- and hyper-RSFC patterns. Most participants expressed multiple (categorical) factors, suggestive of a mosaic of subtypes within individuals. All factors shared abnormal RSFC involving the default mode network, but the directionality (hypo- or hyper-RSFC) differed across factors. Factor 1 was associated with core ASD symptoms. Factors 1 and 2 were associated with distinct comorbid symptoms. Older male participants preferentially expressed factor 3. Factors were robust across control analyses and were not associated with IQ or head motion.

CONCLUSIONS

There exist at least three ASD factors with dissociable whole-brain RSFC patterns, behaviors, and demographics. Heterogeneous default mode network hypo- and hyper-RSFC across the factors might explain previously reported inconsistencies. The factors differentiated between core ASD and comorbid symptoms-a less appreciated domain of heterogeneity in ASD. These factors are coexpressed in individuals with ASD with different degrees, thus reconciling categorical and dimensional perspectives of ASD heterogeneity.

Identifying latent subgroups of children with developmental delay using Bayesian sequential updating and Dirichlet process mixture modelling

Identifying children who are at-risk for developmental delay, so that these children can have access to interventions as early as possible, is an important and challenging problem in developmental research. This research aimed to identify latent subgroups of children with developmental delay, by modelling and clustering developmental milestones. The main objectives were to (a) create a developmental profile for each child by modelling milestone achievements, from birth to three years of age, across multiple domains of development, and (b) cluster the profiles to identify groups of children who show similar deviations from typical development. The ensemble methodology used in this research consisted of three components: (1) Bayesian sequential updating was used to model the achievement of milestones, which allows for updated predictions of development to be made in real time; (2) a measure was created that indicated how far away each child deviated from typical development for each functional domain, by calculating the area between each child’s obtained sequence of posterior means and a sequence of posterior means representing typical development; and (3) Dirichlet process mixture modelling was used to cluster the obtained areas. The data used were 348 binary developmental milestone measurements, collected from birth to three years of age, from a small community sample of young children (N = 79). The model identified nine latent groups of children with similar features, ranging from no delays in all functional domains, to large delays in all domains. The performance of the Dirichlet process mixture model was validated with two simulation studies.

T cell populations in children with autism spectrum disorder and co-morbid gastrointestinal symptoms

Children with ASD are more likely to experience gastrointestinal (GI) symptoms than typically-developed children. Numerous studies have reported immune abnormalities and inflammatory profiles in the majority of individuals with ASD. Immune dysfunction is often hypothesized as a driving factor in many GI diseases and it has been suggested that it is more apparent in children with ASD that exhibit GI symptoms. In this study we sought to characterize peripheral T cell subsets in children with and without GI symptoms, compared to healthy typically-developing children. Peripheral blood mononuclear cells were isolated from participants, who were categorized into three groups: children with ASD who experience GI symptoms (n ​= ​14), children with ASD who do not experience GI symptoms (n ​= ​10) and typically-developing children who do not experience GI symptoms (n ​= ​15). In order to be included in the GI group, GI symptoms such as diarrhea, constipation, and/or pain while defecating, had to be present in the child regularly for the past 6 months; likewise, in order to be placed in the no GI groups, bowel movements could not include the above symptoms present throughout development. Cells were assessed for surface markers and intracellular cytokines to identify T cell populations. Children with ASD and GI symptoms displayed elevated TH17 populations (0.757% ​± ​0.313% compared to 0.297% ​± ​0.197), while children with ASD who did not experience GI symptoms showed increased frequency of TH2 populations (2.02% ​± ​1.08% compared to 1.01% ​± ​0.58%). Both ASD groups showed evidence of reduced gut homing regulatory T cell populations compared to typically developing children (ASDGI:1.93% ​± ​0.75% and ASDNoGI:1.85% ​± ​0.89 compared to 2.93% ​± ​1.16%). Children with ASD may have deficits in immune regulation that lead to differential inflammatory T cell subsets that could be linked to associated co-morbidities.

Affected Sib-Pair Analyses Identify Signaling Networks Associated With Social Behavioral Deficits in Autism

Autism spectrum disorders (ASDs) are characterized by deficits in three core behavioral domains: reciprocal social interactions, communication, and restricted interests and/or repetitive behaviors. Several hundreds of risk genes for autism have been identified, however, it remains a challenge to associate these genes with specific core behavioral deficits. In multiplex autism families, affected sibs often show significant differences in severity of individual core phenotypes. We hypothesize that a higher mutation burden contributes to a larger difference in the severity of specific core phenotypes between affected sibs. We tested this hypothesis on social behavioral deficits in autism. We sequenced synaptome genes (n = 1,886) in affected male sib-pairs (n = 274) in families from the Autism Genetics Research Exchange (AGRE) and identified rare (MAF ≤ 1%) and predicted functional variants. We selected affected sib-pairs with a large (≥10; n = 92 pairs) or a small (≤4; n = 108 pairs) difference in total cumulative Autism Diagnostic Interview-Revised (ADI-R) social scores (SOCT_CS). We compared burdens of unshared variants present only in sibs with severe social deficits and found a higher burden in SOCT_CS≥10 compared to SOCT_CS ≤ 4 (SOCT_CS≥10: 705.1 ± 16.2; SOCT_CS ≤ 4, 668.3 ± 9.0; p = 0.025). Unshared SOCT_CS≥10 genes only in sibs with severe social deficits are significantly enriched in the SFARI gene set. Network analyses of these genes using InWeb_IM, molecular signatures database (MSigDB), and GeNetMeta identified enrichment for phosphoinositide 3-kinase (PI3K)-AKT-mammalian target of rapamycin (mTOR) (Enrichment Score [eScore] p value = 3.36E−07; n = 8 genes) and Nerve growth factor (NGF) (eScore p value = 8.94E−07; n = 9 genes) networks. These studies support a key role for these signaling networks in social behavioral deficits and present a novel approach to associate risk genes and signaling networks with core behavioral domains in autism.

Multivariate Analysis of Plasma Metabolites in Children with Autism Spectrum Disorder and Gastrointestinal Symptoms Before and After Microbiota Transfer Therapy

Current diagnosis of autism spectrum disorder (ASD) is based on assessment of behavioral symptoms, although there is strong evidence that ASD affects multiple organ systems including the gastrointestinal (GI) tract. This study used Fisher discriminant analysis (FDA) to evaluate plasma metabolites from 18 children with ASD and chronic GI problems (ASD + GI cohort) and 20 typically developing (TD) children without GI problems (TD − GI cohort). Using three plasma metabolites that may represent three general groups of metabolic abnormalities, it was possible to distinguish the ASD + GI cohort from the TD − GI cohort with 94% sensitivity and 100% specificity after leave-one-out cross-validation. After the ASD + GI participants underwent Microbiota Transfer Therapy with significant improvement in GI and ASD-related symptoms, their metabolic profiles shifted significantly to become more similar to the TD − GI group, indicating potential utility of this combination of plasma metabolites as a biomarker for treatment efficacy. Two of the metabolites, sarcosine and inosine 5′-monophosphate, improved greatly after treatment. The third metabolite, tyramine O-sulfate, showed no change in median value, suggesting it and correlated metabolites to be a possible target for future therapies. Since it is unclear whether the observed differences are due to metabolic abnormalities associated with ASD or with GI symptoms (or contributions from both), future studies aiming to classify ASD should feature TD participants with GI symptoms and have larger sample sizes to improve confidence in the results.

Prevalence and determinants of motor stereotypies in autism spectrum disorder: A systematic review and meta-analysis

Stereotypies are frequently reported in people with autism spectrum disorder (ASD) but remain one of the less explained phenomena. We aimed to describe, through a systematic review and a meta-analysis, the prevalence of motor stereotypies in ASD and study the factors that influence this prevalence. Our literature search included MEDLINE, Scopus, and PsycINFO databases. Quality and risk of bias were assessed. Thirty-seven studies were included and the median prevalence of motor stereotypies in ASD was 51.8%, ranging from 21.9% to 97.5%. The most frequent determinants associated with a higher number of stereotypies in ASD were a younger age, lower intelligence quotient, and a greater severity of ASD. Moreover, gender did not seem to influence the prevalence of stereotypies. Meta-analytic analysis showed that lower IQ and autism diagnosis (independent of IQ) are associated with a higher prevalence of motor stereotypies (odds ratio = 2.5 and 4.7, respectively). Limitations of the reviewed literature include the use of convenience samples, with small sizes and heterogeneous inclusion criteria, and the predominance of high-functioning autism individuals.

Rapid Communication: Plasma Interleukin-35 in Children with Autism

In autism spectrum disorders (ASD) many individuals have co-morbid immune dysregulation that can lead to inflammation in the brain and periphery. The novel cytokine interleukin (IL)-35 has described anti-inflammatory properties; however, the plasma levels of IL-35 in children with ASD have never been investigated. The plasma levels of IL-35 were measured by an enzyme-linked immunosorbent assay in 30 children with ASD and 39 typically developing (TD) controls. In the current study, we found that plasma IL-35 levels were significantly decreased in children with ASD compared with TD children. Furthermore, lower IL-35 levels were associated with worse behaviors as assessed using the aberrant behavior checklist. These findings are in line with other observations of decreased regulatory cytokines such as transforming growth factor beta and IL-10 in ASD, and associations with severity of behaviors. In conclusion, regulating the expression of IL-35 may provide a new possible target for the treatment of immune issues in ASD to address an imbalance between pro- and anti-inflammatory signals that alter the behavioral phenotype.

Clustering of co-occurring conditions in autism spectrum disorder during early childhood: A retrospective analysis of medical claims data

Individuals with autism spectrum disorder (ASD) are frequently affected by co-occurring medical conditions (COCs), which vary in severity, age of onset, and pathophysiological characteristics. The presence of COCs contributes to significant heterogeneity in the clinical presentation of ASD between individuals and a better understanding of COCs may offer greater insight into the etiology of ASD in specific subgroups while also providing guidance for diagnostic and treatment protocols. This study retrospectively analyzed medical claims data from a private United States health plan between years 2000 and 2015 to investigate patterns of COC diagnoses in a cohort of 3,278 children with ASD throughout their first 5 years of enrollment compared to 279,693 children from the general population without ASD diagnoses (POP cohort). Three subgroups of children with ASD were identified by k-means clustering using these COC patterns. The first cluster was characterized by generally high rates of COC diagnosis and comprised 23.7% (n = 776) of the cohort. Diagnoses of developmental delays were dominant in the second cluster containing 26.5% (n = 870) of the cohort. Children in the third cluster, making up 49.8% (n = 1,632) of the cohort, had the lowest rates of COC diagnosis, which were slightly higher than rates observed in the POP cohort. A secondary analysis using these data found that gastrointestinal and immune disorders showed similar longitudinal patterns of prevalence, as did seizure and sleep disorders. These findings may help to better inform the development of diagnostic workup and treatment protocols for COCs in children with ASD. Autism Res 2019, 12: 1272-1285. © 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Medical conditions that co-occur with autism spectrum disorder (ASD) vary significantly from person to person. This study analyzed patterns in diagnosis of co-occurring conditions from medical claims data and observed three subtypes of children with ASD. These results may aid with screening for co-occurring conditions in children with ASD and with understanding ASD subtypes.

Immune Dysfunction and Autoimmunity as Pathological Mechanisms in Autism Spectrum Disorders

Autism spectrum disorders (ASD) are a group of heterogeneous neurological disorders that are highly variable and are clinically characterized by deficits in social interactions, communication, and stereotypical behaviors. Prevalence has risen from 1 in 10,000 in 1972 to 1 in 59 children in the United States in 2014. This rise in prevalence could be due in part to better diagnoses and awareness, however, these together cannot solely account for such a significant rise. While causative connections have not been proven in the majority of cases, many current studies focus on the combined effects of genetics and environment. Strikingly, a distinct picture of immune dysfunction has emerged and been supported by many independent studies over the past decade. Many players in the immune-ASD puzzle may be mechanistically contributing to pathogenesis of these disorders, including skewed cytokine responses, differences in total numbers and frequencies of immune cells and their subsets, neuroinflammation, and adaptive and innate immune dysfunction, as well as altered levels of immunoglobulin and the presence of autoantibodies which have been found in a substantial number of individuals with ASD. This review summarizes the latest research linking ASD, autoimmunity and immune dysfunction, and discusses evidence of a potential autoimmune component of ASD.

Homogeneous Subgroups of Young Children with Autism Improve Phenotypic Characterization in the Study to Explore Early Development

The objective of this study was to identify homogenous classes of young children with autism spectrum disorder (ASD) to improve phenotypic characterization. Children were enrolled in the Study to Explore Early Development between 2 and 5 years of age. 707 children were classified with ASD after a comprehensive evaluation with strict diagnostic algorithms. Four classes of children with ASD were identified from latent class analysis: mild language delay with cognitive rigidity, mild language and motor delay with dysregulation, general developmental delay, and significant developmental delay with repetitive motor behaviors. We conclude that a four-class phenotypic model of children with ASD best describes our data and improves phenotypic characterization of young children with ASD. Implications for screening, diagnosis, and research are discussed.

Copy number variation in 19 Italian multiplex families with autism spectrum disorder: Importance of synaptic and neurite elongation genes

Autism Spectrum Disorder (ASD) is endowed with impressive heritability estimates and high recurrence rates. Its genetic underpinnings are nonetheless very heterogeneous, with common, and rare contributing variants located in hundreds of different loci, each characterized by variable levels of penetrance. Multiplex families from single ethnic groups represent a useful means to reduce heterogeneity and enhance genetic load. We screened 19 Italian ASD multiplex families (3 triplets and 16 duplets, total N = 41 ASD subjects), using array-CGH (Agilent 180 K). Causal or ASD-relevant CNVs were detected in 36.6% (15/41) of ASD probands, corresponding to 36.8% (7/19) multiplex families with at least one affected sibling genetically positive. However, only in less than half (3/7) of positive families, affected siblings share the same causal or ASD-relevant CNV. Even in these three families, additional potentially relevant CNVs not shared by affected sib pairs were also detected. These results provide further evidence of genetic heterogeneity in ASD even within multiplex families belonging to a single ethnic group. Differences in CNV burden may likely contribute to the substantial clinical heterogeneity observed between affected siblings. In addition, Gene Ontology enrichment analysis indicates that most potentially causal or relevant ASD genes detected in our cohort belong to nervous system-specific categories, especially involved in neurite elongation and synaptic structure/function. These findings point toward the existence of genomic instability in these families, whose underlying genetic and epigenetic mechanisms deserve further scrutiny.

Phenotyping, Etiological Factors, and Biomarkers: Toward Precision Medicine in Autism Spectrum Disorders

Despite the progress made in understanding the biology of autism spectrum disorder (ASD), effective biological interventions for the core symptoms remain elusive. Because of the etiological heterogeneity of ASD, identification of a "one-size-fits-all" treatment approach will likely continue to be challenging. A meeting was convened at the University of Missouri and the Thompson Center to discuss strategies for stratifying patients with ASD for the purpose of moving toward precision medicine. The "white paper" presented here articulates the challenges involved and provides suggestions for future solutions.

Beyond Lumping and Splitting: A Review of Computational Approaches for Stratifying Psychiatric Disorders

Heterogeneity is a key feature of all psychiatric disorders that manifests on many levels, including symptoms, disease course, and biological underpinnings. These form a substantial barrier to understanding disease mechanisms and developing effective, personalized treatments. In response, many studies have aimed to stratify psychiatric disorders, aiming to find more consistent subgroups on the basis of many types of data. Such approaches have received renewed interest after recent research initiatives, such as the National Institute of Mental Health Research Domain Criteria and the European Roadmap for Mental Health Research, both of which emphasize finding stratifications that are based on biological systems and that cut across current classifications. We first introduce the basic concepts for stratifying psychiatric disorders and then provide a methodologically oriented and critical review of the existing literature. This shows that the predominant clustering approach that aims to subdivide clinical populations into more coherent subgroups has made a useful contribution but is heavily dependent on the type of data used; it has produced many different ways to subgroup the disorders we review, but for most disorders it has not converged on a consistent set of subgroups. We highlight problems with current approaches that are not widely recognized and discuss the importance of validation to ensure that the derived subgroups index clinically relevant variation. Finally, we review emerging techniques-such as those that estimate normative models for mappings between biology and behavior-that provide new ways to parse the heterogeneity underlying psychiatric disorders and evaluate all methods to meeting the objectives of such as the National Institute of Mental Health Research Domain Criteria and Roadmap for Mental Health Research.

Theory of mind predicts severity level in autism

We investigated whether theory of mind skills can indicate autism spectrum disorder severity. In all, 62 children with autism spectrum disorder completed a developmentally sensitive theory of mind battery. We used intelligence quotient, Diagnostic and Statistical Manual of Mental Disorders (4th ed.) diagnosis and level of support needed as indicators of severity level. Using hierarchical cluster analysis, we found three distinct clusters of theory of mind ability: early-developing theory of mind (Cluster 1), false-belief reasoning (Cluster 2) and sophisticated theory of mind understanding (Cluster 3). The clusters corresponded to severe, moderate and mild autism spectrum disorder. As an indicator of level of support needed, cluster grouping predicted the type of school children attended. All Cluster 1 children attended autism-specific schools; Cluster 2 was divided between autism-specific and special needs schools and nearly all Cluster 3 children attended general special needs and mainstream schools. Assessing theory of mind skills can reliably discriminate severity levels within autism spectrum disorder.

Can biological components predict short-term evolution in Autism Spectrum Disorders? A proof-of-concept study

Background

The clinical and pathogenetic heterogeneity of Autism Spectrum Disorders (ASD) limits our ability to predict its short- and long-term evolution. Aim of this naturalistic study was to observe the clinical evolution of very young children with ASD for 12 months after first diagnosis, in order to identify those children who might develop a more positive trajectory and understand how a wide range of biological, clinical and familial factors can influence prognosis.

Methods

Ninety-two children were characterized in terms of family history, prenatal and perinatal variables, and clinical conditions. The sample was divided into four subgroups based on the association of 22 biological, clinical and family history variables. Developmental Quotient (DQ), determined using the Psychoeducational Profile Revised (PEP-R), and symptoms severity, measured by means of the Autism Diagnostic Observation Schedule (ADOS), were evaluated at baseline (T0) and after one year (T1), while receiving treatment as usual. Changes in DQ and ADOS between baseline and follow-up and differences in the short-term evolution of the four subgroups were analyzed.

Results

At T1, 55.4 % of the children demonstrated some gains either of autistic symptomatology or of developmental skills. Mean ADOS score was 13.63 ± 3.67 at T0 and 10.85 ± 4.10 at T1 and mean DQ was 0.64 ± 0.14 at T0 and 0.66 ± 0.15 at T1. At follow-up, 33.7 % of the children showed an improvement in DQ and 37 % presented a less severe symptomatology, measured by means of ADOS. Overall, 15.2 % of the sample displayed major improvements both on developmental quotient and ADOS severity score; these children presented less EEG abnormalities and familial psychiatric disorders. The four subgroups, based on biological, clinical and familial variables, showed differing trends in terms of evolution.

Conclusions

Categorizing very young children with ASD in terms of biological, clinical and familial variables can be instrumental in predicting short-term evolution. This exploratory study highlights the importance of a precise characterization and thorough analysis of interactions among biological and clinical variables, in order to predict the developmental evolution in children with ASD.

Brain structure and function correlates of cognitive subtypes in schizophrenia

Stable neuropsychological deficits may provide a reliable basis for identifying etiological subtypes of schizophrenia. The aim of this study was to identify clusters of individuals with schizophrenia based on dimensions of neuropsychological performance, and to characterize their neural correlates. We acquired neuropsychological data as well as structural and functional magnetic resonance imaging from 129 patients with schizophrenia and 165 healthy controls. We derived eight cognitive dimensions and subsequently applied a cluster analysis to identify possible schizophrenia subtypes. Analyses suggested the following four cognitive clusters of schizophrenia: (1) Diminished Verbal Fluency, (2) Diminished Verbal Memory and Poor Motor Control, (3) Diminished Face Memory and Slowed Processing, and (4) Diminished Intellectual Function. The clusters were characterized by a specific pattern of structural brain changes in areas such as Wernicke's area, lingual gyrus and occipital face area, and hippocampus as well as differences in working memory-elicited neural activity in several fronto-parietal brain regions. Separable measures of cognitive function appear to provide a method for deriving cognitive subtypes meaningfully related to brain structure and function. Because the present study identified brain-based neural correlates of the cognitive clusters, the proposed groups of individuals with schizophrenia have some external validity.

Slow intestinal transit contributes to elevate urinary p-cresol level in Italian autistic children

The uremic toxin p-cresol (4-methylphenol) is either of environmental origin or can be synthetized from tyrosine by cresol-producing bacteria present in the gut lumen. Elevated p-cresol amounts have been previously found in the urines of Italian and French autism spectrum disorder (ASD) children up until 8 years of age, and may be associated with autism severity or with the intensity of abnormal behaviors. This study aims to investigate the mechanism producing elevated urinary p-cresol in ASD. Urinary p-cresol levels were thus measured by High Performance Liquid Chromatography in a sample of 53 Italian ASD children assessed for (a) presence of Clostridium spp. strains in the gut by means of an in vitro fecal stool test and of Clostridium difficile-derived toxin A/B in the feces, (b) intestinal permeability using the lactulose/mannitol (LA/MA) test, (c) frequent use of antibiotics due to recurrent infections during the first 2 years of postnatal life, and (d) stool habits with the Bristol Stool Form Scale. Chronic constipation was the only variable significantly associated with total urinary p-cresol concentration (P < 0.05). No association was found with presence of Clostridium spp. in the gut flora (P = 0.92), augmented intestinal permeability (P = 0.18), or frequent use of antibiotics in early infancy (P = 0.47). No ASD child was found to carry C. difficile in the gut or to release toxin A/B in the feces. In conclusion, urinary p-cresol levels are elevated in young ASD children with increased intestinal transit time and chronic constipation. Autism Res 2016, 9: 752-759. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Increased production of IL-17 in children with autism spectrum disorders and co-morbid asthma

Inflammation and asthma have both been reported in some children with autism spectrum disorder (ASD). To further assess this connection, peripheral immune cells isolated from young children with ASD and typically developing (TD) controls and the production of cytokines IL-17, -13, and -4 assessed following ex vivo mitogen stimulation. Notably, IL-17 production was significantly higher following stimulation in ASD children compared to controls. Moreover, IL-17 was increased in ASD children with co-morbid asthma compared to controls with the same condition. In conclusion, children with ASD exhibited a differential response to T cell stimulation with elevated IL-17 production compared to controls.

Pharmacogenomic medicine in autism: challenges and opportunities

Autism spectrum disorder (ASD) affects 1 in 68 children in the US and is distinguished by core deficits in social interactions. Developing pharmacologic treatments for ASD is complicated by clinical and genetic heterogeneity. Although pharmacological treatments have not been shown to be effective in treating the core symptoms of ASD (i.e., social deficits), there is evidence that the burden of emotional and behavioral problems can be reduced with pharmacotherapy. Numerous randomized clinical trials of treatments for the core ASD deficits have been conducted; however, most have provided inconclusive results due to the substantial variation in treatment response. Variation also exists in the considerable metabolic side effects of many of the current treatments. Some of this variation may be explained by differences in the underlying genetic pathways. Exploiting the link between genetic heterogeneity and clinical variation associated with behavioral problems may provide an opportunity for targeted treatment of ASD. In this review, we summarize the recent findings from pharmacogenomics studies of ASD and suggest further how understanding how genetic liability modifies the effect of drugs may present an opportunity to address the challenges of personalized medicine in autism.

The GLO1 C332 (Ala111) allele confers autism vulnerability: family-based genetic association and functional correlates

Glyoxalase I (GLO1) is a homodimeric Zn(2+)-dependent isomerase involved in the detoxification of methylglyoxal and in limiting the formation of advanced glycation end-products (AGE). We previously found the rs4746 A332 (Glu111) allele of the GLO1 gene, which encodes for glyoxalase I, associated with "unaffected sibling" status in families with one or more children affected by Autism Spectrum Disorder (ASD). To identify and characterize this protective allele, we sequenced GLO1 exons and exon-intron junctions, detecting two additional SNPs (rs1049346, rs1130534) in linkage disequilibrium with rs4746. A family-based association study involving 385 simplex and 20 multiplex Italian families yielded a significant association with autism driven only by the rs4746 C332 (Ala111) allele itself (P < 0.05 and P < 0.001 under additive and dominant/recessive models, respectively). Glyoxalase enzymatic activity was significantly reduced both in leukocytes and in post-mortem temporocortical tissue (N = 38 and 13, respectively) of typically developing C332 allele carriers (P < 0.05 and <0.01), with no difference in Glo1 protein levels. Conversely, AGE amounts were significantly higher in the same C332 post-mortem brains (P = 0.001), with a strong negative correlation between glyoxalase activity and AGE levels (τ = -0.588, P < 0.01). Instead, 19 autistic brains show a dysregulation of the glyoxalase-AGE axis (τ = -0.209, P = 0.260), with significant blunting of glyoxalase activity and AGE amounts compared to controls (P < 0.05), and loss of rs4746 genotype effects. In summary, the GLO1 C332 (Ala111) allele confers autism vulnerability by reducing brain glyoxalase activity and enhancing AGE formation, but years after an autism diagnosis the glyoxalase-AGE axis appears profoundly disrupted, with loss of C332 allelic effects.

A genotype-first approach to defining the subtypes of a complex disease

Medical genetics typically entails the detailed characterization of a patient's phenotypes followed by genotyping to discover the responsible gene or mutation. Here, we propose that the systematic discovery of genetic variants associated with complex diseases such as autism are progressing to a point where a reverse strategy may be fruitful in assigning the pathogenic effects of many different genes and in determining whether particular genotypes manifest as clinically recognizable phenotypes. This "genotype-first" approach for complex disease necessitates the development of large, highly integrated networks of researchers, clinicians, and patient families, with the promise of improved therapies for subsets of patients.

Anti-brain antibodies are associated with more severe cognitive and behavioral profiles in Italian children with Autism Spectrum Disorder

Circulating 45 and 62kDa antibodies targeting the cerebellum were previously associated with Autism Spectrum Disorder (ASD), lower adaptive/cognitive function and aberrant behaviors. Moreover, 37, 39 and 73kDa maternal antibodies (mAb) targeting the fetal brain were previously correlated with broad autism spectrum, irritability, abnormal brain enlargement and impaired expressive language. The present study aims towards clinically characterizing individuals with brain-targeted IgG and/or exposed to maternal antibrain antibodies in a large sample of Italian autistic children (N=355), their unaffected siblings (N=142) and mothers (N=333). The presence of patient- and mother-produced anti-brain antibodies does not confer increased risk of autism within the same sibship. However, the 45 and 62kDa antibodies are correlated with autism severity: the 45kDa Ab is associated with cognitive impairment and lower scores at the Vineland Adaptive Behavior Scales, the 62kDa Ab with motor stereotypies, while both correlate with larger head circumference (all P<0.05). On the other hand, maternal 37, 39 and 73kDa antibrain antibodies, either alone or in combination, are correlated with impaired verbal and non-verbal language development, neurodevelopmental delay and sleep/wake cycle disturbances in their autistic children (P<0.05). Presence of the 62kDa autoAb in the child is significantly associated with presence of the 39 and/or 73kDa antibodies in his/her mother. Our results confirm and extend previous observations in an ethnically distinct sample, providing further evidence of a pathomorphic role for anti-brain antibodies in autism while demonstrating their familial clustering.

Biomarkers in autism spectrum disorder: the old and the new

RATIONALE

Autism spectrum disorder (ASD) is a complex heterogeneous neurodevelopmental disorder with onset during early childhood and typically a life-long course. The majority of ASD cases stems from complex, 'multiple-hit', oligogenic/polygenic underpinnings involving several loci and possibly gene-environment interactions. These multiple layers of complexity spur interest into the identification of biomarkers able to define biologically homogeneous subgroups, predict autism risk prior to the onset of behavioural abnormalities, aid early diagnoses, predict the developmental trajectory of ASD children, predict response to treatment and identify children at risk for severe adverse reactions to psychoactive drugs.

OBJECTIVES

The present paper reviews (a) similarities and differences between the concepts of 'biomarker' and 'endophenotype', (b) established biomarkers and endophenotypes in autism research (biochemical, morphological, hormonal, immunological, neurophysiological and neuroanatomical, neuropsychological, behavioural), (c) -omics approaches towards the discovery of novel biomarker panels for ASD, (d) bioresource infrastructures and (e) data management for biomarker research in autism.

RESULTS

Known biomarkers, such as abnormal blood levels of serotonin, oxytocin, melatonin, immune cytokines and lymphocyte subtypes, multiple neuropsychological, electrophysiological and brain imaging parameters, will eventually merge with novel biomarkers identified using unbiased genomic, epigenomic, transcriptomic, proteomic and metabolomic methods, to generate multimarker panels. Bioresource infrastructures, data management and data analysis using artificial intelligence networks will be instrumental in supporting efforts to identify these biomarker panels.

CONCLUSIONS

Biomarker research has great heuristic potential in targeting autism diagnosis and treatment.

Recommendations for early diagnosis and intervention in autism spectrum disorders: an Italian-Israeli consensus conference

On April 2013 experts in the field of autism from Italy and Israel convened in Jerusalem to discuss and finalize clinical recommendations for early diagnosis and intervention in Autism Spectrum Disorders (ASDs). In this paper, we summarize the results of this Italian-Israeli consensus conference. ASDs constitute a class of severe and heterogeneous neurodevelopmental conditions caused by atypical brain development beginning during early prenatal life, reflecting many genetic, neurobiological and environmental influences. The first clinical signs of ASDs begin to be evident in children between 12 and 18 months of age, often after a period of relatively typical postnatal development. Recent longitudinal studies reveal substantial diversity in developmental trajectories through childhood and adolescence. Some intervention approaches have been demonstrated to be effective in improving core symptoms of ASDs, even if the heterogeneity and developmental nature of the disorder make it implausible that only one specific treatment will be best for all children with ASDs. More randomized control trials (RCTs) on early intervention are needed to identify the most effective strategies and provide the most efficient allocation of resources during the critical early intervention time period. Future research should focus on linking biological phenotypes with specific genotypes, thus establishing a foundation for the development of diagnostic screening tools and individualization of treatments.

Comorbidity clusters in autism spectrum disorders: an electronic health record time-series analysis

OBJECTIVE

The distinct trajectories of patients with autism spectrum disorders (ASDs) have not been extensively studied, particularly regarding clinical manifestations beyond the neurobehavioral criteria from the Diagnostic and Statistical Manual of Mental Disorders. The objective of this study was to investigate the patterns of co-occurrence of medical comorbidities in ASDs.

METHODS

International Classification of Diseases, Ninth Revision codes from patients aged at least 15 years and a diagnosis of ASD were obtained from electronic medical records. These codes were aggregated by using phenotype-wide association studies categories and processed into 1350-dimensional vectors describing the counts of the most common categories in 6-month blocks between the ages of 0 to 15. Hierarchical clustering was used to identify subgroups with distinct courses.

RESULTS

Four subgroups were identified. The first was characterized by seizures (n = 120, subgroup prevalence 77.5%). The second (n = 197) was characterized by multisystem disorders including gastrointestinal disorders (prevalence 24.3%) and auditory disorders and infections (prevalence 87.8%), and the third was characterized by psychiatric disorders (n = 212, prevalence 33.0%). The last group (n = 4316) could not be further resolved. The prevalence of psychiatric disorders was uncorrelated with seizure activity (P = .17), but a significant correlation existed between gastrointestinal disorders and seizures (P < .001). The correlation results were replicated by using a second sample of 496 individuals from a different geographic region.

CONCLUSIONS

Three distinct patterns of medical trajectories were identified by unsupervised clustering of electronic health record diagnoses. These may point to distinct etiologies with different genetic and environmental contributions. Additional clinical and molecular characterizations will be required to further delineate these subgroups.

The neurobiology of autism spectrum disorders

Data is progressively and robustly accumulating regarding the biological basis of autism. Autism spectrum disorders (ASD) are currently considered a group of neurodevelopmental disorders with onset very early in life and a complex, heterogeneous, multifactorial aetiology. A comprehensive search of the last five years of the Medline database was conducted in order to summarize recent evidence on the neurobiological bases of autism. The main findings on genetic influence, neuropathology, neurostructure and brain networks are summarized. In addition, findings from peripheral samples of subjects with autism and animal models, which show immune, oxidative, mitochondrial dysregulations, are reported. Then, other biomarkers from very different systems associated with autism are reported. Finally, an attempt is made to try and integrate the available evidence, which points to a oligogenetic, multifactorial aetiology that converges in an aberrant micro-organization of the cortex, with abnormal functioning of the synapses and abnormalities in very general physiological pathways (such as inflammatory, immune and redox systems).

Antibodies against food antigens in patients with autistic spectrum disorders

PURPOSE

Immune system of some autistic patients could be abnormally triggered by gluten/casein assumption. The prevalence of antibodies to gliadin and milk proteins in autistic children with paired/impaired intestinal permeability and under dietary regimen either regular or restricted is reported.

METHODS

162 ASDs and 44 healthy children were investigated for intestinal permeability, tissue-transglutaminase (tTG), anti-endomysium antibodies (EMA)-IgA, and total mucosal IgA to exclude celiac disease; HLA-DQ2/-DQ8 haplotypes; total systemic antibodies (IgA, IgG, and IgE); specific systemic antibodies: α-gliadin (AGA-IgA and IgG), deamidated-gliadin-peptide (DGP-IgA and IgG), total specific gliadin IgG (all fractions: α, β, γ, and ω), β-lactoglobulin IgG, α-lactalbumin IgG, casein IgG; and milk IgE, casein IgE, gluten IgE,-lactoglobulin IgE, and α-lactalbumin IgE.

RESULTS

AGA-IgG and DPG-IgG titers resulted to be higher in ASDs compared to controls and are only partially influenced by diet regimen. Casein IgG titers resulted to be more frequently and significantly higher in ASDs than in controls. Intestinal permeability was increased in 25.6% of ASDs compared to 2.3% of healthy children. Systemic antibodies production was not influenced by paired/impaired intestinal permeability.

CONCLUSIONS

Immune system of a subgroup of ASDs is triggered by gluten and casein; this could be related either to AGA, DPG, and Casein IgG elevated production or to impaired intestinal barrier function.

Immune dysregulation in autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heterogeneous disorder diagnosed based on the presence and severity of core abnormalities in social communication and repetitive behavior, yet several studies converge on immune dysregulation as a feature of ASD. Widespread alterations in immune molecules and responses are seen in the brains and periphery of ASD individuals, and early life immune disruptions are associated with ASD. This chapter discusses immune-related environmental and genetic risk factors for ASD, emphasizing population-wide studies and animal research that reveal potential mechanistic pathways involved in the development of ASD-related symptoms. It further reviews immunologic pathologies seen in ASD individuals and how such abnormalities can impact neurodevelopment and behavior. Finally, it evaluates emerging evidence for an immune contribution to the pathogenesis of ASD and a potential role for immunomodulatory effects in current treatments for ASD.