Del espectro autista a la constelación autista / From autism spectrum to autism constellation

La investigación sobre el autismo, y sobre los trastornos mentales en general, ha sido poco fructífera durante las últimas décadas, como se desprende de los escasos resultados obtenidos en comparación con los avances en otras enfermedades. Preocupa que, tras más de medio siglo de investigación basada en el Diagnostic and Statistical Manual of Mental Disorders (DSM), no se hayan encontrado marcadores biológicos que acrediten la validez de los trastornos mentales que lo configuran. Las críticas al DSM, todas ellas aplicables al autismo, se han centrado principalmente en la conceptualización categórica, en la falsa comorbilidad y en el carácter politético de los criterios diagnósticos. La falta de validez del modelo del DSM insta a un cambio en los diseños de investigación, con el fin de superar el bloqueo derivado de un paradigma que ha dejado de ser productivo. En el terreno de la práctica clínica resulta, incluso más apremiante, un cambio de mentalidad que permita: incorporar la heterogeneidad de endofenotipos que desbordan la clasificación del DSM, adoptar una perspectiva dimensional de los problemas mentales y desarrollar una interpretación alternativa de la comorbilidad Con referencia a la investigación, se proponen diseños basados en criterios de investigación por dominios (Research Domain Criteria) y en análisis multifactoriales con muestras muy grandes (big data). Por lo que respecta a práctica clínica se sugiere un enfoque dimensional basado en las especificidades de cada persona con autismo, lo cual desborda el patrón clínico del espectro.

Research on autism and mental disorders has been unsuccessful over the past few decades, as can be inferred from the poor results related to advances in other diseases. It is concerning that, after more than a half century of research based on the Diagnostic and Statistical Manual of Mental Disorders (DSM), no biological markers have been found to prove the validity of the DSM mental disorders. Criticisms to DSM have been focused mainly on the categorical conceptualization, false comorbidity and the polythetic nature of diagnostic criteria. The lack of validity of the DSM model requests for a change in research designs, in order to overcome the problems derived from a paradigm that has stopped to be productive. In the field of clinical practice, it is even more pressing a change of mindset in order to incorporate the heterogeneity of endophenotypes that overflows the classification of the DSM, to adopt a dimensional perspective of mental problems and to develop an alternative interpretation for comorbidity. Related to research are suggested designs based on Domain Research Criteria and a multifactorial analysis with very large samples (big data). For clinical practice it is suggested a dimensional approach based on the specificities of each person with autism.

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).

Autism: One or many spectrums?

Our conceptualisation of autism spectrum disorder has changed over time, with recent classifications reflecting a heterogeneous clinical presentation now regularly encountered in routine general paediatric practice. As the prevalence of autism and associated demands for services have increased so has research into understanding the cause and trials aimed at providing best care and intervention. However, the heterogeneity of autism has meant that no single aetiology can account for all differences in presentation, and not all children benefit from broad-based interventions. Now is the time to rethink how best to understand individual differences in order to focus research efforts and take steps towards more sophisticated strategies that go beyond the behaviours we look for when making an autism diagnosis. We suggest adopting a dimensional approach to autism assessment, with the consideration of eight spectrums of abilities, ways of thinking and behaviour. This eight-spectrum approach will assist clinicians to consider each individual's strengths and needs and personalise interventions and support accordingly. Profiling individual skills across these dimensions may also provide researchers with a greater capacity to link causal pathways with specific phenotypes, which is needed to develop precision medicine for autism.

The social responsiveness scale in relation to DSM IV and DSM5 ASD in Korean children.

The Social Responsiveness Scale (SRS) is an autism rating scales in widespread use, with over 20 official foreign language translations. It has proven highly feasible for quantitative ascertainment of autistic social impairment in public health settings, however, little is known about the validity of the reinforcement in Asia populations or in references to DSM5. The current study aims to evaluate psychometric properties and cross-cultural aspects of the SRS-Korean version (K-SRS).The study subjects were ascertained from three samples: a general sample from 3 regular education elementary schools (n=790), a clinical sample (n=154) of 6-12-year-olds from four psychiatric clinics, and an epidemiological sample of children with ASD, diagnosed using both DSM IV PDD, DSM5 ASD and SCD criteria (n=151). Their parents completed the K-SRS and the Autism Spectrum Screening Questionnaire(ASSQ). Descriptive statistics, correlation analyses and principal components analysis (PCA) were performed on the total population. Mean total scores on the K-SRS differed significantly between the three samples. ASSQ scores were significantly correlated with the K-SRS T-scores. PCA suggested a one-factor solution for the total population.Our results indicate that the K-SRS exhibits adequate reliability and validity for measuring ASD symptoms in Korean children with DSM IV PDD and DSM5 ASD. Our findings further suggest that it is difficult to distinguish SCD from other child psychiatric conditions using the K-SRS.This is the first study to examine the relationship between the SRS subscales and DSM5-based clinical diagnoses. This study provides cross-cultural confirmation of the factor structure for ASD symptoms and traits measured by the SRS. Autism Res 2016, 9: 970-980. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

The promise of multi-omics and clinical data integration to identify and target personalized healthcare approaches in autism spectrum disorders.

Complex diseases are caused by a combination of genetic and environmental factors, creating a difficult challenge for diagnosis and defining subtypes. This review article describes how distinct disease subtypes can be identified through integration and analysis of clinical and multi-omics data. A broad shift toward molecular subtyping of disease using genetic and omics data has yielded successful results in cancer and other complex diseases. To determine molecular subtypes, patients are first classified by applying clustering methods to different types of omics data, then these results are integrated with clinical data to characterize distinct disease subtypes. An example of this molecular-data-first approach is in research on Autism Spectrum Disorder (ASD), a spectrum of social communication disorders marked by tremendous etiological and phenotypic heterogeneity. In the case of ASD, omics data such as exome sequences and gene and protein expression data are combined with clinical data such as psychometric testing and imaging to enable subtype identification. Novel ASD subtypes have been proposed, such as CHD8, using this molecular subtyping approach. Broader use of molecular subtyping in complex disease research is impeded by data heterogeneity, diversity of standards, and ineffective analysis tools. The future of molecular subtyping for ASD and other complex diseases calls for an integrated resource to identify disease mechanisms, classify new patients, and inform effective treatment options. This in turn will empower and accelerate precision medicine and personalized healthcare.