Brain imaging research in autism spectrum disorders

Lainhart, Janet E.

doi:10.1097/yco.0000000000000130

Cited by 40 publications

(22 citation statements)

References 70 publications

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“…Lenroot and Yeung (2013) reported that the majority of individuals diagnosed with ASD had typical brain and head size. However, in other studies, approximately 10 to 24 % of individuals diagnosed with ASD had persisting macrocephaly (Gillberg and de Souza 2002;Lainhart 2015;Nebel et al 2015;Sacco et al 2015;Tammimies et al 2015). In addition, a number of studies have reported that 3 to 15 % of individuals with ASD had persisting microcephaly (Gillberg and de Souza 2002;Nebel et al 2015;Roullet et al 2013;Stevens et al 2013).…”

Section: Does Asd Have Neurobiological Validity?mentioning

confidence: 98%

“…The researchers found that underconnectivity occurred in syndromic ASD with TSC, and in idiopathic ASD, but not in TSC alone. Similarly, Lainhart (2015) claimed that syndromic ASD with TSC and idiopathic ASD both expressed the ASD-specific reduced long-range connectivity with increased short-range connectivity.…”

Section: Does Asd Have Neurobiological Validity?mentioning

confidence: 99%

“…Lainhart (2015) reviewed research and noted that only Ba very small subgroup of ASD children^(p. 79) had larger brain volumes. In a meta-analysis, Sacco et al (2015) found only 5.7 % of individuals with ASD had macrocephaly and just 9.1 % had brain overgrowth.…”

Section: Does Asd Have Neurobiological Validity?mentioning

confidence: 99%

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ASD Validity

Waterhouse

London

Gillberg

2016

Rev J Autism Dev Disord

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ASD research is at an important crossroads. The ASD diagnosis is important for assigning a child to early behavioral intervention and explaining a child's condition. But ASD research has not provided a diagnosis-specific medical treatment, or a consistent early predictor, or a unified life course. If the ASD diagnosis also lacks biological and construct validity, a shift away from studying ASD-defined samples would be warranted. Consequently, this paper reviews recent findings for the neurobiological validity of ASD, the construct validity of ASD diagnostic criteria, and the construct validity of ASD spectrum features. The findings reviewed indicate that the ASD diagnosis lacks biological and construct validity. The paper concludes with proposals for research going forward.Keywords DSM-5 . ASD . Autism . Diagnosis . Validity . Comorbidity . HeterogeneityThe goal of the DSM-3 nosology (American Psychiatric Association 1980) was to create reliable and standard categorical psychiatric diagnoses (Robins and Guze 1970). However, in the past 30 years, clinical, genetics, and neuroscience findings have revealed that the DSM diagnoses are not biologically valid. The National Institutes of Mental Health (NIMH) responded by proposing the Research Domain Criteria (RDoC) framework for a brain-based transdiagnostic psychiatric symptom nosology (Cuthbert and Insel 2013;Insel et al. 2010;Lilienfeld and Treadway 2016). Peterson (2015) and Weinberger et al. (2015) argued that the RDoC could not replace the DSM-5 psychiatric nosology (American Psychiatric Association 2013) or the parallel International Classification of Diseases (ICD) psychiatric nosology (World Health Organization 2012). But BFor the foreseeable future, RDoC is not envisioned as a system of psychiatric classification in its own right. Instead, in the near term, RDoC and DSM-ICD are expected to coexist. Nevertheless, RDoC is intended to provide scaffolding for a large-scale research program that will ultimately yield an alternative to DSM-ICD^ (Lilienfeld and Treadway 2016, p. 445).RDoC advocates accept that DSM-5/ICD psychiatric categories remain necessary in clinical practice, but argue that researchers should shift to RDoC study designs immediately. They assert that studying psychiatric categories lacking biological validity blocks the discovery of brain bases for psychopathology and thus cannot lead to effective medical treatments for specific psychiatric symptoms (Cuthbert and Insel 2013;Insel et al. 2010;Lilienfeld and Treadway 2016;Yee et al. 2015). Against this RDoC imperative for biological validity, Weinberger et al. (2015) countered that current DSM-5 psychiatric behavioral diagnoses were valid when they yielded effective medical treatment, clear prognosis, and a life course specific to a diagnosis.Autism spectrum disorder (ASD) research has been productive (Dawson 2016;de la Torre-Ubieta et al. 2016;Szatmari et al. 2016), but no ASD research findings have met the validity criteria of Weinberger et al. (2015). DSM-5 ASD research has found no s...

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Section: Does Asd Have Neurobiological Validity?mentioning

confidence: 98%

Section: Does Asd Have Neurobiological Validity?mentioning

confidence: 99%

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ASD Validity

Waterhouse

London

Gillberg

2016

Rev J Autism Dev Disord

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“…Magnetic resonance imaging (MRI) studies of brain development in ASD have shown widespread changes in grey and white matter development (Stigler et al, 2011), associated with changes in brain function and connectivity (Amaral et al, 2008, Anagnostou and Taylor, 2011). Recent reviews of the literature have suggested that ASD is associated with subtle increases in brain volume in the first years of life, followed by a period of arrested growth or a decline in volume (Ecker, 2016, Lainhart, 2015, Raznahan et al, 2013). Most of the reviewed studies investigating brain development in ASD focused on cortical volume.…”

Section: Introductionmentioning

confidence: 99%

Development of cortical thickness and surface area in autism spectrum disorder

Mensen

Wierenga

Dijk

et al. 2017

NeuroImage: Clinical

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Autism spectrum disorder (ASD) is a neurodevelopmental disorder often associated with changes in cortical volume. The constituents of cortical volume – cortical thickness and surface area – have separable developmental trajectories and are related to different neurobiological processes. However, little is known about the developmental trajectories of cortical thickness and surface area in ASD. In this magnetic resonance imaging (MRI) study, we used an accelerated longitudinal design to investigate the cortical development in 90 individuals with ASD and 90 typically developing controls, aged 9 to 20 years. We quantified cortical measures using the FreeSurfer software package, and then used linear mixed model analyses to estimate the developmental trajectories for each cortical measure. Our primary finding was that the development of surface area follows a linear trajectory in ASD that differs from typically developing controls. In typical development, we found a decline in cortical surface area between the ages of 9 and 20 that was absent in ASD. We found this pattern in all regions where developmental trajectories for surface area differed between groups. When we applied a more stringent correction that takes the interdependency of measures into account, this effect on cortical surface area retained significance for left banks of superior temporal sulcus, postcentral area, and right supramarginal area. These areas have previously been implicated in ASD and are involved in the interpretation and processing of audiovisual social stimuli and distinction between self and others. Although some differences in cortical volume and thickness were found, none survived the more stringent correction for multiple testing. This study underscores the importance of distinguishing between cortical surface area and thickness in investigating cortical development, and suggests the development of cortical surface area is of importance to ASD.

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“…Also the rate of brain growth in the first 2 years of life may contribute to ASD. Although abnormally enlarged brain volumes and increased rates of brain growth during early childhood are observed only in a minority of ASD children, nevertheless there is evidence of abnormalities in posterior lobes and posterior brain networks during the first 2 years of life in ASD (Lainhart, 2015 ).…”

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confidence: 99%