Autism Spectrum Disorder: Sniffing Out a New Biomarker

Pelphrey, Kevin A.

doi:10.1016/j.cub.2015.06.050

Cited by 8 publications

(6 citation statements)

References 12 publications

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“…For this reason, this network seems to be stable across ages. In literature, it has been reported that an early diagnosis could lead to better outcomes after the intervention (Dawson et al ., ; Small & Pelphrey, ). The main problem of getting an early diagnosis is that so far the most used assessment tools require abilities already structured in children, as the language.…”

Section: Discussionmentioning

confidence: 99%

“…Because of that, recent research is focusing on investigating the presence of biological markers for the ASD conditions, which may overstep the limits imposed by diagnostic tests. Being a growing research interest the detection of these biomarkers for ASD (Small & Pelphrey, ; Wang et al ., ), continuing our research line in the future it would be very necessary to investigate the presence of ASN already in toddlers. If the ASN would be confirmed also in toddlers, it may be considered as an important indicator for the areas of interest.…”

Section: Discussionmentioning

confidence: 99%

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Three shades of grey: detecting brain abnormalities in children with autism using source‐, voxel‐ and surface‐based morphometry

Pappaianni

Šiugždaitė

Vettori

et al. 2017

Eur J of Neuroscience

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Autistic spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interactions, communication and stereotyped behaviour. Recent evidence from neuroimaging supports the hypothesis that ASD deficits in adults may be related to abnormalities in a specific frontal-temporal network [Autism-specific Structural Network (ASN)]. To see whether these results extend to younger children and to better characterize these abnormalities, we applied three morphometric methods on brain grey matter (GM) of children with and without ASD. We selected 39 sMRI images of male children with ASD and 42 typically developing (TD) from the Autism Brain Imaging Data Exchange database. We used source-based morphometry (SoBM), a whole-brain multivariate approach to identify GM networks, voxel-based morphometry (VBM), a voxel-wise comparison of the local GM concentration and surface-based morphometry (SuBM) for the estimation of the cortical parameters. SoBM showed a bilateral frontal-parietal-temporal network different between groups, including the inferior-middle temporal gyrus, the inferior parietal lobule and the postcentral gyrus; VBM returned differences only in the right temporal lobe; SuBM returned a thinning in the right inferior temporal lobe thinner in ASD, a higher gyrification in the right superior parietal lobule in TD and in the middle frontal gyrus in ASD. For the first time, we investigated the brain abnormalities in children with ASD using three morphometric techniques. The results were relatively consistent between methods, stressing the role of an Autism-specific Structural Network in ASD individuals. We also make methodological speculations on the relevance of using multivariate and whole-brain neuroimaging analysis to capture ASD complexity.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Three shades of grey: detecting brain abnormalities in children with autism using source‐, voxel‐ and surface‐based morphometry

Pappaianni

Šiugždaitė

Vettori

et al. 2017

Eur J of Neuroscience

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“…ReebSutherland and Fox (2015), however, suggested that atypical eyeblink conditioning was a possible single ASD biomarker, and Jeste et al (2015) proposed that EEG patterns might be a possible biomarker for ASD. Small and Pelphrey (2015) proposed, BInnate olfactory behaviors may provide a link between early emerging sensory motor behaviors and the social deficits that characterize ASD( p. R675). Rozenkrantz et al (2015) reported that longer time sniffing an unpleasant odor was 81 % accurate in differentiating children with ASD from typically developing children, and Rozenkrantz et al (2015) and Small and Pelphrey (2015) suggested that a sniff test could serve as an effective single biomarker for ASD.…”

Section: Do Shared Features Provide Construct Validity For An Asd Spementioning

confidence: 99%

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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“…However, in the vast majority of cases such diagnosis is not done before of an age of 5-6 years, and this is probably due to the lack of objective markers. Earlier detection of autism can lead to better responses to interventions [5,6]. Recently there is a growing interest among clinicians and scholars to find the possibility of isolating objective biological markers for autism [6,7].…”

Section: Introductionmentioning

confidence: 99%

“…Earlier detection of autism can lead to better responses to interventions [5,6]. Recently there is a growing interest among clinicians and scholars to find the possibility of isolating objective biological markers for autism [6,7]. The problem has been approached from different perspectives: behavioral, biochemical, neuroanatomical, neurophysiological, immunological, and even hormonal.…”

Section: Introductionmentioning

confidence: 99%

An Abnormal Cerebellar Network in Children with Autistic Spectrum Disorder: A Morphometric Study

Pappaianni

Grecucci²,

Siugzdaite³

2016

Autism Open Access

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Autism is a neurodevelopmental disorder characterized by poor social abilities, communication deficiency and restricted behavioural patterns. Recently, scholars started to consider the possibility of detecting biological markers for better and faster diagnosing autism. This problem has been approached from different perspectives considering biochemical, neurophysiological, and neuroanatomical markers. Following this perspective, our intent was to investigate whether a structural brain signature of autism can be detected in children by using a whole brain morphological analysis. To this aim, we selected 43 male children with autistic spectrum disorder and 46 male controls, matched for age. Structural brain images (T1 image), intelligence scores (Full IQ, Verbal IQ, Performance IQ), and Autism Diagnostic Observation Schedule (ADOS) scores were considered for analyses. Source-Based Morphometry, a multivariate method based on Independent Component Analysis to detect maximally independent cortical networks of gray matter differences was applied to autistic and control brains. Results showed a statistically different network between ASD children and controls, including several cerebellar regions (Inferior Semi-lunar lobule, Tuble, Uvula, Pyramis, Declive, Cerebellar Tonsil) and the Fusiform Gyrus, confirming, but, also expanding previous results. In addition, separate temporal, frontal, and parietal networks were found to be significantly correlated with the Stereotyped Behaviour ADOS scores. These morphologic differences may be particularly useful in paving the way for future objective methods to diagnose autism.

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Autism Spectrum Disorder: Sniffing Out a New Biomarker

Abstract: Early intervention improves prognosis in autism spectrum disorder, yet diagnosis is very difficult in preverbal children. A new study demonstrates that the automatic adjustments in sniffing patterns to pleasant and unpleasant odors may provide a window into early diagnosis.

Cited by 8 publications

References 12 publications

Three shades of grey: detecting brain abnormalities in children with autism using source‐, voxel‐ and surface‐based morphometry

Three shades of grey: detecting brain abnormalities in children with autism using source‐, voxel‐ and surface‐based morphometry

ASD Validity

An Abnormal Cerebellar Network in Children with Autistic Spectrum Disorder: A Morphometric Study

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