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Compared to what? Early brain overgrowth in autism and the perils of population norms.

ABSTRACT: BACKGROUND:Early brain overgrowth (EBO) in autism spectrum disorder (ASD) is among the best replicated biological associations in psychiatry. Most positive reports have compared head circumference (HC) in ASD (an excellent proxy for early brain size) with well-known reference norms. We sought to reappraise evidence for the EBO hypothesis given 1) the recent proliferation of longitudinal HC studies in ASD, and 2) emerging reports that several of the reference norms used to define EBO in ASD may be biased toward detecting HC overgrowth in contemporary samples of healthy children. METHODS:Systematic review of all published HC studies in children with ASD. Comparison of 330 longitudinally gathered HC measures between birth and 18 months from male children with autism (n = 35) and typically developing control subjects (n = 22). RESULTS:In systematic review, comparisons with locally recruited control subjects were significantly less likely to identify EBO in ASD than norm-based studies (p < .001). Through systematic review and analysis of new data, we replicate seminal reports of EBO in ASD relative to classical HC norms but show that this overgrowth relative to norms is mimicked by patterns of HC growth age in a large contemporary community-based sample of US children (n ~ 75,000). Controlling for known HC norm biases leaves inconsistent support for a subtle, later emerging and subgroup specific pattern of EBO in clinically ascertained ASD versus community control subjects. CONCLUSIONS:The best-replicated aspects of EBO reflect generalizable HC norm biases rather than disease-specific biomarkers. The potential HC norm biases we detail are not specific to ASD research but apply throughout clinical and academic medicine.

SUBMITTER: Raznahan A

PROVIDER: S-EPMC4837958 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Compared to what? Early brain overgrowth in autism and the perils of population norms.

Raznahan Armin A Wallace Gregory L GL Antezana Ligia L Greenstein Dede D Lenroot Rhoshel R Thurm Audrey A Gozzi Marta M Spence Sarah S Martin Alex A Swedo Susan E SE Giedd Jay N JN

Biological psychiatry 20130523 8

<h4>Background</h4>Early brain overgrowth (EBO) in autism spectrum disorder (ASD) is among the best replicated biological associations in psychiatry. Most positive reports have compared head circumference (HC) in ASD (an excellent proxy for early brain size) with well-known reference norms. We sought to reappraise evidence for the EBO hypothesis given 1) the recent proliferation of longitudinal HC studies in ASD, and 2) emerging reports that several of the reference norms used to define EBO in A ...[more]

PMID: 23706681

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Project description:BackgroundThe frequently cited Early Overgrowth Hypothesis of autism spectrum disorder (ASD) postulates that there is overgrowth of the brain in the first 2 years of life, which is followed by a period of arrested growth leading to normalized brain volume in late childhood and beyond. While there is consistent evidence for early brain overgrowth, there is mixed evidence for normalization of brain volume by middle childhood. The outcome of this debate is important to understanding the etiology and neurodevelopmental trajectories of ASD.MethodsBrain volume was examined in two very large single-site samples of children, adolescents, and adults. The primary sample comprised 456 6-25-year-olds (ASD n = 240, typically developing controls (TDC) n = 216), including a large number of females (n = 102) and spanning a wide IQ range (47-158). The replication sample included 175 males. High-resolution T1-weighted anatomical MRI images were examined for group differences in total brain, cerebellar, ventricular, gray, and white matter volumes.ResultsThe ASD group had significantly larger total brain, cerebellar, gray matter, white matter, and lateral ventricular volumes in both samples, indicating that brain volume remains enlarged through young adulthood, rather than normalizing. There were no significant age or sex interactions with diagnosis in these measures. However, a significant diagnosis-by-IQ interaction was detected in the larger sample, such that increased brain volume was related to higher IQ in the TDCs, but not in the ASD group. Regions-of-significance analysis indicated that total brain volume was larger in ASD than TDC for individuals with IQ less than 115, providing a potential explanation for prior inconsistent brain size results. No relationships were found between brain volume and measures of autism symptom severity within the ASD group.LimitationsOur cross-sectional sample may not reflect individual changes over time in brain volume and cannot quantify potential changes in volume prior to age 6.ConclusionsThese findings challenge the "normalization" prediction of the brain overgrowth hypothesis by demonstrating that brain enlargement persists across childhood into early adulthood. The findings raise questions about the clinical implications of brain enlargement, since we find that it neither confers cognitive benefits nor predicts increased symptom severity in ASD.

Project description:BackgroundComorbidity of Autism Spectrum Disorders with seizures or abnormal EEG (Autism-Epilepsy Phenotype) suggests shared pathomechanisms, and might be a starting point to identify distinct populations within the clinical complexity of the autistic spectrum. In this study, we tried to assess whether distinct subgroups, having distinctive clinical hallmarks, emerge from this comorbid condition.MethodsTwo-hundred and six individuals with idiopathic Autism Spectrum Disorders were subgrouped into three experimental classes depending on the presence of seizures and EEG abnormalities. Neurobehavioral, electroclinical and auxological parameters were investigated to identify differences among groups and features which increase the risk of seizures. Our statistical analyses used ANOVA, post-hoc multiple comparisons, and the Chi-squared test to analyze continuous and categorical variables. A correspondence analysis was also used to decompose significant Chi-squared and reduce variables dimensions.ResultsThe high percentage of children with seizures (28.2% of our whole cohort) and EEG abnormalities (64.1%) confirmed that the prevalence of epilepsy in Autism Spectrum Disorders exceeds that of the general population. Seizures were associated with severe intellectual disability, and not with autism severity. Interestingly, tall stature (without macrocephaly) was significantly associated with EEG abnormalities or later onset seizures. However, isolated macrocephaly was equally distributed among groups or associated with early onset seizures when accompanied by tall stature.ConclusionsTall stature seems to be a phenotypic "biomarker" of susceptibility to EEG abnormalities or late epilepsy in Autism Spectrum Disorders and, when concurring with macrocephaly, predisposes to early onset seizures. Growth pattern might act as an endophenotypic marker in Autism-Epilepsy comorbidity, delineating distinct pathophysiological subtypes and addressing personalized diagnostic work-up and therapeutic approaches.

Project description:We have previously argued from a theoretical basis that the standard practice of regression of the Global Signal from the fMRI time series in functional connectivity studies is ill advised, particularly when comparing groups of participants. Here, we demonstrate in resting-state data from participants with an Autism Spectrum Disorder and matched controls that these concerns are also well founded in real data. Using the prior theoretical work to formulate predictions, we show: (1) rather than simply altering the mean or range of correlation values amongst pairs of brain regions, Global Signal Regression systematically alters the rank ordering of values in addition to introducing negative values, (2) it leads to a reversal in the direction of group correlation differences relative to other preprocessing approaches, with a higher incidence of both long-range and local correlation differences that favor the Autism Spectrum Disorder group, (3) the strongest group differences under other preprocessing approaches are the ones most altered by Global Signal Regression, and (4) locations showing group differences no longer agree with those showing correlations with behavioral symptoms within the Autism Spectrum Disorder group. The correlation matrices of both participant groups under Global Signal Regression were well predicted by our previous mathematical analyses, demonstrating that there is nothing mysterious about these results. Finally, when independent physiological nuisance measures are lacking, we provide a simple alternative approach for assessing and lessening the influence of global correlations on group comparisons that replicates our previous findings. While this alternative performs less well for symptom correlations than our favored preprocessing approach that includes removal of independent physiological measures, it is preferable to the use of Global Signal Regression, which prevents unequivocal conclusions about the direction or location of group differences.

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Compared to what? Early brain overgrowth in autism and the perils of population norms.

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Compared to what? Early brain overgrowth in autism and the perils of population norms.

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