Exploring the multidimensional nature of repetitive and restricted behaviors and interests (RRBI) in autism: neuroanatomical correlates and clinical implications.

BACKGROUND: Repetitive and restricted behaviors and interests (RRBI) are core symptoms of autism with a complex entity and are commonly categorized into 'motor-driven' and 'cognitively driven'. RRBI symptomatology depends on the individual's clinical environment limiting the understanding of RRBI physiology, particularly their associated neuroanatomical structures. The complex RRBI heterogeneity needs to explore the whole RRBI spectrum by integrating the clinical context [autistic individuals, their relatives and typical developing (TD) individuals]. We hypothesized that different RRBI dimensions would emerge by exploring the whole spectrum of RRBI and that these dimensions are associated with neuroanatomical signatures-involving cortical and subcortical areas. METHOD: A sample of 792 individuals composed of 267 autistic subjects, their 370 first-degree relatives and 155 TD individuals was enrolled in the study. We assessed the whole patterns of RRBI in each individual by using the Repetitive Behavior Scale-Revised and the Yale-Brown Obsessive Compulsive Scale. We estimated brain volumes using MRI scanner for a subsample of the subjects (n = 152, 42 ASD, 89 relatives and 13 TD). We first investigated the dimensionality of RRBI by performing a principal component analysis on all items of these scales and included all the sampling population. We then explored the relationship between RRBI-derived factors with brain volumes using linear regression models. RESULTS: We identified 3 main factors (with 30.3% of the RRBI cumulative variance): Factor 1 (FA1, 12.7%) reflected mainly the 'motor-driven' RRBI symptoms; Factor 2 and 3 (respectively, 8.8% and 7.9%) gathered mainly Y-BOCS related items and represented the 'cognitively driven' RRBI symptoms. These three factors were significantly associated with the right/left putamen volumes but with opposite effects: FA1 was negatively associated with an increased volume of the right/left putamen conversely to FA2 and FA3 (all uncorrected p < 0.05). FA1 was negatively associated with the left amygdala (uncorrected p < 0.05), and FA2 was positively associated with the left parietal structure (uncorrected p = 0.001). CONCLUSION: Our results suggested 3 coherent RRBI dimensions involving the putamen commonly and other structures according to the RRBI dimension. The exploration of the putamen's integrative role in RSBI needs to be strengthened in further studies.

Enhancing fetal alcohol spectrum disorders diagnosis with a classifier based on the intracerebellar gradient of volumetric undersizing.

In fetal alcohol spectrum disorders (FASD), brain growth deficiency is a hallmark of subjects both with fetal alcohol syndrome (FAS) and with non-syndromic FASD (NS-FASD, i.e., those without specific diagnostic features). However, although the cerebellum was suggested to be more severely undersized than the rest of the brain, it has not yet been given a specific place in the FASD diagnostic criteria where neuroanatomical features still count for little if anything in diagnostic specificity. We applied a combination of cerebellar segmentation tools on a 1.5 T 3DT1 brain MRI dataset from a monocentric population of 89 FASD (52 FAS, 37 NS-FASD) and 126 typically developing controls (6-20 years old), providing 8 volumes: cerebellum, vermis and 3 lobes (anterior, posterior, inferior), plus total brain volume. After adjustment of confounders, the allometric scaling relationship between these cerebellar volumes (Vi ) and the total brain or cerebellum volume (Vt ) was fitted (Vi = bVt a ), and the effect of group (FAS, control) on allometric scaling was evaluated. We then estimated for each cerebellar volume in the FAS population the deviation from the typical scaling (v DTS) learned in the controls. Lastly, we trained and tested two classifiers to discriminate FAS from controls, one based on the total cerebellum v DTS only, the other based on all the cerebellar v DTS, comparing their performance both in the FAS and the NS-FASD group. Allometric scaling was significantly different between FAS and control group for all the cerebellar volumes (p < .001). We confirmed the excess of total cerebellum volume deficit (v DTS = -10.6%) and revealed an antero-inferior-posterior gradient of volumetric undersizing in the hemispheres (-12.4%, 1.1%, 2.0%, respectively) and the vermis (-16.7%, -9.2%, -8.6%, repectively). The classifier based on the intracerebellar gradient of v DTS performed more efficiently than the one based on total cerebellum v DTS only (AUC = 92% vs. 82%, p = .001). Setting a high probability threshold for >95% specificity of the classifiers, the gradient-based classifier identified 35% of the NS-FASD to have a FAS cerebellar phenotype, compared to 11% with the cerebellum-only classifier (pFISHER = 0.027). In a large series of FASD, this study details the volumetric undersizing within the cerebellum at the lobar and vermian level using allometric scaling, revealing an anterior-inferior-posterior gradient of vulnerability to prenatal alcohol exposure. It also strongly suggests that this intracerebellar gradient of volumetric undersizing may be a reliable neuroanatomical signature of FAS that could be used to improve the specificity of the diagnosis of NS-FASD.

Tackling hypo and hyper sensory processing heterogeneity in autism: From clinical stratification to genetic pathways.

As an integral part of autism spectrum symptoms, sensory processing issues including both hypo and hyper sensory sensitivities. These sensory specificities may result from an excitation/inhibition imbalance with a poorly understood of their level of convergence with genetic alterations in GABA-ergic and glutamatergic pathways. In our study, we aimed to characterize the hypo/hyper-sensory profile among autistic individuals. We then explored its link with the burden of deleterious mutations in a subset of individuals with available whole-genome sequencing data. To characterize the hypo/hyper-sensory profile, the differential Short Sensory Profile (dSSP) was defined as a normalized and centralized hypo/hypersensitivity ratio from the Short Sensory Profile (SSP). Including 1136 participants (533 autistic individuals, 210 first-degree relatives, and 267 controls) from two independent study samples (PARIS and LEAP), we observed a statistically significant dSSP mean difference between autistic individuals and controls, driven mostly by a high dSSP variability, with an intermediated profile represented by relatives. Our genetic analysis tended to associate the dSSP and the hyposensitivity with mutations of the GABAergic pathway. The major limitation was the dSSP difficulty to discriminate subjects with a similar quantum of hypo- and hyper-sensory symptoms to those with no such symptoms, resulting both in a similar ratio score of 0. However, the dSSP could be a relevant clinical score, and combined with additional sensory descriptions, genetics and endophenotypic substrates, will improve the exploration of the underlying neurobiological mechanisms of sensory processing differences in autism spectrum.

Combining neuroanatomical features to support diagnosis of fetal alcohol spectrum disorders.

AIM: To identify easily accessible neuroanatomical abnormalities useful for diagnosing fetal alcohol spectrum disorders (FASD) in fetal alcohol syndrome (FAS) but more importantly for the probabilistic diagnosis of non-syndromic forms (NS-FASD). METHOD: We retrospectively collected monocentric data from 52 individuals with FAS, 37 with NS-FASD, and 94 paired typically developing individuals (6-20 years, 99 males, 84 females). On brain T1-weighted magnetic resonance imaging, we measured brain size, corpus callosum length and thicknesses, vermis height, then evaluated vermis foliation (Likert scale). For each parameter, we established variations with age and brain size in comparison individuals (growth and scaling charts), then identified participants with abnormal measurements (<10th centile). RESULTS: According to growth charts, there was an excess of FAS with abnormally small brain, isthmus, splenium, and vermis. According to scaling charts, this excess remained only for isthmus thickness and vermis height. The vermis foliation was pathological in 18% of those with FASD but in no comparison individual. Overall, 39% of those with FAS, 27% with NS-FASD, but only 2% of comparison individuals presented with two FAS-recurrent abnormalities, and 19% of those with FAS had all three. Considering the number of anomalies, there was a higher likelihood of a causal link with alcohol in 14% of those with NS-FASD. INTERPRETATION: Our results suggest that adding an explicit composite neuroanatomical-radiological criterion for FASD diagnosis may improve its specificity, especially in NS-FASD. WHAT THIS PAPER ADDS: Neuroanatomical anomalies independent of microcephaly can be measured with clinical-imaging tools. Small-for-age brain, small-for-brain-size callosal isthmus or vermian height, and disrupted vermis foliation are fetal alcohol syndrome (FAS)-recurrent anomalies. Associations of these anomalies are frequent in fetal alcohol spectrum disorder (FASD) even without FAS, while exceptional in typically developing individuals. These associations support higher likelihood of causal link with alcohol in some individuals with non-syndromic FASD. A new explicit and composite neuroanatomical-radiological criterion can improve the specificity of FASD diagnosis.

Insights from an autism imaging biomarker challenge: Promises and threats to biomarker discovery.

MRI has been extensively used to identify anatomical and functional differences in Autism Spectrum Disorder (ASD). Yet, many of these findings have proven difficult to replicate because studies rely on small cohorts and are built on many complex, undisclosed, analytic choices. We conducted an international challenge to predict ASD diagnosis from MRI data, where we provided preprocessed anatomical and functional MRI data from > 2,000 individuals. Evaluation of the predictions was rigorously blinded. 146 challengers submitted prediction algorithms, which were evaluated at the end of the challenge using unseen data and an additional acquisition site. On the best algorithms, we studied the importance of MRI modalities, brain regions, and sample size. We found evidence that MRI could predict ASD diagnosis: the 10 best algorithms reliably predicted diagnosis with AUC∼0.80 - far superior to what can be currently obtained using genotyping data in cohorts 20-times larger. We observed that functional MRI was more important for prediction than anatomical MRI, and that increasing sample size steadily increased prediction accuracy, providing an efficient strategy to improve biomarkers. We also observed that despite a strong incentive to generalise to unseen data, model development on a given dataset faces the risk of overfitting: performing well in cross-validation on the data at hand, but not generalising. Finally, we were able to predict ASD diagnosis on an external sample added after the end of the challenge (EU-AIMS), although with a lower prediction accuracy (AUC=0.72). This indicates that despite being based on a large multisite cohort, our challenge still produced biomarkers fragile in the face of dataset shifts.

Discriminant value of repetitive behaviors in families with autism spectrum disorder and obsessional compulsive disorder probands.

Repetitive behaviors (RB) represent a wide spectrum of symptoms ranging from sensory-motor stereotypies to complex cognitive rituals, frequently dichotomized as low- and high-order sub-groups of symptoms. Even though these subgroups are considered as phenomenologically distinct in autism spectrum disorder (ASD) and obsessive-compulsive disorder (OCD), brain imaging and genetic studies suggest that they have common mechanisms and pathways. This discrepancy may be explained by the frequent intellectual disability reported in ASD, which blurs the RB expressivity. Given the high heritability of RB, that is, the diversity of symptoms expressed in the relatives are dependent on those expressed in their probands, we hypothesize that if RB expressed in ASD or OCD are two distinct entities, then the RB expressed in relatives will also reflect these two dimensions. We thus conduct a linear discriminant analysis on RB in both the relatives of probands with ASD and OCD and subjects from the general population (n = 1023). The discriminant analysis results in a classification of 81.1% of the controls (p < 10-4 ), but poorly differentiated the ASD and OCD relatives (≈46%). The stepwise analysis reveals that five symptoms attributed to high-order RB and two related to low-order RB (including hypersensitivity) are the most discriminant. Our results support the idea that the difference of RB patterns in the relatives is mild compared with the distribution of symptoms in controls. Our findings reinforce the evidence of a common biological pattern of RB both in ASD and OCD but with minor differences, specific to each of these two neuro-developmental disorders. LAY SUMMARY: Repetitive behaviors (RB), a key symptom in the classification of both OCD and ASD, are phenomenologically considered as distinct in the two disorders, which is in contrast with brain imaging studies describing a common neural circuit. Intellectual disability, which is frequently associated with ASD, makes RB in ASD more difficult to understand as it affects the expression of the RB symptoms. To avoid this bias, we propose to consider the familial aggregation in ASD and OCD by exploring RB in the first-degree relatives of ASD and OCD. Our results highlight the existence of RB expressed in relatives compared to the general population, with a common pattern of symptoms in relatives of both ASD and OCD but also minor differences, specific to each of these two neuro-developmental disorders.

Adjusting for allometric scaling in ABIDE I challenges subcortical volume differences in autism spectrum disorder.

Inconsistencies across studies investigating subcortical correlates of autism spectrum disorder (ASD) may stem from small sample size, sample heterogeneity, and omitting or linearly adjusting for total brain volume (TBV). To properly adjust for TBV, brain allometry-the nonlinear scaling relationship between regional volumes and TBV-was considered when examining subcortical volumetric differences between typically developing (TD) and ASD individuals. Autism Brain Imaging Data Exchange I (ABIDE I; N = 654) data was analyzed with two methodological approaches: univariate linear mixed effects models and multivariate multiple group confirmatory factor analyses. Analyses were conducted on the entire sample and in subsamples based on age, sex, and full scale intelligence quotient (FSIQ). A similar ABIDE I study was replicated and the impact of different TBV adjustments on neuroanatomical group differences was investigated. No robust subcortical allometric or volumetric group differences were observed in the entire sample across methods. Exploratory analyses suggested that allometric scaling and volume group differences may exist in certain subgroups defined by age, sex, and/or FSIQ. The type of TBV adjustment influenced some reported volumetric and scaling group differences. This study supports the absence of robust volumetric differences between ASD and TD individuals in the investigated volumes when adjusting for brain allometry, expands the literature by finding no group difference in allometric scaling, and further suggests that differing TBV adjustments contribute to the variability of reported neuroanatomical differences in ASD.

Patients with autism spectrum disorders display reproducible functional connectivity alterations.

Despite the high clinical burden, little is known about pathophysiology underlying autism spectrum disorder (ASD). Recent resting-state functional magnetic resonance imaging (rs-fMRI) studies have found atypical synchronization of brain activity in ASD. However, no consensus has been reached on the nature and clinical relevance of these alterations. Here, we addressed these questions in four large ASD cohorts. Using rs-fMRI, we identified functional connectivity alterations associated with ASD. We tested for associations of these imaging phenotypes with clinical and demographic factors such as age, sex, medication status, and clinical symptom severity. Our results showed reproducible patterns of ASD-associated functional hyper- and hypoconnectivity. Hypoconnectivity was primarily restricted to sensory-motor regions, whereas hyperconnectivity hubs were predominately located in prefrontal and parietal cortices. Shifts in cortico-cortical between-network connectivity from outside to within the identified regions were shown to be a key driver of these abnormalities. This reproducible pathophysiological phenotype was partially associated with core ASD symptoms related to communication and daily living skills and was not affected by age, sex, or medication status. Although the large effect sizes in standardized cohorts are encouraging with respect to potential application as a treatment and for patient stratification, the moderate link to clinical symptoms and the large overlap with healthy controls currently limit the usability of identified alterations as diagnostic or efficacy readout.

Morning Plasma Melatonin Differences in Autism: Beyond the Impact of Pineal Gland Volume.

While low plasma melatonin, a neuro-hormone synthesized in the pineal gland, has been frequently associated with autism, our understanding of the mechanisms behind it have remained unclear. In this exploratory study, we hypothesized that low melatonin levels in ASD could be linked to a decrease of the pineal gland volume (PGV). PGV estimates with magnetic resonance imaging (MRI) with a voxel-based volumetric measurement method and early morning plasma melatonin levels were evaluated for 215 participants, including 78 individuals with ASD, 90 unaffected relatives, and 47 controls. We first found that both early morning melatonin level and PGV were lower in patients compared to controls. We secondly built a linear model and observed that plasma melatonin was correlated to the group of the participant, but also to the PGV. To further understand the relationship between PGV and melatonin, we generated a normative model of the PGV relationship with melatonin level based on control participant data. We found an effect of PGV on normalized melatonin levels in ASD. Melatonin deficit appeared however more related to the group of the subject. Thus, melatonin variations in ASD could be mainly driven by melatonin pathway dysregulation.

Increased risk of ADHD in families with ASD.

Attention Deficit and Hyperactive Disorder (ADHD) and Autism Spectrum Disorders (ASD) are frequent comorbid neurodevelopmental conditions and the overlap between both disorders remains to be delineated. A more complete understanding of the shared genetic and environmental factors is needed. Using a family-based method, we evaluated the risk of ADHD in a group of relatives with an ASD proband (ASD-) and a group of relatives with an ASD and ADHD proband (ASD+). We enrolled 1245 individuals in the study: 499 probands, their 746 first-degree relatives and 140 controls. We used a multivariate generalized estimating equation (GEE) model, in which the dependent variable was the ADHD diagnosis in the relatives and the independent variable the ASD+ or ASD- in probands. We adjusted for sociodemographic factors (age, sex, IQ) and for the nature of the familial relationship with the affected proband (parent or sibling). Among the probands, there were 287 ASD- and 212 ASD+ individuals. ADHD was more frequent in relatives (19%) than in the control group (7%) (p = 0.001). The risk of ADHD was higher in the ASD+ relatives group than in the ASD- relatives group (GEE model OR 1.58 [95% CI 1.04-2.38], p = 0.032). This result was found in parents (OR 1.96 [95% CI 1.14-3.36], but not in siblings (OR 1.28 [95% CI 0.84-1.94], p = 0.434). Our study provides a representative estimate of the family distribution of ADHD in relatives of ASD probands but supports the modest effect of shared genetic and environmental factors between both disorders.

Alpha Waves as a Neuromarker of Autism Spectrum Disorder: The Challenge of Reproducibility and Heterogeneity.

Background: There is no consensus in the literature concerning the presence of abnormal alpha wave profiles in patients with autism spectrum disorder (ASD). This may be due to phenotypic heterogeneity among patients as well as the limited sample sizes utilized. Here we present our results of alpha wave profile analysis based on a sample larger than most of those in the field, performed using a robust processing pipeline. Methods: We compared the alpha waves profiles at rest in children with ASD to those of age-, sex-, and IQ-matched control individuals. We used linear regression and non-parametric normative models using age as covariate forparsing the clinical heterogeneity. We explored the correlation between EEG profiles and the patient's brain volumes, obtained from structural MRI. We automatized the detection of the alpha peak and visually quality controled our MRI measurements. We assessed the robustness of our results by running the EEG preprocessing with two different versions of Matlab as well as Python. Results: A simple linear regression between peak power or frequency of the alpha waves and the status or age of the participants did not allow to identify any statistically significant relationship. The non-parametric normative model (which took account the non-linear effect of age on the alpha profiles) suggested that participants with ASD displayed more variability than control participants for both frequency and amplitude of the alpha peak (p < 0.05). Independent of the status of the individual, we also observed weak associations (uncorrected p < 0.05) between the alpha frequency, and the volumes of several cortical and subcortical structures (in particular the striatum), but which did not survive correction for multiple testing and changed between analysis pelines. Discussions: Our study did not find evidence for abnormal alpha wave profiles in ASD. We propose, however, an analysis pipeline to perform standardized and automatized EEG analyses on large cohorts. These should help the community to address the challenge of clinical heterogeneity of ASD and to tackle the problems of reproducibility.

Sleep in youth with autism spectrum disorders: systematic review and meta-analysis of subjective and objective studies.

BACKGROUND: Sleep problems are common and impairing in individuals with autism spectrum disorders (ASD). Evidence synthesis including both subjective (ie, measured with questionnaires) and objective (ie, quantified with neurophysiological tools) sleep alterations in youth with ASD is currently lacking. OBJECTIVE: We conducted a systematic review and meta-analysis of subjective and objective studies sleep studies in youth with ASD. METHODS: We searched the following electronic databases with no language, date or type of document restriction up to 23 May 2018: PubMed, PsycInfo, Embase+Embase Classic, Ovid Medline and Web of Knowledge. Random-effects models were used. Heterogeneity was assessed with Cochran's Q and I2 statistics. Publication (small studies) bias was assessed with final plots and the Egger's test. Study quality was evaluated with the Newcastle Ottawa Scale. Analyses were conducted using Review Manager and Comprehensive Meta-Analysis. FINDINGS: From a pool of 3359 non-duplicate potentially relevant references, 47 datasets were included in the meta-analyses. Subjective and objective sleep outcome measures were extracted from 37 and 15 studies, respectively. Only five studies were based on comorbidity free, medication-naïve participants. Compared with typically developing controls, youth with ASD significantly differed in 10/14 subjective parameters and in 7/14 objective sleep parameters. The average quality score in the Newcastle-Ottawa Scale was 5.9/9. DISCUSSION AND CLINICAL IMPLICATIONS: A number of subjective and, to a less extent, objective sleep alterations might characterise youth with ASD, but future studies should assess the impact of pharmacological treatment and psychiatric comorbidities.

Cerebellar Volume in Autism: Literature Meta-analysis and Analysis of the Autism Brain Imaging Data Exchange Cohort.

BACKGROUND: The neuroanatomical bases of autism spectrum disorder remain largely unknown. Among the most widely discussed candidate endophenotypes, differences in cerebellar volume have been often reported as statistically significant. METHODS: We aimed at objectifying this possible alteration by performing a systematic meta-analysis of the literature and an analysis of the ABIDE (Autism Brain Imaging Data Exchange) cohort. Our meta-analysis sought to determine a combined effect size of autism spectrum disorder diagnosis on different measures of the cerebellar anatomy as well as the effect of possible factors of variability across studies. We then analyzed the cerebellar volume of 328 patients and 353 control subjects from the ABIDE project. RESULTS: The meta-analysis of the literature suggested a weak but significant association between autism spectrum disorder diagnosis and increased cerebellar volume (p = .049, uncorrected), but the analysis of ABIDE did not show any relationship. The studies meta-analyzed were generally underpowered; however, the number of statistically significant findings was larger than expected. CONCLUSIONS: Although we could not provide a conclusive explanation for this excess of significant findings, our analyses would suggest publication bias as a possible reason. Finally, age, sex, and IQ were important sources of cerebellar volume variability, although independent of autism diagnosis.

Enhancing studies of the connectome in autism using the autism brain imaging data exchange II.

The second iteration of the Autism Brain Imaging Data Exchange (ABIDE II) aims to enhance the scope of brain connectomics research in Autism Spectrum Disorder (ASD). Consistent with the initial ABIDE effort (ABIDE I), that released 1112 datasets in 2012, this new multisite open-data resource is an aggregate of resting state functional magnetic resonance imaging (MRI) and corresponding structural MRI and phenotypic datasets. ABIDE II includes datasets from an additional 487 individuals with ASD and 557 controls previously collected across 16 international institutions. The combination of ABIDE I and ABIDE II provides investigators with 2156 unique cross-sectional datasets allowing selection of samples for discovery and/or replication. This sample size can also facilitate the identification of neurobiological subgroups, as well as preliminary examinations of sex differences in ASD. Additionally, ABIDE II includes a range of psychiatric variables to inform our understanding of the neural correlates of co-occurring psychopathology; 284 diffusion imaging datasets are also included. It is anticipated that these enhancements will contribute to unraveling key sources of ASD heterogeneity.

Gender differences in autism spectrum disorders: Divergence among specific core symptoms.

Community-based studies have consistently shown a sex ratio heavily skewed towards males in autism spectrum disorders (ASD). The factors underlying this predominance of males are largely unknown, but the way girls score on standardized categorical diagnostic tools might account for the underrecognition of ASD in girls. Despite the existence of different norms for boys and girls with ASD on several major screening tests, the algorithm of the Autism Diagnosis Interview-Revised (ADI-R) has not been reformulated. The aim of our study was to investigate which ADI-R items discriminate between males and females, and to evaluate their weighting in the final diagnosis of autism. We then conducted discriminant analysis (DA) on a sample of 594 probands including 129 females with ASD, recruited by the Paris Autism Research International Sibpair (PARIS) Study. A replication analysis was run on an independent sample of 1716 probands including 338 females with ASD, recruited through the Autism Genetics Resource Exchange (AGRE) program. Entering the raw scores for all ADI-R items as independent variables, the DA correctly classified 78.9% of males and 72.9% of females (P < 0.001) in the PARIS cohort, and 72.2% of males and 68.3% of females (P < 0.0001) in the AGRE cohort. Among the items extracted by the stepwise DA, four belonged to the ADI-R algorithm used for the final diagnosis of ASD. In conclusion, several items of the ADI-R that are taken into account in the diagnosis of autism significantly differentiates between males and females. The potential gender bias thus induced may participate in the underestimation of the prevalence of ASD in females. Autism Res 2016,. © 2016 International Society for Autism Research, Wiley Periodicals, Inc. Autism Res 2017, 10: 680-689. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

11q24.2-25 micro-rearrangements in autism spectrum disorders: Relation to brain structures.

Jacobsen syndrome (JS) is characterized by intellectual disability and higher risk for autism spectrum disorders (ASD). All patients with JS are carriers of contiguous de novo deletions of 11q24.2-25, but the causative genes remain unknown. Within the critical interval, we hypothesized that haploinsufficiency of the neuronal cell adhesion molecule Neurotrimin (NTM) might increase the risk for ASD and could affect brain structure volumes. We searched for deleterious mutations affecting NTM in 1256 ASD patients and 1287 controls, using SNP arrays, and by direct sequencing of 250 ASD patients and 180 controls. We compared our results to those obtained from independent cohorts of ASD patients and controls. We identified two patients with Copy Number Variants (CNV) encompassing NTM, one with a large de novo deletion, and a clinical phenotype of JS (including macrocephaly), and a second with a paternally inherited duplication, not consistent with JS. Interestingly, no similar CNVs were observed in controls. We did not observe enrichment for deleterious NTM mutations in our cohort. We then explored if the macrocephaly in the patient with JS was associated with a homogeneous increase of brain structures volumes using automatic segmentation. Compared to subjects without NTM micro-rearrangements (n=188), the patient had an increased volume of the sub-cortical structures but a decrease of the occipital gray matter. Finally our explorations could not incriminate NTM as a susceptibility gene for ASD, but provides new information on the impact of the 11q24.2-25 deletion on brain anatomy.

Neuroanatomical Diversity of Corpus Callosum and Brain Volume in Autism: Meta-analysis, Analysis of the Autism Brain Imaging Data Exchange Project, and Simulation.

BACKGROUND: Patients with autism have been often reported to have a smaller corpus callosum (CC) than control subjects. METHODS: We conducted a meta-analysis of the literature, analyzed the CC in 694 subjects of the Autism Brain Imaging Data Exchange project, and performed computer simulations to study the effect of different analysis strategies. RESULTS: Our meta-analysis suggested a group difference in CC size; however, the studies were heavily underpowered (20% power to detect Cohen's d = .3). In contrast, we did not observe significant differences in the Autism Brain Imaging Data Exchange cohort, despite having achieved 99% power. However, we observed that CC scaled nonlinearly with brain volume (BV): large brains had a proportionally smaller CC. Our simulations showed that because of this nonlinearity, CC normalization could not control for eventual BV differences, but using BV as a covariate in a linear model would. We also observed a weaker correlation of IQ and BV in cases compared with control subjects. Our simulations showed that matching populations by IQ could then induce artifactual BV differences. CONCLUSIONS: The lack of statistical power in the previous literature prevents us from establishing the reality of the claims of a smaller CC in autism, and our own analyses did not find any. However, the nonlinear relationship between CC and BV and the different correlation between BV and IQ in cases and control subjects may induce artifactual differences. Overall, our results highlight the necessity for open data sharing to provide a more solid ground for the discovery of neuroimaging biomarkers within the context of the wide human neuroanatomical diversity.

Heterozygous FA2H mutations in autism spectrum disorders.

BACKGROUND: Widespread abnormalities in white matter development are frequently reported in cases of autism spectrum disorders (ASD) and could be involved in the disconnectivity suggested in these disorders. Homozygous mutations in the gene coding for fatty-acid 2-hydroxylase (FA2H), an enzyme involved in myelin synthesis, are associated with complex leukodystrophies, but little is known about the functional impact of heterozygous FA2H mutations. We hypothesized that rare deleterious heterozygous mutations of FA2H might constitute risk factors for ASD. METHODS: We searched deleterious mutations affecting FA2H, by genotyping 1256 independent patients with ASD genotyped using Genome Wide SNP arrays, and also by sequencing in independent set of 186 subjects with ASD and 353 controls. We then explored the impact of the identified mutations by measuring FA2H enzymatic activity and expression, in transfected COS7 cells. RESULTS: One heterozygous deletion within 16q22.3-q23.1 including FA2H was observed in two siblings who share symptoms of autism and severe cognitive impairment, axial T2-FLAIR weighted MRI posterior periventricular white matter lesions. Also, two rare non-synonymous mutations (R113W and R113Q) were reported. Although predictive models suggested that R113W should be a deleterious, we did not find that FA2H activity was affected by expression of the R113W mutation in cultured COS cells. CONCLUSIONS: While our results do not support a major role for FA2H coding variants in ASD, a screening of other genes related to myelin synthesis would allow us to better understand the role of non-neuronal elements in ASD susceptibility.