Mapping brain abnormalities in boys with autism

Pten haploinsufficiency causes desynchronized growth of brain areas involved in sensory processing

How changes in brain scaling relate to altered behavior is an important question in neurodevelopmental disorder research. Mice with germline Pten haploinsufficiency (Pten ^+/-) closely mirror the abnormal brain scaling and behavioral deficits seen in humans with macrocephaly/autism syndrome, which is caused by PTEN mutations. We explored whether deviation from normal patterns of growth can predict behavioral abnormalities. Brain regions associated with sensory processing (e.g., pons and inferior colliculus) had the biggest deviations from expected volume. While Pten ^+/- mice showed little or no abnormal behavior on most assays, both sexes showed sensory deficits, including impaired sensorimotor gating and hyporeactivity to high-intensity stimuli. Developmental analysis of this phenotype showed sexual dimorphism for hyporeactivity. Mapping behavioral phenotypes of Pten ^+/- mice onto relevant brain regions suggested abnormal behavior is likely when associated with relatively enlarged brain regions, while unchanged or relatively decreased brain regions have little predictive value.

Editorial comment on "Diagnosing autism spectrum disorder in children using conventional MRI and apparent diffusion coefficient based deep learning algorithms"

This editorial comment refers to the article: "Diagnosing autism spectrum disorder in children using conventional MRI and apparent diffusion coefficient based deep learning algorithms" by Guo et al. (Eur Radiol, 2021). KEY POINTS: •Deep learning may help to uncover imaging features of autism spectrum disorder on MRI.

Automatic classification of autism spectrum disorder in children using cortical thickness and support vector machine

OBJECTIVE

Autism spectrum disorder (ASD) is a neurodevelopmental condition with a heterogeneous phenotype. The role of biomarkers in ASD diagnosis has been highlighted; cortical thickness has proved to be involved in the etiopathogenesis of ASD core symptoms. We apply support vector machine, a supervised machine learning method, in order to identify specific cortical thickness alterations in ASD subjects.

METHODS

A sample of 76 subjects (9.5 ± 3.4 years old) has been selected, 40 diagnosed with ASD and 36 typically developed subjects. All children underwent a magnetic resonance imaging (MRI) examination; T1-MPRAGE sequences were analyzed to extract features for the characterization and parcellation of regions of interests (ROI); average cortical thickness (CT) has been measured for each ROI. For the classification process, the extracted features were used as input for a classifier to identify ASD subjects through a "learning by example" procedure; the features with best performance was then selected by "greedy forward-feature selection." Finally, this model underwent a leave-one-out cross-validation approach.

RESULTS

From the training set of 68 ROIs, five ROIs reached accuracies of over 70%. After this phase, we used a recursive feature selection process in order to identify the eight features with the best accuracy (84.2%). CT resulted higher in ASD compared to controls in all the ROIs identified at the end of the process.

CONCLUSION

We found increased CT in various brain regions in ASD subjects, confirming their role in the pathogenesis of this condition. Considering the brain development curve during ages, these changes in CT may normalize during development. Further validation on a larger sample is required.

Paving the Way toward Personalized Medicine: Current Advances and Challenges in Multi-OMICS Approach in Autism Spectrum Disorder for Biomarkers Discovery and Patient Stratification

Autism spectrum disorder (ASD) is a multifactorial neurodevelopmental disorder characterized by impairments in two main areas: social/communication skills and repetitive behavioral patterns. The prevalence of ASD has increased in the past two decades, however, it is not known whether the evident rise in ASD prevalence is due to changes in diagnostic criteria or an actual increase in ASD cases. Due to the complexity and heterogeneity of ASD, symptoms vary in severity and may be accompanied by comorbidities such as epilepsy, attention deficit hyperactivity disorder (ADHD), and gastrointestinal (GI) disorders. Identifying biomarkers of ASD is not only crucial to understanding the biological characteristics of the disorder, but also as a detection tool for its early screening. Hence, this review gives an insight into the main areas of ASD biomarker research that show promising findings. Finally, it covers success stories that highlight the importance of precision medicine and the current challenges in ASD biomarker discovery studies.

Dissociating regional gray matter density and gray matter volume in autism spectrum condition

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Local gray matter structure can be separated into density and volume.

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Gray matter density increased and volume decreased with age in adolescence.

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Increased gray matter density but reduced volume in girls relative to boys.

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Autism is associated with increased gray matter volume, but not density.

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Regions with increased volume align with prior studies in autistic youth.

Background

Despite decades of research, there is continued uncertainty regarding whether autism is associated with a specific profile of gray matter (GM) structure. This inconsistency may stem from the widespread use of voxel-based morphometry (VBM) methods that combine indices of GM density and GM volume. If GM density or volume, but not both, prove different in autism, the traditional VBM approach of combining the two indices may obscure the difference. The present study measures GM density and volume separately to examine whether autism is associated with alterations in GM volume, density, or both.

Methods

Differences in MRI-based GM density and volume were examined in 6–25 year-olds with a diagnosis of autism spectrum disorder (n = 213, 80.8% male, IQ 47–154) and a typically developing (TD) sample (n = 190, 71.6% male, IQ 67–155). High-resolution T1-weighted anatomical images were collected on a single MRI scanner. Regional density and volume were estimated via whole-brain parcellation comprised of 1625 parcels. Parcel-wise analyses were conducted using generalized additive models while controlling the false discovery rate (FDR, q < 0.05). Volume differences in the 68-region Desikan-Killiany atlas derived from Freesurfer were also examined, to establish the generalizability of findings across methods.

Results

No density differences were observed between the autistic and TD groups, either in individual parcels or whole brain mean density. Increased volume was observed in autism compared to the TD group when controlling for Age, Sex, and IQ, both at the level of the whole brain (total volume) and in 45 parcels (2.8% of total parcels). Parcels with greater volume included inferior, middle, and superior temporal gyrus, inferior and superior frontal gyrus, precuneus, and fusiform gyrus. Converging evidence from a standard Freesurfer pipeline also identified greater volume in a number of overlapping regions.

Limitations

The method for determining “density” is not a direct measure of neuronal density, and this study cannot reveal underlying cellular differences. While this study represents possibly the largest single-site sample of its kind, it is underpowered to detect very small differences.

Conclusions

These results provide compelling evidence that autism is associated with regional GM volumetric differences, which are more prominent than density differences. This underscores the importance of examining volume and density separately, and suggests that direct measures of volume (e.g. region-of-interest or tensor-based morphometry approaches) may be more sensitive to autism-relevant differences in neuroanatomy than concentration/density-based approaches.

Brain Ventricular System and Cerebrospinal Fluid Development and Function: Light at the End of the Tube: A Primer with Latest Insights

The brain ventricular system is a series of connected cavities, filled with cerebrospinal fluid (CSF), that forms within the vertebrate central nervous system (CNS). The hollow neural tube is a hallmark of the chordate CNS, and a closed neural tube is essential for normal development. Development and function of the ventricular system is examined, emphasizing three interdigitating components that form a functional system: ventricle walls, CSF fluid properties, and activity of CSF constituent factors. The cellular lining of the ventricle both can produce and is responsive to CSF. Fluid properties and conserved CSF components contribute to normal CNS development. Anomalies of the CSF/ventricular system serve as diagnostics and may cause CNS disorders, further highlighting their importance. This review focuses on the evolution and development of the brain ventricular system, associated function, and connected pathologies. It is geared as an introduction for scholars with little background in the field.

Structural brain abnormalities in children and adolescents with comorbid autism spectrum disorder and attention-deficit/hyperactivity disorder

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) share high rates of comorbidity, with the Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition now acknowledging the comorbid diagnosis of ASD and ADHD. Although structural abnormalities in the prefrontal cortex, cerebellum, and basal ganglia occur in both ASD and ADHD, no structural studies have focused exclusively on patients with comorbid ASD and ADHD. We thus aimed to clarify the structural features and developmental changes in patients with comorbid ASD and ADHD in a relatively large sample from two sites. Ninety-two patients were age-matched to 141 typically developing (TD) controls (age range: 5-16 years) and assessed for volumetric characteristics using structural magnetic resonance imaging (i.e. surface-based morphometry). While there were no significant differences in prefrontal cortex, cerebellum, and basal ganglia volumes, patients with ASD and ADHD exhibited significantly lower left postcentral gyrus volumes than TD controls. We observed significantly lower postcentral gyrus volumes exclusively in children and preadolescents, and not in adolescents. Our findings suggest that abnormal somatosensory, attributed to delayed maturation of the left postcentral gyrus, leads to the core symptoms experienced by patients with comorbid ASD and ADHD.

Pten haploinsufficiency disrupts scaling across brain areas during development in mice

Haploinsufficiency for PTEN is a cause of autism spectrum disorder and brain overgrowth; however, it is not known if PTEN mutations disrupt scaling across brain areas during development. To address this question, we used magnetic resonance imaging to analyze brains of male Pten haploinsufficient (Pten^+/-) mice and wild-type littermates during early postnatal development and adulthood. Adult Pten^+/- mice display a consistent pattern of abnormal scaling across brain areas, with white matter (WM) areas being particularly affected. This regional and WM enlargement recapitulates structural abnormalities found in individuals with PTEN haploinsufficiency and autism. Early postnatal Pten^+/- mice do not display the same pattern, instead exhibiting greater variability across mice and brain regions than controls. This suggests that Pten haploinsufficiency may desynchronize growth across brain regions during early development before stabilizing by maturity. Pten^+/- cortical cultures display increased proliferation of glial cell populations, indicating a potential substrate of WM enlargement, and provide a platform for testing candidate therapeutics. Pten haploinsufficiency dysregulates coordinated growth across brain regions during development. This results in abnormally scaled brain areas and associated behavioral deficits, potentially explaining the relationship between PTEN mutations and neurodevelopmental disorders.

Disruptions to the cerebellar GABAergic system in juvenile guinea pigs following preterm birth

BACKGROUND

Children that are born preterm are at an increased risk of developing cognitive problems and behavioural disorders, such as attention deficit hyperactivity disorder (ADHD). There is increasing interest in the role of the cerebellum in these processes and the potential involvement of GABAergic pathways in neurodevelopmental disorders. We propose that preterm birth, and the associated loss of the trophic intrauterine environment, alters the development of the cerebellum, contributing to ongoing neurobehavioral disorders.

METHODS

Guinea pigs were delivered preterm (GA62) or spontaneously at term (GA69), and tissues collected at corrected postnatal day (PND) 28. Neurodevelopmental and GABAergic markers myelin basic protein (MBP), neuronal nuclei (NeuN), calbindin (Purkinje cells), and GAD67 (GABA synthesis enzyme) were analysed in cerebellar lobules IX and X by immunohistochemistry. Protein expression of GAD67 and GAT1 (GABA transporter enzyme) were quantified by western blot, whilst neurosteroid-sensitive GABA_A receptor subunits were measured by RT-PCR.

RESULTS

MBP immunostaining was increased in lobule IX of preterm males, and reduced in lobule X of preterm females when compared to their term counterparts. GAD67 staining was decreased in lobule IX and X of the preterm males, but only in lobule X of the preterm females compared to term cohorts for each sex. Internal granule cell layer width of lobule X was decreased in preterm cohorts of both sexes compared to terms. There were no differences between gestational age groups for NeuN staining, GAD67 and GAT1 protein expression as measured by western blotting, or GABA_A receptor subunits as measured by RT-PCR between preterm and term for either sex.

CONCLUSIONS

The present findings suggest that components of the cerebellar GABAergic system of the ex-preterm cerebellum are disrupted. The higher expression of myelin in the preterm males may be due to a deficit in axonal pruning, whereas females have a deficit in myelination at 28 corrected days of age. Together these ongoing alterations may contribute to the neurodevelopmental and behavioural disorders observed in those born preterm.

Maternal SSRI exposure increases the risk of autistic offspring: A meta-analysis and systematic review

BACKGROUND

Selective serotonin reuptake inhibitors (SSRIs) are the most common antidepressants used to preclude maternal pregnancy depression. There is a growing body of literature assessing the association of prenatal exposure to SSRIs with autism spectrum disorder (ASD). The present systematic review and meta-analysis reviewed the medical literature and pooled the results of the association of prenatal exposure to SSRIs with ASD.

METHODS

Published investigations in English by June 2016 with keywords of selective serotonin reuptake inhibitors, SSRI, autism spectrum disorder, ASD, pregnancy, childhood, children, neurodevelopment were identified using databases PubMed and PMC, MEDLINE, EMBASE, SCOPUS, and Google Scholar. Cochran's Q statistic-value (Q), degree of freedom (df), and I² indices (variation in odds ratio [OR] attributable to heterogeneity) were calculated to analyze the risk of heterogeneity of the within- and between-study variability. Pooled odds ratio (OR) and 95% confidence interval (CI) were reported by a Mantel-Haenszel test.

RESULTS

There was a non-significant heterogeneity for the included studies ([Q=3.61, df=6, P=0.730], I²=0%). The pooled results showed a significant association between prenatal SSRI exposure and ASD (OR=1.82, 95% CI=1.59-2.10, Z=8.49, P=0.00).

CONCLUSION

The evidence from the present study suggests that prenatal exposure to SSRIs is associated with a higher risk of ASD.

A Novel Approach to Prenatal Measurement of the Fetal Frontal Lobe Using Three-Dimensional Sonography

OBJECTIVE

While prenatal 3D ultrasonography results in improved diagnostic accuracy, no data are available on biometric assessment of the fetal frontal lobe. This study was designed to assess feasibility of a standardized approach to biometric measurement of the fetal frontal lobe and to construct frontal lobe growth trajectories throughout gestation.

STUDY DESIGN

A sonographic 3D volume set was obtained and measured in 101 patients between 16.1 and 33.7 gestational weeks. Measurements were obtained by two independent raters. To model the relationship between gestational age and each frontal lobe measurement, flexible linear regression models were fit using penalized regression splines.

RESULTS

The sample contained an ethnically diverse population (7.9% Native Americans, 45.5% Hispanic/Latina). There was high inter-rater reliability (correlation coefficients: 0.95, 1.0, and 0.87 for frontal lobe length, width, and height; p-values < 0.001). Graphs of the growth trajectories and corresponding percentiles were estimated as a function of gestational age. The estimated rates of frontal lobe growth were 0.096 cm/week, 0.247 cm/week, and 0.111 cm/week for length, width, and height.

CONCLUSION

To our knowledge, this is the first study to examine fetal frontal lobe growth trajectories through 3D prenatal ultrasound examination. Such normative data will allow for future prenatal evaluation of a particular disease state by 3D ultrasound imaging.

Vestibulo-ocular reflex function in children with high-functioning autism spectrum disorders

Sensorimotor processing alterations are a growing focus in the assessment and treatment of Autism Spectrum Disorders (ASD). The rotational vestibulo-ocular reflex (rVOR), which functions to maintain stable vision during head movements, is a sensorimotor system that may be useful in understanding such alterations and their underlying neurobiology. In this study, we assessed post-rotary nystagmus elicited by continuous whole body rotation among children with high-functioning ASD and typically developing children. Children with ASD exhibited increased rVOR gain, the ratio of eye velocity to head velocity, indicating a possible lack of cerebellar inhibitory input to brainstem vestibular nuclei in this population. The ASD group also showed less regular or periodic horizontal eye movements as indexed by greater variance accounted for by multiple higher frequency bandwidths as well as greater entropy scores compared to typically developing children. The decreased regularity or dysrhythmia in the temporal structure of nystagmus beats in children with ASD may be due to alterations in cerebellum and brainstem circuitry. These findings could potentially serve as a model to better understand the functional effects of differences in these brain structures in ASD. Autism Res 2017, 10: 251-266. © 2016 International Society for Autism Research, Wiley Periodicals, Inc.

Studying Autism Spectrum Disorder with Structural and Diffusion Magnetic Resonance Imaging: A Survey

Magnetic resonance imaging (MRI) modalities have emerged as powerful means that facilitate non-invasive clinical diagnostics of various diseases and abnormalities since their inception in the 1980s. Multiple MRI modalities, such as different types of the sMRI and DTI, have been employed to investigate facets of ASD in order to better understand this complex syndrome. This paper reviews recent applications of structural magnetic resonance imaging (sMRI) and diffusion tensor imaging (DTI), to study autism spectrum disorder (ASD). Main reported findings are sometimes contradictory due to different age ranges, hardware protocols, population types, numbers of participants, and image analysis parameters. The primary anatomical structures, such as amygdalae, cerebrum, and cerebellum, associated with clinical-pathological correlates of ASD are highlighted through successive life stages, from infancy to adulthood. This survey demonstrates the absence of consistent pathology in the brains of autistic children and lack of research investigations in patients under 2 years of age in the literature. The known publications also emphasize advances in data acquisition and analysis, as well as significance of multimodal approaches that combine resting-state, task-evoked, and sMRI measures. Initial results obtained with the sMRI and DTI show good promise toward the early and non-invasive ASD diagnostics.

Neuroanatomical variation in autism spectrum disorder: A comprehensive review

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by impairments in socialization, communication, and behavior. Many investigators have described the anatomical abnormalities in autistic brains, in an attempt to correlate them with the manifestations of ASD. Herein, we reviewed all the available literature about the neuroanatomical findings in ASD available via "PubMed" and "Google Scholar." References found in review articles were also searched manually. There was substantial discrepancy throughout the literature regarding the reported presence and significance of neuroanatomical findings in ASD, and this is thoroughly discussed in the present review.

Neurodevelopmental sequelae associated with gray and white matter changes and their cellular basis: A comparison between Autism Spectrum Disorder, ADHD and dyslexia

Many psychiatric diseases, such as major depression and schizophrenia, are accompanied by patterns of gray matter and white matter changes in the cortex that may be due to structural pathologies of synapses and their dendrites in the gray matter on the one hand and to pathologies in myelinating oligodendrocytes on the other. Here the possibility has been briefly examined that such a generalization might also hold for Autistic Spectrum Disorders (ASD). Evidence is presented that gray matter changes that accompany ASD may in fact reflect changes in synapses and subsequently of their dendrites, whereas those in the white matter reflect changes in myelination due to pathologies of oligodendrocytes. It is proposed that such structural pathologies during development provide a coherent biological model not only for the onset and course of ASD but also provide the basis for development and systematic evaluation of new treatment strategies.

MRI Surface-Based Brain Morphometry in Egyptian Autistic and Typically Developing Children

OBJECTIVES

The verbal abilities of autistic children differ from those of typically developing ones and they also differ among autistic children themselves. Neuroanatomical changes and an abnormal organization of functional networks are expected to accompany such a neurodevelopmental disorder. The aim of this study was to delineate the brain neuroanatomical changes in Egyptian children with autism and to compare them with previous studies in order to add more insight into the global brain imaging deviations linked to autism.

PATIENTS AND METHODS

Twenty-five autistic children and 25 typically developing children underwent MRI. Further analysis was performed using surface-based morphometry to obtain cortical thickness, brain volume, and cortical complexity.

RESULTS

MRI analysis results revealed significantly greater cortical thickness, cortical complexity, and gray matter volume in the autistic as compared to the control group. On the other hand, the white matter volume was significantly smaller.

CONCLUSION

These findings generally align with findings in previous studies, except for occasional differences.

Disorder-specific grey matter deficits in attention deficit hyperactivity disorder relative to autism spectrum disorder

BACKGROUND

Attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) are two common childhood disorders that exhibit genetic and behavioural overlap and have abnormalities in similar brain systems, in particular in frontal and cerebellar regions. This study compared the two neurodevelopmental disorders to investigate shared and disorder-specific structural brain abnormalities.

METHOD

Forty-four predominantly medication-naïve male adolescents with ADHD, 19 medication-naïve male adolescents with ASD and 33 age-matched healthy male controls were scanned using high-resolution T1-weighted volumetric imaging in a 3-T magnetic resonance imaging (MRI) scanner. Voxel-based morphometry (VBM) was used to test for group-level differences in structural grey matter (GM) and white matter (WM) volumes.

RESULTS

There was a significant group difference in the GM of the right posterior cerebellum and left middle/superior temporal gyrus (MTG/STG). Post-hoc analyses revealed that this was due to ADHD boys having a significantly smaller right posterior cerebellar GM volume compared to healthy controls and ASD boys, who did not differ from each other. ASD boys had a larger left MTG/STG GM volume relative to healthy controls and at a more lenient threshold relative to ADHD boys.

CONCLUSIONS

The study shows for the first time that the GM reduction in the cerebellum in ADHD is disorder specific relative to ASD whereas GM enlargement in the MTG/STG in ASD may be disorder specific relative to ADHD. This study is a first step towards elucidating disorder-specific structural biomarkers for these two related childhood disorders.

Integrative proteomic analysis of the NMDA NR1 knockdown mouse model reveals effects on central and peripheral pathways associated with schizophrenia and autism spectrum disorders

Background

Over the last decade, the transgenic N-methyl-D-aspartate receptor (NMDAR) NR1-knockdown mouse (NR1^neo−/−) has been investigated as a glutamate hypofunction model for schizophrenia. Recent research has now revealed that the model also recapitulates cognitive and negative symptoms in the continuum of other psychiatric diseases, particularly autism spectrum disorders (ASD). As previous studies have mostly focussed on behavioural readouts, a molecular characterisation of this model will help to identify novel biomarkers or potential drug targets.

Methods

Here, we have used multiplex immunoassay analyses to investigate peripheral analyte alterations in serum of NR1^neo−/− mice, as well as a combination of shotgun label-free liquid chromatography mass spectrometry, bioinformatic pathway analyses, and a shotgun-based 40-plex selected reaction monitoring (SRM) assay to investigate altered molecular pathways in the frontal cortex and hippocampus. All findings were cross compared to identify translatable findings between the brain and periphery.

Results

Multiplex immunoassay profiling led to identification of 29 analytes that were significantly altered in sera of NR1^neo−/− mice. The highest magnitude changes were found for neurotrophic factors (VEGFA, EGF, IGF-1), apolipoprotein A1, and fibrinogen. We also found decreased levels of several chemokines. Following this, LC-MS^E profiling led to identification of 48 significantly changed proteins in the frontal cortex and 41 in the hippocampus. In particular, MARCS, the mitochondrial pyruvate kinase, and CamKII-alpha were affected. Based on the combination of protein set enrichment and bioinformatic pathway analysis, we designed orthogonal SRM-assays which validated the abnormalities of proteins involved in synaptic long-term potentiation, myelination, and the ERK-signalling pathway in both brain regions. In contrast, increased levels of proteins involved in neurotransmitter metabolism and release were found only in the frontal cortex and abnormalities of proteins involved in the purinergic system were found exclusively in the hippocampus.

Conclusions

Taken together, this multi-platform profiling study has identified peripheral changes which are potentially linked to central alterations in synaptic plasticity and neuronal function associated with NMDAR-NR1 hypofunction. Therefore, the reported proteomic changes may be useful as translational biomarkers in human and rodent model drug discovery efforts.

Typical and atypical brain development: a review of neuroimaging studies

In the course of development, the brain undergoes a remarkable process of restructuring as it adapts to the environment and becomes more efficient in processing information. A variety of brain imaging methods can be used to probe how anatomy, connectivity, and function change in the developing brain. Here we review recent discoveries regarding these brain changes in both typically developing individuals and individuals with neurodevelopmental disorders. We begin with typical development, summarizing research on changes in regional brain volume and tissue density, cortical thickness, white matter integrity, and functional connectivity. Space limits preclude the coverage of all neurodevelopmental disorders; instead, we cover a representative selection of studies examining neural correlates of autism, attention deficit/hyperactivity disorder, Fragile X, 22q11.2 deletion syndrome, Williams syndrome, Down syndrome, and Turner syndrome. Where possible, we focus on studies that identify an age by diagnosis interaction, suggesting an altered developmental trajectory. The studies we review generally cover the developmental period from infancy to early adulthood. Great progress has been made over the last 20 years in mapping how the brain matures with MR technology. With ever-improving technology, we expect this progress to accelerate, offering a deeper understanding of brain development, and more effective interventions for neurodevelopmental disorders.

Low maternal progesterone may contribute to both obstetrical complications and autism

Studies show increased autism risk among children born to mothers experiencing obstetrical complications. Although this is usually interpreted as suggesting that the obstetrical complications could be causing autism, it is possible that a single factor could be responsible for both complications and autism. We hypothesized that low levels of the hormone progesterone is responsible since it is supplied to the fetus maternally and does not only support pregnancy but also promotes brain development. Following a review of the literature, we report findings from a survey of mothers of autistic children (n=86) compared to mothers of typically-developing children (n=88) regarding obstetrical histories, including five obstetrical risk factors indicative of low progesterone. Using this analysis, the ASD group had significantly more risk factors than controls (1.21 ± 0.09 vs. 0.76 ± 0.08, p<.0001), suggesting low progesterone. Thus, results suggest that low progesterone may be responsible for both obstetrical complications and brain changes associated with autism and that progesterone levels should be routinely monitored in at-risk pregnancies. Our hypothesis also suggests that ensuring adequate levels of progesterone may decrease the likelihood of autism.

Defining the contribution of CNTNAP2 to autism susceptibility

Multiple lines of genetic evidence suggest a role for CNTNAP2 in autism. To assess its population impact we studied 2148 common single nucleotide polymorphisms (SNPs) using transmission disequilibrium test (TDT) across the entire ~3.3 Mb CNTNAP2 locus in 186 (408 trios) multiplex and 323 simplex families with autistic spectrum disorder (ASD). This analysis yielded two SNPs with nominal statistical significance (rs17170073, p = 2.0 x 10^-4; rs2215798, p = 1.6 x 10^-4) that did not survive multiple testing. In a combined analysis of all families, two highly correlated (r² = 0.99) SNPs in intron 14 showed significant association with autism (rs2710093, p = 9.0 x 10^-6; rs2253031, p = 2.5 x 10^-5). To validate these findings and associations at SNPs from previous autism studies (rs7794745, rs2710102 and rs17236239) we genotyped 2051 additional families (572 multiplex and 1479 simplex). None of these variants were significantly associated with ASD after corrections for multiple testing. The analysis of Mendelian errors within each family did not indicate any segregating deletions. Nevertheless, a study of CNTNAP2 gene expression in brains of autistic patients and of normal controls, demonstrated altered expression in a subset of patients (p = 1.9 x10^-5). Consequently, this study suggests that although CNTNAP2 dysregulation plays a role in some cases, its population contribution to autism susceptibility is limited.

Computational analysis of LDDMM for brain mapping

One goal of computational anatomy (CA) is to develop tools to accurately segment brain structures in healthy and diseased subjects. In this paper, we examine the performance and complexity of such segmentation in the framework of the large deformation diffeomorphic metric mapping (LDDMM) registration method with reference to atlases and parameters. First we report the application of a multi-atlas segmentation approach to define basal ganglia structures in healthy and diseased kids' brains. The segmentation accuracy of the multi-atlas approach is compared with the single atlas LDDMM implementation and two state-of-the-art segmentation algorithms-Freesurfer and FSL-by computing the overlap errors between automatic and manual segmentations of the six basal ganglia nuclei in healthy subjects as well as subjects with diseases including ADHD and Autism. The high accuracy of multi-atlas segmentation is obtained at the cost of increasing the computational complexity because of the calculations necessary between the atlases and a subject. Second, we examine the effect of parameters on total LDDMM computation time and segmentation accuracy for basal ganglia structures. Single atlas LDDMM method is used to automatically segment the structures in a population of 16 subjects using different sets of parameters. The results show that a cascade approach and using fewer time steps can reduce computational complexity as much as five times while maintaining reliable segmentations.

Current progress and challenges in the search for autism biomarkers

Autism spectrum disorders (ASD) encompass a range of neurodevelopmental conditions that are clinically and etiologically very heterogeneous. ASD is currently diagnosed entirely on behavioral criteria, but intensive research efforts are focused on identifying biological markers for disease risk and early diagnosis. Here, we discuss recent progress toward identifying biological markers for ASD and highlight specific challenges as well as ethical aspects of translating ASD biomarker research into the clinic.

"Normative content" and health inequity enculturation: a logic model of men's health advocacy

Epidemiologic studies and related literature consistently report that males have fewer years of life expectancy than females. Moreover, males experience fewer quality years of life in that they tend to live with greater rates of morbidity such as heart disease, cancer, and diabetes among other conditions. Causal evidence traditionally highlights the role of biology in determining the life course for males. However, emerging literature suggests that social determinants of health play a more central role in male morbidity and mortality, and thus contribute to health inequities between the sexes. The purpose of this article is to explore core concepts of social determinants of health as they pertain to male health inequities and provide a systematic conceptualization of how society has become encultured to view these inequities as "normative." Strategies to improve male health are discussed using a logic model to illustrate male health advocacy in the face of the social climes of encultured health inequities.

Disease and genetic contributions toward local tissue volume disturbances in schizophrenia: a tensor-based morphometry study

Structural brain deficits, especially frontotemporal volume reduction and ventricular enlargement, have been repeatedly reported in patients with schizophrenia. However, it remains unclear whether brain structural deformations may be attributable to disease-related or genetic factors. In this study, the structural magnetic resonance imaging data of 48 adult-onset schizophrenia patients, 65 first-degree nonpsychotic relatives of schizophrenia patients, 27 community comparison (CC) probands, and 73 CC relatives were examined using tensor-based morphometry (TBM) to isolate global and localized differences in tissue volume across the entire brain between groups. We found brain tissue contractions most prominently in frontal and temporal regions and expansions in the putamen/pallidum, and lateral and third ventricles in schizophrenia patients when compared with unrelated CC probands. Results were similar, though less prominent when patients were compared with their nonpsychotic relatives. Structural deformations observed in unaffected patient relatives compared to age-similar CC relatives were suggestive of schizophrenia-related genetic liability and were pronounced in the putamen/pallidum and medial temporal regions. Schizophrenia and genetic liability effects for the putamen/pallidum were confirmed by regions-of-interest analysis. In conclusion, TBM findings complement reports of frontal, temporal, and ventricular dysmorphology in schizophrenia and further indicate that putamen/pallidum enlargements, originally linked mainly with medication exposure in early studies, also reflect a genetic predisposition for schizophrenia. Thus, brain deformation profiles revealed in this study may help to clarify the role of specific genetic or environmental risk factors toward altered brain morphology in schizophrenia.

Modeling psychiatric disorders at the cellular and network levels

Although psychiatric disorders such as autism spectrum disorders, schizophrenia and bipolar disorder affect a number of brain regions and produce a complex array of clinical symptoms, basic phenotypes likely exist at the level of single neurons and simple networks. Being highly heritable, it is hypothesized that these disorders are amenable to cell-based studies in vitro. Using induced pluripotent stem cell-derived neurons and/or induced neurons from fibroblasts, limitless numbers of live human neurons can now be generated from patients with a genetic background permissive to the disease state. We predict that cell-based studies will ultimately contribute to our understanding of the initiation, progression and treatment of these psychiatric disorders.

Autism spectrum disorder: does neuroimaging support the DSM-5 proposal for a symptom dyad? A systematic review of functional magnetic resonance imaging and diffusion tensor imaging studies

A systematic review of 208 studies comprising functional magnetic resonance imaging and diffusion tensor imaging data in patients with 'autism spectrum disorder' (ASD) was conducted, in order to determine whether these data support the forthcoming DSM-5 proposal of a social communication and behavioral symptom dyad. Studies consistently reported abnormal function and structure of fronto-temporal and limbic networks with social and pragmatic language deficits, of temporo-parieto-occipital networks with syntactic-semantic language deficits, and of fronto-striato-cerebellar networks with repetitive behaviors and restricted interests in ASD patients. Therefore, this review partially supports the DSM-5 proposal for the ASD dyad.

Voxelwise multivariate statistics and brain-wide machine learning using the full diffusion tensor

In this paper, we propose to use the full diffusion tensor to perform brain-wide score prediction on diffusion tensor imaging (DTI) using the log-Euclidean framework., rather than the commonly used fractional anisotropy (FA). Indeed, scalar values such as the FA do not capture all the information contained in the diffusion tensor. Additionally, full tensor information is included in every step of the pre-processing pipeline: registration, smoothing and feature selection using voxelwise multivariate regression analysis. This approach was tested on data obtained from 30 children and adolescents with autism spectrum disorder and showed some improvement over the FA-only analysis.

Involvement of the anterior thalamic radiation in boys with high functioning autism spectrum disorders: a Diffusion Tensor Imaging study

BACKGROUND

Autism has been hypothesized to reflect neuronal disconnection. Several recent reports implicate the key thalamic relay nuclei and cortico-thalamic connectivity in the pathophysiology of autism. Accordingly, we aimed to focus on evaluating the integrity of the thalamic radiation and sought to replicate prior white matter findings in Korean boys with high-functioning autism spectrum disorders (ASD) using Diffusion Tensor Imaging (DTI).

METHODS

We compared fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD) and radial diffusivity (RD) in 17 boys with ASD and 17 typically developing controls in the anterior thalamic radiation (ATR), superior thalamic radiation (STR), posterior thalamic radiation (PTR), corpus callosum (CC), uncinate fasciculus (UF) and inferior longitudinal fasciculus (ILF).

RESULTS

The two groups were group-matched on age, IQ, handedness and head circumference. In whole-brain voxel-wise analyses, FA was significantly reduced and MD was significantly increased in the right ATR, CC, and left UF in subjects with ASD (p<0.05, corrected). We found significantly lower FA in right and left ATR, CC, left UF and right and left ILF and significantly higher MD values of the CC in the ASD group in region of interest-based analyses. We also observed significantly higher RD values of right and left ATR, CC, left UF, left ILF in subjects with ASD compared to typically developing boys and significantly lower AD values of both ILF. Right ATR and right UF FA was significantly negatively correlated with total SRS score within the ASD group (r=-.56, p=.02).

CONCLUSIONS

Our preliminary findings support evidence implicating disturbances in the thalamo-frontal connections in autism. These findings highlight the role of hypoconnectivity between the frontal cortex and thalamus in ASD.

Mapping fetal brain development in utero using magnetic resonance imaging: the Big Bang of brain mapping

The development of tools to construct and investigate probabilistic maps of the adult human brain from magnetic resonance imaging (MRI) has led to advances in both basic neuroscience and clinical diagnosis. These tools are increasingly being applied to brain development in adolescence and childhood, and even to neonatal and premature neonatal imaging. Even earlier in development, parallel advances in clinical fetal MRI have led to its growing use as a tool in challenging medical conditions. This has motivated new engineering developments encompassing optimal fast MRI scans and techniques derived from computer vision, the combination of which allows full 3D imaging of the moving fetal brain in utero without sedation. These promise to provide a new and unprecedented window into early human brain growth. This article reviews the developments that have led us to this point, examines the current state of the art in the fields of fast fetal imaging and motion correction, and describes the tools to analyze dynamically changing fetal brain structure. New methods to deal with developmental tissue segmentation and the construction of spatiotemporal atlases are examined, together with techniques to map fetal brain growth patterns.

Structural MRI in autism spectrum disorder

Magnetic resonance (MR) examination provides a powerful tool for investigating brain structural changes in children with autism spectrum disorder (ASD). We review recent advances in the understanding of structural MR correlates of ASD. We summarize findings from studies based on voxel-based morphometry, surface-based morphometry, tensor-based morphometry, and diffusion-tensor imaging. Finally, we discuss diagnostic models of ASD based on MR-derived features.

Structural and functional magnetic resonance imaging of autism spectrum disorders

The neurobiology of autism spectrum disorders (ASDs) has become increasingly understood since the advent of magnetic resonance imaging (MRI). Initial observations of an above-average head circumference were supported by structural MRI studies that found evidence of increased total brain volume and early rapid brain overgrowth in affected individuals. Subsequent research revealed consistent abnormalities in cortical gray and white matter volume in ASDs. The structural integrity and orientation of white matter have been further elucidated via diffusion tensor imaging methods. The emergence of functional MRI techniques led to an enhanced understanding of the neural circuitry of ASDs, demonstrating areas of dysfunctional cortical activation and atypical cortical specialization. These studies have provided evidence of underconnectivity in distributed cortical networks integral to the core impairments associated with ASDs. Abnormalities in the default-mode network during the resting state have also been identified. Overall, structural and functional MRI research has generated important insights into the neurobiology of ASDs. Additional research is needed to further delineate the underlying brain basis of this constellation of disorders.

Differentiating prenatal exposure to methamphetamine and alcohol versus alcohol and not methamphetamine using tensor-based brain morphometry and discriminant analysis

Here we investigate the effects of prenatal exposure to methamphetamine (MA) on local brain volume using magnetic resonance imaging. Because many who use MA during pregnancy also use alcohol, a known teratogen, we examined whether local brain volumes differed among 61 children (ages 5-15 years), 21 with prenatal MA exposure, 18 with concomitant prenatal alcohol exposure (the MAA group), 13 with heavy prenatal alcohol but not MA exposure (ALC group), and 27 unexposed controls. Volume reductions were observed in both exposure groups relative to controls in striatal and thalamic regions bilaterally and in right prefrontal and left occipitoparietal cortices. Striatal volume reductions were more severe in the MAA group than in the ALC group, and, within the MAA group, a negative correlation between full-scale intelligence quotient (FSIQ) scores and caudate volume was observed. Limbic structures, including the anterior and posterior cingulate, the inferior frontal gyrus (IFG), and ventral and lateral temporal lobes bilaterally, were increased in volume in both exposure groups. Furthermore, cingulate and right IFG volume increases were more pronounced in the MAA than ALC group. Discriminant function analyses using local volume measurements and FSIQ were used to predict group membership, yielding factor scores that correctly classified 72% of participants in jackknife analyses. These findings suggest that striatal and limbic structures, known to be sites of neurotoxicity in adult MA abusers, may be more vulnerable to prenatal MA exposure than alcohol exposure and that more severe striatal damage is associated with more severe cognitive deficit.

Multivariate tensor-based morphometry on surfaces: application to mapping ventricular abnormalities in HIV/AIDS

Here we developed a new method, called multivariate tensor-based surface morphometry (TBM), and applied it to study lateral ventricular surface differences associated with HIV/AIDS. Using concepts from differential geometry and the theory of differential forms, we created mathematical structures known as holomorphic one-forms, to obtain an efficient and accurate conformal parameterization of the lateral ventricular surfaces in the brain. The new meshing approach also provides a natural way to register anatomical surfaces across subjects, and improves on prior methods as it handles surfaces that branch and join at complex 3D junctions. To analyze anatomical differences, we computed new statistics from the Riemannian surface metrics-these retain multivariate information on local surface geometry. We applied this framework to analyze lateral ventricular surface morphometry in 3D MRI data from 11 subjects with HIV/AIDS and 8 healthy controls. Our method detected a 3D profile of surface abnormalities even in this small sample. Multivariate statistics on the local tensors gave better effect sizes for detecting group differences, relative to other TBM-based methods including analysis of the Jacobian determinant, the largest and smallest eigenvalues of the surface metric, and the pair of eigenvalues of the Jacobian matrix. The resulting analysis pipeline may improve the power of surface-based morphometry studies of the brain.