New Insights into the Developing Rabbit Brain Using Diffusion Tensor Tractography and Generalized q-Sampling MRI

The use of modern neuroimaging methods to characterize the complex anatomy of brain development at different stages reveals an enormous wealth of information in understanding this highly ordered process and provides clues to detect neurological and neurobehavioral disorders that have their origin in early structural and functional cerebral maturation. Non-invasive diffusion tensor magnetic resonance imaging (DTI) is able to distinguish cerebral microscopic structures, especially in the white matter regions. However, DTI is unable to resolve the complicated neural structure, i.e., the fiber crossing that is frequently observed during the maturation process. To overcome this limitation, several methods have been proposed. One such method, generalized q-sampling imaging (GQI), can be applied to a variety of datasets, including the single shell, multi-shell or grid sampling schemes that are believed to be able to resolve the complicated crossing fibers. Rabbits have been widely used for neurodevelopment research because they exhibit human-like timing of perinatal brain white matter maturation. Here, we present a longitudinal study using both DTI and GQI to demonstrate the changes in cerebral maturation of in vivo developing rabbit brains over a period of 40 weeks. Fractional anisotropy (FA) of DTI and generalized fractional anisotropy (GFA) of GQI indices demonstrated that the white matter anisotropy increased with age, with GFA exhibiting an increase in the hippocampus as well. Normalized quantitative anisotropy (NQA) of GQI also revealed an increase in the hippocampus, allowing us to observe the changes in gray matter as well. Regional and whole brain DTI tractography also demonstrated refinement in fiber pathway architecture with maturation. We concluded that DTI and GQI results were able to characterize the white matter anisotropy changes, whereas GQI provided further information about the gray matter hippocampus area. This developing rabbit brain DTI and GQI database could also be used for educational purposes and neuroscience investigations.     

Convergent Findings of Altered Functional and Structural Brain Connectivity in Individuals with High Functioning Autism: A Multimodal MRI Study

Brain tissue changes in autism spectrum disorders seem to be rather subtle and widespread than anatomically distinct. Therefore a multimodal, whole brain imaging technique appears to be an appropriate approach to investigate whether alterations in white and gray matter integrity relate to consistent changes in functional resting state connectivity in individuals with high functioning autism (HFA). We applied diffusion tensor imaging (DTI), voxel-based morphometry (VBM) and resting state functional connectivity magnetic resonance imaging (fcMRI) to assess differences in brain structure and function between 12 individuals with HFA (mean age 35.5, SD 11.4, 9 male) and 12 healthy controls (mean age 33.3, SD 9.0, 8 male). Psychological measures of empathy and emotionality were obtained and correlated with the most significant DTI, VBM and fcMRI findings. We found three regions of convergent structural and functional differences between HFA participants and controls. The right temporo-parietal junction area and the left frontal lobe showed decreased fractional anisotropy (FA) values along with decreased functional connectivity and a trend towards decreased gray matter volume. The bilateral superior temporal gyrus displayed significantly decreased functional connectivity that was accompanied by the strongest trend of gray matter volume decrease in the temporal lobe of HFA individuals. FA decrease in the right temporo-parietal region was correlated with psychological measurements of decreased emotionality. In conclusion, our results indicate common sites of structural and functional alterations in higher order association cortex areas and may therefore provide multimodal imaging support to the long-standing hypothesis of autism as a disorder of impaired higher-order multisensory integration.     

Probing the Brain in Autism Using fMRI and Diffusion Tensor Imaging

Newly emerging theories suggest that the brain does not function as a cohesive unit in autism, and this discordance is reflected in the behavioral symptoms displayed by individuals with autism. While structural neuroimaging findings have provided some insights into brain abnormalities in autism, the consistency of such findings is questionable. Functional neuroimaging, on the other hand, has been more fruitful in this regard because autism is a disorder of dynamic processing and allows examination of communication between cortical networks, which appears to be where the underlying problem occurs in autism. Functional connectivity is defined as the temporal correlation of spatially separate neurological events1. Findings from a number of recent fMRI studies have supported the idea that there is weaker coordination between different parts of the brain that should be working together to accomplish complex social or language problems^2,3,4,5,6. One of the mysteries of autism is the coexistence of deficits in several domains along with relatively intact, sometimes enhanced, abilities. Such complex manifestation of autism calls for a global and comprehensive examination of the disorder at the neural level. A compelling recent account of the brain functioning in autism, the cortical underconnectivity theory,^2,7 provides an integrating framework for the neurobiological bases of autism. The cortical underconnectivity theory of autism suggests that any language, social, or psychological function that is dependent on the integration of multiple brain regions is susceptible to disruption as the processing demand increases. In autism, the underfunctioning of integrative circuitry in the brain may cause widespread underconnectivity. In other words, people with autism may interpret information in a piecemeal fashion at the expense of the whole. Since cortical underconnectivity among brain regions, especially the frontal cortex and more posterior areas ^3,6, has now been relatively well established, we can begin to further understand brain connectivity as a critical component of autism symptomatology.A logical next step in this direction is to examine the anatomical connections that may mediate the functional connections mentioned above. Diffusion Tensor Imaging (DTI) is a relatively novel neuroimaging technique that helps probe the diffusion of water in the brain to infer the integrity of white matter fibers. In this technique, water diffusion in the brain is examined in several directions using diffusion gradients. While functional connectivity provides information about the synchronization of brain activation across different brain areas during a task or during rest, DTI helps in understanding the underlying axonal organization which may facilitate the cross-talk among brain areas. This paper will describe these techniques as valuable tools in understanding the brain in autism and the challenges involved in this line of research. Download video file.^{(73M, mov)}     

Brain IL-6 elevation causes neuronal circuitry imbalances and mediates autism-like behaviors

Abnormal immune responses have been reported to be associated with autism. A number of studies showed that cytokines were increased in the blood, brain, and cerebrospinal fluid of autistic subjects. Elevated IL-6 in autistic brain has been a consistent finding. However, the mechanisms by which IL-6 may be involved in the pathogenesis of autism are not well understood. Here we show that mice with elevated IL-6 in the brain display many autistic features, including impaired cognitive abilities, deficits in learning, abnormal anxiety traits and habituations, as well as decreased social interactions. IL-6 elevation caused alterations in excitatory and inhibitory synaptic formations and disrupted the balance of excitatory/inhibitory synaptic transmissions. IL-6 elevation also resulted in an abnormal change in the shape, length and distributing pattern of dendritic spines. These findings suggest that IL-6 elevation in the brain could mediate autistic-like behaviors, possibly through the imbalances of neural circuitry and impairments of synaptic plasticity.     

Population Differences in Brain Morphology and Microstructure among Chinese,Malay, and Indian Neonates

We studied a sample of 75 Chinese, 73 Malay, and 29 Indian healthy neonates taking part in a cohort study to examine potential differences in neonatal brain morphology and white matter microstructure as a function of ethnicity using both structural T2-weighted magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). We first examined the differences in global size and morphology of the brain among the three groups. We then constructed the T2-weighted MRI and DTI atlases and employed voxel-based analysis to investigate ethnic differences in morphological shape of the brain from the T2-weighted MRI, and white matter microstructure measured by fractional anisotropy derived from DTI. Compared with Malay neonates, the brains of Indian neonates’ tended to be more elongated in anterior and posterior axis relative to the superior-inferior axis of the brain even though the total brain volume was similar among the three groups. Although most anatomical regions of the brain were similar among Chinese, Malay, and Indian neonates, there were anatomical variations in the spinal-cerebellar and cortical-striatal-thalamic neural circuits among the three populations. The population-related brain regions highlighted in our study are key anatomical substrates associated with sensorimotor functions.     

Examination of Cognitive Fatigue in Multiple Sclerosis using Functional Magnetic Resonance Imaging and Diffusion Tensor Imaging

The present study investigated the neural correlates of cognitive fatigue in Multiple Sclerosis (MS), looking specifically at the relationship between self-reported fatigue and objective measures of cognitive fatigue. In Experiment 1, functional magnetic resonance imaging (fMRI) was used to examine where in the brain BOLD activity covaried with “state” fatigue, assessed during performance of a task designed to induce cognitive fatigue while in the scanner. In Experiment 2, diffusion tensor imaging (DTI) was used to examine where in the brain white matter damage correlated with increased “trait” fatigue in individuals with MS, assessed by the Fatigue Severity Scale (FSS) completed outside the scanning session. During the cognitively fatiguing task, the MS group had increased brain activity associated with fatigue in the caudate as compared with HCs. DTI findings revealed that reduced fractional anisotropy in the anterior internal capsule was associated with increased self-reported fatigue on the FSS. Results are discussed in terms of identifying a “fatigue-network” in MS.     

Spatio-Temporal Correlation Tensors Reveal Functional Structure in Human Brain

Resting state functional magnetic resonance imaging (fMRI) has been commonly used to measure functional connectivity between cortical regions, while diffusion tensor imaging (DTI) can be used to characterize structural connectivity of white matter tracts. In principle combining resting state fMRI and DTI data could allow characterization of structure-function relations of distributed neural networks. However, due to differences in the biophysical origins of their signals and in the tissues to which they apply, there has been no direct integration of these techniques to date. We demonstrate that MRI signal variations and power spectra in a resting state are largely comparable between gray matter and white matter, that there are temporal correlations of fMRI signals that persist over long distances within distinct white matter structures, and that neighboring intervoxel correlations of low frequency resting state signals showed distinct anisotropy in many regions. These observations suggest that MRI signal variations from within white matter in a resting state may convey similar information as their corresponding fluctuations of MRI signals in gray matter. We thus derive a local spatio-temporal correlation tensor which captures directional variations of resting-state correlations and which reveals distinct structures in both white and gray matter. This novel concept is illustrated with in vivo experiments in a resting state, which demonstrate the potential of the technique for mapping the functional structure of neural networks and for direct integration of structure-function relations in the human brain.     

Behavioral phenotypes in males with XYY and possible role of increased NLGN4Y expression in autism features

The male sex chromosome disorder, 47,XYY syndrome (XYY), is associated with increased risk for social‐emotional difficulties, attention‐deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD). We hypothesize that increased Y chromosome gene copy number in XYY leads to overexpression of Y‐linked genes related to brain development and function, thereby increasing risk for these phenotypes. We measured expression in blood of two Y genes NLGN4Y and RPS4Y in 26 boys with XYY and 11 male controls and evaluated whether NLGN4Y expression correlates with anxiety, ADHD, depression and autistic behaviors (from questionnaires) in boys with XYY. The XYY cohort had increased risk of ASD behaviors on the social responsiveness scale (SRS) and increased attention deficits on the Conners' DSM‐IV inattention and hyperactive scales. In contrast, there was no increase in reported symptoms of anxiety or depression by the XYY group. Peripheral expression of two Y genes in boys with XYY vs. typically developing controls was increased twofold in the XYY group. Results from the SRS total and autistic mannerisms scales, but not from the attention, anxiety or depression measures, correlated with peripheral expression of NLGN4Y in boys with XYY. Males with XYY have social phenotypes that include increased risk for autism‐related behaviors and ADHD. Expression of NLGN4Y, a gene that may be involved in synaptic function, is increased in boys with XYY, and the level of expression correlates with overall social responsiveness and autism symptoms. Thus, further investigation of NLGN4Y as a plausible ASD risk gene in XYY is warranted.     

Structural neuroimaging in autism

Structural neuroimaging studies done by means of magnetic resonance imaging (MRI) have provided important insights into the neurobiological basis for autism. The aim of this article is to review the current state of knowledge regarding structural brain abnormalities in autism. Results of MRI studies dealing with total brain volume, the volume of the cerebellum, caudate nucleus, thalamus, amygdala, hippocampus and the area of the corpus callosum are summarized. Existing research suggests that autistic individuals have larger total brain, cerebellar and caudate nucleus volumes; however, the area of the corpus callosum is reduced. Results of studies involving the amygdala and hippocampus volume in autistic subjects remain inconsistent and no changes have been detected in thalamic volume.     

Levels of Bcl-2 and P53 Are Altered in Superior Frontal and Cerebellar Cortices of Autistic Subjects

1. Autistic disease (AD) is a severe neuropsychiatric disorder affecting 2-4 children per 10,000. We have recently shown reduction of Bcl-2 and increase in P53, two important markers of apoptosis, in parietal cortex of autistic subjects. 2. We hypothesized that brain levels of Bcl-2 and P53 would also be altered in superior frontal cortex and cerebellum of age-, sex, and postmortem-interval (PMI)-matched autistic subjects (N = 5 autistic, N = 4 controls). 3. Brain extracts were prepared from superior frontal cortex and cerebellum and subjected to Western blotting. 4. Results showed that levels of Bcl-2 decreased by 38% and 36% in autistic superior frontal and cerebellar cortices, respectively when compared to control tissues. By the same token, levels of P53 increased by 67.5% and 38% in the same brain areas in autistic subjects vs. controls respectively. Calculations of ratios of Bcl-2/P53 values also decreased by 75% and 43% in autistic frontal and cerebellar cortices vs. controls respectively. The autistic cerebellar values were significantly reduced (p < 0.08) vs. control only. There were no significant differences in levels of beta-actin between the two groups. Additionally, there were no correlations between Bcl-2, P53, and beta-actin concentrations vs. age or PMI in either group. 5. These results confirm and extend previous data that levels of Bcl-2 and P53 are altered in three important brain tissues, i.e. frontal, parietal, and cerebellar cortices of autistic subjects, alluding to deranged apoptotic mechanisms in autism.     

Interhemispheric Functional and Structural Disconnection in Alzheimer’s Disease: A Combined Resting-State fMRI and DTI Study

Neuroimaging studies have demonstrated that patients with Alzheimer’s disease presented disconnection syndrome. However, little is known about the alterations of interhemispheric functional interactions and underlying structural connectivity in the AD patients. In this study, we combined resting-state functional MRI and diffusion tensor imaging (DTI) to investigate interhemispheric functional and structural connectivity in 16 AD, 16 mild cognitive impairment (MCI), as well as 16 cognitive normal healthy subjects (CN). The pattern of the resting state interhemispheric functional connectivity was measured with a voxel-mirrored homotopic connectivity (VMHC) method. Decreased VMHC was observed in AD and MCI subjects in anterior brain regions including the prefrontal cortices and subcortical regions with a pattern of AD<MCI<CN. Increased VMHC was observed in MCI subjects in posterior brain regions with patterns of AD/CN < MCI (sensorimotor cortex) and AD < CN/MCI (occipital gyrus). DTI analysis showed the most significant difference among the three cohorts was the fractional anisotropy in the genu of corpus callosum, which was positively associated with the VMHC of prefrontal and subcortical regions. Across all the three cohorts, the diffusion parameters in the genu of corpus callosum and VMHC in the above brain regions had significant correlation with the cognitive performance. These results demonstrate that there are specific patterns of interhemispheric functional connectivity changes in the AD and MCI, which can be significantly correlated with the integrity changes in the midline white matter structures. These results suggest that VMHC can be used as a biomarker for the degeneration of the interhemispheric connectivity in AD.     

人脑功能连通性研究进展

对人脑结构和功能的深入研究,已经要求脑成像技术不能仅仅局限于研究简单的脑功能定位问题,即寻找和定位与特定认知任务相关的某一块或者一组大脑皮层功能区,而必须研究分析各功能区间的动态功能连通和整合问题,即描述特定脑功能区域间的交互作用以及这些交互作用如何受认知任务的影响.已有几种非常规的脑成像技术和数据分析方法,包括时间相关性分析、心理生理交互作用(PPI)、结构方程模型(SEM)、动态因果模型(DCM)、弥散张量成像(DTI)等等,被成功用于人脑功能连通性和有效连通性的研究.脑功能连通性研究的发展,有利于深入理解人脑在系统水平上的动态运作方式,是今后认知神经科学发展的一个重要方向.     

Structural and Functional Brain Connectivity of People with Obesity and Prediction of Body Mass Index Using Connectivity

Obesity is a medical condition affecting billions of people. Various neuroimaging methods including magnetic resonance imaging (MRI) have been used to obtain information about obesity. We adopted a multi-modal approach combining diffusion tensor imaging (DTI) and resting state functional MRI (rs-fMRI) to incorporate complementary information and thus better investigate the brains of non-healthy weight subjects. The objective of this study was to explore multi-modal neuroimaging and use it to predict a practical clinical score, body mass index (BMI). Connectivity analysis was applied to DTI and rs-fMRI. Significant regions and associated imaging features were identified based on group-wise differences between healthy weight and non-healthy weight subjects. Six DTI-driven connections and 10 rs-fMRI-driven connectivities were identified. DTI-driven connections better reflected group-wise differences than did rs-fMRI-driven connectivity. We predicted BMI values using multi-modal imaging features in a partial least-square regression framework (percent error 15.0%). Our study identified brain regions and imaging features that can adequately explain BMI. We identified potentially good imaging biomarker candidates for obesity-related diseases.     

Neuropsychological Outcome and Diffusion Tensor Imaging in Complicated versus Uncomplicated Mild Traumatic Brain Injury

This study examined whether intracranial neuroimaging abnormalities in those with mild traumatic brain injury (MTBI) (i.e., “complicated” MTBIs) are associated with worse subacute outcomes as measured by cognitive testing, symptom ratings, and/or diffusion tensor imaging (DTI). We hypothesized that (i) as a group, participants with complicated MTBIs would report greater symptoms and have worse neurocognitive outcomes than those with uncomplicated MTBI, and (ii) as a group, participants with complicated MTBIs would show more Diffusion Tensor Imaging (DTI) abnormalities. Participants were 62 adults with MTBIs (31 complicated and 31 uncomplicated) who completed neurocognitive testing, symptom ratings, and DTI on a 3T MRI scanner approximately 6-8 weeks post injury. There were no statistically significant differences between groups on symptom ratings or on a broad range of neuropsychological tests. When comparing the groups using tract-based spatial statistics for DTI, no significant difference was found for axial diffusivity or mean diffusivity. However, several brain regions demonstrated increased radial diffusivity (purported to measure myelin integrity), and decreased fractional anisotropy in the complicated group compared with the uncomplicated group. Finally, when we extended the DTI analysis, using a multivariate atlas based approach, to 32 orthopedic trauma controls (TC), the findings did not reveal significantly more areas of abnormal DTI signal in the complicated vs. uncomplicated groups, although both MTBI groups had a greater number of areas with increased radial diffusivity compared with the trauma controls. This study illustrates that macrostructural neuroimaging changes following MTBI are associated with measurable changes in DTI signal. Of note, however, the division of MTBI into complicated and uncomplicated subtypes did not predict worse clinical outcome at 6-8 weeks post injury.     

Gestational Age and Neonatal Brain Microstructure in Term Born Infants: A Birth Cohort Study

Objective

Understanding healthy brain development in utero is crucial in order to detect abnormal developmental trajectories due to developmental disorders. However, in most studies neuroimaging was done after a significant postnatal period, and in those studies that performed neuroimaging on fetuses, the quality of data has been affected due to complications of scanning during pregnancy. To understand healthy brain development between 37–41 weeks of gestational age, our study assessed the in utero growth of the brain in healthy term born babies with DTI scanning soon after birth.

Methods

A cohort of 93 infants recruited from maternity hospitals in Singapore underwent diffusion tensor imaging between 5 to 17 days after birth. We did a cross-sectional examination of white matter microstructure of the brain among healthy term infants as a function of gestational age via voxel-based analysis on fractional anisotropy.

Results

Greater gestational age at birth in term infants was associated with larger fractional anisotropy values in early developing brain regions, when corrected for age at scan. Specifically, it was associated with a cluster located at the corpus callosum (corrected p<0.001), as well as another cluster spanning areas of the anterior corona radiata, anterior limb of internal capsule, and external capsule (corrected p<0.001).

Conclusions

Our findings show variation in brain maturation associated with gestational age amongst ‘term’ infants, with increased brain maturation when born with a relatively higher gestational age in comparison to those infants born with a relatively younger gestational age. Future studies should explore if these differences in brain maturation between 37 and 41 weeks of gestational age will persist over time due to development outside the womb.     

Features of the spectral power of the EEG rhythms in autistic children and their relation with the progress of different symptoms in schizophrenia

Right hemispheric dominance of the baseline alpha-band spectral power was revealed in 5-7 years boys with autism. This feature persisted during performance of a cognitive task (counting). Also, boys with autism showed lowered level of the alpha spectral power as compared with healthy children. In healthy children, the gamma spectral power increased during performance of the cognitive task as compared to baseline state. Autistic persons showed higher values of the gamma spectral power as compared with normal boys. Boys with autism showed less expressed changes in the gamma spectral power during the cognitive task than healthy children. The reduced spectral power of the alpha band in autistic boys may serve as a precursor of conversion from autism to schizophrenia. Higher level of the gamma spectral power in autistic boys is characteristic also of schizophrenic patients with positive symptoms. Lowered levels of fast rhythms reactivity revealed in autistic boys and the same effect earlier described in schizophrenic adults probably have the similar nature.     

White Matter Changes in Patients with Amnestic Mild Cognitive Impairment Detected by Diffusion Tensor Imaging

Compared to normal aging adults, individuals with amnestic mild cognitive impairment (aMCI) have significantly increased risk for progressing into Alzheimer’s disease (AD). Autopsy studies found that most of the brains of aMCI cases showed anatomical features associated with AD pathology. The recent development of non-invasive neuroimaging technique, such as diffusion tensor imaging (DTI), makes it possible to investigate the microstructures of the cerebral white matter in vivo. We hypothesized that disrupted white matter (WM) integrity existed in aMCI. So we used DTI technique, by measuring fractional anisotropy (FA) and mean diffusivity (MD), to test the brain structures involved in patients with aMCI. DTI scans were collected from 40 patients with aMCI, and 28 normal controls (NC). Tract-based spatial statistics (TBSS) analyses of whole-brain FA and MD images in each individual and group comparisons were carried out. Compared to NC, aMCI patients showed significant FA reduction bilaterally, in the association and projection fibers of frontal, parietal, and temporal lobes, corpus callosum, bilateral corona radiation, right posterior thalamic radiation and right sagittal stratum. aMCI patients also showed significantly increased MD widespreadly in the association and projection fibers of frontal, parietal and temporal lobes, and corpus callosum. Assessment of the WM integrity of the frontal, parietal, temporal lobes, and corpus callosum by using DTI measures may aid early diagnosis of aMCI.     

Upregulation of Ras/Raf/ERK1/2 signaling and ERK5 in the brain of autistic subjects

Autism is a neurodevelopmental disorder characterized by impairments in social interaction, verbal communication and repetitive behaviors. A number of studies have shown that the Ras/Raf/ERK1/2 (extracellular signal-regulated kinase) signaling pathway plays important roles in the genesis of neural progenitors, learning and memory. Ras/Raf/ERK1/2 and ERK5 have also been shown to have death-promoting apoptotic roles in neural cells. Recent studies have shown a possible association between neural cell death and autism. In addition, two recent studies reported that a deletion of a locus on chromosome 16, which included the mitogen-activated protein kinase 3 (MAPK3) gene that encodes ERK1, is associated with autism. Most recently, our laboratory detected that Ras/Raf/ERK1/2 signaling activities were significantly enhanced in the brain of BTBR mice that model autism, as they exhibit many autism-like behaviors. We thus hypothesized that Ras/Raf/ERK1/2 signaling and ERK5 could be abnormally regulated in the brain of autistic subjects. In this study, we show that the expression of Ras protein was significantly elevated in the frontal cortex of autistic subjects. C-Raf phosphorylation was increased in the frontal cortex, while both C-Raf and A-Raf activities were enhanced in the cerebellum of autistic subjects. We also detected that both the protein expression and activities of ERK1/2 were significantly upregulated in the frontal cortex of autistic subjects, but not in the cerebellum. Furthermore, we showed that ERK5 protein expression is upregulated in both frontal cortex and cerebellum of autistic subjects. These results suggest that the upregulation of Ras/Raf/ERK1/2 signaling and ERK5 activities mainly found in the frontal cortex of autistic subjects may be critically involved in the pathogenesis of autism.     

Influence of Low-Level Prenatal Exposure to PCDD/Fs and PCBs on Empathizing,Systemizing and Autistic Traits: Results from the Duisburg Birth Cohort Study

Background

Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and polychlorinated biphenyls (PCBs) are assumed to act as endocrine disruptor chemicals. Prenatal exposure to these pollutants might influence fetal steroid hormone levels, which are thought to be related to sex-typical development and autistic traits.

Objectives

We examined associations of prenatal levels of PCDD/Fs and PCBs with autism traits and sex-typical behaviour in childhood.

Methods

We measured levels of PCDD/Fs and PCBs in maternal blood samples during pregnancy using gas chromatography/high-resolution mass spectrometry. Sex-typical behaviour was assessed at 9 years of age (n = 96) and autistic traits at 10 years of age using the Social Responsiveness Scale (SRS; n = 100). Multiple regression analyses were conducted to estimate the associations between prenatal exposure and outcome variables.

Results

Blood concentrations (WHO₂₀₀₅-TEq) of ƩPCDD/Fs ranged from 2.93–46.45 pg/g _{lipid base} (median = 12.91 pg/g _{lipid base}) and concentrations of ƩPCBs were in the range of 1.24–25.47 pg/g _{lipid base} (median = 6.85 pg/g _{lipid base}) which is within the range of German background exposure. We found significant negative associations between PCDD/F levels in maternal blood and SRS scores in the whole group (β = -6.66, p < .05), in girls (β = -10.98, p < .05) and, in one SRS subscale, in boys (β = -6.86, p < .05). For PCB levels, associations with one SRS subscale were significant for the whole study group as were associations with two subscales in girls. We did not find significant associations between PCDD/F or PCB levels and sex-typical behaviour for either sex.

Conclusions

In an earlier part of this study, prenatal exposure to PCDD/Fs and PCBs was found to be associated with lower testosterone levels, therefore, our findings are consistent with the idea that autism spectrum conditions are related to fetal androgen levels. Several possible mechanisms, through which PCDD/Fs and PCBs might influence autistic behaviour, are discussed.