Paternal age contribution to brain white matter aberrations in autism spectrum disorder

Identify aberrant white matter microstructure in ASD, ADHD and other neurodevelopmental disorders: A meta-analysis of diffusion tensor imaging studies

BACKGROUND

Neurodevelopmental disorders (NDDs) usually present overlapping symptoms. Abnormal white matter (WM) microstructure has been found in these disorders. Identification of common and unique neural abnormalities across NDDs could provide further insight into the underlying pathophysiological mechanisms.

METHODS

We performed a voxel-based meta-analysis of whole-brain diffusion tensor imaging (DTI) studies in autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD) and other NDDs. A systematic literature search was conducted through March 2020 to identify studies that compared measures of WM microstructure between patients with NDDs and neurotypical controls. Peak voxel coordinates were meta-analyzed via anisotropic effect size-signed differential mapping (AES-SDM) as well as activation likelihood estimation (ALE).

RESULTS

Our final sample included a total of 4137 subjects from 66 studies across five NDDs. Fractional anisotropy (FA) reductions were found in the splenium of the CC in ADHD, and the genu and splenium of CC in ASD. And mean diffusivity (MD) increases were shown in posterior thalamic radiation in ASD. No consistent abnormalities were detected in specific learning disorder, motor disorder or communication disorder. Significant differences between child/adolescent and adult patients were found within the CC across NDDs, reflective of aberrant neurodevelopmental processes in NDDs.

CONCLUSIONS

The current study demonstrated atypical WM patterns in ASD, ADHD and other NDDs. Microstructural abnormalities in the splenium of the CC were possibly shared among ASD and ADHD.

Heritability of abnormalities in limbic networks of autism spectrum disorder children: Evidence from an autism spectrum disorder twin study

Although the limbic system is closely related to emotion and social behaviors, little is known about the integrity of limbic pathways and how genetics influence the anatomical abnormalities of limbic networks in children with autism spectrum disorder (ASD). Therefore, we used an ASD twin study design to evaluate the microstructural integrity and autism-related differences in limbic pathways of young children with ASD and to estimate the heritability of limbic tracts microstructure variance. We obtained diffusion tensor imaging scans from 33 pairs of twins with ASD aged 2-9 years and 20 age-matched typically developing children. The ACE model was used to estimate the relative effects of additive genetic factors (A), shared environmental factors (C) and specific environmental factors (E) on the variability of diffusivity measurements. We found a significant decrease in fractional anisotropy (FA) in the bilateral fornix and uncinate fasciculus (UF), as well as increased mean diffusivity (MD) and radial diffusivity (RD) in the bilateral fornix and right UF of ASD children. Correlation analysis showed that FA, MD, and lateralization indices of UF were correlated with autism diagnostic observation schedule scores. The ACE model revealed that genetic effects may drive some of the variability of microstructure in the bilateral fornix, cingulum, and left UF. In conclusion, in children with ASD, there are abnormalities in the white matter microstructure of the limbic system, which is related to the core symptoms; these abnormalities may be related to the relative contribution of genetic and environmental effects on specific tracts. LAY SUMMARY: Autism spectrum disorder (ASD) children have abnormal white matter structure in limbic system related to ASD symptoms, and genetic factors play an important role in the development of limbic tracts.

Sperm DNA methylation epimutation biomarker for paternal offspring autism susceptibility

BACKGROUND

Autism spectrum disorder (ASD) has increased over tenfold over the past several decades and appears predominantly associated with paternal transmission. Although genetics is anticipated to be a component of ASD etiology, environmental epigenetics is now also thought to be an important factor. Epigenetic alterations, such as DNA methylation, have been correlated with ASD. The current study was designed to identify a DNA methylation signature in sperm as a potential biomarker to identify paternal offspring autism susceptibility.

METHODS AND RESULTS

Sperm samples were obtained from fathers that have children with or without autism, and the sperm then assessed for alterations in DNA methylation. A genome-wide analysis (> 90%) for differential DNA methylation regions (DMRs) was used to identify DMRs in the sperm of fathers (n = 13) with autistic children in comparison with those (n = 13) without ASD children. The 805 DMR genomic features such as chromosomal location, CpG density and length of the DMRs were characterized. Genes associated with the DMRs were identified and found to be linked to previously known ASD genes, as well as other neurobiology-related genes. The potential sperm DMR biomarkers/diagnostic was validated with blinded test sets (n = 8-10) of individuals with an approximately 90% accuracy.

CONCLUSIONS

Observations demonstrate a highly significant set of 805 DMRs in sperm that can potentially act as a biomarker for paternal offspring autism susceptibility. Ancestral or early-life paternal exposures that alter germline epigenetics are anticipated to be a molecular component of ASD etiology.

Role of Oligodendrocytes and Myelin in the Pathophysiology of Autism Spectrum Disorder

Autism Spectrum Disorder (ASD) is an early neurodevelopmental disorder that involves deficits in interpersonal communication, social interaction, and repetitive behaviors. Although ASD pathophysiology is still uncertain, alterations in the abnormal development of the frontal lobe, limbic areas, and putamen generate an imbalance between inhibition and excitation of neuronal activity. Interestingly, recent findings suggest that a disruption in neuronal connectivity is associated with neural alterations in white matter production and myelination in diverse brain regions of patients with ASD. This review is aimed to summarize the most recent evidence that supports the notion that abnormalities in the oligodendrocyte generation and axonal myelination in specific brain regions are involved in the pathophysiology of ASD. Fundamental molecular mediators of these pathological processes are also examined. Determining the role of alterations in oligodendrogenesis and myelination is a fundamental step to understand the pathophysiology of ASD and identify possible therapeutic targets.

Machine-learning classification using neuroimaging data in schizophrenia, autism, ultra-high risk and first-episode psychosis

Neuropsychiatric disorders are diagnosed based on behavioral criteria, which makes the diagnosis challenging. Objective biomarkers such as neuroimaging are needed, and when coupled with machine learning, can assist the diagnostic decision and increase its reliability. Sixty-four schizophrenia, 36 autism spectrum disorder (ASD), and 106 typically developing individuals were analyzed. FreeSurfer was used to obtain the data from the participant's brain scans. Six classifiers were utilized to classify the subjects. Subsequently, 26 ultra-high risk for psychosis (UHR) and 17 first-episode psychosis (FEP) subjects were run through the trained classifiers. Lastly, the classifiers' output of the patient groups was correlated with their clinical severity. All six classifiers performed relatively well to distinguish the subject groups, especially support vector machine (SVM) and Logistic regression (LR). Cortical thickness and subcortical volume feature groups were most useful for the classification. LR and SVM were highly consistent with clinical indices of ASD. When UHR and FEP groups were run with the trained classifiers, majority of the cases were classified as schizophrenia, none as ASD. Overall, SVM and LR were the best performing classifiers. Cortical thickness and subcortical volume were most useful for the classification, compared to surface area. LR, SVM, and DT's output were clinically informative. The trained classifiers were able to help predict the diagnostic category of both UHR and FEP Individuals.

Parental age effects on neonatal white matter development

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Advanced paternal age is associated with a range of later negative outcomes.

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It is not known if these negative outcomes are due to genetics or environment.

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We use neonatal diffusion MRI to demonstrate paternal age effect on white matter.

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The babies of older fathers had reduced fractional anisotropy in multiple areas.

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These changes correlated with cognitive outcome at 18 months.

Objective

Advanced paternal age is associated with poor offspring developmental outcome. Though an increase in paternal age-related germline mutations may affect offspring white matter development, outcome differences could also be due to psychosocial factors. Here we investigate possible cerebral changes prior to strong environmental influences using brain MRI in a cohort of healthy term-born neonates.

Methods

We used structural and diffusion MRI images acquired soon after birth from a cohort (n = 275) of healthy term-born neonates. Images were analysed using a customised tract based spatial statistics (TBSS) processing pipeline. Neurodevelopmental assessment using the Bayley-III scales was offered to all participants at age 18 months. For statistical analysis neonates were compared in two groups, representing the upper quartile (paternal age ≥38 years) and lower three quartiles. The same method was used to assess associations with maternal age.

Results

In infants with older fathers (≥38 years), fractional anisotropy, a marker of white matter organisation, was significantly reduced in three early maturing anatomical locations (the corticospinal tract, the corpus callosum, and the optic radiation). Fractional anisotropy in these locations correlated positively with Bayley-III cognitive composite score at 18 months in the advanced paternal age group. A small but significant reduction in total brain volume was also observed in in the infants of older fathers. No significant associations were found between advanced maternal age and neonatal imaging.

Conclusions

The epidemiological association between advanced paternal age and offspring outcome is extremely robust. We have for the first time demonstrated a neuroimaging phenotype of advanced paternal age before sustained parental interaction that correlates with later outcome.