scholarly journals Neural correlates of polygenic risk score for autism spectrum disorders in general population

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Budhachandra Khundrakpam ◽  
Uku Vainik ◽  
Jinnan Gong ◽  
Noor Al-Sharif ◽  
Neha Bhutani ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
White Matter ◽  
General Population ◽  
Cortical Thickness ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Cortical Regions ◽  
White Matter Connectivity

Abstract Autism spectrum disorder is a highly prevalent and highly heritable neurodevelopmental condition, but studies have mostly taken traditional categorical diagnosis approach (yes/no for autism spectrum disorder). In contrast, an emerging notion suggests a continuum model of autism spectrum disorder with a normal distribution of autistic tendencies in the general population, where a full diagnosis is at the severe tail of the distribution. We set out to investigate such a viewpoint by investigating the interaction of polygenic risk scores for autism spectrum disorder and Age2 on neuroimaging measures (cortical thickness and white matter connectivity) in a general population (n = 391, with age ranging from 3 to 21 years from the Pediatric Imaging, Neurocognition and Genetics study). We observed that children with higher polygenic risk for autism spectrum disorder exhibited greater cortical thickness for a large age span starting from 3 years up to ∼14 years in several cortical regions localized in bilateral precentral gyri and the left hemispheric postcentral gyrus and precuneus. In an independent case–control dataset from the Autism Brain Imaging Data Exchange (n = 560), we observed a similar pattern: children with autism spectrum disorder exhibited greater cortical thickness starting from 6 years onwards till ∼14 years in wide-spread cortical regions including (the ones identified using the general population). We also observed statistically significant regional overlap between the two maps, suggesting that some of the cortical abnormalities associated with autism spectrum disorder overlapped with brain changes associated with genetic vulnerability for autism spectrum disorder in healthy individuals. Lastly, we observed that white matter connectivity between the frontal and parietal regions showed significant association with polygenic risk for autism spectrum disorder, indicating that not only the brain structure, but the white matter connectivity might also show a predisposition for the risk of autism spectrum disorder. Our findings showed that the fronto-parietal thickness and connectivity are dimensionally related to genetic risk for autism spectrum disorder in general population and are also part of the cortical abnormalities associated with autism spectrum disorder. This highlights the necessity of considering continuum models in studying the aetiology of autism spectrum disorder using polygenic risk scores and multimodal neuroimaging.

scholarly journals Identification of infants at high‐risk for autism spectrum disorder using multiparameter multiscale white matter connectivity networks

2015 ◽  
Vol 36 (12) ◽  
pp. 4880-4896 ◽  
Author(s):  
Yan Jin ◽  
Chong‐Yaw Wee ◽  
Feng Shi ◽  
Kim‐Han Thung ◽  
Dong Ni ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
White Matter ◽  
High Risk ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
White Matter Connectivity

scholarly journals Relationship Between Cortical Gyrification, White Matter Connectivity, and Autism Spectrum Disorder

2016 ◽  
Vol 26 (7) ◽  
pp. 3297-3309 ◽  
Author(s):  
C. Ecker ◽  
D. Andrews ◽  
F. Dell'Acqua ◽  
E. Daly ◽  
C. Murphy ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
White Matter ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
White Matter Connectivity

scholarly journals High Body Mass Polygenic Risk in Mothers Enhances De Novo Functional Mutations in Epigenetic and Microtubule Gene Pathways in Their Offspring With Autism Spectrum Disorder

2021 ◽  
Author(s):  
Brian Lohman ◽  
Andrey A Shabalin ◽  
Andrew Farrell ◽  
Gabor T Marth ◽  
Anna R. Docherty ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Body Mass ◽  
De Novo ◽  
Epigenetic Modification ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Risk Scores ◽  
Maternal Body Mass Index ◽  
Polygenic Risk ◽  
Functional Variants

Abstract Background. Autism Spectrum Disorder (ASD) is a neurodevelopmental diagnosis that encompasses deficits in social communication in addition to repetitive and restrictive behaviors and interests. Accumulated evidence implicates over 100 risk genes and suggests possible genetic subtypes. We tested one previously characterized subtype relating to high maternal body mass index (BMI) as an enhancing risk factor in genetically vulnerable offspring. Methods. Using 1,300 families from the Simons Simplex Collection (SSC), we created an objectively defined subgroup of mothers in the highest quartile of the distribution of derived BMI polygenic risk scores. Polygenic risk for BMI reflects background genetic risk independent of the many environmental modifiers of BMI.Results. In the ASD offspring of mothers in this highest quartile, we found significant associations with de novo, putatively functional variants in genes in pathways related to chromatin state, chromatin structure, histone activity, and microtubule function. These gene pathways represent potential epigenetic vulnerability to alterations in the metabolic prenatal environment and/or alterations in microtubule-related brain development processes. The observed pathway enrichments were maternal-specific, and were not observed in neurotypical offspring. Two-thirds of the 36 genes in the significant epigenetic pathways and over half of the 33 genes in the significant microtubule pathways had existing ASD or neurodevelopmental risk evidence. Limitations. Though tests and simulations were done to ensure robustness of results, these findings have not been replicated in an external cohort.Conclusions. Our results suggest that epigenetic modification and/or microtubule deficits may be unique to a subset of ASD probands of mothers at increased genetic metabolic risk, pending external replication. Beyond the current application of these methods, our approach presents a strategy to reveal genetic subsets through polygenic risk stratification across phenotypic domains.

scholarly journals Examining the boundary sharpness coefficient as an index of cortical microstructure and its relationship to age and sex in autism spectrum disorder

2020 ◽  
Author(s):  
Emily Olafson ◽  
Saashi Bedford ◽  
Gabriel A. Devenyi ◽  
Raihaan Patel ◽  
Stephanie Tullo ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
White Matter ◽  
Cortical Thickness ◽  
Meta Analysis ◽  
Inferior Frontal Gyrus ◽  
Superior Temporal Gyrus ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Sharpness Coefficient

AbstractAutism spectrum disorder (ASD) is associated with atypical brain development. However, the phenotype of regionally specific increased cortical thickness observed in ASD may be driven by several independent biological processes that influence the gray/white matter boundary, such as synaptic pruning, myelination, or atypical migration. Here, we propose to use the boundary sharpness coefficient (BSC), a proxy for alterations in microstructure at the cortical gray/white matter boundary, to investigate brain differences in individuals with ASD, including factors that may influence ASD-related heterogeneity (age, sex, and intelligence quotient). Using a vertex-based meta-analysis and a large multi-center magnetic resonance structural imaging (MRI) dataset, with a total of 1136 individuals, 415 with ASD (112 female; 303 male) and 721 controls (283 female; 438 male), we observed that individuals with ASD had significantly greater BSC in the bilateral superior temporal gyrus and left inferior frontal gyrus indicating an abrupt transition (high contrast) between white matter and cortical intensities. Increases were observed in different brain regions in males and females, with larger effect sizes in females. Individuals with ASD under 18 had significantly greater BSC in the bilateral superior temporal gyrus and right postcentral gyrus; individuals with ASD over 18 had significantly increased BSC in the bilateral precuneus and superior temporal gyrus. BSC correlated with ADOS-2 CSS in individuals with ASD in the right medial temporal pole. Importantly, there was a significant spatial overlap between maps of the effect of diagnosis on BSC when compared to cortical thickness. These results invite studies to use BSC as a possible new measure of cortical development in ASD and to further examine the microstructural underpinnings of BSC-related differences and their impact on measures of cortical morphology.

scholarly journals Common polygenic risk for autism spectrum disorder (ASD) is associated with cognitive ability in the general population

2015 ◽  
Vol 21 (3) ◽  
pp. 419-425 ◽  
Author(s):  
T-K Clarke ◽  
M K Lupton ◽  
A M Fernandez-Pujals ◽  
J Starr ◽  
G Davies ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
General Population ◽  
Cognitive Ability ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Polygenic Risk

scholarly journals Polygenic risk for autism spectrum disorder affects left amygdala activity and negative emotion in schizophrenia

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yue Qin ◽  
Jujiao Kang ◽  
Zeyu Jiao ◽  
Yi Wang ◽  
Jiucun Wang ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Emotion Recognition ◽  
Negative Emotion ◽  
Enrichment Analysis ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Functional Enrichment ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Intermediate Phenotypes

Abstract Although the diagnoses based on phenomenology have many practical advantages, accumulating evidence shows that schizophrenia and autism spectrum disorder (ASD) share some overlap in genetics and clinical presentation. It remains largely unknown how ASD-associated polygenetic risk contributes to the pathogenesis of schizophrenia. In the present study, we calculated high-resolution ASD polygenic risk scores (ASD PRSs) and selected optimal ten ASD PRS with minimal P values in the association analysis of PRSs, with schizophrenia to assess the effect of ASD PRS on brain neural activity in schizophrenia cases and controls. We found that amplitude of low-frequency fluctuation in left amygdala was positively associated with ASD PRSs in our cohort. Correlation analysis of ASD PRSs with facial emotion recognition test identified the negative correlation of ASD PRSs with negative emotions in schizophrenia cases and controls. Finally, functional enrichment analysis of PRS genes revealed that neural system function and development, as well as signal transduction, were mainly enriched in PRS genes. Our results provide empirical evidence that polygenic risk for ASD contributes to schizophrenia by the intermediate phenotypes of left amygdala function and emotion recognition. It provides a promising strategy to understand the relationship between phenotypes and genotypes shared in mental disorders.

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