Dataset Information

Age-related decreased inhibitory vs. excitatory gene expression in the adult autistic brain.

ABSTRACT: Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by impaired social interaction and communication, and restricted behavior and interests. A disruption in the balance of excitatory and inhibitory neurotransmission has been hypothesized to underlie these disorders. Here we demonstrate that genes of both pathways are affected by ASD, and that gene expression of inhibitory and excitatory genes is altered in the cerebral cortex of adult but not younger autistic individuals. We have developed a measure for the difference in the level of excitation and inhibition based on gene expression and observe that in this measure inhibition is decreased relative to excitation in adult ASD compared to control. This difference was undetectable in young autistic brains. Given that many psychiatric features of autism are already present at an early age, this suggests that the observed imbalance in gene expression is an aging phenomenon in ASD rather than its underlying cause.

SUBMITTER: van de Lagemaat LN

PROVIDER: S-EPMC4259106 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Age-related decreased inhibitory vs. excitatory gene expression in the adult autistic brain.

van de Lagemaat Louie N LN Nijhof Bonnie B Bosch Daniëlle G M DG Kohansal-Nodehi Mahdokht M Keerthikumar Shivakumar S Heimel J Alexander JA

Frontiers in neuroscience 20141208

Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by impaired social interaction and communication, and restricted behavior and interests. A disruption in the balance of excitatory and inhibitory neurotransmission has been hypothesized to underlie these disorders. Here we demonstrate that genes of both pathways are affected by ASD, and that gene expression of inhibitory and excitatory genes is altered in the cerebral cortex of adult but not younger autistic individu ...[more]

PMID: 25538548

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Project description:Probabilistic inference offers a principled framework for understanding both behaviour and cortical computation. However, two basic and ubiquitous properties of cortical responses seem difficult to reconcile with probabilistic inference: neural activity displays prominent oscillations in response to constant input, and large transient changes in response to stimulus onset. Indeed, cortical models of probabilistic inference have typically either concentrated on tuning curve or receptive field properties and remained agnostic as to the underlying circuit dynamics, or had simplistic dynamics that gave neither oscillations nor transients. Here we show that these dynamical behaviours may in fact be understood as hallmarks of the specific representation and algorithm that the cortex employs to perform probabilistic inference. We demonstrate that a particular family of probabilistic inference algorithms, Hamiltonian Monte Carlo (HMC), naturally maps onto the dynamics of excitatory-inhibitory neural networks. Specifically, we constructed a model of an excitatory-inhibitory circuit in primary visual cortex that performed HMC inference, and thus inherently gave rise to oscillations and transients. These oscillations were not mere epiphenomena but served an important functional role: speeding up inference by rapidly spanning a large volume of state space. Inference thus became an order of magnitude more efficient than in a non-oscillatory variant of the model. In addition, the network matched two specific properties of observed neural dynamics that would otherwise be difficult to account for using probabilistic inference. First, the frequency of oscillations as well as the magnitude of transients increased with the contrast of the image stimulus. Second, excitation and inhibition were balanced, and inhibition lagged excitation. These results suggest a new functional role for the separation of cortical populations into excitatory and inhibitory neurons, and for the neural oscillations that emerge in such excitatory-inhibitory networks: enhancing the efficiency of cortical computations.

Project description:Background: The brain atrophy and lesion index (BALI) has been developed to assess whole-brain structural deficits that are commonly seen on magnetic resonance imaging (MRI) in aging. It is unclear whether such changes can be detected at younger ages and how they might relate to other exposures. Here, we investigate how BALI scores, and the subcategories that make the total score, compare across adulthood and whether they are related to the level of cardiovascular risks, in both young and old adulthood. Methods: Data were from 229 subjects (72% men; 24-80 years of age) whose annual health evaluation included a routine anatomical MRI examination. A BALI score was generated for each subject from T2-weighted MRI. Differences in the BALI total score and categorical subscores were examined by age and by the level of cardiovascular risk factors (CVRFs). Regression analysis was used to evaluate relationships between continuous variables. Relative risk ratios (RRRs) of CVRF on BALI were examined using a multinomial logistic regression. The area under the receiver operating characteristic (ROC) curve was used to estimate the classification accuracy. Results: Nearly 90% of the participants had at least one CVRF. Mean CVRF scores increased with age (slope = 0.03; r = 0.36, 95% confidence intervals: 0.23-0.48; p < 0.001). The BALI total score was closely related to age (slope = 0.18; r = 0.69, 95% confidence intervals: 0.59-0.78; p < 0.001), as so were the categorical subscores (r's = 0.41-0.61, p < 0.001); each differed by the number of CVRF (t-test: 4.16-14.83, ? 2: 6.9-43.9, p's < 0.050). Multivariate analyses adjusted for age and sex suggested an independent impact of age and the CVRF on the BALI score (for each year of advanced age, RRR = 1.20, 95% CI = 1.11-1.29; for each additional CVRF, RRR = 3.63, 95% CI = 2.12-6.23). The CVRF and BALI association remained significant even in younger adults. Conclusion: The accumulation of MRI-detectable structural brain deficits can be evident from young adulthood. Age and the number of CVFR are independently associated with BALI score. Further research is needed to understand the extent to which other age-related health deficits can increase the risk of abnormalities in brain structure and function, and how these, with BALI scores, relate to cognition.

Dataset Information

Age-related decreased inhibitory vs. excitatory gene expression in the adult autistic brain.

Publications

Age-related decreased inhibitory vs. excitatory gene expression in the adult autistic brain.

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