DNA methylation signatures in autism spectrum disorders

Banerjee, Nilanjana; Adak, Pallabi

doi:10.1007/s13237-021-00370-3

Cited by 2 publications

(1 citation statement)

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“…A fine balance maintains the normal profile of the cell and an imbalance can be associated with development of diseased states including cancer, neuronal disorder, impaired DNA repair, exposure associated disorders [6,27,42,51]. In the present issue, Dhar et al [12] and Banerjee et al [2] outlines some of the major aspects of DNA methylation and how it affects gene expression and development of neuronal disorder like autism. In both the articles, issues relating to genomic imprinting have been discussed along with how understanding epigenetic alterations can help in countering these disorders in humans, clinically.…”

Section: Covalent Modifications Of the Chromatin Lead To Epigenetically Regulated Expression Profilementioning

confidence: 93%

Impact of epigenetics on human health and possible tool for remediation

Paul

2021

Nucleus

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Section: Covalent Modifications Of the Chromatin Lead To Epigenetically Regulated Expression Profilementioning

confidence: 93%

Impact of epigenetics on human health and possible tool for remediation

Paul

2021

Nucleus

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Comprehensive exploration of multi-modal and multi-branch imaging markers for autism diagnosis and interpretation: insights from an advanced deep learning model

Gao,

Xu,

et al. 2024

Cerebral Cortex

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Autism spectrum disorder is a complex neurodevelopmental condition with diverse genetic and brain involvement. Despite magnetic resonance imaging advances, autism spectrum disorder diagnosis and understanding its neurogenetic factors remain challenging. We propose a dual-branch graph neural network that effectively extracts and fuses features from bimodalities, achieving 73.9% diagnostic accuracy. To explain the mechanism distinguishing autism spectrum disorder from healthy controls, we establish a perturbation model for brain imaging markers and perform a neuro-transcriptomic joint analysis using partial least squares regression and enrichment to identify potential genetic biomarkers. The perturbation model identifies brain imaging markers related to structural magnetic resonance imaging in the frontal, temporal, parietal, and occipital lobes, while functional magnetic resonance imaging markers primarily reside in the frontal, temporal, occipital lobes, and cerebellum. The neuro-transcriptomic joint analysis highlights genes associated with biological processes, such as “presynapse,” “behavior,” and “modulation of chemical synaptic transmission” in autism spectrum disorder’s brain development. Different magnetic resonance imaging modalities offer complementary information for autism spectrum disorder diagnosis. Our dual-branch graph neural network achieves high accuracy and identifies abnormal brain regions and the neuro-transcriptomic analysis uncovers important genetic biomarkers. Overall, our study presents an effective approach for assisting in autism spectrum disorder diagnosis and identifying genetic biomarkers, showing potential for enhancing the diagnosis and treatment of this condition.

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DNA methylation signatures in autism spectrum disorders

Cited by 2 publications

References 100 publications

Impact of epigenetics on human health and possible tool for remediation

Impact of epigenetics on human health and possible tool for remediation

Comprehensive exploration of multi-modal and multi-branch imaging markers for autism diagnosis and interpretation: insights from an advanced deep learning model

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