Altered expression of lncRNAs in autism spectrum disorder

Tamizkar, Kasra Honarmand; Ghafouri‐Fard, Soudeh; Omrani, Mir Davood; Pouresmaeili, Farkhondeh; Arsang‐Jang, Shahram

doi:10.1007/s11011-021-00681-z

Cited by 6 publications

(2 citation statements)

References 25 publications

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“…Strong body of evidence for an association of lncRNAs with NDDs and MCDs arouse from ASD-related studies ( Luo et al, 2019 ; Safari et al, 2020 ; Tamizkar et al, 2021 ). Mutation-screening analyses of patients affected by ASD identified several rare variants of non-coding loci RAY1/ST7 and ST7OT1–3 , which were not detectable in healthy control samples ( Table 2 ; Vincent et al, 2002 ).…”

Section: Implications Of Epigenetic Mechanisms In Neurodevelopmental Diseasesmentioning

confidence: 99%

The Epigenome in Neurodevelopmental Disorders

Reichard

Zimmer-Bensch

2021

Front. Neurosci.

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Neurodevelopmental diseases (NDDs), such as autism spectrum disorders, epilepsy, and schizophrenia, are characterized by diverse facets of neurological and psychiatric symptoms, differing in etiology, onset and severity. Such symptoms include mental delay, cognitive and language impairments, or restrictions to adaptive and social behavior. Nevertheless, all have in common that critical milestones of brain development are disrupted, leading to functional deficits of the central nervous system and clinical manifestation in child- or adulthood. To approach how the different development-associated neuropathologies can occur and which risk factors or critical processes are involved in provoking higher susceptibility for such diseases, a detailed understanding of the mechanisms underlying proper brain formation is required. NDDs rely on deficits in neuronal identity, proportion or function, whereby a defective development of the cerebral cortex, the seat of higher cognitive functions, is implicated in numerous disorders. Such deficits can be provoked by genetic and environmental factors during corticogenesis. Thereby, epigenetic mechanisms can act as an interface between external stimuli and the genome, since they are known to be responsive to external stimuli also in cortical neurons. In line with that, DNA methylation, histone modifications/variants, ATP-dependent chromatin remodeling, as well as regulatory non-coding RNAs regulate diverse aspects of neuronal development, and alterations in epigenomic marks have been associated with NDDs of varying phenotypes. Here, we provide an overview of essential steps of mammalian corticogenesis, and discuss the role of epigenetic mechanisms assumed to contribute to pathophysiological aspects of NDDs, when being disrupted.

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Section: Implications Of Epigenetic Mechanisms In Neurodevelopmental Diseasesmentioning

confidence: 99%

The Epigenome in Neurodevelopmental Disorders

Reichard

Zimmer-Bensch

2021

Front. Neurosci.

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“…LRRC2 is located in a region including GWS variants that modify the inverse relationship between education attainment and AD 34 . A recent study showed that the expression of a LRRC2 long noncoding RNA (LCCR2-AS1) is significantly increased in children with autism spectrum disorder compared to children with normal development 48 . The human leukocyte antigen (HLA) region is the key susceptibility gene in many immunological diseases and many associations have been reported between neurodegenerative diseases and HLA haplotypes 49 .…”

Section: Discussionmentioning

confidence: 99%

Cell-type-specific expression quantitative trait loci associated with Alzheimer disease in blood and brain tissue

et al. 2021

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Because regulation of gene expression is heritable and context-dependent, we investigated AD-related gene expression patterns in cell types in blood and brain. Cis-expression quantitative trait locus (eQTL) mapping was performed genome-wide in blood from 5257 Framingham Heart Study (FHS) participants and in brain donated by 475 Religious Orders Study/Memory & Aging Project (ROSMAP) participants. The association of gene expression with genotypes for all cis SNPs within 1 Mb of genes was evaluated using linear regression models for unrelated subjects and linear-mixed models for related subjects. Cell-type-specific eQTL (ct-eQTL) models included an interaction term for the expression of “proxy” genes that discriminate particular cell type. Ct-eQTL analysis identified 11,649 and 2533 additional significant gene-SNP eQTL pairs in brain and blood, respectively, that were not detected in generic eQTL analysis. Of note, 386 unique target eGenes of significant eQTLs shared between blood and brain were enriched in apoptosis and Wnt signaling pathways. Five of these shared genes are established AD loci. The potential importance and relevance to AD of significant results in myeloid cell types is supported by the observation that a large portion of GWS ct-eQTLs map within 1 Mb of established AD loci and 58% (23/40) of the most significant eGenes in these eQTLs have previously been implicated in AD. This study identified cell-type-specific expression patterns for established and potentially novel AD genes, found additional evidence for the role of myeloid cells in AD risk, and discovered potential novel blood and brain AD biomarkers that highlight the importance of cell-type-specific analysis.

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