11 research outputs found

    Synaptic processes and immune-related pathways implicated in Tourette syndrome.

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    Tourette syndrome (TS) is a neuropsychiatric disorder of complex genetic architecture involving multiple interacting genes. Here, we sought to elucidate the pathways that underlie the neurobiology of the disorder through genome-wide analysis. We analyzed genome-wide genotypic data of 3581 individuals with TS and 7682 ancestry-matched controls and investigated associations of TS with sets of genes that are expressed in particular cell types and operate in specific neuronal and glial functions. We employed a self-contained, set-based association method (SBA) as well as a competitive gene set method (MAGMA) using individual-level genotype data to perform a comprehensive investigation of the biological background of TS. Our SBA analysis identified three significant gene sets after Bonferroni correction, implicating ligand-gated ion channel signaling, lymphocytic, and cell adhesion and transsynaptic signaling processes. MAGMA analysis further supported the involvement of the cell adhesion and trans-synaptic signaling gene set. The lymphocytic gene set was driven by variants in FLT3, raising an intriguing hypothesis for the involvement of a neuroinflammatory element in TS pathogenesis. The indications of involvement of ligand-gated ion channel signaling reinforce the role of GABA in TS, while the association of cell adhesion and trans-synaptic signaling gene set provides additional support for the role of adhesion molecules in neuropsychiatric disorders. This study reinforces previous findings but also provides new insights into the neurobiology of TS

    Multiethnic Meta-Analysis Identifies RAI1 as a Possible Obstructive Sleep Apnea-related Quantitative Trait Locus in Men.

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    Obstructive sleep apnea (OSA) is a common heritable disorder displaying marked sexual dimorphism in disease prevalence and progression. Previous genetic association studies have identified a few genetic loci associated with OSA and related quantitative traits, but they have only focused on single ethnic groups, and a large proportion of the heritability remains unexplained. The apnea-hypopnea index (AHI) is a commonly used quantitative measure characterizing OSA severity. Because OSA differs by sex, and the pathophysiology of obstructive events differ in rapid eye movement (REM) and non-REM (NREM) sleep, we hypothesized that additional genetic association signals would be identified by analyzing the NREM/REM-specific AHI and by conducting sex-specific analyses in multiethnic samples. We performed genome-wide association tests for up to 19,733 participants of African, Asian, European, and Hispanic/Latino American ancestry in 7 studies. We identified rs12936587 on chromosome 17 as a possible quantitative trait locus for NREM AHI in men (N = 6,737; P = 1.7 × 10 <sup>-8</sup> ) but not in women (P = 0.77). The association with NREM AHI was replicated in a physiological research study (N = 67; P = 0.047). This locus overlapping the RAI1 gene and encompassing genes PEMT1, SREBF1, and RASD1 was previously reported to be associated with coronary artery disease, lipid metabolism, and implicated in Potocki-Lupski syndrome and Smith-Magenis syndrome, which are characterized by abnormal sleep phenotypes. We also identified gene-by-sex interactions in suggestive association regions, suggesting that genetic variants for AHI appear to vary by sex, consistent with the clinical observations of strong sexual dimorphism

    Characterization of genome-methylome interactions in 22 nuclear pedigrees

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    Genetic polymorphisms can shape the global landscape of DNA methylation, by either changing substrates for DNA methyltransferases or altering the DNA binding affinity of cis-regulatory proteins. The interactions between CpG methylation and genetic polymorphisms have been previously investigated by methylation quantitative trait loci (mQTL) and allele-specific methylation (ASM) analysis. However, it remains unclear whether these approaches can effectively and comprehensively identify all genetic variants that contribute to the inter-individual variation of DNA methylation levels. Here we used three independent approaches to systematically investigate the influence of genetic polymorphisms on variability in DNA methylation by characterizing the methylation state of 96 whole blood samples in 52 parent-child trios from 22 nuclear pedigrees. We performed targeted bisulfite sequencing with padlock probes to quantify the absolute DNA methylation levels at a set of 411,800 CpG sites in the human genome. With mid-parent offspring analysis (MPO), we identified 10,593 CpG sites that exhibited heritable methylation patterns, among which 70.1% were SNPs directly present in methylated CpG dinucleotides. We determined the mQTL analysis identified 49.9% of heritable CpG sites for which regulation occurred in a distal cis-regulatory manner, and that ASM analysis was only able to identify 5%. Finally, we identified hundreds of clusters in the human genome for which the degree of variation of CpG methylation, as opposed to whether or not CpG sites were methylated, was associated with genetic polymorphisms, supporting a recent hypothesis on the genetic influence of phenotypic plasticity. These results show that cis-regulatory SNPs identified by mQTL do not comprise the full extent of heritable CpG methylation, and that ASM appears overall unreliable. Overall, the extent of genome-methylome interactions is well beyond what is detectible with the commonly used mQTL and ASM approaches, and is likely to include effects on plasticity
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