70 research outputs found

    Mapping genomic loci implicates genes and synaptic biology in schizophrenia

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    Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies

    Probing the Association between Early Evolutionary Markers and Schizophrenia

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    <div><p>Schizophrenia is suggested to be a by-product of the evolution in humans, a compromise for our language, creative thinking and cognitive abilities, and thus, essentially, a human disorder. The time of its origin during the course of human evolution remains unclear. Here we investigate several markers of early human evolution and their relationship to the genetic risk of schizophrenia. We tested the schizophrenia evolutionary hypothesis by analyzing genome-wide association studies of schizophrenia and other human phenotypes in a statistical framework suited for polygenic architectures. We analyzed evolutionary proxy measures: human accelerated regions, segmental duplications, and ohnologs, representing various time periods of human evolution for overlap with the human genomic loci associated with schizophrenia. Polygenic enrichment plots suggest a higher prevalence of schizophrenia associations in human accelerated regions, segmental duplications and ohnologs. However, the enrichment is mostly accounted for by linkage disequilibrium, especially with functional elements like introns and untranslated regions. Our results did not provide clear evidence that markers of early human evolution are more likely associated with schizophrenia. While SNPs associated with schizophrenia are enriched in HAR, Ohno and SD regions, the enrichment seems to be mediated by affiliation to known genomic enrichment categories. Taken together with previous results, these findings suggest that schizophrenia risk may have mainly developed more recently in human evolution.</p></div

    Combinations of genetic variants associated with bipolar disorder

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    <div><p>The main objective of the study was to find genetic variants that in combination are significantly associated with bipolar disorder. In previous studies of bipolar disorder, combinations of three and four single nucleotide polymorphisms (SNP) genotypes taken from 803 SNPs were analyzed, and five clusters of combinations were found to be significantly associated with bipolar disorder. In the present study, combinations of ten SNP genotypes taken from the same 803 SNPs were analyzed, and one cluster of combinations was found to be significantly associated with bipolar disorder. Combinations from the new cluster and from the five previous clusters were identified in the genomes of 266 or 44% of the 607 patients in the study whereas none of the 1355 control participants had any of these combinations in their genome.The SNP genotypes in the smaller combinations were the normal homozygote, heterozygote or variant homozygote. In the combinations containing 10 SNP genotypes almost all the genotypes were the normal homozygote. Such a finding may indicate that accumulation in the genome of combinations containing few SNP genotypes may be a risk factor for bipolar disorder when those combinations contain relatively many rare SNP genotypes, whereas combinations need to contain many SNP genotypes to be a risk factor when most of the SNP genotypes are the normal homozygote.</p></div

    Combinations of Genetic Data Present in Bipolar Patients, but Absent in Control Persons

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    <div><p>The main objective of the study was to find combinations of genetic variants significantly associated with bipolar disorder. In a previous study of bipolar disorder, combinations of three single nucleotide polymorphism (SNP) genotypes taken from 803 SNPs were analyzed, and four clusters of combinations were found to be significantly associated with bipolar disorder. In the present study, combinations of four SNP genotypes taken from the same 803 SNPs were analyzed, and one cluster of combinations was found to be significantly associated with bipolar disorder. Combinations from the new cluster and from the four previous clusters were identified in the genomes of 209 of the 607 patients in the study whereas none of the 1355 control participants had any of these combinations in their genome.</p></div

    Conditional FDR; SCZ loci given BD (SCZ|BD).

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    <p>Independent complex or single gene loci (r<sup>2</sup><0.2) with SNP(s) with a conditional FDR (condFDR)<0.05 in schizophrenia (SCZ) given the association in bipolar disorder (BD). We defined the most significant SCZ SNP in each LD block based on the minimum condFDR for BD. The most significant SNPs in each LD block are listed. All loci with SNPs with condFDR<0.05 were used to define the number of the loci. Chromosome location (Chr). SCZ FDR values<0.05 are in bold.</p>†<p>Same locus identified in previous SCZ genome-wide association studies. All data were first corrected for genomic inflation.</p

    Gene expression data of the Allen Human Brain Atlas were mapped onto the 12 genetically based cortical regions in the MR space.

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    <p>A) Resulting volume registration between FreeSurfer surface (fsaverage) and Allen brain MNI coordinates displayed as a point cloud, with a slice of the MRI imaging at the bottom (colin27). B) After the volume registration, gene expression data points are mapped to FreeSurfer surface vertices by assigning each surface vertex the gene expression of the closest (Euclidean distance) Allen brain data point using nearest neighbor interpolation. If two vertices have the same closest Allen brain data point, they belong to the same patch and the patch id is displayed as color. Thus, the color patches illustrate the local density of data points. The color patches with similar sizes across the cortex represent an even distribution of Allen brain data points and their surface correspondences. Colors of the dots in both (A) and (B) panels represent cortical regions to which they were assigned, corresponding to the color schemes in <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1006143#pgen.1006143.g001" target="_blank">Fig 1B</a>.</p

    Association of <i>DCKL1</i> genetic variants with psychiatric and cognitive traits.

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    <p>Markers are ordered from 5′ to 3′ of the gene, anti-sense to the reference sequence. <b>A.</b> Representation of the genomic region covered and of 6 <i>DCLK1</i> transcripts (from top to bottom: <i>DCL</i>, <i>CARP</i>, 2 short variants and 2 long variants). In addition to alternative start sites, the transcripts can be alternatively spliced for part of exon 9, for exon 19 and in the 3′UTR. <b>B.</b> All markers showing nominal association to psychiatric traits in this study or to cognitive traits in our previous study <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0035424#pone.0035424-LeHellard1" target="_blank">[16]</a> are displayed. Color code: yellow, P-value between 0.05 and 0.001; orange, P-value between 0.001 and 0.0001; red, P-value<0.0001; white, P-value>0.05; grey, marker not tested in this sample. The markers used in the cross-phenotype analyses are highlighted in red. <b>C.</b> LD between the markers used in the cross-phenotype analyses, and the markers associated with cognitive traits in our previous study <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0035424#pone.0035424-LeHellard1" target="_blank">[16]</a>. LD is displayed using a r<sup>2</sup> scale ranging from r<sup>2</sup> = 1 in black to r<sup>2</sup> = 0 in white.</p
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