Dataset with genome-wide array data from Algerian Amazigh (Chaoui and Mozabite) and non-Amazigh individuals
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PROVIDER: EGAS00001007235 | EGA |
REPOSITORIES: EGA
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Project description:Study of high-coverage whole-exome sequences from Amazigh (Tamazight-speakers) and non-Amazigh individuals (Arab-speakers) from Tunisia to analyze the impact of demography in functional genomic variation in the complex demographic context of North Africa. Amazigh individuals were sampled in Chenini and Douiret, and non-Amazigh individuals were sampled in Tunis.
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Project description:Study of high-coverage whole-exome sequences from Amazigh (Tamazight-speakers) and non-Amazigh individuals (Arab-speakers) from Algeria to analyze the impact of demography in functional genomic variation in the complex demographic context of North Africa. Amazigh individuals were sampled in Oum El Bouaghi, Batna, Khenchela, and Ghardaïa, and non-Amazigh individuals were sampled in Algiers.
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Project description:BackgroundSchizophrenia is a disorder characterized by pervasive deficits in cognitive functioning. However, few well-powered studies have examined the degree to which cognitive performance is impaired even among individuals with schizophrenia not currently on antipsychotic medications using a wide range of cognitive and reinforcement learning measures derived from cognitive neuroscience. Such research is particularly needed in the domain of reinforcement learning, given the central role of dopamine in reinforcement learning, and the potential impact of antipsychotic medications on dopamine function.MethodsThe present study sought to fill this gap by examining healthy controls (N = 75), unmedicated (N = 48) and medicated (N = 148) individuals with schizophrenia. Participants were recruited across five sites as part of the CNTRaCS Consortium to complete tasks assessing processing speed, cognitive control, working memory, verbal learning, relational encoding and retrieval, visual integration and reinforcement learning.ResultsIndividuals with schizophrenia who were not taking antipsychotic medications, as well as those taking antipsychotic medications, showed pervasive deficits across cognitive domains including reinforcement learning, processing speed, cognitive control, working memory, verbal learning and relational encoding and retrieval. Further, we found that chlorpromazine equivalency rates were significantly related to processing speed and working memory, while there were no significant relationships between anticholinergic load and performance on other tasks.ConclusionsThese findings add to a body of literature suggesting that cognitive deficits are an enduring aspect of schizophrenia, present in those off antipsychotic medications as well as those taking antipsychotic medications.
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2011-10-12 | E-GEOD-32924 | biostudies-arrayexpress
Project description:BackgroundDepression is a debilitating mental disorder that often coexists with anxiety. The genetic mechanisms of depression and anxiety have considerable overlap, and studying depression in non-anxiety samples could help to discover novel gene. We assess the genetic variation of depression in non-anxiety samples, using genome-wide association studies (GWAS) and linkage disequilibrium score regression (LDSC).MethodsThe GWAS of depression score and self-reported depression were conducted using the UK Biobank samples, comprising 99,178 non-anxiety participants with anxiety score <5 and 86,503 non-anxiety participants without self-reported anxiety, respectively. Replication analysis was then performed using two large-scale GWAS summary data of depression from Psychiatric Genomics Consortium (PGC). LDSC was finally used to evaluate genetic correlations with 855 health-related traits based on the primary GWAS.ResultsTwo genome-wide significant loci for non-anxiety depression were identified: rs139702470 (p = 1.54 × 10-8, OR = 0.29) locate in PIEZO2, and rs6046722 (p = 2.52 × 10-8, OR = 1.09) locate in CFAP61. These associated genes were replicated in two GWAS of depression from PGC, such as rs1040582 (preplication GWAS1 = 0.02, preplication GWAS2 = 2.71 × 10-3) in CFAP61, and rs11661122 (preplication GWAS1 = 8.16 × 10-3, preplication GWAS2 = 8.08 × 10-3) in PIEZO2. LDSC identified 19 traits genetically associated with non-anxiety depression (p < 0.001), such as marital separation/divorce (rg = 0.45, SE = 0.15).ConclusionsOur findings provide novel clues for understanding of the complex genetic architecture of depression.
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