6 research outputs found

    COGA phenotypes and linkages on chromosome 2

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    An initial linkage analysis of the alcoholism phenotype as defined by DSM-III-R criteria and alcoholism defined by DSM-IV criteria showed many, sometimes striking, inconsistencies. These inconsistencies are greatly reduced by making the definition of alcoholism more specific. We defined new phenotypes combining the alcoholism definitions and the latent variables, defining an individual as affected if that individual is alcoholic under one of the definitions (either DSM-III-R or DSM-IV), and indicated having a symptom defined by one of the latent variables. This was done for each of the two alcoholism definitions and five latent variables, selected from a canonical discriminant analyses indicating they formed significant groupings using the electrophysiological variables. We found that linkage analyses utilizing these latent variables were much more robust and consistent than the linkage results based on DSM-III-R or DSM-IV criteria for definition of alcoholism. We also performed linkage analyses on two first prinicipal components derived phenotypes, one derived from the electrophysiolocical variables, and the other derived from the latent variables. A region on chromosome 2 at 250 cM was found to be linked to both of these derived phenotypes. Further examination of the SNPs in this region identified several haplotypes strongly associated with these derived phenotypes

    Ancestry reported by white adults with cutaneous melanoma and control subjects in central Alabama

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    BACKGROUND: We sought to evaluate the hypothesis that the high incidence of cutaneous melanoma in white persons in central Alabama is associated with a predominance of Irish and Scots descent. METHODS: Frequencies of country of ancestry reports were tabulated. The reports were also converted to scores that reflect proportional countries of ancestry in individuals. Using the scores, we computed aggregate country of ancestry indices as estimates of group ancestry composition. HLA-DRB1*04 allele frequencies and relationships to countries of ancestry were compared in probands and controls. Results were compared to those of European populations with HLA-DRB1*04 frequencies. RESULTS: Ninety evaluable adult white cutaneous melanoma probands and 324 adult white controls reported countries of ancestry of their grandparents. The respective frequencies of Ireland, and Scotland and "British Isles" reported countries of ancestry were significantly greater in probands than in controls. The respective frequencies of Wales, France, Italy and Poland were significantly greater in controls. 16.7% of melanoma probands and 23.8% of controls reported "Native American" ancestry; the corresponding "Native American" country of ancestry index was not significantly different in probands and controls. The frequency of HLA-DRB1*04 was significantly greater in probands, but was not significantly associated with individual or aggregate countries of ancestry. The frequency of DRB1*04 observed in Alabama was compared to DRB1*04 frequencies reported from England, Wales, Ireland, Orkney Island, France, Germany, and Australia. CONCLUSION: White adults with cutaneous melanoma in central Alabama have a predominance of Irish, Scots, and "British Isles" ancestry and HLA-DRB1*04 that likely contributes to their high incidence of cutaneous melanoma

    Comparison of measures of marker informativeness for ancestry and admixture mapping

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    <p>Abstract</p> <p>Background</p> <p>Admixture mapping is a powerful gene mapping approach for an admixed population formed from ancestral populations with different allele frequencies. The power of this method relies on the ability of ancestry informative markers (AIMs) to infer ancestry along the chromosomes of admixed individuals. In this study, more than one million SNPs from HapMap databases and simulated data have been interrogated in admixed populations using various measures of ancestry informativeness: Fisher Information Content (FIC), Shannon Information Content (SIC), F statistics (F<sub>ST</sub>), Informativeness for Assignment Measure (I<sub>n</sub>), and the Absolute Allele Frequency Differences (delta, δ). The objectives are to compare these measures of informativeness to select SNP markers for ancestry inference, and to determine the accuracy of AIM panels selected by each measure in estimating the contributions of the ancestors to the admixed population.</p> <p>Results</p> <p>F<sub>ST </sub>and I<sub>n </sub>had the highest Spearman correlation and the best agreement as measured by Kappa statistics based on deciles. Although the different measures of marker informativeness performed comparably well, analyses based on the top 1 to 10% ranked informative markers of simulated data showed that I<sub>n </sub>was better in estimating ancestry for an admixed population.</p> <p>Conclusions</p> <p>Although millions of SNPs have been identified, only a small subset needs to be genotyped in order to accurately predict ancestry with a minimal error rate in a cost-effective manner. In this article, we compared various methods for selecting ancestry informative SNPs using simulations as well as SNP genotype data from samples of admixed populations and showed that the I<sub>n </sub>measure estimates ancestry proportion (in an admixed population) with lower bias and mean square error.</p

    Spatial and temporal mapping of de novo mutations in schizophrenia to a fetal prefrontal cortical network.

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    Genes disrupted in schizophrenia may be revealed by&nbsp;de novo mutations in affected persons from otherwise&nbsp;healthy families. Furthermore, during normal brain development, genes are expressed in patterns specific to developmental stage and neuroanatomical structure. We identified de novo mutations in persons with schizophrenia and then mapped the responsible genes onto transcriptome profiles of normal human brain tissues from age 13&nbsp;weeks gestation to adulthood. In the dorsolateral and ventrolateral prefrontal cortex during fetal development, genes harboring damaging de novo mutations in schizophrenia formed a network significantly enriched for transcriptional coexpression and protein interaction. The 50 genes in the network function in neuronal migration, synaptic transmission, signaling, transcriptional regulation, and transport. These results suggest that disruptions of fetal prefrontal cortical neurogenesis are critical to the pathophysiology of schizophrenia. These results also support the feasibility of integrating genomic and transcriptome analyses to map critical neurodevelopmental processes in time and space in the brain
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