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Gialluisi, A., Dediu, D., Francks, C., & Fisher, S. E. (2013). Persistence and transmission of recessive deafness and sign language: New insights from village sign languages. European Journal of Human Genetics, 21, 894-896. doi:10.1038/ejhg.2012.292.
Abstract
First paragraph: The study of the transmission of sign languages can give novel insights into the transmission of spoken languages1 and, more generally, into gene–culture coevolution. Over the years, several papers related to the persistence of sign language have been
reported.2–6 All of these studies have emphasized the role of assortative (non-random) mating by deafness state (ie, a tendency for deaf individuals to partner together) for increasing the frequency of recessive deafness, and hence for the persistence of sign language in a population. -
Stephens, S., Hartz, S., Hoft, N., Saccone, N., Corley, R., Hewitt, J., Hopfer, C., Breslau, N., Coon, H., Chen, X., Ducci, F., Dueker, N., Franceschini, N., Frank, J., Han, Y., Hansel, N., Jiang, C., Korhonen, T., Lind, P., Liu, J. and 105 moreStephens, S., Hartz, S., Hoft, N., Saccone, N., Corley, R., Hewitt, J., Hopfer, C., Breslau, N., Coon, H., Chen, X., Ducci, F., Dueker, N., Franceschini, N., Frank, J., Han, Y., Hansel, N., Jiang, C., Korhonen, T., Lind, P., Liu, J., Michel, M., Lyytikäinen, L.-P., Shaffer, J., Short, S., Sun, J., Teumer, A., Thompson, J., Vogelzangs, N., Vink, J., Wenzlaff, A., Wheeler, W., Yang, B.-Z., Aggen, S., Balmforth, A., Baumesiter, S., Beaty, T., Benjamin, D., Bergen, A., Broms, U., Cesarini, D., Chatterjee, N., Chen, J., Cheng, Y.-C., Cichon, S., Couper, D., Cucca, F., Dick, D., Foround, T., Furberg, H., Giegling, I., Gillespie, N., Gu, F.,.Hall, A., Hällfors, J., Han, S., Hartmann, A., Heikkilä, K., Hickie, I., Hottenga, J., Jousilahti, P., Kaakinen, M., Kähönen, M., Koellinger, P., Kittner, S., Konte, B., Landi, M.-T., Laatikainen, T., Leppert, M., Levy, S., Mathias, R., McNeil, D., Medlund, S., Montgomery, G., Murray, T., Nauck, M., North, K., Paré, P., Pergadia, M., Ruczinski, I., Salomaa, V., Viikari, J., Willemsen, G., Barnes, K., Boerwinkle, E., Boomsma, D., Caporaso, N., Edenberg, H., Francks, C., Gelernter, J., Grabe, H., Hops, H., Jarvelin, M.-R., Johannesson, M., Kendler, K., Lehtimäki, T., Magnusson, P., Marazita, M., Marchini, J., Mitchell, B., Nöthen, M., Penninx, B., Raitakari, O., Rietschel, M., Rujescu, D., Samani, N., Schwartz, A., Shete, S., Spitz, M., Swan, G., Völzke, H., Veijola, J., Wei, Q., Amos, C., Canon, D., Grucza, R., Hatsukami, D., Heath, A., Johnson, E., Kaprio, J., Madden, P., Martin, N., Stevens, V., Weiss, R., Kraft, P., Bierut, L., & Ehringer, M. (2013). Distinct Loci in the CHRNA5/CHRNA3/CHRNB4 Gene Cluster are Associated with Onset of Regular Smoking. Genetic Epidemiology, 37, 846-859. doi:10.1002/gepi.21760.
Abstract
Neuronal nicotinic acetylcholine receptor (nAChR) genes (CHRNA5/CHRNA3/CHRNB4) have been reproducibly associated with nicotine dependence, smoking behaviors, and lung cancer risk. Of the few reports that have focused on early smoking behaviors, association results have been mixed. This meta-analysis examines early smoking phenotypes and SNPs in the gene cluster to determine: (1) whether the most robust association signal in this region (rs16969968) for other smoking behaviors is also associated with early behaviors, and/or (2) if additional statistically independent signals are important in early smoking. We focused on two phenotypes: age of tobacco initiation (AOI) and age of first regular tobacco use (AOS). This study included 56,034 subjects (41 groups) spanning nine countries and evaluated five SNPs including rs1948, rs16969968, rs578776, rs588765, and rs684513. Each dataset was analyzed using a centrally generated script. Meta-analyses were conducted from summary statistics. AOS yielded significant associations with SNPs rs578776 (beta = 0.02, P = 0.004), rs1948 (beta = 0.023, P = 0.018), and rs684513 (beta = 0.032, P = 0.017), indicating protective effects. There were no significant associations for the AOI phenotype. Importantly, rs16969968, the most replicated signal in this region for nicotine dependence, cigarettes per day, and cotinine levels, was not associated with AOI (P = 0.59) or AOS (P = 0.92). These results provide important insight into the complexity of smoking behavior phenotypes, and suggest that association signals in the CHRNA5/A3/B4 gene cluster affecting early smoking behaviors may be different from those affecting the mature nicotine dependence phenotypeAdditional information
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Fisher, S. E., & Francks, C. (2006). Genes, cognition and dyslexia: Learning to read the genome. Trends in Cognitive Sciences, 10, 250-257. doi:10.1016/j.tics.2006.04.003.
Abstract
Studies of dyslexia provide vital insights into the cognitive architecture underpinning both disordered and normal reading. It is well established that inherited factors contribute to dyslexia susceptibility, but only very recently has evidence emerged to implicate specific candidate genes. In this article, we provide an accessible overview of four prominent examples--DYX1C1, KIAA0319, DCDC2 and ROBO1--and discuss their relevance for cognition. In each case correlations have been found between genetic variation and reading impairments, but precise risk variants remain elusive. Although none of these genes is specific to reading-related neuronal circuits, or even to the human brain, they have intriguing roles in neuronal migration or connectivity. Dissection of cognitive mechanisms that subserve reading will ultimately depend on an integrated approach, uniting data from genetic investigations, behavioural studies and neuroimaging. -
Ogdie, M. N., Bakker, S. C., Fisher, S. E., Francks, C., Yang, M. H., Cantor, R. M., Loo, S. K., Van der Meulen, E., Pearson, P., Buitelaar, J., Monaco, A., Nelson, S. F., Sinke, R. J., & Smalley, S. L. (2006). Pooled genome-wide linkage data on 424 ADHD ASPs suggests genetic heterogeneity and a common risk locus at 5p13 [Letter to the editor]. Molecular Psychiatry, 11, 5-8. doi:10.1038/sj.mp.4001760.
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Paracchini, S., Thomas, A., Castro, S., Lai, C., Paramasivam, M., Wang, Y., Keating, B. J., Taylor, J. M., Hacking, D. F., Scerri, T., Francks, C., Richardson, A. J., Wade-Martins, R., Stein, J. F., Knight, J. C., Copp, A. J., LoTurco, J., & Monaco, A. P. (2006). The chromosome 6p22 haplotype associated with dyslexia reduces the expression of KIAA0319, a novel gene involved in neuronal migration. Human Molecular Genetics, 15(10), 1659-1666. doi:10.1093/hmg/ddl089.
Abstract
Dyslexia is one of the most prevalent childhood cognitive disorders, affecting approximately 5% of school-age children. We have recently identified a risk haplotype associated with dyslexia on chromosome 6p22.2 which spans the TTRAP gene and portions of THEM2 and KIAA0319. Here we show that in the presence of the risk haplotype, the expression of the KIAA0319 gene is reduced but the expression of the other two genes remains unaffected. Using in situ hybridization, we detect a very distinct expression pattern of the KIAA0319 gene in the developing cerebral neocortex of mouse and human fetuses. Moreover, interference with rat Kiaa0319 expression in utero leads to impaired neuronal migration in the developing cerebral neocortex. These data suggest a direct link between a specific genetic background and a biological mechanism leading to the development of dyslexia: the risk haplotype on chromosome 6p22.2 down-regulates the KIAA0319 gene which is required for neuronal migration during the formation of the cerebral neocortex. -
Gayán, J., Willcutt, E. G., Fisher, S. E., Francks, C., Cardon, L. R., Olson, R. K., Pennington, B. F., Smith, S., Monaco, A. P., & DeFries, J. C. (2005). Bivariate linkage scan for reading disability and attention-deficit/hyperactivity disorder localizes pleiotropic loci. Journal of Child Psychology and Psychiatry, 46(10), 1045-1056. doi:10.1111/j.1469-7610.2005.01447.x.
Abstract
BACKGROUND: There is a growing interest in the study of the genetic origins of comorbidity, a direct consequence of the recent findings of genetic loci that are seemingly linked to more than one disorder. There are several potential causes for these shared regions of linkage, but one possibility is that these loci may harbor genes with manifold effects. The established genetic correlation between reading disability (RD) and attention-deficit/hyperactivity disorder (ADHD) suggests that their comorbidity is due at least in part to genes that have an impact on several phenotypes, a phenomenon known as pleiotropy. METHODS: We employ a bivariate linkage test for selected samples that could help identify these pleiotropic loci. This linkage method was employed to carry out the first bivariate genome-wide analysis for RD and ADHD, in a selected sample of 182 sibling pairs. RESULTS: We found evidence for a novel locus at chromosome 14q32 (multipoint LOD=2.5; singlepoint LOD=3.9) with a pleiotropic effect on RD and ADHD. Another locus at 13q32, which had been implicated in previous univariate scans of RD and ADHD, seems to have a pleiotropic effect on both disorders. 20q11 is also suggested as a pleiotropic locus. Other loci previously implicated in RD or ADHD did not exhibit bivariate linkage. CONCLUSIONS: Some loci are suggested as having pleiotropic effects on RD and ADHD, while others might have unique effects. These results highlight the utility of this bivariate linkage method to study pleiotropy.
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