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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. -
Bailey, A., Hervas, A., Matthews, N., Palferman, S., Wallace, S., Aubin, A., Michelotti, J., Wainhouse, C., Papanikolaou, K., Rutter, M., Maestrini, E., Marlow, A., Weeks, D. E., Lamb, J., Francks, C., Kearsley, G., Scudder, P., Monaco, A. P., Baird, G., Cox, A. and 46 moreBailey, A., Hervas, A., Matthews, N., Palferman, S., Wallace, S., Aubin, A., Michelotti, J., Wainhouse, C., Papanikolaou, K., Rutter, M., Maestrini, E., Marlow, A., Weeks, D. E., Lamb, J., Francks, C., Kearsley, G., Scudder, P., Monaco, A. P., Baird, G., Cox, A., Cockerill, H., Nuffield, F., Le Couteur, A., Berney, T., Cooper, H., Kelly, T., Green, J., Whittaker, J., Gilchrist, A., Bolton, P., Schönewald, A., Daker, M., Ogilvie, C., Docherty, Z., Deans, Z., Bolton, B., Packer, R., Poustka, F., Rühl, D., Schmötzer, G., Bölte, S., Klauck, S. M., Spieler, A., Poustka., A., Van Engeland, H., Kemner, C., De Jonge, M., Den Hartog, I., Lord, C., Cook, E., Leventhal, B., Volkmar, F., Pauls, D., Klin, A., Smalley, S., Fombonne, E., Rogé, B., Tauber, M., Arti-Vartayan, E., Fremolle-Kruck., J., Pederson, L., Haracopos, D., Brondum-Nielsen, K., & Cotterill, R. (1998). A full genome screen for autism with evidence for linkage to a region on chromosome 7q. International Molecular Genetic Study of Autism Consortium. Human Molecular Genetics, 7(3), 571-578. doi:10.1093/hmg/7.3.571.
Abstract
Autism is characterized by impairments in reciprocal social interaction and communication, and restricted and sterotyped patterns of interests and activities. Developmental difficulties are apparent before 3 years of age and there is evidence for strong genetic influences most likely involving more than one susceptibility gene. A two-stage genome search for susceptibility loci in autism was performed on 87 affected sib pairs plus 12 non-sib affected relative-pairs, from a total of 99 families identified by an international consortium. Regions on six chromosomes (4, 7, 10, 16, 19 and 22) were identified which generated a multipoint maximum lod score (MLS) > 1. A region on chromosome 7q was the most significant with an MLS of 3.55 near markers D7S530 and D7S684 in the subset of 56 UK affected sib-pair families, and an MLS of 2.53 in all 87 affected sib-pair families. An area on chromosome 16p near the telomere was the next most significant, with an MLS of 1.97 in the UK families, and 1.51 in all families. These results are an important step towards identifying genes predisposing to autism; establishing their general applicability requires further study.
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