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Hartz, S. M., Short, S. E., Saccone, N. L., Culverhouse, R., Chen, L., Schwantes-An, T.-H., Coon, H., Han, Y., Stephens, S. H., Sun, J., Chen, X., Ducci, F., Dueker, N., Franceschini, N., Frank, J., Geller, F., Gubjartsson, D., Hansel, N. N., Jiang, C., Keskitalo-Vuokko, K. and 132 moreHartz, S. M., Short, S. E., Saccone, N. L., Culverhouse, R., Chen, L., Schwantes-An, T.-H., Coon, H., Han, Y., Stephens, S. H., Sun, J., Chen, X., Ducci, F., Dueker, N., Franceschini, N., Frank, J., Geller, F., Gubjartsson, D., Hansel, N. N., Jiang, C., Keskitalo-Vuokko, K., Liu, Z., Lyytikainen, L.-P., Michel, M., Rawal, R., Rosenberger, A., Scheet, P., Shaffer, J. R., Teumer, A., Thompson, J. R., Vink, J. M., Vogelzangs, N., Wenzlaff, A. S., Wheeler, W., Xiao, X., Yang, B.-Z., Aggen, S. H., Balmforth, A. J., Baumeister, S. E., Beaty, T., Bennett, S., Bergen, A. W., Boyd, H. A., Broms, U., Campbell, H., Chatterjee, N., Chen, J., Cheng, Y.-C., Cichon, S., Couper, D., Cucca, F., Dick, D. M., Foroud, T., Furberg, H., Giegling, I., Gu, F., Hall, A. S., Hallfors, J., Han, S., Hartmann, A. M., Hayward, C., Heikkila, K., Hewitt, J. K., Hottenga, J. J., Jensen, M. K., Jousilahti, P., Kaakinen, M., Kittner, S. J., Konte, B., Korhonen, T., Landi, M.-T., Laatikainen, T., Leppert, M., Levy, S. M., Mathias, R. A., McNeil, D. W., Medland, S. E., Montgomery, G. W., Muley, T., Murray, T., Nauck, M., North, K., Pergadia, M., Polasek, O., Ramos, E. M., Ripatti, S., Risch, A., Ruczinski, I., Rudan, I., Salomaa, V., Schlessinger, D., Styrkarsdottir, U., Terracciano, A., Uda, M., Willemsen, G., Wu, X., Abecasis, G., Barnes, K., Bickeboller, H., Boerwinkle, E., Boomsma, D. I., Caporaso, N., Duan, J., Edenberg, H. J., Francks, C., Gejman, P. V., Gelernter, J., Grabe, H. J., Hops, H., Jarvelin, M.-R., Viikari, J., Kahonen, M., Kendler, K. S., Lehtimaki, T., Levinson, D. F., Marazita, M. L., Marchini, J., Melbye, M., Mitchell, B., Murray, J. C., Nothen, M. M., Penninx, B. W., Raitakari, O., Rietschel, M., Rujescu, D., Samani, N. J., Sanders, A. R., Schwartz, A. G., Shete, S., Shi, J., Spitz, M., Stefansson, K., Swan, G. E., Thorgeirsson, T., Volzke, H., Wei, Q., Wichmann, H.-E., Amos, C. I., Breslau, N., Cannon, D. S., Ehringer, M., Grucza, R., Hatsukami, D., Heath, A., Johnson, E. O., Kaprio, J., Madden, P., Martin, N. G., Stevens, V. L., Stitzel, J. A., Weiss, R. B., Kraft, P., & Bierut, L. J. (2012). Increased genetic vulnerability to smoking at CHRNA5 in early-onset smokers. Archives of General Psychiatry, 69, 854-860. doi:10.1001/archgenpsychiatry.2012.124.
Abstract
CONTEXT Recent studies have shown an association between cigarettes per day (CPD) and a nonsynonymous single-nucleotide polymorphism in CHRNA5, rs16969968. OBJECTIVE To determine whether the association between rs16969968 and smoking is modified by age at onset of regular smoking. DATA SOURCES Primary data. STUDY SELECTION Available genetic studies containing measures of CPD and the genotype of rs16969968 or its proxy. DATA EXTRACTION Uniform statistical analysis scripts were run locally. Starting with 94 050 ever-smokers from 43 studies, we extracted the heavy smokers (CPD >20) and light smokers (CPD ≤10) with age-at-onset information, reducing the sample size to 33 348. Each study was stratified into early-onset smokers (age at onset ≤16 years) and late-onset smokers (age at onset >16 years), and a logistic regression of heavy vs light smoking with the rs16969968 genotype was computed for each stratum. Meta-analysis was performed within each age-at-onset stratum. DATA SYNTHESIS Individuals with 1 risk allele at rs16969968 who were early-onset smokers were significantly more likely to be heavy smokers in adulthood (odds ratio [OR] = 1.45; 95% CI, 1.36-1.55; n = 13 843) than were carriers of the risk allele who were late-onset smokers (OR = 1.27; 95% CI, 1.21-1.33, n = 19 505) (P = .01). CONCLUSION These results highlight an increased genetic vulnerability to smoking in early-onset smokers.Additional information
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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. -
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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