Beate St Pourcain

Publications

Displaying 1 - 20 of 20
  • Nivard, M. G., Gage, S. H., Hottenga, J. J., van Beijsterveldt, C. E. M., Abdellaoui, A., Bartels, M., Baselmans, B. M. L., Ligthart, L., St Pourcain, B., Boomsma, D. I., Munafò, M. R., & Middeldorp, C. M. (2017). Genetic overlap between schizophrenia and developmental psychopathology: Longitudinal and multivariate polygenic risk prediction of common psychiatric traits during development. Schizophrenia Bulletin, 43(6), 1197-1207. doi:10.1093/schbul/sbx031.

    Abstract

    Background: Several nonpsychotic psychiatric disorders in childhood and adolescence can precede the onset of schizophrenia, but the etiology of this relationship remains unclear. We investigated to what extent the association between schizophrenia and psychiatric disorders in childhood is explained by correlated genetic risk factors. Methods: Polygenic risk scores (PRS), reflecting an individual’s genetic risk for schizophrenia, were constructed for 2588 children from the Netherlands Twin Register (NTR) and 6127 from the Avon Longitudinal Study of Parents And Children (ALSPAC). The associations between schizophrenia PRS and measures of anxiety, depression, attention deficit hyperactivity disorder (ADHD), and oppositional defiant disorder/conduct disorder (ODD/CD) were estimated at age 7, 10, 12/13, and 15 years in the 2 cohorts. Results were then meta-analyzed, and a meta-regression analysis was performed to test differences in effects sizes over, age and disorders. Results: Schizophrenia PRS were associated with childhood and adolescent psychopathology. Meta-regression analysis showed differences in the associations over disorders, with the strongest association with childhood and adolescent depression and a weaker association for ODD/CD at age 7. The associations increased with age and this increase was steepest for ADHD and ODD/CD. Genetic correlations varied between 0.10 and 0.25. Conclusion: By optimally using longitudinal data across diagnoses in a multivariate meta-analysis this study sheds light on the development of childhood disorders into severe adult psychiatric disorders. The results are consistent with a common genetic etiology of schizophrenia and developmental psychopathology as well as with a stronger shared genetic etiology between schizophrenia and adolescent onset psychopathology.
  • Nivard, M. G., Lubke, G. H., Dolan, C. V., Evans, D. M., St Pourcain, B., Munafo, M. R., & Middeldorp, C. M. (2017). Joint developmental trajectories of internalizing and externalizing disorders between childhood and adolescence. Development and Psychopathology, 29(3), 919-928. doi:10.1017/S0954579416000572.

    Abstract

    This study sought to identify trajectories of DSM-IV based internalizing (INT) and externalizing (EXT) problem scores across childhood and adolescence and to provide insight into the comorbidity by modeling the co-occurrence of INT and EXT trajectories. INT and EXT were measured repeatedly between age 7 and age 15 years in over 7,000 children and analyzed using growth mixture models. Five trajectories were identified for both INT and EXT, including very low, low, decreasing, and increasing trajectories. In addition, an adolescent onset trajectory was identified for INT and a stable high trajectory was identified for EXT. Multinomial regression showed that similar EXT and INT trajectories were associated. However, the adolescent onset INT trajectory was independent of high EXT trajectories, and persisting EXT was mainly associated with decreasing INT. Sex and early life environmental risk factors predicted EXT and, to a lesser extent, INT trajectories. The association between trajectories indicates the need to consider comorbidity when a child presents with INT or EXT disorders, particularly when symptoms start early. This is less necessary when INT symptoms start at adolescence. Future studies should investigate the etiology of co-occurring INT and EXT and the specific treatment needs of these severely affected children.
  • Stergiakouli, E., Martin, J., Hamshere, M. L., Heron, J., St Pourcain, B., Timpson, N. J., Thapar, A., & Smith, G. D. (2017). Association between polygenic risk scores for attention-deficit hyperactivity disorder and educational and cognitive outcomes in the general population. International Journal of Epidemiology, 46(2), 421-428. doi:10.1093/ije/dyw216.

    Abstract

    Background: Children with a diagnosis of attention-deficit hyperactivity disorder (ADHD) have lower cognitive ability and are at risk of adverse educational outcomes; ADHD genetic risks have been found to predict childhood cognitive ability and other neurodevelopmental traits in the general population; thus genetic risks might plausibly also contribute to cognitive ability later in development and to educational underachievement.

    Methods: We generated ADHD polygenic risk scores in the Avon Longitudinal Study of Parents and Children participants (maximum N: 6928 children and 7280 mothers) based on the results of a discovery clinical sample, a genome-wide association study of 727 cases with ADHD diagnosis and 5081 controls. We tested if ADHD polygenic risk scores were associated with educational outcomes and IQ in adolescents and their mothers.

    Results: High ADHD polygenic scores in adolescents were associated with worse educational outcomes at Key Stage 3 [national tests conducted at age 13–14 years; β = −1.4 (−2.0 to −0.8), P = 2.3 × 10−6), at General Certificate of Secondary Education exams at age 15–16 years (β = −4.0 (−6.1 to −1.9), P = 1.8 × 10−4], reduced odds of sitting Key Stage 5 examinations at age 16–18 years [odds ratio (OR) = 0.90 (0.88 to 0.97), P = 0.001] and lower IQ scores at age 15.5 [β = −0.8 (−1.2 to −0.4), P = 2.4 × 10−4]. Moreover, maternal ADHD polygenic scores were associated with lower maternal educational achievement [β = −0.09 (−0.10 to −0.06), P = 0.005] and lower maternal IQ [β = −0.6 (−1.2 to −0.1), P = 0.03].

    Conclusions: ADHD diagnosis risk alleles impact on functional outcomes in two generations (mother and child) and likely have intergenerational environmental effects.
  • Stergiakouli, E., Smith, G. D., Martin, J., Skuse, D. H., Viechtbauer, W., Ring, S. M., Ronald, A., Evans, D. E., Fisher, S. E., Thapar, A., & St Pourcain, B. (2017). Shared genetic influences between dimensional ASD and ADHD symptoms during child and adolescent development. Molecular Autism, 8: 18. doi:10.1186/s13229-017-0131-2.

    Abstract

    Background: Shared genetic influences between attention-deficit/hyperactivity disorder (ADHD) symptoms and
    autism spectrum disorder (ASD) symptoms have been reported. Cross-trait genetic relationships are, however,
    subject to dynamic changes during development. We investigated the continuity of genetic overlap between ASD
    and ADHD symptoms in a general population sample during childhood and adolescence. We also studied uni- and
    cross-dimensional trait-disorder links with respect to genetic ADHD and ASD risk.
    Methods: Social-communication difficulties (N ≤ 5551, Social and Communication Disorders Checklist, SCDC) and
    combined hyperactive-impulsive/inattentive ADHD symptoms (N ≤ 5678, Strengths and Difficulties Questionnaire,
    SDQ-ADHD) were repeatedly measured in a UK birth cohort (ALSPAC, age 7 to 17 years). Genome-wide summary
    statistics on clinical ASD (5305 cases; 5305 pseudo-controls) and ADHD (4163 cases; 12,040 controls/pseudo-controls)
    were available from the Psychiatric Genomics Consortium. Genetic trait variances and genetic overlap between
    phenotypes were estimated using genome-wide data.
    Results: In the general population, genetic influences for SCDC and SDQ-ADHD scores were shared throughout
    development. Genetic correlations across traits reached a similar strength and magnitude (cross-trait rg ≤ 1,
    pmin = 3 × 10−4) as those between repeated measures of the same trait (within-trait rg ≤ 0.94, pmin = 7 × 10−4).
    Shared genetic influences between traits, especially during later adolescence, may implicate variants in K-RAS signalling
    upregulated genes (p-meta = 6.4 × 10−4).
    Uni-dimensionally, each population-based trait mapped to the expected behavioural continuum: risk-increasing alleles
    for clinical ADHD were persistently associated with SDQ-ADHD scores throughout development (marginal regression
    R2 = 0.084%). An age-specific genetic overlap between clinical ASD and social-communication difficulties during
    childhood was also shown, as per previous reports. Cross-dimensionally, however, neither SCDC nor SDQ-ADHD scores
    were linked to genetic risk for disorder.
    Conclusions: In the general population, genetic aetiologies between social-communication difficulties and ADHD
    symptoms are shared throughout child and adolescent development and may implicate similar biological pathways
    that co-vary during development. Within both the ASD and the ADHD dimension, population-based traits are also linked
    to clinical disorder, although much larger clinical discovery samples are required to reliably detect cross-dimensional
    trait-disorder relationships.
  • Tachmazidou, I., Süveges, D., Min, J. L., Ritchie, G. R. S., Steinberg, J., Walter, K., Iotchkova, V., Schwartzentruber, J., Huang, J., Memari, Y., McCarthy, S., Crawford, A. A., Bombieri, C., Cocca, M., Farmaki, A.-E., Gaunt, T. R., Jousilahti, P., Kooijman, M. N., Lehne, B., Malerba, G. and 83 moreTachmazidou, I., Süveges, D., Min, J. L., Ritchie, G. R. S., Steinberg, J., Walter, K., Iotchkova, V., Schwartzentruber, J., Huang, J., Memari, Y., McCarthy, S., Crawford, A. A., Bombieri, C., Cocca, M., Farmaki, A.-E., Gaunt, T. R., Jousilahti, P., Kooijman, M. N., Lehne, B., Malerba, G., Männistö, S., Matchan, A., Medina-Gomez, C., Metrustry, S. J., Nag, A., Ntalla, I., Paternoster, L., Rayner, N. W., Sala, C., Scott, W. R., Shihab, H. A., Southam, L., St Pourcain, B., Traglia, M., Trajanoska, K., Zaza, G., Zhang, W., Artigas, M. S., Bansal, N., Benn, M., Chen, Z., Danecek, P., Lin, W.-Y., Locke, A., Luan, J., Manning, A. K., Mulas, A., Sidore, C., Tybjaerg-Hansen, A., Varbo, A., Zoledziewska, M., Finan, C., Hatzikotoulas, K., Hendricks, A. E., Kemp, J. P., Moayyeri, A., Panoutsopoulou, K., Szpak, M., Wilson, S. G., Boehnke, M., Cucca, F., Di Angelantonio, E., Langenberg, C., Lindgren, C., McCarthy, M. I., Morris, A. P., Nordestgaard, B. G., Scott, R. A., Tobin, M. D., Wareham, N. J., Burton, P., Chambers, J. C., Smith, G. D., Dedoussis, G., Felix, J. F., Franco, O. H., Gambaro, G., Gasparini, P., Hammond, C. J., Hofman, A., Jaddoe, V. W. V., Kleber, M., Kooner, J. S., Perola, M., Relton, C., Ring, S. M., Rivadeneira, F., Salomaa, V., Spector, T. D., Stegle, O., Toniolo, D., Uitterlinden, A. G., Barroso, I., Greenwood, C. M. T., Perry, J. R. B., Walker, B. R., Butterworth, A. S., Xue, Y., Durbin, R., Small, K. S., Soranzo, N., Timpson, N. J., & Zeggini, E. (2017). Whole-Genome Sequencing coupled to imputation discovers genetic signals for anthropometric traits. The American Journal of Human Genetics, 100(6), 865-884. doi:10.1016/j.ajhg.2017.04.014.

    Abstract

    Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common- and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.
  • Bønnelykke, K., Matheson, M. C., Pers, T. H., Granell, R., Strachan, D. P., Alves, A. C., Linneberg, A., Curtin, J. A., Warrington, N. M., Standl, M., Kerkhof, M., Jonsdottir, I., Bukvic, B. K., Kaakinen, M., Sleimann, P., Thorleifsson, G., Thorsteinsdottir, U., Schramm, K., Baltic, S., Kreiner-Møller, E. and 47 moreBønnelykke, K., Matheson, M. C., Pers, T. H., Granell, R., Strachan, D. P., Alves, A. C., Linneberg, A., Curtin, J. A., Warrington, N. M., Standl, M., Kerkhof, M., Jonsdottir, I., Bukvic, B. K., Kaakinen, M., Sleimann, P., Thorleifsson, G., Thorsteinsdottir, U., Schramm, K., Baltic, S., Kreiner-Møller, E., Simpson, A., St Pourcain, B., Coin, L., Hui, J., Walters, E. H., Tiesler, C. M. T., Duffy, D. L., Jones, G., Ring, S. M., McArdle, W. L., Price, L., Robertson, C. F., Pekkanen, J., Tang, C. S., Thiering, E., Montgomery, G. W., Hartikainen, A.-L., Dharmage, S. C., Husemoen, L. L., Herder, C., Kemp, J. P., Elliot, P., James, A., Waldenberger, M., Abramson, M. J., Fairfax, B. P., Knight, J. C., Gupta, R., Thompson, P. J., Holt, P., Sly, P., Hirschhorn, J. N., Blekic, M., Weidinger, S., Hakonarsson, H., Stefansson, K., Heinrich, J., Postma, D. S., Custovic, A., Pennell, C. E., Jarvelin, M.-R., Koppelman, G. H., Timpson, N., Ferreira, M. A., Bisgaard, H., Henderson, A. J., Australian Asthma Genetics Consortium (AAGC), & EArly Genetics and Lifecourse Epidemiology (EAGLE) Consortium (2013). Meta-analysis of genome-wide association studies identifies ten loci influencing allergic sensitization. Nature Genetics, 45(8), 902-906. doi:10.1038/ng.2694.

    Abstract

    Allergen-specific immunoglobulin E (present in allergic sensitization) has a central role in the pathogenesis of allergic disease. We performed the first large-scale genome-wide association study (GWAS) of allergic sensitization in 5,789 affected individuals and 10,056 controls and followed up the top SNP at each of 26 loci in 6,114 affected individuals and 9,920 controls. We increased the number of susceptibility loci with genome-wide significant association with allergic sensitization from three to ten, including SNPs in or near TLR6, C11orf30, STAT6, SLC25A46, HLA-DQB1, IL1RL1, LPP, MYC, IL2 and HLA-B. All the top SNPs were associated with allergic symptoms in an independent study. Risk-associated variants at these ten loci were estimated to account for at least 25% of allergic sensitization and allergic rhinitis. Understanding the molecular mechanisms underlying these associations may provide new insights into the etiology of allergic disease.
  • Brandler, W. M., Morris, A. P., Evans, D. M., Scerri, T. S., Kemp, J. P., Timpson, N. J., St Pourcain, B., Davey Smith, G., Ring, S. M., Stein, J., Monaco, A. P., Talcott, J. B., Fisher, S. E., Webber, C., & Paracchini, S. (2013). Common variants in left/right asymmetry genes and pathways are associated with relative hand skill. PLoS Genetics, 9(9): e1003751. doi:10.1371/journal.pgen.1003751.

    Abstract

    Humans display structural and functional asymmetries in brain organization, strikingly with respect to language and handedness. The molecular basis of these asymmetries is unknown. We report a genome-wide association study meta-analysis for a quantitative measure of relative hand skill in individuals with dyslexia [reading disability (RD)] (n = 728). The most strongly associated variant, rs7182874 (P = 8.68×10−9), is located in PCSK6, further supporting an association we previously reported. We also confirmed the specificity of this association in individuals with RD; the same locus was not associated with relative hand skill in a general population cohort (n = 2,666). As PCSK6 is known to regulate NODAL in the development of left/right (LR) asymmetry in mice, we developed a novel approach to GWAS pathway analysis, using gene-set enrichment to test for an over-representation of highly associated variants within the orthologs of genes whose disruption in mice yields LR asymmetry phenotypes. Four out of 15 LR asymmetry phenotypes showed an over-representation (FDR≤5%). We replicated three of these phenotypes; situs inversus, heterotaxia, and double outlet right ventricle, in the general population cohort (FDR≤5%). Our findings lead us to propose that handedness is a polygenic trait controlled in part by the molecular mechanisms that establish LR body asymmetry early in development.
  • Cousminer, D. L., Berry, D. J., Timpson, N. J., Ang, W., Thiering, E., Byrne, E. M., Taal, H. R., Huikari, V., Bradfield, J. P., Kerkhof, M., Groen-Blokhuis, M. M., Kreiner-Møller, E., Marinelli, M., Holst, C., Leinonen, J. T., Perry, J. R. B., Surakka, I., Pietiläinen, O., Kettunen, J., Anttila, V. and 50 moreCousminer, D. L., Berry, D. J., Timpson, N. J., Ang, W., Thiering, E., Byrne, E. M., Taal, H. R., Huikari, V., Bradfield, J. P., Kerkhof, M., Groen-Blokhuis, M. M., Kreiner-Møller, E., Marinelli, M., Holst, C., Leinonen, J. T., Perry, J. R. B., Surakka, I., Pietiläinen, O., Kettunen, J., Anttila, V., Kaakinen, M., Sovio, U., Pouta, A., Das, S., Lagou, V., Power, C., Prokopenko, I., Evans, D. M., Kemp, J. P., St Pourcain, B., Ring, S., Palotie, A., Kajantie, E., Osmond, C., Lehtimäki, T., Viikari, J. S., Kähönen, M., Warrington, N. M., Lye, S. J., Palmer, L. J., Tiesler, C. M. T., Flexeder, C., Montgomery, G. W., Medland, S. E., Hofman, A., Hakonarson, H., Guxens, M., Bartels, M., Salomaa, V., Murabito, J. M., Kaprio, J., Sørensen, T. I. A., Ballester, F., Bisgaard, H., Boomsma, D. I., Koppelman, G. H., Grant, S. F. A., Jaddoe, V. W. V., Martin, N. G., Heinrich, J., Pennell, C. E., Raitakari, O. T., Eriksson, J. G., Smith, G. D., Hyppönen, E., Järvelin, M.-R., McCarthy, M. I., Ripatti, S., Widén, E., Consortium ReproGen, & Consortium Early Growth Genetics (EGG) (2013). Genome-wide association and longitudinal analyses reveal genetic loci linking pubertal height growth, pubertal timing and childhood adiposity. Human Molecular Genetics, 22(13), 2735-2747. doi:10.1093/hmg/ddt104.

    Abstract

    The pubertal height growth spurt is a distinctive feature of childhood growth reflecting both the central onset of puberty and local growth factors. Although little is known about the underlying genetics, growth variability during puberty correlates with adult risks for hormone-dependent cancer and adverse cardiometabolic health. The only gene so far associated with pubertal height growth, LIN28B, pleiotropically influences childhood growth, puberty and cancer progression, pointing to shared underlying mechanisms. To discover genetic loci influencing pubertal height and growth and to place them in context of overall growth and maturation, we performed genome-wide association meta-analyses in 18 737 European samples utilizing longitudinally collected height measurements. We found significant associations (P < 1.67 × 10(-8)) at 10 loci, including LIN28B. Five loci associated with pubertal timing, all impacting multiple aspects of growth. In particular, a novel variant correlated with expression of MAPK3, and associated both with increased prepubertal growth and earlier menarche. Another variant near ADCY3-POMC associated with increased body mass index, reduced pubertal growth and earlier puberty. Whereas epidemiological correlations suggest that early puberty marks a pathway from rapid prepubertal growth to reduced final height and adult obesity, our study shows that individual loci associating with pubertal growth have variable longitudinal growth patterns that may differ from epidemiological observations. Overall, this study uncovers part of the complex genetic architecture linking pubertal height growth, the timing of puberty and childhood obesity and provides new information to pinpoint processes linking these traits.
  • den Hoed, M., Eijgelsheim, M., Esko, T., Brundel, B. J. J. M., Peal, D. S., Evans, D. M., Nolte, I. M., Segrè, A. V., Holm, H., Handsaker, R. E., Westra, H.-J., Johnson, T., Isaacs, A., Yang, J., Lundby, A., Zhao, J. H., Kim, Y. J., Go, M. J., Almgren, P., Bochud, M. and 249 moreden Hoed, M., Eijgelsheim, M., Esko, T., Brundel, B. J. J. M., Peal, D. S., Evans, D. M., Nolte, I. M., Segrè, A. V., Holm, H., Handsaker, R. E., Westra, H.-J., Johnson, T., Isaacs, A., Yang, J., Lundby, A., Zhao, J. H., Kim, Y. J., Go, M. J., Almgren, P., Bochud, M., Boucher, G., Cornelis, M. C., Gudbjartsson, D., Hadley, D., van der Harst, P., Hayward, C., den Heijer, M., Igl, W., Jackson, A. U., Kutalik, Z., Luan, J., Kemp, J. P., Kristiansson, K., Ladenvall, C., Lorentzon, M., Montasser, M. E., Njajou, O. T., O'Reilly, P. F., Padmanabhan, S., St Pourcain, B., Rankinen, T., Salo, P., Tanaka, T., Timpson, N. J., Vitart, V., Waite, L., Wheeler, W., Zhang, W., Draisma, H. H. M., Feitosa, M. F., Kerr, K. F., Lind, P. A., Mihailov, E., Onland-Moret, N. C., Song, C., Weedon, M. N., Xie, W., Yengo, L., Absher, D., Albert, C. M., Alonso, A., Arking, D. E., de Bakker, P. I. W., Balkau, B., Barlassina, C., Benaglio, P., Bis, J. C., Bouatia-Naji, N., Brage, S., Chanock, S. J., Chines, P. S., Chung, M., Darbar, D., Dina, C., Dörr, M., Elliott, P., Felix, S. B., Fischer, K., Fuchsberger, C., de Geus, E. J. C., Goyette, P., Gudnason, V., Harris, T. B., Hartikainen, A.-L., Havulinna, A. S., Heckbert, S. R., Hicks, A. A., Hofman, A., Holewijn, S., Hoogstra-Berends, F., Hottenga, J.-J., Jensen, M. K., Johansson, A., Junttila, J., Kääb, S., Kanon, B., Ketkar, S., Khaw, K.-T., Knowles, J. W., Kooner, A. S., Kors, J. A., Kumari, M., Milani, L., Laiho, P., Lakatta, E. G., Langenberg, C., Leusink, M., Liu, Y., Luben, R. N., Lunetta, K. L., Lynch, S. N., Markus, M. R. P., Marques-Vidal, P., Mateo Leach, I., McArdle, W. L., McCarroll, S. A., Medland, S. E., Miller, K. A., Montgomery, G. W., Morrison, A. C., Müller-Nurasyid, M., Navarro, P., Nelis, M., O'Connell, J. R., O'Donnell, C. J., Ong, K. K., Newman, A. B., Peters, A., Polasek, O., Pouta, A., Pramstaller, P. P., Psaty, B. M., Rao, D. C., Ring, S. M., Rossin, E. J., Rudan, D., Sanna, S., Scott, R. A., Sehmi, J. S., Sharp, S., Shin, J. T., Singleton, A. B., Smith, A. V., Soranzo, N., Spector, T. D., Stewart, C., Stringham, H. M., Tarasov, K. V., Uitterlinden, A. G., Vandenput, L., Hwang, S.-J., Whitfield, J. B., Wijmenga, C., Wild, S. H., Willemsen, G., Wilson, J. F., Witteman, J. C. M., Wong, A., Wong, Q., Jamshidi, Y., Zitting, P., Boer, J. M. A., Boomsma, D. I., Borecki, I. B., van Duijn, C. M., Ekelund, U., Forouhi, N. G., Froguel, P., Hingorani, A., Ingelsson, E., Kivimaki, M., Kronmal, R. A., Kuh, D., Lind, L., Martin, N. G., Oostra, B. A., Pedersen, N. L., Quertermous, T., Rotter, J. I., van der Schouw, Y. T., Verschuren, W. M. M., Walker, M., Albanes, D., Arnar, D. O., Assimes, T. L., Bandinelli, S., Boehnke, M., de Boer, R. A., Bouchard, C., Caulfield, W. L. M., Chambers, J. C., Curhan, G., Cusi, D., Eriksson, J., Ferrucci, L., van Gilst, W. H., Glorioso, N., de Graaf, J., Groop, L., Gyllensten, U., Hsueh, W.-C., Hu, F. B., Huikuri, H. V., Hunter, D. J., Iribarren, C., Isomaa, B., Jarvelin, M.-R., Jula, A., Kähönen, M., Kiemeney, L. A., van der Klauw, M. M., Kooner, J. S., Kraft, P., Iacoviello, L., Lehtimäki, T., Lokki, M.-L.-L., Mitchell, B. D., Navis, G., Nieminen, M. S., Ohlsson, C., Poulter, N. R., Qi, L., Raitakari, O. T., Rimm, E. B., Rioux, J. D., Rizzi, F., Rudan, I., Salomaa, V., Sever, P. S., Shields, D. C., Shuldiner, A. R., Sinisalo, J., Stanton, A. V., Stolk, R. P., Strachan, D. P., Tardif, J.-C., Thorsteinsdottir, U., Tuomilehto, J., van Veldhuisen, D. J., Virtamo, J., Viikari, J., Vollenweider, P., Waeber, G., Widen, E., Cho, Y. S., Olsen, J. V., Visscher, P. M., Willer, C., Franke, L., Erdmann, J., Thompson, J. R., Pfeufer, A., Sotoodehnia, N., Newton-Cheh, C., Ellinor, P. T., Stricker, B. H. C., Metspalu, A., Perola, M., Beckmann, J. S., Smith, G. D., Stefansson, K., Wareham, N. J., Munroe, P. B., Sibon, O. C. M., Milan, D. J., Snieder, H., Samani, N. J., Loos, R. J. F., Global BPgen Consortium, CARDIoGRAM Consortium, PR GWAS Consortium, QRS GWAS Consortium, QT-IGC Consortium, & CHARGE-AF Consortium (2013). Identification of heart rate-associated loci and their effects on cardiac conduction and rhythm disorders. Nature Genetics, 45(6), 621-631. doi:10.1038/ng.2610.

    Abstract

    Elevated resting heart rate is associated with greater risk of cardiovascular disease and mortality. In a 2-stage meta-analysis of genome-wide association studies in up to 181,171 individuals, we identified 14 new loci associated with heart rate and confirmed associations with all 7 previously established loci. Experimental downregulation of gene expression in Drosophila melanogaster and Danio rerio identified 20 genes at 11 loci that are relevant for heart rate regulation and highlight a role for genes involved in signal transmission, embryonic cardiac development and the pathophysiology of dilated cardiomyopathy, congenital heart failure and/or sudden cardiac death. In addition, genetic susceptibility to increased heart rate is associated with altered cardiac conduction and reduced risk of sick sinus syndrome, and both heart rate-increasing and heart rate-decreasing variants associate with risk of atrial fibrillation. Our findings provide fresh insights into the mechanisms regulating heart rate and identify new therapeutic targets.
  • Eicher, J. D., Powers, N. R., Miller, L. L., Akshoomoff, N., Amaral, D. G., Bloss, C. S., Libiger, O., Schork, N. J., Darst, B. F., Casey, B. J., Chang, L., Ernst, T., Frazier, J., Kaufmann, W. E., Keating, B., Kenet, T., Kennedy, D., Mostofsky, S., Murray, S. S., Sowell, E. R. and 11 moreEicher, J. D., Powers, N. R., Miller, L. L., Akshoomoff, N., Amaral, D. G., Bloss, C. S., Libiger, O., Schork, N. J., Darst, B. F., Casey, B. J., Chang, L., Ernst, T., Frazier, J., Kaufmann, W. E., Keating, B., Kenet, T., Kennedy, D., Mostofsky, S., Murray, S. S., Sowell, E. R., Bartsch, H., Kuperman, J. M., Brown, T. T., Hagler, D. J., Dale, A. M., Jernigan, T. L., St Pourcain, B., Davey Smith, G., Ring, S. M., Gruen, J. R., & Pediatric Imaging, Neurocognition, and Genetics Study (2013). Genome-wide association study of shared components of reading disability and language impairment. Genes, Brain and Behavior, 12(8), 792-801. doi:10.1111/gbb.12085.

    Abstract

    Written and verbal languages are neurobehavioral traits vital to the development of communication skills. Unfortunately, disorders involving these traits-specifically reading disability (RD) and language impairment (LI)-are common and prevent affected individuals from developing adequate communication skills, leaving them at risk for adverse academic, socioeconomic and psychiatric outcomes. Both RD and LI are complex traits that frequently co-occur, leading us to hypothesize that these disorders share genetic etiologies. To test this, we performed a genome-wide association study on individuals affected with both RD and LI in the Avon Longitudinal Study of Parents and Children. The strongest associations were seen with markers in ZNF385D (OR = 1.81, P = 5.45 × 10(-7) ) and COL4A2 (OR = 1.71, P = 7.59 × 10(-7) ). Markers within NDST4 showed the strongest associations with LI individually (OR = 1.827, P = 1.40 × 10(-7) ). We replicated association of ZNF385D using receptive vocabulary measures in the Pediatric Imaging Neurocognitive Genetics study (P = 0.00245). We then used diffusion tensor imaging fiber tract volume data on 16 fiber tracts to examine the implications of replicated markers. ZNF385D was a predictor of overall fiber tract volumes in both hemispheres, as well as global brain volume. Here, we present evidence for ZNF385D as a candidate gene for RD and LI. The implication of transcription factor ZNF385D in RD and LI underscores the importance of transcriptional regulation in the development of higher order neurocognitive traits. Further study is necessary to discern target genes of ZNF385D and how it functions within neural development of fluent language.
  • Evans, D. M., Zhu, G., Dy, V., Heath, A. C., Madden, P. A. F., Kemp, J. P., McMahon, G., St Pourcain, B., Timpson, N. J., Golding, J., Lawlor, D. A., Steer, C., Montgomery, G. W., Martin, N. G., Smith, G. D., & Whitfield, J. B. (2013). Genome-wide association study identifies loci affecting blood copper, selenium and zinc. Human Molecular Genetics, 22(19), 3998-4006. doi:10.1093/hmg/ddt239.

    Abstract

    Genetic variation affecting absorption, distribution or excretion of essential trace elements may lead to health effects related to sub-clinical deficiency. We have tested for allelic effects of single-nucleotide polymorphisms (SNPs) on blood copper, selenium and zinc in a genome-wide association study using two adult cohorts from Australia and the UK. Participants were recruited in Australia from twins and their families and in the UK from pregnant women. We measured erythrocyte Cu, Se and Zn (Australian samples) or whole blood Se (UK samples) using inductively coupled plasma mass spectrometry. Genotyping was performed with Illumina chips and > 2.5 m SNPs were imputed from HapMap data. Genome-wide significant associations were found for each element. For Cu, there were two loci on chromosome 1 (most significant SNPs rs1175550, P = 5.03 × 10(-10), and rs2769264, P = 2.63 × 10(-20)); for Se, a locus on chromosome 5 was significant in both cohorts (combined P = 9.40 × 10(-28) at rs921943); and for Zn three loci on chromosomes 8, 15 and X showed significant results (rs1532423, P = 6.40 × 10(-12); rs2120019, P = 1.55 × 10(-18); and rs4826508, P = 1.40 × 10(-12), respectively). The Se locus covers three genes involved in metabolism of sulphur-containing amino acids and potentially of the analogous Se compounds; the chromosome 8 locus for Zn contains multiple genes for the Zn-containing enzyme carbonic anhydrase. Where potentially relevant genes were identified, they relate to metabolism of the element (Se) or to the presence at high concentration of a metal-containing protein (Cu).
  • Evans, D. M., Brion, M. J. A., Paternoster, L., Kemp, J. P., McMahon, G., Munafò, M., Whitfield, J. B., Medland, S. E., Montgomery, G. W., Timpson, N. J., St Pourcain, B., Lawlor, D. A., Martin, N. G., Dehghan, A., Hirschhorn, J., Davey Smith, G., The GIANT consortium, The CRP consortium, & The TAG Consortium (2013). Mining the Human Phenome Using Allelic Scores That Index Biological Intermediates. PLoS Genet, 9(10): e1003919. doi:10.1371/journal.pgen.1003919.

    Abstract

    Author SummaryThe standard approach in genome-wide association studies is to analyse the relationship between genetic variants and disease one marker at a time. Significant associations between markers and disease are then used as evidence to implicate biological intermediates and pathways likely to be involved in disease aetiology. However, single genetic variants typically only explain small amounts of disease risk. Our idea is to construct allelic scores that explain greater proportions of the variance in biological intermediates than single markers, and then use these scores to data mine genome-wide association studies. We show how allelic scores derived from known variants as well as allelic scores derived from hundreds of thousands of genetic markers across the genome explain significant portions of the variance in body mass index, levels of C-reactive protein, and LDLc cholesterol, and many of these scores show expected correlations with disease. Power calculations confirm the feasibility of scaling our strategy to the analysis of tens of thousands of molecular phenotypes in large genome-wide meta-analyses. Our method represents a simple way in which tens of thousands of molecular phenotypes could be screened for potential causal relationships with disease.
  • Fatemifar, G., Hoggart, C. J., Paternoster, L., Kemp, J. P., Prokopenko, I., Horikoshi, M., Wright, V. J., Tobias, J. H., Richmond, S., Zhurov, A. I., Toma, A. M., Pouta, A., Taanila, A., Sipila, K., Lähdesmäki, R., Pillas, D., Geller, F., Feenstra, B., Melbye, M., Nohr, E. A. and 6 moreFatemifar, G., Hoggart, C. J., Paternoster, L., Kemp, J. P., Prokopenko, I., Horikoshi, M., Wright, V. J., Tobias, J. H., Richmond, S., Zhurov, A. I., Toma, A. M., Pouta, A., Taanila, A., Sipila, K., Lähdesmäki, R., Pillas, D., Geller, F., Feenstra, B., Melbye, M., Nohr, E. A., Ring, S. M., St Pourcain, B., Timpson, N. J., Davey Smith, G., Jarvelin, M.-R., & Evans, D. M. (2013). Genome-wide association study of primary tooth eruption identifies pleiotropic loci associated with height and craniofacial distances. Human Molecular Genetics, 22(18), 3807-3817. doi:10.1093/hmg/ddt231.

    Abstract

    Twin and family studies indicate that the timing of primary tooth eruption is highly heritable, with estimates typically exceeding 80%. To identify variants involved in primary tooth eruption, we performed a population-based genome-wide association study of 'age at first tooth' and 'number of teeth' using 5998 and 6609 individuals, respectively, from the Avon Longitudinal Study of Parents and Children (ALSPAC) and 5403 individuals from the 1966 Northern Finland Birth Cohort (NFBC1966). We tested 2 446 724 SNPs imputed in both studies. Analyses were controlled for the effect of gestational age, sex and age of measurement. Results from the two studies were combined using fixed effects inverse variance meta-analysis. We identified a total of 15 independent loci, with 10 loci reaching genome-wide significance (P < 5 × 10(-8)) for 'age at first tooth' and 11 loci for 'number of teeth'. Together, these associations explain 6.06% of the variation in 'age of first tooth' and 4.76% of the variation in 'number of teeth'. The identified loci included eight previously unidentified loci, some containing genes known to play a role in tooth and other developmental pathways, including an SNP in the protein-coding region of BMP4 (rs17563, P = 9.080 × 10(-17)). Three of these loci, containing the genes HMGA2, AJUBA and ADK, also showed evidence of association with craniofacial distances, particularly those indexing facial width. Our results suggest that the genome-wide association approach is a powerful strategy for detecting variants involved in tooth eruption, and potentially craniofacial growth and more generally organ development.
  • Hinds, D. A., McMahon, G., Kiefer, A. K., Do, C. B., Eriksson, N., Evans, D. M., St Pourcain, B., Ring, S. M., Mountain, J. L., Francke, U., Davey-Smith, G., Timpson, N. J., & Tung, J. Y. (2013). A genome-wide association meta-analysis of self-reported allergy identifies shared and allergy-specific susceptibility loci. Nat Genet, 45(8), 907-911. doi:10.1038/ng.2686.

    Abstract

    Allergic disease is very common and carries substantial public-health burdens. We conducted a meta-analysis of genome-wide associations with self-reported cat, dust-mite and pollen allergies in 53,862 individuals. We used generalized estimating equations to model shared and allergy-specific genetic effects. We identified 16 shared susceptibility loci with association P<5×10(-8), including 8 loci previously associated with asthma, as well as 4p14 near TLR1, TLR6 and TLR10 (rs2101521, P=5.3×10(-21)); 6p21.33 near HLA-C and MICA (rs9266772, P=3.2×10(-12)); 5p13.1 near PTGER4 (rs7720838, P=8.2×10(-11)); 2q33.1 in PLCL1 (rs10497813, P=6.1×10(-10)), 3q28 in LPP (rs9860547, P=1.2×10(-9)); 20q13.2 in NFATC2 (rs6021270, P=6.9×10(-9)), 4q27 in ADAD1 (rs17388568, P=3.9×10(-8)); and 14q21.1 near FOXA1 and TTC6 (rs1998359, P=4.8×10(-8)). We identified one locus with substantial evidence of differences in effects across allergies at 6p21.32 in the class II human leukocyte antigen (HLA) region (rs17533090, P=1.7×10(-12)), which was strongly associated with cat allergy. Our study sheds new light on the shared etiology of immune and autoimmune disease.
  • Julvez, J., Smith, G. D., Golding, J., Ring, S., St Pourcain, B., Gonzalez, J. R., & Grandjean, P. (2013). Prenatal methylmercury exposure and genetic predisposition to cognitive deficit at age 8 years. Epidemiology, 24(5), 643-650. doi:10.1097/EDE.0b013e31829d5c93.

    Abstract

    BACKGROUND: Cognitive consequences at school age associated with prenatal methylmercury (MeHg) exposure may need to take into account nutritional and sociodemographic cofactors as well as relevant genetic polymorphisms. METHODS: A subsample (n = 1,311) of the Avon Longitudinal Study of Parents and Children (Bristol, UK) was selected, and mercury (Hg) concentrations were measured in freeze-dried umbilical cord tissue as a measure of MeHg exposure. A total of 1135 children had available data on 247 single-nucleotide polymorphisms (SNPs) within relevant genes, as well as the Wechsler Intelligence Scale for Children Intelligence Quotient (IQ) scores at age 8 years. Multivariate regression models were used to assess the associations between MeHg exposure and IQ and to determine possible gene-environment interactions. RESULTS: Hg concentrations indicated low background exposures (mean = 26 ng/g, standard deviation = 13). Log10-transformed Hg was positively associated with IQ, which attenuated after adjustment for nutritional and sociodemographic cofactors. In stratified analyses, a reverse association was found in higher social class families (for performance IQ, P value for interaction = 0.0013) among whom there was a wider range of MeHg exposure. Among 40 SNPs showing nominally significant main effects, MeHg interactions were detected for rs662 (paraoxonase 1) and rs1042838 (progesterone receptor) (P <} 0.05) and for rs3811647 (transferrin) and rs2049046 (brain-derived neurotrophic factor) (P {< 0.10). CONCLUSIONS: In this population with a low level of MeHg exposure, there were only equivocal associations between MeHg exposure and adverse neuropsychological outcomes. Heterogeneities in several relevant genes suggest possible genetic predisposition to MeHg neurotoxicity in a substantial proportion of the population. Future studies need to address this possibility.
  • Mandy, W., Skuse, D., Steer, C., St Pourcain, B., & Oliver, B. R. (2013). Oppositionality and Socioemotional Competence: Interacting Risk Factors in the Development of Childhood Conduct Disorder Symptoms. Journal of the American Academy of Child & Adolescent Psychiatry, 52(7), 718-727. doi:10.1016/j.jaac.2013.04.011.

    Abstract

    Objectives Oppositional behavior in childhood is a probabilistic risk factor for the subsequent development of more serious conduct problems characteristic of conduct disorder (CD). The capacity to understand the subjective states of others (socioemotional competence) helps regulate antisocial behavior in typical development. We hypothesized that socioemotional competence moderates the developmental relationship between oppositionality and CD symptoms, such that oppositional defiant disorder (ODD) symptoms pose the greatest risk for subsequent CD symptoms in children with poor socioemotional competence. Method Parent-report data were collected for 6,218 children at 7 and 10 years of age. Bootstrap multiple regression predicting CD symptoms at age 10 was used to test for an interaction between socioemotional competence and ODD symptoms, while also accounting for direct effects and controlling for sex, maternal education, attention-deficit/hyperactivity disorder symptoms, and CD symptoms at 7 years. We further tested whether the interaction applied to both males and females, and to both aggressive and rule-breaking CD symptoms. Results A significant interaction was found between ODD and socioemotional competence: the association between oppositionality at 7 years and CD traits at 10 years was strongest for children with poor socioemotional capacities. As predicted, this moderation effect was significant in a model predicting aggression, but it was not significant for rule-breaking CD symptoms. Conclusion Socioemotional competence moderates the developmental relationship between mid-childhood oppositionality and more serious conduct problems in later childhood. A capacity to understand the subjective states of others may buffer the risk posed by oppositionality for later CD symptoms, including aggression.
  • St Pourcain, B., Whitehouse, A. J. O., Ang, W. Q., Warrington, N. M., Glessner, J. T., Wang, K., Timpson, N. J., Evans, D. M., Kemp, J. P., Ring, S. M., McArdle, W. L., Golding, J., Hakonarson, H., Pennell, C. E., & Smith, G. (2013). Common variation contributes to the genetic architecture of social communication traits. Molecular Autism, 4: 34. doi:10.1186/2040-2392-4-34.

    Abstract

    Background: Social communication difficulties represent an autistic trait that is highly heritable and persistent during the course of development. However, little is known about the underlying genetic architecture of this phenotype. Methods: We performed a genome-wide association study on parent-reported social communication problems using items of the children’s communication checklist (age 10 to 11 years) studying single and/or joint marker effects. Analyses were conducted in a large UK population-based birth cohort (Avon Longitudinal Study of Parents and their Children, ALSPAC, N = 5,584) and followed-up within a sample of children with comparable measures from Western Australia (RAINE, N = 1364). Results: Two of our seven independent top signals (P- discovery <1.0E-05) were replicated (0.009 < P- replication ≤0.02) within RAINE and suggested evidence for association at 6p22.1 (rs9257616, meta-P = 2.5E-07) and 14q22.1 (rs2352908, meta-P = 1.1E-06). The signal at 6p22.1 was identified within the olfactory receptor gene cluster within the broader major histocompatibility complex (MHC) region. The strongest candidate locus within this genomic area was TRIM27. This gene encodes an ubiquitin E3 ligase, which is an interaction partner of methyl-CpG-binding domain (MBD) proteins, such as MBD3 and MBD4, and rare protein-coding mutations within MBD3 and MBD4 have been linked to autism. The signal at 14q22.1 was found within a gene-poor region. Single-variant findings were complemented by estimations of the narrow-sense heritability in ALSPAC suggesting that approximately a fifth of the phenotypic variance in social communication traits is accounted for by joint additive effects of genotyped single nucleotide polymorphisms throughout the genome (h2(SE) = 0.18(0.066), P = 0.0027). Conclusion: Overall, our study provides both joint and single-SNP-based evidence for the contribution of common polymorphisms to variation in social communication phenotypes.
  • Rietveld, C. A., Medland, S. E., Derringer, J., Yang, J., Esko, T., Martin, N. W., Westra, H.-J., Shakhbazov, K., Abdellaoui, A., Agrawal, A., Albrecht, E., Alizadeh, B. Z., Amin, N., Barnard, J., Baumeister, S. E., Benke, K. S., Bielak, L. F., Boatman, J. A., Boyle, P. A., Davies, G. and 184 moreRietveld, C. A., Medland, S. E., Derringer, J., Yang, J., Esko, T., Martin, N. W., Westra, H.-J., Shakhbazov, K., Abdellaoui, A., Agrawal, A., Albrecht, E., Alizadeh, B. Z., Amin, N., Barnard, J., Baumeister, S. E., Benke, K. S., Bielak, L. F., Boatman, J. A., Boyle, P. A., Davies, G., de Leeuw, C., Eklund, N., Evans, D. S., Ferhmann, R., Fischer, K., Gieger, C., Gjessing, H. K., Hägg, S., Harris, J. R., Hayward, C., Holzapfel, C., Ibrahim-Verbaas, C. A., Ingelsson, E., Jacobsson, B., Joshi, P. K., Jugessur, A., Kaakinen, M., Kanoni, S., Karjalainen, J., Kolcic, I., Kristiansson, K., Kutalik, Z., Lahti, J., Lee, S. H., Lin, P., Lind, P. A., Liu, Y., Lohman, K., Loitfelder, M., McMahon, G., Vidal, P. M., Meirelles, O., Milani, L., Myhre, R., Nuotio, M.-L., Oldmeadow, C. J., Petrovic, K. E., Peyrot, W. J., Polasek, O., Quaye, L., Reinmaa, E., Rice, J. P., Rizzi, T. S., Schmidt, H., Schmidt, R., Smith, A. V., Smith, J. A., Tanaka, T., Terracciano, A., van der Loos, M. J. H. M., Vitart, V., Völzke, H., Wellmann, J., Yu, L., Zhao, W., Allik, J., Attia, J. R., Bandinelli, S., Bastardot, F., Beauchamp, J., Bennett, D. A., Berger, K., Bierut, L. J., Boomsma, D. I., Bültmann, U., Campbell, H., Chabris, C. F., Cherkas, L., Chung, M. K., Cucca, F., de Andrade, M., De Jager, P. L., De Neve, J.-E., Deary, I. J., Dedoussis, G. V., Deloukas, P., Dimitriou, M., Eiríksdóttir, G., Elderson, M. F., Eriksson, J. G., Evans, D. M., Faul, J. D., Ferrucci, L., Garcia, M. E., Grönberg, H., Guðnason, V., Hall, P., Harris, J. M., Harris, T. B., Hastie, N. D., Heath, A. C., Hernandez, D. G., Hoffmann, W., Hofman, A., Holle, R., Holliday, E. G., Hottenga, J.-J., Iacono, W. G., Illig, T., Järvelin, M.-R., Kähönen, M., Kaprio, J., Kirkpatrick, R. M., Kowgier, M., Latvala, A., Launer, L. J., Lawlor, D. A., Lehtimäki, T., Li, J., Lichtenstein, P., Lichtner, P., Liewald, D. C., Madden, P. A., Magnusson, P. K. E., Mäkinen, T. E., Masala, M., McGue, M., Metspalu, A., Mielck, A., Miller, M. B., Montgomery, G. W., Mukherjee, S., Nyholt, D. R., Oostra, B. A., Palmer, L. J., Palotie, A., Penninx, B. W. J. H., Perola, M., Peyser, P. A., Preisig, M., Räikkönen, K., Raitakari, O. T., Realo, A., Ring, S. M., Ripatti, S., Rivadeneira, F., Rudan, I., Rustichini, A., Salomaa, V., Sarin, A.-P., Schlessinger, D., Scott, R. J., Snieder, H., St Pourcain, B., Starr, J. M., Sul, J. H., Surakka, I., Svento, R., Teumer, A., Tiemeier, H., van Rooij, F. J. A., Van Wagoner, D. R., Vartiainen, E., Viikari, J., Vollenweider, P., Vonk, J. M., Waeber, G., Weir, D. R., Wichmann, H.-E., Widen, E., Willemsen, G., Wilson, J. F., Wright, A. F., Conley, D., Davey-Smith, G., Franke, L., Groenen, P. J. F., Hofman, A., Johannesson, M., Kardia, S. L. R., Krueger, R. F., Laibson, D., Martin, N. G., Meyer, M. N., Posthuma, D., Thurik, A. R., Timpson, N. J., Uitterlinden, A. G., van Duijn, C. M., Visscher, P. M., Benjamin, D. J., Cesarini, D., Koellinger, P. D., & Study LifeLines Cohort (2013). GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science, 340(6139), 1467-1471. doi:10.1126/science.1235488.

    Abstract

    A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R(2) ≈ 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for ≈2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.

    Additional information

    Rietveld.SM.revision.2.pdf
  • Van der Valk, R. J. P., Duijts, L., Timpson, N. J., Salam, M. T., Standl, M., Curtin, J. A., Genuneit, J., Kerhof, M., Kreiner-Møller, E., Cáceres, A., Gref, A., Liang, L. L., Taal, H. R., Bouzigon, E., Demenais, F., Nadif, R., Ober, C., Thompson, E. E., Estrada, K., Hofman, A. and 39 moreVan der Valk, R. J. P., Duijts, L., Timpson, N. J., Salam, M. T., Standl, M., Curtin, J. A., Genuneit, J., Kerhof, M., Kreiner-Møller, E., Cáceres, A., Gref, A., Liang, L. L., Taal, H. R., Bouzigon, E., Demenais, F., Nadif, R., Ober, C., Thompson, E. E., Estrada, K., Hofman, A., Uitterlinden, A. G., van Duijn, C., Rivadeneira, F., Li, X., Eckel, S. P., Berhane, K., Gauderman, W. J., Granell, R., Evans, D. M., St Pourcain, B., McArdle, W., Kemp, J. P., Smith, G. D., Tiesler, C. M. T., Flexeder, C., Simpson, A., Murray, C. S., Fuchs, O., Postma, D. S., Bønnelykke, K., Torrent, M., Andersson, M., Sleiman, P., Hakonarson, H., Cookson, W. O., Moffatt, M. F., Paternoster, L., Melén, E., Sunyer, J., Bisgaard, H., Koppelman, G. H., Ege, M., Custovic, A., Heinrich, J., Gilliland, F. D., Henderson, A. J., Jaddoe, V. W. V., de Jongste, J. C., & EArly Genetics and Lifecourse Epidemiology (EAGLE) Consortium (2013). Fraction of exhaled nitric oxide values in childhood are associated with 17q11.2-q12 and 17q12-q21 variants. Journal of Allergy and Clinical Immunology, 134(1), 46-55. doi:10.1016/j.jaci.2013.08.053.

    Abstract

    BACKGROUND: The fraction of exhaled nitric oxide (Feno) value is a biomarker of eosinophilic airway inflammation and is associated with childhood asthma. Identification of common genetic variants associated with childhood Feno values might help to define biological mechanisms related to specific asthma phenotypes.
    OBJECTIVE: We sought to identify the genetic variants associated with childhood Feno values and their relation with asthma.
    METHODS: Feno values were measured in children age 5 to 15 years. In 14 genome-wide association studies (N = 8,858), we examined the associations of approximately 2.5 million single nucleotide polymorphisms (SNPs) with Feno values. Subsequently, we assessed whether significant SNPs were expression quantitative trait loci in genome-wide expression data sets of lymphoblastoid cell lines (n = 1,830) and were related to asthma in a previously published genome-wide association data set (cases, n = 10,365; control subjects: n = 16,110).
    RESULTS: We identified 3 SNPs associated with Feno values: rs3751972 in LYR motif containing 9 (LYRM9; P = 1.97 × 10(-10)) and rs944722 in inducible nitric oxide synthase 2 (NOS2; P = 1.28 × 10(-9)), both of which are located at 17q11.2-q12, and rs8069176 near gasdermin B (GSDMB; P = 1.88 × 10(-8)) at 17q12-q21. We found a cis expression quantitative trait locus for the transcript soluble galactoside-binding lectin 9 (LGALS9) that is in linkage disequilibrium with rs944722. rs8069176 was associated with GSDMB and ORM1-like 3 (ORMDL3) expression. rs8069176 at 17q12-q21, but not rs3751972 and rs944722 at 17q11.2-q12, were associated with physician-diagnosed asthma.
    CONCLUSION: This study identified 3 variants associated with Feno values, explaining 0.95% of the variance. Identification of functional SNPs and haplotypes in these regions might provide novel insight into the regulation of Feno values. This study highlights that both shared and distinct genetic factors affect Feno values and childhood asthma.
  • Verhoeven, V. J. M., Hysi, P. G., Wojciechowski, R., Fan, Q., Guggenheim, J. A., Höhn, R., MacGregor, S., Hewitt, A. W., Nag, A., Cheng, C.-Y., Yonova-Doing, E., Zhou, X., Ikram, M. K., Buitendijk, G. H. S., McMahon, G., Kemp, J. P., St Pourcain, B., Simpson, C. L., Mäkelä, K.-M., Lehtimäki, T. and 90 moreVerhoeven, V. J. M., Hysi, P. G., Wojciechowski, R., Fan, Q., Guggenheim, J. A., Höhn, R., MacGregor, S., Hewitt, A. W., Nag, A., Cheng, C.-Y., Yonova-Doing, E., Zhou, X., Ikram, M. K., Buitendijk, G. H. S., McMahon, G., Kemp, J. P., St Pourcain, B., Simpson, C. L., Mäkelä, K.-M., Lehtimäki, T., Kähönen, M., Paterson, A. D., Hosseini, S. M., Wong, H. S., Xu, L., Jonas, J. B., Pärssinen, O., Wedenoja, J., Yip, S. P., Ho, D. W. H., Pang, C. P., Chen, L. J., Burdon, K. P., Craig, J. E., Klein, B. E. K., Klein, R., Haller, T., Metspalu, A., Khor, C.-C., Tai, E.-S., Aung, T., Vithana, E., Tay, W.-T., Barathi, V. A., Chen, P., Li, R., Liao, J., Zheng, Y., Ong, R. T., Döring, A., Evans, D. M., Timpson, N. J., Verkerk, A. J. M. H., Meitinger, T., Raitakari, O., Hawthorne, F., Spector, T. D., Karssen, L. C., Pirastu, M., Murgia, F., Ang, W., Mishra, A., Montgomery, G. W., Pennell, C. E., Cumberland, P. M., Cotlarciuc, I., Mitchell, P., Wang, J. J., Schache, M., Janmahasatian, S., Janmahasathian, S., Igo, R. P., Lass, J. H., Chew, E., Iyengar, S. K., Gorgels, T. G. M. F., Rudan, I., Hayward, C., Wright, A. F., Polasek, O., Vatavuk, Z., Wilson, J. F., Fleck, B., Zeller, T., Mirshahi, A., Müller, C., Uitterlinden, A. G., Rivadeneira, F., Vingerling, J. R., Hofman, A., Oostra, B. A., Amin, N., Bergen, A. A. B., Teo, Y.-Y., Rahi, J. S., Vitart, V., Williams, C., Baird, P. N., Wong, T.-Y., Oexle, K., Pfeiffer, N., Mackey, D. A., Young, T. L., van Duijn, C. M., Saw, S.-M., Bailey-Wilson, J. E., Stambolian, D., Klaver, C. C., Hammond, C. J., Consortium for Refractive Error and Myopia (CREAM), The Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Research Group, Wellcome Trust Case Control Consortium 2 (WTCCC2), & The Fuchs' Genetics Multi-Center Study Group (2013). Genome-wide meta-analyses of multiancestry cohorts identify multiple new susceptibility loci for refractive error and myopia. Nature Genetics, 45(3), 314-318. doi:10.1038/ng.2554.

    Abstract

    Refractive error is the most common eye disorder worldwide and is a prominent cause of blindness. Myopia affects over 30% of Western populations and up to 80% of Asians. The CREAM consortium conducted genome-wide meta-analyses, including 37,382 individuals from 27 studies of European ancestry and 8,376 from 5 Asian cohorts. We identified 16 new loci for refractive error in individuals of European ancestry, of which 8 were shared with Asians. Combined analysis identified 8 additional associated loci. The new loci include candidate genes with functions in neurotransmission (GRIA4), ion transport (KCNQ5), retinoic acid metabolism (RDH5), extracellular matrix remodeling (LAMA2 and BMP2) and eye development (SIX6 and PRSS56). We also confirmed previously reported associations with GJD2 and RASGRF1. Risk score analysis using associated SNPs showed a tenfold increased risk of myopia for individuals carrying the highest genetic load. Our results, based on a large meta-analysis across independent multiancestry studies, considerably advance understanding of the mechanisms involved in refractive error and myopia.

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