Displaying 1 - 54 of 54
  • Schlag, F., Allegrini, A. G., Buitelaar, J., Verhoef, E., Van Donkelaar, M. M. J., Plomin, R., Rimfeld, K., Fisher, S. E., & St Pourcain, B. (in press). Polygenic risk for mental disorder reveals distinct association profiles across social behaviour in the general population. Molecular Psychiatry.
  • Laureys, F., De Waelle, S., Barendse, M. T., Lenoir, M., & Deconinck, F. J. (2022). The factor structure of executive function in childhood and adolescence. Intelligence, 90: 101600. doi:10.1016/j.intell.2021.101600.

    Abstract

    Executive functioning (EF) plays a major role in many domains of human behaviour, including self-regulation, academic achievement, and even sports expertise. While a significant proportion of cross-sectional research has focused on the developmental pathways of EF, the existing literature is fractionated due to a wide range of methodologies applied to narrow age ranges, impeding comparison across a broad range of age groups. The current study used a cross-sectional design to investigate the factor structure of EF within late childhood and adolescence. A total of 2166 Flemish children and adolescents completed seven tasks of the Cambridge Brain Sciences test battery. Based on the existing literature, a Confirmatory Factor Analysis was performed, which indicated that a unitary factor model provides the best fit for the youngest age group (7–12 years). For the adolescents (12–18 years), the factor structure consists of four different components, including working memory, shifting, inhibition and planning. With regard to differences between early (12–15 years) and late (15–18 years) adolescents, working memory, inhibition and planning show higher scores for the late adolescents, while there was no difference on shifting. The current study is one of the first to administer the same seven EF tests in a considerably large sample of children and adolescents, and as such contributes to the understanding of the developmental trends in EF. Future studies, especially with longitudinal designs, are encouraged to further increase the knowledge concerning the factor structure of EF, and the development of the different EF components.
  • Ahluwalia, T. S., Prins, B. P., Abdollahi, M., Armstrong, N. J., Aslibekyan, S., Bain, L., Jefferis, B., Baumert, J., Beekman, M., Ben-Shlomo, Y., Bis, J. C., Mitchell, B. D., De Geus, E., Delgado, G. E., Marek, D., Eriksson, J., Kajantie, E., Kanoni, S., Kemp, J. P., Lu, C. and 106 moreAhluwalia, T. S., Prins, B. P., Abdollahi, M., Armstrong, N. J., Aslibekyan, S., Bain, L., Jefferis, B., Baumert, J., Beekman, M., Ben-Shlomo, Y., Bis, J. C., Mitchell, B. D., De Geus, E., Delgado, G. E., Marek, D., Eriksson, J., Kajantie, E., Kanoni, S., Kemp, J. P., Lu, C., Marioni, R. E., McLachlan, S., Milaneschi, Y., Nolte, I. M., Petrelis, A. M., Porcu, E., Sabater-Lleal, M., Naderi, E., Seppälä, I., Shah, T., Singhal, G., Standl, M., Teumer, A., Thalamuthu, A., Thiering, E., Trompet, S., Ballantyne, C. M., Benjamin, E. J., Casas, J. P., Toben, C., Dedoussis, G., Deelen, J., Durda, P., Engmann, J., Feitosa, M. F., Grallert, H., Hammarstedt, A., Harris, S. E., Homuth, G., Hottenga, J.-J., Jalkanen, S., Jamshidi, Y., Jawahar, M. C., Jess, T., Kivimaki, M., Kleber, M. E., Lahti, J., Liu, Y., Marques-Vidal, P., Mellström, D., Mooijaart, S. P., Müller-Nurasyid, M., Penninx, B., Revez, J. A., Rossing, P., Räikkönen, K., Sattar, N., Scharnagl, H., Sennblad, B., Silveira, A., St Pourcain, B., Timpson, N. J., Trollor, J., CHARGE Inflammation Working Group, Van Dongen, J., Van Heemst, D., Visvikis-Siest, S., Vollenweider, P., Völker, U., Waldenberger, M., Willemsen, G., Zabaneh, D., Morris, R. W., Arnett, D. K., Baune, B. T., Boomsma, D. I., Chang, Y.-P.-C., Deary, I. J., Deloukas, P., Eriksson, J. G., Evans, D. M., Ferreira, M. A., Gaunt, T., Gudnason, V., Hamsten, A., Heinrich, J., Hingorani, A., Humphries, S. E., Jukema, J. W., Koenig, W., Kumari, M., Kutalik, Z., Lawlor, D. A., Lehtimäki, T., März, W., Mather, K. A., Naitza, S., Nauck, M., Ohlsson, C., Price, J. F., Raitakari, O., Rice, K., Sachdev, P. S., Slagboom, E., Sørensen, T. I. A., Spector, T., Stacey, D., Stathopoulou, M. G., Tanaka, T., Wannamethee, S. G., Whincup, P., Rotter, J. I., Dehghan, A., Boerwinkle, E., Psaty, B. M., Snieder, H., & Alizadeh, B. Z. (2021). Genome-wide association study of circulating interleukin 6 levels identifies novel loci. Human Molecular Genetics, 5(1), 393-409. doi:10.1093/hmg/ddab023.

    Abstract

    Interleukin 6 (IL-6) is a multifunctional cytokine with both pro- and anti-inflammatory properties with a heritability estimate of up to 61%. The circulating levels of IL-6 in blood have been associated with an increased risk of complex disease pathogenesis. We conducted a two-staged, discovery and replication meta genome-wide association study (GWAS) of circulating serum IL-6 levels comprising up to 67 428 (ndiscovery = 52 654 and nreplication = 14 774) individuals of European ancestry. The inverse variance fixed effects based discovery meta-analysis, followed by replication led to the identification of two independent loci, IL1F10/IL1RN rs6734238 on chromosome (Chr) 2q14, (Pcombined = 1.8 × 10−11), HLA-DRB1/DRB5 rs660895 on Chr6p21 (Pcombined = 1.5 × 10−10) in the combined meta-analyses of all samples. We also replicated the IL6R rs4537545 locus on Chr1q21 (Pcombined = 1.2 × 10−122). Our study identifies novel loci for circulating IL-6 levels uncovering new immunological and inflammatory pathways that may influence IL-6 pathobiology.
  • Cuellar-Partida, G., Tung, J. Y., Eriksson, N., Albrecht, E., Aliev, F., Andreassen, O. A., Barroso, I., Beckmann, J. S., Boks, M. P., Boomsma, D. I., Boyd, H. A., Breteler, M. M. B., Campbell, H., Chasman, D. I., Cherkas, L. F., Davies, G., De Geus, E. J. C., Deary, I. J., Deloukas, P., Dick, D. M. and 98 moreCuellar-Partida, G., Tung, J. Y., Eriksson, N., Albrecht, E., Aliev, F., Andreassen, O. A., Barroso, I., Beckmann, J. S., Boks, M. P., Boomsma, D. I., Boyd, H. A., Breteler, M. M. B., Campbell, H., Chasman, D. I., Cherkas, L. F., Davies, G., De Geus, E. J. C., Deary, I. J., Deloukas, P., Dick, D. M., Duffy, D. L., Eriksson, J. G., Esko, T., Feenstra, B., Geller, F., Gieger, C., Giegling, I., Gordon, S. D., Han, J., Hansen, T. F., Hartmann, A. M., Hayward, C., Heikkilä, K., Hicks, A. A., Hirschhorn, J. N., Hottenga, J.-J., Huffman, J. E., Hwang, L.-D., Ikram, M. A., Kaprio, J., Kemp, J. P., Khaw, K.-T., Klopp, N., Konte, B., Kutalik, Z., Lahti, J., Li, X., Loos, R. J. F., Luciano, M., Magnusson, S. H., Mangino, M., Marques-Vidal, P., Martin, N. G., McArdle, W. L., McCarthy, M. I., Medina-Gomez, C., Melbye, M., Melville, S. A., Metspalu, A., Milani, L., Mooser, V., Nelis, M., Nyholt, D. R., O'Connell, K. S., Ophoff, R. A., Palmer, C., Palotie, A., Palviainen, T., Pare, G., Paternoster, L., Peltonen, L., Penninx, B. W. J. H., Polasek, O., Pramstaller, P. P., Prokopenko, I., Raikkonen, K., Ripatti, S., Rivadeneira, F., Rudan, I., Rujescu, D., Smit, J. H., Smith, G. D., Smoller, J. W., Soranzo, N., Spector, T. D., St Pourcain, B., Starr, J. M., Stefánsson, H., Steinberg, S., Teder-Laving, M., Thorleifsson, G., Stefansson, K., Timpson, N. J., Uitterlinden, A. G., Van Duijn, C. M., Van Rooij, F. J. A., Vink, J. M., Vollenweider, P., Vuoksimaa, E., Waeber, G., Wareham, N. J., Warrington, N., Waterworth, D., Werge, T., Wichmann, H.-E., Widen, E., Willemsen, G., Wright, A. F., Wright, M. J., Xu, M., Zhao, J. H., Kraft, P., Hinds, D. A., Lindgren, C. M., Magi, R., Neale, B. M., Evans, D. M., & Medland, S. E. (2021). Genome-wide association study identifies 48 common genetic variants associated with handedness. Nature Human Behaviour, 5, 59-70. doi:10.1038/s41562-020-00956-y.

    Abstract

    Handedness has been extensively studied because of its relationship with language and the over-representation of left-handers in some neurodevelopmental disorders. Using data from the UK Biobank, 23andMe and the International Handedness Consortium, we conducted a genome-wide association meta-analysis of handedness (N = 1,766,671). We found 41 loci associated (P < 5 × 10−8) with left-handedness and 7 associated with ambidexterity. Tissue-enrichment analysis implicated the CNS in the aetiology of handedness. Pathways including regulation of microtubules and brain morphology were also highlighted. We found suggestive positive genetic correlations between left-handedness and neuropsychiatric traits, including schizophrenia and bipolar disorder. Furthermore, the genetic correlation between left-handedness and ambidexterity is low (rG = 0.26), which implies that these traits are largely influenced by different genetic mechanisms. Our findings suggest that handedness is highly polygenic and that the genetic variants that predispose to left-handedness may underlie part of the association with some psychiatric disorders.

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  • Gialluisi, A., Andlauer, T. F. M., Mirza-Schreiber, N., Moll, K., Becker, J., Hoffmann, P., Ludwig, K. U., Czamara, D., St Pourcain, B., Honbolygó, F., Tóth, D., Csépe, V., Huguet, H., Chaix, Y., Iannuzzi, S., Demonet, J.-F., Morris, A. P., Hulslander, J., Willcutt, E. G., DeFries, J. C. and 29 moreGialluisi, A., Andlauer, T. F. M., Mirza-Schreiber, N., Moll, K., Becker, J., Hoffmann, P., Ludwig, K. U., Czamara, D., St Pourcain, B., Honbolygó, F., Tóth, D., Csépe, V., Huguet, H., Chaix, Y., Iannuzzi, S., Demonet, J.-F., Morris, A. P., Hulslander, J., Willcutt, E. G., DeFries, J. C., Olson, R. K., Smith, S. D., Pennington, B. F., Vaessen, A., Maurer, U., Lyytinen, H., Peyrard-Janvid, M., Leppänen, P. H. T., Brandeis, D., Bonte, M., Stein, J. F., Talcott, J. B., Fauchereau, F., Wilcke, A., Kirsten, H., Müller, B., Francks, C., Bourgeron, T., Monaco, A. P., Ramus, F., Landerl, K., Kere, J., Scerri, T. S., Paracchini, S., Fisher, S. E., Schumacher, J., Nöthen, M. M., Müller-Myhsok, B., & Schulte-Körne, G. (2021). Genome-wide association study reveals new insights into the heritability and genetic correlates of developmental dyslexia. Molecular Psychiatry, 26, 3004-3017. doi:10.1038/s41380-020-00898-x.

    Abstract

    Developmental dyslexia (DD) is a learning disorder affecting the ability to read, with a heritability of 40–60%. A notable part of this heritability remains unexplained, and large genetic studies are warranted to identify new susceptibility genes and clarify the genetic bases of dyslexia. We carried out a genome-wide association study (GWAS) on 2274 dyslexia cases and 6272 controls, testing associations at the single variant, gene, and pathway level, and estimating heritability using single-nucleotide polymorphism (SNP) data. We also calculated polygenic scores (PGSs) based on large-scale GWAS data for different neuropsychiatric disorders and cortical brain measures, educational attainment, and fluid intelligence, testing them for association with dyslexia status in our sample. We observed statistically significant (p  < 2.8 × 10−6) enrichment of associations at the gene level, for LOC388780 (20p13; uncharacterized gene), and for VEPH1 (3q25), a gene implicated in brain development. We estimated an SNP-based heritability of 20–25% for DD, and observed significant associations of dyslexia risk with PGSs for attention deficit hyperactivity disorder (at pT = 0.05 in the training GWAS: OR = 1.23[1.16; 1.30] per standard deviation increase; p  = 8 × 10−13), bipolar disorder (1.53[1.44; 1.63]; p = 1 × 10−43), schizophrenia (1.36[1.28; 1.45]; p = 4 × 10−22), psychiatric cross-disorder susceptibility (1.23[1.16; 1.30]; p = 3 × 10−12), cortical thickness of the transverse temporal gyrus (0.90[0.86; 0.96]; p = 5 × 10−4), educational attainment (0.86[0.82; 0.91]; p = 2 × 10−7), and intelligence (0.72[0.68; 0.76]; p = 9 × 10−29). This study suggests an important contribution of common genetic variants to dyslexia risk, and novel genomic overlaps with psychiatric conditions like bipolar disorder, schizophrenia, and cross-disorder susceptibility. Moreover, it revealed the presence of shared genetic foundations with a neural correlate previously implicated in dyslexia by neuroimaging evidence.
  • Pender, R., Fearon, P., St Pourcain, B., Heron, J., & Mandy, W. (2021). Developmental trajectories of autistic social traits in the general population. Psychological Medicine. Advance online publication. doi:10.1017/S0033291721002166.

    Abstract

    Background Autistic people show diverse trajectories of autistic traits over time, a phenomenon labelled ‘chronogeneity’. For example, some show a decrease in symptoms, whilst others experience an intensification of difficulties. Autism spectrum disorder (ASD) is a dimensional condition, representing one end of a trait continuum that extends throughout the population. To date, no studies have investigated chronogeneity across the full range of autistic traits. We investigated the nature and clinical significance of autism trait chronogeneity in a large, general population sample. Methods Autistic social/communication traits (ASTs) were measured in the Avon Longitudinal Study of Parents and Children using the Social and Communication Disorders Checklist (SCDC) at ages 7, 10, 13 and 16 (N = 9744). We used Growth Mixture Modelling (GMM) to identify groups defined by their AST trajectories. Measures of ASD diagnosis, sex, IQ and mental health (internalising and externalising) were used to investigate external validity of the derived trajectory groups. Results The selected GMM model identified four AST trajectory groups: (i) Persistent High (2.3% of sample), (ii) Persistent Low (83.5%), (iii) Increasing (7.3%) and (iv) Decreasing (6.9%) trajectories. The Increasing group, in which females were a slight majority (53.2%), showed dramatic increases in SCDC scores during adolescence, accompanied by escalating internalising and externalising difficulties. Two-thirds (63.6%) of the Decreasing group were male. Conclusions Clinicians should note that for some young people autism-trait-like social difficulties first emerge during adolescence accompanied by problems with mood, anxiety, conduct and attention. A converse, majority-male group shows decreasing social difficulties during adolescence.
  • Shapland, C. Y., Verhoef, E., Smith, G. D., Fisher, S. E., Verhulst, B., Dale, P. S., & St Pourcain, B. (2021). Multivariate genome-wide covariance analyses of literacy, language and working memory skills reveal distinct etiologies. npj Science of Learning, 6: 23. doi:10.1038/s41539-021-00101-y.

    Abstract

    Several abilities outside literacy proper are associated with reading and spelling, both phenotypically and genetically, though our knowledge of multivariate genomic covariance structures is incomplete. Here, we introduce structural models describing genetic and residual influences between traits to study multivariate links across measures of literacy, phonological awareness, oral language, and phonological working memory (PWM) in unrelated UK youth (8-13 years, N=6,453). We find that all phenotypes share a large proportion of underlying genetic variation, although especially oral language and PWM reveal substantial differences in their genetic variance composition with substantial trait-specific genetic influences. Multivariate genetic and residual trait covariance showed concordant patterns, except for marked differences between oral language and literacy/phonological awareness, where strong genetic links contrasted near-zero residual overlap. These findings suggest differences in etiological mechanisms, acting beyond a pleiotropic set of genetic variants, and implicate variation in trait modifiability even among phenotypes that have high genetic correlations.

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  • Ip, H. F., van der Laan, C. M., Krapohl, E. M. L., Brikell, I., Sánchez-Mora, C., Nolte, I. M., St Pourcain, B., Bolhuis, K., Palviainen, T., Zafarmand, H., Colodro-Conde, L., Gordon, S., Zayats, T., Aliev, F., Jiang, C., Wang, C. A., Saunders, G., Karhunen, V., Hammerschlag, A. R., Adkins, D. E. and 129 moreIp, H. F., van der Laan, C. M., Krapohl, E. M. L., Brikell, I., Sánchez-Mora, C., Nolte, I. M., St Pourcain, B., Bolhuis, K., Palviainen, T., Zafarmand, H., Colodro-Conde, L., Gordon, S., Zayats, T., Aliev, F., Jiang, C., Wang, C. A., Saunders, G., Karhunen, V., Hammerschlag, A. R., Adkins, D. E., Border, R., Peterson, R. E., Prinz, J. A., Thiering, E., Seppälä, I., Vilor-Tejedor, N., Ahluwalia, T. S., Day, F. R., Hottenga, J.-J., Allegrini, A. G., Rimfeld, K., Chen, Q., Lu, Y., Martin, J., Soler Artigas, M., Rovira, P., Bosch, R., Español, G., Ramos Quiroga, J. A., Neumann, A., Ensink, J., Grasby, K., Morosoli, J. J., Tong, X., Marrington, S., Middeldorp, C., Scott, J. G., Vinkhuyzen, A., Shabalin, A. A., Corley, R., Evans, L. M., Sugden, K., Alemany, S., Sass, L., Vinding, R., Ruth, K., Tyrrell, J., Davies, G. E., Ehli, E. A., Hagenbeek, F. A., De Zeeuw, E., Van Beijsterveldt, T. C., Larsson, H., Snieder, H., Verhulst, F. C., Amin, N., Whipp, A. M., Korhonen, T., Vuoksimaa, E., Rose, R. J., Uitterlinden, A. G., Heath, A. C., Madden, P., Haavik, J., Harris, J. R., Helgeland, Ø., Johansson, S., Knudsen, G. P. S., Njolstad, P. R., Lu, Q., Rodriguez, A., Henders, A. K., Mamun, A., Najman, J. M., Brown, S., Hopfer, C., Krauter, K., Reynolds, C., Smolen, A., Stallings, M., Wadsworth, S., Wall, T. L., Silberg, J. L., Miller, A., Keltikangas-Järvinen, L., Hakulinen, C., Pulkki-Råback, L., Havdahl, A., Magnus, P., Raitakari, O. T., Perry, J. R. B., Llop, S., Lopez-Espinosa, M.-J., Bønnelykke, K., Bisgaard, H., Sunyer, J., Lehtimäki, T., Arseneault, L., Standl, M., Heinrich, J., Boden, J., Pearson, J., Horwood, L. J., Kennedy, M., Poulton, R., Eaves, L. J., Maes, H. H., Hewitt, J., Copeland, W. E., Costello, E. J., Williams, G. M., Wray, N., Järvelin, M.-R., McGue, M., Iacono, W., Caspi, A., Moffitt, T. E., Whitehouse, A., Pennell, C. E., Klump, K. L., Burt, S. A., Dick, D. M., Reichborn-Kjennerud, T., Martin, N. G., Medland, S. E., Vrijkotte, T., Kaprio, J., Tiemeier, H., Davey Smith, G., Hartman, C. A., Oldehinkel, A. J., Casas, M., Ribasés, M., Lichtenstein, P., Lundström, S., Plomin, R., Bartels, M., Nivard, M. G., & Boomsma, D. I. (2021). Genetic association study of childhood aggression across raters, instruments, and age. Translational Psychiatry, 11: 413. doi:10.1038/s41398-021-01480-x.
  • Verhoef, E., Shapland, C. Y., Fisher, S. E., Dale, P. S., & St Pourcain, B. (2021). The developmental genetic architecture of vocabulary skills during the first three years of life: Capturing emerging associations with later-life reading and cognition. PLoS Genetics, 17(2): e1009144. doi:10.1371/journal.pgen.1009144.

    Abstract

    Individual differences in early-life vocabulary measures are heritable and associated with subsequent reading and cognitive abilities, although the underlying mechanisms are little understood. Here, we (i) investigate the developmental genetic architecture of expressive and receptive vocabulary in early-life and (ii) assess timing of emerging genetic associations with mid-childhood verbal and non-verbal skills. We studied longitudinally assessed early-life vocabulary measures (15–38 months) and later-life verbal and non-verbal skills (7–8 years) in up to 6,524 unrelated children from the population-based Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. We dissected the phenotypic variance of rank-transformed scores into genetic and residual components by fitting multivariate structural equation models to genome-wide genetic-relationship matrices. Our findings show that the genetic architecture of early-life vocabulary involves multiple distinct genetic factors. Two of these genetic factors are developmentally stable and also contribute to genetic variation in mid-childhood skills: One genetic factor emerging with expressive vocabulary at 24 months (path coefficient: 0.32(SE = 0.06)) was also related to later-life reading (path coefficient: 0.25(SE = 0.12)) and verbal intelligence (path coefficient: 0.42(SE = 0.13)), explaining up to 17.9% of the phenotypic variation. A second, independent genetic factor emerging with receptive vocabulary at 38 months (path coefficient: 0.15(SE = 0.07)), was more generally linked to verbal and non-verbal cognitive abilities in mid-childhood (reading path coefficient: 0.57(SE = 0.07); verbal intelligence path coefficient: 0.60(0.10); performance intelligence path coefficient: 0.50(SE = 0.08)), accounting for up to 36.1% of the phenotypic variation and the majority of genetic variance in these later-life traits (≥66.4%). Thus, the genetic foundations of mid-childhood reading and cognitive abilities are diverse. They involve at least two independent genetic factors that emerge at different developmental stages during early language development and may implicate differences in cognitive processes that are already detectable during toddlerhood.

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  • Verhoef, E. (2021). Why do we change how we speak? Multivariate genetic analyses of language and related traits across development and disorder. PhD Thesis, Radboud University Nijmegen, Nijmegen.
  • Verhoef, E., Shapland, C. Y., Fisher, S. E., Dale, P. S., & St Pourcain, B. (2021). The developmental origins of genetic factors influencing language and literacy: Associations with early-childhood vocabulary. Journal of Child Psychology and Psychiatry, 62(6), 728-738. doi:10.1111/jcpp.13327.

    Abstract

    Background The heritability of language and literacy skills increases from early‐childhood to adolescence. The underlying mechanisms are little understood and may involve (a) the amplification of genetic influences contributing to early language abilities, and/or (b) the emergence of novel genetic factors (innovation). Here, we investigate the developmental origins of genetic factors influencing mid‐childhood/early‐adolescent language and literacy. We evaluate evidence for the amplification of early‐childhood genetic factors for vocabulary, in addition to genetic innovation processes. Methods Expressive and receptive vocabulary scores at 38 months, thirteen language‐ and literacy‐related abilities and nonverbal cognition (7–13 years) were assessed in unrelated children from the Avon Longitudinal Study of Parents and Children (ALSPAC, Nindividuals ≤ 6,092). We investigated the multivariate genetic architecture underlying early‐childhood expressive and receptive vocabulary, and each of 14 mid‐childhood/early‐adolescent language, literacy or cognitive skills with trivariate structural equation (Cholesky) models as captured by genome‐wide genetic relationship matrices. The individual path coefficients of the resulting structural models were finally meta‐analysed to evaluate evidence for overarching patterns. Results We observed little support for the emergence of novel genetic sources for language, literacy or cognitive abilities during mid‐childhood or early adolescence. Instead, genetic factors of early‐childhood vocabulary, especially those unique to receptive skills, were amplified and represented the majority of genetic variance underlying many of these later complex skills (≤99%). The most predictive early genetic factor accounted for 29.4%(SE = 12.9%) to 45.1%(SE = 7.6%) of the phenotypic variation in verbal intelligence and literacy skills, but also for 25.7%(SE = 6.4%) in performance intelligence, while explaining only a fraction of the phenotypic variation in receptive vocabulary (3.9%(SE = 1.8%)). Conclusions Genetic factors contributing to many complex skills during mid‐childhood and early adolescence, including literacy, verbal cognition and nonverbal cognition, originate developmentally in early‐childhood and are captured by receptive vocabulary. This suggests developmental genetic stability and overarching aetiological mechanisms.

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  • Verhoef, E., Grove, J., Shapland, C. Y., Demontis, D., Burgess, S., Rai, D., Børglum, A. D., & St Pourcain, B. (2021). Discordant associations of educational attainment with ASD and ADHD implicate a polygenic form of pleiotropy. Nature Communications, 12: 6534. doi:10.1038/s41467-021-26755-1.

    Abstract

    Autism Spectrum Disorder (ASD) and Attention-Deficit/Hyperactivity Disorder (ADHD) are complex co-occurring neurodevelopmental conditions. Their genetic architectures reveal striking similarities but also differences, including strong, discordant polygenic associations with educational attainment (EA). To study genetic mechanisms that present as ASD-related positive and ADHD-related negative genetic correlations with EA, we carry out multivariable regression analyses using genome-wide summary statistics (N = 10,610–766,345). Our results show that EA-related genetic variation is shared across ASD and ADHD architectures, involving identical marker alleles. However, the polygenic association profile with EA, across shared marker alleles, is discordant for ASD versus ADHD risk, indicating independent effects. At the single-variant level, our results suggest either biological pleiotropy or co-localisation of different risk variants, implicating MIR19A/19B microRNA mechanisms. At the polygenic level, they point to a polygenic form of pleiotropy that contributes to the detectable genome-wide correlation between ASD and ADHD and is consistent with effect cancellation across EA-related regions.

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    supplementary information
  • Grasby, K. L., Jahanshad, N., Painter, J. N., Colodro-Conde, L., Bralten, J., Hibar, D. P., Lind, P. A., Pizzagalli, F., Ching, C. R. K., McMahon, M. A. B., Shatokhina, N., Zsembik, L. C. P., Thomopoulos, S. I., Zhu, A. H., Strike, L. T., Agartz, I., Alhusaini, S., Almeida, M. A. A., Alnæs, D., Amlien, I. K. and 341 moreGrasby, K. L., Jahanshad, N., Painter, J. N., Colodro-Conde, L., Bralten, J., Hibar, D. P., Lind, P. A., Pizzagalli, F., Ching, C. R. K., McMahon, M. A. B., Shatokhina, N., Zsembik, L. C. P., Thomopoulos, S. I., Zhu, A. H., Strike, L. T., Agartz, I., Alhusaini, S., Almeida, M. A. A., Alnæs, D., Amlien, I. K., Andersson, M., Ard, T., Armstrong, N. J., Ashley-Koch, A., Atkins, J. R., Bernard, M., Brouwer, R. M., Buimer, E. E. L., Bülow, R., Bürger, C., Cannon, D. M., Chakravarty, M., Chen, Q., Cheung, J. W., Couvy-Duchesne, B., Dale, A. M., Dalvie, S., De Araujo, T. K., De Zubicaray, G. I., De Zwarte, S. M. C., Den Braber, A., Doan, N. T., Dohm, K., Ehrlich, S., Engelbrecht, H.-R., Erk, S., Fan, C. C., Fedko, I. O., Foley, S. F., Ford, J. M., Fukunaga, M., Garrett, M. E., Ge, T., Giddaluru, S., Goldman, A. L., Green, M. J., Groenewold, N. A., Grotegerd, D., Gurholt, T. P., Gutman, B. A., Hansell, N. K., Harris, M. A., Harrison, M. B., Haswell, C. C., Hauser, M., Herms, S., Heslenfeld, D. J., Ho, N. F., Hoehn, D., Hoffmann, P., Holleran, L., Hoogman, M., Hottenga, J.-J., Ikeda, M., Janowitz, D., Jansen, I. E., Jia, T., Jockwitz, C., Kanai, R., Karama, S., Kasperaviciute, D., Kaufmann, T., Kelly, S., Kikuchi, M., Klein, M., Knapp, M., Knodt, A. R., Krämer, B., Lam, M., Lancaster, T. M., Lee, P. H., Lett, T. A., Lewis, L. B., Lopes-Cendes, I., Luciano, M., Macciardi, F., Marquand, A. F., Mathias, S. R., Melzer, T. R., Milaneschi, Y., Mirza-Schreiber, N., Moreira, J. C. V., Mühleisen, T. W., Müller-Myhsok, B., Najt, P., Nakahara, S., Nho, K., Olde Loohuis, L. M., Orfanos, D. P., Pearson, J. F., Pitcher, T. L., Pütz, B., Quidé, Y., Ragothaman, A., Rashid, F. M., Reay, W. R., Redlich, R., Reinbold, C. S., Repple, J., Richard, G., Riedel, B. C., Risacher, S. L., Rocha, C. S., Mota, N. R., Salminen, L., Saremi, A., Saykin, A. J., Schlag, F., Schmaal, L., Schofield, P. R., Secolin, R., Shapland, C. Y., Shen, L., Shin, J., Shumskaya, E., Sønderby, I. E., Sprooten, E., Tansey, K. E., Teumer, A., Thalamuthu, A., Tordesillas-Gutiérrez, D., Turner, J. A., Uhlmann, A., Vallerga, C. L., Van der Meer, D., Van Donkelaar, M. M. J., Van Eijk, L., Van Erp, T. G. M., Van Haren, N. E. M., Van Rooij, D., Van Tol, M.-J., Veldink, J. H., Verhoef, E., Walton, E., Wang, M., Wang, Y., Wardlaw, J. M., Wen, W., Westlye, L. T., Whelan, C. D., Witt, S. H., Wittfeld, K., Wolf, C., Wolfers, T., Wu, J. Q., Yasuda, C. L., Zaremba, D., Zhang, Z., Zwiers, M. P., Artiges, E., Assareh, A. A., Ayesa-Arriola, R., Belger, A., Brandt, C. L., Brown, G. G., Cichon, S., Curran, J. E., Davies, G. E., Degenhardt, F., Dennis, M. F., Dietsche, B., Djurovic, S., Doherty, C. P., Espiritu, R., Garijo, D., Gil, Y., Gowland, P. A., Green, R. C., Häusler, A. N., Heindel, W., Ho, B.-C., Hoffmann, W. U., Holsboer, F., Homuth, G., Hosten, N., Jack Jr., C. R., Jang, M., Jansen, A., Kimbrel, N. A., Kolskår, K., Koops, S., Krug, A., Lim, K. O., Luykx, J. J., Mathalon, D. H., Mather, K. A., Mattay, V. S., Matthews, S., Mayoral Van Son, J., McEwen, S. C., Melle, I., Morris, D. W., Mueller, B. A., Nauck, M., Nordvik, J. E., Nöthen, M. M., O’Leary, D. S., Opel, N., Paillère Martinot, M.-L., Pike, G. B., Preda, A., Quinlan, E. B., Rasser, P. E., Ratnakar, V., Reppermund, S., Steen, V. M., Tooney, P. A., Torres, F. R., Veltman, D. J., Voyvodic, J. T., Whelan, R., White, T., Yamamori, H., Adams, H. H. H., Bis, J. C., Debette, S., Decarli, C., Fornage, M., Gudnason, V., Hofer, E., Ikram, M. A., Launer, L., Longstreth, W. T., Lopez, O. L., Mazoyer, B., Mosley, T. H., Roshchupkin, G. V., Satizabal, C. L., Schmidt, R., Seshadri, S., Yang, Q., Alzheimer’s Disease Neuroimaging Initiative, CHARGE Consortium, EPIGEN Consortium, IMAGEN Consortium, SYS Consortium, Parkinson’s Progression Markers Initiative, Alvim, M. K. M., Ames, D., Anderson, T. J., Andreassen, O. A., Arias-Vasquez, A., Bastin, M. E., Baune, B. T., Beckham, J. C., Blangero, J., Boomsma, D. I., Brodaty, H., Brunner, H. G., Buckner, R. L., Buitelaar, J. K., Bustillo, J. R., Cahn, W., Cairns, M. J., Calhoun, V., Carr, V. J., Caseras, X., Caspers, S., Cavalleri, G. L., Cendes, F., Corvin, A., Crespo-Facorro, B., Dalrymple-Alford, J. C., Dannlowski, U., De Geus, E. J. C., Deary, I. J., Delanty, N., Depondt, C., Desrivières, S., Donohoe, G., Espeseth, T., Fernández, G., Fisher, S. E., Flor, H., Forstner, A. J., Francks, C., Franke, B., Glahn, D. C., Gollub, R. L., Grabe, H. J., Gruber, O., Håberg, A. K., Hariri, A. R., Hartman, C. A., Hashimoto, R., Heinz, A., Henskens, F. A., Hillegers, M. H. J., Hoekstra, P. J., Holmes, A. J., Hong, L. E., Hopkins, W. D., Hulshoff Pol, H. E., Jernigan, T. L., Jönsson, E. G., Kahn, R. S., Kennedy, M. A., Kircher, T. T. J., Kochunov, P., Kwok, J. B. J., Le Hellard, S., Loughland, C. M., Martin, N. G., Martinot, J.-L., McDonald, C., McMahon, K. L., Meyer-Lindenberg, A., Michie, P. T., Morey, R. A., Mowry, B., Nyberg, L., Oosterlaan, J., Ophoff, R. A., Pantelis, C., Paus, T., Pausova, Z., Penninx, B. W. J. H., Polderman, T. J. C., Posthuma, D., Rietschel, M., Roffman, J. L., Rowland, L. M., Sachdev, P. S., Sämann, P. G., Schall, U., Schumann, G., Scott, R. J., Sim, K., Sisodiya, S. M., Smoller, J. W., Sommer, I. E., St Pourcain, B., Stein, D. J., Toga, A. W., Trollor, J. N., Van der Wee, N. J. A., van 't Ent, D., Völzke, H., Walter, H., Weber, B., Weinberger, D. R., Wright, M. J., Zhou, J., Stein, J. L., Thompson, P. M., & Medland, S. E. (2020). The genetic architecture of the human cerebral cortex. Science, 367(6484): eaay6690. doi:10.1126/science.aay6690.

    Abstract

    The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson’s disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
  • Howe, L. J., Hemani, G., Lesseur, C., Gaborieau, V., Ludwig, K. U., Mangold, E., Brennan, P., Ness, A. R., St Pourcain, B., Smith, G. D., & Lewis, S. J. (2020). Evaluating shared genetic influences on nonsyndromic cleft lip/palate and oropharyngeal neoplasms. Genetic Epidemiology, 44(8), 924-933. doi:10.1002/gepi.22343.

    Abstract

    It has been hypothesised that nonsyndromic cleft lip/palate (nsCL/P) and cancer may share aetiological risk factors. Population studies have found inconsistent evidence for increased incidence of cancer in nsCL/P cases, but several genes (e.g.,CDH1,AXIN2) have been implicated in the aetiologies of both phenotypes. We aimed to evaluate shared genetic aetiology between nsCL/P and oral cavity/oropharyngeal cancers (OC/OPC), which affect similar anatomical regions. Using a primary sample of 5,048 OC/OPC cases and 5,450 controls of European ancestry and a replication sample of 750 cases and 336,319 controls from UK Biobank, we estimate genetic overlap using nsCL/P polygenic risk scores (PRS) with Mendelian randomization analyses performed to evaluate potential causal mechanisms. In the primary sample, we found strong evidence for an association between a nsCL/P PRS and increased odds of OC/OPC (per standard deviation increase in score, odds ratio [OR]: 1.09; 95% confidence interval [CI]: 1.04, 1.13;p = .000053). Although confidence intervals overlapped with the primary estimate, we did not find confirmatory evidence of an association between the PRS and OC/OPC in UK Biobank (OR 1.02; 95% CI: 0.95, 1.10;p = .55). Mendelian randomization analyses provided evidence that major nsCL/P risk variants are unlikely to influence OC/OPC. Our findings suggest possible shared genetic influences on nsCL/P and OC/OPC.

    Additional information

    Supporting information
  • Gialluisi, A., Andlauer, T. F. M., Mirza-Schreiber, N., Moll, K., Becker, J., Hoffmann, P., Ludwig, K. U., Czamara, D., St Pourcain, B., Brandler, W., Honbolygó, F., Tóth, D., Csépe, V., Huguet, G., Morris, A. P., Hulslander, J., Willcutt, E. G., DeFries, J. C., Olson, R. K., Smith, S. D. and 25 moreGialluisi, A., Andlauer, T. F. M., Mirza-Schreiber, N., Moll, K., Becker, J., Hoffmann, P., Ludwig, K. U., Czamara, D., St Pourcain, B., Brandler, W., Honbolygó, F., Tóth, D., Csépe, V., Huguet, G., Morris, A. P., Hulslander, J., Willcutt, E. G., DeFries, J. C., Olson, R. K., Smith, S. D., Pennington, B. F., Vaessen, A., Maurer, U., Lyytinen, H., Peyrard-Janvid, M., Leppänen, P. H. T., Brandeis, D., Bonte, M., Stein, J. F., Talcott, J. B., Fauchereau, F., Wilcke, A., Francks, C., Bourgeron, T., Monaco, A. P., Ramus, F., Landerl, K., Kere, J., Scerri, T. S., Paracchini, S., Fisher, S. E., Schumacher, J., Nöthen, M. M., Müller-Myhsok, B., & Schulte-Körne, G. (2019). Genome-wide association scan identifies new variants associated with a cognitive predictor of dyslexia. Translational Psychiatry, 9(1): 77. doi:10.1038/s41398-019-0402-0.

    Abstract

    Developmental dyslexia (DD) is one of the most prevalent learning disorders, with high impact on school and psychosocial development and high comorbidity with conditions like attention-deficit hyperactivity disorder (ADHD), depression, and anxiety. DD is characterized by deficits in different cognitive skills, including word reading, spelling, rapid naming, and phonology. To investigate the genetic basis of DD, we conducted a genome-wide association study (GWAS) of these skills within one of the largest studies available, including nine cohorts of reading-impaired and typically developing children of European ancestry (N = 2562–3468). We observed a genome-wide significant effect (p < 1 × 10−8) on rapid automatized naming of letters (RANlet) for variants on 18q12.2, within MIR924HG (micro-RNA 924 host gene; rs17663182 p = 4.73 × 10−9), and a suggestive association on 8q12.3 within NKAIN3 (encoding a cation transporter; rs16928927, p = 2.25 × 10−8). rs17663182 (18q12.2) also showed genome-wide significant multivariate associations with RAN measures (p = 1.15 × 10−8) and with all the cognitive traits tested (p = 3.07 × 10−8), suggesting (relational) pleiotropic effects of this variant. A polygenic risk score (PRS) analysis revealed significant genetic overlaps of some of the DD-related traits with educational attainment (EDUyears) and ADHD. Reading and spelling abilities were positively associated with EDUyears (p ~ [10−5–10−7]) and negatively associated with ADHD PRS (p ~ [10−8−10−17]). This corroborates a long-standing hypothesis on the partly shared genetic etiology of DD and ADHD, at the genome-wide level. Our findings suggest new candidate DD susceptibility genes and provide new insights into the genetics of dyslexia and its comorbities.
  • Grove, J., Ripke, S., Als, T. D., Mattheisen, M., Walters, R., Won, H., Pallesen, J., Agerbo, E., Andreassen, O. A., Anney, R., Belliveau, R., Bettella, F., Buxbaum, J. D., Bybjerg-Grauholm, J., Bækved-Hansen, M., Cerrato, F., Chambert, K., Christensen, J. H., Churchhouse, C., Dellenvall, K. and 55 moreGrove, J., Ripke, S., Als, T. D., Mattheisen, M., Walters, R., Won, H., Pallesen, J., Agerbo, E., Andreassen, O. A., Anney, R., Belliveau, R., Bettella, F., Buxbaum, J. D., Bybjerg-Grauholm, J., Bækved-Hansen, M., Cerrato, F., Chambert, K., Christensen, J. H., Churchhouse, C., Dellenvall, K., Demontis, D., De Rubeis, S., Devlin, B., Djurovic, S., Dumont, A., Goldstein, J., Hansen, C. S., Hauberg, M. E., Hollegaard, M. V., Hope, S., Howrigan, D. P., Huang, H., Hultman, C., Klei, L., Maller, J., Martin, J., Martin, A. R., Moran, J., Nyegaard, M., Nærland, T., Palmer, D. S., Palotie, A., Pedersen, C. B., Pedersen, M. G., Poterba, T., Poulsen, J. B., St Pourcain, B., Qvist, P., Rehnström, K., Reichenberg, A., Reichert, J., Robinson, E. B., Roeder, K., Roussos, P., Saemundsen, E., Sandin, S., Satterstrom, F. K., Smith, G. D., Stefansson, H., Stefansson, K., Steinberg, S., Stevens, C., Sullivan, P. F., Turley, P., Walters, G. B., Xu, X., Autism Spectrum Disorders Working Group of The Psychiatric Genomics Consortium, BUPGEN, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Me Research Team, Geschwind, D., Nordentoft, M., Hougaard, D. M., Werge, T., Mors, O., Mortensen, P. B., Neale, B. M., Daly, M. J., & Børglum, A. D. (2019). Identification of common genetic risk variants for autism spectrum disorder. Nature Genetics, 51, 431-444. doi:10.1038/s41588-019-0344-8.

    Abstract

    Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.

    Additional information

    Supplementary Text and Figures
  • Gunz, P., Tilot, A. K., Wittfeld, K., Teumer, A., Shapland, C. Y., Van Erp, T. G. M., Dannemann, M., Vernot, B., Neubauer, S., Guadalupe, T., Fernandez, G., Brunner, H., Enard, W., Fallon, J., Hosten, N., Völker, U., Profico, A., Di Vincenzo, F., Manzi, G., Kelso, J. and 7 moreGunz, P., Tilot, A. K., Wittfeld, K., Teumer, A., Shapland, C. Y., Van Erp, T. G. M., Dannemann, M., Vernot, B., Neubauer, S., Guadalupe, T., Fernandez, G., Brunner, H., Enard, W., Fallon, J., Hosten, N., Völker, U., Profico, A., Di Vincenzo, F., Manzi, G., Kelso, J., St Pourcain, B., Hublin, J.-J., Franke, B., Pääbo, S., Macciardi, F., Grabe, H. J., & Fisher, S. E. (2019). Neandertal introgression sheds light on modern human endocranial globularity. Current Biology, 29(1), 120-127. doi:10.1016/j.cub.2018.10.065.

    Abstract

    One of the features that distinguishes modern humans from our extinct relatives and ancestors is a globular shape of the braincase [1-4]. As the endocranium closely mirrors the outer shape of the brain, these differences might reflect altered neural architecture [4,5]. However, in the absence of fossil brain tissue the underlying neuroanatomical changes as well as their genetic bases remain elusive. To better understand the biological foundations of modern human endocranial shape, we turn to our closest extinct relatives, the Neandertals. Interbreeding between modern humans and Neandertals has resulted in introgressed fragments of Neandertal DNA in the genomes of present-day non- Africans [6,7]. Based on shape analyses of fossil skull endocasts, we derive a measure of endocranial globularity from structural magnetic resonance imaging (MRI) scans of thousands of modern humans, and study the effects of introgressed fragments of Neandertal DNA on this phenotype. We find that Neandertal alleles on chromosomes 1 and 18 are associated with reduced endocranial globularity. These alleles influence expression of two nearby genes, UBR4 and PHLPP1, which are involved in neurogenesis and myelination, respectively. Our findings show how integration of fossil skull data with archaic genomics and neuroimaging can suggest developmental mechanisms that may contribute to the unique modern human endocranial shape.

    Additional information

    mmc1.pdf mmc2.xlsx
  • Harneit, A., Braun, U., Geiger, L. S., Zang, Z., Hakobjan, M., Van Donkelaar, M. M. J., Schweiger, J. I., Schwarz, K., Gan, G., Erk, S., Heinz, A., Romanczuk‐Seiferth, N., Witt, S., Rietschel, M., Walter, H., Franke, B., Meyer‐Lindenberg, A., & Tost, H. (2019). MAOA-VNTR genotype affects structural and functional connectivity in distributed brain networks. Human Brain Mapping, 40(18), 5202-5212. doi:10.1002/hbm.24766.

    Abstract

    Previous studies have linked the low expression variant of a variable number of tandem repeat polymorphism in the monoamine oxidase A gene (MAOA‐L) to the risk for impulsivity and aggression, brain developmental abnormalities, altered cortico‐limbic circuit function, and an exaggerated neural serotonergic tone. However, the neurobiological effects of this variant on human brain network architecture are incompletely understood. We studied healthy individuals and used multimodal neuroimaging (sample size range: 219–284 across modalities) and network‐based statistics (NBS) to probe the specificity of MAOA‐L‐related connectomic alterations to cortical‐limbic circuits and the emotion processing domain. We assessed the spatial distribution of affected links across several neuroimaging tasks and data modalities to identify potential alterations in network architecture. Our results revealed a distributed network of node links with a significantly increased connectivity in MAOA‐L carriers compared to the carriers of the high expression (H) variant. The hyperconnectivity phenotype primarily consisted of between‐lobe (“anisocoupled”) network links and showed a pronounced involvement of frontal‐temporal connections. Hyperconnectivity was observed across functional magnetic resonance imaging (fMRI) of implicit emotion processing (pFWE = .037), resting‐state fMRI (pFWE = .022), and diffusion tensor imaging (pFWE = .044) data, while no effects were seen in fMRI data of another cognitive domain, that is, spatial working memory (pFWE = .540). These observations are in line with prior research on the MAOA‐L variant and complement these existing data by novel insights into the specificity and spatial distribution of the neurogenetic effects. Our work highlights the value of multimodal network connectomic approaches for imaging genetics.
  • Haworth, S., Shapland, C. Y., Hayward, C., Prins, B. P., Felix, J. F., Medina-Gomez, C., Rivadeneira, F., Wang, C., Ahluwalia, T. S., Vrijheid, M., Guxens, M., Sunyer, J., Tachmazidou, I., Walter, K., Iotchkova, V., Jackson, A., Cleal, L., Huffmann, J., Min, J. L., Sass, L. and 15 moreHaworth, S., Shapland, C. Y., Hayward, C., Prins, B. P., Felix, J. F., Medina-Gomez, C., Rivadeneira, F., Wang, C., Ahluwalia, T. S., Vrijheid, M., Guxens, M., Sunyer, J., Tachmazidou, I., Walter, K., Iotchkova, V., Jackson, A., Cleal, L., Huffmann, J., Min, J. L., Sass, L., Timmers, P. R. H. J., UK10K consortium, Davey Smith, G., Fisher, S. E., Wilson, J. F., Cole, T. J., Fernandez-Orth, D., Bønnelykke, K., Bisgaard, H., Pennell, C. E., Jaddoe, V. W. V., Dedoussis, G., Timpson, N. J., Zeggini, E., Vitart, V., & St Pourcain, B. (2019). Low-frequency variation in TP53 has large effects on head circumference and intracranial volume. Nature Communications, 10: 357. doi:10.1038/s41467-018-07863-x.

    Abstract

    Cranial growth and development is a complex process which affects the closely related traits of head circumference (HC) and intracranial volume (ICV). The underlying genetic influences affecting these traits during the transition from childhood to adulthood are little understood, but might include both age-specific genetic influences and low-frequency genetic variation. To understand these influences, we model the developmental genetic architecture of HC, showing this is genetically stable and correlated with genetic determinants of ICV. Investigating up to 46,000 children and adults of European descent, we identify association with final HC and/or final ICV+HC at 9 novel common and low-frequency loci, illustrating that genetic variation from a wide allele frequency spectrum contributes to cranial growth. The largest effects are reported for low-frequency variants within TP53, with 0.5 cm wider heads in increaser-allele carriers versus non-carriers during mid-childhood, suggesting a previously unrecognized role of TP53 transcripts in human cranial development.

    Additional information

    Supplementary Information
  • Howe, L. J., Richardson, T. G., Arathimos, R., Alvizi, L., Passos-Bueno, M. R., Stanier, P., Nohr, E., Ludwig, K. U., Mangold, E., Knapp, M., Stergiakouli, E., St Pourcain, B., Smith, G. D., Sandy, J., Relton, C. L., Lewis, S. J., Hemani, G., & Sharp, G. C. (2019). Evidence for DNA methylation mediating genetic liability to non-syndromic cleft lip/palate. Epigenomics, 11(2), 133-145. doi:10.2217/epi-2018-0091.

    Abstract

    Aim: To determine if nonsyndromic cleft lip with or without cleft palate (nsCL/P) genetic risk variants influence liability to nsCL/P through gene regulation pathways, such as those involving DNA methylation. Materials & methods: nsCL/P genetic summary data and methylation data from four studies were used in conjunction with Mendelian randomization and joint likelihood mapping to investigate potential mediation of nsCL/P genetic variants. Results & conclusion: Evidence was found at VAX1 (10q25.3), LOC146880 (17q23.3) and NTN1 (17p13.1), that liability to nsCL/P and variation in DNA methylation might be driven by the same genetic variant, suggesting that genetic variation at these loci may increase liability to nsCL/P by influencing DNA methylation. Follow-up analyses using different tissues and gene expression data provided further insight into possible biological mechanisms.

    Additional information

    Supplementary material
  • Howe, L., Lawson, D. J., Davies, N. M., St Pourcain, B., Lewis, S. J., Smith, G. D., & Hemani, G. (2019). Genetic evidence for assortative mating on alcohol consumption in the UK Biobank. Nature Communications, 10: 5039. doi:10.1038/s41467-019-12424-x.

    Abstract

    Alcohol use is correlated within spouse-pairs, but it is difficult to disentangle effects of alcohol consumption on mate-selection from social factors or the shared spousal environment. We hypothesised that genetic variants related to alcohol consumption may, via their effect on alcohol behaviour, influence mate selection. Here, we find strong evidence that an individual’s self-reported alcohol consumption and their genotype at rs1229984, a missense variant in ADH1B, are associated with their partner’s self-reported alcohol use. Applying Mendelian randomization, we estimate that a unit increase in an individual’s weekly alcohol consumption increases partner’s alcohol consumption by 0.26 units (95% C.I. 0.15, 0.38; P = 8.20 × 10−6). Furthermore, we find evidence of spousal genotypic concordance for rs1229984, suggesting that spousal concordance for alcohol consumption existed prior to cohabitation. Although the SNP is strongly associated with ancestry, our results suggest some concordance independent of population stratification. Our findings suggest that alcohol behaviour directly influences mate selection.
  • Middeldorp, C. M., Felix, J. F., Mahajan, A., EArly Genetics and Lifecourse Epidemiology (EAGLE) Consortium, Early Growth Genetics (EGG) consortium, & McCarthy, M. I. (2019). The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia: Design, results and future prospects. European Journal of Epidemiology, 34(3), 279-300. doi:10.1007/s10654-019-00502-9.

    Abstract

    The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.
  • Tilot, A. K., Vino, A., Kucera, K. S., Carmichael, D. A., Van den Heuvel, L., Den Hoed, J., Sidoroff-Dorso, A. V., Campbell, A., Porteous, D. J., St Pourcain, B., Van Leeuwen, T. M., Ward, J., Rouw, R., Simner, J., & Fisher, S. E. (2019). Investigating genetic links between grapheme-colour synaesthesia and neuropsychiatric traits. Philosophical Transactions of the Royal Society of London, Series B: Biological Sciences, 374: 20190026. doi:10.1098/rstb.2019.0026.

    Abstract

    Synaesthesia is a neurological phenomenon affecting perception, where triggering stimuli (e.g. letters and numbers) elicit unusual secondary sensory experiences (e.g. colours). Family-based studies point to a role for genetic factors in the development of this trait. However, the contributions of common genomic variation to synaesthesia have not yet been investigated. Here, we present the SynGenes cohort, the largest genotyped collection of unrelated people with grapheme–colour synaesthesia (n = 723). Synaesthesia has been associated with a range of other neuropsychological traits, including enhanced memory and mental imagery, as well as greater sensory sensitivity. Motivated by the prior literature on putative trait overlaps, we investigated polygenic scores derived from published genome-wide scans of schizophrenia and autism spectrum disorder (ASD), comparing our SynGenes cohort to 2181 non-synaesthetic controls. We found a very slight association between schizophrenia polygenic scores and synaesthesia (Nagelkerke's R2 = 0.0047, empirical p = 0.0027) and no significant association for scores related to ASD (Nagelkerke's R2 = 0.00092, empirical p = 0.54) or body mass index (R2 = 0.00058, empirical p = 0.60), included as a negative control. As sample sizes for studying common genomic variation continue to increase, genetic investigations of the kind reported here may yield novel insights into the shared biology between synaesthesia and other traits, to complement findings from neuropsychology and brain imaging.

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  • Verhoef, E., Demontis, D., Burgess, S., Shapland, C. Y., Dale, P. S., Okbay, A., Neale, B. M., Faraone, S. V., iPSYCH-Broad-PGC ADHD Consortium, Stergiakouli, E., Davey Smith, G., Fisher, S. E., Borglum, A., & St Pourcain, B. (2019). Disentangling polygenic associations between Attention-Deficit/Hyperactivity Disorder, educational attainment, literacy and language. Translational Psychiatry, 9: 35. doi:10.1038/s41398-018-0324-2.

    Abstract

    Interpreting polygenic overlap between ADHD and both literacy-related and language-related impairments is challenging as genetic associations might be influenced by indirectly shared genetic factors. Here, we investigate genetic overlap between polygenic ADHD risk and multiple literacy-related and/or language-related abilities (LRAs), as assessed in UK children (N ≤ 5919), accounting for genetically predictable educational attainment (EA). Genome-wide summary statistics on clinical ADHD and years of schooling were obtained from large consortia (N ≤ 326,041). Our findings show that ADHD-polygenic scores (ADHD-PGS) were inversely associated with LRAs in ALSPAC, most consistently with reading-related abilities, and explained ≤1.6% phenotypic variation. These polygenic links were then dissected into both ADHD effects shared with and independent of EA, using multivariable regressions (MVR). Conditional on EA, polygenic ADHD risk remained associated with multiple reading and/or spelling abilities, phonemic awareness and verbal intelligence, but not listening comprehension and non-word repetition. Using conservative ADHD-instruments (P-threshold < 5 × 10−8), this corresponded, for example, to a 0.35 SD decrease in pooled reading performance per log-odds in ADHD-liability (P = 9.2 × 10−5). Using subthreshold ADHD-instruments (P-threshold < 0.0015), these effects became smaller, with a 0.03 SD decrease per log-odds in ADHD risk (P = 1.4 × 10−6), although the predictive accuracy increased. However, polygenic ADHD-effects shared with EA were of equal strength and at least equal magnitude compared to those independent of EA, for all LRAs studied, and detectable using subthreshold instruments. Thus, ADHD-related polygenic links with LRAs are to a large extent due to shared genetic effects with EA, although there is evidence for an ADHD-specific association profile, independent of EA, that primarily involves literacy-related impairments.

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    41398_2018_324_MOESM1_ESM.docx
  • Howe, L. J., Lee, M. K., Sharp, G. C., Smith, G. D. W., St Pourcain, B., Shaffer, J. R., Ludwig, K. U., Mangold, E., Marazita, M. L., Feingold, E., Zhurov, A., Stergiakouli, E., Sandy, J., Richmond, S., Weinberg, S. M., Hemani, G., & Lewis, S. J. (2018). Investigating the shared genetics of non-syndromic cleft lip/palate and facial morphology. PLoS Genetics, 14(8): e1007501. doi:10.1371/journal.pgen.1007501.

    Abstract

    There is increasing evidence that genetic risk variants for non-syndromic cleft lip/palate (nsCL/P) are also associated with normal-range variation in facial morphology. However, previous analyses are mostly limited to candidate SNPs and findings have not been consistently replicated. Here, we used polygenic risk scores (PRS) to test for genetic overlap between nsCL/P and seven biologically relevant facial phenotypes. Where evidence was found of genetic overlap, we used bidirectional Mendelian randomization (MR) to test the hypothesis that genetic liability to nsCL/P is causally related to implicated facial phenotypes. Across 5,804 individuals of European ancestry from two studies, we found strong evidence, using PRS, of genetic overlap between nsCL/P and philtrum width; a 1 S.D. increase in nsCL/P PRS was associated with a 0.10 mm decrease in philtrum width (95% C.I. 0.054, 0.146; P = 2x10-5). Follow-up MR analyses supported a causal relationship; genetic variants for nsCL/P homogeneously cause decreased philtrum width. In addition to the primary analysis, we also identified two novel risk loci for philtrum width at 5q22.2 and 7p15.2 in our Genome-wide Association Study (GWAS) of 6,136 individuals. Our results support a liability threshold model of inheritance for nsCL/P, related to abnormalities in development of the philtrum.
  • Ligthart, S., Vaez, A., Võsa, U., Stathopoulou, M. G., De Vries, P. S., Prins, B. P., Van der Most, P. J., Tanaka, T., Naderi, E., Rose, L. M., Wu, Y., Karlsson, R., Barbalic, M., Lin, H., Pool, R., Zhu, G., Macé, A., Sidore, C., Trompet, S., Mangino, M. and 267 moreLigthart, S., Vaez, A., Võsa, U., Stathopoulou, M. G., De Vries, P. S., Prins, B. P., Van der Most, P. J., Tanaka, T., Naderi, E., Rose, L. M., Wu, Y., Karlsson, R., Barbalic, M., Lin, H., Pool, R., Zhu, G., Macé, A., Sidore, C., Trompet, S., Mangino, M., Sabater-Lleal, M., Kemp, J. P., Abbasi, A., Kacprowski, T., Verweij, N., Smith, A. V., Huang, T., Marzi, C., Feitosa, M. F., Lohman, K. K., Kleber, M. E., Milaneschi, Y., Mueller, C., Huq, M., Vlachopoulou, E., Lyytikäinen, L.-P., Oldmeadow, C., Deelen, J., Perola, M., Zhao, J. H., Feenstra, B., LifeLines Cohort Study, Amini, M., CHARGE Inflammation Working Group, Lahti, J., Schraut, K. E., Fornage, M., Suktitipat, B., Chen, W.-M., Li, X., Nutile, T., Malerba, G., Luan, J., Bak, T., Schork, N., Del Greco M., F., Thiering, E., Mahajan, A., Marioni, R. E., Mihailov, E., Eriksson, J., Ozel, A. B., Zhang, W., Nethander, M., Cheng, Y.-C., Aslibekyan, S., Ang, W., Gandin, I., Yengo, L., Portas, L., Kooperberg, C., Hofer, E., Rajan, K. B., Schurmann, C., Den Hollander, W., Ahluwalia, T. S., Zhao, J., Draisma, H. H. M., Ford, I., Timpson, N., Teumer, A., Huang, H., Wahl, S., Liu, Y., Huang, J., Uh, H.-W., Geller, F., Joshi, P. K., Yanek, L. R., Trabetti, E., Lehne, B., Vozzi, D., Verbanck, M., Biino, G., Saba, Y., Meulenbelt, I., O’Connell, J. R., Laakso, M., Giulianini, F., Magnusson, P. K. E., Ballantyne, C. M., Hottenga, J. J., Montgomery, G. W., Rivadineira, F., Rueedi, R., Steri, M., Herzig, K.-H., Stott, D. J., Menni, C., Franberg, M., St Pourcain, B., Felix, S. B., Pers, T. H., Bakker, S. J. L., Kraft, P., Peters, A., Vaidya, D., Delgado, G., Smit, J. H., Großmann, V., Sinisalo, J., Seppälä, I., Williams, S. R., Holliday, E. G., Moed, M., Langenberg, C., Räikkönen, K., Ding, J., Campbell, H., Sale, M. M., Chen, Y.-D.-I., James, A. L., Ruggiero, D., Soranzo, N., Hartman, C. A., Smith, E. N., Berenson, G. S., Fuchsberger, C., Hernandez, D., Tiesler, C. M. T., Giedraitis, V., Liewald, D., Fischer, K., Mellström, D., Larsson, A., Wang, Y., Scott, W. R., Lorentzon, M., Beilby, J., Ryan, K. A., Pennell, C. E., Vuckovic, D., Balkau, B., Concas, M. P., Schmidt, R., Mendes de Leon, C. F., Bottinger, E. P., Kloppenburg, M., Paternoster, L., Boehnke, M., Musk, A. W., Willemsen, G., Evans, D. M., Madden, P. A. F., Kähönen, M., Kutalik, Z., Zoledziewska, M., Karhunen, V., Kritchevsky, S. B., Sattar, N., Lachance, G., Clarke, R., Harris, T. B., Raitakari, O. T., Attia, J. R., Van Heemst, D., Kajantie, E., Sorice, R., Gambaro, G., Scott, R. A., Hicks, A. A., Ferrucci, L., Standl, M., Lindgren, C. M., Starr, J. M., Karlsson, M., Lind, L., Li, J. Z., Chambers, J. C., Mori, T. A., De Geus, E. J. C. N., Heath, A. C., Martin, N. G., Auvinen, J., Buckley, B. M., De Craen, A. J. M., Waldenberger, M., Strauch, K., Meitinger, T., Scott, R. J., McEvoy, M., Beekman, M., Bombieri, C., Ridker, P. M., Mohlke, K. L., Pedersen, N. L., Morrison, A. C., Boomsma, D. I., Whitfield, J. B., Strachan, D. P., Hofman, A., Vollenweider, P., Cucca, F., Jarvelin, M.-R., Jukema, J. W., Spector, T. D., Hamsten, A., Zeller, T., Uitterlinden, A. G., Nauck, M., Gudnason, V., Qi, L., Grallert, H., Borecki, I. B., Rotter, J. I., März, W., Wild, P. S., Lokki, M.-L., Boyle, M., Salomaa, V., Melbye, M., Eriksson, J. G., Wilson, J. F., Penninx, B. W. J. H., Becker, D. M., Worrall, B. B., Gibson, G., Krauss, R. M., Ciullo, M., Zaza, G., Wareham, N. J., Oldehinkel, A. J., Palmer, L. J., Murray, S. S., Pramstaller, P. P., Bandinelli, S., Heinrich, J., Ingelsson, E., Deary, I. J., Ma¨gi, R., Vandenput, L., Van der Harst, P., Desch, K. C., Kooner, J. S., Ohlsson, C., Hayward, C., Lehtima¨ki, T., Shuldiner, A. R., Arnett, D. K., Beilin, L. J., Robino, A., Froguel, P., Pirastu, M., Jess, T., Koenig, W., Loos, R. J. F., Evans, D. A., Schmidt, H., Smith, G. D., Slagboom, P. E., Eiriksdottir, G., Morris, A. P., Psaty, B. M., Tracy, R. P., Nolte, I. M., Boerwinkle, E., Visvikis-Siest, S., Reiner, A. P., Gross, M., Bis, J. C., Franke, L., Franco, O. H., Benjamin, E. J., Chasman, D. I., Dupuis, J., Snieder, H., Dehghan, A., & Alizadeh, B. Z. (2018). Genome Analyses of >200,000 Individuals Identify 58 Loci for Chronic Inflammation and Highlight Pathways that Link Inflammation and Complex Disorders. The American Journal of Human Genetics, 103(5), 691-706. doi:10.1016/j.ajhg.2018.09.009.

    Abstract

    C-reactive protein (CRP) is a sensitive biomarker of chronic low-grade inflammation and is associated with multiple complex diseases. The genetic determinants of chronic inflammation remain largely unknown, and the causal role of CRP in several clinical outcomes is debated. We performed two genome-wide association studies (GWASs), on HapMap and 1000 Genomes imputed data, of circulating amounts of CRP by using data from 88 studies comprising 204,402 European individuals. Additionally, we performed in silico functional analyses and Mendelian randomization analyses with several clinical outcomes. The GWAS meta-analyses of CRP revealed 58 distinct genetic loci (p < 5 × 10−8). After adjustment for body mass index in the regression analysis, the associations at all except three loci remained. The lead variants at the distinct loci explained up to 7.0% of the variance in circulating amounts of CRP. We identified 66 gene sets that were organized in two substantially correlated clusters, one mainly composed of immune pathways and the other characterized by metabolic pathways in the liver. Mendelian randomization analyses revealed a causal protective effect of CRP on schizophrenia and a risk-increasing effect on bipolar disorder. Our findings provide further insights into the biology of inflammation and could lead to interventions for treating inflammation and its clinical consequences.
  • Mandy, W., Pellicano, L., St Pourcain, B., Skuse, D., & Heron, J. (2018). The development of autistic social traits across childhood and adolescence in males and females. The Journal of Child Psychology and Psychiatry, 59(11), 1143-1151. doi:10.1111/jcpp.12913.

    Abstract

    Background Autism is a dimensional condition, representing the extreme end of a continuum of social competence that extends throughout the general population. Currently, little is known about how autistic social traits (ASTs), measured across the full spectrum of severity, develop during childhood and adolescence, including whether there are developmental differences between boys and girls. Therefore, we sought to chart the trajectories of ASTs in the general population across childhood and adolescence, with a focus on gender differences. Methods Participants were 9,744 males (n = 4,784) and females (n = 4,960) from ALSPAC, a UK birth cohort study. ASTs were assessed when participants were aged 7, 10, 13 and 16 years, using the parent‐report Social Communication Disorders Checklist. Data were modelled using latent growth curve analysis. Results Developmental trajectories of males and females were nonlinear, showing a decline from 7 to 10 years, followed by an increase between 10 and 16 years. At 7 years, males had higher levels of ASTs than females (mean raw score difference = 0.88, 95% CI [.72, 1.04]), and were more likely (odds ratio [OR] = 1.99; 95% CI, 1.82, 2.16) to score in the clinical range on the SCDC. By 16 years this gender difference had disappeared: males and females had, on average, similar levels of ASTs (mean difference = 0.00, 95% CI [−0.19, 0.19]) and were equally likely to score in the SCDC's clinical range (OR = 0.91, 95% CI, 0.73, 1.10). This was the result of an increase in females’ ASTs between 10 and 16 years. Conclusions There are gender‐specific trajectories of autistic social impairment, with females more likely than males to experience an escalation of ASTs during early‐ and midadolescence. It remains to be discovered whether the observed female adolescent increase in ASTs represents the genuine late onset of social difficulties or earlier, subtle, pre‐existing difficulties becoming more obvious.

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  • St Pourcain, B., Robinson, E. B., Anttila, V., Sullivan, B. B., Maller, J., Golding, J., Skuse, D., Ring, S., Evans, D. M., Zammit, S., Fisher, S. E., Neale, B. M., Anney, R., Ripke, S., Hollegaard, M. V., Werge, T., iPSYCH-SSI-Broad Autism Group, Ronald, A., Grove, J., Hougaard, D. M., Børglum, A. D. and 3 moreSt Pourcain, B., Robinson, E. B., Anttila, V., Sullivan, B. B., Maller, J., Golding, J., Skuse, D., Ring, S., Evans, D. M., Zammit, S., Fisher, S. E., Neale, B. M., Anney, R., Ripke, S., Hollegaard, M. V., Werge, T., iPSYCH-SSI-Broad Autism Group, Ronald, A., Grove, J., Hougaard, D. M., Børglum, A. D., Mortensen, P. B., Daly, M., & Davey Smith, G. (2018). ASD and schizophrenia show distinct developmental profiles in common genetic overlap with population-based social-communication difficulties. Molecular Psychiatry, 23, 263-270. doi:10.1038/mp.2016.198.

    Abstract

    Difficulties in social communication are part of the phenotypic overlap between autism spectrum disorders (ASD) and schizophrenia. Both conditions follow, however, distinct developmental patterns. Symptoms of ASD typically occur during early childhood, whereas most symptoms characteristic of schizophrenia do not appear before early adulthood. We investigated whether overlap in common genetic in fluences between these clinical conditions and impairments in social communication depends on the developmental stage of the assessed trait. Social communication difficulties were measured in typically-developing youth (Avon Longitudinal Study of Parents and Children,N⩽5553, longitudinal assessments at 8, 11, 14 and 17 years) using the Social Communication Disorder Checklist. Data on clinical ASD (PGC-ASD: 5305 cases, 5305 pseudo-controls; iPSYCH-ASD: 7783 cases, 11 359 controls) and schizophrenia (PGC-SCZ2: 34 241 cases, 45 604 controls, 1235 trios) were either obtained through the Psychiatric Genomics Consortium (PGC) or the Danish iPSYCH project. Overlap in genetic in fluences between ASD and social communication difficulties during development decreased with age, both in the PGC-ASD and the iPSYCH-ASD sample. Genetic overlap between schizophrenia and social communication difficulties, by contrast, persisted across age, as observed within two independent PGC-SCZ2 subsamples, and showed an increase in magnitude for traits assessed during later adolescence. ASD- and schizophrenia-related polygenic effects were unrelated to each other and changes in trait-disorder links reflect the heterogeneity of genetic factors in fluencing social communication difficulties during childhood versus later adolescence. Thus, both clinical ASD and schizophrenia share some genetic in fluences with impairments in social communication, but reveal distinct developmental profiles in their genetic links, consistent with the onset of clinical symptoms

    Additional information

    mp2016198x1.docx
  • St Pourcain, B., Eaves, L. J., Ring, S. M., Fisher, S. E., Medland, S., Evans, D. M., & Smith, G. D. (2018). Developmental changes within the genetic architecture of social communication behaviour: A multivariate study of genetic variance in unrelated individuals. Biological Psychiatry, 83(7), 598-606. doi:10.1016/j.biopsych.2017.09.020.

    Abstract

    Background: Recent analyses of trait-disorder overlap suggest that psychiatric dimensions may relate to distinct sets of genes that exert their maximum influence during different periods of development. This includes analyses of social-communciation difficulties that share, depending on their developmental stage, stronger genetic links with either Autism Spectrum Disorder or schizophrenia. Here we developed a multivariate analysis framework in unrelated individuals to model directly the developmental profile of genetic influences contributing to complex traits, such as social-communication difficulties, during a ~10-year period spanning childhood and adolescence. Methods: Longitudinally assessed quantitative social-communication problems (N ≤ 5,551) were studied in participants from a UK birth cohort (ALSPAC, 8 to 17 years). Using standardised measures, genetic architectures were investigated with novel multivariate genetic-relationship-matrix structural equation models (GSEM) incorporating whole-genome genotyping information. Analogous to twin research, GSEM included Cholesky decomposition, common pathway and independent pathway models. Results: A 2-factor Cholesky decomposition model described the data best. One genetic factor was common to SCDC measures across development, the other accounted for independent variation at 11 years and later, consistent with distinct developmental profiles in trait-disorder overlap. Importantly, genetic factors operating at 8 years explained only ~50% of the genetic variation at 17 years. Conclusion: Using latent factor models, we identified developmental changes in the genetic architecture of social-communication difficulties that enhance the understanding of ASD and schizophrenia-related dimensions. More generally, GSEM present a framework for modelling shared genetic aetiologies between phenotypes and can provide prior information with respect to patterns and continuity of trait-disorder overlap
  • Klein, M., Van Donkelaar, M., Verhoef, E., & Franke, B. (2017). Imaging genetics in neurodevelopmental psychopathology. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 174(5), 485-537. doi:10.1002/ajmg.b.32542.

    Abstract

    Neurodevelopmental disorders are defined by highly heritable problems during development and brain growth. Attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASDs), and intellectual disability (ID) are frequent neurodevelopmental disorders, with common comorbidity among them. Imaging genetics studies on the role of disease-linked genetic variants on brain structure and function have been performed to unravel the etiology of these disorders. Here, we reviewed imaging genetics literature on these disorders attempting to understand the mechanisms of individual disorders and their clinical overlap. For ADHD and ASD, we selected replicated candidate genes implicated through common genetic variants. For ID, which is mainly caused by rare variants, we included genes for relatively frequent forms of ID occurring comorbid with ADHD or ASD. We reviewed case-control studies and studies of risk variants in healthy individuals. Imaging genetics studies for ADHD were retrieved for SLC6A3/DAT1, DRD2, DRD4, NOS1, and SLC6A4/5HTT. For ASD, studies on CNTNAP2, MET, OXTR, and SLC6A4/5HTT were found. For ID, we reviewed the genes FMR1, TSC1 and TSC2, NF1, and MECP2. Alterations in brain volume, activity, and connectivity were observed. Several findings were consistent across studies, implicating, for example, SLC6A4/5HTT in brain activation and functional connectivity related to emotion regulation. However, many studies had small sample sizes, and hypothesis-based, brain region-specific studies were common. Results from available studies confirm that imaging genetics can provide insight into the link between genes, disease-related behavior, and the brain. However, the field is still in its early stages, and conclusions about shared mechanisms cannot yet be drawn.
  • 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.
  • Ho, Y. Y. W., Evans, D. M., Montgomery, G. W., Henders, A. K., Kemp, J. P., Timpson, N. J., St Pourcain, B., Heath, A. C., Madden, P. A. F., Loesch, D. Z., McNevin, D., Daniel, R., Davey-Smith, G., Martin, N. G., & Medland, S. E. (2016). Common genetic variants influence whorls in fingerprint patterns. Journal of Investigative Dermatology, 136(4), 859-862. doi:10.1016/j.jid.2015.10.062.
  • Fan, Q., Guo, X., Tideman, J. W. L., Williams, K. M., Yazar, S., Hosseini, S. M., Howe, L. D., St Pourcain, B., Evans, D. M., Timpson, N. J., McMahon, G., Hysi, P. G., Krapohl, E., Wang, Y. X., Jonas, J. B., Baird, P. N., Wang, J. J., Cheng, C. Y., Teo, Y. Y., Wong, T. Y. and 17 moreFan, Q., Guo, X., Tideman, J. W. L., Williams, K. M., Yazar, S., Hosseini, S. M., Howe, L. D., St Pourcain, B., Evans, D. M., Timpson, N. J., McMahon, G., Hysi, P. G., Krapohl, E., Wang, Y. X., Jonas, J. B., Baird, P. N., Wang, J. J., Cheng, C. Y., Teo, Y. Y., Wong, T. Y., Ding, X., Wojciechowski, R., Young, T. L., Parssinen, O., Oexle, K., Pfeiffer, N., Bailey-Wilson, J. E., Paterson, A. D., Klaver, C. C. W., Plomin, R., Hammond, C. J., Mackey, D. A., He, M. G., Saw, S. M., Williams, C., Guggenheim, J. A., & Cream, C. (2016). Childhood gene-environment interactions and age-dependent effects of genetic variants associated with refractive error and myopia: The CREAM Consortium. Scientific Reports, 6: 25853. doi:10.1038/srep25853.

    Abstract

    Myopia, currently at epidemic levels in East Asia, is a leading cause of untreatable visual impairment. Genome-wide association studies (GWAS) in adults have identified 39 loci associated with refractive error and myopia. Here, the age-of-onset of association between genetic variants at these 39 loci and refractive error was investigated in 5200 children assessed longitudinally across ages 7-15 years, along with gene-environment interactions involving the major environmental risk-factors, nearwork and time outdoors. Specific variants could be categorized as showing evidence of: (a) early-onset effects remaining stable through childhood, (b) early-onset effects that progressed further with increasing age, or (c) onset later in childhood (N = 10, 5 and 11 variants, respectively). A genetic risk score (GRS) for all 39 variants explained 0.6% (P = 6.6E-08) and 2.3% (P = 6.9E-21) of the variance in refractive error at ages 7 and 15, respectively, supporting increased effects from these genetic variants at older ages. Replication in multi-ancestry samples (combined N = 5599) yielded evidence of childhood onset for 6 of 12 variants present in both Asians and Europeans. There was no indication that variant or GRS effects altered depending on time outdoors, however 5 variants showed nominal evidence of interactions with nearwork (top variant, rs7829127 in ZMAT4; P = 6.3E-04).

    Additional information

    srep25853-s1.pdf
  • Fan, Q., Verhoeven, V. J., Wojciechowski, R., Barathi, V. A., Hysi, P. G., Guggenheim, J. A., Höhn, R., Vitart, V., Khawaja, A. P., Yamashiro, K., Hosseini, S. M., Lehtimäki, T., Lu, Y., Haller, T., Xie, J., Delcourt, C., Pirastu, M., Wedenoja, J., Gharahkhani, P., Venturini, C. and 83 moreFan, Q., Verhoeven, V. J., Wojciechowski, R., Barathi, V. A., Hysi, P. G., Guggenheim, J. A., Höhn, R., Vitart, V., Khawaja, A. P., Yamashiro, K., Hosseini, S. M., Lehtimäki, T., Lu, Y., Haller, T., Xie, J., Delcourt, C., Pirastu, M., Wedenoja, J., Gharahkhani, P., Venturini, C., Miyake, M., Hewitt, A. W., Guo, X., Mazur, J., Huffman, J. E., Williams, K. M., Polasek, O., Campbell, H., Rudan, I., Vatavuk, Z., Wilson, J. F., Joshi, P. K., McMahon, G., St Pourcain, B., Evans, D. M., Simpson, C. L., Schwantes-An, T.-H., Igo, R. P., Mirshahi, A., Cougnard-Gregoire, A., Bellenguez, C., Blettner, M., Raitakari, O., Kähönen, M., Seppälä, I., Zeller, T., Meitinger, T., Ried, J. S., Gieger, C., Portas, L., Van Leeuwen, E. M., Amin, N., Uitterlinden, A. G., Rivadeneira, F., Hofman, A., Vingerling, J. R., Wang, Y. X., Wang, X., Boh, E.-T.-H., Ikram, M. K., Sabanayagam, C., Gupta, P., Tan, V., Zhou, L., Ho, C. E., Lim, W., Beuerman, R. W., Siantar, R., Tai, E.-S., Vithana, E., Mihailov, E., Khor, C.-C., Hayward, C., Luben, R. N., Foster, P. J., Klein, B. E., Klein, R., Wong, H.-S., Mitchell, P., Metspalu, A., Aung, T., Young, T. L., He, M., Pärssinen, O., Van Duijn, C. M., Wang, J. J., Williams, C., Jonas, J. B., Teo, Y.-Y., Mackey, D. A., Oexle, K., Yoshimura, N., Paterson, A. D., Pfeiffer, N., Wong, T.-Y., Baird, P. N., Stambolian, D., Bailey-Wilson, J. E., Cheng, C.-Y., Hammond, C. J., Klaver, C. C., Saw, S.-M., & Consortium for Refractive Error and Myopia (CREAM) (2016). Meta-analysis of gene–environment-wide association scans accounting for education level identifies additional loci for refractive error. Nature Communications, 7: 11008. doi:10.1038/ncomms11008.

    Abstract

    Myopia is the most common human eye disorder and it results from complex genetic and environmental causes. The rapidly increasing prevalence of myopia poses a major public health challenge. Here, the CREAM consortium performs a joint meta-analysis to test single-nucleotide polymorphism (SNP) main effects and SNP × education interaction effects on refractive error in 40,036 adults from 25 studies of European ancestry and 10,315 adults from 9 studies of Asian ancestry. In European ancestry individuals, we identify six novel loci (FAM150B-ACP1, LINC00340, FBN1, DIS3L-MAP2K1, ARID2-SNAT1 and SLC14A2) associated with refractive error. In Asian populations, three genome-wide significant loci AREG, GABRR1 and PDE10A also exhibit strong interactions with education (P<8.5 × 10−5), whereas the interactions are less evident in Europeans. The discovery of these loci represents an important advance in understanding how gene and environment interactions contribute to the heterogeneity of myopia

    Additional information

    Fan_etal_2016sup.pdf
  • Hugh-Jones, D., Verweij, K. J. H., St Pourcain, B., & Abdellaoui, A. (2016). Assortative mating on educational attainment leads to genetic spousal resemblance for causal alleles. Intelligence, 59, 103-108. doi:10.1016/j.intell.2016.08.005.

    Abstract

    We examined whether assortative mating for educational attainment (“like marries like”) can be detected in the genomes of ~ 1600 UK spouse pairs of European descent. Assortative mating on heritable traits like educational attainment increases the genetic variance and heritability of the trait in the population, which may increase social inequalities. We test for genetic assortative mating in the UK on educational attainment, a phenotype that is indicative of socio-economic status and has shown substantial levels of assortative mating. We use genome-wide allelic effect sizes from a large genome-wide association study on educational attainment (N ~ 300 k) to create polygenic scores that are predictive of educational attainment in our independent sample (r = 0.23, p < 2 × 10− 16). The polygenic scores significantly predict partners' educational outcome (r = 0.14, p = 4 × 10− 8 and r = 0.19, p = 2 × 10− 14, for prediction from males to females and vice versa, respectively), and are themselves significantly correlated between spouses (r = 0.11, p = 7 × 10− 6). Our findings provide molecular genetic evidence for genetic assortative mating on education in the UK
  • Middeldorp, C. M., Hammerschlag, A. R., Ouwens, K. G., Groen-Blokhuis, M. M., St Pourcain, B., Greven, C. U., Pappa, I., Tiesler, C. M. T., Ang, W., Nolte, I. M., Vilor-Tejedor, N., Bacelis, J., Ebejer, J. L., Zhao, H., Davies, G. E., Ehli, E. A., Evans, D. M., Fedko, I. O., Guxens, M., Hottenga, J.-J. and 31 moreMiddeldorp, C. M., Hammerschlag, A. R., Ouwens, K. G., Groen-Blokhuis, M. M., St Pourcain, B., Greven, C. U., Pappa, I., Tiesler, C. M. T., Ang, W., Nolte, I. M., Vilor-Tejedor, N., Bacelis, J., Ebejer, J. L., Zhao, H., Davies, G. E., Ehli, E. A., Evans, D. M., Fedko, I. O., Guxens, M., Hottenga, J.-J., Hudziak, J. J., Jugessur, A., Kemp, J. P., Krapohl, E., Martin, N. G., Murcia, M., Myhre, R., Ormel, J., Ring, S. M., Standl, M., Stergiakouli, E., Stoltenberg, C., Thiering, E., Timpson, N. J., Trzaskowski, M., van der Most, P. J., Wang, C., EArly Genetics and Lifecourse Epidemiology (EAGLE) Consortium, Psychiatric Genomics Consortium ADHD Working Group, Nyholt, D. R., Medland, S. E., Neale, B., Jacobsson, B., Sunyer, J., Hartman, C. A., Whitehouse, A. J. O., Pennell, C. E., Heinrich, J., Plomin, R., Smith, G. D., Tiemeier, H., Posthuma, D., & Boomsma, D. I. (2016). A Genome-Wide Association Meta-Analysis of Attention-Deficit/Hyperactivity Disorder Symptoms in Population-Based Paediatric Cohorts. Journal of the American Academy of Child & Adolescent Psychiatry, 55(10), 896-905. doi:10.1016/j.jaac.2016.05.025.

    Abstract

    Objective To elucidate the influence of common genetic variants on childhood attention-deficit/hyperactivity disorder (ADHD) symptoms, to identify genetic variants that explain its high heritability, and to investigate the genetic overlap of ADHD symptom scores with ADHD diagnosis. Method Within the EArly Genetics and Lifecourse Epidemiology (EAGLE) consortium, genome-wide single nucleotide polymorphisms (SNPs) and ADHD symptom scores were available for 17,666 children (< 13 years) from nine population-based cohorts. SNP-based heritability was estimated in data from the three largest cohorts. Meta-analysis based on genome-wide association (GWA) analyses with SNPs was followed by gene-based association tests, and the overlap in results with a meta-analysis in the Psychiatric Genomics Consortium (PGC) case-control ADHD study was investigated. Results SNP-based heritability ranged from 5% to 34%, indicating that variation in common genetic variants influences ADHD symptom scores. The meta-analysis did not detect genome-wide significant SNPs, but three genes, lying close to each other with SNPs in high linkage disequilibrium (LD), showed a gene-wide significant association (p values between 1.46×10-6 and 2.66×10-6). One gene, WASL, is involved in neuronal development. Both SNP- and gene-based analyses indicated overlap with the PGC meta-analysis results with the genetic correlation estimated at 0.96. Conclusion The SNP-based heritability for ADHD symptom scores indicates a polygenic architecture and genes involved in neurite outgrowth are possibly involved. Continuous and dichotomous measures of ADHD appear to assess a genetically common phenotype. A next step is to combine data from population-based and case-control cohorts in genetic association studies to increase sample size and improve statistical power for identifying genetic variants.
  • Okbay, A., Beauchamp, J. P., Fontana, M. A., Lee, J. J., Pers, T. H., Rietveld, C. A., Turley, P., Chen, G. B., Emilsson, V., Meddens, S. F. W., Oskarsson, S., Pickrell, J. K., Thom, K., Timshel, P., De Vlaming, R., Abdellaoui, A., Ahluwalia, T. S., Bacelis, J., Baumbach, C., Bjornsdottir, G. and 236 moreOkbay, A., Beauchamp, J. P., Fontana, M. A., Lee, J. J., Pers, T. H., Rietveld, C. A., Turley, P., Chen, G. B., Emilsson, V., Meddens, S. F. W., Oskarsson, S., Pickrell, J. K., Thom, K., Timshel, P., De Vlaming, R., Abdellaoui, A., Ahluwalia, T. S., Bacelis, J., Baumbach, C., Bjornsdottir, G., Brandsma, J., Pina Concas, M., Derringer, J., Furlotte, N. A., Galesloot, T. E., Girotto, G., Gupta, R., Hall, L. M., Harris, S. E., Hofer, E., Horikoshi, M., Huffman, J. E., Kaasik, K., Kalafati, I. P., Karlsson, R., Kong, A., Lahti, J., Lee, S. J. V. D., DeLeeuw, C., Lind, P. A., Lindgren, K.-.-O., Liu, T., Mangino, M., Marten, J., Mihailov, E., Miller, M. B., Van der Most, P. J., Oldmeadow, C., Payton, A., Pervjakova, N., Peyrot, W. J., Qian, Y., Raitakari, O., Rueedi, R., Salvi, E., Schmidt, B., Schraut, K. E., Shi, J., Smith, A. V., Poot, R. A., St Pourcain, B., Teumer, A., Thorleifsson, G., Verweij, N., Vuckovic, D., Wellmann, J., Westra, H.-.-J., Yang, J., Zhao, W., Zhu, Z., Alizadeh, B. Z., Amin, N., Bakshi, A., Baumeister, S. E., Biino, G., Bønnelykke, K., Boyle, P. A., Campbell, H., Cappuccio, F. P., Davies, G., De Neve, J.-.-E., Deloukas, P., Demuth, I., Ding, J., Eibich, P., Eisele, L., Eklund, N., Evans, D. M., Faul, J. D., Feitosa, M. F., Forstner, A. J., Gandin, I., Gunnarsson, B., Halldórsson, B. V., Harris, T. B., Heath, A. C., Hocking, L. J., Holliday, E. G., Homuth, G., Horan, M. A., Hottenga, J.-.-J., De Jager, P. L., Joshi, P. K., Jugessur, A., Kaakinen, M. A., Kähönen, M., Kanoni, S., Keltigangas-Järvinen, L., Kiemeney, L. A. L. M., Kolcic, I., Koskinen, S., Kraja, A. T., Kroh, M., Kutalik, Z., Latvala, A., Launer, L. J., Lebreton, M. P., Levinson, D. F., Lichtenstein, P., Lichtner, P., Liewald, D. C. M., Cohert Study, L., Loukola, A., Madden, P. A., Mägi, R., Mäki-Opas, T., Marioni, R. E., Marques-Vidal, P., Meddens, G. A., McMahon, G., Meisinger, C., Meitinger, T., Milaneschi, Y., Milani, L., Montgomery, G. W., Myhre, R., Nelson, C. P., Nyholt, D. R., Ollier, W. E. R., Palotie, A., Paternoster, L., Pedersen, N. L., Petrovic, K. E., Porteous, D. J., Räikkönen, K., Ring, S. M., Robino, A., Rostapshova, O., Rudan, I., Rustichini, A., Salomaa, V., Sanders, A. R., Sarin, A.-.-P., Schmidt, H., Scott, R. J., Smith, B. H., Smith, J. A., Staessen, J. A., Steinhagen-Thiessen, E., Strauch, K., Terracciano, A., Tobin, M. D., Ulivi, S., Vaccargiu, S., Quaye, L., Van Rooij, F. J. A., Venturini, C., Vinkhuyzen, A. A. E., Völker, U., Völzke, H., Vonk, J. M., Vozzi, D., Waage, J., Ware, E. B., Willemsen, G., Attia, J. R., Bennett, D. A., Berger, K., Bertram, L., Bisgaard, H., Boomsma, D. I., Borecki, I. B., Bültmann, U., Chabris, C. F., Cucca, F., Cusi, D., Deary, I. J., Dedoussis, G. V., Van Duijn, C. M., Eriksson, J. G., Franke, B., Franke, L., Gasparini, P., Gejman, P. V., Gieger, C., Grabe, H.-.-J., Gratten, J., Groenen, P. J. F., Gudnason, V., Van der Harst, P., Hayward, C., Hinds, D. A., Hoffmann, W., Hyppönen, E., Iacono, W. G., Jacobsson, B., Järvelin, M.-.-R., Jöckel, K.-.-H., Kaprio, J., Kardia, S. L. R., Lehtimäki, T., Lehrer, S. F., Magnusson, P. K. E., Martin, N. G., McGue, M., Metspalu, A., Pendleton, N., Penninx, B. W. J. H., Perola, M., Pirastu, N., Pirastu, M., Polasek, O., Posthuma, D., Power, C., Province, M. A., Samani, N. J., Schlessinger, D., Schmidt, R., Sørensen, T. I. A., Spector, T. D., Stefansson, K., Thorsteinsdottir, U., Thurik, A. R., Timpson, N. J., Tiemeier, H., Tung, J. Y., Uitterlinden, A. G., Vitart, V., Vollenweider, P., Weir, D. R., Wilson, J. F., Wright, A. F., Conley, D. C., Krueger, R. F., Davey Smith, G., Hofman, A., Laibson, D. I., Medland, S. E., Meyer, M. N., Yang, J., Johannesson, M., Visscher, P. M., Esko, T., Koellinger, P. D., Cesarini, D., & Benjamin, D. J. (2016). Genome-wide association study identifies 74 loci associated with educational attainment. Nature, 533, 539-542. doi:10.1038/nature17671.

    Abstract

    Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases
  • Pappa, I., St Pourcain, B., Benke, K., Cavadino, A., Hakulinen, C., Nivard, M. G., Nolte, I. M., Tiesler, C. M. T., Bakermans-Kranenburg, M. J., Davies, G. E., Evans, D. M., Geoffroy, M.-C., Grallert, H., Groen-Blokhuis, M. M., Hudziak, J. J., Kemp, J. P., Keltikangas-Järvinen, L., McMahon, G., Mileva-Seitz, V. R., Motazedi, E. and 23 morePappa, I., St Pourcain, B., Benke, K., Cavadino, A., Hakulinen, C., Nivard, M. G., Nolte, I. M., Tiesler, C. M. T., Bakermans-Kranenburg, M. J., Davies, G. E., Evans, D. M., Geoffroy, M.-C., Grallert, H., Groen-Blokhuis, M. M., Hudziak, J. J., Kemp, J. P., Keltikangas-Järvinen, L., McMahon, G., Mileva-Seitz, V. R., Motazedi, E., Power, C., Raitakari, O. T., Ring, S. M., Rivadeneira, F., Rodriguez, A., Scheet, P. A., Seppälä, I., Snieder, H., Standl, M., Thiering, E., Timpson, N. J., Veenstra, R., Velders, F. P., Whitehouse, A. J. O., Smith, G. D., Heinrich, J., Hypponen, E., Lehtimäki, T., Middeldorp, C. M., Oldehinkel, A. J., Pennell, C. E., Boomsma, D. I., & Tiemeier, H. (2016). A genome-wide approach to children's aggressive behavior: The EAGLE consortium. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 171(5), 562-572. doi:10.1002/ajmg.b.32333.

    Abstract

    Individual differences in aggressive behavior emerge in early childhood and predict persisting behavioral problems and disorders. Studies of antisocial and severe aggression in adulthood indicate substantial underlying biology. However, little attention has been given to genome-wide approaches of aggressive behavior in children. We analyzed data from nine population-based studies and assessed aggressive behavior using well-validated parent-reported questionnaires. This is the largest sample exploring children's aggressive behavior to date (N = 18,988), with measures in two developmental stages (N = 15,668 early childhood and N = 16,311 middle childhood/early adolescence). First, we estimated the additive genetic variance of children's aggressive behavior based on genome-wide SNP information, using genome-wide complex trait analysis (GCTA). Second, genetic associations within each study were assessed using a quasi-Poisson regression approach, capturing the highly right-skewed distribution of aggressive behavior. Third, we performed meta-analyses of genome-wide associations for both the total age-mixed sample and the two developmental stages. Finally, we performed a gene-based test using the summary statistics of the total sample. GCTA quantified variance tagged by common SNPs (10–54%). The meta-analysis of the total sample identified one region in chromosome 2 (2p12) at near genome-wide significance (top SNP rs11126630, P = 5.30 × 10−8). The separate meta-analyses of the two developmental stages revealed suggestive evidence of association at the same locus. The gene-based analysis indicated association of variation within AVPR1A with aggressive behavior. We conclude that common variants at 2p12 show suggestive evidence for association with childhood aggression. Replication of these initial findings is needed, and further studies should clarify its biological meaning.
  • Robinson, E. B., St Pourcain, B., Anttila, V., Kosmicki, J. A., Bulik-Sullivan, B., Grove, J., Maller, J., Samocha, K. E., Sanders, S. J., Ripke, S., Martin, J., Hollegaard, M. V., Werge, T., Hougaard, D. M., i Psych- S. S. I. Broad Autism Group, Neale, B. M., Evans, D. M., Skuse, D., Mortensen, P. B., Borglum, A. D., Ronald, A. and 2 moreRobinson, E. B., St Pourcain, B., Anttila, V., Kosmicki, J. A., Bulik-Sullivan, B., Grove, J., Maller, J., Samocha, K. E., Sanders, S. J., Ripke, S., Martin, J., Hollegaard, M. V., Werge, T., Hougaard, D. M., i Psych- S. S. I. Broad Autism Group, Neale, B. M., Evans, D. M., Skuse, D., Mortensen, P. B., Borglum, A. D., Ronald, A., Smith, G. D., & Daly, M. J. (2016). Genetic risk for autism spectrum disorders and neuropsychiatric variation in the general population. Nature Genetics, 48, 552-555. doi:10.1038/ng.3529.

    Abstract

    Almost all genetic risk factors for autism spectrum disorders (ASDs) can be found in the general population, but the effects of this risk are unclear in people not ascertained for neuropsychiatric symptoms. Using several large ASD consortium and population-based resources (total n > 38,000), we find genome-wide genetic links between ASDs and typical variation in social behavior and adaptive functioning. This finding is evidenced through both LD score correlation and de novo variant analysis, indicating that multiple types of genetic risk for ASDs influence a continuum of behavioral and developmental traits, the severe tail of which can result in diagnosis with an ASD or other neuropsychiatric disorder. A continuum model should inform the design and interpretation of studies of neuropsychiatric disease biology.

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  • Stock, N. M., Humphries, K., St Pourcain, B., Bailey, M., Persson, M., Ho, K. M., Ring, S., Marsh, C., Albery, L., Rumsey, N., & Sandy, J. (2016). Opportunities and Challenges in Establishing a Cohort Study: An Example From Cleft Lip/Palate Research in the United Kingdom. Cleft Palate-Craniofacial Journal, (3), 317-325. doi:10.1597/14-306.

    Abstract

    Full text and MPG-specific services(opens in a new window)| Export | Download | Add to List | More... Cleft Palate-Craniofacial Journal Volume 53, Issue 3, May 2016, Pages 317-325 Opportunities and challenges in establishing a cohort study: An example from cleft lip/palate research in the United Kingdom (Article) Stock, N.M.a , Humphries, K.b, St. Pourcain, B.b, Bailey, M.b, Persson, M.a, Ho, K.M.b, Ring, S.b, Marsh, C.c, Albery, L.c, Rumsey, N.a, Sandy, J.b a Centre for Appearance Research, University of the West of England, Coldharbour Lane, Bristol, United Kingdom b Faculty of Medicine and Dentistry, University of Bristol, United Kingdom c South West Cleft Service, University Hospitals Bristol NHS Foundation Trust, United Kingdom Hide additional affiliations View references (32) Abstract Background: Cleft lip and/or palate (CL/P) is one of the most common birth conditions in the world, but little is known about its causes. Professional opinion remains divided as to which treatments may be the most beneficial for patients with CL/P, and the factors that contribute to psychological adjustment are poorly understood. The use of different methodological approaches and tools plays a key role in hampering efforts to address discrepancies within the evidence base. A new UK-wide program of research, The Cleft Collective, was established to combat many of these methodological challenges and to address some of the key research questions important to all CL/P stakeholders. Objective: To describe the establishment of CL/P cohort studies in the United Kingdom and to consider the many opportunities this resource will generate. Results: To date, protocols have been developed and implemented within most UK cleft teams. Biological samples, environmental information, and data pertaining to parental psychological well-being and child development are being collected successfully. Recruitment is currently on track to meet the ambitious target of approximately 9800 individuals from just more than 3000 families. Conclusions: The Cleft Collective cohort studies represent a significant step forward for research in the field of CL/P. The data collected will form a comprehensive resource of information about individuals with CL/P and their families. This resource will provide the basis for many future projects and collaborations, both in the United Kingdom and around the world.
  • van den Berg, S. M., de Moor, M. H. M., Verweij, K. J. H., Krueger, R. F., Luciano, M., Arias Vasquez, A., Matteson, L. K., Derringer, J., Esko, T., Amin, N. F., Gordon, S. D., Hansell, N. K., Hart, A. B., Seppälä, I., Huffman, J. E., Konte, B., Lahti, J., Lee, M., Miller, M., Nutile, T. and 101 morevan den Berg, S. M., de Moor, M. H. M., Verweij, K. J. H., Krueger, R. F., Luciano, M., Arias Vasquez, A., Matteson, L. K., Derringer, J., Esko, T., Amin, N. F., Gordon, S. D., Hansell, N. K., Hart, A. B., Seppälä, I., Huffman, J. E., Konte, B., Lahti, J., Lee, M., Miller, M., Nutile, T., Tanaka, T., Teumer, A., Viktorin, A., Wedenoja, J., Abdellaoui, A., Abecasis, G. R., Adkins, D. E., Agrawal, A., Allik, J., Appel, K., Bigdeli, T. B., Busonero, F., Campbell, H., Costa, P., Smith, G. D., Davies, G., de Wit, H., Ding, J., Engelhardt, B. E., Eriksson, J. G., Fedko, I. O., Ferrucci, L., Franke, B., Giegling, I., Grucza, R., Hartmann, A. M., Heath, A. C., Heinonen, K., Henders, A. K., Homuth, G., Hottenga, J.-J., Iacono, W. G., Janzing, J., Jokela, M., Karlsson, R., Kemp, J., Kirkpatrick, M. G., Latvala, A., Lehtimäki, T., Liewald, D. C., Madden, P. F., Magri, C., Magnusson, P. E., Marten, J., Maschio, A., Mbarek, H., Medland, S. E., Mihailov, E., Milaneschi, Y., Montgomery, G. W., Nauck, M., Nivard, M. G., Ouwens, K. G., Palotie, A., Pettersson, E., Polasek, O., Qian, Y., Pulkki-Råback, L., Raitakari, O., Realo, A., Rose, R. J., Ruggiero, D., Schmidt, C. O., Slutske, W. S., Sorice, R., Starr, J. M., St Pourcain, B., Sutin, A. R., Timpson, N. J., Trochet, H., Vermeulen, S., Vuoksimaa, E., Widen, E., Wouda, J., Wright, M. J., Zgaga, L., Porteous, D., Minelli, A., Palmer, A. A., Rujescu, D., Ciullo, M., Hayward, C., Rudan, I., Metspalu, A., Kaprio, J., Deary, I. J., Räikkönen, K., Wilson, J. F., Keltikangas-Järvinen, L., Bierut, L. J., Hettema, J. M., Grabe, H. J., Penninx, B. W. J. H., van Duijn, C. M., Evans, D. M., Schlessinger, D., Pedersen, N. L., Terracciano, A., McGue, M., Martin, N. G., & Boomsma, D. I. (2016). Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium. Behavior Genetics, 46, 170-182. doi:10.1007/s10519-015-9735-5.

    Abstract

    Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero, but polygenic risk scores, weighted using linkage information, significantly predicted extraversion scores in an independent cohort. These results show that extraversion is a highly polygenic personality trait, with an architecture possibly different from other complex human traits, including other personality traits. Future studies are required to further determine which genetic variants, by what modes of gene action, constitute the heritable nature of extraversion. © 2015 The Author(s)

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  • Genetics of Personality Consortium (2015). Meta-analysis of genome-wide association studies for neuroticism, and the polygenic association with major depressive disorder. JAMA Psychiatry, 72(7), 642-650. doi:10.1001/jamapsychiatry.2015.0554.

    Abstract

    Importance  Neuroticism is a pervasive risk factor for psychiatric conditions. It genetically overlaps with major depressive disorder (MDD) and is therefore an important phenotype for psychiatric genetics. The Genetics of Personality Consortium has created a resource for genome-wide association analyses of personality traits in more than 63 000 participants (including MDD cases).Objectives To identify genetic variants associated with neuroticism by performing a meta-analysis of genome-wide association results based on 1000 Genomes imputation; to evaluate whether common genetic variants as assessed by single-nucleotide polymorphisms (SNPs) explain variation in neuroticism by estimating SNP-based heritability; and to examine whether SNPs that predict neuroticism also predict MDD.Design, Setting, and Participants Genome-wide association meta-analysis of 30 cohorts with genome-wide genotype, personality, and MDD data from the Genetics of Personality Consortium. The study included 63 661 participants from 29 discovery cohorts and 9786 participants from a replication cohort. Participants came from Europe, the United States, or Australia. Analyses were conducted between 2012 and 2014.Main Outcomes and Measures Neuroticism scores harmonized across all 29 discovery cohorts by item response theory analysis, and clinical MDD case-control status in 2 of the cohorts.Results A genome-wide significant SNP was found on 3p14 in MAGI1 (rs35855737; P = 9.26 × 10−9 in the discovery meta-analysis). This association was not replicated (P = .32), but the SNP was still genome-wide significant in the meta-analysis of all 30 cohorts (P = 2.38 × 10−8). Common genetic variants explain 15% of the variance in neuroticism. Polygenic scores based on the meta-analysis of neuroticism in 27 cohorts significantly predicted neuroticism (1.09 × 10−12 <} P {<} .05) and MDD (4.02 × 10−9 {<} P {< .05) in the 2 other cohorts.Conclusions and Relevance This study identifies a novel locus for neuroticism. The variant is located in a known gene that has been associated with bipolar disorder and schizophrenia in previous studies. In addition, the study shows that neuroticism is influenced by many genetic variants of small effect that are either common or tagged by common variants. These genetic variants also influence MDD. Future studies should confirm the role of the MAGI1 locus for neuroticism and further investigate the association of MAGI1 and the polygenic association to a range of other psychiatric disorders that are phenotypically correlated with neuroticism.

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  • Guggenheim, J. A., St Pourcain, B., McMahon, G., Timpson, N. J., Evans, D. M., & Williams, C. (2015). Assumption-free estimation of the genetic contribution to refractive error across childhood. Molecular Vision, 21, 621-632. Retrieved from http://www.molvis.org/molvis/v21/621.

    Abstract

    Studies in relatives have generally yielded high heritability estimates for refractive error: twins 75–90%, families 15–70%. However, because related individuals often share a common environment, these estimates are inflated (via misallocation of unique/common environment variance). We calculated a lower-bound heritability estimate for refractive error free from such bias. Between the ages 7 and 15 years, participants in the Avon Longitudinal Study of Parents and Children (ALSPAC) underwent non-cycloplegic autorefraction at regular research clinics. At each age, an estimate of the variance in refractive error explained by single nucleotide polymorphism (SNP) genetic variants was calculated using genome-wide complex trait analysis (GCTA) using high-density genome-wide SNP genotype information (minimum N at each age=3,404). The variance in refractive error explained by the SNPs (“SNP heritability”) was stable over childhood: Across age 7–15 years, SNP heritability averaged 0.28 (SE=0.08, p<0.001). The genetic correlation for refractive error between visits varied from 0.77 to 1.00 (all p<0.001) demonstrating that a common set of SNPs was responsible for the genetic contribution to refractive error across this period of childhood. Simulations suggested lack of cycloplegia during autorefraction led to a small underestimation of SNP heritability (adjusted SNP heritability=0.35; SE=0.09). To put these results in context, the variance in refractive error explained (or predicted) by the time participants spent outdoors was <0.005 and by the time spent reading was <0.01, based on a parental questionnaire completed when the child was aged 8–9 years old. Genetic variation captured by common SNPs explained approximately 35% of the variation in refractive error between unrelated subjects. This value sets an upper limit for predicting refractive error using existing SNP genotyping arrays, although higher-density genotyping in larger samples and inclusion of interaction effects is expected to raise this figure toward twin- and family-based heritability estimates. The same SNPs influenced refractive error across much of childhood. Notwithstanding the strong evidence of association between time outdoors and myopia, and time reading and myopia, less than 1% of the variance in myopia at age 15 was explained by crude measures of these two risk factors, indicating that their effects may be limited, at least when averaged over the whole population.
  • St Pourcain, B., Haworth, C. M. A., Davis, O. S. P., Wang, K., Timpson, N. J., Evans, D. M., Kemp, J. P., Ronald, A., Price, T., Meaburn, E., Ring, S. M., Golding, J., Hakonarson, H., Plomin, R., & Davey Smith, G. (2015). Heritability and genome-wide analyses of problematic peer relationships during childhood and adolescence. Human Genetics, 134(6), 539-551. doi:10.1007/s00439-014-1514-5.

    Abstract

    Peer behaviour plays an important role in the development of social adjustment, though little is known about its genetic architecture. We conducted a twin study combined with a genome-wide complex trait analysis (GCTA) and a genome-wide screen to characterise genetic influences on problematic peer behaviour during childhood and adolescence. This included a series of longitudinal measures (parent-reported Strengths-and-Difficulties Questionnaire) from a UK population-based birth-cohort (ALSPAC, 4–17 years), and a UK twin sample (TEDS, 4–11 years). Longitudinal twin analysis (TEDS; N ≤ 7,366 twin pairs) showed that peer problems in childhood are heritable (4–11 years, 0.60 < twin-h 2 ≤ 0.71) but genetically heterogeneous from age to age (4–11 years, twin-r g = 0.30). GCTA (ALSPAC: N ≤ 5,608, TEDS: N ≤ 2,691) provided furthermore little support for the contribution of measured common genetic variants during childhood (4–12 years, 0.02 < GCTA-h 2(Meta) ≤ 0.11) though these influences become stronger in adolescence (13–17 years, 0.14 < GCTA-h 2(ALSPAC) ≤ 0.27). A subsequent cross-sectional genome-wide screen in ALSPAC (N ≤ 6,000) focussed on peer problems with the highest GCTA-heritability (10, 13 and 17 years, 0.0002 < GCTA-P ≤ 0.03). Single variant signals (P ≤ 10−5) were followed up in TEDS (N ≤ 2835, 9 and 11 years) and, in search for autism quantitative trait loci, explored within two autism samples (AGRE: N Pedigrees = 793; ACC: N Cases = 1,453/N Controls = 7,070). There was, however, no evidence for association in TEDS and little evidence for an overlap with the autistic continuum. In summary, our findings suggest that problematic peer relationships are heritable but genetically complex and heterogeneous from age to age, with an increase in common measurable genetic variation during adolescence.
  • Stergiakouli, E., Martin, J., Hamshere, M. L., Langley, K., Evans, D. M., St Pourcain, B., Timpson, N. J., Owen, M. J., O'Donovan, M., Thapar, A., & Davey Smith, G. (2015). Shared Genetic Influences Between Attention-Deficit/Hyperactivity Disorder (ADHD) Traits in Children and Clinical ADHD. Journal of the American Academy of Child and Adolescent Psychiatry, 54(4), 322-327. doi:10.1016/j.jaac.2015.01.010.
  • The UK10K Consortium (2015). The UK10K project identifies rare variants in health and disease. Nature, 526(7571), 82-89. doi:10.1038/nature14962.

    Abstract

    The contribution of rare and low-frequency variants to human traits is largely unexplored. Here we describe insights from sequencing whole genomes (low read depth, 7×) or exomes (high read depth, 80×) of nearly 10,000 individuals from population-based and disease collections. In extensively phenotyped cohorts we characterize over 24 million novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with levels of triglycerides (APOB), adiponectin (ADIPOQ) and low-density lipoprotein cholesterol (LDLR and RGAG1) from single-marker and rare variant aggregation tests. We describe population structure and functional annotation of rare and low-frequency variants, use the data to estimate the benefits of sequencing for association studies, and summarize lessons from disease-specific collections. Finally, we make available an extensive resource, including individual-level genetic and phenotypic data and web-based tools to facilitate the exploration of association results.
  • van der Valk, R. J. P., Kreiner-Møller, E., Kooijman, M. N., Guxens, M., Stergiakouli, E., Sääf, A., Bradfield, J. P., Geller, F., Hayes, M. G., Cousminer, D. L., Körner, A., Thiering, E., Curtin, J. A., Myhre, R., Huikari, V., Joro, R., Kerkhof, M., Warrington, N. M., Pitkänen, N., Ntalla, I. and 98 morevan der Valk, R. J. P., Kreiner-Møller, E., Kooijman, M. N., Guxens, M., Stergiakouli, E., Sääf, A., Bradfield, J. P., Geller, F., Hayes, M. G., Cousminer, D. L., Körner, A., Thiering, E., Curtin, J. A., Myhre, R., Huikari, V., Joro, R., Kerkhof, M., Warrington, N. M., Pitkänen, N., Ntalla, I., Horikoshi, M., Veijola, R., Freathy, R. M., Teo, Y.-Y., Barton, S. J., Evans, D. M., Kemp, J. P., St Pourcain, B., Ring, S. M., Davey Smith, G., Bergström, A., Kull, I., Hakonarson, H., Mentch, F. D., Bisgaard, H., Chawes, B., Stokholm, J., Waage, J., Eriksen, P., Sevelsted, A., Melbye, M., van Duijn, C. M., Medina-Gomez, C., Hofman, A., de Jongste, J. C., Taal, H. R., Uitterlinden, A. G., Armstrong, L. L., Eriksson, J., Palotie, A., Bustamante, M., Estivill, X., Gonzalez, J. R., Llop, S., Kiess, W., Mahajan, A., Flexeder, C., Tiesler, C. M. T., Murray, C. S., Simpson, A., Magnus, P., Sengpiel, V., Hartikainen, A.-L., Keinanen-Kiukaanniemi, S., Lewin, A., Da Silva Couto Alves, A., Blakemore, A. I., Buxton, J. L., Kaakinen, M., Rodriguez, A., Sebert, S., Vaarasmaki, M., Lakka, T., Lindi, V., Gehring, U., Postma, D. S., Ang, W., Newnham, J. P., Lyytikäinen, L.-P., Pahkala, K., Raitakari, O. T., Panoutsopoulou, K., Zeggini, E., Boomsma, D. I., Groen-Blokhuis, M., Ilonen, J., Franke, L., Hirschhorn, J. N., Pers, T. H., Liang, L., Huang, J., Hocher, B., Knip, M., Saw, S.-M., Holloway, J. W., Melén, E., Grant, S. F. A., Feenstra, B., Lowe, W. L., Widén, E., Sergeyev, E., Grallert, H., Custovic, A., Jacobsson, B., Jarvelin, M.-R., Atalay, M., Koppelman, G. H., Pennell, C. E., Niinikoski, H., Dedoussis, G. V., Mccarthy, M. I., Frayling, T. M., Sunyer, J., Timpson, N. J., Rivadeneira, F., Bønnelykke, K., Jaddoe, V. W. V., & Early Growth Genetics (EGG) Consortium (2015). A novel common variant in DCST2 is associated with length in early life and height in adulthood. Human Molecular Genetics, 24(4), 1155-1168. doi:10.1093/hmg/ddu510.

    Abstract

    Common genetic variants have been identified for adult height, but not much is known about the genetics of skeletal growth in early life. To identify common genetic variants that influence fetal skeletal growth, we meta-analyzed 22 genome-wide association studies (Stage 1; N = 28 459). We identified seven independent top single nucleotide polymorphisms (SNPs) (P < 1 × 10(-6)) for birth length, of which three were novel and four were in or near loci known to be associated with adult height (LCORL, PTCH1, GPR126 and HMGA2). The three novel SNPs were followed-up in nine replication studies (Stage 2; N = 11 995), with rs905938 in DC-STAMP domain containing 2 (DCST2) genome-wide significantly associated with birth length in a joint analysis (Stages 1 + 2; β = 0.046, SE = 0.008, P = 2.46 × 10(-8), explained variance = 0.05%). Rs905938 was also associated with infant length (N = 28 228; P = 5.54 × 10(-4)) and adult height (N = 127 513; P = 1.45 × 10(-5)). DCST2 is a DC-STAMP-like protein family member and DC-STAMP is an osteoclast cell-fusion regulator. Polygenic scores based on 180 SNPs previously associated with human adult stature explained 0.13% of variance in birth length. The same SNPs explained 2.95% of the variance of infant length. Of the 180 known adult height loci, 11 were genome-wide significantly associated with infant length (SF3B4, LCORL, SPAG17, C6orf173, PTCH1, GDF5, ZNFX1, HHIP, ACAN, HLA locus and HMGA2). This study highlights that common variation in DCST2 influences variation in early growth and adult height.
  • Warrington, N. M., Howe, L. D., Paternoster, L., Kaakinen, M., Herrala, S., Huikari, V., Wu, Y. Y., Kemp, J. P., Timpson, N. J., St Pourcain, B., Smith, G. D., Tilling, K., Jarvelin, M.-R., Pennell, C. E., Evans, D. M., Lawlor, D. A., Briollais, L., & Palmer, L. J. (2015). A genome-wide association study of body mass index across early life and childhood. International Journal of Epidemiology, 44(2), 700-712. doi:10.1093/ije/dyv077.

    Abstract

    Background: Several studies have investigated the effect of known adult body mass index (BMI) associated single nucleotide polymorphisms (SNPs) on BMI in childhood. There has been no genome-wide association study (GWAS) of BMI trajectories over childhood. Methods: We conducted a GWAS meta-analysis of BMI trajectories from 1 to 17 years of age in 9377 children (77 967 measurements) from the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Western Australian Pregnancy Cohort (Raine) Study. Genome-wide significant loci were examined in a further 3918 individuals (48 530 measurements) from Northern Finland. Linear mixed effects models with smoothing splines were used in each cohort for longitudinal modelling of BMI. Results: A novel SNP, downstream from the FAM120AOS gene on chromosome 9, was detected in the meta-analysis of ALSPAC and Raine. This association was driven by a difference in BMI at 8 years (T allele of rs944990 increased BMI; PSNP = 1.52 × 10−8), with a modest association with change in BMI over time (PWald(Change) = 0.006). Three known adult BMI-associated loci (FTO, MC4R and ADCY3) and one childhood obesity locus (OLFM4) reached genome-wide significance (PWald < 1.13 × 10−8) with BMI at 8 years and/or change over time. Conclusions: This GWAS of BMI trajectories over childhood identified a novel locus that warrants further investigation. We also observed genome-wide significance with previously established obesity loci, making the novel observation that these loci affected both the level and the rate of change in BMI. We have demonstrated that the use of repeated measures data can increase power to allow detection of genetic loci with smaller sample sizes.
  • Warrington, N. M., Zhu, G., Dy, V., Heath, A. C., Madden, P. A. F., Hemani, G., Kemp, J. P., McMahon, G., St Pourcain, B., Timpson, N. J., Taylor, C. M., Golding, J., Lawlor, D. A., Steer, C., Montgomery, G. W., Martin, N. G., Smith, G. D., Evans, D. M., & Whitfield, J. B. (2015). Genome-wide association study of blood lead shows multiple associations near ALAD. Human Molecular Genetics, 24(13), 3871-3879. doi:10.1093/hmg/ddv112.

    Abstract

    Exposure to high levels of environmental lead, or biomarker evidence of high body lead content, is associated with anaemia, developmental and neurological deficits in children, and increased mortality in adults. Adverse effects of lead still occur despite substantial reduction in environmental exposure. There is genetic variation between individuals in blood lead concentration but the polymorphisms contributing to this have not been defined. We measured blood or erythrocyte lead content, and carried out genome-wide association analysis, on population-based cohorts of adult volunteers from Australia and UK (N = 5433). Samples from Australia were collected in two studies, in 1993–1996 and 2002–2005 and from UK in 1991–1992. One locus, at ALAD on chromosome 9, showed consistent association with blood lead across countries and evidence for multiple independent allelic effects. The most significant single nucleotide polymorphism (SNP), rs1805313 (P = 3.91 × 10−14 for lead concentration in a meta-analysis of all data), is known to have effects on ALAD expression in blood cells but other SNPs affecting ALAD expression did not affect blood lead. Variants at 12 other loci, including ABO, showed suggestive associations (5 × 10−6 >} P {> 5 × 10−8). Identification of genetic polymorphisms affecting blood lead reinforces the view that genetic factors, as well as environmental ones, are important in determining blood lead levels. The ways in which ALAD variation affects lead uptake or distribution are still to be determined.
  • Li, Q., Wojciechowski, R., Simpson, C. L., Hysi, P. G., Verhoeven, V. J. M., Ikram, M. K., Höhn, R., Vitart, V., Hewitt, A. W., Oexle, K., Mäkelä, K.-M., MacGregor, S., Pirastu, M., Fan, Q., Cheng, C.-Y., St Pourcain, B., McMahon, G., Kemp, J. P., Northstone, K., Rahi, J. S. and 69 moreLi, Q., Wojciechowski, R., Simpson, C. L., Hysi, P. G., Verhoeven, V. J. M., Ikram, M. K., Höhn, R., Vitart, V., Hewitt, A. W., Oexle, K., Mäkelä, K.-M., MacGregor, S., Pirastu, M., Fan, Q., Cheng, C.-Y., St Pourcain, B., McMahon, G., Kemp, J. P., Northstone, K., Rahi, J. S., Cumberland, P. M., Martin, N. G., Sanfilippo, P. G., Lu, Y., Wang, Y. X., Hayward, C., Polašek, O., Campbell, H., Bencic, G., Wright, A. F., Wedenoja, J., Zeller, T., Schillert, A., Mirshahi, A., Lackner, K., Yip, S. P., Yap, M. K. H., Ried, J. S., Gieger, C., Murgia, F., Wilson, J. F., Fleck, B., Yazar, S., Vingerling, J. R., Hofman, A., Uitterlinden, A., Rivadeneira, F., Amin, N., Karssen, L., Oostra, B. A., Zhou, X., Teo, Y.-Y., Tai, E. S., Vithana, E., Barathi, V., Zheng, Y., Siantar, R. G., Neelam, K., Shin, Y., Lam, J., Yonova-Doing, E., Venturini, C., Hosseini, S. M., Wong, H.-S., Lehtimäki, T., Kähönen, M., Raitakari, O., Timpson, N. J., Evans, D. M., Khor, C.-C., Aung, T., Young, T. L., Mitchell, P., Klein, B., van Duijn, C. M., Meitinger, T., Jonas, J. B., Baird, P. N., Mackey, D. A., Wong, T. Y., Saw, S.-M., Pärssinen, O., Stambolian, D., Hammond, C. J., Klaver, C. C. W., Williams, C., Paterson, A. D., Bailey-Wilson, J. E., & Guggenheim, J. A. (2015). Genome-wide association study for refractive astigmatism reveals genetic co-determination with spherical equivalent refractive error: the CREAM consortium. Human Genetics, 134, 131-146. doi:10.1007/s00439-014-1500-y.

    Abstract

    To identify genetic variants associated with refractive astigmatism in the general population, meta-analyses of genome-wide association studies were performed for: White Europeans aged at least 25 years (20 cohorts, N = 31,968); Asian subjects aged at least 25 years (7 cohorts, N = 9,295); White Europeans aged <25 years (4 cohorts, N = 5,640); and all independent individuals from the above three samples combined with a sample of Chinese subjects aged <25 years (N = 45,931). Participants were classified as cases with refractive astigmatism if the average cylinder power in their two eyes was at least 1.00 diopter and as controls otherwise. Genome-wide association analysis was carried out for each cohort separately using logistic regression. Meta-analysis was conducted using a fixed effects model. In the older European group the most strongly associated marker was downstream of the neurexin-1 (NRXN1) gene (rs1401327, P = 3.92E−8). No other region reached genome-wide significance, and association signals were lower for the younger European group and Asian group. In the meta-analysis of all cohorts, no marker reached genome-wide significance: The most strongly associated regions were, NRXN1 (rs1401327, P = 2.93E−07), TOX (rs7823467, P = 3.47E−07) and LINC00340 (rs12212674, P = 1.49E−06). For 34 markers identified in prior GWAS for spherical equivalent refractive error, the beta coefficients for genotype versus spherical equivalent, and genotype versus refractive astigmatism, were highly correlated (r = −0.59, P = 2.10E−04). This work revealed no consistent or strong genetic signals for refractive astigmatism; however, the TOX gene region previously identified in GWAS for spherical equivalent refractive error was the second most strongly associated region. Analysis of additional markers provided evidence supporting widespread genetic co-susceptibility for spherical and astigmatic refractive errors.

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