Displaying 1 - 19 of 19
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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.Additional information
supplementary tables -
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.Additional information
Supplementary File S1 Supplementary File S2 Supplementary File S3 Supplementary File S4 Acknowledgements -
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.Additional information
supplementary information -
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.
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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.Additional information
supplementary information -
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.
Additional information
supporting information -
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.Additional information
supporting information -
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.Additional information
http://www.sciencedirect.com/science/article/pii/S0002929717301593#appd002 -
Guggenheim, J. A., Northstone, K., McMahon, G., Ness, A. R., Deere, K., Mattocks, C., St Pourcain, B., & Williams, C. (2012). Time outdoors and physical activity as predictors of incident myopia in childhood: a prospective cohort study. Investigative Ophthalmology and Visual Science, 53(6), 2856-2865. doi:10.1167/iovs.11-9091.
Abstract
PURPOSE: Time spent in "sports/outdoor activity" has shown a negative association with incident myopia during childhood. We investigated the association of incident myopia with time spent outdoors and physical activity separately. METHODS: Participants in the Avon Longitudinal Study of Parents and Children (ALSPAC) were assessed by noncycloplegic autorefraction at ages 7, 10, 11, 12, and 15 years, and classified as myopic (≤-1 diopters) or as emmetropic/hyperopic (≥-0.25 diopters) at each visit (N = 4,837-7,747). Physical activity at age 11 years was measured objectively using an accelerometer, worn for 1 week. Time spent outdoors was assessed via a parental questionnaire administered when children were aged 8-9 years. Variables associated with incident myopia were examined using Cox regression. RESULTS: In analyses using all available data, both time spent outdoors and physical activity were associated with incident myopia, with time outdoors having the larger effect. The results were similar for analyses restricted to children classified as either nonmyopic or emmetropic/hyperopic at age 11 years. Thus, for children nonmyopic at age 11, the hazard ratio (95% confidence interval, CI) for incident myopia was 0.66 (0.47-0.93) for a high versus low amount of time spent outdoors, and 0.87 (0.76-0.99) per unit standard deviation above average increase in moderate/vigorous physical activity. CONCLUSION: Time spent outdoors was predictive of incident myopia independently of physical activity level. The greater association observed for time outdoors suggests that the previously reported link between "sports/outdoor activity" and incident myopia is due mainly to its capture of information relating to time outdoors rather than physical activity.Additional information
http://iovs.arvojournals.org/article.aspx?articleid=2127681#90733836 -
Ikram, M. A., Fornage, M., Smith, A. V., Seshadri, S., Schmidt, R., Debette, S., Vrooman, H. A., Sigurdsson, S., Ropele, S., Taal, H. R., Mook-Kanamori, D. O., Coker, L. H., Longstreth, W. T., Niessen, W. J., DeStefano, A. L., Beiser, A., Zijdenbos, A. P., Struchalin, M., Jack, C. R., Rivadeneira, F. and 37 moreIkram, M. A., Fornage, M., Smith, A. V., Seshadri, S., Schmidt, R., Debette, S., Vrooman, H. A., Sigurdsson, S., Ropele, S., Taal, H. R., Mook-Kanamori, D. O., Coker, L. H., Longstreth, W. T., Niessen, W. J., DeStefano, A. L., Beiser, A., Zijdenbos, A. P., Struchalin, M., Jack, C. R., Rivadeneira, F., Uitterlinden, A. G., Knopman, D. S., Hartikainen, A.-L., Pennell, C. E., Thiering, E., Steegers, E. A. P., Hakonarson, H., Heinrich, J., Palmer, L. J., Jarvelin, M.-R., McCarthy, M. I., Grant, S. F. A., St Pourcain, B., Timpson, N. J., Smith, G. D., Sovio, U., Nalls, M. A., Au, R., Hofman, A., Gudnason, H., van der Lugt, A., Harris, T. B., Meeks, W. M., Vernooij, M. W., van Buchem, M. A., Catellier, D., Jaddoe, V. W. V., Gudnason, V., Windham, B. G., Wolf, P. A., van Duijn, C. M., Mosley, T. H., Schmidt, H., Launer, L. J., Breteler, M. M. B., DeCarli, C., Consortiumthe Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, & Early Growth Genetics (EGG) Consortium (2012). Common variants at 6q22 and 17q21 are associated with intracranial volume. Nature Genetics, 44(5), 539-544. doi:10.1038/ng.2245.
Abstract
During aging, intracranial volume remains unchanged and represents maximally attained brain size, while various interacting biological phenomena lead to brain volume loss. Consequently, intracranial volume and brain volume in late life reflect different genetic influences. Our genome-wide association study (GWAS) in 8,175 community-dwelling elderly persons did not reveal any associations at genome-wide significance (P < 5 × 10(-8)) for brain volume. In contrast, intracranial volume was significantly associated with two loci: rs4273712 (P = 3.4 × 10(-11)), a known height-associated locus on chromosome 6q22, and rs9915547 (P = 1.5 × 10(-12)), localized to the inversion on chromosome 17q21. We replicated the associations of these loci with intracranial volume in a separate sample of 1,752 elderly persons (P = 1.1 × 10(-3) for 6q22 and 1.2 × 10(-3) for 17q21). Furthermore, we also found suggestive associations of the 17q21 locus with head circumference in 10,768 children (mean age of 14.5 months). Our data identify two loci associated with head size, with the inversion at 17q21 also likely to be involved in attaining maximal brain size. -
Paternoster, L., Zhurov, A., Toma, A., Kemp, J., St Pourcain, B., Timpson, N., McMahon, G., McArdle, W., Ring, S., Smith, G., Richmond, S., & Evans, D. (2012). Genome-wide Association Study of Three-Dimensional Facial Morphology Identifies a Variant in PAX3 Associated with Nasion Position. The American Journal of Human Genetics, 90(3), 478-485. doi:10.1016/j.ajhg.2011.12.021.
Abstract
Craniofacial morphology is highly heritable, but little is known about which genetic variants influence normal facial variation in the general population. We aimed to identify genetic variants associated with normal facial variation in a population-based cohort of 15-year-olds from the Avon Longitudinal Study of Parents and Children. 3D high-resolution images were obtained with two laser scanners, these were merged and aligned, and 22 landmarks were identified and their x, y, and z coordinates used to generate 54 3D distances reflecting facial features. 14 principal components (PCs) were also generated from the landmark locations. We carried out genome-wide association analyses of these distances and PCs in 2,185 adolescents and attempted to replicate any significant associations in a further 1,622 participants. In the discovery analysis no associations were observed with the PCs, but we identified four associations with the distances, and one of these, the association between rs7559271 in PAX3 and the nasion to midendocanthion distance (n-men), was replicated (p = 4 × 10−7). In a combined analysis, each G allele of rs7559271 was associated with an increase in n-men distance of 0.39 mm (p = 4 × 10−16), explaining 1.3% of the variance. Independent associations were observed in both the z (nasion prominence) and y (nasion height) dimensions (p = 9 × 10−9 and p = 9 × 10−10, respectively), suggesting that the locus primarily influences growth in the yz plane. Rare variants in PAX3 are known to cause Waardenburg syndrome, which involves deafness, pigmentary abnormalities, and facial characteristics including a broad nasal bridge. Our findings show that common variants within this gene also influence normal craniofacial development.Additional information
http://www.sciencedirect.com/science/article/pii/S000292971200002X#appd002 -
Relton, C. L., Groom, A., St Pourcain, B., Sayers, A. E., Swan, D. C., Embleton, N. D., Pearce, M. S., Ring, S. M., Northstone, K., Tobias, J. H., Trakalo, J., Ness, A. R., Shaheen, S. O., & Davey Smith, G. (2012). DNA Methylation Patterns in Cord Blood DNA and Body Size in Childhood. PLoS ONE, 7(3): e31821. doi:10.1371/journal.pone.0031821.
Abstract
BACKGROUND: Epigenetic markings acquired in early life may have phenotypic consequences later in development through their role in transcriptional regulation with relevance to the developmental origins of diseases including obesity. The goal of this study was to investigate whether DNA methylation levels at birth are associated with body size later in childhood. PRINCIPAL FINDINGS: A study design involving two birth cohorts was used to conduct transcription profiling followed by DNA methylation analysis in peripheral blood. Gene expression analysis was undertaken in 24 individuals whose biological samples and clinical data were collected at a mean ± standard deviation (SD) age of 12.35 (0.95) years, the upper and lower tertiles of body mass index (BMI) were compared with a mean (SD) BMI difference of 9.86 (2.37) kg/m(2). This generated a panel of differentially expressed genes for DNA methylation analysis which was then undertaken in cord blood DNA in 178 individuals with body composition data prospectively collected at a mean (SD) age of 9.83 (0.23) years. Twenty-nine differentially expressed genes (>}1.2-fold and p{<10(-4)) were analysed to determine DNA methylation levels at 1-3 sites per gene. Five genes were unmethylated and DNA methylation in the remaining 24 genes was analysed using linear regression with bootstrapping. Methylation in 9 of the 24 (37.5%) genes studied was associated with at least one index of body composition (BMI, fat mass, lean mass, height) at age 9 years, although only one of these associations remained after correction for multiple testing (ALPL with height, p(Corrected) = 0.017). CONCLUSIONS: DNA methylation patterns in cord blood show some association with altered gene expression, body size and composition in childhood. The observed relationship is correlative and despite suggestion of a mechanistic epigenetic link between in utero life and later phenotype, further investigation is required to establish causality.Additional information
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0031821#s5 -
Scott, R. A., Lagou, V., Welch, R. P., Wheeler, E., Montasser, M. E., Luan, J., Mägi, R., Strawbridge, R. J., Rehnberg, E., Gustafsson, S., Kanoni, S., Rasmussen-Torvik, L. J., Yengo, L., Lecoeur, C., Shungin, D., Sanna, S., Sidore, C., Johnson, P. C. D., Jukema, J. W., Johnson, T. and 195 moreScott, R. A., Lagou, V., Welch, R. P., Wheeler, E., Montasser, M. E., Luan, J., Mägi, R., Strawbridge, R. J., Rehnberg, E., Gustafsson, S., Kanoni, S., Rasmussen-Torvik, L. J., Yengo, L., Lecoeur, C., Shungin, D., Sanna, S., Sidore, C., Johnson, P. C. D., Jukema, J. W., Johnson, T., Mahajan, A., Verweij, N., Thorleifsson, G., Hottenga, J.-J., Shah, S., Smith, A. V., Sennblad, B., Gieger, C., Salo, P., Perola, M., Timpson, N. J., Evans, D. M., St Pourcain, B., Wu, Y., Andrews, J. S., Hui, J., Bielak, L. F., Zhao, W., Horikoshi, M., Navarro, P., Isaacs, A., O'Connell, J. R., Stirrups, K., Vitart, V., Hayward, C., Esko, T., Mihailov, E., Fraser, R. M., Fall, T., Voight, B. F., Raychaudhuri, S., Chen, H., Lindgren, C. M., Morris, A. P., Rayner, N. W., Robertson, N., Rybin, D., Liu, C.-T., Beckmann, J. S., Willems, S. M., Chines, P. S., Jackson, A. U., Kang, H. M., Stringham, H. M., Song, K., Tanaka, T., Peden, J. F., Goel, A., Hicks, A. A., An, P., Müller-Nurasyid, M., Franco-Cereceda, A., Folkersen, L., Marullo, L., Jansen, H., Oldehinkel, A. J., Bruinenberg, M., Pankow, J. S., North, K. E., Forouhi, N. G., Loos, R. J. F., Edkins, S., Varga, T. V., Hallmans, G., Oksa, H., Antonella, M., Nagaraja, R., Trompet, S., Ford, I., Bakker, S. J. L., Kong, A., Kumari, M., Gigante, B., Herder, C., Munroe, P. B., Caulfield, M., Antti, J., Mangino, M., Small, K., Miljkovic, I., Liu, Y., Atalay, M., Kiess, W., James, A. L., Rivadeneira, F., Uitterlinden, A. G., Palmer, C. N. A., Doney, A. S. F., Willemsen, G., Smit, J. H., Campbell, S., Polasek, O., Bonnycastle, L. L., Hercberg, S., Dimitriou, M., Bolton, J. L., Fowkes, G. R., Kovacs, P., Lindström, J., Zemunik, T., Bandinelli, S., Wild, S. H., Basart, H. V., Rathmann, W., Grallert, H., Maerz, W., Kleber, M. E., Boehm, B. O., Peters, A., Pramstaller, P. P., Province, M. A., Borecki, I. B., Hastie, N. D., Rudan, I., Campbell, H., Watkins, H., Farrall, M., Stumvoll, M., Ferrucci, L., Waterworth, D. M., Bergman, R. N., Collins, F. S., Tuomilehto, J., Watanabe, R. M., de Geus, E. J. C., Penninx, B. W., Hofman, A., Oostra, B. A., Psaty, B. M., Vollenweider, P., Wilson, J. F., Wright, A. F., Hovingh, G. K., Metspalu, A., Uusitupa, M., Magnusson, P. K. E., Kyvik, K. O., Kaprio, J., Price, J. F., Dedoussis, G. V., Deloukas, P., Meneton, P., Lind, L., Boehnke, M., Shuldiner, A. R., van Duijn, C. M., Morris, A. D., Toenjes, A., Peyser, P. A., Beilby, J. P., Körner, A., Kuusisto, J., Laakso, M., Bornstein, S. R., Schwarz, P. E. H., Lakka, T. A., Rauramaa, R., Adair, L. S., Smith, G. D., Spector, T. D., Illig, T., de Faire, U., Hamsten, A., Gudnason, V., Kivimaki, M., Hingorani, A., Keinanen-Kiukaanniemi, S. M., Saaristo, T. E., Boomsma, D. I., Stefansson, K., van der Harst, P., Dupuis, J., Pedersen, N. L., Sattar, N., Harris, T. B., Cucca, F., Ripatti, S., Salomaa, V., Mohlke, K. L., Balkau, B., Froguel, P., Pouta, A., Jarvelin, M.-R., Wareham, N. J., Bouatia-Naji, N., McCarthy, M. I., Franks, P. W., Meigs, J. B., Teslovich, T. M., Florez, J. C., Langenberg, C., Ingelsson, E., Prokopenko, I., Barroso, I., & Diabetes Genetics Replication and Meta-analysis (DIAGRAM) Consortium (2012). Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nature Genetics, 44(9), 991-1005. doi:10.1038/ng.2385.
Abstract
Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.Additional information
http://www.nature.com/ng/journal/v44/n9/full/ng.2385.html#supplementary-informa… -
Taal, H. R., St Pourcain, B., Thiering, E., Das, S., Mook-Kanamori, D. O., Warrington, N. M., Kaakinen, M., Kreiner-Møller, E., Bradfield, J. P., Freathy, R. M., Geller, F., Guxens, M., Cousminer, D. L., Kerkhof, M., Timpson, N. J., Ikram, M. A., Beilin, L. J., Bønnelykke, K., Buxton, J. L., Charoen, P. and 68 moreTaal, H. R., St Pourcain, B., Thiering, E., Das, S., Mook-Kanamori, D. O., Warrington, N. M., Kaakinen, M., Kreiner-Møller, E., Bradfield, J. P., Freathy, R. M., Geller, F., Guxens, M., Cousminer, D. L., Kerkhof, M., Timpson, N. J., Ikram, M. A., Beilin, L. J., Bønnelykke, K., Buxton, J. L., Charoen, P., Chawes, B. L. K., Eriksson, J., Evans, D. M., Hofman, A., Kemp, J. P., Kim, C. E., Klopp, N., Lahti, J., Lye, S. J., McMahon, G., Mentch, F. D., Müller-Nurasyid, M., O'Reilly, P. F., Prokopenko, I., Rivadeneira, F., Steegers, E. A. P., Sunyer, J., Tiesler, C., Yaghootkar, H., Breteler, M. M. B., Decarli, C., Breteler, M. M. B., Debette, S., Fornage, M., Gudnason, V., Launer, L. J., van der Lugt, A., Mosley, T. H., Seshadri, S., Smith, A. V., Vernooij, M. W., Blakemore, A. I. F., Chiavacci, R. M., Feenstra, B., Fernandez-Banet, J., Grant, S. F. A., Hartikainen, A.-L., van der Heijden, A. J., Iñiguez, C., Lathrop, M., McArdle, W. L., Mølgaard, A., Newnham, J. P., Palmer, L. J., Palotie, A., Pouta, A., Ring, S. M., Sovio, U., Standl, M., Uitterlinden, A. G., Wichmann, H.-E., Vissing, N. H., DeCarli, C., van Duijn, C. M., McCarthy, M. I., Koppelman, G. H., Estivill, X., Hattersley, A. T., Melbye, M., Bisgaard, H., Pennell, C. E., Widen, E., Hakonarson, H., Smith, G. D., Heinrich, J., Jarvelin, M.-R., Jaddoe, V. W. V., The Cohorts for Heart and Aging Research in Genetic Epidemiology (CHARGE) Consortium, EArly Genetics and Lifecourse Epidemiology (EAGLE) Consortium, & Early Growth Genetics (EGG) Consortium (2012). Common variants at 12q15 and 12q24 are associated with infant head circumference. Nature Genetics, 44(5), 532-538. doi:10.1038/ng.2238.
Abstract
To identify genetic variants associated with head circumference in infancy, we performed a meta-analysis of seven genome-wide association studies (GWAS) (N = 10,768 individuals of European ancestry enrolled in pregnancy and/or birth cohorts) and followed up three lead signals in six replication studies (combined N = 19,089). rs7980687 on chromosome 12q24 (P = 8.1 × 10(-9)) and rs1042725 on chromosome 12q15 (P = 2.8 × 10(-10)) were robustly associated with head circumference in infancy. Although these loci have previously been associated with adult height, their effects on infant head circumference were largely independent of height (P = 3.8 × 10(-7) for rs7980687 and P = 1.3 × 10(-7) for rs1042725 after adjustment for infant height). A third signal, rs11655470 on chromosome 17q21, showed suggestive evidence of association with head circumference (P = 3.9 × 10(-6)). SNPs correlated to the 17q21 signal have shown genome-wide association with adult intracranial volume, Parkinson's disease and other neurodegenerative diseases, indicating that a common genetic variant in this region might link early brain growth with neurological disease in later life.Additional information
http://www.nature.com/ng/journal/v44/n5/full/ng.2238.html#supplementary-informa…
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