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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 -
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.Additional information
6887519.zip http://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1007501#s… -
Lee, J. J., Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., Nguyen-Viet, T. A., Bowers, P., Sidorenko, J., Linnér, R. K., Fontana, M. A., Kundu, T., Lee, C., Li, H., Li, R., Royer, R., Timshel, P. N., Walters, R. K., Willoughby, E. A., Yengo, L. and 57 moreLee, J. J., Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., Nguyen-Viet, T. A., Bowers, P., Sidorenko, J., Linnér, R. K., Fontana, M. A., Kundu, T., Lee, C., Li, H., Li, R., Royer, R., Timshel, P. N., Walters, R. K., Willoughby, E. A., Yengo, L., 23andMe Research Team, COGENT (Cognitive Genomics Consortium), Social Science Genetic Association Consortium, Alver, M., Bao, Y., Clark, D. W., Day, F. R., Furlotte, N. A., Joshi, P. K., Kemper, K. E., Kleinman, A., Langenberg, C., Mägi, R., Trampush, J. W., Verma, S. S., Wu, Y., Lam, M., Zhao, J. H., Zheng, Z., Boardman, J. D., Campbell, H., Freese, J., Harris, K. M., Hayward, C., Herd, P., Kumari, M., Lencz, T., Luan, J., Malhotra, A. K., Metspalu, A., Milani, L., Ong, K. K., Perry, J. R. B., Porteous, D. J., Ritchie, M. D., Smart, M. C., Smith, B. H., Tung, J. Y., Wareham, N. J., Wilson, J. F., Beauchamp, J. P., Conley, D. C., Esko, T., Lehrer, S. F., Magnusson, P. K. E., Oskarsson, S., Pers, T. H., Robinson, M. R., Thom, K., Watson, C., Chabris, C. F., Meyer, M. N., Laibson, D. I., Yang, J., Johannesson, M., Koellinger, P. D., Turley, P., Visscher, P. M., Benjamin, D. J., & Cesarini, D. (2018). Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nature Genetics, 50(8), 1112-1121. doi:10.1038/s41588-018-0147-3.
Abstract
Here we conducted a large-scale genetic association analysis of educational attainment in a sample of approximately 1.1 million individuals and identify 1,271 independent genome-wide-significant SNPs. For the SNPs taken together, we found evidence of heterogeneous effects across environments. The SNPs implicate genes involved in brain-development processes and neuron-to-neuron communication. In a separate analysis of the X chromosome, we identify 10 independent genome-wide-significant SNPs and estimate a SNP heritability of around 0.3% in both men and women, consistent with partial dosage compensation. A joint (multi-phenotype) analysis of educational attainment and three related cognitive phenotypes generates polygenic scores that explain 11–13% of the variance in educational attainment and 7–10% of the variance in cognitive performance. This prediction accuracy substantially increases the utility of polygenic scores as tools in research. -
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.
Additional information
jcpp12913-sup-0001-supinfo.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 overlapAdditional information
https://ars.els-cdn.com/content/image/1-s2.0-S0006322317320085-mmc1.pdf -
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 symptomsAdditional information
mp2016198x1.docx -
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
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