Displaying 1 - 17 of 17
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Doust, C., Fontanillas, P., Eising, E., Gordon, S. D., Wang, Z., Alagöz, G., Molz, B., 23andMe Research Team, Quantitative Trait Working Group of the GenLang Consortium, St Pourcain, B., Francks, C., Marioni, R. E., Zhao, J., Paracchini, S., Talcott, J. B., Monaco, A. P., Stein, J. F., Gruen, J. R., Olson, R. K., Willcutt, E. G., DeFries, J. C., Pennington, B. F. and 7 moreDoust, C., Fontanillas, P., Eising, E., Gordon, S. D., Wang, Z., Alagöz, G., Molz, B., 23andMe Research Team, Quantitative Trait Working Group of the GenLang Consortium, St Pourcain, B., Francks, C., Marioni, R. E., Zhao, J., Paracchini, S., Talcott, J. B., Monaco, A. P., Stein, J. F., Gruen, J. R., Olson, R. K., Willcutt, E. G., DeFries, J. C., Pennington, B. F., Smith, S. D., Wright, M. J., Martin, N. G., Auton, A., Bates, T. C., Fisher, S. E., & Luciano, M. (2022). Discovery of 42 genome-wide significant loci associated with dyslexia. Nature Genetics. doi:10.1038/s41588-022-01192-y.
Abstract
Reading and writing are crucial life skills but roughly one in ten children are affected by dyslexia, which can persist into adulthood. Family studies of dyslexia suggest heritability up to 70%, yet few convincing genetic markers have been found. Here we performed a genome-wide association study of 51,800 adults self-reporting a dyslexia diagnosis and 1,087,070 controls and identified 42 independent genome-wide significant loci: 15 in genes linked to cognitive ability/educational attainment, and 27 new and potentially more specific to dyslexia. We validated 23 loci (13 new) in independent cohorts of Chinese and European ancestry. Genetic etiology of dyslexia was similar between sexes, and genetic covariance with many traits was found, including ambidexterity, but not neuroanatomical measures of language-related circuitry. Dyslexia polygenic scores explained up to 6% of variance in reading traits, and might in future contribute to earlier identification and remediation of dyslexia. -
Eising, E., Mirza-Schreiber, N., De Zeeuw, E. L., Wang, C. A., Truong, D. T., Allegrini, A. G., Shapland, C. Y., Zhu, G., Wigg, K. G., Gerritse, M., Molz, B., Alagöz, G., Gialluisi, A., Abbondanza, F., Rimfeld, K., Van Donkelaar, M. M. J., Liao, Z., Jansen, P. R., Andlauer, T. F. M., Bates, T. C. and 70 moreEising, E., Mirza-Schreiber, N., De Zeeuw, E. L., Wang, C. A., Truong, D. T., Allegrini, A. G., Shapland, C. Y., Zhu, G., Wigg, K. G., Gerritse, M., Molz, B., Alagöz, G., Gialluisi, A., Abbondanza, F., Rimfeld, K., Van Donkelaar, M. M. J., Liao, Z., Jansen, P. R., Andlauer, T. F. M., Bates, T. C., Bernard, M., Blokland, K., Børglum, A. D., Bourgeron, T., Brandeis, D., Ceroni, F., Dale, P. S., Landerl, K., Lyytinen, H., De Jong, P. F., DeFries, J. C., Demontis, D., Feng, Y., Gordon, S. D., Guger, S. L., Hayiou-Thomas, M. E., Hernández-Cabrera, J. A., Hottenga, J.-J., Hulme, C., Kerr, E. N., Koomar, T., Lovett, M. W., Martin, N. G., Martinelli, A., Maurer, U., Michaelson, J. J., Moll, K., Monaco, A. P., Morgan, A. T., Nöthen, M. M., Pausova, Z., Pennell, C. E., Pennington, B. F., Price, K. M., Rajagopal, V. M., Ramus, F., Richer, L., Simpson, N. H., Smith, S., Snowling, M. J., Stein, J., Strug, L. J., Talcott, J. B., Tiemeier, H., Van de Schroeff, M. M. P., Verhoef, E., Watkins, K. E., Wilkinson, M., Wright, M. J., Barr, C. L., Boomsma, D. I., Carreiras, M., Franken, M.-C.-J., Gruen, J. R., Luciano, M., Müller-Myhsok, B., Newbury, D. F., Olson, R. K., Paracchini, S., Paus, T., Plomin, R., Schulte-Körne, G., Reilly, S., Tomblin, J. B., Van Bergen, E., Whitehouse, A. J., Willcutt, E. G., St Pourcain, B., Francks, C., & Fisher, S. E. (2022). Genome-wide analyses of individual differences in quantitatively assessed reading- and language-related skills in up to 34,000 people. Proceedings of the National Academy of Sciences of the United States of America, 119(35): e2202764119. doi:10.1073/pnas.2202764119.
Abstract
The use of spoken and written language is a fundamental human capacity. Individual differences in reading- and language-related skills are influenced by genetic variation, with twin-based heritability estimates of 30 to 80% depending on the trait. The genetic architecture is complex, heterogeneous, and multifactorial, but investigations of contributions of single-nucleotide polymorphisms (SNPs) were thus far underpowered. We present a multicohort genome-wide association study (GWAS) of five traits assessed individually using psychometric measures (word reading, nonword reading, spelling, phoneme awareness, and nonword repetition) in samples of 13,633 to 33,959 participants aged 5 to 26 y. We identified genome-wide significant association with word reading (rs11208009, P = 1.098 × 10−8) at a locus that has not been associated with intelligence or educational attainment. All five reading-/language-related traits showed robust SNP heritability, accounting for 13 to 26% of trait variability. Genomic structural equation modeling revealed a shared genetic factor explaining most of the variation in word/nonword reading, spelling, and phoneme awareness, which only partially overlapped with genetic variation contributing to nonword repetition, intelligence, and educational attainment. A multivariate GWAS of word/nonword reading, spelling, and phoneme awareness maximized power for follow-up investigation. Genetic correlation analysis with neuroimaging traits identified an association with the surface area of the banks of the left superior temporal sulcus, a brain region linked to the processing of spoken and written language. Heritability was enriched for genomic elements regulating gene expression in the fetal brain and in chromosomal regions that are depleted of Neanderthal variants. Together, these results provide avenues for deciphering the biological underpinnings of uniquely human traits. -
Neumann, A., Nolte, I. M., Pappa, I., Ahluwalia, T. S., Pettersson, E., Rodriguez, A., Whitehouse, A., Van Beijsterveldt, C. E. M., Benyamin, B., Hammerschlag, A. R., Helmer, Q., Karhunen, V., Krapohl, E., Lu, Y., Van der Most, P. J., Palviainen, T., St Pourcain, B., Seppälä, I., Suarez, A., Vilor-Tejedor, N. and 41 moreNeumann, A., Nolte, I. M., Pappa, I., Ahluwalia, T. S., Pettersson, E., Rodriguez, A., Whitehouse, A., Van Beijsterveldt, C. E. M., Benyamin, B., Hammerschlag, A. R., Helmer, Q., Karhunen, V., Krapohl, E., Lu, Y., Van der Most, P. J., Palviainen, T., St Pourcain, B., Seppälä, I., Suarez, A., Vilor-Tejedor, N., Tiesler, C. M. T., Wang, C., Wills, A., Zhou, A., Alemany, S., Bisgaard, H., Bønnelykke, K., Davies, G. E., Hakulinen, C., Henders, A. K., Hyppönen, E., Stokholm, J., Bartels, M., Hottenga, J.-J., Heinrich, J., Hewitt, J., Keltikangas-Järvinen, L., Korhonen, T., Kaprio, J., Lahti, J., Lahti-Pulkkinen, M., Lehtimäki, T., Middeldorp, C. M., Najman, J. M., Pennell, C., Power, C., Oldehinkel, A. J., Plomin, R., Räikkönen, K., Raitakari, O. T., Rimfeld, K., Sass, L., Snieder, H., Standl, M., Sunyer, J., Williams, G. M., Bakermans-Kranenburg, M. J., Boomsma, D. I., Van IJzendoorn, M. H., Hartman, C. A., & Tiemeier, H. (2022). A genome-wide association study of total child psychiatric problems scores. PLOS ONE, 17(8): e0273116. doi:10.1371/journal.pone.0273116.
Abstract
Substantial genetic correlations have been reported across psychiatric disorders and numerous cross-disorder genetic variants have been detected. To identify the genetic variants underlying general psychopathology in childhood, we performed a genome-wide association study using a total psychiatric problem score. We analyzed 6,844,199 common SNPs in 38,418 school-aged children from 20 population-based cohorts participating in the EAGLE consortium. The SNP heritability of total psychiatric problems was 5.4% (SE = 0.01) and two loci reached genome-wide significance: rs10767094 and rs202005905. We also observed an association of SBF2, a gene associated with neuroticism in previous GWAS, with total psychiatric problems. The genetic effects underlying the total score were shared with common psychiatric disorders only (attention-deficit/hyperactivity disorder, anxiety, depression, insomnia) (rG > 0.49), but not with autism or the less common adult disorders (schizophrenia, bipolar disorder, or eating disorders) (rG < 0.01). Importantly, the total psychiatric problem score also showed at least a moderate genetic correlation with intelligence, educational attainment, wellbeing, smoking, and body fat (rG > 0.29). The results suggest that many common genetic variants are associated with childhood psychiatric symptoms and related phenotypes in general instead of with specific symptoms. Further research is needed to establish causality and pleiotropic mechanisms between related traits.Additional information
Full summary results -
Okbay, A., Wu, Y., Wang, N., Jayashankar, H., Bennett, M., Nehzati, S. M., Sidorenko, J., Kweon, H., Goldman, G., Gjorgjieva, T., Jiang, Y., Hicks, B., Tian, C., Hinds, D. A., Ahlskog, R., Magnusson, P. K. E., Oskarsson, S., Hayward, C., Campbell, A., Porteous, D. J. and 18 moreOkbay, A., Wu, Y., Wang, N., Jayashankar, H., Bennett, M., Nehzati, S. M., Sidorenko, J., Kweon, H., Goldman, G., Gjorgjieva, T., Jiang, Y., Hicks, B., Tian, C., Hinds, D. A., Ahlskog, R., Magnusson, P. K. E., Oskarsson, S., Hayward, C., Campbell, A., Porteous, D. J., Freese, J., Herd, P., 23andMe Research Team, Social Science Genetic Association Consortium, Watson, C., Jala, J., Conley, D., Koellinger, P. D., Johannesson, M., Laibson, D., Meyer, M. N., Lee, J. J., Kong, A., Yengo, L., Cesarini, D., Turley, P., Visscher, P. M., Beauchamp, J. P., Benjamin, D. J., & Young, A. I. (2022). Polygenic prediction of educational attainment within and between families from genome-wide association analyses in 3 million individuals. Nature Genetics, 54, 437-449. doi:10.1038/s41588-022-01016-z.
Abstract
We conduct a genome-wide association study (GWAS) of educational attainment (EA) in a sample of ~3 million individuals and identify 3,952 approximately uncorrelated genome-wide-significant single-nucleotide polymorphisms (SNPs). A genome-wide polygenic predictor, or polygenic index (PGI), explains 12–16% of EA variance and contributes to risk prediction for ten diseases. Direct effects (i.e., controlling for parental PGIs) explain roughly half the PGI’s magnitude of association with EA and other phenotypes. The correlation between mate-pair PGIs is far too large to be consistent with phenotypic assortment alone, implying additional assortment on PGI-associated factors. In an additional GWAS of dominance deviations from the additive model, we identify no genome-wide-significant SNPs, and a separate X-chromosome additive GWAS identifies 57.Additional information
supplementary information -
Price, K. M., Wigg, K. G., Eising, E., Feng, Y., Blokland, K., Wilkinson, M., Kerr, E. N., Guger, S. L., Quantitative Trait Working Group of the GenLang Consortium, Fisher, S. E., Lovett, M. W., Strug, L. J., & Barr, C. L. (2022). Hypothesis-driven genome-wide association studies provide novel insights into genetics of reading disabilities. Translational Psychiatry, 12: 495. doi:10.1038/s41398-022-02250-z.
Abstract
Reading Disability (RD) is often characterized by difficulties in the phonology of the language. While the molecular mechanisms underlying it are largely undetermined, loci are being revealed by genome-wide association studies (GWAS). In a previous GWAS for word reading (Price, 2020), we observed that top single-nucleotide polymorphisms (SNPs) were located near to or in genes involved in neuronal migration/axon guidance (NM/AG) or loci implicated in autism spectrum disorder (ASD). A prominent theory of RD etiology posits that it involves disturbed neuronal migration, while potential links between RD-ASD have not been extensively investigated. To improve power to identify associated loci, we up-weighted variants involved in NM/AG or ASD, separately, and performed a new Hypothesis-Driven (HD)–GWAS. The approach was applied to a Toronto RD sample and a meta-analysis of the GenLang Consortium. For the Toronto sample (n = 624), no SNPs reached significance; however, by gene-set analysis, the joint contribution of ASD-related genes passed the threshold (p~1.45 × 10–2, threshold = 2.5 × 10–2). For the GenLang Cohort (n = 26,558), SNPs in DOCK7 and CDH4 showed significant association for the NM/AG hypothesis (sFDR q = 1.02 × 10–2). To make the GenLang dataset more similar to Toronto, we repeated the analysis restricting to samples selected for reading/language deficits (n = 4152). In this GenLang selected subset, we found significant association for a locus intergenic between BTG3-C21orf91 for both hypotheses (sFDR q < 9.00 × 10–4). This study contributes candidate loci to the genetics of word reading. Data also suggest that, although different variants may be involved, alleles implicated in ASD risk may be found in the same genes as those implicated in word reading. This finding is limited to the Toronto sample suggesting that ascertainment influences genetic associations. -
Schlag, F., Allegrini, A. G., Buitelaar, J., Verhoef, E., Van Donkelaar, M. M. J., Plomin, R., Rimfeld, K., Fisher, S. E., & St Pourcain, B. (2022). Polygenic risk for mental disorder reveals distinct association profiles across social behaviour in the general population. Molecular Psychiatry, 27, 1588-1598. doi:10.1038/s41380-021-01419-0.
Abstract
Many mental health conditions present a spectrum of social difficulties that overlaps with social behaviour in the general population including shared but little characterised genetic links. Here, we systematically investigate heterogeneity in shared genetic liabilities with attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorders (ASD), bipolar disorder (BP), major depression (MD) and schizophrenia across a spectrum of different social symptoms. Longitudinally assessed low-prosociality and peer-problem scores in two UK population-based cohorts (4–17 years; parent- and teacher-reports; Avon Longitudinal Study of Parents and Children(ALSPAC): N ≤ 6,174; Twins Early Development Study(TEDS): N ≤ 7,112) were regressed on polygenic risk scores for disorder, as informed by genome-wide summary statistics from large consortia, using negative binomial regression models. Across ALSPAC and TEDS, we replicated univariate polygenic associations between social behaviour and risk for ADHD, MD and schizophrenia. Modelling variation in univariate genetic effects jointly using random-effect meta-regression revealed evidence for polygenic links between social behaviour and ADHD, ASD, MD, and schizophrenia risk, but not BP. Differences in age, reporter and social trait captured 45–88% in univariate effect variation. Cross-disorder adjusted analyses demonstrated that age-related heterogeneity in univariate effects is shared across mental health conditions, while reporter- and social trait-specific heterogeneity captures disorder-specific profiles. In particular, ADHD, MD, and ASD polygenic risk were more strongly linked to peer problems than low prosociality, while schizophrenia was associated with low prosociality only. The identified association profiles suggest differences in the social genetic architecture across mental disorders when investigating polygenic overlap with population-based social symptoms spanning 13 years of child and adolescent development. -
Vogelezang, S., Bradfield, J. P., the Early Growth Genetics Consortium, Grant, S. F. A., Felix, J. F., & Jaddoe, V. W. V. (2022). Genetics of early-life head circumference and genetic correlations with neurological, psychiatric and cognitive outcomes. BMC Medical Genomics, 15: 124. doi:10.1186/s12920-022-01281-1.
Abstract
Background
Head circumference is associated with intelligence and tracks from childhood into adulthood.
Methods
We performed a genome-wide association study meta-analysis and follow-up of head circumference in a total of 29,192 participants between 6 and 30 months of age.
Results
Seven loci reached genome-wide significance in the combined discovery and replication analysis of which three loci near ARFGEF2, MYCL1, and TOP1, were novel. We observed positive genetic correlations for early-life head circumference with adult intracranial volume, years of schooling, childhood and adult intelligence, but not with adult psychiatric, neurological, or personality-related phenotypes.
Conclusions
The results of this study indicate that the biological processes underlying early-life head circumference overlap largely with those of adult head circumference. The associations of early-life head circumference with cognitive outcomes across the life course are partly explained by genetics. -
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… -
Glaser, B., Nikolov, I., Chubb, D., Hamshere, M. L., Segurado, R., Moskvina, V., & Holmans, P. (2007). Analyses of single marker and pairwise effects of candidate loci for rheumatoid arthritis using logistic regression and random forests. BMC Proceedings, 1(Suppl 1): 54.
Abstract
Using parametric and nonparametric techniques, our study investigated the presence of single locus and pairwise effects between 20 markers of the Genetic Analysis Workshop 15 (GAW15) North American Rheumatoid Arthritis Consortium (NARAC) candidate gene data set (Problem 2), analyzing 463 independent patients and 855 controls. Specifically, our work examined the correspondence between logistic regression (LR) analysis of single-locus and pairwise interaction effects, and random forest (RF) single and joint importance measures. For this comparison, we selected small but stable RFs (500 trees), which showed strong correlations (r~0.98) between their importance measures and those by RFs grown on 5000 trees. Both RF importance measures captured most of the LR single-locus and pairwise interaction effects, while joint importance measures also corresponded to full LR models containing main and interaction effects. We furthermore showed that RF measures were particularly sensitive to data imputation. The most consistent pairwise effect on rheumatoid arthritis was found between two markers within MAP3K7IP2/SUMO4 on 6q25.1, although LR and RFs assigned different significance levels. Within a hypothetical two-stage design, pairwise LR analysis of all markers with significant RF single importance would have reduced the number of possible combinations in our small data set by 61%, whereas joint importance measures would have been less efficient for marker pair reduction. This suggests that RF single importance measures, which are able to detect a wide range of interaction effects and are computationally very efficient, might be exploited as pre-screening tool for larger association studies. Follow-up analysis, such as by LR, is required since RFs do not indicate highrisk genotype combinations. -
Hamshere, M. L., Segurado, R., Moskvina, V., Nikolov, I., Glaser, B., & Holmans, P. A. (2007). Large-scale linkage analysis of 1302 affected relative pairs with rheumatoid arthritis. BMC Proceedings, 1 (Suppl 1), S100.
Abstract
Rheumatoid arthritis is the most common systematic autoimmune disease and its etiology is believed to have both strong genetic and environmental components. We demonstrate the utility of including genetic and clinical phenotypes as covariates within a linkage analysis framework to search for rheumatoid arthritis susceptibility loci. The raw genotypes of 1302 affected relative pairs were combined from four large family-based samples (North American Rheumatoid Arthritis Consortium, United Kingdom, European Consortium on Rheumatoid Arthritis Families, and Canada). The familiality of the clinical phenotypes was assessed. The affected relative pairs were subjected to autosomal multipoint affected relative-pair linkage analysis. Covariates were included in the linkage analysis to take account of heterogeneity within the sample. Evidence of familiality was observed with age at onset (p <} 0.001) and rheumatoid factor (RF) IgM (p {< 0.001), but not definite erosions (p = 0.21). Genome-wide significant evidence for linkage was observed on chromosome 6. Genome-wide suggestive evidence for linkage was observed on chromosomes 13 and 20 when conditioning on age at onset, chromosome 15 conditional on gender, and chromosome 19 conditional on RF IgM after allowing for multiple testing of covariates. -
Segurado, R., Hamshere, M. L., Glaser, B., Nikolov, I., Moskvina, V., & Holmans, P. A. (2007). Combining linkage data sets for meta-analysis and mega-analysis: the GAW15 rheumatoid arthritis data set. BMC Proceedings, 1(Suppl 1): S104.
Abstract
We have used the genome-wide marker genotypes from Genetic Analysis Workshop 15 Problem 2 to explore joint evidence for genetic linkage to rheumatoid arthritis across several samples. The data consisted of four high-density genome scans on samples selected for rheumatoid arthritis. We cleaned the data, removed intermarker linkage disequilibrium, and assembled the samples onto a common genetic map using genome sequence positions as a reference for map interpolation. The individual studies were combined first at the genotype level (mega-analysis) prior to a multipoint linkage analysis on the combined sample, and second using the genome scan meta-analysis method after linkage analysis of each sample. The two approaches were compared, and give strong support to the HLA locus on chromosome 6 as a susceptibility locus. Other regions of interest include loci on chromosomes 11, 2, and 12. -
Ziegler, A., DeStefano, A. L., König, I. R., Bardel, C., Brinza, D., Bull, S., Cai, Z., Glaser, B., Jiang, W., Lee, K. E., Li, C. X., Li, J., Li, X., Majoram, P., Meng, Y., Nicodemus, K. K., Platt, A., Schwarz, D. F., Shi, W., Shugart, Y. Y. and 7 moreZiegler, A., DeStefano, A. L., König, I. R., Bardel, C., Brinza, D., Bull, S., Cai, Z., Glaser, B., Jiang, W., Lee, K. E., Li, C. X., Li, J., Li, X., Majoram, P., Meng, Y., Nicodemus, K. K., Platt, A., Schwarz, D. F., Shi, W., Shugart, Y. Y., Stassen, H. H., Sun, Y. V., Won, S., Wang, W., Wahba, G., Zagaar, U. A., & Zhao, Z. (2007). Data mining, neural nets, trees–problems 2 and 3 of Genetic Analysis Workshop 15. Genetic Epidemiology, 31(Suppl 1), S51-S60. doi:10.1002/gepi.20280.
Abstract
Genome-wide association studies using thousands to hundreds of thousands of single nucleotide polymorphism (SNP) markers and region-wide association studies using a dense panel of SNPs are already in use to identify disease susceptibility genes and to predict disease risk in individuals. Because these tasks become increasingly important, three different data sets were provided for the Genetic Analysis Workshop 15, thus allowing examination of various novel and existing data mining methods for both classification and identification of disease susceptibility genes, gene by gene or gene by environment interaction. The approach most often applied in this presentation group was random forests because of its simplicity, elegance, and robustness. It was used for prediction and for screening for interesting SNPs in a first step. The logistic tree with unbiased selection approach appeared to be an interesting alternative to efficiently select interesting SNPs. Machine learning, specifically ensemble methods, might be useful as pre-screening tools for large-scale association studies because they can be less prone to overfitting, can be less computer processor time intensive, can easily include pair-wise and higher-order interactions compared with standard statistical approaches and can also have a high capability for classification. However, improved implementations that are able to deal with hundreds of thousands of SNPs at a time are required.
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