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Genomic epidemiology of addictions and their consequences - national, Nordic and international dimensions. (263278)
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  • Open Access English
    Authors: 
    Eilis Hannon; Emma Dempster; Georgina Mansell; Joe Burrage; Nick Bass; Marc M. Bohlken; Aiden Corvin; Charles Curtis; David Dempster; Marta Di Forti; +36 more
    Countries: Finland, Netherlands, Turkey
    Project: AKA | Genomic epidemiology of a... (265240), AKA | Genomic epidemiology of a... (263278), AKA | Center of Excellence in C... (312073)

    We performed a systematic analysis of blood DNA methylation profiles from 4483 participants from seven independent cohorts identifying differentially methylated positions (DMPs) associated with psychosis, schizophrenia, and treatment-resistant schizophrenia. Psychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNA methylation data, with the largest differences seen in treatment-resistant schizophrenia patients. We implemented a stringent pipeline to meta-analyze epigenome-wide association study (EWAS) results across datasets, identifying 95 DMPs associated with psychosis and 1048 DMPs associated with schizophrenia, with evidence of colocalization to regions nominated by genetic association studies of disease. Many schizophrenia-associated DNA methylation differences were only present in patients with treatment-resistant schizophrenia, potentially reflecting exposure to the atypical antipsychotic clozapine. Our results highlight how DNA methylation data can be leveraged to identify physiological (e.g., differential cell counts) and environmental (e.g., smoking) factors associated with psychosis and molecular biomarkers of treatment-resistant schizophrenia.

  • Open Access
    Authors: 
    Tuomo Kiiskinen; Nina Mars; Teemu Palviainen; Jukka Koskela; Pietari Ripatti; Joel T. Rämö; Sanni Ruotsalainen; Aarno Palotie; Pamela A. F. Madden; Richard J. Rose; +5 more
    Publisher: Cold Spring Harbor Laboratory
    Project: AKA | Human model for genetic v... (285380), AKA | Center of Excellence in C... (312062), WT , AKA | Genomic epidemiology of a... (263278), AKA | Genomic epidemiology of a... (265240), AKA | Longitudinal birth cohort... (308248)

    AbstractObjectiveTo develop a highly polygenic risk score (PRS) for alcohol consumption and study whether it predicts alcohol-related morbidity and all-cause mortality.DesignBiobank-based prospective cohort studySettingFinnGen Study (Finland)Participants96,499 genotyped participants from the nationwide prospective FinnGen study and 36,499 participants from prospective cohorts (Health 2000, FINRISK, Twin Cohort) with detailed baseline data and up to 25 years of follow-up time.Main outcome measuresIncident alcohol-related morbidity and alcohol-related or all-cause mortality, based on hospitalizations, outpatient specialist care, drug purchases, and death reports.ResultsIn 96,499 FinnGen participants there were in total 4,785 first-observed incident alcohol-related health events. The PRS of alcohol consumption was associated with alcohol-related morbidity and the risk estimate (hazard ratio, HR) between the highest and lowest quintiles of the PRS was 1.67 [ 95 % confidence interval: 1.52-1.84], p=3.2*10−27). In 28,639 participants with comprehensive baseline data from prospective Health 2000 and FINRISK cohorts, 911 incident first alcohol-related events were observed. When adjusted for self-reported alcohol consumption, education, marital status, and gamma-glutamyl transferase blood levels, the risk estimate between the highest and lowest quintiles of the PRS was 1.58 (CI=[1.26-1.99], p=8.2*10−5). The PRS was also associated with all-cause mortality with a risk estimate of 1.33 between the highest and lowest quintiles (CI=[1.2-1.47], p=4.5e-08) in the adjusted model. In all 39,695 participants with self-reported alcohol consumption available, a 1 SD increase in the PRS was associated with 11.2 g (=0.93 drinks) higher weekly alcohol consumption (β=11.2 [9.85-12.58 g], p = 2.3*10−58).ConclusionsThe PRS for alcohol consumption associates for both alcohol-related morbidity and all-cause mortality. These findings underline the importance of heritable factors in alcohol-related behavior and the related health burden. The results highlight how measured genetic risk for an important behavioral risk factor can be used to predict related health outcomes.

  • Open Access English
    Authors: 
    Law, PJ; Timofeeva, M; Fernandez-Rozadilla, C; Broderick, P; Studd, J; Fernandez-Tajes, J; Farrington, S; Svinti, V; Palles, C; Orlando, G; +89 more
    Publisher: NATURE PUBLISHING GROUP
    Countries: United Kingdom, Croatia, Finland
    Project: EC | ENGAGE (201413), NIH | Colon Cancer Family Regis... (4UM1CA167551-04), UKRI | A genome-wide association... (BB/F019394/1), AKA | The Application of 'Omics... (139635), AKA | ELIXIR - Data for Life  E... (271642), AKA | Biomedinfra - Implementin... (263164), WT | A national DNA control se... (068545), NIH | Data sharing: the Colon C... (3U01CA167551-07S1), AKA | Center of Excellence in T... (312041), NIH | Imputation-based approach... (7U01CA188392-03),...

    Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide, and has a strong heritable basis. We report a genome-wide association analysis of 34,627 CRC cases and 71,379 controls of European ancestry that identifies SNPs at 31 new CRC risk loci. We also identify eight independent risk SNPs at the new and previously reported European CRC loci, and a further nine CRC SNPs at loci previously only identified in Asian populations. We use in situ promoter capture Hi-C (CHi-C), gene expression, and in silico annotation methods to identify likely target genes of CRC SNPs. Whilst these new SNP associations implicate target genes that are enriched for known CRC pathways such as Wnt and BMP, they also highlight novel pathways with no prior links to colorectal tumourigenesis. These findings provide further insight into CRC susceptibility and enhance the prospects of applying genetic risk scores to personalised screening and prevention. In colorectal cancer (CRC), finding loci associated with risk may give insight into disease aetiology. Here, the authors report a genome-wide association analysis in Europeans of 34,627 CRC cases and 71,379 controls, and find 31 new risk loci and 17 new risk SNPs at previously reported loci.

  • Open Access English
    Authors: 
    Middeldorp, Christel M.; Mahajan, Anubha; Horikoshi, Momoko; Robertson, Neil R.; Beaumont, Robin N.; Bradfield, Jonathan P.; Bustamante, Mariona; Cousminer, Diana L.; Day, Felix R.; De Silva, N. Maneka; +193 more
    Publisher: Springer Netherlands
    Countries: United Kingdom, United Kingdom, Germany, Switzerland, United Kingdom, Spain, United Kingdom, Denmark, United Kingdom, Netherlands ...
    Project: WT | Genome-wide association s... (084762), EC | GERONIMO (603794), NIH | A Genome-wide Association... (1R01HL087680-01), NIH | JH/CIDR Genotyping for Ge... (5U01HG004438-04), AKA | Northern Finland Birth Co... (285547), EC | MULTIEPIGEN (742927), WT | New insights from Neonata... (098395), AKA | Genetic and environmental... (141054), NIH | Genome Wide Association C... (5U01HG004446-04), EC | GLUCOSEGENES (323195),...

    We are grateful to all families and participants who took part in these studies. We also acknowledge and appreciate the unique efforts of the research teams and practitioners contributing to the collection of this wealth of data. C. M. M. is supported by funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 721567. J. F. F. has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 633595 (DynaHEALTH) and 733206 (LifeCycle). R. M. F. and R. N. B. are supported by Sir Henry Dale Fellowship (Wellcome Trust and Royal Society grant: WT104150). D. L. C. is funded by the American Diabetes Association Grant 1-17-PDF-077. D. O. M-K. was supported by Dutch Science Organization (ZonMW-VENI Grant 916.14.023). N. M. W. is supported by an Australian National Health and Medical Research Council Early Career Fellowship (APP1104818). T. S. A. was partially funded by the Gene-Diet Interactions in Obesity (GENDINOB) project on behalf of GOYA male cohort data management and analyses and acknowledges the same. S. D. was supported by National Institute of Health Research. T. M. F. is supported by the European Research Council grant: 323195 SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC. The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent Research Center at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation (www.metabol.ku.dk).H.H.is funded by The Children's Hospital of Philadelphia Endowed Chair in Genomic Research. A. T. H. is supported by the Wellcome Trust Senior Investigator Awards (WT098395), National Institute for Health Research (NIHR) Senior Investigator Award (NF-SI-0611-10219). J. Hebebrand received grants from German Research Society, German Ministry of Education and Research. M-F. H. is currently supported by an American Diabetes Association (ADA) Pathway Program Accelerator Early Investigator Award (1-15-ACE-26). S. J. is supported by Helse Vest no. 23929, Bergen Forskningsstiftelse and KG Jebsen Foundation and University of Bergen. J. K. has been supported by the Academy of Finland Research Professor program (grants 265240 & 263278). J. P. K. is funded by a University of Queensland Development Fellowship (UQFEL1718945). H. L. has served as a speaker for Eli-Lilly and Shire and has received research grants from Shire; all outside the submitted work. C. M. L is supported by the Li Ka Shing Foundation, WT-SSI/John Fell funds and by the NIHR Biomedical Research Centre, Oxford, by Widenlife and NIH (5P50HD028138-27). S. E. M. was funded by an NHMRC Senior Reseach Fellowship (APP1103623). K. Panoutsopoulou is funded by a career development fellowship (grant 20308) and by the Wellcome Trust (WT098051). C. P. at UCL Institute of Child Health, with support from the National Institute for Health Research Biomedical Research Centre at Great Ormond Street Hospital for Children NHS Foundation Trust and University College London. I. P. was funded in part by the Wellcome Trust (WT205915), and the European Union's Horizon 2020 research, the European Union FP7-IDEAS-ERC Advanced Grant (GEPIDIAB, ERC-AG -ERC-294785), and innovation programme (DYNAhealth, H2020-PHC-2014-633595). R. C. R. is supported by CRUK (grant number C18281/A19169). J. G. S. is supported by an NHMRC Practitioner Fellowship Grant (APP1105807). J. T.; r is funded by the European Regional Development Fund (ERDF), the European Social Fund (ESF), Convergence Programme for Cornwall and the Isles of Scilly and the Diabetes Research and Wellness Foundation Non-Clinical Fellowship. N. V-T. is funded by a pre-doctoral grant from the Agencia de Gestio d'Ajuts Universitaris i de Recerca (AGAUR) (2015 FI_B 00636), Generalitat de Catalunya. T. G. M. V was supported by ZonMW (TOP 40-00812-98-11010. J. F. W. is supported by the MRC Human Genetics Unit quinquennial programme QTL in Health and Disease. H. Y. is funded by Diabetes UK RD Lawrence fellowship (grant: 17/0005594). M. H. Z was supported by BBMRI-NL (CP2013-50). E. Z. is supported by the Wellcome Trust (098051). B. F. is supported by Novo Nordisk Foundation (12955) and an Oak Foundation Fellowship. S. S. and M-R. J. have received funding from the European Union's Horizon 2020 research and innovation programme [under grant agreement No 633595] for the DynaHEALTH action. P. R. N. was supported by the European Research Council (ERC), University of Bergen, KG Jebsen and Helse Vest. G. D. S. works within the MRC Integrative Epidemiology Unit at the University of Bristol (MC_UU_12013/1). D. A. L was supported by the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement (Grant number 669545; DevelopObese), US National Institute of Health (grant: R01 DK10324), the UK Medical Research Council (grant: MC_UU_00011/6), Wellcome Trust GWAS grant (WT088806), an NIHR Senior Investigator Award (NF-SI-0611-10196) and the NIHR Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol. L. Paternoster was supported by the UK Medical Research Council Unit grants MC_UU_12013_5. N. J. T. is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 102215/2/13/2), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC) and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). V.W.V.J. received an additional grant from the Netherlands Organization for Health Research and Development (NWO, ZonMw-VIDI 016.136.361), a European Research Council Consolidator Grant (ERC-2014-CoG-648916) and funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 633595 (DynaHEALTH) and 733206 (LifeCycle). D. M. E. is funded by the UK Medical Research Council Unit grant MC_UU_12013_4, Australian Research Council Future Fellowship (FT130101709) and a NHMRC Senior Research Fellowship (GNT1137714). S. F. A. G. is funded by the Daniel B. Burke Endowed Chair for Diabetes Research and R01 HD056465. D. I. B. is supported by Spinozapremie (NWO-56-464-14192) and the Royal Netherlands Academy of Science Professor Award (PAH/6635) to DIB. M. I. M. is a Wellcome Senior Investgator and NIHR Senior Investigator supported by the Wellcome (090532, 098381, 203141), NIHR (NF-SI-0617-10090) and the US National Institute of Health (grant: R01 DK10324), the UK Medical Research Council (grant: MCiabetes UK RD Lawrence fellowship (grant: 17/0005594). M. H. Z was supported by BBMRI-NLNIHR Biomedical Research Centre, Oxford. The views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.

  • Open Access English
    Authors: 
    Richa Gupta; Jenny van Dongen; Yu Fu; Abdel Abdellaoui; Rachel F. Tyndale; Vidya Velagapudi; Dorret I. Boomsma; Tellervo Korhonen; Jaakko Kaprio; Anu Loukola; +1 more
    Countries: Netherlands, Finland
    Project: AKA | CoE in Complex Disease Ge... (213506), NWO | BBMRI-NL (2300154272), AKA | Epigenetic pathways to ob... (297908), AKA | Center of Excellence in C... (129680), CIHR , AKA | Genomic epidemiology of a... (263278), EC | GMI (230374), AKA | Genomic epidemiology of a... (265240)

    Background DNA methylation alteration extensively associates with smoking and is a plausible link between smoking and adverse health. We examined the association between epigenome-wide DNA methylation and serum cotinine levels as a proxy of nicotine exposure and smoking quantity, assessed the role of SNPs in these associations, and evaluated molecular mediation by methylation in a sample of biochemically verified current smokers (N = 310). Results DNA methylation at 50 CpG sites was associated (FDR < 0.05) with cotinine levels, 17 of which are novel associations. As cotinine levels are influenced not only by nicotine intake but also by CYP2A6-mediated nicotine metabolism rate, we performed secondary analyses adjusting for genetic risk score of nicotine metabolism rate and identified five additional novel associations. We further assessed the potential role of genetic variants in the detected association between methylation and cotinine levels observing 124 cis and 3898 trans methylation quantitative trait loci (meQTLs). Nineteen of these SNPs were also associated with cotinine levels (FDR < 0.05). Further, at seven CpG sites, we observed a trend (P < 0.05) that altered DNA methylation mediates the effect of SNPs on nicotine exposure rather than a direct consequence of smoking. Finally, we performed replication of our findings in two independent cohorts of biochemically verified smokers (N = 450 and N = 79). Conclusions Using cotinine, a biomarker of nicotine exposure, we replicated and extended identification of novel epigenetic associations in smoking-related genes. We also demonstrated that DNA methylation in some of the identified loci is driven by the underlying genotype and may mediate the causal effect of genotype on cotinine levels. Electronic supplementary material The online version of this article (10.1186/s13148-018-0606-9) contains supplementary material, which is available to authorized users.

  • Open Access
    Authors: 
    Gupta, Richa; Dongen, Jenny; Fu, Yu; Abdellaoui, Abdel; Tyndale, Rachel; Velagapudi, Vidya; Dorret Boomsma; Korhonen, Tellervo; Kaprio, Jaakko; Loukola, Anu; +1 more
    Publisher: figshare
    Project: AKA | Center of Excellence in C... (129680), CIHR , AKA | CoE in Complex Disease Ge... (213506), NWO | BBMRI-NL (2300154272), AKA | Epigenetic pathways to ob... (297908), EC | GMI (230374), AKA | Genomic epidemiology of a... (263278), AKA | Genomic epidemiology of a... (265240)

    Figure S3. Mediation analysis to assess whether DNA methylation is a causal mediator to the observed association between genetic variants and cotinine levels. (PDF 588 kb)

  • Open Access
    Authors: 
    Gupta, Richa; Dongen, Jenny; Fu, Yu; Abdellaoui, Abdel; Tyndale, Rachel; Velagapudi, Vidya; Dorret Boomsma; Korhonen, Tellervo; Kaprio, Jaakko; Loukola, Anu; +1 more
    Publisher: figshare
    Project: CIHR , AKA | Center of Excellence in C... (129680), EC | GMI (230374), AKA | Genomic epidemiology of a... (265240), AKA | Genomic epidemiology of a... (263278), AKA | CoE in Complex Disease Ge... (213506), NWO | BBMRI-NL (2300154272), AKA | Epigenetic pathways to ob... (297908)

    Figure S2. QQ plot for genetic association analysis of cotinine levels and 46,780 SNPs in 40 genes. (PDF 17 kb)

  • Open Access
    Authors: 
    Gupta, Richa; Dongen, Jenny; Fu, Yu; Abdellaoui, Abdel; Tyndale, Rachel; Velagapudi, Vidya; Dorret Boomsma; Korhonen, Tellervo; Kaprio, Jaakko; Loukola, Anu; +1 more
    Publisher: figshare
    Project: AKA | Genomic epidemiology of a... (263278), EC | GMI (230374), AKA | Genomic epidemiology of a... (265240), CIHR , AKA | Center of Excellence in C... (129680), AKA | CoE in Complex Disease Ge... (213506), NWO | BBMRI-NL (2300154272), AKA | Epigenetic pathways to ob... (297908)

    Figure S1. Manhattan and QQ plots showing epigenome-wide association results from secondary analysis when accounting for the rate of nicotine metabolism using a GRS. (A) QQ plot showing observed versus expected − log10(P) for association at all loci. (B) Manhattan plot showing chromosomal locations of − log10(P) for association at each locus. All CpG sites with FDR

  • Open Access
    Authors: 
    Yoshie Yokoyama; Aline Jelenkovic; Yoon-Mi Hur; Reijo Sund; Corrado Fagnani; Maria Antonietta Stazi; Sonia Brescianini; Fuling Ji; Feng Ning; Zengchang Pang; +50 more
    Publisher: Oxford University Press (OUP)
    Countries: United Kingdom, Finland, Denmark, Netherlands
    Project: AKA | Indicators of marginaliza... (264146), AKA | Genomic epidemiology of a... (263278), CIHR , AKA | Genomic epidemiology of a... (265240), AKA | Genetic and environmental... (141054), SSHRC , AKA | Predictors, neuropsycholo... (118555), AKA | Oxygenology of soil (205585)

    Background: The genetic architecture of birth size may differ geographically and over time. We examined differences in the genetic and environmental contributions to birth weight, length, and ponderal index (PI) across geographic-cultural regions (Europe, North-America and Australia, and East-Asia) and across birth cohorts and how gestational age modifies these effects.Methods: Data from 26 twin cohorts in 16 countries including 57613 monozygotic and dizygotic twin pairs were pooled. Genetic and environmental variations of birth size were estimated using genetic structural equation modeling.Results: The variance of birth weight and length was predominantly explained by shared environmental factors, whereas the variance of PI was explained both by shared and unique environmental factors. Genetic variance contributing to birth size was small. Adjusting for gestational age decreased the proportions of shared environmental variance and increased the propositions of unique environmental variance. Genetic variance was similar in the geographic-cultural regions, but shared environmental variance was smaller in East-Asia than in Europe and North-America and Australia. The total variance and shared environmental variance of birth length and PI were greater from the birth cohort 1990-1999 onwards compared with the birth cohorts from 1970-1979 to 1980-1989.Conclusion: The contribution of genetic factors to birth size is smaller than that of shared environmental factors, which is partly explained by gestational age. Shared environmental variances of birth length and PI were greater in the latest birth cohorts and differed also across geographic-cultural regions. Shared environmental factors are important when explaining differences in the variation of birth size globally and over time.

  • Open Access English
    Authors: 
    Aline Jelenkovic; Yoshie Yokoyama; Reijo Sund; Yoon-Mi Hur; Jennifer R. Harris; Ingunn Brandt; Thomas Sevenius Nilsen; Syuichi Ooki; Vilhelmina Ullemar; Catarina Almqvist; +59 more
    Countries: Finland, United Kingdom, Denmark, Netherlands, Belgium, Spain, United Kingdom, Denmark, Belgium, Norway
    Project: AKA | Macro level variation in ... (266592), AKA | Indicators of marginaliza... (264146), CIHR , SSHRC , AKA | Individualized treatments... (314383), AKA | Oxygenology of soil (205585), AKA | Sequelae of metabolic com... (266286), AKA | Predictors, neuropsycholo... (118555), AKA | Genetic and environmental... (141054), AKA | Genomic epidemiology of a... (263278),...

    Background: There is evidence that birth size is positively associated with height in later life, but it remains unclear whether this is explained by genetic factors or the intrauterine environment. Aim: To analyze the associations of birth weight, length and ponderal index with height from infancy through adulthood within mono- and dizygotic twin pairs, which provides insights into the role of genetic and environmental individual-specific factors. Methods: This study is based on the data from 28 twin cohorts in 17 countries. The pooled data included 41,852 complete twin pairs (55% monozygotic and 45% same-sex dizygotic) with information on birth weight and a total of 112,409 paired height measurements at ages ranging from 1 to 69 years. Birth length was available for 19,881 complete twin pairs, with a total of 72,692 paired height measurements. The association between birth size and later height was analyzed at both the individual and within-pair level by linear regression analyses. Results: Within twin pairs, regression coefficients showed that a 1-kg increase in birth weight and a 1-cm increase in birth length were associated with 1.14-4.25 cm and 0.18-0.90 cm taller height, respectively. The magnitude of the associations was generally greater within dizygotic than within monozygotic twin pairs, and this difference between zygosities was more pronounced for birth length. Conclusion: Both genetic and individual-specific environmental factors play a role in the association between birth size and later height from infancy to adulthood, with a larger role for genetics in the association with birth length than with birth weight. This work was supported by the Academy of Finland (grant number #266592). The Australian Twin Registry is supported by a Centre of Research Excellence (grant ID 1079102) from the National Health and Medical Research Council administered by the University of Melbourne. The Boston University Twin Project is funded by grants (#R01 HD068435 #R01 MH062375) from the National Institutes of Health to K. Saudino. The Carolina African American Twin Study of Aging (CAATSA) was funded by a grant from the National Institute on Aging (grant 1RO1-AG13662-01A2) to K. E. Whitfield. The CATSS-Study is supported by the Swedish Research Council through the Swedish Initiative for Research on Microdata in the Social And Medical Sciences (SIMSAM) framework grant no 340-2013-5867, grants provided by the Stockholm County Council (ALF-projects), the Swedish Heart-Lung Foundation and the Swedish Asthma and Allergy Association's Research Foundation. Colorado Twin Registry is funded by NIDA funded center grant DA011015, & Longitudinal Twin Study HD10333; Author Huibregtse is supported by 5T32DA017637 and 5T32AG052371. Since its origin the East Flanders Prospective Survey has been partly supported by grants from the Fund of Scientific Research, Flanders and Twins, a non-profit Association for Scientific Research in Multiple Births (Belgium). Data collection and analyses in Finnish twin cohorts have been supported by ENGAGE - European Network for Genetic and Genomic Epidemiology, FP7-HEALTH-F4-2007, grant agreement number 201413, National Institute of Alcohol Abuse and Alcoholism (grants AA-12502, AA-00145, and AA-09203 to R J Rose, the Academy of Finland Center of Excellence in Complex Disease Genetics (grant numbers: 213506, 129680), Centre of Excellence in Research on Mitochondria, Metabolism and Disease (FinMIT, grant 272376), the Academy of Finland (grants 100499, 205585, 118555, 141054, 265240, 263278 and 264146 to J Kaprio and grant 266286 and 314383 to K Pietilainen), the Finnish Diabetes Research Foundation, Novo Nordisk Foundation, Helsinki University Central Hospital and University of Helsinki. K Silventoinen is supported by Osaka University's International Joint Research Promotion Program. Gemini was supported by a grant from Cancer Research UK (C1418/A7974). Anthropometric measurements of the Hungarian twins were supported by Medexpert Ltd., Budapest, Hungary. Korean Twin-Family Register was supported by the Global Research Network Program of the National Research Foundation (NRF 2011-220-E00006). Longitudinal Israeli Study of Twins was funded by the Starting Grant no. 240994 from the European Research Council (ERC) to Ariel Knafo. The Michigan State University Twin Registry has been supported by Michigan State University, as well as grants R01-MH081813, R01-MH0820-54, R01-MH092377-02, R21-MH070542-01, R03-MH63851-01 from the National Institute of Mental Health (NIMH), R01-HD066040 from the Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD), and 11-SPG-2518 from the MSU Foundation. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the NIMH, the NICHD, or the National Institutes of Health. PETS was supported by grants from the Australian National Health and Medical Research Council (grant numbers 437015 and 607358 to JC, and RS), the Bonnie Babes Foundation (grant number BBF20704 to JMC), the Financial Markets Foundation for Children (grant no. r 032-2007 to JMC), and by the Victorian Governments Operational Infrastructure Support Program. The Quebec Newborn Twin Study acknowledges financial support from the Fonds Quebecois de la Recherche sur la Societe et la Culture, the Fonds de la Recherche en Sante du Quebec, the Social Science and Humanities Research Council of Canada, the National Health Research Development Program, the Canadian Institutes for Health Research, Sainte-Justine Hospital's Research Center, and the Canada Research Chair Program (Michel Boivin). The Twins Early Development Study (TEDS) is supported by a program grant (MR/M021475/1) from the UK Medical Research Council and the work on obesity in TEDS is supported in part by a grant from the UK Biotechnology and Biological Sciences Research Council (31/D19086). The West Japan Twins and Higher Order Multiple Births Registry was supported by Grant-in-Aid for Scientific Research (B) (grant number 15H05105) from the Japan Society for the Promotion of Science. Netherlands Twin Register acknowledges the Netherlands Organization for Scientific Research (NWO) and MagW/ZonMW grants 904-61-090, 985-10-002, 912-10-020, 904-61-193, 480-04-004, 463-06-001, 451-04-034, 400-05-717, Addiction-31160008, Middelgroot-911-09-032, Spinozapremie 56-464-14192; VU University's Institute for Health and Care Research (EMGO +); the European Research Council (ERC - 230374), the Avera Institute, Sioux Falls, South Dakota (USA).

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Genomic epidemiology of addictions and their consequences - national, Nordic and international dimensions. (263278)
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The following results are related to Canada. Are you interested to view more results? Visit OpenAIRE - Explore.
28 Research products, page 1 of 3
  • Open Access English
    Authors: 
    Eilis Hannon; Emma Dempster; Georgina Mansell; Joe Burrage; Nick Bass; Marc M. Bohlken; Aiden Corvin; Charles Curtis; David Dempster; Marta Di Forti; +36 more
    Countries: Finland, Netherlands, Turkey
    Project: AKA | Genomic epidemiology of a... (265240), AKA | Genomic epidemiology of a... (263278), AKA | Center of Excellence in C... (312073)

    We performed a systematic analysis of blood DNA methylation profiles from 4483 participants from seven independent cohorts identifying differentially methylated positions (DMPs) associated with psychosis, schizophrenia, and treatment-resistant schizophrenia. Psychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNA methylation data, with the largest differences seen in treatment-resistant schizophrenia patients. We implemented a stringent pipeline to meta-analyze epigenome-wide association study (EWAS) results across datasets, identifying 95 DMPs associated with psychosis and 1048 DMPs associated with schizophrenia, with evidence of colocalization to regions nominated by genetic association studies of disease. Many schizophrenia-associated DNA methylation differences were only present in patients with treatment-resistant schizophrenia, potentially reflecting exposure to the atypical antipsychotic clozapine. Our results highlight how DNA methylation data can be leveraged to identify physiological (e.g., differential cell counts) and environmental (e.g., smoking) factors associated with psychosis and molecular biomarkers of treatment-resistant schizophrenia.

  • Open Access
    Authors: 
    Tuomo Kiiskinen; Nina Mars; Teemu Palviainen; Jukka Koskela; Pietari Ripatti; Joel T. Rämö; Sanni Ruotsalainen; Aarno Palotie; Pamela A. F. Madden; Richard J. Rose; +5 more
    Publisher: Cold Spring Harbor Laboratory
    Project: AKA | Human model for genetic v... (285380), AKA | Center of Excellence in C... (312062), WT , AKA | Genomic epidemiology of a... (263278), AKA | Genomic epidemiology of a... (265240), AKA | Longitudinal birth cohort... (308248)

    AbstractObjectiveTo develop a highly polygenic risk score (PRS) for alcohol consumption and study whether it predicts alcohol-related morbidity and all-cause mortality.DesignBiobank-based prospective cohort studySettingFinnGen Study (Finland)Participants96,499 genotyped participants from the nationwide prospective FinnGen study and 36,499 participants from prospective cohorts (Health 2000, FINRISK, Twin Cohort) with detailed baseline data and up to 25 years of follow-up time.Main outcome measuresIncident alcohol-related morbidity and alcohol-related or all-cause mortality, based on hospitalizations, outpatient specialist care, drug purchases, and death reports.ResultsIn 96,499 FinnGen participants there were in total 4,785 first-observed incident alcohol-related health events. The PRS of alcohol consumption was associated with alcohol-related morbidity and the risk estimate (hazard ratio, HR) between the highest and lowest quintiles of the PRS was 1.67 [ 95 % confidence interval: 1.52-1.84], p=3.2*10−27). In 28,639 participants with comprehensive baseline data from prospective Health 2000 and FINRISK cohorts, 911 incident first alcohol-related events were observed. When adjusted for self-reported alcohol consumption, education, marital status, and gamma-glutamyl transferase blood levels, the risk estimate between the highest and lowest quintiles of the PRS was 1.58 (CI=[1.26-1.99], p=8.2*10−5). The PRS was also associated with all-cause mortality with a risk estimate of 1.33 between the highest and lowest quintiles (CI=[1.2-1.47], p=4.5e-08) in the adjusted model. In all 39,695 participants with self-reported alcohol consumption available, a 1 SD increase in the PRS was associated with 11.2 g (=0.93 drinks) higher weekly alcohol consumption (β=11.2 [9.85-12.58 g], p = 2.3*10−58).ConclusionsThe PRS for alcohol consumption associates for both alcohol-related morbidity and all-cause mortality. These findings underline the importance of heritable factors in alcohol-related behavior and the related health burden. The results highlight how measured genetic risk for an important behavioral risk factor can be used to predict related health outcomes.

  • Open Access English
    Authors: 
    Law, PJ; Timofeeva, M; Fernandez-Rozadilla, C; Broderick, P; Studd, J; Fernandez-Tajes, J; Farrington, S; Svinti, V; Palles, C; Orlando, G; +89 more
    Publisher: NATURE PUBLISHING GROUP
    Countries: United Kingdom, Croatia, Finland
    Project: EC | ENGAGE (201413), NIH | Colon Cancer Family Regis... (4UM1CA167551-04), UKRI | A genome-wide association... (BB/F019394/1), AKA | The Application of 'Omics... (139635), AKA | ELIXIR - Data for Life  E... (271642), AKA | Biomedinfra - Implementin... (263164), WT | A national DNA control se... (068545), NIH | Data sharing: the Colon C... (3U01CA167551-07S1), AKA | Center of Excellence in T... (312041), NIH | Imputation-based approach... (7U01CA188392-03),...

    Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide, and has a strong heritable basis. We report a genome-wide association analysis of 34,627 CRC cases and 71,379 controls of European ancestry that identifies SNPs at 31 new CRC risk loci. We also identify eight independent risk SNPs at the new and previously reported European CRC loci, and a further nine CRC SNPs at loci previously only identified in Asian populations. We use in situ promoter capture Hi-C (CHi-C), gene expression, and in silico annotation methods to identify likely target genes of CRC SNPs. Whilst these new SNP associations implicate target genes that are enriched for known CRC pathways such as Wnt and BMP, they also highlight novel pathways with no prior links to colorectal tumourigenesis. These findings provide further insight into CRC susceptibility and enhance the prospects of applying genetic risk scores to personalised screening and prevention. In colorectal cancer (CRC), finding loci associated with risk may give insight into disease aetiology. Here, the authors report a genome-wide association analysis in Europeans of 34,627 CRC cases and 71,379 controls, and find 31 new risk loci and 17 new risk SNPs at previously reported loci.

  • Open Access English
    Authors: 
    Middeldorp, Christel M.; Mahajan, Anubha; Horikoshi, Momoko; Robertson, Neil R.; Beaumont, Robin N.; Bradfield, Jonathan P.; Bustamante, Mariona; Cousminer, Diana L.; Day, Felix R.; De Silva, N. Maneka; +193 more
    Publisher: Springer Netherlands
    Countries: United Kingdom, United Kingdom, Germany, Switzerland, United Kingdom, Spain, United Kingdom, Denmark, United Kingdom, Netherlands ...
    Project: WT | Genome-wide association s... (084762), EC | GERONIMO (603794), NIH | A Genome-wide Association... (1R01HL087680-01), NIH | JH/CIDR Genotyping for Ge... (5U01HG004438-04), AKA | Northern Finland Birth Co... (285547), EC | MULTIEPIGEN (742927), WT | New insights from Neonata... (098395), AKA | Genetic and environmental... (141054), NIH | Genome Wide Association C... (5U01HG004446-04), EC | GLUCOSEGENES (323195),...

    We are grateful to all families and participants who took part in these studies. We also acknowledge and appreciate the unique efforts of the research teams and practitioners contributing to the collection of this wealth of data. C. M. M. is supported by funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement no. 721567. J. F. F. has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 633595 (DynaHEALTH) and 733206 (LifeCycle). R. M. F. and R. N. B. are supported by Sir Henry Dale Fellowship (Wellcome Trust and Royal Society grant: WT104150). D. L. C. is funded by the American Diabetes Association Grant 1-17-PDF-077. D. O. M-K. was supported by Dutch Science Organization (ZonMW-VENI Grant 916.14.023). N. M. W. is supported by an Australian National Health and Medical Research Council Early Career Fellowship (APP1104818). T. S. A. was partially funded by the Gene-Diet Interactions in Obesity (GENDINOB) project on behalf of GOYA male cohort data management and analyses and acknowledges the same. S. D. was supported by National Institute of Health Research. T. M. F. is supported by the European Research Council grant: 323195 SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC. The Novo Nordisk Foundation Center for Basic Metabolic Research is an independent Research Center at the University of Copenhagen partially funded by an unrestricted donation from the Novo Nordisk Foundation (www.metabol.ku.dk).H.H.is funded by The Children's Hospital of Philadelphia Endowed Chair in Genomic Research. A. T. H. is supported by the Wellcome Trust Senior Investigator Awards (WT098395), National Institute for Health Research (NIHR) Senior Investigator Award (NF-SI-0611-10219). J. Hebebrand received grants from German Research Society, German Ministry of Education and Research. M-F. H. is currently supported by an American Diabetes Association (ADA) Pathway Program Accelerator Early Investigator Award (1-15-ACE-26). S. J. is supported by Helse Vest no. 23929, Bergen Forskningsstiftelse and KG Jebsen Foundation and University of Bergen. J. K. has been supported by the Academy of Finland Research Professor program (grants 265240 & 263278). J. P. K. is funded by a University of Queensland Development Fellowship (UQFEL1718945). H. L. has served as a speaker for Eli-Lilly and Shire and has received research grants from Shire; all outside the submitted work. C. M. L is supported by the Li Ka Shing Foundation, WT-SSI/John Fell funds and by the NIHR Biomedical Research Centre, Oxford, by Widenlife and NIH (5P50HD028138-27). S. E. M. was funded by an NHMRC Senior Reseach Fellowship (APP1103623). K. Panoutsopoulou is funded by a career development fellowship (grant 20308) and by the Wellcome Trust (WT098051). C. P. at UCL Institute of Child Health, with support from the National Institute for Health Research Biomedical Research Centre at Great Ormond Street Hospital for Children NHS Foundation Trust and University College London. I. P. was funded in part by the Wellcome Trust (WT205915), and the European Union's Horizon 2020 research, the European Union FP7-IDEAS-ERC Advanced Grant (GEPIDIAB, ERC-AG -ERC-294785), and innovation programme (DYNAhealth, H2020-PHC-2014-633595). R. C. R. is supported by CRUK (grant number C18281/A19169). J. G. S. is supported by an NHMRC Practitioner Fellowship Grant (APP1105807). J. T.; r is funded by the European Regional Development Fund (ERDF), the European Social Fund (ESF), Convergence Programme for Cornwall and the Isles of Scilly and the Diabetes Research and Wellness Foundation Non-Clinical Fellowship. N. V-T. is funded by a pre-doctoral grant from the Agencia de Gestio d'Ajuts Universitaris i de Recerca (AGAUR) (2015 FI_B 00636), Generalitat de Catalunya. T. G. M. V was supported by ZonMW (TOP 40-00812-98-11010. J. F. W. is supported by the MRC Human Genetics Unit quinquennial programme QTL in Health and Disease. H. Y. is funded by Diabetes UK RD Lawrence fellowship (grant: 17/0005594). M. H. Z was supported by BBMRI-NL (CP2013-50). E. Z. is supported by the Wellcome Trust (098051). B. F. is supported by Novo Nordisk Foundation (12955) and an Oak Foundation Fellowship. S. S. and M-R. J. have received funding from the European Union's Horizon 2020 research and innovation programme [under grant agreement No 633595] for the DynaHEALTH action. P. R. N. was supported by the European Research Council (ERC), University of Bergen, KG Jebsen and Helse Vest. G. D. S. works within the MRC Integrative Epidemiology Unit at the University of Bristol (MC_UU_12013/1). D. A. L was supported by the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement (Grant number 669545; DevelopObese), US National Institute of Health (grant: R01 DK10324), the UK Medical Research Council (grant: MC_UU_00011/6), Wellcome Trust GWAS grant (WT088806), an NIHR Senior Investigator Award (NF-SI-0611-10196) and the NIHR Biomedical Research Centre at University Hospitals Bristol NHS Foundation Trust and the University of Bristol. L. Paternoster was supported by the UK Medical Research Council Unit grants MC_UU_12013_5. N. J. T. is a Wellcome Trust Investigator (202802/Z/16/Z), is the PI of the Avon Longitudinal Study of Parents and Children (MRC & WT 102215/2/13/2), is supported by the University of Bristol NIHR Biomedical Research Centre (BRC) and works within the CRUK Integrative Cancer Epidemiology Programme (C18281/A19169). V.W.V.J. received an additional grant from the Netherlands Organization for Health Research and Development (NWO, ZonMw-VIDI 016.136.361), a European Research Council Consolidator Grant (ERC-2014-CoG-648916) and funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 633595 (DynaHEALTH) and 733206 (LifeCycle). D. M. E. is funded by the UK Medical Research Council Unit grant MC_UU_12013_4, Australian Research Council Future Fellowship (FT130101709) and a NHMRC Senior Research Fellowship (GNT1137714). S. F. A. G. is funded by the Daniel B. Burke Endowed Chair for Diabetes Research and R01 HD056465. D. I. B. is supported by Spinozapremie (NWO-56-464-14192) and the Royal Netherlands Academy of Science Professor Award (PAH/6635) to DIB. M. I. M. is a Wellcome Senior Investgator and NIHR Senior Investigator supported by the Wellcome (090532, 098381, 203141), NIHR (NF-SI-0617-10090) and the US National Institute of Health (grant: R01 DK10324), the UK Medical Research Council (grant: MCiabetes UK RD Lawrence fellowship (grant: 17/0005594). M. H. Z was supported by BBMRI-NLNIHR Biomedical Research Centre, Oxford. The views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.

  • Open Access English
    Authors: 
    Richa Gupta; Jenny van Dongen; Yu Fu; Abdel Abdellaoui; Rachel F. Tyndale; Vidya Velagapudi; Dorret I. Boomsma; Tellervo Korhonen; Jaakko Kaprio; Anu Loukola; +1 more
    Countries: Netherlands, Finland
    Project: AKA | CoE in Complex Disease Ge... (213506), NWO | BBMRI-NL (2300154272), AKA | Epigenetic pathways to ob... (297908), AKA | Center of Excellence in C... (129680), CIHR , AKA | Genomic epidemiology of a... (263278), EC | GMI (230374), AKA | Genomic epidemiology of a... (265240)

    Background DNA methylation alteration extensively associates with smoking and is a plausible link between smoking and adverse health. We examined the association between epigenome-wide DNA methylation and serum cotinine levels as a proxy of nicotine exposure and smoking quantity, assessed the role of SNPs in these associations, and evaluated molecular mediation by methylation in a sample of biochemically verified current smokers (N = 310). Results DNA methylation at 50 CpG sites was associated (FDR < 0.05) with cotinine levels, 17 of which are novel associations. As cotinine levels are influenced not only by nicotine intake but also by CYP2A6-mediated nicotine metabolism rate, we performed secondary analyses adjusting for genetic risk score of nicotine metabolism rate and identified five additional novel associations. We further assessed the potential role of genetic variants in the detected association between methylation and cotinine levels observing 124 cis and 3898 trans methylation quantitative trait loci (meQTLs). Nineteen of these SNPs were also associated with cotinine levels (FDR < 0.05). Further, at seven CpG sites, we observed a trend (P < 0.05) that altered DNA methylation mediates the effect of SNPs on nicotine exposure rather than a direct consequence of smoking. Finally, we performed replication of our findings in two independent cohorts of biochemically verified smokers (N = 450 and N = 79). Conclusions Using cotinine, a biomarker of nicotine exposure, we replicated and extended identification of novel epigenetic associations in smoking-related genes. We also demonstrated that DNA methylation in some of the identified loci is driven by the underlying genotype and may mediate the causal effect of genotype on cotinine levels. Electronic supplementary material The online version of this article (10.1186/s13148-018-0606-9) contains supplementary material, which is available to authorized users.

  • Open Access
    Authors: 
    Gupta, Richa; Dongen, Jenny; Fu, Yu; Abdellaoui, Abdel; Tyndale, Rachel; Velagapudi, Vidya; Dorret Boomsma; Korhonen, Tellervo; Kaprio, Jaakko; Loukola, Anu; +1 more
    Publisher: figshare
    Project: AKA | Center of Excellence in C... (129680), CIHR , AKA | CoE in Complex Disease Ge... (213506), NWO | BBMRI-NL (2300154272), AKA | Epigenetic pathways to ob... (297908), EC | GMI (230374), AKA | Genomic epidemiology of a... (263278), AKA | Genomic epidemiology of a... (265240)

    Figure S3. Mediation analysis to assess whether DNA methylation is a causal mediator to the observed association between genetic variants and cotinine levels. (PDF 588 kb)

  • Open Access
    Authors: 
    Gupta, Richa; Dongen, Jenny; Fu, Yu; Abdellaoui, Abdel; Tyndale, Rachel; Velagapudi, Vidya; Dorret Boomsma; Korhonen, Tellervo; Kaprio, Jaakko; Loukola, Anu; +1 more
    Publisher: figshare
    Project: CIHR , AKA | Center of Excellence in C... (129680), EC | GMI (230374), AKA | Genomic epidemiology of a... (265240), AKA | Genomic epidemiology of a... (263278), AKA | CoE in Complex Disease Ge... (213506), NWO | BBMRI-NL (2300154272), AKA | Epigenetic pathways to ob... (297908)

    Figure S2. QQ plot for genetic association analysis of cotinine levels and 46,780 SNPs in 40 genes. (PDF 17 kb)

  • Open Access
    Authors: 
    Gupta, Richa; Dongen, Jenny; Fu, Yu; Abdellaoui, Abdel; Tyndale, Rachel; Velagapudi, Vidya; Dorret Boomsma; Korhonen, Tellervo; Kaprio, Jaakko; Loukola, Anu; +1 more
    Publisher: figshare
    Project: AKA | Genomic epidemiology of a... (263278), EC | GMI (230374), AKA | Genomic epidemiology of a... (265240), CIHR , AKA | Center of Excellence in C... (129680), AKA | CoE in Complex Disease Ge... (213506), NWO | BBMRI-NL (2300154272), AKA | Epigenetic pathways to ob... (297908)

    Figure S1. Manhattan and QQ plots showing epigenome-wide association results from secondary analysis when accounting for the rate of nicotine metabolism using a GRS. (A) QQ plot showing observed versus expected − log10(P) for association at all loci. (B) Manhattan plot showing chromosomal locations of − log10(P) for association at each locus. All CpG sites with FDR

  • Open Access
    Authors: 
    Yoshie Yokoyama; Aline Jelenkovic; Yoon-Mi Hur; Reijo Sund; Corrado Fagnani; Maria Antonietta Stazi; Sonia Brescianini; Fuling Ji; Feng Ning; Zengchang Pang; +50 more
    Publisher: Oxford University Press (OUP)
    Countries: United Kingdom, Finland, Denmark, Netherlands
    Project: AKA | Indicators of marginaliza... (264146), AKA | Genomic epidemiology of a... (263278), CIHR , AKA | Genomic epidemiology of a... (265240), AKA | Genetic and environmental... (141054), SSHRC , AKA | Predictors, neuropsycholo... (118555), AKA | Oxygenology of soil (205585)

    Background: The genetic architecture of birth size may differ geographically and over time. We examined differences in the genetic and environmental contributions to birth weight, length, and ponderal index (PI) across geographic-cultural regions (Europe, North-America and Australia, and East-Asia) and across birth cohorts and how gestational age modifies these effects.Methods: Data from 26 twin cohorts in 16 countries including 57613 monozygotic and dizygotic twin pairs were pooled. Genetic and environmental variations of birth size were estimated using genetic structural equation modeling.Results: The variance of birth weight and length was predominantly explained by shared environmental factors, whereas the variance of PI was explained both by shared and unique environmental factors. Genetic variance contributing to birth size was small. Adjusting for gestational age decreased the proportions of shared environmental variance and increased the propositions of unique environmental variance. Genetic variance was similar in the geographic-cultural regions, but shared environmental variance was smaller in East-Asia than in Europe and North-America and Australia. The total variance and shared environmental variance of birth length and PI were greater from the birth cohort 1990-1999 onwards compared with the birth cohorts from 1970-1979 to 1980-1989.Conclusion: The contribution of genetic factors to birth size is smaller than that of shared environmental factors, which is partly explained by gestational age. Shared environmental variances of birth length and PI were greater in the latest birth cohorts and differed also across geographic-cultural regions. Shared environmental factors are important when explaining differences in the variation of birth size globally and over time.

  • Open Access English
    Authors: 
    Aline Jelenkovic; Yoshie Yokoyama; Reijo Sund; Yoon-Mi Hur; Jennifer R. Harris; Ingunn Brandt; Thomas Sevenius Nilsen; Syuichi Ooki; Vilhelmina Ullemar; Catarina Almqvist; +59 more
    Countries: Finland, United Kingdom, Denmark, Netherlands, Belgium, Spain, United Kingdom, Denmark, Belgium, Norway
    Project: AKA | Macro level variation in ... (266592), AKA | Indicators of marginaliza... (264146), CIHR , SSHRC , AKA | Individualized treatments... (314383), AKA | Oxygenology of soil (205585), AKA | Sequelae of metabolic com... (266286), AKA | Predictors, neuropsycholo... (118555), AKA | Genetic and environmental... (141054), AKA | Genomic epidemiology of a... (263278),...

    Background: There is evidence that birth size is positively associated with height in later life, but it remains unclear whether this is explained by genetic factors or the intrauterine environment. Aim: To analyze the associations of birth weight, length and ponderal index with height from infancy through adulthood within mono- and dizygotic twin pairs, which provides insights into the role of genetic and environmental individual-specific factors. Methods: This study is based on the data from 28 twin cohorts in 17 countries. The pooled data included 41,852 complete twin pairs (55% monozygotic and 45% same-sex dizygotic) with information on birth weight and a total of 112,409 paired height measurements at ages ranging from 1 to 69 years. Birth length was available for 19,881 complete twin pairs, with a total of 72,692 paired height measurements. The association between birth size and later height was analyzed at both the individual and within-pair level by linear regression analyses. Results: Within twin pairs, regression coefficients showed that a 1-kg increase in birth weight and a 1-cm increase in birth length were associated with 1.14-4.25 cm and 0.18-0.90 cm taller height, respectively. The magnitude of the associations was generally greater within dizygotic than within monozygotic twin pairs, and this difference between zygosities was more pronounced for birth length. Conclusion: Both genetic and individual-specific environmental factors play a role in the association between birth size and later height from infancy to adulthood, with a larger role for genetics in the association with birth length than with birth weight. This work was supported by the Academy of Finland (grant number #266592). The Australian Twin Registry is supported by a Centre of Research Excellence (grant ID 1079102) from the National Health and Medical Research Council administered by the University of Melbourne. The Boston University Twin Project is funded by grants (#R01 HD068435 #R01 MH062375) from the National Institutes of Health to K. Saudino. The Carolina African American Twin Study of Aging (CAATSA) was funded by a grant from the National Institute on Aging (grant 1RO1-AG13662-01A2) to K. E. Whitfield. The CATSS-Study is supported by the Swedish Research Council through the Swedish Initiative for Research on Microdata in the Social And Medical Sciences (SIMSAM) framework grant no 340-2013-5867, grants provided by the Stockholm County Council (ALF-projects), the Swedish Heart-Lung Foundation and the Swedish Asthma and Allergy Association's Research Foundation. Colorado Twin Registry is funded by NIDA funded center grant DA011015, & Longitudinal Twin Study HD10333; Author Huibregtse is supported by 5T32DA017637 and 5T32AG052371. Since its origin the East Flanders Prospective Survey has been partly supported by grants from the Fund of Scientific Research, Flanders and Twins, a non-profit Association for Scientific Research in Multiple Births (Belgium). Data collection and analyses in Finnish twin cohorts have been supported by ENGAGE - European Network for Genetic and Genomic Epidemiology, FP7-HEALTH-F4-2007, grant agreement number 201413, National Institute of Alcohol Abuse and Alcoholism (grants AA-12502, AA-00145, and AA-09203 to R J Rose, the Academy of Finland Center of Excellence in Complex Disease Genetics (grant numbers: 213506, 129680), Centre of Excellence in Research on Mitochondria, Metabolism and Disease (FinMIT, grant 272376), the Academy of Finland (grants 100499, 205585, 118555, 141054, 265240, 263278 and 264146 to J Kaprio and grant 266286 and 314383 to K Pietilainen), the Finnish Diabetes Research Foundation, Novo Nordisk Foundation, Helsinki University Central Hospital and University of Helsinki. K Silventoinen is supported by Osaka University's International Joint Research Promotion Program. Gemini was supported by a grant from Cancer Research UK (C1418/A7974). Anthropometric measurements of the Hungarian twins were supported by Medexpert Ltd., Budapest, Hungary. Korean Twin-Family Register was supported by the Global Research Network Program of the National Research Foundation (NRF 2011-220-E00006). Longitudinal Israeli Study of Twins was funded by the Starting Grant no. 240994 from the European Research Council (ERC) to Ariel Knafo. The Michigan State University Twin Registry has been supported by Michigan State University, as well as grants R01-MH081813, R01-MH0820-54, R01-MH092377-02, R21-MH070542-01, R03-MH63851-01 from the National Institute of Mental Health (NIMH), R01-HD066040 from the Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD), and 11-SPG-2518 from the MSU Foundation. The content of this manuscript is solely the responsibility of the authors and does not necessarily represent the official views of the NIMH, the NICHD, or the National Institutes of Health. PETS was supported by grants from the Australian National Health and Medical Research Council (grant numbers 437015 and 607358 to JC, and RS), the Bonnie Babes Foundation (grant number BBF20704 to JMC), the Financial Markets Foundation for Children (grant no. r 032-2007 to JMC), and by the Victorian Governments Operational Infrastructure Support Program. The Quebec Newborn Twin Study acknowledges financial support from the Fonds Quebecois de la Recherche sur la Societe et la Culture, the Fonds de la Recherche en Sante du Quebec, the Social Science and Humanities Research Council of Canada, the National Health Research Development Program, the Canadian Institutes for Health Research, Sainte-Justine Hospital's Research Center, and the Canada Research Chair Program (Michel Boivin). The Twins Early Development Study (TEDS) is supported by a program grant (MR/M021475/1) from the UK Medical Research Council and the work on obesity in TEDS is supported in part by a grant from the UK Biotechnology and Biological Sciences Research Council (31/D19086). The West Japan Twins and Higher Order Multiple Births Registry was supported by Grant-in-Aid for Scientific Research (B) (grant number 15H05105) from the Japan Society for the Promotion of Science. Netherlands Twin Register acknowledges the Netherlands Organization for Scientific Research (NWO) and MagW/ZonMW grants 904-61-090, 985-10-002, 912-10-020, 904-61-193, 480-04-004, 463-06-001, 451-04-034, 400-05-717, Addiction-31160008, Middelgroot-911-09-032, Spinozapremie 56-464-14192; VU University's Institute for Health and Care Research (EMGO +); the European Research Council (ERC - 230374), the Avera Institute, Sioux Falls, South Dakota (USA).