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A Twin Study of Personality and Illicit Drug Use and Abuse/Dependence
In: Twin research, Band 7, Heft 1, S. 72-81
ISSN: 2053-6003
Correlates of smoking cessation in a nationally representative sample of U.S. adults
Persistent cigarette smoking is associated with significant morbidity and mortality. Correlates of difficulty quitting smoking include psychopathology, such as major depressive disorder, and problems with other substances, such as alcoholism. In addition, socio-demographic risk (e.g. poverty) and protective (e.g. living in a region with stringent tobacco laws) influences can modify risk for persistent cigarette smoking. Using data on 17,919 individuals with a lifetime history of smoking 100 or more cigarettes, from a nationally representative U.S. sample, we examine the constellation of risk and protective factors that correlate with smoking cessation (defined as remaining smoke-free in the past 12 months) across four cohorts: young (18–31 years), intermediate-aged (32–43 years), middle-aged (44–60 years) and older (61–99 years) adults. Using survival analyses, we demonstrate that in addition to a history of DSM-IV nicotine dependence, which is negatively associated with smoking cessation, living below the poverty line is also associated with persistent smoking across all age cohorts. Residents over the age of 31 years living on the U.S. West Coast are less likely to be persistent smokers as well. Major depressive disorder is associated with persistent smoking, but interestingly, only in middle-aged and older adults. Alcoholism and a family history of substance use problems are both correlated with persistent smoking but only in older adults. Here, we find evidence for psychopathology that may hinder successful quit attempts during the developmental period when a majority of quit attempts are made (early to mid-40's). However, our analyses also highlight the important benefits of effective tobacco legislation on the U.S. West Coast and urge policy makers to actively consider addressing issues surrounding tobacco taxation and the impact of poverty on tobacco use, in addition to the risks posed by co-occurring psychiatric problems and other substance use disorders.
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A Population Based Twin Study of Sex Differences in Depressive Symptoms
In: Twin research, Band 7, Heft 2, S. 176-181
ISSN: 2053-6003
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Working paper
An Australian Twin Study of Cannabis and Other Illicit Drug Use and Misuse, and Other Psychopathology
In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 15, Heft 5, S. 631-641
ISSN: 1839-2628
Cannabis is the most widely used illicit drug throughout the developed world and there is consistent evidence of heritable influences on multiple stages of cannabis involvement including initiation of use and abuse/dependence. In this paper, we describe the methodology and preliminary results of a large-scale interview study of 3,824 young adult twins (born 1972–1979) and their siblings. Cannabis use was common with 75.2% of males and 64.7% of females reporting some lifetime use of cannabis while 24.5% of males and 11.8% of females reported meeting criteria for DSM-IV cannabis abuse or dependence. Rates of other drug use disorders and common psychiatric conditions were highly correlated with extent of cannabis involvement and there was consistent evidence of heritable influences across a range of cannabis phenotypes including early (≤15 years) opportunity to use (h2 = 72%), early (≤16 years) onset use (h2 = 80%), using cannabis 11+ times lifetime (h2 = 76%), and DSM abuse/dependence (h2 = 72%). Early age of onset of cannabis use was strongly associated with increased rates of subsequent use of other illicit drugs and with illicit drug abuse/dependence; further analyses indicating that some component of this association may have been mediated by increasing exposure to and opportunity to use other illicit drugs.
Nicotine Withdrawal Symptoms in Adolescent and Adult Twins
In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 13, Heft 4, S. 359-369
ISSN: 1839-2628
AbstractWe examined the variation and heritability of DSM-IV nicotine withdrawal (NW) in adult and adolescent male and female twin cigarette smokers (who reported smoking 100 or more cigarettes lifetime). Telephone diagnostic interviews were completed with 3,112 Australian adult male and female smokers (53% women; age: 24–36) and 702 Missouri adolescent male and female smokers (59% girls; age: 15–21). No gender or cohort differences emerged in rates of meeting criteria for NW (44%). Latent class analyses found that NW symptoms were best conceptualized as a severity continuum (three levels in adults and two levels in adolescents). Across all groups, increasing NW severity was associated with difficulty quitting, impairment following cessation, heavy smoking, depression, anxiety, conduct disorder and problems with alcohol use. NW was also associated with seeking smoking cessation treatment and with smoking persistence in adults. The latent class structure of NW was equally heritable across adult and adolescent smokers with additive genetic influences accounting for 49% of the variance and the remaining 51% of variance accounted for by unique environmental influences. Overall, findings suggest remarkable similarity in the pattern and heritability of NW across adult and adolescent smokers, and highlight the important role of NW in psychiatric comorbidity and the process of smoking cessation across both age groups.
Functioning of Cannabis Abuse and Dependence Criteria Across Two Different Countries: The United States and The Netherlands
In: Substance use & misuse: an international interdisciplinary forum, Band 50, Heft 2, S. 242-250
ISSN: 1532-2491
Is the Relationship Between Binge Eating Episodes and Personality Attributable to Genetic Factors?
In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 17, Heft 2, S. 65-71
ISSN: 1839-2628
Aspects of disordered eating and personality traits, such as neuroticism, are correlated and individually heritable. We examined the phenotypic correlation between binge eating episodes and indices of personality (neuroticism, extraversion, openness to experience, agreeableness, conscientiousness, and control/impulsivity). For correlations ≥|0.20|, we estimated the extent to which genetic and environmental factors contributed to this correlation. Participants included 3,446 European American same-sex female twins from the Missouri Adolescent Female Twin Study (median age = 22 years). Binge eating episode was assessed via interview questions. Personality traits were assessed by self-report questionnaires. There was a significant moderate phenotypic correlation between binge eating episode and neuroticism (r = 0.33) as well as conscientiousness (r = -0.21), while other correlations were significant but smaller (r ranging from -0.14 to 0.14). Individual differences in binge eating episodes, neuroticism, and conscientiousness were attributed to additive genetic influences (38% [95% CI: 21–53%], 45% [95% CI: 38–52%], and 44% [95% CI: 0.33–0.55%] respectively), with the remaining variance attributed to individual-specific environmental influences. Covariance was attributable to genetic (neuroticism rg = 0.37; conscientiousness rg = -0.22) and individual-specific environmental (neuroticism re = 0.28; conscientiousness re = -0.19) influences. Personality traits may be an early indicator of genetic vulnerability to a variety of pathological behaviors, including binge eating episode. Furthermore, prior research documenting phenotypic correlations between eating disorder diagnoses and personality may have stemmed from etiological overlap between these personality traits and aspects of disordered eating, such as binge eating episode.
Subtypes of Illicit Drug Users: A Latent Class Analysis of Data From an Australian Twin Sample
In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 9, Heft 4, S. 523-530
ISSN: 1839-2628
Neuroticism and the Overlap Between Autistic and ADHD Traits: Findings From a Population Sample of Young Adult Australian Twins
In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 20, Heft 4, S. 319-329
ISSN: 1839-2628
Neuroticism, a 'Big Five' personality trait, has been associated with sub-clinical traits of both autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). The objective of the current study was to examine whether causal overlap between ASD and ADHD traits can be accounted for by genetic and environmental risk factors that are shared with neuroticism. We performed twin-based structural equation modeling using self-report data from 12 items of the Neo Five-Factor Inventory Neuroticism domain, 11 Social Responsiveness Scale items, and 12 Adult ADHD Self-Report Scale items obtained from 3,170 young adult Australian individual twins (1,081 complete pairs). Univariate analysis for neuroticism, ASD, and ADHD traits suggested that the most parsimonious models were those with additive genetic and unique environmental components, without sex limitation effects. Heritability of neuroticism, ASD, and ADHD traits, as measured by these methods, was moderate (between 40% and 45% for each respective trait). In a trivariate model, we observed moderate phenotypic (between 0.45 and 0.62), genetic (between 0.56 and 0.71), and unique environmental correlations (between 0.37and 0.55) among neuroticism, ASD, and ADHD traits, with the highest value for the shared genetic influence between neuroticism and self-reported ASD traits (rg = 0.71). Together, our results suggest that in young adults, genetic, and unique environmental risk factors indexed by neuroticism overlap with those that are shared by ASD and ADHD.
Long-Term Stability and Heritability of Telephone Interview Measures of Alcohol Consumption and Dependence
In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 11, Heft 3, S. 287-305
ISSN: 1839-2628
AbstractAlcohol dependence symptoms and consumption measures were examined for stability and heritability. Data were collected from 12,045 individuals (5376 twin pairs, 1293 single twins) aged 19 to 90 years in telephone interviews conducted in three collection phases. Phases 1 and 2 were independent samples, but Phase 3 targeted families of smokers and drinkers from the Phase 1 and 2 samples. The stability of dependence symptoms and consumption was examined for 1158 individuals interviewed in both Phases 1 and 3 (mean interval = 11.0 years). For 1818 individuals interviewed in Phases 2 and 3 (mean interval = 5.5 years) the stability of consumption was examined. Heritability was examined for each collection phase and retest samples from the selected Phase 3 collection. The measures examined were a dependence score, based on DSM-IIIR and DSM-IV criteria for substance dependence, and a quantity × frequency measure. Measures were moderately stable, with test–retest correlations ranging from .58 to .61 for dependence and from .55 to .64 for consumption. However, the pattern of changes over time for dependence suggested that the measure may more strongly reflect recent than lifetime experience. Similar to previous findings, heritabilities ranged from .42 to .51 for dependence and from .31 to .51 for consumption. Consumption was significantly less heritable in the younger Phase 2 cohort (23–39 years) compared to the older Phase 1 cohort (28–90 years).
How Phenotype and Developmental Stage Affect the Genes We Find:GABRA2and Impulsivity
In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 16, Heft 3, S. 661-669
ISSN: 1839-2628
Context:The detection and replication of genes involved in psychiatric outcome has been notoriously difficult. Phenotypic measurement has been offered as one explanation, although most of this discussion has focused on problems with binary diagnoses.Objective:This article focuses on two additional components of phenotypic measurement that deserve further consideration in evaluating genetic associations: (1) the measure used to reflect the outcome of interest, and (2) the developmental stage of the study population. We focus our discussion of these issues around the construct of impulsivity and externalizing disorders, and the association of these measures with a specific gene,GABRA2.Design, Setting, and Participants:Data were analyzed from the Collaborative Study on the Genetics of Alcoholism Phase IV assessment of adolescents and young adults (ages 12–26;N= 2,128).Main Outcome Measures:Alcohol dependence, illicit drug dependence, childhood conduct disorder, and adult antisocial personality disorder symptoms were measured by psychiatric interview; Achenbach youth/adult self-report externalizing scale; Zuckerman Sensation-Seeking scale; Barratt Impulsivity scale; NEO extraversion and consciousness.Results: GABRA2was associated with subclinical levels of externalizing behavior as measured by the Achenbach in both the adolescent and young adult samples. Contrary to previous associations in adult samples, it was not associated with clinical-level DSM symptom counts of any externalizing disorders in these younger samples. There was also association with sensation-seeking and extraversion, but only in the adolescent sample. There was no association with the Barratt impulsivity scale or conscientiousness.Conclusions:Our results suggest that the pathway by whichGABRA2initially confers risk for eventual alcohol problems begins with a predisposition to sensation-seeking early in adolescence. The findings support the heterogeneous nature of impulsivity and demonstrate that both the measure used to assess a construct of interest and the age of the participants can have profound implications for the detection of genetic associations.
Genetic and Environmental Risk for Major Depression in African-American and European-American Women
In: Twin research and human genetics: the official journal of the International Society for Twin Studies (ISTS) and the Human Genetics Society of Australasia, Band 17, Heft 4, S. 244-253
ISSN: 1839-2628
It is unknown whether there are racial differences in the heritability of major depressive disorder (MDD) because most psychiatric genetic studies have been conducted in samples comprised largely of white non-Hispanics. To examine potential differences between African-American (AA) and European-American (EA) young adult women in (1) Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) MDD prevalence, symptomatology, and risk factors, and (2) genetic and/or environmental liability to MDD, we analyzed data from a large population-representative sample of twins ascertained from birth records (n = 550 AA and n = 3226 EA female twins) aged 18–28 years at the time of MDD assessment by semi-structured psychiatric interview. AA women were more likely to have MDD risk factors; however, there were no significant differences in lifetime MDD prevalence between AA and EA women after adjusting for covariates (odds ratio = 0.88, 95% confidence interval [CI]: 0.67–1.15). Most MDD risk factors identified among AA women were also associated with MDD at similar magnitudes among EA women. Although the MDD heritability point estimate was higher among AA women than EA women in a model with paths estimated separately by race (56%, 95% CI: 29–78% vs. 41%, 95% CI: 29–52%), the best fitting model was one in which additive genetic and non-shared environmental paths for AA and EA women were constrained to be equal (A = 43%, 33–53% and E = 57%, 47–67%). In spite of a marked elevation in the prevalence of environmental risk exposures related to MDD among AA women, there were no significant differences in lifetime prevalence or heritability of MDD between AA and EA young women.
Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci
Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10-8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10-8) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10-3) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation. ; The authors would like to thank the many colleagues who contributed to collection and phenotypic characterisation of the clinical samples, as well as genotyping and analysis of the GWA data. Special mentions are as follows: CGSB participating cohorts: Some of the data utilised in this study were provided by the Understanding Society: The UK Household Longitudinal Study, which is led by the Institute for Social and Economic Research at the University of Essex and funded by the Economic and Social Research Council. The data were collected by NatCen and the genome wide scan data were analysed by the Wellcome Trust Sanger Institute. The Understanding Society DAC have an application system for genetics data and all use of the data should be approved by them. The application form is at: https://www.understandingsociety.ac.uk/about/health/data. The Airwave Health Monitoring Study is funded by the UK Home Office, (Grant number 780-TETRA) with additional support from the National Institute for Health Research Imperial College Health Care NHS Trust and Imperial College Biomedical Research Centre. We thank all participants in the Airwave Health Monitoring Study. This work used computing resources provided by the MRC- funded UK MEDical Bioinformatics partnership programme (UK MED-BIO) (MR/L01632X/1). Paul Elliott wishes to acknowledge the Medical Research Council and Public Health England (MR/L01341X/1) for the MRC-PHE Centre for Environment and Health; and the NIHR Health Protection Research Unit in Health Impact of Environmental Hazards (HPRU-2012-10141). Paul Elliott is supported by the UK Dementia Research Institute which receives its funding from UK DRI Ltd funded by the UK Medical Research Council, Alzheimer's Society and Alzheimer's Research UK. Paul Elliott is associate director of the Health Data Research UK London funded by a consortium led by the UK Medical Research Council. SHIP (Study of Health in Pomerania) and SHIP-TREND both represent population-based studies. SHIP is supported by the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung (BMBF); grants 01ZZ9603, 01ZZ0103, and 01ZZ0403) and the German Research Foundation (Deutsche Forschungsgemeinschaft (DFG); grant GR 1912/5-1). SHIP and SHIP-TREND are part of the Community Medicine Research net (CMR) of the Ernst-Moritz-Arndt University Greifswald (EMAU) which is funded by the BMBF as well as the Ministry for Education, Science and Culture and the Ministry of Labor, Equal Opportunities, and Social Affairs of the Federal State of Mecklenburg-West Pomerania. The CMR encompasses several research projects that share data from SHIP. SNP typing of SHIP and SHIP-TREND using the Illumina Infinium HumanExome BeadChip (version v1.0) was supported by the BMBF (grant 03Z1CN22). LifeLines authors thank Behrooz Alizadeh, Annemieke Boesjes, Marcel Bruinenberg, Noortje Festen, Ilja Nolte, Lude Franke, Mitra Valimohammadi for their help in creating the GWAS database, and Rob Bieringa, Joost Keers, René Oostergo, Rosalie Visser, Judith Vonk for their work related to data-collection and validation. The authors are grateful to the study participants, the staff from the LifeLines Cohort Study and Medical Biobank Northern Netherlands, and the participating general practitioners and pharmacists. LifeLines Scientific Protocol Preparation: Rudolf de Boer, Hans Hillege, Melanie van der Klauw, Gerjan Navis, Hans Ormel, Dirkje Postma, Judith Rosmalen, Joris Slaets, Ronald Stolk, Bruce Wolffenbuttel; LifeLines GWAS Working Group: Behrooz Alizadeh, Marike Boezen, Marcel Bruinenberg, Noortje Festen, Lude Franke, Pim van der Harst, Gerjan Navis, Dirkje Postma, Harold Snieder, Cisca Wijmenga, Bruce Wolffenbuttel. The authors wish to acknowledge the services of the LifeLines Cohort Study, the contributing research centres delivering data to LifeLines, and all the study participants. Niek Verweij was supported by NWO VENI (016.186.125). Fenland authors thank Fenland Study volunteers for their time and help, Fenland Study general Practitioners and practice staff for assistance with recruitment, and Fenland Study Investigators, Co-ordination team and the Epidemiology Field, Data and Laboratory teams for study design, sample/data collection and genotyping. We thank all ASCOT trial participants, physicians, nurses, and practices in the participating countries for their important contribution to the study. In particular we thank Clare Muckian and David Toomey for their help in DNA extraction, storage, and handling. We would also like to acknowledge the Barts and The London Genome Centre staff for genotyping the Exome Chip array. The BRIGHT study is extremely grateful to all the patients who participated in the study and the BRIGHT nursing team. We would also like to thank the Barts Genome Centre staff for their assistance with this project. Patricia B. Munroe, Mark J. Caulfield, and Helen R. Warren wish to acknowledge the NIHR Cardiovascular Biomedical Research Unit at Barts and The London, Queen Mary University of London, UK for support. Mark J. Caulfield are Senior National Institute for Health Research Investigators. EMBRACE Collaborating Centres are: Coordinating Centre, Cambridge: Daniel Barrowdale, Debra Frost, Jo Perkins. North of Scotland Regional Genetics Service, Aberdeen: Zosia Miedzybrodzka, Helen Gregory. Northern Ireland Regional Genetics Service, Belfast: Patrick Morrison, Lisa Jeffers. West Midlands Regional Clinical Genetics Service, Birmingham: Kai-ren Ong, Jonathan Hoffman. South West Regional Genetics Service, Bristol: Alan Donaldson, Margaret James. East Anglian Regional Genetics Service, Cambridge: Joan Paterson, Marc Tischkowitz, Sarah Downing, Amy Taylor. Medical Genetics Services for Wales, Cardiff: Alexandra Murray, Mark T. Rogers, Emma McCann. St James's Hospital, Dublin & National Centre for Medical Genetics, Dublin: M. John Kennedy, David Barton. South East of Scotland Regional Genetics Service, Edinburgh: Mary Porteous, Sarah Drummond. Peninsula Clinical Genetics Service, Exeter: Carole Brewer, Emma Kivuva, Anne Searle, Selina Goodman, Kathryn Hill. West of Scotland Regional Genetics Service, Glasgow: Rosemarie Davidson, Victoria Murday, Nicola Bradshaw, Lesley Snadden, Mark Longmuir, Catherine Watt, Sarah Gibson, Eshika Haque, Ed Tobias, Alexis Duncan. South East Thames Regional Genetics Service, Guy's Hospital London: Louise Izatt, Chris Jacobs, Caroline Langman. North West Thames Regional Genetics Service, Harrow: Huw Dorkins. Leicestershire Clinical Genetics Service, Leicester: Julian Barwell. Yorkshire Regional Genetics Service, Leeds: Julian Adlard, Gemma Serra-Feliu. Cheshire & Merseyside Clinical Genetics Service, Liverpool: Ian Ellis, Claire Foo. Manchester Regional Genetics Service, Manchester: D Gareth Evans, Fiona Lalloo, Jane Taylor. North East Thames Regional Genetics Service, NE Thames, London: Lucy Side, Alison Male, Cheryl Berlin. Nottingham Centre for Medical Genetics, Nottingham: Jacqueline Eason, Rebecca Collier. Northern Clinical Genetics Service, Newcastle: Alex Henderson, Oonagh Claber, Irene Jobson. Oxford Regional Genetics Service, Oxford: Lisa Walker, Diane McLeod, Dorothy Halliday, Sarah Durell, Barbara Stayner. The Institute of Cancer Research and Royal Marsden NHS Foundation Trust: Ros Eeles, Nazneen Rahman, Elizabeth Bancroft, Elizabeth Page, Audrey Ardern-Jones, Kelly Kohut, Jennifer Wiggins, Jenny Pope, Sibel Saya, Natalie Taylor, Zoe Kemp and Angela George. North Trent Clinical Genetics Service, Sheffield: Jackie Cook, Oliver Quarrell, Cathryn Bardsley. South West Thames Regional Genetics Service, London: Shirley Hodgson, Sheila Goff, Glen Brice, Lizzie Winchester, Charlotte Eddy, Vishakha Tripathi, Virginia Attard. Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton: Diana Eccles, Anneke Lucassen, Gillian Crawford, Donna McBride, Sarah Smalley. Understanding Society Scientific Group is funded by the Economic and Social Research Council (ES/H029745/1) and the Wellcome Trust (WT098051). Paul D.P. Pharoah is funded by Cancer Research UK (C490/A16561). SHIP is funded by the German Federal Ministry of Education and Research (BMBF) and the German Research Foundation (DFG); see acknowledgements for details. F.W. Asselbergs is funded by the Netherlands Heart Foundation (2014T001) and supported by UCL Hospitals NIHR Biomedical Research Centre. The LifeLines Cohort Study, and generation and management of GWAS genotype data for the LifeLines Cohort Study is supported by the Netherlands Organization of Scientific Research NWO (grant 175.010.2007.006), the Economic Structure Enhancing Fund (FES) of the Dutch government, the Ministry of Economic Affairs, the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the Northern Netherlands Collaboration of Provinces (SNN), the Province of Groningen, University Medical Center Groningen, the University of Groningen, Dutch Kidney Foundation and Dutch Diabetes Research Foundation. Niek Verweij is supported by Horizon 2020, Marie Sklodowska-Curie (661395) and ICIN-NHI. Phenotype collection in the Lothian Birth Cohort 1921 was supported by the UK's Biotechnology and Biological Sciences Research Council (BBSRC), The Royal Society and The Chief Scientist Office of the Scottish Government. Phenotype collection in the Lothian Birth Cohort 1936 was supported by Age UK (The Disconnected Mind project). Genotyping was supported by Centre for Cognitive Ageing and Cognitive Epidemiology (Pilot Fund award), Age UK, and the Royal Society of Edinburgh. The work was undertaken by The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative (MR/K026992/1). Funding from the BBSRC and Medical Research Council (MRC) is gratefully acknowledged. Paul W. Franks is supported by Novo Nordisk, the Swedish Research Council, Påhlssons Foundation, Swedish Heart Lung Foundation (2020389), and Skåne Regional Health Authority. Nicholas J Wareham, Claudia Langenberg, Robert A Sacott, and Jian'an Luan are supported by the MRC (MC_U106179471 and MC_UU_12015/1). The BRIGHT study was supported by the Medical Research Council of Great Britain (Grant Number G9521010D); and by the British Heart Foundation (Grant Number PG/02/128). The BRIGHT study is extremely grateful to all the patients who participated in the study and the BRIGHT nursing team. The Exome Chip genotyping was funded by Wellcome Trust Strategic Awards (083948 and 085475). We would also like to thank the Barts Genome Centre staff for their assistance with this project. The ASCOT study and the collection of the ASCOT DNA repository was supported by Pfizer, New York, NY, USA, Servier Research Group, Paris, France; and by Leo Laboratories, Copenhagen, Denmark. Genotyping of the Exome Chip in ASCOT-SC and ASCOT-UK was funded by the National Institutes of Health Research (NIHR). Anna F. Dominiczak was supported by the British Heart Foundation (Grant Numbers RG/07/005/23633, SP/08/005/25115); and by the European Union Ingenious HyperCare Consortium: Integrated Genomics, Clinical Research, and Care in Hypertension (grant number LSHM-C7-2006-037093). Nilesh J. Samani is supported by the British Heart Foundation and is a Senior National Institute for Health Research Investigator. Panos Deloukas is supported by the British Heart Foundation (RG/14/5/30893), and NIHR, where his work forms part of the research themes contributing to the translational research portfolio of Barts Cardiovascular Biomedical Research Centre which is funded by the National Institute for Health Research (NIHR). The LOLIPOP study is supported by the National Institute for Health Research (NIHR) Comprehensive Biomedical Research Centre Imperial College Healthcare NHS Trust, the British Heart Foundation (SP/04/002), the Medical Research Council (G0601966, G0700931), the Wellcome Trust (084723/Z/08/Z, 090532 & 098381) the NIHR (RP-PG-0407-10371), the NIHR Official Development Assistance (ODA, award 16/136/68), the European Union FP7 (EpiMigrant, 279143) and H2020 programs (iHealth-T2D, 643774). We acknowledge support of the MRC-PHE Centre for Environment and Health, and the NIHR Health Protection Research Unit on Health Impact of Environmental Hazards. The work was carried out in part at the NIHR/Wellcome Trust Imperial Clinical Research Facility. The views expressed are those of the author(s) and not necessarily those of the Imperial College Healthcare NHS Trust, the NHS, the NIHR or the Department of Health. We thank the participants and research staff who made the study possible. JC is supported by the Singapore Ministry of Health's National Medical Research Council under its Singapore Translational Research Investigator (STaR) Award (NMRC/STaR/0028/2017). The research was supported by the National Institute for Health Research (NIHR) Exeter Clinical Research Facility and ERC grant 323195; SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC to T.M. Frayling. Hanieh Yaghootkar is funded by Diabetes UK RD Lawrence fellowship (grant:17/0005594) Anna Dominiczak was funded by a BHF Centre of Research Excellence Award (RE/13/5/30177) GSCAN participating cohorts: The Collaborative Study on the Genetics of Alcoholism (COGA), Principal Investigators: B. Porjesz, V. Hesselbrock, H. Edenberg, L. Bierut. The study includes eleven different centers: University of Connecticut (V. Hesselbrock); Indiana University (H.J. Edenberg, J. Nurnberger Jr., T. Foroud); University of Iowa (S. Kuperman, J. Kramer); SUNY Downstate (B. Porjesz); Washington University in St. Louis (L. Bierut, J. Rice, K. Bucholz, A. Agrawal); University of California at San Diego (M. Schuckit); Rutgers University (J. Tischfield, A. Brooks); Department of Biomedical and Health Informatics, The Children's Hospital of Philadelphia; Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia PA (L. Almasy), Virginia Commonwealth University (D. Dick), Icahn School of Medicine at Mount Sinai (A. Goate), and Howard University (R. Taylor). Other COGA collaborators include: L. Bauer (University of Connecticut); J. McClintick, L. Wetherill, X. Xuei, Y. Liu, D. Lai, S. O'Connor, M. Plawecki, S. Lourens (Indiana University); G. Chan (University of Iowa; University of Connecticut); J. Meyers, D. Chorlian, C. Kamarajan, A. Pandey, J. Zhang (SUNY Downstate); J.-C. Wang, M. Kapoor, S. Bertelsen (Icahn School of Medicine at Mount Sinai); A. Anokhin, V. McCutcheon, S. Saccone (Washington University); J. Salvatore, F. Aliev, B. Cho (Virginia Commonwealth University); and Mark Kos (University of Texas Rio Grande Valley). A. Parsian and M. Reilly are the NIAAA Staff Collaborators. COGA investigators continue to be inspired by their memories of Henri Begleiter and Theodore Reich, founding PI and Co-PI of COGA, and also owe a debt of gratitude to other past organizers of COGA, including Ting-Kai Li, P. Michael Conneally, Raymond Crowe, and Wendy Reich, for their critical contributions. COGA investigators are very grateful to Dr. Bruno Buecher without whom this project would not have existed. The authors also thank all those at the GECCO Coordinating Center for helping bring together the data and people that made this project possible. ASTERISK, a GECCO sub-study, also thanks all those who agreed to participate in this study, including the patients and the healthy control persons, as well as all the physicians, technicians and students. As part of the GECCO sub-studies, CPS-II authors thank the CPS-II participants and Study Management Group for their invaluable contributions to this research. The authors would also like to acknowledge the contribution to this study from central cancer registries supported through the Centers for Disease Control and Prevention National Program of Cancer Registries, and cancer registries supported by the National Cancer Institute Surveillance Epidemiology and End Results program. Another GECCO sub-study, HPFS and NHS investigators would like to acknowledge Patrice Soule and Hardeep Ranu of the Dana Farber Harvard Cancer Center High-Throughput Polymorphism Core who assisted in the genotyping for NHS, HPFS under the supervision of Dr. Immaculata Devivo and Dr. David Hunter, Qin (Carolyn) Guo and Lixue Zhu who assisted in programming for NHS and HPFS. HPFS and NHS investigators also thank the participants and staff of the Nurses' Health Study and the Health Professionals Follow-Up Study, for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. The authors assume full responsibility for analyses and interpretation of these data. PLCO, a substudy within GECCO, was supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, and additionally supported by contracts from the Division of Cancer Prevention, National Cancer Institute, NIH, DHHS. Additionally, a subset of control samples were genotyped as part of the Cancer Genetic Markers of Susceptibility (CGEMS) Prostate Cancer GWAS1, CGEMS pancreatic cancer scan (PanScan)2, 3, and the Lung Cancer and Smoking study4. The prostate and PanScan study datasets were accessed with appropriate approval through the dbGaP online resource (http://cgems.cancer.gov/data/) accession numbers phs000207.v1.p1 and phs000206.v3.p2, respectively, and the lung datasets were accessed from the dbGaP website (http://www.ncbi.nlm.nih.gov/gap) through accession number phs000093.v2.p2. For the lung study, the GENEVA Coordinating Center provided assistance with genotype cleaning and general study coordination, and the Johns Hopkins University Center for Inherited Disease Research conducted genotyping. The authors thank Drs. Christine Berg and Philip Prorok, Division of Cancer Prevention, National Cancer Institute, the Screening Center investigators and staff or the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial, Mr. Tom Riley and staff, Information Management Services, Inc., Ms. Barbara O'Brien and staff, Westat, Inc., and Drs. Bill Kopp and staff, SAIC-Frederick. Most importantly, we acknowledge the study participants for their contributions to making this study possible. We also thank all participants and staff of the André and France Desmarais Montreal Heart Institute's (MHI) Biobank. The genotyping of the MHI Biobank was done at the MHI Pharmacogenomic Centre and funded by the MHI Foundation. HRS is supported by the National Institute on Aging (NIA U01AG009740). The genotyping was funded separately by the National Institute on Aging (RC2 AG036495, RC4 AG039029). Our genotyping was conducted by the NIH Center for Inherited Disease Research (CIDR) at Johns Hopkins University. Genotyping quality control and final preparation of the data were performed by the University of Michigan School of Public Health. CHDExome+ participating cohorts: BRAVE: The BRAVE study genetic epidemiology working group is a collaboration between the Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, UK, the Centre for Control of Chronic Diseases, icddr,b, Dhaka, Bangladesh and the National Institute of Cardiovascular Diseases, Dhaka, Bangladesh. CCHS, CIHDS, and CGPS collaborators thank participants and staff of the Copenhagen City Heart Study, Copenhagen Ischemic Heart Disease Study, and the Copenhagen General Population Study for their important contributions. EPIC-CVD: CHD case ascertainment and validation, genotyping, and clinical chemistry assays in EPIC-CVD were principally supported by grants awarded to the University of Cambridge from the EU Framework Programme 7 (HEALTH-F2-2012-279233), the UK Medical Research Council (G0800270) and British Heart Foundation (SP/09/002), and the European Research Council (268834). We thank all EPIC participants and staff for their contribution to the study, the laboratory teams at the Medical Research Council Epidemiology Unit for sample management and Cambridge Genomic Services for genotyping, Sarah Spackman for data management, and the team at the EPIC-CVD Coordinating Centre for study coordination and administration. MORGAM: The work by MORGAM collaborators has been sustained by the MORGAM Project's recent funding: European Union FP 7 projects ENGAGE (HEALTH-F4-2007-201413), CHANCES (HEALTH-F3-2010-242244) and BiomarCaRE (278913). This has supported central coordination, workshops and part of the activities of the The MORGAM Data Centre, at THL in Helsinki, Finland. MORGAM Participating Centres are funded by regional and national governments, research councils, charities, and other local sources. PROSPER: collaborators have received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement n° HEALTH-F2-2009-223004 PROMIS: The PROMIS collaborators are are thankful to all the study participants in Pakistan. Recruitment in PROMIS was funded through grants available to investigators at the Center for Non-Communicable Diseases, Pakistan (Danish Saleheen and Philippe Frossard) and investigators at the University of Cambridge, UK (Danish Saleheen and John Danesh). Field-work, genotyping, and standard clinical chemistry assays in PROMIS were principally supported by grants awarded to the University of Cambridge from the British Heart Foundation, UK Medical Research Council, Wellcome Trust, EU Framework 6-funded Bloodomics Integrated Project, Pfizer. We would like to acknowledge the contributions made by the following individuals who were involved in the field work and other administrative aspects of the study: Mohammad Zeeshan Ozair, Usman Ahmed, Abdul Hakeem, Hamza Khalid, Kamran Shahid, Fahad Shuja, Ali Kazmi, Mustafa Qadir Hameed, Naeem Khan, Sadiq Khan, Ayaz Ali, Madad Ali, Saeed Ahmed, Muhammad Waqar Khan, Muhammad Razaq Khan, Abdul Ghafoor, Mir Alam, Riazuddin, Muhammad Irshad Javed, Abdul Ghaffar, Tanveer Baig Mirza, Muhammad Shahid, Jabir Furqan, Muhammad Iqbal Abbasi, Tanveer Abbas, Rana Zulfiqar, Muhammad Wajid, Irfan Ali, Muhammad Ikhlaq, Danish Sheikh and Muhammad Imran. INTERVAL: Participants in the INTERVAL randomised controlled trial were recruited with the active collaboration of NHS Blood and Transplant England (www.nhsbt.nhs.uk), which has supported field work and other elements of the trial. DNA extraction and genotyping was funded by the National Institute of Health Research (NIHR), the NIHR BioResource (http://bioresource.nihr.ac.uk/) and the NIHR Cambridge Biomedical Research Centre (www.cambridge-brc.org.uk). The academic coordinating centre for INTERVAL was supported by core funding from: NIHR Blood and Transplant Research Unit in Donor Health and Genomics, UK Medical Research Council (MR/L003120/1), British Heart Foundation (RG/13/13/30194), and NIHR Research Cambridge Biomedical Research Centre. A complete list of the investigators and contributors to the INTERVAL trial is provided in reference.
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