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1. Proteogenomic links to human metabolic diseases

Author

Mine Koprulu, Julia Carrasco-Zanini, Eleanor Wheeler, Sam Lockhart, Nicola D. Kerrison, Nicholas J. Wareham, Maik Pietzner, and Claudia Langenberg

Subjects
Physiology (medical), Endocrinology, Diabetes and Metabolism, Internal Medicine, Cell Biology
Published
2023

2. Genomic atlas of the plasma metabolome prioritizes metabolites implicated in human diseases

Author

Yiheng Chen, Tianyuan Lu, Ulrika Pettersson-Kymmer, Isobel D. Stewart, Guillaume Butler-Laporte, Tomoko Nakanishi, Agustin Cerani, Kevin Y. H. Liang, Satoshi Yoshiji, Julian Daniel Sunday Willett, Chen-Yang Su, Parminder Raina, Celia M. T. Greenwood, Yossi Farjoun, Vincenzo Forgetta, Claudia Langenberg, Sirui Zhou, Claes Ohlsson, and J. Brent Richards

Subjects
Genetics, Article
Abstract

Metabolic processes can influence disease risk and provide therapeutic targets. By conducting genome-wide association studies of 1,091 blood metabolites and 309 metabolite ratios, we identified associations with 690 metabolites at 248 loci; and associations with 143 metabolite ratios at 69 loci. Integrating metabolite-gene and gene expression information identified 94 effector genes for 109 metabolites and 48 metabolite ratios. Using Mendelian Randomization (MR), we identified 22 metabolites and 20 metabolite ratios having estimated causal effect on 12 traits and diseases, including orotate for estimated bone mineral density, alpha-hydroxyisovalerate for body mass index and ergothioneine for inflammatory bowel disease and asthma. We further measured orotate level in a separate cohort and demonstrated that, consistent with MR, orotate levels were positively associated with incident hip fractures. This study provides a valuable resource describing the genetic architecture of metabolites and delivers insights into their roles in common diseases, thereby offering opportunities for therapeutic targets.

Published
2023

3. MC3R links nutritional state to childhood growth and the timing of puberty

Author

Anthony P. Coll, MN Bedenbaugh, DT Porter, David H. Rowitch, John R. B. Perry, D A van Heel, X Dai, Rachel N. Lippert, Debra Rimmington, A. L. Gonçalves Soares, Felix R. Day, Duckett K, Patrick Sweeney, Zhaoyang Xu, Ahsan Nabi Khan, Hilary C. Martin, John Tadross, Roger D. Cone, Brian Y.H. Lam, Klj Ellacott, Richard B. Simerly, J Rosmaninho-Salgado, Alice E. Williamson, Gkc Dowsett, Sarah Finer, Irene Cimino, Giles S.H. Yeo, Audrey Melvin, Kara Rainbow, Claudia Langenberg, Stephen O'Rahilly, Nicholas J. Wareham, Katherine Ridley, Richard C. Trembath, Staffan Holmqvist, Sophie Buller, N J Timpson, Kaitlin H Wade, Ken K. Ong, and Elena G. Bochukova

Subjects
Male, medicine.medical_specialty, Time Factors, Calorie, Adolescent, media_common.quotation_subject, Hypothalamus, Nutritional Status, Estrous Cycle, Nutrient sensing, Biology, Weight Gain, Article, Mice, Child Development, Central melanocortin system, Internal medicine, medicine, Animals, Humans, Sexual maturity, Obesity, Sexual Maturation, Insulin-Like Growth Factor I, Child, media_common, Aged, 80 and over, Menarche, Multidisciplinary, Homozygote, Puberty, Appetite, Melanocortins, Melanocortin 4 receptor, Phenotype, medicine.anatomical_structure, Endocrinology, Lean body mass, Female, Melanocortin, Receptor, Melanocortin, Type 3
Abstract

The state of somatic energy stores in metazoans is communicated to the brain, which regulates key aspects of behaviour, growth, nutrient partitioning and development1. The central melanocortin system acts through melanocortin 4 receptor (MC4R) to control appetite, food intake and energy expenditure2. Here we present evidence that MC3R regulates the timing of sexual maturation, the rate of linear growth and the accrual of lean mass, which are all energy-sensitive processes. We found that humans who carry loss-of-function mutations in MC3R, including a rare homozygote individual, have a later onset of puberty. Consistent with previous findings in mice, they also had reduced linear growth, lean mass and circulating levels of IGF1. Mice lacking Mc3r had delayed sexual maturation and an insensitivity of reproductive cycle length to nutritional perturbation. The expression of Mc3r is enriched in hypothalamic neurons that control reproduction and growth, and expression increases during postnatal development in a manner that is consistent with a role in the regulation of sexual maturation. These findings suggest a bifurcating model of nutrient sensing by the central melanocortin pathway with signalling through MC4R controlling the acquisition and retention of calories, whereas signalling through MC3R primarily regulates the disposition of calories into growth, lean mass and the timing of sexual maturation. MC3R deficiency is associated with a delay in the onset of puberty, and a reduction in growth and lean mass.

Published
2021

5. A Neanderthal OAS1 isoform protects individuals of European ancestry against COVID-19 susceptibility and severity

Author

David R. Morrison, Elsa Brunet-Ratnasingham, Marc Afilalo, Nardin Rezk, Michael Hultström, Maik Pietzner, Hugo Zeberg, Tala Abdullah, Nicola D. Kerrison, Daniel Kaufmann, Celia M. T. Greenwood, Tomoko Nakanishi, Guillaume Butler-Laporte, Elin Thysell, Claudia Langenberg, Kaiqiong Zhao, Danielle Henry, Michaël Chassé, Vincenzo Forgetta, Madeleine Durand, Miklos Lipcsey, Clare Paterson, Michael Pollak, Jonathan Afilalo, Yiheng Chen, Vincent Mooser, Xiaoqing Xue, Zaman Afrasiabi, Louis Petitjean, Meriem Bouab, J. Brent Richards, Johan Normark, Branka Vulesevic, Nofar Kimchi, Charlotte Guzman, Noor Almamlouk, Chris Tselios, Sirui Zhou, Robert Frithiof, Olumide Adeleye, and Laetitia Laurent

Subjects
0301 basic medicine, Innate immune system, business.industry, Confounding, Case-control study, Mendelian Randomization Analysis, General Medicine, Odds ratio, Quantitative trait locus, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, 030220 oncology & carcinogenesis, Severity of illness, Mendelian randomization, Immunology, Medicine, business
Abstract

To identify circulating proteins influencing Coronavirus Disease 2019 (COVID-19) susceptibility and severity, we undertook a two-sample Mendelian randomization (MR) study, rapidly scanning hundreds of circulating proteins while reducing bias due to reverse causation and confounding. In up to 14,134 cases and 1.2 million controls, we found that an s.d. increase in OAS1 levels was associated with reduced COVID-19 death or ventilation (odds ratio (OR) = 0.54, P = 7 × 10−8), hospitalization (OR = 0.61, P = 8 × 10−8) and susceptibility (OR = 0.78, P = 8 × 10−6). Measuring OAS1 levels in 504 individuals, we found that higher plasma OAS1 levels in a non-infectious state were associated with reduced COVID-19 susceptibility and severity. Further analyses suggested that a Neanderthal isoform of OAS1 in individuals of European ancestry affords this protection. Thus, evidence from MR and a case–control study support a protective role for OAS1 in COVID-19 adverse outcomes. Available pharmacological agents that increase OAS1 levels could be prioritized for drug development. A variant of the OAS1 gene, which encodes an enzyme that is critical for the innate immune response to viral infections, is associated with decreased risk of death in patients with COVID-19.

Published
2021

6. Author Correction: Proteogenomic links to human metabolic diseases

Author

Mine Koprulu, Julia Carrasco-Zanini, Eleanor Wheeler, Sam Lockhart, Nicola D. Kerrison, Nicholas J. Wareham, Maik Pietzner, and Claudia Langenberg

Subjects
Physiology (medical), Endocrinology, Diabetes and Metabolism, Internal Medicine, Cell Biology
Published
2023

7. A cross-platform approach identifies genetic regulators of human metabolism and health

Author

Kay-Tee Khaw, Angela M. Wood, Julian L. Griffin, Gabi Kastenmüller, Fiona M. Gribble, Adam S. Butterworth, Luca A. Lotta, Verena Zuber, Chen Li, Victoria P W Auyeung, Johannes Raffler, Isobel D. Stewart, Nita G. Forouhi, Jian'an Luan, Nicholas J. Wareham, Claudia Langenberg, Maik Pietzner, Laura B. L. Wittemans, Eleanor Wheeler, Robert A. Scott, Roberto Bonelli, John Danesh, Frank Reimann, Praveen Surendran, Stephen Burgess, Ellie Paige, Clare Oliver-Williams, Albert Koulman, Fumiaki Imamura, Eric B. Fauman, Gregory A. Michelotti, Melanie Bahlo, Eleanor Sanderson, and Emma K. Biggs

Subjects
Nonsynonymous substitution, 0303 health sciences, Mechanism (biology), Genome-wide association study, Computational biology, Biology, 03 medical and health sciences, 0302 clinical medicine, Pleiotropy, Mendelian randomization, Genetics, Genetic Pleiotropy, Metabolome, Allelic heterogeneity, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract

In cross-platform analyses of 174 metabolites, we identify 499 associations (P

Published
2021

8. Metabolomic profiling reveals extensive adrenal suppression due to inhaled corticosteroid therapy in asthma

Author

Priyadarshini Kachroo, Isobel D. Stewart, Rachel S. Kelly, Meryl Stav, Kevin Mendez, Amber Dahlin, Djøra I. Soeteman, Su H. Chu, Mengna Huang, Margaret Cote, Hanna M. Knihtilä, Kathleen Lee-Sarwar, Michael McGeachie, Alberta Wang, Ann Chen Wu, Yamini Virkud, Pei Zhang, Nicholas J. Wareham, Elizabeth W. Karlson, Craig E. Wheelock, Clary Clish, Scott T. Weiss, Claudia Langenberg, Jessica A. Lasky-Su, Kachroo, Priyadarshini [0000-0002-5807-1333], Kelly, Rachel S [0000-0003-3023-1822], Stav, Meryl [0000-0001-6565-3617], Cote, Margaret [0000-0001-8079-7221], Lee-Sarwar, Kathleen [0000-0003-0550-1640], Wareham, Nicholas J [0000-0003-1422-2993], Clish, Clary [0000-0001-8259-9245], Langenberg, Claudia [0000-0002-5017-7344], Lasky-Su, Jessica A [0000-0001-6236-4705], and Apollo - University of Cambridge Repository

Subjects
Adrenal Cortex Hormones, Administration, Inhalation, Humans, General Medicine, General Economics, Econometrics and Finance, General Biochemistry, Genetics and Molecular Biology, health care economics and organizations, Asthma
Abstract

The application of large-scale metabolomic profiling provides new opportunities for realizing the potential of omics-based precision medicine for asthma. By leveraging data from over 14,000 individuals in four distinct cohorts, this study identifies and independently replicates 17 steroid metabolites whose levels were significantly reduced in individuals with prevalent asthma. Although steroid levels were reduced among all asthma cases regardless of medication use, the largest reductions were associated with inhaled corticosteroid (ICS) treatment, as confirmed in a 4-year low-dose ICS clinical trial. Effects of ICS treatment on steroid levels were dose dependent; however, significant reductions also occurred with low-dose ICS treatment. Using information from electronic medical records, we found that cortisol levels were substantially reduced throughout the entire 24-hour daily period in patients with asthma who were treated with ICS compared to those who were untreated and to patients without asthma. Moreover, patients with asthma who were treated with ICS showed significant increases in fatigue and anemia as compared to those without ICS treatment. Adrenal suppression in patients with asthma treated with ICS might, therefore, represent a larger public health problem than previously recognized. Regular cortisol monitoring of patients with asthma treated with ICS is needed to provide the optimal balance between minimizing adverse effects of adrenal suppression while capitalizing on the established benefits of ICS treatment.

Published
2022

9. Plasma protein patterns as comprehensive indicators of health

Author

Tim Bauer, Martin J. Shipley, Mark A. Sarzynski, Leigh Alexander, Yolanda Hagar, Michael A Hinterberg, Aroon D. Hingorani, Stephen A. Williams, Mika Kivimäki, Juan P. Casas, Sophie Weiss, Christian Jonasson, Claudia Langenberg, Nicholas J. Wareham, Rachel Ostroff, Peter Ganz, Gargi Datta, Jessica Chadwick, Jessica A. Ash, Robert Kirk DeLisle, and Claude Bouchard

Subjects
Male, 0301 basic medicine, Diabetes risk, Immunology, Disease, Intra-Abdominal Fat, Cardiovascular, Bioinformatics, Medical and Health Sciences, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, 0302 clinical medicine, Risk Factors, Behavioral and Social Science, Health care, Humans, Medicine, Obesity, Precision Medicine, Exercise, Life Style, Metabolic and endocrine, Nutrition, business.industry, Prevention, Blood Proteins, General Medicine, Precision medicine, Blood proteins, Health indicator, Heart Disease, Good Health and Well Being, 030104 developmental biology, Adipose Tissue, Liver, Health assessment, 030220 oncology & carcinogenesis, Body Composition, Lean body mass, Female, Generic health relevance, business
Abstract

Proteins are effector molecules that mediate the functions of genes1,2 and modulate comorbidities3–10, behaviors and drug treatments11. They represent an enormous potential resource for personalized, systemic and data-driven diagnosis, prevention, monitoring and treatment. However, the concept of using plasma proteins for individualized health assessment across many health conditions simultaneously has not been tested. Here, we show that plasma protein expression patterns strongly encode for multiple different health states, future disease risks and lifestyle behaviors. We developed and validated protein-phenotype models for 11 different health indicators: liver fat, kidney filtration, percentage body fat, visceral fat mass, lean body mass, cardiopulmonary fitness, physical activity, alcohol consumption, cigarette smoking, diabetes risk and primary cardiovascular event risk. The analyses were prospectively planned, documented and executed at scale on archived samples and clinical data, with a total of ~85 million protein measurements in 16,894 participants. Our proof-of-concept study demonstrates that protein expression patterns reliably encode for many different health issues, and that large-scale protein scanning12–16 coupled with machine learning is viable for the development and future simultaneous delivery of multiple measures of health. We anticipate that, with further validation and the addition of more protein-phenotype models, this approach could enable a single-source, individualized so-called liquid health check. Large-scale aptamer-based scanning of plasma proteins coupled with machine learning demonstrates proof-of-concept and feasibility of an individualized health check using a single blood sample.

Published
2019

10. Autoimmunity plays a role in the onset of diabetes after 40 years of age

Author

Vittorio Krogh, Rudolf Kaaks, Yvonne T. van der Schouw, Gianluca Severi, Eva Ardanaz, Marc J. Gunter, Tilman Kühn, Nicholas J. Wareham, Timothy J. Key, Francesca Mancini, Carlotta Sacerdote, María José Sánchez, Heiner Boeing, Annemieke M.W. Spijkerman, Peter M. Nilsson, Guy Fagherazzi, Miren Dorronsoro, María Dolores Chirlaque, Kay-Tee Khaw, Olov Rolandsson, Stephen J. Sharp, Salvatore Panico, Domenico Palli, Nita G. Forouhi, Christiane S. Hampe, Claudia Langenberg, Kim Overvad, Rosario Tumino, Elio Riboli, Centre de recherche en épidémiologie et santé des populations (CESP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris-Sud - Paris 11 (UP11)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), LSHM_CT_2006_037197 N∫ 6236 National Institutes of Health, NIH: DK26190 Compagnia di San Paolo Kræftens Bekæmpelse, DCS German Cancer Research Center, DKFZ Medical Research Council, MRC: MC_UU_12015/1, MC_UU_12015/5, MR/N003284/1 Cancer Research UK, CRUK World Cancer Research Fund, WCRF Bundesministerium für Bildung und Forschung, BMBF Västerbotten Läns Landsting Ministerie van Volksgezondheid, Welzijn en Sport, VWS Agentschap NL: IGE05012 Vetenskapsrådet, VR Umeå Universitet Bundesministerium für Forschung und Technologie, BMFT Deutsche Krebshilfe Bundesministerium für Bildung und Frauen, BMBF Stichting Diabetes Onderzoek Nederland NIHR Imperial Biomedical Research Centre, BRC NIHR Cambridge Biomedical Research Centre: IS-BRC-1215-20014, O. Rolandsson: The Västerboten County Council, M. Dorronsoro: We thank the participants of the Spanish EPIC cohort for their contribution to the study as well as to the team of trained nurses who participated in the recruitment, R. Kaaks: German Cancer Aid, German Ministry of Research (BMBF), K. T. Khaw: Medical Research Council UK, Cancer Research UK, T. Kühn: German Cancer Aid, German Cancer Research Center (DKFZ), German Federal Ministry of Education and Research (BMBF), S. Panico: Compagnia di San Paolo, A. M. W. Spijkerman: EPIC Bilthoven and Utrecht acknowledge the Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), Statistics Netherlands (the Netherlands), EPIC Ragusa acknowledges for their participation blood donors of AVIS-Ragusa (local blood donors association), Y. T. van der Schouw: EPIC Bilthoven and Utrecht acknowledge the Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), Dutch ZON (Zorg Onderzoek Nederland), WCRF, Statistics Netherland, E. Riboli: Imperial College Biomedical Research Centre., Open access funding provided by Umea University. Funding for the InterAct project was provided by the EU FP6 Programme (grant number LSHM_CT_2006_037197). The autoantibody measurement was funded by Västerbotten County Council and Umeå University, Sweden (OR), the National Institutes of Health (DK26190) (CSH) and the Medical Research Council (MC_UU_12015/1) (NJW). OR: the Västerbotten County Council, Umeå University, MDC: Health Research Fund (FIS) of the Spanish Ministry of Health, Murcia Regional Government (N∫ 6236), EA: the Health Research Fund (FIS) of the Spanish Ministry of Health and Navarre Regional Government, RK: German Cancer Aid, the German Ministry of Research (BMBF), TJK: Cancer Research UK, KTK: the Medical Research Council UK, Cancer Research UK, PMN: the Swedish Research Council, KO: the Danish Cancer Society, SP: Compagnia di San Paolo, AMWS: the Dutch Ministry of Public Health, Welfare and Sports (VWS), the Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands, RT: AIRE-ONLUS Ragusa, AVIS-Ragusa, Sicilian Regional Government, AMWS: LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), YTvdS: verification of diabetes cases was additionally funded by NL Agency grant IGE05012 and an Incentive Grant from the Board of the UMC Utrecht, LK Research Funds, Dutch Prevention Funds, NGF: MRC core support (MC_UU_12015/5), NIHR Cambridge Biomedical Research Centre (IS-BRC-1215-20014). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Acknowledgements, We thank all EPIC participants and staff for their contribution to this study. We thank N. Kerrison (MRC Epidemiology Unit, Cambridge, UK) for managing the data and the laboratory team at the MRC Epidemiology Unit, Cambridge for managing the blood samples for the EPIC-InterAct project. We thank the participants of the Spanish EPIC cohort for their contribution to the study as well as the team of trained nurses who participated in the recruitment. O. Rolandsson: The V?sterboten County Council, T. K?hn: German Cancer Aid, German Cancer Research Center (DKFZ), German Federal Ministry of Education and Research (BMBF), E. Riboli: Imperial College Biomedical Research Centre. Some of the data were presented as an abstract at the 54th EASD Annual Meeting in 2018., Rolandsson, Olov [0000-0002-1341-6828], and Apollo - University of Cambridge Repository

Subjects
Male, [SDV]Life Sciences [q-bio], Endocrinology, Diabetes and Metabolism, Autoimmunity, Type 2 diabetes, medicine.disease_cause, LADA, Endocrinology, Autoantibody, 0302 clinical medicine, POPULATION, RISK, 0303 health sciences, Glutamate Decarboxylase, ANTIBODY POSITIVITY, GAD, Middle Aged, Phenotype, Genetic risk score, Pathophysiology, 3. Good health, Diabetes and Metabolism, Type 1 diabetes, Endokrinologi och diabetes, Female, Life Sciences & Biomedicine, Adult, 030209 endocrinology & metabolism, Endocrinology and Diabetes, Antibodies, Article, 1117 Public Health and Health Services, Endocrinology & Metabolism, 03 medical and health sciences, GLUTAMIC-ACID DECARBOXYLASE, Insulin resistance, Diabetes mellitus, Internal Medicine, medicine, Humans, TYPE-1, Aged, 030304 developmental biology, Science & Technology, business.industry, RECOGNITION, 1103 Clinical Sciences, ADULTS, medicine.disease, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Incident diabetes, Case-Control Studies, Immunology, 1114 Paediatrics and Reproductive Medicine, AUTOANTIBODIES, indident diabetes, business
Abstract

Aims/hypothesis Type 1 and type 2 diabetes differ with respect to pathophysiological factors such as beta cell function, insulin resistance and phenotypic appearance, but there may be overlap between the two forms of diabetes. However, there are relatively few prospective studies that have characterised the relationship between autoimmunity and incident diabetes. We investigated associations of antibodies against the 65 kDa isoform of GAD (GAD65) with type 1 diabetes and type 2 diabetes genetic risk scores and incident diabetes in adults in European Prospective Investigation into Cancer and Nutrition (EPIC)-InterAct, a case-cohort study nested in the EPIC cohort. Methods GAD65 antibodies were analysed in EPIC participants (over 40 years of age and free of known diabetes at baseline) by radioligand binding assay in a random subcohort (n = 15,802) and in incident diabetes cases (n = 11,981). Type 1 diabetes and type 2 diabetes genetic risk scores were calculated. Associations between GAD65 antibodies and incident diabetes were estimated using Prentice-weighted Cox regression. Results GAD65 antibody positivity at baseline was associated with development of diabetes during a median follow-up time of 10.9 years (HR for GAD65 antibody positive vs negative 1.78; 95% CI 1.43, 2.20) after adjustment for sex, centre, physical activity, smoking status and education. The genetic risk score for type 1 diabetes but not type 2 diabetes was associated with GAD65 antibody positivity in both the subcohort (OR per SD genetic risk 1.24; 95% CI 1.03, 1.50) and incident cases (OR 1.97; 95% CI 1.72, 2.26) after adjusting for age and sex. The risk of incident diabetes in those in the top tertile of the type 1 diabetes genetic risk score who were also GAD65 antibody positive was 3.23 (95% CI 2.10, 4.97) compared with all other individuals, suggesting that 1.8% of incident diabetes in adults was attributable to this combination of risk factors. Conclusions/interpretation Our study indicates that incident diabetes in adults has an element of autoimmune aetiology. Thus, there might be a reason to re-evaluate the present subclassification of diabetes in adulthood.

Published
2019

11. Author Correction: Metabolomic profiling reveals extensive adrenal suppression due to inhaled corticosteroid therapy in asthma

Author

Priyadarshini Kachroo, Isobel D. Stewart, Rachel S. Kelly, Meryl Stav, Kevin Mendez, Amber Dahlin, Djøra I. Soeteman, Su H. Chu, Mengna Huang, Margaret Cote, Hanna M. Knihtilä, Kathleen Lee-Sarwar, Michael McGeachie, Alberta Wang, Ann Chen Wu, Yamini Virkud, Pei Zhang, Nicholas J. Wareham, Elizabeth W. Karlson, Craig E. Wheelock, Clary Clish, Scott T. Weiss, Claudia Langenberg, and Jessica A. Lasky-Su

Subjects
General Medicine, General Biochemistry, Genetics and Molecular Biology
Published
2022

12. Genetic disruption of serine biosynthesis is a key driver of macular telangiectasia type 2 aetiology and progression

Author

Tunde Peto, Alan C. Bird, Ferenc B Sallo, Brendan R E Ansell, Roberto Bonelli, Claudia Langenberg, Thomas S. Scerri, Traci E Clemons, Irene Leung, Luca A. Lotta, Melanie Bahlo, Bahlo, Melanie [0000-0001-5132-0774], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, lcsh:Medicine, Genome-wide association study, Disease, 0302 clinical medicine, Serine, GWAS, Mendelian randomisation, Genetics (clinical), Macular telangiectasia, Genetics, 0303 health sciences, 3. Good health, Statistical genetics, Disease Progression, Metabolome, Molecular Medicine, Retinal Disorder, lcsh:QH426-470, Endophenotypes, Genomics, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Mendelian randomization, medicine, Metabolomics, Humans, Genetic Predisposition to Disease, Molecular Biology, 030304 developmental biology, Genetic association, Research, lcsh:R, Retinal Vessels, medicine.disease, Human genetics, Biosynthetic Pathways, lcsh:Genetics, 030104 developmental biology, Diabetes Mellitus, Type 2, Genetic Loci, Endophenotype, Retinal disease, 030221 ophthalmology & optometry, Retinal Telangiectasis, Genome-Wide Association Study
Abstract

Background Macular telangiectasia type 2 (MacTel) is a rare, heritable and largely untreatable retinal disorder, often comorbid with diabetes. Genetic risk loci subtend retinal vascular calibre and glycine/serine/threonine metabolism genes. Serine deficiency may contribute to MacTel via neurotoxic deoxysphingolipid production; however, an independent vascular contribution is also suspected. Here, we use statistical genetics to dissect the causal mechanisms underpinning this complex disease. Methods We integrated genetic markers for MacTel, vascular and metabolic traits, and applied Mendelian randomisation and conditional and interaction genome-wide association analyses to discover the causal contributors to both disease and spatial retinal imaging sub-phenotypes. Results Genetically induced serine deficiency is the primary causal metabolic driver of disease occurrence and progression, with a lesser, but significant, causal contribution of type 2 diabetes genetic risk. Conversely, glycine, threonine and retinal vascular traits are unlikely to be causal for MacTel. Conditional regression analysis identified three novel disease loci independent of endogenous serine biosynthetic capacity. By aggregating spatial retinal phenotypes into endophenotypes, we demonstrate that SNPs constituting independent risk loci act via related endophenotypes. Conclusions Follow-up studies after GWAS integrating publicly available data with deep phenotyping are still rare. Here, we describe such analysis, where we integrated retinal imaging data with MacTel and other traits genomics data to identify biochemical mechanisms likely causing this disorder. Our findings will aid in early diagnosis and accurate prognosis of MacTel and improve prospects for effective therapeutic intervention. Our integrative genetics approach also serves as a useful template for post-GWAS analyses in other disorders.

Published
2021

13. Author Correction: Genetic architecture of host proteins involved in SARS-CoV-2 infection

Author

Chris Finan, Aroon D. Hingorani, Johannes Raffler, Jian'an Luan, Claudia Langenberg, Maik Pietzner, Victoria P W Auyeung, Rachel Ostroff, Julia Carrasco-Zanini, Markus Ralser, Juan P Casas, Eleanor Wheeler, Steve A. Williams, Nicholas J. Wareham, Nicola D. Kerrison, Gabi Kastenmüller, Eric R. Gamazon, and Erin Oerton

Subjects
2019-20 coronavirus outbreak, Multidisciplinary, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Science, General Physics and Astronomy, General Chemistry, Biology, Virology, Host protein, Genetic architecture, General Biochemistry, Genetics and Molecular Biology
Abstract

A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-21370-6

Published
2021
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14. Genome-wide association analysis of type 2 diabetes in the EPIC-InterAct study

Author

Peter M. Nilsson, Olov Rolandsson, Eleanor Wheeler, Nicholas J. Wareham, Nita G. Forouhi, Matthias B. Schulze, Kim Overvad, Claudia Langenberg, Nicola D. Kerrison, Pilar Amiano, Catalina Bonet, Mark I. McCarthy, Inês Barroso, Yvonne T. van der Schouw, Lina Cai, Giovanna Masala, José María Huerta, Eva Ardanaz, Anne Tjønneland, Miguel Rodríguez-Barranco, Panos Deloukas, Leif Groop, Guy Fagherazzi, Jian'an Luan, Valeria Pala, Elio Riboli, Carlotta Sacerdote, Rosario Tumino, Paul W. Franks, Annemieke M.W. Spijkerman, Stephen J. Sharp, Salvatore Panico, Rudolf Kaaks, Cai, Lina [0000-0003-2598-8388], Wheeler, Eleanor [0000-0002-8616-6444], Luan, Jian'an [0000-0003-3137-6337], Deloukas, Panos [0000-0001-9251-070X], Groop, Leif C [0000-0002-0187-3263], Huerta, José María [0000-0002-9637-3869], Masala, Giovanna [0000-0002-5758-9069], Nilsson, Peter M [0000-0002-5652-8459], Overvad, Kim [0000-0001-6429-7921], Schulze, Matthias B [0000-0002-0830-5277], Tumino, Rosario [0000-0003-2666-414X], van der Schouw, Yvonne T [0000-0002-4605-435X], Forouhi, Nita G [0000-0002-5041-248X], Barroso, Inês [0000-0001-5800-4520], Langenberg, Claudia [0000-0002-5017-7344], Apollo - University of Cambridge Repository, Luan, Jian’an [0000-0003-3137-6337], Groop, Leif C. [0000-0002-0187-3263], Nilsson, Peter M. [0000-0002-5652-8459], Schulze, Matthias B. [0000-0002-0830-5277], van der Schouw, Yvonne T. [0000-0002-4605-435X], and Forouhi, Nita G. [0000-0002-5041-248X]

Subjects
Gerontology, Data Descriptor, endocrine system diseases, Epidemiology, Type 2 diabetes, 0302 clinical medicine, Risk Factors, Genetics research, 692/699/2743/137/773, 692/308/174, Prospective Studies, lcsh:Science, Prospective cohort study, 0303 health sciences, Diabetis, Diabetes, Computer Science Applications, Europe, Cardiovascular diseases, Endokrinologi och diabetes, Cohort, Statistics, Probability and Uncertainty, data-descriptor, Information Systems, Statistics and Probability, medicine.medical_specialty, MEDLINE, 030209 endocrinology & metabolism, Single-nucleotide polymorphism, Endocrinology and Diabetes, Library and Information Sciences, Education, 03 medical and health sciences, medicine, Mortalitat, Humans, Mortality, Life Style, 030304 developmental biology, Genetic association, business.industry, Malalties cardiovasculars, Public health, 692/308/2056, nutritional and metabolic diseases, medicine.disease, Summary statistics, Diabetes Mellitus, Type 2, lcsh:Q, business, Genome-Wide Association Study
Abstract

Funder: European Union FP6 programme grant number LSHM_CT_2006_037197, Type 2 diabetes (T2D) is a global public health challenge. Whilst the advent of genome-wide association studies has identified >400 genetic variants associated with T2D, our understanding of its biological mechanisms and translational insights is still limited. The EPIC-InterAct project, centred in 8 countries in the European Prospective Investigations into Cancer and Nutrition study, is one of the largest prospective studies of T2D. Established as a nested case-cohort study to investigate the interplay between genetic and lifestyle behavioural factors on the risk of T2D, a total of 12,403 individuals were identified as incident T2D cases, and a representative sub-cohort of 16,154 individuals was selected from a larger cohort of 340,234 participants with a follow-up time of 3.99 million person-years. We describe the results from a genome-wide association analysis between more than 8.9 million SNPs and T2D risk among 22,326 individuals (9,978 cases and 12,348 non-cases) from the EPIC-InterAct study. The summary statistics to be shared provide a valuable resource to facilitate further investigations into the genetics of T2D.

Published
2020

15. Assessing the causal association of glycine with risk of cardio-metabolic diseases

Author

Heribert Schunkert, Stephen Burgess, Adam S. Butterworth, Nita G. Forouhi, Julian L. Griffin, Claudia Langenberg, Savita Karthikeyan, Clare Oliver-Williams, Lingyao Zeng, Laura B. L. Wittemans, Felix R. Day, Albert Koulman, Isobel D. Stewart, Angela M. Wood, Kay-Tee Khaw, Luca A. Lotta, Nicholas J. Wareham, John Danesh, Praveen Surendran, Jeanette Erdmann, Joanna M. M. Howson, Robert A. Scott, Fumiaki Imamura, Day, Felix R [0000-0003-3789-7651], Koulman, Albert [0000-0001-9998-051X], Imamura, Fumiaki [0000-0002-6841-8396], Forouhi, Nita G [0000-0002-5041-248X], Burgess, Stephen [0000-0001-5365-8760], Howson, Joanna MM [0000-0001-7618-0050], Butterworth, Adam S [0000-0002-6915-9015], Langenberg, Claudia [0000-0002-5017-7344], and Apollo - University of Cambridge Repository

Subjects
0301 basic medicine, Science, Glycine, General Physics and Astronomy, Genome-wide association study, Coronary Disease, 02 engineering and technology, Type 2 diabetes, Bioinformatics, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, Insulin resistance, Polymorphism (computer science), Diabetes mellitus, Hyperinsulinism, medicine, Humans, Genetic Predisposition to Disease, lcsh:Science, Genetic association, Multidisciplinary, business.industry, Incidence, General Chemistry, 021001 nanoscience & nanotechnology, medicine.disease, 3. Good health, ddc, 030104 developmental biology, Diabetes Mellitus, Type 2, Genetic Loci, Meta-analysis, lcsh:Q, 0210 nano-technology, business, Metabolic Networks and Pathways, Genome-Wide Association Study
Abstract

Circulating levels of glycine have previously been associated with lower incidence of coronary heart disease (CHD) and type 2 diabetes (T2D) but it remains uncertain if glycine plays an aetiological role. We present a meta-analysis of genome-wide association studies for glycine in 80,003 participants and investigate the causality and potential mechanisms of the association between glycine and cardio-metabolic diseases using genetic approaches. We identify 27 genetic loci, of which 22 have not previously been reported for glycine. We show that glycine is genetically associated with lower CHD risk and find that this may be partly driven by blood pressure. Evidence for a genetic association of glycine with T2D is weaker, but we find a strong inverse genetic effect of hyperinsulinaemia on glycine. Our findings strengthen evidence for a protective effect of glycine on CHD and show that the glycine-T2D association may be driven by a glycine-lowering effect of insulin resistance., Epidemiological studies have associated circulating levels of the amino acid glycine with cardiometabolic outcomes. Here, in a genome-wide meta-analysis of 80,003 individuals, Wittemans et al. identify 22 novel genetic loci for glycine and find a causal relationship with coronary heart disease using MR.

Published
2019

16. Correction: Appetite disinhibition rather than hunger explains genetic effects on adult BMI trajectory

Author

Archana Singh-Manoux, Daryth Stallone, Ayako Hiyoshi, Hiroyasu Iso, Adam G. Tabak, David Boniface, Martin J. Shipley, Koutatsu Maruyama, Clare H. Llewellyn, Meena Kumari, Noriko Cable, Eric J. Brunner, Nicholas J. Wareham, Mika Kivimäki, John Wilson, Claudia Langenberg, and Aroon D. Hingorani

Subjects
Nutrition and Dietetics, Disinhibition, Endocrinology, Diabetes and Metabolism, media_common.quotation_subject, Trajectory, medicine, Medicine (miscellaneous), Appetite, medicine.symptom, Psychology, Cognitive psychology, media_common
Abstract

A Correction to this paper has been published: https://doi.org/10.1038/s41366-021-00770-0

Published
2021

17. Genetic analysis reveals role of testosterone levels in human disease

Author

Claudia Langenberg, Benjamin Hollis, Jessica Tyrrell, Robin N Beaumont, Laura B. L. Wittemans, Douglas F. Easton, John R. B. Perry, Mark I. McCarthy, Felix R. Day, Tracy A. O'Mara, Anubha Mahajan, Stephen Burgess, A. Mesut Erzurumluoglu, Timothy M. Frayling, Nicholas J. Wareham, Alexander S Busch, Katherine S. Ruth, Anna Murray, Ken K. Ong, Andrew R. Wood, Deborah J. Thompson, and Susan Martin

Subjects
0301 basic medicine, Male, Endocrinology, Diabetes and Metabolism, Physiology, Type 2 diabetes, Disease, Bioinformatics, Genetic analysis, 0302 clinical medicine, Sex hormone-binding globulin, Endocrinology, Human disease, Odds Ratio, Cluster Analysis, Testosterone, Biological Specimen Banks, Estradiol, biology, medicine.diagnostic_test, General Medicine, Polycystic ovary, Phenotype, 030220 oncology & carcinogenesis, Body Composition, Female, Polycystic Ovary Syndrome, Genotype, MEDLINE, Breast Neoplasms, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, Sex Factors, medicine, Humans, Genetic Testing, Genetic testing, business.industry, Prostatic Neoplasms, Human Genetics, Testosterone (patch), Odds ratio, Mendelian Randomization Analysis, medicine.disease, United Kingdom, Human genetics, Endometrial Neoplasms, 030104 developmental biology, Diabetes Mellitus, Type 2, Haplotypes, biology.protein, Metabolic syndrome, Sexual function, business, Biomarkers, Software, Genome-Wide Association Study
Abstract

Testosterone supplementation is commonly used for its effects on sexual function, bone health and body composition, yet its effects on disease outcomes are unknown. To better understand this, we identified genetic determinants of testosterone levels and related sex hormone traits in 425,097 UK Biobank study participants. Using 2,571 genome-wide significant associations, we demonstrate that the genetic determinants of testosterone levels are substantially different between sexes and that genetically higher testosterone is harmful for metabolic diseases in women but beneficial in men. For example, a genetically determined 1 s.d. higher testosterone increases the risks of type 2 diabetes (odds ratio (OR) = 1.37 (95% confidence interval (95% CI): 1.22–1.53)) and polycystic ovary syndrome (OR = 1.51 (95% CI: 1.33–1.72)) in women, but reduces type 2 diabetes risk in men (OR = 0.86 (95% CI: 0.76–0.98)). We also show adverse effects of higher testosterone on breast and endometrial cancers in women and prostate cancer in men. Our findings provide insights into the disease impacts of testosterone and highlight the importance of sex-specific genetic analyses. Genetic analysis of data from over 400,000 participants in the UK Biobank Study shows that circulating testosterone levels have sex-specific implications for cardiometabolic diseases and cancer outcomes.

Published
2020

18. Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes

Author

Claire Morgan, Antonio Zorzano, Jason Flannick, Claudia Langenberg, David Torrents, Torben Hansen, Juan R. González, Tune H. Pers, Jorge Ferrer, Ehm A. Andersson, Jian'an Luan, Jose C. Florez, Ivan Brandslund, Aaron Leong, Marit E. Jørgensen, Ignasi Moran, Pascal Timshel, Robert A. Scott, Cramer Christensen, Emil V. R. Appel, Niels Grarup, Paula Cortes-Sánchez, Jonathan Marti, Varindepal Kaur, Oluf Pedersen, Santi González, Elias Rodriguez-Fos, Nicholas J. Wareham, Miriam S. Udler, Josep M. Mercader, Torben Jørgensen, Montserrat Puiggròs, Sílvia Bonàs-Guarch, Irene Miguel-Escalada, Carlos Díaz, David Sebastián, Rosa M. Badia, Daniel R. Witte, Allan Linneberg, Friman Sánchez, Mercè Planas-Fèlix, Marta Guindo-Martínez, Goutham Atla, Ministerio de Economía y Competitividad (España), European Foundation for the Study of Diabetes, Instituto de Salud Carlos III, Generalitat de Catalunya, Wellcome Trust, European Commission, Fundación 'la Caixa', National Institute for Health Research (UK), Novo Nordisk Foundation, Badia, Rosa M. [0000-0003-2941-5499], Bonàs-Guarch, Sílvia [0000-0002-2085-7488], Guindo-Martínez, Marta [0000-0002-8099-9170], Miguel-Escalada, Irene [0000-0003-3461-6404], Grarup, Niels [0000-0001-5526-1070], Rodriguez-Fos, Elias [0000-0002-2555-0178], Planas-Fèlix, Mercè [0000-0002-8267-576X], González, Santi [0000-0001-5685-4580], Morgan, Claire C [0000-0002-8191-3738], Moran, Ignasi [0000-0002-3307-7106], Puiggros, Montserrat [0000-0001-5034-7924], Linneberg, Allan [0000-0002-0994-0184], Jørgensen, Marit E [0000-0001-8356-5565], Hansen, Torben [0000-0001-8748-3831], Ferrer, Jorge [0000-0002-5959-5729], Mercader, Josep Maria [0000-0001-8494-3660], Torrents, David [0000-0002-6086-9037], Apollo - University of Cambridge Repository, Barcelona Supercomputing Center, Medical Research Council (MRC), Universitat de Barcelona, and Badia, Rosa M.

Subjects
Male, 0301 basic medicine, Insulin Resistance/genetics, General Physics and Astronomy, GLUCOSE, Technical support, 0302 clinical medicine, Human genetics, Risk Factors, Gene Regulatory Networks, lcsh:Science, media_common, Independent research, RISK, INSULIN-RESISTANCE, Diabetis, Genètica humana, Genome, Multidisciplinary, Genetic Predisposition to Disease/genetics, Diabetes, Biobank, 3. Good health, Multidisciplinary Sciences, Research centre, Science & Technology - Other Topics, LOW-FREQUENCY, DIET-INDUCED OBESITY, Genetic data, SUSCEPTIBILITY LOCI, Genotype, Science, Library science, Polymorphism, Single Nucleotide, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Chromosomes, Human, X/genetics, Diabetis--Diagnòstic, Political science, MD Multidisciplinary, Journal Article, Humans, media_common.cataloged_instance, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, European union, METAANALYSIS, Alleles, Chromosomes, Human, X, Science & Technology, Models, Genetic, Diabetes--Diagnosis, Extramural, PANCREATIC-ISLETS, General Chemistry, 030104 developmental biology, CELLS, Susceptibility locus, lcsh:Q, Insulin Resistance, 030217 neurology & neurosurgery, Gene Regulatory Networks/genetics, Genome-Wide Association Study, Ciències de la salut [Àrees temàtiques de la UPC]
Abstract

The reanalysis of existing GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics of complex diseases. By reanalyzing publicly available type 2 diabetes (T2D) genome-wide association studies (GWAS) data for 70,127 subjects, we identify seven novel associated regions, five driven by common variants (LYPLAL1, NEUROG3, CAMKK2, ABO, and GIP genes), one by a low-frequency (EHMT2), and one driven by a rare variant in chromosome Xq23, rs146662057, associated with a twofold increased risk for T2D in males. rs146662057 is located within an active enhancer associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a modulator of insulin sensitivity, and exhibits allelic specific activity in muscle cells. Beyond providing insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly available data using novel genetic resources and analytical approaches., This work has been sponsored by the grant SEV-2011-00067 of Severo Ochoa Program, awarded by the Spanish Government. This work was supported by an EFSD/Lilly research fellowship. Josep M. Mercader was supported by Sara Borrell Fellowship from the Instituto Carlos III and Beatriu de Pinós fellowship from the Agency for Management of University and Research Grants (AGAUR). Sílvia Bonàs was FI-DGR Fellowship from FI-DGR 2013 from Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR, Generalitat de Catalunya). This study makes use of data generated by the WTCCC. A full list of the investigators who contributed to the generation of the data is available from www.wtccc.org.uk. Funding for the project was provided by the Wellcome Trust under award 076113. This study also makes use of data generated by the UK10K Consortium, derived from samples from UK10K COHORT IMPUTATION (EGAS00001000713). A full list of the investigators who contributed to the generation of the data is available in www.UK10K.org. Funding for UK10K was provided by the Wellcome Trust under award WT091310. We acknowledge PRACE for awarding us to access MareNostrum supercomputer, based in Spain at Barcelona. The technical support group, particularly Pablo Ródenas and Jorge Rodríguez, from the Barcelona Supercomputing Center is gratefully acknowledged. This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 667191. Mercè Planas-Fèlix is funded by the Obra Social Fundación la Caixa fellowship under the Severo Ochoa 2013 program. Work from Irene Miguel-Escalada, Ignasi Moran, Goutham Atla, and Jorge Ferrer was supported by the National Institute for Health Research (NIHR) Imperial Biomedical Research Centre, the Wellcome Trust (WT101033), Ministerio de Economía y Competitividad (BFU2014-54284-R) and Horizon 2020 (667191). Irene Miguel-Escalada has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska–Curie grant agreement No 658145. We acknowledge Prof. Giulio Cossu (Institute of Inflammation and Repair, University of Manchester) for providing the muscle myoblast cell line. We also acknowledge the InterAct and SIGMA Type 2 Diabetes Consortia for access to the data to replicate the rs146662075 variant. A full list of the investigators of the SIGMA Type 2 Diabetes and the InterAct consortia is provided in Supplementary Notes 3 and 4. 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). This research has been conducted using the UK Biobank Resource (application number 16803). We also acknowledge Bianca C. Porneala, MS for his technical assistance in the collection and curation of the genotype and phenotype data from Partners Biobank. We also thank Marcin von Grotthuss for their support for uploading the summary statistics data to the Type 2 Diabetes Genetic Portal (AMP-T2D portal). Finally, we thank all the Computational Genomics group at the BSC for their helpful discussions and valuable comments on the manuscript.

Published
2018

19. Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility

Author

Tazeen H. Jafar, Lars Lind, Peter Almgren, Wendy Winckler, Eitaro Nakashima, Young Min Cho, Annette Peters, Rona J. Strawbridge, Ananda R. Wickremasinghe, Katharine R. Owen, Lee-Ming Chuang, Tien-Jyun Chang, Graeme I. Bell, James B. Meigs, Bill Musk, Timo A. Lakka, Elin Grundberg, Wei Lu, Sarah Edkins, George Dedoussis, Weiping Jia, Danish Saleheen, Suthesh Sivapalaratnam, Maria Samuel, Tien Yin Wong, Lu Qi, Pierre Fontanillas, Momoko Horikoshi, Jirong Long, Abdul Basit, Anubha Mahajan, Andrew T. Hattersley, Markus M. Nöthen, Denis Rybin, Inger Njølstad, S. Krithika, Miguel Cruz, Delilah Zabaneh, Leena Peltonen, Jasmina Kravic, Sangsoo Kim, David Couper, Lori L. Bonnycastle, Heather M. Stringham, Yi-Cheng Chang, Paul Elliott, Eric J.G. Sijbrands, Nita G. Forouhi, Alena Stančáková, Ghazala Mirza, Robert W. Lawrence, Ruth J. F. Loos, Norman Klopp, Shiro Maeda, Martina Müller-Nurasyid, Jer-Yuarn Wu, Jianjun Liu, Kee Seng Chia, Elodie Eury, Loukianos S. Rallidis, Timothy M. Frayling, Ken Yamamoto, David Altshuler, Gunnar Sigurosson, Harald Grallert, Jackie F. Price, Barbara Thorand, Jouko Saramies, Malene M. Kristensen, Sonali Pechlivanis, Inês Barroso, Jong-Young Lee, Melissa Parkin, Josée Dupuis, Stéphane Lobbens, Jesús Kumate, Elena Tremoli, Sudhir Kowlessur, Xueling Sim, Norihiro Kato, Philippe Froguel, Kathleen Stirrups, Eero Lindholm, Alex S. F. Doney, Andres Metspalu, Yu-Tang Gao, Roman Wennauer, Xiao-Ou Shu, Marilyn C. Cornelis, Veikko Salomaa, Nanette R. Lee, Johanna Kuusisto, Caroline S. Fox, Man Li, James Scott, Wing-Yee So, Andrew R. Wood, Inga Prokopenko, Oddgeir L. Holmen, Tin Aung, Ryoichi Takayanagi, Chen Suo, Hara Kazuo, Carl G. P. Platou, Ann M. Kelly, Teresa Ferreira, Karl-Heinz Jöckel, Wei-Yen Lim, James F. Wilson, Tom Forsén, Qi Sun, Valur Emilsson, Gonçalo R. Abecasis, Fan Zhang, Timo Saaristo, Harry Campbell, Ying Wu, Mark Seielstad, Wei Zheng, Han Chen, Stavroula Kanoni, Yuqian Bao, Jose C. Florez, Wan Ting Tay, Ronald C. WMa, Gerald Steinbach, Min Jin Go, Rong Zhang, Junbin Liang, Vasiliki Lagou, Leif Groop, Emil Rehnberg, Nabi Shah, Weihua Zhang, Yun Li, Bengt Sennblad, Olle Melander, Nancy L. Pedersen, Muhammed Islam, Jaakko Tuomilehto, Young Jin Kim, Richard N. Bergman, Juliana C.N. Chan, Eleftheria Zeggini, Andrew D. Johnson, Kees Hovingh, Joban Sehmi, Rainer Rauramaa, Satu Männistö, Reedik Mägi, Samuel Liju, Mingyu Yang, Ayellet V. Segrè, Noël P. Burtt, Mozhgan Dorkhan, Beverley Balkau, Neelam Hassanali, Hyun Min Kang, Fabrizio Veglia, Eeva Korpi-Hyövälti, Loic Yengo, Elizabeth J. Rossin, Angela Silveira, Maggie C.Y. Ng, Yuan-Tsong Chen, Anders Hamsten, David R. Matthews, Mark J. Caulfield, Emmi Tikkanen, Tanya M. Teslovich, John R. B. Perry, Karen L. Mohlke, Sarah E. Hunt, Soo Heon Kwak, Jorge Escobedo, Christopher J. Groves, Ulf de Faire, Jeremy B M Jowett, Gudmar Thorleifsson, Michael Roden, Evelin Mihailov, Viswanathan Mohan, Craig L. Hanis, Thomas WMühleisen, Congrong Wang, Sonia Shah, Kyle J. Gaulton, Jaspal S. Kooner, Jiro Nakamura, Mustafa Atalay, Linda S. Adair, S Wiltshire, Tõnu Esko, Anna Jonsson, Antigone S. Dimas, Karin Leander, Li Ching Chang, George B. Grant, Bo Isomaa, Anne U. Jackson, Claudia Langenberg, Kristian Hveem, Yoon Shin Cho, Astradur B. Hreidarsson, Xu Wang, Keizo Ohnaka, Alexandra C. Nica, Simon D. Rees, Pau Navarro, Sekar Kathiresan, Rob M. van Dam, Zafar I. Hydrie, Bok Ghee Han, Francis S. Collins, Fuu Jen Tsai, Unnur Thorsteinsdottir, Ross M. Fraser, Caroline Hayward, Cornelia M. van Duijn, Samuli Ripatti, Mieke D. Trip, Hyung Lae Kim, Rafn Benediktsson, Candace Guiducci, Bruna Gigante, Kyong Soo Park, Wen Hong L. Kao, Tom Wilsgaard, Leena Kinnunen, John Danesh, Alan James, Alan R. Shuldiner, Mitsuhiro Yokota, Jen Mai Lee, Kari Stefansson, Erik Ingelsson, Colin N. A. Palmer, David J. Hunter, Paul Zimmet, Manickam Chidambaram, Sirkka Keinänen-Kiukaanniemi, Laura J. Scott, Susanne Moebus, Benjamin F. Voight, Wolfgang Rathmann, Hassan Khan, Thomas Illig, Prasad Katulanda, Christian Gieger, Andrew D. Morris, Yik Ying Teo, Andrew P. Morris, Venkatesan Radha, N. William Rayner, Johan G. Eriksson, Christian Dina, Igor Rudan, Sailaja Vedantam, Cheng Hu, James S. Pankow, Ann-Christine Syvänen, Karl Gertow, Valeriya Lyssenko, Guillaume Charpentier, Albert Hofman, Chiea Chuen Khor, Joseph Trakalo, Peter Kraft, Takashi Kadowaki, Qiuyin Cai, John C. Chambers, André G. Uitterlinden, Simon C. Potter, Nicholas J. Wareham, Soumya Raychaudhuri, Jian'an Luan, Tiinamaija Tuomi, Anthony H. Barnett, Juha Saltevo, Robert A. Scott, Valgerdur Steinthorsdottir, Peng Keat Ng, Mark I. McCarthy, Åsa K. Hedman, Kerrin S. Small, Julia Meyer, Frank B. Hu, Cecilia M. Lindgren, Jennifer E. Below, Nancy J. Cox, Jennie Hui, Andrew Crenshaw, Latonya F. Been, Nam H. Cho, Janani Pinidiyapathirage, A. Samad Shera, Bernhard OBoehm, Jason Carey, Augustine Kong, Twee Hee Ong, Philippe M. Frossard, Donald W. Bowden, Toshimasa Yamauchi, Steve E. Humphries, Cordelia Langford, Xinzhong Li, Hiroshi Ikegami, Stéphane Cauchi, Ching-Ti Liu, Michael Boehnke, Peter M. Nilsson, Debashish Das, John Beilby, Robin Young, Christian Herder, Asif Rasheed, Neil Robertson, Raimund Erbel, Fumihiko Takeuchi, Markku Laakso, Esteban J. Parra, Panos Deloukas, Eric Boerwinkle, Adan Valladares-Salgado, Chien-Hsiun Chen, Kay-Tee Khaw, Damiano Baldassarre, Ashok Kumar, E. Shyong Tai, Peter S. Chines, Dharambir KSanghera, Peter Donnelly, [ 1 ] Univ Oxford, Wellcome Trust Ctr Human Genet, Oxford, England [ 2 ] Natl Inst Hlth, Ctr Genome Sci, Gangoe Myeon, Yeonje Ri, South Korea [ 3 ] Univ London Imperial Coll Sci Technol & Med, London, England [ 4 ] Univ Washington, Dept Genome Sci, Seattle, WA 98195 USA [ 5 ] Univ Oxford, Oxford Ctr Diabet Endocrinol & Metab, Oxford OX1 2JD, England [ 6 ] NHLBI, Framingham Heart Study, Framingham, MA USA [ 7 ] Wake Forest Sch Med, Ctr Genom & Personalized Med Res, Winston Salem, NC USA [ 8 ] Wake Forest Sch Med, Ctr Diabet Res, Winston Salem, NC USA [ 9 ] Univ London Imperial Coll Sci Technol & Med, Hammersmith Hosp, London, England [ 10 ] Univ Cambridge, Dept Publ Hlth & Primary Care, Cambridge, England [ 11 ] Ctr Noncommunicable Dis Pakistan, Karachi, Pakistan [ 12 ] Natl Univ Singapore, Dept Epidemiol & Publ Hlth, Singapore 117548, Singapore [ 13 ] Wellcome Trust Sanger Inst, Cambridge, England [ 14 ] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA [ 15 ] Univ N Carolina, Dept Nutr, Chapel Hill, NC USA [ 16 ] Lund Univ, Scania Univ Hosp, Dept Clin Sci Malmo, Ctr Diabet, Malmo, Sweden [ 17 ] Univ Eastern Finland, Inst Biomed, Kuopio, Finland [ 18 ] Singapore Natl Eye Ctr, Singapore Eye Res Inst, Singapore, Singapore [ 19 ] Natl Univ Singapore, Dept Ophthalmol, Singapore 117548, Singapore [ 20 ] IRCCS, Ctr Cardiol Monzino, Milan, Italy [ 21 ] Univ Milan, Dept Pharmacol Sci, Milan, Italy [ 22 ] INSERM, Ctr Rech Epidemiol & Sante Populat CESP, U1018, Villejuif, France [ 23 ] Univ Paris 11, UMRS 1018, Villejuif, France [ 24 ] Shanghai Jiao Tong Univ, Affiliated Peoples Hosp 6, Dept Endocrinol & Metab, Shanghai Key Lab Diabet Mellitus,Shanghai Diabet, Shanghai 200030, Peoples R China [ 25 ] Univ Birmingham, Coll Med & Dent Sci, Birmingham, W Midlands, England [ 26 ] Heart England Natl Hlth Serv NHS Fdn Trust, Ctr Biomed Res, Birmingham, W Midlands, England [ 27 ] Univ Cambridge, Addenbrookes Hosp, Metab Res Labs, Inst Metab Sci, Cambridge CB2 2QQ, England [ 28 ] Addenbrookes Hosp, Inst Metab Sci, Cambridge Biomed Res Ctr, Natl Inst Hlth Res, Cambridge, England [ 29 ] Baqai Inst Diabetol & Endocrinol, Karachi, Pakistan [ 30 ] Univ Oklahoma, Hlth Sci Ctr, Coll Med, Dept Pediat,Sect Genet, Oklahoma City, OK 73190 USA [ 31 ] Sir Charles Gairdner Hosp, Busselton Populat Med Res Inst, Nedlands, WA 6009, Australia [ 32 ] Queen Elizabeth II Med Ctr, PathWest Lab Med Western Australia, Nedlands, WA, Australia [ 33 ] Univ Western Australia, Sch Pathol & Lab Med, Nedlands, WA 6009, Australia [ 34 ] Univ Chicago, Dept Med, Chicago, IL 60637 USA [ 35 ] Univ Chicago, Dept Human Genet, Chicago, IL 60637 USA [ 36 ] Univ Iceland, Fac Med, Reykjavik, Iceland [ 37 ] Landspitali Univ Hosp, Reykjavik, Iceland [ 38 ] Cedars Sinai Med Ctr, Diabet & Obes Res Inst, Los Angeles, CA 90048 USA [ 39 ] Univ Med Ctr Ulm, Div Endocrinol & Diabet, Dept Internal Med, Ulm, Germany [ 40 ] Nanyang Technol Univ, Lee Kong Chian LKC Sch Med, Singapore 639798, Singapore [ 41 ] Univ Texas Hlth Sci Ctr Houston, Ctr Human Genet, Houston, TX 77030 USA [ 42 ] Baylor Coll Med, Human Genome Sequencing Ctr, Houston, TX 77030 USA [ 43 ] NHGRI, NIH, Bethesda, MD 20892 USA [ 44 ] Broad Inst Harvard & Massachusetts Inst Technol M, Cambridge, MA USA [ 45 ] Vanderbilt Univ, Sch Med, Vanderbilt Ingram Canc Ctr, Vanderbilt Epidemiol Ctr,Dept Med, Nashville, TN 37212 USA [ 46 ] Univ Edinburgh, Ctr Populat Hlth Sci, Edinburgh, Midlothian, Scotland [ 47 ] Univ Edinburgh, Western Gen Hosp, MRC, Inst Genet & Mol Med, Edinburgh, Midlothian, Scotland [ 48 ] CNRS, Unite Mixte Rech UMR 8199, Inst Biol, Lille, France [ 49 ] Univ Lille 2, Inst Pasteur, Lille, France [ 50 ] Queen Mary Univ London, Barts & London Sch Med, William Harvey Res Inst, London, England [ 51 ] Queen Mary Univ London, Barts & London Sch Med, William Harvey Res Inst, Barts & London Genome Ctr, London, England [ 52 ] Chinese Univ Hong Kong, Prince Wales Hosp, Dept Med & Therapeut, Hong Kong, Hong Kong, Peoples R China [ 53 ] Acad Sinica, Inst Biomed Sci, Taipei, Taiwan [ 54 ] Natl Taiwan Univ Hosp, Dept Internal Med, Taipei 100, Taiwan [ 55 ] Corbeil Essonnes Hosp, Endocrinol Diabetol Unit, Corbeil Essonnes, France [ 56 ] China Med Univ, Sch Chinese Med, Taichung, Taiwan [ 57 ] Boston Univ, Sch Publ Hlth, Dept Biostat, Boston, MA USA [ 58 ] Natl Univ Singapore, Ctr Mol Epidemiol, Singapore 117548, Singapore [ 59 ] Indian Council Med Res, Adv Ctr Genom Diabet, Madras Diabet Res Fdn, Dept Mol Genet, Madras, Tamil Nadu, India [ 60 ] Ajou Univ, Sch Med, Dept Prevent Med, Suwon 441749, South Korea [ 61 ] Seoul Natl Univ, Coll Med, Dept Internal Med, Seoul 151, South Korea [ 62 ] Natl Taiwan Univ, Sch Med, Grad Inst Clin Med, Taipei 10764, Taiwan [ 63 ] Harvard Univ, Sch Publ Hlth, Dept Nutr & Epidemiol, Boston, MA 02115 USA [ 64 ] Univ N Carolina, Dept Biostat, Collaborat Studies Coordinating Ctr, Chapel Hill, NC USA [ 65 ] Natl Univ Singapore, Saw Swee Hock Sch Publ Hlth, Singapore 117548, Singapore [ 66 ] Ealing Hosp NHS Trust, Southall, Middx, England [ 67 ] Karolinska Inst, Inst Environm Med, Divis Cardiovasc Epidemiol, S-10401 Stockholm, Sweden [ 68 ] Harokopio Univ, Dept Dietet Nutr, Athens, Greece [ 69 ] Univ Geneva, Sch Med, Dept Genet Med & Dev, CH-1211 Geneva, Switzerland [ 70 ] Biomed Sci Res Ctr Alexander Fleming, Vari, Greece [ 71 ] INSERM, UMR 1087, Nantes, France [ 72 ] CNRS, UMR 6291, Nantes, France [ 73 ] Univ Nantes, Nantes, France [ 74 ] Univ Dundee, Ninewells Hosp, Biomed Res Inst, Diabet Res Ctr, Dundee, Scotland [ 75 ] Univ Dundee, Ninewells Hosp, Biomed Res Inst, Pharmacogen Ctr, Dundee, Scotland [ 76 ] Univ Oxford, Dept Stat, Oxford OX1 3TG, England [ 77 ] Erasmus Univ, Med Ctr, Dept Epidemiol, Rotterdam, Netherlands [ 78 ] Netherlands Consortium Healthy Ageing, Netherland Genom Initiat, Rotterdam, Netherlands [ 79 ] Ctr Med Syst Biol, Rotterdam, Netherlands [ 80 ] Univ London Imperial Coll Sci Technol & Med, MRC, Hlth Protect Agcy, Ctr Environm & Hlth, London, England [ 81 ] Iceland Heart Assoc, Kopavogur, Iceland [ 82 ] Univ Duisburg Essen, Univ Hosp Essen, West German Heart Ctr, Clin Cardiol, Essen, Germany [ 83 ] Natl Inst Hlth & Welf, Dept Chron Dis Prevent, Helsinki, Finland [ 84 ] Univ Helsinki, Dept Gen Practice & Primary Hlth Care, Helsinki, Finland [ 85 ] Univ Helsinki, Gen Hosp, Unit Gen Practice, Helsinki, Finland [ 86 ] Folkhalsan Res Ctr, Helsinki, Finland [ 87 ] Inst Mexicano Seguro Social, Hosp Gen Reg 1, Unidad Invest Epidemiol Clin, Mexico City, DF, Mexico [ 88 ] Univ Tartu, Estonian Genome Ctr, EE-50090 Tartu, Estonia [ 89 ] Univ Tartu, Inst Mol & Cell Biol, EE-50090 Tartu, Estonia [ 90 ] Broad Inst, Program Med & Populat Genet, Cambridge, MA USA [ 91 ] Childrens Hosp, Div Genet & Endocrinol, Boston, MA 02115 USA [ 92 ] Harvard Univ, Sch Med, Dept Med, Boston, MA USA [ 93 ] Massachusetts Gen Hosp, Ctr Human Genet Res, Boston, MA 02114 USA [ 94 ] Massachusetts Gen Hosp, Diabet Res Ctr, Diabet Unit, Boston, MA 02114 USA [ 95 ] Addenbrookes Hosp, Inst Metab Sci, MRC, Epidemiol Unit, Cambridge, England [ 96 ] Vaasa Hlth Care Ctr, Vaasa, Finland [ 97 ] Brigham & Womens Hosp, Div Endocrinol & Metab, Boston, MA 02115 USA [ 98 ] Harvard Univ, Sch Med, Boston, MA USA [ 99 ] Univ Exeter, Peninsula Med Sch, Inst Biomed & Clin Sci, Exeter, Devon, England [ 100 ] Shanghai Canc Inst, Dept Epidemiol, Shanghai, Peoples R China [ 101 ] Karolinska Inst, Dept Med Solna, Atherosclerosis Res Unit, Stockholm, Sweden [ 102 ] Karolinska Univ, Hosp Solna, Ctr Mol Med, Stockholm, Sweden [ 103 ] Helmholtz Zentrum Muenchen, Inst Genet Epidemiol, Neuherberg, Germany [ 104 ] Helmholtz Zentrum Muenchen, Res Unit Mol Epidemiol, Neuherberg, Germany [ 105 ] Univ Munich, Clin Cooperat Grp Diabet, Munich, Germany [ 106 ] Helmholtz Zentrum Muenchen, Munich, Germany [ 107 ] Tech Univ Munich, Clin Cooperat Grp Nutrigen & Type Diabet 2, Munich, Germany [ 108 ] German Ctr Diabet Res DZD, Neuherberg, Germany [ 109 ] Kings Coll London, Dept Twin Res & Genet Epidemiol, London, England [ 110 ] Univ Tokyo, Grad Sch Med, Dept Diabet & Metab Dis, Tokyo, Japan [ 111 ] Univ Exeter, Peninsula Med Sch, Inst Biomed & Clin Sci, Exeter, Devon, England [ 112 ] Univ Dusseldorf, Leibniz Ctr Diabet Res, German Diabet Ctr, Inst Clin Diabetol, Dusseldorf, Germany [ 113 ] Norwegian Univ Sci & Technol, Dept Publ Hlth & Gen Practice, HUNT Res Ctr, Levanger, Norway [ 114 ] Univ Amsterdam, Acad Med Ctr, Dept Vasc Med, NL-1105 AZ Amsterdam, Netherlands [ 115 ] Brigham & Womens Hosp, Dept Med, Channing Lab, Boston, MA USA [ 116 ] Univ Western Australia, Sch Populat Hlth, Nedlands, WA 6009, Australia [ 117 ] UCL, Inst Cardiovasc Sci, London, England [ 118 ] Harvard Univ, Sch Publ Hlth, Program Mol & Genet Epidemiol, Boston, MA 02115 USA [ 119 ] Kinki Univ, Sch Med, Dept Diabet Endocrinol & Metab, Osaka 589, Japan [ 120 ] Hannover Med Sch, Hannover Unified Biobank, Hannover, Germany [ 121 ] Univ Uppsala Hosp, Dept Mol Sci, Mol Epidemiol & Sci Life Lab, Uppsala, Sweden [ 122 ] Aga Khan Univ, Dept Community Hlth Sci, Karachi, Pakistan [ 123 ] Dept Social Serv & Hlth Care, Pietarsaari, Finland [ 124 ] Aga Khan Univ, Dept Med, Karachi, Pakistan [ 125 ] Queen Elizabeth II Med Ctr, West Australian Sleep Disorders Res Inst, Dept Pulm Physiol & Sleep Med, Nedlands, WA, Australia [ 126 ] Univ Western Australia, Sch Med & Pharmacol, Nedlands, WA 6009, Australia [ 127 ] Univ Hosp Essen, Inst Med Informat Biometry & Epidemiol, Essen, Germany [ 128 ] Heart & Diabet Inst, Baker Int Diabet Inst IDI, Melbourne, Australia [ 129 ] Johns Hopkins Bloomberg Sch Publ Hlth, Dept Epidemiol, Baltimore, MD USA [ 130 ] Massachusetts Gen Hosp, Cardiovasc Res Ctr, Boston, MA 02114 USA [ 131 ] Natl Ctr Global Hlth & Med, Res Inst, Shinjuku Ku, Tokyo, Japan [ 132 ] Univ Colombo, Dept Clin Med, Diabet Res Unit, Colombo, Sri Lanka [ 133 ] Univ Oulu, Inst Hlth Sci, Fac Med, Oulu, Finland [ 134 ] Oulu Univ Hosp, Unit Gen Practice, Oulu, Finland [ 135 ] Agcy Sci Technol & Res, Genome Inst Singapore, Singapore, Singapore [ 136 ] Ewha Womans Univ, Sch Med, Dept Biochem, Seoul, South Korea [ 137 ] Soongsil Univ, Sch Syst Biomed Sci, Seoul, South Korea [ 138 ] Natl Inst Hlth & Welf, Diabet Prevent Unit, Helsinki, Finland [ 139 ] deCODE Genet, Reykjavik, Iceland [ 140 ] South Ostrobothnia Cent Hosp, Seinajoki, Finland [ 141 ] Minist Hlth, Port Louis, Mauritius [ 142 ] Univ Toronto, Dept Anthropol, Mississauga, ON L5L 1C6, Canada [ 143 ] Fdn IMSS, Mexico City, DF, Mexico [ 144 ] Univ Eastern Finland, Dept Med, Kuopio, Finland [ 145 ] Kuopio Univ Hosp, SF-70210 Kuopio, Finland [ 146 ] Kuopio Res Inst Exercise Med, Kuopio, Finland [ 147 ] Univ Western Australia, Ctr Genet Epidemiol & Biostat, Nedlands, WA 6009, Australia [ 148 ] Univ San Carlos, Off Populat Studies Fdn Inc, Cebu, Philippines [ 149 ] Univ London Imperial Coll Sci Technol & Med, Hammersmith Hosp, Natl Heart & Lung Inst, London, England [ 150 ] Univ N Carolina, Dept Genet, Chapel Hill, NC USA [ 151 ] Univ N Carolina, Dept Biostat, Chapel Hill, NC USA [ 152 ] Beijing Genom Inst, Shenzhen, Peoples R China [ 153 ] Uppsala Univ, Akad Sjukhuset, Dept Med Sci, Uppsala, Sweden [ 154 ] Mt Sinai Sch Med, Charles R Bronfman Inst Personalized Med, New York, NY USA [ 155 ] Mt Sinai Sch Med, Child Hlth & Dev Inst, New York, NY USA [ 156 ] Mt Sinai Sch Med, Dept Prevent Med, New York, NY USA [ 157 ] Shanghai Inst Prevent Med, Shanghai, Peoples R China [ 158 ] Massachusetts Gen Hosp, Div Gen Med, Boston, MA 02114 USA [ 159 ] Dr Mohans Diabet Specialties Ctr, Madras, Tamil Nadu, India [ 160 ] Univ Bonn, Inst Human Genet, Bonn, Germany [ 161 ] Univ Bonn, Life & Brain Ctr, Dept Genom, Bonn, Germany [ 162 ] Univ Munich, Chair Genet Epidemiol, Inst Med Informat Biometry & Epidemiol, Munich, Germany [ 163 ] Univ Munich, Univ Hosp Grosshadern, Dept Med 1, Munich, Germany [ 164 ] Sir Charles Gairdner Hosp, Nedlands, WA 6009, Australia [ 165 ] Nagoya Univ, Grad Sch Med, Div Endocrinol & Diabet, Dept Internal Med, Nagoya, Aichi 4648601, Japan [ 166 ] Chubu Rosai Hosp, Dept Endocrinol & Diabet, Nagoya, Aichi, Japan [ 167 ] Univ Tromso, Fac Hlth Sci, Dept Community Med, Tromso, Norway [ 168 ] Kyushu Univ, Grad Sch Med Sci, Dept Geriatr Med, Higashi Ku, Fukuoka 812, Japan [ 169 ] Churchill Hosp, Hlth Res Biomed Res Ctr, Oxford Natl Inst, Oxford OX3 7LJ, England [ 170 ] Univ Minnesota, Div Epidemiol & Community Hlth, Minneapolis, MN USA [ 171 ] Seoul Natl Univ, Grad Sch Convergence Sci & Technol, Dept Mol Med & Biopharmaceut Sci, World Class Univ Program, Seoul, South Korea [ 172 ] Seoul Natl Univ, Coll Med, Seoul, South Korea [ 173 ] Karolinska Inst, Dept Med Epidemiol & Biostat, Stockholm, Sweden [ 174 ] Inst Mol Med Finland FIMM, Helsinki, Finland [ 175 ] Helmholtz Zentrum Muenchen, Inst Epidemiol 2, Neuherberg, Germany [ 176 ] Univ Kelaniya, Fac Med, Dept Publ Hlth, Ragama, Sri Lanka [ 177 ] Nord Trondelag Hlth Trust, Levanger Hosp, Dept Internal Med, Levanger, Norway [ 178 ] Univ Gen Hosp Attikon, Athens, Greece [ 179 ] Univ Dusseldorf, Leibniz Ctr Diabet Res, German Diabet Ctr, Inst Biometr & Epidemiol, Dusseldorf, Germany [ 180 ] Kuopio Univ Hosp, Dept Clin Physiol & Nucl Med, SF-70210 Kuopio, Finland [ 181 ] Harvard Univ, Brigham & Womens Hosp, Sch Med, Div Rheumatol Immunol & Allergy, Boston, MA 02115 USA [ 182 ] Partners Ctr Personalized Genom Med, Boston, MA USA [ 183 ] Univ Dusseldorf, Dept Endocrinol & Diabetol, Dusseldorf, Germany [ 184 ] Univ Dusseldorf, Dept Metab Dis, Dusseldorf, Germany [ 185 ] Harvard Univ, Hlth Sci & Technol MD Program, Boston, MA 02115 USA [ 186 ] MIT, Boston, MA USA [ 187 ] Harvard Univ, Harvard Biol & Biomed Sci Program, Boston, MA 02115 USA [ 188 ] Boston Univ, Data Coordinating Ctr, Boston, MA 02215 USA [ 189 ] Finnish Diabet Assoc, Tampere, Finland [ 190 ] Pirkanmaa Hosp Dist, Tampere, Finland [ 191 ] Cent Finland Cent Hosp, Dept Med, Jyvaskyla, Finland [ 192 ] South Karelia Cent Hosp, Lappeenranta, Finland [ 193 ] UCL, Dept Genet Evolut & Environm, Genet Inst, London, England [ 194 ] Diabet Assoc Pakistan, Karachi, Pakistan [ 195 ] Univ Maryland, Sch Med, Div Endocrinol Diabet & Nutr, Baltimore, MD 21201 USA [ 196 ] Baltimore Vet Adm Med Ctr, Geriatr Res Educ & Clin Ctr, Baltimore, MD USA [ 197 ] Univ Maryland, Sch Med, Program Personalised & Genom Med, Baltimore, MD 21201 USA [ 198 ] Erasmus Univ, Med Ctr, Dept Internal Med, Rotterdam, Netherlands [ 199 ] Univ Ulm, Dept Clin Chem, D-89069 Ulm, Germany [ 200 ] Univ Ulm, Cent Lab, D-89069 Ulm, Germany [ 201 ] Uppsala Univ, Dept Med Sci, Uppsala, Sweden [ 202 ] Kyushu Univ, Grad Sch Med Sci, Dept Internal Med & Bioregulatory Sci, Higashi Ku, Fukuoka 812, Japan [ 203 ] Univ Helsinki, Helsinki Univ Hosp, Dept Med, Helsinki, Finland [ 204 ] Hosp Univ LaPaz IdiPAZ, Inst Invest Sanitaria, Madrid, Spain [ 205 ] Danube Univ Krems, Ctr Vasc Prevent, Krems, Austria [ 206 ] King Abdulaziz Univ, Diabet Res Grp, Jeddah 21413, Saudi Arabia [ 207 ] IMSS, Ctr Med Nacl Siglo 21, Hosp Especialidades, Unidad Invest Med Bioquim, Mexico City, DF, Mexico [ 208 ] Univ Penn, Perelman Sch Med, Dept Pharmacol, Philadelphia, PA 19104 USA [ 209 ] Univ Melbourne, Ctr Eye Res Australia, East Melbourne, Vic, Australia [ 210 ] Kyushu Univ, Med Inst Bioregulat, Res Ctr Genet Informat, Div Genome Anal,Higashi Ku, Fukuoka 812, Japan [ 211 ] Univ Lille 1, Math Lab, CNRS UMR 8524, MODAL Team,INRIA Lille Nord Europe, F-59655 Villeneuve Dascq, France [ 212 ] Aichi Gakuin Univ, Sch Dent, Dept Genome Sci, Nagoya, Aichi 464, Japan [ 213 ] Harvard Univ, Sch Med, Dept Genet, Boston, MA USA [ 214 ] Harvard Univ, Sch Med, Dept Mol Biol, Boston, MA USA [ 215 ] Massachusetts Gen Hosp, Diabet Unit, Boston, MA 02114 USA [ 216 ] Wake Forest Sch Med, Dept Biochem, Winston Salem, NC USA [ 217 ] Wake Forest Sch Med, Dept Internal Med, Winston Salem, NC USA [ 218 ] Hallym Univ, Dept Biomed Sci, Chunchon, Gangwon Do, South Korea [ 219 ] Univ Texas Hlth Sci Ctr Houston, Ctr Human Genet, Houston, TX 77030 USA [ 220 ] Imperial Coll Healthcare NHS Trust, London, England [ 221 ] Univ Calif San Francisco, Inst Human Genet, San Francisco, CA 94143 USA [ 222 ] Blood Syst Res Inst, San Francisco, CA USA [ 223 ] Natl Univ Singapore, Grad Sch Integrat Sci & Engn, Singapore 117548, Singapore [ 224 ] Natl Univ Singapore, Dept Stat & Appl Probabil, Singapore 117548, Singapore [ 225 ] Natl Univ Singapore, Dept Med, Singapore 117548, Singapore [ 226 ] Duke Natl Univ Singapore, Grad Sch Med, Singapore, Singapore [ 227 ] Univ Liverpool, Dept Biostat, Liverpool L69 3BX, Merseyside, England, Obstetrics & Gynecology, Radiology & Nuclear Medicine, Surgery, Epidemiology, Dermatology, Internal Medicine, Medical Microbiology & Infectious Diseases, Medical Research Council (MRC), National Institute for Health Research, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, and Cardiology

Subjects
CHROMATIN, endocrine system diseases, South Asian Type 2 Diabetes (SAT2D) Consortium, SCALE ASSOCIATION ANALYSIS, Medizin, LOCI, Genome-wide association study, VARIANTS, 0302 clinical medicine, Risk Factors, IMPUTATION, Glucose homeostasis, 11 Medical and Health Sciences, Genetics & Heredity, Genetics, 0303 health sciences, IDENTIFY, Hispanic or Latino, 3. Good health, MAP, POPULATIONS, Medical genetics, Type 2 Diabetes Genetic Exploration by Nex-generation sequencing in muylti-Ethnic Samples (T2D-GENES) Consortium, Hispanic Americans, Life Sciences & Biomedicine, Asian Continental Ancestry Group, medicine.medical_specialty, European Continental Ancestry Group, TRANSETHNIC METAANALYSIS, 030209 endocrinology & metabolism, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Article, White People, Sykursýki, 03 medical and health sciences, Asian People, SDG 3 - Good Health and Well-being, medicine, Humans, Genetic Predisposition to Disease, Allele, Asian Genetic Epidemiology Network Type 2 Diabetes (AGEN-T2D) Consortium, Alleles, 030304 developmental biology, Genetic association, Science & Technology, DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Mexican American Type 2 Diabetes (MAT2D) Consortium, 06 Biological Sciences, Arfgengi, Genetic architecture, INDIVIDUALS, Diabetes Mellitus, Type 2, Case-Control Studies, GLUCOSE-HOMEOSTASIS, ASSOCIATION ANALYSES, Imputation (genetics), Developmental Biology, Genome-Wide Association Study
Abstract

To access publisher's full text version of this article click on the hyperlink at the bottom of the page To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry. Canadian Institutes of Health Research Medical Research Council UK G0601261 Mexico Convocatoria SSA/IMMS/ISSSTE-CONACYT 2012-2 clave 150352 IMSS R-2011-785-018 CONACYT Salud-2007-C01-71068 US National Institutes of Health DK062370 HG000376 DK085584 DK085545 DK073541 DK085501 Wellcome Trust WT098017 WT090532 WT090367 WT098381 WT081682 WT085475 info:eu-repo/grantAgreement/EC/FP7/201413

Published
2014

20. Fruit and vegetable intake and type 2 diabetes: EPIC-InterAct prospective study and meta-analysis

Author

Birgit Teucher, B. Balkau, Nita G. Forouhi, Kim Overvad, Giovanna Masala, Annemieke M.W. Spijkerman, Andrew J. M. Cooper, Elio Riboli, M-J Sanchez, Guy Fagherazzi, Timothy J. Key, C. Navarro, Anne Tjønneland, Larraitz Arriola, C A González, Olov Rolandsson, Edith J. M. Feskens, Brian Buijsse, Rudolf Kaaks, Zheng Ye, Joline W.J. Beulens, Stephen J. Sharp, Salvatore Panico, Peter M. Nilsson, Sara Grioni, Ivonne Sluijs, Rosario Tumino, Claudia Langenberg, N. Roswall, J. Ramón Quirós, B. de Lauzon-Guillain, Nadia Slimani, Paul W. Franks, Aurelio Barricarte, Heiner Boeing, Christina C. Dahm, Nicholas J. Wareham, Frederike L. Büchner, Carlotta Sacerdote, Cooper, Aj, Forouhi, Ng, Ye, Z, Buijsse, B, Arriola, L, Balkau, B, Barricarte, A, Beulens, Jw, Boeing, H, B?chner, Fl, Dahm, Cc, de Lauzon Guillain, B, Fagherazzi, G, Franks, Pw, Gonzalez, C, Grioni, S, Kaaks, R, Key, Tj, Masala, G, Navarro, C, Nilsson, P, Overvad, K, Panico, Salvatore, Ram?n Quir?s, J, Rolandsson, O, Roswall, N, Sacerdote, C, S?nchez, Mj, Slimani, N, Sluijs, I, Spijkerman, Am, Teucher, B, Tjonneland, A, Tumino, R, Sharp, Sj, Langenberg, C, Feskens, Ej, Riboli, E, Wareham, Nj, and Interact, Consortium

Subjects
Risk, life-style, Nutrition and Disease, food frequency questionnaire, dietary patterns, Medicine (miscellaneous), Type 2 diabetes, Plant Roots, Article, Voeding en Ziekte, Diabetes mellitus, Environmental health, Vegetables, Prevalence, Humans, cancer, Medicine, consumption, Food science, Prospective cohort study, VLAG, Global Nutrition, Wereldvoeding, Evidence-Based Medicine, Nutrition and Dietetics, business.industry, Incidence, Hazard ratio, medicine.disease, 10 european countries, Confidence interval, Diet, chronic disease risk, Europe, Plant Leaves, beta-carotene, magnesium intake, Diabetes Mellitus, Type 2, Quartile, Fruit, Meta-analysis, Relative risk, randomized controlled-trial, business
Abstract

Fruit and vegetable intake (FVI) may reduce the risk of type 2 diabetes (T2D), but the epidemiological evidence is inconclusive. The aim of this study is to examine the prospective association of FVI with T2D and conduct an updated meta-analysis. In the European Prospective Investigation into Cancer-InterAct (EPIC-InterAct) prospective case-cohort study nested within eight European countries, a representative sample of 16 154 participants and 12 403 incident cases of T2D were identified from 340 234 individuals with 3.99 million person-years of follow-up. For the meta-analysis we identified prospective studies on FVI and T2D risk by systematic searches of MEDLINE and EMBASE until April 2011. In EPIC-InterAct, estimated FVI by dietary questionnaires varied more than twofold between countries. In adjusted analyses the hazard ratio (95% confidence interval) comparing the highest with lowest quartile of reported intake was 0.90 (0.80-1.01) for FVI; 0.89 (0.76-1.04) for fruit and 0.94 (0.84-1.05) for vegetables. Among FV subtypes, only root vegetables were inversely associated with diabetes 0.87 (0.77-0.99). In meta-analysis using pooled data from five studies including EPIC-InterAct, comparing the highest with lowest category for FVI was associated with a lower relative risk of diabetes (0.93 (0.87-1.00)). Fruit or vegetables separately were not associated with diabetes. Among FV subtypes, only green leafy vegetable (GLV) intake (relative risk: 0.84 (0.74-0.94)) was inversely associated with diabetes. Subtypes of vegetables, such as root vegetables or GLVs may be beneficial for the prevention of diabetes, while total FVI may exert a weaker overall effect.European Journal of Clinical Nutrition advance online publication, 1 August 2012; doi:10.1038/ejcn.2012.85.

Published
2012

21. The association between prior infection with five serotypes of Coxsackievirus B and incident type 2 diabetes mellitus in the EPIC-Norfolk study

Author

Heikki Hyöty, Nita G. Forouhi, Nicholas J. Wareham, Robert Luben, Sisko Tauriainen, Effrossyni Gkrania-Klotsas, S. J. Sharp, Kay-Tee Khaw, and Claudia Langenberg

Subjects
Adult, Male, Endocrinology, Diabetes and Metabolism, Coxsackievirus Infections, Type 2 diabetes, Coxsackievirus, Risk Factors, Diabetes mellitus, Internal Medicine, medicine, Humans, biology, business.industry, Incidence, Incidence (epidemiology), Type 2 Diabetes Mellitus, medicine.disease, biology.organism_classification, Enterovirus B, Human, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Coxsackieviruses B, Immunology, Etiology, Female, business, Follow-Up Studies, Cohort study
Abstract

Infections with Coxsackieviruses have been linked to beta cell dysfunction. Given the importance of beta cell dysfunction in the aetiology of type 2 diabetes, we hypothesised that prior infection with Coxsackieviruses B would increase the risk of type 2 diabetes. The aims of the study were to estimate cross-sectional associations between potential predictors of previous infection and seropositivity for Coxsackievirus B serotypes 1-5 (CBV1-5), and then to assess the association between seropositivity and incident type 2 diabetes.Using a case-cohort design nested within the European Prospective Investigation of Cancer (EPIC)-Norfolk study, we ascertained n = 603 cases of incident type 2 diabetes. From within the entire cohort we identified a random subcohort of n = 835, without diabetes at baseline. The presence of Coxsackievirus B neutralising antibodies against serotypes 1-5 was assessed using a plaque neutralisation assay. Weighted Cox regression was used to examine the association between presence of antibodies to CBV1-5 and the development of type 2 diabetes.Seropositivity in the subcohort for CBV1-5 was 50%, 67%, 66%, 75% and 45%, respectively. After adjustment for age, sex, BMI, physical activity and family history of diabetes, the presence of antibodies against CBV1-5 was not associated with incident type 2 diabetes, over a mean follow-up of 5.7 years (HR [95% CIs] 0.94 [0.72,1.25], 0.92 [0.68, 1.23], 1.33 [0.98,1.81], 1.16 [0.83,1.61] and 1.03 [0.77,1.39] for CBV1-5, respectively).The presence of antibodies against any of five serotypes of Coxsackievirus B was not associated with incident type 2 diabetes.

Published
2012

22. An amino acid profile to predict diabetes?

Author

David B. Savage and Claudia Langenberg

Subjects
chemistry.chemical_classification, medicine.medical_specialty, Diabetes risk, General Medicine, Disease, Biology, Bioinformatics, medicine.disease, Obesity, General Biochemistry, Genetics and Molecular Biology, Amino acid, Endocrinology, Insulin resistance, Intervention measures, chemistry, Internal medicine, Diabetes mellitus, medicine, Metabolome
Abstract

By the time diabetes is diagnosed, irreversible pathology is typically present, challenging therapeutic intervention. A reliable test for predicting diabetes risk could allow earlier implementation of intervention measures. Increased blood concentrations of amino acids are now suggested to predict risk of diabetes (pages 448–453), and amino acid profiling might also provide mechanistic insights into this disease.

Published
2011

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