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1. Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models

Author

Allesøe, Rosa Lundbye, Lundgaard, Agnete Troen, Hernández Medina, Ricardo, Aguayo-Orozco, Alejandro, Johansen, Joachim, Nissen, Jakob Nybo, Brorsson, Caroline, Mazzoni, Gianluca, Niu, Lili, Biel, Jorge Hernansanz, Brasas, Valentas, Webel, Henry, Benros, Michael Eriksen, Pedersen, Anders Gorm, Chmura, Piotr Jaroslaw, Jacobsen, Ulrik Plesner, Mari, Andrea, Koivula, Robert, Mahajan, Anubha, Vinuela, Ana, Tajes, Juan Fernandez, Sharma, Sapna, Haid, Mark, Hong, Mun-Gwan, Musholt, Petra B., de Masi, Federico, Vogt, Josef, Pedersen, Helle Krogh, Gudmundsdottir, Valborg, Jones, Angus, Kennedy, Gwen, Bell, Jimmy, Thomas, E. Louise, Frost, Gary, Thomsen, Henrik, Hansen, Elizaveta, Hansen, Tue Haldor, Vestergaard, Henrik, Muilwijk, Mirthe, Blom, Marieke T., ‘t Hart, Leen M., Pattou, Francois, Raverdy, Violeta, Brage, Soren, Kokkola, Tarja, Heggie, Alison, McEvoy, Donna, Mourby, Miranda, Kaye, Jane, Hattersley, Andrew, McDonald, Timothy, Ridderstråle, Martin, Walker, Mark, Forgie, Ian, Giordano, Giuseppe N., Pavo, Imre, Ruetten, Hartmut, Pedersen, Oluf, Hansen, Torben, Dermitzakis, Emmanouil, Franks, Paul W., Schwenk, Jochen M., Adamski, Jerzy, McCarthy, Mark I., Pearson, Ewan, Banasik, Karina, Rasmussen, Simon, Brunak, S. ren, Froguel, Philippe, Thomas, Cecilia Engel, Haussler, Ragna, Beulens, Joline, Rutters, Femke, Nijpels, Giel, van Oort, Sabine, Groeneveld, Lenka, Elders, Petra, Giorgino, Toni, Rodriquez, Marianne, Nice, Rachel, Perry, Mandy, Bianzano, Susanna, Graefe-Mody, Ulrike, Hennige, Anita, Grempler, Rolf, Baum, Patrick, Stærfeldt, Hans-Henrik, Shah, Nisha, Teare, Harriet, Ehrhardt, Beate, Tillner, Joachim, Dings, Christiane, Lehr, Thorsten, Scherer, Nina, Sihinevich, Iryna, Cabrelli, Louise, Loftus, Heather, Bizzotto, Roberto, Tura, Andrea, Dekkers, Koen, van Leeuwen, Nienke, Groop, Leif, Slieker, Roderick, Ramisch, Anna, Jennison, Christopher, McVittie, Ian, Frau, Francesca, Steckel-Hamann, Birgit, Adragni, Kofi, Thomas, Melissa, Pasdar, Naeimeh Atabaki, Fitipaldi, Hugo, Kurbasic, Azra, Mutie, Pascal, Pomares-Millan, Hugo, Bonnefond, Amelie, Canouil, Mickael, Caiazzo, Robert, Verkindt, Helene, Holl, Reinhard, Kuulasmaa, Teemu, Deshmukh, Harshal, Cederberg, Henna, Laakso, Markku, Vangipurapu, Jagadish, Dale, Matilda, Thorand, Barbara, Nicolay, Claudia, Fritsche, Andreas, Hill, Anita, Hudson, Michelle, Thorne, Claire, Allin, Kristine, Arumugam, Manimozhiyan, Jonsson, Anna, Engelbrechtsen, Line, Forman, Annemette, Dutta, Avirup, Sondertoft, Nadja, Fan, Yong, Gough, Stephen, Robertson, Neil, McRobert, Nicky, Wesolowska-Andersen, Agata, Brown, Andrew, Davtian, David, Dawed, Adem, Donnelly, Louise, Palmer, Colin, White, Margaret, Ferrer, Jorge, Whitcher, Brandon, Artati, Anna, Prehn, Cornelia, Adam, Jonathan, Grallert, Harald, Gupta, Ramneek, Sackett, Peter Wad, Nilsson, Birgitte, Tsirigos, Konstantinos, Eriksen, Rebeca, Jablonka, Bernd, Uhlen, Mathias, Gassenhuber, Johann, Baltauss, Tania, de Preville, Nathalie, Klintenberg, Maria, Abdalla, Moustafa, Lundgaard, Agnete Troen [0000-0001-7447-6560], Hernández Medina, Ricardo [0000-0001-6373-2362], Johansen, Joachim [0000-0001-7052-1870], Niu, Lili [0000-0003-4571-4368], Biel, Jorge Hernansanz [0000-0002-3125-2951], Benros, Michael Eriksen [0000-0003-4939-9465], Pedersen, Anders Gorm [0000-0001-9650-8965], Jacobsen, Ulrik Plesner [0000-0001-9181-6854], Koivula, Robert [0000-0002-1646-4163], Vinuela, Ana [0000-0003-3771-8537], Haid, Mark [0000-0001-6118-1333], Hong, Mun-Gwan [0000-0001-8603-8293], Kennedy, Gwen [0000-0002-9856-3236], Thomas, E Louise [0000-0003-4235-4694], Frost, Gary [0000-0003-0529-6325], Hansen, Tue Haldor [0000-0001-5948-8993], Kaye, Jane [0000-0002-7311-4725], Hattersley, Andrew [0000-0001-5620-473X], Ridderstråle, Martin [0000-0002-3270-9167], Pedersen, Oluf [0000-0002-3321-3972], Hansen, Torben [0000-0001-8748-3831], Schwenk, Jochen M [0000-0001-8141-8449], Rasmussen, Simon [0000-0001-6323-9041], Brunak, Søren [0000-0003-0316-5866], Apollo - University of Cambridge Repository, Epidemiology and Data Science, ACS - Diabetes & metabolism, APH - Health Behaviors & Chronic Diseases, General practice, ACS - Heart failure & arrhythmias, APH - Aging & Later Life, Graduate School, and APH - Methodology

Subjects
Biomedical Engineering, Type 2 diabetes, Bioengineering, Applied Microbiology and Biotechnology, Deep Learning, SDG 3 - Good Health and Well-being, Diabetes Mellitus, Type 2, Machine learning, Molecular Medicine, Humans, Data integration, IMI DIRECT Consortium, Systems biology, Algorithms, Biotechnology
Abstract

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug–omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug–drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.

Published
2023

9. Leukocyte Function in COPD: Clinical Relevance and Potential for Drug Therapy

Author

Baker,Jonathan R and Donnelly,Louise E

Subjects
respiratory system, International Journal of Chronic Obstructive Pulmonary Disease, respiratory tract diseases
Abstract

Jonathan R Baker, Louise E Donnelly Airway Disease, National Heart and Lung Institute, Imperial College London, London, UKCorrespondence: Louise E DonnellyAirway Disease, National Heart and Lung Institute, Imperial College London, Dovehouse Street, London, SW3 6LY, UKTel +44 207 594 7895Email l.donnnelly@imperial.ac.ukAbstract: Chronic obstructive pulmonary disease (COPD) is a progressive lung condition affecting 10% of the global population over 45 years. Currently, there are no disease-modifying treatments, with current therapies treating only the symptoms of the disease. COPD is an inflammatory disease, with a high infiltration of leukocytes being found within the lung of COPD patients. These leukocytes, if not kept in check, damage the lung, leading to the pathophysiology associated with the disease. In this review, we focus on the main leukocytes found within the COPD lung, describing how the release of chemokines from the damaged epithelial lining recruits these cells into the lung. Once present, these cells become active and may be driven towards a more pro-inflammatory phenotype. These cells release their own subtypes of inflammatory mediators, growth factors and proteases which can all lead to airway remodeling, mucus hypersecretion and emphysema. Finally, we describe some of the current therapies and potential new targets that could be utilized to target aberrant leukocyte function in the COPD lung. Here, we focus on old therapies such as statins and corticosteroids, but also look at the emerging field of biologics describing those which have been tested in COPD already and potential new monoclonal antibodies which are under review.Keywords: neutrophil, macrophage, eosinophil, CD8+ T cell, mast cell

Published
2021

10. 'Wasn't offered one, too poorly to ask for one'– Reasons why some patients do not receive a psychosocial assessment following self-harm: Qualitative patient and carer survey

Author

Quinlivan, Leah, Donnelly, Louise, Littlewood, Donna, Monaghan, Elizabeth, Barlow, Stephen, Campbell, Stephen, Webb, Roger, and Kapur, Nav

Subjects
PPI, qualitative, health services, patients, self-harm, psychosocial assessment
Abstract

Objective: Psychosocial assessment following self-harm presentations to hospital is an important aspect of care. However, many people attending hospital following self-harm do not receive an assessment. We sought to explore reasons why some patients do not receive a psychosocial assessment following self-harm from the perspective of patients and carers. Methods: Between March and November 2019, we recruited 88 patients and 14 carers aged ⩾18 years from 16 mental health trusts and community organisations in the United Kingdom, via social media, to a co-designed qualitative survey. Thematic analyses were used to interpret the data. Results: Patients’ reasons for refusing an assessment included long waiting times, previous problematic interactions with staff and feeling unsafe when in the emergency department. Two people refused an assessment because they wanted to harm themselves again. Participants reported organisational reasons for non-assessment, including clinicians not offering assessments and exclusion due to alcohol intoxication. Other patients felt they did not reach clinically determined thresholds because of misconceptions over perceived heightened fatality risk with certain self-harm methods (e.g. self-poisoning vs self-cutting). Conclusion: Our results provide important insights into some of the reasons why some people may not receive a psychosocial assessment following self-harm. Parallel assessments, compassionate care and specialist alcohol services in acute hospitals may help reduce the number of people who leave before an assessment. Education may help address erroneous beliefs that self-injury and self-harm repetition are not associated with greatly raised suicide risk.

Published
2021

11. Introducing a low-risk breast screening pathway into the NHS Breast Screening Programme: views from healthcare professionals who implement a feasibility study for risk-stratified screening

Author

Woof, Victoria, McWilliams, Lorna, Donnelly, Louise, Howell, Anthony, Maxwell, Anthony, Evans, D Gareth, and French, David

Subjects
screening frequency, low-risk, risk estimation, risk-stratified breast screening, healthcare professionals
Abstract

Objectives:Proposals to stratify breast screening by breast cancer risk aim to produce a better balance of benefits to harms. Notably, risk estimation calculated from common risk factors and a polygenic risk score would enable high-risk women to benefit from more frequent screening or preventive medication. This service would also identify low-risk women who experience fewer benefits from attending, as lower grade and in situ cancers may be treated unnecessarily. It may therefore be appropriate for low-risk women to attend screening less. This study aimed to elicit views regarding implementing less frequent screening for low-risk women from healthcare professionals who implement risk-stratified screening.Methods:Healthcare professionals involved in the delivery of risk-stratified breast screening were invited to participate in a focus group within the screening setting in which they work or have a telephone interview. Primary care staff were also invited to provide their perspective. Three focus groups and two telephone interviews were conducted with 28 healthcare professionals. To identify patterns across the sample, data were analysed as a single dataset using reflexive thematic analysis.Results:Analysis yielded three themes: Reservations concerning the introduction of less frequent screening, highlighting healthcare professionals’ unease and concerns towards implementing less frequent screening; Considerations for the management of public knowledge, providing views on media impact on public opinion and the potential for a low-risk pathway to cause confusion and raise suspicion regarding implementation motives; and Deliberating service implications and reconfiguration management, where the practicalities of implementation are discussed.Conclusions:Healthcare professionals broadly supported less frequent screening but had concerns about implementation. It will be essential to address concerns regarding risk estimate accuracy, healthcare professional confidence, service infrastructure and public communication prior to introducing less frequent screening for low-risk women.

Published
2021

12. Additional file 2 of Testing a breast cancer prevention and a multiple disease prevention weight loss programme amongst women within the UK NHS breast screening programme���a randomised feasibility study

Author

Harvie, Michelle, French, David P., Pegington, Mary, Cooper, Grace, Howell, Anthony, McDiarmid, Sarah, Lombardelli, Cheryl, Donnelly, Louise, Ruane, Helen, Sellers, Katharine, Barrett, Emma, Armitage, Christopher J., and Evans, D. Gareth

Abstract

Additional file 2: Supplementary Table 2. Completeness of weight and self -reported lifestyle, anxiety and health status endpoints

Published
2021
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14. sj-pdf-1-whe-10.1177_17455065211009746 – Supplemental material for Introducing a low-risk breast screening pathway into the NHS Breast Screening Programme: Views from healthcare professionals who are delivering risk-stratified screening

Author

Woof, Victoria G, McWilliams, Lorna, Donnelly, Louise S, Howell, Anthony, D Gareth Evans, Maxwell, Anthony J, and French, David P

Subjects
FOS: Clinical medicine, education, 111402 Obstetrics and Gynaecology
Abstract

Supplemental material, sj-pdf-1-whe-10.1177_17455065211009746 for Introducing a low-risk breast screening pathway into the NHS Breast Screening Programme: Views from healthcare professionals who are delivering risk-stratified screening by Victoria G Woof, Lorna McWilliams, Louise S Donnelly, Anthony Howell, D Gareth Evans, Anthony J Maxwell and David P French in Women’s Health

Published
2021
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15. Additional file 1 of Testing a breast cancer prevention and a multiple disease prevention weight loss programme amongst women within the UK NHS breast screening programme���a randomised feasibility study

Author

Harvie, Michelle, French, David P., Pegington, Mary, Cooper, Grace, Howell, Anthony, McDiarmid, Sarah, Lombardelli, Cheryl, Donnelly, Louise, Ruane, Helen, Sellers, Katharine, Barrett, Emma, Armitage, Christopher J., and Evans, D. Gareth

Abstract

Additional file 1: Supplementary Table 1. Multivariable logistic regression of the association between baseline risk of type 2 diabetes and cardiovascular disease and withdrawal and percentage weight loss within the multiple disease prevention group (n = 81). Adjusting for age, Townsend deprivation vation, smoking status, BMI and breast cancer risk category

Published
2021
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16. Hepcidin is essential for alveolar macrophage function and is disrupted by smoke in a murine COPD model

Author

Perez, Elizabeth, Baker, Jonathan R., Di Giandomenico, Silvana, Kermani, Pouneh, Parker, Jacqueline, Kim, Kihwan, Yang, Jianjun, Barnes, Peter J., Vaulont, Sophie, Scandura, Joseph M., Donnelly, Louise E., Stout-Delgado, Heather, and Cloonan, Suzanne M.

Subjects
Iron, Smoking, Article, respiratory tract diseases, Cigarette Smoking, Mice, Inbred C57BL, Disease Models, Animal, Mice, Pulmonary Disease, Chronic Obstructive, Hepcidins, Bone Marrow, hemic and lymphatic diseases, Smoke, Macrophages, Alveolar, Disease Progression, Animals, Humans, Peptides, Cation Transport Proteins, Erythropoietin, Lung
Abstract

Chronic obstructive pulmonary disease (COPD) is a debilitating lung disease associated with cigarette smoking. Alterations in local lung and systemic iron regulation are associated with disease progression and pathogenesis. Hepcidin, an iron regulatory peptide hormone, is altered in subjects with COPD, however, the molecular role of hepcidin in COPD pathogenesis remains to be determined. In this study, utilizing a murine model of smoke-induced COPD, we demonstrate that lung and circulating hepcidin levels are inhibited by cigarette smoke. We show that cigarette smoke exposure increases erythropoietin (EPO) and bone marrow-derived erythroferrone (EFRE) and leads to expanded but inefficient erythropoiesis in murine bone marrow, and an increase in ferroportin on alveolar macrophages (AMs). AMs from smokers and subjects with COPD display increased expression of ferroportin, as well as hepcidin. Notably, murine AMs exposed to smoke fail to increase hepcidin in response to gram-negative or gram-positive infection. Loss of hepcidin in vivo results in blunted functional responses of AMs and exaggerated responses to Streptococcus pneumoniae infection.

Published
2020

17. Visit-to-Visit HbA1c Variability Is Associated With Cardiovascular Disease and Microvascular Complications in Patients With Newly Diagnosed Type 2 Diabetes

Author

Li, Sheyu, Nemeth, Imola, Donnelly, Louise, Hapca, Simona, Zhou, Kaixin, and Pearson, Ewan R

Subjects
Endocrinology, Diabetes and Metabolism, Internal Medicine, Advanced and Specialised Nursing
Abstract

OBJECTIVE To investigate the association between visit-to-visit HbA1c variability and cardiovascular events and microvascular complications in patients with newly diagnosed type 2 diabetes. RESEARCH DESIGN AND METHODS This retrospective cohort study analyzed patients from Tayside and Fife in the Scottish Care Information–Diabetes Collaboration (SCI-DC) who were observable from the diagnosis of diabetes and had at least five HbA1c measurements before the outcomes were evaluated. We used the previously reported HbA1c variability score (HVS), calculated as the percentage of the number of changes in HbA1c >0.5% (5.5 mmol/mol) among all HbA1c measurements within an individual. The association between HVS and 10 outcomes was assessed using Cox proportional hazards models. RESULTS We included 13,111–19,883 patients in the analyses of each outcome. The patients with HVS >60% were associated with elevated risks of all outcomes compared with the lowest quintile (for example, hazard ratios and 95% CIs [HVS >80 to ≤100 vs. HVS ≥0 to ≤20]: 2.38 [1.61–3.53] for major adverse cardiovascular events, 2.4 [1.72–3.33] for all-cause mortality, 2.4 [1.13–5.11] for atherosclerotic cardiovascular death, 2.63 [1.81–3.84] for coronary artery disease, 2.04 [1.12–3.73] for ischemic stroke, 3.23 [1.76–5.93] for heart failure, 7.4 [3.84–14.27] for diabetic retinopathy, 3.07 [2.23–4.22] for diabetic peripheral neuropathy, 5.24 [2.61–10.49] for diabetic foot ulcer, and 3.49 [2.47–4.95] for new-onset chronic kidney disease). Four sensitivity analyses, including adjustment for time-weighted average HbA1c, confirmed the robustness of the results. CONCLUSIONS Our study shows that higher HbA1c variability is associated with increased risks of all-cause mortality, cardiovascular events, and microvascular complications of diabetes independently of high HbA1c.

Published
2020

21. MOESM1 of Breast cancer risk status influences uptake, retention and efficacy of a weight loss programme amongst breast cancer screening attendees: two randomised controlled feasibility trials

Author

Harvie, Michelle, Pegington, Mary, French, David, Cooper, Grace, McDiarmid, Sarah, Howell, Anthony, Donnelly, Louise, Ruane, Helen, Sellers, Katharine, Foden, Philip, and D. Evans

Abstract

Additional file 1. Characteristics of women who joined and did not join Study 1 and Study 2.

Published
2019
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24. Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease (vol 374, pg 1134, 2016)

Author

Stitziel, Nathan O, Stirrups, Kathleen E, Masca, Nicholas GD, Erdmann, Jeanette, Ferrario, Paola G, Koenig, Inke R, Weeke, Peter E, Webb, Thomas R, Auer, Paul L, Schick, Ursula M, Lu, Yingchang, Zhang, He, Dube, Marie-Pierre, Goel, Anuj, Farrall, Martin, Peloso, Gina M, Won, Hong-Hee, Do, Ron, Van Iperen, Erik, Kanoni, Stavroula, Kruppa, Jochen, Mahajan, Anubha, Scott, Robert A, Willenborg, Christina, Braund, Peter S, Van Capelleveen, Julian C, Doney, Alex SF, Donnelly, Louise A, Asselta, Rosanna, Merlini, Piera A, Duga, Stefano, Marziliano, Nicola, Denny, Josh C, Shaffer, Christian M, El-Mokhtari, Nour Eddine, Franke, Andre, Gottesman, Omri, Heilmann, Stefanie, Hengstenberg, Christian, Hoffmann, Per, Holmen, Oddgeir L, Hveem, Kristian, Jansson, Jan-Hakan, Joeckel, Karl-Heinz, Kessler, Thorsten, Kriebel, Jennifer, Laugwitz, Karl L, Marouli, Eirini, Martinelli, Nicola, McCarthy, Mark I, Van Zuydam, Natalie R, Meisinger, Christa, Esko, Tonu, Mihailov, Evelin, Escher, Stefan A, Alver, Maris, Moebus, Susanne, Morris, Andrew D, Muller-Nurasyid, Martina, Nikpay, Majid, Olivieri, Oliviero, Perreault, Louis-Philippe Lemieux, AlQarawi, Alaa, Robertson, Neil R, Akinsanya, Karen O, Reilly, Dermot F, Vogt, Thomas F, Yin, Wu, Asselbergs, Folkert W, Kooperberg, Charles, Jackson, Rebecca D, Stahl, Eli, Strauch, Konstantin, Varga, Tibor V, Waldenberger, Melanie, Zeng, Lingyao, Kraja, Aldi T, Liu, Chunyu, Ehret, Georg B, Newton-Cheh, Christopher, Chasman, Daniel I, Chowdhury, Rajiv, Ferrario, Marco, Ford, Ian, Jukema, J Wouter, Kee, Frank, Kuulasmaa, Kari, Nordestgaard, Borge G, Perola, Markus, Saleheen, Danish, Sattar, Naveed, Surendran, Praveen, Tregouet, David, Young, Robin, Howson, Joanna MM, Butterworth, Adam S, Danesh, John, Ardissino, Diego, Bottinger, Erwin P, Erbel, Raimund, Franks, Paul W, Girelli, Domenico, Hall, Alistair S, Hovingh, G Kees, Kastrati, Adnan, Lieb, Wolfgang, Meitinger, Thomas, Kraus, William E, Shah, Svati H, McPherson, Ruth, Orho-Melander, Marju, Melander, Olle, Metspalu, Andres, Palmer, Colin NA, Peters, Annette, Rader, Daniel J, Reilly, Muredach P, Loos, Ruth JF, Reiner, Alex P, Roden, Dan M, Tardif, Jean-Claude, Thompson, John R, Wareham, Nicholas J, Watkins, Hugh, Willer, Cristen J, Kathiresan, Sekar, Deloukas, Panos, Samani, Nilesh J, Schunkert, Heribert, Other departments, Vascular Medicine, Johnson, Kathleen [0000-0002-6823-3252], Surendran, Praveen [0000-0002-4911-6077], Danesh, John [0000-0003-1158-6791], Wareham, Nicholas [0000-0003-1422-2993], and Apollo - University of Cambridge Repository

Subjects
03 medical and health sciences, 0302 clinical medicine, 030212 general & internal medicine, 030204 cardiovascular system & hematology
Abstract

BACKGROUND The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets. METHODS Through DNA genotyping, we tested 54,003 coding-sequence variants covering 13,715 human genes in up to 72,868 patients with coronary artery disease and 120,770 controls who did not have coronary artery disease. Through DNA sequencing, we studied the effects of loss-of-function mutations in selected genes. RESULTS We confirmed previously observed significant associations between coronary artery disease and low-frequency missense variants in the genes LPA and PCSK9. We also found significant associations between coronary artery disease and low-frequency missense variants in the genes SVEP1 (p.D2702G; minor-allele frequency, 3.60%; odds ratio for disease, 1.14; P=4.2×10−10) and ANGPTL4 (p.E40K; minor-allele frequency, 2.01%; odds ratio, 0.86; P=4.0×10−8), which encodes angiopoietin-like 4. Through sequencing of ANGPTL4, we identified 9 carriers of loss-of-function mutations among 6924 patients with myocardial infarction, as compared with 19 carriers among 6834 controls (odds ratio, 0.47; P=0.04); carriers of ANGPTL4 loss-of-function alleles had triglyceride levels that were 35% lower than the levels among persons who did not carry a loss-of-function allele (P=0.003). ANGPTL4 inhibits lipoprotein lipase; we therefore searched for mutations in LPL and identified a loss-of-function variant that was associated with an increased risk of coronary artery disease (p.D36N; minor-allele frequency, 1.9%; odds ratio, 1.13; P=2.0×10−4) and a gain-of-function variant that was associated with protection from coronary artery disease (p.S447*; minor-allele frequency, 9.9%; odds ratio, 0.94; P=2.5×10−7). CONCLUSIONS We found that carriers of loss-of-function mutations in ANGPTL4 had triglyceride levels that were lower than those among noncarriers; these mutations were also associated with protection from coronary artery disease. (Funded by the National Institutes of Health and others.)

Published
2017
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25. Acute kidney injury, plasma lactate concentrations and lactic acidosis in metformin users: a GoDarts study

Author

Connelly, Paul J., Lonergan, Mike, Soto-Pedre, Enrique, Donnelly, Louise, Zhou, Kaixin, and Pearson, Ewan R.

Abstract

Aims: \ud Metformin is renally excreted and has been associated with the development of lactic acidosis. Although current advice is to omit metformin during illnesses that may increase the risk of acute kidney injury (AKI), the evidence supporting this is lacking. We investigated the relationship between AKI, lactate concentrations and the risk of lactic acidosis in those exposed to metformin.\ud \ud Materials and Methods: \ud We undertook a population‐based case‐control study of lactic acidosis in 1746 participants with Type 2 diabetes and 846 individuals without diabetes with clinically measured lactates with and without AKI between 1994 and 2014. AKI was stratified by severity according to “Kidney Disease: Improving Global Outcomes” guidelines. Mixed‐effects logistic and linear regression were used to analyse lactic acidosis risk and lactate concentrations, respectively.\ud \ud Results: \ud Eighty‐two cases of lactic acidosis were identified. In Type 2 diabetes, those treated with metformin had a greater incidence of lactic acidosis [45.7 per 100 000 patient years; 95% confidence interval (CI) 35.9‐58.3] compared to those not exposed to this drug (11.8 per 100 000 patient years; 95% CI 4.9‐28.5). Lactate concentrations were 0.34 mmol/L higher in the metformin‐exposed cohort (P

Published
2017

27. Catalog of Differentially Expressed Long Non-Coding RNA following Activation of Human and Mouse Innate Immune Response

Author

Roux, Benoit T., Heward, James A., Donnelly, Louise E., Jones, Simon W., and Lindsay, Mark A.

Subjects
TOOLS, Science & Technology, mouse catalog, long non-coding RNA, conserved motif, LANDSCAPE, Immunology, INFLAMMATORY RESPONSE, SEQUENCE, ANNOTATION, EVOLUTION, GENOME, inflammation, TRANSCRIPTS, REVEALS, human catalog, T-CELL DEVELOPMENT, Life Sciences & Biomedicine, innate immunity
Abstract

Despite increasing evidence to indicate that long non-coding RNAs (lncRNAs) are novel regulators of immunity, there has been no systematic attempt to identify and characterize the lncRNAs whose expression is changed following the induction of the innate immune response. To address this issue, we have employed next-generation sequencing data to determine the changes in the lncRNA profile in four human (monocytes, macrophages, epithelium, and chondrocytes) and four mouse cell types (RAW 264.7 macrophages, bone marrow-derived macrophages, peritoneal macrophages, and splenic dendritic cells) following exposure to the pro-inflammatory mediators, lipopolysaccharides (LPS), or interleukin-1β. We show differential expression of 204 human and 210 mouse lncRNAs, with positional analysis demonstrating correlation with immune-related genes. These lncRNAs are predominantly cell-type specific, composed of large regions of repeat sequences, and show poor evolutionary conservation. Comparison within the human and mouse sequences showed less than 1% sequence conservation, although we identified multiple conserved motifs. Of the 204 human lncRNAs, 21 overlapped with syntenic mouse lncRNAs, of which five were differentially expressed in both species. Among these syntenic lncRNA was IL7-AS (antisense), which was induced in multiple cell types and shown to regulate the production of the pro-inflammatory mediator interleukin-6 in both human and mouse cells. In summary, we have identified and characterized those lncRNAs that are differentially expressed following activation of the human and mouse innate immune responses and believe that these catalogs will provide the foundation for the future analysis of the role of lncRNAs in immune and inflammatory responses.

Published
2017

29. Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease

Author

Webb, Thomas R, Erdmann, Jeanette, Stirrups, Kathleen E, Stitziel, Nathan O, Masca, Nicholas G D, Jansen, Henning, Kanoni, Stavroula, Nelson, Christopher P, Ferrario, Paola G, König, Inke R, Eicher, John D, Johnson, Andrew D, Hamby, Stephen E, Betsholtz, Christer, Ruusalepp, Arno, Franzén, Oscar, Schadt, Eric E, Björkegren, Johan L M, Weeke, Peter E, Auer, Paul L, Schick, Ursula M, Lu, Yingchang, Zhang, He, Dube, Marie-Pierre, Goel, Anuj, Farrall, Martin, Peloso, Gina M, Won, Hong-Hee, Do, Ron, van Iperen, Erik, Kruppa, Jochen, Mahajan, Anubha, Scott, Robert A, Willenborg, Christina, Braund, Peter S, van Capelleveen, Julian C, Doney, Alex S F, Donnelly, Louise A, Asselta, Rosanna, Merlini, Pier A, Duga, Stefano, Marziliano, Nicola, Denny, Josh C, Shaffer, Christian, El-Mokhtari, Nour Eddine, Franke, Andre, Heilmann, Stefanie, Hengstenberg, Christian, Hoffmann, Per, and Asselbergs, Folkert W

Subjects
expression quantitative trait loci, single nucleotide polymorphism, cholesteryl ester transfer protein, genome-wide association, Journal Article, genetics
Abstract

BACKGROUND: Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits. OBJECTIVES: This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci. METHODS: In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency >5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs. RESULTS: We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p < 1 × 10(-4) with a range of other diseases/traits. CONCLUSIONS: We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk.

Published
2017

30. Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease

Author

Webb, Thomas R, Erdmann, Jeanette, Stirrups, Kathleen E, Stitziel, Nathan O, Masca, Nicholas G D, Jansen, Henning, Kanoni, Stavroula, Nelson, Christopher P, Ferrario, Paola G, König, Inke R, Eicher, John D, Johnson, Andrew D, Hamby, Stephen E, Betsholtz, Christer, Ruusalepp, Arno, Franzén, Oscar, Schadt, Eric, Auer, Paul L, Björkegren, Johan L M, Weeke, Peter Ejvin, Schick, Ursula M, Lu, Yingchang, Zhang, He, Dubé, Marie-Pierre, Goel, Anuj, Farrall, Martin, Peloso, Gina M, Won, Hong-Hee, Do, Ron, van Iperen, Erik P A, Kruppa, Jochen, Mahajan, Anubha, Scott, Robert A, Willenborg, Christina, Braund, Peter S, van Capelleveen, Julian C, Doney, Alex S F, Donnelly, Louise A, Asselta, Rosanna, Angelica Merlini, Pier, Duga, Stefano, Marziliano, Nicola, Denny, Josh C, Shaffer, Christian M, El Mokhtari, Nour Eddine, Franke, Andre, Heilmann-Heimbach, Stefanie, Hengstenberg, Christian, Hoffmann, Per, Nordestgaard, Børge G, and V Varga, Tibor

Subjects
expression quantitative trait loci, single nucleotide polymorphism, cholesteryl ester transfer protein, genome-wide association, Journal Article, genetics
Abstract

BACKGROUND: Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits.OBJECTIVES: This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci.METHODS: In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency >5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs.RESULTS: We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p < 1 × 10(-4) with a range of other diseases/traits.CONCLUSIONS: We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk.

Published
2017

31. Systematic evaluation of pleiotropy identifies 6 further loci associated with coronary artery disease

Author

Webb, Thomas R., Erdmann, Jeanette, Stirrups, Kathleen E., Stitziel, Nathan O., Masca, Nicholas G.D., Jansen, Henning, Kanoni, Stavroula, Nelson, Christopher P., Ferrario, Paola G., König, Inke R., Eicher, John D., Johnson, Andrew D., Hamby, Stephen E., Betsholtz, Christer, Ruusalepp, Arno, Franzén, Oscar, Schadt, Eric E., Björkegren, Johan L.M., Weeke, Peter E., Auer, Paul L., Schick, Ursula M., Lu, Yingchang, Zhang, He, Dube, Marie-Pierre, Goel, Anuj, Farrall, Martin, Peloso, Gina M., Won, Hong-Hee, Do, Ron, van Iperen, Erik, Kruppa, Jochen, Mahajan, Anubha, Scott, Robert A., Willenborg, Christina, Braund, Peter S., van Capelleveen, Julian C., Doney, Alex S.F., Donnelly, Louise A., Asselta, Rosanna, Merlini, Pier A., Duga, Stefano, Marziliano, Nicola, Denny, Josh C., Shaffer, Christian, El-Mokhtari, Nour Eddine, Franke, Andre, Heilmann, Stefanie, Hengstenberg, Christian, Hoffmann, Per, Holmen, Oddgeir L., Hveem, Kristian, Jansson, Jan-Håkan, Jöckel, Karl-Heinz, Kessler, Thorsten, Kriebel, Jennifer, Laugwitz, Karl L., Marouli, Eirini, Martinelli, Nicola, McCarthy, Mark I., Van Zuydam, Natalie R., Meisinger, Christa, Esko, Tõnu, Mihailov, Evelin, Escher, Stefan A., Alver, Maris, Moebus, Susanne, Morris, Andrew D., Virtamo, Jarma, Nikpay, Majid, Olivieri, Oliviero, Provost, Sylvie, AlQarawi, Alaa, Robertson, Neil R., Akinsansya, Karen O., Reilly, Dermot F., Vogt, Thomas F., Yin, Wu, Asselbergs, Folkert W., Kooperberg, Charles, Jackson, Rebecca D., Stahl, Eli, Müller-Nurasyid, Martina, Strauch, Konstantin, Varga, Tibor V., Waldenberger, Melanie, Zeng, Lingyao, Chowdhury, Rajiv, Salomaa, Veikko, Ford, Ian, Jukema, J. Wouter, Amouyel, Philippe, Kontto, Jukka, Nordestgaard, Børge G., Ferrières, Jean, Saleheen, Danish, Sattar, Naveed, Surendran, Praveen, Wagner, Aline, Young, Robin, Howson, Joanna M.M., Butterworth, Adam S., Danesh, John, Ardissino, Diego, Bottinger, Erwin P., Erbel, Raimund, Franks, Paul W., Girelli, Domenico, Hall, Alistair S., Hovingh, G. Kees, Kastrati, Adnan, Lieb, Wolfgang, Meitinger, Thomas, Kraus, William E., Shah, Svati H., McPherson, Ruth, Orho-Melander, Marju, Melander, Olle, Metspalu, Andres, Palmer, Colin N.A., Peters, Annette, Rader, Daniel J., Reilly, Muredach P., Loos, Ruth J.F., Reiner, Alex P., Roden, Dan M., Tardif, Jean-Claude, Thompson, John R., Wareham, Nicholas J., Watkins, Hugh, Willer, Cristen J., Samani, Nilesh J., Schunkert, Heribert, Deloukas, Panos, Kathiresan, Sekar, Vascular Medicine, Graduate School, ACS - Amsterdam Cardiovascular Sciences, and ACS - Atherosclerosis & ischemic syndromes

Subjects
Medicin och hälsovetenskap, Kardiologi, expression quantitative trait loci, single nucleotide polymorphism, cholesteryl ester transfer protein, genome-wide association, genetics, Cardiac and Cardiovascular Systems, Medical and Health Sciences, Medical Genetics, R1, Medicinsk genetik
Abstract

BACKGROUND Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits. OBJECTIVES This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci. METHODS In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency >5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs. RESULTS We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p < 1 x 10(-4) with a range of other diseases/traits. CONCLUSIONS We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk. (C) 2017 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation.

Published
2017

32. Systematic evaluation of pleiotropy identifies 6 further loci associated with coronary artery disease

Author

Webb, Thomas R., Erdmann, Jeanette, Stirrups, Kathleen E., Stitziel, Nathan O., Masca, Nicholas G. D., Jansen, Henning, Kanoni, Stavroula, Nelson, Christopher P., Ferrario, Paola G., Koenig, Inke R., Eicher, John D., Johnson, Andrew D., Hamby, Stephen E., Betsholtz, Christer, Ruusalepp, Arno, Franzen, Oscar, Schadt, Eric E., Bjoerkegren, Johan L. M., Weeke, Peter E., Auer, Paul L., Schick, Ursula M., Lu, Yingchang, Zhang, He, Dube, Marie-Pierre, Goel, Anuj, Farrall, Martin, Peloso, Gina M., Won, Hong-Hee, Do, Ron, van Iperen, Erik, Kruppa, Jochen, Mahajan, Anubha, Scott, Robert A., Willenborg, Christina, Braund, Peter S., van Capelleveen, Julian C., Doney, Alex S. F., Donnelly, Louise A., Asselta, Rosanna, Merlini, Pier A., Duga, Stefano, Marziliano, Nicola, Denny, Josh C., Shaffer, Christian, El-Mokhtari, Nour Eddine, Franke, Andre, Heilmann, Stefanie, Hengstenberg, Christian, Hoffmann, Per, and Morris, Andrew D.

Subjects
ABDOMINAL AORTIC-ANEURYSM, RISK, expression quantitative trait loci, cholesteryl ester transfer protein, COMMON VARIANTS, SR-BI, HEART-DISEASE, CETP MASS, PHOSPHOLIPASE A(2), DENSITY-LIPOPROTEIN RECEPTOR, single nucleotide polymorphism, genome-wide association, genetics, SCAVENGER RECEPTOR
Abstract

BACKGROUND: Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits.OBJECTIVES: This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci.METHODS: In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency >5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs.RESULTS: We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p -4 with a range of other diseases/traits.CONCLUSIONS We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk. (C) 2017 The Authors. Published by Elsevier on behalf of the American College of Cardiology Foundation.

Published
2017

33. Systematic evaluation of pleiotropy identifies 6 further loci associated with coronary artery disease

Author

Webb, Thomas R., Erdmann, Jeanette, Stirrups, Kathleen E., Stitziel, Nathan O., Masca, Nicholas G., Jansen, Henning, Kanoni, Stavroula, Nelson, Christopher P., Ferrario, Paola G., König, Inke R., Eicher, John D., Johnson, Andrew D., Hamby, Stephen E., Betsholtz, Christer, Ruusalepp, Arno, Franzén, Oscar, Schadt, Eric E., Björkegren, Johan L., Weeke, Peter E., Auer, Paul L., Schick, Ursula M., Lu, Yingchang, Zhang, He, Dube, Marie-Pierre, Goel, Anuj, Farrall, Martin, Peloso, Gina M., Won, Hong-Hee, Do, Ron, van Iperen, Erik, Kruppa, Jochen, Mahajan, Anubha, Scott, Robert A., Willenborg, Christina, Braund, Peter S., van Capelleveen, Julian C., Doney, Alex S., Donnelly, Louise A., Asselta, Rosanna, Merlini, Pier A., Duga, Stefano, Marziliano, Nicola, Denny, Josh C., Shaffer, Christian, El-Mokhtari, Nour Eddine, Franke, Andre, Heilmann, Stefanie, Hengstenberg, Christian, Hoffmann, Per, Holmen, Oddgeir L., Hveem, Kristian, Jansson, Jan-Håkan, Jöckel, Karl-Heinz, Kessler, Thorsten, Kriebel, Jennifer, Laugwitz, Karl L., Marouli, Eirini, Martinelli, Nicola, McCarthy, Mark I., Van Zuydam, Natalie R., Meisinger, Christa, Esko, Tõnu, Mihailov, Evelin, Escher, Stefan A., Alver, Maris, Moebus, Susanne, Morris, Andrew D., Virtamo, Jarma, Nikpay, Majid, and Olivieri, Oliviero

Subjects
ddc:610
Published
2017

34. Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins

Author

Postmus, Iris, Trompet, Stella, Deshmukh, Harshal A., Barnes, Michael R., Li, Xiaohui, Warren, Helen R., Chasman, Daniel I., Zhou, Kaixin, Arsenault, Benoit J., Donnelly, Louise A., Wiggins, Kerri L., Avery, Christy L., Griffin, Paula, Feng, QiPing, Taylor, Kent D., Li, Guo, Evans, Daniel S., Smith, Albert V., de Keyser, Catherine E., Johnson, Andrew D., de Craen, Anton J.M., Stott, David J., Buckley, Brendan M., Ford, Ian, Westendorp, Rudi G. J., Eline Slagboom, P., Sattar, Naveed, Munroe, Patricia B., Sever, Peter, Poulter, Neil, Stanton, Alice, Shields, Denis C., O’Brien, Eoin, Shaw-Hawkins, Sue, Ida Chen, Y.-D., Nickerson, Deborah A., Smith, Joshua D., Pierre Dubé, Marie, Matthijs Boekholdt, S., Kees Hovingh, G., Kastelein, John J.P., McKeigue, Paul M., Betteridge, John, Neil, Andrew, Durrington, Paul N., Doney, Alex, Carr, Fiona, Morris, Andrew, McCarthy, Mark I., Groop, Leif, Ahlqvist, Emma, Bis, Joshua C., Rice, Kenneth, Smith, Nicholas L., Lumley, Thomas, Whitsel, Eric A., Stürmer, Til, Boerwinkle, Eric, Ngwa, Julius S., O’Donnell, Christopher J., Vasan, Ramachandran S., Wei, Wei-Qi, Wilke, Russell A., Liu, Ching-Ti, Sun, Fangui, Guo, Xiuqing, Heckbert, Susan R, Post, Wendy, Sotoodehnia, Nona, Arnold, Alice M., Stafford, Jeanette M., Ding, Jingzhong, Herrington, David M., Kritchevsky, Stephen B., Eiriksdottir, Gudny, Launer, Leonore J., Harris, Tamara B., Chu, Audrey Y., Giulianini, Franco, MacFadyen, Jean G., Barratt, Bryan J., Nyberg, Fredrik, Stricker, Bruno H., Uitterlinden, André G., Hofman, Albert, Rivadeneira, Fernando, Emilsson, Valur, Franco, Oscar H., Ridker, Paul M., Gudnason, Vilmundur, Liu, Yongmei, Denny, Joshua C., Ballantyne, Christie M., Rotter, Jerome I., Adrienne Cupples, L., Psaty, Bruce M., Palmer, Colin N.A., Tardif, Jean-Claude, Colhoun, Helen M., Hitman, Graham, Krauss, Ronald M., Wouter Jukema, J, Caulfield, Mark J., Donnelly, Peter, Barroso, Ines, Blackwell, Jenefer M., Bramon, Elvira, Brown, Matthew A., Casas, Juan P., Corvin, Aiden, Deloukas, Panos, Duncanson, Audrey, Jankowski, Janusz, Markus, Hugh S., Mathew, Christopher G., Plomin, Robert, Rautanen, Anna, Sawcer, Stephen J., Trembath, Richard C., Viswanathan, Ananth C., Wood, Nicholas W., Spencer, Chris C.A., Band, Gavin, Bellenguez, Céline, Freeman, Colin, Hellenthal, Garrett, Giannoulatou, Eleni, Pirinen, Matti, Pearson, Richard, Strange, Amy, Su, Zhan, Vukcevic, Damjan, Langford, Cordelia, Hunt, Sarah E., Edkins, Sarah, Gwilliam, Rhian, Blackburn, Hannah, Bumpstead, Suzannah J., Dronov, Serge, Gillman, Matthew, Gray, Emma, Hammond, Naomi, Jayakumar, Alagurevathi, McCann, Owen T., Liddle, Jennifer, Potter, Simon C., Ravindrarajah, Radhi, Ricketts, Michelle, Waller, Matthew, Weston, Paul, Widaa, Sara, Whittaker, Pamela, Erasmus MC other, Epidemiology, Internal Medicine, ACS - Amsterdam Cardiovascular Sciences, Cardiology, and Vascular Medicine

Subjects
Apolipoprotein E, BLOOD, LOCI, General Physics and Astronomy, Genome-wide association study, VARIANTS, 030204 cardiovascular system & hematology, Pharmacology, Bioinformatics, THERAPY, DISEASE, chemistry.chemical_compound, 0302 clinical medicine, GENE-EXPRESSION, 0303 health sciences, Multidisciplinary, biology, 3. Good health, Multidisciplinary Sciences, Meta-analysis, WHOLE-GENOME, Science & Technology - Other Topics, lipids (amino acids, peptides, and proteins), Statin, medicine.drug_class, Endocrinology and Diabetes, Polymorphism, Single Nucleotide, INDUCED MYOPATHY, General Biochemistry, Genetics and Molecular Biology, Article, 03 medical and health sciences, medicine, Humans, cardiovascular diseases, 030304 developmental biology, Genetic association, Science & Technology, Cholesterol, business.industry, HUMAN PREFRONTAL CORTEX, nutritional and metabolic diseases, General Chemistry, Cholesterol, LDL, A300, chemistry, Pharmacogenetics, biology.protein, PLASMA LIPOPROTEIN(A) LEVELS, Hydroxymethylglutaryl-CoA Reductase Inhibitors, SLCO1B1, business, Genome-Wide Association Study
Abstract

Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response., Statins are effectively used to prevent and manage cardiovascular disease, but patient response to these drugs is highly variable. Here, the authors identify two new genes associated with the response of LDL cholesterol to statins and advance our understanding of the genetic basis of drug response.

Published
2016

35. Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease

Author

Webb, Thomas R., Erdmann, Jeanette, Stirrups, Kathleen E., Stitziel, Nathan O., Masca, Nicholas G.D., Jansen, Henning, Kanoni, Stavroula, Nelson, Christopher P., Ferrario, Paola G., König, Inke R., Eicher, John D., Johnson, Andrew D., Hamby, Stephen E., Betsholtz, Christer, Ruusalepp, Arno, Franzén, Oscar, Schadt, Eric E., Björkegren, Johan L.M., Weeke, Peter E., Auer, Paul L., Schick, Ursula M., Lu, Yingchang, Zhang, He, Dube, Marie-Pierre, Goel, Anuj, Farrall, Martin, Peloso, Gina M., Won, Hong-Hee, Do, Ron, van Iperen, Erik, Kruppa, Jochen, Mahajan, Anubha, Scott, Robert A., Willenborg, Christina, Braund, Peter S., van Capelleveen, Julian C., Doney, Alex S.F., Donnelly, Louise A., Asselta, Rosanna, Merlini, Pier A., Duga, Stefano, Marziliano, Nicola, Denny, Josh C., Shaffer, Christian, El-Mokhtari, Nour Eddine, Franke, Andre, Heilmann, Stefanie, Hengstenberg, Christian, Hoffmann, Per, Holmen, Oddgeir L., Hveem, Kristian, Jansson, Jan-Håkan, Jöckel, Karl-Heinz, Kessler, Thorsten, Kriebel, Jennifer, Laugwitz, Karl L., Marouli, Eirini, Martinelli, Nicola, McCarthy, Mark I., Van Zuydam, Natalie R., Meisinger, Christa, Esko, Tõnu, Mihailov, Evelin, Escher, Stefan A., Alver, Maris, Moebus, Susanne, Morris, Andrew D., Virtamo, Jarma, Nikpay, Majid, Olivieri, Oliviero, Provost, Sylvie, AlQarawi, Alaa, Robertson, Neil R., Akinsansya, Karen O., Reilly, Dermot F., Vogt, Thomas F., Yin, Wu, Asselbergs, Folkert W., Kooperberg, Charles, Jackson, Rebecca D., Stahl, Eli, Müller-Nurasyid, Martina, Strauch, Konstantin, Varga, Tibor V., Waldenberger, Melanie, Zeng, Lingyao, Chowdhury, Rajiv, Salomaa, Veikko, Ford, Ian, Jukema, J. Wouter, Amouyel, Philippe, Kontto, Jukka, Nordestgaard, Børge G., Ferrières, Jean, Saleheen, Danish, Sattar, Naveed, Surendran, Praveen, Wagner, Aline, Young, Robin, Howson, Joanna M.M., Butterworth, Adam S., Danesh, John, Ardissino, Diego, Bottinger, Erwin P., Erbel, Raimund, Franks, Paul W., Girelli, Domenico, Hall, Alistair S., Hovingh, G. Kees, Kastrati, Adnan, Lieb, Wolfgang, Meitinger, Thomas, Kraus, William E., Shah, Svati H., McPherson, Ruth, Orho-Melander, Marju, Melander, Olle, Metspalu, Andres, Palmer, Colin N.A., Peters, Annette, Rader, Daniel J., Reilly, Muredach P., Loos, Ruth J.F., Reiner, Alex P., Roden, Dan M., Tardif, Jean-Claude, Thompson, John R., Wareham, Nicholas J., Watkins, Hugh, Willer, Cristen J., Samani, Nilesh J., Schunkert, Heribert, Deloukas, Panos, and Kathiresan, Sekar

Subjects
Male, expression quantitative trait loci, cholesteryl ester transfer protein, Medizin, Genetic Pleiotropy, Coronary Artery Disease, genetics, genome-wide association, single nucleotide polymorphism, Polymorphism, Single Nucleotide, Gene Frequency, Genetic Loci, Case-Control Studies, Odds Ratio, Humans, Female, Cardiology and Cardiovascular Medicine, Genome-Wide Association Study
Abstract

Background Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits. Objectives This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci. Methods In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency >5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs. Results We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p < 1 × 10−4 with a range of other diseases/traits. Conclusions We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk.

Published
2016

36. Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease

Author

Myocardial Infarction Genetics and CARDIoGRAM Exome Consortia Investigators, Stitziel, Nathan O, Stirrups, Kathleen E, Masca, Nicholas GD, Erdmann, Jeanette, Ferrario, Paola G, König, Inke R, Weeke, Peter E, Webb, Thomas R, Auer, Paul L, Schick, Ursula M, Lu, Yingchang, Zhang, He, Dube, Marie-Pierre, Goel, Anuj, Farrall, Martin, Peloso, Gina M, Won, Hong-Hee, Do, Ron, van Iperen, Erik, Kanoni, Stavroula, Kruppa, Jochen, Mahajan, Anubha, Scott, Robert A, Willenberg, Christina, Braund, Peter S, van Capelleveen, Julian C, Doney, Alex SF, Donnelly, Louise A, Asselta, Rosanna, Merlini, Piera A, Duga, Stefano, Marziliano, Nicola, Denny, Josh C, Shaffer, Christian M, El-Mokhtari, Nour Eddine, Franke, Andre, Gottesman, Omri, Heilmann, Stefanie, Hengstenberg, Christian, Hoffman, Per, Holmen, Oddgeir L, Hveem, Kristian, Jansson, Jan-Håkan, Jöckel, Karl-Heinz, Kessler, Thorsten, Kriebel, Jennifer, Laugwitz, Karl L, Marouli, Eirini, Martinelli, Nicola, McCarthy, Mark I, Van Zuydam, Natalie R, Meisinger, Christa, Esko, Tõnu, Mihailov, Evelin, Escher, Stefan A, Alver, Maris, Moebus, Susanne, Morris, Andrew D, Müller-Nurasyid, Martina, Nikpay, Majid, Olivieri, Oliviero, Lemieux Perreault, Louis-Philippe, AlQarawi, Alaa, Robertson, Neil R, Akinsanya, Karen O, Reilly, Dermot F, Vogt, Thomas F, Yin, Wu, Asselbergs, Folkert W, Kooperberg, Charles, Jackson, Rebecca D, Stahl, Eli, Strauch, Konstantin, Varga, Tibor V, Waldenberger, Melanie, Zeng, Lingyao, Kraja, Aldi T, Liu, Chunyu, Ehret, George B, Newton-Cheh, Christopher, Chasman, Daniel I, Chowdhury, Rajiv, Ferrario, Marco, Ford, Ian, Jukema, J Wouter, Kee, Frank, Kuulasmaa, Kari, Nordestgaard, Børge G, Perola, Markus, Saleheen, Danish, Sattar, Naveed, Surendran, Praveen, Tregouet, David, Young, Robin, Howson, Joanna MM, Butterworth, Adam S, Danesh, John, Ardissino, Diego, Bottinger, Erwin P, Erbel, Raimund, Franks, Paul W, Girelli, Domenico, Hall, Alistair S, Hovingh, G Kees, Kastrati, Adnan, Lieb, Wolfgang, Meitinger, Thomas, Kraus, William E, Shah, Svati H, McPherson, Ruth, Orho-Melander, Marju, Melander, Olle, Metspalu, Andres, Palmer, Colin NA, Peters, Annette, Rader, Daniel, Reilly, Muredach P, Loos, Ruth JF, Reiner, Alex P, Roden, Dan M, Tardif, Jean-Claude, Thompson, John R, Wareham, Nicholas J, Watkins, Hugh, Willer, Cristen J, Kathiresan, Sekkar, Deloukas, Panos, Samani, Nilesh J, Schunkert, Heribert, Johnson, Kathleen [0000-0002-6823-3252], Chowdhury, Rajiv [0000-0003-4881-5690], Surendran, Praveen [0000-0002-4911-6077], Howson, Joanna [0000-0001-7618-0050], Butterworth, Adam [0000-0002-6915-9015], Danesh, John [0000-0003-1158-6791], Wareham, Nicholas [0000-0003-1422-2993], and Apollo - University of Cambridge Repository

Subjects
Male, Genotyping Techniques, education, Mutation, Missense, Coronary Artery Disease, Sequence Analysis, DNA, Middle Aged, Lipoprotein Lipase, Risk Factors, Mutation, Angiopoietin-Like Protein 4, Humans, Female, Angiopoietins, Cell Adhesion Molecules, Triglycerides, Aged
Abstract

BACKGROUND: The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets. METHODS: Through DNA genotyping, we tested 54,003 coding-sequence variants covering 13,715 human genes in up to 72,868 patients with coronary artery disease and 120,770 controls who did not have coronary artery disease. Through DNA sequencing, we studied the effects of loss-of-function mutations in selected genes. RESULTS: We confirmed previously observed significant associations between coronary artery disease and low-frequency missense variants in the genes LPA and PCSK9. We also found significant associations between coronary artery disease and low-frequency missense variants in the genes SVEP1 (p.D2702G; minor-allele frequency, 3.60%; odds ratio for disease, 1.14; P=4.2×10(-10)) and ANGPTL4 (p.E40K; minor-allele frequency, 2.01%; odds ratio, 0.86; P=4.0×10(-8)), which encodes angiopoietin-like 4. Through sequencing of ANGPTL4, we identified 9 carriers of loss-of-function mutations among 6924 patients with myocardial infarction, as compared with 19 carriers among 6834 controls (odds ratio, 0.47; P=0.04); carriers of ANGPTL4 loss-of-function alleles had triglyceride levels that were 35% lower than the levels among persons who did not carry a loss-of-function allele (P=0.003). ANGPTL4 inhibits lipoprotein lipase; we therefore searched for mutations in LPL and identified a loss-of-function variant that was associated with an increased risk of coronary artery disease (p.D36N; minor-allele frequency, 1.9%; odds ratio, 1.13; P=2.0×10(-4)) and a gain-of-function variant that was associated with protection from coronary artery disease (p.S447*; minor-allele frequency, 9.9%; odds ratio, 0.94; P=2.5×10(-7)). CONCLUSIONS: We found that carriers of loss-of-function mutations in ANGPTL4 had triglyceride levels that were lower than those among noncarriers; these mutations were also associated with protection from coronary artery disease. (Funded by the National Institutes of Health and others.).

Published
2016

37. Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease

Author

Stitziel, Nathan O, Stirrups, Kathleen E, Masca, Nicholas G D, Erdmann, Jeanette, Ferrario, Paola G, König, Inke R, Weeke, Peter E, Webb, Thomas R, Auer, Paul L, Schick, Ursula M, Lu, Yingchang, Zhang, He, Dube, Marie-Pierre, Goel, Anuj, Farrall, Martin, Peloso, Gina M, Won, Hong-Hee, Do, Ron, van Iperen, Erik, Kanoni, Stavroula, Kruppa, Jochen, Mahajan, Anubha, Scott, Robert A, Willenberg, Christina, Braund, Peter S, van Capelleveen, Julian C, Doney, Alex S F, Donnelly, Louise A, Asselta, Rosanna, Merlini, Piera A, Duga, Stefano, Marziliano, Nicola, Denny, Josh C, Shaffer, Christian M, El-Mokhtari, Nour Eddine, Franke, Andre, Gottesman, Omri, Heilmann, Stefanie, Hengstenberg, Christian, Hoffman, Per, Holmen, Oddgeir L, Hveem, Kristian, Jansson, Jan-Håkan, Jöckel, Karl-Heinz, Kessler, Thorsten, Kriebel, Jennifer, Laugwitz, Karl L, Marouli, Eirini, Martinelli, Nicola, Asselbergs, Folkert W, and Myocardial Infarction Genetics and CARDIoGRAM Exome Consortia Investigators

Subjects
Male, Genotyping Techniques, Research Support, Non-U.S. Gov't, Mutation, Missense, Coronary Artery Disease, Sequence Analysis, DNA, Middle Aged, Lipoprotein Lipase, Research Support, N.I.H., Extramural, Risk Factors, Mutation, Journal Article, Humans, Female, Angiopoietins, Cell Adhesion Molecules, Triglycerides, Aged
Abstract

BACKGROUND: The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets. METHODS: Through DNA genotyping, we tested 54,003 coding-sequence variants covering 13,715 human genes in up to 72,868 patients with coronary artery disease and 120,770 controls who did not have coronary artery disease. Through DNA sequencing, we studied the effects of loss-of-function mutations in selected genes. RESULTS: We confirmed previously observed significant associations between coronary artery disease and low-frequency missense variants in the genes LPA and PCSK9. We also found significant associations between coronary artery disease and low-frequency missense variants in the genes SVEP1 (p.D2702G; minor-allele frequency, 3.60%; odds ratio for disease, 1.14; P=4.2×10(-10)) and ANGPTL4 (p.E40K; minor-allele frequency, 2.01%; odds ratio, 0.86; P=4.0×10(-8)), which encodes angiopoietin-like 4. Through sequencing of ANGPTL4, we identified 9 carriers of loss-of-function mutations among 6924 patients with myocardial infarction, as compared with 19 carriers among 6834 controls (odds ratio, 0.47; P=0.04); carriers of ANGPTL4 loss-of-function alleles had triglyceride levels that were 35% lower than the levels among persons who did not carry a loss-of-function allele (P=0.003). ANGPTL4 inhibits lipoprotein lipase; we therefore searched for mutations in LPL and identified a loss-of-function variant that was associated with an increased risk of coronary artery disease (p.D36N; minor-allele frequency, 1.9%; odds ratio, 1.13; P=2.0×10(-4)) and a gain-of-function variant that was associated with protection from coronary artery disease (p.S447*; minor-allele frequency, 9.9%; odds ratio, 0.94; P=2.5×10(-7)). CONCLUSIONS: We found that carriers of loss-of-function mutations in ANGPTL4 had triglyceride levels that were lower than those among noncarriers; these mutations were also associated with protection from coronary artery disease. (Funded by the National Institutes of Health and others.).

Published
2016

38. Trans-ancestry meta-analyses identify rare and common variants associated with blood pressure and hypertension

Author

Surendran, Praveen, Drenos, Fotios, Young, Robin, Warren, Helen, Cook, James P, Manning, Alisa K, Grarup, Niels, Sim, Xueling, Barnes, Daniel R, Witkowska, Kate, Staley, James R, Tragante, Vinicius, Tukiainen, Taru, Yaghootkar, Hanieh, Masca, Nicholas, Freitag, Daniel F, Ferreira, Teresa, Giannakopoulou, Olga, Tinker, Andrew, Harakalova, Magdalena, Mihailov, Evelin, Liu, Chunyu, Kraja, Aldi T, Nielsen, Sune Fallgaard, Rasheed, Asif, Samuel, Maria, Zhao, Wei, Bonnycastle, Lori L, Jackson, Anne U, Narisu, Narisu, Swift, Amy J, Southam, Lorraine, Marten, Jonathan, Huyghe, Jeroen R, Stančáková, Alena, Fava, Cristiano, Ohlsson, Therese, Matchan, Angela, Stirrups, Kathleen E, Bork-Jensen, Jette, Gjesing, Anette P, Kontto, Jukka, Perola, Markus, Shaw-Hawkins, Susan, Havulinna, Aki S, Zhang, He, Donnelly, Louise A, de Bakker, Paul I W, Numans, Mattijs E, Asselbergs, Folkert W, and CHARGE-Heart Failure Consortium

Subjects
Journal Article
Abstract

High blood pressure is a major risk factor for cardiovascular disease and premature death. However, there is limited knowledge on specific causal genes and pathways. To better understand the genetics of blood pressure, we genotyped 242,296 rare, low-frequency and common genetic variants in up to 192,763 individuals and used ∼155,063 samples for independent replication. We identified 30 new blood pressure- or hypertension-associated genetic regions in the general population, including 3 rare missense variants in RBM47, COL21A1 and RRAS with larger effects (>1.5 mm Hg/allele) than common variants. Multiple rare nonsense and missense variant associations were found in A2ML1, and a low-frequency nonsense variant in ENPEP was identified. Our data extend the spectrum of allelic variation underlying blood pressure traits and hypertension, provide new insights into the pathophysiology of hypertension and indicate new targets for clinical intervention.

Published
2016

39. Adherence to oral glucose lowering therapies and associations with one year HbA1c: a retrospective cohort analysis in a large primary care database

Author

Farmer, Andrew J., Rodgers, Lauren R, Lonergan, Mike, Shields, Beverley, Weedon, Michael N., Donnelly, Louise, Holman, Rury R., Pearson, Ewan R., and Hattersley, Andrew T

Subjects
Blood Glucose, Glycated Hemoglobin, Male, Dipeptidyl-Peptidase IV Inhibitors, Databases, Factual, Primary Health Care, Middle Aged, Article, Metformin, Medication Adherence, Cohort Studies, Sulfonylurea Compounds, Diabetes Mellitus, Type 2, Humans, Hypoglycemic Agents, Female, Thiazolidinediones, Aged, Retrospective Studies
Abstract

The impact of taking oral glucose-lowering medicines intermittently, rather than as recommended, is unclear. We conducted a retrospective cohort study using community-acquired U.K. clinical data (Clinical Practice Research Database [CPRD] and GoDARTS database) to examine the prevalence of nonadherence to treatment for type 2 diabetes and investigate its potential impact on HbA1c reduction stratified by type of glucose-lowering medication.Data were extracted for patients treated between 2004 and 2014 who were newly prescribed metformin, sulfonylurea, thiazolidinedione, or dipeptidyl peptidase 4 inhibitors and who continued to obtain prescriptions over 1 year. Cohorts were defined by prescribed medication type, and good adherence was defined as a medication possession ratio ≥0.8. Linear regression was used to determine potential associations between adherence and 1-year baseline-adjusted HbA1c reduction.In CPRD and GoDARTS, 13% and 15% of patients, respectively, were nonadherent. Proportions of nonadherent patients varied by the oral glucose-lowering treatment prescribed (range 8.6% [thiazolidinedione] to 18.8% [metformin]). Nonadherent, compared with adherent, patients had a smaller HbA1c reduction (0.4% [4.4 mmol/mol] and 0.46% [5.0 mmol/mol] for CPRD and GoDARTs, respectively). Difference in HbA1c response for adherent compared with nonadherent patients varied by drug (range 0.38% [4.1 mmol/mol] to 0.75% [8.2 mmol/mol] lower in adherent group). Decreasing levels of adherence were consistently associated with a smaller reduction in HbA1c.Reduced medication adherence for commonly used glucose-lowering therapies among patients persisting with treatment is associated with smaller HbA1c reductions compared with those taking treatment as recommended. Differences observed in HbA1c responses to glucose-lowering treatments may be explained in part by their intermittent use.

Published
2015

40. Genetic studies of body mass index yield new insights for obesity biology

Author

Locke, Adam E, Kahali, Bratati, Croteau-Chonka, Damien C, Doney, Alex S F, He, Bing, Heikkilä, Outi, Hietala, Kustaa, Kytö, Janne, Lahermo, Päivi, Lehto, Markku, Österholm, Anne-May, Parkkonen, Maija, Pitkäniemi, Janne, Rosengård-Bärlund, Milla, Eklund, Niina, Saraheimo, Markku, Sarti, Cinzia, Söderlund, Jenny, Soro-Paavonen, Aino, Syreeni, Anna, Thorn, Lena M, Tikkanen, Heikki, Tolonen, Nina, Tryggvason, Karl, Tuomilehto, Jaakko, Estrada, Karol, Wadén, Johan, Gill, Geoffrey V, Prior, Sarah, Guiducci, Candace, Mirel, Daniel B, Taylor, Andrew, Hosseini, Mohsen, Parving, Hans-Henrik, Rossing, Peter, Tarnow, Lise, Eury, Elodie, Ladenvall, Claes, Alhenc-Gelas, François, Lefebvre, Pierre, Rigalleau, Vincent, Roussel, Ronan, Tregouet, David-Alexandre, Maestroni, Anna, Maestroni, Silvia, Falhammar, Henrik, Gu, Tianwei, Folkersen, Lasse, Möllsten, Anna, Cimponeriu, Dan, Mihai, Ioana, Mota, Maria, Mota, Eugen, Serafinceanu, Cristian, Stavarachi, Monica, Hanson, Robert L, Nelson, Robert G, Kretzler, Matthias, Fraser, Ross M, Colhoun, Helen M, Panduru, Nicolae Mircea, Gu, Harvest F, Brismar, Kerstin, Zerbini, Gianpaolo, Hadjadj, Samy, Marre, Michel, Groop, Leif, Lajer, Maria, Bull, Shelley B, Garcia, Melissa E, Waggott, Daryl, Paterson, Andrew D, Savage, David A, Bain, Stephen C, Martin, Finian, Hirschhorn, Joel N, Godson, Catherine, Florez, Jose C, Groop, Per-Henrik, Maxwell, Alexander P, Geller, Frank, Willer, Cristen J, Schmidt, Ellen M, Sengupta, Sebanti, Peloso, Gina M, Gustafsson, Stefan, Kanoni, Stavroula, Ganna, Andrea, Chen, Jin, Buchkovich, Martin L, Mora, Samia, Giedraitis, Vilmantas, Beckmann, Jacques S, Bragg-Gresham, Jennifer L, Chang, Hsing-Y, Demirkan, Ayşe, Den Hertog, Heleen M, Do, Ron, Donnelly, Louise A, Ehret, Georg B, Esko, Tõnu, Feitosa, Mary F, Gigante, Bruna, Ferreira, Teresa, Fischer, Krista, Fontanillas, Pierre, Freitag, Daniel F, Gurdasani, Deepti, Heikkilä, Kauko, Hyppönen, Elina, Isaacs, Aaron, Jackson, Anne U, Esko, Tonu, Go, Alan S, Johansson, Åsa, Johnson, Toby, Kaakinen, Marika, Kettunen, Johannes, Kleber, Marcus E, Li, Xiaohui, Luan, Jian'an, Lyytikäinen, Leo-Pekka, Magnusson, Patrik K E, Mangino, Massimo, Golay, Alain, Mihailov, Evelin, Montasser, May E, Müller-Nurasyid, Martina, Nolte, Ilja M, O'Connell, Jeffrey R, Palmer, Cameron D, Perola, Markus, Petersen, Ann-Kristin, Sanna, Serena, Saxena, Richa, Goodall, Alison H, Service, Susan K, Shah, Sonia, Shungin, Dmitry, Sidore, Carlo, Song, Ci, Strawbridge, Rona J, Surakka, Ida, Tanaka, Toshiko, Teslovich, Tanya M, Thorleifsson, Gudmar, Gordon, Scott D, Van den Herik, Evita G, Voight, Benjamin F, Volcik, Kelly A, Waite, Lindsay L, Wong, Andrew, Wu, Ying, Zhang, Weihua, Absher, Devin, Asiki, Gershim, Barroso, Inês, Gorski, Mathias, Been, Latonya F, Bolton, Jennifer L, Bonnycastle, Lori L, Brambilla, Paolo, Burnett, Mary S, Cesana, Giancarlo, Dimitriou, Maria, Doring, Angela, Elliott, Paul, Grabe, Hans-Jörgen, Epstein, Stephen E, Eyjolfsson, Gudmundur Ingi, Goodarzi, Mark O, Grallert, Harald, Gravito, Martha L, Groves, Christopher J, Hallmans, Göran, Hartikainen, Anna-Liisa, Hayward, Caroline, Hernandez, Dena, Hicks, Andrew A, Holm, Hilma, Hung, Yi-Jen, Illig, Thomas, Jones, Michelle R, Kaleebu, Pontiano, Kastelein, John J P, Khaw, Kay-Tee, Kim, Eric, Grammer, Tanja B, Klopp, Norman, Komulainen, Pirjo, Kumari, Meena, Langenberg, Claudia, Lehtimaki, Terho, Lin, Shih-Yi, Lindstrom, Jaana, Loos, Ruth J F, Mach, François, McArdle, Wendy L, Gräßler, Jürgen, Meisinger, Christa, Mitchell, Braxton D, Muller, Gabrielle, Nagaraja, Ramaiah, Narisu, Narisu, Nieminen, Tuomo V M, Nsubuga, Rebecca N, Olafsson, Isleifur, Ong, Ken K, Palotie, Aarno, Grönberg, Henrik, Papamarkou, Theodore, Pomilla, Cristina, Pouta, Anneli, Rader, Daniel J, Reilly, Muredach P, Ridker, Paul M, Rivadeneira, Fernando, Rudan, Igor, Ruokonen, Aimo, Samani, Nilesh, Fall, Tove, Scharnagl, Hubert, Seeley, Janet, Silander, Kaisa, Stančáková, Alena, Stirrups, Kathleen, Swift, Amy J, Tiret, Laurence, Uitterlinden, Andre G, van Pelt, L Joost, Vedantam, Sailaja, Gusto, Gaëlle, Wainwright, Nicholas, Wijmenga, Cisca, Wild, Sarah H, Willemsen, Gonneke, Wilsgaard, Tom, Wilson, James F, Young, Elizabeth H, Zhao, Jing Hua, Adair, Linda S, Arveiler, Dominique, Haessler, Jeffrey, Assimes, Themistocles L, Bandinelli, Stefania, Bennett, Franklyn, Bochud, Murielle, Boehm, Bernhard O, Boomsma, Dorret I, Borecki, Ingrid B, Bornstein, Stefan R, Bovet, Pascal, Burnier, Michel, Hall, Per, Campbell, Harry, Chakravarti, Aravinda, Chambers, John C, Chen, Yii-Der Ida, Collins, Francis S, Cooper, Richard S, Danesh, John, Dedoussis, George, de Faire, Ulf, Feranil, Alan B, Haller, Toomas, Ferrieres, Jean, Ferrucci, Luigi, Freimer, Nelson B, Gieger, Christian, Groop, Leif C, Gudnason, Vilmundur, Gyllensten, Ulf, Hamsten, Anders, Harris, Tamara B, Hingorani, Aroon, Hallmans, Goran, Hofman, Albert, Hovingh, G Kees, Hsiung, Chao Agnes, Humphries, Steve E, Hunt, Steven C, Hveem, Kristian, Iribarren, Carlos, Jarvelin, Marjo-Riitta, Jula, Antti, Hartman, Catharina A, Kähönen, Mika, Kaprio, Jaakko, Kesäniemi, Antero, Kivimaki, Mika, Kooner, Jaspal S, Koudstaal, Peter J, Krauss, Ronald M, Kuh, Diana, Kuusisto, Johanna, Kyvik, Kirsten O, Hassinen, Maija, Laakso, Markku, Lakka, Timo A, Lind, Lars, Lindgren, Cecilia M, Martin, Nicholas G, März, Winfried, McCarthy, Mark I, McKenzie, Colin A, Meneton, Pierre, Metspalu, Andres, Moilanen, Leena, Morris, Andrew D, Munroe, Patricia B, Njølstad, Inger, Pedersen, Nancy L, Power, Chris, Pramstaller, Peter P, Price, Jackie F, Psaty, Bruce M, Quertermous, Thomas, Heard-Costa, Nancy L, Rauramaa, Rainer, Saleheen, Danish, Salomaa, Veikko, Sanghera, Dharambir K, Saramies, Jouko, Schwarz, Peter E H, Sheu, Wayne H-H, Shuldiner, Alan R, Siegbahn, Agneta, Spector, Tim D, Helmer, Quinta, Stefansson, Kari, Strachan, David P, Tayo, Bamidele O, Tremoli, Elena, Uusitupa, Matti, van Duijn, Cornelia M, Vollenweider, Peter, Wallentin, Lars, Wareham, Nicholas J, Hengstenberg, Christian, Whitfield, John B, Wolffenbuttel, Bruce H R, Ordovas, Jose M, Boerwinkle, Eric, Palmer, Colin N A, Thorsteinsdottir, Unnur, Chasman, Daniel I, Rotter, Jerome I, Franks, Paul W, Ripatti, Samuli, Holmen, Oddgeir, Cupples, L Adrienne, Sandhu, Manjinder S, Rich, Stephen S, Boehnke, Michael, Deloukas, Panos, Kathiresan, Sekar, Mohlke, Karen L, Ingelsson, Erik, Abecasis, Gonçalo R, Abecasis, Gonçalo, Hottenga, Jouke-Jan, Caulfield, Mark, Chasman, Dan, Ehret, Georg, Johnson, Andrew, Johnson, Louise, Larson, Martin, Levy, Daniel, James, Alan L, Munroe, Patricia, Newton-Cheh, Christopher, O'Reilly, Paul, Palmas, Walter, Psaty, Bruce, Rice, Kenneth, Smith, Albert, Snider, Harold, Tobin, Martin, Van Duijn, Cornelia, Jeff, Janina M, Verwoert, Germaine, Rice, Kenneth M, Johnson, Andrew D, Smith, Albert V, Tobin, Martin D, Verwoert, Germaine C, Hwang, Shih-Jen, Pihur, Vasyl, O'Reilly, Paul F, Amin, Najaf, Teumer, Alexander, Glazer, Nicole L, Launer, Lenore, Jolley, Jennifer, Aulchenko, Yurii, Heath, Simon, Sõber, Siim, Parsa, Afshin, Arora, Pankaj, Dehghan, Abbas, Zhang, Feng, Lucas, Gavin, Juliusdottir, Thorhildur, Peden, John F, Igl, Wilmar, Milaneschi, Yuri, Parker, Alex N, Fava, Cristiano, Kinnunen, Leena, Fox, Ervin R, Go, Min Jin, van der Harst, Pim, Kao, Wen Hong Linda, Sjögren, Marketa, Vinay, D. G., Alexander, Myriam, Tabara, Yasuharu, Shaw-Hawkins, Sue, Koenig, Wolfgang, Whincup, Peter H, Liu, Yongmei, Shi, Gang, Tayo, Bamidele, Seielstad, Mark, Sim, Xueling, Nguyen, Khanh-Dung Hoang, Lehtimäki, Terho, Matullo, Giuseppe, Koskenvuo, Markku, Gaunt, Tom R, Onland-Moret, N Charlotte, Cooper, Matthew N, Platou, Carl G P, Org, Elin, Hardy, Rebecca, Dahgam, Santosh, Palmen, Jutta, Vitart, Veronique, Kratzer, Wolfgang, Braund, Peter S, Kuznetsova, Tatiana, Uiterwaal, Cuno S P M, Adeyemo, Adebowale, Ludwig, Barbara, Tomaszewski, Maciej, Tzoulaki, Ioanna, Palmer, Nicholette D, Laitinen, Jaana, Aspelund, Thor, Garcia, Melissa, Chang, Yen-Pei C, Steinle, Nanette I, Grobbee, Diederick E, Arking, Dan E, Kardia, Sharon L, Morrison, Alanna C, Lamina, Claudia, Najjar, Samer, Hadley, David, Brown, Morris J, Connell, John M, Hingorani, Aroon D, Day, Ian N M, Lawlor, Debbie A, Beilby, John P, Lawrence, Robert W, Leander, Karin, Clarke, Robert, Collins, Rory, Hopewell, Jemma C, Ongen, Halit, Dreisbach, Albert W, Li, Yali, Young, J. H., Bis, Joshua C, Viikari, Jorma, Lee, Nanette R, Chen, Ming-Huei, Olden, Matthias, Pattaro, Cristian, Bolton, Judith A Hoffman, Köttgen, Anna, Bergmann, Sven, Mooser, Vincent, Chaturvedi, Nish, Lichtner, Peter, Frayling, Timothy M, Islam, Muhammad, Jafar, Tazeen H, Erdmann, Jeanette, Kulkarni, Smita R, Grässler, Jürgen, Howard, Philip, Guarrera, Simonetta, Ricceri, Fulvio, Emilsson, Valur, Plump, Andrew, Weder, Alan B, Lindström, Jaana, Sun, Yan V, Bergman, Richard N, Scott, Laura J, Stringham, Heather M, Peltonen, Leena, Vartiainen, Erkki, Brand, Stefan-Martin, Kutalik, Zoltán, Lo, Ken Sin, Staessen, Jan A, Wang, Thomas J, Burton, Paul R, Artigas, Maria Soler, Dong, Yanbin, Snieder, Harold, Wang, Xiaoling, Zhu, Haidong, Lohman, Kurt K, Rudock, Megan E, Lobbens, Stéphane, Heckbert, Susan R, Smith, Nicholas L, Wiggins, Kerri L, Doumatey, Ayo, Shriner, Daniel, Veldre, Gudrun, Viigimaa, Margus, Kinra, Sanjay, Prabhakaran, Dorairajan, Tripathy, Vikal, Lorbeer, Roberto, Langefeld, Carl D, Rosengren, Annika, Thelle, Dag S, Corsi, Anna Maria, Singleton, Andrew, Forrester, Terrence, Hilton, Gina, Salako, Tunde, Iwai, Naoharu, Lu, Yingchang, Kita, Yoshikuni, Ogihara, Toshio, Ohkubo, Takayoshi, Okamura, Tomonori, Ueshima, Hirotsugu, Umemura, Satoshi, Eyheramendy, Susana, Meitinger, Thomas, Wichmann, H-Erich, Cho, Yoon Shin, Kim, Hyung-Lae, Lee, Jong-Young, Scott, James, Sehmi, Joban S, Hedblad, Bo, Nilsson, Peter, Smith, George Davey, Raffel, Leslie J, Yao, Jie, O'Donnell, Chris, Schwartz, Stephen M, Ikram, M Arfan, Longstreth, W. T., Mosley, Thomas H, Seshadri, Sudha, Mahajan, Anubha, Shrine, Nick R G, Wain, Louise V, Morken, Mario A, Prokopenko, Inga, Zitting, Paavo, Cooper, Jackie A, Rasheed, Asif, Goel, Anuj, Watkins, Hugh, Bakker, Stephan J L, van Gilst, Wiek H, Janipalli, Charles S, Mani, K Radha, Yajnik, Chittaranjan S, McLachlan, Stela, Mattace-Raso, Francesco U S, Oostra, Ben A, Demirkan, Ayse, Lakatta, Edward G, Orru, Marco, Scuteri, Angelo, Ala-Korpela, Mika, Kangas, Antti J, Menni, Cristina, Soininen, Pasi, Tukiainen, Taru, Würtz, Peter, Ong, Rick Twee-Hee, Dörr, Marcus, Kroemer, Heyo K, Völker, Uwe, Völzke, Henry, Galan, Pilar, Merger, Sigrun, Hercberg, Serge, Lathrop, Mark, Zelenika, Diana, Zhai, Guangju, Meschia, James F, Nalls, Michael A, Sharma, Pankaj, Terzic, Janos, Kumar, M J Kranthi, Denniff, Matthew, Zukowska-Szczechowska, Ewa, Wagenknecht, Lynne E, Fowkes, F Gerald R, Charchar, Fadi J, Guo, Xiuqing, Milani, Lili, Rotimi, Charles, Bots, Michiel L, Brand, Eva, Samani, Nilesh J, Polasek, 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EN., Warrington, NM., Alavere, H., Barroso, I., Berenson, GS., Blackburn, H., Busonero, F., Chen, W., Couper, D., Easton, DF., Eriksson, J., Foroud, T., Geller, F., Hernandez, DG., Kilpeläinen, TO., Li, S., Melbye, M., Murray, JC., Murray, SS., Nelis, M., Ness, AR., Northstone, K., Peacock, M., Pennell, CE., Pharoah, P., Rafnar, T., Rice, JP., Ring, SM., Schork, NJ., Segrè, AV., Sovio, U., Srinivasan, SR., Tammesoo, ML., Tyrer, J., van Meurs JB., Weedon, MN., Wichmann, H., Young, L., Bierut, LJ., Boyd, HA., Econs, MJ., Van T'Hooft, Ferdinand M., Njølstad, Inger, Abecasis, Gonçalo R., Barroso, Inɥ, The MIGEN Consortium, Investigator, Casari, GIORGIO NEVIO, Other departments, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, Landsteiner Laboratory, Clinical Haematology, Damage and Repair in Cancer Development and Cancer Treatment (DARE), Guided Treatment in Optimal Selected Cancer Patients (GUTS), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Groningen Research Institute for Asthma and COPD (GRIAC), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Groningen Kidney Center (GKC), Cardiovascular Centre (CVC), Center for Liver, Digestive and Metabolic Diseases (CLDM), Stem Cell Aging Leukemia and Lymphoma (SALL), Locke, A, Kahali, B, Berndt, S, Justice, A, Pers, T, Day, F, Powell, C, Vedantam, S, Buchkovich, M, Yang, J, Croteau-Chonka, D, Esko, T, Fall, T, Ferreira, T, Gustafsson, S, Kutalik, Z, Luan, J, Magi, R, Randall, J, Winkler, T, Wood, A, Workalemahu, T, Faul, J, Smith, J, Zhao, J, Zhao, W, Chen, J, Fehrmann, R, Hedman, A, Karjalainen, J, Schmidt, E, Absher, D, Amin, N, Anderson, D, Beekman, M, Bolton, J, Bragg-Gresham, J, Buyske, S, Demirkan, A, Deng, G, Ehret, G, Feenstra, B, Feitosa, M, Fischer, K, Goel, A, Gong, J, Jackson, A, Kanoni, S, Kleber, M, Kristiansson, K, Lim, U, Lotay, V, 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J, Ramos, R, Williams, G, Nathan, D, Macrae, C, Berglund, G, Asselta, R, Duga, S, Spreafico, M, Daly, M, Nemesh, J, Korn, J, Surti, A, Gianniny, L, Parkin, M, Burtt, N, Gabriel, S, Wright, B, Ball, S, Schunkert, I, Linsel-Nitschke, P, Lieb, W, Fischer, M, Grosshennig, A, Preuss, M, Scholz, M, Chen, Z, Wilensky, R, Matthai, W, Qasim, A, Hakonarson, H, Devaney, J, Pichard, A, Kent, K, Satler, L, Lindsay, J, Waksman, R, Knouff, C, Scheffold, T, Berger, K, Huge, A, Martinelli, N, Olivieri, O, Corrocher, R, Xie, C, Ahmadi, K, Ainali, C, Bataille, V, Bell, J, Buil, A, Dermitzakis, E, Dimas, A, Durbin, R, Glass, D, Hassanali, N, Ingle, C, Knowles, D, Krestyaninova, M, Lowe, C, Meduri, E, Di Meglio, P, Montgomery, S, Nestle, F, Nica, A, Nisbet, J, O'Rahilly, S, Parts, L, Potter, S, Sekowska, M, Shin, S, Surdulescu, G, Travers, M, Tsaprouni, L, Tsoka, S, Wilk, A, Yang, T, Higashio, J, Williams, R, Nato, A, Ambite, J, Deelman, E, Manolio, T, Heiss, G, Taylor, K, Avery, C, Graff, M, Lin, D, 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Liu, J, Lopez, L, Louwers, Y, Marongiu, M, Klaric, I, Masciullo, C, Melzer, D, Newman, A, Pare, G, Peeters, P, Pop, V, Raikkonen, K, Salumets, A, Stacey, S, Starr, J, Stathopoulou, M, Styrkarsdottir, U, Tenesa, A, Tryggvadottir, L, Tsui, K, van Dam, R, van Gils, C, van Nierop, P, Vink, J, Voorhuis, M, Widen, E, Wijnands-Van Gent, C, Yerges-Armstrong, L, Zgaga, L, Zygmunt, M, Buring, J, Crisponi, L, Demerath, E, Streeten, E, Murray, A, Visser, J, Lunetta, K, Elks, C, Cousminer, D, Koller, D, Lin, P, Smith, E, Warrington, N, Alavere, H, Berenson, G, Blackburn, H, Busonero, F, Chen, W, Couper, D, Easton, D, Foroud, T, Kilpelainen, T, Li, S, Murray, S, Ness, A, Northstone, K, Peacock, M, Pennell, C, Pharoah, P, Rafnar, T, Rice, J, Ring, S, Schork, N, Segre, A, Sovio, U, Srinivasan, S, Tammesoo, M, van Meurs, J, Young, L, Bierut, L, Econs, M, The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The GLGC, The ICBP, The MAGIC Investigators, The MuTHER Consortium, The MIGen Consortium, The PAGE Consortium, The ReproGen Consortium, The GENIE Consortium, The International Endogene Consortium, Berndt, Sonja I, Justice, Anne E, Hyppönen, Elina Tuulikki, Epidemiology and Data Science, NCA - Neurobiology of mental health, and EMGO - Lifestyle, overweight and diabetes

Subjects
Male, LOCI, Genome-wide association study, Continental Population Groups/genetics, VARIANTS, Body Mass Index, Insulin Secretion, Insulin, Age Factor, Adiposity, ddc:616, Adipogenesis, Genetic Predisposition to Disease/genetics, Synapse, 3. Good health, Continental Population Group, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], GENOME-WIDE ASSOCIATIONPROVIDES INSIGHTSGLYCEMIC TRAITSLOCIMETAANALYSISVARIANTSINDIVIDUALSHIPPOCAMPALARCHITECTURETOPIRAMATE, ddc:500, Adipogenesis/genetics, Single Nucleotide/genetics, Age Factors, Continental Population Groups, Energy Metabolism, Europe, Female, Genetic Predisposition to Disease, Glutamic Acid, Humans, Obesity, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Synapses, Genome-Wide Association Study, Multidisciplinary, genetics [Adiposity], Human, Socio-culturale, genetics [Energy Metabolism], ta3111, genetic, body mass index, obesity, SDG 3 - Good Health and Well-being, GLYCEMIC TRAITS, genetics [Continental Population Groups], Genetic variability, Polymorphism, GENOME-WIDE ASSOCIATION, genetics [Adipogenesis], METAANALYSIS, Genetic association, Adipogenesi, genetics [Quantitative Trait Loci], ta1184, metabolism [Glutamic Acid], ta1182, PATHWAYS, metabolism [Synapses], ta3121, medicine.disease, metabolism [Insulin], Adiposity/genetics, Clinical Medicine, Quantitative Trait Loci/genetics, Body mass index, HUMAN HEIGHT, BIO/12 - BIOCHIMICA CLINICA E BIOLOGIA MOLECOLARE CLINICA, Synapses/metabolism, Medizin, Obesity/genetics, Bioinformatics, genetic basis, Obesity/metabolism, genetics [Obesity], body mass index (BMI), genetics [Genetic Predisposition to Disease], ethnology [Europe], 2. Zero hunger, Genetics, ARCHITECTURE, Genetics of obesity, Medicine (all), Single Nucleotide, Polymorphism, Single Nucleotide/genetics, Insulin/metabolism/secretion, Glutamic Acid/metabolism, genetics [Polymorphism, Single Nucleotide], EXPRESSION, Insulin/metabolism, PROVIDES INSIGHTS, genetics [Racial Groups], Biology, Obesity/genetics/metabolism, Europe/ethnology, metabolism [Obesity], Mendelian randomization, medicine, Energy Metabolism/genetics, body mass, genetic analysis, obesity, Klinisk medicin
Abstract

Item does not contain fulltext Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in up to 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 x 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for approximately 2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous system in obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

Published
2015

41. Additional file 1: Appendix 1. of Mammographic density adds accuracy to both the Tyrer-Cuzick and Gail breast cancer risk models in a prospective UK screening cohort

Author

Brentnall, Adam, Harkness, Elaine, Astley, Susan, Donnelly, Louise, Stavrinos, Paula, Sampson, Sarah, Fox, Lynne, Sergeant, Jamie, Harvie, Michelle, Wilson, Mary, Beetles, Ursula, Soujanya Gadde, Yit Lim, Jain, Anil, Bundred, Sara, Barr, Nicola, Reece, Valerie, Howell, Anthony, Cuzick, Jack, and D. Evans

Subjects
body regions
Abstract

Density residual: description of methods. Appendix 2: Table S1. Univariate and multivariate performance of breast density and the Tyrer-Cuzick and Gail risk models, subgroup analysis by time of cancer diagnosis. (PDF 396 kb)

Published
2015
Full Text
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42. New genetic loci link adipose and insulin biology to body fat distribution

Author

Shungin, Dmitry, Winkler, Thomas W, Workalemahu, Tsegaselassie, Hartman, Catharina A, Duncan, Emma L, Ntzani, Evangelia E, Oei, Ling, Albagha, Omar M E, Amin, Najaf, Kemp, John P, Koller, Daniel L, Li, Guo, Liu, Ching-Ti, Minster, Ryan L, Hassinen, Maija, Moayyeri, Alireza, Vandenput, Liesbeth, Willner, Dana, Xiao, Su-Mei, Yerges-Armstrong, Laura M, Zheng, Hou-Feng, Alonso, Nerea, Eriksson, Joel, Kammerer, Candace M, Kaptoge, Stephen K, Hayward, Caroline, Leo, Paul J, Thorleifsson, Gudmar, Wilson, Scott G, Wilson, James F, Aalto, Ville, Alen, Markku, Aragaki, Aaron K, Aspelund, Thor, Center, Jacqueline R, Dailiana, Zoe, Heikkilä, Kauko, Duggan, David J, Garcia, Melissa, Garcia-Giralt, Natàlia, Giroux, Sylvie, Hallmans, Göran, Hocking, Lynne J, Husted, Lise Bjerre, Jameson, Karen A, Khusainova, Rita, Kim, Ghi Su, Herzig, Karl-Heinz, Kooperberg, Charles, Koromila, Theodora, Kruk, Marcin, Laaksonen, Marika, Lacroix, Andrea Z, Lee, Seung Hun, Leung, Ping C, Lewis, Joshua R, Masi, Laura, Mencej-Bedrac, Simona, Helmer, Quinta, Nguyen, Tuan V, Nogues, Xavier, Patel, Millan S, Prezelj, Janez, Rose, Lynda M, Scollen, Serena, Siggeirsdottir, Kristin, Smith, Albert V, Svensson, Olle, Trompet, Stella, Hillege, Hans L, Trummer, Olivia, van Schoor, Natasja M, Woo, Jean, Zhu, Kun, Balcells, Susana, Brandi, Maria Luisa, Buckley, Brendan M, Cheng, Sulin, Christiansen, Claus, Cooper, Cyrus, Holmen, Oddgeir, Dedoussis, George, Ford, Ian, Frost, Morten, Goltzman, David, González-Macías, Jesús, Kähönen, Mika, Karlsson, Magnus, Khusnutdinova, Elza, Koh, Jung-Min, Kollia, Panagoula, Hunt, Steven C, Langdahl, Bente Lomholt, Leslie, William D, Lips, Paul, Ljunggren, Östen, Lorenc, Roman S, Marc, Janja, Mellström, Dan, Obermayer-Pietsch, Barbara, Olmos, José M, Pettersson-Kymmer, Ulrika, Isaacs, Aaron, Reid, David M, Riancho, José A, Ridker, Paul M, Rousseau, François, Slagboom, P Eline, Tang, Nelson L S, Urreizti, Roser, Van Hul, Wim, Viikari, Jorma, Zarrabeitia, María T, Wu, Joseph M W, 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NourEddine, Van Vliet-Ostaptchouk, Jana V, Hager, Jörg, Hunt, Sarah E, Kang, Hyun M, Kessler, Thorsten, Knowles, Joshua W, Kolovou, Genovefa, Langford, Cordelia, Lokki, Marja-Liisa, Lundmark, Anders, Maouche, Seraya, Nikus, Kjell, Rayner, N William, Rosinger, Silke, Rubin, Diana, Rumpf, Moritz P, Schäfer, Arne, Sivananthan, Mohan, Stewart, Alexandre F R, Tan, Sian-Tsung, Thorgeirsson, Gudmundur, van der Schoot, C Ellen, Wagner, Peter J, Wells, George A, Wild, Philipp S, Ärnlöv, Johan, Basart, Hanneke, Cambien, Francois, Cupples, Adrienne L, Arscott, Gillian M, Diemert, Patrick, Evans, Alun, Ferrario, Marco M, Gauguier, Dominique, Go, Alan S, Goodall, Alison H, Gudnason, Villi, Hazen, Stanley L, Jang, Yangsoo, Kim, Hyo-Soo, Laaksonen, Reijo, Lee, Ji-Young, Ouwehand, Willem H, Parish, Sarah, Park, Jeong E, Bellis, Claire, Schadt, Eric, Shah, Svati H, Stark, Klaus, Trégouët, David-Alexandre, Virtamo, Jarmo, Bennett, Amanda J, Wareham, Nicholas, Zimmermann, Martina E, Nieminen, Markku S, Hengstenberg, Christian, Berne, Christian, Zalloua, Pierre A, Blankenberg, Stefan S, Pers, Tune H, Blüher, Matthias, O'Donnell, Christopher, Roberts, Robert, Schunkert, Heribert, Garnaas, Maija, Böger, Carsten A, Bonnet, Fabrice, Tin, Adrienne, Taliun, Daniel, Li, Man, Gao, Xiaoyi, Gorski, Mathias, Yang, Qiong, Hundertmark, Claudia, Böttcher, Yvonne, Foster, Meredith C, O'Seaghdha, Conall M, Struchalin, Maksim, Gierman, Hinco J, Feitosa, Mary, Atkinson, Elizabeth J, Carba, Delia B, Chouraki, Vincent, Holliday, Elizabeth G, Sorice, Rossella, Kutalik, Zoltan, Deshmukh, Harshal, Chu, Audrey Y, Murgia, Federico, Caspersen, Ida H, Imboden, Medea, Kollerits, Barbara, Schmidt, Helena, Cavalieri, Margherita, Rao, Madhumathi, de Andrade, Mariza, Turner, Stephen T, Ding, Jingzhong, Daw, E Warwick, Freedman, Barry I, Wichmann, H -Erich, Minelli, Cosetta, Wheeler, Heather E, Deelen, Joris, Zaboli, Ghazal, Ellinghaus, David, Nöthlings, Ute, Jacobs, Gunnar, Biffar, Reiner, Endlich, Karlhans, Nauck, 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Surdulescu, G., Travers, ME., Tsaprouni, L., Tsoka, S., Wilk, A., Matise, T., Buyske, S., Higashio, J., Williams, R., Nato, A., Ambite, JL., Deelman, E., Manolio, T., Hindorff, L., Heiss, G., Taylor, K., Avery, C., Graff, M., Lin, D., Quibrera, M., Cochran, B., Kao, L., Umans, J., Cole, S., MacCluer, J., Person, S., Pankow, J., Gross, M., Fornage, M., Durda, P., Jenny, N., Patsy, B., Arnold, A., Buzkova, P., Crawford, D., Haines, J., Murdock, D., Glenn, K., Brown-Gentry, K., Thornton-Wells, T., Dumitrescu, L., Jeff, J., Bush, WS., Mitchell, SL., Goodloe, R., Wilson, S., Boston, J., Malinowski, J., Restrepo, N., Oetjens, M., Fowke, J., Zheng, W., Spencer, K., Ritchie, M., Pendergrass, S., Le Marchand£££Loïc£££ L., Wilkens, L., Park, L., Tiirikainen, M., Kolonel, L., Lim, U., Cheng, I., Wang, H., Shohet, R., Haiman, C., Stram, D., Henderson, B., Monroe, K., Schumacher, F., Peters, U., Anderson, G., Carlson, C., Prentice, R., LaCroix, A., Wu, C., Carty, C., Gong, J., Rosse, S., Young, A., Haessler, J., Kocarnik, J., Lin, Y., Jackson, R., Duggan, D., Kuller, L., Stolk, L., He, C., Sulem, P., Barbalic, M., Broer, L., Byrne, EM., Gudbjartsson, DF., McArdle, PF., Porcu, E., van Wingerden, S., Zhuang, W., Albrecht, E., Alizadeh, BZ., Lauc, LB., Broekmans, FJ., Burri, A., Chanock, SJ., Chen, C., Corre, T., Coviello, AD., d'Adamo, P., Davies, G., Deary, IJ., Ebrahim, S., Fauser, BC., Ferreli, L., Folsom, AR., Garcia, ME., Hall, P., Haller, T., Hankinson, SE., Hass, M., Heath, AC., Janssens, AC., Keyzer, J., Lahti, J., Lai, S., Laisk, T., Laven, JS., Liu, J., Lopez, LM., Louwers, YV., Marongiu, M., Klaric, IM., Masciullo, C., McKnight, B., Medland, SE., Melzer, D., Newman, AB., Paré, G., Peeters, PH., Plump, AS., Pop, VJ., Räikkönen, K., Salumets, A., Smith, JA., Stacey, SN., Starr, JM., Stathopoulou, MG., Tenesa, A., Thorand, B., Tryggvadottir, L., Tsui, K., van Dam RM., van Gils CH., van Nierop, P., Vink, JM., Voorhuis, M., Wallaschofski, H., Widen, E., Wijnands-van Gent CJ., Zgaga, L., Zygmunt, M., Arnold, AM., Buring, JE., Crisponi, L., Demerath, EW., Hunter, DJ., Schlessinger, D., Murray, A., Murabito, JM., Visser, JA., Lunetta, KL., Elks, CE., Cousminer, DL., Feenstra, B., Lin, P., van Wingerden SW., Smith, EN., Warrington, NM., Alavere, H., Barroso, I., Berenson, GS., Blackburn, H., Busonero, F., Chen, W., Couper, D., Easton, DF., Foroud, T., Geller, F., Hernandez, DG., Kilpeläinen, TO., Li, S., Melbye, M., Murray, JC., Murray, SS., Nelis, M., Ness, AR., Northstone, K., Pennell, CE., Pharoah, P., Rafnar, T., Rice, JP., Ring, SM., Schork, NJ., Segrè, AV., Sovio, U., Srinivasan, SR., Tammesoo, ML., Tyrer, J., Weedon, MN., Wichmann, H., Young, L., Zhuang, WV., Bierut, LJ., Boyd, HA., Department of Clinical Sciences, Lund University [Lund], Genetic Epidemiology and Clinical Research Group, Umea University Hospital, Department of Odontology, Umeå University, Signalisation et Transports Ioniques Membranaires (STIM), Université de Poitiers-Université de Tours (UT)-Centre National de la Recherche Scientifique (CNRS), Department of Medical Sciences, Center for Biological Sequence Analysis [Lyngby], Danmarks Tekniske Universitet = Technical University of Denmark (DTU), Laboratory of Image Science and Technology [Nanjing] (LIST), Southeast University [Jiangsu]-School of Computer Science and Engineering, Limnology, Ecology, Estonian Genome and Medicine, University of Tartu, Institute of Molecular and Cell Biology, Department of Medical Epidemiology and Biostatistics (MEB), Karolinska Institutet [Stockholm], Department of Medical Genetics, Université de Lausanne = University of Lausanne (UNIL), Institute of Medical Informatics, Biometry and Epidemiology, Universität Duisburg-Essen = University of Duisburg-Essen [Essen], Centre d'Immunologie de Marseille - Luminy (CIML), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Genetic Epidemiology Unit, 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(INSERM)-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Geriatric Rehabilitation Unit, Azienda Sanitaria Firenze, Department of Pharmacy Sciences, Creighton University Medical Center, Medical Department III, Universität Leipzig, Foie, métabolismes et cancer, Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Department of Epidemiology, Erasmus Medical Centre, Netherlands Genomics Initiative (NGI), Netherlands Genomics Initiative, Institute of Epidemiology [Neuherberg] (EPI), German Research Center for Environmental Health - Helmholtz Center München (GmbH), Department of Public Health and Clinical Medicine, Medstar Research Institute, Genetics and Pathology, Finnish Institute of Occupational Health, Epidemiology, University Medical Centre Groningen, Departments of Microbiology & Molecular Genetics and Molecular Biology & Biochemistry, University of California [Irvine] (UC Irvine), Department of Odontology, Cariology, Institute of Human Genetics, Helmholtz Zentrum München = German Research Center for Environmental Health, Génétique des maladies multifactorielles (GMM), Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), Division of Cardiology, Geneva University Hospital (HUG), Department of Psychiatry and Psychotherapy, Rheinische Friedrich-Wilhelms-Universität Bonn, Department of Physics, Indian Institute of Technology Kanpur (IIT Kanpur), University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), Department of Genomics, Life and Brain Center, Universität Bonn = University of Bonn, Anaesthesia and Intensive care, Royal Aberdeen Childrens Hospital, UCL Institute of neurology, UCL Institute of Neurology, Human Genetics, The Wellcome Trust Sanger Institute [Cambridge], 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= University of Helsinki, Unit of Genetic Epidemiology and Bioinformatics, Department of Epidemiology, University Medical Center Groningen, Department of Pediatrics, Augusta University - Medical College of Georgia, University System of Georgia (USG)-University System of Georgia (USG), Department of Public Health, South Ostrobothnia Central Hospital, Department of Clinical and Preventive Medicine, Danube-University Krems, Netherlands Consortium for Healthy Aging [Leiden, Netherlands] (NCHA), Institute of Public Health and Clinical Nutrition, University of Eastern Finland, MRC epidemiology Unit, Institute of Epidemiology, Clinical Genetics Branch, Division of Cancer Epidemiology & Genetics, National Institutes of Health [Bethesda] (NIH)-National Cancer Institute [Bethesda] (NCI-NIH), National Institutes of Health [Bethesda] (NIH), Department of Oncology, Queensland Brain Institute, University of Queensland [Brisbane], Harvard Reproductive Sciences Center and Reproductive Endocrine Unit, 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(BU)-National Heart, Lung, and Blood Institute [Bethesda] (NHLBI), Endocrinology and Metabolism, The Churchill Hospital-Oxford Centre for Diabetes, Landsteiner Laboratory, Clinical Haematology, Other departments, ACS - Amsterdam Cardiovascular Sciences, Vascular Medicine, Lund University Diabetes Centre-Lund University [Lund], Université de Tours-Centre National de la Recherche Scientifique (CNRS)-Université de Poitiers, Technical University of Denmark [Lyngby] (DTU), Université de Lausanne (UNIL), Universität Duisburg-Essen [Essen], Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU), University of California [Berkeley], University of California-University of California, Génomique Intégrative et Modélisation des Maladies Métaboliques (EGID), Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche 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Université de Lille, Sciences et Technologies-Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique (CNRS), University of Helsinki-University of Helsinki, Helmholtz-Zentrum München (HZM), National Heart, Lung, and Blood Institute [Bethesda] (NHLBI)-Boston University [Boston] (BU), Internal Medicine, Child and Adolescent Psychiatry / Psychology, Clinical Genetics, Medical Informatics, Obstetrics & Gynecology, Lund University [Lund]-Lund University Diabetes Centre, Metabolic functional (epi)genomics and molecular mechanisms involved in type 2 diabetes and related diseases - UMR 8199 - UMR 1283 (GI3M), Institute of Medicine-University of Gothenburg (GU), Signalisation et Transports Ioniques Membranaires ( STIM ), Université de Poitiers-Centre National de la Recherche Scientifique ( CNRS ), Technical University of Denmark [Lyngby] ( DTU ), Laboratory of Image Science and Technology [Nanjing] ( LIST ), Department of Medical Epidemiology and Biostatistics ( MEB ), University of Lausanne, Centre d'Immunologie de Marseille - Luminy ( CIML ), Aix Marseille Université ( AMU ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), Erasmus MC, Space Sciences Laboratory [Berkeley] ( SSL ), Génomique Intégrative et Modélisation des Maladies Métaboliques ( EGID ), Université de Lille-Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Institut Pasteur de Lille, Réseau International des Instituts Pasteur ( RIIP ) -Réseau International des Instituts Pasteur ( RIIP ) -Centre National de la Recherche Scientifique ( CNRS ) -Centre Hospitalier Régional Universitaire [Lille] ( CHRU Lille ), University of Leipzig, Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique ), Institute of Epidemiology [Neuherberg] ( EPI ), University of California [Irvine] ( UCI ), Génétique des maladies multifactorielles ( GMM ), Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique ( CNRS ), Geneva University Hospital ( HUG ), Bonn Universität [Bonn], Indian Institute of Technology Kanpur ( IIT Kanpur ), The University of North Carolina at Chapel Hill, Université de Bonn, Wellcome Trust Sanger Institute, Harvard University School of Public Health, Czech Academy of Sciences [Prague] ( ASCR ), deCODE genetics, University of Groningen [Groningen]-University Medical Center Groningen-Beatrix Children's Hospital-Groningen Research Institute for Asthma and COPD, Yale School of Medicine, National Heart and Lung Institute ( NHLI ), Réseau International des Instituts Pasteur ( RIIP ) -Réseau International des Instituts Pasteur ( RIIP ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Université de Lille, Droit et Santé, University Medical Center Groningen, University of Cambridge [UK] ( CAM ), Wellcome Trust Centre for Human Genetics, University of Pisa [Pisa], University of Cambridge [UK] ( CAM ) -Institute of Metabolic Science, German Research Center for Environmental Health-Helmholtz-Zentrum München ( HZM ), University of Otago, University of Greifswald, University College of London [London] ( UCL ), National Institute for Health and Welfare, Queen's University [Belfast] ( QUB ), University of Hawaii at Manoa ( UHM ), University of Gothenburg ( GU ) -Institute of Medicine, Recherches en Psychopathologie, nouveaux symptômes et lien social ( EA 4050 ), Université de Poitiers-Université de Brest ( UBO ) -Université Catholique de l'Ouest-Université de Rennes 2 ( UR2 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ), Institut de biologie de Lille - IBL ( IBLI ), Réseau International des Instituts Pasteur ( RIIP ) -Réseau International des Instituts Pasteur ( RIIP ) -Université de Lille, Droit et Santé-Centre National de la Recherche Scientifique ( CNRS ), Institut Cochin ( UM3 (UMR 8104 / U1016) ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Centre National de la Recherche Scientifique ( CNRS ), University Medicine Greifswald,-HELIOS Hospital Stralsund, Finland Institute for Molecular Medicine ( FIMM ), Georgia Prevention Institute, Netherlands Consortium for Healthy Aging, Helmholtz-Zentrum München ( HZM ), National Institutes of Health ( NIH ) -National Cancer Institute ( NIH ), Massachusetts General Hospital, Children's Hospital, Boston, Broad Institute, Cambridge, MA, The University of North Carolina at Chapel Hill-UNC Gillings School of Global Public Health-Carolina Center for Genome Sciences, Shungin D, Winkler TW, Adipogen, Consortium, Cardiogramplusc4d, Consortium, Ckdgen, Consortium, Gefos, Consortium, Genie, Consortium, Glgc, Icbp, International, Endogene Consortium, Lifelines, Cohort Study, Magic, Investigator, Muther, Consortium, Consortium, Page, ReproGen Consortium, Amouyel P, D'Adamo, ADAMO PIO, Gasparini, Paolo, Shungin, Dmitry, Winkler, Thomas W, Croteau-Chonka, Damien C, Ferreira, Teresa, Hypponen, Elina, Mohlke, Karen L, ADIPOGEN Consortium, Int Endogene Consortium, Lee Kong Chian School of Medicine (LKCMedicine), Epidemiologie, RS: CARIM - R3.02 - Hypertension and target organ damage, Université de Tours-Université de Poitiers-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Biological Psychology, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, EMGO+ - Lifestyle, Overweight and Diabetes, Damage and Repair in Cancer Development and Cancer Treatment (DARE), Guided Treatment in Optimal Selected Cancer Patients (GUTS), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Life Course Epidemiology (LCE), Cardiovascular Centre (CVC), Groningen Kidney Center (GKC), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Groningen Research Institute for Asthma and COPD (GRIAC), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Center for Liver, Digestive and Metabolic Diseases (CLDM), Stem Cell Aging Leukemia and Lymphoma (SALL), Shungin, D, Winkler, T, Croteau Chonka, D, Ferreira, T, Locke, A, Mägi, R, Strawbridge, R, Pers, T, Fischer, K, Justice, A, Workalemahu, T, Wu, J, Buchkovich, M, Heard Costa, N, Roman, T, Drong, A, Song, C, Gustafsson, S, Day, F, Esko, T, Fall, T, Kutalik, Z, Luan, J, Randall, J, Scherag, A, Vedantam, S, Wood, A, Chen, J, Fehrmann, R, Karjalainen, J, Kahali, B, Liu, C, Schmidt, E, Absher, D, Amin, N, Anderson, D, Beekman, M, Bragg Gresham, J, Buyske, S, Demirkan, A, Ehret, G, Feitosa, M, Goel, A, Jackson, A, Johnson, T, Kleber, M, Kristiansson, K, Mangino, M, Leach, I, Medina Gomez, C, Palmer, C, Pasko, D, Pechlivanis, S, Peters, M, Prokopenko, I, Stanca'Kova', A, Sung, Y, Tanaka, T, Teumer, A, Van Vliet Ostaptchouk, J, Yengo, L, Zhang, W, Albrecht, E, Ärnlöv, J, Arscott, G, Bandinelli, S, Barrett, A, Bellis, C, Bennett, A, Berne, C, Blüher, M, Böhringer, S, Bonnet, F, Böttcher, Y, Bruinenberg, M, Carba, D, Caspersen, I, Clarke, R, Daw, E, Deelen, J, Deelman, E, Delgado, G, Doney, A, Eklund, N, Erdos, M, Estrada, K, Eury, E, Friedrich, N, Garcia, M, Giedraitis, V, Gigante, B, Go, A, Golay, A, Grallert, H, Grammer, T, Gräsler, J, Grewal, J, Groves, C, Haller, T, Hallmans, G, Hartman, C, Hassinen, M, Hayward, C, Heikkilä, K, Herzig, K, Helmer, Q, Hillege, H, Holmen, O, Hunt, S, Isaacs, A, Ittermann, T, James, A, Johansson, I, Juliusdottir, T, Kalafati, I, Kinnunen, L, Koenig, W, Kooner, I, Kratzer, W, Lamina, C, Leander, K, Lee, N, Lichtner, P, Lind, L, Lindström, J, Lobbens, S, Lorentzon, M, Mach, F, Magnusson, P, Mahajan, A, Mcardle, W, Menni, C, Merger, S, Mihailov, E, Milani, L, Mills, R, Moayyeri, A, Monda, K, Mooijaart, S, Mühleisen, T, Mulas, A, Müller, G, Müller Nurasyid, M, Nagaraja, R, Nalls, M, Narisu, N, Glorioso, N, Nolte, I, Olden, M, Rayner, N, Renstrom, F, Ried, J, Robertson, N, Rose, L, Sanna, S, Scharnagl, H, Scholtens, S, Sennblad, B, Seufferlein, T, Sitlani, C, Smith, A, Stirrups, K, Stringham, H, Sundström, J, Swertz, M, Swift, A, Syvänen, A, Tayo, B, Thorand, B, Thorleifsson, G, Tomaschitz, A, Troffa, C, Van Oort, F, Verweij, N, Vonk, J, Waite, L, Wennauer, R, Wilsgaard, T, Wojczynski, M, Wong, A, Zhang, Q, Zhao, J, Brennan, E, Choi, M, Eriksson, P, Folkersen, L, Franco Cereceda, A, Gharavi, A, Hedman, A, Hivert, M, Huang, J, Kanoni, S, Karpe, F, Keildson, S, Kiryluk, K, Liang, L, Lifton, R, Ma, B, Mcknight, A, Mcpherson, R, Metspalu, A, 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Smith, J, Stacey, S, Starr, J, Stathopoulou, M, Tenesa, A, Tryggvadottir, L, Tsui, K, van Dam, R, van Gils, C, van Nierop, P, Vink, J, Voorhuis, M, Wallaschofski, H, Widen, E, Wijnands van Gent, C, Zgaga, L, Zygmunt, M, Buring, J, Crisponi, L, Demerath, E, Murray, A, Visser, J, Lunetta, K, Elks, C, Cousminer, D, Feenstra, B, Lin, P, Smith, E, Warrington, N, Alavere, H, Berenson, G, Blackburn, H, Busonero, F, Chen, W, Easton, D, Foroud, T, Geller, F, Kilpeläinen, T, Li, S, Melbye, M, Murray, J, Murray, S, Ness, A, Northstone, K, Pennell, C, Pharoah, P, Rafnar, T, Rice, J, Ring, S, Schork, N, Segrè, A, Sovio, U, Srinivasan, S, Tammesoo, M, Tyrer, J, Weedon, M, Young, L, Bierut, L, Boyd, H, Psychiatry, NCA - Neurobiology of mental health, and EMGO - Lifestyle, overweight and diabetes

Subjects
Adipose Tissue/metabolism, Male, genetic association, subcutaneous fat, Transcription, Genetic, Adipocytes, Adipogenesis, Adipose Tissue, Age Factors, Body Mass Index, Continental Population Groups, Epigenesis, Genetic, Europe, Female, Genome, Human, Humans, Insulin, Insulin Resistance, Models, Biological, Neovascularization, Physiologic, Obesity, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Sex Characteristics, Waist-Hip Ratio, Body Fat Distribution, Genome-Wide Association Study, Multidisciplinary, Insulin Resistance/genetics, Genome-wide association study, Continental Population Groups/genetics, genetic analysis, heritability, gene cluster, Science::Biological sciences::Human anatomy and physiology [DRNTU], 0302 clinical medicine, high density lipoprotein cholesterol, Models, genetics [Insulin Resistance], histone modification, Age Factor, insulin receptor, 0303 health sciences, Adipocyte, Human/genetics, CARDIOGRAMplusC4D Consortium, ADIPOGENIC DIFFERENTIATION, genetic correlation, body fat, Continental Population Group, priority journal, 5 trisphosphate 3 phosphatase, GEFOS Consortium, meta analysis (topic), Science & Technology - Other Topics, ddc:500, transcription regulation, Adipogenesis/genetics, Single Nucleotide/genetics, Human, medicine.medical_specialty, Waist, phosphatidylinositol 3, European, ta3111, genetic regulation, Article, developmental biology, 03 medical and health sciences, MAGIC Investigators, transcription initiation site, SDG 3 - Good Health and Well-being, Genetic, genomics, GLYCEMIC TRAITS, genetics [Continental Population Groups], Polymorphism, GENOME-WIDE ASSOCIATION, Physiologic, genetics [Adipogenesis], Adipocytes/metabolism, Europe/ethnology, Genome, Human/genetics, Insulin/metabolism, Neovascularization, Physiologic/genetics, Obesity/genetics, Polymorphism, Single Nucleotide/genetics, Quantitative Trait Loci/genetics, Transcription, Genetic/genetics, Genetic/genetics, Adipogenesi, Science & Technology, adiponectin, [ SDV ] Life Sciences [q-bio], vasculotropin, genetics [Quantitative Trait Loci], ta1184, Racial Groups, ta1182, gene mapping, ta3121, triacylglycerol blood level, medicine.disease, Biological, major clinical study, amino acid sequence, metabolism [Insulin], Endocrinology, metabolism [Adipocytes], genetic loci, insulin, body fat, GLGC, International Endogene Consortium, metabolism [Adipose Tissue], Body mass index, HUMAN HEIGHT, Epigenesis, LifeLines Cohort Study, ReproGen Consortium, BIO/12 - BIOCHIMICA CLINICA E BIOLOGIA MOLECOLARE CLINICA, tissue level, Physiologic/genetics, [SDV]Life Sciences [q-bio], Medizin, Adipose tissue, low density lipoprotein cholesterol, PAGE Consortium, COMMON SNPS, angiogenesis, Waist–hip ratio, genetics [Obesity], MESH: Adipocytes/metabolism Adipogenesis/genetics Adipose Tissue/metabolism* Age Factors Body Fat Distribution* Body Mass Index Continental Population Groups/genetics Epigenesis, Genetic Europe/ethnology Female Genome, Human/genetics Genome-Wide Association Study* Humans Insulin/metabolism* Insulin Resistance/genetics Male Models, Biological Neovascularization, Physiologic/genetics Obesity/genetics Polymorphism, Single Nucleotide/genetics Quantitative Trait Loci/genetics* Sex Characteristics Transcription, Genetic/genetics Waist-Hip Ratio, single nucleotide polymorphism, fat, genetic variability, molecular biology, body mass index (BMI), ethnology [Europe], peroxisome proliferator activated receptor, 2. Zero hunger, Genetics, Genome, Single Nucleotide, waist circumference, insulin, phosphatidylinositol 3,4,5 trisphosphate 3 phosphatase, triacylglycerol, vasculotropin, developmental biology, gene expression, genome, numerical model, adipocyte, adipose tissue, body fat distribution, body mass, female, gene locus, gene structure, hip circumference, human, insulin resistance, lipoprotein blood level, male, obesity, protein protein interaction, sex difference, waist hip ratio, Multidisciplinary Sciences, genetics [Transcription, Genetic], genetics [Polymorphism, Single Nucleotide], ADIPOGen Consortium, genetics [Neovascularization, Physiologic], Transcription, SUSCEPTIBILITY LOCI, General Science & Technology, ICBP, 030209 endocrinology & metabolism, Biology, adipocyte, MESH : Adipocytes/metabolism Adipogenesis/genetics Adipose Tissue/metabolism* Age Factors Body Fat Distribution* Body Mass Index Continental Population Groups/genetics Epigenesis, Genetic Europe/ethnology Female Genome, Human/genetics Genome-Wide Association Study* Humans Insulin/metabolism* Insulin Resistance/genetics Male Models, Biological Neovascularization, Physiologic/genetics Obesity/genetics Polymorphism, Single Nucleotide/genetics Quantitative Trait Loci/genetics* Sex Characteristics Transcription, Genetic/genetics Waist-Hip Ratio, MESENCHYMAL STEM-CELLS, GENIE Consortium, SEXUAL-DIMORPHISM, Insulin resistance, Internal medicine, medicine, genetics [Genome, Human], ABDOMINAL ADIPOSITY, Neovascularization, 030304 developmental biology, FALSE DISCOVERY, CKDGen Consortium, Sex Characteristic, MuTHER Consortium, numerical model
Abstract

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P

Published
2015

43. Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins

Author

Postmus, Iris, Trompet, Stella, Deshmukh, Harshal A, Barnes, Michael R, Li, Xiaohui, Warren, Helen R, Chasman, Daniel I, Zhou, Kaixin, Arsenault, Benoit J, Donnelly, Louise A, Wiggins, Kerri L, Avery, Christy L, Griffin, Paula, Feng, QiPing, Taylor, Kent D, Li, Guo, Evans, Daniel S, Smith, Albert V, de Keyser, Catherine E, Johnson, Andrew D, de Craen, Anton JM, Stott, David J, Buckley, Brendan M, Ford, Ian, Westendorp, Rudi GJ, Slagboom, P Eline, Sattar, Naveed, Munroe, Patricia B, Sever, Peter, Poulter, Neil, Stanton, Alice, Shields, Denis C, O'Brien, Eoin, Shaw-Hawkins, Sue, Chen, Y-D Ida, Nickerson, Deborah A, Smith, Joshua D, Dubé, Marie Pierre, Boekholdt, S Matthijs, Hovingh, G Kees, Kastelein, John JP, McKeigue, Paul M, Betteridge, John, Neil, Andrew, Durrington, Paul N, Doney, Alex, Carr, Fiona, Morris, Andrew, McCarthy, Mark I, Groop, Leif, Ahlqvist, Emma, Welcome Trust Case Control Consortium, Bis, Joshua C, Rice, Kenneth, Smith, Nicholas L, Lumley, Thomas, Whitsel, Eric A, Stürmer, Til, Boerwinkle, Eric, Ngwa, Julius S, O'Donnell, Christopher J, Vasan, Ramachandran S, Wei, Wei-Qi, Wilke, Russell A, Liu, Ching-Ti, Sun, Fangui, Guo, Xiuqing, Heckbert, Susan R, Post, Wendy, Sotoodehnia, Nona, Arnold, Alice M, Stafford, Jeanette M, Ding, Jingzhong, Herrington, David M, Kritchevsky, Stephen B, Eiriksdottir, Gudny, Launer, Leonore J, Harris, Tamara B, Chu, Audrey Y, Giulianini, Franco, MacFadyen, Jean G, Barratt, Bryan J, Nyberg, Fredrik, Stricker, Bruno H, Uitterlinden, André G, Hofman, Albert, Rivadeneira, Fernando, Emilsson, Valur, Franco, Oscar H, Ridker, Paul M, Gudnason, Vilmundur, Liu, Yongmei, Denny, Joshua C, Ballantyne, Christie M, Rotter, Jerome I, Adrienne Cupples, L, Psaty, Bruce M, Palmer, Colin NA, Tardif, Jean-Claude, and Colhoun, Helen M

Subjects
Welcome Trust Case Control Consortium, Human Genome, nutritional and metabolic diseases, Single Nucleotide, Atherosclerosis, LDL, Cholesterol, Clinical Research, Pharmacogenetics, Genetics, 2.1 Biological and endogenous factors, Humans, lipids (amino acids, peptides, and proteins), cardiovascular diseases, Aetiology, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Polymorphism, Genome-Wide Association Study
Abstract

Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response.

Published
2014

45. Pharmacogenetic meta-analysis of genome-wide association studies of LDL cholesterol response to statins

Author

de Craen, Anton J. M., Chasman, Daniel I., Poulter, Neil, Postmus, Iris, de Keyser, Catherine E., Stott, David J., Avery, Christy L., Donnelly, Louise A., Barnes, Michael R., Johnson, Andrew D., Deshmukh, Harshal A., Zhou, Kaixin, Buckley, Brendan M., Evans, Daniel S., Li, Guo, Eline Slagboom, P., Wiggins, Kerri L., Sattar, Naveed, Shields, Denis C., Warren, Helen R., Munroe, Patricia B., Taylor, Kent D., Westendorp, Rudi G. J., Sever, Peter, Li, Xiaohui, Trompet, Stella, Arsenault, Benoit J., Feng, QiPing, Smith, Albert V., Ford, Ian, Griffin, Paula, and Stanton, Alice

Subjects
nutritional and metabolic diseases, lipids (amino acids, peptides, and proteins), cardiovascular diseases
Abstract

Statins effectively lower LDL cholesterol levels in large studies and the observed interindividual response variability may be partially explained by genetic variation. Here we perform a pharmacogenetic meta-analysis of genome-wide association studies (GWAS) in studies addressing the LDL cholesterol response to statins, including up to 18,596 statin-treated subjects. We validate the most promising signals in a further 22,318 statin recipients and identify two loci, SORT1/CELSR2/PSRC1 and SLCO1B1, not previously identified in GWAS. Moreover, we confirm the previously described associations with APOE and LPA. Our findings advance the understanding of the pharmacogenetic architecture of statin response. Statins are effectively used to prevent and manage cardiovascular disease, but patient response to these drugs is highly variable. Here, the authors identify two new genes associated with the response of LDL cholesterol to statins and advance our understanding of the genetic basis of drug response.

Published
2014
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46. Discovery and refinement of loci associated with lipid levels

Author

Willer, Cristen J, Schmidt, Ellen M, Sengupta, Sebanti, Peloso, Gina M, Gustafsson, Stefan, Kanoni, Stavroula, Ganna, Andrea, Chen, Jin, Buchkovich, Martin L, Mora, Samia, Beckmann, Jacques S, Bragg-Gresham, Jennifer L, Chang, Hsing-Yi, Demirkan, Ayşe, Den Hertog, Heleen M, Do, Ron, Donnelly, Louise A, Ehret, Georg B, Esko, Tõnu, Feitosa, Mary F, Ferreira, Teresa, Fischer, Krista, Fontanillas, Pierre, Fraser, Ross M, Freitag, Daniel F, Gurdasani, Deepti, Heikkilä, Kauko, Hyppönen, Elina, Isaacs, Aaron, Jackson, Anne U, Johansson, Åsa, Johnson, Toby, Kaakinen, Marika, Kettunen, Johannes, Kleber, Marcus E, Li, Xiaohui, Luan, Jian'an, Lyytikäinen, Leo-Pekka, Magnusson, Patrik KE, Mangino, Massimo, Mihailov, Evelin, Montasser, May E, Müller-Nurasyid, Martina, Nolte, Ilja M, O'Connell, Jeffrey R, Palmer, Cameron D, Perola, Markus, Petersen, Ann-Kristin, Sanna, Serena, Saxena, Richa, Service, Susan K, Shah, Sonia, Shungin, Dmitry, Sidore, Carlo, Song, Ci, Strawbridge, Rona J, Surakka, Ida, Tanaka, Toshiko, Teslovich, Tanya M, Thorleifsson, Gudmar, Van den Herik, Evita G, Voight, Benjamin F, Volcik, Kelly A, Waite, Lindsay L, Wong, Andrew, Wu, Ying, Zhang, Weihua, Absher, Devin, Asiki, Gershim, Barroso, Inês, Been, Latonya F, Bolton, Jennifer L, Bonnycastle, Lori L, Brambilla, Paolo, Burnett, Mary S, Cesana, Giancarlo, Dimitriou, Maria, Doney, Alex SF, Döring, Angela, Elliott, Paul, Epstein, Stephen E, Ingi Eyjolfsson, Gudmundur, Gigante, Bruna, Goodarzi, Mark O, Grallert, Harald, Gravito, Martha L, Groves, Christopher J, Hallmans, Göran, Hartikainen, Anna-Liisa, Hayward, Caroline, Hernandez, Dena, Hicks, Andrew A, Holm, Hilma, Hung, Yi-Jen, Illig, Thomas, Jones, Michelle R, Kaleebu, Pontiano, Kastelein, John JP, Khaw, Kay-Tee, and Kim, Eric

Subjects
Asian Continental Ancestry Group, Genotype, HDL, European Continental Ancestry Group, Black People, Coronary Artery Disease, Cardiovascular, Medical and Health Sciences, White People, LDL, Asian People, Genetics, Humans, 2.1 Biological and endogenous factors, Genetic Predisposition to Disease, Aetiology, Heart Disease - Coronary Heart Disease, Metabolic and endocrine, Triglycerides, African Continental Ancestry Group, Nutrition, Human Genome, Global Lipids Genetics Consortium, Biological Sciences, Atherosclerosis, Lipids, Heart Disease, Cholesterol, lipids (amino acids, peptides, and proteins), Genome-Wide Association Study, Developmental Biology
Abstract

Levels of low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, triglycerides and total cholesterol are heritable, modifiable risk factors for coronary artery disease. To identify new loci and refine known loci influencing these lipids, we examined 188,577 individuals using genome-wide and custom genotyping arrays. We identify and annotate 157 loci associated with lipid levels at P < 5 × 10(-8), including 62 loci not previously associated with lipid levels in humans. Using dense genotyping in individuals of European, East Asian, South Asian and African ancestry, we narrow association signals in 12 loci. We find that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index. Our results demonstrate the value of using genetic data from individuals of diverse ancestry and provide insights into the biological mechanisms regulating blood lipids to guide future genetic, biological and therapeutic research.

Published
2013

47. Common variants associated with plasma triglycerides and risk for coronary artery disease

Author

Do, Ron, Willer, Cristen J, Schmidt, Ellen M, Sengupta, Sebanti, Gao, Chi, Peloso, Gina M, Gustafsson, Stefan, Kanoni, Stavroula, Ganna, Andrea, Chen, Jin, Buchkovich, Martin L, Mora, Samia, Beckmann, Jacques S, Bragg-Gresham, Jennifer L, Chang, Hsing-Yi, Demirkan, Ayşe, Den Hertog, Heleen M, Donnelly, Louise A, Ehret, Georg B, Esko, Tõnu, Feitosa, Mary F, Ferreira, Teresa, Fischer, Krista, Fontanillas, Pierre, Fraser, Ross M, Freitag, Daniel F, Gurdasani, Deepti, Heikkilä, Kauko, Hyppönen, Elina, Isaacs, Aaron, Jackson, Anne U, Johansson, Asa, Johnson, Toby, Kaakinen, Marika, Kettunen, Johannes, Kleber, Marcus E, Li, Xiaohui, Luan, Jian'an, Lyytikäinen, Leo-Pekka, Magnusson, Patrik KE, Mangino, Massimo, Mihailov, Evelin, Montasser, May E, Müller-Nurasyid, Martina, Nolte, Ilja M, O'Connell, Jeffrey R, Palmer, Cameron D, Perola, Markus, Petersen, Ann-Kristin, Sanna, Serena, Saxena, Richa, Service, Susan K, Shah, Sonia, Shungin, Dmitry, Sidore, Carlo, Song, Ci, Strawbridge, Rona J, Surakka, Ida, Tanaka, Toshiko, Teslovich, Tanya M, Thorleifsson, Gudmar, Van den Herik, Evita G, Voight, Benjamin F, Volcik, Kelly A, Waite, Lindsay L, Wong, Andrew, Wu, Ying, Zhang, Weihua, Absher, Devin, Asiki, Gershim, Barroso, Inês, Been, Latonya F, Bolton, Jennifer L, Bonnycastle, Lori L, Brambilla, Paolo, Burnett, Mary S, Cesana, Giancarlo, Dimitriou, Maria, Doney, Alex SF, Döring, Angela, Elliott, Paul, Epstein, Stephen E, Eyjolfsson, Gudmundur Ingi, Gigante, Bruna, Goodarzi, Mark O, Grallert, Harald, Gravito, Martha L, Groves, Christopher J, Hallmans, Göran, Hartikainen, Anna-Liisa, Hayward, Caroline, Hernandez, Dena, Hicks, Andrew A, Holm, Hilma, Hung, Yi-Jen, Illig, Thomas, Jones, Michelle R, Kaleebu, Pontiano, Kastelein, John JP, and Khaw, Kay-Tee

Subjects
HDL, Prevention, Biological Transport, Single Nucleotide, Coronary Artery Disease, Biological Sciences, Cardiovascular, Atherosclerosis, Medical and Health Sciences, LDL, Heart Disease, Cholesterol, Risk Factors, 2.1 Biological and endogenous factors, Humans, lipids (amino acids, peptides, and proteins), Aetiology, Polymorphism, Heart Disease - Coronary Heart Disease, Triglycerides, Developmental Biology
Abstract

Triglycerides are transported in plasma by specific triglyceride-rich lipoproteins; in epidemiological studies, increased triglyceride levels correlate with higher risk for coronary artery disease (CAD). However, it is unclear whether this association reflects causal processes. We used 185 common variants recently mapped for plasma lipids (P < 5 × 10(-8) for each) to examine the role of triglycerides in risk for CAD. First, we highlight loci associated with both low-density lipoprotein cholesterol (LDL-C) and triglyceride levels, and we show that the direction and magnitude of the associations with both traits are factors in determining CAD risk. Second, we consider loci with only a strong association with triglycerides and show that these loci are also associated with CAD. Finally, in a model accounting for effects on LDL-C and/or high-density lipoprotein cholesterol (HDL-C) levels, the strength of a polymorphism's effect on triglyceride levels is correlated with the magnitude of its effect on CAD risk. These results suggest that triglyceride-rich lipoproteins causally influence risk for CAD.

Published
2013

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