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158 results on '"Evangelou, Marina"'

1. Logistic Variational Bayes Revisited

Author

Komodromos, Michael, Evangelou, Marina, and Filippi, Sarah

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Methodology
Abstract

Variational logistic regression is a popular method for approximate Bayesian inference seeing wide-spread use in many areas of machine learning including: Bayesian optimization, reinforcement learning and multi-instance learning to name a few. However, due to the intractability of the Evidence Lower Bound, authors have turned to the use of Monte Carlo, quadrature or bounds to perform inference, methods which are costly or give poor approximations to the true posterior. In this paper we introduce a new bound for the expectation of softplus function and subsequently show how this can be applied to variational logistic regression and Gaussian process classification. Unlike other bounds, our proposal does not rely on extending the variational family, or introducing additional parameters to ensure the bound is tight. In fact, we show that this bound is tighter than the state-of-the-art, and that the resulting variational posterior achieves state-of-the-art performance, whilst being significantly faster to compute than Monte-Carlo methods., Comment: Accepted at the 41st International Conference on Machine Learning

Published
2024

2. Dual feature reduction for the sparse-group lasso and its adaptive variant

Author

Feser, Fabio and Evangelou, Marina

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning
Abstract

The sparse-group lasso performs both variable and group selection, making simultaneous use of the strengths of the lasso and group lasso. It has found widespread use in genetics, a field that regularly involves the analysis of high-dimensional data, due to its sparse-group penalty, which allows it to utilize grouping information. However, the sparse-group lasso can be computationally more expensive than both the lasso and group lasso, due to the added shrinkage complexity, and its additional hyper-parameter that needs tuning. In this paper a novel dual feature reduction method, Dual Feature Reduction (DFR), is presented that uses strong screening rules for the sparse-group lasso and the adaptive sparse-group lasso to reduce their input space before optimization. DFR applies two layers of screening and is based on the dual norms of the sparse-group lasso and adaptive sparse-group lasso. Through synthetic and real numerical studies, it is shown that the proposed feature reduction approach is able to drastically reduce the computational cost in many different scenarios., Comment: 46 pages, 18 figures, 41 tables

Published
2024

3. Strong screening rules for group-based SLOPE models

Author

Feser, Fabio and Evangelou, Marina

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Methodology
Abstract

Tuning the regularization parameter in penalized regression models is an expensive task, requiring multiple models to be fit along a path of parameters. Strong screening rules drastically reduce computational costs by lowering the dimensionality of the input prior to fitting. We develop strong screening rules for group-based Sorted L-One Penalized Estimation (SLOPE) models: Group SLOPE and Sparse-group SLOPE. The developed rules are applicable for the wider family of group-based OWL models, including OSCAR. Our experiments on both synthetic and real data show that the screening rules significantly accelerate the fitting process. The screening rules make it accessible for group SLOPE and sparse-group SLOPE to be applied to high-dimensional datasets, particularly those encountered in genetics., Comment: 31 pages, 18 figures, 10 tables

Published
2024

4. Group Spike and Slab Variational Bayes

Author

Komodromos, Michael, Evangelou, Marina, Filippi, Sarah, and Ray, Kolyan

Subjects
Statistics - Methodology, Statistics - Computation
Abstract

We introduce Group Spike-and-slab Variational Bayes (GSVB), a scalable method for group sparse regression. A fast co-ordinate ascent variational inference (CAVI) algorithm is developed for several common model families including Gaussian, Binomial and Poisson. Theoretical guarantees for our proposed approach are provided by deriving contraction rates for the variational posterior in grouped linear regression. Through extensive numerical studies, we demonstrate that GSVB provides state-of-the-art performance, offering a computationally inexpensive substitute to MCMC, whilst performing comparably or better than existing MAP methods. Additionally, we analyze three real world datasets wherein we highlight the practical utility of our method, demonstrating that GSVB provides parsimonious models with excellent predictive performance, variable selection and uncertainty quantification., Comment: 66 pages, 5 figures, 7 tables

Published
2023

5. Sparse-group SLOPE: adaptive bi-level selection with FDR-control

Author

Feser, Fabio and Evangelou, Marina

Subjects
Statistics - Methodology
Abstract

In this manuscript, a new high-dimensional approach for simultaneous variable and group selection is proposed, called sparse-group SLOPE (SGS). SGS achieves false discovery rate control at both variable and group levels by incorporating the SLOPE model into a sparse-group framework and exploiting grouping information. A proximal algorithm is implemented for fitting SGS that works for both Gaussian and Binomial distributed responses. Through the analysis of both synthetic and real datasets, the proposed SGS approach is found to outperform other existing lasso- and SLOPE-based models for bi-level selection and prediction accuracy. Further, model selection and noise estimation approaches for selecting the tuning parameter of the regularisation model are proposed and explored., Comment: 45 pages, 25 figures, 9 tables

Published
2023

6. Variational Bayes for high-dimensional proportional hazards models with applications within gene expression

Author

Komodromos, Michael, Aboagye, Eric, Evangelou, Marina, Filippi, Sarah, and Ray, Kolyan

Subjects
Statistics - Methodology, Statistics - Machine Learning
Abstract

Few Bayesian methods for analyzing high-dimensional sparse survival data provide scalable variable selection, effect estimation and uncertainty quantification. Such methods often either sacrifice uncertainty quantification by computing maximum a posteriori estimates, or quantify the uncertainty at high (unscalable) computational expense. We bridge this gap and develop an interpretable and scalable Bayesian proportional hazards model for prediction and variable selection, referred to as SVB. Our method, based on a mean-field variational approximation, overcomes the high computational cost of MCMC whilst retaining useful features, providing a posterior distribution for the parameters and offering a natural mechanism for variable selection via posterior inclusion probabilities. The performance of our proposed method is assessed via extensive simulations and compared against other state-of-the-art Bayesian variable selection methods, demonstrating comparable or better performance. Finally, we demonstrate how the proposed method can be used for variable selection on two transcriptomic datasets with censored survival outcomes, and how the uncertainty quantification offered by our method can be used to provide an interpretable assessment of patient risk., Comment: Published in Bioinformatics

Published
2021
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7. S-multi-SNE: Semi-Supervised Classification and Visualisation of Multi-View Data

Author

Rodosthenous, Theodoulos, Shahrezaei, Vahid, and Evangelou, Marina

Subjects
Computer Science - Machine Learning, Computer Science - Human-Computer Interaction, Statistics - Machine Learning
Abstract

An increasing number of multi-view data are being published by studies in several fields. This type of data corresponds to multiple data-views, each representing a different aspect of the same set of samples. We have recently proposed multi-SNE, an extension of t-SNE, that produces a single visualisation of multi-view data. The multi-SNE approach provides low-dimensional embeddings of the samples, produced by being updated iteratively through the different data-views. Here, we further extend multi-SNE to a semi-supervised approach, that classifies unlabelled samples by regarding the labelling information as an extra data-view. We look deeper into the performance, limitations and strengths of multi-SNE and its extension, S-multi-SNE, by applying the two methods on various multi-view datasets with different challenges. We show that by including the labelling information, the projection of the samples improves drastically and it is accompanied by a strong classification performance., Comment: 13 pages; 3 figures; 3 tables

Published
2021

9. Multi-view Data Visualisation via Manifold Learning

Author

Rodosthenous, Theodoulos, Shahrezaei, Vahid, and Evangelou, Marina

Subjects
Statistics - Machine Learning, Computer Science - Machine Learning, Statistics - Computation
Abstract

Non-linear dimensionality reduction can be performed by \textit{manifold learning} approaches, such as Stochastic Neighbour Embedding (SNE), Locally Linear Embedding (LLE) and Isometric Feature Mapping (ISOMAP). These methods aim to produce two or three latent embeddings, primarily to visualise the data in intelligible representations. This manuscript proposes extensions of Student's t-distributed SNE (t-SNE), LLE and ISOMAP, for dimensionality reduction and visualisation of multi-view data. Multi-view data refers to multiple types of data generated from the same samples. The proposed multi-view approaches provide more comprehensible projections of the samples compared to the ones obtained by visualising each data-view separately. Commonly visualisation is used for identifying underlying patterns within the samples. By incorporating the obtained low-dimensional embeddings from the multi-view manifold approaches into the K-means clustering algorithm, it is shown that clusters of the samples are accurately identified. Through the analysis of real and synthetic data the proposed multi-SNE approach is found to have the best performance. We further illustrate the applicability of the multi-SNE approach for the analysis of multi-omics single-cell data, where the aim is to visualise and identify cell heterogeneity and cell types in biological tissues relevant to health and disease., Comment: 39 pages, 20 figures, 9 tables

Published
2021

14. Data from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

Author

Aglago, Elom K., primary, Kim, Andre, primary, Lin, Yi, primary, Qu, Conghui, primary, Evangelou, Marina, primary, Ren, Yu, primary, Morrison, John, primary, Albanes, Demetrius, primary, Arndt, Volker, primary, Barry, Elizabeth L., primary, Baurley, James W., primary, Berndt, Sonja I., primary, Bien, Stephanie A., primary, Bishop, D. Timothy, primary, Bouras, Emmanouil, primary, Brenner, Hermann, primary, Buchanan, Daniel D., primary, Budiarto, Arif, primary, Carreras-Torres, Robert, primary, Casey, Graham, primary, Cenggoro, Tjeng Wawan, primary, Chan, Andrew T., primary, Chang-Claude, Jenny, primary, Chen, Xuechen, primary, Conti, David V., primary, Devall, Matthew, primary, Diez-Obrero, Virginia, primary, Dimou, Niki, primary, Drew, David, primary, Figueiredo, Jane C., primary, Gallinger, Steven, primary, Giles, Graham G., primary, Gruber, Stephen B., primary, Gsur, Andrea, primary, Gunter, Marc J., primary, Hampel, Heather, primary, Harlid, Sophia, primary, Hidaka, Akihisa, primary, Harrison, Tabitha A., primary, Hoffmeister, Michael, primary, Huyghe, Jeroen R., primary, Jenkins, Mark A., primary, Jordahl, Kristina, primary, Joshi, Amit D., primary, Kawaguchi, Eric S., primary, Keku, Temitope O., primary, Kundaje, Anshul, primary, Larsson, Susanna C., primary, Marchand, Loic Le, primary, Lewinger, Juan Pablo, primary, Li, Li, primary, Lynch, Brigid M., primary, Mahesworo, Bharuno, primary, Mandic, Marko, primary, Obón-Santacana, Mireia, primary, Moreno, Victor, primary, Murphy, Neil, primary, Nan, Hongmei, primary, Nassir, Rami, primary, Newcomb, Polly A., primary, Ogino, Shuji, primary, Ose, Jennifer, primary, Pai, Rish K., primary, Palmer, Julie R., primary, Papadimitriou, Nikos, primary, Pardamean, Bens, primary, Peoples, Anita R., primary, Platz, Elizabeth A., primary, Potter, John D., primary, Prentice, Ross L., primary, Rennert, Gad, primary, Ruiz-Narvaez, Edward, primary, Sakoda, Lori C., primary, Scacheri, Peter C., primary, Schmit, Stephanie L., primary, Schoen, Robert E., primary, Shcherbina, Anna, primary, Slattery, Martha L., primary, Stern, Mariana C., primary, Su, Yu-Ru, primary, Tangen, Catherine M., primary, Thibodeau, Stephen N., primary, Thomas, Duncan C., primary, Tian, Yu, primary, Ulrich, Cornelia M., primary, van Duijnhoven, Franzel JB, primary, Van Guelpen, Bethany, primary, Visvanathan, Kala, primary, Vodicka, Pavel, primary, Wang, Jun, primary, White, Emily, primary, Wolk, Alicja, primary, Woods, Michael O., primary, Wu, Anna H., primary, Zemlianskaia, Natalia, primary, Hsu, Li, primary, Gauderman, W. James, primary, Peters, Ulrike, primary, Tsilidis, Konstantinos K., primary, and Campbell, Peter T., primary

Published
2023
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15. Supplementary Data from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

Author

Aglago, Elom K., primary, Kim, Andre, primary, Lin, Yi, primary, Qu, Conghui, primary, Evangelou, Marina, primary, Ren, Yu, primary, Morrison, John, primary, Albanes, Demetrius, primary, Arndt, Volker, primary, Barry, Elizabeth L., primary, Baurley, James W., primary, Berndt, Sonja I., primary, Bien, Stephanie A., primary, Bishop, D. Timothy, primary, Bouras, Emmanouil, primary, Brenner, Hermann, primary, Buchanan, Daniel D., primary, Budiarto, Arif, primary, Carreras-Torres, Robert, primary, Casey, Graham, primary, Cenggoro, Tjeng Wawan, primary, Chan, Andrew T., primary, Chang-Claude, Jenny, primary, Chen, Xuechen, primary, Conti, David V., primary, Devall, Matthew, primary, Diez-Obrero, Virginia, primary, Dimou, Niki, primary, Drew, David, primary, Figueiredo, Jane C., primary, Gallinger, Steven, primary, Giles, Graham G., primary, Gruber, Stephen B., primary, Gsur, Andrea, primary, Gunter, Marc J., primary, Hampel, Heather, primary, Harlid, Sophia, primary, Hidaka, Akihisa, primary, Harrison, Tabitha A., primary, Hoffmeister, Michael, primary, Huyghe, Jeroen R., primary, Jenkins, Mark A., primary, Jordahl, Kristina, primary, Joshi, Amit D., primary, Kawaguchi, Eric S., primary, Keku, Temitope O., primary, Kundaje, Anshul, primary, Larsson, Susanna C., primary, Marchand, Loic Le, primary, Lewinger, Juan Pablo, primary, Li, Li, primary, Lynch, Brigid M., primary, Mahesworo, Bharuno, primary, Mandic, Marko, primary, Obón-Santacana, Mireia, primary, Moreno, Victor, primary, Murphy, Neil, primary, Nan, Hongmei, primary, Nassir, Rami, primary, Newcomb, Polly A., primary, Ogino, Shuji, primary, Ose, Jennifer, primary, Pai, Rish K., primary, Palmer, Julie R., primary, Papadimitriou, Nikos, primary, Pardamean, Bens, primary, Peoples, Anita R., primary, Platz, Elizabeth A., primary, Potter, John D., primary, Prentice, Ross L., primary, Rennert, Gad, primary, Ruiz-Narvaez, Edward, primary, Sakoda, Lori C., primary, Scacheri, Peter C., primary, Schmit, Stephanie L., primary, Schoen, Robert E., primary, Shcherbina, Anna, primary, Slattery, Martha L., primary, Stern, Mariana C., primary, Su, Yu-Ru, primary, Tangen, Catherine M., primary, Thibodeau, Stephen N., primary, Thomas, Duncan C., primary, Tian, Yu, primary, Ulrich, Cornelia M., primary, van Duijnhoven, Franzel JB, primary, Van Guelpen, Bethany, primary, Visvanathan, Kala, primary, Vodicka, Pavel, primary, Wang, Jun, primary, White, Emily, primary, Wolk, Alicja, primary, Woods, Michael O., primary, Wu, Anna H., primary, Zemlianskaia, Natalia, primary, Hsu, Li, primary, Gauderman, W. James, primary, Peters, Ulrike, primary, Tsilidis, Konstantinos K., primary, and Campbell, Peter T., primary

Published
2023
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16. Table 2 from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

Author

Aglago, Elom K., primary, Kim, Andre, primary, Lin, Yi, primary, Qu, Conghui, primary, Evangelou, Marina, primary, Ren, Yu, primary, Morrison, John, primary, Albanes, Demetrius, primary, Arndt, Volker, primary, Barry, Elizabeth L., primary, Baurley, James W., primary, Berndt, Sonja I., primary, Bien, Stephanie A., primary, Bishop, D. Timothy, primary, Bouras, Emmanouil, primary, Brenner, Hermann, primary, Buchanan, Daniel D., primary, Budiarto, Arif, primary, Carreras-Torres, Robert, primary, Casey, Graham, primary, Cenggoro, Tjeng Wawan, primary, Chan, Andrew T., primary, Chang-Claude, Jenny, primary, Chen, Xuechen, primary, Conti, David V., primary, Devall, Matthew, primary, Diez-Obrero, Virginia, primary, Dimou, Niki, primary, Drew, David, primary, Figueiredo, Jane C., primary, Gallinger, Steven, primary, Giles, Graham G., primary, Gruber, Stephen B., primary, Gsur, Andrea, primary, Gunter, Marc J., primary, Hampel, Heather, primary, Harlid, Sophia, primary, Hidaka, Akihisa, primary, Harrison, Tabitha A., primary, Hoffmeister, Michael, primary, Huyghe, Jeroen R., primary, Jenkins, Mark A., primary, Jordahl, Kristina, primary, Joshi, Amit D., primary, Kawaguchi, Eric S., primary, Keku, Temitope O., primary, Kundaje, Anshul, primary, Larsson, Susanna C., primary, Marchand, Loic Le, primary, Lewinger, Juan Pablo, primary, Li, Li, primary, Lynch, Brigid M., primary, Mahesworo, Bharuno, primary, Mandic, Marko, primary, Obón-Santacana, Mireia, primary, Moreno, Victor, primary, Murphy, Neil, primary, Nan, Hongmei, primary, Nassir, Rami, primary, Newcomb, Polly A., primary, Ogino, Shuji, primary, Ose, Jennifer, primary, Pai, Rish K., primary, Palmer, Julie R., primary, Papadimitriou, Nikos, primary, Pardamean, Bens, primary, Peoples, Anita R., primary, Platz, Elizabeth A., primary, Potter, John D., primary, Prentice, Ross L., primary, Rennert, Gad, primary, Ruiz-Narvaez, Edward, primary, Sakoda, Lori C., primary, Scacheri, Peter C., primary, Schmit, Stephanie L., primary, Schoen, Robert E., primary, Shcherbina, Anna, primary, Slattery, Martha L., primary, Stern, Mariana C., primary, Su, Yu-Ru, primary, Tangen, Catherine M., primary, Thibodeau, Stephen N., primary, Thomas, Duncan C., primary, Tian, Yu, primary, Ulrich, Cornelia M., primary, van Duijnhoven, Franzel JB, primary, Van Guelpen, Bethany, primary, Visvanathan, Kala, primary, Vodicka, Pavel, primary, Wang, Jun, primary, White, Emily, primary, Wolk, Alicja, primary, Woods, Michael O., primary, Wu, Anna H., primary, Zemlianskaia, Natalia, primary, Hsu, Li, primary, Gauderman, W. James, primary, Peters, Ulrike, primary, Tsilidis, Konstantinos K., primary, and Campbell, Peter T., primary

Published
2023
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17. Table 1 from A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

Author

Aglago, Elom K., primary, Kim, Andre, primary, Lin, Yi, primary, Qu, Conghui, primary, Evangelou, Marina, primary, Ren, Yu, primary, Morrison, John, primary, Albanes, Demetrius, primary, Arndt, Volker, primary, Barry, Elizabeth L., primary, Baurley, James W., primary, Berndt, Sonja I., primary, Bien, Stephanie A., primary, Bishop, D. Timothy, primary, Bouras, Emmanouil, primary, Brenner, Hermann, primary, Buchanan, Daniel D., primary, Budiarto, Arif, primary, Carreras-Torres, Robert, primary, Casey, Graham, primary, Cenggoro, Tjeng Wawan, primary, Chan, Andrew T., primary, Chang-Claude, Jenny, primary, Chen, Xuechen, primary, Conti, David V., primary, Devall, Matthew, primary, Diez-Obrero, Virginia, primary, Dimou, Niki, primary, Drew, David, primary, Figueiredo, Jane C., primary, Gallinger, Steven, primary, Giles, Graham G., primary, Gruber, Stephen B., primary, Gsur, Andrea, primary, Gunter, Marc J., primary, Hampel, Heather, primary, Harlid, Sophia, primary, Hidaka, Akihisa, primary, Harrison, Tabitha A., primary, Hoffmeister, Michael, primary, Huyghe, Jeroen R., primary, Jenkins, Mark A., primary, Jordahl, Kristina, primary, Joshi, Amit D., primary, Kawaguchi, Eric S., primary, Keku, Temitope O., primary, Kundaje, Anshul, primary, Larsson, Susanna C., primary, Marchand, Loic Le, primary, Lewinger, Juan Pablo, primary, Li, Li, primary, Lynch, Brigid M., primary, Mahesworo, Bharuno, primary, Mandic, Marko, primary, Obón-Santacana, Mireia, primary, Moreno, Victor, primary, Murphy, Neil, primary, Nan, Hongmei, primary, Nassir, Rami, primary, Newcomb, Polly A., primary, Ogino, Shuji, primary, Ose, Jennifer, primary, Pai, Rish K., primary, Palmer, Julie R., primary, Papadimitriou, Nikos, primary, Pardamean, Bens, primary, Peoples, Anita R., primary, Platz, Elizabeth A., primary, Potter, John D., primary, Prentice, Ross L., primary, Rennert, Gad, primary, Ruiz-Narvaez, Edward, primary, Sakoda, Lori C., primary, Scacheri, Peter C., primary, Schmit, Stephanie L., primary, Schoen, Robert E., primary, Shcherbina, Anna, primary, Slattery, Martha L., primary, Stern, Mariana C., primary, Su, Yu-Ru, primary, Tangen, Catherine M., primary, Thibodeau, Stephen N., primary, Thomas, Duncan C., primary, Tian, Yu, primary, Ulrich, Cornelia M., primary, van Duijnhoven, Franzel JB, primary, Van Guelpen, Bethany, primary, Visvanathan, Kala, primary, Vodicka, Pavel, primary, Wang, Jun, primary, White, Emily, primary, Wolk, Alicja, primary, Woods, Michael O., primary, Wu, Anna H., primary, Zemlianskaia, Natalia, primary, Hsu, Li, primary, Gauderman, W. James, primary, Peters, Ulrike, primary, Tsilidis, Konstantinos K., primary, and Campbell, Peter T., primary

Published
2023
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19. A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

Author

Aglago, Elom K., primary, Kim, Andre, additional, Lin, Yi, additional, Qu, Conghui, additional, Evangelou, Marina, additional, Ren, Yu, additional, Morrison, John, additional, Albanes, Demetrius, additional, Arndt, Volker, additional, Barry, Elizabeth L., additional, Baurley, James W., additional, Berndt, Sonja I., additional, Bien, Stephanie A., additional, Bishop, D. Timothy, additional, Bouras, Emmanouil, additional, Brenner, Hermann, additional, Buchanan, Daniel D., additional, Budiarto, Arif, additional, Carreras-Torres, Robert, additional, Casey, Graham, additional, Cenggoro, Tjeng Wawan, additional, Chan, Andrew T., additional, Chang-Claude, Jenny, additional, Chen, Xuechen, additional, Conti, David V., additional, Devall, Matthew, additional, Diez-Obrero, Virginia, additional, Dimou, Niki, additional, Drew, David, additional, Figueiredo, Jane C., additional, Gallinger, Steven, additional, Giles, Graham G., additional, Gruber, Stephen B., additional, Gsur, Andrea, additional, Gunter, Marc J., additional, Hampel, Heather, additional, Harlid, Sophia, additional, Hidaka, Akihisa, additional, Harrison, Tabitha A., additional, Hoffmeister, Michael, additional, Huyghe, Jeroen R., additional, Jenkins, Mark A., additional, Jordahl, Kristina, additional, Joshi, Amit D., additional, Kawaguchi, Eric S., additional, Keku, Temitope O., additional, Kundaje, Anshul, additional, Larsson, Susanna C., additional, Marchand, Loic Le, additional, Lewinger, Juan Pablo, additional, Li, Li, additional, Lynch, Brigid M., additional, Mahesworo, Bharuno, additional, Mandic, Marko, additional, Obón-Santacana, Mireia, additional, Moreno, Victor, additional, Murphy, Neil, additional, Nan, Hongmei, additional, Nassir, Rami, additional, Newcomb, Polly A., additional, Ogino, Shuji, additional, Ose, Jennifer, additional, Pai, Rish K., additional, Palmer, Julie R., additional, Papadimitriou, Nikos, additional, Pardamean, Bens, additional, Peoples, Anita R., additional, Platz, Elizabeth A., additional, Potter, John D., additional, Prentice, Ross L., additional, Rennert, Gad, additional, Ruiz-Narvaez, Edward, additional, Sakoda, Lori C., additional, Scacheri, Peter C., additional, Schmit, Stephanie L., additional, Schoen, Robert E., additional, Shcherbina, Anna, additional, Slattery, Martha L., additional, Stern, Mariana C., additional, Su, Yu-Ru, additional, Tangen, Catherine M., additional, Thibodeau, Stephen N., additional, Thomas, Duncan C., additional, Tian, Yu, additional, Ulrich, Cornelia M., additional, van Duijnhoven, Franzel JB, additional, Van Guelpen, Bethany, additional, Visvanathan, Kala, additional, Vodicka, Pavel, additional, Wang, Jun, additional, White, Emily, additional, Wolk, Alicja, additional, Woods, Michael O., additional, Wu, Anna H., additional, Zemlianskaia, Natalia, additional, Hsu, Li, additional, Gauderman, W. James, additional, Peters, Ulrike, additional, Tsilidis, Konstantinos K., additional, and Campbell, Peter T., additional

Published
2023
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21. Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits

Author

Evangelou, Evangelos, Warren, Helen R., Mosen-Ansorena, David, Mifsud, Borbala, Pazoki, Raha, Gao, He, Ntritsos, Georgios, Dimou, Niki, Cabrera, Claudia P., Karaman, Ibrahim, Ng, Fu Liang, Evangelou, Marina, Witkowska, Katarzyna, Tzanis, Evan, Hellwege, Jacklyn N., Giri, Ayush, Velez Edwards, Digna R., Sun, Yan V., Cho, Kelly, Gaziano, J. Michael, Wilson, Peter W. F., Tsao, Philip S., Kovesdy, Csaba P., Esko, Tonu, Mägi, Reedik, Milani, Lili, Almgren, Peter, Boutin, Thibaud, Debette, Stéphanie, Ding, Jun, Giulianini, Franco, Holliday, Elizabeth G., Jackson, Anne U., Li-Gao, Ruifang, Lin, Wei-Yu, Luan, Jian’an, Mangino, Massimo, Oldmeadow, Christopher, Prins, Bram Peter, Qian, Yong, Sargurupremraj, Muralidharan, Shah, Nabi, Surendran, Praveen, Thériault, Sébastien, Verweij, Niek, Willems, Sara M., Zhao, Jing-Hua, Amouyel, Philippe, Connell, John, de Mutsert, Renée, Doney, Alex S. F., Farrall, Martin, Menni, Cristina, Morris, Andrew D., Noordam, Raymond, Paré, Guillaume, Poulter, Neil R., Shields, Denis C., Stanton, Alice, Thom, Simon, Abecasis, Gonçalo, Amin, Najaf, Arking, Dan E., Ayers, Kristin L., Barbieri, Caterina M., Batini, Chiara, Bis, Joshua C., Blake, Tineka, Bochud, Murielle, Boehnke, Michael, Boerwinkle, Eric, Boomsma, Dorret I., Bottinger, Erwin P., Braund, Peter S., Brumat, Marco, Campbell, Archie, Campbell, Harry, Chakravarti, Aravinda, Chambers, John C., Chauhan, Ganesh, Ciullo, Marina, Cocca, Massimiliano, Collins, Francis, Cordell, Heather J., Davies, Gail, de Borst, Martin H., de Geus, Eco J., Deary, Ian J., Deelen, Joris, Del Greco M., Fabiola, Demirkale, Cumhur Yusuf, Dörr, Marcus, Ehret, Georg B., Elosua, Roberto, Enroth, Stefan, Erzurumluoglu, A. Mesut, Ferreira, Teresa, Frånberg, Mattias, Franco, Oscar H., Gandin, Ilaria, Gasparini, Paolo, Giedraitis, Vilmantas, Gieger, Christian, Girotto, Giorgia, Goel, Anuj, Gow, Alan J., Gudnason, Vilmundur, Guo, Xiuqing, Gyllensten, Ulf, Hamsten, Anders, Harris, Tamara B., Harris, Sarah E., Hartman, Catharina A., Havulinna, Aki S., Hicks, Andrew A., Hofer, Edith, Hofman, Albert, Hottenga, Jouke-Jan, Huffman, Jennifer E., Hwang, Shih-Jen, Ingelsson, Erik, James, Alan, Jansen, Rick, Jarvelin, Marjo-Riitta, Joehanes, Roby, Johansson, Åsa, Johnson, Andrew D., Joshi, Peter K., Jousilahti, Pekka, Jukema, J. Wouter, Jula, Antti, Kähönen, Mika, Kathiresan, Sekar, Keavney, Bernard D., Khaw, Kay-Tee, Knekt, Paul, Knight, Joanne, Kolcic, Ivana, Kooner, Jaspal S., Koskinen, Seppo, Kristiansson, Kati, Kutalik, Zoltan, Laan, Maris, Larson, Marty, Launer, Lenore J., Lehne, Benjamin, Lehtimäki, Terho, Liewald, David C. M., Lin, Li, Lind, Lars, Lindgren, Cecilia M., Liu, YongMei, Loos, Ruth J. F., Lopez, Lorna M., Lu, Yingchang, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Mamasoula, Chrysovalanto, Marrugat, Jaume, Marten, Jonathan, Milaneschi, Yuri, Morgan, Anna, Morris, Andrew P., Morrison, Alanna C., Munson, Peter J., Nalls, Mike A., Nandakumar, Priyanka, Nelson, Christopher P., Niiranen, Teemu, Nolte, Ilja M., Nutile, Teresa, Oldehinkel, Albertine J., Oostra, Ben A., O’Reilly, Paul F., Org, Elin, Padmanabhan, Sandosh, Palmas, Walter, Palotie, Aarno, Pattie, Alison, Penninx, Brenda W. J. H., Perola, Markus, Peters, Annette, Polasek, Ozren, Pramstaller, Peter P., Nguyen, Quang Tri, Raitakari, Olli T., Ren, Meixia, Rettig, Rainer, Rice, Kenneth, Ridker, Paul M., Ried, Janina S., Riese, Harriëtte, Ripatti, Samuli, Robino, Antonietta, Rose, Lynda M., Rotter, Jerome I., Rudan, Igor, Ruggiero, Daniela, Saba, Yasaman, Sala, Cinzia F., Salomaa, Veikko, Samani, Nilesh J., Sarin, Antti-Pekka, Schmidt, Reinhold, Schmidt, Helena, Shrine, Nick, Siscovick, David, Smith, Albert V., Snieder, Harold, Sõber, Siim, Sorice, Rossella, Starr, John M., Stott, David J., Strachan, David P., Strawbridge, Rona J., Sundström, Johan, Swertz, Morris A., Taylor, Kent D., Teumer, Alexander, Tobin, Martin D., Tomaszewski, Maciej, Toniolo, Daniela, Traglia, Michela, Trompet, Stella, Tuomilehto, Jaakko, Tzourio, Christophe, Uitterlinden, André G., Vaez, Ahmad, van der Most, Peter J., van Duijn, Cornelia M., Vergnaud, Anne-Claire, Verwoert, Germaine C., Vitart, Veronique, Völker, Uwe, Vollenweider, Peter, Vuckovic, Dragana, Watkins, Hugh, Wild, Sarah H., Willemsen, Gonneke, Wilson, James F., Wright, Alan F., Yao, Jie, Zemunik, Tatijana, Zhang, Weihua, Attia, John R., Butterworth, Adam S., Chasman, Daniel I., Conen, David, Cucca, Francesco, Danesh, John, Hayward, Caroline, Howson, Joanna M. M., Laakso, Markku, Lakatta, Edward G., Langenberg, Claudia, Melander, Olle, Mook-Kanamori, Dennis O., Palmer, Colin N. A., Risch, Lorenz, Scott, Robert A., Scott, Rodney J., Sever, Peter, Spector, Tim D., van der Harst, Pim, Wareham, Nicholas J., Zeggini, Eleftheria, Levy, Daniel, Munroe, Patricia B., Newton-Cheh, Christopher, Brown, Morris J., Metspalu, Andres, Hung, Adriana M., O’Donnell, Christopher J., Edwards, Todd L., Psaty, Bruce M., Tzoulaki, Ioanna, Barnes, Michael R., Wain, Louise V., Elliott, Paul, Caulfield, Mark J., and the Million Veteran Program

Published
2018
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23. A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk

Author

Aglago, Elom K., Kim, Andre, Lin, Yi, Qu, Conghui, Evangelou, Marina, Ren, Yu, Morrison, John, Albanes, Demetrius, Arndt, Volker, Barry, Elizabeth L., Baurley, James W., Berndt, Sonja I., Bien, Stephanie A., Bishop, D Timothy, Bouras, Emmanouil, Brenner, Hermann, Buchanan, Daniel D., Budiarto, Arif, Carreras-Torres, Robert, Casey, Graham, Cenggoro, Tjeng Wawan, Chan, Andrew T., Chang-Claude, Jenny, Chen, Xuechen, Conti, David V., Devall, Matthew, Diez-Obrero, Virginia, Dimou, Niki, Drew, David, Figueiredo, Jane C., Gallinger, Steven, Giles, Graham G., Gruber, Stephen B., Gsur, Andrea, Gunter, Marc J., Hampel, Heather, Harlid, Sophia, Hidaka, Akihisa, Harrison, Tabitha A., Hoffmeister, Michael, Huyghe, Jeroen R., Jenkins, Mark A., Jordahl, Kristina, Joshi, Amit D., Kawaguchi, Eric S., Keku, Temitope O., Kundaje, Anshul, Larsson, Susanna C., Marchand, Loic Le, Lewinger, Juan Pablo, Li, Li, Lynch, Brigid M., Mahesworo, Bharuno, Mandic, Marko, Obón-Santacana, Mireia, Moreno, Victor, Murphy, Neil, Nan, Hongmei, Nassir, Rami, Newcomb, Polly A., Ogino, Shuji, Ose, Jennifer, Pai, Rish K., Palmer, Julie R., Papadimitriou, Nikos, Pardamean, Bens, Peoples, Anita R., Platz, Elizabeth A., Potter, John D., Prentice, Ross L., Rennert, Gad, Ruiz-Narvaez, Edward, Sakoda, Lori C., Scacheri, Peter C., Schmit, Stephanie L., Schoen, Robert E., Shcherbina, Anna, Slattery, Martha L., Stern, Mariana C., Su, Yu-Ru, Tangen, Catherine M., Thibodeau, Stephen N., Thomas, Duncan C., Tian, Yu, Ulrich, Cornelia M., van Duijnhoven, Franzel Jb, van Guelpen, Bethany, Visvanathan, Kala, Vodicka, Pavel, Wang, Jun, White, Emily, Wolk, Alicja, Woods, Michael O., Wu, Anna H., Zemlianskaia, Natalia, Hsu, Li, Gauderman, W James, Peters, Ulrike, Tsilidis, Konstantinos K., Campbell, Peter T., Aglago, Elom K., Kim, Andre, Lin, Yi, Qu, Conghui, Evangelou, Marina, Ren, Yu, Morrison, John, Albanes, Demetrius, Arndt, Volker, Barry, Elizabeth L., Baurley, James W., Berndt, Sonja I., Bien, Stephanie A., Bishop, D Timothy, Bouras, Emmanouil, Brenner, Hermann, Buchanan, Daniel D., Budiarto, Arif, Carreras-Torres, Robert, Casey, Graham, Cenggoro, Tjeng Wawan, Chan, Andrew T., Chang-Claude, Jenny, Chen, Xuechen, Conti, David V., Devall, Matthew, Diez-Obrero, Virginia, Dimou, Niki, Drew, David, Figueiredo, Jane C., Gallinger, Steven, Giles, Graham G., Gruber, Stephen B., Gsur, Andrea, Gunter, Marc J., Hampel, Heather, Harlid, Sophia, Hidaka, Akihisa, Harrison, Tabitha A., Hoffmeister, Michael, Huyghe, Jeroen R., Jenkins, Mark A., Jordahl, Kristina, Joshi, Amit D., Kawaguchi, Eric S., Keku, Temitope O., Kundaje, Anshul, Larsson, Susanna C., Marchand, Loic Le, Lewinger, Juan Pablo, Li, Li, Lynch, Brigid M., Mahesworo, Bharuno, Mandic, Marko, Obón-Santacana, Mireia, Moreno, Victor, Murphy, Neil, Nan, Hongmei, Nassir, Rami, Newcomb, Polly A., Ogino, Shuji, Ose, Jennifer, Pai, Rish K., Palmer, Julie R., Papadimitriou, Nikos, Pardamean, Bens, Peoples, Anita R., Platz, Elizabeth A., Potter, John D., Prentice, Ross L., Rennert, Gad, Ruiz-Narvaez, Edward, Sakoda, Lori C., Scacheri, Peter C., Schmit, Stephanie L., Schoen, Robert E., Shcherbina, Anna, Slattery, Martha L., Stern, Mariana C., Su, Yu-Ru, Tangen, Catherine M., Thibodeau, Stephen N., Thomas, Duncan C., Tian, Yu, Ulrich, Cornelia M., van Duijnhoven, Franzel Jb, van Guelpen, Bethany, Visvanathan, Kala, Vodicka, Pavel, Wang, Jun, White, Emily, Wolk, Alicja, Woods, Michael O., Wu, Anna H., Zemlianskaia, Natalia, Hsu, Li, Gauderman, W James, Peters, Ulrike, Tsilidis, Konstantinos K., and Campbell, Peter T.

Abstract

Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Gene-environment interactions (G × E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G × E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G × E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G × E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant G×BMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer. SIGNIFICANCE: This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal cancer risk, suggesting potential implications for precision prevention strategies.

Published
2023
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24. Phenome-wide association study on miRNA-related sequence variants:the UK Biobank

Author

Mustafa, Rima, Ghanbari, Mohsen, Karhunen, Ville, Evangelou, Marina, Dehghan, Abbas, Mustafa, Rima, Ghanbari, Mohsen, Karhunen, Ville, Evangelou, Marina, and Dehghan, Abbas

Abstract

BACKGROUND: Genetic variants in the coding region could directly affect the structure and expression levels of genes and proteins. However, the importance of variants in the non-coding region, such as microRNAs (miRNAs), remain to be elucidated. Genetic variants in miRNA-related sequences could affect their biogenesis or functionality and ultimately affect disease risk. Yet, their implications and pleiotropic effects on many clinical conditions remain unknown. METHODS: Here, we utilised genotyping and hospital records data in the UK Biobank (N = 423,419) to investigate associations between 346 genetic variants in miRNA-related sequences and a wide range of clinical diagnoses through phenome-wide association studies. Further, we tested whether changes in blood miRNA expression levels could affect disease risk through colocalisation and Mendelian randomisation analysis. RESULTS: We identified 122 associations for six variants in the seed region of miRNAs, nine variants in the mature region of miRNAs, and 27 variants in the precursor miRNAs. These included associations with hypertension, dyslipidaemia, immune-related disorders, and others. Nineteen miRNAs were associated with multiple diagnoses, with six of them associated with multiple disease categories. The strongest association was reported between rs4285314 in the precursor of miR-3135b and celiac disease risk (odds ratio (OR) per effect allele increase = 0.37, P = 1.8 × 10-162). Colocalisation and Mendelian randomisation analysis highlighted potential causal role of miR-6891-3p in dyslipidaemia. CONCLUSIONS: Our study demonstrates the pleiotropic effect of miRNAs and offers insights to their possible clinical importance.

Published
2023

25. An atlas of genetic regulation and disease associations of microRNAs

Author

Mustafa, Rima, primary, Mens, Michelle M.J., additional, van Hilten, Arno, additional, Huang, Jian, additional, Roshchupkin, Gennady, additional, Huan, Tianxiao, additional, Broer, Linda, additional, Elliott, Paul, additional, Levy, Daniel, additional, Ikram, M. Arfan, additional, Evangelou, Marina, additional, Dehghan, Abbas, additional, and Ghanbari, Mohsen, additional

Published
2022
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26. An atlas of genetic regulation and disease associations of microRNAs

Author

Ghanbari, Mohsen, primary, Mustafa, Rima, additional, Mens, Michelle, additional, Hilten, Arno van, additional, Huang, Jian, additional, Roshchupkin, Gennady, additional, Huan, Tianxiao, additional, Broer, Linda, additional, Elliott, Paul, additional, Levy, Daniel, additional, Ikram, M. Arfan, additional, Evangelou, Marina, additional, and Dehghan, Abbas, additional

Published
2022
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31. Higher thyrotropin leads to unfavorable lipid profile and somewhat higher cardiovascular disease risk:evidence from multi-cohort Mendelian randomization and metabolomic profiling

Author

van Vliet, Nicolien A., Bos, Maxime M., Thesing, Carisha S., Chaker, Layal, Pietzner, Maik, Houtman, Evelyn, Neville, Matt J., Li-Gao, Ruifang, Trompet, Stella, Mustafa, Rima, Ahmadizar, Fariba, Beekman, Marian, Bot, Mariska, Budde, Kathrin, Christodoulides, Constantinos, Dehghan, Abbas, Delles, Christian, Elliott, Paul, Evangelou, Marina, Gao, He, Ghanbari, Mohsen, van Herwaarden, Antonius E., Ikram, M. Arfan, Jaeger, Martin, Jukema, J. Wouter, Karaman, Ibrahim, Karpe, Fredrik, Kloppenburg, Margreet, Meessen, Jennifer M.T.A., Meulenbelt, Ingrid, Milaneschi, Yuri, Mooijaart, Simon P., Mook-Kanamori, Dennis O., Netea, Mihai G., Netea-Maier, Romana T., Peeters, Robin P., Penninx, Brenda W.J.H., Sattar, Naveed, Slagboom, P. Eline, Suchiman, H. Eka D., Völzke, Henry, Willems van Dijk, Ko, Noordam, Raymond, van Heemst, Diana, van Vliet, Nicolien A., Bos, Maxime M., Thesing, Carisha S., Chaker, Layal, Pietzner, Maik, Houtman, Evelyn, Neville, Matt J., Li-Gao, Ruifang, Trompet, Stella, Mustafa, Rima, Ahmadizar, Fariba, Beekman, Marian, Bot, Mariska, Budde, Kathrin, Christodoulides, Constantinos, Dehghan, Abbas, Delles, Christian, Elliott, Paul, Evangelou, Marina, Gao, He, Ghanbari, Mohsen, van Herwaarden, Antonius E., Ikram, M. Arfan, Jaeger, Martin, Jukema, J. Wouter, Karaman, Ibrahim, Karpe, Fredrik, Kloppenburg, Margreet, Meessen, Jennifer M.T.A., Meulenbelt, Ingrid, Milaneschi, Yuri, Mooijaart, Simon P., Mook-Kanamori, Dennis O., Netea, Mihai G., Netea-Maier, Romana T., Peeters, Robin P., Penninx, Brenda W.J.H., Sattar, Naveed, Slagboom, P. Eline, Suchiman, H. Eka D., Völzke, Henry, Willems van Dijk, Ko, Noordam, Raymond, and van Heemst, Diana

Abstract

Background: Observational studies suggest interconnections between thyroid status, metabolism, and risk of coronary artery disease (CAD), but causality remains to be proven. The present study aimed to investigate the potential causal relationship between thyroid status and cardiovascular disease and to characterize the metabolomic profile associated with thyroid status. Methods: Multi-cohort two-sample Mendelian randomization (MR) was performed utilizing genome-wide significant variants as instruments for standardized thyrotropin (TSH) and free thyroxine (fT4) within the reference range. Associations between TSH and fT4 and metabolic profile were investigated in a two-stage manner: associations between TSH and fT4 and the full panel of 161 metabolomic markers were first assessed hypothesis-free, then directional consistency was assessed through Mendelian randomization, another metabolic profile platform, and in individuals with biochemically defined thyroid dysfunction. Results: Circulating TSH was associated with 52/161 metabolomic markers, and fT4 levels were associated with 21/161 metabolomic markers among 9432 euthyroid individuals (median age varied from 23.0 to 75.4 years, 54.5% women). Positive associations between circulating TSH levels and concentrations of very low-density lipoprotein subclasses and components, triglycerides, and triglyceride content of lipoproteins were directionally consistent across the multivariable regression, MR, metabolomic platforms, and for individuals with hypo- and hyperthyroidism. Associations with fT4 levels inversely reflected those observed with TSH. Among 91,810 CAD cases and 656,091 controls of European ancestry, per 1-SD increase of genetically determined TSH concentration risk of CAD increased slightly, but not significantly, with an OR of 1.03 (95% CI 0.99–1.07; p value 0.16), whereas higher genetically determined fT4 levels were not associated with CAD risk (OR 1.00 per SD increase of fT4; 95% CI 0.96–1.04; p value

Published
2021

35. Higher thyrotropin leads to unfavorable lipid profile and somewhat higher cardiovascular disease risk: evidence from multi-cohort Mendelian randomization and metabolomic profiling.

Author

van Vliet, Nicolien A., Bos, Maxime M., Thesing, Carisha S., Chaker, Layal, Pietzner, Maik, Houtman, Evelyn, Neville, Matt J., Li-Gao, Ruifang, Trompet, Stella, Mustafa, Rima, Ahmadizar, Fariba, Beekman, Marian, Bot, Mariska, Budde, Kathrin, Christodoulides, Constantinos, Dehghan, Abbas, Delles, Christian, Elliott, Paul, Evangelou, Marina, and Gao, He

Subjects
THYROID diseases, CARDIOVASCULAR diseases, CARDIOVASCULAR diseases risk factors, CORONARY artery disease, METABOLOMICS, THYROTROPIN, LIPIDS
Abstract

Background: Observational studies suggest interconnections between thyroid status, metabolism, and risk of coronary artery disease (CAD), but causality remains to be proven. The present study aimed to investigate the potential causal relationship between thyroid status and cardiovascular disease and to characterize the metabolomic profile associated with thyroid status.Methods: Multi-cohort two-sample Mendelian randomization (MR) was performed utilizing genome-wide significant variants as instruments for standardized thyrotropin (TSH) and free thyroxine (fT4) within the reference range. Associations between TSH and fT4 and metabolic profile were investigated in a two-stage manner: associations between TSH and fT4 and the full panel of 161 metabolomic markers were first assessed hypothesis-free, then directional consistency was assessed through Mendelian randomization, another metabolic profile platform, and in individuals with biochemically defined thyroid dysfunction.Results: Circulating TSH was associated with 52/161 metabolomic markers, and fT4 levels were associated with 21/161 metabolomic markers among 9432 euthyroid individuals (median age varied from 23.0 to 75.4 years, 54.5% women). Positive associations between circulating TSH levels and concentrations of very low-density lipoprotein subclasses and components, triglycerides, and triglyceride content of lipoproteins were directionally consistent across the multivariable regression, MR, metabolomic platforms, and for individuals with hypo- and hyperthyroidism. Associations with fT4 levels inversely reflected those observed with TSH. Among 91,810 CAD cases and 656,091 controls of European ancestry, per 1-SD increase of genetically determined TSH concentration risk of CAD increased slightly, but not significantly, with an OR of 1.03 (95% CI 0.99-1.07; p value 0.16), whereas higher genetically determined fT4 levels were not associated with CAD risk (OR 1.00 per SD increase of fT4; 95% CI 0.96-1.04; p value 0.59).Conclusions: Lower thyroid status leads to an unfavorable lipid profile and a somewhat increased cardiovascular disease risk. [ABSTRACT FROM AUTHOR]

Published
2021
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36. Regulatory T Cell Responses in Participants with Type 1 Diabetes after a Single Dose of Interleukin-2: A Non-Randomised, Open Label, Adaptive Dose-Finding Trial

Author

Todd, John A., Evangelou, Marina, Cutler, Antony J., Pekalski, Marcin L., Walker, Neil M., Stevens, Helen E., Porter, Linsey, Smyth, Deborah J., Rainbow, Daniel B., Ferreira, Ricardo C., Esposito, Laura, Hunter, Kara M. D., Loudon, Kevin, Irons, Kathryn, Yang, Jennie H., Bell, Charles J. M., Schuilenburg, Helen, Heywood, James, Challis, Ben, Neupane, Sankalpa, Clarke, Pamela, Coleman, Gillian, Dawson, Sarah, Goymer, Donna, Anselmiova, Katerina, Kennet, Jane, Brown, Judy, Caddy, Sarah L., Lu, Jia, Greatorex, Jane, Goodfellow, Ian, Wallace, Chris, Tree, Tim I., Evans, Mark, Mander, Adrian P., Bond, Simon, Wicker, Linda S., and Waldron-Lynch, Frank

Subjects
Immunotherapy -- Analysis -- Health aspects -- Research, Interleukin-2 -- Physiological aspects -- Genetic aspects -- Research, Type 1 diabetes -- Analysis -- Health aspects -- Genetic aspects -- Care and treatment -- Research, T cells -- Analysis -- Health aspects -- Physiological aspects -- Genetic aspects -- Research, Biological sciences
Abstract

Background Interleukin-2 (IL-2) has an essential role in the expansion and function of CD4.sup.+ regulatory T cells (Tregs). Tregs reduce tissue damage by limiting the immune response following infection and regulate autoreactive CD4.sup.+ effector T cells (Teffs) to prevent autoimmune diseases, such as type 1 diabetes (T1D). Genetic susceptibility to T1D causes alterations in the IL-2 pathway, a finding that supports Tregs as a cellular therapeutic target. Aldesleukin (Proleukin; recombinant human IL-2), which is administered at high doses to activate the immune system in cancer immunotherapy, is now being repositioned to treat inflammatory and autoimmune disorders at lower doses by targeting Tregs. Methods and Findings To define the aldesleukin dose response for Tregs and to find doses that increase Tregs physiologically for treatment of T1D, a statistical and systematic approach was taken by analysing the pharmacokinetics and pharmacodynamics of single doses of subcutaneous aldesleukin in the Adaptive Study of IL-2 Dose on Regulatory T Cells in Type 1 Diabetes (DILT1D), a single centre, non-randomised, open label, adaptive dose-finding trial with 40 adult participants with recently diagnosed T1D. The primary endpoint was the maximum percentage increase in Tregs (defined as CD3.sup.+ CD4.sup.+ CD25.sup.high CD127.sup.low) from the baseline frequency in each participant measured over the 7 d following treatment. There was an initial learning phase with five pairs of participants, each pair receiving one of five pre-assigned single doses from 0.04 x 10.sup.6 to 1.5 x 10.sup.6 IU/m.sup.2, in order to model the dose-response curve. Results from each participant were then incorporated into interim statistical modelling to target the two doses most likely to induce 10% and 20% increases in Treg frequencies. Primary analysis of the evaluable population (n = 39) found that the optimal doses of aldesleukin to induce 10% and 20% increases in Tregs were 0.101 x 10.sup.6 IU/m.sup.2 (standard error [SE] = 0.078, 95% CI = -0.052, 0.254) and 0.497 x 10.sup.6 IU/m.sup.2 (SE = 0.092, 95% CI = 0.316, 0.678), respectively. On analysis of secondary outcomes, using a highly sensitive IL-2 assay, the observed plasma concentrations of the drug at 90 min exceeded the hypothetical Treg-specific therapeutic window determined in vitro (0.015-0.24 IU/ml), even at the lowest doses (0.040 x 10.sup.6 and 0.045 x 10.sup.6 IU/m.sup.2) administered. A rapid decrease in Treg frequency in the circulation was observed at 90 min and at day 1, which was dose dependent (mean decrease 11.6%, SE = 2.3%, range 10.0%-48.2%, n = 37), rebounding at day 2 and increasing to frequencies above baseline over 7 d. Teffs, natural killer cells, and eosinophils also responded, with their frequencies rapidly and dose-dependently decreased in the blood, then returning to, or exceeding, pretreatment levels. Furthermore, there was a dose-dependent down modulation of one of the two signalling subunits of the IL-2 receptor, the [beta] chain (CD122) (mean decrease = 58.0%, SE = 2.8%, range 9.8%-85.5%, n = 33), on Tregs and a reduction in their sensitivity to aldesleukin at 90 min and day 1 and 2 post-treatment. Due to blood volume requirements as well as ethical and practical considerations, the study was limited to adults and to analysis of peripheral blood only. Conclusions The DILT1D trial results, most notably the early altered trafficking and desensitisation of Tregs induced by a single ultra-low dose of aldesleukin that resolves within 2-3 d, inform the design of the next trial to determine a repeat dosing regimen aimed at establishing a steady-state Treg frequency increase of 20%-50%, with the eventual goal of preventing T1D. Trial Registration ISRCTN Registry ISRCTN27852285; ClinicalTrials.gov NCT01827735, Author(s): John A. Todd 1,*, Marina Evangelou 2, Antony J. Cutler 1, Marcin L. Pekalski 1, Neil M. Walker 1, Helen E. Stevens 1, Linsey Porter 1, Deborah J. Smyth [...]

Published
2016
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37. Genetic analysis of over one million people identifies 535 novel loci for blood pressure

Author

Evangelou, Evangelos, Warren, Helen R, Mosen-Ansorena, David, Mifsud, Borbala, Pazoki, Raha, Gao, He, Ntritsos, Georgios, Dimou, Niki, Cabrera, Claudia P, Karaman, Ibrahim, Ng, Fu Liang, Evangelou, Marina, Witkowska, Katarzyna, Tzanis, Evan, Hellwege, Jacklyn N, Giri, Ayush, Edwards, Jacklyn N Hellwege, Sun, Yan V, Cho, Kelly, Gaziano, J Michael, Wilson, Peter WF, Tsao, Philip S, Kovesdy, Csaba P, Esko, Tonu, Magi, Reedik, Milani, Lili, Almgren, Peter, Levy, Daniel, Munroe, Patricia B, Newton-Cheh, Christopher, Brown, Morris J, Metspalu, Andres, Hung, Adriana M, O'Donnell, Christopher, Edwards, Todd L, Psaty, Bruce M, Tzoulaki, Ioanna, Barnes, Michael R, Wain, Louise V, Elliott, Paul, Caulfield, Mark J, and Apollo - University of Cambridge Repository

Subjects
Adult, Aged, 80 and over, Male, Quantitative Trait Loci, Blood Pressure, Middle Aged, Polymorphism, Single Nucleotide, Genetics, Population, Cardiovascular Diseases, Genetic Loci, Risk Factors, Hypertension, Human Umbilical Vein Endothelial Cells, Humans, Female, Genetic Predisposition to Disease, Genetic Testing, Life Style, Cells, Cultured, Aged, Genome-Wide Association Study
Abstract

High blood pressure is the foremost heritable global risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits to date (systolic, diastolic, pulse pressure) in over one million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also reveal shared loci influencing lifestyle exposures. Our findings offer the potential for a precision medicine strategy for future cardiovascular disease prevention.

Published
2018

41. A Method for Gene-Based Pathway Analysis Using Genomewide Association Study Summary Statistics Reveals Nine New Type 1 Diabetes Associations

Author

Evangelou, Marina, Smyth, Deborah J, Fortune, Mary D, Burren, Oliver S, Walker, Neil M, Guo, Hui, Onengut-Gumuscu, Suna, Chen, Wei-Min, Concannon, Patrick, Rich, Stephen S, Todd, John A, Wallace, Chris, Fortune, Mary [0000-0002-6006-4343], Burren, Oliver [0000-0002-3388-5760], Wallace, Chris [0000-0001-9755-1703], and Apollo - University of Cambridge Repository

Subjects
meta-analysis, Diabetes Mellitus, Type 1, Genotype, genomewide association data, nutritional and metabolic diseases, Humans, Reproducibility of Results, Polymorphism, Single Nucleotide, Research Articles, pathway analysis, Genome-Wide Association Study
Abstract

Pathway analysis can complement point-wise single nucleotide polymorphism (SNP) analysis in exploring genomewide association study (GWAS) data to identify specific disease-associated genes that can be candidate causal genes. We propose a straightforward methodology that can be used for conducting a gene-based pathway analysis using summary GWAS statistics in combination with widely available reference genotype data. We used this method to perform a gene-based pathway analysis of a type 1 diabetes (T1D) meta-analysis GWAS (of 7,514 cases and 9,045 controls). An important feature of the conducted analysis is the removal of the major histocompatibility complex gene region, the major genetic risk factor for T1D. Thirty-one of the 1,583 (2%) tested pathways were identified to be enriched for association with T1D at a 5% false discovery rate. We analyzed these 31 pathways and their genes to identify SNPs in or near these pathway genes that showed potentially novel association with T1D and attempted to replicate the association of 22 SNPs in additional samples. Replication P-values were skewed (P=9.85×10-11) with 12 of the 22 SNPs showing P

Published
2014

42. Investigating gene- and pathway-environment interaction analysis approaches

Author

Broc, Camilo, Evangelou, Marina, Guenel, Pascal, Truong, Therese, Liquet, Benoit, Broc, Camilo, Evangelou, Marina, Guenel, Pascal, Truong, Therese, and Liquet, Benoit

Abstract

Free to read on publisher website Pathway analysis can increase power to detect associations with a gene or a pathway by combining several signals at the single nucleotide polymorphism (SNP)-level into a single test. In this work, we propose to extend two well-known self-contained methods, the Fisher’s method (FM) and the Adaptive Rank Truncated Product (ARTP) method to the analysis of gene-environment (GxE) interaction at the gene and pathway-level. It has been previously suggested that the permutation procedures that are usually used to derive the significance of these tests are not appropriate for the analysis of GxE interaction and should be replaced by a bootstrap approach. We analyse and compare the performance of the extension of FM and ARTP using the permutation and the parametric bootstrap procedure in simulation studies. We illustrate its application by analysing the interaction between night work and circadian gene polymorphisms in the risk of breast cancer in a case-control study. The ARTP method, adapted for both gene- and pathway-environment interactions, gives promising results and has been wrapped to the R package PIGE available on the CRAN.

Published
2018

43. Genetic analysis of over one million people identifies 535 new loci associated with blood pressure traits

Author

Evangelou, Evangelos, Warren, Helen R., Mosen-Ansorena, David, Mifsud, Borbala, Pazoki, Raha, Gao, He, Ntritsos, Georgios, Dimou, Niki, Cabrera, Claudia, Karaman, Ibrahim, Ng, Fu Liang, Evangelou, Marina, Witkowska, Katarzyna, Tzanis, Evan, Hellwege, Jacklyn, Giri, Ayush, Edwards, Digna R. Velez, Sun, Yan V., Cho, Kelly, Gaziano, J. Michael, Wilson, Peter W.F., Tsao, Philip S., Kovesdy, Csaba P., Esko, Tonu, Magi, Reedik, Milani, Lili, Almgren, Peter, Boutin, Thibaud, Debette, Stephanie, Ding, Jun, Giulianini, Franco, Holliday, Elizabeth G., Jackson, Anne U., Li-Gao, Ruifang, Lin, Wei-Yu, Luan, Jian'an, Mangino, Massimo, Oldmeadow, Christopher, Prins, Bram Peter, Qian, Yong, Sargurupremraj, Muralidharan, Shah, Nabi, Surendran, Praveen, Theriault, Sebastien, Verweij, Niek, Willems, Sara M., Zhao, Jing-Hua, Amouyel, Phillippe, Connell, John, de Mutsert, Renee, Doney, Alex S.F., Farrall, Martin, Menni, Cristina, Morris, Andrew D., Noordam, Raymond, Pare, Guillaume, Poulter, Neil R., Shields, Denis C., Stanton, Alice, Thom, Simon, Abecasis, Gonçalo, Amin, Najaf, Arking, Dan E., Ayers, Kristin L., Barbieri, Caterina M., Batini, Chiara, Bis, Joshua C., Blake, Tineka, Bochud, Murielle, Boehnke, Michael, Boerwinkle, Eric, Boomsma, Dorret I., Bottinger, Erwin P., Braund, Peter S., Brumat, Marco, Campbell, Archie, Campbell, Harry, Chakravarti, Aavinda, Chambers, John C., Chauhan, Ganesh, Ciullo, Marina, Cocca, Massimiliano, Collins, Francis, Cordell, Heather J., Davies, Gail, de Borst, Martin H., de Geus, Eco J., Deary, Ian J., Deelen, Joris, Del Greco, M. Fabiola, Demirkale, Cumhur Yusuf, Dörr, Marcus, Ehret, Georg B., Elosua, Roberto, Enroth, Stefan, Erzurumluoglu, A. Mesut, Ferreira, Teresa, Franberg, Mattias, Franco, Oscar H., Gandin, Ilaria, Gasparini, Paolo, Giedraitis, Vilmantas, Gieger, Christian, Girotto, Giorgia, Goel, Anuj, Gow, Alan, Gudnason, Vilmundur, Guo, Xiuqing, Gyllensten, Ulf, Hamsten, Anders, Harris, Tamara B., Harris, Sarah E., Hartman, Catharina A., Havulinna, Aki S., Hicks, Andrew A., Hofer, Edith, Hofman, Albert, Jottenga, Jouke-Jan, Huffman, Jennifer, Hwang, Shih-Jen, Ingelsson, Erik, James, Alan, Jansen, Rick, Jarvelin, Marjo-Riitta, Joehanes, Roby, Johansson, Asa, Johnson, Adnrew D., Joshi, Peter K., Jousilahti, Pekka, Jukema, J. Wouter, Jula, Antti, Kähönen, Mika, Kathiresan, Sekar, Keavney, Bernard D., Khaw, Kay-Tee, Knekt, Paul, Knight, Joanne, Kolcic, Ivana, Kooner, Jaspal S., Koskinen, Seppo, Kristiansson, Kati, Kutalik, Zoltan, Laan, Maris, Larson, Marty, Launer, Lenore J., Lehne, Benjamin, Lehtimäki, Terho, Liewald, David C.M., Lin, Li, Lind, Lars, Lindgren, Cecilia M., Liu, YongMei, Loos, Ruth J.F., Lopez, Lorna, Lu, Yingchang, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Mamasoula, Chrysovalanto, Marrugat, Jaume, Marten, Jonathan, Milaneschi, Yuri, Morgan, Anna, Morris, Andrew, Morrison, Alanna C., Munson, Peter J., Nalls, Mike A., Nandakumar, Priyanka, Nelson, Christopher P., Niiranen, Teemu, Nolte, Ilja M., Nutile, Teresa, Oldehinkel, Albertine J., Oostra, Ben A., O'Reilly, Paul F., Org, Elin, Padmanabhan, Sandosh, Palmas, Walter, Palotie, Aarno, Pattie, Alison, Polasek, Ozren, Pramstaller, Peter P., Nguyen, Quang Tri, Raitakari, Olli T., Ren, Meixia, Rettig, Rainer, Rice, Kenneth, Ridker, Paul M., Ried, Janina S., Riese, Harriëtte, Ripatti, Samuli, Robino, Antonietta, Rose, Lynda M., Rotter, Jerome I., Rudan, Igor, Ruggiero, Daniela, Saba, Yasaman, Sala, Cinzia F., Salomaa, Veikko, Samani, Nilesh J., Sarin, Antti-Pekka, Schmidt, Reinhold, Schmidt, Helena, Shrine, Nick, Siscovick, David, Smith, Albert V., Snieder, Harold, Sõber, Siim, Sorice, Rossella, Starr, John M., Stott, David, Strachan, David P., Strawbridge, Rona J., Sundström, Johan, Swertz, Morris A., Taylor, Kent D., Teumer, Alexander, Tobin, Martin D., Tomaszewski, Maciej, Toniolo, Daniela, Traglia, Michela, Trompet, Stella, Tuomilehto, Jaako, Tzourio, Christophe, Uitterlinden, Andre G., Vaez, Ahmad, van der Most, Peter J., van Duijn, Cornelia M., Vergnaud, Anne-Claire, verwoert, Germaine C., Vitart, Veronique, Völke, Uwe, Vollenweider, Peter, Vuckovic, Dragana, Watkins, Hugh, Wild, Sarah H., Willemsen, Gonneke, Wilson, James F., Wright, Alan F., Yao, Jie, Zemunik, Tatijana, Zhang, Weihua, Attia, John R., Butterworth, Adam S., Chasman, Daniel I., Conen, David, Cucca, Francesco, Danesh, John, Hayward, Caroline, Howson, Joanna M.M., Laakso, Markku, Lakatta, Edward G., Langenberg, Claudia, Melander, Olle, Mook-Kanamor, Dennis O., Palmer, Colin, Risch, Lorenz, Scott, Robert, Scott, Rodney, Sever, Peter, Spector, Tim D., van der Harst, Pim, Wareham, Nicholas J., Zeggini, Eleftheria, Levy, Daniel, Munroe, Patricia B., Newton-Cheh, Christopher, Brown, Morris J., Metspalu, Andres, Hung, Adriana M., O'Donnell, Christopher, Edwards, Todd L., Psaty, Bruce M., Tzoulaki, Ioanna, Barnes, Michael R., Wain, Louise V., Elliott, Paul, Caulfield, Mark J., Evangelou, Evangelos, Warren, Helen R., Mosen-Ansorena, David, Mifsud, Borbala, Pazoki, Raha, Gao, He, Ntritsos, Georgios, Dimou, Niki, Cabrera, Claudia, Karaman, Ibrahim, Ng, Fu Liang, Evangelou, Marina, Witkowska, Katarzyna, Tzanis, Evan, Hellwege, Jacklyn, Giri, Ayush, Edwards, Digna R. Velez, Sun, Yan V., Cho, Kelly, Gaziano, J. Michael, Wilson, Peter W.F., Tsao, Philip S., Kovesdy, Csaba P., Esko, Tonu, Magi, Reedik, Milani, Lili, Almgren, Peter, Boutin, Thibaud, Debette, Stephanie, Ding, Jun, Giulianini, Franco, Holliday, Elizabeth G., Jackson, Anne U., Li-Gao, Ruifang, Lin, Wei-Yu, Luan, Jian'an, Mangino, Massimo, Oldmeadow, Christopher, Prins, Bram Peter, Qian, Yong, Sargurupremraj, Muralidharan, Shah, Nabi, Surendran, Praveen, Theriault, Sebastien, Verweij, Niek, Willems, Sara M., Zhao, Jing-Hua, Amouyel, Phillippe, Connell, John, de Mutsert, Renee, Doney, Alex S.F., Farrall, Martin, Menni, Cristina, Morris, Andrew D., Noordam, Raymond, Pare, Guillaume, Poulter, Neil R., Shields, Denis C., Stanton, Alice, Thom, Simon, Abecasis, Gonçalo, Amin, Najaf, Arking, Dan E., Ayers, Kristin L., Barbieri, Caterina M., Batini, Chiara, Bis, Joshua C., Blake, Tineka, Bochud, Murielle, Boehnke, Michael, Boerwinkle, Eric, Boomsma, Dorret I., Bottinger, Erwin P., Braund, Peter S., Brumat, Marco, Campbell, Archie, Campbell, Harry, Chakravarti, Aavinda, Chambers, John C., Chauhan, Ganesh, Ciullo, Marina, Cocca, Massimiliano, Collins, Francis, Cordell, Heather J., Davies, Gail, de Borst, Martin H., de Geus, Eco J., Deary, Ian J., Deelen, Joris, Del Greco, M. Fabiola, Demirkale, Cumhur Yusuf, Dörr, Marcus, Ehret, Georg B., Elosua, Roberto, Enroth, Stefan, Erzurumluoglu, A. Mesut, Ferreira, Teresa, Franberg, Mattias, Franco, Oscar H., Gandin, Ilaria, Gasparini, Paolo, Giedraitis, Vilmantas, Gieger, Christian, Girotto, Giorgia, Goel, Anuj, Gow, Alan, Gudnason, Vilmundur, Guo, Xiuqing, Gyllensten, Ulf, Hamsten, Anders, Harris, Tamara B., Harris, Sarah E., Hartman, Catharina A., Havulinna, Aki S., Hicks, Andrew A., Hofer, Edith, Hofman, Albert, Jottenga, Jouke-Jan, Huffman, Jennifer, Hwang, Shih-Jen, Ingelsson, Erik, James, Alan, Jansen, Rick, Jarvelin, Marjo-Riitta, Joehanes, Roby, Johansson, Asa, Johnson, Adnrew D., Joshi, Peter K., Jousilahti, Pekka, Jukema, J. Wouter, Jula, Antti, Kähönen, Mika, Kathiresan, Sekar, Keavney, Bernard D., Khaw, Kay-Tee, Knekt, Paul, Knight, Joanne, Kolcic, Ivana, Kooner, Jaspal S., Koskinen, Seppo, Kristiansson, Kati, Kutalik, Zoltan, Laan, Maris, Larson, Marty, Launer, Lenore J., Lehne, Benjamin, Lehtimäki, Terho, Liewald, David C.M., Lin, Li, Lind, Lars, Lindgren, Cecilia M., Liu, YongMei, Loos, Ruth J.F., Lopez, Lorna, Lu, Yingchang, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Mamasoula, Chrysovalanto, Marrugat, Jaume, Marten, Jonathan, Milaneschi, Yuri, Morgan, Anna, Morris, Andrew, Morrison, Alanna C., Munson, Peter J., Nalls, Mike A., Nandakumar, Priyanka, Nelson, Christopher P., Niiranen, Teemu, Nolte, Ilja M., Nutile, Teresa, Oldehinkel, Albertine J., Oostra, Ben A., O'Reilly, Paul F., Org, Elin, Padmanabhan, Sandosh, Palmas, Walter, Palotie, Aarno, Pattie, Alison, Polasek, Ozren, Pramstaller, Peter P., Nguyen, Quang Tri, Raitakari, Olli T., Ren, Meixia, Rettig, Rainer, Rice, Kenneth, Ridker, Paul M., Ried, Janina S., Riese, Harriëtte, Ripatti, Samuli, Robino, Antonietta, Rose, Lynda M., Rotter, Jerome I., Rudan, Igor, Ruggiero, Daniela, Saba, Yasaman, Sala, Cinzia F., Salomaa, Veikko, Samani, Nilesh J., Sarin, Antti-Pekka, Schmidt, Reinhold, Schmidt, Helena, Shrine, Nick, Siscovick, David, Smith, Albert V., Snieder, Harold, Sõber, Siim, Sorice, Rossella, Starr, John M., Stott, David, Strachan, David P., Strawbridge, Rona J., Sundström, Johan, Swertz, Morris A., Taylor, Kent D., Teumer, Alexander, Tobin, Martin D., Tomaszewski, Maciej, Toniolo, Daniela, Traglia, Michela, Trompet, Stella, Tuomilehto, Jaako, Tzourio, Christophe, Uitterlinden, Andre G., Vaez, Ahmad, van der Most, Peter J., van Duijn, Cornelia M., Vergnaud, Anne-Claire, verwoert, Germaine C., Vitart, Veronique, Völke, Uwe, Vollenweider, Peter, Vuckovic, Dragana, Watkins, Hugh, Wild, Sarah H., Willemsen, Gonneke, Wilson, James F., Wright, Alan F., Yao, Jie, Zemunik, Tatijana, Zhang, Weihua, Attia, John R., Butterworth, Adam S., Chasman, Daniel I., Conen, David, Cucca, Francesco, Danesh, John, Hayward, Caroline, Howson, Joanna M.M., Laakso, Markku, Lakatta, Edward G., Langenberg, Claudia, Melander, Olle, Mook-Kanamor, Dennis O., Palmer, Colin, Risch, Lorenz, Scott, Robert, Scott, Rodney, Sever, Peter, Spector, Tim D., van der Harst, Pim, Wareham, Nicholas J., Zeggini, Eleftheria, Levy, Daniel, Munroe, Patricia B., Newton-Cheh, Christopher, Brown, Morris J., Metspalu, Andres, Hung, Adriana M., O'Donnell, Christopher, Edwards, Todd L., Psaty, Bruce M., Tzoulaki, Ioanna, Barnes, Michael R., Wain, Louise V., Elliott, Paul, and Caulfield, Mark J.

Abstract

High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic, pulse pressure) to date in over one million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also reveal shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.

Published
2018

44. Genetic analysis of over one million people identifies 535 novel loci for blood pressure

Author

Evangelou, Evangelos, Warren, Helen R, Mosen-Ansorena, David, Mifsud, Borbala, Pazoki, Raha, Gao, He, Ntritsos, Georgios, Dimou, Niki, Cabrera, Claudia P, Karaman, Ibrahim, Ng, Fu Liang, Evangelou, Marina, Witkowska, Katarzyna, Tzanis, Evan, Hellwege, Jacklyn N, Giri, Ayush, Velez Edwards, Digna R, Sun, Yan V, Cho, Kelly, Gaziano, J.Michael, Wilson, Peter WF, Tsao, Philip S, Kovesdy, Csaba P, Esko, Tonu, Mägi, Reedik, Milani, Lili, Almgren, Peter, Boutin, Thibaud, Debette, Stéphanie, Ding, Jun, Giulianini, Franco, Holliday, Elizabeth G, Jackson, Anne U, Li-Gao, Ruifang, Lin, Wei-Yu, Luan, Jian'an, Mangino, Massimo, Oldmeadow, Christopher, Prins, Bram, Qian, Yong, Sargurupremraj, Muralidharan, Shah, Nabi, Surendran, Praveen, Thériault, Sébastien, Verweij, Niek, Willems, Sara M, Zhao, Jing-Hua, Amouyel, Philippe, Connell, John, de Mutsert, Renée, Doney, Alex SF, Farrall, Martin, Menni, Cristina, Morris, Andrew D, Noordam, Raymond, Paré, Guillaume, Poulter, Neil R, Shields, Denis C, Stanton, Alice, Thom, Simon, Abecasis, Gonçalo, Amin, Najaf, Arking, Dan E, Ayers, Kristin L, Barbieri, Caterina M, Batini, Chiara, Bis, Joshua C, Blake, Tineka, Bochud, Murielle, Boehnke, Michael, Boerwinkle, Eric, Boomsma, Dorret I, Bottinger, Erwin P, Braund, Peter S, Brumat, Marco, Campbell, Archie, Campbell, Harry, Chakravarti, Aravinda, Chambers, John C, Chauhan, Ganesh, Ciullo, Marina, Cocca, Massimiliano, Collins, Francis, Cordell, Heather J, Davies, Gail, de Borst, Martin H, de Geus, Eco J, Deary, Ian J, Deelen, Joris, Del Greco, Fabiola M, Demirkale, Cumhur Yusuf, Dörr, Marcus, Ehret, Georg B, Elosua, Roberto, Enroth, Stefan, Erzurumluoglu, A.Mesut, Ferreira, Teresa, Frånberg, Mattias, Franco, Oscar H, Gandin, Ilaria, Gasparini, Paolo, Giedraitis, Vilmantas, Gieger, Christian, Girotto, Giorgia, Goel, Anuj, Gow, Alan J, Gudnason, Vilmundur, Guo, Xiuqing, Gyllensten, Ulf, Hamsten, Anders, Harris, Tamara B, Harris, Sarah E, Hartman, Catharina A, Havulinna, Aki S, Hicks, Andrew A, Hofer, Edith, Hofman, Albert, Hottenga, Jouke-Jan, Huffman, Jennifer E, Hwang, Shih-Jen, Ingelsson, Erik, James, Alan, Jansen, Rick, Jarvelin, Marjo-Riitta, Joehanes, Roby, Johansson, Åsa, Johnson, Andrew D, Joshi, Peter K, Jousilahti, Pekka, Jukema, J Wouter, Jula, Antti, Kähönen, Mika, Kathiresan, Sekar, Keavney, Bernard D, Khaw, Kay-Tee, Knekt, Paul, Knight, Joanne, Kolcic, Ivana, Kooner, Jaspal S, Koskinen, Seppo, Kristiansson, Kati, Kutalik, Zoltan, Laan, Maris, Larson, Marty, Launer, Lenore J, Lehne, Benjamin C, Lehtimäki, Terho, Levy, Daniel, Liewald, David CM, Lin, Li, Lind, Lars, Lindgren, Cecilia M, Liu, Yongmei, Loos, Ruth JF, Lopez, Lorna M, Lu, Lingchan, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Mamasoula, Chrysovalanto, Marrugat, Jaume, Marten, Jonathan, Milaneschi, Yuri, Morgan, Anna, Morris, Andrew P, Morrison, Alanna C, Munson, Peter J, Nalls, Mike A, Nandakumar, Priyanka, Nelson, Christopher P, Newton-Cheh, Christopher, Niiranen, Teemu, Nolte, Ilja M, Nutile, Teresa, Oldehinkel, Albertine J, Oostra, Ben A, O'Reilly, Paul F, Org, Elin, Padmanabhan, Sandosh, Palmas, Walter, Palotie, Arno, Pattie, Alison, Penninx, Brenda WJH, Perola, Markus, Peters, Annette, Polasek, Ozren, Pramstaller, Peter P, Quang Tri, Nguyen, Raitakari, Olli T, Ren, Meixia, Rettig, Rainer, Rice, Kenneth, Ridker, Paul M, Reid, Janina S, Riese, Harriëtte, Ripatti, Samuli, Robino, Antonietta, Rose, Lynda M, Rotter, Jerome I, Rudan, Igor, Ruggiero, Daniella, Saba, Yasaman, Sala, Cinzia F, Salomaa, Veikko, Samani, Nilesh J, Sarin, Antti-Pekka, Schmidt, Rheinhold, Schmidt, Helena, Shrine, Nick, Siscovick, David, Smith, Albert V, Schneider, Harold, Sõber, Siim, Sorice, Rossella, Starr, John M, Stott, David J, Strachan, David P, Strawbridge, Rona J, Sundström, Johan, Swertz, Morris A, Taylor, Kent D, Teumer, Alexander, Tobin, Martin D, Toniolo, Daniela, Traglia, Michela, Trompet, Stella, Tuomilehto, Jaakko, Tzourio, Christophe, Uitterlinden, André G, Vaez, Ahmad, van der Most, Peter J, van Duijn, Cornelia M, Vergnaud, Anne-Claire, Verwoert, Germaine C, Vitart, Veronique, Völker, Uwe, Vollenweider, Peter, Vuckovic, Dragana, Watkins, Hugh, Wild, Sarah H, Willemsen, Gonneke, Wilson, James F, Wright, Alan F, Yao, Jie, Zemunik, Tatijana, Zhang, Weihua, Attia, John R, Butterworth, Adam S, Chasman, Dan, Conen, David, Cucca, Francesco, Danesh, John, Hayward, Caroline, Howson, Joanna MM, Laakso, Markku, Lakatta, Edward G, Langenberg, Claudia, Melander, Ollie, Mook-Kanamori, Dennis O, Munroe, Patricia B, Palmer, Colin NA, Risch, Lorenz, Scott, Robert A, Scott, Rodney J, Sever, Peter, Spector, Tim D, van der Harst, Pim, Wareham, Nicholas J, Zeggini, Eleftheria, Brown, Morris J, Metspalu, Andres, Hung, Adriana M, O'Donnell, Christopher J, Edwards, Todd L, Psaty, Bruce M., Tzoulaki, Ioanna, Barnes, Michael R, Wain, Louise V, Elliott, Paul, Caulfield, Mark J, Evangelou, Evangelos, Warren, Helen R, Mosen-Ansorena, David, Mifsud, Borbala, Pazoki, Raha, Gao, He, Ntritsos, Georgios, Dimou, Niki, Cabrera, Claudia P, Karaman, Ibrahim, Ng, Fu Liang, Evangelou, Marina, Witkowska, Katarzyna, Tzanis, Evan, Hellwege, Jacklyn N, Giri, Ayush, Velez Edwards, Digna R, Sun, Yan V, Cho, Kelly, Gaziano, J.Michael, Wilson, Peter WF, Tsao, Philip S, Kovesdy, Csaba P, Esko, Tonu, Mägi, Reedik, Milani, Lili, Almgren, Peter, Boutin, Thibaud, Debette, Stéphanie, Ding, Jun, Giulianini, Franco, Holliday, Elizabeth G, Jackson, Anne U, Li-Gao, Ruifang, Lin, Wei-Yu, Luan, Jian'an, Mangino, Massimo, Oldmeadow, Christopher, Prins, Bram, Qian, Yong, Sargurupremraj, Muralidharan, Shah, Nabi, Surendran, Praveen, Thériault, Sébastien, Verweij, Niek, Willems, Sara M, Zhao, Jing-Hua, Amouyel, Philippe, Connell, John, de Mutsert, Renée, Doney, Alex SF, Farrall, Martin, Menni, Cristina, Morris, Andrew D, Noordam, Raymond, Paré, Guillaume, Poulter, Neil R, Shields, Denis C, Stanton, Alice, Thom, Simon, Abecasis, Gonçalo, Amin, Najaf, Arking, Dan E, Ayers, Kristin L, Barbieri, Caterina M, Batini, Chiara, Bis, Joshua C, Blake, Tineka, Bochud, Murielle, Boehnke, Michael, Boerwinkle, Eric, Boomsma, Dorret I, Bottinger, Erwin P, Braund, Peter S, Brumat, Marco, Campbell, Archie, Campbell, Harry, Chakravarti, Aravinda, Chambers, John C, Chauhan, Ganesh, Ciullo, Marina, Cocca, Massimiliano, Collins, Francis, Cordell, Heather J, Davies, Gail, de Borst, Martin H, de Geus, Eco J, Deary, Ian J, Deelen, Joris, Del Greco, Fabiola M, Demirkale, Cumhur Yusuf, Dörr, Marcus, Ehret, Georg B, Elosua, Roberto, Enroth, Stefan, Erzurumluoglu, A.Mesut, Ferreira, Teresa, Frånberg, Mattias, Franco, Oscar H, Gandin, Ilaria, Gasparini, Paolo, Giedraitis, Vilmantas, Gieger, Christian, Girotto, Giorgia, Goel, Anuj, Gow, Alan J, Gudnason, Vilmundur, Guo, Xiuqing, Gyllensten, Ulf, Hamsten, Anders, Harris, Tamara B, Harris, Sarah E, Hartman, Catharina A, Havulinna, Aki S, Hicks, Andrew A, Hofer, Edith, Hofman, Albert, Hottenga, Jouke-Jan, Huffman, Jennifer E, Hwang, Shih-Jen, Ingelsson, Erik, James, Alan, Jansen, Rick, Jarvelin, Marjo-Riitta, Joehanes, Roby, Johansson, Åsa, Johnson, Andrew D, Joshi, Peter K, Jousilahti, Pekka, Jukema, J Wouter, Jula, Antti, Kähönen, Mika, Kathiresan, Sekar, Keavney, Bernard D, Khaw, Kay-Tee, Knekt, Paul, Knight, Joanne, Kolcic, Ivana, Kooner, Jaspal S, Koskinen, Seppo, Kristiansson, Kati, Kutalik, Zoltan, Laan, Maris, Larson, Marty, Launer, Lenore J, Lehne, Benjamin C, Lehtimäki, Terho, Levy, Daniel, Liewald, David CM, Lin, Li, Lind, Lars, Lindgren, Cecilia M, Liu, Yongmei, Loos, Ruth JF, Lopez, Lorna M, Lu, Lingchan, Lyytikäinen, Leo-Pekka, Mahajan, Anubha, Mamasoula, Chrysovalanto, Marrugat, Jaume, Marten, Jonathan, Milaneschi, Yuri, Morgan, Anna, Morris, Andrew P, Morrison, Alanna C, Munson, Peter J, Nalls, Mike A, Nandakumar, Priyanka, Nelson, Christopher P, Newton-Cheh, Christopher, Niiranen, Teemu, Nolte, Ilja M, Nutile, Teresa, Oldehinkel, Albertine J, Oostra, Ben A, O'Reilly, Paul F, Org, Elin, Padmanabhan, Sandosh, Palmas, Walter, Palotie, Arno, Pattie, Alison, Penninx, Brenda WJH, Perola, Markus, Peters, Annette, Polasek, Ozren, Pramstaller, Peter P, Quang Tri, Nguyen, Raitakari, Olli T, Ren, Meixia, Rettig, Rainer, Rice, Kenneth, Ridker, Paul M, Reid, Janina S, Riese, Harriëtte, Ripatti, Samuli, Robino, Antonietta, Rose, Lynda M, Rotter, Jerome I, Rudan, Igor, Ruggiero, Daniella, Saba, Yasaman, Sala, Cinzia F, Salomaa, Veikko, Samani, Nilesh J, Sarin, Antti-Pekka, Schmidt, Rheinhold, Schmidt, Helena, Shrine, Nick, Siscovick, David, Smith, Albert V, Schneider, Harold, Sõber, Siim, Sorice, Rossella, Starr, John M, Stott, David J, Strachan, David P, Strawbridge, Rona J, Sundström, Johan, Swertz, Morris A, Taylor, Kent D, Teumer, Alexander, Tobin, Martin D, Toniolo, Daniela, Traglia, Michela, Trompet, Stella, Tuomilehto, Jaakko, Tzourio, Christophe, Uitterlinden, André G, Vaez, Ahmad, van der Most, Peter J, van Duijn, Cornelia M, Vergnaud, Anne-Claire, Verwoert, Germaine C, Vitart, Veronique, Völker, Uwe, Vollenweider, Peter, Vuckovic, Dragana, Watkins, Hugh, Wild, Sarah H, Willemsen, Gonneke, Wilson, James F, Wright, Alan F, Yao, Jie, Zemunik, Tatijana, Zhang, Weihua, Attia, John R, Butterworth, Adam S, Chasman, Dan, Conen, David, Cucca, Francesco, Danesh, John, Hayward, Caroline, Howson, Joanna MM, Laakso, Markku, Lakatta, Edward G, Langenberg, Claudia, Melander, Ollie, Mook-Kanamori, Dennis O, Munroe, Patricia B, Palmer, Colin NA, Risch, Lorenz, Scott, Robert A, Scott, Rodney J, Sever, Peter, Spector, Tim D, van der Harst, Pim, Wareham, Nicholas J, Zeggini, Eleftheria, Brown, Morris J, Metspalu, Andres, Hung, Adriana M, O'Donnell, Christopher J, Edwards, Todd L, Psaty, Bruce M., Tzoulaki, Ioanna, Barnes, Michael R, Wain, Louise V, Elliott, Paul, and Caulfield, Mark J

Abstract

High blood pressure is the foremost heritable global risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits to date (systolic, diastolic, pulse pressure) in over one million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also reveal shared loci influencing lifestyle exposures. Our findings offer the potential for a precision medicine strategy for future cardiovascular disease prevention.

Published
2017

45. Protocol of the adaptive study of IL-2 dose frequency on regulatory T cells in type 1 diabetes (DILfrequency): a mechanistic, non-randomised, repeat dose, open-label, response-adaptive study

Author

Truman, Lucy A, Pekalski, Marcin L, Kareclas, Paula, Evangelou, Marina, Walker, Neil M, Howlett, James, Mander, Adrian P, Kennet, Jane, Wicker, Linda S, Bond, Simon, Todd, John A, Waldron-Lynch, Frank, Howlett, James [0000-0001-9274-5170], Mander, Adrian [0000-0002-0742-9040], Bond, Simon [0000-0003-2528-1040], Waldron-Lynch, Frank [0000-0002-0597-4328], and Apollo - University of Cambridge Repository

Subjects
Adult, Male, GENETICS, Adolescent, DIABETES & ENDOCRINOLOGY, Interleukin-2 Receptor alpha Subunit, Middle Aged, T-Lymphocytes, Regulatory, IMMUNOLOGY, Diabetes and Endocrinology, Young Adult, Diabetes Mellitus, Type 1, Protocol, Humans, Interleukin-2, Female, Aged
Abstract

INTRODUCTION: Type 1 diabetes (T1D) is caused by autoimmune destruction of the insulin-producing β cells in the pancreatic islets, leading to insulinopenia and hyperglycaemia. Genetic analyses indicate that alterations of the interleukin-2 (IL-2) pathway mediating immune activation and tolerance predispose to T1D, specifically the polymorphic expression of the IL-2 receptor-α chain (CD25) on T lymphocytes. Replacement of physiological doses of IL-2 could restore self-tolerance and prevent further autoimmunity by enhancing the function of CD4(+) T regulatory cells (Tregs) to limit the activation of auto reactive T effector cells (Teffs). In this experimental medicine study, we use an adaptive trial design to determine the optimal dosing regimen for IL-2 to improve Treg function while limiting activation of Teffs in participants with T1D. METHODS AND ANALYSIS: The Adaptive study of IL-2 dose frequency on Tregs in type 1 diabetes(DILfrequency) is a mechanistic, non-randomised, repeat dose open-label, response-adaptive study of 36 participants with T1D. The objective is to establish the optimal dose and frequency of ultra-low dose IL-2: to increase Treg frequency within the physiological range, to increase CD25 expression on Tregs, without increasing CD4(+) Teffs. DILfrequency has an initial learning phase where 12 participants are allocated to six different doses and frequencies followed by an interim statistical analysis. After analysis of the learning phase, the Dose and Frequency Committee will select the optimal targets for Treg frequency, Treg CD25 expression and Teff frequency. Three groups of eight participants will be treated consecutively in the confirming phase. Each dose and frequency selected will be based on statistical analysis of all data collected from the previous groups. ETHICS: Ethical approval for DILfrequency was granted on 12 August 2014. RESULTS: The results of this study will be reported, through peer-reviewed journals, conference presentations and an internal organisational report. TRIAL REGISTRATION NUMBERS: NCT02265809, ISRCTN40319192, CRN17571.

Published
2015

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