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1. bursty_dynamics: A Python Package for Exploring the Temporal Properties of Longitudinal Data

Author

Angdembe, Alisha, Iqbal, Wasim A, Hamad, Rebeen Ali, Casement, John, Consortium, AI-Multiply, Missier, Paolo, Reynolds, Nick, Henkin, Rafael, and Barnes, Michael R

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Understanding the temporal properties of longitudinal data is critical for identifying trends, predicting future events, and making informed decisions in any field where temporal data is analysed, including health and epidemiology, finance, geosciences, and social sciences. Traditional time-series analysis techniques often fail to capture the complexity of irregular temporal patterns present in such data. To address this gap, we introduce bursty_dynamics, a Python package that enables the quantification of bursty dynamics through the calculation of the Burstiness Parameter (BP) and Memory Coefficient (MC). In temporal data, BP and MC provide insights into the irregularity and temporal dependencies within event sequences, shedding light on complex patterns of disease aetiology, human behaviour, or other information diffusion over time. An event train detection method is also implemented to identify clustered events occurring within a specified time interval, allowing for more focused analysis with reduced noise. With built-in visualisation tools, bursty_dynamics provides an accessible yet powerful platform for researchers to explore and interpret the temporal dynamics of longitudinal data. This paper outlines the core functionalities of the package, demonstrates its applications in diverse research domains, and discusses the advantages of using BP, MC, and event train detection for enhanced temporal data analysis.

Published
2024

2. Going Beyond H&E and Oncology: How Do Histopathology Foundation Models Perform for Multi-stain IHC and Immunology?

Author

Gallagher-Syed, Amaya, Pontarini, Elena, Lewis, Myles J., Barnes, Michael R., and Slabaugh, Gregory

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Quantitative Biology - Quantitative Methods, Quantitative Biology - Tissues and Organs
Abstract

This study evaluates the generalisation capabilities of state-of-the-art histopathology foundation models on out-of-distribution multi-stain autoimmune Immunohistochemistry datasets. We compare 13 feature extractor models, including ImageNet-pretrained networks, and histopathology foundation models trained on both public and proprietary data, on Rheumatoid Arthritis subtyping and Sjogren's Disease detection tasks. Using a simple Attention-Based Multiple Instance Learning classifier, we assess the transferability of learned representations from cancer H&E images to autoimmune IHC images. Contrary to expectations, histopathology-pretrained models did not significantly outperform ImageNet-pretrained models. Furthermore, there was evidence of both autoimmune feature misinterpretation and biased feature importance. Our findings highlight the challenges in transferring knowledge from cancer to autoimmune histopathology and emphasise the need for careful evaluation of AI models across diverse histopathological tasks. The code to run this benchmark is available at https://github.com/AmayaGS/ImmunoHistoBench., Comment: Accepted at Workshop on Advancements In Medical Foundation Models (NeurIPS 2024)

Published
2024

3. Automated segmentation of rheumatoid arthritis immunohistochemistry stained synovial tissue

Author

Gallagher-Syed, Amaya, Khan, Abbas, Rivellese, Felice, Pitzalis, Costantino, Lewis, Myles J., Slabaugh, Gregory, and Barnes, Michael R.

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Quantitative Biology - Quantitative Methods
Abstract

Rheumatoid Arthritis (RA) is a chronic, autoimmune disease which primarily affects the joint's synovial tissue. It is a highly heterogeneous disease, with wide cellular and molecular variability observed in synovial tissues. Over the last two decades, the methods available for their study have advanced considerably. In particular, Immunohistochemistry stains are well suited to highlighting the functional organisation of samples. Yet, analysis of IHC-stained synovial tissue samples is still overwhelmingly done manually and semi-quantitatively by expert pathologists. This is because in addition to the fragmented nature of IHC stained synovial tissue, there exist wide variations in intensity and colour, strong clinical centre batch effect, as well as the presence of many undesirable artefacts present in gigapixel Whole Slide Images (WSIs), such as water droplets, pen annotation, folded tissue, blurriness, etc. There is therefore a strong need for a robust, repeatable automated tissue segmentation algorithm which can cope with this variability and provide support to imaging pipelines. We train a UNET on a hand-curated, heterogeneous real-world multi-centre clinical dataset R4RA, which contains multiple types of IHC staining. The model obtains a DICE score of 0.865 and successfully segments different types of IHC staining, as well as dealing with variance in colours, intensity and common WSIs artefacts from the different clinical centres. It can be used as the first step in an automated image analysis pipeline for synovial tissue samples stained with IHC, increasing speed, reproducibility and robustness.

Published
2023

4. Large-Scale Pharmacogenomics Analysis of Patients With Cancer Within the 100,000 Genomes Project Combining Whole-Genome Sequencing and Medical Records to Inform Clinical Practice

Author

Leong, Ivone U.S., Cabrera, Claudia P., Cipriani, Valentina, Ross, Paul J., Turner, Richard M., Stuckey, Alex, Sanghvi, Sonali, Pasko, Dorota, Moutsianas, Loukas, Odhams, Christopher A., Elgar, Greg S., Chan, Georgia, Giess, Adam, Walker, Susan, Foulger, Rebecca E., Williams, Eleanor M., Daugherty, Louise C., Rueda-Martin, Antonio, Rhodes, Daniel J., Niblock, Olivia, Pickard, Alexandra, Marks, Lauren, Leigh, Sarah E.A., Welland, Matthew J., Bleda, Marta, Snow, Catherine, Deans, Zandra, Murugaesu, Nirupa, Scott, Richard H., Barnes, Michael R., Brown, Matthew A., Rendon, Augusto, Hill, Sue, Sosinsky, Alona, Caulfield, Mark J., and McDonagh, Ellen M.

Published
2024
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8. The Benefits of Managed Turfgrass Spaces

Author

Barnes, Michael R.

Subjects
Ecosystems, Company business management, Agricultural industry, Business, Sports, sporting goods and toys industry
Abstract

Abroad narrative exists among those not involved in turfgrass management and research that turfgrass spaces provide few benefits beyond simple aesthetics. Most commonly, such narratives frame this comparison based on [...]

Published
2023

9. Statin-induced LDL cholesterol response and type 2 diabetes: a bidirectional two-sample Mendelian randomization study.

Author

Smit, Roelof AJ, Trompet, Stella, Leong, Aaron, Goodarzi, Mark O, Postmus, Iris, Warren, Helen, Theusch, Elizabeth, Barnes, Michael R, Arsenault, Benoit J, Li, Xiaohui, Feng, QiPing, Chasman, Daniel I, Cupples, L Adrienne, Hitman, Graham A, Krauss, Ronald M, Psaty, Bruce M, Rotter, Jerome I, Cessie, Saskia le, Stein, C Michael, Jukema, J Wouter, and GIST consortium

Subjects
GIST consortium, Humans, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Female, Male, Cholesterol, LDL, Genetic Variation, Genome-Wide Association Study, Mendelian Randomization Analysis, Atherosclerosis, Clinical Research, Diabetes, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Pharmacology and Pharmaceutical Sciences, Pharmacology & Pharmacy
Abstract

It remains unclear whether the increased risk of new-onset type 2 diabetes (T2D) seen in statin users is due to low LDL-C concentrations, or due to the statin-induced proportional change in LDL-C. In addition, genetic instruments have not been proposed before to examine whether liability to T2D might cause greater proportional statin-induced LDL-C lowering. Using summary-level statistics from the Genomic Investigation of Statin Therapy (GIST, nmax = 40,914) and DIAGRAM (nmax = 159,208) consortia, we found a positive genetic correlation between LDL-C statin response and T2D using LD score regression (rgenetic = 0.36, s.e. = 0.13). However, mendelian randomization analyses did not provide support for statin response having a causal effect on T2D risk (OR 1.00 (95% CI: 0.97, 1.03) per 10% increase in statin response), nor that liability to T2D has a causal effect on statin-induced LDL-C response (0.20% increase in response (95% CI: -0.40, 0.80) per doubling of odds of liability to T2D). Although we found no evidence to suggest that proportional statin response influences T2D risk, a definitive assessment should be made in populations comprised exclusively of statin users, as the presence of nonstatin users in the DIAGRAM dataset may have substantially diluted our effect estimate.

Published
2020

10. Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction.

Author

Ntalla, Ioanna, Weng, Lu-Chen, Cartwright, James H, Hall, Amelia Weber, Sveinbjornsson, Gardar, Tucker, Nathan R, Choi, Seung Hoan, Chaffin, Mark D, Roselli, Carolina, Barnes, Michael R, Mifsud, Borbala, Warren, Helen R, Hayward, Caroline, Marten, Jonathan, Cranley, James J, Concas, Maria Pina, Gasparini, Paolo, Boutin, Thibaud, Kolcic, Ivana, Polasek, Ozren, Rudan, Igor, Araujo, Nathalia M, Lima-Costa, Maria Fernanda, Ribeiro, Antonio Luiz P, Souza, Renan P, Tarazona-Santos, Eduardo, Giedraitis, Vilmantas, Ingelsson, Erik, Mahajan, Anubha, Morris, Andrew P, Del Greco M, Fabiola, Foco, Luisa, Gögele, Martin, Hicks, Andrew A, Cook, James P, Lind, Lars, Lindgren, Cecilia M, Sundström, Johan, Nelson, Christopher P, Riaz, Muhammad B, Samani, Nilesh J, Sinagra, Gianfranco, Ulivi, Sheila, Kähönen, Mika, Mishra, Pashupati P, Mononen, Nina, Nikus, Kjell, Caulfield, Mark J, Dominiczak, Anna, Padmanabhan, Sandosh, Montasser, May E, O'Connell, Jeff R, Ryan, Kathleen, Shuldiner, Alan R, Aeschbacher, Stefanie, Conen, David, Risch, Lorenz, Thériault, Sébastien, Hutri-Kähönen, Nina, Lehtimäki, Terho, Lyytikäinen, Leo-Pekka, Raitakari, Olli T, Barnes, Catriona LK, Campbell, Harry, Joshi, Peter K, Wilson, James F, Isaacs, Aaron, Kors, Jan A, van Duijn, Cornelia M, Huang, Paul L, Gudnason, Vilmundur, Harris, Tamara B, Launer, Lenore J, Smith, Albert V, Bottinger, Erwin P, Loos, Ruth JF, Nadkarni, Girish N, Preuss, Michael H, Correa, Adolfo, Mei, Hao, Wilson, James, Meitinger, Thomas, Müller-Nurasyid, Martina, Peters, Annette, Waldenberger, Melanie, Mangino, Massimo, Spector, Timothy D, Rienstra, Michiel, van de Vegte, Yordi J, van der Harst, Pim, Verweij, Niek, Kääb, Stefan, Schramm, Katharina, Sinner, Moritz F, Strauch, Konstantin, Cutler, Michael J, Fatkin, Diane, London, Barry, Olesen, Morten, and Roden, Dan M

Subjects
Humans, Cardiovascular Diseases, Genetic Predisposition to Disease, Electrocardiography, Gene Expression, Multifactorial Inheritance, Quantitative Trait Loci, Female, Male, Arrhythmias, Cardiac, Genetic Variation, Genome-Wide Association Study, Genetic Loci, Endophenotypes, Arrhythmias, Cardiac
Abstract

The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.

Published
2020

11. A national initiative in data science for health: an evaluation of the UK Farr Institute

Author

Hemingway, H, Lyons, R, Li, Q, Buchan, I, Ainsworth, J, Pell, J, Morris, A, Barnes, Michael R, Bedford, Helen, Bennie, Marion, Blandford, Ann, Briggs, Andy, Brocklehurst, Peter, Brophy, Sinead, Brown, Gavin, Burton, Paul, Butler, Christopher, Capewell, Simon, Carpenter, James, Carroll, John, Cassell, Jackie A, Castillo, Fortunato, Catchpole, Mike, Caulfield, Mark, Colhoun, Helen, Coveney, Peter, Cunningham-Burley, Sarah, Custovic, Adnan, Deanfield, John, Denaxas, Spiros, Dennis, Michael, Dezateux, Carol, Dibben, Chris, Diggle, Peter, Dixon, Will, Dunn, Graham, Emam, Khaled El, Fone, David, Ford, David, Ford, Ian, Frank, John, Freemantle, Nick, Gabbe, Belinda, Gallacher, John, Gibson, Martin, Gilbert, Ruth, Gissler, Mika, Goble, Carol, Goldberg, Andy, Gravenor, Mike, Gunnell, David, Hannaford, Phil, Hayward, Andrew, Hickman, Matthew, Hingorani, Aroon, Holm, Soren, Holman, Cashel, John, Gareth, John, Ann, Jones, Kerina, Kalra, Dipak, Laurie, Graeme, Lewis, Shon, Lloyd, Keith, Lowe, Sarah, McCowan, Colin, Macleod, John, Martin, Richard M, Moore, Anthony, Moore, Laurence, Nazareth, Irwin, Nenadic, Goran, Paranjothy, Shantini, Parmar, Max, Pebody, Richard, Petersen, Steffen, Petersen, Irene, Pillay, Deenan, Preen, David, Pickett, Kate, Pritchard-Jones, Kathy, Przulj, Natasa, Renehan, Andrew, Roberts, Stephen, Robson, John, Rodgers, Sarah, Rossor, Martin, Russell, Ian, Shawe-Taylor, John, Sheikh, Aziz, Siebert, Stefan, Snooks, Helen, Sperrin, Matthew, Stephenson, Judith, Sullivan, Frank, Taylor, Chris, Taylor, Paul, Timmis, Adam, and Ward, Hester JT

Subjects
Information and Computing Sciences, Library and Information Studies, Health Sciences, Generic health relevance, Health sciences, Human society, Information and computing sciences
Abstract

ObjectiveTo evaluate the extent to which the inter-institutional, inter-disciplinary mobilisation of data and skills in the Farr Institute contributed to establishing the emerging field of data science for health in the UK.Design and outcome measuresWe evaluated evidence of six domains characterising a new field of science:defining central scientific challenges,demonstrating how the central challenges might be solved,creating novel interactions among groups of scientists,training new types of experts,re-organising universities,demonstrating impacts in society.We carried out citation, network and time trend analyses of publications, and a narrative review of infrastructure, methods and tools.SettingFour UK centres in London, North England, Scotland and Wales (23 university partners), 2013-2018.Results1. The Farr Institute helped define a central scientific challenge publishing a research corpus, demonstrating insights from electronic health record (EHR) and administrative data at each stage of the translational cycle in 593 papers with at least one Farr Institute author affiliation on PubMed. 2. The Farr Institute offered some demonstrations of how these scientific challenges might be solved: it established the first four ISO27001 certified trusted research environments in the UK, and approved more than 1000 research users, published on 102 unique EHR and administrative data sources, although there was no clear evidence of an increase in novel, sustained record linkages. The Farr Institute established open platforms for the EHR phenotyping algorithms and validations (>70 diseases, CALIBER). Sample sizes showed some evidence of increase but remained less than 10% of the UK population in primary care-hospital care linked studies. 3.The Farr Institute created novel interactions among researchers: the co-author publication network expanded from 944 unique co-authors (based on 67 publications in the first 30 months) to 3839 unique co-authors (545 papers in the final 30 months). 4. Training expanded substantially with 3 new masters courses, training >400 people at masters, short-course and leadership level and 48 PhD students. 5. Universities reorganised with 4/5 Centres established 27 new faculty (tenured) positions, 3 new university institutes. 6. Emerging evidence of impacts included: > 3200 citations for the 10 most cited papers and Farr research informed eight practice-changing clinical guidelines and policies relevant to the health of millions of UK citizens.ConclusionThe Farr Institute played a major role in establishing and growing the field of data science for health in the UK, with some initial evidence of benefits for health and healthcare. The Farr Institute has now expanded into Health Data Research (HDR) UK but key challenges remain including, how to network such activities internationally.

Published
2020

12. Rituximab versus tocilizumab in rheumatoid arthritis: synovial biopsy-based biomarker analysis of the phase 4 R4RA randomized trial

Author

Rivellese, Felice, Surace, Anna E. A., Goldmann, Katriona, Sciacca, Elisabetta, Çubuk, Cankut, Giorli, Giovanni, John, Christopher R., Nerviani, Alessandra, Fossati-Jimack, Liliane, Thorborn, Georgina, Ahmed, Manzoor, Prediletto, Edoardo, Church, Sarah E., Hudson, Briana M., Warren, Sarah E., McKeigue, Paul M., Humby, Frances, Bombardieri, Michele, Barnes, Michael R., Lewis, Myles J., and Pitzalis, Costantino

Published
2022
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14. Cultivating connections: Framing turfgrass as a thriving social–ecological–technological system.

Author

Barnes, Michael R., Friell, Joshua, Runck, Bryan C., Soldat, Douglas J., Watkins, Eric, and Yue, Chengyan

Subjects
*PERMACULTURE, *INTELLIGENT sensors, *LANDSCAPE changes, *GREEN infrastructure, *ROBOTICS
Abstract

Turfgrass systems are some of the most ubiquitous forms of perennial agricultural systems. People interact with them on a daily basis, and they provide a wide variety of social and environmental benefits. Over the past two decades, turfgrass systems have been increasingly seen as coupled human‐natural systems, which has prompted new avenues of research across multiple areas from breeding to management. While this human‐natural systems framework has been helpful, the rapid development and integration of technology (e.g., smart sensors, robotic mowers) and the push for nature‐based solutions and green infrastructure have changed the landscape significantly for turfgrass systems. With this in mind, the current work advocates for the adoption of a new framework, social–ecological–technological systems (SETS), to better understand where turfgrass systems research is situated now and, more importantly, what directions it could go in the future. [ABSTRACT FROM AUTHOR]

Published
2024
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19. Meta-analysis of genome-wide association studies of HDL cholesterol response to statins

Author

Postmus, Iris, Warren, Helen R, Trompet, Stella, Arsenault, Benoit J, Avery, Christy L, Bis, Joshua C, Chasman, Daniel I, de Keyser, Catherine E, Deshmukh, Harshal A, Evans, Daniel S, Feng, QiPing, Li, Xiaohui, Smit, Roelof AJ, Smith, Albert V, Sun, Fangui, Taylor, Kent D, Arnold, Alice M, Barnes, Michael R, Barratt, Bryan J, Betteridge, John, Boekholdt, S Matthijs, Boerwinkle, Eric, Buckley, Brendan M, Chen, Y-D Ida, de Craen, Anton JM, Cummings, Steven R, Denny, Joshua C, Dubé, Marie Pierre, Durrington, Paul N, Eiriksdottir, Gudny, Ford, Ian, Guo, Xiuqing, Harris, Tamara B, Heckbert, Susan R, Hofman, Albert, Hovingh, G Kees, Kastelein, John JP, Launer, Leonore J, Liu, Ching-Ti, Liu, Yongmei, Lumley, Thomas, McKeigue, Paul M, Munroe, Patricia B, Neil, Andrew, Nickerson, Deborah A, Nyberg, Fredrik, O'Brien, Eoin, O'Donnell, Christopher J, Post, Wendy, Poulter, Neil, Vasan, Ramachandran S, Rice, Kenneth, Rich, Stephen S, Rivadeneira, Fernando, Sattar, Naveed, Sever, Peter, Shaw-Hawkins, Sue, Shields, Denis C, Slagboom, P Eline, Smith, Nicholas L, Smith, Joshua D, Sotoodehnia, Nona, Stanton, Alice, Stott, David J, Stricker, Bruno H, Stürmer, Til, Uitterlinden, André G, Wei, Wei-Qi, Westendorp, Rudi GJ, Whitsel, Eric A, Wiggins, Kerri L, Wilke, Russell A, Ballantyne, Christie M, Colhoun, Helen M, Cupples, L Adrienne, Franco, Oscar H, Gudnason, Vilmundur, Hitman, Graham, Palmer, Colin NA, Psaty, Bruce M, Ridker, Paul M, Stafford, Jeanette M, Stein, Charles M, Tardif, Jean-Claude, Caulfield, Mark J, Jukema, J Wouter, Rotter, Jerome I, and Krauss, Ronald M

Subjects
Atherosclerosis, Genetics, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Stroke, Good Health and Well Being, Cholesterol Ester Transfer Proteins, Cholesterol, HDL, Female, Genome-Wide Association Study, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Male, Pharmacogenomic Variants, Polymorphism, Single Nucleotide, Treatment Outcome, White People, Genome-wide association study, HDL-cholesterol, Statins, pharmacogenetics, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

BackgroundIn addition to lowering low density lipoprotein cholesterol (LDL-C), statin therapy also raises high density lipoprotein cholesterol (HDL-C) levels. Inter-individual variation in HDL-C response to statins may be partially explained by genetic variation.Methods and resultsWe performed a meta-analysis of genome-wide association studies (GWAS) to identify variants with an effect on statin-induced high density lipoprotein cholesterol (HDL-C) changes. The 123 most promising signals with p

Published
2016

20. Unearthing green potential: Assessing the state of managed urban landscape curricula in Minnesota’s higher education institutions.

Author

Barnes, Michael R., Campagna, Ileana A., Haddad, Becky, and Watkins, Eric

Subjects
UNIVERSITIES & colleges, UNDERGRADUATE programs, ENVIRONMENTAL sciences, NATURAL resources, LANDSCAPES, GREEN infrastructure
Abstract

As urbanization increases, managed urban landscapes are frequently the mode through which people experience nature and where careers in natural resources are increasing. There is a lack of knowledge related to curricula and programs where students are exposed to managed urban landscapes and careers related to them. We aimed to evaluate the current status of managed urban landscape curricula (MULC) in undergraduate programs in Minnesota through a systematic investigation of programs and courses at higher education institutions. All undergraduate courses offered by included higher education institutions were reviewed to determine the presence, absence, or possibility of MULC based on the course’s publicly available descriptions and were combined with departmental and institutional characteristics to identify patterns of MULC across the state. Only about 1% of over 50,000 courses reviewed contain MULC. Courses with MULC were concentrated in public doctoral-level institutions and in departments such as biology and environmental studies, however MULC courses were found at 94% of included institutions and across 60 different departments. While the number of courses with MULC was minimal, courses with the possibility of including MULC show there are ample opportunities for MULC to be added to existing courses, especially core requirements such as introductory biology or a survey of environmental science in the state of Minnesota and more broadly. [ABSTRACT FROM AUTHOR]

Published
2024
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22. Clinical Impact of Antibodies against Ustekinumab in Psoriasis: An Observational, Cross-Sectional, Multicenter Study

Author

Barker, Jonathan, Benham, Marilyn, Burden, David, Evans, Ian, Griffiths, Christopher, Hussain, Sagair, Kirby, Brian, Lawson, Linda, Mason, Kayleigh, McElhone, Kathleen, Murphy, Ruth, Ormerod, Anthony, Owen, Caroline, Reynolds, Nick, Smith, Catherine, Warren, Richard, Barker, Jonathan N.W.N., Barnes, Michael R., Burden, A. David, DiMeglio, Paola, Emsley, Richard, Evans, Andrea, Griffiths, Christopher E.M., Payne, Katherine, Reynolds, Nick J., Smith, Catherine H., Stocken, Deborah, Warren, Richard B., Loeff, Floris C., Tsakok, Teresa, Dijk, Lisanne, Hart, Margreet H., Duckworth, Michael, Baudry, David, Russell, Alice, Dand, Nick, van Leeuwen, Astrid, de Vries, Annick, Bloem, Karien, Wolbink, Gerrit Jan, and Rispens, Theo

Published
2020
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24. Rooted in risk: genetic predisposition for low-density lipoprotein cholesterol level associates with diminished low-density lipoprotein cholesterol response to statin treatment

Author

Smit, Roelof AJ, Postmus, Iris, Trompet, Stella, Barnes, Michael R, Warren, Helen, Arsenault, Benoit J, Chasman, Daniel I, Cupples, L Adrienne, Hitman, Graham A, Krauss, Ronald M, Li, Xiaohui, Psaty, Bruce M, Stein, Charles M, Rotter, Jerome I, and Jukema, J Wouter

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Heart Disease, Cardiovascular, Atherosclerosis, Human Genome, Prevention, Aetiology, 2.1 Biological and endogenous factors, Cholesterol, LDL, Genetic Predisposition to Disease, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Pharmacogenetics, Polymorphism, Single Nucleotide, Triglycerides, MR-Egger, pharmacogenetics, statin therapy, MR–Egger, Medical and Health Sciences, Pharmacology & Pharmacy, Pharmacology and pharmaceutical sciences
Abstract

AimsTo utilize previously reported lead SNPs for low-density lipoprotein cholesterol (LDL-c) levels to find additional loci of importance to statin response, and examine whether genetic predisposition to LDL-c levels associates with differential statin response.MethodsWe investigated effects on statin response of 59 LDL-c SNPs, by combining summary level statistics from the Global Lipids Genetics and Genomic Investigation of Statin Therapy consortia.ResultsLead SNPs for APOE, SORT1 and NPC1L1 were associated with a decreased LDL-c response to statin treatment, as was overall genetic predisposition for increased LDL-c levels as quantified with 59 SNPs, with a 5.4% smaller statin response per standard deviation increase in genetically raised LDL-c levels.ConclusionGenetic predisposition for increased LDL-c level may decrease efficacy of statin therapy.

Published
2016

25. The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals.

Author

Ehret, Georg B, Ferreira, Teresa, Chasman, Daniel I, Jackson, Anne U, Schmidt, Ellen M, Johnson, Toby, Thorleifsson, Gudmar, Luan, Jian'an, Donnelly, Lousie A, Kanoni, Stavroula, Petersen, Ann-Kristin, Pihur, Vasyl, Strawbridge, Rona J, Shungin, Dmitry, Hughes, Maria F, Meirelles, Osorio, Kaakinen, Marika, Bouatia-Naji, Nabila, Kristiansson, Kati, Shah, Sonia, Kleber, Marcus E, Guo, Xiuqing, Lyytikäinen, Leo-Pekka, Fava, Cristiano, Eriksson, Niclas, Nolte, Ilja M, Magnusson, Patrik K, Salfati, Elias L, Rallidis, Loukianos S, Theusch, Elizabeth, Smith, Andrew JP, Folkersen, Lasse, Witkowska, Kate, Pers, Tune H, Joehanes, Roby, Kim, Stuart K, Lataniotis, Lazaros, Jansen, Rick, Johnson, Andrew D, Warren, Helen, Kim, Young Jin, Zhao, Wei, Wu, Ying, Tayo, Bamidele O, Bochud, Murielle, CHARGE-EchoGen consortium, CHARGE-HF consortium, Wellcome Trust Case Control Consortium, Absher, Devin, Adair, Linda S, Amin, Najaf, Arking, Dan E, Axelsson, Tomas, Baldassarre, Damiano, Balkau, Beverley, Bandinelli, Stefania, Barnes, Michael R, Barroso, Inês, Bevan, Stephen, Bis, Joshua C, Bjornsdottir, Gyda, Boehnke, Michael, Boerwinkle, Eric, Bonnycastle, Lori L, Boomsma, Dorret I, Bornstein, Stefan R, Brown, Morris J, Burnier, Michel, Cabrera, Claudia P, Chambers, John C, Chang, I-Shou, Cheng, Ching-Yu, Chines, Peter S, Chung, Ren-Hua, Collins, Francis S, Connell, John M, Döring, Angela, Dallongeville, Jean, Danesh, John, de Faire, Ulf, Delgado, Graciela, Dominiczak, Anna F, Doney, Alex SF, Drenos, Fotios, Edkins, Sarah, Eicher, John D, Elosua, Roberto, Enroth, Stefan, Erdmann, Jeanette, Eriksson, Per, Esko, Tonu, Evangelou, Evangelos, Evans, Alun, Fall, Tove, Farrall, Martin, Felix, Janine F, Ferrières, Jean, Ferrucci, Luigi, Fornage, Myriam, and Forrester, Terrence

Subjects
CHARGE-EchoGen consortium, CHARGE-HF consortium, Wellcome Trust Case Control Consortium, Cells, Cultured, Humans, Hypertension, Microarray Analysis, Blood Pressure, Polymorphism, Single Nucleotide, African Continental Ancestry Group, Asian Continental Ancestry Group, Genome-Wide Association Study, Cells, Cultured, Polymorphism, Single Nucleotide, Developmental Biology, Biological Sciences, Medical and Health Sciences
Abstract

To dissect the genetic architecture of blood pressure and assess effects on target organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry, and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure-associated loci, of which 17 were new; 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target organ damage in multiple tissues but with minor effects in the kidney. Our findings expand current knowledge of blood pressure-related pathways and highlight tissues beyond the classical renal system in blood pressure regulation.

Published
2016

27. Author Correction: Enhanced NF-κB signaling in type-2 dendritic cells at baseline predicts non-response to adalimumab in psoriasis

Author

Andres-Ejarque, Rosa, Ale, Hira Bahadur, Grys, Katarzyna, Tosi, Isabella, Solanky, Shane, Ainali, Chrysanthi, Catak, Zeynep, Sreeneebus, Hemawtee, Saklatvala, Jake, Dand, Nick, de Rinaldis, Emanuele, Chapman, Anna, Nestle, Frank O., Barnes, Michael R., Warren, Richard B., Reynolds, Nick J., Griffiths, Christopher E. M., Barker, Jonathan N., Smith, Catherine H., and Di Meglio, Paola

Published
2021
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28. Enhanced NF-κB signaling in type-2 dendritic cells at baseline predicts non-response to adalimumab in psoriasis

Author

Andres-Ejarque, Rosa, Ale, Hira Bahadur, Grys, Katarzyna, Tosi, Isabella, Solanky, Shane, Ainali, Chrysanthi, Catak, Zeynep, Sreeneebus, Hemawtee, Saklatvala, Jake, Dand, Nick, de Rinaldis, Emanuele, Chapman, Anna, Nestle, Frank O., Barnes, Michael R., Warren, Richard B., Reynolds, Nick J., Griffiths, Christopher E. M., Barker, Jonathan N., Smith, Catherine H., and Di Meglio, Paola

Published
2021
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31. Psychiatric genome-wide association study analyses implicate neuronal, immune and histone pathways

Author

O'Dushlaine, Colm, Rossin, Lizzy, Lee, Phil H, Duncan, Laramie, Parikshak, Neelroop N, Newhouse, Stephen, Ripke, Stephan, Neale, Benjamin M, Purcell, Shaun M, Posthuma, Danielle, Nurnberger, John I, Lee, S Hong, Faraone, Stephen V, Perlis, Roy H, Mowry, Bryan J, Thapar, Anita, Goddard, Michael E, Witte, John S, Absher, Devin, Agartz, Ingrid, Akil, Huda, Amin, Farooq, Andreassen, Ole A, Anjorin, Adebayo, Anney, Richard, Anttila, Verneri, Arking, Dan E, Asherson, Philip, Azevedo, Maria H, Backlund, Lena, Badner, Judith A, Bailey, Anthony J, Banaschewski, Tobias, Barchas, Jack D, Barnes, Michael R, Barrett, Thomas B, Bass, Nicholas, Battaglia, Agatino, Bauer, Michael, Bayes, Monica, Bellivier, Frank, Bergen, Sarah E, Berrettini, Wade, Betancur, Catalina, Bettecken, Thomas, Biederman, Joseph, Binder, Elisabeth B, Black, Donald W, Blackwood, Douglas HR, Bloss, Cinnamon S, Boehnke, Michael, Boomsma, Dorret I, Breuer, Rene, Bruggeman, Richard, Cormican, Paul, Buccola, Nancy G, Buitelaar, Jan K, Bunney, William E, Buxbaum, Joseph D, Byerley, William F, Byrne, Enda M, Caesar, Sian, Cahn, Wiepke, Cantor, Rita M, Casas, Miguel, Chakravarti, Aravinda, Chambert, Kimberly, Choudhury, Khalid, Cichon, Sven, Mattheisen, Manuel, Cloninger, C Robert, Collier, David A, Cook, Edwin H, Coon, Hilary, Cormand, Bru, Corvin, Aiden, Coryell, William H, Craig, David W, Craig, Ian W, Crosbie, Jennifer, Cuccaro, Michael L, Curtis, David, Czamara, Darina, Datta, Susmita, Dawson, Geraldine, Day, Richard, De Geus, Eco J, Degenhardt, Franziska, Djurovic, Srdjan, Donohoe, Gary J, Doyle, Alysa E, Duan, Jubao, Dudbridge, Frank, Duketis, Eftichia, Ebstein, Richard P, Edenberg, Howard J, Elia, Josephine, Ennis, Sean, Etain, Bruno, and Fanous, Ayman

Subjects
Human Genome, Brain Disorders, Serious Mental Illness, Schizophrenia, Genetics, Depression, Mental Health, Aetiology, 2.1 Biological and endogenous factors, Mental health, Good Health and Well Being, Brain, Databases, Genetic, Genetic Predisposition to Disease, Genome-Wide Association Study, Histones, Humans, Mental Disorders, Signal Transduction, Network and Pathway Analysis Subgroup of Psychiatric Genomics Consortium, Neurosciences, Psychology, Cognitive Sciences, Neurology & Neurosurgery
Abstract

Genome-wide association studies (GWAS) of psychiatric disorders have identified multiple genetic associations with such disorders, but better methods are needed to derive the underlying biological mechanisms that these signals indicate. We sought to identify biological pathways in GWAS data from over 60,000 participants from the Psychiatric Genomics Consortium. We developed an analysis framework to rank pathways that requires only summary statistics. We combined this score across disorders to find common pathways across three adult psychiatric disorders: schizophrenia, major depression and bipolar disorder. Histone methylation processes showed the strongest association, and we also found statistically significant evidence for associations with multiple immune and neuronal signaling pathways and with the postsynaptic density. Our study indicates that risk variants for psychiatric disorders aggregate in particular biological pathways and that these pathways are frequently shared between disorders. Our results confirm known mechanisms and suggest several novel insights into the etiology of psychiatric disorders.

Published
2015

32. HLA-C*06:02 genotype is a predictive biomarker of biologic treatment response in psoriasis

Author

Benham, Marilyn, Hussain, Sagair, Kirby, Brian, Lawson, Linda, McElhone, Kathleen, Ormerod, Anthony, Owen, Caroline, Barnes, Michael R., Di Meglio, Paola, Emsley, Richard, Evans, Andrea, Payne, Katherine, Stocken, Deborah, Dand, Nick, Duckworth, Michael, Baudry, David, Russell, Alice, Curtis, Charles J., Lee, Sang Hyuck, Evans, Ian, Mason, Kayleigh J., Alsharqi, Ali, Becher, Gabrielle, Burden, A. David, Goodwin, Richard G., McKenna, Kevin, Murphy, Ruth, Perera, Gayathri K., Rotarescu, Radu, Wahie, Shyamal, Wright, Andrew, Reynolds, Nick J., Warren, Richard B., Griffiths, Christopher E.M., Smith, Catherine H., Simpson, Michael A., and Barker, Jonathan N.

Published
2019
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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 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, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Pharmacogenetics, Polymorphism, Single Nucleotide, Cholesterol, LDL, Genome-Wide Association Study, Cholesterol, LDL, Polymorphism, Single Nucleotide
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

38. Pathway and network-based analysis of genome-wide association studies in multiple sclerosis

Author

Baranzini, Sergio E, Galwey, Nicholas W, Wang, Joanne, Khankhanian, Pouya, Lindberg, Raija, Pelletier, Daniel, Wu, Wen, Uitdehaag, Bernard MJ, Kappos, Ludwig, Consortium, GeneMSA, Polman, Chris H, Matthews, Paul M, Hauser, Stephen L, Gibson, Rachel A, Oksenberg, Jorge R, and Barnes, Michael R

Subjects
Multiple Sclerosis, Prevention, Brain Disorders, Neurosciences, Autoimmune Disease, Genetics, Neurodegenerative, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Neurological, Female, Gene Regulatory Networks, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Polymorphism, Single Nucleotide, Signal Transduction, GeneMSA Consortium, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Genome-wide association studies (GWAS) testing several hundred thousand SNPs have been performed in multiple sclerosis (MS) and other complex diseases. Typically, the number of markers in which the evidence for association exceeds the genome-wide significance threshold is very small, and markers that do not exceed this threshold are generally neglected. Classical statistical analysis of these datasets in MS revealed genes with known immunological functions. However, many of the markers showing modest association may represent false negatives. We hypothesize that certain combinations of genes flagged by these markers can be identified if they belong to a common biological pathway. Here we conduct a pathway-oriented analysis of two GWAS in MS that takes into account all SNPs with nominal evidence of association (P < 0.05). Gene-wise P-values were superimposed on a human protein interaction network and searches were conducted to identify sub-networks containing a higher proportion of genes associated with MS than expected by chance. These sub-networks, and others generated at random as a control, were categorized for membership of biological pathways. GWAS from eight other diseases were analyzed to assess the specificity of the pathways identified. In the MS datasets, we identified sub-networks of genes from several immunological pathways including cell adhesion, communication and signaling. Remarkably, neural pathways, namely axon-guidance and synaptic potentiation, were also over-represented in MS. In addition to the immunological pathways previously identified, we report here for the first time the potential involvement of neural pathways in MS susceptibility.

Published
2009

42. 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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43. Genome-wide association study of response to methotrexate in early rheumatoid arthritis patients

Author

Taylor, John C., Bongartz, Tim, Massey, Jonathan, Mifsud, Borbala, Spiliopoulou, Athina, Scott, Ian C., Wang, Jianmei, Morgan, Michael, Plant, Darren, Colombo, Marco, Orchard, Peter, Twigg, Sarah, McInnes, Iain B., Porter, Duncan, Freeston, Jane E., Nam, Jackie L., Cordell, Heather J., Isaacs, John D., Strathdee, Jenna L., Arnett, Donna, de Hair, Maria J. H., Tak, Paul P., Aslibekyan, Stella, van Vollenhoven, Ronald F., Padyukov, Leonid, Bridges, S. Louis, Pitzalis, Costantino, Cope, Andrew P., Verstappen, Suzanne M. M., Emery, Paul, Barnes, Michael R., Agakov, Felix, McKeigue, Paul, Mushiroda, Taisei, Kubo, Michiaki, Weinshilboum, Richard, Barton, Anne, Morgan, Ann W., Barrett, Jennifer H., on behalf of the MATURA, and PAMERA, and Consortia

Published
2018
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45. Ethnic differences in early onset multimorbidity and associations with health service use, long-term prescribing, years of life lost, and mortality: an observational study using person-level clustering in the UK Clinical Practice Research Datalink

Author

Eto, Fabiola, primary, Samuel, Miriam, additional, Henkin, Rafael, additional, Mahesh, Meera, additional, Ahmad, Tahania, additional, Angdembe, Alisha, additional, McAllister-Williams, R. Hamish, additional, Missier, Paolo, additional, Reynolds, Nick J, additional, Barnes, Michael R, additional, Hull, Sally, additional, Finer, Sarah, additional, and Mathur, Rohini, additional

Published
2023
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46. Investigating Collaborative Data Practices: a Case Study on Artificial Intelligence for Healthcare Research

Author

Henkin, Rafael, Remfry, Elizabeth, Reynolds, Duncan J., Clinch, Megan, Barnes, Michael R., Henkin, Rafael, Remfry, Elizabeth, Reynolds, Duncan J., Clinch, Megan, and Barnes, Michael R.

Abstract

Developing artificial intelligence (AI) tools for healthcare is a collaborative effort, bringing data scientists, clinicians, patients and other disciplines together. In this paper, we explore the collaborative data practices of research consortia tasked with applying AI tools to understand and manage multiple long-term conditions in the UK. Through an inductive thematic analysis of 13 semi-structured interviews with participants of these consortia, we aimed to understand how collaboration happens based on the tools used, communication processes and settings, as well as the conditions and obstacles for collaborative work. Our findings reveal the adaptation of tools that are used for sharing knowledge and the tailoring of information based on the audience, particularly those from a clinical or patient perspective. Limitations on the ability to do this were also found to be imposed by the use of electronic healthcare records and access to datasets. We identified meetings as the key setting for facilitating exchanges between disciplines and allowing for the blending and creation of knowledge. Finally, we bring to light the conditions needed to facilitate collaboration and discuss how some of the challenges may be navigated in future work., Comment: 17 pages

Published
2023

47. Health and population effects of rare gene knockouts in adult humans with related parents

Author

Narasimhan, Vagheesh M., Hunt, Karen A., Mason, Dan, Baker, Christopher L., Karczewski, Konrad J., Barnes, Michael R., Barnett, Anthony H., Bates, Chris, Bellary, Srikanth, Bockett, Nicholas A., Giorda, Kristina, Griffiths, Christopher J., Hemingway, Harry, Jia, Zhilong, Kelly, M. Ann, Khawaja, Hajrah A., Lek, Monkol, McCarthy, Shane, McEachan, Rosie, O'Donnell-Luria, Anne, Paigen, Kenneth, Parisinos, Constantinos A., Sheridan, Eamonn, Southgate, Laura, Tee, Louise, Thomas, Mark, Xue, Yali, Schnall-Levin, Michael, Petkov, Petko M., Tyler-Smith, Chris, Maher, Eamonn R., Trembath, Richard C., MacArthur, Daniel G., Wright, John, Durbin, Richard, and van Heel, David A.

Published
2016

48. Genome-Wide Analysis of Left Ventricular Image-Derived Phenotypes Identifies Fourteen Loci Associated With Cardiac Morphogenesis and Heart Failure Development

Author

Aung, Nay, Vargas, Jose D., Yang, Chaojie, Cabrera, Claudia P., Warren, Helen R., Fung, Kenneth, Tzanis, Evan, Barnes, Michael R., Rotter, Jerome I., Taylor, Kent D., Manichaikul, Ani W., Lima, Joao A.C., Bluemke, David A., Piechnik, Stefan K., Neubauer, Stefan, Munroe, Patricia B., and Petersen, Steffen E.

Published
2019
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49. Local delivery of nitric oxide prevents endothelial dysfunction in periodontitis

Author

Fernandes, Daniel, primary, Khambata, Rayomand S., additional, Massimo, Gianmichele, additional, Ruivo, Ernesto, additional, Gee, Lorna C., additional, Foster, Julie, additional, Goddard, Alison, additional, Curtis, Mike, additional, Barnes, Michael R., additional, Wade, William G., additional, Godec, Thomas, additional, Orlandi, Marco, additional, D’Aiuto, Francesco, additional, and Ahluwalia, Amrita, additional

Published
2023
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50. Bayesian network analysis of panomic biological big data identifies the importance of triglyceride-rich LDL in atherosclerosis development

Author

Voros, Szilard, primary, Bansal, Aruna T., additional, Barnes, Michael R., additional, Narula, Jagat, additional, Maurovich-Horvat, Pal, additional, Vazquez, Gustavo, additional, Marvasty, Idean B., additional, Brown, Bradley O., additional, Voros, Isaac D., additional, Harris, William, additional, Voros, Viktor, additional, Dayspring, Thomas, additional, Neff, David, additional, Greenfield, Alex, additional, Furchtgott, Leon, additional, Church, Bruce, additional, Runge, Karl, additional, Khalil, Iya, additional, Hayete, Boris, additional, Lucero, Diego, additional, Remaley, Alan T., additional, and Newton, Roger S., additional

Published
2023
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