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14 results on '"Perry, Mandy"'

1. HLA-DQA1*05 Carriage Associated With Development of Anti-Drug Antibodies to Infliximab and Adalimumab in Patients With Crohn’s Disease

Author

Patel, Vinod, Mazhar, Zia, Saich, Rebecca, Colleypriest, Ben, Tham, Tony C, Iqbal, Tariq H, Kaushik, Vishal, Murugesan, Senthil, Singh, Salil, Weaver, Sean, Preston, Cathryn, Butt, Assad, Smith, Melissa, Basude, Dharamveer, Beale, Amanda, Langlands, Sarah, Direkze, Natalie, Parkes, Miles, Torrente, Franco, De La Revella Negro, Juan, Ewen MacDonald, Chris, Evans, Stephen M, Gunasekera, Anton V J, Thakur, Alka, Elphick, David, Shenoy, Achuth, Nwokolo, Chuka U, Dhar, Anjan, Cole, Andrew T, Agrawal, Anurag, Bridger, Stephen, Doherty, Julie, Cooper, Sheldon C, de Silva, Shanika, Mowat, Craig, Mayhead, Phillip, Lees, Charlie, Jones, Gareth, Ahmad, Tariq, Hart, James W, Gaya, Daniel R, Russell, Richard K, Gervais, Lisa, Dunckley, Paul, Mahmood, Tariq, Banim, Paul J R, Sonwalkar, Sunil, Ghosh, Deb, Phillips, Rosemary H, Azaz, Amer, Sebastian, Shaji, Shenderey, Richard, Armstrong, Lawrence, Bell, Claire, Hariraj, Radhakrishnan, Matthews, Helen, Jafferbhoy, Hasnain, Selinger, Christian P, Zamvar, Veena, De Caestecker, John S, Willmott, Anne, Miller, Richard, Sathish Babu, Palani, Tzivinikos, Christos, Bloom, Stuart L, Chung-Faye, Guy, Croft, Nicholas M, Fell, John ME, Harbord, Marcus, Hart, Ailsa, Hope, Ben, Irving, Peter M, Lindsay, James O, Mawdsley, Joel E, McNair, Alistair, Monahan, Kevin J, Murray, Charles D, Orchard, Timothy, Paul, Thankam, Pollok, Richard, Shah, Neil, Bouri, Sonia, Johnson, Matt W, Modi, Anita, Dawa Kabiru, Kasamu, Baburajan, B K, Bhaduri, Bim, Adebayo Fagbemi, Andrew, Levison, Scott, Limdi, Jimmy K, Watts, Gill, Foley, Stephen, Ramadas, Arvind, MacFaul, George, Mansfield, John, Grellier, Leonie, Morris, Mary-Anne, Tremelling, Mark, Hawkey, Chris, Kirkham, Sian, Charlton, Charles PJ, Rodrigues, Astor, Simmons, Alison, Lewis, Stephen J, Snook, Jonathon, Tighe, Mark, Goggin, Patrick M, De Silva, Aminda N, Lal, Simon, Smith, Mark S, Panter, Simon, Cummings, Fraser, Dharmisari, Suranga, Carter, Martyn, Watts, David, Mahmood, Zahid, McLain, Bruce, Sen, Sandip, Pigott, Anna J, Hobday, David, Wesley, Emma, Johnston, Richard, Edwards, Cathryn, Beckly, John, Vani, Deven, Ramakrishnan, Subramaniam, Chaudhary, Rakesh, Trudgill, Nigel J, Cooney, Rachel, Bell, Andy, Prasad, Neeraj, Gordon, John N, Brookes, Matthew J, Li, Andy, Gore, Stephen, Sazonovs, Aleksejs, Kennedy, Nicholas A., Moutsianas, Loukas, Heap, Graham A., Rice, Daniel L., Reppell, Mark, Bewshea, Claire M., Chanchlani, Neil, Walker, Gareth J., Perry, Mandy H., McDonald, Timothy J., Lees, Charlie W., Cummings, J.R. Fraser, Mansfield, John C., Irving, Peter M., Barrett, Jeffrey C., McGovern, Dermot, Goodhand, James R., and Anderson, Carl A.

Published
2020
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2. Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: descriptive characteristics of the epidemiological studies within the IMI DIRECT Consortium

Author

Koivula, Robert W., Forgie, Ian M., Kurbasic, Azra, Viñuela, Ana, Heggie, Alison, Giordano, Giuseppe N., Hansen, Tue H., Hudson, Michelle, Koopman, Anitra D. M., Rutters, Femke, Siloaho, Maritta, Allin, Kristine H., Brage, Søren, Brorsson, Caroline A., Dawed, Adem Y., De Masi, Federico, Groves, Christopher J., Kokkola, Tarja, Mahajan, Anubha, Perry, Mandy H., Rauh, Simone P., Ridderstråle, Martin, Teare, Harriet J. A., Thomas, E. Louise, Tura, Andrea, Vestergaard, Henrik, White, Tom, Adamski, Jerzy, Bell, Jimmy D., Beulens, Joline W., Brunak, Søren, Dermitzakis, Emmanouil T., Froguel, Philippe, Frost, Gary, Gupta, Ramneek, Hansen, Torben, Hattersley, Andrew, Jablonka, Bernd, Kaye, Jane, Laakso, Markku, McDonald, Timothy J., Pedersen, Oluf, Schwenk, Jochen M., Pavo, Imre, Mari, Andrea, McCarthy, Mark I., Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, Franks, Paul W., and for the IMI DIRECT Consortium

Published
2019
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3. Discovery of drug–omics associations in type 2 diabetes with generative deep-learning models

Author

Allesøe, Rosa Lundbye, Lundgaard, Agnete Troen, Hernández Medina, Ricardo, Aguayo-Orozco, Alejandro, Johansen, Joachim, Nissen, Jakob Nybo, Brorsson, Caroline, Mazzoni, Gianluca, Niu, Lili, Biel, Jorge Hernansanz, Brasas, Valentas, Webel, Henry, Benros, Michael Eriksen, Pedersen, Anders Gorm, Chmura, Piotr Jaroslaw, Jacobsen, Ulrik Plesner, Mari, Andrea, Koivula, Robert, Mahajan, Anubha, Vinuela, Ana, Tajes, Juan Fernandez, Sharma, Sapna, Haid, Mark, Hong, Mun-Gwan, Musholt, Petra B., De Masi, Federico, Vogt, Josef, Pedersen, Helle Krogh, Gudmundsdottir, Valborg, Jones, Angus, Kennedy, Gwen, Bell, Jimmy, Thomas, E. Louise, Frost, Gary, Thomsen, Henrik, Hansen, Elizaveta, Hansen, Tue Haldor, Vestergaard, Henrik, Muilwijk, Mirthe, Blom, Marieke T., ‘t Hart, Leen M., Pattou, Francois, Raverdy, Violeta, Brage, Soren, Kokkola, Tarja, Heggie, Alison, McEvoy, Donna, Mourby, Miranda, Kaye, Jane, Hattersley, Andrew, McDonald, Timothy, Ridderstråle, Martin, Walker, Mark, Forgie, Ian, Giordano, Giuseppe N., Pavo, Imre, Ruetten, Hartmut, Pedersen, Oluf, Hansen, Torben, Dermitzakis, Emmanouil, Franks, Paul W., Schwenk, Jochen M., Adamski, Jerzy, McCarthy, Mark I., Pearson, Ewan, Banasik, Karina, Rasmussen, Simon, Brunak, Søren, Froguel, Philippe, Thomas, Cecilia Engel, Häussler, Ragna S., Beulens, Joline, Rutters, Femke, Nijpels, Giel, van Oort, Sabine, Groeneveld, Lenka, Elders, Petra, Giorgino, Toni, Rodriquez, Marianne, Nice, Rachel, Perry, Mandy, Bianzano, Susanna, Graefe-Mody, Ulrike, Hennige, Anita, Grempler, Rolf, Baum, Patrick, Stærfeldt, Hans Henrik, Shah, Nisha, Teare, Harriet, Ehrhardt, Beate, Tillner, Joachim, Dings, Christiane, Lehr, Thorsten, Scherer, Nina, Sihinevich, Iryna, Cabrelli, Louise, Loftus, Heather, Bizzotto, Roberto, Tura, Andrea, Dekkers, Koen, Allesøe, Rosa Lundbye, Lundgaard, Agnete Troen, Hernández Medina, Ricardo, Aguayo-Orozco, Alejandro, Johansen, Joachim, Nissen, Jakob Nybo, Brorsson, Caroline, Mazzoni, Gianluca, Niu, Lili, Biel, Jorge Hernansanz, Brasas, Valentas, Webel, Henry, Benros, Michael Eriksen, Pedersen, Anders Gorm, Chmura, Piotr Jaroslaw, Jacobsen, Ulrik Plesner, Mari, Andrea, Koivula, Robert, Mahajan, Anubha, Vinuela, Ana, Tajes, Juan Fernandez, Sharma, Sapna, Haid, Mark, Hong, Mun-Gwan, Musholt, Petra B., De Masi, Federico, Vogt, Josef, Pedersen, Helle Krogh, Gudmundsdottir, Valborg, Jones, Angus, Kennedy, Gwen, Bell, Jimmy, Thomas, E. Louise, Frost, Gary, Thomsen, Henrik, Hansen, Elizaveta, Hansen, Tue Haldor, Vestergaard, Henrik, Muilwijk, Mirthe, Blom, Marieke T., ‘t Hart, Leen M., Pattou, Francois, Raverdy, Violeta, Brage, Soren, Kokkola, Tarja, Heggie, Alison, McEvoy, Donna, Mourby, Miranda, Kaye, Jane, Hattersley, Andrew, McDonald, Timothy, Ridderstråle, Martin, Walker, Mark, Forgie, Ian, Giordano, Giuseppe N., Pavo, Imre, Ruetten, Hartmut, Pedersen, Oluf, Hansen, Torben, Dermitzakis, Emmanouil, Franks, Paul W., Schwenk, Jochen M., Adamski, Jerzy, McCarthy, Mark I., Pearson, Ewan, Banasik, Karina, Rasmussen, Simon, Brunak, Søren, Froguel, Philippe, Thomas, Cecilia Engel, Häussler, Ragna S., Beulens, Joline, Rutters, Femke, Nijpels, Giel, van Oort, Sabine, Groeneveld, Lenka, Elders, Petra, Giorgino, Toni, Rodriquez, Marianne, Nice, Rachel, Perry, Mandy, Bianzano, Susanna, Graefe-Mody, Ulrike, Hennige, Anita, Grempler, Rolf, Baum, Patrick, Stærfeldt, Hans Henrik, Shah, Nisha, Teare, Harriet, Ehrhardt, Beate, Tillner, Joachim, Dings, Christiane, Lehr, Thorsten, Scherer, Nina, Sihinevich, Iryna, Cabrelli, Louise, Loftus, Heather, Bizzotto, Roberto, Tura, Andrea, and Dekkers, Koen

Abstract

The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug–omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug–drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities., Correction in DOI 10.1038/s41587-023-01805-9QC 20230626

Published
2023
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4. Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits

Author

Brown, Andrew A., Fernandez-Tajes, Juan J., Hong, Mun gwan, Brorsson, Caroline A., Koivula, Robert W., Davtian, David, Dupuis, Théo, Sartori, Ambra, Michalettou, Theodora Dafni, Forgie, Ian M., Adam, Jonathan, Allin, Kristine H., Caiazzo, Robert, Cederberg, Henna, De Masi, Federico, Elders, Petra J.M., Giordano, Giuseppe N., Haid, Mark, Hansen, Torben, Hansen, Tue H., Hattersley, Andrew T., Heggie, Alison J., Howald, Cédric, Jones, Angus G., Kokkola, Tarja, Laakso, Markku, Mahajan, Anubha, Mari, Andrea, McDonald, Timothy J., McEvoy, Donna, Mourby, Miranda, Musholt, Petra B., Nilsson, Birgitte, Pattou, Francois, Penet, Deborah, Raverdy, Violeta, Ridderstråle, Martin, Romano, Luciana, Rutters, Femke, Sharma, Sapna, Teare, Harriet, ‘t Hart, Leen, Tsirigos, Konstantinos D., Vangipurapu, Jagadish, Vestergaard, Henrik, Brunak, Søren, Franks, Paul W., Frost, Gary, Grallert, Harald, Jablonka, Bernd, McCarthy, Mark I., Pavo, Imre, Pedersen, Oluf, Ruetten, Hartmut, Walker, Mark, Adragni, Kofi, Allesøe, Rosa Lundbye L., Artati, Anna A., Arumugam, Manimozhiyan, Atabaki-Pasdar, Naeimeh, Baltauss, Tania, Banasik, Karina, Barnett, Anna L., Baum, Patrick, Bell, Jimmy D., Beulens, Joline W., Bianzano, Susanna B., Bizzotto, Roberto, Bonnefond, Amelie, Cabrelli, Louise, Dale, Matilda, Dawed, Adem Y., de Preville, Nathalie, Dekkers, Koen F., Deshmukh, Harshal A., Dings, Christiane, Donnelly, Louise, Dutta, Avirup, Ehrhardt, Beate, Engelbrechtsen, Line, Eriksen, Rebeca, Fan, Yong, Ferrer, Jorge, Fitipaldi, Hugo, Forman, Annemette, Fritsche, Andreas, Froguel, Philippe, Gassenhuber, Johann, Gough, Stephen, Graefe-Mody, Ulrike, Grempler, Rolf, Groeneveld, Lenka, Groop, Leif, Gudmundsdóttir, Valborg, Gupta, Ramneek, Hennige, Anita M.H., Hill, Anita V., Holl, Reinhard W., Hudson, Michelle, Jacobsen, Ulrik Plesner, Jennison, Christopher, Johansen, Joachim, Jonsson, Anna, Karaderi, Tugce, Kaye, Jane, Kennedy, Gwen, Klintenberg, Maria, Kuulasmaa, Teemu, Lehr, Thorsten, Loftus, Heather, Lundgaard, Agnete Troen T., Mazzoni, Gianluca, McRobert, Nicky, McVittie, Ian, Nice, Rachel, Nicolay, Claudia, Nijpels, Giel, Palmer, Colin N., Pedersen, Helle K., Perry, Mandy H., Pomares-Millan, Hugo, Prehn, Cornelia P., Ramisch, Anna, Rasmussen, Simon, Robertson, Neil, Rodriquez, Marianne, Sackett, Peter, Scherer, Nina, Shah, Nisha, Sihinevich, Iryna, Slieker, Roderick C., Sondertoft, Nadja B., Steckel-Hamann, Birgit, Thomas, Melissa K., Thomas, Cecilia Engel E., Thomas, Elizabeth Louise L., Thorand, Barbara, Thorne, Claire E., Tillner, Joachim, Tura, Andrea, Uhlen, Mathias, van Leeuwen, Nienke, van Oort, Sabine, Verkindt, Helene, Vogt, Josef, Wad Sackett, Peter W., Wesolowska-Andersen, Agata, Whitcher, Brandon, White, Margaret W., Adamski, Jerzy, Schwenk, Jochen M., Pearson, Ewan R., Dermitzakis, Emmanouil T., Viñuela, Ana, Brown, Andrew A., Fernandez-Tajes, Juan J., Hong, Mun gwan, Brorsson, Caroline A., Koivula, Robert W., Davtian, David, Dupuis, Théo, Sartori, Ambra, Michalettou, Theodora Dafni, Forgie, Ian M., Adam, Jonathan, Allin, Kristine H., Caiazzo, Robert, Cederberg, Henna, De Masi, Federico, Elders, Petra J.M., Giordano, Giuseppe N., Haid, Mark, Hansen, Torben, Hansen, Tue H., Hattersley, Andrew T., Heggie, Alison J., Howald, Cédric, Jones, Angus G., Kokkola, Tarja, Laakso, Markku, Mahajan, Anubha, Mari, Andrea, McDonald, Timothy J., McEvoy, Donna, Mourby, Miranda, Musholt, Petra B., Nilsson, Birgitte, Pattou, Francois, Penet, Deborah, Raverdy, Violeta, Ridderstråle, Martin, Romano, Luciana, Rutters, Femke, Sharma, Sapna, Teare, Harriet, ‘t Hart, Leen, Tsirigos, Konstantinos D., Vangipurapu, Jagadish, Vestergaard, Henrik, Brunak, Søren, Franks, Paul W., Frost, Gary, Grallert, Harald, Jablonka, Bernd, McCarthy, Mark I., Pavo, Imre, Pedersen, Oluf, Ruetten, Hartmut, Walker, Mark, Adragni, Kofi, Allesøe, Rosa Lundbye L., Artati, Anna A., Arumugam, Manimozhiyan, Atabaki-Pasdar, Naeimeh, Baltauss, Tania, Banasik, Karina, Barnett, Anna L., Baum, Patrick, Bell, Jimmy D., Beulens, Joline W., Bianzano, Susanna B., Bizzotto, Roberto, Bonnefond, Amelie, Cabrelli, Louise, Dale, Matilda, Dawed, Adem Y., de Preville, Nathalie, Dekkers, Koen F., Deshmukh, Harshal A., Dings, Christiane, Donnelly, Louise, Dutta, Avirup, Ehrhardt, Beate, Engelbrechtsen, Line, Eriksen, Rebeca, Fan, Yong, Ferrer, Jorge, Fitipaldi, Hugo, Forman, Annemette, Fritsche, Andreas, Froguel, Philippe, Gassenhuber, Johann, Gough, Stephen, Graefe-Mody, Ulrike, Grempler, Rolf, Groeneveld, Lenka, Groop, Leif, Gudmundsdóttir, Valborg, Gupta, Ramneek, Hennige, Anita M.H., Hill, Anita V., Holl, Reinhard W., Hudson, Michelle, Jacobsen, Ulrik Plesner, Jennison, Christopher, Johansen, Joachim, Jonsson, Anna, Karaderi, Tugce, Kaye, Jane, Kennedy, Gwen, Klintenberg, Maria, Kuulasmaa, Teemu, Lehr, Thorsten, Loftus, Heather, Lundgaard, Agnete Troen T., Mazzoni, Gianluca, McRobert, Nicky, McVittie, Ian, Nice, Rachel, Nicolay, Claudia, Nijpels, Giel, Palmer, Colin N., Pedersen, Helle K., Perry, Mandy H., Pomares-Millan, Hugo, Prehn, Cornelia P., Ramisch, Anna, Rasmussen, Simon, Robertson, Neil, Rodriquez, Marianne, Sackett, Peter, Scherer, Nina, Shah, Nisha, Sihinevich, Iryna, Slieker, Roderick C., Sondertoft, Nadja B., Steckel-Hamann, Birgit, Thomas, Melissa K., Thomas, Cecilia Engel E., Thomas, Elizabeth Louise L., Thorand, Barbara, Thorne, Claire E., Tillner, Joachim, Tura, Andrea, Uhlen, Mathias, van Leeuwen, Nienke, van Oort, Sabine, Verkindt, Helene, Vogt, Josef, Wad Sackett, Peter W., Wesolowska-Andersen, Agata, Whitcher, Brandon, White, Margaret W., Adamski, Jerzy, Schwenk, Jochen M., Pearson, Ewan R., Dermitzakis, Emmanouil T., and Viñuela, Ana

Abstract

We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.

Published
2023

6. Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: rationale and design of the epidemiological studies within the IMI DIRECT Consortium

Author

Koivula, Robert W., Heggie, Alison, Barnett, Anna, Cederberg, Henna, Hansen, Tue H., Koopman, Anitra D., Ridderstråle, Martin, Rutters, Femke, Vestergaard, Henrik, Gupta, Ramneek, Herrgård, Sanna, Heymans, Martijn W., Perry, Mandy H., Rauh, Simone, Siloaho, Maritta, Teare, Harriet J. A., Thorand, Barbara, Bell, Jimmy, Brunak, Søren, Frost, Gary, Jablonka, Bernd, Mari, Andrea, McDonald, Tim J., Dekker, Jacqueline M., Hansen, Torben, Hattersley, Andrew, Laakso, Markku, Pedersen, Oluf, Koivisto, Veikko, Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, Franks, Paul W., and for the DIRECT Consortium

Published
2014
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7. Post-load glucose subgroups and associated metabolic traits in individuals with type 2 diabetes:An IMI-DIRECT study

Author

Obura, Morgan, Beulens, Joline W.J., Slieker, Roderick, Koopman, Anitra D.M., Hoekstra, Trynke, Nijpels, Giel, Elders, Petra, Koivula, Robert W., Kurbasic, Azra, Laakso, Markku, Hansen, Tue H., Ridderstråle, Martin, Hansen, Torben, Pavo, Imre, Forgie, Ian, Jablonka, Bernd, Ruetten, Hartmut, Mari, Andrea, McCarthy, Mark I., Walker, Mark, Heggie, Alison, McDonald, Timothy J., Perry, Mandy H., de Masi, Federico, Brunak, Søren, Mahajan, Anubha, Giordano, Giuseppe N., Kokkola, Tarja, Dermitzakis, Emmanouil, Viñuela, Ana, Pedersen, Oluf, Schwenk, Jochen M., Adamski, Jurek, Teare, Harriet J.A., Pearson, Ewan R., Franks, Paul W., Hart, Leen M.t., Rutters, Femke, Obura, Morgan, Beulens, Joline W.J., Slieker, Roderick, Koopman, Anitra D.M., Hoekstra, Trynke, Nijpels, Giel, Elders, Petra, Koivula, Robert W., Kurbasic, Azra, Laakso, Markku, Hansen, Tue H., Ridderstråle, Martin, Hansen, Torben, Pavo, Imre, Forgie, Ian, Jablonka, Bernd, Ruetten, Hartmut, Mari, Andrea, McCarthy, Mark I., Walker, Mark, Heggie, Alison, McDonald, Timothy J., Perry, Mandy H., de Masi, Federico, Brunak, Søren, Mahajan, Anubha, Giordano, Giuseppe N., Kokkola, Tarja, Dermitzakis, Emmanouil, Viñuela, Ana, Pedersen, Oluf, Schwenk, Jochen M., Adamski, Jurek, Teare, Harriet J.A., Pearson, Ewan R., Franks, Paul W., Hart, Leen M.t., and Rutters, Femke

Abstract

Aim Subclasses of different glycaemic disturbances could explain the variation in characteristics of individuals with type 2 diabetes (T2D). We aimed to examine the association between subgroups based on their glucose curves during a five-point mixed-meal tolerance test (MMT) and metabolic traits at baseline and glycaemic deterioration in individuals with T2D. Methods The study included 787 individuals with newly diagnosed T2D from the Diabetes Research on Patient Stratification (IMI-DIRECT) Study. Latent class trajectory analysis (LCTA) was used to identify distinct glucose curve subgroups during a five-point MMT. Using general linear models, these subgroups were associated with metabolic traits at baseline and after 18 months of follow up, adjusted for potential confounders. Results At baseline, we identified three glucose curve subgroups, labelled in order of increasing glucose peak levels as subgroup 1–3. Individuals in subgroup 2 and 3 were more likely to have higher levels of HbA1c, triglycerides and BMI at baseline, compared to those in subgroup 1. At 18 months (n = 651), the beta coefficients (95% CI) for change in HbA1c (mmol/mol) increased across subgroups with 0.37 (-0.18–1.92) for subgroup 2 and 1.88 (-0.08–3.85) for subgroup 3, relative to subgroup 1. The same trend was observed for change in levels of triglycerides and fasting glucose. Conclusions Different glycaemic profiles with different metabolic traits and different degrees of subsequent glycaemic deterioration can be identified using data from a frequently sampled mixed-meal tolerance test in individuals with T2D. Subgroups with the highest peaks had greater metabolic risk.

Published
2020

9. HLA-DQA1*05 Carriage Associated With Development of Anti-Drug Antibodies to Infliximab and Adalimumab in Patients With Crohn’s Disease

Author

Sazonovs, Aleksejs, primary, Kennedy, Nicholas A., additional, Moutsianas, Loukas, additional, Heap, Graham A., additional, Rice, Daniel L., additional, Reppell, Mark, additional, Bewshea, Claire M., additional, Chanchlani, Neil, additional, Walker, Gareth J., additional, Perry, Mandy H., additional, McDonald, Timothy J., additional, Lees, Charlie W., additional, Cummings, J.R. Fraser, additional, Parkes, Miles, additional, Mansfield, John C., additional, Irving, Peter M., additional, Barrett, Jeffrey C., additional, McGovern, Dermot, additional, Goodhand, James R., additional, Anderson, Carl A., additional, Ahmad, Tariq, additional, Patel, Vinod, additional, Mazhar, Zia, additional, Saich, Rebecca, additional, Colleypriest, Ben, additional, Tham, Tony C, additional, Iqbal, Tariq H, additional, Kaushik, Vishal, additional, Murugesan, Senthil, additional, Singh, Salil, additional, Weaver, Sean, additional, Preston, Cathryn, additional, Butt, Assad, additional, Smith, Melissa, additional, Basude, Dharamveer, additional, Beale, Amanda, additional, Langlands, Sarah, additional, Direkze, Natalie, additional, Torrente, Franco, additional, De La Revella Negro, Juan, additional, Ewen MacDonald, Chris, additional, Evans, Stephen M, additional, Gunasekera, Anton V J, additional, Thakur, Alka, additional, Elphick, David, additional, Shenoy, Achuth, additional, Nwokolo, Chuka U, additional, Dhar, Anjan, additional, Cole, Andrew T, additional, Agrawal, Anurag, additional, Bridger, Stephen, additional, Doherty, Julie, additional, Cooper, Sheldon C, additional, de Silva, Shanika, additional, Mowat, Craig, additional, Mayhead, Phillip, additional, Lees, Charlie, additional, Jones, Gareth, additional, Hart, James W, additional, Gaya, Daniel R, additional, Russell, Richard K, additional, Gervais, Lisa, additional, Dunckley, Paul, additional, Mahmood, Tariq, additional, Banim, Paul J R, additional, Sonwalkar, Sunil, additional, Ghosh, Deb, additional, Phillips, Rosemary H, additional, Azaz, Amer, additional, Sebastian, Shaji, additional, Shenderey, Richard, additional, Armstrong, Lawrence, additional, Bell, Claire, additional, Hariraj, Radhakrishnan, additional, Matthews, Helen, additional, Jafferbhoy, Hasnain, additional, Selinger, Christian P, additional, Zamvar, Veena, additional, De Caestecker, John S, additional, Willmott, Anne, additional, Miller, Richard, additional, Sathish Babu, Palani, additional, Tzivinikos, Christos, additional, Bloom, Stuart L, additional, Chung-Faye, Guy, additional, Croft, Nicholas M, additional, Fell, John ME, additional, Harbord, Marcus, additional, Hart, Ailsa, additional, Hope, Ben, additional, Irving, Peter M, additional, Lindsay, James O, additional, Mawdsley, Joel E, additional, McNair, Alistair, additional, Monahan, Kevin J, additional, Murray, Charles D, additional, Orchard, Timothy, additional, Paul, Thankam, additional, Pollok, Richard, additional, Shah, Neil, additional, Bouri, Sonia, additional, Johnson, Matt W, additional, Modi, Anita, additional, Dawa Kabiru, Kasamu, additional, Baburajan, B K, additional, Bhaduri, Bim, additional, Adebayo Fagbemi, Andrew, additional, Levison, Scott, additional, Limdi, Jimmy K, additional, Watts, Gill, additional, Foley, Stephen, additional, Ramadas, Arvind, additional, MacFaul, George, additional, Mansfield, John, additional, Grellier, Leonie, additional, Morris, Mary-Anne, additional, Tremelling, Mark, additional, Hawkey, Chris, additional, Kirkham, Sian, additional, Charlton, Charles PJ, additional, Rodrigues, Astor, additional, Simmons, Alison, additional, Lewis, Stephen J, additional, Snook, Jonathon, additional, Tighe, Mark, additional, Goggin, Patrick M, additional, De Silva, Aminda N, additional, Lal, Simon, additional, Smith, Mark S, additional, Panter, Simon, additional, Cummings, Fraser, additional, Dharmisari, Suranga, additional, Carter, Martyn, additional, Watts, David, additional, Mahmood, Zahid, additional, McLain, Bruce, additional, Sen, Sandip, additional, Pigott, Anna J, additional, Hobday, David, additional, Wesley, Emma, additional, Johnston, Richard, additional, Edwards, Cathryn, additional, Beckly, John, additional, Vani, Deven, additional, Ramakrishnan, Subramaniam, additional, Chaudhary, Rakesh, additional, Trudgill, Nigel J, additional, Cooney, Rachel, additional, Bell, Andy, additional, Prasad, Neeraj, additional, Gordon, John N, additional, Brookes, Matthew J, additional, Li, Andy, additional, and Gore, Stephen, additional

Published
2020
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10. Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes:descriptive characteristics of the epidemiological studies within the IMI DIRECT Consortium

Author

Koivula, Robert W, Forgie, Ian M, Kurbasic, Azra, Viñuela, Ana, Heggie, Alison, Giordano, Giuseppe N, Hansen, Tue H., Hudson, Michelle, Koopman, Anitra D M, Rutters, Femke, Siloaho, Maritta, Allin, Kristine H., Brage, Søren, Brorsson, Caroline A, Dawed, Adem Y, De Masi, Federico, Groves, Christopher J, Kokkola, Tarja, Mahajan, Anubha, Perry, Mandy H, Rauh, Simone P, Ridderstråle, Martin, Teare, Harriet J A, Thomas, E Louise, Tura, Andrea, Vestergaard, Henrik, White, Tom, Adamski, Jerzy, Bell, Jimmy D, Beulens, Joline W, Brunak, Søren, Dermitzakis, Emmanouil T, Froguel, Philippe, Frost, Gary, Gupta, Ramneek, Hansen, Torben, Hattersley, Andrew, Jablonka, Bernd, Kaye, Jane, Laakso, Markku, McDonald, Timothy J, Pedersen, Oluf, Schwenk, Jochen M, Pavo, Imre, Mari, Andrea, McCarthy, Mark I, Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, Franks, Paul W, Koivula, Robert W, Forgie, Ian M, Kurbasic, Azra, Viñuela, Ana, Heggie, Alison, Giordano, Giuseppe N, Hansen, Tue H., Hudson, Michelle, Koopman, Anitra D M, Rutters, Femke, Siloaho, Maritta, Allin, Kristine H., Brage, Søren, Brorsson, Caroline A, Dawed, Adem Y, De Masi, Federico, Groves, Christopher J, Kokkola, Tarja, Mahajan, Anubha, Perry, Mandy H, Rauh, Simone P, Ridderstråle, Martin, Teare, Harriet J A, Thomas, E Louise, Tura, Andrea, Vestergaard, Henrik, White, Tom, Adamski, Jerzy, Bell, Jimmy D, Beulens, Joline W, Brunak, Søren, Dermitzakis, Emmanouil T, Froguel, Philippe, Frost, Gary, Gupta, Ramneek, Hansen, Torben, Hattersley, Andrew, Jablonka, Bernd, Kaye, Jane, Laakso, Markku, McDonald, Timothy J, Pedersen, Oluf, Schwenk, Jochen M, Pavo, Imre, Mari, Andrea, McCarthy, Mark I, Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, and Franks, Paul W

Abstract

AIMS/HYPOTHESIS: Here, we describe the characteristics of the Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) epidemiological cohorts at baseline and follow-up examinations (18, 36 and 48 months of follow-up).METHODS: From a sampling frame of 24,682 adults of European ancestry enrolled in population-based cohorts across Europe, participants at varying risk of glycaemic deterioration were identified using a risk prediction algorithm (based on age, BMI, waist circumference, use of antihypertensive medication, smoking status and parental history of type 2 diabetes) and enrolled into a prospective cohort study (n = 2127) (cohort 1, prediabetes risk). We also recruited people from clinical registries with type 2 diabetes diagnosed 6-24 months previously (n = 789) into a second cohort study (cohort 2, diabetes). Follow-up examinations took place at ~18 months (both cohorts) and at ~48 months (cohort 1) or ~36 months (cohort 2) after baseline examinations. The cohorts were studied in parallel using matched protocols across seven clinical centres in northern Europe.RESULTS: Using ADA 2011 glycaemic categories, 33% (n = 693) of cohort 1 (prediabetes risk) had normal glucose regulation and 67% (n = 1419) had impaired glucose regulation. Seventy-six per cent of participants in cohort 1 was male. Cohort 1 participants had the following characteristics (mean ± SD) at baseline: age 62 (6.2) years; BMI 27.9 (4.0) kg/m2; fasting glucose 5.7 (0.6) mmol/l; 2 h glucose 5.9 (1.6) mmol/l. At the final follow-up examination the participants' clinical characteristics were as follows: fasting glucose 6.0 (0.6) mmol/l; 2 h OGTT glucose 6.5 (2.0) mmol/l. In cohort 2 (diabetes), 66% (n = 517) were treated by lifestyle modification and 34% (n = 272) were treated with metformin plus lifestyle modification at enrolment. Fifty-eight per cent of participants in cohort 2 was male. Cohort 2 participants had the following characteristics at

Published
2019

11. Validating the positivity thresholds of drug‐tolerant anti‐infliximab and anti‐adalimumab antibody assays.

Author

Nice, Rachel, Chanchlani, Neil, Green, Harry, Bewshea, Claire, Ahmad, Tariq, Goodhand, James R., McDonald, Timothy J., Perry, Mandy H., and Kennedy, Nicholas A.

Subjects
ADALIMUMAB, CROHN'S disease, DRUG monitoring, IMMUNOGLOBULINS
Abstract

Summary: Background: When used proactively, drug‐tolerant anti‐tumour necrosis factor (TNF) antibody assays provide early opportunity to suppress immunogenicity. Aim: To validate positivity thresholds of IDKmonitor drug‐tolerant anti‐infliximab and ‐adalimumab antibody assays. Methods: We applied positivity thresholds, defined by testing sera from 498 anti‐TNF naive healthy adults, from the Exeter Ten Thousand study to data from our therapeutic drug monitoring (TDM) service and Personalised Anti‐TNF Therapy in Crohn's disease (PANTS) cohort to explore associations with drug level and treatment outcomes. Results: The 80% one‐sided lower confidence interval of the 99th centile concentration for anti‐infliximab and –adalimumab antibodies were lower than the manufacturers threshold of 10 arbitrary units (AU)/mL; 9 and 6 AU/mL, respectively. Using these new thresholds in the TDM cohort, more adalimumab‐ than infliximab‐ (11.2% [814/7272] vs 3.1% [390/12 683] P < 0.0001) treated patients were reclassified as antibody‐positive. Adalimumab drug concentrations in this reclassified group (median 8.1, interquartile range [IQR] 5.5‐11.0 mg/L) were lower than those below the new threshold (<5AU/mL) (median 9.9, IQR 7.1‐13.0 mg/L; P < 0.0001), but higher than at the manufacturer's threshold (10‐29 AU/mL) (median 5.9 mg/L, IQR 3.5‐8.7; P < 0.0001). No difference in infliximab drug concentration was observed using the new or manufacturer's positivity threshold (P = 0.11). In the PANTS cohort, patients with anti‐adalimumab antibody concentrations at or above the new threshold were more likely to be in primary non‐response (25/68 [37%] vs. 64/332 [19%], P = 0.0035), and non‐remission at week 54 (51/62 [82%] vs. 168/279 [60%], P = 0.0011), than patients with anti‐drug antibody concentrations in the group below the new threshold (0‐5 AU/mL); this was not seen for anti‐infliximab antibodies. Conclusion: Laboratories should derive antibody positivity thresholds for assays they use. For adalimumab, low‐concentration anti‐drug antibodies were associated with lower drug levels and treatment failure. [ABSTRACT FROM AUTHOR]

Published
2021
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12. Discovery of biomarkers for glycaemic deterioration before and after the onset of type 2 diabetes: rationale and design of the epidemiological studies within the IMI DIRECT Consortium.

Author

Koivula, Robert, Heggie, Alison, Barnett, Anna, Cederberg, Henna, Hansen, Tue H, Koopman, Anitra D, Ridderstråle, Martin, Rutters, Femke, Vestergaard, Henrik, Gupta, Ramneek, Herrgård, Sanna, Heymans, Martijn W, Perry, Mandy H, Rauh, Simone, Siloaho, Maritta, Teare, Harriet J A, Thorand, Barbara, Bell, Jimmy, Brunak, Søren, Frost, Gary, Jablonka, Bernd, Mari, Andrea, McDonald, Tim J, Dekker, Jacqueline M, Hansen, Torben, Hattersley, Andrew, Laakso, Markku, Pedersen, Oluf, Koivisto, Veikko, Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, Franks, Paul, Koivula, Robert, Heggie, Alison, Barnett, Anna, Cederberg, Henna, Hansen, Tue H, Koopman, Anitra D, Ridderstråle, Martin, Rutters, Femke, Vestergaard, Henrik, Gupta, Ramneek, Herrgård, Sanna, Heymans, Martijn W, Perry, Mandy H, Rauh, Simone, Siloaho, Maritta, Teare, Harriet J A, Thorand, Barbara, Bell, Jimmy, Brunak, Søren, Frost, Gary, Jablonka, Bernd, Mari, Andrea, McDonald, Tim J, Dekker, Jacqueline M, Hansen, Torben, Hattersley, Andrew, Laakso, Markku, Pedersen, Oluf, Koivisto, Veikko, Ruetten, Hartmut, Walker, Mark, Pearson, Ewan, and Franks, Paul

Abstract

The DIRECT (Diabetes Research on Patient Stratification) Study is part of a European Union Framework 7 Innovative Medicines Initiative project, a joint undertaking between four industry and 21 academic partners throughout Europe. The Consortium aims to discover and validate biomarkers that: (1) predict the rate of glycaemic deterioration before and after type 2 diabetes onset; (2) predict the response to diabetes therapies; and (3) help stratify type 2 diabetes into clearly definable disease subclasses that can be treated more effectively than without stratification. This paper describes two new prospective cohort studies conducted as part of DIRECT.

Published
2014

14. Post-load glucose subgroups and associated metabolic traits in individuals with type 2 diabetes: An IMI-DIRECT study.

Author

Obura M, Beulens JWJ, Slieker R, Koopman ADM, Hoekstra T, Nijpels G, Elders P, Koivula RW, Kurbasic A, Laakso M, Hansen TH, Ridderstråle M, Hansen T, Pavo I, Forgie I, Jablonka B, Ruetten H, Mari A, McCarthy MI, Walker M, Heggie A, McDonald TJ, Perry MH, De Masi F, Brunak S, Mahajan A, Giordano GN, Kokkola T, Dermitzakis E, Viñuela A, Pedersen O, Schwenk JM, Adamski J, Teare HJA, Pearson ER, Franks PW, 't Hart LM, and Rutters F

Subjects
Aged, Blood Glucose analysis, Diabetes Mellitus, Type 2 blood, Fasting blood, Fasting metabolism, Female, Follow-Up Studies, Glycated Hemoglobin analysis, Glycated Hemoglobin metabolism, Humans, Male, Middle Aged, Triglycerides blood, Triglycerides metabolism, Blood Glucose metabolism, Diabetes Mellitus, Type 2 metabolism
Abstract

Aim: Subclasses of different glycaemic disturbances could explain the variation in characteristics of individuals with type 2 diabetes (T2D). We aimed to examine the association between subgroups based on their glucose curves during a five-point mixed-meal tolerance test (MMT) and metabolic traits at baseline and glycaemic deterioration in individuals with T2D., Methods: The study included 787 individuals with newly diagnosed T2D from the Diabetes Research on Patient Stratification (IMI-DIRECT) Study. Latent class trajectory analysis (LCTA) was used to identify distinct glucose curve subgroups during a five-point MMT. Using general linear models, these subgroups were associated with metabolic traits at baseline and after 18 months of follow up, adjusted for potential confounders., Results: At baseline, we identified three glucose curve subgroups, labelled in order of increasing glucose peak levels as subgroup 1-3. Individuals in subgroup 2 and 3 were more likely to have higher levels of HbA1c, triglycerides and BMI at baseline, compared to those in subgroup 1. At 18 months (n = 651), the beta coefficients (95% CI) for change in HbA1c (mmol/mol) increased across subgroups with 0.37 (-0.18-1.92) for subgroup 2 and 1.88 (-0.08-3.85) for subgroup 3, relative to subgroup 1. The same trend was observed for change in levels of triglycerides and fasting glucose., Conclusions: Different glycaemic profiles with different metabolic traits and different degrees of subsequent glycaemic deterioration can be identified using data from a frequently sampled mixed-meal tolerance test in individuals with T2D. Subgroups with the highest peaks had greater metabolic risk., Competing Interests: The authors have read the journal’s policy and have the following competing interests: IP is employed by Eli Lilly Regional Operations GmbH, Vienna, Austria and BJ and HR are employees of Sanofi-Aventis Deutschland GmbH, R&D, Frankfurt am Main, Germany. This does not alter our adherence to PLOS ONE policies on sharing data and materials. There are no patents, products in development or marketed products associated with this research to declare.

Published
2020
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