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1. Subclassification of obesity for precision prediction of cardiometabolic diseases

Author

Coral, Daniel E., Smit, Femke, Farzaneh, Ali, Gieswinkel, Alexander, Tajes, Juan Fernandez, Sparsø, Thomas, Delfin, Carl, Bauvin, Pierre, Wang, Kan, Temprosa, Marinella, De Cock, Diederik, Blanch, Jordi, Fernández-Real, José Manuel, Ramos, Rafael, Ikram, M. Kamran, Gomez, Maria F., Kavousi, Maryam, Panova-Noeva, Marina, Wild, Philipp S., van der Kallen, Carla, Adriaens, Michiel, van Greevenbroek, Marleen, Arts, Ilja, Le Roux, Carel, Ahmadizar, Fariba, Frayling, Timothy M., Giordano, Giuseppe N., Pearson, Ewan R., and Franks, Paul W.

Published
2024
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3. Role of human plasma metabolites in prediabetes and type 2 diabetes from the IMI-DIRECT study

Author

Sharma, Sapna, Dong, Qiuling, Haid, Mark, Adam, Jonathan, Bizzotto, Roberto, Fernandez-Tajes, Juan J., Jones, Angus G., Tura, Andrea, Artati, Anna, Prehn, Cornelia, Kastenmüller, Gabi, Koivula, Robert W., Franks, Paul W., Walker, Mark, Forgie, Ian M., Giordano, Giuseppe, Pavo, Imre, Ruetten, Hartmut, Dermitzakis, Manolis, McCarthy, Mark I., Pedersen, Oluf, Schwenk, Jochen M., Tsirigos, Konstantinos D., De Masi, Federico, Brunak, Soren, Viñuela, Ana, Mari, Andrea, McDonald, Timothy J., Kokkola, Tarja, Adamski, Jerzy, Pearson, Ewan R., and Grallert, Harald

Published
2024
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11. Routine measurement of cardiometabolic disease risk factors in primary care in England before, during, and after the COVID-19 pandemic: A population-based cohort study

Author

Ho, Frederick K., Dale, Caroline, Mizani, Mehrdad A., Bolton, Thomas, Pearson, Ewan R., Valabhji, Jonathan, Delles, Christian, Welsh, Paul, Nakada, Shinya, Mackay, Daniel, Pell, Jill P., Tomlinson, Chris, Petersen, Steffen E., Bray, Benjamin, Ashworth, Mark, Rahimi, Kazem, Mamas, Mamas, Halcox, Julian, Sudlow, Cathie, Sofat, Reecha, and Sattar, Naveed

Subjects
Glycosylated hemoglobin -- Measurement -- Health aspects, Primary health care -- Usage, Cardiovascular diseases -- Risk factors -- Prevention, Blood pressure -- Measurement, Biological sciences
Abstract

Background This study estimated to what extent the number of measurements of cardiometabolic risk factors (e.g., blood pressure, cholesterol, glycated haemoglobin) were impacted by the COVID-19 pandemic and whether these have recovered to expected levels. Methods and findings A cohort of individuals aged [greater than or equal to]18 years in England with records in the primary care-COVID-19 General Practice Extraction Service Data for Pandemic Planning and Research (GDPPR) were identified. Their records of 12 risk factor measurements were extracted between November 2018 and March 2024. Number of measurements per 1,000 individuals were calculated by age group, sex, ethnicity, and area deprivation quintile. The observed number of measurements were compared to a composite expectation band, derived as the union of the 95% confidence intervals of 2 estimates: (1) a projected trend based on data prior to the COVID-19 pandemic; and (2) an assumed stable trend from before pandemic. Point estimates were calculated as the mid-point of the expectation band. A cohort of 49,303,410 individuals aged [greater than or equal to]18 years were included. There was sharp drop in all measurements in March 2020 to February 2022, but overall recovered to the expected levels during March 2022 to February 2023 except for blood pressure, which had prolonged recovery. In March 2023 to March 2024, blood pressure measurements were below expectation by 16% (-19 per 1,000) overall, in people aged 18 to 39 (-23%; -18 per 1,000), 60 to 79 (-17%; -27 per 1,000), and [greater than or equal to]80 (-31%; -57 per 1,000). There was suggestion that recovery in blood pressure measurements was socioeconomically patterned. The second most deprived quintile had the highest deviation (-20%; -23 per 1,000) from expectation compared to least deprived quintile (-13%; -15 per 1,000). Conclusions There was a substantial reduction in routine measurements of cardiometabolic risk factors following the COVID-19 pandemic, with variable recovery. The implications for missed diagnoses, worse prognosis, and health inequality are a concern., Author(s): Frederick K. Ho 1,*, Caroline Dale 2, Mehrdad A. Mizani 3, Thomas Bolton 3, Ewan R. Pearson 3,4, Jonathan Valabhji 5, Christian Delles 6, Paul Welsh 6, Shinya Nakada [...]

Published
2024
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12. Author Correction: Subclassification of obesity for precision prediction of cardiometabolic diseases

Author

Coral, Daniel E., Smit, Femke, Farzaneh, Ali, Gieswinkel, Alexander, Tajes, Juan Fernandez, Sparsø, Thomas, Delfin, Carl, Bauvin, Pierre, Wang, Kan, Temprosa, Marinella, De Cock, Diederik, Blanch, Jordi, Fernández-Real, José Manuel, Ramos, Rafael, Ikram, M. Kamran, Gomez, Maria F., Kavousi, Maryam, Panova-Noeva, Marina, Wild, Philipp S., van der Kallen, Carla, Adriaens, Michiel, van Greevenbroek, Marleen, Arts, Ilja, Le Roux, Carel, Ahmadizar, Fariba, Frayling, Timothy M., Giordano, Giuseppe N., Pearson, Ewan R., and Franks, Paul W.

Published
2024
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13. Initial Insights into the Genetic Variation Associated with Metformin Treatment Failure in Youth with Type 2 Diabetes

Author

Srinivasan, Shylaja, Chen, Ling, Udler, Miriam, Todd, Jennifer, Kelsey, Megan M, Haymond, Morey W, Arslanian, Silva, Zeitler, Philip, Gubitosi-Klug, Rose, Nadeau, Kristen J, Kutney, Katherine, White, Neil H, Li, Josephine H, Perry, James A, Kaur, Varinderpal, Brenner, Laura, Mercader, Josep M, Dawed, Adem, Pearson, Ewan R, Yee, Sook-Wah, Giacomini, Kathleen M, Pollin, Toni, and Florez, Jose C

Subjects
Paediatrics, Biomedical and Clinical Sciences, Clinical Sciences, Diabetes, Pediatric, Genetics, Human Genome, Prevention, Clinical Research, 2.1 Biological and endogenous factors, Metabolic and endocrine, Adult, Humans, Adolescent, Metformin, Diabetes Mellitus, Type 2, C-Peptide, Treatment Failure, Genetic Variation, Blood Glucose, Hypoglycemic Agents, Paediatrics and Reproductive Medicine, Endocrinology & Metabolism, Clinical sciences
Abstract

Metformin is the first-line treatment for type 2 diabetes (T2D) in youth but with limited sustained glycemic response. To identify common variants associated with metformin response, we used a genome-wide approach in 506 youth from the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) study and examined the relationship between T2D partitioned polygenic scores (pPS), glycemic traits, and metformin response in these youth. Several variants met a suggestive threshold (P < 1 × 10-6), though none including published adult variants reached genome-wide significance. We pursued replication of top nine variants in three cohorts, and rs76195229 in ATRNL1 was associated with worse metformin response in the Metformin Genetics Consortium (n = 7,812), though statistically not being significant after Bonferroni correction (P = 0.06). A higher β-cell pPS was associated with a lower insulinogenic index (P = 0.02) and C-peptide (P = 0.047) at baseline and higher pPS related to two insulin resistance processes were associated with increased C-peptide at baseline (P = 0.04,0.02). Although pPS were not associated with changes in glycemic traits or metformin response, our results indicate a trend in the association of the β-cell pPS with reduced β-cell function over time. Our data show initial evidence for genetic variation associated with metformin response in youth with T2D.

Published
2023

15. Genome-wide association study of placental weight identifies distinct and shared genetic influences between placental and fetal growth

Author

Beaumont, Robin N., Flatley, Christopher, Vaudel, Marc, Wu, Xiaoping, Chen, Jing, Moen, Gunn-Helen, Skotte, Line, Helgeland, Øyvind, Solé-Navais, Pol, Banasik, Karina, Albiñana, Clara, Ronkainen, Justiina, Fadista, João, Stinson, Sara Elizabeth, Trajanoska, Katerina, Wang, Carol A., Westergaard, David, Srinivasan, Sundararajan, Sánchez-Soriano, Carlos, Bilbao, Jose Ramon, Allard, Catherine, Groleau, Marika, Kuulasmaa, Teemu, Leirer, Daniel J., White, Frédérique, Jacques, Pierre-Étienne, Cheng, Haoxiang, Hao, Ke, Andreassen, Ole A., Åsvold, Bjørn Olav, Atalay, Mustafa, Bhatta, Laxmi, Bouchard, Luigi, Brumpton, Ben Michael, Brunak, Søren, Bybjerg-Grauholm, Jonas, Ebbing, Cathrine, Elliott, Paul, Engelbrechtsen, Line, Erikstrup, Christian, Estarlich, Marisa, Franks, Stephen, Gaillard, Romy, Geller, Frank, Grove, Jakob, Hougaard, David M., Kajantie, Eero, Morgen, Camilla S., Nohr, Ellen A., Nyegaard, Mette, Palmer, Colin N. A., Pedersen, Ole Birger, Rivadeneira, Fernando, Sebert, Sylvain, Shields, Beverley M., Stoltenberg, Camilla, Surakka, Ida, Thørner, Lise Wegner, Ullum, Henrik, Vaarasmaki, Marja, Vilhjalmsson, Bjarni J., Willer, Cristen J., Lakka, Timo A., Gybel-Brask, Dorte, Bustamante, Mariona, Hansen, Torben, Pearson, Ewan R., Reynolds, Rebecca M., Ostrowski, Sisse R., Pennell, Craig E., Jaddoe, Vincent W. V., Felix, Janine F., Hattersley, Andrew T., Melbye, Mads, Lawlor, Deborah A., Hveem, Kristian, Werge, Thomas, Nielsen, Henriette Svarre, Magnus, Per, Evans, David M., Jacobsson, Bo, Järvelin, Marjo-Riitta, Zhang, Ge, Hivert, Marie-France, Johansson, Stefan, Freathy, Rachel M., Feenstra, Bjarke, and Njølstad, Pål R.

Published
2023
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16. Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine

Author

Tobias, Deirdre K., Merino, Jordi, Ahmad, Abrar, Aiken, Catherine, Benham, Jamie L., Bodhini, Dhanasekaran, Clark, Amy L., Colclough, Kevin, Corcoy, Rosa, Cromer, Sara J., Duan, Daisy, Felton, Jamie L., Francis, Ellen C., Gillard, Pieter, Gingras, Véronique, Gaillard, Romy, Haider, Eram, Hughes, Alice, Ikle, Jennifer M., Jacobsen, Laura M., Kahkoska, Anna R., Kettunen, Jarno L. T., Kreienkamp, Raymond J., Lim, Lee-Ling, Männistö, Jonna M. E., Massey, Robert, Mclennan, Niamh-Maire, Miller, Rachel G., Morieri, Mario Luca, Most, Jasper, Naylor, Rochelle N., Ozkan, Bige, Patel, Kashyap Amratlal, Pilla, Scott J., Prystupa, Katsiaryna, Raghavan, Sridharan, Rooney, Mary R., Schön, Martin, Semnani-Azad, Zhila, Sevilla-Gonzalez, Magdalena, Svalastoga, Pernille, Takele, Wubet Worku, Tam, Claudia Ha-ting, Thuesen, Anne Cathrine B., Tosur, Mustafa, Wallace, Amelia S., Wang, Caroline C., Wong, Jessie J., Yamamoto, Jennifer M., Young, Katherine, Amouyal, Chloé, Andersen, Mette K., Bonham, Maxine P., Chen, Mingling, Cheng, Feifei, Chikowore, Tinashe, Chivers, Sian C., Clemmensen, Christoffer, Dabelea, Dana, Dawed, Adem Y., Deutsch, Aaron J., Dickens, Laura T., DiMeglio, Linda A., Dudenhöffer-Pfeifer, Monika, Evans-Molina, Carmella, Fernández-Balsells, María Mercè, Fitipaldi, Hugo, Fitzpatrick, Stephanie L., Gitelman, Stephen E., Goodarzi, Mark O., Grieger, Jessica A., Guasch-Ferré, Marta, Habibi, Nahal, Hansen, Torben, Huang, Chuiguo, Harris-Kawano, Arianna, Ismail, Heba M., Hoag, Benjamin, Johnson, Randi K., Jones, Angus G., Koivula, Robert W., Leong, Aaron, Leung, Gloria K. W., Libman, Ingrid M., Liu, Kai, Long, S. Alice, Lowe, Jr, William L., Morton, Robert W., Motala, Ayesha A., Onengut-Gumuscu, Suna, Pankow, James S., Pathirana, Maleesa, Pazmino, Sofia, Perez, Dianna, Petrie, John R., Powe, Camille E., Quinteros, Alejandra, Jain, Rashmi, Ray, Debashree, Ried-Larsen, Mathias, Saeed, Zeb, Santhakumar, Vanessa, Kanbour, Sarah, Sarkar, Sudipa, Monaco, Gabriela S. F., Scholtens, Denise M., Selvin, Elizabeth, Sheu, Wayne Huey-Herng, Speake, Cate, Stanislawski, Maggie A., Steenackers, Nele, Steck, Andrea K., Stefan, Norbert, Støy, Julie, Taylor, Rachael, Tye, Sok Cin, Ukke, Gebresilasea Gendisha, Urazbayeva, Marzhan, Van der Schueren, Bart, Vatier, Camille, Wentworth, John M., Hannah, Wesley, White, Sara L., Yu, Gechang, Zhang, Yingchai, Zhou, Shao J., Beltrand, Jacques, Polak, Michel, Aukrust, Ingvild, de Franco, Elisa, Flanagan, Sarah E., Maloney, Kristin A., McGovern, Andrew, Molnes, Janne, Nakabuye, Mariam, Njølstad, Pål Rasmus, Pomares-Millan, Hugo, Provenzano, Michele, Saint-Martin, Cécile, Zhang, Cuilin, Zhu, Yeyi, Auh, Sungyoung, de Souza, Russell, Fawcett, Andrea J., Gruber, Chandra, Mekonnen, Eskedar Getie, Mixter, Emily, Sherifali, Diana, Eckel, Robert H., Nolan, John J., Philipson, Louis H., Brown, Rebecca J., Billings, Liana K., Boyle, Kristen, Costacou, Tina, Dennis, John M., Florez, Jose C., Gloyn, Anna L., Gomez, Maria F., Gottlieb, Peter A., Greeley, Siri Atma W., Griffin, Kurt, Hattersley, Andrew T., Hirsch, Irl B., Hivert, Marie-France, Hood, Korey K., Josefson, Jami L., Kwak, Soo Heon, Laffel, Lori M., Lim, Siew S., Loos, Ruth J. F., Ma, Ronald C. W., Mathieu, Chantal, Mathioudakis, Nestoras, Meigs, James B., Misra, Shivani, Mohan, Viswanathan, Murphy, Rinki, Oram, Richard, Owen, Katharine R., Ozanne, Susan E., Pearson, Ewan R., Perng, Wei, Pollin, Toni I., Pop-Busui, Rodica, Pratley, Richard E., Redman, Leanne M., Redondo, Maria J., Reynolds, Rebecca M., Semple, Robert K., Sherr, Jennifer L., Sims, Emily K., Sweeting, Arianne, Tuomi, Tiinamaija, Udler, Miriam S., Vesco, Kimberly K., Vilsbøll, Tina, Wagner, Robert, Rich, Stephen S., and Franks, Paul W.

Published
2023
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18. Precision Medicine in Diabetes

Author

Dawed, Adem Y., Haider, Eram, Pearson, Ewan R., Michel, Martin C., Editor-in-Chief, Barrett, James E., Editorial Board Member, Centurión, David, Editorial Board Member, Flockerzi, Veit, Editorial Board Member, Geppetti, Pierangelo, Editorial Board Member, Hofmann, Franz B., Editorial Board Member, Meier, Kathryn Elaine, Editorial Board Member, Page, Clive P., Editorial Board Member, Wang, KeWei, Editorial Board Member, Cascorbi, Ingolf, editor, and Schwab, Matthias, editor

Published
2023
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19. Genome-Wide Meta-analysis Identifies Genetic Variants Associated With Glycemic Response to Sulfonylureas

Author

Dawed, Adem Y, Yee, Sook Wah, Zhou, Kaixin, van Leeuwen, Nienke, Zhang, Yanfei, Siddiqui, Moneeza K, Etheridge, Amy, Innocenti, Federico, Xu, Fei, Li, Josephine H, Beulens, Joline W, van der Heijden, Amber A, Slieker, Roderick C, Chang, Yu-Chuan, Mercader, Josep M, Kaur, Varinderpal, Witte, John S, Lee, Ming Ta Michael, Kamatani, Yoichiro, Momozawa, Yukihide, Kubo, Michiaki, Palmer, Colin NA, Florez, Jose C, Hedderson, Monique M, Hart, Leen MT, Giacomini, Kathleen M, Pearson, Ewan R, investigators:, MetGen Plus, Pearson, Ewan, Dawed, Adem, Holman, Rury, Coleman, Ruth, Hart, Leen T, Slieker, Roderick, Beulens, Joline, van der Heijden, Amber, Nijpels, Giel, Elders, Petra, Rutters, Femke, Stricker, Bruno, Ahmadizar, Fariba, de Keyser, Catherine, Koov, Adriaan, Out, Mattijs, Kloviņš, Jānis, Zaharenko, Linda, Javorsky, Martin, Tkac, Ivan, Florez, Jose, Giacomini, Kathy, Hedderson, Monique, Motsinger-Reif, Alison, Wagner, Michael, Semiz, Sabina, Dujic, Tanja, Christensen, Mette, Brøsen, Kim, Waterworth, Dawn, Ehm, Meg, Ma, Ronald, Psaty, Bruce, and Floyd, James

Subjects
Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Prevention, Diabetes, Human Genome, Genetics, Evaluation of treatments and therapeutic interventions, 6.1 Pharmaceuticals, Metabolic and endocrine, Blood Glucose, Diabetes Mellitus, Type 2, Genome-Wide Association Study, Glycated Hemoglobin, Humans, Hypoglycemic Agents, Likelihood Functions, Liver-Specific Organic Anion Transporter 1, Metformin, Sulfonylurea Compounds, for MetGen Plus, for the DIRECT Consortium, MetGen Plus investigators:
Abstract

ObjectiveSulfonylureas, the first available drugs for the management of type 2 diabetes, remain widely prescribed today. However, there exists significant variability in glycemic response to treatment. We aimed to establish heritability of sulfonylurea response and identify genetic variants and interacting treatments associated with HbA1c reduction.Research design and methodsAs an initiative of the Metformin Genetics Plus Consortium (MetGen Plus) and the DIabetes REsearCh on patient straTification (DIRECT) consortium, 5,485 White Europeans with type 2 diabetes treated with sulfonylureas were recruited from six referral centers in Europe and North America. We first estimated heritability using the generalized restricted maximum likelihood approach and then undertook genome-wide association studies of glycemic response to sulfonylureas measured as HbA1c reduction after 12 months of therapy followed by meta-analysis. These results were supported by acute glipizide challenge in humans who were naïve to type 2 diabetes medications, cis expression quantitative trait loci (eQTL), and functional validation in cellular models. Finally, we examined for possible drug-drug-gene interactions.ResultsAfter establishing that sulfonylurea response is heritable (mean ± SEM 37 ± 11%), we identified two independent loci near the GXYLT1 and SLCO1B1 genes associated with HbA1c reduction at a genome-wide scale (P < 5 × 10-8). The C allele at rs1234032, near GXYLT1, was associated with 0.14% (1.5 mmol/mol), P = 2.39 × 10-8), lower reduction in HbA1c. Similarly, the C allele was associated with higher glucose trough levels (β = 1.61, P = 0.005) in healthy volunteers in the SUGAR-MGH given glipizide (N = 857). In 3,029 human whole blood samples, the C allele is a cis eQTL for increased expression of GXYLT1 (β = 0.21, P = 2.04 × 10-58). The C allele of rs10770791, in an intronic region of SLCO1B1, was associated with 0.11% (1.2 mmol/mol) greater reduction in HbA1c (P = 4.80 × 10-8). In 1,183 human liver samples, the C allele at rs10770791 is a cis eQTL for reduced SLCO1B1 expression (P = 1.61 × 10-7), which, together with functional studies in cells expressing SLCO1B1, supports a key role for hepatic SLCO1B1 (encoding OATP1B1) in regulation of sulfonylurea transport. Further, a significant interaction between statin use and SLCO1B1 genotype was observed (P = 0.001). In statin nonusers, C allele homozygotes at rs10770791 had a large absolute reduction in HbA1c (0.48 ± 0.12% [5.2 ± 1.26 mmol/mol]), equivalent to that associated with initiation of a dipeptidyl peptidase 4 inhibitor.ConclusionsWe have identified clinically important genetic effects at genome-wide levels of significance, and important drug-drug-gene interactions, which include commonly prescribed statins. With increasing availability of genetic data embedded in clinical records these findings will be important in prescribing glucose-lowering drugs.

Published
2021

20. Analysis of type 2 diabetes heterogeneity with a tree-like representation: insights from the prospective German Diabetes Study and the LURIC cohort

Author

Al-Hasani, Hadi, Belgardt, Bengt-Frederik, Bönhof, Gidon J., Geerling, Gerd, Herder, Christian, Icks, Andrea, Jandeleit-Dahm, Karin, Kotzka, Jörg, Kuss, Oliver, Lammert, Eckhard, Rathmann, Wolfgang, Roden, Michael, Schlesinger, Sabrina, Schrauwen-Hinderling, Vera, Szendroedi, Julia, Trenkamp, Sandra, Wagner, Robert, Schön, Martin, Prystupa, Katsiaryna, Mori, Tim, Zaharia, Oana P, Bódis, Kálmán, Bombrich, Maria, Möser, Clara, Yurchenko, Iryna, Kupriyanova, Yuliya, Strassburger, Klaus, Bobrov, Pavel, Nair, Anand T N, Bönhof, Gidon J, Strom, Alexander, Delgado, Graciela E, Kaya, Sema, Guthoff, Rainer, Stefan, Norbert, Birkenfeld, Andreas L, Hauner, Hans, Seissler, Jochen, Pfeiffer, Andreas, Blüher, Matthias, Bornstein, Stefan, Meyhöfer, Svenja, Burkart, Volker, Schrauwen-Hinderling, Vera B, Kleber, Marcus E, Niessner, Alexander, März, Winfried, and Pearson, Ewan R

Published
2024
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21. Stopping Versus Continuing Metformin in Patients With Advanced CKD: A Nationwide Scottish Target Trial Emulation Study

Author

McCrimmon, Rory, Armstrong, Catherine, Emslie-Smith, Alistair, Lindsay, Robert, MacRury, Sandra, McKnight, John, Pearson, Donald, McKinstry, Brian, Lambourg, Emilie J., Fu, Edouard L., McGurnaghan, Stuart, Conway, Bryan R., Dhaun, Neeraj, Grant, Christopher H., Pearson, Ewan R., Mark, Patrick B., Petrie, John, Colhoun, Helen, and Bell, Samira

Published
2024
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23. 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, Adamski, Jerzy, Schwenk, Jochen M., Pearson, Ewan R., Dermitzakis, Emmanouil T., and Viñuela, Ana

Published
2023
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24. Competing risks analysis for neutrophil to lymphocyte ratio as a predictor of diabetic retinopathy incidence in the Scottish population

Author

Rajendrakumar, Aravind Lathika, Hapca, Simona M., Nair, Anand Thakarakkattil Narayanan, Huang, Yu, Chourasia, Mehul Kumar, Kwan, Ryan Shun-Yuen, Nangia, Charvi, Siddiqui, Moneeza K., Vijayaraghavan, Prathiba, Matthew, Shona Z., Leese, Graham P., Mohan, Viswanathan, Pearson, Ewan R., Doney, Alexander S. F., and Palmer, Colin N. A.

Published
2023
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25. Identification of biomarkers for glycaemic deterioration in type 2 diabetes

Author

Slieker, Roderick C., Donnelly, Louise A., Akalestou, Elina, Lopez-Noriega, Livia, Melhem, Rana, Güneş, Ayşim, Abou Azar, Frederic, Efanov, Alexander, Georgiadou, Eleni, Muniangi-Muhitu, Hermine, Sheikh, Mahsa, Giordano, Giuseppe N., Åkerlund, Mikael, Ahlqvist, Emma, Ali, Ashfaq, Banasik, Karina, Brunak, Søren, Barovic, Marko, Bouland, Gerard A., Burdet, Frédéric, Canouil, Mickaël, Dragan, Iulian, Elders, Petra J. M., Fernandez, Celine, Festa, Andreas, Fitipaldi, Hugo, Froguel, Phillippe, Gudmundsdottir, Valborg, Gudnason, Vilmundur, Gerl, Mathias J., van der Heijden, Amber A., Jennings, Lori L., Hansen, Michael K., Kim, Min, Leclerc, Isabelle, Klose, Christian, Kuznetsov, Dmitry, Mansour Aly, Dina, Mehl, Florence, Marek, Diana, Melander, Olle, Niknejad, Anne, Ottosson, Filip, Pavo, Imre, Duffin, Kevin, Syed, Samreen K., Shaw, Janice L., Cabrera, Over, Pullen, Timothy J., Simons, Kai, Solimena, Michele, Suvitaival, Tommi, Wretlind, Asger, Rossing, Peter, Lyssenko, Valeriya, Legido Quigley, Cristina, Groop, Leif, Thorens, Bernard, Franks, Paul W., Lim, Gareth E., Estall, Jennifer, Ibberson, Mark, Beulens, Joline W. J., ’t Hart, Leen M, Pearson, Ewan R., and Rutter, Guy A.

Published
2023
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35. The Type 2 Diabetes Knowledge Portal: An open access genetic resource dedicated to type 2 diabetes and related traits

Author

Abecasis, Gonçalo, Akolkar, Beena, Alexander, Benjamin R., Allred, Nicholette D., Altshuler, David, Below, Jennifer E., Bergman, Richard, Beulens, Joline W.J., Blangero, John, Boehnke, Michael, Bokvist, Krister, Bottinger, Erwin, Boughton, Andrew P., Bowden, Donald, Brosnan, M. Julia, Brown, Christopher, Bruskiewicz, Kenneth, Burtt, Noël P., Carmichael, Mary, Caulkins, Lizz, Cebola, Inês, Chambers, John, Ida Chen, Yii-Der, Cherkas, Andriy, Chu, Audrey Y., Clark, Christopher, Claussnitzer, Melina, Costanzo, Maria C., Cox, Nancy J., Hoed, Marcel den, Dong, Duc, Duby, Marc, Duggirala, Ravindranath, Dupuis, Josée, Elders, Petra J.M., Engreitz, Jesse M., Fauman, Eric, Ferrer, Jorge, Flannick, Jason, Flicek, Paul, Flickinger, Matthew, Florez, Jose C., Fox, Caroline S., Frayling, Timothy M., Frazer, Kelly A., Gaulton, Kyle J., Gilbert, Clint, Gloyn, Anna L., Green, Todd, Hanis, Craig L., Hanson, Robert, Hattersley, Andrew T., Hoang, Quy, Im, Hae Kyung, Iqbal, Sidra, Jacobs, Suzanne B.R., Jang, Dong-Keun, Jordan, Tad, Kamphaus, Tania, Karpe, Fredrik, Keane, Thomas M., Kim, Seung K., Kluge, Alexandria, Koesterer, Ryan, Kudtarkar, Parul, Lage, Kasper, Lange, Leslie A., Lazar, Mitchell, Lehman, Donna, Liu, Ching-Ti, Loos, Ruth J.F., Ma, Ronald Ching-wan, MacDonald, Patrick, Massung, Jeffrey, Maurano, Matthew T., McCarthy, Mark I., McVean, Gil, Meigs, James B., Mercader, Josep M., Miller, Melissa R., Mitchell, Braxton, Mohlke, Karen L., Morabito, Samuel, Morgan, Claire, Mullican, Shannon, Narendra, Sharvari, Ng, Maggie C.Y., Nguyen, Lynette, Palmer, Colin N.A., Parker, Stephen C.J., Parrado, Antonio, Parsa, Afshin, Pawlyk, Aaron C., Pearson, Ewan R., Plump, Andrew, Province, Michael, Quertermous, Thomas, Redline, Susan, Reilly, Dermot F., Ren, Bing, Rich, Stephen S., Richards, J. Brent, Rotter, Jerome I., Ruebenacker, Oliver, Ruetten, Hartmut, Salem, Rany M., Sander, Maike, Sanders, Michael, Sanghera, Dharambir, Scott, Laura J., Sengupta, Sebanti, Siedzik, David, Sim, Xueling, Singh, Preeti, Sladek, Robert, Small, Kerrin, Smith, Philip, Stein, Peter, Spalding, Dylan, Stringham, Heather M., Sun, Ying, Susztak, Katalin, ’t Hart, Leen M., Taliun, Daniel, Taylor, Kent, Thomas, Melissa K., Todd, Jennifer A., Udler, Miriam S., Voight, Benjamin, von Grotthuss, Marcin, Wan, Andre, Welch, Ryan P., Wholley, David, Yuksel, Kaan, Zaghloul, Norann A., Jang, Dongkeun, Moriondo, Annie, Nguyen, Trang, Smadbeck, Patrick, Brandes, MacKenzie, Dornbos, Peter, Huellas-Bruskiewicz, Kenneth C., Ji, Yue, McMahon, Aoife C., Fauman, Eric B., Kamphaus, Tania Nayak, and Abecasis, Gonçalo R.

Published
2023
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38. Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials

Author

't Hart, L.M., Abdalla, M., Adam, J., Adamski, J., Adragni, K., Allin, K.H., Arumugam, M., Atabaki Pasdar, N., Baltauss, T., Banasik, K.B., Baum, P., Bell, J.D., Bergstrom, M., Beulens, J.W., Bianzano, S., Bizzotto, R., Bonneford, A., Brorsson, C.A.B., Brown, A.A., Brunak, S.B., Cabrelli, L., Caiazzo, R., Canouil, M., Dale, M., Davtian, D., Dawed, A.Y., De Masi, F.M., de Preville, N., Dekkers, K.F., Dermitzakis, E.T., Deshmukh, H.A., Dings, C., Donnelly, L., Dutta, A., Ehrhardt, B., Elders, P.J.M., Engel Thomas, C.E.T., Engelbrechtsen, L., Eriksen, R.G., Eriksen, R.E., Fan, Y., Fernandez, J., Ferrer, J., Fitipaldi, H., Forgie, I.M., Forman, A., Franks, P.W., Frau, F., Fritsche, A., Froguel, P., Frost, G., Gassenhuber, J., Giordano, G.N., Giorgino, T., Gough, S., Graefe-Mody, U., Grallert, H., Grempler, R., Groeneveld, L., Groop, L., Gudmundsdóttir, V.G., Gupta, R.G., Haid, M., Hansen, T., Hansen, T.H., Hattersley, A.T., Haussler, R.S., Heggie, A.J., Hennige, A.M., Hill, A.V., Holl, R.W., Hong, M.-G., Hudson, M., Jablonka, B., Jennison, C., Jiao, J., Johansen, J.J., Jones, A.G., Jonsson, A., Karaderi, T.K., Kaye, J., Klintenberg, M., Koivula, R.W., Kokkola, T., Koopman, A.D.M., Kurbasic, A, Kuulasmaa, T., Laakso, M., Lehr, T., Loftus, H., Lundbye Allesøe, R.L.A, Mahajan, A., Mari, A., Mazzoni, G.M., McCarthy, M.I., McDonald, T.J., McEvoy, D., McRobert, N., McVittie, I., Mourby, M., Musholt, P., Mutie, P, Nice, R., Nicolay, C., Nielsen, A.M.N., Nilsson, B.N., Palmer, C.N., Pattou, F., Pavo, I., Pearson, E.R., Pedersen, O., Pedersen, H.K.P., Perry, M.H., Pomares-Millan, H., Ramisch, A., Rasmussen, S.R., Raverdi, V., Ridderstrale, M., Robertson, N., Roderick, R.C., Rodriquez, M., Ruetten, H., Rutters, F., Sackett, W., Scherer, N., Schwenk, J.M., Shah, N., Sharma, S., Sihinevich, I., Sondertoft, N.B., Staerfeldt, H., Steckel-Hamann, B., Teare, H., Thomas, M.K., Thomas, E.L., Thomsen, H.S., Thorand, B., Thorne, C.E., Tillner, J., Troen Lundgaard, A.T.L., Troll, M., Tsirigos, K.D.T., Tura, A., Uhlen, M., van Leeuwen, N., van Oort, S., Verkindt, H., Vestergaard, H., Viñuela, A., Vogt, J.K, Wad Sackett, P.W.S, Wake, D., Walker, M., Wesolowska-Andersen, A., Whitcher, B., White, M.W., Wu, H., Dawed, Adem Y, Mari, Andrea, Brown, Andrew, McDonald, Timothy J, Li, Lin, Wang, Shuaicheng, Hong, Mun-Gwan, Sharma, Sapna, Robertson, Neil R, Mahajan, Anubha, Wang, Xuan, Walker, Mark, Gough, Stephen, Hart, Leen M ‘t, Zhou, Kaixin, Forgie, Ian, Ruetten, Hartmut, Pavo, Imre, Bhatnagar, Pallav, Jones, Angus G, and Pearson, Ewan R

Published
2023
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42. Autoantibodies to Truncated GAD(96-585) Antigen Stratify Risk of Early Insulin Requirement in Adult-Onset Diabetes.

Author

Grace, Sian L., Gillespie, Kathleen M., Williams, Claire L., Lampasona, Vito, Achenbach, Peter, Pearson, Ewan R., Williams, Alistair J.K., Long, Anna E., McDonald, Timothy J., and Jones, Angus G.

Subjects
GENETIC risk score, TYPE 2 diabetes, TYPE 1 diabetes, INSULIN therapy, INSULIN
Abstract

We investigated whether characterization of full-length GAD (f-GADA) antibody (GADA) responses could identify early insulin requirement in adult-onset diabetes. In 179 f-GADA–positive participants diagnosed with type 2 diabetes, we assessed associations of truncated GADA (t-GADA) positivity, f-GADA IgG subclasses, and f-GADA affinity with early insulin requirement (<5 years), type 1 diabetes genetic risk score (T1D GRS), and C-peptide. t-GADA positivity was lower in f-GADA–positive without early insulin in comparison with f-GADA–positive type 2 diabetes requiring insulin within 5 years, and T1D (75% vs. 91% and 95% respectively, P < 0.0001). t-GADA positivity (in those f-GADA positive) identified a group with a higher T1D genetic susceptibility (mean T1D GRS 0.248 vs. 0.225, P = 0.003), lower C-peptide (1,156 pmol/L vs. 4,289 pmol/L, P = 1 × 10−7), and increased IA-2 antigen positivity (23% vs. 6%, P = 0.03). In survival analysis, t-GADA positivity was associated with early insulin requirement compared with those only positive for f-GADA, independently from age of diagnosis, f-GADA titer, and duration of diabetes (adjusted hazard ratio 5.7 [95% CI 1.4, 23.5], P = 0.017). The testing of t-GADA in f-GADA–positive individuals with type 2 diabetes identifies those who have genetic and clinical characteristics comparable to T1D and stratifies those at higher risk of early insulin requirement. Article Highlights: Progression to insulin therapy is highly variable in adult-onset GAD antibody (GADA)–positive diabetes. We further characterized GADA in adult-onset diabetes and assessed whether these are associated with early insulin requirement. Truncated GADA positivity was associated with a type 1 diabetes–like phenotype and stratified risk of early insulin requirement. Those GADA positive who were negative for truncated GADA had the characteristics and progression of classic type 2 diabetes. Assessing full-length GADA IgG subclass and affinity did not further stratify risk of progression. Truncated GADA assessment remains underused in clinical practice but could assist correct therapy allocation in adult-onset diabetes. [ABSTRACT FROM AUTHOR]

Published
2024
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43. Genetic Variants in CPA6 and PRPF31 are Associated with Variation in Response to Metformin in Individuals with Type 2 Diabetes

Author

Rotroff, Daniel M, Yee, Sook Wah, Zhou, Kaixin, Marvel, Skylar W, Shah, Hetal S, Jack, John R, Havener, Tammy M, Hedderson, Monique M, Kubo, Michiaki, Herman, Mark A, Gao, He, Mychaleckyi, Josyf C, McLeod, Howard L, Doria, Alessandro, Giacomini, Kathleen M, Pearson, Ewan R, Wagner, Michael J, Buse, John B, Motsinger-Reif, Alison A, and Investigators, MetGen Investigators and the ACCORD ACCORDion

Subjects
Biomedical and Clinical Sciences, Prevention, Diabetes, Genetics, Obesity, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Carboxypeptidases A, Cohort Studies, Diabetes Mellitus, Type 2, Double-Blind Method, Eye Proteins, Female, Genome-Wide Association Study, Humans, Male, Metformin, Middle Aged, Pharmacogenomic Variants, Polymorphism, Single Nucleotide, STAT3 Transcription Factor, Treatment Outcome, MetGen Investigators, ACCORD/ACCORDion Investigators, Medical and Health Sciences, Endocrinology & Metabolism, Biomedical and clinical sciences
Abstract

Metformin is the first-line treatment for type 2 diabetes (T2D). Although widely prescribed, the glucose-lowering mechanism for metformin is incompletely understood. Here, we used a genome-wide association approach in a diverse group of individuals with T2D from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial to identify common and rare variants associated with HbA1c response to metformin treatment and followed up these findings in four replication cohorts. Common variants in PRPF31 and CPA6 were associated with worse and better metformin response, respectively (P < 5 × 10-6), and meta-analysis in independent cohorts displayed similar associations with metformin response (P = 1.2 × 10-8 and P = 0.005, respectively). Previous studies have shown that PRPF31(+/-) knockout mice have increased total body fat (P = 1.78 × 10-6) and increased fasted circulating glucose (P = 5.73 × 10-6). Furthermore, rare variants in STAT3 associated with worse metformin response (q

Published
2018

44. The Effect of Metformin Treatment on the Circulating Proteome

Author

Connolly, Benjamin W, primary, McCreight, Laura, additional, Slieker, Roderick, additional, Bedair, Khaled F, additional, Donnelly, Louise, additional, de Klerk, Juliette A, additional, Beulens, Joline WJ, additional, Elders, Petra M, additional, Bergstrom, Goran, additional, Hong, Mun-Gwan, additional, Koivula, Robert w, additional, Franks, Paul W, additional, 't Hart, Leen, additional, Schwenk, Jochen, additional, Gummesson, Anders, additional, and Pearson, Ewan R, additional

Published
2024
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45. Participants aux Davidson's Principles and Practice of Medicine, 23eédition

Author

Angus, Brian J., primary, Anstee, Quentin M., additional, Burnett, Leslie, additional, Byers, Mark, additional, Campbell, Harry, additional, Clunie, Gavin P.R., additional, Colvin, Lesley A., additional, Conway, Bryan, additional, Cooper, Nicola, additional, Cracknell, Alison L., additional, Culligan, Dominic J., additional, Dark, Graham G., additional, Davenport, Richard J., additional, Dockrell, David H., additional, El-Omar, Emad, additional, Fallon, Marie, additional, FitzPatrick, David R., additional, Grubb, Neil R., additional, Ibbotson, Sally H., additional, Innes, J. Alastair, additional, Jenks, Sara J., additional, Johnston, Sarah L., additional, Jones, David E.J., additional, Langhorne, Peter, additional, Lawrie, Stephen M., additional, Leach, John Paul, additional, Maartens, Gary, additional, Mackillop, Lucy, additional, MacMahon, Michael J., additional, Mann, Rebecca, additional, Manson, Lynn M., additional, Marshall, Sara E., additional, Mather, Amanda, additional, Maxwell, Simon R., additional, McAllister, David A., additional, McCrimmon, Rory J., additional, McLean, Mairi, additional, Neuberger, Francesca E.M., additional, Newby, David E., additional, Newell-Price, John D.C., additional, Olson, John, additional, Pearson, Ewan R., additional, Phelan, Paul J., additional, Ralston, Stuart H., additional, Reid, Peter T., additional, Sandoe, Jonathan A.T., additional, Scott, Gordon R., additional, Shand, Alan G., additional, Steel, Robby M., additional, Stewart, Grant D., additional, Stewart, Peter, additional, Strachan, Mark W.J., additional, Sullivan, David R., additional, Sundar, Shyam, additional, Tallentire, Victoria R., additional, Tatton-Brown, Katrina, additional, Thomas, Simon H.L., additional, Watson, Henry G., additional, White, Julian, additional, Wilding, John P.H., additional, and Witham, Miles D., additional

Published
2022
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47. Replication and cross-validation of type 2 diabetes subtypes based on clinical variables: an IMI-RHAPSODY study

Author

Slieker, Roderick C., Donnelly, Louise A., Fitipaldi, Hugo, Bouland, Gerard A., Giordano, Giuseppe N., Åkerlund, Mikael, Gerl, Mathias J., Ahlqvist, Emma, Ali, Ashfaq, Dragan, Iulian, Festa, Andreas, Hansen, Michael K., Mansour Aly, Dina, Kim, Min, Kuznetsov, Dmitry, Mehl, Florence, Klose, Christian, Simons, Kai, Pavo, Imre, Pullen, Timothy J., Suvitaival, Tommi, Wretlind, Asger, Rossing, Peter, Lyssenko, Valeriya, Legido-Quigley, Cristina, Groop, Leif, Thorens, Bernard, Franks, Paul W., Ibberson, Mark, Rutter, Guy A., Beulens, Joline W. J., ‘t Hart, Leen M., and Pearson, Ewan R.

Published
2021
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48. An omics-based machine learning approach to predict diabetes progression: a RHAPSODY study

Author

Circulatory Health, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Cardiometabolic Health, Slieker, Roderick C., Münch, Magnus, Donnelly, Louise A., Bouland, Gerard A., Dragan, Iulian, Kuznetsov, Dmitry, Elders, Petra J.M., Rutter, Guy A., Ibberson, Mark, Pearson, Ewan R., ’t Hart, Leen M., van de Wiel, Mark A., Beulens, Joline W.J., Circulatory Health, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Cardiometabolic Health, Slieker, Roderick C., Münch, Magnus, Donnelly, Louise A., Bouland, Gerard A., Dragan, Iulian, Kuznetsov, Dmitry, Elders, Petra J.M., Rutter, Guy A., Ibberson, Mark, Pearson, Ewan R., ’t Hart, Leen M., van de Wiel, Mark A., and Beulens, Joline W.J.

Published
2024

49. Trajectories of clinical characteristics, complications and treatment choices in data-driven subgroups of type 2 diabetes

Author

Circulatory Health, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Cardiometabolic Health, Li, Xinyu, Donnelly, Louise A., Slieker, Roderick C., Beulens, Joline W.J., ‘t Hart, Leen M., Elders, Petra J.M., Pearson, Ewan R., van Giessen, Anoukh, Leal, Jose, Feenstra, Talitha, Circulatory Health, JC onderzoeksprogramma Cardiovasculaire Epidemiologie, Cardiometabolic Health, Li, Xinyu, Donnelly, Louise A., Slieker, Roderick C., Beulens, Joline W.J., ‘t Hart, Leen M., Elders, Petra J.M., Pearson, Ewan R., van Giessen, Anoukh, Leal, Jose, and Feenstra, Talitha

Published
2024

50. The Association of Cardiometabolic, Diet and Lifestyle Parameters With Plasma Glucagon-like Peptide-1: An IMI DIRECT Study

Author

Eriksen, Rebeca, Schwenk, Jochen M., Pearson, Ewan R., et al., Eriksen, Rebeca, Schwenk, Jochen M., Pearson, Ewan R., and et al.

Abstract

Context: The role of glucagon-like peptide-1 (GLP-1) in type 2 diabetes (T2D) and obesity is not fully understood. Objective: We investigate the association of cardiometabolic, diet, and lifestyle parameters on fasting and postprandial GLP-1 in people at risk of, or living with, T2D. Methods: We analyzed cross-sectional data from the two Innovative Medicines Initiative (IMI) Diabetes Research on Patient Stratification (DIRECT) cohorts, cohort 1 (n = 2127) individuals at risk of diabetes; cohort 2 (n = 789) individuals with new-onset T2D. Results: Our multiple regression analysis reveals that fasting total GLP-1 is associated with an insulin-resistant phenotype and observe a strong independent relationship with male sex, increased adiposity, and liver fat, particularly in the prediabetes population. In contrast, we showed that incremental GLP-1 decreases with worsening glycemia, higher adiposity, liver fat, male sex, and reduced insulin sensitivity in the prediabetes cohort. Higher fasting total GLP-1 was associated with a low intake of wholegrain, fruit, and vegetables in people with prediabetes, and with a high intake of red meat and alcohol in people with diabetes. Conclusion: These studies provide novel insights into the association between fasting and incremental GLP-1, metabolic traits of diabetes and obesity, and dietary intake, and raise intriguing questions regarding the relevance of fasting GLP-1 in the pathophysiology T2D., QC 20240906

Published
2024
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