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2. 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 LT, Kreienkamp, Raymond J, Lim, Lee-Ling, Männistö, Jonna ME, 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 KW, Libman, Ingrid M, Liu, Kai, Long, S Alice, Lowe, 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, and Ried-Larsen, Mathias

Subjects
Health Services and Systems, Biomedical and Clinical Sciences, Health Sciences, Health Services, Diabetes, Clinical Research, Pediatric, Metabolic and endocrine, Good Health and Well Being, Humans, Precision Medicine, Consensus, Diabetes Mellitus, Evidence-Based Medicine, Medical and Health Sciences, Immunology, Biomedical and clinical sciences, Health sciences
Abstract

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.

Published
2023

3. 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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4. 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

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

Author

Eriksen, Rebeca, White, Margaret C, Dawed, Adem Y, Perez, Isabel Garcia, Posma, Joram M, Haid, Mark, Sharma, Sapna, Prehn, Cornelia, Thomas, E Louise, Koivula, Robert W, Bizzotto, Roberto, Mari, Andrea, Giordano, Giuseppe N, Pavo, Imre, Schwenk, Jochen M, Masi, Federico De, Tsirigos, Konstantinos D, Brunak, Søren, Viñuela, Ana, and Mahajan, Anubha

Subjects
TYPE 2 diabetes, PEOPLE with diabetes, MULTIPLE regression analysis, INSULIN resistance, FOOD consumption
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. [ABSTRACT FROM AUTHOR]

Published
2024
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14. Correction to: Young-onset diabetes in Asian Indians is associated with lower measured and genetically determined beta cell function

Author

Siddiqui, Moneeza K., Anjana, Ranjit Mohan, Dawed, Adem Y., Martoeau, Cyrielle, Srinivasan, Sundararajan, Saravanan, Jebarani, Madanagopal, Sathish K., Taylor, Alasdair, Bell, Samira, Veluchamy, Abirami, Pradeepa, Rajendra, Sattar, Naveed, Venkatesan, Radha, Palmer, Colin N. A., Pearson, Ewan R., and Mohan, Viswanathan

Published
2022
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15. 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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17. Type 2 Diabetes risk alleles in Peptidyl-glycine Alpha-amidating Monooxygenase influence GLP-1 levels and response to GLP-1 Receptor Agonists

Author

Umapathysivam, Mahesh M, primary, Araldi, Elisa, additional, Hastoy, Benoit, additional, Dawed, Adem Y, additional, Vatandaslar, Hasan, additional, Sengupta, Shahana, additional, Kaufmann, Adrian, additional, Thomsen, Søren, additional, Hartmann, Bolette, additional, Jonsson, Anna E, additional, Kabakci, Hasan, additional, Thaman, Swaraj, additional, Grarup, Niels, additional, Have, Christian T, additional, Færch, Kristine, additional, Gjesing, Anette P, additional, Nawaz, Sameena, additional, Cheeseman, Jane, additional, Neville, Matthew J, additional, Pedersen, Oluf, additional, Walker, Mark, additional, Jennison, Christopher, additional, Hattersley, Andrew T, additional, Hansen, Torben, additional, Karpe, Fredrik, additional, Holst, Jens J, additional, Jones, Angus G, additional, Ristow, Michael, additional, McCarthy, Mark I, additional, Pearson, Ewan R, additional, Stoffel, Markus, additional, and Gloyn, Anna L, additional

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

Author

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., Pearson, Ewan R., DIRECT consortium, for the D. I. R. E. C. T. consortium, 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., Pearson, Ewan R., and DIRECT consortium, for the D. I. R. E. C. T. consortium

Abstract

Background: In the treatment of type 2 diabetes, GLP-1 receptor agonists lower blood glucose concentrations, body weight, and have cardiovascular benefits. The efficacy and side effects of GLP-1 receptor agonists vary between people. Human pharmacogenomic studies of this inter-individual variation can provide both biological insight into drug action and provide biomarkers to inform clinical decision making. We therefore aimed to identify genetic variants associated with glycaemic response to GLP-1 receptor agonist treatment. Methods: In this genome-wide analysis we included adults (aged >= 18 years) with type 2 diabetes treated with GLP-1 receptor agonists with baseline HbA1c of 7% or more (53 mmol/mol) from four prospective observational cohorts (DIRECT, PRIBA, PROMASTER, and GoDARTS) and two randomised clinical trials (HARMONY phase 3 and AWARD). The primary endpoint was HbA1c reduction at 6 months after starting GLP-1 receptor agonists. We evaluated variants in GLP1R, then did a genome-wide association study and gene-based burden tests. Findings: 4571 adults were included in our analysis, of these, 3339 (73%) were White European, 449 (10%) Hispanic, 312 (7%) American Indian or Alaskan Native, and 471 (10%) were other, and around 2140 (47%) of the participants were women. Variation in HbA1c reduction with GLP-1 receptor agonists treatment was associated with rs6923761G -> A (Gly168Ser) in the GLP1R (0.08% [95% CI 0.04-0.12] or 0.9 mmol/mol lower reduction in HbA1c per serine, p=6.0 x 10(-5)) and low frequency variants in ARRB1 (optimal sequence kernel association test p=6.7 x 10(-8)), largely driven by rs140226575G -> A (Thr370Met; 0.25% [SE 0.06] or 2.7 mmol/mol [SE 0.7] greater HbA1c reduction per methionine, p=5.2 x 10(-6)). A similar effect size for the ARRB1 Thr370Met was seen in Hispanic and American Indian or Alaska Native populations who have a higher frequency of this variant (6-11%) than in White European populations. Combining these two genes i

Published
2023
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19. 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, 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., Franks, Paul W., 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, 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.

Abstract

Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.

Published
2023

20. 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

21. Type 2 Diabetes risk alleles in Peptidyl-glycine Alpha-amidating Monooxygenase influence GLP-1 levels and response to GLP-1 Receptor Agonists

Author

Umapathysivam, Mahesh M, Araldi, Elisa, Hastoy, Benoit, Dawed, Adem Y, Vatandaslar, Hasan, Sengupta, Shahana, Kaufmann, Adrian, Thomsen, Søren, Hartmann, Bolette, Jonsson, Anna E, Kabakci, Hasan, Thaman, Swaraj, Grarup, Niels, Have, Christian T, Færch, Kristine, Gjesing, Anette P, Nawaz, Sameena, Cheeseman, Jane, Neville, Matthew J, Pedersen, Oluf, Walker, Mark, Jennison, Christopher, Hattersley, Andrew T, Hansen, Torben, Karpe, Fredrik, Holst, Jens J, Jones, Angus G, Ristow, Michael, McCarthy, Mark I, Pearson, Ewan R, Stoffel, Markus, Gloyn, Anna L, Umapathysivam, Mahesh M, Araldi, Elisa, Hastoy, Benoit, Dawed, Adem Y, Vatandaslar, Hasan, Sengupta, Shahana, Kaufmann, Adrian, Thomsen, Søren, Hartmann, Bolette, Jonsson, Anna E, Kabakci, Hasan, Thaman, Swaraj, Grarup, Niels, Have, Christian T, Færch, Kristine, Gjesing, Anette P, Nawaz, Sameena, Cheeseman, Jane, Neville, Matthew J, Pedersen, Oluf, Walker, Mark, Jennison, Christopher, Hattersley, Andrew T, Hansen, Torben, Karpe, Fredrik, Holst, Jens J, Jones, Angus G, Ristow, Michael, McCarthy, Mark I, Pearson, Ewan R, Stoffel, Markus, and Gloyn, Anna L

Abstract

UNLABELLED: Patients with type 2 diabetes vary in their response to currently available therapeutic agents (including GLP-1 receptor agonists) leading to suboptimal glycemic control and increased risk of complications. We show that human carriers of hypomorphic T2D-risk alleles in the gene encoding peptidyl-glycine alpha-amidating monooxygenase (PAM), as well as Pam- knockout mice, display increased resistance to GLP-1 in vivo . Pam inactivation in mice leads to reduced gastric GLP-1R expression and faster gastric emptying: this persists during GLP-1R agonist treatment and is rescued when GLP-1R activity is antagonized, indicating resistance to GLP-1's gastric slowing properties. Meta-analysis of human data from studies examining GLP-1R agonist response (including RCTs) reveals a relative loss of 44% and 20% of glucose lowering (measured by glycated hemoglobin) in individuals with hypomorphic PAM alleles p.S539W and p.D536G treated with GLP-1R agonist. Genetic variation in PAM has effects on incretin signaling that alters response to medication used commonly for treatment of T2D. (Funded by the Wellcome, Medical Research Council, European Union, NIHR Oxford Biomedical Research Centre, United Kingdom, Registered on ClinicalTrials.gov, NCT02723110 .). SUMMARY PARAGRAPH: Type 2 diabetes (T2D) is a leading cause of morbidity and mortality globally 1 . Current management of T2D patients focuses on lowering glycemic exposure and reducing complications with lifestyle and pharmacological interventions 2 . Despite the availability of multiple medications to lower glycated hemoglobin (HbA1c), only 53% of individuals with T2D reach the glycemic target (HbA1c <7%) 3, 4 . There is potential to improve medication selection through "precision medicine" where patient specific factors (e.g. genetic markers) are used to indicate whether a patient is more or less likely to respond to a medication. Here we show that human carriers of hypomorphic T2D-risk alleles in the gen

Published
2023

22. Precision medicine in type 2 diabetes: A systematic review of treatment effect heterogeneity for GLP1-receptor agonists and SGLT2-inhibitors

Author

Young, Katherine G, McInnes, Eram Haider, Massey, Robert J, Kahkohska, Anna R, Pilla, Scott J, Raghaven, Sridharan, Stanislawski, Maggie A, Tobias, Deirdre K, McGovern, Andrew P, Dawed, Adem Y, Jones, Angus G, Pearson, Ewan R, and Dennis, John M

Subjects
Article
Abstract

BACKGROUND: A precision medicine approach in type 2 diabetes requires identification of clinical and biological features that are reproducibly associated with differences in clinical outcomes with specific anti-hyperglycaemic therapies. Robust evidence of such treatment effect heterogeneity could support more individualized clinical decisions on optimal type 2 diabetes therapy. METHODS: We performed a pre-registered systematic review of meta-analysis studies, randomized control trials, and observational studies evaluating clinical and biological features associated with heterogenous treatment effects for SGLT2-inhibitor and GLP1-receptor agonist therapies, considering glycaemic, cardiovascular, and renal outcomes. RESULTS: After screening 5,686 studies, we included 101 studies of SGLT2-inhibitors and 75 studies of GLP1-receptor agonists in the final systematic review. The majority of papers had methodological limitations precluding robust assessment of treatment effect heterogeneity. For glycaemic outcomes, most cohorts were observational, with multiple analyses identifying lower renal function as a predictor of lesser glycaemic response with SGLT2-inhibitors and markers of reduced insulin secretion as predictors of lesser response with GLP1-receptor agonists. For cardiovascular and renal outcomes, the majority of included studies were post-hoc analyses of randomized control trials (including meta-analysis studies) which identified limited clinically relevant treatment effect heterogeneity. CONCLUSIONS: Current evidence on treatment effect heterogeneity for SGLT2-inhibitor and GLP1-receptor agonist therapies is limited, likely reflecting the methodological limitations of published studies. Robust and appropriately powered studies are required to understand type 2 diabetes treatment effect heterogeneity and evaluate the potential for precision medicine to inform future clinical care. PLAIN LANGUAGE SUMMARY: This review identifies research that helps understand which clinical and biological factors that are associated with different outcomes for specific type 2 diabetes treatments. This information could help clinical providers and patients make better informed personalized decisions about type 2 diabetes treatments. We focused on two common type 2 diabetes treatments: SGLT2-inhibitors and GLP1-receptor agonists, and three outcomes: blood glucose control, heart disease, and kidney disease. We identified some potential factors that are likely to lessen blood glucose control including lower kidney function for SGLT2-inhibitors and lower insulin secretion for GLP1-receptor agonists. We did not identify clear factors that alter heart and renal disease outcomes for either treatment. Most of the studies had limitations, meaning more research is needed to fully understand the factors that influence treatment outcomes in type 2 diabetes.

Published
2023

23. Identification of genetic variation influencing metformin response in a multi-ancestry genome-wide association study in the Diabetes Prevention Program (DPP)

Author

Li, Josephine, primary, Perry, James A., primary, Jablonski, Kathleen A., primary, Srinivasan, Shylaja, primary, Chen, Ling, primary, Todd, Jennifer N., primary, Harden, Maegan, primary, Mercader, Josep M., primary, Pan, Qing, primary, Dawed, Adem Y., primary, Yee, Sook Wah, primary, Pearson, Ewan R., primary, Giacomini, Kathleen M., primary, Giri, Ayush, primary, Hung, Adriana M., primary, Xiao, Shujie, primary, Williams, L. Keoki, primary, Franks, Paul W., primary, Hanson, Robert L., primary, Kahn, Steven E., primary, Knowler, William C., primary, Pollin, Toni I., primary, Florez, Jose C., primary, and Group, Diabetes Prevention Program Research, primary

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

Author

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

Published
2023
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25. Additional file 1 of Weight variability and cardiovascular outcomes: a systematic review and meta-analysis

Author

Massey, Robert J., Siddiqui, Moneeza K., Pearson, Ewan R., and Dawed, Adem Y.

Abstract

Additional file 1: Appendix S1. Search Strategies. Appendix S2. Description of Emails. Appendix S3. List of Inclusion and Exclusion Criteria. Table S1. Descriptions and Definitions of Weight Variability Metrics. Table S2. Table of Study Characteristics. Table S3. Additional Table of Study Characteristics. Figure S1. Results of Per +1 SD in Weight Variability Analysis. Figure S2. Results of Degree of BMI Variability Analysis. Figure S3. Results of Ethnicity Stratification. Figure S4. Results of Diabetes Status Stratification. Figure S5. Results of Metric of Variability Stratification. Figure S6. Results of Quantile Stratification. Figure S7. Results of Previous Cardiovascular Disease Stratification. Figure S8. Results of adjustment for change in BMI or average BMI stratification. Figure S9. Results of Univariate Meta-Regression by Age. Figure S10. Egger’s Regression and Funnel Plots. Figure S11. Results of Newcastle-Ottawa Bias Analysis. Appendix S4. MOOSE Checklist. Table S4. Newcastle – Ottawa Scale Quality Assessment Results. Appendix S5. Newcastle-Ottawa Quality Assessment Scale.

Published
2023
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27. Identification of genetic variation influencing metformin response in a multi-ancestry genome-wide association study in the Diabetes Prevention Program (DPP)

Author

Li, Josephine, primary, Perry, James A., primary, Jablonski, Kathleen A., primary, Srinivasan, Shylaja, primary, Chen, Ling, primary, Todd, Jennifer N., primary, Harden, Maegan, primary, Mercader, Josep M., primary, Pan, Qing, primary, Dawed, Adem Y., primary, Yee, Sook Wah, primary, Pearson, Ewan R., primary, Giacomini, Kathleen M., primary, Giri, Ayush, primary, Hung, Adriana M., primary, Xiao, Shujie, primary, Williams, L. Keoki, primary, Franks, Paul W., primary, Hanson, Robert L., primary, Kahn, Steven E., primary, Knowler, William C., primary, Pollin, Toni I., primary, Florez, Jose C., primary, and Group, Diabetes Prevention Program Research, primary

Published
2022
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28. Identification of Genetic Variation Influencing Metformin Response in a Multiancestry Genome-Wide Association Study in the Diabetes Prevention Program (DPP).

Author

Li, Josephine H., Perry, James A., Jablonski, Kathleen A., Srinivasan, Shylaja, Chen, Ling, Todd, Jennifer N., Harden, Maegan, Mercader, Josep M., Pan, Qing, Dawed, Adem Y., Yee, Sook Wah, Pearson, Ewan R., Giacomini, Kathleen M., Giri, Ayush, Hung, Adriana M., Xiao, Shujie, Williams, L. Keoki, Franks, Paul W., Hanson, Robert L., and Kahn, Steven E.

Subjects
GENOME-wide association studies, GENETIC variation, GLYCOSYLATED hemoglobin, TYPE 2 diabetes, PROPORTIONAL hazards models
Abstract

Genome-wide significant loci for metformin response in type 2 diabetes reported elsewhere have not been replicated in the Diabetes Prevention Program (DPP). To assess pharmacogenetic interactions in prediabetes, we conducted a genome-wide association study (GWAS) in the DPP. Cox proportional hazards models tested associations with diabetes incidence in the metformin (MET; n = 876) and placebo (PBO; n = 887) arms. Multiple linear regression assessed association with 1-year change in metformin-related quantitative traits, adjusted for baseline trait, age, sex, and 10 ancestry principal components. We tested for gene-by-treatment interaction. No significant associations emerged for diabetes incidence. We identified four genome-wide significant variants after correcting for correlated traits (P < 9 × 10−9). In the MET arm, rs144322333 near ENOSF1 (minor allele frequency [MAF]AFR = 0.07; MAFEUR = 0.002) was associated with an increase in percentage of glycated hemoglobin (per minor allele, β = 0.39 [95% CI 0.28, 0.50]; P = 2.8 × 10−12). rs145591055 near OMSR (MAF = 0.10 in American Indians) was associated with weight loss (kilograms) (per G allele, β = −7.55 [95% CI −9.88, −5.22]; P = 3.2 × 10−10) in the MET arm. Neither variant was significant in PBO; gene-by-treatment interaction was significant for both variants [P(G×T) < 1.0 × 10−4]. Replication in individuals with diabetes did not yield significant findings. A GWAS for metformin response in prediabetes revealed novel ethnic-specific associations that require further investigation but may have implications for tailored therapy. [ABSTRACT FROM AUTHOR]

Published
2023
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31. Genome-Wide Meta-analysis Identifies Genetic Variants Associated With Glycemic Response to Sulfonylureas. Diabetes Care 2021;44:2673–2682

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 N.A., Florez, Jose C., Hedderson, Monique M., Mt Hart, Leen, Giacomini, Kathleen M., Pearson, Ewan R., Epidemiology and Data Science, ACS - Diabetes & metabolism, ACS - Heart failure & arrhythmias, APH - Health Behaviors & Chronic Diseases, General practice, APH - Methodology, and APH - Aging & Later Life

Published
2022
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32. Diabetes status modifies the long-term effect of lipoprotein-associated phospholipase A2 on major coronary events.

Author

Siddiqui, Moneeza K, Smith, Gillian, St Jean, Pamela, Dawed, Adem Y, Bell, Samira, Soto-Pedre, Enrique, Kennedy, Gwen, Carr, Fiona, Wallentin, Lars, White, Harvey, Macphee, Colin H, Waterworth, Dawn, Palmer, Colin N A, Siddiqui, Moneeza K, Smith, Gillian, St Jean, Pamela, Dawed, Adem Y, Bell, Samira, Soto-Pedre, Enrique, Kennedy, Gwen, Carr, Fiona, Wallentin, Lars, White, Harvey, Macphee, Colin H, Waterworth, Dawn, and Palmer, Colin N A

Abstract

AIMS/HYPOTHESIS: Lipoprotein-associated phospholipase A2 (Lp-PLA2) activity has an independent prognostic association with major coronary events (MCE). However, no study has investigated whether type 2 diabetes status modifies the effect of Lp-PLA2 activity or inhibition on the risk of MCE. We investigate the interaction between diabetes status and Lp-PLA2 activity with risk of MCE. Subsequently, we test the resulting hypothesis that diabetes status will play a role in modifying the efficacy of an Lp-PLA2 inhibitor. METHODS: A retrospective cohort study design was utilised in two study populations. Discovery analyses were performed in the Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) cohort based in Scotland, UK. Participants were categorised by type 2 diabetes control status: poorly controlled (HbA1c ≥ 48 mmol/mol or ≥6.5%) and well-controlled (HbA1c < 48 mmol/mol or <6.5%) diabetes (n = 7420). In a secondary analysis of the Stabilization of Atherosclerotic Plaque by Initiation of Darapladib Therapy (STABILITY) trial of Lp-PLA2 inhibitor (darapladib) efficacy, 15,828 participants were stratified post hoc by type 2 diabetes diagnosis status (diabetes or no diabetes) at time of recruitment. Lp-PLA2 activity was then divided into population-specific quartiles. MCE were determined from linked medical records in GoDARTS and trial records in STABILITY. First, the interaction between diabetes control status and Lp-PLA2 activity on the outcome of MCE was explored in GoDARTS. The effect was replicated in the placebo arm of STABILITY. The effect of Lp-PLA2 on MCE was then examined in models stratified by diabetes status. This helped determine participants at higher risk. Finally, the effect of Lp-PLA2 inhibition was assessed in STABILITY in the higher risk group. Cox proportional hazards models adjusted for confounders were used to assess associations. RESULTS: In GoDARTS, a significant interaction between increased Lp-PLA2 activity (continuous

Published
2022
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34. Genomic editing of metformin efficacy-associated genetic variants in SLC47A1 does not alter SLC47A1 expression

Author

MetGen Plus Consortium, Kalamajski, Sebastian, Huang, Mi, Dalla-Riva, Jonathan, Keller, Maria, Dawed, Adem Y., Hansson, Ola, Pearson, Ewan R., Mulder, Hindrik, Franks, Paul W., and Institute for Molecular Medicine Finland

Subjects
PHARMACOKINETICS, SLC47A1, endocrine system diseases, Genotype, Organic Cation Transport Proteins, In silico, Locus (genetics), 030226 pharmacology & pharmacy, Polymorphism, Single Nucleotide, 03 medical and health sciences, 0302 clinical medicine, Genetics, medicine, Hypoglycemic Agents, Allele, Molecular Biology, Gene, Genetics (clinical), 030304 developmental biology, Glycated Hemoglobin, 0303 health sciences, EXCRETION, biology, EXTRUSION 1 MATE1, Intron, 1184 Genetics, developmental biology, physiology, nutritional and metabolic diseases, General Medicine, Genomics, Metformin, MULTIDRUG, TRANSPORTER PROTEIN, RNA splicing, biology.protein, 1182 Biochemistry, cell and molecular biology, medicine.drug
Abstract

Several pharmacogenetics studies have identified an association between a greater metformin-dependent reduction in HbA1c levels and the minor A allele at rs2289669 in intron 10 of SLC47A1, encoding multidrug and toxin extrusion 1 (MATE1), a presumed metformin transporter. It is currently unknown if the rs2289669 locus is a cis-eQTL, which would validate its role as predictor of metformin efficacy. We looked at association between common genetic variants in the SLC47A1 gene region and HbA1c reduction after metformin treatment using locus-wise meta-analysis from the MetGen consortium. CRISPR-Cas9 was applied to perform allele editing of, or genomic deletion around, rs2289669 and of the closely linked rs8065082 in HepG2 cells. The genome-edited cells were evaluated for SLC47A1 expression and splicing. None of the common variants including rs2289669 showed significant association with metformin response. Genomic editing of either rs2289669 or rs8065082 did not alter SLC47A1 expression or splicing. Experimental and in silico analyses show that the rs2289669-containing haploblock does not appear to carry genetic variants that could explain its previously reported association with metformin efficacy.

Published
2021

35. Genome-Wide Meta-analysis Identifies Genetic Variants Associated With Glycemic Response to Sulfonylureas

Author

Dawed, Adem Y, primary, Yee, Sook Wah, primary, Zhou, Kaixin, primary, Leeuwen, Nienke van, primary, Zhang, Yanfei, primary, Siddiqui, Moneeza K, primary, Etheridge, Amy, primary, Innocenti, Federico, primary, Xu, Fei, primary, Li, Josephine H., primary, Beulens, Joline W, primary, Heijden, Amber A van der, primary, Slieker, Roderick C, primary, Chang, Yu-Chuan, primary, Mercader, Josep M., primary, Kaur, Varinderpal, primary, Witte, John S., primary, Lee, Ming Ta Michael, primary, Kamatani, Yoichiro, primary, Momozawa, Yukihide, primary, Kubo, Michiaki, primary, Palmer, Colin N A, primary, Florez, Jose C., primary, Hedderson, Monique M., primary, Hart, Leen M. ‘t, primary, Giacomini, Kathleen M., primary, Pearson, Ewan R, primary, Consortium, the MetGen Plus, primary, and Consortium, the DIRECT, primary

Published
2021
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36. Common Statin Intolerance Variants in ABCB1 and LILRB5 Show Synergistic Effects on Statin Response: An Observational Study Using Electronic Health Records

Author

Melhem, Alaa’ Lutfi, primary, Chourasia, Mehul Kumar, additional, Bigossi, Margherita, additional, Maroteau, Cyrielle, additional, Taylor, Alasdair, additional, Pola, Roberto, additional, Dawed, Adem Y., additional, Tornio, Aleksi, additional, Palmer, Colin N. A., additional, and Siddiqui, Moneeza K., additional

Published
2021
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37. Diabetes status modifies the long-term effect of lipoprotein-associated phospholipase A2 on major coronary events

Author

Siddiqui, Moneeza K., primary, Smith, Gillian, additional, St Jean, Pamela, additional, Dawed, Adem Y., additional, Bell, Samira, additional, Soto-Pedre, Enrique, additional, Kennedy, Gwen, additional, Carr, Fiona, additional, Wallentin, Lars, additional, White, Harvey, additional, Macphee, Colin H., additional, Waterworth, Dawn, additional, and Palmer, Colin N. A., additional

Published
2021
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41. Predicting and elucidating the etiology of fatty liver disease:A machine learning modeling and validation study in the IMI DIRECT cohorts

Author

Atabaki-Pasdar, Naeimeh, Ohlsson, Mattias, Viñuela, Ana, Frau, Francesca, Pomares-Millan, Hugo, Haid, Mark, Jones, Angus G, Thomas, E Louise, Koivula, Robert W, Kurbasic, Azra, Mutie, Pascal M, Fitipaldi, Hugo, Fernandez, Juan, Dawed, Adem Y, Giordano, Giuseppe N, Forgie, Ian M, McDonald, Timothy J, Rutters, Femke, Cederberg, Henna, Chabanova, Elizaveta, Dale, Matilda, Masi, Federico De, Thomas, Cecilia Engel, Allin, Kristine H., Hansen, Tue H, Heggie, Alison, Hong, Mun-Gwan, Elders, Petra J M, Kennedy, Gwen, Kokkola, Tarja, Pedersen, Helle Krogh, Mahajan, Anubha, McEvoy, Donna, Pattou, Francois, Raverdy, Violeta, Häussler, Ragna S, Sharma, Sapna, Thomsen, Henrik S, Vangipurapu, Jagadish, Vestergaard, Henrik, Adamski, Jerzy, Musholt, Petra B, Brage, Søren, Brunak, Søren, Dermitzakis, Emmanouil, Frost, Gary, Hansen, Torben, Laakso, Markku, and Pedersen, Oluf

Abstract

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning.METHODS AND FINDINGS: We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (CONCLUSIONS: In this study, we developed several models with different combinations of clinical and omics data and identified biological features that appear to be associated with liver fat accumulation. In general, the clinical variables showed better prediction ability than the complex omics variables. However, the combination of omics and clinical variables yielded the highest accuracy. We have incorporated the developed clinical models into a web interface (see: https://www.predictliverfat.org/) and made it available to the community.TRIAL REGISTRATION: ClinicalTrials.gov NCT03814915.

Published
2020
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42. Genome-Wide Meta-Analysis Identifies the Organic Anion-Transporting Polypeptide Gene SLCO1B1 and Statins as Modifiers of Glycemic Response to Sulfonylureas

Author

Dawed, Adem Y., primary, Yee, Sook Wah, additional, Zhou, Kaixin, additional, van Leeuwen, Nienke, additional, Zhang, Yanfei, additional, Siddiqui, Moneeza K., additional, Etheridge, Amy, additional, Innocenti, Federico, additional, Xu, Fei, additional, Li, Josephine H., additional, Beulens, Joline W., additional, van der Heijden, Amber A., additional, Slieker, Roderick C., additional, Chang, Yu-Chuan, additional, Mercader, Josep M., additional, Kaur, Varinderpal, additional, Witte, John S., additional, Lee, Ming Ta Michael, additional, Kamatani, Yoichiro, additional, Momozawa, Yukihide, additional, Kubo, Michiaki, additional, Palmer, Colin N. A., additional, Florez, Jose C., additional, Hedderson, Monique M., additional, ‘t Hart, Leen M., additional, Giacomini, Kathleen M., additional, and Pearson, Ewan R., additional

Published
2021
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43. Response to Comment on Gan et al. Efficacy of Modern Diabetes Treatments DPP-4i, SGLT-2i, and GLP-1RA in White and Asian Patients With Diabetes: A Systematic Review and Meta-analysis of Randomized Controlled Trials. Diabetes Care 2020;43:1948–1957

Author

Gan, Sushrima, primary, Dawed, Adem Y., additional, Donnelly, Louise A., additional, Nair, Anand T.N., additional, Palmer, Colin N.A., additional, Mohan, Viswanathan, additional, and Pearson, Ewan R., additional

Published
2020
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48. Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts

Author

Atabaki-Pasdar, Naeimeh, primary, Ohlsson, Mattias, additional, Viñuela, Ana, additional, Frau, Francesca, additional, Pomares-Millan, Hugo, additional, Haid, Mark, additional, Jones, Angus G., additional, Thomas, E. Louise, additional, Koivula, Robert W., additional, Kurbasic, Azra, additional, Mutie, Pascal M., additional, Fitipaldi, Hugo, additional, Fernandez, Juan, additional, Dawed, Adem Y., additional, Giordano, Giuseppe N., additional, Forgie, Ian M., additional, McDonald, Timothy J., additional, Rutters, Femke, additional, Cederberg, Henna, additional, Chabanova, Elizaveta, additional, Dale, Matilda, additional, Masi, Federico De, additional, Thomas, Cecilia Engel, additional, Allin, Kristine H., additional, Hansen, Tue H., additional, Heggie, Alison, additional, Hong, Mun-Gwan, additional, Elders, Petra J. M., additional, Kennedy, Gwen, additional, Kokkola, Tarja, additional, Pedersen, Helle Krogh, additional, Mahajan, Anubha, additional, McEvoy, Donna, additional, Pattou, Francois, additional, Raverdy, Violeta, additional, Häussler, Ragna S., additional, Sharma, Sapna, additional, Thomsen, Henrik S., additional, Vangipurapu, Jagadish, additional, Vestergaard, Henrik, additional, ‘t Hart, Leen M., additional, Adamski, Jerzy, additional, Musholt, Petra B., additional, Brage, Soren, additional, Brunak, Søren, additional, Dermitzakis, Emmanouil, additional, Frost, Gary, additional, Hansen, Torben, additional, Laakso, Markku, additional, Pedersen, Oluf, additional, Ridderstråle, Martin, additional, Ruetten, Hartmut, additional, Hattersley, Andrew T., additional, Walker, Mark, additional, Beulens, Joline W. J., additional, Mari, Andrea, additional, Schwenk, Jochen M., additional, Gupta, Ramneek, additional, McCarthy, Mark I., additional, Pearson, Ewan R., additional, Bell, Jimmy D., additional, Pavo, Imre, additional, and Franks, Paul W., additional

Published
2020
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49. Predicting and elucidating the etiology of fatty liver disease using a machine learning-based approach: an IMI DIRECT study

Author

Atabaki-Pasdar, Naeimeh, primary, Ohlsson, Mattias, additional, Viñuela, Ana, additional, Frau, Francesca, additional, Pomares-Millan, Hugo, additional, Haid, Mark, additional, Jones, Angus G, additional, Thomas, E Louise, additional, Koivula, Robert W, additional, Kurbasic, Azra, additional, Mutie, Pascal M, additional, Fitipaldi, Hugo, additional, Fernandez, Juan, additional, Dawed, Adem Y, additional, Giordano, Giuseppe N, additional, Forgie, Ian M, additional, McDonald, Timothy J, additional, Rutters, Femke, additional, Cederberg, Henna, additional, Chabanova, Elizaveta, additional, Dale, Matilda, additional, De Masi, Federico, additional, Thomas, Cecilia Engel, additional, Allin, Kristine H, additional, Hansen, Tue H, additional, Heggie, Alison, additional, Hong, Mun-Gwan, additional, Elders, Petra JM, additional, Kennedy, Gwen, additional, Kokkola, Tarja, additional, Pedersen, Helle Krogh, additional, Mahajan, Anubha, additional, McEvoy, Donna, additional, Pattou, Francois, additional, Raverdy, Violeta, additional, Häussler, Ragna S, additional, Sharma, Sapna, additional, Thomsen, Henrik S, additional, Vangipurapu, Jagadish, additional, Vestergaard, Henrik, additional, ‘t Hart, Leen M, additional, Adamski, Jerzy, additional, Musholt, Petra B, additional, Brage, Soren, additional, Brunak, Søren, additional, Dermitzakis, Emmanouil, additional, Frost, Gary, additional, Hansen, Torben, additional, Laakso, Markku, additional, Pedersen, Oluf, additional, Ridderstråle, Martin, additional, Ruetten, Hartmut, additional, Hattersley, Andrew T, additional, Walker, Mark, additional, Beulens, Joline WJ, additional, Mari, Andrea, additional, Schwenk, Jochen M, additional, Gupta, Ramneek, additional, McCarthy, Mark I, additional, Pearson, Ewan R, additional, Bell, Jimmy D, additional, Pavo, Imre, additional, and Franks, Paul W, additional

Published
2020
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