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2. Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Author

Suzuki, Ken, Hatzikotoulas, Konstantinos, Southam, Lorraine, Taylor, Henry, Yin, Xianyong, Lorenz, Kim, Mandla, Ravi, Huerta-Chagoya, Alicia, Melloni, Giorgio, Kanoni, Stavroula, Rayner, Nigel, Bocher, Ozvan, Arruda, Ana, Sonehara, Kyuto, Namba, Shinichi, Lee, Simon, Preuss, Michael, Petty, Lauren, Schroeder, Philip, Vanderwerff, Brett, Kals, Mart, Bragg, Fiona, Lin, Kuang, Guo, Xiuqing, Zhang, Weihua, Yao, Jie, Kim, Young, Graff, Mariaelisa, Takeuchi, Fumihiko, Nano, Jana, Lamri, Amel, Nakatochi, Masahiro, Moon, Sanghoon, Scott, Robert, Cook, James, Lee, Jung-Jin, Pan, Ian, Taliun, Daniel, Parra, Esteban, Chai, Jin-Fang, Bielak, Lawrence, Tabara, Yasuharu, Hai, Yang, Thorleifsson, Gudmar, Grarup, Niels, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloé, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Kwak, Soo-Heon, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Nongmaithem, Suraj, Noordam, Raymond, Lim, Victor, Tam, Claudia, Joo, Yoonjung, Chen, Chien-Hsiun, Raffield, Laura, Prins, Bram, Nicolas, Aude, Yanek, Lisa, Chen, Guanjie, Brody, Jennifer, Kabagambe, Edmond, An, Ping, Xiang, Anny, Choi, Hyeok, Cade, Brian, Tan, Jingyi, Broadaway, K, Williamson, Alice, Kamali, Zoha, Cui, Jinrui, Thangam, Manonanthini, Adair, Linda, Adeyemo, Adebowale, Aguilar-Salinas, Carlos, Ahluwalia, Tarunveer, Anand, Sonia, Bertoni, Alain, Bork-Jensen, Jette, Brandslund, Ivan, Buchanan, Thomas, Burant, Charles, Butterworth, Adam, Canouil, Mickaël, Chan, Juliana, Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, and Cushman, Mary

Subjects
Humans, Adipocytes, Chromatin, Coronary Artery Disease, Diabetes Mellitus, Type 2, Diabetic Nephropathies, Disease Progression, Endothelial Cells, Enteroendocrine Cells, Epigenomics, Genetic Predisposition to Disease, Genome-Wide Association Study, Islets of Langerhans, Multifactorial Inheritance, Peripheral Arterial Disease, Single-Cell Analysis
Abstract

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P

Published
2024

5. Genetic architecture and biology of youth-onset type 2 diabetes

Author

Kwak, Soo Heon, Srinivasan, Shylaja, Chen, Ling, Todd, Jennifer, Mercader, Josep M., Jensen, Elizabeth T., Divers, Jasmin, Mottl, Amy K., Pihoker, Catherine, Gandica, Rachelle G., Laffel, Lori M., Isganaitis, Elvira, Haymond, Morey W., Levitsky, Lynne L., Pollin, Toni I., Florez, Jose C., and Flannick, Jason

Published
2024
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8. 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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11. Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

Author

Mahajan, Anubha, Spracklen, Cassandra N, Zhang, Weihua, Ng, Maggie CY, Petty, Lauren E, Kitajima, Hidetoshi, Yu, Grace Z, Rüeger, Sina, Speidel, Leo, Kim, Young Jin, Horikoshi, Momoko, Mercader, Josep M, Taliun, Daniel, Moon, Sanghoon, Kwak, Soo-Heon, Robertson, Neil R, Rayner, Nigel W, Loh, Marie, Kim, Bong-Jo, Chiou, Joshua, Miguel-Escalada, Irene, della Briotta Parolo, Pietro, Lin, Kuang, Bragg, Fiona, Preuss, Michael H, Takeuchi, Fumihiko, Nano, Jana, Guo, Xiuqing, Lamri, Amel, Nakatochi, Masahiro, Scott, Robert A, Lee, Jung-Jin, Huerta-Chagoya, Alicia, Graff, Mariaelisa, Chai, Jin-Fang, Parra, Esteban J, Yao, Jie, Bielak, Lawrence F, Tabara, Yasuharu, Hai, Yang, Steinthorsdottir, Valgerdur, Cook, James P, Kals, Mart, Grarup, Niels, Schmidt, Ellen M, Pan, Ian, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloe, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Ahmad, Meraj, Noordam, Raymond, Lim, Victor JY, Tam, Claudia HT, Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M, Lecoeur, Cécile, Prins, Bram Peter, Nicolas, Aude, Yanek, Lisa R, Chen, Guanjie, Jensen, Richard A, Tajuddin, Salman, Kabagambe, Edmond K, An, Ping, Xiang, Anny H, Choi, Hyeok Sun, Cade, Brian E, Tan, Jingyi, Flanagan, Jack, Abaitua, Fernando, Adair, Linda S, Adeyemo, Adebowale, Aguilar-Salinas, Carlos A, Akiyama, Masato, Anand, Sonia S, Bertoni, Alain, Bian, Zheng, Bork-Jensen, Jette, Brandslund, Ivan, Brody, Jennifer A, Brummett, Chad M, Buchanan, Thomas A, Canouil, Mickaël, Chan, Juliana CN, Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, and Cushman, Mary

Subjects
Genetics, Diabetes, Human Genome, Metabolic and endocrine, Diabetes Mellitus, Type 2, Ethnicity, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Risk Factors, FinnGen, eMERGE Consortium, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P 50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

Published
2022

14. Determinants of penetrance and variable expressivity in monogenic metabolic conditions across 77,184 exomes.

Author

Goodrich, Julia K, Singer-Berk, Moriel, Son, Rachel, Sveden, Abigail, Wood, Jordan, England, Eleina, Cole, Joanne B, Weisburd, Ben, Watts, Nick, Caulkins, Lizz, Dornbos, Peter, Koesterer, Ryan, Zappala, Zachary, Zhang, Haichen, Maloney, Kristin A, Dahl, Andy, Aguilar-Salinas, Carlos A, Atzmon, Gil, Barajas-Olmos, Francisco, Barzilai, Nir, Blangero, John, Boerwinkle, Eric, Bonnycastle, Lori L, Bottinger, Erwin, Bowden, Donald W, Centeno-Cruz, Federico, Chambers, John C, Chami, Nathalie, Chan, Edmund, Chan, Juliana, Cheng, Ching-Yu, Cho, Yoon Shin, Contreras-Cubas, Cecilia, Córdova, Emilio, Correa, Adolfo, DeFronzo, Ralph A, Duggirala, Ravindranath, Dupuis, Josée, Garay-Sevilla, Ma Eugenia, García-Ortiz, Humberto, Gieger, Christian, Glaser, Benjamin, González-Villalpando, Clicerio, Gonzalez, Ma Elena, Grarup, Niels, Groop, Leif, Gross, Myron, Haiman, Christopher, Han, Sohee, Hanis, Craig L, Hansen, Torben, Heard-Costa, Nancy L, Henderson, Brian E, Hernandez, Juan Manuel Malacara, Hwang, Mi Yeong, Islas-Andrade, Sergio, Jørgensen, Marit E, Kang, Hyun Min, Kim, Bong-Jo, Kim, Young Jin, Koistinen, Heikki A, Kooner, Jaspal Singh, Kuusisto, Johanna, Kwak, Soo-Heon, Laakso, Markku, Lange, Leslie, Lee, Jong-Young, Lee, Juyoung, Lehman, Donna M, Linneberg, Allan, Liu, Jianjun, Loos, Ruth JF, Lyssenko, Valeriya, Ma, Ronald CW, Martínez-Hernández, Angélica, Meigs, James B, Meitinger, Thomas, Mendoza-Caamal, Elvia, Mohlke, Karen L, Morris, Andrew D, Morrison, Alanna C, Ng, Maggie CY, Nilsson, Peter M, O'Donnell, Christopher J, Orozco, Lorena, Palmer, Colin NA, Park, Kyong Soo, Post, Wendy S, Pedersen, Oluf, Preuss, Michael, Psaty, Bruce M, Reiner, Alexander P, Revilla-Monsalve, Cristina, Rich, Stephen S, Rotter, Jerome I, Saleheen, Danish, Schurmann, Claudia, Sim, Xueling, Sladek, Rob, and Small, Kerrin S

Subjects
AMP-T2D-GENES Consortia, Humans, Diabetes Mellitus, Type 2, Genetic Predisposition to Disease, Risk Assessment, Genotype, Multifactorial Inheritance, Penetrance, Adult, Dyslipidemias, Exome, Biomarkers, Biological Variation, Population
Abstract

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.

Published
2021

15. Identification of type 2 diabetes loci in 433,540 East Asian individuals

Author

Spracklen, Cassandra N, Horikoshi, Momoko, Kim, Young Jin, Lin, Kuang, Bragg, Fiona, Moon, Sanghoon, Suzuki, Ken, Tam, Claudia HT, Tabara, Yasuharu, Kwak, Soo-Heon, Takeuchi, Fumihiko, Long, Jirong, Lim, Victor JY, Chai, Jin-Fang, Chen, Chien-Hsiun, Nakatochi, Masahiro, Yao, Jie, Choi, Hyeok Sun, Iyengar, Apoorva K, Perrin, Hannah J, Brotman, Sarah M, van de Bunt, Martijn, Gloyn, Anna L, Below, Jennifer E, Boehnke, Michael, Bowden, Donald W, Chambers, John C, Mahajan, Anubha, McCarthy, Mark I, Ng, Maggie CY, Petty, Lauren E, Zhang, Weihua, Morris, Andrew P, Adair, Linda S, Akiyama, Masato, Bian, Zheng, Chan, Juliana CN, Chang, Li-Ching, Chee, Miao-Li, Chen, Yii-Der Ida, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, Du, Shufa, Gordon-Larsen, Penny, Gross, Myron, Guo, Xiuqing, Guo, Yu, Han, Sohee, Howard, Annie-Green, Huang, Wei, Hung, Yi-Jen, Hwang, Mi Yeong, Hwu, Chii-Min, Ichihara, Sahoko, Isono, Masato, Jang, Hye-Mi, Jiang, Guozhi, Jonas, Jost B, Kamatani, Yoichiro, Katsuya, Tomohiro, Kawaguchi, Takahisa, Khor, Chiea-Chuen, Kohara, Katsuhiko, Lee, Myung-Shik, Lee, Nanette R, Li, Liming, Liu, Jianjun, Luk, Andrea O, Lv, Jun, Okada, Yukinori, Pereira, Mark A, Sabanayagam, Charumathi, Shi, Jinxiu, Shin, Dong Mun, So, Wing Yee, Takahashi, Atsushi, Tomlinson, Brian, Tsai, Fuu-Jen, van Dam, Rob M, Xiang, Yong-Bing, Yamamoto, Ken, Yamauchi, Toshimasa, Yoon, Kyungheon, Yu, Canqing, Yuan, Jian-Min, Zhang, Liang, Zheng, Wei, Igase, Michiya, Cho, Yoon Shin, Rotter, Jerome I, Wang, Ya-Xing, Sheu, Wayne HH, Yokota, Mitsuhiro, Wu, Jer-Yuarn, Cheng, Ching-Yu, Wong, Tien-Yin, Shu, Xiao-Ou, Kato, Norihiro, and Park, Kyong-Soo

Subjects
Human Genome, Diabetes, Biotechnology, Genetics, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Aldehyde Dehydrogenase, Mitochondrial, Alleles, Ankyrins, Asian People, Body Mass Index, Case-Control Studies, Diabetes Mellitus, Type 2, Europe, Eye Proteins, Asia, Eastern, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Homeodomain Proteins, Humans, Male, Nerve Tissue Proteins, RNA, Messenger, Transcription Factors, Transcription, Genetic, General Science & Technology
Abstract

Meta-analyses of genome-wide association studies (GWAS) have identified more than 240 loci that are associated with type 2 diabetes (T2D)1,2; however, most of these loci have been identified in analyses of individuals with European ancestry. Here, to examine T2D risk in East Asian individuals, we carried out a meta-analysis of GWAS data from 77,418 individuals with T2D and 356,122 healthy control individuals. In the main analysis, we identified 301 distinct association signals at 183 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 61 loci that are newly implicated in predisposition to T2D. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. Previously undescribed associations include signals in or near GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect the differentiation of muscle and adipose cells3. At another locus, expression quantitative trait loci at two overlapping T2D signals affect two genes-NKX6-3 and ANK1-in different tissues4-6. Association studies in diverse populations identify additional loci and elucidate disease-associated genes, biology, and pathways.

Published
2020

17. Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls

Author

Flannick, Jason, Mercader, Josep M, Fuchsberger, Christian, Udler, Miriam S, Mahajan, Anubha, Wessel, Jennifer, Teslovich, Tanya M, Caulkins, Lizz, Koesterer, Ryan, Barajas-Olmos, Francisco, Blackwell, Thomas W, Boerwinkle, Eric, Brody, Jennifer A, Centeno-Cruz, Federico, Chen, Ling, Chen, Siying, Contreras-Cubas, Cecilia, Córdova, Emilio, Correa, Adolfo, Cortes, Maria, DeFronzo, Ralph A, Dolan, Lawrence, Drews, Kimberly L, Elliott, Amanda, Floyd, James S, Gabriel, Stacey, Garay-Sevilla, Maria Eugenia, García-Ortiz, Humberto, Gross, Myron, Han, Sohee, Heard-Costa, Nancy L, Jackson, Anne U, Jørgensen, Marit E, Kang, Hyun Min, Kelsey, Megan, Kim, Bong-Jo, Koistinen, Heikki A, Kuusisto, Johanna, Leader, Joseph B, Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Lyssenko, Valeriya, Manning, Alisa K, Marcketta, Anthony, Malacara-Hernandez, Juan Manuel, Martínez-Hernández, Angélica, Matsuo, Karen, Mayer-Davis, Elizabeth, Mendoza-Caamal, Elvia, Mohlke, Karen L, Morrison, Alanna C, Ndungu, Anne, Ng, Maggie CY, O’Dushlaine, Colm, Payne, Anthony J, Pihoker, Catherine, Post, Wendy S, Preuss, Michael, Psaty, Bruce M, Vasan, Ramachandran S, Rayner, N William, Reiner, Alexander P, Revilla-Monsalve, Cristina, Robertson, Neil R, Santoro, Nicola, Schurmann, Claudia, So, Wing Yee, Soberón, Xavier, Stringham, Heather M, Strom, Tim M, Tam, Claudia HT, Thameem, Farook, Tomlinson, Brian, Torres, Jason M, Tracy, Russell P, van Dam, Rob M, Vujkovic, Marijana, Wang, Shuai, Welch, Ryan P, Witte, Daniel R, Wong, Tien-Yin, Atzmon, Gil, Barzilai, Nir, Blangero, John, Bonnycastle, Lori L, Bowden, Donald W, Chambers, John C, Chan, Edmund, Cheng, Ching-Yu, Cho, Yoon Shin, Collins, Francis S, de Vries, Paul S, Duggirala, Ravindranath, Glaser, Benjamin, Gonzalez, Clicerio, Gonzalez, Ma Elena, Groop, Leif, Kooner, Jaspal Singh, and Kwak, Soo Heon

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Prevention, Biotechnology, Diabetes, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Animals, Case-Control Studies, Decision Support Techniques, Diabetes Mellitus, Type 2, Exome, Female, Gene Frequency, Genome-Wide Association Study, Humans, Male, Mice, Mice, Knockout, Exome Sequencing, Broad Genomics Platform, DiscovEHR Collaboration, CHARGE, LuCamp, ProDiGY, GoT2D, ESP, SIGMA-T2D, T2D-GENES, AMP-T2D-GENES, General Science & Technology
Abstract

Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10-3) and candidate genes from knockout mice (P = 5.2 × 10-3). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.

Published
2019

20. Long‐term efficacy and safety of enavogliflozin in Korean people with type 2 diabetes: A 52‐week extension of a Phase 3 randomized controlled trial.

Author

Kwak, Soo Heon, Han, Kyung Ah, Kim, Eun Sook, Choi, Sung Hee, Won, Jong Chul, Yu, Jae Myung, Oh, Seungjoon, Yoo, Hye Jin, Kim, Chong Hwa, Kim, Kyung‐Soo, Chun, SungWan, Kim, Yong Hyun, Cho, Seung Ah, Kim, Da Hye, and Park, Kyong Soo

Subjects
*TYPE 2 diabetes, *CLINICAL trials, *DRUG side effects, *GLYCEMIC control, *KOREANS
Abstract

Aims: To evaluate the long‐term safety and efficacy of enavogliflozin monotherapy (0.3 mg/day) in individuals with type 2 diabetes mellitus (T2DM). Materials and Methods: Following a 24‐week randomized, double‐blind treatment period with enavogliflozin 0.3 mg/day (n = 77) or placebo (n = 69), consenting participants received enavogliflozin 0.3 mg/day for an additional 28 weeks during an open‐label extension (OLE) period. The safety and efficacy of enavogliflozin were assessed at Week 52. Results: A total of 37 participants continued enavogliflozin (maintenance group), and 26 participants switched from placebo to enavogliflozin (switch group). No additional adverse drug reactions related to enavogliflozin were observed during the OLE period. At Week 52, glycated haemoglobin (HbA1c) and fasting plasma glucose were significantly lower than at the baseline, by 0.9% and 24.9 mg/dL, respectively, in the maintenance group (p < 0.0001 for both), and by 0.7% and 18.0 mg/dL, respectively, in the switch group (p < 0.0001 and p = 0.002). The proportions of participants reaching HbA1c 7.0% (53 mmol/mol) at Week 52 were 69.4% in the maintenance group and 65.4% in the switch group. A significant increase in urine glucose‐to‐creatinine ratio was observed at Week 52, by 84.9 g/g and 67.1 g/g in the maintenance and switch groups, respectively (p < 0.0001 for both). Body weight in both groups decreased significantly (p < 0.0001) from baseline to Week 52, by 3.5 kg and 3.8 kg in the maintenance and switch groups, respectively. Conclusions: Enavogliflozin 0.3 mg monotherapy provides long‐term glycaemic control in T2DM and is safe and well tolerated during a 52‐week treatment period. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Discrepancy Between Genetically Predicted and Observed BMI Predicts Incident Type 2 Diabetes.

Author

Rhee, Tae-Min, Choi, Jaewon, Lee, Hyunsuk, Merino, Jordi, Park, Jun-Bean, and Kwak, Soo Heon

Subjects
GENETIC risk score, PROPORTIONAL hazards models, TYPE 2 diabetes, INSULIN sensitivity, EXPERIMENTAL design
Abstract

OBJECTIVE: Obesity is a key predictor of type 2 diabetes (T2D). However, metabolic complications are not solely due to increased BMI. We hypothesized that differences between genetically predicted BMI and observed BMI (BMI-diff) could reflect deviation from individual set point and may predict incident T2D. RESEARCH DESIGN AND METHODS: From the UK Biobank cohort, we selected participants of European ancestry without T2D (n = 332,154). The polygenic risk score for BMI was calculated via Bayesian regression and continuous shrinkage priors (PRS-CS). According to the BMI-diff, the 10-year risk of T2D was assessed using multivariable Cox proportional hazards model. Independent data from the Korean Genome and Epidemiology Study (KoGES) cohort from South Korea (n = 7,430) were used for replication. RESULTS: Participants from the UK Biobank were divided into train (n = 268,041) and test set (n = 115,119) to establish genetically predicted BMI. In the test set, the genetically predicted BMI explained 7.1% of the variance of BMI, and there were 3,599 T2D cases (3.1%) during a 10-year follow-up. Participants in the higher quintiles of BMI-diff (more obese than genetically predicted) had significantly higher risk of T2D than those in the lowest quintile after adjusting for observed BMI: the adjusted hazard ratio of the 1st quintile (vs. 5th quintile) was 1.61 (95% CI 1.26–2.05, P < 0.001). Results were consistent among individuals in the KoGES study. Moreover, higher BMI than predicted was associated with impaired insulin sensitivity. CONCLUSIONS: Having a higher BMI than genetically predicted is associated with an increased risk of T2D. These findings underscore the potential to reassess T2D risk based on individual levels of obesity using genetic thresholds for BMI. [ABSTRACT FROM AUTHOR]

Published
2024
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22. 청년 2형당뇨병의 통합적 관리 전략.

Author

Seo, Mi-Hae and Kwak, Soo Heon

Abstract

The prevalence of young-onset type 2 diabetes is increasing rapidly worldwide along with the incidence of obesity, including in Korea. Compared with later onset type 2 diabetes, patients with young-onset type 2 diabetes have a higher risk of microvascular complication, macrovascular complication, and disease-related mortality. Thus, integrated attention and management of associated pathobiological, socioeconomic, and mental health factors are needed. Based on the very few evidence-based studies in management, in this review, we describe strategies for the integrated management for young-onset type 2 diabetes. [ABSTRACT FROM AUTHOR]

Published
2024
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23. Efficacy and tolerability of initial triple combination therapy with metformin, dapagliflozin and saxagliptin compared with stepwise add‐on therapy in drug‐naïve patients with type 2 diabetes (TRIPLE‐AXEL study): A multicentre, randomized, 104‐week, open‐label, active‐controlled trial

Author

Kim, Nam Hoon, Moon, Jun Sung, Lee, Yong‐ho, Cho, Ho Chan, Kwak, Soo Heon, Lim, Soo, Moon, Min Kyong, Kim, Dong‐Lim, Kim, Tae Ho, Ko, Eunvin, Lee, Juneyoung, and Kim, Sin Gon

Subjects
TYPE 2 diabetes, GLYCEMIC control, SODIUM-glucose cotransporter 2 inhibitors, WEIGHT gain, HYPOGLYCEMIA, DAPAGLIFLOZIN
Abstract

Aim: To evaluate the efficacy and tolerability of an initial triple combination therapy (TCT) compared with conventional stepwise add‐on therapy (SAT) in patients with newly diagnosed type 2 diabetes (T2D). Materials and Methods: This multicentre, randomized, 104‐week, open‐label trial randomized 105 patients with drug‐naïve T2D (with HbA1c level ≥ 8.0%, < 11.0%) to the TCT (1000 mg of metformin, 10 mg of dapagliflozin and 5 mg of saxagliptin once daily) or SAT (initiated with metformin, followed by glimepiride and sitagliptin) groups. The primary outcome was the proportion of patients who achieved an HbA1c level of less than 6.5% without hypoglycaemia, weight gain of 5% or higher, or discontinuation of drugs because of adverse events at week 104. Results: HbA1c reduction from baseline at week 104 was similar between the groups (the least squares mean change was −2.56% in the TCT group vs. –2.75% in the SAT group). The primary outcome was achieved in 39.0% and 17.1% of the TCT and SAT groups, respectively, with a risk difference of 22.0 (95% confidence interval 3.0, 40.8; P =.027). HbA1c level less than 6.5% at week 104 was 46.3% in both the TCT and SAT groups, whereas the incidence of hypoglycaemia, weight gain, or discontinuation of drugs was 16.7% and 62.0% in the TCT and SAT groups, respectively (P <.001). TCT was well‐tolerated and had fewer adverse events than SAT. Conclusions: Among newly diagnosed patients with T2D, initial TCT effectively lowered HbA1c levels with higher tolerability and safety than SAT for 104 weeks, suggesting a novel strategy for initial combination therapy in T2D patients. [ABSTRACT FROM AUTHOR]

Published
2024
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24. Genome-Wide Polygenic Risk Score Predicts Incident Type 2 Diabetes in Women With History of Gestational Diabetes.

Author

Choi, Jaewon, Lee, Hyunsuk, Kuang, Alan, Huerta-Chagoya, Alicia, Scholtens, Denise M., Choi, Daeho, Han, Minseok, Lowe, William L., Manning, Alisa K., Jang, Hak Chul, Park, Kyong Soo, and Kwak, Soo Heon

Subjects
GENETIC risk score, GESTATIONAL diabetes, RECEIVER operating characteristic curves, TYPE 2 diabetes, SYSTOLIC blood pressure
Abstract

OBJECTIVE: Women with a history of gestational diabetes mellitus (GDM) are at increased risk of developing type 2 diabetes (T2D). It remains unclear whether genetic information improves prediction of incident T2D in these women. RESEARCH DESIGN AND METHODS: Using five independent cohorts representing four different ancestries (n = 1,895), we investigated whether a genome-wide T2D polygenic risk score (PRS) is associated with increased risk of incident T2D. We also calculated the area under the receiver operating characteristics curve (AUROC) and continuous net reclassification improvement (NRI) following the incorporation of T2D PRS into clinical risk models to assess the diagnostic utility. RESULTS: Among 1,895 women with previous history of GDM, 363 (19.2%) developed T2D in a range of 2 to 30 years. T2D PRS was higher in those who developed T2D (−0.08 vs. 0.31, P = 2.3 × 10−11) and was associated with an increased risk of incident T2D (odds ratio 1.52 per 1-SD increase, 95% CI 1.05–2.21, P = 0.03). In a model that includes age, family history of diabetes, systolic blood pressure, and BMI, the incorporation of PRS led to an increase in AUROC for T2D from 0.71 to 0.74 and an intermediate improvement of NRI (0.32, 95% CI 0.15–0.49, P = 3.0 × 10−4). Although there was variation, a similar trend was observed across study cohorts. CONCLUSIONS: In cohorts of GDM women with diverse ancestry, T2D PRS was significantly associated with future development of T2D. A significant but small improvement was observed in AUROC when T2D PRS was integrated into clinical risk models to predict incident T2D. [ABSTRACT FROM AUTHOR]

Published
2024
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25. Erratum: Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

Author

Flannick, Jason, Fuchsberger, Christian, Mahajan, Anubha, Teslovich, Tanya M, Agarwala, Vineeta, Gaulton, Kyle J, Caulkins, Lizz, Koesterer, Ryan, Ma, Clement, Moutsianas, Loukas, McCarthy, Davis J, Rivas, Manuel A, Perry, John RB, Sim, Xueling, Blackwell, Thomas W, Robertson, Neil R, Rayner, N William, Cingolani, Pablo, Locke, Adam E, Tajes, Juan Fernandez, Highland, Heather M, Dupuis, Josee, Chines, Peter S, Lindgren, Cecilia M, Hartl, Christopher, Jackson, Anne U, Chen, Han, Huyghe, Jeroen R, van de Bunt, Martijn, Pearson, Richard D, Kumar, Ashish, Müller-Nurasyid, Martina, Grarup, Niels, Stringham, Heather M, Gamazon, Eric R, Lee, Jaehoon, Chen, Yuhui, Scott, Robert A, Below, Jennifer E, Chen, Peng, Huang, Jinyan, Go, Min Jin, Stitzel, Michael L, Pasko, Dorota, Parker, Stephen CJ, Varga, Tibor V, Green, Todd, Beer, Nicola L, Day-Williams, Aaron G, Ferreira, Teresa, Fingerlin, Tasha, Horikoshi, Momoko, Hu, Cheng, Huh, Iksoo, Ikram, Mohammad Kamran, Kim, Bong-Jo, Kim, Yongkang, Kim, Young Jin, Kwon, Min-Seok, Lee, Juyoung, Lee, Selyeong, Lin, Keng-Han, Maxwell, Taylor J, Nagai, Yoshihiko, Wang, Xu, Welch, Ryan P, Yoon, Joon, Zhang, Weihua, Barzilai, Nir, Voight, Benjamin F, Han, Bok-Ghee, Jenkinson, Christopher P, Kuulasmaa, Teemu, Kuusisto, Johanna, Manning, Alisa, Ng, Maggie CY, Palmer, Nicholette D, Balkau, Beverley, Stančáková, Alena, Abboud, Hanna E, Boeing, Heiner, Giedraitis, Vilmantas, Prabhakaran, Dorairaj, Gottesman, Omri, Scott, James, Carey, Jason, Kwan, Phoenix, Grant, George, Smith, Joshua D, Neale, Benjamin M, Purcell, Shaun, Butterworth, Adam S, Howson, Joanna MM, Lee, Heung Man, Lu, Yingchang, Kwak, Soo-Heon, Zhao, Wei, Danesh, John, and Lam, Vincent KL

Abstract

This corrects the article DOI: 10.1038/sdata.2017.179.

Published
2018

26. Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.

Author

Flannick, Jason, Fuchsberger, Christian, Mahajan, Anubha, Teslovich, Tanya M, Agarwala, Vineeta, Gaulton, Kyle J, Caulkins, Lizz, Koesterer, Ryan, Ma, Clement, Moutsianas, Loukas, McCarthy, Davis J, Rivas, Manuel A, Perry, John RB, Sim, Xueling, Blackwell, Thomas W, Robertson, Neil R, Rayner, N William, Cingolani, Pablo, Locke, Adam E, Tajes, Juan Fernandez, Highland, Heather M, Dupuis, Josee, Chines, Peter S, Lindgren, Cecilia M, Hartl, Christopher, Jackson, Anne U, Chen, Han, Huyghe, Jeroen R, van de Bunt, Martijn, Pearson, Richard D, Kumar, Ashish, Müller-Nurasyid, Martina, Grarup, Niels, Stringham, Heather M, Gamazon, Eric R, Lee, Jaehoon, Chen, Yuhui, Scott, Robert A, Below, Jennifer E, Chen, Peng, Huang, Jinyan, Go, Min Jin, Stitzel, Michael L, Pasko, Dorota, Parker, Stephen CJ, Varga, Tibor V, Green, Todd, Beer, Nicola L, Day-Williams, Aaron G, Ferreira, Teresa, Fingerlin, Tasha, Horikoshi, Momoko, Hu, Cheng, Huh, Iksoo, Ikram, Mohammad Kamran, Kim, Bong-Jo, Kim, Yongkang, Kim, Young Jin, Kwon, Min-Seok, Lee, Juyoung, Lee, Selyeong, Lin, Keng-Han, Maxwell, Taylor J, Nagai, Yoshihiko, Wang, Xu, Welch, Ryan P, Yoon, Joon, Zhang, Weihua, Barzilai, Nir, Voight, Benjamin F, Han, Bok-Ghee, Jenkinson, Christopher P, Kuulasmaa, Teemu, Kuusisto, Johanna, Manning, Alisa, Ng, Maggie CY, Palmer, Nicholette D, Balkau, Beverley, Stančáková, Alena, Abboud, Hanna E, Boeing, Heiner, Giedraitis, Vilmantas, Prabhakaran, Dorairaj, Gottesman, Omri, Scott, James, Carey, Jason, Kwan, Phoenix, Grant, George, Smith, Joshua D, Neale, Benjamin M, Purcell, Shaun, Butterworth, Adam S, Howson, Joanna MM, Lee, Heung Man, Lu, Yingchang, Kwak, Soo-Heon, Zhao, Wei, Danesh, John, and Lam, Vincent KL

Subjects
Humans, Diabetes Mellitus, Type 2, European Continental Ancestry Group, Genetic Variation, Diabetes, Human Genome, Genetics, 2.1 Biological and endogenous factors, Metabolic and endocrine
Abstract

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

Published
2017

27. Alcohol is neither a risk factor nor a protective factor for sudden cardiac death and/or fatal ventricular arrhythmia; a population-based study with genetic traits and alcohol consumption in UK Biobank

Author

Park, Chan Soon, primary, Choi, Jaewon, additional, Choi, JungMin, additional, Lee, Kyung-Yeon, additional, Ahn, Hyo-Jeong, additional, Kwon, Soonil, additional, Lee, So-Ryoung, additional, Choi, Eue-Keun, additional, Kwak, Soo Heon, additional, and Oh, Seil, additional

Published
2024
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29. Higher Genetic Risk for Type 2 Diabetes Is Associated With a Faster Decline of β-Cell Function in an East Asian Population.

Author

Lee, Hyunsuk, Choi, Jaewon, Kim, Jong-Il, Watanabe, Richard M., Cho, Nam H., Park, Kyong Soo, and Kwak, Soo Heon

Subjects
EAST Asians, TYPE 2 diabetes, GENETIC risk score, GLUCOSE tolerance tests, GENETIC variation
Abstract

OBJECTIVE: While most genetic variants of type 2 diabetes (T2D) are suggested to be associated with β-cell dysfunction cross sectionally, their association with the longitudinal change of β-cell function remains largely unknown. RESEARCH DESIGN AND METHODS: We analyzed data from 6,311 participants without T2D at baseline (mean [SD] age 51.6 [8.7] years) from a community-based prospective cohort in Korea. Participants underwent biennial 2-h 75-g oral glucose tolerance tests (OGTTs) during 14 years of follow-up, and the OGTT-derived disposition index (DI) was used as a marker for β-cell function. Genetic risk was quantified using the genome-wide polygenic risk score (PRS) and was stratified into low (1st quintile), intermediate (2nd–4th quintiles), and high (5th quintile) genetic risk. Lifestyle was assessed according to Life's Essential 8. RESULTS: During a mean follow-up of 10.9 years, 374 (29.6%), 851 (22.5%), and 188 (14.9%) participants developed T2D in the high, intermediate, and low genetic risk groups, respectively. Compared with the low genetic risk group, participants in the high genetic risk group had a 25% lower DI at baseline. Furthermore, in longitudinal analysis, we observed a 1.83-fold faster decline in log2-transformed DI per year (−0.034 vs. −0.019, P = 2.1 × 10−3; per 1-SD increase in T2D PRS, P = 1.2 × 10−4). Healthy lifestyle attenuated the rate of decline in DI across all genetic risk groups. CONCLUSIONS: Individuals with a higher genetic risk for T2D exhibited not only a lower OGTT-derived β-cell function at baseline but also a notably more rapid decline during follow-up. This information could be used to enable a focused precision prevention with lifestyle intervention. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People With Type 2 Diabetes.

Author

Kwak, Soo Heon, Hernandez-Cancela, Ryan B., DiCorpo, Daniel A., Condon, David E., Merino, Jordi, Wu, Peitao, Brody, Jennifer A., Yao, Jie, Guo, Xiuqing, Ahmadizar, Fariba, Meyer, Mariah, Sincan, Murat, Mercader, Josep M., Lee, Sujin, Haessler, Jeffrey, Vy, Ha My T., Lin, Zhaotong, Armstrong, Nicole D., Gu, Shaopeng, and Tsao, Noah L.

Subjects
*GENOME-wide association studies, *TYPE 2 diabetes, *CARDIOVASCULAR diseases, *CARDIOVASCULAR diseases risk factors, *CORONARY artery disease
Abstract

OBJECTIVE: To identify genetic risk factors for incident cardiovascular disease (CVD) among people with type 2 diabetes (T2D). RESEARCH DESIGN AND METHODS: We conducted a multiancestry time-to-event genome-wide association study for incident CVD among people with T2D. We also tested 204 known coronary artery disease (CAD) variants for association with incident CVD. RESULTS: Among 49,230 participants with T2D, 8,956 had incident CVD events (event rate 18.2%). We identified three novel genetic loci for incident CVD: rs147138607 (near CACNA1E/ZNF648 , hazard ratio [HR] 1.23, P = 3.6 × 10−9), rs77142250 (near HS3ST1 , HR 1.89, P = 9.9 × 10−9), and rs335407 (near TFB1M/NOX3 , HR 1.25, P = 1.5 × 10−8). Among 204 known CAD loci, 5 were associated with incident CVD in T2D (multiple comparison–adjusted P < 0.00024, 0.05/204). A standardized polygenic score of these 204 variants was associated with incident CVD with HR 1.14 (P = 1.0 × 10−16). CONCLUSIONS: The data point to novel and known genomic regions associated with incident CVD among individuals with T2D. [ABSTRACT FROM AUTHOR]

Published
2024
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36. Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus

Author

Kwak, Soo Heon, primary, Hernandez-Cancela, Ryan B., additional, DiCorpo, Daniel A, additional, Condon, David E., additional, Merino, Jordi, additional, Wu, Peitao, additional, Brody, Jennifer A, additional, Yao, Jie, additional, Guo, Xiuqing, additional, Ahmadizar, Fariba, additional, Meyer, Mariah, additional, Sincan, Murat, additional, Mercader, Josep M., additional, Lee, Sujin, additional, Haessler, Jeffrey, additional, Vy, Ha My T., additional, Lin, Zhaotong, additional, Armstrong, Nicole D., additional, Gu, Shaopeng, additional, Tsao, Noah L., additional, Lange, Leslie A., additional, Wang, Ningyuan, additional, Wiggins, Kerri L., additional, Trompet, Stella, additional, Liu, Simin, additional, Loos, Ruth J.F., additional, Judy, Renae, additional, Schroeder, Philip H., additional, Hasbani, Natalie R., additional, Bos, Maxime M., additional, Morrison, Alanna C., additional, Jackson, Rebecca D., additional, Reiner, Alexander P., additional, Manson, JoAnn E., additional, Chaudhary, Ninad S., additional, Carmichael, Lynn K., additional, Chen, Yii-Der Ida, additional, Taylor, Kent D., additional, Ghanbari, Mohsen, additional, van Meurs, Joyce, additional, Pitsillides, Achilleas N, additional, Psaty, Bruce M., additional, Noordam, Raymond, additional, Do, Ron, additional, Park, Kyong Soo, additional, Jukema, J Wouter, additional, Kavousi, Maryam, additional, Correa, Adolfo, additional, Rich, Stephen S., additional, Damrauer, Scott M., additional, Hajek, Catherine, additional, Cho, Nam H., additional, Irvin, Marguerite R., additional, Pankow, James S., additional, Nadkarni, Girish N., additional, Sladek, Robert, additional, Goodarzi, Mark O., additional, Florez, Jose C., additional, Chasman, Daniel I., additional, Heckbert, Susan R., additional, Kooperberg, Charles, additional, Dupuis, Josée, additional, Malhotra, Rajeev, additional, de Vries, Paul S., additional, Liu, Ching-Ti, additional, Rotter, Jerome I., additional, and Meigs, James B., additional

Published
2023
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38. Insights from rare variants into the genetic architecture and biology of youth-onset type 2 diabetes

Author

Kwak, Soo Heon, primary, Sriniva, Shylaja, additional, Chen, Ling, additional, Todd, Jennifer, additional, Mercader, Josep, additional, Jensen, Elizabeth, additional, Divers, Jasmin, additional, Mottl, Amy, additional, Pihoker, Catherine, additional, Gandica, Rachelle, additional, Laffel, Lori, additional, Isganaitis, Elvira, additional, Haymond, Morey, additional, Levitsky, Lynne, additional, Pollin, Toni, additional, Florez, Jose, additional, and Flannick, Jason, additional

Published
2023
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43. Efficacy and safety of enavogliflozin, a novel SGLT2 inhibitor, in Korean people with type 2 diabetes: a 24‐week, multicentre, randomised, double‐blind, placebo‐controlled, phase III trial

Author

Kwak, Soo Heon, primary, Han, Kyung Ah, additional, Kim, Kyung‐Soo, additional, Yu, Jae Myung, additional, Kim, EunSook, additional, Won, Jong Chul, additional, Kang, Jun Goo, additional, Chung, Choon Hee, additional, Oh, Seungjoon, additional, Choi, Sung Hee, additional, Won, Kyu Chang, additional, Kim, Sin Gon, additional, Cho, Seung Ah, additional, Cho, Bo Young, additional, and Park, Kyong Soo, additional

Published
2023
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44. Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus

Author

RWE/Causal inference, Child Health, Kwak, Soo Heon, Hernandez-Cancela, Ryan B, DiCorpo, Daniel A, Condon, David E, Merino, Jordi, Wu, Peitao, Brody, Jennifer A, Yao, Jie, Guo, Xiuqing, Ahmadizar, Fariba, Meyer, Mariah, Sincan, Murat, Mercader, Josep M, Lee, Sujin, Haessler, Jeffrey, Vy, Ha My T, Lin, Zhaotong, Armstrong, Nicole D, Gu, Shaopeng, Tsao, Noah L, Lange, Leslie A, Wang, Ningyuan, Wiggins, Kerri L, Trompet, Stella, Liu, Simin, Loos, Ruth J F, Judy, Renae, Schroeder, Philip H, Hasbani, Natalie R, Bos, Maxime M, Morrison, Alanna C, Jackson, Rebecca D, Reiner, Alexander P, Manson, JoAnn E, Chaudhary, Ninad S, Carmichael, Lynn K, Chen, Yii-Der Ida, Taylor, Kent D, Ghanbari, Mohsen, van Meurs, Joyce, Pitsillides, Achilleas N, Psaty, Bruce M, Noordam, Raymond, Do, Ron, Park, Kyong Soo, Jukema, J Wouter, Kavousi, Maryam, Correa, Adolfo, Rich, Stephen S, Damrauer, Scott M, Hajek, Catherine, Cho, Nam H, Irvin, Marguerite R, Pankow, James S, Nadkarni, Girish N, Sladek, Robert, Goodarzi, Mark O, Florez, Jose C, Chasman, Daniel I, Heckbert, Susan R, Kooperberg, Charles, Dupuis, Josée, Malhotra, Rajeev, de Vries, Paul S, Liu, Ching-Ti, Rotter, Jerome I, Meigs, James B, RWE/Causal inference, Child Health, Kwak, Soo Heon, Hernandez-Cancela, Ryan B, DiCorpo, Daniel A, Condon, David E, Merino, Jordi, Wu, Peitao, Brody, Jennifer A, Yao, Jie, Guo, Xiuqing, Ahmadizar, Fariba, Meyer, Mariah, Sincan, Murat, Mercader, Josep M, Lee, Sujin, Haessler, Jeffrey, Vy, Ha My T, Lin, Zhaotong, Armstrong, Nicole D, Gu, Shaopeng, Tsao, Noah L, Lange, Leslie A, Wang, Ningyuan, Wiggins, Kerri L, Trompet, Stella, Liu, Simin, Loos, Ruth J F, Judy, Renae, Schroeder, Philip H, Hasbani, Natalie R, Bos, Maxime M, Morrison, Alanna C, Jackson, Rebecca D, Reiner, Alexander P, Manson, JoAnn E, Chaudhary, Ninad S, Carmichael, Lynn K, Chen, Yii-Der Ida, Taylor, Kent D, Ghanbari, Mohsen, van Meurs, Joyce, Pitsillides, Achilleas N, Psaty, Bruce M, Noordam, Raymond, Do, Ron, Park, Kyong Soo, Jukema, J Wouter, Kavousi, Maryam, Correa, Adolfo, Rich, Stephen S, Damrauer, Scott M, Hajek, Catherine, Cho, Nam H, Irvin, Marguerite R, Pankow, James S, Nadkarni, Girish N, Sladek, Robert, Goodarzi, Mark O, Florez, Jose C, Chasman, Daniel I, Heckbert, Susan R, Kooperberg, Charles, Dupuis, Josée, Malhotra, Rajeev, de Vries, Paul S, Liu, Ching-Ti, Rotter, Jerome I, and Meigs, James B

Published
2023

47. Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications

Author

Suzuki, Ken, Hatzikotoulas, Konstantinos, Southam, Lorraine, Taylor, Henry J., Yin, Xianyong, Lorenz, Kim M., Mandla, Ravi, Huerta-Chagoya, Alicia, Rayner, Nigel W., Bocher, Ozvan, Ana Luiza de, S. V. Arruda, Sonehara, Kyuto, Namba, Shinichi, Lee, Simon S. K., Preuss, Michael H., Petty, Lauren E., Schroeder, Philip, Vanderwerff, Brett, Kals, Mart, Bragg, Fiona, Lin, Kuang, Guo, Xiuqing, Zhang, Weihua, Yao, Jie, Kim, Young Jin, Graff, Mariaelisa, Takeuchi, Fumihiko, Nano, Jana, Lamri, Amel, Nakatochi, Masahiro, Moon, Sanghoon, Scott, Robert A., Cook, James P., Lee, Jung-Jin, Pan, Ian, Taliun, Daniel, Parra, Esteban J., Chai, Jin-Fang, Bielak, Lawrence F., Tabara, Yasuharu, Hai, Yang, Thorleifsson, Gudmar, Grarup, Niels, Sofer, Tamar, Wuttke, Matthias, Sarnowski, Chloé, Gieger, Christian, Nousome, Darryl, Trompet, Stella, Kwak, Soo-Heon, Long, Jirong, Sun, Meng, Tong, Lin, Chen, Wei-Min, Nongmaithem, Suraj S., Noordam, Raymond, Lim, Victor J. Y., Tam, Claudia H. T., Joo, Yoonjung Yoonie, Chen, Chien-Hsiun, Raffield, Laura M., Prins, Bram Peter, Nicolas, Aude, Yanek, Lisa R., Chen, Guanjie, Brody, Jennifer A., Kabagambe, Edmond, An, Ping, Xiang, Anny H., Choi, Hyeok Sun, Cade, Brian E., Tan, Jingyi, Alaine Broadaway, K., Williamson, Alice, Kamali, Zoha, Cui, Jinrui, Adair, Linda S., Adeyemo, Adebowale, Aguilar-Salinas, Carlos A., Ahluwalia, Tarunveer S., Anand, Sonia S., Bertoni, Alain, Bork-Jensen, Jette, Brandslund, Ivan, Buchanan, Thomas A., Burant, Charles F., Butterworth, Adam S., Canouil, Mickaël, Chan, Juliana C. N., Chang, Li-Ching, Chee, Miao-Li, Chen, Ji, Chen, Shyh-Huei, Chen, Yuan-Tsong, Chen, Zhengming, Chuang, Lee-Ming, Cushman, Mary, Danesh, John, Das, Swapan K., Janaka de Silva, H., Dedoussis, George, Dimitrov, Latchezar, Doumatey, Ayo P., Du, Shufa, Duan, Qing, Eckardt, Kai-Uwe, Emery, Leslie S., Evans, Daniel S., Evans, Michele K., Fischer, Krista, Floyd, James S., Ford, Ian, Franco, Oscar H., Frayling, Timothy M., Freedman, Barry I., Genter, Pauline, Gerstein, Hertzel C., Giedraitis, Vilmantas, González-Villalpando, Clicerio, González-Villalpando, Maria Elena, Gordon-Larsen, Penny, Gross, Myron, Guare, Lindsay A., Hackinger, Sophie, Han, Sohee, Hattersley, Andrew T., Herder, Christian, Horikoshi, Momoko, Howard, Annie-Green, Hsueh, Willa, Huang, Mengna, Huang, Wei, Hung, Yi-Jen, Hwang, Mi Yeong, Hwu, Chii-Min, Ichihara, Sahoko, Ikram, Mohammad Arfan, Ingelsson, Martin, Islam, Md. Tariqul, Isono, Masato, Jang, Hye-Mi, Jasmine, Farzana, Jiang, Guozhi, Jonas, Jost B., Jørgensen, Torben, Kandeel, Fouad R., Kasturiratne, Anuradhani, Katsuya, Tomohiro, Kaur, Varinderpal, Kawaguchi, Takahisa, Keaton, Jacob M., Kho, Abel N., Khor, Chiea-Chuen, Kibriya, Muhammad G., Kim, Duk-Hwan, Kronenberg, Florian, Kuusisto, Johanna, Läll, Kristi, Lange, Leslie A., Lee, Kyung Min, Lee, Myung-Shik, Lee, Nanette R., Leong, Aaron, Li, Liming, Li, Yun, Li-Gao, Ruifang, Lithgart, Symen, Lindgren, Cecilia M., Linneberg, Allan, Liu, Ching-Ti, Liu, Jianjun, Locke, Adam E., Louie, Tin, Luan, Jian’an, Luk, Andrea O., Luo, Xi, Lv, Jun, Lynch, Julie A., Lyssenko, Valeriya, Maeda, Shiro, Mamakou, Vasiliki, Mansuri, Sohail Rafik, Matsuda, Koichi, Meitinger, Thomas, Metspalu, Andres, Mo, Huan, Morris, Andrew D., Nadler, Jerry L., Nalls, Michael A., Nayak, Uma, Ntalla, Ioanna, Okada, Yukinori, Orozco, Lorena, Patel, Sanjay R., Patil, Snehal, Pei, Pei, Pereira, Mark A, Peters, Annette, Pirie, Fraser J., Polikowsky, Hannah G., Porneala, Bianca, Prasad, Gauri, Rasmussen-Torvik, Laura J., Reiner, Alexander P., Roden, Michael, Rohde, Rebecca, Roll, Katheryn, Sabanayagam, Charumathi, Sandow, Kevin, Sankareswaran, Alagu, Sattar, Naveed, Schönherr, Sebastian, Shahriar, Mohammad, Shen, Botong, Shi, Jinxiu, Shin, Dong Mun, Shojima, Nobuhiro, Smith, Jennifer A., So, Wing Yee, Stančáková, Alena, Steinthorsdottir, Valgerdur, Stilp, Adrienne M., Strauch, Konstantin, Taylor, Kent D., Thorand, Barbara, Thorsteinsdottir, Unnur, Tomlinson, Brian, Tran, Tam C., Tsai, Fuu-Jen, Tuomilehto, Jaakko, Tusie-Luna, Teresa, Udler, Miriam S., Valladares-Salgado, Adan, van Dam, Rob M., van Klinken, Jan B., Varma, Rohit, Wacher-Rodarte, Niels, Wheeler, Eleanor, Wickremasinghe, Ananda R., van Dijk, Ko Willems, Witte, Daniel R., Yajnik, Chittaranjan S., Yamamoto, Ken, Yamamoto, Kenichi, Yoon, Kyungheon, Yu, Canqing, Yuan, Jian-Min, Yusuf, Salim, Zawistowski, Matthew, Zhang, Liang, Zheng, Wei, Project, Biobank Japan, BioBank, Penn Medicine, Center, Regeneron Genetics, Consortium, eMERGE, Raffel, Leslie J, Igase, Michiya, Ipp, Eli, Redline, Susan, Cho, Yoon Shin, Lind, Lars, Province, Michael A., Fornage, Myriam, Hanis, Craig L., Ingelsson, Erik, Zonderman, Alan B., Psaty, Bruce M., Wang, Ya-Xing, Rotimi, Charles N., Becker, Diane M., Matsuda, Fumihiko, Liu, Yongmei, Yokota, Mitsuhiro, Kardia, Sharon L. R., Peyser, Patricia A., Pankow, James S., Engert, James C., Bonnefond, Amélie, Froguel, Philippe, Wilson, James G., Sheu, Wayne H. H., Wu, Jer-Yuarn, Geoffrey Hayes, M., Ma, Ronald C. W., Wong, Tien-Yin, Mook-Kanamori, Dennis O., Tuomi, Tiinamaija, Chandak, Giriraj R., Collins, Francis S., Bharadwaj, Dwaipayan, Paré, Guillaume, Sale, Michèle M., Ahsan, Habibul, Motala, Ayesha A., Shu, Xiao-Ou, Park, Kyong-Soo, Jukema, J Wouter, Cruz, Miguel, Chen, Yii-Der Ida, Rich, Stephen S., McKean-Cowdin, Roberta, Grallert, Harald, Cheng, Ching-Yu, Ghanbari, Mohsen, Tai, E-Shyong, Dupuis, Josee, Kato, Norihiro, Laakso, Markku, Köttgen, Anna, Koh, Woon-Puay, Bowden, Donald W., Palmer, Colin N. A., Kooner, Jaspal S., Kooperberg, Charles, Liu, Simin, North, Kari E., Saleheen, Danish, Hansen, Torben, Pedersen, Oluf, Wareham, Nicholas J., Lee, Juyoung, Kim, Bong-Jo, Millwood, Iona Y., Walters, Robin G., Stefansson, Kari, Goodarzi, Mark O., Mohlke, Karen L., Langenberg, Claudia, Haiman, Christopher A., Loos, Ruth J. F., Florez, Jose C., Rader, Daniel J., Ritchie, Marylyn D., Zöllner, Sebastian, Mägi, Reedik, Denny, Joshua C., Yamauchi, Toshimasa, Kadowaki, Takashi, Chambers, John C., Ng, Maggie C. Y., Sim, Xueling, Below, Jennifer E., Tsao, Philip S., Chang, Kyong-Mi, McCarthy, Mark I., Meigs, James B., Mahajan, Anubha, Spracklen, Cassandra N., Mercader, Josep M., Boehnke, Michael, Rotter, Jerome I., Vujkovic, Marijana, Voight, Benjamin F., Morris, Andrew P., and Zeggini, Eleftheria

Subjects
Article
Abstract

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P

Published
2023

49. Metabolic dysfunction-associated fatty liver disease as a risk factor for adverse outcomes in subsequent pregnancy: a nationwide cohort study

Author

Lee, Seung Mi, primary, Cho, Geum Joon, additional, Wi, Won Young, additional, Norwitz, Errol R., additional, Koo, Bo Kyung, additional, Lee, Jeesun, additional, Jung, Young Mi, additional, Kwak, Soo Heon, additional, Park, Chan-Wook, additional, Jun, Jong Kwan, additional, Joo, Sae Kyung, additional, Oh, Min-Jeong, additional, Kim, Won, additional, and Park, Joong Shin, additional

Published
2022
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50. High-throughput genetic clustering of type 2 diabetes loci reveals heterogeneous mechanistic pathways of metabolic disease

Author

Kim, Hyunkyung, primary, Westerman, Kenneth E., additional, Smith, Kirk, additional, Chiou, Joshua, additional, Cole, Joanne B., additional, Majarian, Timothy, additional, von Grotthuss, Marcin, additional, Kwak, Soo Heon, additional, Kim, Jaegil, additional, Mercader, Josep M., additional, Florez, Jose C., additional, Gaulton, Kyle, additional, Manning, Alisa K., additional, and Udler, Miriam S., additional

Published
2022
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