Record W3087920238 · doi:10.1101/2020.09.22.20198937

Trans-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation

2020· preprint· en· W3087920238 on OpenAlexaff

Anubha Mahajan, Cassandra N. Spracklen, Weihua Zhang, Maggie C. Y. Ng, Lauren E. Petty, Hidetoshi Kitajima, Grace Z. Yu, Sina Rüeger, Leo Speidel, Young Jin Kim, Momoko Horikoshi, Josep M. Mercader, Daniel Taliun, Sanghoon Moon, Soo‐Heon Kwak, Neil R. Robertson, Nigel W. Rayner, Marie Loh, Bong-Jo Kim, Joshua Chiou, Irene Miguel-Escalada, Pietro Della Briotta Parolo, Kuang Lin, Fiona Bragg, Michael Preuß, Fumihiko Takeuchi, Jana Nano, Xiuqing Guo, Amel Lamri, Masahiro Nakatochi, Robert A. Scott, Jung‐Jin Lee, Alicia Huerta‐Chagoya, Mariaelisa Graff, Jin Fang Chai, Esteban J. Parra, Jie Yao, Lawrence F. Bielak, Yasuharu Tabara, Yang Hai, Valgerður Steinthórsdóttir, James P. Cook, Mart Kals, Niels Grarup, Ellen M. Schmidt, Ian Pan, Tamar Sofer, Matthias Wuttke, Chloé Sarnowski, Christian Gieger, Darryl Nousome, Stella Trompet, Jirong Long, Meng Sun, Lin Tong, Wei‐Min Chen, Meraj Ahmad, Raymond Noordam, Victor JY Lim, Claudia H. T. Tam, Yoonjung Yoonie Joo, Chien-Hsiun Chen, Laura M. Raffield, Nisa M. Maruthur, Bram P. Prins, Aude Nicolas, Lisa R. Yanek, Guanjie Chen, Richard A. Jensen, Salman M. Tajuddin, Edmond K. Kabagambe, Ping An, Anny H. Xiang, Hyeok Sun Choi, Brian E. Cade, Jingyi Tan, Fernando Abaitua, Linda S. Adair, Adebowale Adeyemo, Carlos A. Aguilar‐Salinas, Masato Akiyama, Sonia S. Anand, Alain G. Bertoni, Zheng Bian, Jette Bork‐Jensen, Ivan Brandslund, Jennifer A. Brody, Chad M. Brummett, Thomas A. Buchanan, Mickaël Canouil, Juliana C.N. Chan, Li-Ching Chang, Miao-Li Chee, Ji Chen, Shyh‐Huei Chen, Yuan-Tsong Chen, Zhengming Chen, Lee‐Ming Chuang, Mary Cushman, Swapan K. Das, H. Janaka de Silva, George Dedoussis, Latchezar Dimitrov, Ayo P. Doumatey, Shufa Du, Qing Duan, Kai‐Uwe Eckardt, Leslie S. Emery, Daniel S. Evans, Michele K. Evans, Krista Fischer, James S. Floyd, Ian Ford, Myriam Fornage, Oscar H. Franco, Timothy M. Frayling, Barry I. Freedman, Christian Fuchsberger, Pauline Genter, Hertzel C. Gerstein, Vilmantas Giedraitis, Clicerio González‐Villalpando, María Elena González-Villalpando, Mark O. Goodarzi, Penny Gordon‐Larsen, David U. Gorkin, Myron D. Gross, Yu Guo, Sophie Hackinger, Sohee Han, Andrew T. Hattersley, Christian Herder, Annie-Green Howard, Willa A. Hsueh, Mengna Huang, Wei Huang, Yi‐Jen Hung, Mi Yeong Hwang, Chii‐Min Hwu, Sahoko Ichihara, M. Arfan Ikram, Martin Ingelsson, Tariqul Islam, Masato Isono, Hye-Mi Jang, Farzana Jasmine, Guozhi Jiang, Jost B. Jonas, Marit E. Jørgensen, Torben Jørgensen, Fouad Kandeel, Anuradhani Kasturiratne, Tomohiro Katsuya, Varinderpal Kaur, Takahisa Kawaguchi, Jacob M. Keaton, Abel Kho, Chiea Chuen Khor, Muhammad G. Kibriya, Duk-Hwan Kim, Katsuhiko Kohara, Jennifer Kriebel, Florian Kronenberg, Johanna Kuusisto, Kristi Läll, Leslie A. Lange, Myung‐Shik Lee, Sang Lee, Aaron Leong, Liming Li, Yun Li, Ruifang Li‐Gao, Symen Ligthart, Cecilia M. Lindgren, Allan Linneberg, Ching‐Ti Liu, Jianjun Liu, Adam E. Locke, Tin Louie, Jian’an Luan, Andrea O. Y. Luk, Xi Luo, Jun Lv, Valeriya Lyssenko, Vasiliki Mamakou, K. Radha Mani, Thomas Meitinger, Andres Metspalu, Andrew D. Morris, Girish N. Nadkarni, Jerry L. Nadler, Michael A. Nalls, Uma Nayak, Ioanna Ntalla, Yukinori Okada, Lorena Orozco, Sanjay R. Patel, Mark A. Pereira, Annette Peters, Fraser Pirie, Bianca Porneala, Gauri Prasad, Sebastian Preißl, Laura J. Rasmussen‐Torvik, Alex P. Reiner, Michael Roden, Rebecca Rohde, Katheryn Roll, Charumathi Sabanayagam, Maike Sander, Kevin Sandow, Naveed Sattar, Sebastian Schönherr, Claudia Schurmann, Hasan Shahriar, Jinxiu Shi, Dong Mun Shin, Daniel Shriner, Jennifer A. Smith, Wing Yee So, Alena Stančáková, Adrienne M. Stilp, Konstantin Strauch, Ken Suzuki, Atsushi Takahashi, Kent D. Taylor, Barbara Thorand, Guðmar Þorleifsson, Unnur Þorsteinsdóttir, Brian Tomlinson, Jason Torres, Fuu‐Jen Tsai, Jaakko Tuomilehto, Teresa Tusié‐Luna, Miriam S. Udler, Adán Valladares‐Salgado, Rob M. van Dam, Jan B. van Klinken, Rohit Varma, Marijana Vujković, Niels H. Wacher, Ellie Wheeler, Eric A. Whitsel, Konstantin Willems van Dijk, Daniel R. Witte, Chittaranjan S. Yajnik, Ken Yamamoto, Toshimasa Yamauchi, Loïc Yengo, Kyungheon Yoon, Canqing Yu, Jian-Min Yuan, Salim Yusuf, Liang Zhang, Wei Zheng, FinnGen, Leslie J. Raffel, Michiya Igase, Eli Ipp, Susan Redline, Yoon Shin Cho, Lars Lind, Michael A. Province, Craig L. Hanis, Patricia A. Peyser, Erik Ingelsson, Alan B. Zonderman, Bruce M. Psaty, Ya Xing Wang, Charles N. Rotimi, Diane M. Becker, Fumihiko Matsuda, Eleftheria Zeggini, Mitsuhiro Yokota, Stephen S. Rich, Charles Kooperberg, James S. Pankow, James C. Engert, Yii‐Der Ida Chen, Philippe Froguel, James G. Wilson, Wayne HH Sheu, Sharon LR Kardia, Jer‐Yuarn Wu, M. Geoffrey Hayes, Ronald C.W., Tien Yin Wong, Dennis O. Mook‐Kanamori, Giriraj R. Chandak, Francis S. Collins, Dwaipayan Bharadwaj, Guillaume Paré, Michèle M. Sale, Habibul Ahsan, Ayesha A. Motala, Xiao-Ou Shu, Kyong Soo Park, J. Wouter Jukema, Miguel Cruz, Roberta McKean‐Cowdin, Harald Grallert, Ching‐Yu Cheng, Erwin P. Böttinger, Abbas Dehghan, E Shyong Tai, Josée Dupuis, Norihiro Kato, Markku Laakso, Anna Köttgen, Woon-Puay Koh, Simin Liu, Gonçalo R. Abecasis, Jaspal S. Kooner, Ruth J. F. Loos, Kari E. North, Christopher A. Haiman, José C. Florez, Danish Saleheen, Torben Hansen, Oluf Pedersen, Reedik Mägi, Claudia Langenberg, Nicholas J. Wareham, Shiro Maeda, Takashi Kadowaki, Juyoung Lee, Iona Y. Millwood, Robin Walters, Kāri Stefánsson, Simon Myers, Jorge Ferrer, Kyle J. Gaulton, James B. Meigs, Karen L. Mohlke, Anna L. Gloyn, Donald W. Bowden, Jennifer E. Below, John C. Chambers, Xueling Sim, Michael Boehnke, Jerome I. Rotter, Mark I. McCarthy, Andrew P. Morris

Bibliographic record

VenuemedRxiv · 2020

Typepreprint

Languageen

FieldBiochemistry, Genetics and Molecular Biology

TopicGenetic Associations and Epidemiology

Canadian institutionsMcGill UniversityImpactHamilton Health SciencesUniversity of TorontoMcMaster UniversityPopulation Health Research Institute

Fundersnot available

KeywordsGenome-wide association studyType 2 diabetesGeneticsGenetic associationBiologyEvolutionary biologyPopulation stratificationPopulationTranslation (biology)1000 Genomes ProjectComputational biologyTransferabilityGenomeGenetic genealogyGeneGenotypeSingle-nucleotide polymorphismMedicineDiabetes mellitusComputer scienceEnvironmental healthMachine learning

DOI10.1101/2020.09.22.20198937

Abstract

fetched live from OpenAlex

ABSTRACT We assembled an ancestrally diverse collection of genome-wide association studies of type 2 diabetes (T2D) in 180,834 cases and 1,159,055 controls (48.9% non-European descent). We identified 277 loci at genome-wide significance ( p <5×10 -8 ), including 237 attaining a more stringent trans-ancestry threshold ( p <5×10 -9 ), which were delineated to 338 distinct association signals. Trans-ancestry meta-regression offered substantial enhancements to fine-mapping, with 58.6% of associations more precisely localised due to population diversity, and 54.4% of signals resolved to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying foundations for functional investigations. Trans-ancestry genetic risk scores enhanced transferability across diverse populations, providing a step towards more effective clinical translation to improve global health.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000

metaresearch head score (Gemma)0.000

Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated

Candidate categoriesnone

Consensus categoriesnone

DomainCandidate signal: none · Consensus signal: none

Study designCandidate signal: Observational · Consensus signal: Observational

GenreCandidate signal: Empirical · Consensus signal: Empirical

Teacher disagreement score0.048

Threshold uncertainty score0.425

Codex and Gemma teacher scores by category

Category	Codex	Gemma
Metaresearch	0.000	0.000
Meta-epidemiology (narrow)	0.000	0.000
Meta-epidemiology (broad)	0.000	0.000
Bibliometrics	0.000	0.000
Science and technology studies	0.000	0.000
Scholarly communication	0.000	0.000
Open science	0.000	0.000
Research integrity	0.000	0.000
Insufficient payload (model declined to judge)	0.000	0.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.059

GPT teacher head0.306

Teacher spread0.247 · how far apart the two teachers sit on this one work

Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.

Study designObservational

Domainnot available

GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations27

Published2020

Admission routes1

Has abstractyes

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