Author: "Erwin P, Bottinger" - Searchworks@Jio Institute Digital Library Search Results

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1. Genetic insights into resting heart rate and its role in cardiovascular disease

Author: Yordi J. van de Vegte, Ruben N. Eppinga, M. Yldau van der Ende, Yanick P. Hagemeijer, Yuvaraj Mahendran, Elias Salfati, Albert V. Smith, Vanessa Y. Tan, Dan E. Arking, Ioanna Ntalla, Emil V. Appel, Claudia Schurmann, Jennifer A. Brody, Rico Rueedi, Ozren Polasek, Gardar Sveinbjornsson, Cecile Lecoeur, Claes Ladenvall, Jing Hua Zhao, Aaron Isaacs, Lihua Wang, Jian’an Luan, Shih-Jen Hwang, Nina Mononen, Kirsi Auro, Anne U. Jackson, Lawrence F. Bielak, Linyao Zeng, Nabi Shah, Maria Nethander, Archie Campbell, Tuomo Rankinen, Sonali Pechlivanis, Lu Qi, Wei Zhao, Federica Rizzi, Toshiko Tanaka, Antonietta Robino, Massimiliano Cocca, Leslie Lange, Martina Müller-Nurasyid, Carolina Roselli, Weihua Zhang, Marcus E. Kleber, Xiuqing Guo, Henry J. Lin, Francesca Pavani, Tessel E. Galesloot, Raymond Noordam, Yuri Milaneschi, Katharina E. Schraut, Marcel den Hoed, Frauke Degenhardt, Stella Trompet, Marten E. van den Berg, Giorgio Pistis, Yih-Chung Tham, Stefan Weiss, Xueling S. Sim, Hengtong L. Li, Peter J. van der Most, Ilja M. Nolte, Leo-Pekka Lyytikäinen, M. Abdullah Said, Daniel R. Witte, Carlos Iribarren, Lenore Launer, Susan M. Ring, Paul S. de Vries, Peter Sever, Allan Linneberg, Erwin P. Bottinger, Sandosh Padmanabhan, Bruce M. Psaty, Nona Sotoodehnia, Ivana Kolcic, The DCCT/EDIC Research Group, David O. Arnar, Daniel F. Gudbjartsson, Hilma Holm, Beverley Balkau, Claudia T. Silva, Christopher H. Newton-Cheh, Kjell Nikus, Perttu Salo, Karen L. Mohlke, Patricia A. Peyser, Heribert Schunkert, Mattias Lorentzon, Jari Lahti, Dabeeru C. Rao, Marilyn C. Cornelis, Jessica D. Faul, Jennifer A. Smith, Katarzyna Stolarz-Skrzypek, Stefania Bandinelli, Maria Pina Concas, Gianfranco Sinagra, Thomas Meitinger, Melanie Waldenberger, Moritz F. Sinner, Konstantin Strauch, Graciela E. Delgado, Kent D. Taylor, Jie Yao, Luisa Foco, Olle Melander, Jacqueline de Graaf, Renée de Mutsert, Eco J. C. de Geus, Åsa Johansson, Peter K. Joshi, Lars Lind, Andre Franke, Peter W. Macfarlane, Kirill V. Tarasov, Nicholas Tan, Stephan B. Felix, E-Shyong Tai, Debra Q. Quek, Harold Snieder, Johan Ormel, Martin Ingelsson, Cecilia Lindgren, Andrew P. Morris, Olli T. Raitakari, Torben Hansen, Themistocles Assimes, Vilmundur Gudnason, Nicholas J. Timpson, Alanna C. Morrison, Patricia B. Munroe, David P. Strachan, Niels Grarup, Ruth J. F. Loos, Susan R. Heckbert, Peter Vollenweider, Caroline Hayward, Kari Stefansson, Philippe Froguel, Leif Groop, Nicholas J. Wareham, Cornelia M. van Duijn, Mary F. Feitosa, Christopher J. O’Donnell, Mika Kähönen, Markus Perola, Michael Boehnke, Sharon L. R. Kardia, Jeanette Erdmann, Colin N. A. Palmer, Claes Ohlsson, David J. Porteous, Johan G. Eriksson, Claude Bouchard, Susanne Moebus, Peter Kraft, David R. Weir, Daniele Cusi, Luigi Ferrucci, Sheila Ulivi, Giorgia Girotto, Adolfo Correa, Stefan Kääb, Annette Peters, John C. Chambers, Jaspal S. Kooner, Winfried März, Jerome I. Rotter, Andrew A. Hicks, J. Gustav Smith, Lambertus A. L. M. Kiemeney, Dennis O. Mook-Kanamori, Brenda W. J. H. Penninx, Ulf Gyllensten, James F. Wilson, Stephen Burgess, Johan Sundström, Wolfgang Lieb, J. Wouter Jukema, Mark Eijgelsheim, Edward L. M. Lakatta, Ching-Yu Cheng, Marcus Dörr, Tien-Yin Wong, Charumathi Sabanayagam, Albertine J. Oldehinkel, Harriette Riese, Terho Lehtimäki, Niek Verweij, and Pim van der Harst
Subjects: Science
Abstract: Abstract Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.
Published: 2023
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2. Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization [version 1; peer review: 2 approved]

Author: Natasha H. J. Ng, Sara M. Willems, Jian'an Luan, Rebecca S. Fine, Juan Fernandez, Jennifer Wessel, Eleanor Wheeler, Gaelle Marenne, Hidetoshi Kitajima, Hanieh Yaghootkar, Xueling Sim, Ian J. Deary, Sai Chen, Shuai Wang, Yii-Der Ida Chen, Caroline Hayward, Yuning Chen, Jennifer L. Asimit, Claudia Langenberg, Tibor V. Varga, Archie Campbell, Rona J. Strawbridge, Shuang Feng, Tarunveer S. Ahluwalia, Erica L. Kleinbrink, Emil V. Appel, Ping An, Lawrence F. Bielak, Dan E. Arking, Jennifer A. Brody, Nathan A. Bihlmeyer, David Porteous, Ayse Demirkan, Audrey Y. Chu, Franco Giulianini, James S. Floyd, Stefan Gustafsson, Xiuqing Guo, Johanna Jakobsdottir, Anne U. Jackson, Stavroula Kanoni, Richard A. Jensen, Igor Rudan, Man Li, Sirkka Keinanen-Kiukaanniemi, Alisa K. Manning, Yingchang Lu, Karina Meidtner, Jonathan Marten, Giorgio Pistis, Taulant Muka, Kenneth M. Rice, Bram Prins, Albert Vernon Smith, Serena Sanna, Lorraine Southam, Jennifer A. Smith, Vinicius Tragante, Heather M. Stringham, Helen R. Warren, Sander W. van der Laan, Andrianos M. Yiorkas, Jie Yao, Wei Zhao, Weihua Zhang, Heather M. Highland, Mariaelisa Graff, Eirini Marouli, Anne E. Justice, Wesam A. Alhejily, Saima Afaq, Folkert W. Asselbergs, Najaf Amin, Michiel L. Bots, Lori L. Bonnycastle, Ji Chen, Ivan Brandslund, Abbas Dehghan, John Danesh, Tapani Ebeling, Jessica D. Faul, Aliki-Eleni Farmaki, Steve Franks, Paul W. Franks, Anette P. Gjesing, Andreas Fritsche, Göran Hallmans, Mark O. Goodarzi, Karl-Heinz Herzig, Tamara B. Harris, Min A Jhun, Marie-France Hivert, Marit E. Jørgensen, Torben Jørgensen, Eero Kajantie, Pekka Jousilahti, Sharon L.R. Kardia, Maria Karaleftheri, Heikki A. Koistinen, Leena Kinnunen, Peter Kovacs, Pirjo Komulainen, Markku Laakso, Johanna Kuusisto, Aaron Leong, Lenore J. Launer, Jocelyn E. Manning Fox, Jaana Lindström, Nisa M. Maruthur, Satu Männistö, Antonella Mulas, Leena Moilanen, Matthew Neville, Mike A. Nalls, Alison Pattie, James S. Pankow, Hannu Puolijoki, Eva R.B. Petersen, Paul Redmond, Asif Rasheed, Michael Roden, Frida Renström, Juha Saltevo, Danish Saleheen, Sylvain Sebert, Kai Savonen, Alena Stančáková, Kerrin S. Small, Konstantin Strauch, Jakob Stokholm, Betina H. Thuesen, Juha Auvinen, E-Shyong Tai, Emmanouil Tsafantakis, Anke Tönjes, Jaakko Tuomilehto, Tiinamaija Tuomi, Marja Vääräsmäki, Matti Uusitupa, Magdalena Zoledziewska, Ilonca Vaartjes, Beverley Balkau, Goncalo Abecasis, Alexandra I. Blakemore, Hans Bisgaard, Heiner Boeing, Ruth J.F. Loos, Matthias Blüher, Klaus Bønnelykke, Eric Boerwinkle, Mark J. Caulfield, Erwin P. Bottinger, Daniel I. Chasman, John C. Chambers, Francis S. Collins, Ching-Yu Cheng, Francesco Cucca, Josef Coresh, George Dedoussis, Gert J. de Borst, Hester M. den Ruijter, Panos Deloukas, Ele Ferrannini, Michele K. Evans, Harald Grallert, Oscar H. Franco, Arfan Ikram, Joel N. Hirschhorn, Fredrik Karpe, Erik Ingelsson, Wieland Kiess, Carolina Medina-Gomez, Kay-Tee Kaw, Antje Körner, Jaspal S. Kooner, Cecilia M. Lindgren, Timo Lakka, Ching-Ti Liu, Leonard Lipovich, Patrick E. MacDonald, Jun Liu, Andrew D. Morris, Karen L. Mohlke, Alison Murray, Patricia B. Munroe, Gerard Pasterkamp, Colin N. A . Palmer, Patricia A. Peyser, Oluf Pedersen, Paul M. Ridker, Rainer Rauramaa, Patrik Rorsman, Olov Rolandsson, Veikko Salomaa, Frits R. Rosendaal, Robert Sladek, Matthias B. Schulze, Michael Stumvoll, Timothy D. Spector, Mark Walker, Cornelia M. van Duijn, David R. Weir, Nick J. Wareham, Tien Yin Wong, James G. Wilson, Alan B. Zonderman, Eleftheria Zeggini, Andrew P. Morris, Jerome I. Rotter, Jose C. Florez, Michael Boehnke, James B. Meigs, Mark I. McCarthy, Robert A. Scott, Anubha Mahajan, Inês Barroso, Anna L. Gloyn, Michael A. Province, Niels Grarup, Ruifang Li-Gao, Jette Bork-Jensen, Yongmei Liu, Allan Linneberg, Leslie A. Lange, Sandosh Padmanabhan, Gail Davies, Lars Lind, Bruce M. Psaty, Tea Skaaby, Torben Hansen, Ozren Polasek, John M. Starr, Dennis O. Mook-Kanamori, Vilmundur Gudnason, Kent D. Taylor, Marjo-Riitta Järvelin, Renée de Mutsert, Paul Elliott, Josée Dupuis, Blair H. Smith, and Andrew T. Hattersley
Subjects: exome chip, glycaemic traits, genetic discovery, effector genes, summary statistics resources, eng, Medicine, Science
Abstract: Background Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways. Methods To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses. Results Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology. Conclusions Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.
Published: 2023
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3. Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

Author: Thomas W. Winkler, Humaira Rasheed, Alexander Teumer, Mathias Gorski, Bryce X. Rowan, Kira J. Stanzick, Laurent F. Thomas, Adrienne Tin, Anselm Hoppmann, Audrey Y. Chu, Bamidele Tayo, Chris H. L. Thio, Daniele Cusi, Jin-Fang Chai, Karsten B. Sieber, Katrin Horn, Man Li, Markus Scholz, Massimiliano Cocca, Matthias Wuttke, Peter J. van der Most, Qiong Yang, Sahar Ghasemi, Teresa Nutile, Yong Li, Giulia Pontali, Felix Günther, Abbas Dehghan, Adolfo Correa, Afshin Parsa, Agnese Feresin, Aiko P. J. de Vries, Alan B. Zonderman, Albert V. Smith, Albertine J. Oldehinkel, Alessandro De Grandi, Alexander R. Rosenkranz, Andre Franke, Andrej Teren, Andres Metspalu, Andrew A. Hicks, Andrew P. Morris, Anke Tönjes, Anna Morgan, Anna I. Podgornaia, Annette Peters, Antje Körner, Anubha Mahajan, Archie Campbell, Barry I. Freedman, Beatrice Spedicati, Belen Ponte, Ben Schöttker, Ben Brumpton, Bernhard Banas, Bernhard K. Krämer, Bettina Jung, Bjørn Olav Åsvold, Blair H. Smith, Boting Ning, Brenda W. J. H. Penninx, Brett R. Vanderwerff, Bruce M. Psaty, Candace M. Kammerer, Carl D. Langefeld, Caroline Hayward, Cassandra N. Spracklen, Cassianne Robinson-Cohen, Catharina A. Hartman, Cecilia M. Lindgren, Chaolong Wang, Charumathi Sabanayagam, Chew-Kiat Heng, Chiara Lanzani, Chiea-Chuen Khor, Ching-Yu Cheng, Christian Fuchsberger, Christian Gieger, Christian M. Shaffer, Christina-Alexandra Schulz, Cristen J. Willer, Daniel I. Chasman, Daniel F. Gudbjartsson, Daniela Ruggiero, Daniela Toniolo, Darina Czamara, David J. Porteous, Dawn M. Waterworth, Deborah Mascalzoni, Dennis O. Mook-Kanamori, Dermot F. Reilly, E. Warwick Daw, Edith Hofer, Eric Boerwinkle, Erika Salvi, Erwin P. Bottinger, E-Shyong Tai, Eulalia Catamo, Federica Rizzi, Feng Guo, Fernando Rivadeneira, Franco Guilianini, Gardar Sveinbjornsson, Georg Ehret, Gerard Waeber, Ginevra Biino, Giorgia Girotto, Giorgio Pistis, Girish N. Nadkarni, Graciela E. Delgado, Grant W. Montgomery, Harold Snieder, Harry Campbell, Harvey D. White, He Gao, Heather M. Stringham, Helena Schmidt, Hengtong Li, Hermann Brenner, Hilma Holm, Holgen Kirsten, Holly Kramer, Igor Rudan, Ilja M. Nolte, Ioanna Tzoulaki, Isleifur Olafsson, Jade Martins, James P. Cook, James F. Wilson, Jan Halbritter, Janine F. Felix, Jasmin Divers, Jaspal S. Kooner, Jeannette Jen-Mai Lee, Jeffrey O’Connell, Jerome I. Rotter, Jianjun Liu, Jie Xu, Joachim Thiery, Johan Ärnlöv, Johanna Kuusisto, Johanna Jakobsdottir, Johanne Tremblay, John C. Chambers, John B. Whitfield, John M. Gaziano, Jonathan Marten, Josef Coresh, Jost B. Jonas, Josyf C. Mychaleckyj, Kaare Christensen, Kai-Uwe Eckardt, Karen L. Mohlke, Karlhans Endlich, Katalin Dittrich, Kathleen A. Ryan, Kenneth M. Rice, Kent D. Taylor, Kevin Ho, Kjell Nikus, Koichi Matsuda, Konstantin Strauch, Kozeta Miliku, Kristian Hveem, Lars Lind, Lars Wallentin, Laura M. Yerges-Armstrong, Laura M. Raffield, Lawrence S. Phillips, Lenore J. Launer, Leo-Pekka Lyytikäinen, Leslie A. Lange, Lorena Citterio, Lucija Klaric, M. Arfan Ikram, Marcus Ising, Marcus E. Kleber, Margherita Francescatto, Maria Pina Concas, Marina Ciullo, Mario Piratsu, Marju Orho-Melander, Markku Laakso, Markus Loeffler, Markus Perola, Martin H. de Borst, Martin Gögele, Martina La Bianca, Mary Ann Lukas, Mary F. Feitosa, Mary L. Biggs, Mary K. Wojczynski, Maryam Kavousi, Masahiro Kanai, Masato Akiyama, Masayuki Yasuda, Matthias Nauck, Melanie Waldenberger, Miao-Li Chee, Miao-Ling Chee, Michael Boehnke, Michael H. Preuss, Michael Stumvoll, Michael A. Province, Michele K. Evans, Michelle L. O’Donoghue, Michiaki Kubo, Mika Kähönen, Mika Kastarinen, Mike A. Nalls, Mikko Kuokkanen, Mohsen Ghanbari, Murielle Bochud, Navya Shilpa Josyula, Nicholas G. Martin, Nicholas Y. Q. Tan, Nicholette D. Palmer, Nicola Pirastu, Nicole Schupf, Niek Verweij, Nina Hutri-Kähönen, Nina Mononen, Nisha Bansal, Olivier Devuyst, Olle Melander, Olli T. Raitakari, Ozren Polasek, Paolo Manunta, Paolo Gasparini, Pashupati P. Mishra, Patrick Sulem, Patrik K. E. Magnusson, Paul Elliott, Paul M. Ridker, Pavel Hamet, Per O. Svensson, Peter K. Joshi, Peter Kovacs, Peter P. Pramstaller, Peter Rossing, Peter Vollenweider, Pim van der Harst, Rajkumar Dorajoo, Ralene Z. H. Sim, Ralph Burkhardt, Ran Tao, Raymond Noordam, Reedik Mägi, Reinhold Schmidt, Renée de Mutsert, Rico Rueedi, Rob M. van Dam, Robert J. Carroll, Ron T. Gansevoort, Ruth J. F. Loos, Sala Cinzia Felicita, Sanaz Sedaghat, Sandosh Padmanabhan, Sandra Freitag-Wolf, Sarah A. Pendergrass, Sarah E. Graham, Scott D. Gordon, Shih-Jen Hwang, Shona M. Kerr, Simona Vaccargiu, Snehal B. Patil, Stein Hallan, Stephan J. L. Bakker, Su-Chi Lim, Susanne Lucae, Suzanne Vogelezang, Sven Bergmann, Tanguy Corre, Tarunveer S. Ahluwalia, Terho Lehtimäki, Thibaud S. Boutin, Thomas Meitinger, Tien-Yin Wong, Tobias Bergler, Ton J. Rabelink, Tõnu Esko, Toomas Haller, Unnur Thorsteinsdottir, Uwe Völker, Valencia Hui Xian Foo, Veikko Salomaa, Veronique Vitart, Vilmantas Giedraitis, Vilmundur Gudnason, Vincent W. V. Jaddoe, Wei Huang, Weihua Zhang, Wen Bin Wei, Wieland Kiess, Winfried März, Wolfgang Koenig, Wolfgang Lieb, Xin Gao, Xueling Sim, Ya Xing Wang, Yechiel Friedlander, Yih-Chung Tham, Yoichiro Kamatani, Yukinori Okada, Yuri Milaneschi, Zhi Yu, Lifelines cohort study, DiscovEHR/MyCode study, VA Million Veteran Program, Klaus J. Stark, Kari Stefansson, Carsten A. Böger, Adriana M. Hung, Florian Kronenberg, Anna Köttgen, Cristian Pattaro, and Iris M. Heid
Subjects: Biology (General), QH301-705.5
Abstract: A large-scale GWAS provides insight on diabetes-dependent genetic effects on the glomerular filtration rate, a common metric to monitor kidney health in disease.
Published: 2022
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4. Acute Kidney Injury in Patients Hospitalized With COVID-19 in New York City: Temporal Trends From March 2020 to April 2021

Author: Sergio Dellepiane, MD, PhD, Akhil Vaid, MD, Suraj K. Jaladanki, Steven Coca, DO, Zahi A. Fayad, MD, Alexander W. Charney, MD, PhD, Erwin P. Bottinger, MD, John Cijiang He, MD, PhD, Benjamin S. Glicksberg, PhD, Lili Chan, MD, and Girish Nadkarni, MD
Subjects: Diseases of the genitourinary system. Urology, RC870-923
Published: 2021
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5. Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction

Author: Ioanna Ntalla, Lu-Chen Weng, James H. Cartwright, Amelia Weber Hall, Gardar Sveinbjornsson, Nathan R. Tucker, Seung Hoan Choi, Mark D. Chaffin, Carolina Roselli, Michael R. Barnes, Borbala Mifsud, Helen R. Warren, Caroline Hayward, Jonathan Marten, James J. Cranley, Maria Pina Concas, Paolo Gasparini, Thibaud Boutin, Ivana Kolcic, Ozren Polasek, Igor Rudan, Nathalia M. Araujo, Maria Fernanda Lima-Costa, Antonio Luiz P. Ribeiro, Renan P. Souza, Eduardo Tarazona-Santos, Vilmantas Giedraitis, Erik Ingelsson, Anubha Mahajan, Andrew P. Morris, Fabiola Del Greco M, Luisa Foco, Martin Gögele, Andrew A. Hicks, James P. Cook, Lars Lind, Cecilia M. Lindgren, Johan Sundström, Christopher P. Nelson, Muhammad B. Riaz, Nilesh J. Samani, Gianfranco Sinagra, Sheila Ulivi, Mika Kähönen, Pashupati P. Mishra, Nina Mononen, Kjell Nikus, Mark J. Caulfield, Anna Dominiczak, Sandosh Padmanabhan, May E. Montasser, Jeff R. O’Connell, Kathleen Ryan, Alan R. Shuldiner, Stefanie Aeschbacher, David Conen, Lorenz Risch, Sébastien Thériault, Nina Hutri-Kähönen, Terho Lehtimäki, Leo-Pekka Lyytikäinen, Olli T. Raitakari, Catriona L. K. Barnes, Harry Campbell, Peter K. Joshi, James F. Wilson, Aaron Isaacs, Jan A. Kors, Cornelia M. van Duijn, Paul L. Huang, Vilmundur Gudnason, Tamara B. Harris, Lenore J. Launer, Albert V. Smith, Erwin P. Bottinger, Ruth J. F. Loos, Girish N. Nadkarni, Michael H. Preuss, Adolfo Correa, Hao Mei, James Wilson, Thomas Meitinger, Martina Müller-Nurasyid, Annette Peters, Melanie Waldenberger, Massimo Mangino, Timothy D. Spector, Michiel Rienstra, Yordi J. van de Vegte, Pim van der Harst, Niek Verweij, Stefan Kääb, Katharina Schramm, Moritz F. Sinner, Konstantin Strauch, Michael J. Cutler, Diane Fatkin, Barry London, Morten Olesen, Dan M. Roden, M. Benjamin Shoemaker, J. Gustav Smith, Mary L. Biggs, Joshua C. Bis, Jennifer A. Brody, Bruce M. Psaty, Kenneth Rice, Nona Sotoodehnia, Alessandro De Grandi, Christian Fuchsberger, Cristian Pattaro, Peter P. Pramstaller, Ian Ford, J. Wouter Jukema, Peter W. Macfarlane, Stella Trompet, Marcus Dörr, Stephan B. Felix, Uwe Völker, Stefan Weiss, Aki S. Havulinna, Antti Jula, Katri Sääksjärvi, Veikko Salomaa, Xiuqing Guo, Susan R. Heckbert, Henry J. Lin, Jerome I. Rotter, Kent D. Taylor, Jie Yao, Renée de Mutsert, Arie C. Maan, Dennis O. Mook-Kanamori, Raymond Noordam, Francesco Cucca, Jun Ding, Edward G. Lakatta, Yong Qian, Kirill V. Tarasov, Daniel Levy, Honghuang Lin, Christopher H. Newton-Cheh, Kathryn L. Lunetta, Alison D. Murray, David J. Porteous, Blair H. Smith, Bruno H. Stricker, André Uitterlinden, Marten E. van den Berg, Jeffrey Haessler, Rebecca D. Jackson, Charles Kooperberg, Ulrike Peters, Alexander P. Reiner, Eric A. Whitsel, Alvaro Alonso, Dan E. Arking, Eric Boerwinkle, Georg B. Ehret, Elsayed Z. Soliman, Christy L. Avery, Stephanie M. Gogarten, Kathleen F. Kerr, Cathy C. Laurie, Amanda A. Seyerle, Adrienne Stilp, Solmaz Assa, M. Abdullah Said, M. Yldau van der Ende, Pier D. Lambiase, Michele Orini, Julia Ramirez, Stefan Van Duijvenboden, David O. Arnar, Daniel F. Gudbjartsson, Hilma Holm, Patrick Sulem, Gudmar Thorleifsson, Rosa B. Thorolfsdottir, Unnur Thorsteinsdottir, Emelia J. Benjamin, Andrew Tinker, Kari Stefansson, Patrick T. Ellinor, Yalda Jamshidi, Steven A. Lubitz, and Patricia B. Munroe
Subjects: Science
Abstract: On the electrocardiogram, the PR interval reflects conduction from the atria to ventricles and also serves as risk indicator of cardiovascular morbidity and mortality. Here, the authors perform genome-wide meta-analyses for PR interval in multiple ancestries and identify 141 previously unreported genetic loci.
Published: 2020
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6. Factors Associated With Longitudinal Psychological and Physiological Stress in Health Care Workers During the COVID-19 Pandemic: Observational Study Using Apple Watch Data

Author: Robert P Hirten, Matteo Danieletto, Lewis Tomalin, Katie Hyewon Choi, Micol Zweig, Eddye Golden, Sparshdeep Kaur, Drew Helmus, Anthony Biello, Renata Pyzik, Claudia Calcagno, Robert Freeman, Bruce E Sands, Dennis Charney, Erwin P Bottinger, James W Murrough, Laurie Keefer, Mayte Suarez-Farinas, Girish N Nadkarni, and Zahi A Fayad
Subjects: Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract: BackgroundThe COVID-19 pandemic has resulted in a high degree of psychological distress among health care workers (HCWs). There is a need to characterize which HCWs are at an increased risk of developing psychological effects from the pandemic. Given the differences in the response of individuals to stress, an analysis of both the perceived and physiological consequences of stressors can provide a comprehensive evaluation of its impact. ObjectiveThis study aimed to determine characteristics associated with longitudinal perceived stress in HCWs and to assess whether changes in heart rate variability (HRV), a marker of autonomic nervous system function, are associated with features protective against longitudinal stress. MethodsHCWs across 7 hospitals in New York City, NY, were prospectively followed in an ongoing observational digital study using the custom Warrior Watch Study app. Participants wore an Apple Watch for the duration of the study to measure HRV throughout the follow-up period. Surveys measuring perceived stress, resilience, emotional support, quality of life, and optimism were collected at baseline and longitudinally. ResultsA total of 361 participants (mean age 36.8, SD 10.1 years; female: n=246, 69.3%) were enrolled. Multivariate analysis found New York City’s COVID-19 case count to be associated with increased longitudinal stress (P=.008). Baseline emotional support, quality of life, and resilience were associated with decreased longitudinal stress (P
Published: 2021
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7. Genetic Risk Score for Intracranial Aneurysms: Prediction of Subarachnoid Hemorrhage and Role in Clinical Heterogeneity

Author: Mark K. Bakker, Jos P. Kanning, Gad Abraham, Amy E. Martinsen, Bendik S. Winsvold, John-Anker Zwart, Romain Bourcier, Tomonobu Sawada, Masaru Koido, Yoichiro Kamatani, Sandrine Morel, Philippe Amouyel, Stéphanie Debette, Philippe Bijlenga, Takiy Berrandou, Santhi K. Ganesh, Nabila Bouatia-Naji, Gregory Jones, Matthew Bown, Gabriel J.E. Rinkel, Jan H. Veldink, Ynte M. Ruigrok, Anne Hege Aamodt, Anne Heidi Skogholt, Ben M Brumpton, Cristen J Willer, Else C Sandset, Espen S Kristoffersen, Hanne Ellekjær, Ingrid Heuch, Jonas B Nielsen, Knut Hagen, Kristian Hveem, Lars G Fritsche, Laurent F Thomas, Linda M Pedersen, Maiken E Gabrielsen, Oddgeir L Holmen, Sigrid Børte, Wei Zhou, Shérine Abboud, Massimo Pandolfo, Vincent Thijs, Didier Leys, Marie Bodenant, Fabien Louillet, Emmanuel Touzé, Jean-Louis Mas, Yves Samson, Sara Leder, Anne Léger, Sandrine Deltour, Sophie Crozier, Isabelle Méresse, Sandrine Canaple, Olivier Godefroy, Maurice Giroud, Yannick Béjot, Pierre Decavel, Elizabeth Medeiros, Paola Montiel, Thierry Moulin, Fabrice Vuillier, Jean Dallongeville, Antti J Metso, Tiina Metso, Turgut Tatlisumak, Caspar Grond-Ginsbach, Christoph Lichy, Manja Kloss, Inge Werner, Marie-Luise Arnold, Michael Dos Santos, Armin Grau, Martin Dichgans, Constanze Thomas-Feles, Ralf Weber, Tobias Brandt, Alessandro Pezzini, Valeria De Giuli, Filomena Caria, Loris Poli, Alessandro Padovani, Anna Bersano, Silvia Lanfranconi, Simone Beretta, Carlo Ferrarese, Giacomo Giacolone, Stefano Paolucci, Philippe Lyrer, Stefan Engelter, Felix Fluri, Florian Hatz, Dominique Gisler, Leo Bonati, Henrik Gensicke, Margareth Amort, Hugh Markus, Jennifer Majersik, Bradford Worrall, Andrew Southerland, John Cole, Steven Kittner, Evangelos Evangelou, Helen R Warren, He Gao, Georgios Ntritsos, Niki Dimou, Tonu Esko, Reedik Mägi, Lili Milani, Peter Almgren, Thibaud Boutin, Jun Ding, Franco Giulianini, Elizabeth G Holliday, Anne U Jackson, Ruifang Li-Gao, Wei-Yu Lin, Jian’an Luan, Massimo Mangino, Christopher Oldmeadow, Bram Peter Prins, Yong Qian, Muralidharan Sargurupremraj, Nabi Shah, Praveen Surendran, Sébastien Thériault, Niek Verweij, Sara M Willems, Jing-Hua Zhao, John Connell, Renée de Mutsert, Alex SF Doney, Martin Farrall, Cristina Menni, Andrew D Morris, Raymond Noordam, Guillaume Paré, Neil R Poulter, Denis C Shields, Alice Stanton, Simon Thom, Gonçalo Abecasis, Najaf Amin, Dan E Arking, Kristin L Ayers, Caterina M Barbieri, Chiara Batini, Joshua C Bis, Tineka Blake, Murielle Bochud, Michael Boehnke, Eric Boerwinkle, Dorret I Boomsma, Erwin P Bottinger, Peter S Braund, Marco Brumat, Archie Campbell, Harry Campbell, Aravinda Chakravarti, John C Chambers, Ganesh Chauhan, Marina Ciullo, Massimiliano Cocca, Francis Collins, Heather J Cordell, Gail Davies, Martin H de Borst, Eco J de Geus, Ian J Deary, Joris Deelen, Fabiola Del Greco M, Cumhur Yusuf Demirkale, Marcus Dörr, Georg B Ehret, Roberto Elosua, Stefan Enroth, A Mesut Erzurumluoglu, Teresa Ferreira, Mattias Frånberg, Oscar H Franco, Ilaria Gandin, Paolo Gasparini, Vilmantas Giedraitis, Christian Gieger, Giorgia Girotto, Anuj Goel, Alan J Gow, Vilmundur Gudnason, Xiuqing Guo, Ulf Gyllensten, Anders Hamsten, Tamara B Harris, Sarah E Harris, Catharina A Hartman, Aki S Havulinna, Andrew A Hicks, Edith Hofer, Albert Hofman, Jouke-Jan Hottenga, Jennifer E Huffman, Shih-Jen Hwang, Erik Ingelsson, Alan James, Rick Jansen, Marjo-Riitta Jarvelin, Roby Joehanes, Åsa Johansson, Andrew D Johnson, Peter K Joshi, Pekka Jousilahti, J Wouter Jukema, Antti Jula, Mika Kähönen, Sekar Kathiresan, Bernard D Keavney, Kay-Tee Khaw, Paul Knekt, Joanne Knight, Ivana Kolcic, Jaspal S Kooner, Seppo Koskinen, Kati Kristiansson, Zoltan Kutalik, Maris Laan, Marty Larson, Lenore J Launer, Benjamin Lehne, Terho Lehtimäki, David CM Liewald, Li Lin, Lars Lind, Cecilia M Lindgren, YongMei Liu, Ruth JF Loos, Lorna M Lopez, Yingchang Lu, Leo-Pekka Lyytikäinen, Anubha Mahajan, Chrysovalanto Mamasoula, Jaume Marrugat, Jonathan Marten, Yuri Milaneschi, Anna Morgan, Andrew P Morris, Alanna C Morrison, Peter J Munson, Mike A Nalls, Priyanka Nandakumar, Christopher P Nelson, Teemu Niiranen, Ilja M Nolte, Teresa Nutile, Albertine J Oldehinkel, Ben A Oostra, Paul F O’Reilly, Elin Org, Sandosh Padmanabhan, Walter Palmas, Aarno Palotie, Alison Pattie, Brenda WJH Penninx, Markus Perola, Annette Peters, Ozren Polasek, Peter P Pramstaller, Quang Tri Nguyen, Olli T Raitakari, Rainer Rettig, Kenneth Rice, Paul M Ridker, Janina S Ried, Harriëtte Riese, Samuli Ripatti, Antonietta Robino, Lynda M Rose, Jerome I Rotter, Igor Rudan, Daniela Ruggiero, Yasaman Saba, Cinzia F Sala, Veikko Salomaa, Nilesh J Samani, Antti-Pekka Sarin, Reinhold Schmidt, Helena Schmidt, Nick Shrine, David Siscovick, Albert V Smith, Harold Snieder, Siim Sõber, Rossella Sorice, John M Starr, David J Stott, David P Strachan, Rona J Strawbridge, Johan Sundström, Morris A Swertz, Kent D Taylor, Alexander Teumer, Martin D Tobin, Maciej Tomaszewski, Daniela Toniolo, Michela Traglia, Stella Trompet, Jaakko Tuomilehto, Christophe Tzourio, André G Uitterlinden, Ahmad Vaez, Peter J van der Most, Cornelia M van Duijn, Germaine C Verwoert, Veronique Vitart, Uwe Völker, Peter Vollenweider, Dragana Vuckovic, Hugh Watkins, Sarah H Wild, Gonneke Willemsen, James F Wilson, Alan F Wright, Jie Yao, Tatijana Zemunik, Weihua Zhang, John R Attia, Adam S Butterworth, Daniel I Chasman, David Conen, Francesco Cucca, John Danesh, Caroline Hayward, Joanna MM Howson, Markku Laakso, Edward G Lakatta, Claudia Langenberg, Olle Melander, Dennis O Mook-Kanamori, Colin NA Palmer, Lorenz Risch, Robert A Scott, Rodney J Scott, Peter Sever, Tim D Spector, Pim van der Harst, Nicholas J Wareham, Eleftheria Zeggini, Daniel Levy, Patricia B Munroe, Christopher Newton-Cheh, Morris J Brown, Andres Metspalu, Bruce M. Psaty, Louise V Wain, Paul Elliott, Mark J Caulfield, Padhraig Gormley, Verneri Anttila, Priit Palta, Tune H Pers, Kai-How Farh, Ester Cuenca-Leon, Mikko Muona, Nicholas A Furlotte, Tobias Kurth, Andres Ingason, George McMahon, Lannie Ligthart, Gisela M Terwindt, Mikko Kallela, Tobias M Freilinger, Caroline Ran, Scott G Gordon, Anine H Stam, Stacy Steinberg, Guntram Borck, Markku Koiranen, Lydia Quaye, Hieab H H Adams, Juho Wedenoja, David A Hinds, Julie E Buring, Markus Schürks, Maria Gudlaug Hrafnsdottir, Hreinn Stefansson, Susan M Ring, Brenda W J H Penninx, Markus Färkkilä, Ville Artto, Mari Kaunisto, Salli Vepsäläinen, Rainer Malik, Andrew C Heath, Pamela A F Madden, Nicholas G Martin, Grant W Montgomery, Mitja I Kurki, Mart Kals, Kalle Pärn, Eija Hämäläinen, Hailiang Huang, Andrea E Byrnes, Lude Franke, Jie Huang, Evie Stergiakouli, Phil H Lee, Cynthia Sandor, Caleb Webber, Zameel Cader, Bertram Muller-Myhsok, Stefan Schreiber, Thomas Meitinger, Johan G Eriksson, Kauko Heikkilä, Elizabeth Loehrer, Andre G Uitterlinden, Lynn Cherkas, Audun Stubhaug, Christopher S Nielsen, Minna Männikkö, Evelin Mihailov, Hartmut Göbel, Ann-Louise Esserlind, Anne Francke Christensen, Thomas Folkmann Hansen, Thomas Werge, Jaakko Kaprio, Arpo J Aromaa, Olli Raitakari, M Arfan Ikram, Tim Spector, Marjo-Riitta Järvelin, Christian Kubisch, Michel D Ferrari, Andrea C Belin, Maija Wessman, Arn M J M van den Maagdenberg, George Davey Smith, Kari Stefansson, Nicholas Eriksson, Mark J Daly, Benjamin M Neale, Jes Olesen, Dale R Nyholt, Masato Akiyama, Varinder S. Alg, Joseph P. Broderick, Ben M. Brumpton, Jérôme Dauvillier, Hubert Desal, Christian Dina, Christoph M. Friedrich, Emília I. Gaál-Paavola, Jean-Christophe Gentric, Sven Hirsch, Isabel C. Hostettler, Henry Houlden, Juha E. Jääskeläinen, Marianne Bakke Johnsen, Liming Li, Kuang Lin, Antti Lindgren, Olivier Martin, Koichi Matsuda, Iona Y. Millwood, Olivier Naggara, Mika Niemelä, Joanna Pera, Richard Redon, Guy A. Rouleau, Marie Søfteland Sandvei, Sabine Schilling, Eimad Shotar, Agnieszka Slowik, Chikashi Terao, W. M. Monique Verschuren, Robin G. Walters, David J. Werring, Cristen J. Willer, Daniel Woo, Bradford B. Worrall, Sirui Zhou, Biological Psychology, Amsterdam Reproduction & Development, APH - Mental Health, APH - Methodology, AMS - Sports, AMS - Ageing & Vitality, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Systems Ecology, Sociology and Social Gerontology, Bakker, Mark K., Kanning, Jos P., Abraham, Gad, Martinsen, Amy E., Winsvold, Bendik S., Zwart, John-Anker, Bourcier, Romain, Sawada, Tomonobu, Koido, Masaru, Kamatani, Yoichiro, Morel, Sandrine, Amouyel, Philippe, Debette, Stéphanie, Bijlenga, Philippe, Berrandou, Takiy, Ganesh, Santhi K., Bouatia-Naji, Nabila, Jones, Gregory, Bown, Matthew, Rinkel, Gabriel J. E., Veldink, Jan H., Ruigrok, Ynte M., Girotto, G., All-In Stroke, Hunt, Group, Cadisp, Consortium for Blood Pressure, International, Headache Genetics Consortium, International, Stroke Genetics Consortium (ISGC) Intracranial Aneurysm Working Group, International, Utrecht University [Utrecht], Baker Heart and Diabetes Institute (AUSTRALIA), University of Melbourne, University of Oslo (UiO), Norwegian University of Science and Technology (NTNU), Oslo University Hospital [Oslo], Centre hospitalier universitaire de Nantes (CHU Nantes), unité de recherche de l'institut du thorax UMR1087 UMR6291 (ITX), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Nantes Université - UFR de Médecine et des Techniques Médicales (Nantes Univ - UFR MEDECINE), Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), The University of Tokyo (UTokyo), RIKEN Center for Integrative Medical Sciences [Yokohama] (RIKEN IMS), RIKEN - Institute of Physical and Chemical Research [Japon] (RIKEN), Hôpital Universitaire de Genève = University Hospitals of Geneva (HUG), Université de Genève = University of Geneva (UNIGE), Excellence Laboratory LabEx DISTALZ, Facteurs de Risque et Déterminants Moléculaires des Maladies liées au Vieillissement - U 1167 (RID-AGE), Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Bordeaux [Bordeaux], Paris-Centre de Recherche Cardiovasculaire (PARCC (UMR_S 970/ U970)), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), University of Michigan Medical School [Ann Arbor], University of Michigan [Ann Arbor], University of Michigan System-University of Michigan System, University of Otago [Dunedin, Nouvelle-Zélande], University of Leicester, Laboratoire de Neurosciences Fonctionnelles et Pathologies - UR UPJV 4559 (LNFP), Université de Picardie Jules Verne (UPJV), CHU Amiens-Picardie, HUNT All-In Stroke, CADISP group, International Consortium for Blood Pressure, International Headache Genetics Consortium, International Stroke Genetics Consortium (ISGC) Intracranial Aneurysm Working Group: Anne Hege Aamodt, Anne Heidi Skogholt, Ben M Brumpton, Cristen J Willer, Else C Sandset, Espen S Kristoffersen, Hanne Ellekjær, Ingrid Heuch, Jonas B Nielsen, Knut Hagen, Kristian Hveem, Lars G Fritsche, Laurent F Thomas, Linda M Pedersen, Maiken E Gabrielsen, Oddgeir L Holmen, Sigrid Børte, Wei Zhou, Shérine Abboud, Massimo Pandolfo, Vincent Thijs, Didier Leys, Marie Bodenant, Fabien Louillet, Emmanuel Touzé, Jean-Louis Mas, Yves Samson, Sara Leder, Anne Léger, Sandrine Deltour, Sophie Crozier, Isabelle Méresse, Sandrine Canaple, Olivier Godefroy, Maurice Giroud, Yannick Béjot, Pierre Decavel, Elizabeth Medeiros, Paola Montiel, Thierry Moulin, Fabrice Vuillier, Jean Dallongeville, Antti J Metso, Tiina Metso, Turgut Tatlisumak, Caspar Grond-Ginsbach, Christoph Lichy, Manja Kloss, Inge Werner, Marie-Luise Arnold, Michael Dos Santos, Armin Grau, Martin Dichgans, Constanze Thomas-Feles, Ralf Weber, Tobias Brandt, Alessandro Pezzini, Valeria De Giuli, Filomena Caria, Loris Poli, Alessandro Padovani, Anna Bersano, Silvia Lanfranconi, Simone Beretta, Carlo Ferrarese, Giacomo Giacolone, Stefano Paolucci, Philippe Lyrer, Stefan Engelter, Felix Fluri, Florian Hatz, Dominique Gisler, Leo Bonati, Henrik Gensicke, Margareth Amort, Hugh Markus, Jennifer Majersik, Bradford Worrall, Andrew Southerland, John Cole, Steven Kittner, Evangelos Evangelou, Helen R Warren, He Gao, Georgios Ntritsos, Niki Dimou, Tonu Esko, Reedik Mägi, Lili Milani, Peter Almgren, Thibaud Boutin, Jun Ding, Franco Giulianini, Elizabeth G Holliday, Anne U Jackson, Ruifang Li-Gao, Wei-Yu Lin, Jian'an Luan, Massimo Mangino, Christopher Oldmeadow, Bram Peter Prins, Yong Qian, Muralidharan Sargurupremraj, Nabi Shah, Praveen Surendran, Sébastien Thériault, Niek Verweij, Sara M Willems, Jing-Hua Zhao, John Connell, Renée de Mutsert, Alex Sf Doney, Martin Farrall, Cristina Menni, Andrew D Morris, Raymond Noordam, Guillaume Paré, Neil R Poulter, Denis C Shields, Alice Stanton, Simon Thom, Gonçalo Abecasis, Najaf Amin, Dan E Arking, Kristin L Ayers, Caterina M Barbieri, Chiara Batini, Joshua C Bis, Tineka Blake, Murielle Bochud, Michael Boehnke, Eric Boerwinkle, Dorret I Boomsma, Erwin P Bottinger, Peter S Braund, Marco Brumat, Archie Campbell, Harry Campbell, Aravinda Chakravarti, John C Chambers, Ganesh Chauhan, Marina Ciullo, Massimiliano Cocca, Francis Collins, Heather J Cordell, Gail Davies, Martin H de Borst, Eco J de Geus, Ian J Deary, Joris Deelen, Fabiola Del Greco M, Cumhur Yusuf Demirkale, Marcus Dörr, Georg B Ehret, Roberto Elosua, Stefan Enroth, A Mesut Erzurumluoglu, Teresa Ferreira, Mattias Frånberg, Oscar H Franco, Ilaria Gandin, Paolo Gasparini, Vilmantas Giedraitis, Christian Gieger, Giorgia Girotto, Anuj Goel, Alan J Gow, Vilmundur Gudnason, Xiuqing Guo, Ulf Gyllensten, Anders Hamsten, Tamara B Harris, Sarah E Harris, Catharina A Hartman, Aki S Havulinna, Andrew A Hicks, Edith Hofer, Albert Hofman, Jouke-Jan Hottenga, Jennifer E Huffman, Shih-Jen Hwang, Erik Ingelsson, Alan James, Rick Jansen, Marjo-Riitta Jarvelin, Roby Joehanes, Åsa Johansson, Andrew D Johnson, Peter K Joshi, Pekka Jousilahti, J Wouter Jukema, Antti Jula, Mika Kähönen, Sekar Kathiresan, Bernard D Keavney, Kay-Tee Khaw, Paul Knekt, Joanne Knight, Ivana Kolcic, Jaspal S Kooner, Seppo Koskinen, Kati Kristiansson, Zoltan Kutalik, Maris Laan, Marty Larson, Lenore J Launer, Benjamin Lehne, Terho Lehtimäki, David Cm Liewald, Li Lin, Lars Lind, Cecilia M Lindgren, YongMei Liu, Ruth Jf Loos, Lorna M Lopez, Yingchang Lu, Leo-Pekka Lyytikäinen, Anubha Mahajan, Chrysovalanto Mamasoula, Jaume Marrugat, Jonathan Marten, Yuri Milaneschi, Anna Morgan, Andrew P Morris, Alanna C Morrison, Peter J Munson, Mike A Nalls, Priyanka Nandakumar, Christopher P Nelson, Teemu Niiranen, Ilja M Nolte, Teresa Nutile, Albertine J Oldehinkel, Ben A Oostra, Paul F O'Reilly, Elin Org, Sandosh Padmanabhan, Walter Palmas, Aarno Palotie, Alison Pattie, Brenda Wjh Penninx, Markus Perola, Annette Peters, Ozren Polasek, Peter P Pramstaller, Quang Tri Nguyen, Olli T Raitakari, Rainer Rettig, Kenneth Rice, Paul M Ridker, Janina S Ried, Harriëtte Riese, Samuli Ripatti, Antonietta Robino, Lynda M Rose, Jerome I Rotter, Igor Rudan, Daniela Ruggiero, Yasaman Saba, Cinzia F Sala, Veikko Salomaa, Nilesh J Samani, Antti-Pekka Sarin, Reinhold Schmidt, Helena Schmidt, Nick Shrine, David Siscovick, Albert V Smith, Harold Snieder, Siim Sõber, Rossella Sorice, John M Starr, David J Stott, David P Strachan, Rona J Strawbridge, Johan Sundström, Morris A Swertz, Kent D Taylor, Alexander Teumer, Martin D Tobin, Maciej Tomaszewski, Daniela Toniolo, Michela Traglia, Stella Trompet, Jaakko Tuomilehto, Christophe Tzourio, André G Uitterlinden, Ahmad Vaez, Peter J van der Most, Cornelia M van Duijn, Germaine C Verwoert, Veronique Vitart, Uwe Völker, Peter Vollenweider, Dragana Vuckovic, Hugh Watkins, Sarah H Wild, Gonneke Willemsen, James F Wilson, Alan F Wright, Jie Yao, Tatijana Zemunik, Weihua Zhang, John R Attia, Adam S Butterworth, Daniel I Chasman, David Conen, Francesco Cucca, John Danesh, Caroline Hayward, Joanna Mm Howson, Markku Laakso, Edward G Lakatta, Claudia Langenberg, Olle Melander, Dennis O Mook-Kanamori, Colin Na Palmer, Lorenz Risch, Robert A Scott, Rodney J Scott, Peter Sever, Tim D Spector, Pim van der Harst, Nicholas J Wareham, Eleftheria Zeggini, Daniel Levy, Patricia B Munroe, Christopher Newton-Cheh, Morris J Brown, Andres Metspalu, Bruce M Psaty, Louise V Wain, Paul Elliott, Mark J Caulfield, Padhraig Gormley, Verneri Anttila, Priit Palta, Tonu Esko, Tune H Pers, Kai-How Farh, Ester Cuenca-Leon, Mikko Muona, Nicholas A Furlotte, Tobias Kurth, Andres Ingason, George McMahon, Lannie Ligthart, Gisela M Terwindt, Mikko Kallela, Tobias M Freilinger, Caroline Ran, Scott G Gordon, Anine H Stam, Stacy Steinberg, Guntram Borck, Markku Koiranen, Lydia Quaye, Hieab H H Adams, Terho Lehtimäki, Antti-Pekka Sarin, Juho Wedenoja, David A Hinds, Julie E Buring, Markus Schürks, Paul M Ridker, Maria Gudlaug Hrafnsdottir, Hreinn Stefansson, Susan M Ring, Jouke-Jan Hottenga, Brenda W J H Penninx, Markus Färkkilä, Ville Artto, Mari Kaunisto, Salli Vepsäläinen, Rainer Malik, Andrew C Heath, Pamela A F Madden, Nicholas G Martin, Grant W Montgomery, Mitja I Kurki, Mart Kals, Reedik Mägi, Kalle Pärn, Eija Hämäläinen, Hailiang Huang, Andrea E Byrnes, Lude Franke, Jie Huang, Evie Stergiakouli, Phil H Lee, Cynthia Sandor, Caleb Webber, Zameel Cader, Bertram Muller-Myhsok, Stefan Schreiber, Thomas Meitinger, Johan G Eriksson, Veikko Salomaa, Kauko Heikkilä, Elizabeth Loehrer, Andre G Uitterlinden, Albert Hofman, Cornelia M van Duijn, Lynn Cherkas, Linda M Pedersen, Audun Stubhaug, Christopher S Nielsen, Minna Männikkö, Evelin Mihailov, Lili Milani, Hartmut Göbel, Ann-Louise Esserlind, Anne Francke Christensen, Thomas Folkmann Hansen, Thomas Werge, Jaakko Kaprio, Arpo J Aromaa, Olli Raitakari, M Arfan Ikram, Tim Spector, Marjo-Riitta Järvelin, Andres Metspalu, Christian Kubisch, David P Strachan, Michel D Ferrari, Andrea C Belin, Martin Dichgans, Maija Wessman, Arn M J M van den Maagdenberg, Dorret I Boomsma, George Davey Smith, Kari Stefansson, Nicholas Eriksson, Mark J Daly, Benjamin M Neale, Jes Olesen, Daniel I Chasman, Dale R Nyholt, Aarno Palotie, Masato Akiyama, Varinder S Alg, Sigrid Børte, Joseph P Broderick, Ben M Brumpton, Jérôme Dauvillier, Hubert Desal, Christian Dina, Christoph M Friedrich, Emília I Gaál-Paavola, Jean-Christophe Gentric, Sven Hirsch, Isabel C Hostettler, Henry Houlden, Kristian Hveem, Juha E Jääskeläinen, Marianne Bakke Johnsen, Liming Li, Kuang Lin, Antti Lindgren, Olivier Martin, Koichi Matsuda, Iona Y Millwood, Olivier Naggara, Mika Niemelä, Joanna Pera, Richard Redon, Guy A Rouleau, Marie Søfteland Sandvei, Sabine Schilling, Eimad Shotar, Agnieszka Slowik, Chikashi Terao, W M Monique Verschuren, Robin G Walters, David J Werring, Cristen J Willer, Daniel Woo, Bradford B Worrall, Sirui Zhou, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, and Admin, Oskar
Subjects: Advanced and Specialized Nursing, Incidence, risk assessment, Smoking/epidemiology, intracranial aneurysm, genetic heterogeneity, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Risk Factors, Intracranial Aneurysm/epidemiology, Humans, Subarachnoid Hemorrhage/epidemiology, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, genetics, Neurology (clinical), aneurysmal subarachnoid hemorrhage, genetic, Cardiology and Cardiovascular Medicine
Abstract: Background: Recently, common genetic risk factors for intracranial aneurysm (IA) and aneurysmal subarachnoid hemorrhage (ASAH) were found to explain a large amount of disease heritability and therefore have potential to be used for genetic risk prediction. We constructed a genetic risk score to (1) predict ASAH incidence and IA presence (combined set of unruptured IA and ASAH) and (2) assess its association with patient characteristics. Methods: A genetic risk score incorporating genetic association data for IA and 17 traits related to IA (so-called metaGRS) was created using 1161 IA cases and 407 392 controls from the UK Biobank population study. The metaGRS was validated in combination with risk factors blood pressure, sex, and smoking in 828 IA cases and 68 568 controls from the Nordic HUNT population study. Furthermore, we assessed association between the metaGRS and patient characteristics in a cohort of 5560 IA patients. Results: Per SD increase of metaGRS, the hazard ratio for ASAH incidence was 1.34 (95% CI, 1.20–1.51) and the odds ratio for IA presence 1.09 (95% CI, 1.01–1.18). Upon including the metaGRS on top of clinical risk factors, the concordance index to predict ASAH hazard increased from 0.63 (95% CI, 0.59–0.67) to 0.65 (95% CI, 0.62–0.69), while prediction of IA presence did not improve. The metaGRS was statistically significantly associated with age at ASAH (β=−4.82×10 −3 per year [95% CI, −6.49×10 −3 to −3.14×10 −3 ]; P =1.82×10 −8 ), and location of IA at the internal carotid artery (odds ratio=0.92 [95% CI, 0.86–0.98]; P =0.0041). Conclusions: The metaGRS was predictive of ASAH incidence, although with limited added value over clinical risk factors. The metaGRS was not predictive of IA presence. Therefore, we do not recommend using this metaGRS in daily clinical care. Genetic risk does partly explain the clinical heterogeneity of IA warranting prioritization of clinical heterogeneity in future genetic prediction studies of IA and ASAH.
Published: 2023

8. Associations of autozygosity with a broad range of human phenotypes

Author: David W Clark, Yukinori Okada, Kristjan H S Moore, Dan Mason, Nicola Pirastu, Ilaria Gandin, Hannele Mattsson, Catriona L K Barnes, Kuang Lin, Jing Hua Zhao, Patrick Deelen, Rebecca Rohde, Claudia Schurmann, Xiuqing Guo, Franco Giulianini, Weihua Zhang, Carolina Medina-Gomez, Robert Karlsson, Yanchun Bao, Traci M Bartz, Clemens Baumbach, Ginevra Biino, Matthew J Bixley, Marco Brumat, Jin-Fang Chai, Tanguy Corre, Diana L Cousminer, Annelot M Dekker, David A Eccles, Kristel R van Eijk, Christian Fuchsberger, He Gao, Marine Germain, Scott D Gordon, Hugoline G de Haan, Sarah E Harris, Edith Hofer, Alicia Huerta-Chagoya, Catherine Igartua, Iris E Jansen, Yucheng Jia, Tim Kacprowski, Torgny Karlsson, Marcus E Kleber, Shengchao Alfred Li, Ruifang Li-Gao, Anubha Mahajan, Koichi Matsuda, Karina Meidtner, Weihua Meng, May E Montasser, Peter J van der Most, Matthias Munz, Teresa Nutile, Teemu Palviainen, Gauri Prasad, Rashmi B Prasad, Tallapragada Divya Sri Priyanka, Federica Rizzi, Erika Salvi, Bishwa R Sapkota, Daniel Shriner, Line Skotte, Melissa C Smart, Albert Vernon Smith, Ashley van der Spek, Cassandra N Spracklen, Rona J Strawbridge, Salman M Tajuddin, Stella Trompet, Constance Turman, Niek Verweij, Clara Viberti, Lihua Wang, Helen R Warren, Robyn E Wootton, Lisa R Yanek, Jie Yao, Noha A Yousri, Wei Zhao, Adebowale A Adeyemo, Saima Afaq, Carlos Alberto Aguilar-Salinas, Masato Akiyama, Matthew L Albert, Matthew A Allison, Maris Alver, Tin Aung, Fereidoun Azizi, Amy R Bentley, Heiner Boeing, Eric Boerwinkle, Judith B Borja, Gert J de Borst, Erwin P Bottinger, Linda Broer, Harry Campbell, Stephen Chanock, Miao-Li Chee, Guanjie Chen, Yii-Der I Chen, Zhengming Chen, Yen-Feng Chiu, Massimiliano Cocca, Francis S Collins, Maria Pina Concas, Janie Corley, Giovanni Cugliari, Rob M van Dam, Anna Damulina, Maryam S Daneshpour, Felix R Day, Graciela E Delgado, Klodian Dhana, Alexander S F Doney, Marcus Dörr, Ayo P Doumatey, Nduna Dzimiri, S Sunna Ebenesersdóttir, Joshua Elliott, Paul Elliott, Ralf Ewert, Janine F Felix, Krista Fischer, Barry I Freedman, Giorgia Girotto, Anuj Goel, Martin Gögele, Mark O Goodarzi, Mariaelisa Graff, Einat Granot-Hershkovitz, Francine Grodstein, Simonetta Guarrera, Daniel F Gudbjartsson, Kamran Guity, Bjarni Gunnarsson, Yu Guo, Saskia P Hagenaars, Christopher A Haiman, Avner Halevy, Tamara B Harris, Mehdi Hedayati, David A van Heel, Makoto Hirata, Imo Höfer, Chao Agnes Hsiung, Jinyan Huang, Yi-Jen Hung, M Arfan Ikram, Anuradha Jagadeesan, Pekka Jousilahti, Yoichiro Kamatani, Masahiro Kanai, Nicola D Kerrison, Thorsten Kessler, Kay-Tee Khaw, Chiea Chuen Khor, Dominique P V de Kleijn, Woon-Puay Koh, Ivana Kolcic, Peter Kraft, Bernhard K Krämer, Zoltán Kutalik, Johanna Kuusisto, Claudia Langenberg, Lenore J Launer, Deborah A Lawlor, I-Te Lee, Wen-Jane Lee, Markus M Lerch, Liming Li, Jianjun Liu, Marie Loh, Stephanie J London, Stephanie Loomis, Yingchang Lu, Jian’an Luan, Reedik Mägi, Ani W Manichaikul, Paolo Manunta, Gísli Másson, Nana Matoba, Xue W Mei, Christa Meisinger, Thomas Meitinger, Massimo Mezzavilla, Lili Milani, Iona Y Millwood, Yukihide Momozawa, Amy Moore, Pierre-Emmanuel Morange, Hortensia Moreno-Macías, Trevor A Mori, Alanna C Morrison, Taulant Muka, Yoshinori Murakami, Alison D Murray, Renée de Mutsert, Josyf C Mychaleckyj, Mike A Nalls, Matthias Nauck, Matt J Neville, Ilja M Nolte, Ken K Ong, Lorena Orozco, Sandosh Padmanabhan, Gunnar Pálsson, James S Pankow, Cristian Pattaro, Alison Pattie, Ozren Polasek, Neil Poulter, Peter P Pramstaller, Lluis Quintana-Murci, Katri Räikkönen, Sarju Ralhan, Dabeeru C Rao, Wouter van Rheenen, Stephen S Rich, Paul M Ridker, Cornelius A Rietveld, Antonietta Robino, Frank J A van Rooij, Daniela Ruggiero, Yasaman Saba, Charumathi Sabanayagam, Maria Sabater-Lleal, Cinzia Felicita Sala, Veikko Salomaa, Kevin Sandow, Helena Schmidt, Laura J Scott, William R Scott, Bahareh Sedaghati-Khayat, Bengt Sennblad, Jessica van Setten, Peter J Sever, Wayne H-H Sheu, Yuan Shi, Smeeta Shrestha, Sharvari Rahul Shukla, Jon K Sigurdsson, Timo Tonis Sikka, Jai Rup Singh, Blair H Smith, Alena Stančáková, Alice Stanton, John M Starr, Lilja Stefansdottir, Leon Straker, Patrick Sulem, Gardar Sveinbjornsson, Morris A Swertz, Adele M Taylor, Kent D Taylor, Natalie Terzikhan, Yih-Chung Tham, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Annika Tillander, Russell P Tracy, Teresa Tusié-Luna, Ioanna Tzoulaki, Simona Vaccargiu, Jagadish Vangipurapu, Jan H Veldink, Veronique Vitart, Uwe Völker, Eero Vuoksimaa, Salma M Wakil, Melanie Waldenberger, Gurpreet S Wander, Ya Xing Wang, Nicholas J Wareham, Sarah Wild, Chittaranjan S Yajnik, Jian-Min Yuan, Lingyao Zeng, Liang Zhang, Jie Zhou, Najaf Amin, Folkert W Asselbergs, Stephan J L Bakker, Diane M Becker, Benjamin Lehne, David A Bennett, Leonard H van den Berg, Sonja I Berndt, Dwaipayan Bharadwaj, Lawrence F Bielak, Murielle Bochud, Mike Boehnke, Claude Bouchard, Jonathan P Bradfield, Jennifer A Brody, Archie Campbell, Shai Carmi, Mark J Caulfield, David Cesarini, John C Chambers, Giriraj Ratan Chandak, Ching-Yu Cheng, Marina Ciullo, Marilyn Cornelis, Daniele Cusi, George Davey Smith, Ian J Deary, Rajkumar Dorajoo, Cornelia M van Duijn, David Ellinghaus, Jeanette Erdmann, Johan G Eriksson, Evangelos Evangelou, Michele K Evans, Jessica D Faul, Bjarke Feenstra, Mary Feitosa, Sylvain Foisy, Andre Franke, Yechiel Friedlander, Paolo Gasparini, Christian Gieger, Clicerio Gonzalez, Philippe Goyette, Struan F A Grant, Lyn R Griffiths, Leif Groop, Vilmundur Gudnason, Ulf Gyllensten, Hakon Hakonarson, Anders Hamsten, Pim van der Harst, Chew-Kiat Heng, Andrew A Hicks, Hagit Hochner, Heikki Huikuri, Steven C Hunt, Vincent W V Jaddoe, Philip L De Jager, Magnus Johannesson, Åsa Johansson, Jost B Jonas, J Wouter Jukema, Juhani Junttila, Jaakko Kaprio, Sharon L. R. Kardia, Fredrik Karpe, Meena Kumari, Markku Laakso, Sander W van der Laan, Jari Lahti, Matthias Laudes, Rodney A Lea, Wolfgang Lieb, Thomas Lumley, Nicholas G Martin, Winfried März, Giuseppe Matullo, Mark I McCarthy, Sarah E Medland, Tony R Merriman, Andres Metspalu, Brian F Meyer, Karen L Mohlke, Grant W Montgomery, Dennis Mook-Kanamori, Patricia B Munroe, Kari E North, Dale R Nyholt, Jeffery R O’connell, Carole Ober, Albertine J Oldehinkel, Walter Palmas, Colin Palmer, Gerard G Pasterkamp, Etienne Patin, Craig E Pennell, Louis Perusse, Patricia A Peyser, Mario Pirastu, Tinca J. C. Polderman, David J Porteous, Danielle Posthuma, Bruce M Psaty, John D Rioux, Fernando Rivadeneira, Charles Rotimi, Jerome I Rotter, Igor Rudan, Hester M Den Ruijter, Dharambir K Sanghera, Naveed Sattar, Reinhold Schmidt, Matthias B Schulze, Heribert Schunkert, Robert A Scott, Alan R Shuldiner, Xueling Sim, Neil Small, Jennifer A Smith, Nona Sotoodehnia, E-Shyong Tai, Alexander Teumer, Nicholas J Timpson, Daniela Toniolo, David-Alexandre Tregouet, Tiinamaija Tuomi, Peter Vollenweider, Carol A Wang, David R Weir, John B Whitfield, Cisca Wijmenga, Tien-Yin Wong, John Wright, Jingyun Yang, Lei Yu, Babette S Zemel, Alan B Zonderman, Markus Perola, Patrik K. E. Magnusson, André G Uitterlinden, Jaspal S Kooner, Daniel I Chasman, Ruth J. F. Loos, Nora Franceschini, Lude Franke, Chris S Haley, Caroline Hayward, Robin G Walters, John R. B. Perry, Tōnu Esko, Agnar Helgason, Kari Stefansson, Peter K Joshi, Michiaki Kubo, and James F Wilson
Subjects: Science
Abstract: Inbreeding depression has been observed in many different species, but in humans a systematic analysis has been difficult so far. Here, analysing more than 1.3 million individuals, the authors show that a genomic inbreeding coefficient (FROH) is associated with disadvantageous outcomes in 32 out of 100 traits tested.
Published: 2019
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9. Trans-ethnic kidney function association study reveals putative causal genes and effects on kidney-specific disease aetiologies

Author: Andrew P. Morris, Thu H. Le, Haojia Wu, Artur Akbarov, Peter J. van der Most, Gibran Hemani, George Davey Smith, Anubha Mahajan, Kyle J. Gaulton, Girish N. Nadkarni, Adan Valladares-Salgado, Niels Wacher-Rodarte, Josyf C. Mychaleckyj, Nicole D. Dueker, Xiuqing Guo, Yang Hai, Jeffrey Haessler, Yoichiro Kamatani, Adrienne M. Stilp, Gu Zhu, James P. Cook, Johan Ärnlöv, Susan H. Blanton, Martin H. de Borst, Erwin P. Bottinger, Thomas A. Buchanan, Sylvia Cechova, Fadi J. Charchar, Pei-Lun Chu, Jeffrey Damman, James Eales, Ali G. Gharavi, Vilmantas Giedraitis, Andrew C. Heath, Eli Ipp, Krzysztof Kiryluk, Holly J. Kramer, Michiaki Kubo, Anders Larsson, Cecilia M. Lindgren, Yingchang Lu, Pamela A. F. Madden, Grant W. Montgomery, George J. Papanicolaou, Leslie J. Raffel, Ralph L. Sacco, Elena Sanchez, Holger Stark, Johan Sundstrom, Kent D. Taylor, Anny H. Xiang, Aleksandra Zivkovic, Lars Lind, Erik Ingelsson, Nicholas G. Martin, John B. Whitfield, Jianwen Cai, Cathy C. Laurie, Yukinori Okada, Koichi Matsuda, Charles Kooperberg, Yii-Der Ida Chen, Tatjana Rundek, Stephen S. Rich, Ruth J. F. Loos, Esteban J. Parra, Miguel Cruz, Jerome I. Rotter, Harold Snieder, Maciej Tomaszewski, Benjamin D. Humphreys, and Nora Franceschini
Subjects: Science
Abstract: Estimated glomerular filtration rate (eGFR) is a measure of kidney function used to define chronic kidney disease. Here, Morris et al. perform trans-ethnic genome-wide meta-analyses for eGFR in 312,468 individuals and identify novel loci and downstream putative causal genes.
Published: 2019
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10. Association of SARS-CoV-2 viral load at admission with in-hospital acute kidney injury: A retrospective cohort study.

Author: Ishan Paranjpe, Kumardeep Chaudhary, Kipp W Johnson, Suraj K Jaladanki, Shan Zhao, Jessica K De Freitas, Elisabet Pujdas, Fayzan Chaudhry, Erwin P Bottinger, Matthew A Levin, Zahi A Fayad, Alexander W Charney, Jane Houldsworth, Carlos Cordon-Cardo, Benjamin S Glicksberg, and Girish N Nadkarni
Subjects: Medicine, Science
Abstract: BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the associated Coronavirus Disease 2019 (COVID-19) is a public health emergency. Acute kidney injury (AKI) is a common complication in hospitalized patients with COVID-19 although mechanisms underlying AKI are yet unclear. There may be a direct effect of SARS-CoV-2 virus on the kidney; however, there is currently no data linking SARS-CoV-2 viral load (VL) to AKI. We explored the association of SARS-CoV-2 VL at admission to AKI in a large diverse cohort of hospitalized patients with COVID-19.Methods and findingsWe included patients hospitalized between March 13th and May 19th, 2020 with SARS-CoV-2 in a large academic healthcare system in New York City (N = 1,049) with available VL at admission quantified by real-time RT-PCR. We extracted clinical and outcome data from our institutional electronic health records (EHRs). AKI was defined by KDIGO guidelines. We fit a Fine-Gray competing risks model (with death as a competing risk) using demographics, comorbidities, admission severity scores, and log10 transformed VL as covariates and generated adjusted hazard ratios (aHR) and 95% Confidence Intervals (CIs). VL was associated with an increased risk of AKI (aHR = 1.04, 95% CI: 1.01-1.08, p = 0.02) with a 4% increased hazard for each log10 VL change. Patients with a viral load in the top 50th percentile had an increased adjusted hazard of 1.27 (95% CI: 1.02-1.58, p = 0.03) for AKI as compared to those in the bottom 50th percentile.ConclusionsVL is weakly but significantly associated with in-hospital AKI after adjusting for confounders. This may indicate the role of VL in COVID-19 associated AKI. This data may inform future studies to discover the mechanistic basis of COVID-19 associated AKI.
Published: 2021
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11. Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City

Author: Girish N Nadkarni, Zahi A Fayad, Benjamin S Glicksberg, David L Reich, Prem Timsina, Arash Kia, Patricia Kovatch, Jessica K De Freitas, Paul O’Reilly, Allan Just, Dennis Charney, Ishan Paranjpe, Ross O'Hagan, Adam J Russak, Anuradha Lala, Riccardo Miotto, Akhil Vaid, Kipp W Johnson, Matteo Danieletto, Eddye Golden, Dara Meyer, Manbir Singh, Sulaiman Somani, Arjun Kapoor, Sayan Manna, Udit Nangia, Suraj K Jaladanki, Laura M Huckins, Patricia Glowe, Robert M Freeman, Matthew A Levin, Jeffrey Jhang, Adolfo Firpo, Joseph Finkelstein, Judith A Aberg, Emilia Bagiella, Carol R Horowitz, Barbara Murphy, Eric J Nestler, V Fuster, Carlos Cordon-Cardo, Erwin P Bottinger, and Alexander W Charney
Subjects: Medicine
Abstract: Objective The COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-hospital mortality with those who were discharged alive.Design Demographic, clinical and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed COVID-19 between 27 February and 2 April 2020 were identified through institutional electronic health records. We performed a retrospective comparative analysis of patients who had in-hospital mortality or were discharged alive.Setting All patients were admitted to the Mount Sinai Health System, a large quaternary care urban hospital system.Participants Participants over the age of 18 years were included.Primary outcomes We investigated in-hospital mortality during the study period.Results A total of 2199 patients with COVID-19 were hospitalised during the study period. As of 2 April, 1121 (51%) patients remained hospitalised, and 1078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 μg/mL, C reactive protein was 162 mg/L and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 μg/mL, C reactive protein was 79 mg/L and procalcitonin was 0.09 ng/mL.Conclusions In our cohort of hospitalised patients, requirement of intensive care and mortality were high. Patients who died typically had more pre-existing conditions and greater perturbations in inflammatory markers as compared with those who were discharged.
Published: 2020
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12. Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose.

Author: Peitao Wu, Denis Rybin, Lawrence F Bielak, Mary F Feitosa, Nora Franceschini, Yize Li, Yingchang Lu, Jonathan Marten, Solomon K Musani, Raymond Noordam, Sridharan Raghavan, Lynda M Rose, Karen Schwander, Albert V Smith, Salman M Tajuddin, Dina Vojinovic, Najaf Amin, Donna K Arnett, Erwin P Bottinger, Ayse Demirkan, Jose C Florez, Mohsen Ghanbari, Tamara B Harris, Lenore J Launer, Jingmin Liu, Jun Liu, Dennis O Mook-Kanamori, Alison D Murray, Mike A Nalls, Patricia A Peyser, André G Uitterlinden, Trudy Voortman, Claude Bouchard, Daniel Chasman, Adolfo Correa, Renée de Mutsert, Michele K Evans, Vilmundur Gudnason, Caroline Hayward, Linda Kao, Sharon L R Kardia, Charles Kooperberg, Ruth J F Loos, Michael M Province, Tuomo Rankinen, Susan Redline, Paul M Ridker, Jerome I Rotter, David Siscovick, Blair H Smith, Cornelia van Duijn, Alan B Zonderman, D C Rao, James G Wilson, Josée Dupuis, James B Meigs, Ching-Ti Liu, and Jason L Vassy
Subjects: Medicine, Science
Abstract: Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p
Published: 2020
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13. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension

Author: Tanika N, Kelly, Xiao, Sun, Karen Y, He, Michael R, Brown, Sarah A Gagliano, Taliun, Jacklyn N, Hellwege, Marguerite R, Irvin, Xuenan, Mi, Jennifer A, Brody, Nora, Franceschini, Xiuqing, Guo, Shih-Jen, Hwang, Paul S, de Vries, Yan, Gao, Arden, Moscati, Girish N, Nadkarni, Lisa R, Yanek, Tali, Elfassy, Jennifer A, Smith, Ren-Hua, Chung, Amber L, Beitelshees, Amit, Patki, Stella, Aslibekyan, Brandon M, Blobner, Juan M, Peralta, Themistocles L, Assimes, Walter R, Palmas, Chunyu, Liu, Adam P, Bress, Zhijie, Huang, Lewis C, Becker, Chii-Min, Hwa, Jeffrey R, O'Connell, Jenna C, Carlson, Helen R, Warren, Sayantan, Das, Ayush, Giri, Lisa W, Martin, W, Craig Johnson, Ervin R, Fox, Erwin P, Bottinger, Alexander C, Razavi, Dhananjay, Vaidya, Lee-Ming, Chuang, Yen-Pei C, Chang, Take, Naseri, Deepti, Jain, Hyun Min, Kang, Adriana M, Hung, Vinodh, Srinivasasainagendra, Beverly M, Snively, Dongfeng, Gu, May E, Montasser, Muagututi'a Sefuiva, Reupena, Benjamin D, Heavner, Jonathon, LeFaive, James E, Hixson, Kenneth M, Rice, Fei Fei, Wang, Jonas B, Nielsen, Jianfeng, Huang, Alyna T, Khan, Wei, Zhou, Jovia L, Nierenberg, Cathy C, Laurie, Nicole D, Armstrong, Mengyao, Shi, Yang, Pan, Adrienne M, Stilp, Leslie, Emery, Quenna, Wong, Nicola L, Hawley, Ryan L, Minster, Joanne E, Curran, Patricia B, Munroe, Daniel E, Weeks, Kari E, North, Russell P, Tracy, Eimear E, Kenny, Daichi, Shimbo, Aravinda, Chakravarti, Stephen S, Rich, Alex P, Reiner, John, Blangero, Susan, Redline, Braxton D, Mitchell, Dabeeru C, Rao, Yii-Der, Ida Chen, Sharon L R, Kardia, Robert C, Kaplan, Rasika A, Mathias, Jiang, He, Bruce M, Psaty, Myriam, Fornage, Ruth J F, Loos, Adolfo, Correa, Eric, Boerwinkle, Jerome I, Rotter, Charles, Kooperberg, Todd L, Edwards, Gonçalo R, Abecasis, Xiaofeng, Zhu, Daniel, Levy, Donna K, Arnett, and Alanna C, Morrison
Subjects: Hypertension, Internal Medicine, Humans, Blood Pressure, Genomics, Precision Medicine, Polymorphism, Single Nucleotide, Genome-Wide Association Study
Abstract: Background: The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure. Methods: We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants. Results: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings ( P -8 ). Among them, a rare intergenic variant at novel locus, LOC100506274 , was associated with lower systolic blood pressure in stage-1 (beta [SE]=−32.6 [6.0]; P =4.99×10 -8 ) but not stage-2 analysis ( P =0.11). Furthermore, a novel common variant at the known INSR locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=−0.36 [0.07]; P =4.18×10 -7 ) and attained genome-wide significance in stage-2 (beta [SE]=−0.29 [0.03]; P =7.28×10 -23 ). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings ( P -6 and P -4 , respectively). Discussion: We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.
Published: 2023

14. CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits

Author: Aurélien Macé, Marcus A. Tuke, Patrick Deelen, Kati Kristiansson, Hannele Mattsson, Margit Nõukas, Yadav Sapkota, Ursula Schick, Eleonora Porcu, Sina Rüeger, Aaron F. McDaid, David Porteous, Thomas W. Winkler, Erika Salvi, Nick Shrine, Xueping Liu, Wei Q. Ang, Weihua Zhang, Mary F. Feitosa, Cristina Venturini, Peter J. van der Most, Anders Rosengren, Andrew R. Wood, Robin N. Beaumont, Samuel E. Jones, Katherine S. Ruth, Hanieh Yaghootkar, Jessica Tyrrell, Aki S. Havulinna, Harmen Boers, Reedik Mägi, Jennifer Kriebel, Martina Müller-Nurasyid, Markus Perola, Markku Nieminen, Marja-Liisa Lokki, Mika Kähönen, Jorma S. Viikari, Frank Geller, Jari Lahti, Aarno Palotie, Päivikki Koponen, Annamari Lundqvist, Harri Rissanen, Erwin P. Bottinger, Saima Afaq, Mary K. Wojczynski, Petra Lenzini, Ilja M. Nolte, Thomas Sparsø, Nicole Schupf, Kaare Christensen, Thomas T. Perls, Anne B. Newman, Thomas Werge, Harold Snieder, Timothy D. Spector, John C. Chambers, Seppo Koskinen, Mads Melbye, Olli T. Raitakari, Terho Lehtimäki, Martin D. Tobin, Louise V. Wain, Juha Sinisalo, Annette Peters, Thomas Meitinger, Nicholas G. Martin, Naomi R. Wray, Grant W. Montgomery, Sarah E. Medland, Morris A. Swertz, Erkki Vartiainen, Katja Borodulin, Satu Männistö, Anna Murray, Murielle Bochud, Sébastien Jacquemont, Fernando Rivadeneira, Thomas F. Hansen, Albertine J. Oldehinkel, Massimo Mangino, Michael A. Province, Panos Deloukas, Jaspal S. Kooner, Rachel M. Freathy, Craig Pennell, Bjarke Feenstra, David P. Strachan, Guillaume Lettre, Joel Hirschhorn, Daniele Cusi, Iris M. Heid, Caroline Hayward, Katrin Männik, Jacques S. Beckmann, Ruth J. F. Loos, Dale R. Nyholt, Andres Metspalu, Johan G. Eriksson, Michael N. Weedon, Veikko Salomaa, Lude Franke, Alexandre Reymond, Timothy M. Frayling, and Zoltán Kutalik
Subjects: Science
Abstract: Individual SNPs have small effects on anthropometric traits, yet the impact of CNVs has remained largely unknown. Here, Kutalik and co-workers perform a large-scale genome-wide meta-analysis of structural variation and find rare CNVs associated with height, weight and BMI with large effect sizes.
Published: 2017
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15. Protein-altering and regulatory genetic variants near GATA4 implicated in bicuspid aortic valve

Author: Bo Yang, Wei Zhou, Jiao Jiao, Jonas B. Nielsen, Michael R. Mathis, Mahyar Heydarpour, Guillaume Lettre, Lasse Folkersen, Siddharth Prakash, Claudia Schurmann, Lars Fritsche, Gregory A. Farnum, Maoxuan Lin, Mohammad Othman, Whitney Hornsby, Anisa Driscoll, Alexandra Levasseur, Marc Thomas, Linda Farhat, Marie-Pierre Dubé, Eric M. Isselbacher, Anders Franco-Cereceda, Dong-chuan Guo, Erwin P. Bottinger, G. Michael Deeb, Anna Booher, Sachin Kheterpal, Y. Eugene Chen, Hyun Min Kang, Jacob Kitzman, Heather J. Cordell, Bernard D. Keavney, Judith A. Goodship, Santhi K. Ganesh, Gonçalo Abecasis, Kim A. Eagle, Alan P. Boyle, Ruth J. F. Loos, Per Eriksson, Jean-Claude Tardif, Chad M. Brummett, Dianna M. Milewicz, Simon C. Body, and Cristen J. Willer
Subjects: Science
Abstract: Bicuspid aortic valve (BAV) is the most common human congenital cardiovascular malformation. Here, the authors perform a genome-wide association study for BAV and identify risk variants in the gene region of cardiac-specific transcription factor GATA4 and implicate GATA4 in heart valve development.
Published: 2017
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16. A machine learning approach to determine resilience utilizing wearable device data: analysis of an observational cohort

Author: Robert P Hirten, Maria Suprun, Matteo Danieletto, Micol Zweig, Eddye Golden, Renata Pyzik, Sparshdeep Kaur, Drew Helmus, Anthony Biello, Kyle Landell, Jovita Rodrigues, Erwin P Bottinger, Laurie Keefer, Dennis Charney, Girish N Nadkarni, Mayte Suarez-Farinas, and Zahi A Fayad
Subjects: Health Informatics
Abstract: Objective To assess whether an individual’s degree of psychological resilience can be determined from physiological metrics passively collected from a wearable device. Materials and Methods Data were analyzed in this secondary analysis of the Warrior Watch Study dataset, a prospective cohort of healthcare workers enrolled across 7 hospitals in New York City. Subjects wore an Apple Watch for the duration of their participation. Surveys were collected measuring resilience, optimism, and emotional support at baseline. Results We evaluated data from 329 subjects (mean age 37.4 years, 37.1% male). Across all testing sets, gradient-boosting machines (GBM) and extreme gradient-boosting models performed best for high- versus low-resilience prediction, stratified on a median Connor-Davidson Resilience Scale-2 score of 6 (interquartile range = 5–7), with an AUC of 0.60. When predicting resilience as a continuous variable, multivariate linear models had a correlation of 0.24 (P = .029) and RMSE of 1.37 in the testing data. A positive psychological construct, comprised of resilience, optimism, and emotional support was also evaluated. The oblique random forest method performed best in estimating high- versus low-composite scores stratified on a median of 32.5, with an AUC of 0.65, a sensitivity of 0.60, and a specificity of 0.70. Discussion In a post hoc analysis, machine learning models applied to physiological metrics collected from wearable devices had some predictive ability in identifying resilience states and a positive psychological construct. Conclusions These findings support the further assessment of psychological characteristics from passively collected wearable data in dedicated studies.
Published: 2023

17. Leveraging hierarchy in medical codes for predictive modeling.

Author: Anima Singh, Girish N. Nadkarni, John V. Guttag, and Erwin P. Bottinger
Published: 2014
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18. Genetic associations at 53 loci highlight cell types and biological pathways relevant for kidney function

Author: Cristian Pattaro, Alexander Teumer, Mathias Gorski, Audrey Y. Chu, Man Li, Vladan Mijatovic, Maija Garnaas, Adrienne Tin, Rossella Sorice, Yong Li, Daniel Taliun, Matthias Olden, Meredith Foster, Qiong Yang, Ming-Huei Chen, Tune H. Pers, Andrew D. Johnson, Yi-An Ko, Christian Fuchsberger, Bamidele Tayo, Michael Nalls, Mary F. Feitosa, Aaron Isaacs, Abbas Dehghan, Pio d’Adamo, Adebowale Adeyemo, Aida Karina Dieffenbach, Alan B. Zonderman, Ilja M. Nolte, Peter J. van der Most, Alan F. Wright, Alan R. Shuldiner, Alanna C. Morrison, Albert Hofman, Albert V. Smith, Albert W. Dreisbach, Andre Franke, Andre G. Uitterlinden, Andres Metspalu, Anke Tonjes, Antonio Lupo, Antonietta Robino, Åsa Johansson, Ayse Demirkan, Barbara Kollerits, Barry I. Freedman, Belen Ponte, Ben A. Oostra, Bernhard Paulweber, Bernhard K. Krämer, Braxton D. Mitchell, Brendan M. Buckley, Carmen A. Peralta, Caroline Hayward, Catherine Helmer, Charles N. Rotimi, Christian M. Shaffer, Christian Müller, Cinzia Sala, Cornelia M. van Duijn, Aude Saint-Pierre, Daniel Ackermann, Daniel Shriner, Daniela Ruggiero, Daniela Toniolo, Yingchang Lu, Daniele Cusi, Darina Czamara, David Ellinghaus, David S. Siscovick, Douglas Ruderfer, Christian Gieger, Harald Grallert, Elena Rochtchina, Elizabeth J. Atkinson, Elizabeth G. Holliday, Eric Boerwinkle, Erika Salvi, Erwin P. Bottinger, Federico Murgia, Fernando Rivadeneira, Florian Ernst, Florian Kronenberg, Frank B. Hu, Gerjan J. Navis, Gary C. Curhan, George B. Ehret, Georg Homuth, Stefan Coassin, Gian-Andri Thun, Giorgio Pistis, Giovanni Gambaro, Giovanni Malerba, Grant W. Montgomery, Gudny Eiriksdottir, Gunnar Jacobs, Guo Li, H-Erich Wichmann, Harry Campbell, Helena Schmidt, Henri Wallaschofski, Henry Völzke, Hermann Brenner, Heyo K. Kroemer, Holly Kramer, Honghuang Lin, I. Mateo Leach, Ian Ford, Idris Guessous, Igor Rudan, Inga Prokopenko, Ingrid Borecki, Iris M. Heid, Ivana Kolcic, Ivana Persico, J. Wouter Jukema, James F. Wilson, Janine F. Felix, Jasmin Divers, Jean-Charles Lambert, Jeanette M. Stafford, Jean-Michel Gaspoz, Jennifer A. Smith, Jessica D. Faul, Jie Jin Wang, Jingzhong Ding, Joel N. Hirschhorn, John Attia, John B. Whitfield, John Chalmers, Jorma Viikari, Josef Coresh, Joshua C. Denny, Juha Karjalainen, Jyotika K. Fernandes, Karlhans Endlich, Katja Butterbach, Keith L. Keene, Kurt Lohman, Laura Portas, Lenore J. Launer, Leo-Pekka Lyytikäinen, Loic Yengo, Lude Franke, Luigi Ferrucci, Lynda M. Rose, Lyudmyla Kedenko, Madhumathi Rao, Maksim Struchalin, Marcus E. Kleber, Margherita Cavalieri, Margot Haun, Marilyn C. Cornelis, Marina Ciullo, Mario Pirastu, Mariza de Andrade, Mark A. McEvoy, Mark Woodward, Martin Adam, Massimiliano Cocca, Matthias Nauck, Medea Imboden, Melanie Waldenberger, Menno Pruijm, Marie Metzger, Michael Stumvoll, Michele K. Evans, Michele M. Sale, Mika Kähönen, Mladen Boban, Murielle Bochud, Myriam Rheinberger, Niek Verweij, Nabila Bouatia-Naji, Nicholas G. Martin, Nick Hastie, Nicole Probst-Hensch, Nicole Soranzo, Olivier Devuyst, Olli Raitakari, Omri Gottesman, Oscar H. Franco, Ozren Polasek, Paolo Gasparini, Patricia B. Munroe, Paul M. Ridker, Paul Mitchell, Paul Muntner, Christa Meisinger, Johannes H. Smit, ICBP Consortium, AGEN Consortium, CARDIOGRAM, CHARGe-Heart Failure Group, ECHOGen Consortium, Peter Kovacs, Philipp S. Wild, Philippe Froguel, Rainer Rettig, Reedik Mägi, Reiner Biffar, Reinhold Schmidt, Rita P. S. Middelberg, Robert J. Carroll, Brenda W. Penninx, Rodney J. Scott, Ronit Katz, Sanaz Sedaghat, Sarah H. Wild, Sharon L. R. Kardia, Sheila Ulivi, Shih-Jen Hwang, Stefan Enroth, Stefan Kloiber, Stella Trompet, Benedicte Stengel, Stephen J. Hancock, Stephen T. Turner, Sylvia E. Rosas, Sylvia Stracke, Tamara B. Harris, Tanja Zeller, Tatijana Zemunik, Terho Lehtimäki, Thomas Illig, Thor Aspelund, Tiit Nikopensius, Tonu Esko, Toshiko Tanaka, Ulf Gyllensten, Uwe Völker, Valur Emilsson, Veronique Vitart, Ville Aalto, Vilmundur Gudnason, Vincent Chouraki, Wei-Min Chen, Wilmar Igl, Winfried März, Wolfgang Koenig, Wolfgang Lieb, Ruth J. F. Loos, Yongmei Liu, Harold Snieder, Peter P. Pramstaller, Afshin Parsa, Jeffrey R. O’Connell, Katalin Susztak, Pavel Hamet, Johanne Tremblay, Ian H. de Boer, Carsten A. Böger, Wolfram Goessling, Daniel I. Chasman, Anna Köttgen, W. H. Linda Kao, and Caroline S. Fox
Subjects: Science
Abstract: Reduced glomerular filtration rate (eGFR) is a hallmark of chronic kidney disease. Here, Pattaro et al. conduct a meta-analysis to discover several new loci associated with variation in eGFR and find that genes associated with eGFR loci often encode proteins potentially related to kidney development.
Published: 2016
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19. Correction: Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.

Author: Jingjing Liang, Thu H Le, Digna R Velez Edwards, Bamidele O Tayo, Kyle J Gaulton, Jennifer A Smith, Yingchang Lu, Richard A Jensen, Guanjie Chen, Lisa R Yanek, Karen Schwander, Salman M Tajuddin, Tamar Sofer, Wonji Kim, James Kayima, Colin A McKenzie, Ervin Fox, Michael A Nalls, J Hunter Young, Yan V Sun, Jacqueline M Lane, Sylvia Cechova, Jie Zhou, Hua Tang, Myriam Fornage, Solomon K Musani, Heming Wang, Juyoung Lee, Adebowale Adeyemo, Albert W Dreisbach, Terrence Forrester, Pei-Lun Chu, Anne Cappola, Michele K Evans, Alanna C Morrison, Lisa W Martin, Kerri L Wiggins, Qin Hui, Wei Zhao, Rebecca D Jackson, Erin B Ware, Jessica D Faul, Alex P Reiner, Michael Bray, Joshua C Denny, Thomas H Mosley, Walter Palmas, Xiuqing Guo, George J Papanicolaou, Alan D Penman, Joseph F Polak, Kenneth Rice, Ken D Taylor, Eric Boerwinkle, Erwin P Bottinger, Kiang Liu, Neil Risch, Steven C Hunt, Charles Kooperberg, Alan B Zonderman, Cathy C Laurie, Diane M Becker, Jianwen Cai, Ruth J F Loos, Bruce M Psaty, David R Weir, Sharon L R Kardia, Donna K Arnett, Sungho Won, Todd L Edwards, Susan Redline, Richard S Cooper, D C Rao, Jerome I Rotter, Charles Rotimi, Daniel Levy, Aravinda Chakravarti, Xiaofeng Zhu, and Nora Franceschini
Subjects: Genetics, QH426-470
Abstract: [This corrects the article DOI: 10.1371/journal.pgen.1006728.].
Published: 2018
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20. The genetic underpinnings of variation in ages at menarche and natural menopause among women from the multi-ethnic Population Architecture using Genomics and Epidemiology (PAGE) Study: A trans-ethnic meta-analysis.

Author: Lindsay Fernández-Rhodes, Jennifer R Malinowski, Yujie Wang, Ran Tao, Nathan Pankratz, Janina M Jeff, Sachiko Yoneyama, Cara L Carty, V Wendy Setiawan, Loic Le Marchand, Christopher Haiman, Steven Corbett, Ellen Demerath, Gerardo Heiss, Myron Gross, Petra Buzkova, Dana C Crawford, Steven C Hunt, D C Rao, Karen Schwander, Aravinda Chakravarti, Omri Gottesman, Noura S Abul-Husn, Erwin P Bottinger, Ruth J F Loos, Leslie J Raffel, Jie Yao, Xiuqing Guo, Suzette J Bielinski, Jerome I Rotter, Dhananjay Vaidya, Yii-Der Ida Chen, Sheila F Castañeda, Martha Daviglus, Robert Kaplan, Gregory A Talavera, Kelli K Ryckman, Ulrike Peters, Jose Luis Ambite, Steven Buyske, Lucia Hindorff, Charles Kooperberg, Tara Matise, Nora Franceschini, and Kari E North
Subjects: Medicine, Science
Abstract: Current knowledge of the genetic architecture of key reproductive events across the female life course is largely based on association studies of European descent women. The relevance of known loci for age at menarche (AAM) and age at natural menopause (ANM) in diverse populations remains unclear. We investigated 32 AAM and 14 ANM previously-identified loci and sought to identify novel loci in a trans-ethnic array-wide study of 196,483 SNPs on the MetaboChip (Illumina, Inc.). A total of 45,364 women of diverse ancestries (African, Hispanic/Latina, Asian American and American Indian/Alaskan Native) in the Population Architecture using Genomics and Epidemiology (PAGE) Study were included in cross-sectional analyses of AAM and ANM. Within each study we conducted a linear regression of SNP associations with self-reported or medical record-derived AAM or ANM (in years), adjusting for birth year, population stratification, and center/region, as appropriate, and meta-analyzed results across studies using multiple meta-analytic techniques. For both AAM and ANM, we observed more directionally consistent associations with the previously reported risk alleles than expected by chance (p-valuesbinomial≤0.01). Eight densely genotyped reproductive loci generalized significantly to at least one non-European population. We identified one trans-ethnic array-wide SNP association with AAM and two significant associations with ANM, which have not been described previously. Additionally, we observed evidence of independent secondary signals at three of six AAM trans-ethnic loci. Our findings support the transferability of reproductive trait loci discovered in European women to women of other race/ethnicities and indicate the presence of additional trans-ethnic associations both at both novel and established loci. These findings suggest the benefit of including diverse populations in future studies of the genetic architecture of female growth and development.
Published: 2018
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21. Albuminuria Testing in Hypertension and Diabetes

Author: Jung-Im Shin, Alex R. Chang, Morgan E. Grams, Josef Coresh, Shoshana H. Ballew, Aditya Surapaneni, Kunihiro Matsushita, Henk J.G. Bilo, Juan J. Carrero, Gabriel Chodick, Kenn B. Daratha, Simerjot K. Jassal, Girish N. Nadkarni, Robert G. Nelson, Christoph Nowak, Nikita Stempniewicz, Keiichi Sumida, Jamie P. Traynor, Mark Woodward, Yingying Sang, Ron T. Gansevoort, John Chalmers, Katherine Tuttle, Radica Alicic, Sterling McPherson, Cami Jones, Gurmukteshwar Singh, Jamie Green, H. Lester Kirchner, Varda Shalev, Erwin P. Bottinger, Ruth J.F. Loos, Stephen B. Ellis, John Cuddeback, Elizabeth Ciemins, Emily Carbonara, Stephan Dunning, William C. Knowler, Helen C. Looker, Lyane M. Kieneker, Stephan J.L. Bakker, Hans L. Hillege, Pim van der Harst, Jacklyn Bergstrom, Joachim Ix, Csaba P. Kovesdy, Praveen Potukuchi, Marco Trevisan, Carl Gustaf Elinder, Björn Wettermark, Johan Ärnlöv, Patrick B. Mark, Peter C. Thomson, Colin C. Geddes, Gijs W.D. Landman, Kornelis J.J. van Hateren, Nanne Kleefstra, Orlando Gutierrez, Tsuneo Konta, Andrew S. Levey, Kevan Polkinghorne, Elke Schäffner, Jingsha Chen, Aditya Surapeneni, Groningen Kidney Center (GKC), and Cardiovascular Centre (CVC)
Subjects: Adult, medicine.medical_specialty, Article, Diabetes mellitus, Internal medicine, Internal Medicine, Diabetes Mellitus, Medicine, Albuminuria, Humans, Renal Insufficiency, Chronic, Aged, business.industry, Incidence (epidemiology), Odds ratio, Middle Aged, medicine.disease, Blood pressure, Meta-analysis, Creatinine, Cohort, Hypertension, medicine.symptom, business, Kidney disease, Glomerular Filtration Rate
Abstract: Albuminuria is an under-recognized component of chronic kidney disease definition, staging, and prognosis. Guidelines, particularly for hypertension, conflict on recommendations for urine albumin-to-creatinine ratio (ACR) measurement. Separately among 1 344 594 adults with diabetes and 2 334 461 nondiabetic adults with hypertension from the chronic kidney disease Prognosis Consortium, we assessed ACR testing, estimated the prevalence and incidence of ACR ≥30 mg/g and developed risk models for ACR ≥30 mg/g. The ACR screening rate (cohort range) was 35.1% (12.3%–74.5%) in diabetes and 4.1% (1.3%–20.7%) in hypertension. Screening was largely unrelated to the predicted risk of prevalent albuminuria. The median prevalence of ACR ≥30 mg/g across cohorts was 32.1% in diabetes and 21.8% in hypertension. Higher systolic blood pressure was associated with a higher prevalence of albuminuria (odds ratio [95% CI] per 20 mm Hg in diabetes, 1.50 [1.42–1.60]; in hypertension, 1.36 [1.28–1.45]). The ratio of undetected (due to lack of screening) to detected ACR ≥30 mg/g was estimated at 1.8 in diabetes and 19.5 in hypertension. Among those with ACR
Published: 2021

22. Neptune: an environment for the delivery of genomic medicine

Author: Venner Eric, Victoria Yi, David Murdock, Sara E. Kalla, Tsung-Jung Wu, Aniko Sabo, Shoudong Li, Qingchang Meng, Xia Tian, Mullai Murugan, Michelle Cohen, Christie Kovar, Wei-Qi Wei, Wendy K. Chung, Chunhua Weng, Georgia L. Wiesner, Gail P. Jarvik, Donna Muzny, Richard A. Gibbs, Debra Abrams, Samuel E. Adunyah, Ladia Albertson-Junkans, Berta Almoguera, Darren C. Ames, Paul Appelbaum, Samuel Aronson, Sharon Aufox, Lawrence J. Babb, Adithya Balasubramanian, Hana Bangash, Melissa Basford, Lisa Bastarache, Samantha Baxter, Meckenzie Behr, Barbara Benoit, Elizabeth Bhoj, Suzette J. Bielinski, Sarah T. Bland, Carrie Blout, Kenneth Borthwick, Erwin P. Bottinger, Mark Bowser, Harrison Brand, Murray Brilliant, Wendy Brodeur, Pedro Caraballo, David Carrell, Andrew Carroll, Lisa Castillo, Victor Castro, Gauthami Chandanavelli, Theodore Chiang, Rex L. Chisholm, Kurt D. Christensen, Wendy Chung, Christopher G. Chute, Brittany City, Beth L. Cobb, John J. Connolly, Paul Crane, Katherine Crew, David R. Crosslin, Jyoti Dayal, Mariza De Andrade, Jessica De la Cruz, Josh C. Denny, Shawn Denson, Tim DeSmet, Ozan Dikilitas, Michael J. Dinsmore, Sheila Dodge, Phil Dunlea, Todd L. Edwards, Christine M. Eng, David Fasel, Alex Fedotov, Qiping Feng, Mark Fleharty, Andrea Foster, Robert Freimuth, Christopher Friedrich, Stephanie M. Fullerton, Birgit Funke, Stacey Gabriel, Vivian Gainer, Ali Gharavi, Andrew M. Glazer, Joseph T. Glessner, Jessica Goehringer, Adam S. Gordon, Chet Graham, Robert C. Green, Justin H. Gundelach, Heather S. Hain, Hakon Hakonarson, Maegan V. Harden, John Harley, Margaret Harr, Andrea Hartzler, M. Geoffrey Hayes, Scott Hebbring, Nora Henrikson, Andrew Hershey, Christin Hoell, Ingrid Holm, Kayla M. Howell, George Hripcsak, Jianhong Hu, Elizabeth Duffy Hynes, Joy C. Jayaseelan, Yunyun Jiang, Yoonjung Yoonie Joo, Sheethal Jose, Navya Shilpa Josyula, Anne E. Justice, Divya Kalra, Elizabeth W. Karlson, Brendan J. Keating, Melissa A. Kelly, Eimear E. Kenny, Dustin Key, Krzysztof Kiryluk, Terrie Kitchner, Barbara Klanderman, Eric Klee, David C. Kochan, Viktoriya Korchina, Leah Kottyan, Emily Kudalkar, Alanna Kulchak Rahm, Iftikhar J. Kullo, Philip Lammers, Eric B. Larson, Matthew S. Lebo, Magalie Leduc, Ming Ta (Michael) Lee, Niall J. Lennon, Kathleen A. Leppig, Nancy D. Leslie, Rongling Li, Wayne H. Liang, Chiao-Feng Lin, Jodell E. Linder, Noralane M. Lindor, Todd Lingren, James G. Linneman, Cong Liu, Wen Liu, Xiuping Liu, John Lynch, Hayley Lyon, Alyssa Macbeth, Harshad Mahadeshwar, Lisa Mahanta, Bradley Malin, Teri Manolio, Maddalena Marasa, Keith Marsolo, Michelle L. McGowan, Elizabeth McNally, Jim Meldrim, Frank Mentch, Hila Milo Rasouly, Jonathan Mosley, Shubhabrata Mukherjee, Thomas E. Mullen, Jesse Muniz, David R. Murdock, Shawn Murphy, Melanie F. Myers, Bahram Namjou, Yizhao Ni, Robert C. Onofrio, Aniwaa Owusu Obeng, Thomas N. Person, Josh F. Peterson, Lynn Petukhova, Cassandra J. Pisieczko, Siddharth Pratap, Cynthia A. Prows, Megan J. Puckelwartz, Ritika Raj, James D. Ralston, Arvind Ramaprasan, Andrea Ramirez, Luke Rasmussen, Laura Rasmussen-Torvik, Soumya Raychaudhuri, Heidi L. Rehm, Marylyn D. Ritchie, Catherine Rives, Beenish Riza, Dan M. Roden, Elisabeth A. Rosenthal, Avni Santani, Schaid Dan, Steven Scherer, Stuart Scott, Aaron Scrol, Soumitra Sengupta, Ning Shang, Himanshu Sharma, Richard R. Sharp, Rajbir Singh, Patrick M.A. Sleiman, Kara Slowik, Joshua C. Smith, Maureen E. Smith, Duane T. Smoot, Jordan W. Smoller, Sunghwan Sohn, Ian B. Stanaway, Justin Starren, Mary Stroud, Jessica Su, Casey Overby Taylor, Kasia Tolwinski, Sara L. Van Driest, Sean M. Vargas, Matthew Varugheese, David Veenstra, Eric Venner, Miguel Verbitsky, Gina Vicente, Michael Wagner, Kimberly Walker, Theresa Walunas, Liwen Wang, Qiaoyan Wang, Scott T. Weiss, Quinn S. Wells, Peter S. White, Ken L. Wiley, Janet L. Williams, Marc S. Williams, Michael W. Wilson, Leora Witkowski, Laura Allison Woods, Betty Woolf, Julia Wynn, Yaping Yang, Ge Zhang, Lan Zhang, and Hana Zouk
Subjects: Computer science, business.industry, Process (engineering), MEDLINE, High-Throughput Nucleotide Sequencing, Genomics, Data science, Article, Personalization, Variety (cybernetics), Workflow, Neptune, Pharmacogenomics, Health care, Electronic Health Records, Humans, business, Software, Genetics (clinical)
Abstract: Genomic medicine holds great promise for improving health care, but integrating searchable and actionable genetic data into electronic health records (EHRs) remains a challenge. Here we describe Neptune, a system for managing the interaction between a clinical laboratory and an EHR system during the clinical reporting process. We developed Neptune and applied it to two clinical sequencing projects that required report customization, variant reanalysis, and EHR integration. Neptune has been applied for the generation and delivery of over 15,000 clinical genomic reports. This work spans two clinical tests based on targeted gene panels that contain 68 and 153 genes respectively. These projects demanded customizable clinical reports that contained a variety of genetic data types including single-nucleotide variants (SNVs), copy-number variants (CNVs), pharmacogenomics, and polygenic risk scores. Two variant reanalysis activities were also supported, highlighting this important workflow. Methods are needed for delivering structured genetic data to EHRs. This need extends beyond developing data formats to providing infrastructure that manages the reporting process itself. Neptune was successfully applied on two high-throughput clinical sequencing projects to build and deliver clinical reports to EHR systems. The software is open source and available at https://gitlab.com/bcm-hgsc/neptune .
Published: 2021

23. Predictive Approaches for Acute Dialysis Requirement and Death in COVID-19

Author: Adam Russak, Lili Chan, Alexander W. Charney, Matthew A. Levin, Benjamin S. Glicksberg, Prem Timsina, Ishan Paranjpe, Suraj K. Jaladanki, Erwin P. Bottinger, Arash Kia, John Cijiang He, Girish N. Nadkarni, Akhil Vaid, Zahi A. Fayad, Steven G. Coca, and Kumardeep Chaudhary
Subjects: 0301 basic medicine, medicine.medical_specialty, Epidemiology, medicine.medical_treatment, 030232 urology & nephrology, Vital signs, Critical Care and Intensive Care Medicine, Logistic regression, Machine Learning, 03 medical and health sciences, 0302 clinical medicine, Renal Dialysis, Humans, Medicine, Imputation (statistics), Dialysis, Transplantation, Receiver operating characteristic, SARS-CoV-2, business.industry, COVID-19, Red blood cell distribution width, Original Articles, Acute Kidney Injury, Hospitalization, 030104 developmental biology, Nephrology, Cohort, Emergency medicine, business, Complication
Abstract: Background and objectives AKI treated with dialysis initiation is a common complication of coronavirus disease 2019 (COVID-19) among hospitalized patients. However, dialysis supplies and personnel are often limited. Design, setting, participants, & measurements Using data from adult patients hospitalized with COVID-19 from five hospitals from the Mount Sinai Health System who were admitted between March 10 and December 26, 2020, we developed and validated several models (logistic regression, Least Absolute Shrinkage and Selection Operator (LASSO), random forest, and eXtreme GradientBoosting [XGBoost; with and without imputation]) for predicting treatment with dialysis or death at various time horizons (1, 3, 5, and 7 days) after hospital admission. Patients admitted to the Mount Sinai Hospital were used for internal validation, whereas the other hospitals formed part of the external validation cohort. Features included demographics, comorbidities, and laboratory and vital signs within 12 hours of hospital admission. Results A total of 6093 patients (2442 in training and 3651 in external validation) were included in the final cohort. Of the different modeling approaches used, XGBoost without imputation had the highest area under the receiver operating characteristic (AUROC) curve on internal validation (range of 0.93–0.98) and area under the precision-recall curve (AUPRC; range of 0.78–0.82) for all time points. XGBoost without imputation also had the highest test parameters on external validation (AUROC range of 0.85–0.87, and AUPRC range of 0.27–0.54) across all time windows. XGBoost without imputation outperformed all models with higher precision and recall (mean difference in AUROC of 0.04; mean difference in AUPRC of 0.15). Features of creatinine, BUN, and red cell distribution width were major drivers of the model’s prediction. Conclusions An XGBoost model without imputation for prediction of a composite outcome of either death or dialysis in patients positive for COVID-19 had the best performance, as compared with standard and other machine learning models. Podcast This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2021_07_09_CJN17311120.mp3
Published: 2021

24. Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis.

Author: Eleanor Wheeler, Aaron Leong, Ching-Ti Liu, Marie-France Hivert, Rona J Strawbridge, Clara Podmore, Man Li, Jie Yao, Xueling Sim, Jaeyoung Hong, Audrey Y Chu, Weihua Zhang, Xu Wang, Peng Chen, Nisa M Maruthur, Bianca C Porneala, Stephen J Sharp, Yucheng Jia, Edmond K Kabagambe, Li-Ching Chang, Wei-Min Chen, Cathy E Elks, Daniel S Evans, Qiao Fan, Franco Giulianini, Min Jin Go, Jouke-Jan Hottenga, Yao Hu, Anne U Jackson, Stavroula Kanoni, Young Jin Kim, Marcus E Kleber, Claes Ladenvall, Cecile Lecoeur, Sing-Hui Lim, Yingchang Lu, Anubha Mahajan, Carola Marzi, Mike A Nalls, Pau Navarro, Ilja M Nolte, Lynda M Rose, Denis V Rybin, Serena Sanna, Yuan Shi, Daniel O Stram, Fumihiko Takeuchi, Shu Pei Tan, Peter J van der Most, Jana V Van Vliet-Ostaptchouk, Andrew Wong, Loic Yengo, Wanting Zhao, Anuj Goel, Maria Teresa Martinez Larrad, Dörte Radke, Perttu Salo, Toshiko Tanaka, Erik P A van Iperen, Goncalo Abecasis, Saima Afaq, Behrooz Z Alizadeh, Alain G Bertoni, Amelie Bonnefond, Yvonne Böttcher, Erwin P Bottinger, Harry Campbell, Olga D Carlson, Chien-Hsiun Chen, Yoon Shin Cho, W Timothy Garvey, Christian Gieger, Mark O Goodarzi, Harald Grallert, Anders Hamsten, Catharina A Hartman, Christian Herder, Chao Agnes Hsiung, Jie Huang, Michiya Igase, Masato Isono, Tomohiro Katsuya, Chiea-Chuen Khor, Wieland Kiess, Katsuhiko Kohara, Peter Kovacs, Juyoung Lee, Wen-Jane Lee, Benjamin Lehne, Huaixing Li, Jianjun Liu, Stephane Lobbens, Jian'an Luan, Valeriya Lyssenko, Thomas Meitinger, Tetsuro Miki, Iva Miljkovic, Sanghoon Moon, Antonella Mulas, Gabriele Müller, Martina Müller-Nurasyid, Ramaiah Nagaraja, Matthias Nauck, James S Pankow, Ozren Polasek, Inga Prokopenko, Paula S Ramos, Laura Rasmussen-Torvik, Wolfgang Rathmann, Stephen S Rich, Neil R Robertson, Michael Roden, Ronan Roussel, Igor Rudan, Robert A Scott, William R Scott, Bengt Sennblad, David S Siscovick, Konstantin Strauch, Liang Sun, Morris Swertz, Salman M Tajuddin, Kent D Taylor, Yik-Ying Teo, Yih Chung Tham, Anke Tönjes, Nicholas J Wareham, Gonneke Willemsen, Tom Wilsgaard, Aroon D Hingorani, EPIC-CVD Consortium, EPIC-InterAct Consortium, Lifelines Cohort Study, Josephine Egan, Luigi Ferrucci, G Kees Hovingh, Antti Jula, Mika Kivimaki, Meena Kumari, Inger Njølstad, Colin N A Palmer, Manuel Serrano Ríos, Michael Stumvoll, Hugh Watkins, Tin Aung, Matthias Blüher, Michael Boehnke, Dorret I Boomsma, Stefan R Bornstein, John C Chambers, Daniel I Chasman, Yii-Der Ida Chen, Yduan-Tsong Chen, Ching-Yu Cheng, Francesco Cucca, Eco J C de Geus, Panos Deloukas, Michele K Evans, Myriam Fornage, Yechiel Friedlander, Philippe Froguel, Leif Groop, Myron D Gross, Tamara B Harris, Caroline Hayward, Chew-Kiat Heng, Erik Ingelsson, Norihiro Kato, Bong-Jo Kim, Woon-Puay Koh, Jaspal S Kooner, Antje Körner, Diana Kuh, Johanna Kuusisto, Markku Laakso, Xu Lin, Yongmei Liu, Ruth J F Loos, Patrik K E Magnusson, Winfried März, Mark I McCarthy, Albertine J Oldehinkel, Ken K Ong, Nancy L Pedersen, Mark A Pereira, Annette Peters, Paul M Ridker, Charumathi Sabanayagam, Michele Sale, Danish Saleheen, Juha Saltevo, Peter Eh Schwarz, Wayne H H Sheu, Harold Snieder, Timothy D Spector, Yasuharu Tabara, Jaakko Tuomilehto, Rob M van Dam, James G Wilson, James F Wilson, Bruce H R Wolffenbuttel, Tien Yin Wong, Jer-Yuarn Wu, Jian-Min Yuan, Alan B Zonderman, Nicole Soranzo, Xiuqing Guo, David J Roberts, Jose C Florez, Robert Sladek, Josée Dupuis, Andrew P Morris, E-Shyong Tai, Elizabeth Selvin, Jerome I Rotter, Claudia Langenberg, Inês Barroso, and James B Meigs
Subjects: Medicine
Abstract: BackgroundGlycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes.Methods & findingsUsing genome-wide association meta-analyses in up to 159,940 individuals from 82 cohorts of European, African, East Asian, and South Asian ancestry, we identified 60 common genetic variants associated with HbA1c. We classified variants as implicated in glycemic, erythrocytic, or unclassified biology and tested whether additive genetic scores of erythrocytic variants (GS-E) or glycemic variants (GS-G) were associated with higher T2D incidence in multiethnic longitudinal cohorts (N = 33,241). Nineteen glycemic and 22 erythrocytic variants were associated with HbA1c at genome-wide significance. GS-G was associated with higher T2D risk (incidence OR = 1.05, 95% CI 1.04-1.06, per HbA1c-raising allele, p = 3 × 10-29); whereas GS-E was not (OR = 1.00, 95% CI 0.99-1.01, p = 0.60). In Europeans and Asians, erythrocytic variants in aggregate had only modest effects on the diagnostic accuracy of HbA1c. Yet, in African Americans, the X-linked G6PD G202A variant (T-allele frequency 11%) was associated with an absolute decrease in HbA1c of 0.81%-units (95% CI 0.66-0.96) per allele in hemizygous men, and 0.68%-units (95% CI 0.38-0.97) in homozygous women. The G6PD variant may cause approximately 2% (N = 0.65 million, 95% CI 0.55-0.74) of African American adults with T2D to remain undiagnosed when screened with HbA1c. Limitations include the smaller sample sizes for non-European ancestries and the inability to classify approximately one-third of the variants. Further studies in large multiethnic cohorts with HbA1c, glycemic, and erythrocytic traits are required to better determine the biological action of the unclassified variants.ConclusionsAs G6PD deficiency can be clinically silent until illness strikes, we recommend investigation of the possible benefits of screening for the G6PD genotype along with using HbA1c to diagnose T2D in populations of African ancestry or groups where G6PD deficiency is common. Screening with direct glucose measurements, or genetically-informed HbA1c diagnostic thresholds in people with G6PD deficiency, may be required to avoid missed or delayed diagnoses.
Published: 2017
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25. Genetic identification of a common collagen disease in Puerto Ricans via identity-by-descent mapping in a health system

Author: Gillian Morven Belbin, Jacqueline Odgis, Elena P Sorokin, Muh-Ching Yee, Sumita Kohli, Benjamin S Glicksberg, Christopher R Gignoux, Genevieve L Wojcik, Tielman Van Vleck, Janina M Jeff, Michael Linderman, Claudia Schurmann, Douglas Ruderfer, Xiaoqiang Cai, Amanda Merkelson, Anne E Justice, Kristin L Young, Misa Graff, Kari E North, Ulrike Peters, Regina James, Lucia Hindorff, Ruth Kornreich, Lisa Edelmann, Omri Gottesman, Eli EA Stahl, Judy H Cho, Ruth JF Loos, Erwin P Bottinger, Girish N Nadkarni, Noura S Abul-Husn, and Eimear E Kenny
Subjects: GWAS, medical genetics, population genetics, Electronic Health Records, collagen disorder, Medicine, Science, Biology (General), QH301-705.5
Abstract: Achieving confidence in the causality of a disease locus is a complex task that often requires supporting data from both statistical genetics and clinical genomics. Here we describe a combined approach to identify and characterize a genetic disorder that leverages distantly related patients in a health system and population-scale mapping. We utilize genomic data to uncover components of distant pedigrees, in the absence of recorded pedigree information, in the multi-ethnic BioMe biobank in New York City. By linking to medical records, we discover a locus associated with both elevated genetic relatedness and extreme short stature. We link the gene, COL27A1, with a little-known genetic disease, previously thought to be rare and recessive. We demonstrate that disease manifests in both heterozygotes and homozygotes, indicating a common collagen disorder impacting up to 2% of individuals of Puerto Rican ancestry, leading to a better understanding of the continuum of complex and Mendelian disease.
Published: 2017
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26. Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.

Author: Jingjing Liang, Thu H Le, Digna R Velez Edwards, Bamidele O Tayo, Kyle J Gaulton, Jennifer A Smith, Yingchang Lu, Richard A Jensen, Guanjie Chen, Lisa R Yanek, Karen Schwander, Salman M Tajuddin, Tamar Sofer, Wonji Kim, James Kayima, Colin A McKenzie, Ervin Fox, Michael A Nalls, J Hunter Young, Yan V Sun, Jacqueline M Lane, Sylvia Cechova, Jie Zhou, Hua Tang, Myriam Fornage, Solomon K Musani, Heming Wang, Juyoung Lee, Adebowale Adeyemo, Albert W Dreisbach, Terrence Forrester, Pei-Lun Chu, Anne Cappola, Michele K Evans, Alanna C Morrison, Lisa W Martin, Kerri L Wiggins, Qin Hui, Wei Zhao, Rebecca D Jackson, Erin B Ware, Jessica D Faul, Alex P Reiner, Michael Bray, Joshua C Denny, Thomas H Mosley, Walter Palmas, Xiuqing Guo, George J Papanicolaou, Alan D Penman, Joseph F Polak, Kenneth Rice, Ken D Taylor, Eric Boerwinkle, Erwin P Bottinger, Kiang Liu, Neil Risch, Steven C Hunt, Charles Kooperberg, Alan B Zonderman, Cathy C Laurie, Diane M Becker, Jianwen Cai, Ruth J F Loos, Bruce M Psaty, David R Weir, Sharon L R Kardia, Donna K Arnett, Sungho Won, Todd L Edwards, Susan Redline, Richard S Cooper, D C Rao, Jerome I Rotter, Charles Rotimi, Daniel Levy, Aravinda Chakravarti, Xiaofeng Zhu, and Nora Franceschini
Subjects: Genetics, QH426-470
Abstract: Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10-8) for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4) and multiple-trait analyses identified one novel locus (FRMD3) for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.
Published: 2017
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27. Discovery and fine-mapping of adiposity loci using high density imputation of genome-wide association studies in individuals of African ancestry: African Ancestry Anthropometry Genetics Consortium.

Author: Maggie C Y Ng, Mariaelisa Graff, Yingchang Lu, Anne E Justice, Poorva Mudgal, Ching-Ti Liu, Kristin Young, Lisa R Yanek, Mary F Feitosa, Mary K Wojczynski, Kristin Rand, Jennifer A Brody, Brian E Cade, Latchezar Dimitrov, Qing Duan, Xiuqing Guo, Leslie A Lange, Michael A Nalls, Hayrettin Okut, Salman M Tajuddin, Bamidele O Tayo, Sailaja Vedantam, Jonathan P Bradfield, Guanjie Chen, Wei-Min Chen, Alessandra Chesi, Marguerite R Irvin, Badri Padhukasahasram, Jennifer A Smith, Wei Zheng, Matthew A Allison, Christine B Ambrosone, Elisa V Bandera, Traci M Bartz, Sonja I Berndt, Leslie Bernstein, William J Blot, Erwin P Bottinger, John Carpten, Stephen J Chanock, Yii-Der Ida Chen, David V Conti, Richard S Cooper, Myriam Fornage, Barry I Freedman, Melissa Garcia, Phyllis J Goodman, Yu-Han H Hsu, Jennifer Hu, Chad D Huff, Sue A Ingles, Esther M John, Rick Kittles, Eric Klein, Jin Li, Barbara McKnight, Uma Nayak, Barbara Nemesure, Adesola Ogunniyi, Andrew Olshan, Michael F Press, Rebecca Rohde, Benjamin A Rybicki, Babatunde Salako, Maureen Sanderson, Yaming Shao, David S Siscovick, Janet L Stanford, Victoria L Stevens, Alex Stram, Sara S Strom, Dhananjay Vaidya, John S Witte, Jie Yao, Xiaofeng Zhu, Regina G Ziegler, Alan B Zonderman, Adebowale Adeyemo, Stefan Ambs, Mary Cushman, Jessica D Faul, Hakon Hakonarson, Albert M Levin, Katherine L Nathanson, Erin B Ware, David R Weir, Wei Zhao, Degui Zhi, Bone Mineral Density in Childhood Study (BMDCS) Group, Donna K Arnett, Struan F A Grant, Sharon L R Kardia, Olufunmilayo I Oloapde, D C Rao, Charles N Rotimi, Michele M Sale, L Keoki Williams, Babette S Zemel, Diane M Becker, Ingrid B Borecki, Michele K Evans, Tamara B Harris, Joel N Hirschhorn, Yun Li, Sanjay R Patel, Bruce M Psaty, Jerome I Rotter, James G Wilson, Donald W Bowden, L Adrienne Cupples, Christopher A Haiman, Ruth J F Loos, and Kari E North
Subjects: Genetics, QH426-470
Abstract: Genome-wide association studies (GWAS) have identified >300 loci associated with measures of adiposity including body mass index (BMI) and waist-to-hip ratio (adjusted for BMI, WHRadjBMI), but few have been identified through screening of the African ancestry genomes. We performed large scale meta-analyses and replications in up to 52,895 individuals for BMI and up to 23,095 individuals for WHRadjBMI from the African Ancestry Anthropometry Genetics Consortium (AAAGC) using 1000 Genomes phase 1 imputed GWAS to improve coverage of both common and low frequency variants in the low linkage disequilibrium African ancestry genomes. In the sex-combined analyses, we identified one novel locus (TCF7L2/HABP2) for WHRadjBMI and eight previously established loci at P < 5×10-8: seven for BMI, and one for WHRadjBMI in African ancestry individuals. An additional novel locus (SPRYD7/DLEU2) was identified for WHRadjBMI when combined with European GWAS. In the sex-stratified analyses, we identified three novel loci for BMI (INTS10/LPL and MLC1 in men, IRX4/IRX2 in women) and four for WHRadjBMI (SSX2IP, CASC8, PDE3B and ZDHHC1/HSD11B2 in women) in individuals of African ancestry or both African and European ancestry. For four of the novel variants, the minor allele frequency was low (
Published: 2017
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28. Prescriber Adoption of SLCO1B1 Genotype-Guided Simvastatin Clinical Decision Support in a Clinical Pharmacogenetics Program

Author: Aniwaa Owusu Obeng, Stuart A. Scott, Tom Kaszemacher, Stephen B. Ellis, Ana Mejia, Alanna Gomez, Rajiv Nadukuru, Noura S. Abul‐Husn, Aida Vega, Eva Waite, Omri Gottesman, Judy Cho, and Erwin P. Bottinger
Subjects: Pharmacology, Pharmacology (medical)
Abstract: Pharmacogenetic implementation programs are increasingly feasible due to the availability of clinical guidelines for implementation research. The utilization of these resources has been reported with selected drug-gene pairs; however, little is known about how prescribers respond to pharmacogenetic recommendations for statin therapy. We prospectively assessed prescriber interaction with point-of-care clinical decision support (CDS) to guide simvastatin therapy for a diverse cohort of primary care patients enrolled in a clinical pharmacogenetics program. Of the 1,639 preemptively genotyped patients, 298 (18.2%) had an intermediate function (IF) OATP1B1 phenotype and 25 (1.53%) had a poor function (PF) phenotype, predicted by a common single nucleotide variant in the SLCO1B1 gene (c.521TC; rs4149056). Clinicians were presented with CDS when simvastatin was prescribed for patients with IF or PF through the electronic health record. Importantly, 64.2% of the CDS deployed at the point-of-care was accepted by the prescribers and resulted in prescription changes. Statin intensity was found to significantly influence prescriber adoption of the pharmacogenetic-guided CDS, whereas patient gender or race, prescriber type, or pharmacogenetic training status did not significantly influence adoption. This study demonstrates that primary care providers readily adopt pharmacogenetic information to guide statin therapy for the majority of patients with preemptive genotype data.
Published: 2022

29. Quantifying the phenome-wide disease burden of obesity using electronic health records and genomics

Author: Jamie R. Robinson, Robert J. Carroll, Lisa Bastarache, Qingxia Chen, James Pirruccello, Zongyang Mou, Wei‐Qi Wei, John Connolly, Frank Mentch, Paul K. Crane, Scott J. Hebbring, David R. Crosslin, Adam S. Gordon, Elisabeth A. Rosenthal, Ian B. Stanaway, M. Geoffrey Hayes, Wei Wei, Lynn Petukhova, Bahram Namjou‐Khales, Ge Zhang, Mayya S. Safarova, Nephi A. Walton, Christopher Still, Erwin P. Bottinger, Ruth J. F. Loos, Shawn N. Murphy, Gretchen P. Jackson, Naji Abumrad, Iftikhar J. Kullo, Gail P. Jarvik, Eric B. Larson, Chunhua Weng, Dan Roden, Amit V. Khera, and Joshua C. Denny
Subjects: Nutrition and Dietetics, Endocrinology, Diabetes and Metabolism, Medicine (miscellaneous), Genomics, Polymorphism, Single Nucleotide, Endocrinology, Phenotype, Diabetes Mellitus, Type 2, Cost of Illness, Humans, Electronic Health Records, Genetic Predisposition to Disease, Obesity, Phenomics, Genome-Wide Association Study
Abstract: High BMI is associated with many comorbidities and mortality. This study aimed to elucidate the overall clinical risk of obesity using a genome- and phenome-wide approach.This study performed a phenome-wide association study of BMI using a clinical cohort of 736,726 adults. This was followed by genetic association studies using two separate cohorts: one consisting of 65,174 adults in the Electronic Medical Records and Genomics (eMERGE) Network and another with 405,432 participants in the UK Biobank.Class 3 obesity was associated with 433 phenotypes, representing 59.3% of all billing codes in individuals with severe obesity. A genome-wide polygenic risk score for BMI, accounting for 7.5% of variance in BMI, was associated with 296 clinical diseases, including strong associations with type 2 diabetes, sleep apnea, hypertension, and chronic liver disease. In all three cohorts, 199 phenotypes were associated with class 3 obesity and polygenic risk for obesity, including novel associations such as increased risk of renal failure, venous insufficiency, and gastroesophageal reflux.This combined genomic and phenomic systematic approach demonstrated that obesity has a strong genetic predisposition and is associated with a considerable burden of disease across all disease classes.
Published: 2022

30. Disease progression subtype discovery from longitudinal EMR data with a majority of missing values and unknown initial time points.

Author: Ilkka Huopaniemi, Girish N. Nadkarni, Rajiv Nadukuru, Vaneet Lotay, Stephen B. Ellis, Omri Gottesman, and Erwin P. Bottinger
Published: 2014

31. Development and validation of an electronic phenotyping algorithm for chronic kidney disease.

Author: Girish N. Nadkarni, Omri Gottesman, James G. Linneman, Herbert S. Chase, Richard L. Berg, Samira Farouk, Vaneet Lotay, Stephen B. Ellis, George Hripcsak, Peggy L. Peissig, Chunhua Weng, Rajiv Nadukuru, and Erwin P. Bottinger
Published: 2014

32. Evaluation of a machine learning approach utilizing wearable data for prediction of SARS-CoV-2 infection in healthcare workers

Author: Robert P Hirten, Lewis Tomalin, Matteo Danieletto, Eddye Golden, Micol Zweig, Sparshdeep Kaur, Drew Helmus, Anthony Biello, Renata Pyzik, Erwin P Bottinger, Laurie Keefer, Dennis Charney, Girish N Nadkarni, Mayte Suarez-Farinas, and Zahi A Fayad
Subjects: Health Informatics
Abstract: Objective To determine whether a machine learning model can detect SARS-CoV-2 infection from physiological metrics collected from wearable devices. Materials and Methods Health care workers from 7 hospitals were enrolled and prospectively followed in a multicenter observational study. Subjects downloaded a custom smart phone app and wore Apple Watches for the duration of the study period. Daily surveys related to symptoms and the diagnosis of Coronavirus Disease 2019 were answered in the app. Results We enrolled 407 participants with 49 (12%) having a positive nasal SARS-CoV-2 polymerase chain reaction test during follow-up. We examined 5 machine-learning approaches and found that gradient-boosting machines (GBM) had the most favorable validation performance. Across all testing sets, our GBM model predicted SARS-CoV-2 infection with an average area under the receiver operating characteristic (auROC) = 86.4% (confidence interval [CI] 84–89%). The model was calibrated to value sensitivity over specificity, achieving an average sensitivity of 82% (CI ±∼4%) and specificity of 77% (CI ±∼1%). The most important predictors included parameters describing the circadian heart rate variability mean (MESOR) and peak-timing (acrophase), and age. Discussion We show that a tree-based ML algorithm applied to physiological metrics passively collected from a wearable device can identify and predict SARS-CoV-2 infection. Conclusion Applying machine learning models to the passively collected physiological metrics from wearable devices may improve SARS-CoV-2 screening methods and infection tracking.
Published: 2022

33. Effects of Testing and Disclosing Ancestry-Specific Genetic Risk for Kidney Failure on Patients and Health Care Professionals: A Randomized Clinical Trial

Author: Girish N. Nadkarni, Kezhen Fei, Michelle A. Ramos, Diane Hauser, Emilia Bagiella, Stephen B. Ellis, Saskia Sanderson, Stuart A. Scott, Tatiana Sabin, Ebony Madden, Richard Cooper, Martin Pollak, Neil Calman, Erwin P. Bottinger, and Carol R. Horowitz
Subjects: Adult, Male, Health Personnel, General Medicine, Disclosure, Middle Aged, Apolipoprotein L1, Black or African American, Hypertension, Humans, Female, Genetic Predisposition to Disease, Genetic Testing, Renal Insufficiency, Chronic
Abstract: Risk variants in the apolipoprotein L1 (APOL1 [OMIM 603743]) gene on chromosome 22 are common in individuals of West African ancestry and confer increased risk of kidney failure for people with African ancestry and hypertension. Whether disclosing APOL1 genetic testing results to patients of African ancestry and their clinicians affects blood pressure, kidney disease screening, or patient behaviors is unknown.To determine the effects of testing and disclosing APOL1 genetic results to patients of African ancestry with hypertension and their clinicians.This pragmatic randomized clinical trial randomly assigned 2050 adults of African ancestry with hypertension and without existing chronic kidney disease in 2 US health care systems from November 1, 2014, through November 28, 2016; the final date of follow-up was January 16, 2018. Patients were randomly assigned to undergo immediate (intervention) or delayed (waiting list control group) APOL1 testing in a 7:1 ratio. Statistical analysis was performed from May 1, 2018, to July 31, 2020.Patients randomly assigned to the intervention group received APOL1 genetic testing results from trained staff; their clinicians received results through clinical decision support in electronic health records. Waiting list control patients received the results after their 12-month follow-up visit.Coprimary outcomes were the change in 3-month systolic blood pressure and 12-month urine kidney disease screening comparing intervention patients with high-risk APOL1 genotypes and those with low-risk APOL1 genotypes. Secondary outcomes compared these outcomes between intervention group patients with high-risk APOL1 genotypes and controls. Exploratory analyses included psychobehavioral factors.Among 2050 randomly assigned patients (1360 women [66%]; mean [SD] age, 53 [10] years), the baseline mean (SD) systolic blood pressure was significantly higher in patients with high-risk APOL1 genotypes vs those with low-risk APOL1 genotypes and controls (137 [21] vs 134 [19] vs 133 [19] mm Hg; P = .003 for high-risk vs low-risk APOL1 genotypes; P = .001 for high-risk APOL1 genotypes vs controls). At 3 months, the mean (SD) change in systolic blood pressure was significantly greater in patients with high-risk APOL1 genotypes vs those with low-risk APOL1 genotypes (6 [18] vs 3 [18] mm Hg; P = .004) and controls (6 [18] vs 3 [19] mm Hg; P = .01). At 12 months, there was a 12% increase in urine kidney disease testing among patients with high-risk APOL1 genotypes (from 39 of 234 [17%] to 68 of 234 [29%]) vs a 6% increase among those with low-risk APOL1 genotypes (from 278 of 1561 [18%] to 377 of 1561 [24%]; P = .10) and a 7% increase among controls (from 33 of 255 [13%] to 50 of 255 [20%]; P = .01). In response to testing, patients with high-risk APOL1 genotypes reported more changes in lifestyle (a subjective measure that included better dietary and exercise habits; 129 of 218 [59%] vs 547 of 1468 [37%]; P .001) and increased blood pressure medication use (21 of 218 [10%] vs 68 of 1468 [5%]; P = .005) vs those with low-risk APOL1 genotypes; 1631 of 1686 (97%) declared they would get tested again.In this randomized clinical trial, disclosing APOL1 genetic testing results to patients of African ancestry with hypertension and their clinicians was associated with a greater reduction in systolic blood pressure, increased kidney disease screening, and positive self-reported behavior changes in those with high-risk genotypes.ClinicalTrials.gov Identifier: NCT02234063.
Published: 2022

34. Type 2 Diabetes Partitioned Polygenic Scores Associate With Disease Outcomes in 454,193 Individuals Across 13 Cohorts

Author: Daniel DiCorpo, Jessica LeClair, Joanne B. Cole, Chloé Sarnowski, Fariba Ahmadizar, Lawrence F. Bielak, Anneke Blokstra, Erwin P. Bottinger, Layal Chaker, Yii-Der I. Chen, Ye Chen, Paul S. de Vries, Tariq Faquih, Mohsen Ghanbari, Valborg Gudmundsdottir, Xiuqing Guo, Natalie R. Hasbani, Dorina Ibi, M. Arfan Ikram, Maryam Kavousi, Hampton L. Leonard, Aaron Leong, Josep M. Mercader, Alanna C. Morrison, Girish N. Nadkarni, Mike A. Nalls, Raymond Noordam, Michael Preuss, Jennifer A. Smith, Stella Trompet, Petra Vissink, Jie Yao, Wei Zhao, Eric Boerwinkle, Mark O. Goodarzi, Vilmundur Gudnason, J. Wouter Jukema, Sharon L.R. Kardia, Ruth J.F. Loos, Ching-Ti Liu, Alisa K. Manning, Dennis Mook-Kanamori, James S. Pankow, H. Susan J. Picavet, Naveed Sattar, Eleanor M. Simonsick, W.M. Monique Verschuren, Ko Willems van Dijk, Jose C. Florez, Jerome I. Rotter, James B. Meigs, Josée Dupuis, Miriam S. Udler, Epidemiology, and Internal Medicine
Subjects: Endocrinology, Diabetes and Metabolism, Cardiovascular, Medical and Health Sciences, Endocrinology & Metabolism, SDG 3 - Good Health and Well-being, Internal Medicine, Diabetes Mellitus, Genetics, Humans, 2.1 Biological and endogenous factors, Obesity, Aetiology, Alleles, Heart Disease - Coronary Heart Disease, Metabolic and endocrine, Nutrition, Advanced and Specialized Nursing, Liver Disease, Prevention, Diabetes, Cross-Sectional Studies, Heart Disease, Good Health and Well Being, Diabetes Mellitus, Type 2, Pharmaceutical Preparations, Genetic Loci, Digestive Diseases, Type 2
Abstract: OBJECTIVE Type 2 diabetes (T2D) has heterogeneous patient clinical characteristics and outcomes. In previous work, we investigated the genetic basis of this heterogeneity by clustering 94 T2D genetic loci using their associations with 47 diabetes-related traits and identified five clusters, termed β-cell, proinsulin, obesity, lipodystrophy, and liver/lipid. The relationship between these clusters and individual-level metabolic disease outcomes has not been assessed. RESEARCH DESIGN AND METHODS Here we constructed individual-level partitioned polygenic scores (pPS) for these five clusters in 12 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (n = 454,193) and tested for cross-sectional association with T2D-related outcomes, including blood pressure, renal function, insulin use, age at T2D diagnosis, and coronary artery disease (CAD). RESULTS Despite all clusters containing T2D risk-increasing alleles, they had differential associations with metabolic outcomes. Increased obesity and lipodystrophy cluster pPS, which had opposite directions of association with measures of adiposity, were both significantly associated with increased blood pressure and hypertension. The lipodystrophy and liver/lipid cluster pPS were each associated with CAD, with increasing and decreasing effects, respectively. An increased liver/lipid cluster pPS was also significantly associated with reduced renal function. The liver/lipid cluster includes known loci linked to liver lipid metabolism (e.g., GCKR, PNPLA3, and TM6SF2), and these findings suggest that cardiovascular disease risk and renal function may be impacted by these loci through their shared disease pathway. CONCLUSIONS Our findings support that genetically driven pathways leading to T2D also predispose differentially to clinical outcomes.
Published: 2022

35. Correction: The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

Author: Thomas W Winkler, Anne E Justice, Mariaelisa Graff, Llilda Barata, Mary F Feitosa, Su Chu, Jacek Czajkowski, Tõnu Esko, Tove Fall, Tuomas O Kilpeläinen, Yingchang Lu, Reedik Mägi, Evelin Mihailov, Tune H Pers, Sina Rüeger, Alexander Teumer, Georg B Ehret, Teresa Ferreira, Nancy L Heard-Costa, Juha Karjalainen, Vasiliki Lagou, Anubha Mahajan, Michael D Neinast, Inga Prokopenko, Jeannette Simino, Tanya M Teslovich, Rick Jansen, Harm-Jan Westra, Charles C White, Devin Absher, Tarunveer S Ahluwalia, Shafqat Ahmad, Eva Albrecht, Alexessander Couto Alves, Jennifer L Bragg-Gresham, Anton J M de Craen, Joshua C Bis, Amélie Bonnefond, Gabrielle Boucher, Gemma Cadby, Yu-Ching Cheng, Charleston W K Chiang, Graciela Delgado, Ayse Demirkan, Nicole Dueker, Niina Eklund, Gudny Eiriksdottir, Joel Eriksson, Bjarke Feenstra, Krista Fischer, Francesca Frau, Tessel E Galesloot, Frank Geller, Anuj Goel, Mathias Gorski, Tanja B Grammer, Stefan Gustafsson, Saskia Haitjema, Jouke-Jan Hottenga, Jennifer E Huffman, Anne U Jackson, Kevin B Jacobs, Åsa Johansson, Marika Kaakinen, Marcus E Kleber, Jari Lahti, Irene Mateo Leach, Benjamin Lehne, Youfang Liu, Ken Sin Lo, Mattias Lorentzon, Jian'an Luan, Pamela A F Madden, Massimo Mangino, Barbara McKnight, Carolina Medina-Gomez, Keri L Monda, May E Montasser, Gabriele Müller, Martina Müller-Nurasyid, Ilja M Nolte, Kalliope Panoutsopoulou, Laura Pascoe, Lavinia Paternoster, Nigel W Rayner, Frida Renström, Federica Rizzi, Lynda M Rose, Kathy A Ryan, Perttu Salo, Serena Sanna, Hubert Scharnagl, Jianxin Shi, Albert Vernon Smith, Lorraine Southam, Alena Stančáková, Valgerdur Steinthorsdottir, Rona J Strawbridge, Yun Ju Sung, Ioanna Tachmazidou, Toshiko Tanaka, Gudmar Thorleifsson, Stella Trompet, Natalia Pervjakova, Jonathan P Tyrer, Liesbeth Vandenput, Sander W van der Laan, Nathalie van der Velde, Jessica van Setten, Jana V van Vliet-Ostaptchouk, Niek Verweij, Efthymia Vlachopoulou, Lindsay L Waite, Sophie R Wang, Zhaoming Wang, Sarah H Wild, Christina Willenborg, James F Wilson, Andrew Wong, Jian Yang, Loïc Yengo, Laura M Yerges-Armstrong, Lei Yu, Weihua Zhang, Jing Hua Zhao, Ehm A Andersson, Stephan J L Bakker, Damiano Baldassarre, Karina Banasik, Matteo Barcella, Cristina Barlassina, Claire Bellis, Paola Benaglio, John Blangero, Matthias Blüher, Fabrice Bonnet, Lori L Bonnycastle, Heather A Boyd, Marcel Bruinenberg, Aron S Buchman, Harry Campbell, Yii-Der Ida Chen, Peter S Chines, Simone Claudi-Boehm, John Cole, Francis S Collins, Eco J C de Geus, Lisette C P G M de Groot, Maria Dimitriou, Jubao Duan, Stefan Enroth, Elodie Eury, Aliki-Eleni Farmaki, Nita G Forouhi, Nele Friedrich, Pablo V Gejman, Bruna Gigante, Nicola Glorioso, Alan S Go, Omri Gottesman, Jürgen Gräßler, Harald Grallert, Niels Grarup, Yu-Mei Gu, Linda Broer, Annelies C Ham, Torben Hansen, Tamara B Harris, Catharina A Hartman, Maija Hassinen, Nicholas Hastie, Andrew T Hattersley, Andrew C Heath, Anjali K Henders, Dena Hernandez, Hans Hillege, Oddgeir Holmen, Kees G Hovingh, Jennie Hui, Lise L Husemoen, Nina Hutri-Kähönen, Pirro G Hysi, Thomas Illig, Philip L De Jager, Shapour Jalilzadeh, Torben Jørgensen, J Wouter Jukema, Markus Juonala, Stavroula Kanoni, Maria Karaleftheri, Kay Tee Khaw, Leena Kinnunen, Steven J Kittner, Wolfgang Koenig, Ivana Kolcic, Peter Kovacs, Nikolaj T Krarup, Wolfgang Kratzer, Janine Krüger, Diana Kuh, Meena Kumari, Theodosios Kyriakou, Claudia Langenberg, Lars Lannfelt, Chiara Lanzani, Vaneet Lotay, Lenore J Launer, Karin Leander, Jaana Lindström, Allan Linneberg, Yan-Ping Liu, Stéphane Lobbens, Robert Luben, Valeriya Lyssenko, Satu Männistö, Patrik K Magnusson, Wendy L McArdle, Cristina Menni, Sigrun Merger, Lili Milani, Grant W Montgomery, Andrew P Morris, Narisu Narisu, Mari Nelis, Ken K Ong, Aarno Palotie, Louis Pérusse, Irene Pichler, Maria G Pilia, Anneli Pouta, Myriam Rheinberger, Rasmus Ribel-Madsen, Marcus Richards, Kenneth M Rice, Treva K Rice, Carlo Rivolta, Veikko Salomaa, Alan R Sanders, Mark A Sarzynski, Salome Scholtens, Robert A Scott, William R Scott, Sylvain Sebert, Sebanti Sengupta, Bengt Sennblad, Thomas Seufferlein, Angela Silveira, P Eline Slagboom, Jan H Smit, Thomas H Sparsø, Kathleen Stirrups, Ronald P Stolk, Heather M Stringham, Morris A Swertz, Amy J Swift, Ann-Christine Syvänen, Sian-Tsung Tan, Barbara Thorand, Anke Tönjes, Angelo Tremblay, Emmanouil Tsafantakis, Peter J van der Most, Uwe Völker, Marie-Claude Vohl, Judith M Vonk, Melanie Waldenberger, Ryan W Walker, Roman Wennauer, Elisabeth Widén, Gonneke Willemsen, Tom Wilsgaard, Alan F Wright, M Carola Zillikens, Suzanne C van Dijk, Natasja M van Schoor, Folkert W Asselbergs, Paul I W de Bakker, Jacques S Beckmann, John Beilby, David A Bennett, Richard N Bergman, Sven Bergmann, Carsten A Böger, Bernhard O Boehm, Eric Boerwinkle, Dorret I Boomsma, Stefan R Bornstein, Erwin P Bottinger, Claude Bouchard, John C Chambers, Stephen J Chanock, Daniel I Chasman, Francesco Cucca, Daniele Cusi, George Dedoussis, Jeanette Erdmann, Johan G Eriksson, Denis A Evans, Ulf de Faire, Martin Farrall, Luigi Ferrucci, Ian Ford, Lude Franke, Paul W Franks, Philippe Froguel, Ron T Gansevoort, Christian Gieger, Henrik Grönberg, Vilmundur Gudnason, Ulf Gyllensten, Per Hall, Anders Hamsten, Pim van der Harst, Caroline Hayward, Markku Heliövaara, Christian Hengstenberg, Andrew A Hicks, Aroon Hingorani, Albert Hofman, Frank Hu, Heikki V Huikuri, Kristian Hveem, Alan L James, Joanne M Jordan, Antti Jula, Mika Kähönen, Eero Kajantie, Sekar Kathiresan, Lambertus A L M Kiemeney, Mika Kivimaki, Paul B Knekt, Heikki A Koistinen, Jaspal S Kooner, Seppo Koskinen, Johanna Kuusisto, Winfried Maerz, Nicholas G Martin, Markku Laakso, Timo A Lakka, Terho Lehtimäki, Guillaume Lettre, Douglas F Levinson, Lars Lind, Marja-Liisa Lokki, Pekka Mäntyselkä, Mads Melbye, Andres Metspalu, Braxton D Mitchell, Frans L Moll, Jeffrey C Murray, Arthur W Musk, Markku S Nieminen, Inger Njølstad, Claes Ohlsson, Albertine J Oldehinkel, Ben A Oostra, Lyle J Palmer, James S Pankow, Gerard Pasterkamp, Nancy L Pedersen, Oluf Pedersen, Brenda W Penninx, Markus Perola, Annette Peters, Ozren Polašek, Peter P Pramstaller, Bruce M Psaty, Lu Qi, Thomas Quertermous, Olli T Raitakari, Tuomo Rankinen, Rainer Rauramaa, Paul M Ridker, John D Rioux, Fernando Rivadeneira, Jerome I Rotter, Igor Rudan, Hester M den Ruijter, Juha Saltevo, Naveed Sattar, Heribert Schunkert, Peter E H Schwarz, Alan R Shuldiner, Juha Sinisalo, Harold Snieder, Thorkild I A Sørensen, Tim D Spector, Jan A Staessen, Bandinelli Stefania, Unnur Thorsteinsdottir, Michael Stumvoll, Jean-Claude Tardif, Elena Tremoli, Jaakko Tuomilehto, André G Uitterlinden, Matti Uusitupa, André L M Verbeek, Sita H Vermeulen, Jorma S Viikari, Veronique Vitart, Henry Völzke, Peter Vollenweider, Gérard Waeber, Mark Walker, Henri Wallaschofski, Nicholas J Wareham, Hugh Watkins, Eleftheria Zeggini, arcOGEN Consortium, CHARGE Consortium, DIAGRAM Consortium, GLGC Consortium, Global-BPGen Consortium, ICBP Consortium, MAGIC Consortium, Aravinda Chakravarti, Deborah J Clegg, L Adrienne Cupples, Penny Gordon-Larsen, Cashell E Jaquish, D C Rao, Goncalo R Abecasis, Themistocles L Assimes, Inês Barroso, Sonja I Berndt, Michael Boehnke, Panos Deloukas, Caroline S Fox, Leif C Groop, David J Hunter, Erik Ingelsson, Robert C Kaplan, Mark I McCarthy, Karen L Mohlke, Jeffrey R O'Connell, David Schlessinger, David P Strachan, Kari Stefansson, Cornelia M van Duijn, Joel N Hirschhorn, Cecilia M Lindgren, Iris M Heid, Kari E North, Ingrid B Borecki, Zoltán Kutalik, and Ruth J F Loos
Subjects: Genetics, QH426-470
Abstract: [This corrects the article DOI: 10.1371/journal.pgen.1005378.].
Published: 2016
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36. Variant Discovery and Fine Mapping of Genetic Loci Associated with Blood Pressure Traits in Hispanics and African Americans.

Author: Nora Franceschini, Cara L Carty, Yingchang Lu, Ran Tao, Yun Ju Sung, Ani Manichaikul, Jeff Haessler, Myriam Fornage, Karen Schwander, Niha Zubair, Stephanie Bien, Lucia A Hindorff, Xiuqing Guo, Suzette J Bielinski, Georg Ehret, Joel D Kaufman, Stephen S Rich, Christopher S Carlson, Erwin P Bottinger, Kari E North, D C Rao, Aravinda Chakravarti, Paula Q Barrett, Ruth J F Loos, Steven Buyske, and Charles Kooperberg
Subjects: Medicine, Science
Abstract: Despite the substantial burden of hypertension in US minority populations, few genetic studies of blood pressure have been conducted in Hispanics and African Americans, and it is unclear whether many of the established loci identified in European-descent populations contribute to blood pressure variation in non-European descent populations. Using the Metabochip array, we sought to characterize the genetic architecture of previously identified blood pressure loci, and identify novel cardiometabolic variants related to systolic and diastolic blood pressure in a multi-ethnic US population including Hispanics (n = 19,706) and African Americans (n = 18,744). Several known blood pressure loci replicated in African Americans and Hispanics. Fourteen variants in three loci (KCNK3, FGF5, ATXN2-SH2B3) were significantly associated with blood pressure in Hispanics. The most significant diastolic blood pressure variant identified in our analysis, rs2586886/KCNK3 (P = 5.2 x 10-9), also replicated in independent Hispanic and European-descent samples. African American and trans-ethnic meta-analysis data identified novel variants in the FGF5, ULK4 and HOXA-EVX1 loci, which have not been previously associated with blood pressure traits. Our identification and independent replication of variants in KCNK3, a gene implicated in primary hyperaldosteronism, as well as a variant in HOTTIP (HOXA-EVX1) suggest that further work to clarify the roles of these genes may be warranted. Overall, our findings suggest that loci identified in European descent populations also contribute to blood pressure variation in diverse populations including Hispanics and African Americans-populations that are understudied for hypertension genetic risk factors.
Published: 2016
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37. Rapid response to the alpha-1 adrenergic agent phenylephrine in the perioperative period is impacted by genomics and ancestry

Author: Muh-Ching Yee, Aniwaa Owusu Obeng, Eimear E. Kenny, Omri Gottesman, Stephen B. Ellis, Matthew A. Levin, Stephane Wenric, Erwin P. Bottinger, Thomas T. Joseph, Janina M. Jeff, and Gillian M. Belbin
Subjects: 0301 basic medicine, Male, Genome-wide association study, Blood Pressure, Bioinformatics, Phenylephrine, 0302 clinical medicine, Medicine, 10. No inequality, 0303 health sciences, education.field_of_study, Genomics, Middle Aged, Phenotype, 3. Good health, Cohort, Cardiology, Molecular Medicine, Female, medicine.drug, Agonist, medicine.medical_specialty, Mean arterial pressure, medicine.drug_class, Population, Diastole, Alpha (ethology), Therapeutics, Polymorphism, Single Nucleotide, Article, White People, 03 medical and health sciences, Adrenergic Agents, Internal medicine, Genetics, Humans, education, Perioperative Period, 030304 developmental biology, Genetic association, Genetic association study, Pharmacology, business.industry, Perioperative, Translational research, Personalized medicine, Black or African American, 030104 developmental biology, Blood pressure, Pharmacogenomics, business, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: BackgroundThe emergence of genomic data in biobanks and health systems offers new ways to derive medically important phenotypes, including acute phenotypes that occur during in-patient clinical care. We hypothesized that there is a genetic underpinning to the magnitude of the response to phenylephrine, an α1-adrenergic receptor agonist commonly used to treat hypotension during anesthesia and surgery.MethodsWe quantified the response to phenylephrine by determining the delta between the minimum blood pressure (BP) within five minutes before and the maximum BP within five minutes after bolus administration. We then performed a genome-wide association study (GWAS) adjusted for genetic ancestry, demographics, and relevant clinical covariates to investigate genetic factors underlying individual differences systolic BP response to phenylephrine (ΔSBP), as well as mean arterial pressure (ΔMAP) and diastolic BP (ΔDBP), for both the entire study cohort as well as for each of 3 ancestry sub-cohorts; European American(EA), African American(AA), and Hispanic American(HA).Results4,317 patients met inclusion criteria, of which 3,699 were genotyped. Average ΔBP values over the entire cohort were ΔSBP=17(+-25) mmHg, ΔMAP=14(+-18) mmHg, ΔDBP=11(+-14) mmHg. The largest difference between populations was observed for ΔSBP (ΔSBPEA=20(+-24) mmHg; ΔSBPHA=16(+-25) mmHg; ΔSBPAA=15(+-25) mmHg). The differences remained after adjusting for clinical covariates and ancestry (EA vs. HA: ΔSBP, p-5;ΔMAP,p-4;ΔDBP,p-4). GWAS revealed significant associations between loci and BP response in 5 different genome regions (p-8) in the entire cohort, and suggestive associations in 2 different regions in EAs (p-8,p-8). We observed non-random enrichment in association with SBP drug response in 165 loci previously reported to be associated with systolic blood pressure. Finally, we discovered rare variants, rs188427942 and rs147664194 present at ∼1% in EAs and rs146535276 present at ∼1% in AAs respectively, where patients carrying one copy of these variants show no response to phenylephrine.ConclusionsIt is possible to derive a quantitative phenotype suited for comparative statistics and genome-wide association studies from routinely collected perioperative data. There are population differences in rapid response to phenylephrine, large effect alleles and novel genes affecting pharmaceutical response, and phenylephrine non-responders, with implications for personalized treatment during surgery.
Published: 2020

38. Outcomes of Patients on Maintenance Dialysis Hospitalized with COVID-19

Author: Benjamin S. Glicksberg, Matthew A. Levin, Lewis Kaufman, Steven G. Coca, Shan Zhao, Erwin P. Bottinger, Staci Leisman, Shuchita Sharma, Girish N. Nadkarni, Zahi A. Fayad, Lili Chan, Ishan Paranjpe, Sulaiman Somani, John Cijiang He, Arvind Kumar, Suraj K. Jaladanki, Alexander W. Charney, and Barbara Murphy
Subjects: Male, 2019-20 coronavirus outbreak, medicine.medical_specialty, Critical Care, Coronavirus disease 2019 (COVID-19), Epidemiology, viruses, medicine.medical_treatment, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 030232 urology & nephrology, Comorbidity, 030204 cardiovascular system & hematology, Critical Care and Intensive Care Medicine, Risk Assessment, 03 medical and health sciences, 0302 clinical medicine, Renal Dialysis, Risk Factors, Internal medicine, Humans, Medicine, Hospital Mortality, Renal Insufficiency, skin and connective tissue diseases, Dialysis, Aged, Retrospective Studies, Transplantation, Kidney, business.industry, fungi, COVID-19, virus diseases, Retrospective cohort study, Middle Aged, medicine.disease, Respiration, Artificial, Research Letters, Hospitalization, body regions, Treatment Outcome, medicine.anatomical_structure, Nephrology, Female, New York City, business, Risk assessment
Abstract: Coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had devastating effects worldwide. Patients with kidney failure on dialysis may have a higher risk of worse outcomes. Reports from China found that these patients with SARS-CoV-2 had fewer
Published: 2020

39. Utilization of Deep Learning for Subphenotype Identification in Sepsis-Associated Acute Kidney Injury

Author: Akhil Vaid, Benjamin S. Glicksberg, Kumardeep Chaudhary, Lili Chan, Avantee Gokhale, Erwin P. Bottinger, Ross O'Hagan, Steven G. Coca, Kipp W. Johnson, Richard S. Cooper, Ishan Paranjpe, Girish N. Nadkarni, Kinsuk Chauhan, Manish Paranjpe, Aine Duffy, Tielman Van Vleck, Pattharawin Pattharanitima, and Suraj K. Jaladanki
Subjects: Male, Databases, Factual, Epidemiology, medicine.medical_treatment, 030232 urology & nephrology, Comorbidity, Critical Care and Intensive Care Medicine, Blood Urea Nitrogen, law.invention, Leukocyte Count, 0302 clinical medicine, law, Electronic Health Records, Medicine, Simplified Acute Physiology Score, Liver Diseases, Acute kidney injury, Alanine Transaminase, Acute Kidney Injury, Middle Aged, Prognosis, Intensive care unit, Phenotype, Nephrology, Creatinine, Female, medicine.medical_specialty, Vital signs, Glutamyl Aminopeptidase, 03 medical and health sciences, Deep Learning, Renal Dialysis, Sepsis, Intensive care, Internal medicine, Humans, Lactic Acid, Dialysis, Aged, Transplantation, L-Lactate Dehydrogenase, business.industry, Editorials, Bilirubin, 030208 emergency & critical care medicine, Odds ratio, medicine.disease, United States, Confidence interval, business
Abstract: Background and objectives Sepsis-associated AKI is a heterogeneous clinical entity. We aimed to agnostically identify sepsis-associated AKI subphenotypes using deep learning on routinely collected data in electronic health records. Design, setting, participants, & measurements We used the Medical Information Mart for Intensive Care III database, which consists of electronic health record data from intensive care units in a tertiary care hospital in the United States. We included patients ≥18 years with sepsis who developed AKI within 48 hours of intensive care unit admission. We then used deep learning to utilize all available vital signs, laboratory measurements, and comorbidities to identify subphenotypes. Outcomes were mortality 28 days after AKI and dialysis requirement. Results We identified 4001 patients with sepsis-associated AKI. We utilized 2546 combined features for K-means clustering, identifying three subphenotypes. Subphenotype 1 had 1443 patients, and subphenotype 2 had 1898 patients, whereas subphenotype 3 had 660 patients. Subphenotype 1 had the lowest proportion of liver disease and lowest Simplified Acute Physiology Score II scores compared with subphenotypes 2 and 3. The proportions of patients with CKD were similar between subphenotypes 1 and 3 (15%) but highest in subphenotype 2 (21%). Subphenotype 1 had lower median bilirubin levels, aspartate aminotransferase, and alanine aminotransferase compared with subphenotypes 2 and 3. Patients in subphenotype 1 also had lower median lactate, lactate dehydrogenase, and white blood cell count than patients in subphenotypes 2 and 3. Subphenotype 1 also had lower creatinine and BUN than subphenotypes 2 and 3. Dialysis requirement was lowest in subphenotype 1 (4% versus 7% [subphenotype 2] versus 26% [subphenotype 3]). The mortality 28 days after AKI was lowest in subphenotype 1 (23% versus 35% [subphenotype 2] versus 49% [subphenotype 3]). After adjustment, the adjusted odds ratio for mortality for subphenotype 3, with subphenotype 1 as a reference, was 1.9 (95% confidence interval, 1.5 to 2.4). Conclusions Utilizing routinely collected laboratory variables, vital signs, and comorbidities, we were able to identify three distinct subphenotypes of sepsis-associated AKI with differing outcomes.
Published: 2020

40. AKI in Hospitalized Patients with COVID-19

Author: Riccardo Miotto, Benjamin S. Glicksberg, Lili Chan, Allan C. Just, Felix Richter, Anuradha Lala, Valentin Fuster, Girish N. Nadkarni, Arash Kia, Carlos Cordon-Cardo, Akhil Vaid, Alexander W. Charney, Aparna Saha, Robert Freeman, Sulaiman Somani, Prem Timsina, Eric E. Schadt, Barbara Murphy, John Cijiang He, Ishan Paranjpe, David Reich, Kumardeep Chaudhary, Matthew A. Levin, Shan Zhao, Jagat Narula, Steven G. Coca, Rong Chen, Erwin P. Bottinger, Li Li, Kinsuk Chauhan, Carol R. Horowitz, and Zahi A. Fayad
Subjects: medicine.medical_specialty, Proteinuria, urogenital system, Hospitalized patients, business.industry, medicine.medical_treatment, 030232 urology & nephrology, Renal function, General Medicine, Urine, Odds ratio, 030204 cardiovascular system & hematology, urologic and male genital diseases, female genital diseases and pregnancy complications, Confidence interval, 03 medical and health sciences, 0302 clinical medicine, Nephrology, Internal medicine, Intensive care, medicine, medicine.symptom, business, Dialysis
Abstract: Background Early reports indicate that AKI is common among patients with coronavirus disease 2019 (COVID-19) and associated with worse outcomes. However, AKI among hospitalized patients with COVID-19 in the United States is not well described. Methods This retrospective, observational study involved a review of data from electronic health records of patients aged ≥18 years with laboratory-confirmed COVID-19 admitted to the Mount Sinai Health System from February 27 to May 30, 2020. We describe the frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aORs) with mortality. Results Of 3993 hospitalized patients with COVID-19, AKI occurred in 1835 (46%) patients; 347 (19%) of the patients with AKI required dialysis. The proportions with stages 1, 2, or 3 AKI were 39%, 19%, and 42%, respectively. A total of 976 (24%) patients were admitted to intensive care, and 745 (76%) experienced AKI. Of the 435 patients with AKI and urine studies, 84% had proteinuria, 81% had hematuria, and 60% had leukocyturia. Independent predictors of severe AKI were CKD, men, and higher serum potassium at admission. In-hospital mortality was 50% among patients with AKI versus 8% among those without AKI (aOR, 9.2; 95% confidence interval, 7.5 to 11.3). Of survivors with AKI who were discharged, 35% had not recovered to baseline kidney function by the time of discharge. An additional 28 of 77 (36%) patients who had not recovered kidney function at discharge did so on posthospital follow-up. Conclusions AKI is common among patients hospitalized with COVID-19 and is associated with high mortality. Of all patients with AKI, only 30% survived with recovery of kidney function by the time of discharge.
Published: 2020

41. Characterization of Patients Who Return to Hospital Following Discharge from Hospitalization for COVID-19

Author: Shan Zhao, Girish N. Nadkarni, Zahi A. Fayad, Sulaiman Somani, Matthew A. Levin, Erwin P. Bottinger, Jessica K De Freitas, Benjamin S. Glicksberg, Valentin Fuster, Anuradha Lala, Keith Sigel, Felix Richter, Allan C Just, Alexander W. Charney, and Nidhi Naik
Subjects: Male, Comorbidity, 030204 cardiovascular system & hematology, 01 natural sciences, Pulmonary Disease, Chronic Obstructive, 0302 clinical medicine, 030212 general & internal medicine, Original Research, Respiratory Distress Syndrome, COPD, Respiratory distress, Middle Aged, After discharge, 3. Good health, Hypertension, Female, Coronavirus Infections, Emergency Service, Hospital, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Pneumonia, Viral, Patient Readmission, Article, Betacoronavirus, 03 medical and health sciences, Internal medicine, Intensive care, Internal Medicine, medicine, Humans, 0101 mathematics, Pandemics, Aged, Retrospective Studies, SARS-CoV-2, business.industry, 010102 general mathematics, Case-control study, Anticoagulants, COVID-19, Retrospective cohort study, Emergency department, Length of Stay, medicine.disease, Pneumonia, Case-Control Studies, Emergency medicine, New York City, Index hospitalization, business
Abstract: Background Data on patients with coronavirus disease 2019 (COVID-19) who return to hospital after discharge are scarce. Characterization of these patients may inform post-hospitalization care. Objective To describe clinical characteristics of patients with COVID-19 who returned to the emergency department (ED) or required readmission within 14 days of discharge. Design Retrospective cohort study of SARS-COV-2-positive patients with index hospitalization between February 27 and April 12, 2020, with ≥ 14-day follow-up. Significance was defined as P < 0.05 after multiplying P by 125 study-wide comparisons. Participants Hospitalized patients with confirmed SARS-CoV-2 discharged alive from five New York City hospitals. Main Measures Readmission or return to ED following discharge. Results Of 2864 discharged patients, 103 (3.6%) returned for emergency care after a median of 4.5 days, with 56 requiring inpatient readmission. The most common reason for return was respiratory distress (50%). Compared with patients who did not return, there were higher proportions of COPD (6.8% vs 2.9%) and hypertension (36% vs 22.1%) among those who returned. Patients who returned also had a shorter median length of stay (LOS) during index hospitalization (4.5 [2.9,9.1] vs 6.7 [3.5, 11.5] days; Padjusted = 0.006), and were less likely to have required intensive care on index hospitalization (5.8% vs 19%; Padjusted = 0.001). A trend towards association between absence of in-hospital treatment-dose anticoagulation on index admission and return to hospital was also observed (20.9% vs 30.9%, Padjusted = 0.06). On readmission, rates of intensive care and death were 5.8% and 3.6%, respectively. Conclusions Return to hospital after admission for COVID-19 was infrequent within 14 days of discharge. The most common cause for return was respiratory distress. Patients who returned more likely had COPD and hypertension, shorter LOS on index-hospitalization, and lower rates of in-hospital treatment-dose anticoagulation. Future studies should focus on whether these comorbid conditions, longer LOS, and anticoagulation are associated with reduced readmissions. Electronic supplementary material The online version of this article (10.1007/s11606-020-06120-6) contains supplementary material, which is available to authorized users.
Published: 2020

42. Trans-ethnic and Ancestry-Specific Blood-Cell Genetics in 746,667 Individuals from 5 Global Populations

Author: Andrew D Beswick, Tõnu Esko, Niki Dimou, Xue Zhong, Jette Bork-Jensen, Petra Schubert, Masato Akiyama, Girish N. Nadkarni, Ruth J. F. Loos, Huijun Qian, Michele K. Evans, Stephen S. Rich, Nicole Soranzo, Henry Völzke, Yongmei Liu, Nicholas A. Watkins, Markus M. Lerch, Richard C. Trembath, Adam S. Butterworth, Erwin P. Bottinger, Jennifer E. Huffman, Bruce M. Psaty, Jingzhong Ding, Michael Preuss, Yoav Ben-Shlomo, Bhavi Trivedi, Yoichiro Kamatani, David A. van Heel, Kjell Nikus, Torben Hansen, Adolfo Correa, Mohsen Ghanbari, Paul L. Auer, Véronique Laplante, Ken Sin Lo, Hua Tang, Peter W.F. Wilson, Paul Elliott, David J. Roberts, Hilary C. Martin, Jean-Claude Tardif, Praveen Surendran, Regina Manansala, Terho Lehtimäki, Emanuele Di Angelantonio, Fotis Koskeridis, Alexander P. Reiner, Mélissa Beaudoin, Vijay G. Sankaran, Benjamin Rodriguez, William J. Astle, Parsa Akbari, Frank J. A. van Rooij, Yun Li, Andreas Greinacher, Abdou Mousas, Andrew D. Johnson, Yukinori Okada, Michael H. Guo, Leo-Pekka Lyytikäinen, Traci M. Bartz, Minhui Chen, Alan B. Zonderman, Niels Grarup, Oluf Pedersen, Kumaraswamynaidu Chitrala, Jeffrey Haessler, Ming-Huei Chen, Cassandra N. Spracklen, Karen L. Mohlke, Guillaume Lettre, Erik L. Bao, Bingshan Li, James S. Floyd, Wei Huang, Ani Manichaikul, John Danesh, Uwe Völker, Allan Linneberg, Evangelos Evangelou, Joanna M. M. Howson, Olli T. Raitakari, Tim Kacprowski, Jean-François Gauchat, Hélène Choquet, Arden Moscati, Saori Sakaue, Mika Kähönen, Linda Broer, Caleb A. Lareau, Qin Qin Huang, Matthias Nauck, Yoshinori Murakami, Charleston W. K. Chiang, VA Million Veteran Program, Nina Mononen, Tao Jiang, Laura M. Raffield, Jerome I. Rotter, Leslie A. Lange, Jonathan D. Rosen, Eric Jorgenson, Savita Karthikeyan, Karen A. Hunt, Nathan Pankratz, Kelly Cho, Masahiro Kanai, Willem H. Ouwehand, Jennifer A. Brody, Koichi Matsuda, Dragana Vuckovic, Epidemiology, and Internal Medicine
Subjects: LOCI, Mutation, Missense, Ethnic group, POLYGENIC RISK SCORES, HUMAN HEMATOPOIESIS, Biology, BIOBANK, phenome-wide association study, Polymorphism, Single Nucleotide, DISEASE, White People, General Biochemistry, Genetics and Molecular Biology, Article, Blood cell, 03 medical and health sciences, SINGLE-CELL, selective sweeps, 0302 clinical medicine, Asian People, parasitic diseases, Genetics, medicine, Humans, GENOME-WIDE ASSOCIATION, 030304 developmental biology, AFRICAN-AMERICANS, 0303 health sciences, interleukin-7, Interleukin-7, genetic architecture, Genetic architecture, TRAIT, HEK293 Cells, Phenotype, medicine.anatomical_structure, fine-mapping, polygenic trait score, lipids (amino acids, peptides, and proteins), FREQUENCY CODING VARIANTS, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10-9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.
Published: 2020

43. Multi-ethnic polygenic risk modifies the association between APOL1 high risk genotypes and chronic kidney disease

Author: Richard S. Cooper, Judy H. Cho, Ha My T. Vy, Orlando M. Gutiérrez, Girish N. Nadkarni, Ron Do, Erwin P. Bottinger, Ruth J. F. Loos, Benjamin S. Glicksberg, Faris F. Gulamali, and Carol R. Horowitz
Subjects: business.industry, Risk stratification, Genotype, medicine, Ethnic group, Polygenic risk score, Population screening, medicine.disease, business, Penetrance, Kidney disease, Demography
Abstract: The burden of advanced chronic kidney disease (CKD) falls disproportionately on minorities including African Americans (AAs) and Hispanic Americans (HAs) with admixed ancestry. Even though APOL1 high-risk genotypes increase risk of kidney disease, their penetrance is incomplete, indicating that the modification of APOL1 high risk may be polygenic. For this study, we used three multi-ethnic cohorts with APOL1 high risk genotypes and calculated a multi-ethnic PRS using publicly available summary statistics. We show that CKD risk is significantly modified by a multi-ethnic polygenic risk score. Standardizing population screening for CKD by including APOL1 high-risk genotypes and polygenic risk score may improve risk stratification and outcomes.
Published: 2021

44. Evaluation of a Machine Learning Approach Utilizing Wearable Data for Prediction of SARS-CoV-2 Infection in Healthcare Workers

Author: Matteo Danieletto, Dennis S. Charney, Mayte Suárez-Fariñas, Lewis Tomalin, Eddye Golden, Renata Pyzik, Sparshdeep Kaur, Drew Helmus, Laurie Keefer, Micol Zweig, Zahi A. Fayad, Girish N. Nadkarni, Robert Hirten, Anthony Biello, and Erwin P. Bottinger
Subjects: Receiver operating characteristic, business.industry, Wearable computer, Machine learning, computer.software_genre, Confidence interval, Test (assessment), Health care, Medicine, Heart rate variability, Observational study, Artificial intelligence, business, computer, Wearable technology
Abstract: ImportancePassive and non-invasive identification of SARS-CoV-2 infection remains a challenge. Widespread use of wearable devices represents an opportunity to leverage physiological metrics and fill this knowledge gap.ObjectiveTo determine whether a machine learning model can detect SARS-CoV-2 infection from physiological metrics collected from wearable devices.DesignA multicenter observational study enrolling health care workers with remote follow-up.SettingSeven hospitals from the Mount Sinai Health System in New York CityParticipantsEligibility criteria included health care workers who were ≥18 years, employees of one of the participating hospitals, with at least an iPhone series 6, and willing to wear an Apple Watch Series 4 or higher. We excluded participants with underlying autoimmune/inflammatory diseases, and medications known to interfere with autonomic function. We enrolled participants between April 29th, 2020, and March 2nd, 2021, and followed them for a median of 73 days (range, 3-253 days). Participants provided patient-reported outcome measures through a custom smartphone application and wore an Apple Watch, collecting heart rate variability and heart rate data, throughout the follow-up period.ExposureParticipants were exposed to SARS-CoV-2 infection over time due to ongoing community spread.Main Outcome and MeasureThe primary outcome was SARS-CoV-2 infection, defined as ±7 days from a self-reported positive SARS-CoV-2 nasal PCR test.ResultsWe enrolled 407 participants with 49 (12%) having a positive SARS-CoV-2 test during follow-up. We examined five machine-learning approaches and found that gradient-boosting machines (GBM) had the most favorable 10-CV performance. Across all testing sets, our GBM model predicted SARS-CoV-2 infection with an average area under the receiver operating characteristic (auROC)=85% (Confidence Interval 83-88%). The model was calibrated to improve sensitivity over specificity, achieving an average sensitivity of 76% (CI ±∼4%) and specificity of 84% (CI ±∼0.4%). The most important predictors included parameters describing the circadian HRV mean (MESOR) and peak-timing (acrophase), and age.Conclusions and RelevanceWe show that a tree-based ML algorithm applied to physiological metrics passively collected from a wearable device can identify and predict SARS-CoV2 infection. Utilizing physiological metrics from wearable devices may improve screening methods and infection tracking.
Published: 2021

45. The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study.

Author: Thomas W Winkler, Anne E Justice, Mariaelisa Graff, Llilda Barata, Mary F Feitosa, Su Chu, Jacek Czajkowski, Tõnu Esko, Tove Fall, Tuomas O Kilpeläinen, Yingchang Lu, Reedik Mägi, Evelin Mihailov, Tune H Pers, Sina Rüeger, Alexander Teumer, Georg B Ehret, Teresa Ferreira, Nancy L Heard-Costa, Juha Karjalainen, Vasiliki Lagou, Anubha Mahajan, Michael D Neinast, Inga Prokopenko, Jeannette Simino, Tanya M Teslovich, Rick Jansen, Harm-Jan Westra, Charles C White, Devin Absher, Tarunveer S Ahluwalia, Shafqat Ahmad, Eva Albrecht, Alexessander Couto Alves, Jennifer L Bragg-Gresham, Anton J M de Craen, Joshua C Bis, Amélie Bonnefond, Gabrielle Boucher, Gemma Cadby, Yu-Ching Cheng, Charleston W K Chiang, Graciela Delgado, Ayse Demirkan, Nicole Dueker, Niina Eklund, Gudny Eiriksdottir, Joel Eriksson, Bjarke Feenstra, Krista Fischer, Francesca Frau, Tessel E Galesloot, Frank Geller, Anuj Goel, Mathias Gorski, Tanja B Grammer, Stefan Gustafsson, Saskia Haitjema, Jouke-Jan Hottenga, Jennifer E Huffman, Anne U Jackson, Kevin B Jacobs, Åsa Johansson, Marika Kaakinen, Marcus E Kleber, Jari Lahti, Irene Mateo Leach, Benjamin Lehne, Youfang Liu, Ken Sin Lo, Mattias Lorentzon, Jian'an Luan, Pamela A F Madden, Massimo Mangino, Barbara McKnight, Carolina Medina-Gomez, Keri L Monda, May E Montasser, Gabriele Müller, Martina Müller-Nurasyid, Ilja M Nolte, Kalliope Panoutsopoulou, Laura Pascoe, Lavinia Paternoster, Nigel W Rayner, Frida Renström, Federica Rizzi, Lynda M Rose, Kathy A Ryan, Perttu Salo, Serena Sanna, Hubert Scharnagl, Jianxin Shi, Albert Vernon Smith, Lorraine Southam, Alena Stančáková, Valgerdur Steinthorsdottir, Rona J Strawbridge, Yun Ju Sung, Ioanna Tachmazidou, Toshiko Tanaka, Gudmar Thorleifsson, Stella Trompet, Natalia Pervjakova, Jonathan P Tyrer, Liesbeth Vandenput, Sander W van der Laan, Nathalie van der Velde, Jessica van Setten, Jana V van Vliet-Ostaptchouk, Niek Verweij, Efthymia Vlachopoulou, Lindsay L Waite, Sophie R Wang, Zhaoming Wang, Sarah H Wild, Christina Willenborg, James F Wilson, Andrew Wong, Jian Yang, Loïc Yengo, Laura M Yerges-Armstrong, Lei Yu, Weihua Zhang, Jing Hua Zhao, Ehm A Andersson, Stephan J L Bakker, Damiano Baldassarre, Karina Banasik, Matteo Barcella, Cristina Barlassina, Claire Bellis, Paola Benaglio, John Blangero, Matthias Blüher, Fabrice Bonnet, Lori L Bonnycastle, Heather A Boyd, Marcel Bruinenberg, Aron S Buchman, Harry Campbell, Yii-Der Ida Chen, Peter S Chines, Simone Claudi-Boehm, John Cole, Francis S Collins, Eco J C de Geus, Lisette C P G M de Groot, Maria Dimitriou, Jubao Duan, Stefan Enroth, Elodie Eury, Aliki-Eleni Farmaki, Nita G Forouhi, Nele Friedrich, Pablo V Gejman, Bruna Gigante, Nicola Glorioso, Alan S Go, Omri Gottesman, Jürgen Gräßler, Harald Grallert, Niels Grarup, Yu-Mei Gu, Linda Broer, Annelies C Ham, Torben Hansen, Tamara B Harris, Catharina A Hartman, Maija Hassinen, Nicholas Hastie, Andrew T Hattersley, Andrew C Heath, Anjali K Henders, Dena Hernandez, Hans Hillege, Oddgeir Holmen, Kees G Hovingh, Jennie Hui, Lise L Husemoen, Nina Hutri-Kähönen, Pirro G Hysi, Thomas Illig, Philip L De Jager, Shapour Jalilzadeh, Torben Jørgensen, J Wouter Jukema, Markus Juonala, Stavroula Kanoni, Maria Karaleftheri, Kay Tee Khaw, Leena Kinnunen, Steven J Kittner, Wolfgang Koenig, Ivana Kolcic, Peter Kovacs, Nikolaj T Krarup, Wolfgang Kratzer, Janine Krüger, Diana Kuh, Meena Kumari, Theodosios Kyriakou, Claudia Langenberg, Lars Lannfelt, Chiara Lanzani, Vaneet Lotay, Lenore J Launer, Karin Leander, Jaana Lindström, Allan Linneberg, Yan-Ping Liu, Stéphane Lobbens, Robert Luben, Valeriya Lyssenko, Satu Männistö, Patrik K Magnusson, Wendy L McArdle, Cristina Menni, Sigrun Merger, Lili Milani, Grant W Montgomery, Andrew P Morris, Narisu Narisu, Mari Nelis, Ken K Ong, Aarno Palotie, Louis Pérusse, Irene Pichler, Maria G Pilia, Anneli Pouta, Myriam Rheinberger, Rasmus Ribel-Madsen, Marcus Richards, Kenneth M Rice, Treva K Rice, Carlo Rivolta, Veikko Salomaa, Alan R Sanders, Mark A Sarzynski, Salome Scholtens, Robert A Scott, William R Scott, Sylvain Sebert, Sebanti Sengupta, Bengt Sennblad, Thomas Seufferlein, Angela Silveira, P Eline Slagboom, Jan H Smit, Thomas H Sparsø, Kathleen Stirrups, Ronald P Stolk, Heather M Stringham, Morris A Swertz, Amy J Swift, Ann-Christine Syvänen, Sian-Tsung Tan, Barbara Thorand, Anke Tönjes, Angelo Tremblay, Emmanouil Tsafantakis, Peter J van der Most, Uwe Völker, Marie-Claude Vohl, Judith M Vonk, Melanie Waldenberger, Ryan W Walker, Roman Wennauer, Elisabeth Widén, Gonneke Willemsen, Tom Wilsgaard, Alan F Wright, M Carola Zillikens, Suzanne C van Dijk, Natasja M van Schoor, Folkert W Asselbergs, Paul I W de Bakker, Jacques S Beckmann, John Beilby, David A Bennett, Richard N Bergman, Sven Bergmann, Carsten A Böger, Bernhard O Boehm, Eric Boerwinkle, Dorret I Boomsma, Stefan R Bornstein, Erwin P Bottinger, Claude Bouchard, John C Chambers, Stephen J Chanock, Daniel I Chasman, Francesco Cucca, Daniele Cusi, George Dedoussis, Jeanette Erdmann, Johan G Eriksson, Denis A Evans, Ulf de Faire, Martin Farrall, Luigi Ferrucci, Ian Ford, Lude Franke, Paul W Franks, Philippe Froguel, Ron T Gansevoort, Christian Gieger, Henrik Grönberg, Vilmundur Gudnason, Ulf Gyllensten, Per Hall, Anders Hamsten, Pim van der Harst, Caroline Hayward, Markku Heliövaara, Christian Hengstenberg, Andrew A Hicks, Aroon Hingorani, Albert Hofman, Frank Hu, Heikki V Huikuri, Kristian Hveem, Alan L James, Joanne M Jordan, Antti Jula, Mika Kähönen, Eero Kajantie, Sekar Kathiresan, Lambertus A L M Kiemeney, Mika Kivimaki, Paul B Knekt, Heikki A Koistinen, Jaspal S Kooner, Seppo Koskinen, Johanna Kuusisto, Winfried Maerz, Nicholas G Martin, Markku Laakso, Timo A Lakka, Terho Lehtimäki, Guillaume Lettre, Douglas F Levinson, Lars Lind, Marja-Liisa Lokki, Pekka Mäntyselkä, Mads Melbye, Andres Metspalu, Braxton D Mitchell, Frans L Moll, Jeffrey C Murray, Arthur W Musk, Markku S Nieminen, Inger Njølstad, Claes Ohlsson, Albertine J Oldehinkel, Ben A Oostra, Lyle J Palmer, James S Pankow, Gerard Pasterkamp, Nancy L Pedersen, Oluf Pedersen, Brenda W Penninx, Markus Perola, Annette Peters, Ozren Polašek, Peter P Pramstaller, Bruce M Psaty, Lu Qi, Thomas Quertermous, Olli T Raitakari, Tuomo Rankinen, Rainer Rauramaa, Paul M Ridker, John D Rioux, Fernando Rivadeneira, Jerome I Rotter, Igor Rudan, Hester M den Ruijter, Juha Saltevo, Naveed Sattar, Heribert Schunkert, Peter E H Schwarz, Alan R Shuldiner, Juha Sinisalo, Harold Snieder, Thorkild I A Sørensen, Tim D Spector, Jan A Staessen, Bandinelli Stefania, Unnur Thorsteinsdottir, Michael Stumvoll, Jean-Claude Tardif, Elena Tremoli, Jaakko Tuomilehto, André G Uitterlinden, Matti Uusitupa, André L M Verbeek, Sita H Vermeulen, Jorma S Viikari, Veronique Vitart, Henry Völzke, Peter Vollenweider, Gérard Waeber, Mark Walker, Henri Wallaschofski, Nicholas J Wareham, Hugh Watkins, Eleftheria Zeggini, CHARGE Consortium, DIAGRAM Consortium, GLGC Consortium, Global-BPGen Consortium, ICBP Consortium, MAGIC Consortium, Aravinda Chakravarti, Deborah J Clegg, L Adrienne Cupples, Penny Gordon-Larsen, Cashell E Jaquish, D C Rao, Goncalo R Abecasis, Themistocles L Assimes, Inês Barroso, Sonja I Berndt, Michael Boehnke, Panos Deloukas, Caroline S Fox, Leif C Groop, David J Hunter, Erik Ingelsson, Robert C Kaplan, Mark I McCarthy, Karen L Mohlke, Jeffrey R O'Connell, David Schlessinger, David P Strachan, Kari Stefansson, Cornelia M van Duijn, Joel N Hirschhorn, Cecilia M Lindgren, Iris M Heid, Kari E North, Ingrid B Borecki, Zoltán Kutalik, and Ruth J F Loos
Subjects: Genetics, QH426-470
Abstract: Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHRadjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHRadjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHRadjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR
Published: 2015
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46. FIBER: enabling flexible retrieval of electronic health records data for clinical predictive modeling

Author: Suparno Datta, Philipp Bode, Benjamin S. Glicksberg, Tom Martensen, Harry Freitas Da Cruz, Erwin P. Bottinger, Ariane Morassi Sasso, and Jan Philipp Sachs
Subjects: AcademicSubjects/SCI01060, databases, Computer science, Process (engineering), workflow, Health Informatics, Research and Applications, information storage and retrieval, 03 medical and health sciences, 0302 clinical medicine, Software, 030212 general & internal medicine, software/instrumentation, 030304 developmental biology, computer.programming_language, 0303 health sciences, Information retrieval, business.industry, Python (programming language), Data warehouse, Schema (genetic algorithms), Workflow, electronic health records, Data extraction, Star schema, factual, AcademicSubjects/SCI01530, business, AcademicSubjects/MED00010, computer
Abstract: Objectives The development of clinical predictive models hinges upon the availability of comprehensive clinical data. Tapping into such resources requires considerable effort from clinicians, data scientists, and engineers. Specifically, these efforts are focused on data extraction and preprocessing steps required prior to modeling, including complex database queries. A handful of software libraries exist that can reduce this complexity by building upon data standards. However, a gap remains concerning electronic health records (EHRs) stored in star schema clinical data warehouses, an approach often adopted in practice. In this article, we introduce the FlexIBle EHR Retrieval (FIBER) tool: a Python library built on top of a star schema (i2b2) clinical data warehouse that enables flexible generation of modeling-ready cohorts as data frames. Materials and Methods FIBER was developed on top of a large-scale star schema EHR database which contains data from 8 million patients and over 120 million encounters. To illustrate FIBER’s capabilities, we present its application by building a heart surgery patient cohort with subsequent prediction of acute kidney injury (AKI) with various machine learning models. Results Using FIBER, we were able to build the heart surgery cohort (n = 12 061), identify the patients that developed AKI (n = 1005), and automatically extract relevant features (n = 774). Finally, we trained machine learning models that achieved area under the curve values of up to 0.77 for this exemplary use case. Conclusion FIBER is an open-source Python library developed for extracting information from star schema clinical data warehouses and reduces time-to-modeling, helping to streamline the clinical modeling process.
Published: 2021

47. Acute Kidney Injury in Patients Hospitalized With COVID-19 in New York City: Temporal Trends From March 2020 to April 2021

Author: Zahi A. Fayad, Akhil Vaid, Suraj K. Jaladanki, Benjamin S. Glicksberg, Alexander W. Charney, Erwin P. Bottinger, Steven G. Coca, Lili Chan, John Cijiang He, Sergio Dellepiane, and Girish N. Nadkarni
Subjects: 2019-20 coronavirus outbreak, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), business.industry, medicine.medical_treatment, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Kidney Replacement Therapy, Acute kidney injury, COVID-19, Acute Kidney Injury, medicine.disease, Diseases of the genitourinary system. Urology, Nephrology, Internal medicine, Hemodialysis, Internal Medicine, medicine, Research Letter, In patient, RC870-923, business
Published: 2021

48. Factors Associated With Longitudinal Psychological and Physiological Stress in Health Care Workers During the COVID-19 Pandemic: Observational Study Using Apple Watch Data (Preprint)

Author: Robert P Hirten, Matteo Danieletto, Lewis Tomalin, Katie Hyewon Choi, Micol Zweig, Eddye Golden, Sparshdeep Kaur, Drew Helmus, Anthony Biello, Renata Pyzik, Claudia Calcagno, Robert Freeman, Bruce E Sands, Dennis Charney, Erwin P Bottinger, James W Murrough, Laurie Keefer, Mayte Suarez-Farinas, Girish N Nadkarni, and Zahi A Fayad
Abstract: BACKGROUND The COVID-19 pandemic has resulted in a high degree of psychological distress among health care workers (HCWs). There is a need to characterize which HCWs are at an increased risk of developing psychological effects from the pandemic. Given the differences in the response of individuals to stress, an analysis of both the perceived and physiological consequences of stressors can provide a comprehensive evaluation of its impact. OBJECTIVE This study aimed to determine characteristics associated with longitudinal perceived stress in HCWs and to assess whether changes in heart rate variability (HRV), a marker of autonomic nervous system function, are associated with features protective against longitudinal stress. METHODS HCWs across 7 hospitals in New York City, NY, were prospectively followed in an ongoing observational digital study using the custom Warrior Watch Study app. Participants wore an Apple Watch for the duration of the study to measure HRV throughout the follow-up period. Surveys measuring perceived stress, resilience, emotional support, quality of life, and optimism were collected at baseline and longitudinally. RESULTS A total of 361 participants (mean age 36.8, SD 10.1 years; female: n=246, 69.3%) were enrolled. Multivariate analysis found New York City’s COVID-19 case count to be associated with increased longitudinal stress (P=.008). Baseline emotional support, quality of life, and resilience were associated with decreased longitudinal stress (P<.001). A significant reduction in stress during the 4-week period after COVID-19 diagnosis was observed in the highest tertial of emotional support (P=.03) and resilience (P=.006). Participants in the highest tertial of baseline emotional support and resilience had a significantly different circadian pattern of longitudinally collected HRV compared to subjects in the low or medium tertial. CONCLUSIONS High resilience, emotional support, and quality of life place HCWs at reduced risk of longitudinal perceived stress and have a distinct physiological stress profile. Our findings support the use of these characteristics to identify HCWs at risk of the psychological and physiological stress effects of the pandemic.
Published: 2021

49. Association of Genetic Risk of Obesity with Postoperative Complications Using Mendelian Randomization

Author: Eric B. Larson, Jamie R. Robinson, Nephi A. Walton, Ge Zhang, Lisa Bastarache, Gail P. Jarvik, David Carrell, Maya S. Safarova, Ian B. Stanaway, Ruth J. F. Loos, Adam S. Gordon, Dan M. Roden, Shawn N. Murphy, David R. Crosslin, Zongyang Mou, Chunhua Weng, Gretchen Purcell Jackson, Wei-Qi Wei, Paul K. Crane, Bahram Namjou, Robert J. Carroll, Wei Wei, Qingxia Chen, Scott J. Hebbring, John J. Connolly, Hakon Hakonarson, Christopher D. Still, Iftikhar J. Kullo, Elisabeth A. Rosenthal, Frank D. Mentch, Lynn Petukhova, Erwin P. Bottinger, Joshua C. Denny, M. Geoffrey Hayes, and Patrick M. A. Sleiman
Subjects: Adult, Male, medicine.medical_specialty, Incisional hernia, Population, 030230 surgery, Overweight, Polymorphism, Single Nucleotide, Article, Body Mass Index, 03 medical and health sciences, Postoperative Complications, 0302 clinical medicine, Risk Factors, Internal medicine, Mendelian randomization, Humans, Medicine, Obesity, education, Retrospective Studies, education.field_of_study, business.industry, Retrospective cohort study, Odds ratio, Mendelian Randomization Analysis, Middle Aged, medicine.disease, Logistic Models, 030220 oncology & carcinogenesis, Cohort, Female, Surgery, medicine.symptom, business, Body mass index
Abstract: BACKGROUND: The extent to which obesity and genetics determine post-operative complications is incompletely understood. METHODS: We performed a retrospective study using two population cohorts with electronic health record (EHR) data. The first included 736,726 adults with body mass index (BMI) recorded between 1990-2017 at Vanderbilt University Medical Center. The second cohort consisted of 65,174 individuals from 12 institutions contributing EHR and genome-wide genotyping data to the Electronic Medical Records & Genomics (eMERGE) Network. Pairwise logistic regression analyses were used to measure the association of BMI categories with postoperative complications derived from International Classification of Disease-9 codes, including postoperative infection, incisional hernia, and intestinal obstruction. A genetic risk score (GRS) was constructed from 97 obesity-risk single nucleotide polymorphisms for a Mendelian randomization study to determine the association of genetic risk for obesity on postoperative complications. Logistic regression analyses were adjusted for sex, age, site, and race/principal components. RESULTS: Individuals with overweight or obese BMI (≥25 kg/m(2)) had increased risk for incisional hernia (Odds ratio [OR] 1.7-5.5, p
Published: 2019

50. Harmonizing Clinical Sequencing and Interpretation for the eMERGE III Network

Author: Ian B. Stanaway, Dan M. Roden, Divya Kalra, Dustin Key, Debra J. Abrams, David Fasel, Victor Castro, Brad Malin, Berta Almoguera, Beenish Riza, Meckenzie A. Behr, Eric Venner, Christine M. Eng, Joy Jayaseelan, Scott J. Hebbring, Michelle L. McGowan, Steven E. Scherer, Theresa L. Walunas, Mark Bowser, James D. Ralston, Wei-Qi Wei, Liwen Wang, David R. Murdock, Wayne H. Liang, Julia Wynn, Nancy D. Leslie, Laura J. Rasmussen-Torvik, Ming Ta (Michael) Lee, Frank D. Mentch, Lan Zhang, Alanna Kulchak Rahm, Josh F. Peterson, Jodell E. Linder, Joshua C. Smith, Soumitra Sengupta, Brendan J. Keating, Gina Vicente, Andrew Carroll, Nora B. Henrikson, Anne E. Justice, Heather S. Hain, Wen Liu, Andrea H. Ramirez, Matthew S. Lebo, Hana Zouk, Georgia L. Wiesner, Andrea L. Hartzler, Cassandra J. Pisieczko, Catherine M. Rives, Jessica Goehringer, Maegan V. Harden, John Lynch, Chiao-Feng Lin, Peter White, Phil Dunlea, Shawn N. Murphy, Mullai Murugan, Harshad Mahadeshwar, Mark Fleharty, Andrea Foster, Arvind Ramaprasan, Christopher A. Friedrich, Justin H. Gundelach, Hayley Lyon, Niall J. Lennon, Eric W. Klee, David R. Crosslin, Ge Zhang, Rongling Li, Ozan Dikilitas, Xiuping Liu, Christin Hoell, Aniwaa Owusu Obeng, Katherine D. Crew, Lisa M. Castillo, Justin Starren, Jonathan D. Mosley, Carrie L. Blout, Himanshu Sharma, Elizabeth M. McNally, Sarah T. Bland, Megan J. Puckelwartz, Matthew Varugheese, Keith Marsolo, Betty Woolf, Sharon Aufox, Janet L. Williams, Kimberly Walker, Murray H. Brilliant, Birgit Funke, Laura Allison Woods, Marylyn D. Ritchie, Brittany City, Todd Lingren, Hila Milo Rasouly, Lawrence J. Babb, Alex Fedotov, Robert C. Onofrio, Margaret Harr, Suzette J. Bielinski, Michael W. Wilson, Shubhabrata Mukherjee, Robert R. Freimuth, Chet Graham, Todd L. Edwards, Quinn S. Wells, Marc S. Williams, Jordan W. Smoller, Wendy K. Chung, Avni Santani, Paul K. Crane, George Hripcsak, QiPing Feng, Ali G. Gharavi, Yizhao Ni, Iftikhar J. Kullo, Michael Wagner, Philip E. Lammers, Michael J. Dinsmore, Thomas N. Person, Victoria Yi, Samuel E. Adunyah, Tim DeSmet, Eric B. Larson, Elizabeth Hynes, David C. Kochan, Eimear E. Kenny, Magalie S. Leduc, Lisa Mahanta, David Carrell, Paul S. Appelbaum, Viktoriya Korchina, Beth L. Cobb, Lynn Petukhova, Jessica De la Cruz, Patrick M. A. Sleiman, Stuart A. Scott, Tsung-Jung Wu, Gail P. Jarvik, Erwin P. Bottinger, Ken Wiley, Josh C. Denny, Melissa A. Basford, Samuel J. Aronson, David L. Veenstra, Yaping Yang, Kayla Marie Howell, John J. Connolly, Jessica Su, Yoonjung Yoonie Joo, Miguel Verbitsky, Sean M. Vargas, Cong Liu, Barbara Benoit, Andrew Hershey, Richard A. Gibbs, Cynthia A. Prows, Hana Bangash, Wendy Brodeur, Gauthami Chandanavelli, Sara L. Van Driest, Kurt D. Christensen, Elizabeth J. Bhoj, Vivian S. Gainer, Adam S. Gordon, Robert C. Green, Hakon Hakonarson, Krzysztof Kiryluk, Elisabeth A. Rosenthal, Rajbir Singh, James G. Linneman, Harrison Brand, Theodore Chiang, Sheila Dodge, Ingrid A. Holm, M. Geoffrey Hayes, Yunyun Jiang, Ning Shang, Samantha Baxter, Noralane M. Lindor, Kathleen A. Leppig, Teri A. Manolio, Sara E. Kalla, Pedro J. Caraballo, Ritika Raj, Aaron Scrol, Jyoti G. Dayal, Richard R. Sharp, Christie Kovar, Soumya Raychaudhuri, Sunghwan Sohn, Emily Kudalkar, Maddalena Marasa, Stacey Gabriel, Dan Schaid, Ladia Albertson-Junkans, Rex L. Chisholm, Maureen E. Smith, Donna M. Muzny, Casey Overby Taylor, Jianhong Hu, Elizabeth W. Karlson, Lisa Bastarache, Darren C. Ames, Joseph T. Glessner, Leora Witkowski, Siddharth Pratap, Qiaoyan Wang, Melissa A. Kelly, Adithya Balasubramanian, Kara Slowik, Terrie Kitchner, Barbara J. Klanderman, Shawn Denson, Mary Stroud, Alyssa Macbeth, Melanie F. Myers, Jesse Muniz, Kasia Tolwinski, Scott T. Weiss, Chunhua Weng, Stephanie M. Fullerton, John B. Harley, Christopher G. Chute, Heidi L. Rehm, Sheethal Jose, Andrew M. Glazer, Navya Shilpa Josyula, Kenneth M. Borthwick, Thomas E. Mullen, Mariza de Andrade, Leah C. Kottyan, Luke V. Rasmussen, James Meldrim, and Bahram Namjou
Subjects: 0301 basic medicine, Standardization, Test data generation, business.industry, Computer science, Sequence Analysis, DNA, 030105 genetics & heredity, Precision medicine, Data science, Clinical decision support system, Biobank, Article, 3. Good health, Data sharing, 03 medical and health sciences, 030104 developmental biology, Genetics, Humans, Genetic Testing, Prospective Studies, Sample collection, Personalized medicine, Precision Medicine, business, Genetics (clinical)
Abstract: The advancement of precision medicine requires new methods to coordinate and deliver genetic data from heterogeneous sources to physicians and patients. The eMERGE III Network enrolled >25,000 participants from biobank and prospective cohorts of predominantly healthy individuals for clinical genetic testing to determine clinically actionable findings. The network developed protocols linking together the 11 participant collection sites and 2 clinical genetic testing laboratories. DNA capture panels targeting 109 genes were used for testing of DNA and sample collection, data generation, interpretation, reporting, delivery, and storage were each harmonized. A compliant and secure network enabled ongoing review and reconciliation of clinical interpretations, while maintaining communication and data sharing between clinicians and investigators. A total of 202 individuals had positive diagnostic findings relevant to the indication for testing and 1,294 had additional/secondary findings of medical significance deemed to be returnable, establishing data return rates for other testing endeavors. This study accomplished integration of structured genomic results into multiple electronic health record (EHR) systems, setting the stage for clinical decision support to enable genomic medicine. Further, the established processes enable different sequencing sites to harmonize technical and interpretive aspects of sequencing tests, a critical achievement toward global standardization of genomic testing. The eMERGE protocols and tools are available for widespread dissemination.
Published: 2019

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