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1. Mendelian randomization indicates causal effects of estradiol levels on kidney function in males

Author

M. Kamal Nasr, Claudia Schurmann, Erwin P. Böttinger, and Alexander Teumer

Subjects
glomerular filtration rate, steroids, albuminuria, genome-wide association study, causality, Diseases of the endocrine glands. Clinical endocrinology, RC648-665
Abstract

ContextChronic kidney disease (CKD) is a public health burden worldwide. Epidemiological studies observed an association between sex hormones, including estradiol, and kidney function.ObjectiveWe conducted a Mendelian randomization (MR) study to assess a possible causal effect of estradiol levels on kidney function in males and females.DesignWe performed a bidirectional two-sample MR using published genetic associations of serum levels of estradiol in men (n = 206,927) and women (n = 229,966), and of kidney traits represented by estimated glomerular filtration rate (eGFR, n = 567,460), urine albumin-to-creatinine ratio (UACR, n = 547,361), and CKD (n = 41,395 cases and n = 439,303 controls) using data obtained from the CKDGen Consortium. Additionally, we conducted a genome-wide association study using UK Biobank cohort study data (n = 11,798 men and n = 6,835 women) to identify novel genetic associations with levels of estradiol, and then used these variants as instruments in a one-sample MR.ResultsThe two-sample MR indicated that genetically predicted estradiol levels are significantly associated with eGFR in men (beta = 0.077; p = 5.2E-05). We identified a single locus at chromosome 14 associated with estradiol levels in men being significant in the one-sample MR on eGFR (beta = 0.199; p = 0.017). We revealed significant results with eGFR in postmenopausal women and with UACR in premenopausal women, which did not reach statistical significance in the sensitivity MR analyses. No causal effect of eGFR or UACR on estradiol levels was found.ConclusionsWe conclude that serum estradiol levels may have a causal effect on kidney function. Our MR results provide starting points for studies to develop therapeutic strategies to reduce kidney disease.

Published
2023
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2. Implementation and evaluation of personal genetic testing as part of genomics analysis courses in German universities

Author

Tamara Slosarek, Susanne Ibing, Barbara Schormair, Henrike O. Heyne, Erwin P. Böttinger, Till F. M. Andlauer, and Claudia Schurmann

Subjects
Genomics education, Personal genotyping, Personalized medicine, Internal medicine, RC31-1245, Genetics, QH426-470
Abstract

Abstract Purpose Due to the increasing application of genome analysis and interpretation in medical disciplines, professionals require adequate education. Here, we present the implementation of personal genotyping as an educational tool in two genomics courses targeting Digital Health students at the Hasso Plattner Institute (HPI) and medical students at the Technical University of Munich (TUM). Methods We compared and evaluated the courses and the students’ perceptions on the course setup using questionnaires. Results During the course, students changed their attitudes towards genotyping (HPI: 79% [15 of 19], TUM: 47% [25 of 53]). Predominantly, students became more critical of personal genotyping (HPI: 73% [11 of 15], TUM: 72% [18 of 25]) and most students stated that genetic analyses should not be allowed without genetic counseling (HPI: 79% [15 of 19], TUM: 70% [37 of 53]). Students found the personal genotyping component useful (HPI: 89% [17 of 19], TUM: 92% [49 of 53]) and recommended its inclusion in future courses (HPI: 95% [18 of 19], TUM: 98% [52 of 53]). Conclusion Students perceived the personal genotyping component as valuable in the described genomics courses. The implementation described here can serve as an example for future courses in Europe.

Published
2023
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3. Interaction-Based Feature Selection Algorithm Outperforms Polygenic Risk Score in Predicting Parkinson’s Disease Status

Author

Justin L. Cope, Hannes A. Baukmann, Jörn E. Klinger, Charles N. J. Ravarani, Erwin P. Böttinger, Stefan Konigorski, and Marco F. Schmidt

Subjects
epistasis, machine learning, feature selection, parkinson's disease, PPMI (parkinson’s progression markers initiative), Genetics, QH426-470
Abstract

Polygenic risk scores (PRS) aggregating results from genome-wide association studies are the state of the art in the prediction of susceptibility to complex traits or diseases, yet their predictive performance is limited for various reasons, not least of which is their failure to incorporate the effects of gene-gene interactions. Novel machine learning algorithms that use large amounts of data promise to find gene-gene interactions in order to build models with better predictive performance than PRS. Here, we present a data preprocessing step by using data-mining of contextual information to reduce the number of features, enabling machine learning algorithms to identify gene-gene interactions. We applied our approach to the Parkinson’s Progression Markers Initiative (PPMI) dataset, an observational clinical study of 471 genotyped subjects (368 cases and 152 controls). With an AUC of 0.85 (95% CI = [0.72; 0.96]), the interaction-based prediction model outperforms the PRS (AUC of 0.58 (95% CI = [0.42; 0.81])). Furthermore, feature importance analysis of the model provided insights into the mechanism of Parkinson’s disease. For instance, the model revealed an interaction of previously described drug target candidate genes TMEM175 and GAPDHP25. These results demonstrate that interaction-based machine learning models can improve genetic prediction models and might provide an answer to the missing heritability problem.

Published
2021
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4. Shared Genetic Risk Factors of Intracranial, Abdominal, and Thoracic Aneurysms

Author

Femke N. G. van ’t Hof, Ynte M. Ruigrok, Cue Hyunkyu Lee, Stephan Ripke, Graig Anderson, Mariza de Andrade, Annette F. Baas, Jan D. Blankensteijn, Erwin P. Böttinger, Matthew J. Bown, Joseph Broderick, Philippe Bijlenga, David S. Carrell, Dana C. Crawford, David R. Crosslin, Christian Ebeling, Johan G. Eriksson, Myriam Fornage, Tatiana Foroud, Mikael von und zu Fraunberg, Christoph M. Friedrich, Emília I. Gaál, Omri Gottesman, Dong‐Chuan Guo, Seamus C. Harrison, Juha Hernesniemi, Albert Hofman, Ituro Inoue, Juha E. Jääskeläinen, Gregory T. Jones, Lambertus A. L. M. Kiemeney, Riku Kivisaari, Nerissa Ko, Seppo Koskinen, Michiaki Kubo, Iftikhar J. Kullo, Helena Kuivaniemi, Mitja I. Kurki, Aki Laakso, Dongbing Lai, Suzanne M. Leal, Hanna Lehto, Scott A. LeMaire, Siew‐Kee Low, Jennifer Malinowski, Catherine A. McCarty, Dianna M. Milewicz, Thomas H. Mosley, Yusuke Nakamura, Hirofumi Nakaoka, Mika Niemelä, Jennifer Pacheco, Peggy L. Peissig, Joanna Pera, Laura Rasmussen‐Torvik, Marylyn D. Ritchie, Fernando Rivadeneira, Andre M. van Rij, Regie Lyn P. Santos‐Cortez, Athanasios Saratzis, Agnieszka Slowik, Atsushi Takahashi, Gerard Tromp, André G. Uitterlinden, Shefali S. Verma, Sita H. Vermeulen, Gao T. Wang, Buhm Han, Gabriël J. E. Rinkel, Paul I. W. de Bakker, Ana Verissimo, Benjamin J. Wright, Suzannah Bumpstead, Solveig Gretarsdottir, Stephen A. Badger, Anne H. Child, Rachel E. Clough, Gillian Cockerill, Hany Hafez, D. Julian A. Scott, Simon Futers, Soroush Sohrabi, Alberto Smith, Matthew M. Thompson, Frank M. van Bockxmeer, Stefan E. Matthiasson, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Joep A. W. Teijink, Cisca Wijmenga, Jacqueline de Graaf, Lambertus A. Kiemeney, Jutta Palmen, Andrew J. Smith, Jes S. Lindholt, Declan T. Bradley, Matthew Waltham, Sarah Edkins, Rhian Gwilliam, Sarah E. Hunt, Simon Potter, Jonathan Golledge, Per Eriksson, Paul E. Norman, Janet T. Powell, Kari Stefansson, John R. Thompson, Steve E. Humphries, Robert D. Sayers, Panos Deloukas, Nilesh J. Samani, L. Victoria Phillip, Geraldine B. Hill, Michael J. A. Williams, Ian A. Thomson, Jo Krysa, Gerard T. Wilkins, Tony R. Merriman, Thodor M. Vasudevan, David R. Lewis, Ross D. Blair, and Andrew A. Hill

Subjects
abdominal aortic aneurysm, genome wide association study, intracranial aneurysm, thoracic aortic aneurysm, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

BackgroundIntracranial aneurysms (IAs), abdominal aortic aneurysms (AAAs), and thoracic aortic aneurysms (TAAs) all have a familial predisposition. Given that aneurysm types are known to co‐occur, we hypothesized that there may be shared genetic risk factors for IAs, AAAs, and TAAs. Methods and ResultsWe performed a mega‐analysis of 1000 Genomes Project‐imputed genome‐wide association study (GWAS) data of 4 previously published aneurysm cohorts: 2 IA cohorts (in total 1516 cases, 4305 controls), 1 AAA cohort (818 cases, 3004 controls), and 1 TAA cohort (760 cases, 2212 controls), and observed associations of 4 known IA, AAA, and/or TAA risk loci (9p21, 18q11, 15q21, and 2q33) with consistent effect directions in all 4 cohorts. We calculated polygenic scores based on IA‐, AAA‐, and TAA‐associated SNPs and tested these scores for association to case‐control status in the other aneurysm cohorts; this revealed no shared polygenic effects. Similarly, linkage disequilibrium–score regression analyses did not show significant correlations between any pair of aneurysm subtypes. Last, we evaluated the evidence for 14 previously published aneurysm risk single‐nucleotide polymorphisms through collaboration in extended aneurysm cohorts, with a total of 6548 cases and 16 843 controls (IA) and 4391 cases and 37 904 controls (AAA), and found nominally significant associations for IA risk locus 18q11 near RBBP8 to AAA (odds ratio [OR]=1.11; P=4.1×10−5) and for TAA risk locus 15q21 near FBN1 to AAA (OR=1.07; P=1.1×10−3). ConclusionsAlthough there was no evidence for polygenic overlap between IAs, AAAs, and TAAs, we found nominally significant effects of two established risk loci for IAs and TAAs in AAAs. These two loci will require further replication.

Published
2016
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13. HPI-DHC at TREC 2018 Precision Medicine Track.

Author

Michel Oleynik, Erik Faessler, Ariane Morassi Sasso, Arpita Kappattanavar, Benjamin Bergner, Harry Freitas Da Cruz, Jan-Philipp Sachs, Suparno Datta, and Erwin P. Böttinger

Published
2018

15. Predicting hypertension onset from longitudinal electronic health records with deep learning

Author

Suparno Datta, Ariane Morassi Sasso, Nina Kiwit, Subhronil Bose, Girish Nadkarni, Riccardo Miotto, and Erwin P Böttinger

Subjects
Health Informatics
Abstract

Objective Hypertension has long been recognized as one of the most important predisposing factors for cardiovascular diseases and mortality. In recent years, machine learning methods have shown potential in diagnostic and predictive approaches in chronic diseases. Electronic health records (EHRs) have emerged as a reliable source of longitudinal data. The aim of this study is to predict the onset of hypertension using modern deep learning (DL) architectures, specifically long short-term memory (LSTM) networks, and longitudinal EHRs. Materials and Methods We compare this approach to the best performing models reported from previous works, particularly XGboost, applied to aggregated features. Our work is based on data from 233 895 adult patients from a large health system in the United States. We divided our population into 2 distinct longitudinal datasets based on the diagnosis date. To ensure generalization to unseen data, we trained our models on the first dataset (dataset A “train and validation”) using cross-validation, and then applied the models to a second dataset (dataset B “test”) to assess their performance. We also experimented with 2 different time-windows before the onset of hypertension and evaluated the impact on model performance. Results With the LSTM network, we were able to achieve an area under the receiver operating characteristic curve value of 0.98 in the “train and validation” dataset A and 0.94 in the “test” dataset B for a prediction time window of 1 year. Lipid disorders, type 2 diabetes, and renal disorders are found to be associated with incident hypertension. Conclusion These findings show that DL models based on temporal EHR data can improve the identification of patients at high risk of hypertension and corresponding driving factors. In the long term, this work may support identifying individuals who are at high risk for developing hypertension and facilitate earlier intervention to prevent the future development of hypertension.

Published
2022

16. Acute Kidney Injury in Hospitalized Patients with COVID-19

Author

Lili Chan, Kumardeep Chaudhary, Aparna Saha, Kinsuk Chauhan, Akhil Vaid, Mukta Baweja, Kirk Campbell, Nicholas Chun, Miriam Chung, Priya Deshpande, Samira S. Farouk, Lewis Kaufman, Tonia Kim, Holly Koncicki, Vijay Lapsia, Staci Leisman, Emily Lu, Kristin Meliambro, Madhav C. Menon, Joshua L. Rein, Shuchita Sharma, Joji Tokita, Jaime Uribarri, Joseph A. Vassalotti, Jonathan Winston, Kusum S. Mathews, Shan Zhao, Ishan Paranjpe, Sulaiman Somani, Felix Richter, Ron Do, Riccardo Miotto, Anuradha Lala, Arash Kia, Prem Timsina, Li Li, Matteo Danieletto, Eddye Golden, Patricia Glowe, Micol Zweig, Manbir Singh, Robert Freeman, Rong Chen, Eric Nestler, Jagat Narula, Allan C. Just, Carol Horowitz, Judith Aberg, Ruth J.F. Loos, Judy Cho, Zahi Fayad, Carlos Cordon-Cardo, Eric Schadt, Matthew A. Levin, David L. Reich, Valentin Fuster, Barbara Murphy, John Cijiang He, Alexander W. Charney, Erwin P. Böttinger, Benjamin S. Glicksberg, Steven G. Coca, and Girish N. Nadkarni

Subjects
medicine.medical_specialty, medicine.medical_treatment, 030232 urology & nephrology, Renal function, urologic and male genital diseases, Article, law.invention, 03 medical and health sciences, 0302 clinical medicine, law, Clinical Research, Internal medicine, Intensive care, medicine, 030212 general & internal medicine, Renal replacement therapy, Dialysis, business.industry, urogenital system, Acute kidney injury, Retrospective cohort study, medicine.disease, Intensive care unit, female genital diseases and pregnancy complications, 3. Good health, business, Kidney disease
Abstract

ImportancePreliminary reports indicate that acute kidney injury (AKI) is common in coronavirus disease (COVID)-19 patients and is associated with worse outcomes. AKI in hospitalized COVID-19 patients in the United States is not well-described.ObjectiveTo provide information about frequency, outcomes and recovery associated with AKI and dialysis in hospitalized COVID-19 patients.DesignObservational, retrospective study.SettingAdmitted to hospital between February 27 and April 15, 2020.ParticipantsPatients aged ≥18 years with laboratory confirmed COVID-19ExposuresAKI (peak serum creatinine increase of 0.3 mg/dL or 50% above baseline).Main Outcomes and MeasuresFrequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aOR) with mortality. We also trained and tested a machine learning model for predicting dialysis requirement with independent validation.ResultsA total of 3,235 hospitalized patients were diagnosed with COVID-19. AKI occurred in 1406 (46%) patients overall and 280 (20%) with AKI required renal replacement therapy. The incidence of AKI (admission plus new cases) in patients admitted to the intensive care unit was 68% (553 of 815). In the entire cohort, the proportion with stages 1, 2, and 3 AKI were 35%, 20%, 45%, respectively. In those needing intensive care, the respective proportions were 20%, 17%, 63%, and 34% received acute renal replacement therapy. Independent predictors of severe AKI were chronic kidney disease, systolic blood pressure, and potassium at baseline. In-hospital mortality in patients with AKI was 41% overall and 52% in intensive care. The aOR for mortality associated with AKI was 9.6 (95% CI 7.4-12.3) overall and 20.9 (95% CI 11.7-37.3) in patients receiving intensive care. 56% of patients with AKI who were discharged alive recovered kidney function back to baseline. The area under the curve (AUC) for the machine learned predictive model using baseline features for dialysis requirement was 0.79 in a validation test.Conclusions and RelevanceAKI is common in patients hospitalized with COVID-19, associated with worse mortality, and the majority of patients that survive do not recover kidney function. A machine-learned model using admission features had good performance for dialysis prediction and could be used for resource allocation.Key PointsQuestionWhat is incidence and outcomes of acute kidney injury (AKI) in patients hospitalized with COVID-19?FindingsIn this observational study of 3,235 hospitalized patients with COVID-19 in New York City, AKI occurred in 46% of patients and 20% of those patients required dialysis. AKI was associated with increased mortality. 44% of patients discharged alive had residual acute kidney disease. A machine learned predictive model using baseline features for dialysis requirement had an AUC Of 0.79.MeaningAKI was common in patients with COVID-19, associated with increased mortality, and nearly half of patients had acute kidney disease on discharge.

Published
2020

17. 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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18. 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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19. 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
Full Text
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20. The Electronic Medical Records and Genomics (eMERGE) Network: past, present, and future

Author

Omri, Gottesman, Helena, Kuivaniemi, Gerard, Tromp, W Andrew, Faucett, Rongling, Li, Teri A, Manolio, Saskia C, Sanderson, Joseph, Kannry, Randi, Zinberg, Melissa A, Basford, Murray, Brilliant, David J, Carey, Rex L, Chisholm, Christopher G, Chute, John J, Connolly, David, Crosslin, Joshua C, Denny, Carlos J, Gallego, Jonathan L, Haines, Hakon, Hakonarson, John, Harley, Gail P, Jarvik, Isaac, Kohane, Iftikhar J, Kullo, Eric B, Larson, Catherine, McCarty, Marylyn D, Ritchie, Dan M, Roden, Maureen E, Smith, Erwin P, Böttinger, Marc S, Williams, and Weiyi, Xia

Subjects
Decision support system, Genetic Research, Research groups, Genotype, Best practice, Genomics, Review, Bioinformatics, 03 medical and health sciences, 0302 clinical medicine, electronic medical records, Medicine, Electronic Health Records, Humans, collaborative research, 030212 general & internal medicine, Precision Medicine, Genetics (clinical), 030304 developmental biology, 0303 health sciences, business.industry, Medical record, Electronic medical record, personalized medicine, Data science, genetics and genomics, United States, 3. Good health, National Human Genome Research Institute (U.S.), Phenotype, Informatics, genome-wide association studies, Personalized medicine, business, Genome-Wide Association Study
Abstract

The Electronic Medical Records and Genomics Network is a National Human Genome Research Institute–funded consortium engaged in the development of methods and best practices for using the electronic medical record as a tool for genomic research. Now in its sixth year and second funding cycle, and comprising nine research groups and a coordinating center, the network has played a major role in validating the concept that clinical data derived from electronic medical records can be used successfully for genomic research. Current work is advancing knowledge in multiple disciplines at the intersection of genomics and health-care informatics, particularly for electronic phenotyping, genome-wide association studies, genomic medicine implementation, and the ethical and regulatory issues associated with genomics research and returning results to study participants. Here, we describe the evolution, accomplishments, opportunities, and challenges of the network from its inception as a five-group consortium focused on genotype–phenotype associations for genomic discovery to its current form as a nine-group consortium pivoting toward the implementation of genomic medicine. Genet Med 15 10, 761–771.

Published
2013

21. The human beta 2 integrin CD18 promoter consists of two inverted Ets cis elements

Author

M A Arnaout, Erwin P. Böttinger, Carl Simon Shelley, and Omid C. Farokhzad

Subjects
General transcription factor, Regulatory sequence, Cellular differentiation, Gene expression, CAAT box, Promoter, Cell Biology, Biology, Binding site, Molecular Biology, Molecular biology, Transcription factor
Abstract

To define the minimal promoter responsible for expression of CD18 in myeloid and lymphoid cells, we generated 5' and 3' deletion constructs of a segment extending 785 bp upstream and 19 bp downstream of a major transcription start site and determined their effects on driving expression of the luciferase reporter gene in transfected hematopoietic cell lines. A region extending from nucleotides (nt) -302 to +19 was sufficient for cell-restricted and phorbol ester-inducible expression. DNase I footprinting of this region revealed two adjacent protected segments extending from nt -81 to -68 (box A) and -55 to -41 (box B). When a construct of 47 nt in length containing box A and box B and lacking other 3' or 5' elements was cloned into a promoterless vector, it conferred tissue-specific and phorbol ester-inducible expression. Gel retardation revealed that the protein components of two major protein-DNA complexes that form on both box A and box B and are required for transcriptional activation are members of the Ets oncoprotein family; one is related to the GA-binding protein (GABP), and the other is related to PU.1/Spi-1. The minimal CD18 promoter, lacking TATA, CAAT, and initiator elements and consisting primarily of Ets repeats, may exemplify an emerging class of promoters with which the concerted binding of Ets factors is necessary and sufficient to mediate transcriptional activation through direct recruitment of the basal transcription machinery.

Published
1994

22. Antineutrophil cytoplasmic autoantibody-associated vasculitis presenting as sjögren's syndrome

Author

M. Amin Arnaout, John L. Niles, Robert T. McCluskey, A. Bernard Collins, and Erwin P. Böttinger

Subjects
Systemic disease, Pathology, medicine.medical_specialty, Immunology, urologic and male genital diseases, medicine.disease_cause, Autoimmunity, Rheumatology, immune system diseases, Proteinase 3, medicine, Immunology and Allergy, Pharmacology (medical), cardiovascular diseases, skin and connective tissue diseases, biology, business.industry, Autoantibody, medicine.disease, respiratory tract diseases, Myeloperoxidase, biology.protein, Differential diagnosis, business, Vasculitis, Systemic vasculitis
Abstract

A 63-year-old woman, in whom a diagnosis of Sjogren's syndrome was initially made, proved to have systemic vasculitis with salivary gland involvement and necrotizing and crescentic glomerulonephritis. Antineutrophil cytoplasmic autoantibodies (ANCA) against myeloperoxidase were positive. ANCA-associated vasculitis should be considered in the differential diagnosis of Sjogren's syndrome. A positive finding on immunoassay for ANCA against myeloperoxidase or proteinase 3 may help establish the diagnosis.

Published
1992

24. Glucose-induced reactive oxygen species cause apoptosis of podocytes and podocyte depletion at the onset of diabetic nephropathy

Author

Katalin, Susztak, Amanda C, Raff, Mario, Schiffer, and Erwin P, Böttinger

Subjects
Blood Glucose, Male, Podocytes, NADPH Oxidases, Apoptosis, p38 Mitogen-Activated Protein Kinases, Glomerular Mesangium, Mice, Diabetes Mellitus, Type 1, Diabetes Mellitus, Type 2, Albuminuria, Animals, Diabetic Nephropathies, Reactive Oxygen Species
Abstract

Diabetic nephropathy is the most common cause of end-stage renal disease in the U.S. Recent studies demonstrate that loss of podocytes is an early feature of diabetic nephropathy that predicts its progressive course. Cause and consequences of podocyte loss during early diabetic nephropathy remain poorly understood. Here, we demonstrate that podocyte apoptosis increased sharply with onset of hyperglycemia in Ins2(Akita) (Akita) mice with type 1 diabetes and Lepr(db/db) (db/db) mice with obesity and type 2 diabetes. Podocyte apoptosis coincided with the onset of urinary albumin excretion (UAE) and preceded significant losses of podocytes in Akita (37% reduction) and db/db (27% reduction) mice. Increased extracellular glucose (30 mmol/l) rapidly stimulated generation of intracellular reactive oxygen species (ROS) through NADPH oxidase and mitochondrial pathways and led to activation of proapoptotic p38 mitogen-activated protein kinase and caspase 3 and to apoptosis of conditionally immortalized podocytes in vitro. Chronic inhibition of NADPH oxidase prevented podocyte apoptosis and ameliorated podocyte depletion, UAE, and mesangial matrix expansion in db/db mice. In conclusion, our results demonstrate for the first time that glucose-induced ROS production initiates podocyte apoptosis and podocyte depletion in vitro and in vivo and suggest that podocyte apoptosis/depletion represents a novel early pathomechanism(s) leading to diabetic nephropathy in murine type 1 and type 2 diabetic models.

Published
2005

25. RNA labeling and hybridization of DNA microarrays

Author

Erwin P, Böttinger, Akiva, Novetsky, and Jiri, Zavadil

Subjects
DNA, Complementary, Transcription, Genetic, Gene Expression Profiling, Animals, Humans, Nucleic Acid Hybridization, RNA, Kidney, Fluorescent Dyes, Oligonucleotide Array Sequence Analysis
Published
2003

26. TGF-beta signaling in renal disease

Author

Erwin P, Böttinger and Markus, Bitzer

Subjects
Transforming Growth Factor beta, Disease Progression, Humans, Kidney Diseases, Signal Transduction
Abstract

Since discovery over a decade ago of a role for the cytokine TGF-beta as key mediator of glomerular and tubulointerstitial pathobiology in chronic kidney diseases, studies of TGF-beta signaling in the kidney have focused on the molecular biology of fibrogenesis. In recent years, glomerular and tubular epithelial cell apoptosis and cellular transdifferentiation have been proposed as putative primary pathomechanisms that may underlie progression of renal disease. This review describes evidence in support of nonlinear models and functional roles of TGF-beta signaling in mediating apoptosis and epithelial-to-mesenchymal transdifferentiation (EMT) in chronic progressive renal disease. Emphasis is placed on cell context-dependent models of TGF-beta signaling providing a conceptual framework to consolidate seemingly distinct pathomechanisms of progression of glomerular and tubulointerstitial disease.

Published
2002

27. During differentiation of the monocytic cell line U937, Pur alpha mediates induction of the CD11c beta 2 integrin gene promoter

Author

Jens M. Teodoridis, Heiyoung Park, C. Simon Shelley, Erwin P. Böttinger, M. Amin Arnaout, and Omid C. Farokhzad

Subjects
Sp1 Transcription Factor, Immunology, Molecular Sequence Data, CD11c, DNA, Single-Stranded, Integrin alphaXbeta2, CD18, Biology, Monocytes, Gene expression, Immunology and Allergy, Humans, Cyclic AMP Response Element-Binding Protein, Promoter Regions, Genetic, Transcription factor, integumentary system, U937 cell, Base Sequence, Cell adhesion molecule, hemic and immune systems, Chemotaxis, Cell Differentiation, U937 Cells, Molecular biology, DNA-Binding Proteins, Gene Expression Regulation, Cell culture, CD18 Antigens, Trans-Activators, Protein Binding, Transcription Factors
Abstract

CD11c is a member of the β2 integrin family of adhesion molecules that, together with CD18, forms a heterodimeric receptor on the surface of myeloid, NK, dendritic, and certain leukemic, lymphoma, and activated lymphoid cells. Monocytic differentiation is associated with an induction of both CD11c and CD18 gene expression. The resulting CD11c/CD18 receptor mediates firm adhesion to the vascular endothelium, transendothelial migration, chemotaxis, and phagocytosis. Monocytic differentiation can be mimicked in vitro by treatment of the promonocytic cell line U937 with PMA. Recently, we reported that in U937 cells, expression of the CD11c gene is controlled by an unidentified transcription factor that binds ssDNA. This finding suggested that DNA secondary structure plays an important role in controlling the CD11c gene and prompted us to search for additional ssDNA-binding activities with which this gene interacts. In this study, we report that in U937 cells, expression of the CD11c gene is mediated by the ssDNA-binding protein Purα. During PMA-induced differentiation, the ability of Purα to activate the CD11c promoter in U937 cells increases, as does that of Sp1. Together, these increases in the functional activity of both Purα and Sp1 combine to induce CD11c expression.

Published
2002

28. 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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29. The human beta 2 integrin CD18 promoter consists of two inverted Ets cis elements

Author

Erwin P. Böttinger, C. Simon Shelley, Omid C. Farokhzad, and M. Amin Arnaout

Subjects
Integrins, Transcription, Genetic, Molecular Sequence Data, Transfection, Polymerase Chain Reaction, Antigens, CD, Proto-Oncogene Proteins, Tumor Cells, Cultured, Humans, Cloning, Molecular, Luciferases, Promoter Regions, Genetic, Molecular Biology, DNA Primers, Repetitive Sequences, Nucleic Acid, Sequence Deletion, Binding Sites, Base Sequence, Proto-Oncogene Proteins c-ets, Receptors, Leukocyte-Adhesion, Nuclear Proteins, Cell Differentiation, Cell Biology, CD18 Antigens, Tetradecanoylphorbol Acetate, HeLa Cells, Transcription Factors, Research Article
Abstract

To define the minimal promoter responsible for expression of CD18 in myeloid and lymphoid cells, we generated 5' and 3' deletion constructs of a segment extending 785 bp upstream and 19 bp downstream of a major transcription start site and determined their effects on driving expression of the luciferase reporter gene in transfected hematopoietic cell lines. A region extending from nucleotides (nt) -302 to +19 was sufficient for cell-restricted and phorbol ester-inducible expression. DNase I footprinting of this region revealed two adjacent protected segments extending from nt -81 to -68 (box A) and -55 to -41 (box B). When a construct of 47 nt in length containing box A and box B and lacking other 3' or 5' elements was cloned into a promoterless vector, it conferred tissue-specific and phorbol ester-inducible expression. Gel retardation revealed that the protein components of two major protein-DNA complexes that form on both box A and box B and are required for transcriptional activation are members of the Ets oncoprotein family; one is related to the GA-binding protein (GABP), and the other is related to PU.1/Spi-1. The minimal CD18 promoter, lacking TATA, CAAT, and initiator elements and consisting primarily of Ets repeats, may exemplify an emerging class of promoters with which the concerted binding of Ets factors is necessary and sufficient to mediate transcriptional activation through direct recruitment of the basal transcription machinery.

Published
1994

30. 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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31. 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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32. 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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33. 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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34. Return of Genomic Results in the Genomic Medicine Projects of the eMERGE Network

Author

Iftikhar J. Kullo, Ra'ad eHaddad, Cynthia A. Prows, Ingrid eHolm, Saskia C. Sanderson, Nanibaa' A. Garrison, Richard R. Sharp, Maureen E. Smith, Helena eKuivaniemi, Erwin P. Bottinger, John eConnolly, Brendan J. Keating, Catherine A. McCarty, Marc S. Williams, and Gail P. Jarvik

Subjects
Electronic Health Records, Genetic Counseling, Genomics, Pharmacogenetics, next generation sequencing, Incidental Findings, Genetics, QH426-470
Abstract

The electronic Medical Records and Genomics (eMERGE) (Phase I) network was established in 2007 to further genomic discovery using biorepositories linked to the electronic health record (EHR). In Phase II, which began in 2011, genomic discovery efforts continue and in addition the network is investigating best practices for implementing genomic medicine for patient care, in particular, the return of genomic results in the EHR for use by physicians at point-of-care. To develop strategies for addressing the challenges of implementing genomic medicine in the clinical setting, the eMERGE network is conducting studies that return clinically-relevant genomic results to research participants and their health care providers. These genomic medicine pilot studies include returning individual genetic variants associated with disease susceptibility or drug response, as well as genetic risk scores for common ‘complex’ disorders. Additionally, as part of a network-wide pharmacogenomics-related project, targeted resequencing of 84 pharmacogenes is being performed and select genotypes of pharmacogenetic relevance are being placed in the EHR to guide individualized drug therapy. Individual sites within the eMERGE network are exploring mechanisms to address incidental findings generated by resequencing of the 84 pharmacogenes. In this paper, we describe studies being conducted within the eMERGE network to develop best practices for integrating genomic findings into the EHR, and the challenges associated with such work.

Published
2014
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35. Multiple metabolic hits converge on CD36 as novel mediator of tubular epithelial apoptosis in diabetic nephropathy.

Author

Katalin Susztak, Emilio Ciccone, Peter McCue, Kumar Sharma, and Erwin P Böttinger

Subjects
Medicine
Abstract

Diabetic nephropathy (DNP) is a common complication of type 1 and type 2 diabetes mellitus and the most common cause of kidney failure. While DNP manifests with albuminuria and diabetic glomerulopathy, its progression correlates best with tubular epithelial degeneration (TED) and interstitial fibrosis. However, mechanisms leading to TED in DNP remain poorly understood.We found that expression of scavenger receptor CD36 coincided with proximal tubular epithelial cell (PTEC) apoptosis and TED specifically in human DNP. High glucose stimulated cell surface expression of CD36 in PTECs. CD36 expression was necessary and sufficient to mediate PTEC apoptosis induced by glycated albumins (AGE-BSA and CML-BSA) and free fatty acid palmitate through sequential activation of src kinase, and proapoptotic p38 MAPK and caspase 3. In contrast, paucity of expression of CD36 in PTECs in diabetic mice with diabetic glomerulopathy was associated with normal tubular epithelium and the absence of tubular apoptosis. Mouse PTECs lacked CD36 and were resistant to AGE-BSA-induced apoptosis. Recombinant expression of CD36 in mouse PTECs conferred susceptibility to AGE-BSA-induced apoptosis.Our findings suggest a novel role for CD36 as an essential mediator of proximal tubular apoptosis in human DNP. Because CD36 expression was induced by glucose in PTECs, and because increased CD36 mediated AGE-BSA-, CML-BSA-, and palmitate-induced PTEC apoptosis, we propose a two-step metabolic hit model for TED, a hallmark of progression in DNP.

Published
2005
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