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1. Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics

Author: Ruowang Li, Rui Duan, Xinyuan Zhang, Thomas Lumley, Sarah Pendergrass, Christopher Bauer, Hakon Hakonarson, David S. Carrell, Jordan W. Smoller, Wei-Qi Wei, Robert Carroll, Digna R. Velez Edwards, Georgia Wiesner, Patrick Sleiman, Josh C. Denny, Jonathan D. Mosley, Marylyn D. Ritchie, Yong Chen, and Jason H. Moore
Subjects: Science
Abstract: Thus far, pleiotropy analysis using individual-level Electronic Health Records data has been limited to data from one site. Here, the authors introduce Sum-Share, a method designed to efficiently and losslessly integrate EHR and genetic data from multiple sites to perform pleiotropy analysis.
Published: 2021
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2. A study paradigm integrating prospective epidemiologic cohorts and electronic health records to identify disease biomarkers

Author: Jonathan D. Mosley, QiPing Feng, Quinn S. Wells, Sara L. Van Driest, Christian M. Shaffer, Todd L. Edwards, Lisa Bastarache, Wei-Qi Wei, Lea K. Davis, Catherine A. McCarty, Will Thompson, Christopher G. Chute, Gail P. Jarvik, Adam S. Gordon, Melody R. Palmer, David R. Crosslin, Eric B. Larson, David S. Carrell, Iftikhar J. Kullo, Jennifer A. Pacheco, Peggy L. Peissig, Murray H. Brilliant, James G. Linneman, Bahram Namjou, Marc S. Williams, Marylyn D. Ritchie, Kenneth M. Borthwick, Shefali S. Verma, Jason H. Karnes, Scott T. Weiss, Thomas J. Wang, C. Michael Stein, Josh C. Denny, and Dan M. Roden
Subjects: Science
Abstract: Biomarker identification requires prohibitively large cohorts with gene expression and phenotype data. The approach introduced here learns polygenic predictors of expression from genetic and expression data, used to infer biomarker levels in patients with genetic and disease information.
Published: 2018
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3. PR interval genome-wide association meta-analysis identifies 50 loci associated with atrial and atrioventricular electrical activity

Author: Jessica van Setten, Jennifer A. Brody, Yalda Jamshidi, Brenton R. Swenson, Anne M. Butler, Harry Campbell, Fabiola M. Del Greco, Daniel S. Evans, Quince Gibson, Daniel F. Gudbjartsson, Kathleen F. Kerr, Bouwe P. Krijthe, Leo-Pekka Lyytikäinen, Christian Müller, Martina Müller-Nurasyid, Ilja M. Nolte, Sandosh Padmanabhan, Marylyn D. Ritchie, Antonietta Robino, Albert V. Smith, Maristella Steri, Toshiko Tanaka, Alexander Teumer, Stella Trompet, Sheila Ulivi, Niek Verweij, Xiaoyan Yin, David O. Arnar, Folkert W. Asselbergs, Joel S. Bader, John Barnard, Josh Bis, Stefan Blankenberg, Eric Boerwinkle, Yuki Bradford, Brendan M. Buckley, Mina K. Chung, Dana Crawford, Marcel den Hoed, Josh C. Denny, Anna F. Dominiczak, Georg B. Ehret, Mark Eijgelsheim, Patrick T. Ellinor, Stephan B. Felix, Oscar H. Franco, Lude Franke, Tamara B. Harris, Hilma Holm, Gandin Ilaria, Annamaria Iorio, Mika Kähönen, Ivana Kolcic, Jan A. Kors, Edward G. Lakatta, Lenore J. Launer, Honghuang Lin, Henry J. Lin, Ruth J. F. Loos, Steven A. Lubitz, Peter W. Macfarlane, Jared W. Magnani, Irene Mateo Leach, Thomas Meitinger, Braxton D. Mitchell, Thomas Munzel, George J. Papanicolaou, Annette Peters, Arne Pfeufer, Peter P. Pramstaller, Olli T. Raitakari, Jerome I. Rotter, Igor Rudan, Nilesh J. Samani, David Schlessinger, Claudia T. Silva Aldana, Moritz F. Sinner, Jonathan D. Smith, Harold Snieder, Elsayed Z. Soliman, Timothy D. Spector, David J. Stott, Konstantin Strauch, Kirill V. Tarasov, Unnur Thorsteinsdottir, Andre G. Uitterlinden, David R. Van Wagoner, Uwe Völker, Henry Völzke, Melanie Waldenberger, Harm Jan Westra, Philipp S. Wild, Tanja Zeller, Alvaro Alonso, Christy L. Avery, Stefania Bandinelli, Emelia J. Benjamin, Francesco Cucca, Marcus Dörr, Luigi Ferrucci, Paolo Gasparini, Vilmundur Gudnason, Caroline Hayward, Susan R. Heckbert, Andrew A. Hicks, J. Wouter Jukema, Stefan Kääb, Terho Lehtimäki, Yongmei Liu, Patricia B. Munroe, Afshin Parsa, Ozren Polasek, Bruce M. Psaty, Dan M. Roden, Renate B. Schnabel, Gianfranco Sinagra, Kari Stefansson, Bruno H. Stricker, Pim van der Harst, Cornelia M. van Duijn, James F. Wilson, Sina A. Gharib, Paul I. W. de Bakker, Aaron Isaacs, Dan E. Arking, and Nona Sotoodehnia
Subjects: Science
Abstract: Abnormal PR interval duration is associated with risk for atrial fibrillation and heart block. Here, van Setten et al. identify 44 PR interval loci in a genome-wide association study of over 92,000 individuals and find genetic overlap with QRS duration, heart rate and atrial fibrillation.
Published: 2018
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4. Uterine fibroid polygenic risk score (PRS) associates and predicts risk for uterine fibroid

Author: Jacqueline A. Piekos, Jacklyn N. Hellwege, Yanfei Zhang, Eric S. Torstenson, Gail P. Jarvik, Ozan Dikilitas, Iftikhar J. Kullo, Daniel J. Schaid, David R. Crosslin, Sarah A. Pendergrass, Ming Ta Michael Lee, Dan Roden, Josh C. Denny, Todd L. Edwards, and Digna R. Velez Edwards
Subjects: Genetics, Genetics (clinical)
Published: 2022

5. Cloud gazing: demonstrating paths for unlocking the value of cloud genomics through cross-cohort analysis

Author: Nicole Deflaux, Margaret Sunitha Selvaraj, Henry Robert Condon, Kelsey Mayo, Sara Haidermota, Melissa A. Basford, Chris Lunt, Anthony A. Philippakis, Dan M. Roden, Josh C. Denny, Anjene Musick, Rory Collins, Naomi Allen, Mark Effingham, David Glazer, Pradeep Natarajan, and Alexander G. Bick
Abstract: The rapid growth of genomic data has led to a new research paradigm where data are stored centrally in Trusted Research Environments (TREs) such as theAll of UsResearcher Workbench (AoU RW) and the UK Biobank Research Analysis Platform (RAP). To characterize the advantages and drawbacks of different TRE attributes in facilitating cross-cohort analysis, we conducted a Genome-Wide Association Study (GWAS) of standard lipid measures on the UKB RAP and AoU RW using two approaches: meta-analysis and pooled analysis. We curated lipid measurements for 37,754All of Usparticipants with whole genome sequence (WGS) data and 190,982 UK Biobank participants with whole exome sequence (WES) data. For the meta-analysis, we performed a GWAS of each cohort in their respective platform and meta-analyzed the results. We separately performed a pooled GWAS on both datasets combined. We identified 490 and 464 significant variants in meta-analysis and pooled analysis, respectively. Comparison of full summary data from both meta-analysis and pooled analysis with an external study showed strong correlation of known loci with lipid levels (R2∼83-97%). Importantly, 90 variants met the significance threshold only in the meta-analysis and 64 variants were significant only in pooled analysis. These method-specific differences may be explained by differences in cohort size, ancestry, and phenotype distributions inAll of Usand UK Biobank. We noted approximately 20% of variants significant in only the pooled analysis or significant in only the meta-analysis were most prevalent in non-European, non-Asian ancestry individuals. Pooled analyses included more variants than meta-analyses. Pooled analysis required about half as many computational steps as meta-analysis. These findings have important implications for both platform implementations and researchers undertaking large-scale cross-cohort analyses, as technical and policy choices lead to cross-cohort analyses generating similar, but not identical results, particularly for non-European ancestral populations.
Published: 2022

6. 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

7. Lossless integration of multiple electronic health records for identifying pleiotropy using summary statistics

Author: Josh C. Denny, Yong Chen, Ruowang Li, Xinyuan Zhang, Patrick M. A. Sleiman, Rui Duan, Thomas Lumley, Marylyn D. Ritchie, David Carrell, Christopher R. Bauer, Jason H. Moore, Wei-Qi Wei, Jonathan D. Mosley, Georgia L. Wiesner, Robert J. Carroll, Hakon Hakonarson, Digna R. Velez Edwards, Jordan W. Smoller, and Sarah A. Pendergrass
Subjects: 0301 basic medicine, Databases, Factual, Statistical methods, Computer science, Science, General Physics and Astronomy, Health records, Models, Biological, Polymorphism, Single Nucleotide, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, 0302 clinical medicine, Genetic Pleiotropy, Electronic Health Records, Humans, Generalizability theory, Statistical hypothesis testing, Lossless compression, Multidisciplinary, Communication, Genetic data, General Chemistry, Data science, Summary statistics, Phenotype, 030104 developmental biology, Pleiotropy (drugs), Privacy, Data integration, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Increasingly, clinical phenotypes with matched genetic data from bio-bank linked electronic health records (EHRs) have been used for pleiotropy analyses. Thus far, pleiotropy analysis using individual-level EHR data has been limited to data from one site. However, it is desirable to integrate EHR data from multiple sites to improve the detection power and generalizability of the results. Due to privacy concerns, individual-level patients’ data are not easily shared across institutions. As a result, we introduce Sum-Share, a method designed to efficiently integrate EHR and genetic data from multiple sites to perform pleiotropy analysis. Sum-Share requires only summary-level data and one round of communication from each site, yet it produces identical test statistics compared with that of pooled individual-level data. Consequently, Sum-Share can achieve lossless integration of multiple datasets. Using real EHR data from eMERGE, Sum-Share is able to identify 1734 potential pleiotropic SNPs for five cardiovascular diseases., Thus far, pleiotropy analysis using individual-level Electronic Health Records data has been limited to data from one site. Here, the authors introduce Sum-Share, a method designed to efficiently and losslessly integrate EHR and genetic data from multiple sites to perform pleiotropy analysis.
Published: 2021

8. Uterine fibroid polygenic risk score (PRS) associates and predicts risk for uterine fibroid

Author: Jacqueline A, Piekos, Jacklyn N, Hellwege, Yanfei, Zhang, Eric S, Torstenson, Gail P, Jarvik, Ozan, Dikilitas, Iftikhar J, Kullo, Daniel J, Schaid, David R, Crosslin, Sarah A, Pendergrass, Ming Ta Michael, Lee, Dan, Roden, Josh C, Denny, Todd L, Edwards, and Digna R, Velez Edwards
Subjects: Leiomyoma, Risk Factors, Humans, Female, Genetic Predisposition to Disease, Genomics, Linkage Disequilibrium, Genome-Wide Association Study
Abstract: Uterine fibroids (UF) are common pelvic tumors in women, heritable, and genome-wide association studies (GWAS) have identified ~ 30 loci associated with increased risk in UF. Using summary statistics from a previously published UF GWAS performed in a non-Hispanic European Ancestry (NHW) female subset from the Electronic Medical Records and Genomics (eMERGE) Network, we constructed a polygenic risk score (PRS) for UF. UF-PRS was developed using PRSice and optimized in the separate clinical population of BioVU. PRS was validated using parallel methods of 10-fold cross-validation logistic regression and phenome-wide association study (PheWAS) in a seperate subset of eMERGE NHW females (validation set), excluding samples used in GWAS. PRSice determined p
Published: 2021

9. 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

10. Effect of CYP4F2, VKORC1, and CYP2C9 in Influencing Coumarin Dose: A Single-Patient Data Meta-Analysis in More Than 15,000 Individuals

Author: Rajagopal Krishnamoorthy, Yusuke Nakamura, Alice Giontella, Elisa Danese, Munir Pirmohamed, Hoi Y. Tong, Angela Tagetti, Marie-Anne Loriot, Pietro Minuz, Anke H. Maitland-van der Zee, Sheng-Lan Tan, Jim K Burmester, Richard B. Kim, Jamila Alessandra Perini, Ming Ta Michael Lee, Nita A. Limdi, Min Huang, Mohamed H. Shahin, Guilherme Suarez-Kurtz, Vanessa Roldán, Carlos Isaza, Hersh Sagreiya, Hye Sun Gwak, Vijay Kumar Kutala, Han-Jing Cen, Russ B. Altman, Antonio J. Carcas, Kunihiko Itoh, Vaiva Lesauskaite, Richard L. Berg, Cristina Mazzaccara, Kyung Eun Lee, Mariana R. Botton, Jieying Eunice Zhang, Anthonius de Boer, Yumao Zhang, Inna Y. Gong, Marianne K. Kringen, Paola Borgiani, Taimour Y. Langaee, Monica Taljaard, Vacis Tatarunas, Panos Deloukas, Chrisly Dillon, Alberto M. Borobia, Michael D. Caldwell, Katarzyna Drozda, Larisa H. Cavallari, Julie A. Johnson, Stephane Bourgeois, Lucia Sacchetti, Saurabh Singh Rathore, Stuart A. Scott, Martina Montagnana, Li-Zi Zhao, Charles A. Rivers, Mahmut Ozer, Taisei Mushiroda, Cristina Lucía Dávila-Fajardo, Andras Paldi, Marisa Cañadas-Garre, Rocío González-Conejero, Talitha I. Verhoef, Sherief Khalifa, Ivet Suriapranata, Carlo Federico Zambon, Balraj Mittal, Sara Raimondi, Ece Genc, Virginie Siguret, Andrea H. Ramirez, Cinzia Ciccacci, Keita Hirai, Enrique Jiménez-Varo, Hong-Hao Zhou, Anil Pathare, Steven A. Lubitz, Josh C. Denny, Aditi Shendre, Leonardo Beltrán, Kari Bente Foss Haug, Cristiano Fava, Vittorio Pengo, Department of Biochemistry, Università degli Studi di Pavia = University of Pavia (UNIPV), Department of Morphological and Biomedical Sciences, Università degli studi di Verona = University of Verona (UNIVR), Laboratoire de Mécanique et d'Acoustique [Marseille] (LMA ), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Queen Mary University of London (QMUL), Merck and Co., Merck & Co. Inc, Innovations thérapeutiques en hémostase = Innovative Therapies in Haemostasis (IThEM - U1140), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Service d’Hématologie Biologique [CHU Lariboisière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Lariboisière-Fernand-Widal [APHP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Paediatric Pulmonology, Pulmonology, APH - Personalized Medicine, Danese, Elisa, Raimondi, Sara, Montagnana, Martina, Tagetti, Angela, Langaee, Taimour, Borgiani, Paola, Ciccacci, Cinzia, Carcas, Antonio J, Borobia, Alberto M, Tong, Hoi Y, Dávila-Fajardo, Cristina, Rodrigues Botton, Mariana, Bourgeois, Stephane, Deloukas, Pano, Caldwell, Michael D, Burmester, Jim K, Berg, Richard L, Cavallari, Larisa H, Drozda, Katarzyna, Huang, Min, Zhao, Li-Zi, Cen, Han-Jing, Gonzalez-Conejero, Rocio, Roldan, Vanessa, Nakamura, Yusuke, Mushiroda, Taisei, Gong, Inna Y, Kim, Richard B, Hirai, Keita, Itoh, Kunihiko, Isaza, Carlo, Beltrán, Leonardo, Jiménez-Varo, Enrique, Cañadas-Garre, Marisa, Giontella, Alice, Kringen, Marianne K, Haug, Kari Bente Fo, Gwak, Hye Sun, Lee, Kyung Eun, Minuz, Pietro, Lee, Ming Ta Michael, Lubitz, Steven A, Scott, Stuart, Mazzaccara, Cristina, Sacchetti, Lucia, Genç, Ece, Özer, Mahmut, Pathare, Anil, Krishnamoorthy, Rajagopal, Paldi, Andra, Siguret, Virginie, Loriot, Marie-Anne, Kutala, Vijay Kumar, Suarez-Kurtz, Guilherme, Perini, Jamila, Denny, Josh C, Ramirez, Andrea H, Mittal, Balraj, Rathore, Saurabh Singh, Sagreiya, Hersh, Altman, Ru, Shahin, Mohamed Hossam A, Khalifa, Sherief I, Limdi, Nita A, Rivers, Charle, Shendre, Aditi, Dillon, Chrisly, Suriapranata, Ivet M, Zhou, Hong-Hao, Tan, Sheng-Lan, Tatarunas, Vaci, Lesauskaite, Vaiva, Zhang, Yumao, Maitland-van der Zee, Anke H, Verhoef, Talitha I, de Boer, Anthoniu, Taljaard, Monica, Zambon, Carlo Federico, Pengo, Vittorio, Zhang, Jieying Eunice, Pirmohamed, Munir, Johnson, Julie A, and Fava, Cristiano
Subjects: CYP2C9, CYP4F2, VKORC1, coumarin drugs, meta-analysis, pharmacogenetics, predictive models, Male, medicine.medical_specialty, [SDV]Life Sciences [q-bio], 030226 pharmacology & pharmacy, Polymorphism, Single Nucleotide, Article, Cohort Studies, 03 medical and health sciences, 0302 clinical medicine, Coumarins, Internal medicine, Vitamin K Epoxide Reductases, Taverne, medicine, Humans, Pharmacology (medical), heterocyclic compounds, Dosing, Cytochrome P450 Family 4, Aged, Cytochrome P-450 CYP2C9, Pharmacology, Aged, 80 and over, Acenocoumarol, Dose-Response Relationship, Drug, business.industry, Middle Aged, Confidence interval, Settore MED/03 - Genetica Medica, 030220 oncology & carcinogenesis, Meta-analysis, Female, business, Pharmacogenetics, medicine.drug
Abstract: The CYP4F2 gene is known to influence mean coumarin dose. The aim of the present study was to undertake a meta-analysis at individual patients' level to capture the possible effect of ethnicity, gene-gene interaction or other drugs on the association and to verify if inclusion of CYP4F2*3 variant into dosing algorithms improves the prediction of mean coumarin dose. We asked the authors of our previous meta-analysis (30 articles) and of 38 new articles retrieved by a systematic review to send us individual patients' data. The final collection consists 15,754 patients split into a derivation and validation cohort. The CYP4F2*3 polymorphism was consistently associated with an increase in mean coumarin dose (+9% (95%CI 7-10%), with a higher effect in females, in patients taking acenocoumarol and in Whites. The inclusion of the CYP4F2*3 in dosing algorithms slightly improved the prediction of stable coumarin dose. New pharmacogenetic equations potentially useful for clinical practice were derived. This article is protected by copyright. All rights reserved.
Published: 2019

11. Arrhythmia variant associations and reclassifications in the eMERGE-III sequencing study

Author: Gail P. Jarvik, Carlos G. Vanoye, Reshma R. Desai, Lauren Lee Rinke, Hakon Hakonarson, Eric B. Larson, Ozan Dikilitas, Christian M. Shaffer, Zachary T. Yoneda, Ning Shang, George Hripcsak, Teri A. Manolio, Giovanni Davogustto, Bahram Namjou, Tooraj Mirshahi, Patrick Sleiman, Ayesha Muhammad, Elizabeth M. McNally, Olivia R. Kalash, Quinn S. Wells, Kathleen A. Leppig, Jonathan D. Mosley, Driest Slv, Jonathan Z. Luo, Daniel J. Schaid, Yuko Wada, Shoemaker Mb, Tao Yang, Wei-Qi Wei, Brett M. Kroncke, James D. Ralston, Sarah Bland, David Carrell, J. Glessner, Devyn Mitchell, Jennifer A. Pacheco, Cong Liu, Wendy K. Chung, Dan M. Roden, Chunhua Weng, Iftikhar J. Kullo, Tarek Alsaied, Sunghwan Sohn, Josh C. Denny, Adam S. Gordon, Rajbir Singh, Ashutosh Singhal, Alfred L. George, Eric Farber-Eger, and Andrew M. Glazer
Subjects: Long QT syndrome, Bioinformatics, Article, Genomic Medicine, Likely benign, Physiology (medical), medicine, Humans, Genetic Predisposition to Disease, Genetic Testing, Prospective Studies, Functional studies, Uncertain significance, Gene, Likely pathogenic, Disease gene, business.industry, Arrhythmias, Cardiac, Genomics, medicine.disease, Phenotype, Death, Sudden, Cardiac, HEK293 Cells, Cardiology and Cardiovascular Medicine, business
Abstract: Background: Sequencing Mendelian arrhythmia genes in individuals without an indication for arrhythmia genetic testing can identify carriers of pathogenic or likely pathogenic (P/LP) variants. However, the extent to which these variants are associated with clinically meaningful phenotypes before or after return of variant results is unclear. In addition, the majority of discovered variants are currently classified as variants of uncertain significance, limiting clinical actionability. Methods: The eMERGE-III study (Electronic Medical Records and Genomics Phase III) is a multicenter prospective cohort that included 21 846 participants without previous indication for cardiac genetic testing. Participants were sequenced for 109 Mendelian disease genes, including 10 linked to arrhythmia syndromes. Variant carriers were assessed with electronic health record–derived phenotypes and follow-up clinical examination. Selected variants of uncertain significance (n=50) were characterized in vitro with automated electrophysiology experiments in HEK293 cells. Results: As previously reported, 3.0% of participants had P/LP variants in the 109 genes. Herein, we report 120 participants (0.6%) with P/LP arrhythmia variants. Compared with noncarriers, arrhythmia P/LP carriers had a significantly higher burden of arrhythmia phenotypes in their electronic health records. Fifty-four participants had variant results returned. Nineteen of these 54 participants had inherited arrhythmia syndrome diagnoses (primarily long-QT syndrome), and 12 of these 19 diagnoses were made only after variant results were returned (0.05%). After in vitro functional evaluation of 50 variants of uncertain significance, we reclassified 11 variants: 3 to likely benign and 8 to P/LP. Conclusions: Genome sequencing in a large population without indication for arrhythmia genetic testing identified phenotype-positive carriers of variants in congenital arrhythmia syndrome disease genes. As the genomes of large numbers of people are sequenced, the disease risk from rare variants in arrhythmia genes can be assessed by integrating genomic screening, electronic health record phenotypes, and in vitro functional studies. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier; NCT03394859.
Published: 2021

12. A study paradigm integrating prospective epidemiologic cohorts and electronic health records to identify disease biomarkers

Author: Dan M. Roden, Thomas J. Wang, Quinn S. Wells, Murray H. Brilliant, David R. Crosslin, Eric B. Larson, Catherine A. McCarty, Gail P. Jarvik, Iftikhar J. Kullo, Jennifer A. Pacheco, Todd L. Edwards, Christopher G. Chute, Marylyn D. Ritchie, Lisa Bastarache, Melody R. Palmer, Kenneth M. Borthwick, Jonathan D. Mosley, Bahram Namjou, Sara L. Van Driest, Wei-Qi Wei, Adam S. Gordon, Jason H. Karnes, Scott T. Weiss, C. Michael Stein, Peggy L. Peissig, Lea K. Davis, Christian M. Shaffer, QiPing Feng, David Carrell, Josh C. Denny, William K. Thompson, Shefali S. Verma, Marc S. Williams, and James G. Linneman
Subjects: 0301 basic medicine, medicine.medical_specialty, Science, Population, General Physics and Astronomy, Computational biology, Disease, 030204 cardiovascular system & hematology, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, symbols.namesake, Bayes' theorem, 0302 clinical medicine, Risk Factors, Epidemiology, medicine, Electronic Health Records, Humans, SNP, Prospective Studies, education, lcsh:Science, education.field_of_study, Multidisciplinary, business.industry, Bayes Theorem, Cholesterol, LDL, General Chemistry, 3. Good health, 030104 developmental biology, Bonferroni correction, Cohort, symbols, Biomarker (medicine), lcsh:Q, business, Biomarkers, Genome-Wide Association Study
Abstract: Defining the full spectrum of human disease associated with a biomarker is necessary to advance the biomarker into clinical practice. We hypothesize that associating biomarker measurements with electronic health record (EHR) populations based on shared genetic architectures would establish the clinical epidemiology of the biomarker. We use Bayesian sparse linear mixed modeling to calculate SNP weightings for 53 biomarkers from the Atherosclerosis Risk in Communities study. We use the SNP weightings to computed predicted biomarker values in an EHR population and test associations with 1139 diagnoses. Here we report 116 associations meeting a Bonferroni level of significance. A false discovery rate (FDR)-based significance threshold reveals more known and undescribed associations across a broad range of biomarkers, including biometric measures, plasma proteins and metabolites, functional assays, and behaviors. We confirm an inverse association between LDL-cholesterol level and septicemia risk in an independent epidemiological cohort. This approach efficiently discovers biomarker-disease associations., Biomarker identification requires prohibitively large cohorts with gene expression and phenotype data. The approach introduced here learns polygenic predictors of expression from genetic and expression data, used to infer biomarker levels in patients with genetic and disease information.
Published: 2018

13. Clinical Features Associated With Nascent Left Ventricular Diastolic Dysfunction in a Population Aged 40 to 55 Years

Author: Quinn S. Wells, Dan M. Roden, Rebecca T. Levinson, Eric Farber-Eger, Christian M. Shaffer, Jonathan D. Mosley, Josh C. Denny, Evan L. Brittain, and Deepak K. Gupta
Subjects: Adult, Male, medicine.medical_specialty, Databases, Factual, Population, Diastole, Kaplan-Meier Estimate, 030204 cardiovascular system & hematology, Risk Assessment, Severity of Illness Index, Article, Cohort Studies, Ventricular Dysfunction, Left, 03 medical and health sciences, Age Distribution, 0302 clinical medicine, Internal medicine, medicine, Humans, 030212 general & internal medicine, Sex Distribution, education, Retrospective Studies, Heart Failure, Diastolic, education.field_of_study, Ejection fraction, business.industry, Incidence, Stroke Volume, Odds ratio, Middle Aged, Prognosis, medicine.disease, Survival Analysis, United States, Blood pressure, Diabetes Mellitus, Type 2, Echocardiography, Heart failure, Hypertension, Multivariate Analysis, Linear Models, Cardiology, Female, Transthoracic echocardiogram, Cardiology and Cardiovascular Medicine, business, Heart failure with preserved ejection fraction
Abstract: Diastolic dysfunction (DD), an abnormality in cardiac left ventricular (LV) chamber compliance, is associated with an increased risk of morbidity and mortality. While DD has been extensively studied in older populations, co-morbidity patterns are less well characterized among middle-aged individuals. We screened 156,434 subjects with transthoracic echocardiogram reports available through Vanderbilt’s de-identified electronic heath record data resource and identified 6,612 individuals 40–55 years old with LV ejection fraction ≥50% and diastolic function staging. We tested 452 incident and prevalent clinical diagnoses for associations with early stage (grade 1: impaired LV relaxation) DD versus normal function. Among 1,676 subjects with grade 1 DD we identified associations (FDR q
Published: 2018

14. Uncovering exposures responsible for birth season – disease effects: a global study

Author: Martijn J. Schuemie, Pierre Gentine, Sean D. Mooney, Pradipta Parhi, George Hripcsak, Riccardo Miotto, Donahue Smith, Patrick B. Ryan, Robert J. Carroll, Usman Iqbal, Rae Woong Park, Josh C. Denny, Li Li, Nicholas P. Tatonetti, Seng Chan You, Yu-Chuan Jack Li, Mary Regina Boland, Joel T. Dudley, and Phung Anh Nguyen
Subjects: 0301 basic medicine, Pregnancy, seasons, business.industry, Birth Month, environmental exposure, Type 2 Diabetes Mellitus, Health Informatics, Environmental exposure, Disease, Research and Applications, medicine.disease, Culprit, Confidence interval, 03 medical and health sciences, electronic health records, attention deficit hyperactivity disorder, 030104 developmental biology, 0302 clinical medicine, medicine, Attention deficit hyperactivity disorder, pregnancy, 030212 general & internal medicine, business, Demography
Abstract: Objective Birth month and climate impact lifetime disease risk, while the underlying exposures remain largely elusive. We seek to uncover distal risk factors underlying these relationships by probing the relationship between global exposure variance and disease risk variance by birth season. Material and Methods This study utilizes electronic health record data from 6 sites representing 10.5 million individuals in 3 countries (United States, South Korea, and Taiwan). We obtained birth month–disease risk curves from each site in a case-control manner. Next, we correlated each birth month–disease risk curve with each exposure. A meta-analysis was then performed of correlations across sites. This allowed us to identify the most significant birth month–exposure relationships supported by all 6 sites while adjusting for multiplicity. We also successfully distinguish relative age effects (a cultural effect) from environmental exposures. Results Attention deficit hyperactivity disorder was the only identified relative age association. Our methods identified several culprit exposures that correspond well with the literature in the field. These include a link between first-trimester exposure to carbon monoxide and increased risk of depressive disorder (R = 0.725, confidence interval [95% CI], 0.529-0.847), first-trimester exposure to fine air particulates and increased risk of atrial fibrillation (R = 0.564, 95% CI, 0.363-0.715), and decreased exposure to sunlight during the third trimester and increased risk of type 2 diabetes mellitus (R = −0.816, 95% CI, −0.5767, −0.929). Conclusion A global study of birth month–disease relationships reveals distal risk factors involved in causal biological pathways that underlie them.
Published: 2017

15. Heritability and genome-wide association study of benign prostatic hyperplasia (BPH) in the eMERGE network

Author: Peggy L. Peissig, Adam S. Gordon, Jacklyn N. Hellwege, Sarah C. Stallings, Murray H. Brilliant, Ning Shang, James G. Linneman, Hakon Hakonarson, David R. Crosslin, Eric S. Torstenson, Digna R. Velez Edwards, Shefali S. Verma, Todd L. Edwards, Kenneth M. Borthwick, George Hripcsak, Gail P. Jarvik, Josh C. Denny, Marylyn D. Ritchie, Robert J. Carroll, P. Sleiman, Dan M. Roden, and Parimala Devi
Subjects: Male, 0301 basic medicine, Oncology, medicine.medical_specialty, Genotyping Techniques, Inheritance Patterns, Prostatic Hyperplasia, lcsh:Medicine, Genome-wide association study, Disease, urologic and male genital diseases, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Prostate cancer, 0302 clinical medicine, Internal medicine, Genotype, medicine, Electronic Health Records, Humans, SNP, Genetic Predisposition to Disease, lcsh:Science, Aged, Aged, 80 and over, Multidisciplinary, business.industry, Gene Expression Profiling, lcsh:R, Prostate, Middle Aged, Heritability, medicine.disease, 3. Good health, 030104 developmental biology, Case-Control Studies, lcsh:Q, Benign prostatic hyperplasia (BPH), business, Chromosome 22, Biomarkers, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Benign prostatic hyperplasia (BPH) results in a significant public health burden due to the morbidity caused by the disease and many of the available remedies. As much as 70% of men over 70 will develop BPH. Few studies have been conducted to discover the genetic determinants of BPH risk. Understanding the biological basis for this condition may provide necessary insight for development of novel pharmaceutical therapies or risk prediction. We have evaluated SNP-based heritability of BPH in two cohorts and conducted a genome-wide association study (GWAS) of BPH risk using 2,656 cases and 7,763 controls identified from the Electronic Medical Records and Genomics (eMERGE) network. SNP-based heritability estimates suggest that roughly 60% of the phenotypic variation in BPH is accounted for by genetic factors. We used logistic regression to model BPH risk as a function of principal components of ancestry, age, and imputed genotype data, with meta-analysis performed using METAL. The top result was on chromosome 22 in SYN3 at rs2710383 (p-value = 4.6 × 10−7; Odds Ratio = 0.69, 95% confidence interval = 0.55–0.83). Other suggestive signals were near genes GLGC, UNCA13, SORCS1 and between BTBD3 and SPTLC3. We also evaluated genetically-predicted gene expression in prostate tissue. The most significant result was with increasing predicted expression of ETV4 (chr17; p-value = 0.0015). Overexpression of this gene has been associated with poor prognosis in prostate cancer. In conclusion, although there were no genome-wide significant variants identified for BPH susceptibility, we present evidence supporting the heritability of this phenotype, have identified suggestive signals, and evaluated the association between BPH and genetically-predicted gene expression in prostate.
Published: 2019

16. Surgical repair of bicuspid aortopathy at small diameters: Clinical and institutional factors

Author: Alexander P. Nissen, Van Thi Thanh Truong, Bader A. Alhafez, Jyothy J. Puthumana, Anthony L. Estrera, Simon C. Body, Siddharth K. Prakash, Eduardo Bossone, Rodolfo Citro, Simon Body, J. Daniel Muehlschlegel, Jasmine T. Shahram, Thy B. Nguyen, Vicenza Stefano Nistri, Dan Gilon, Ronen Durst, Carlo de Vincentiis, Francesca R. Pluchinotta, Thoralf M. Sundt, Hector I. Michelena, Giuseppe Limongelli, Patrick M. McCarthy, S. Chris Malaisrie, Aakash Bavishi, Malenka M. Bissell, Gordon S. Huggins, Victor Dayan, Francois Dagenais, Alessandro Della Corte, Evaldas Girdsaukas, Bo Yang, Kim Eagle, Dianna M. Milewicz, Tom C. Nguyen, Harleen K. Sandhu, Hazim J. Safi, Josh C. Denny, Arturo Evangelista, Laura Galian-Gay, Kim A. Eagle, Williams Ravekes, Harry C. Dietz, Kathryn W. Holmes, Jennifer Habashi, Scott A. LeMaire, Joseph S. Coselli, Shaine A. Morris, Cheryl L. Maslen, Howard K. Song, G. Michael Silberbach, Reed E. Pyeritz, Joseph E. Bavaria, Karianna Milewski, Richard B. Devereux, Jonathan W. Weinsaft, Mary J. Roman, Ralph V. Shohet, Nazli McDonnell, Federico M. Asch, H. Eser Tolunay, Patrice Desvigne-Nickens, Hung Tseng, Barbara L. Kroner, Nissen, A. P., Truong, V. T. T., Alhafez, B. A., Puthumana, J. J., Estrera, A. L., Body, S. C., Prakash, S. K., Bossone, E., Citro, R., Body, S., Muehlschlegel, J. D., Shahram, J. T., Nguyen, T. B., Stefano Nistri, V., Gilon, D., Durst, R., de Vincentiis, C., Pluchinotta, F. R., Sundt, T. M., Michelena, H. I., Limongelli, G., Mccarthy, P. M., Malaisrie, S. C., Bavishi, A., Bissell, M. M., Huggins, G. S., Dayan, V., Dagenais, F., Corte, A. D., Girdsaukas, E., Yang, B., Eagle, K., Milewicz, D. M., Nguyen, T. C., Sandhu, H. K., Safi, H. J., Denny, J. C., Evangelista, A., Galian-Gay, L., Eagle, K. A., Ravekes, W., Dietz, H. C., Holmes, K. W., Habashi, J., Lemaire, S. A., Coselli, J. S., Morris, S. A., Maslen, C. L., Song, H. K., Silberbach, G. M., Pyeritz, R. E., Bavaria, J. E., Milewski, K., Devereux, R. B., Weinsaft, J. W., Roman, M. J., Shohet, R. V., Mcdonnell, N., Asch, F. M., Tolunay, H. E., Desvigne-Nickens, P., Tseng, H., and Kroner, B. L.
Subjects: Registrie, Male, Time Factors, thoracic aortic aneurysm, Heart Valve Diseases, Patient characteristics, ascending aortic intervention, thoracic aortic dissection, 030204 cardiovascular system & hematology, 0302 clinical medicine, Bicuspid aortic valve, Aortic valve replacement, Bicuspid Aortic Valve Disease, Risk Factors, Registries, Heart Valve Prosthesis Implantation, Middle Aged, Dissection, Heart Valve Disease, Treatment Outcome, Elective Surgical Procedures, Aortic Valve, cardiovascular system, Cardiology, Female, Cardiology and Cardiovascular Medicine, Vascular Surgical Procedures, Human, Pulmonary and Respiratory Medicine, United State, Adult, medicine.medical_specialty, bicuspid aortic valve, Time Factor, Aortic Valve Insufficiency, Clinical Decision-Making, Thoracic aortic aneurysm, Risk Assessment, 03 medical and health sciences, Internal medicine, medicine, Humans, Limited evidence, Risk factor, Aged, Surgical repair, Cross-Sectional Studie, Elective Surgical Procedure, Aortic Aneurysm, Thoracic, business.industry, Risk Factor, Patient Selection, Aortic Valve Stenosis, medicine.disease, Aortic Valve Stenosi, United States, Cross-Sectional Studies, 030228 respiratory system, Surgery, business
Abstract: Objective: Bicuspid aortic valve is a common risk factor for thoracic aortic aneurysm and dissection. Guidelines for elective ascending aortic intervention (AAI) in bicuspid aortic valve are derived from limited evidence, and the extent of practice variation due to patient and provider characteristics is unknown. Using data from 2 large cardiovascular registries, we investigated factors that influence decisions for AAI. Methods: All bicuspid aortic valve cases with known aortic diameters and surgical status were included. We used multivariable logistic regression to profile predictors of isolated aortic valve replacement (AVR) or AVR+AAI, stratified by patient characteristics, surgical indications, and institution. Results: We studied 2861 subjects at 18 institutions from 1996 to 2015. The median aortic diameter of patients who underwent AVR+AAI varied widely across institutions (39-52 mm). Aortic diameters were
Published: 2019

17. Trans-ethnic association study of blood pressure determinants in over 750,000 individuals

Author: Dennis O. Mook-Kanamori, J M Gaziano, Harst Pvd., Derek Klarin, K A Birdwell, Josh C. Denny, Martin Farrall, Thibaud Boutin, Najim Lahrouchi, Nabi Shah, Scott M. Damrauer, Cecilia P. Chung, Neil Poulter, Herzig K-H., E E Siew, John Concato, Yan V. Sun, Sara M. Willems, Louise V. Wain, Philip S. Tsao, Massimo Mangino, Wei W-Q., Ioanna Ntalla, Brian S. Mautz, David Schlessinger, Daniel I. Chasman, Branwen J. Hennig, Christopher Newton-Cheh, Michael E. Matheny, Palmer Cna., Caroline Hayward, Zhao J-H., Eleftheria Zeggini, Paul Elliott, C M Lindgren, Praveen Surendran, Csaba P. Kovesdy, Jacob M. Keaton, Chengxiang Qiu, Claudia Langenberg, Christopher Oldmeadow, Stéphanie Debette, D.R. Velez Edwards, Evangelos Evangelou, Howson Jmm., Adriana M. Hung, Yaomin Xu, Nicholas J. Wareham, James P. Cook, Scott L. DuVall, Peter Almgren, Jacklyn N. Hellwege, Sébastien Thériault, Helen R. Warren, Jian'an Luan, Ching-Ti Liu, Christopher J. O'Donnell, Michael Boehnke, Peter S. Sever, Ruifang Li-Gao, Cassianne Robinson-Cohen, Robert A. Scott, Muralidharan Sargurupremraj, Mark J. Caulfield, Jarvelin M-R., Tim D. Spector, Todd L. Edwards, Elena V. Feofanova, Francesco Cucca, Jihwan Park, Savita Karthikeyan, J C Smith, Wilson Pwf., Markku Laakso, Ayush Giri, Christianne L. Roumie, Rojesh Shrestha, Claudia P. Cabrera, Kelly Cho, Laura J. Scott, Elvis A. Akwo, Yu Wang, Tom G. Richardson, Patricia B. Munroe, Eric S. Torstenson, Katalin Susztak, John Attia, Bruce M. Psaty, Aldi T. Kraja, Olle Melander, Nicholas J. Timpson, George Dedoussis, Paul M. Ridker, Niek Verweij, David Conen, Philippe Amouyel, Otis D. Wilson, Nuno Sepúlveda, 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), Cardiology, ACS - Heart failure & arrhythmias, Cardiovascular Centre (CVC), Luan, Jian'an [0000-0003-3137-6337], Zhao, Jing Hua [0000-0003-4930-3582], Surendran, Praveen [0000-0002-4911-6077], Karthikeyan, Savita [0000-0002-4798-5746], Langenberg, Claudia [0000-0002-5017-7344], Wareham, Nicholas [0000-0003-1422-2993], Howson, Joanna [0000-0001-7618-0050], and Apollo - University of Cambridge Repository
Subjects: Male, LOCI, Gene Expression, Physiology, Blood Pressure, Genome-wide association study, IDENTIFIES 8, Mice, 0302 clinical medicine, Ethnicity, PARTITIONING HERITABILITY, Genetics & Heredity, 0303 health sciences, Kidney, Blood Pressure-International Consortium of Exome Chip Studies, Million Veteran Program, PULSE PRESSURE, 11 Medical And Health Sciences, Middle Aged, Up-Regulation, 3. Good health, Pulse pressure, Kidney Tubules, medicine.anatomical_structure, VINTAGE, International Consortium for Blood Pressure, AUTOSOMAL-DOMINANT HYPERTENSION, Female, Life Sciences & Biomedicine, Understanding Society Scientific Group, Adolescent, Diastole, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, 03 medical and health sciences, Genetics, medicine, Animals, Humans, GENOME-WIDE ASSOCIATION, Gene, 030304 developmental biology, Genetic association, Science & Technology, 06 Biological Sciences, GLOBAL BURDEN, MEAN ARTERIAL, GENE, Blood pressure, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, SOLUBLE GUANYLYL CYCLASE, Transcriptome, 030217 neurology & neurosurgery, Genome-Wide Association Study, Developmental Biology
Abstract: International audience; In this trans-ethnic multi-omic study, we reinterpret the genetic architecture of blood pressure to identify genes, tissues, phenomes and medication contexts of blood pressure homeostasis. We discovered 208 novel common blood pressure SNPs and 53 rare variants in genome-wide association studies of systolic, diastolic and pulse pressure in up to 776,078 participants from the Million Veteran Program (MVP) and collaborating studies, with analysis of the blood pressure clinical phenome in MVP. Our transcriptome-wide association study detected 4,043 blood pressure associations with genetically predicted gene expression of 840 genes in 45 tissues, and mouse renal single-cell RNA sequencing identified upregulated blood pressure genes in kidney tubule cells.
Published: 2019

18. 570 A genome-wide association study in an African American cohort implicates IL-12A in acne

Author: Alex K. Shalek, Berta Almoguera, George Hripcsak, Maria C. Garzon, Christine T. Lauren, Travis K. Hughes, J. C. Love, E. Dabela, Josh C. Denny, Hakon Hakonarson, Krzysztof Kiryluk, Z. Dai, C. Wang, John Connolly, P. Sleiman, Lynn Petukhova, Chunhua Weng, Iuliana Ionita-Laza, Azim J. Khan, J. McGovern, L.E. Levin, Frank D. Mentch, M. Hayes, and Z. Yang
Subjects: African american, medicine.medical_specialty, business.industry, Genome-wide association study, Cell Biology, Dermatology, medicine.disease, Biochemistry, Cohort, medicine, business, Molecular Biology, Acne
Published: 2021

19. Developing an Algorithm to Detect Early Childhood Obesity in Two Tertiary Pediatric Medical Centers

Author: Jonathan Bickel, Cassandra Brady, Sara L. Van Driest, Keith Marsolo, John B. Harley, Ingrid A. Holm, Lixin Chen, Imre Solti, Bahram Namjou, Beth L. Cobb, Jacqueline Kirby, Yizhao Ni, Nancy A. Crimmins, Stephanie Kennebeck, Josh C. Denny, Todd Lingren, Lisa Bailey-Davis, Nandan Patibandla, Guergana Savova, Marc S. Williams, Ashton Roach, Vidhu V Thaker, and Isaac S. Kohane
Subjects: Male, 0301 basic medicine, Pediatric Obesity, Health Informatics, Comorbidity, Clinical decision support system, Childhood obesity, Machine Learning, 03 medical and health sciences, 0302 clinical medicine, Health Information Management, Health care, medicine, Humans, 030212 general & internal medicine, Early childhood, Medical diagnosis, Child, Tertiary Healthcare, business.industry, Unified Medical Language System, Infant, medicine.disease, Computer Science Applications, Early Diagnosis, 030104 developmental biology, Child, Preschool, Cohort, Female, business, RxNorm, Algorithm, Research Article
Abstract: SummaryThe objective of this study is to develop an algorithm to accurately identify children with severe early onset childhood obesity (ages 1–5.99 years) using structured and unstructured data from the electronic health record (EHR).Childhood obesity increases risk factors for cardiovascular morbidity and vascular disease. Accurate definition of a high precision phenotype through a standardize tool is critical to the success of large-scale genomic studies and validating rare monogenic variants causing severe early onset obesity.Rule based and machine learning based algorithms were developed using structured and unstructured data from two EHR databases from Boston Children’s Hospital (BCH) and Cincinnati Children’s Hospital and Medical Center (CCHMC). Exclusion criteria including medications or comorbid diagnoses were defined. Machine learning algorithms were developed using cross-site training and testing in addition to experimenting with natural language processing features.Precision was emphasized for a high fidelity cohort. The rule-based algorithm performed the best overall, 0.895 (CCHMC) and 0.770 (BCH). The best feature set for machine learning employed Unified Medical Language System (UMLS) concept unique identifiers (CUIs), ICD-9 codes, and RxNorm codes.Detecting severe early childhood obesity is essential for the intervention potential in children at the highest long-term risk of developing comorbidities related to obesity and excluding patients with underlying pathological and non-syndromic causes of obesity assists in developing a high-precision cohort for genetic study. Further such phenotyping efforts inform future practical application in health care environments utilizing clinical decision support.Citation: Lingren T, Thaker V, Brady C, Namjou B, Kennebeck S, Bickel J, Patibandla N, Ni Y, Van Driest SL, Chen L, Roach A, Cobb B, Kirby J, Denny J, Bailey-Davis L, Williams MS, Marsolo K, Solti I, Holm IA, Harley J, Kohane IS, Savova G, Crimmins N. Developing an algorithm to detect early childhood obesity in two tertiary pediatric medical centers.
Published: 2016

20. Physician response to implementation of genotype-tailored antiplatelet therapy

Author: John A. McPherson, Kevin B. Johnson, Ioana Danciu, Jonathan S. Schildcrout, Daniel C. Johnson, Josh C. Denny, Dan M. Roden, Michael Laposata, Yaping Shi, Kim M. Unertl, Jill M. Pulley, John H. Cleator, Josh F. Peterson, and Julie R. Field
Subjects: Male, medicine.medical_specialty, Ticlopidine, Genotype, Clinical Decision-Making, CYP2C19, 030204 cardiovascular system & hematology, 030226 pharmacology & pharmacy, Article, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, medicine, Humans, Pharmacology (medical), Prospective Studies, cardiovascular diseases, Practice Patterns, Physicians', Precision Medicine, Prospective cohort study, Aged, Pharmacology, business.industry, Hazard ratio, Age Factors, Genetic Variation, Middle Aged, Clopidogrel, Surgery, Cytochrome P-450 CYP2C19, Pharmacogenetics, Cohort, Platelet aggregation inhibitor, Female, Stents, business, Platelet Aggregation Inhibitors, medicine.drug
Abstract: Physician responses to genomic information are vital to the success of precision medicine initiatives. We prospectively studied a pharmacogenomics implementation program for the propensity of clinicians to select antiplatelet therapy based on CYP2C19 loss-of-function variants in stented patients. Among 2,676 patients, 514 (19.2%) were found to have a CYP2C19 variant affecting clopidogrel metabolism. For the majority (93.6%) of the cohort, cardiologists received active and direct notification of CYP2C19 status. Over 12 months, 57.6% of poor metabolizers and 33.2% of intermediate metabolizers received alternatives to clopidogrel. CYP2C19 variant status was the most influential factor impacting the prescribing decision (hazard ratio [HR] in poor metabolizers 8.1, 95% confidence interval [CI] [5.4, 12.2] and HR 5.0, 95% CI [4.0, 6.3] in intermediate metabolizers), followed by patient age and type of stent implanted. We conclude that cardiologists tailored antiplatelet therapy for a minority of patients with a CYP2C19 variant and considered both genomic and nongenomic risks in their clinical decision-making.
Published: 2016

21. Probing the virtual proteome to identify novel disease biomarkers

Author: Patrick M. A. Sleiman, Eric B. Larson, Mark D. Benson, Marylyn D. Ritchie, Iftikhar J. Kullo, Kenneth M. Borthwick, Adam S. Gordon, Robert E. Gerszten, James G. Linneman, Gail P. Jarvik, David R. Crosslin, Frank D. Mentch, Dan M. Roden, Catherine A. McCarty, Yineng Zhu, Qiong Yang, Krzysztof Kiryluk, Josh C. Denny, Christopher G. Chute, David Carrell, Peggy L. Peissig, J. Gustav Smith, Bahram Namjou, Shefali S. Verma, Jane F. Ferguson, Marc S. Williams, Jennifer A. Pacheco, Debby Ngo, Terrie Kitchner, Christian M. Shaffer, Ramachandran S. Vasan, Melody R. Palmer, Elizabeth W. Karlson, Jonathan D. Mosley, Murray H. Brilliant, Thomas J. Wang, Olle Melander, and Matthew Herzig
Subjects: 0301 basic medicine, False discovery rate, Apolipoprotein E, Adult, Carotid Artery Diseases, Male, Proteomics, Genotype, Proteome, Oligonucleotides, Computational biology, 030204 cardiovascular system & hematology, Polymorphism, Single Nucleotide, Article, Receptor, Platelet-Derived Growth Factor beta, 03 medical and health sciences, 0302 clinical medicine, Diet and cancer, Framingham Heart Study, Physiology (medical), Odds Ratio, Medicine, Humans, Lectins, C-Type, Biomarker discovery, Aged, Aged, 80 and over, business.industry, Odds ratio, Middle Aged, 030104 developmental biology, Phenotype, Female, Cardiology and Cardiovascular Medicine, business, Biomarkers, Genome-Wide Association Study
Abstract: Background: Proteomic approaches allow measurement of thousands of proteins in a single specimen, which can accelerate biomarker discovery. However, applying these technologies to massive biobanks is not currently feasible because of the practical barriers and costs of implementing such assays at scale. To overcome these challenges, we used a “virtual proteomic” approach, linking genetically predicted protein levels to clinical diagnoses in >40 000 individuals. Methods: We used genome-wide association data from the Framingham Heart Study (n=759) to construct genetic predictors for 1129 plasma protein levels. We validated the genetic predictors for 268 proteins and used them to compute predicted protein levels in 41 288 genotyped individuals in the Electronic Medical Records and Genomics (eMERGE) cohort. We tested associations for each predicted protein with 1128 clinical phenotypes. Lead associations were validated with directly measured protein levels and either low-density lipoprotein cholesterol or subclinical atherosclerosis in the MDCS (Malmö Diet and Cancer Study; n=651). Results: In the virtual proteomic analysis in eMERGE, 55 proteins were associated with 89 distinct diagnoses at a false discovery rate qP =0.006) per 1-SD increment in C-type lectin domain family 1 member B and 0.79 (0.66–0.94; P =0.008) per 1-SD increment in platelet-derived growth factor receptor-β. Conclusions: We demonstrate a biomarker discovery paradigm to identify candidate biomarkers of cardiovascular and other diseases.
Published: 2018

22. PR interval genome-wide association meta-analysis identifies 50 loci associated with atrial and atrioventricular electrical activity

Author: Bruno H. Stricker, Antonietta Robino, Gandin Ilaria, Marylyn D. Ritchie, Mark Eijgelsheim, Hilma Holm, Marcus Dörr, Philipp S. Wild, Jessica van Setten, Stephan B. Felix, Maristella Steri, Jared W. Magnani, Brendan M. Buckley, Peter P. Pramstaller, Claudia T. Silva Aldana, Niek Verweij, Tim D. Spector, Ruth J. F. Loos, Dan M. Roden, Martina Müller-Nurasyid, Mina K. Chung, Sandosh Padmanabhan, Stefania Bandinelli, Harm-Jan Westra, James F. Wilson, Honghuang Lin, Braxton D. Mitchell, Patrick T. Ellinor, Patricia B. Munroe, Harold Snieder, Thomas Münzel, Sheila Ulivi, Andrew A. Hicks, Nona Sotoodehnia, Daniel S. Evans, Annamaria Iorio, Peter W. Macfarlane, Vilmundur Gudnason, Christy L. Avery, Caroline Hayward, Cornelia M. van Duijn, John Barnard, Alvaro Alonso, Dana C. Crawford, Uwe Völker, David R. Van Wagoner, Tamara B. Harris, Harry Campbell, Ozren Polasek, Daniel F. Gudbjartsson, Ilja M. Nolte, Bouwe P. Krijthe, Eric Boerwinkle, Moritz F. Sinner, Elsayed Z. Soliman, Mika Kähönen, Christian Müller, Renate B. Schnabel, Unnur Thorsteinsdottir, Leo-Pekka Lyytikäinen, George J. Papanicolaou, Ivana Kolcic, Stella Trompet, Jerome I. Rotter, Dan E. Arking, Kirill V. Tarasov, Igor Rudan, Bruce M. Psaty, Gianfranco Sinagra, Alexander Teumer, Yalda Jamshidi, David O. Arnar, Toshiko Tanaka, Melanie Waldenberger, Henry J. Lin, Luigi Ferrucci, Susan R. Heckbert, Jan A. Kors, Irene Mateo Leach, Joel S. Bader, Konstantin Strauch, Albert V. Smith, Paul I.W. de Bakker, Stefan Blankenberg, J. C. Bis, Edward G. Lakatta, Lenore J. Launer, Thomas Meitinger, Anna F. Dominiczak, Marcel den Hoed, Steven A. Lubitz, Stefan Kääb, David J. Stott, Francesco Cucca, Olli T. Raitakari, Afshin Parsa, Nilesh J. Samani, Josh C. Denny, Lude Franke, Oscar H. Franco, Yongmei Liu, Folkert W. Asselbergs, Henry Völzke, Terho Lehtimäki, Arne Pfeufer, Annette Peters, David Schlessinger, Xiaoyan Yin, Jennifer A. Brody, J. Wouter Jukema, Paolo Gasparini, Tanja Zeller, Aaron Isaacs, Anne M. Butler, Sina A. Gharib, Kathleen F. Kerr, Jonathan D. Smith, Pim van der Harst, André G. Uitterlinden, Quince Gibson, Yuki Bradford, Brenton R. Swenson, Emelia J. Benjamin, Georg Ehret, Kari Stefansson, Fabiola M. Del Greco, Biochemie, RS: CARIM - R1.01 - Blood proteins & engineering, RS: CARIM - R1.06 - Genetic Epidemiology and Genomics of cardiovascular diseases, RS: FHML MaCSBio, van Setten, Jessica, Brody, Jennifer A, Jamshidi, Yalda, Swenson, Brenton R, Butler, Anne M, Campbell, Harry, Del Greco, Fabiola M, Evans, Daniel S, Gibson, Quince, Gudbjartsson, Daniel F, Kerr, Kathleen F, Krijthe, Bouwe P, Lyytikäinen, Leo-Pekka, Müller, Christian, Müller-Nurasyid, Martina, Nolte, Ilja M, Padmanabhan, Sandosh, Ritchie, Marylyn D, Robino, Antonietta, Smith, Albert V, Steri, Maristella, Tanaka, Toshiko, Teumer, Alexander, Trompet, Stella, Ulivi, Sheila, Verweij, Niek, Yin, Xiaoyan, Arnar, David O, Asselbergs, Folkert W, Bader, Joel S, Barnard, John, Bis, Josh, Blankenberg, Stefan, Boerwinkle, Eric, Bradford, Yuki, Buckley, Brendan M, Chung, Mina K, Crawford, Dana, den Hoed, Marcel, Denny, Josh C, Dominiczak, Anna F, Ehret, Georg B, Eijgelsheim, Mark, Ellinor, Patrick T, Felix, Stephan B, Franco, Oscar H, Franke, Lude, Harris, Tamara B, Holm, Hilma, Gandin, Ilaria, Iorio, Annamaria, Kähönen, Mika, Kolcic, Ivana, Kors, Jan A, Lakatta, Edward G, Launer, Lenore J, Lin, Honghuang, Lin, Henry J, Loos, Ruth J F, Lubitz, Steven A, Macfarlane, Peter W, Magnani, Jared W, Leach, Irene Mateo, Meitinger, Thoma, Mitchell, Braxton D, Munzel, Thoma, Papanicolaou, George J, Peters, Annette, Pfeufer, Arne, Pramstaller, Peter P, Raitakari, Olli T, Rotter, Jerome I, Rudan, Igor, Samani, Nilesh J, Schlessinger, David, Silva Aldana, Claudia T, Sinner, Moritz F, Smith, Jonathan D, Snieder, Harold, Soliman, Elsayed Z, Spector, Timothy D, Stott, David J, Strauch, Konstantin, Tarasov, Kirill V, Thorsteinsdottir, Unnur, Uitterlinden, Andre G, Van Wagoner, David R, Völker, Uwe, Völzke, Henry, Waldenberger, Melanie, Jan Westra, Harm, Wild, Philipp S, Zeller, Tanja, Alonso, Alvaro, Avery, Christy L, Bandinelli, Stefania, Benjamin, Emelia J, Cucca, Francesco, Dörr, Marcu, Ferrucci, Luigi, Gasparini, Paolo, Gudnason, Vilmundur, Hayward, Caroline, Heckbert, Susan R, Hicks, Andrew A, Jukema, J Wouter, Kääb, Stefan, Lehtimäki, Terho, Liu, Yongmei, Munroe, Patricia B, Parsa, Afshin, Polasek, Ozren, Psaty, Bruce M, Roden, Dan M, Schnabel, Renate B, Sinagra, Gianfranco, Stefansson, Kari, Stricker, Bruno H, van der Harst, Pim, van Duijn, Cornelia M, Wilson, James F, Gharib, Sina A, de Bakker, Paul I W, Isaacs, Aaron, Arking, Dan E, Sotoodehnia, Nona, Faculty of Medicine (UI), Læknadeild (HÍ), School of Engineering and Natural Sciences (UI), Verkfræði- og náttúruvísindasvið (HÍ), School of Health Sciences (UI), Heilbrigðisvísindasvið (HÍ), Háskóli Íslands (HÍ), University of Iceland (UI), Epidemiology, Medical Informatics, Internal Medicine, Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Cardiovascular Centre (CVC), and Stem Cell Aging Leukemia and Lymphoma (SALL)
Subjects: Male, QRS duration, Epidemiology, Genome-wide association study, Biochemistry, Linkage Disequilibrium, Electrocardiography, 0302 clinical medicine, Atrioventricular Conduction, lcsh:Science, COMMON VARIANTS, Heart Depolarization, Canal de iones, Cardiovascular system, Gene Locus, Blood, cardiovascular system, Qrs Interval, FIBRILLATION, Enfermedades cardiovasculares, Human, Missense Mutation, Heart block, Science, HEART-RATE, Single-nucleotide polymorphism, Missense/genetics, Physics and Astronomy(all), Factor de transcripción, European, General Biochemistry, Genetics and Molecular Biology, Article, PR interval genome, atrial electrical activity, atrioventricular electrical activity, 03 medical and health sciences, CARDIAC CONDUCTION, Cardiac conduction, Humans, Sistema cardiovascular, Common variants, Sangre, Cardiovascular genetics, medicine.disease, Heart-rate, Enfermedades, Electrophysiological Phenomena, 030104 developmental biology, Heart Block, Electric Activity, Mutation, lcsh:Q, Cell Junction, Cohorts, Meta-Analysis, 0301 basic medicine, Chemistry(all), Transcription Factor, General Physics and Astronomy, 030204 cardiovascular system & hematology, Fibrilación auricular, Electrophysiological Phenomena/genetics, RARE, Ion Channel, Heart Rate, Risk Factors, Atrial Fibrillation, EPIDEMIOLOGY, Bloqueo cardíaco, SNPS, Genetics, RISK, Multidisciplinary, Genome, Atrial fibrillation, Genetic Analysis, Atrioventricular Node/physiology, Atrial Function, Phenotype, Heart Disease, Rare, Atrioventricular Node, Female, medicine.symptom, QRS DURATION, Atrial Function/physiology, Medical Genetics, SNPs, Signal Transduction, Risk, Heart Diseases, Mutation, Missense, macromolecular substances, Biology, QRS complex, medicine, Disequilibrium, Linkage Disequilibrium/genetics, cardiovascular diseases, PR interval, Medicinsk genetik, Fibrillation, Biochemistry, Genetics and Molecular Biology(all), Risk Factor, African, General Chemistry, COHORTS, Pr Interval, Gene Linkage Disequilibrium, Genetics and Molecular Biology(all), Genome-Wide Association Study
Abstract: Publisher's version (útgefin grein). Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations., Electrocardiographic PR interval measures atrio-ventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. Our genome-wide association study of over 92,000 European-descent individuals identifies 44 PR interval loci (34 novel). Examination of these loci reveals known and previously not-yet-reported biological processes involved in cardiac atrial electrical activity. Genes in these loci are over-represented in cardiac disease processes including heart block and atrial fibrillation. Variants in over half of the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with missense variants. Six additional loci were identified either by meta-analysis of ~105,000 African and European-descent individuals and/or by pleiotropic analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation. These findings implicate developmental pathways, and identify transcription factors, ion-channel genes, and cell-junction/cell-signaling proteins in atrio-ventricular conduction, identifying potential targets for drug development., Acknowledgements per cohort are listed in Supplementary Note 2. We thank the following studies for sharing their summary level results: QRS voltage (van der Harst et al., 2016)[12], heart rate (den Hoed et al., 2013)[35], RR interval (Eijgelsheim et al., 2010)[11], atrial fibrillation (Christophersen et al., 2017[15]), and CARe-COGENT AA PR Consortium (Butler et al., 2012)[33]. We acknowledge Dr. Vinicius Tragante for his help generating the author list.
Published: 2018

23. Discovering patterns of pleiotropy in genome-wide association studies

Author: Harold Snieder, Moritz F. Sinner, Daniel F. Gudbjartsson, Niek Verweij, PM Pramstaller, B. D. Mitchell, Stephan B. Felix, Elsayed Z. Soliman, R. J. F. Loos, T.B. Harris, Mika Kähönen, Philipp S. Wild, Christy L. Avery, Kirill V. Tarasov, Stefania Bandinelli, Stefan Kääb, Tim D. Spector, Patrick T. Ellinor, David J. Stott, Renate B. Schnabel, Igor Rudan, O Polasekd, Brendan M. Buckley, Thomas Meitinger, James F. Wilson, Honghuang Lin, Gandin Ilaria, CM Duijn van, James P. Brody, L. J. Launer, Xiaoyan Yin, Ritchie, CT Aldana Silva, Paolo Gasparini, Dan M. Roden, Diane M. Crawford, Eric Boerwinkle, Davíð O. Arnar, Annette Peters, Caroline Hayward, Ilja M. Nolte, Terho Lehtimäki, Joop Jukema, Pi Bakker de, Thomas Münzel, Steven R. Cummings, Henry Völzke, Peter W. Macfarlane, John Barnard, Fabiola M Del Greco, Dan E. Arking, Anna F. Dominiczak, Patricia B. Munroe, Jonathan D. Smith, Anne M. Butler, Bruno H. Stricker, Stefan Blankenberg, Pv Harst der, S. Ulivi, Jerome I. Rotter, Hilma Holm, Alvaro Alonso, Haonan Lin, Gianfranco Sinagra, Alexander Teumer, Q Gibson, Bruce M. Psaty, Uwe Völker, Olli T. Raitakari, Annamaria Iorio, Bouwe P. Krijthe, Lude Franke, Folkert W. Asselbergs, Jared W. Magnani, G. Ehret, Susan R. Heckbert, L Ferrucci, Edward G. Lakatta, N. Sotoodehnia, Harry Campbell, Toshiko Tanaka, Wagoner van, JS Baderab, Yalda Jamshidi, Daniel S. Evans, David Schlessinger, Kari Stefansson, Nilesh J. Samani, Martina Müller-Nurasyid, Mark Eijgelsheim, Vilmundar Gudnason, Brenton R. Swenson, Sina A. Gharib, Kathleen F. Kerr, Josh C. Denny, Maristella Steri, E J Benjamin, George J. Papanicolaou, Unnur Thorsteinsdottir, Ivana Kolcic, Yuki Bradford, Mina K. Chung, Yongmei Liu, M. Waldenberger, Stella Trompet, Hoed, Jv Setten, Tanja Zeller, Jan A. Kors, Francesco Cucca, Irene Mateo Leach, A.G. Uitterlinden, Albert V. Smith, Craig Muller, Andrew A. Hicks, A Isaacs, Leo-Pekka Lyytikäinen, Konstantin Strauch, Steven A. Lubitz, Antonietta Robino, J Zhana, A. Pfeufer, Sandosh Padmanabhan, Afshin Parsa, Harm-Jan Westra, Marcus Dörr, and J. C. Bis
Subjects: False discovery rate, Linkage disequilibrium, Genotype-phenotype distinction, Pleiotropy, Genotype, SNP, Genome-wide association study, Computational biology, Biology, Genetic association
Abstract: MotivationGenome-wide association studies have had great success in identifying human genetic variants associated with disease, disease risk factors, and other biomedical phenotypes. Many variants are associated with multiple traits, even after correction for trait-trait correlation. Discovering subsets of variants associated with a shared subset of phenotypes could help reveal disease mechanisms, suggest new therapeutic options, and increase the power to detect additional variants with similar pattern of associations. Here we introduce two methods based on a Bayesian framework, SNP And Pleiotropic PHenotype Organization (SAPPHO), one modeling independent phenotypes (SAPPHO-I) and the other incorporating a full phenotype covariance structure (SAPPHO-C). These two methods learn patterns of pleiotropy from genotype and phenotype data, using identified associations to discover additional associations with shared patterns.ResultsThe SAPPHO methods, along with other recent approaches for pleiotropic association tests, were assessed using data from the Atherosclerotic Risk in Communities (ARIC) study of 8,000 individuals, whose gold-standard associations were provided by meta-analysis of 40,000 to 100,000 individuals from the CHARGE consortium. Using power to detect gold-standard associations at genome-wide significance (0.05 family-wise error rate) as a metric, SAPPHO performed best. The SAPPHO methods were also uniquely able to select the most significant variants in a parsimonious model, excluding other less likely variants within a linkage disequilibrium block. For meta-analysis, the SAPPHO methods implement summary modes that use sufficient statistics rather than full phenotype and genotype data. Meta-analysis applied to CHARGE detected 16 additional associations to the gold-standard loci, as well as 124 novel loci, at 0.05 false discovery rate. Reasons for the superior performance were explored by performing simulations over a range of scenarios describing different genetic architectures. With SAPPHO we were able to learn genetic structures that were hidden using the traditional univariate tests.Availabilityhttps://bitbucket.org/baderlab/fast/wiki/Home. SAPPHO software is available under the GNU General Public License, v2.
Published: 2018

24. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

Author: Alison Pattie, Ailith Pirie, Francis S. Collins, Charles Kooperberg, Nienke van Leeuwen, Carmel Moore, Sharon L.R. Kardia, Neil R. Robertson, Lisa Bastarache, Allan Linneberg, Peter T. Campbell, Helena Kuivaniemi, Struan F.A. Grant, Sascha Fauser, Sekar Kathiresan, Lars Lind, Erin B. Ware, Olli T. Raitakari, Dawn M. Waterworth, James G. Wilson, Markus Perola, Chris J. Packard, Michelle L. O'Donoghue, Fredrik Karpe, Roel A. Ophoff, Sailaja Vedantam, Artitaya Lophatananon, Uwe Völker, Emmanouil Tsafantakis, Hakon Hakonarson, Dajiang J. Liu, Craig E. Pennell, Xueling Sim, Jennifer E. Huffman, Sandosh Padmanabhan, Digna R. Velez Edwards, Michiel L. Bots, Ayush Giri, Renée de Mutsert, Emanuele Di Angelantonio, Nicholas J. Wareham, Jin Li, Gail P. Jarvik, Evangelos Evangelou, Anne Tybjærg-Hansen, Patricia B. Munroe, Penny Gordon-Larsen, Lia E. Bang, Ivan Brandslund, Hester M. den Ruijter, Jussi Hernesniemi, Nancy L. Heard-Costa, Angela L. Mazul, Jonathan Tyrer, Danish Saleheen, Mark J. Caulfield, John Andrew Pospisilik, Annette Peters, Caroline Hayward, Iris M. Heid, J. Wouter Jukema, Valérie Turcot, Matt Neville, Rudolf Uher, Patricia A. Peyser, Jessica D. Faul, Asif Rasheed, Shuai Wang, John C. Chambers, Jordi Corominas Galbany, Murray H. Brilliant, Yucheng Jia, Torben Hansen, Veikko Salomaa, Mary F. Feitosa, Mathias Gorski, Li-An Lin, George Dedoussis, Honghuang Lin, Ethan M. Lange, Veronique Vitart, Bratati Kahali, Alexander Teumer, Jerome I. Rotter, Wayne H-H Sheu, Vilmantas Giedraitis, Aliki-Eleni Farmaki, Lorraine Southam, Ele Ferrannini, Anette P. Gjesing, Krina T. Zondervan, Stavroula Kanoni, David J. Roberts, Rebecca S. Fine, Svati H. Shah, Tugce Karaderi, Claudia Langenberg, Stefan Johansson, Elizabeth K. Speliotes, Alexander P. Reiner, Ching-Ti Liu, Yiqin Wang, Pål R. Njølstad, Gabriel Cuellar-Partida, Amanda J. Cox, Tim D. Spector, Paul W. Franks, Anke Tönjes, John D. Rioux, Jeffrey Haessler, Paul L. Auer, Ingrid B. Borecki, Deborah J. Thompson, Weihua Zhang, John R. B. Perry, Paul Elliott, Folkert W. Asselbergs, Myriam Fornage, Ken Sin Lo, Marie Moitry, Paul Mitchell, Martin den Heijer, Zoltán Kutalik, Tune H. Pers, Kari Stefansson, Kari Kuulasmaa, Robert E. Schoen, Mark C.H. De Groot, Laura M. Yerges-Armstrong, Jing Hua Zhao, Beverley Balkau, Peggy L. Peissig, Michael Boehnke, Janie Corley, Katharine R. Owen, Unnur Thorsteinsdottir, Naveed Sattar, Sita H. Vermeulen, Thomas N. Person, Mark I. McCarthy, Paul I.W. de Bakker, David Lamparter, Poorva Mudgal, Nicholette D. Palmer, Maria Karaleftheri, Jan-Håkan Jansson, Ozren Polasek, Ruth J. F. Loos, Daniel R. Witte, Dermot F. Reilly, Anubha Mahajan, Stella Trompet, James A. Perry, Yingchang Lu, Claudia Schurmann, Yii-Der Ida Chen, Hidetoshi Kitajima, Dale R. Nyholt, John Danesh, Pamela J. Schreiner, Narisu Narisu, Jose C. Florez, Adelheid Lempradl, Gerome Breen, Torben Jørgensen, Anu Loukola, Joe Dennis, Hans-Jörgen Grabe, Vilmundur Gudnason, Timo A. Lakka, Heather M. Highland, Sven Bergmann, Marie-Pierre Dubé, Giovanni Veronesi, Martina Müller-Nurasyid, Jaakko Tuomilehto, Nele Friedrich, Joel N. Hirschhorn, Pia R. Kamstrup, Nilesh J. Samani, Josh C. Denny, Mika Kähönen, Massimiliano Cocca, Liang Sun, Karina Meidtner, Carsten A. Böger, Sara M. Willems, Marcelo P. Segura-Lepe, Johanna Kuusisto, Hanieh Yaghootkar, Konstantin Strauch, Ruth Frikke-Schmidt, Jane Gibson, Matti Uusitupa, Oscar H. Franco, Yongmei Liu, Heather M. Stringham, Rohit Varma, Grant W. Montgomery, Dennis O. Mook-Kanamori, Stefania Cappellani, Paul L. Huang, Albert V. Smith, Eric Kim, Anke R. Hammerschlag, Katherine S. Ruth, Carolina Medina-Gomez, Gerard Pasterkamp, Cristen J. Willer, Alisa K. Manning, Frida Renström, René S. Kahn, Lili Milani, Feijie Wang, Tessel E. Galesloot, Fernando Rivadeneira, Leo-Pekka Lyytikäinen, Adam S. Butterworth, Tamara B. Harris, Matthew A. Allison, Paul M. Ridker, David J. Carey, Todd L. Edwards, Panos Deloukas, Xiuqing Guo, Lawrence F. Bielak, Leena Moilanen, Heiner Boeing, Peter Kovacs, Karen L. Mohlke, Myriam Rheinberger, Cramer Christensen, Betina H. Thuesen, Mike A. Nalls, Erik Ingelsson, Nicholas G. D. Masca, Colin N. A. Palmer, Audrey E. Hendricks, Linda Broer, Vanisha Mistry, Praveen Surendran, Audrey Y. Chu, Rainer Rauramaa, Angela D'Eustacchio, Helen Griffiths, Satu Männistö, Patrick T. Ellinor, Terho Lehtimäki, Katherine E. Tansey, I. Sadaf Farooqi, Gaëlle Marenne, Anneke I. den Hollander, Jessica van Setten, Hannu Puolijoki, Tinca J. C. Polderman, Timothy M. Frayling, Niels Grarup, Eric Boerwinkle, Gonçalo R. Abecasis, Adam E. Locke, Mengmeng Du, Manuel A. Rivas, Philippe Amouyel, Jaakko Kaprio, Leslie A. Lange, Loes M. Olde Loohuis, Trevor A. Mori, Lambertus A. Kiemeney, Wei Zhao, Eva Rb Petersen, Huaixing Li, Thomas W. Winkler, Tellervo Korhonen, Kathleen Stirrups, Jean Ferrières, Wei Zhou, Ian J. Deary, Guillaume Lettre, M. Arfan Ikram, Alex W. Hewitt, Marit E. Jørgensen, Ian Ford, Liang He, Mark Walker, Stefan Gustafsson, Andre Franke, Yao Hu, Jaana Lindström, Jonathan P. Bradfield, Anne E. Justice, Kristin L. Young, Sander W. van der Laan, Shuang Feng, Yadav Sapkota, Douglas F. Easton, Cornelia M. van Duijn, Amy J. Swift, Kjell Nikus, Helen R. Warren, Christian Theil Have, Wei Gan, Steven A. Lubitz, Harvey D. White, Pirjo Komulainen, John M. Starr, Jeffrey R. O'Connel, Anette Varbo, Daniel I. Chasman, Ruifang Li-Gao, Lynne E. Wagenknecht, Matthias Blüher, Xiaowei Zhan, Thomas F. Vogt, Eleftheria Zeggini, Tamuno Alfred, Katja K.H. Aben, Lars Wallentin, Joanna M. M. Howson, Jie Yao, Eulalia Catamo, Henrik Vestergaard, Gina M. Peloso, Markku Laakso, Matthias B. Schulze, Hayato Tada, Jennifer Wessel, Andrew R. Wood, Erwin P. Bottinger, Cora E. Lewis, Robin Young, Carol A. Wang, Oddgeir L. Holmen, Andrew J. Slater, Jean-Claude Tardif, Xu Lin, Inês Barroso, Gail Davies, Tibor V. Varga, Andrew J. Lotery, Igor Rudan, Andrew T. Hattersley, Michael Stumvoll, David Ellinghaus, Andrew C. Heath, Frank Kee, Christopher P. Nelson, Donald W. Bowden, Alison M. Dunning, Marianne Benn, Oluf Pedersen, Amber A. Burt, Aniruddh P. Patel, G. Kees Hovingh, David S. Crosslin, Gorm B. Jensen, Keng-Hung Lin, Dewan S. Alam, Jian'an Luan, Ying Wu, Tõnu Esko, Kathleen Mullan Harris, Antonietta Robino, Anne U. Jackson, Eirini Marouli, Robert A. Scott, Jette Bork-Jensen, Olov Rolandsson, Nanette R. Lee, Gerard Tromp, Megan L. Grove, Suthesh Sivapalaratnam, Sameer E. Al-Harthi, Roberta McKean-Cowdin, Paolo Gasparini, Ellen W. Demerath, Marco Brumat, Maggie C.Y. Ng, Børge G. Nordestgaard, Kari E. North, Rajiv Chowdhury, Mauno Vanhala, Andrew P. Morris, Sarah E. Medland, Sune F. Nielsen, Ilaria Gandin, Øyvind Helgeland, James P. Cook, Kent D. Taylor, Andrew D. Morris, Gudmar Thorleifsson, André G. Uitterlinden, Pang Yao, Valgerdur Steinthorsdottir, Eric B. Larson, Kerrin S. Small, Cecilia M. Lindgren, Dragana Vuckovic, Mariaelisa Graff, Fotios Drenos, Jaspal S. Kooner, Schurmann, Claudia [0000-0003-4158-9192], Justice, Anne E [0000-0002-8903-8712], Giri, Ayush [0000-0002-7786-4670], Locke, Adam E [0000-0001-6227-198X], Young, Kristin L [0000-0003-0070-6145], Medina-Gomez, Carolina [0000-0001-7999-5538], Winkler, Thomas W [0000-0003-0292-5421], Zeggini, Eleftheria [0000-0003-4238-659X], Zhao, Wei [0000-0002-8301-9297], Zondervan, Krina T [0000-0002-0275-9905], Pospisilik, John A [0000-0002-9745-0977], Rivadeneira, Fernando [0000-0001-9435-9441], Deloukas, Panos [0000-0001-9251-070X], Apollo - University of Cambridge Repository, Vascular Medicine, ACS - Amsterdam Cardiovascular Sciences, ACS - Atherosclerosis & ischemic syndromes, Internal Medicine, Epidemiology, Obstetrics & Gynecology, Radiology & Nuclear Medicine, CHD Exome+ Consortium, EPIC-CVD Consortium, ExomeBP Consortium, Global Lipids Genetic Consortium, GoT2D Genes Consortium, EPIC InterAct Consortium, INTERVAL Study, ReproGen Consortium, T2D-Genes Consortium, MAGIC Investigators, Understanding Society Scientific Group, Biological Psychology, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, British Heart Foundation, Wellcome Trust, Medical Research Council (MRC), National Institute for Health Research, Home Office, National Institutes of Health, Imperial College Healthcare NHS Trust- BRC Funding, Turcot, Valérie, Lu, Yingchang, Highland, Heather M., Schurmann, Claudia, Justice, Anne E., Fine, Rebecca S., Bradfield, Jonathan P., Esko, Tõnu, Giri, Ayush, Graff, Mariaelisa, Guo, Xiuqing, Hendricks, Audrey E., Karaderi, Tugce, Lempradl, Adelheid, Locke, Adam E., Mahajan, Anubha, Marouli, Eirini, Sivapalaratnam, Suthesh, Young, Kristin L., Alfred, Tamuno, Feitosa, Mary F., Masca, Nicholas G. D., Manning, Alisa K., Medina-Gomez, Carolina, Mudgal, Poorva, Ng, Maggie C. Y., Reiner, Alex P., Vedantam, Sailaja, Willems, Sara M., Winkler, Thomas W., Abecasis, Gonçalo, Aben, Katja K., Alam, Dewan S., Alharthi, Sameer E., Allison, Matthew, Amouyel, Philippe, Asselbergs, Folkert W., Auer, Paul L., Balkau, Beverley, Bang, Lia E., Barroso, Inê, Bastarache, Lisa, Benn, Marianne, Bergmann, Sven, Bielak, Lawrence F., Blüher, Matthia, Boehnke, Michael, Boeing, Heiner, Boerwinkle, Eric, Böger, Carsten A., Bork-Jensen, Jette, Bots, Michiel L., Bottinger, Erwin P., Bowden, Donald W., Brandslund, Ivan, Breen, Gerome, Brilliant, Murray H., Broer, Linda, Brumat, Marco, Burt, Amber A., Butterworth, Adam S., Campbell, Peter T., Cappellani, Stefania, Carey, David J., Catamo, Eulalia, Caulfield, Mark J., Chambers, John C., Chasman, Daniel I., Chen, Yii-Der I., Chowdhury, Rajiv, Christensen, Cramer, Chu, Audrey Y., Cocca, Massimiliano, Collins, Francis S., Cook, James P., Corley, Janie, Corominas Galbany, Jordi, Cox, Amanda J., Crosslin, David S., Cuellar-Partida, Gabriel, D'Eustacchio, Angela, Danesh, John, Davies, Gail, Bakker, Paul I. W., Groot, Mark C. H., Mutsert, Renée, Deary, Ian J., Dedoussis, George, Demerath, Ellen W., Heijer, Martin, Hollander, Anneke I., Ruijter, Hester M., Dennis, Joe G., Denny, Josh C., Angelantonio, Emanuele, Drenos, Fotio, Du, Mengmeng, Dubé, Marie-Pierre, Dunning, Alison M., Easton, Douglas F., Edwards, Todd L., Ellinghaus, David, Ellinor, Patrick T., Elliott, Paul, Evangelou, Evangelo, Farmaki, Aliki-Eleni, Farooqi, I. Sadaf, Faul, Jessica D., Fauser, Sascha, Feng, Shuang, Ferrannini, Ele, Ferrieres, Jean, Florez, Jose C., Ford, Ian, Fornage, Myriam, Franco, Oscar H., Franke, Andre, Franks, Paul W., Friedrich, Nele, Frikke-Schmidt, Ruth, Galesloot, Tessel E., Gan, Wei, Gandin, Ilaria, Gasparini, Paolo, Gibson, Jane, Giedraitis, Vilmanta, Gjesing, Anette P., Gordon-Larsen, Penny, Gorski, Mathia, Grabe, Hans-Jörgen, Grant, Struan F. A., Grarup, Niel, Griffiths, Helen L., Grove, Megan L., Gudnason, Vilmundur, Gustafsson, Stefan, Haessler, Jeff, Hakonarson, Hakon, Hammerschlag, Anke R., Hansen, Torben, Harris, Kathleen Mullan, Harris, Tamara B., Hattersley, Andrew T., Have, Christian T., Hayward, Caroline, He, Liang, Heard-Costa, Nancy L., Heath, Andrew C., Heid, Iris M., Helgeland, Øyvind, Hernesniemi, Jussi, Hewitt, Alex W., Holmen, Oddgeir L., Hovingh, G. Kee, Howson, Joanna M. M., Hu, Yao, Huang, Paul L., Huffman, Jennifer E., Ikram, M. Arfan, Ingelsson, Erik, Jackson, Anne U., Jansson, Jan-Håkan, Jarvik, Gail P., Jensen, Gorm B., Jia, Yucheng, Johansson, Stefan, Jørgensen, Marit E., Jørgensen, Torben, Jukema, J. Wouter, Kahali, Bratati, Kahn, René S., Kähönen, Mika, Kamstrup, Pia R., Kanoni, Stavroula, Kaprio, Jaakko, Karaleftheri, Maria, Kardia, Sharon L. R., Karpe, Fredrik, Kathiresan, Sekar, Kee, Frank, Kiemeney, Lambertus A., Kim, Eric, Kitajima, Hidetoshi, Komulainen, Pirjo, Kooner, Jaspal S., Kooperberg, Charle, Korhonen, Tellervo, Kovacs, Peter, Kuivaniemi, Helena, Kutalik, Zoltán, Kuulasmaa, Kari, Kuusisto, Johanna, Laakso, Markku, Lakka, Timo A., Lamparter, David, Lange, Ethan M., Lange, Leslie A., Langenberg, Claudia, Larson, Eric B., Lee, Nanette R., Lehtimäki, Terho, Lewis, Cora E., Li, Huaixing, Li, Jin, Li-Gao, Ruifang, Lin, Honghuang, Lin, Keng-Hung, Lin, Li-An, Lin, Xu, Lind, Lar, Lindström, Jaana, Linneberg, Allan, Liu, Ching-Ti, Liu, Dajiang J., Liu, Yongmei, Lo, Ken S., Lophatananon, Artitaya, Lotery, Andrew J., Loukola, Anu, Luan, Jian'An, Lubitz, Steven A., Lyytikäinen, Leo-Pekka, Männistö, Satu, Marenne, Gaëlle, Mazul, Angela L., Mccarthy, Mark I., McKean-Cowdin, Roberta, Medland, Sarah E., Meidtner, Karina, Milani, Lili, Mistry, Vanisha, Mitchell, Paul, Mohlke, Karen L., Moilanen, Leena, Moitry, Marie, Montgomery, Grant W., Mook-Kanamori, Dennis O., Moore, Carmel, Mori, Trevor A., Morris, Andrew D., Morris, Andrew P., Müller-Nurasyid, Martina, Munroe, Patricia B., Nalls, Mike A., Narisu, Narisu, Nelson, Christopher P., Neville, Matt, Nielsen, Sune F., Nikus, Kjell, Njølstad, Pål R., Nordestgaard, Børge G., Nyholt, Dale R., O'Connel, Jeffrey R., O'Donoghue, Michelle L., Olde Loohuis, Loes M., Ophoff, Roel A., Owen, Katharine R., Packard, Chris J., Padmanabhan, Sandosh, Palmer, Colin N. A., Palmer, Nicholette D., Pasterkamp, Gerard, Patel, Aniruddh P., Pattie, Alison, Pedersen, Oluf, Peissig, Peggy L., Peloso, Gina M., Pennell, Craig E., Perola, Marku, Perry, James A., Perry, John R. B., Pers, Tune H., Person, Thomas N., Peters, Annette, Petersen, Eva R. B., Peyser, Patricia A., Pirie, Ailith, Polasek, Ozren, Polderman, Tinca J., Puolijoki, Hannu, Raitakari, Olli T., Rasheed, Asif, Rauramaa, Rainer, Reilly, Dermot F., Renström, Frida, Rheinberger, Myriam, Ridker, Paul M., Rioux, John D., Rivas, Manuel A., Roberts, David J., Robertson, Neil R., Robino, Antonietta, Rolandsson, Olov, Rudan, Igor, Ruth, Katherine S., Saleheen, Danish, Salomaa, Veikko, Samani, Nilesh J., Sapkota, Yadav, Sattar, Naveed, Schoen, Robert E., Schreiner, Pamela J., Schulze, Matthias B., Scott, Robert A., Segura-Lepe, Marcelo P., Shah, Svati H., Sheu, Wayne H. -H., Sim, Xueling, Slater, Andrew J., Small, Kerrin S., Smith, Albert V., Southam, Lorraine, Spector, Timothy D., Speliotes, Elizabeth K., Starr, John M., Stefansson, Kari, Steinthorsdottir, Valgerdur, Stirrups, Kathleen E., Strauch, Konstantin, Stringham, Heather M., Stumvoll, Michael, Sun, Liang, Surendran, Praveen, Swift, Amy J., Tada, Hayato, Tansey, Katherine E., Tardif, Jean-Claude, Taylor, Kent D., Teumer, Alexander, Thompson, Deborah J., Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Thuesen, Betina H., Tönjes, Anke, Tromp, Gerard, Trompet, Stella, Tsafantakis, Emmanouil, Tuomilehto, Jaakko, Tybjaerg-Hansen, Anne, Tyrer, Jonathan P., Uher, Rudolf, Uitterlinden, André G., Uusitupa, Matti, Laan, Sander W., Duijn, Cornelia M., Leeuwen, Nienke, Van Setten, Jessica, Vanhala, Mauno, Varbo, Anette, Varga, Tibor V., Varma, Rohit, Velez Edwards, Digna R., Vermeulen, Sita H., Veronesi, Giovanni, Vestergaard, Henrik, Vitart, Veronique, Vogt, Thomas F., Völker, Uwe, Vuckovic, Dragana, Wagenknecht, Lynne E., Walker, Mark, Wallentin, Lar, Wang, Feijie, Wang, Carol A., Wang, Shuai, Wang, Yiqin, Ware, Erin B., Wareham, Nicholas J., Warren, Helen R., Waterworth, Dawn M., Wessel, Jennifer, White, Harvey D., Willer, Cristen J., Wilson, James G., Witte, Daniel R., Wood, Andrew R., Wu, Ying, Yaghootkar, Hanieh, Yao, Jie, Yao, Pang, Yerges-Armstrong, Laura M., Young, Robin, Zeggini, Eleftheria, Zhan, Xiaowei, Zhang, Weihua, Zhao, Jing Hua, Zhao, Wei, Zhou, Wei, Zondervan, Krina T, Rotter, Jerome I., Pospisilik, John A., Rivadeneira, Fernando, Borecki, Ingrid B., Deloukas, Pano, Frayling, Timothy M., Lettre, Guillaume, North, Kari E., Lindgren, Cecilia M., Hirschhorn, Joel N., Loos, Ruth J. F., Internal medicine, AGEM - Endocrinology, metabolism and nutrition, Amsterdam Movement Sciences - Rehabilitation & Development, Amsterdam Movement Sciences - Restoration and Development, APH - Aging & Later Life, Physiology, and VU University medical center
Subjects: 0301 basic medicine, Male, ReproGen Consortium, MathematicsofComputing_GENERAL, Genome-wide association study, medicine.disease_cause, Sensory disorders Donders Center for Medical Neuroscience [Radboudumc 12], Body Mass Index, genetics [Obesity], 0302 clinical medicine, Gene Frequency, Glucose homeostasis, Adult, Animals, Drosophila/genetics, Energy Intake/genetics, Energy Metabolism/genetics, Female, Genetic Variation, Humans, Obesity/genetics, Proteins/genetics, Syndrome, 11 Medical and Health Sciences, 2. Zero hunger, Genetics, Genetics & Heredity, Mutation, CHD Exome+ Consortium, body mass index, TheoryofComputation_GENERAL, T2D-Genes Consortium, GENOME-WIDE ASSOCIATION, MELANOCORTIN-4 RECEPTOR GENE, DONEPEZIL 23 MG, FRAMESHIFT MUTATION, GLUCOSE-HOMEOSTASIS, HYPOTHALAMIC AMPK, CODING VARIANTS, BLOOD-PRESSURE, RARE, LOCI, Urological cancers Radboud Institute for Health Sciences [Radboudumc 15], Drosophila, ExomeBP Consortium, Life Sciences & Biomedicine, INTERVAL Study, Understanding Society Scientific Group, EPIC InterAct Consortium, genetics [Energy Metabolism], Biology, EPIC-CVD Consortium, Frameshift mutation, 03 medical and health sciences, MAGIC Investigators, All institutes and research themes of the Radboud University Medical Center, Genetic, SDG 3 - Good Health and Well-being, ddc:570, genetics [Drosophila], medicine, Journal Article, Global Lipids Genetic Consortium, Obesity, Gene, Allele frequency, Genetic association, Science & Technology, Proteins, 06 Biological Sciences, genetics [Proteins], Minor allele frequency, 030104 developmental biology, GoT2D Genes Consortium, Energy Intake, Energy Metabolism, genetics [Energy Intake], 030217 neurology & neurosurgery, Developmental Biology
Abstract: Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
Published: 2018

25. Genome-wide association meta-analysis of PR interval identifies 47 novel loci associated with atrial and atrioventricular electrical activity

Author: Aaron Isaacs, Sina A. Gharib, Kathleen F. Kerr, Lenore J. Launer, Yuki Bradford, J. Wouter Jukema, Stefan Kääb, Ruth J. F. Loos, Philipp S. Wild, Igor Rudan, Moritz F. Sinner, Annamaria Iorio, David J. Stott, Sheila Ulivi, Martina Müller-Nurasyid, Jerome I. Rotter, Andrew A. Hicks, Leo-Pekka Lyytikäinen, Vilmundur Gudnason, Dan M. Roden, Dana C. Crawford, James F. Wilson, Renate B. Schnabel, Eric Boerwinkle, Mina K. Chung, M. Fabiola Del Greco, Jan A. Kors, Honghuang Lin, Dan E. Arking, Annette Peters, Daniel S. Evans, Kari Stefansson, Francesco Cucca, Harold Snieder, Nona Sotoodehnia, Claudia T. Silva Aldana, Paul I.W. de Bakker, David Schlessinger, Pim van der Harst, Irene Mateo Leach, Kirill V. Tarasov, Marylyn D. Ritchie, Xiaoyan Yin, Marcus Dörr, Jennifer A. Brody, Patrick T. Ellinor, Olli T. Raitakari, Christy L. Avery, Peter W. Macfarlane, Paolo Gasparini, Susan R. Heckbert, John Barnard, Jessica van Setten, Anna F. Dominiczak, Henry Völzke, Edward G. Lakatta, Nilesh J. Samani, Tamara B. Harris, Brenton R. Swenson, Joel S. Bader, Thomas Münzel, Patricia B. Munroe, Hilma Holm, Stefania Bandinelli, Christian Müller, Bruno H. Stricker, Oscar H. Franco, Yongmei Liu, Ivana Kolcic, Peter P. Pramstaller, Josh C. Denny, Maristella Steri, Henry J. Lin, Luigi Ferrucci, Arne Pfeufer, Antonietta Robino, Bruce M. Psaty, Niek Verweij, Lude Franke, Mark Eijgelsheim, Afshin Parsa, Toshiko Tanaka, Folkert W. Asselbergs, Terho Lehtimäki, Stella Trompet, Alvaro Alonso, Harm-Jan Westra, David O. Arnar, Jared W. Magnani, Bouwe P. Krijthe, Cornelia M. van Duijn, Brendan M. Buckley, Jonathan D. Smith, Tim D. Spector, George J. Papanicolaou, Anne M. Butler, Emelia J. Benjamin, Tanja Zeller, Quince Gibson, David R. Van Wagoner, André G. Uitterlinden, Albert V. Smith, Stephan B. Felix, Uwe Völker, Yalda Jamshidi, Ozren Polasek, Daniel F. Gudbjartsson, Harry Campbell, Caroline Hayward, Ilja M. Nolte, Elsayed Z. Soliman, Georg Ehret, Mika Kähönen, Konstantin Strauch, Steven A. Lubitz, Melanie Waldenberger, Alexander Teumer, Sandosh Padmanabhan, Braxton D. Mitchell, Gianfranco Sinagra, Gandin Ilaria, Thomas Meitinger, Marcel den Hoed, Stefan Blankenberg, and J. C. Bis
Subjects: Genetics, QRS complex, Heart block, medicine, cardiovascular system, Missense mutation, Genome-wide association study, Atrial fibrillation, PR interval, Biology, medicine.disease, Genome, Gene
Abstract: Electrocardiographic PR interval measures atrial and atrioventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. We performed a genome-wide association study in over 92,000 individuals of European descent and identified 44 loci associated with PR interval (34 novel). Examination of the 44 loci revealed known and novel biological processes involved in cardiac atrial electrical activity, and genes in these loci were highly over-represented in several cardiac disease processes. Nearly half of the 61 independent index variants in the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with one or more missense variants. Cardiac regulatory regions of the genome as measured by cardiac DNA hypersensitivity sites were enriched for variants associated with PR interval, compared to non-cardiac regulatory regions. Joint analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation identified additional new pleiotropic loci. The majority of associations discovered in European-descent populations were also present in African-American populations. Meta-analysis examining over 105,000 individuals of African and European descent identified additional novel PR loci. These additional analyses identified another 13 novel loci. Together, these findings underscore the power of GWAS to extend knowledge of the molecular underpinnings of clinical processes.
Published: 2018
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26. Rare Variants in the Gene ALPL That Cause Hypophosphatasia Are Strongly Associated With Ovarian and Uterine Disorders

Author: Derek K. Smith, Daniel R Tilden, Margo Black, Jeremy L. Warner, Lisa Bastarache, Andrea H. Ramirez, Aliya Gifford, Jill S Simmons, John H. Newman, Kathryn Dahir, and Josh C. Denny
Subjects: 0301 basic medicine, Adult, Male, medicine.medical_specialty, Genotype, Endocrinology, Diabetes and Metabolism, Clinical Biochemistry, DNA Mutational Analysis, Hypophosphatasia, 030209 endocrinology & metabolism, Context (language use), Biochemistry, Gastroenterology, Polymorphism, Single Nucleotide, 03 medical and health sciences, 0302 clinical medicine, Endocrinology, Gene Frequency, Polymorphism (computer science), Internal medicine, medicine, Humans, Genetic Predisposition to Disease, Ovarian Diseases, Allele, Allele frequency, Alleles, Clinical Research Articles, Aged, Aged, 80 and over, Uterine Diseases, business.industry, Biochemistry (medical), ALPL, Middle Aged, medicine.disease, Alkaline Phosphatase, 030104 developmental biology, Phenotype, Mutation, Biomarker (medicine), Female, business
Abstract: Context Mutations in alkaline phosphatase (AlkP), liver/bone/kidney (ALPL), which encodes tissue-nonspecific isozyme AlkP, cause hypophosphatasia (HPP). HPP is suspected by a low-serum AlkP. We hypothesized that some patients with bone or dental disease have undiagnosed HPP, caused by ALPL variants. Objective Our objective was to discover the prevalence of these gene variants in the Vanderbilt University DNA Biobank (BioVU) and to assess phenotypic associations. Design We identified subjects in BioVU, a repository of DNA, that had at least one of three known, rare HPP disease-causing variants in ALPL: rs199669988, rs121918007, and/or rs121918002. To evaluate for phenotypic associations, we conducted a sequential phenome-wide association study of ALPL variants and then performed a de-identified manual record review to refine the phenotype. Results Out of 25,822 genotyped individuals, we identified 52 women and 53 men with HPP disease-causing variants in ALPL, 7/1000. None had a clinical diagnosis of HPP. For patients with ALPL variants, the average serum AlkP levels were in the lower range of normal or lower. Forty percent of men and 62% of women had documented bone and/or dental disease, compatible with the diagnosis of HPP. Forty percent of the female patients had ovarian pathology or other gynecological abnormalities compared with 15% seen in controls. Conclusions Variants in the ALPL gene cause bone and dental disease in patients with and without the standard biomarker, low plasma AlkP. ALPL gene variants are more prevalent than currently reported and underdiagnosed. Gynecologic disease appears to be associated with HPP-causing variants in ALPL.
Published: 2017

27. Evaluation of the F2R IVS-14A/T PAR1 polymorphism with subsequent cardiovascular events and bleeding in patients who have undergone percutaneous coronary intervention

Author: Dan M. Roden, Eitan A. Friedman, Luisa Texeira, Peter Weeke, Jessica T. Delaney, Heidi E. Hamm, Frank E. Harrell, John H. Cleator, Josh C. Denny, Yanna Song, Donald R Lynch, and Ehab S. Kasasbeh
Subjects: Male, medicine.medical_specialty, medicine.medical_treatment, Population, Myocardial Infarction, Coronary Artery Disease, Postoperative Hemorrhage, 030204 cardiovascular system & hematology, Lower risk, Coronary artery disease, 03 medical and health sciences, Percutaneous Coronary Intervention, 0302 clinical medicine, Internal medicine, medicine, Humans, Receptor, PAR-1, cardiovascular diseases, 030212 general & internal medicine, Myocardial infarction, education, Aged, Vorapaxar, Aged, 80 and over, education.field_of_study, Polymorphism, Genetic, business.industry, Percutaneous coronary intervention, Hematology, Middle Aged, medicine.disease, Surgery, Stroke, Conventional PCI, Cardiology, Female, Cardiology and Cardiovascular Medicine, business, Mace, medicine.drug
Abstract: Abnormal platelet reactivity is associated with recurrent ischemia and bleeding following percutaneous coronary intervention (PCI). Protease-activated receptor-1 (PAR1), encoded by F2R, is a high affinity thrombin receptor on platelets and the target of the antiplatelet drug vorapaxar. The intronic single nucleotide polymorphism F2R IVS-14 A/T affects PAR1 receptor density and function. We hypothesized that carriers of the T allele, who have been shown to have decreased platelet reactivity, would be at lower risk for thrombotic events, but higher risk for bleeding following PCI. Using BioVU, the Vanderbilt DNA repository linked to the electronic medical record, we studied 660 patients who underwent PCI for unstable or stable coronary artery disease. Primary outcome measures were major adverse cardiovascular events (MACE, composite of revascularization, MI, stroke, death) and bleeding (assessed by Bleeding Academic Research Consortium scale) over 24 months. The minor allele (T) frequency was 14.8 %. There were no genotypic differences in the frequency of MACE (33.7, 28.8, and 31.6 % for A/A, A/T, and T/T respectively, P = 0.50) or bleeding (15.7, 14.7, and 18.8 % for A/A, A/T, and T/T respectively, P = 0.90). In a Cox regression model, fully adjusted for age, race, sex, BMI, and smoking status, carrying a T allele was not associated with MACE (HR 1.19, 95 % CI 0.89-1.59, P = 0.23) or bleeding (HR 0.73, 95 % CI 0.37-1.4, P = 0.34). In conclusion, in our population, F2R IVS-14 PAR1 variability does not affect risk of MACE or bleeding following PCI.
Published: 2015

28. Investigating the Genetic Architecture of the PR Interval Using Clinical Phenotypes

Author: Iftikhar J. Kullo, Dawood Darbar, Jonathan D. Mosley, Dan M. Roden, David R. Crosslin, Christian M. Shaffer, Eric B. Larson, Catherine A. McCarty, Murray H. Brilliant, Quinn S. Wells, M. Benjamin Shoemaker, Jennifer A. Pacheco, Christopher G. Chute, Gail P. Jarvik, James G. Linneman, John S. Witte, Todd L. Edwards, Peggy L. Peissig, Lisa Bastarache, Josh C. Denny, and William K. Thompson
Subjects: Male, 0301 basic medicine, Medical Biotechnology, Cardiorespiratory Medicine and Haematology, Cardiovascular, Bioinformatics, molecular epidemiology, Body Mass Index, Electrocardiography, Risk Factors, Atrial Fibrillation, Odds Ratio, 2.1 Biological and endogenous factors, Aetiology, Genetics (clinical), Metabolic Syndrome, Genetics, Atrial fibrillation, Single Nucleotide, Middle Aged, Phenotype, Heart Disease, biomarker, Biomarker (medicine), Female, Waist Circumference, Cardiology and Cardiovascular Medicine, Adult, Adolescent, Genotype, Polymorphism, Single Nucleotide, Genetic correlation, Article, Young Adult, 03 medical and health sciences, medicine, Humans, Polymorphism, PR interval, Aged, business.industry, Odds ratio, Atherosclerosis, medicine.disease, Confidence interval, Genetic architecture, Good Health and Well Being, 030104 developmental biology, Cardiovascular System & Hematology, Case-Control Studies, business, cardiac electrophysiology
Abstract: Background— One potential use for the PR interval is as a biomarker of disease risk. We hypothesized that quantifying the shared genetic architectures of the PR interval and a set of clinical phenotypes would identify genetic mechanisms contributing to PR variability and identify diseases associated with a genetic predictor of PR variability. Methods and Results— We used ECG measurements from the ARIC study (Atherosclerosis Risk in Communities; n=6731 subjects) and 63 genetically modulated diseases from the eMERGE network (Electronic Medical Records and Genomics; n=12 978). We measured pairwise genetic correlations (rG) between PR phenotypes (PR interval, PR segment, P-wave duration) and each of the 63 phenotypes. The PR segment was genetically correlated with atrial fibrillation (rG=−0.88; P =0.0009). An analysis of metabolic phenotypes in ARIC also showed that the P wave was genetically correlated with waist circumference (rG=0.47; P =0.02). A genetically predicted PR interval phenotype based on 645 714 single-nucleotide polymorphisms was associated with atrial fibrillation (odds ratio=0.89 per SD change; 95% confidence interval, 0.83–0.95; P =0.0006). The differing pattern of associations among the PR phenotypes is consistent with analyses that show that the genetic correlation between the P wave and PR segment was not significantly different from 0 (rG=−0.03 [0.16]). Conclusions— The genetic architecture of the PR interval comprises modulators of atrial fibrillation risk and obesity.
Published: 2017

29. 001 Genome-wide association study of acne inversa in a multi-ethnic cohort

Author: Josh C. Denny, P. Sleiman, Chunhua Weng, Lynn Petukhova, M. Hayes, Krzysztof Kiryluk, John Connolly, Frank D. Mentch, G.M. Hripcsak, Hakon Hakonarson, and Azim J. Khan
Subjects: medicine.medical_specialty, business.industry, Ethnic group, Genome-wide association study, Cell Biology, Dermatology, medicine.disease, Biochemistry, Cohort, Medicine, business, Molecular Biology, Acne
Published: 2019

30. 854 GWAS of acne vulgaris among African Americans

Author: Azim J. Khan, Frank D. Mentch, Lynn Petukhova, Hakon Hakonarson, George Hripcsak, Krzysztof Kiryluk, John Connolly, Josh C. Denny, M. Hayes, C. Wang, and Berta Almoguera
Subjects: medicine.medical_specialty, business.industry, medicine, Genome-wide association study, Cell Biology, Dermatology, medicine.disease, business, Molecular Biology, Biochemistry, Acne
Published: 2019

31. PRECISION MEDICINE: DATA AND DISCOVERY FOR IMPROVED HEALTH AND THERAPY

Author: Sean D. Mooney, Bruce J. Aronow, Josh C. Denny, Alexander A. Morgan, Dana C. Crawford, and Steven E. Brenner
Subjects: 0301 basic medicine, Social network, business.industry, Computer science, MEDLINE, Personalized health, Precision medicine, Data science, Article, Session (web analytics), 03 medical and health sciences, 030104 developmental biology, Data acquisition, Biomedical data, Knowledge integration, business
Abstract: The major goal of precision medicine is to improve human health. A feature that unites much research in the field is the use of large datasets such as genomic data and electronic health records. Research in this field includes examination of variation in the core bases of DNA and their methylation status, through variations in metabolic and signaling molecules, all the way up to broader systems level changes in physiology and disease presentation. Intermediate goals include understanding the individual drivers of disease that differentiate the cause of disease in each individual. To match this development of approaches to physical and activity-based measurements, computational approaches to using these new streams of data to better understand improve human health are being rapidly developed by the thriving biomedical informatics research community. This session of the 2017 Pacific Symposium of Biocomputing presents some of the latest advances in the capture, analysis and use of diverse biomedical data in precision medicine.
Published: 2016

32. Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease

Author: Adnan Kastrati, Wu Yin, Jeanette Erdmann, Ruth J. F. Loos, Paul L. Auer, Susanne Moebus, Christina Willenborg, Piera Angelica Merlini, Jochen Kruppa, Anubha Mahajan, Julian C. van Capelleveen, Christa Meisinger, Charles Kooperberg, Natalie R. van Zuydam, Domenico Girelli, Erik P A Van Iperen, Rebecca D. Jackson, Tom R. Webb, Dan M. Roden, Ursula M. Schick, Colin N. A. Palmer, Eli A. Stahl, Mark I. McCarthy, Andres Metspalu, David-Alexandre Trégouët, Markus Perola, Kathleen Stirrups, G. Kees Hovingh, Martina Mueller-Nurasyid, Maris Alver, Christopher Newton-Cheh, Daniel J. Rader, Karl-Heinz Joeckel, Karen O. Akinsanya, Nilesh J. Samani, Alistair S. Hall, Stefano Duga, Louise A. Donnelly, J. Wouter Jukema, Nour Eddine El-Mokhtari, Rosanna Asselta, Tibor V. Varga, Heribert Schunkert, Erwin P. Bottinger, Paola G. Ferrario, Nathan O. Stitziel, Nicola Marziliano, Marie-Pierre Dubé, Andre Franke, Robert A. Scott, Thomas Meitinger, Stavroula Kanoni, Jan-Håkan Jansson, Christian Hengstenberg, Svati H. Shah, Josh C. Denny, Melanie Waldenberger, Alex S. F. Doney, Nicola Martinelli, Cristen J. Willer, Olle Melander, Hugh Watkins, He Zhang, Inke R. Koenig, Ron Do, Thomas F. Vogt, Chunyu Liu, Omri Gottesman, Kari Kuulasmaa, Peter S. Braund, Praveen Surendran, Dermot F. Reilly, Per Hoffmann, Georg Ehret, Karl L. Laugwitz, Diego Ardissino, Børge G. Nordestgaard, Joanna M. M. Howson, Raimund Erbel, Stefan A. Escher, Wolfgang Lieb, Hong-Hee Won, Majid Nikpay, Martin Farrall, Stefanie Heilmann, Ruth McPherson, Nicholas G. D. Masca, Evelin Mihailov, Danish Saleheen, Andrew D. Morris, Neil R. Robertson, Oddgeir L. Holmen, Sekar Kathiresan, Annette Peters, Jean-Claude Tardif, Alaa AlQarawi, Frank Kee, Jennifer Kriebel, Panos Deloukas, Anuj Goel, Kristian Hveem, Konstantin Strauch, Alexander P. Reiner, Paul W. Franks, John R. Thompson, Robin Young, William E. Kraus, Nicholas J. Wareham, Aldi T. Kraja, Rajiv Chowdhury, Oliviero Olivieri, Folkert W. Asselbergs, Adam S. Butterworth, Daniel I. Chasman, Gina M. Peloso, Peter Weeke, Christian M. Shaffer, Naveed Sattar, Muredach P. Reilly, John Danesh, Marco M Ferrario, Ian Ford, Lingyao Zeng, Marju Orho-Melander, Louis-Philippe Lemieux Perreault, Tõnu Esko, Eirini Marouli, Thorsten Kessler, Yingchang Lu, Ehret, Georg Benedikt, Vascular Medicine, Graduate School, and ACS - Amsterdam Cardiovascular Sciences
Subjects: 0301 basic medicine, Male, Pathology, Heart disease, Genotyping Techniques, Aged, Angiopoietins, Cell Adhesion Molecules, Coronary Artery Disease, Female, Humans, Lipoprotein Lipase, Middle Aged, Mutation, Missense, Risk Factors, Sequence Analysis, DNA, Triglycerides, Mutation, Medicine (all), Medizin, 030204 cardiovascular system & hematology, Coronary disease, Bioinformatics, medicine.disease_cause, Coronary artery disease, 0302 clinical medicine, ANGPTL4, Angiopoietin-like 4 Protein, Non-U.S. Gov't, ddc:616, Research Support, Non-U.S. Gov't, Coronary Artery Disease/genetics, General Medicine, 3. Good health, Variation (linguistics), Cardiology, Medical genetics, LPL, Cell Adhesion Molecules/genetics, Sequence Analysis, ANGPTL4, LPL, SVEP1 and coronary artery disease, medicine.medical_specialty, Lipoprotein Lipase/antagonists & inhibitors/genetics/metabolism, Research Support, Article, SVEP1 and coronary artery disease, N.I.H, 03 medical and health sciences, Triglycerides/blood/genetics, Research Support, N.I.H., Extramural, Internal medicine, Angiopoietins/genetics, Journal Article, medicine, Genotyping, business.industry, PCSK9, Extramural, DNA, medicine.disease, 030104 developmental biology, Missense, business, Coding (social sciences)
Abstract: BACKGROUND: \ud \ud The discovery of low-frequency coding variants affecting the risk of coronary artery disease has facilitated the identification of therapeutic targets.\ud \ud METHODS: \ud \ud Through DNA genotyping, we tested 54,003 coding-sequence variants covering 13,715 human genes in up to 72,868 patients with coronary artery disease and 120,770 controls who did not have coronary artery disease. Through DNA sequencing, we studied the effects of loss-of-function mutations in selected genes.\ud \ud RESULTS: \ud \ud We confirmed previously observed significant associations between coronary artery disease and low-frequency missense variants in the genes LPA and PCSK9. We also found significant associations between coronary artery disease and low-frequency missense variants in the genes SVEP1 (p.D2702G; minor-allele frequency, 3.60%; odds ratio for disease, 1.14; P=4.2×10(-10)) and ANGPTL4 (p.E40K; minor-allele frequency, 2.01%; odds ratio, 0.86; P=4.0×10(-8)), which encodes angiopoietin-like 4. Through sequencing of ANGPTL4, we identified 9 carriers of loss-of-function mutations among 6924 patients with myocardial infarction, as compared with 19 carriers among 6834 controls (odds ratio, 0.47; P=0.04); carriers of ANGPTL4 loss-of-function alleles had triglyceride levels that were 35% lower than the levels among persons who did not carry a loss-of-function allele (P=0.003). ANGPTL4 inhibits lipoprotein lipase; we therefore searched for mutations in LPL and identified a loss-of-function variant that was associated with an increased risk of coronary artery disease (p.D36N; minor-allele frequency, 1.9%; odds ratio, 1.13; P=2.0×10(-4)) and a gain-of-function variant that was associated with protection from coronary artery disease (p.S447*; minor-allele frequency, 9.9%; odds ratio, 0.94; P=2.5×10(-7)).\ud \ud CONCLUSIONS: \ud \ud We found that carriers of loss-of-function mutations in ANGPTL4 had triglyceride levels that were lower than those among noncarriers; these mutations were also associated with protection from coronary artery disease. (Funded by the National Institutes of Health and others.).
Published: 2016

33. The use of a DNA biobank linked to electronic medical records to characterize pharmacogenomic predictors of tacrolimus dose requirement in kidney transplant recipients

Author: Marylyn D. Ritchie, Danielle M. Richardson, Melanie P. Robinson, Min Jiang, Talat Alp Ikizler, Melissa A. Basford, Kelly A. Birdwell, David W. Haas, Josh C. Denny, Aihua Bian, Ben Grady, Leena Choi, Gayle Vranic, James D. Cowan, Hua Xu, and Charles M. Stein
Subjects: Adult, Male, Oncology, Receptors, Steroid, medicine.medical_specialty, ATP Binding Cassette Transporter, Subfamily B, Genotype, medicine.medical_treatment, Biology, Pharmacology, Polymorphism, Single Nucleotide, Article, Linkage Disequilibrium, Tacrolimus, Hemoglobins, Therapeutic index, Pharmacokinetics, Internal medicine, Genetics, medicine, Cytochrome P-450 CYP3A, Electronic Health Records, Humans, ATP Binding Cassette Transporter, Subfamily B, Member 1, General Pharmacology, Toxicology and Pharmaceutics, Molecular Biology, Genetic Association Studies, Genetics (clinical), Kidney transplantation, ADME, Dose-Response Relationship, Drug, medicine.diagnostic_test, Body Weight, Age Factors, Pregnane X Receptor, Middle Aged, medicine.disease, Kidney Transplantation, surgical procedures, operative, Immunosuppressive drug, Therapeutic drug monitoring, Pharmacogenomics, Molecular Medicine, Female, Drug Monitoring, Databases, Nucleic Acid, Immunosuppressive Agents
Abstract: Tacrolimus, an immunosuppressive drug widely prescribed in kidney transplantation, requires therapeutic drug monitoring due to its marked interindividual pharmacokinetic variability and narrow therapeutic index. Previous studies have established that CYP3A5 rs776746 is associated with tacrolimus clearance, blood concentration, and dose requirement. The importance of other drug absorption, distribution, metabolism, and elimination (ADME) gene variants has not been well characterized.We used novel DNA biobank and electronic medical record resources to identify ADME variants associated with tacrolimus dose requirement. Broad ADME genotyping was performed on 446 kidney transplant recipients, who had been dosed to a steady state with tacrolimus. The cohort was obtained from Vanderbilt's DNA biobank, BioVU, which contains linked deidentified electronic medical record data. Genotyping included Affymetrix drug-metabolizing enzymes and transporters Plus (1936 polymorphisms), custom Sequenom Massarray iPLEX Gold assay (95 polymorphisms), and ancestry-informative markers. The primary outcome was tacrolimus dose requirement defined as blood concentration to dose ratio.In analyses, which adjusted for race and other clinical factors, we replicated the association of tacrolimus blood concentration to dose ratio with CYP3A5 rs776746 (P=7.15×10), and identified associations with nine variants in linkage disequilibrium with rs776746, including eight CYP3A4 variants. No NR1I2 variants were significantly associated. Age, weight, and hemoglobin were also significantly associated with the outcome. In final models, rs776746 explained 39% of variability in dose requirement and 46% was explained by the model containing clinical covariates.This study highlights the utility of DNA biobanks and electronic medical records for tacrolimus pharmacogenomic research.
Published: 2012

34. Clinical and Genetic Factors Associated With Cutaneous Squamous Cell Carcinoma in Kidney and Heart Transplant Recipients

Author: Josh C. Denny, Dan M. Roden, T. Alp Ikizler, M. Lee Sanders, Kelly A. Birdwell, and Jason H. Karnes
Subjects: Oncology, Transplantation, Kidney, medicine.medical_specialty, education.field_of_study, Cutaneous squamous cell carcinoma, business.industry, Population, Malignancy, medicine.disease, Original Clinical Science, Metastasis, medicine.anatomical_structure, Increased risk, Internal medicine, medicine, Skin cancer, business, Complication, education
Abstract: Cutaneous squamous cell carcinoma (cSCC) occurs with higher frequency and recurrence rates, increased morbidity and mortality, and more aggressive metastasis in kidney and heart transplant recipients compared to the general population but all transplant recipients do not develop cSCC. In addition, the phenotypic expression of cSCC among transplant recipients can vary between mild disease to extensive recurrent metastatic disease. These clinically observed differences in occurrence and severity of cSCC among transplant recipients suggest the possibility that an underlying genetic component might modify risk.We identified 88 white post-transplant cSCC cases (71 kidney and 17 heart) and 300 white post-transplant controls (265 kidney and 35 heart) using a DNA biobank linked with de-identified electronic medical records. Logistic regression was used to determine adjusted odds ratios (OR) for clinical characteristics and single nucleotide polymorphisms (SNP) associated with cSCC in both a candidate SNP and genome wide analysis.Age (OR 1.08 [1.05-1.11], p0.001) and azathioprine exposure (OR 8.64 [3.92-19.03], p0.001) were significantly associated while gender, smoking tobacco use, dialysis duration and immunosuppression duration were not. Ten candidate SNPs previously associated with non-melanoma skin cancer in the general population were significantly associated with cSCC in transplant recipients. Genome wide association analysis implicated SNPs in genes previously associated with malignancy,This study shows an association of increasing age and azathioprine exposure with cSCC and confirms a genetic contribution for cSCC development in kidney and heart transplant recipients.
Published: 2015

35. Abstract 1293: ABO blood type and cancer risk: preliminary findings from a phenome analysis

Author: Lisa Bastarache, Ayush Giri, Alicia Beeghly-Fadiel, Jill M. Pulley, Jeremy L. Warner, and Josh C. Denny
Subjects: Blood type, Cervical cancer, Oncology, Cancer Research, medicine.medical_specialty, Cancer prevention, Cancer, Odds ratio, Biology, medicine.disease, Bioinformatics, ABO blood group system, Internal medicine, medicine, Population study, Skin cancer
Abstract: Introduction: ABO blood type has long been implicated in disease susceptibility, including cancer. However, evidence for associations with many malignancies is mixed. We applied a novel phenome approach to test to cancer codes from electronic medical records (EMR) in relation to ABO blood type in a large predominantly Caucasian study population. Approach: Among adults aged 18-100, cancer case and control status were assigned using 58 general neoplasm related phenome codes to de-identified EMR at the Vanderbilt University Medical Center. Blood type from serologic assays was ascertained from EMR-linked laboratory reports. Associations between blood type and cancer phenomes were quantified with Odds Ratios (OR) and corresponding 95% Confidence Intervals (CI) from logistic regression in models adjusted for sex and stratified by race/ethnicity. Only analyses with at least 100 cases per strata were conducted. Results: Among 221,015 Non-Hispanic Caucasians, 37,841 Blacks, 7,714 Hispanic Caucasians, and 3,616 Asian subjects with ABO blood type available in linked EMR, we evaluated 56, 37, 4, and 3 general cancer phenome codes, respectively. After employing Bonferroni corrections, ABO blood type was significantly associated with cancers of the pancreas, ovary, cervix, skin, and hematopoietic system. Caucasians with blood type O were less likely to have ovarian cancer (OR: 0.82, 95% CI 0.73-0.91) and pancreatic cancer (OR: 0.83, 95% CI: 0.74-0.92), and more likely to have squamous cell or other skin cancer (OR: 1.08, 95% CI: 1.04-1.13) and myeloid leukemia (OR: 1.15, 95% CI: 1.06-1.25) than those with other blood types (A, B, or AB). Hispanic Caucasians with blood type O were less likely to have cervical cancer (OR: 0.56, 95% CI: 0.38-0.82) than those with other blood types. No associations surpassed correction for multiple comparisons among Blacks or Asians. Conclusions: Our phenome approach confirmed known associations between blood type and risk of pancreatic and ovarian cancer, and adds to accumulating evidence supporting associations with skin cancer and leukemia. Our novel cervical cancer association among Hispanic Caucasians and other nominally significant findings, especially in understudied non-Caucasians, should be further evaluated in large and diverse populations. In addition, research to determine how ABO blood type may influence cancer development and progression, and if such associations can be exploited for risk prediction or cancer prevention is warranted. Citation Format: Alicia Beeghly-Fadiel, Ayush Giri, Lisa Bastarache, Jill Pulley, Jeremy Warner, Josh Denny. ABO blood type and cancer risk: preliminary findings from a phenome analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 1293. doi:10.1158/1538-7445.AM2017-1293
Published: 2017

36. CTNNA3 and SEMA3D: Promising loci for asthma exacerbation identified through multiple genome-wide association studies

Author: George L. Clemmer, Dan M. Roden, Benjamin A. Raby, Scott T. Weiss, Joanne E. Sordillo, Josh C. Denny, Robert P. Chase, Michael J. McGeachie, Kelan G. Tantisira, Ann Chen Wu, Hua Xu, Peter Weeke, Fernando D. Martinez, Reynold A. Panettieri, Christian M. Shaffer, Blanca E. Himes, Sze Man Tse, and Jessica Lasky-Su
Subjects: Adult, Male, Linkage disequilibrium, Exacerbation, Adolescent, Immunology, Genome-wide association study, Single-nucleotide polymorphism, Semaphorins, Polymorphism, Single Nucleotide, Article, Young Adult, Immunology and Allergy, SNP, Medicine, Humans, RNA, Messenger, Allele, Child, Asthma, business.industry, Sequence Analysis, RNA, Infant, medicine.disease, Child, Preschool, Expression quantitative trait loci, Female, business, alpha Catenin, Genome-Wide Association Study
Abstract: Background Asthma exacerbations are a major cause of morbidity and medical cost. Objective The objective of this study was to identify genetic predictors of exacerbations in asthmatic subjects. Methods We performed a genome-wide association study meta-analysis of acute asthma exacerbation in 2 pediatric clinical trials: the Childhood Asthma Management Program (n = 581) and the Childhood Asthma Research and Education (n = 205) network. Acute asthma exacerbations were defined as treatment with a 5-day course of oral steroids. We obtained a replication cohort from Biobank of Vanderbilt University Medical Center (BioVU; n = 786), the Vanderbilt University electronic medical record–linked DNA biobank. We used CD4 + lymphocyte genome-wide mRNA expression profiling to identify associations of top single nucleotide polymorphisms with mRNA abundance of nearby genes. Results A locus in catenin (cadherin-associated protein), alpha 3 (CTNNA3) , reached genome-wide significance (rs7915695, P = 2.19 × 10 −8 ; mean exacerbations, 6.05 for minor alleles vs 3.71 for homozygous major alleles). Among the 4 top single nucleotide polymorphisms replicated in BioVU, rs993312 in Sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3D (SEMA3D) was significant ( P = .0083) and displayed stronger association among African Americans ( P = .0004 in BioVU [mean exacerbations, 3.91 vs 1.53]; P = .0089 in the Childhood Asthma Management Program [mean exacerbations, 6.0 vs 3.25]). CTNNA3 variants did not replicate in BioVU. A regulatory variant in the CTNNA3 locus was associated with CTNNA3 mRNA expression in CD4 + cells from asthmatic patients ( P = .00079). CTNNA3 appears to be active in the immune response, and SEMA3D has a plausible role in airway remodeling. We also provide a replication of a previous association of purinergic receptor P2X, ligand-gated ion channel, 7 (P2RX7) , with asthma exacerbation. Conclusions We identified 2 loci associated with exacerbations through a genome-wide association study. CTNNA3 met genome-wide significance thresholds, and SEMA3D replicated in a clinical biobank database.
Published: 2014

37. Integrating EMR-linked and in vivo functional genetic data to identify new genotype-phenotype associations

Author: Josh C. Denny, Peter Weeke, Dan M. Roden, Quinn S. Wells, Jessica T. Delaney, Jonathan D. Mosley, Lisa Bastarache, and Sara L. Van Driest
Subjects: Male, Genotyping Techniques, Inheritance Patterns, lcsh:Medicine, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, 03 medical and health sciences, Mice, 0302 clinical medicine, OMIM : Online Mendelian Inheritance in Man, Genome-Wide Association Studies, Genetics, Animals, Electronic Health Records, Humans, Allele, lcsh:Science, Genotyping, Genetic Association Studies, 030304 developmental biology, 0303 health sciences, Multidisciplinary, lcsh:R, Biology and Life Sciences, Computational Biology, Reproducibility of Results, Human Genetics, Middle Aged, Genome Analysis, Human genetics, 3. Good health, Minor allele frequency, Phenotype, Genetics of Disease, Female, lcsh:Q, 030217 neurology & neurosurgery, Medical Informatics, Research Article
Abstract: The coupling of electronic medical records (EMR) with genetic data has created the potential for implementing reverse genetic approaches in humans, whereby the function of a gene is inferred from the shared pattern of morbidity among homozygotes of a genetic variant. We explored the feasibility of this approach to identify phenotypes associated with low frequency variants using Vanderbilt's EMR-based BioVU resource. We analyzed 1,658 low frequency non-synonymous SNPs (nsSNPs) with a minor allele frequency (MAF)
Published: 2014

38. Mechanistic phenotypes: an aggregative phenotyping strategy to identify disease mechanisms using GWAS data

Author: Emma K. Larkin, Jonathan D. Mosley, Quinn S. Wells, John S. Witte, Yan Guo, David J. Carey, Sara L. Van Driest, Dan M. Roden, Lana M. Olson, Catherine A. McCarty, Jason H. Karnes, Gail P. Jarvik, Marylyn D. Ritchie, Helena Kuivaniemi, Jennifer A. Pacheco, David R. Crosslin, Peter Weeke, Eric B. Larson, Gerard Tromp, Lisa Bastarache, Josh C. Denny, David Carrell, and Iftikhar J. Kullo
Subjects: Population, lcsh:Medicine, Single-nucleotide polymorphism, Genome-wide association study, Biology, Polymorphism, Single Nucleotide, 03 medical and health sciences, 0302 clinical medicine, Genetic model, Electronic Health Records, Humans, Genetic Predisposition to Disease, Allele, lcsh:Science, education, 030304 developmental biology, Genetics, 0303 health sciences, education.field_of_study, Multidisciplinary, lcsh:R, Phenotype, FANCA, 3. Good health, Minor allele frequency, 030220 oncology & carcinogenesis, lcsh:Q, Genome-Wide Association Study, Research Article
Abstract: A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency (MAF
Published: 2013

39. Electronic health record design and implementation for pharmacogenomics: a local perspective

Author: Jill M. Pulley, Marc Beller, Dan M. Roden, Jim Jirjis, Jennifer Mitchell, Josh C. Denny, Kevin B. Johnson, Jonathan S. Schildcrout, Julie R. Field, Erica Bowton, William M. Gregg, and Josh F. Peterson
Subjects: medicine.medical_specialty, Decision support system, Academic Medical Centers, Process management, Genotype, Extramural, business.industry, Perspective (graphical), Health Plan Implementation, Decision Support Systems, Clinical, Clinical decision support system, Article, Translational Research, Biomedical, Phenotype, Electronic health record, Pharmacogenetics, Family medicine, Pharmacogenomics, medicine, Electronic Health Records, Humans, business, Genetics (clinical)
Abstract: The design of electronic health records to translate genomic medicine into clinical care is crucial to successful introduction of new genomic services, yet there are few published guides to implementation.The design, implemented features, and evolution of a locally developed electronic health record that supports a large pharmacogenomics program at a tertiary-care academic medical center was tracked over a 4-year development period.Developers and program staff created electronic health record mechanisms for ordering a pharmacogenomics panel in advance of clinical need (preemptive genotyping) and in response to a specific drug indication. Genetic data from panel-based genotyping were sequestered from the electronic health record until drug-gene interactions met evidentiary standards and deemed clinically actionable. A service to translate genotype to predicted drug-response phenotype populated a summary of drug-gene interactions, triggered inpatient and outpatient clinical decision support, updated laboratory records, and created gene results within online personal health records.The design of a locally developed electronic health record supporting pharmacogenomics has generalizable utility. The challenge of representing genomic data in a comprehensible and clinically actionable format is discussed along with reflection on the scalability of the model to larger sets of genomic data.
Published: 2013

40. Extracting semantic lexicons from discharge summaries using machine learning and the C-Value method

Author: Min, Jiang, Josh C, Denny, Buzhou, Tang, Hongxin, Cao, and Hua, Xu
Subjects: ComputingMethodologies_PATTERNRECOGNITION, Vocabulary, Controlled, Artificial Intelligence, Terminology as Topic, InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL, Humans, Articles, Algorithms, Patient Discharge, Natural Language Processing, Semantics
Abstract: Semantic lexicons that link words and phrases to specific semantic types such as diseases are valuable assets for clinical natural language processing (NLP) systems. Although terminological terms with predefined semantic types can be generated easily from existing knowledge bases such as the Unified Medical Language Systems (UMLS), they are often limited and do not have good coverage for narrative clinical text. In this study, we developed a method for building semantic lexicons from clinical corpus. It extracts candidate semantic terms using a conditional random field (CRF) classifier and then selects terms using the C-Value algorithm. We applied the method to a corpus containing 10 years of discharge summaries from Vanderbilt University Hospital (VUH) and extracted 44,957 new terms for three semantic groups: Problem, Treatment, and Test. A manual analysis of 200 randomly selected terms not found in the UMLS demonstrated that 59% of them were meaningful new clinical concepts and 25% were lexical variants of exiting concepts in the UMLS. Furthermore, we compared the effectiveness of corpus-derived and UMLS-derived semantic lexicons in the concept extraction task of the 2010 i2b2 clinical NLP challenge. Our results showed that the classifier with corpus-derived semantic lexicons as features achieved a better performance (F-score 82.52%) than that with UMLS-derived semantic lexicons as features (F-score 82.04%). We conclude that such corpus-based methods are effective for generating semantic lexicons, which may improve named entity recognition tasks and may aid in augmenting synonymy within existing terminologies.
Published: 2013

41. Using a gene-environment interaction study to evaluate risk for lung cancer

Author: Travis J. Osterman, Lisa Bastarache, Wei-Qi Wei, Jonathan D. Mosley, and Josh C. Denny
Subjects: Cancer Research, business.industry, Single-nucleotide polymorphism, respiratory system, Bioinformatics, medicine.disease, Germline, respiratory tract diseases, Oncology, Tobacco exposure, Genotype, medicine, Risk factor, Lung cancer, business, Gene
Abstract: 1524Background: Lung cancer is known be associated with over 20 germline single nucleotide polymorphisms (SNPs). Tobacco exposure is a known risk factor for developing lung cancer. Genotype by envi...
Published: 2016

42. Extracting and integrating data from entire electronic health records for detecting colorectal cancer cases

Author: Hua, Xu, Zhenming, Fu, Anushi, Shah, Yukun, Chen, Neeraja B, Peterson, Qingxia, Chen, Subramani, Mani, Mia A, Levy, Qi, Dai, and Josh C, Denny
Subjects: Artificial Intelligence, Data Mining, Electronic Health Records, Humans, Articles, Colorectal Neoplasms, Algorithms, Natural Language Processing
Abstract: Identification of a cohort of patients with specific diseases is an important step for clinical research that is based on electronic health records (EHRs). Informatics approaches combining structured EHR data, such as billing records, with narrative text data have demonstrated utility for such tasks. This paper describes an algorithm combining machine learning and natural language processing to detect patients with colorectal cancer (CRC) from entire EHRs at Vanderbilt University Hospital. We developed a general case detection method that consists of two steps: 1) extraction of positive CRC concepts from all clinical notes (document-level concept identification); and 2) determination of CRC cases using aggregated information from both clinical narratives and structured billing data (patient-level case determination). For each step, we compared performance of rule-based and machine-learning-based approaches. Using a manually reviewed data set containing 300 possible CRC patients (150 for training and 150 for testing), we showed that our method achieved F-measures of 0.996 for document level concept identification, and 0.93 for patient level case detection.
Published: 2011

43. Prevalence and Clinical Significance of Discrepancies within Three Computerized Pre-Admission Medication Lists

Author: Josh F, Peterson, Yaping, Shi, Josh C, Denny, Michael E, Matheny, Jonathan S, Schildcrout, Lemuel R, Waitman, and Randolph A, Miller
Subjects: Hospitalization, Medication Reconciliation, Patient Admission, Prevalence, Humans, Medication Errors, Articles
Abstract: Inaccurate records of pre-admission medication exposure have been identified as a major source of medication error. Authors collected records of patients’ pre-admission medications: 1) the most recent outpatient medication list (“EMR”), 2) the medication list recorded by admitting providers (“H&P”), and 3) a list generated by a medication reconciliation process conducted by nursing staff (“PAML”). Forty-eight sets of pre-admission records composed of 1087 medication entries were compared to a reference standard generated by trained study staff conducting an independent interview. Sensitivity was greatest for PAML (85%), compared to EMR (76%) and H&P (76%) sources. However, positive predictive value was greatest for the H&P source at 96% vs 88% and 91% for PAML and EMR sources respectively. Potentially harmful medication discrepancies were found within all lists. The authors concluded no single list was sufficiently accurate to avoid serious medication errors.
Published: 2011

44. Genome-Wide Association Study of Serum Creatinine Levels during Vancomycin Therapy

Author: Lana M. Olson, Richard H. Ho, Ben Saville, Yuki Bradford, Sara L. Van Driest, Dan M. Roden, Sarah Wilson, Josh C. Denny, Prince J. Kannankeril, Christian M. Shaffer, Jessica T. Delaney, Terrie Kitchner, Dana C. Crawford, Iftikhar J. Kullo, Neelam A. Patel, Hayan Jouni, Amy L. Potts, Murray H. Brilliant, C. Buddy Creech, Scott J. Hebbring, Erica Bowton, Digna R. Velez Edwards, Tracy L. McGregor, and Susan I. Vear
Subjects: Adult, Male, Nephrology, Oncology, medicine.medical_specialty, Genotype, 030232 urology & nephrology, lcsh:Medicine, Renal function, Locus (genetics), Genome-wide association study, Single-nucleotide polymorphism, Biology, Bioinformatics, Polymorphism, Single Nucleotide, Nephrotoxicity, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Vancomycin, Internal medicine, medicine, Chromosomes, Human, Humans, lcsh:Science, Adaptor Proteins, Signal Transducing, Aged, 030304 developmental biology, 0303 health sciences, Creatinine, Multidisciplinary, lcsh:R, GTPase-Activating Proteins, Middle Aged, 3. Good health, chemistry, Connexin 43, lcsh:Q, Chromosomes, Human, Pair 6, Female, Genome-Wide Association Study, Research Article, medicine.drug
Abstract: Vancomycin, a commonly used antibiotic, can be nephrotoxic. Known risk factors such as age, creatinine clearance, vancomycin dose / dosing interval, and concurrent nephrotoxic medications fail to accurately predict nephrotoxicity. To identify potential genomic risk factors, we performed a genome-wide association study (GWAS) of serum creatinine levels while on vancomycin in 489 European American individuals and validated findings in three independent cohorts totaling 439 European American individuals. In primary analyses, the chromosome 6q22.31 locus was associated with increased serum creatinine levels while on vancomycin therapy (most significant variant rs2789047, risk allele A, β = -0.06, p = 1.1 x 10(-7)). SNPs in this region had consistent directions of effect in the validation cohorts, with a meta-p of 1.1 x 10(-7). Variation in this region on chromosome 6, which includes the genes TBC1D32/C6orf170 and GJA1 (encoding connexin43), may modulate risk of vancomycin-induced kidney injury.
Published: 2015

45. Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

Author: Dragana Vuckovic, Mariaelisa Graff, M. Arfan Ikram, Marit E. Jørgensen, Lia E. Bang, Gerome Breen, Torben Jørgensen, Matthias Blüher, Ivan Brandslund, Hester M. den Ruijter, Ian Ford, Timo A. Lakka, Jennifer Wessel, J. Wouter Jukema, Adam S. Butterworth, Iris M. Heid, Xiuqing Guo, Shuai Wang, Paul L. Auer, Tamuno Alfred, Katja K.H. Aben, Inês Barroso, Gail Davies, Helen Griffiths, Heather M. Highland, Myriam Fornage, Claudia Langenberg, Daniel R. Witte, Ilaria Gandin, Kent D. Taylor, Patrick T. Ellinor, Matti Uusitupa, Laura M. Yerges-Armstrong, Fotios Drenos, Lars Wallentin, Joanna M. M. Howson, Jaakko Tuomilehto, Andrew D. Morris, Lawrence F. Bielak, Mengmeng Du, Andrew J. Lotery, Ailith Pirie, Francis S. Collins, Eva Rabing Brix Petersen, Carolina Medina-Gomez, Manuel A. Rivas, Maria Karaleftheri, Jan-Håkan Jansson, Peter Kovacs, Jaspal S. Kooner, Markku Laakso, Fredrik Karpe, Markus Perola, Anubha Mahajan, Heather M. Stringham, Rohit Varma, Alex W. Hewitt, Chris J. Packard, Andrew C. Heath, Claudia Schurmann, Nele Friedrich, David Lamparter, Vanisha Mistry, Renée de Mutsert, Unnur Thorsteinsdottir, Naveed Sattar, Jennifer E. Huffman, Dale R. Nyholt, Johanna Kuusisto, Angela L. Mazul, Hanieh Yaghootkar, George Dedoussis, Yadav Sapkota, Elizabeth K. Speliotes, Amanda J. Cox, Jane Gibson, Christian Theil Have, Penny Gordon-Larsen, Alisa K. Manning, Jaakko Kaprio, Sita H. Vermeulen, Stella Trompet, Yucheng Jia, Dennis O. Mook-Kanamori, Torben Hansen, Kathleen Stirrups, Jean Ferrières, Douglas F. Easton, Ruth J. F. Loos, Gerard Pasterkamp, John M. Starr, Tellervo Korhonen, Betina H. Thuesen, Olov Rolandsson, Veikko Salomaa, Eric B. Larson, Thomas F. Vogt, John Danesh, Honghuang Lin, Gaëlle Marenne, Timothy M. Frayling, Anette Varbo, Daniel I. Chasman, Aliki-Eleni Farmaki, Lorraine Southam, Martina Müller-Nurasyid, Katharine R. Owen, Paul Mitchell, Ching-Ti Liu, Massimiliano Cocca, Anette P. Gjesing, Charles Kooperberg, Rebecca S. Fine, Wei Gan, Amy J. Swift, Gerard Tromp, Krina T. Zondervan, Henrik Vestergaard, Katherine S. Ruth, Angela D'Eustacchio, Uwe Völker, Beverley Balkau, Hayato Tada, Ingrid B. Borecki, Xueling Sim, Gudmar Thorleifsson, Wei Zhou, Yiqin Wang, Eleftheria Zeggini, Cora E. Lewis, Michael Boehnke, Evangelos Evangelou, Gabriel Cuellar-Partida, Sven Bergmann, Tinca J. C. Polderman, Philippe Amouyel, Roberta McKean-Cowdin, Ellen W. Demerath, Marco Brumat, Kjell Nikus, Anneke I den Hollander, Stefan Gustafsson, Allan Linneberg, Peter T. Campbell, Weihua Zhang, Leslie A. Lange, Gina M. Peloso, Jonathan P. Bradfield, Cornelia M. van Duijn, Xiaowei Zhan, Marie-Pierre Dubé, Liang He, André G. Uitterlinden, Anne Tybjærg-Hansen, Yingchang Lu, Wei Zhao, Liang Sun, Yii-Der Ida Chen, Paul I. W. de Bakker, Børge G. Nordestgaard, Karina Meidtner, Carsten A. Böger, Lynne E. Wagenknecht, Eric Kim, Pang Yao, Olli T. Raitakari, Nanette R. Lee, René S. Kahn, Lili Milani, Tessel E. Galesloot, Jussi Hernesniemi, Valgerdur Steinthorsdottir, Jie Yao, Eulalia Catamo, Kerrin S. Small, Sara M. Willems, Marcelo P. Segura-Lepe, Cecilia M. Lindgren, Asif Rasheed, Gonçalo R. Abecasis, Adam E. Locke, Konstantin Strauch, Albert V. Smith, Anke R. Hammerschlag, Frida Renström, Zoltán Kutalik, Giovanni Veronesi, Paul M. Ridker, David J. Carey, Yao Hu, Jaana Lindström, John Andrew Pospisilik, Mike A. Nalls, Erik Ingelsson, Colin N. A. Palmer, Mary F. Feitosa, John R. B. Perry, Anne E. Justice, Ele Ferrannini, Shuang Feng, Helen R. Warren, David J. Roberts, Igor Rudan, Jeffrey R. O'Connel, Alison Pattie, Christopher P. Nelson, Lars Lind, Feijie Wang, Tamara B. Harris, Keng-Hung Lin, Jerome I. Rotter, Matthew A. Allison, Robin Young, Fernando Rivadeneira, Leo-Pekka Lyytikäinen, Stefan Johansson, Alexander P. Reiner, Jing Hua Zhao, Poorva Mudgal, Tim D. Spector, Paul W. Franks, Loes M. Olde Loohuis, Harvey D. White, Pirjo Komulainen, Michelle L. O'Donoghue, Todd L. Edwards, Ozren Polasek, Andrew R. Wood, Dermot F. Reilly, Myriam Rheinberger, Cramer Christensen, G. Kees Hovingh, Hidetoshi Kitajima, Kristin L. Young, Audrey Y. Chu, Megan L. Grove, Suthesh Sivapalaratnam, Lisa Bastarache, Martin den Heijer, Oddgeir L. Holmen, Vilmundur Gudnason, Sameer E. Al-Harthi, Dewan S. Alam, Robert E. Schoen, Jin Li, Sascha Fauser, Janie Corley, Paolo Gasparini, Niels Grarup, Guillaume Lettre, Thomas N. Person, Mark I. McCarthy, Joel N. Hirschhorn, Ying Wu, Pia R. Kamstrup, Nilesh J. Samani, Panos Deloukas, Ethan M. Lange, Helena Kuivaniemi, Mika Kähönen, Michiel L. Bots, Annette Peters, Peggy L. Peissig, Wayne Huey-Herng Sheu, Steven A. Lubitz, Stefania Cappellani, Mauno Vanhala, Andrew P. Morris, Struan F.A. Grant, Mark Walker, Trevor A. Mori, Jian'an Luan, Matthias B. Schulze, Josh C. Denny, Sarah E. Medland, Sander W. van der Laan, Maggie C.Y. Ng, Eric Boerwinkle, Tibor V. Varga, Øyvind Helgeland, Anke Tönjes, Jessica van Setten, James P. Cook, Patricia B. Munroe, Heiner Boeing, Robert A. Scott, Karen L. Mohlke, Leena Moilanen, Ayush Giri, Andrew J. Slater, Andrew T. Hattersley, Mark J. Caulfield, Tõnu Esko, Mark C. H. Groot, Nancy L. Heard-Costa, Narisu Narisu, Danish Saleheen, Valérie Turcot, Lambertus A. Kiemeney, Nicholas G. D. Masca, Ruifang Li-Gao, Jean-Claude Tardif, Xu Lin, Kathleen Mullan Harris, Antonietta Robino, Alison M. Dunning, Jonathan Tyrer, Audrey E. Hendricks, Linda Broer, Patricia A. Peyser, Jessica D. Faul, Jose C. Florez, Anne U. Jackson, Eirini Marouli, Jette Bork-Jensen, John C. Chambers, Jordi Corominas Galbany, Ruth Frikke-Schmidt, David S. Crosslin, Bratati Kahali, Stavroula Kanoni, Gorm B. Jensen, Nicholas J. Wareham, Paul Elliott, Tune H. Pers, James A. Perry, Tugce Karaderi, Matt J. Neville, Marianne Benn, Svati H. Shah, Mathias Gorski, Michael Stumvoll, David Ellinghaus, Amber A. Burt, Kari E. North, Jeffrey Haessler, Rajiv Chowdhury, Folkert W. Asselbergs, Marie Moitry, Aniruddh P. Patel, Pamela J. Schreiner, Frank Kee, Donald W. Bowden, Sune F. Nielsen, Oluf Pedersen, John D. Rioux, Rainer Rauramaa, Satu Männistö, Deborah J. Thompson, Cristen J. Willer, Andre Franke, Kari Kuulasmaa, Nienke van Leeuwen, Carmel Moore, Sharon L.R. Kardia, Neil R. Robertson, Sekar Kathiresan, Erin B. Ware, Dawn M. Waterworth, James G. Wilson, Sandosh Padmanabhan, Emmanouil Tsafantakis, Hakon Hakonarson, Dajiang J. Liu, Digna R. Velez Edwards, Artitaya Lophatananon, Craig E. Pennell, Gail P. Jarvik, Adelheid Lempradl, Anu Loukola, Joe Dennis, Hans-Jörgen Grabe, Oscar H. Franco, Yongmei Liu, I. Sadaf Farooqi, Hannu Puolijoki, Huaixing Li, Caroline Hayward, Rudolf Uher, Veronique Vitart, Murray H. Brilliant, Kari Stefansson, Alexander Teumer, Nicholette D. Palmer, Vilmantas Giedraitis, Roel A. Ophoff, Sailaja Vedantam, Emanuele Di Angelantonio, Ken S. Lo, Grant W. Montgomery, Paul L. Huang, Praveen Surendran, Terho Lehtimäki, Katherine E. Tansey, Li-An Lin, Pål R. Njølstad, Thomas W. Winkler, Ian J. Deary, Erwin P. Bottinger, Carol A. Wang, Biological Psychology, Complex Trait Genetics, and Amsterdam Neuroscience - Complex Trait Genetics
Subjects: 0301 basic medicine, 2. Zero hunger, 0303 health sciences, ComputerSystemsOrganization_COMPUTERSYSTEMIMPLEMENTATION, Published Erratum, Computational biology, Biology, medicine.disease, Obesity, Genealogy, 3. Good health, 03 medical and health sciences, 030104 developmental biology, 0302 clinical medicine, ddc:570, Genetics, medicine, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, Biological sciences, Body mass index, 030217 neurology & neurosurgery, 030304 developmental biology
Abstract: In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.
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46. Genome-Wide Association Study of Serum Creatinine Levels during Vancomycin Therapy.

Author: Sara L Van Driest, Tracy L McGregor, Digna R Velez Edwards, Ben R Saville, Terrie E Kitchner, Scott J Hebbring, Murray Brilliant, Hayan Jouni, Iftikhar J Kullo, C Buddy Creech, Prince J Kannankeril, Susan I Vear, Kyle B Brothers, Erica A Bowton, Christian M Shaffer, Neelam Patel, Jessica T Delaney, Yuki Bradford, Sarah Wilson, Lana M Olson, Dana C Crawford, Amy L Potts, Richard H Ho, Dan M Roden, and Josh C Denny
Subjects: Medicine, Science
Abstract: Vancomycin, a commonly used antibiotic, can be nephrotoxic. Known risk factors such as age, creatinine clearance, vancomycin dose / dosing interval, and concurrent nephrotoxic medications fail to accurately predict nephrotoxicity. To identify potential genomic risk factors, we performed a genome-wide association study (GWAS) of serum creatinine levels while on vancomycin in 489 European American individuals and validated findings in three independent cohorts totaling 439 European American individuals. In primary analyses, the chromosome 6q22.31 locus was associated with increased serum creatinine levels while on vancomycin therapy (most significant variant rs2789047, risk allele A, β = -0.06, p = 1.1 x 10(-7)). SNPs in this region had consistent directions of effect in the validation cohorts, with a meta-p of 1.1 x 10(-7). Variation in this region on chromosome 6, which includes the genes TBC1D32/C6orf170 and GJA1 (encoding connexin43), may modulate risk of vancomycin-induced kidney injury.
Published: 2015
Full Text: View/download PDF

47. Integrating EMR-linked and in vivo functional genetic data to identify new genotype-phenotype associations.

Author: Jonathan D Mosley, Sara L Van Driest, Peter E Weeke, Jessica T Delaney, Quinn S Wells, Lisa Bastarache, Dan M Roden, and Josh C Denny
Subjects: Medicine, Science
Abstract: The coupling of electronic medical records (EMR) with genetic data has created the potential for implementing reverse genetic approaches in humans, whereby the function of a gene is inferred from the shared pattern of morbidity among homozygotes of a genetic variant. We explored the feasibility of this approach to identify phenotypes associated with low frequency variants using Vanderbilt's EMR-based BioVU resource. We analyzed 1,658 low frequency non-synonymous SNPs (nsSNPs) with a minor allele frequency (MAF)
Published: 2014
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48. Mechanistic phenotypes: an aggregative phenotyping strategy to identify disease mechanisms using GWAS data.

Author: Jonathan D Mosley, Sara L Van Driest, Emma K Larkin, Peter E Weeke, John S Witte, Quinn S Wells, Jason H Karnes, Yan Guo, Lisa Bastarache, Lana M Olson, Catherine A McCarty, Jennifer A Pacheco, Gail P Jarvik, David S Carrell, Eric B Larson, David R Crosslin, Iftikhar J Kullo, Gerard Tromp, Helena Kuivaniemi, David J Carey, Marylyn D Ritchie, Josh C Denny, and Dan M Roden
Subjects: Medicine, Science
Abstract: A single mutation can alter cellular and global homeostatic mechanisms and give rise to multiple clinical diseases. We hypothesized that these disease mechanisms could be identified using low minor allele frequency (MAF
Published: 2013
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