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1. Bringing Code to Data: Do Not Forget Governance

Author

Suver, Christine, Thorogood, Adrian, Doerr, Megan, Wilbanks, John, and Knoppers, Bartha

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Public aspects of medicine, RA1-1270
Abstract

Developing or independently evaluating algorithms in biomedical research is difficult because of restrictions on access to clinical data. Access is restricted because of privacy concerns, the proprietary treatment of data by institutions (fueled in part by the cost of data hosting, curation, and distribution), concerns over misuse, and the complexities of applicable regulatory frameworks. The use of cloud technology and services can address many of the barriers to data sharing. For example, researchers can access data in high performance, secure, and auditable cloud computing environments without the need for copying or downloading. An alternative path to accessing data sets requiring additional protection is the model-to-data approach. In model-to-data, researchers submit algorithms to run on secure data sets that remain hidden. Model-to-data is designed to enhance security and local control while enabling communities of researchers to generate new knowledge from sequestered data. Model-to-data has not yet been widely implemented, but pilots have demonstrated its utility when technical or legal constraints preclude other methods of sharing. We argue that model-to-data can make a valuable addition to our data sharing arsenal, with 2 caveats. First, model-to-data should only be adopted where necessary to supplement rather than replace existing data-sharing approaches given that it requires significant resource commitments from data stewards and limits scientific freedom, reproducibility, and scalability. Second, although model-to-data reduces concerns over data privacy and loss of local control when sharing clinical data, it is not an ethical panacea. Data stewards will remain hesitant to adopt model-to-data approaches without guidance on how to do so responsibly. To address this gap, we explored how commitments to open science, reproducibility, security, respect for data subjects, and research ethics oversight must be re-evaluated in a model-to-data context.

Published
2020
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2. Formative Evaluation of Participant Experience With Mobile eConsent in the App-Mediated Parkinson mPower Study: A Mixed Methods Study

Author

Doerr, Megan, Maguire Truong, Amy, Bot, Brian M, Wilbanks, John, Suver, Christine, and Mangravite, Lara M

Subjects
Information technology, T58.5-58.64, Public aspects of medicine, RA1-1270
Abstract

BackgroundTo fully capitalize on the promise of mobile technology to enable scalable, participant-centered research, we must develop companion self-administered electronic informed consent (eConsent) processes. As we do so, we have an ethical obligation to ensure that core tenants of informed consent—informedness, comprehension, and voluntariness—are upheld. Furthermore, we should be wary of recapitulating the pitfalls of “traditional” informed consent processes. ObjectiveOur objective was to describe the essential qualities of participant experience, including delineation of common and novel themes relating to informed consent, with a self-administered, smartphone-based eConsent process. We sought to identify participant responses related to informedness, comprehension, and voluntariness as well as to capture any emergent themes relating to the informed consent process in an app-mediated research study. MethodsWe performed qualitative thematic analysis of participant responses to a daily general prompt collected over a 6-month period within the Parkinson mPower app. We employed a combination of a priori and emergent codes for our analysis. A priori codes focused on the core concepts of informed consent; emergent codes were derived to capture additional themes relating to self-administered consent processes. We used self-reported demographic information from the study’s baseline survey to characterize study participants and respondents. ResultsDuring the study period, 9846 people completed the eConsent process and enrolled in the Parkinson mPower study. In total, 2758 participants submitted 7483 comments; initial categorization identified a subset of 3875 germane responses submitted by 1678 distinct participants. Respondents were more likely to self-report a Parkinson disease diagnosis (30.21% vs 11.10%), be female (28.26% vs 20.18%), be older (42.89 years vs 34.47 years), and have completed more formal education (66.23% with a 4-year college degree or more education vs 55.77%) than all the mPower participants (P

Published
2017
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3. Young people's data governance preferences for their mental health data: MindKind Study findings from India, South Africa, and the United Kingdom.

Author

Sieberts, Solveig K, Marten, Carly, Bampton, Emily, Björling, Elin A, Burn, Anne-Marie, Carey, Emma Grace, Carlson, Sonia, Fernandes, Blossom, Kalha, Jasmine, Lindani, Simthembile, Masomera, Hedwick, Neelakantan, Lakshmi, Pasquale, Lisa, Ranganathan, Swetha, Joy Scanlan, Erin, Shah, Himani, Sibisi, Refiloe, Sumant, Sushmita, Suver, Christine, Thungana, Yanga, Tummalacherla, Meghasyam, Velloza, Jennifer, Collins, Pamela Y, Fazel, Mina, Ford, Tamsin, Freeman, Melvyn, Pathare, Soumitra, Zingela, Zukiswa, MindKind Consortium, and Doerr, Megan

Subjects
MindKind Consortium, Humans, Mental Health, Qualitative Research, Adolescent, Adult, South Africa, India, Young Adult, United Kingdom, Clinical Research, Clinical Trials and Supportive Activities, Behavioral and Social Science, Pediatric, 7.1 Individual care needs, Management of diseases and conditions, Mental health, Good Health and Well Being, General Science & Technology
Abstract

Mobile devices offer a scalable opportunity to collect longitudinal data that facilitate advances in mental health treatment to address the burden of mental health conditions in young people. Sharing these data with the research community is critical to gaining maximal value from rich data of this nature. However, the highly personal nature of the data necessitates understanding the conditions under which young people are willing to share them. To answer this question, we developed the MindKind Study, a multinational, mixed methods study that solicits young people's preferences for how their data are governed and quantifies potential participants' willingness to join under different conditions. We employed a community-based participatory approach, involving young people as stakeholders and co-researchers. At sites in India, South Africa, and the UK, we enrolled 3575 participants ages 16-24 in the mobile app-mediated quantitative study and 143 participants in the public deliberation-based qualitative study. We found that while youth participants have strong preferences for data governance, these preferences did not translate into (un)willingness to join the smartphone-based study. Participants grappled with the risks and benefits of participation as well as their desire that the "right people" access their data. Throughout the study, we recognized young people's commitment to finding solutions and co-producing research architectures to allow for more open sharing of mental health data to accelerate and derive maximal benefit from research.

Published
2023

4. Crowd-sourced machine learning prediction of long COVID using data from the National COVID Cohort Collaborative

Author

Aggarwal, Ataes, Agor, Joseph, Al-Amery, Amera, Aminu, Oluwatobiloba, Anand, Adit, Antonescu, Corneliu, Arora, Mehak, Asaduzzaman, Sayed, Asmussen, Tanner, Baghbanzadeh, Mahdi, Baker, Frazier, Bangert, Bridget, Bekhet, Laila, Bhattacharya, Biplab, Blase, Jenny, Butzin-Dozier, Zachary, Caffo, Brian, Chang, Hao, Chen, Zeyuan, Chen, Jiandong, Chiang, Jeffrey, Cho, Peter, Cockrell, Robert, Combs, Parker, Coyle, Jeremy, Crosby, Ciara, Dai, Zongyu, Dai, Ran, Danesharasteh, Anseh, Yildirim, Elif, Delong, Grant, Demilt, Ryan, Deng, Kaiwen, Dey, Sanjoy, Dhamdhere, Rohan, Dickson, Andrew, Dijour, Phoebe, Dinh, Dong, Dixon, Richard, Domi, Albi, Dutta, Souradeep, Elizondo, Mirna, Ertem, Zeynep, Feuerwerker, Solomon, Fliss, Danica, Fowler, Jennifer, Fu, Sunyang, Gardner, Kelly, Getty, Neil, Ghalwash, Mohamed, Gloster, Logan, Greer, Phil, Guan, Yuanfang, Ham, Colby, Hanoudi, Samer, Harper, Jeremy, Hendrix, Nathaniel, Hershkovich, Leeor, Hightower, Jake, Hu, Junjie, Huang, Jiani, Huang, Yu, Huang, Tongtong, Hur, Junguk, Isgut, Monica, Ismail, Hamid, Izmirlian, Grant, Jang, Kuk, Jemiyo, Christianah, Jeong, Hayoung, Ji, Yunwen, Ji, Xiayan, Jiang, Ming, Jiang, Sihang, Jiang, Xiaoqian, Jiang, Yuye, Johnson, Akin, Analyst, Zach, Kapse, Saarthak, Kartoun, Uri, KC, Dukka, Fard, Zahra, Kosfeld, Tim, Krichevsky, Spencer, Kuo, Mike, Larie, Dale, Lederer, Lauren, Leng, Shan, Li, Ziyang, Li, Hongyang, Li, Haodong, Li, Jianfu, Li, Tiantian, Liang, Xinwen, Liang, Hengyue, Liu, Feifan, Liu, Daniel, Luo, Gang, Munia, Tamanna, Madduri, Ravi, Madhira, Vithal, Mani, Shivali, Mansourifard, Farzaneh, Matson, Robert, Mertens, Andrew, Metsis, Vangelis, Meyer, Pablo, Mikhailova, Catherine, Miller, Dante, Milo, Christopher, Mitchell, Elliot, Modanwal, Gourav, Moore, Ronald, Morgenthaler, David, Musal, Rasim, Naik, Mayur, Nalawade, Vinit, Narain, Rohan, Narendrula, Saideep, Obiri, Alena, Okawa, Satoshi, Okechukwu, Chima, Olorunnisola, Toluwanimi, Ossowski, Tim, Parekh, Harsh, Park, Jean, Patel, Saaya, Patterson, Jason, Paul, Chetan, Peng, Le, Perkins, Diana, Pokharel, Suresh, Poplavskiy, Dmytro, Pryor, Zach, Pungitore, Sarah, Qin, Hong, Rababa, Salahaldeen, Rahman, Mahbubur, Rahmani, Elior, Rahnavard, Gholamali, Raihan, Md, Rajendran, Suraj, Ravichandran, Sarangan, Reddy, Chandan, Reyes, Abel, Roghanizad, Ali, Rouffa, Sean, Ruan, Xiaoyang, Saha, Arpita, Sawant, Sahil, Schiaffino, Melody, Seira, Diego, Sengupta, Saurav, Shalaev, Ruslan, Shetty, Gaurav, Shi, Seraphina, Shinguyen, Linh, Singh, Karnika, Sinha, Soumya, Socia, Damien, Stalians, Halen, Stavropoulos, Charalambos, Strube, Jan, Subramanian, Devika, Sun, Jiehuan, Sun, Ju, Sun, Chengkun, Sundararajan, Prathic, Talebi, Salmonn, Tawiah, Edward, Tesic, Jelena, Thiess, Mikaela, Tian, Raymond, Torre-Healy; Ming-Tse Tsai, Luke, Tyus, David, Vardhan, Madhurima, Velingker, Neelay, Walzer, Benjamin, Walzer, Jacob, Wang, Junda, Wang, Lu, Wang, Will, Wang, Jonathan, Wang, Yisen, Weatherly, Chad, Wu, Fanyou, Wu, Yifeng, Wu, Yinjun, Xia, Fangfang, Yan, Hao, Yang, Zhichao, Ye, Biao, Yin, Rui, Yin, Changyu, Yoo, Yun, You, Albert, Yu, June, Zanaj, Martin, Zaiman, Zachary, Zhang, Kai, Zhang, Xiaoyi, Zhang, Tianmai, Zhao, Zixuan, Zhi, Degui, Zhong, Yishan, Zhou, Huixue, Zhou, Andrea, Zhu, Yuanda, Zhu, Yitan, Zhu, Sophie, Adams, Meredith, Alexander, Caleb, Amor, Benjamin, Anzalone, Alfred, Bates, Benjamin, Beasley, Will, Bennett, Tellen, Bissell, Mark, Boudreau, Eilis, Bozzette, Samuel, Bradwell, Katie, Bramante, Carolyn, Brown, Don, Burgoon, Penny, Buse, John, Callahan, Tiffany, Cato, Kenrick, Chapman, Scott, Chute, Christopher, Clark, Jaylyn, Clark, Marshall, Cooper, Will, Cottrell, Lesley, Crowley, Karen, Deacy, Mariam, Dillon, Christopher, Eichmann, David, Emmett, Mary, Erwin-Cohen, Rebecca, Francis, Patricia, French, Evan, Fuentes, Rafael, Gabriel, Davera, Gagnier, Joel, Garbarini, Nicole, Ge, Jin, Gersing, Kenneth, Girvin, Andrew, Gordon, Valery, Graves, Alexis, Guinney, Justin, Haendel, Melissa, Hayanga, J.W., Hendricks, Brian, Hernandez, Wenndy, Hill, Elaine, Hillegass, William, Hong, Stephanie, Housman, Dan, Hurley, Robert, Islam, Jessica, Jawa, Randeep, Johnson, Steve, Kamaleswaran, Rishi, Kibbe, Warren, Koraishy, Farrukh, Kostka, Kristin, Kurilla, Michael, Lee, Adam, Lehmann, Harold, Liu, Hongfang, Loomba, Johanna, Madlock-Brown; Sandeep Mallipattu, Charisse, Manna, Amin, Mariona, Federico, Marti, Emily, Martin, Greg, Mathew, Jomol, Mazzotti, Diego, McMurry, Julie, Mehta, Hemalkumar, Michael, Sam, Miller, Robert, Misquitta, Leonie, Moffitt, Richard, Morris, Michele, Murray, Kimberly, Northington, Lavance, O’Neil, Shawn, Olex, Amy, Palchuk, Matvey, Patel, Brijesh, Patel, Rena, Payne, Philip, Pfaff, Emily, Pincavitch, Jami, Portilla, Lili, Prior, Fred, Pyarajan, Saiju, Pyles, Lee, Qureshi, Nabeel, Robinson, Peter, Rutter, Joni, Sadan, Ofer, Safdar, Nasia, Saha, Amit, Saltz, Joel, Saltz, Mary, Schmitt, Clare, Setoguchi, Soko, Sharafeldin, Noha, Sharathkumar, Anjali, Sheikh, Usman, Sidky, Hythem, Sokos, George, Southerland, Andrew, Spratt, Heidi, Starren, Justin, Subbian, Vignesh, Suver, Christine, Takemoto, Cliff, Temple-O'Connor, Meredith, Topaloglu, Umit, Vedula, Satyanarayana, Walden, Anita, Walters, Kellie, Ward-Caviness, Cavin, Wilcox, Adam, Wilkins, Ken, Williams, Andrew, Wu, Chunlei, Zampino, Elizabeth, Zhang, Xiaohan, Zhu, Richard, Bergquist, Timothy, Tariq, Adbul, Philips, Rachael V., Pirracchio, Romain, van der Laan, Mark, Colford, John M., Jr., Hubbard, Alan, Gao, Jifan, Chen, Guanhua, Stein, Adam, Long, Qi, Holmes, John, Mowery, Danielle, Wong, Eric, Parekh, Ravi, Getzen, Emily, and Blase, Jennifer

Published
2024
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5. Real-world behavioral dataset from two fully remote smartphone-based randomized clinical trials for depression

Author

Pratap, Abhishek, Homiar, Ava, Waninger, Luke, Herd, Calvin, Suver, Christine, Volponi, Joshua, Anguera, Joaquin A, and Areán, Pat

Subjects
Clinical Trials and Supportive Activities, Depression, Behavioral and Social Science, Brain Disorders, Comparative Effectiveness Research, Mental Health, Prevention, Health Services, Clinical Research, Generic health relevance, Mental health, Good Health and Well Being, Anxiety, Humans, Randomized Controlled Trials as Topic, Smartphone
Abstract

Most people with mental health disorders cannot receive timely and evidence-based care despite billions of dollars spent by healthcare systems. Researchers have been exploring using digital health technologies to measure behavior in real-world settings with mixed results. There is a need to create accessible and computable digital mental health datasets to advance inclusive and transparently validated research for creating robust real-world digital biomarkers of mental health. Here we share and describe one of the largest and most diverse real-world behavior datasets from over two thousand individuals across the US. The data were generated as part of the two NIMH-funded randomized clinical trials conducted to assess the effectiveness of delivering mental health care continuously remotely. The longitudinal dataset consists of self-assessment of mood, depression, anxiety, and passively gathered phone-based behavioral data streams in real-world settings. This dataset will provide a timely and long-term data resource to evaluate analytical approaches for developing digital behavioral markers and understand the effectiveness of mental health care delivered continuously and remotely.

Published
2022

6. Decreasing Case Fatality Rates for Patients With Cirrhosis Infected With SARS-CoV-2: A National COVID Cohort Collaborative Study

Author

Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred (Jerrod), Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J.W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O'Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O'Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, Zhang, Xiaohan Tanner, Far, Aryana T., Digitale, Jean C., Pletcher, Mark J., and Lai, Jennifer C.

Published
2024
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7. Nonelective coronary artery bypass graft outcomes are adversely impacted by Coronavirus disease 2019 infection, but not altered processes of care: A National COVID Cohort Collaborative and National Surgery Quality Improvement Program analysis

Author

Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred (Jerrod), Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J.W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O'Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O'Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, Zhang, Xiaohan Tanner, Grimsley, Emily A., Torikashvili, Johnathan V., Janjua, Haroon M., Read, Meagan D., Kothari, Anai N., Verhagen, Nate B., Pietrobon, Ricardo, Kuo, Paul C., and Rogers, Michael P.

Published
2023
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8. The National COVID Cohort Collaborative (N3C): Rationale, Design, Infrastructure, and Deployment

Author

Haendel, Melissa A, Chute, Christopher G, Bennett, Tellen D, Eichmann, David A, Guinney, Justin, Kibbe, Warren A, Payne, Philip RO, Pfaff, Emily R, Robinson, Peter N, Saltz, Joel H, Spratt, Heidi, Suver, Christine, Wilbanks, John, Wilcox, Adam B, Williams, Andrew E, Wu, Chunlei, Blacketer, Clair, Bradford, Robert L, Cimino, James J, Clark, Marshall, Colmenares, Evan W, Francis, Patricia A, Gabriel, Davera, Graves, Alexis, Hemadri, Raju, Hong, Stephanie S, Hripscak, George, Jiao, Dazhi, Klann, Jeffrey G, Kostka, Kristin, Lee, Adam M, Lehmann, Harold P, Lingrey, Lora, Miller, Robert T, Morris, Michele, Murphy, Shawn N, Natarajan, Karthik, Palchuk, Matvey B, Sheikh, Usman, Solbrig, Harold, Visweswaran, Shyam, Walden, Anita, Walters, Kellie M, Weber, Griffin M, Zhang, Xiaohan Tanner, Zhu, Richard L, Amor, Benjamin, Girvin, Andrew T, Manna, Amin, Qureshi, Nabeel, Kurilla, Michael G, Michael, Sam G, Portilla, Lili M, Rutter, Joni L, Austin, Christopher P, and Gersing, Ken R

Subjects
COVID-19, Computer Security, Data Analysis, Data Science, Ethics Committees, Research, Government Regulation, Humans, Information Dissemination, Intersectoral Collaboration, National Institutes of Health (U.S.), United States, N3C Consortium, EHR data, SARS-CoV-2, clinical data model harmonization, collaborative analytics, open science, Information and Computing Sciences, Engineering, Medical and Health Sciences, Medical Informatics
Abstract

ObjectiveCoronavirus disease 2019 (COVID-19) poses societal challenges that require expeditious data and knowledge sharing. Though organizational clinical data are abundant, these are largely inaccessible to outside researchers. Statistical, machine learning, and causal analyses are most successful with large-scale data beyond what is available in any given organization. Here, we introduce the National COVID Cohort Collaborative (N3C), an open science community focused on analyzing patient-level data from many centers.Materials and methodsThe Clinical and Translational Science Award Program and scientific community created N3C to overcome technical, regulatory, policy, and governance barriers to sharing and harmonizing individual-level clinical data. We developed solutions to extract, aggregate, and harmonize data across organizations and data models, and created a secure data enclave to enable efficient, transparent, and reproducible collaborative analytics.ResultsOrganized in inclusive workstreams, we created legal agreements and governance for organizations and researchers; data extraction scripts to identify and ingest positive, negative, and possible COVID-19 cases; a data quality assurance and harmonization pipeline to create a single harmonized dataset; population of the secure data enclave with data, machine learning, and statistical analytics tools; dissemination mechanisms; and a synthetic data pilot to democratize data access.ConclusionsThe N3C has demonstrated that a multisite collaborative learning health network can overcome barriers to rapidly build a scalable infrastructure incorporating multiorganizational clinical data for COVID-19 analytics. We expect this effort to save lives by enabling rapid collaboration among clinicians, researchers, and data scientists to identify treatments and specialized care and thereby reduce the immediate and long-term impacts of COVID-19.

Published
2021

9. Indicators of retention in remote digital health studies: A cross-study evaluation of 100,000 participants

Author

Pratap, Abhishek, Neto, Elias Chaibub, Snyder, Phil, Stepnowsky, Carl, Elhadad, Noémie, Grant, Daniel, Mohebbi, Matthew H., Mooney, Sean, Suver, Christine, Wilbanks, John, Mangravite, Lara, Heagerty, Patrick, Arean, Pat, and Omberg, Larsson

Subjects
Statistics - Applications, Computer Science - Computers and Society
Abstract

Digital technologies such as smartphones are transforming the way scientists conduct biomedical research using real-world data. Several remotely-conducted studies have recruited thousands of participants over a span of a few months. Unfortunately, these studies are hampered by substantial participant attrition, calling into question the representativeness of the collected data including generalizability of findings from these studies. We report the challenges in retention and recruitment in eight remote digital health studies comprising over 100,000 participants who participated for more than 850,000 days, completing close to 3.5 million remote health evaluations. Survival modeling surfaced several factors significantly associated(P < 1e-16) with increase in median retention time i) Clinician referral(increase of 40 days), ii) Effect of compensation (22 days), iii) Clinical conditions of interest to the study (7 days) and iv) Older adults(4 days). Additionally, four distinct patterns of daily app usage behavior that were also associated(P < 1e-10) with participant demographics were identified. Most studies were not able to recruit a representative sample, either demographically or regionally. Combined together these findings can help inform recruitment and retention strategies to enable equitable participation of populations in future digital health research.

Published
2019

10. Hormone replacement therapy and COVID-19 outcomes in solid organ transplant recipients compared with the general population

Author

Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred (Jerrod), Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J.W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O'Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O'Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, Zhang, Xiaohan Tanner, Vinson, Amanda J., Anzalone, Alfred, Schissel, Makayla, Dai, Ran, French, Evan T., Olex, Amy L., and Mannon, Roslyn B.

Published
2023
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11. Risk of severe acute respiratory syndrome coronavirus 2 infection among women with polycystic ovary syndrome

Author

Haendel, Melissa A., Chute, Christopher G., Walden, Anita, Gersing, Kenneth R., Misquitta, Leonie, Burgoon, Penny Wung, Bozzette, Samuel, Deacy, Mariam, Dillon, Christopher, Erwin-Cohen, Rebecca, Garbarini, Nicole, Gordon, Valery, Kurilla, Michael G., Marti, Emily Carlson, Michael, Sam G., Portilla, Lili, Schmitt, Clare, Temple-O'Connor, Meredith, Bennett, Tellen D., Eichmann, David A., Guinney, Justin, Kibbe, Warren A., Liu, Hongfang, Payne, Philip R.O., Pfaff, Emily R., Robinson, Peter N., Saltz, Joel H., Spratt, Heidi, Starren, Justin, Suver, Christine, Wilcox, Adam B., Williams, Andrew E., Wu, Chunlei, Gabriel, Davera, Hong, Stephanie S., Kostka, Kristin, Lehmann, Harold P., Moffitt, Richard A., Morris, Michele, Palchuk, Matvey B., Zhang, Xiaohan Tanner, Zhu, Richard L., Clark, Marshall, Girvin, Andrew T., Lee, Adam M., Miller, Robert T., Walters, Kellie M., Cooper, Will, Francis, Patricia A., Fuentes, Rafael, Graves, Alexis, McMurry, Julie A., Neumann, Andrew J., O'Neil, Shawn T., Sheikh, Usman, Zampino, Elizabeth, Bissell, Mark M., Bradwell, Katie Rebecca, Manna, Amin, Qureshi, Nabeel, Saltz, Mary Morrison, Volz, Andréa M., Bramante, Carolyn, Harper, Jeremy Richard, Hernandez, Wenndy, Koraishy, Farrukh M., Mariona, Federico, Saha, Amit, Vedula, Satyanarayana, Alur-Gupta, Snigdha, Boland, Mary Regina, and Dokras, Anuja

Published
2023
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12. COVID-19 outcomes in persons with hemophilia: results from a US-based national COVID-19 surveillance registry

Author

Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred (Jerrod), Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J. W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O’Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O’Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, Zhang, Xiaohan Tanner, Sharathkumar, Anjali, Wendt, Linder, Ortman, Chris, Srinivasan, Ragha, Chute, Christopher G., Chrischilles, Elizabeth, and Takemoto, Clifford M.

Published
2023
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13. Remote smartphone monitoring of Parkinson’s disease and individual response to therapy

Author

Omberg, Larsson, Chaibub Neto, Elias, Perumal, Thanneer M., Pratap, Abhishek, Tediarjo, Aryton, Adams, Jamie, Bloem, Bastiaan R., Bot, Brian M., Elson, Molly, Goldman, Samuel M., Kellen, Michael R., Kieburtz, Karl, Klein, Arno, Little, Max A., Schneider, Ruth, Suver, Christine, Tarolli, Christopher, Tanner, Caroline M., Trister, Andrew D., Wilbanks, John, Dorsey, E. Ray, and Mangravite, Lara M.

Published
2022
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14. An Application of Evidence‐Based Approaches to Engage Young People in the Design of a Global Mental Health Databank.

Author

Mensa‐Kwao, Augustina, Neelakantan, Lakshmi, Velloza, Jennifer, Bampton, Emily, Ranganathan, Swetha, Sibisi, Refiloe, Bowes, Joshua, Buonasorte, Lilliana, Juma, Damian Omari, Veluvali, Manasa, Doerr, Megan, Ford, Tamsin Jane, Suver, Christine, Marten, Carly, Adeyemi, Faith Oluwasemilore, Areán, Patricia A., Björling, Elin A., Bradic, Ljubomir, Burn, Anne‐Marie, and Carey, Emma Grace

Subjects
DATABASES, MIDDLE-income countries, MENTAL health, RESEARCH funding, QUALITATIVE research, CONTENT analysis, DESCRIPTIVE statistics, INTERNET, DECISION making in clinical medicine, WORLD health, MEDICAL research, PATIENT participation, LOW-income countries
Abstract

Introduction: Engaging youth in mental health research and intervention design has the potential to improve their relevance and effectiveness. Frameworks like Roger Hart's ladder of participation, Shier's pathways to participation and Lundy's voice and influence model aim to balance power between youth and adults. Hart's Ladder, specifically, is underutilized in global mental health research, presenting new opportunities to examine power dynamics across various contexts. Drawing on Hart's ladder, our study examined youth engagement in mental health research across high‐ and middle‐income countries using Internet‐based technologies, evaluating youth involvement in decision‐making and presenting research stages that illustrate these engagements. Methods: We conducted a directed content analysis of youth engagement in the study using primary data from project documents, weekly AirTable updates and discussions and interviews with youth and the research consortium. Using Hart's Ladder as a framework, we describe youth engagement along rungs throughout different research stages: cross‐cutting research process, onboarding, formative research and quantitative and qualitative study designs. Results: Youth engagement in the MindKind study fluctuated between Rung 4 ('Assign, but informed') and Rung 7 ('Youth initiated and directed') on Hart's Ladder. Engagement was minimal in the early project stages as project structures and goals were defined, with some youth feeling that their experiences were underutilized and many decisions being adult‐led. Communication challenges and structural constraints, like tight timelines and limited budget, hindered youth engagement in highest ladder rungs. Despite these obstacles, youth engagement increased, particularly in developing recruitment strategies and in shaping data governance models and the qualitative study design. Youth helped refine research tools and protocols, resulting in moderate to substantial engagement in the later research stages. Conclusion: Our findings emphasize the value of youth–adult partnerships, which offer promise in amplifying voices and nurturing skills, leadership and inclusiveness of young people. Youth engagement in project decision‐making progressed from lower to higher rungs on Hart's Ladder over time; however, this was not linear. Effective youth engagement requires dynamic strategies, transparent communication and mutual respect, shaping outcomes that authentically reflect diverse perspectives and mental health experiences. Patient or Public Contribution: There was substantial patient and public involvement in this study. This paper reports findings on youth engagement conducted with 35 young people from India, South Africa and the United Kingdom, all of whom had lived experience of mental health challenges. Youth engagement in the MindKind study was coordinated and led by three professional youth advisors (PYAs) in these contexts, who were also young people with lived experience of mental health challenges. Each of the three study sites embedded a full‐time, community‐based PYA within their study team to inform all aspects of the research project, including the development of informational materials and the facilitation of Young People's Advisory Group (YPAG) sessions referenced in this paper. Each PYA also consulted with a site‐specific YPAG that met bi‐monthly throughout the project, shaping the formation of study materials and serving as a test group in both the quantitative and qualitative studies. Youth participants in this study also contributed extensively, engaging in data collection and manuscript writing. The following youth advisory panels members (J.B., L.B., D.O.J., M.V.) and all PYAs (E.B., S.R., R.S.) in the MindKind study contributed to the writing of this manuscript and are acknowledged as co‐authors. [ABSTRACT FROM AUTHOR]

Published
2024
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15. Common dysregulation network in the human prefrontal cortex underlies two neurodegenerative diseases.

Author

Narayanan, Manikandan, Huynh, Jimmy L, Wang, Kai, Yang, Xia, Yoo, Seungyeul, McElwee, Joshua, Zhang, Bin, Zhang, Chunsheng, Lamb, John R, Xie, Tao, Suver, Christine, Molony, Cliona, Melquist, Stacey, Johnson, Andrew D, Fan, Guoping, Stone, David J, Schadt, Eric E, Casaccia, Patrizia, Emilsson, Valur, and Zhu, Jun

Subjects
Prefrontal Cortex, Chromatin, Animals, Mice, Knockout, Humans, Mice, Huntington Disease, Dementia, Alzheimer Disease, Autopsy, Case-Control Studies, Reproducibility of Results, Gene Expression Profiling, Gene Expression Regulation, Gene Regulatory Networks, DNA (Cytosine-5-)-Methyltransferase 1, DNA (Cytosine-5-)-Methyltransferases, differential co‐expression, dysregulatory gene networks, epigenetic regulation of neural differentiation, network alignment, neurodegenerative diseases, differential co-expression, Knockout, DNA (Cytosine-5-)-Methyltransferase, Bioinformatics, Biochemistry and Cell Biology, Other Biological Sciences
Abstract

Using expression profiles from postmortem prefrontal cortex samples of 624 dementia patients and non-demented controls, we investigated global disruptions in the co-regulation of genes in two neurodegenerative diseases, late-onset Alzheimer's disease (AD) and Huntington's disease (HD). We identified networks of differentially co-expressed (DC) gene pairs that either gained or lost correlation in disease cases relative to the control group, with the former dominant for both AD and HD and both patterns replicating in independent human cohorts of AD and aging. When aligning networks of DC patterns and physical interactions, we identified a 242-gene subnetwork enriched for independent AD/HD signatures. This subnetwork revealed a surprising dichotomy of gained/lost correlations among two inter-connected processes, chromatin organization and neural differentiation, and included DNA methyltransferases, DNMT1 and DNMT3A, of which we predicted the former but not latter as a key regulator. To validate the inter-connection of these two processes and our key regulator prediction, we generated two brain-specific knockout (KO) mice and show that Dnmt1 KO signature significantly overlaps with the subnetwork (P = 3.1 × 10(-12)), while Dnmt3a KO signature does not (P = 0.017).

Published
2014

16. The N3C governance ecosystem: a model socio-technical partnership for the future of collaborative analytics at scale

Author

Suver, Christine, primary, Harper, Jeremy, additional, Loomba, Johanna, additional, Saltz, Mary, additional, Solway, Julian, additional, Anzalone, Alfred Jerrod, additional, Walters, Kellie, additional, Pfaff, Emily, additional, Walden, Anita, additional, McMurry, Julie, additional, Chute, Christopher G, additional, and Haendel, Melissa, additional

Published
2023
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17. Nonelective coronary artery bypass graft outcomes are adversely impacted by Coronavirus disease 2019 infection, but not altered processes of care: A National COVID Cohort Collaborative and National Surgery Quality Improvement Program analysis

Author

Grimsley, Emily A., primary, Torikashvili, Johnathan V., additional, Janjua, Haroon M., additional, Read, Meagan D., additional, Kothari, Anai N., additional, Verhagen, Nate B., additional, Pietrobon, Ricardo, additional, Kuo, Paul C., additional, Rogers, Michael P., additional, Wilcox, Adam B., additional, Lee, Adam M., additional, Graves, Alexis, additional, Anzalone, Alfred (Jerrod), additional, Manna, Amin, additional, Saha, Amit, additional, Olex, Amy, additional, Zhou, Andrea, additional, Williams, Andrew E., additional, Southerland, Andrew, additional, Girvin, Andrew T., additional, Walden, Anita, additional, Sharathkumar, Anjali A., additional, Amor, Benjamin, additional, Bates, Benjamin, additional, Hendricks, Brian, additional, Patel, Brijesh, additional, Alexander, Caleb, additional, Bramante, Carolyn, additional, Ward-Caviness, Cavin, additional, Madlock-Brown, Charisse, additional, Suver, Christine, additional, Chute, Christopher, additional, Dillon, Christopher, additional, Wu, Chunlei, additional, Schmitt, Clare, additional, Takemoto, Cliff, additional, Housman, Dan, additional, Gabriel, Davera, additional, Eichmann, David A., additional, Mazzotti, Diego, additional, Brown, Don, additional, Boudreau, Eilis, additional, Hill, Elaine, additional, Zampino, Elizabeth, additional, Marti, Emily Carlson, additional, Pfaff, Emily R., additional, French, Evan, additional, Koraishy, Farrukh M., additional, Mariona, Federico, additional, Prior, Fred, additional, Sokos, George, additional, Martin, Greg, additional, Lehmann, Harold, additional, Spratt, Heidi, additional, Mehta, Hemalkumar, additional, Liu, Hongfang, additional, Sidky, Hythem, additional, Hayanga, J.W. Awori, additional, Pincavitch, Jami, additional, Clark, Jaylyn, additional, Harper, Jeremy Richard, additional, Islam, Jessica, additional, Ge, Jin, additional, Gagnier, Joel, additional, Saltz, Joel H., additional, Saltz, Joel, additional, Loomba, Johanna, additional, Buse, John, additional, Mathew, Jomol, additional, Rutter, Joni L., additional, McMurry, Julie A., additional, Guinney, Justin, additional, Starren, Justin, additional, Crowley, Karen, additional, Bradwell, Katie Rebecca, additional, Walters, Kellie M., additional, Wilkins, Ken, additional, Gersing, Kenneth R., additional, Cato, Kenrick Dwain, additional, Murray, Kimberly, additional, Kostka, Kristin, additional, Northington, Lavance, additional, Pyles, Lee Allan, additional, Misquitta, Leonie, additional, Cottrell, Lesley, additional, Portilla, Lili, additional, Deacy, Mariam, additional, Bissell, Mark M., additional, Clark, Marshall, additional, Emmett, Mary, additional, Saltz, Mary Morrison, additional, Palchuk, Matvey B., additional, Haendel, Melissa A., additional, Adams, Meredith, additional, Temple-O'Connor, Meredith, additional, Kurilla, Michael G., additional, Morris, Michele, additional, Qureshi, Nabeel, additional, Safdar, Nasia, additional, Garbarini, Nicole, additional, Sharafeldin, Noha, additional, Sadan, Ofer, additional, Francis, Patricia A., additional, Burgoon, Penny Wung, additional, Robinson, Peter, additional, Payne, Philip R.O., additional, Fuentes, Rafael, additional, Jawa, Randeep, additional, Erwin-Cohen, Rebecca, additional, Patel, Rena, additional, Moffitt, Richard A., additional, Zhu, Richard L., additional, Kamaleswaran, Rishi, additional, Hurley, Robert, additional, Miller, Robert T., additional, Pyarajan, Saiju, additional, Michael, Sam G., additional, Bozzette, Samuel, additional, Mallipattu, Sandeep, additional, Vedula, Satyanarayana, additional, Chapman, Scott, additional, O'Neil, Shawn T., additional, Setoguchi, Soko, additional, Hong, Stephanie S., additional, Johnson, Steve, additional, Bennett, Tellen D., additional, Callahan, Tiffany, additional, Topaloglu, Umit, additional, Sheikh, Usman, additional, Gordon, Valery, additional, Subbian, Vignesh, additional, Kibbe, Warren A., additional, Hernandez, Wenndy, additional, Beasley, Will, additional, Cooper, Will, additional, Hillegass, William, additional, and Zhang, Xiaohan Tanner, additional

Published
2023
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20. Meta-analysis of Dense Genecentric Association Studies Reveals Common and Uncommon Variants Associated with Height

Author

Lanktree, Matthew B, Guo, Yiran, Murtaza, Muhammed, Glessner, Joseph T, Bailey, Swneke D, Onland-Moret, N Charlotte, Lettre, Guillaume, Ongen, Halit, Rajagopalan, Ramakrishnan, Johnson, Toby, Shen, Haiqing, Nelson, Christopher P, Klopp, Norman, Baumert, Jens, Padmanabhan, Sandosh, Pankratz, Nathan, Pankow, James S, Shah, Sonia, Taylor, Kira, Barnard, John, Peters, Bas J, Maloney, Cliona M, Lobmeyer, Maximilian T, Stanton, Alice, Zafarmand, M Hadi, Romaine, Simon PR, Mehta, Amar, van Iperen, Erik PA, Gong, Yan, Price, Tom S, Smith, Erin N, Kim, Cecilia E, Li, Yun R, Asselbergs, Folkert W, Atwood, Larry D, Bailey, Kristian M, Bhatt, Deepak, Bauer, Florianne, Behr, Elijah R, Bhangale, Tushar, Boer, Jolanda MA, Boehm, Bernhard O, Bradfield, Jonathan P, Brown, Morris, Braund, Peter S, Burton, Paul R, Carty, Cara, Chandrupatla, Hareesh R, Chen, Wei, Connell, John, Dalgeorgou, Chrysoula, de Boer, Anthonius, Drenos, Fotios, Elbers, Clara C, Fang, James C, Fox, Caroline S, Frackelton, Edward C, Fuchs, Barry, Furlong, Clement E, Gibson, Quince, Gieger, Christian, Goel, Anuj, Grobbee, Diederik E, Hastie, Claire, Howard, Philip J, Huang, Guan-Hua, Johnson, W Craig, Li, Qing, Kleber, Marcus E, Klein, Barbara EK, Klein, Ronald, Kooperberg, Charles, Ky, Bonnie, LaCroix, Andrea, Lanken, Paul, Lathrop, Mark, Li, Mingyao, Marshall, Vanessa, Melander, Olle, Mentch, Frank D, Meyer, Nuala J, Monda, Keri L, Montpetit, Alexandre, Murugesan, Gurunathan, Nakayama, Karen, Nondahl, Dave, Onipinla, Abiodun, Rafelt, Suzanne, Newhouse, Stephen J, Otieno, F George, Patel, Sanjey R, Putt, Mary E, Rodriguez, Santiago, Safa, Radwan N, Sawyer, Douglas B, Schreiner, Pamela J, Simpson, Claire, Sivapalaratnam, Suthesh, Srinivasan, Sathanur R, and Suver, Christine

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Adult, Black or African American, Asian People, Body Height, Cardiovascular System, Female, Gene Frequency, Genetic Heterogeneity, Genetic Loci, Genome-Wide Association Study, Hispanic or Latino, Humans, Interleukin-11, Male, Polymorphism, Single Nucleotide, Smad3 Protein, White People, Hugh Watkins on behalf of PROCARDIS, Meena Kumari on behalf of the Whitehall II Study and the WHII 50K Group, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Height is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 × 10(-6)), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 × 10(-8)). Common variants with minor allele frequencies greater than 5% were observed to be associated with height in 37 previously reported loci. In individuals of European ancestry, uncommon SNPs in IL11 and SMAD3, which would not be genotyped with the use of standard genome-wide genotyping arrays, were strongly associated with height (p < 3 × 10(-11)). Conditional analysis within associated regions revealed five additional variants associated with height independent of lead SNPs within the locus, suggesting allelic heterogeneity. Although underpowered to replicate findings from individuals of European ancestry, the direction of effect of associated variants was largely consistent in African American, South Asian, and Hispanic populations. Overall, we show that dense coverage of genes for uncommon SNPs, coupled with large-scale meta-analysis, can successfully identify additional variants associated with a common complex trait.

Published
2011

21. Systematic genetic and genomic analysis of cytochrome P450 enzyme activities in human liver

Author

Yang, Xia, Zhang, Bin, Molony, Cliona, Chudin, Eugene, Hao, Ke, Zhu, Jun, Gaedigk, Andrea, Suver, Christine, Zhong, Hua, Leeder, J Steven, Guengerich, F Peter, Strom, Stephen C, Schuetz, Erin, Rushmore, Thomas H, Ulrich, Roger G, Slatter, J Greg, Schadt, Eric E, Kasarskis, Andrew, and Lum, Pek Yee

Subjects
Biotechnology, Genetics, Digestive Diseases, Liver Disease, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Adolescent, Adult, Aged, Aged, 80 and over, Animals, Child, Child, Preschool, Cytochrome P-450 Enzyme System, Female, Gene Expression, Gene Expression Regulation, Enzymologic, Genome-Wide Association Study, Genomics, Humans, Infant, Infant, Newborn, Liver, Male, Mice, Middle Aged, Pharmaceutical Preparations, Polymorphism, Single Nucleotide, Rats, Systems Biology, Transcription, Genetic, Young Adult, Biological Sciences, Medical and Health Sciences, Bioinformatics
Abstract

Liver cytochrome P450s (P450s) play critical roles in drug metabolism, toxicology, and metabolic processes. Despite rapid progress in the understanding of these enzymes, a systematic investigation of the full spectrum of functionality of individual P450s, the interrelationship or networks connecting them, and the genetic control of each gene/enzyme is lacking. To this end, we genotyped, expression-profiled, and measured P450 activities of 466 human liver samples and applied a systems biology approach via the integration of genetics, gene expression, and enzyme activity measurements. We found that most P450s were positively correlated among themselves and were highly correlated with known regulators as well as thousands of other genes enriched for pathways relevant to the metabolism of drugs, fatty acids, amino acids, and steroids. Genome-wide association analyses between genetic polymorphisms and P450 expression or enzyme activities revealed sets of SNPs associated with P450 traits, and suggested the existence of both cis-regulation of P450 expression (especially for CYP2D6) and more complex trans-regulation of P450 activity. Several novel SNPs associated with CYP2D6 expression and enzyme activity were validated in an independent human cohort. By constructing a weighted coexpression network and a Bayesian regulatory network, we defined the human liver transcriptional network structure, uncovered subnetworks representative of the P450 regulatory system, and identified novel candidate regulatory genes, namely, EHHADH, SLC10A1, and AKR1D1. The P450 subnetworks were then validated using gene signatures responsive to ligands of known P450 regulators in mouse and rat. This systematic survey provides a comprehensive view of the functionality, genetic control, and interactions of P450s.

Published
2010

22. Liver and adipose expression associated SNPs are enriched for association to type 2 diabetes.

Author

Zhong, Hua, Beaulaurier, John, Lum, Pek Yee, Molony, Cliona, Yang, Xia, Macneil, Douglas J, Weingarth, Drew T, Zhang, Bin, Greenawalt, Danielle, Dobrin, Radu, Hao, Ke, Woo, Sangsoon, Fabre-Suver, Christine, Qian, Su, Tota, Michael R, Keller, Mark P, Kendziorski, Christina M, Yandell, Brian S, Castro, Victor, Attie, Alan D, Kaplan, Lee M, and Schadt, Eric E

Subjects
Liver, Adipose Tissue, Animals, Mice, Inbred C57BL, Mice, Knockout, Humans, Mice, Mice, Obese, Diabetes Mellitus, Type 2, DNA-Binding Proteins, Transcription Factors, Cohort Studies, Gene Expression, Polymorphism, Single Nucleotide, Female, Male, Genome-Wide Association Study, Diabetes Mellitus, Type 2, Inbred C57BL, Knockout, Obese, Polymorphism, Single Nucleotide, Genetics, Developmental Biology
Abstract

Genome-wide association studies (GWAS) have demonstrated the ability to identify the strongest causal common variants in complex human diseases. However, to date, the massive data generated from GWAS have not been maximally explored to identify true associations that fail to meet the stringent level of association required to achieve genome-wide significance. Genetics of gene expression (GGE) studies have shown promise towards identifying DNA variations associated with disease and providing a path to functionally characterize findings from GWAS. Here, we present the first empiric study to systematically characterize the set of single nucleotide polymorphisms associated with expression (eSNPs) in liver, subcutaneous fat, and omental fat tissues, demonstrating these eSNPs are significantly more enriched for SNPs that associate with type 2 diabetes (T2D) in three large-scale GWAS than a matched set of randomly selected SNPs. This enrichment for T2D association increases as we restrict to eSNPs that correspond to genes comprising gene networks constructed from adipose gene expression data isolated from a mouse population segregating a T2D phenotype. Finally, by restricting to eSNPs corresponding to genes comprising an adipose subnetwork strongly predicted as causal for T2D, we dramatically increased the enrichment for SNPs associated with T2D and were able to identify a functionally related set of diabetes susceptibility genes. We identified and validated malic enzyme 1 (Me1) as a key regulator of this T2D subnetwork in mouse and provided support for the association of this gene to T2D in humans. This integration of eSNPs and networks provides a novel approach to identify disease susceptibility networks rather than the single SNPs or genes traditionally identified through GWAS, thereby extracting additional value from the wealth of data currently being generated by GWAS.

Published
2010

23. Hormone Replacement Therapy and COVID-19 Outcomes in Solid Organ Transplant Recipients Compared with the General Population

Author

Vinson, Amanda J., primary, Anzalone, Alfred, additional, Schissel, Makayla, additional, Dai, Ran, additional, French, Evan T., additional, Olex, Amy L., additional, Mannon, Roslyn B., additional, Wilcox, Adam B., additional, Lee, Adam M., additional, Graves, Alexis, additional, Anzalone, Alfred Jerrod, additional, Manna, Amin, additional, Saha, Amit, additional, Olex, Amy, additional, Zhou, Andrea, additional, Williams, Andrew E., additional, Southerland, Andrew, additional, Girvin, Andrew T., additional, Walden, Anita, additional, Sharathkumar, Anjali A., additional, Amor, Benjamin, additional, Bates, Benjamin, additional, Hendricks, Brian, additional, Patel, Brijesh, additional, Alexander, Caleb, additional, Bramante, Carolyn, additional, Ward-Caviness, Cavin, additional, Madlock-Brown, Charisse, additional, Suver, Christine, additional, Chute, Christopher, additional, Dillon, Christopher, additional, Wu, Chunlei, additional, Schmitt, Clare, additional, Takemoto, Cliff, additional, Housman, Dan, additional, Gabriel, Davera, additional, Eichmann, David A., additional, Mazzotti, Diego, additional, Brown, Don, additional, Boudreau, Eilis, additional, Hill, Elaine, additional, Zampino, Elizabeth, additional, Marti, Emily Carlson, additional, Pfaff, Emily R., additional, French, Evan, additional, Koraishy, Farrukh M., additional, Mariona, Federico, additional, Prior, Fred, additional, Sokos, George, additional, Martin, Greg, additional, Lehmann, Harold, additional, Spratt, Heidi, additional, Mehta, Hemalkumar, additional, Liu, Hongfang, additional, Sidky, Hythem, additional, Hayanga, J.W. Awori, additional, Pincavitch, Jami, additional, Clark, Jaylyn, additional, Harper, Jeremy Richard, additional, Islam, Jessica, additional, Ge, Jin, additional, Gagnier, Joel, additional, Saltz, Joel H., additional, Saltz, Joel, additional, Loomba, Johanna, additional, Buse, John, additional, Mathew, Jomol, additional, Rutter, Joni L., additional, McMurry, Julie A., additional, Guinney, Justin, additional, Starren, Justin, additional, Crowley, Karen, additional, Bradwell, Katie Rebecca, additional, Walters, Kellie M., additional, Wilkins, Ken, additional, Gersing, Kenneth R., additional, Cato, Kenrick Dwain, additional, Murray, Kimberly, additional, Kostka, Kristin, additional, Northington, Lavance, additional, Pyles, Lee Allan, additional, Misquitta, Leonie, additional, Cottrell, Lesley, additional, Portilla, Lili, additional, Deacy, Mariam, additional, Bissell, Mark M., additional, Clark, Marshall, additional, Emmett, Mary, additional, Saltz, Mary Morrison, additional, Palchuk, Matvey B., additional, Haendel, Melissa A., additional, Adams, Meredith, additional, Temple-O'Connor, Meredith, additional, Kurilla, Michael G., additional, Morris, Michele, additional, Qureshi, Nabeel, additional, Safdar, Nasia, additional, Garbarini, Nicole, additional, Sharafeldin, Noha, additional, Sadan, Ofer, additional, Francis, Patricia A., additional, Burgoon, Penny Wung, additional, Robinson, Peter, additional, Payne, Philip R.O., additional, Fuentes, Rafael, additional, Jawa, Randeep, additional, Erwin-Cohen, Rebecca, additional, Patel, Rena, additional, Moffitt, Richard A., additional, Zhu, Richard L., additional, Kamaleswaran, Rishi, additional, Hurley, Robert, additional, Miller, Robert T., additional, Pyarajan, Saiju, additional, Michael, Sam G., additional, Bozzette, Samuel, additional, Mallipattu, Sandeep, additional, Vedula, Satyanarayana, additional, Chapman, Scott, additional, O'Neil, Shawn T., additional, Setoguchi, Soko, additional, Hong, Stephanie S., additional, Johnson, Steve, additional, Bennett, Tellen D., additional, Callahan, Tiffany, additional, Topaloglu, Umit, additional, Sheikh, Usman, additional, Gordon, Valery, additional, Subbian, Vignesh, additional, Kibbe, Warren A., additional, Hernandez, Wenndy, additional, Beasley, Will, additional, Cooper, Will, additional, Hillegass, William, additional, and Zhang, Xiaohan Tanner, additional

Published
2023
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24. Young people's data governance preferences for their mental health data: MindKind Study findings from India, South Africa, and the United Kingdom

Author

Sieberts, Solveig K., Marten, Carly, Bampton, Emily, Björling, Elin A., Burn, Anne-Marie, Carey, Emma Grace, Carlson, Sonia, Fernandes, Blossom, Kalha, Jasmine, Lindani, Simthembile, Masomera, Hedwick, Neelakantan, Lakshmi, Pasquale, Lisa, Ranganathan, Swetha, Joy Scanlan, Erin, Shah, Himani, Sibisi, Refiloe, Sumant, Sushmita, Suver, Christine, Thungana, Yanga, Tummalacherla, Meghasyam, Velloza, Jennifer, Collins, Pamela Y., Fazel, Mina, Ford, Tamsin, Freeman, Melvyn, Pathare, Soumitra, Zingela, Zukiswa, The MindKind Consortium, Doerr, Megan, Ramalho, André, Marten, Carly [0000-0003-3942-310X], Burn, Anne-Marie [0000-0002-0637-2118], Carey, Emma Grace [0000-0002-2294-7989], Carlson, Sonia [0000-0002-1413-4056], Thungana, Yanga [0000-0001-9854-314X], Velloza, Jennifer [0000-0001-7242-7415], Doerr, Megan [0000-0003-2383-5978], and Apollo - University of Cambridge Repository

Subjects
Medicine and health sciences, Adult, Pediatric, Biology and life sciences, Adolescent, General Science & Technology, Clinical Trials and Supportive Activities, India, Social sciences, United Kingdom, Research and analysis methods, South Africa, Young Adult, Mental Health, Good Health and Well Being, 7.1 Individual care needs, Clinical Research, Behavioral and Social Science, Humans, Management of diseases and conditions, People and places, Qualitative Research, Research Article, MindKind Consortium
Abstract

Mobile devices offer a scalable opportunity to collect longitudinal data that facilitate advances in mental health treatment to address the burden of mental health conditions in young people. Sharing these data with the research community is critical to gaining maximal value from rich data of this nature. However, the highly personal nature of the data necessitates understanding the conditions under which young people are willing to share them. To answer this question, we developed the MindKind Study, a multinational, mixed methods study that solicits young people’s preferences for how their data are governed and quantifies potential participants’ willingness to join under different conditions. We employed a community-based participatory approach, involving young people as stakeholders and co-researchers. At sites in India, South Africa, and the UK, we enrolled 3575 participants ages 16–24 in the mobile app-mediated quantitative study and 143 participants in the public deliberation-based qualitative study. We found that while youth participants have strong preferences for data governance, these preferences did not translate into (un)willingness to join the smartphone-based study. Participants grappled with the risks and benefits of participation as well as their desire that the “right people” access their data. Throughout the study, we recognized young people’s commitment to finding solutions and co-producing research architectures to allow for more open sharing of mental health data to accelerate and derive maximal benefit from research.

Published
2023

27. Remote smartphone monitoring of Parkinson’s disease and individual response to therapy

Author

Omberg, Larsson, primary, Chaibub Neto, Elias, additional, Perumal, Thanneer M., additional, Pratap, Abhishek, additional, Tediarjo, Aryton, additional, Adams, Jamie, additional, Bloem, Bastiaan R., additional, Bot, Brian M., additional, Elson, Molly, additional, Goldman, Samuel M., additional, Kellen, Michael R., additional, Kieburtz, Karl, additional, Klein, Arno, additional, Little, Max A., additional, Schneider, Ruth, additional, Suver, Christine, additional, Tarolli, Christopher, additional, Tanner, Caroline M., additional, Trister, Andrew D., additional, Wilbanks, John, additional, Dorsey, E. Ray, additional, and Mangravite, Lara M., additional

Published
2021
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28. NP2021_mHealth Wearables and Apps A Changing Privacy Landscape

Author

Suver, Christine

Subjects
Data_MISCELLANEOUS
Abstract

Slides from “Privacy: global perspectives"Description: mHealth Wearables and Apps: A changing privacy landscapeThe use of wearables and smartphone apps to collect health-related data (mHealth) is a growing field. Wearable and health apps can continuously monitor our physical activity, sleep, heart rate, glucose levels, etc. They provide a rich data set that can supplement the data from occasional doctor's visit. But what are the privacy considerations of mHealth? We will explore global privacy principles, discuss the tension between anonymity and data utility, and propose ways to improve privacy notices/policies.

Published
2021
Full Text
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29. Assessment of network module identification across complex diseases

Author

Choobdar, Sarvenaz, Ahsen, Mehmet E., Natoli, Ted, Lysenko, Artem, Ma, Tianle, Mall, Raghvendra, Marbach, Daniel, Mattia, Tomasoni, Medvedovic, Mario, Menche, Jörg, Mercer, Johnathan, Micarelli, Elisa, Monaco, Alfonso, Narayan, Rajiv, Müller, Felix, Narykov, Oleksandr, Norman, Thea, Park, Sungjoon, Perfetto, Livia, Perrin, Dimitri, Pirrò, Stefano, Przytycka, Teresa M., DREAM Module Identification Challenge Consortium, Qian, Xiaoning, Raman, Karthik, Ramazzotti, Daniele, Ramsahai, Emilie, Ravindran, Balaraman, Rennert, Philip, Sáez Rodríguez, Julio, Schärfe, Charlotta, Sharan, Roded, Shi, Ning, Subramanian, Aravind, Shin, Wonho, Shu, Hai, Sinha, Himanshu, Slonim, Donna K., Spinelli, Lionel, Srinivasan, Suhas, Suver, Christine, Szklarczyk, Damian, Tangaro, Sabina, Zhang, Jitao D., Thiagarajan, Suresh, Tichit, Laurent, Tiede, Thorsten, Tripathi, Beethika, Tsherniak, Aviad, Tsunoda, Tatsuhiko, Türei, Dénes, Ullah, Ehsan, Vahedi, Golnaz, Valdeolivas, Alberto, Stolovitzky, Gustavo, Vivek, Jayaswal, von Mering, Christian, Waagmeester, Andra, Wang, Bo, Wang, Yijie, Weir, Barbara A., White, Shana, Winkler, Sebastian, Xu, Ke, Xu, Taosheng, Kutalik, Zoltán, Yan, Chunhua, Yang, Liuqing, Yu, Kaixian, Yu, Xiangtian, Zaffaroni, Gaia, Zaslavskiy, Mikhail, Zeng, Tao, Zhang, Lu, Zhang, Weijia, Lage, Kasper, Zhang, Lixia, Zhang, Xinyu, Zhang, Junpeng, Zhou, Xin, Zhou, Jiarui, Zhu, Hongtu, Zhu, Junjie, Zuccon, Guido, Crawford, Jake, Cowen, Lenore J., Bergmann, Sven, Aicheler, Fabian, Amoroso, Nicola, Arenas, Alex, Azhagesan, Karthik, Baker, Aaron, Banf, Michael, Batzoglou, Serafim, Tomasoni, Mattia, Baudot, Anaïs, Bellotti, Roberto, Boroevich, Keith A., Brun, Christine, Cai, Stanley, Caldera, Michael, Calderone, Alberto, Cesareni, Gianni, Chen, Weiqi, Fang, Tao, Chichester, Christine, Cowen, Lenore, Cui, Hongzhu, Dao, Phuong, De Domenico, Manlio, Dhroso, Andi, Didier, Gilles, Divine, Mathew, Lamparter, David, Del Sol, Antonio, Feng, Xuyang, Flores-Canales, Jose C., Fortunato, Santo, Gitter, Anthony, Gorska, Anna, Guan, Yuanfang, Guénoche, Alain, Gómez, Sergio, Lin, Junyuan, Hamza, Hatem, Hartmann, András, He, Shan, Heijs, Anton, Heinrich, Julian, Hescott, Benjamin, Hu, Xiaozhe, Hu, Ying, Huang, Xiaoqing, Hughitt, V. Keith, Jeon, Minji, Jeub, Lucas, Johnson, Nathan T., Joo, Keehyoung, Joung, InSuk, Jung, Sascha, Kalko, Susana G., Kamola, Piotr J., Kang, Jaewoo, Kaveelerdpotjana, Benjapun, Kim, Minjun, Kim, Yoo-Ah, Kohlbacher, Oliver, Korkin, Dmitry, Krzysztof, Kiryluk, Kunji, Khalid, Kutalik, Zoltàn, Lang-Brown, Sean, Le, Thuc Duy, Lee, Jooyoung, Lee, Sunwon, Lee, Juyong, Li, Dong, Li, Jiuyong, Liu, Lin, Loizou, Antonis, Luo, Zhenhua, Choobdar, Sarvenaz, Ahsen, Mehmet E., Crawford, Jake, Tomasoni, Mattia, Le, Thuc Duy, Li, Jiuyong, Liu, Lin, Zhang, W, Marbach, D, The DREAM Module Identification Challenge Consortium, Choobdar, S, Ahsen, M, Crawford, J, Tomasoni, M, Fang, T, Lamparter, D, Lin, J, Hescott, B, Hu, X, Mercer, J, Natoli, T, Narayan, R, Aicheler, F, Amoroso, N, Arenas, A, Azhagesan, K, Baker, A, Banf, M, Batzoglou, S, Baudot, A, Bellotti, R, Bergmann, S, Boroevich, K, Brun, C, Cai, S, Caldera, M, Calderone, A, Cesareni, G, Chen, W, Chichester, C, Cowen, L, Cui, H, Dao, P, De Domenico, M, Dhroso, A, Didier, G, Divine, M, del Sol, A, Feng, X, Flores-Canales, J, Fortunato, S, Gitter, A, Gorska, A, Guan, Y, Guenoche, A, Gomez, S, Hamza, H, Hartmann, A, He, S, Heijs, A, Heinrich, J, Hu, Y, Huang, X, Hughitt, V, Jeon, M, Jeub, L, Johnson, N, Joo, K, Joung, I, Jung, S, Kalko, S, Kamola, P, Kang, J, Kaveelerdpotjana, B, Kim, M, Kim, Y, Kohlbacher, O, Korkin, D, Krzysztof, K, Kunji, K, Kutalik, Z, Lage, K, Lang-Brown, S, Le, T, Lee, J, Lee, S, Li, D, Li, J, Liu, L, Loizou, A, Luo, Z, Lysenko, A, Ma, T, Mall, R, Mattia, T, Medvedovic, M, Menche, J, Micarelli, E, Monaco, A, Muller, F, Narykov, O, Norman, T, Park, S, Perfetto, L, Perrin, D, Pirro, S, Przytycka, T, Qian, X, Raman, K, Ramazzotti, D, Ramsahai, E, Ravindran, B, Rennert, P, Saez-Rodriguez, J, Scharfe, C, Sharan, R, Shi, N, Shin, W, Shu, H, Sinha, H, Slonim, D, Spinelli, L, Srinivasan, S, Subramanian, A, Suver, C, Szklarczyk, D, Tangaro, S, Thiagarajan, S, Tichit, L, Tiede, T, Tripathi, B, Tsherniak, A, Tsunoda, T, Turei, D, Ullah, E, Vahedi, G, Valdeolivas, A, Vivek, J, von Mering, C, Waagmeester, A, Wang, B, Wang, Y, Weir, B, White, S, Winkler, S, Xu, K, Xu, T, Yan, C, Yang, L, Yu, K, Yu, X, Zaffaroni, G, Zaslavskiy, M, Zeng, T, Zhang, J, Zhang, L, Zhang, X, Zhou, X, Zhou, J, Zhu, H, Zhu, J, Zuccon, G, Stolovitzky, G, Spinelli, Lionel, Institut de Mathématiques de Marseille (I2M), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS), Marseille medical genetics - Centre de génétique médicale de Marseille (MMG), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Theories and Approaches of Genomic Complexity (TAGC), DREAM Module Identification Challenge Consortium, Aicheler, F., Amoroso, N., Arenas, A., Azhagesan, K., Baker, A., Banf, M., Batzoglou, S., Baudot, A., Bellotti, R., Bergmann, S., Boroevich, K.A., Brun, C., Cai, S., Caldera, M., Calderone, A., Cesareni, G., Chen, W., Chichester, C., Choobdar, S., Cowen, L., Crawford, J., Cui, H., Dao, P., De Domenico, M., Dhroso, A., Didier, G., Divine, M., Del Sol, A., Fang, T., Feng, X., Flores-Canales, J.C., Fortunato, S., Gitter, A., Gorska, A., Guan, Y., Guénoche, A., Gómez, S., Hamza, H., Hartmann, A., He, S., Heijs, A., Heinrich, J., Hescott, B., Hu, X., Hu, Y., Huang, X., Hughitt, V.K., Jeon, M., Jeub, L., Johnson, N.T., Joo, K., Joung, I., Jung, S., Kalko, S.G., Kamola, P.J., Kang, J., Kaveelerdpotjana, B., Kim, M., Kim, Y.A., Kohlbacher, O., Korkin, D., Krzysztof, K., Kunji, K., Kutalik, Z., Lage, K., Lamparter, D., Lang-Brown, S., Le, T.D., Lee, J., Lee, S., Li, D., Li, J., Lin, J., Liu, L., Loizou, A., Luo, Z., Lysenko, A., Ma, T., Mall, R., Marbach, D., Mattia, T., Medvedovic, M., Menche, J., Mercer, J., Micarelli, E., Monaco, A., Müller, F., Narayan, R., Narykov, O., Natoli, T., Norman, T., Park, S., Perfetto, L., Perrin, D., Pirrò, S., Przytycka, T.M., Qian, X., Raman, K., Ramazzotti, D., Ramsahai, E., Ravindran, B., Rennert, P., Saez-Rodriguez, J., Schärfe, C., Sharan, R., Shi, N., Shin, W., Shu, H., Sinha, H., Slonim, D.K., Spinelli, L., Srinivasan, S., Subramanian, A., Suver, C., Szklarczyk, D., Tangaro, S., Thiagarajan, S., Tichit, L., Tiede, T., Tripathi, B., Tsherniak, A., Tsunoda, T., Türei, D., Ullah, E., Vahedi, G., Valdeolivas, A., Vivek, J., von Mering, C., Waagmeester, A., Wang, B., Wang, Y., Weir, B.A., White, S., Winkler, S., Xu, K., Xu, T., Yan, C., Yang, L., Yu, K., Yu, X., Zaffaroni, G., Zaslavskiy, M., Zeng, T., Zhang, J.D., Zhang, L., Zhang, W., Zhang, X., Zhang, J., Zhou, X., Zhou, J., Zhu, H., Zhu, J., and Zuccon, G.

Subjects
Identification methods, Cellular signalling networks, Computer science, Population genetics, [SDV]Life Sciences [q-bio], Quantitative Trait Loci, Gene regulatory network, DREAM challenge, network, modules, predictions, Genome-wide association study, Computational biology, Biochemistry, Models, Biological, Polymorphism, Single Nucleotide, Gene regulatory networks, Functional clustering, 03 medical and health sciences, Human disease, Humans, Disease, ddc:610, Protein Interaction Maps, Molecular Biology, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 0303 health sciences, Network module, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Network topology, Gene Expression Profiling, Computational Biology, Cell Biology, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Gene expression profiling, [SDV] Life Sciences [q-bio], Molecular network, Phenotype, Protein network, Network Module Identification, Analysis, Algorithms, Biotechnology, Genome-Wide Association Study
Abstract

Many bioinformatics methods have been proposed for reducing the complexity of large gene or protein networks into relevant subnetworks or modules. Yet, how such methods compare to each other in terms of their ability to identify disease-relevant modules in different types of network remains poorly understood. We launched the ‘Disease Module Identification DREAM Challenge’, an open competition to comprehensively assess module identification methods across diverse protein–protein interaction, signaling, gene co-expression, homology and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies. Our robust assessment of 75 module identification methods reveals top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets. This community challenge establishes biologically interpretable benchmarks, tools and guidelines for molecular network analysis to study human disease biology., In this DREAM challenge, 75 methods for the identification of disease-relevant modules from molecular networks are compared and validated with GWAS data. The authors provide practical guidelines for users and establish benchmarks for network analysis.

Published
2019

30. Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Author

Sieberts, Solveig K., Zhu, Fan, García-García, Javier, Stahl, Eli, Pratap, Abhishek, Pandey, Gaurav, Pappas, Dimitrios, Aguilar, Daniel, Anton, Bernat, Bonet, Jaume, Eksi, Ridvan, Fornés, Oriol, Guney, Emre, Li, Hongdong, Marín, Manuel Alejandro, Panwar, Bharat, Planas-Iglesias, Joan, Poglayen, Daniel, Cui, Jing, Falcao, Andre O., Suver, Christine, Hoff, Bruce, Balagurusamy, Venkat S. K., Dillenberger, Donna, Neto, Elias Chaibub, Norman, Thea, Aittokallio, Tero, Ammad-ud-din, Muhammad, Azencott, Chloe-Agathe, Bellón, Víctor, Boeva, Valentina, Bunte, Kerstin, Chheda, Himanshu, Cheng, Lu, Corander, Jukka, Dumontier, Michel, Goldenberg, Anna, Gopalacharyulu, Peddinti, Hajiloo, Mohsen, Hidru, Daniel, Jaiswal, Alok, Kaski, Samuel, Khalfaoui, Beyrem, Khan, Suleiman Ali, Kramer, Eric R., Marttinen, Pekka, Mezlini, Aziz M., Molparia, Bhuvan, Pirinen, Matti, Saarela, Janna, Samwald, Matthias, Stoven, Véronique, Tang, Hao, Tang, Jing, Torkamani, Ali, Vert, Jean-Phillipe, Wang, Bo, Wang, Tao, Wennerberg, Krister, Wineinger, Nathan E., Xiao, Guanghua, Xie, Yang, Yeung, Rae, Zhan, Xiaowei, Zhao, Cheng, Calaza, Manuel, Elmarakeby, Haitham, Heath, Lenwood S., Long, Quan, Moore, Jonathan D., Opiyo, Stephen Obol, Savage, Richard S., Zhu, Jun, Greenberg, Jeff, Kremer, Joel, Michaud, Kaleb, Barton, Anne, Coenen, Marieke, Mariette, Xavier, Miceli, Corinne, Shadick, Nancy, Weinblatt, Michael, de Vries, Niek, Tak, Paul P., Gerlag, Danielle, Huizinga, Tom W. J., Kurreeman, Fina, Allaart, Cornelia F., Louis Bridges Jr., S., Criswell, Lindsey, Moreland, Larry, Klareskog, Lars, Saevarsdottir, Saedis, Padyukov, Leonid, Gregersen, Peter K., Friend, Stephen, Plenge, Robert, Stolovitzky, Gustavo, Oliva, Baldo, Guan, Yuanfang, Mangravite, Lara M., Bridges, S. Louis, Intelligent Systems, Institute for Molecular Medicine Finland, Department of Mathematics and Statistics, Helsinki Institute for Information Technology, Jukka Corander / Principal Investigator, Department of Computer Science, Janna Saarela / Principal Investigator, Krister Wennerberg / Principal Investigator, Biostatistics Helsinki, Statistical and population genetics, AII - Amsterdam institute for Infection and Immunity, Clinical Immunology and Rheumatology, Zhejiang University, Universidad del Pais Vasco / Euskal Herriko Unibertsitatea [Espagne] (UPV/EHU), Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), DYNBIO LEGOS, Laboratoire d'études en Géophysique et océanographie spatiales (LEGOS), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Institut d'Ecologia Aquàtica, Universitat de Girona (UdG), Department of Medical Genetics, Faculty of Medicine-Child and Family Research Institute-Centre for Molecular Medicine and Therapeutics-University of British Columbia (UBC), China Agricultural University (CAU), Computational Intelligence Research Group (CA3), Centre of Technology and Systems (CTS), Faculdade de Ciências e Tecnologia = School of Science & Technology (FCT NOVA), Universidade Nova de Lisboa = NOVA University Lisbon (NOVA)-Universidade Nova de Lisboa = NOVA University Lisbon (NOVA)-Faculdade de Ciências e Tecnologia = School of Science & Technology (FCT NOVA), Universidade Nova de Lisboa = NOVA University Lisbon (NOVA)-Universidade Nova de Lisboa = NOVA University Lisbon (NOVA), Cancer et génome: Bioinformatique, biostatistiques et épidémiologie d'un système complexe, Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Bioinformatique (CBIO), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Hefei University of Technology (HFUT), Stanford Center for BioMedical Informatics Research (BMIR), Stanford University, Service de génétique [Rouen], CHU Rouen, Normandie Université (NU)-Normandie Université (NU)-Université de Rouen Normandie (UNIROUEN), Normandie Université (NU), Technical Research Centre of Finland, VTT Technical Research Centre of Finland (VTT), U.S. Food and Drug Administration (FDA), Jet Propulsion Laboratory (JPL), NASA-California Institute of Technology (CALTECH), Profium Oy [Helsinki], Chinese Academy of Agricultural Sciences (CAAS), Business School [Hohai University], Hohai University, Institute of Industrial Economics [Hohai University], State Key Laboratory of Medical Genetics of China, Hunan Medical College, State Key Laboratory of Advanced Special Steel, Shanghai University, Quantitative Biomedical Research Center (QBRC), University of Texas Southwestern Medical Center [Dallas], Harold C. Simmons Comprehensive Cancer Center [Dallas, TX, États-Unis], Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique (LHEEA), École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS), China National Research Center of Intelligent Equipment for Agriculture [Beijing] (NRCIEA), Centro Nacional de Análisi Genómico (CNAG), Centro Nacional de Análisis Genómico, Gregor Mendel Institute of Molecular Plant Biology (GMI), Austrian Academy of Sciences (OeAW), Department of Mechanical and Aerospace Engineering [Univ California Davis] (MAE - UC Davis), University of California [Davis] (UC Davis), University of California (UC)-University of California (UC), Tongji University, Laboratory for Measles and Rubella, Laboratoire National de Santé [Luxembourg] (LNS), Department of Human Genetics, Radboud University Medical Center [Nijmegen], INSERM U1012, AP-HP Hôpital Bicêtre (Le Kremlin-Bicêtre), School of biosciences and biotechnology, University of Camerino, Università degli Studi di Camerino = University of Camerino (UNICAM), Division of Rheumatology, Immunology and Allergy and Partners Asthma Center, Brigham and Women's Hospital [Boston], Department of Health Education and Promotion, Maastricht University [Maastricht], University of Amsterdam [Amsterdam] (UvA), Department of rheumatology, Leiden University Medical Center (LUMC), Universiteit Leiden-Universiteit Leiden, Rheumatology Unit, Department of Medicine, University of California [San Francisco] (UC San Francisco), University of California (UC), Rheumatology Unit, Karolinska Institutet [Stockholm], Merck & Co. Inc, Structural Bioinformatics Group (GRIB), Barcelona Research Park of Biomedicine (PRBB), Universitat Pompeu Fabra [Barcelona] (UPF), Capital Normal University [Beijing], Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Centre National de la Recherche Scientifique (CNRS), MINES ParisTech - École nationale supérieure des mines de Paris, California Institute of Technology (CALTECH)-NASA, Department of Mechanical and Aerospace Engineering [Davis], University of California-University of California, Università degli Studi di Camerino (UNICAM), University of California [San Francisco] (UCSF), University of California, Sage Bionetworks, University of Michigan, Ann Arbor, Pompeu Fabra University, Icahn School of Medicine at Mount Sinai, Corrona LLC, Northeastern University, Harvard University, University of Lisbon, IBM, INSERM U900, University of Helsinki, University of Toronto, Scripps Research Institute, Medical University of Vienna, University of Texas at Dallas, New York University, Albany Medical College, Arthritis Research Center Foundation, Radboud University Nijmegen, INSERM U1184, University of Amsterdam, Glaxo Smith Kline, Leiden University, University of Alabama at Birmingham, University of California San Francisco, University of Pittsburgh, Karolinska Institutet, North Shore-Long Island Jewish Health System, Merck, Aalto-yliopisto, and Aalto University

Subjects
Male, 0301 basic medicine, General Physics and Astronomy, Arthritis, Genome-wide association study, Bioinformatics, DISEASE, Arthritis, Rheumatoid, Cohort Studies, Missing heritability problem, MISSING HERITABILITY, Medicine, Certolizumab pegol, RISK, Multidisciplinary, Antibodies, Monoclonal, Middle Aged, Prognosis, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], 3. Good health, STACKED GENERALIZATION, Treatment Outcome, Antirheumatic Agents, Crowdsourcing, Biomarker (medicine), Female, Erratum, medicine.drug, Adult, Science, Context (language use), Antibodies, Monoclonal, Humanized, Polymorphism, Single Nucleotide, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, INFLIXIMAB, Journal Article, Humans, SNP, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, METAANALYSIS, Aged, ta113, Tumor Necrosis Factor-alpha, business.industry, NETWORK INFERENCE, COMPLEX TRAITS, Artritis reumatoide -- Tractament, CLINICAL-RESPONSE, General Chemistry, 113 Computer and information sciences, medicine.disease, Infliximab, 030104 developmental biology, 3121 General medicine, internal medicine and other clinical medicine, Certolizumab Pegol, business, RC
Abstract

Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in ∼one-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h2=0.18, P value=0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data., Rheumatoid arthritis patients respond differently to anti-TNF treatment. Using community-based challenge, the authors show that currently available data does not reveal meaningful genetic predictors of response to anti-TNF therapy, thus confirming clinical observations.

Published
2016

31. Open Community Challenge Reveals Molecular Network Modules with Key Roles in Diseases

Author

Choobdar, Sarvenaz, Ahsen, Mehmet E., Crawford, Jake, Tomasoni, Mattia, Fang, Tao, Lamparter, David, Lin, Junyuan, Hescott, Benjamin, Hu, Xiaozhe, Mercer, Johnathan, Natoli, Ted, Narayan, Rajiv, Subramanian, Aravind, Zhang, Jitao D., Stolovitzky, Gustavo, Kutalik, Zoltán, Lage, Kasper, Slonim, Donna K., Saez-Rodriguez, Julio, Cowen, Lenore J., Bergmann, Sven, Marbach, Daniel, Aicheler, Fabian, Amoroso, Nicola, Arenas, Alex, Azhagesan, Karthik, Baker, Aaron, Banf, Michael, Batzoglou, Serafim, Baudot, Anaïs, Bellotti, Roberto, Boroevich, Keith A., Brun, Christine, Cai, Stanley, Caldera, Michael, Calderone, Alberto, Cesareni, Gianni, Chen, Weiqi, Chichester, Christine, Cowen, Lenore, Cui, Hongzhu, Dao, Phuong, Domenico, Manlio De, Dhroso, Andi, Didier, Gilles, Divine, Mathew, Sol, Antonio del, Feng, Xuyang, Flores-Canales, Jose C., Fortunato, Santo, Gitter, Anthony, Gorska, Anna, Guan, Yuanfang, Guénoche, Alain, Gómez, Sergio, Hamza, Hatem, Hartmann, András, He, Shan, Heijs, Anton, Heinrich, Julian, Hu, Ying, Huang, Xiaoqing, Hughitt, V. Keith, Jeon, Minji, Jeub, Lucas, Johnson, Nathan, Joo, Keehyoung, Joung, InSuk, Jung, Sascha, Kalko, Susana G., Kamola, Piotr J., Kang, Jaewoo, Kaveelerdpotjana, Benjapun, Kim, Minjun, Kim, Yoo-Ah, Kohlbacher, Oliver, Korkin, Dmitry, Krzysztof, Kiryluk, Kunji, Khalid, Kutalik, Zoltàn, Lang-Brown, Sean, Le, Thuc Duy, Lee, Jooyoung, Lee, Sunwon, Lee, Juyong, Li, Dong, Li, Jiuyong, Liu, Lin, Loizou, Antonis, Luo, Zhenhua, Lysenko, Artem, Ma, Tianle, Mall, Raghvendra, Mattia, Tomasoni, Medvedovic, Mario, Menche, Jörg, Micarelli, Elisa, Monaco, Alfonso, Müller, Felix, Narykov, Oleksandr, Norman, Thea, Park, Sungjoon, Perfetto, Livia, Perrin, Dimitri, Pirrò, Stefano, Przytycka, Teresa M., Qian, Xiaoning, Raman, Karthik, Ramazzotti, Daniele, Ramsahai, Emilie, Ravindran, Balaraman, Rennert, Philip, Schärfe, Charlotta, Sharan, Roded, Shi, Ning, Shin, Wonho, Shu, Hai, Sinha, Himanshu, Spinelli, Lionel, Srinivasan, Suhas, Suver, Christine, Szklarczyk, Damian, Tangaro, Sabina, Thiagarajan, Suresh, Tichit, Laurent, Tiede, Thorsten, Tripathi, Beethika, Tsherniak, Aviad, Tsunoda, Tatsuhiko, Türei, Dénes, Ullah, Ehsan, Vahedi, Golnaz, Valdeolivas, Alberto, Vivek, Jayaswal, Mering, Christian von, Waagmeester, Andra, Wang, Bo, Wang, Yijie, Weir, Barbara A., White, Shana, Winkler, Sebastian, Xu, Ke, Xu, Taosheng, Yan, Chunhua, Yang, Liuqing, Yu, Kaixian, Yu, Xiangtian, Zaffaroni, Gaia, Zaslavskiy, Mikhail, Zeng, Tao, Zhang, Lu, Zhang, Weijia, Zhang, Lixia, Zhang, Xinyu, Zhang, Junpeng, Zhou, Xin, Zhou, Jiarui, Zhu, Hongtu, Zhu, Junjie, and Zuccon, Guido

Subjects
Identification methods, Molecular network, Computer science, Association (object-oriented programming), Key (cryptography), Open community, Genome-wide association study, Identification (biology), Computational biology, Disease
Abstract

Identification of modules in molecular networks is at the core of many current analysis methods in biomedical research. However, how well different approaches identify disease-relevant modules in different types of gene and protein networks remains poorly understood. We launched the “Disease Module Identification DREAM Challenge”, an open competition to comprehensively assess module identification methods across diverse protein-protein interaction, signaling, gene co-expression, homology, and cancer-gene networks. Predicted network modules were tested for association with complex traits and diseases using a unique collection of 180 genome-wide association studies (GWAS). Our critical assessment of 75 contributed module identification methods reveals novel top-performing algorithms, which recover complementary trait-associated modules. We find that most of these modules correspond to core disease-relevant pathways, which often comprise therapeutic targets and correctly prioritize candidate disease genes. This community challenge establishes benchmarks, tools and guidelines for molecular network analysis to study human disease biology (https://synapse.org/modulechallenge).

Published
2018
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34. Device-based assessment through a mobile application in the Luxembourg Parkinson Cohort

Author

Stallinger, Christian, Satagopam, Venkata, Banda, Peter, Kolber, Pierre, Suver, Christine, Trister, Andrew, Friend, Stephen, Rejko, Krüger, Stallinger, Christian, Satagopam, Venkata, Banda, Peter, Kolber, Pierre, Suver, Christine, Trister, Andrew, Friend, Stephen, and Rejko, Krüger

Abstract

Introduction: The project focuses on the integration device-based assessment (DBA) with a mobile application (mPower) into the longitudinal deeply-phenotyped HELP-PD (Health in the Elderly Luxembourgish Population with a focus on Parkinson’s disease) cohort for patients with Parkinsonism in Luxembourg and the Greater Region to monitor frequency and degree of variation in symptoms of Parkinsonism, to identify potential sources and modulators of variation and to evaluate how symptoms are correlated with these modulators across patients. Methods: We integrate for the first time the mPower iOS app into a deeply phenotyped cohort. mPower is one of the first apps to use Apple’s Research Kit framework and combines a traditional survey-based approach with more granular and precise data gained from a person’s iPhone related to sensor- (e.g. step count, GPS-tracking) or task-based assessments (e.g. finger tapping, tremor detection, sustained phonation, simple gait analysis, memory test). Anonymized longitudinal data is sent to a repository, then retrieved, matched, and correlated with conventional HELP-PD data from a total of 47 screening instruments for motor and non-motor functions in Parkinsonism obtained from annual visits of study participants. 14 patients with clinically confirmed IPD are currently included in the pilot phase. Results/Discussion: We modified the mPower app and successfully integrated it into HELP-PD’s novel database infrastructure, allowing for a wide variety of analyses. The reporting system is able to handle multiple DBAs, with the implementation of an in-depth gait analysis system currently pending. Considerable attention was given to data protection. The system is currently fully functional with the pilot phase having started in June 2016. First correlations with traditional clinical data are planned for early 2017.

Published
2017

36. Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis

Author

University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Department of Mathematics and Statistics, University of Helsinki, Department of Computer Science, Sieberts, Solveig K., Zhu, Fan, Garcia-Garcia, Javier, Stahl, Eli, Pratap, Abhishek, Pandey, Gaurav, Pappas, Dimitrios, Aguilar, Daniel, Anton, Bernat, Bonet, Jaume, Eksi, Ridvan, Fornes, Oriol, Guney, Emre, Li, Hongdong, Marin, Manuel Alejandro, Panwar, Bharat, Planas-Iglesias, Joan, Poglayen, Daniel, Cui, Jing, Falcao, Andre O., Suver, Christine, Hoff, Bruce, Balagurusamy, Venkat S. K., Dillenberger, Donna, Neto, Elias Chaibub, Norman, Thea, Aittokallio, Tero, Ammad-ud-din, Muhammad, Azencott, Chloe-Agathe, Bellon, Victor, Boeva, Valentina, Bunte, Kerstin, Chheda, Himanshu, Cheng, Lu, Corander, Jukka, Dumontier, Michel, Goldenberg, Anna, Gopalacharyulu, Peddinti, Hajiloo, Mohsen, Hidru, Daniel, Jaiswal, Alok, Kaski, Samuel, Khalfaoui, Beyrem, Khan, Suleiman Ali, Kramer, Eric R., Marttinen, Pekka, Mezlini, Aziz M., Molparia, Bhuvan, Pirinen, Matti, Saarela, Janna, Samwald, Matthias, Stoven, Veronique, Tang, Hao, Tang, Jing, Torkamani, Ali, Vert, Jean-Phillipe, Wang, Bo, Wang, Tao, Wennerberg, Krister, Wineinger, Nathan E., Xiao, Guanghua, Xie, Yang, Yeung, Rae, Zhan, Xiaowei, Zhao, Cheng, Greenberg, Jeff, Kremer, Joel, Michaud, Kaleb, Barton, Anne, Coenen, Marieke, Mariette, Xavier, Miceli, Corinne, Shadick, Nancy, Weinblatt, Michael, de Vries, Niek, Tak, Paul P., Gerlag, Danielle, Huizinga, Tom W. J., Kurreeman, Fina, Allaart, Cornelia F., Bridges, S. Louis, Criswell, Lindsey, Moreland, Larry, Klareskog, Lars, Saevarsdottir, Saedis, Padyukov, Leonid, Gregersen, Peter K., Friend, Stephen, Plenge, Robert, Stolovitzky, Gustavo, Oliva, Baldo, Guan, Yuanfang, Mangravite, Lara M., Rheumatoid Arth Challenge, University of Helsinki, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Department of Mathematics and Statistics, University of Helsinki, Department of Computer Science, Sieberts, Solveig K., Zhu, Fan, Garcia-Garcia, Javier, Stahl, Eli, Pratap, Abhishek, Pandey, Gaurav, Pappas, Dimitrios, Aguilar, Daniel, Anton, Bernat, Bonet, Jaume, Eksi, Ridvan, Fornes, Oriol, Guney, Emre, Li, Hongdong, Marin, Manuel Alejandro, Panwar, Bharat, Planas-Iglesias, Joan, Poglayen, Daniel, Cui, Jing, Falcao, Andre O., Suver, Christine, Hoff, Bruce, Balagurusamy, Venkat S. K., Dillenberger, Donna, Neto, Elias Chaibub, Norman, Thea, Aittokallio, Tero, Ammad-ud-din, Muhammad, Azencott, Chloe-Agathe, Bellon, Victor, Boeva, Valentina, Bunte, Kerstin, Chheda, Himanshu, Cheng, Lu, Corander, Jukka, Dumontier, Michel, Goldenberg, Anna, Gopalacharyulu, Peddinti, Hajiloo, Mohsen, Hidru, Daniel, Jaiswal, Alok, Kaski, Samuel, Khalfaoui, Beyrem, Khan, Suleiman Ali, Kramer, Eric R., Marttinen, Pekka, Mezlini, Aziz M., Molparia, Bhuvan, Pirinen, Matti, Saarela, Janna, Samwald, Matthias, Stoven, Veronique, Tang, Hao, Tang, Jing, Torkamani, Ali, Vert, Jean-Phillipe, Wang, Bo, Wang, Tao, Wennerberg, Krister, Wineinger, Nathan E., Xiao, Guanghua, Xie, Yang, Yeung, Rae, Zhan, Xiaowei, Zhao, Cheng, Greenberg, Jeff, Kremer, Joel, Michaud, Kaleb, Barton, Anne, Coenen, Marieke, Mariette, Xavier, Miceli, Corinne, Shadick, Nancy, Weinblatt, Michael, de Vries, Niek, Tak, Paul P., Gerlag, Danielle, Huizinga, Tom W. J., Kurreeman, Fina, Allaart, Cornelia F., Bridges, S. Louis, Criswell, Lindsey, Moreland, Larry, Klareskog, Lars, Saevarsdottir, Saedis, Padyukov, Leonid, Gregersen, Peter K., Friend, Stephen, Plenge, Robert, Stolovitzky, Gustavo, Oliva, Baldo, Guan, Yuanfang, Mangravite, Lara M., and Rheumatoid Arth Challenge

Abstract

Rheumatoid arthritis (RA) affects millions world-wide. While anti-TNF treatment is widely used to reduce disease progression, treatment fails in Bone-third of patients. No biomarker currently exists that identifies non-responders before treatment. A rigorous community-based assessment of the utility of SNP data for predicting anti-TNF treatment efficacy in RA patients was performed in the context of a DREAM Challenge (http://www.synapse.org/RA_Challenge). An open challenge framework enabled the comparative evaluation of predictions developed by 73 research groups using the most comprehensive available data and covering a wide range of state-of-the-art modelling methodologies. Despite a significant genetic heritability estimate of treatment non-response trait (h(2) = 0.18, P value = 0.02), no significant genetic contribution to prediction accuracy is observed. Results formally confirm the expectations of the rheumatology community that SNP information does not significantly improve predictive performance relative to standard clinical traits, thereby justifying a refocusing of future efforts on collection of other data.

Published
2016

37. Systematic genetic and genomic analysis of cytochrome P450 enzyme activities in human liver

Author

Xia Yang, Bin Zhang, Molony, Cliona, Chudin, Eugene, Ke Hao, Jun Zhu, Gaedigk, Andrea, Suver, Christine, Hua Zhong, Leeder, J. Steven, Guengerich, F. Peter, Strom, Stephen C., Schuetz, Erin, Rushmore, Thomas H., Ulrich, Roger G., Slatter, J. Greg, Schadt, Eric E., Kasarskis, Andrew, and Pek Yee Lum

Subjects
Cytochrome P-450 -- Research, Gene expression -- Analysis, Single nucleotide polymorphisms -- Analysis, Health
Published
2010

38. The mPower study, Parkinson disease mobile data collected using ResearchKit

Author

Bot, Brian M., primary, Suver, Christine, additional, Neto, Elias Chaibub, additional, Kellen, Michael, additional, Klein, Arno, additional, Bare, Christopher, additional, Doerr, Megan, additional, Pratap, Abhishek, additional, Wilbanks, John, additional, Dorsey, E. Ray, additional, Friend, Stephen H., additional, and Trister, Andrew D., additional

Published
2016
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39. Integrated Systems Approach Identifies Genetic Nodes and Networks in Late-Onset Alzheimer’s Disease

Author

Zhang, Bin, primary, Gaiteri, Chris, additional, Bodea, Liviu-Gabriel, additional, Wang, Zhi, additional, McElwee, Joshua, additional, Podtelezhnikov, Alexei A., additional, Zhang, Chunsheng, additional, Xie, Tao, additional, Tran, Linh, additional, Dobrin, Radu, additional, Fluder, Eugene, additional, Clurman, Bruce, additional, Melquist, Stacey, additional, Narayanan, Manikandan, additional, Suver, Christine, additional, Shah, Hardik, additional, Mahajan, Milind, additional, Gillis, Tammy, additional, Mysore, Jayalakshmi, additional, MacDonald, Marcy E., additional, Lamb, John R., additional, Bennett, David A., additional, Molony, Cliona, additional, Stone, David J., additional, Gudnason, Vilmundur, additional, Myers, Amanda J., additional, Schadt, Eric E., additional, Neumann, Harald, additional, Zhu, Jun, additional, and Emilsson, Valur, additional

Published
2013
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40. Correction: Lung eQTLs to Help Reveal the Molecular Underpinnings of Asthma

Author

Hao, Ke, primary, Bossé, Yohan, additional, Nickle, David C., additional, Paré, Peter D., additional, Postma, Dirkje S., additional, Laviolette, Michel, additional, Sandford, Andrew, additional, Hackett, Tillie L., additional, Daley, Denise, additional, Hogg, James C., additional, Elliott, W. Mark, additional, Couture, Christian, additional, Lamontagne, Maxime, additional, Brandsma, Corry-Anke, additional, van den Berge, Maarten, additional, Koppelman, Gerard, additional, Reicin, Alise S., additional, Nicholson, Donald W., additional, Malkov, Vladislav, additional, Derry, Jonathan M., additional, Suver, Christine, additional, Tsou, Jeffrey A., additional, Kulkarni, Amit, additional, Zhang, Chunsheng, additional, Vessey, Rupert, additional, Opiteck, Greg J., additional, Curtis, Sean P., additional, Timens, Wim, additional, and Sin, Don D., additional

Published
2012
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41. Lung eQTLs to Help Reveal the Molecular Underpinnings of Asthma

Author

Hao, Ke, primary, Bossé, Yohan, additional, Nickle, David C., additional, Paré, Peter D., additional, Postma, Dirkje S., additional, Laviolette, Michel, additional, Sandford, Andrew, additional, Hackett, Tillie L., additional, Daley, Denise, additional, Hogg, James C., additional, Elliott, W. Mark, additional, Couture, Christian, additional, Lamontagne, Maxime, additional, Brandsma, Corry-Anke, additional, van den Berge, Maarten, additional, Koppelman, Gerard, additional, Reicin, Alise S., additional, Nicholson, Donald W., additional, Malkov, Vladislav, additional, Derry, Jonathan M., additional, Suver, Christine, additional, Tsou, Jeffrey A., additional, Kulkarni, Amit, additional, Zhang, Chunsheng, additional, Vessey, Rupert, additional, Opiteck, Greg J., additional, Curtis, Sean P., additional, Timens, Wim, additional, and Sin, Don D., additional

Published
2012
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42. Meta-analysis of Dense Genecentric Association Studies Reveals Common and Uncommon Variants Associated with Height

Author

Lanktree, Matthew B., primary, Guo, Yiran, additional, Murtaza, Muhammed, additional, Glessner, Joseph T., additional, Bailey, Swneke D., additional, Onland-Moret, N. Charlotte, additional, Lettre, Guillaume, additional, Ongen, Halit, additional, Rajagopalan, Ramakrishnan, additional, Johnson, Toby, additional, Shen, Haiqing, additional, Nelson, Christopher P., additional, Klopp, Norman, additional, Baumert, Jens, additional, Padmanabhan, Sandosh, additional, Pankratz, Nathan, additional, Pankow, James S., additional, Shah, Sonia, additional, Taylor, Kira, additional, Barnard, John, additional, Peters, Bas J., additional, Maloney, Cliona M., additional, Lobmeyer, Maximilian T., additional, Stanton, Alice, additional, Zafarmand, M. Hadi, additional, Romaine, Simon P.R., additional, Mehta, Amar, additional, van Iperen, Erik P.A., additional, Gong, Yan, additional, Price, Tom S., additional, Smith, Erin N., additional, Kim, Cecilia E., additional, Li, Yun R., additional, Asselbergs, Folkert W., additional, Atwood, Larry D., additional, Bailey, Kristian M., additional, Bhatt, Deepak, additional, Bauer, Florianne, additional, Behr, Elijah R., additional, Bhangale, Tushar, additional, Boer, Jolanda M.A., additional, Boehm, Bernhard O., additional, Bradfield, Jonathan P., additional, Brown, Morris, additional, Braund, Peter S., additional, Burton, Paul R., additional, Carty, Cara, additional, Chandrupatla, Hareesh R., additional, Chen, Wei, additional, Connell, John, additional, Dalgeorgou, Chrysoula, additional, de Boer, Anthonius, additional, Drenos, Fotios, additional, Elbers, Clara C., additional, Fang, James C., additional, Fox, Caroline S., additional, Frackelton, Edward C., additional, Fuchs, Barry, additional, Furlong, Clement E., additional, Gibson, Quince, additional, Gieger, Christian, additional, Goel, Anuj, additional, Grobbee, Diederik E., additional, Hastie, Claire, additional, Howard, Philip J., additional, Huang, Guan-Hua, additional, Johnson, W. Craig, additional, Li, Qing, additional, Kleber, Marcus E., additional, Klein, Barbara E.K., additional, Klein, Ronald, additional, Kooperberg, Charles, additional, Ky, Bonnie, additional, LaCroix, Andrea, additional, Lanken, Paul, additional, Lathrop, Mark, additional, Li, Mingyao, additional, Marshall, Vanessa, additional, Melander, Olle, additional, Mentch, Frank D., additional, Meyer, Nuala J., additional, Monda, Keri L., additional, Montpetit, Alexandre, additional, Murugesan, Gurunathan, additional, Nakayama, Karen, additional, Nondahl, Dave, additional, Onipinla, Abiodun, additional, Rafelt, Suzanne, additional, Newhouse, Stephen J., additional, Otieno, F. George, additional, Patel, Sanjey R., additional, Putt, Mary E., additional, Rodriguez, Santiago, additional, Safa, Radwan N., additional, Sawyer, Douglas B., additional, Schreiner, Pamela J., additional, Simpson, Claire, additional, Sivapalaratnam, Suthesh, additional, Srinivasan, Sathanur R., additional, Suver, Christine, additional, Swergold, Gary, additional, Sweitzer, Nancy K., additional, Thomas, Kelly A., additional, Thorand, Barbara, additional, Timpson, Nicholas J., additional, Tischfield, Sam, additional, Tobin, Martin, additional, Tomaszewski, Maciej, additional, Verschuren, W.M. Monique, additional, Wallace, Chris, additional, Winkelmann, Bernhard, additional, Zhang, Haitao, additional, Zheng, Dongling, additional, Zhang, Li, additional, Zmuda, Joseph M., additional, Clarke, Robert, additional, Balmforth, Anthony J., additional, Danesh, John, additional, Day, Ian N., additional, Schork, Nicholas J., additional, de Bakker, Paul I.W., additional, Delles, Christian, additional, Duggan, David, additional, Hingorani, Aroon D., additional, Hirschhorn, Joel N., additional, Hofker, Marten H., additional, Humphries, Steve E., additional, Kivimaki, Mika, additional, Lawlor, Debbie A., additional, Kottke-Marchant, Kandice, additional, Mega, Jessica L., additional, Mitchell, Braxton D., additional, Morrow, David A., additional, Palmen, Jutta, additional, Redline, Susan, additional, Shields, Denis C., additional, Shuldiner, Alan R., additional, Sleiman, Patrick M., additional, Smith, George Davey, additional, Farrall, Martin, additional, Jamshidi, Yalda, additional, Christiani, David C., additional, Casas, Juan P., additional, Hall, Alistair S., additional, Doevendans, Pieter A., additional, Christie, Jason D., additional, Berenson, Gerald S., additional, Murray, Sarah S., additional, Illig, Thomas, additional, Dorn, Gerald W., additional, Cappola, Thomas P., additional, Boerwinkle, Eric, additional, Sever, Peter, additional, Rader, Daniel J., additional, Reilly, Muredach P., additional, Caulfield, Mark, additional, Talmud, Philippa J., additional, Topol, Eric, additional, Engert, James C., additional, Wang, Kai, additional, Dominiczak, Anna, additional, Hamsten, Anders, additional, Curtis, Sean P., additional, Silverstein, Roy L., additional, Lange, Leslie A., additional, Sabatine, Marc S., additional, Trip, Mieke, additional, Saleheen, Danish, additional, Peden, John F., additional, Cruickshanks, Karen J., additional, März, Winfried, additional, O'Connell, Jeffrey R., additional, Klungel, Olaf H., additional, Wijmenga, Cisca, additional, Maitland-van der Zee, Anke Hilse, additional, Schadt, Eric E., additional, Johnson, Julie A., additional, Jarvik, Gail P., additional, Papanicolaou, George J., additional, Grant, Struan F.A., additional, Munroe, Patricia B., additional, North, Kari E., additional, Samani, Nilesh J., additional, Koenig, Wolfgang, additional, Gaunt, Tom R., additional, Anand, Sonia S., additional, van der Schouw, Yvonne T., additional, Soranzo, Nicole, additional, FitzGerald, Garret A., additional, Reiner, Alex, additional, Hegele, Robert A., additional, Hakonarson, Hakon, additional, and Keating, Brendan J., additional

Published
2012
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43. Predictive Genes in Adjacent Normal Tissue Are Preferentially Altered by sCNV during Tumorigenesis in Liver Cancer and May Rate Limiting

Author

Lamb, John R., primary, Zhang, Chunsheng, additional, Xie, Tao, additional, Wang, Kai, additional, Zhang, Bin, additional, Hao, Ke, additional, Chudin, Eugene, additional, Fraser, Hunter B., additional, Millstein, Joshua, additional, Ferguson, Mark, additional, Suver, Christine, additional, Ivanovska, Irena, additional, Scott, Martin, additional, Philippar, Ulrike, additional, Bansal, Dimple, additional, Zhang, Zhan, additional, Burchard, Julja, additional, Smith, Ryan, additional, Greenawalt, Danielle, additional, Cleary, Michele, additional, Derry, Jonathan, additional, Loboda, Andrey, additional, Watters, James, additional, Poon, Ronnie T. P., additional, Fan, Sheung T., additional, Yeung, Chun, additional, Lee, Nikki P. Y., additional, Guinney, Justin, additional, Molony, Cliona, additional, Emilsson, Valur, additional, Buser-Doepner, Carolyn, additional, Zhu, Jun, additional, Friend, Stephen, additional, Mao, Mao, additional, Shaw, Peter M., additional, Dai, Hongyue, additional, Luk, John M., additional, and Schadt, Eric E., additional

Published
2011
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44. A survey of the genetics of stomach, liver, and adipose gene expression from a morbidly obese cohort

Author

Greenawalt, Danielle M., primary, Dobrin, Radu, additional, Chudin, Eugene, additional, Hatoum, Ida J., additional, Suver, Christine, additional, Beaulaurier, John, additional, Zhang, Bin, additional, Castro, Victor, additional, Zhu, Jun, additional, Sieberts, Solveig K., additional, Wang, Susanna, additional, Molony, Cliona, additional, Heymsfield, Steven B., additional, Kemp, Daniel M., additional, Reitman, Marc L., additional, Lum, Pek Yee, additional, Schadt, Eric E., additional, and Kaplan, Lee M., additional

Published
2011
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45. Mapping the Genetic Architecture of Gene Expression in Human Liver

Author

Schadt, Eric E, primary, Molony, Cliona, additional, Chudin, Eugene, additional, Hao, Ke, additional, Yang, Xia, additional, Lum, Pek Y, additional, Kasarskis, Andrew, additional, Zhang, Bin, additional, Wang, Susanna, additional, Suver, Christine, additional, Zhu, Jun, additional, Millstein, Joshua, additional, Sieberts, Solveig, additional, Lamb, John, additional, GuhaThakurta, Debraj, additional, Derry, Jonathan, additional, Storey, John D, additional, Avila-Campillo, Iliana, additional, Kruger, Mark J, additional, Johnson, Jason M, additional, Rohl, Carol A, additional, van Nas, Atila, additional, Mehrabian, Margarete, additional, Drake, Thomas A, additional, Lusis, Aldons J, additional, Smith, Ryan C, additional, Guengerich, F. Peter, additional, Strom, Stephen C, additional, Schuetz, Erin, additional, Rushmore, Thomas H, additional, and Ulrich, Roger, additional

Published
2008
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46. COVID-19 outcomes in persons with hemophilia: results from a US-based national COVID-19 surveillance registry

Author

Sharathkumar, Anjali, Wendt, Linder, Ortman, Chris, Srinivasan, Ragha, Chute, Christopher G., Chrischilles, Elizabeth, Takemoto, Clifford M., Wilcox, Adam B., Lee, Adam M., Graves, Alexis, Anzalone, Alfred (Jerrod), Manna, Amin, Saha, Amit, Olex, Amy, Zhou, Andrea, Williams, Andrew E., Southerland, Andrew, Girvin, Andrew T., Walden, Anita, Sharathkumar, Anjali A., Amor, Benjamin, Bates, Benjamin, Hendricks, Brian, Patel, Brijesh, Alexander, Caleb, Bramante, Carolyn, Ward-Caviness, Cavin, Madlock-Brown, Charisse, Suver, Christine, Chute, Christopher, Dillon, Christopher, Wu, Chunlei, Schmitt, Clare, Takemoto, Cliff, Housman, Dan, Gabriel, Davera, Eichmann, David A., Mazzotti, Diego, Brown, Don, Boudreau, Eilis, Hill, Elaine, Zampino, Elizabeth, Marti, Emily Carlson, Pfaff, Emily R., French, Evan, Koraishy, Farrukh M., Mariona, Federico, Prior, Fred, Sokos, George, Martin, Greg, Lehmann, Harold, Spratt, Heidi, Mehta, Hemalkumar, Liu, Hongfang, Sidky, Hythem, Hayanga, J. W. Awori, Pincavitch, Jami, Clark, Jaylyn, Harper, Jeremy Richard, Islam, Jessica, Ge, Jin, Gagnier, Joel, Saltz, Joel H., Saltz, Joel, Loomba, Johanna, Buse, John, Mathew, Jomol, Rutter, Joni L., McMurry, Julie A., Guinney, Justin, Starren, Justin, Crowley, Karen, Bradwell, Katie Rebecca, Walters, Kellie M., Wilkins, Ken, Gersing, Kenneth R., Cato, Kenrick Dwain, Murray, Kimberly, Kostka, Kristin, Northington, Lavance, Pyles, Lee Allan, Misquitta, Leonie, Cottrell, Lesley, Portilla, Lili, Deacy, Mariam, Bissell, Mark M., Clark, Marshall, Emmett, Mary, Saltz, Mary Morrison, Palchuk, Matvey B., Haendel, Melissa A., Adams, Meredith, Temple-O’Connor, Meredith, Kurilla, Michael G., Morris, Michele, Qureshi, Nabeel, Safdar, Nasia, Garbarini, Nicole, Sharafeldin, Noha, Sadan, Ofer, Francis, Patricia A., Burgoon, Penny Wung, Robinson, Peter, Payne, Philip R.O., Fuentes, Rafael, Jawa, Randeep, Erwin-Cohen, Rebecca, Patel, Rena, Moffitt, Richard A., Zhu, Richard L., Kamaleswaran, Rishi, Hurley, Robert, Miller, Robert T., Pyarajan, Saiju, Michael, Sam G., Bozzette, Samuel, Mallipattu, Sandeep, Vedula, Satyanarayana, Chapman, Scott, O’Neil, Shawn T., Setoguchi, Soko, Hong, Stephanie S., Johnson, Steve, Bennett, Tellen D., Callahan, Tiffany, Topaloglu, Umit, Sheikh, Usman, Gordon, Valery, Subbian, Vignesh, Kibbe, Warren A., Hernandez, Wenndy, Beasley, Will, Cooper, Will, Hillegass, William, and Zhang, Xiaohan Tanner

Abstract

Hypercoagulable state contributing to thrombotic complications worsens COVID-19 severity and outcomes, whereas anticoagulation improves outcomes by alleviating hypercoagulability.

Published
2023
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48. Liver and Adipose Expression Associated SNPs Are Enriched for Association to Type 2 Diabetes.

Author

Hua Zhong, Beaulaurier, John, Pek Yee Lum, Molony, Cliona, Xia Yang, MacNeil, Douglas J., Weingarth, Drew T., Bin Zhang, Greenawalt, Danielle, Dobrin, Radu, Ke Hao, Sangsoon Woo, Fabre-Suver, Christine, Su Qian, Tota, Michael R., Keller, Mark P., Kendziorski, Christina M., Yandell, Brian S., Castro, Victor, and Attie, Alan D.

Subjects
ETIOLOGY of diseases, GENETICS, GENE expression, DIABETES, GENETIC polymorphisms
Abstract

Genome-wide association studies (GWAS) have demonstrated the ability to identify the strongest causal common variants in complex human diseases. However, to date, the massive data generated from GWAS have not been maximally explored to identify true associations that fail to meet the stringent level of association required to achieve genome-wide significance. Genetics of gene expression (GGE) studies have shown promise towards identifying DNA variations associated with disease and providing a path to functionally characterize findings from GWAS. Here, we present the first empiric study to systematically characterize the set of single nucleotide polymorphisms associated with expression (eSNPs) in liver, subcutaneous fat, and omental fat tissues, demonstrating these eSNPs are significantly more enriched for SNPs that associate with type 2 diabetes (T2D) in three large-scale GWAS than a matched set of randomly selected SNPs. This enrichment for T2D association increases as we restrict to eSNPs that correspond to genes comprising gene networks constructed from adipose gene expression data isolated from a mouse population segregating a T2D phenotype. Finally, by restricting to eSNPs corresponding to genes comprising an adipose subnetwork strongly predicted as causal for T2D, we dramatically increased the enrichment for SNPs associated with T2D and were able to identify a functionally related set of diabetes susceptibility genes. We identified and validated malic enzyme 1 (Me1) as a key regulator of this T2D subnetwork in mouse and provided support for the association of this gene to T2D in humans. This integration of eSNPs and networks provides a novel approach to identify disease susceptibility networks rather than the single SNPs or genes traditionally identified through GWAS, thereby extracting additional value from the wealth of data currently being generated by GWAS. [ABSTRACT FROM AUTHOR]

Published
2010
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49. Sharing Data from the Human Tumor Atlas Network through Standards, Infrastructure, and Community Engagement.

Author

de Bruijn I, Nikolov M, Lau C, Clayton A, Gibbs DL, Mitraka E, Pozhidayeva D, Lash A, Sumer SO, Altreuter J, Anton K, DeFelice M, Li X, Lisman A, R Longabaugh WJ, Muhlich J, Santagata S, Nandakumar S, Sorger PK, Suver C, Schultz N, Taylor AJ, Thorsson V, Cerami E, and Eddy JA

Abstract

The Data Coordinating Center (DCC) of the Human Tumor Atlas Network (HTAN) has played a crucial role in enabling the broad sharing and effective utilization of HTAN data within the scientific community. Data from the first phase of HTAN are now available publicly. We describe the diverse datasets and modalities shared, multiple access routes to HTAN assay data and metadata, data standards, technical infrastructure and governance approaches, as well as our approach to sustained community engagement. HTAN data can be accessed via the HTAN Portal, explored in visualization tools-including CellxGene, Minerva, and cBioPortal-and analyzed in the cloud through the NCI Cancer Research Data Commons nodes. We have developed a streamlined infrastructure to ingest and disseminate data by leveraging the Synapse platform. Taken together, the HTAN DCC's approach demonstrates a successful model for coordinating, standardizing, and disseminating complex cancer research data via multiple resources in the cancer data ecosystem, offering valuable insights for similar consortia, and researchers looking to leverage HTAN data.

Published
2024
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50. Increased Incidence of Vestibular Disorders in Patients With SARS-CoV-2.

Author

Lee L, French E, Coelho DH, Manzoor NF, Wilcox AB, Lee AM, Graves A, Anzalone A, Manna A, Saha A, Olex A, Zhou A, Williams AE, Southerland A, Girvin AT, Walden A, Sharathkumar AA, Amor B, Bates B, Hendricks B, Patel B, Alexander C, Bramante C, Ward-Caviness C, Madlock-Brown C, Suver C, Chute C, Dillon C, Wu C, Schmitt C, Takemoto C, Housman D, Gabriel D, Eichmann DA, Mazzotti D, Brown D, Boudreau E, Hill E, Zampino E, Marti EC, Pfaff ER, French E, Koraishy FM, Mariona F, Prior F, Sokos G, Martin G, Lehmann H, Spratt H, Mehta H, Liu H, Sidky H, Awori Hayanga JW, Pincavitch J, Clark J, Harper JR, Islam J, Ge J, Gagnier J, Saltz JH, Saltz J, Loomba J, Buse J, Mathew J, Rutter JL, McMurry JA, Guinney J, Starren J, Crowley K, Bradwell KR, Walters KM, Wilkins K, Gersing KR, Cato KD, Murray K, Kostka K, Northington L, Pyles LA, Misquitta L, Cottrell L, Portilla L, Deacy M, Bissell MM, Clark M, Emmett M, Saltz MM, Palchuk MB, Haendel MA, Adams M, Temple-O'Connor M, Kurilla MG, Morris M, Qureshi N, Safdar N, Garbarini N, Sharafeldin N, Sadan O, Francis PA, Burgoon PW, Robinson P, Payne PRO, Fuentes R, Jawa R, Erwin-Cohen R, Patel R, Moffitt RA, Zhu RL, Kamaleswaran R, Hurley R, Miller RT, Pyarajan S, Michael SG, Bozzette S, Mallipattu S, Vedula S, Chapman S, O'Neil ST, Setoguchi S, Hong SS, Johnson S, Bennett TD, Callahan T, Topaloglu U, Sheikh U, Gordon V, Subbian V, Kibbe WA, Hernandez W, Beasley W, Cooper W, Hillegass W, and Zhang XT

Abstract

Objective: Determine the incidence of vestibular disorders in patients with SARS-CoV-2 compared to the control population., Study Design: Retrospective., Setting: Clinical data in the National COVID Cohort Collaborative database (N3C)., Methods: Deidentified patient data from the National COVID Cohort Collaborative database (N3C) were queried based on variant peak prevalence (untyped, alpha, delta, omicron 21K, and omicron 23A) from covariants.org to retrospectively analyze the incidence of vestibular disorders in patients with SARS-CoV-2 compared to control population, consisting of patients without documented evidence of COVID infection during the same period., Results: Patients testing positive for COVID-19 were significantly more likely to have a vestibular disorder compared to the control population. Compared to control patients, the odds ratio of vestibular disorders was significantly elevated in patients with untyped (odds ratio [OR], 2.39; confidence intervals [CI], 2.29-2.50; P < 0.001), alpha (OR, 3.63; CI, 3.48-3.78; P < 0.001), delta (OR, 3.03; CI, 2.94-3.12; P < 0.001), omicron 21K variant (OR, 2.97; CI, 2.90-3.04; P < 0.001), and omicron 23A variant (OR, 8.80; CI, 8.35-9.27; P < 0.001)., Conclusions: The incidence of vestibular disorders differed between COVID-19 variants and was significantly elevated in COVID-19-positive patients compared to the control population. These findings have implications for patient counseling and further research is needed to discern the long-term effects of these findings., Competing Interests: None declared., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of Otology & Neurotology, Inc.)

Published
2024
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