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11,152 results on '"Karlson IS"'

152. Metabolomic profiling reveals extensive adrenal suppression due to inhaled corticosteroid therapy in asthma

Author

Kachroo, Priyadarshini, Stewart, Isobel D., Kelly, Rachel S., Stav, Meryl, Mendez, Kevin, Dahlin, Amber, Soeteman, Djøra I., Chu, Su H., Huang, Mengna, Cote, Margaret, Knihtilä, Hanna M., Lee-Sarwar, Kathleen, McGeachie, Michael, Wang, Alberta, Wu, Ann Chen, Virkud, Yamini, Zhang, Pei, Wareham, Nicholas J., Karlson, Elizabeth W., Wheelock, Craig E., Clish, Clary, Weiss, Scott T., Langenberg, Claudia, and Lasky-Su, Jessica A.

Published
2022
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154. Psychiatric manifestations of rare variation in medically actionable genes: a PheWAS approach

Author

Yen-Chen A. Feng, Ian B. Stanaway, John J. Connolly, Joshua C. Denny, Yuan Luo, Chunhua Weng, Wei-Qi Wei, Scott T. Weiss, Elizabeth W. Karlson, and Jordan W. Smoller

Subjects
Genomic sequencing, Incidental findings, Rare variation, Psychiatric disorders, Biotechnology, TP248.13-248.65, Genetics, QH426-470
Abstract

Abstract Background As genomic sequencing moves closer to clinical implementation, there has been an increasing acceptance of returning incidental findings to research participants and patients for mutations in highly penetrant, medically actionable genes. A curated list of genes has been recommended by the American College of Medical Genetics and Genomics (ACMG) for return of incidental findings. However, the pleiotropic effects of these genes are not fully known. Such effects could complicate genetic counseling when returning incidental findings. In particular, there has been no systematic evaluation of psychiatric manifestations associated with rare variation in these genes. Results Here, we leveraged a targeted sequence panel and real-world electronic health records from the eMERGE network to assess the burden of rare variation in the ACMG-56 genes and two psychiatric-associated genes (CACNA1C and TCF4) across common mental health conditions in 15,181 individuals of European descent. As a positive control, we showed that this approach replicated the established association between rare mutations in LDLR and hypercholesterolemia with no visible inflation from population stratification. However, we did not identify any genes significantly enriched with rare deleterious variants that confer risk for common psychiatric disorders after correction for multiple testing. Suggestive associations were observed between depression and rare coding variation in PTEN (P = 1.5 × 10–4), LDLR (P = 3.6 × 10–4), and CACNA1S (P = 5.8 × 10–4). We also observed nominal associations between rare variants in KCNQ1 and substance use disorders (P = 2.4 × 10–4), and APOB and tobacco use disorder (P = 1.1 × 10–3). Conclusions Our results do not support an association between psychiatric disorders and incidental findings in medically actionable gene mutations, but power was limited with the available sample sizes. Given the phenotypic and genetic complexity of psychiatric phenotypes, future work will require a much larger sequencing dataset to determine whether incidental findings in these genes have implications for risk of psychopathology.

Published
2022
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155. Aortic Dissection During Pregnancy and Puerperium: Contemporary Incidence and Outcomes in the United States

Author

Yunda Wang, Kanhua Yin, Yesh Datar, Joy Mohnot, Ariana Y. Nodoushani, Yong Zhan, Karl J. Karlson, Niloo M. Edwards, Michael J. Reardon, and Nikola Dobrilovic

Subjects
aortic dissection, incidence, mortality, population, pregnancy, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Background Aortic dissection (AD) during pregnancy and puerperium is a rare catastrophe with devastating consequences for both parent and fetus. Population‐level incidence trends and outcomes remain relatively undetermined. Methods and Results We queried a US population‐based health care database, the National Inpatient Sample, and identified all patients with a pregnancy‐related AD hospitalization from 2002 to 2017. In total, 472 pregnancy‐related AD hospitalizations (mean age, 30.9±0.6 years) were identified from 68 514 000 pregnancy‐related hospitalizations (0.69 per 100 000 pregnancy‐related hospitalizations), with 107 (22.7%) being type A and 365 (77.3%) being type B. The incidence of AD appeared to increase over the 16‐year study period but was not statistically significant (P for trend >0.05). Marfan syndrome, primary hypertension, and preeclampsia/eclampsia were found in 21.9%, 14.4%, and 11.5%, respectively. On multivariable logistic regression analysis, Marfan syndrome was associated with the highest risk of developing AD during pregnancy and puerperium (adjusted odds ratio, 3469.36 [95% CI, 1767.84–6831.75]; P

Published
2023
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157. LPA Variants are Associated with Residual Cardiovascular Risk in Patients Receiving Statins

Author

Wei, Wei-Qi, Li, Xiaohui, Feng, Qiping, Kubo, Michiaki, Kullo, Iftikhar J, Peissig, Peggy L, Karlson, Elizabeth W, Jarvik, Gail P, Lee, Ming Ta Michael, Shang, Ning, Larson, Eric A, Edwards, Todd, Shaffer, Christian M, Mosley, Jonathan D, Maeda, Shiro, Horikoshi, Momoko, Ritchie, Marylyn, Williams, Marc S, Larson, Eric B, Crosslin, David R, Bland, Harris T, Pacheco, Jennifer A, Rasmussen-Torvik, Laura J, Cronkite, David, Hripcsak, George, Cox, Nancy J, Wilke, Russell A, Stein, C Michael, Rotter, Jerome I, Momozawa, Yukihide, Roden, Dan M, Krauss, Ronald M, and Denny, Joshua C

Subjects
Human Genome, Genetics, Clinical Research, Heart Disease, Atherosclerosis, Cardiovascular, Heart Disease - Coronary Heart Disease, Aetiology, 2.1 Biological and endogenous factors, Case-Control Studies, Coronary Disease, Databases, Genetic, Dyslipidemias, Electronic Health Records, Gene Frequency, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Lipoprotein(a), Phenotype, Polymorphism, Single Nucleotide, Risk Assessment, Risk Factors, Time Factors, Treatment Outcome, cholesterol, coronary disease, electronic health records, hydroxymethylglutaryl-CoA, LDL reductase inhibitors, lysophosphatidic acid, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology
Abstract

BackgroundCoronary heart disease (CHD) is a leading cause of death globally. Although therapy with statins decreases circulating levels of low-density lipoprotein cholesterol and the incidence of CHD, additional events occur despite statin therapy in some individuals. The genetic determinants of this residual cardiovascular risk remain unknown.MethodsWe performed a 2-stage genome-wide association study of CHD events during statin therapy. We first identified 3099 cases who experienced CHD events (defined as acute myocardial infarction or the need for coronary revascularization) during statin therapy and 7681 controls without CHD events during comparable intensity and duration of statin therapy from 4 sites in the Electronic Medical Records and Genomics Network. We then sought replication of candidate variants in another 160 cases and 1112 controls from a fifth Electronic Medical Records and Genomics site, which joined the network after the initial genome-wide association study. Finally, we performed a phenome-wide association study for other traits linked to the most significant locus.ResultsThe meta-analysis identified 7 single nucleotide polymorphisms at a genome-wide level of significance within the LPA/PLG locus associated with CHD events on statin treatment. The most significant association was for an intronic single nucleotide polymorphism within LPA/PLG (rs10455872; minor allele frequency, 0.069; odds ratio, 1.58; 95% confidence interval, 1.35-1.86; P=2.6×10-10). In the replication cohort, rs10455872 was also associated with CHD events (odds ratio, 1.71; 95% confidence interval, 1.14-2.57; P=0.009). The association of this single nucleotide polymorphism with CHD events was independent of statin-induced change in low-density lipoprotein cholesterol (odds ratio, 1.62; 95% confidence interval, 1.17-2.24; P=0.004) and persisted in individuals with low-density lipoprotein cholesterol ≤70 mg/dL (odds ratio, 2.43; 95% confidence interval, 1.18-4.75; P=0.015). A phenome-wide association study supported the effect of this region on coronary heart disease and did not identify noncardiovascular phenotypes.ConclusionsGenetic variations at the LPA locus are associated with CHD events during statin therapy independently of the extent of low-density lipoprotein cholesterol lowering. This finding provides support for exploring strategies targeting circulating concentrations of lipoprotein(a) to reduce CHD events in patients receiving statins.

Published
2018

158. Reanalysis of eMERGE phase III sequence variants in 10,500 participants and infrastructure to support the automated return of knowledge updates

Author

Zouk, Hana, Yu, Wanfeng, Oza, Andrea, Hawley, Megan, Vijay Kumar, Prathik K., Koch, Christopher, Mahanta, Lisa M., Harley, John B., Jarvik, Gail P., Karlson, Elizabeth W., Leppig, Kathleen A., Myers, Melanie F., Prows, Cynthia A., Williams, Marc S., Weiss, Scott T., Lebo, Matthew S., and Rehm, Heidi L.

Published
2022
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162. New onset diabetes in children during the COVID-19 Pandemic: an assessment of biomarkers and psychosocial risk factors at play in Mississippi

Author

Stout, Josephine, primary, Dixit, Naznin, additional, Pasha, Simeen, additional, Sukumaran, Anju, additional, Topaloglu, Ali Kemal, additional, Armstrong, Mary K., additional, Garg, Padma, additional, Karlson, Cynthia, additional, Bates, John T., additional, Ansari, Md Abu Yusuf, additional, and Kamran, Fariha, additional

Published
2024
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163. POS0593 CONTRIBUTION OF RARE EXONIC VARIANTS IN TELOMERE-RELATED GENES TO INTERSTITIAL LUNG DISEASE RISK IN PATIENTS WITH RHEUMATOID ARTHRITIS AND IDIOPATHIC PULMONARY FIBROSIS

Author

Juge, P. A., primary, Kawano-Dourado, L., additional, Stockwell, A., additional, Lee, J. S., additional, Gazal, S., additional, Mcdermott, G., additional, Hayashi, K., additional, Cui, J., additional, Granger, B., additional, Kannengiesser, C., additional, Borie, R., additional, Wemeau Stervinou, L., additional, Debray, M. P., additional, Wolters, P. J., additional, Marchand-Adam, S., additional, Richez, C., additional, Nunes, H., additional, Froguel, P., additional, Avouac, J., additional, Flipo, R. M., additional, Cottin, V., additional, Boissier, M. C., additional, Schaeverbeke, T., additional, Saidenberg Kermanac’h, N., additional, Crestani, B., additional, Doyle, T., additional, Raychaudhuri, S., additional, Karlson, E., additional, Yaspan, B. L., additional, and Dieudé, P., additional

Published
2024
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164. POS0034 ASSOCIATIONS OF 31 NOVEL COPA NON-SYNONYMOUS VARIANTS WITH AUTOIMMUNE AND INFLAMMATORY CLINICAL PHENOTYPES AMONG 160,365 INDIVIDUALS: DEFINING A COPA SPECTRUM DISORDER

Author

Juge, P. A., primary, Kronzer, V. L., additional, David-Gabarre, C., additional, Frémond, M. L., additional, Kechiche, R., additional, Mcdermott, G., additional, Wang, X., additional, Hayashi, K., additional, Cui, J., additional, Mueller, K., additional, Own, M., additional, Wobma, H., additional, Lee, P. Y., additional, Raychaudhuri, S., additional, Wallace, Z. S., additional, Karlson, E., additional, Dieudé, P., additional, and Sparks, J. A., additional

Published
2024
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165. Education and Social Fluidity: A Reweighting Approach

Author

Kristian Bernt Karlson

Subjects
social mobility, social class, education, direct effects, stratification, inequality, Sociology (General), HM401-1281
Abstract

Although sociologists have devoted considerable attention to studying the role of education in intergenerational social class mobility using log-linear models for contingency tables, indings in this literature are not free from rescaling or non-collapsibility bias caused by adjusting for education in these models. Drawing on the methodological literature on inverse probability reweighting, I present a straightforward standardization approach free from this bias. The approach reweighs in an initial step the mobility table cell frequencies to create a pseudo-population in which social class origins and education are independent of each other, after which one can apply any loglinear model to the reweighted mobility table. In contrast to the Karlson-Holm-Breen method, the approach yields coefficients that are comparable across different studies because they are unaffected by education's predictive power of class destinations. Moreover, the approach is easily applied to models for various types of mobility patterns such as those in the core model of fluidity; it yields a single summary measure of overall mediation; and it can incorporate several mediating variables, allowing researchers to control for additional merit proxies such as cognitive skills or potential confounders such as age. I illustrate the utility of the approach in four empirical examples.

Published
2022
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168. Returning actionable genomic results in a research biobank: Analytic validity, clinical implementation, and resource utilization

Author

Blout Zawatsky, Carrie L., Shah, Nidhi, Machini, Kalotina, Perez, Emma, Christensen, Kurt D., Zouk, Hana, Steeves, Marcie, Koch, Christopher, Uveges, Melissa, Shea, Janelle, Gold, Nina, Krier, Joel, Boutin, Natalie, Mahanta, Lisa, Rehm, Heidi L., Weiss, Scott T., Karlson, Elizabeth W., Smoller, Jordan W., Lebo, Matthew S., and Green, Robert C.

Published
2021
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169. Researching COVID to Enhance Recovery (RECOVER) adult study protocol: Rationale, objectives, and design.

Author

Leora I Horwitz, Tanayott Thaweethai, Shari B Brosnahan, Mine S Cicek, Megan L Fitzgerald, Jason D Goldman, Rachel Hess, S L Hodder, Vanessa L Jacoby, Michael R Jordan, Jerry A Krishnan, Adeyinka O Laiyemo, Torri D Metz, Lauren Nichols, Rachel E Patzer, Anisha Sekar, Nora G Singer, Lauren E Stiles, Barbara S Taylor, Shifa Ahmed, Heather A Algren, Khamal Anglin, Lisa Aponte-Soto, Hassan Ashktorab, Ingrid V Bassett, Brahmchetna Bedi, Nahid Bhadelia, Christian Bime, Marie-Abele C Bind, Lora J Black, Andra L Blomkalns, Hassan Brim, Mario Castro, James Chan, Alexander W Charney, Benjamin K Chen, Li Qing Chen, Peter Chen, David Chestek, Lori B Chibnik, Dominic C Chow, Helen Y Chu, Rebecca G Clifton, Shelby Collins, Maged M Costantine, Sushma K Cribbs, Steven G Deeks, John D Dickinson, Sarah E Donohue, Matthew S Durstenfeld, Ivette F Emery, Kristine M Erlandson, Julio C Facelli, Rachael Farah-Abraham, Aloke V Finn, Melinda S Fischer, Valerie J Flaherman, Judes Fleurimont, Vivian Fonseca, Emily J Gallagher, Jennifer C Gander, Maria Laura Gennaro, Kelly S Gibson, Minjoung Go, Steven N Goodman, Joey P Granger, Frank L Greenway, John W Hafner, Jenny E Han, Michelle S Harkins, Kristine S P Hauser, James R Heath, Carla R Hernandez, On Ho, Matthew K Hoffman, Susan E Hoover, Carol R Horowitz, Harvey Hsu, Priscilla Y Hsue, Brenna L Hughes, Prasanna Jagannathan, Judith A James, Janice John, Sarah Jolley, S E Judd, Joy J Juskowich, Diane G Kanjilal, Elizabeth W Karlson, Stuart D Katz, J Daniel Kelly, Sara W Kelly, Arthur Y Kim, John P Kirwan, Kenneth S Knox, Andre Kumar, Michelle F Lamendola-Essel, Margaret Lanca, Joyce K Lee-Lannotti, R Craig Lefebvre, Bruce D Levy, Janet Y Lin, Brian P Logarbo, Jennifer K Logue, Michele T Longo, Carlos A Luciano, Karen Lutrick, Shahdi K Malakooti, Gail Mallett, Gabrielle Maranga, Jai G Marathe, Vincent C Marconi, Gailen D Marshall, Christopher F Martin, Jeffrey N Martin, Heidi T May, Grace A McComsey, Dylan McDonald, Hector Mendez-Figueroa, Lucio Miele, Murray A Mittleman, Sindhu Mohandas, Christian Mouchati, Janet M Mullington, Girish N Nadkarni, Erica R Nahin, Robert B Neuman, Lisa T Newman, Amber Nguyen, Janko Z Nikolich, Igho Ofotokun, Princess U Ogbogu, Anna Palatnik, Kristy T S Palomares, Tanyalak Parimon, Samuel Parry, Sairam Parthasarathy, Thomas F Patterson, Ann Pearman, Michael J Peluso, Priscilla Pemu, Christian M Pettker, Beth A Plunkett, Kristen Pogreba-Brown, Athena Poppas, J Zachary Porterfield, John G Quigley, Davin K Quinn, Hengameh Raissy, Candida J Rebello, Uma M Reddy, Rebecca Reece, Harrison T Reeder, Franz P Rischard, Johana M Rosas, Clifford J Rosen, Nadine G Rouphael, Dwight J Rouse, Adam M Ruff, Christina Saint Jean, Grecio J Sandoval, Jorge L Santana, Shannon M Schlater, Frank C Sciurba, Caitlin Selvaggi, Sudha Seshadri, Howard D Sesso, Dimpy P Shah, Eyal Shemesh, Zaki A Sherif, Daniel J Shinnick, Hyagriv N Simhan, Upinder Singh, Amber Sowles, Vignesh Subbian, Jun Sun, Mehul S Suthar, Larissa J Teunis, John M Thorp, Amberly Ticotsky, Alan T N Tita, Robin Tragus, Katherine R Tuttle, Alfredo E Urdaneta, P J Utz, Timothy M VanWagoner, Andrew Vasey, Suzanne D Vernon, Crystal Vidal, Tiffany Walker, Honorine D Ward, David E Warren, Ryan M Weeks, Steven J Weiner, Jordan C Weyer, Jennifer L Wheeler, Sidney W Whiteheart, Zanthia Wiley, Natasha J Williams, Juan P Wisnivesky, John C Wood, Lynn M Yee, Natalie M Young, Sokratis N Zisis, and Andrea S Foulkes

Subjects
Medicine, Science
Abstract

ImportanceSARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or other health effects after the acute phase of infection; termed post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are ill-defined. The objectives of the Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC in Adults (RECOVER-Adult) are to: (1) characterize PASC prevalence; (2) characterize the symptoms, organ dysfunction, natural history, and distinct phenotypes of PASC; (3) identify demographic, social and clinical risk factors for PASC onset and recovery; and (4) define the biological mechanisms underlying PASC pathogenesis.MethodsRECOVER-Adult is a combined prospective/retrospective cohort currently planned to enroll 14,880 adults aged ≥18 years. Eligible participants either must meet WHO criteria for suspected, probable, or confirmed infection; or must have evidence of no prior infection. Recruitment occurs at 86 sites in 33 U.S. states, Washington, DC and Puerto Rico, via facility- and community-based outreach. Participants complete quarterly questionnaires about symptoms, social determinants, vaccination status, and interim SARS-CoV-2 infections. In addition, participants contribute biospecimens and undergo physical and laboratory examinations at approximately 0, 90 and 180 days from infection or negative test date, and yearly thereafter. Some participants undergo additional testing based on specific criteria or random sampling. Patient representatives provide input on all study processes. The primary study outcome is onset of PASC, measured by signs and symptoms. A paradigm for identifying PASC cases will be defined and updated using supervised and unsupervised learning approaches with cross-validation. Logistic regression and proportional hazards regression will be conducted to investigate associations between risk factors, onset, and resolution of PASC symptoms.DiscussionRECOVER-Adult is the first national, prospective, longitudinal cohort of PASC among US adults. Results of this study are intended to inform public health, spur clinical trials, and expand treatment options.RegistrationNCT05172024.

Published
2023
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170. Tearing down Stanford right now was a costly mistake

Author

Karlson, Katie

Subjects
News, opinion and commentary, Sports and fitness
Abstract

Byline: Katie Karlson Students universally dread housing application season. It's stressful, expensive and more complicated than it needs to be. UM students, especially incoming freshmen, faced a uniquely difficult application [...]

Published
2024

171. Healthy and happy: Top tips for college wellness

Author

Karlson, Katie

Subjects
News, opinion and commentary, Sports and fitness
Abstract

Byline: Katie Karlson Your first semester in college can be stressful. With so many new things to absorb, it can be easy to let your health routine go by the [...]

Published
2024

172. Transportation 101: Safe, easy, and affordable ways to get around Miami

Author

Karlson, Katie

Subjects
Transportation, Transportation industry, News, opinion and commentary, Sports and fitness
Abstract

Byline: Katie Karlson The hardest part about leaving for college wasn't abandoning my bed, or missing out on home-cooked meals or living apart from my parents. No, it was leaving [...]

Published
2024

173. Top 10 items every freshman should have in their dorm

Author

Karlson, Katie

Subjects
News, opinion and commentary, Sports and fitness
Abstract

Byline: Katie Karlson It's a month away from move in day, and you're likely pulling together your packing list for your dorm. While most freshmen arrive on campus with plenty [...]

Published
2024

174. Recycled cathode materials enabled superior performance for lithium-ion batteries

Author

Ma, Xiaotu, Chen, Mengyuan, Zheng, Zhangfeng, Bullen, Dennis, Wang, Jun, Harrison, Chloe, Gratz, Eric, Lin, Yulin, Yang, Zhenzhen, Zhang, Youtian, Wang, Fan, Robertson, David, Son, Seoung-Bum, Bloom, Ira, Wen, Jianguo, Ge, Mingyuan, Xiao, Xianghui, Lee, Wah-Keat, Tang, Ming, Wang, Qiang, Fu, Jinzhao, Zhang, Yubin, Sousa, Bryer C., Arsenault, Renata, Karlson, Peter, Simon, Nakia, and Wang, Yan

Published
2021
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175. SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Author

Neale, Benjamin M., Daly, Mark, Ganna, Andrea, Stevens, Christine, Pathak, Gita A., Andrews, Shea J., Kanai, Masahiro, Cordioli, Mattia, Karjalainen, Juha, Polimanti, Renato, Pirinen, Matti, Harerimana, Nadia, Veerapen, Kumar, Wolford, Brooke, Nguyen, Huy, Solomonson, Matthew, Liao, Rachel G., Chwialkowska, Karolina, Trankiem, Amy, Balaconis, Mary K., Hayward, Caroline, Richmond, Anne, Campbell, Archie, Morris, Marcela, Fawns-Ritchie, Chloe, Glessner, Joseph T., Shaw, Douglas M., Chang, Xiao, Polikowski, Hannah, Lauren, Petty E., Chen, Hung-Hsin, Wanying, Zhu, Hakonarson, Hakon, Porteous, David J., Below, Jennifer, North, Kari, McCormick, Joseph B., Timmers, Paul R.H.J., Wilson, James F., Tenesa, Albert, D’Mellow, Kenton, Kerr, Shona M., Niemi, Mari E.K., Nkambul, Lindokuhle, Aprile von Hohenstaufen, Kathrin, Sobh, Ali, Eltoukhy, Madonna M., Yassen, Amr M., Hegazy, Mohamed A.F., Okasha, Kamal, Eid, Mohammed A., Moahmed, Hanteera S., Shahin, Doaa, El-Sherbiny, Yasser M., Elhadidy, Tamer A., Abd Elghafar, Mohamed S., El-Jawhari, Jehan J., Mohamed, Attia A.S., Elnagdy, Marwa H., Samir, Amr, Abdel-Aziz, Mahmoud, Khafaga, Walid T., El-Lawaty, Walaa M., Torky, Mohamed S., El-shanshory, Mohamed R., Batini, Chiara, Lee, Paul H., Shrine, Nick, Williams, Alexander T., Tobin, Martin D., Guyatt, Anna L., John, Catherine, Packer, Richard J., Ali, Altaf, Free, Robert C., Wang, Xueyang, Wain, Louise V., Hollox, Edward J., Venn, Laura D., Bee, Catherine E., Adams, Emma L., Niavarani, Ahmadreza, Sharififard, Bahareh, Aliannejad, Rasoul, Amirsavadkouhi, Ali, Naderpour, Zeinab, Tadi, Hengameh Ansari, Aleagha, Afshar Etemadi, Ahmadi, Saeideh, Mohseni Moghaddam, Seyed Behrooz, Adamsara, Alireza, Saeedi, Morteza, Abdollahi, Hamed, Hosseini, Abdolmajid, Chariyavilaskul, Pajaree, Chamnanphon, Monpat, Suttichet, Thitima B., Shotelersuk, Vorasuk, Pongpanich, Monnat, Phokaew, Chureerat, Chetruengchai, Wanna, Jantarabenjakul, Watsamon, Putchareon, Opass, Torvorapanit, Pattama, Puthanakit, Thanyawee, Suchartlikitwong, Pintip, Hirankarn, Nattiya, Nilaratanakul, Voraphoj, Sodsai, Pimpayao, Brumpton, Ben M., Hveem, Kristian, Willer, Cristen, Zhou, Wei, Rogne, Tormod, Solligard, Erik, Åsvold, Bjørn Olav, Abedalthagafi, Malak, Alaamery, Manal, Alqahtani, Saleh, Baraka, Dona, Al Harthi, Fawz, Alsolm, Ebtehal, Safieh, Leen Abu, Alowayn, Albandary M., Alqubaishi, Fatimah, Al Mutairi, Amal, Mangul, Serghei, Alshareef, Abdulraheem, Sawaji, Mona, Almutairi, Mansour, Aljawini, Nora, Albesher, Nour, Arabi, Yaseen M., Mahmoud, Ebrahim S., Khattab, Amin K., Halawani, Roaa T., Alahmadey, Ziab Z., Albakri, Jehad K., Felemban, Walaa A., Suliman, Bandar A., Hasanato, Rana, Al-Awdah, Laila, Alghamdi, Jahad, AlZahrani, Deema, AlJohani, Sameera, Al-Afghani, Hani, Alrashed, May, AlDhawi, Nouf, AlBardis, Hadeel, Alkwai, Sarah, Alswailm, Moneera, Almalki, Faisal, Albeladi, Maha, Almohammed, Iman, Barhoush, Eman, Albader, Anoud, Massadeh, Salam, AlMalik, Abdulaziz, Alotaibi, Sara, Alghamdi, Bader, Jung, Junghyun, Fawzy, Mohammad S., Lee, Yunsung, Magnus, Per, Trogstad, Lill-Iren S., Helgeland, Øyvind, Harris, Jennifer R., Mangino, Massimo, Spector, Tim D., Emma, Duncan, Smieszek, Sandra P., Przychodzen, Bartlomiej P., Polymeropoulos, Christos, Polymeropoulos, Vasilios, Polymeropoulos, Mihael H., Fernandez-Cadenas, Israel, Perez-Tur, Jordi, Llucià-Carol, Laia, Cullell, Natalia, Muiño, Elena, Cárcel-Márquez, Jara, DeDiego, Marta L., Iglesias, Lara Lloret, Planas, Anna M., Soriano, Alex, Rico, Veronica, Agüero, Daiana, Bedini, Josep L., Lozano, Francisco, Domingo, Carlos, Robles, Veronica, Ruiz-Jaén, Francisca, Márquez, Leonardo, Gomez, Juan, Coto, Eliecer, Albaiceta, Guillermo M., García-Clemente, Marta, Dalmau, David, Arranz, Maria J., Dietl, Beatriz, Serra-Llovich, Alex, Soler, Pere, Colobrán, Roger, Martín-Nalda, Andrea, Martínez, Alba Parra, Bernardo, David, Rojo, Silvia, Fiz-López, Aida, Arribas, Elisa, Cal-Sabater, Paloma de la, Segura, Tomás, González-Villa, Esther, Serrano-Heras, Gemma, Martí-Fàbregas, Joan, Jiménez-Xarrié, Elena, de Felipe Mimbrera, Alicia, Masjuan, Jaime, García-Madrona, Sebastian, Domínguez-Mayoral, Anna, Villalonga, Joan Montaner, Menéndez-Valladares, Paloma, Chasman, Daniel I., Buring, Julie E., Ridker, Paul M., Franco, Giulianini, Sesso, Howard D., Manson, JoAnn E., Glessner, Joseph R., Medina-Gomez, Carolina, Uitterlinden, Andre G., Ikram, M. Arfan, Kristiansson, Kati, Koskelainen, Sami, Perola, Markus, Donner, Kati, Kivinen, Katja, Palotie, Aarno, Ripatti, Samuli, Ruotsalainen, Sanni, Kaunisto, Mari, FinnGen, Nakanishi, Tomoko, Butler-Laporte, Guillaume, Forgetta, Vincenzo, Morrison, David R., Ghosh, Biswarup, Laurent, Laetitia, Belisle, Alexandre, Henry, Danielle, Abdullah, Tala, Adeleye, Olumide, Mamlouk, Noor, Kimchi, Nofar, Afrasiabi, Zaman, Branka Vulesevic, Nardin Rezk, Bouab, Meriem, Guzman, Charlotte, Petitjean, Louis, Tselios, Chris, Xue, Xiaoqing, Schurr, Erwin, Afilalo, Jonathan, Afilalo, Marc, Oliveira, Maureen, Brenner, Bluma, Lepage, Pierre, Ragoussis, Jiannis, Auld, Daniel, Brassard, Nathalie, Durand, Madeleine, Chassé, Michaël, Kaufmann, Daniel E., Lathrop, G. Mark, Mooser, Vincent, Richards, J. Brent, Li, Rui, Adra, Darin, Rahmouni, Souad, Georges, Michel, Moutschen, Michel, Misset, Benoit, Darcis, Gilles, Guiot, Julien, Guntz, Julien, Azarzar, Samira, Gofflot, Stéphanie, Beguin, Yves, Claassen, Sabine, Malaise, Olivier, Huynen, Pascale, Meuris, Christelle, Thys, Marie, Jacques, Jessica, Léonard, Philippe, Frippiat, Frederic, Giot, Jean-Baptiste, Sauvage, Anne-Sophie, Von Frenckell, Christian, Belhaj, Yasmine, Lambermont, Bernard, Pigazzini, Sara, Nkambule, Lindokuhle, Daya, Michelle, Shortt, Jonathan, Rafaels, Nicholas, Wicks, Stephen J., Crooks, Kristy, Barnes, Kathleen C., Gignoux, Christopher R., Chavan, Sameer, Laisk, Triin, Läll, Kristi, Lepamets, Maarja, Mägi, Reedik, Esko, Tõnu, Reimann, Ene, Milani, Lili, Alavere, Helene, Metsalu, Kristjan, Puusepp, Mairo, Metspalu, Andres, Naaber, Paul, Laane, Edward, Pesukova, Jaana, Peterson, Pärt, Kisand, Kai, Tabri, Jekaterina, Allos, Raili, Hensen, Kati, Starkopf, Joel, Ringmets, Inge, Tamm, Anu, Kallaste, Anne, Bochud, Pierre-Yves, Rivolta, Carlo, Bibert, Stéphanie, Quinodoz, Mathieu, Kamdar, Dhryata, Boillat, Noémie, Nussle, Semira Gonseth, Albrich, Werner, Suh, Noémie, Neofytos, Dionysios, Erard, Véronique, Voide, Cathy, FHoGID, RegCOVID, P-PredictUs, SeroCOVID, CRiPSI, de Cid, Rafael, Galván-Femenía, Iván, Blay, Natalia, Carreras, Anna, Cortés, Beatriz, Farré, Xavier, Sumoy, Lauro, Moreno, Victor, Mercader, Josep Maria, Guindo-Martinez, Marta, Torrents, David, Kogevinas, Manolis, Garcia-Aymerich, Judith, Castaño-Vinyals, Gemma, Dobaño, Carlota, Renieri, Alessandra, Mari, Francesca, Fallerini, Chiara, Daga, Sergio, Benetti, Elisa, Baldassarri, Margherita, Fava, Francesca, Frullanti, Elisa, Valentino, Floriana, Doddato, Gabriella, Giliberti, Annarita, Tita, Rossella, Amitrano, Sara, Bruttini, Mirella, Croci, Susanna, Meloni, Ilaria, Mencarelli, Maria Antonietta, Lo Rizzo, Caterina, Pinto, Anna Maria, Beligni, Giada, Tommasi, Andrea, Di Sarno, Laura, Palmieri, Maria, Carriero, Miriam Lucia, Alaverdian, Diana, Busani, Stefano, Bruno, Raffaele, Vecchia, Marco, Belli, Mary Ann, Picchiotti, Nicola, Sanarico, Maurizio, Gori, Marco, Furini, Simone, Mantovani, Stefania, Ludovisi, Serena, Mondelli, Mario Umberto, Castelli, Francesco, Quiros-Roldan, Eugenia, Antoni, Melania Degli, Zanella, Isabella, Vaghi, Massimo, Rusconi, Stefano, Siano, Matteo, Montagnani, Francesca, Emiliozzi, Arianna, Fabbiani, Massimiliano, Rossetti, Barbara, Bargagli, Elena, Bergantini, Laura, D’Alessandro, Miriana, Cameli, Paolo, Bennett, David, Anedda, Federico, Marcantonio, Simona, Scolletta, Sabino, Franchi, Federico, Mazzei, Maria Antonietta, Guerrini, Susanna, Conticini, Edoardo, Cantarini, Luca, Frediani, Bruno, Tacconi, Danilo, Spertilli, Chiara, Feri, Marco, Donati, Alice, Scala, Raffaele, Guidelli, Luca, Spargi, Genni, Corridi, Marta, Nencioni, Cesira, Croci, Leonardo, Bandini, Maria, Caldarelli, Gian Piero, Piacentini, Paolo, Desanctis, Elena, Cappelli, Silvia, Canaccini, Anna, Verzuri, Agnese, Anemoli, Valentina, Ognibene, Agostino, Pancrazzi, Alessandro, Lorubbio, Maria, D’Arminio Monforte, Antonella, Miraglia, Federica Gaia, Girardis, Massimo, Venturelli, Sophie, Cossarizza, Andrea, Antinori, Andrea, Vergori, Alessandra, Gabrieli, Arianna, Riva, Agostino, Francisci, Daniela, Schiaroli, Elisabetta, Paciosi, Francesco, Scotton, Pier Giorgio, Andretta, Francesca, Panese, Sandro, Scaggiante, Renzo, Gatti, Francesca, Parisi, Saverio Giuseppe, Baratti, Stefano, Della Monica, Matteo, Piscopo, Carmelo, Capasso, Mario, Russo, Roberta, Andolfo, Immacolata, Iolascon, Achille, Fiorentino, Giuseppe, Carella, Massimo, Castori, Marco, Merla, Giuseppe, Squeo, Gabriella Maria, Aucella, Filippo, Raggi, Pamela, Marciano, Carmen, Perna, Rita, Bassetti, Matteo, Di Biagio, Antonio, Sanguinetti, Maurizio, Masucci, Luca, Valente, Serafina, Mandalà, Marco, Giorli, Alessia, Salerni, Lorenzo, Zucchi, Patrizia, Parravicini, Pierpaolo, Menatti, Elisabetta, Trotta, Tullio, Giannattasio, Ferdinando, Coiro, Gabriella, Lena, Fabio, Coviello, Domenico A., Mussini, Cristina, Martinelli, Enrico, Mancarella, Sandro, Tavecchia, Luisa, Crotti, Lia, Gabbi, Chiara, Rizzi, Marco, Maggiolo, Franco, Ripamonti, Diego, Bachetti, Tiziana, La Rovere, Maria Teresa, Sarzi-Braga, Simona, Bussotti, Maurizio, Ceri, Stefano, Pinoli, Pietro, Raimondi, Francesco, Biscarini, Filippo, Stella, Alessandra, Zguro, Kristina, Capitani, Katia, Suardi, Claudia, Dei, Simona, Parati, Gianfranco, Ravaglia, Sabrina, Artuso, Rosangela, Bottà, Giordano, Di Domenico, Paolo, Rancan, Ilaria, Francesco Bianchi, Antonio Perrella, Romani, Davide, Bergomi, Paola, Catena, Emanuele, Colombo, Riccardo, Tanfoni, Marco, Vincenti, Antonella, Ferri, Claudio, Grassi, Davide, Pessina, Gloria, Tumbarello, Mario, Di Pietro, Massimo, Sabrina, Ravaglia, Luchi, Sauro, Barbieri, Chiara, Acquilini, Donatella, Andreucci, Elena, Segala, Francesco Vladimiro, Tiseo, Giusy, Falcone, Marco, Lista, Mirjam, Poscente, Monica, De Vivo, Oreste, Petrocelli, Paola, Guarnaccia, Alessandra, Baroni, Silvia, Smith, Albert V., Boughton, Andrew P., Li, Kevin W., LeFaive, Jonathon, Annis, Aubrey, Justice, Anne E., Mirshahi, Tooraj, Chittoor, Geetha, Josyula, Navya Shilpa, Kosmicki, Jack A., Ferreira, Manuel A.R., Leader, Joseph B., Carey, Dave J., Gass, Matthew C., Horowitz, Julie E., Cantor, Michael N., Yadav, Ashish, Baras, Aris, Abecasis, Goncalo R., van Heel, David A., Hunt, Karen A., Mason, Dan, Huang, Qin Qin, Finer, Sarah, Genes & Health Research Team, Trivedi, Bhavi, Griffiths, Christopher J., Martin, Hilary C., Wright, John, Trembath, Richard C., Soranzo, Nicole, Zhao, Jing Hua, Butterworth, Adam S., Danesh, John, Di Angelantonio, Emanuele, Marike Boezen, Lude Franke, Deelen, Patrick, Claringbould, Annique, Lopera, Esteban, Warmerdam, Robert, Vonk, Judith.M., van Blokland, Irene, Lanting, Pauline, Ori, Anil P.S., Sebastian Zöllner, Brooke Wolford, Wang, Jiongming, Beck, Andrew, Peloso, Gina, Ho, Yuk-Lam, Sun, Yan V., Huffman, Jennifer E., O’Donnell, Christopher J., Cho, Kelly, Tsao, Phil, Gaziano, J. Michael, Nivard, Michel (M.G.), de geus, Eco (E.J.C.), Bartels, Meike, Hottenga, Jouke Jan, Weiss, Scott T., Karlson, Elizabeth W., Smoller, Jordan W., Green, Robert C., Anne Feng, Yen-Chen, Mercader, Josep, Murphy, Shawn N., Meigs, James B., Woolley, Ann E., Perez, Emma F., Rader, Daniel, Verma, Anurag, Ritchie, Marylyn D., Li, Binglan, Verma, Shefali S., Lucas, Anastasia, Bradford, Yuki, Zeberg, Hugo, Frithiof, Robert, Hultström, Michael, Lipcsey, Miklos, Nkambul, Lindo, Tardif, Nicolas, Rooyackers, Olav, Grip, Jonathan, Maricic, Tomislav, Karczewski, Konrad J., Atkinson, Elizabeth G., Tsuo, Kristin, Baya, Nikolas, Turley, Patrick, Gupta, Rahul, Callier, Shawneequa, Walters, Raymond K., Palmer, Duncan S., Sarma, Gopal, Cheng, Nathan, Lu, Wenhan, Bryant, Sam, Churchhouse, Claire, Cusick, Caroline, Goldstein, Jacqueline I., King, Daniel, Seed, Cotton, Finucane, Hilary, Martin, Alicia R., Satterstrom, F. Kyle, Wilson, Daniel J., Armstrong, Jacob, Rudkin, Justine K., Band, Gavin, Earle, Sarah G., Lin, Shang-Kuan, Arning, Nicolas, Crook, Derrick W., Wyllie, David H., O’Connell, Anne Marie, Spencer, Chris C.A., Koelling, Nils, Caulfield, Mark J., Scott, Richard H., Fowler, Tom, Moutsianas, Loukas, Kousathanas, Athanasios, Pasko, Dorota, Walker, Susan, Rendon, Augusto, Stuckey, Alex, Odhams, Christopher A., Rhodes, Daniel, Chan, Georgia, Arumugam, Prabhu, Ball, Catherine A., Hong, Eurie L., Rand, Kristin, Girshick, Ahna, Guturu, Harendra, Baltzell, Asher Haug, Roberts, Genevieve, Park, Danny, Coignet, Marie, McCurdy, Shannon, Knight, Spencer, Partha, Raghavendran, Rhead, Brooke, Zhang, Miao, Berkowitz, Nathan, Gaddis, Michael, Noto, Keith, Ruiz, Luong, Pavlovic, Milos, Sloofman, Laura G., Charney, Alexander W., Beckmann, Noam D., Schadt, Eric E., Jordan, Daniel M., Thompson, Ryan C., Gettler, Kyle, Abul-Husn, Noura S., Ascolillo, Steven, Buxbaum, Joseph D., Chaudhary, Kumardeep, Cho, Judy H., Itan, Yuval, Kenny, Eimear E., Belbin, Gillian M., Sealfon, Stuart C., Sebra, Robert P., Salib, Irene, Collins, Brett L., Levy, Tess, Britvan, Bari, Keller, Katherine, Tang, Lara, Peruggia, Michael, Hiester, Liam L., Niblo, Kristi, Aksentijevich, Alexandra, Labkowsky, Alexander, Karp, Avromie, Zlatopolsky, Menachem, Preuss, Michael, Loos, Ruth J.F., Nadkarni, Girish N., Do, Ron, Hoggart, Clive, Choi, Sam, Underwood, Slayton J., O’Reilly, Paul, Huckins, Laura M., Zyndorf, Marissa, D’Antonio, Matteo, Nguyen, Jennifer P., Arthur, Timothy D., Matsui, Hiroko, D’Antonio-Chronowska, Agnieszka, and Frazer, Kelly A.

Published
2021
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177. Neptune: an environment for the delivery of genomic medicine

Author

Eric, Venner, Yi, Victoria, Murdock, David, Kalla, Sara E., Wu, Tsung-Jung, Sabo, Aniko, Li, Shoudong, Meng, Qingchang, Tian, Xia, Murugan, Mullai, Cohen, Michelle, Kovar, Christie, Wei, Wei-Qi, Chung, Wendy K., Weng, Chunhua, Wiesner, Georgia L., Jarvik, Gail P., Muzny, Donna, Gibbs, Richard A., Abrams, Debra, Adunyah, Samuel E., Albertson-Junkans, Ladia, Almoguera, Berta, Ames, Darren C., Appelbaum, Paul, Aronson, Samuel, Aufox, Sharon, Babb, Lawrence J., Balasubramanian, Adithya, Bangash, Hana, Basford, Melissa, Bastarache, Lisa, Baxter, Samantha, Behr, Meckenzie, Benoit, Barbara, Bhoj, Elizabeth, Bielinski, Suzette J., Bland, Harris T., Blout, Carrie, Borthwick, Kenneth, Bottinger, Erwin P., Bowser, Mark, Brand, Harrison, Brilliant, Murray, Brodeur, Wendy, Caraballo, Pedro, Carrell, David, Carroll, Andrew, Castillo, Lisa, Castro, Victor, Chandanavelli, Gauthami, Chiang, Theodore, Chisholm, Rex L., Christensen, Kurt D., Chung, Wendy, Chute, Christopher G., City, Brittany, Cobb, Beth L., Connolly, John J., Crane, Paul, Crew, Katherine, Crosslin, David R., Dayal, Jyoti, De Andrade, Mariza, De la Cruz, Jessica, Denny, Josh C., Denson, Shawn, DeSmet, Tim, Dikilitas, Ozan, Dinsmore, Michael J., Dodge, Sheila, Dunlea, Phil, Edwards, Todd L., Eng, Christine M., Fasel, David, Fedotov, Alex, Feng, Qiping, Fleharty, Mark, Foster, Andrea, Freimuth, Robert, Friedrich, Christopher, Fullerton, Stephanie M., Funke, Birgit, Gabriel, Stacey, Gainer, Vivian, Gharavi, Ali, Glazer, Andrew M., Glessner, Joseph T., Goehringer, Jessica, Gordon, Adam S., Graham, Chet, Green, Robert C., Gundelach, Justin H., Hain, Heather S., Hakonarson, Hakon, Harden, Maegan V., Harley, John, Harr, Margaret, Hartzler, Andrea, Hayes, M. Geoffrey, Hebbring, Scott, Henrikson, Nora, Hershey, Andrew, Hoell, Christin, Holm, Ingrid, Howell, Kayla M., Hripcsak, George, Hu, Jianhong, Hynes, Elizabeth Duffy, Jayaseelan, Joy C., Jiang, Yunyun, Joo, Yoonjung Yoonie, Jose, Sheethal, Josyula, Navya Shilpa, Justice, Anne E., Kalra, Divya, Karlson, Elizabeth W., Keating, Brendan J., Kelly, Melissa A., Kenny, Eimear E., Key, Dustin, Kiryluk, Krzysztof, Kitchner, Terrie, Klanderman, Barbara, Klee, Eric, Kochan, David C., Korchina, Viktoriya, Kottyan, Leah, Kudalkar, Emily, Rahm, Alanna Kulchak, Kullo, Iftikhar J., Lammers, Philip, Larson, Eric B., Lebo, Matthew S., Leduc, Magalie, Lee, Ming Ta (Michael), Lennon, Niall J., Leppig, Kathleen A., Leslie, Nancy D., Li, Rongling, Liang, Wayne H., Lin, Chiao-Feng, Linder, Jodell E., Lindor, Noralane M., Lingren, Todd, Linneman, James G., Liu, Cong, Liu, Wen, Liu, Xiuping, Lynch, John, Lyon, Hayley, Macbeth, Alyssa, Mahadeshwar, Harshad, Mahanta, Lisa, Malin, Bradley, Manolio, Teri, Marasa, Maddalena, Marsolo, Keith, McGowan, Michelle L., McNally, Elizabeth, Meldrim, Jim, Mentch, Frank, Rasouly, Hila Milo, Mosley, Jonathan, Mukherjee, Shubhabrata, Mullen, Thomas E., Muniz, Jesse, Murdock, David R., Murphy, Shawn, Myers, Melanie F., Namjou, Bahram, Ni, Yizhao, Onofrio, Robert C., Obeng, Aniwaa Owusu, Person, Thomas N., Peterson, Josh F., Petukhova, Lynn, Pisieczko, Cassandra J., Pratap, Siddharth, Prows, Cynthia A., Puckelwartz, Megan J., Raj, Ritika, Ralston, James D., Ramaprasan, Arvind, Ramirez, Andrea, Rasmussen, Luke, Rasmussen-Torvik, Laura, Raychaudhuri, Soumya, Rehm, Heidi L., Ritchie, Marylyn D., Rives, Catherine, Riza, Beenish, Roden, Dan M., Rosenthal, Elisabeth A., Santani, Avni, Dan, Schaid, Scherer, Steven, Scott, Stuart, Scrol, Aaron, Sengupta, Soumitra, Shang, Ning, Sharma, Himanshu, Sharp, Richard R., Singh, Rajbir, Sleiman, Patrick M.A., Slowik, Kara, Smith, Joshua C., Smith, Maureen E., Smoot, Duane T., Smoller, Jordan W., Sohn, Sunghwan, Stanaway, Ian B., Starren, Justin, Stroud, Mary, Su, Jessica, Taylor, Casey Overby, Tolwinski, Kasia, Van Driest, Sara L., Vargas, Sean M., Varugheese, Matthew, Veenstra, David, Venner, Eric, Verbitsky, Miguel, Vicente, Gina, Wagner, Michael, Walker, Kimberly, Walunas, Theresa, Wang, Liwen, Wang, Qiaoyan, Weiss, Scott T., Wells, Quinn S., White, Peter S., Wiley, Ken L., Jr, Williams, Janet L., Williams, Marc S., Wilson, Michael W., Witkowski, Leora, Woods, Laura Allison, Woolf, Betty, Wynn, Julia, Yang, Yaping, Zhang, Ge, Zhang, Lan, and Zouk, Hana

Published
2021
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180. Is Denmark a Much More Educationally Mobile Society than the United States? Comment on Andrade and Thomsen, 'Intergenerational Educational Mobility in Denmark and the United States' (2018)

Author

Kristian Bernt Karlson

Subjects
educational mobility, social mobility, stratification, welfare states, educational inequality, education, Sociology (General), HM401-1281
Abstract

I evaluate Andrade and Thomsen (A&T)'s (2018) study, which concludes that Denmark is significantly more educationally mobile than the United States. I make three observations. First, A&T overstate the difference in educational mobility between Denmark and the United States. Both in international comparison and compared with differences in intergenerational income mobility, A&T's reported country differences in educational mobility are negligible. For example, whereas income mobility estimates reported in the literature differ by 300 to 600 percent between the two countries, the corresponding educational mobility estimates that A&T report differ by 10 to 20 percent. Second, I provide evidence suggesting that A&T's use of crude categorical education measures leads them to overstate these negligible differences. Third, A&T's empirical analyses of the U.S. data contain several statistical and data-related flaws, some so severe that they potentially undermine the credibility of their analyses. In sum, A&T's results are perfectly consistent with the existence of a mobility paradox very similar to what Sweden–United States comparisons show: although Denmark and the United States are dissimilar with respect to income mobility, they are similar with respect to educational mobility. Understanding the nature of this paradox should be a key concern for future mobility research.

Published
2021
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181. An independently validated, portable algorithm for the rapid identification of COPD patients using electronic health records

Author

Su H. Chu, Emily S. Wan, Michael H. Cho, Sergey Goryachev, Vivian Gainer, James Linneman, Erica J. Scotty, Scott J. Hebbring, Shawn Murphy, Jessica Lasky-Su, Scott T. Weiss, Jordan W. Smoller, and Elizabeth Karlson

Subjects
Medicine, Science
Abstract

Abstract Electronic health records (EHR) provide an unprecedented opportunity to conduct large, cost-efficient, population-based studies. However, the studies of heterogeneous diseases, such as chronic obstructive pulmonary disease (COPD), often require labor-intensive clinical review and testing, limiting widespread use of these important resources. To develop a generalizable and efficient method for accurate identification of large COPD cohorts in EHRs, a COPD datamart was developed from 3420 participants meeting inclusion criteria in the Mass General Brigham Biobank. Training and test sets were selected and labeled with gold-standard COPD classifications obtained from chart review by pulmonologists. Multiple classes of algorithms were built utilizing both structured (e.g. ICD codes) and unstructured (e.g. medical notes) data via elastic net regression. Models explicitly including and excluding spirometry features were compared. External validation of the final algorithm was conducted in an independent biobank with a different EHR system. The final COPD classification model demonstrated excellent positive predictive value (PPV; 91.7%), sensitivity (71.7%), and specificity (94.4%). This algorithm performed well not only within the MGBB, but also demonstrated similar or improved classification performance in an independent biobank (PPV 93.5%, sensitivity 61.4%, specificity 90%). Ancillary comparisons showed that the classification model built including a binary feature for FEV1/FVC produced substantially higher sensitivity than those excluding. This study fills a gap in COPD research involving population-based EHRs, providing an important resource for the rapid, automated classification of COPD cases that is both cost-efficient and requires minimal information from unstructured medical records.

Published
2021
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184. Dairy consumption, plasma metabolites, and risk of type 2 diabetes

Author

Drouin-Chartier, Jean-Philippe, Hernández-Alonso, Pablo, Guasch-Ferré, Marta, Ruiz-Canela, Miguel, Li, Jun, Wittenbecher, Clemens, Razquin, Cristina, Toledo, Estefanía, Dennis, Courtney, Corella, Dolores, Estruch, Ramon, Fitó, Montserrat, Eliassen, A Heather, Tobias, Deirdre K, Ascherio, Alberto, Mucci, Lorelei A, Rexrode, Kathryn M, Karlson, Elizabeth W, Costenbader, Karen H, Fuchs, Charles S, Liang, Liming, Clish, Clary B, Martínez-González, Miguel A, Salas-Salvadó, Jordi, and Hu, Frank B

Published
2021
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191. Interoperable vocabulary for marine microbial flow cytometry

Author

Melilotus Thyssen, Gérald Grégori, Véronique Créach, Soumaya Lahbib, Mathilde Dugenne, Hedy M. Aardema, Luis-Felipe Artigas, Bangqin Huang, Aude Barani, Laureen Beaugeard, Amel Bellaaj-Zouari, Alfred Beran, Raffaella Casotti, Yolanda Del Amo, Michel Denis, George B.J. Dubelaar, Sonja Endres, Lumi Haraguchi, Bengt Karlson, Christophe Lambert, Arnaud Louchart, Dominique Marie, Gwenaëlle Moncoiffé, David Pecqueur, François Ribalet, Machteld Rijkeboer, Tina Silovic, Ricardo Silva, Sophie Marro, Heidi M. Sosik, Marc Sourisseau, Glen Tarran, Nicolas Van Oostende, Li Zhao, and Shan Zheng

Subjects
flow cytometry, marine microorganisms, standardization, vocabulary, FAIR principle interoperable vocabulary for marine flow cytometry, Science, General. Including nature conservation, geographical distribution, QH1-199.5
Abstract

The recent development of biological sensors has extended marine plankton studies from conducting laboratory bench work to in vivo and real-time observations. Flow cytometry (FCM) has shed new light on marine microorganisms since the 1980s through its single-cell approach and robust detection of the smallest cells. FCM records valuable optical properties of light scattering and fluorescence from cells passing in a single file in front of a narrow-collimated light source, recording tens of thousands of cells within a few minutes. Depending on the instrument settings, the sampling strategy, and the automation level, it resolves the spatial and temporal distribution of microbial marine prokaryotes and eukaryotes. Cells are usually classified and grouped on cytograms by experts and are still lacking standards, reducing data sharing capacities. Therefore, the need to make FCM data sets FAIR (Findability, Accessibility, Interoperability, and Reusability of digital assets) is becoming critical. In this paper, we present a consensus vocabulary for the 13 most common marine microbial groups observed with FCM using blue and red-light excitation. The authors designed a common layout on two-dimensional log-transformed cytograms reinforced by a decision tree that facilitates the characterization of groups. The proposed vocabulary aims at standardising data analysis and definitions, to promote harmonisation and comparison of data between users and instruments. This represents a much-needed step towards FAIRification of flow cytometric data collected in various marine environments.

Published
2022
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192. Concordance of SARS-CoV-2 Antibody Results during a Period of Low Prevalence

Author

Cheryl N. Miller, Keri N. Althoff, David J. Schlueter, Hoda Anton-Culver, Qingxia Chen, Shawn Garbett, Francis Ratsimbazafy, Isaac Thomsen, Elizabeth W. Karlson, Mine Cicek, Ligia A. Pinto, Bradley A. Malin, Lucila Ohno-Machado, Carolyn Williams, David Goldstein, Aymone Kouame, Andrea Ramirez, Kelly A. Gebo, and Sheri D. Schully

Subjects
SARS-CoV-2, IgG antibodies, spike protein, nucleocapsid protein, low prevalence, Microbiology, QR1-502
Abstract

ABSTRACT Accurate, highly specific immunoassays for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are needed to evaluate seroprevalence. This study investigated the concordance of results across four immunoassays targeting different antigens for sera collected at the beginning of the SARS-CoV-2 pandemic in the United States. Specimens from All of Us participants contributed between January and March 2020 were tested using the Abbott Architect SARS-CoV-2 IgG (immunoglobulin G) assay (Abbott) and the EuroImmun SARS-CoV-2 enzyme-linked immunosorbent assay (ELISA) (EI). Participants with discordant results, participants with concordant positive results, and a subset of concordant negative results by Abbott and EI were also tested using the Roche Elecsys anti-SARS-CoV-2 (IgG) test (Roche) and the Ortho-Clinical Diagnostics Vitros anti-SARS-CoV-2 IgG test (Ortho). The agreement and 95% confidence intervals were estimated for paired assay combinations. SARS-CoV-2 antibody concentrations were quantified for specimens with at least two positive results across four immunoassays. Among the 24,079 participants, the percent agreement for the Abbott and EI assays was 98.8% (95% confidence interval, 98.7%, 99%). Of the 490 participants who were also tested by Ortho and Roche, the probability-weighted percentage of agreement (95% confidence interval) between Ortho and Roche was 98.4% (97.9%, 98.9%), that between EI and Ortho was 98.5% (92.9%, 99.9%), that between Abbott and Roche was 98.9% (90.3%, 100.0%), that between EI and Roche was 98.9% (98.6%, 100.0%), and that between Abbott and Ortho was 98.4% (91.2%, 100.0%). Among the 32 participants who were positive by at least 2 immunoassays, 21 had quantifiable anti-SARS-CoV-2 antibody concentrations by research assays. The results across immunoassays revealed concordance during a period of low prevalence. However, the frequency of false positivity during a period of low prevalence supports the use of two sequentially performed tests for unvaccinated individuals who are seropositive by the first test. IMPORTANCE What is the agreement of commercial SARS-CoV-2 immunoglobulin G (IgG) assays during a time of low coronavirus disease 2019 (COVID-19) prevalence and no vaccine availability? Serological tests produced concordant results in a time of low SARS-CoV-2 prevalence and no vaccine availability, driven largely by the proportion of samples that were negative by two immunoassays. The CDC recommends two sequential tests for positivity for future pandemic preparedness. In a subset analysis, quantified antinucleocapsid and antispike SARS-CoV-2 IgG antibodies do not suggest the need to specify the antigen targets of the sequential assays in the CDC’s recommendation because false positivity varied as much between assays targeting the same antigen as it did between assays targeting different antigens.

Published
2022
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195. Hypertension prevalence in the All of Us Research Program among groups traditionally underrepresented in medical research

Author

Paulette D. Chandler, Cheryl R. Clark, Guohai Zhou, Nyia L. Noel, Confidence Achilike, Lizette Mendez, Andrea H. Ramirez, Roxana Loperena-Cortes, Kelsey Mayo, Elizabeth Cohn, Lucila Ohno-Machado, Eric Boerwinkle, Mine Cicek, Jun Qian, Sheri Schully, Francis Ratsimbazafy, Stephen Mockrin, Kelly Gebo, Julien J. Dedier, Shawn N. Murphy, Jordan W. Smoller, Elizabeth W. Karlson, and the All of Us Research Program Investigators

Subjects
Medicine, Science
Abstract

Abstract The All of Us Research Program was designed to enable broad-based precision medicine research in a cohort of unprecedented scale and diversity. Hypertension (HTN) is a major public health concern. The validity of HTN data and definition of hypertension cases in the All of Us (AoU) Research Program for use in rule-based algorithms is unknown. In this cross-sectional, population-based study, we compare HTN prevalence in the AoU Research Program to HTN prevalence in the 2015–2016 National Health and Nutrition Examination Survey (NHANES). We used AoU baseline data from patient (age ≥ 18) measurements (PM), surveys, and electronic health record (EHR) blood pressure measurements. We retrospectively examined the prevalence of HTN in the EHR cohort using Systemized Nomenclature of Medicine (SNOMED) codes and blood pressure medications recorded in the EHR. We defined HTN as the participant having at least 2 HTN diagnosis/billing codes on separate dates in the EHR data AND at least one HTN medication. We calculated an age-standardized HTN prevalence according to the age distribution of the U.S. Census, using 3 groups (18–39, 40–59, and ≥ 60). Among the 185,770 participants enrolled in the AoU Cohort (mean age at enrollment = 51.2 years) available in a Researcher Workbench as of October 2019, EHR data was available for at least one SNOMED code from 112,805 participants, medications for 104,230 participants, and 103,490 participants had both medication and SNOMED data. The total number of persons with SNOMED codes on at least two distinct dates and at least one antihypertensive medication was 33,310 for a crude prevalence of HTN of 32.2%. AoU age-adjusted HTN prevalence was 27.9% using 3 groups compared to 29.6% in NHANES. The AoU cohort is a growing source of diverse longitudinal data to study hypertension nationwide and develop precision rule-based algorithms for use in hypertension treatment and prevention research. The prevalence of hypertension in this cohort is similar to that in prior population-based surveys.

Published
2021
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