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1. Causal machine learning for predicting treatment outcomes

Author

Feuerriegel, Stefan, Frauen, Dennis, Melnychuk, Valentyn, Schweisthal, Jonas, Hess, Konstantin, Curth, Alicia, Bauer, Stefan, Kilbertus, Niki, Kohane, Isaac S., and van der Schaar, Mihaela

Subjects
Computer Science - Machine Learning, Statistics - Applications, Statistics - Machine Learning
Abstract

Causal machine learning (ML) offers flexible, data-driven methods for predicting treatment outcomes including efficacy and toxicity, thereby supporting the assessment and safety of drugs. A key benefit of causal ML is that it allows for estimating individualized treatment effects, so that clinical decision-making can be personalized to individual patient profiles. Causal ML can be used in combination with both clinical trial data and real-world data, such as clinical registries and electronic health records, but caution is needed to avoid biased or incorrect predictions. In this Perspective, we discuss the benefits of causal ML (relative to traditional statistical or ML approaches) and outline the key components and steps. Finally, we provide recommendations for the reliable use of causal ML and effective translation into the clinic., Comment: Accepted version; not Version of Record

Published
2024
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2. Systematic Characterization of the Effectiveness of Alignment in Large Language Models for Categorical Decisions

Author

Kohane, Isaac

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

As large language models (LLMs) are deployed in high-stakes domains like healthcare, understanding how well their decision-making aligns with human preferences and values becomes crucial, especially when we recognize that there is no single gold standard for these preferences. This paper applies a systematic methodology for evaluating preference alignment in LLMs on categorical decision-making with medical triage as a domain-specific use case. It also measures how effectively an alignment procedure will change the alignment of a specific model. Key to this methodology is a novel simple measure, the Alignment Compliance Index (ACI), that quantifies how effectively a LLM can be aligned to a given preference function or gold standard. Since the ACI measures the effect rather than the process of alignment, it is applicable to alignment methods beyond the in-context learning used in this study. Using a dataset of simulated patient pairs, three frontier LLMs (GPT4o, Claude 3.5 Sonnet, and Gemini Advanced) were assessed on their ability to make triage decisions consistent with an expert clinician's preferences. The models' performance before and after alignment attempts was evaluated using various prompting strategies. The results reveal significant variability in alignment effectiveness across models and alignment approaches. Notably, models that performed well, as measured by ACI, pre-alignment sometimes degraded post-alignment, and small changes in the target preference function led to large shifts in model rankings. The implicit ethical principles, as understood by humans, underlying the LLMs' decisions were also explored through targeted questioning. This study motivates the use of a practical set of methods and the ACI, in the near term, to understand the correspondence between the variety of human and LLM decision-making values in categorical decision-making such as triage., Comment: 19 pages (without Appendix) Appendix 7 pages. 7 Figures

Published
2024

3. Implications of mappings between ICD clinical diagnosis codes and Human Phenotype Ontology terms

Author

Tan, Amelia LM, Gonçalves, Rafael S, Yuan, William, Brat, Gabriel A, EHR, The Consortium for Clinical Characterization of COVID-19 by, Gentleman, Robert, and Kohane, Isaac S

Subjects
Computer Science - Databases
Abstract

Objective: Integrating EHR data with other resources is essential in rare disease research due to low disease prevalence. Such integration is dependent on the alignment of ontologies used for data annotation. The International Classification of Diseases (ICD) is used to annotate clinical diagnoses; the Human Phenotype Ontology (HPO) to annotate phenotypes. Although these ontologies overlap in biomedical entities described, the extent to which they are interoperable is unknown. We investigate how well aligned these ontologies are and whether such alignments facilitate EHR data integration. Materials and Methods: We conducted an empirical analysis of the coverage of mappings between ICD and HPO. We interpret this mapping coverage as a proxy for how easily clinical data can be integrated with research ontologies such as HPO. We quantify how exhaustively ICD codes are mapped to HPO by analyzing mappings in the UMLS Metathesaurus. We analyze the proportion of ICD codes mapped to HPO within a real-world EHR dataset. Results and Discussion: Our analysis revealed that only 2.2% of ICD codes have direct mappings to HPO in UMLS. Within our EHR dataset, less than 50% of ICD codes have mappings to HPO terms. ICD codes that are used frequently in EHR data tend to have mappings to HPO; ICD codes that represent rarer medical conditions are seldom mapped. Conclusion: We find that interoperability between ICD and HPO via UMLS is limited. While other mapping sources could be incorporated, there are no established conventions for what resources should be used to complement UMLS.

Published
2024

6. Geoinference of author affiliations using NLP-based text classification

Author

Brian Lee, John S. Brownstein, and Isaac S. Kohane

Subjects
Medicine, Science
Abstract

Abstract Author affiliations are essential in bibliometric studies, requiring relevant information extraction from free-text affiliations. Precisely determining an author’s location from their affiliation is crucial for understanding research networks, collaborations, and geographic distribution. Existing geoparsing tools using regular expressions have limitations due to unstructured and ambiguous affiliations, resulting in erroneous location identification, especially for unconventional variations or misspellings. Moreover, their inefficient handling of big datasets hampers large-scale bibliometric studies. Though machine learning-based geoparsers exist, they depend on explicit location information, creating challenges when detailed geographic data is absent. To address these issues, we developed and evaluated a natural language processing model to predict the city, state, and country from an author’s free-text affiliation. Our model automates location inference, overcoming drawbacks of existing methods. Trained and tested with MapAffil, a publicly available geoparsed dataset of PubMed affiliations up to 2018, our model accurately retrieves high-resolution locations, even without explicit mentions of a city, state, or even country. Leveraging NLP techniques and the LinearSVC algorithm, our machine learning model achieves superior accuracy based on several validation datasets. This research demonstrates a practical application of text classification for inferring specific geographical locations from free-text affiliations, benefiting researchers and institutions in analyzing research output distribution.

Published
2024
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7. Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Events

Author

McDermott, Matthew B. A., Nestor, Bret, Argaw, Peniel, and Kohane, Isaac

Subjects
Computer Science - Machine Learning
Abstract

Generative, pre-trained transformers (GPTs, a.k.a. "Foundation Models") have reshaped natural language processing (NLP) through their versatility in diverse downstream tasks. However, their potential extends far beyond NLP. This paper provides a software utility to help realize this potential, extending the applicability of GPTs to continuous-time sequences of complex events with internal dependencies, such as medical record datasets. Despite their potential, the adoption of foundation models in these domains has been hampered by the lack of suitable tools for model construction and evaluation. To bridge this gap, we introduce Event Stream GPT (ESGPT), an open-source library designed to streamline the end-to-end process for building GPTs for continuous-time event sequences. ESGPT allows users to (1) build flexible, foundation-model scale input datasets by specifying only a minimal configuration file, (2) leverage a Hugging Face compatible modeling API for GPTs over this modality that incorporates intra-event causal dependency structures and autoregressive generation capabilities, and (3) evaluate models via standardized processes that can assess few and even zero-shot performance of pre-trained models on user-specified fine-tuning tasks.

Published
2023

8. Construction of extra-large scale screening tools for risks of severe mental illnesses using real world healthcare data

Author

Liu, Dianbo, Choi, Karmel W., Lizano, Paulo, Yuan, William, Yu, Kun-Hsing, Smoller, Jordan W., and Kohane, Isaac

Subjects
Computer Science - Artificial Intelligence, Quantitative Biology - Quantitative Methods
Abstract

Importance: The prevalence of severe mental illnesses (SMIs) in the United States is approximately 3% of the whole population. The ability to conduct risk screening of SMIs at large scale could inform early prevention and treatment. Objective: A scalable machine learning based tool was developed to conduct population-level risk screening for SMIs, including schizophrenia, schizoaffective disorders, psychosis, and bipolar disorders,using 1) healthcare insurance claims and 2) electronic health records (EHRs). Design, setting and participants: Data from beneficiaries from a nationwide commercial healthcare insurer with 77.4 million members and data from patients from EHRs from eight academic hospitals based in the U.S. were used. First, the predictive models were constructed and tested using data in case-control cohorts from insurance claims or EHR data. Second, performance of the predictive models across data sources were analyzed. Third, as an illustrative application, the models were further trained to predict risks of SMIs among 18-year old young adults and individuals with substance associated conditions. Main outcomes and measures: Machine learning-based predictive models for SMIs in the general population were built based on insurance claims and EHR.

Published
2022

9. Identifying Heterogeneous Treatment Effects in Multiple Outcomes using Joint Confidence Intervals

Author

Argaw, Peniel N., Healey, Elizabeth, and Kohane, Isaac S.

Subjects
Computer Science - Machine Learning
Abstract

Heterogeneous treatment effects (HTEs) are commonly identified during randomized controlled trials (RCTs). Identifying subgroups of patients with similar treatment effects is of high interest in clinical research to advance precision medicine. Often, multiple clinical outcomes are measured during an RCT, each having a potentially heterogeneous effect. Recently there has been high interest in identifying subgroups from HTEs, however, there has been less focus on developing tools in settings where there are multiple outcomes. In this work, we propose a framework for partitioning the covariate space to identify subgroups across multiple outcomes based on the joint CIs. We test our algorithm on synthetic and semi-synthetic data where there are two outcomes, and demonstrate that our algorithm is able to capture the HTE in both outcomes simultaneously., Comment: Accepted to ML4H 2022. Available at https://proceedings.mlr.press/v193/argaw22a.html

Published
2022

10. To do no harm — and the most good — with AI in health care

Author

Goldberg, Carey Beth, Adams, Laura, Blumenthal, David, Brennan, Patricia Flatley, Brown, Noah, Butte, Atul J., Cheatham, Morgan, deBronkart, Dave, Dixon, Jennifer, Drazen, Jeffrey, Evans, Barbara J., Hoffman, Sara M., Holmes, Chris, Lee, Peter, Manrai, Arjun Kumar, Omenn, Gilbert S., Perlin, Jonathan B., Ramoni, Rachel, Sapiro, Guillermo, Sarkar, Rupa, Sood, Harpreet, Vayena, Effy, and Kohane, Isaac S.

Published
2024
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11. Polygenic risk scores for autoimmune related diseases are significantly different in cancer exceptional responders

Author

Siyuan Chen, Amelia L. M. Tan, Maria C. Saad Menezes, Jenny F. Mao, Cassandra L. Perry, Margaret E. Vella, Vinayak V. Viswanadham, Shilpa Kobren, Susanne Churchill, and Isaac S. Kohane

Subjects
Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Abstract A small number of cancer patients respond exceptionally well to therapies and survive significantly longer than patients with similar diagnoses. Profiling the germline genetic backgrounds of exceptional responder (ER) patients, with extreme survival times, can yield insights into the germline polymorphisms that influence response to therapy. As ERs showed a high incidence in autoimmune diseases, we hypothesized the differences in autoimmune disease risk could reflect the immune background of ERs and contribute to better cancer treatment responses. We analyzed the germline variants of 51 ERs using polygenic risk score (PRS) analysis. Compared to typical cancer patients, the ERs had significantly elevated PRSs for several autoimmune-related diseases: type 1 diabetes, hypothyroidism, and psoriasis. This indicates that an increased genetic predisposition towards these autoimmune diseases is more prevalent among the ERs. In contrast, ERs had significantly lower PRSs for developing inflammatory bowel disease. The left-skew of type 1 diabetes score was significant for exceptional responders. Variants on genes involved in the T1D PRS model associated with cancer drug response are more likely to co-occur with other variants among ERs. In conclusion, ERs exhibited different risks for autoimmune diseases compared to typical cancer patients, which suggests that changes in a patient’s immune set point or immune surveillance specificity could be a potential mechanistic link to their exceptional response. These findings expand upon previous research on immune checkpoint inhibitor-treated patients to include those who received chemotherapy or radiotherapy.

Published
2024
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12. Acute respiratory distress syndrome after SARS-CoV-2 infection on young adult population: International observational federated study based on electronic health records through the 4CE consortium

Author

Moal, Bertrand, Orieux, Arthur, Ferté, Thomas, Neuraz, Antoine, Brat, Gabriel A, Avillach, Paul, Bonzel, Clara-Lea, Cai, Tianxi, Cho, Kelly, Cossin, Sébastien, Griffier, Romain, Hanauer, David A, Haverkamp, Christian, Ho, Yuk-Lam, Hong, Chuan, Hutch, Meghan R, Klann, Jeffrey G, Le, Trang T, Loh, Ne Hooi Will, Luo, Yuan, Makoudjou, Adeline, Morris, Michele, Mowery, Danielle L, Olson, Karen L, Patel, Lav P, Samayamuthu, Malarkodi J, Vidorreta, Fernando J Sanz, Schriver, Emily R, Schubert, Petra, Verdy, Guillaume, Visweswaran, Shyam, Wang, Xuan, Weber, Griffin M, Xia, Zongqi, Yuan, William, Zhang, Harrison G, Zöller, Daniela, Kohane, Isaac S, EHR, The Consortium for Clinical Characterization of COVID-19 by, Boyer, Alexandre, and Jouhet, Vianney

Subjects
Health Services and Systems, Biomedical and Clinical Sciences, Health Sciences, Infectious Diseases, Acute Respiratory Distress Syndrome, Rare Diseases, Lung, Clinical Research, Emerging Infectious Diseases, Prevention, Patient Safety, Aetiology, 2.4 Surveillance and distribution, Good Health and Well Being, Humans, Young Adult, Aged, Adolescent, Adult, Middle Aged, COVID-19, SARS-CoV-2, Cohort Studies, Retrospective Studies, Electronic Health Records, Respiratory Distress Syndrome, Obesity, Consortium for Clinical Characterization of COVID-19 by EHR, General Science & Technology
Abstract

PurposeIn young adults (18 to 49 years old), investigation of the acute respiratory distress syndrome (ARDS) after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been limited. We evaluated the risk factors and outcomes of ARDS following infection with SARS-CoV-2 in a young adult population.MethodsA retrospective cohort study was conducted between January 1st, 2020 and February 28th, 2021 using patient-level electronic health records (EHR), across 241 United States hospitals and 43 European hospitals participating in the Consortium for Clinical Characterization of COVID-19 by EHR (4CE). To identify the risk factors associated with ARDS, we compared young patients with and without ARDS through a federated analysis. We further compared the outcomes between young and old patients with ARDS.ResultsAmong the 75,377 hospitalized patients with positive SARS-CoV-2 PCR, 1001 young adults presented with ARDS (7.8% of young hospitalized adults). Their mortality rate at 90 days was 16.2% and they presented with a similar complication rate for infection than older adults with ARDS. Peptic ulcer disease, paralysis, obesity, congestive heart failure, valvular disease, diabetes, chronic pulmonary disease and liver disease were associated with a higher risk of ARDS. We described a high prevalence of obesity (53%), hypertension (38%- although not significantly associated with ARDS), and diabetes (32%).ConclusionTrough an innovative method, a large international cohort study of young adults developing ARDS after SARS-CoV-2 infection has been gather. It demonstrated the poor outcomes of this population and associated risk factor.

Published
2023

13. WINDOW OPENING STATUTES: Child Victims Act Claims and the Quest for Lost Policies

Author

Burns, Timothy W. and Kohane, Dan D.

Subjects
Aero-Motive Co. -- Laws, regulations and rules, Aetna Inc. -- Laws, regulations and rules, Machinery industry -- Laws, regulations and rules, Insurance industry -- Laws, regulations and rules, Child sexual abuse -- Laws, regulations and rules, Government regulation, Insurance industry, Law, New York. Child Victims Act
Abstract

In recent years, there has been a wave of states reforming their statutes of limitations for civil actions based upon child sexual abuse. For instance, New York passed the Child [...]

Published
2024

14. Cohort Expansion and Genotype-Phenotype Analysis of RAB11A-Associated Neurodevelopmental Disorder

Author

Acosta, Maria T., Adam, Margaret, Adams, David R., Alvarez, Raquel L., Alvey, Justin, Amendola, Laura, Andrews, Ashley, Ashley, Euan A., Bacino, Carlos A., Bademci, Guney, Balasubramanyam, Ashok, Baldridge, Dustin, Bale, Jim, Bamshad, Michael, Barbouth, Deborah, Bayrak-Toydemir, Pinar, Beck, Anita, Beggs, Alan H., Behrens, Edward, Bejerano, Gill, Bellen, Hugo J., Bennett, Jimmy, Berg-Rood, Beverly, Bernstein, Jonathan A., Berry, Gerard T., Bican, Anna, Bivona, Stephanie, Blue, Elizabeth, Bohnsack, John, Bonner, Devon, Botto, Lorenzo, Boyd, Brenna, Briere, Lauren C., Brokamp, Elly, Brown, Gabrielle, Burke, Elizabeth A., Burrage, Lindsay C., Butte, Manish J., Byers, Peter, Byrd, William E., Carey, John, Carrasquillo, Olveen, Cassini, Thomas, Peter Chang, Ta Chen, Chanprasert, Sirisak, Chao, Hsiao-Tuan, Clark, Gary D., Coakley, Terra R., Cobban, Laurel A., Cogan, Joy D., Coggins, Matthew, Cole, F. Sessions, Colley, Heather A., Cooper, Cynthia M., Cope, Heidi, Corona, Rosario, Craigen, William J., Crouse, Andrew B., Cunningham, Michael, D'Souza, Precilla, Dai, Hongzheng, Dasari, Surendra, Davis, Joie, Dayal, Jyoti G., Dell'Angelica, Esteban C., Dipple, Katrina, Doherty, Daniel, Dorrani, Naghmeh, Doss, Argenia L., Douine, Emilie D., Duncan, Laura, Earl, Dawn, Eckstein, David J., Emrick, Lisa T., Eng, Christine M., Falk, Marni, Fieg, Elizabeth L., Fisher, Paul G., Fogel, Brent L., Forghani, Irman, Gahl, William A., Glass, Ian, Gochuico, Bernadette, Goddard, Page C., Godfrey, Rena A., Golden-Grant, Katie, Grajewski, Alana, Hadley, Don, Hahn, Sihoun, Halley, Meghan C., Hamid, Rizwan, Hassey, Kelly, Hayes, Nichole, High, Frances, Hing, Anne, Hisama, Fuki M., Holm, Ingrid A., Hom, Jason, Horike-Pyne, Martha, Huang, Alden, Hutchison, Sarah, Introne, Wendy, Isasi, Rosario, Izumi, Kosuke, Jamal, Fariha, Jarvik, Gail P., Jarvik, Jeffrey, Jayadev, Suman, Jean-Marie, Orpa, Jobanputra, Vaidehi, Karaviti, Lefkothea, Kennedy, Jennifer, Ketkar, Shamika, Kiley, Dana, Kilich, Gonench, Kobren, Shilpa N., Kohane, Isaac S., Kohler, Jennefer N., Korrick, Susan, Kozuira, Mary, Krakow, Deborah, Krasnewich, Donna M., Kravets, Elijah, Lalani, Seema R., Lam, Byron, Lam, Christina, Lanpher, Brendan C., Lanza, Ian R., LeBlanc, Kimberly, Lee, Brendan H., Levitt, Roy, Lewis, Richard A., Liu, Pengfei, Liu, Xue Zhong, Longo, Nicola, Loo, Sandra K., Loscalzo, Joseph, Maas, Richard L., Macnamara, Ellen F., MacRae, Calum A., Maduro, Valerie V., Maghiro, AudreyStephannie, Mahoney, Rachel, Malicdan, May Christine V., Mamounas, Laura A., Manolio, Teri A., Mao, Rong, Maravilla, Kenneth, Marom, Ronit, Marth, Gabor, Martin, Beth A., Martin, Martin G., Martínez-Agosto, Julian A., Marwaha, Shruti, McCauley, Jacob, McConkie-Rosell, Allyn, McCray, Alexa T., McGee, Elisabeth, Mefford, Heather, Merritt, J. Lawrence, Might, Matthew, Mirzaa, Ghayda, Morava, Eva, Moretti, Paolo, Mulvihill, John, Nakano-Okuno, Mariko, Nelson, Stanley F., Newman, John H., Nicholas, Sarah K., Nickerson, Deborah, Nieves-Rodriguez, Shirley, Novacic, Donna, Oglesbee, Devin, Orengo, James P., Pace, Laura, Pak, Stephen, Pallais, J. Carl, Palmer, Christina G.S., Papp, Jeanette C., Parker, Neil H., Phillips, John A., III, Posey, Jennifer E., Potocki, Lorraine, Pusey Swerdzewski, Barbara N., Quinlan, Aaron, Rao, Deepak A., Raper, Anna, Raskind, Wendy, Renteria, Genecee, Reuter, Chloe M., Rives, Lynette, Robertson, Amy K., Rodan, Lance H., Rosenfeld, Jill A., Rosenwasser, Natalie, Rossignol, Francis, Ruzhnikov, Maura, Sacco, Ralph, Sampson, Jacinda B., Saporta, Mario, Schaechter, Judy, Schedl, Timothy, Schoch, Kelly, Scott, Daryl A., Scott, C. Ron, Shashi, Vandana, Shin, Jimann, Silverman, Edwin K., Sinsheimer, Janet S., Sisco, Kathy, Smith, Edward C., Smith, Kevin S., Solem, Emily, Solnica-Krezel, Lilianna, Solomon, Ben, Spillmann, Rebecca C., Stoler, Joan M., Sullivan, Kathleen, Sullivan, Jennifer A., Sun, Angela, Sutton, Shirley, Sweetser, David A., Sybert, Virginia, Tabor, Holly K., Tan, Queenie K.-G., Tan, Amelia L.M., Tekin, Mustafa, Telischi, Fred, Thorson, Willa, Tifft, Cynthia J., Toro, Camilo, Tran, Alyssa A., Ungar, Rachel A., Urv, Tiina K., Vanderver, Adeline, Velinder, Matt, Viskochil, Dave, Vogel, Tiphanie P., Wahl, Colleen E., Walker, Melissa, Wallace, Stephanie, Walley, Nicole M., Wambach, Jennifer, Wan, Jijun, Wang, Lee-kai, Wangler, Michael F., Ward, Patricia A., Wegner, Daniel, Hubshman, Monika Weisz, Wener, Mark, Wenger, Tara, Westerfield, Monte, Wheeler, Matthew T., Whitlock, Jordan, Wolfe, Lynne A., Worley, Kim, Xiao, Changrui, Yamamoto, Shinya, Yang, John, Zhang, Zhe, Zuchner, Stephan, Borroto, Maria Carla, Patel, Heena, Srivastava, Siddharth, Swanson, Lindsay C., Keren, Boris, Whalen, Sandra, Mignot, Cyril, Wang, Xiaodong, Chen, Qian, McLean, Scott, Littlejohn, Rebecca O., Emrick, Lisa, Attali, Ruben, Lesca, Gaetan, Acquaviva-Bourdain, Cecile, Sarret, Catherine, Seaver, Laurie H., Platzer, Konrad, Bartolomaeus, Tobias, Wünsch, Cornelia, Fischer, Susann, Rodriguez Barreto, Ana Maria, Granadillo, Jorge L., Schreiner, Elisabeth, Brunet, Theresa, Schatz, Ulrich A., Thiffault, Isabelle, Mullegama, Sureni V., Michaud, Jacques L., Hamdan, Fadi F., Rossignol, Elsa, and Campeau, Philippe M.

Published
2024
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15. Loss-of-function in RBBP5 results in a syndromic neurodevelopmental disorder associated with microcephaly

Author

Acosta, Maria T., Adams, David R., Raquel, Alvarez, L., Alvey, Justin, Allworth, Aimee, Andrews, Ashley, Ashley, Euan A., Bacino, Carlos A., Bademci, Guney, Balasubramanyam, Ashok, Baldridge, Dustin, Bale, Jim, Bamshad, Michael, Barbouth, Deborah, Bayrak-Toydemir, Pinar, Beck, Anita, Beggs, Alan H., Behrens, Edward, Bejerano, Gill, Bellen, Hugo J., Bennett, Jimmy, Bernstein, Jonathan A., Berry, Gerard T., Bican, Anna, Bivona, Stephanie, Blue, Elizabeth, Bohnsack, John, Bonner, Devon, Botto, Lorenzo, Briere, Lauren C., Brown, Gabrielle, Burke, Elizabeth A., Burrage, Lindsay C., Butte, Manish J., Byers, Peter, Byrd, William E., Carey, John, Carrasquillo, Olveen, Carvhalo Neto, George D., Cassini, Thomas, Peter Chang, Ta Chen, Chanprasert, Sirisak, Chao, Hsiao-Tuan, Chinn, Ivan, Clark, Gary D., Coakley, Terra R., Cobban, Laurel A., Cogan, Joy D., Coggins, Matthew, Cole, F. Sessions, Colley, Heather A., Cope, Heidi, Corona, Rosario, Craigen, William J., Crouse, Andrew B., Cunningham, Michael, D’Souza, Precilla, Dai, Hongzheng, Dasari, Surendra, Davis, Joie, Dayal, Jyoti G., Dell'Angelica, Esteban C., Dipple, Katrina, Doherty, Daniel, Dorrani, Naghmeh, Doss, Argenia L., Douine, Emilie D., Earl, Dawn, Eckstein, David J., Emrick, Lisa T., Eng, Christine M., Falk, Marni, Fieg, Elizabeth L., Fisher, Paul G., Fogel, Brent L., Forghani, Irman, Gahl, William A., Glass, Ian, Gochuico, Bernadette, Goddard, Page C., Godfrey, Rena A., Grajewski, Alana, Hadley, Don, Halley, Meghan C., Hamid, Rizwan, Hassey, Kelly, Hayes, Nichole, High, Frances, Hing, Anne, Hisama, Fuki M., Holm, Ingrid A., Hom, Jason, Horike-Pyne, Martha, Huang, Alden, Hutchison, Sarah, Introne, Wendy, Isasi, Rosario, Izumi, Kosuke, Jarvik, Gail P., Jarvik, Jeffrey, Jayadev, Suman, Jean-Marie, Orpa, Jobanputra, Vaidehi, Kaitryn, Emerald, Ketkar, Shamika, Kiley, Dana, Kilich, Gonench, Kobren, Shilpa N., Kohane, Isaac S., Kohler, Jennefer N., Korrick, Susan, Krakow, Deborah, Krasnewich, Donna M., Kravets, Elijah, Lalani, Seema R., Lam, Byron, Lam, Christina, Lanpher, Brendan C., Lanza, Ian R., LeBlanc, Kimberly, Lee, Brendan H., Levitt, Roy, Lewis, Richard A., Liu, Pengfei, Liu, Xue Zhong, Longo, Nicola, Loo, Sandra K., Loscalzo, Joseph, Maas, Richard L., Macnamara, Ellen F., MacRae, Calum A., Maduro, Valerie V., Maghiro, Audrey Stephannie, Mahoney, Rachel, Malicdan, May Christine V., Mamounas, Laura A., Manolio, Teri A., Mao, Rong, Marom, Ronit, Marth, Gabor, Martin, Beth A., Martin, Martin G., Martínez-Agosto, Julian A., Marwaha, Shruti, McCauley, Jacob, McConkie-Rosell, Allyn, McCray, Alexa T., McGee, Elisabeth, Might, Matthew, Miller, Danny, Mirzaa, Ghayda, Moore, Ryan M., Morava, Eva, Moretti, Paolo, Mulvihill, John J., Nakano-Okuno, Mariko, Nelson, Stanley F., Nieves-Rodriguez, Shirley, Novacic, Donna, Oglesbee, Devin, Orengo, James P., Pace, Laura, Pak, Stephen, Pallais, J. Carl, Palmer, Christina G.S., Papp, Jeanette C., Parker, Neil H., Phillips, John A., III, Posey, Jennifer E., Potocki, Lorraine, Pusey Swerdzewski, Barbara N., Quinlan, Aaron, Rao, Deepak A., Raper, Anna, Raskind, Wendy, Renteria, Genecee, Reuter, Chloe M., Rives, Lynette, Robertson, Amy K., Rodan, Lance H., Rosenfeld, Jill A., Rosenthal, Elizabeth, Rossignol, Francis, Ruzhnikov, Maura, Sacco, Ralph, Sampson, Jacinda B., Saporta, Mario, Schaechter, Judy, Schedl, Timothy, Schoch, Kelly, Scott, Daryl A., Seto, Elaine, Shashi, Vandana, Shelkowitz, Emily, Sheppeard, Sam, Shin, Jimann, Silverman, Edwin K., Sinsheimer, Janet S., Sisco, Kathy, Smith, Edward C., Smith, Kevin S., Solnica-Krezel, Lilianna, Solomon, Ben, Spillmann, Rebecca C., Stergachis, Andrew, Stoler, Joan M., Sullivan, Kathleen, Sullivan, Jennifer A., Sutton, Shirley, Sweetser, David A., Sybert, Virginia, Tabor, Holly K., Tan, Queenie K.-G., Tan, Amelia L.M., Tarakad, Arjun, Tekin, Mustafa, Telischi, Fred, Thorson, Willa, Tifft, Cynthia J., Toro, Camilo, Tran, Alyssa A., Ungar, Rachel A., Urv, Tiina K., Vanderver, Adeline, Velinder, Matt, Viskochil, Dave, Vogel, Tiphanie P., Wahl, Colleen E., Walker, Melissa, Walley, Nicole M., Wambach, Jennifer, Wan, Jijun, Wang, Lee-kai, Wangler, Michael F., Ward, Patricia A., Wegner, Daniel, Hubshman, Monika Weisz, Wener, Mark, Wenger, Tara, Westerfield, Monte, Wheeler, Matthew T., Whitlock, Jordan, Wolfe, Lynne A., Worley, Kim, Xiao, Changrui, Yamamoto, Shinya, Yang, John, Zhang, Zhe, Zuchner, Stephan, Huang, Yue, Jay, Kristy L., Yen-Wen Huang, Alden, Jangam, Sharayu V., Chorin, Odelia, Rothschild, Annick, Barel, Ortal, Mariani, Milena, Iascone, Maria, Xue, Han, Huang, Jing, Mignot, Cyril, Keren, Boris, Saillour, Virginie, Mah-Som, Annelise Y., Sacharow, Stephanie, Rajabi, Farrah, Costin, Carrie, Kanca, Oguz, and Martinez-Agosto, Julian A.

Published
2024
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16. The Undiagnosed Diseases Network: Characteristics of solvable applicants and diagnostic suggestions for nonaccepted ones

Author

Acosta, Maria T., Adams, David R., Afzali, Ben, Al-Beshri, Ali, Allworth, Aimee, Alvarez, Raquel L., Alvey, Justin, Andrews, Ashley, Ashley, Euan A., Bacino, Carlos A., Bademci, Guney, Balasubramanyam, Ashok, Baldridge, Dustin, Bale, Jim, Bamshad, Michael, Barbouth, Deborah, Bayrak-Toydemir, Pinar, Beck, Anita, Beggs, Alan H., Behrens, Edward, Bejerano, Gill, Bellen, Hugo J., Bennett, Jimmy, Bernstein, Jonathan A., Berry, Gerard T., Bican, Anna, Bivona, Stephanie, Blue, Elizabeth, Bohnsack, John, Bonner, Devon, Borja, Nicholas, Botto, Lorenzo, Briere, Lauren C., Burke, Elizabeth A., Burrage, Lindsay C., Butte, Manish J., Byers, Peter, Byrd, William E., Callaway, Kaitlin, Carey, John, Carvalho, George, Cassini, Thomas, Chanprasert, Sirisak, Chao, Hsiao-Tuan, Chinn, Ivan, Clark, Gary D., Coakley, Terra R., Cobban, Laurel A., Cogan, Joy D., Coggins, Matthew, Cole, F. Sessions, Corner, Brian, Corona, Rosario I., Craigen, William J., Crouse, Andrew B., Cuddapah, Vishnu, Cunningham, Michael, D’Souza, Precilla, Dai, Hongzheng, Dasari, Surendra, Davis, Joie, Delgado, Margaret, Dell’Angelica, Esteban C., Dipple, Katrina, Doherty, Daniel, Dorrani, Naghmeh, Douglas, Jessica, Douine, Emilie D., Earl, Dawn, Emrick, Lisa T., Eng, Christine M., Ezell, Kimberly, Fieg, Elizabeth L., Fisher, Paul G., Fogel, Brent L., Fu, Jiayu, Gahl, William A., Ganetzky, Rebecca, Glanton, Emily, Glass, Ian, Goddard, Page C., Gonzalez, Joanna M., Gropman, Andrea, Halley, Meghan C., Hamid, Rizwan, Hanchard, Neal, Hassey, Kelly, Hayes, Nichole, High, Frances, Hing, Anne, Hisama, Fuki M., Holm, Ingrid A., Hom, Jason, Horike-Pyne, Martha, Huang, Alden, Huang, Yan, Hurst, Anna, Introne, Wendy, Jarvik, Gail P., Jarvik, Jeffrey, Jayadev, Suman, Marie, Orpa Jean, Jobanputra, Vaidehi, Kaitryn, Emerald, Kanca, Oguz, Karasozen, Yigit, Ketkar, Shamika, Kiley, Dana, Kilich, Gonench, Kobren, Shilpa N., Kohane, Isaac S., Kohler, Jennefer N., Korf, Bruce, Korrick, Susan, Krakow, Deborah, Kravets, Elijah, Lalani, Seema R., Lam, Christina, Lanpher, Brendan C., Lanza, Ian R., Latchman, Kumarie, LeBlanc, Kimberly, Lee, Brendan H., Lewis, Richard A., Liu, Pengfei, Longo, Nicola, Loscalzo, Joseph, Maas, Richard L., Macnamara, Ellen F., MacRae, Calum A., Maduro, Valerie V., Maghiro, Audrey Stephannie, Mahoney, Rachel, Malicdan, May Christine V., Mao, Rong, Marom, Ronit, Marth, Gabor, Martin, Beth A., Martin, Martin G., Martínez-Agosto, Julian A., Marwaha, Shruti, McConkie-Rosell, Allyn, McCray, Alexa T., Might, Matthew, Mikati, Mohamad, Miller, Danny, Mirzaa, Ghayda, Morava, Eva, Moretti, Paolo, Morimoto, Marie, Mulvihill, John J., Nakano-Okuno, Mariko, Nelson, Stanley F., Neumann, Serena, Novacic, Donna, Oglesbee, Devin, Orengo, James P., Pace, Laura, Pak, Stephen, Pallais, J. Carl, Parker, Neil H., Peart, LéShon, Petcharet, Leoyklang, Phillips, John A., III, Posey, Jennifer E., Potocki, Lorraine, Pusey Swerdzewski, Barbara N., Quinlan, Aaron, Rajagopalan, Ramakrishnan, Rao, Deepak A., Raper, Anna, Raskind, Wendy, Rebelo, Adriana, Reuter, Chloe M., Rives, Lynette, Robertson, Amy K., Rodan, Lance H., Rodriguez, Martin, Rosenfeld, Jill A., Rosenthal, Elizabeth, Rossignol, Francis, Ruzhnikov, Maura, Sabaii, Marla, Sampson, Jacinda B., Schedl, Timothy, Schoch, Kelly, Scott, Daryl A., Seto, Elaine, Shashi, Vandana, Shelkowitz, Emily, Sheppeard, Sam, Shin, Jimann, Silverman, Edwin K., Sisco, Kathy, Skelton, Tammi, Skraban, Cara, Smith, Carson A., Smith, Kevin S., Solnica-Krezel, Lilianna, Solomon, Ben, Spillmann, Rebecca C., Stergachis, Andrew, Stoler, Joan M., Sullivan, Kathleen, Sutton, Shirley, Sweetser, David A., Sybert, Virginia, Tabor, Holly K., Tan, Queenie K.-G., Tan, Amelia L.M., Tarakad, Arjun, Taylor, Herman, Tekin, Mustafa, Thorson, Willa, Tifft, Cynthia J., Toro, Camilo, Tran, Alyssa A., Ungar, Rachel A., Vanderver, Adeline, Velinder, Matt, Viskochil, Dave, Vogel, Tiphanie P., Wahl, Colleen E., Walker, Melissa, Walley, Nicole M., Wambach, Jennifer, Wangler, Michael F., Ward, Patricia A., Wegner, Daniel, Hubshman, Monika Weisz, Wener, Mark, Wenger, Tara, Westerfield, Monte, Wheeler, Matthew T., Whitlock, Jordan, Wolfe, Lynne A., Wood, Heidi, Worley, Kim, Yamamoto, Shinya, Zhang, Zhe, Zuchner, Stephan, Findley, Laura, Ni, Weihong, Sinsheimer, Janet S., Cole, F. Session, Esteves, Cecilia, Newman, John H., and Mokry, Jill R.

Published
2024
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17. Disease progression strikingly differs in research and real-world Parkinson’s populations

Author

Brett K. Beaulieu-Jones, Francesca Frau, Sylvie Bozzi, Karen J. Chandross, M. Judith Peterschmitt, Caroline Cohen, Catherine Coulovrat, Dinesh Kumar, Mark J. Kruger, Scott L. Lipnick, Lane Fitzsimmons, Isaac S. Kohane, and Clemens R. Scherzer

Subjects
Neurology. Diseases of the nervous system, RC346-429
Abstract

Abstract Characterization of Parkinson’s disease (PD) progression using real-world evidence could guide clinical trial design and identify subpopulations. Efforts to curate research populations, the increasing availability of real-world data, and advances in natural language processing, particularly large language models, allow for a more granular comparison of populations than previously possible. This study includes two research populations and two real-world data-derived (RWD) populations. The research populations are the Harvard Biomarkers Study (HBS, N = 935), a longitudinal biomarkers cohort study with in-person structured study visits; and Fox Insights (N = 36,660), an online self-survey-based research study of the Michael J. Fox Foundation. Real-world cohorts are the Optum Integrated Claims-electronic health records (N = 157,475), representing wide-scale linked medical and claims data and de-identified data from Mass General Brigham (MGB, N = 22,949), an academic hospital system. Structured, de-identified electronic health records data at MGB are supplemented using a manually validated natural language processing with a large language model to extract measurements of PD progression. Motor and cognitive progression scores change more rapidly in MGB than HBS (median survival until H&Y 3: 5.6 years vs. >10, p

Published
2024
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19. The literacy barrier in clinical trial consents: a retrospective analysis

Author

Mirza, Fatima N., Wu, Eric, Abdulrazeq, Hael F., Connolly, Ian D., Tang, Oliver Y., Zogg, Cheryl K., Williamson, Theresa, Galamaga, Paul F., Roye, G. Dean, Sampath, Prakash, Telfeian, Albert E., Qureshi, Abrar A., Groff, Michael W., Shin, John H., Asaad, Wael F., Libby, Tiffany J., Gokaslan, Ziya L., Kohane, Isaac S., Zou, James, and Ali, Rohaid

Published
2024
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20. Dominant missense variants in SREBF2 are associated with complex dermatological, neurological, and skeletal abnormalities

Author

Bacino, Carlos A., Balasubramanyam, Ashok, Burrage, Lindsay C., Chao, Hsiao-Tuan, Chinn, Ivan, Clark, Gary D., Craigen, William J., Dai, Hongzheng, Emrick, Lisa T., Ketkar, Shamika, Lalani, Seema R., Lee, Brendan H., Lewis, Richard A., Marom, Ronit, Orengo, James P., Posey, Jennifer E., Potocki, Lorraine, Rosenfeld, Jill A., Seto, Elaine, Scott, Daryl A., Tarakad, Arjun, Tran, Alyssa A., Vogel, Tiphanie P., Hubshman, Monika Weisz, Worley, Kim, Bellen, Hugo J., Wangler, Michael F., Yamamoto, Shinya, Kanca, Oguz, Eng, Christine M., Liu, Pengfei, Ward, Patricia A., Behrens, Edward, Falk, Marni, Hassey, Kelly, Izumi, Kosuke, Kilich, Gonench, Sullivan, Kathleen, Vanderver, Adeline, Zhang, Zhe, Raper, Anna, Jobanputra, Vaidehi, Mikati, Mohamad, McConkie-Rosell, Allyn, Schoch, Kelly, Shashi, Vandana, Spillmann, Rebecca C., Tan, Queenie K.-G., Walley, Nicole M., Beggs, Alan H., Berry, Gerard T., Briere, Lauren C., Cobban, Laurel A., Coggins, Matthew, Fieg, Elizabeth L., High, Frances, Holm, Ingrid A., Korrick, Susan, Loscalzo, Joseph, Maas, Richard L., MacRae, Calum A., Pallais, J. Carl, Rao, Deepak A., Rodan, Lance H., Silverman, Edwin K., Stoler, Joan M., Sweetser, David A., Walker, Melissa, Douglas, Jessica, Glanton, Emily, Kobren, Shilpa N., Kohane, Isaac S., LeBlanc, Kimberly, Maghiro, Audrey Stephannie C., Mahoney, Rachel, McCray, Alexa T., Tan, Amelia L.M., Dasari, Surendra, Lanpher, Brendan C., Lanza, Ian R., Morava, Eva, Oglesbee, Devin, Bademci, Guney, Barbouth, Deborah, Bivona, Stephanie, Borja, Nicholas, Gonzalez, Joanna M., Latchman, Kumarie, Peart, LéShon, Rebelo, Adriana, Smith, Carson A., Tekin, Mustafa, Thorson, Willa, Zuchner, Stephan, Taylor, Herman, Colley, Heather A., Dayal, Jyoti G., Doss, Argenia L., Eckstein, David J., Hutchison, Sarah, Krasnewich, Donna M., Mamounas, Laura A., Manolio, Teri A., Urv, Tiina K., Acosta, Maria T., D'Souza, Precilla, Gropman, Andrea, Macnamara, Ellen F., Maduro, Valerie V., Mulvihill, John J., Novacic, Donna, Pusey Swerdzewski, Barbara N., Toro, Camilo, Wahl, Colleen E., Adams, David R., Afzali, Ben, Burke, Elizabeth A., Davis, Joie, Delgado, Margaret, Fu, Jiayu, Gahl, William A., Hanchard, Neil, Huang, Yan, Introne, Wendy, Jean-Marie, Orpa, Malicdan, May Christine V., Morimoto, Marie, Petcharet, Leoyklang, Rossignol, Francis, Sabaii, Marla, Solomon, Ben, Tifft, Cynthia J., Wolfe, Lynne A., Wood, Heidi, Allworth, Aimee, Bamshad, Michael, Beck, Anita, Bennett, Jimmy, Blue, Elizabeth, Byers, Peter, Chanprasert, Sirisak, Cunningham, Michael, Dipple, Katrina, Doherty, Daniel, Earl, Dawn, Glass, Ian, Hing, Anne, Hisama, Fuki M., Horike-Pyne, Martha, Jarvik, Gail P., Jarvik, Jeffrey, Jayadev, Suman, Kaitryn, Emerald, Lam, Christina, Miller, Danny, Mirzaa, Ghayda, Raskind, Wendy, Rosenthal, Elizabeth, Shelkowitz, Emily, Sheppeard, Sam, Stergachis, Andrew, Sybert, Virginia, Wener, Mark, Wenger, Tara, Alvarez, Raquel L., Bejerano, Gill, Bernstein, Jonathan A., Bonner, Devon, Coakley, Terra R., Fisher, Paul G., Goddard, Page C., Halley, Meghan C., Hom, Jason, Kohler, Jennefer N., Kravets, Elijah, Martin, Beth A., Marwaha, Shruti, Reuter, Chloe M., Ruzhnikov, Maura, Sampson, Jacinda B., Smith, Kevin S., Sutton, Shirley, Tabor, Holly K., Ungar, Rachel A., Wheeler, Matthew T., Ashley, Euan A., Byrd, William E., Crouse, Andrew B., Might, Matthew, Nakano-Okuno, Mariko, Whitlock, Jordan, Butte, Manish J., Corona, Rosario, Dell'Angelica, Esteban C., Dorrani, Naghmeh, Douine, Emilie D., Fogel, Brent L., Huang, Alden, Krakow, Deborah, Loo, Sandra K., Martin, Martin G., Martínez-Agosto, Julian A., McGee, Elisabeth, Nelson, Stanley F., Nieves-Rodriguez, Shirley, Papp, Jeanette C., Parker, Neil H., Renteria, Genecee, Sinsheimer, Janet S., Wan, Jijun, Alvey, Justin, Andrews, Ashley, Bale, Jim, Bohnsack, John, Botto, Lorenzo, Carey, John, Longo, Nicola, Moretti, Paolo, Pace, Laura, Quinlan, Aaron, Velinder, Matt, Viskochil, Dave, Marth, Gabor, Bayrak-Toydemir, Pinar, Mao, Rong, Westerfield, Monte, Bican, Anna, Cassini, Thomas, Corner, Brian, Hamid, Rizwan, Neumann, Serena, Phillips, John A., III, Rives, Lynette, Robertson, Amy K., Ezell, Kimberly, Cogan, Joy D., Hayes, Nichole, Kiley, Dana, Sisco, Kathy, Wambach, Jennifer, Wegner, Daniel, Baldridge, Dustin, Cole, F. Sessions, Pak, Stephen, Schedl, Timothy, Shin, Jimann, Solnica-Krezel, Lilianna, Moulton, Matthew J., Atala, Kristhen, Zheng, Yiming, Dutta, Debdeep, Grange, Dorothy K., Lin, Wen-Wen, Wegner, Daniel J., Wambach, Jennifer A., Duker, Angela L., Bober, Michael B., Kratz, Lisa, Wise, Carol A., Oxendine, Ila, Khanshour, Anas, and Rios, Jonathan

Published
2024
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21. Loss of function of FAM177A1, a Golgi complex localized protein, causes a novel neurodevelopmental disorder

Author

Acosta, Maria T., Adam, Margaret, Adams, David R., Alvarez, Raquel L., Alvey, Justin, Amendola, Laura, Andrews, Ashley, Ashley, Euan A., Bacino, Carlos A., Bademci, Guney, Balasubramanyam, Ashok, Baldridge, Dustin, Bale, Jim, Bamshad, Michael, Barbouth, Deborah, Bayrak-Toydemir, Pinar, Beck, Anita, Beggs, Alan H., Behrens, Edward, Bejerano, Gill, Bellen, Hugo J., Bennett, Jimmy, Berg-Rood, Beverly, Bernstein, Jonathan A., Berry, Gerard T., Bican, Anna, Bivona, Stephanie, Blue, Elizabeth, Bohnsack, John, Bonner, Devon, Botto, Lorenzo, Boyd, Brenna, Briere, Lauren C., Burke, Elizabeth A., Burrage, Lindsay C., Butte, Manish J., Byers, Peter, Byrd, William E., Carey, John, Carrasquillo, Olveen, Cassini, Thomas, Chang, Ta Chen Peter, Chanprasert, Sirisak, Chao, Hsiao-Tuan, Chinn, Ivan, Clark, Gary D., Coakley, Terra R., Cobban, Laurel A., Cogan, Joy D., Coggins, Matthew, Sessions Cole, F., Colley, Heather A., Cope, Heidi, Corner, Brian, Corona, Rosario, Craigen, William J., Crouse, Andrew B., Cunningham, Michael, D’Souza, Precilla, Dai, Hongzheng, Dasari, Surendra, Davis, Joie, Dayal, Jyoti G., Dell’Angelica, Esteban C., Dickson, Patricia, Dipple, Katrina, Doherty, Daniel, Dorrani, Naghmeh, Doss, Argenia L., Douine, Emilie D., Earl, Dawn, Eckstein, David J., Emrick, Lisa T., Eng, Christine M., Ezell, Kimberly, Falk, Marni, Fieg, Elizabeth L., Fisher, Paul G., Fogel, Brent L., Forghani, Irman, Gahl, William A., Glass, Ian, Gochuico, Bernadette, Goddard, Page C., Godfrey, Rena A., Golden-Grant, Katie, Grajewski, Alana, Hadley, Don, Hahn, Sihoun, Halley, Meghan C., Hamid, Rizwan, Hassey, Kelly, Hayes, Nichole, High, Frances, Hing, Anne, Hisama, Fuki M., Holm, Ingrid A., Hom, Jason, Horike-Pyne, Martha, Huang, Alden, Hutchison, Sarah, Introne, Wendy, Isasi, Rosario, Izumi, Kosuke, Jamal, Fariha, Jarvik, Gail P., Jarvik, Jeffrey, Jayadev, Suman, Jean-Marie, Orpa, Jobanputra, Vaidehi, Karaviti, Lefkothea, Ketkar, Shamika, Kiley, Dana, Kilich, Gonench, Kobren, Shilpa N., Kohane, Isaac S., Kohler, Jennefer N., Korrick, Susan, Kozuira, Mary, Krakow, Deborah, Krasnewich, Donna M., Kravets, Elijah, Lalani, Seema R., Lam, Byron, Lam, Christina, Lanpher, Brendan C., Lanza, Ian R., LeBlanc, Kimberly, Lee, Brendan H., Levitt, Roy, Lewis, Richard A., Liu, Pengfei, Liu, Xue Zhong, Longo, Nicola, Loo, Sandra K., Loscalzo, Joseph, Maas, Richard L., Macnamara, Ellen F., MacRae, Calum A., Maduro, Valerie V., Maghiro, AudreyStephannie, Mahoney, Rachel, Malicdan, May Christine V., Mamounas, Laura A., Manolio, Teri A., Mao, Rong, Maravilla, Kenneth, Marom, Ronit, Marth, Gabor, Martin, Beth A., Martin, Martin G., Martínez-Agosto, Julian A., Marwaha, Shruti, McCauley, Jacob, McConkie-Rosell, Allyn, McCray, Alexa T., McGee, Elisabeth, Mefford, Heather, Lawrence Merritt, J., Might, Matthew, Mirzaa, Ghayda, Morava, Eva, Moretti, Paolo, Mulvihill, John, Nakano-Okuno, Mariko, Nelson, Stanley F., Neumann, Serena, Newman, John H., Nicholas, Sarah K., Nickerson, Deborah, Nieves-Rodriguez, Shirley, Novacic, Donna, Oglesbee, Devin, Orengo, James P., Pace, Laura, Pak, Stephen, Carl Pallais, J., Palmer, Christina G.S., Papp, Jeanette C., Parker, Neil H., Phillips, John A., III, Posey, Jennifer E., Potocki, Lorraine, Pusey Swerdzewski, Barbara N., Quinlan, Aaron, Rao, Deepak A., Raper, Anna, Raskind, Wendy, Renteria, Genecee, Reuter, Chloe M., Rives, Lynette, Robertson, Amy K., Rodan, Lance H., Rosenfeld, Jill A., Rosenwasser, Natalie, Rossignol, Francis, Ruzhnikov, Maura, Sacco, Ralph, Sampson, Jacinda B., Saporta, Mario, Schaechter, Judy, Schedl, Timothy, Schoch, Kelly, Scott, Daryl A., Ron Scott, C., Seto, Elaine, Shashi, Vandana, Shin, Jimann, Silverman, Edwin K., Sinsheimer, Janet S., Sisco, Kathy, Smith, Edward C., Smith, Kevin S., Solnica-Krezel, Lilianna, Solomon, Ben, Spillmann, Rebecca C., Stoler, Joan M., Sullivan, Kathleen, Sullivan, Jennifer A., Sun, Angela, Sutton, Shirley, Sweetser, David A., Sybert, Virginia, Tabor, Holly K., Tan, Queenie K.-G., Tan, Amelia L.M., Tarakad, Arjun, Tekin, Mustafa, Telischi, Fred, Thorson, Willa, Tifft, Cynthia J., Toro, Camilo, Tran, Alyssa A., Ungar, Rachel A., Urv, Tiina K., Vanderver, Adeline, Velinder, Matt, Viskochil, Dave, Vogel, Tiphanie P., Wahl, Colleen E., Walker, Melissa, Wallace, Stephanie, Walley, Nicole M., Wambach, Jennifer, Wan, Jijun, Wangler, Michael F., Ward, Patricia A., Wegner, Daniel, Hubshman, Monika Weisz, Wener, Mark, Wenger, Tara, Westerfield, Monte, Wheeler, Matthew T., Whitlock, Jordan, Wolfe, Lynne A., Worley, Kim, Xiao, Changrui, Yamamoto, Shinya, Yang, John, Zhang, Zhe, Zuchner, Stephan, Legro, Nicole R., Bowman, Angela, Ugur, Berrak, Jackstadt, Madelyn M., Shriver, Leah P., Patti, Gary J., Zhang, Bo, Feng, Wenjia, McAdow, Anthony R., Goddard, Pagé, Jensen, Tanner, Fresard, Laure, Alvarez, Raquel, McCormack, Colleen, Holt, James M., Worthey, Elizabeth A., Montgomery, Stephen B., Postlethwait, John, De Camilli, Pietro, and Solnica-Krezel, Lila

Published
2024
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24. Aromatized liposomes for sustained drug delivery

Author

Yang Li, Tianjiao Ji, Matthew Torre, Rachelle Shao, Yueqin Zheng, Dali Wang, Xiyu Li, Andong Liu, Wei Zhang, Xiaoran Deng, Ran Yan, and Daniel S. Kohane

Subjects
Science
Abstract

Abstract Insufficient drug loading and leakage of payload remain major challenges in designing liposome-based drug delivery systems. These phenomena can limit duration of effect and cause toxicity. Targeting the rate-limiting step in drug release from liposomes, we modify (aromatized) them to have aromatic groups within their lipid bilayers. Aromatized liposomes are designed with synthetic phospholipids with aromatic groups covalently conjugated onto acyl chains. The optimized aromatized liposome increases drug loading and significantly decreases the burst release of a broad range of payloads (small molecules and macromolecules, different degrees of hydrophilicity) and extends their duration of release. Aromatized liposomes encapsulating the anesthetic tetrodotoxin (TTX) achieve markedly prolonged effect and decreased toxicity in an application where liposomes are used clinically: local anesthesia, even though TTX is a hydrophilic small molecule which is typically difficult to encapsulate. Aromatization of lipid bilayers can improve the performance of liposomal drug delivery systems.

Published
2023
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25. Simulation of undiagnosed patients with novel genetic conditions

Author

Emily Alsentzer, Samuel G. Finlayson, Michelle M. Li, Undiagnosed Diseases Network, Shilpa N. Kobren, and Isaac S. Kohane

Subjects
Science
Abstract

Abstract Rare Mendelian disorders pose a major diagnostic challenge and collectively affect 300–400 million patients worldwide. Many automated tools aim to uncover causal genes in patients with suspected genetic disorders, but evaluation of these tools is limited due to the lack of comprehensive benchmark datasets that include previously unpublished conditions. Here, we present a computational pipeline that simulates realistic clinical datasets to address this deficit. Our framework jointly simulates complex phenotypes and challenging candidate genes and produces patients with novel genetic conditions. We demonstrate the similarity of our simulated patients to real patients from the Undiagnosed Diseases Network and evaluate common gene prioritization methods on the simulated cohort. These prioritization methods recover known gene-disease associations but perform poorly on diagnosing patients with novel genetic disorders. Our publicly-available dataset and codebase can be utilized by medical genetics researchers to evaluate, compare, and improve tools that aid in the diagnostic process.

Published
2023
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26. Exome and genome sequencing in a heterogeneous population of patients with rare disease: Identifying predictors of a diagnosis

Author

Acosta, Maria T., Adams, David R., Alvarez, Raquel L., Alvey, Justin, Allworth, Aimee, Andrews, Ashley, Ashley, Euan A., Bacino, Carlos A., Bademci, Guney, Balasubramanyam, Ashok, Baldridge, Dustin, Bale, Jim, Bamshad, Michael, Barbouth, Deborah, Bayrak-Toydemir, Pinar, Beck, Anita, Beggs, Alan H., Behrens, Edward, Bejerano, Gill, Bellen, Hugo J., Bennett, Jimmy, Bernstein, Jonathan A., Berry, Gerard T., Bican, Anna, Bivona, Stephanie, Blue, Elizabeth, Bohnsack, John, Bonner, Devon, Botto, Lorenzo, Briere, Lauren C., Brown, Gabrielle, Burke, Elizabeth A., Burrage, Lindsay C., Butte, Manish J., Byers, Peter, Byrd, William E., Carey, John, Carrasquillo, Olveen, Cassini, Thomas, Peter Chang, Ta Chen, Chanprasert, Sirisak, Chao, Hsiao-Tuan, Chinn, Ivan, Clark, Gary D., Coakley, Terra R., Cobban, Laurel A., Cogan, Joy D., Coggins, Matthew, Cole, F. Sessions, Colley, Heather A., Cope, Heidi, Corona, Rosario, Craigen, William J., Crouse, Andrew B., Cunningham, Michael, D’Souza, Precilla, Dai, Hongzheng, Dasari, Surendra, Davis, Joie, Dayal, Jyoti G., Dell'Angelica, Esteban C., Dipple, Katrina, Doherty, Daniel, Dorrani, Naghmeh, Doss, Argenia L., Douine, Emilie D., Earl, Dawn, Eckstein, David J., Emrick, Lisa T., Eng, Christine M., Falk, Marni, Fieg, Elizabeth L., Fisher, Paul G., Fogel, Brent L., Forghani, Irman, Gahl, William A., Glass, Ian, Gochuico, Bernadette, Goddard, Page C., Godfrey, Rena A., Grajewski, Alana, Hadley, Don, Halley, Meghan C., Hamid, Rizwan, Hassey, Kelly, Hayes, Nichole, High, Frances, Hing, Anne, Hisama, Fuki M., Holm, Ingrid A., Hom, Jason, Horike-Pyne, Martha, Huang, Alden, Hutchison, Sarah, Introne, Wendy, Isasi, Rosario, Izumi, Kosuke, Jarvik, Gail P., Jarvik, Jeffrey, Jayadev, Suman, Jean-Marie, Orpa, Jobanputra, Vaidehi, Kaitryn, Emerald, Ketkar, Shamika, Kiley, Dana, Kilich, Gonench, Kobren, Shilpa N., Kohane, Isaac S., Kohler, Jennefer N., Korrick, Susan, Krakow, Deborah, Krasnewich, Donna M., Kravets, Elijah, Lalani, Seema R., Lam, Byron, Lam, Christina, Lanpher, Brendan C., Lanza, Ian R., LeBlanc, Kimberly, Lee, Brendan H., Levitt, Roy, Lewis, Richard A., Liu, Pengfei, Liu, Xue Zhong, Longo, Nicola, Loo, Sandra K., Loscalzo, Joseph, Maas, Richard L., Macnamara, Ellen F., MacRae, Calum A., Maduro, Valerie V., Maghiro, AudreyStephannie, Mahoney, Rachel, Malicdan, May Christine V., Mamounas, Laura A., Manolio, Teri A., Mao, Rong, Marom, Ronit, Marth, Gabor, Martin, Beth A., Martin, Martin G., Martínez-Agosto, Julian A., Marwaha, Shruti, McCauley, Jacob, McConkie-Rosell, Allyn, McCray, Alexa T., McGee, Elisabeth, Might, Matthew, Miller, Danny, Mirzaa, Ghayda, Morava, Eva, Moretti, Paolo, Mulvihill, John J., Nakano-Okuno, Mariko, Nelson, Stanley F., Nieves-Rodriguez, Shirley, Novacic, Donna, Oglesbee, Devin, Orengo, James P., Pace, Laura, Pak, Stephen, Pallais, J. Carl, Palmer, Christina G.S., Papp, Jeanette C., Parker, Neil H., Phillips, John A., III, Posey, Jennifer E., Potocki, Lorraine, Pusey Swerdzewski, Barbara N., Quinlan, Aaron, Rao, Deepak A., Raper, Anna, Raskind, Wendy, Renteria, Genecee, Reuter, Chloe M., Rives, Lynette, Robertson, Amy K., Rodan, Lance H., Rosenfeld, Jill A., Rosenthal, Elizabeth, Rossignol, Francis, Ruzhnikov, Maura, Sacco, Ralph, Sampson, Jacinda B., Saporta, Mario, Schaechter, Judy, Schedl, Timothy, Schoch, Kelly, Scott, Daryl A., Seto, Elaine, Shashi, Vandana, Shelkowitz, Emily, Sheppeard, Sam, Shin, Jimann, Silverman, Edwin K., Sinsheimer, Janet S., Sisco, Kathy, Smith, Edward C., Smith, Kevin S., Solnica-Krezel, Lilianna, Solomon, Ben, Spillmann, Rebecca C., Stergachis, Andrew, Stoler, Joan M., Sullivan, Kathleen, Sullivan, Jennifer A., Sutton, Shirley, Sweetser, David A., Sybert, Virginia, Tabor, Holly K., Tan, Queenie K.-G., Tan, Amelia L.M., Tarakad, Arjun, Tekin, Mustafa, Telischi, Fred, Thorson, Willa, Tifft, Cynthia J., Toro, Camilo, Tran, Alyssa A., Ungar, Rachel A., Urv, Tiina K., Vanderver, Adeline, Velinder, Matt, Viskochil, Dave, Vogel, Tiphanie P., Wahl, Colleen E., Walker, Melissa, Walley, Nicole M., Wambach, Jennifer, Wan, Jijun, Wang, Lee-kai, Wangler, Michael F., Ward, Patricia A., Wegner, Daniel, Hubshman, Monika Weisz, Wener, Mark, Wenger, Tara, Westerfield, Monte, Wheeler, Matthew T., Whitlock, Jordan, Wolfe, Lynne A., Worley, Kim, Xiao, Changrui, Yamamoto, Shinya, Yang, John, Zhang, Zhe, Zuchner, Stephan, Pucel, Jenna, Reuter, Chloe, and Gochyyev, Perman

Published
2024
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30. International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality

Author

Weber, Griffin M, Hong, Chuan, Xia, Zongqi, Palmer, Nathan P, Avillach, Paul, L’Yi, Sehi, Keller, Mark S, Murphy, Shawn N, Gutiérrez-Sacristán, Alba, Bonzel, Clara-Lea, Serret-Larmande, Arnaud, Neuraz, Antoine, Omenn, Gilbert S, Visweswaran, Shyam, Klann, Jeffrey G, South, Andrew M, Loh, Ne Hooi Will, Cannataro, Mario, Beaulieu-Jones, Brett K, Bellazzi, Riccardo, Agapito, Giuseppe, Alessiani, Mario, Aronow, Bruce J, Bell, Douglas S, Benoit, Vincent, Bourgeois, Florence T, Chiovato, Luca, Cho, Kelly, Dagliati, Arianna, DuVall, Scott L, Barrio, Noelia García, Hanauer, David A, Ho, Yuk-Lam, Holmes, John H, Issitt, Richard W, Liu, Molei, Luo, Yuan, Lynch, Kristine E, Maidlow, Sarah E, Malovini, Alberto, Mandl, Kenneth D, Mao, Chengsheng, Matheny, Michael E, Moore, Jason H, Morris, Jeffrey S, Morris, Michele, Mowery, Danielle L, Ngiam, Kee Yuan, Patel, Lav P, Pedrera-Jimenez, Miguel, Ramoni, Rachel B, Schriver, Emily R, Schubert, Petra, Balazote, Pablo Serrano, Spiridou, Anastasia, Tan, Amelia LM, Tan, Byorn WL, Tibollo, Valentina, Torti, Carlo, Trecarichi, Enrico M, Wang, Xuan, Kohane, Isaac S, Cai, Tianxi, and Brat, Gabriel A

Subjects
Health Services and Systems, Health Sciences, Basic Behavioral and Social Science, Behavioral and Social Science, Good Health and Well Being, Consortium for Clinical Characterization of COVID-19 by EHR, Health services and systems
Abstract

Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach.

Published
2022

34. De novo variants in DENND5B cause a neurodevelopmental disorder

Author

Acosta, Maria T., Adams, David R., Alvarez, Raquel L., Alvey, Justin, Allworth, Aimee, Andrews, Ashley, Ashley, Euan A., Afzali, Ben, Bacino, Carlos A., Bademci, Guney, Balasubramanyam, Ashok, Baldridge, Dustin, Bale, Jim, Bamshad, Michael, Barbouth, Deborah, Bayrak-Toydemir, Pinar, Beck, Anita, Beggs, Alan H., Behrens, Edward, Bejerano, Gill, Bellen, Hugo J., Bennett, Jimmy, Bernstein, Jonathan A., Berry, Gerard T., Bican, Anna, Bivona, Stephanie, Blue, Elizabeth, Bohnsack, John, Bonner, Devon, Botto, Lorenzo, Briere, Lauren C., Brown, Gabrielle, Burke, Elizabeth A., Burrage, Lindsay C., Butte, Manish J., Byers, Peter, Byrd, William E., Carey, John, Carrasquillo, Olveen, Cassini, Thomas, Chang, Ta Chen Peter, Chanprasert, Sirisak, Chao, HsiaoTuan, Chinn, Ivan, Clark, Gary D., Coakley, Terra R., Cobban, Laurel A., Cogan, Joy D., Coggins, Matthew, Cole, F. Sessions, Colley, Heather A., Cope, Heidi, Corona, Rosario, Craigen, William J., Crouse, Andrew B., Cunningham, Michael, D’Souza, Precilla, Dai, Hongzheng, Dasari, Surendra, Davis, Joie, Dayal, Jyoti G., Delgado, Margaret, Dell'Angelica, Esteban C., Dipple, Katrina, Doherty, Daniel, Dorrani, Naghmeh, Doss, Argenia L., Douine, Emilie D., Earl, Dawn, Eckstein, David J., Emrick, Lisa T., Eng, Christine M., Falk, Marni, Fieg, Elizabeth L., Fisher, Paul G., Fogel, Brent L., Forghani, Irman, Fu, Jiayu, Gahl, William A., Glass, Ian, Goddard, Page C., Godfrey, Rena A., Grajewski, Alana, Gropman, Andrea, Halley, Meghan C., Hamid, Rizwan, Hanchard, Neal, Hassey, Kelly, Hayes, Nichole, High, Frances, Hing, Anne, Hisama, Fuki M., Holm, Ingrid A., Hom, Jason, Horike-Pyne, Martha, Huang, Alden, Huang, Yan, Hutchison, Sarah, Introne, Wendy, Isasi, Rosario, Izumi, Kosuke, Jarvik, Gail P., Jarvik, Jeffrey, Jayadev, Suman, Jean-Marie, Orpa, Jobanputra, Vaidehi, Kaitryn, Emerald, Ketkar, Shamika, Kiley, Dana, Kilich, Gonench, Kobren, Shilpa N., Kohane, Isaac S., Kohler, Jennefer N., Korrick, Susan, Krakow, Deborah, Krasnewich, Donna M., Kravets, Elijah, Lalani, Seema R., Lam, Byron, Lam, Christina, Lanpher, Brendan C., Lanza, Ian R., LeBlanc, Kimberly, Lee, Brendan H., Levitt, Roy, Lewis, Richard A., Liu, Pengfei, Liu, Xue Zhong, Longo, Nicola, Loo, Sandra K., Loscalzo, Joseph, Maas, Richard L., Macnamara, Ellen F., MacRae, Calum A., Maduro, Valerie V., Maghiro, AudreyStephannie, Mahoney, Rachel, Malicdan, May Christine V., Mamounas, Laura A., Manolio, Teri A., Mao, Rong, Marom, Ronit, Marth, Gabor, Martin, Beth A., Martin, Martin G., Martínez-Agosto, Julian A., Marwaha, Shruti, McCauley, Jacob, McConkie-Rosell, Allyn, McCray, Alexa T., McGee, Elisabeth, Might, Matthew, Miller, Danny, Mirzaa, Ghayda, Morava, Eva, Moretti, Paolo, Morimoto, Marie, Mulvihill, John J., Nakano-Okuno, Mariko, Nelson, Stanley F., Nieves-Rodriguez, Shirley, Novacic, Donna, Oglesbee, Devin, Orengo, James P., Pace, Laura, Pak, Stephen, Pallais, J. Carl, Papp, Jeanette C., Parker, Neil H., Petcharet, Leoyklang, Phillips, John A., III, Posey, Jennifer E., Potocki, Lorraine, Swerdzewski, Barbara N. Pusey, Quinlan, Aaron, Rao, Deepak A., Raper, Anna, Raskind, Wendy, Renteria, Genecee, Reuter, Chloe M., Rives, Lynette, Robertson, Amy K., Rodan, Lance H., Rosenfeld, Jill A., Rosenthal, Elizabeth, Rossignol, Francis, Ruzhnikov, Maura, Sabaii, Marla, Sacco, Ralph, Sampson, Jacinda B., Saporta, Mario, Schaechter, Judy, Schedl, Timothy, Schoch, Kelly, Scott, Daryl A., Seto, Elaine, Sharma, Prashant, Shashi, Vandana, Shelkowitz, Emily, Sheppeard, Sam, Shin, Jimann, Silverman, Edwin K., Sinsheimer, Janet S., Sisco, Kathy, Smith, Edward C., Smith, Kevin S., Solnica-Krezel, Lilianna, Solomon, Ben, Spillmann, Rebecca C., Stergachis, Andrew, Stoler, Joan M., Sullivan, Kathleen, Sullivan, Jennifer A., Sutton, Shirley, Sweetser, David A., Sybert, Virginia, Tabor, Holly K., Tan, Queenie K.-G., Tan, Amelia L.M., Tarakad, Arjun, Taylor, Herman, Tekin, Mustafa, Telischi, Fred, Thorson, Willa, Tifft, Cynthia J., Toro, Camilo, Tran, Alyssa A., Ungar, Rachel A., Urv, Tiina K., Vanderver, Adeline, Velinder, Matt, Viskochil, Dave, Vogel, Tiphanie P., Wahl, Colleen E., Walker, Melissa, Walley, Nicole M., Wambach, Jennifer, Wan, Jijun, Wang, Lee-kai, Wangler, Michael F., Ward, Patricia A., Wegner, Daniel, Weisz Hubshman, Monika, Wener, Mark, Wenger, Tara, Westerfield, Monte, Wheeler, Matthew T., Whitlock, Jordan, Wolfe, Lynne A., Worley, Kim, Yamamoto, Shinya, Zhang, Zhe, Zuchner, Stephan, Scala, Marcello, Tomati, Valeria, Ferla, Matteo, Lena, Mariateresa, Cohen, Julie S., Fatemi, Ali, Brokamp, Elly, Koziura, Mary E., Nicouleau, Michael, Rio, Marlene, Siquier, Karine, Boddaert, Nathalie, Musante, Ilaria, Tamburro, Serena, Baldassari, Simona, Iacomino, Michele, Scudieri, Paolo, Bellus, Gary, Reed, Sara, Al Saif, Hind, Russo, Rossana Sanchez, Walsh, Matthew B., Cantagrel, Vincent, Crunk, Amy, Gustincich, Stefano, Ruggiero, Sarah M., Fitzgerald, Mark P., Helbig, Ingo, Striano, Pasquale, Severino, Mariasavina, Salpietro, Vincenzo, Pedemonte, Nicoletta, and Zara, Federico

Published
2024
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35. Biallelic CRELD1 variants cause a multisystem syndrome, including neurodevelopmental phenotypes, cardiac dysrhythmias, and frequent infections

Author

Borras, Silvia, Clark, Caroline, Dean, John, Miedzybrodzka, Zosia, Ross, Alison, Tennant, Stephen, Dabir, Tabib, Donnelly, Deirdre, Humphreys, Mervyn, Magee, Alex, McConnell, Vivienne, McKee, Shane, McNerlan, Susan, Morrison, Patrick J., Rea, Gillian, Stewart, Fiona, Cole, Trevor, Cooper, Nicola, Cooper-Charles, Lisa, Cox, Helen, Islam, Lily, Jarvis, Joanna, Keelagher, Rebecca, Lim, Derek, McMullan, Dominic, Morton, Jenny, Naik, Swati, O’Driscoll, Mary, Ong, Kai-Ren, Osio, Deborah, Ragge, Nicola, Turton, Sarah, Vogt, Julie, Williams, Denise, Bodek, Simon, Donaldson, Alan, Hills, Alison, Low, Karen, Newbury-Ecob, Ruth, Norman, Andrew M., Roberts, Eileen, Scurr, Ingrid, Smithson, Sarah, Tooley, Madeleine, Abbs, Steve, Armstrong, Ruth, Dunn, Carolyn, Holden, Simon, Park, Soo-Mi, Paterson, Joan, Raymond, Lucy, Reid, Evan, Sandford, Richard, Simonic, Ingrid, Tischkowitz, Marc, Woods, Geoff, Bradley, Lisa, Comerford, Joanne, Green, Andrew, Lynch, Sally, McQuaid, Shirley, Mullaney, Brendan, Berg, Jonathan, Goudie, David, Mavrak, Eleni, McLean, Joanne, McWilliam, Catherine, Reavey, Eleanor, Azam, Tara, Cleary, Elaine, Jackson, Andrew, Lam, Wayne, Lampe, Anne, Moore, David, Porteous, Mary, Baple, Emma, Baptista, Júlia, Brewer, Carole, Castle, Bruce, Kivuva, Emma, Owens, Martina, Rankin, Julia, Shaw-Smith, Charles, Turner, Claire, Turnpenny, Peter, Tysoe, Carolyn, Bradley, Therese, Davidson, Rosemarie, Gardiner, Carol, Joss, Shelagh, Kinning, Esther, Longman, Cheryl, McGowan, Ruth, Murday, Victoria, Pilz, Daniela, Tobias, Edward, Whiteford, Margo, Williams, Nicola, Barnicoat, Angela, Clement, Emma, Faravelli, Francesca, Hurst, Jane, Jenkins, Lucy, Jones, Wendy, Ajith Kumar, V.K., Lees, Melissa, Loughlin, Sam, Male, Alison, Morrogh, Deborah, Rosser, Elisabeth, Scott, Richard, Wilson, Louise, Beleza, Ana, Deshpande, Charu, Flinter, Frances, Holder, Muriel, Irving, Melita, Izatt, Louise, Josifova, Dragana, Mohammed, Shehla, Molenda, Aneta, Robert, Leema, Roworth, Wendy, Ruddy, Deborah, Ryten, Mina, Yau, Shu, Bennett, Christopher, Blyth, Moira, Campbell, Jennifer, Coates, Andrea, Dobbie, Angus, Hewitt, Sarah, Hobson, Emma, Jackson, Eilidh, Jewell, Rosalyn, Kraus, Alison, Prescott, Katrina, Sheridan, Eamonn, Thomson, Jenny, Bradshaw, Kirsty, Dixit, Abhijit, Eason, Jacqueline, Haines, Rebecca, Harrison, Rachel, Mutch, Stacey, Sarkar, Ajoy, Searle, Claire, Shannon, Nora, Sharif, Abid, Suri, Mohnish, Vasudevan, Pradeep, Canham, Natalie, Ellis, Ian, Greenhalgh, Lynn, Howard, Emma, Stinton, Victoria, Swale, Andrew, Weber, Astrid, Banka, Siddharth, Breen, Catherine, Briggs, Tracy, Burkitt-Wright, Emma, Chandler, Kate, Clayton-Smith, Jill, Donnai, Dian, Douzgou, Sofia, Gaunt, Lorraine, Jones, Elizabeth, Kerr, Bronwyn, Langley, Claire, Metcalfe, Kay, Smith, Audrey, Wright, Ronnie, Bourn, David, Burn, John, Fisher, Richard, Hellens, Steve, Henderson, Alex, Montgomery, Tara, Splitt, Miranda, Straub, Volker, Wright, Michael, Zwolinski, Simon, Allen, Zoe, Bernhard, Birgitta, Brady, Angela, Brooks, Claire, Busby, Louise, Clowes, Virginia, Ghali, Neeti, Holder, Susan, Ibitoye, Rita, Wakeling, Emma, Blair, Edward, Carmichael, Jenny, Cilliers, Deirdre, Clasper, Susan, Gibbons, Richard, Kini, Usha, Lester, Tracy, Nemeth, Andrea, Poulton, Joanna, Price, Sue, Shears, Debbie, Stewart, Helen, Wilkie, Andrew, Albaba, Shadi, Baker, Duncan, Balasubramanian, Meena, Johnson, Diana, Parker, Michael, Quarrell, Oliver, Stewart, Alison, Willoughby, Josh, Crosby, Charlene, Elmslie, Frances, Homfray, Tessa, Jin, Huilin, Lahiri, Nayana, Mansour, Sahar, Marks, Karen, McEntagart, Meriel, Saggar, Anand, Tatton-Brown, Kate, Butler, Rachel, Clarke, Angus, Corrin, Sian, Fry, Andrew, Kamath, Arveen, McCann, Emma, Mugalaasi, Hood, Pottinger, Caroline, Procter, Annie, Sampson, Julian, Sansbury, Francis, Varghese, Vinod, Baralle, Diana, Callaway, Alison, Cassidy, Emma J., Daniels, Stacey, Douglas, Andrew, Foulds, Nicola, Hunt, David, Kharbanda, Mira, Lachlan, Katherine, Mercer, Catherine, Side, Lucy, Temple, I. Karen, Wellesley, Diana, Ambrose, J.C., Arumugam, P., Baple, E.L., Bleda, M., Boardman-Pretty, F., Boissiere, J.M., Boustred, C.R., Caulfield, M.J., Chan, G.C., Craig, C.E.H., Daugherty, L.C., de Burca, A., Devereau, A., Elgar, G., Foulger, R.E., Fowler, T., FurióTarí, P., Hackett, J.M., Halai, D., Hamblin, A., Henderson, S., Holman, J.E., Hubbard, T.J.P., Ibáñez, K., Jackson, R., Jones, L.J., Kasperaviciute, D., Kayikci, M., Lahnstein, L., Lawson, K., Leigh, S.E.A., Leong, I.U.S., Lopez, F.J., MaleadyCrowe, F., Mason, J., McDonagh, E.M., Moutsianas, L., Mueller, M., Murugaesu, N., Need, A.C., Odhams, C.A., Patch, C., Perez-Gil, D., Polychronopoulos, D., Pullinger, J., Rahim, T., Rendon, A., Riesgo-Ferreiro, P., Rogers, T., Ryten, M., Savage, K., Sawant, K., Scott, R.H., Siddiq, A., Sieghart, A., Smedley, D., Smith, K.R., Sosinsky, A., Spooner, W., Stevens, H.E., Stuckey, A., Sultana, R., Thomas, E.R.A., Thompson, S.R., Tucci, A., Walsh, E., Watters, S.A., Welland, M.J., Williams, E., Witkowska, K., Acosta, Maria T., Adam, Margaret, Adams, David R., Agrawal, Pankaj B., Alejandro, Mercedes E., Alvey, Justin, Amendola, Laura, Andrews, Ashley, Ashley, Euan A., Azamian, Mahshid S., Bacino, Carlos A., Bademci, Guney, Baker, Eva, Balasubramanyam, Ashok, Baldridge, Dustin, Bale, Jim, Bamshad, Michael, Barbouth, Deborah, Bayrak-Toydemir, Pinar, Beck, Anita, Beggs, Alan H., Behrens, Edward, Bejerano, Gill, Bennet, Jimmy, Berg-Rood, Beverly, Bernstein, Jonathan A., Berry, Gerard T., Bican, Anna, Bivona, Stephanie, Blue, Elizabeth, Bohnsack, John, Bonnenmann, Carsten, Bonner, Devon, Botto, Lorenzo, Boyd, Brenna, Briere, Lauren C., Brokamp, Elly, Brown, Gabrielle, Burke, Elizabeth A., Burrage, Lindsay C., Butte, Manish J., Byers, Peter, Byrd, William E., Carey, John, Carrasquillo, Olveen, Peter Chang, Ta Chen, Chanprasert, Sirisak, Chao, Hsiao-Tuan, Clark, Gary D., Coakley, Terra R., Cobban, Laurel A., Cogan, Joy D., Coggins, Matthew, Cole, F. Sessions, Colley, Heather A., Cooper, Cynthia M., Craigen, William J., Crouse, Andrew B., Cunningham, Michael, D'Souza, Precilla, Dai, Hongzheng, Dasari, Surendra, Davids, Mariska, Dayal, Jyoti G., Deardorff, Matthew, Dell'Angelica, Esteban C., Dhar, Shweta U., Dipple, Katrina, Doherty, Daniel, Dorrani, Naghmeh, Douine, Emilie D., Draper, David D., Duncan, Laura, Earl, Dawn, Eckstein, David J., Emrick, Lisa T., Eng, Christine M., Esteves, Cecilia, Estwick, Tyra, Falk, Marni, Fernandez, Liliana, Ferreira, Carlos, Fieg, Elizabeth L., Findley, Laurie C., Fisher, Paul G., Fogel, Brent L., Forghani, Irman, Fresard, Laure, Gahl, William A., Glass, Ian, Godfrey, Rena A., Golden-Grant, Katie, Goldman, Alica M., Goldstein, David B., Grajewski, Alana, Groden, Catherine A., Gropman, Andrea L., Gutierrez, Irma, Hahn, Sihoun, Hamid, Rizwan, Hanchard, Neil A., Hassey, Kelly, Hayes, Nichole, High, Frances, Hing, Anne, Hisama, Fuki M., Holm, Ingrid A., Hom, Jason, Horike-Pyne, Martha, Huang, Alden, Huang, Yong, Isasi, Rosario, Jamal, Fariha, Jarvik, Gail P., Jarvik, Jeffrey, Jayadev, Suman, Johnston, Jean M., Karaviti, Lefkothea, Kelley, Emily G., Kennedy, Jennifer, Kiley, Dana, Kohane, Isaac S., Kohler, Jennefer N., Krakow, Deborah, Krasnewich, Donna M., Kravets, Elijah, Korrick, Susan, Koziura, Mary, Krier, Joel B., Lalani, Seema R., Lam, Byron, Lam, Christina, Lanpher, Brendan C., Lanza, Ian R., Lau, C. Christopher, LeBlanc, Kimberly, Lee, Brendan H., Lee, Hane, Levitt, Roy, Lewis, Richard A., Lincoln, Sharyn A., Liu, Pengfei, Liu, Xue Zhong, Longo, Nicola, Loo, Sandra K., Loscalzo, Joseph, Maas, Richard L., Macnamara, Ellen F., MacRae, Calum A., Maduro, Valerie V., Majcherska, Marta M., Mak, Bryan, Malicdan, May Christine V., Mamounas, Laura A., Manolio, Teri A., Mao, Rong, Maravilla, Kenneth, Markello, Thomas C., Marom, Ronit, Marth, Gabor, Martin, Beth A., Martin, Martin G., Martínez-Agosto, Julian A., Marwaha, Shruti, McCauley, Jacob, McCormack, Colleen E., McCray, Alexa T., McGee, Elisabeth, Mefford, Heather, Merritt, J. Lawrence, Might, Matthew, Mirzaa, Ghayda, Morava, Eva, Moretti, Paolo M., Morimoto, Marie, Mulvihill, John J., Murdock, David R., Nakano-Okuno, Mariko, Nath, Avi, Nelson, Stan F., Newman, John H., Nicholas, Sarah K., Nickerson, Deborah, Nieves-Rodriguez, Shirley, Novacic, Donna, Oglesbee, Devin, Orengo, James P., Pace, Laura, Pak, Stephen, Pallais, J. Carl, Papp, Jeanette C., Parker, Neil H., Phillips, John A., Posey, Jennifer E., Potocki, Lorraine, Pusey, Barbara N., Quinlan, Aaron, Raskind, Wendy, Raja, Archana N., Rao, Deepak A., Renteria, Genecee, Reuter, Chloe M., Rives, Lynette, Robertson, Amy K., Rodan, Lance H., Rosenfeld, Jill A., Rosenwasser, Natalie, Ruzhnikov, Maura, Sacco, Ralph, Sampson, Jacinda B., Samson, Susan L., Saporta, Mario, Scott, C. Ron, Schaechter, Judy, Schedl, Timothy, Scott, Daryl A., Sharma, Prashant, Shin, Jimann, Signer, Rebecca, Sillari, Catherine H., Silverman, Edwin K., Sinsheimer, Janet S., Sisco, Kathy, Smith, Edward C., Smith, Kevin S., Solem, Emily, Solnica-Krezel, Lilianna, Stoler, Joan M., Stong, Nicholas, Sullivan, Jennifer A., Sun, Angela, Sutton, Shirley, Sweetser, David A., Sybert, Virginia, Tabor, Holly K., Tamburro, Cecelia P., Tekin, Mustafa, Telischi, Fred, Thorson, Willa, Tifft, Cynthia J., Toro, Camilo, Tran, Alyssa A., Tucker, Brianna M., Urv, Tiina K., Vanderver, Adeline, Velinder, Matt, Viskochil, Dave, Vogel, Tiphanie P., Wahl, Colleen E., Wallace, Stephanie, Walley, Nicole M., Walsh, Chris A., Walker, Melissa, Wambach, Jennifer, Wan, Jijun, Wang, Lee-Kai, Wangler, Michael F., Ward, Patricia A., Wegner, Daniel, Wener, Mark, Wenger, Tara, Perry, Katherine Wesseling, Westerfield, Monte, Wheeler, Matthew T., Whitlock, Jordan, Wolfe, Lynne A., Woods, Jeremy D., Yamamoto, Shinya, Yang, John, Yu, Guoyun, Zastrow, Diane B., Zhao, Chunli, Zuchner, Stephan, Jeffries, Lauren, Mis, Emily K., McWalter, Kirsty, Donkervoort, Sandra, Brodsky, Nina N., Carpier, Jean-Marie, Ji, Weizhen, Ionita, Cristian, Roy, Bhaskar, Morrow, Jon S., Darbinyan, Armine, Iyer, Krishna, Aul, Ritu B., Chao, Katherine R., Cobbold, Laura, Cohen, Stacey, Custodio, Helena M., Drummond-Borg, Margaret, Finanger, Erika, Hainline, Bryan E., Helbig, Ingo, Hewson, Stacy, Hu, Ying, Jackson, Adam, Konstantino, Monica, Leach, Meganne E., McCormick, David, Nelson, Stanley, Nguyen, Joanne, Nugent, Kimberly, Ortega, Lucy, Goodkin, Howard P., Roeder, Elizabeth, Roy, Sani, Sapp, Katie, Saade, Dimah, Sisodiya, Sanjay M., Stals, Karen, Towner, Shelley, Wilson, William, Khokha, Mustafa K., Bönnemann, Carsten G., Lucas, Carrie L., and Lakhani, Saquib A.

Published
2024
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36. A syndromic neurodevelopmental disorder caused by rare variants in PPFIA3

Author

Acosta, Maria T., Adam, Margaret, Adams, David R., Alvarez, Raquel L., Alvey, Justin, Amendola, Laura, Andrews, Ashley, Ashley, Euan A., Bacino, Carlos A., Bademci, Guney, Balasubramanyam, Ashok, Baldridge, Dustin, Bale, Jim, Bamshad, Michael, Barbouth, Deborah, Bayrak-Toydemir, Pinar, Beck, Anita, Beggs, Alan H., Behrens, Edward, Bejerano, Gill, Bellen, Hugo J., Bennett, Jimmy, Berg-Rood, Beverly, Bernstein, Jonathan A., Berry, Gerard T., Bican, Anna, Bivona, Stephanie, Blue, Elizabeth, Bohnsack, John, Bonner, Devon, Botto, Lorenzo, Boyd, Brenna, Briere, Lauren C., Brown, Gabrielle, Burke, Elizabeth A., Burrage, Lindsay C., Butte, Manish J., Byers, Peter, Byrd, William E., Carey, John, Carrasquillo, Olveen, Cassini, Thomas, Chang, Ta Chen Peter, Chanprasert, Sirisak, Chao, Hsiao-Tuan, Chinn, Ivan, Clark, Gary D., Coakley, Terra R., Cobban, Laurel A., Cogan, Joy D., Coggins, Matthew, Cole, F. Sessions, Colley, Heather A., Cope, Heidi, Corona, Rosario, Craigen, William J., Crouse, Andrew B., Cunningham, Michael, D’Souza, Precilla, Dai, Hongzheng, Dasari, Surendra, Davis, Joie, Dayal, Jyoti G., Dell'Angelica, Esteban C., Dipple, Katrina, Doherty, Daniel, Dorrani, Naghmeh, Doss, Argenia L., Douine, Emilie D., Earl, Dawn, Eckstein, David J., Emrick, Lisa T., Eng, Christine M., Falk, Marni, Fieg, Elizabeth L., Fisher, Paul G., Fogel, Brent L., Forghani, Irman, Gahl, William A., Glass, Ian, Gochuico, Bernadette, Goddard, Page C., Godfrey, Rena A., Golden-Grant, Katie, Grajewski, Alana, Hadley, Don, Hahn, Sihoun, Halley, Meghan C., Hamid, Rizwan, Hassey, Kelly, Hayes, Nichole, High, Frances, Hing, Anne, Hisama, Fuki M., Holm, Ingrid A., Hom, Jason, Horike-Pyne, Martha, Huang, Alden, Hutchison, Sarah, Introne, Wendy, Isasi, Rosario, Izumi, Kosuke, Jamal, Fariha, Jarvik, Gail P., Jarvik, Jeffrey, Jayadev, Suman, Jean-Marie, Orpa, Jobanputra, Vaidehi, Karaviti, Lefkothea, Ketkar, Shamika, Kiley, Dana, Kilich, Gonench, Kobren, Shilpa N., Kohane, Isaac S., Kohler, Jennefer N., Korrick, Susan, Kozuira, Mary, Krakow, Deborah, Krasnewich, Donna M., Kravets, Elijah, Lalani, Seema R., Lam, Byron, Lam, Christina, Lanpher, Brendan C., Lanza, Ian R., LeBlanc, Kimberly, Lee, Brendan H., Levitt, Roy, Lewis, Richard A., Liu, Pengfei, Liu, Xue Zhong, Longo, Nicola, Loo, Sandra K., Loscalzo, Joseph, Maas, Richard L., Macnamara, Ellen F., MacRae, Calum A., Maduro, Valerie V., Maghiro, Audrey Stephannie, Mahoney, Rachel, Malicdan, May Christine V., Mamounas, Laura A., Manolio, Teri A., Mao, Rong, Maravilla, Kenneth, Marom, Ronit, Marth, Gabor, Martin, Beth A., Martin, Martin G., Martínez-Agosto, Julian A., Marwaha, Shruti, McCauley, Jacob, McConkie-Rosell, Allyn, McCray, Alexa T., McGee, Elisabeth, Mefford, Heather, Merritt, J. Lawrence, Might, Matthew, Mirzaa, Ghayda, Morava, Eva, Moretti, Paolo, Mulvihill, John, Nakano-Okuno, Mariko, Nelson, Stanley F., Newman, John H., Nicholas, Sarah K., Nickerson, Deborah, Nieves-Rodriguez, Shirley, Novacic, Donna, Oglesbee, Devin, Orengo, James P., Pace, Laura, Pak, Stephen, Pallais, J. Carl, Palmer, Christina G.S., Papp, Jeanette C., Parker, Neil H., Phillips III, John A., Posey, Jennifer E., Potocki, Lorraine, Pusey Swerdzewski, Barbara N., Quinlan, Aaron, Rao, Deepak A., Raper, Anna, Raskind, Wendy, Renteria, Genecee, Reuter, Chloe M., Rives, Lynette, Robertson, Amy K., Rodan, Lance H., Rosenfeld, Jill A., Rosenwasser, Natalie, Rossignol, Francis, Ruzhnikov, Maura, Sacco, Ralph, Sampson, Jacinda B., Saporta, Mario, Schaechter, Judy, Schedl, Timothy, Schoch, Kelly, Scott, Daryl A., Scott, C. Ron, Seto, Elaine, Shashi, Vandana, Shin, Jimann, Silverman, Edwin K., Sinsheimer, Janet S., Sisco, Kathy, Smith, Edward C., Smith, Kevin S., Solnica-Krezel, Lilianna, Solomon, Ben, Spillmann, Rebecca C., Stoler, Joan M., Sullivan, Kathleen, Sullivan, Jennifer A., Sun, Angela, Sutton, Shirley, Sweetser, David A., Sybert, Virginia, Tabor, Holly K., Tan, Queenie K.-G., Tan, Amelia L.M., Tarakad, Arjun, Tekin, Mustafa, Telischi, Fred, Thorson, Willa, Tifft, Cynthia J., Toro, Camilo, Tran, Alyssa A., Ungar, Rachel A., Urv, Tiina K., Vanderver, Adeline, Velinder, Matt, Viskochil, Dave, Vogel, Tiphanie P., Wahl, Colleen E., Walker, Melissa, Wallace, Stephanie, Walley, Nicole M., Wambach, Jennifer, Wan, Jijun, Wang, Lee-kai, Wangler, Michael F., Ward, Patricia A., Wegner, Daniel, Weisz Hubshman, Monika, Wener, Mark, Wenger, Tara, Westerfield, Monte, Wheeler, Matthew T., Whitlock, Jordan, Wolfe, Lynne A., Worley, Kim, Xiao, Changrui, Yamamoto, Shinya, Yang, John, Zhang, Zhe, Zuchner, Stephan, Paul, Maimuna S., Michener, Sydney L., Pan, Hongling, Chan, Hiuling, Pfliger, Jessica M., Lerma, Vanesa C., Tran, Alyssa, Longley, Megan A., Weisz-Hubshman, Monika, Bekheirnia, Mir Reza, Bekheirnia, Nasim, Massingham, Lauren, Zech, Michael, Wagner, Matias, Engels, Hartmut, Cremer, Kirsten, Mangold, Elisabeth, Peters, Sophia, Trautmann, Jessica, Perne, Claudia, Mester, Jessica L., Guillen Sacoto, Maria J., Person, Richard, McDonnell, Pamela P., Cohen, Stacey R., Lusk, Laina, Cohen, Ana S.A., Le Pichon, Jean-Baptiste, Pastinen, Tomi, Zhou, Dihong, Engleman, Kendra, Racine, Caroline, Faivre, Laurence, Moutton, Sébastien, Denommé-Pichon, Anne-Sophie, Koh, Hyun Yong, Poduri, Annapurna, Bolton, Jeffrey, Knopp, Cordula, Julia Suh, Dong Sun, Maier, Andrea, Toosi, Mehran Beiraghi, Karimiani, Ehsan Ghayoor, Maroofian, Reza, Schaefer, Gerald Bradley, Ramakumaran, Vijayalakshmi, Vasudevan, Pradeep, Banos-Pinero, Benito, Pagnamenta, Alistair T., Prasad, Chitra, Osmond, Matthew, Schuhmann, Sarah, Vasileiou, Georgia, Russ-Hall, Sophie, Scheffer, Ingrid E., and Carvill, Gemma L.

Published
2024
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37. Potential pitfalls in the use of real-world data for studying long COVID

Author

Zhang, Harrison G., Honerlaw, Jacqueline P., Maripuri, Monika, Samayamuthu, Malarkodi Jebathilagam, Beaulieu-Jones, Brendin R., Baig, Huma S., L’Yi, Sehi, Ho, Yuk-Lam, Morris, Michele, Panickan, Vidul Ayakulangara, Wang, Xuan, Weber, Griffin M., Liao, Katherine P., Visweswaran, Shyam, Tan, Bryce W. Q., Yuan, William, Gehlenborg, Nils, Muralidhar, Sumitra, Ramoni, Rachel B., Kohane, Isaac S., Xia, Zongqi, Cho, Kelly, Cai, Tianxi, and Brat, Gabriel A.

Published
2023
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38. Copper chelation suppresses epithelial-mesenchymal transition by inhibition of canonical and non-canonical TGF-β signaling pathways in cancer

Author

Ensieh M. Poursani, Daniele Mercatelli, Prahlad Raninga, Jessica L. Bell, Federica Saletta, Felix V. Kohane, Daniel P. Neumann, Ye Zheng, Jourdin R. C. Rouaen, Toni Rose Jue, Filip T. Michniewicz, Piper Schadel, Erin Kasiou, Maria Tsoli, Giuseppe Cirillo, Shafagh Waters, Tyler Shai-Hee, Riccardo Cazzoli, Merryn Brettle, Iveta Slapetova, Maria Kasherman, Renee Whan, Fernando Souza-Fonseca-Guimaraes, Linda Vahdat, David Ziegler, John G. Lock, Federico M. Giorgi, KumKum Khanna, and Orazio Vittorio

Subjects
Cancer, Copper chelation, EMT, Metastasis, TGF-β signaling pathways, Biotechnology, TP248.13-248.65, Biology (General), QH301-705.5, Biochemistry, QD415-436
Abstract

Abstract Background Metastatic cancer cells exploit Epithelial-mesenchymal-transition (EMT) to enhance their migration, invasion, and resistance to treatments. Recent studies highlight that elevated levels of copper are implicated in cancer progression and metastasis. Clinical trials using copper chelators are associated with improved patient survival; however, the molecular mechanisms by which copper depletion inhibits tumor progression and metastasis are poorly understood. This remains a major hurdle to the clinical translation of copper chelators. Here, we propose that copper chelation inhibits metastasis by reducing TGF-β levels and EMT signaling. Given that many drugs targeting TGF-β have failed in clinical trials, partly because of severe side effects arising in patients, we hypothesized that copper chelation therapy might be a less toxic alternative to target the TGF-β/EMT axis. Results Our cytokine array and RNA-seq data suggested a link between copper homeostasis, TGF-β and EMT process. To validate this hypothesis, we performed single-cell imaging, protein assays, and in vivo studies. Here, we used the copper chelating agent TEPA to block copper trafficking. Our in vivo study showed a reduction of TGF-β levels and metastasis to the lung in the TNBC mouse model. Mechanistically, TEPA significantly downregulated canonical (TGF-β/SMAD2&3) and non-canonical (TGF-β/PI3K/AKT, TGF-β/RAS/RAF/MEK/ERK, and TGF-β/WNT/β-catenin) TGF-β signaling pathways. Additionally, EMT markers of MMP-9, MMP-14, Vimentin, β-catenin, ZEB1, and p-SMAD2 were downregulated, and EMT transcription factors of SNAI1, ZEB1, and p-SMAD2 accumulated in the cytoplasm after treatment. Conclusions Our study suggests that copper chelation therapy represents a potentially effective therapeutic approach for targeting TGF-β and inhibiting EMT in a diverse range of cancers.

Published
2023
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41. Copper chelation suppresses epithelial-mesenchymal transition by inhibition of canonical and non-canonical TGF-β signaling pathways in cancer

Author

Poursani, Ensieh M., Mercatelli, Daniele, Raninga, Prahlad, Bell, Jessica L., Saletta, Federica, Kohane, Felix V., Neumann, Daniel P., Zheng, Ye, Rouaen, Jourdin R. C., Jue, Toni Rose, Michniewicz, Filip T., Schadel, Piper, Kasiou, Erin, Tsoli, Maria, Cirillo, Giuseppe, Waters, Shafagh, Shai-Hee, Tyler, Cazzoli, Riccardo, Brettle, Merryn, Slapetova, Iveta, Kasherman, Maria, Whan, Renee, Souza-Fonseca-Guimaraes, Fernando, Vahdat, Linda, Ziegler, David, Lock, John G., Giorgi, Federico M., Khanna, KumKum, and Vittorio, Orazio

Published
2023
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43. Validation of an internationally derived patient severity phenotype to support COVID-19 analytics from electronic health record data

Author

Klann, Jeffrey G, Estiri, Hossein, Weber, Griffin M, Moal, Bertrand, Avillach, Paul, Hong, Chuan, Tan, Amelia LM, Beaulieu-Jones, Brett K, Castro, Victor, Maulhardt, Thomas, Geva, Alon, Malovini, Alberto, South, Andrew M, Visweswaran, Shyam, Morris, Michele, Samayamuthu, Malarkodi J, Omenn, Gilbert S, Ngiam, Kee Yuan, Mandl, Kenneth D, Boeker, Martin, Olson, Karen L, Mowery, Danielle L, Follett, Robert W, Hanauer, David A, Bellazzi, Riccardo, Moore, Jason H, Loh, Ne-Hooi Will, Bell, Douglas S, Wagholikar, Kavishwar B, Chiovato, Luca, Tibollo, Valentina, Rieg, Siegbert, Li, Anthony LLJ, Jouhet, Vianney, Schriver, Emily, Xia, Zongqi, Hutch, Meghan, Luo, Yuan, Kohane, Isaac S, EHR, The Consortium for Clinical Characterization of COVID-19 by, Brat, Gabriel A, and Murphy, Shawn N

Subjects
Health Services and Systems, Health Sciences, Patient Safety, HIV/AIDS, Good Health and Well Being, COVID-19, Electronic Health Records, Hospitalization, Humans, Machine Learning, Prognosis, ROC Curve, Sensitivity and Specificity, Severity of Illness Index, novel coronavirus, disease severity, computable phenotype, medical informatics, data networking, data interoperability, Consortium for Clinical Characterization of COVID-19 by EHR (4CE), Information and Computing Sciences, Engineering, Medical and Health Sciences, Medical Informatics, Biomedical and clinical sciences, Health sciences, Information and computing sciences
Abstract

ObjectiveThe Consortium for Clinical Characterization of COVID-19 by EHR (4CE) is an international collaboration addressing coronavirus disease 2019 (COVID-19) with federated analyses of electronic health record (EHR) data. We sought to develop and validate a computable phenotype for COVID-19 severity.Materials and methodsTwelve 4CE sites participated. First, we developed an EHR-based severity phenotype consisting of 6 code classes, and we validated it on patient hospitalization data from the 12 4CE clinical sites against the outcomes of intensive care unit (ICU) admission and/or death. We also piloted an alternative machine learning approach and compared selected predictors of severity with the 4CE phenotype at 1 site.ResultsThe full 4CE severity phenotype had pooled sensitivity of 0.73 and specificity 0.83 for the combined outcome of ICU admission and/or death. The sensitivity of individual code categories for acuity had high variability-up to 0.65 across sites. At one pilot site, the expert-derived phenotype had mean area under the curve of 0.903 (95% confidence interval, 0.886-0.921), compared with an area under the curve of 0.956 (95% confidence interval, 0.952-0.959) for the machine learning approach. Billing codes were poor proxies of ICU admission, with as low as 49% precision and recall compared with chart review.DiscussionWe developed a severity phenotype using 6 code classes that proved resilient to coding variability across international institutions. In contrast, machine learning approaches may overfit hospital-specific orders. Manual chart review revealed discrepancies even in the gold-standard outcomes, possibly owing to heterogeneous pandemic conditions.ConclusionsWe developed an EHR-based severity phenotype for COVID-19 in hospitalized patients and validated it at 12 international sites.

Published
2021

44. BioN∅T: A searchable database of biomedical negated sentences

Author

Agarwal Shashank, Yu Hong, and Kohane Issac

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Negated biomedical events are often ignored by text-mining applications; however, such events carry scientific significance. We report on the development of BioN∅T, a database of negated sentences that can be used to extract such negated events. Description Currently BioN∅T incorporates ≈32 million negated sentences, extracted from over 336 million biomedical sentences from three resources: ≈2 million full-text biomedical articles in Elsevier and the PubMed Central, as well as ≈20 million abstracts in PubMed. We evaluated BioN∅T on three important genetic disorders: autism, Alzheimer's disease and Parkinson's disease, and found that BioN∅T is able to capture negated events that may be ignored by experts. Conclusions The BioN∅T database can be a useful resource for biomedical researchers. BioN∅T is freely available at http://bionot.askhermes.org/. In future work, we will develop semantic web related technologies to enrich BioN∅T.

Published
2011
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45. Commonalities across computational workflows for uncovering explanatory variants in undiagnosed cases.

Author

Kobren, Shilpa Nadimpalli, Baldridge, Dustin, Velinder, Matt, Krier, Joel B, LeBlanc, Kimberly, Esteves, Cecilia, Pusey, Barbara N, Züchner, Stephan, Blue, Elizabeth, Lee, Hane, Huang, Alden, Bastarache, Lisa, Bican, Anna, Cogan, Joy, Marwaha, Shruti, Alkelai, Anna, Murdock, David R, Liu, Pengfei, Wegner, Daniel J, Paul, Alexander J, Undiagnosed Diseases Network, Sunyaev, Shamil R, and Kohane, Isaac S

Subjects
Undiagnosed Diseases Network, Humans, Computational Biology, Genomics, Genome, Software, Genetic Testing, Workflow, Undiagnosed Diseases, Genetics, Human Genome, Genetics & Heredity, Clinical Sciences
Abstract

PurposeGenomic sequencing has become an increasingly powerful and relevant tool to be leveraged for the discovery of genetic aberrations underlying rare, Mendelian conditions. Although the computational tools incorporated into diagnostic workflows for this task are continually evolving and improving, we nevertheless sought to investigate commonalities across sequencing processing workflows to reveal consensus and standard practice tools and highlight exploratory analyses where technical and theoretical method improvements would be most impactful.MethodsWe collected details regarding the computational approaches used by a genetic testing laboratory and 11 clinical research sites in the United States participating in the Undiagnosed Diseases Network via meetings with bioinformaticians, online survey forms, and analyses of internal protocols.ResultsWe found that tools for processing genomic sequencing data can be grouped into four distinct categories. Whereas well-established practices exist for initial variant calling and quality control steps, there is substantial divergence across sites in later stages for variant prioritization and multimodal data integration, demonstrating a diversity of approaches for solving the most mysterious undiagnosed cases.ConclusionThe largest differences across diagnostic workflows suggest that advances in structural variant detection, noncoding variant interpretation, and integration of additional biomedical data may be especially promising for solving chronically undiagnosed cases.

Published
2021

46. An aptamer-based depot system for sustained release of small molecule therapeutics

Author

Dali Wang, Yang Li, Xiaoran Deng, Matthew Torre, Zipei Zhang, Xiyu Li, Wei Zhang, Kathleen Cullion, Daniel S. Kohane, and Christopher B. Weldon

Subjects
Science
Abstract

Abstract Delivery of hydrophilic small molecule therapeutics by traditional drug delivery systems is challenging. Herein, we have used the specific interaction between DNA aptamers and drugs to create simple and effective drug depot systems. The specific binding of a phosphorothioate-modified aptamer to drugs formed non-covalent aptamer/drug complexes, which created a sustained release system. We demonstrated the effectiveness of this system with small hydrophilic molecules, the site 1 sodium channel blockers tetrodotoxin and saxitoxin. The aptamer-based delivery system greatly prolonged the duration of local anesthesia and reduced systemic toxicity. The beneficial effects of the aptamers were restricted to the compounds they were specific to. These studies establish aptamers as a class of highly specific, modifiable drug delivery systems, and demonstrate potential usefulness in the management of postoperative pain.

Published
2023
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47. Calculating the return on investment of mobile healthcare

Author

Bennet Jennifer, Vavasis Anthony P, Cote Paul J, Oriol Nancy E, DeLorenzo Darien, Blanc Philip, and Kohane Isaac

Subjects
Medicine
Abstract

Abstract Background Mobile health clinics provide an alternative portal into the healthcare system for the medically disenfranchised, that is, people who are underinsured, uninsured or who are otherwise outside of mainstream healthcare due to issues of trust, language, immigration status or simply location. Mobile health clinics as providers of last resort are an essential component of the healthcare safety net providing prevention, screening, and appropriate triage into mainstream services. Despite the face value of providing services to underserved populations, a focused analysis of the relative value of the mobile health clinic model has not been elucidated. The question that the return on investment algorithm has been designed to answer is: can the value of the services provided by mobile health programs be quantified in terms of quality adjusted life years saved and estimated emergency department expenditures avoided? Methods Using a sample mobile health clinic and published research that quantifies health outcomes, we developed and tested an algorithm to calculate the return on investment of a typical broad-service mobile health clinic: the relative value of mobile health clinic services = annual projected emergency department costs avoided + value of potential life years saved from the services provided. Return on investment ratio = the relative value of the mobile health clinic services/annual cost to run the mobile health clinic. Results Based on service data provided by The Family Van for 2008 we calculated the annual cost savings from preventing emergency room visits, $3,125,668 plus the relative value of providing 7 of the top 25 priority prevention services during the same period, US$17,780,000 for a total annual value of $20,339,968. Given that the annual cost to run the program was $567,700, the calculated return on investment of The Family Van was 36:1. Conclusion By using published data that quantify the value of prevention practices and the value of preventing unnecessary use of emergency departments, an empirical method was developed to determine the value of a typical mobile health clinic. The Family Van, a mobile health clinic that has been serving the medically disenfranchised of Boston for 16 years, was evaluated accordingly and found to have return on investment of $36 for every $1 invested in the program.

Published
2009
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48. Genomics Research with Undiagnosed Children: Ethical Challenges at the Boundaries of Research and Clinical Care

Author

Acosta, Maria T., Adam, Margaret, Adams, David R., Alvarez, Raquel L., Alvey, Justin, Amendola, Laura, Andrews, Ashley, Bacino, Carlos A., Bademci, Guney, Balasubramanyam, Ashok, Baldridge, Dustin, Bale, Jim, Bamshad, Michael, Barbouth, Deborah, Bayrak-Toydemir, Pinar, Beck, Anita, Beggs, Alan H., Behrens, Edward, Bejerano, Gill, Bellen, Hugo J., Bennett, Jimmy, Berg-Rood, Beverly, Bernstein, Jonathan A., Berry, Gerard T., Bican, Anna, Bivona, Stephanie, Blue, Elizabeth, Bohnsack, John, Bonner, Devon, Botto, Lorenzo, Boyd, Brenna, Briere, Lauren C., Brown, Gabrielle, Burke, Elizabeth A., Burrage, Lindsay C., Butte, Manish J., Byers, Peter, Byrd, William E., Carey, John, Carrasquillo, Olveen, Cassini, Thomas, Peter Chang, Ta Chen, Chanprasert, Sirisak, Chao, Hsiao-Tuan, Chinn, Ivan, Clark, Gary D., Coakley, Terra R., Cobban, Laurel A., Cogan, Joy D., Coggins, Matthew, Sessions Cole, F., Colley, Heather A., Cope, Heidi, Corona, Rosario, Craigen, William J., Crouse, Andrew B., Cunningham, Michael, D'Souza, Precilla, Dai, Hongzheng, Dasari, Surendra, Davis, Joie, Dayal, Jyoti G., Dell'Angelica, Esteban C., Dickson, Patricia, Dipple, Katrina, Doherty, Daniel, Dorrani, Naghmeh, Doss, Argenia L., Douine, Emilie D., Earl, Dawn, Eckstein, David J., Emrick, Lisa T., Eng, Christine M., Falk, Marni, Fieg, Elizabeth L., Fisher, Paul G., Fogel, Brent L., Forghani, Irman, Gahl, William A., Glass, Ian, Gochuico, Bernadette, Goddard, Page C., Godfrey, Rena A., Golden-Grant, Katie, Grajewski, Alana, Hadley, Don, Hahn, Sihoun, Hamid, Rizwan, Hassey, Kelly, Hayes, Nichole, High, Frances, Hing, Anne, Hisama, Fuki M., Holm, Ingrid A., Hom, Jason, Horike-Pyne, Martha, Huang, Alden, Hutchison, Sarah, Introne, Wendy, Isasi, Rosario, Izumi, Kosuke, Jarvik, Gail P., Jarvik, Jeffrey, Jayadev, Suman, Jean-Marie, Orpa, Jobanputra, Vaidehi, Ketkar, Shamika, Kiley, Dana, Kilich, Gonench, Kobren, Shilpa N., Kohane, Isaac S., Kohler, Jennefer N., Korrick, Susan, Kozuira, Mary, Krakow, Deborah, Krasnewich, Donna M., Kravets, Elijah, Lalani, Seema R., Lam, Byron, Lam, Christina, Lanpher, Brendan C., Lanza, Ian R., LeBlanc, Kimberly, Lee, Brendan H., Levitt, Roy, Lewis, Richard A., Liu, Pengfei, Liu, Xue Zhong, Longo, Nicola, Loo, Sandra K., Loscalzo, Joseph, Maas, Richard L., Macnamara, Ellen F., MacRae, Calum A., Maduro, Valerie V., Mahoney, Rachel, Malicdan, May Christine V., Mamounas, Laura A., Manolio, Teri A., Mao, Rong, Maravilla, Kenneth, Marom, Ronit, Marth, Gabor, Martin, Beth A., Martin, Martin G., Martínez-Agosto, Julian A., Marwaha, Shruti, McCauley, Jacob, McConkie-Rosell, Allyn, McCray, Alexa T., McGee, Elisabeth, Mefford, Heather, Merritt, J. Lawrence, Might, Matthew, Mirzaa, Ghayda, Morava, Eva, Moretti, Paolo, Mulvihill, John J., Nakano-Okuno, Mariko, Nelson, Stanley F., Newman, John H., Nickerson, Deborah, Nieves-Rodriguez, Shirley, Novacic, Donna, Oglesbee, Devin, Orengo, James P., Pace, Laura, Pak, Stephen, Carl Pallais, J., Palmer, Christina G.S., Papp, Jeanette C., Parker, Neil H., Phillips, John A., III, Posey, Jennifer E., Potocki, Lorraine, Pusey Swerdzewski, Barbara N., Quinlan, Aaron, Rao, Deepak A., Raper, Anna, Raskind, Wendy, Renteria, Genecee, Reuter, Chloe M., Rives, Lynette, Robertson, Amy K., Rodan, Lance H., Rosenfeld, Jill A., Rosenwasser, Natalie, Rossignol, Francis, Ruzhnikov, Maura, Sacco, Ralph, Sampson, Jacinda B., Saporta, Mario, Schaechter, Judy, Schedl, Timothy, Schoch, Kelly, Scott, Daryl A., Scott, C. Ron, Seto, Elaine, Shashi, Vandana, Shin, Jimann, Silverman, Edwin K., Sinsheimer, Janet S., Sisco, Kathy, Smith, Edward C., Smith, Kevin S., Solnica-Krezel, Lilianna, Solomon, Ben, Spillmann, Rebecca C., Stoler, Joan M., Sullivan, Kathleen, Sullivan, Jennifer A., Sun, Angela, Sutton, Shirley, Sweetser, David A., Sybert, Virginia, Tan, Queenie K.-G., Tan, Amelia L.M., Tarakad, Arjun, Tekin, Mustafa, Telischi, Fred, Thorson, Willa, Tifft, Cynthia J., Toro, Camilo, Tran, Alyssa A., Ungar, Rachel A., Urv, Tiina K., Vanderver, Adeline, Velinder, Matt, Viskochil, Dave, Vogel, Tiphanie P., Wahl, Colleen E., Walker, Melissa, Wallace, Stephanie, Walley, Nicole M., Wambach, Jennifer, Wan, Jijun, Wang, Lee-kai, Wangler, Michael F., Ward, Patricia A., Wegner, Daniel, Hubshman, Monika Weisz, Wener, Mark, Wenger, Tara, Westerfield, Monte, Wheeler, Matthew T., Whitlock, Jordan, Wolfe, Lynne A., Worley, Kim, Xiao, Changrui, Yamamoto, Shinya, Yang, John, Zhang, Zhe, Zuchner, Stephan, Halley, Meghan C., Young, Jennifer L., Tang, Charis, Mintz, Kevin T., Lucas-Griffin, Sawyer, Maghiro, AudreyStephannie, Ashley, Euan A., and Tabor, Holly K.

Published
2023
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49. Clinical phenotypes and outcomes in children with multisystem inflammatory syndrome across SARS-CoV-2 variant eras: a multinational study from the 4CE consortium

Author

Aaron, James R., Adam, Atif, Agapito, Giuseppe, Albayrak, Adem, Albi, Giuseppe, Alessiani, Mario, Alloni, Anna, Amendola, Danilo F., Angoulvant, François, Anthony, Li LLJ., Aronow, Bruce J., Ashraf, Fatima, Atz, Andrew, Avillach, Paul, Panickan, Vidul Ayakulangara, Azevedo, Paula S., Badenes, Rafael, Balshi, James, Batugo, Ashley, Beaulieu-Jones, Brendin R., Beaulieu-Jones, Brett K., Bell, Douglas S., Bellasi, Antonio, Bellazzi, Riccardo, Benoit, Vincent, Beraghi, Michele, Bernal-Sobrino, José Luis, Bernaux, Mélodie, Bey, Romain, Bhatnagar, Surbhi, Blanco-Martínez, Alvar, Boeker, Martin, Bonzel, Clara-Lea, Booth, John, Bosari, Silvano, Bourgeois, Florence T., Bradford, Robert L., Brat, Gabriel A., Bréant, Stéphane, Brown, Nicholas W., Bruno, Raffaele, Bryant, William A., Bucalo, Mauro, Bucholz, Emily, Burgun, Anita, Cai, Tianxi, Cannataro, Mario, Carmona, Aldo, Cattelan, Anna Maria, Caucheteux, Charlotte, Champ, Julien, Chen, Jin, Chen, Krista Y., Chiovato, Luca, Chiudinelli, Lorenzo, Cho, Kelly, Cimino, James J., Colicchio, Tiago K., Cormont, Sylvie, Cossin, Sébastien, Craig, Jean B., Cruz-Bermúdez, Juan Luis, Cruz-Rojo, Jaime, Dagliati, Arianna, Daniar, Mohamad, Daniel, Christel, Das, Priyam, Devkota, Batsal, Dionne, Audrey, Duan, Rui, Dubiel, Julien, DuVall, Scott L., Esteve, Loic, Estiri, Hossein, Fan, Shirley, Follett, Robert W., Ganslandt, Thomas, García-Barrio, Noelia, Garmire, Lana X., Gehlenborg, Nils, Getzen, Emily J., Geva, Alon, Goh, Rachel SJ., González, Tomás González, Gradinger, Tobias, Gramfort, Alexandre, Griffier, Romain, Griffon, Nicolas, Grisel, Olivier, Gutiérrez-Sacristán, Alba, Guzzi, Pietro H., Han, Larry, Hanauer, David A., Haverkamp, Christian, Hazard, Derek Y., He, Bing, Henderson, Darren W., Hilka, Martin, Ho, Yuk-Lam, Holmes, John H., Honerlaw, Jacqueline P., Hong, Chuan, Huling, Kenneth M., Hutch, Meghan R., Issitt, Richard W., Jannot, Anne Sophie, Jouhet, Vianney, Kainth, Mundeep K., Kate, Kernan F., Kavuluru, Ramakanth, Keller, Mark S., Kennedy, Chris J., Kernan, Kate F., Key, Daniel A., Kirchoff, Katie, Klann, Jeffrey G., Kohane, Isaac S., Krantz, Ian D., Kraska, Detlef, Krishnamurthy, Ashok K., L'Yi, Sehi, Leblanc, Judith, Lemaitre, Guillaume, Lenert, Leslie, Leprovost, Damien, Liu, Molei, Will Loh, Ne Hooi, Long, Qi, Lozano-Zahonero, Sara, Luo, Yuan, Lynch, Kristine E., Mahmood, Sadiqa, Maidlow, Sarah E., Makoudjou, Adeline, Makwana, Simran, Malovini, Alberto, Mandl, Kenneth D., Mao, Chengsheng, Maram, Anupama, Maripuri, Monika, Martel, Patricia, Martins, Marcelo R., Marwaha, Jayson S., Masino, Aaron J., Mazzitelli, Maria, Mazzotti, Diego R., Mensch, Arthur, Milano, Marianna, Minicucci, Marcos F., Moal, Bertrand, Ahooyi, Taha Mohseni, Moore, Jason H., Moraleda, Cinta, Morris, Jeffrey S., Morris, Michele, Moshal, Karyn L., Mousavi, Sajad, Mowery, Danielle L., Murad, Douglas A., Murphy, Shawn N., Naughton, Thomas P., Breda Neto, Carlos Tadeu, Neuraz, Antoine, Newburger, Jane, Ngiam, Kee Yuan, Njoroge, Wanjiku FM., Norman, James B., Obeid, Jihad, Okoshi, Marina P., Olson, Karen L., Omenn, Gilbert S., Orlova, Nina, Ostasiewski, Brian D., Palmer, Nathan P., Paris, Nicolas, Patel, Lav P., Pedrera-Jiménez, Miguel, Pfaff, Ashley C., Pfaff, Emily R., Pillion, Danielle, Pizzimenti, Sara, Priya, Tanu, Prokosch, Hans U., Prudente, Robson A., Prunotto, Andrea, Quirós-González, Víctor, Ramoni, Rachel B., Raskin, Maryna, Rieg, Siegbert, Roig-Domínguez, Gustavo, Rojo, Pablo, Romero-Garcia, Nekane, Rubio-Mayo, Paula, Sacchi, Paolo, Sáez, Carlos, Salamanca, Elisa, Samayamuthu, Malarkodi Jebathilagam, Sanchez-Pinto, L. Nelson, Sandrin, Arnaud, Santhanam, Nandhini, Santos, Janaina C.C., Sanz Vidorreta, Fernando J., Savino, Maria, Schriver, Emily R., Schubert, Petra, Schuettler, Juergen, Scudeller, Luigia, Sebire, Neil J., Serrano-Balazote, Pablo, Serre, Patricia, Serret-Larmande, Arnaud, Shah, Mohsin A., Hossein Abad, Zahra Shakeri, Silvio, Domenick, Sliz, Piotr, Son, Jiyeon, Sonday, Charles, South, Andrew M., Sperotto, Francesca, Spiridou, Anastasia, Strasser, Zachary H., Tan, Amelia LM., Tan, Bryce W.Q., Tan, Byorn W.L., Tanni, Suzana E., Taylor, Deanne M., Terriza-Torres, Ana I., Tibollo, Valentina, Tippmann, Patric, Toh, Emma MS., Torti, Carlo, Trecarichi, Enrico M., Vallejos, Andrew K., Varoquaux, Gael, Vella, Margaret E., Verdy, Guillaume, Vie, Jill-Jênn, Visweswaran, Shyam, Vitacca, Michele, Wagholikar, Kavishwar B., Waitman, Lemuel R., Wang, Xuan, Wassermann, Demian, Weber, Griffin M., Wolkewitz, Martin, Wong, Scott, Xia, Zongqi, Xiong, Xin, Ye, Ye, Yehya, Nadir, Yuan, William, Zachariasse, Joany M., Zahner, Janet J., Zambelli, Alberto, Zhang, Harrison G., Zöller, Daniela, Zuccaro, Valentina, Zucco, Chiara, Li, Xiudi, Rofeberg, Valerie N., Elias, Matthew D., Laird-Gion, Jessica, and Newburger, Jane W.

Published
2023
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50. Characterization of long COVID temporal sub-phenotypes by distributed representation learning from electronic health record data: a cohort study

Author

Aaron, James R., Agapito, Giuseppe, Albayrak, Adem, Albi, Giuseppe, Alessiani, Mario, Alloni, Anna, Amendola, Danilo F., François Angoulvant, Anthony, Li L.L.J., Aronow, Bruce J., Ashraf, Fatima, Atz, Andrew, Avillach, Paul, Azevedo, Paula S., Balshi, James, Beaulieu-Jones, Brett K., Bell, Douglas S., Bellasi, Antonio, Bellazzi, Riccardo, Benoit, Vincent, Beraghi, Michele, Bernal-Sobrino, José Luis, Bernaux, Mélodie, Bey, Romain, Bhatnagar, Surbhi, Blanco-Martínez, Alvar, Bonzel, Clara-Lea, Booth, John, Bosari, Silvano, Bourgeois, Florence T., Bradford, Robert L., Brat, Gabriel A., Bréant, Stéphane, Brown, Nicholas W., Bruno, Raffaele, Bryant, William A., Bucalo, Mauro, Bucholz, Emily, Burgun, Anita, Cai, Tianxi, Cannataro, Mario, Carmona, Aldo, Caucheteux, Charlotte, Champ, Julien, Chen, Jin, Chen, Krista Y., Chiovato, Luca, Chiudinelli, Lorenzo, Cho, Kelly, Cimino, James J., Colicchio, Tiago K., Cormont, Sylvie, Cossin, Sébastien, Craig, Jean B., Cruz-Bermúdez, Juan Luis, Cruz-Rojo, Jaime, Dagliati, Arianna, Daniar, Mohamad, Daniel, Christel, Das, Priyam, Devkota, Batsal, Dionne, Audrey, Duan, Rui, Dubiel, Julien, DuVall, Scott L., Esteve, Loic, Estiri, Hossein, Fan, Shirley, Follett, Robert W., Ganslandt, Thomas, Barrio, Noelia García, Garmire, Lana X., Gehlenborg, Nils, Getzen, Emily J., Geva, Alon, Gradinger, Tobias, Gramfort, Alexandre, Griffier, Romain, Griffon, Nicolas, Grisel, Olivier, Gutiérrez-Sacristán, Alba, Han, Larry, Hanauer, David A., Haverkamp, Christian, Hazard, Derek Y., He, Bing, Henderson, Darren W., Hilka, Martin, Ho, Yuk-Lam, Holmes, John H., Hong, Chuan, Huling, Kenneth M., Hutch, Meghan R., Issitt, Richard W., Jannot, Anne Sophie, Jouhet, Vianney, Kavuluru, Ramakanth, Keller, Mark S., Kennedy, Chris J., Key, Daniel A., Kirchoff, Katie, Klann, Jeffrey G., Kohane, Isaac S., Krantz, Ian D., Kraska, Detlef, Krishnamurthy, Ashok K., L'Yi, Sehi, Le, Trang T., Leblanc, Judith, Lemaitre, Guillaume, Lenert, Leslie, Leprovost, Damien, Liu, Molei, Will Loh, Ne Hooi, Long, Qi, Lozano-Zahonero, Sara, Luo, Yuan, Lynch, Kristine E., Mahmood, Sadiqa, Maidlow, Sarah E., Makoudjou, Adeline, Malovini, Alberto, Mandl, Kenneth D., Mao, Chengsheng, Maram, Anupama, Martel, Patricia, Martins, Marcelo R., Marwaha, Jayson S., Masino, Aaron J., Mazzitelli, Maria, Mensch, Arthur, Milano, Marianna, Minicucci, Marcos F., Moal, Bertrand, Ahooyi, Taha Mohseni, Moore, Jason H., Moraleda, Cinta, Morris, Jeffrey S., Morris, Michele, Moshal, Karyn L., Mousavi, Sajad, Mowery, Danielle L., Murad, Douglas A., Murphy, Shawn N., Naughton, Thomas P., Breda Neto, Carlos Tadeu, Neuraz, Antoine, Newburger, Jane, Ngiam, Kee Yuan, Njoroge, Wanjiku F.M., Norman, James B., Obeid, Jihad, Okoshi, Marina P., Olson, Karen L., Omenn, Gilbert S., Orlova, Nina, Ostasiewski, Brian D., Palmer, Nathan P., Paris, Nicolas, Patel, Lav P., Pedrera-Jiménez, Miguel, Pfaff, Emily R., Pfaff, Ashley C., Pillion, Danielle, Pizzimenti, Sara, Prokosch, Hans U., Prudente, Robson A., Prunotto, Andrea, Quirós-González, Víctor, Ramoni, Rachel B., Raskin, Maryna, Rieg, Siegbert, Roig-Domínguez, Gustavo, Rojo, Pablo, Rubio-Mayo, Paula, Sacchi, Paolo, Sáez, Carlos, Salamanca, Elisa, Samayamuthu, Malarkodi Jebathilagam, Sanchez-Pinto, L. Nelson, Sandrin, Arnaud, Santhanam, Nandhini, Santos, Janaina C.C., Sanz Vidorreta, Fernando J., Savino, Maria, Schriver, Emily R., Schubert, Petra, Schuettler, Juergen, Scudeller, Luigia, Sebire, Neil J., Serrano-Balazote, Pablo, Serre, Patricia, Serret-Larmande, Arnaud, Shah, Mohsin, Hossein Abad, Zahra Shakeri, Silvio, Domenick, Sliz, Piotr, Son, Jiyeon, Sonday, Charles, South, Andrew M., Spiridou, Anastasia, Strasser, Zachary H., Tan, Amelia L.M., Tan, Bryce W.Q., Tan, Byorn W.L., Tanni, Suzana E., Taylor, Deanne M., Terriza-Torres, Ana I., Tibollo, Valentina, Tippmann, Patric, Toh, Emma M.S., Torti, Carlo, Trecarichi, Enrico M., Tseng, Yi-Ju, Vallejos, Andrew K., Varoquaux, Gael, Vella, Margaret E., Verdy, Guillaume, Vie, Jill-Jênn, Visweswaran, Shyam, Vitacca, Michele, Wagholikar, Kavishwar B., Waitman, Lemuel R., Wang, Xuan, Wassermann, Demian, Weber, Griffin M., Wolkewitz, Martin, Wong, Scott, Xia, Zongqi, Xiong, Xin, Ye, Ye, Yehya, Nadir, Yuan, William, Zambelli, Alberto, Zhang, Harrison G., Zo¨ller, Daniela, Zuccaro, Valentina, Zucco, Chiara, Mesa, Rebecca, and Verdy, Guillame

Published
2023
Full Text
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