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

Author: Leora I Horwitz, Tanayott Thaweethai, Shari B Brosnahan, Mine S Cicek, Megan L Fitzgerald, Jason D Goldman, Rachel Hess, S L Hodder, Vanessa L Jacoby, Michael R Jordan, Jerry A Krishnan, Adeyinka O Laiyemo, Torri D Metz, Lauren Nichols, Rachel E Patzer, Anisha Sekar, Nora G Singer, Lauren E Stiles, Barbara S Taylor, Shifa Ahmed, Heather A Algren, Khamal Anglin, Lisa Aponte-Soto, Hassan Ashktorab, Ingrid V Bassett, Brahmchetna Bedi, Nahid Bhadelia, Christian Bime, Marie-Abele C Bind, Lora J Black, Andra L Blomkalns, Hassan Brim, Mario Castro, James Chan, Alexander W Charney, Benjamin K Chen, Li Qing Chen, Peter Chen, David Chestek, Lori B Chibnik, Dominic C Chow, Helen Y Chu, Rebecca G Clifton, Shelby Collins, Maged M Costantine, Sushma K Cribbs, Steven G Deeks, John D Dickinson, Sarah E Donohue, Matthew S Durstenfeld, Ivette F Emery, Kristine M Erlandson, Julio C Facelli, Rachael Farah-Abraham, Aloke V Finn, Melinda S Fischer, Valerie J Flaherman, Judes Fleurimont, Vivian Fonseca, Emily J Gallagher, Jennifer C Gander, Maria Laura Gennaro, Kelly S Gibson, Minjoung Go, Steven N Goodman, Joey P Granger, Frank L Greenway, John W Hafner, Jenny E Han, Michelle S Harkins, Kristine S P Hauser, James R Heath, Carla R Hernandez, On Ho, Matthew K Hoffman, Susan E Hoover, Carol R Horowitz, Harvey Hsu, Priscilla Y Hsue, Brenna L Hughes, Prasanna Jagannathan, Judith A James, Janice John, Sarah Jolley, S E Judd, Joy J Juskowich, Diane G Kanjilal, Elizabeth W Karlson, Stuart D Katz, J Daniel Kelly, Sara W Kelly, Arthur Y Kim, John P Kirwan, Kenneth S Knox, Andre Kumar, Michelle F Lamendola-Essel, Margaret Lanca, Joyce K Lee-Lannotti, R Craig Lefebvre, Bruce D Levy, Janet Y Lin, Brian P Logarbo, Jennifer K Logue, Michele T Longo, Carlos A Luciano, Karen Lutrick, Shahdi K Malakooti, Gail Mallett, Gabrielle Maranga, Jai G Marathe, Vincent C Marconi, Gailen D Marshall, Christopher F Martin, Jeffrey N Martin, Heidi T May, Grace A McComsey, Dylan McDonald, Hector Mendez-Figueroa, Lucio Miele, Murray A Mittleman, Sindhu Mohandas, Christian Mouchati, Janet M Mullington, Girish N Nadkarni, Erica R Nahin, Robert B Neuman, Lisa T Newman, Amber Nguyen, Janko Z Nikolich, Igho Ofotokun, Princess U Ogbogu, Anna Palatnik, Kristy T S Palomares, Tanyalak Parimon, Samuel Parry, Sairam Parthasarathy, Thomas F Patterson, Ann Pearman, Michael J Peluso, Priscilla Pemu, Christian M Pettker, Beth A Plunkett, Kristen Pogreba-Brown, Athena Poppas, J Zachary Porterfield, John G Quigley, Davin K Quinn, Hengameh Raissy, Candida J Rebello, Uma M Reddy, Rebecca Reece, Harrison T Reeder, Franz P Rischard, Johana M Rosas, Clifford J Rosen, Nadine G Rouphael, Dwight J Rouse, Adam M Ruff, Christina Saint Jean, Grecio J Sandoval, Jorge L Santana, Shannon M Schlater, Frank C Sciurba, Caitlin Selvaggi, Sudha Seshadri, Howard D Sesso, Dimpy P Shah, Eyal Shemesh, Zaki A Sherif, Daniel J Shinnick, Hyagriv N Simhan, Upinder Singh, Amber Sowles, Vignesh Subbian, Jun Sun, Mehul S Suthar, Larissa J Teunis, John M Thorp, Amberly Ticotsky, Alan T N Tita, Robin Tragus, Katherine R Tuttle, Alfredo E Urdaneta, P J Utz, Timothy M VanWagoner, Andrew Vasey, Suzanne D Vernon, Crystal Vidal, Tiffany Walker, Honorine D Ward, David E Warren, Ryan M Weeks, Steven J Weiner, Jordan C Weyer, Jennifer L Wheeler, Sidney W Whiteheart, Zanthia Wiley, Natasha J Williams, Juan P Wisnivesky, John C Wood, Lynn M Yee, Natalie M Young, Sokratis N Zisis, and Andrea S Foulkes
Subjects: Medicine, Science
Abstract: ImportanceSARS-CoV-2 infection can result in ongoing, relapsing, or new symptoms or other health effects after the acute phase of infection; termed post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID. The characteristics, prevalence, trajectory and mechanisms of PASC are ill-defined. The objectives of the Researching COVID to Enhance Recovery (RECOVER) Multi-site Observational Study of PASC in Adults (RECOVER-Adult) are to: (1) characterize PASC prevalence; (2) characterize the symptoms, organ dysfunction, natural history, and distinct phenotypes of PASC; (3) identify demographic, social and clinical risk factors for PASC onset and recovery; and (4) define the biological mechanisms underlying PASC pathogenesis.MethodsRECOVER-Adult is a combined prospective/retrospective cohort currently planned to enroll 14,880 adults aged ≥18 years. Eligible participants either must meet WHO criteria for suspected, probable, or confirmed infection; or must have evidence of no prior infection. Recruitment occurs at 86 sites in 33 U.S. states, Washington, DC and Puerto Rico, via facility- and community-based outreach. Participants complete quarterly questionnaires about symptoms, social determinants, vaccination status, and interim SARS-CoV-2 infections. In addition, participants contribute biospecimens and undergo physical and laboratory examinations at approximately 0, 90 and 180 days from infection or negative test date, and yearly thereafter. Some participants undergo additional testing based on specific criteria or random sampling. Patient representatives provide input on all study processes. The primary study outcome is onset of PASC, measured by signs and symptoms. A paradigm for identifying PASC cases will be defined and updated using supervised and unsupervised learning approaches with cross-validation. Logistic regression and proportional hazards regression will be conducted to investigate associations between risk factors, onset, and resolution of PASC symptoms.DiscussionRECOVER-Adult is the first national, prospective, longitudinal cohort of PASC among US adults. Results of this study are intended to inform public health, spur clinical trials, and expand treatment options.RegistrationNCT05172024.
Published: 2023
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2. Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative.

Author: Guillaume Butler-Laporte, Gundula Povysil, Jack A Kosmicki, Elizabeth T Cirulli, Theodore Drivas, Simone Furini, Chadi Saad, Axel Schmidt, Pawel Olszewski, Urszula Korotko, Mathieu Quinodoz, Elifnaz Çelik, Kousik Kundu, Klaudia Walter, Junghyun Jung, Amy D Stockwell, Laura G Sloofman, Daniel M Jordan, Ryan C Thompson, Diane Del Valle, Nicole Simons, Esther Cheng, Robert Sebra, Eric E Schadt, Seunghee Kim-Schulze, Sacha Gnjatic, Miriam Merad, Joseph D Buxbaum, Noam D Beckmann, Alexander W Charney, Bartlomiej Przychodzen, Timothy Chang, Tess D Pottinger, Ning Shang, Fabian Brand, Francesca Fava, Francesca Mari, Karolina Chwialkowska, Magdalena Niemira, Szymon Pula, J Kenneth Baillie, Alex Stuckey, Antonio Salas, Xabier Bello, Jacobo Pardo-Seco, Alberto Gómez-Carballa, Irene Rivero-Calle, Federico Martinón-Torres, Andrea Ganna, Konrad J Karczewski, Kumar Veerapen, Mathieu Bourgey, Guillaume Bourque, Robert Jm Eveleigh, Vincenzo Forgetta, David Morrison, David Langlais, Mark Lathrop, Vincent Mooser, Tomoko Nakanishi, Robert Frithiof, Michael Hultström, Miklos Lipcsey, Yanara Marincevic-Zuniga, Jessica Nordlund, Kelly M Schiabor Barrett, William Lee, Alexandre Bolze, Simon White, Stephen Riffle, Francisco Tanudjaja, Efren Sandoval, Iva Neveux, Shaun Dabe, Nicolas Casadei, Susanne Motameny, Manal Alaamery, Salam Massadeh, Nora Aljawini, Mansour S Almutairi, Yaseen M Arabi, Saleh A Alqahtani, Fawz S Al Harthi, Amal Almutairi, Fatima Alqubaishi, Sarah Alotaibi, Albandari Binowayn, Ebtehal A Alsolm, Hadeel El Bardisy, Mohammad Fawzy, Fang Cai, Nicole Soranzo, Adam Butterworth, COVID-19 Host Genetics Initiative, DeCOI Host Genetics Group, GEN-COVID Multicenter Study (Italy), Mount Sinai Clinical Intelligence Center, GEN-COVID consortium (Spain), GenOMICC Consortium, Japan COVID-19 Task Force, Regeneron Genetics Center, Daniel H Geschwind, Stephanie Arteaga, Alexis Stephens, Manish J Butte, Paul C Boutros, Takafumi N Yamaguchi, Shu Tao, Stefan Eng, Timothy Sanders, Paul J Tung, Michael E Broudy, Yu Pan, Alfredo Gonzalez, Nikhil Chavan, Ruth Johnson, Bogdan Pasaniuc, Brian Yaspan, Sandra Smieszek, Carlo Rivolta, Stephanie Bibert, Pierre-Yves Bochud, Maciej Dabrowski, Pawel Zawadzki, Mateusz Sypniewski, Elżbieta Kaja, Pajaree Chariyavilaskul, Voraphoj Nilaratanakul, Nattiya Hirankarn, Vorasuk Shotelersuk, Monnat Pongpanich, Chureerat Phokaew, Wanna Chetruengchai, Katsushi Tokunaga, Masaya Sugiyama, Yosuke Kawai, Takanori Hasegawa, Tatsuhiko Naito, Ho Namkoong, Ryuya Edahiro, Akinori Kimura, Seishi Ogawa, Takanori Kanai, Koichi Fukunaga, Yukinori Okada, Seiya Imoto, Satoru Miyano, Serghei Mangul, Malak S Abedalthagafi, Hugo Zeberg, Joseph J Grzymski, Nicole L Washington, Stephan Ossowski, Kerstin U Ludwig, Eva C Schulte, Olaf Riess, Marcin Moniuszko, Miroslaw Kwasniewski, Hamdi Mbarek, Said I Ismail, Anurag Verma, David B Goldstein, Krzysztof Kiryluk, Alessandra Renieri, Manuel A R Ferreira, and J Brent Richards
Subjects: Genetics, QH426-470
Abstract: Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75-10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.
Published: 2022
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3. Association of SARS-CoV-2 viral load at admission with in-hospital acute kidney injury: A retrospective cohort study.

Author: Ishan Paranjpe, Kumardeep Chaudhary, Kipp W Johnson, Suraj K Jaladanki, Shan Zhao, Jessica K De Freitas, Elisabet Pujdas, Fayzan Chaudhry, Erwin P Bottinger, Matthew A Levin, Zahi A Fayad, Alexander W Charney, Jane Houldsworth, Carlos Cordon-Cardo, Benjamin S Glicksberg, and Girish N Nadkarni
Subjects: Medicine, Science
Abstract: BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the associated Coronavirus Disease 2019 (COVID-19) is a public health emergency. Acute kidney injury (AKI) is a common complication in hospitalized patients with COVID-19 although mechanisms underlying AKI are yet unclear. There may be a direct effect of SARS-CoV-2 virus on the kidney; however, there is currently no data linking SARS-CoV-2 viral load (VL) to AKI. We explored the association of SARS-CoV-2 VL at admission to AKI in a large diverse cohort of hospitalized patients with COVID-19.Methods and findingsWe included patients hospitalized between March 13th and May 19th, 2020 with SARS-CoV-2 in a large academic healthcare system in New York City (N = 1,049) with available VL at admission quantified by real-time RT-PCR. We extracted clinical and outcome data from our institutional electronic health records (EHRs). AKI was defined by KDIGO guidelines. We fit a Fine-Gray competing risks model (with death as a competing risk) using demographics, comorbidities, admission severity scores, and log10 transformed VL as covariates and generated adjusted hazard ratios (aHR) and 95% Confidence Intervals (CIs). VL was associated with an increased risk of AKI (aHR = 1.04, 95% CI: 1.01-1.08, p = 0.02) with a 4% increased hazard for each log10 VL change. Patients with a viral load in the top 50th percentile had an increased adjusted hazard of 1.27 (95% CI: 1.02-1.58, p = 0.03) for AKI as compared to those in the bottom 50th percentile.ConclusionsVL is weakly but significantly associated with in-hospital AKI after adjusting for confounders. This may indicate the role of VL in COVID-19 associated AKI. This data may inform future studies to discover the mechanistic basis of COVID-19 associated AKI.
Published: 2021
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4. Retrospective cohort study of clinical characteristics of 2199 hospitalised patients with COVID-19 in New York City

Author: Girish N Nadkarni, Zahi A Fayad, Benjamin S Glicksberg, David L Reich, Prem Timsina, Arash Kia, Patricia Kovatch, Jessica K De Freitas, Paul O’Reilly, Allan Just, Dennis Charney, Ishan Paranjpe, Ross O'Hagan, Adam J Russak, Anuradha Lala, Riccardo Miotto, Akhil Vaid, Kipp W Johnson, Matteo Danieletto, Eddye Golden, Dara Meyer, Manbir Singh, Sulaiman Somani, Arjun Kapoor, Sayan Manna, Udit Nangia, Suraj K Jaladanki, Laura M Huckins, Patricia Glowe, Robert M Freeman, Matthew A Levin, Jeffrey Jhang, Adolfo Firpo, Joseph Finkelstein, Judith A Aberg, Emilia Bagiella, Carol R Horowitz, Barbara Murphy, Jagat Narula, Eric J Nestler, V Fuster, Carlos Cordon-Cardo, Erwin P Bottinger, and Alexander W Charney
Subjects: Medicine
Abstract: Objective The COVID-19 pandemic is a global public health crisis, with over 33 million cases and 999 000 deaths worldwide. Data are needed regarding the clinical course of hospitalised patients, particularly in the USA. We aimed to compare clinical characteristic of patients with COVID-19 who had in-hospital mortality with those who were discharged alive.Design Demographic, clinical and outcomes data for patients admitted to five Mount Sinai Health System hospitals with confirmed COVID-19 between 27 February and 2 April 2020 were identified through institutional electronic health records. We performed a retrospective comparative analysis of patients who had in-hospital mortality or were discharged alive.Setting All patients were admitted to the Mount Sinai Health System, a large quaternary care urban hospital system.Participants Participants over the age of 18 years were included.Primary outcomes We investigated in-hospital mortality during the study period.Results A total of 2199 patients with COVID-19 were hospitalised during the study period. As of 2 April, 1121 (51%) patients remained hospitalised, and 1078 (49%) completed their hospital course. Of the latter, the overall mortality was 29%, and 36% required intensive care. The median age was 65 years overall and 75 years in those who died. Pre-existing conditions were present in 65% of those who died and 46% of those discharged. In those who died, the admission median lymphocyte percentage was 11.7%, D-dimer was 2.4 μg/mL, C reactive protein was 162 mg/L and procalcitonin was 0.44 ng/mL. In those discharged, the admission median lymphocyte percentage was 16.6%, D-dimer was 0.93 μg/mL, C reactive protein was 79 mg/L and procalcitonin was 0.09 ng/mL.Conclusions In our cohort of hospitalised patients, requirement of intensive care and mortality were high. Patients who died typically had more pre-existing conditions and greater perturbations in inflammatory markers as compared with those who were discharged.
Published: 2020
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5. Genetic Overlap Between Alzheimer’s Disease and Bipolar Disorder Implicates the MARK2 and VAC14 Genes

Author: Ole Kristian Drange, Olav Bjerkehagen Smeland, Alexey A. Shadrin, Per Ivar Finseth, Aree Witoelar, Oleksandr Frei, Psychiatric Genomics Consortium Bipolar Disorder Working Group, Yunpeng Wang, Sahar Hassani, Srdjan Djurovic, Anders M. Dale, Ole A. Andreassen, Eli A Stahl, Gerome Breen, Andreas J Forstner, Andrew McQuillin, Stephan Ripke, Vassily Trubetskoy, Manuel Mattheisen, Jonathan R I Coleman, Heìleìna A Gaspar, Christiaan A de Leeuw, Stacy Steinberg, Jennifer M Whitehead Pavlides, Maciej Trzaskowski, Tune H Pers, Peter A Holmans, Liam Abbott, Esben Agerbo, Huda Akil, Diego Albani, Ney Alliey-Rodriguez, Thomas D Als, Adebayo Anjorin, Verneri Antilla, Swapnil Awasthi, Judith A Badner, Marie Bækvad-Hansen, Jack D Barchas, Nicholas Bass, Michael Bauer, Richard Belliveau, Sarah E Bergen, Carsten Bøcker Pedersen, Erlend Bøen, Marco Boks, James Boocock, Monika Budde, William Bunney, Margit Burmeister, Jonas Bybjerg-Grauholm, William Byerley, Miquel Casas, Felecia Cerrato, Pablo Cervantes, Kimberly Chambert, Alexander W Charney, Danfeng Chen, Claire Churchhouse, Toni-Kim Clarke, William Coryell, David W Craig, Cristiana Cruceanu, David Curtis, Piotr M Czerski, Anders M Dale, Simone de Jong, Franziska Degenhardt, Jurgen Del-Favero, J Raymond DePaulo, Amanda L Dobbyn, Ashley Dumont, Torbjørn Elvsåshagen, Valentina Escott-Price, Chun Chieh Fan, Sascha B Fischer, Matthew Flickinger, Tatiana M Foroud, Liz Forty, Josef Frank, Christine Fraser, Nelson B Freimer, Louise Friseìn, Katrin Gade, Diane Gage, Julie Garnham, Claudia Giambartolomei, Marianne Giørtz Pedersen, Jaqueline Goldstein, Scott D Gordon, Katherine Gordon-Smith, Elaine K Green, Melissa J Green, Tiffany A Greenwood, Jakob Grove, Weihua Guan, Joseì Guzman Parra, Marian L Hamshere, Martin Hautzinger, Urs Heilbronner, Stefan Herms, Maria Hipolito, Per Hoffmann, Dominic Holland, Laura Huckins, Steìphane Jamain, Jessica S Johnson, Anders Jureìus, Radhika Kandaswamy, Robert Karlsson, James L Kennedy, Sarah Kittel-Schneider, Sarah V Knott, James A Knowles, Manolis Kogevinas, Anna C Koller, Ralph Kupka, Catharina Lavebratt, Jacob Lawrence, William B Lawson, Markus Leber, Phil H Lee, Shawn E Levy, Jun Z Li, Chunyu Liu, Susanne Lucae, Anna Maaser, Donald J MacIntyre, Pamela B Mahon, Wolfgang Maier, Lina Martinsson, Steve McCarroll, Peter McGuffin, Melvin G McInnis, James D McKay, Helena Medeiros, Sarah E Medland, Fan Meng, Lili Milani, Grant W Montgomery, Derek W Morris, Thomas W Mühleisen, Niamh Mullins, Hoang Nguyen, Caroline M Nievergelt, Annelie Nordin Adolfsson, Evaristus A Nwulia, Claire O’Donovan, Loes M Olde Loohuis, Anil P S Ori, Lilijana Oruc, Urban Ösby, Roy H Perlis, Amy Perry, Andrea Pfennig, James B Potash, Shaun M Purcell, Eline J Regeer, Andreas Reif, Ceìline S Reinbold, John P Rice, Fabio Rivas, Margarita Rivera, Panos Roussos, Douglas M Ruderfer, Euijung Ryu, Cristina Saìnchez-Mora, Alan F Schatzberg, William A Scheftner, Nicholas J Schork, Cynthia Shannon Weickert, Tatyana Shehktman, Paul D Shilling, Engilbert Sigurdsson, Claire Slaney, Olav B Smeland, Janet L Sobell, Christine Søholm Hansen, Anne T Spijker, David St Clair, Michael Steffens, John S Strauss, Fabian Streit, Jana Strohmaier, Szabolcs Szelinger, Robert C Thompson, Thorgeir E Thorgeirsson, Jens Treutlein, Helmut Vedder, Weiqing Wang, Stanley J Watson, Thomas W Weickert, Stephanie H Witt, Simon Xi, Wei Xu, Allan H Young, Peter Zandi, Peng Zhang, Sebastian Zollner, Rolf Adolfsson, Ingrid Agartz, Martin Alda, Lena Backlund, Bernhard T Baune, Frank Bellivier, Wade H Berrettini, Joanna M Biernacka, Douglas H R Blackwood, Michael Boehnke, Anders D Børglum, Aiden Corvin, Nicholas Craddock, Mark J Daly, Udo Dannlowski, ToÞnu Esko, Bruno Etain, Mark Frye, Janice M Fullerton, Elliot S Gershon, Michael Gill, Fernando Goes, Maria Grigoroiu-Serbanescu, Joanna Hauser, David M Hougaard, Christina M Hultman, Ian Jones, Lisa A Jones, Reneì S Kahn, George Kirov, Mikael Landeìn, Marion Leboyer, Cathryn M Lewis, Qingqin S Li, Jolanta Lissowska, Nicholas G Martin, Fermin Mayoral, Susan L McElroy, Andrew M McIntosh, Francis J McMahon, Ingrid Melle, Andres Metspalu, Philip B Mitchell, Gunnar Morken, Ole Mors, Preben Bo Mortensen, Bertram Müller-Myhsok, Richard M Myers, Benjamin M Neale, Vishwajit Nimgaonkar, Merete Nordentoft, Markus M Nöthen, Michael C O’Donovan, Ketil J Oedegaard, Michael J Owen, Sara A Paciga, Carlos Pato, Michele T Pato, Danielle Posthuma, Josep Antoni Ramos-Quiroga, Marta Ribaseìs, Marcella Rietschel, Guy A Rouleau, Martin Schalling, Peter R Schofield, Thomas G Schulze, Alessandro Serretti, Jordan W Smoller, Hreinn Stefansson, Kari Stefansson, Eystein Stordal, Patrick F Sullivan, Gustavo Turecki, Arne E Vaaler, Eduard Vieta, John B Vincent, Thomas Werge, John I Nurnberger, Naomi R Wray, Arianna Di Florio, Howard J Edenberg, Sven Cichon, Roel A Ophoff, Laura J Scott, Ole A Andreassen, John Kelsoe, and Pamela Sklar
Subjects: Alzheimer’s disease, bipolar disorder, GWAS, pleiotropy, cognitive symptoms, affective symptoms, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Background: Alzheimer’s disease (AD) and bipolar disorder (BIP) are complex traits influenced by numerous common genetic variants, most of which remain to be detected. Clinical and epidemiological evidence suggest that AD and BIP are related. However, it is not established if this relation is of genetic origin. Here, we applied statistical methods based on the conditional false discovery rate (FDR) framework to detect genetic overlap between AD and BIP and utilized this overlap to increase the power to identify common genetic variants associated with either or both traits.Methods: We obtained genome wide association studies data from the International Genomics of Alzheimer’s Project part 1 (17,008 AD cases and 37,154 controls) and the Psychiatric Genetic Consortium Bipolar Disorder Working Group (20,352 BIP cases and 31,358 controls). We used conditional QQ-plots to assess overlap in common genetic variants between AD and BIP. We exploited the genetic overlap to re-rank test-statistics for AD and BIP and improve detection of genetic variants using the conditional FDR framework.Results: Conditional QQ-plots demonstrated a polygenic overlap between AD and BIP. Using conditional FDR, we identified one novel genomic locus associated with AD, and nine novel loci associated with BIP. Further, we identified two novel loci jointly associated with AD and BIP implicating the MARK2 gene (lead SNP rs10792421, conjunctional FDR = 0.030, same direction of effect) and the VAC14 gene (lead SNP rs11649476, conjunctional FDR = 0.022, opposite direction of effect).Conclusion: We found polygenic overlap between AD and BIP and identified novel loci for each trait and two jointly associated loci. Further studies should examine if the shared loci implicating the MARK2 and VAC14 genes could explain parts of the shared and distinct features of AD and BIP.
Published: 2019
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6. A translational genomics approach identifies IL10RB as the top candidate gene target for COVID-19 susceptibility

Author: Georgios Voloudakis, James M. Vicari, Sanan Venkatesh, Gabriel E. Hoffman, Kristina Dobrindt, Wen Zhang, Noam D. Beckmann, Christina A. Higgins, Stathis Argyriou, Shan Jiang, Daisy Hoagland, Lina Gao, André Corvelo, Kelly Cho, Kyung Min Lee, Jiantao Bian, Jennifer S. Lee, Sudha K. Iyengar, Shiuh-Wen Luoh, Schahram Akbarian, Robert Striker, Themistocles L. Assimes, Eric E. Schadt, Julie A. Lynch, Miriam Merad, Benjamin R. tenOever, Alexander W. Charney, Mount Sinai COVID-19 Biobank, VA Million Veteran Program COVID-19 Science Initiative, Kristen J. Brennand, John F. Fullard, and Panos Roussos
Subjects: Medicine, Genetics, QH426-470
Abstract: Abstract Recent efforts have identified genetic loci that are associated with coronavirus disease 2019 (COVID-19) infection rates and disease outcome severity. Translating these genetic findings into druggable genes that reduce COVID-19 host susceptibility is a critical next step. Using a translational genomics approach that integrates COVID-19 genetic susceptibility variants, multi-tissue genetically regulated gene expression (GReX), and perturbagen signatures, we identified IL10RB as the top candidate gene target for COVID-19 host susceptibility. In a series of validation steps, we show that predicted GReX upregulation of IL10RB and higher IL10RB expression in COVID-19 patient blood is associated with worse COVID-19 outcomes and that in vitro IL10RB overexpression is associated with increased viral load and activation of disease-relevant molecular pathways.
Published: 2022
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7. Impact of Vaccination on Major Adverse Cardiovascular Events in Patients With COVID-19 Infection

Author: Joy Jiang, Lili Chan, Justin Kauffman, Jagat Narula, Alexander W. Charney, Wonsuk Oh, and Girish Nadkarni
Subjects: Cardiology and Cardiovascular Medicine
Published: 2023
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8. The importance of social activity to risk of major depression in older adults

Author: Alexander W. Charney, Myrna M. Weissman, Euijung Ryu, Brandon J. Coombes, Lauren Lepow, Benjamin S. Glicksberg, Joanna M. Biernacka, Priya Wickramaratne, Mark Olfson, J. John Mann, Gregory D. Jenkins, Ardesheer Talati, Yanshan Wang, and Jyotishman Pathak
Subjects: Gerontology, Proportional hazards model, business.industry, Social activity, Hazard ratio, medicine.disease, Biobank, Psychiatry and Mental health, Cohort, medicine, Major depressive disorder, Social determinants of health, business, Applied Psychology, Depression (differential diagnoses)
Abstract: BackgroundSeveral social determinants of health (SDoH) have been associated with the onset of major depressive disorder (MDD). However, prior studies largely focused on individual SDoH and thus less is known about the relative importance (RI) of SDoH variables, especially in older adults. Given that risk factors for MDD may differ across the lifespan, we aimed to identify the SDoH that was most strongly related to newly diagnosed MDD in a cohort of older adults.MethodsWe used self-reported health-related survey data from 41 174 older adults (50–89 years, median age = 67 years) who participated in the Mayo Clinic Biobank, and linked ICD codes for MDD in the participants' electronic health records. Participants with a history of clinically documented or self-reported MDD prior to survey completion were excluded from analysis (N = 10 938, 27%). We used Cox proportional hazards models with a gradient boosting machine approach to quantify the RI of 30 pre-selected SDoH variables on the risk of future MDD diagnosis.ResultsFollowing biobank enrollment, 2073 older participants were diagnosed with MDD during the follow-up period (median duration = 6.7 years). The most influential SDoH was perceived level of social activity (RI = 0.17). Lower level of social activity was associated with a higher risk of MDD [hazard ratio = 2.27 (95% CI 2.00–2.50) for highest v. lowest level].ConclusionAcross a range of SDoH variables, perceived level of social activity is most strongly related to MDD in older adults. Monitoring changes in the level of social activity may help identify older adults at an increased risk of MDD.
Published: 2023

9. Quantitative prediction of right ventricular and size and function from the electrocardiogram

Author: Son Q. Duong, Akhil Vaid, Ha My Thi Vy, Liam R. Butler, Joshua Lampert, Robert H. Pass, Alexander W. Charney, Jagat Narula, Rohan Khera, Hayit Greenspan, Bruce D. Gelb, Ron Do, and Girish Nadkarni
Subjects: Article
Abstract: BackgroundRight ventricular ejection fraction (RVEF) and end-diastolic volume (RVEDV) are not readily assessed through traditional modalities. Deep-learning enabled 12-lead electrocardiogram analysis (DL-ECG) for estimation of RV size or function is unexplored.MethodsWe trained a DL-ECG model to predict RV dilation (RVEDV>120 mL/m2), RV dysfunction (RVEF<40%), and numerical RVEDV/RVEF from 12-lead ECG paired with reference-standard cardiac MRI (cMRI) volumetric measurements in UK biobank (UKBB; n=42,938). We fine-tuned in a multi-center health system (MSHoriginal; n=3,019) with prospective validation over 4 months (MSHvalidation; n=115). We evaluated performance using area under the receiver operating curve (AUROC) for categorical and mean absolute error (MAE) for continuous measures overall and in key subgroups. We assessed association of RVEF prediction with transplant-free survival with Cox proportional hazards models.ResultsPrevalence of RV dysfunction for UKBB/MSHoriginal/MSHvalidationcohorts was 1.0%/18.0%/15.7%, respectively. RV dysfunction model AUROC for UKBB/MSHoriginal/MSHvalidationcohorts was 0.86/0.81/0.77, respectively. Prevalence of RV dilation for UKBB/MSHoriginal/MSHvalidationcohorts was 1.6%/10.6%/4.3%. RV dilation model AUROC for UKBB/MSHoriginal/MSHvalidationcohorts 0.91/0.81/0.92, respectively. MSHoriginalMAE was RVEF=7.8% and RVEDV=17.6 ml/m2. Performance was similar in key subgroups including with and without left ventricular dysfunction. Over median follow-up of 2.3 years, predicted RVEF was independently associated with composite outcome (HR 1.37 for each 10% decrease, p=0.046).ConclusionsDL-ECG analysis can accurately identify significant RV dysfunction and dilation both overall and in key subgroups. Predicted RVEF is independently associated with clinical outcome.
Published: 2023

10. A study of gene expression in the living human brain

Author: Lora E. Liharska, You Jeong Park, Kimia Ziafat, Lillian Wilkins, Hannah Silk, Lisa M. Linares, Ryan C. Thompson, Eric Vornholt, Brendan Sullivan, Vanessa Cohen, Prashant Kota, Claudia Feng, Esther Cheng, Jessica S. Johnson, Marysia-Kolbe Rieder, Jia Huang, Joseph Scarpa, Jairo Polanco, Emily Moya, Alice Hashemi, Jaroslav Bendl, Gabriel E. Hoffman, Panos Roussos, Matthew A. Levin, Girish N. Nadkarni, Robert Sebra, John Crary, Pamela Sklar, Eric E. Schadt, Noam D. Beckmann, Brian H. Kopell, and Alexander W. Charney
Subjects: Article
Abstract: A central goal of neuroscience is to advance knowledge of the molecular basis of human brain function. Most molecular studies of the human brain have been performed using tissue from postmortem brain donors rather than living people. The assumption underlying this practice – which had never been rigorously tested prior to this report – is that the postmortem human brain is an appropriate proxy for the living human brain at the molecular level. Here, this assumption is thoroughly challenged for the first time by comparing human prefrontal cortex gene expression between 275 living samples and 243 postmortem samples. Vast differences in gene expression were found between the living and postmortem human brain. Expression levels differed significantly for nearly 80% of genes, and this finding was not a consequence of any potential technical or biological confounders of the gene expression data. Postmortem brain gene expression signatures of Alzheimer’s disease, schizophrenia, Parkinson’s disease, bipolar disorder, and autism spectrum disorder were shown to be inaccurate representations of disease processes occurring in the living brain. In light of these findings, the use of postmortem tissue as a proxy for living tissue in human brain research should be reconsidered. To advance knowledge of the molecular basis of human brain function, the study of tissue from living people should be prioritized.
Published: 2023
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11. Immersion Fixation and Staining of Multicubic Millimeter Volumes for Electron Microscopy–Based Connectomics of Human Brain Biopsies

Author: Neha Karlupia, Richard L. Schalek, Yuelong Wu, Yaron Meirovitch, Donglai Wei, Alexander W. Charney, Brian H. Kopell, and Jeff W. Lichtman
Subjects: Biological Psychiatry
Published: 2023
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12. Predictive Approaches for Acute Dialysis Requirement and Death in COVID-19

Author: Adam Russak, Lili Chan, Alexander W. Charney, Matthew A. Levin, Benjamin S. Glicksberg, Prem Timsina, Ishan Paranjpe, Suraj K. Jaladanki, Erwin P. Bottinger, Arash Kia, John Cijiang He, Girish N. Nadkarni, Akhil Vaid, Zahi A. Fayad, Steven G. Coca, and Kumardeep Chaudhary
Subjects: 0301 basic medicine, medicine.medical_specialty, Epidemiology, medicine.medical_treatment, 030232 urology & nephrology, Vital signs, Critical Care and Intensive Care Medicine, Logistic regression, Machine Learning, 03 medical and health sciences, 0302 clinical medicine, Renal Dialysis, Humans, Medicine, Imputation (statistics), Dialysis, Transplantation, Receiver operating characteristic, SARS-CoV-2, business.industry, COVID-19, Red blood cell distribution width, Original Articles, Acute Kidney Injury, Hospitalization, 030104 developmental biology, Nephrology, Cohort, Emergency medicine, business, Complication
Abstract: Background and objectives AKI treated with dialysis initiation is a common complication of coronavirus disease 2019 (COVID-19) among hospitalized patients. However, dialysis supplies and personnel are often limited. Design, setting, participants, & measurements Using data from adult patients hospitalized with COVID-19 from five hospitals from the Mount Sinai Health System who were admitted between March 10 and December 26, 2020, we developed and validated several models (logistic regression, Least Absolute Shrinkage and Selection Operator (LASSO), random forest, and eXtreme GradientBoosting [XGBoost; with and without imputation]) for predicting treatment with dialysis or death at various time horizons (1, 3, 5, and 7 days) after hospital admission. Patients admitted to the Mount Sinai Hospital were used for internal validation, whereas the other hospitals formed part of the external validation cohort. Features included demographics, comorbidities, and laboratory and vital signs within 12 hours of hospital admission. Results A total of 6093 patients (2442 in training and 3651 in external validation) were included in the final cohort. Of the different modeling approaches used, XGBoost without imputation had the highest area under the receiver operating characteristic (AUROC) curve on internal validation (range of 0.93–0.98) and area under the precision-recall curve (AUPRC; range of 0.78–0.82) for all time points. XGBoost without imputation also had the highest test parameters on external validation (AUROC range of 0.85–0.87, and AUPRC range of 0.27–0.54) across all time windows. XGBoost without imputation outperformed all models with higher precision and recall (mean difference in AUROC of 0.04; mean difference in AUPRC of 0.15). Features of creatinine, BUN, and red cell distribution width were major drivers of the model’s prediction. Conclusions An XGBoost model without imputation for prediction of a composite outcome of either death or dialysis in patients positive for COVID-19 had the best performance, as compared with standard and other machine learning models. Podcast This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2021_07_09_CJN17311120.mp3
Published: 2021
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13. Phenotype-by-phenome-wide association study of treatment resistant depression

Author: Brandon J Coombes, Jorge A Sanchez Ruiz, Brian Fennessy, Vanessa Pazdernik, Prakash Adekkanattu, Nicolas A Nunez, Lauren Lepow, Euijung Ryu, Ardesheer Talati, Greg D Jenkins, Richard Pendegraft, Priya Wickramaratne, J John Mann, Mark Olfson, Myrna M Weissman, Jyotishman Pathak, Alexander W Charney, and Joanna M Biernacka
Abstract: ObjectiveTreatment-resistant depression (TRD), defined as inadequate response to at least one or at least two antidepressant (AD) trials, is common in major depressive disorder (MDD). In this study, electronic health records (EHR) were used to identify clinical associations with TRD.MethodsUsing two biobanks, phenomes of patients with at least one MDD-related diagnostic code and one AD prescription (N=17,049) were generated using aggregated diagnostic codes (phecodes) from EHRs. Phenotype-by-phenome-wide association analyses were performed for two binary definitions of TRD, based on either one or more, or two or more, AD switches after at least 30 days but within 14 weeks, and a quantitative measure defined as the number of unique ADs prescribed for at least 30 days.ResultsOf the 17,049 patients with MDD, 1624 (9.5%) had at least one switch, 422 (2.5%) had at least two switches, and the number of unique antidepressant prescriptions ranged from one to twelve. After accounting for multiple testing, 142, 18, and 7 phecodes were significantly associated with the quantitative definition and the two binary definitions (≥1 AD switch or ≥2 AD switches), respectively. All three outcomes were significantly associated with known TRD risk factors including anxiety disorders, insomnia, and suicidal ideation. The quantitative measure was uniquely associated with other conditions including irritable bowel syndrome and decreased white blood cell count.ConclusionsIn addition to identifying known clinical associations, the quantitative measure of treatment resistance uncovered new factors potentially associated with TRD. This measure may also facilitate discovery of genetic correlates of TRD in future analyses.
Published: 2022
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14. Automated Determination of Left Ventricular Function Using Electrocardiogram Data in Patients on Maintenance Hemodialysis

Author: Akhil Vaid, Joy J. Jiang, Ashwin Sawant, Karandeep Singh, Patricia Kovatch, Alexander W. Charney, David M. Charytan, Jasmin Divers, Benjamin S. Glicksberg, Lili Chan, and Girish N. Nadkarni
Subjects: Transplantation, Electrocardiography, Nephrology, Epidemiology, Echocardiography, Renal Dialysis, Humans, Original Article, Stroke Volume, Critical Care and Intensive Care Medicine, Ventricular Function, Left
Abstract: BACKGROUND AND OBJECTIVES: Left ventricular ejection fraction is disrupted in patients on maintenance hemodialysis and can be estimated using deep learning models on electrocardiograms. Smaller sample sizes within this population may be mitigated using transfer learning. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: We identified patients on hemodialysis with transthoracic echocardiograms within 7 days of electrocardiogram using diagnostic/procedure codes. We developed four models: (1) trained from scratch in patients on hemodialysis, (2) pretrained on a publicly available set of natural images (ImageNet), (3) pretrained on all patients not on hemodialysis, and (4) pretrained on patients not on hemodialysis and fine-tuned on patients on hemodialysis. We assessed the ability of the models to classify left ventricular ejection fraction into clinically relevant categories of ≤40%, 41% to ≤50%, and >50%. We compared performance by area under the receiver operating characteristic curve. RESULTS: We extracted 705,075 electrocardiogram:echocardiogram pairs for 158,840 patients not on hemodialysis used for development of models 3 and 4 and n=18,626 electrocardiogram:echocardiogram pairs for 2168 patients on hemodialysis for models 1, 2, and 4. The transfer learning model achieved area under the receiver operating characteristic curves of 0.86, 0.63, and 0.83 in predicting left ventricular ejection fraction categories of ≤40% (n=461), 41%–50% (n=398), and >50% (n=1309), respectively. For the same tasks, model 1 achieved area under the receiver operating characteristic curves of 0.74, 0.55, and 0.71, respectively; model 2 achieved area under the receiver operating characteristic curves of 0.71, 0.55, and 0.69, respectively, and model 3 achieved area under the receiver operating characteristic curves of 0.80, 0.51, and 0.77, respectively. We found that predictions of left ventricular ejection fraction by the transfer learning model were associated with mortality in a Cox regression with an adjusted hazard ratio of 1.29 (95% confidence interval, 1.04 to 1.59). CONCLUSION: A deep learning model can determine left ventricular ejection fraction for patients on hemodialysis following pretraining on electrocardiograms of patients not on hemodialysis. Predictions of low ejection fraction from this model were associated with mortality over a 5-year follow-up period. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_06_06_CJN16481221.mp3
Published: 2022

15. A streamlined whole blood <scp>CyTOF</scp> workflow defines a circulating immune cell signature of <scp>COVID</scp> ‐19

Author: Geoffrey Kelly, Edgar Gonzalez-Kozlova, Manon Herbinet, Diana Handler, Brian T. Lee, Seunghee Kim-Schulze, Bhaskar Upadhyaya, Adeeb Rahman, Sacha Gnjatic, Daniel Geanon, Diane Marie Del Valle, John Leech, Assaf Magen, Miriam Merad, Alexander W. Charney, and Ronaldo de Real
Subjects: Adult, Male, mass cytometry, 0301 basic medicine, Histology, Coronavirus disease 2019 (COVID-19), Computer science, human whole blood immunophenotyping, Cell Separation, Computational biology, Immune monitoring, Severity of Illness Index, Immunophenotyping, Workflow, Pathology and Forensic Medicine, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Immune system, Predictive Value of Tests, COVID‐19, High-Throughput Screening Assays, Leukocytes, Humans, Mass cytometry, Aged, Whole blood, Aged, 80 and over, SARS-CoV-2, COVID-19, Original Articles, Cell Biology, Middle Aged, Flow Cytometry, 030104 developmental biology, Case-Control Studies, 030220 oncology & carcinogenesis, Host-Pathogen Interactions, Female, Original Article, CyTOF, Sample collection, Biomarkers
Abstract: Mass cytometry (CyTOF) represents one of the most powerful tools in immune phenotyping, allowing high throughput quantification of over 40 parameters at single‐cell resolution. However, wide deployment of CyTOF‐based immune phenotyping studies are limited by complex experimental workflows and the need for specialized CyTOF equipment and technical expertise. Furthermore, differences in cell isolation and enrichment protocols, antibody reagent preparation, sample staining, and data acquisition protocols can all introduce technical variation that can confound integrative analyses of large data‐sets of samples processed across multiple labs. Here, we present a streamlined whole blood CyTOF workflow which addresses many of these sources of experimental variation and facilitates wider adoption of CyTOF immune monitoring across sites with limited technical expertise or sample‐processing resources or equipment. Our workflow utilizes commercially available reagents including the Fluidigm MaxPar Direct Immune Profiling Assay (MDIPA), a dry tube 30‐marker immunophenotyping panel, and SmartTube Proteomic Stabilizer, which allows for simple and reliable fixation and cryopreservation of whole blood samples. We validate a workflow that allows for streamlined staining of whole blood samples with minimal processing requirements or expertise at the site of sample collection, followed by shipment to a central CyTOF core facility for batched downstream processing and data acquisition. We apply this workflow to characterize 184 whole blood samples collected longitudinally from a cohort of 72 hospitalized COVID‐19 patients and healthy controls, highlighting dynamic disease‐associated changes in circulating immune cell frequency and phenotype.
Published: 2021
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16. The contribution of genetic risk to the comorbidity of depression and anxiety: a multi-site electronic health records study

Author: Brandon J Coombes, Isotta Landi, Karmel W Choi, Kritika Singh, Y Nina Gao, Brian Fennessy, Greg D Jenkins, Anthony Batzler, Richard Pendegraft, Nicolas A Nunez, Euijung Ryu, Priya Wickramaratne, Jyotishman Pathak, J John Mann, Lea K Davis, Jordan W Smoller, Mark Olfson, Alexander W Charney, and Joanna M Biernacka
Abstract: ImportanceDepression and anxiety are common and highly comorbid, posing a clinical and public health concern because such comorbidity is associated with poorer outcomes.ObjectiveTo evaluate association of genetic risk scores with depression and anxiety diagnosis either in isolation or comorbid with each other.DesignInternational Classification of Diseases (ICD) ninth and tenth edition codes were extracted from longitudinal electronic health records (EHR) from four EHR-linked biobanks with genetic data available. Data analysis was performed between February 2021 to October 2021.SettingEHR-linked biorepository study.ParticipantsAcross the four biobanks, 140947 patients (80601 female [57.2%] including 109592 European ancestry [77.8%], 22321 African ancestry [15.8%], and 9034 Hispanic [6.4%]) were included in the study.Main outcomes and measuresPolygenic risk scores (PRS) for depression and anxiety were computed for all participants. They were assessed for diagnosis of depression and anxiety using ICD9/10 codes. The primary outcome was a four-level depression/anxiety diagnosis group variable: neither, depression-only, anxiety-only, and comorbid. Estimated effect measures include odds ratios and the proportion of variance on the liability scale explained by the PRS.Results95992 patients had neither diagnosis (68.1%), 14918 depression-only (10.6%), 12682 anxiety-only (9.0%), and 17355 comorbid (12.3%). PRS for depression and anxiety predicted their respective diagnoses within each biobank and each ancestry with the exception of anxiety-PRS not predicting anxiety in any ancestral group from one biobank. In the meta-analysis across participants of European ancestries, both PRSs for depression and anxiety were higher in each diagnosis group compared to controls. Notably, depression-PRS (OR=1.20 per SD increase in PRS; 95% CI= 1.18-1.23) and anxiety-PRS (OR=1.07; 95% CI=1.05-1.09) had the largest effect size for the comorbid group when compared to controls. The confidence interval for the depression-PRS effect did not overlap across groups demonstrating a gradient of genetic risk across the four diagnosis groups.Conclusions and RelevanceThe genetic risk of depression and anxiety make distinct contributions to the risk of comorbid depression and anxiety, supporting the hypothesis that the correlated disorders represent distinct nosological entities.Key PointsQuestionIs the genetic risk of depression and anxiety associated with comorbidity of depression and anxiety?FindingsUsing electronic health records from four academic medical centers, this study found that genetic risk of depression and anxiety are jointly associated with clinical depression and anxiety diagnoses with better prediction occurring for a diagnosis of depression.MeaningThe genetic risk of depression and anxiety make distinct contributions to comorbid depression and anxiety, which supports the hypothesis that the correlated disorders represent distinct nosological entities.
Published: 2022
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17. Mapping anorexia nervosa genes to clinical phenotypes

Author: Jessica S, Johnson, Alanna C, Cote, Amanda, Dobbyn, Laura G, Sloofman, Jiayi, Xu, Liam, Cotter, Alexander W, Charney, Andreas, Birgegård, Jennifer, Jordan, Martin, Kennedy, Mikaél, Landén, Sarah L, Maguire, Nicholas G, Martin, Preben Bo, Mortensen, Laura M, Thornton, Cynthia M, Bulik, and Laura M, Huckins
Subjects: PrediXcan, Psychiatry and Mental health, EHR, transcriptomic imputation, Anorexia nervosa, pheWAS, Applied Psychology
Abstract: BackgroundAnorexia nervosa (AN) is a psychiatric disorder with complex etiology, with a significant portion of disease risk imparted by genetics. Traditional genome-wide association studies (GWAS) produce principal evidence for the association of genetic variants with disease. Transcriptomic imputation (TI) allows for the translation of those variants into regulatory mechanisms, which can then be used to assess the functional outcome of genetically regulated gene expression (GReX) in a broader setting through the use of phenome-wide association studies (pheWASs) in large and diverse clinical biobank populations with electronic health record phenotypes.MethodsHere, we applied TI using S-PrediXcan to translate the most recent PGC-ED AN GWAS findings into AN-GReX. For significant genes, we imputed AN-GReX in the Mount Sinai BioMe™ Biobank and performed pheWASs on over 2000 outcomes to test the clinical consequences of aberrant expression of these genes. We performed a secondary analysis to assess the impact of body mass index (BMI) and sex on AN-GReX clinical associations.ResultsOur S-PrediXcan analysis identified 53 genes associated with AN, including what is, to our knowledge, the first-genetic association of AN with the major histocompatibility complex. AN-GReX was associated with autoimmune, metabolic, and gastrointestinal diagnoses in our biobank cohort, as well as measures of cholesterol, medications, substance use, and pain. Additionally, our analyses showed moderation of AN-GReX associations with measures of cholesterol and substance use by BMI, and moderation of AN-GReX associations with celiac disease by sex.ConclusionsOur BMI-stratified results provide potential avenues of functional mechanism for AN-genes to investigate further.
Published: 2022
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18. Outcomes of Patients on Maintenance Dialysis Hospitalized with COVID-19

Author: Benjamin S. Glicksberg, Matthew A. Levin, Lewis Kaufman, Steven G. Coca, Shan Zhao, Erwin P. Bottinger, Staci Leisman, Shuchita Sharma, Girish N. Nadkarni, Zahi A. Fayad, Lili Chan, Ishan Paranjpe, Sulaiman Somani, John Cijiang He, Arvind Kumar, Suraj K. Jaladanki, Alexander W. Charney, and Barbara Murphy
Subjects: Male, 2019-20 coronavirus outbreak, medicine.medical_specialty, Critical Care, Coronavirus disease 2019 (COVID-19), Epidemiology, viruses, medicine.medical_treatment, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), 030232 urology & nephrology, Comorbidity, 030204 cardiovascular system & hematology, Critical Care and Intensive Care Medicine, Risk Assessment, 03 medical and health sciences, 0302 clinical medicine, Renal Dialysis, Risk Factors, Internal medicine, Humans, Medicine, Hospital Mortality, Renal Insufficiency, skin and connective tissue diseases, Dialysis, Aged, Retrospective Studies, Transplantation, Kidney, business.industry, fungi, COVID-19, virus diseases, Retrospective cohort study, Middle Aged, medicine.disease, Respiration, Artificial, Research Letters, Hospitalization, body regions, Treatment Outcome, medicine.anatomical_structure, Nephrology, Female, New York City, business, Risk assessment
Abstract: Coronavirus disease 2019 (COVID-19) due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has had devastating effects worldwide. Patients with kidney failure on dialysis may have a higher risk of worse outcomes. Reports from China found that these patients with SARS-CoV-2 had fewer
Published: 2020
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19. AKI in Hospitalized Patients with COVID-19

Author: Riccardo Miotto, Benjamin S. Glicksberg, Lili Chan, Allan C. Just, Felix Richter, Anuradha Lala, Valentin Fuster, Girish N. Nadkarni, Arash Kia, Carlos Cordon-Cardo, Akhil Vaid, Alexander W. Charney, Aparna Saha, Robert Freeman, Sulaiman Somani, Prem Timsina, Eric E. Schadt, Barbara Murphy, John Cijiang He, Ishan Paranjpe, David Reich, Kumardeep Chaudhary, Matthew A. Levin, Shan Zhao, Jagat Narula, Steven G. Coca, Rong Chen, Erwin P. Bottinger, Li Li, Kinsuk Chauhan, Carol R. Horowitz, and Zahi A. Fayad
Subjects: medicine.medical_specialty, Proteinuria, urogenital system, Hospitalized patients, business.industry, medicine.medical_treatment, 030232 urology & nephrology, Renal function, General Medicine, Urine, Odds ratio, 030204 cardiovascular system & hematology, urologic and male genital diseases, female genital diseases and pregnancy complications, Confidence interval, 03 medical and health sciences, 0302 clinical medicine, Nephrology, Internal medicine, Intensive care, medicine, medicine.symptom, business, Dialysis
Abstract: Background Early reports indicate that AKI is common among patients with coronavirus disease 2019 (COVID-19) and associated with worse outcomes. However, AKI among hospitalized patients with COVID-19 in the United States is not well described. Methods This retrospective, observational study involved a review of data from electronic health records of patients aged ≥18 years with laboratory-confirmed COVID-19 admitted to the Mount Sinai Health System from February 27 to May 30, 2020. We describe the frequency of AKI and dialysis requirement, AKI recovery, and adjusted odds ratios (aORs) with mortality. Results Of 3993 hospitalized patients with COVID-19, AKI occurred in 1835 (46%) patients; 347 (19%) of the patients with AKI required dialysis. The proportions with stages 1, 2, or 3 AKI were 39%, 19%, and 42%, respectively. A total of 976 (24%) patients were admitted to intensive care, and 745 (76%) experienced AKI. Of the 435 patients with AKI and urine studies, 84% had proteinuria, 81% had hematuria, and 60% had leukocyturia. Independent predictors of severe AKI were CKD, men, and higher serum potassium at admission. In-hospital mortality was 50% among patients with AKI versus 8% among those without AKI (aOR, 9.2; 95% confidence interval, 7.5 to 11.3). Of survivors with AKI who were discharged, 35% had not recovered to baseline kidney function by the time of discharge. An additional 28 of 77 (36%) patients who had not recovered kidney function at discharge did so on posthospital follow-up. Conclusions AKI is common among patients hospitalized with COVID-19 and is associated with high mortality. Of all patients with AKI, only 30% survived with recovery of kidney function by the time of discharge.
Published: 2020
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20. An inflammatory cytokine signature predicts COVID-19 severity and survival

Author: Jeffrey S. Jhang, Keith Sigel, Manishkumar Patel, Hsin-Hui Huang, Carlos Cordon-Cardo, Diane Marie Del Valle, Talia H. Swartz, Kevin Tuballes, Judith A. Aberg, David Reich, Adolfo Firpo-Betancourt, Noam D. Beckmann, Sundar Jagannath, Aryeh Stock, Bo Wang, Samir Parekh, Patricia Kovatch, Oliver Van Oekelen, Damodara Rao Mendu, Hui Xie, Adeeb Rahman, Eric E. Schadt, Madhu Mazumdar, Yonit Lavin, Miriam Merad, Marc Feldmann, Alexander W. Charney, Sharon Nirenberg, Thomas U. Marron, Sacha Gnjatic, Deepu Madduri, and Seunghee Kim-Schulze
Subjects: 0301 basic medicine, medicine.medical_specialty, medicine.medical_treatment, Inflammation, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Severity of illness, medicine, Humans, Survival rate, SARS-CoV-2, business.industry, COVID-19, General Medicine, medicine.disease, Clinical trial, Pneumonia, 030104 developmental biology, Cytokine, 030220 oncology & carcinogenesis, Cohort, Cytokines, medicine.symptom, Outcomes research, Cytokine Release Syndrome, business
Abstract: Several studies have revealed that the hyper-inflammatory response induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major cause of disease severity and death. However, predictive biomarkers of pathogenic inflammation to help guide targetable immune pathways are critically lacking. We implemented a rapid multiplex cytokine assay to measure serum interleukin (IL)-6, IL-8, tumor necrosis factor (TNF)-α and IL-1β in hospitalized patients with coronavirus disease 2019 (COVID-19) upon admission to the Mount Sinai Health System in New York. Patients (n = 1,484) were followed up to 41 d after admission (median, 8 d), and clinical information, laboratory test results and patient outcomes were collected. We found that high serum IL-6, IL-8 and TNF-α levels at the time of hospitalization were strong and independent predictors of patient survival (P
Published: 2020
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21. Characterization of Patients Who Return to Hospital Following Discharge from Hospitalization for COVID-19

Author: Shan Zhao, Girish N. Nadkarni, Zahi A. Fayad, Sulaiman Somani, Matthew A. Levin, Erwin P. Bottinger, Jessica K De Freitas, Benjamin S. Glicksberg, Valentin Fuster, Anuradha Lala, Keith Sigel, Felix Richter, Allan C Just, Alexander W. Charney, and Nidhi Naik
Subjects: Male, Comorbidity, 030204 cardiovascular system & hematology, 01 natural sciences, Pulmonary Disease, Chronic Obstructive, 0302 clinical medicine, 030212 general & internal medicine, Original Research, Respiratory Distress Syndrome, COPD, Respiratory distress, Middle Aged, After discharge, 3. Good health, Hypertension, Female, Coronavirus Infections, Emergency Service, Hospital, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Pneumonia, Viral, Patient Readmission, Article, Betacoronavirus, 03 medical and health sciences, Internal medicine, Intensive care, Internal Medicine, medicine, Humans, 0101 mathematics, Pandemics, Aged, Retrospective Studies, SARS-CoV-2, business.industry, 010102 general mathematics, Case-control study, Anticoagulants, COVID-19, Retrospective cohort study, Emergency department, Length of Stay, medicine.disease, Pneumonia, Case-Control Studies, Emergency medicine, New York City, Index hospitalization, business
Abstract: Background Data on patients with coronavirus disease 2019 (COVID-19) who return to hospital after discharge are scarce. Characterization of these patients may inform post-hospitalization care. Objective To describe clinical characteristics of patients with COVID-19 who returned to the emergency department (ED) or required readmission within 14 days of discharge. Design Retrospective cohort study of SARS-COV-2-positive patients with index hospitalization between February 27 and April 12, 2020, with ≥ 14-day follow-up. Significance was defined as P < 0.05 after multiplying P by 125 study-wide comparisons. Participants Hospitalized patients with confirmed SARS-CoV-2 discharged alive from five New York City hospitals. Main Measures Readmission or return to ED following discharge. Results Of 2864 discharged patients, 103 (3.6%) returned for emergency care after a median of 4.5 days, with 56 requiring inpatient readmission. The most common reason for return was respiratory distress (50%). Compared with patients who did not return, there were higher proportions of COPD (6.8% vs 2.9%) and hypertension (36% vs 22.1%) among those who returned. Patients who returned also had a shorter median length of stay (LOS) during index hospitalization (4.5 [2.9,9.1] vs 6.7 [3.5, 11.5] days; Padjusted = 0.006), and were less likely to have required intensive care on index hospitalization (5.8% vs 19%; Padjusted = 0.001). A trend towards association between absence of in-hospital treatment-dose anticoagulation on index admission and return to hospital was also observed (20.9% vs 30.9%, Padjusted = 0.06). On readmission, rates of intensive care and death were 5.8% and 3.6%, respectively. Conclusions Return to hospital after admission for COVID-19 was infrequent within 14 days of discharge. The most common cause for return was respiratory distress. Patients who returned more likely had COPD and hypertension, shorter LOS on index-hospitalization, and lower rates of in-hospital treatment-dose anticoagulation. Future studies should focus on whether these comorbid conditions, longer LOS, and anticoagulation are associated with reduced readmissions. Electronic supplementary material The online version of this article (10.1007/s11606-020-06120-6) contains supplementary material, which is available to authorized users.
Published: 2020
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22. Sex-Dependent Shared and Nonshared Genetic Architecture Across Mood and Psychotic Disorders

Author: Gabriëlla A.M. Blokland, Jakob Grove, Chia-Yen Chen, Chris Cotsapas, Stuart Tobet, Robert Handa, David St Clair, Todd Lencz, Bryan J. Mowry, Sathish Periyasamy, Murray J. Cairns, Paul A. Tooney, Jing Qin Wu, Brian Kelly, George Kirov, Patrick F. Sullivan, Aiden Corvin, Brien P. Riley, Tõnu Esko, Lili Milani, Erik G. Jönsson, Aarno Palotie, Hannelore Ehrenreich, Martin Begemann, Agnes Steixner-Kumar, Pak C. Sham, Nakao Iwata, Daniel R. Weinberger, Pablo V. Gejman, Alan R. Sanders, Joseph D. Buxbaum, Dan Rujescu, Ina Giegling, Bettina Konte, Annette M. Hartmann, Elvira Bramon, Robin M. Murray, Michele T. Pato, Jimmy Lee, Ingrid Melle, Espen Molden, Roel A. Ophoff, Andrew McQuillin, Nicholas J. Bass, Rolf Adolfsson, Anil K. Malhotra, Nicholas G. Martin, Janice M. Fullerton, Philip B. Mitchell, Peter R. Schofield, Andreas J. Forstner, Franziska Degenhardt, Sabrina Schaupp, Ashley L. Comes, Manolis Kogevinas, José Guzman-Parra, Andreas Reif, Fabian Streit, Lea Sirignano, Sven Cichon, Maria Grigoroiu-Serbanescu, Joanna Hauser, Jolanta Lissowska, Fermin Mayoral, Bertram Müller-Myhsok, Beata Świątkowska, Thomas G. Schulze, Markus M. Nöthen, Marcella Rietschel, John Kelsoe, Marion Leboyer, Stéphane Jamain, Bruno Etain, Frank Bellivier, John B. Vincent, Martin Alda, Claire O’Donovan, Pablo Cervantes, Joanna M. Biernacka, Mark Frye, Susan L. McElroy, Laura J. Scott, Eli A. Stahl, Mikael Landén, Marian L. Hamshere, Olav B. Smeland, Srdjan Djurovic, Arne E. Vaaler, Ole A. Andreassen, Bernhard T. Baune, Tracy Air, Martin Preisig, Rudolf Uher, Douglas F. Levinson, Myrna M. Weissman, James B. Potash, Jianxin Shi, James A. Knowles, Roy H. Perlis, Susanne Lucae, Dorret I. Boomsma, Brenda W.J.H. Penninx, Jouke-Jan Hottenga, Eco J.C. de Geus, Gonneke Willemsen, Yuri Milaneschi, Henning Tiemeier, Hans J. Grabe, Alexander Teumer, Sandra Van der Auwera, Uwe Völker, Steven P. Hamilton, Patrik K.E. Magnusson, Alexander Viktorin, Divya Mehta, Niamh Mullins, Mark J. Adams, Gerome Breen, Andrew M. McIntosh, Cathryn M. Lewis, David M. Hougaard, Merete Nordentoft, Ole Mors, Preben B. Mortensen, Thomas Werge, Thomas D. Als, Anders D. Børglum, Tracey L. Petryshen, Jordan W. Smoller, Jill M. Goldstein, Stephan Ripke, Benjamin M. Neale, James T.R. Walters, Kai-How Farh, Peter A. Holmans, Phil Lee, Brendan Bulik-Sullivan, David A. Collier, Hailiang Huang, Tune H. Pers, Ingrid Agartz, Esben Agerbo, Margot Albus, Madeline Alexander, Farooq Amin, Silviu A. Bacanu, Richard A. Belliveau, Judit Bene, Sarah E. Bergen, Elizabeth Bevilacqua, Tim B. Bigdeli, Donald W. Black, Richard Bruggeman, Nancy G. Buccola, Randy L. Buckner, William Byerley, Wiepke Cahn, Guiqing Cai, Dominique Campion, Rita M. Cantor, Vaughan J. Carr, Noa Carrera, Stanley V. Catts, Kimberly D. Chambert, Raymond C.K. Chan, Ronald Y.L. Chen, Eric Y.H. Chen, Wei Cheng, Eric F.C. Cheung, Siow Ann Chong, C. Robert Cloninger, David Cohen, Nadine Cohen, Paul Cormican, Nick Craddock, James J. Crowley, David Curtis, Michael Davidson, Kenneth L. Davis, Jurgen Del Favero, Ditte Demontis, Dimitris Dikeos, Timothy Dinan, Gary Donohoe, Elodie Drapeau, Jubao Duan, Frank Dudbridge, Naser Durmishi, Peter Eichhammer, Johan Eriksson, Valentina Escott-Price, Laurent Essioux, Ayman H. Fanous, Martilias S. Farrell, Josef Frank, Lude Franke, Robert Freedman, Nelson B. Freimer, Marion Friedl, Joseph I. Friedman, Menachem Fromer, Giulio Genovese, Lyudmila Georgieva, Paola Giusti-Rodríguez, Stephanie Godard, Jacqueline I. Goldstein, Vera Golimbet, Srihari Gopal, Jacob Gratten, Lieuwe de Haan, Christian Hammer, Mark Hansen, Thomas Hansen, Vahram Haroutunian, Frans A. Henskens, Stefan Herms, Joel N. Hirschhorn, Per Hoffmann, Andrea Hofman, Mads V. Hollegaard, Masashi Ikeda, Inge Joa, Antonio Julià, René S. Kahn, Luba Kalaydjieva, Sena Karachanak-Yankova, Juha Karjalainen, David Kavanagh, Matthew C. Keller, James L. Kennedy, Andrey Khrunin, Yunjung Kim, Janis Klovins, Vaidutis Kucinskas, Zita Ausrele Kucinskiene, Hana Kuzelova-Ptackova, Anna K. Kähler, Claudine Laurent, Jimmy Lee Chee Keong, S. Hong Lee, Sophie E. Legge, Bernard Lerer, Miaoxin Li, Tao Li, Kung-Yee Liang, Jeffrey Lieberman, Svetlana Limborska, Carmel M. Loughland, Jan Lubinski, Jouko Lönnqvist, Milan Macek, Brion S. Maher, Wolfgang Maier, Jacques Mallet, Sara Marsal, Manuel Mattheisen, Morten Mattingsdal, Robert W. McCarley, Colm McDonald, Sandra Meier, Carin J. Meijer, Bela Melegh, Raquelle I. Mesholam-Gately, Andres Metspalu, Patricia T. Michie, Vihra Milanova, Younes Mokrab, Derek W. Morris, Kieran C. Murphy, Inez Myin-Germeys, Mari Nelis, Igor Nenadic, Deborah A. Nertney, Gerald Nestadt, Kristin K. Nicodemus, Liene Nikitina-Zake, Laura Nisenbaum, Annelie Nordin, Eadbhard O’Callaghan, Colm O’Dushlaine, F. Anthony O’Neill, Sang-Yun Oh, Ann Olincy, Line Olsen, Jim Van Os, Christos Pantelis, George N. Papadimitriou, Sergi Papiol, Elena Parkhomenko, Tiina Paunio, Milica Pejovic-Milovancevic, Diana O. Perkins, Olli Pietiläinen, Jonathan Pimm, Andrew J. Pocklington, John Powell, Alkes Price, Ann E. Pulver, Shaun M. Purcell, Digby Quested, Henrik B. Rasmussen, Abraham Reichenberg, Mark A. Reimers, Alexander L. Richards, Joshua L. Roffman, Panos Roussos, Douglas M. Ruderfer, Veikko Salomaa, Ulrich Schall, Christian R. Schubert, Sibylle G. Schwab, Edward M. Scolnick, Rodney J. Scott, Larry J. Seidman, Engilbert Sigurdsson, Teimuraz Silagadze, Jeremy M. Silverman, Kang Sim, Petr Slominsky, Hon-Cheong So, Chris C.A. Spencer, Hreinn Stefansson, Stacy Steinberg, Elisabeth Stogmann, Richard E. Straub, Eric Strengman, Jana Strohmaier, T. Scott Stroup, Mythily Subramaniam, Jaana Suvisaari, Dragan M. Svrakic, Jin P. Szatkiewicz, Erik Söderman, Srinivas Thirumalai, Draga Toncheva, Sarah Tosato, Juha Veijola, John Waddington, Dermot Walsh, Dai Wang, Qiang Wang, Bradley T. Webb, Mark Weiser, Dieter B. Wildenauer, Nigel M. Williams, Stephanie Williams, Stephanie H. Witt, Aaron R. Wolen, Emily H.M. Wong, Brandon K. Wormley, Hualin Simon Xi, Clement C. Zai, Xuebin Zheng, Fritz Zimprich, Naomi R. Wray, Kari Stefansson, Peter M. Visscher, Douglas H.R. Blackwood, Ariel Darvasi, Enrico Domenici, Michael Gill, Hugh Gurling, Christina M. Hultman, Assen V. Jablensky, Kenneth S. Kendler, Jo Knight, Qingqin S. Li, Jianjun Liu, Steven A. McCarroll, Jennifer L. Moran, Michael J. Owen, Carlos N. Pato, Danielle Posthuma, Pamela Sklar, Jens R. Wendland, Mark J. Daly, Michael C. O’Donovan, Peter Donnelly, Ines Barroso, Jenefer M. Blackwell, Matthew A. Brown, Juan P. Casas, Panos Deloukas, Audrey Duncanson, Janusz Jankowski, Hugh S. Markus, Christopher G. Mathew, Colin N.A. Palmer, Robert Plomin, Anna Rautanen, Stephen J. Sawcer, Richard C. Trembath, Ananth C. Viswanathan, Nicholas W. Wood, Gavin Band, Céline Bellenguez, Colin Freeman, Eleni Giannoulatou, Garrett Hellenthal, Richard Pearson, Matti Pirinen, Amy Strange, Zhan Su, Damjan Vukcevic, Cordelia Langford, Hannah Blackburn, Suzannah J. Bumpstead, Serge Dronov, Sarah Edkins, Matthew Gillman, Emma Gray, Rhian Gwilliam, Naomi Hammond, Sarah E. Hunt, Alagurevathi Jayakumar, Jennifer Liddle, Owen T. McCann, Simon C. Potter, Radhi Ravindrarajah, Michelle Ricketts, Avazeh Tashakkori-Ghanbaria, Matthew Waller, Paul Weston, Pamela Whittaker, Sara Widaa, Mark I. McCarthy, Maria J. Arranz, Steven Bakker, Stephan Bender, Benedicto Crespo-Facorro, Jeremy Hall, Conrad Iyegbe, Stephen Lawrie, Kuang Lin, Don H. Linszen, Ignacio Mata, Muriel Walshe, Matthias Weisbrod, Durk Wiersma, Vassily Trubetskoy, Yunpeng Wang, Jonathan R.I. Coleman, Héléna A. Gaspar, Christiaan A. de Leeuw, Jennifer M. Whitehead Pavlides, Maciej Trzaskowski, Enda M. Byrne, Liam Abbott, Huda Akil, Diego Albani, Ney Alliey-Rodriguez, Adebayo Anjorin, Verneri Antilla, Swapnil Awasthi, Judith A. Badner, Marie Bækvad-Hansen, Jack D. Barchas, Nicholas Bass, Michael Bauer, Richard Belliveau, Carsten Bøcker Pedersen, Erlend Bøen, Marco P. Boks, James Boocock, Monika Budde, William Bunney, Margit Burmeister, Jonas Bybjerg-Grauholm, Miquel Casas, Felecia Cerrato, Kimberly Chambert, Alexander W. Charney, Danfeng Chen, Claire Churchhouse, Toni-Kim Clarke, William Coryell, David W. Craig, Cristiana Cruceanu, Piotr M. Czerski, Anders M. Dale, Simone de Jong, Jurgen Del-Favero, J. Raymond DePaulo, Amanda L. Dobbyn, Ashley Dumont, Torbjørn Elvsåshagen, Chun Chieh Fan, Sascha B. Fischer, Matthew Flickinger, Tatiana M. Foroud, Liz Forty, Christine Fraser, Katrin Gade, Diane Gage, Julie Garnham, Claudia Giambartolomei, Marianne Giørtz Pedersen, Jaqueline Goldstein, Scott D. Gordon, Katherine Gordon-Smith, Elaine K. Green, Melissa J. Green, Tiffany A. Greenwood, Weihua Guan, Martin Hautzinger, Urs Heilbronner, Maria Hipolito, Dominic Holland, Laura Huckins, Jessica S. Johnson, Radhika Kandaswamy, Robert Karlsson, Sarah Kittel-Schneider, Anna C. Koller, Ralph Kupka, Catharina Lavebratt, Jacob Lawrence, William B. Lawson, Markus Leber, Phil H. Lee, Shawn E. Levy, Jun Z. Li, Chunyu Liu, Anna Maaser, Donald J. MacIntyre, Pamela B. Mahon, Lina Martinsson, Steve McCarroll, Peter McGuffin, Melvin G. McInnis, James D. McKay, Helena Medeiros, Sarah E. Medland, Fan Meng, Grant W. Montgomery, Thomas W. Mühleisen, Hoang Nguyen, Caroline M. Nievergelt, Annelie Nordin Adolfsson, Evaristus A. Nwulia, Claire O'Donovan, Loes M. Olde Loohuis, Anil P.S. Ori, Lilijana Oruc, Urban Ösby, Amy Perry, Andrea Pfennig, Eline J. Regeer, Céline S. Reinbold, John P. Rice, Fabio Rivas, Margarita Rivera, Euijung Ryu, Cristina Sánchez-Mora, Alan F. Schatzberg, William A. Scheftner, Nicholas J. Schork, Cynthia Shannon Weickert, Tatyana Shehktman, Paul D. Shilling, Claire Slaney, Janet L. Sobell, Christine Søholm Hansen, Anne T. Spijker, Michael Steffens, John S. Strauss, Szabolcs Szelinger, Robert C. Thompson, Thorgeir E. Thorgeirsson, Jens Treutlein, Helmut Vedder, Weiqing Wang, Stanley J. Watson, Thomas W. Weickert, Simon Xi, Wei Xu, Allan H. Young, Peter Zandi, Peng Zhang, Sebastian Zöllner, Abdel Abdellaoui, Tracy M. Air, Till F.M. Andlauer, Silviu-Alin Bacanu, Aartjan T.F. Beekman, Elisabeth B. Binder, Julien Bryois, Henriette N. Buttenschøn, Na Cai, Enrique Castelao, Jane Hvarregaard Christensen, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Gregory E. Crawford, Gail Davies, Ian J. Deary, Eske M. Derks, Nese Direk, Conor V. Dolan, Erin C. Dunn, Thalia C. Eley, Farnush Farhadi Hassan Kiadeh, Hilary K. Finucane, Jerome C. Foo, Fernando S. Goes, Lynsey S. Hall, Thomas F. Hansen, Ian B. Hickie, Georg Homuth, Carsten Horn, David M. Howard, Marcus Ising, Rick Jansen, Ian Jones, Lisa A. Jones, Eric Jorgenson, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Dean F. MacKinnon, Robert M. Maier, Jonathan Marchini, Hamdi Mbarek, Patrick McGrath, Christel M. Middeldorp, Evelin Mihailov, Francis M. Mondimore, Sara Mostafavi, Matthias Nauck, Bernard Ng, Michel G. Nivard, Dale R. Nyholt, Paul F. O'Reilly, Hogni Oskarsson, Jodie N. Painter, Roseann E. Peterson, Wouter J. Peyrot, Giorgio Pistis, Jorge A. Quiroz, Per Qvist, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Stanley I. Shyn, Grant C.B. Sinnamon, Johannes H. Smit, Daniel J. Smith, Katherine E. Tansey, Henning Teismann, Wesley Thompson, Pippa A. Thomson, Matthew Traylor, André G. Uitterlinden, Daniel Umbricht, Albert M. van Hemert, Shantel Marie Weinsheimer, Jürgen Wellmann, Yang Wu, Hualin S. Xi, Jian Yang, Futao Zhang, Volker Arolt, Klaus Berger, Udo Dannlowski, Katharina Domschke, Caroline Hayward, Andrew C. Heath, Stefan Kloiber, Glyn Lewis, Pamela AF. Madden, Patrik K. Magnusson, Preben Bo Mortensen, Michael C. O'Donovan, Sara A. Paciga, Nancy L. Pedersen, David J. Porteous, Catherine Schaefer, Henry Völzke, Marco Bortolato, Janita Bralten, Cynthia M. Bulik, Christie L. Burton, Caitlin E. Carey, Lea K. Davis, Laramie E. Duncan, Howard J. Edenberg, Lauren Erdman, Stephen V. Faraone, Slavina B. Goleva, Wei Guo, Christopher Hübel, Laura M. Huckins, Ekaterina A. Khramtsova, Joanna Martin, Carol A. Mathews, Elise Robinson, Eli Stahl, Barbara E. Stranger, Michela Traglia, Raymond K. Walters, Lauren A. Weiss, Stacey J. Winham, Yin Yao, Kristjar Skajaa, Markus Nöthen, Michael Owen, Robert H. Yolken, Niels Plath, Jonathan Mill, Daniel Geschwind, Psychiatry 1, RS: MHeNs - R2 - Mental Health, Psychiatrie & Neuropsychologie, Centre of Excellence in Complex Disease Genetics, Research Programme of Molecular Medicine, Research Programs Unit, Aarno Palotie / Principal Investigator, Institute for Molecular Medicine Finland, Genomics of Neurological and Neuropsychiatric Disorders, Functional Genomics, Biological Psychology, APH - Mental Health, APH - Methodology, Sociology and Social Gerontology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, Blokland, Gabriella AM, Grove, Jakob, Chen, Chia Yen, Cotsapas, Chris, Tobet, Stuart, Handa, Robert, Lee, Sang Hong, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Sex Differences Cross-Disorder Analysis Group of the Psychiatric Genomics Consortium, iPSYCH, Psychiatry, Amsterdam Neuroscience - Complex Trait Genetics, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Human genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Reproduction & Development (AR&D), Child and Adolescent Psychiatry / Psychology, Adult Psychiatry, ANS - Complex Trait Genetics, and ANS - Mood, Anxiety, Psychosis, Stress & Sleep
Subjects: 0301 basic medicine, Male, Bipolar Disorder, Schizophrenia/genetics, LD SCORE REGRESSION, Genome-wide association study, 0302 clinical medicine, Receptors, SCHIZOPHRENIA, Psychotic Disorders/genetics, KYNURENINE PATHWAY METABOLISM, Genetics, RISK, Sex Characteristics, Vascular Endothelial Growth Factor, Bipolar Disorder/genetics, Major/genetics, Single Nucleotide, AFFECTIVE STIMULI IMPACT, Schizophrenia, Sulfurtransferases, Major depressive disorder, Female, Depressive Disorder, Major/genetics, Bipolar disorder, Locus (genetics), Genomics, Biology, Polymorphism, Single Nucleotide, Article, DYSPHORIC MOOD, 03 medical and health sciences, Sex differences, medicine, Humans, Genetic Predisposition to Disease, ddc:610, Polymorphism, GENOME-WIDE ASSOCIATION, Genotype-by-sex interaction, Biological Psychiatry, Depressive Disorder, Major, Depressive Disorder, GENDER-DIFFERENCES, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], PARAVENTRICULAR NUCLEUS, 3112 Neurosciences, Endothelial Cells, MAJOR DEPRESSION, medicine.disease, Genetic architecture, 030104 developmental biology, Mood, Receptors, Vascular Endothelial Growth Factor, Psychotic Disorders, 3111 Biomedicine, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: Contains fulltext : 248656.pdf (Publisher’s version ) (Closed access) BACKGROUND: Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk. METHODS: We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH. RESULTS: Across disorders, genome-wide significant single nucleotide polymorphism-by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10(-8)), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10(-6)) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10(-7); rs73033497, p = 8.8 × 10(-7); rs7914279, p = 6.4 × 10(-7)), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10(-7)) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10(-7)), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10(-7)) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05). CONCLUSIONS: In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.
Published: 2022
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23. Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Author: Niamh Mullins, JooEun Kang, Adrian I. Campos, Jonathan R.I. Coleman, Alexis C. Edwards, Hanga Galfalvy, Daniel F. Levey, Adriana Lori, Andrey Shabalin, Anna Starnawska, Mei-Hsin Su, Hunna J. Watson, Mark Adams, Swapnil Awasthi, Michael Gandal, Jonathan D. Hafferty, Akitoyo Hishimoto, Minsoo Kim, Satoshi Okazaki, Ikuo Otsuka, Stephan Ripke, Erin B. Ware, Andrew W. Bergen, Wade H. Berrettini, Martin Bohus, Harry Brandt, Xiao Chang, Wei J. Chen, Hsi-Chung Chen, Steven Crawford, Scott Crow, Emily DiBlasi, Philibert Duriez, Fernando Fernández-Aranda, Manfred M. Fichter, Steven Gallinger, Stephen J. Glatt, Philip Gorwood, Yiran Guo, Hakon Hakonarson, Katherine A. Halmi, Hai-Gwo Hwu, Sonia Jain, Stéphane Jamain, Susana Jiménez-Murcia, Craig Johnson, Allan S. Kaplan, Walter H. Kaye, Pamela K. Keel, James L. Kennedy, Kelly L. Klump, Dong Li, Shih-Cheng Liao, Klaus Lieb, Lisa Lilenfeld, Chih-Min Liu, Pierre J. Magistretti, Christian R. Marshall, James E. Mitchell, Eric T. Monson, Richard M. Myers, Dalila Pinto, Abigail Powers, Nicolas Ramoz, Stefan Roepke, Vsevolod Rozanov, Stephen W. Scherer, Christian Schmahl, Marcus Sokolowski, Michael Strober, Laura M. Thornton, Janet Treasure, Ming T. Tsuang, Stephanie H. Witt, D. Blake Woodside, Zeynep Yilmaz, Lea Zillich, Rolf Adolfsson, Ingrid Agartz, Tracy M. Air, Martin Alda, Lars Alfredsson, Ole A. Andreassen, Adebayo Anjorin, Vivek Appadurai, María Soler Artigas, Sandra Van der Auwera, M. Helena Azevedo, Nicholas Bass, Claiton H.D. Bau, Bernhard T. Baune, Frank Bellivier, Klaus Berger, Joanna M. Biernacka, Tim B. Bigdeli, Elisabeth B. Binder, Michael Boehnke, Marco P. Boks, Rosa Bosch, David L. Braff, Richard Bryant, Monika Budde, Enda M. Byrne, Wiepke Cahn, Miguel Casas, Enrique Castelao, Jorge A. Cervilla, Boris Chaumette, Sven Cichon, Aiden Corvin, Nicholas Craddock, David Craig, Franziska Degenhardt, Srdjan Djurovic, Howard J. Edenberg, Ayman H. Fanous, Jerome C. Foo, Andreas J. Forstner, Mark Frye, Janice M. Fullerton, Justine M. Gatt, Pablo V. Gejman, Ina Giegling, Hans J. Grabe, Melissa J. Green, Eugenio H. Grevet, Maria Grigoroiu-Serbanescu, Blanca Gutierrez, Jose Guzman-Parra, Steven P. Hamilton, Marian L. Hamshere, Annette Hartmann, Joanna Hauser, Stefanie Heilmann-Heimbach, Per Hoffmann, Marcus Ising, Ian Jones, Lisa A. Jones, Lina Jonsson, René S. Kahn, John R. Kelsoe, Kenneth S. Kendler, Stefan Kloiber, Karestan C. Koenen, Manolis Kogevinas, Bettina Konte, Marie-Odile Krebs, Mikael Landén, Jacob Lawrence, Marion Leboyer, Phil H. Lee, Douglas F. Levinson, Calwing Liao, Jolanta Lissowska, Susanne Lucae, Fermin Mayoral, Susan L. McElroy, Patrick McGrath, Peter McGuffin, Andrew McQuillin, Sarah E. Medland, Divya Mehta, Ingrid Melle, Yuri Milaneschi, Philip B. Mitchell, Esther Molina, Gunnar Morken, Preben Bo Mortensen, Bertram Müller-Myhsok, Caroline Nievergelt, Vishwajit Nimgaonkar, Markus M. Nöthen, Michael C. O’Donovan, Roel A. Ophoff, Michael J. Owen, Carlos Pato, Michele T. Pato, Brenda W.J.H. Penninx, Jonathan Pimm, Giorgio Pistis, James B. Potash, Robert A. Power, Martin Preisig, Digby Quested, Josep Antoni Ramos-Quiroga, Andreas Reif, Marta Ribasés, Vanesa Richarte, Marcella Rietschel, Margarita Rivera, Andrea Roberts, Gloria Roberts, Guy A. Rouleau, Diego L. Rovaris, Dan Rujescu, Cristina Sánchez-Mora, Alan R. Sanders, Peter R. Schofield, Thomas G. Schulze, Laura J. Scott, Alessandro Serretti, Jianxin Shi, Stanley I. Shyn, Lea Sirignano, Pamela Sklar, Olav B. Smeland, Jordan W. Smoller, Edmund J.S. Sonuga-Barke, Gianfranco Spalletta, John S. Strauss, Beata Świątkowska, Maciej Trzaskowski, Gustavo Turecki, Laura Vilar-Ribó, John B. Vincent, Henry Völzke, James T.R. Walters, Cynthia Shannon Weickert, Thomas W. Weickert, Myrna M. Weissman, Leanne M. Williams, Naomi R. Wray, Clement C. Zai, Allison E. Ashley-Koch, Jean C. Beckham, Elizabeth R. Hauser, Michael A. Hauser, Nathan A. Kimbrel, Jennifer H. Lindquist, Benjamin McMahon, David W. Oslin, Xuejun Qin, Esben Agerbo, Anders D. Børglum, Gerome Breen, Annette Erlangsen, Tõnu Esko, Joel Gelernter, David M. Hougaard, Ronald C. Kessler, Henry R. Kranzler, Qingqin S. Li, Nicholas G. Martin, Andrew M. McIntosh, Ole Mors, Merete Nordentoft, Catherine M. Olsen, David Porteous, Robert J. Ursano, Danuta Wasserman, Thomas Werge, David C. Whiteman, Cynthia M. Bulik, Hilary Coon, Ditte Demontis, Anna R. Docherty, Po-Hsiu Kuo, Cathryn M. Lewis, J. John Mann, Miguel E. Rentería, Daniel J. Smith, Eli A. Stahl, Murray B. Stein, Fabian Streit, Virginia Willour, Douglas M. Ruderfer, Manuel Mattheisen, Abdel Abdellaoui, Mark J. Adams, Till F.M. Andlauer, Silviu-Alin Bacanu, Marie Bækvad-Hansen, Aartjan T.F. Beekman, Julien Bryois, Henriette N. Buttenschøn, Jonas Bybjerg-Grauholm, Na Cai, Jane Hvarregaard Christensen, Toni-Kim Clarke, Lucía Colodro-Conde, Baptiste Couvy-Duchesne, Nick Craddock, Gregory E. Crawford, Gail Davies, Eske M. Derks, Nese Direk, Conor V. Dolan, Erin C. Dunn, Thalia C. Eley, Valentina Escott-Price, Farnush Farhadi Hassan Kiadeh, Hilary K. Finucane, Josef Frank, Héléna A. Gaspar, Michael Gill, Fernando S. Goes, Scott D. Gordon, Shantel Marie Weinsheimer, Jürgen Wellmann, Gonneke Willemsen, Yang Wu, Hualin S. Xi, Jian Yang, Futao Zhang, Volker Arolt, Dorret I. Boomsma, Udo Dannlowski, E.J.C. de Geus, J. Raymond Depaulo, Enrico Domenici, Katharina Domschke, Jakob Grove, Lynsey S. Hall, Christine Søholm Hansen, Thomas F. Hansen, Stefan Herms, Ian B. Hickie, Georg Homuth, Carsten Horn, Jouke-Jan Hottenga, David M. Howard, Rick Jansen, Eric Jorgenson, James A. Knowles, Isaac S. Kohane, Julia Kraft, Warren W. Kretzschmar, Zoltán Kutalik, Yihan Li, Penelope A. Lind, Donald J. MacIntyre, Dean F. MacKinnon, Robert M. Maier, Wolfgang Maier, Jonathan Marchini, Hamdi Mbarek, Christel M. Middeldorp, Evelin Mihailov, Lili Milani, Francis M. Mondimore, Grant W. Montgomery, Sara Mostafavi, Matthias Nauck, Bernard Ng, Michel G. Nivard, Dale R. Nyholt, Paul F. O’Reilly, Hogni Oskarsson, Caroline Hayward, Andrew C. Heath, Glyn Lewis, Pamela A.F. Madden, Patrik K. Magnusson, Andres Metspalu, Sara A. Paciga, Nancy L. Pedersen, Jodie N. Painter, Carsten Bøcker Pedersen, Marianne Giørtz Pedersen, Roseann E. Peterson, Wouter J. Peyrot, Danielle Posthuma, Jorge A. Quiroz, Per Qvist, John P. Rice, Brien P. Riley, Saira Saeed Mirza, Robert Schoevers, Eva C. Schulte, Ling Shen, Engilbert Sigurdsson, Grant C.B. Sinnamon, Johannes H. Smit, Hreinn Stefansson, Stacy Steinberg, Jana Strohmaier, Katherine E. Tansey, Henning Teismann, Alexander Teumer, Wesley Thompson, Pippa A. Thomson, Thorgeir E. Thorgeirsson, Matthew Traylor, Jens Treutlein, Vassily Trubetskoy, André G. Uitterlinden, Daniel Umbricht, Albert M. van Hemert, Alexander Viktorin, Peter M. Visscher, Yunpeng Wang, Bradley T. Webb, Roy H. Perlis, David J. Porteous, Catherine Schaefer, Kari Stefansson, Henning Tiemeier, Rudolf Uher, Patrick F. Sullivan, Kevin S. O’Connell, Brandon Coombes, Zhen Qiao, Thomas D. Als, Sigrid Børte, Alexander W. Charney, Ole Kristian Drange, Michael J. Gandal, Saskia P. Hagenaars, Masashi Ikeda, Nolan Kamitaki, Kristi Krebs, Georgia Panagiotaropoulou, Brian M. Schilder, Laura G. Sloofman, Bendik S. Winsvold, Hong-Hee Won, Liliya Abramova, Kristina Adorjan, Mariam Al Eissa, Diego Albani, Ney Alliey-Rodriguez, Verneri Antilla, Anastasia Antoniou, Ji Hyun Baek, Michael Bauer, Eva C. Beins, Sarah E. Bergen, Armin Birner, Erlend Bøen, Murielle Brum, Ben M. Brumpton, Nathalie Brunkhorst-Kanaan, William Byerley, Murray Cairns, Miquel Casas, Pablo Cervantes, Cristiana Cruceanu, Alfredo Cuellar-Barboza, Julie Cunningham, David Curtis, Piotr M. Czerski, Anders M. Dale, Nina Dalkner, Friederike S. David, Amanda L. Dobbyn, Athanassios Douzenis, Torbjørn Elvsåshagen, I. Nicol Ferrier, Alessia Fiorentino, Tatiana M. 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Regeer, Fabio Rivas, Julian Roth, Panos Roussos, Fanny Senner, Sally Sharp, Paul D. Shilling, Claire Slaney, Janet L. Sobell, Maria Soler Artigas, Anne T. Spijker, Dan J. Stein, Chikashi Terao, Claudio Toma, Paul Tooney, Evangelia-Eirini Tsermpini, Marquis P. Vawter, Helmut Vedder, Simon Xi, Wei Xu, Jessica Mei Kay Yang, Allan H. Young, Hannah Young, Peter P. Zandi, Hang Zhou, null HUNT All-In Psychiatry, Gulja Babadjanova, Lena Backlund, Susanne Bengesser, Douglas H.R. Blackwood, Vaughan J. Carr, Stanley Catts, Dimitris Dikeos, Bruno Etain, Panagiotis Ferentinos, Micha Gawlik, Elliot S. Gershon, Frans Henskens, Jan Hillert, Kyung Sue Hong, Christina M. Hultman, Kristian Hveem, Nakao Iwata, Assen V. Jablensky, George Kirov, Christine Lochner, Carmel Loughland, Carol A. Mathews, Francis J. McMahon, Patricia Michie, Bryan Mowry, Benjamin M. Neale, Caroline M. Nievergelt, Ketil J. Oedegaard, Tomas Olsson, Chris Pantelis, George P. Patrinos, Eva Z. 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J., Wasserman, D., Coon, H., Demontis, D., Docherty, A. R., Kuo, P. -H., Mann, J. J., Renteria, M. E., Stein, M. B., Willour, V., Psychiatry, Biological Psychology, APH - Methodology, APH - Mental Health, APH - Health Behaviors & Chronic Diseases, AMS - Sports, AMS - Ageing & Vitality, APH - Personalized Medicine, Amsterdam Neuroscience - Complex Trait Genetics, Complex Trait Genetics, Institute for Molecular Medicine Finland, Centre of Excellence in Complex Disease Genetics, Aarno Palotie / Principal Investigator, Genomics of Neurological and Neuropsychiatric Disorders, HUS Psychiatry, Department of Public Health, Clinicum, Nuorisopsykiatria, Faculty Common Matters (Faculty of Social Sciences), Samuli Olli Ripatti / Principal Investigator, Complex Disease Genetics, Biostatistics Helsinki, Anna Keski-Rahkonen / Principal Investigator, Elisabeth Ingrid Maria Widen / Principal Investigator, Genomic Discoveries and Clinical Translation, Internal medicine, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Digital Health, Mullins N., Kang J., Campos A.I., Coleman J.R.I., Edwards 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T.F.M., Bacanu S.-A., Baekvad-Hansen M., Beekman A.T.F., Bryois J., Buttenschon H.N., Bybjerg-Grauholm J., Cai N., Christensen J.H., Clarke T.-K., Colodro-Conde L., Couvy-Duchesne B., Crawford G.E., Davies G., Derks E.M., Direk N., Dolan C.V., Dunn E.C., Eley T.C., Escott-Price V., Hassan Kiadeh F.F., Finucane H.K., Frank J., Gaspar H.A., Gill M., Goes F.S., Gordon S.D., Weinsheimer S.M., Wellmann J., Willemsen G., Wu Y., Xi H.S., Yang J., Zhang F., Arolt V., Boomsma D.I., Dannlowski U., de Geus E.J.C., Depaulo J.R., Domenici E., Domschke K., Esko T., Grove J., Hall L.S., Hansen C.S., Hansen T.F., Herms S., Hickie I.B., Homuth G., Horn C., Hottenga J.-J., Hougaard D.M., Howard D.M., Jansen R., Jorgenson E., Knowles J.A., Kohane I.S., Kraft J., Kretzschmar W.W., Kutalik Z., Li Y., Lind P.A., MacIntyre D.J., MacKinnon D.F., Maier R.M., Maier W., Marchini J., Mbarek H., Middeldorp C.M., Mihailov E., Milani L., Mondimore F.M., Montgomery G.W., Mostafavi S., Nauck M., Ng B., Nivard M.G., Nyholt D.R., O'Reilly P.F., Oskarsson H., Hayward C., Heath A.C., Lewis G., Li Q.S., Madden P.A.F., Magnusson P.K., Martin N.G., McIntosh A.M., Metspalu A., Mors O., Nordentoft M., Paciga S.A., Pedersen N.L., Painter J.N., Pedersen C.B., Pedersen M.G., Peterson R.E., Peyrot W.J., Posthuma D., Quiroz J.A., Qvist P., Rice J.P., Riley B.P., Mirza S.S., Schoevers R., Schulte E.C., Shen L., Sigurdsson E., Sinnamon G.C.B., Smit J.H., Smith D.J., Stefansson H., Steinberg S., Streit F., Strohmaier J., Tansey K.E., Teismann H., Teumer A., Thompson W., Thomson P.A., Thorgeirsson T.E., Traylor M., Treutlein J., Trubetskoy V., Uitterlinden A.G., Umbricht D., der Auwera S.V., van Hemert A.M., Viktorin A., Visscher P.M., Wang Y., Webb B.T., Perlis R.H., Porteous D.J., Schaefer C., Stefansson K., Tiemeier H., Uher R., Werge T., Lewis C.M., Breen G., Borglum A.D., Sullivan P.F., O'Connell K.S., Coombes B., Qiao Z., Als T.D., Borte S., Charney A.W., Drange O.K., Gandal M.J., Hagenaars S.P., Ikeda M., Kamitaki N., Krebs K., Panagiotaropoulou G., Schilder B.M., Sloofman L.G., Winsvold B.S., Won H.-H., Abramova L., Adorjan K., Al Eissa M., Albani D., Alliey-Rodriguez N., Antilla V., Antoniou A., Baek J.H., Bauer M., Beins E.C., Bergen S.E., Birner A., Boen E., Brum M., Brumpton B.M., Brunkhorst-Kanaan N., Byerley W., Cairns M., Cervantes P., Cruceanu C., Cuellar-Barboza A., Cunningham J., Curtis D., Czerski P.M., Dale A.M., Dalkner N., David F.S., Dobbyn A.L., Douzenis A., Elvsashagen T., Ferrier I.N., Fiorentino A., Foroud T.M., Forty L., Frei O., Freimer N.B., Frisen L., Gade K., Garnham J., Gelernter J., Gizer I.R., Gordon-Smith K., Greenwood T.A., Ha K., Haraldsson M., Hautzinger M., Heilbronner U., Hellgren D., Holmans P.A., Huckins L., Johnson J.S., Kalman J.L., Kamatani Y., Kittel-Schneider S., Koromina M., Kranz T.M., Kranzler H.R., Kubo M., Kupka R., Kushner S.A., Lavebratt C., Leber M., Lee H.-J., Levy S.E., Lewis C., Lundberg M., Magnusson S.H., Maihofer A., Malaspina D., Maratou E., Martinsson L., McGregor N.W., McKay J.D., Medeiros H., Millischer V., Moran J.L., Morris D.W., Muhleisen T.W., O'Brien N., O'Donovan C., Olde Loohuis L.M., Oruc L., Papiol S., Pardinas A.F., Perry A., Pfennig A., Porichi E., Raj T., Rapaport M.H., Regeer E.J., Rivas F., Roth J., Roussos P., Ruderfer D.M., Senner F., Sharp S., Shilling P.D., Slaney C., Sobell J.L., Artigas M.S., Spijker A.T., Stein D.J., Terao C., Toma C., Tooney P., Tsermpini E.-E., Vawter M.P., Vedder H., Xi S., Xu W., Kay Yang J.M., Young A.H., Young H., Zandi P.P., Zhou H., HUNT All-In Psychiatry, Babadjanova G., Backlund L., Bengesser S., Blackwood D.H.R., Carr V.J., Catts S., Dikeos D., Etain B., Ferentinos P., Gawlik M., Gershon E.S., Henskens F., Hillert J., Hong K.S., Hultman C.M., Hveem K., Iwata N., Jablensky A.V., Kirov G., Lochner C., Loughland C., Mathews C.A., McMahon F.J., Michie P., Mowry B., Neale B.M., Nievergelt C.M., Oedegaard K.J., Olsson T., Pantelis C., Patrinos G.P., Reininghaus E.Z., Saito T., Schall U., Schalling M., Scott R.J., Weickert C.S., Stordal E., Vaaler A.E., Vieta E., Waldman I.D., Zwart J.-A., Nurnberger J.I., Stahl E.A., Di Florio A., Adan R.A.H., Ando T., Aschauer H., Baker J.H., Bencko V., Birgegard A., Boden J.M., Boehm I., Boni C., Perica V.B., Buehren K., Bulik C.M., Burghardt R., Carlberg L., Cassina M., Clementi M., Cone R.D., Courtet P., Crowley J.J., Danner U.N., Davis O.S.P., de Zwaan M., Dedoussis G., Degortes D., DeSocio J.E., Dick D.M., Dina C., Dmitrzak-Weglarz M., Martinez E.D., Duncan L.E., Egberts K., Mattingsdal M., McDevitt S., Meulenbelt I., Micali N., Mitchell J., Mitchell K., Monteleone P., Monteleone A.M., Munn-Chernoff M.A., Nacmias B., Navratilova M., Ntalla I., Olsen C.M., O'Toole J.K., Padyukov L., Palotie A., Pantel J., Papezova H., Parker R., Pearson J.F., Ehrlich S., Escaramis G., Espeseth T., Estivill X., Farmer A., Favaro A., Fischer K., Floyd J.A.B., Focker M., Foretova L., Forzan M., Franklin C.S., Gambaro G., Giuranna J., Giusti-Rodriquez P., Gonidakis F., Gordon S., Mayora M.G., Guillaume S., Hanscombe K.B., Hatzikotoulas K., Hebebrand J., Helder S.G., Henders A.K., Herpertz-Dahlmann B., Herzog W., Hinney A., Horwood L.J., Hubel C., Petersen L.V., Purves K.L., Raevuori A., Reichborn-Kjennerud T., Ricca V., Ripatti S., Ritschel F., Roberts M., Rybakowski F., Santonastaso P., Scherag A., Schmidt U., Schork N.J., Schosser A., Seitz J., Slachtova L., Slagboom P.E., Slof-Op 't Landt M.C.T., Slopien A., Soranzo N., Sorbi S., Southam L., Steen V.W., Huckins L.M., Hudson J.I., Imgart H., Inoko H., Janout V., Jordan J., Julia A., Kalsi G., Kaminska D., Kaprio J., Karhunen L., Karwautz A., Kas M.J.H., Kennedy M.A., Keski-Rahkonen A., Kiezebrink K., Kim Y.-R., Kirk K.M., Klareskog L., Knudsen G.P.S., Larsen J.T., Le Hellard S., Leppa V.M., Lichtenstein P., Lin B.D., Lundervold A., Luykx J., Maj M., Mannik K., Marsal S., Stuber G.D., Szatkiewicz J.P., Tachmazidou I., Tenconi E., Tortorella A., Tozzi F., Tsitsika A., Tyszkiewicz-Nwafor M., Tziouvas K., van Elburg A.A., van Furth E.F., Wade T.D., Wagner G., Walton E., Whiteman D.C., Wichmann H.E., Widen E., Yao S., Zeggini E., Zerwas S., Zipfel S., Jungkunz M., Dietl L., Schwarze C.E., Dahmen N., Schott B.H., Mobascher A., Crivelli S., Dennis M.F., Harvey P.D., Carter B.W., Huffman J.E., Jacobson D., Madduri R., Olsen M.K., Pestian J., Gaziano J.M., Muralidhar S., Ramoni R., Beckham J., Chang K.-M., O'Donnell C.J., Tsao P.S., Breeling J., Huang G., Romero J.P.C., Moser J., Whitbourne S.B., Brewer J.V., Aslan M., Connor T., Argyres D.P., Stephens B., Brophy M.T., Humphries D.E., Selva L.E., Do N., Shayan S., Cho K., Pyarajan S., Hauser E., Sun Y., Zhao H., Wilson P., McArdle R., Dellitalia L., Mattocks K., Harley J., Zablocki C.J., Whittle J., Jacono F., Gutierrez S., Gibson G., Hammer K., Kaminsky L., Villareal G., Kinlay S., Xu J., Hamner M., Mathew R., Bhushan S., Iruvanti P., Godschalk M., Ballas Z., Ivins D., Mastorides S., Moorman J., Gappy S., Klein J., Ratcliffe N., Florez H., Okusaga O., Murdoch M., Sriram P., Yeh S.S., Tandon N., Jhala D., Aguayo S., Cohen D., Sharma S., Liangpunsakul S., Oursler K.A., Whooley M., Ahuja S., Constans J., Meyer P., Greco J., Rauchman M., Servatius R., Gaddy M., Wallbom A., Morgan T., Stapley T., Sherman S., Ross G., Tsao P., Strollo P., Boyko E., Meyer L., Gupta S., Huq M., Fayad J., Hung A., Lichy J., Hurley R., Robey B., Striker R., Erlangsen A., Kessler R.C., Porteous D., Ursano R.J., Wasserman D., Coon H., Demontis D., Docherty A.R., Kuo P.-H., Mann J.J., Renteria M.E., Stein M.B., and Willour V.
Subjects: LD SCORE REGRESSION, Genome-wide association study, Suicide, Attempted, 3124 Neurology and psychiatry, 0302 clinical medicine, Risk Factors, Insomnia, Suicide attempt, GWAS, Suïcidi, Depression (differential diagnoses), Cause of death, Psychiatry, 0303 health sciences, Factors de risc en les malalties, Mental Disorders, Genetic Correlation, Genome-wide Association Study, Pleiotropy, Polygenicity, Suicide, Suicide Attempt, DEPRESSION, 3. Good health, Genetic correlation, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Depressive Disorder, Major, Mental illness, Cohort, SEX, medicine.symptom, Human, medicine.medical_specialty, Risk factors in diseases, BF, Locus (genetics), BEHAVIORS, Psykiatri, EVENTS, 03 medical and health sciences, SDG 3 - Good Health and Well-being, medicine, ddc:610, GENOME-WIDE ASSOCIATION, IDEATION, Socioeconomic status, METAANALYSIS, Biological Psychiatry, 030304 developmental biology, business.industry, Risk Factor, Genetic architecture, THOUGHTS, RC0321, business, Malalties mentals, 030217 neurology & neurosurgery
Abstract: Statistical analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org) hosted by SURFsara and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu), which is supported by the Office of Research Infrastructure of the National Institutes of Health (Grant Nos. S10OD018522 and S10OD026880). This work was conducted in part using the resources of the Advanced Computing Center for Research and Education at Vanderbilt University, Nashville, TN. This work was funded by the National Institutes of Health (Grant Nos. R01MH116269 and R01MH121455 [to DMR]), NIGMS of the National Institutes of Health (Grant No. T32GM007347 [to JK]), and the Brain & Behavior Research Foundation (NARSAD Young Investigator Award No. 29551 [to NM])., BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders., Office of Research Infrastructure of the National Institutes of Health S10OD018522 S10OD026880, United States Department of Health & Human Services, National Institutes of Health (NIH) - USA R01MH116269 R01MH121455, NIH National Institute of General Medical Sciences (NIGMS) T32GM007347 NARSAD 29551
Published: 2022
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24. Cannabis Use and CKD: Epidemiological Associations and Mendelian Randomization

Author: Sergio Dellepiane, Ishan Paranjpe, Madhumitha Rajagopal, Samir Kamat, Ross O’Hagan, Faris Gulamali, Joshua L. Rein, Alexander W. Charney, Ron Do, Steven Coca, Benjamin S. Glicksberg, and Girish N. Nadkarni
Subjects: Nephrology, Internal Medicine
Published: 2023
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25. Acute COVID-19 gene-expression profiles show multiple etiologies of long-term sequelae

Author: Laura M. Huckins, Jessica Le Berichel, Brian Fennessy, Edgar Gonzalez-Kozlova, Kai Nie, Seunghee Kim-Schulze, Kevin Tuballes, Lillian Wilkins, Konstantinos Mouskas, Esther Cheng, Aviva G. Beckmann, Mario A. Cedillo, Panagiotis Roussos, Lauren Lepow, Ryan Thompson, Eric E. Schadt, Nancy Francoeur, Nicole W. Simons, Gabriel E. Hoffman, Sacha Gnjatic, Miriam Merad, Noam D. Beckmann, Nicholas Zaki, Thomas U. Marron, Christie Chang, Alexander W. Charney, Vanessa Barcessat, Girish N. Nadkarni, Ying-Chih Wang, Jessica S. Johnson, Diane Marie Del-Valle, Benjamin S. Glicksberg, and Robert Sebra
Subjects: Immune system, Coronavirus disease 2019 (COVID-19), business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Concomitant, Gene expression, Immunology, Etiology, Medicine, business, Virus, Article, Whole blood
Abstract: Summary ParagraphTwo years into the SARS-CoV-2 pandemic, the post-acute sequelae of infection are compounding the global health crisis. Often debilitating, these sequelae are clinically heterogeneous and of unknown molecular etiology. Here, a transcriptome-wide investigation of this new condition was performed in a large cohort of acutely infected patients followed clinically into the post-acute period. Gene expression signatures of post-acute sequelae were already present in whole blood during the acute phase of infection, with both innate and adaptive immune cells involved. Plasma cells stood out as driving at least two distinct clusters of sequelae, one largely dependent on circulating antibodies against the SARS-CoV-2 spike protein and the other antibody-independent. Altogether, multiple etiologies of post-acute sequelae were found concomitant with SARS-CoV-2 infection, directly linking the emergence of these sequelae with the host response to the virus.
Published: 2021

26. Circulating proteins to predict adverse COVID-19 outcomes

Author: Edgar Gonzalez-Kozlova, David R. Morrison, Branka Vulesevic, Nofar Kimchi, Robert Marvin, Maik Pietzner, Zaman Afrasiabi, Kimberly Argueta, Louis Petitjean, Naomi Duggan, Ryan Thompson, Meriem Bouab, Manishkumar Patel, Kevin Tuballes, Ieisha Scott, J. Brent Richards, Mario A. Cedillo, Nicole W. Simons, Jocelyn Harris, Tala Abdullah, Claudia Langenberg, Danielle Henry, Vincenzo Forgetta, Daniel Kaufmann, Madeleine Durand, Chen-Yang Su Mr., Michael A Hinterberg, Elsa Brunet-Ratnasingham, Celia M. T. Greenwood, Miriam Merad, Wonseok Jeon, Alexander W. Charney, Sacha Gnjatic, Noam D. Beckmann, Xiaoqing Xue, Nicolas Zaki, Julia Carrasco-Zanini, Diane Marie Del Valle, Joelle Pineau, Esther Cheng, Tomoko Nakanishi, Olumide Adeleye, Kai Nie, Chantal DeLuca, Konstantinos Mouskas, Thomas U. Marron, Marc Afilalo, Guillaume Butler-Laporte, Yiheng Chen, Yossi Farjoun, Yara Moussa, Vincent Mooser, Eric E. Schadt, Clare Paterson, Noor Almamlouk, Chris Tselios, Nathalie Brassard, Sirui Zhou, Hui Xie, Ephraim Kenigsberg, Nardin Rezk, Seunghee Kim-Schulze, Laetitia Laurent, Charlotte Guzman, Erwin Schurr, and Joanthan Afilalo
Subjects: Oncology, medicine.medical_specialty, Receiver operating characteristic, Coronavirus disease 2019 (COVID-19), business.industry, medicine.medical_treatment, Disease progression, Age and sex, Cytokine, Internal medicine, Cohort, Medicine, Generalizability theory, business, Predictive modelling
Abstract: Predicting COVID-19 severity is difficult, and the biological pathways involved are not fully understood. To approach this problem, we measured 4,701 circulating human protein abundances in two independent cohorts totaling 986 individuals. We then trained prediction models including protein abundances and clinical risk factors to predict adverse COVID-19 outcomes in 417 subjects and tested these models in a separate cohort of 569 individuals. For severe COVID-19, a baseline model including age and sex provided an area under the receiver operator curve (AUC) of 65% in the test cohort. Selecting 92 proteins from the 4,701 unique protein abundances improved the AUC to 88% in the training cohort, which remained relatively stable in the testing cohort at 86%, suggesting good generalizability. Proteins selected from different adverse COVID-19 outcomes were enriched for cytokine and cytokine receptors, but more than half of the enriched pathways were not immune-related. Taken together, these findings suggest that circulating proteins measured at early stages of disease progression are reasonably accurate predictors of adverse COVID-19 outcomes. Further research is needed to understand how to incorporate protein measurement into clinical care.
Published: 2021
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27. Molecular states during acute COVID-19 reveal distinct etiologies of long-term sequelae

Author: Ryan C, Thompson, Nicole W, Simons, Lillian, Wilkins, Esther, Cheng, Diane Marie, Del Valle, Gabriel E, Hoffman, Carlo, Cervia, Brian, Fennessy, Konstantinos, Mouskas, Nancy J, Francoeur, Jessica S, Johnson, Lauren, Lepow, Jessica, Le Berichel, Christie, Chang, Aviva G, Beckmann, Ying-Chih, Wang, Kai, Nie, Nicholas, Zaki, Kevin, Tuballes, Vanessa, Barcessat, Mario A, Cedillo, Dan, Yuan, Laura, Huckins, Panos, Roussos, Thomas U, Marron, Benjamin S, Glicksberg, Girish, Nadkarni, James R, Heath, Edgar, Gonzalez-Kozlova, Onur, Boyman, Seunghee, Kim-Schulze, Robert, Sebra, Miriam, Merad, Sacha, Gnjatic, Eric E, Schadt, Alexander W, Charney, and Renyuan, Zha
Abstract: Post-acute sequelae of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are debilitating, clinically heterogeneous and of unknown molecular etiology. A transcriptome-wide investigation was performed in 165 acutely infected hospitalized individuals who were followed clinically into the post-acute period. Distinct gene expression signatures of post-acute sequelae were already present in whole blood during acute infection, with innate and adaptive immune cells implicated in different symptoms. Two clusters of sequelae exhibited divergent plasma-cell-associated gene expression patterns. In one cluster, sequelae associated with higher expression of immunoglobulin-related genes in an anti-spike antibody titer-dependent manner. In the other, sequelae associated independently of these titers with lower expression of immunoglobulin-related genes, indicating lower non-specific antibody production in individuals with these sequelae. This relationship between lower total immunoglobulins and sequelae was validated in an external cohort. Altogether, multiple etiologies of post-acute sequelae were already detectable during SARS-CoV-2 infection, directly linking these sequelae with the acute host response to the virus and providing early insights into their development.
Published: 2021

28. Genetics of the human microglia regulome refines Alzheimer's disease risk loci

Author: Panos Roussos, Samir Rahman, Towfique Raj, Alexander W. Charney, Roman Kosoy, Vahram Haroutunian, Zhiping Shao, Katia de Paiva Lopes, Steven P. Kleopoulos, Gabriel E. Hoffman, Brian H. Kopell, Jack Humphrey, John F. Fullard, Jaroslav Bendl, David A. Bennett, Biao Zeng, Pengfei Dong, and Christopher P. Kellner
Subjects: SPI1, Microglia, Brain, Membrane Proteins, Regulome, Neurodegenerative Diseases, Disease, Computational biology, Biology, Article, Chromatin, Transcriptome, medicine.anatomical_structure, Alzheimer Disease, Gene expression, medicine, Genetics, Humans, Carrier Proteins, Transcription factor
Abstract: Microglia are brain resident myeloid cells that play a critical role in neuroimmunity and the etiology of Alzheimer’s Disease (AD). Yet our understanding of how the genetic regulatory landscape controls microglial function and contributes to disease is limited. Here, we performed transcriptome and chromatin accessibility profiling in primary human microglia from 150 donors to identify genetically-driven variation and cell-specific enhancer-promoter interactions. Integrative fine-mapping analysis identified putative regulatory mechanisms for 21 AD risk loci, of which 18 were refined to a single gene, including 3 novel genes (KCNN4, FIBP and LRRC25). Transcription factor regulatory networks captured AD risk variation and identified SPI1 as a key regulator of microglia expression and AD risk. This comprehensive resource capturing variation in the human microglia regulome provides novel insights into the etiology of neurodegenerative disease.One-Sentence SummaryCharacterizing the genetic regulation of chromatin accessibility and gene expression in human microglia refines molecular mechanisms of Alzheimer’s disease risk loci.
Published: 2021

29. Targeting the coronavirus nucleocapsid protein through GSK-3 inhibition

Author: Rebecca L. Myers, Wade H. Berrettini, Gustavo Garcia, Holly Ramage, Sara Cherry, Daniel J. Rader, David C. Schultz, Marcelo G. Kazanietz, Jacob J. Michaelson, Xiaolei Liu, Vaithilingaraja Arumugaswami, Robert Damoiseaux, Anastasia Lucas, Peter S. Klein, Alexander W. Charney, Arvind Kumar, Marylyn D. Ritchie, Anurag Verma, and William Coryell
Subjects: Adult, Male, COVID19, viruses, coronavirus, nucleocapsid, macromolecular substances, Biology, medicine.disease_cause, Microbiology, Article, Glycogen Synthase Kinase 3, GSK-3, Transcription (biology), medicine, Coronavirus Nucleocapsid Proteins, Humans, Molecular Targeted Therapy, Phosphorylation, GSK3B, Coronavirus, Aged, Retrospective Studies, Multidisciplinary, HEK 293 cells, virus diseases, COVID-19, Biological Sciences, Middle Aged, medicine.disease, Phosphoproteins, Virology, respiratory tract diseases, body regions, HEK293 Cells, Viral replication, Virion assembly, lithium, Lithium Compounds, Middle East respiratory syndrome, Female
Abstract: Significance COVID-19 is taking a major toll on personal health, healthcare systems, and the global economy. With three betacoronavirus epidemics in less than 20 y, there is an urgent need for therapies to combat new and existing coronavirus outbreaks. Our analysis of clinical data from over 300,000 patients in three major health systems demonstrates a 50% reduced risk of COVID-19 in patients taking lithium, a direct inhibitor of glycogen synthase kinase-3 (GSK-3). We further show that GSK-3 is essential for phosphorylation of the SARS-CoV-2 nucleocapsid protein and that GSK-3 inhibition blocks SARS-CoV-2 infection in human lung epithelial cells. These findings suggest an antiviral strategy for COVID-19 and new coronaviruses that may arise in the future., The coronaviruses responsible for severe acute respiratory syndrome (SARS-CoV), COVID-19 (SARS-CoV-2), Middle East respiratory syndrome-CoV, and other coronavirus infections express a nucleocapsid protein (N) that is essential for viral replication, transcription, and virion assembly. Phosphorylation of N from SARS-CoV by glycogen synthase kinase 3 (GSK-3) is required for its function and inhibition of GSK-3 with lithium impairs N phosphorylation, viral transcription, and replication. Here we report that the SARS-CoV-2 N protein contains GSK-3 consensus sequences and that this motif is conserved in diverse coronaviruses, raising the possibility that SARS-CoV-2 may be sensitive to GSK-3 inhibitors, including lithium. We conducted a retrospective analysis of lithium use in patients from three major health systems who were PCR-tested for SARS-CoV-2. We found that patients taking lithium have a significantly reduced risk of COVID-19 (odds ratio = 0.51 [0.35–0.74], P = 0.005). We also show that the SARS-CoV-2 N protein is phosphorylated by GSK-3. Knockout of GSK3A and GSK3B demonstrates that GSK-3 is essential for N phosphorylation. Alternative GSK-3 inhibitors block N phosphorylation and impair replication in SARS-CoV-2 infected lung epithelial cells in a cell-type–dependent manner. Targeting GSK-3 may therefore provide an approach to treat COVID-19 and future coronavirus outbreaks.
Published: 2021

30. Prognostic value of polygenic risk scores for adults with psychosis

Author: Paul F. O'Reilly, Steven A. McCarroll, Mark Hyman Rapaport, Noam D. Beckmann, Eric D. Achtyes, Dolores Malaspina, Ruth J. F. Loos, Michele T. Pato, Gillian M. Belbin, Liam Cotter, Alexander W. Charney, Michael Preuss, Carlos N. Pato, Benjamin S. Glicksberg, Ayman H. Fanous, Deepak Kaji, Eimear E. Kenny, Peter F. Buckley, Douglas S. Lehrer, Tim B. Bigdeli, Tielman Van Vleck, Isotta Landi, Girish N. Nadkarni, and Eric E. Schadt
Subjects: Adult, Male, medicine.medical_specialty, Psychosis, Multifactorial Inheritance, MEDLINE, Disease, General Biochemistry, Genetics and Molecular Biology, Article, Risk Factors, Medicine, Humans, Genetic Predisposition to Disease, business.industry, General Medicine, Middle Aged, medicine.disease, Prognosis, Psychotic Disorders, Schizophrenia, Predictive power, Medical genetics, Polygenic risk score, Female, Psychiatric interview, business, Clinical psychology, Genome-Wide Association Study
Abstract: Polygenic risk scores (PRS) summarize genetic liability to a disease at the individual level, and the aim is to use them as biomarkers of disease and poor outcomes in real-world clinical practice. To date, few studies have assessed the prognostic value of PRS relative to standards of care. Schizophrenia (SCZ), the archetypal psychotic illness, is an ideal test case for this because the predictive power of the SCZ PRS exceeds that of most other common diseases. Here, we analyzed clinical and genetic data from two multi-ethnic cohorts totaling 8,541 adults with SCZ and related psychotic disorders, to assess whether the SCZ PRS improves the prediction of poor outcomes relative to clinical features captured in a standard psychiatric interview. For all outcomes investigated, the SCZ PRS did not improve the performance of predictive models, an observation that was generally robust to divergent case ascertainment strategies and the ancestral background of the study participants. The inclusion of polygenic risk scores does not improve the performance of standard-of-care predictive models of disease outcomes in patients with psychosis.
Published: 2021

31. Electroencephalography at the height of a pandemic: EEG findings in patients with COVID-19

Author: Gabriela B. Tantillo, Nathalie Jetté, Kapil Gururangan, Parul Agarwal, Lara Marcuse, Anuradha Singh, Jonathan Goldstein, Churl-Su Kwon, Mandip S. Dhamoon, Allison Navis, Girish N. Nadkarni, Alexander W. Charney, James J. Young, Leah J. Blank, Madeline Fields, and Ji Yeoun Yoo
Subjects: Neurology, Seizures, Physiology (medical), COVID-19, Humans, Electroencephalography, Neurology (clinical), Pandemics, Sensory Systems, Retrospective Studies
Abstract: To characterize continuous video electroencephalogram (VEEG) findings of hospitalized COVID-19 patients.We performed a retrospective chart review of patients admitted at three New York City hospitals who underwent VEEG at the peak of the COVID-19 pandemic. Demographics, comorbidities, neuroimaging, VEEG indications and findings, treatment, and outcomes were collected.Of 93 patients monitored, 77% had severe COVID-19 and 40% died. Acute ischemic or hemorrhagic stroke was present in 26% and 15%, respectively. Most common VEEG indications were encephalopathy/coma (60%) and seizure-like movements (38%). Most common VEEG findings were generalized slowing (97%), generalized attenuation (31%), generalized periodic discharges (17%) and generalized sharp waves (15%). Epileptiform abnormalities were present in 43% and seizures in 8% of patients, all of whom had seizure risk factors. Factors associated with an epileptiform VEEG included increasing age (OR 1.07, p = 0.001) and hepatic/renal failure (OR 2.99, p = 0.03).Most COVID-19 patients who underwent VEEG monitoring had severe COVID-19 and over one-third had acute cerebral injury (e.g., stroke, anoxia). Seizures were uncommon. VEEG findings were nonspecific.VEEG findings in this cohort of hospitalized COVID-19 patients were those often seen in critical illness. Seizures were uncommon and occurred in the setting of common seizure risk factors.
Published: 2021

32. Downregulation of exhausted cytotoxic T cells in gene expression networks of multisystem inflammatory syndrome in children

Author: Noam D. Beckmann, Nancy J. Francoeur, Diane Marie Del Valle, Gurpawan Kang, Anh Do, Emily Moya, Lillian Wilkins, Jessica Le Berichel, Christie Chang, Robert Marvin, Sharlene Calorossi, Phillip H. Comella, Alona Lansky, Laura Walker, Nancy Yi, Alex Yu, Jonathan Chung, Matthew Hartnett, Melody Eaton, Sandra Hatem, Hajra Jamal, Alara Akyatan, Esther Cheng, Alexandra Tabachnikova, Lora E. Liharska, Liam Cotter, Brian Fennessy, Akhil Vaid, Guillermo Barturen, Hardik Shah, Ying-chih Wang, Shwetha Hara Sridhar, Juan Soto, Lauren Lepow, Swaroop Bose, Kent Madrid, Ethan Ellis, Elyze Merzier, Konstantinos Vlachos, Nataly Fishman, Manying Tin, Melissa Smith, Hui Xie, Manishkumar Patel, Aviva G. Beckmann, Kai Nie, Kimberly Argueta, Jocelyn Harris, Neha Karekar, Craig Batchelor, Jose Lacunza, Mahlet Yishak, Kevin Tuballes, Ieisha Scott, Arvind Kumar, Scott R. Tyler, Suraj Jaladanki, Charuta Agashe, Ryan Thompson, Evan Clark, Bojan Losic, Lauren Peters, The Mount Sinai COVID-19 Biobank Team, Panagiotis Roussos, Jun Zhu, Wenhui Wang, Konstantinos Mouskas, Andrew Kasarskis, Benjamin S. Glicksberg, Girish Nadkarni, Dusan Bogunovic, Cordelia Elaiho, Sandeep Gangadharan, George Ofori-Amanfo, Kasey Alesso-Carra, Kenan Onel, Karen M. Wilson, Nicole W. Simons, Carmen Argmann, Supinda Bunyavanich, Marta E. Alarcón-Riquelme, Thomas U. Marron, Adeeb Rahman, Seunghee Kim-Schulze, Sacha Gnjatic, Bruce D. Gelb, Miriam Merad, Robert Sebra, Gabriel E. Hoffman, Eric E. Schadt, and Alexander W. Charney
Subjects: Male, TBX21, Cell type, Adolescent, Science, Down-Regulation, General Physics and Astronomy, Inflammation, CD8-Positive T-Lymphocytes, Mucocutaneous Lymph Node Syndrome, Biology, General Biochemistry, Genetics and Molecular Biology, Pathogenesis, Transcriptome, Young Adult, CD57 Antigens, Downregulation and upregulation, otorhinolaryngologic diseases, medicine, Humans, Cytotoxic T cell, Child, Multidisciplinary, SARS-CoV-2, Infant, Newborn, COVID-19, Infant, General Chemistry, CD56 Antigen, Systemic Inflammatory Response Syndrome, Killer Cells, Natural, Child, Preschool, Immunology, Female, medicine.symptom, CD8
Abstract: Multisystem inflammatory syndrome in children (MIS-C) presents with fever, inflammation and pathology of multiple organs in individuals under 21 years of age in the weeks following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Although an autoimmune pathogenesis has been proposed, the genes, pathways and cell types causal to this new disease remain unknown. Here we perform RNA sequencing of blood from patients with MIS-C and controls to find disease-associated genes clustered in a co-expression module annotated to CD56dimCD57+ natural killer (NK) cells and exhausted CD8+ T cells. A similar transcriptome signature is replicated in an independent cohort of Kawasaki disease (KD), the related condition after which MIS-C was initially named. Probing a probabilistic causal network previously constructed from over 1,000 blood transcriptomes both validates the structure of this module and reveals nine key regulators, including TBX21, a central coordinator of exhausted CD8+ T cell differentiation. Together, this unbiased, transcriptome-wide survey implicates downregulation of NK cells and cytotoxic T cell exhaustion in the pathogenesis of MIS-C., Multisystem inflammatory syndrome in children (MIS-C) onsets in COVID-19 patients with manifestations similar to Kawasaki disease (KD). Here the author probe the peripheral blood transcriptome of MIS-C patients to find signatures related to natural killer (NK) cell activation and CD8+ T cell exhaustion that are shared with KD patients.
Published: 2021

33. Acute Kidney Injury in Patients Hospitalized With COVID-19 in New York City: Temporal Trends From March 2020 to April 2021

Author: Zahi A. Fayad, Akhil Vaid, Suraj K. Jaladanki, Benjamin S. Glicksberg, Alexander W. Charney, Erwin P. Bottinger, Steven G. Coca, Lili Chan, John Cijiang He, Sergio Dellepiane, and Girish N. Nadkarni
Subjects: 2019-20 coronavirus outbreak, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), business.industry, medicine.medical_treatment, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Kidney Replacement Therapy, Acute kidney injury, COVID-19, Acute Kidney Injury, medicine.disease, Diseases of the genitourinary system. Urology, Nephrology, Internal medicine, Hemodialysis, Internal Medicine, medicine, Research Letter, In patient, RC870-923, business
Published: 2021

34. Development of a federated learning approach to predict acute kidney injury in adult hospitalized patients with COVID-19 in New York City

Author: Ashwin Sawant, Sergio Dellepiane, Jie Xu, Benjamin S. Glicksberg, Kush Shah, Akhil Vaid, Lili Chan, Suraj K. Jaladanki, Alexander W. Charney, Girish N. Nadkarni, Patricia Kovatch, Ishan Paranjpe, Fei Wang, and Karandeep Singh
Subjects: Information privacy, Coronavirus disease 2019 (COVID-19), business.industry, Hospitalized patients, privacy protection, Acute kidney injury, Vital signs, Federated learning, Data security, COVID-19, Acute Kidney Injury, medicine.disease, Article, machine learning, electronic health records, medicine, Medical emergency, business, Kidney disease
Abstract: Federated learning is a technique for training predictive models without sharing patient-level data, thus maintaining data security while allowing inter-institutional collaboration. We used federated learning to predict acute kidney injury within three and seven days of admission, using demographics, comorbidities, vital signs, and laboratory values, in 4029 adults hospitalized with COVID-19 at five sociodemographically diverse New York City hospitals, between March-October 2020. Prediction performance of federated models was generally higher than single-hospital models and was comparable to pooled-data models. In the first use-case in kidney disease, federated learning improved prediction of a common complication of COVID-19, while preserving data privacy.
Published: 2021

35. IL10RB as a key regulator of COVID-19 host susceptibility and severity

Author: Sanan Venkatesh, Sudha K Iyengar, Jiantao Bian, Themistocles L. Assimes, Miriam Merad, Alexander W. Charney, Lina Gao, Jennifer Lee, Daisy A. Hoagland, Kristina Dobrindt, Kristen J. Brennand, Panos Roussos, Julie Lynch, André Corvelo, John F. Fullard, Schahram Akbarian, Rob Striker, Wen Zhang, Noam D. Beckmann, Kelly Cho, Eric E. Schadt, Shiuh-Wen Luoh, James M. Vicari, Gabriel E. Hoffman, Georgios Voloudakis, Benjamin R. tenOever, Kyung Min Lee, and Shan Jiang
Subjects: Transcriptome, Drug repositioning, Candidate gene, In silico, Genetic predisposition, Druggability, Computational biology, Biology, Gene, Viral load, Article
Abstract: BackgroundRecent efforts have identified genetic loci that are associated with coronavirus disease 2019 (COVID-19) infection rates and disease outcome severity. Translating these genetic findings into druggable genes and readily available compounds that reduce COVID-19 host susceptibility is a critical next step.MethodsWe integrate COVID-19 genetic susceptibility variants, multi-tissue genetically regulated gene expression (GReX) and perturbargen signatures to identify candidate genes and compounds that reverse the predicted gene expression dysregulation associated with COVID-19 susceptibility. The top candidate gene is validated by testing both its GReX and observed blood transcriptome association with COVID-19 severity, as well as by in vitro perturbation to quantify effects on viral load and molecular pathway dysregulation. We validate the in silico drug repositioning analysis by examining whether the top candidate compounds decrease COVID-19 incidence based on epidemiological evidence.ResultsWe identify IL10RB as the top key regulator of COVID-19 host susceptibility. Predicted GReX up-regulation of IL10RB and higher IL10RB expression in COVID-19 patient blood is associated with worse COVID-19 outcomes. In vitro IL10RB overexpression is associated with increased viral load and activation of immune-related molecular pathways. Azathioprine and retinol are prioritized as candidate compounds to reduce the likelihood of testing positive for COVID-19.ConclusionsWe establish an integrative data-driven approach for gene target prioritization. We identify and validate IL10RB as a suitable molecular target for modulation of COVID-19 host susceptibility. Finally, we provide evidence for a few readily available medications that would warrant further investigation as drug repositioning candidates.
Published: 2021

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

Author: Matteo D’Antonio, Jennifer P. Nguyen, Timothy D. Arthur, Hiroko Matsui, Agnieszka D’Antonio-Chronowska, Kelly A. Frazer, Benjamin M. Neale, Mark Daly, Andrea Ganna, Christine Stevens, Gita A. Pathak, Shea J. Andrews, Masahiro Kanai, Mattia Cordioli, Juha Karjalainen, Renato Polimanti, Matti Pirinen, Nadia Harerimana, Kumar Veerapen, Brooke Wolford, Huy Nguyen, Matthew Solomonson, Rachel G. Liao, Karolina Chwialkowska, Amy Trankiem, Mary K. Balaconis, Caroline Hayward, Anne Richmond, Archie Campbell, Marcela Morris, Chloe Fawns-Ritchie, Joseph T. Glessner, Douglas M. Shaw, Xiao Chang, Hannah Polikowski, Petty E. Lauren, Hung-Hsin Chen, Zhu Wanying, Hakon Hakonarson, David J. Porteous, Jennifer Below, Kari North, Joseph B. McCormick, Paul R.H.J. Timmers, James F. Wilson, Albert Tenesa, Kenton D’Mellow, Shona M. Kerr, Mari E.K. Niemi, Lindokuhle Nkambul, Kathrin Aprile von Hohenstaufen, Ali Sobh, Madonna M. Eltoukhy, Amr M. Yassen, Mohamed A.F. Hegazy, Kamal Okasha, Mohammed A. Eid, Hanteera S. Moahmed, Doaa Shahin, Yasser M. El-Sherbiny, Tamer A. Elhadidy, Mohamed S. Abd Elghafar, Jehan J. El-Jawhari, Attia A.S. Mohamed, Marwa H. Elnagdy, Amr Samir, Mahmoud Abdel-Aziz, Walid T. Khafaga, Walaa M. El-Lawaty, Mohamed S. Torky, Mohamed R. El-shanshory, Chiara Batini, Paul H. Lee, Nick Shrine, Alexander T. Williams, Martin D. Tobin, Anna L. Guyatt, Catherine John, Richard J. Packer, Altaf Ali, Robert C. Free, Xueyang Wang, Louise V. Wain, Edward J. Hollox, Laura D. Venn, Catherine E. Bee, Emma L. Adams, Ahmadreza Niavarani, Bahareh Sharififard, Rasoul Aliannejad, Ali Amirsavadkouhi, Zeinab Naderpour, Hengameh Ansari Tadi, Afshar Etemadi Aleagha, Saeideh Ahmadi, Seyed Behrooz Mohseni Moghaddam, Alireza Adamsara, Morteza Saeedi, Hamed Abdollahi, Abdolmajid Hosseini, Pajaree Chariyavilaskul, Monpat Chamnanphon, Thitima B. Suttichet, Vorasuk Shotelersuk, Monnat Pongpanich, Chureerat Phokaew, Wanna Chetruengchai, Watsamon Jantarabenjakul, Opass Putchareon, Pattama Torvorapanit, Thanyawee Puthanakit, Pintip Suchartlikitwong, Nattiya Hirankarn, Voraphoj Nilaratanakul, Pimpayao Sodsai, Ben M. Brumpton, Kristian Hveem, Cristen Willer, Wei Zhou, Tormod Rogne, Erik Solligard, Bjørn Olav Åsvold, Malak Abedalthagafi, Manal Alaamery, Saleh Alqahtani, Dona Baraka, Fawz Al Harthi, Ebtehal Alsolm, Leen Abu Safieh, Albandary M. Alowayn, Fatimah Alqubaishi, Amal Al Mutairi, Serghei Mangul, Abdulraheem Alshareef, Mona Sawaji, Mansour Almutairi, Nora Aljawini, Nour Albesher, Yaseen M. Arabi, Ebrahim S. Mahmoud, Amin K. Khattab, Roaa T. Halawani, Ziab Z. Alahmadey, Jehad K. Albakri, Walaa A. Felemban, Bandar A. Suliman, Rana Hasanato, Laila Al-Awdah, Jahad Alghamdi, Deema AlZahrani, Sameera AlJohani, Hani Al-Afghani, May Alrashed, Nouf AlDhawi, Hadeel AlBardis, Sarah Alkwai, Moneera Alswailm, Faisal Almalki, Maha Albeladi, Iman Almohammed, Eman Barhoush, Anoud Albader, Salam Massadeh, Abdulaziz AlMalik, Sara Alotaibi, Bader Alghamdi, Junghyun Jung, Mohammad S. Fawzy, Yunsung Lee, Per Magnus, Lill-Iren S. Trogstad, Øyvind Helgeland, Jennifer R. Harris, Massimo Mangino, Tim D. Spector, Duncan Emma, Sandra P. Smieszek, Bartlomiej P. Przychodzen, Christos Polymeropoulos, Vasilios Polymeropoulos, Mihael H. Polymeropoulos, Israel Fernandez-Cadenas, Jordi Perez-Tur, Laia Llucià-Carol, Natalia Cullell, Elena Muiño, Jara Cárcel-Márquez, Marta L. DeDiego, Lara Lloret Iglesias, Anna M. Planas, Alex Soriano, Veronica Rico, Daiana Agüero, Josep L. Bedini, Francisco Lozano, Carlos Domingo, Veronica Robles, Francisca Ruiz-Jaén, Leonardo Márquez, Juan Gomez, Eliecer Coto, Guillermo M. Albaiceta, Marta García-Clemente, David Dalmau, Maria J. Arranz, Beatriz Dietl, Alex Serra-Llovich, Pere Soler, Roger Colobrán, Andrea Martín-Nalda, Alba Parra Martínez, David Bernardo, Silvia Rojo, Aida Fiz-López, Elisa Arribas, Paloma de la Cal-Sabater, Tomás Segura, Esther González-Villa, Gemma Serrano-Heras, Joan Martí-Fàbregas, Elena Jiménez-Xarrié, Alicia de Felipe Mimbrera, Jaime Masjuan, Sebastian García-Madrona, Anna Domínguez-Mayoral, Joan Montaner Villalonga, Paloma Menéndez-Valladares, Daniel I. Chasman, Julie E. Buring, Paul M. Ridker, Giulianini Franco, Howard D. Sesso, JoAnn E. Manson, Joseph R. Glessner, Carolina Medina-Gomez, Andre G. Uitterlinden, M. Arfan Ikram, Kati Kristiansson, Sami Koskelainen, Markus Perola, Kati Donner, Katja Kivinen, Aarno Palotie, Samuli Ripatti, Sanni Ruotsalainen, Mari Kaunisto, null FinnGen, Tomoko Nakanishi, Guillaume Butler-Laporte, Vincenzo Forgetta, David R. Morrison, Biswarup Ghosh, Laetitia Laurent, Alexandre Belisle, Danielle Henry, Tala Abdullah, Olumide Adeleye, Noor Mamlouk, Nofar Kimchi, Zaman Afrasiabi, Nardin Rezk Branka Vulesevic, Meriem Bouab, Charlotte Guzman, Louis Petitjean, Chris Tselios, Xiaoqing Xue, Erwin Schurr, Jonathan Afilalo, Marc Afilalo, Maureen Oliveira, Bluma Brenner, Pierre Lepage, Jiannis Ragoussis, Daniel Auld, Nathalie Brassard, Madeleine Durand, Michaël Chassé, Daniel E. Kaufmann, G. Mark Lathrop, Vincent Mooser, J. Brent Richards, Rui Li, Darin Adra, Souad Rahmouni, Michel Georges, Michel Moutschen, Benoit Misset, Gilles Darcis, Julien Guiot, Julien Guntz, Samira Azarzar, Stéphanie Gofflot, Yves Beguin, Sabine Claassen, Olivier Malaise, Pascale Huynen, Christelle Meuris, Marie Thys, Jessica Jacques, Philippe Léonard, Frederic Frippiat, Jean-Baptiste Giot, Anne-Sophie Sauvage, Christian Von Frenckell, Yasmine Belhaj, Bernard Lambermont, Sara Pigazzini, Lindokuhle Nkambule, Michelle Daya, Jonathan Shortt, Nicholas Rafaels, Stephen J. Wicks, Kristy Crooks, Kathleen C. Barnes, Christopher R. Gignoux, Sameer Chavan, Triin Laisk, Kristi Läll, Maarja Lepamets, Reedik Mägi, Tõnu Esko, Ene Reimann, Lili Milani, Helene Alavere, Kristjan Metsalu, Mairo Puusepp, Andres Metspalu, Paul Naaber, Edward Laane, Jaana Pesukova, Pärt Peterson, Kai Kisand, Jekaterina Tabri, Raili Allos, Kati Hensen, Joel Starkopf, Inge Ringmets, Anu Tamm, Anne Kallaste, Pierre-Yves Bochud, Carlo Rivolta, Stéphanie Bibert, Mathieu Quinodoz, Dhryata Kamdar, Noémie Boillat, Semira Gonseth Nussle, Werner Albrich, Noémie Suh, Dionysios Neofytos, Véronique Erard, Cathy Voide, null FHoGID, null RegCOVID, null P-PredictUs, null SeroCOVID, null CRiPSI, Rafael de Cid, Iván Galván-Femenía, Natalia Blay, Anna Carreras, Beatriz Cortés, Xavier Farré, Lauro Sumoy, Victor Moreno, Josep Maria Mercader, Marta Guindo-Martinez, David Torrents, Manolis Kogevinas, Judith Garcia-Aymerich, Gemma Castaño-Vinyals, Carlota Dobaño, Alessandra Renieri, Francesca Mari, Chiara Fallerini, Sergio Daga, Elisa Benetti, Margherita Baldassarri, Francesca Fava, Elisa Frullanti, Floriana Valentino, Gabriella Doddato, Annarita Giliberti, Rossella Tita, Sara Amitrano, Mirella Bruttini, Susanna Croci, Ilaria Meloni, Maria Antonietta Mencarelli, Caterina Lo Rizzo, Anna Maria Pinto, Giada Beligni, Andrea Tommasi, Laura Di Sarno, Maria Palmieri, Miriam Lucia Carriero, Diana Alaverdian, Stefano Busani, Raffaele Bruno, Marco Vecchia, Mary Ann Belli, Nicola Picchiotti, Maurizio Sanarico, Marco Gori, Simone Furini, Stefania Mantovani, Serena Ludovisi, Mario Umberto Mondelli, Francesco Castelli, Eugenia Quiros-Roldan, Melania Degli Antoni, Isabella Zanella, Massimo Vaghi, Stefano Rusconi, Matteo Siano, Francesca Montagnani, Arianna Emiliozzi, Massimiliano Fabbiani, Barbara Rossetti, Elena Bargagli, Laura Bergantini, Miriana D’Alessandro, Paolo Cameli, David Bennett, Federico Anedda, Simona Marcantonio, Sabino Scolletta, Federico Franchi, Maria Antonietta Mazzei, Susanna Guerrini, Edoardo Conticini, Luca Cantarini, Bruno Frediani, Danilo Tacconi, Chiara Spertilli, Marco Feri, Alice Donati, Raffaele Scala, Luca Guidelli, Genni Spargi, Marta Corridi, Cesira Nencioni, Leonardo Croci, Maria Bandini, Gian Piero Caldarelli, Paolo Piacentini, Elena Desanctis, Silvia Cappelli, Anna Canaccini, Agnese Verzuri, Valentina Anemoli, Agostino Ognibene, Alessandro Pancrazzi, Maria Lorubbio, Antonella D’Arminio Monforte, Federica Gaia Miraglia, Massimo Girardis, Sophie Venturelli, Andrea Cossarizza, Andrea Antinori, Alessandra Vergori, Arianna Gabrieli, Agostino Riva, Daniela Francisci, Elisabetta Schiaroli, Francesco Paciosi, Pier Giorgio Scotton, Francesca Andretta, Sandro Panese, Renzo Scaggiante, Francesca Gatti, Saverio Giuseppe Parisi, Stefano Baratti, Matteo Della Monica, Carmelo Piscopo, Mario Capasso, Roberta Russo, Immacolata Andolfo, Achille Iolascon, Giuseppe Fiorentino, Massimo Carella, Marco Castori, Giuseppe Merla, Gabriella Maria Squeo, Filippo Aucella, Pamela Raggi, Carmen Marciano, Rita Perna, Matteo Bassetti, Antonio Di Biagio, Maurizio Sanguinetti, Luca Masucci, Serafina Valente, Marco Mandalà, Alessia Giorli, Lorenzo Salerni, Patrizia Zucchi, Pierpaolo Parravicini, Elisabetta Menatti, Tullio Trotta, Ferdinando Giannattasio, Gabriella Coiro, Fabio Lena, Domenico A. Coviello, Cristina Mussini, Enrico Martinelli, Sandro Mancarella, Luisa Tavecchia, Lia Crotti, Chiara Gabbi, Marco Rizzi, Franco Maggiolo, Diego Ripamonti, Tiziana Bachetti, Maria Teresa La Rovere, Simona Sarzi-Braga, Maurizio Bussotti, Stefano Ceri, Pietro Pinoli, Francesco Raimondi, Filippo Biscarini, Alessandra Stella, Kristina Zguro, Katia Capitani, Claudia Suardi, Simona Dei, Gianfranco Parati, Sabrina Ravaglia, Rosangela Artuso, Giordano Bottà, Paolo Di Domenico, Ilaria Rancan, Antonio Perrella Francesco Bianchi, Davide Romani, Paola Bergomi, Emanuele Catena, Riccardo Colombo, Marco Tanfoni, Antonella Vincenti, Claudio Ferri, Davide Grassi, Gloria Pessina, Mario Tumbarello, Massimo Di Pietro, Ravaglia Sabrina, Sauro Luchi, Chiara Barbieri, Donatella Acquilini, Elena Andreucci, Francesco Vladimiro Segala, Giusy Tiseo, Marco Falcone, Mirjam Lista, Monica Poscente, Oreste De Vivo, Paola Petrocelli, Alessandra Guarnaccia, Silvia Baroni, Albert V. Smith, Andrew P. Boughton, Kevin W. Li, Jonathon LeFaive, Aubrey Annis, Anne E. Justice, Tooraj Mirshahi, Geetha Chittoor, Navya Shilpa Josyula, Jack A. Kosmicki, Manuel A.R. Ferreira, Joseph B. Leader, Dave J. Carey, Matthew C. Gass, Julie E. Horowitz, Michael N. Cantor, Ashish Yadav, Aris Baras, Goncalo R. Abecasis, David A. van Heel, Karen A. Hunt, Dan Mason, Qin Qin Huang, Sarah Finer, null Genes & Health Research Team, Bhavi Trivedi, Christopher J. Griffiths, Hilary C. Martin, John Wright, Richard C. Trembath, Nicole Soranzo, Jing Hua Zhao, Adam S. Butterworth, John Danesh, Emanuele Di Angelantonio, Lude Franke Marike Boezen, Patrick Deelen, Annique Claringbould, Esteban Lopera, Robert Warmerdam, Judith.M. Vonk, Irene van Blokland, Pauline Lanting, Anil P.S. Ori, Brooke Wolford Sebastian Zöllner, Jiongming Wang, Andrew Beck, Gina Peloso, Yuk-Lam Ho, Yan V. Sun, Jennifer E. Huffman, Christopher J. O’Donnell, Kelly Cho, Phil Tsao, J. Michael Gaziano, Michel (M.G.) Nivard, Eco (E.J.C.) de geus, Meike Bartels, Jouke Jan Hottenga, Scott T. Weiss, Elizabeth W. Karlson, Jordan W. Smoller, Robert C. Green, Yen-Chen Anne Feng, Josep Mercader, Shawn N. Murphy, James B. Meigs, Ann E. Woolley, Emma F. Perez, Daniel Rader, Anurag Verma, Marylyn D. Ritchie, Binglan Li, Shefali S. Verma, Anastasia Lucas, Yuki Bradford, Hugo Zeberg, Robert Frithiof, Michael Hultström, Miklos Lipcsey, Lindo Nkambul, Nicolas Tardif, Olav Rooyackers, Jonathan Grip, Tomislav Maricic, Konrad J. Karczewski, Elizabeth G. Atkinson, Kristin Tsuo, Nikolas Baya, Patrick Turley, Rahul Gupta, Shawneequa Callier, Raymond K. Walters, Duncan S. Palmer, Gopal Sarma, Nathan Cheng, Wenhan Lu, Sam Bryant, Claire Churchhouse, Caroline Cusick, Jacqueline I. Goldstein, Daniel King, Cotton Seed, Hilary Finucane, Alicia R. Martin, F. Kyle Satterstrom, Daniel J. Wilson, Jacob Armstrong, Justine K. Rudkin, Gavin Band, Sarah G. Earle, Shang-Kuan Lin, Nicolas Arning, Derrick W. Crook, David H. Wyllie, Anne Marie O’Connell, Chris C.A. Spencer, Nils Koelling, Mark J. Caulfield, Richard H. Scott, Tom Fowler, Loukas Moutsianas, Athanasios Kousathanas, Dorota Pasko, Susan Walker, Augusto Rendon, Alex Stuckey, Christopher A. Odhams, Daniel Rhodes, Georgia Chan, Prabhu Arumugam, Catherine A. Ball, Eurie L. Hong, Kristin Rand, Ahna Girshick, Harendra Guturu, Asher Haug Baltzell, Genevieve Roberts, Danny Park, Marie Coignet, Shannon McCurdy, Spencer Knight, Raghavendran Partha, Brooke Rhead, Miao Zhang, Nathan Berkowitz, Michael Gaddis, Keith Noto, Luong Ruiz, Milos Pavlovic, Laura G. Sloofman, Alexander W. Charney, Noam D. Beckmann, Eric E. Schadt, Daniel M. Jordan, Ryan C. Thompson, Kyle Gettler, Noura S. Abul-Husn, Steven Ascolillo, Joseph D. Buxbaum, Kumardeep Chaudhary, Judy H. Cho, Yuval Itan, Eimear E. Kenny, Gillian M. Belbin, Stuart C. Sealfon, Robert P. Sebra, Irene Salib, Brett L. Collins, Tess Levy, Bari Britvan, Katherine Keller, Lara Tang, Michael Peruggia, Liam L. Hiester, Kristi Niblo, Alexandra Aksentijevich, Alexander Labkowsky, Avromie Karp, Menachem Zlatopolsky, Michael Preuss, Ruth J.F. Loos, Girish N. Nadkarni, Ron Do, Clive Hoggart, Sam Choi, Slayton J. Underwood, Paul O’Reilly, Laura M. Huckins, Marissa Zyndorf, AII - Infectious diseases, Amsterdam Neuroscience - Neuroinfection & -inflammation, and Neurology
Subjects: Medical Physiology, Gene Expression, Genome-wide association study, Genome, Severity of Illness Index, colocalization, Gene expression, Databases, Genetic, Ethnicity, 2.1 Biological and endogenous factors, GWAS, Aetiology, Biology (General), Lung, Genetics, Chromosome Mapping, Single Nucleotide, Organ Specificity, Biotechnology, Cell type, QH301-705.5, Quantitative Trait Loci, Single-nucleotide polymorphism, Biology, eQTL, Polymorphism, Single Nucleotide, Article, General Biochemistry, Genetics and Molecular Biology, Databases, Genetic, SNP, Humans, Genetic Predisposition to Disease, COVID-19 Host Genetics Initiative, Polymorphism, Gene, COVID-19, SARS-CoV-2, Gene Expression Profiling, Prevention, Human Genome, Computational Biology, Genetic Variation, Good Health and Well Being, Expression quantitative trait loci, Biochemistry and Cell Biology, Transcriptome, Genome-Wide Association Study
Abstract: Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types., Graphical abstract, D’Antonio et al. characterize associations between GWAS signals for COVID-19 disease and eQTLs in 69 human tissues to identify causal variants and their underlying molecular mechanisms. They show that diverse symptoms and disease severity of COVID-19 are associated with variants affecting gene expression in a wide variety of tissues.
Published: 2022
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37. Fatal breakthrough infection after anti-BCMA CAR-T therapy highlights suboptimal immune response to SARS-CoV-2 vaccination in myeloma patients

Author: Adeeb Rahman, Florian Krammer, Brian D. Brown, Bhaskar Upadhyaya, Ana S. Gonzalez-Reiche, Komal Srivastava, Ania Wajnberg, Kevin Tuballes, Sarita Agte, Tarek H. Mouhieddine, Konstantinos Mouskas, Viviana Simon, Sundar Jagannath, Miriam Merad, Alexander W Charney, Emilia Mia Sordillo, Adolfo Aleman, Bo Wang, Ajai Chari, Nicole W Simons, Seunghee Kim-Schulze, Daniel Geanon, Oliver Van Oekelen, Harm van Bakel, Zenab Khan, Samir Parekh, Charles R Gleason, Katherine Beach, Carlos Cordon-Cardo, Larysa Sanchez, Sacha Gnjatic, Katerina Kappes, and Nina Bhardwaj
Subjects: Cellular immunity, biology, business.industry, T cell, Breakthrough infection, medicine.disease, Chimeric antigen receptor, Vaccination, Immune system, medicine.anatomical_structure, Immunology, biology.protein, medicine, Antibody, business, Multiple myeloma
Abstract: SUMMARYSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines are highly effective in healthy individuals. Patients with multiple myeloma (MM) are immunocompromised due to defects in humoral and cellular immunity as well as immunosuppressive therapies. The efficacy after two doses of SARS-CoV-2 mRNA vaccination in MM patients is currently unknown. Here, we report the case of a MM patient who developed a fatal SARS-CoV-2 infection after full vaccination while in remission after B cell maturation antigen (BCMA)-targeted chimeric antigen receptor (CAR)-T treatment. We show that the patient failed to generate antibodies or SARS-CoV-2-specific B and T cell responses, highlighting the continued risk of severe coronavirus disease 2019 (COVID-19) in vaccine non-responders. In the largest cohort of vaccinated MM patients to date, we demonstrate that 15.9% lack SARS-CoV-2 spike antibody response more than 10 days after the second mRNA vaccine dose. The patients actively receiving MM treatment, especially on regimens containing anti-CD38 and anti-BCMA, have lower antibody responses compared to healthy controls. Thus, it is of critical importance to monitor this patient population for serological responses. Non-responders may benefit from ongoing public health measures and from urgent study of prophylactic treatments to prevent SARS-CoV-2 infection.
Published: 2021
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38. Using deep learning algorithms to simultaneously identify right and left ventricular dysfunction from the electrocardiogram

Author: Bette Kim, Kipp W. Johnson, Alexander W. Charney, Atul Kukar, Tatyana Danilov, Sulaiman Somani, Adam Russak, Isotta Landi, Robert S. Freeman, Akhil Vaid, Mesude Bicak, Stamatios Lerakis, Girish N. Nadkarni, Edgar Argulian, Jagat Narula, Benjamin S. Glicksberg, Matthew A. Levin, Shan Zhao, and Marcus A. Badgeley
Subjects: Lv function, medicine.medical_specialty, Ejection fraction, Ventricular function, business.industry, Deep learning, Composite outcomes, External validation, medicine.disease, Internal medicine, Heart failure, Area under curve, medicine, Cardiology, cardiovascular diseases, Artificial intelligence, business
Abstract: BackgroundRapid evaluation of left and right ventricular function using deep learning (DL) on electrocardiograms (ECG) can assist diagnostic workflow. However, DL tools to estimate right ventricular (RV) function do not exist, while ones to estimate left ventricular (LV) function are restricted to quantification of very low LV function only.ObjectivesThis study sought to develop deep learning models capable of comprehensively quantifying left and right ventricular dysfunction from ECG data in a large, diverse population.MethodsA multi-center study was conducted with data from five New York City hospitals; four for internal testing and one serving as external validation. We created novel DL models to classify Left Ventricular Ejection Fraction (LVEF) into categories derived from the latest universal definition of heart failure, estimate LVEF through regression, and predict a composite outcome of either RV systolic dysfunction or RV dilation.ResultsWe obtained echocardiogram LVEF estimates for 147,636 patients paired to 715,890 ECGs. We used Natural Language Processing (NLP) to extract RV size and systolic function information from 404,502 echocardiogram reports paired to 761,510 ECGs for 148,227 patients.For LVEF classification in internal testing, Area Under Curve (AUC) at detection of LVEF50% was 0.94 (95% CI:0.94-0.94), 0.82 (0.81-0.83), and 0.89 (0.89-0.89) respectively. For external validation, these results were 0.94 (0.94-0.95), 0.73 (0.72-0.74) and 0.87 (0.87-0.88). For regression, the mean absolute error was 5.84% (5.82-5.85) for internal testing, and 6.14% (6.13-6.16) in external validation. For prediction of the composite RV outcome, AUC was 0.84 (0.84-0.84) in both internal testing and external validation.ConclusionsDL on ECG data can be utilized to create inexpensive screening, diagnostic, and predictive tools for both LV/RV dysfunction. Such tools may bridge the applicability of ECGs and echocardiography, and enable prioritization of patients for further interventions for either sided failure progressing to biventricular disease.
Published: 2021
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39. Using Deep-Learning Algorithms to Simultaneously Identify Right and Left Ventricular Dysfunction From the Electrocardiogram

Author: Benjamin S. Glicksberg, Marcus A. Badgeley, Tatyana Danilov, Robert S. Freeman, Adam Russak, Alexander W. Charney, Stamatios Lerakis, Matthew A. Levin, Kipp W. Johnson, Edgar Argulian, Akhil Vaid, Shan Zhao, Sulaiman Somani, Girish N. Nadkarni, Mesude Bicak, Jagat Narula, Atul Kukar, Isotta Landi, and Bette Kim
Subjects: Left and right, medicine.medical_specialty, Ventricular Dysfunction, Right, Ventricular Function, Left, Electrocardiography, Ventricular Dysfunction, Left, Text mining, Right heart failure, Deep Learning, Predictive Value of Tests, Internal medicine, medicine, Humans, Radiology, Nuclear Medicine and imaging, cardiovascular diseases, Ejection fraction, business.industry, Deep learning, Left heart failure, Stroke Volume, Diverse population, Cardiology, Ventricular Function, Right, Artificial intelligence, Cardiology and Cardiovascular Medicine, business, human activities
Abstract: This study sought to develop DL models capable of comprehensively quantifying left and right ventricular dysfunction from ECG data in a large, diverse population.Rapid evaluation of left and right ventricular function using deep learning (DL) on electrocardiograms (ECGs) can assist diagnostic workflow. However, DL tools to estimate right ventricular (RV) function do not exist, whereas those to estimate left ventricular (LV) function are restricted to quantification of very low LV function only.A multicenter study was conducted with data from 5 New York City hospitals: 4 for internal testing and 1 serving as external validation. We created novel DL models to classify left ventricular ejection fraction (LVEF) into categories derived from the latest universal definition of heart failure, estimate LVEF through regression, and predict a composite outcome of either RV systolic dysfunction or RV dilation.We obtained echocardiogram LVEF estimates for 147,636 patients paired to 715,890 ECGs. We used natural language processing (NLP) to extract RV size and systolic function information from 404,502 echocardiogram reports paired to 761,510 ECGs for 148,227 patients. For LVEF classification in internal testing, area under curve (AUC) at detection of LVEF ≤40%, 40% LVEF ≤50%, and LVEF50% was 0.94 (95% CI: 0.94-0.94), 0.82 (95% CI: 0.81-0.83), and 0.89 (95% CI: 0.89-0.89), respectively. For external validation, these results were 0.94 (95% CI: 0.94-0.95), 0.73 (95% CI: 0.72-0.74), and 0.87 (95% CI: 0.87-0.88). For regression, the mean absolute error was 5.84% (95% CI: 5.82%-5.85%) for internal testing and 6.14% (95% CI: 6.13%-6.16%) in external validation. For prediction of the composite RV outcome, AUC was 0.84 (95% CI: 0.84-0.84) in both internal testing and external validation.DL on ECG data can be used to create inexpensive screening, diagnostic, and predictive tools for both LV and RV dysfunction. Such tools may bridge the applicability of ECGs and echocardiography and enable prioritization of patients for further interventions for either sided failure progressing to biventricular disease.
Published: 2021

40. Polygenic risk scores lack prognostic value for adults with severe mental illness

Author: Liam Cotter, Girish N. Nadkarni, Eric D. Achtyes, Noam D. Beckmann, Douglas S. Lehrer, Deepak Kaji, Ayman H. Fanous, Carlos N. Pato, Michael Preuss, Eric E. Schadt, Gillian M. Belbin, Alexander W. Charney, Isotta Landi, Steve McCarroll, Mark Hyman Rapaport, Tim B. Bigdeli, M. T. Pato, Loos R, Van Vleck T, Peter F. Buckley, Dolores Malaspina, Eimear E. Kenny, and Benjamin S. Glicksberg
Subjects: business.industry, Schizophrenia, medicine, Predictive power, Polygenic risk score, Psychiatric interview, Disease, Mental illness, medicine.disease, business, Precision medicine, Value (mathematics), Clinical psychology
Abstract: Schizophrenia (SCZ) is the archetypal severe mental illness and one of the most deeply characterized human genetic traits. Like most common diseases SCZ is highly polygenic, and as such its genetic liability can be summarized at the individual level by a polygenic risk score (PRS). Polygenic risk scores are a cornerstone of the precision medicine vision, as it is widely anticipated they will come to serve as biomarkers of disease and poor outcomes in real-world clinical practice. However, to date, few studies have assessed their actual prognostic value relative to current standards-of-care. SCZ is an ideal test case towards this end because the predictive power of the SCZ PRS exceeds that of most other common diseases. Here, we analyzed clinical and genetic data from two multi-ethnic cohorts totaling 8,541 adults with SCZ and related psychotic disorders, assessing whether the SCZ PRS improves poor outcome prediction relative to clinical features captured in a standard psychiatric interview. For all outcomes investigated, the SCZ PRS did not improve the performance of predictive models, an observation that was generally robust to divergent case definitions and ancestral backgrounds of study participants. These findings demonstrate the limited potential of even the most powerful contemporary polygenic risk scores as a tool for individualized outcome prediction.
Published: 2021
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41. 50. IDENTIFICATION OF MOLECULAR RELATIONSHIPS BETWEEN LIVING AND POST-MORTEM BRAIN TISSUE

Author: Eli A. Stahl, Brian H. Kopell, Julie Park, Pamela Sklar, Eric E. Schadt, Jaroslav Bendl, Claudia Feng, Alexander W. Charney, Gabriel E. Hoffman, Lora Liharska, Noam D. Beckmann, and Panos Roussos
Subjects: Pharmacology, Psychiatry and Mental health, Pathology, medicine.medical_specialty, Neurology, business.industry, Medicine, Pharmacology (medical), Identification (biology), Neurology (clinical), business, Post mortem brain, Biological Psychiatry
Published: 2021
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42. POLYGENIC RISK OF COMORBID ANXIETY AND DEPRESSION ACROSS HEALTH SYSTEMS

Author: Myrna M. Weissman, Brandon J. Coombes, Nicolas A. Nunez, J. John Mann, Alexander W. Charney, Jyotishman Pathak, Isotta Landi, Mark Olfson, Priya Wickramaratne, Yanshan Wang, Euijung Ryu, Joanna M. Biernacka, Anthony Batzler, Gregory D. Jenkins, and Colin L. Colby
Subjects: Pharmacology, medicine.medical_specialty, Comorbid anxiety, business.industry, Psychiatry and Mental health, Neurology, medicine, Pharmacology (medical), Polygenic risk score, Neurology (clinical), Psychiatry, business, Biological Psychiatry, Depression (differential diagnoses), Healthcare system
Published: 2021
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43. 11. ANALYSIS OF GENOMIC COPY NUMBER VARIATION AND THEIR INTERACTION WITH POLYGENIC RISK SCORES ACROSS PSYCHIATRIC DISORDERS

Author: Alexander W. Charney, Jonathan Sebat, Jeffrey R. MacDonald, Elise Douard, Stanley Letovsky, Stephen W. Scherer, Omar Shanta, Sébastien Jacquemont, Agathe de Pins, Bhooma Thiruvahindrapuram, Marieke Klein, Oanh Hong, and Jake Humphrey
Subjects: Pharmacology, Genetics, Psychiatry and Mental health, Neurology, Pharmacology (medical), Polygenic risk score, Neurology (clinical), Copy-number variation, Biology, Biological Psychiatry
Published: 2021
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44. The Phenome-wide Consequences of Anorexia Nervosa Genes

Author: Cynthia M. Bulik, Preben Bo Mortensen, Laura G. Sloofman, Laura M. Huckins, Alexander W. Charney, Sarah Maguire, Martin A. Kennedy, Mikael Landén, Jennifer Jordan, Liam Cotter, Nicholas G. Martin, Jiayi Xu, Amanda Dobbyn, Alanna C. Cote, and Jessica S. Johnson
Subjects: Anorexia nervosa (differential diagnoses), business.industry, Medicine, Genome-wide association study, Single-nucleotide polymorphism, Disease, Phenome, Bioinformatics, business, Biobank, Imputation (genetics), Genetic association
Abstract: Anorexia nervosa (AN) is a psychiatric disorder with complex etiology, with a significant portion of disease risk imparted by genetics. Traditional GWAS studies produce principal evidence for the association of genetic variants with disease, and provide a jumping-off point for downstream functional analyses. Transcriptomic imputation (TI) allows for the translation of SNPs into regulatory mechanisms, which can then be used to assess the functional outcome of genetically regulated gene expression (GReX) in a more broad setting through the use of phenome-wide association studies (PheWAS) in large and diverse clinical biobank populations with electronic health record (EHR) phenotypes. Here, we applied TI using S-PrediXcan to translate the most recent PGC-ED AN GWAS findings into AN-GReX. For significant genes, we imputed AN-GReX in the Mount Sinai BioMe™ Biobank and performed PheWAS on over 2000 clinical outcomes to test the clinical consequences of aberrant expression of these genes. We performed a secondary analysis to assess the impact of BMI on AN-GReX clinical associations.Our S-PrediXcan analysis identified 47 genes associated with AN, including what is, to our knowledge, the first genetic association of AN with the Major Histocompatibility Complex (MHC). AN-GReX was associated with autoimmune, anthropometric, metabolic, psychiatric and gastrointestinal diagnoses in our biobank cohort, as well as measures of anthropometry, substance use, and pain score. Our analyses reveal that AN-GReX associations with measures of weight and substance use are modified by BMI, and indicate potential avenues of functional mechanism to investigate further.
Published: 2021
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45. A Molecular network approach reveals shared cellular and molecular signatures between chronic fatigue syndrome and other fatiguing illnesses

Author: Miriam Merad, Alexander W. Charney, Scott R. Tyler, Shreya Chandrasekar, Eric E. Schadt, Bojan Losic, Wenhui Wang, Irene Font Peradejordi, Carmen Argmann, Christian D. Becker, Roman Kosoy, Gabriel E. Hoffman, Noam D. Beckmann, Edgar Gonzalez-Kozlova, Zeynep H. Gümüş, Phillip H. Comella, Jingjing Qi, Jun Zhu, Andrew Kasarskis, Manishkumar Patel, Mayte Suárez-Fariñas, and Seunghee Kim-Schulze
Subjects: musculoskeletal diseases, Coronavirus disease 2019 (COVID-19), business.industry, Cell type specific, virus diseases, Master regulator, Context (language use), Disease, medicine.disease, Article, nervous system diseases, Molecular network, Immunology, Etiology, Chronic fatigue syndrome, medicine, business, human activities
Abstract: IntroThe molecular mechanisms of chronic fatigue syndrome (CFS, or Myalgic encephalomyelitis), a disease defined by extreme, long-term fatigue, remain largely uncharacterized, and presently no molecular diagnostic test and no specific treatments exist to diagnose and treat CFS patients. While CFS has historically had an estimated prevalence of 0.1-0.5% [1], concerns of a “long hauler” version of Coronavirus disease 2019 (COVID-19) that symptomatically overlaps CFS to a significant degree(Supplemental Table-1)and appears to occur in 10% of COVID-19 patients[2], has raised concerns of a larger spike in CFS [3]. Here, we established molecular signatures of CFS and a corresponding network-based disease context from RNA-sequencing data generated on whole blood and FACs sorted specific peripheral blood mononuclear cells (PBMCs) isolated from CFS cases and non-CFS controls. The immune cell type specific molecular signatures of CFS we identified, overlapped molecular signatures from other fatiguing illnesses, demonstrating a common molecular etiology. Further, after constructing a probabilistic causal model of the CFS gene expression data, we identified master regulator genes modulating network states associated with CFS, suggesting potential therapeutic targets for CFS.
Published: 2021
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46. Use of Physiological Data From a Wearable Device to Identify SARS-CoV-2 Infection and Symptoms and Predict COVID-19 Diagnosis: Observational Study

Author: Katie Hyewon Choi, Drew Helmus, Renata Pyzik, Sparshdeep Kaur, Erwin P. Bottinger, Micol Zweig, Benjamin S. Glicksberg, Riccardo Miotto, Ismail Nabeel, Dennis S. Charney, Anthony Biello, Laurie Keefer, Mayte Suárez-Fariñas, David Reich, Eddye Golden, Zahi A. Fayad, Matteo Danieletto, Lewis Tomalin, Girish N. Nadkarni, Judith A. Aberg, Matthew A. Levin, Robert Hirten, and Alexander W. Charney
Subjects: Adult, Male, 0301 basic medicine, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), diagnosis, infectious disease, Health Personnel, physiological, Wearable computer, wearable device, Health Informatics, lcsh:Computer applications to medicine. Medical informatics, wearable, Wearable Electronic Devices, 03 medical and health sciences, COVID-19 Testing, 0302 clinical medicine, Heart Rate, Internal medicine, medicine, Humans, Heart rate variability, observational, 030212 general & internal medicine, Circadian rhythm, app, Original Paper, SARS-CoV-2, business.industry, lcsh:Public aspects of medicine, heart rate variability, COVID-19, lcsh:RA1-1270, prediction, symptom, Circadian Rhythm, Autonomic nervous system, 030104 developmental biology, data, identification, lcsh:R858-859.7, Female, Observational study, Metric (unit), business, Interbeat interval
Abstract: Background Changes in autonomic nervous system function, characterized by heart rate variability (HRV), have been associated with infection and observed prior to its clinical identification. Objective We performed an evaluation of HRV collected by a wearable device to identify and predict COVID-19 and its related symptoms. Methods Health care workers in the Mount Sinai Health System were prospectively followed in an ongoing observational study using the custom Warrior Watch Study app, which was downloaded to their smartphones. Participants wore an Apple Watch for the duration of the study, measuring HRV throughout the follow-up period. Surveys assessing infection and symptom-related questions were obtained daily. Results Using a mixed-effect cosinor model, the mean amplitude of the circadian pattern of the standard deviation of the interbeat interval of normal sinus beats (SDNN), an HRV metric, differed between subjects with and without COVID-19 (P=.006). The mean amplitude of this circadian pattern differed between individuals during the 7 days before and the 7 days after a COVID-19 diagnosis compared to this metric during uninfected time periods (P=.01). Significant changes in the mean and amplitude of the circadian pattern of the SDNN was observed between the first day of reporting a COVID-19–related symptom compared to all other symptom-free days (P=.01). Conclusions Longitudinally collected HRV metrics from a commonly worn commercial wearable device (Apple Watch) can predict the diagnosis of COVID-19 and identify COVID-19–related symptoms. Prior to the diagnosis of COVID-19 by nasal swab polymerase chain reaction testing, significant changes in HRV were observed, demonstrating the predictive ability of this metric to identify COVID-19 infection.
Published: 2021

47. Application of a 27-protein candidate cardiovascular surrogate endpoint to track risk ascendancy and resolution in COVID-19

Author: Yolanda Hagar, Sacha Gnjatic, Jason D Goldman, Lori L. Jennings, Stephen A. Williams, Michael R. Filbin, Rainer Hillenbrand, Konstantinos Mouskas, Michael A Hinterberg, Seunghee Kim-Schulze, Nir Hacohen, Diane Marie Del Valle, Nicole W. Simons, Andrew T. Magis, James R. Heath, Clare Paterson, Miriam Merad, and Alexander W. Charney
Subjects: medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), Surrogate endpoint, business.industry, Convalescence, media_common.quotation_subject, Disease, Disease Presentation, Internal medicine, Cohort, medicine, Risk factor, Adverse effect, business, media_common
Abstract: BackgroundThere is an urgent need for tools allowing the early prognosis and subsequent monitoring of individuals with heterogeneous COVID-19 disease trajectories. Pre-existing cardiovascular (CV) disease is a leading risk factor for COVID-19 susceptibility and poor outcomes, and cardiac involvement is prevalent in COVID-19 patients both during the acute phase as well as in convalescence. The utility of traditional CV risk biomarkers in mild COVID-19 disease or across disease course is poorly understood. We sought to determine if a previously validated 27-protein predictor of CV outcomes served a purpose in COVID-19.MethodsThe 27-protein test of residual CV (RCV) risk was applied without modification to n=860 plasma samples from hospitalized and non-hospitalized SARS-CoV-2 infected individuals at disease presentation from three independent cohorts to predict COVID-19 severity and mortality. The same test was applied to an additional n=991 longitudinal samples to assess sensitivity to change in CV risk throughout the course of infection into convalescence.ResultsIn each independent cohort, RCV predictions were significantly related to maximal subsequent COVID-19 severity and to mortality. At the baseline blood draw, the mean protein-predicted likelihood of an event in subjects who died during the study period ranged from 88-99% while it ranged from 8-36% in subjects who were not admitted to hospital. Additionally, the test outperformed existing risk predictors based on commonly used laboratory chemistry values or presence of comorbidities. Application of the RCV test to sequential samples showed dramatic increases in risk during the first few days of infection followed by risk reduction in the survivors; a period of catastrophically high cardiovascular risk (above 50%) typically lasted 8-12 days and had not resolved to normal levels in most people within that timescale.ConclusionsThe finding that a 27-protein candidate CV surrogate endpoint developed in multi-morbid patients prior to the pandemic is both prognostic and acutely sensitive to the adverse effects of COVID-19 suggests that this disease activates the same biologic risk-related mechanisms. The test may be useful for monitoring recovery and drug response.
Published: 2021
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48. An integrative multiomic network model links lipid metabolism to glucose regulation in coronary artery disease

Author: Zhidong Tu, Ariella Cohain, Jason C. Kovacic, Arno Ruusalepp, Aldons J. Lusis, Jun Zhu, Katyayani Sukhavasi, Raili Ermel, Daniel M. Jordan, Li-Ming Gan, Jialiang Yang, Ke Hao, Carmen Argmann, Ron Do, Eimear E. Kenny, Sander M. Houten, Chiara Giannarelli, William T. Barrington, Johan L.M. Björkegren, Noam D. Beckmann, Eric E. Schadt, Simon Koplev, Gillian M. Belbin, Oscar Franzen, Carl Whatling, and Alexander W. Charney
Subjects: Blood Glucose, 0301 basic medicine, Metabolic disorders, General Physics and Astronomy, Coronary Artery Disease, Type 2 diabetes, 030204 cardiovascular system & hematology, Coronary artery disease, chemistry.chemical_compound, 0302 clinical medicine, Gene Regulatory Networks, Multidisciplinary, biology, Cardiovascular diseases, Cholesterol, Female, lipids (amino acids, peptides, and proteins), medicine.medical_specialty, Science, Hypercholesterolemia, Models, Biological, Polymorphism, Single Nucleotide, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, Metabolomics, Diabetes mellitus, Internal medicine, medicine, Animals, Humans, Genetic Predisposition to Disease, business.industry, Lipid metabolism, General Chemistry, Lipid Metabolism, medicine.disease, Regulatory networks, Computational biology and bioinformatics, Mice, Inbred C57BL, Glucose, 030104 developmental biology, Endocrinology, Diabetes Mellitus, Type 2, Gene Expression Regulation, chemistry, biology.protein, Blood sugar regulation, business, Genome-Wide Association Study, Lanosterol synthase
Abstract: Elevated plasma cholesterol and type 2 diabetes (T2D) are associated with coronary artery disease (CAD). Individuals treated with cholesterol-lowering statins have increased T2D risk, while individuals with hypercholesterolemia have reduced T2D risk. We explore the relationship between lipid and glucose control by constructing network models from the STARNET study with sequencing data from seven cardiometabolic tissues obtained from CAD patients during coronary artery by-pass grafting surgery. By integrating gene expression, genotype, metabolomic, and clinical data, we identify a glucose and lipid determining (GLD) regulatory network showing inverse relationships with lipid and glucose traits. Master regulators of the GLD network also impact lipid and glucose levels in inverse directions. Experimental inhibition of one of the GLD network master regulators, lanosterol synthase (LSS), in mice confirms the inverse relationships to glucose and lipid levels as predicted by our model and provides mechanistic insights., Some cholesterol-lowering drugs can increase the risk of type 2 diabetes, but the mechanism behind this is not fully understood. Here the authors show that there is a single genetic regulatory module that influences both cholesterol levels and glucose levels, providing a link between cholesterol levels and diabetes.
Published: 2021
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49. Temporal Trends in COVID-19 associated AKI from March to December 2020 in New York City

Author: Ishan Paranjpe, Sergio Dellepiane, Girish N. Nadkarni, Erwin P. Bottinger, Zahi A. Fayad, Suraj K. Jaladanki, John Cijiang He, Lili Chan, Stevn Coca, Alexander W. Charney, Akhil Vaid, and Benjamin S. Glicksberg
Subjects: medicine.medical_specialty, 2019-20 coronavirus outbreak, Coronavirus disease 2019 (COVID-19), business.industry, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), medicine.medical_treatment, Incidence (epidemiology), Acute kidney injury, urologic and male genital diseases, medicine.disease, Pandemic, Emergency medicine, medicine, Retrospective analysis, Renal replacement therapy, business
Abstract: Acute Kidney Injury (AKI) is among the most common complications of Coronavirus Disease 2019 (COVID-19). Throughout 2020 pandemic, the clinical approach to COVID-19 has progressively improved, but it is unknown how these changes have affected AKI incidence and severity. In this retrospective analysis, we report the trend over time of COVID-19 associated AKI and need of renal replacement therapy in a large health system in New York City, the first COVID-19 epicenter in United States.
Published: 2021
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50. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

Author: James McKay, Frank Bellivier, Mark A. Frye, Bertram Müller-Myhsok, Fermín Mayoral, I. Nicol Ferrier, Marion Leboyer, Fabian Streit, Dan J. Stein, James L. Kennedy, Christine Søholm Hansen, Scott D. Gordon, Beata Świątkowska, Valentina Escott-Price, Michael Bauer, Lina Martinsson, Donald J. MacIntyre, Oleksandr Frei, Daniel J. Smith, Sara A. Paciga, Takeo Saito, Jennifer L. Moran, Verneri Antilla, C Pantelis, Tomas Olsson, Swapnil Awasthi, Lena Backlund, Eirini Maratou, Martin Schalling, John B. Vincent, Niamh Mullins, Sarah E. Bergen, Niamh L. O'Brien, Marco P. Boks, Carsten Bøcker Pedersen, Mikael Landén, Franziska Degenhardt, Hang Zhou, Margarita Rivera, Andrew M. McIntosh, Manuel Mattheisen, Shawn Levy, Roy H. Perlis, John P. Rice, Sigurdur H. Magnusson, Amanda Dobbyn, Michael Conlon O'Donovan, Julien Bryois, Wolfgang Maier, John-Anker Zwart, J. Raymond DePaulo, Martin Alda, Laura G. Sloofman, Friederike Sophie David, James A. Knowles, Aiden Corvin, Thomas G. Schulze, Markus M. Nöthen, Nolan Kamitaki, Nina Dalkner, Brandon J. Coombes, Gustavo Turecki, Allan H. Young, Caroline M. Nievergelt, Patricia T. Michie, Ingrid Agartz, Towfique Raj, Diego Albani, Maria Grigoroiu-Serbanescu, Bernhard T. Baune, Kyooseob Ha, Vincent Millischer, Engilbert Sigurdsson, Eva C. Beins, Nicholas G. Martin, Gulja Babadjanova, Josef Frank, Eva Z. Reininghaus, Patrick F. Sullivan, Ian R. Gizer, Guy A. Rouleau, Carmel M. Loughland, Christine Lochner, Thorsten M. Kranz, Amy Perry, Arne E. Vaaler, Mariam M. Al Eissa, Simon Xi, Claire O'Donovan, Josep Antoni Ramos-Quiroga, Ketil J. Oedegaard, Helmut Vedder, Carol A. Mathews, Panagiotis Ferentinos, Tim B. Bigdeli, Derek W. Morris, Per Hoffmann, Mark Hyman Rapaport, Peter P. Zandi, Michael John Owen, Douglas M. Ruderfer, Anders D. Børglum, Catharina Lavebratt, Thorgeir E. Thorgeirsson, Paul A. Tooney, Michiaki Kubo, Steven A. Kushner, Jan Hillert, Loes M. Olde Loohuis, Anastasia Antoniou, Murielle Brum, Chikashi Terao, Nathaniel W. McGregor, Fabio Rivas, James B. Potash, Kevin S. O’Connell, Susanne Lucae, Brian M. Schilder, Katrin Gade, Stephan Ripke, Kristina Adorjan, Kari Stefansson, Tiffany A. Greenwood, Panos Roussos, Sarah Kittel-Schneider, Steven A. McCarroll, Sergi Papiol, Heon Jeong Lee, Assen Jablensky, Liliya Abramova, Dennis Hellgren, Jonas Bybjerg-Grauholm, Martin Lundberg, Hong-Hee Won, William Byerley, Lars Alfredsson, Joel Gelernter, Andrew McQuillin, Claire Slaney, Marta Ribasés, Stephanie H. Witt, Yoichiro Kamatani, Kyung Sue Hong, Marie Bækvad-Hansen, María Soler Artigas, Julie M. Cunningham, Fanny Senner, Stacy Steinberg, Paul D. Shilling, Nakao Iwata, Eystein Stordal, Armin Birner, Sarah E. Medland, Miquel Casas, Ben Michael Brumpton, Erlend Bøen, Bryan J. Mowry, Jolanta Lissowska, Francis J. McMahon, Howard J. Edenberg, Grant W. Montgomery, John I. Nurnberger, Stéphane Jamain, Claudio Toma, Ney Alliey-Rodriguez, Ole Mors, Micha Gawlik, David Curtis, Catrin Lewis, Evangelia-Eirini Tsermpini, Georgia Panagiotaropoulou, Marcella Rietschel, Jessica Yang, Ian Jones, Eduard Vieta, Ole A. Andreassen, Richard M. Myers, Dimitris Dikeos, Melissa J. Green, Janet L. Sobell, Maria Koromina, Piotr M. Czerski, Lilijana Oruc, Sven Cichon, Udo Dannlowski, Bruno Etain, Monika Budde, Alessia Fiorentino, Naomi R. Wray, Qingqin S. Li, Murray J. Cairns, Jonathan R. I. Coleman, Jose Guzman-Parra, Andreas J. Forstner, Hannah Young, Alfredo B. Cuellar-Barboza, Julian Roth, Torbjørn Elvsåshagen, Zhen Qiao, Thomas Werge, Athanassios Douzenis, Cristiana Cruceanu, Rolf Adolfsson, Peter Holmans, Vaughan J. Carr, Thomas W. Weickert, Masashi Ikeda, Joanna M. Biernacka, Lea Sirignano, Adam X. Maihofer, Ralph W. Kupka, John Strauss, Anders M. Dale, Elliot S. Gershon, Jakob Grove, Arianna Di Florio, Helena Medeiros, Ingrid Melle, Preben Bo Mortensen, Kristi Krebs, Saskia P. Hagenaars, Liz Forty, Stanley V. Catts, David M. Hougaard, Marianne Giørtz Pedersen, Andreas Reif, Toni-Kim Clarke, Anne T. Spijker, Danielle Posthuma, Manolis Kogevinas, Michael Boehnke, Rosa Bosch, Gerome Breen, Benjamin M. Neale, Jessica S. Johnson, Katherine Gordon-Smith, Cristina Sánchez-Mora, Alexander W. Charney, Henry R. Kranzler, Digby Quested, René S. Kahn, Lili Milani, Merete Nordentoft, Nathalie Brunkhorst-Kanaan, Laura M. Huckins, James T.R. Walters, Sigrid Børte, Antonio F. Pardiñas, Kristian Hveem, Julie Garnham, Jacob Lawrence, Vassily Trubetskoy, Rodney J. Scott, Nicholas Bass, Carlos N. Pato, Andrea Pfennig, Wei Xu, Calwing Liao, Nicholas John Craddock, Thomas Damm Als, Christina M. Hultman, Fernando S. Goes, Adebayo Anjorin, Evgenia Porichi, Frans Henskens, Nelson B. Freimer, Janice M. Fullerton, Cathryn M. Lewis, Srdjan Djurovic, Roel A. Ophoff, Phil Lee, Peter McGuffin, Gunnar Morken, George P. Patrinos, Alessandro Serretti, Cynthia Shannon Weickert, Pablo Cervantes, Bendik S. Winsvold, Tatiana Foroud, Tõnu Esko, Ulrich Schall, Michele T. Pato, Ji Hyun Baek, John R. Kelsoe, Olav B. Smeland, Janos Kalman, Eva C. Schulte, Joanna Hauser, Urs Heilbronner, Magnús Haraldsson, Martin Hautzinger, Lea Zillich, Eline J. Regeer, Douglas Blackwood, Laura J. Scott, Jordan W. Smoller, Michael J. Gandal, Marquis P. Vawter, Philip B. Mitchell, Ole Kristian Drange, Peter R. Schofield, Susanne Bengesser, Stefan Herms, George Kirov, Markus Leber, Louise Frisén, Thomas W. Mühleisen, Susan L. McElroy, Irwin D. Waldman, Wade H. Berrettini, Sally I. Sharp, Minsoo Kim, Lisa Jones, Eli A. Stahl, Hreinn Stefansson, Esben Agerbo, Dolores Malaspina, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, Psychiatry, APH - Mental Health, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Human genetics, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Reproduction & Development (AR&D), APH - Digital Health, Mullins N., Forstner A.J., O'Connell K.S., Coombes B., Coleman J.R.I., Qiao Z., Als T.D., Bigdeli T.B., Borte S., Bryois J., Charney A.W., Drange O.K., Gandal M.J., Hagenaars S.P., Ikeda M., Kamitaki N., Kim M., Krebs K., Panagiotaropoulou G., Schilder B.M., Sloofman L.G., Steinberg S., Trubetskoy V., Winsvold B.S., Won H.-H., Abramova L., Adorjan K., Agerbo E., Al Eissa M., Albani D., Alliey-Rodriguez N., Anjorin A., Antilla V., Antoniou A., Awasthi S., Baek J.H., Baekvad-Hansen M., Bass N., Bauer M., Beins E.C., Bergen S.E., Birner A., Bocker Pedersen C., Boen E., Boks M.P., Bosch R., Brum M., Brumpton B.M., Brunkhorst-Kanaan N., Budde M., Bybjerg-Grauholm J., Byerley W., Cairns M., Casas M., Cervantes P., Clarke T.-K., Cruceanu C., Cuellar-Barboza A., Cunningham J., Curtis D., Czerski P.M., Dale A.M., Dalkner N., David F.S., Degenhardt F., Djurovic S., Dobbyn A.L., Douzenis A., Elvsashagen T., Escott-Price V., Ferrier I.N., Fiorentino A., Foroud T.M., Forty L., Frank J., Frei O., Freimer N.B., Frisen L., Gade K., Garnham J., Gelernter J., Giortz Pedersen M., Gizer I.R., Gordon S.D., Gordon-Smith K., Greenwood T.A., Grove J., Guzman-Parra J., Ha K., Haraldsson M., Hautzinger M., Heilbronner U., Hellgren D., Herms S., Hoffmann P., Holmans P.A., Huckins L., Jamain S., Johnson J.S., Kalman J.L., Kamatani Y., Kennedy J.L., Kittel-Schneider S., Knowles J.A., Kogevinas M., Koromina M., Kranz T.M., Kranzler H.R., Kubo M., Kupka R., Kushner S.A., Lavebratt C., Lawrence J., Leber M., Lee H.-J., Lee P.H., Levy S.E., Lewis C., Liao C., Lucae S., Lundberg M., MacIntyre D.J., Magnusson S.H., Maier W., Maihofer A., Malaspina D., Maratou E., Martinsson L., Mattheisen M., McCarroll S.A., McGregor N.W., McGuffin P., McKay J.D., Medeiros H., Medland S.E., Millischer V., Montgomery G.W., Moran J.L., Morris D.W., Muhleisen T.W., O'Brien N., O'Donovan C., Olde Loohuis L.M., Oruc L., Papiol S., Pardinas A.F., Perry A., Pfennig A., Porichi E., Potash J.B., Quested D., Raj T., Rapaport M.H., DePaulo J.R., Regeer E.J., Rice J.P., Rivas F., Rivera M., Roth J., Roussos P., Ruderfer D.M., Sanchez-Mora C., Schulte E.C., Senner F., Sharp S., Shilling P.D., Sigurdsson E., Sirignano L., Slaney C., Smeland O.B., Smith D.J., Sobell J.L., Soholm Hansen C., Soler Artigas M., Spijker A.T., Stein D.J., Strauss J.S., Swiatkowska B., Terao C., Thorgeirsson T.E., Toma C., Tooney P., Tsermpini E.-E., Vawter M.P., Vedder H., Walters J.T.R., Witt S.H., Xi S., Xu W., Yang J.M.K., Young A.H., Young H., Zandi P.P., Zhou H., Zillich L., Adolfsson R., Agartz I., Alda M., Alfredsson L., Babadjanova G., Backlund L., Baune B.T., Bellivier F., Bengesser S., Berrettini W.H., Blackwood D.H.R., Boehnke M., Borglum A.D., Breen G., Carr V.J., Catts S., Corvin A., Craddock N., Dannlowski U., Dikeos D., Esko T., Etain B., Ferentinos P., Frye M., Fullerton J.M., Gawlik M., Gershon E.S., Goes F.S., Green M.J., Grigoroiu-Serbanescu M., Hauser J., Henskens F., Hillert J., Hong K.S., Hougaard D.M., Hultman C.M., Hveem K., Iwata N., Jablensky A.V., Jones I., Jones L.A., Kahn R.S., Kelsoe J.R., Kirov G., Landen M., Leboyer M., Lewis C.M., Li Q.S., Lissowska J., Lochner C., Loughland C., Martin N.G., Mathews C.A., Mayoral F., McElroy S.L., McIntosh A.M., McMahon F.J., Melle I., Michie P., Milani L., Mitchell P.B., Morken G., Mors O., Mortensen P.B., Mowry B., Muller-Myhsok B., Myers R.M., Neale B.M., Nievergelt C.M., Nordentoft M., Nothen M.M., O'Donovan M.C., Oedegaard K.J., Olsson T., Owen M.J., Paciga S.A., Pantelis C., Pato C., Pato M.T., Patrinos G.P., Perlis R.H., Posthuma D., Ramos-Quiroga J.A., Reif A., Reininghaus E.Z., Ribases M., Rietschel M., Ripke S., Rouleau G.A., Saito T., Schall U., Schalling M., Schofield P.R., Schulze T.G., Scott L.J., Scott R.J., Serretti A., Shannon Weickert C., Smoller J.W., Stefansson H., Stefansson K., Stordal E., Streit F., Sullivan P.F., Turecki G., Vaaler A.E., Vieta E., Vincent J.B., Waldman I.D., Weickert T.W., Werge T., Wray N.R., Zwart J.-A., Biernacka J.M., Nurnberger J.I., Cichon S., Edenberg H.J., Stahl E.A., McQuillin A., Di Florio A., Ophoff R.A., Andreassen O.A., IMRB - 'Neuropsychiatrie translationnelle' [Créteil] (U955 Inserm - UPEC), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Centre International de Recherche contre le Cancer - International Agency for Research on Cancer (CIRC - IARC), Organisation Mondiale de la Santé / World Health Organization Office (OMS / WHO), Optimisation thérapeutique en Neuropsychopharmacologie (OPTeN (UMR_S_1144 / U1144)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Groupe Hospitalier Saint Louis - Lariboisière - Fernand Widal [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), and Etain, Bruno
Subjects: Multifactorial Inheritance, Bipolar Disorder, [SDV.MHEP.PSM] Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, Medizin, Genome-wide association study, Major Histocompatibility Complex/genetics, Major Histocompatibility Complex, 0302 clinical medicine, Risk Factors, MESH: Risk Factors, MESH: Bipolar Disorder, Chromosomes, Human, Spectrum disorder, Genetics, 0303 health sciences, Bipolar Disorder/genetics, MESH: Genetic Predisposition to Disease, MESH: Case-Control Studies, Phenotype, Schizophrenia, Synaptic signaling, Case-Control Studie, Human, Quantitative Trait Loci, Biology, MESH: Phenotype, MESH: Chromosomes, Human, Article, 03 medical and health sciences, MESH: Major Histocompatibility Complex, SDG 3 - Good Health and Well-being, ddc:570, medicine, Humans, Genetic Predisposition to Disease, Bipolar disorder, Multifactorial Inheritance/genetics, MESH: Genome, Human, 030304 developmental biology, MESH: Humans, Genome, Human, Risk Factor, Chromosomes, Human/genetics, Mental illness, medicine.disease, MESH: Quantitative Trait Loci, Human genetics, Psychologie, Case-Control Studies, [SDV.MHEP.PSM]Life Sciences [q-bio]/Human health and pathology/Psychiatrics and mental health, MESH: Genome-Wide Association Study, Expression quantitative trait loci, MESH: Multifactorial Inheritance, Quantitative Trait Loci/genetics, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract: International audience; Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.
Published: 2021
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