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1. Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis.

Author

Kennedy, Eamonn, Liebel, Spencer, Lindsey, Hannah, Vadlamani, Shashank, Lei, Pui-Wa, Adamson, Maheen, Alda, Martin, Alonso-Lana, Silvia, Anderson, Tim, Arango, Celso, Asarnow, Robert, Avram, Mihai, Ayesa-Arriola, Rosa, Babikian, Talin, Banaj, Nerisa, Bird, Laura, Borgwardt, Stefan, Brodtmann, Amy, Brosch, Katharina, Caeyenberghs, Karen, Calhoun, Vince, Chiaravalloti, Nancy, Cifu, David, Crespo-Facorro, Benedicto, Dalrymple-Alford, John, Dams-OConnor, Kristen, Dannlowski, Udo, Darby, David, Davenport, Nicholas, DeLuca, John, Diaz-Caneja, Covadonga, Disner, Seth, Dobryakova, Ekaterina, Ehrlich, Stefan, Esopenko, Carrie, Ferrarelli, Fabio, Frank, Lea, Franz, Carol, Fuentes-Claramonte, Paola, Genova, Helen, Giza, Christopher, Goltermann, Janik, Grotegerd, Dominik, Gruber, Marius, Gutierrez-Zotes, Alfonso, Ha, Minji, Haavik, Jan, Hinkin, Charles, Hoskinson, Kristen, Hubl, Daniela, Irimia, Andrei, Jansen, Andreas, Kaess, Michael, Kang, Xiaojian, Kenney, Kimbra, Keřková, Barbora, Khlif, Mohamed, Kim, Minah, Kindler, Jochen, Kircher, Tilo, Knížková, Karolina, Kolskår, Knut, Krch, Denise, Kremen, William, Kuhn, Taylor, Kumari, Veena, Kwon, Junsoo, Langella, Roberto, Laskowitz, Sarah, Lee, Jungha, Lengenfelder, Jean, Liou-Johnson, Victoria, Lippa, Sara, Løvstad, Marianne, Lundervold, Astri, Marotta, Cassandra, Marquardt, Craig, Mattos, Paulo, Mayeli, Ahmad, McDonald, Carrie, Meinert, Susanne, Melzer, Tracy, Merchán-Naranjo, Jessica, Michel, Chantal, Morey, Rajendra, Mwangi, Benson, Myall, Daniel, Nenadić, Igor, Newsome, Mary, Nunes, Abraham, OBrien, Terence, Oertel, Viola, Ollinger, John, Olsen, Alexander, Ortiz García de la Foz, Victor, Ozmen, Mustafa, Pardoe, Heath, Parent, Marise, Piras, Fabrizio, and Piras, Federica

Subjects
Parkinson’s disease, attention-deficit/hyperactivity disorder, bipolar disorder, dementia, depression, memory, schizophrenia, stroke, traumatic brain injury, verbal learning
Abstract

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinsons disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p < 0.001), while neither depression nor ADHD showed consistent associations with VLM scores (p > 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders.

Published
2024

2. Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk.

Author

Zhu, Yinghan, Maikusa, Norihide, Radua, Joaquim, Sämann, Philipp, Fusar-Poli, Paolo, Agartz, Ingrid, Andreassen, Ole, Bachman, Peter, Baeza, Inmaculada, Chen, Xiaogang, Choi, Sunah, Corcoran, Cheryl, Ebdrup, Bjørn, Fortea, Adriana, Garani, Ranjini, Glenthøj, Birte, Glenthøj, Louise, Haas, Shalaila, Hamilton, Holly, Hayes, Rebecca, He, Ying, Heekeren, Karsten, Kasai, Kiyoto, Katagiri, Naoyuki, Kim, Minah, Kristensen, Tina, Kwon, Jun, Lawrie, Stephen, Lebedeva, Irina, Lee, Jimmy, Loewy, Rachel, Mathalon, Daniel, McGuire, Philip, Mizrahi, Romina, Mizuno, Masafumi, Møller, Paul, Nemoto, Takahiro, Nordholm, Dorte, Omelchenko, Maria, Raghava, Jayachandra, Røssberg, Jan, Rössler, Wulf, Salisbury, Dean, Sasabayashi, Daiki, Smigielski, Lukasz, Sugranyes, Gisela, Takahashi, Tsutomu, Tamnes, Christian, Tang, Jinsong, Theodoridou, Anastasia, Tomyshev, Alexander, Uhlhaas, Peter, Værnes, Tor, van Amelsvoort, Therese, Waltz, James, Westlye, Lars, Zhou, Juan, Thompson, Paul, Hernaus, Dennis, Jalbrzikowski, Maria, and Koike, Shinsuke

Subjects
Humans, Psychotic Disorders, Magnetic Resonance Imaging, Male, Female, Brain, Neuroimaging, Adult, Young Adult, Machine Learning, Adolescent, Prodromal Symptoms
Abstract

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.

Published
2024

3. White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group

Author

Kim, Bo-Gyeom, Kim, Gakyung, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie, Anticevic, Alan, Arnold, Paul D., Balachander, Srinivas, Banaj, Nerisa, Bargalló, Nuria, Batistuzzo, Marcelo C., Benedetti, Francesco, Bertolín, Sara, Beucke, Jan Carl, Bollettini, Irene, Brem, Silvia, Brennan, Brian P., Buitelaar, Jan K., Calvo, Rosa, Castelo-Branco, Miguel, Cheng, Yuqi, Chhatkuli, Ritu Bhusal, Ciullo, Valentina, Coelho, Ana, Couto, Beatriz, Dallaspezia, Sara, Ely, Benjamin A., Ferreira, Sónia, Fontaine, Martine, Fouche, Jean-Paul, Grazioplene, Rachael, Gruner, Patricia, Hagen, Kristen, Hansen, Bjarne, Hanna, Gregory L., Hirano, Yoshiyuki, Höxter, Marcelo Q., Hough, Morgan, Hu, Hao, Huyser, Chaim, Ikuta, Toshikazu, Jahanshad, Neda, James, Anthony, Jaspers-Fayer, Fern, Kasprzak, Selina, Kathmann, Norbert, Kaufmann, Christian, Kim, Minah, Koch, Kathrin, Kvale, Gerd, Kwon, Jun Soo, Lazaro, Luisa, Lee, Junhee, Lochner, Christine, Lu, Jin, Manrique, Daniela Rodriguez, Martínez-Zalacaín, Ignacio, Masuda, Yoshitada, Matsumoto, Koji, Maziero, Maria Paula, Menchón, Jose M., Minuzzi, Luciano, Moreira, Pedro Silva, Morgado, Pedro, Narayanaswamy, Janardhanan C., Narumoto, Jin, Ortiz, Ana E., Ota, Junko, Pariente, Jose C., Perriello, Chris, Picó-Pérez, Maria, Pittenger, Christopher, Poletti, Sara, Real, Eva, Reddy, Y. C. Janardhan, van Rooij, Daan, Sakai, Yuki, Sato, João Ricardo, Segalas, Cinto, Shavitt, Roseli G., Shen, Zonglin, Shimizu, Eiji, Shivakumar, Venkataram, Soreni, Noam, Soriano-Mas, Carles, Sousa, Nuno, Sousa, Mafalda Machado, Spalletta, Gianfranco, Stern, Emily R., Stewart, S. Evelyn, Szeszko, Philip R., Thomas, Rajat, Thomopoulos, Sophia I., Vecchio, Daniela, Venkatasubramanian, Ganesan, Vriend, Chris, Walitza, Susanne, Wang, Zhen, Watanabe, Anri, Wolters, Lidewij, Xu, Jian, Yamada, Kei, Yun, Je-Yeon, Zarei, Mojtaba, Zhao, Qing, Zhu, Xi, Thompson, Paul M., Bruin, Willem B., van Wingen, Guido A., Piras, Federica, Piras, Fabrizio, Stein, Dan J., van den Heuvel, Odile A., Simpson, Helen Blair, Marsh, Rachel, and Cha, Jiook

Published
2024
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4. The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium.

Author

Bruin, Willem, Abe, Yoshinari, Alonso, Pino, Anticevic, Alan, Backhausen, Lea, Balachander, Srinivas, Bargallo, Nuria, Batistuzzo, Marcelo, Benedetti, Francesco, Bertolin Triquell, Sara, Brem, Silvia, Calesella, Federico, Couto, Beatriz, Denys, Damiaan, Echevarria, Marco, Eng, Goi, Ferreira, Sónia, Feusner, Jamie, Grazioplene, Rachael, Gruner, Patricia, Guo, Joyce, Hagen, Kristen, Hansen, Bjarne, Hirano, Yoshiyuki, Hoexter, Marcelo, Jahanshad, Neda, Jaspers-Fayer, Fern, Kasprzak, Selina, Kim, Minah, Koch, Kathrin, Bin Kwak, Yoo, Kwon, Jun, Lazaro, Luisa, Li, Chiang-Shan, Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Menchon, Jose, Moreira, Pedro, Morgado, Pedro, Nakagawa, Akiko, Nakao, Tomohiro, Narayanaswamy, Janardhanan, Nurmi, Erika, Zorrilla, Jose, Picó-Pérez, Maria, Piras, Fabrizio, Piras, Federica, Pittenger, Christopher, Reddy, Janardhan, Rodriguez-Manrique, Daniela, Sakai, Yuki, Shimizu, Eiji, Shivakumar, Venkataram, Simpson, Blair, Soriano-Mas, Carles, Sousa, Nuno, Spalletta, Gianfranco, Stern, Emily, Evelyn Stewart, S, Szeszko, Philip, Tang, Jinsong, Thomopoulos, Sophia, Thorsen, Anders, Yoshida, Tokiko, Tomiyama, Hirofumi, Vai, Benedetta, Veer, Ilya, Venkatasubramanian, Ganesan, Vetter, Nora, Vriend, Chris, Walitza, Susanne, Waller, Lea, Wang, Zhen, Watanabe, Anri, Wolff, Nicole, Yun, Je-Yeon, Zhao, Qing, van Leeuwen, Wieke, van Marle, Hein, van de Mortel, Laurens, van der Straten, Anouk, van der Werf, Ysbrand, Thompson, Paul, Stein, Dan, van den Heuvel, Odile, van Wingen, Guido, and Piacentini, John

Subjects
Humans, Connectome, Brain Mapping, Magnetic Resonance Imaging, Brain, Obsessive-Compulsive Disorder, Biomarkers, Neural Pathways
Abstract

Current knowledge about functional connectivity in obsessive-compulsive disorder (OCD) is based on small-scale studies, limiting the generalizability of results. Moreover, the majority of studies have focused only on predefined regions or functional networks rather than connectivity throughout the entire brain. Here, we investigated differences in resting-state functional connectivity between OCD patients and healthy controls (HC) using mega-analysis of data from 1024 OCD patients and 1028 HC from 28 independent samples of the ENIGMA-OCD consortium. We assessed group differences in whole-brain functional connectivity at both the regional and network level, and investigated whether functional connectivity could serve as biomarker to identify patient status at the individual level using machine learning analysis. The mega-analyses revealed widespread abnormalities in functional connectivity in OCD, with global hypo-connectivity (Cohens d: -0.27 to -0.13) and few hyper-connections, mainly with the thalamus (Cohens d: 0.19 to 0.22). Most hypo-connections were located within the sensorimotor network and no fronto-striatal abnormalities were found. Overall, classification performances were poor, with area-under-the-receiver-operating-characteristic curve (AUC) scores ranging between 0.567 and 0.673, with better classification for medicated (AUC = 0.702) than unmedicated (AUC = 0.608) patients versus healthy controls. These findings provide partial support for existing pathophysiological models of OCD and highlight the important role of the sensorimotor network in OCD. However, resting-state connectivity does not so far provide an accurate biomarker for identifying patients at the individual level.

Published
2023

5. Growth hormone receptor agonists and antagonists: From protein expression and purification to long-acting formulations.

Author

Wang, Yue, Kim, Minah, Buckley, Chantal, Maynard, Heather, Langley, Ries, and Perry, Jo

Subjects
PEGylation, antagonist, biotherapeutic, fusion protein, growth hormone, long-acting, recombinant protein production, Humans, Human Growth Hormone, Recombinant Proteins, Receptors, Somatotropin
Abstract

Recombinant human growth hormone (rhGH) and GH receptor antagonists (GHAs) are used clinically to treat a range of disorders associated with GH deficiency or hypersecretion, respectively. However, these biotherapeutics can be difficult and expensive to manufacture with multiple challenges from recombinant protein generation through to the development of long-acting formulations required to improve the circulating half-life of the drug. In this review, we summarize methodologies and approaches used for making and purifying recombinant GH and GHA proteins, and strategies to improve pharmacokinetic and pharmacodynamic properties, including PEGylation and fusion proteins. Therapeutics that are in clinical use or are currently under development are also discussed.

Published
2023

8. Validation of the Collaborative Outcomes study on Health and Functioning during Infection Times (COH-FIT) questionnaire for adults

Author

Solmi, Marco, Thompson, Trevor, Estradé, Andrés, Agorastos, Agorastos, Radua, Joaquim, Cortese, Samuele, Dragioti, Elena, Leisch, Friedrich, Vancampfort, Davy, Thygesen, Lau Caspar, Aschauer, Harald, Schlögelhofer, Monika, Aschauer, Elena, Schneeberger, Andres, Huber, Christian G, Hasler, Gregor, Conus, Philippe, Do Cuénod, Kim Q, von Känel, Roland, Arrondo, Gonzalo, Fusar-Poli, Paolo, Gorwood, Philip, Llorca, Pierre-Michel, Krebs, Marie-Odile, Scanferla, Elisabetta, Kishimoto, Taishiro, Rabbani, Golam, Skonieczna-Żydecka, Karolina, Brambilla, Paolo, Favaro, Angela, Takamiya, Akihiro, Zoccante, Leonardo, Colizzi, Marco, Bourgin, Julie, Kamiński, Karol, Moghadasin, Maryam, Seedat, Soraya, Matthews, Evan, Wells, John, Vassilopoulou, Emilia, Gadelha, Ary, Su, Kuan-Pin, Kwon, Jun Soo, Kim, Minah, Lee, Tae Young, Papsuev, Oleg, Manková, Denisa, Boscutti, Andrea, Gerunda, Cristiano, Saccon, Diego, Righi, Elena, Monaco, Francesco, Croatto, Giovanni, Cereda, Guido, Demurtas, Jacopo, Brondino, Natascia, Veronese, Nicola, Enrico, Paolo, Politi, Pierluigi, Ciappolino, Valentina, Pfennig, Andrea, Bechdolf, Andreas, Meyer-Lindenberg, Andreas, Kahl, Kai G, Domschke, Katharina, Bauer, Michael, Koutsouleris, Nikolaos, Winter, Sibylle, Borgwardt, Stefan, Bitter, Istvan, Balazs, Judit, Czobor, Pál, Unoka, Zsolt, Mavridis, Dimitris, Tsamakis, Konstantinos, Bozikas, Vasilios P, Tunvirachaisakul, Chavit, Maes, Michael, Rungnirundorn, Teerayuth, Supasitthumrong, Thitiporn, Haque, Ariful, Brunoni, Andre R, Costardi, Carlos Gustavo, Schuch, Felipe Barreto, Polanczyk, Guilherme, Luiz, Jhoanne Merlyn, Fonseca, Lais, Aparicio, Luana V, Valvassori, Samira S, Nordentoft, Merete, Vendsborg, Per, Hoffmann, Sofie Have, Sehli, Jihed, Sartorius, Norman, Heuss, Sabina, Guinart, Daniel, Hamilton, Jane, Kane, John, Rubio, Jose, and Sand, Michael

Subjects
Clinical and Health Psychology, Health Sciences, Psychology, Mental Health, Behavioral and Social Science, Brain Disorders, Depression, Mental health, Good Health and Well Being, Humans, Adult, Reproducibility of Results, Pandemics, COVID-19, Surveys and Questionnaires, Outcome Assessment, Health Care, Factor Analysis, Statistical, Psychometrics, Covid-19, Pandemic, COH-FIT, Survey: P-factor: well-being: mental health: psychiatry: psychometric, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Biomedical and clinical sciences, Health sciences
Abstract

BackgroundThe Collaborative Outcome study on Health and Functioning during Infection Times (COH-FIT; www.coh-fit.com) is an anonymous and global online survey measuring health and functioning during the COVID-19 pandemic. The aim of this study was to test concurrently the validity of COH-FIT items and the internal validity of the co-primary outcome, a composite psychopathology "P-score".MethodsThe COH-FIT survey has been translated into 30 languages (two blind forward-translations, consensus, one independent English back-translation, final harmonization). To measure mental health, 1-4 items ("COH-FIT items") were extracted from validated questionnaires (e.g. Patient Health Questionnaire 9). COH-FIT items measured anxiety, depressive, post-traumatic, obsessive-compulsive, bipolar and psychotic symptoms, as well as stress, sleep and concentration. COH-FIT Items which correlated r ≥ 0.5 with validated companion questionnaires, were initially retained. A P-score factor structure was then identified from these items using exploratory factor analysis (EFA) and confirmatory factor analyses (CFA) on data split into training and validation sets. Consistency of results across languages, gender and age was assessed.ResultsFrom >150,000 adult responses by May 6th, 2022, a subset of 22,456 completed both COH-FIT items and validated questionnaires. Concurrent validity was consistently demonstrated across different languages for COH-FIT items. CFA confirmed EFA results of five first-order factors (anxiety, depression, post-traumatic, psychotic, psychophysiologic symptoms) and revealed a single second-order factor P-score, with high internal reliability (ω = 0.95). Factor structure was consistent across age and sex.ConclusionsCOH-FIT is a valid instrument to globally measure mental health during infection times. The P-score is a valid measure of multidimensional mental health.

Published
2023

9. Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium.

Author

Constantinides, Constantinos, Han, Laura KM, Alloza, Clara, Antonucci, Linda Antonella, Arango, Celso, Ayesa-Arriola, Rosa, Banaj, Nerisa, Bertolino, Alessandro, Borgwardt, Stefan, Bruggemann, Jason, Bustillo, Juan, Bykhovski, Oleg, Calhoun, Vince, Carr, Vaughan, Catts, Stanley, Chung, Young-Chul, Crespo-Facorro, Benedicto, Díaz-Caneja, Covadonga M, Donohoe, Gary, Plessis, Stefan Du, Edmond, Jesse, Ehrlich, Stefan, Emsley, Robin, Eyler, Lisa T, Fuentes-Claramonte, Paola, Georgiadis, Foivos, Green, Melissa, Guerrero-Pedraza, Amalia, Ha, Minji, Hahn, Tim, Henskens, Frans A, Holleran, Laurena, Homan, Stephanie, Homan, Philipp, Jahanshad, Neda, Janssen, Joost, Ji, Ellen, Kaiser, Stefan, Kaleda, Vasily, Kim, Minah, Kim, Woo-Sung, Kirschner, Matthias, Kochunov, Peter, Kwak, Yoo Bin, Kwon, Jun Soo, Lebedeva, Irina, Liu, Jingyu, Mitchie, Patricia, Michielse, Stijn, Mothersill, David, Mowry, Bryan, de la Foz, Víctor Ortiz-García, Pantelis, Christos, Pergola, Giulio, Piras, Fabrizio, Pomarol-Clotet, Edith, Preda, Adrian, Quidé, Yann, Rasser, Paul E, Rootes-Murdy, Kelly, Salvador, Raymond, Sangiuliano, Marina, Sarró, Salvador, Schall, Ulrich, Schmidt, André, Scott, Rodney J, Selvaggi, Pierluigi, Sim, Kang, Skoch, Antonin, Spalletta, Gianfranco, Spaniel, Filip, Thomopoulos, Sophia I, Tomecek, David, Tomyshev, Alexander S, Tordesillas-Gutiérrez, Diana, van Amelsvoort, Therese, Vázquez-Bourgon, Javier, Vecchio, Daniela, Voineskos, Aristotle, Weickert, Cynthia S, Weickert, Thomas, Thompson, Paul M, Schmaal, Lianne, van Erp, Theo GM, Turner, Jessica, Cole, James H, ENIGMA Schizophrenia Consortium, Dima, Danai, and Walton, Esther

Subjects
ENIGMA Schizophrenia Consortium, Brain, Humans, Magnetic Resonance Imaging, Prospective Studies, Schizophrenia, Aging, Adolescent, Adult, Aged, Middle Aged, Female, Male, Young Adult, Mental Health, Serious Mental Illness, Brain Disorders, Neurosciences, Biomedical Imaging, Clinical Research, Behavioral and Social Science, Neurological, Mental health, Good Health and Well Being, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen's d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

Published
2023

10. Beyond verbal fluency in the verbal fluency task: semantic clustering as a predictor of remission in individuals at clinical high risk for psychosis

Author

Choe, Eugenie, Ha, Minji, Choi, Sunah, Park, Sunghyun, Jang, Moonyoung, Kim, Minah, and Kwon, Jun Soo

Subjects
Medical research, Medicine, Experimental, Medical colleges, Health, Psychology and mental health
Abstract

Background: There have been conflicting reports on whether conventional verbal fluency measures can predict the prognosis of individuals at clinical high risk (CHR) for psychosis. We aimed to investigate whether verbal fluency task measures that represent semantic processing more directly than conventional measures could be more reliable predictors of later remission in CHR individuals. Methods: We recruited CHR individuals and healthy controls to participate in a baseline verbal fluency assessment. We identified semantic clusters within the verbal fluency task responses based on cosine similarity between consecutive words, calculated from the word embedding model. Binomial logistic regression was performed to test whether average semantic cluster size and number of words produced could be predictors of remission in CHR individuals. Results: Our study sample included 96 CHR individuals and 178 healthy controls. According to clinical assessment at the last follow-up, 23 CHR individuals were classified as remitters and 73 as nonremitters, including 29 individuals who converted to psychosis. The CHR remitters showed larger average and maximum semantic cluster sizes than CHR nonremitters and healthy controls. Average semantic cluster size, but not the number of words, was a significant predictor of later remission in CHR individuals. Limitations: Our sample included only native Korean speakers. Conclusion: A verbal fluency task measure that more specifically represents semantic processing may be a better neurocognitive predictive marker for remission in CHR individuals than conventional verbal fluency measures. Our results provide an explanation for heterogeneous reports on whether verbal fluency can predict prognosis in CHR individuals and suggest that semantic processing is a putative cognitive predictor of their prognosis., Introduction The clinical high risk state (CHR) for psychosis is a concept that was established for early intervention to prevent or delay the onset of psychotic disorders. (1) However, it [...]

Published
2023
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13. Correction: White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group

Author

Kim, Bo-Gyeom, Kim, Gakyung, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie, Anticevic, Alan, Arnold, Paul D., Balachander, Srinivas, Banaj, Nerisa, Bargalló, Nuria, Batistuzzo, Marcelo C., Benedetti, Francesco, Bertolín, Sara, Beucke, Jan Carl, Bollettini, Irene, Brem, Silvia, Brennan, Brian P., Buitelaar, Jan K., Calvo, Rosa, Castelo-Branco, Miguel, Cheng, Yuqi, Chhatkuli, Ritu Bhusal, Ciullo, Valentina, Coelho, Ana, Couto, Beatriz, Dallaspezia, Sara, Ely, Benjamin A., Ferreira, Sónia, Fontaine, Martine, Fouche, Jean-Paul, Grazioplene, Rachael, Gruner, Patricia, Hagen, Kristen, Hansen, Bjarne, Hanna, Gregory L., Hirano, Yoshiyuki, Höxter, Marcelo Q., Hough, Morgan, Hu, Hao, Huyser, Chaim, Ikuta, Toshikazu, Jahanshad, Neda, James, Anthony, Jaspers-Fayer, Fern, Kasprzak, Selina, Kathmann, Norbert, Kaufmann, Christian, Kim, Minah, Koch, Kathrin, Kvale, Gerd, Kwon, Jun Soo, Lazaro, Luisa, Lee, Junhee, Lochner, Christine, Lu, Jin, Manrique, Daniela Rodriguez, Martínez-Zalacaín, Ignacio, Masuda, Yoshitada, Matsumoto, Koji, Maziero, Maria Paula, Menchón, Jose M., Minuzzi, Luciano, Moreira, Pedro Silva, Morgado, Pedro, Narayanaswamy, Janardhanan C., Narumoto, Jin, Ortiz, Ana E., Ota, Junko, Pariente, Jose C., Perriello, Chris, Picó-Pérez, Maria, Pittenger, Christopher, Poletti, Sara, Real, Eva, Reddy, Y. C. Janardhan, van Rooij, Daan, Sakai, Yuki, Sato, João Ricardo, Segalas, Cinto, Shavitt, Roseli G., Shen, Zonglin, Shimizu, Eiji, Shivakumar, Venkataram, Soreni, Noam, Soriano-Mas, Carles, Sousa, Nuno, Sousa, Mafalda Machado, Spalletta, Gianfranco, Stern, Emily R., Stewart, S. Evelyn, Szeszko, Philip R., Thomas, Rajat, Thomopoulos, Sophia I., Vecchio, Daniela, Venkatasubramanian, Ganesan, Vriend, Chris, Walitza, Susanne, Wang, Zhen, Watanabe, Anri, Wolters, Lidewij, Xu, Jian, Yamada, Kei, Yun, Je-Yeon, Zarei, Mojtaba, Zhao, Qing, Zhu, Xi, Thompson, Paul M., Bruin, Willem B., van Wingen, Guido A., Piras, Federica, Piras, Fabrizio, Stein, Dan J., van den Heuvel, Odile A., Simpson, Helen Blair, Marsh, Rachel, and Cha, Jiook

Published
2024
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15. Learning Oculomotor Behaviors from Scanpath

Author

Li, Beibin, Nuechterlein, Nicholas, Barney, Erin, Foster, Claire, Kim, Minah, Mahony, Monique, Atyabi, Adham, Feng, Li, Wang, Quan, Ventola, Pamela, Shapiro, Linda, and Shic, Frederick

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Human-Computer Interaction, Computer Science - Machine Learning
Abstract

Identifying oculomotor behaviors relevant for eye-tracking applications is a critical but often challenging task. Aiming to automatically learn and extract knowledge from existing eye-tracking data, we develop a novel method that creates rich representations of oculomotor scanpaths to facilitate the learning of downstream tasks. The proposed stimulus-agnostic Oculomotor Behavior Framework (OBF) model learns human oculomotor behaviors from unsupervised and semi-supervised tasks, including reconstruction, predictive coding, fixation identification, and contrastive learning tasks. The resultant pre-trained OBF model can be used in a variety of applications. Our pre-trained model outperforms baseline approaches and traditional scanpath methods in autism spectrum disorder and viewed-stimulus classification tasks. Ablation experiments further show our proposed method could achieve even better results with larger model sizes and more diverse eye-tracking training datasets, supporting the model's potential for future eye-tracking applications. Open source code: http://github.com/BeibinLi/OBF., Comment: Accepted ACM ICMI 2021

Published
2021
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24. Oncolytic vaccinia virus injected intravenously sensitizes pancreatic neuroendocrine tumors and metastases to immune checkpoint blockade.

Author

Inoue, Mitsuko, Kim, Minah, Inoue, Tomoyoshi, Tait, Madeline, Byrne, Thomas, Nitschké, Maximilian, Murer, Patrizia, Cha, Howard, Subramanian, Aishwarya, De Silva, Naomi, Chiaverotti, Teresa, and McDonald, Donald

Subjects
A/J mice, NK cells, PD-1, Pexa-Vec, RIP1-Tag2 mice, apoptosis, cytotoxic T cells, hypoglycemia, insulin, liver metastasis, regression
Abstract

This study determined the influence of intravenous (i.v.) oncolytic vaccinia virus mpJX-594 (mpJX) on antitumor activity of anti-programmed death receptor-1 antibody (aPD1) in functional and metastatic pancreatic neuroendocrine tumors (PanNETs). One i.v. dose of mpJX, engineered for mice with the same plasmid design as clinical virus Pexa-Vec, was administered alone or with repeated dosing of aPD1 (mpJX+aPD1) to two contrasting genetic models of PanNET: one developing benign insulin-secreting tumors (RIP1-Tag2;C57BL/6J mice) and the other developing liver metastases (RIP1-Tag2;AB6F1 mice). Experiments revealed that aPD1 had synergistic actions with mpJX on CD8+ T cell and natural killer (NK) cell influx, apoptosis, and suppression of proliferation in PanNETs. After mpJX+aPD1, the 53-fold increase in apoptosis (5 days) and 85% reduction in proliferation (20 days) exceeded the sum of mpJX and aPD1 given separately. mpJX+aPD1 also stabilized blood insulin and glucose in mice with functional PanNETs, regressed liver metastases in mice with aggressive PanNETs, and prolonged survival of both. The findings revealed that mpJX+aPD1 converted cold PanNETs into immunogenic tumors with widespread cytotoxic T cell influx, tumor cell killing, and suppression of proliferation. Reduction of tumor insulin secretion from functional PanNETs prolonged survival, and anti-metastatic actions on aggressive PanNETs reduced the metastatic burden to less than before treatment. The findings support the efficacy of the vaccinia virus with aPD1 for functional and metastatic PanNETs.

Published
2022

25. Neuroanatomical heterogeneity and homogeneity in individuals at clinical high risk for psychosis

Author

Baldwin, Helen, Radua, Joaquim, Antoniades, Mathilde, Haas, Shalaila S, Frangou, Sophia, Agartz, Ingrid, Allen, Paul, Andreassen, Ole A, Atkinson, Kimberley, Bachman, Peter, Baeza, Inmaculada, Bartholomeusz, Cali F, Chee, Michael WL, Colibazzi, Tiziano, Cooper, Rebecca E, Corcoran, Cheryl M, Cropley, Vanessa L, Ebdrup, Bjørn H, Fortea, Adriana, Glenthøj, Louise Birkedal, Hamilton, Holly K, Haut, Kristen M, Hayes, Rebecca A, He, Ying, Heekeren, Karsten, Kaess, Michael, Kasai, Kiyoto, Katagiri, Naoyuki, Kim, Minah, Kindler, Jochen, Klaunig, Mallory J, Koike, Shinsuke, Koppel, Alex, Kristensen, Tina D, Bin Kwak, Yoo, Kwon, Jun Soo, Lawrie, Stephen M, Lebedeva, Irina, Lee, Jimmy, Lin, Ashleigh, Loewy, Rachel L, Mathalon, Daniel H, Michel, Chantal, Mizrahi, Romina, Møller, Paul, Nelson, Barnaby, Nemoto, Takahiro, Nordholm, Dorte, Omelchenko, Maria A, Pantelis, Christos, Raghava, Jayachandra M, Røssberg, Jan I, Rössler, Wulf, Salisbury, Dean F, Sasabayashi, Daiki, Schall, Ulrich, Smigielski, Lukasz, Sugranyes, Gisela, Suzuki, Michio, Takahashi, Tsutomu, Tamnes, Christian K, Tang, Jinsong, Theodoridou, Anastasia, Thomopoulos, Sophia I, Tomyshev, Alexander S, Uhlhaas, Peter J, Værnes, Tor G, van Amelsvoort, Therese AMJ, Van Erp, Theo GM, Waltz, James A, Westlye, Lars T, Wood, Stephen J, Zhou, Juan H, McGuire, Philip, Thompson, Paul M, Jalbrzikowski, Maria, Hernaus, Dennis, and Fusar-Poli, Paolo

Subjects
Serious Mental Illness, Prevention, Biomedical Imaging, Mental Health, Clinical Research, Neurosciences, Brain, Humans, Magnetic Resonance Imaging, Psychotic Disorders, ENIGMA Clinical High Risk for Psychosis Working Group, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

Individuals at Clinical High Risk for Psychosis (CHR-P) demonstrate heterogeneity in clinical profiles and outcome features. However, the extent of neuroanatomical heterogeneity in the CHR-P state is largely undetermined. We aimed to quantify the neuroanatomical heterogeneity in structural magnetic resonance imaging measures of cortical surface area (SA), cortical thickness (CT), subcortical volume (SV), and intracranial volume (ICV) in CHR-P individuals compared with healthy controls (HC), and in relation to subsequent transition to a first episode of psychosis. The ENIGMA CHR-P consortium applied a harmonised analysis to neuroimaging data across 29 international sites, including 1579 CHR-P individuals and 1243 HC, offering the largest pooled CHR-P neuroimaging dataset to date. Regional heterogeneity was indexed with the Variability Ratio (VR) and Coefficient of Variation (CV) ratio applied at the group level. Personalised estimates of heterogeneity of SA, CT and SV brain profiles were indexed with the novel Person-Based Similarity Index (PBSI), with two complementary applications. First, to assess the extent of within-diagnosis similarity or divergence of neuroanatomical profiles between individuals. Second, using a normative modelling approach, to assess the 'normativeness' of neuroanatomical profiles in individuals at CHR-P. CHR-P individuals demonstrated no greater regional heterogeneity after applying FDR corrections. However, PBSI scores indicated significantly greater neuroanatomical divergence in global SA, CT and SV profiles in CHR-P individuals compared with HC. Normative PBSI analysis identified 11 CHR-P individuals (0.70%) with marked deviation (>1.5 SD) in SA, 118 (7.47%) in CT and 161 (10.20%) in SV. Psychosis transition was not significantly associated with any measure of heterogeneity. Overall, our examination of neuroanatomical heterogeneity within the CHR-P state indicated greater divergence in neuroanatomical profiles at an individual level, irrespective of psychosis conversion. Further large-scale investigations are required of those who demonstrate marked deviation.

Published
2022

30. Angiopoietin-2 blockade suppresses growth of liver metastases from pancreatic neuroendocrine tumors by promoting T cell recruitment

Author

Lee, Eunhyeong, O'Keefe, Sophie, Leong, Alessandra, Park, Ha-Ram, Varadarajan, Janani, Chowdhury, Subrata, Hiner, Shannon, Kim, Sungsoo, Shiva, Anahita, Friedman, Richard A., Remotti, Helen, Fojo, Tito, Yang, Hee Won, Thurston, Gavin, and Kim, Minah

Subjects
Regeneron Pharmaceuticals Inc. -- Growth, Immunohistochemistry -- Health aspects, T cells -- Growth, RNA sequencing -- Health aspects -- Growth, Metastasis -- Development and progression, Endothelium -- Growth, B cells -- Growth -- Health aspects, Genetic engineering -- Growth -- Health aspects, Pharmaceutical industry -- Growth -- Health aspects, Company growth, Health care industry
Abstract

Improving the management of metastasis in pancreatic neuroendocrine tumors (PanNETs) is critical, as nearly half of patients with PanNETs present with liver metastases, and this accounts for the majority of patient mortality. We identified angiopoietin-2 (ANGPT2) as one of the most upregulated angiogenic factors in RNA-Seq data from human PanNET liver metastases and found that higher ANGPT2 expression correlated with poor survival rates. Immunohistochemical staining revealed that ANGPT2 was localized to the endothelial cells of blood vessels in PanNET liver metastases. We observed an association between the upregulation of endothelial ANGPT2 and liver metastatic progression in both patients and transgenic mouse models of PanNETs. In human and mouse PanNET liver metastases, ANGPT2 upregulation coincided with poor T cell infiltration, indicative of an immunosuppressive tumor microenvironment. Notably, both pharmacologic inhibition and genetic deletion of ANGPT2 in PanNET mouse models slowed the growth of PanNET liver metastases. Furthermore, pharmacologic inhibition of ANGPT2 promoted T cell infiltration and activation in liver metastases, improving the survival of mice with metastatic PanNETs. These changes were accompanied by reduced plasma leakage and improved vascular integrity in metastases. Together, these findings suggest that ANGPT2 blockade may be an effective strategy for promoting T cell infiltration and immunostimulatory reprogramming to reduce the growth of liver metastases in PanNETs., Introduction Pancreatic neuroendocrine tumors (PanNETs) account for approximately 3%-5% of all pancreatic cancers. Their incidence has been steadily increasing over recent decades; however, they remain an understudied area of pancreatic [...]

Published
2023
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31. Correction: The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium

Author

Bruin, Willem B., Abe, Yoshinari, Alonso, Pino, Anticevic, Alan, Backhausen, Lea L., Balachander, Srinivas, Bargallo, Nuria, Batistuzzo, Marcelo C., Benedetti, Francesco, Bertolin Triquell, Sara, Brem, Silvia, Calesella, Federico, Couto, Beatriz, Denys, Damiaan A. J. P., Echevarria, Marco A. N., Eng, Goi Khia, Ferreira, Sónia, Feusner, Jamie D., Grazioplene, Rachael G., Gruner, Patricia, Guo, Joyce Y., Hagen, Kristen, Hansen, Bjarne, Hirano, Yoshiyuki, Hoexter, Marcelo Q., Jahanshad, Neda, Jaspers-Fayer, Fern, Kasprzak, Selina, Kim, Minah, Koch, Kathrin, Bin Kwak, Yoo, Kwon, Jun Soo, Lazaro, Luisa, Li, Chiang-Shan R., Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Menchon, Jose M., Moreira, Pedro S., Morgado, Pedro, Nakagawa, Akiko, Nakao, Tomohiro, Narayanaswamy, Janardhanan C., Nurmi, Erika L., Zorrilla, Jose C. Pariente, Piacentini, John, Picó-Pérez, Maria, Piras, Fabrizio, Piras, Federica, Pittenger, Christopher, Reddy, Janardhan Y. C., Rodriguez-Manrique, Daniela, Sakai, Yuki, Shimizu, Eiji, Shivakumar, Venkataram, Simpson, Blair H., Soriano-Mas, Carles, Sousa, Nuno, Spalletta, Gianfranco, Stern, Emily R., Evelyn Stewart, S., Szeszko, Philip R., Tang, Jinsong, Thomopoulos, Sophia I., Thorsen, Anders L., Yoshida, Tokiko, Tomiyama, Hirofumi, Vai, Benedetta, Veer, Ilya M., Venkatasubramanian, Ganesan, Vetter, Nora C., Vriend, Chris, Walitza, Susanne, Waller, Lea, Wang, Zhen, Watanabe, Anri, Wolff, Nicole, Yun, Je-Yeon, Zhao, Qing, van Leeuwen, Wieke A., van Marle, Hein J. F., van de Mortel, Laurens A., van der Straten, Anouk, van der Werf, Ysbrand D., Thompson, Paul M., Stein, Dan J., van den Heuvel, Odile A., and van Wingen, Guido A.

Published
2023
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37. In Vivo Reactive Astrocyte Imaging in Patients With Schizophrenia Using Fluorine 18–Labeled THK5351

Author

Kim, Minah, primary, Choi, Woori, additional, Choi, Sunah, additional, Oh, Harin, additional, Kim, Jongrak, additional, Lee, Jungha, additional, An, Su-Jin, additional, Hwang, Jun Seo, additional, Lee, Yun-Sang, additional, Song, In Chan, additional, Moon, Sun-Young, additional, Lho, Silvia Kyungjin, additional, Cho, Sang Soo, additional, and Kwon, Jun Soo, additional

Published
2024
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38. Global and risk-group stratified well-being and mental health during the COVID-19 pandemic in adults: Results from the international COH-FIT Study

Author

Solmi, Marco, primary, Thompson, Trevor, additional, Estradé, Andrés, additional, Agorastos, Agorastos, additional, Radua, Joaquim, additional, Cortese, Samuele, additional, Dragioti, Elena, additional, Leisch, Friedrich, additional, Vancampfort, Davy, additional, Thygesen, Lau Caspar, additional, Aschauer, Harald, additional, Schlögelhofer, Monika, additional, Aschauer, Elena, additional, Schneeberger, Andres, additional, Huber, Christian G., additional, Hasler, Gregor, additional, Conus, Philippe, additional, Cuénod, Kim Q. Do, additional, von Känel, Roland, additional, Arrondo, Gonzalo, additional, Fusar-Poli, Paolo, additional, Gorwood, Philip, additional, Llorca, Pierre-Michel, additional, Krebs, Marie-Odile, additional, Scanferla, Elisabetta, additional, Kishimoto, Taishiro, additional, Rabbani, Golam, additional, Skonieczna-Żydecka, Karolina, additional, Brambilla, Paolo, additional, Favaro, Angela, additional, Takamiya, Akihiro, additional, Zoccante, Leonardo, additional, Colizzi, Marco, additional, Bourgin, Julie, additional, Kamiński, Karol, additional, Moghadasin, Maryam, additional, Seedat, Soraya, additional, Matthews, Evan, additional, Wells, John, additional, Vassilopoulou, Emilia, additional, Gadelha, Ary, additional, Su, Kuan-Pin, additional, Kwon, Jun Soo, additional, Kim, Minah, additional, Lee, Tae Young, additional, Papsuev, Oleg, additional, Manková, Denisa, additional, Boscutti, Andrea, additional, Gerunda, Cristiano, additional, Saccon, Diego, additional, Righi, Elena, additional, Monaco, Francesco, additional, Croatto, Giovanni, additional, Cereda, Guido, additional, Demurtas, Jacopo, additional, Brondino, Natascia, additional, Veronese, Nicola, additional, Enrico, Paolo, additional, Politi, Pierluigi, additional, Ciappolino, Valentina, additional, Pfennig, Andrea, additional, Bechdolf, Andreas, additional, Meyer-Lindenberg, Andreas, additional, Kahl, Kai G., additional, Domschke, Katharina, additional, Bauer, Michael, additional, Koutsouleris, Nikolaos, additional, Winter, Sibylle, additional, Borgwardt, Stefan, additional, Bitter, Istvan, additional, Balazs, Judit, additional, Czobor, Pál, additional, Unoka, Zsolt, additional, Mavridis, Dimitris, additional, Tsamakis, Konstantinos, additional, Bozikas, Vasilios P., additional, Tunvirachaisakul, Chavit, additional, Maes, Michael, additional, Rungnirundorn, Teerayuth, additional, Supasitthumrong, Thitiporn, additional, Haque, Ariful, additional, Brunoni, Andre R., additional, Costardi, Carlos Gustavo, additional, Schuch, Felipe Barreto, additional, Polanczyk, Guilherme, additional, Luiz, Jhoanne Merlyn, additional, Fonseca, Lais, additional, Aparicio, Luana V., additional, Valvassori, Samira S., additional, Nordentoft, Merete, additional, Vendsborg, Per, additional, Hoffmann, Sofie Have, additional, Sehli, Jihed, additional, Sartorius, Norman, additional, Heuss, Sabina, additional, Guinart, Daniel, additional, Hamilton, Jane, additional, Kane, John, additional, Rubio, Jose, additional, Sand, Michael, additional, Koyanagi, Ai, additional, Solanes, Aleix, additional, Andreu-Bernabeu, Alvaro, additional, Cáceres, Antonia San José, additional, Arango, Celso, additional, Díaz-Caneja, Covadonga M., additional, Hidalgo-Mazzei, Diego, additional, Vieta, Eduard, additional, Gonzalez-Peñas, Javier, additional, Fortea, Lydia, additional, Parellada, Mara, additional, Fullana, Miquel A., additional, Verdolini, Norma, additional, Andrlíková, Eva, additional, Janků, Karolina, additional, Millan, Mark J., additional, Honciuc, Mihaela, additional, Moniuszko-Malinowska, Anna, additional, Łoniewski, Igor, additional, Samochowiec, Jerzy, additional, Kiszkiel, Łukasz, additional, Marlicz, Maria, additional, Sowa, Paweł, additional, Marlicz, Wojciech, additional, Spies, Georgina, additional, Stubbs, Brendon, additional, Firth, Joseph, additional, Sullivan, Sarah, additional, Darcin, Asli Enez, additional, Aksu, Hatice, additional, Dilbaz, Nesrin, additional, Noyan, Onur, additional, Kitazawa, Momoko, additional, Kurokawa, Shunya, additional, Tazawa, Yuki, additional, Anselmi, Alejandro, additional, Cracco, Cecilia, additional, Machado, Ana Inés, additional, Estrade, Natalia, additional, De Leo, Diego, additional, Curtis, Jackie, additional, Berk, Michael, additional, Carvalho, Andre F., additional, Ward, Philip, additional, Teasdale, Scott, additional, Rosenbaum, Simon, additional, Marx, Wolfgang, additional, Horodnic, Adrian Vasile, additional, Oprea, Liviu, additional, Alexinschi, Ovidiu, additional, Ifteni, Petru, additional, Turliuc, Serban, additional, Ciuhodaru, Tudor, additional, Bolos, Alexandra, additional, Matei, Valentin, additional, Nieman, Dorien H., additional, Sommer, Iris, additional, van Os, Jim, additional, van Amelsvoort, Therese, additional, Sun, Ching-Fang, additional, Guu, Ta-wei, additional, Jiao, Can, additional, Zhang, Jieting, additional, Fan, Jialin, additional, Zou, Liye, additional, Yu, Xin, additional, Chi, Xinli, additional, de Timary, Philippe, additional, van Winkel, Ruud, additional, Ng, Bernardo, additional, Pena, Edilberto, additional, Arellano, Ramon, additional, Roman, Raquel, additional, Sanchez, Thelma, additional, Movina, Larisa, additional, Morgado, Pedro, additional, Brissos, Sofia, additional, Aizberg, Oleg, additional, Mosina, Anna, additional, Krinitski, Damir, additional, Mugisha, James, additional, Sadeghi-Bahmani, Dena, additional, Sheybani, Farshad, additional, Sadeghi, Masoud, additional, Hadi, Samira, additional, Brand, Serge, additional, Errazuriz, Antonia, additional, Crossley, Nicolas, additional, Ristic, Dragana Ignjatovic, additional, López-Jaramillo, Carlos, additional, Efthymiou, Dimitris, additional, Kuttichira, Praveenlal, additional, Kallivayalil, Roy Abraham, additional, Javed, Afzal, additional, Afridi, Muhammad Iqbal, additional, James, Bawo, additional, Seb-Akahomen, Omonefe Joy, additional, Fiedorowicz, Jess, additional, Daskalakis, Jeff, additional, Yatham, Lakshmi N., additional, Yang, Lin, additional, Okasha, Tarek, additional, Dahdouh, Aïcha, additional, Gerdle, Björn, additional, Tiihonen, Jari, additional, Shin, Jae Il, additional, Lee, Jinhee, additional, Mhalla, Ahmed, additional, Gaha, Lotfi, additional, Brahim, Takoua, additional, Altynbekov, Kuanysh, additional, Negay, Nikolay, additional, Nurmagambetova, Saltanat, additional, Jamei, Yasser Abu, additional, Weiser, Mark, additional, and Correll, Christoph U., additional

Published
2024
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45. The thalamus and its subnuclei—a gateway to obsessive-compulsive disorder

Author

Weeland, Cees J., Kasprzak, Selina, de Joode, Niels T., Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie H., Anticevic, Alan, Arnold, Paul D., Balachander, Srinivas, Banaj, Nerisa, Bargallo, Nuria, Batistuzzo, Marcelo C., Benedetti, Francesco, Beucke, Jan C., Bollettini, Irene, Brecke, Vilde, Brem, Silvia, Cappi, Carolina, Cheng, Yuqi, Cho, Kang Ik K., Costa, Daniel L. C., Dallaspezia, Sara, Denys, Damiaan, Eng, Goi Khia, Ferreira, Sónia, Feusner, Jamie D., Fontaine, Martine, Fouche, Jean-Paul, Grazioplene, Rachael G., Gruner, Patricia, He, Mengxin, Hirano, Yoshiyuki, Hoexter, Marcelo Q., Huyser, Chaim, Hu, Hao, Jaspers-Fayer, Fern, Kathmann, Norbert, Kaufmann, Christian, Kim, Minah, Koch, Kathrin, Bin Kwak, Yoo, Kwon, Jun Soo, Lazaro, Luisa, Li, Chiang-shan R., Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Menchón, Jose M., Minnuzi, Luciano, Moreira, Pedro Silva, Morgado, Pedro, Nakagawa, Akiko, Nakamae, Takashi, Narayanaswamy, Janardhanan C., Nurmi, Erika L., Ortiz, Ana E., Pariente, Jose C., Piacentini, John, Picó-Pérez, Maria, Piras, Fabrizio, Piras, Federica, Pittenger, Christopher, Reddy, Y. C. Janardhan, Rodriguez-Manrique, Daniela, Sakai, Yuki, Shimizu, Eiji, Shivakumar, Venkataram, Simpson, Helen Blair, Soreni, Noam, Soriano-Mas, Carles, Sousa, Nuno, Spalletta, Gianfranco, Stern, Emily R., Stevens, Michael C., Stewart, S. Evelyn, Szeszko, Philip R., Takahashi, Jumpei, Tanamatis, Tais, Tang, Jinsong, Thorsen, Anders Lillevik, Tolin, David, van der Werf, Ysbrand D., van Marle, Hein, van Wingen, Guido A., Vecchio, Daniela, Venkatasubramanian, G., Walitza, Susanne, Wang, Jicai, Wang, Zhen, Watanabe, Anri, Wolters, Lidewij H., Xu, Xiufeng, Yun, Je-Yeon, Zhao, Qing, White, Tonya, Thompson, Paul M., Stein, Dan J., van den Heuvel, Odile A., and Vriend, Chris

Published
2022
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47. The Autism Biomarkers Consortium for Clinical Trials: evaluation of a battery of candidate eye-tracking biomarkers for use in autism clinical trials

Author

Shic, Frederick, Naples, Adam J., Barney, Erin C., Chang, Shou An, Li, Beibin, McAllister, Takumi, Kim, Minah, Dommer, Kelsey J., Hasselmo, Simone, Atyabi, Adham, Wang, Quan, Helleman, Gerhard, Levin, April R., Seow, Helen, Bernier, Raphael, Charwaska, Katarzyna, Dawson, Geraldine, Dziura, James, Faja, Susan, Jeste, Shafali Spurling, Johnson, Scott P., Murias, Michael, Nelson, Charles A., Sabatos-DeVito, Maura, Senturk, Damla, Sugar, Catherine A., Webb, Sara J., and McPartland, James C.

Published
2022
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49. Amplification of oncolytic vaccinia virus widespread tumor cell killing by sunitinib through multiple mechanisms

Author

Kim, Minah, Nitschké, Maximilian, Sennino, Barbara, Murer, Patrizia, Schriver, Brian J, Bell, Alexander, Subramanian, Aishwarya, McDonald, Corry E, Wang, Jiahu, Cha, Howard, Bourgeois-Daigneault, Marie-Claude, Kirn, David H, Bell, John C, De Silva, Naomi, Breitbach, Caroline J, and McDonald, Donald M

Subjects
Rare Diseases, Cancer, Aetiology, 2.1 Biological and endogenous factors, Infection, Animals, Antineoplastic Agents, Humans, Mice, Mice, Transgenic, Oncolytic Virotherapy, Oncolytic Viruses, Sunitinib, Vaccinia virus, Oncology and Carcinogenesis, Oncology & Carcinogenesis
Abstract

Oncolytic viruses pose many questions in their use in cancer therapy. In this study, we assessed the potential of mpJX-594 (mouse-prototype JX-594), a replication-competent vaccinia virus administered by intravenous injection, to target the tumor vasculature, produce immune activation and tumor cell killing more widespread than the infection, and suppress invasion and metastasis. These actions were examined in RIP-Tag2 transgenic mice with pancreatic neuroendocrine tumors that developed spontaneously and progressed as in humans. mpJX-594 initially infected tumor vascular endothelial cells, leading to vascular pruning and prolonged leakage in tumors but not in normal organs; parallel effects were observed in U87 gliomas. Viral infection spread to tumor cells, where tumor cell killing was much more widespread than the infection. Widespread tumor cell killing at 5 days was prevented by depletion of CD8+ T lymphocytes and did not require GM-CSF, as mpJX-594 variants that expressed human, mouse, or no GM-CSF produced equivalent amounts of killing. The antivascular, antitumor, and antimetastatic effects of mpJX-594 were amplified by concurrent or sequential administration of sunitinib, a multitargeted receptor tyrosine kinase inhibitor. These effects were not mimicked by selective inhibition of VEGFR2 despite equivalent vascular pruning, but were accompanied by suppression of regulatory T cells and greater influx of activated CD8+ T cells. Together, our results showed that mpJX-594 targets tumor blood vessels, spreads secondarily to tumor cells, and produces widespread CD8+ T-cell-dependent tumor cell killing in primary tumors and metastases, and that these effects can be amplified by coadministration of sunitinib.Significance: These findings reveal multiple unrecognized features of the antitumor properties of oncolytic vaccinia viruses, all of which can be amplified by the multitargeted kinase inhibitor sunitinib. Cancer Res; 78(4); 922-37. ©2017 AACR.

Published
2018

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