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Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach – CORRIGENDUM
- Micah Cearns, Azmeraw T. Amare, Klaus Oliver Schubert, Anbupalam Thalamuthu, Joseph Frank, Fabian Streit, Mazda Adli, Nirmala Akula, Kazufumi Akiyama, Raffaella Ardau, Bárbara Arias, JeanMichel Aubry, Lena Backlund, Abesh Kumar Bhattacharjee, Frank Bellivier, Antonio Benabarre, Susanne Bengesser, Joanna M. Biernacka, Armin Birner, Clara Brichant-Petitjean, Pablo Cervantes, HsiChung Chen, Caterina Chillotti, Sven Cichon, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Alexandre Dayer, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Bruno Étain, Peter Falkai, Andreas J. Forstner, Louise Frisen, Mark A. Frye, Janice M. Fullerton, Sébastien Gard, Julie S. Garnham, Fernando S. Goes, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Joanna Hauser, Urs Heilbronner, Stefan Herms, Per Hoffmann, Andrea Hofmann, Liping Hou, Yi-Hsiang Hsu, Stephane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Po-Hsiu Kuo, Tadafumi Kato, John Kelsoe, Sarah Kittel-Schneider, Sebastian Kliwicki, Barbara König, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G. Leckband, Mario Maj, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Mirko Manchia, Lina Martinsson, Michael J. McCarthy, Susan McElroy, Francesc Colom, Marina Mitjans, Francis M. Mondimore, Palmiero Monteleone, Caroline M. Nievergelt, Markus M. Nöthen, Tomas Novák, Claire O'Donovan, Norio Ozaki, Vincent Millischer, Sergi Papiol, Andrea Pfennig, Claudia Pisanu, James B. Potash, Andreas Reif, Eva Reininghaus, Guy A. Rouleau, Janusz K. Rybakowski, Martin Schalling, Peter R. Schofield, Barbara W. Schweizer, Giovanni Severino, Tatyana Shekhtman, Paul D. Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M. Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Fasil TekolaAyele, Alfonso Tortorella, Gustavo Turecki, Julia Veeh, Eduard Vieta, Stephanie H. Witt, Gloria Roberts, Peter P. Zandi, Martin Alda, Michael Bauer, Francis J. McMahon, Philip B. Mitchell, Thomas G. Schulze, Marcella Rietschel, Scott R. Clark, Bernhard T. Baune
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- Journal:
- The British Journal of Psychiatry / Volume 221 / Issue 2 / August 2022
- Published online by Cambridge University Press:
- 04 May 2022, p. 494
- Print publication:
- August 2022
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Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach
- Micah Cearns, Azmeraw T. Amare, Klaus Oliver Schubert, Anbupalam Thalamuthu, Joseph Frank, Fabian Streit, Mazda Adli, Nirmala Akula, Kazufumi Akiyama, Raffaella Ardau, Bárbara Arias, Jean-Michel Aubry, Lena Backlund, Abesh Kumar Bhattacharjee, Frank Bellivier, Antonio Benabarre, Susanne Bengesser, Joanna M. Biernacka, Armin Birner, Clara Brichant-Petitjean, Pablo Cervantes, Hsi-Chung Chen, Caterina Chillotti, Sven Cichon, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Alexandre Dayer, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Bruno Étain, Peter Falkai, Andreas J. Forstner, Louise Frisen, Mark A. Frye, Janice M. Fullerton, Sébastien Gard, Julie S. Garnham, Fernando S. Goes, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Joanna Hauser, Urs Heilbronner, Stefan Herms, Per Hoffmann, Andrea Hofmann, Liping Hou, Yi-Hsiang Hsu, Stephane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Po-Hsiu Kuo, Tadafumi Kato, John Kelsoe, Sarah Kittel-Schneider, Sebastian Kliwicki, Barbara König, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G. Leckband, Mario Maj, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Mirko Manchia, Lina Martinsson, Michael J. McCarthy, Susan McElroy, Francesc Colom, Marina Mitjans, Francis M. Mondimore, Palmiero Monteleone, Caroline M. Nievergelt, Markus M. Nöthen, Tomas Novák, Claire O'Donovan, Norio Ozaki, Vincent Millischer, Sergi Papiol, Andrea Pfennig, Claudia Pisanu, James B. Potash, Andreas Reif, Eva Reininghaus, Guy A. Rouleau, Janusz K. Rybakowski, Martin Schalling, Peter R. Schofield, Barbara W. Schweizer, Giovanni Severino, Tatyana Shekhtman, Paul D. Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M. Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Fasil Tekola-Ayele, Alfonso Tortorella, Gustavo Turecki, Julia Veeh, Eduard Vieta, Stephanie H. Witt, Gloria Roberts, Peter P. Zandi, Martin Alda, Michael Bauer, Francis J. McMahon, Philip B. Mitchell, Thomas G. Schulze, Marcella Rietschel, Scott R. Clark, Bernhard T. Baune
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- Journal:
- The British Journal of Psychiatry / Volume 220 / Issue 4 / April 2022
- Published online by Cambridge University Press:
- 28 February 2022, pp. 219-228
- Print publication:
- April 2022
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Background
Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.
AimsTo use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.
MethodThis study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.
ResultsThe best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.
ConclusionsUsing PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.
Evidence, and replication thereof, that molecular-genetic and environmental risks for psychosis impact through an affective pathway
- Jim van Os, Lotta-Katrin Pries, Margreet ten Have, Ron de Graaf, Saskia van Dorsselaer, Philippe Delespaul, Maarten Bak, Gunter Kenis, Bochao D. Lin, Jurjen J. Luykx, Alexander L. Richards, Berna Akdede, Tolga Binbay, Vesile Altınyazar, Berna Yalınçetin, Güvem Gümüş-Akay, Burçin Cihan, Haldun Soygür, Halis Ulaş, Eylem Şahin Cankurtaran, Semra Ulusoy Kaymak, Marina M. Mihaljevic, Sanja Andric Petrovic, Tijana Mirjanic, Miguel Bernardo, Gisela Mezquida, Silvia Amoretti, Julio Bobes, Pilar A. Saiz, María Paz García-Portilla, Julio Sanjuan, Eduardo J. Aguilar, José Luis Santos, Estela Jiménez-López, Manuel Arrojo, Angel Carracedo, Gonzalo López, Javier González-Peñas, Mara Parellada, Nadja P. Maric, Cem Atbaşoğlu, Alp Ucok, Köksal Alptekin, Meram Can Saka, Celso Arango, Michael O'Donovan, Bart P. F. Rutten, Sinan Guloksuz
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- Journal:
- Psychological Medicine / Volume 52 / Issue 10 / July 2022
- Published online by Cambridge University Press:
- 19 October 2020, pp. 1910-1922
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Background
There is evidence that environmental and genetic risk factors for schizophrenia spectrum disorders are transdiagnostic and mediated in part through a generic pathway of affective dysregulation.
MethodsWe analysed to what degree the impact of schizophrenia polygenic risk (PRS-SZ) and childhood adversity (CA) on psychosis outcomes was contingent on co-presence of affective dysregulation, defined as significant depressive symptoms, in (i) NEMESIS-2 (n = 6646), a representative general population sample, interviewed four times over nine years and (ii) EUGEI (n = 4068) a sample of patients with schizophrenia spectrum disorder, the siblings of these patients and controls.
ResultsThe impact of PRS-SZ on psychosis showed significant dependence on co-presence of affective dysregulation in NEMESIS-2 [relative excess risk due to interaction (RERI): 1.01, p = 0.037] and in EUGEI (RERI = 3.39, p = 0.048). This was particularly evident for delusional ideation (NEMESIS-2: RERI = 1.74, p = 0.003; EUGEI: RERI = 4.16, p = 0.019) and not for hallucinatory experiences (NEMESIS-2: RERI = 0.65, p = 0.284; EUGEI: −0.37, p = 0.547). A similar and stronger pattern of results was evident for CA (RERI delusions and hallucinations: NEMESIS-2: 3.02, p < 0.001; EUGEI: 6.44, p < 0.001; RERI delusional ideation: NEMESIS-2: 3.79, p < 0.001; EUGEI: 5.43, p = 0.001; RERI hallucinatory experiences: NEMESIS-2: 2.46, p < 0.001; EUGEI: 0.54, p = 0.465).
ConclusionsThe results, and internal replication, suggest that the effects of known genetic and non-genetic risk factors for psychosis are mediated in part through an affective pathway, from which early states of delusional meaning may arise.
A replication study of JTC bias, genetic liability for psychosis and delusional ideation
- Cécile Henquet, Jim van Os, Lotta K. Pries, Christian Rauschenberg, Philippe Delespaul, Gunter Kenis, Jurjen J. Luykx, Bochao D. Lin, Alexander L. Richards, Berna Akdede, Tolga Binbay, Vesile Altınyazar, Berna Yalınçetin, Güvem Gümüş-Akay, Burçin Cihan, Haldun Soygür, Halis Ulaş, Eylem S. Cankurtaran, Semra U. Kaymak, Marina M. Mihaljevic, Sanja S. Petrovic, Tijana Mirjanic, Miguel Bernardo, Gisela Mezquida, Silvia Amoretti, Julio Bobes, Pilar A. Saiz, Maria P. García-Portilla, Julio Sanjuan, Eduardo J. Aguilar, Jose L. Santos, Estela Jiménez-López, Manuel Arrojo, Angel Carracedo, Gonzalo López, Javier González-Peñas, Mara Parellada, Nadja P. Maric, Cem Atbaşoğlu, Alp Ucok, Köksal Alptekin, Meram C. Saka, Celso Arango, Michael O'Donovan, Bart P.F. Rutten, Sinan Gülöksüz
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- Journal:
- Psychological Medicine / Volume 52 / Issue 9 / July 2022
- Published online by Cambridge University Press:
- 13 October 2020, pp. 1777-1783
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Background
This study attempted to replicate whether a bias in probabilistic reasoning, or ‘jumping to conclusions’(JTC) bias is associated with being a sibling of a patient with schizophrenia spectrum disorder; and if so, whether this association is contingent on subthreshold delusional ideation.
MethodsData were derived from the EUGEI project, a 25-centre, 15-country effort to study psychosis spectrum disorder. The current analyses included 1261 patients with schizophrenia spectrum disorder, 1282 siblings of patients and 1525 healthy comparison subjects, recruited in Spain (five centres), Turkey (three centres) and Serbia (one centre). The beads task was used to assess JTC bias. Lifetime experience of delusional ideation and hallucinatory experiences was assessed using the Community Assessment of Psychic Experiences. General cognitive abilities were taken into account in the analyses.
ResultsJTC bias was positively associated not only with patient status but also with sibling status [adjusted relative risk (aRR) ratio : 4.23 CI 95% 3.46–5.17 for siblings and aRR: 5.07 CI 95% 4.13–6.23 for patients]. The association between JTC bias and sibling status was stronger in those with higher levels of delusional ideation (aRR interaction in siblings: 3.77 CI 95% 1.67–8.51, and in patients: 2.15 CI 95% 0.94–4.92). The association between JTC bias and sibling status was not stronger in those with higher levels of hallucinatory experiences.
ConclusionsThese findings replicate earlier findings that JTC bias is associated with familial liability for psychosis and that this is contingent on the degree of delusional ideation but not hallucinations.
Replicated evidence that endophenotypic expression of schizophrenia polygenic risk is greater in healthy siblings of patients compared to controls, suggesting gene–environment interaction. The EUGEI study
- Jim van Os, Lotta-Katrin Pries, Philippe Delespaul, Gunter Kenis, Jurjen J. Luykx, Bochao D. Lin, Alexander L. Richards, Berna Akdede, Tolga Binbay, Vesile Altınyazar, Berna Yalınçetin, Güvem Gümüş-Akay, Burçin Cihan, Haldun Soygür, Halis Ulaş, Eylem Şahin Cankurtaran, Semra Ulusoy Kaymak, Marina M. Mihaljevic, Sanja Andric Petrovic, Tijana Mirjanic, Miguel Bernardo, Bibiana Cabrera, Julio Bobes, Pilar A. Saiz, María Paz García-Portilla, Julio Sanjuan, Eduardo J. Aguilar, José Luis Santos, Estela Jiménez-López, Manuel Arrojo, Angel Carracedo, Gonzalo López, Javier González-Peñas, Mara Parellada, Nadja P. Maric, Cem Atbaşoğlu, Alp Ucok, Köksal Alptekin, Meram Can Saka, Genetic Risk and Outcome Investigators (GROUP), Celso Arango, Michael O'Donovan, Bart P. F. Rutten, Sinan Guloksuz
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- Journal:
- Psychological Medicine / Volume 50 / Issue 11 / August 2020
- Published online by Cambridge University Press:
- 15 August 2019, pp. 1884-1897
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Background
First-degree relatives of patients with psychotic disorder have higher levels of polygenic risk (PRS) for schizophrenia and higher levels of intermediate phenotypes.
MethodsWe conducted, using two different samples for discovery (n = 336 controls and 649 siblings of patients with psychotic disorder) and replication (n = 1208 controls and 1106 siblings), an analysis of association between PRS on the one hand and psychopathological and cognitive intermediate phenotypes of schizophrenia on the other in a sample at average genetic risk (healthy controls) and a sample at higher than average risk (healthy siblings of patients). Two subthreshold psychosis phenotypes, as well as a standardised measure of cognitive ability, based on a short version of the WAIS-III short form, were used. In addition, a measure of jumping to conclusion bias (replication sample only) was tested for association with PRS.
ResultsIn both discovery and replication sample, evidence for an association between PRS and subthreshold psychosis phenotypes was observed in the relatives of patients, whereas in the controls no association was observed. Jumping to conclusion bias was similarly only associated with PRS in the sibling group. Cognitive ability was weakly negatively and non-significantly associated with PRS in both the sibling and the control group.
ConclusionsThe degree of endophenotypic expression of schizophrenia polygenic risk depends on having a sibling with psychotic disorder, suggestive of underlying gene–environment interaction. Cognitive biases may better index genetic risk of disorder than traditional measures of neurocognition, which instead may reflect the population distribution of cognitive ability impacting the prognosis of psychotic disorder.
Summary of the Snowmastodon Project Special Volume A high-elevation, multi-proxy biotic and environmental record of MIS 6–4 from the Ziegler Reservoir fossil site, Snowmass Village, Colorado, USA
- Ian M. Miller, Jeffrey S. Pigati, R. Scott Anderson, Kirk R. Johnson, Shannon A. Mahan, Thomas A. Ager, Richard G. Baker, Maarten Blaauw, Jordon Bright, Peter M. Brown, Bruce Bryant, Zachary T. Calamari, Paul E. Carrara, Michael D. Cherney, John R. Demboski, Scott A. Elias, Daniel C. Fisher, Harrison J. Gray, Danielle R. Haskett, Jeffrey S. Honke, Stephen T. Jackson, Gonzalo Jiménez-Moreno, Douglas Kline, Eric M. Leonard, Nathaniel A. Lifton, Carol Lucking, H. Gregory McDonald, Dane M. Miller, Daniel R. Muhs, Stephen E. Nash, Cody Newton, James B. Paces, Lesley Petrie, Mitchell A. Plummer, David F. Porinchu, Adam N. Rountrey, Eric Scott, Joseph J.W. Sertich, Saxon E. Sharpe, Gary L. Skipp, Laura E. Strickland, Richard K. Stucky, Robert S. Thompson, Jim Wilson
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- Journal:
- Quaternary Research / Volume 82 / Issue 3 / November 2014
- Published online by Cambridge University Press:
- 20 January 2017, pp. 618-634
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In North America, terrestrial records of biodiversity and climate change that span Marine Oxygen Isotope Stage (MIS) 5 are rare. Where found, they provide insight into how the coupling of the ocean–atmosphere system is manifested in biotic and environmental records and how the biosphere responds to climate change. In 2010–2011, construction at Ziegler Reservoir near Snowmass Village, Colorado (USA) revealed a nearly continuous, lacustrine/wetland sedimentary sequence that preserved evidence of past plant communities between ~140 and 55 ka, including all of MIS 5. At an elevation of 2705 m, the Ziegler Reservoir fossil site also contained thousands of well-preserved bones of late Pleistocene megafauna, including mastodons, mammoths, ground sloths, horses, camels, deer, bison, black bear, coyotes, and bighorn sheep. In addition, the site contained more than 26,000 bones from at least 30 species of small animals including salamanders, otters, muskrats, minks, rabbits, beavers, frogs, lizards, snakes, fish, and birds. The combination of macro- and micro-vertebrates, invertebrates, terrestrial and aquatic plant macrofossils, a detailed pollen record, and a robust, directly dated stratigraphic framework shows that high-elevation ecosystems in the Rocky Mountains of Colorado are climatically sensitive and varied dramatically throughout MIS 5.
Contributors
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- By Mark S. Aloia, Ellemarije Altena, Peter Anderer, Christopher L. Asplund, Nitin Bangera, Jeroen S. Benjamins, Daniela Berg, Bohdan Bybel, Vincenza Castronovo, Suk-tak Chan, Michael W. L. Chee, Pietro Cortelli, Michael Czisch, Joseph T. Daley, Thien Thanh Dang-Vu, Yazmín de la Garza-Neme, Lourdes DelRosso, Derk-Jan Dijk, Maria Engström, Thorleif Etgen, Bruce J. Fisch, Ariane Foret, Patrice Fort, Steffen Gais, Anne Germain, Jana Godau, Andrew L. Goertzen, William A. Gomes, Ronald M. Harper, Seung Bong Hong, Romy Hoque, Scott A. Huettel, Yuichi Inoue, Alex Iranzo, Mathieu Jaspar, Zayd Jedidi, Alejandro Jiménez-Genchi, Eun Yeon Joo, Gerhard Klösch, Karsten Krakow, Rajesh Kumar, Caroline Kussé, Hans-Peter Landolt, Helmut Laufs, Jeffrey David Lewine, Camilo Libedinsky, Michael L. Lipton, Mordechai Lorberboym, Cheng Luo, Pierre-Hervé Luppi, Paul M. Macey, Pierre Maquet, Laura Mascetti, Christelle Meyer, Sarah Moens, Vincenzo Muto, Shadreck Mzengeza, Eric Nofzinger, Takashi Nomura, Daniela Perani, Jennifer R. Ramautar, Bernd Saletu, Michael T. Saletu, Gerda Saletu-Zyhlarz, Christina Schmidt, Monika Schönauer, Richard J. Schwab, Sophie Schwartz, Keivan Shifteh, Sanjib Sinha, Victor I. Spoormaker, Ryan P. J. Stocker, A. Jon Stoessl, Diederick Stoffers, A. B. Taly, Robert Joseph Thomas, Michael J. Thorpy, Emily Urry, Jason Valerio, Ysbrand D. Van Der Werf, Gilles Vandewalle, Hans P. A. Van Dongen, Eus J. W. Van Someren, Vinod Venkatraman, Frederic von Wegner, Thomas C. Wetter, Dezhong Yao
- Edited by Eric Nofzinger, University of Pittsburgh, Pierre Maquet, Université de Liège, Belgium, Michael J. Thorpy
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- Neuroimaging of Sleep and Sleep Disorders
- Published online:
- 05 March 2013
- Print publication:
- 07 March 2013, pp viii-xii
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- By Alberto Albanese, Karine Auré, Selim R. Benbadis, Jose Biller, Matthew Bower, Francisco Cardoso, Kelvin L. Chou, Rima M. Dafer, Praveen Dayalu, Michelle M. Dompenciel, Eissa Ibrahim Al Eissa, Alberto J. Espay, Hubert H. Fernandez, Brent L. Fogel, Steven Frucht, Victor S. C. Fung, Néstor Gálvez-Jiménez, David Grabli, Era Hanspal, Claire Henchcliffe, Nelson Hwynn, Kurt A. Jellinger, Julia Johnson, Danita Jones, Daniel Kantor, Ninith Kartha, Jan Kassubek, Taranum Khan, Samuel Kim, Christine Klein, Neeraj Kumar, Roger Kurlan, Corneliu Luca, Ramon Lugo, Roneil Malkani, Giacomo Della Marca, Marcelo Merello, Henry Moore, Sarkis Morales-Vidal, Santiago Perez-Lloret, Susan Perlman, Elmar H. Pinkhardt, David E. Riley, Emmanuel Roze, Daniel S. Sa, Virgilio D. Salanga, Michael J. Schneck, Susanne A. Schneider, David Shprecher, Carlos Singer, Mark Stacy, Sylvia Stemberger, Pichet Termsarasab, Paul J. Tuite, Marie Vidailhet, Mary Vo, Ruth H. Walker, Gregor K. Wenning, Cindy Zadikoff
- Edited by Néstor Gálvez-Jiménez, Paul Tuite, University of Minnesota
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- Uncommon Causes of Movement Disorders
- Published online:
- 05 August 2011
- Print publication:
- 12 May 2011, pp ix-xii
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- By Robert Acosta, Elizabeth M. Alderman, Dan Barlev, Stephen M. Blumberg, Katherine J. Chou, Anthony J. Ciorciari, Christina M. Coyle, Ellen F. Crain, Sandra J. Cunningham, Joan Di Martino-Nardi, Nancy Dougherty, Glenn Fennelly, Sheila Fallon Friedlander, Jeffrey C. Gershel, Michael H. Gewitz, Beatrice Goilav, Michael Gorn, Waseem Hafeez, Dominic Hollman, Olga Jimenez, Carl Kaplan, Jeffrey Keller, Sergey Kunkov, Carolyn Lederman, Martin Lederman, Stephanie R. Lichten, Julie Lin, Stephen Ludwig, Svetlana Lvovich, Frank A. Maffei, Soe Mar, Robert W. Marion, Morri Markowitz, Daniel Mason, Teresa McCann, Alexandra D. McCollum, Mary Mehlman, James Meltzer, Scott Miller, Kirsten Roberts, Michael Rosenberg, Joy Samanich, David P. Sole, Preeti Venkataraman, Joshua Vova, Mark Weinblatt, Paul K. Woolf, Loren Yellin
- Edited by Ellen F. Crain, Albert Einstein College of Medicine, New York, Jeffrey C. Gershel, Albert Einstein College of Medicine, New York
- Edited in association with Sandra J. Cunningham
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- Book:
- Clinical Manual of Emergency Pediatrics
- Published online:
- 10 January 2011
- Print publication:
- 02 December 2010, pp x-xiv
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- By Amelia Evoli, Ami K. Mankodi, Ana Ferreiro, Anders Oldfors, Anne K. Lampe, Anneke J. van der Kooi, Bernard Brais, Bertrand Fontaine, Bjarne Udd, Carina Wallgren-Pettersson, Caroline A. Sewry, Carsten G. Bönnemann, Cecilia Jimenez-Mallebera, Chad Heatwole, Charles A. Thornton, Corrado Angelini, David Hilton-Jones, Doreen Fialho, Duygu Selcen, Edward J. Cupler, Emma Ciafaloni, Enrico Bertini, Eric A. Shoubridge, Eric Logigian, Erin O’Ferrall, Eugenio Mercuri, Franco Taroni, Frank L. Mastaglia, Frederic Relaix, George Karpati, Giovanni Meola, Gisèle Bonne, Hannah R. Briemberg, Hanns Lochmüller, Heinz Jungbluth, Ichizo Nishino, Jenny E. Morgan, John Day, John Vissing, John T. Kissel, Kate Bushby, Leslie Morrison, Maria J. Molnar, Marianne de Visser, Marinos C. Dalakas, Mary Kay Floeter, Mariz Vainzof, Maxwell S. Damian, Michael G. Hanna, Michael Rose, Michael Sinnreich, Michael Swash, Miranda D. Grounds, Mohammed Kian Salajegheh, Nigel G. Laing, Patrick F. Chinnery, Rabi Tawil, Rénald Gilbert, Richard Orrell, Robert C. Griggs, Roberto Massa, Saiju Jacob, Shannon L. Venance, Stefano Di Donato, Stella Mitrani-Rosenbaum, Stephen Gee, Stuart Viegas, Susan C. Brown, Tahseen Mozaffar, Tanja Taivassalo, Valeria A. Sansone, Violeta Mihaylova, Yaacov Anziska, Zohar Argov
- George Karpati, McGill University, Montréal
- Edited by David Hilton-Jones, Kate Bushby, Robert C. Griggs
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- Disorders of Voluntary Muscle
- Published online:
- 26 February 2010
- Print publication:
- 21 January 2010, pp vii-x
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21 - Managing wolf–human conflict in the northwestern United States
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- By Edward E. Bangs, US Fish and Wildlife Service, USA, Joseph A. Fontaine, US Fish and Wildlife Service, USA, Michael D. Jimenez, US Fish and Wildlife Service, USA, Thomas J. Meier, US Fish and Wildlife Service, USA, Elizabeth H. Bradley, University of Montana, USA, Carter C. Niemeyer, US Fish and Wildlife Service, USA, Douglas W. Smith, National Park Service, USA, Curt M. Mack, Nez Percé Tribe, USA, Val Asher, Turner Endangered Species Fund, USA, John K. Oakleaf, US Fish and Wildlife Service, USA
- Edited by Rosie Woodroffe, University of California, Davis, Simon Thirgood, Zoological Society, Frankfurt, Alan Rabinowitz, Wildlife Conservation Society, New York
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- People and Wildlife, Conflict or Co-existence?
- Published online:
- 23 November 2009
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- 25 August 2005, pp 340-356
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Summary
INTRODUCTION
The grey wolf (Canis lupus) is the most widely distributed large carnivore in the northern hemisphere (Nowak 1995) and has a reputation for killing livestock and competing with human hunters for wild ungulates (Young 1944; Fritts et al. 2003). Wolves rarely threaten human safety, but many people still fear them. In the western USA, widespread extirpation of ungulates by colonizing settlers, wolf depredation on livestock and negative public attitudes towards wolves resulted in extirpation of wolf populations by 1930 (Mech 1970; McIntyre 1995). By 1970, mule deer (Odocoileus hemionus), white-tailed deer (O. virginianus), elk (Cervus elaphus), moose (Alces alces) and bighorn sheep (Ovis canadensis) populations had been restored throughout the western USA while bison (Bison bison) were recovered only in Yellowstone National Park. However, grey wolves were still persecuted. In 1974, grey wolves were protected and managed by the US Fish and Wildlife Service under the federal Endangered Species Act of 1973.
In 1986, the first recorded den in the western USA in over 50 years was established in Glacier National Park by wolves that naturally dispersed from Canada (Ream et al. 1989). Restoration of wolves in that region emphasized legal protection and building local public tolerance. Wolves from Canada were reintroduced to central Idaho and Yellowstone National Park in 1995 and 1996 to accelerate restoration (Bangs and Fritts 1996; Fritts et al. 1997). The Northern Rocky Mountains wolf population grew from 10 wolves in 1987 to 663 wolves by 2003 (US Fish and Wildlife Service et al. 2003) (Fig. 21.1, Table 21.1).