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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.
Characterisation of age and polarity at onset in bipolar disorder
- Janos L. Kalman, Loes M. Olde Loohuis, Annabel Vreeker, Andrew McQuillin, Eli A. Stahl, Douglas Ruderfer, Maria Grigoroiu-Serbanescu, Georgia Panagiotaropoulou, Stephan Ripke, Tim B. Bigdeli, Frederike Stein, Tina Meller, Susanne Meinert, Helena Pelin, Fabian Streit, Sergi Papiol, Mark J. Adams, Rolf Adolfsson, Kristina Adorjan, Ingrid Agartz, Sofie R. Aminoff, Heike Anderson-Schmidt, Ole A. Andreassen, Raffaella Ardau, Jean-Michel Aubry, Ceylan Balaban, Nicholas Bass, Bernhard T. Baune, Frank Bellivier, Antoni Benabarre, Susanne Bengesser, Wade H Berrettini, Marco P. Boks, Evelyn J. Bromet, Katharina Brosch, Monika Budde, William Byerley, Pablo Cervantes, Catina Chillotti, Sven Cichon, Scott R. Clark, Ashley L. Comes, Aiden Corvin, William Coryell, Nick Craddock, David W. Craig, Paul E. Croarkin, Cristiana Cruceanu, Piotr M. Czerski, Nina Dalkner, Udo Dannlowski, Franziska Degenhardt, Maria Del Zompo, J. Raymond DePaulo, Srdjan Djurovic, Howard J. Edenberg, Mariam Al Eissa, Torbjørn Elvsåshagen, Bruno Etain, Ayman H. Fanous, Frederike Fellendorf, Alessia Fiorentino, Andreas J. Forstner, Mark A. Frye, Janice M. Fullerton, Katrin Gade, Julie Garnham, Elliot Gershon, Michael Gill, Fernando S. Goes, Katherine Gordon-Smith, Paul Grof, Jose Guzman-Parra, Tim Hahn, Roland Hasler, Maria Heilbronner, Urs Heilbronner, Stephane Jamain, Esther Jimenez, Ian Jones, Lisa Jones, Lina Jonsson, Rene S. Kahn, John R. Kelsoe, James L. Kennedy, Tilo Kircher, George Kirov, Sarah Kittel-Schneider, Farah Klöhn-Saghatolislam, James A. Knowles, Thorsten M. Kranz, Trine Vik Lagerberg, Mikael Landen, William B. Lawson, Marion Leboyer, Qingqin S. Li, Mario Maj, Dolores Malaspina, Mirko Manchia, Fermin Mayoral, Susan L. McElroy, Melvin G. McInnis, Andrew M. McIntosh, Helena Medeiros, Ingrid Melle, Vihra Milanova, Philip B. Mitchell, Palmiero Monteleone, Alessio Maria Monteleone, Markus M. Nöthen, Tomas Novak, John I. Nurnberger, Niamh O'Brien, Kevin S. O'Connell, Claire O'Donovan, Michael C. O'Donovan, Nils Opel, Abigail Ortiz, Michael J. Owen, Erik Pålsson, Carlos Pato, Michele T. Pato, Joanna Pawlak, Julia-Katharina Pfarr, Claudia Pisanu, James B. Potash, Mark H Rapaport, Daniela Reich-Erkelenz, Andreas Reif, Eva Reininghaus, Jonathan Repple, Hélène Richard-Lepouriel, Marcella Rietschel, Kai Ringwald, Gloria Roberts, Guy Rouleau, Sabrina Schaupp, William A Scheftner, Simon Schmitt, Peter R. Schofield, K. Oliver Schubert, Eva C. Schulte, Barbara Schweizer, Fanny Senner, Giovanni Severino, Sally Sharp, Claire Slaney, Olav B. Smeland, Janet L. Sobell, Alessio Squassina, Pavla Stopkova, John Strauss, Alfonso Tortorella, Gustavo Turecki, Joanna Twarowska-Hauser, Marin Veldic, Eduard Vieta, John B. Vincent, Wei Xu, Clement C. Zai, Peter P. Zandi, Psychiatric Genomics Consortium (PGC) Bipolar Disorder Working Group, International Consortium on Lithium Genetics (ConLiGen), Colombia-US Cross Disorder Collaboration in Psychiatric Genetics, Arianna Di Florio, Jordan W. Smoller, Joanna M. Biernacka, Francis J. McMahon, Martin Alda, Bertram Müller-Myhsok, Nikolaos Koutsouleris, Peter Falkai, Nelson B. Freimer, Till F.M. Andlauer, Thomas G. Schulze, Roel A. Ophoff
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- Journal:
- The British Journal of Psychiatry / Volume 219 / Issue 6 / December 2021
- Published online by Cambridge University Press:
- 25 August 2021, pp. 659-669
- Print publication:
- December 2021
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Background
Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.
AimsTo examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.
MethodGenome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.
ResultsEarlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.
ConclusionsAAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.
Role of psychiatric hospitals during a pandemic: introducing the Munich Psychiatric COVID-19 Pandemic Contingency Plan
- Kristina Adorjan, Oliver Pogarell, Dorothee Streb, Frank Padberg, Christian Erdmann, Gabriele Koller, Florian Raabe, Daniela Reich-Erkelenz, Sylvia de Jonge, Karin Neumeier, Peter Zill, Karl-Walter Jauch, Thomas G. Schulze, Peter Falkai
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- Journal:
- BJPsych Open / Volume 7 / Issue 2 / March 2021
- Published online by Cambridge University Press:
- 01 February 2021, e41
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Background
Psychiatry is facing major challenges during the current coronavirus disease 2019 (COVID)-19 pandemic. These challenges involve its actual and perceived role within the medical system, in particular how psychiatric hospitals can maintain their core mission of attending to people with mental illness while at the same time providing relief to overstretched general medicine services. Although psychiatric disorders comprise the leading cause of the global burden of disease, mental healthcare has been deemphasised in the wake of the onslaught of the pandemic: to make room for emergency care, psychiatric wards have been downsized, clinics closed, psychiatric support systems discontinued and so on. To deal with this pressing issue, we developed a pandemic contingency plan with the aim to contain, decelerate and, preferably, avoid transmission of COVID-19 and to enable and maintain medical healthcare for patients with mental disorders.
AimsTo describe our plan as an example of how a psychiatric hospital can share in providing acute care in a healthcare system facing an acute and highly infectious pandemic like COVID-19 and at the same time provide support for people with mental illness, with or without a COVID-19 infection.
MethodThis was a descriptive study.
ResultsThe plan was based on the German national pandemic strategy and several legal recommendations and was implemented step by step on the basis of the local COVID-19 situation. In addition, mid- and long-term plans were developed for coping with the aftermath of the pandemic.
ConclusionsThe plan enabled the University Hospital to maintain medical healthcare for patients with mental disorders. It has offered the necessary flexibility to adapt its implementation to the first and second waves of the COVID-19 pandemic in Germany. The plan is designed to serve as an easily adaptable blueprint for psychiatric hospitals around the world.
European Goods Market Integration in the Very Long Run: From the Black Death to the First World War
- Giovanni Federico, Max-Stephan Schulze, Oliver Volckart
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- Journal:
- The Journal of Economic History / Volume 81 / Issue 1 / March 2021
- Published online by Cambridge University Press:
- 13 January 2021, pp. 276-308
- Print publication:
- March 2021
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This paper examines price convergence and changes in the efficiency of wheat markets, covering the period from the mid-fourteenth to the early twentieth century and most of Europe. The analysis is based on a new data set of prices from almost 600 markets. Unlike previous research, we find that convergence was a predominantly pre-modern phenomenon. It started in the late fifteenth century, advanced rapidly until the beginning of the seventeenth century when it temporarily stalled, resumed after the Thirty Years’ War, and accelerated after the Napoleonic Wars in response to trade liberalization. From the late 1840s, convergence petered out and turned into divergence after 1875 as policy decisions dominated technological change. Our results point to the ‘Little Divergence’ between North-Western Europe and the rest of the continent as starting about 1600. Long-term improvements in market efficiency began in the early sixteenth century, with advances over time being as uneven as in price convergence. We trace this to differential institutional change and the non-synchronous spread of modern media and systems of information transmission that affected the ability of merchants to react to news.
VP31 Searching Non-English Literature For HTA Reports May Be Unnecessary
- Lisa Schell, Elke Hausner, Lina Rodenhäuser, Oliver Assall, Anke Schulz, Wiebke Sieben, Kerstin van der Leck, Stefan Sauerland
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- Journal:
- International Journal of Technology Assessment in Health Care / Volume 35 / Issue S1 / 2019
- Published online by Cambridge University Press:
- 31 December 2019, pp. 83-84
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Introduction
Currently, the Institute for Quality and Efficiency in Health Care (IQWiG) does not restrict literature searches by language. Given limited resources, it is unclear whether the effort put into screening and translating studies published in non-English and non-German (nEnG) languages yields much new information when compared to including only English and German literature. Therefore, we aimed to analyze the impact of nEnG literature on the conclusion of IQWiG's health technology assessments (HTAs).
MethodsWe checked for seventy-two IQWiG HTAs (all non-drug intervention HTAs published until August 2018 and three additional HTAs on drugs) whether they included nEnG studies. For all HTAs including at least one nEnG study, we analyzed whether the statistical significance would have changed for any endpoint without the respective nEnG study(ies). If no endpoint was impacted by a nEnG study, we classified the study as non-relevant to the HTA's conclusion and specified a reason for this.
ResultsOf seventy-two HTAs, twenty-nine (40 percent) included a total of eighty-three nEnG publications). Three HTAs were impacted by the inclusion of altogether seven Chinese publications. For one HTA on systemic therapy, five endpoints’ conclusions were changed; for the other two HTAs, the statistical significance would have changed for one endpoint each. The remaining seventy-six publications (included in sixty-nine HTAs) were judged as non-relevant to the HTA's conclusion, the most prominent reason being “meta-analysis would have had the same result without respective study” (44 percent of nEnG publications).
ConclusionsOnly three of seventy-two HTAs (4 percent) were impacted by nEnG publications, the changes being minimal for two of these. When faced with limited time or personnel resources, searching only for English and German publications may be sufficient, especially when generalizability issues are a possible concern.
Benefits of Empire? Capital Market Integration North and South of the Alps, 1350–1800
- David Chilosi, Max-Stephan Schulze, Oliver Volckart
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- Journal:
- The Journal of Economic History / Volume 78 / Issue 3 / September 2018
- Published online by Cambridge University Press:
- 07 September 2018, pp. 637-672
- Print publication:
- September 2018
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This article addresses two questions. First, when and to what extent did capital markets integrate north and south of the Alps? Second, how mobile was capital? Analysing a unique new dataset on pre-modern urban annuities, we find that northern markets were consistently better integrated than Italian markets. Long-term integration was driven by initially peripheral places in the Netherlands and Upper Germany integrating with the rest of the Holy Roman Empire where the distance and volume of inter-urban investments grew primarily in the sixteenth century. The institutions of the Empire contributed to stronger market integration north of the Alps.
“Port Cities, Diaspora Communities and Emerging Nationalism in the Ottoman Empire: Balkan Merchants in Odessa and Their Network in the Early Nineteenth Century”
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- By Oliver Schulz, Düsseldorf University
- Edited by Adrian Jarvis, Robert Lee
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- Book:
- Trade, Migration and Urban Networks in Port Cities, c. 1640–1940
- Published by:
- Liverpool University Press
- Published online:
- 05 May 2018
- Print publication:
- 01 January 2008, pp 127-148
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Summary
Introduction and Methodological Remarks
Port cities are an interesting subject for historical studies due to their inherent cosmopolitan character, with a multitude of different communities living together as a result of foreign trade and international trading contacts. These links led not only to the exchange of goods and money but also to the migration of significant groups of people between different port cities. Odessa, in the present-day Ukraine, is a particularly attractive subject for an historical study because the migration and settlement of foreigners formed a deliberate part of Russian policy in the newly-conquered territories on the Black Sea shore in the late eighteenth century, when Catherine Ð founded the city on the spot of a former Tatar village. My interest in the topic evolved during research for a PhD thesis on the intervention of the “European Concert” in the Greek War of Independence (1826-1832). To gain a full understanding of Russian foreign policy in the Ottoman Empire in the late eighteenth and early nineteenth century, and the emergence of Greek nationalism, a number of issues had to be taken into account, including Russian southward expansion to the Black Sea, settlement and population policy in Novorossija and the subsequent role of the Greek diaspora in Odessa and its contribution to the rise of a national identity. In fact, the Greek diaspora set a pattern for other Orthodox Balkan people living under Ottoman domination. The Bulgarian merchants in Odessa in the early nineteenth century, who are unfortunately much less known and studied than their Greek “colleagues,” will receive particular attention here. Previous articles have already pointed out how the Bulgarian diaspora in the nineteenth century modelled its own national movement on the Greek experience and often even participated in the Greek national movement against the Ottomans before emancipating itself from Greek tutelage in its fight for an independent Bulgarian state.
This essay cannot examine this question in detail on the basis of extensive archival research. It seeks instead to present a synthesis of this huge subject and to develop perspectives for future research. Before exploring the topic, however, it is necessary to make some methodological remarks about the study of the history of Odessa and its communities in the nineteenth century.