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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.
Prevalence and 1-year incidence of HIV-associated neurocognitive disorder (HAND) in adults aged ≥50 years attending standard HIV clinical care in Kilimanjaro, Tanzania
- Aidan Flatt, Tom Gentry, Johanna Kellett-Wright, Patrick Eaton, Marcella Joseph, Sarah Urasa, William Howlett, Marieke Dekker, Aloyce Kisoli, Jane Rogathe, Lindsay Henderson, Thomas Lewis, Jessica Thornton, Judith McCartney, Vanessa Yarwood, Charlotte Irwin, Elizabeta B. Mukaetova-Ladinska, Rufus Akinyemi, William K. Gray, Richard W. Walker, Catherine L. Dotchin, Andrew-Leon S. Quaker, Philip C. Makupa, Stella-Maria Paddick
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- Journal:
- International Psychogeriatrics / Volume 35 / Issue 7 / July 2023
- Published online by Cambridge University Press:
- 24 March 2021, pp. 339-350
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Objectives:
HIV-associated neurocognitive disorders (HANDs) are prevalent in older people living with HIV (PLWH) worldwide. HAND prevalence and incidence studies of the newly emergent population of combination antiretroviral therapy (cART)-treated older PLWH in sub-Saharan Africa are currently lacking. We aimed to estimate HAND prevalence and incidence using robust measures in stable, cART-treated older adults under long-term follow-up in Tanzania and report cognitive comorbidities.
Design:Longitudinal study
Participants:A systematic sample of consenting HIV-positive adults aged ≥50 years attending routine clinical care at an HIV Care and Treatment Centre during March–May 2016 and followed up March–May 2017.
Measurements:HAND by consensus panel Frascati criteria based on detailed locally normed low-literacy neuropsychological battery, structured neuropsychiatric clinical assessment, and collateral history. Demographic and etiological factors by self-report and clinical records.
Results:In this cohort (n = 253, 72.3% female, median age 57), HAND prevalence was 47.0% (95% CI 40.9–53.2, n = 119) despite well-managed HIV disease (Mn CD4 516 (98-1719), 95.5% on cART). Of these, 64 (25.3%) were asymptomatic neurocognitive impairment, 46 (18.2%) mild neurocognitive disorder, and 9 (3.6%) HIV-associated dementia. One-year incidence was high (37.2%, 95% CI 25.9 to 51.8), but some reversibility (17.6%, 95% CI 10.0–28.6 n = 16) was observed.
Conclusions:HAND appear highly prevalent in older PLWH in this setting, where demographic profile differs markedly to high-income cohorts, and comorbidities are frequent. Incidence and reversibility also appear high. Future studies should focus on etiologies and potentially reversible factors in this setting.
Contributors
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- By Maricela Alarcón, Laura A. Baker, Trygve Bakken, Serena Bezdjian, Andrew W. Bergen, Laura J. Bierut, Andrew C. Chen, C. Robert Cloninger, David W. Craig, Anibal Cravchik, Raymond R. Crowe, Carlos Cruchaga, Joseph F. Cubells, Marcella Devoto, Stephen H. Dinwiddie, Howard J. Edenberg, Josephine Elia, Craig A. Erickson, Thomas V. Fernandez, Xiaowu Gai, Elliot Gershon, Daniel H. Geschwind, Alison M. Goate, Hugh M. D. Gurling, Hakon Hakonarson, Sarah M. Hartz, Akiko Hayashi-Takagi, Jinger Hoop, Hanna Jaaro-Peled, Atsushi Kamiya, John S. K. Kauwe, Walter H. Kaye, John R. Kelsoe, Karestan C. Koenen, Mary Jeanne Kreek, Francesca Lantieri, James F. Leckman, Ondrej Libiger, Falk W. Lohoff, Michael J. Lyons, Christopher J. McDougle, Andrew McQuillin, Kathleen Ries Merikangas, Maria G. Motlagh, Pablo R. Moya, Dennis L. Murphy, Eric J. Nestler, Alexander B. Niculescu, David A. Nielsen, Khendra I. Peay, Bernice Porjesz, James B. Potash, R. Arlen Price, Dmitri Proudnikov, Adrian Raine, Madhavi Rangaswamy, William Renthal, Akira Sawa, Nicholas J. Schork, Saurav Seshadri, Shelley D. Smith, Wanli W. Smith, Toshinobu Takeda, Ardesheer Talati, Yi-Lang Tang, Kiara Timpano, Ali Torkamani, Catherine Tuvblad, Myrna M. Weissman, Jens R. Wendland, Jennifer Wessel, Peter S. White, Vadim Yuferov, Tyler Zink
- Edited by John I. Nurnberger, Jr, Wade Berrettini, University of Pennsylvania School of Medicine
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- Book:
- Principles of Psychiatric Genetics
- Published online:
- 05 October 2012
- Print publication:
- 13 September 2012, pp vii-x
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