11 results
Mega-analysis of association between obesity and cortical morphology in bipolar disorders: ENIGMA study in 2832 participants
- Sean R. McWhinney, Christoph Abé, Martin Alda, Francesco Benedetti, Erlend Bøen, Caterina del Mar Bonnin, Tiana Borgers, Katharina Brosch, Erick J. Canales-Rodríguez, Dara M. Cannon, Udo Dannlowski, Ana M. Diaz-Zuluaga, Lorielle M.F. Dietze, Torbjørn Elvsåshagen, Lisa T. Eyler, Janice M. Fullerton, Jose M. Goikolea, Janik Goltermann, Dominik Grotegerd, Bartholomeus C. M. Haarman, Tim Hahn, Fleur M. Howells, Martin Ingvar, Neda Jahanshad, Tilo T. J. Kircher, Axel Krug, Rayus T. Kuplicki, Mikael Landén, Hannah Lemke, Benny Liberg, Carlos Lopez-Jaramillo, Ulrik F. Malt, Fiona M. Martyn, Elena Mazza, Colm McDonald, Genevieve McPhilemy, Sandra Meier, Susanne Meinert, Tina Meller, Elisa M. T. Melloni, Philip B. Mitchell, Leila Nabulsi, Igor Nenadic, Nils Opel, Roel A. Ophoff, Bronwyn J. Overs, Julia-Katharina Pfarr, Julian A. Pineda-Zapata, Edith Pomarol-Clotet, Joaquim Raduà, Jonathan Repple, Maike Richter, Kai G. Ringwald, Gloria Roberts, Alex Ross, Raymond Salvador, Jonathan Savitz, Simon Schmitt, Peter R. Schofield, Kang Sim, Dan J. Stein, Frederike Stein, Henk S. Temmingh, Katharina Thiel, Sophia I. Thomopoulos, Neeltje E. M. van Haren, Cristian Vargas, Eduard Vieta, Annabel Vreeker, Lena Waltemate, Lakshmi N. Yatham, Christopher R. K. Ching, Ole A. Andreassen, Paul M. Thompson, Tomas Hajek, for the ENIGMA Bipolar Disorder Working Group
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- Journal:
- Psychological Medicine / Volume 53 / Issue 14 / October 2023
- Published online by Cambridge University Press:
- 27 February 2023, pp. 6743-6753
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Background:
Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.
Methods:We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.
Results:BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.
Conclusions:We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.
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.
Paternal age at childbirth and eating disorders in offspring
- K. N. Javaras, M. E. Rickert, L. M. Thornton, C. M. Peat, J. H. Baker, A. Birgegård, C. Norring, M. Landén, C. Almqvist, H. Larsson, P. Lichtenstein, C. M. Bulik, B. M. D'Onofrio
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- Journal:
- Psychological Medicine / Volume 47 / Issue 3 / February 2017
- Published online by Cambridge University Press:
- 03 November 2016, pp. 576-584
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Background
Advanced paternal age at childbirth is associated with psychiatric disorders in offspring, including schizophrenia, bipolar disorder and autism. However, few studies have investigated paternal age's relationship with eating disorders in offspring. In a large, population-based cohort, we examined the association between paternal age and offspring eating disorders, and whether that association remains after adjustment for potential confounders (e.g. parental education level) that may be related to late/early selection into fatherhood and to eating disorder incidence.
MethodData for 2 276 809 individuals born in Sweden 1979–2001 were extracted from Swedish population and healthcare registers. The authors used Cox proportional hazards models to examine the effect of paternal age on the first incidence of healthcare-recorded anorexia nervosa (AN) and all eating disorders (AED) occurring 1987–2009. Models were adjusted for sex, birth order, maternal age at childbirth, and maternal and paternal covariates including country of birth, highest education level, and lifetime psychiatric and criminal history.
ResultsEven after adjustment for covariates including maternal age, advanced paternal age was associated with increased risk, and younger paternal age with decreased risk, of AN and AED. For example, the fully adjusted hazard ratio for the 45+ years (v. the 25–29 years) paternal age category was 1.32 [95% confidence interval (CI) 1.14–1.53] for AN and 1.26 (95% CI 1.13–1.40) for AED.
ConclusionsIn this large, population-based cohort, paternal age at childbirth was positively associated with eating disorders in offspring, even after adjustment for potential confounders. Future research should further explore potential explanations for the association, including de novo mutations in the paternal germline.
Somatic, positive and negative domains of the Center for Epidemiological Studies Depression (CES-D) scale: a meta-analysis of genome-wide association studies
- A. Demirkan, J. Lahti, N. Direk, A. Viktorin, K. L. Lunetta, A. Terracciano, M. A. Nalls, T. Tanaka, K. Hek, M. Fornage, J. Wellmann, M. C. Cornelis, H. M. Ollila, L. Yu, J. A. Smith, L. C. Pilling, A. Isaacs, A. Palotie, W. V. Zhuang, A. Zonderman, J. D. Faul, A. Sutin, O. Meirelles, A. Mulas, A. Hofman, A. Uitterlinden, F. Rivadeneira, M. Perola, W. Zhao, V. Salomaa, K. Yaffe, A. I. Luik, NABEC, UKBEC, Y. Liu, J. Ding, P. Lichtenstein, M. Landén, E. Widen, D. R. Weir, D. J. Llewellyn, A. Murray, S. L. R. Kardia, J. G. Eriksson, K. Koenen, P. K. E. Magnusson, L. Ferrucci, T. H. Mosley, F. Cucca, B. A. Oostra, D. A. Bennett, T. Paunio, K. Berger, T. B. Harris, N. L. Pedersen, J. M. Murabito, H. Tiemeier, C. M. van Duijn, K. Räikkönen
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- Journal:
- Psychological Medicine / Volume 46 / Issue 8 / June 2016
- Published online by Cambridge University Press:
- 21 March 2016, pp. 1613-1623
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Background
Major depressive disorder (MDD) is moderately heritable, however genome-wide association studies (GWAS) for MDD, as well as for related continuous outcomes, have not shown consistent results. Attempts to elucidate the genetic basis of MDD may be hindered by heterogeneity in diagnosis. The Center for Epidemiological Studies Depression (CES-D) scale provides a widely used tool for measuring depressive symptoms clustered in four different domains which can be combined together into a total score but also can be analysed as separate symptom domains.
MethodWe performed a meta-analysis of GWAS of the CES-D symptom clusters. We recruited 12 cohorts with the 20- or 10-item CES-D scale (32 528 persons).
ResultsOne single nucleotide polymorphism (SNP), rs713224, located near the brain-expressed melatonin receptor (MTNR1A) gene, was associated with the somatic complaints domain of depression symptoms, with borderline genome-wide significance (pdiscovery = 3.82 × 10−8). The SNP was analysed in an additional five cohorts comprising the replication sample (6813 persons). However, the association was not consistent among the replication sample (pdiscovery+replication = 1.10 × 10−6) with evidence of heterogeneity.
ConclusionsDespite the effort to harmonize the phenotypes across cohorts and participants, our study is still underpowered to detect consistent association for depression, even by means of symptom classification. On the contrary, the SNP-based heritability and co-heritability estimation results suggest that a very minor part of the variation could be captured by GWAS, explaining the reason of sparse findings.
Impact of a cis-associated gene expression SNP on chromosome 20q11.22 on bipolar disorder susceptibility, hippocampal structure and cognitive performance
- Ming Li, Xiong-jian Luo, Mikael Landén, Sarah E. Bergen, Christina M. Hultman, Xiao Li, Wen Zhang, Yong-Gang Yao, Chen Zhang, Jiewei Liu, Manuel Mattheisen, Sven Cichon, Thomas W. Mühleisen, Franziska A. Degenhardt, Markus M. Nöthen, Thomas G. Schulze, Maria Grigoroiu-Serbanescu, Hao Li, Chris K. Fuller, Chunhui Chen, Qi Dong, Chuansheng Chen, Stéphane Jamain, Marion Leboyer, Frank Bellivier, Bruno Etain, Jean-Pierre Kahn, Chantal Henry, Martin Preisig, Zoltán Kutalik, Enrique Castelao, Adam Wright, Philip B. Mitchell, Janice M. Fullerton, Peter R. Schofield, Grant W. Montgomery, Sarah E. Medland, Scott D. Gordon, Nicholas G. Martin, MooDS Consortium, The Swedish Bipolar Study Group, Marcella Rietschel, Chunyu Liu, Joel E. Kleinman, Thomas M. Hyde, Daniel R. Weinberger, Bing Su
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- Journal:
- The British Journal of Psychiatry / Volume 208 / Issue 2 / February 2016
- Published online by Cambridge University Press:
- 02 January 2018, pp. 128-137
- Print publication:
- February 2016
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Background
Bipolar disorder is a highly heritable polygenic disorder. Recent enrichment analyses suggest that there may be true risk variants for bipolar disorder in the expression quantitative trait loci (eQTL) in the brain.
AimsWe sought to assess the impact of eQTL variants on bipolar disorder risk by combining data from both bipolar disorder genome-wide association studies (GWAS) and brain eQTL.
MethodTo detect single nucleotide polymorphisms (SNPs) that influence expression levels of genes associated with bipolar disorder, we jointly analysed data from a bipolar disorder GWAS (7481 cases and 9250 controls) and a genome-wide brain (cortical) eQTL (193 healthy controls) using a Bayesian statistical method, with independent follow-up replications. The identified risk SNP was then further tested for association with hippocampal volume (n = 5775) and cognitive performance (n = 342) among healthy individuals.
ResultsIntegrative analysis revealed a significant association between a brain eQTL rs6088662 on chromosome 20q11.22 and bipolar disorder (log Bayes factor = 5.48; bipolar disorder P = 5.85×10–5). Follow-up studies across multiple independent samples confirmed the association of the risk SNP (rs6088662) with gene expression and bipolar disorder susceptibility (P = 3.54×10–8). Further exploratory analysis revealed that rs6088662 is also associated with hippocampal volume and cognitive performance in healthy individuals.
ConclusionsOur findings suggest that 20q11.22 is likely a risk region for bipolar disorder; they also highlight the informative value of integrating functional annotation of genetic variants for gene expression in advancing our understanding of the biological basis underlying complex disorders, such as bipolar disorder.
A case-control study of risk factors for death from 2009 pandemic influenza A(H1N1): is American Indian racial status an independent risk factor?
- T. W. HENNESSY, D. BRUDEN, L. CASTRODALE, K. KOMATSU, L. M. ERHART, D. THOMPSON, K. BRADLEY, D. R. O'LEARY, J. McLAUGHLIN, M. LANDEN, the Investigative Team
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- Journal:
- Epidemiology & Infection / Volume 144 / Issue 2 / January 2016
- Published online by Cambridge University Press:
- 29 June 2015, pp. 315-324
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Historically, American Indian/Alaska Native (AI/AN) populations have suffered excess morbidity and mortality from influenza. We investigated the risk factors for death from 2009 pandemic influenza A(H1N1) in persons residing in five states with substantial AI/AN populations. We conducted a case-control investigation using pandemic influenza fatalities from 2009 in Alaska, Arizona, New Mexico, Oklahoma and Wyoming. Controls were outpatients with influenza. We reviewed medical records and interviewed case proxies and controls. We used multiple imputation to predict missing data and multivariable conditional logistic regression to determine risk factors. We included 145 fatal cases and 236 controls; 22% of cases were AI/AN. Risk factors (P < 0·05) included: older age [adjusted matched odds ratio (mOR) 3·2, for >45 years vs. <18 years], pre-existing medical conditions (mOR 7·1), smoking (mOR 3·0), delayed receipt of antivirals (mOR 6·5), and barriers to healthcare access (mOR 5·3). AI/AN race was not significantly associated with death. The increased influenza mortality in AI/AN individuals was due to factors other than racial status. Prevention of influenza deaths should focus on modifiable factors (smoking, early antiviral use, access to care) and identifying high-risk persons for immunization and prompt medical attention.
A newly discovered wildlife migration in Namibia and Botswana is the longest in Africa
- R. Naidoo, M. J. Chase, P. Beytell, P. Du Preez, K. Landen, G. Stuart-Hill, R. Taylor
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Migrations of most animal taxa are declining as a result of anthropogenic pressures and land-use transformation. Here, we document and characterize a previously unknown multi-country migration of Burchell's zebra Equus quagga that is the longest of all recorded large mammal migrations in Africa. Our data from eight adult female zebras collared on the border of Namibia and Botswana show that in December 2012 all individuals crossed the Chobe River and moved due south to Nxai Pan National Park in Botswana, where they spent a mean duration of 10 weeks before returning, less directly, to their dry season floodplain habitat. The same southward movements were also observed in December 2013. Nxai Pan appeared to have similar environmental conditions to several possible alternative wet season destinations that were closer to the dry season habitat on the Chobe River, and water availability, but not habitat or vegetation biomass, was associated with higher-use areas along the migratory pathway. These results suggest a genetic and/or cultural basis for the choice of migration destination, rather than an environmental one. Regardless of the cause, the round-trip, straight-line migration distance of 500 km is greater than that covered by wildebeest Connochaetes taurinus during their well-known seasonal journey in the Serengeti ecosystem. It merits conservation attention, given the decline of large-scale ecological processes such as animal migrations.
Observation of amplification of light by Langmuir waves and its saturation on the electron kinetic timescale
- R. K. KIRKWOOD, Y. PING, S. C. WILKS, N. MEEZAN, P. MICHEL, E. WILLIAMS, D. CLARK, L. SUTER, O. LANDEN, N. J. FISCH, E. J. VALEO, V. MALKIN, D. TURNBULL, S. SUCKEWER, J. WURTELE, T. L. WANG, S. F. MARTINS, C. JOSHI, L. YIN, B. J. ALBRIGHT, H. A. ROSE, K. J. BOWERS
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- Journal:
- Journal of Plasma Physics / Volume 77 / Issue 4 / August 2011
- Published online by Cambridge University Press:
- 21 December 2010, pp. 521-528
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Experiments demonstrate the ~77× amplification of 0.5 to 3.5-ps pulses of seed light by interaction with Langmuir waves in a low density (1.2 × 1019 cm−3) plasma produced by a 1-ns, 230-J, 1054-nm pump beam with 1.2 × 1014 W/cm2 intensity. The waves are strongly damped (kλD = 0.38, Te = 244 eV) and grow over a ~ 1 mm length, similar to what is experienced by scattered light when it interacts with crossing beams as it exits an ignition target. The amplification reduces when the seed intensity increases above ~1 × 1011 W/cm2, indicating that saturation of the plasma waves on the electron kinetic time scale (<0.5 ps) limits the scatter to ~1% of the available pump energy. The observations are in agreement with 2D PIC simulations in this case.
Time-resolved X-ray spectroscopy of deeply buried tracer layers as a density and temperature diagnostic for the fast ignitor
- J. A. Koch, C. A. Back, C. Brown, K. Estabrook, B. A. Hammel, S. P. Hatchett, M. H. Key, J. D. Kilkenny, O. L. Landen, R. W. Lee, J. D. Moody, A. A. Offenberger, D. Pennington, M. D. Perry, M. Tabak, V. Yanovsky, R. J. Wallace, K. B. Wharton, S. C. Wilks
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- Journal:
- Laser and Particle Beams / Volume 16 / Issue 1 / March 1998
- Published online by Cambridge University Press:
- 16 October 2009, pp. 225-232
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The fast ignitor concept for inertial confinement fusion relies on the generation of hot electrons, produced by a short-pulse ultrahigh intensity laser, which propagate through high-density plasma to deposit their energy in the compressed fuel core and heat it to ignition. In preliminary experiments designed to investigate deep heating of high-density matter, we used a 20 joule, 0.5–30 ps laser to heat solid targets, and used emission spectroscopy to measure plasma temperatures and densities achieved at large depths (2–20 microns) away from the initial target surface. The targets consisted of an Al tracer layer buried within a massive CH slab; H-like and He-like line emission was then used to diagnose plasma conditions. We observe spectra from tracer layers buried up to 20 microns deep, measure emission durations of up to 200 ps, measure plasma temperatures up to Te=650 eV, and measure electron densities above 1023 cm−3. Analysis is in progress, but the data are in reasonable agreement with heating simulations when space-charge induced inhibition is included in hot-electron transport, and this supports the conclusion that the deep heating is initiated by hot electrons.