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4 Evaluating Plasma GFAP for the Detection of Alzheimer’s Disease Dementia
- Madeline Ally, Henrik Zetterberg, Kaj Blennow, Nicholas J. Ashton, Thomas K. Karikari, Hugo Aparicio, Michael A. Sugarman, Brandon Frank, Yorghos Tripodis, Ann C. McKee, Thor D. Stein, Brett Martin, Joseph N. Palmisano, Eric G. Steinberg, Irene Simkina, Lindsay Farrer, Gyungah Jun, Katherine W. Turk, Andrew E. Budson, Maureen K. O’Connor, Rhoda Au, Wei Qiao Qiu, Lee E. Goldstein, Ronald Killiany, Neil W. Kowall, Robert A. Stern, Jesse Mez, Michael L. Alosco
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 408-409
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Objective:
Blood-based biomarkers represent a scalable and accessible approach for the detection and monitoring of Alzheimer’s disease (AD). Plasma phosphorylated tau (p-tau) and neurofilament light (NfL) are validated biomarkers for the detection of tau and neurodegenerative brain changes in AD, respectively. There is now emphasis to expand beyond these markers to detect and provide insight into the pathophysiological processes of AD. To this end, a reactive astrocytic marker, namely plasma glial fibrillary acidic protein (GFAP), has been of interest. Yet, little is known about the relationship between plasma GFAP and AD. Here, we examined the association between plasma GFAP, diagnostic status, and neuropsychological test performance. Diagnostic accuracy of plasma GFAP was compared with plasma measures of p-tau181 and NfL.
Participants and Methods:This sample included 567 participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC) Longitudinal Clinical Core Registry, including individuals with normal cognition (n=234), mild cognitive impairment (MCI) (n=180), and AD dementia (n=153). The sample included all participants who had a blood draw. Participants completed a comprehensive neuropsychological battery (sample sizes across tests varied due to missingness). Diagnoses were adjudicated during multidisciplinary diagnostic consensus conferences. Plasma samples were analyzed using the Simoa platform. Binary logistic regression analyses tested the association between GFAP levels and diagnostic status (i.e., cognitively impaired due to AD versus unimpaired), controlling for age, sex, race, education, and APOE e4 status. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate diagnostic groups compared with plasma p-tau181 and NfL. Linear regression models tested the association between plasma GFAP and neuropsychological test performance, accounting for the above covariates.
Results:The mean (SD) age of the sample was 74.34 (7.54), 319 (56.3%) were female, 75 (13.2%) were Black, and 223 (39.3%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having cognitive impairment (GFAP z-score transformed: OR=2.233, 95% CI [1.609, 3.099], p<0.001; non-z-transformed: OR=1.004, 95% CI [1.002, 1.006], p<0.001). ROC analyses, comprising of GFAP and the above covariates, showed plasma GFAP discriminated the cognitively impaired from unimpaired (AUC=0.75) and was similar, but slightly superior, to plasma p-tau181 (AUC=0.74) and plasma NfL (AUC=0.74). A joint panel of the plasma markers had greatest discrimination accuracy (AUC=0.76). Linear regression analyses showed that higher GFAP levels were associated with worse performance on neuropsychological tests assessing global cognition, attention, executive functioning, episodic memory, and language abilities (ps<0.001) as well as higher CDR Sum of Boxes (p<0.001).
Conclusions:Higher plasma GFAP levels differentiated participants with cognitive impairment from those with normal cognition and were associated with worse performance on all neuropsychological tests assessed. GFAP had similar accuracy in detecting those with cognitive impairment compared with p-tau181 and NfL, however, a panel of all three biomarkers was optimal. These results support the utility of plasma GFAP in AD detection and suggest the pathological processes it represents might play an integral role in the pathogenesis of AD.
5 Antemortem Plasma GFAP Predicts Alzheimer’s Disease Neuropathological Changes
- Madeline Ally, Henrik Zetterberg, Kaj Blennow, Nicholas J. Ashton, Thomas K. Karikari, Hugo Aparicio, Michael A. Sugarman, Brandon Frank, Yorghos Tripodis, Brett Martin, Joseph N. Palmisano, Eric G. Steinberg, Irene Simkina, Lindsay Farrer, Gyungah Jun, Katherine W. Turk, Andrew E. Budson, Maureen K. O’Connor, Rhoda Au, Wei Qiao Qiu, Lee E. Goldstein, Ronald Killiany, Neil W. Kowall, Robert A. Stern, Jesse Mez, Bertran R. Huber, Ann C. McKee, Thor D. Stein, Michael L. Alosco
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- Journal:
- Journal of the International Neuropsychological Society / Volume 29 / Issue s1 / November 2023
- Published online by Cambridge University Press:
- 21 December 2023, pp. 409-410
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Objective:
Blood-based biomarkers offer a more feasible alternative to Alzheimer’s disease (AD) detection, management, and study of disease mechanisms than current in vivo measures. Given their novelty, these plasma biomarkers must be assessed against postmortem neuropathological outcomes for validation. Research has shown utility in plasma markers of the proposed AT(N) framework, however recent studies have stressed the importance of expanding this framework to include other pathways. There is promising data supporting the usefulness of plasma glial fibrillary acidic protein (GFAP) in AD, but GFAP-to-autopsy studies are limited. Here, we tested the association between plasma GFAP and AD-related neuropathological outcomes in participants from the Boston University (BU) Alzheimer’s Disease Research Center (ADRC).
Participants and Methods:This sample included 45 participants from the BU ADRC who had a plasma sample within 5 years of death and donated their brain for neuropathological examination. Most recent plasma samples were analyzed using the Simoa platform. Neuropathological examinations followed the National Alzheimer’s Coordinating Center procedures and diagnostic criteria. The NIA-Reagan Institute criteria were used for the neuropathological diagnosis of AD. Measures of GFAP were log-transformed. Binary logistic regression analyses tested the association between GFAP and autopsy-confirmed AD status, as well as with semi-quantitative ratings of regional atrophy (none/mild versus moderate/severe) using binary logistic regression. Ordinal logistic regression analyses tested the association between plasma GFAP and Braak stage and CERAD neuritic plaque score. Area under the curve (AUC) statistics from receiver operating characteristics (ROC) using predicted probabilities from binary logistic regression examined the ability of plasma GFAP to discriminate autopsy-confirmed AD status. All analyses controlled for sex, age at death, years between last blood draw and death, and APOE e4 status.
Results:Of the 45 brain donors, 29 (64.4%) had autopsy-confirmed AD. The mean (SD) age of the sample at the time of blood draw was 80.76 (8.58) and there were 2.80 (1.16) years between the last blood draw and death. The sample included 20 (44.4%) females, 41 (91.1%) were White, and 20 (44.4%) were APOE e4 carriers. Higher GFAP concentrations were associated with increased odds for having autopsy-confirmed AD (OR=14.12, 95% CI [2.00, 99.88], p=0.008). ROC analysis showed plasma GFAP accurately discriminated those with and without autopsy-confirmed AD on its own (AUC=0.75) and strengthened as the above covariates were added to the model (AUC=0.81). Increases in GFAP levels corresponded to increases in Braak stage (OR=2.39, 95% CI [0.71-4.07], p=0.005), but not CERAD ratings (OR=1.24, 95% CI [0.004, 2.49], p=0.051). Higher GFAP levels were associated with greater temporal lobe atrophy (OR=10.27, 95% CI [1.53,69.15], p=0.017), but this was not observed with any other regions.
Conclusions:The current results show that antemortem plasma GFAP is associated with non-specific AD neuropathological changes at autopsy. Plasma GFAP could be a useful and practical biomarker for assisting in the detection of AD-related changes, as well as for study of disease mechanisms.
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.
Antarctic ice sheet response to sudden and sustained ice-shelf collapse (ABUMIP)
- Sainan Sun, Frank Pattyn, Erika G. Simon, Torsten Albrecht, Stephen Cornford, Reinhard Calov, Christophe Dumas, Fabien Gillet-Chaulet, Heiko Goelzer, Nicholas R. Golledge, Ralf Greve, Matthew J. Hoffman, Angelika Humbert, Elise Kazmierczak, Thomas Kleiner, Gunter R. Leguy, William H. Lipscomb, Daniel Martin, Mathieu Morlighem, Sophie Nowicki, David Pollard, Stephen Price, Aurélien Quiquet, Hélène Seroussi, Tanja Schlemm, Johannes Sutter, Roderik S. W. van de Wal, Ricarda Winkelmann, Tong Zhang
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- Journal:
- Journal of Glaciology / Volume 66 / Issue 260 / December 2020
- Published online by Cambridge University Press:
- 14 September 2020, pp. 891-904
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Antarctica's ice shelves modulate the grounded ice flow, and weakening of ice shelves due to climate forcing will decrease their ‘buttressing’ effect, causing a response in the grounded ice. While the processes governing ice-shelf weakening are complex, uncertainties in the response of the grounded ice sheet are also difficult to assess. The Antarctic BUttressing Model Intercomparison Project (ABUMIP) compares ice-sheet model responses to decrease in buttressing by investigating the ‘end-member’ scenario of total and sustained loss of ice shelves. Although unrealistic, this scenario enables gauging the sensitivity of an ensemble of 15 ice-sheet models to a total loss of buttressing, hence exhibiting the full potential of marine ice-sheet instability. All models predict that this scenario leads to multi-metre (1–12 m) sea-level rise over 500 years from present day. West Antarctic ice sheet collapse alone leads to a 1.91–5.08 m sea-level rise due to the marine ice-sheet instability. Mass loss rates are a strong function of the sliding/friction law, with plastic laws cause a further destabilization of the Aurora and Wilkes Subglacial Basins, East Antarctica. Improvements to marine ice-sheet models have greatly reduced variability between modelled ice-sheet responses to extreme ice-shelf loss, e.g. compared to the SeaRISE assessments.
Genome-wide association study of pathological gambling
- M. Lang, T. Leménager, F. Streit, M. Fauth-Bühler, J. Frank, D. Juraeva, S.H. Witt, F. Degenhardt, A. Hofmann, S. Heilmann-Heimbach, F. Kiefer, B. Brors, H.-J. Grabe, U. John, A. Bischof, G. Bischof, U. Völker, G. Homuth, M. Beutel, P.A. Lind, S.E. Medland, W.S. Slutske, N.G. Martin, H. Völzke, M.M. Nöthen, C. Meyer, H.-J. Rumpf, F.M. Wurst, M. Rietschel, K.F. Mann
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- Journal:
- European Psychiatry / Volume 36 / August 2016
- Published online by Cambridge University Press:
- 23 March 2020, pp. 38-46
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Background
Pathological gambling is a behavioural addiction with negative economic, social, and psychological consequences. Identification of contributing genes and pathways may improve understanding of aetiology and facilitate therapy and prevention. Here, we report the first genome-wide association study of pathological gambling. Our aims were to identify pathways involved in pathological gambling, and examine whether there is a genetic overlap between pathological gambling and alcohol dependence.
MethodsFour hundred and forty-five individuals with a diagnosis of pathological gambling according to the Diagnostic and Statistical Manual of Mental Disorders were recruited in Germany, and 986 controls were drawn from a German general population sample. A genome-wide association study of pathological gambling comprising single marker, gene-based, and pathway analyses, was performed. Polygenic risk scores were generated using data from a German genome-wide association study of alcohol dependence.
ResultsNo genome-wide significant association with pathological gambling was found for single markers or genes. Pathways for Huntington's disease (P-value = 6.63 × 10−3); 5′-adenosine monophosphate-activated protein kinase signalling (P-value = 9.57 × 10−3); and apoptosis (P-value = 1.75 × 10−2) were significant. Polygenic risk score analysis of the alcohol dependence dataset yielded a one-sided nominal significant P-value in subjects with pathological gambling, irrespective of comorbid alcohol dependence status.
ConclusionsThe present results accord with previous quantitative formal genetic studies which showed genetic overlap between non-substance- and substance-related addictions. Furthermore, pathway analysis suggests shared pathology between Huntington's disease and pathological gambling. This finding is consistent with previous imaging studies.
Geographic Access to Stroke Care Services in Rural Communities in Ontario, Canada
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- Moira K. Kapral, Ruth Hall, Peter Gozdyra, Amy Y.X. Yu, Albert Y. Jin, Cally Martin, Frank L. Silver, Richard H. Swartz, Douglas G. Manuel, Jiming Fang, Joan Porter, Julius Koifman, Peter C. Austin
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- Journal:
- Canadian Journal of Neurological Sciences / Volume 47 / Issue 3 / May 2020
- Published online by Cambridge University Press:
- 10 January 2020, pp. 301-308
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Background:
Optimal stroke care requires access to resources such as neuroimaging, acute revascularization, rehabilitation, and stroke prevention services, which may not be available in rural areas. We aimed to determine geographic access to stroke care for residents of rural communities in the province of Ontario, Canada.
Methods:We used the Ontario Road Network File database linked with the 2016 Ontario Acute Stroke Care Resource Inventory to estimate the proportion of people in rural communities, defined as those with a population size <10,000, who were within 30, 60, and 240 minutes of travel time by car from stroke care services, including brain imaging, thrombolysis treatment centers, stroke units, stroke prevention clinics, inpatient rehabilitation facilities, and endovascular treatment centers.
Results:Of the 1,496,262 people residing in rural communities, the majority resided within 60 minutes of driving time to a center with computed tomography (85%), thrombolysis (81%), a stroke unit (68%), a stroke prevention clinic (74%), or inpatient rehabilitation (77.0%), but a much lower proportion (32%) were within 60 minutes of driving time to a center capable of providing endovascular thrombectomy (EVT).
Conclusions:Most rural Ontario residents have appropriate geographic access to stroke services, with the exception of EVT. This information may be useful for jurisdictions seeking to optimize the regional organization of stroke care services.
Evidence of causal effect of major depression on alcohol dependence: findings from the psychiatric genomics consortium
- Renato Polimanti, Roseann E. Peterson, Jue-Sheng Ong, Stuart MacGregor, Alexis C. Edwards, Toni-Kim Clarke, Josef Frank, Zachary Gerring, Nathan A. Gillespie, Penelope A. Lind, Hermine H. Maes, Nicholas G. Martin, Hamdi Mbarek, Sarah E. Medland, Fabian Streit, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Substance Use Disorder Working Group of the Psychiatric Genomics Consortium, 23andMe Research Team, Arpana Agrawal, Howard J. Edenberg, Kenneth S. Kendler, Cathryn M. Lewis, Patrick F. Sullivan, Naomi R. Wray, Joel Gelernter, Eske M. Derks
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- Journal:
- Psychological Medicine / Volume 49 / Issue 7 / May 2019
- Published online by Cambridge University Press:
- 01 April 2019, pp. 1218-1226
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Background
Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC.
MethodsLinkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals).
ResultsPositive genetic correlation was observed between MD and AD (rgMD−AD = + 0.47, P = 6.6 × 10−10). AC-quantity showed positive genetic correlation with both AD (rgAD−AC quantity = + 0.75, P = 1.8 × 10−14) and MD (rgMD−AC quantity = + 0.14, P = 2.9 × 10−7), while there was negative correlation of AC-frequency with MD (rgMD−AC frequency = −0.17, P = 1.5 × 10−10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10−6). There was no evidence for reverse causation.
ConclusionThis study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.
Subjective cognitive decline is longitudinally associated with lower health-related quality of life
- Susanne Roehr, Tobias Luck, Alexander Pabst, Horst Bickel, Hans-Helmut König, Dagmar Lühmann, Angela Fuchs, Steffen Wolfsgruber, Birgitt Wiese, Siegfried Weyerer, Edelgard Mösch, Christian Brettschneider, Tina Mallon, Michael Pentzek, Michael Wagner, Silke Mamone, Jochen Werle, Martin Scherer, Wolfgang Maier, Frank Jessen, Steffi G. Riedel-Heller, for the AgeCoDe study group
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- Journal:
- International Psychogeriatrics / Volume 29 / Issue 12 / December 2017
- Published online by Cambridge University Press:
- 24 July 2017, pp. 1939-1950
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Background:
Subjective cognitive decline (SCD), the potentially earliest notable manifestation of preclinical Alzheimer's disease and other dementias, was consistently associated with lower quality of life in cross-sectional studies. The aim of this study was to investigate whether such an association persists longitudinally – particularly with health-related quality of life (HRQoL) in older individuals without cognitive impairment.
Methods:Data were derived from follow-up 2–6 of the prospective Germany Study on Ageing, Cognition and Dementia in Primary Care (AgeCoDe) covering a total six-year observation period. We used linear mixed effects models to estimate the effect of SCD on HRQoL measured by the EQ-5D visual analogue scale (EQ VAS).
Results:Of 1,387 cognitively unimpaired individuals aged 82.2 years (SD = 3.2) on average, 702 (50.6%) reported SCD and 230 (16.6%) with SCD-related concerns. Effect estimates of the linear mixed effects models revealed lower HRQoL in individuals with SCD (unadjusted: –3.7 points on the EQ VAS, 95%CI = –5.3 to –2.1; SE = 0.8; p < 0.001; adjusted: –2.9 points, 95%CI = –3.9 to –1.9; SE = 0.5; p < 0.001) than in individuals without SCD. The effect was most pronounced in SCD with related concerns (unadjusted: –5.4, 95%CI = –7.6 to –3.2; SE = 1.1; p < 0.001; adjusted: –4.3, 95%CI = –5.8 to –2.9, SE = 0.7; p < 0.001).
Conclusion:SCD constitutes a serious issue to older cognitively unimpaired individuals that is depicted in persisting lower levels of HRQoL beyond depressive symptoms and functional impairment. Therefore, SCD should be taken seriously in clinical practice.
Grounding-line migration in plan-view marine ice-sheet models: results of the ice2sea MISMIP3d intercomparison
- Frank Pattyn, Laura Perichon, Gaël Durand, Lionel Favier, Olivier Gagliardini, Richard C.A. Hindmarsh, Thomas Zwinger, Torsten Albrecht, Stephen Cornford, David Docquier, Johannes J. Fürst, Daniel Goldberg, G. Hilmar Gudmundsson, Angelika Humbert, Moritz Hütten, Philippe Huybrechts, Guillaume Jouvet, Thomas Kleiner, Eric Larour, Daniel Martin, Mathieu Morlighem, Anthony J. Payne, David Pollard, Martin Rückamp, Oleg Rybak, Hélène Seroussi, Malte Thoma, Nina Wilkens
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- Journal:
- Journal of Glaciology / Volume 59 / Issue 215 / 2013
- Published online by Cambridge University Press:
- 10 July 2017, pp. 410-422
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Predictions of marine ice-sheet behaviour require models able to simulate grounding-line migration. We present results of an intercomparison experiment for plan-view marine ice-sheet models. Verification is effected by comparison with approximate analytical solutions for flux across the grounding line using simplified geometrical configurations (no lateral variations, no buttressing effects from lateral drag). Perturbation experiments specifying spatial variation in basal sliding parameters permitted the evolution of curved grounding lines, generating buttressing effects. The experiments showed regions of compression and extensional flow across the grounding line, thereby invalidating the boundary layer theory. Steady-state grounding-line positions were found to be dependent on the level of physical model approximation. Resolving grounding lines requires inclusion of membrane stresses, a sufficiently small grid size (<500 m), or subgrid interpolation of the grounding line. The latter still requires nominal grid sizes of <5 km. For larger grid spacings, appropriate parameterizations for ice flux may be imposed at the grounding line, but the short-time transient behaviour is then incorrect and different from models that do not incorporate grounding-line parameterizations. The numerical error associated with predicting grounding-line motion can be reduced significantly below the errors associated with parameter ignorance and uncertainties in future scenarios.
Smutgrass (Sporobolus indicus) Control in Bahiagrass (Paspalum notatum) Pastures
- Paul Mislevy, Donn G. Shilling, Frank G. Martin, Stephan L. Hatch
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- Weed Technology / Volume 13 / Issue 3 / September 1999
- Published online by Cambridge University Press:
- 12 June 2017, pp. 571-575
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Field experiments were conducted in 1989 and 1990 to evaluate seasonal effects of herbicide application, smutgrass (Sporobolus indicus) growth stage, and herbicide rate on smutgrass control. The experimental design was a split–split plot, with season (late spring, midsummer, and fall) as the whole plot, physiological stage at application (uncut, 15-, and 30-cm regrowth) the subplot, and hexazinone rate (0.0, 0.56, 0.84, and 1.12 kg ai/ha) as the sub-subplot treatment. Whole plots were arranged in three randomized complete blocks. Smutgrass control for the mean of the hexazinone treatments (1989 and 1990) was 95%. Application of 0.56 kg/ha hexazinone during late spring, midsummer, and fall seasons provided 77, 92, and 92% smutgrass control, respectively. Generally, the influence of plant stage at time of hexazinone application had no effect (P > 0.05) on smutgrass control. At 20 d after treatment (DAT), hexazinone had injured bahiagrass (Paspalum notatum) plants by yellowing them, but the plants reverted to their usual dark green color by 40 DAT. Total nonstructural carbohydrates were lower for the 30-cm regrowth than for the uncut plants, regardless of season; however, 30-cm regrowth had little effect on smutgrass control.
Preherbicide Mowing and Herbicide Rate on Tropical Soda Apple (Solanum viarum) Control
- Paul Mislevy, J. Jeffrey Mullahey, Frank G. Martin
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- Weed Technology / Volume 13 / Issue 1 / March 1999
- Published online by Cambridge University Press:
- 12 June 2017, pp. 172-175
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Field studies were conducted in 1993–1994 and 1994–1995 to evaluate the effects of preherbicide mowing and herbicide rate on tropical soda apple (TSA) control. Mature TSA plants were mowed one, two, or three times to a 7.5-cm stubble with a 60-d interval between mowings. Triclopyr was applied at 0, 0.6, and 1.1 kg ai/ha at 375 L/ha at 207 kPa 60 d after each mowing treatment. Mowing TSA plants twice before an application of 0.6 kg ai/ha triclopyr resulted in 100% control. Tropical soda apple control (2-yr average) for the triclopyr treatment increased between one (28% control) and two (82% control) preherbicide mowings, with no additional control benefits from three mowings (84% control). In a second study, TSA control increased from 10% 60 d after a single mowing to 92% after three consecutive mowings at 60-d intervals with no herbicide. Total nonstructural carbohydrates in TSA crowns decreased from 19.1% for unclipped plants to 4.3% 60 d after three preherbicide mowings.
West Indian Dropseed/Giant Smutgrass (Sporobolus indicus var. pyramidalis) Control in Bahiagrass (Paspalum notatum) Pastures
- Paul Mislevy, Frank G. Martin, David W. Hall
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- Journal:
- Weed Technology / Volume 16 / Issue 4 / December 2002
- Published online by Cambridge University Press:
- 20 January 2017, pp. 707-711
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Field experiments were conducted in 1997 and 1998 to evaluate the effect of mowing followed by hexazinone for West Indian dropseed/giant smutgrass (Sporobolus indicus var. pyramidalis) (hereafter referred to as dropseed) control. The experimental design was a split plot, with mowing (nonmowed [mature] and 35-cm regrowth) as the whole plot and hexazinone rate (0.0 [control], 0.56, 0.84, 1.12, 1.40, and 1.68 kg ai/ha) as the subplot treatments. The application of 0.84 kg/ha hexazinone provided 94 and 81% dropseed control, 365 d after treatment (DAT) during 1997 and 1998, respectively. Increasing application rate to 1.12 kg/ha hexazinone provided 87 and 88% dropseed control, 365 DAT during 1997 and 1998, respectively. Both the 0.84 and 1.12 kg/ha rates provided the same average control (87.5%); however, the 1.12 kg/ha rate provided consistent control over years. Mowing dropseed, followed by hexazinone application at 35-cm regrowth, provided no additional control when compared with no mowing treatments. Rates of hexazinone at 1.40 and 1.68 kg/ha caused phytotoxicity to bahiagrass and increased bare soil surface area, especially 90 and 120 DAT. Phytotoxic effect on bahiagrass and on bare soil decreased 365 DAT, resulting in 75 to 80% total forage cover. Concentration and yield of total nonstructural carbohydrates were significantly lower for the mowed 35-cm regrowth treatment than for the nonmowed plants; however, even in its weakened condition this reduction had no effect on dropseed control.
Hair Cortisol and Its Association With Psychological Risk Factors for Psychiatric Disorders: A Pilot Study in Adolescent Twins
- Liz Rietschel, Fabian Streit, Gu Zhu, Kerrie McAloney, Clemens Kirschbaum, Josef Frank, Narelle K. Hansell, Margaret J. Wright, John J. McGrath, Stephanie H. Witt, Marcella Rietschel, Nicholas G. Martin
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- Journal:
- Twin Research and Human Genetics / Volume 19 / Issue 5 / October 2016
- Published online by Cambridge University Press:
- 04 July 2016, pp. 438-446
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Measuring cortisol in hair is a promising method to assess long-term alterations of the biological stress response system, and hair cortisol concentrations (HCC) may be altered in psychiatric disorders and in subjects suffering from chronic stress. However, the pattern of associations between HCC, chronic stress and mental health require clarification. Our exploratory study: (1) assessed the association between HCC and perceived stress, symptoms of depression and neuroticism, and the trait extraversion (as a control variable); and (2) made use of the twin design to estimate the genetic and environmental covariance between the variables of interest. Hair samples from 109 (74 female) subjects (age range 12–21 years, mean 15.1) including 8 monozygotic (MZ) and 21 dizygotic (DZ) twin pairs were analyzed. Perceived stress was measured with the Perceived Stress Scale and/or the Daily Life and Stressors Scale, neuroticism, and extraversion with the NEO-Five Factor Inventory or the Junior Eysenck Personality Questionnaire, and depressive symptoms with the Somatic and Psychological Health Report. We found a modest positive association between HCC and the three risk factors — perceived stress, symptoms of depression, and neuroticism (r = 0.22–0.33) — but no correlation with extraversion (-0.06). A median split revealed that the associations between HCC and risk factors were stronger (0.47–0.60) in those subjects with HCC >11.36 pg/mg. Furthermore, our results suggest that the genetic effects underlying HCC are largely shared with those that influence perceived stress, depressive symptoms, and neuroticism. These results of our proof of principle study warrant replication in a bigger sample but raise the interesting question of the direction of causation between these variables.
Twin's Birth-Order Differences in Height and Body Mass Index From Birth to Old Age: A Pooled Study of 26 Twin Cohorts Participating in the CODATwins Project
- Yoshie Yokoyama, Aline Jelenkovic, Reijo Sund, Joohon Sung, John L. Hopper, Syuichi Ooki, Kauko Heikkilä, Sari Aaltonen, Adam D. Tarnoki, David L. Tarnoki, Gonneke Willemsen, Meike Bartels, Toos C. E. M. van Beijsterveldt, Kimberly J. Saudino, Tessa L. Cutler, Tracy L. Nelson, Keith E. Whitfield, Jane Wardle, Clare H. Llewellyn, Abigail Fisher, Mingguang He, Xiaohu Ding, Morten Bjerregaard-Andersen, Henning Beck-Nielsen, Morten Sodemann, Yun-Mi Song, Sarah Yang, Kayoung Lee, Hoe-Uk Jeong, Ariel Knafo-Noam, David Mankuta, Lior Abramson, S. Alexandra Burt, Kelly L. Klump, Juan R. Ordoñana, Juan F. Sánchez-Romera, Lucia Colodro-Conde, Jennifer R. Harris, Ingunn Brandt, Thomas Sevenius Nilsen, Jeffrey M. Craig, Richard Saffery, Fuling Ji, Feng Ning, Zengchang Pang, Lise Dubois, Michel Boivin, Mara Brendgen, Ginette Dionne, Frank Vitaro, Nicholas G. Martin, Sarah E. Medland, Grant W. Montgomery, Patrik K. E. Magnusson, Nancy L. Pedersen, Anna K. Dahl Aslan, Per Tynelius, Claire M. A. Haworth, Robert Plomin, Esther Rebato, Richard J. Rose, Jack H. Goldberg, Finn Rasmussen, Yoon-Mi Hur, Thorkild I. A. Sørensen, Dorret I. Boomsma, Jaakko Kaprio, Karri Silventoinen
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- Journal:
- Twin Research and Human Genetics / Volume 19 / Issue 2 / April 2016
- Published online by Cambridge University Press:
- 09 March 2016, pp. 112-124
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We analyzed birth order differences in means and variances of height and body mass index (BMI) in monozygotic (MZ) and dizygotic (DZ) twins from infancy to old age. The data were derived from the international CODATwins database. The total number of height and BMI measures from 0.5 to 79.5 years of age was 397,466. As expected, first-born twins had greater birth weight than second-born twins. With respect to height, first-born twins were slightly taller than second-born twins in childhood. After adjusting the results for birth weight, the birth order differences decreased and were no longer statistically significant. First-born twins had greater BMI than the second-born twins over childhood and adolescence. After adjusting the results for birth weight, birth order was still associated with BMI until 12 years of age. No interaction effect between birth order and zygosity was found. Only limited evidence was found that birth order influenced variances of height or BMI. The results were similar among boys and girls and also in MZ and DZ twins. Overall, the differences in height and BMI between first- and second-born twins were modest even in early childhood, while adjustment for birth weight reduced the birth order differences but did not remove them for BMI.
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.
Contributors
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- By Mitchell Aboulafia, Frederick Adams, Marilyn McCord Adams, Robert M. Adams, Laird Addis, James W. Allard, David Allison, William P. Alston, Karl Ameriks, C. Anthony Anderson, David Leech Anderson, Lanier Anderson, Roger Ariew, David Armstrong, Denis G. Arnold, E. J. Ashworth, Margaret Atherton, Robin Attfield, Bruce Aune, Edward Wilson Averill, Jody Azzouni, Kent Bach, Andrew Bailey, Lynne Rudder Baker, Thomas R. Baldwin, Jon Barwise, George Bealer, William Bechtel, Lawrence C. Becker, Mark A. Bedau, Ernst Behler, José A. Benardete, Ermanno Bencivenga, Jan Berg, Michael Bergmann, Robert L. Bernasconi, Sven Bernecker, Bernard Berofsky, Rod Bertolet, Charles J. Beyer, Christian Beyer, Joseph Bien, Joseph Bien, Peg Birmingham, Ivan Boh, James Bohman, Daniel Bonevac, Laurence BonJour, William J. Bouwsma, Raymond D. Bradley, Myles Brand, Richard B. Brandt, Michael E. Bratman, Stephen E. Braude, Daniel Breazeale, Angela Breitenbach, Jason Bridges, David O. Brink, Gordon G. Brittan, Justin Broackes, Dan W. Brock, Aaron Bronfman, Jeffrey E. Brower, Bartosz Brozek, Anthony Brueckner, Jeffrey Bub, Lara Buchak, Otavio Bueno, Ann E. Bumpus, Robert W. Burch, John Burgess, Arthur W. Burks, Panayot Butchvarov, Robert E. Butts, Marina Bykova, Patrick Byrne, David Carr, Noël Carroll, Edward S. Casey, Victor Caston, Victor Caston, Albert Casullo, Robert L. Causey, Alan K. L. Chan, Ruth Chang, Deen K. Chatterjee, Andrew Chignell, Roderick M. Chisholm, Kelly J. Clark, E. J. Coffman, Robin Collins, Brian P. Copenhaver, John Corcoran, John Cottingham, Roger Crisp, Frederick J. Crosson, Antonio S. Cua, Phillip D. Cummins, Martin Curd, Adam Cureton, Andrew Cutrofello, Stephen Darwall, Paul Sheldon Davies, Wayne A. Davis, Timothy Joseph Day, Claudio de Almeida, Mario De Caro, Mario De Caro, John Deigh, C. F. Delaney, Daniel C. Dennett, Michael R. DePaul, Michael Detlefsen, Daniel Trent Devereux, Philip E. Devine, John M. Dillon, Martin C. Dillon, Robert DiSalle, Mary Domski, Alan Donagan, Paul Draper, Fred Dretske, Mircea Dumitru, Wilhelm Dupré, Gerald Dworkin, John Earman, Ellery Eells, Catherine Z. Elgin, Berent Enç, Ronald P. Endicott, Edward Erwin, John Etchemendy, C. Stephen Evans, Susan L. Feagin, Solomon Feferman, Richard Feldman, Arthur Fine, Maurice A. Finocchiaro, William FitzPatrick, Richard E. Flathman, Gvozden Flego, Richard Foley, Graeme Forbes, Rainer Forst, Malcolm R. Forster, Daniel Fouke, Patrick Francken, Samuel Freeman, Elizabeth Fricker, Miranda Fricker, Michael Friedman, Michael Fuerstein, Richard A. Fumerton, Alan Gabbey, Pieranna Garavaso, Daniel Garber, Jorge L. A. Garcia, Robert K. Garcia, Don Garrett, Philip Gasper, Gerald Gaus, Berys Gaut, Bernard Gert, Roger F. Gibson, Cody Gilmore, Carl Ginet, Alan H. Goldman, Alvin I. Goldman, Alfonso Gömez-Lobo, Lenn E. Goodman, Robert M. Gordon, Stefan Gosepath, Jorge J. E. Gracia, Daniel W. Graham, George A. Graham, Peter J. Graham, Richard E. Grandy, I. Grattan-Guinness, John Greco, Philip T. Grier, Nicholas Griffin, Nicholas Griffin, David A. Griffiths, Paul J. Griffiths, Stephen R. Grimm, Charles L. Griswold, Charles B. Guignon, Pete A. Y. Gunter, Dimitri Gutas, Gary Gutting, Paul Guyer, Kwame Gyekye, Oscar A. Haac, Raul Hakli, Raul Hakli, Michael Hallett, Edward C. Halper, Jean Hampton, R. James Hankinson, K. R. Hanley, Russell Hardin, Robert M. Harnish, William Harper, David Harrah, Kevin Hart, Ali Hasan, William Hasker, John Haugeland, Roger Hausheer, William Heald, Peter Heath, Richard Heck, John F. Heil, Vincent F. Hendricks, Stephen Hetherington, Francis Heylighen, Kathleen Marie Higgins, Risto Hilpinen, Harold T. Hodes, Joshua Hoffman, Alan Holland, Robert L. Holmes, Richard Holton, Brad W. Hooker, Terence E. Horgan, Tamara Horowitz, Paul Horwich, Vittorio Hösle, Paul Hoβfeld, Daniel Howard-Snyder, Frances Howard-Snyder, Anne Hudson, Deal W. Hudson, Carl A. Huffman, David L. Hull, Patricia Huntington, Thomas Hurka, Paul Hurley, Rosalind Hursthouse, Guillermo Hurtado, Ronald E. Hustwit, Sarah Hutton, Jonathan Jenkins Ichikawa, Harry A. Ide, David Ingram, Philip J. Ivanhoe, Alfred L. Ivry, Frank Jackson, Dale Jacquette, Joseph Jedwab, Richard Jeffrey, David Alan Johnson, Edward Johnson, Mark D. Jordan, Richard Joyce, Hwa Yol Jung, Robert Hillary Kane, Tomis Kapitan, Jacquelyn Ann K. Kegley, James A. Keller, Ralph Kennedy, Sergei Khoruzhii, Jaegwon Kim, Yersu Kim, Nathan L. King, Patricia Kitcher, Peter D. Klein, E. D. Klemke, Virginia Klenk, George L. Kline, Christian Klotz, Simo Knuuttila, Joseph J. Kockelmans, Konstantin Kolenda, Sebastian Tomasz Kołodziejczyk, Isaac Kramnick, Richard Kraut, Fred Kroon, Manfred Kuehn, Steven T. Kuhn, Henry E. Kyburg, John Lachs, Jennifer Lackey, Stephen E. Lahey, Andrea Lavazza, Thomas H. Leahey, Joo Heung Lee, Keith Lehrer, Dorothy Leland, Noah M. Lemos, Ernest LePore, Sarah-Jane Leslie, Isaac Levi, Andrew Levine, Alan E. Lewis, Daniel E. Little, Shu-hsien Liu, Shu-hsien Liu, Alan K. L. Chan, Brian Loar, Lawrence B. Lombard, John Longeway, Dominic McIver Lopes, Michael J. Loux, E. J. Lowe, Steven Luper, Eugene C. Luschei, William G. Lycan, David Lyons, David Macarthur, Danielle Macbeth, Scott MacDonald, Jacob L. Mackey, Louis H. Mackey, Penelope Mackie, Edward H. Madden, Penelope Maddy, G. B. Madison, Bernd Magnus, Pekka Mäkelä, Rudolf A. Makkreel, David Manley, William E. Mann (W.E.M.), Vladimir Marchenkov, Peter Markie, Jean-Pierre Marquis, Ausonio Marras, Mike W. Martin, A. P. Martinich, William L. McBride, David McCabe, Storrs McCall, Hugh J. McCann, Robert N. McCauley, John J. McDermott, Sarah McGrath, Ralph McInerny, Daniel J. McKaughan, Thomas McKay, Michael McKinsey, Brian P. McLaughlin, Ernan McMullin, Anthonie Meijers, Jack W. Meiland, William Jason Melanson, Alfred R. Mele, Joseph R. Mendola, Christopher Menzel, Michael J. Meyer, Christian B. Miller, David W. Miller, Peter Millican, Robert N. Minor, Phillip Mitsis, James A. Montmarquet, Michael S. Moore, Tim Moore, Benjamin Morison, Donald R. Morrison, Stephen J. Morse, Paul K. Moser, Alexander P. D. Mourelatos, Ian Mueller, James Bernard Murphy, Mark C. Murphy, Steven Nadler, Jan Narveson, Alan Nelson, Jerome Neu, Samuel Newlands, Kai Nielsen, Ilkka Niiniluoto, Carlos G. Noreña, Calvin G. Normore, David Fate Norton, Nikolaj Nottelmann, Donald Nute, David S. Oderberg, Steve Odin, Michael O’Rourke, Willard G. Oxtoby, Heinz Paetzold, George S. Pappas, Anthony J. Parel, Lydia Patton, R. P. Peerenboom, Francis Jeffry Pelletier, Adriaan T. Peperzak, Derk Pereboom, Jaroslav Peregrin, Glen Pettigrove, Philip Pettit, Edmund L. Pincoffs, Andrew Pinsent, Robert B. Pippin, Alvin Plantinga, Louis P. Pojman, Richard H. Popkin, John F. Post, Carl J. Posy, William J. Prior, Richard Purtill, Michael Quante, Philip L. Quinn, Philip L. Quinn, Elizabeth S. Radcliffe, Diana Raffman, Gerard Raulet, Stephen L. Read, Andrews Reath, Andrew Reisner, Nicholas Rescher, Henry S. Richardson, Robert C. Richardson, Thomas Ricketts, Wayne D. Riggs, Mark Roberts, Robert C. Roberts, Luke Robinson, Alexander Rosenberg, Gary Rosenkranz, Bernice Glatzer Rosenthal, Adina L. Roskies, William L. Rowe, T. M. Rudavsky, Michael Ruse, Bruce Russell, Lilly-Marlene Russow, Dan Ryder, R. M. Sainsbury, Joseph Salerno, Nathan Salmon, Wesley C. Salmon, Constantine Sandis, David H. Sanford, Marco Santambrogio, David Sapire, Ruth A. Saunders, Geoffrey Sayre-McCord, Charles Sayward, James P. Scanlan, Richard Schacht, Tamar Schapiro, Frederick F. Schmitt, Jerome B. Schneewind, Calvin O. Schrag, Alan D. Schrift, George F. Schumm, Jean-Loup Seban, David N. Sedley, Kenneth Seeskin, Krister Segerberg, Charlene Haddock Seigfried, Dennis M. Senchuk, James F. Sennett, William Lad Sessions, Stewart Shapiro, Tommie Shelby, Donald W. Sherburne, Christopher Shields, Roger A. Shiner, Sydney Shoemaker, Robert K. Shope, Kwong-loi Shun, Wilfried Sieg, A. John Simmons, Robert L. Simon, Marcus G. Singer, Georgette Sinkler, Walter Sinnott-Armstrong, Matti T. Sintonen, Lawrence Sklar, Brian Skyrms, Robert C. Sleigh, Michael Anthony Slote, Hans Sluga, Barry Smith, Michael Smith, Robin Smith, Robert Sokolowski, Robert C. Solomon, Marta Soniewicka, Philip Soper, Ernest Sosa, Nicholas Southwood, Paul Vincent Spade, T. L. S. Sprigge, Eric O. Springsted, George J. Stack, Rebecca Stangl, Jason Stanley, Florian Steinberger, Sören Stenlund, Christopher Stephens, James P. Sterba, Josef Stern, Matthias Steup, M. A. Stewart, Leopold Stubenberg, Edith Dudley Sulla, Frederick Suppe, Jere Paul Surber, David George Sussman, Sigrún Svavarsdóttir, Zeno G. Swijtink, Richard Swinburne, Charles C. Taliaferro, Robert B. Talisse, John Tasioulas, Paul Teller, Larry S. Temkin, Mark Textor, H. S. Thayer, Peter Thielke, Alan Thomas, Amie L. Thomasson, Katherine Thomson-Jones, Joshua C. Thurow, Vzalerie Tiberius, Terrence N. Tice, Paul Tidman, Mark C. Timmons, William Tolhurst, James E. Tomberlin, Rosemarie Tong, Lawrence Torcello, Kelly Trogdon, J. D. Trout, Robert E. Tully, Raimo Tuomela, John Turri, Martin M. Tweedale, Thomas Uebel, Jennifer Uleman, James Van Cleve, Harry van der Linden, Peter van Inwagen, Bryan W. Van Norden, René van Woudenberg, Donald Phillip Verene, Samantha Vice, Thomas Vinci, Donald Wayne Viney, Barbara Von Eckardt, Peter B. M. Vranas, Steven J. Wagner, William J. Wainwright, Paul E. Walker, Robert E. Wall, Craig Walton, Douglas Walton, Eric Watkins, Richard A. Watson, Michael V. Wedin, Rudolph H. Weingartner, Paul Weirich, Paul J. Weithman, Carl Wellman, Howard Wettstein, Samuel C. Wheeler, Stephen A. White, Jennifer Whiting, Edward R. Wierenga, Michael Williams, Fred Wilson, W. Kent Wilson, Kenneth P. Winkler, John F. Wippel, Jan Woleński, Allan B. Wolter, Nicholas P. Wolterstorff, Rega Wood, W. Jay Wood, Paul Woodruff, Alison Wylie, Gideon Yaffe, Takashi Yagisawa, Yutaka Yamamoto, Keith E. Yandell, Xiaomei Yang, Dean Zimmerman, Günter Zoller, Catherine Zuckert, Michael Zuckert, Jack A. Zupko (J.A.Z.)
- Edited by Robert Audi, University of Notre Dame, Indiana
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- The Cambridge Dictionary of Philosophy
- Published online:
- 05 August 2015
- Print publication:
- 27 April 2015, pp ix-xxx
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Consensus Statement: The National Depressive and Manic-Depressive Association Consensus Statement on the Undertreatment of Depression
- Robert M. A. Hirschfeld, Martin B. Keller, Susan Panico, Bernard S. Arons, David Barlow, Frank Davidoff, Jean Endicott, Jack Froom, Michael Goldstein, Jack M. Gorman, Don Guthrie, Richard G. Marek, Theodore A. Maurer, Roger Meyer, Katharine Phillips, Jerilyn Ross, Thomas L. Schwenk, Steven S. Sharfstein, Michael E. Thase, Richard J. Wyatt
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- CNS Spectrums / Volume 2 / Issue 2 / February 1997
- Published online by Cambridge University Press:
- 07 November 2014, pp. 39-50
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A consensus conference on the reasons for the undertreatment of depression was organized by the National Depressive and Manic Depressive Association (NDMDA) on January 17–18,1996. The target audience included health policymakers, clinicians, patients and their families, and the public at large. Six key questions were addressed: (1) Is depression undertreated in the community and in the clinic? (2) What is the economic cost to society of depression? (3) What have been the efforts in the past to redress undertreatment and how successful have they been? (4) What are the reasons for the gap between our knowledge of the diagnosis and treatment of depression and actual treatment received in this country? (5) What can we do to narrow this gap? (6) What can we do immediately to narrow this gap?
Notes on Contributors
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- By Charles Altieri, Faith Barrett, Alfred Bendixen, David Bergman, Edward Brunner, Stephen Burt, Susan Castillo Street, Michael C. Cohen, Robert Daly, Betty Booth Donohue, Jim Egan, Richard Flynn, Ed Folsom, Stephen Fredman, Frank Gado, Roger Gilbert, Rigoberto González, Nick Halpern, Jeffrey A. Hammond, Kevin J. Hayes, Matthew Hofer, Tyler Hoffman, Christoph Irmscher, Virginia Jackson, Joseph Jonghyun Jeon, John D. Kerkering, George S. Lensing, Mary Loeffelholz, Wendy Martin, Cristanne Miller, David Chioni Moore, Walton Muyumba, John Timberman Newcomb, Bob Perelman, Siobhan Phillips, Brian M. Reed, Elizabeth Renker, Eliza Richards, Reena Sastri, Robin G. Schulze, Mark Scroggins, David E. E. Sloane, Angela Sorby, Juliana Spahr, Willard Spiegelman, Lisa M. Steinman, Ernest Suarez, Joseph T. Thomas, Lesley Wheeler, David Wojahn
- Edited by Alfred Bendixen, Princeton University, New Jersey, Stephen Burt, Harvard University, Massachusetts
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- Book:
- The Cambridge History of American Poetry
- Published online:
- 05 December 2014
- Print publication:
- 27 October 2014, pp xi-xviii
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- Chapter
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