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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.
Confirmatory test of two factors and four subtypes of bipolar disorder based on lifetime psychiatric co-morbidity
- P. O. Monahan, T. Stump, W. H. Coryell, J. Harezlak, G. A. Marcoulides, H. Liu, C. M. Steeger, P. B. Mitchell, H. C. Wilcox, L. A. Hulvershorn, A. L. Glowinski, Bipolar Disorder Genome Study (BiGS) Consortium, Bipolar High Risk Study Group, P. A. Iyer-Eimerbrink, M. McInnis, J. I. Nurnberger, Jr
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- Journal:
- Psychological Medicine / Volume 45 / Issue 10 / July 2015
- Published online by Cambridge University Press:
- 31 March 2015, pp. 2181-2196
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Background
The first aim was to use confirmatory factor analysis (CFA) to test a hypothesis that two factors (internalizing and externalizing) account for lifetime co-morbid DSM-IV diagnoses among adults with bipolar I (BPI) disorder. The second aim was to use confirmatory latent class analysis (CLCA) to test the hypothesis that four clinical subtypes are detectible: pure BPI; BPI plus internalizing disorders only; BPI plus externalizing disorders only; and BPI plus internalizing and externalizing disorders.
MethodA cohort of 699 multiplex BPI families was studied, ascertained and assessed (1998–2003) by the National Institute of Mental Health Genetics Initiative Bipolar Consortium: 1156 with BPI disorder (504 adult probands; 594 first-degree relatives; and 58 more distant relatives) and 563 first-degree relatives without BPI. Best-estimate consensus DSM-IV diagnoses were based on structured interviews, family history and medical records. MPLUS software was used for CFA and CLCA.
ResultsThe two-factor CFA model fit the data very well, and could not be improved by adding or removing paths. The four-class CLCA model fit better than exploratory LCA models or post-hoc-modified CLCA models. The two factors and four classes were associated with distinctive clinical course and severity variables, adjusted for proband gender. Co-morbidity, especially more than one internalizing and/or externalizing disorder, was associated with a more severe and complicated course of illness. The four classes demonstrated significant familial aggregation, adjusted for gender and age of relatives.
ConclusionsThe BPI two-factor and four-cluster hypotheses demonstrated substantial confirmatory support. These models may be useful for subtyping BPI disorders, predicting course of illness and refining the phenotype in genetic studies.
Familial depression versus depression identified in a control group: are they the same?
- G. Winokur, W. Coryell, J. Endicott, H. Akiskal, M. Keller, J. D. Maser, M. Warshaw
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- Journal:
- Psychological Medicine / Volume 25 / Issue 4 / July 1995
- Published online by Cambridge University Press:
- 09 July 2009, pp. 797-806
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Subjects who meet the criteria for an affective syndrome possibly are aetiologically heterogeneous. An approach to this possibility involves examining affectively ill subjects obtained by different methods of ascertainment. This study compares depressed and manic subjects who are related to affectively ill probands with affectively ill subjects who were obtained from a study of a control population, and, therefore, were less likely to be familial. The subjects were identified in a large collaborative study of depression where both family members as well as controls were personally interviewed and followed up for 6 years after admission to the study. Data were obtained on subtypes of affective disorder using the Research Diagnostic Criteria and information was gathered about psychiatric hospitalizations, suicide attempts, alcoholism and psychological functioning prior to admission. Similar assessments were made for the comparison groups for the 6 year period between intake and follow-up. Relatives of bipolar I/schizoaffective manic probands were more likely to show mania than affectively ill controls or relatives of unipolar/schizoaffective depressed probands. Affectively ill controls were less likely to be hospitalized and less likely to suffer from an incapacitating depression. They were also likely to have functioned in a more healthy fashion than the affectively ill relatives of the bipolars and unipolars, in the 5 years before admission to the study. In the 6 year follow-up, both the subjects themselves and raters assessed the depressed controls as functioning better than the affectively ill relatives of the probands. Further, assessment of global adjustment during the 6 year period was worse for the relatives of affectively ill probands than for the depressed controls. Length of major depression was longer in relatives of bipolar and unipolar probands than in controls. Though all of the subjects in this study met research criteria for an affective illness, there were marked differences in the qualitative aspects of these illnesses with the relatives of affectively ill probands, who functioned less well and had longer and more severe episodes and more hospitalizations.
Do risk factors for suicidal behavior differ by affective disorder polarity?
- J. G. Fiedorowicz, A. C. Leon, M. B. Keller, D. A. Solomon, J. P. Rice, W. H. Coryell
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- Journal:
- Psychological Medicine / Volume 39 / Issue 5 / May 2009
- Published online by Cambridge University Press:
- 30 July 2008, pp. 763-771
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Background
Suicide is a leading cause of death and has been strongly associated with affective disorders. The influence of affective disorder polarity on subsequent suicide attempts or completions and any differential effect of suicide risk factors by polarity were assessed in a prospective cohort.
MethodParticipants with major affective disorders in the National Institute of Mental Health (NIMH) Collaborative Depression Study (CDS) were followed prospectively for up to 25 years. A total of 909 participants meeting prospective diagnostic criteria for major depressive and bipolar disorders were followed through 4204 mood cycles. Suicidal behavior was defined as suicide attempts or completions. Mixed-effects, grouped-time survival analysis assessed risk of suicidal behavior and differential effects of risk factors for suicidal behavior by polarity. In addition to polarity, the main effects of age, gender, hopelessness, married status, prior suicide attempts and active substance abuse were modeled, with mood cycle as the unit of analysis.
ResultsAfter controlling for age of onset, there were no differences in prior suicide attempts by polarity although bipolar participants had more prior severe attempts. During follow-up, 40 cycles ended in suicide and 384 cycles contained at least one suicide attempt. Age, hopelessness and active substance abuse but not polarity predicted suicidal behavior. The effects of risk factors did not differ by polarity.
ConclusionsBipolarity does not independently influence risk of suicidal behavior or alter the influence of well-established suicide risk factors within affective disorders. Suicide risk assessment strategies may continue to appraise these common risk factors without regard to mood polarity.