11 results
The genetic contribution to the comorbidity of depression and anxiety: a multi-site electronic health records study of almost 178 000 people
- Brandon J Coombes, Isotta Landi, Karmel W Choi, Kritika Singh, Brian Fennessy, Greg D Jenkins, Anthony Batzler, Richard Pendegraft, Nicolas A Nunez, Y Nina Gao, Euijung Ryu, Priya Wickramaratne, Myrna M Weissman, Regeneron Genetics Center, Jyotishman Pathak, J John Mann, Jordan W Smoller, Lea K Davis, Mark Olfson, Alexander W Charney, Joanna M Biernacka
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- Journal:
- Psychological Medicine / Volume 53 / Issue 15 / November 2023
- Published online by Cambridge University Press:
- 05 May 2023, pp. 7368-7374
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Background
Depression and anxiety are common and highly comorbid, and their comorbidity is associated with poorer outcomes posing clinical and public health concerns. We evaluated the polygenic contribution to comorbid depression and anxiety, and to each in isolation.
MethodsDiagnostic codes were extracted from electronic health records for four biobanks [N = 177 865 including 138 632 European (77.9%), 25 612 African (14.4%), and 13 621 Hispanic (7.7%) ancestry participants]. The outcome was a four-level variable representing the depression/anxiety diagnosis group: neither, depression-only, anxiety-only, and comorbid. Multinomial regression was used to test for association of depression and anxiety polygenic risk scores (PRSs) with the outcome while adjusting for principal components of ancestry.
ResultsIn total, 132 960 patients had neither diagnosis (74.8%), 16 092 depression-only (9.0%), 13 098 anxiety-only (7.4%), and 16 584 comorbid (9.3%). In the European meta-analysis across biobanks, both PRSs were higher in each diagnosis group compared to controls. Notably, depression-PRS (OR 1.20 per s.d. increase in PRS; 95% CI 1.18–1.23) and anxiety-PRS (OR 1.07; 95% CI 1.05–1.09) had the largest effect when the comorbid group was compared with controls. Furthermore, the depression-PRS was significantly higher in the comorbid group than the depression-only group (OR 1.09; 95% CI 1.06–1.12) and the anxiety-only group (OR 1.15; 95% CI 1.11–1.19) and was significantly higher in the depression-only group than the anxiety-only group (OR 1.06; 95% CI 1.02–1.09), showing a genetic risk gradient across the conditions and the comorbidity.
ConclusionsThis study suggests that depression and anxiety have partially independent genetic liabilities and the genetic vulnerabilities to depression and anxiety make distinct contributions to comorbid depression and anxiety.
Prior differences in previous trauma exposure primarily drive the observed racial/ethnic differences in posttrauma depression and anxiety following a recent trauma
- N. G. Harnett, N. M. Dumornay, M. Delity, L. D. Sanchez, K. Mohiuddin, P. I. Musey, Jr., M. J. Seamon, S. A. McLean, R. C. Kessler, K. C. Koenen, F. L. Beaudoin, L. A. M. Lebois, S. J. H. van Rooij, N. A. Sampson, V. Michopoulos, J. L. Maples-Keller, J. P. Haran, A. B. Storrow, C. Lewandowski, P. L. Hendry, S. Sheikh, C. W. Jones, B. E. Punches, M. C. Kurz, R. A. Swor, M. E. McGrath, L. A. Hudak, J. L. Pascual, S. L. House, X. An, J. S. Stevens, T. C. Neylan, T. Jovanovic, S. D. Linnstaedt, L. T. Germine, E. M. Datner, A. M. Chang, C. Pearson, D. A. Peak, R. C. Merchant, R. M. Domeier, N. K. Rathlev, B. J. O'Neil, P. Sergot, S. E. Bruce, M. W. Miller, R. H. Pietrzak, J. Joormann, D. M. Barch, D. A. Pizzagalli, J. F. Sheridan, J. W. Smoller, B. Luna, S. E. Harte, J. M. Elliott, K. J. Ressler
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- Journal:
- Psychological Medicine / Volume 53 / Issue 6 / April 2023
- Published online by Cambridge University Press:
- 31 January 2022, pp. 2553-2562
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Background
Racial and ethnic groups in the USA differ in the prevalence of posttraumatic stress disorder (PTSD). Recent research however has not observed consistent racial/ethnic differences in posttraumatic stress in the early aftermath of trauma, suggesting that such differences in chronic PTSD rates may be related to differences in recovery over time.
MethodsAs part of the multisite, longitudinal AURORA study, we investigated racial/ethnic differences in PTSD and related outcomes within 3 months after trauma. Participants (n = 930) were recruited from emergency departments across the USA and provided periodic (2 weeks, 8 weeks, and 3 months after trauma) self-report assessments of PTSD, depression, dissociation, anxiety, and resilience. Linear models were completed to investigate racial/ethnic differences in posttraumatic dysfunction with subsequent follow-up models assessing potential effects of prior life stressors.
ResultsRacial/ethnic groups did not differ in symptoms over time; however, Black participants showed reduced posttraumatic depression and anxiety symptoms overall compared to Hispanic participants and White participants. Racial/ethnic differences were not attenuated after accounting for differences in sociodemographic factors. However, racial/ethnic differences in depression and anxiety were no longer significant after accounting for greater prior trauma exposure and childhood emotional abuse in White participants.
ConclusionsThe present findings suggest prior differences in previous trauma exposure partially mediate the observed racial/ethnic differences in posttraumatic depression and anxiety symptoms following a recent trauma. Our findings further demonstrate that racial/ethnic groups show similar rates of symptom recovery over time. Future work utilizing longer time-scale data is needed to elucidate potential racial/ethnic differences in long-term symptom trajectories.
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.
Dissecting the heterogeneity of posttraumatic stress disorder: differences in polygenic risk, stress exposures, and course of PTSD subtypes
- Laura Campbell-Sills, Xiaoying Sun, Karmel W. Choi, Feng He, Robert J. Ursano, Ronald C. Kessler, Daniel F. Levey, Jordan W. Smoller, Joel Gelernter, Sonia Jain, Murray B. Stein
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- Journal:
- Psychological Medicine / Volume 52 / Issue 15 / November 2022
- Published online by Cambridge University Press:
- 05 May 2021, pp. 3646-3654
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Background
Definition of disorder subtypes may facilitate precision treatment for posttraumatic stress disorder (PTSD). We aimed to identify PTSD subtypes and evaluate their associations with genetic risk factors, types of stress exposures, comorbidity, and course of PTSD.
MethodsData came from a prospective study of three U.S. Army Brigade Combat Teams that deployed to Afghanistan in 2012. Soldiers with probable PTSD (PTSD Checklist for Diagnostic and Statistical Manual of Mental Disorders-Fifth Edition ≥31) at three months postdeployment comprised the sample (N = 423) for latent profile analysis using Gaussian mixture modeling and PTSD symptom ratings as indicators. PTSD profiles were compared on polygenic risk scores (derived from external genomewide association study summary statistics), experiences during deployment, comorbidity at three months postdeployment, and persistence of PTSD at nine months postdeployment.
ResultsLatent profile analysis revealed profiles characterized by prominent intrusions, avoidance, and hyperarousal (threat-reactivity profile; n = 129), anhedonia and negative affect (dysphoric profile; n = 195), and high levels of all PTSD symptoms (high-symptom profile; n = 99). The threat-reactivity profile had the most combat exposure and the least comorbidity. The dysphoric profile had the highest polygenic risk for major depression, and more personal life stress and co-occurring major depression than the threat-reactivity profile. The high-symptom profile had the highest rates of concurrent mental disorders and persistence of PTSD.
ConclusionsGenetic and trauma-related factors likely contribute to PTSD heterogeneity, which can be parsed into subtypes that differ in symptom expression, comorbidity, and course. Future studies should evaluate whether PTSD typology modifies treatment response and should clarify distinctions between the dysphoric profile and depressive disorders.
Resilience to mental disorders in a low-income, non-Westernized setting
- Kate M. Scott, Yang Zhang, Stephanie Chardoul, Dirgha J. Ghimire, Jordan W. Smoller, William G. Axinn
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- Journal:
- Psychological Medicine / Volume 51 / Issue 16 / December 2021
- Published online by Cambridge University Press:
- 01 June 2020, pp. 2825-2834
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Background
Cross-national studies have found, unexpectedly, that mental disorder prevalence is higher in high-income relative to low-income countries, but few rigorous studies have been conducted in very low-income countries. This study assessed mental disorders in Nepal, employing unique methodological features designed to maximize disorder detection and reporting.
MethodsIn 2016–2018, 10714 respondents aged 15–59 were interviewed as part of an ongoing panel study, with a response rate of 93%. The World Mental Health version of the Composite International Diagnostic Interview (WMH-CIDI 3.0) measured lifetime and 12-month prevalence of selected anxiety, mood, alcohol use, and impulse control disorders. Lifetime recall was enhanced using a life history calendar.
ResultsLifetime prevalence ranged from 0.3% (95% CI 0.2–0.4) for bipolar disorder to 15.1% (95% CI 14.4–15.7) for major depressive disorder. The 12-month prevalences were low, ranging from 0.2% for panic disorder (95% CI 0.1–0.3) and bipolar disorder (95% CI 0.1–0.2) to 2.7% for depression (95% CI 2.4–3.0). Lifetime disorders were higher among those with less education and in the low-caste ethnic group. Gender differences were pronounced.
ConclusionsAlthough cultural effects on reporting cannot be ruled out, these low 12-month prevalences are consistent with reduced prevalence of mental disorders in other low-income countries. Identification of sociocultural factors that mediate the lower prevalence of mental disorders in low-income, non-Westernized settings may have implications for understanding disorder etiology and for clinical or policy interventions aimed at facilitating resilience.
Prospective study of polygenic risk, protective factors, and incident depression following combat deployment in US Army soldiers
- Karmel W. Choi, Chia-Yen Chen, Robert J. Ursano, Xiaoying Sun, Sonia Jain, Ronald C. Kessler, Karestan C. Koenen, Min-Jung Wang, Gary H. Wynn, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Laura Campbell-Sills, Murray B. Stein, Jordan W. Smoller
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- Journal:
- Psychological Medicine / Volume 50 / Issue 5 / April 2020
- Published online by Cambridge University Press:
- 15 April 2019, pp. 737-745
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Background
Whereas genetic susceptibility increases the risk for major depressive disorder (MDD), non-genetic protective factors may mitigate this risk. In a large-scale prospective study of US Army soldiers, we examined whether trait resilience and/or unit cohesion could protect against the onset of MDD following combat deployment, even in soldiers at high polygenic risk.
MethodsData were analyzed from 3079 soldiers of European ancestry assessed before and after their deployment to Afghanistan. Incident MDD was defined as no MDD episode at pre-deployment, followed by a MDD episode following deployment. Polygenic risk scores were constructed from a large-scale genome-wide association study of major depression. We first examined the main effects of the MDD PRS and each protective factor on incident MDD. We then tested the effects of each protective factor on incident MDD across strata of polygenic risk.
ResultsPolygenic risk showed a dose–response relationship to depression, such that soldiers at high polygenic risk had greatest odds for incident MDD. Both unit cohesion and trait resilience were prospectively associated with reduced risk for incident MDD. Notably, the protective effect of unit cohesion persisted even in soldiers at highest polygenic risk.
ConclusionsPolygenic risk was associated with new-onset MDD in deployed soldiers. However, unit cohesion – an index of perceived support and morale – was protective against incident MDD even among those at highest genetic risk, and may represent a potent target for promoting resilience in vulnerable soldiers. Findings illustrate the value of combining genomic and environmental data in a prospective design to identify robust protective factors for mental health.
Using life history calendars to improve measurement of lifetime experience with mental disorders
- William G. Axinn, Stephanie Chardoul, Heather Gatny, Dirgha J. Ghimire, Jordan W. Smoller, Yang Zhang, Kate M. Scott
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- Journal:
- Psychological Medicine / Volume 50 / Issue 3 / February 2020
- Published online by Cambridge University Press:
- 11 March 2019, pp. 515-522
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Background
Retrospective reports of lifetime experience with mental disorders greatly underestimate the actual experiences of disorder because recall error biases reporting of earlier life symptoms downward. This fundamental obstacle to accurate reporting has many adverse consequences for the study and treatment of mental disorders. Better tools for accurate retrospective reporting of mental disorder symptoms have the potential for broad scientific benefits.
MethodsWe designed a life history calendar (LHC) to support this task, and randomized more than 1000 individuals to each arm of a retrospective diagnostic interview with and without the LHC. We also conducted a careful validation with the Structured Clinical Interview for the Diagnostic and Statistical Manual of Mental Disorders-Fourth Edition.
ResultsResults demonstrate that—just as with frequent measurement longitudinal studies—use of an LHC in retrospective measurement can more than double reports of lifetime experience of some mental disorders.
ConclusionsThe LHC significantly improves retrospective reporting of mental disorders. This tool is practical for application in both large cross-sectional surveys of the general population and clinical intake of new patients.
Contributors
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- By Agoston T. Agoston, Syed Z. Ali, Mahul B. Amin, Daniel A. Arber, Pedram Argani, Sylvia L. Asa, Rebecca N. Baergen, Zubair W. Baloch, Andrew M. Bellizzi, Kurt Benirschke, Allen Burke, Kenneth B. Calder, Karen L. Chang, Rebecca D. Chernock, Wang Cheung, Thomas V. Colby, Byron P. Croker, Ronald A. DeLellis, Edward F. DiCarlo, Ralph C. Eagle, Hormoz Ehya, Brett M. Elicker, Tarik M. Elsheikh, Robert E. Fechner, Linda D. Ferrell, Melina B. Flanagan, Douglas B. Flieder, Christopher S. Foster, Lillian Gaber, Karuna Garg, Kim R. Geisinger, Ryan M. Gill, Eric F. Glassy, David J. Glembocki, Zachary D. Goodman, Robert O. Greer, David J. Grignon, Gerardo E. Guiter, Kymberly A. Gyure, Ian S. Hagemann, Michael R. Henry, Jason L. Hornick, Ralph H. Hruban, Phyllis C. Huettner, Peter A. Humphrey, Olga B. Ioffe, Edward C. Klatt, Michael J. Klein, Ernest E. Lack, James N. Lampros, Lester J. Layfield, Robin D. LeGallo, Kevin O. Leslie, James S. Lewis, Virginia A. LiVolsi, Alberto M. Marchevsky, Anne Marie McNicol, Mitra Mehrad, Elizabeth Montgomery, Cesar A. Moran, Christopher A. Moskaluk, George J. Netto, G. Petur Nielsen, Robert D. Odze, Arthur S. Patchefsky, James W. Patterson, Elizabeth N. Pavlisko, John D. Pfeifer, Celeste N. Powers, Richard A. Prayson, Anja C. Roden, Victor L. Roggli, Andrew E. Rosenberg, Sherif Said, Margie A. Scott, Raja R. Seethala, Carlie S. Sigel, Jan F. Silverman, Bruce R. Smoller, Edward B. Stelow, Nora C. J. Sun, Mark W. Teague, Satish K. Tickoo, Thomas M. Ulbright, Paul E. Wakely, Jun Wang, Lawrence M. Weiss, Mark R. Wick, Howard H. Wu, Rhonda K. Yantiss, Charles Zaloudek, Yaxia Zhang, Xiaohui Sheila Zhao
- Edited by Mark R. Wick, University of Virginia, Virginia A. LiVolsi, University of Pennsylvania School of Medicine, John D. Pfeifer, Washington University School of Medicine, St Louis, Edward B. Stelow, University of Virginia, Paul E. Wakely, Jr
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- Book:
- Silverberg's Principles and Practice of Surgical Pathology and Cytopathology
- Published online:
- 13 March 2015
- Print publication:
- 26 March 2015, pp vii-x
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Psychosocial stressors and the prognosis of major depression: a test of Axis IV
- S. E. Gilman, N.-H. Trinh, J. W. Smoller, M. Fava, J. M. Murphy, J. Breslau
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- Journal:
- Psychological Medicine / Volume 43 / Issue 2 / February 2013
- Published online by Cambridge University Press:
- 28 May 2012, pp. 303-316
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Background
Axis IV is for reporting ‘psychosocial and environmental problems that may affect the diagnosis, treatment and prognosis of mental disorders’. No studies have examined the prognostic value of Axis IV in DSM-IV.
MethodWe analyzed data from 2497 participants in the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC) with major depressive episode (MDE). We hypothesized that psychosocial stressors predict a poor prognosis of MDE. Secondarily, we hypothesized that psychosocial stressors predict a poor prognosis of anxiety and substance use disorders. Stressors were defined according to DSM-IV's taxonomy, and empirically using latent class analysis (LCA).
ResultsPrimary support group problems, occupational problems and childhood adversity increased the risks of depressive episodes and suicidal ideation by 20–30%. Associations of the empirically derived classes of stressors with depression were larger in magnitude. Economic stressors conferred a 1.5-fold increase in risk for a depressive episode [95% confidence interval (CI) 1.2–1.9]; financial and interpersonal instability conferred a 1.3-fold increased risk of recurrent depression (95% CI 1.1–1.6). These two classes of stressors also predicted the recurrence of anxiety and substance use disorders. Stressors were not related to suicidal ideation independent from depression severity.
ConclusionsPsychosocial and environmental problems are associated with the prognosis of MDE and other Axis I disorders. Although DSM-IV's taxonomy of stressors stands to be improved, these results provide empirical support for the prognostic value of Axis IV. Future work is needed to determine the reliability of Axis IV assessments in clinical practice, and the usefulness of this information to improving the clinical course of mental disorders.
Using electronic medical records to enable large-scale studies in psychiatry: treatment resistant depression as a model
- R. H. Perlis, D. V. Iosifescu, V. M. Castro, S. N. Murphy, V. S. Gainer, J. Minnier, T. Cai, S. Goryachev, Q. Zeng, P. J. Gallagher, M. Fava, J. B. Weilburg, S. E. Churchill, I. S. Kohane, J. W. Smoller
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- Journal:
- Psychological Medicine / Volume 42 / Issue 1 / January 2012
- Published online by Cambridge University Press:
- 20 June 2011, pp. 41-50
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Background
Electronic medical records (EMR) provide a unique opportunity for efficient, large-scale clinical investigation in psychiatry. However, such studies will require development of tools to define treatment outcome.
MethodNatural language processing (NLP) was applied to classify notes from 127 504 patients with a billing diagnosis of major depressive disorder, drawn from out-patient psychiatry practices affiliated with multiple, large New England hospitals. Classifications were compared with results using billing data (ICD-9 codes) alone and to a clinical gold standard based on chart review by a panel of senior clinicians. These cross-sectional classifications were then used to define longitudinal treatment outcomes, which were compared with a clinician-rated gold standard.
ResultsModels incorporating NLP were superior to those relying on billing data alone for classifying current mood state (area under receiver operating characteristic curve of 0.85–0.88 v. 0.54–0.55). When these cross-sectional visits were integrated to define longitudinal outcomes and incorporate treatment data, 15% of the cohort remitted with a single antidepressant treatment, while 13% were identified as failing to remit despite at least two antidepressant trials. Non-remitting patients were more likely to be non-Caucasian (p<0.001).
ConclusionsThe application of bioinformatics tools such as NLP should enable accurate and efficient determination of longitudinal outcomes, enabling existing EMR data to be applied to clinical research, including biomarker investigations. Continued development will be required to better address moderators of outcome such as adherence and co-morbidity.
Personality and bipolar disorder: dissecting state and trait associations between mood and personality
- J. H. Barnett, J. Huang, R. H. Perlis, M. M. Young, J. F. Rosenbaum, A. A. Nierenberg, G. Sachs, V. L. Nimgaonkar, D. J. Miklowitz, J. W. Smoller
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- Journal:
- Psychological Medicine / Volume 41 / Issue 8 / August 2011
- Published online by Cambridge University Press:
- 07 December 2010, pp. 1593-1604
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Background
Some personality characteristics have previously been associated with an increased risk for psychiatric disorder. Longitudinal studies are required in order to tease apart temporary (state) and enduring (trait) differences in personality among individuals with bipolar disorder (BD). This study aimed to determine whether there is a characteristic personality profile in BD, and whether associations between BD and personality are best explained by state or trait effects.
MethodA total of 2247 participants in the Systematic Treatment Enhancement Program for Bipolar Disorder study completed the NEO Five-Factor Inventory administered at study entry, and at 1 and 2 years.
ResultsPersonality in BD was characterized by high neuroticism (N) and openness (O), and low agreeableness (A), conscientiousness (C) and extraversion (E). This profile was replicated in two independent samples, and openness was found to distinguish BD from major depressive disorder. Latent growth modeling demonstrated that manic symptoms were associated with increased E and decreased A, and depressed symptoms with higher N and lower E, A, C and O. During euthymic phases, high N and low E scores predicted a future depression-prone course.
ConclusionsWhile there are clear state effects of mood on self-reported personality, personality variables during euthymia predict future course of illness. Personality disturbances in extraversion, neuroticism and openness may be enduring characteristics of patients with BD.