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Adjunctive short- and long-term combination treatment of esketamine and VNS in difficult to treat depression (DTD)
- E. Kavakbasi, B. T. Baune
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- Journal:
- European Psychiatry / Volume 66 / Issue S1 / March 2023
- Published online by Cambridge University Press:
- 19 July 2023, pp. S249-S250
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Introduction
NMDA-Receptor antagonists have rapid antidepressant and antisuicidal properties. However, the antidepressant effect is short lasting raising the question of best maintenance strategy, which is unanswered so far. Invasive vagus nerve stimulation (VNS) as a treatment option for refractory and chronic major depression was shown to reduce the need of maintenance treatment sessions in electroconvulsive therapy (ECT) patients.
ObjectivesThere are no published data on the combination of VNS and esketamine. To determine the impact of the combination of VNS and esketamine in DTD.
MethodsIn this naturalistic observational study, we investigated the short- and long-term impact of combination of VNS and esketamine in n=8 patients with difficult-to-treat depression (DTD). Follow-up evaluations were scheduled prospectively pre-surgery at baseline and every 3 months after VNS-implantation (follow-up period 12-24 months, mean 17).
ResultsThe mean age of patients was 50,8 years. 50 % of patients (n=4) were female. All patients suffered from severe DTD (mean MADRS at baseline 30,9). Mean number of hospitalizations per months decreased from 0.17 to 0.11 after VNS implantation. 6 of 8 patients were offered maintenance esketamine treatment. Mean MADRS at 12-months was 19 (38.5 % MADRS reduction). The need of mean esketamine treatment sessions decreased from 2.3 at 6-months visit (V6) to 1.37 at V9 and 0.96 at V12 respectively. Termination of maintenance esketamine was possible in 4 cases after a mean of 11.5 months.
ConclusionsCombination of esketamine and VNS is a safe and effective treatment option in severely ill DTD patients to relieve disease severity and reduce hospitalizations. Need of esketamine treatment sessions decreases 6 months after VNS implantation.
Disclosure of InterestNone Declared
Methylation changes in association with early life stress and trauma-focused psychotherapy in treatment-resistant depression
- R. Carvalho Silva, C. Hohoff, P. Martini, M. Bortolomasi, R. Bazzanella, V. Menesello, M. Gennarelli, B. T. Baune, A. Minelli
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- Journal:
- European Psychiatry / Volume 66 / Issue S1 / March 2023
- Published online by Cambridge University Press:
- 19 July 2023, pp. S115-S116
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Introduction
Early life stress (ELS) associates with unfavourable outcome in Major depressive disorder (MDD) and treatment-resistant depression (TRD). Trauma-focused psychotherapy benefits TRD patients exposed to ELS. Epigenetic processes are altered in stress-related disorders, but few studies show epigenetic signatures associated with trauma.
ObjectivesWe performed an epigenome-wide association study (EWAS) to explore the relation between methylation changes in TRD patients characterized for recent and ELS and trauma-focused psychotherapy outcomes.
MethodsThirty TRD patients participated. They underwent psychotherapy, from which 12 cognitive behavioural therapy and 18 Eye Movement Desensitization and Reprocessing (EMDR). We used validated interviews and questionnaires for symptom evaluation and stress exposure. Patients were evaluated at T0 (baseline), T8 (end of psychotherapy), T12 (follow-up) and T26. Methylation was profiled with Illumina Infinium EPIC array for T0, T8 and T12. Methylation levels were quantified after quality control and normalization using ChAMP R package. We tested the association between B-values for each CpG site (each probe set) and each phenotype/condition using a linear model approach (with paired values) as implemented in the Limma R package. P-values were adjusted using Benjamini & Hochberg method. Probe sets were considered significant with an adjusted p-value q ≤ 0.05. CpG site annotation was performed using IlluminaHumanMethylationEPICanno.ilm10b2.hg19 R package (hg19 genome reference).
ResultsAssociation analyses between baseline methylation levels and emotional abuse resulted in two significant probe sets annotated in SLCO4A1 (p=1,72E-08; q=0,008), involved in sodium independent transmembrane substrate transport, and GPNMB (p=1,53E-07; q=0,022), involved in cell differentiation. Associations between baseline methylation levels and physical abuse resulted in one significant probe set annotated in DDIT4L (p=4,77E-08; q=0,035), involved in cell growth.
In longitudinal analyses, association between T0-T8 methylation levels and response at T8 resulted in two significant probe sets annotated in PLEKHB1 (p=3,54E-08; q=0,013), involved in cell differentiation, and NUDT4P2 (p=1,34E-07; q=0,032). Longitudinal T12-T0 EWAS analyses in patients undergoing EMDR resulted in 44 significant probe sets annotated in genes, highlighting MAD1L1 (p=6,28E-07; q=0,035), involved in cell division, and TNFAIP3 (p=3,00E-06; q=0,045), which regulates immunity.
ConclusionsWe identified epigenetic signatures of ELS in TRD patients, suggesting that ELS may modulate the intensity of epigenetic alterations. Longitudinal methylation analyses along psychotherapy showed significant genes in relation to response, especially for patients undergoing EMDR. Some genes are associated with post-traumatic stress disorder (MAD1L1) and anxiety disorders and MDD (TNFAIP3).
Disclosure of InterestNone Declared
Efficacy and safety of a 4-week course of repeated subcutaneous ketamine injections for treatment-resistant depression (KADS study): randomised double-blind active-controlled trial
- Colleen Loo, Nick Glozier, David Barton, Bernhard T. Baune, Natalie T. Mills, Paul Fitzgerald, Paul Glue, Shanthi Sarma, Veronica Galvez-Ortiz, Dusan Hadzi-Pavlovic, Angelo Alonzo, Vanessa Dong, Donel Martin, Stevan Nikolin, Philip B. Mitchell, Michael Berk, Gregory Carter, Maree Hackett, John Leyden, Sean Hood, Andrew A. Somogyi, Kyle Lapidus, Elizabeth Stratton, Kirsten Gainsford, Deepak Garg, Nicollette L. R. Thornton, Célia Fourrier, Karyn Richardson, Demi Rozakis, Anish Scaria, Cathrine Mihalopoulos, Mary Lou Chatterton, William M. McDonald, Philip Boyce, Paul E. Holtzheimer, F. Andrew Kozel, Patricio Riva-Posse, Anthony Rodgers
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- Journal:
- The British Journal of Psychiatry / Volume 223 / Issue 6 / December 2023
- Published online by Cambridge University Press:
- 14 July 2023, pp. 533-541
- Print publication:
- December 2023
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Background
Prior trials suggest that intravenous racemic ketamine is a highly effective for treatment-resistant depression (TRD), but phase 3 trials of racemic ketamine are needed.
AimsTo assess the acute efficacy and safety of a 4-week course of subcutaneous racemic ketamine in participants with TRD. Trial registration: ACTRN12616001096448 at www.anzctr.org.au.
MethodThis phase 3, double-blind, randomised, active-controlled multicentre trial was conducted at seven mood disorders centres in Australia and New Zealand. Participants received twice-weekly subcutaneous racemic ketamine or midazolam for 4 weeks. Initially, the trial tested fixed-dose ketamine 0.5 mg/kg versus midazolam 0.025 mg/kg (cohort 1). Dosing was revised, after a Data Safety Monitoring Board recommendation, to flexible-dose ketamine 0.5–0.9 mg/kg or midazolam 0.025–0.045 mg/kg, with response-guided dosing increments (cohort 2). The primary outcome was remission (Montgomery-Åsberg Rating Scale for Depression score ≤10) at the end of week 4.
ResultsThe final analysis (those who received at least one treatment) comprised 68 in cohort 1 (fixed-dose), 106 in cohort 2 (flexible-dose). Ketamine was more efficacious than midazolam in cohort 2 (remission rate 19.6% v. 2.0%; OR = 12.1, 95% CI 2.1–69.2, P = 0.005), but not different in cohort 1 (remission rate 6.3% v. 8.8%; OR = 1.3, 95% CI 0.2–8.2, P = 0.76). Ketamine was well tolerated. Acute adverse effects (psychotomimetic, blood pressure increases) resolved within 2 h.
ConclusionsAdequately dosed subcutaneous racemic ketamine was efficacious and safe in treating TRD over a 4-week treatment period. The subcutaneous route is practical and feasible.
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.
Cognitive side-effects of electroconvulsive therapy: what are they, how to monitor them and what to tell patients
- Richard J. Porter, Bernhard T. Baune, Grace Morris, Amber Hamilton, Darryl Bassett, Philip Boyce, Malcolm J. Hopwood, Roger Mulder, Gordon Parker, Ajeet B. Singh, Tim Outhred, Pritha Das, Gin S. Malhi
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- Journal:
- BJPsych Open / Volume 6 / Issue 3 / May 2020
- Published online by Cambridge University Press:
- 17 April 2020, e40
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Background
Electroconvulsive therapy (ECT) is recommended in treatment guidelines as an efficacious therapy for treatment-resistant depression. However, it has been associated with loss of autobiographical memory and short-term reduction in new learning.
AimsTo provide clinically useful guidelines to aid clinicians in informing patients regarding the cognitive side-effects of ECT and in monitoring these during a course of ECT, using complex data.
MethodA Committee of clinical and academic experts from Australia and New Zealand met to the discuss the key issues pertaining to ECT and cognitive side-effects. Evidence regarding cognitive side-effects was reviewed, as was the limited evidence regarding how to monitor them. Both issues were supplemented by the clinical experience of the authors.
ResultsMeta-analyses suggest that new learning is impaired immediately following ECT but that group mean scores return at least to baseline by 14 days after ECT. Other cognitive functions are generally unaffected. However, the finding of a mean score that is not reduced from baseline cannot be taken to indicate that impairment, particularly of new learning, cannot occur in individuals, particularly those who are at greater risk. Therefore, monitoring is still important. Evidence suggests that ECT does cause deficits in autobiographical memory. The evidence for schedules of testing to monitor cognitive side-effects is currently limited. We therefore make practical recommendations based on clinical experience.
ConclusionsDespite modern ECT techniques, cognitive side-effects remain an important issue, although their nature and degree remains to be clarified fully. In these circumstances it is useful for clinicians to have guidance regarding what to tell patients and how to monitor these side-effects clinically.
Interactive impact of childhood maltreatment, depression, and age on cortical brain structure: mega-analytic findings from a large multi-site cohort
- Leonardo Tozzi, Lisa Garczarek, Deborah Janowitz, Dan J. Stein, Katharina Wittfeld, Henrik Dobrowolny, Jim Lagopoulos, Sean N. Hatton, Ian B. Hickie, Angela Carballedo, Samantha J. Brooks, Daniella Vuletic, Anne Uhlmann, Ilya M. Veer, Henrik Walter, Robin Bülow, Henry Völzke, Johanna Klinger-König, Knut Schnell, Dieter Schoepf, Dominik Grotegerd, Nils Opel, Udo Dannlowski, Harald Kugel, Elisabeth Schramm, Carsten Konrad, Tilo Kircher, Dilara Jüksel, Igor Nenadić, Axel Krug, Tim Hahn, Olaf Steinsträter, Ronny Redlich, Dario Zaremba, Bartosz Zurowski, Cynthia H.Y. Fu, Danai Dima, James Cole, Hans J. Grabe, Colm G. Connolly, Tony T. Yang, Tiffany C. Ho, Kaja Z. LeWinn, Meng Li, Nynke A. Groenewold, Lauren E. Salminen, Martin Walter, Alan N Simmons, Theo G.M. van Erp, Neda Jahanshad, Bernhard T. Baune, Nic J.A. van der Wee, Marie-Jose van Tol, Brenda W.J.H. Penninx, Derrek P. Hibar, Paul M. Thompson, Dick J. Veltman, Lianne Schmaal, Thomas Frodl, ‘for the ENIGMA-MDD Consortium’
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- Journal:
- Psychological Medicine / Volume 50 / Issue 6 / April 2020
- Published online by Cambridge University Press:
- 14 May 2019, pp. 1020-1031
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Background
Childhood maltreatment (CM) plays an important role in the development of major depressive disorder (MDD). The aim of this study was to examine whether CM severity and type are associated with MDD-related brain alterations, and how they interact with sex and age.
MethodsWithin the ENIGMA-MDD network, severity and subtypes of CM using the Childhood Trauma Questionnaire were assessed and structural magnetic resonance imaging data from patients with MDD and healthy controls were analyzed in a mega-analysis comprising a total of 3872 participants aged between 13 and 89 years. Cortical thickness and surface area were extracted at each site using FreeSurfer.
ResultsCM severity was associated with reduced cortical thickness in the banks of the superior temporal sulcus and supramarginal gyrus as well as with reduced surface area of the middle temporal lobe. Participants reporting both childhood neglect and abuse had a lower cortical thickness in the inferior parietal lobe, middle temporal lobe, and precuneus compared to participants not exposed to CM. In males only, regardless of diagnosis, CM severity was associated with higher cortical thickness of the rostral anterior cingulate cortex. Finally, a significant interaction between CM and age in predicting thickness was seen across several prefrontal, temporal, and temporo-parietal regions.
ConclusionsSeverity and type of CM may impact cortical thickness and surface area. Importantly, CM may influence age-dependent brain maturation, particularly in regions related to the default mode network, perception, and theory of mind.
Expert Consensus on Screening and Assessment of Cognition in Psychiatry
- Roger S. McIntyre, Nicole Anderson, Bernhard T. Baune, Elisa Brietzke, Katherine Burdick, Phillipe Fossati, Philip Gorwood, Catherine Harmer, John Harrison, Philip Harvey, Rodrigo B. Mansur, Alice Medalia, Kamilla Miskowiak, Tanya Ramey, Carola Rong, Joshua D. Rosenblat, Allan Young, Stephen M. Stahl
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- Journal:
- CNS Spectrums / Volume 24 / Issue 1 / February 2019
- Published online by Cambridge University Press:
- 15 January 2019, pp. 154-162
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During the past two decades, it has been amply documented that neuropsychiatric disorders (NPDs) disproportionately account for burden of illness attributable to chronic non-communicable medical disorders globally. It is also likely that human capital costs attributable to NPDs will disproportionately increase as a consequence of population aging and beneficial risk factor modification of other common and chronic medical disorders (e.g., cardiovascular disease). Notwithstanding the availability of multiple modalities of antidepressant treatment, relatively few studies in psychiatry have primarily sought to determine whether improving cognitive function in MDD improves patient reported outcomes (PROs) and/or is cost effective. The mediational relevance of cognition in MDD potentially extrapolates to all NPDs, indicating that screening for, measuring, preventing, and treating cognitive deficits in psychiatry is not only a primary therapeutic target, but also should be conceptualized as a transdiagnostic domain to be considered regardless of patient age and/or differential diagnosis.
Defining a mood stabiliser: novel framework for research and clinical practice
- Gin S. Malhi, Richard Porter, Lauren Irwin, Amber Hamilton, Grace Morris, Darryl Bassett, Bernhard T. Baune, Philip Boyce, Malcolm J. Hopwood, Roger Mulder, Gordon Parker, Zola Mannie, Tim Outhred, Pritha Das, Ajeet B. Singh
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- Journal:
- BJPsych Open / Volume 4 / Issue 4 / July 2018
- Published online by Cambridge University Press:
- 20 July 2018, pp. 278-281
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The term ‘mood stabiliser’ is ill-defined and lacks clinical utility. We propose a framework to evaluate medications and effectively communicate their mood stabilising properties – their acute and prophylactic efficacy across the domains of mania and depression. The standardised framework provides a common definition to facilitate research and clinical practice.
Declaration of interestThe Treatment Algorithm Group (TAG) was supported logistically by Servier who provided financial assistance with travel and accommodation for those TAG members travelling interstate or overseas to attend the meeting in Sydney (held on 18 November 2017). None of the committee were paid to participate in this project and Servier have not had any input into the content, format or outputs from this project.
White matter connectivity disruptions in early and chronic schizophrenia
- M. A. Di Biase, V. L. Cropley, B. T. Baune, J. Olver, G. P. Amminger, C. Phassouliotis, C. Bousman, P. D. McGorry, I. Everall, C. Pantelis, A. Zalesky
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- Journal:
- Psychological Medicine / Volume 47 / Issue 16 / December 2017
- Published online by Cambridge University Press:
- 22 May 2017, pp. 2797-2810
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Background
White matter disruptions in schizophrenia have been widely reported, but it remains unclear whether these abnormalities differ between illness stages. We mapped the connectome in patients with recently diagnosed and chronic schizophrenia and investigated the extent and overlap of white matter connectivity disruptions between these illness stages.
MethodsDiffusion-weighted magnetic resonance images were acquired in recent-onset (n = 19) and chronic patients (n = 45) with schizophrenia, as well as age-matched controls (n = 87). Whole-brain fiber tracking was performed to quantify the strength of white matter connections. Connections were tested for significant streamline count reductions in recent-onset and chronic groups, relative to separate age-matched controls. Permutation tests were used to assess whether disrupted connections significantly overlapped between chronic and recent-onset patients. Linear regression was performed to test whether connectivity was strongest in controls, weakest in chronic patients, and midway between these extremities in recent-onset patients (controls > recent-onset > chronic).
ResultsCompared with controls, chronic patients displayed a widespread network of connectivity disruptions (p < 0.01). In contrast, connectivity reductions were circumscribed to the anterior fibers of the corpus callosum in recent-onset patients (p < 0.01). A significant proportion of disrupted connections in recent-onset patients (86%) coincided with disrupted connections in chronic patients (p < 0.01). Linear regression revealed that chronic patients displayed reduced connectivity relative to controls, while recent-onset patients showed an intermediate reduction compared with chronic patients (p < 0.01).
ConclusionsConnectome pathology in recent-onset patients with schizophrenia is confined to select tracts within a more extensive network of white matter connectivity disruptions found in chronic illness. These findings may suggest a trajectory of progressive deterioration of connectivity in schizophrenia.
Lack of association between iron metabolism and depressive mood in an elderly general population
- B. T. Baune, A. v. Eckardstein, K. Berger
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- Journal:
- International Psychogeriatrics / Volume 18 / Issue 3 / September 2006
- Published online by Cambridge University Press:
- 10 February 2006, pp. 437-444
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- Article
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Background: Alterations in iron metabolism have been suggested as potential pathological markers in patients with manifest depression. No data on the association between iron and depression exist from population-based studies, in which milder forms of depressive symptoms are much more common. The aim of this study was to analyze the relationship between six parameters of iron metabolism and depressive mood in a population-based cross-sectional study in Germany.
Methods: A total of 374 participants, aged 65–83 years, of the Memory and Morbidity in Augsburg Elderly (MEMO) Study were assessed using the Center for Epidemiologic Studies – Depression Scale (CES-D) for depression. Iron, ferritin, transferrin, soluble transferrin receptor, iron binding capacity, transferrin saturation and C-reactive protein were analyzed with standard laboratory methods. Linear and logistic regression analyses were applied to evaluate the relationship between iron parameters and depressive mood.
Results: The 7-day prevalence of depressive mood was 10.2%, with a higher risk in women compared to men [odds ratio (OR) = 2.04; 95% confidence interval (95% CI) = 1.04–4.0]. Correlation and linear regression analyses adjusted for age, gender, hypertension and smoking yielded no significant relationship between any of the iron parameters and the CES-D scores. In gender-stratified analyses a statistically significant association between serum iron and depressive mood was observed in men only. This finding disappeared after applying a Bonferroni correction for multiple testing.
Conclusions: The lack of association of iron metabolism and depressive mood reported in this population-based study does not support previous findings in patients with major depression. This negative finding in milder forms of depression in elderly people indicates either the absence or a more complex nature of the interactions between iron metabolism, low-grade inflammation and depression.