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Mega-analysis of association between obesity and cortical morphology in bipolar disorders: ENIGMA study in 2832 participants
- Sean R. McWhinney, Christoph Abé, Martin Alda, Francesco Benedetti, Erlend Bøen, Caterina del Mar Bonnin, Tiana Borgers, Katharina Brosch, Erick J. Canales-Rodríguez, Dara M. Cannon, Udo Dannlowski, Ana M. Diaz-Zuluaga, Lorielle M.F. Dietze, Torbjørn Elvsåshagen, Lisa T. Eyler, Janice M. Fullerton, Jose M. Goikolea, Janik Goltermann, Dominik Grotegerd, Bartholomeus C. M. Haarman, Tim Hahn, Fleur M. Howells, Martin Ingvar, Neda Jahanshad, Tilo T. J. Kircher, Axel Krug, Rayus T. Kuplicki, Mikael Landén, Hannah Lemke, Benny Liberg, Carlos Lopez-Jaramillo, Ulrik F. Malt, Fiona M. Martyn, Elena Mazza, Colm McDonald, Genevieve McPhilemy, Sandra Meier, Susanne Meinert, Tina Meller, Elisa M. T. Melloni, Philip B. Mitchell, Leila Nabulsi, Igor Nenadic, Nils Opel, Roel A. Ophoff, Bronwyn J. Overs, Julia-Katharina Pfarr, Julian A. Pineda-Zapata, Edith Pomarol-Clotet, Joaquim Raduà, Jonathan Repple, Maike Richter, Kai G. Ringwald, Gloria Roberts, Alex Ross, Raymond Salvador, Jonathan Savitz, Simon Schmitt, Peter R. Schofield, Kang Sim, Dan J. Stein, Frederike Stein, Henk S. Temmingh, Katharina Thiel, Sophia I. Thomopoulos, Neeltje E. M. van Haren, Cristian Vargas, Eduard Vieta, Annabel Vreeker, Lena Waltemate, Lakshmi N. Yatham, Christopher R. K. Ching, Ole A. Andreassen, Paul M. Thompson, Tomas Hajek, for the ENIGMA Bipolar Disorder Working Group
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- Journal:
- Psychological Medicine / Volume 53 / Issue 14 / October 2023
- Published online by Cambridge University Press:
- 27 February 2023, pp. 6743-6753
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Background:
Obesity is highly prevalent and disabling, especially in individuals with severe mental illness including bipolar disorders (BD). The brain is a target organ for both obesity and BD. Yet, we do not understand how cortical brain alterations in BD and obesity interact.
Methods:We obtained body mass index (BMI) and MRI-derived regional cortical thickness, surface area from 1231 BD and 1601 control individuals from 13 countries within the ENIGMA-BD Working Group. We jointly modeled the statistical effects of BD and BMI on brain structure using mixed effects and tested for interaction and mediation. We also investigated the impact of medications on the BMI-related associations.
Results:BMI and BD additively impacted the structure of many of the same brain regions. Both BMI and BD were negatively associated with cortical thickness, but not surface area. In most regions the number of jointly used psychiatric medication classes remained associated with lower cortical thickness when controlling for BMI. In a single region, fusiform gyrus, about a third of the negative association between number of jointly used psychiatric medications and cortical thickness was mediated by association between the number of medications and higher BMI.
Conclusions:We confirmed consistent associations between higher BMI and lower cortical thickness, but not surface area, across the cerebral mantle, in regions which were also associated with BD. Higher BMI in people with BD indicated more pronounced brain alterations. BMI is important for understanding the neuroanatomical changes in BD and the effects of psychiatric medications on the brain.
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.
High educational performance is a distinctive feature of bipolar disorder: a study on cognition in bipolar disorder, schizophrenia patients, relatives and controls
- A. Vreeker, M. P. M. Boks, L. Abramovic, S. Verkooijen, A. H. van Bergen, M. H. J. Hillegers, A. T. Spijker, E. Hoencamp, E. J. Regeer, R. F. Riemersma-Van der Lek, A. W. M. M. Stevens, P. F. J. Schulte, R. Vonk, R. Hoekstra, N. J. M. van Beveren, R. W. Kupka, R. M. Brouwer, C. E. Bearden, J. H. MacCabe, R. A. Ophoff, GROUP Investigators
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- Journal:
- Psychological Medicine / Volume 46 / Issue 4 / March 2016
- Published online by Cambridge University Press:
- 01 December 2015, pp. 807-818
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Background
Schizophrenia is associated with lower intelligence and poor educational performance relative to the general population. This is, to a lesser degree, also found in first-degree relatives of schizophrenia patients. It is unclear whether bipolar disorder I (BD-I) patients and their relatives have similar lower intellectual and educational performance as that observed in schizophrenia.
MethodThis cross-sectional study investigated intelligence and educational performance in two outpatient samples [494 BD-I patients, 952 schizophrenia spectrum (SCZ) patients], 2231 relatives of BD-I and SCZ patients, 1104 healthy controls and 100 control siblings. Mixed-effects and regression models were used to compare groups on intelligence and educational performance.
ResultsBD-I patients were more likely to have completed the highest level of education (odds ratio 1.88, 95% confidence interval 1.66–2.70) despite having a lower IQ compared to controls (β = −9.09, s.e. = 1.27, p < 0.001). In contrast, SCZ patients showed both a lower IQ (β = −15.31, s.e. = 0.86, p < 0.001) and lower educational levels compared to controls. Siblings of both patient groups had significantly lower IQ than control siblings, but did not differ on educational performance. IQ scores did not differ between BD-I parents and SCZ parents, but BD-I parents had completed higher educational levels.
ConclusionsAlthough BD-I patients had a lower IQ than controls, they were more likely to have completed the highest level of education. This contrasts with SCZ patients, who showed both intellectual and educational deficits compared to healthy controls. Since relatives of BD-I patients did not demonstrate superior educational performance, our data suggest that high educational performance may be a distinctive feature of bipolar disorder patients.
Schizophrenia genetic variants are not associated with intelligence
- A. F. Terwisscha van Scheltinga, S. C. Bakker, N. E. M. van Haren, E. M. Derks, J. E. Buizer-Voskamp, W. Cahn, S. Ripke, R. A. Ophoff, R. S. Kahn
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- Journal:
- Psychological Medicine / Volume 43 / Issue 12 / December 2013
- Published online by Cambridge University Press:
- 15 February 2013, pp. 2563-2570
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Background
Schizophrenia is associated with lower pre-morbid intelligence (IQ) in addition to (pre-morbid) cognitive decline. Both schizophrenia and IQ are highly heritable traits. Therefore, we hypothesized that genetic variants associated with schizophrenia, including copy number variants (CNVs) and a polygenic schizophrenia (risk) score (PSS), may influence intelligence.
MethodIQ was estimated with the Wechsler Adult Intelligence Scale (WAIS). CNVs were determined from single nucleotide polymorphism (SNP) data using the QuantiSNP and PennCNV algorithms. For the PSS, odds ratios for genome-wide SNP data were calculated in a sample collected by the Psychiatric Genome-Wide Association Study (GWAS) Consortium (8690 schizophrenia patients and 11 831 controls). These were used to calculate individual PSSs in our independent sample of 350 schizophrenia patients and 322 healthy controls.
ResultsAlthough significantly more genes were disrupted by deletions in schizophrenia patients compared to controls (p = 0.009), there was no effect of CNV measures on IQ. The PSS was associated with disease status (R2 = 0.055, p = 2.1 × 10−7) and with IQ in the entire sample (R2 = 0.018, p = 0.0008) but the effect on IQ disappeared after correction for disease status.
ConclusionsOur data suggest that rare and common schizophrenia-associated variants do not explain the variation in IQ in healthy subjects or in schizophrenia patients. Thus, reductions in IQ in schizophrenia patients may be secondary to other processes related to schizophrenia risk.
Cannabis use at a young age is associated with psychotic experiences
- C. D. Schubart, W. A. van Gastel, E. J. Breetvelt, S. L. Beetz, R. A. Ophoff, I. E. C. Sommer, R. S. Kahn, M. P. M. Boks
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- Journal:
- Psychological Medicine / Volume 41 / Issue 6 / June 2011
- Published online by Cambridge University Press:
- 07 October 2010, pp. 1301-1310
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Background
Cannabis use is associated with psychosis and a range of subclinical psychiatric symptoms. The strength of this association depends on dosage and age at first use. The current study investigates whether level of cannabis exposure and starting age are associated with specific profiles of subclinical symptoms.
MethodWe collected cross-sectional data from a young adult population sample by administering an online version of the Community Assessment of Psychic Experiences (CAPE). Cannabis exposure was quantified as the amount of Euros spent on cannabis per week and the age of initial cannabis use. The primary outcome measure was the odds ratio (OR) to belong to the highest 10% of scores on the total CAPE and the positive-, negative- and depressive symptom dimensions.
ResultsIn 17 698 adolescents (mean age 21.6, s.d.=4.2 years), cannabis use at age 12 years or younger was strongly associated with a top 10% score on psychotic experiences [OR 3.1, 95% confidence interval (CI) 2.1–4.3] and to a lesser degree with negative symptoms (OR 1.7, 95% CI 1.1–2.5). The OR of heavy users (>€25/week) for negative symptoms was 3.4 (95% CI 2.9–4.1), for psychotic experiences 3.0 (95% CI 2.4–3.6), and for depressive symptoms 2.8 (95% CI 2.3–3.3).
ConclusionsEarly start of cannabis use is strongly associated with subclinical psychotic symptoms and to a lesser degree with negative symptoms, while smoking high amounts of cannabis is associated with increased levels of all three symptom dimensions: psychotic, negative and depressive. These results support the hypothesis that the impact of cannabis use is age specific.