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1. Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Author

McWhinney, Sean, Hlinka, Jaroslav, Bakstein, Eduard, Dietze, Lorielle, Corkum, Emily, Abé, Christoph, Alda, Martin, Alexander, Nina, Benedetti, Francesco, Berk, Michael, Bøen, Erlend, Bonnekoh, Linda, Boye, Birgitte, Brosch, Katharina, Canales-Rodríguez, Erick, Cannon, Dara, Dannlowski, Udo, Demro, Caroline, Diaz-Zuluaga, Ana, Elvsåshagen, Torbjørn, Eyler, Lisa, Fortea, Lydia, Fullerton, Janice, Goltermann, Janik, Gotlib, Ian, Grotegerd, Dominik, Haarman, Bartholomeus, Hahn, Tim, Howells, Fleur, Jamalabadi, Hamidreza, Jansen, Andreas, Kircher, Tilo, Klahn, Anna, Kuplicki, Rayus, Lahud, Elijah, Landén, Mikael, Leehr, Elisabeth, Lopez-Jaramillo, Carlos, Mackey, Scott, Malt, Ulrik, Martyn, Fiona, Mazza, Elena, McDonald, Colm, McPhilemy, Genevieve, Meier, Sandra, Meinert, Susanne, Melloni, Elisa, Mitchell, Philip, Nabulsi, Leila, Nenadić, Igor, Nitsch, Robert, Opel, Nils, Ophoff, Roel, Ortuño, Maria, Overs, Bronwyn, Pineda-Zapata, Julian, Pomarol-Clotet, Edith, Radua, Joaquim, Repple, Jonathan, Roberts, Gloria, Rodriguez-Cano, Elena, Sacchet, Matthew, Salvador, Raymond, Savitz, Jonathan, Scheffler, Freda, Schofield, Peter, Schürmeyer, Navid, Shen, Chen, Sim, Kang, Sponheim, Scott, Stein, Dan, Stein, Frederike, Straube, Benjamin, Suo, Chao, Temmingh, Henk, Teutenberg, Lea, Thomas-Odenthal, Florian, Thomopoulos, Sophia, Urosevic, Snezana, Usemann, Paula, van Haren, Neeltje, Vargas, Cristian, Vieta, Eduard, Vilajosana, Enric, Vreeker, Annabel, Winter, Nils, Yatham, Lakshmi, Thompson, Paul, Andreassen, Ole, Ching, Christopher, and Hajek, Tomas

Subjects
MRI, bipolar disorder, body mass index, obesity, principal component analysis, psychiatry, Humans, Bipolar Disorder, Principal Component Analysis, Adult, Female, Male, Magnetic Resonance Imaging, Middle Aged, Obesity, Schizophrenia, Cerebral Cortex, Cluster Analysis, Young Adult, Brain
Abstract

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

Published
2024

2. White matter microstructure in obesity and bipolar disorders: an ENIGMA bipolar disorder working group study in 2186 individuals

Author

Dietze, Lorielle M. F., McWhinney, Sean R., Favre, Pauline, Abé, Christoph, Alexander, Nina, Barkhau, Carlotta, Benedetti, Francesco, Berk, Michael, Bøen, Erlend, Boye, Birgitte, Brosch, Katharina, Canales-Rodríguez, Erick J., Cannon, Dara M., Carruthers, Sean P., Corkum, Emily L. V., Dannlowski, Udo, Díaz-Zuluaga, Ana M., Dohm, Katharina, Elvsåshagen, Torbjørn, Flinkenflügel, Kira, Fortea, Lydia, Furlong, Lisa S., Goldstein, Benjamin I., Grotegerd, Dominik, Gruber, Marius, Haarman, Bartholomeus C. M., Howells, Fleur M., Jahanshad, Neda, Jamalabadi, Hamidreza, Jansen, Andreas, Karantonis, James A., Kennedy, Kody G., Kircher, Tilo T. J., Klahn, Anna Luisa, Kochunov, Peter, Kraus, Anna, Landén, Mikael, López-Jaramillo, Carlos, MacIntosh, Bradley J., Mazza, Elena, McDonald, Colm, McIntosh, Andrew M., Meinert, Hannah, Meinert, Susanne, Melloni, Elisa M. T., Mitchell, Philip B., Nenadić, Igor, Opel, Nils, Phillips, Mary, Piguet, Camille, Polosan, Mircea, Pomarol-Clotet, Edith, Pouchon, Arnaud, Radua, Joaquim, Roberts, Gloria, Ross, Alex J., Rossell, Susan L., Salvador, Raymond, Sim, Kang, Soares, Jair C., Zunta-Soares, Giovana B., Stein, Frederike, Straube, Benjamin, Suo, Chao, Teutenberg, Lea, Thomas-Odenthal, Florian, Thomopoulos, Sophia I., Usemann, Paula, Van Rheenen, Tamsyn E., Versace, Amelia, Vieta, Eduard, Vilajosana, Enric, Mwangi, Benson, Wen, Wei, Whalley, Heather C., Wu, Mon-Ju, Andreassen, Ole A., Ching, Christopher R. K., Thompson, Paul M., Houenou, Josselin, and Hajek, Tomas

Published
2024
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4. Mega-analysis of association between obesity and cortical morphology in bipolar disorders: ENIGMA study in 2832 participants.

Author

Fullerton, Janice, Goikolea, Jose, Goltermann, Janik, Grotegerd, Dominik, Haarman, Bartholomeus, Hahn, Tim, Howells, Fleur, Ingvar, Martin, Jahanshad, Neda, Kircher, Tilo, Krug, Axel, Kuplicki, Rayus, Landén, Mikael, Lemke, Hannah, Liberg, Benny, Lopez-Jaramillo, Carlos, Malt, Ulrik, Martyn, Fiona, Mazza, Elena, McDonald, Colm, McPhilemy, Genevieve, Meier, Sandra, Meinert, Susanne, Meller, Tina, Melloni, Elisa, Mitchell, Philip, Nabulsi, Leila, Nenadic, Igor, Opel, Nils, Ophoff, Roel, Overs, Bronwyn, Pfarr, Julia-Katharina, Pineda-Zapata, Julian, Pomarol-Clotet, Edith, Raduà, Joaquim, Repple, Jonathan, Richter, Maike, Ringwald, Kai, Roberts, Gloria, Ross, Alex, Salvador, Raymond, Savitz, Jonathan, Schmitt, Simon, Schofield, Peter, Sim, Kang, Stein, Dan, Stein, Frederike, Temmingh, Henk, Thiel, Katharina, Thomopoulos, Sophia, van Haren, Neeltje, Vargas, Cristian, Vieta, Eduard, Vreeker, Annabel, Waltemate, Lena, Yatham, Lakshmi, Ching, Christopher, Andreassen, Ole, Thompson, Paul, Hajek, Tomas, McWhinney, Sean, Abé, Christoph, Alda, Martin, Benedetti, Francesco, Bøen, Erlend, Del Mar Bonnin, Caterina, Borgers, Tiana, Brosch, Katharina, Canales-Rodríguez, Erick, Cannon, Dara, Dannlowski, Udo, Diaz-Zuluaga, Ana, Dietze, Lorielle, Elvsåshagen, Torbjørn, and Eyler, Lisa

Subjects
Body mass index, antipsychotics, bipolar disorders, cortical thickness, heterogeneity, lithium, obesity, surface area
Abstract

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.

Published
2023

5. Diagnosis of bipolar disorders and body mass index predict clustering based on similarities in cortical thickness-ENIGMA study in 2436 individuals.

Author

McWhinney, Sean, Abé, Christoph, Alda, Martin, Benedetti, Francesco, Bøen, Erlend, Del Mar Bonnin, Caterina, Borgers, Tiana, Brosch, Katharina, Canales-Rodríguez, Erick, Cannon, Dara, Dannlowski, Udo, Diaz-Zuluaga, Ana, Dietze, Lorielle, Elvsåshagen, Torbjørn, Fullerton, Janice, Goikolea, Jose, Goltermann, Janik, Grotegerd, Dominik, Haarman, Bartholomeus, Hahn, Tim, Howells, Fleur, Ingvar, Martin, Kircher, Tilo, Krug, Axel, Kuplicki, Rayus, Landén, Mikael, Lemke, Hannah, Liberg, Benny, Lopez-Jaramillo, Carlos, Malt, Ulrik, Martyn, Fiona, Mazza, Elena, McDonald, Colm, McPhilemy, Genevieve, Meier, Sandra, Meinert, Susanne, Meller, Tina, Melloni, Elisa, Mitchell, Philip, Nabulsi, Leila, Nenadic, Igor, Opel, Nils, Overs, Bronwyn, Pfarr, Julia-Katharina, Pineda-Zapata, Julian, Pomarol-Clotet, Edith, Raduà, Joaquim, Repple, Jonathan, Richter, Maike, Ringwald, Kai, Roberts, Gloria, Ross, Alex, Salvador, Raymond, Savitz, Jonathan, Schmitt, Simon, Schofield, Peter, Sim, Kang, Stein, Dan, Stein, Frederike, Temmingh, Henk, Thiel, Katharina, Thomopoulos, Sophia, van Haren, Neeltje, Van Gestel, Holly, Vargas, Cristian, Vieta, Eduard, Vreeker, Annabel, Waltemate, Lena, Yatham, Lakshmi, Ching, Christopher, Andreassen, Ole, Thompson, Paul, Hajek, Tomas, Ophoff, Roel, and Eyler, Lisa

Subjects
bipolar disorders, body mass index, cortical thickness, heterogeneity, obesity, surface area, Bipolar Disorder, Body Mass Index, Cluster Analysis, Humans, Magnetic Resonance Imaging, Obesity, Temporal Lobe
Abstract

AIMS: Rates of obesity have reached epidemic proportions, especially among people with psychiatric disorders. While the effects of obesity on the brain are of major interest in medicine, they remain markedly under-researched in psychiatry. METHODS: We obtained body mass index (BMI) and magnetic resonance imaging-derived regional cortical thickness, surface area from 836 bipolar disorders (BD) and 1600 control individuals from 14 sites within the ENIGMA-BD Working Group. We identified regionally specific profiles of cortical thickness using K-means clustering and studied clinical characteristics associated with individual cortical profiles. RESULTS: We detected two clusters based on similarities among participants in cortical thickness. The lower thickness cluster (46.8% of the sample) showed thinner cortex, especially in the frontal and temporal lobes and was associated with diagnosis of BD, higher BMI, and older age. BD individuals in the low thickness cluster were more likely to have the diagnosis of bipolar disorder I and less likely to be treated with lithium. In contrast, clustering based on similarities in the cortical surface area was unrelated to BD or BMI and only tracked age and sex. CONCLUSIONS: We provide evidence that both BD and obesity are associated with similar alterations in cortical thickness, but not surface area. The fact that obesity increased the chance of having low cortical thickness could explain differences in cortical measures among people with BD. The thinner cortex in individuals with higher BMI, which was additive and similar to the BD-associated alterations, may suggest that treating obesity could lower the extent of cortical thinning in BD.

Published
2022

6. In vivo hippocampal subfield volumes in bipolar disorder—A mega‐analysis from The Enhancing Neuro Imaging Genetics through Meta‐Analysis Bipolar Disorder Working Group

Author

Haukvik, Unn K, Gurholt, Tiril P, Nerland, Stener, Elvsåshagen, Torbjørn, Akudjedu, Theophilus N, Alda, Martin, Alnæs, Dag, Alonso‐Lana, Silvia, Bauer, Jochen, Baune, Bernhard T, Benedetti, Francesco, Berk, Michael, Bettella, Francesco, Bøen, Erlend, Bonnín, Caterina M, Brambilla, Paolo, Canales‐Rodríguez, Erick J, Cannon, Dara M, Caseras, Xavier, Dandash, Orwa, Dannlowski, Udo, Delvecchio, Giuseppe, Díaz‐Zuluaga, Ana M, Erp, Theo GM, Fatjó‐Vilas, Mar, Foley, Sonya F, Förster, Katharina, Fullerton, Janice M, Goikolea, José M, Grotegerd, Dominik, Gruber, Oliver, Haarman, Bartholomeus CM, Haatveit, Beathe, Hajek, Tomas, Hallahan, Brian, Harris, Mathew, Hawkins, Emma L, Howells, Fleur M, Hülsmann, Carina, Jahanshad, Neda, Jørgensen, Kjetil N, Kircher, Tilo, Krämer, Bernd, Krug, Axel, Kuplicki, Rayus, Lagerberg, Trine V, Lancaster, Thomas M, Lenroot, Rhoshel K, Lonning, Vera, López‐Jaramillo, Carlos, Malt, Ulrik F, McDonald, Colm, McIntosh, Andrew M, McPhilemy, Genevieve, Meer, Dennis, Melle, Ingrid, Melloni, Elisa MT, Mitchell, Philip B, Nabulsi, Leila, Nenadić, Igor, Oertel, Viola, Oldani, Lucio, Opel, Nils, Otaduy, Maria CG, Overs, Bronwyn J, Pineda‐Zapata, Julian A, Pomarol‐Clotet, Edith, Radua, Joaquim, Rauer, Lisa, Redlich, Ronny, Repple, Jonathan, Rive, Maria M, Roberts, Gloria, Ruhe, Henricus G, Salminen, Lauren E, Salvador, Raymond, Sarró, Salvador, Savitz, Jonathan, Schene, Aart H, Sim, Kang, Soeiro‐de‐Souza, Marcio G, Stäblein, Michael, Stein, Dan J, Stein, Frederike, Tamnes, Christian K, Temmingh, Henk S, Thomopoulos, Sophia I, Veltman, Dick J, Vieta, Eduard, Waltemate, Lena, Westlye, Lars T, Whalley, Heather C, Sämann, Philipp G, Thompson, Paul M, Ching, Christopher RK, Andreassen, Ole A, Agartz, Ingrid, and Group, ENIGMA Bipolar Disorder Working

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Brain Disorders, Mental Health, Serious Mental Illness, Neurosciences, Biomedical Imaging, Bipolar Disorder, Mental health, Genetics, Hippocampus, Humans, Magnetic Resonance Imaging, Neuroimaging, ENIGMA Bipolar Disorder Working Group, bipolar disorder subtype, hippocampus, large-scale, lithium, psychosis, structural brain MRI, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta-Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1-weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed-effects models and mega-analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = -0.20), cornu ammonis (CA)1 (d = -0.18), CA2/3 (d = -0.11), CA4 (d = -0.19), molecular layer (d = -0.21), granule cell layer of dentate gyrus (d = -0.21), hippocampal tail (d = -0.10), subiculum (d = -0.15), presubiculum (d = -0.18), and hippocampal amygdala transition area (d = -0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non-users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.

Published
2022

7. Reproducibility in the absence of selective reporting: An illustration from large‐scale brain asymmetry research

Author

Kong, Xiang‐Zhen, Mathias, Samuel R, Guadalupe, Tulio, Abé, Christoph, Agartz, Ingrid, Akudjedu, Theophilus N, Aleman, Andre, Alhusaini, Saud, Allen, Nicholas B, Ames, David, Andreassen, Ole A, Vasquez, Alejandro Arias, Armstrong, Nicola J, Asherson, Phil, Bergo, Felipe, Bastin, Mark E, Batalla, Albert, Bauer, Jochen, Baune, Bernhard T, Baur‐Streubel, Ramona, Biederman, Joseph, Blaine, Sara K, Boedhoe, Premika, Bøen, Erlend, Bose, Anushree, Bralten, Janita, Brandeis, Daniel, Brem, Silvia, Brodaty, Henry, Yüksel, Dilara, Brooks, Samantha J, Buitelaar, Jan, Bürger, Christian, Bülow, Robin, Calhoun, Vince, Calvo, Anna, Canales‐Rodríguez, Erick Jorge, Cannon, Dara M, Caparelli, Elisabeth C, Castellanos, Francisco X, Cendes, Fernando, Chaim‐Avancini, Tiffany Moukbel, Chantiluke, Kaylita, Chen, Qun‐lin, Chen, Xiayu, Cheng, Yuqi, Christakou, Anastasia, Clark, Vincent P, Coghill, David, Connolly, Colm G, Conzelmann, Annette, Córdova‐Palomera, Aldo, Cousijn, Janna, Crow, Tim, Cubillo, Ana, Dannlowski, Udo, de Bruttopilo, Sara Ambrosino, de Zeeuw, Patrick, Deary, Ian J, Demeter, Damion V, Di Martino, Adriana, Dickie, Erin W, Dietsche, Bruno, Doan, Nhat Trung, Doherty, Colin P, Doyle, Alysa, Durston, Sarah, Earl, Eric, Ehrlich, Stefan, Ekman, Carl Johan, Elvsåshagen, Torbjørn, Epstein, Jeffery N, Fair, Damien A, Faraone, Stephen V, Fernández, Guillén, Flint, Claas, Filho, Geraldo Busatto, Förster, Katharina, Fouche, Jean‐Paul, Foxe, John J, Frodl, Thomas, Fuentes‐Claramonte, Paola, Fullerton, Janice M, Garavan, Hugh, do Santos Garcia, Danielle, Gotlib, Ian H, Goudriaan, Anna E, Grabe, Hans Jörgen, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gurholt, Tiril, Haavik, Jan, Hahn, Tim, Hansell, Narelle K, Harris, Mathew A, Hartman, Catharina A, del Carmen Valdés Hernández, Maria, and Heslenfeld, Dirk

Subjects
Biological Psychology, Psychology, Neurosciences, Neurological, Adolescent, Adult, Aged, Brain Cortical Thickness, Cerebral Cortex, Datasets as Topic, Humans, Magnetic Resonance Imaging, Middle Aged, Multicenter Studies as Topic, Neuroimaging, Publication Bias, Reproducibility of Results, Young Adult, ENIGMA Laterality Working Group, P-hacking, multisite collaboration, publication bias, reproducibility, team science, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes.

Published
2022

8. What we learn about bipolar disorder from large‐scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group

Author

Ching, Christopher RK, Hibar, Derrek P, Gurholt, Tiril P, Nunes, Abraham, Thomopoulos, Sophia I, Abé, Christoph, Agartz, Ingrid, Brouwer, Rachel M, Cannon, Dara M, Zwarte, Sonja MC, Eyler, Lisa T, Favre, Pauline, Hajek, Tomas, Haukvik, Unn K, Houenou, Josselin, Landén, Mikael, Lett, Tristram A, McDonald, Colm, Nabulsi, Leila, Patel, Yash, Pauling, Melissa E, Paus, Tomas, Radua, Joaquim, Soeiro‐de‐Souza, Marcio G, Tronchin, Giulia, Haren, Neeltje EM, Vieta, Eduard, Walter, Henrik, Zeng, Ling‐Li, Alda, Martin, Almeida, Jorge, Alnæs, Dag, Alonso‐Lana, Silvia, Altimus, Cara, Bauer, Michael, Baune, Bernhard T, Bearden, Carrie E, Bellani, Marcella, Benedetti, Francesco, Berk, Michael, Bilderbeck, Amy C, Blumberg, Hilary P, Bøen, Erlend, Bollettini, Irene, Bonnin, Caterina Mar, Brambilla, Paolo, Canales‐Rodríguez, Erick J, Caseras, Xavier, Dandash, Orwa, Dannlowski, Udo, Delvecchio, Giuseppe, Díaz‐Zuluaga, Ana M, Dima, Danai, Duchesnay, Édouard, Elvsåshagen, Torbjørn, Fears, Scott C, Frangou, Sophia, Fullerton, Janice M, Glahn, David C, Goikolea, Jose M, Green, Melissa J, Grotegerd, Dominik, Gruber, Oliver, Haarman, Bartholomeus CM, Henry, Chantal, Howells, Fleur M, Ives‐Deliperi, Victoria, Jansen, Andreas, Kircher, Tilo TJ, Knöchel, Christian, Kramer, Bernd, Lafer, Beny, López‐Jaramillo, Carlos, Machado‐Vieira, Rodrigo, MacIntosh, Bradley J, Melloni, Elisa MT, Mitchell, Philip B, Nenadic, Igor, Nery, Fabiano, Nugent, Allison C, Oertel, Viola, Ophoff, Roel A, Ota, Miho, Overs, Bronwyn J, Pham, Daniel L, Phillips, Mary L, Pineda‐Zapata, Julian A, Poletti, Sara, Polosan, Mircea, Pomarol‐Clotet, Edith, Pouchon, Arnaud, Quidé, Yann, Rive, Maria M, Roberts, Gloria, Ruhe, Henricus G, Salvador, Raymond, Sarró, Salvador, Satterthwaite, Theodore D, Schene, Aart H, and Sim, Kang

Subjects
Serious Mental Illness, Brain Disorders, Biomedical Imaging, Bipolar Disorder, Clinical Research, Behavioral and Social Science, Mental Health, Neurosciences, Mental health, Neurological, Good Health and Well Being, Cerebral Cortex, Humans, Magnetic Resonance Imaging, Meta-Analysis as Topic, Multicenter Studies as Topic, Neuroimaging, bipolar disorder, cortical surface area, cortical thickness, ENIGMA, mega-analysis, meta-analysis, MRI, neuroimaging, psychiatry, volume, ENIGMA Bipolar Disorder Working Group, Cognitive Sciences, Experimental Psychology
Abstract

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.

Published
2022

9. Characterisation of age and polarity at onset in bipolar disorder.

Author

Kalman, Janos L, Olde Loohuis, Loes M, Vreeker, Annabel, McQuillin, Andrew, Stahl, Eli A, Ruderfer, Douglas, Grigoroiu-Serbanescu, Maria, Panagiotaropoulou, Georgia, Ripke, Stephan, Bigdeli, Tim B, Stein, Frederike, Meller, Tina, Meinert, Susanne, Pelin, Helena, Streit, Fabian, Papiol, Sergi, Adams, Mark J, Adolfsson, Rolf, Adorjan, Kristina, Agartz, Ingrid, Aminoff, Sofie R, Anderson-Schmidt, Heike, Andreassen, Ole A, Ardau, Raffaella, Aubry, Jean-Michel, Balaban, Ceylan, Bass, Nicholas, Baune, Bernhard T, Bellivier, Frank, Benabarre, Antoni, Bengesser, Susanne, Berrettini, Wade H, Boks, Marco P, Bromet, Evelyn J, Brosch, Katharina, Budde, Monika, Byerley, William, Cervantes, Pablo, Chillotti, Catina, Cichon, Sven, Clark, Scott R, Comes, Ashley L, Corvin, Aiden, Coryell, William, Craddock, Nick, Craig, David W, Croarkin, Paul E, Cruceanu, Cristiana, Czerski, Piotr M, Dalkner, Nina, Dannlowski, Udo, Degenhardt, Franziska, Del Zompo, Maria, DePaulo, J Raymond, Djurovic, Srdjan, Edenberg, Howard J, Eissa, Mariam Al, Elvsåshagen, Torbjørn, Etain, Bruno, Fanous, Ayman H, Fellendorf, Frederike, Fiorentino, Alessia, Forstner, Andreas J, Frye, Mark A, Fullerton, Janice M, Gade, Katrin, Garnham, Julie, Gershon, Elliot, Gill, Michael, Goes, Fernando S, Gordon-Smith, Katherine, Grof, Paul, Guzman-Parra, Jose, Hahn, Tim, Hasler, Roland, Heilbronner, Maria, Heilbronner, Urs, Jamain, Stephane, Jimenez, Esther, Jones, Ian, Jones, Lisa, Jonsson, Lina, Kahn, Rene S, Kelsoe, John R, Kennedy, James L, Kircher, Tilo, Kirov, George, Kittel-Schneider, Sarah, Klöhn-Saghatolislam, Farah, Knowles, James A, Kranz, Thorsten M, Lagerberg, Trine Vik, Landen, Mikael, Lawson, William B, Leboyer, Marion, Li, Qingqin S, Maj, Mario, Malaspina, Dolores, Manchia, Mirko, and Mayoral, Fermin

Subjects
Psychiatric Genomics Consortium (PGC) Bipolar Disorder Working Group, International Consortium on Lithium Genetics, Colombia-US Cross Disorder Collaboration in Psychiatric Genetics, Humans, Bipolar Disorder, Depressive Disorder, Major, Age of Onset, Multifactorial Inheritance, Genome-Wide Association Study, Autism Spectrum Disorder, Bipolar disorder, GWAS, age at onset, polarity at onset, polygenic score, Genetics, Mental Health, Prevention, Brain Disorders, Serious Mental Illness, 2.1 Biological and endogenous factors, Aetiology, Mental health, Good Health and Well Being, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

BackgroundStudying 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.

Published
2021

10. Association between body mass index and subcortical brain volumes in bipolar disorders–ENIGMA study in 2735 individuals

Author

McWhinney, Sean R, Abé, Christoph, Alda, Martin, Benedetti, Francesco, Bøen, Erlend, del Mar Bonnin, Caterina, Borgers, Tiana, Brosch, Katharina, Canales-Rodríguez, Erick J, Cannon, Dara M, Dannlowski, Udo, Díaz-Zuluaga, Ana M, Elvsåshagen, Torbjørn, Eyler, Lisa T, Fullerton, Janice M, Goikolea, Jose M, Goltermann, Janik, Grotegerd, Dominik, Haarman, Bartholomeus CM, Hahn, Tim, Howells, Fleur M, Ingvar, Martin, Kircher, Tilo TJ, Krug, Axel, Kuplicki, Rayus T, Landén, Mikael, Lemke, Hannah, Liberg, Benny, Lopez-Jaramillo, Carlos, Malt, Ulrik F, Martyn, Fiona M, Mazza, Elena, McDonald, Colm, McPhilemy, Genevieve, Meier, Sandra, Meinert, Susanne, Meller, Tina, Melloni, Elisa MT, Mitchell, Philip B, Nabulsi, Leila, Nenadic, Igor, Opel, Nils, Ophoff, Roel A, Overs, Bronwyn J, Pfarr, Julia-Katharina, Pineda-Zapata, Julian A, Pomarol-Clotet, Edith, Raduà, Joaquim, Repple, Jonathan, Richter, Maike, Ringwald, Kai G, Roberts, Gloria, Salvador, Raymond, Savitz, Jonathan, Schmitt, Simon, Schofield, Peter R, Sim, Kang, Stein, Dan J, Stein, Frederike, Temmingh, Henk S, Thiel, Katharina, van Haren, Neeltje EM, Gestel, Holly Van, Vargas, Cristian, Vieta, Eduard, Vreeker, Annabel, Waltemate, Lena, Yatham, Lakshmi N, Ching, Christopher RK, Andreassen, Ole, Thompson, Paul M, and Hajek, Tomas

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Mental Health, Biomedical Imaging, Nutrition, Brain Disorders, Obesity, Neurosciences, Clinical Research, Prevention, Mental health, Amygdala, Bipolar Disorder, Body Mass Index, Brain, Humans, Magnetic Resonance Imaging, ENIGMA Bipolar Disorders Working Group, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles  and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediated by BMI (Z = 2.73, p = 0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.

Published
2021

11. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Author

Han, Laura KM, Dinga, Richard, Hahn, Tim, Ching, Christopher RK, Eyler, Lisa T, Aftanas, Lyubomir, Aghajani, Moji, Aleman, André, Baune, Bernhard T, Berger, Klaus, Brak, Ivan, Filho, Geraldo Busatto, Carballedo, Angela, Connolly, Colm G, Couvy-Duchesne, Baptiste, Cullen, Kathryn R, Dannlowski, Udo, Davey, Christopher G, Dima, Danai, Duran, Fabio LS, Enneking, Verena, Filimonova, Elena, Frenzel, Stefan, Frodl, Thomas, Fu, Cynthia HY, Godlewska, Beata R, Gotlib, Ian H, Grabe, Hans J, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Hall, Geoffrey B, Harrison, Ben J, Hatton, Sean N, Hermesdorf, Marco, Hickie, Ian B, Ho, Tiffany C, Hosten, Norbert, Jansen, Andreas, Kähler, Claas, Kircher, Tilo, Klimes-Dougan, Bonnie, Krämer, Bernd, Krug, Axel, Lagopoulos, Jim, Leenings, Ramona, MacMaster, Frank P, MacQueen, Glenda, McIntosh, Andrew, McLellan, Quinn, McMahon, Katie L, Medland, Sarah E, Mueller, Bryon A, Mwangi, Benson, Osipov, Evgeny, Portella, Maria J, Pozzi, Elena, Reneman, Liesbeth, Repple, Jonathan, Rosa, Pedro GP, Sacchet, Matthew D, Sämann, Philipp G, Schnell, Knut, Schrantee, Anouk, Simulionyte, Egle, Soares, Jair C, Sommer, Jens, Stein, Dan J, Steinsträter, Olaf, Strike, Lachlan T, Thomopoulos, Sophia I, van Tol, Marie-José, Veer, Ilya M, Vermeiren, Robert RJM, Walter, Henrik, van der Wee, Nic JA, van der Werff, Steven JA, Whalley, Heather, Winter, Nils R, Wittfeld, Katharina, Wright, Margaret J, Wu, Mon-Ju, Völzke, Henry, Yang, Tony T, Zannias, Vasileios, de Zubicaray, Greig I, Zunta-Soares, Giovana B, Abé, Christoph, Alda, Martin, Andreassen, Ole A, Bøen, Erlend, Bonnin, Caterina M, Canales-Rodriguez, Erick J, Cannon, Dara, Caseras, Xavier, Chaim-Avancini, Tiffany M, Elvsåshagen, Torbjørn, Favre, Pauline, Foley, Sonya F, and Fullerton, Janice M

Subjects
Depression, Aging, Brain Disorders, Biomedical Imaging, Serious Mental Illness, Mental Health, Major Depressive Disorder, Behavioral and Social Science, Clinical Research, Neurosciences, 2.3 Psychological, social and economic factors, Aetiology, Mental health, Adolescent, Adult, Aged, Brain, Depressive Disorder, Major, Female, Humans, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Young Adult, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Published
2021

13. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

Author

Mullins, Niamh, Forstner, Andreas J, O’Connell, Kevin S, Coombes, Brandon, Coleman, Jonathan RI, Qiao, Zhen, Als, Thomas D, Bigdeli, Tim B, Børte, Sigrid, Bryois, Julien, Charney, Alexander W, Drange, Ole Kristian, Gandal, Michael J, Hagenaars, Saskia P, Ikeda, Masashi, Kamitaki, Nolan, Kim, Minsoo, Krebs, Kristi, Panagiotaropoulou, Georgia, Schilder, Brian M, Sloofman, Laura G, Steinberg, Stacy, Trubetskoy, Vassily, Winsvold, Bendik S, Won, Hong-Hee, Abramova, Liliya, Adorjan, Kristina, Agerbo, Esben, Al Eissa, Mariam, Albani, Diego, Alliey-Rodriguez, Ney, Anjorin, Adebayo, Antilla, Verneri, Antoniou, Anastasia, Awasthi, Swapnil, Baek, Ji Hyun, Bækvad-Hansen, Marie, Bass, Nicholas, Bauer, Michael, Beins, Eva C, Bergen, Sarah E, Birner, Armin, Bøcker Pedersen, Carsten, Bøen, Erlend, Boks, Marco P, Bosch, Rosa, Brum, Murielle, Brumpton, Ben M, Brunkhorst-Kanaan, Nathalie, Budde, Monika, Bybjerg-Grauholm, Jonas, Byerley, William, Cairns, Murray, Casas, Miquel, Cervantes, Pablo, Clarke, Toni-Kim, Cruceanu, Cristiana, Cuellar-Barboza, Alfredo, Cunningham, Julie, Curtis, David, Czerski, Piotr M, Dale, Anders M, Dalkner, Nina, David, Friederike S, Degenhardt, Franziska, Djurovic, Srdjan, Dobbyn, Amanda L, Douzenis, Athanassios, Elvsåshagen, Torbjørn, Escott-Price, Valentina, Ferrier, I Nicol, Fiorentino, Alessia, Foroud, Tatiana M, Forty, Liz, Frank, Josef, Frei, Oleksandr, Freimer, Nelson B, Frisén, Louise, Gade, Katrin, Garnham, Julie, Gelernter, Joel, Giørtz Pedersen, Marianne, Gizer, Ian R, Gordon, Scott D, Gordon-Smith, Katherine, Greenwood, Tiffany A, Grove, Jakob, Guzman-Parra, José, Ha, Kyooseob, Haraldsson, Magnus, Hautzinger, Martin, Heilbronner, Urs, Hellgren, Dennis, Herms, Stefan, Hoffmann, Per, Holmans, Peter A, Huckins, Laura, Jamain, Stéphane, Johnson, Jessica S, and Kalman, Janos L

Subjects
Biological Sciences, Genetics, Biotechnology, Serious Mental Illness, Human Genome, Bipolar Disorder, Neurosciences, Brain Disorders, Mental Health, Aetiology, 2.1 Biological and endogenous factors, Neurological, Mental health, Good Health and Well Being, Case-Control Studies, Chromosomes, Human, Genetic Predisposition to Disease, Genome, Human, Genome-Wide Association Study, Humans, Major Histocompatibility Complex, Multifactorial Inheritance, Phenotype, Quantitative Trait Loci, Risk Factors, HUNT All-In Psychiatry, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

Published
2021

15. Relationship between function and structure in the visual cortex in healthy individuals and in patients with severe mental disorders

Author

Slapø, Nora Berz, Jørgensen, Kjetil Nordbø, Elvsåshagen, Torbjørn, Nerland, Stener, Roelfs, Daniel, Valstad, Mathias, Timpe, Clara M.F., Richard, Geneviève, Beck, Dani, Sæther, Linn Sofie, Frogner Werner, Maren C., Lagerberg, Trine Vik, Andreassen, Ole A., Melle, Ingrid, Agartz, Ingrid, Westlye, Lars T., Moberget, Torgeir, and Jönsson, Erik G.

Published
2023
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16. Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Author

Nunes, Abraham, Schnack, Hugo G, Ching, Christopher RK, Agartz, Ingrid, Akudjedu, Theophilus N, Alda, Martin, Alnæs, Dag, Alonso-Lana, Silvia, Bauer, Jochen, Baune, Bernhard T, Bøen, Erlend, Bonnin, Caterina del Mar, Busatto, Geraldo F, Canales-Rodríguez, Erick J, Cannon, Dara M, Caseras, Xavier, Chaim-Avancini, Tiffany M, Dannlowski, Udo, Díaz-Zuluaga, Ana M, Dietsche, Bruno, Doan, Nhat Trung, Duchesnay, Edouard, Elvsåshagen, Torbjørn, Emden, Daniel, Eyler, Lisa T, Fatjó-Vilas, Mar, Favre, Pauline, Foley, Sonya F, Fullerton, Janice M, Glahn, David C, Goikolea, Jose M, Grotegerd, Dominik, Hahn, Tim, Henry, Chantal, Hibar, Derrek P, Houenou, Josselin, Howells, Fleur M, Jahanshad, Neda, Kaufmann, Tobias, Kenney, Joanne, Kircher, Tilo TJ, Krug, Axel, Lagerberg, Trine V, Lenroot, Rhoshel K, López-Jaramillo, Carlos, Machado-Vieira, Rodrigo, Malt, Ulrik F, McDonald, Colm, Mitchell, Philip B, Mwangi, Benson, Nabulsi, Leila, Opel, Nils, Overs, Bronwyn J, Pineda-Zapata, Julian A, Pomarol-Clotet, Edith, Redlich, Ronny, Roberts, Gloria, Rosa, Pedro G, Salvador, Raymond, Satterthwaite, Theodore D, Soares, Jair C, Stein, Dan J, Temmingh, Henk S, Trappenberg, Thomas, Uhlmann, Anne, van Haren, Neeltje EM, Vieta, Eduard, Westlye, Lars T, Wolf, Daniel H, Yüksel, Dilara, Zanetti, Marcus V, Andreassen, Ole A, Thompson, Paul M, and Hajek, Tomas

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Brain Disorders, Biomedical Imaging, Neurosciences, Mental Health, Clinical Research, Mental health, Bipolar Disorder, Brain, Humans, Machine Learning, Magnetic Resonance Imaging, Neuroimaging, ENIGMA Bipolar Disorders Working Group, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47-67.00, ROC-AUC = 71.49%, 95% CI = 69.39-73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70-60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen's Kappa = 0.83, 95% CI = 0.829-0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.

Published
2020

18. Common brain disorders are associated with heritable patterns of apparent aging of the brain

Author

Kaufmann, Tobias, van der Meer, Dennis, Doan, Nhat Trung, Schwarz, Emanuel, Lund, Martina J, Agartz, Ingrid, Alnæs, Dag, Barch, Deanna M, Baur-Streubel, Ramona, Bertolino, Alessandro, Bettella, Francesco, Beyer, Mona K, Bøen, Erlend, Borgwardt, Stefan, Brandt, Christine L, Buitelaar, Jan, Celius, Elisabeth G, Cervenka, Simon, Conzelmann, Annette, Córdova-Palomera, Aldo, Dale, Anders M, de Quervain, Dominique JF, Di Carlo, Pasquale, Djurovic, Srdjan, Dørum, Erlend S, Eisenacher, Sarah, Elvsåshagen, Torbjørn, Espeseth, Thomas, Fatouros-Bergman, Helena, Flyckt, Lena, Franke, Barbara, Frei, Oleksandr, Haatveit, Beathe, Håberg, Asta K, Harbo, Hanne F, Hartman, Catharina A, Heslenfeld, Dirk, Hoekstra, Pieter J, Høgestøl, Einar A, Jernigan, Terry L, Jonassen, Rune, Jönsson, Erik G, Kirsch, Peter, Kłoszewska, Iwona, Kolskår, Knut K, Landrø, Nils Inge, Le Hellard, Stephanie, Lesch, Klaus-Peter, Lovestone, Simon, Lundervold, Arvid, Lundervold, Astri J, Maglanoc, Luigi A, Malt, Ulrik F, Mecocci, Patrizia, Melle, Ingrid, Meyer-Lindenberg, Andreas, Moberget, Torgeir, Norbom, Linn B, Nordvik, Jan Egil, Nyberg, Lars, Oosterlaan, Jaap, Papalino, Marco, Papassotiropoulos, Andreas, Pauli, Paul, Pergola, Giulio, Persson, Karin, Richard, Geneviève, Rokicki, Jaroslav, Sanders, Anne-Marthe, Selbæk, Geir, Shadrin, Alexey A, Smeland, Olav B, Soininen, Hilkka, Sowa, Piotr, Steen, Vidar M, Tsolaki, Magda, Ulrichsen, Kristine M, Vellas, Bruno, Wang, Lei, Westman, Eric, Ziegler, Georg C, Zink, Mathias, Andreassen, Ole A, and Westlye, Lars T

Subjects
Biological Psychology, Psychology, Rare Diseases, Mental Health, Neurosciences, Brain Disorders, Biomedical Imaging, Aging, Aetiology, 2.3 Psychological, social and economic factors, 1.1 Normal biological development and functioning, Underpinning research, Mental health, Neurological, Adolescent, Adult, Aged, Aged, 80 and over, Algorithms, Brain, Brain Diseases, Child, Child, Preschool, Female, Genome-Wide Association Study, Humans, Infant, Magnetic Resonance Imaging, Male, Mental Disorders, Middle Aged, Neuropsychological Tests, Schizophrenia, Sex Characteristics, Young Adult, Karolinska Schizophrenia Project, Cognitive Sciences, Neurology & Neurosurgery, Biological psychology
Abstract

Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3-96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.

Published
2019

19. Genome-wide association study identifies 30 loci associated with bipolar disorder

Author

Stahl, Eli A, Breen, Gerome, Forstner, Andreas J, McQuillin, Andrew, Ripke, Stephan, Trubetskoy, Vassily, Mattheisen, Manuel, Wang, Yunpeng, Coleman, Jonathan RI, Gaspar, Héléna A, de Leeuw, Christiaan A, Steinberg, Stacy, Pavlides, Jennifer M Whitehead, Trzaskowski, Maciej, Byrne, Enda M, Pers, Tune H, Holmans, Peter A, Richards, Alexander L, Abbott, Liam, Agerbo, Esben, Akil, Huda, Albani, Diego, Alliey-Rodriguez, Ney, Als, Thomas D, Anjorin, Adebayo, Antilla, Verneri, Awasthi, Swapnil, Badner, Judith A, Bækvad-Hansen, Marie, Barchas, Jack D, Bass, Nicholas, Bauer, Michael, Belliveau, Richard, Bergen, Sarah E, Pedersen, Carsten Bøcker, Bøen, Erlend, Boks, Marco P, Boocock, James, Budde, Monika, Bunney, William, Burmeister, Margit, Bybjerg-Grauholm, Jonas, Byerley, William, Casas, Miquel, Cerrato, Felecia, Cervantes, Pablo, Chambert, Kimberly, Charney, Alexander W, Chen, Danfeng, Churchhouse, Claire, Clarke, Toni-Kim, Coryell, William, Craig, David W, Cruceanu, Cristiana, Curtis, David, Czerski, Piotr M, Dale, Anders M, de Jong, Simone, Degenhardt, Franziska, Del-Favero, Jurgen, DePaulo, J Raymond, Djurovic, Srdjan, Dobbyn, Amanda L, Dumont, Ashley, Elvsåshagen, Torbjørn, Escott-Price, Valentina, Fan, Chun Chieh, Fischer, Sascha B, Flickinger, Matthew, Foroud, Tatiana M, Forty, Liz, Frank, Josef, Fraser, Christine, Freimer, Nelson B, Frisén, Louise, Gade, Katrin, Gage, Diane, Garnham, Julie, Giambartolomei, Claudia, Pedersen, Marianne Giørtz, Goldstein, Jaqueline, Gordon, Scott D, Gordon-Smith, Katherine, Green, Elaine K, Green, Melissa J, Greenwood, Tiffany A, Grove, Jakob, Guan, Weihua, Guzman-Parra, José, Hamshere, Marian L, Hautzinger, Martin, Heilbronner, Urs, Herms, Stefan, Hipolito, Maria, Hoffmann, Per, Holland, Dominic, Huckins, Laura, Jamain, Stéphane, Johnson, Jessica S, and Juréus, Anders

Subjects
Biological Sciences, Genetics, Serious Mental Illness, Mental Health, Human Genome, Brain Disorders, Schizophrenia, Aetiology, 2.1 Biological and endogenous factors, Mental health, Bipolar Disorder, Case-Control Studies, Depressive Disorder, Major, Female, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Polymorphism, Single Nucleotide, Psychotic Disorders, Systems Biology, eQTLGen Consortium, BIOS Consortium, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P

Published
2019

20. Alterations in Schizophrenia-Associated Genes Can Lead to Increased Power in Delta Oscillations

Author

Mäki-Marttunen, Tuomo, Krull, Florian, Bettella, Francesco, Hagen, Espen, Næss, Solveig, Ness, Torbjørn V, Moberget, Torgeir, Elvsåshagen, Torbjørn, Metzner, Christoph, Devor, Anna, Edwards, Andrew G, Fyhn, Marianne, Djurovic, Srdjan, Dale, Anders M, Andreassen, Ole A, and Einevoll, Gaute T

Subjects
Human Genome, Neurosciences, Serious Mental Illness, Mental Health, Schizophrenia, Genetics, Brain Disorders, 1.1 Normal biological development and functioning, Underpinning research, Aetiology, 2.1 Biological and endogenous factors, Adult, Animals, Delta Rhythm, Female, Genetic Variation, Humans, Male, Mice, Models, Neurological, Nerve Net, Visual Cortex, Young Adult, forward modeling of EEG, functional genomics, ion channels, multicompartmental neuron modeling, schizophrenia genetics, Psychology, Cognitive Sciences, Experimental Psychology
Abstract

Genome-wide association studies have implicated many ion channels in schizophrenia pathophysiology. Although the functions of these channels are relatively well characterized by single-cell studies, the contributions of common variation in these channels to neurophysiological biomarkers and symptoms of schizophrenia remain elusive. Here, using computational modeling, we show that a common biomarker of schizophrenia, namely, an increase in delta-oscillation power, may be a direct consequence of altered expression or kinetics of voltage-gated ion channels or calcium transporters. Our model of a circuit of layer V pyramidal cells highlights multiple types of schizophrenia-related variants that contribute to altered dynamics in the delta-frequency band. Moreover, our model predicts that the same membrane mechanisms that increase the layer V pyramidal cell network gain and response to delta-frequency oscillations may also cause a deficit in a single-cell correlate of the prepulse inhibition, which is a behavioral biomarker highly associated with schizophrenia.

Published
2019

21. Genetic variants associated with longitudinal changes in brain structure across the lifespan

Author

Brouwer, Rachel M., Klein, Marieke, Grasby, Katrina L., Schnack, Hugo G., Jahanshad, Neda, Teeuw, Jalmar, Thomopoulos, Sophia I., Sprooten, Emma, Franz, Carol E., Gogtay, Nitin, Kremen, William S., Panizzon, Matthew S., Olde Loohuis, Loes M., Whelan, Christopher D., Aghajani, Moji, Alloza, Clara, Alnæs, Dag, Artiges, Eric, Ayesa-Arriola, Rosa, Barker, Gareth J., Bastin, Mark E., Blok, Elisabet, Bøen, Erlend, Breukelaar, Isabella A., Bright, Joanna K., Buimer, Elizabeth E. L., Bülow, Robin, Cannon, Dara M., Ciufolini, Simone, Crossley, Nicolas A., Damatac, Christienne G., Dazzan, Paola, de Mol, Casper L., de Zwarte, Sonja M. C., Desrivières, Sylvane, Díaz-Caneja, Covadonga M., Doan, Nhat Trung, Dohm, Katharina, Fröhner, Juliane H., Goltermann, Janik, Grigis, Antoine, Grotegerd, Dominik, Han, Laura K. M., Harris, Mathew A., Hartman, Catharina A., Heany, Sarah J., Heindel, Walter, Heslenfeld, Dirk J., Hohmann, Sarah, Ittermann, Bernd, Jansen, Philip R., Janssen, Joost, Jia, Tianye, Jiang, Jiyang, Jockwitz, Christiane, Karali, Temmuz, Keeser, Daniel, Koevoets, Martijn G. J. C., Lenroot, Rhoshel K., Malchow, Berend, Mandl, René C. W., Medel, Vicente, Meinert, Susanne, Morgan, Catherine A., Mühleisen, Thomas W., Nabulsi, Leila, Opel, Nils, de la Foz, Víctor Ortiz-García, Overs, Bronwyn J., Paillère Martinot, Marie-Laure, Redlich, Ronny, Marques, Tiago Reis, Repple, Jonathan, Roberts, Gloria, Roshchupkin, Gennady V., Setiaman, Nikita, Shumskaya, Elena, Stein, Frederike, Sudre, Gustavo, Takahashi, Shun, Thalamuthu, Anbupalam, Tordesillas-Gutiérrez, Diana, van der Lugt, Aad, van Haren, Neeltje E. M., Wardlaw, Joanna M., Wen, Wei, Westeneng, Henk-Jan, Wittfeld, Katharina, Zhu, Alyssa H., Zugman, Andre, Armstrong, Nicola J., Bonfiglio, Gaia, Bralten, Janita, Dalvie, Shareefa, Davies, Gail, Di Forti, Marta, Ding, Linda, Donohoe, Gary, Forstner, Andreas J., Gonzalez-Peñas, Javier, Guimaraes, Joao P. O. F. T., Homuth, Georg, Hottenga, Jouke-Jan, Knol, Maria J., Kwok, John B. J., Le Hellard, Stephanie, Mather, Karen A., Milaneschi, Yuri, Morris, Derek W., Nöthen, Markus M., Papiol, Sergi, Rietschel, Marcella, Santoro, Marcos L., Steen, Vidar M., Stein, Jason L., Streit, Fabian, Tankard, Rick M., Teumer, Alexander, van ‘t Ent, Dennis, van der Meer, Dennis, van Eijk, Kristel R., Vassos, Evangelos, Vázquez-Bourgon, Javier, Witt, Stephanie H., Adams, Hieab H. H., Agartz, Ingrid, Ames, David, Amunts, Katrin, Andreassen, Ole A., Arango, Celso, Banaschewski, Tobias, Baune, Bernhard T., Belangero, Sintia I., Bokde, Arun L. W., Boomsma, Dorret I., Bressan, Rodrigo A., Brodaty, Henry, Buitelaar, Jan K., Cahn, Wiepke, Caspers, Svenja, Cichon, Sven, Crespo-Facorro, Benedicto, Cox, Simon R., Dannlowski, Udo, Elvsåshagen, Torbjørn, Espeseth, Thomas, Falkai, Peter G., Fisher, Simon E., Flor, Herta, Fullerton, Janice M., Garavan, Hugh, Gowland, Penny A., Grabe, Hans J., Hahn, Tim, Heinz, Andreas, Hillegers, Manon, Hoare, Jacqueline, Hoekstra, Pieter J., Ikram, Mohammad A., Jackowski, Andrea P., Jansen, Andreas, Jönsson, Erik G., Kahn, Rene S., Kircher, Tilo, Korgaonkar, Mayuresh S., Krug, Axel, Lemaitre, Herve, Malt, Ulrik F., Martinot, Jean-Luc, McDonald, Colm, Mitchell, Philip B., Muetzel, Ryan L., Murray, Robin M., Nees, Frauke, Nenadić, Igor, Oosterlaan, Jaap, Ophoff, Roel A., Pan, Pedro M., Penninx, Brenda W. J. H., Poustka, Luise, Sachdev, Perminder S., Salum, Giovanni A., Schofield, Peter R., Schumann, Gunter, Shaw, Philip, Sim, Kang, Smolka, Michael N., Stein, Dan J., Trollor, Julian N., van den Berg, Leonard H., Veldink, Jan H., Walter, Henrik, Westlye, Lars T., Whelan, Robert, White, Tonya, Wright, Margaret J., Medland, Sarah E., Franke, Barbara, Thompson, Paul M., and Hulshoff Pol, Hilleke E.

Published
2022
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23. Increased circulating IL-18 levels in severe mental disorders indicate systemic inflammasome activation

Author

Szabo, Attila, O‘Connell, Kevin S., Ueland, Thor, Sheikh, Mashhood A., Agartz, Ingrid, Andreou, Dimitrios, Aukrust, Pål, Boye, Birgitte, Bøen, Erlend, Drange, Ole Kristian, Elvsåshagen, Torbjørn, Engh, John Abel, Hope, Sigrun, Collier Høegh, Margrethe, Joa, Inge, Johnsen, Erik, Kroken, Rune Andreas, Vik Lagerberg, Trine, Lekva, Tove, Malt, Ulrik Fredrik, Melle, Ingrid, Morken, Gunnar, Nærland, Terje, Steen, Vidar Martin, Sørensen, Kjetil, Wedervang-Resell, Kirsten, Auten Weibell, Melissa, Westlye, Lars T., Steen, Nils Eiel, Andreassen, Ole, and Djurovic, Srdjan

Published
2022
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24. Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium

Author

Kong, Xiang-Zhen, Mathias, Samuel R, Guadalupe, Tulio, Glahn, David C, Franke, Barbara, Crivello, Fabrice, Tzourio-Mazoyer, Nathalie, Fisher, Simon E, Thompson, Paul M, Francks, Clyde, Abé, Christoph, Agartz, Ingrid, Akudjedu, Theophilus N, Aleman, Andre, Alhusaini, Saud, Allen, Nicholas B, Ames, David, Andreassen, Ole A, Vasquez, Alejandro Arias, Armstrong, Nicola J, Bergo, Felipe, Bastin, Mark E, Batalla, Albert, Bauer, Jochen, Baune, Bernhard T, Baur-Streubel, Ramona, Biederman, Joseph, Blaine, Sara K, Boedhoe, Premika, Bøen, Erlend, Bose, Anushree, Bralten, Janita, Brandeis, Daniel, Brem, Silvia, Brodaty, Henry, Yüksel, Dilara, Brooks, Samantha J, Buitelaar, Jan, Bürger, Christian, Bülow, Robin, Calhoun, Vince, Calvo, Anna, Canales-Rodríguez, Erick Jorge, Canive, Jose M, Cannon, Dara M, Caparelli, Elisabeth C, Castellanos, Francisco X, Cavalleri, Gianpiero L, Cendes, Fernando, Chaim-Avancini, Tiffany Moukbel, Chantiluke, Kaylita, Chen, Qun-lin, Chen, Xiayu, Cheng, Yuqi, Christakou, Anastasia, Clark, Vincent P, Coghill, David, Connolly, Colm G, Conzelmann, Annette, Córdova-Palomera, Aldo, Cousijn, Janna, Crow, Tim, Cubillo, Ana, Dale, Anders, Dannlowski, Udo, Ambrosino de Bruttopilo, Sara, de Zeeuw, Patrick, Deary, Ian J, Delanty, Norman, Demeter, Damion V, Di Martino, Adriana, Dickie, Erin W, Dietsche, Bruno, Doan, N Trung, Doherty, Colin P, Doyle, Alysa, Durston, Sarah, Earl, Eric, Ehrlich, Stefan, Ekman, Carl Johan, Elvsåshagen, Torbjørn, Epstein, Jeffery N, Fair, Damien A, Faraone, Stephen V, Fernández, Guillén, Filho, Geraldo Busatto, Förster, Katharina, Fouche, Jean-Paul, Foxe, John J, Frodl, Thomas, Fuentes-Claramonte, Paola, Fullerton, Janice, Garavan, Hugh, Garcia, Danielle do Santos, Gotlib, Ian H, Goudriaan, Anna E, and Grabe, Hans Jörgen

Subjects
Neurosciences, Clinical Research, Brain Disorders, Mental Health, Biomedical Imaging, Underpinning research, 1.1 Normal biological development and functioning, Neurological, Mental health, Adolescent, Adult, Aged, Aged, 80 and over, Cerebral Cortex, Child, Child, Preschool, Databases, Factual, Female, Humans, Infant, Male, Middle Aged, Neuroimaging, Young Adult, brain asymmetry, lateralization, cortical thickness, surface area, meta-analysis, ENIGMA Laterality Working Group
Abstract

Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here, the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium presents the largest-ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and intracranial volume. Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets (n = 1,443 and 1,113, respectively), we found several asymmetries showing significant, replicable heritability. The structural asymmetries identified and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders.

Published
2018

28. Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity

Author

Onderzoeksgroep 1, McWhinney, Sean R., Hlinka, Jaroslav, Bakstein, Eduard, Dietze, Lorielle M.F., Corkum, Emily L.V., Abé, Christoph, Alda, Martin, Alexander, Nina, Benedetti, Francesco, Berk, Michael, Bøen, Erlend, Bonnekoh, Linda M., Boye, Birgitte, Brosch, Katharina, Canales-Rodríguez, Erick J., Cannon, Dara M., Dannlowski, Udo, Demro, Caroline, Diaz-Zuluaga, Ana, Elvsåshagen, Torbjørn, Eyler, Lisa T., Fortea, Lydia, Fullerton, Janice M., Goltermann, Janik, Gotlib, Ian H., Grotegerd, Dominik, Haarman, Bartholomeus, Hahn, Tim, Howells, Fleur M., Jamalabadi, Hamidreza, Jansen, Andreas, Kircher, Tilo, Klahn, Anna Luisa, Kuplicki, Rayus, Lahud, Elijah, Landén, Mikael, Leehr, Elisabeth J., Lopez-Jaramillo, Carlos, Mackey, Scott, Malt, Ulrik, Martyn, Fiona, Mazza, Elena, McDonald, Colm, McPhilemy, Genevieve, Meier, Sandra, Meinert, Susanne, Melloni, Elisa, Mitchell, Philip B., Nabulsi, Leila, Nenadić, Igor, Nitsch, Robert, Opel, Nils, Ophoff, Roel A., Ortuño, Maria, Overs, Bronwyn J., Pineda-Zapata, Julian, Pomarol-Clotet, Edith, Radua, Joaquim, Repple, Jonathan, Roberts, Gloria, Rodriguez-Cano, Elena, Sacchet, Matthew D., Salvador, Raymond, Savitz, Jonathan, Scheffler, Freda, Schofield, Peter R., Schürmeyer, Navid, Shen, Chen, Sim, Kang, Sponheim, Scott R., Stein, Dan J., Stein, Frederike, Straube, Benjamin, Suo, Chao, Temmingh, Henk, Teutenberg, Lea, Thomas-Odenthal, Florian, Thomopoulos, Sophia I., Urosevic, Snezana, Usemann, Paula, van Haren, Neeltje E.M., Vargas, Cristian, Vieta, Eduard, Vilajosana, Enric, Vreeker, Annabel, Winter, Nils R., Yatham, Lakshmi N., Thompson, Paul M., Andreassen, Ole A., Ching, Christopher R.K., Hajek, Tomas, Onderzoeksgroep 1, McWhinney, Sean R., Hlinka, Jaroslav, Bakstein, Eduard, Dietze, Lorielle M.F., Corkum, Emily L.V., Abé, Christoph, Alda, Martin, Alexander, Nina, Benedetti, Francesco, Berk, Michael, Bøen, Erlend, Bonnekoh, Linda M., Boye, Birgitte, Brosch, Katharina, Canales-Rodríguez, Erick J., Cannon, Dara M., Dannlowski, Udo, Demro, Caroline, Diaz-Zuluaga, Ana, Elvsåshagen, Torbjørn, Eyler, Lisa T., Fortea, Lydia, Fullerton, Janice M., Goltermann, Janik, Gotlib, Ian H., Grotegerd, Dominik, Haarman, Bartholomeus, Hahn, Tim, Howells, Fleur M., Jamalabadi, Hamidreza, Jansen, Andreas, Kircher, Tilo, Klahn, Anna Luisa, Kuplicki, Rayus, Lahud, Elijah, Landén, Mikael, Leehr, Elisabeth J., Lopez-Jaramillo, Carlos, Mackey, Scott, Malt, Ulrik, Martyn, Fiona, Mazza, Elena, McDonald, Colm, McPhilemy, Genevieve, Meier, Sandra, Meinert, Susanne, Melloni, Elisa, Mitchell, Philip B., Nabulsi, Leila, Nenadić, Igor, Nitsch, Robert, Opel, Nils, Ophoff, Roel A., Ortuño, Maria, Overs, Bronwyn J., Pineda-Zapata, Julian, Pomarol-Clotet, Edith, Radua, Joaquim, Repple, Jonathan, Roberts, Gloria, Rodriguez-Cano, Elena, Sacchet, Matthew D., Salvador, Raymond, Savitz, Jonathan, Scheffler, Freda, Schofield, Peter R., Schürmeyer, Navid, Shen, Chen, Sim, Kang, Sponheim, Scott R., Stein, Dan J., Stein, Frederike, Straube, Benjamin, Suo, Chao, Temmingh, Henk, Teutenberg, Lea, Thomas-Odenthal, Florian, Thomopoulos, Sophia I., Urosevic, Snezana, Usemann, Paula, van Haren, Neeltje E.M., Vargas, Cristian, Vieta, Eduard, Vilajosana, Enric, Vreeker, Annabel, Winter, Nils R., Yatham, Lakshmi N., Thompson, Paul M., Andreassen, Ole A., Ching, Christopher R.K., and Hajek, Tomas

Published
2024

29. Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders—ENIGMA study in people with bipolar disorders and obesity

Author

McWhinney, Sean R., Hlinka, Jaroslav, Bakstein, Eduard, Dietze, Lorielle M.F., Corkum, Emily L.V., Abé, Christoph, Alda, Martin, Alexander, Nina, Benedetti, Francesco, Berk, Michael, Bøen, Erlend, Bonnekoh, Linda M., Boye, Birgitte, Brosch, Katharina, Canales-Rodríguez, Erick J., Cannon, Dara M., Dannlowski, Udo, Demro, Caroline, Diaz-Zuluaga, Ana, Elvsåshagen, Torbjørn, Eyler, Lisa T., Fortea, Lydia, Fullerton, Janice M., Goltermann, Janik, Gotlib, Ian H., Grotegerd, Dominik, Haarman, Bartholomeus, Hahn, Tim, Howells, Fleur M., Jamalabadi, Hamidreza, Jansen, Andreas, Kircher, Tilo, Klahn, Anna Luisa, Kuplicki, Rayus, Lahud, Elijah, Landén, Mikael, Leehr, Elisabeth J., Lopez-Jaramillo, Carlos, Mackey, Scott, Malt, Ulrik, Martyn, Fiona, Mazza, Elena, McDonald, Colm, McPhilemy, Genevieve, Meier, Sandra, Meinert, Susanne, Melloni, Elisa, Mitchell, Philip B., Nabulsi, Leila, Nenadić, Igor, Nitsch, Robert, Opel, Nils, Ophoff, Roel A., Ortuño, Maria, Overs, Bronwyn J., Pineda-Zapata, Julian, Pomarol-Clotet, Edith, Radua, Joaquim, Repple, Jonathan, Roberts, Gloria, Rodriguez-Cano, Elena, Sacchet, Matthew D., Salvador, Raymond, Savitz, Jonathan, Scheffler, Freda, Schofield, Peter R., Schürmeyer, Navid, Shen, Chen, Sim, Kang, Sponheim, Scott R., Stein, Dan J., Stein, Frederike, Straube, Benjamin, Suo, Chao, Temmingh, Henk, Teutenberg, Lea, Thomas-Odenthal, Florian, Thomopoulos, Sophia I., Urosevic, Snezana, Usemann, Paula, van Haren, Neeltje E.M., Vargas, Cristian, Vieta, Eduard, Vilajosana, Enric, Vreeker, Annabel, Winter, Nils R., Yatham, Lakshmi N., Thompson, Paul M., Andreassen, Ole A., Ching, Christopher R.K., Hajek, Tomas, McWhinney, Sean R., Hlinka, Jaroslav, Bakstein, Eduard, Dietze, Lorielle M.F., Corkum, Emily L.V., Abé, Christoph, Alda, Martin, Alexander, Nina, Benedetti, Francesco, Berk, Michael, Bøen, Erlend, Bonnekoh, Linda M., Boye, Birgitte, Brosch, Katharina, Canales-Rodríguez, Erick J., Cannon, Dara M., Dannlowski, Udo, Demro, Caroline, Diaz-Zuluaga, Ana, Elvsåshagen, Torbjørn, Eyler, Lisa T., Fortea, Lydia, Fullerton, Janice M., Goltermann, Janik, Gotlib, Ian H., Grotegerd, Dominik, Haarman, Bartholomeus, Hahn, Tim, Howells, Fleur M., Jamalabadi, Hamidreza, Jansen, Andreas, Kircher, Tilo, Klahn, Anna Luisa, Kuplicki, Rayus, Lahud, Elijah, Landén, Mikael, Leehr, Elisabeth J., Lopez-Jaramillo, Carlos, Mackey, Scott, Malt, Ulrik, Martyn, Fiona, Mazza, Elena, McDonald, Colm, McPhilemy, Genevieve, Meier, Sandra, Meinert, Susanne, Melloni, Elisa, Mitchell, Philip B., Nabulsi, Leila, Nenadić, Igor, Nitsch, Robert, Opel, Nils, Ophoff, Roel A., Ortuño, Maria, Overs, Bronwyn J., Pineda-Zapata, Julian, Pomarol-Clotet, Edith, Radua, Joaquim, Repple, Jonathan, Roberts, Gloria, Rodriguez-Cano, Elena, Sacchet, Matthew D., Salvador, Raymond, Savitz, Jonathan, Scheffler, Freda, Schofield, Peter R., Schürmeyer, Navid, Shen, Chen, Sim, Kang, Sponheim, Scott R., Stein, Dan J., Stein, Frederike, Straube, Benjamin, Suo, Chao, Temmingh, Henk, Teutenberg, Lea, Thomas-Odenthal, Florian, Thomopoulos, Sophia I., Urosevic, Snezana, Usemann, Paula, van Haren, Neeltje E.M., Vargas, Cristian, Vieta, Eduard, Vilajosana, Enric, Vreeker, Annabel, Winter, Nils R., Yatham, Lakshmi N., Thompson, Paul M., Andreassen, Ole A., Ching, Christopher R.K., and Hajek, Tomas

Abstract

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associ

Published
2024

30. Experience-dependent modulation of the visual evoked potential: Testing effect sizes, retention over time, and associations with age in 415 healthy individuals

Author

Valstad, Mathias, Moberget, Torgeir, Roelfs, Daniël, Slapø, Nora B., Timpe, Clara M.F., Beck, Dani, Richard, Geneviève, Sæther, Linn Sofie, Haatveit, Beathe, Skaug, Knut Andre, Nordvik, Jan Egil, Hatlestad-Hall, Christoffer, Einevoll, Gaute T., Mäki-Marttunen, Tuomo, Westlye, Lars T., Jönsson, Erik G., Andreassen, Ole A., and Elvsåshagen, Torbjørn

Published
2020
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31. Genetic mechanisms for impaired synaptic plasticity in schizophrenia revealed by computational modeling.

Author

Mäki-Marttunen, Tuomo, Blackwell, Kim T., Akkouh, Ibrahim, Shadrin, Alexey, Valstad, Mathias, Elvsåshagen, Torbjørn, Linne, Marja-Leena, Djurovic, Srdjan, Einevoll, Gaute T., and Andreassen, Ole A.

Subjects
GENE expression, VISUAL evoked potentials, LONG-term potentiation, NEUROPLASTICITY, CINGULATE cortex
Abstract

Schizophrenia phenotypes are suggestive of impaired cortical plasticity in the disease, but the mechanisms of these deficits are unknown. Genomic association studies have implicated a large number of genes that regulate neuromodulation and plasticity, indicating that the plasticity deficits have a genetic origin. Here, we used biochemically detailed computational modeling of postsynaptic plasticity to investigate how schizophrenia-associated genes regulate long-term potentiation (LTP) and depression (LTD). We combined our model with data from postmortem RNA expression studies (CommonMind gene-expression datasets) to assess the consequences of altered expression of plasticity-regulating genes for the amplitude of LTP and LTD. Our results show that the expression alterations observed post mortem, especially those in the anterior cingulate cortex, lead to impaired protein kinase A (PKA)-pathwaymediated LTP in synapses containing GluR1 receptors. We validated these findings using a genotyped electroencephalogram (EEG) dataset where polygenic risk scores for synaptic and ion channel-encoding genes as well as modulation of visual evoked potentials were determined for 286 healthy controls. Our results provide a possible genetic mechanism for plasticity impairments in schizophrenia, which can lead to improved understanding and, ultimately, treatment of the disorder. [ABSTRACT FROM AUTHOR]

Published
2024
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32. The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls

Author

Byrne, Enda M., Forstner, Andreas J., Holmans, Peter A., de Leeuw, Christiaan A., Mattheisen, Manuel, McQuillin, Andrew, Whitehead Pavlides, Jennifer M., Pers, Tune H., Ripke, Stephan, Stahl, Eli A., Steinberg, Stacy, Trubetskoy, Vassily, Trzaskowski, Maciej, Wang, Yunpeng, Abbott, Liam, Abdellaoui, Abdel, Adams, Mark J., Adolfsson, Annelie Nordin, Agerbo, Esben, Akil, Huda, Albani, Diego, Alliey-Rodriguez, Ney, Als, Thomas D., Andlauer, Till F.M., Anjorin, Adebayo, Antilla, Verneri, Van der Auwera, Sandra, Awasthi, Swapnil, Bacanu, Silviu-Alin, Badner, Judith A., Bækvad-Hansen, Marie, Barchas, Jack D., Bass, Nicholas, Bauer, Michael, Beekman, Aartjan T.F., Belliveau, Richard, Bergen, Sarah E., Bigdeli, Tim B., Binder, Elisabeth B., Bøen, Erlend, Boks, Marco, Boocock, James, Budde, Monika, Bunney, William, Burmeister, Margit, Buttenschøn, Henriette N., Bybjerg-Grauholm, Jonas, Byerley, William, Cai, Na, Casas, Miquel, Castelao, Enrique, Cerrato, Felecia, Cervantes, Pablo, Chambert, Kimberly, Charney, Alexander W., Chen, Danfeng, Christensen, Jane Hvarregaard, Churchhouse, Claire, St Clair, David, Clarke, Toni-Kim, Colodro-Conde, Lucía, Coryell, William, Couvy-Duchesne, Baptiste, Craig, David W., Crawford, Gregory E., Cruceanu, Cristiana, Czerski, Piotr M., Dale, Anders M., Davies, Gail, Deary, Ian J., Degenhardt, Franziska, Del-Favero, Jurgen, DePaulo, J Raymond, Derks, Eske M., Direk, Nese, Djurovic, Srdjan, Dobbyn, Amanda L., Dolan, Conor V., Dumont, Ashley, Dunn, Erin C., Eley, Thalia C., Elvsåshagen, Torbjørn, Escott-Price, Valentina, Fan, Chun Chieh, Finucane, Hilary K., Fischer, Sascha B., Flickinger, Matthew, Foo, Jerome C., Foroud, Tatiana M., Forty, Liz, Frank, Josef, Fraser, Christine, Freimer, Nelson B., Frisén, Louise, Gade, Katrin, Gage, Diane, Garnham, Julie, Giambartolomei, Claudia, Goes, Fernando S., Goldstein, Jaqueline, Gordon, Scott D., Gordon-Smith, Katherine, Green, Elaine K., Green, Melissa J., Greenwood, Tiffany A., Grove, Jakob, Guan, Weihua, Hall, Lynsey S., Hamshere, Marian L., Hansen, Christine Søholm, Hansen, Thomas F., Hautzinger, Martin, Heilbronner, Urs, van Hemert, Albert M., Herms, Stefan, Hickie, Ian B., Hipolito, Maria, Hoffmann, Per, Holland, Dominic, Homuth, Georg, Horn, Carsten, Hottenga, Jouke-Jan, Huckins, Laura, Ising, Marcus, Jamain, Stéphane, Jansen, Rick, Johnson, Jessica S., de Jong, Simone, Jorgenson, Eric, Juréus, Anders, Kandaswamy, Radhika, Karlsson, Robert, Kennedy, James L., Hassan Kiadeh, Farnush Farhadi, Kittel-Schneider, Sarah, Knowles, James A., Kogevinas, Manolis, Kohane, Isaac S., Koller, Anna C., Kraft, Julia, Kretzschmar, Warren W., Krogh, Jesper, Kupka, Ralph, Kutalik, Zoltán, Lavebratt, Catharina, Lawrence, Jacob, Lawson, William B., Leber, Markus, Lee, Phil H., Levy, Shawn E., Li, Jun Z., Li, Yihan, Lind, Penelope A., Liu, Chunyu, Olde Loohuis, Loes M., Maaser, Anna, MacIntyre, Donald J., MacKinnon, Dean F., Mahon, Pamela B., Maier, Wolfgang, Maier, Robert M., Marchini, Jonathan, Martinsson, Lina, Mbarek, Hamdi, McCarroll, Steve, McGrath, Patrick, McGuffin, Peter, McInnis, Melvin G., McKay, James D., Medeiros, Helena, Medland, Sarah E., Mehta, Divya, Meng, Fan, Middeldorp, Christel M., Mihailov, Evelin, Milaneschi, Yuri, Milani, Lili, Mirza, Saira Saeed, Mondimore, Francis M., Montgomery, Grant W., Morris, Derek W., Mostafavi, Sara, Mühleisen, Thomas W., Mullins, Niamh, Nauck, Matthias, Ng, Bernard, Nguyen, Hoang, Nievergelt, Caroline M., Nivard, Michel G., Nwulia, Evaristus A., Nyholt, Dale R., O'Donovan, Claire, O'Reilly, Paul F., Ori, Anil P.S., Oruc, Lilijana, Ösby, Urban, Oskarsson, Hogni, Painter, Jodie N., Parra, José Guzman, Pedersen, Carsten Bøcker, Pedersen, Marianne Giørtz, Perry, Amy, Peterson, Roseann E., Pettersson, Erik, Peyrot, Wouter J., Pfennig, Andrea, Pistis, Giorgio, Purcell, Shaun M., Quiroz, Jorge A., Qvist, Per, Regeer, Eline J., Reif, Andreas, Reinbold, Céline S., Rice, John P., Riley, Brien P., Rivas, Fabio, Rivera, Margarita, Roussos, Panos, Ruderfer, Douglas M., Ryu, Euijung, Sánchez-Mora, Cristina, Schatzberg, Alan F., Scheftner, William A., Schoevers, Robert, Schork, Nicholas J., Schulte, Eva C., Shehktman, Tatyana, Shen, Ling, Shi, Jianxin, Shilling, Paul D., Shyn, Stanley I., Sigurdsson, Engilbert, Slaney, Claire, Smeland, Olav B., Smit, Johannes H., Smith, Daniel J., Sobell, Janet L., Spijker, Anne T., Steffens, Michael, Strauss, John S., Streit, Fabian, Strohmaier, Jana, Szelinger, Szabolcs, Tansey, Katherine E., Teismann, Henning, Teumer, Alexander, Thompson, Robert C., Thompson, Wesley, Thomson, Pippa A., Thorgeirsson, Thorgeir E., Traylor, Matthew, Treutlein, Jens, Uitterlinden, André G., Umbricht, Daniel, Vedder, Helmut, Viktorin, Alexander, Visscher, Peter M., Wang, Weiqing, Watson, Stanley J., Webb, Bradley T., Weickert, Cynthia Shannon, Weickert, Thomas W., Weinsheimer, Shantel Marie, Wellmann, Jürgen, Willemsen, Gonneke, Witt, Stephanie H., Wu, Yang, Xi, Hualin S., Xu, Wei, Yang, Jian, Young, Allan H., Zandi, Peter, Zhang, Peng, Zhang, Futao, Zollner, Sebastian, Adolfsson, Rolf, Agartz, Ingrid, Alda, Martin, Arolt, Volker, Backlund, Lena, Baune, Bernhard T., Bellivier, Frank, Berger, Klaus, Berrettini, Wade H., Biernacka, Joanna M., Blackwood, Douglas H.R., Boehnke, Michael, Boomsma, Dorret I., Corvin, Aiden, Craddock, Nicholas, Daly, Mark J., Dannlowski, Udo, Domenici, Enrico, Domschke, Katharina, Esko, Tõnu, Etain, Bruno, Frye, Mark, Fullerton, Janice M., Gershon, Elliot S., de Geus, E.J.C., Gill, Michael, Goes, Fernando, Grabe, Hans J., Grigoroiu-Serbanescu, Maria, Hamilton, Steven P., Hauser, Joanna, Hayward, Caroline, Heath, Andrew C., Hougaard, David M., Hultman, Christina M., Jones, Ian, Jones, Lisa A., Kahn, René S., Kendler, Kenneth S., Kirov, George, Kloiber, Stefan, Landén, Mikael, Leboyer, Marion, Lewis, Glyn, Li, Qingqin S., Lissowska, Jolanta, Lucae, Susanne, Madden, Pamela A.F., Magnusson, Patrik K., Martin, Nicholas G., Mayoral, Fermin, McElroy, Susan L., McIntosh, Andrew M., McMahon, Francis J., Melle, Ingrid, Metspalu, Andres, Mitchell, Philip B., Morken, Gunnar, Mors, Ole, Mortensen, Preben Bo, Müller-Myhsok, Bertram, Myers, Richard M., Neale, Benjamin M., Nimgaonkar, Vishwajit, Nordentoft, Merete, Nöthen, Markus M., O'Donovan, Michael C., Oedegaard, Ketil J., Owen, Michael J., Paciga, Sara A., Pato, Carlos, Pato, Michele T., Pedersen, Nancy L., Penninx, Brenda W.J. H., Perlis, Roy H., Porteous, David J., Posthuma, Danielle, Potash, James B., Preisig, Martin, Ramos-Quiroga, Josep Antoni, Ribasés, Marta, Rietschel, Marcella, Rouleau, Guy A., Schaefer, Catherine, Schalling, Martin, Schofield, Peter R., Schulze, Thomas G., Serretti, Alessandro, Smoller, Jordan W., Stefansson, Hreinn, Stefansson, Kari, Stordal, Eystein, Tiemeier, Henning, Turecki, Gustavo, Uher, Rudolf, Vaaler, Arne E., Vieta, Eduard, Vincent, John B., Völzke, Henry, Weissman, Myrna M., Werge, Thomas, Andreassen, Ole A., Børglum, Anders D., Cichon, Sven, Edenberg, Howard J., Di Florio, Arianna, Kelsoe, John, Levinson, Douglas F., Lewis, Cathryn M., Nurnberger, John I., Ophoff, Roel A., Scott, Laura J., Sklar, Pamela, Sullivan, Patrick F., Wray, Naomi R., Coleman, Jonathan R.I., Gaspar, Héléna A., Bryois, Julien, and Breen, Gerome

Published
2020
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37. Polygenic overlap and shared genetic loci between loneliness, severe mental disorders, and cardiovascular disease risk factors suggest shared molecular mechanisms

Author

Rødevand, Linn, Bahrami, Shahram, Frei, Oleksandr, Lin, Aihua, Gani, Osman, Shadrin, Alexey, Smeland, Olav B., Connell, Kevin S. O’, Elvsåshagen, Torbjørn, Winterton, Adriano, Quintana, Daniel S., Hindley, Guy F. L., Werner, Maren C. F., Djurovic, Srdjan, Dale, Anders M., Lagerberg, Trine V., Steen, Nils Eiel, and Andreassen, Ole A.

Published
2021
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38. The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

Author

Thompson, Paul M, Stein, Jason L, Medland, Sarah E, Hibar, Derrek P, Vasquez, Alejandro Arias, Renteria, Miguel E, Toro, Roberto, Jahanshad, Neda, Schumann, Gunter, Franke, Barbara, Wright, Margaret J, Martin, Nicholas G, Agartz, Ingrid, Alda, Martin, Alhusaini, Saud, Almasy, Laura, Almeida, Jorge, Alpert, Kathryn, Andreasen, Nancy C, Andreassen, Ole A, Apostolova, Liana G, Appel, Katja, Armstrong, Nicola J, Aribisala, Benjamin, Bastin, Mark E, Bauer, Michael, Bearden, Carrie E, Bergmann, Ørjan, Binder, Elisabeth B, Blangero, John, Bockholt, Henry J, Bøen, Erlend, Bois, Catherine, Boomsma, Dorret I, Booth, Tom, Bowman, Ian J, Bralten, Janita, Brouwer, Rachel M, Brunner, Han G, Brohawn, David G, Buckner, Randy L, Buitelaar, Jan, Bulayeva, Kazima, Bustillo, Juan R, Calhoun, Vince D, Cannon, Dara M, Cantor, Rita M, Carless, Melanie A, Caseras, Xavier, Cavalleri, Gianpiero L, Chakravarty, M Mallar, Chang, Kiki D, Ching, Christopher RK, Christoforou, Andrea, Cichon, Sven, Clark, Vincent P, Conrod, Patricia, Coppola, Giovanni, Crespo-Facorro, Benedicto, Curran, Joanne E, Czisch, Michael, Deary, Ian J, de Geus, Eco JC, den Braber, Anouk, Delvecchio, Giuseppe, Depondt, Chantal, de Haan, Lieuwe, de Zubicaray, Greig I, Dima, Danai, Dimitrova, Rali, Djurovic, Srdjan, Dong, Hongwei, Donohoe, Gary, Duggirala, Ravindranath, Dyer, Thomas D, Ehrlich, Stefan, Ekman, Carl Johan, Elvsåshagen, Torbjørn, Emsell, Louise, Erk, Susanne, Espeseth, Thomas, Fagerness, Jesen, Fears, Scott, Fedko, Iryna, Fernández, Guillén, Fisher, Simon E, Foroud, Tatiana, Fox, Peter T, Francks, Clyde, Frangou, Sophia, Frey, Eva Maria, Frodl, Thomas, Frouin, Vincent, Garavan, Hugh, Giddaluru, Sudheer, Glahn, David C, Godlewska, Beata, Goldstein, Rita Z, Gollub, Randy L, and Grabe, Hans J

Subjects
Biological Psychology, Health Sciences, Psychology, Biomedical Imaging, Neurosciences, Brain Disorders, Schizophrenia, Mental Illness, Mental Health, Genetics, Human Genome, 2.1 Biological and endogenous factors, Mental health, Neurological, Good Health and Well Being, Brain Mapping, Cooperative Behavior, Genome-Wide Association Study, Humans, Meta-Analysis as Topic, Neuroimaging, MRI, GWAS, Consortium, Meta-analysis, Multi-site, Alzheimer’s Disease Neuroimaging Initiative, EPIGEN Consortium, IMAGEN Consortium, Saguenay Youth Study (SYS) Group, Medical and Health Sciences, Psychology and Cognitive Sciences, Experimental Psychology, Biomedical and clinical sciences, Health sciences
Abstract

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Published
2014

41. Baseline long‐term potentiation‐like cortical plasticity is associated with longitudinal cortical thinning in healthy adults and in adults with bipolar disorder type II

Author

Zak, Nathalia, primary, Moberget, Torgeir, additional, Bøen, Erlend, additional, Boye, Birgitte, additional, Rygvold, Trine W., additional, Malt, Ulrik F., additional, Andreassen, Ole A., additional, Andersson, Stein, additional, Westlye, Lars T., additional, and Elvsåshagen, Torbjørn, additional

Published
2023
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42. Corrigendum to “Sleep and sleep deprivation differentially alter white matter microstructure: A mixed model design utilising advanced diffusion modelling”

Author

Voldsbekk, Irene, primary, Groote, Inge, additional, Zak, Nathalia, additional, Roelfs, Daniël, additional, Geier, Oliver, additional, Due-Tønnessen, Paulina, additional, Løkken, Lise-Linn, additional, Strømstad, Marie, additional, Blakstvedt, Taran Y., additional, Kuiper, Yvonne S., additional, Elvsåshagen, Torbjørn, additional, Westlye, Lars T., additional, Bjørnerud, Atle, additional, and Maximov, Ivan I., additional

Published
2023
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44. Auditory Cortex Thickness Is Associated With N100 Amplitude in Schizophrenia Spectrum Disorders

Author

Slapø, Nora Berz, primary, Nerland, Stener, additional, Jørgensen, Kjetil Nordbø, additional, Mørch-Johnsen, Lynn, additional, Pettersen, Johanne Hagen, additional, Roelfs, Daniel, additional, Parker, Nadine, additional, Valstad, Mathias, additional, Pentz, Atle, additional, Timpe, Clara M F, additional, Richard, Geneviève, additional, Beck, Dani, additional, Frogner Werner, Maren C, additional, Lagerberg, Trine Vik, additional, Melle, Ingrid, additional, Agartz, Ingrid, additional, Westlye, Lars T, additional, Steen, Nils Eiel, additional, Andreassen, Ole A, additional, Moberget, Torgeir, additional, Elvsåshagen, Torbjørn, additional, and Jönsson, Erik G, additional

Published
2023
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45. Systemic Cell Adhesion Molecules in Severe Mental Illness: Potential Role of Intercellular CAM-1 in Linking Peripheral and Neuroinflammation

Author

Sheikh, Mashhood A., primary, O’Connell, Kevin S., additional, Lekva, Tove, additional, Szabo, Attila, additional, Akkouh, Ibrahim A., additional, Osete, Jordi Requena, additional, Agartz, Ingrid, additional, Engh, John A., additional, Andreou, Dimitrios, additional, Boye, Birgitte, additional, Bøen, Erlend, additional, Elvsåshagen, Torbjørn, additional, Hope, Sigrun, additional, Frogner Werner, Maren Caroline, additional, Joa, Inge, additional, Johnsen, Erik, additional, Kroken, Rune A., additional, Lagerberg, Trine Vik, additional, Melle, Ingrid, additional, Drange, Ole Kristian, additional, Morken, Gunnar, additional, Nærland, Terje, additional, Sørensen, Kjetil, additional, Vaaler, Arne E., additional, Weibell, Melissa Authen, additional, Westlye, Lars T., additional, Aukrust, Pål, additional, Djurovic, Srdjan, additional, Steen, Nils Eiel, additional, Andreassen, Ole A., additional, and Ueland, Thor, additional

Published
2023
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47. Elevated Systemic Levels of Markers Reflecting Intestinal Barrier Dysfunction and Inflammasome Activation Are Correlated in Severe Mental Illness

Author

Jensen, Søren B, primary, Sheikh, Mashhood A, additional, Akkouh, Ibrahim A, additional, Szabo, Attila, additional, O’Connell, Kevin S, additional, Lekva, Tove, additional, Engh, John A, additional, Agartz, Ingrid, additional, Elvsåshagen, Torbjørn, additional, Ormerod, Monica B E G, additional, Weibell, Melissa A, additional, Johnsen, Erik, additional, Kroken, Rune A, additional, Melle, Ingrid, additional, Drange, Ole K, additional, Nærland, Terje, additional, Vaaler, Arne E, additional, Westlye, Lars T, additional, Aukrust, Pål, additional, Djurovic, Srdjan, additional, Eiel Steen, Nils, additional, Andreassen, Ole A, additional, and Ueland, Thor, additional

Published
2022
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48. Brain age prediction in subjects with sleep deprivation based on the ENIGMA-Sleep data

Author

Hoffstaedter, Felix, Antonopoulos, Georgios, Bajaj, Sahil, Bi, Hanwen, Chu, Congying, Cross, Nathan, Deantoni, Michele, Vu, Thien, Grova, Christophe, Eickhoff, Simon, Elmenhorst, Eva-Maria, Elvsåshagen, Torbjørn, Holst, Sebastian, Jahanshad, Neda, Jegou, Aude, Jones, Richard, Landolt, Hans-Peter, Lekander, Mats, Mohamed, Abdalla, Mortazavi, Nasrin, Nilsonne, Gustav, Olsen, Alexander, Patil, Kaustubh, Peigneux, Philippe, Pomares, Florence, Poudel, Govinda, Raimondo, Federico, Smevik, Hanne, Spiegelhalder, Kai, Tamm, Sandra, Thomopoulos, Sophia, Thompson, Paul, Vandewalle, Gilles, Voldsbekk, Irene, Åkerstedt, Torbjörn, Tahmasian, Masoud, and Elmenhorst, David

Subjects
Sleep Medicine, ENIGMA-Sleep, Neuroscience and Neurobiology, Medicine and Health Sciences, Medical Specialties, Life Sciences, Social and Behavioral Sciences, sleep deprivation
Abstract

Sleep is essential for the maintenance of human physical health (Grandner et al., 2012; Reid et al., 2006), cognitive performance (Ferrie et al., 2011; Leng et al., 2017), and mental health (Freeman et al., 2017; Joao et al., 2018). Experimental sleep deprivation and different degrees of sleep restriction permit the characterization of human sleep behaviors and brain's responses to inadequate sleep (Durmer and Dinges, 2005; Elmenhorst et al., 2017; Elmenhorst et al., 2018; Van Dongen et al., 2003). Sleep disruption is known to impact not only brain functions but also affects brain anatomy; earlier studies found that sleep deprivation is associated with lower volumes of gray matter across various brain regions (Åkerstedt et al., 2020; Liu et al., 2014; Long et al., 2020; Sun et al., 2020), however with inconsistent localization of effects. Other studies reported alterations in white matter microstructure (Elvsåshagen et al., 2015; Voldsbekk et al., 2021), increased ventricles size, and cognitive decline (Lo et al., 2014). In addition, one-night sleep deprivation was found to increase the Aβ burden in the right hippocampus and thalamus of healthy controls (Shokri-Kojori 2018), suggesting an interrupted clearance pathway due to sleep deprivation. These prior studies suggest that sleep deprivation may impact anatomical features of the brain, but there is a need for large-scale replications and extensions of previous work. Increased brain age compared to chronological age is a risk factor for several neurodegenerative and psychiatric disorders (Wyss-Coray, 2016). Brain-age prediction is a widely studied topic that aims to estimate the trajectory of brain aging (Franke et al., 2019), and its association with pathological conditions. MRI-derived features used to predict individuals’ brain age have proven to constitute a proxy for overall health (Habes et al., 2016, Koutsouleris et al., 2014, Cole et al., 2018). Sleep patterns also change with aging. In particular, older adults tend to sleep less, and present a more fragmented sleep with lower slow-wave sleep. They also present a reduced sleep rebound following sleep deprivation, report less sleepiness under acute sleep deprivation conditions, and report a smaller increase in lapses of attention after sleep deprivation [23]. However, little is known on whether brain-age models reflect the impact of sleep deprivation on the brain structure - i.e., the difference between predicted age and real age (so-called brain-age delta) using MRI data. We hypothesized that the morphological alterations associated with sleep deprivation would lead to an increased brain-delta score.

Published
2022
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49. A family study of symbolic learning and synaptic plasticity in autism spectrum disorder

Author

Granerud, Guro, Elvsåshagen, Torbjørn, Arntzen, Erik, Juhasz, Katalin, Emilsen, Nina Merete, Sønderby, Ida Elken, Nærland, Terje, and Malt, Eva Albertsen

Subjects
Behavioral Neuroscience, Psychiatry and Mental health, Neuropsychology and Physiological Psychology, Neurology, Neuropsychology, Autism, Stimulus equivalence, Biological Psychiatry
Abstract

The current study presents a male with autism spectrum disorder (ASD) and a 3q29 deletion, and three healthy first-degree relatives. Our magnetic resonance imaging (MRI) dataset included a healthy control subset. We describe a comprehensive multimodal approach, including equivalence class formation, neurocognitive testing, MRI, and electroencephalography (EEG)-based cortical plasticity, which can provide new insights into socio-communicative and learning impairments and neural underpinnings in ASD. On neurocognitive testing, the proband showed reduced processing speed, attending behavior, and executive function. He required more training trials in equivalence class training compared with family members and exhibited impaired priming of words compared with priming with images. The proband had smaller intracranial volume and surface area and a larger visual evoked potential (VEP) C1 amplitude than family members and intact long-term potentiation (LTP)-like visual cortex plasticity. Together, these results suggest that 3q29 deletion-related ASD is associated with impaired problem-solving strategies in complex socio-communicative and learning tasks, smaller intracranial and surface area, altered VEP amplitude, and normal LTP-like visual cortex plasticity. Further studies are needed to clarify whether this multimodal approach can be used to identify ASD subgroups with distinct neurobiological alterations and to uncover mechanisms underlying socio-communicative and learning impairments.Lay Summary: We studied learning, brain activity, and brain structure in a person with autism and a genetic aberration, and his close relatives. Compared with relatives, the person with autism required more training for learning, and visual learning was better than verbal learning. This person had some changes in the activity of the visual cortex, and the size and the surface area of the brain were reduced. Knowledge about learning and brain mechanisms is valuable for the development of training programs for individuals with autism.

Published
2022

50. Reproducibility in the absence of selective reporting : An illustration from large-scale brain asymmetry research

Author

Kong, Xiang-Zhen, Francks, Clyde, Allen, Nicholas B., Heslenfeld, Dirk, Hester, Robert, Hibar, Derrek Paul, Ho, Beng-Choon, Ho, Tiffany C., Hoekstra, Pieter J., Holst, Ruth J., Hoogman, Martine, Høvik, Marie F., Howells, Fleur M., Ames, David, Hugdahl, Kenneth, Huyser, Chaim, Ingvar, Martin, Ishikawa, Akari, James, Anthony, Jahanshad, Neda, Jernigan, Terry L., Jönsson, Erik G, Kaleda, Vasily, Kelly, Clare, Andreassen, Ole A., Kerich, Michael, Keshavan, Matcheri S., Khadka, Sabin, Kircher, Tilo, Kohls, Gregor, Konrad, Kerstin, Korucuoglu, Ozlem, Krämer, Bernd, Krug, Axel, Kuntsi, Jonna, Vasquez, Alejandro Arias, Kwon, Jun Soo, Lambregts-Rommelse, Nanda, Landén, Mikael, Lázaro, Luisa, Lebedeva, Irina, Lenroot, Rhoshel, Lesch, Klaus-Peter, Li, Qinqin, Lim, Kelvin O., Liu, Jia, Armstrong, Nicola J., Lochner, Christine, London, Edythe D., Lorenzetti, Valentina, Luciano, Michelle, Luijten, Maartje, Lundervold, Astri J., Mackey, Scott, MacMaster, Frank P., Maingault, Sophie, Malpas, Charles B., Asherson, Phil, Malt, Ulrik F., Mataix-Cols, David, Martin-Santos, Rocio, Mayer, Andrew R., McCarthy, Hazel, Medland, Sarah, Metha, Mitul, Mitchell, Philip B., Mueller, Bryon A., Maniega, Susana Muñoz, Bergo, Felipe, Mazoyer, Bernard, McDonald, Colm, McLellan, Quinn, McMahon, Katie L., McPhilemy, Genevieve, Momenan, Reza, Morales, Angelica M., Narayanaswamy, Janardhanan C., Moreira, José Carlos Vasques, Nerland, Stener, Bastin, Mark E., Nestor, Liam, Newman, Erik, Nigg, Joel T., Nordvik, Jan Egil, Novotny, Stephanie, Weiss, Eileen Oberwelland, O'Gorman, Ruth L., Oosterlaan, Jaap, Oranje, Bob, Orr, Catherine, Batalla, Albert, Overs, Bronwyn, Paloyelis, Yannis, Pauli, Paul, Paulus, Martin, Plessen, Kerstin Jessica, Polier, Georg G., Pomarol-Clotet, Edith, Portella, Maria J., Qiu, Jiang, Radua, Joaquim, Bauer, Jochen, Ramos-Quiroga, Josep Antoni, Reddy, Y. C. Janardhan, Reif, Andreas, Roberts, Gloria, Rosa, Pedro, Rubia, Katya, Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Schmaal, Lianne, Baune, Bernhard T, Schulte-Rüther, Martin, Schweren, Lizanne, Seitz, Jochen, Serpa, Mauricio Henriques, Shaw, Philip, Shumskaya, Elena, Silk, Timothy J., Simmons, Alan N., Simulionyte, Egle, Sinha, Rajita, Baur-Streubel, Ramona, Sjoerds, Zsuzsika, Smelror, Runar Elle, Soliva, Joan Carlos, Solowij, Nadia, Souza-Duran, Fabio Luisde, Sponheim, Scott R., Stein, Dan J., Stein, Elliot A., Stevens, Michael, Strike, Lachlan T., Biederman, Joseph, Sudre, Gustavo, Sui, Jing, Tamm, Leanne, Temmingh, Hendrik S., Thoma, Robert J., Tomyshev, Alexander, Tronchin, Giulia, Turner, Jessica, Uhlmann, Anne, Erp, Theo G. M., Blaine, Sara K., Heuvel, Odile A., Meer, Dennis, Eijk, Liza, Vance, Alasdair, Veer, Ilya M., Veltman, Dick J., Venkatasubramanian, Ganesan, Vilarroya, Oscar, Vives-Gilabert, Yolanda, Voineskos, Aristotle N, Boedhoe, Premika, Völzke, Henry, Vuletic, Daniella, Walitza, Susanne, Walter, Henrik, Walton, Esther, Wardlaw, Joanna M., Wen, Wei, Westlye, Lars T., Whelan, Christopher D., White, Tonya, Bøen, Erlend, Wiers, Reinout W., Wright, Margaret J., Wittfeld, Katharina, Yang, Tony T., Yasuda, Clarissa L., Yoncheva, Yuliya, Yücel, Murat, Yun, Je-Yeon, Zanetti, Marcus Vinicius, Zhen, Zonglei, Bose, Anushree, Zhu, Xing-xing, Ziegler, Georg C., Zubicaray, Greig I., Zwiers, Marcel, Project, Karolinska Schizophrenia, Glahn, David C., Crivello, Fabrice, Fisher, Simon E., Thompson, Paul M., Bralten, Janita, Farde, Lars, Flyckt, Lena, Engberg, Göran, Erhardt, Sophie, Fatouros-Bergman, Helena, Cervenka, Simon, Schwieler, Lilly, Piehl, Fredrik, Agartz, Ingrid, Collste, Karin, Brandeis, Daniel, Victorsson, Pauliina, Malmqvist, Anna, Hedberg, Mikael, Orhan, Funda, Sellgren, Carl, Brem, Silvia, Mathias, Samuel R., Brodaty, Henry, Yüksel, Dilara, Brooks, Samantha J., Buitelaar, Jan, Bürger, Christian, Bülow, Robin, Calhoun, Vince, Calvo, Anna, Canales-Rodríguez, Erick Jorge, Cannon, Dara M., Guadalupe, Tulio, Caparelli, Elisabeth C., Castellanos, Francisco X., Cendes, Fernando, Chaim-Avancini, Tiffany Moukbel, Chantiluke, Kaylita, Chen, Qun-lin, Chen, Xiayu, Cheng, Yuqi, Christakou, Anastasia, Clark, Vincent P., Abé, Christoph, Coghill, David, Connolly, Colm G., Conzelmann, Annette, Córdova-Palomera, Aldo, Cousijn, Janna, Crow, Tim, Cubillo, Ana, Dannlowski, Udo, Bruttopilo, Sara Ambrosino, Zeeuw, Patrick, Deary, Ian J., Demeter, Damion V., Di Martino, Adriana, Dickie, Erin W, Dietsche, Bruno, Doan, Nhat Trung, Doherty, Colin P., Doyle, Alysa, Durston, Sarah, Earl, Eric, Akudjedu, Theophilus N., Ehrlich, Stefan, Ekman, Carl Johan, Elvsåshagen, Torbjørn, Epstein, Jeffery N., Fair, Damien A., Faraone, Stephen V., Fernández, Guillén, Flint, Claas, Filho, Geraldo Busatto, Förster, Katharina, Aleman, Andre, Fouche, Jean-Paul, Foxe, John J., Frodl, Thomas, Fuentes-Claramonte, Paola, Fullerton, Janice M., Garavan, Hugh, Santos Garcia, Danielle, Gotlib, Ian H., Goudriaan, Anna E., Grabe, Hans Jörgen, Alhusaini, Saud, Groenewold, Nynke A., Grotegerd, Dominik, Gruber, Oliver, Gurholt, Tiril, Haavik, Jan, Hahn, Tim, Hansell, Narelle K., Harris, Mathew A., Hartman, Catharina A., Carmen Valdés Hernández, Maria, Alhusaini, Saud, Del Carmen Valdés Hernández, Maria, Heslenfeld, Dirk, Hester, Robert, Hibar, Derrek Paul, Ho, Beng-Choon, Ho, Tiffany C., Hoekstra, Pieter J., van Holst, Ruth J., Hoogman, Martine, Høvik, Marie F., Allen, Nicholas B., Howells, Fleur M., Hugdahl, Kenneth, Huyser, Chaim, Ingvar, Martin, Ishikawa, Akari, James, Anthony, Jahanshad, Neda, Jernigan, Terry L., Jönsson, Erik G., Kaleda, Vasily, Ames, David, Kelly, Clare, Kerich, Michael, Keshavan, Matcheri S., Khadka, Sabin, Kircher, Tilo, Kohls, Gregor, Konrad, Kerstin, Korucuoglu, Ozlem, Krämer, Bernd, Krug, Axel, Andreassen, Ole A., Kuntsi, Jonna, Kwon, Jun Soo, Lambregts-Rommelse, Nanda, Landén, Mikael, Lázaro, Luisa, Lebedeva, Irina, Lenroot, Rhoshel, Lesch, Klaus-Peter, Li, Qinqin, Lim, Kelvin O., Vasquez, Alejandro Arias, Liu, Jia, Lochner, Christine, London, Edythe D., Lorenzetti, Valentina, Luciano, Michelle, Luijten, Maartje, Lundervold, Astri J., Mackey, Scott, MacMaster, Frank P., Maingault, Sophie, Armstrong, Nicola J., Malpas, Charles B., Malt, Ulrik F., Mataix-Cols, David, Martin-Santos, Rocio, Mayer, Andrew R., McCarthy, Hazel, Medland, Sarah, Metha, Mitul, Mitchell, Philip B., Mueller, Bryon A., Asherson, Phil, Maniega, Susana Muñoz, Mazoyer, Bernard, McDonald, Colm, McLellan, Quinn, McMahon, Katie L., McPhilemy, Genevieve, Momenan, Reza, Morales, Angelica M., Narayanaswamy, Janardhanan C., Moreira, José Carlos Vasques, Bergo, Felipe, Nerland, Stener, Nestor, Liam, Newman, Erik, Nigg, Joel T., Nordvik, Jan Egil, Novotny, Stephanie, Weiss, Eileen Oberwelland, O'Gorman, Ruth L., Oosterlaan, Jaap, Oranje, Bob, Bastin, Mark E., Orr, Catherine, Overs, Bronwyn, Paloyelis, Yannis, Pauli, Paul, Paulus, Martin, Plessen, Kerstin Jessica, von Polier, Georg G., Pomarol-Clotet, Edith, Portella, Maria J., Qiu, Jiang, Batalla, Albert, Radua, Joaquim, Ramos-Quiroga, Josep Antoni, Reddy, Y. C. Janardhan, Reif, Andreas, Roberts, Gloria, Rosa, Pedro, Rubia, Katya, Sacchet, Matthew D., Sachdev, Perminder S., Salvador, Raymond, Bauer, Jochen, Schmaal, Lianne, Schulte-Rüther, Martin, Schweren, Lizanne, Seitz, Jochen, Serpa, Mauricio Henriques, Shaw, Philip, Shumskaya, Elena, Silk, Timothy J., Simmons, Alan N., Simulionyte, Egle, Baune, Bernhard T., Sinha, Rajita, Sjoerds, Zsuzsika, Smelror, Runar Elle, Soliva, Joan Carlos, Solowij, Nadia, Souza-Duran, Fabio Luisde, Sponheim, Scott R., Stein, Dan J., Stein, Elliot A., Stevens, Michael, Baur-Streubel, Ramona, Strike, Lachlan T., Sudre, Gustavo, Sui, Jing, Tamm, Leanne, Temmingh, Hendrik S., Thoma, Robert J., Tomyshev, Alexander, Tronchin, Giulia, Turner, Jessica, Uhlmann, Anne, Biederman, Joseph, van Erp, Theo G. M., van den Heuvel, Odile A., van der Meer, Dennis, van Eijk, Liza, Vance, Alasdair, Veer, Ilya M., Veltman, Dick J., Venkatasubramanian, Ganesan, Vilarroya, Oscar, Vives-Gilabert, Yolanda, Blaine, Sara K., Voineskos, Aristotle N., Völzke, Henry, Vuletic, Daniella, Walitza, Susanne, Walter, Henrik, Walton, Esther, Wardlaw, Joanna M., Wen, Wei, Westlye, Lars T., Whelan, Christopher D., Boedhoe, Premika, White, Tonya, Wiers, Reinout W., Wright, Margaret J., Wittfeld, Katharina, Yang, Tony T., Yasuda, Clarissa L., Yoncheva, Yuliya, Yücel, Murat, Yun, Je-Yeon, Zanetti, Marcus Vinicius, Bøen, Erlend, Zhen, Zonglei, Zhu, Xing-Xing, Ziegler, Georg C., de Zubicaray, Greig I., Zwiers, Marcel, Project, Karolinska Schizophrenia, Glahn, David C., Crivello, Fabrice, Fisher, Simon E., Thompson, Paul M., Bose, Anushree, Francks, Clyde, Farde, Lars, Flyckt, Lena, Engberg, Göran, Erhardt, Sophie, Fatouros-Bergman, Helena, Cervenka, Simon, Schwieler, Lilly, Piehl, Fredrik, Agartz, Ingrid, Bralten, Janita, Collste, Karin, Victorsson, Pauliina, Malmqvist, Anna, Hedberg, Mikael, Orhan, Funda, Sellgren, Carl, Brandeis, Daniel, Kong, Xiang-Zhen, Brem, Silvia, Brodaty, Henry, Yüksel, Dilara, Brooks, Samantha J., Buitelaar, Jan, Bürger, Christian, Bülow, Robin, Calhoun, Vince, Calvo, Anna, Canales-Rodríguez, Erick Jorge, Mathias, Samuel R., Cannon, Dara M., Caparelli, Elisabeth C., Castellanos, Francisco X., Cendes, Fernando, Chaim-Avancini, Tiffany Moukbel, Chantiluke, Kaylita, Chen, Qun-Lin, Chen, Xiayu, Cheng, Yuqi, Christakou, Anastasia, Guadalupe, Tulio, Clark, Vincent P., Coghill, David, Connolly, Colm G., Conzelmann, Annette, Córdova-Palomera, Aldo, Cousijn, Janna, Crow, Tim, Cubillo, Ana, Dannlowski, Udo, de Bruttopilo, Sara Ambrosino, Abé, Christoph, de Zeeuw, Patrick, Deary, Ian J., Demeter, Damion V., Di Martino, Adriana, Dickie, Erin W., Dietsche, Bruno, Doan, Nhat Trung, Doherty, Colin P., Doyle, Alysa, Durston, Sarah, Earl, Eric, Ehrlich, Stefan, Ekman, Carl Johan, Elvsåshagen, Torbjørn, Epstein, Jeffery N., Fair, Damien A., Faraone, Stephen V., Fernández, Guillén, Flint, Claas, Filho, Geraldo Busatto, Akudjedu, Theophilus N., Förster, Katharina, Fouche, Jean-Paul, Foxe, John J., Frodl, Thomas, Fuentes-Claramonte, Paola, Fullerton, Janice M., Garavan, Hugh, do Santos Garcia, Danielle, Gotlib, Ian H., Goudriaan, Anna E., Aleman, Andre, Grabe, Hans Jörgen, Groenewold, Nynke A., Grotegerd, Dominik, Gruber, Oliver, Gurholt, Tiril, Haavik, Jan, Hahn, Tim, Hansell, Narelle K., Harris, Mathew A., Hartman, Catharina A., Ontwikkelingspsychologie (Psychologie, FMG), Adult Psychiatry, APH - Mental Health, ANS - Compulsivity, Impulsivity & Attention, Child and Adolescent Psychiatry & Psychosocial Care, Child Psychiatry, ANS - Cellular & Molecular Mechanisms, Laboratory Genetic Metabolic Diseases, Paediatrics, General Paediatrics, ARD - Amsterdam Reproduction and Development, Paediatric Pulmonology, Graduate School, and APH - Digital Health

Subjects
P‐hacking, Datasets as Topic, Publication bias, 0302 clinical medicine, 130 000 Cognitive Neurology & Memory, Statistics, team science, Brain asymmetry, Multicenter Studies as Topic, Cervell, Research Articles, Cerebral Cortex, Radiological and Ultrasound Technology, P-hacking, 05 social sciences, Brain, Cerebral cortex, Middle Aged, Magnetic Resonance Imaging, Discoveries in science, Escorça cerebral, Neurology, Biaix de publicació, Anatomy, Psychology, Research Article, Neuroinformatics, Adult, Adolescent, Neuroimaging, Descobriments científics, 050105 experimental psychology, Statistical power, 03 medical and health sciences, Young Adult, Magnetic resonance imaging, Imatges per ressonància magnètica, multisite collaboration, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, ddc:610, reproducibility, Aged, publication bias, Reproducibility, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], Perspective (graphical), Reproducibility of Results, Brain Cortical Thickness, Research data, Sample size determination, Dades de recerca, Neurology (clinical), Scale (map), Developmental Psychopathology, 030217 neurology & neurosurgery
Abstract

The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p‐hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left–right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta‐analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an “ideal publishing environment,” that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically‐used sample sizes., Region‐wise effect sizes and reproducibility rates of hemispheric asymmetry effects. In general, effects with higher effect sizes showed higher reproducibility, given the same conditions (e.g., sample size and data heterogeneity).

Published
2022

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