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1. Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI

Author

Yang, Yunju, Knol, Maria J, Wang, Ruiqi, Mishra, Aniket, Liu, Dan, Luciano, Michelle, Teumer, Alexander, Armstrong, Nicola, Bis, Joshua C, Jhun, Min A, Li, Shuo, Adams, Hieab HH, Aziz, Nasir Ahmad, Bastin, Mark E, Bourgey, Mathieu, Brody, Jennifer A, Frenzel, Stefan, Gottesman, Rebecca F, Hosten, Norbert, Hou, Lifang, Kardia, Sharon LR, Lohner, Valerie, Marquis, Pascale, Maniega, Susana Muñoz, Satizabal, Claudia L, Sorond, Farzaneh A, Valdés Hernández, Maria C, van Duijn, Cornelia M, Vernooij, Meike W, Wittfeld, Katharina, Yang, Qiong, Zhao, Wei, Boerwinkle, Eric, Levy, Daniel, Deary, Ian J, Jiang, Jiyang, Mather, Karen A, Mosley, Thomas H, Psaty, Bruce M, Sachdev, Perminder S, Smith, Jennifer A, Sotoodehnia, Nona, DeCarli, Charles S, Breteler, Monique MB, Ikram, M Arfan, Grabe, Hans J, Wardlaw, Joanna, Longstreth, WT, Launer, Lenore J, Seshadri, Sudha, Debette, Stephanie, and Fornage, Myriam

Subjects
Health Sciences, Genetics, Aging, Brain Disorders, Neurosciences, Human Genome, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Middle Aged, Humans, Aged, White Matter, Genome-Wide Association Study, Brain, DNA Methylation, Magnetic Resonance Imaging, Epigenesis, Genetic, Protein-Arginine N-Methyltransferases, Repressor Proteins, epigenome-wide association study, white matter hyperintensities, cerebral small vessel disease, integrative cross-omics analysis, blood-brain barrier dysfunction, blood–brain barrier dysfunction, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences, Psychology
Abstract

Cerebral white matter hyperintensities on MRI are markers of cerebral small vessel disease, a major risk factor for dementia and stroke. Despite the successful identification of multiple genetic variants associated with this highly heritable condition, its genetic architecture remains incompletely understood. More specifically, the role of DNA methylation has received little attention. We investigated the association between white matter hyperintensity burden and DNA methylation in blood at ∼450 000 cytosine-phosphate-guanine (CpG) sites in 9732 middle-aged to older adults from 14 community-based studies. Single CpG and region-based association analyses were carried out. Functional annotation and integrative cross-omics analyses were performed to identify novel genes underlying the relationship between DNA methylation and white matter hyperintensities. We identified 12 single CpG and 46 region-based DNA methylation associations with white matter hyperintensity burden. Our top discovery single CpG, cg24202936 (P = 7.6 × 10-8), was associated with F2 expression in blood (P = 6.4 × 10-5) and co-localized with FOLH1 expression in brain (posterior probability = 0.75). Our top differentially methylated regions were in PRMT1 and in CCDC144NL-AS1, which were also represented in single CpG associations (cg17417856 and cg06809326, respectively). Through Mendelian randomization analyses cg06809326 was putatively associated with white matter hyperintensity burden (P = 0.03) and expression of CCDC144NL-AS1 possibly mediated this association. Differentially methylated region analysis, joint epigenetic association analysis and multi-omics co-localization analysis consistently identified a role of DNA methylation near SH3PXD2A, a locus previously identified in genome-wide association studies of white matter hyperintensities. Gene set enrichment analyses revealed functions of the identified DNA methylation loci in the blood-brain barrier and in the immune response. Integrative cross-omics analysis identified 19 key regulatory genes in two networks related to extracellular matrix organization, and lipid and lipoprotein metabolism. A drug-repositioning analysis indicated antihyperlipidaemic agents, more specifically peroxisome proliferator-activated receptor-alpha, as possible target drugs for white matter hyperintensities. Our epigenome-wide association study and integrative cross-omics analyses implicate novel genes influencing white matter hyperintensity burden, which converged on pathways related to the immune response and to a compromised blood-brain barrier possibly due to disrupted cell-cell and cell-extracellular matrix interactions. The results also suggest that antihyperlipidaemic therapy may contribute to lowering risk for white matter hyperintensities possibly through protection against blood-brain barrier disruption.

Published
2023

2. Circulating Metabolome and White Matter Hyperintensities in Women and Men

Author

Sliz, Eeva, Shin, Jean, Ahmad, Shahzad, Williams, Dylan M, Frenzel, Stefan, Gauß, Friederike, Harris, Sarah E, Henning, Ann-Kristin, Hernandez, Maria Valdes, Hu, Yi-Han, Jiménez, Beatriz, Sargurupremraj, Muralidharan, Sudre, Carole, Wang, Ruiqi, Wittfeld, Katharina, Yang, Qiong, Wardlaw, Joanna M, Völzke, Henry, Vernooij, Meike W, Schott, Jonathan M, Richards, Marcus, Proitsi, Petroula, Nauck, Matthias, Lewis, Matthew R, Launer, Lenore, Hosten, Norbert, Grabe, Hans J, Ghanbari, Mohsen, Deary, Ian J, Cox, Simon R, Chaturvedi, Nishi, Barnes, Josephine, Rotter, Jerome I, Debette, Stephanie, Ikram, M Arfan, Fornage, Myriam, Paus, Tomas, Seshadri, Sudha, Pausova, Zdenka, and Group, for the NeuroCHARGE Working

Subjects
Epidemiology, Biomedical and Clinical Sciences, Health Sciences, Prevention, Clinical Research, Aging, Aged, Brain, Diabetes Mellitus, Type 2, Female, Humans, Magnetic Resonance Imaging, Male, Metabolome, Middle Aged, White Matter, NeuroCHARGE Working Group, brain, glucuronic acid, hydroxyphenylpyruvate, lipid ratios, lipidomics, lipids, lysophosphatidylcholines, metabolomics, sphingomyelins, white matter, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences, Sports science and exercise
Abstract

BackgroundWhite matter hyperintensities (WMH), identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness, are a major risk factor of stroke, dementia, and death. There are no large-scale studies testing associations between WMH and circulating metabolites.MethodsWe studied up to 9290 individuals (50.7% female, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted P values (PFDR)

Published
2022

4. Automated image quality assessment for selecting among multiple magnetic resonance image acquisitions in the German National Cohort study

Author

Schuppert, Christopher, Rospleszcz, Susanne, Hirsch, Jochen G., Hoinkiss, Daniel C., Köhn, Alexander, von Krüchten, Ricarda, Russe, Maximilian F., Keil, Thomas, Krist, Lilian, Schmidt, Börge, Michels, Karin B., Schipf, Sabine, Brenner, Hermann, Kröncke, Thomas J., Pischon, Tobias, Niendorf, Thoralf, Schulz-Menger, Jeanette, Forsting, Michael, Völzke, Henry, Hosten, Norbert, Bülow, Robin, Zaitsev, Maxim, Kauczor, Hans-Ulrich, Bamberg, Fabian, Günther, Matthias, and Schlett, Christopher L.

Published
2023
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5. Insulin-Like Growth Factor, Inflammation, and MRI Markers of Alzheimer's Disease in Predominantly Middle-Aged Adults.

Author

Wittfeld, Katharina, Raman, Mekala R, Conner, Sarah C, Aslam, Asra, Teumer, Alexander, Nauck, Matthias, Hosten, Norbert, Habes, Mohamad, DeCarli, Charles, Vasan, Ramachandran S, Beiser, Alexa S, Himali, Jayandra J, Seshadri, Sudha, Grabe, Hans J, and Satizabal, Claudia L

Subjects
Paediatrics, Biomedical and Clinical Sciences, Clinical Sciences, Brain Disorders, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Aging, Dementia, Acquired Cognitive Impairment, Neurodegenerative, Clinical Research, Alzheimer's Disease, 2.1 Biological and endogenous factors, Aetiology, Neurological, Adult, Alzheimer Disease, Biomarkers, C-Reactive Protein, Female, Humans, Inflammation, Insulin-Like Growth Factor Binding Protein 3, Insulin-Like Growth Factor I, Magnetic Resonance Imaging, Male, Middle Aged, Alzheimer's disease endophenotype, C-reactive protein, cohort study, epidemiology, hippocampus, insulin-like growth factor, neuroimaging, white matter hyperintensity, Alzheimer’s disease endophenotype, white matter hyperintensity, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences, Biological psychology
Abstract

BackgroundInsulin-like growth factor 1 (IGF-1) signaling has been implicated in Alzheimer's disease pathogenesis, and further evidence suggests inflammation can be a moderator of this association. However, most research to date has been conducted on older adults.ObjectiveTo investigate the association of serum IGF-1 and IGF binding protein 3 (IGFBP-3) concentrations with MRI markers of Alzheimer's disease in predominantly middle-aged adults, and further assess moderation by chronic inflammation.MethodsWe included participants from the Framingham Heart Study (n = 1,852, mean age 46±8, 46% men) and the Study of Health in Pomerania (n = 674, mean age 50±13, 42% men) with available serum IGF-1, IFGBP-3, as well as brain MRI. IGF-1 and IFGBP-3 were related to MRI outcomes (i.e., total brain, cortical gray matter, white matter, white matter hyperintensities (WMH), and hippocampal volumes) using multivariable regression models adjusting for potential confounders. Subgroup analyses by C-reactive protein (CRP) concentrations were also performed. Cohort-specific summary statistics were meta-analyzed using random-effects models and corrected for multiple comparisons.ResultsMeta-analysis results revealed that higher IGF-1 concentrations were associated with lower WMH (estimate [β] [95% CI], -0.05 [-0.09, -0.02], p = 0.006) and larger hippocampal volumes (0.07 [0.02, 0.12], p = 0.01), independent of vascular risk factors. These associations occurred predominantly in individuals with CRP concentrations

Published
2022

6. Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

Author

Dima, Danai, Modabbernia, Amirhossein, Papachristou, Efstathios, Doucet, Gaelle E, Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N, Albajes-Eizagirre, Anton, Alnaes, Dag, Alpert, Kathryn I, Andersson, Micael, Andreasen, Nancy C, Andreassen, Ole A, Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur-Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret I, Borgwardt, Stefan, Bourque, Josiane, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M, Buitelaar, Jan K, Busatto, Geraldo F, Buckner, Randy L, Calhoun, Vincent, Canales-Rodríguez, Erick J, Cannon, Dara M, Caseras, Xavier, Castellanos, Francisco X, Cervenka, Simon, Chaim-Avancini, Tiffany M, Ching, Christopher RK, Chubar, Victoria, Clark, Vincent P, Conrod, Patricia, Conzelmann, Annette, Crespo-Facorro, Benedicto, Crivello, Fabrice, Crone, Eveline A, Dannlowski, Udo, Dale, Anders M, Davey, Christopher, de Geus, Eco JC, de Haan, Lieuwe, de Zubicaray, Greig I, den Braber, Anouk, Dickie, Erin W, Di Giorgio, Annabella, Doan, Nhat Trung, Dørum, Erlend S, Ehrlich, Stefan, Erk, Susanne, Espeseth, Thomas, Fatouros-Bergman, Helena, Fisher, Simon E, Fouche, Jean-Paul, Franke, Barbara, Frodl, Thomas, Fuentes-Claramonte, Paola, Glahn, David C, Gotlib, Ian H, Grabe, Hans-Jörgen, Grimm, Oliver, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Gur, Rachel E, Gur, Ruben C, Hahn, Tim, Harrison, Ben J, Hartman, Catharine A, Hatton, Sean N, Heinz, Andreas, Heslenfeld, Dirk J, Hibar, Derrek P, Hickie, Ian B, Ho, Beng-Choon, Hoekstra, Pieter J, Hohmann, Sarah, Holmes, Avram J, Hoogman, Martine, Hosten, Norbert, Howells, Fleur M, Hulshoff Pol, Hilleke E, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Jernigan, Terry L, Jiang, Jiyang, Jönsson, Erik G, Joska, John A, Kahn, Rene, and Kalnin, Andrew

Subjects
Karolinska Schizophrenia Project, Amygdala, Hippocampus, Thalamus, Corpus Striatum, Humans, Human Development, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Child, Child, Preschool, Female, Male, Young Adult, Neuroimaging, ENIGMA, brain morphometry, longitudinal trajectories, multisite, Neurosciences, Aging, Aetiology, 2.1 Biological and endogenous factors, Mental health, Cognitive Sciences, Experimental Psychology
Abstract

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.

Published
2022

7. Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3–90 years

Author

Frangou, Sophia, Modabbernia, Amirhossein, Williams, Steven CR, Papachristou, Efstathios, Doucet, Gaelle E, Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N, Albajes‐Eizagirre, Anton, Alnæs, Dag, Alpert, Kathryn I, Andersson, Micael, Andreasen, Nancy C, Andreassen, Ole A, Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur‐Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret I, Borgwardt, Stefan, Bourque, Josiane, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M, Buitelaar, Jan K, Busatto, Geraldo F, Buckner, Randy L, Calhoun, Vincent, Canales‐Rodríguez, Erick J, Cannon, Dara M, Caseras, Xavier, Castellanos, Francisco X, Cervenka, Simon, Chaim‐Avancini, Tiffany M, Ching, Christopher RK, Chubar, Victoria, Clark, Vincent P, Conrod, Patricia, Conzelmann, Annette, Crespo‐Facorro, Benedicto, Crivello, Fabrice, Crone, Eveline A, Dale, Anders M, Dannlowski, Udo, Davey, Christopher, Geus, Eco JC, Haan, Lieuwe, Zubicaray, Greig I, Braber, Anouk, Dickie, Erin W, Di Giorgio, Annabella, Doan, Nhat Trung, Dørum, Erlend S, Ehrlich, Stefan, Erk, Susanne, Espeseth, Thomas, Fatouros‐Bergman, Helena, Fisher, Simon E, Fouche, Jean‐Paul, Franke, Barbara, Frodl, Thomas, Fuentes‐Claramonte, Paola, Glahn, David C, Gotlib, Ian H, Grabe, Hans‐Jörgen, Grimm, Oliver, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Gur, Rachel E, Gur, Ruben C, Hahn, Tim, Harrison, Ben J, Hartman, Catharine A, Hatton, Sean N, Heinz, Andreas, Heslenfeld, Dirk J, Hibar, Derrek P, Hickie, Ian B, Ho, Beng‐Choon, Hoekstra, Pieter J, Hohmann, Sarah, Holmes, Avram J, Hoogman, Martine, Hosten, Norbert, Howells, Fleur M, Pol, Hilleke E Hulshoff, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Jernigan, Terry L, Jiang, Jiyang, Jönsson, Erik G, Joska, John A, and Kahn, Rene

Subjects
Behavioral and Social Science, Neurosciences, Aging, Adolescent, Adult, Aged, Aged, 80 and over, Cerebral Cortex, Child, Child, Preschool, Cross-Sectional Studies, Female, Human Development, Humans, Male, Middle Aged, Neuroimaging, Young Adult, aging, cortical thickness, development, trajectories, Karolinska Schizophrenia Project, Cognitive Sciences, Experimental Psychology
Abstract

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.

Published
2022

8. 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

9. ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

Author

Thompson, Paul M, Jahanshad, Neda, Ching, Christopher RK, Salminen, Lauren E, Thomopoulos, Sophia I, Bright, Joanna, Baune, Bernhard T, Bertolín, Sara, Bralten, Janita, Bruin, Willem B, Bülow, Robin, Chen, Jian, Chye, Yann, Dannlowski, Udo, de Kovel, Carolien GF, Donohoe, Gary, Eyler, Lisa T, Faraone, Stephen V, Favre, Pauline, Filippi, Courtney A, Frodl, Thomas, Garijo, Daniel, Gil, Yolanda, Grabe, Hans J, Grasby, Katrina L, Hajek, Tomas, Han, Laura KM, Hatton, Sean N, Hilbert, Kevin, Ho, Tiffany C, Holleran, Laurena, Homuth, Georg, Hosten, Norbert, Houenou, Josselin, Ivanov, Iliyan, Jia, Tianye, Kelly, Sinead, Klein, Marieke, Kwon, Jun Soo, Laansma, Max A, Leerssen, Jeanne, Lueken, Ulrike, Nunes, Abraham, Neill, Joseph O', Opel, Nils, Piras, Fabrizio, Piras, Federica, Postema, Merel C, Pozzi, Elena, Shatokhina, Natalia, Soriano-Mas, Carles, Spalletta, Gianfranco, Sun, Daqiang, Teumer, Alexander, Tilot, Amanda K, Tozzi, Leonardo, van der Merwe, Celia, Van Someren, Eus JW, van Wingen, Guido A, Völzke, Henry, Walton, Esther, Wang, Lei, Winkler, Anderson M, Wittfeld, Katharina, Wright, Margaret J, Yun, Je-Yeon, Zhang, Guohao, Zhang-James, Yanli, Adhikari, Bhim M, Agartz, Ingrid, Aghajani, Moji, Aleman, André, Althoff, Robert R, Altmann, Andre, Andreassen, Ole A, Baron, David A, Bartnik-Olson, Brenda L, Marie Bas-Hoogendam, Janna, Baskin-Sommers, Arielle R, Bearden, Carrie E, Berner, Laura A, Boedhoe, Premika SW, Brouwer, Rachel M, Buitelaar, Jan K, Caeyenberghs, Karen, Cecil, Charlotte AM, Cohen, Ronald A, Cole, James H, Conrod, Patricia J, De Brito, Stephane A, de Zwarte, Sonja MC, Dennis, Emily L, Desrivieres, Sylvane, Dima, Danai, Ehrlich, Stefan, Esopenko, Carrie, Fairchild, Graeme, Fisher, Simon E, Fouche, Jean-Paul, and Francks, Clyde

Subjects
ENIGMA Consortium, Brain, Humans, Magnetic Resonance Imaging, Reproducibility of Results, Depressive Disorder, Major, Neuroimaging, Neurosciences, Clinical Research, Mental Health, Brain Disorders, Behavioral and Social Science, Genetics, Basic Behavioral and Social Science, Prevention, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Mental health, Neurological, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Published
2020

12. Genetic and lifestyle risk factors for MRI-defined brain infarcts in a population-based setting

Author

Chauhan, Ganesh, Adams, Hieab HH, Satizabal, Claudia L, Bis, Joshua C, Teumer, Alexander, Sargurupremraj, Muralidharan, Hofer, Edith, Trompet, Stella, Hilal, Saima, Smith, Albert Vernon, Jian, Xueqiu, Malik, Rainer, Traylor, Matthew, Pulit, Sara L, Amouyel, Philippe, Mazoyer, Bernard, Zhu, Yi-Cheng, Kaffashian, Sara, Schilling, Sabrina, Beecham, Gary W, Montine, Thomas J, Schellenberg, Gerard D, Kjartansson, Olafur, Guðnason, Vilmundur, Knopman, David S, Griswold, Michael E, Windham, B Gwen, Gottesman, Rebecca F, Mosley, Thomas H, Schmidt, Reinhold, Saba, Yasaman, Schmidt, Helena, Takeuchi, Fumihiko, Yamaguchi, Shuhei, Nabika, Toru, Kato, Norihiro, Rajan, Kumar B, Aggarwal, Neelum T, De Jager, Philip L, Evans, Denis A, Psaty, Bruce M, Rotter, Jerome I, Rice, Kenneth, Lopez, Oscar L, Liao, Jiemin, Chen, Christopher, Cheng, Ching-Yu, Wong, Tien Y, Ikram, Mohammad K, van der Lee, Sven J, Amin, Najaf, Chouraki, Vincent, DeStefano, Anita L, Aparicio, Hugo J, Romero, Jose R, Maillard, Pauline, DeCarli, Charles, Wardlaw, Joanna M, del C. Valdés Hernández, Maria, Luciano, Michelle, Liewald, David, Deary, Ian J, Starr, John M, Bastin, Mark E, Maniega, Susana Muñoz, Slagboom, P Eline, Beekman, Marian, Deelen, Joris, Uh, Hae-Won, Lemmens, Robin, Brodaty, Henry, Wright, Margaret J, Ames, David, Boncoraglio, Giorgio B, Hopewell, Jemma C, Beecham, Ashley H, Blanton, Susan H, Wright, Clinton B, Sacco, Ralph L, Wen, Wei, Thalamuthu, Anbupalam, Armstrong, Nicola J, Chong, Elizabeth, Schofield, Peter R, Kwok, John B, van der Grond, Jeroen, Stott, David J, Ford, Ian, Jukema, J Wouter, Vernooij, Meike W, Hofman, Albert, Uitterlinden, André G, van der Lugt, Aad, Wittfeld, Katharina, Grabe, Hans J, Hosten, Norbert, von Sarnowski, Bettina, Völker, Uwe, Levi, Christopher, and Jimenez-Conde, Jordi

Subjects
Biomedical and Clinical Sciences, Neurosciences, Clinical Sciences, Prevention, Cardiovascular, Human Genome, Aging, Brain Disorders, Genetics, Stroke, Cerebrovascular, 2.1 Biological and endogenous factors, Good Health and Well Being, Stroke Genetics Network (SiGN), the International Stroke Genetics Consortium (ISGC), METASTROKE, Alzheimer's Disease Genetics Consortium (ADGC), and the Neurology Working Group of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, Cognitive Sciences, Neurology & Neurosurgery, Clinical sciences
Abstract

ObjectiveTo explore genetic and lifestyle risk factors of MRI-defined brain infarcts (BI) in large population-based cohorts.MethodsWe performed meta-analyses of genome-wide association studies (GWAS) and examined associations of vascular risk factors and their genetic risk scores (GRS) with MRI-defined BI and a subset of BI, namely, small subcortical BI (SSBI), in 18 population-based cohorts (n = 20,949) from 5 ethnicities (3,726 with BI, 2,021 with SSBI). Top loci were followed up in 7 population-based cohorts (n = 6,862; 1,483 with BI, 630 with SBBI), and we tested associations with related phenotypes including ischemic stroke and pathologically defined BI.ResultsThe mean prevalence was 17.7% for BI and 10.5% for SSBI, steeply rising after age 65. Two loci showed genome-wide significant association with BI: FBN2, p = 1.77 × 10-8; and LINC00539/ZDHHC20, p = 5.82 × 10-9. Both have been associated with blood pressure (BP)-related phenotypes, but did not replicate in the smaller follow-up sample or show associations with related phenotypes. Age- and sex-adjusted associations with BI and SSBI were observed for BP traits (p value for BI, p [BI] = 9.38 × 10-25; p [SSBI] = 5.23 × 10-14 for hypertension), smoking (p [BI] = 4.4 × 10-10; p [SSBI] = 1.2 × 10-4), diabetes (p [BI] = 1.7 × 10-8; p [SSBI] = 2.8 × 10-3), previous cardiovascular disease (p [BI] = 1.0 × 10-18; p [SSBI] = 2.3 × 10-7), stroke (p [BI] = 3.9 × 10-69; p [SSBI] = 3.2 × 10-24), and MRI-defined white matter hyperintensity burden (p [BI] = 1.43 × 10-157; p [SSBI] = 3.16 × 10-106), but not with body mass index or cholesterol. GRS of BP traits were associated with BI and SSBI (p ≤ 0.0022), without indication of directional pleiotropy.ConclusionIn this multiethnic GWAS meta-analysis, including over 20,000 population-based participants, we identified genetic risk loci for BI requiring validation once additional large datasets become available. High BP, including genetically determined, was the most significant modifiable, causal risk factor for BI.

Published
2019

13. Neandertal Introgression Sheds Light on Modern Human Endocranial Globularity.

Author

Gunz, Philipp, Tilot, Amanda, Wittfeld, Katharina, Teumer, Alexander, Shapland, Chin, Dannemann, Michael, Vernot, Benjamin, Neubauer, Simon, Guadalupe, Tulio, Fernández, Guillén, Brunner, Han, Enard, Wolfgang, Fallon, James, Hosten, Norbert, Völker, Uwe, Profico, Antonio, Di Vincenzo, Fabio, Manzi, Giorgio, Kelso, Janet, St Pourcain, Beate, Hublin, Jean-Jacques, Franke, Barbara, Pääbo, Svante, Grabe, Hans, Fisher, Simon, Van Erp, Theodorus, and Macciardi, Fabio

Subjects
Neandertal, basal ganglia, brain shape, cerebellum, evolution, gene expression, genetic association, homo sapiens, magnetic resonance imaging, myelination, Adolescent, Adult, Aged, Aged, 80 and over, Animals, Biological Evolution, Female, Fossils, Humans, Hybridization, Genetic, Male, Middle Aged, Neanderthals, Netherlands, Phenotype, Skull, Young Adult
Abstract

One of the features that distinguishes modern humans from our extinct relatives and ancestors is a globular shape of the braincase [1-4]. As the endocranium closely mirrors the outer shape of the brain, these differences might reflect altered neural architecture [4, 5]. However, in the absence of fossil brain tissue, the underlying neuroanatomical changes as well as their genetic bases remain elusive. To better understand the biological foundations of modern human endocranial shape, we turn to our closest extinct relatives: the Neandertals. Interbreeding between modern humans and Neandertals has resulted in introgressed fragments of Neandertal DNA in the genomes of present-day non-Africans [6, 7]. Based on shape analyses of fossil skull endocasts, we derive a measure of endocranial globularity from structural MRI scans of thousands of modern humans and study the effects of introgressed fragments of Neandertal DNA on this phenotype. We find that Neandertal alleles on chromosomes 1 and 18 are associated with reduced endocranial globularity. These alleles influence expression of two nearby genes, UBR4 and PHLPP1, which are involved in neurogenesis and myelination, respectively. Our findings show how integration of fossil skull data with archaic genomics and neuroimaging can suggest developmental mechanisms that may contribute to the unique modern human endocranial shape.

Published
2019

15. Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders: Evidence through univariate and multivariate mega-analysis including 6420 participants from the ENIGMA MDD working group

Author

Opel, Nils, Thalamuthu, Anbupalam, Milaneschi, Yuri, Grotegerd, Dominik, Flint, Claas, Leenings, Ramona, Goltermann, Janik, Richter, Maike, Hahn, Tim, Woditsch, Georg, Berger, Klaus, Hermesdorf, Marco, McIntosh, Andrew, Whalley, Heather C., Harris, Mathew A., MacMaster, Frank P., Walter, Henrik, Veer, Ilya M., Frodl, Thomas, Carballedo, Angela, Krug, Axel, Nenadic, Igor, Kircher, Tilo, Aleman, Andre, Groenewold, Nynke A., Stein, Dan J., Soares, Jair C., Zunta-Soares, Giovana B., Mwangi, Benson, Wu, Mon-Ju, Walter, Martin, Li, Meng, Harrison, Ben J., Davey, Christopher G., Cullen, Kathryn R., Klimes-Dougan, Bonnie, Mueller, Bryon A., Sämann, Philipp G., Penninx, Brenda, Nawijn, Laura, Veltman, Dick J., Aftanas, Lyubomir, Brak, Ivan V., Filimonova, Elena A., Osipov, Evgeniy A., Reneman, Liesbeth, Schrantee, Anouk, Grabe, Hans J., Van der Auwera, Sandra, Wittfeld, Katharina, Hosten, Norbert, Völzke, Henry, Sim, Kang, Gotlib, Ian H., Sacchet, Matthew D., Lagopoulos, Jim, Hatton, Sean N., Hickie, Ian, Pozzi, Elena, Thompson, Paul M., Jahanshad, Neda, Schmaal, Lianne, Baune, Bernhard T., and Dannlowski, Udo

Published
2021
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16. ENIGMA and the individual: Predicting factors that affect the brain in 35 countries worldwide

Author

Thompson, Paul M, Andreassen, Ole A, Arias-Vasquez, Alejandro, Bearden, Carrie E, Boedhoe, Premika S, Brouwer, Rachel M, Buckner, Randy L, Buitelaar, Jan K, Bulayeva, Kazima B, Cannon, Dara M, Cohen, Ronald A, Conrod, Patricia J, Dale, Anders M, Deary, Ian J, Dennis, Emily L, de Reus, Marcel A, Desrivieres, Sylvane, Dima, Danai, Donohoe, Gary, Fisher, Simon E, Fouche, Jean-Paul, Francks, Clyde, Frangou, Sophia, Franke, Barbara, Ganjgahi, Habib, Garavan, Hugh, Glahn, David C, Grabe, Hans J, Guadalupe, Tulio, Gutman, Boris A, Hashimoto, Ryota, Hibar, Derrek P, Holland, Dominic, Hoogman, Martine, Pol, Hilleke E Hulshoff, Hosten, Norbert, Jahanshad, Neda, Kelly, Sinead, Kochunov, Peter, Kremen, William S, Lee, Phil H, Mackey, Scott, Martin, Nicholas G, Mazoyer, Bernard, McDonald, Colm, Medland, Sarah E, Morey, Rajendra A, Nichols, Thomas E, Paus, Tomas, Pausova, Zdenka, Schmaal, Lianne, Schumann, Gunter, Shen, Li, Sisodiya, Sanjay M, Smit, Dirk JA, Smoller, Jordan W, Stein, Dan J, Stein, Jason L, Toro, Roberto, Turner, Jessica A, van den Heuvel, Martijn P, van den Heuvel, Odile L, van Erp, Theo GM, van Rooij, Daan, Veltman, Dick J, Walter, Henrik, Wang, Yalin, Wardlaw, Joanna M, Whelan, Christopher D, Wright, Margaret J, Ye, Jieping, and Consortium, for the ENIGMA

Subjects
Biomedical and Clinical Sciences, Health Sciences, Genetics, Mental Health, Prevention, Brain Disorders, Neurosciences, 2.1 Biological and endogenous factors, Aetiology, Mental health, Neurological, Good Health and Well Being, Brain Diseases, Genome-Wide Association Study, Humans, Mental Disorders, Multicenter Studies as Topic, ENIGMA Consortium, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences
Abstract

In this review, we discuss recent work by the ENIGMA Consortium (http://enigma.ini.usc.edu) - a global alliance of over 500 scientists spread across 200 institutions in 35 countries collectively analyzing brain imaging, clinical, and genetic data. Initially formed to detect genetic influences on brain measures, ENIGMA has grown to over 30 working groups studying 12 major brain diseases by pooling and comparing brain data. In some of the largest neuroimaging studies to date - of schizophrenia and major depression - ENIGMA has found replicable disease effects on the brain that are consistent worldwide, as well as factors that modulate disease effects. In partnership with other consortia including ADNI, CHARGE, IMAGEN and others1, ENIGMA's genomic screens - now numbering over 30,000 MRI scans - have revealed at least 8 genetic loci that affect brain volumes. Downstream of gene findings, ENIGMA has revealed how these individual variants - and genetic variants in general - may affect both the brain and risk for a range of diseases. The ENIGMA consortium is discovering factors that consistently affect brain structure and function that will serve as future predictors linking individual brain scans and genomic data. It is generating vast pools of normative data on brain measures - from tens of thousands of people - that may help detect deviations from normal development or aging in specific groups of subjects. We discuss challenges and opportunities in applying these predictors to individual subjects and new cohorts, as well as lessons we have learned in ENIGMA's efforts so far.

Published
2017

21. Genetic architecture of subcortical brain structures in 38,851 individuals

Author

Satizabal, Claudia L., Adams, Hieab H. H., Hibar, Derrek P., White, Charles C., Knol, Maria J., Stein, Jason L., Scholz, Markus, Sargurupremraj, Muralidharan, Jahanshad, Neda, Roshchupkin, Gennady V., Smith, Albert V., Bis, Joshua C., Jian, Xueqiu, Luciano, Michelle, Hofer, Edith, Teumer, Alexander, van der Lee, Sven J., Yang, Jingyun, Yanek, Lisa R., Lee, Tom V., Li, Shuo, Hu, Yanhui, Koh, Jia Yu, Eicher, John D., Desrivières, Sylvane, Arias-Vasquez, Alejandro, Chauhan, Ganesh, Athanasiu, Lavinia, Rentería, Miguel E., Kim, Sungeun, Hoehn, David, Armstrong, Nicola J., Chen, Qiang, Holmes, Avram J., den Braber, Anouk, Kloszewska, Iwona, Andersson, Micael, Espeseth, Thomas, Grimm, Oliver, Abramovic, Lucija, Alhusaini, Saud, Milaneschi, Yuri, Papmeyer, Martina, Axelsson, Tomas, Ehrlich, Stefan, Roiz-Santiañez, Roberto, Kraemer, Bernd, Håberg, Asta K., Jones, Hannah J., Pike, G. Bruce, Stein, Dan J., Stevens, Allison, Bralten, Janita, Vernooij, Meike W., Harris, Tamara B., Filippi, Irina, Witte, A. Veronica, Guadalupe, Tulio, Wittfeld, Katharina, Mosley, Thomas H., Becker, James T., Doan, Nhat Trung, Hagenaars, Saskia P., Saba, Yasaman, Cuellar-Partida, Gabriel, Amin, Najaf, Hilal, Saima, Nho, Kwangsik, Mirza-Schreiber, Nazanin, Arfanakis, Konstantinos, Becker, Diane M., Ames, David, Goldman, Aaron L., Lee, Phil H., Boomsma, Dorret I., Lovestone, Simon, Giddaluru, Sudheer, Le Hellard, Stephanie, Mattheisen, Manuel, Bohlken, Marc M., Kasperaviciute, Dalia, Schmaal, Lianne, Lawrie, Stephen M., Agartz, Ingrid, Walton, Esther, Tordesillas-Gutierrez, Diana, Davies, Gareth E., Shin, Jean, Ipser, Jonathan C., Vinke, Louis N., Hoogman, Martine, Jia, Tianye, Burkhardt, Ralph, Klein, Marieke, Crivello, Fabrice, Janowitz, Deborah, Carmichael, Owen, Haukvik, Unn K., Aribisala, Benjamin S., Schmidt, Helena, Strike, Lachlan T., Cheng, Ching-Yu, Risacher, Shannon L., Pütz, Benno, Fleischman, Debra A., Assareh, Amelia A., Mattay, Venkata S., Buckner, Randy L., Mecocci, Patrizia, Dale, Anders M., Cichon, Sven, Boks, Marco P., Matarin, Mar, Penninx, Brenda W. J. H., Calhoun, Vince D., Chakravarty, M. Mallar, Marquand, Andre F., Macare, Christine, Kharabian Masouleh, Shahrzad, Oosterlaan, Jaap, Amouyel, Philippe, Hegenscheid, Katrin, Rotter, Jerome I., Schork, Andrew J., Liewald, David C. M., de Zubicaray, Greig I., Wong, Tien Yin, Shen, Li, Sämann, Philipp G., Brodaty, Henry, Roffman, Joshua L., de Geus, Eco J. C., Tsolaki, Magda, Erk, Susanne, van Eijk, Kristel R., Cavalleri, Gianpiero L., van der Wee, Nic J. A., McIntosh, Andrew M., Gollub, Randy L., Bulayeva, Kazima B., Bernard, Manon, Richards, Jennifer S., Himali, Jayandra J., Loeffler, Markus, Rommelse, Nanda, Hoffmann, Wolfgang, Westlye, Lars T., Valdés Hernández, Maria C., Hansell, Narelle K., van Erp, Theo G. M., Wolf, Christiane, Kwok, John B. J., Vellas, Bruno, Heinz, Andreas, Olde Loohuis, Loes M., Delanty, Norman, Ho, Beng-Choon, Ching, Christopher R. K., Shumskaya, Elena, Singh, Baljeet, Hofman, Albert, van der Meer, Dennis, Homuth, Georg, Psaty, Bruce M., Bastin, Mark E., Montgomery, Grant W., Foroud, Tatiana M., Reppermund, Simone, Hottenga, Jouke-Jan, Simmons, Andrew, Meyer-Lindenberg, Andreas, Cahn, Wiepke, Whelan, Christopher D., van Donkelaar, Marjolein M. J., Yang, Qiong, Hosten, Norbert, Green, Robert C, Thalamuthu, Anbupalam, Mohnke, Sebastian, Hulshoff Pol, Hilleke E., Lin, Honghuang, Jack, Jr, Clifford R., Schofield, Peter R., Mühleisen, Thomas W., Maillard, Pauline, Potkin, Steven G., Wen, Wei, Fletcher, Evan, Toga, Arthur W., Gruber, Oliver, Huentelman, Matthew, Davey Smith, George, Launer, Lenore J., Nyberg, Lars, Jönsson, Erik G., Crespo-Facorro, Benedicto, Koen, Nastassja, Greve, Douglas N., Uitterlinden, André G., Weinberger, Daniel R., Steen, Vidar M., Fedko, Iryna O., Groenewold, Nynke A., Niessen, Wiro J., Toro, Roberto, Tzourio, Christophe, Longstreth, Jr, William T., Ikram, M. Kamran, Smoller, Jordan W., van Tol, Marie-Jose, Sussmann, Jessika E., Paus, Tomas, Lemaître, Hervé, Schroeter, Matthias L., Mazoyer, Bernard, Andreassen, Ole A., Holsboer, Florian, Depondt, Chantal, Veltman, Dick J., Turner, Jessica A., Pausova, Zdenka, Schumann, Gunter, van Rooij, Daan, Djurovic, Srdjan, Deary, Ian J., McMahon, Katie L., Müller-Myhsok, Bertram, Brouwer, Rachel M., Soininen, Hilkka, Pandolfo, Massimo, Wassink, Thomas H., Cheung, Joshua W., Wolfers, Thomas, Martinot, Jean-Luc, Zwiers, Marcel P., Nauck, Matthias, Melle, Ingrid, Martin, Nicholas G., Kanai, Ryota, Westman, Eric, Kahn, René S., Sisodiya, Sanjay M., White, Tonya, Saremi, Arvin, van Bokhoven, Hans, Brunner, Han G., Völzke, Henry, Wright, Margaret J., van ‘t Ent, Dennis, Nöthen, Markus M., Ophoff, Roel A., Buitelaar, Jan K., Fernández, Guillén, Sachdev, Perminder S., Rietschel, Marcella, van Haren, Neeltje E. M., Fisher, Simon E., Beiser, Alexa S., Francks, Clyde, Saykin, Andrew J., Mather, Karen A., Romanczuk-Seiferth, Nina, Hartman, Catharina A., DeStefano, Anita L., Heslenfeld, Dirk J., Weiner, Michael W., Walter, Henrik, Hoekstra, Pieter J., Nyquist, Paul A., Franke, Barbara, Bennett, David A., Grabe, Hans J., Johnson, Andrew D., Chen, Christopher, van Duijn, Cornelia M., Lopez, Oscar L., Fornage, Myriam, Wardlaw, Joanna M., Schmidt, Reinhold, DeCarli, Charles, De Jager, Philip L., Villringer, Arno, Debette, Stéphanie, Gudnason, Vilmundur, Medland, Sarah E., Shulman, Joshua M., Thompson, Paul M., Seshadri, Sudha, and Ikram, M. Arfan

Published
2019
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24. Correction: Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders

Author

Opel, Nils, Thalamuthu, Anbupalam, Milaneschi, Yuri, Grotegerd, Dominik, Flint, Claas, Leenings, Ramona, Goltermann, Janik, Richter, Maike, Hahn, Tim, Woditsch, Georg, Berger, Klaus, Hermesdorf, Marco, McIntosh, Andrew, Whalley, Heather C., Harris, Mathew A., MacMaster, Frank P., Walter, Henrik, Veer, Ilya M., Frodl, Thomas, Carballedo, Angela, Krug, Axel, Nenadic, Igor, Kircher, Tilo, Aleman, Andre, Groenewold, Nynke A., Stein, Dan J., Soares, Jair C., Zunta-Soares, Giovana B., Mwangi, Benson, Wu, Mon-Ju, Walter, Martin, Li, Meng, Harrison, Ben J., Davey, Christopher G., Cullen, Kathryn R., Klimes-Dougan, Bonnie, Mueller, Bryon A., Sämann, Philipp G., Penninx, Brenda, Nawijn, Laura, Veltman, Dick J., Aftanas, Lyubomir, Brak, Ivan V., Filimonova, Elena A., Osipov, Evgeniy A., Reneman, Liesbeth, Schrantee, Anouk, Grabe, Hans J., Van der Auwera, Sandra, Wittfeld, Katharina, Hosten, Norbert, Völzke, Henry, Sim, Kang, Gotlib, Ian H., Sacchet, Matthew D., Lagopoulos, Jim, Hatton, Sean N., Hickie, Ian, Pozzi, Elena, Thompson, Paul M., Jahanshad, Neda, Schmaal, Lianne, Baune, Bernhard T., and Dannlowski, Udo

Published
2021
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25. Analysis of volume and topography of adipose tissue in the trunk: Results of MRI of 11,141 participants in the German National Cohort

Author

Haueise, Tobias, primary, Schick, Fritz, additional, Stefan, Norbert, additional, Schlett, Christopher L., additional, Weiss, Jakob B., additional, Nattenmüller, Johanna, additional, Göbel-Guéniot, Katharina, additional, Norajitra, Tobias, additional, Nonnenmacher, Tobias, additional, Kauczor, Hans-Ulrich, additional, Maier-Hein, Klaus H., additional, Niendorf, Thoralf, additional, Pischon, Tobias, additional, Jöckel, Karl-Heinz, additional, Umutlu, Lale, additional, Peters, Annette, additional, Rospleszcz, Susanne, additional, Kröncke, Thomas, additional, Hosten, Norbert, additional, Völzke, Henry, additional, Krist, Lilian, additional, Willich, Stefan N., additional, Bamberg, Fabian, additional, and Machann, Juergen, additional

Published
2023
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31. Subcortical shape alterations in major depressive disorder

Author

Ho, Tiffany C, Gutman, Boris, Grotegerd, Dominik, Redlich, Ronny, Jansen, Andreas, Kircher, Tilo, Krug, Axel, Meinert, Susanne, Nenadic, Igor, Opel, Nils, Dinga, Richard, Veltman, Dick J, Pozzi, Elena, Schnell, Knut, Veer, Ilya, Psychiatry, Brain Research Department of, Walter, Henrik, Gotlib, Ian H, Sacchet, Matthew D, Aleman, André, Groenewold, Nynke A, Stein, Dan J, Li, Meng, Grabe, Hans J, Walter, Martin, Ching, Christopher R K, Jahanshad, Neda, Ragothaman, Anjanibhargavi, Isaev, Dmitry, Zavaliangos-Petropulu, Artemis, Thompson, Paul M, Sämann, Philipp G, Schmaal, Lianne, Hosten, Norbert, Wittfeld, Katharina, Völzke, Henry, Baune, Bernhard, Dannlowski, Udo, Förster, Katharina, Academic Medical Center, Ontwikkelingspsychologie (Psychologie, FMG), Psychiatry, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Neuroscience - Brain Imaging, Clinical Cognitive Neuropsychiatry Research Program (CCNP), and Clinical Neuropsychology

Subjects
pathology [Corpus Striatum], CORTEX, diagnostic imaging [Corpus Striatum], STRESS, hippocampus, nucleus accumbens, MODELS, shape analysis, Neuroimaging, diagnostic imaging [Depressive Disorder, Major], behavioral disciplines and activities, pathology [Thalamus], Thalamus, mental disorders, Humans, Multicenter Studies as Topic, HIPPOCAMPAL SUBFIELDS, Radiology, Nuclear Medicine and imaging, ddc:610, diagnostic imaging [Amygdala], BRAIN, NEURONS, Research Articles, METAANALYSIS, diagnostic imaging [Hippocampus], pathology [Depressive Disorder, Major], diagnostic imaging [Thalamus], Depressive Disorder, Major, Radiological and Ultrasound Technology, major depressive disorder (MDD), ABNORMALITIES, ENIGMA, BIPOLAR DISORDER, amygdala, Corpus Striatum, AMYGDALA VOLUME, pathology [Hippocampus], Neurology, nervous system, pathology [Amygdala], Neurology (clinical), Anatomy, Research Article
Abstract

Alterations in regional subcortical brain volumes have been investigated as part of the efforts of an international consortium, ENIGMA, to identify reliable neural correlates of major depressive disorder (MDD). Given that subcortical structures are comprised of distinct subfields, we sought to build significantly from prior work by precisely mapping localized MDD-related differences in subcortical regions using shape analysis. In this meta-analysis of subcortical shape from the ENIGMA-MDD working group, we compared 1,781 patients with MDD and 2,953 healthy controls (CTL) on individual measures of shape metrics (thickness and surface area) on the surface of seven bilateral subcortical structures: nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Harmonized data processing and statistical analyses were conducted locally at each site, and findings were aggregated by meta-analysis. Relative to CTL, patients with adolescent-onset MDD (≤ 21 years) had lower thickness and surface area of the subiculum, cornu ammonis (CA) 1 of the hippocampus and basolateral amygdala (Cohen's d = −0.164 to −0.180). Relative to first-episode MDD, recurrent MDD patients had lower thickness and surface area in the CA1 of the hippocampus and the basolateral amygdala (Cohen's d = −0.173 to −0.184). Our results suggest that previously reported MDD-associated volumetric differences may be localized to specific subfields of these structures that have been shown to be sensitive to the effects of stress, with important implications for mapping treatments to patients based on specific neural targets and key clinical features.

Published
2022

32. Do brachycephaly and nose size predict the severity of obstructive sleep apnea (OSA)? A sample‐based geometric morphometric analysis of craniofacial variation in relation to OSA syndrome and the role of confounding factors

Author

Daboul, Amro, primary, Krüger, Markus, additional, Ivanovska, Tatyana, additional, Obst, Anne, additional, Ewert, Ralf, additional, Stubbe, Beate, additional, Fietze, Ingo, additional, Penzel, Thomas, additional, Hosten, Norbert, additional, Biffar, Reiner, additional, and Cardini, Andrea, additional

Published
2022
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34. Epigenetic and integrative cross-omics analyses of cerebral white matter hyperintensities on MRI

Author

Yang, Yunju, primary, Knol, Maria J, additional, Wang, Ruiqi, additional, Mishra, Aniket, additional, Liu, Dan, additional, Luciano, Michelle, additional, Teumer, Alexander, additional, Armstrong, Nicola, additional, Bis, Joshua C, additional, Jhun, Min A, additional, Li, Shuo, additional, Adams, Hieab H H, additional, Aziz, Nasir Ahmad, additional, Bastin, Mark E, additional, Bourgey, Mathieu, additional, Brody, Jennifer A, additional, Frenzel, Stefan, additional, Gottesman, Rebecca F, additional, Hosten, Norbert, additional, Hou, Lifang, additional, Kardia, Sharon L R, additional, Lohner, Valerie, additional, Marquis, Pascale, additional, Maniega, Susana Muñoz, additional, Satizabal, Claudia L, additional, Sorond, Farzaneh A, additional, Valdés Hernández, Maria C, additional, van Duijn, Cornelia M, additional, Vernooij, Meike W, additional, Wittfeld, Katharina, additional, Yang, Qiong, additional, Zhao, Wei, additional, Boerwinkle, Eric, additional, Levy, Daniel, additional, Deary, Ian J, additional, Jiang, Jiyang, additional, Mather, Karen A, additional, Mosley, Thomas H, additional, Psaty, Bruce M, additional, Sachdev, Perminder S, additional, Smith, Jennifer A, additional, Sotoodehnia, Nona, additional, DeCarli, Charles S, additional, Breteler, Monique M B, additional, Ikram, M Arfan, additional, Grabe, Hans J, additional, Wardlaw, Joanna, additional, Longstreth, W T, additional, Launer, Lenore J, additional, Seshadri, Sudha, additional, Debette, Stephanie, additional, and Fornage, Myriam, additional

Published
2022
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35. Interventional Oncology

Author

Clasen, Stephan, Pereira, Philippe L., Lubienski, Andreas, Schäfer, Arnd-Oliver, Mahnken, Andreas H., Helmberger, Thomas, Vogl, Thomas J., Eichler, Katrin, Lehnert, Thomas, Mack, Martin G., Meister, Dirk, Rosenberg, Christian, Hosten, Norbert, Düx, Markus, Mohnike, Konrad, Ricke, Jens, Beck, Alexander, Hengst, Susanne, Mahnken, Andreas H., editor, and Ricke, Jens, editor

Published
2009
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39. Brain, Head, and Neck

Author

Wintermark, Max, Wirt, Michael D., Mukherjee, Pratik, Zaharchuk, Greg, Barbier, Emmanuel, Dillon, William P., Ertl-Wagner, Birgit B., Rummeny, Claudia, Essig, Marco, Bergen, Daryl C., Fagnou, John M., Sevick, Robert, Tali, E. Turgut, Gültekin, Serap, Karimi, Sasan, Holodny, Andrei I., Kanagaki, Mitsunori, Sato, Noriko, Miki, Yukio, Hosten, Norbert, Zwicker, B., Langer, Mathias, Maroldi, Roberto, Farina, D., Borghesi, Andrea, Botturi, Elisa, Ambrosi, Claudia, Stambuk, Hilda, Fischbein, Nancy, Reiser, Maximilian F., editor, Semmler, Wolfhard, editor, and Hricak, Hedvig, editor

Published
2008
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41. Do brachycephaly and nose size predict the severity of obstructive sleep apnea (OSA)? A sample‐based geometric morphometric analysis of craniofacial variation in relation to OSA syndrome and the role of confounding factors.

Author

Daboul, Amro, Krüger, Markus, Ivanonvka, Tatyana, Obst, Anne, Ewert, Ralf, Stubbe, Beate, Fietze, Ingo, Penzel, Thomas, Hosten, Norbert, Biffar, Reiner, and Cardini, Andrea

Subjects
SLEEP apnea syndromes, GEOMETRIC analysis, SOMNOLOGY, BRACHYCEPHALY, NOSE, SYNDROMES, MORPHOMETRICS
Abstract

Summary: Obstructive sleep apnea is a common disorder that leads to sleep fragmentation and is potentially bidirectionally related to a variety of comorbidities, including an increased risk of heart failure and stroke. It is often considered a consequence of anatomical abnormalities, especially in the head and neck, but its pathophysiology is likely to be multifactorial in origin. With geometric morphometrics, and a large sample of adults from the Study for Health in Pomerania, we explore the association of craniofacial morphology to the apnea–hypopnea index used as an estimate of obstructive sleep apnea severity. We show that craniofacial size and asymmetry, an aspect of morphological variation seldom analysed in obstructive sleep apnea research, are both uncorrelated to apnea–hypopnea index. In contrast, as in previous analyses, we find evidence that brachycephaly and larger nasal proportions might be associated to obstructive sleep apnea severity. However, this correlational signal is weak and completely disappears when age‐related shape variation is statistically controlled for. Our findings suggest that previous work might need to be re‐evaluated, and urge researchers to take into account the role of confounders to avoid potentially spurious findings in association studies. [ABSTRACT FROM AUTHOR]

Published
2023
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42. Quantitative Diffusion-Weighted MRI of Neuroblastoma.

Author

Abele, Niklas, Langner, Soenke, Felbor, Ute, Lode, Holger, and Hosten, Norbert

Subjects
DIGITAL image processing, BIOMARKERS, NEUROBLASTOMA, MAGNETIC resonance imaging, RETROSPECTIVE studies, MANN Whitney U Test, TUMOR classification, GENE expression, DESCRIPTIVE statistics
Abstract

Simple Summary: In this study quantified diffusion weitgthed imaging in MRI was analized in neuroblastoma. We were able to show a significant increase of apparent diffusion coefficient in regressive diseases and a decrease for progressive diseases. This was even true within the first 120 days after the start of therapy. Neuroblastoma is the most common extracranial, malignant, solid tumor found in children. In more than one-third of cases, the tumor is in an advanced stage, with limited resectability. The treatment options include resection, with or without (neo-/) adjuvant therapy, and conservative therapy, the latter even with curative intent. Contrast-enhanced MRI is used for staging and therapy monitoring. Diffusion-weighted imaging (DWI) is often included. DWI allows for a calculation of the apparent diffusion coefficient (ADC) for quantitative assessment. Histological tumor characteristics can be derived from ADC maps. Monitoring the response to treatment is possible using ADC maps, with an increase in ADC values in cases of a response to therapy. Changes in the ADC value precede volume reduction. The usual criteria for determining the response to therapy can therefore be supplemented by ADC values. While these changes have been observed in neuroblastoma, early changes in the ADC value in response to therapy are less well described. In this study, we evaluated whether there is an early change in the ADC values in neuroblastoma under therapy; if this change depends on the form of therapy; and whether this change may serve as a prognostic marker. We retrospectively evaluated neuroblastoma cases treated in our institution between June 2007 and August 2014. The examinations were grouped as 'prestaging'; 'intermediate staging'; 'final staging'; and 'follow-up'. A classification of "progress", "stable disease", or "regress" was made. For the determination of ADC values, regions of interest were drawn along the borders of all tumor manifestations. To calculate ADC changes (∆ADC), the respective MRI of the prestaging was used as a reference point or, in the case of therapies that took place directly after previous therapies, the associated previous staging. In the follow-up examinations, the previous examination was used as a reference point. The ∆ADC were grouped into ∆ADCregress for regressive disease, ∆ADCstable for stable disease, and ∆ADC for progressive disease. In addition, examinations at 60 to 120 days from the baseline were grouped as er∆ADCregress, er∆ADCstable, and er∆ADCprogress. Any differences were tested for significance using the Mann–Whitney test (level of significance: p < 0.05). In total, 34 patients with 40 evaluable tumor manifestations and 121 diffusion-weighted MRI examinations were finally included. Twenty-seven patients had INSS stage IV neuroblastoma, and seven had INSS stage III neuroblastoma. A positive N-Myc expression was found in 11 tumor diseases, and 17 patients tested negative for N-Myc (with six cases having no information). 26 patients were assigned to the high-risk group according to INRG and eight patients to the intermediate-risk group. There was a significant difference in mean ADC values from the high-risk group compared to those from the intermediate-risk group, according to INRG. The differences between the mean ∆ADC values (absolute and percentage) according to the course of the disease were significant: between ∆ADCregress and ∆ADCstable, between ∆ADCprogress and ∆ADCstable, as well as between ∆ADCregress and ∆ADCprogress. The differences between the mean er∆ADC values (absolute and percentage) according to the course of the disease were significant: between er∆ADCregress and er∆ADCstable, as well as between er∆ADCregress and er∆ADCprogress. Forms of therapy, N-Myc status, and risk groups showed no further significant differences in mean ADC values and ∆ADC/er∆ADC. A clear connection between the ADC changes and the response to therapy could be demonstrated. This held true even within the first 120 days after the start of therapy: an increase in the ADC value corresponds to a probable response to therapy, while a decrease predicts progression. Minimal or no changes were seen in cases of stable disease. [ABSTRACT FROM AUTHOR]

Published
2023
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43. Laser-Induced Thermotherapy

Author

Mensel, Birger, Weigel, Christiane, Hosten, Norbert, Schlag, P. M., editor, Senn, H. -J., editor, Kleihues, P., editor, Stiefel, F., editor, Groner, B., editor, Wallgren, A., editor, Rentchnik, P., editor, and Stroszczynski, Christian, editor

Published
2006
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45. Circulating Metabolome and White Matter Hyperintensities in Females and Males

Author

SLIZ, Eeva, SHIN, Jean, AHMAD, Shahzad, WILLIAMS, Dylan M, FRENZEL, Stefan, GAUSS, Friederike, HARRIS, Sarah E., HENNING, Ann-Kristin, VALDES HERNANDEZ, Maria Del C., HU, Yi-Han, JIMENEZ, Beatriz, SARGURUPREMRAJ, Muralidharan, SUDRE, Carole, WANG, Ruiqi, WITTFELD, Katharina, YANG, Qiong, WARDLAW, Joanna M., VOLZKE, Henry, VERNOOIJ, Meike W., SCHOTT, Jonathan M., RICHARDS, Marcus, PROITSI, Petroula, NAUCK, Matthias, LEWIS, Matthew R., LAUNER, Lenore, HOSTEN, Norbert, GRABE, Hans J., GHANBARI, Mohsen, DEARY, Ian J., COX, Simon R., CHATURVEDI, Nishi, BARNES, Josephine, ROTTER, Jerome I., DEBETTE, Stephanie, IKRAM, M. Arfan, FORNAGE, Myriam, PAUS, Tomas, SESHADRI, Sudha, and PAUSOVA, Zdenka

Published
2022

46. Whole-Body Magnetic Resonance Imaging in the Large Population-Based German National Cohort Study : Predictive Capability of Automated Image Quality Assessment for Protocol Repetitions

Author

Schuppert, Christopher, Krüchten, Ricarda von, Hirsch, Jochen G., Rospleszcz, Susanne, Hoinkiss, Daniel C., Selder, Sonja, Köhn, Alexander, Stackelberg, Oyunbileg von, Peters, Annette, Völzke, Henry, Kröncke, Thomas, Niendorf, Thoralf, Forsting, Michael, Hosten, Norbert, Hendel, Thomas, Pischon, Tobias, Jöckel, Karl-Heinz, Kaaks, Rudolf, Bamberg, Fabian, Kauczor, Hans-Ulrich, Günther, Matthias, Schlett, Christopher L., von Krüchten, Ricarda, and von Stackelberg, Oyunbileg

Subjects
Cohort Studies, Medizin, Humans, Multicenter Studies as Topic, Reproducibility of Results, Radiology, Nuclear Medicine and imaging, Whole Body Imaging, General Medicine, Prospective Studies, Magnetic Resonance Imaging, Retrospective Studies
Abstract

Reproducible image quality is of high relevance for large cohort studies and can be challenging for magnetic resonance imaging (MRI). Automated image quality assessment may contribute to conducting radiologic studies effectively.The aims of this study were to assess protocol repetition frequency in population-based whole-body MRI along with its effect on examination time and to examine the applicability of automated image quality assessment for predicting decision-making regarding repeated acquisitions.All participants enrolled in the prospective, multicenter German National Cohort (NAKO) study who underwent whole-body MRI at 1 of 5 sites from 2014 to 2016 were included in this analysis (n = 11,347). A standardized examination program of 12 protocols was used. Acquisitions were carried out by certified radiologic technologists, who were authorized to repeat protocols based on their visual perception of image quality. Eleven image quality parameters were derived fully automatically from the acquired images, and their discrimination ability regarding baseline acquisitions and repetitions was tested.At least 1 protocol was repeated in 12% (n = 1359) of participants, and more than 1 protocol in 1.6% (n = 181). The repetition frequency differed across protocols (P0.001), imaging sites (P0.001), and over the study period (P0.001). The mean total scan time was 62.6 minutes in participants without and 67.4 minutes in participants with protocol repetitions (mean difference, 4.8 minutes; 95% confidence interval, 4.5-5.2 minutes). Ten of the automatically derived image quality parameters were individually retrospectively predictive for the repetition of particular protocols; for instance, "signal-to-noise ratio" alone provided an area under the curve of 0.65 (P0.001) for repetition of the Cardio Cine SSFP SAX protocol. Combinations generally improved prediction ability, as exemplified by "image sharpness" plus "foreground ratio" yielding an area under the curve of 0.89 (P0.001) for repetition of the Neuro T1w 3D MPRAGE protocol, versus 0.85 (P0.001) and 0.68 (P0.001) as individual parameters.Magnetic resonance imaging protocol repetitions were necessary in approximately 12% of scans even in the highly standardized setting of a large cohort study. Automated image quality assessment shows predictive value for the technologists' decision to perform protocol repetitions and has the potential to improve imaging efficiency.

Published
2022

47. Virtuelle Endoskopie bei kranialen Gefäßen

Author

Beier, Jürgen, Schmitz, Dirk, Rohlfing, Torsten, Hosten, Norbert, Felix, Roland, Brauer, W., editor, Evers, Harald, editor, Glombitza, Gerald, editor, Meinzer, Hans-Peter, editor, and Lehmann, Thomas, editor

Published
1999
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