Displaying 1 - 15 of 15
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Roe, J. M., Vidal-Piñeiro, D., Amlien, I. K., Pan, M., Sneve, M. H., Thiebaut de Schotten, M., Friedrich, P., Sha, Z., Francks, C., Eilertsen, E. M., Wang, Y., Walhovd, K. B., Fjell, A. M., & Westerhausen, R. (2023). Tracing the development and lifespan change of population-level structural asymmetry in the cerebral cortex. eLife, 12: e84685. doi:10.7554/eLife.84685.
Abstract
Cortical asymmetry is a ubiquitous feature of brain organization that is altered in neurodevelopmental disorders and aging. Achieving consensus on cortical asymmetries in humans is necessary to uncover the genetic-developmental mechanisms that shape them and factors moderating cortical lateralization. Here, we delineate population-level asymmetry in cortical thickness and surface area vertex-wise in 7 datasets and chart asymmetry trajectories across life (4-89 years; observations = 3937; 70% longitudinal). We reveal asymmetry interrelationships, heritability, and test associations in UK Biobank (N=∼37,500). Cortical asymmetry was robust across datasets. Whereas areal asymmetry is predominantly stable across life, thickness asymmetry grows in development and declines in aging. Areal asymmetry correlates in specific regions, whereas thickness asymmetry is globally interrelated across cortex and suggests high directional variability in global thickness lateralization. Areal asymmetry is moderately heritable (max h2SNP ∼19%), and phenotypic correlations are reflected by high genetic correlations, whereas heritability of thickness asymmetry is low. Finally, we detected an asymmetry association with cognition and confirm recently-reported handedness links. Results suggest areal asymmetry is developmentally stable and arises in early life, whereas developmental changes in thickness asymmetry may lead to directional variability of global thickness lateralization. Our results bear enough reproducibility to serve as a standard for future brain asymmetry studies. -
Schijven, D., Postema, M., Fukunaga, M., Matsumoto, J., Miura, K., De Zwarte, S. M., Van Haren, N. E. M., Cahn, W., Hulshoff Pol, H. E., Kahn, R. S., Ayesa-Arriola, R., Ortiz-García de la Foz, V., Tordesillas-Gutierrez, D., Vázquez-Bourgon, J., Crespo-Facorro, B., Alnæs, D., Dahl, A., Westlye, L. T., Agartz, I., Andreassen, O. A. and 129 moreSchijven, D., Postema, M., Fukunaga, M., Matsumoto, J., Miura, K., De Zwarte, S. M., Van Haren, N. E. M., Cahn, W., Hulshoff Pol, H. E., Kahn, R. S., Ayesa-Arriola, R., Ortiz-García de la Foz, V., Tordesillas-Gutierrez, D., Vázquez-Bourgon, J., Crespo-Facorro, B., Alnæs, D., Dahl, A., Westlye, L. T., Agartz, I., Andreassen, O. A., Jönsson, E. G., Kochunov, P., Bruggemann, J. M., Catts, S. V., Michie, P. T., Mowry, B. J., Quidé, Y., Rasser, P. E., Schall, U., Scott, R. J., Carr, V. J., Green, M. J., Henskens, F. A., Loughland, C. M., Pantelis, C., Weickert, C. S., Weickert, T. W., De Haan, L., Brosch, K., Pfarr, J.-K., Ringwald, K. G., Stein, F., Jansen, A., Kircher, T. T., Nenadić, I., Krämer, B., Gruber, O., Satterthwaite, T. D., Bustillo, J., Mathalon, D. H., Preda, A., Calhoun, V. D., Ford, J. M., Potkin, S. G., Chen, J., Tan, Y., Wang, Z., Xiang, H., Fan, F., Bernardoni, F., Ehrlich, S., Fuentes-Claramonte, P., Garcia-Leon, M. A., Guerrero-Pedraza, A., Salvador, R., Sarró, S., Pomarol-Clotet, E., Ciullo, V., Piras, F., Vecchio, D., Banaj, N., Spalletta, G., Michielse, S., Van Amelsvoort, T., Dickie, E. W., Voineskos, A. N., Sim, K., Ciufolini, S., Dazzan, P., Murray, R. M., Kim, W.-S., Chung, Y.-C., Andreou, C., Schmidt, A., Borgwardt, S., McIntosh, A. M., Whalley, H. C., Lawrie, S. M., Du Plessis, S., Luckhoff, H. K., Scheffler, F., Emsley, R., Grotegerd, D., Lencer, R., Dannlowski, U., Edmond, J. T., Rootes-Murdy, K., Stephen, J. M., Mayer, A. R., Antonucci, L. A., Fazio, L., Pergola, G., Bertolino, A., Díaz-Caneja, C. M., Janssen, J., Lois, N. G., Arango, C., Tomyshev, A. S., Lebedeva, I., Cervenka, S., Sellgren, C. M., Georgiadis, F., Kirschner, M., Kaiser, S., Hajek, T., Skoch, A., Spaniel, F., Kim, M., Kwak, Y. B., Oh, S., Kwon, J. S., James, A., Bakker, G., Knöchel, C., Stäblein, M., Oertel, V., Uhlmann, A., Howells, F. M., Stein, D. J., Temmingh, H. S., Diaz-Zuluaga, A. M., Pineda-Zapata, J. A., López-Jaramillo, C., Homan, S., Ji, E., Surbeck, W., Homan, P., Fisher, S. E., Franke, B., Glahn, D. C., Gur, R. C., Hashimoto, R., Jahanshad, N., Luders, E., Medland, S. E., Thompson, P. M., Turner, J. A., Van Erp, T. G., & Francks, C. (2023). Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium. Proceedings of the National Academy of Sciences of the United States of America, 120(14): e2213880120. doi:10.1073/pnas.2213880120.
Abstract
Left–right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case–control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case–control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case–control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case–control status. Subtle case–control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia. -
Sha, Z., Schijven, D., Fisher, S. E., & Francks, C. (2023). Genetic architecture of the white matter connectome of the human brain. Science Advances, 9(7): eadd2870. doi:10.1126/sciadv.add2870.
Abstract
White matter tracts form the structural basis of large-scale brain networks. We applied brain-wide tractography to diffusion images from 30,810 adults (U.K. Biobank) and found significant heritability for 90 node-level and 851 edge-level network connectivity measures. Multivariate genome-wide association analyses identified 325 genetic loci, of which 80% had not been previously associated with brain metrics. Enrichment analyses implicated neurodevelopmental processes including neurogenesis, neural differentiation, neural migration, neural projection guidance, and axon development, as well as prenatal brain expression especially in stem cells, astrocytes, microglia, and neurons. The multivariate association profiles implicated 31 loci in connectivity between core regions of the left-hemisphere language network. Polygenic scores for psychiatric, neurological, and behavioral traits also showed significant multivariate associations with structural connectivity, each implicating distinct sets of brain regions with trait-relevant functional profiles. This large-scale mapping study revealed common genetic contributions to variation in the structural connectome of the human brain.Additional information
figs. S1 to S14, legends for tables S1 to S31 tables S1 to S31 link to Preprint on bioRxiv -
Vingerhoets, G., Verhelst, H., Gerrits, R., Badcock, N., Bishop, D. V. M., Carey, D., Flindall, J., Grimshaw, G., Harris, L. J., Hausmann, M., Hirnstein, M., Jäncke, L., Joliot, M., Specht, K., Westerhausen, R., & LICI consortium (2023). Laterality indices consensus initiative (LICI): A Delphi expert survey report on recommendations to record, assess, and report asymmetry in human behavioural and brain research. Laterality, 28(2-3), 122-191. doi:10.1080/1357650X.2023.2199963.
Abstract
Laterality indices (LIs) quantify the left-right asymmetry of brain and behavioural variables and provide a measure that is statistically convenient and seemingly easy to interpret. Substantial variability in how structural and functional asymmetries are recorded, calculated, and reported, however, suggest little agreement on the conditions required for its valid assessment. The present study aimed for consensus on general aspects in this context of laterality research, and more specifically within a particular method or technique (i.e., dichotic listening, visual half-field technique, performance asymmetries, preference bias reports, electrophysiological recording, functional MRI, structural MRI, and functional transcranial Doppler sonography). Experts in laterality research were invited to participate in an online Delphi survey to evaluate consensus and stimulate discussion. In Round 0, 106 experts generated 453 statements on what they considered good practice in their field of expertise. Statements were organised into a 295-statement survey that the experts then were asked, in Round 1, to independently assess for importance and support, which further reduced the survey to 241 statements that were presented again to the experts in Round 2. Based on the Round 2 input, we present a set of critically reviewed key recommendations to record, assess, and report laterality research for various methods.Additional information
data that support the findings of this study are openly available in OSFFiles private
Request files -
Carrion Castillo, A., Pepe, A., Kong, X., Fisher, S. E., Mazoyer, B., Tzourio-Mazoyer, N., Crivello, F., & Francks, C. (2020). Genetic effects on planum temporale asymmetry and their limited relevance to neurodevelopmental disorders, intelligence or educational attainment. Cortex, 124, 137-153. doi:10.1016/j.cortex.2019.11.006.
Abstract
Previous studies have suggested that altered asymmetry of the planum temporale (PT) is associated with neurodevelopmental disorders, including dyslexia, schizophrenia, and autism. Shared genetic factors have been suggested to link PT asymmetry to these disorders. In a dataset of unrelated subjects from the general population (UK Biobank, N= 18,057), we found that PT volume asymmetry had a significant heritability of roughly 14%. In genome-wide association analysis, two loci were significantly associated with PT asymmetry, including a coding polymorphism within the gene ITIH5 that is predicted to affect the protein’s function and to be deleterious (rs41298373, P=2.01×10−15), and a locus that affects the expression of the genes BOK and DTYMK (rs7420166, P=7.54×10-10). DTYMK showed left-right asymmetry of mRNA expression in post mortem PT tissue. Cortex-wide mapping of these SNP effects revealed influences on asymmetry that went somewhat beyond the PT. Using publicly available genome-wide association statistics from large-scale studies, we saw no significant genetic correlations of PT asymmetry with autism spectrum disorder, attention deficit hyperactivity disorder, schizophrenia, educational attainment or intelligence. Of the top two individual loci associated with PT asymmetry, rs41298373 showed a tentative association with intelligence (unadjusted P=0.025), while the locus at BOK/DTYMK showed tentative association with educational attainment (unadjusted Ps<0.05). These findings provide novel insights into the genetic contributions to human brain asymmetry, but do not support a substantial polygenic association of PT asymmetry with cognitive variation and mental disorders, as far as can be discerned with current sample sizes.Additional information
Supplementary data -
Grasby, K. L., Jahanshad, N., Painter, J. N., Colodro-Conde, L., Bralten, J., Hibar, D. P., Lind, P. A., Pizzagalli, F., Ching, C. R. K., McMahon, M. A. B., Shatokhina, N., Zsembik, L. C. P., Thomopoulos, S. I., Zhu, A. H., Strike, L. T., Agartz, I., Alhusaini, S., Almeida, M. A. A., Alnæs, D., Amlien, I. K. and 341 moreGrasby, K. L., Jahanshad, N., Painter, J. N., Colodro-Conde, L., Bralten, J., Hibar, D. P., Lind, P. A., Pizzagalli, F., Ching, C. R. K., McMahon, M. A. B., Shatokhina, N., Zsembik, L. C. P., Thomopoulos, S. I., Zhu, A. H., Strike, L. T., Agartz, I., Alhusaini, S., Almeida, M. A. A., Alnæs, D., Amlien, I. K., Andersson, M., Ard, T., Armstrong, N. J., Ashley-Koch, A., Atkins, J. R., Bernard, M., Brouwer, R. M., Buimer, E. E. L., Bülow, R., Bürger, C., Cannon, D. M., Chakravarty, M., Chen, Q., Cheung, J. W., Couvy-Duchesne, B., Dale, A. M., Dalvie, S., De Araujo, T. K., De Zubicaray, G. I., De Zwarte, S. M. C., Den Braber, A., Doan, N. T., Dohm, K., Ehrlich, S., Engelbrecht, H.-R., Erk, S., Fan, C. C., Fedko, I. O., Foley, S. F., Ford, J. M., Fukunaga, M., Garrett, M. E., Ge, T., Giddaluru, S., Goldman, A. L., Green, M. J., Groenewold, N. A., Grotegerd, D., Gurholt, T. P., Gutman, B. A., Hansell, N. K., Harris, M. A., Harrison, M. B., Haswell, C. C., Hauser, M., Herms, S., Heslenfeld, D. J., Ho, N. F., Hoehn, D., Hoffmann, P., Holleran, L., Hoogman, M., Hottenga, J.-J., Ikeda, M., Janowitz, D., Jansen, I. E., Jia, T., Jockwitz, C., Kanai, R., Karama, S., Kasperaviciute, D., Kaufmann, T., Kelly, S., Kikuchi, M., Klein, M., Knapp, M., Knodt, A. R., Krämer, B., Lam, M., Lancaster, T. M., Lee, P. H., Lett, T. A., Lewis, L. B., Lopes-Cendes, I., Luciano, M., Macciardi, F., Marquand, A. F., Mathias, S. R., Melzer, T. R., Milaneschi, Y., Mirza-Schreiber, N., Moreira, J. C. V., Mühleisen, T. W., Müller-Myhsok, B., Najt, P., Nakahara, S., Nho, K., Olde Loohuis, L. M., Orfanos, D. P., Pearson, J. F., Pitcher, T. L., Pütz, B., Quidé, Y., Ragothaman, A., Rashid, F. M., Reay, W. R., Redlich, R., Reinbold, C. S., Repple, J., Richard, G., Riedel, B. C., Risacher, S. L., Rocha, C. S., Mota, N. R., Salminen, L., Saremi, A., Saykin, A. J., Schlag, F., Schmaal, L., Schofield, P. R., Secolin, R., Shapland, C. Y., Shen, L., Shin, J., Shumskaya, E., Sønderby, I. E., Sprooten, E., Tansey, K. E., Teumer, A., Thalamuthu, A., Tordesillas-Gutiérrez, D., Turner, J. A., Uhlmann, A., Vallerga, C. L., Van der Meer, D., Van Donkelaar, M. M. J., Van Eijk, L., Van Erp, T. G. M., Van Haren, N. E. M., Van Rooij, D., Van Tol, M.-J., Veldink, J. H., Verhoef, E., Walton, E., Wang, M., Wang, Y., Wardlaw, J. M., Wen, W., Westlye, L. T., Whelan, C. D., Witt, S. H., Wittfeld, K., Wolf, C., Wolfers, T., Wu, J. Q., Yasuda, C. L., Zaremba, D., Zhang, Z., Zwiers, M. P., Artiges, E., Assareh, A. A., Ayesa-Arriola, R., Belger, A., Brandt, C. L., Brown, G. G., Cichon, S., Curran, J. E., Davies, G. E., Degenhardt, F., Dennis, M. F., Dietsche, B., Djurovic, S., Doherty, C. P., Espiritu, R., Garijo, D., Gil, Y., Gowland, P. A., Green, R. C., Häusler, A. N., Heindel, W., Ho, B.-C., Hoffmann, W. U., Holsboer, F., Homuth, G., Hosten, N., Jack Jr., C. R., Jang, M., Jansen, A., Kimbrel, N. A., Kolskår, K., Koops, S., Krug, A., Lim, K. O., Luykx, J. J., Mathalon, D. H., Mather, K. A., Mattay, V. S., Matthews, S., Mayoral Van Son, J., McEwen, S. C., Melle, I., Morris, D. W., Mueller, B. A., Nauck, M., Nordvik, J. E., Nöthen, M. M., O’Leary, D. S., Opel, N., Paillère Martinot, M.-L., Pike, G. B., Preda, A., Quinlan, E. B., Rasser, P. E., Ratnakar, V., Reppermund, S., Steen, V. M., Tooney, P. A., Torres, F. R., Veltman, D. J., Voyvodic, J. T., Whelan, R., White, T., Yamamori, H., Adams, H. H. H., Bis, J. C., Debette, S., Decarli, C., Fornage, M., Gudnason, V., Hofer, E., Ikram, M. A., Launer, L., Longstreth, W. T., Lopez, O. L., Mazoyer, B., Mosley, T. H., Roshchupkin, G. V., Satizabal, C. L., Schmidt, R., Seshadri, S., Yang, Q., Alzheimer’s Disease Neuroimaging Initiative, CHARGE Consortium, EPIGEN Consortium, IMAGEN Consortium, SYS Consortium, Parkinson’s Progression Markers Initiative, Alvim, M. K. M., Ames, D., Anderson, T. J., Andreassen, O. A., Arias-Vasquez, A., Bastin, M. E., Baune, B. T., Beckham, J. C., Blangero, J., Boomsma, D. I., Brodaty, H., Brunner, H. G., Buckner, R. L., Buitelaar, J. K., Bustillo, J. R., Cahn, W., Cairns, M. J., Calhoun, V., Carr, V. J., Caseras, X., Caspers, S., Cavalleri, G. L., Cendes, F., Corvin, A., Crespo-Facorro, B., Dalrymple-Alford, J. C., Dannlowski, U., De Geus, E. J. C., Deary, I. J., Delanty, N., Depondt, C., Desrivières, S., Donohoe, G., Espeseth, T., Fernández, G., Fisher, S. E., Flor, H., Forstner, A. J., Francks, C., Franke, B., Glahn, D. C., Gollub, R. L., Grabe, H. J., Gruber, O., Håberg, A. K., Hariri, A. R., Hartman, C. A., Hashimoto, R., Heinz, A., Henskens, F. A., Hillegers, M. H. J., Hoekstra, P. J., Holmes, A. J., Hong, L. E., Hopkins, W. D., Hulshoff Pol, H. E., Jernigan, T. L., Jönsson, E. G., Kahn, R. S., Kennedy, M. A., Kircher, T. T. J., Kochunov, P., Kwok, J. B. J., Le Hellard, S., Loughland, C. M., Martin, N. G., Martinot, J.-L., McDonald, C., McMahon, K. L., Meyer-Lindenberg, A., Michie, P. T., Morey, R. A., Mowry, B., Nyberg, L., Oosterlaan, J., Ophoff, R. A., Pantelis, C., Paus, T., Pausova, Z., Penninx, B. W. J. H., Polderman, T. J. C., Posthuma, D., Rietschel, M., Roffman, J. L., Rowland, L. M., Sachdev, P. S., Sämann, P. G., Schall, U., Schumann, G., Scott, R. J., Sim, K., Sisodiya, S. M., Smoller, J. W., Sommer, I. E., St Pourcain, B., Stein, D. J., Toga, A. W., Trollor, J. N., Van der Wee, N. J. A., van 't Ent, D., Völzke, H., Walter, H., Weber, B., Weinberger, D. R., Wright, M. J., Zhou, J., Stein, J. L., Thompson, P. M., & Medland, S. E. (2020). The genetic architecture of the human cerebral cortex. Science, 367(6484): eaay6690. doi:10.1126/science.aay6690.
Abstract
The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson’s disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder. -
Hofer, E., Roshchupkin, G. V., Adams, H. H. H., Knol, M. J., Lin, H., Li, S., Zare, H., Ahmad, S., Armstrong, N. J., Satizabal, C. L., Bernard, M., Bis, J. C., Gillespie, N. A., Luciano, M., Mishra, A., Scholz, M., Teumer, A., Xia, R., Jian, X., Mosley, T. H. and 79 moreHofer, E., Roshchupkin, G. V., Adams, H. H. H., Knol, M. J., Lin, H., Li, S., Zare, H., Ahmad, S., Armstrong, N. J., Satizabal, C. L., Bernard, M., Bis, J. C., Gillespie, N. A., Luciano, M., Mishra, A., Scholz, M., Teumer, A., Xia, R., Jian, X., Mosley, T. H., Saba, Y., Pirpamer, L., Seiler, S., Becker, J. T., Carmichael, O., Rotter, J. I., Psaty, B. M., Lopez, O. L., Amin, N., Van der Lee, S. J., Yang, Q., Himali, J. J., Maillard, P., Beiser, A. S., DeCarli, C., Karama, S., Lewis, L., Harris, M., Bastin, M. E., Deary, I. J., Witte, A. V., Beyer, F., Loeffler, M., Mather, K. A., Schofield, P. R., Thalamuthu, A., Kwok, J. B., Wright, M. J., Ames, D., Trollor, J., Jiang, J., Brodaty, H., Wen, W., Vernooij, M. W., Hofman, A., Uitterlinden, A. G., Niessen, W. J., Wittfeld, K., Bülow, R., Völker, U., Pausova, Z., Pike, G. B., Maingault, S., Crivello, F., Tzourio, C., Amouyel, P., Mazoyer, B., Neale, M. C., Franz, C. E., Lyons, M. J., Panizzon, M. S., Andreassen, O. A., Dale, A. M., Logue, M., Grasby, K. L., Jahanshad, N., Painter, J. N., Colodro-Conde, L., Bralten, J., Hibar, D. P., Lind, P. A., Pizzagalli, F., Stein, J. L., Thompson, P. M., Medland, S. E., ENIGMA-consortium, Sachdev, P. S., Kremen, W. S., Wardlaw, J. M., Villringer, A., Van Duijn, C. M., Grabe, H. J., Longstreth, W. T., Fornage, M., Paus, T., Debette, S., Ikram, M. A., Schmidt, H., Schmidt, R., & Seshadri, S. (2020). Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults. Nature Communications, 11: 4796. doi:10.1038/s41467-020-18367-y.
Additional information
supplementary information -
Kong, X., Tzourio-Mazoyer, N., Joliot, M., Fedorenko, E., Liu, J., Fisher, S. E., & Francks, C. (2020). Gene expression correlates of the cortical network underlying sentence processing. Neurobiology of Language, 1(1), 77-103. doi:10.1162/nol_a_00004.
Abstract
A pivotal question in modern neuroscience is which genes regulate brain circuits that underlie cognitive functions. However, the field is still in its infancy. Here we report an integrated investigation of the high-level language network (i.e., sentence processing network) in the human cerebral cortex, combining regional gene expression profiles, task fMRI, large-scale neuroimaging meta-analysis, and resting-state functional network approaches. We revealed reliable gene expression-functional network correlations using three different network definition strategies, and identified a consensus set of genes related to connectivity within the sentence-processing network. The genes involved showed enrichment for neural development and actin-related functions, as well as association signals with autism, which can involve disrupted language functioning. Our findings help elucidate the molecular basis of the brain’s infrastructure for language. The integrative approach described here will be useful to study other complex cognitive traits. -
Kong, X., Boedhoe, P. S. W., Abe, Y., Alonso, P., Ameis, S. H., Arnold, P. D., Assogna, F., Baker, J. T., Batistuzzo, M. C., Benedetti, F., Beucke, J. C., Bollettini, I., Bose, A., Brem, S., Brennan, B. P., Buitelaar, J., Calvo, R., Cheng, Y., Cho, K. I. K., Dallaspezia, S. and 71 moreKong, X., Boedhoe, P. S. W., Abe, Y., Alonso, P., Ameis, S. H., Arnold, P. D., Assogna, F., Baker, J. T., Batistuzzo, M. C., Benedetti, F., Beucke, J. C., Bollettini, I., Bose, A., Brem, S., Brennan, B. P., Buitelaar, J., Calvo, R., Cheng, Y., Cho, K. I. K., Dallaspezia, S., Denys, D., Ely, B. A., Feusner, J., Fitzgerald, K. D., Fouche, J.-P., Fridgeirsson, E. A., Glahn, D. C., Gruner, P., Gürsel, D. A., Hauser, T. U., Hirano, Y., Hoexter, M. Q., Hu, H., Huyser, C., James, A., Jaspers-Fayer, F., Kathmann, N., Kaufmann, C., Koch, K., Kuno, M., Kvale, G., Kwon, J. S., Lazaro, L., Liu, Y., Lochner, C., Marques, P., Marsh, R., Martínez-Zalacaín, I., Mataix-Cols, D., Medland, S. E., Menchón, J. M., Minuzzi, L., Moreira, P. S., Morer, A., Morgado, P., Nakagawa, A., Nakamae, T., Nakao, T., Narayanaswamy, J. C., Nurmi, E. L., O'Neill, J., Pariente, J. C., Perriello, C., Piacentini, J., Piras, F., Piras, F., Pittenger, C., Reddy, Y. J., Rus-Oswald, O. G., Sakai, Y., Sato, J. R., Schmaal, L., Simpson, H. B., Soreni, N., Soriano-Mas, C., Spalletta, G., Stern, E. R., Stevens, M. C., Stewart, S. E., Szeszko, P. R., Tolin, D. F., Tsuchiyagaito, A., Van Rooij, D., Van Wingen, G. A., Venkatasubramanian, G., Wang, Z., Yun, J.-Y., ENIGMA-OCD Working Group, Thompson, P. M., Stein, D. J., Van den Heuvel, O. A., & Francks, C. (2020). Mapping cortical and subcortical asymmetry in obsessive-compulsive disorder: Findings from the ENIGMA Consortium. Biological Psychiatry, 87(12), 1022-1034. doi:10.1016/j.biopsych.2019.04.022.
Abstract
Objective
Lateralized dysfunction has been suggested in Obsessive-Compulsive Disorder (OCD). However, it is currently unclear whether OCD is characterized by abnormal patterns of structural brain asymmetry. Here we carried out by far the largest study of brain structural asymmetry in OCD.
Method
We studied a collection of 16 pediatric datasets (501 OCD patients and 439 healthy controls), as well as 30 adult datasets (1777 patients and 1654 controls) from the OCD Working Group within the ENIGMA (Enhancing Neuro-Imaging Genetics through Meta-Analysis) consortium. Asymmetries of the volumes of subcortical structures, and of regional cortical thickness and surface area measures, were assessed based on T1-weighted MRI scans, using harmonized image analysis and quality control protocols. We investigated possible alterations of brain asymmetry in OCD patients. We also explored potential associations of asymmetry with specific aspects of the disorder and medication status.
Results
In the pediatric datasets, the largest case-control differences were observed for volume asymmetry of the thalamus (more leftward; Cohen’s d = 0.19) and the pallidum (less leftward; d = -0.21). Additional analyses suggested putative links between these asymmetry patterns and medication status, OCD severity, and/or anxiety and depression comorbidities. No significant case-control differences were found in the adult datasets.
Conclusions
The results suggest subtle changes of the average asymmetry of subcortical structures in pediatric OCD, which are not detectable in adults with the disorder. These findings may reflect altered neurodevelopmental processes in OCD. -
Postema, M., Carrion Castillo, A., Fisher, S. E., Vingerhoets, G., & Francks, C. (2020). The genetics of situs inversus without primary ciliary dyskinesia. Scientific Reports, 10: 3677. doi:10.1038/s41598-020-60589-z.
Abstract
Situs inversus (SI), a left-right mirror reversal of the visceral organs, can occur with recessive Primary Ciliary Dyskinesia (PCD). However, most people with SI do not have PCD, and the etiology of their condition remains poorly studied. We sequenced the genomes of 15 people with SI, of which six had PCD, as well as 15 controls. Subjects with non-PCD SI in this sample had an elevated rate of left-handedness (five out of nine), which suggested possible developmental mechanisms linking brain and body laterality. The six SI subjects with PCD all had likely recessive mutations in genes already known to cause PCD. Two non-PCD SI cases also had recessive mutations in known PCD genes, suggesting reduced penetrance for PCD in some SI cases. One non-PCD SI case had recessive mutations in PKD1L1, and another in CFAP52 (also known as WDR16). Both of these genes have previously been linked to SI without PCD. However, five of the nine non-PCD SI cases, including three of the left-handers in this dataset, had no obvious monogenic basis for their condition. Environmental influences, or possible random effects in early development, must be considered.Additional information
Supplementary information -
Thompson, P. M., Jahanshad, N., Ching, C. R. K., Salminen, L. E., Thomopoulos, S. I., Bright, J., Baune, B. T., Bertolín, S., Bralten, J., Bruin, W. B., Bülow, R., Chen, J., Chye, Y., Dannlowski, U., De Kovel, C. G. F., Donohoe, G., Eyler, L. T., Faraone, S. V., Favre, P., Filippi, C. A. and 151 moreThompson, P. M., Jahanshad, N., Ching, C. R. K., Salminen, L. E., Thomopoulos, S. I., Bright, J., Baune, B. T., Bertolín, S., Bralten, J., Bruin, W. B., Bülow, R., Chen, J., Chye, Y., Dannlowski, U., De Kovel, C. G. F., Donohoe, G., Eyler, L. T., Faraone, S. V., Favre, P., Filippi, C. A., Frodl, T., Garijo, D., Gil, Y., Grabe, H. J., Grasby, K. L., Hajek, T., Han, L. K. M., Hatton, S. N., Hilbert, K., Ho, T. C., Holleran, L., Homuth, G., Hosten, N., Houenou, J., Ivanov, I., Jia, T., Kelly, S., Klein, M., Kwon, J. S., Laansma, M. A., Leerssen, J., Lueken, U., Nunes, A., O'Neill, J., Opel, N., Piras, F., Piras, F., Postema, M., Pozzi, E., Shatokhina, N., Soriano-Mas, C., Spalletta, G., Sun, D., Teumer, A., Tilot, A. K., Tozzi, L., Van der Merwe, C., Van Someren, E. J. W., Van Wingen, G. A., Völzke, H., Walton, E., Wang, L., Winkler, A. M., Wittfeld, K., Wright, M. J., Yun, J.-Y., Zhang, G., Zhang-James, Y., Adhikari, B. M., Agartz, I., Aghajani, M., Aleman, A., Althoff, R. R., Altmann, A., Andreassen, O. A., Baron, D. A., Bartnik-Olson, B. L., Bas-Hoogendam, J. M., Baskin-Sommers, A. R., Bearden, C. E., Berner, L. A., Boedhoe, P. S. W., Brouwer, R. M., Buitelaar, J. K., Caeyenberghs, K., Cecil, C. A. M., Cohen, R. A., Cole, J. H., Conrod, P. J., De Brito, S. A., De Zwarte, S. M. C., Dennis, E. L., Desrivieres, S., Dima, D., Ehrlich, S., Esopenko, C., Fairchild, G., Fisher, S. E., Fouche, J.-P., Francks, C., Frangou, S., Franke, B., Garavan, H. P., Glahn, D. C., Groenewold, N. A., Gurholt, T. P., Gutman, B. A., Hahn, T., Harding, I. H., Hernaus, D., Hibar, D. P., Hillary, F. G., Hoogman, M., Hulshoff Pol, H. E., Jalbrzikowski, M., Karkashadze, G. A., Klapwijk, E. T., Knickmeyer, R. C., Kochunov, P., Koerte, I. K., Kong, X., Liew, S.-L., Lin, A. P., Logue, M. W., Luders, E., Macciardi, F., Mackey, S., Mayer, A. R., McDonald, C. R., McMahon, A. B., Medland, S. E., Modinos, G., Morey, R. A., Mueller, S. C., Mukherjee, P., Namazova-Baranova, L., Nir, T. M., Olsen, A., Paschou, P., Pine, D. S., Pizzagalli, F., Rentería, M. E., Rohrer, J. D., Sämann, P. G., Schmaal, L., Schumann, G., Shiroishi, M. S., Sisodiya, S. M., Smit, D. J. A., Sønderby, I. E., Stein, D. J., Stein, J. L., Tahmasian, M., Tate, D. F., Turner, J. A., Van den Heuvel, O. A., Van der Wee, N. J. A., Van der Werf, Y. D., Van Erp, T. G. M., Van Haren, N. E. M., Van Rooij, D., Van Velzen, L. S., Veer, I. M., Veltman, D. J., Villalon-Reina, J. E., Walter, H., Whelan, C. D., Wilde, E. A., Zarei, M., Zelman, V., & Enigma Consortium (2020). ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries. Translational Psychiatry, 10(1): 100. doi:10.1038/s41398-020-0705-1.
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.Additional information
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Francks, C., Paracchini, S., Smith, S. D., Richardson, A. J., Scerri, T. S., Cardon, L. R., Marlow, A. J., MacPhie, I. L., Walter, J., Pennington, B. F., Fisher, S. E., Olson, R. K., DeFries, J. C., Stein, J. F., & Monaco, A. P. (2004). A 77-kilobase region of chromosome 6p22.2 is associated with dyslexia in families from the United Kingdom and from the United States. American Journal of Human Genetics, 75(6), 1046-1058. doi:10.1086/426404.
Abstract
Several quantitative trait loci (QTLs) that influence developmental dyslexia (reading disability [RD]) have been mapped to chromosome regions by linkage analysis. The most consistently replicated area of linkage is on chromosome 6p23-21.3. We used association analysis in 223 siblings from the United Kingdom to identify an underlying QTL on 6p22.2. Our association study implicates a 77-kb region spanning the gene TTRAP and the first four exons of the neighboring uncharacterized gene KIAA0319. The region of association is also directly upstream of a third gene, THEM2. We found evidence of these associations in a second sample of siblings from the United Kingdom, as well as in an independent sample of twin-based sibships from Colorado. One main RD risk haplotype that has a frequency of ∼12% was found in both the U.K. and U.S. samples. The haplotype is not distinguished by any protein-coding polymorphisms, and, therefore, the functional variation may relate to gene expression. The QTL influences a broad range of reading-related cognitive abilities but has no significant impact on general cognitive performance in these samples. In addition, the QTL effect may be largely limited to the severe range of reading disability. -
Loo, S. K., Fisher, S. E., Francks, C., Ogdie, M. N., MacPhie, I. L., Yang, M., McCracken, J. T., McGough, J. J., Nelson, S. F., Monaco, A. P., & Smalley, S. L. (2004). Genome-wide scan of reading ability in affected sibling pairs with attention-deficit/hyperactivity disorder: Unique and shared genetic effects. Molecular Psychiatry, 9, 485-493. doi:10.1038/sj.mp.4001450.
Abstract
Attention-deficit/hyperactivity disorder (ADHD) and reading disability (RD) are common highly heritable disorders of childhood, which frequently co-occur. Data from twin and family studies suggest that this overlap is, in part, due to shared genetic underpinnings. Here, we report the first genome-wide linkage analysis of measures of reading ability in children with ADHD, using a sample of 233 affected sibling pairs who previously participated in a genome-wide scan for susceptibility loci in ADHD. Quantitative trait locus (QTL) analysis of a composite reading factor defined from three highly correlated reading measures identified suggestive linkage (multipoint maximum lod score, MLS>2.2) in four chromosomal regions. Two regions (16p, 17q) overlap those implicated by our previous genome-wide scan for ADHD in the same sample: one region (2p) provides replication for an RD susceptibility locus, and one region (10q) falls approximately 35 cM from a modestly highlighted region in an independent genome-wide scan of siblings with ADHD. Investigation of an individual reading measure of Reading Recognition supported linkage to putative RD susceptibility regions on chromosome 8p (MLS=2.4) and 15q (MLS=1.38). Thus, the data support the existence of genetic factors that have pleiotropic effects on ADHD and reading ability--as suggested by shared linkages on 16p, 17q and possibly 10q--but also those that appear to be unique to reading--as indicated by linkages on 2p, 8p and 15q that coincide with those previously found in studies of RD. Our study also suggests that reading measures may represent useful phenotypes in ADHD research. The eventual identification of genes underlying these unique and shared linkages may increase our understanding of ADHD, RD and the relationship between the two. -
Ogdie, M. N., Fisher, S. E., Yang, M., Ishii, J., Francks, C., Loo, S. K., Cantor, R. M., McCracken, J. T., McGough, J. J., Smalley, S. L., & Nelson, S. F. (2004). Attention Deficit Hyperactivity Disorder: Fine mapping supports linkage to 5p13, 6q12, 16p13, and 17p11. American Journal of Human Genetics, 75(4), 661-668. doi:10.1086/424387.
Abstract
We completed fine mapping of nine positional candidate regions for attention-deficit/hyperactivity disorder (ADHD) in an extended population sample of 308 affected sibling pairs (ASPs), constituting the largest linkage sample of families with ADHD published to date. The candidate chromosomal regions were selected from all three published genomewide scans for ADHD, and fine mapping was done to comprehensively validate these positional candidate regions in our sample. Multipoint maximum LOD score (MLS) analysis yielded significant evidence of linkage on 6q12 (MLS 3.30; empiric P=.024) and 17p11 (MLS 3.63; empiric P=.015), as well as suggestive evidence on 5p13 (MLS 2.55; empiric P=.091). In conjunction with the previously reported significant linkage on the basis of fine mapping 16p13 in the same sample as this report, the analyses presented here indicate that four chromosomal regions—5p13, 6q12, 16p13, and 17p11—are likely to harbor susceptibility genes for ADHD. The refinement of linkage within each of these regions lays the foundation for subsequent investigations using association methods to detect risk genes of moderate effect size. -
Scerri, T. S., Fisher, S. E., Francks, C., MacPhie, I. L., Paracchini, S., Richardson, A. J., Stein, J. F., & Monaco, A. P. (2004). Putative functional alleles of DYX1C1 are not associated with dyslexia susceptibility in a large sample of sibling pairs from the UK [Letter to JMG]. Journal of Medical Genetics, 41(11), 853-857. doi:10.1136/jmg.2004.018341.
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