Displaying 1 - 11 of 11
  • Pu, Y., Francks, C., & Kong, X. (2025). Global brain asymmetry. Trends in Cognitive Sciences, 29(2), 114-117. doi:10.1016/j.tics.2024.10.008.

    Abstract

    Lateralization is a defining characteristic of the human brain, often studied through localized approaches that focus on interhemispheric differences between homologous pairs of regions. It is also important to emphasize an integrative perspective of global brain asymmetry, in which hemispheric differences are understood through global patterns across the entire brain.
  • Korbmacher, M., Tranfa, M., Pontillo, G., Van der Meer, D., Wang, M.-Y., Andreassen, O. A., Westlye, L. T., & Maximov, I. I. (2025). White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life. NeuroImage, 310: 121132. doi:10.1016/j.neuroimage.2025.121132.

    Abstract

    Advanced diffusion magnetic resonance imaging (dMRI) allows one to probe and assess brain white matter (WM) organisation and microstructure in vivo. Various dMRI models with different theoretical and practical assumptions have been developed, representing partly overlapping characteristics of the underlying brain biology with potentially complementary value in the cognitive and clinical neurosciences. To which degree the different dMRI metrics relate to clinically relevant geno- and phenotypes is still debated. Hence, we investigate how tract-based and whole WM skeleton parameters from different dMRI approaches associate with clinically relevant and white matter-related phenotypes (sex, age, pulse pressure (PP), body-mass-index (BMI), brain asymmetry) and genetic markers in the UK Biobank (UKB, n=52,140) and the Adolescent Brain Cognitive Development (ABCD) Study (n=5,844). In general, none of the imaging approaches could explain all examined phenotypes, though the approaches were overall similar in explaining variability of the examined phenotypes. Nevertheless, particular diffusion parameters of the used dMRI approaches stood out in explaining some important phenotypes known to correlate with general human health outcomes. A multi-compartment Bayesian dMRI approach provided the strongest WM associations with age, and together with diffusion tensor imaging, the largest accuracy for sex-classifications. We find a similar pattern of metric and tract-dependent asymmetries across datasets, with stronger asymmetries in ABCD data. The magnitude of WM associations with polygenic scores as well as PP depended more on the sample, and likely age, than dMRI metrics. However, kurtosis was most indicative of BMI and potentially of bipolar disorder polygenic scores. We conclude that WM microstructure is differentially associated with clinically relevant pheno- and genotypes at different points in life.

    Additional information

    supplementary data supplementary tables
  • Rivera-Olvera, A., Houwing, D. J., Ellegood, J., Masifi, S., Martina, S., Silberfeld, A., Pourquie, O., Lerch, J. P., Francks, C., Homberg, J. R., Van Heukelum, S., & Grandjean, J. (2025). The universe is asymmetric, the mouse brain too. Molecular Psychiatry, 30, 489-496. doi:10.1038/s41380-024-02687-2.

    Abstract

    Hemispheric brain asymmetry is a basic organizational principle of the human brain and has been implicated in various psychiatric conditions, including autism spectrum disorder. Brain asymmetry is not a uniquely human feature and is observed in other species such as the mouse. Yet, asymmetry patterns are generally nuanced, and substantial sample sizes are required to detect these patterns. In this pre-registered study, we use a mouse dataset from the Province of Ontario Neurodevelopmental Network, which comprises structural MRI data from over 2000 mice, including genetic models for autism spectrum disorder, to reveal the scope and magnitude of hemispheric asymmetry in the mouse. Our findings demonstrate the presence of robust hemispheric asymmetry in the mouse brain, such as larger right hemispheric volumes towards the anterior pole and larger left hemispheric volumes toward the posterior pole, opposite to what has been shown in humans. This suggests the existence of species-specific traits. Further clustering analysis identified distinct asymmetry patterns in autism spectrum disorder models, a phenomenon that is also seen in atypically developing participants. Our study shows potential for the use of mouse models in studying the biological bases of typical and atypical brain asymmetry but also warrants caution as asymmetry patterns seem to differ between humans and mice.

    Additional information

    tables link to preprint on BioRxiv
  • Sha, Z., & Francks, C. (2025). Large-scale genetic mapping for human brain asymmetry. In C. Papagno, & P. Corballis (Eds.), Handbook of Clinical Neurology: Cerebral Asymmetries (pp. 241-254). Amsterdam: Elsevier.

    Abstract

    Left-right asymmetry is an important aspect of human brain organization for functions including language and hand motor control, which can be altered in some psychiatric traits. The last five years have seen rapid advances in the identification of specific genes linked to variation in asymmetry of the human brain and/or handedness. These advances have been driven by a new generation of large-scale genome-wide association studies, carried out in samples ranging from roughly 16,000 to over 1.5 million participants. The implicated genes tend to be most active in the embryonic and fetal brain, consistent with early developmental patterning of brain asymmetry. Several of the genes encode components of microtubules, or other microtubule-associated proteins. Microtubules are key elements of the internal cellular skeleton (cytoskeleton). A major challenge remains to understand how these genes affect, or even induce, the brain’s left-right axis. Several of the implicated genes have also been associated with psychiatric or neurological disorders, and polygenic dispositions to autism and schizophrenia have been associated with structural brain asymmetry. Knowledge of developmental mechanisms that lead to hemispheric specialization may ultimately help to define etiologic subtypes of brain disorders.
  • 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
  • Francks, C. (2020). Peer Review Report For: Heritability of language laterality assessed by functional transcranial Doppler ultrasound: a twin study [version 2; peer review: 1 approved, 2 approved with reservations] Wellcome Open Research 2020, 4:161. doi:10.21956/wellcomeopenres.17276.r38148.
  • 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.
  • 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.

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