Clyde Francks

Publications

Displaying 1 - 14 of 14
  • 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.
  • 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

    41398_2020_705_MOESM1_ESM.pdf
  • Francks, C., Tozzi, F., Farmer, A., Vincent, J. B., Rujescu, D., St Clair, D., & Muglia, P. (2010). Population-based linkage analysis of schizophrenia and bipolar case-control cohorts identifies a potential susceptibility locus on 19q13. Molecular Psychiatry, 15, 319-325. doi:10.1038/mp.2008.100.

    Abstract

    Population-based linkage analysis is a new method for analysing genomewide single nucleotide polymorphism (SNP) genotype data in case-control samples, which does not assume a common disease, common variant model. The genome is scanned for extended segments that show increased identity-by-descent sharing within case-case pairs, relative to case-control or control-control pairs. The method is robust to allelic heterogeneity and is suited to mapping genes which contain multiple, rare susceptibility variants of relatively high penetrance. We analysed genomewide SNP datasets for two schizophrenia case-control cohorts, collected in Aberdeen (461 cases, 459 controls) and Munich (429 cases, 428 controls). Population-based linkage testing must be performed within homogeneous samples and it was therefore necessary to analyse the cohorts separately. Each cohort was first subjected to several procedures to improve genetic homogeneity, including identity-by-state outlier detection and multidimensional scaling analysis. When testing only cases who reported a positive family history of major psychiatric disease, consistent with a model of strongly penetrant susceptibility alleles, we saw a distinct peak on chromosome 19q in both cohorts that appeared in meta-analysis (P=0.000016) to surpass the traditional level for genomewide significance for complex trait linkage. The linkage signal was also present in a third case-control sample for familial bipolar disorder, such that meta-analysing all three datasets together yielded a linkage P=0.0000026. A model of rare but highly penetrant disease alleles may be more applicable to some instances of major psychiatric diseases than the common disease common variant model, and we therefore suggest that other genome scan datasets are analysed with this new, complementary method.
  • Ingason, A., Giegling, I., Cichon, S., Hansen, T., Rasmussen, H. B., Nielsen, J., Jurgens, G., Muglia, P., Hartmann, A. M., Strengman, E., Vasilescu, C., Muhleisen, T. W., Djurovic, S., Melle, I., Lerer, B., Möller, H.-J., Francks, C., Pietilainen, O. P. H., Lonnqvist, J., Suvisaari, J. and 20 moreIngason, A., Giegling, I., Cichon, S., Hansen, T., Rasmussen, H. B., Nielsen, J., Jurgens, G., Muglia, P., Hartmann, A. M., Strengman, E., Vasilescu, C., Muhleisen, T. W., Djurovic, S., Melle, I., Lerer, B., Möller, H.-J., Francks, C., Pietilainen, O. P. H., Lonnqvist, J., Suvisaari, J., Tuulio-Henriksson, A., Walshe, M., Vassos, E., Di Forti, M., Murray, R., Bonetto, C., Tosato, S., Cantor, R. M., Rietschel, M., Craddock, N., Owen, M. J., Andreassen, O. A., Nothen, M. M., Peltonen, L., St. Clair, D., Ophoff, R. A., O’Donovan, M. C., Collier, D. A., Werge, T., & Rujescu, D. (2010). A large replication study and meta-analysis in European samples provides further support for association of AHI1 markers with schizophrenia. Human Molecular Genetics, 19(7), 1379-1386. doi:10.1093/hmg/ddq009.

    Abstract

    The Abelson helper integration site 1 (AHI1) gene locus on chromosome 6q23 is among a group of candidate loci for schizophrenia susceptibility that were initially identified by linkage followed by linkage disequilibrium mapping, and subsequent replication of the association in an independent sample. Here, we present results of a replication study of AHI1 locus markers, previously implicated in schizophrenia, in a large European sample (in total 3907 affected and 7429 controls). Furthermore, we perform a meta-analysis of the implicated markers in 4496 affected and 18,920 controls. Both the replication study of new samples and the meta-analysis show evidence for significant overrepresentation of all tested alleles in patients compared with controls (meta-analysis; P = 8.2 x 10(-5)-1.7 x 10(-3), common OR = 1.09-1.11). The region contains two genes, AHI1 and C6orf217, and both genes-as well as the neighbouring phosphodiesterase 7B (PDE7B)-may be considered candidates for involvement in the genetic aetiology of schizophrenia.
  • Liu, J. Z., Tozzi, F., Waterworth, D. M., Pillai, S. G., Muglia, P., Middleton, L., Berrettini, W., Knouff, C. W., Yuan, X., Waeber, G., Vollenweider, P., Preisig, M., Wareham, N. J., Zhao, J. H., Loos, R. J. F., Barroso, I., Khaw, K.-T., Grundy, S., Barter, P., Mahley, R. and 86 moreLiu, J. Z., Tozzi, F., Waterworth, D. M., Pillai, S. G., Muglia, P., Middleton, L., Berrettini, W., Knouff, C. W., Yuan, X., Waeber, G., Vollenweider, P., Preisig, M., Wareham, N. J., Zhao, J. H., Loos, R. J. F., Barroso, I., Khaw, K.-T., Grundy, S., Barter, P., Mahley, R., Kesaniemi, A., McPherson, R., Vincent, J. B., Strauss, J., Kennedy, J. L., Farmer, A., McGuffin, P., Day, R., Matthews, K., Bakke, P., Gulsvik, A., Lucae, S., Ising, M., Brueckl, T., Horstmann, S., Wichmann–, H.-E., Rawal, R., Dahmen, N., Lamina, C., Polasek, O., Zgaga, L., Huffman, J., Campbell, S., Kooner, J., Chambers, J. C., Burnett, M. S., Devaney, J. M., Pichard, A. D., Kent, K. M., Satler, L., Lindsay, J. M., Waksman, R., Epstein, S., Wilson, J. F., Wild, S. H., Campbell, H., Vitart, V., Reilly, M. P., Li, M., Qu, L., Wilensky, R., Matthai, W., Hakonarson, H. H., Rader, D. J., Franke, A., Wittig, M., Schäfer, A., Uda, M., Terracciano, A., Xiao, X., Busonero, F., Scheet, P., Schlessinger, D., St. Clair, D., Rujescu, D., Abecasis, G. R., Grabe, H. J., Teumer, A., Völzke, H., Petersmann, A., John, U., Rudan, I., Hayward, C., Wright, A. F., Kolcic, I., Wright, B. J., Thompson, J. R., Balmforth, A. J., Hall, A. S., Samani, N. J., Anderson, C. A., Ahmad, T., Mathew, C. G., Parkes, M., Satsangi, J., Caulfield, M., Munroe, P. B., Farrall, M., Dominiczak, A., Worthington, J., Thomson, W., Eyre, S., Barton, A., Mooser, V., Francks, C., & Marchini, J. (2010). Meta-analysis and imputation refines the association of 15q25 with smoking quantity. Nature Genetics, 42(5), 436-440. doi:10.1038/ng.572.

    Abstract

    Smoking is a leading global cause of disease and mortality. We established the Oxford-GlaxoSmithKline study (Ox-GSK) to perform a genome-wide meta-analysis of SNP association with smoking-related behavioral traits. Our final data set included 41,150 individuals drawn from 20 disease, population and control cohorts. Our analysis confirmed an effect on smoking quantity at a locus on 15q25 (P = 9.45 x 10(-19)) that includes CHRNA5, CHRNA3 and CHRNB4, three genes encoding neuronal nicotinic acetylcholine receptor subunits. We used data from the 1000 Genomes project to investigate the region using imputation, which allowed for analysis of virtually all common SNPs in the region and offered a fivefold increase in marker density over HapMap2 (ref. 2) as an imputation reference panel. Our fine-mapping approach identified a SNP showing the highest significance, rs55853698, located within the promoter region of CHRNA5. Conditional analysis also identified a secondary locus (rs6495308) in CHRNA3.
  • Muglia, P., Tozzi, F., Galwey, N. W., Francks, C., Upmanyu, R., Kong, X., Antoniades, A., Domenici, E., Perry, J., Rothen, S., Vandeleur, C. L., Mooser, V., Waeber, G., Vollenweider, P., Preisig, M., Lucae, S., Muller-Myhsok, B., Holsboer, F., Middleton, L. T., & Roses, A. D. (2010). Genome-wide association study of recurrent major depressive disorder in two European case-control cohorts. Molecular Psychiatry, 15(6), 589-601. doi:10.1038/mp.2008.131.

    Abstract

    Major depressive disorder (MDD) is a highly prevalent disorder with substantial heritability. Heritability has been shown to be substantial and higher in the variant of MDD characterized by recurrent episodes of depression. Genetic studies have thus far failed to identify clear and consistent evidence of genetic risk factors for MDD. We conducted a genome-wide association study (GWAS) in two independent datasets. The first GWAS was performed on 1022 recurrent MDD patients and 1000 controls genotyped on the Illumina 550 platform. The second was conducted on 492 recurrent MDD patients and 1052 controls selected from a population-based collection, genotyped on the Affymetrix 5.0 platform. Neither GWAS identified any SNP that achieved GWAS significance. We obtained imputed genotypes at the Illumina loci for the individuals genotyped on the Affymetrix platform, and performed a meta-analysis of the two GWASs for this common set of approximately half a million SNPs. The meta-analysis did not yield genome-wide significant results either. The results from our study suggest that SNPs with substantial odds ratio are unlikely to exist for MDD, at least in our datasets and among the relatively common SNPs genotyped or tagged by the half-million-loci arrays. Meta-analysis of larger datasets is warranted to identify SNPs with smaller effects or with rarer allele frequencies that contribute to the risk of MDD.
  • Berrettini, W., Yuan, X., Tozzi, F., Song, K., Francks, C., Chilcoat, H., Waterworth, D., Muglia, P., & Mooser, V. (2008). Alpha-5/alpha-3 nicotinic receptor subunit alleles increase risk for heavy smoking. Molecular Psychiatry, 13, 368-373. doi:10.1038/sj.mp.4002154.

    Abstract

    Twin studies indicate that additive genetic effects explain most of the variance in nicotine dependence (ND), a construct emphasizing habitual heavy smoking despite adverse consequences, tolerance and withdrawal. To detect ND alleles, we assessed cigarettes per day (CPD) regularly smoked, in two European populations via whole genome association techniques. In these approximately 7500 persons, a common haplotype in the CHRNA3-CHRNA5 nicotinic receptor subunit gene cluster was associated with CPD (nominal P=6.9 x 10(-5)). In a third set of European populations (n= approximately 7500) which had been genotyped for approximately 6000 SNPs in approximately 2000 genes, an allele in the same haplotype was associated with CPD (nominal P=2.6 x 10(-6)). These results (in three independent populations of European origin, totaling approximately 15 000 individuals) suggest that a common haplotype in the CHRNA5/CHRNA3 gene cluster on chromosome 15 contains alleles, which predispose to ND.

    Additional information

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  • Need, A. C., Attix, D. K., McEvoy, J. M., Cirulli, E. T., Linney, K. N., Wagoner, A. P., Gumbs, C. E., Giegling, I., Möller, H.-J., Francks, C., Muglia, P., Roses, A., Gibson, G., Weale, M. E., Rujescu, D., & Goldstein, D. B. (2008). Failure to replicate effect of Kibra on human memory in two large cohorts of European origin. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 147B, 667-668. doi:10.1002/ajmg.b.30658.

    Abstract

    It was recently suggested that the Kibra polymorphism rs17070145 has a strong effect on multiple episodic memory tasks in humans. We attempted to replicate this using two cohorts of European genetic origin (n = 319 and n = 365). We found no association with either the original SNP or a set of tagging SNPs in the Kibra gene with multiple verbal memory tasks, including one that was an exact replication (Auditory Verbal Learning Task, AVLT). These results suggest that Kibra does not have a strong and general effect on human memory.

    Additional information

    SupplementaryMethodsIAmJMedGen.doc
  • Stefansson, H., Rujescu, D., Cichon, S., Pietilainen, O. P. H., Ingason, A., Steinberg, S., Fossdal, R., Sigurdsson, E., Sigmundsson, T., Buizer-Voskamp, J. E., Hansen, T., Jakobsen, K. D., Muglia, P., Francks, C., Matthews, P. M., Gylfason, A., Halldorsson, B. V., Gudbjartsson, D., Thorgeirsson, T. E., Sigurdsson, A. and 55 moreStefansson, H., Rujescu, D., Cichon, S., Pietilainen, O. P. H., Ingason, A., Steinberg, S., Fossdal, R., Sigurdsson, E., Sigmundsson, T., Buizer-Voskamp, J. E., Hansen, T., Jakobsen, K. D., Muglia, P., Francks, C., Matthews, P. M., Gylfason, A., Halldorsson, B. V., Gudbjartsson, D., Thorgeirsson, T. E., Sigurdsson, A., Jonasdottir, A., Jonasdottir, A., Bjornsson, A., Mattiasdottir, S., Blondal, T., Haraldsson, M., Magnusdottir, B. B., Giegling, I., Möller, H.-J., Hartmann, A., Shianna, K. V., Ge, D., Need, A. C., Crombie, C., Fraser, G., Walker, N., Lonnqvist, J., Suvisaari, J., Tuulio-Henriksson, A., Paunio, T., Toulopoulou, T., Bramon, E., Forti, M. D., Murray, R., Ruggeri, M., Vassos, E., Tosato, S., Walshe, M., Li, T., Vasilescu, C., Muhleisen, T. W., Wang, A. G., Ullum, H., Djurovic, S., Melle, I., Olesen, J., Kiemeney, L. A., Franke, B., Sabatti, C., Freimer, N. B., Gulcher, J. R., Thorsteinsdottir, U., Kong, A., Andreassen, O. A., Ophoff, R. A., Georgi, A., Rietschel, M., Werge, T., Petursson, H., Goldstein, D. B., Nothen, M. M., Peltonen, L., Collier, D. A., St. Clair, D., & Stefansson, K. (2008). Large recurrent microdeletions associated with schizophrenia [Letter to Nature]. Nature, 455(7210), 232-236. doi:10.1038/nature07229.

    Abstract

    Reduced fecundity, associated with severe mental disorders, places negative selection pressure on risk alleles and may explain, in part, why common variants have not been found that confer risk of disorders such as autism, schizophrenia and mental retardation. Thus, rare variants may account for a larger fraction of the overall genetic risk than previously assumed. In contrast to rare single nucleotide mutations, rare copy number variations (CNVs) can be detected using genome-wide single nucleotide polymorphism arrays. This has led to the identification of CNVs associated with mental retardation and autism. In a genome-wide search for CNVs associating with schizophrenia, we used a population-based sample to identify de novo CNVs by analysing 9,878 transmissions from parents to offspring. The 66 de novo CNVs identified were tested for association in a sample of 1,433 schizophrenia cases and 33,250 controls. Three deletions at 1q21.1, 15q11.2 and 15q13.3 showing nominal association with schizophrenia in the first sample (phase I) were followed up in a second sample of 3,285 cases and 7,951 controls (phase II). All three deletions significantly associate with schizophrenia and related psychoses in the combined sample. The identification of these rare, recurrent risk variants, having occurred independently in multiple founders and being subject to negative selection, is important in itself. CNV analysis may also point the way to the identification of additional and more prevalent risk variants in genes and pathways involved in schizophrenia.

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