Clyde Francks

Publications

Displaying 1 - 12 of 12
  • 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.

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  • 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.

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  • 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.
  • 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.

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  • Brucato, N., Guadalupe, T., Franke, B., Fisher, S. E., & Francks, C. (2015). A schizophrenia-associated HLA locus affects thalamus volume and asymmetry. Brain, Behavior, and Immunity, 46, 311-318. doi:10.1016/j.bbi.2015.02.021.

    Abstract

    Genes of the Major Histocompatibility Complex (MHC) have recently been shown to have neuronal functions in the thalamus and hippocampus. Common genetic variants in the Human Leukocyte Antigens (HLA) region, human homologue of the MHC locus, are associated with small effects on susceptibility to schizophrenia, while volumetric changes of the thalamus and hippocampus have also been linked to schizophrenia. We therefore investigated whether common variants of the HLA would affect volumetric variation of the thalamus and hippocampus. We analyzed thalamus and hippocampus volumes, as measured using structural magnetic resonance imaging, in 1.265 healthy participants. These participants had also been genotyped using genome-wide single nucleotide polymorphism (SNP) arrays. We imputed genotypes for single nucleotide polymorphisms at high density across the HLA locus, as well as HLA allotypes and HLA amino acids, by use of a reference population dataset that was specifically targeted to the HLA region. We detected a significant association of the SNP rs17194174 with thalamus volume (nominal P=0.0000017, corrected P=0.0039), as well as additional SNPs within the same region of linkage disequilibrium. This effect was largely lateralized to the left thalamus and is localized within a genomic region previously associated with schizophrenia. The associated SNPs are also clustered within a potential regulatory element, and a region of linkage disequilibrium that spans genes expressed in the thalamus, including HLA-A. Our data indicate that genetic variation within the HLA region influences the volume and asymmetry of the human thalamus. The molecular mechanisms underlying this association may relate to HLA influences on susceptibility to schizophrenia
  • Ceroni, F., Simpson, N. H., Francks, C., Baird, G., Conti-Ramsden, G., Clark, A., Bolton, P. F., Hennessy, E. R., Donnelly, P., Bentley, D. R., Martin, H., IMGSAC, SLI Consortium, WGS500 Consortium, Parr, J., Pagnamenta, A. T., Maestrini, E., Bacchelli, E., Fisher, S. E., & Newbury, D. F. (2015). Reply to Pembrey et al: ‘ZNF277 microdeletions, specific language impairment and the meiotic mismatch methylation (3M) hypothesis’. European Journal of Human Genetics, 23, 1113-1115. doi:10.1038/ejhg.2014.275.
  • Francks, C. (2015). Exploring human brain lateralization with molecular genetics and genomics. Annals of the New York Academy of Sciences, 1359, 1-13. doi:10.1111/nyas.12770.

    Abstract

    Lateralizations of brain structure and motor behavior have been observed in humans as early as the first trimester of gestation, and are likely to arise from asymmetrical genetic–developmental programs, as in other animals. Studies of gene expression levels in postmortem tissue samples, comparing the left and right sides of the human cerebral cortex, have generally not revealed striking transcriptional differences between the hemispheres. This is likely due to lateralization of gene expression being subtle and quantitative. However, a recent re-analysis and meta-analysis of gene expression data from the adult superior temporal and auditory cortex found lateralization of transcription of genes involved in synaptic transmission and neuronal electrophysiology. Meanwhile, human subcortical mid- and hindbrain structures have not been well studied in relation to lateralization of gene activity, despite being potentially important developmental origins of asymmetry. Genetic polymorphisms with small effects on adult brain and behavioral asymmetries are beginning to be identified through studies of large datasets, but the core genetic mechanisms of lateralized human brain development remain unknown. Identifying subtly lateralized genetic networks in the brain will lead to a new understanding of how neuronal circuits on the left and right are differently fine-tuned to preferentially support particular cognitive and behavioral functions.
  • Guadalupe, T., Zwiers, M. P., Wittfeld, K., Teumer, A., Vasquez, A. A., Hoogman, M., Hagoort, P., Fernandez, G., Buitelaar, J., van Bokhoven, H., Hegenscheid, K., Völzke, H., Franke, B., Fisher, S. E., Grabe, H. J., & Francks, C. (2015). Asymmetry within and around the human planum temporale is sexually dimorphic and influenced by genes involved in steroid hormone receptor activity. Cortex, 62, 41-55. doi:10.1016/j.cortex.2014.07.015.

    Abstract

    The genetic determinants of cerebral asymmetries are unknown. Sex differences in asymmetry of the planum temporale, that overlaps Wernicke’s classical language area, have been inconsistently reported. Meta-analysis of previous studies has suggested that publication bias established this sex difference in the literature. Using probabilistic definitions of cortical regions we screened over the cerebral cortex for sexual dimorphisms of asymmetry in 2337 healthy subjects, and found the planum temporale to show the strongest sex-linked asymmetry of all regions, which was supported by two further datasets, and also by analysis with the Freesurfer package that performs automated parcellation of cerebral cortical regions. We performed a genome-wide association scan meta-analysis of planum temporale asymmetry in a pooled sample of 3095 subjects, followed by a candidate-driven approach which measured a significant enrichment of association in genes of the ´steroid hormone receptor activity´ and 'steroid metabolic process' pathways. Variants in the genes and pathways identified may affect the role of the planum temporale in language cognition.
  • Hibar, D. P., Stein, J. L., Renteria, M. E., Arias-Vasquez, A., Desrivières, S., Jahanshad, N., Toro, R., Wittfeld, K., Abramovic, L., Andersson, M., Aribisala, B. S., Armstrong, N. J., Bernard, M., Bohlken, M. M., Boks, M. P., Bralten, J., Brown, A. A., Chakravarty, M. M., Chen, Q., Ching, C. R. K. and 267 moreHibar, D. P., Stein, J. L., Renteria, M. E., Arias-Vasquez, A., Desrivières, S., Jahanshad, N., Toro, R., Wittfeld, K., Abramovic, L., Andersson, M., Aribisala, B. S., Armstrong, N. J., Bernard, M., Bohlken, M. M., Boks, M. P., Bralten, J., Brown, A. A., Chakravarty, M. M., Chen, Q., Ching, C. R. K., Cuellar-Partida, G., den Braber, A., Giddaluru, S., Goldman, A. L., Grimm, O., Guadalupe, T., Hass, J., Woldehawariat, G., Holmes, A. J., Hoogman, M., Janowitz, D., Jia, T., Kim, S., Klein, M., Kraemer, B., Lee, P. H., Olde Loohuis, L. M., Luciano, M., Macare, C., Mather, K. A., Mattheisen, M., Milaneschi, Y., Nho, K., Papmeyer, M., Ramasamy, A., Risacher, S. L., Roiz-Santiañez, R., Rose, E. J., Salami, A., Sämann, P. G., Schmaal, L., Schork, A. J., Shin, J., Strike, L. T., Teumer, A., Van Donkelaar, M. M. J., Van Eijk, K. R., Walters, R. K., Westlye, L. T., Whelan, C. D., Winkler, A. M., Zwiers, M. P., Alhusaini, S., Athanasiu, L., Ehrlich, S., Hakobjan, M. M. H., Hartberg, C. B., Haukvik, U. K., Heister, A. J. G. A. M., Hoehn, D., Kasperaviciute, D., Liewald, D. C. M., Lopez, L. M., Makkinje, R. R. R., Matarin, M., Naber, M. A. M., McKay, D. R., Needham, M., Nugent, A. C., Pütz, B., Royle, N. A., Shen, L., Sprooten, E., Trabzuni, D., Van der Marel, S. S. L., Van Hulzen, K. J. E., Walton, E., Wolf, C., Almasy, L., Ames, D., Arepalli, S., Assareh, A. A., Bastin, M. E., Brodaty, H., Bulayeva, K. B., Carless, M. A., Cichon, S., Corvin, A., Curran, J. E., Czisch, M., De Zubicaray, G. I., Dillman, A., Duggirala, R., Dyer, T. D., Erk, S., Fedko, I. O., Ferrucci, L., Foroud, T. M., Fox, P. T., Fukunaga, M., Gibbs, J. R., Göring, H. H. H., Green, R. C., Guelfi, S., Hansell, N. K., Hartman, C. A., Hegenscheid, K., Heinz, A., Hernandez, D. G., Heslenfeld, D. J., Hoekstra, P. J., Holsboer, F., Homuth, G., Hottenga, J.-J., Ikeda, M., Jack, C. R., Jenkinson, M., Johnson, R., Kanai, R., Keil, M., Kent, J. W., Kochunov, P., Kwok, J. B., Lawrie, S. M., Liu, X., Longo, D. L., McMahon, K. L., Meisenzahl, E., Melle, I., Mohnke, S., Montgomery, G. W., Mostert, J. C., Mühleisen, T. W., Nalls, M. A., Nichols, T. E., Nilsson, L. G., Nöthen, M. M., Ohi, K., Olvera, R. L., Perez-Iglesias, R., Pike, G. B., Potkin, S. G., Reinvang, I., Reppermund, S., Rietschel, M., Romanczuk-Seiferth, N., Rosen, G. D., Rujescu, D., Schnell, K., Schofield, P. R., Smith, C., Steen, V. M., Sussmann, J. E., Thalamuthu, A., Toga, A. W., Traynor, B. J., Troncoso, J., Turner, J. A., Valdes Hernández, M. C., van Ent, D. ’., Van der Brug, M., Van der Wee, N. J. A., Van Tol, M.-J., Veltman, D. J., Wassink, T. H., Westman, E., Zielke, R. H., Zonderman, A. B., Ashbrook, D. G., Hager, R., Lu, L., McMahon, F. J., Morris, D. W., Williams, R. W., Brunner, H. G., Buckner, R. L., Buitelaar, J. K., Cahn, W., Calhoun, V. D., Cavalleri, G. L., Crespo-Facorro, B., Dale, A. M., Davies, G. E., Delanty, N., Depondt, C., Djurovic, S., Drevets, W. C., Espeseth, T., Gollub, R. L., Ho, B.-C., Hoffmann, W., Hosten, N., Kahn, R. S., Le Hellard, S., Meyer-Lindenberg, A., Müller-Myhsok, B., Nauck, M., Nyberg, L., Pandolfo, M., Penninx, B. W. J. H., Roffman, J. L., Sisodiya, S. M., Smoller, J. W., Van Bokhoven, H., Van Haren, N. E. M., Völzke, H., Walter, H., Weiner, M. W., Wen, W., White, T., Agartz, I., Andreassen, O. A., Blangero, J., Boomsma, D. I., Brouwer, R. M., Cannon, D. M., Cookson, M. R., De Geus, E. J. C., Deary, I. J., Donohoe, G., Fernández, G., Fisher, S. E., Francks, C., Glahn, D. C., Grabe, H. J., Gruber, O., Hardy, J., Hashimoto, R., Hulshoff Pol, H. E., Jönsson, E. G., Kloszewska, I., Lovestone, S., Mattay, V. S., Mecocci, P., McDonald, C., McIntosh, A. M., Ophoff, R. A., Paus, T., Pausova, Z., Ryten, M., Sachdev, P. S., Saykin, A. J., Simmons, A., Singleton, A., Soininen, H., Wardlaw, J. M., Weale, M. E., Weinberger, D. R., Adams, H. H. H., Launer, L. J., Seiler, S., Schmidt, R., Chauhan, G., Satizabal, C. L., Becker, J. T., Yanek, L., van der Lee, S. J., Ebling, M., Fischl, B., Longstreth, W. T., Greve, D., Schmidt, H., Nyquist, P., Vinke, L. N., Van Duijn, C. M., Xue, L., Mazoyer, B., Bis, J. C., Gudnason, V., Seshadri, S., Ikram, M. A., The Alzheimer’s Disease Neuroimaging Initiative, The CHARGE Consortium, EPIGEN, IMAGEN, SYS, Martin, N. G., Wright, M. J., Schumann, G., Franke, B., Thompson, P. M., & Medland, S. E. (2015). Common genetic variants influence human subcortical brain structures. Nature, 520, 224-229. doi:10.1038/nature14101.

    Abstract

    The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08 × 10-33; 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction

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  • Karlebach, G., & Francks, C. (2015). Lateralization of gene expression in human language cortex. Cortex, 67, 30-36. doi:10.1016/j.cortex.2015.03.003.

    Abstract

    Lateralization is an important aspect of the functional brain architecture for language and other cognitive faculties. The molecular genetic basis of human brain lateralization is unknown, and recent studies have suggested that gene expression in the cerebral cortex is bilaterally symmetrical. Here we have re-analyzed two transcriptomic datasets derived from post mortem human cerebral cortex, with a specific focus on superior temporal and auditory language cortex in adults. We applied an empirical Bayes approach to model differential left-right expression, together with gene ontology analysis and meta-analysis. There was robust and reproducible lateralization of individual genes and gene ontology groups that are likely to fine-tune the electrophysiological and neurotransmission properties of cortical circuits, most notably synaptic transmission, nervous system development and glutamate receptor activity. Our findings anchor the cerebral biology of language to the molecular genetic level. Future research in model systems may determine how these molecular signatures of neurophysiological lateralization effect fine-tuning of cerebral cortical function, differently in the two hemispheres.
  • Villanueva, P., Nudel, R., Hoischen, A., Fernández, M. A., Simpson, N. H., Gilissen, C., Reader, R. H., Jara, L., Echeverry, M., Francks, C., Baird, G., Conti-Ramsden, G., O’Hare, A., Bolton, P., Hennessy, E. R., the SLI Consortium, Palomino, H., Carvajal-Carmona Veltman J.A., L., Veltman, J. A., Cazier, J.-B. and 3 moreVillanueva, P., Nudel, R., Hoischen, A., Fernández, M. A., Simpson, N. H., Gilissen, C., Reader, R. H., Jara, L., Echeverry, M., Francks, C., Baird, G., Conti-Ramsden, G., O’Hare, A., Bolton, P., Hennessy, E. R., the SLI Consortium, Palomino, H., Carvajal-Carmona Veltman J.A., L., Veltman, J. A., Cazier, J.-B., De Barbieri, Z., Fisher, S. E., & Newbury, D. (2015). Exome sequencing in an admixed isolated population indicates NFXL1 variants confer a risk for Specific Language Impairment. PLoS Genetics, 11(3): e1004925. doi:10.1371/journal.pgen.1004925.
  • Bailey, A., Hervas, A., Matthews, N., Palferman, S., Wallace, S., Aubin, A., Michelotti, J., Wainhouse, C., Papanikolaou, K., Rutter, M., Maestrini, E., Marlow, A., Weeks, D. E., Lamb, J., Francks, C., Kearsley, G., Scudder, P., Monaco, A. P., Baird, G., Cox, A. and 46 moreBailey, A., Hervas, A., Matthews, N., Palferman, S., Wallace, S., Aubin, A., Michelotti, J., Wainhouse, C., Papanikolaou, K., Rutter, M., Maestrini, E., Marlow, A., Weeks, D. E., Lamb, J., Francks, C., Kearsley, G., Scudder, P., Monaco, A. P., Baird, G., Cox, A., Cockerill, H., Nuffield, F., Le Couteur, A., Berney, T., Cooper, H., Kelly, T., Green, J., Whittaker, J., Gilchrist, A., Bolton, P., Schönewald, A., Daker, M., Ogilvie, C., Docherty, Z., Deans, Z., Bolton, B., Packer, R., Poustka, F., Rühl, D., Schmötzer, G., Bölte, S., Klauck, S. M., Spieler, A., Poustka., A., Van Engeland, H., Kemner, C., De Jonge, M., Den Hartog, I., Lord, C., Cook, E., Leventhal, B., Volkmar, F., Pauls, D., Klin, A., Smalley, S., Fombonne, E., Rogé, B., Tauber, M., Arti-Vartayan, E., Fremolle-Kruck., J., Pederson, L., Haracopos, D., Brondum-Nielsen, K., & Cotterill, R. (1998). A full genome screen for autism with evidence for linkage to a region on chromosome 7q. International Molecular Genetic Study of Autism Consortium. Human Molecular Genetics, 7(3), 571-578. doi:10.1093/hmg/7.3.571.

    Abstract

    Autism is characterized by impairments in reciprocal social interaction and communication, and restricted and sterotyped patterns of interests and activities. Developmental difficulties are apparent before 3 years of age and there is evidence for strong genetic influences most likely involving more than one susceptibility gene. A two-stage genome search for susceptibility loci in autism was performed on 87 affected sib pairs plus 12 non-sib affected relative-pairs, from a total of 99 families identified by an international consortium. Regions on six chromosomes (4, 7, 10, 16, 19 and 22) were identified which generated a multipoint maximum lod score (MLS) > 1. A region on chromosome 7q was the most significant with an MLS of 3.55 near markers D7S530 and D7S684 in the subset of 56 UK affected sib-pair families, and an MLS of 2.53 in all 87 affected sib-pair families. An area on chromosome 16p near the telomere was the next most significant, with an MLS of 1.97 in the UK families, and 1.51 in all families. These results are an important step towards identifying genes predisposing to autism; establishing their general applicability requires further study.

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