Clyde Francks

Publications

Displaying 1 - 17 of 17
  • Amelink, J., Postema, M., Kong, X., Schijven, D., Carrion Castillo, A., Soheili-Nezhad, S., Sha, Z., Molz, B., Joliot, M., Fisher, S. E., & Francks, C. (2024). Imaging genetics of language network functional connectivity reveals links with language-related abilities, dyslexia and handedness. Communications Biology, 7: 1209. doi:10.1038/s42003-024-06890-3.

    Abstract

    Language is supported by a distributed network of brain regions with a particular contribution from the left hemisphere. A multi-level understanding of this network requires studying the genetic architecture of its functional connectivity and hemispheric asymmetry. We used resting state functional imaging data from 29,681 participants from the UK Biobank to measure functional connectivity between 18 left-hemisphere regions implicated in multimodal sentence-level processing, as well as their homotopic regions in the right-hemisphere, and interhemispheric connections. Multivariate genome-wide association analysis of this total network, based on common genetic variants (with population frequencies above 1%), identified 14 loci associated with network functional connectivity. Three of these loci were also associated with hemispheric differences of intrahemispheric connectivity. Polygenic dispositions to lower language-related abilities, dyslexia and left-handedness were associated with generally reduced leftward asymmetry of functional connectivity, but with some trait- and connection-specific exceptions. Exome-wide association analysis based on rare, protein-altering variants (frequencies < 1%) suggested 7 additional genes. These findings shed new light on the genetic contributions to language network connectivity and its asymmetry based on both common and rare genetic variants, and reveal genetic links to language-related traits and hemispheric dominance for hand preference.
  • García-Marín, L. M., Campos, A. I., Diaz-Torres, S., Rabinowitz, J. A., Ceja, Z., Mitchell, B. L., Grasby, K. L., Thorp, J. G., Agartz, I., Alhusaini, S., Ames, D., Amouyel, P., Andreassen, O. A., Arfanakis, K., Arias Vasquez, A., Armstrong, N. J., Athanasiu, L., Bastin, M. E., Beiser, A. S., Bennett, D. A. García-Marín, L. M., Campos, A. I., Diaz-Torres, S., Rabinowitz, J. A., Ceja, Z., Mitchell, B. L., Grasby, K. L., Thorp, J. G., Agartz, I., Alhusaini, S., Ames, D., Amouyel, P., Andreassen, O. A., Arfanakis, K., Arias Vasquez, A., Armstrong, N. J., Athanasiu, L., Bastin, M. E., Beiser, A. S., Bennett, D. A., Bis, J. C., Boks, M. P. M., Boomsma, D. I., Brodaty, H., Brouwer, R. M., Buitelaar, J. K., Burkhardt, R., Cahn, W., Calhoun, V. D., Carmichael, O. T., Chakravarty, M., Chen, Q., Ching, C. R. K., Cichon, S., Crespo-Facorro, B., Crivello, F., Dale, A. M., Smith, G. D., De Geus, E. J. C., De Jager, P. L., De Zubicaray, G. I., Debette, S., DeCarli, C., Depondt, C., Desrivières, S., Djurovic, S., Ehrlich, S., Erk, S., Espeseth, T., Fernández, G., Filippi, I., Fisher, S. E., Fleischman, D. A., Fletcher, E., Fornage, M., Forstner, A. J., Francks, C., Franke, B., Ge, T., Goldman, A. L., Grabe, H. J., Green, R. C., Grimm, O., Groenewold, N. A., Gruber, O., Gudnason, V., Håberg, A. K., Haukvik, U. K., Heinz, A., Hibar, D. P., Hilal, S., Himali, J. J., Ho, B.-C., Hoehn, D. F., Hoekstra, P. J., Hofer, E., Hoffmann, W., Holmes, A. J., Homuth, G., Hosten, N., Ikram, M. K., Ipser, J. C., Jack Jr, C. R., Jahanshad, N., Jönsson, E. G., Kahn, R. S., Kanai, R., Klein, M., Knol, M. J., Launer, L. J., Lawrie, S. M., Le Hellard, S., Lee, P. H., Lemaître, H., Li, S., Liewald, D. C. M., Lin, H., Longstreth Jr, W. T., Lopez, O. L., Luciano, M., Maillard, P., Marquand, A. F., Martin, N. G., Martinot, J.-L., Mather, K. A., Mattay, V. S., McMahon, K. L., Mecocci, P., Melle, I., Meyer-Lindenberg, A., Mirza-Schreiber, N., Milaneschi, Y., Mosley, T. H., Mühleisen, T. W., Müller-Myhsok, B., Muñoz Maniega, S., Nauck, M., Nho, K., Niessen, W. J., Nöthen, M. M., Nyquist, P. A., Oosterlaan, J., Pandolfo, M., Paus, T., Pausova, Z., Penninx, B. W. J. H., Pike, G. B., Psaty, B. M., Pütz, B., Reppermund, S., Rietschel, M. D., Risacher, S. L., Romanczuk-Seiferth, N., Romero-Garcia, R., Roshchupkin, G. V., Rotter, J. I., Sachdev, P. S., Sämann, P. G., Saremi, A., Sargurupremraj, M., Saykin, A. J., Schmaal, L., Schmidt, H., Schmidt, R., Schofield, P. R., Scholz, M., Schumann, G., Schwarz, E., Shen, L., Shin, J., Sisodiya, S. M., Smith, A. V., Smoller, J. W., Soininen, H. S., Steen, V. M., Stein, D. J., Stein, J. L., Thomopoulos, S. I., Toga, A., Tordesillas-Gutiérrez, D. T., Trollor, J. N., Valdes-Hernandez, M. C., Van 't Ent, D., Van Bokhoven, H., Van der Meer, D., Van der Wee, N. J. A., Vázquez-Bourgon, J., Veltman, D. J., Vernooij, M. W., Villringer, A., Vinke, L. N., Völzke, H., Walter, H., Wardlaw, J. M., Weinberger, D. R., Weiner, M. W., Wen, W., Westlye, L. T., Westman, E., White, T., Witte, A. V., Wolf, C., Yang, J., Zwiers, M. P., Ikram, M. A., Seshadri, S., Thompson, P. M., Satizabal, C. L., Medland, S. E., & Rentería, M. E. (2024). Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for brain variation across ancestries. Nature Genetics, 56, 2333-2344. doi:10.1038/s41588-024-01951-z.

    Abstract

    Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. Here we performed genome-wide association studies meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signaling and brain aging-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson’s disease and attention-deficit/hyperactivity disorder. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases.
  • Kurth, F., Schijven, D., Van den Heuvel, O. A., Hoogman, M., Van Rooij, D., Stein, D. J., Buitelaar, J. K., Bölte, S., Auzias, G., Kushki, A., Venkatasubramanian, G., Rubia, K., Bollmann, S., Isaksson, J., Jaspers-Fayer, F., Marsh, R., Batistuzzo, M. C., Arnold, P. D., Bressan, R. A., Stewart, E. S. Kurth, F., Schijven, D., Van den Heuvel, O. A., Hoogman, M., Van Rooij, D., Stein, D. J., Buitelaar, J. K., Bölte, S., Auzias, G., Kushki, A., Venkatasubramanian, G., Rubia, K., Bollmann, S., Isaksson, J., Jaspers-Fayer, F., Marsh, R., Batistuzzo, M. C., Arnold, P. D., Bressan, R. A., Stewart, E. S., Gruner, P., Sorensen, L., Pan, P. M., Silk, T. J., Gur, R. C., Cubillo, A. I., Haavik, J., O'Gorman Tuura, R. L., Hartman, C. A., Calvo, R., McGrath, J., Calderoni, S., Jackowski, A., Chantiluke, K. C., Satterthwaite, T. D., Busatto, G. F., Nigg, J. T., Gur, R. E., Retico, A., Tosetti, M., Gallagher, L., Szeszko, P. R., Neufeld, J., Ortiz, A. E., Ghisleni, C., Lazaro, L., Hoekstra, P. J., Anagnostou, E., Hoekstra, L., Simpson, B., Plessen, J. K., Deruelle, C., Soreni, N., James, A., Narayanaswamy, J., Reddy, J. Y. C., Fitzgerald, J., Bellgrove, M. A., Salum, G. A., Janssen, J., Muratori, F., Vila, M., Garcia Giral, M., Ameis, S. H., Bosco, P., Lundin Remnélius, K., Huyser, C., Pariente, J. C., Jalbrzikowski, M., Rosa, P. G. P., O'Hearn, K. M., Ehrlich, S., Mollon, J., Zugman, A., Christakou, A., Arango, C., Fisher, S. E., Kong, X., Franke, B., Medland, S. E., Thomopoulos, S. I., Jahanshad, N., Glahn, D. C., Thompson, P. M., Francks, C., & Luders, E. (2024). Large-scale analysis of structural brain asymmetries during neurodevelopment: Age effects and sex differences in 4,265 children and adolescents. Human Brain Mapping, 45(11): e26754. doi:10.1002/hbm.26754.

    Abstract

    Only a small number of studies have assessed structural differences between the two hemispheres during childhood and adolescence. However, the existing findings lack consistency or are restricted to a particular brain region, a specific brain feature, or a relatively narrow age range. Here, we investigated associations between brain asymmetry and age as well as sex in one of the largest pediatric samples to date (n = 4265), aged 1–18 years, scanned at 69 sites participating in the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium. Our study revealed that significant brain asymmetries already exist in childhood, but their magnitude and direction depend on the brain region examined and the morphometric measurement used (cortical volume or thickness, regional surface area, or subcortical volume). With respect to effects of age, some asymmetries became weaker over time while others became stronger; sometimes they even reversed direction. With respect to sex differences, the total number of regions exhibiting significant asymmetries was larger in females than in males, while the total number of measurements indicating significant asymmetries was larger in males (as we obtained more than one measurement per cortical region). The magnitude of the significant asymmetries was also greater in males. However, effect sizes for both age effects and sex differences were small. Taken together, these findings suggest that cerebral asymmetries are an inherent organizational pattern of the brain that manifests early in life. Overall, brain asymmetry appears to be relatively stable throughout childhood and adolescence, with some differential effects in males and females.
  • Schijven, D., Soheili-Nezhad, S., Fisher, S. E., & Francks, C. (2024). Exome-wide analysis implicates rare protein-altering variants in human handedness. Nature Communications, 15: 2632. doi:10.1038/s41467-024-46277-w.

    Abstract

    Handedness is a manifestation of brain hemispheric specialization. Left-handedness occurs at increased rates in neurodevelopmental disorders. Genome-wide association studies have identified common genetic effects on handedness or brain asymmetry, which mostly involve variants outside protein-coding regions and may affect gene expression. Implicated genes include several that encode tubulins (microtubule components) or microtubule-associated proteins. Here we examine whether left-handedness is also influenced by rare coding variants (frequencies ≤ 1%), using exome data from 38,043 left-handed and 313,271 right-handed individuals from the UK Biobank. The beta-tubulin gene TUBB4B shows exome-wide significant association, with a rate of rare coding variants 2.7 times higher in left-handers than right-handers. The TUBB4B variants are mostly heterozygous missense changes, but include two frameshifts found only in left-handers. Other TUBB4B variants have been linked to sensorineural and/or ciliopathic disorders, but not the variants found here. Among genes previously implicated in autism or schizophrenia by exome screening, DSCAM and FOXP1 show evidence for rare coding variant association with left-handedness. The exome-wide heritability of left-handedness due to rare coding variants was 0.91%. This study reveals a role for rare, protein-altering variants in left-handedness, providing further evidence for the involvement of microtubules and disorder-relevant genes.
  • Soheili-Nezhad, S., Schijven, D., Mars, R. B., Fisher, S. E., & Francks, C. (2024). Distinct impact modes of polygenic disposition to dyslexia in the adult brain. Science Advances, 10(51): eadq2754. doi:10.1126/sciadv.adq2754.

    Abstract

    Dyslexia is a common condition that impacts reading ability. Identifying affected brain networks has been hampered by limited sample sizes of imaging case-control studies. We focused instead on brain structural correlates of genetic disposition to dyslexia in large-scale population data. In over 30,000 adults (UK Biobank), higher polygenic disposition to dyslexia was associated with lower head and brain size, and especially reduced volume and/or altered fiber density in networks involved in motor control, language and vision. However, individual genetic variants disposing to dyslexia often had quite distinct patterns of association with brain structural features. Independent component analysis applied to brain-wide association maps for thousands of dyslexia-disposing genetic variants revealed multiple impact modes on the brain, that corresponded to anatomically distinct areas with their own genomic profiles of association. Polygenic scores for dyslexia-related cognitive and educational measures, as well as attention-deficit/hyperactivity disorder, showed similarities to dyslexia polygenic disposition in terms of brain-wide associations, with microstructure of the internal capsule consistently implicated. In contrast, lower volume of the primary motor cortex was only associated with higher dyslexia polygenic disposition among all traits. These findings robustly reveal heterogeneous neurobiological aspects of dyslexia genetic disposition, and whether they are shared or unique with respect to other genetically correlated traits.

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  • Wong, M. M. K., Sha, Z., Lütje, L., Kong, X., Van Heukelum, S., Van de Berg, W. D. J., Jonkman, L. E., Fisher, S. E., & Francks, C. (2024). The neocortical infrastructure for language involves region-specific patterns of laminar gene expression. Proceedings of the National Academy of Sciences of the United States of America, 121(34): e2401687121. doi:10.1073/pnas.2401687121.

    Abstract

    The language network of the human brain has core components in the inferior frontal cortex and superior/middle temporal cortex, with left-hemisphere dominance in most people. Functional specialization and interconnectivity of these neocortical regions is likely to be reflected in their molecular and cellular profiles. Excitatory connections between cortical regions arise and innervate according to layer-specific patterns. Here we generated a new gene expression dataset from human postmortem cortical tissue samples from core language network regions, using spatial transcriptomics to discriminate gene expression across cortical layers. Integration of these data with existing single-cell expression data identified 56 genes that showed differences in laminar expression profiles between frontal and temporal language cortex together with upregulation in layer II/III and/or layer V/VI excitatory neurons. Based on data from large-scale genome-wide screening in the population, DNA variants within these 56 genes showed set-level associations with inter-individual variation in structural connectivity between left-hemisphere frontal and temporal language cortex, and with predisposition to dyslexia. The axon guidance genes SLIT1 and SLIT2 were consistently implicated. These findings identify region-specific patterns of laminar gene expression as a feature of the brain’s language network.
  • 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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  • Fisher, S. E., Francks, C., McCracken, J. T., McGough, J. J., Marlow, A. J., MacPhie, I. L., Newbury, D. F., Crawford, L. R., Palmer, C. G. S., Woodward, J. A., Del’Homme, M., Cantwell, D. P., Nelson, S. F., Monaco, A. P., & Smalley, S. L. (2002). A genomewide scan for loci involved in Attention-Deficit/Hyperactivity Disorder. American Journal of Human Genetics, 70(5), 1183-1196. doi:10.1086/340112.

    Abstract

    Attention deficit/hyperactivity disorder (ADHD) is a common heritable disorder with a childhood onset. Molecular genetic studies of ADHD have previously focused on examining the roles of specific candidate genes, primarily those involved in dopaminergic pathways. We have performed the first systematic genomewide linkage scan for loci influencing ADHD in 126 affected sib pairs, using a ∼10-cM grid of microsatellite markers. Allele-sharing linkage methods enabled us to exclude any loci with a λs of ⩾3 from 96% of the genome and those with a λs of ⩾2.5 from 91%, indicating that there is unlikely to be a major gene involved in ADHD susceptibility in our sample. Under a strict diagnostic scheme we could exclude all screened regions of the X chromosome for a locus-specific λs of ⩾2 in brother-brother pairs, demonstrating that the excess of affected males with ADHD is probably not attributable to a major X-linked effect. Qualitative trait maximum LOD score analyses pointed to a number of chromosomal sites that may contain genetic risk factors of moderate effect. None exceeded genomewide significance thresholds, but LOD scores were >1.5 for regions on 5p12, 10q26, 12q23, and 16p13. Quantitative-trait analysis of ADHD symptom counts implicated a region on 12p13 (maximum LOD 2.6) that also yielded a LOD >1 when qualitative methods were used. A survey of regions containing 36 genes that have been proposed as candidates for ADHD indicated that 29 of these genes, including DRD4 and DAT1, could be excluded for a λs of 2. Only three of the candidates—DRD5, 5HTT, and CALCYON—coincided with sites of positive linkage identified by our screen. Two of the regions highlighted in the present study, 2q24 and 16p13, coincided with the top linkage peaks reported by a recent genome-scan study of autistic sib pairs.
  • Fisher, S. E., Francks, C., Marlow, A. J., MacPhie, I. L., Newbury, D. F., Cardon, L. R., Ishikawa-Brush, Y., Richardson, A. J., Talcott, J. B., Gayán, J., Olson, R. K., Pennington, B. F., Smith, S. D., DeFries, J. C., Stein, J. F., & Monaco, A. P. (2002). Independent genome-wide scans identify a chromosome 18 quantitative-trait locus influencing dyslexia. Nature Genetics, 30(1), 86-91. doi:10.1038/ng792.

    Abstract

    Developmental dyslexia is defined as a specific and significant impairment in reading ability that cannot be explained by deficits in intelligence, learning opportunity, motivation or sensory acuity. It is one of the most frequently diagnosed disorders in childhood, representing a major educational and social problem. It is well established that dyslexia is a significantly heritable trait with a neurobiological basis. The etiological mechanisms remain elusive, however, despite being the focus of intensive multidisciplinary research. All attempts to map quantitative-trait loci (QTLs) influencing dyslexia susceptibility have targeted specific chromosomal regions, so that inferences regarding genetic etiology have been made on the basis of very limited information. Here we present the first two complete QTL-based genome-wide scans for this trait, in large samples of families from the United Kingdom and United States. Using single-point analysis, linkage to marker D18S53 was independently identified as being one of the most significant results of the genome in each scan (P< or =0.0004 for single word-reading ability in each family sample). Multipoint analysis gave increased evidence of 18p11.2 linkage for single-word reading, yielding top empirical P values of 0.00001 (UK) and 0.0004 (US). Measures related to phonological and orthographic processing also showed linkage at this locus. We replicated linkage to 18p11.2 in a third independent sample of families (from the UK), in which the strongest evidence came from a phoneme-awareness measure (most significant P value=0.00004). A combined analysis of all UK families confirmed that this newly discovered 18p QTL is probably a general risk factor for dyslexia, influencing several reading-related processes. This is the first report of QTL-based genome-wide scanning for a human cognitive trait.
  • Francks, C., Fisher, S. E., MacPhie, I. L., Richardson, A. J., Marlow, A. J., Stein, J. F., & Monaco, A. P. (2002). A genomewide linkage screen for relative hand skill in sibling pairs. American Journal of Human Genetics, 70(3), 800-805. doi:10.1086/339249.

    Abstract

    Genomewide quantitative-trait locus (QTL) linkage analysis was performed using a continuous measure of relative hand skill (PegQ) in a sample of 195 reading-disabled sibling pairs from the United Kingdom. This was the first genomewide screen for any measure related to handedness. The mean PegQ in the sample was equivalent to that of normative data, and PegQ was not correlated with tests of reading ability (correlations between −0.13 and 0.05). Relative hand skill could therefore be considered normal within the sample. A QTL on chromosome 2p11.2-12 yielded strong evidence for linkage to PegQ (empirical P=.00007), and another suggestive QTL on 17p11-q23 was also identified (empirical P=.002). The 2p11.2-12 locus was further analyzed in an independent sample of 143 reading-disabled sibling pairs, and this analysis yielded an empirical P=.13. Relative hand skill therefore is probably a complex multifactorial phenotype with a heterogeneous background, but nevertheless is amenable to QTL-based gene-mapping approaches.
  • Francks, C., Fisher, S. E., Olson, R. K., Pennington, B. F., Smith, S. D., DeFries, J. C., & Monaco, A. P. (2002). Fine mapping of the chromosome 2p12-16 dyslexia susceptibility locus: Quantitative association analysis and positional candidate genes SEMA4F and OTX1. Psychiatric Genetics, 12(1), 35-41.

    Abstract

    A locus on chromosome 2p12-16 has been implicated in dyslexia susceptibility by two independent linkage studies, including our own study of 119 nuclear twin-based families, each with at least one reading-disabled child. Nonetheless, no variant of any gene has been reported to show association with dyslexia, and no consistent clinical evidence exists to identify candidate genes with any strong a priori logic. We used 21 microsatellite markers spanning 2p12-16 to refine our 1-LOD unit linkage support interval to 12cM between D2S337 and D2S286. Then, in quantitative association analysis, two microsatellites yielded P values<0.05 across a range of reading-related measures (D2S2378 and D2S2114). The exon/intron borders of two positional candidate genes within the region were characterized, and the exons were screened for polymorphisms. The genes were Semaphorin4F (SEMA4F), which encodes a protein involved in axonal growth cone guidance, and OTX1, encoding a homeodomain transcription factor involved in forebrain development. Two non-synonymous single nucleotide polymorphisms were found in SEMA4F, each with a heterozygosity of 0.03. One intronic single nucleotide polymorphism between exons 12 and 13 of SEMA4F was tested for quantitative association, but no significant association was found. Only one single nucleotide polymorphism was found in OTX1, which was exonic but silent. Our data therefore suggest that linkage with reading disability at 2p12-16 is not caused by coding variants of SEMA4F or OTX1. Our study outlines the approach necessary for the identification of genetic variants causing dyslexia susceptibility in an epidemiological population of dyslexics.
  • Francks, C., MacPhie, I. L., & Monaco, A. P. (2002). The genetic basis of dyslexia. The Lancet Neurology, 1(8), 483-490. doi:10.1016/S1474-4422(02)00221-1.

    Abstract

    Dyslexia, a disorder of reading and spelling, is a heterogeneous neurological syndrome with a complex genetic and environmental aetiology. People with dyslexia differ in their individual profiles across a range of cognitive, physiological, and behavioural measures related to reading disability. Some or all of the subtypes of dyslexia might have partly or wholly distinct genetic causes. An understanding of the role of genetics in dyslexia could help to diagnose and treat susceptible children more effectively and rapidly than is currently possible and in ways that account for their individual disabilities. This knowledge will also give new insights into the neurobiology of reading and language cognition. Genetic linkage analysis has identified regions of the genome that might harbour inherited variants that cause reading disability. In particular, loci on chromosomes 6 and 18 have shown strong and replicable effects on reading abilities. These genomic regions contain tens or hundreds of candidate genes, and studies aimed at the identification of the specific causal genetic variants are underway.
  • Marlow, A. J., Fisher, S. E., Richardson, A. J., Francks, C., Talcott, J. B., Monaco, A. P., Stein, J. F., & Cardon, L. R. (2002). Investigation of quantitative measures related to reading disability in a large sample of sib-pairs from the UK. Behavior Genetics, 31(2), 219-230. doi:10.1023/A:1010209629021.

    Abstract

    We describe a family-based sample of individuals with reading disability collected as part of a quantitative trait loci (QTL) mapping study. Eighty-nine nuclear families (135 independent sib-pairs) were identified through a single proband using a traditional discrepancy score of predicted/actual reading ability and a known family history. Eight correlated psychometric measures were administered to each sibling, including single word reading, spelling, similarities, matrices, spoonerisms, nonword and irregular word reading, and a pseudohomophone test. Summary statistics for each measure showed a reduced mean for the probands compared to the co-sibs, which in turn was lower than that of the population. This partial co-sib regression back to the mean indicates that the measures are influenced by familial factors and therefore, may be suitable for a mapping study. The variance of each of the measures remained largely unaffected, which is reassuring for the application of a QTL approach. Multivariate genetic analysis carried out to explore the relationship between the measures identified a common factor between the reading measures that accounted for 54% of the variance. Finally the familiality estimates (range 0.32–0.73) obtained for the reading measures including the common factor (0.68) supported their heritability. These findings demonstrate the viability of this sample for QTL mapping, and will assist in the interpretation of any subsequent linkage findings in an ongoing genome scan.
  • Smalley, S. L., Kustanovich, V., Minassian, S. L., Stone, J. L., Ogdie, M. N., McGough, J. J., McCracken, J. T., MacPhie, I. L., Francks, C., Fisher, S. E., Cantor, R. M., Monaco, A. P., & Nelson, S. F. (2002). Genetic linkage of Attention-Deficit/Hyperactivity Disorder on chromosome 16p13, in a region implicated in autism. American Journal of Human Genetics, 71(4), 959-963. doi:10.1086/342732.

    Abstract

    Attention-deficit/hyperactivity disorder (ADHD) is the most commonly diagnosed behavioral disorder in childhood and likely represents an extreme of normal behavior. ADHD significantly impacts learning in school-age children and leads to impaired functioning throughout the life span. There is strong evidence for a genetic etiology of the disorder, although putative alleles, principally in dopamine-related pathways suggested by candidate-gene studies, have very small effect sizes. We use affected-sib-pair analysis in 203 families to localize the first major susceptibility locus for ADHD to a 12-cM region on chromosome 16p13 (maximum LOD score 4.2; P=.000005), building upon an earlier genomewide scan of this disorder. The region overlaps that highlighted in three genome scans for autism, a disorder in which inattention and hyperactivity are common, and physically maps to a 7-Mb region on 16p13. These findings suggest that variations in a gene on 16p13 may contribute to common deficits found in both ADHD and autism.

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