Clyde Francks

Publications

Displaying 1 - 18 of 18
  • Adams, H. H. H., Hibar, D. P., Chouraki, V., Stein, J. L., Nyquist, P., Renteria, M. E., Trompet, S., Arias-Vasquez, A., Seshadri, S., Desrivières, S., Beecham, A. H., Jahanshad, N., Wittfeld, K., Van der Lee, S. J., Abramovic, L., Alhusaini, S., Amin, N., Andersson, M., Arfanakis, K. A., Aribisala, B. S. and 322 moreAdams, H. H. H., Hibar, D. P., Chouraki, V., Stein, J. L., Nyquist, P., Renteria, M. E., Trompet, S., Arias-Vasquez, A., Seshadri, S., Desrivières, S., Beecham, A. H., Jahanshad, N., Wittfeld, K., Van der Lee, S. J., Abramovic, L., Alhusaini, S., Amin, N., Andersson, M., Arfanakis, K. A., Aribisala, B. S., Armstrong, N. J., Athanasiu, L., Axelsson, T., Beiser, A., Bernard, M., Bis, J. C., Blanken, L. M. E., Blanton, S. H., Bohlken, M. M., Boks, M. P., Bralten, J., Brickman, A. M., Carmichael, O., Chakravarty, M. M., Chauhan, G., Chen, Q., Ching, C. R. K., Cuellar-Partida, G., Den Braber, A., Doan, N. T., Ehrlich, S., Filippi, I., Ge, T., Giddaluru, S., Goldman, A. L., Gottesman, R. F., Greven, C. U., Grimm, O., Griswold, M. E., Guadalupe, T., Hass, J., Haukvik, U. K., Hilal, S., Hofer, E., Höhn, D., Holmes, A. J., Hoogman, M., Janowitz, D., Jia, T., Karbalai, N., Kasperaviciute, D., Kim, S., Klein, M., Krämer, B., Lee–, P. H., Liao, J., Liewald, D. C. M., Lopez, L. M., Luciano, M., Macare, C., Marquand, A., Matarin, M., Mather, K. A., Mattheisen, M., Mazoyer, B., McKay, D. R., McWhirter, R., Milaneschi, Y., Muetzel, R. L., Muñoz Maniega, S., Nho, K., Nugent, A. C., Olde Loohuis, L. M., Oosterlaan, J., Papmeyer, M., Pappa, I., Pirpamer, L., Pudas, S., Pütz, B., Rajan, K. B., Ramasamy, A., Richards, J. S., Risacher, S. L., Roiz-Santiañez, R., Rommelse, N., Rose, E. J., Royle, N. A., Rundek, T., Sämann, P. G., Satizabal, C. L., Schmaal, L., Schork, A. J., Shen, L., Shin, J., Shumskaya, E., Smith, A. V., Sprooten, E., Strike, L. T., Teumer, A., Thomson, R., Tordesillas-Gutierrez, D., Toro, R., Trabzuni, D., Vaidya, D., Van der Grond, J., Van der Meer, D., Van Donkelaar, M. M. J., Van Eijk, K. R., VanErp, T. G. M., Van Rooij, D., Walton, E., Westlye, L. T., Whelan, C. D., Windham, B. G., Winkler, A. M., Woldehawariat, G., Wolf, C., Wolfers, T., Xu, B., Yanek, L. R., Yang, J., Zijdenbos, A., Zwiers, M. P., Agartz, I., Aggarwal, N. T., Almasy, L., Ames, D., Amouyel, P., Andreassen, O. A., Arepalli, S., Assareh, A. A., Barral, S., Bastin, M. E., Becker, J. T., Becker, D. M., Bennett, D. A., Blangero, J., Van Bokhoven, H., Boomsma, D. I., Brodaty, H., Brouwer, R. M., Brunner, H. G., Buckner, R. L., Buitelaar, J. K., Bulayeva, K. B., Cahn, W., Calhoun, V. D., Cannon, D. M., Cavalleri, G. L., Chen, C., Cheng, C.-Y., Cichon, S., Cookson, M. R., Corvin, A., Crespo-Facorro, B., Curran, J. E., Czisch, M., Dale, A. M., Davies, G. E., De Geus, E. J. C., De Jager, P. L., De Zubicaray, G. I., Delanty, N., Depondt, C., DeStefano, A., Dillman, A., Djurovic, S., Donohoe, G., Drevets, W. C., Duggirala, R., Dyer, T. D., Erk, S., Espeseth, T., Evans, D. A., Fedko, I. O., Fernández, G., Ferrucci, L., Fisher, S. E., Fleischman, D. A., Ford, I., Foroud, T. M., Fox, P. T., Francks, C., Fukunaga, M., Gibbs, J. R., Glahn, D. C., Gollub, R. L., Göring, H. H. H., Grabe, H. J., Green, R. C., Gruber, O., Guelfi, S., Hansell, N. K., Hardy, J., Hartman, C. A., Hashimoto, R., Hegenscheid, K., Heinz, A., Le Hellard, S., Hernandez, D. G., Heslenfeld, D. J., Ho, B.-C., Hoekstra, P. J., Hoffmann, W., Hofman, A., Holsboer, F., Homuth, G., Hosten, N., Hottenga, J.-J., Hulshoff Pol, H. E., Ikeda, M., Ikram, M. K., Jack Jr, C. R., Jenkinson, M., Johnson, R., Jönsson, E. G., Jukema, J. W., Kahn, R. S., Kanai, R., Kloszewska, I., Knopman, D. S., Kochunov, P., Kwok, J. B., Launer, L. J., Lawrie, S. M., Lemaître, H., Liu, X., Longo, D. L., Longstreth Jr, W. T., Lopez, O. L., Lovestone, S., Martinez, O., Martinot, J.-L., Mattay, V. S., McDonald, C., McIntosh, A. M., McMahon, F. J., McMahon, K. L., Mecocci, P., Melle, I., Meyer-Lindenberg, A., Mohnke, S., Montgomery, G. W., Morris, D. W., Mosley, T. H., Mühleisen, T. W., Müller-Myhsok, B., Nalls, M. A., Nauck, M., Nichols, T. E., Niessen, W. J., Nöthen, M. M., Nyberg, L., Ohi, K., Olvera, R. L., Ophoff, R. A., Pandolfo, M., Paus, T., Pausova, Z., Penninx, B. W. J. H., Pike, G. B., Potkin, S. G., Psaty, B. M., Reppermund, S., Rietschel, M., Roffman, J. L., Romanczuk-Seiferth, N., Rotter, J. I., Ryten, M., Sacco, R. L., Sachdev, P. S., Saykin, A. J., Schmidt, R., Schofield, P. R., Sigursson, S., Simmons, A., Singleton, A., Sisodiya, S. M., Smith, C., Smoller, J. W., Soininen, H., Srikanth, V., Steen, V. M., Stott, D. J., Sussmann, J. E., Thalamuthu, A., Tiemeier, H., Toga, A. W., Traynor, B., Troncoso, J., Turner, J. A., Tzourio, C., Uitterlinden, A. G., Valdés Hernández, M. C., Van der Brug, M., Van der Lugt, A., Van der Wee, N. J. A., Van Duijn, C. M., Van Haren, N. E. M., Van 't Ent, D., Van Tol, M.-J., Vardarajan, B. N., Veltman, D. J., Vernooij, M. W., Völzke, H., Walter, H., Wardlaw, J. M., Wassink, T. H., Weale, M. E., Weinberger, D. R., Weiner, M. W., Wen, W., Westman, E., White, T., Wong, T. Y., Wright, C. B., Zielke, R. H., Zonderman, A. B., the Alzheimer's Disease Neuroimaging Initiative, EPIGEN, IMAGEN, SYS, Deary, I. J., DeCarli, C., Schmidt, H., Martin, N. G., De Craen, A. J. M., Wright, M. J., Gudnason, V., Schumann, G., Fornage, M., Franke, B., Debette, S., Medland, S. E., Ikram, M. A., & Thompson, P. M. (2016). Novel genetic loci underlying human intracranial volume identified through genome-wide association. Nature Neuroscience, 19, 1569-1582. doi:10.1038/nn.4398.

    Abstract

    Intracranial volume reflects the maximally attained brain size during development, and remains stable with loss of tissue in late
    life. It is highly heritable, but the underlying genes remain largely undetermined. In a genome-wide association study of 32,438
    adults, we discovered five previously unknown loci for intracranial volume and confirmed two known signals. Four of the loci were
    also associated with adult human stature, but these remained associated with intracranial volume after adjusting for height.
    We found a high genetic correlation with child head circumference (genetic = 0.748), which indicates a similar genetic
    background and allowed us to identify four additional loci through meta-analysis (Ncombined = 37,345). Variants for intracranial
    volume were also related to childhood and adult cognitive function, and Parkinson’s disease, and were enriched near genes
    involved in growth pathways, including PI3K-AKT signaling. These findings identify the biological underpinnings of intracranial
    volume and provide genetic support for theories on brain reserve and brain overgrowth.
  • Becker, M., Guadalupe, T., Franke, B., Hibar, D. P., Renteria, M. E., Stein, J. L., Thompson, P. M., Francks, C., Vernes, S. C., & Fisher, S. E. (2016). Early developmental gene enhancers affect subcortical volumes in the adult human brain. Human Brain Mapping, 37(5), 1788-1800. doi:10.1002/hbm.23136.

    Abstract

    Genome-wide association screens aim to identify common genetic variants contributing to the phenotypic variability of complex traits, such as human height or brain morphology. The identified genetic variants are mostly within noncoding genomic regions and the biology of the genotype–phenotype association typically remains unclear. In this article, we propose a complementary targeted strategy to reveal the genetic underpinnings of variability in subcortical brain volumes, by specifically selecting genomic loci that are experimentally validated forebrain enhancers, active in early embryonic development. We hypothesized that genetic variation within these enhancers may affect the development and ultimately the structure of subcortical brain regions in adults. We tested whether variants in forebrain enhancer regions showed an overall enrichment of association with volumetric variation in subcortical structures of >13,000 healthy adults. We observed significant enrichment of genomic loci that affect the volume of the hippocampus within forebrain enhancers (empirical P = 0.0015), a finding which robustly passed the adjusted threshold for testing of multiple brain phenotypes (cutoff of P < 0.0083 at an alpha of 0.05). In analyses of individual single nucleotide polymorphisms (SNPs), we identified an association upstream of the ID2 gene with rs7588305 and variation in hippocampal volume. This SNP-based association survived multiple-testing correction for the number of SNPs analyzed but not for the number of subcortical structures. Targeting known regulatory regions offers a way to understand the underlying biology that connects genotypes to phenotypes, particularly in the context of neuroimaging genetics. This biology-driven approach generates testable hypotheses regarding the functional biology of identified associations.
  • Carrion Castillo, A., van Bergen, E., Vino, A., van Zuijen, T., de Jong, P. F., Francks, C., & Fisher, S. E. (2016). Evaluation of results from genome-wide studies of language and reading in a novel independent dataset. Genes, Brain and Behavior, 15(6), 531-541. doi:10.1111/gbb.12299.

    Abstract

    Recent genome wide association scans (GWAS) for reading and language abilities have pin-pointed promising new candidate loci. However, the potential contributions of these loci remain to be validated. In the present study, we tested 17 of the most significantly associated single nucleotide polymorphisms (SNPs) from these GWAS studies (p < 10−6 in the original studies) in a new independent population dataset from the Netherlands: known as FIOLA (Familial Influences On Literacy Abilities). This dataset comprised 483 children from 307 nuclear families, plus 505 adults (including parents of participating children), and provided adequate statistical power to detect the effects that were previously reported. The following measures of reading and language performance were collected: word reading fluency, nonword reading fluency, phonological awareness, and rapid automatized naming. Two SNPs (rs12636438, rs7187223) were associated with performance in multivariate and univariate testing, but these did not remain significant after correction for multiple testing. Another SNP (rs482700) was only nominally associated in the multivariate test. For the rest of the SNPs we did not find supportive evidence of association. The findings may reflect differences between our study and the previous investigations in respects such as the language of testing, the exact tests used, and the recruitment criteria. Alternatively, most of the prior reported associations may have been false positives. A larger scale GWAS meta-analysis than those previously performed will likely be required to obtain robust insights into the genomic architecture underlying reading and language.
  • Franke, B., Stein, J. L., Ripke, S., Anttila, V., Hibar, D. P., Van Hulzen, K. J. E., Arias-Vasquez, A., Smoller, J. W., Nichols, T. E., Neale, M. C., McIntosh, A. M., Lee, P., McMahon, F. J., Meyer-Lindenberg, A., Mattheisen, M., Andreassen, O. A., Gruber, O., Sachdev, P. S., Roiz-Santiañez, R., Saykin, A. J. and 17 moreFranke, B., Stein, J. L., Ripke, S., Anttila, V., Hibar, D. P., Van Hulzen, K. J. E., Arias-Vasquez, A., Smoller, J. W., Nichols, T. E., Neale, M. C., McIntosh, A. M., Lee, P., McMahon, F. J., Meyer-Lindenberg, A., Mattheisen, M., Andreassen, O. A., Gruber, O., Sachdev, P. S., Roiz-Santiañez, R., Saykin, A. J., Ehrlich, S., Mather, K. A., Turner, J. A., Schwarz, E., Thalamuthu, A., Yao, Y., Ho, Y. Y. W., Martin, N. G., Wright, M. J., Guadalupe, T., Fisher, S. E., Francks, C., Schizophrenia Working Group of the Psychiatric Genomics Consortium, ENIGMA Consortium, O’Donovan, M. C., Thompson, P. M., Neale, B. M., Medland, S. E., & Sullivan, P. F. (2016). Genetic influences on schizophrenia and subcortical brain volumes: large-scale proof of concept. Nature Neuroscience, 19, 420-431. doi:10.1038/nn.4228.

    Abstract

    Schizophrenia is a devastating psychiatric illness with high heritability. Brain structure and function differ, on average, between people with schizophrenia and healthy individuals. As common genetic associations are emerging for both schizophrenia and brain imaging phenotypes, we can now use genome-wide data to investigate genetic overlap. Here we integrated results from common variant studies of schizophrenia (33,636 cases, 43,008 controls) and volumes of several (mainly subcortical) brain structures (11,840 subjects). We did not find evidence of genetic overlap between schizophrenia risk and subcortical volume measures either at the level of common variant genetic architecture or for single genetic markers. These results provide a proof of concept (albeit based on a limited set of structural brain measures) and define a roadmap for future studies investigating the genetic covariance between structural or functional brain phenotypes and risk for psychiatric disorders

    Additional information

    Franke_etal_2016_supp1.pdf
  • Gialluisi, A., Visconti, A., Wilcutt, E. G., Smith, S., Pennington, B., Falchi, M., DeFries, J., Olson, R., Francks, C., & Fisher, S. E. (2016). Investigating the effects of copy number variants on reading and language performance. Journal of Neurodevelopmental Disorders, 8: 17. doi:10.1186/s11689-016-9147-8.

    Abstract

    Background

    Reading and language skills have overlapping genetic bases, most of which are still unknown. Part of the missing heritability may be caused by copy number variants (CNVs).
    Methods

    In a dataset of children recruited for a history of reading disability (RD, also known as dyslexia) or attention deficit hyperactivity disorder (ADHD) and their siblings, we investigated the effects of CNVs on reading and language performance. First, we called CNVs with PennCNV using signal intensity data from Illumina OmniExpress arrays (~723,000 probes). Then, we computed the correlation between measures of CNV genomic burden and the first principal component (PC) score derived from several continuous reading and language traits, both before and after adjustment for performance IQ. Finally, we screened the genome, probe-by-probe, for association with the PC scores, through two complementary analyses: we tested a binary CNV state assigned for the location of each probe (i.e., CNV+ or CNV−), and we analyzed continuous probe intensity data using FamCNV.
    Results

    No significant correlation was found between measures of CNV burden and PC scores, and no genome-wide significant associations were detected in probe-by-probe screening. Nominally significant associations were detected (p~10−2–10−3) within CNTN4 (contactin 4) and CTNNA3 (catenin alpha 3). These genes encode cell adhesion molecules with a likely role in neuronal development, and they have been previously implicated in autism and other neurodevelopmental disorders. A further, targeted assessment of candidate CNV regions revealed associations with the PC score (p~0.026–0.045) within CHRNA7 (cholinergic nicotinic receptor alpha 7), which encodes a ligand-gated ion channel and has also been implicated in neurodevelopmental conditions and language impairment. FamCNV analysis detected a region of association (p~10−2–10−4) within a frequent deletion ~6 kb downstream of ZNF737 (zinc finger protein 737, uncharacterized protein), which was also observed in the association analysis using CNV calls.
    Conclusions

    These data suggest that CNVs do not underlie a substantial proportion of variance in reading and language skills. Analysis of additional, larger datasets is warranted to further assess the potential effects that we found and to increase the power to detect CNV effects on reading and language.
  • Kavaklioglu, T., Ajmal, M., Hameed, A., & Francks, C. (2016). Whole exome sequencing for handedness in a large and highly consanguineous family. Neuropsychologia, 93, part B, 342-349. doi:10.1016/j.neuropsychologia.2015.11.010.

    Abstract

    Pinpointing genes involved in non-right-handedness has the potential to clarify developmental contributions to human brain lateralization. Major-gene models have been considered for human handedness which allow for phenocopy and reduced penetrance, i.e. an imperfect correspondence between genotype and phenotype. However, a recent genome-wide association scan did not detect any common polymorphisms with substantial genetic effects. Previous linkage studies in families have also not yielded significant findings. Genetic heterogeneity and/or polygenicity are therefore indicated, but it remains possible that relatively rare, or even unique, major-genetic effects may be detectable in certain extended families with many non-right-handed members. Here we applied whole exome sequencing to 17 members from a single, large consanguineous family from Pakistan. Multipoint linkage analysis across all autosomes did not yield clear candidate genomic regions for involvement in the trait and single-point analysis of exomic variation did not yield clear candidate mutations/genes. Any genetic contribution to handedness in this unusual family is therefore likely to have a complex etiology, as at the population level.
  • Francks, C., DeLisi, L. E., Fisher, S. E., Laval, S. H., Rue, J. E., Stein, J. F., & Monaco, A. P. (2003). Confirmatory evidence for linkage of relative hand skill to 2p12-q11 [Letter to the editor]. American Journal of Human Genetics, 72(2), 499-502. doi:10.1086/367548.
  • Francks, C., Fisher, S. E., Marlow, A. J., MacPhie, I. L., Taylor, K. E., Richardson, A. J., Stein, J. F., & Monaco, A. P. (2003). Familial and genetic effects on motor coordination, laterality, and reading-related cognition. American Journal of Psychiatry, 160(11), 1970-1977. doi:10.1176/appi.ajp.160.11.1970.

    Abstract

    OBJECTIVE: Recent research has provided evidence for a genetically mediated association between language or reading-related cognitive deficits and impaired motor coordination. Other studies have identified relationships between lateralization of hand skill and cognitive abilities. With a large sample, the authors aimed to investigate genetic relationships between measures of reading-related cognition, hand motor skill, and hand skill lateralization.

    METHOD: The authors applied univariate and bivariate correlation and familiality analyses to a range of measures. They also performed genomewide linkage analysis of hand motor skill in a subgroup of 195 sibling pairs.

    RESULTS: Hand motor skill was significantly familial (maximum heritability=41%), as were reading-related measures. Hand motor skill was weakly but significantly correlated with reading-related measures, such as nonword reading and irregular word reading. However, these correlations were not significantly familial in nature, and the authors did not observe linkage of hand motor skill to any chromosomal regions implicated in susceptibility to dyslexia. Lateralization of hand skill was not correlated with reading or cognitive ability.

    CONCLUSIONS: The authors confirmed a relationship between lower motor ability and poor reading performance. However, the genetic effects on motor skill and reading ability appeared to be largely or wholly distinct, suggesting that the correlation between these traits may have arisen from environmental influences. Finally, the authors found no evidence that reading disability and/or low general cognitive ability were associated with ambidexterity.
  • Francks, C., DeLisi, L. E., Shaw, S. H., Fisher, S. E., Richardson, A. J., Stein, J. F., & Monaco, A. P. (2003). Parent-of-origin effects on handedness and schizophrenia susceptibility on chromosome 2p12-q11. Human Molecular Genetics, 12(24), 3225-3230. doi:10.1093/hmg/ddg362.

    Abstract

    Schizophrenia and non-right-handedness are moderately associated, and both traits are often accompanied by abnormalities of asymmetrical brain morphology or function. We have found linkage previously of chromosome 2p12-q11 to a quantitative measure of handedness, and we have also found linkage of schizophrenia/schizoaffective disorder to this same chromosomal region in a separate study. Now, we have found that in one of our samples (191 reading-disabled sibling pairs), the relative hand skill of siblings was correlated more strongly with paternal than maternal relative hand skill. This led us to re-analyse 2p12-q11 under parent-of-origin linkage models. We found linkage of relative hand skill in the RD siblings to 2p12-q11 with P=0.0000037 for paternal identity-by-descent sharing, whereas the maternally inherited locus was not linked to the trait (P>0.2). Similarly, in affected-sib-pair analysis of our schizophrenia dataset (241 sibling pairs), we found linkage to schizophrenia for paternal sharing with LOD=4.72, P=0.0000016, within 3 cM of the peak linkage to relative hand skill. Maternal linkage across the region was weak or non-significant. These similar paternal-specific linkages suggest that the causative genetic effects on 2p12-q11 are related. The linkages may be due to a single maternally imprinted influence on lateralized brain development that contains common functional polymorphisms.
  • Marlow, A. J., Fisher, S. E., Francks, C., MacPhie, I. L., Cherny, S. S., Richardson, A. J., Talcott, J. B., Stein, J. F., Monaco, A. P., & Cardon, L. R. (2003). Use of multivariate linkage analysis for dissection of a complex cognitive trait. American Journal of Human Genetics, 72(3), 561-570. doi:10.1086/368201.

    Abstract

    Replication of linkage results for complex traits has been exceedingly difficult, owing in part to the inability to measure the precise underlying phenotype, small sample sizes, genetic heterogeneity, and statistical methods employed in analysis. Often, in any particular study, multiple correlated traits have been collected, yet these have been analyzed independently or, at most, in bivariate analyses. Theoretical arguments suggest that full multivariate analysis of all available traits should offer more power to detect linkage; however, this has not yet been evaluated on a genomewide scale. Here, we conduct multivariate genomewide analyses of quantitative-trait loci that influence reading- and language-related measures in families affected with developmental dyslexia. The results of these analyses are substantially clearer than those of previous univariate analyses of the same data set, helping to resolve a number of key issues. These outcomes highlight the relevance of multivariate analysis for complex disorders for dissection of linkage results in correlated traits. The approach employed here may aid positional cloning of susceptibility genes in a wide spectrum of complex traits.
  • Ogdie, M. N., MacPhie, I. L., Minassian, S. L., Yang, M., Fisher, S. E., Francks, C., Cantor, R. M., McCracken, J. T., McGough, J. J., Nelson, S. F., Monaco, A. P., & Smalley, S. L. (2003). A genomewide scan for Attention-Deficit/Hyperactivity Disorder in an extended sample: Suggestive linkage on 17p11. American Journal of Human Genetics, 72(5), 1268-1279. doi:10.1086/375139.

    Abstract

    Attention-deficit/hyperactivity disorder (ADHD [MIM 143465]) is a common, highly heritable neurobehavioral disorder of childhood onset, characterized by hyperactivity, impulsivity, and/or inattention. As part of an ongoing study of the genetic etiology of ADHD, we have performed a genomewide linkage scan in 204 nuclear families comprising 853 individuals and 270 affected sibling pairs (ASPs). Previously, we reported genomewide linkage analysis of a “first wave” of these families composed of 126 ASPs. A follow-up investigation of one region on 16p yielded significant linkage in an extended sample. The current study extends the original sample of 126 ASPs to 270 ASPs and provides linkage analyses of the entire sample, using polymorphic microsatellite markers that define an ∼10-cM map across the genome. Maximum LOD score (MLS) analysis identified suggestive linkage for 17p11 (MLS=2.98) and four nominal regions with MLS values >1.0, including 5p13, 6q14, 11q25, and 20q13. These data, taken together with the fine mapping on 16p13, suggest two regions as highly likely to harbor risk genes for ADHD: 16p13 and 17p11. Interestingly, both regions, as well as 5p13, have been highlighted in genomewide scans for autism.
  • 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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