Displaying 1 - 18 of 18
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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 schizophreniaAdditional information
http://www.sciencedirect.com/science/article/pii/S088915911500063X#m0005 -
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.
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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.Additional information
http://www.sciencedirect.com/science/article/pii/S0010945214002469#appd001 -
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 dysfunctionAdditional information
http://www.nature.com/nature/journal/v520/n7546/full/nature14101.html#supplemen…Files private
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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.Additional information
http://www.sciencedirect.com/science/article/pii/S0010945215000817?np=y#appd001 -
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.
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Francks, C., Paracchini, S., Smith, S. D., Richardson, A. J., Scerri, T. S., Cardon, L. R., Marlow, A. J., MacPhie, I. L., Walter, J., Pennington, B. F., Fisher, S. E., Olson, R. K., DeFries, J. C., Stein, J. F., & Monaco, A. P. (2004). A 77-kilobase region of chromosome 6p22.2 is associated with dyslexia in families from the United Kingdom and from the United States. American Journal of Human Genetics, 75(6), 1046-1058. doi:10.1086/426404.
Abstract
Several quantitative trait loci (QTLs) that influence developmental dyslexia (reading disability [RD]) have been mapped to chromosome regions by linkage analysis. The most consistently replicated area of linkage is on chromosome 6p23-21.3. We used association analysis in 223 siblings from the United Kingdom to identify an underlying QTL on 6p22.2. Our association study implicates a 77-kb region spanning the gene TTRAP and the first four exons of the neighboring uncharacterized gene KIAA0319. The region of association is also directly upstream of a third gene, THEM2. We found evidence of these associations in a second sample of siblings from the United Kingdom, as well as in an independent sample of twin-based sibships from Colorado. One main RD risk haplotype that has a frequency of ∼12% was found in both the U.K. and U.S. samples. The haplotype is not distinguished by any protein-coding polymorphisms, and, therefore, the functional variation may relate to gene expression. The QTL influences a broad range of reading-related cognitive abilities but has no significant impact on general cognitive performance in these samples. In addition, the QTL effect may be largely limited to the severe range of reading disability. -
Loo, S. K., Fisher, S. E., Francks, C., Ogdie, M. N., MacPhie, I. L., Yang, M., McCracken, J. T., McGough, J. J., Nelson, S. F., Monaco, A. P., & Smalley, S. L. (2004). Genome-wide scan of reading ability in affected sibling pairs with attention-deficit/hyperactivity disorder: Unique and shared genetic effects. Molecular Psychiatry, 9, 485-493. doi:10.1038/sj.mp.4001450.
Abstract
Attention-deficit/hyperactivity disorder (ADHD) and reading disability (RD) are common highly heritable disorders of childhood, which frequently co-occur. Data from twin and family studies suggest that this overlap is, in part, due to shared genetic underpinnings. Here, we report the first genome-wide linkage analysis of measures of reading ability in children with ADHD, using a sample of 233 affected sibling pairs who previously participated in a genome-wide scan for susceptibility loci in ADHD. Quantitative trait locus (QTL) analysis of a composite reading factor defined from three highly correlated reading measures identified suggestive linkage (multipoint maximum lod score, MLS>2.2) in four chromosomal regions. Two regions (16p, 17q) overlap those implicated by our previous genome-wide scan for ADHD in the same sample: one region (2p) provides replication for an RD susceptibility locus, and one region (10q) falls approximately 35 cM from a modestly highlighted region in an independent genome-wide scan of siblings with ADHD. Investigation of an individual reading measure of Reading Recognition supported linkage to putative RD susceptibility regions on chromosome 8p (MLS=2.4) and 15q (MLS=1.38). Thus, the data support the existence of genetic factors that have pleiotropic effects on ADHD and reading ability--as suggested by shared linkages on 16p, 17q and possibly 10q--but also those that appear to be unique to reading--as indicated by linkages on 2p, 8p and 15q that coincide with those previously found in studies of RD. Our study also suggests that reading measures may represent useful phenotypes in ADHD research. The eventual identification of genes underlying these unique and shared linkages may increase our understanding of ADHD, RD and the relationship between the two. -
Ogdie, M. N., Fisher, S. E., Yang, M., Ishii, J., Francks, C., Loo, S. K., Cantor, R. M., McCracken, J. T., McGough, J. J., Smalley, S. L., & Nelson, S. F. (2004). Attention Deficit Hyperactivity Disorder: Fine mapping supports linkage to 5p13, 6q12, 16p13, and 17p11. American Journal of Human Genetics, 75(4), 661-668. doi:10.1086/424387.
Abstract
We completed fine mapping of nine positional candidate regions for attention-deficit/hyperactivity disorder (ADHD) in an extended population sample of 308 affected sibling pairs (ASPs), constituting the largest linkage sample of families with ADHD published to date. The candidate chromosomal regions were selected from all three published genomewide scans for ADHD, and fine mapping was done to comprehensively validate these positional candidate regions in our sample. Multipoint maximum LOD score (MLS) analysis yielded significant evidence of linkage on 6q12 (MLS 3.30; empiric P=.024) and 17p11 (MLS 3.63; empiric P=.015), as well as suggestive evidence on 5p13 (MLS 2.55; empiric P=.091). In conjunction with the previously reported significant linkage on the basis of fine mapping 16p13 in the same sample as this report, the analyses presented here indicate that four chromosomal regions—5p13, 6q12, 16p13, and 17p11—are likely to harbor susceptibility genes for ADHD. The refinement of linkage within each of these regions lays the foundation for subsequent investigations using association methods to detect risk genes of moderate effect size. -
Scerri, T. S., Fisher, S. E., Francks, C., MacPhie, I. L., Paracchini, S., Richardson, A. J., Stein, J. F., & Monaco, A. P. (2004). Putative functional alleles of DYX1C1 are not associated with dyslexia susceptibility in a large sample of sibling pairs from the UK [Letter to JMG]. Journal of Medical Genetics, 41(11), 853-857. doi:10.1136/jmg.2004.018341.
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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.
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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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