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Genetics of Dyscalculia 2: In Search of Endophenotypes

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Abstract

In this chapter, we review the contribution of genetic syndromes to the understanding of developmental dyscalculia. The guideline for our review is the concept of cognitive endophenotype or intermediate cognitive phenotypes between the genetic/environmental etiologic level and the phenotypic level. Four potential endophenotypes are reviewed that could help clearing up genotypic-phenotypic correlations in dyscalculia: basic number processing, phonological processing, visuospatial and visuoconstructional processing, and working memory/executive functions. Endophenotypes are useful as a complexity-reducing strategy to understand dyscalculia subtypes and comorbidities. Evidence for a role of these endophenotypes comes from the association of dyscalculia and several genetic conditions. On the one hand, a verbal pattern of impairment is identified in Klinefelter syndrome. On the other hand, Turner, velocardiofacial, Williams, and fragile X syndromes present nonverbal difficulties in nonsymbolic number processing and visuospatial and visuoconstructional abilities. Impairments in working memory/executive functions are observed in virtually all conditions. We conclude reviewing the educational implications of the relatively specific patterns of impairments observed in these syndromes.

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References

  • Abbeduto, L., McDuffie, A., & Thurman, A. J. (2014). The fragile X syndrome-autism comorbidity: What do we really know? Frontiers in Genetics, 5. https://doi.org/10.3389/fgene.2014.00355

  • Andersson, U. (2007). The contribution of working memory to children’s mathematical word problem solving. Applied Cognitive Psychology, 21(9), 1201–1216. https://doi.org/10.1002/acp.1317

    Article  Google Scholar 

  • Anobile, G., Castaldi, E., Turi, M., Tinelli, F., & Burr, D. C. (2016). Numerosity but not texture-density discrimination correlates with math ability in children. Developmental Psychology, 52(8), 1206. https://doi.org/10.1037/dev0000155

    Article  Google Scholar 

  • Ansari, D., Donlan, C., & Karmiloff-Smith, A. (2007). Typical and atypical development of visual estimation abilities. Cortex, 43(6), 758–768.

    Article  Google Scholar 

  • Antshel, K. M., Peebles, J., Abdul Sabur, N., Higgins, A. M., Roizen, N., Shprintzen, R., et al. (2008). Associations between performance on the Rey-Osterrieth Complex Figure and regional brain volumes in children with and without velocardiofacial syndrome. Developmental Neuropsychology, 33(5), 601–622.

    Article  Google Scholar 

  • Attout, L., Noël, M. P., Vossius, L., & Rousselle, L. (2017). Evidence of the impact of visuo-spatial processing on magnitude representation in 22q11. 2 microdeletion syndrome. Neuropsychologia, 99, 296–305.

    Article  Google Scholar 

  • Baddeley, A. (2000). The episodic buffer: A new component of working memory? Trends in Cognitive Sciences, 4(11), 417–423.

    Article  Google Scholar 

  • Baddeley, A. D., & Hitch, G. (1974). Working memory. Psychology of Learning and Motivation, 8, 47–89.

    Article  Google Scholar 

  • Bailey, D. B., Raspa, M., Olmsted, M., & Holiday, D. B. (2008). Co-occurring conditions associated with FMR1 gene variations: Findings from a national parent survey. American Journal of Medical Genetics Part A, 146(16), 2060–2069. https://doi.org/10.1002/ajmg.a.32439

    Article  Google Scholar 

  • Bailey Jr., D. B., Hatton, D. D., & Skinner, M. (1998). Early developmental trajectories of males with fragile X syndrome. American Journal of Mental Retardation, 103, 29–39.

    Article  Google Scholar 

  • Baker, J. M., & Reiss, A. L. (2016). A meta-analysis of math performance in Turner syndrome. Developmental Medicine and Child Neurology, 58(2), 123–130. https://doi.org/10.1111/dmcn.12961

    Article  Google Scholar 

  • Barnes, M. A., & Raghubar, K. P. (2014). Mathematics development and difficulties: The role of visual–spatial perception and other cognitive skills. Pediatric Blood & Cancer, 61(10), 1729–1733. https://doi.org/10.1002/pbc.24909

    Article  Google Scholar 

  • Barrouillet, P., Camos, V., Perruchet, P., & Seron, X. (2004). ADAPT: A developmental, a semantic and procedural model for transcoding from verbal to Arabic numerals. Psychological Review, 111, 368–394.

    Article  Google Scholar 

  • Bassell, G. J., & Warren, S. T. (2008). Fragile X syndrome: Loss of local mRNA regulation alters synaptic development and function. Neuron, 60(2), 201–214. https://doi.org/10.1016/j.neuron.2008.10.004

    Article  Google Scholar 

  • Benavides-Varela, S., Piva, D., Burgio, F., Passarini, L., Rolma, G., Meneghello, F., & Semenza, C. (2017). Re-assessing acalculia: Distinguishing spatial and purely arithmetical deficits in right-hemisphere damaged patients. Cortex, 88, 151–164. https://doi.org/10.1016/j.cortex.2016.12.014

    Article  Google Scholar 

  • Bender, B. G., Harmon, R. J., Linden, M. G., Bucher-Bartelson, B., & Robinson, A. (1999). Psychosocial competence of unselected young adults with sex chromosome abnormalities. American Journal of Medical Genetics Part A, 88(2), 200–206.

    Article  Google Scholar 

  • Bender, B. G., Linden, M. G., & Harmon, R. J. (2001). Neuropsychological and functional cognitive skills of 35 unselected adults with sex chromosome abnormalities. American Journal of Medical Genetics Part A, 102(4), 309–313.

    Article  Google Scholar 

  • Bender, B. G., Puck, M. H., Salbenblatt, J. A., & Robinson, A. (1986). Dyslexia in 47, XXY boys identified at birth. Behavior Genetics, 16(3), 343–354.

    Article  Google Scholar 

  • Bishop, D. V. M., & Rutter, M (2009). Neurodevelopmental disorders: conceptual issues. In M. Rutter, D. V. M. Bishop, D. S. Pine, S. Scott, J. Stevenson, E. Taylor & A. Thapar (Orgs.), Rutter’s child and adolescent psychiatry (5a. ed., pp. 32–41). Oxford: Blackwell.

    Google Scholar 

  • Bodega, B., Bione, S., Dalprà, L., Toniolo, D., Ornaghi, F., Vegetti, W., et al. (2006). Influence of intermediate and uninterrupted FMR1 CGG expansions in premature ovarian failure manifestation. Human Reproduction, 21(4), 952–957. https://doi.org/10.1093/humrep/dei432

    Article  Google Scholar 

  • Bonomi, M., Rochira, V., Pasquali, D., Balercia, G., Jannini, E. A., Ferlin, A., & Klinefelter ItaliaN Group (KING). (2017). Klinefelter syndrome (KS): Genetics, clinical phenotype and hypogonadism. Journal of Endocrinological Investigation, 40(2), 123–134. https://doi.org/10.1007/s40618-016-0541-6

    Article  Google Scholar 

  • Brankaer, C., Ghesquière, P., De Wel, A., Swillen, A., & De Smedt, B. (2016). Numerical magnitude processing impairments in genetic syndromes: A cross-syndrome comparison of Turner and 22q11. 2 deletion syndromes. Developmental Science. https://doi.org/10.1111/desc.12458

    Article  Google Scholar 

  • Bretherick, K. L., Fluker, M. R., & Robinson, W. P. (2005). FMR1 repeat sizes in the gray zone and high end of the normal range are associated with premature ovarian failure. Human Genetics, 117(4), 376–382. https://doi.org/10.1007/s00439-005-1326-8

    Article  Google Scholar 

  • Brown, W. T., Jenkins, E. C., Friedman, E., Brooks, J., Wisniewski, K., Raguthu, S., & French, J. (1982). Autism is associated with the fragile-X syndrome. Journal of Autism and Developmental Disorders, 12(3), 303–308. https://doi.org/10.1007/BF01531375

    Article  Google Scholar 

  • Bruandet, M., Molko, N., Cohen, L., & Dehaene, S. (2004). A cognitive characterization of dyscalculia in Turner syndrome. Neuropsychologia, 42(3), 288–298.

    Article  Google Scholar 

  • Bull, R., & Lee, K. (2014). Executive functioning and mathematics achievement. Child Development Perspectives, 8, 36–41. https://doi.org/10.1111/cdep.12059

    Article  Google Scholar 

  • Butterworth, B. (2010). Foundational numerical capacities and the origins of dyscalculia. Trends in Cognitive Sciences, 14(12), 534–541. https://doi.org/10.1016/j.tics.2010.09.007

    Article  Google Scholar 

  • Camos, V. (2008). Low working memory capacity impedes both efficiency and learning of number transcoding in children. Journal of Experimental Child Psychology, 99, 37–57.

    Article  Google Scholar 

  • Camos, V., Barrouillet, P., & Fayol, M. (2001). Does the coordination of verbal and motor information explain the development of counting in children? Journal of Experimental Child Psychology, 78(3), 240–262.

    Article  Google Scholar 

  • Carvalho, M. R. S., & Haase, V. G. (2018). Genetics of Dyscalculia 1: In search of genes. In A. Fritz-Stratmann, V. G. Haase, & P. Räsänen (Eds.), The international handbook of math learning difficulties: from the lab to the classroom. São Paulo, Brazil: Springer.

    Google Scholar 

  • Carvalho, M. R. S., Vianna, G., Oliveira, L. F. S., Júlio-Costa, A., Pinheiro-Chagas, P., Sturzenecker, R., et al. (2014). Are 22q11.2 distal deletions associated with math difficulties? American Journal of Medical Genetics, 164A, 2256–2262. https://doi.org/10.1002/ajmg.a.36649

    Article  Google Scholar 

  • Chang, P. N., Gray, R. M., & O’Brien, L. L. (2000). Patterns of academic achievement among patients treated early with phenylketonuria. European Journal of Pediatrics, 159(Suppl 2), S96–S99.

    Article  Google Scholar 

  • Chen, Q., & Li, J. (2014). Association between individual differences in non-symbolic number acuity and math performance: A meta-analysis. Acta Psychologica, 148, 163–172.

    Article  Google Scholar 

  • Ciaccio, C., Fontana, L., Milani, D., Tabano, S., Miozzo, M., Esposito, S., et al. (2017). Fragile X syndrome: A review of clinical and molecular diagnoses. Italian Journal of Pediatrics, 43(1), 39. https://doi.org/10.1186/s13052-017-0355-y

    Article  Google Scholar 

  • Cornoldi, C., Mammarella, I., & Fine, J. G. (2016). Nonverbal learning disabilities. Oxford: Oxford University Press.

    Google Scholar 

  • Costa, A. J., Lopes-Silva, J. G., Pinheiro-Chagas, P., Krinzinger, H., Lonnemann, J., Willmes, K., et al. (2011). A hand full of numbers: A role for offloading in arithmetics learning. Frontiers in Psychology, 2, 368. https://doi.org/10.3389/fpsyg.2011.00368

    Article  Google Scholar 

  • Crespi, B. J., & Procyshyn, T. L. (2017). Williams syndrome deletions and duplications: Genetic windows to understanding anxiety, sociality, autism, and schizophrenia. Neuroscience & Biobehavioral Reviews, 79, 14–26. https://doi.org/10.1016/j.neubiorev.2017.05.004

    Article  Google Scholar 

  • Davidse, N. J., de Jong, M. T., Shaul, S., & Bus, A. G. (2014). A twin-case study of developmental number sense impairment. Cognitive Neuropsychology, 31, 221–236. https://doi.org/10.1080/02643294.2013.876980

    Article  Google Scholar 

  • De Smedt, B., Devriendt, K., Fryns, J. P., Vogels, A., Gewillig, M., & Swillen, A. (2007). Intellectual abilities in a large sample of children with velo–cardio–facial syndrome: an update. Journal of Intellectual Disability Research, 51(9), 666–670.

    Article  Google Scholar 

  • De Smedt, B., & Gilmore, C. K. (2011). Defective number module or impaired access? Numerical magnitude processing in first graders with mathematical difficulties. Journal of Experimental Child Psychology, 108(2), 278–292. https://doi.org/10.1016/j.jecp.2010.09.003

    Article  Google Scholar 

  • De Smedt, B., Reynvoet, B., Swillen, A., Verschaffel, L., Boets, B., & Ghesquière, P. (2009). Basic number processing and difficulties in single-digit arithmetic: Evidence from Velo-Cardio-Facial Syndrome. Cortex, 45(2), 177–188. https://doi.org/10.1016/j.cortex.2007.06.003

    Article  Google Scholar 

  • De Smedt, B., Swillen, A., Devriendt, K., Fryns, J. P., Verschaffel, L., Boets, B., & Ghesquière, P. (2008). Cognitive correlates of mathematical disabilities in children with velo-cardio-facial syndrome. Genetic Counseling, 19, 71–94.

    Google Scholar 

  • De Visscher, A., & Noël, M. P. (2014). Arithmetic facts storage deficit: The hypersensitivity-to-interference in memory hypothesis. Developmental Science, 17(3), 434–442. https://doi.org/10.1111/desc.12135

    Article  Google Scholar 

  • Debrey, S. M., Leehey, M. A., Klepitskaya, O., Filley, C. M., Shah, R. C., Kluger, B., et al. (2016). Clinical phenotype of adult fragile X gray zone allele carriers: A case series. Cerebellum, 15(5), 623–631. https://doi.org/10.1007/s12311-016-0809-6

    Article  Google Scholar 

  • Dehaene, S. (1992). Varieties of numerical abilities. Cognition, 44, 1–42.

    Article  Google Scholar 

  • Dehaene, S., Bossini, S., & Giraux, P. (1993). The mental representation of parity and number magnitude. Journal of Experimental Psychology: General, 122, 371–396.

    Article  Google Scholar 

  • Dehaene, S., & Cohen, L. (1995). Towards an anatomical and functional model of number processing. Mathematical Cognition, 1, 83–120.

    Google Scholar 

  • Dehaene, S., Dupoux, E., & Mehler, J. (1990). Is numerical comparison digital? Analogical and symbolic effects in two-digit number comparison. Journal of Experimental Psychology: Human Perception and Performance, 16, 626–641.

    Google Scholar 

  • Dumontheil, I., Roggeman, C., Ziermans, T., Peyrard-Janvid, M., Matsson, H., Kere, J., & Klingberg, T. (2011). Influence of the COMT genotype on working memory and brain activity changes during development. Biological Psychiatry, 70(3), 222–229. https://doi.org/10.1016/j.biopsych.2011.02.027

    Article  Google Scholar 

  • Fazio, L. K., Bailey, D. H., Thompson, C. A., & Siegler, R. S. (2014). Relations of different types of numerical magnitude representations to each other and to mathematics achievement. Journal of Experimental Child Psychology, 123, 53–72. https://doi.org/10.1016/j.jecp.2014.01.013

    Article  Google Scholar 

  • Fernandez-Carvajal, I., Lopez Posadas, B., Pan, R., Raske, C., Hagerman, P. J., & Tassone, F. (2009). Expansion of an FMR1 grey-zone allele to a full mutation in two generations. The Journal of Molecular Diagnostics: JMD, 11(4), 306–310. https://doi.org/10.2353/jmoldx.2009.080174

    Article  Google Scholar 

  • Fu, Y. H., Kuhl, D. P., Pizzuti, A., Pieretti, M., Sutcliffe, J. S., Richards, S., et al. (1991). Variation of the CGG repeat at the fragile X site results in genetic instability: Resolution of the Sherman paradox. Cell, 67(6), 1047–1058. https://doi.org/10.1016/0092-8674(91)90283-5

    Article  Google Scholar 

  • Geary, D. C., Bailey, D. H., & Hoard, M. K. (2009). Predicting mathematical achievement and mathematical learning disability with a simple screening tool: The number sets test. Journal of Psychoeducational Assessment, 27(3), 265–279.

    Article  Google Scholar 

  • Granà, A., Hofer, R., & Semenza, C. (2006). Acalculia from a right hemisphere lesion: Dealing with “where” in multiplication procedures. Neuropsychologia, 44(14), 2972–2986.

    Article  Google Scholar 

  • Gravholt, C. H., Andersen, N. H., Conway, G. S., Dekkers, O. M., Geffner, M. E., Klein, K. O., et al. (2017). Clinical practice guidelines for the care of girls and women with Turner syndrome: Proceedings from the 2016 Cincinnati International Turner Syndrome Meeting. European Journal of Endocrinology, 177(3), G1–G70. https://doi.org/10.1530/EJE-17-0430

    Article  Google Scholar 

  • Grigsby, J. (2016). The fragile X mental retardation 1 gene (FMR1): Historical perspective, phenotypes, mechanism, pathology, and epidemiology. The Clinical Neuropsychologist, 30(6), 815–833.

    Article  Google Scholar 

  • Haase, V. G., Júlio-Costa, A., Lopes-Silva, J. B., Starling-Alves, I., Antunes, A. M., Pinheiro-chagas, P., & Wood, G. (2014). Contributions from specific and general factors to unique deficits: Two cases of mathematics learning difficulties. Frontiers in Psychology, 5, 102. https://doi.org/10.3389/fpsyg.2014.00102

    Article  Google Scholar 

  • Hagerman, R. J., Jackson, C., Amiri, K., Cronister Silverman, A., O’Connor, R., & Sobesky, W. (1992). Girls with fragile X syndrome: Physical and neurocognitive status and outcome. Pediatrics, 89, 395–400.

    Article  Google Scholar 

  • Halberda, J., Mazzocco, M. M. M., & Feigenson, L. (2008). Individual differences in non-verbal number acuity correlate with maths achievement. Nature, 455, 665–669.

    Article  Google Scholar 

  • Hall, D. A. (2014). In the gray zone in the fragile X gene: What are the key unanswered clinical and biological questions? Tremor and Other Hyperkinetic Movements (New York, N.Y.), 4, 208. https://doi.org/10.7916/D8NG4NP3

    Article  Google Scholar 

  • Hartje, W. (1987). The effect of spatial disorders on arithmetical skills. In G. Deloche & X. Seron (Eds.), Mathematical disabilities. A cognitive neuropsychological approach (pp. 121–135). Hillsdadel, NJ: Erlbaum.

    Google Scholar 

  • Huang, C. J., Chiu, H. J., Lan, T. H., Wang, H. F., Kuo, S. W., Chen, S. F., et al. (2010). Significance of morphological features in schizophrenia of a Chinese population. Journal of Psychiatry Research, 44, 63–68.

    Article  Google Scholar 

  • Hyde, D. C., & Spelke, E. S. (2011). Neural signatures of number processing in human infants: Evidence for two core systems underlying numerical cognition. Developmental Science, 14(2), 360–371. https://doi.org/10.1111/j.1467-7687.2010.00987.x

    Article  Google Scholar 

  • Jäkälä, P., Hänninen, T., Ryynänen, M., Laakso, M., Partanen, K., Mannermaa, A., & Soininen, H. (1997). Fragile-X: Neuropsychological test performance, CGG triplet repeat lengths, and hippocampal volumes. The Journal of Clinical Investigation, 100(2), 331–338.

    Article  Google Scholar 

  • Johnson, M. H. (2012). Executive function and developmental disorders: The flip side of the coin. Trends in Cognitive Sciences, 16, 454–457.

    Article  Google Scholar 

  • Júlio-Costa, A., Antunes, A. M., Lopes-Silva, J. B., Moreira, B. C., Vianna, G. S., Wood, G., et al. (2013). Count on dopamine: Influences of COMT polymorphisms on numerical cognition. Frontiers in Psychology, 4, 531. https://doi.org/10.3389/fpsyg.2013.00531

    Article  Google Scholar 

  • Júlio-Costa, A., Starling-Alves, I., Lopes-Silva, J. B., Wood, G., & Haase, v. G. (2015). Stable measures of number sense accuracy in math learning disability: Is it time to proceed from basic science to clinical application? PsyCh Journal, 4, 218–225. https://doi.org/10.1002/pchj.114

    Article  Google Scholar 

  • Karayiorgou, M., Simon, T. J., & Gogos, J. A. (2010). 22q11.2 microdeletions: Linking DNA structural variation to brain dysfunction and schizophrenia. Nature Reviews Neuroscience, 11, 402–416.

    Article  Google Scholar 

  • Karlsgodt, K. H., Bachman, P., Winkler, A. M., Bearden, C. E., & Glahn, D. C. (2011). Genetic influence on the working memory circuitry: Behavior, structure, function and extensions to illness. Behavioural Brain Research, 225(2), 610–622. https://doi.org/10.1016/j.bbr.2011.08.016

    Article  Google Scholar 

  • Kenna, H. A., Tartter, M., Hall, S. S., Lightbody, A. A., Nguyen, Q., de los Angeles, C. P., et al. (2013). High rates of comorbid depressive and anxiety disorders among women with premutation of the FMR1 gene. American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics, 162(8), 872–878. https://doi.org/10.1002/ajmg.b.32196

    Article  Google Scholar 

  • Kirk, J. W., Mazzocco, M. M., & Kover, S. T. (2005). Assessing executive dysfunction in girls with fragile X or Turner syndrome using the Contingency Naming Test (CNT). Developmental Neuropsychology, 28(3), 755–777.

    Article  Google Scholar 

  • Koontz, K. L., & Berch, D. B. (1996). Identifying simple numerical stimuli: Processing inefficiencies exhibited by arithmetic learning disabled children. Mathematical Cognition, 2(1), 1–23.

    Article  Google Scholar 

  • Krajcsi, A., Lukács, A., Igács, J., Racsmány, M., & Pléh, C. (2009). Numerical abilities in Williams syndrome: Dissociating the analogue magnitude system and verbal retrieval. Journal of Clinical and Experimental Neuropsychology, 31, 439–446.

    Article  Google Scholar 

  • Lachiewicz, A. M., Dawson, D. V., Spiridigliozzi, G. A., & McConkie-Rosell, A. (2006). Arithmetic difficulties in females with the fragile X premutation. American Journal of Medical Genetics Part A, 140(7), 665–672. https://doi.org/10.1002/ajmg.a

    Article  Google Scholar 

  • Lalli, M. A., Jang, J., Park, J. H. C., Wang, Y., Guzman, E., Zhou, H., et al. (2016). Haploinsufficiency of BAZ1B contributes to Williams syndrome through transcriptional dysregulation of neurodevelopmental pathways. Human Molecular Genetics, 25(7), 1294–1306.

    Article  Google Scholar 

  • Landerl, K., Bevan, A., & Butterworth, B. (2004). Developmental dyscalculia and basic numerical capacities: A study of 8–9-year-old students. Cognition, 93(2), 99–125.

    Article  Google Scholar 

  • Le Corre, M., & Carey, S. (2007). One, two, three, four, nothing more: An investigation of the conceptual sources of the verbal counting principles. Cognition, 105(2), 395–438.

    Article  Google Scholar 

  • Leibovich, T., Katzin, N., Harel, M., & Henik, A. (2017). From “sense of number” to “sense of magnitude”: The role of continuous magnitudes in numerical cognition. Behavioral and Brain Sciences, 40.

    Google Scholar 

  • Libertus, M. E., Feigenson, L., Halberda, J., & Landau, B. (2014). Understanding the mapping between numerical approximation and number words: Evidence from Williams syndrome and typical development. Developmental Science, 17(6), 905–919. https://doi.org/10.1111/desc.12154

    Article  Google Scholar 

  • Lindgren, V., McRae, A., Dineen, R., Saulsberry, A., Hoganson, G., & Schrift, M. (2015). Behavioral abnormalities are common and severe in patients with distal 22q11.2 microdeletions and microduplications. Molecular Genetics & Genomic Medicine, 3(4), 346–353. https://doi.org/10.1002/mgg3.146.

    Article  Google Scholar 

  • Liu, Y., Winarni, T. I., Zhang, L., Tassone, F., & Hagerman, R. J. (2013). Fragile X-associated tremor/ataxia syndrome (FXTAS) in grey zone carriers. Clinical Genetics, 84(1), 74–77. https://doi.org/10.1111/cge.12026.

    Article  Google Scholar 

  • Lopes-Silva, J. B., Moura, R., Júlio-Costa, A., Haase, V. G., & Wood, G. (2014). Phonemic awareness as a pathway to number transcoding. Frontiers in Psychology, 5, 13. https://doi.org/10.3389/fpsyg.2014.00013

    Article  Google Scholar 

  • Lopes-Silva, J. B., Moura, R., Júlio-Costa, A., Wood, G., Salles, J. F., & Haase, V. G. (2016). What is specific and what is shared between numbers and words? Frontiers in Psychology, 7, 22. https://doi.org/10.3389/fpsyg.2016.00022

    Article  Google Scholar 

  • Lozano, R., Martinez-Cerdeno, V., & Hagerman, R. J. (2015). Advances in the understanding of the gabaergic neurobiology of FMR1 expanded alleles leading to targeted treatments for fragile X spectrum disorder. Current Pharmaceutical Design, 21(34), 4972–4979.

    Article  Google Scholar 

  • Lozano, R., Rosero, C. A., & Hagerman, R. J. (2014). Fragile X spectrum disorders. Intractable & Rare Diseases Research, 3(4), 134–146. https://doi.org/10.5582/irdr.2014.01022

    Article  Google Scholar 

  • Maenner, M. J., Baker, M. W., Broman, K. W., Tian, J., Barnes, J. K., Atkins, A., et al. (2013). FMR1 CGG expansions: Prevalence and sex ratios. American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics, 162(5), 466–473. https://doi.org/10.1002/ajmg.b.32176

    Article  Google Scholar 

  • Mammarella, I. C., Caviola, S., Giofrè, D., & Szűcs, D. (2017). The underlying structure of visuospatial working memory in children with mathematical learning disability. The British Journal of Developmental Psychology. https://doi.org/10.1111/bjdp.12202

    Article  Google Scholar 

  • Mazzocco, M. M. (2001). Math learning disability and math LD subtypes: Evidence from studies of Turner syndrome, fragile X syndrome, and neurofibromatosis type 1. Journal of Learning Disabilities, 34(6), 520–533.

    Article  Google Scholar 

  • Mazzocco, M. M., Feigenson, L., & Halberda, J. (2011). Impaired acuity of the approximate number system underlies mathematical learning disability (dyscalculia). Child Development, 82(4), 1224–1237. https://doi.org/10.1111/j.1467-8624.2011.01608.x

    Article  Google Scholar 

  • Mazzocco, M. M., Singh Bhatia, N., & Lesniak-Karpiak, K. (2006). Visuospatial skills and their association with math performance in girls with fragile X or Turner syndrome. Child Neuropsychology, 12(2), 87–110.

    Article  Google Scholar 

  • Mazzocco, M. M. M. (2007). When a genetic disorder is associated with learning disabilities. In M. M. M. Mazzocco & J. L. Ross (Eds.), Neurogenetic developmental disorders. Variation of manifestation in childhood (pp. 414–436). Cambridge, MA: MIT Press.

    Chapter  Google Scholar 

  • McDonald-McGinn, D. M., Sullivan, K. E., Marino, B., Philip, N., Swillen, A., Vorstman, J. A., et al. (2015). 22q11.2 deletion syndrome. Nature Reviews Disease Primers, 1, 15071. https://doi.org/10.1038/nrdp.2015.71

    Article  Google Scholar 

  • Menghini, D., Verucci, L., & Vicari, S. (2004). Reading and phonological awareness in Williams syndrome. Neuropsychology, 18(1), 29.

    Article  Google Scholar 

  • Mikhail, F. M., Burnside, R. D., Rush, B., Ibrahim, J., Godshalk, R., Rutledge, S. L., et al. (2014). The recurrent distal 22q11.2 microdeletions are often de novo and do not represent a single clinical entity: A proposed categorization system. Genetics in Medicine, 16(1), 92–100. https://doi.org/10.1038/gim.2013.79.

    Article  Google Scholar 

  • Miyake, A., Friedman, N. P., Emerson, J., Witzki, A. H., & Howerter, A. (2000). The unity and diversity of executive functions and the contributions to complex “frontal lobe” tasks: A latent variable analysis. Cognitive Psychology, 41, 49–100.

    Article  Google Scholar 

  • Moura, R. J., Wood, G., Pinheiro-Chagas, P., Lonnemann, J., Krinzinger, H., Willmes, K., & Haase, V. G. (2013). Transcoding abilities in typical and atypical mathematics achievers: The role of working memory, procedural and lexical competencies. Journal of Experimental Child Psychology, 116, 707–727.

    Article  Google Scholar 

  • Murphy, M., Mazzocco, M. M. M., Gerner, G., & Henry, A. E. (2006). Mathematics learning disability in girls with Turner syndrome or fragile X syndrome. Brain and Cognition, 61, 195–210.

    Article  Google Scholar 

  • Murphy, M. M., Mazzocco, M. M., & McCloskey, M. (2010). Genetic disorders as models of mathematics learning disability: Fragile X and Turner syndromes. In M. A. Barnes (Ed.), Genes, brain and development. The neurocognition of genetic disorders (pp. 143–174). New York: Cambridge University Press.

    Chapter  Google Scholar 

  • Murphy, M. M., & Mazzocco, M. M. M. (2008). Mathematics learning disabilities in girls with fragile X or Turner syndrome during late elementary school. Journal of Learning Disabilities, 41(1), 29–46.

    Article  Google Scholar 

  • Naess, K. A. (2016). Development of phonological awareness in Down syndrome: A meta-analysis and empirical study. Developmental Psychology, 52(2), 177–190. https://doi.org/10.1037/a0039840

    Article  Google Scholar 

  • Noël, M. P., & Rousselle, L. (2011). Developmental changes in the profiles of dyscalculia: An explanation based on a double exact-and-approximate number representation model. Frontiers in Human Neuroscience, 5, 165. https://doi.org/10.3389/fnhum.2011.00165

    Article  Google Scholar 

  • Nosworthy, N., Bugden, S., Archibald, L., Evans, B., & Ansari, D. (2013). A two-minute paper-and-pencil test of symbolic and nonsymbolic numerical magnitude processing explains variability in primary school children’s arithmetic competence. PLoS One, 8(7), e67918. https://doi.org/10.1371/journal.pone.0067918

    Article  Google Scholar 

  • O’Hearn, K., Hoffman, J. E., & Landau, B. (2011). Small subitizing range in people with Williams syndrome. Visual Cognition, 19, 289–312.

    Article  Google Scholar 

  • O’Hearn, K., & Landau, B. (2007). Mathematical skill in individuals with Williams syndrome: Evidence from a standardized mathematics battery. Brain and Cognition, 64, 238–246.

    Article  Google Scholar 

  • Oliveira, L. F. S., Vianna, G. S., Di Ninno, C. Q. M. S., Giacheti, C. M., Carvalho, M. R. S., Wood, G., et al. (2014). Impaired acuity of the approximate number system in 22q11.2 microdeletion syndrome. Psychology & Neuroscience, 7, 151–158. https://doi.org/10.3922/j.psns.2014.02.04

    Article  Google Scholar 

  • Opfer, J. E., & Martens, M. A. (2012). Learning without representational change: Development of numerical estimation in individuals with Williams syndrome. Developmental Science, 15, 863–875.

    Article  Google Scholar 

  • Passolunghi, M. C., & Mammarella, I. C. (2012). Selective spatial working memory impairment in a group of children with mathematics learning disabilities and poor problem-solving skills. Journal of Learning Disabilities, 45(4), 341–350. https://doi.org/10.1177/0022219411400746 Epub 2011 Mar 28.

    Article  Google Scholar 

  • Paterson, S. J., Brown, J. H., Gsödl, M. K., Johnson, M. H., & Karmiloff-Smith, A. (1999). Cognitive modularity of genetic disorders. Science, 286, 2355–2358.

    Article  Google Scholar 

  • Paterson, S. J., Girelli, L., Butterworth, B., & Karmiloff-Smith, A. (2006). Are numerical impairments syndrome specific? Evidence from Williams syndrome and Down syndrome. Journal of Child Psychology and Psychiatry, 47, 190–204.

    Article  Google Scholar 

  • Pennington, B. F., Bender, B., Puck, M., Salbenblatt, J., & Robinson, A. (1982). Learning disabilities in children with sex chromosome anomalies. Child Development, 1182–1192.

    Article  Google Scholar 

  • Piazza, M. (2010). Neurocognitive start-up tools for symbolic number representations. Trends in Cognitive Sciences, 14(12), 542–551. https://doi.org/10.1016/j.tics.2010.09.008

    Article  Google Scholar 

  • Piazza, M., Facoetti, A., Trussardi, A. N., Berteletti, I., Conte, S., Lucangeli, D., et al. (2010). Developmental trajectory of number acuity reveals a severe impairment in developmental dyscalculia. Cognition, 116(1), 33–41. https://doi.org/10.1016/j.cognition.2010.03.012

    Article  Google Scholar 

  • Pierpont, E. I., Ellis Weismer, S., Roberts, A. E., Tworog-Dube, E., Pierpont, M. E., Mendelsohn, N. J., & Seidenberg, M. S. (2010). The language phenotype of children and adolescents with Noonan syndrome. Journal of Speech, Language, and Hearing Research, 53(4), 917–932. https://doi.org/10.1044/1092-4388(2009/09-0046)

    Article  Google Scholar 

  • Pinheiro-Chagas, P., Wood, G., Knops, A., Krinzinger, H., Lonnemann, J., Starling-Alves, I., et al. (2014). In how many ways is the approximate number system associated with exact calculation? PLoS One, 9, e111155. https://doi.org/10.1371/journal.pone.0111155

    Article  Google Scholar 

  • Pitts, C. H., & Mervis, C. B. (2016). Performance on the Kaufman Brief Intelligence Test-2 by children with Williams syndrome. American Journal on Intellectual and Developmental Disabilities, 121(1), 33–47.

    Article  Google Scholar 

  • Quintin, E. M., Jo, B., Hall, S. S., Bruno, J. L., Chromik, L. C., Raman, M. M., et al. (2016). The cognitive developmental profile associated with fragile X syndrome: A longitudinal investigation of cognitive strengths and weaknesses through childhood and adolescence. Development and Psychopathology, 28, 1457–1469.

    Article  Google Scholar 

  • Raghubar, K., Cirino, P., Barnes, M., Ewing-Cobbs, L., Fletcher, J., & Fuchs, L. (2009). Errors in multi-digit arithmetic and behavioral inattention in children with math difficulties. Journal of Learning Disabilities, 42, 356–371.

    Article  Google Scholar 

  • Raghubar, K. P., Barnes, M. A., & Hecht, S. A. (2010). Working memory and mathematics: A review of developmental, individual difference, and cognitive approaches. Learning and Individual Differences, 20, 110–122.

    Article  Google Scholar 

  • Roberts, J. E., Schaaf, J. M., Skinner, M., Wheeler, A., Hooper, S., Hatton, D. D., & Bailey, D. B. (2005). Academic skills of boys with fragile X syndrome: Profiles and predictors. American Journal of Mental Retardation: AJMR, 110(2), 107–120.

    Article  Google Scholar 

  • Ross, J. L., Roeltgen, D., Kushner, H., Wei, F., & Zinn, A. R. (2000). The Turner syndrome–associated neurocognitive phenotype maps to distal Xp. The American Journal of Human Genetics, 67(3), 672–681.

    Article  Google Scholar 

  • Ross, J. L., Roeltgen, D. P., Stefanatos, G., Benecke, R., Zeger, M. P., Kushner, H., et al. (2008). Cognitive and motor development during childhood in boys with Klinefelter syndrome. American Journal of Medical Genetics Part A, 146(6), 708–719.

    Article  Google Scholar 

  • Ross, J. L., Zeger, M. P., Kushner, H., Zinn, A. R., & Roeltgen, D. P. (2009). An extra X or Y chromosome: Contrasting the cognitive and motor phenotypes in childhood in boys with 47, XYY syndrome or 47, XXY Klinefelter syndrome. Developmental Disabilities Research Reviews, 15(4), 309–317.

    Article  Google Scholar 

  • Rousseau, F., Heitz, D., Tarleton, J., et al. (1994). A multicenter study on genotype-phenotype correlations in the fragile X syndrome, using direct diagnosis with probe StB12.3: The first 2,253 cases. American Journal of Human Genetics, 55, 225–237.

    Google Scholar 

  • Rousselle, L., Dembour, G., & Noël, M. P. (2013). Magnitude representations in Williams syndrome: Differential acuity in time, space and number processing. PLoS One, 8(8), e72621. https://doi.org/10.1371/journal.pone.0072621 eCollection 2013.

    Article  Google Scholar 

  • Rousselle, L., & Noël, M.-P. (2007). Basic numerical skills in children with mathematics learning disabilities: A comparison of symbolic vs non symbolic number magnitude processing. Cognition, 102(3), 361–395. https://doi.org/10.1016/j.cognition.2006.01.005

    Article  Google Scholar 

  • Rovet, J., Netley, C., Keenan, M., Bailey, J., & Stewart, D. (1996). The psychoeducational profile of boys with Klinefelter syndrome. Journal of Learning Disabilities, 29(2), 180–196.

    Article  Google Scholar 

  • Schneider, M., Beeres, K., Coban, L., Merz, S., Susan Schmidt, S., Stricker, J., & De Smedt, B. (2017). Associations of non-symbolic and symbolic numerical magnitude processing with mathematical competence: A meta-analysis. Developmental Science, (3), 20. https://doi.org/10.1111/desc.12372

    Article  Google Scholar 

  • Schoch, K., Harrell, W., Hooper, S. R., Ip, E. H., Saldana, S., Kwapil, T. R., & Shashi, V. (2014). Applicability of the nonverbal learning disability paradigm for children with 22q11.2 deletion syndrome. Journal of Learning Disabilities, 47(2), 153–166. https://doi.org/10.1177/0022219412443556

    Article  Google Scholar 

  • Semenza, C., Bonollo, S., Polli, R., Busana, C., Pignatti, R., Iuculano, T., et al. (2012). Genetics and mathematics: FMR1 premutation female carriers. Neuropsychologia, 50(14), 3757–3763. https://doi.org/10.1016/j.neuropsychologia.2012.10.021

    Article  Google Scholar 

  • Shprintzen, R. J. (2008). Velo-cardio-facial syndrome: 30 Years of study. Developmental Disabilities Research Reviews, 14(1), 3–10. https://doi.org/10.1002/ddrr.2

    Article  Google Scholar 

  • Siegler, R. S., & Braithwaite, D. W. (2017). Numerical development. Annual Review of Psychology, 68, 187–213. https://doi.org/10.1146/annurev-psych-010416-044101

    Article  Google Scholar 

  • Simmons, F. R., & Singleton, C. (2008). Do weak phonological representations impact on arithmetic development? A review of research into arithmetic and dyslexia. Dyslexia, 14, 77–94.

    Article  Google Scholar 

  • Simon, T. J. (2008). A new account of the neurocognitive foundations of impairments in space, time, and number processing in children with chromosome 22q11.2 deletion syndrome. Developmental Disabilities Research Reviews, 14(1), 52–58.

    Article  Google Scholar 

  • Simon, T. J., Bearden, C. E., McDonald-McGinn, D., & Zackai, E. (2005). Visuospatial and numeric cognitive deficits in children with chromosome 22q11.2 deletion syndrome. Cortex, 41, 145–155.

    Article  Google Scholar 

  • Simon, T. J., Bish, J. P., Bearden, C. E., Ding, L., Ferrante, S., Nguyen, V., et al. (2005). A multilevel analysis of cognitive dysfunction and psychopathology associated with chromosome 22q11.2 deletion syndrome in children. Development and Psychopathology, 17, 753–784.

    Article  Google Scholar 

  • Simon, T. J., Takarae, Y., DeBoer, T., McDonald-McGinn, D. M., Zackai, E. H., & Ross, J. L. (2008). Overlapping numerical cognition impairments in children with chromosome 22q11.2 deletion or Turner syndromes. Neuropsychologia, 46, 82–94.

    Article  Google Scholar 

  • Sullivan, A. K., Marcus, M., Epstein, M. P., Allen, E. G., Anido, A. E., Paquin, J. J., et al. (2005). Association of FMR1 repeat size with ovarian dysfunction. Human Reproduction, 20(2), 402–412.

    Article  Google Scholar 

  • Ta’ir, J., Brezner, A., & Ariel, R. (1997). Profound developmental dyscalculia: Evidence for a cardinal/ordinal acquisition device. Brain and Cognition, 35, 184–206.

    Article  Google Scholar 

  • Temple, C. M., & Carney, R. A. (1995). Patterns of spatial functioning in Turner’s syndrome. Cortex, 31(1), 109–118.

    Article  Google Scholar 

  • Temple, C. M., & Shephard, E. E. (2012). Exceptional lexical skills but executive language deficits in school starters and young adults with Turners syndrome: Implications for X chromosome effects on brain function. Brain and Language, 120(3), 345–359.

    Article  Google Scholar 

  • Trbovich, P. L., & LeFevre, J. A. (2003). Phonological and visual working memory in mental addition. Memory & Cognition, 31(5), 738–745.

    Article  Google Scholar 

  • van Herwegen, J., Ansari, D., Xu, F., & Karmiloff-Smith, A. (2008). Small and large number processing in infants and toddlers with Williams syndrome. Developmental Science, 11, 637–643.

    Article  Google Scholar 

  • van Rijn, S., & Swaab, H. (2015). Executive dysfunction and the relation with behavioral problems in children with 47, XXY and 47, XXX. Genes, Brain and Behavior, 14(2), 200–208.

    Article  Google Scholar 

  • Vanbinst, K., Ceulemans, E., Peters, L., Ghesquière, P., & De Smedt, B. (2017). Developmental trajectories of children’s symbolic numerical magnitude processing skills and associated cognitive competencies. Journal of Experimental Child Psychology, 166, 232–250. https://doi.org/10.1016/j.jecp.2017.08.008

    Article  Google Scholar 

  • Vandeweyer, G., Van der Aa, N., Reyniers, E., & Kooy, R. F. (2012). The contribution of CLIP2 haploinsufficiency to the clinical manifestations of the Williams-Beuren syndrome. American Journal of Human Genetics, 90(6), 1071–1078. https://doi.org/10.1016/j.ajhg.2012.04.020

    Article  Google Scholar 

  • Wilson, A. J., & Dehaene, S. (2007). Number sense and developmental dyscalculia. In D. Coch, G. Dawson, & K. W. Fischer (Eds.), Human behavior, learning, and the developing brain: Atypical development (pp. 212–238). New York: Guilford.

    Google Scholar 

  • Zinn, A. R., Roeltgen, D., Stefanatos, G., Ramos, P., Elder, F. F., Kushner, H., et al. (2007). A Turner syndrome neurocognitive phenotype maps to Xp22. 3. Behavioral and Brain Functions, 3(1), 24.

    Article  Google Scholar 

  • Zougkou, K., & Temple, C. M. (2016). The processing of number scales beyond whole numbers in development: Dissociations in arithmetic in Turner’s syndrome. Cognitive Neuropsychology, 33(5–6), 277–298. https://doi.org/10.1080/02643294.2016.1179178

    Article  Google Scholar 

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The authors were supported by CAPES, CNPq, FAPEMIG, and SUS-FAPEMIG.

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Carvalho, M.R.S., Haase, V.G. (2019). Genetics of Dyscalculia 2: In Search of Endophenotypes. In: Fritz, A., Haase, V.G., Räsänen, P. (eds) International Handbook of Mathematical Learning Difficulties. Springer, Cham. https://doi.org/10.1007/978-3-319-97148-3_22

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