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Carrion Castillo, A., Estruch, S. B., Maassen, B., Franke, B., Francks, C., & Fisher, S. E. (2021). Whole-genome sequencing identifies functional noncoding variation in SEMA3C that cosegregates with dyslexia in a multigenerational family. Human Genetics, 140, 1183-1200. doi:10.1007/s00439-021-02289-w.
Abstract
Dyslexia is a common heritable developmental disorder involving impaired reading abilities. Its genetic underpinnings are thought to be complex and heterogeneous, involving common and rare genetic variation. Multigenerational families segregating apparent monogenic forms of language-related disorders can provide useful entrypoints into biological pathways. In the present study, we performed a genome-wide linkage scan in a three-generational family in which dyslexia affects 14 of its 30 members and seems to be transmitted with an autosomal dominant pattern of inheritance. We identified a locus on chromosome 7q21.11 which cosegregated with dyslexia status, with the exception of two cases of phenocopy (LOD = 2.83). Whole-genome sequencing of key individuals enabled the assessment of coding and noncoding variation in the family. Two rare single-nucleotide variants (rs144517871 and rs143835534) within the first intron of the SEMA3C gene cosegregated with the 7q21.11 risk haplotype. In silico characterization of these two variants predicted effects on gene regulation, which we functionally validated for rs144517871 in human cell lines using luciferase reporter assays. SEMA3C encodes a secreted protein that acts as a guidance cue in several processes, including cortical neuronal migration and cellular polarization. We hypothesize that these intronic variants could have a cis-regulatory effect on SEMA3C expression, making a contribution to dyslexia susceptibility in this family. -
Gialluisi, A., Andlauer, T. F. M., Mirza-Schreiber, N., Moll, K., Becker, J., Hoffmann, P., Ludwig, K. U., Czamara, D., St Pourcain, B., Honbolygó, F., Tóth, D., Csépe, V., Huguet, H., Chaix, Y., Iannuzzi, S., Demonet, J.-F., Morris, A. P., Hulslander, J., Willcutt, E. G., DeFries, J. C. and 29 moreGialluisi, A., Andlauer, T. F. M., Mirza-Schreiber, N., Moll, K., Becker, J., Hoffmann, P., Ludwig, K. U., Czamara, D., St Pourcain, B., Honbolygó, F., Tóth, D., Csépe, V., Huguet, H., Chaix, Y., Iannuzzi, S., Demonet, J.-F., Morris, A. P., Hulslander, J., Willcutt, E. G., DeFries, J. C., Olson, R. K., Smith, S. D., Pennington, B. F., Vaessen, A., Maurer, U., Lyytinen, H., Peyrard-Janvid, M., Leppänen, P. H. T., Brandeis, D., Bonte, M., Stein, J. F., Talcott, J. B., Fauchereau, F., Wilcke, A., Kirsten, H., Müller, B., Francks, C., Bourgeron, T., Monaco, A. P., Ramus, F., Landerl, K., Kere, J., Scerri, T. S., Paracchini, S., Fisher, S. E., Schumacher, J., Nöthen, M. M., Müller-Myhsok, B., & Schulte-Körne, G. (2021). Genome-wide association study reveals new insights into the heritability and genetic correlates of developmental dyslexia. Molecular Psychiatry, 26, 3004-3017. doi:10.1038/s41380-020-00898-x.
Abstract
Developmental dyslexia (DD) is a learning disorder affecting the ability to read, with a heritability of 40–60%. A notable part of this heritability remains unexplained, and large genetic studies are warranted to identify new susceptibility genes and clarify the genetic bases of dyslexia. We carried out a genome-wide association study (GWAS) on 2274 dyslexia cases and 6272 controls, testing associations at the single variant, gene, and pathway level, and estimating heritability using single-nucleotide polymorphism (SNP) data. We also calculated polygenic scores (PGSs) based on large-scale GWAS data for different neuropsychiatric disorders and cortical brain measures, educational attainment, and fluid intelligence, testing them for association with dyslexia status in our sample. We observed statistically significant (p < 2.8 × 10−6) enrichment of associations at the gene level, for LOC388780 (20p13; uncharacterized gene), and for VEPH1 (3q25), a gene implicated in brain development. We estimated an SNP-based heritability of 20–25% for DD, and observed significant associations of dyslexia risk with PGSs for attention deficit hyperactivity disorder (at pT = 0.05 in the training GWAS: OR = 1.23[1.16; 1.30] per standard deviation increase; p = 8 × 10−13), bipolar disorder (1.53[1.44; 1.63]; p = 1 × 10−43), schizophrenia (1.36[1.28; 1.45]; p = 4 × 10−22), psychiatric cross-disorder susceptibility (1.23[1.16; 1.30]; p = 3 × 10−12), cortical thickness of the transverse temporal gyrus (0.90[0.86; 0.96]; p = 5 × 10−4), educational attainment (0.86[0.82; 0.91]; p = 2 × 10−7), and intelligence (0.72[0.68; 0.76]; p = 9 × 10−29). This study suggests an important contribution of common genetic variants to dyslexia risk, and novel genomic overlaps with psychiatric conditions like bipolar disorder, schizophrenia, and cross-disorder susceptibility. Moreover, it revealed the presence of shared genetic foundations with a neural correlate previously implicated in dyslexia by neuroimaging evidence.Additional information
Supplementary File S1 Supplementary File S2 Supplementary File S3 Supplementary File S4 Acknowledgements -
Kong, X., Postema, M., Schijven, D., Carrion Castillo, A., Pepe, A., Crivello, F., Joliot, M., Mazoyer, B., Fisher, S. E., & Francks, C. (2021). Large-scale phenomic and genomic analysis of brain asymmetrical skew. Cerebral Cortex, 31(9), 4151-4168. doi:10.1093/cercor/bhab075.
Abstract
The human cerebral hemispheres show a left–right asymmetrical torque pattern, which has been claimed to be absent in chimpanzees. The functional significance and developmental mechanisms are unknown. Here, we carried out the largest-ever analysis of global brain shape asymmetry in magnetic resonance imaging data. Three population datasets were used, UK Biobank (N = 39 678), Human Connectome Project (N = 1113), and BIL&GIN (N = 453). At the population level, there was an anterior and dorsal skew of the right hemisphere, relative to the left. Both skews were associated independently with handedness, and various regional gray and white matter metrics oppositely in the two hemispheres, as well as other variables related to cognitive functions, sociodemographic factors, and physical and mental health. The two skews showed single nucleotide polymorphisms-based heritabilities of 4–13%, but also substantial polygenicity in causal mixture model analysis, and no individually significant loci were found in genome-wide association studies for either skew. There was evidence for a significant genetic correlation between horizontal brain skew and autism, which requires future replication. These results provide the first large-scale description of population-average brain skews and their inter-individual variations, their replicable associations with handedness, and insights into biological and other factors which associate with human brain asymmetry. -
Postema, M., Hoogman, M., Ambrosino, S., Asherson, P., Banaschewski, T., Bandeira, C. E., Baranov, A., Bau, C. H. D., Baumeister, S., Baur-Streubel, R., Bellgrove, M. A., Biederman, J., Bralten, J., Brandeis, D., Brem, S., Buitelaar, J. K., Busatto, G. F., Castellanos, F. X., Cercignani, M., Chaim-Avancini, T. M. and 85 morePostema, M., Hoogman, M., Ambrosino, S., Asherson, P., Banaschewski, T., Bandeira, C. E., Baranov, A., Bau, C. H. D., Baumeister, S., Baur-Streubel, R., Bellgrove, M. A., Biederman, J., Bralten, J., Brandeis, D., Brem, S., Buitelaar, J. K., Busatto, G. F., Castellanos, F. X., Cercignani, M., Chaim-Avancini, T. M., Chantiluke, K. C., Christakou, A., Coghill, D., Conzelmann, A., Cubillo, A. I., Cupertino, R. B., De Zeeuw, P., Doyle, A. E., Durston, S., Earl, E. A., Epstein, J. N., Ethofer, T., Fair, D. A., Fallgatter, A. J., Faraone, S. V., Frodl, T., Gabel, M. C., Gogberashvili, T., Grevet, E. H., Haavik, J., Harrison, N. A., Hartman, C. A., Heslenfeld, D. J., Hoekstra, P. J., Hohmann, S., Høvik, M. F., Jernigan, T. L., Kardatzki, B., Karkashadze, G., Kelly, C., Kohls, G., Konrad, K., Kuntsi, J., Lazaro, L., Lera-Miguel, S., Lesch, K.-P., Louza, M. R., Lundervold, A. J., Malpas, C. B., Mattos, P., McCarthy, H., Namazova-Baranova, L., Nicolau, R., Nigg, J. T., Novotny, S. E., Oberwelland Weiss, E., O'Gorman Tuura, R. L., Oosterlaan, J., Oranje, B., Paloyelis, Y., Pauli, P., Picon, F. A., Plessen, K. J., Ramos-Quiroga, J. A., Reif, A., Reneman, L., Rosa, P. G. P., Rubia, K., Schrantee, A., Schweren, L. J. S., Seitz, J., Shaw, P., Silk, T. J., Skokauskas, N., Soliva Vila, J. C., Stevens, M. C., Sudre, G., Tamm, L., Tovar-Moll, F., Van Erp, T. G. M., Vance, A., Vilarroya, O., Vives-Gilabert, Y., Von Polier, G. G., Walitza, S., Yoncheva, Y. N., Zanetti, M. V., Ziegler, G. C., Glahn, D. C., Jahanshad, N., Medland, S. E., ENIGMA ADHD Working Group, Thompson, P. M., Fisher, S. E., Franke, B., & Francks, C. (2021). Analysis of structural brain asymmetries in Attention-Deficit/Hyperactivity Disorder in 39 datasets. Journal of Child Psychology and Psychiatry, 62(10), 1202-1219. doi:10.1111/jcpp.13396.
Abstract
Objective: Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here we performed the largest-ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium.
Methods: We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modelling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries.
Results: There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t=2.1, P=0.04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t=2.7, P=0.01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen’s d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing.
Conclusion: Prior studies of altered structural brain asymmetry in ADHD were likely under-powered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.Additional information
jcpp13396-sup-0001-supinfo.pdf -
Sha, Z., Schijven, D., & Francks, C. (2021). Patterns of brain asymmetry associated with polygenic risks for autism and schizophrenia implicate language and executive functions but not brain masculinization. Molecular Psychiatry, 26(12), 7652-7660. doi:10.1038/s41380-021-01204-z.
Abstract
Autism spectrum disorder (ASD) and schizophrenia have been conceived as partly opposing disorders in terms of systemizing versus empathizing cognitive styles, with resemblances to male versus female average sex differences. Left-right asymmetry of the brain is an important aspect of its organization that shows average differences between the sexes, and can be altered in both ASD and schizophrenia. Here we mapped multivariate associations of polygenic risk scores for ASD and schizophrenia with asymmetries of regional cerebral cortical surface area, thickness and subcortical volume measures in 32,256 participants from the UK Biobank. Polygenic risks for the two disorders were positively correlated (r=0.08, p=7.13×10-50), and both were higher in females compared to males, consistent with biased participation against higher-risk males. Each polygenic risk score was associated with multivariate brain asymmetry after adjusting for sex, ASD r=0.03, p=2.17×10-9, schizophrenia r=0.04, p=2.61×10-11, but the multivariate patterns were mostly distinct for the two polygenic risks, and neither resembled average sex differences. Annotation based on meta-analyzed functional imaging data showed that both polygenic risks were associated with asymmetries of regions important for language and executive functions, consistent with behavioural associations that arose in phenome-wide association analysis. Overall, the results indicate that distinct patterns of subtly altered brain asymmetry may be functionally relevant manifestations of polygenic risks for ASD and schizophrenia, but do not support brain masculinization or feminization in their etiologies. -
Sha, Z., Pepe, A., Schijven, D., Carrion Castillo, A., Roe, J. M., Westerhausen, R., Joliot, M., Fisher, S. E., Crivello, F., & Francks, C. (2021). Handedness and its genetic influences are associated with structural asymmetries of the cerebral cortex in 31,864 individuals. Proceedings of the National Academy of Sciences of the United States of America, 118(47): e2113095118. doi:10.1073/pnas.2113095118.
Abstract
Roughly 10% of the human population is left-handed, and this rate is increased in some brain-related disorders. The neuroanatomical correlates of hand preference have remained equivocal. We resampled structural brain image data from 28,802 right-handers and 3,062 left-handers (UK Biobank population dataset) to a symmetrical surface template, and mapped asymmetries for each of 8,681 vertices across the cerebral cortex in each individual. Left-handers compared to right-handers showed average differences of surface area asymmetry within the fusiform cortex, the anterior insula, the anterior middle cingulate cortex, and the precentral cortex. Meta-analyzed functional imaging data implicated these regions in executive functions and language. Polygenic disposition to left-handedness was associated with two of these regional asymmetries, and 18 loci previously linked with left-handedness by genome-wide screening showed associations with one or more of these asymmetries. Implicated genes included six encoding microtubule-related proteins: TUBB, TUBA1B, TUBB3, TUBB4A, MAP2, and NME7—mutations in the latter can cause left to right reversal of the visceral organs. There were also two cortical regions where average thickness asymmetry was altered in left-handedness: on the postcentral gyrus and the inferior occipital cortex, functionally annotated with hand sensorimotor and visual roles. These cortical thickness asymmetries were not heritable. Heritable surface area asymmetries of language-related regions may link the etiologies of hand preference and language, whereas nonheritable asymmetries of sensorimotor cortex may manifest as consequences of hand preference. -
Sha, Z., Schijven, D., Carrion Castillo, A., Joliot, M., Mazoyer, B., Fisher, S. E., Crivello, F., & Francks, C. (2021). The genetic architecture of structural left–right asymmetry of the human brain. Nature Human Behaviour, 5, 1226-1236. doi:10.1038/s41562-021-01069-w.
Abstract
Left–right hemispheric asymmetry is an important aspect of healthy brain organization for many functions including language, and it can be altered in cognitive and psychiatric disorders. No mechanism has yet been identified for establishing the human brain’s left–right axis. We performed multivariate genome-wide association scanning of cortical regional surface area and thickness asymmetries, and subcortical volume asymmetries, using data from 32,256 participants from the UK Biobank. There were 21 significant loci associated with different aspects of brain asymmetry, with functional enrichment involving microtubule-related genes and embryonic brain expression. These findings are consistent with a known role of the cytoskeleton in left–right axis determination in other organs of invertebrates and frogs. Genetic variants associated with brain asymmetry overlapped with those associated with autism, educational attainment and schizophrenia. Comparably large datasets will likely be required in future studies, to replicate and further clarify the associations of microtubule-related genes with variation in brain asymmetry, behavioural and psychiatric traits. -
Zhong, S., Wei, L., Zhao, C., Yang, L., Di, Z., Francks, C., & Gong, G. (2021). Interhemispheric relationship of genetic influence on human brain connectivity. Cerebral Cortex, 31(1), 77-88. doi:10.1093/cercor/bhaa207.
Abstract
To understand the origins of interhemispheric differences and commonalities/coupling in human brain wiring, it is crucial to determine how homologous interregional connectivities of the left and right hemispheres are genetically determined and related. To address this, in the present study, we analyzed human twin and pedigree samples with high-quality diffusion magnetic resonance imaging tractography and estimated the heritability and genetic correlation of homologous left and right white matter (WM) connections. The results showed that the heritability of WM connectivity was similar and coupled between the 2 hemispheres and that the degree of overlap in genetic factors underlying homologous WM connectivity (i.e., interhemispheric genetic correlation) varied substantially across the human brain: from complete overlap to complete nonoverlap. Particularly, the heritability was significantly stronger and the chance of interhemispheric complete overlap in genetic factors was higher in subcortical WM connections than in cortical WM connections. In addition, the heritability and interhemispheric genetic correlations were stronger for long-range connections than for short-range connections. These findings highlight the determinants of the genetics underlying WM connectivity and its interhemispheric relationships, and provide insight into genetic basis of WM connectivity asymmetries in both healthy and disease states.Additional information
Supplementary data -
Devanna, P., Chen, X. S., Ho, J., Gajewski, D., Smith, S. D., Gialluisi, A., Francks, C., Fisher, S. E., Newbury, D. F., & Vernes, S. C. (2018). Next-gen sequencing identifies non-coding variation disrupting miRNA binding sites in neurological disorders. Molecular Psychiatry, 23(5), 1375-1384. doi:10.1038/mp.2017.30.
Abstract
Understanding the genetic factors underlying neurodevelopmental and neuropsychiatric disorders is a major challenge given their prevalence and potential severity for quality of life. While large-scale genomic screens have made major advances in this area, for many disorders the genetic underpinnings are complex and poorly understood. To date the field has focused predominantly on protein coding variation, but given the importance of tightly controlled gene expression for normal brain development and disorder, variation that affects non-coding regulatory regions of the genome is likely to play an important role in these phenotypes. Herein we show the importance of 3 prime untranslated region (3'UTR) non-coding regulatory variants across neurodevelopmental and neuropsychiatric disorders. We devised a pipeline for identifying and functionally validating putatively pathogenic variants from next generation sequencing (NGS) data. We applied this pipeline to a cohort of children with severe specific language impairment (SLI) and identified a functional, SLI-associated variant affecting gene regulation in cells and post-mortem human brain. This variant and the affected gene (ARHGEF39) represent new putative risk factors for SLI. Furthermore, we identified 3′UTR regulatory variants across autism, schizophrenia and bipolar disorder NGS cohorts demonstrating their impact on neurodevelopmental and neuropsychiatric disorders. Our findings show the importance of investigating non-coding regulatory variants when determining risk factors contributing to neurodevelopmental and neuropsychiatric disorders. In the future, integration of such regulatory variation with protein coding changes will be essential for uncovering the genetic causes of complex neurological disorders and the fundamental mechanisms underlying health and diseaseAdditional information
mp201730x1.docx -
Kong, X., Mathias, S. R., Guadalupe, T., ENIGMA Laterality Working Group, Glahn, D. C., Franke, B., Crivello, F., Tzourio-Mazoyer, N., Fisher, S. E., Thompson, P. M., & Francks, C. (2018). Mapping Cortical Brain Asymmetry in 17,141 Healthy Individuals Worldwide via the ENIGMA Consortium. Proceedings of the National Academy of Sciences of the United States of America, 115(22), E5154-E5163. doi:10.1073/pnas.1718418115.
Abstract
Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here the ENIGMA consortium presents the largest ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and intracranial volume. Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets (N = 1,443 and 1,113, respectively), we found several asymmetries showing significant, replicable heritability. The structural asymmetries identified, and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders.Additional information
pnas.1718418115.sapp.pdf -
De Kovel, C. G. F., Lisgo, S. N., Fisher, S. E., & Francks, C. (2018). Subtle left-right asymmetry of gene expression profiles in embryonic and foetal human brains. Scientific Reports, 8: 12606. doi:10.1038/s41598-018-29496-2.
Abstract
Left-right laterality is an important aspect of human –and in fact all vertebrate– brain organization for which the genetic basis is poorly understood. Using RNA sequencing data we contrasted gene expression in left- and right-sided samples from several structures of the anterior central nervous systems of post mortem human embryos and foetuses. While few individual genes stood out as significantly lateralized, most structures showed evidence of laterality of their overall transcriptomic profiles. These left-right differences showed overlap with age-dependent changes in expression, indicating lateralized maturation rates, but not consistently in left-right orientation over all structures. Brain asymmetry may therefore originate in multiple locations, or if there is a single origin, it is earlier than 5 weeks post conception, with structure-specific lateralized processes already underway by this age. This pattern is broadly consistent with the weak correlations reported between various aspects of adult brain laterality, such as language dominance and handedness. -
De Kovel, C. G. F., Lisgo, S. N., & Francks, C. (2018). Transcriptomic analysis of left-right differences in human embryonic forebrain and midbrain. Scientific Data, 5: 180164. doi:10.1038/sdata.2018.164.
Abstract
Left-right asymmetry is subtle but pervasive in the human central nervous system. This asymmetry is initiated early during development, but its mechanisms are poorly known. Forebrains and midbrains were dissected from six human embryos at Carnegie stages 15 or 16, one of which was female. The structures were divided into left and right sides, and RNA was isolated. RNA was sequenced with 100 base-pair paired ends using Illumina Hiseq 4000. After quality control, five paired brain sides were available for midbrain and forebrain. A paired analysis between left- and right sides of a given brain structure across the embryos identified left-right differences. The dataset, consisting of Fastq files and a read count table, can be further used to study early development of the human brainAdditional information
https://www.nature.com/articles/sdata2018164#supplementary-information
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