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Pu, Y., Francks, C., & Kong, X. (2025). Global brain asymmetry. Trends in Cognitive Sciences, 29(2), 114-117. doi:10.1016/j.tics.2024.10.008.
Abstract
Lateralization is a defining characteristic of the human brain, often studied through localized approaches that focus on interhemispheric differences between homologous pairs of regions. It is also important to emphasize an integrative perspective of global brain asymmetry, in which hemispheric differences are understood through global patterns across the entire brain. -
Rivera-Olvera, A., Houwing, D. J., Ellegood, J., Masifi, S., Martina, S., Silberfeld, A., Pourquie, O., Lerch, J. P., Francks, C., Homberg, J. R., Van Heukelum, S., & Grandjean, J. (2025). The universe is asymmetric, the mouse brain too. Molecular Psychiatry, 30, 489-496. doi:10.1038/s41380-024-02687-2.
Abstract
Hemispheric brain asymmetry is a basic organizational principle of the human brain and has been implicated in various psychiatric conditions, including autism spectrum disorder. Brain asymmetry is not a uniquely human feature and is observed in other species such as the mouse. Yet, asymmetry patterns are generally nuanced, and substantial sample sizes are required to detect these patterns. In this pre-registered study, we use a mouse dataset from the Province of Ontario Neurodevelopmental Network, which comprises structural MRI data from over 2000 mice, including genetic models for autism spectrum disorder, to reveal the scope and magnitude of hemispheric asymmetry in the mouse. Our findings demonstrate the presence of robust hemispheric asymmetry in the mouse brain, such as larger right hemispheric volumes towards the anterior pole and larger left hemispheric volumes toward the posterior pole, opposite to what has been shown in humans. This suggests the existence of species-specific traits. Further clustering analysis identified distinct asymmetry patterns in autism spectrum disorder models, a phenomenon that is also seen in atypically developing participants. Our study shows potential for the use of mouse models in studying the biological bases of typical and atypical brain asymmetry but also warrants caution as asymmetry patterns seem to differ between humans and mice. -
Sha, Z., & Francks, C. (2025). Large-scale genetic mapping for human brain asymmetry. In C. Papagno, & P. Corballis (
Eds. ), Handbook of Clinical Neurology: Cerebral Asymmetries (pp. 241-254). Amsterdam: Elsevier.Abstract
Left-right asymmetry is an important aspect of human brain organization for functions including language and hand motor control, which can be altered in some psychiatric traits. The last five years have seen rapid advances in the identification of specific genes linked to variation in asymmetry of the human brain and/or handedness. These advances have been driven by a new generation of large-scale genome-wide association studies, carried out in samples ranging from roughly 16,000 to over 1.5 million participants. The implicated genes tend to be most active in the embryonic and fetal brain, consistent with early developmental patterning of brain asymmetry. Several of the genes encode components of microtubules, or other microtubule-associated proteins. Microtubules are key elements of the internal cellular skeleton (cytoskeleton). A major challenge remains to understand how these genes affect, or even induce, the brain’s left-right axis. Several of the implicated genes have also been associated with psychiatric or neurological disorders, and polygenic dispositions to autism and schizophrenia have been associated with structural brain asymmetry. Knowledge of developmental mechanisms that lead to hemispheric specialization may ultimately help to define etiologic subtypes of brain disorders. -
Gialluisi, A., Dediu, D., Francks, C., & Fisher, S. E. (2013). Persistence and transmission of recessive deafness and sign language: New insights from village sign languages. European Journal of Human Genetics, 21, 894-896. doi:10.1038/ejhg.2012.292.
Abstract
First paragraph: The study of the transmission of sign languages can give novel insights into the transmission of spoken languages1 and, more generally, into gene–culture coevolution. Over the years, several papers related to the persistence of sign language have been
reported.2–6 All of these studies have emphasized the role of assortative (non-random) mating by deafness state (ie, a tendency for deaf individuals to partner together) for increasing the frequency of recessive deafness, and hence for the persistence of sign language in a population. -
Stephens, S., Hartz, S., Hoft, N., Saccone, N., Corley, R., Hewitt, J., Hopfer, C., Breslau, N., Coon, H., Chen, X., Ducci, F., Dueker, N., Franceschini, N., Frank, J., Han, Y., Hansel, N., Jiang, C., Korhonen, T., Lind, P., Liu, J. and 105 moreStephens, S., Hartz, S., Hoft, N., Saccone, N., Corley, R., Hewitt, J., Hopfer, C., Breslau, N., Coon, H., Chen, X., Ducci, F., Dueker, N., Franceschini, N., Frank, J., Han, Y., Hansel, N., Jiang, C., Korhonen, T., Lind, P., Liu, J., Michel, M., Lyytikäinen, L.-P., Shaffer, J., Short, S., Sun, J., Teumer, A., Thompson, J., Vogelzangs, N., Vink, J., Wenzlaff, A., Wheeler, W., Yang, B.-Z., Aggen, S., Balmforth, A., Baumesiter, S., Beaty, T., Benjamin, D., Bergen, A., Broms, U., Cesarini, D., Chatterjee, N., Chen, J., Cheng, Y.-C., Cichon, S., Couper, D., Cucca, F., Dick, D., Foround, T., Furberg, H., Giegling, I., Gillespie, N., Gu, F.,.Hall, A., Hällfors, J., Han, S., Hartmann, A., Heikkilä, K., Hickie, I., Hottenga, J., Jousilahti, P., Kaakinen, M., Kähönen, M., Koellinger, P., Kittner, S., Konte, B., Landi, M.-T., Laatikainen, T., Leppert, M., Levy, S., Mathias, R., McNeil, D., Medlund, S., Montgomery, G., Murray, T., Nauck, M., North, K., Paré, P., Pergadia, M., Ruczinski, I., Salomaa, V., Viikari, J., Willemsen, G., Barnes, K., Boerwinkle, E., Boomsma, D., Caporaso, N., Edenberg, H., Francks, C., Gelernter, J., Grabe, H., Hops, H., Jarvelin, M.-R., Johannesson, M., Kendler, K., Lehtimäki, T., Magnusson, P., Marazita, M., Marchini, J., Mitchell, B., Nöthen, M., Penninx, B., Raitakari, O., Rietschel, M., Rujescu, D., Samani, N., Schwartz, A., Shete, S., Spitz, M., Swan, G., Völzke, H., Veijola, J., Wei, Q., Amos, C., Canon, D., Grucza, R., Hatsukami, D., Heath, A., Johnson, E., Kaprio, J., Madden, P., Martin, N., Stevens, V., Weiss, R., Kraft, P., Bierut, L., & Ehringer, M. (2013). Distinct Loci in the CHRNA5/CHRNA3/CHRNB4 Gene Cluster are Associated with Onset of Regular Smoking. Genetic Epidemiology, 37, 846-859. doi:10.1002/gepi.21760.
Abstract
Neuronal nicotinic acetylcholine receptor (nAChR) genes (CHRNA5/CHRNA3/CHRNB4) have been reproducibly associated with nicotine dependence, smoking behaviors, and lung cancer risk. Of the few reports that have focused on early smoking behaviors, association results have been mixed. This meta-analysis examines early smoking phenotypes and SNPs in the gene cluster to determine: (1) whether the most robust association signal in this region (rs16969968) for other smoking behaviors is also associated with early behaviors, and/or (2) if additional statistically independent signals are important in early smoking. We focused on two phenotypes: age of tobacco initiation (AOI) and age of first regular tobacco use (AOS). This study included 56,034 subjects (41 groups) spanning nine countries and evaluated five SNPs including rs1948, rs16969968, rs578776, rs588765, and rs684513. Each dataset was analyzed using a centrally generated script. Meta-analyses were conducted from summary statistics. AOS yielded significant associations with SNPs rs578776 (beta = 0.02, P = 0.004), rs1948 (beta = 0.023, P = 0.018), and rs684513 (beta = 0.032, P = 0.017), indicating protective effects. There were no significant associations for the AOI phenotype. Importantly, rs16969968, the most replicated signal in this region for nicotine dependence, cigarettes per day, and cotinine levels, was not associated with AOI (P = 0.59) or AOS (P = 0.92). These results provide important insight into the complexity of smoking behavior phenotypes, and suggest that association signals in the CHRNA5/A3/B4 gene cluster affecting early smoking behaviors may be different from those affecting the mature nicotine dependence phenotypeAdditional information
http://onlinelibrary.wiley.com/doi/10.1002/gepi.21760/suppinfoFiles private
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Gayán, J., Willcutt, E. G., Fisher, S. E., Francks, C., Cardon, L. R., Olson, R. K., Pennington, B. F., Smith, S., Monaco, A. P., & DeFries, J. C. (2005). Bivariate linkage scan for reading disability and attention-deficit/hyperactivity disorder localizes pleiotropic loci. Journal of Child Psychology and Psychiatry, 46(10), 1045-1056. doi:10.1111/j.1469-7610.2005.01447.x.
Abstract
BACKGROUND: There is a growing interest in the study of the genetic origins of comorbidity, a direct consequence of the recent findings of genetic loci that are seemingly linked to more than one disorder. There are several potential causes for these shared regions of linkage, but one possibility is that these loci may harbor genes with manifold effects. The established genetic correlation between reading disability (RD) and attention-deficit/hyperactivity disorder (ADHD) suggests that their comorbidity is due at least in part to genes that have an impact on several phenotypes, a phenomenon known as pleiotropy. METHODS: We employ a bivariate linkage test for selected samples that could help identify these pleiotropic loci. This linkage method was employed to carry out the first bivariate genome-wide analysis for RD and ADHD, in a selected sample of 182 sibling pairs. RESULTS: We found evidence for a novel locus at chromosome 14q32 (multipoint LOD=2.5; singlepoint LOD=3.9) with a pleiotropic effect on RD and ADHD. Another locus at 13q32, which had been implicated in previous univariate scans of RD and ADHD, seems to have a pleiotropic effect on both disorders. 20q11 is also suggested as a pleiotropic locus. Other loci previously implicated in RD or ADHD did not exhibit bivariate linkage. CONCLUSIONS: Some loci are suggested as having pleiotropic effects on RD and ADHD, while others might have unique effects. These results highlight the utility of this bivariate linkage method to study pleiotropy.
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