Clyde Francks

Publications

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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.

    Additional information

    tables link to preprint on BioRxiv
  • 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.
  • Hartz, S. M., Short, S. E., Saccone, N. L., Culverhouse, R., Chen, L., Schwantes-An, T.-H., Coon, H., Han, Y., Stephens, S. H., Sun, J., Chen, X., Ducci, F., Dueker, N., Franceschini, N., Frank, J., Geller, F., Gubjartsson, D., Hansel, N. N., Jiang, C., Keskitalo-Vuokko, K. and 132 moreHartz, S. M., Short, S. E., Saccone, N. L., Culverhouse, R., Chen, L., Schwantes-An, T.-H., Coon, H., Han, Y., Stephens, S. H., Sun, J., Chen, X., Ducci, F., Dueker, N., Franceschini, N., Frank, J., Geller, F., Gubjartsson, D., Hansel, N. N., Jiang, C., Keskitalo-Vuokko, K., Liu, Z., Lyytikainen, L.-P., Michel, M., Rawal, R., Rosenberger, A., Scheet, P., Shaffer, J. R., Teumer, A., Thompson, J. R., Vink, J. M., Vogelzangs, N., Wenzlaff, A. S., Wheeler, W., Xiao, X., Yang, B.-Z., Aggen, S. H., Balmforth, A. J., Baumeister, S. E., Beaty, T., Bennett, S., Bergen, A. W., Boyd, H. A., Broms, U., Campbell, H., Chatterjee, N., Chen, J., Cheng, Y.-C., Cichon, S., Couper, D., Cucca, F., Dick, D. M., Foroud, T., Furberg, H., Giegling, I., Gu, F., Hall, A. S., Hallfors, J., Han, S., Hartmann, A. M., Hayward, C., Heikkila, K., Hewitt, J. K., Hottenga, J. J., Jensen, M. K., Jousilahti, P., Kaakinen, M., Kittner, S. J., Konte, B., Korhonen, T., Landi, M.-T., Laatikainen, T., Leppert, M., Levy, S. M., Mathias, R. A., McNeil, D. W., Medland, S. E., Montgomery, G. W., Muley, T., Murray, T., Nauck, M., North, K., Pergadia, M., Polasek, O., Ramos, E. M., Ripatti, S., Risch, A., Ruczinski, I., Rudan, I., Salomaa, V., Schlessinger, D., Styrkarsdottir, U., Terracciano, A., Uda, M., Willemsen, G., Wu, X., Abecasis, G., Barnes, K., Bickeboller, H., Boerwinkle, E., Boomsma, D. I., Caporaso, N., Duan, J., Edenberg, H. J., Francks, C., Gejman, P. V., Gelernter, J., Grabe, H. J., Hops, H., Jarvelin, M.-R., Viikari, J., Kahonen, M., Kendler, K. S., Lehtimaki, T., Levinson, D. F., Marazita, M. L., Marchini, J., Melbye, M., Mitchell, B., Murray, J. C., Nothen, M. M., Penninx, B. W., Raitakari, O., Rietschel, M., Rujescu, D., Samani, N. J., Sanders, A. R., Schwartz, A. G., Shete, S., Shi, J., Spitz, M., Stefansson, K., Swan, G. E., Thorgeirsson, T., Volzke, H., Wei, Q., Wichmann, H.-E., Amos, C. I., Breslau, N., Cannon, D. S., Ehringer, M., Grucza, R., Hatsukami, D., Heath, A., Johnson, E. O., Kaprio, J., Madden, P., Martin, N. G., Stevens, V. L., Stitzel, J. A., Weiss, R. B., Kraft, P., & Bierut, L. J. (2012). Increased genetic vulnerability to smoking at CHRNA5 in early-onset smokers. Archives of General Psychiatry, 69, 854-860. doi:10.1001/archgenpsychiatry.2012.124.

    Abstract

    CONTEXT Recent studies have shown an association between cigarettes per day (CPD) and a nonsynonymous single-nucleotide polymorphism in CHRNA5, rs16969968. OBJECTIVE To determine whether the association between rs16969968 and smoking is modified by age at onset of regular smoking. DATA SOURCES Primary data. STUDY SELECTION Available genetic studies containing measures of CPD and the genotype of rs16969968 or its proxy. DATA EXTRACTION Uniform statistical analysis scripts were run locally. Starting with 94 050 ever-smokers from 43 studies, we extracted the heavy smokers (CPD >20) and light smokers (CPD ≤10) with age-at-onset information, reducing the sample size to 33 348. Each study was stratified into early-onset smokers (age at onset ≤16 years) and late-onset smokers (age at onset >16 years), and a logistic regression of heavy vs light smoking with the rs16969968 genotype was computed for each stratum. Meta-analysis was performed within each age-at-onset stratum. DATA SYNTHESIS Individuals with 1 risk allele at rs16969968 who were early-onset smokers were significantly more likely to be heavy smokers in adulthood (odds ratio [OR] = 1.45; 95% CI, 1.36-1.55; n = 13 843) than were carriers of the risk allele who were late-onset smokers (OR = 1.27; 95% CI, 1.21-1.33, n = 19 505) (P = .01). CONCLUSION These results highlight an increased genetic vulnerability to smoking in early-onset smokers.

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  • Bailey, A., Hervas, A., Matthews, N., Palferman, S., Wallace, S., Aubin, A., Michelotti, J., Wainhouse, C., Papanikolaou, K., Rutter, M., Maestrini, E., Marlow, A., Weeks, D. E., Lamb, J., Francks, C., Kearsley, G., Scudder, P., Monaco, A. P., Baird, G., Cox, A. and 46 moreBailey, A., Hervas, A., Matthews, N., Palferman, S., Wallace, S., Aubin, A., Michelotti, J., Wainhouse, C., Papanikolaou, K., Rutter, M., Maestrini, E., Marlow, A., Weeks, D. E., Lamb, J., Francks, C., Kearsley, G., Scudder, P., Monaco, A. P., Baird, G., Cox, A., Cockerill, H., Nuffield, F., Le Couteur, A., Berney, T., Cooper, H., Kelly, T., Green, J., Whittaker, J., Gilchrist, A., Bolton, P., Schönewald, A., Daker, M., Ogilvie, C., Docherty, Z., Deans, Z., Bolton, B., Packer, R., Poustka, F., Rühl, D., Schmötzer, G., Bölte, S., Klauck, S. M., Spieler, A., Poustka., A., Van Engeland, H., Kemner, C., De Jonge, M., Den Hartog, I., Lord, C., Cook, E., Leventhal, B., Volkmar, F., Pauls, D., Klin, A., Smalley, S., Fombonne, E., Rogé, B., Tauber, M., Arti-Vartayan, E., Fremolle-Kruck., J., Pederson, L., Haracopos, D., Brondum-Nielsen, K., & Cotterill, R. (1998). A full genome screen for autism with evidence for linkage to a region on chromosome 7q. International Molecular Genetic Study of Autism Consortium. Human Molecular Genetics, 7(3), 571-578. doi:10.1093/hmg/7.3.571.

    Abstract

    Autism is characterized by impairments in reciprocal social interaction and communication, and restricted and sterotyped patterns of interests and activities. Developmental difficulties are apparent before 3 years of age and there is evidence for strong genetic influences most likely involving more than one susceptibility gene. A two-stage genome search for susceptibility loci in autism was performed on 87 affected sib pairs plus 12 non-sib affected relative-pairs, from a total of 99 families identified by an international consortium. Regions on six chromosomes (4, 7, 10, 16, 19 and 22) were identified which generated a multipoint maximum lod score (MLS) > 1. A region on chromosome 7q was the most significant with an MLS of 3.55 near markers D7S530 and D7S684 in the subset of 56 UK affected sib-pair families, and an MLS of 2.53 in all 87 affected sib-pair families. An area on chromosome 16p near the telomere was the next most significant, with an MLS of 1.97 in the UK families, and 1.51 in all families. These results are an important step towards identifying genes predisposing to autism; establishing their general applicability requires further study.

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