Publications

Displaying 1 - 6 of 6
  • D’Onofrio, G., Accogli, A., Severino, M., Caliskan, H., Kokotović, T., Blazekovic, A., Jercic, K. G., Markovic, S., Zigman, T., Goran, K., Barišić, N., Duranovic, V., Ban, A., Borovecki, F., Ramadža, D. P., Barić, I., Fazeli, W., Herkenrath, P., Marini, C., Vittorini, R. and 30 moreD’Onofrio, G., Accogli, A., Severino, M., Caliskan, H., Kokotović, T., Blazekovic, A., Jercic, K. G., Markovic, S., Zigman, T., Goran, K., Barišić, N., Duranovic, V., Ban, A., Borovecki, F., Ramadža, D. P., Barić, I., Fazeli, W., Herkenrath, P., Marini, C., Vittorini, R., Gowda, V., Bouman, A., Rocca, C., Alkhawaja, I. A., Murtaza, B. N., Rehman, M. M. U., Al Alam, C., Nader, G., Mancardi, M. M., Giacomini, T., Srivastava, S., Alvi, J. R., Tomoum, H., Matricardi, S., Iacomino, M., Riva, A., Scala, M., Madia, F., Pistorio, A., Salpietro, V., Minetti, C., Rivière, J.-B., Srour, M., Efthymiou, S., Maroofian, R., Houlden, H., Vernes, S. C., Zara, F., Striano, P., & Nagy, V. (2023). Genotype–phenotype correlation in contactin-associated protein-like 2 (CNTNAP-2) developmental disorder. Human Genetics, 142, 909-925. doi:10.1007/s00439-023-02552-2.

    Abstract

    Contactin-associated protein-like 2 (CNTNAP2) gene encodes for CASPR2, a presynaptic type 1 transmembrane protein, involved in cell–cell adhesion and synaptic interactions. Biallelic CNTNAP2 loss has been associated with “Pitt-Hopkins-like syndrome-1” (MIM#610042), while the pathogenic role of heterozygous variants remains controversial. We report 22 novel patients harboring mono- (n = 2) and bi-allelic (n = 20) CNTNAP2 variants and carried out a literature review to characterize the genotype–phenotype correlation. Patients (M:F 14:8) were aged between 3 and 19 years and affected by global developmental delay (GDD) (n = 21), moderate to profound intellectual disability (n = 17) and epilepsy (n = 21). Seizures mainly started in the first two years of life (median 22.5 months). Antiseizure medications were successful in controlling the seizures in about two-thirds of the patients. Autism spectrum disorder (ASD) and/or other neuropsychiatric comorbidities were present in nine patients (40.9%). Nonspecific midline brain anomalies were noted in most patients while focal signal abnormalities in the temporal lobes were noted in three subjects. Genotype–phenotype correlation was performed by also including 50 previously published patients (15 mono- and 35 bi-allelic variants). Overall, GDD (p < 0.0001), epilepsy (p < 0.0001), hyporeflexia (p = 0.012), ASD (p = 0.009), language impairment (p = 0.020) and severe cognitive impairment (p = 0.031) were significantly associated with the presence of biallelic versus monoallelic variants. We have defined the main features associated with biallelic CNTNAP2 variants, as severe cognitive impairment, epilepsy and behavioral abnormalities. We propose CASPR2-deficiency neurodevelopmental disorder as an exclusively recessive disease while the contribution of heterozygous variants is less likely to follow an autosomal dominant inheritance pattern.

    Additional information

    supplementary tables
  • Lu, A. T., Fei, Z., Haghani, A., Robeck, T. R., Zoller, J. A., Li, C. Z., Lowe, R., Yan, Q., Zhang, J., Vu, H., Ablaeva, J., Acosta-Rodriguez, V. A., Adams, D. M., Almunia, J., Aloysius, A., Ardehali, R., Arneson, A., Baker, C. S., Banks, G., Belov, K. and 168 moreLu, A. T., Fei, Z., Haghani, A., Robeck, T. R., Zoller, J. A., Li, C. Z., Lowe, R., Yan, Q., Zhang, J., Vu, H., Ablaeva, J., Acosta-Rodriguez, V. A., Adams, D. M., Almunia, J., Aloysius, A., Ardehali, R., Arneson, A., Baker, C. S., Banks, G., Belov, K., Bennett, N. C., Black, P., Blumstein, D. T., Bors, E. K., Breeze, C. E., Brooke, R. T., Brown, J. L., Carter, G. G., Caulton, A., Cavin, J. M., Chakrabarti, L., Chatzistamou, I., Chen, H., Cheng, K., Chiavellini, P., Choi, O. W., Clarke, S. M., Cooper, L. N., Cossette, M. L., Day, J., DeYoung, J., DiRocco, S., Dold, C., Ehmke, E. E., Emmons, C. K., Emmrich, S., Erbay, E., Erlacher-Reid, C., Faulkes, C. G., Ferguson, S. H., Finno, C. J., Flower, J. E., Gaillard, J. M., Garde, E., Gerber, L., Gladyshev, V. N., Gorbunova, V., Goya, R. G., Grant, M. J., Green, C. B., Hales, E. N., Hanson, M. B., Hart, D. W., Haulena, M., Herrick, K., Hogan, A. N., Hogg, C. J., Hore, T. A., Huang, T., Izpisua Belmonte, J. C., Jasinska, A. J., Jones, G., Jourdain, E., Kashpur, O., Katcher, H., Katsumata, E., Kaza, V., Kiaris, H., Kobor, M. S., Kordowitzki, P., Koski, W. R., Krützen, M., Kwon, S. B., Larison, B., Lee, S. G., Lehmann, M., Lemaitre, J. F., Levine, A. J., Li, C., Li, X., Lim, A. R., Lin, D. T. S., Lindemann, D. M., Little, T. J., Macoretta, N., Maddox, D., Matkin, C. O., Mattison, J. A., McClure, M., Mergl, J., Meudt, J. J., Montano, G. A., Mozhui, K., Munshi-South, J., Naderi, A., Nagy, M., Narayan, P., Nathanielsz, P. W., Nguyen, N. B., Niehrs, C., O’Brien, J. K., O’Tierney Ginn, P., Odom, D. T., Ophir, A. G., Osborn, S., Ostrander, E. A., Parsons, K. M., Paul, K. C., Pellegrini, M., Peters, K. J., Pedersen, A. B., Petersen, J. L., Pietersen, D. W., Pinho, G. M., Plassais, J., Poganik, J. R., Prado, N. A., Reddy, P., Rey, B., Ritz, B. R., Robbins, J., Rodriguez, M., Russell, J., Rydkina, E., Sailer, L. L., Salmon, A. B., Sanghavi, A., Schachtschneider, K. M., Schmitt, D., Schmitt, T., Schomacher, L., Schook, L. B., Sears, K. E., Seifert, A. W., Seluanov, A., Shafer, A. B. A., Shanmuganayagam, D., Shindyapina, A. V., Simmons, M., Singh, K., Sinha, I., Slone, J., Snell, R. G., Soltanmaohammadi, E., Spangler, M. L., Spriggs, M. C., Staggs, L., Stedman, N., Steinman, K. J., Stewart, D. T., Sugrue, V. J., Szladovits, B., Takahashi, J. S., Takasugi, M., Teeling, E. C., Thompson, M. J., Van Bonn, B., Vernes, S. C., Villar, D., Vinters, H. V., Wallingford, M. C., Wang, N., Wayne, R. K., Wilkinson, G. S., Williams, C. K., Williams, R. W., Yang, X. W., Yao, M., Young, B. G., Zhang, B., Zhang, Z., Zhao, P., Zhao, Y., Zhou, W., Zimmermann, J., Ernst, J., Raj, K., & Horvath, S. (2023). Universal DNA methylation age across mammalian tissues. Nature aging, 3, 1144-1166. doi:10.1038/s43587-023-00462-6.

    Abstract

    Aging, often considered a result of random cellular damage, can be accurately estimated using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we demonstrate the development of universal pan-mammalian clocks, using 11,754 methylation arrays from our Mammalian Methylation Consortium, which encompass 59 tissue types across 185 mammalian species. These predictive models estimate mammalian tissue age with high accuracy (r > 0.96). Age deviations correlate with human mortality risk, mouse somatotropic axis mutations and caloric restriction. We identified specific cytosines with methylation levels that change with age across numerous species. These sites, highly enriched in polycomb repressive complex 2-binding locations, are near genes implicated in mammalian development, cancer, obesity and longevity. Our findings offer new evidence suggesting that aging is evolutionarily conserved and intertwined with developmental processes across all mammals.
  • Haghani, A., Li, C. Z., Robeck, T. R., Zhang, J., Lu, A. T., Ablaeva, J., Acosta-Rodríguez, V. A., Adams, D. M., Alagaili, A. N., Almunia, J., Aloysius, A., Amor, N. M. S., Ardehali, R., Arneson, A., Baker, C. S., Banks, G., Belov, K., Bennett, N. C., Black, P., Blumstein, D. T. and 170 moreHaghani, A., Li, C. Z., Robeck, T. R., Zhang, J., Lu, A. T., Ablaeva, J., Acosta-Rodríguez, V. A., Adams, D. M., Alagaili, A. N., Almunia, J., Aloysius, A., Amor, N. M. S., Ardehali, R., Arneson, A., Baker, C. S., Banks, G., Belov, K., Bennett, N. C., Black, P., Blumstein, D. T., Bors, E. K., Breeze, C. E., Brooke, R. T., Brown, J. L., Carter, G., Caulton, A., Cavin, J. M., Chakrabarti, L., Chatzistamou, I., Chavez, A. S., Chen, H., Cheng, K., Chiavellini, P., Choi, O.-W., Clarke, S., Cook, J. A., Cooper, L. N., Cossette, M.-L., Day, J., DeYoung, J., Dirocco, S., Dold, C., Dunnum, J. L., Ehmke, E. E., Emmons, C. K., Emmrich, S., Erbay, E., Erlacher-Reid, C., Faulkes, C. G., Fei, Z., Ferguson, S. H., Finno, C. J., Flower, J. E., Gaillard, J.-M., Garde, E., Gerber, L., Gladyshev, V. N., Goya, R. G., Grant, M. J., Green, C. B., Hanson, M. B., Hart, D. W., Haulena, M., Herrick, K., Hogan, A. N., Hogg, C. J., Hore, T. A., Huang, T., Izpisua Belmonte, J. C., Jasinska, A. J., Jones, G., Jourdain, E., Kashpur, O., Katcher, H., Katsumata, E., Kaza, V., Kiaris, H., Kobor, M. S., Kordowitzki, P., Koski, W. R., Krützen, M., Kwon, S. B., Larison, B., Lee, S.-G., Lehmann, M., Lemaître, J.-F., Levine, A. J., Li, X., Li, C., Lim, A. R., Lin, D. T. S., Lindemann, D. M., Liphardt, S. W., Little, T. J., Macoretta, N., Maddox, D., Matkin, C. O., Mattison, J. A., McClure, M., Mergl, J., Meudt, J. J., Montano, G. A., Mozhui, K., Munshi-South, J., Murphy, W. J., Naderi, A., Nagy, M., Narayan, P., Nathanielsz, P. W., Nguyen, N. B., Niehrs, C., Nyamsuren, B., O’Brien, J. K., Ginn, P. O., Odom, D. T., Ophir, A. G., Osborn, S., Ostrander, E. A., Parsons, K. M., Paul, K. C., Pedersen, A. B., Pellegrini, M., Peters, K. J., Petersen, J. L., Pietersen, D. W., Pinho, G. M., Plassais, J., Poganik, J. R., Prado, N. A., Reddy, P., Rey, B., Ritz, B. R., Robbins, J., Rodriguez, M., Russell, J., Rydkina, E., Sailer, L. L., Salmon, A. B., Sanghavi, A., Schachtschneider, K. M., Schmitt, D., Schmitt, T., Schomacher, L., Schook, L. B., Sears, K. E., Seifert, A. W., Shafer, A. B. A., Shindyapina, A. V., Simmons, M., Singh, K., Sinha, I., Slone, J., Snell, R. G., Soltanmohammadi, E., Spangler, M. L., Spriggs, M., Staggs, L., Stedman, N., Steinman, K. J., Stewart, D. T., Sugrue, V. J., Szladovits, B., Takahashi, J. S., Takasugi, M., Teeling, E. C., Thompson, M. J., Van Bonn, B., Vernes, S. C., Villar, D., Vinters, H. V., Vu, H., Wallingford, M. C., Wang, N., Wilkinson, G. S., Williams, R. W., Yan, Q., Yao, M., Young, B. G., Zhang, B., Zhang, Z., Zhao, Y., Zhao, P., Zhou, W., Zoller, J. A., Ernst, J., Seluanov, A., Gorbunova, V., Yang, X. W., Raj, K., & Horvath, S. (2023). DNA methylation networks underlying mammalian traits. Science, 381(6658): eabq5693. doi:10.1126/science.abq5693.

    Abstract

    INTRODUCTION
    Comparative epigenomics is an emerging field that combines epigenetic signatures with phylogenetic relationships to elucidate species characteristics such as maximum life span. For this study, we generated cytosine DNA methylation (DNAm) profiles (n = 15,456) from 348 mammalian species using a methylation array platform that targets highly conserved cytosines.
    RATIONALE
    Nature has evolved mammalian species of greatly differing life spans. To resolve the relationship of DNAm with maximum life span and phylogeny, we performed a large-scale cross-species unsupervised analysis. Comparative studies in many species enables the identification of epigenetic correlates of maximum life span and other traits.
    RESULTS
    We first tested whether DNAm levels in highly conserved cytosines captured phylogenetic relationships among species. We constructed phyloepigenetic trees that paralleled the traditional phylogeny. To avoid potential confounding by different tissue types, we generated tissue-specific phyloepigenetic trees. The high phyloepigenetic-phylogenetic congruence is due to differences in methylation levels and is not confounded by sequence conservation.
    We then interrogated the extent to which DNA methylation associates with specific biological traits. We used an unsupervised weighted correlation network analysis (WGCNA) to identify clusters of highly correlated CpGs (comethylation modules). WGCNA identified 55 distinct comethylation modules, of which 30 were significantly associated with traits including maximum life span, adult weight, age, sex, human mortality risk, or perturbations that modulate murine life span.
    Both the epigenome-wide association analysis (EWAS) and eigengene-based analysis identified methylation signatures of maximum life span, and most of these were independent of aging, presumably set at birth, and could be stable predictors of life span at any point in life. Several CpGs that are more highly methylated in long-lived species are located near HOXL subclass homeoboxes and other genes that play a role in morphogenesis and development. Some of these life span–related CpGs are located next to genes that are also implicated in our analysis of upstream regulators (e.g., ASCL1 and SMAD6). CpGs with methylation levels that are inversely related to life span are enriched in transcriptional start site (TSS1) and promoter flanking (PromF4, PromF5) associated chromatin states. Genes located in chromatin state TSS1 are constitutively active and enriched for nucleic acid metabolic processes. This suggests that long-living species evolved mechanisms that maintain low methylation levels in these chromatin states that would favor higher expression levels of genes essential for an organism’s survival.
    The upstream regulator analysis of the EWAS of life span identified the pluripotency transcription factors OCT4, SOX2, and NANOG. Other factors, such as POLII, CTCF, RAD21, YY1, and TAF1, showed the strongest enrichment for negatively life span–related CpGs.
    CONCLUSION
    The phyloepigenetic trees indicate that divergence of DNA methylation profiles closely parallels that of genetics through evolution. Our results demonstrate that DNA methylation is subjected to evolutionary pressures and selection. The publicly available data from our Mammalian Methylation Consortium are a rich source of information for different fields such as evolutionary biology, developmental biology, and aging.
  • Paulat, N. S., Storer, J. M., Moreno-Santillán, D. D., Osmanski, A. B., Sullivan, K. A. M., Grimshaw, J. R., Korstian, J., Halsey, M., Garcia, C. J., Crookshanks, C., Roberts, J., Smit, A. F. A., Hubley, R., Rosen, J., Teeling, E. C., Vernes, S. C., Myers, E., Pippel, M., Brown, T., Hiller, M. and 5 morePaulat, N. S., Storer, J. M., Moreno-Santillán, D. D., Osmanski, A. B., Sullivan, K. A. M., Grimshaw, J. R., Korstian, J., Halsey, M., Garcia, C. J., Crookshanks, C., Roberts, J., Smit, A. F. A., Hubley, R., Rosen, J., Teeling, E. C., Vernes, S. C., Myers, E., Pippel, M., Brown, T., Hiller, M., Zoonomia Consortium, Rojas, D., Dávalos, L. M., Lindblad-Toh, K., Karlsson, E. K., & Ray, D. A. (2023). Chiropterans are a hotspot for horizontal transfer of DNA transposons in mammalia. Molecular Biology and Evolution, 40(5): msad092. doi:10.1093/molbev/msad092.

    Abstract

    Horizontal transfer of transposable elements (TEs) is an important mechanism contributing to genetic diversity and innovation. Bats (order Chiroptera) have repeatedly been shown to experience horizontal transfer of TEs at what appears to be a high rate compared with other mammals. We investigated the occurrence of horizontally transferred (HT) DNA transposons involving bats. We found over 200 putative HT elements within bats; 16 transposons were shared across distantly related mammalian clades, and 2 other elements were shared with a fish and two lizard species. Our results indicate that bats are a hotspot for horizontal transfer of DNA transposons. These events broadly coincide with the diversification of several bat clades, supporting the hypothesis that DNA transposon invasions have contributed to genetic diversification of bats.

    Additional information

    supplemental methods supplemental tables
  • Rutz, C., Bronstein, M., Raskin, A., Vernes, S. C., Zacarian, K., & Blasi, D. E. (2023). Using machine learning to decode animal communication. Science, 381(6654), 152-155. doi:10.1126/science.adg7314.

    Abstract

    The past few years have seen a surge of interest in using machine learning (ML) methods for studying the behavior of nonhuman animals (hereafter “animals”) (1). A topic that has attracted particular attention is the decoding of animal communication systems using deep learning and other approaches (2). Now is the time to tackle challenges concerning data availability, model validation, and research ethics, and to embrace opportunities for building collaborations across disciplines and initiatives.
  • Johns, T. G., Perera, R. M., Vitali, A. A., Vernes, S. C., & Scott, A. (2004). Phosphorylation of a glioma-specific mutation of the EGFR [Abstract]. Neuro-Oncology, 6, 317.

    Abstract

    Mutations of the epidermal growth factor receptor (EGFR) gene are found at a relatively high frequency in glioma, with the most common being the de2-7 EGFR (or EGFRvIII). This mutation arises from an in-frame deletion of exons 2-7, which removes 267 amino acids from the extracellular domain of the receptor. Despite being unable to bind ligand, the de2-7 EGFR is constitutively active at a low level. Transfection of human glioma cells with the de2-7 EGFR has little effect in vitro, but when grown as tumor xenografts this mutated receptor imparts a dramatic growth advantage. We mapped the phosphorylation pattern of de2-7 EGFR, both in vivo and in vitro, using a panel of antibodies specific for different phosphorylated tyrosine residues. Phosphorylation of de2-7 EGFR was detected constitutively at all tyrosine sites surveyed in vitro and in vivo, including tyrosine 845, a known target in the wild-type EGFR for src kinase. There was a substantial upregulation of phosphorylation at every yrosine residue of the de2-7 EGFR when cells were grown in vivo compared to the receptor isolated from cells cultured in vitro. Upregulation of phosphorylation at tyrosine 845 could be stimulated in vitro by the addition of specific components of the ECM via an integrindependent mechanism. These observations may partially explain why the growth enhancement mediated by de2-7 EGFR is largely restricted to the in vivo environment

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