13 research outputs found

    Histone H3.3 beyond cancer: Germline mutations in Histone 3 Family 3A and 3B cause a previously unidentified neurodegenerative disorder in 46 patients

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    Although somatic mutations in Histone 3.3 (H3.3) are well-studied drivers of oncogenesis, the role of germline mutations remains unreported. We analyze 46 patients bearing de novo germline mutations in histone 3 family 3A (H3F3A) or H3F3B with progressive neurologic dysfunction and congenital anomalies without malignancies. Molecular modeling of all 37 variants demonstrated clear disruptions in interactions with DNA, other histones, and histone chaperone proteins. Patient histone posttranslational modifications (PTMs) analysis revealed notably aberrant local PTM patterns distinct from the somatic lysine mutations that cause global PTM dysregulation. RNA sequencing on patient cells demonstrated up-regulated gene expression related to mitosis and cell division, and cellular assays confirmed an increased proliferative capacity. A zebrafish model showed craniofacial anomalies and a defect in Foxd3-derived glia. These data suggest that the mechanism of germline mutations are distinct from cancer-associated somatic histone mutations but may converge on control of cell proliferation

    Histone H3.3 beyond cancer : Germline mutations in Histone 3 Family 3A and 3B cause a previously unidentified neurodegenerative disorder in 46 patients

    Get PDF
    Germ line mutations in H3F3A and H3F3B cause a previously unidentified neurodevelopmental syndrome. Although somatic mutations in Histone 3.3 (H3.3) are well-studied drivers of oncogenesis, the role of germline mutations remains unreported. We analyze 46 patients bearing de novo germline mutations in histone 3 family 3A (H3F3A) or H3F3B with progressive neurologic dysfunction and congenital anomalies without malignancies. Molecular modeling of all 37 variants demonstrated clear disruptions in interactions with DNA, other histones, and histone chaperone proteins. Patient histone posttranslational modifications (PTMs) analysis revealed notably aberrant local PTM patterns distinct from the somatic lysine mutations that cause global PTM dysregulation. RNA sequencing on patient cells demonstrated up-regulated gene expression related to mitosis and cell division, and cellular assays confirmed an increased proliferative capacity. A zebrafish model showed craniofacial anomalies and a defect in Foxd3-derived glia. These data suggest that the mechanism of germline mutations are distinct from cancer-associated somatic histone mutations but may converge on control of cell proliferatio

    Suspected cases of LF evaluated at the KGH Lassa Laboratory and numbers of patients admitted to the KGH Lassa Ward, 2008–12.

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    <p>Non-admitted patients include those where only blood samples were submitted for screening from referral health-posts, patients dying en route to the hospital (DOA = dead on arrival), and patients not meeting the LF suspected case criteria (<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002748#pntd-0002748-t001" target="_blank">Table 1</a>). Characteristics of study patients are compiled in <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002748#pntd.0002748.s002" target="_blank">Table S1</a>.</p

    Monthly distribution of suspected LF cases presenting to the KGH Lassa Ward by serostatus, 2008–2012.

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    <p>Panel A: antigenemic Lassa fever cases (Ag+/IgM±). Panel B: Patients with serum anti-LASV IgM (Ag−/IgM+). Panel C: Patients with no Lassa virus seropositivity (Ag−/IgM−). The monthly frequency distributions differed between each of the serostatus group comparisons as assessed using a Poisson regression model (p<.001 for all serostatus comparisons; data not shown).</p

    Gender and self-reported pregnancy status of suspected Lassa fever cases presenting to the KGH Lassa Ward, 2008–2012.

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    <p>Panel A: Frequency of suspected Lassa fever cases by gender and serostatus. Panel B: Cases fatality rates by gender and serostatus. Panel C: Percentage of female patients of childbearing age with self-reported pregnancy status by serostatus. Panel D: Case fatality rates in female patients with self-reported pregnancy status Pregnancies are self-reported and therefore likely underestimated as pregnancy tests were not routinely available. Logistic regression was used for group comparisons (<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002748#pntd.0002748.s007" target="_blank">Tables S6</a> and <a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002748#pntd.0002748.s008" target="_blank">S7</a>). NS = not significant.</p

    CFRs in suspected LF cases presenting to the KGH Lassa Ward by serostatus, 2008–12.

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    <p>Panel A: CFR by serostatus. The presence of LASV Ag and anti-LASV IgM in serum of patients with verifiable outcomes was assessed by recombinant Ag− and IgM− capture ELISA, respectively. Panel B: Alternative calculation of CFRs. Ag+/IgM± plus Ag−/IgM+ compared to Ag−/IgM−. Statistical significance was determined using a logistic regression model predicting CFR (<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002748#pntd.0002748.s004" target="_blank">Table S3</a>). NS = not significant.</p

    Geographic distribution of patients presenting to the KGH with LASV antigenemia and anti-LASV IgM serpositivity, 2008–12.

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    <p>Confirmed cases of LF as assessed by LASV Ag in serum or cases anti-LASV IgM are shown by year of presentation, district of residence and frequency of cases. Panel A: Patients presenting in 2008–9. Panel B: Patients presenting in 2010. Panel C: Patients presenting in 2011. Panel D: Patients presenting in 2012.</p

    Age distribution of cases presenting to the KGH Lassa Ward, 2008–12.

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    <p>Panel A: Age distributions of patients presenting while antigenemic (Ag+/IgM±). Panel B: Age distributions of nonantigenemic patients presenting with serum anti-LASV IgM (Ag−/IgM+). Panel C: Age distributions of nonantigenemic patients presenting without anti-LASV IgM seropositivity (Ag−/IgM−). In Panels A–C yellow portion of bars represent patients who were discharged and black portion of bars represent patients who died. Panel D: Age demographic for the population of Sierra Leone (2010 estimate). Among patients who died, the age distributions differed significantly between the Ag+/IgM± and Ag−/IgM− groups (p = .005). Distributional comparisons were carried out using the Kolmogorov-Smirnov technique (<a href="http://www.plosntds.org/article/info:doi/10.1371/journal.pntd.0002748#pntd.0002748.s006" target="_blank">Table S5</a>).</p
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